Intelligent Design

Mechanosensing and Mechanotransduction: how cells touch their world.

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Fig. 1: Cnidaria are probably one of the most ancient phyla of known Metazoa.


Metazoa, or multicellular organisms, are one of the amazing “novelties” in natural history. At some point, single eukaryotic cells begin to be organized in a new, incredibly complex plan: a multicellular organism.

It is well known and understood that one of the main tools to realize that innovation, that new expression of life, is cell differentiation. Cells, while sharing the same genome, become different, incredibly different one from the other. Stem cells differentiate and acquire, through amazing and still poorly understood epigenetic trajectories, completely different cellular phenotypes and functions. The miracle of transcription regulation, as we have seen in another recent OP, is at the center of multiple levels of control involved in that achievement.

But there is another important aspect in metazoa that is even less understood, and at least equally amazing. Cells do not only differentiate: they must form tissues and organs and, in the end, a whole body plan. Body plans are the distinctive feature of the highest categorization of metazoa, the phyla, those individualized general programs that, strangely, appear almost all at the same time at the famous Cambrian Explosion (or, in different and lost forms, even earlier, at the Ediacaran Explosion).

But body plans are made of individual organs, and individual organs are made of different tissues. How can cells, while differentiating and implementing their specific epigenetic programs, form tissues and organs and organisms?

First of all, we should ask: where are cells, while they do that? The subject of this OP is about that question: the relationship of individual cells with their “environment” in the organisms that is being formed and built.

Let’s clarify immediately a few points:

  1. The environment that we are considering here is not really an outer environment. IOWs, it is not the outer world, with all its contingent varieties. It is, instead, an environment that surrounds the cells and is strictly controlled and regulated. It is called the Extracellular Matrix (ECM).
  2. The ECM is created by none other than the cells themselves. They generate it, they control it, they regulate it, they remodel it in many different and complex ways. As we will see.
  3. The ECM is the environment where cells live, differentiate and move. It controls and regulates the individual cells in many ways. As we will see.
  4. The main feature that contributes to generate tissues, organs and body plans, together with cell differentiation, is cell migration. Cells have to move, to migrate according to a precise and strictly regulated plan. Without controlled migration no tissue, no organ can be formed. Cells that differentiate differently must migrate to different places in the growing organism.
  5. Cell migration is not only a pillar of organism development. It remains a basic feature of many cell systems even in “adult” life. That is specially true for important cell systems, first of all the immune system.
  6. All cell migrations happen in the ECM, and are controlled and implemented by the complex interactions between the cells and the ECM.
  7. Those interactions, surprisingly, are not only biochemical (as we usually imagine cell interactions to be), but mainly mechanical.
  8. The cell structures that mediate those interactions between the cells and their ECM are one of the most amazing examples of functional complexity in the cell. Yes, like the spliceosome, the ubiquitin system and the transcription regulation networks, that we have considered previously. As we will see

So, this is a brief summary, just to help the reader to follow the many aspects of this topic that will now be presented in greater detail.

Sounds interesting? It is.

  1. The Extracellular Matrix (ECM)

The ECM is, very simply, the 3D environment where cells exist. It is a very complex structure, and it is very different in different organisms and in different tissues. In bones, the ECM is strongly mineralized, in chartilage it is very dense but not mineralized. In other connective tissues, like reticular tissues, it can be very loose. For circulating cells in blood, plasma is the ECM. A special type of ECM is the basal membrane, which supports epitelial cells.

Here are two good reviews about ECM:

The extracellular matrix at a glance

Biology of the Extracellular Matrix: An Overview

This is how the second paper starts:

The extracellular matrix (ECM) is an intricate network composed of an array of multidomain macromolecules organized in a cell/tissue-specific manner. Components of the ECM link together to form a structurally stable composite, contributing to the mechanical properties of tissues. The ECM is also a reservoir of growth factors and bioactive molecules. It is a highly dynamic entity that is of vital importance, determining and controlling the most fundamental behaviors and characteristics of cells such as proliferation, adhesion, migration, polarity, differentiation, and apoptosis.

So, let’s understand better.

The cells that form a multicellular organism are embedded in a self-generated semi-fluid environment, the ECM. All of them.

Of course, some types of cell are also in contact with the external environment, the world. For example, epithelial cells represent the outer surface of the organism to the external world, for example the epidermis. But the basal part of the epithelial tissue is anyway firmly rooted in some form of ECM.

The ECM is, first of all, water with soluble components in it. This fluid part is called Extracellular fluid, or also Interstitial fluid. That water is our internal ocean, where the basic exhanges between cells and the rest of the organism (nutrients, oxygen, and so on) take place. While this fluid component is very important, it is not really the subject of our discussion here.

In this fluid component, however, cells secrete a lot of important insoluble big proteins and other molecules, that make the ECM what it is, in different tissues. Those substances are “immersed” in the Extracellular fluid, and determine the physical and mechanical properties of that outer environment.

Here is a good general review of those components of ECM, the so called matrisome:

Overview of the Matrisome—An Inventory of Extracellular Matrix Constituents and Functions

While there are many components of the ECM and the matrisome, they can be essentially categorized in three rather different classes of proteins:

  1. Collagens
  2. Glicoproteins
  3. Proteoglicans

About 1000 proteins seem to be implied in the composition of the ECM. However, almost 300 seem to be part of a basic core matrisome. I will refer here mainly to a recent compilation of that core matrisome (see in particular Fig. 1):

The extracellular matrix: Tools and insights for the “omics” era


Collagens are fibrous proteins that build the basic structure of the ECM in most tissues.

I quote from the paper “Overview of the Matrisome”:

Collagens are found in all metazoa and provide structural strength to all forms of extracellular matrices, including the strong fibers of tendons, the organic matrices of bones and cartilages, the laminar sheets of basement membranes, the viscous matrix of the vitreous humor, and the interstitial ECMs of the dermis and of capsules around organs.

Fig.  2:  Vincent R. Sherman and Maria I. Lopez. Transmission electron micrograph of the collagen fibrils in rabbit skin. Licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

There are about 28 different collagen types, assembled from 44 different molecules, according to the core matrisome described in the second paper quoted above.

Collagens form the hard structure of the ECM. To simplify, each basic molecule of collagen (procollagen) is made of three collagen chains (for example, type 1 collagen is made of 2 alpha-1 chains and 1 alpha-2 chain), that form a right-handed triple helix. Out of the cell, those procollagen molecules are assemble into long fibrils and fibers.

One important concept is that, from the point of view os sequence, collagen is a relatively “simple” molecule, because it is formed mainly by highly repetitive short sequences of three AAs one of which is usually glycine, while proline and hydrossyproline are highly represented too. So, this is a rather “repetitive” sequence. But even so, the many modifications of the pattern generate an amazing complexity of the final result: 44 different genes and basic sequences are assembled into 28 different types of collagen triple helics, which have high specific properties and very different expression in different tissues. So, type I collagen is the most common form, present in skin, tendons, bones and many other important tissues. Type II is rather specific of chartilage. Type III makes the delicate reticular fibers so important in loose ECM. Type IV is mainly represented in the extremely important basal lamina that makes the basement membran in epithelial tissues. And so on.


These are  proteins which contain oligosaccharide chains. There are 195 of them included in the essential core matrisome mentioned above. Some of them are exremely important. In particular:

  • Elastin, which confers elasticity to tissues.
  • Laminin, which is an imprtant component of basal lamina in the basement membrane.
  • Fibronectin, about which we have to spend a few more words.

Fibronectin is a protein, or better a group of proteins, that connects to the other components of the ECM (collagens, proteoglycans) and to the cell (by the integrins, see later). Therefore, it is central in the implementation of practically all the complex functions in cell-ECM communication.

Fig. 3:  Fluorescent-labeled fibronectin on a layer of cells. It appears to be green in color. Fibronectin, a protein glue that anchors cells and hold them together often disappears when cells become cancerous.  Source:    National Cancer Institute  Author: Linda Bartlett (Photographer) [Public domain or Public domain], via Wikimedia Commons

Here is a very good review about fibronectin:

Assembly of Fibronectin Extracellular Matrix

And here are a few key points from that paper:

The extracellular matrix (ECM) has been recognized as an essential structural component in multicellular organisms for millennia (Plato trans. 1965). However, the old view of ECM as an inert scaffold is clearly incorrect. ECM is a dynamic network, a reservoir for growth factors and fluids, and an essential organizer of tissues, cellular microenvironments, and stem cell niches. It shows exquisite tissue specificity and adapts to changes in age, development, and disease. Even so, the molecular events that assemble secreted ECM proteins into complex networks are still not completely understood.


Fibronectin (FN) is a ubiquitous ECM glycoprotein that is assembled into a fibrillar matrix in all tissues and throughout all stages of life. Its assembly is a cell-mediated process (McDonald 1988) and is essential for life (George et al. 1993). FN fibrils form linear and branched meshworks around cells and connect neighboring cells


FN is a modular protein composed of types I, II, and III repeating units (Figure 1). Two intramolecular disulfide bonds form within each type I and type II module to stabilize the folded structure. Type III modules are seven-stranded β-barrel structures that lack disulfides (Leahy et al. 1996Potts & Campbell 1994). Modules are organized into binding sites for collagen/gelatin, integrins, heparin, FN, and other extracellular molecules (Figure 1).


FN exists in multiple isoforms generated by alternative splicing. The single FN gene transcript encodes 12 isoforms in rodents and cows and 20 isoforms in humans.

Fibronectin is a 2386 AAs long protein (in humans). As said, it is still a highly modular and partially repetitive sequence, but at a much more sophisticated level than collagen. Moreover, it definitely exhibits a huge re-engineering in vertebrates, with an information jump of 0.92 bits per aminoacid, corresponding to 2188 bits. With the necessary caution implied by the partially repetitive structure of the sequence, I would definitely say that those are huge numbers.

The “fibronectin meshwork” is therefore involved in many functions, but the one we will be focusing on here is its role, in association with integrins, in mechanosensing and cell migration.


Proteoglycans, previously known as mucopolysaccharides, are heavily glycosilated proteins, where the non protein content is represented by one or more chain of Glycosaminoglycan (GAG, a class of hetero-polysaccharides), and amounts to 50-60% of the molecule by weight (vs only 10-15% in glycoproteins).

They are important components of the ECM too.  There are 35 of them listed in the essential core matrisome quoted above.

They have been classified according to the GAG present in the molecule: Hyaluronates, Dermatan sulfates, Chondroitin sulfates, Heparan sulfates, Keratan sulfates. But the recent classifications are based on the protein component, and include: Aggrecan, Neurocan, Syndecans, Versican and many others.

They are not only found in ECM: they are important components of the cell membrane, too.

Their most evident role is mechanical: together with collagen, extracellular proteoglycans are the main determinants of the mechanical properties of ECM, like stiffness, elasticity, compressibility, and so on. But they have also a lot of biochemical functions. The topic is very complex, so for the moment we will not deal with it in detail.

  1. The cell-matrix interaction: Integrins and the Adhesome

How does the cell interact with the ECM?

There are many different ways, indeed. But we will focus here on the main and best known: the system of integrins.

Integrins are a family of transmembrane proteins that have a fundamental role in connecting cells to the ECM. They are heterodimers, and they are always made of an alpha chain + a beta chain. In mammals there are at least 18 alpha chains and at least 8 beta chains, forming at least 24 different heterodimers. Different heterodimers have different specificities and roles.

Alpha chains are about 1000 AAs long, beta chains are about 800 AAs long. While different alpha chains share moderate homology (for example, 25% identity between alpha 1 and alpha 5), and so do beta chains (for example, 46% identity between beta 1 and beta 2), alpha and beta chains share practically no homology between them.

Integrins are exquisitely metazoan proteins. A very simple repertoire is present in the simplest Metazoa, but the full repertoire that we find in mammals is detectable only in chordates, and more specifically in vertebrates. See here:

Integrins: Bidirectional Allosteric Signaling Machines

The Integrin Receptor Family: Evolution and Complexity

Integrins are restricted to the metazoa; no homologs are detected in prokaryotes, plants, or fungi (Whittaker and Hynes, 2002). The simplest metazoa, sponges and cnidaria, have integrins (Burke 1999Hughes 2001) and it is clear that primitive bilateria had at least two integrin αβ heterodimers, the descendents of which persist to this day in organisms as diverse as flies, nematodes, and vertebrates (Hynes and Zhao, 2000). Indeed, that is the entire set of integrins in Caenorhabditis elegans; one β subunit and two α subunits forming two integrins. Orthologs of these two integrins are recognized in Drosophila melanogaster and in vertebrates, although vertebrates have expanded each set (Figure 1). One set (blue in Figure 1) recognizes the tripeptide sequence, RGD, in molecules such as fibronectin and vitronectin in vertebrates and tiggrin in Drosophila, whereas the other set (purple in Figure 1) mediates adhesion to basement membrane laminins. It is plausible that evolution of integrins was necessary to allow the cell-matrix adhesion intrinsic to metazoa, and as diploblastic organisms evolved, the two cell layers may have evolved separate integrins to mediate their asymmetric interactions with the basal lamina; representatives of these two primordial integrins are detected in all higher metazoan phyla.
The same paper highlights the specificity of each integrin molecule:
Each of the 24 integrins shown in Figure 1 appears to have a specific, nonredundant function. In part, this is evident from the details of their ligand specificities (not shown in Figure 1) but is most clearly shown by the phenotypes of knockout mice (Table 1). Genes for the β subunits and all but four of the α subunits have been knocked out and each phenotype is distinct, reflecting the different roles of the various integrins. The phenotypes range from a complete block in preimplantation development (β1), through major developmental defects (α4, α5, αv, β8), to perinatal lethality (α3, α6, α8, αv, β4, β8) and defects in leukocyte function (αL, αM, αE, β2, β7), inflammation (β6), hemostasis (αIIb, β3, α2), bone remodeling (β3), and angiogenesis (α1, β3) as well as others
Indeed, integrins recognize many different ligands in different contexts. Many of them recognize the same rather simple ligand , the 3 AAs sequence Arg-Gly-Asp (RGD), but still the interaction is highly specific in different proteins. For e recent review of the specificity of integrin-ligand interaction, see here, in particular Table 1:

As transmembrane proteins, Integrins bind ECM components (ligands) with their extracellular part, and inner components of the cell, in particular actin, with their intracellular part. Both these interations are very complex. For those interested in details, I would recommend the following very good site, MBINFO, realized by the Mechanobiology Institute of the University of Singapore. I will use a few of their very clear images in the following discussion.

a) Integrin – ECM interaction.

The extracellular domain of the Integrin involves both chains, alpha and beta, and represents the bigger part of the molecule. Both chains have a transmebrane part, and a smaller intracellular tail.

The general structure is common to all integrin molecules. In a very simplified way, both the alpha and the beta chain can be described as a big extracellular “head” which rests on a very long “leg” that can bend at a “knee” region, and then goes through the membrane and ends with the intracellular tail.


Fig 4: A. Low-affinity integrin has an inactive, bent, conformation. B1 and B2. Inside-out integrin activation by cytoplasmic proteins or Outside-in integrin activation via ECM ligands both lead to complete extension of the extracellular domains. C. The hallmark of open, high-affinity activated integrin is separation of the cytoplasmic leg domains.  From: “How is integrin activated?”   licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Essentially, the Integrin can exist in two basic conformations:

a) The inactive conformation (A in Fig.1), in which the two chains are bent at the “knee”, and the intracellular tails are very near.

b) A fully active conformation, usually induced by interaction with inner components (B) or with extracellular ligands in the ECM (C), in which the two “legs” become fully extended, and divaricated, so that the two intracellular tails are separated (D).  The extracellular ligand interacts with the two “heads” in the open configuration.

Here is a similar, but more detailed, image of the two basic configurations:


Fig. 5: Inactive conformation of integrin (left) and a hypothetical model of the open, active form (right), with a fibrinogen peptide in red and a talin domain in magenta. From: PDB-101 Molecule of the month: Integrin.  Attribution: David S. Goodsell and the RCSB PDB. Licensed under a CC-BY-4.0 license

Following activation, integrins tend to migrate in the cell membrane and to form dynamic clusterings. Those clusterings of activated integrins mature into highly dynamic structures called Focal adhesions (FA).

We will see more about the complex functions of FAs later. For the moment, let’s anticipate that FAs are the key complex structure that mediates cell-ECM interactions, and that they have at least two major functions:

  1. In stationary cells, they anchor the cell to the surroundung ECM, and help to make the cell morphology stable.
  2. They are the essential structures that allow cell migration.

Fig. 6 shows a mature Focal Adhesion complex:


Fig 6: A mature FA contains hundreds of proteins that are grouped based on their contribution to four basic processes: receptor/matrix binding, linkage to actin cytoskeleton, intracellular signal transduction, and actin polymerization. Both actin polymerization and actomyosin contractile machinery generate forces that affect mechanosensitive proteins in the actin linking module, the receptor module (e.g. integrins), the signaling module, and the actin polymerization module. The combined activity of the mechanosensitive components form the mechanoresponsive network. The theoretical organization and protein-protein interactions as shown are based upon references.

So, to sum it up, integrins connect the cell to the ECM by:

a) Passing from the inactive conformation to the active conformation (“legs” extended, open active site between the two “heads”), in response to intracellular or extracellular signals.

b) Binding some specific ligand in some specific component of he ECM (for example, fibronectin).

c) Migrating in the cell membrane to form specific clusterings and, in the end, a very complex structure called Focal Adhesion.

A very important point is that FAs, even if very complex, are extremely dynamic: they arise as “nascent” FAs, then grow into mature FAs, and finally they are quickly disassembled.

b) Integrin – cytoskeleton interaction: the Adhesome.

The other side of the Integrin molecule, and therefore of the Focal Adhesion, is of course the link to the cell sytoskeleton, in particular to actin filaments.

Very briefly, actin is a family of globular proteins (G-actin) that polymerize in the form of micro-filaments (F-actin). Those actin filaments form a very dynamic cytoskeleton scaffold in the cell. Together with myosin, they can form contractile structures.

Now, we could think that at least the connection of the inner tails of Integrins to the actin cytoskeleton should be relatively simple. Well, that’s absolutely not the case.

Integrins do not connect directly to actin. They are connected by an extremely complex structure, that is usually called the Adhesome, or Integrin Adhesome.

The Adhesome is an amazing multiprotein structure that assemles dynamically at the intracellular side of Integrins, completing and stabilizing the Focal Adhesion.

Here is a summary table of its known components:

Fig. 7: The integrin adhesome network at a glance. From  The integrin adhesome network at a glance , licensed under CC BY 3.0

There is also a web-site completely dedicated to the Integrin Adhesome. Here it is:

The Adhesome: A Focal Adhesion Network

The site lists at present 150 “bona fide components” of the Adhesome + 82 associated components, and a total of 6,542 interactions. Not bad!

Some important points about the Adhesome:

a) Like the FA, of which it is the main component, it is extremely dynamic. The lifetime of individual proteins in the Adhesome is in the order of seconds, while the whole FA has a mean lifetime in the order of tens of minutes.

b) The proteins in the Adhesome are usually sensitive to mechanical force, and recruited by it (we will come back to that later)

c) While many of the functions and structures in the Adhesome are still poorly understood, it seems clear that it is higly organized in space, with a structure that involves three different functional layers: an Integrin Signaling Layer (nearest to the cell membrane), an intermediate Force Transduction Layer and an inner Actin Regulatory Layer, each with its specific protein compositions. See Fig. 2 here:

The “Stressful” Life of Cell Adhesion Molecules: On the Mechanosensitivity of Integrin Adhesome

Of course, we cannot detail here the 150+ proteins that assemble in the Adhesome. We will just describe in some detail the most important and best studied of them: talin.

c) Talin

Talin is a 2500+ AAs protein which implements a central and extremely complex role in Focal Adhesions. Its structure includes an N-terminal “head” (a FERM domain made of 4 subunits, F0-F3), and a “rod” made of 62 alpha helices arranged into 13 domains (R1-R13) + a homodimerization domain (DD) that corresponds to the 62th alpha helix at the C-terminal end of the molecule . Here it is:


Fig. 8:  Domain structure of talin. A, schematic diagram of talin showing the N-terminal FERM domain (F0, F1, F2, and F3 domains) linked via an unstructured region to the 13 amphipathic helical bundles of the talin rod, which terminates in a single helix, the dimerization domain (DD). Residue numbers for each domain (R1–R13) are shown. Helices are numbered and vinculin-binding sites are colored red. Domains corresponding to the new structures reported here are shaded. B–E, NMR structures of the talin R3, R4, R5, and R6 rod domains. Ribbon diagrams of representative low-energy structures show the overall topology of each bundle. F, model of talin showing the structures of all 18 domains. From: RIAM and Vinculin Binding to Talin Are Mutually Exclusive and Regulate Adhesion Assembly and Turnover ,  licensed under Creative Commons Attribution Non-Commercial License


Essentially, talin is the main protein that connects the intracellular tail of the beta subunit of integrin to actin. To do that, it has two integrin binding sites (one in F3 and 1 in R11) and three actin binding sites (one at F2-F3, one at R4-R8 and one at R13-DD). It has also domains for vinculin, its main co-interactor, and for many other proteins that are part of the Adhesome.

The working of talin is, of course, not completely understood, but much is known. I will  try to sum up the essentials:

a) Talin has an important role in activating integrin and therefore the whole FA.  It is therefore one of the main actors in the inside-out activation signaling shown at Fig. 3.

b)  It is one of the most important protiens that can sense mechanical forces. IOWs, the application of mechanical forces can change its configuration and its biochemical affinities. In that sense, it works as a “hub” that integrates the many signals involved in the function of FAs, so much so that some have even introduced the concept of a “talin code”.

c) In the FA activation phase, talin ismore or less parallel to the cell membrane, linking up to 4 different integrin tails by its 4 integrin binding domains (in the homodimer), contributing to the clustering of integrins and to the growth of the FA.

d) In that same phase, it binds many actin molecules, that can provide a mechanical pull on the actin molecule both in a direction parallel to the call membrane and in a perpendicular direction. Those forces contribute to change talin conformation, and to its ability to recruit new proteins in the Adhesome, such as vinculin, RIAM, FAK, Paxillin and others.

e) In the mature FA, talin spans all three functional layers of the Adhesome, with its head near the cell membrane and the rod end in the actin regulatory layer.

Many of those features are described in detail in this recent paper:

Talin – the master of integrin adhesions

However, the most important point for our discussion is the second one: the ability of talin to repsond to the application of mechanical forces. We will go into greater detail about that in the section about mechanosensing.

Finally, it can be interesting to mention that talin is an extremelly conserved protein. It shows almost 1 bit per AA conservation with human sequence already in cnidaria, and just a little bit more in pre-vertebrates. As the protein is so long, that amounts to about 2500 conserved bits. In vertebrates (cartilaginous fishes) it exhibits a well defined information jump (0.54 baa, corresponding to 1376 bits). That brings the molecule to an astonishing level of homology between cartilaginous fish and humans: 1.67 baa, 4250 bits. IOWs, the human protein and the protein in callorhincus milii (the ghost shark) share 2109 AA identities (83%) after 400+ million years of evolutionary separation!


Fig. 9: The evolutionary history of Talin shows extreme conservation in Metazoa and a definite information jump in vertebrates.


  1. Mechanosensing

So, what is the purpose of all these complex structures, of all these intricate connections and potential regulations?

There are many answers to that, but the first and certainly one of the most important is: to perceive.

For the cell, its outer environment is everything: it is the reality where the destiny of each individual cell has to be implemented. But, as said, that outer environment is not a hostile and unpredictable world: it is a world made by the cells themselves, the Extracellular matrix, including of course the other cells in it.

Indeed, we have to clarify here that “the other cells” are an important part of the whole system. What we have said up to now is about the connection between each individual cell and the ECM. But there two more big and important subjects, and they are the connections, and the communications, between different cells.

Because adhesions are not realized only between a cell and the ECM. They exist between cells, too. And cell-cell adhesions are implemented by specific structures and proteins that are at least as complex as those that implement the cell-ECM adhesions. And yet very different from them.

In particular, cell-cell adhesions are not implemented by Integrins, but by completely different classes of proteins, such as the Cadherins. And of course there is a complex multi-protein structure associated to cadherins too, and it is called the Cadherin Adhesome. And there are different types of cell-cell juntions. And, as we can imagine at this point, cell-cell ahdesions do interact in many ways with the cell-ECM adhesions that we have been describing here.

However, to discuss these other aspects would certainly make this OP infinitely long, and so the discussion here will be “limited” to the cell-ECM interactions.

So, what does the cell need to know about its surrounding ECM?

It needs a lot of different things, certainly. Because, as we have seen, the ECM can be completely different in different parts of the organism. It has different biochemical composition and different physical properties. And both things are very important to the cell.

In a sense, biochemical composition is something that we can easily imagine as a target for the cell’s informational resources. We are accustomed to think that the cell works through membrane receptors, biochemical signaling pathways, and so on. And we have seen that at least part of the mechanisms we have described here are apparently “normal” biochemical affinities between a receptor and a ligand: in particual, the extracellular part of the integrin molecule certainly recognizes different ligands in the different proteins that are present in the ECM, by the active site formed by the two “heads”.

But what about mechanical information? We have seen that the binding to ligand has really the puprose to generate an adhesion to the ECM, which then matures into a very complex structure, the Focal Adhesion. It is not in itself a signal to the cell, but rather a tool to generate a signal. Because the signal that is to be generated is mechanical, not biochemical.

IOWs, the cell has to “perceive” the mechanical properties of the ECM, and also any specific mechanical forces that are applied to the ECM.

The complex mechanisms that implement that “perception” are called, globally, mechanosensing.

Now, here is where things become really complex, in the sense that we still don’t understand them. Everything about mechanosensing is, at present, poorly understood, and remains rather obscure. I will try to list just a few interesting points that are of paramount importance.

First of all, what are the physical properties of the ECM that are perceived by the cell? There are many of them, and all of them seem to be able to influence the cell and its reactions.

The best understood are:

  • Rigidity or stiffness: the extent to which ECM resists deformation in response to an applied force.
  • Elasticity: the ability of ECM to return to its original size and shape when a force is removed.
  • Viscoelasticity: the association of viscous and elastic properties (gradual return to the original size and shape in time).
  • Dimensionality: cells seem to be able to react in specific ways to 1D, 2D and 3D information.
  • Strain-stiffening: ECM seems to be able to stiffen when forces are applied, either from the cell itself or from the outer environment.
  • External forces applied to the ECM and transmitted to the cell, such as tension, compression, shear, swelling.

There seems to be a constant cross-talk between the cell and those mechanical forces: Focal Adhesions are constantly formed and dissolved in response to forces, and at the same time they transmit forces from the cell to the ECM, and the mechanical reaction of the ECM to those cell-generated forces is probably one of the main “messages” that the cell can translate into novel action.

The role of actin

Actin filaments have a very important role in all this, but again it is a role that is still poorly understood.

Actin polymerizes and forms specific structures. Of particular interest for our discussion are the “stress fibers”, long filaments of actin associated to other proteins, including myosin and alpha-actinin. Stress fibers can contract, and there are different types of them. The most relevant here are probably the ventral stress fibers, that are anchored to a Focal Adhesion at both ends.


Fig. 10:  Three types of actin SFs. U2OS human osteosarcoma cells were plated on 10 µg/ml fibronectin-coated coverslips and allowed to attach and spread for 4 h before fixation (Hotulainen and Lappalainen, 2006). In the immunofluorescence image, antiphosphotyrosine was used as a marker for focal adhesions (red), phalloidin was used for F-actin SFs (green), and the nucleus (blue) was detected by DAPI. This single cell exhibits the three main types of actin SFs: (transverse) arcs, dorsal SFs, and ventral SFs. (inset) Schematic drawing depicting the SF subtypes.  From: The tension mounts: Stress fibers as force-generating mechanotransducers , licensed under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at

Moreover, when the cell moves actin is constantly polymerized at the leading edge of the cell, and moves towards the cell body, to be degraded at the trailing edge. That is the cause of the so called “actin retrograde flow”, which is not in itself a contractile movement, but is involved in both the formation of FAs and the cell migration, but in a complex, not well understood and somewhat paradoxical way (the direction of the actin flow is indeed opposite to the direction of the cell movement). Here is an amazing video of the retrograde flow:


  1. Mechanotransduction

OK, so now we know that the cell has many complex ways to become aware of mechanical forces, generate them, perceive them, react to them.

But the problem remains: how does this mechanosensing relate to the more traditional world of cell functions, IOWs the biochemical world? How is mechanical information translated into biochemical sigmals, so that the two layers can communicate and interact?

The answer ot that is mechanotransduction: the translation of mechanical stimuli into biochemical signaling.

We have alredy seen that many proteins involved in the formation of FAs are capable of mechanosensing, first among them talin.

Let’s see more in detail one of the many ways that such mechanosensing can take place. Let’s go back to talin. The different bundles that make the rod of the  molecule have different mechanosensitivity. One of the most mechanosensitive bundles is R3. In this domain, the folding forces are weaker, and they can be antagonized by the application of a mechanical force, which acts to unfold the sequence. That’s what happens when actin binds one of the actin binding sited of talin: the force generated by that binding “stretches” the talin molecule, and the R3 domain is the first to unfold. That partial unfolding “exposes” in R3 specific vinculin binding sites, which were previously hideen in the folded state. So, vinculin binds to talin, and the whole system progresses toward the formation of the FA.

This is just an example of how mechanical forces can generate biochemical activities, when the molecule is programmed in an appropriate way. But still, we are not seeing any connection to cell signaling.

The modifications in the cell that are initiated by mechanical signals are called, as a whole, mechanoresponse. They include a lot of different events, but of course most of the response has to be mediated by the fundamental hub of cell states: transcription regulation. Therefore, mechanical stimuli and their inherent information must, in some way, reach the nucleus.

There are two different modalities for that transmission:

Biochemical signaling.

This is the slower way, but it is extremely complex and can reach practically all aspects of cell activity. Indeed, the system of Integrins and Focal Adhesions has direct effects on many cell signaling pathways.

Many of those connections are mediated by phosphorylation networks, involving for example the Src family kinases, and the specific Adhesome protein FAK (Fochal Adhesion Kinase), plus many small GTPases, including RhoA.

The main signaling pathways that are modulated by mechanical signals deriving from FAs are:

  • Hippo signaling, mainly mediated by the Yap-Taz proteins.
  • Serum response factor (SRF) pathway.
  • Wnt Receptor Signaling
  • NF-kB pathway, directly activated by FAK

All these pathways are extremely complex, and they are at the very center of most cell activities, modulating cell transcription at all levels. All of them are strictly connected to mechanosensing, in many different ways that have been studied in great detail, but that are still poorly understood.

Mechanical signaling.

But there is a quicker way that can transmit information from FAs to the nucleus: direct mechanical signaling, from the cytoskeleton to the nucleoskeleton.

To accomplish that, a specific structure acts as interface between the two skeletons. It’s called LINC (linker of the nucleoskeleton and cytoskeleton) complex, and it includes the nuclear transmembrane protein emerin, the inner nuclear protein SUN and the nuclear lamina.

Again, in the nucleus, mechanical signals are translated into biochemical events, in particular deep chromatin rearrangements and epigenetic modifications, affecting all cell activities thorugh transcription regulation.

Some recent information about these complex topics can be found here:

Integrin-mediated mechanotransduction

In particular, the section: “Cellular responses in mechanotransduction”.

And a simpler summary can be found here:

Which biochemical pathways are regulated by mechanical signals?

Who makes the ECM?

And, of course, the cells themselves are the creators of the ECM. It’s the cells that synthesize the proteins, and all the components. The world where the cells reside and move is made by the cells themselves.

And, as we have seen, it is an extremely dynamic world. The structure and composition of the ECM is subject to constant changes and remodeling, and of course it’s the cells themselves that originate those changes. Different cells, in different ways. And the mechanoresponse in the cell to mechanical information from the ECM is certainly the guide to changes in ECM structure and composition that come from cell activity.

So, it’s a strict and constant crosstalk between the ECM and the cells that generate and remodel it. And hundreds of proteins, networks, components, structures, both in the cell and outside it, are involved in the process.

  1. What about the cell?

So, we know that the cell uses mechanosensing and mechanotransdution to get information about the ECM and to connect to it. And then? What are the active responses of the cell?

As we have said, changes in the secretion of proteins and other components to change the composition and structure of the ECM are certainly an important aspect. But there is more.

As already anticipated, the interaction between the cell and the ECM has two very big purposes, one in stationary cells, and the other, the most important one, in cells that have to move.

Stationary cells

All cells are anchored in different ways to the ECM. That interaction has a definite and complex effect on cell morphology, and contributes to determine cell shape. Cell shape is also connected to cell fate, to mitosis and differentiation, even to apoptosis. All these processes are strongly conditioned by the interaction with the ECM by mechanosensing and mechanotransdution.

Here is a recent paper about these issues:

Mechanochemical Signaling Directs Cell-Shape Change


For specialized cell function, as well as active cell behaviors such as division, migration, and tissue development, cells must undergo dynamic changes in shape. To complete these processes, cells integrate chemical and mechanical signals to direct force production. This mechanochemical integration allows for the rapid production and adaptation of leading-edge machinery in migrating cells, the invasion of one cell into another during cellcell fusion, and the force-feedback loops that ensure robust cytokinesis. A quantitative understanding of cellmechanics coupled with protein dynamics has allowed us to account for furrow ingression during cytokinesis, a model cell-shape-change process. At the core of cell-shape changes is the ability of the cell‘s machinery to sense mechanical forces and tune the force-generating machinery as needed. Force-sensitive cytoskeletal proteins, including myosin II motors and actin cross-linkers such as α-actinin and filamin, accumulate in response to internally generated and externally imposed mechanical stresses, endowing the cell with the ability to discern and respond to mechanical cues. The physical theory behind how these proteins display mechanosensitive accumulation has allowed us to predict paralog-specific behaviors of different cross-linking proteins and identify a zone of optimal actin-binding affinity that allows for mechanical stress-induced protein accumulation. These molecular mechanisms coupled with the mechanical feedback systems ensure robust shape changes, but if they go awry, they are poised to promote disease states such as cancer cell metastasis and loss of tissue integrity.

Cell migration

However, the most complex procedure that is linked to the cell-ECM interaction is probably cell migration.

We all know that cells can move. Bacteria can move, single celled eukaryotes can move, and many different tools implement movement in those cells, including different kinds of flagella and amoeboid movement by pseudopodia. But cells in a multicellular organsism, as we have seen, exist and move in the ECM, and moving in the ECM is quite a specific task, very different from motion in the “exterior” world. That kind of movement is based on adhesions to the ECM, Fochal Adhesions and the role of cell cytoskeleton.

Again, we must acknowledge that movement of cells in the ECM is largely poorly understood, even with all the things we know today.

The main structure in the cell that implements movement is called lamellipodium. It is a flat, plate-like projecion at the leading edge of the cell, including an almost bidimensional actin network. Smaller spikes emerging from the cell edgle or from lamellipodia are called filopodia. Filopodia probably precede and guide the formation of lamellipodia. Focal Adhesions are usually rare or nascent at the tip of lamellipodia, while they are frequent and mature at the boundary between lamellipodium and cell body.

As said, the exact role of actin in generating the propulsion forces is not completely clear. I quote from this site:

Cell motility is driven by coordinated actin polymerization at the cell’s leading edge. However, it is still fiercely debated exactly how actin generates force to move a cell. The fine structure of filaments revealed by electron microscopy is exquisitely sensitive to the preparative methods used, and thus, various models have been proposed. Bringing together information from electron microscopy, live-cell imaging techniques, and super-resolution microscopy will be necessary to construct a definitive model.

Tha main idea is that actin generates the propulsion force in at least two different ways:

a) Contractile actin structures, like stress fibers, where actin is coupled to myosin and can therefore contract, should have a role. Different kinds of stress fibers have been implicated, but the general idea is that contraction is a component of the process.

b) The retrograde flow of actin, due to constant polymerization at the leading edge, would be one of the main sources of the forward propulsion, by some paradox effect linked to the resistance of Focal Adhesions at the rear of the lamellipodium. This is not a contractile mechanism, but it is connected to the polymerization of actin fibers at the leading edge, and its disassembling at the trailing edge. In this case, FAs would act as a “molecular clutch”, able to exist in a disengaged or engaged state, and therefore to connect the force to the propulsion in lamellipodia.

A good summary of these ideas can be found here:

How do focal adhesions act as molecular clutches in lamellipodia?

And this short video gives a good idea of the complex interactions between FA dynamics and the generation of lamellipodia for cell migration:


  1. So, what is the purpose of all this functional complexity?

After all these complex details, let’s try to discuss the general scenario, and to draw some conclusions.

I think that there can be no doubt in anyone’s mind about the amazing complexity of the systems that have been described here. And remember, these are only a few aspects of what is known, and what is not known is certainly much more than what is known.

So the real question is: why? What is the purpose of all that?

To answer that, we must go back to our initial introduction. The real point is: everything depends on these processes, in multicellular organisms.

We know how complex and fascinating is the issue of cell differentiation, and how the many levels of control in transcription regulation certainly hold the key to that basic mystery.

But multicellular agents are not only the sum of differentiated cells. They are made by differentiated cell that build specific microscopic and macroscopic structures, in particular tissues and organs, in the context of the general body plan of the organism.

And remember, as all differentiated cell derive from the single cell that is the zygote, it is equally true that all body structures derive from that single cell, too.

So, when the original cell divides, at a certain point it generates spacial structures. Extracellular matrix comes into the game, hosting and guiding the cells. The basic 3 germ layers are produced, and then all the complex structures in the embryo, and then in the final body.

We don’t really know how all that is implemented, but we certainly know one thing: cells have to migrate to realize the plan. And they do that by moving in the ECM.

So, we can understand how the processes that regulate cell migration become the key to understand the development of a multicellular organism. That’s no small deal.

Cell migration

Indeed, cell migration is of paramount important in two different contexts:

a) Cells which have to migrate because of their intrinsic function. A good example of that are leucocytes and fibroblasts, involved in immune response, inflammation and wound healing. These cells migrate to reach the site where they have to accomplish their tasks.

b) Cell migration during embrional and fetal development. In this case, cells migrate to reach their final site in tissues and organs.

We will focus here on the second type of migration.

Cell migration starts with recognizing a direction. The cell must understand, in the 3D world of ECM, the correct direction it has to follow.

The direction generates three different important events:

  1. The establishment of the correct polarity: the cell defines a leading edge and a trailing edge, before strating to move, and as we have seen different structures are generated at the two poles.
  2. The initiation of propulsion in the right direction
  3. The maintenance and correction of propulsion throughout the pathway

Of course, the big question is: what guides the cells to their final abode? IOWs, what we observe is guided cell migration: cells do not wander randomly, but follow specific trajectories to reach specific places, in accord with their differention and their final roles. And, in doing that, they build highly ordered structures.

The good answer to that would be, again: we don’t really know in detail. However, a few things are known.

There are at least three types of factors influencing cell migration during development:

a) Chemotaxis

b) Haptotaxis

c) Mechanical properties of tyhe ECM (Mechanotaxis)

Electric forces can also have a role, but we will not discuss that aspect here.

Chemotaxis is the simplest concept. It means that some molecule dissolved in the extracellular fluid is recognized by the cell as attracting (or repulsing), and therefore the cell moves according to the concentration gradient of that substance. The important point here is that the chemotactic substance is in soluble form, and its gradient is a concentration gradient in the extracellular fluid, which, as we have said, is the fluid part of the ECM. Chemotaxis is probably more important in type a) migration, for example in inflammation, where inflammatory molecules attract leucocytes to the site of the lesion. In this case, cells are acctracted to a site, but there is no great specificity in that process.

Here is a paper about chemotaxis in organism development:

Chemokine-guided cell migration and motility in zebrafish development

Haptotaxis works in a similar way, but here the attractive (or repulsive) substrate is not soluble: it is, instead, bound to a surface, usually some of the ECM proteins, such as fibronectin and laminin. So, the cell interacts with the ligand through the complex Adhesion system that we have been describing.

Here is a paper about hapotaxis:

Haptotaxis is cell type specific and limited by substrate adhesiveness

Finally, it is well understood that the mechanical properties of the ECM, such as stiffness and so on, have a definite role in determining the path that the cell will follow (mechanotaxis), always by the mediation of the Integrin – FA system. The term “durotaxis”, for example, is used for the effects of stiffness.

Here is a recent paper about mechanotaxis:

Tissue mechanics regulate brain development, homeostasis and disease

The cell, in some way, integrates all those signals to decide what path it is going to follow.

Who sets the signals?

Of course, the cells themselves do that. Cells produce the ligands for both chemiotaxis and haptotaxis, and as we have seen it’s cells, again, that generate and remodel the ECM and determine its mechanical properties.

But the problem is: what cells?

In the case of chemotaxis, and probably haptotaxis, the simplest scenario is that the cells at the target site produce the ligands and, in some way, create the gradients. But, as we have seen, that is probably simpler with chemotaxis, because the ligand is soluble, while in haptotaxis a significant contribution of ECM proteins is more likely. Moreover, even intermediate cells (from sites between the migrating cell and the target site) can probably contribute.

How the mechanical properties of the ECM may be regulated in the pathway to be followed is less clear. It seems reasonable that many cell types hosted by the ECM itself could contribute to that, and possibly even the migrating cell itself.

As said, we do not understand enough yet. But one thing is certain: the migrating cell in some way can receive and integrate a lot of different signals, and in some way can control the complex activity that makes the propulsion possible (lamellipodia, actin activity, FAs and so on) to efficiently implement the correct migration.

A very good model: the axonal growth cone

A model that has been studied in great detail, and which shows many important aspects of the migration process, is the growth of the axon towards its destined synapsis, through the structure known as growth cone. Here, it’s not the whole cell that migrates, but rather its main extension, the axon, which is responsible for the main neuronal connection to another neuron. It is the main costituent of nerve fibers, and it is the structure used by neurons to output their signals to other cells.


Fig. 11: A neuron and its axon.


Please, consider that axons can be very long: their length ranges, in humans, from less than 1 mm to more than 1 m. Each neuron has only one axon, that can innervate many target cells.

So, the axon grows from the neuronal body to its target synapse, and as we have said that pathway can be very long, even 1 meter. That’s a very long walk for a minuscule cell protrusion.

Moreover, axons must connect to the right synapses. Needless to say, the pattern of neuronal connections is what makes the nervous system the wonderful tool that it is, and not a random and useless mess. For example, moto neurons in the brain must connect with great precision to the corresponding second motor neurons in the spine, that connect to the appropriate muscle fibers.

So, how does the axon grow? Indeed, it is a good summary of what we have said before.

The structure that allows the growth is called growth cone. This structure was discovered by Cajal as early as 1890, and in the same year he declared that:

nerve fibers “adopt predetermined directions and establish connections with defined neural or extra neural elements… without deviations or errors, as if guided by an intelligent force”

Cajal, S. R. (1890). Notas anatómicas I. Sobre la aparición de las expansiones celulares en la médula embrionaria. Gac. Sanit. Barc. 12, 413–419.

Ah, the good old times of unbiased scientific research!  🙂

So, what is a growth cone? Let’s take a few concepts from this good internet page:

The Axonal Growth Cone

(The) growth cone (is) a specialized structure at the tip of the extending axon. Growth cones are highly motile structures that explore the extracellular environment, determine the direction of growth, and then guide the extension of the axon in that direction. The primary morphological characteristic of a growth cone is a sheetlike expansion of the growing axon at its tip called a lamellapodium. When examined in vitro, numerous fine processes called filopodia rapidly form and disappear from the terminal expansion, like fingers reaching out to touch or sense the environment (Figure 23.1). The cellular mechanisms that underlie these complex searching movements have become a focus of cell biological studies of axon growth and guidance. Such movements are thought to reflect rapid, controlled rearrangement of cytoskeletal elements—particularly molecules related to the actin cytoskeleton—which modulate the changes in growth cone shape and ultimately its course through the developing tissues.

So, it is a sheetlike structure including at least one lamellipodium and many filopodia, at the leading edge of axonal growth. Exactly as we have seen in cell migration.

While the axon cytoskeleton grows mainly by the elongation of microtubules, the growth cone is primarily an acti-myosin structure. Filopodia are continuously and dynamically generated and they test the surrounding microenvironment in search of attractive and repulsive cues. The final pathway followed by the axon is the result of the integration fo all those signals and of their many different effects on the various intracellular pathways discussed above.

All the mechanisms described in this OP can be seen at work: Focal Adhesions, retrograde actin flow, and so on.

Here is a schematic image of the growth cone from the appropriate MBINFO page:

Fig.  12;  Organization of cytoskeletal components (actin filaments and microtubules) in the growth cone.  From: What is axon guidance and the growth cone?,  licensed under a Creative Commons Attribution-NonCommercial 4.0 International License


And here is a rather detailed video about the axon cone:



Of course, all that is not simple. I really have to quote the following paper, even if it is not so recent (2012), because of its title:

Functional Complexity of the Axonal Growth Cone: A Proteomic Analysis

Functional complexity? Oh, yes!

Here is the abstract:

The growth cone, the tip of the emerging neurite, plays a crucial role in establishing the wiring of the developing nervous system. We performed an extensive proteomic analysis of axonal growth cones isolated from the brains of fetal Sprague-Dawley rats. Approximately 2000 proteins were identified at ≥99% confidence level. Using informatics, including functional annotation cluster and KEGG pathway analysis, we found great diversity of proteins involved in axonal pathfinding, cytoskeletal remodeling, vesicular traffic and carbohydrate metabolism, as expected. We also found a large and complex array of proteins involved in translation, protein folding, posttranslational processing, and proteasome/ubiquitination-dependent degradation. Immunofluorescence studies performed on hippocampal neurons in culture confirmed the presence in the axonal growth cone of proteins representative of these processes. These analyses also provide evidence for rough endoplasmic reticulum and reveal a reticular structure equipped with Golgi-like functions in the axonal growth cone. Furthermore, Western blot revealed the growth cone enrichment, relative to fetal brain homogenate, of some of the proteins involved in protein synthesis, folding and catabolism. Our study provides a resource for further research and amplifies the relatively recently developed concept that the axonal growth cone is equipped with proteins capable of performing a highly diverse range of functions.

OK, now let’s go to the proteins involved in the guidance of the axonal growth cone, because something is known about them. Here is an essential list:

  1. Ephrins and ephrin receptors. These are a well studied class of membrane bound ligands and recepors that have an important role in axon guidance mediated by cell-cell interaction. See here: Ephs and ephrins
  2. Netrins: a class of secreted chemotropic proteins that act as both attractants and repellents in axonal cone guidance.
  3. Semaphorins: a set of classes of proteins, both secreted and membrane bound, that usually act as repellents for axon growth.
  4. Plexins: the main receptors for semaphorins.
  5. Slits: ECM proteins secreted by structures in the nervous system, such as the floor plate or the midline glia, which act as midline repellents, preventing the crossing of axons through the midline of the central nervous system.
  6. Robo: the main receptors for Slits.

An interesting concept is that some axons act as pioneer axons: in a sense, they find a pathway and “open” it for other axons to follow.

And here is a recent (May 2018) review of those topics:

Understanding axon guidance: are we nearly there yet?

Let me quote a few titles from the paper sections:

  • A richness of signals: redundancy of guidance information ensures correct navigation within the spinal cord
  • Crosstalk between different families of guidance cues
  • The regulation of axon guidance receptors at choice point

And finally I quote here the conclusions from the same paper (emphasis mine):

Perspectives: so, are we nearly there yet?

As I have highlighted here, our knowledge of neural circuit formation in the brain is still very much in its infancy. We can infer molecular mechanisms from what we have learned in one system to another but there is still not a single population of axons for which we have a complete understanding of the molecular mechanisms of navigation to the final target. So, we are clearly not there yet! A major challenge remains the characterization of the precise temporal regulation of guidance signals and the interactions between different signalling pathways that cooperate to guide axons to their intermediate, and ultimately final, targets. Axon guidance studies in a variety of organisms clearly indicate that the regulation of axon guidance signalling involves all possible mechanisms of regulation: transcriptional and translational control, trafficking of specific vesicles, and changes in protein-protein interactions as well as protein stability. Furthermore, the link between the interactions of guidance receptors and their ligands with the observed behaviour of growth cones is still missing. We also only have a very superficial understanding of the association between surface receptors and the regulation of cytoskeletal dynamics responsible for steering growth cones (Gomez and Letourneau, 2014). Similarly, our knowledge on specific intra-axonal trafficking of signals is poor. To make the next step in our understanding of axon guidance, it will be important to keep complexity in mind. Classical loss-of-function approaches might not reveal the complex interaction between guidance cues and their different receptors. Precise temporal control of experiments during embryonic development is difficult in mammals. Therefore, it will be important to make use of diverse animal models, each with its strengths and weaknesses. A particular challenge will be the visualization of the functional link between surface receptors and the cytoskeleton. This is becoming easier to do in vitro thanks to high-resolution imaging techniques, but in vitro experiments will not allow for the analysis of axon guidance as they will never be able to mimic the complexity of cell-cell interactions in the developing tissue. It is thus clear that understanding axon guidance remains a challenge, and that a multifaceted, multidisciplinary approach will be required to understand not only how a single axon finds its target but how billions of axons manage to do so.

Yes, billions. There are about 10^11 neurons in the human nervous system, and each of them has probably about 7000 connections.

  1. Conclusions

So, what have we learned from this long discussion?

  1. The transition to metazoa implies a whole new world of functional complexity, a specific general plan that allows the implementation of tissues, organs, body plans.
  2. Part of it is, of course, cell differentiation: each cell must be guided to its final state, its final specific phenotype, starting from one common genome/epigenome. This was the subject of my previous OP about transcription regulation.
  3. But another important part of it is cell location, in time and space. The ordered guidance of each body cell to the right place and to the right functional connections is the foundation for the implementation of the general plan, which is made of specialized tissues that make specialized organs and consistent global organisms.
  4. Cells exist in a complex 3D environment created, maintained and dynamically restructured by the cells themselves: the ECM.
  5. The interaction between cells and the ECM is essential to many cell functions, starting with cell shape, and including cell migration in development and for other functional needs.
  6. The interaction between cells and the ECM is not only chemical, but essentially mechanic.
  7. The Integrins and the Focal Adhesions are an extremely dynamic system that links the ECM to the cytoskeleton, in particular to actin.
  8. Cell migration is realized by the integration of an extremely rich network of signals, both mechanical and biochemical. Cell-cell interactions have also a leading role.
  9. How that integration is achieved by each specific cell is still not understood.
  10. Indeed, a lot of the essential aspects of all these issues are still poorly understood.
  11. The axonal growth cone is another example of “migration” of a cell structure, which involves billions of specific pathways. The whole structure of the central nervous system depends on those processes.
  12. Whatever the mechanisms that we still don’t understand, it is rather clear that coordinated cell migration and axon growth require not only the amazing structures and integration abilities in each individual cell, but also the cooperation of many different actors: the migrating cell, the ECM, guiding proteins and ligands, intermediate cells, the final target, and probably many other components.
  13. To me, this is one of the most beautiful examples of coordinated, irreducible functional complexity: an implementation of design that can only inspire deep awe and wonder.

395 Replies to “Mechanosensing and Mechanotransduction: how cells touch their world.

  1. 1
    nady shamy says:

    Great ……. The only explanation that is scientific and logic is that all of this awesome activities are directed and guided by God , no other explanation is possible since the information needed to construct biostructures are not contained in nature or the cosmic laws .

  2. 2
    gpuccio says:

    nady shamy:

    Welcome to the discussion and thank you for your comment.

    I just want to clarify that my argument about ID as applied to biology is about the design inference. It clearly infers design interventions by come conscious, intelligent and purposeful agent. From a purely scientific point of view, no statement about God is needed, at least IMO. That remains a philosophical or religious problem.

    I absolutely agree that “the information needed to construct biostructures are not contained in nature or the cosmic laws.” That’s exactly why a design inference is absolutely needed to provide a credible explanation.

    No law and no contingency can explain complex functional information. Conscious, intelligent and purposeful design can. That’s why the design inference is absolutely warranted when complex functional information is observed.

    And, when it is observed in the huge amounts implied by the systems described in the OP, I can’t really imagine how any sensible person can deny the inference of design.

    But, of course, they can and they will. 🙂

  3. 3
    OldAndrew says:


    Thank you very much. It’s amazing as always.

    We frequently hear and say that these things are complex, but that word loses its impact over time. This allows us to “see” that complexity, in part by being overwhelmed by it (speaking for myself and probably a few others.) Adding to it is that the writers of all the cited papers aren’t describing things they designed. Instead they spend years studying it to figure out how individual parts work and interact.

    I also appreciate that you explicitly refuse to discuss religion. IMO the only way ID stands a chance is if others follow that example.

  4. 4
    gpuccio says:


    Thank you for your words! 🙂

    Yes, you have really caught a fundamental aspect. It’s not just about saying that things are complex. It’s much more than that.

    The real overwhelming experience is to realize that things are becoming ever more complex day by day, as our understanding of the biological world gets deeper. The “appearance” of design becomes “certainty” of design, and then “overwhelming awe” of design, and then, and then…

    Because overwhelming it is, indeed!

    I consider myself really blessed for having the chance to write about these issues, because each time I start with a definite idea and interest in a specific biological subject, but as I go on reading the recent literature, and trying to understand, and if possible convey, what is being discovered, it becomes a thrilling experience of wonder and beauty.

    So again, thank you for your appreciation. 🙂

  5. 5
    Mung says:

    Awesome OP. Thanks gpuccio.

  6. 6
    gpuccio says:


    Thanks to you! Always nice to hear from an old friend. 🙂

  7. 7
    Mung says:

    So perhaps next up is an OP on how all these are found in the common ancestor of all animals.

  8. 8
    gpuccio says:


    That’s certainly a very interesting aspect, even if I did not toouch it in any detail in the OP for obvious reasons of “brevity”. 🙂

    It is true that many of the proteins involved (not all, of course) are rather specific to Metazoa, often not found in single celled eukaryotes, and that many of them are rather universal in Metazoa, even in not necessarily in the full variety that is found in vertebrates.

  9. 9
    OldAndrew says:


    The real overwhelming experience is to realize that things are becoming ever more complex day by day, as our understanding of the biological world gets deeper.

    You nailed the thing that really excites me. The smarter we get, we build better microscopes, telescopes, computers, and we develop methods for examining and understanding things. And as we do so, things don’t get simpler – they explode.

    Looking in the opposite direction, outward, it took thousands of years to develop the technology and science just to discover that the sun and stars are massively larger than the earth and emitting incomprehensible power, and that some of them are not stars, but galaxies. Bigger and better telescopes don’t show us a boundary. They just reveal a larger universe.

    If we expected our examination of things big and small to make us their all-knowing masters, we’re disappointed. If we expect to be amazed over and over we’re never disappointed.

  10. 10
    gpuccio says:


    Good thoughts.

    Indeed, the advancements in molecular biology, biophtsics and bioinformatics have been amazing in the last ten years. All of them really precious for the ID view, not so for neo-darwinism.

    You say:

    “If we expected our examination of things big and small to make us their all-knowing masters, we’re disappointed. If we expect to be amazed over and over we’re never disappointed.”

    How true! Humility is the highest quality in science, as in many other fields.

    And those who, like me, have been science fiction fans at some point in thier lives, will remember the best feature of great science fiction literature, especially in the beginnings: the “sense of wonder”.

    Which, of course, is rooted in the transcendental. 🙂

  11. 11
    gpuccio says:

    To all:

    As said in the OP, one of the roles of mechanical cell-ECM interactions in stationary cells is to controll cell morphology and other cell decisions.

    Here is a very recent (Nov. 7, 2018) paper about that aspect:

    Steps in Mechanotransduction Pathways that Control Cell Morphology.


    It is increasingly clear that mechanotransduction pathways play important roles in regulating fundamental cellular functions. Of the basic mechanical functions, the determination of cellular morphology is critical. Cells typically use many mechanosensitive steps and different cell states to achieve a polarized shape through repeated testing of the microenvironment. Indeed, morphology is determined by the microenvironment through periodic activation of motility, mechanotesting, and mechanoresponse functions by hormones, internal clocks, and receptor tyrosine kinases. Patterned substrates and controlled environments with defined rigidities limit the range of cell behavior and influence cell state decisions and are thus very useful for studying these steps. The recently defined rigidity sensing process provides a good example of how cells repeatedly test their microenvironment and is also linked to cancer. In general, aberrant extracellular matrix mechanosensing is associated with numerous conditions, including cardiovascular disease, aging, and fibrosis, that correlate with changes in tissue morphology and matrix composition. Hence, detailed descriptions of the steps involved in sensing and responding to the microenvironment are needed to better understand both the mechanisms of tissue homeostasis and the pathomechanisms of human disease.

  12. 12
    gpuccio says:

    To all:

    And this has a captivating title 🙂 :

    Increasing complexity: Mechanical guidance and feedback loops as a basis for self-organization in morphogenesis.


    The article is devoted to physical views on embryo development as a combination of structurally stable dynamics and symmetry-breaking events in the general process of self-organization. The first corresponds to the deterministic aspect of embryo development. The second type of processes is associated with sudden increase of variability in the periods of symmetry-breaking, which manifests unstable dynamics. The biological basis under these considerations includes chemokinetics (a system of inductors, repressors, and interaction with their next surrounding) and morphomechanics (i.e. mechanotransduction, mechanosensing, and related feedback loops). Although the latter research area is evolving rapidly, up to this time the role of mechanical properties of embryonic tissues and mechano-dependent processes in them are integrated in the general picture of embryo development to a lesser extent than biochemical signaling. For this reason, the present article is mostly devoted to experimental data on morphomechanics in the process of embryo development, also including analysis of its limitations and possible contradictions. The general system of feedback-loops and system dynamics delineated in this review is in large part a repetition of the views of Lev Beloussov, who was one of the founders of the whole areas of morphomechanics and morphodynamics, and to whose memory this article is dedicated.

  13. 13
    gpuccio says:

    To all:

    This paper presents the stimulating idea that the tension of the cell sytoskelecton acts as a “second messenger” in the mechanotransduction of mechanical stimuli to transcription factors in the nucleus.

    Here it is:

    Cellular Mechanotransduction: From Tension to Function


    Living cells are constantly exposed to mechanical stimuli arising from the surrounding extracellular matrix (ECM) or from neighboring cells. The intracellular molecular processes through which such physical cues are transformed into a biological response are collectively dubbed as mechanotransduction and are of fundamental importance to help the cell timely adapt to the continuous dynamic modifications of the microenvironment. Local changes in ECM composition and mechanics are driven by a feed forward interplay between the cell and the matrix itself, with the first depositing ECM proteins that in turn will impact on the surrounding cells. As such, these changes occur regularly during tissue development and are a hallmark of the pathologies of aging. Only lately, though, the importance of mechanical cues in controlling cell function (e.g., proliferation, differentiation, migration) has been acknowledged. Here we provide a critical review of the recent insights into the molecular basis of cellular mechanotransduction, by analyzing how mechanical stimuli get transformed into a given biological response through the activation of a peculiar genetic program. Specifically, by recapitulating the processes involved in the interpretation of ECM remodeling by Focal Adhesions at cell-matrix interphase, we revise the role of cytoskeleton tension as the second messenger of the mechanotransduction process and the action of mechano-responsive shuttling proteins converging on stage and cell-specific transcription factors. Finally, we give few paradigmatic examples highlighting the emerging role of malfunctions in cell mechanosensing apparatus in the onset and progression of pathologies.

    It’s really strange that mainstream scientific papers can use concepts such as “Increasing complexity” and “Function” even in their same titles, but if we use the same words and concepts in an ID perspective people form the other side immediately react, fiercely denying that those same words and concepts have any real meaning.

    Really strange.

  14. 14
    gpuccio says:

    To all:

    We have seen in the OP that cell migration is important for development of all tissues and organs, but has also a fundamental role in the normal function of some specific cell types in the adult organism.

    IOWs, there are some cell types that use migration in their everyday funtions. Good examples of that are immune cells and fibroblasts. So, cell migration is important, for example, for immune responses and for wound healing.

    But, apparently, there is more to that. This recent paper (August 2018) adds a new important perspective.

    It is about T lymphocytes and cell mediated immunity.

    Here it is:

    Alpha-beta T Cell Receptor Mechanosensing Forces out Serial Engagement


    T lymphocytes use alpha-beta T cell receptors (TCRs) to recognize sparse antigenic peptides bound to MHC molecules (pMHCs) arrayed on antigen-presenting cells (APCs). Contrary to conventional receptor–ligand associations exemplified by antigen-antibody interactions, forces play a crucial role in nonequilibrium mechanosensor-based T cell activation. Both T cell motility and local cytoskeleton machinery exert forces (i.e., generate loads) on TCR–pMHC bonds. We review biological features of the load-dependent activation process as revealed by optical tweezers single molecule/single cell and other biophysical measurements. The findings link pMHC-triggered TCRs to single cytoskeletal motors; define the importance of energized anisotropic (i.e., force direction dependent) activation; and characterize immunological synapse formation as digital, revealing no serial requirement. The emerging picture suggests new approaches for the monitoring and design of cytotoxic T lymphocyte (CTL)-based immunotherapy.

    What does it mean?

    It mean that mechanosensing in T lymphocytes is fundamental not only for cell migration (which is of course an important component of T cell function), but also, and much more specifically, for antigen recognition by the T cell receptor (TCR). IOWs, the real functional core of T cell immunity.

    I quote again from the paper:

    Alpha-beta T cells specifically recognize foreign peptides displayed on infected or otherwise perturbed cells through a process that discriminates with exquisite specificity. In so doing, T cells can discern a single amino acid difference between two antigens. At the heart of this process is a receptor–ligand interaction between variable domains on the alpha-beta TCR and a peptide cradled in the groove of a major histocompatibility molecule, pMHC ([1,2] and references therein). APCs displaying peptides at single-molecule (SM) levels can be recognized by T cells [3,4]. Equilibrium between a bound and unbound receptor satisfies the law of mass action and mathematically relates the relative population of species found in the bound and unbound states; the ratio of the forward and reverse state transitions; or similarly the ratio of the state lifetimes. From an equilibrium perspective and our basic understanding of receptor–ligand associations, one expects high affinity. Paradoxically, however, TCR–pMHC affinities as conventionally measured by free-solution methods such as surface plasmon resonance reveal low affinity receptor–ligand interactions; typically in the low to high micromolar 3D affinity range.

    Emphasis mine.

    What does that mean?

    It means that T cell can recognize the antigen with amazing specificity and extreme efficiency (even at single molecule levels). But that efficiency cannot be explained by known biochemical affinity, because that affinity is, paradoxically, low.

    That’s where mechanosensing comes to thw rescue.

    The idea is very well summarized by a section title in the paper:

    Nonequilibrium Mechanosensing Activation Provides a Sensitivity Gain Factor Consistent with alpha-beta TCR Performance

    So, in a nutshell, mechanosensing generates an amazinf gain of function, where biochemical affinities alone would be powerless.

    That’s a very, very interesting fact. And the paper analyzes it in great detail, so I would recomment reading it for those who are interested. It is open access.

    It also documents how complex, specific and multi-faceted the mechanosensing regulation is in these cells.

    Extremely interesting and beautiful! 🙂

  15. 15
    jawa says:

    Excellent presentation!

  16. 16
    gpuccio says:


    Thanks to you! 🙂

  17. 17
    gpuccio says:

    To all:

    Well, the content of this OP could help give an answer to an old false objection that is sometimes made by critics of ID theory.

    Some of them use to say, form time to time:

    “But, after all, it’s all chemistry!”

    We know that it is wrong. The right statement is rather:

    “It’s all chemistry + functional information”.

    But, in the light of this OP, even that would not be precise. We should say, at least:

    “It’s all chemistry + mechanics + functional information”.

    And we are still leaving out electric forces, and who knows what else. 🙂

  18. 18
    Mung says:

    Electrical, Mechanical, Chemical, Informational, Biological – it’s still all just chemistry. Atoms and the void. Things bumping into other things. Some times they attract. Some times they repel.

    There’s nothing to see here people. It’s just the wind blowing the leaves.

  19. 19
    bill cole says:

    Thanks for the fascinating post. Along with an unregulated ubiquitin system poor cell adhesion is an important potential cause of cancer. Particularly when the adhesion protein E-cadherin is down regulated. I am writing a short friends and family paper right now on this subject relating to low vitamin d blood levels. Vitamin d regulates both the ubiquitin system and cell adhesion as they both interact. You’re timing with this article is impeccable as usual. 🙂

  20. 20
    gpuccio says:


    Don’t be so cynical: attracting and repelling is a choice, after all, and the wind and the leaves are complex realities! 🙂

  21. 21
    gpuccio says:

    bill cole:

    Thank you for the thoughts! 🙂

    Yes, each of these complex informational systems has a very important role in cancer, when there are errors in the functional information. I have tried to avoid that aspect in the OPs, just for the sake of “simplicity” and clarity.

    Cadherins have a fundamental role in cell-cell adhesions, a subject that I have mentioned only briefly, always for the sake of “brevity”. They are the “integrins” of cell-cell adhesions, and the cadherin adhesome is as complex and fascinating as the integrin adhesome.

  22. 22
    bill cole says:


    Yes, each of these complex informational systems has a very important role in cancer, when there are errors in the functional information. I have tried to avoid that aspect in the OPs, just for the sake of “simplicity” and clarity.

    I have defined these errors as a loss of functional information as defined by a healthy functioning cell. Do you have any comment?

  23. 23
    gpuccio says:

    bill cole:

    That is a very good question.

    There can be no doubt at all that the mutations in cancer cells are at the expense of the general functionality of the organism.

    But it is also true that they can be defined as “locally functional” for the cell where they arise.

    As you certainly know, my approcah to the definition of FI requires that any possible function can be accepted. If a function, any function, can be explicitly defined, we can measure the FI linked to it.

    So the cancer cell can acquire indipendence from the controls of the organism, sometimes a higher reproduction rate, and so on. When we start anticancer therapy, some cancer cells can acquire resistance, exactly as bacteria become resistant to antibiotics.

    Now, it seems rather certain that mutations in cancer cells are random events. Indeed, cancer cells, for their own nature, are mor subject to mutation than normal cells. Much more, in many cases.

    So, even if the mutation in cancer cells are always at the expense of the higher funtions of the organism, still those mutations can be said to implement local functions in the cells.

    So, what is the point?

    The point is, literally, “simple”.

    Like all functions that derive from random, non designed events, the new functions in cancer cells are always simple. They are, indeed, simple modifications that disrupt already existing complex functions, generating some new local function in the process.

    IOWs, the events that disrupt the funcional balance of the organism and give some local advantage to the mutated cell are always simple: one single mutation in the sequence of some proteins, or more often big but simple chromosomal events, like translocations, duplications, and so on.

    They are similar to the citrate mutation in the E. coli long-term evolution experiment: the mutation is simple, but it changes complex regulations in the cell. The complexity was already there, the simple mutation is only changing a regulation.

    It’s like changing how a complex machine works by just pushing a simple button.

    It’s like disrupting the working of a complex computer by destructing a single transistor: the computer can maybe still work, but its functions can be deranged.

    This is what happens oin cancer cells. The mutations are simple, the consequences are a severe loss of function for the organism, accompanied by some local advantages for the individual cells. But the process is always simple, no complex FI is ever generated.

    IOWs, no cancer cell wil ever generate a completely new functional protein, with a complex function that requires more than 500 specific bits to be implemented. In the same way that you will never get new original and efficient CPU functions by destroying a transistor.

    I think that some in the ID fiels seem to believe that functions have to be “good”. That is not true. Functions are often “bad”. The simple functions that arise in cancer cells are certainly bad for the organisms, but they still are functions, and they arise from random events.

    Another apparent belief of some in the ID field is that FI can never be generated by random events. That is not true. Simple functional information can easily arise by random contingency. It’s not difficult to find a stone that has a form that can implement some function. Simple computer instructions can arise from a random search. Very simple English words are easily found by a random engine.

    The common element is always one: simple.

    Random events can generate a few bits of functional information, and not much more.

    Certainly, never 500 bits, in the whole known universe.

    It’s like in my example of the thief: the key to the one big safe can never be found by chance, but it is easy to find the simple keys to many smaller safes.

    So, again, we must stick to the fundamental concepts:

    a) Functional information can be computed for any function that can be objectively defined, good or bad, simple or complex. No function can be refuted a priori.

    b) Simple functional information can often be found in non designed objects.

    c) Complex functional information always arises from a design process.

    It’s as simple as that.

  24. 24
    bill cole says:

    hi gpuccio
    Thanks for the explanation. So functional information depends specifically how function is defined. From my perspective the cancers I have studied are the activation of embryo pathways like the WNT(Wingless) pathway in a mature animal.

    Since these pathways exist in the cell as they are critical in forming an animal from a Zygote, cancer is activating information that already exists. In the case of vitamin d deficiency they can be initiated without change to DNA. As the cell cycle starts to fail as DNA repair and apoptosis fails the cell becomes resistant to cell death and has a competitive advantage. In my opinion this is a loss of functional information if FUNCTIONAL INFORMATION IS DEFINED AS THE PROPER OPERATION OF A MATURE CELL. Defining functional information as cancerous reproduction does not make any sense as the case defined above is the loss of a properly functioning eukaryotic cell cycle.

  25. 25
    gpuccio says:

    bill cole:

    You say:

    “So functional information depends specifically how function is defined.”

    Yes, absolutely! That’s exactly my definition and all my procedures are based on that definition. You can check it in my old OP about FI:

    Functional information defined

    Then you say:

    “Since these pathways exist in the cell as they are critical in forming an animal from a Zygote, cancer is activating information that already exists.”

    Correct. So, the FI implied in the cancer transition is only the few bits necessary to activate the bnew condition. It is, definitely, a simple transition, and therefore the FI linked to the functional transition is very low. As it always is the case when FI is generated by random events.

    Then you say:

    “In the case of vitamin d deficiency they can be initiated without change to DNA. As the cell cycle starts to fail as DNA repair and apoptosis fails the cell becomes resistant to cell death and has a competitive advantage.”

    I am not sure what you mean. I am aware that low levels of vitamin D can increase the risk for some types of cancer, and certainly that is due to some impairment in cell functions. But I am not aware that cancer itself can be initiated without any change to DNA. Is that what you mean? Do you have a reference for that?

    Then you say:

    “In my opinion this is a loss of functional information if FUNCTIONAL INFORMATION IS DEFINED AS THE PROPER OPERATION OF A MATURE CELL.”

    Here I am afraid that our paths divide a little.

    As you certainly understand, that is not compatible with my definition of FI.

    I must state very strongly that in my approach any possible function can be accepted, provided that it can be objectively defined and therefore the FI linked to it can be measured. There is no need to restrict functions to “the proper operation of a mature cell” or “a properly functioning eukaryotic cell cycle”. IOWs, there is no need fro a function to be “proper”, whatever it means.

    Function is simply something that an object can do, or can be used to do, without any restriction or connotation, and that some observer can objectively define, so that the FI linked to that functional definition can be measured. That is valid both for absolute functions and for functional transitions.

    Why am I so strict about that point? I will try to explain.

    a) First of all, I believe that for the design inference we need a definition of function that is completely empirical, and that does not involve any philosophical beckground. Defining concepts like “proper functioning” is difficult and ambiguous, IMO. I would like to be clear about that. Of course I agree with you that a cancer cell is deleterious from the point of view of the organism. I absolutely agree with that. For the organism, cancer is certainly a loss of function. But I don’t want to be tied to the point of view of the organism, or to any other point of view, I want a definition of function that is simple, universal, and that can be applied to any object, and to any possible context. Why? Because there is no need of anything different to infer design, as I am going to explain.

    OK, more in next post.

  26. 26
    gpuccio says:

    bill cole:

    So, let’s go on with my points:

    b) My simple point is that an empirical definition such as mine is not only simple and universal. It is also the strongest definition to make the case for ID.

    To explain why, just compare these two definition, which correspond more or less to yours and mine, as applied to the design inference:

    b1) You can infer design any time that you observe some object that contributes to the proper functioning of a cell, or of any other system, if the specific configuration needed to achieve that is higher than 500 bits.

    b2) You can infer design any time that you observe some object that can do anything that can be objectively defined, if the specific configuration needed to achieve that is higher than 500 bits.

    I hope you can see that the second statement (mine) is much stronger than the first. If the second statement is true, the design inference is much stronger and universal.

    And the simple point is: the second statement is absolutely true. You will never find any object in the universe that is not designed that can implement any independently define function that requirea a specific configuration higher than 500 bits to be achieve.

    That is a very strong statement, but it is absolutely true. And it is the true foundation of the conceptual strength of ID.

    IOWs, there is absolutely no need to restrict function to some general idea of “proper” or “good” or any other concept. We can freely accept any function definition, proveded that it is explicit and objective.

    In all cases, and I say it again, in all cases, if we can independently define a function, any function, that can be implemented by the object, and if that function need a specific configuration higher than 500 bits, then we can infer design for the object.

    Again, this is a very strong statement, and it is absolutely true. No counter example exists in the whole known universe. That’s why I am a convinced supporter of what we could call “strong ID theory”: any object with more than 500 bits of FI, measure for even one single function out of all possible ones, is designed.

    More in next post.

  27. 27
    gpuccio says:

    bill cole:

    Just a short clarification: some may wonder why I have used the word “independently” in my definitions above. It’s very simple: I just want to remind that we cannot use the contingent information in the object to define the function. That is the only restriction.

    The reason for that should be obvious. Let’s go again to my favourite example, the safes.

    Let’s say that I generate a random number of, say, 100 digits. Then I go to my safe and set the key at that random number. So I can say: “Look, I have generated in a random system an object (the number) that has a lot of FI, because it can open this safe”.

    Of course, that is cheating. In this case, I need to know the specific contingent information in the object to set the function. IOWs, the information already existing in the object guides (if you want, designs) the setting of the function.

    That’s cheating, but it is an argument that is often used by neo-darwinists, sometimes in good faith. For example, it was used by Mark Frank, in perfect good faith I believe, a lot of time ago.

    That’s the only reason why I have specified “independently” in my definitions above. It has no other meaning.

    More in next post.

  28. 28
    jawa says:

    gpuccio @27:

    Is the FI associated with the actual mechanisms used for setting the key to any code, regardless of how such code is generated?

  29. 29
    gpuccio says:

    bill cole:

    c) So, I will provide here a very simple example where a functional definition does not coincide with the proper working of the organism or of the eukaryotic cell, and still is perfectly valid.

    I am referring here to the HeLa cells.

    As you certainly know, it’s a human cell line derived form a cancer. But is has many functions that can be objectively defined. I quote here from the Wikipedia page:

    HeLa (also Hela or hela) is an immortal cell line used in scientific research. It is the oldest and most commonly used human cell line.[1] The line was derived from cervical cancer cells taken on February 8, 1951[2] from Henrietta Lacks, a patient who died of cancer on October 4, 1951. The cell line was found to be remarkably durable and prolific which warrants its extensive use in scientific research.

    These were the first human cells grown in a lab that were naturally “immortal”, meaning that they do not die after a set number of cell divisions (i.e. cellular senescence).[7] These cells could be used for conducting a multitude of medical experiments—if the cells died, they could simply be discarded and the experiment attempted again on fresh cells from the culture. This represented an enormous boon to medical and biological research, as previously stocks of living cells were limited and took significant effort to culture.

    The stable growth of HeLa enabled a researcher at the University of Minnesota hospital to successfully grow polio virus, enabling the development of a vaccine,[8] and by 1952, Jonas Salk developed a vaccine for polio using these cells.[4][9] To test Salk’s new vaccine, the cells were put into mass production in the first-ever cell production factory.

    Since the cells’ first mass replications, they have been used by scientists in various types of investigations including disease research, gene mapping, effects of toxic substances on organisms, and radiation on humans.[9] Additionally, HeLa cells have been used to test human sensitivity to tape, glue, cosmetics, and many other products.

    So, can you deny that HeLa cell can implement a lot of important functions, that can be explicitly defined?

    I don’t think so.

    And yet, they are cancer cell. They certainly did nothing good to their original organism, and certainly they are not examples of the proper working of an eukaryotic cell.

    So, what’s the difference between the HeLa cells, cancer cells, and the “normal2 cells of their original host?

    Well, much is known. Their genome has even been completely sequenced, even if the access to it is regulated for privacy reasons.

    But, for example, we know that (from Wikipedia again):

    Horizontal gene transfer from human papillomavirus 18 (HPV18) to human cervical cells created the HeLa genome, which is different from Henrietta Lacks’ genome in various ways, including its number of chromosomes. HeLa cells are rapidly dividing cancer cells, and the number of chromosomes varied during cancer formation and cell culture. The current estimate (excluding very tiny fragments) is a “hypertriploid chromosome number (3n+)” which means 76 to 80 total chromosomes (rather than the normal diploid number of 46) with 22–25 clonally abnormal chromosomes, known as HeLa signature chromosomes.

    So, again, the transition, even if dramatic, is essentially simple. Changes in ploidy can be caused by very simple events. They are not complex FI. They are very frequent in cancer cells. They arise from random events.

    Moreover, the transition in this case was probably cause by HGT form an existin virus, the papilloma virus, which is known to cause cervical cancer.

    So, as you can see, we have cancer cells that have acquired, with the cancer transition, a lot of interesting functions that cannot be implemented by “normal” human cells, functions that have been used by us for decades to achieve specific medical goals.

    Is the cancer transition complex? Absolutely not. It is of course in the range of random events + the information in the already existing papilloma virus.

    Do the specific functions use the existing FI of the normal cells? Of course. They could not even exist or reproduce without that information, and their immortalization is certainly supported by many already existing and complex functional pathways. It’s just the regularion that has been deranged.

    Does the cancer transition represent a loss of functionalinformation? Of course. For the original organism, it is a severe loss of information. There is no doubt about that.

    Does the cancer transition represent a gain of functional information? Of course. For medial researchers it was really an unexpected resource.

    Is there a contradiction in that? Absolutely not. As said, we can define as many different functions for an object as we want. Anyone can do that. But the functions must be objectively defined, so that anyone can measure the FI linked to the function, or to the functional transition.

    In the case of cancer cells, the FI linked to the functional transition (defined for some newly acquired function in the cancer cell) is always low. And there is no need to infer design for that functional transition.

    I hope my point is clear. 🙂

  30. 30
    gpuccio says:


    If you refer to my example of the safe, it’s simple:

    The key to the safe is designed. The designer is the individual who sets the key. That individual uses the random (non functional) total information in the already generated random number to set the key for the safe.

    In that way, a very high total information (about 332 bits) which has no special function at the time of its random generation (and certainly no complex functionality) becomes functional information as the result of the conscious, intelligent and purposeful act of that individual: he just sets the key to a value that he already knows.

    That’s a very good example of how intelligent design can easily generate FI that did not exist before: in this case, simply by mapping existing random information to a specified function. Of course, that intervention requires the intelligent setting of the 100 digits in the safe key to the values observed in the random number.

  31. 31
    jawa says:

    Ok that makes sense

  32. 32
    jawa says:

    What’s the counter argument presented against your safe key ilustración by some professor JF from another website that was referenced by bill cole or another commenter here?
    Maybe I missed reading that comment when it was posted.
    Would you mind to repeat it and explain what’s wrong with it?

  33. 33
    gpuccio says:


    I am not aware of any counter-argument. JF wrote recently that he was going to answer that point, but I don’t know if he did it. If anyone here has read a counter-argument about that point, I would certainly like to know.

    Frankly, I get a little bit lost at TSZ! 🙂

  34. 34
    gpuccio says:

    To all:

    This is another good title, and it introduces a new concept: mechanical memory. Not open access.

    Unforgettable force – crosstalk and memory of mechanosensitive structures.


    The ability of cells to sense and respond to mechanical stimuli is crucial for many developmental and homeostatic processes, while mechanical dysfunction of cells has been associated with numerous pathologies including muscular dystrophies, cardiovascular defects, and epithelial disorders. Yet, how cells detect and process mechanical information is still unclear. In this review, we outline major mechanisms underlying cellular mechanotransduction and we summarize the current understanding of how cells integrate information from distinct mechanosensitive structures to mediate complex mechanoresponses. We also discuss the concept of mechanical memory and describe how cells store information on previous mechanical events for different periods of time.

  35. 35
    gpuccio says:

    To all:

    One important point here is the following.

    Mechano-transduction is a mapping of mechanical signals to biochemicla signals and pathways.

    Now, a mapping where no natural laws can explain the connection, and the connection depends exclusively on specific complex configurations of the system, is in itself symbolic.

    We are familiar with many biochemical systems in the cell where signals are mapped indirectly to responses, through specific configurations realized by specific FI. For example, outer biochemical signals (cytokines, hormones) interact with complex mebrane receptors, and activate complex signaling pathways that translate the message to the nucleus, where the response takes place in terms of chamges in transcription regulation. That is amazing, and highly symbolic. However, we have in some way become accustomed to those things, and our sense of wonder is sleeping.

    But what we see in mechanotransduction is even more amazing, because here the signals and the responses belong to two completely different realms of nature: mechanics and biochemistry. So, the complex mapping is, if we can say so, even more symbolic.

    Look for example at the described mechanism for talin. A domain must be in a folded state, but with a weak folding, and it must include hidden vinculin binding domains, so that, when a force if applied, the domain may unfold and the hidden domains may become active. So the mechanic force generates a biochemical result, but think at how complex the configuration of this small subsystem must be!


  36. 36
    Mung says:

    “So functional information depends specifically how function is defined.”

    Yes, absolutely!

    FI is in the mind of the definer. 🙂

  37. 37
    gpuccio says:


    Yes, just as science is in the mind of the scientist! 🙂

    OK, just to be serious:

    The definition of a function is in the mind of the definer.

    Until he explicitly and objectively defines it.

    After that, the definition is in the mind of anyone who wants to read it.

    After that, FI can be objectively computed for that funtion by anyone.

    So, FI is in the mind of all! 🙂

    (well, maybe except neo-darwinists…)

  38. 38
    ET says:

    Biological specification always refers to function. An organism is a functional system comprising many functional subsystems. In virtue of their function, these systems embody patterns that are objectively given and can be identified independently of the systems that embody them. Hence these systems are specified in the same sense required by the complexity-specification criterion (see sections 1.3 and 2.5). The specification of organisms can be cashed out in any number of ways. Arno Wouters cashes it out globally in terms of the viability of whole organisms. Michael Behe cashes it out in terms of minimal function of biochemical systems.- Wm. Dembski page 148 of NFL

    Functionality is an observation.

  39. 39
    gpuccio says:


    Wonderful quote, thank you! 🙂

  40. 40
    Mung says:


    So, FI is in the mind of all!

    You’ve just proven that FI can increase!

  41. 41
    bill cole says:


    In the case of cancer cells, the FI linked to the functional transition (defined for some newly acquired function in the cancer cell) is always low. And there is no need to infer design for that functional transition.

    I hope my point is clear. ????

    Yes, I agree with most of your points and I really appreciate you keeping to a strict definition of FI.

    The question in my mind is cancer creating FI or destroying it based on the fact that FI that it is using already existed in the organism prior to the initial cause of cancer?

    Did cancer find a functional variation inside the FI of a healthy cell?

  42. 42
    gpuccio says:


    Joe Felsestein will be happy! 🙂

  43. 43
    gpuccio says:

    bill cole:

    “Did cancer find a functional variation inside the FI for a healthy cell?”

    Yes, that’s the idea.

    Remember, in the organism each cell is strictly contrained to do what is best for the organism, in terms of morphology, functions, duplication, apoptosis and so on.

    Cancer cells, as a result of random variations in their informational content, elude part of that control. So, they can replicate independently, avoiding the “limitations” imposed to other cells.

    Of course, they also lose a lot of important functions as a result of the mutations and of the disturbed cell functions. That’s why they are often a good target for chemiotherapy or radiotherapy.

    However, someof the modifications generated by the mutations can be described as new functions.

    So, let’s say that cancer cell acquire some new functions, and lose other old functions. They are simply different, they have a different internal balance, essentially destructive.

    But again, the point is that the mutations that transform a normal cell into a cancer cell are essentially simple. It’s like pushing randomly the button in a dashboard. The action is random and functionless, but as we are pushing buttons that control highly complex functions, what happens is largely impredicatble, and can accomplish something different from the usual functional operations.

    No cancer cell has ever developed a new original protein of 1000 AAs that operates biochemical marvels, and did not exist in the original cell, or in some virus that contributed to the transformation.

    Like all random systems, cancer does not generate new complex FI.

  44. 44
    bill cole says:

    Thank you. This discussion has been very helpful 🙂

  45. 45
    gpuccio says:

    bill cole:

    Thanks to you. It’s a pleasure to discuss with you. 🙂

  46. 46
    jawa says:

    Can Mung or bill cole remind that professor JF at TSZ to present his counter argument to gpuccio’s safe key example?
    Why is it taking so long? If there are questions, I’m sure gpuccio would be delighted to answer them. If somebody else wants to debate it too, go ahead. I’m just curious to find out what they can show at this point.

  47. 47
    ET says:

    Cancer, in the very least, is an over all loss of cellular specificity. The cells clearly not only lost their identity but also lost the ability to behave properly.

    The lowest living life forms and cancer cells utilize the inefficient energy yielding reaction of the fermentation of sugar. This is primitive to our cells normal way of producing energy, namely ATP production via respiration of O2. This is also clearly a loss of function and information. The cancer cells are more primitive than the normal cell they are supposed to be. I don’t see how anyone can argue there is some gain to be had with cancer. I don’t see how anyone can use cancer to try to refute anything ID claims. Seems like desperation to me.

  48. 48
    gpuccio says:

    To all:

    Regarding symbolic mapping and codes, this brand new paper is certainly interesting:

    Radial glia fibers translate Fgf8 morphogenetic signals to generate a thalamic nuclear complex protomap in the mantle layer.


    Thalamic neurons are distributed between different nuclear groups of the thalamic multinuclear complex; they develop topologically ordered specific projections that convey information on voluntary motor programs and sensory modalities to functional areas in the cerebral cortex. Since thalamic neurons present a homogeneous morphology, their functional specificity is derived from their afferent and efferent connectivity. Adequate development of thalamic afferent and efferent connections depends on guide signals that bind receptors in nuclear neuropils and axonal growth cones, respectively. These are finally regulated by regionalization processes in the thalamic neurons, codifying topological information. In this work, we studied the role of Fgf8 morphogenetic signaling in establishing the molecular thalamic protomap, which was revealed by Igsf21, Pde10a and Btbd3 gene expression in the thalamic mantle layer. Fgf8 signaling activity was evidenced by pERK expression in radial glia cells and fibers, which may represent a scaffold that translates neuroepithelial positional information to the mantle layer. In this work, we describe the fact that Fgf8-hypomorphic mice did not express pERK in radial glia cells and fibers and presented disorganized thalamic regionalization, increasing neuronal death in the ventro-lateral thalamus and strong disruption of thalamocortical projections. In conclusion, Fgf8 encodes the positional information required for thalamic nuclear regionalization and the development of thalamocortical projections.

    Please note the key concepts:

    topologically ordered specific projections

    convey information

    functional specificity

    codifying topological information

    translates neuroepithelial positional information

    encodes the positional information

    So, another highly symbolic system! 🙂

  49. 49
    jawa says:

    “Please note the key concepts:
    topologically ordered specific projections
    convey information
    functional specificity
    codifying topological information
    translates neuroepithelial positional information
    encodes the positional information
    So, another highly symbolic system!”

    Was this paper peer-reviewed ?

    Apparently it wasn’t.

    Are the authors ID-proponents ?

    Apparently they are.


  50. 50
    jawa says:

    BTW, any news from the professor JF at TSZ regarding gpuccio’s “safe key” question(s)?
    I still don’t understand why those distinguished academic personalities don’t engage in serious discussions with gpuccio ? Is it that they don’t understand his Italian accent?
    Have Mung or bill cole pass along the memo yet?

  51. 51
    gpuccio says:

    To all:

    The correct guidance of axons in the course of development is really a fascinating topic.

    In brief, it requires at least:

    a) A complex repertoire of signals (ligands) that are secreted by many different cells and tissues, and, either in a soluble form or in specific binding to the ECM, design a complex topography of functional clues for the neurons and axons.

    b) A complex specific pattern of receptors and other components in each specific neuron/axon, that allows wach specific neuron/axon to interpret correctly that topology for its own individual target and pathway.

    How all that may be so perfectly and ifficiently implemented for billions of neurons and axons is really puzzling, even from a design perspective. For a non design perspective, I would say that there is no game at all.

    Here are a couple of recent papers:

    Commissural axon navigation in the spinal cord: A repertoire of repulsive forces is in command


    The navigation of commissural axons in the developing spinal cord has attracted multiple studies over the years. Many important concepts emerged from these studies which have enlighten the general mechanisms of axon guidance. The navigation of commissural axons is regulated by a series of cellular territories which provides the diverse guidance information necessary to ensure the successive steps of their pathfinding towards, across, and away from the ventral midline. In this review, we discuss how repulsive forces, by propelling, channelling, and confining commissural axon navigation, bring key contributions to the formation of this neuronal projection.

    Meninges-derived cues control axon guidance


    The axons of developing neurons travel long distances along stereotyped pathways under the direction of extracellular cues sensed by the axonal growth cone. Guidance cues are either secreted proteins that diffuse freely or bind the extracellular matrix, or membrane-anchored proteins. Different populations of axons express distinct sets of receptors for guidance cues, which results in differential responses to specific ligands. The full repertoire of axon guidance cues and receptors and the identity of the tissues producing these cues remain to be elucidated. The meninges are connective tissue layers enveloping the vertebrate brain and spinal cord that serve to protect the central nervous system (CNS). The meninges also instruct nervous system development by regulating the generation and migration of neural progenitors, but it has not been determined whether they help guide axons to their targets. Here, we investigate a possible role for the meninges in neuronal wiring. Using mouse neural tissue explants, we show that developing spinal cord meninges produce secreted attractive and repulsive cues that can guide multiple types of axons in vitro. We find that motor and sensory neurons, which project axons across the CNS-peripheral nervous system (PNS) boundary, are attracted by meninges. Conversely, axons of both ipsi- and contralaterally projecting dorsal spinal cord interneurons are repelled by meninges. The responses of these axonal populations to the meninges are consistent with their trajectories relative to meninges in vivo, suggesting that meningeal guidance factors contribute to nervous system wiring and control which axons are able to traverse the CNS-PNS boundary.

    Revisiting Netrin-1: One Who Guides (Axons).

    Proper patterning of the nervous system requires that developing axons find appropriate postsynaptic partners; this entails microns to meters of extension through an extracellular milieu exhibiting a wide range of mechanical and chemical properties. Thus, the elaborate networks of fiber tracts and non-fasciculated axons evident in mature organisms are formed via complex pathfinding. The macroscopic structures of axon projections are highly stereotyped across members of the same species, indicating precise mechanisms guide their formation. The developing axon exhibits directionally biased growth toward or away from external guidance cues. One of the most studied guidance cues is netrin-1, however, its presentation in vivo remains debated. Guidance cues can be secreted to form soluble or chemotactic gradients or presented bound to cells or the extracellular matrix to form haptotactic gradients. The growth cone, a highly specialized dynamic structure at the end of the extending axon, detects these guidance cues via transmembrane receptors, such as the netrin-1 receptors deleted in colorectal cancer (DCC) and UNC5. These receptors orchestrate remodeling of the cytoskeleton and cell membrane through both chemical and mechanotransductive pathways, which result in traction forces generated by the cytoskeleton against the extracellular environment and translocation of the growth cone. Through intracellular signaling responses, netrin-1 can trigger either attraction or repulsion of the axon. Here we review the mechanisms by which the classical guidance cue netrin-1 regulates intracellular effectors to respond to the extracellular environment in the context of axon guidance during development of the central nervous system and discuss recent findings that demonstrate the critical importance of mechanical forces in this process.

  52. 52

    It just never stops, eh GP?

    symbols, semiosis, IC.


  53. 53

    Another beautiful OP from GPuccio.

  54. 54
    jawa says:

    UB @52:

    “never stops”?

    Of course not, it keeps getting “worse” (for the neo-Darwinian club)

  55. 55
    gpuccio says:

    Upright BiPed:

    Hi, nice to hear from you! 🙂

    Yes, it never stops. And, as jawa says, it gets worse (for someone)…

    Maybe I have become “complexity addicted”, but I just can’t help being fascinated by each new discovery of overwhelming design in living beings.

    Yes, symbols and semiosis become the absolute rule as soon as we climb the ladder of higher organizational layers.

  56. 56
    jawa says:

    UB @53:


  57. 57
    gpuccio says:

    To all:

    Cytokines are the main tool for cell to cell signaling, especially in the immune system. They are organized in a very complex network, which could in itslef be the subject of some future OP.

    However, it seems that they also have a fundamental role in the development of the central nervous system, and therefore in the processes we have discussed here:

    Nerve cells developmental processes and the dynamic role of cytokine signaling.

    The stunning diversity of neurons and glial cells makes possible the higher functions of the central nervous system (CNS), allowing the organism to sense, interpret and respond appropriately to the external environment. This cellular diversity derives from a single primary progenitor cell type initiating lineage leading to the formation of both differentiated neurons and glial cells. The processes governing the differentiation of the progenitor pool of cells into mature nerve cells will be here briefly reviewed. They involve morphological transformations, specialized modes of cell division, migration, and controlled cell death, and are regulated through cell-cell interactions and cues provided by the extracellular matrix, as well as by humoral factors from the cerebrospinal fluid and the blood system. In this respect, a quite large body of studies have been focused on cytokines, proteins representing the main signaling network that coordinates immune defense and the maintenance of homeostasis. At the same time, they are deeply involved in CNS development as regulatory factors. This dual role in the nervous system appears of particular relevance for CNS pathology, since cytokine dysregulation (occurring as a consequence of maternal infection, exposure to environmental factors or prenatal hypoxia) can profoundly impact on neurodevelopment and likely influence the response of the adult tissue during neuroinflammatory events.

    It’s really incredible how these complex networks, even if relatively different and independent, are at the same time intertwined in what we could call a meta-network.

  58. 58
    jawa says:

    in the very interesting paper @48 they say that “Fgf8 signal is involved in the specification of the neural territories where axonal guidance molecules are expressed.”. But that statement alone raises new questions which eventually lead to uncovering more details about the biological control system. As UB said, it never stops. Apparently some folks out there don’t like this. However, I think it’s fascinating, isn’t it?

  59. 59
    gpuccio says:

    To all:

    And, of course, old friends come back everywhere:

    The ubiquitin-proteasome system regulates focal adhesions at the leading edge of migrating cells.


    Cell migration requires the cyclical assembly and disassembly of focal adhesions. Adhesion induces phosphorylation of focal adhesion proteins, including Cas (Crk-associated substrate/p130Cas/BCAR1). However, Cas phosphorylation stimulates adhesion turnover. This raises the question of how adhesion assembly occurs against opposition from phospho-Cas. Here we show that suppressor of cytokine signaling 6 (SOCS6) and Cullin 5, two components of the CRL5SOCS6 ubiquitin ligase, inhibit Cas-dependent focal adhesion turnover at the front but not rear of migrating epithelial cells. The front focal adhesions contain phospho-Cas which recruits SOCS6. If SOCS6 cannot access focal adhesions, or if cullins or the proteasome are inhibited, adhesion disassembly is stimulated. This suggests that the localized targeting of phospho-Cas within adhesions by CRL5SOCS6 and concurrent cullin and proteasome activity provide a negative feedback loop, ensuring that adhesion assembly predominates over disassembly at the leading edge. By this mechanism, ubiquitination provides a new level of spatio-temporal control over cell migration.

  60. 60
    jawa says:

    “which could in itslef be the subject of some future OP.”

    I like that!


  61. 61
    jawa says:

    “It’s really incredible how these complex networks, even if relatively different and independent, are at the same time intertwined in what we could call a meta-network.”

    Well, it’s more incredible that all that arose through RV+NS!
    However, many distinguished academic personalities seem to believe that.
    Any idea why? I’m clueless.

  62. 62
    jawa says:

    “The ubiquitin-proteasome system regulates focal adhesions at the leading edge of migrating cells.”

    There it goes again!


  63. 63
    jawa says:

    “And, of course, old friends come back everywhere:”

    That’s what friends are for… 🙂

  64. 64
    bill cole says:

    Hi Jawa…here it is.

    Does gpuccio’s 150-safe ‘thief’ example validate the 500-bits rule?
    Posted on December 2, 2018 by Joe Felsenstein
    At Uncommon Descent, poster gpuccio has expressed interest in what I think of his example of a safecracker trying to open a safe with a 150-digit combination, or open 150 safes, each with its own 1-digit combination. It’s actually a cute teaching example, which helps explain why natural selection cannot find a region of “function” in a sequence space in such a case. The implication is that there is some point of contention that I failed to address, in my post which led to the nearly 2,000-comment-long thread on his argument here at TSZ. He asks:

    By the way, has Joe Felsestein answered my argument about the thief? Has he shown how complex functional information can increase gradually in a genome?

    Gpuccio has repeated his call for me to comment on his ‘thief’ scenario a number of times, including here, and UD reader “jawa” taken up the torch (here and here), asking whether I have yet answered the thief argument), at first dramatically asking

    Does anybody else wonder why these professors ran away when the discussions got deep into real evidence territory?

    Any thoughts?

    and then supplying the “thoughts” definitively (here)

    we all know why those distinguished professors ran away from the heat of a serious discussion with gpuccio, it’s obvious: lack of solid arguments.

    I’ll re-explain gpuccio’s example below the fold, and then point out that I never contested gpuccio’s safe example, but I certainly do contest gpuccio’s method of showing that “Complex Functional Information” cannot be achieved by natural selection. gpuccio manages to do that by defining “complex functional information” differently from Szostak and Hazen’s definition of functional information, in a way that makes his rule true. But gpuccio never manages to show that when Functional Information is defined as Hazen and Szostak defined it, that 150 bits of it cannot be accumulated by natural selection.

    The Thief Scenario

    Here is gpuccio’s scenario, as most succinctly stated in comment #65 of his ‘Texas Sharpshooter post at UD (gpuccio gives there links to some earlier appearances of the scenario):

    In essence, we compare two systems. One is made of one single object (a big safe). the other of 50 smaller safes.

    The sum in the big safe is the same as the sums in the 150 smaller safes put together. that ensures that both systems, if solved, increase the fitness of the thief in the same measure.

    Let’s say that our functional objects, in each system, are:

    a) a single piece of card with the 150 figures of the key to the big

    b) 150 pieces of card, each containing the one figure key to one of the small safes (correctly labeled, so that the thief can use them directly).

    Now, if the thief owns the functional objects, he can easily get the sum, both in the big safe and in the small safes.

    But our model is that the keys are not known to the thief, so we want to compute the probability of getting to them in the two different scenarios by a random search.

    So, in the first scenario, the thief tries the 10^150 possible solutions, until he finds the right one.

    In the second scenario, he tries the ten possible solutions for the first safe, opens it, then passes to the second, and so on.

    and gpuccio’s challenge is:

    Do you think that the two scenarios are equivalent?

    What should the thief do, according to your views?

    My answers of course are, to the first question, “No”. To the second question, “Cheat, or hope that in this particular case you have an instance of the second scenario”.

    My reaction: This is a nice teaching example showing why, in the first scenario, there is no hope of guessing the correct key, even once in the history of the universe.

    In the first scenario there is no path to getting the safe open by successively opening parts of it. In the second case one can make an average of 5 guesses and open a safe, and when you have done this 150 times you get all the contents of the safes.

    My question

    Why did gpuccio think that I objected to gpuccio’s logic for the case which has nonzero function only in a set of sequences which is 10^{-150} of all sequences? I was very clear in acknowledging that in such a case, natural selection cannot find the sequences that have nonzero function, if we start in a random sequence.

    Repeating his argument does not help his case, because my point is not that this part of his argument is wrong. And this was made very clear in my previous post on gpuccio’s argument. But let me repeat, for those who did not happen read that post.

    What gpuccio got wrong

    Gpuccio had stated (here) that

    … the idea is that if we observe any object that exhibits complex functional information (for example, more than 500 bits of functional information ) for an explicitly defined function (whatever it is) we can safely infer design.

    Functional information was defined by Jack Szostak (2003) and by Szostak, Hazen, and Carothers (2007). It assumes that we have a set of molecular sequences (for example, the coding sequence of a single protein, or its amino acid sequences), and with each of them is associated a number, the function. For example, its ability to synthesize ATP if it is an ATP synthase.

    In this original definition of FI, there is no assumption that almost all of the sequences have function zero. Given that, there is no way to rule out the possibility that there are paths from many parts of the sequence space that lead to higher and higher function. And given that, we cannot eliminate the possibility that natural selection and mutation could follow such a path to arrive at the function that we observe in nature.

    How gpuccio eliminates natural selection

    Simply by changing the definition of Functional Information for gpuccio’s Complex Functional Information. And only calling it that when the amount of Function is zero for all sequences outside of the target set. That makes gpuccio’s definition of
    Complex Functional Information very different from Szostak’s and Hagen’s. Gpuccio’s restricted definition rules out all cases where there might be a path among sequences leading to the target sequences, a path which has function rising continually along that path.

    This was explained clearly many times in my post and in the 2,000-comment thread that it generated. Apparently all that gpuccio and jawa can do is repeat their argument, one which does not show that 500 bits of Functional Information, defined as Szostak and
    Hagen define it, cannot be achieved by normal evolutionary processes such as natural selection.

  65. 65
    ET says:

    Joe Felsenstein clearly does not understand how science operates:

    Apparently all that gpuccio and jawa can do is repeat their argument, one which does not show that 500 bits of Functional Information, defined as Szostak and
    Hagen define it, cannot be achieved by normal evolutionary processes such as natural selection.

    Clueless. It is up to Joe Felsenstein and others to demonstrate that natural selection can produce 500 bits of functional information and yet he cannot.

    Why are evolutionists so ignorant of science? Why do they think it is up to us to prove a negative in order to refute their claims which have never been demonstrated?

    The regulars of TSZ are hopeless.

  66. 66
    gpuccio says:

    bill cole:

    Bill, thanks for posting it. Just give me the time to read it! 🙂

  67. 67
    gpuccio says:

    Joe Felsestein (at TSZ):

    First of all, thank you for taking the time to answer my comments and to cosnider the thief scenario. To be clear, I have never reqruied that you did that, I was simply hoping that you would, because I like discussion.

    Now I will try to understand your point and to clarify mine. It is not so simple, because our discussions have been many and in different contexts, not to mention the difficulty in the parallel comments on two different blogs.

    So, maybe the first thing is to quote here the specific comment that made me present, is gradual successive phases, the thief scenario that you have well summarized in your comment here.

    Your original comment is in the thread about my ubiquitin OP. Here it is:

    Joe Felsenstein at TSZ:

    April 10, 2018 at 12:32 am

    SCREECH!! [Goalposts moving]

    1. The 500 bits criterion, which originated with Dembski, was gpuccio’s criterion for “complex”, as I demonstrated in clear quotes from gpuccio in my previous comment.

    2. That counts up changes anywhere in the genome, as long as they contribute to the fitness, and it counts up whatever successive changes occur.

    3. Now, in both gpuccio’s and your comments, the requirement is added that all this occur in one protein, in one change, and that it be “new and original function”.

    4. That was not a part of the 500-bit criterion that gpuccio firmly declares to be the foundation of ID.

    5. There was supposed to be some reason why a 500 bit increase in functional information was not attainable by natural selection. Without any requirement that it involve “new and original function”.

    So what is the “foundational” requirement? A 500-bit increase in functional information, taken over multiple changes, possibly throughout the genome? Or attainment of a “new and original function”? In the latter case who judges newness and originality of function?

    To that, I answered with this comment, which is not yet the thief scenario, but certainly lays the foundation for it.

    Comment 828 in the Ubiquitin thread:

    Joe Felsenstein at TSZ:

    April 10, 2018 at 12:32 am

    Are you kidding? Have you lost your mind?

    The 500 bits criterion, which originated with Dembski, was gpuccio’s criterion for “complex”, as I demonstrated in clear quotes from gpuccio in my previous comment.

    It’s of course my criterion for complex functional information: the information linked to the implementation of one explicitly defined function.

    IOWs, if a function can be implemented by an object, or by an IC system, and it requires at least 500 specific bits to be implemented by that object, it is complex.

    As I have always said. See also one of my first OPs here:

    Functional information defined

    That counts up changes anywhere in the genome, as long as they contribute to the fitness, and it counts up whatever successive changes occur.

    Again, are you kidding?

    So, if you have 500 different mutations of 1 AA in different proteins, each of them contributing in completely different and independent ways to fitness, you believe that you have 500 bits of complex functional information?

    Are you really saying that? I cannot believe it!

    Each of those mutations is independent, and has an independent and different functional effect. Each of them contributes to fitness, therefore is selectable. None of them contributes to the same function as the others, even if all of them contribute, independently, to fitness (which is of course a meta-function, ot which many different functions contribute).

    Do you understand why we measure functional information (yes, the same functional information that you recognized as a true and important concept) in bits?

    It’s because it is -log2 of the probability of the event.

    Do you understand? Bits are exponential.

    It is rather easy to have one random AA change which is specific to one function (there is not function, or increase of the function, without it).

    It is more difficult to have two random AA changes that are specific to one function (there is not function, or increase of the function, without both of them).

    It is empirically impossible to have 150 random AA changes that are specific to one function (there is not function, or increase of the function, without all of them).

    The sum of 150 simple mutations, each of which gives inependently an increse of “fitness”, is building no complex function.

    The idea of neo-darwinism is that a complex function (like ATP synthase) should come into existence through hundreds of specific mutations in the same structure which in the end build the function as we observe it today.

    And each of those mutations should increase fitness, and therefore be naturally selectable.

    Now, either each mutation is naturally selectable because the final function already exists: IOWs, ATP synthase appears as a simple mutation (5 AAs top) in something unrelated that already existed, and the humdreds of specific AAs that follow just “optimize” that simple initial function


    The final function (ATP synthase) just appears when hundreds of specific AAs are in place, but for some strange reason there is a ladder of simple mutations, each of them increasing fitness for different and inscrutable reasons, which for some even stranger reason just builds the exact complex sequence that will, one day, provide a completely different function, ATP synthase.

    You choose which of the two is less empirically impossible.

    Now, in both gpuccio’s and your comments, the requirement is added that all this occur in one protein, in one change, and that it be “new and original function”.

    It is not added. It was there from the beginning. Just read any single discussion I have had here in the last ten years. Or just my linked OP about functional complexity. Or anythin from me about the issue.

    That was not a part of the 500-bit criterion that gpuccio firmly declares to be the foundation of ID.

    It was, of course. It’s not my fault if you don’t understand ID theory. Not at all.

    There was supposed to be some reason why a 500 bit increase in functional information was not attainable by natural selection. Without any requirement that it involve “new and original function”.

    I have explained what new and original mean, and why they are part of the definition of functional information from the beginning. See also comment #716, to you.

    And here is what I had already said about “new” and “original”, at comment 716 of the same thread:

    Joe Felsestein at TSZ:

    (as quoted by dazz who apparently quotes Entropy: OK, there is some common descent here. 🙂 )

    Note the extra weasel-words “new original”.Because it has been shown many times that natural selection can put complex functional information into the genome, and this has been discussed here at TSZ and also at Panda’s Thumb many times.

    But add the “new original” and you have the ability to deny that any complex functional information isn’t “new” enough and/or “original” enough to qualify.

    OK, here is an explanation of why I specify “new” and “original”.

    New = functional information that did not exist before. That seems quite obvious, because we are discussing exactly that.

    Original = relating to a new function, that did not exist before. Why that? Because it’s the emergence of new functions that is really the issue here.

    What can we say about the tweaking of an existing funtion?

    As I have said many times, that’s where NS can act in some measure, because some ladder exists once a function is in place, that can gradually improve it. We have examples in the few documented cases of effextive NS: peniciliin resistance, chloroquine resistance, nylonase, and similar. But that measure is extremely limited.

    I have discussed in great detail each of them, here:

    What are the limits of Natural Selection? An interesting open discussion with Gordon Davisson

    and following discussion.

    In those cases, a ladder exists, but:

    a) It is very short, in all cases (a few aminoacids), so it contributes only a few bits to the existing function. In no way is it complex, as previously defined.

    There is a reason for that. A tweaking by simple naturally selectable steps stops very early.

    b) That short ladder can only increase the existing function, but it does not lead to a new function. Indeed, it leads away from them, because the effect of purifying selection will preserve the existing sequence linked to the existing function, and that effect will be stronger as the function increases.

    Therefore, to explain the emergence of new complex functions, which is the issue, we have, I am afraid, to add the word “new” to our reasoning, however little Joe Felsestein likes it.

    So, I hope that clarifies those two little words.

    OK, that was just to set the historical background, so that anyone can have an idea of what originated what.

    Now, I will try to consider your points in order. In next post.

  68. 68
    gpuccio says:

    Joe Felsestein (at TSZ):

    So, let’s start with the few things that we apparently agree upon.

    1) You summarize my thief scenario very correctly, and you draw very correct conclusions from it. You say:

    My reaction: This is a nice teaching example showing why, in the first scenario, there is no hope of guessing the correct key, even once in the history of the universe.

    So, you agree with the basic idea.

    Now, I will make a very simple clarification, that is probably already clear to you (but one can never know), but could possibly not be clear to others.

    In the thief example, the big safe is an example of FI whose value is approximately 500 bits. It is, however, a case where the target space has a numerosity of one. The reason for that is that the scenario is simpler, and can be immediately understood. It is, as you say yourself, “a teaching example”.

    Of course, I am not suggesting that in the case of functional proteins, or in many other settings, the target space has a numerosity of one.

    So, what is the difference when the target space is bigger?

    The answer is easy: there is absolutely no difference, because the FI is -log2 of the ratio of the target space to tyhe search space.

    So, if there is only one key that works, and the search space is 10^150, the FI is about 500 bits, like in the case of the safe in the above scenario.

    But, if the key is longer, say 200 digits, but we have a great number of keys that work, say 10^50 (which is a really big number!), the FI remains the same:

    Target space numerosity = 10^10

    Search space numerosity = 10 ^150

    Ratio = 10^-150

    FI = about 500 bits.

    Nothing has changed. And, of course, our target space now is a big target space, and it can better be considered similar to what happens with proteins, as we will see.

    I hope you agree on this basic concept. I hope you agree that FI has always been defined, in ID, as the ratio of the target space to the search space, and that I am not “adding” anything here.

    Moreover, as you clearly understand the thief scenario, I hope that you agree that FI is computed for one object or set of objects that is necessary to implement a well defined function.

    This is very important. The function (which is a particular form of specification) is the criterion that generates a binary particion in the search space. After defining explicitly the function, we can in principle say for each object in the search space if it is part of the subset that we call the target space, or not.

    If the function is explicitly defined, and there is a clear method to ascertain it as present or absent, then each object in the search space will be inside the target space or out of it.

    That’s why it is important that the function definition be explicit, clear, and that it include a threshold value to define the function as present or absent.

    Again, I hope you agree on these basic concepts.

    I will proceed from that. In next post.

  69. 69
    gpuccio says:

    Joe Felsestein (at TSZ):

    Then you ask:

    Why did gpuccio think that I objected to gpuccio’s logic for the case which has nonzero function only in a set of sequences which is 10^{-150} of all sequences? I was very clear in acknowledging that in such a case, natural selection cannot find the sequences that have nonzero function, if we start in a random sequence.

    So, that’s apparently something else we agree upon:

    “in such a case, natural selection cannot find the sequences that have nonzero function, if we start in a random sequence.”

    So, why did I think that you objected to my logic?

    Let’s go back to your comment quote in my comment #67 here.

    You say:

    1. The 500 bits criterion, which originated with Dembski, was gpuccio’s criterion for “complex”, as I demonstrated in clear quotes from gpuccio in my previous comment.

    That’s very correct.

    Then you say, and this is the crucial point:

    2. That counts up changes anywhere in the genome, as long as they contribute to the fitness, and it counts up whatever successive changes occur.

    This makes no sense. The only correct statement form the point of view of ID is the following:

    “That counts up changes in the ancestor(s) of the specific protein or proteins exhibit the function, as long as they contribute to the final function observed and as long as they can lead to the final sequence observed”.

    Now, before you start saying that I am adding things to definitions, just try to understand what I am saying and why I am saying it.

    In you original statement, you say that tghe 500 bits threshold should “count up changes anywhere in the genome, as long as they contribute to the fitness”.

    This is completely wrong.

    Let’s say that we are considering the alpha and beta chains of ATP synthase, a goof example of high FI that I often use as a “teaching example”.

    So, let’s say that we have an organism (maybe some kind of bacterium) that has not those two sequences, but in some way succeeds to survive quite well. Those two sequences, at time 0, do not exist in the world. They have not yet appeared.

    Always for the sake of simplicity, let’s say that those two sequences are exactly what is needed for the function of ATP synthase. So, let’s assume that all the rest, all the other parts of the molecule, and the proton gradient through a membrane, and so on, are already there by magic. We just need the alpha and beta chains, so that everything can start to wrok, and be selected as a powerful new way to manage energy in the cell.


    Let’s say that the FI in the two chains is 500 bits (it is, indeed, much more, but for the moment this is not the point of the discussion).

    Now, what you are apparenlty saying is that our path to those 500 bits of FI (the equivalent of the 500 digits of our big safe) should:

    “count up changes anywhere in the genome, as long as they contribute to the fitness” (of the organism, I suppose).

    So, let’s say that somewhere in the genome of the bacterium there is some random mutation that contributes to the fitmess of the organism, maybe by making it resistant to some ugly penicillin secreted by other species of bacteria. Let’s say it’s a mutation involving two AAs (I feel generous today), IOWs about 8.6 bits of FI.

    So, that change corresponds to your requirements. It:

    a) happens “anywhere in the genome”


    b) contribute to the fitness

    IOWs, this change is like opening one of the smaller safes. It gives you some money. It happens in another part of the genome (another safe).

    So, my simple question is:

    What has that change to do with the problem of finding the correct sequence for the alpha and beta chains of ATP synthase?

    The obvious answer is: absolutely nothing.

    Are we anyway nearer to find our 500 bits of FI for that function? Of course not.

    We have gained 8.6 bits of FI, there is no doubt. But they are not related in any possible way to the 500 bits that we have to find.

    That seems obvious, but it is important that we make explicit the reasons for that. There are, indeed, two different reasons:

    a) The function that has been gained (penicillin resistance) has absolutely no relationship with building the F1 component of ATP synthase by the corr3ect alpha and beta chains. IOWs, the new functional sequence that has been found, IOWs the two AAs that give the penicillin resistance, is in no way related to the sequence of the alpha and beta chain.

    To be more clear, I am not saying that those two AAs cannot be part of one of the two chains we are looking for. Maybe they are. But there is no reason that they have more probability of being part of that sequence than any other sequence of two AAs.

    IOWs, the variation that is selected here because of its contribution to fitness has nothing to do with the new function we are looking for.

    b) The change happened, as you say “anywhere in the genome”. Not in the protein that will become the alpha (or beta) chain of ATP synthase.

    So, to be more clear, let’s say that 10 different changes, each of two AAs. happen in different parts of the genome, and that we are lucky and each of them correpèsonds to some small part of the final functional sequence (it’s not so difficult to find two AA sequences in a long functional sequence involving hundreds of AAs).

    So, we have opened 10 small safes, and got some money.

    Does that help us to open the big safe?

    Not at all. Not even if all the two AAr sequences we have found can be found in the big sequence.

    Why? Because those 10 simple variation happened in 10 different places in the genome, which have no relationship with the future alpha and beta chains. (And, of course, also because 10 small sequences have not the same FI of those same 20 aminoacids in the correct position in the final sequence).

    That’s why, if the final function is implemented by one protein, all the changes have to happen in one protein. It’s not something we are “adding” to the concept of FI. It’s the essence itself of the concept.

    Only the changes happening in the same protein can contribute to walking the pathway to the 500 bits.

    But there is more:

    c) The changes that happen in the protein of interest, and that contribute to the fitness (so maybe they are selected) are not enough. They must be in some way part of the final functional sequence, or at least help in some way to find it in the search space.

    Let’s make that clear. It is in a way what I have already said at a), but I want to clarify it better.

    So, let’s say that we have a protein, let’s call it A, which is unrelated to the final functional protein (let’s call it B) but that is some way is the ancestor of it. What I am saying is that the pathway, whatever it is, starts in A. In the end, A will be thw winner.

    So, let’s say that a 3 AA change happens in A (which, of course, already has its own function), and the change is selected because it makes A more function. Maybe because the original function of A is improved. Maybe because a new function arises (for example, penicillin resistance).

    OK. So we have a change in the same protein that will become, say, the alpha chain of ATP synthase, and that change contributes to the fiteness, and is selected.

    Does that bring us nearer to the alpha cahin of ATP synthase?

    Of course not. Why? Becaus the 3 AA change, whatever it is, has been selected for a completely different function, even if it happens in the sequence that, in the end,will become the new functional protein.

    IOWs, that specific 3 AA change is not related to the functional sequence that has to be found. That is the same as saying that it has no grater probability of being related to the functional sequence than any random 3 AA sequence.

    I hope that’s clear. More in next post.

  70. 70
    gpuccio says:

    Joe Felsestein (at TSZ):

    Now, let’s go to your third statement in the original comment I quoted:

    3. Now, in both gpuccio’s and your comments, the requirement is added that all this occur in one protein, in one change, and that it be “new and original function”.

    This is supreme confusion of thought!

    As I have show in the precioyus comment, the requirement is of course that the changes must happen in one protein, or in a set of proteins (for example, in the example of ATP sunthase, they will have to happen in two different proteins, but each of them will require specific changes).

    But that’s not something I am “adding”. What in the world do you mean by that?

    The only possible meaning is that you really believe the things that I have commented upon previosuly: you really believe that random changes happening “anywhere in the genome” can contribute to find the functional sequences for thw alpha and beta chains.

    But how can you even think that? It’s completely wrong.

    If one protein succeeds in becoming the alpha chain of ATP synthase, of course the necessary changes have to happen in that protein, and not in other proteins. All proteins can be admitted to the game, of course, but each will play the game for itself, not for the others.

    And please, don’t menton recombination and similars as a magic wand: those are random events, and they do not add anything to the probabilities of the final result.

    So, I am adding nothing. The idea is that the FI is in one object (or set of objects). It is computed for that object, and it must become real in that object. Changes “anywhere in the genome” have nothing to do with that, whatever their individual contributions to a generic “fitness”.

    But there is more that adds to the confusion.

    You say that I have added the requirement that this should happen “in one change”. This is completely false. Wherever have I said such a thing?

    There is no such requirement.

    If protein A has to change to protein B by, say, 300 specific AA changes in its sequence, there is absolutely no need for it to happen “in one change”. However it happens, the probabilities are the same. You just have to adjust the minimum number of events.

    To be more clear:

    a) A is unrelated to B.

    b) We ask how likely it is for A to become B

    c) The transition requires 300 specific AA changes.

    Now, let’s compare two scenarios:

    1) A undergoes a sudden change that involves all its AA sites. That can happen in one event, for example by a frameshift mutation at the beginning of the sequence. All the AAs of A, or at least most of them, will randomly change at one time.

    2) A undergoes 300 random single AA mutations.

    Now, if we ask how different the probabilities of getting B from A are in the two scenarios, the answer is rather simple: they are very similar.

    1) is a random search. 2) is a random walk.

    Starting from an unrelated sequence, the probabilities are more or less the same.

    I know that you will say that NS enters the scenario in the second case. We will discuss that later. For the moment, let’s us acknowledge that, in the case of a random search or a random walk, the probabilities are similar, starting form an unrelated sequence, and without any intervention from NS. A framework mutation would be quicker, because it can happen in one event. The random walk requires, in this case, at least 300 events. But these differences are trivial if compared to the ration betweenfunctional sequences and the search space.

    In next post, I will comment on the “new and original”.

  71. 71
    gpuccio says:

    To all:

    Just a little rest, for the moment. I will go on as soon as possible.

  72. 72
    gpuccio says:

    Joe Felsestein (at TSZ):

    By the way, I have just seen that in your further comment to your OP you add some calrifications that can be useful to understand better your point.

    I will go on as follows: for the moment I will calrify my points in relation to your main discourse in the OP and in the previous comment that started it all. That will help clarify my position.

    After that, I will consider the further comments you added in the thread, for example:

    December 2, 2018 at 5:57 am

    December 2, 2018 at 11:56 am

    December 2, 2018 at 12:14 pm

  73. 73
    jawa says:

    bill cole,
    It’s humbling to see that my inquiring and your mediating action might have indirectly motivated such a distinguished academic personality to respond to gpuccio (finally!).

  74. 74
    jawa says:

    I’m excited by gpuccio’s response. I haven’t processed it yet, but it definitely looks like we’re up for a treat in this discussion. Glad I got a first row seat to watch it. 🙂

  75. 75
    gpuccio says:

    Joe Felsestein (at TSZ):

    Let’s go on.

    New and original. Not weasel words. Simply true concepts, implicit in the idea itself of FI and the design inference.

    First of all, I quote again my explanation in an old comment to you:

    OK, here is an explanation of why I specify “new” and “original”.

    New = functional information that did not exist before. That seems quite obvious, because we are discussing exactly that.

    Original = relating to a new function, that did not exist before. Why that? Because it’s the emergence of new functions that is really the issue here.

    I would like to discuss in more detail those points.

    Of course, if we want to infer design for an object exhibiting FI, that FI must be new. IOWs, it must not be presebt before.

    It seems obvious, but let’s clarify further.

    If I want to infer design for some complex and functional protein that appears in vertebrate, I must consider a protein that did not exist before. IOWs, the sequence of the protein must show no significant homology with other proteins that existed in pre-vertebrates.

    Why? Because of course, if a protein already existed, with great part of the necessary sequence, in pre-vertebrates, then there has been no significant addition of FI in the transition to vertebrate.

    See how “weasel” is the concept? It’s so trivial that there should be no nees even to say it.

    So, let’s anticipate the answer to the question you ask at the end of those points:

    “In the latter case who judges newness and originality of function?”

    Who judges the newness of the FI? In this case, a simple BLAST analysis will suffice.

    What if there is only a partial transition?

    That’s the case for many of the examples of information jumps in the transition to vertebrates. IOWs, a protein that already existed is re-engineered in the transition.

    In that case, nothing changes, but of course we want to infer design only for the new FI added. The procedure is the same, and a BLAST analysis allows us to do that.

    Let’s go to the “original”- It means that the function is new, and not only the optimization of an existing function.

    Of course, a strong optimization can also be a good example of design, but it is clear that the appearance of a completely new function guarantees that the process is beyond the range of NS, because we know that NS can implement modest optimizations of existing functions.

    That’s why the cases of high new FI (at the sequence level) linked to a completely new (original) function is the best scenario to infer design from FI.

    So again, to the question:

    “In the latter case who judges newness and originality of function?”

    It’s easy. we can just give a look at the 2000 protein superfamilies that are well known. They are groupings of proteins that are separated, by definition, at the sequence level, at the strucutre level, and at the function level. Not so difficult, after all.

    So, let’s end with the points of your original comment:

    That was not a part of the 500-bit criterion that gpuccio firmly declares to be the foundation of ID.

    This is not true. As I have shown, all the things that you declare to be “additions” are simply clarifications of the obvious implications of the definition of FI and of its role in design detection.

    The 5th point is not so clear:

    There was supposed to be some reason why a 500 bit increase in functional information was not attainable by natural selection. Without any requirement that it involve “new and original function”.

    Not clear what you mean. However, the 500 bit threshold of course is related to RV. I will discuss the connection with NS later in this discussion.

    Then your final question:

    So what is the “foundational” requirement? A 500-bit increase in functional information, taken over multiple changes, possibly throughout the genome? Or attainment of a “new and original function”? In the latter case who judges newness and originality of function?

    This is just confusion. The requirement for a design inference is a too bit increase in functional information in one object (be it a protein or a set of proteins) that implements one complex function.

    It is an increase in functional information, therefore the 500 bits must be new information. And considering a new and original function helps exclude mere optimizations of an existing function, which are sometimes in the range of NS, as I will discuss later.

    Changes can be sudden or multiple: as discussed,there is no difference. But certainly they cannot be “throughout the genome”. They must be in the protein (or set of protein) that implements the specific function. Of course.

    Regarding the final question about “who judges”, I have already answered.

    More in next post.

  76. 76
    gpuccio says:

    Joe Felsestein (at TSZ):

    Now, let’s go to one of the key statements in your new OP about my thief scenario. You say:

    Functional information was defined by Jack Szostak (2003) and by Szostak, Hazen, and Carothers (2007). It assumes that we have a set of molecular sequences (for example, the coding sequence of a single protein, or its amino acid sequences), and with each of them is associated a number, the function. For example, its ability to synthesize ATP if it is an ATP synthase.

    In this original definition of FI, there is no assumption that almost all of the sequences have function zero. Given that, there is no way to rule out the possibility that there are paths from many parts of the sequence space that lead to higher and higher function. And given that, we cannot eliminate the possibility that natural selection and mutation could follow such a path to arrive at the function that we observe in nature.

    I will try to be very clear:

    1) As already discussed in comment #68, the taget space needs not be 1, and it needs not be samll. FI is always computed by the ratio between target space and search space.

    2) That said, there is absolutely no difference between my definition and the definitions of Szostak and others, as far as I can see. You soeak of an assumption “that almost all of the sequences have function zero”.

    But there is no such assumption. In my definition, the function must be explicitly defined so that we can assess it as present or absent in each object. That’s because we need a binary variable: FI present or absent, so that we can generate the binary partition in the search space that will allow the measurement of FI.

    So, there is no assumption that “almost all of the sequences have function zero”. We only define a function that makes sense in a biological context, and a minimum level of it that is significant in that context.

    Indeed, the neo-darwinist algorithm helps a lot in defining the function and its level. What we need is a function that is naturally selectable, so it must contribute to fitness, and contribute enough to be selectable.

    That means that functions that do not contribute to fitness, or who may be present at low levels, maybe detectable in the lab, but certainly not relevant in a real biologcial context, are not of any interest for the discussion.

    So, let’s go again to the example of the alpha and beta chains of ATP synthase. What is the functional definition?

    Well, it could simply be: two proteins that can build the F1 structure of the enzyme, so that a transmembrane gradient of protons can be transformed into ATP molecules with a minimum efficiency (which can be set by a biochemist, even at a very low level).

    If that is not present, the two chains cannot be of any utility in the cellular context. The function is simply not there, and there is nothing that can be selected.

    Of course you will say that those chains could be selected for other purposes, maybe as components of a different network, and then coopted (what a weasel word, that one!) to the ATP synthase. But nobody who knows how complex, specific and sophisticated is the structure of the F1 structure could ever believe that. And of course there is no fact that supports that kind of pathway for such a complex and specific structure: just imagination and wishful thinking.

    So, to sum it up: there is no need that sequence have zero function: but we are only interested to sequences that have a detectable function which is relevant toi the context. In general, it should be a naturally selectable function, if it has to be of any help to the neo-darwinist model.

    We can discuss where to put the threshold to assess the function, but there is no doubt that Szostak, or you, or any other darwinist, have to put somewhere the threshold between naturally selectable objects and non selectable objects. So, there is no difference between my definition and the others.

    More in next post.

  77. 77
    gpuccio says:

    Joe Felsestein (at TSZ):

    You say:

    Given that, there is no way to rule out the possibility that there are paths from many parts of the sequence space that lead to higher and higher function. And given that, we cannot eliminate the possibility that natural selection and mutation could follow such a path to arrive at the function that we observe in nature.

    Emphasis mine.

    and then, in your further comment:

    December 2, 2018 at 12:14 pm

    you say:

    My interest is not in the islands-of-function argument but in gpuccio’s repeated assertion that the 500-bits-of-FI rule is a general one for detecting Design. Which in effect asserts that fitness surfaces that have paths of gradually-increasing fitness leading to the “island” are impossible. Not just rare, impossible. Impossible for what reason? None, except that gpuccio restricts the term CFI to cases where such paths are impossible.

    Again, emphasis mine.

    So, let’s discuss briefly this question of “possible” and “impossible”.

    Never in my discussion have I argued that selectable pathways to complex FI are impossible. I have always affirmed, with full conviction, that they do not exist. And that we can infer that non existence from the complete absence both of rational reasons and empirical facts that support their existence.

    There is a big difference between the two things.

    All my discussions are empirical. They are based on facts and reasonable inferences. Because I do believe that that’s the way to do empirical science.

    IOWs, we are not discussing a mathemathical theorem here, nor a logical theorem. We are discussing theories aboyìut observed facts.

    The desing inference is not a theorem: it is an inference. We look for the best credible explanation of observed facts.

    You know as well as I do that no gradual naturally selectable pathway to any protein exhibiting complex functional information has ever been observed, shown, or even hygpothesized with any detial or credibility.

    That’s true of proteins, but it is equally true of software, of language, and of complex machines in general.

    Because complex srtucutres implement their function because they are complex: a high number of specific, independent bits must be set to achieve the complex function, even at a minimum level.

    A watch does not work if it is not already a watch: maybe optimizable, but a watch it has to be.

    An ordering algorithm does not work if you son’t set the correct bits in its code. You cant just start with four or eight random bits, and hope that they will order complex inputs, and then be optimized until you have a working program.

    Simple words cannot build a complex paragraph with a specific meaning, starting only with one or two words.

    Complexity is not the sum of many simple things. There is structure in complexity, and strucutre requires the coordination and organization of many bits in one working result, and the probabilites against that result grow exponentially with each additional bit that is required.

    That’s why watches, long meaningful paragraphs, complex software and complex functional proteins are always designed.

    Again, this is not a theorem. It is not impossible that a watch (I will stick to the wacth, no need for a Boeing) comes out of a tornado in a junkyard. It could happen. But it will simply not happen.

    Those things are empirically impossible, not logically impossible

    Very simply, if I build a linear regression model between two conitnuous variables, and I find a p value of 10e-15, I refuse the null hypothesis that the two variables are independent.

    Is that hypothesis inpossible? Logically impossible?

    Not at all. It could be. There is a probability against 10^15 that this may be true.

    And yet, no scientist would ever stick to the explanation that the two variables are independent. Not with that level of improbability.

    Because that’s how empirical science is made. We are not trying to reject what is impossible. We are looking for the best credible explanation. But we cannot accept models that are based only on faith in the extremely unlikely.

    In the case of FI, in the case of proteins, we have values that are much higher (and therefore probabilities that are much lower) of that 10e-15.

    The existence of gradual selectable pathways to complex functional proteins is supported exactly by nothing. Zero reasons, zero facts. If you have not the blind faith that “it must have happened, because we see those complex things, and they cannot be designed”, then there is absolutely no reason in the universe to accept the false model of neo-darwinism.

    OK, more in next post, but tomorrow, I suppose! 🙂

  78. 78
    gpuccio says:

    Joe Felsestein (at TSZ):

    Just a last thing before going to sleep. I have read your comment

    December 2, 2018 at 11:47 pm

    Again you ask if I am using my definition or Szostak’s.

    Well, I am certainly using mine. But I believe that it is not different from Szostak’s.

    Here is Szostak’s definition, quoted from the abstract of his paper about FI:

    Accordingly, we define “functional information,” I(Ex), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, Ex (e.g., the RNA–GTP binding energy), I(Ex) = -log2[F(Ex)], where F(Ex) is the fraction of all possible configurations of the system that possess a degree of function >= Ex.

    Could you please explain where is the difference? He gives the concept of an explicit definition of a function and of its minimal degree in a system, and of the binary partition generated by that definition in the space of possible configuration, and of using the rate of the targer space to the search space to measure FI.

    Where is the difference?

  79. 79
    PeterA says:

    What a discussion between GP and JF. I almost missed it.

  80. 80
    gpuccio says:

    To all:

    While I am going on with answers to Joe felsestein, I would like to also continue proposing papers about the issues presented in this OP.

    We have already said that the ECM is a highly dynamic structure. It is continuously remodelled by the cells it hosts.

    So, here is a paper about that aspect:

    Remodelling the extracellular matrix in development and disease.


    The extracellular matrix (ECM) is a highly dynamic structure that is present in all tissues and continuously undergoes controlled remodelling. This process involves quantitative and qualitative changes in the ECM, mediated by specific enzymes that are responsible for ECM degradation, such as metalloproteinases. The ECM interacts with cells to regulate diverse functions, including proliferation, migration and differentiation. ECM remodelling is crucial for regulating the morphogenesis of the intestine and lungs, as well as of the mammary and submandibular glands. Dysregulation of ECM composition, structure, stiffness and abundance contributes to several pathological conditions, such as fibrosis and invasive cancer. A better understanding of how the ECM regulates organ structure and function and of how ECM remodelling affects disease progression will contribute to the development of new therapeutics.

    This is a very good review about the enzymes that remodel ECM, like the complex protein families of Matrix metalloproteinases (see Fig. 1), Meprins, and others.

    There are also very good and detailed sections about:

    ECM dynamics in intestinal development

    ECM remodelling in branching morphogenesis

    Aberrant ECM remodelling in disease

    This is particularly interesting about stem cells:

    In addition, the role of the ECM in regulating the stem cell niche needs to be more extensively explored. For example, a single mammary stem cell can reproduce an entire organ when transplanted into a cleared fat pad. This suggests the presence of a niche in the mammary gland that contains all the signals required to programme stem cells. The ECM has a crucial role in the release of the niche signals that are essential for stem cell fate133, which probably has implication for diseases such as cancer, in which cancer stem cells might also be using such ECM signals to promote their survival and growth. A better understanding of the niche signals that regulate stem cell behaviour might also have therapeutic potential in regenerative medicine.

    The problem of stem cell niches is very exciting. There has always been the certainty that ECM niches are the true environment that controls the functions of adult stem cells, and now we are finally finding some details about that! 🙂

  81. 81
    gpuccio says:

    To all:

    In the OP I say:

    “How does the cell interact with the ECM?

    There are many different ways, indeed. But we will focus here on the main and best known: the system of integrins.”

    OK, now it’s probably the time to mention another system that contributes to the cell-ECM communication: the so called mechanosensitive channels.

    A good example of that is the transient receptor potential melastatin 7 (TRPM7), a mechanosensitive
    plasma membrane calcium channel.

    In brief, it is a calcium channes which is regulated by mechanical stimuli. In response to those stimuli, membrane TRPM7 opens and conducts Ca2+ influx from the extracellular space. Of course, calcium is a key cell messenger, and it can regulate many downstrem signalings.

    This mechanism seems to have an important role in stem cells. Here is an interesting review:

    The mechanosensor of mesenchymal stem cells: mechanosensitive channel or cytoskeleton?

    Mesenchymal stem cells (MSCs) are multipotent adult stem cells. MSCs and their potential for use in regenerative medicine have been investigated extensively. Recently, the mechanisms by which MSCs detect mechanical stimuli have been described in detail. As in other cell types, both mechanosensitive channels, such as transient receptor potential melastatin 7 (TRPM7), and the cytoskeleton, including actin and actomyosin, have been implicated in mechanosensation in MSCs. This review will focus on discussing the precise role of TRPM7 and the cytoskeleton in mechanosensation in MSCs

    And here is another one, very recent:

    Mechanosensitive channels and their functions in stem cell differentiation

    Stem cells continuously perceive and respond to various environmental signals during development, tissue homeostasis, and pathological conditions. Mechanical force, one of the fundamental signals in the physical world, plays a vital role in the regulation of multiple functions of stem cells. The importance of cell adhesion to the extracellular matrix (ECM), cell-cell junctions, and a mechanoresponsive cell cytoskeleton has been under intensive study in the fields of stem cell biology and mechanobiology. However, the involvement of mechanosensitive (MS) ion channels in the mechanical regulation of stem cell activity has just begun to be realized. Here, we review the diversity and importance of mechanosensitive channels (MSCs), and discuss recently discovered functions of MSCs in stem cell regulation, especially in the determination of cell fate.

    As says my friend UB, it just never stops… 🙂

  82. 82
    gpuccio says:

    To all:

    By the way, let’s just mention that TRPM7 is one of my beloved proteins that exhibit an impressing information jump in the transition to vertebrates.

    It is 1865 AAs long (in humans), and it shows an amazing information jump in human conserved information from pre-vertebrates to vertebrates:

    0.9753351 bits per aminoacid site

    1819 bits

    reaching, already in cartilaginous fishes, the following impressing levels of homology with the human protein:

    2900 bits

    1.55496 bits per aminoacid site

    1430 identities

    1593 positives

  83. 83
    jawa says:

    TRPM7 Has an impressive CV indeed.
    Those numbers demand serious explanations.
    Perhaps distinguished academic personalities like professor JF at TSZ could tell us how that happened?
    Obviously after he finishes his interesting discussion with gpuccio on the power of RV+NS.
    BTW, the distinguished professor AH is welcome to give a hand to his colleague JF too.

  84. 84
    jawa says:

    “The problem of stem cell niches is very exciting. There has always been the certainty that ECM niches are the true environment that controls the functions of adult stem cells, and now we are finally finding some details about that!”

    How are those niches spatiotemporally established ?

  85. 85
    ET says:

    Too funny- all the TSZ ilk can do is whine like little children who were grounded.

    Has any one of them presented any evidence that natural selection can produce what gpuccio shows the math says was intelligently designed? Absolutely NOT! But hey they are so sure that he is wrong. Unfortunately they cannot demonstrate such a thing. But I am sure that will not deter them from their puerile insults and childish taunts.

  86. 86
    jawa says:

    Let’s wait and see. 🙂

  87. 87
    OldAndrew says:

    all the TSZ ilk can do is whine like little children who were grounded.

    This does not encourage polite discussion. No one is whining, not like a child or otherwise. If anything I feel like a child listening to the adults talk.

  88. 88
    gpuccio says:

    Joe felsestein (at TSZ):

    So, let’s go on.

    You say:

    How gpuccio eliminates natural selection

    Simply by changing the definition of Functional Information for gpuccio’s Complex Functional Information. And only calling it that when the amount of Function is zero for all sequences outside of the target set. That makes gpuccio’s definition of Complex Functional Information very different from Szostak’s and Hagen’s.

    But, as shown at #78, there is no difference between my definition and Szostak’s. I have changed nothing.

    We both set a threshold to assess the function as present or absent.

    Even if you want to think that the function is not zero outside the target space (but in most cases it will be practically zero for complex functions), it is by definition below the threshold that we define as “relevant”.

    For all relevant aspects regarding the neo-darwinist algorithm, it must present at least at a level that makes it naturally selectable. That’s no good news for your side, because I think that we could easily show that many “local” functions, while perfectly detectable in the lab at low levels, are not naturally selectable even at high levels, at least not as isolated functions.

    A good example is the ATP binding protein engineered by Szostak in his famous paper.

    The original protein, the only one that was really a random result, had a very low affinity to ATP, enough to separfate the protein on ATP presenting beads, but trivial for any other purpose.

    But even the artificially engineered protein, with its high level of ATP binding, was completely useless, indeed deleterious, in a biological context, its only ability being to deprive the environment of ATP.

    So, naturally selecatble functions are really a tiny subset of all possible functions that can be defined.

    The final point is: if we want to reason about the neo-darwinian algorithm, we are interested only in functions that can be explicitly defined, with an explicit level of function, and such that the defined function is naturally selectable. That allows togenerate an appropriate binary partition and an appropriate target space for which to compute FI and, if applicable, infer design.

    You also say:

    Gpuccio’s restricted definition rules out all cases where there might be a path among sequences leading to the target sequences, a path which has function rising continually along that path.

    Not at all. The path, if it exists, must start where the function already exists at a detectable, relevant, naturally selectable level. Anything else is not visible by NS, and therefore has no role in changing the probability barriers.

    So, using a correct definition for the function, nothing is ruled out.

    More in next post.

  89. 89
    gpuccio says:


    Your contribution is appreciated! Welcome to the discussion. 🙂

  90. 90
    ET says:


    This does not encourage polite discussion. No one is whining, not like a child or otherwise.

    Clearly you have not read what they are saying over on TSZ.

    All I am doing is reporting what they are doing over on TSZ. If you don’t believe me go there and read it for yourself.

  91. 91
    ET says:

    DNA Jock wrote the following about gpuccio:

    His “argument” rests on a series of misconceptions. He is clueless.

    That looks like whining to me.

    Then there is the venomous loser “entropy” who is just another willfully ignorant person who thinks its ignorance is an actual argument.

    Again, clearly Old Andrew has not read what the TSZ ilk have written.

  92. 92
    gpuccio says:

    Joe felsestein (at TSZ):

    Now, I would like to comment on what you say in comment:

    December 2, 2018 at 5:57 am

    You say:

    I should add a reply to another assertion of error that gpuccio has made: I had argued that when the function was fitness itself, changes in different parts of a genome could occur, each changing fitness relatively independently of the others, so that there is a path upwards on the fitness surface. gpuccio declared that this was wrong because function necessarily involves the properties of one local region of the genome.

    No, it doesn’t, in the case where function is fitness.

    OK, this would have helped clarify your thoughts.

    So, now it is clear that you statement about changes occurring “anywhere in the genome”, and “contributing to fitness” was meant only when function is defined as fitness (or better, an increase in fitness), and not in general to the concept of FI and its definition. Moreover, you made that statement at point 2) of the original comment that I quoted at #67, and it is referring to “the 500 bits criterion”.

    Let’s summarize those points:

    a) You say that changes that happen anywhere in the genome and that contribute to fitness count, and you say that in reference to my 500 bit threshold to infer design from FI.

    b) Then you clarify that such a statement is true only if fucntion is defined as fitenss (or, I would say, an increase in fitness), and not in the general case of FI. OK, I can accept that.

    c) But is that even true?

    No, it is not. Or at least, it is not true that those changes count in relation to the 500 bit threshold. Even if we define function as an increase in fitness.

    Let’s see why.

    Let’s say that we define our function, to be evaluated in the object, as:

    “Giving a detectable increase in fitness”

    To be more precise, we can add that the increase must be enough to be visible to NS, IOWs that we can show, at least in principle, that it confers a reproductive advantage in some real biological context. Measuring that level of course could not be easy, but that’s not our concern in this discussion. Let’s assume we can do that.

    So, can we define function in that way?

    Of course we can. In my definition of FI, I state very clearly that any functional definition can be accepted, provided that it is explicit, objective, and that it can be measure to assess if it is present or not in any object.

    So, the definition of function as something that increases fitness is perfectly acceptable.

    So, what is the problem with that definition?

    There is really no problem. But it is certainly true that it defines a function that is rather simple.


    Well, we know well that in many biological contextx, for example in bacteria, there are a few, maybe many, single aminoacid substitutions that can increase fiteness, at least in some environment.

    Again, we can consider penicillin resistance of the simple form. We know that it can start with one mutation, even if it can be optimized by a few others. But the initial mutation already confers resistance.

    In the case of choloroquin resistance, a couple of mutations is necessary.

    Nylonase probably arises with a couple of mutations in some existing penicillinase.

    And so on.

    I have discussed those well known examples in some detail in my OP:

    What are the limits of Natural Selection? An interesting open discussion with Gordon Davisson

    Now, let’s say that one AAs in one protein, let’s call it X, can confer penicillin resistance if it changes to some specific new AA, let’s call it Y.

    Given the generic mutation rate in bacteria, we can say that the probability of one mutation per site per cell generation is about 10^-10. However, for each mutation in that AA site the probability to get the right AA mutation is about 0.05 (1/20).

    Let’s say that we have some probabilistic resources available, for example enough cell generations to mutate each single AA site 1000 times.

    The binomial distribution tells us what are the probabilities to have a success in 1000 attempts, if the probability of success is 0.05.

    The probability of getting a least one success is: practically 1.

    So, in this context, it would be very easy to get 1 success. It would be almost certain.

    That’s because the FI linked to 1 specific AA change is about 4.3 bits.

    So, if there is even only 1 AA site in the bacterial genome that can give an increase in fitness, when we define our function as said:

    “Giving a detectable increase in fitness”

    its FI is about 4.3 bits. It is a very simple function.

    With the hypothetical numners given above, what is the probability of having 50 independent events, each giving an increase in fitness, anywhere in the genome?

    Again, the binomial distribution tells us that the probability of having at least 50 successes with the numbers we have given is:


    IOWs, it is extremely likely to get 50 independent successes, each with probability 0.05, of we can try 1000 times.

    That happens because the probability of success is high if compared to the probabilistic resources.

    This situation is comparable to the many safes with very simple keys: it’s easy to solve them all in a short time and in a limited number of attempts.

    But waht happens if, with the same numbers (1000 attempts) we consider the probability of a specific sequence of 50 AAs?

    Now, the probability of success in one attempt is:

    20^50 = 8.881784e-66

    and the FI is:

    about 216 bits

    And the binomial distribution tells us that the probability of getting at least one success in 1000 attempts is:


    That happens because here the probability of success is much lower than the probabilistic resources.

    So, in that scenario, 50 independent specific mutations giving an increase in fitness can be achieved (if they are available in the genome), with probabilistic resources that change each AAs about 1000 times, with a probability of 0.5202589.

    But a single function that requires 50 specific AA values to increase fiteness has a probability, with the same probabilistic resources, of 8.881784e-63.

    I believe that this is a clear demonstration that:

    “50 small variations that happen anywhere in the genome and that can independently increase fitness”

    is not the same thing as:

    “one single big mutation that can increase fitness by a specific sequence of 50 AAs, and only in that way”

    The first scenario is simply the sum of 50 simple variations, each of them of about 4.3 bits. And, as we have seen, given enough probabilistic resources, it is a very likely event. IOWs, it is a simple scenario.

    The second scenario is about one single complex function, which has a FI of about 216 bits. With the same probabilistic resources, this scenario is extremely more unlikely. It is much more complex.

    The first scenario is the many smaller safes.

    The second scenario is the one big safe.

    (Beware, the binomial distribution is tricky. A key factor is the relationship between probability of success and number of attempts.

    If the probability of success is low vs the number of attempts, increasing the number of successes will make the result exceedingly unlikely in all cases.)

  93. 93
    gpuccio says:


    For the moment, I will consider only JF’s comments.

    You are right that many of the commenters at TSZ don’t really deserve a serious attention. Not all of them, however.

    But my resources are limited, anyway. So, let’s stick to JF for the moment.

  94. 94
    gpuccio says:


    By the way, I see that DNA_Jock is contributing. As usual, he is not a fool, but he is just repeating things that we have discussed in great detail, and about which we have no agreement.

    Again, i will stick to JF for the moment.

  95. 95
    ET says:

    Good point. I will be quiet when it comes to the other TSZ ilk.

  96. 96
    ET says:

    OK the following links are to the Szostak and Szostak et al. papers on functional information :

    Molecular Messages 2003

    Functional information and the emergence of biocomplexity 2007

    The following quote is from the first paper:

    The challenge in determining experimentally the relationship between functional information and activity is the extreme rarity of functional sequences in populations of random sequences (typically 10110 to 10115 for aptamers and ribozymes isolated from random RNA pools).

    Strange how IDists get roasted for saying such a thing and yet no one is trying to roast JS for saying it.

  97. 97
    ET says:

    My goodness, now the TSZ ilk are complaining about Szostak’s definition of functional information.

    I know why they just don’t demonstrate that natural selection can produce it-> they cannot.

  98. 98
    Mung says:

    FI – that which Natural Selection produces. Q.E.D.

  99. 99
    gpuccio says:

    To all:

    Let’s just compare what TSZ is saying to what TSZ is saying:


    I think he is using the Szostak – Hazen definition, but is unable to perceive of function as continuous. Like DNA_Jock noted, he takes traits to be binary “it works”/ “it is broken” characters.

    Joe Felsestein:

    Let’s look at Jack Szostak’s 2003 paper that first defined FI.

    A new measure of information — functional information — is required to account for all possible sequences that could potentially carry out an equivalent biochemical function, independent of the structure or mechanism used. By analogy with classical information, functional information is simply -log_2 of the probability that a random sequence will encode a molecule with greater than any given degree of function. For RNA sequences of length n, that fraction could vary from 4^{-n} if only a single sequence is active, to 1 if all sequences are active.

    The illustration is a cone, with a plane passing through it partway up. The fraction being discussed is the fraction of all sequences above the plane.

    Imagine a pile of DNA, RNA or protein molecules of all possible sequences, sorted by activity with the most active at the top. A horizontal plane through the pile indicates a given level of activity; as this rises, fewer sequences remain above it. The functional information required to specify that activity is -log_2 of the fraction of sequences above the plane.

    I must say that I am really confused! 🙂

  100. 100
    ET says:

    My apologies but I would like to respond to this bit from DNA Jock:

    I agree that it is perfectly valid to treat the whole genome as the sequence space, and organism fitness as the function.

    That means you are starting with the very thing that needs an explanation

    I have been walking through the changes in FI as a gene gets duplicated, then one copy acquires a point mutation that (say) changes the enzyme’s pH optimum.

    A) You have to account for that gene- you know the one that can change it’s PH optimum via a point mutation

    B) Read “Not By Chance” as there isn’t any justification with calling gene duplication an accident, error or mistake

    C) The newly duplicated gene would need a new binding site or else it is useless. With Lenski’s LTEE the newly duplicated gene was put under the control of a different promoter- one that just happened to be OK with O2 (meaning it was active in the presence of O2)

  101. 101
    ET says:

    Hey Mung- If “Entropy” was an IDist he/ she would have been banned from TSZ long ago because of its language and tone.

    Why the double standard?

  102. 102
    gpuccio says:

    To all:

    Corneel is right about one thing: I am using my definition, but it is exactly the same as Szostak’s, so I am using Szostaks.

    The problem is that Corneel seems not to realize that I am using szostak’s definition, and that it’s Szostak’s definition, like mine, that uses a threshold to transform the continuous variable into a binary variable (see the cone in Joe Felsestein’s quote).

    What Corneelss says makes no sense at all.

    I do see the variable as continuous. I also give it a specific name as continuous: FI.

    And then I transform it into a binary variable: present or absent. exactly as Szostak does.

    Moreover, let’s clarify that a continuous variable starts at some minimum level. OK, mathematically it can be conceived as tending to zero, but that is not an useful model in most real contexts.

    Again, let’s consider Szostak’s paper about the ATP binding protein.

    Is it a continuous function?

    Yes, it is. That’s why Szostak succeeds in optimizing it by artificial selection.

    What is the initial state of the function?

    It is the weak ATP binding found in a few sequences in the random library. To be precise, he finds ATP binding sequences in a random library of 6 x 10^12 sequences. He concludes:

    “We therefore estimate that roughly 1 in 10^11 of all random-sequence proteins have ATP-binding activity comparable to the proteins isolated in this study.”

    How is this ATP binding measured? Just by beads exhibiting ATP. This is a very sensitive lab procedure, so we can assume that it selects for a weak binding.

    So, in the random library we have, in average, one sequence that weakly binds ATP, amd all the rest (10^11 -1) that do not.

    Is this a binary partition? Yes, it is.

    The function here is implicitly defined as binding ATP at least as strongly as is needed for a protein to be selected by a lab procedure such as above described.

    So, we have 1 sequence exhibiting the function against almost 10^11 for which the function, as defined, is absent.

    We could say zero, for all practical purposes, but let’s say: absent as defined.

    Now, is that function, as defined, naturally selectable? Of course not, even if Szostak did not even try to select for it in a natural context. He probablt already know what the result would have been.

    So, he used rounds of artificail mutation and artificial selection to optimize the ATP binding function. With very good success.

    His final protein has much higher ATP binding. That shows that artificial selection has good power to optimize a function if there is a continuous pathway for that function. I have discussed these topics in detail in this OP:

    Natural Selection vs Artificial Selection

    So, was the final protein naturally selectable? Absolutely not, according to the only paper that I am aware of that tried to verify it. The protein not only was not naturally selectable, it was indeed deleterious. As anyone could have expected, because it is rather obvious that a protein that can only bind ATP, and strongly, is a real danger for any biological environment, just like a thief who is robbing your money (OK, I must really like thieves, it seems! 🙂 )

    In all this reasoning, FI is defined according to artificial functions that cannot reasonably be natrually selected.

    To test if the neo-darwininian paradigm can generate complex functional information, we should define some function that can really be selected in some real biological environment.

    Again I would suggest something like the alpha and beta chains of ATP synthase. Let’s see if we can find in a random library those two chains, or two chains with their function, defined as the ability to make ATP synthase working, at least at a minimum level that could be naturally selected.

    I am not holding my breath, but that is exactly what would show that the highly specific sequence that allos the functionality of those two chains, as we can observe it today, can be easily found by RV.

    And what about NS? But of course NS has no role until the ATP synthase starts to work.

    Do you believe in cooption? OK, jus show how it would work in this specific case. Suggest something real, something verifiable, not just vague and bad idea like cooption. Answer simple questions, like: what is coopted, and why?

    So, to sum it up:

    a) I am just as aware that function is a continuous variable as Szostak and Corneel are.

    b) Even a continuous function has lots of objects that have zero function for all practical purposes: see the almost 10^11 sequences that did not bind ATP in Szostak’s experiment.

    c) In most cases, a function that is present at low levels is irrelevant in ant biological context. In many cases, even a strong function is irrelevant.

    d) For any discussion about neo-darwinism, only functions that can be well measured and can generate a detectable increase in fitness are relevant. IOWs, naturally selectable functions.

    e) If a function is naturally selectable but is also complex, NS will act only when the complex FI linked to the function is already there. Not before. Up to that point, only RV is in the game. (And, of course, imaginary cooption, which, even if it existed, would be random in relation to the function to be found, because a priori anything can be coopted for something, but there is no reason that this should favor a specific new function).

  103. 103
    gpuccio says:

    ET (and DNA_jock):

    But I agree, too, that:

    “it is perfectly valid to treat the whole genome as the sequence space, and organism fitness as the function.”

    Of course it’s perfectly valid. That’s exactly what I have discussed at my comment #92.

    If we define the whole genome as the sequence space, and an increase in organism fitness as the function, then “fitness increase” is a very simple function. There are indeed a few simple variations that can independently increase the function as defined. And so?

    Again, that’s not a complex function. Not even considering a number of such events. See my computation at comment #92.

    This has nothing to do with complex functions, and with the 500 bits threshold. This is exactly the error that was there just from the beginning in Joe Felsestein’s statements.

  104. 104
    gpuccio says:

    Joe Felsestein (at TSZ):

    You say:

    No sign there of any lower limit — the probability of response could be nonzero for all sequences.

    But again you seem not to understand the point.

    We set a threshold, and generate a binary partition. I have never said that there must ne absolutely no function under the threshold. In many cases, the function will be practically zero. In others, it will be very low. It depends on the function and on the system.

    But we set a threshold because we are interested in at least that level of function. And we consider the function, as defined, present above the threshold and absent below the threshold.

    That’s exactly what Szostak does. Again, there is no difference, and my definition is exactly the same as Szostak’s.

    So, why do we need a threshold?

    Simply because a function below that threshold would be irrelevant in the system.

    In particular, as I have said many times, and I hope you will notice sooner or later, when discussing the neo-darwinian algorithm the function must be at least as strong as to be naturally selectable.

    Can you deny that?

    So that is a very natural threshold. And it has a very specific meaning for our discussion.

    Again, if the function is complex, id really will not appear if the nits are not ther, at least most of them. A softwrae will not start working as a spreadsheet under a certain level of bit complexity. Under that level, the function simply is not there, and there is no spreadsheet. Zero function.

    For many biological functions, the difference between zero observable function and a clearly detectable function is rather abrupt. Of course the affinity of an active site with a substarte is a more gradual variable. Anyway, in the end, there are always variants that will not exhibit the function, or not enough to be naturally selected. Those that exhibit the function enough to be naturally selected are the target space.

    The 500 bits threshold is just a higher threshold of complexity (not to be confused with the threshold of functional level, it is another thing of course).

    We have seen (see #92) that the probability of success in a binomial distribution depends crucially on the difference between the probability in a single attempt ad the number of available attamepts.

    A FI of 500 bits is by far beyond any probabilistic resources in the known universe. That’s because it is a natural higher threshold for FI, to infer design.

    I really don’t understand why all of you at TSZ seem not to understand that simple concept. 500 bits simply allow the event to be empirically impossible, whatever the available probabilistic resources of the system. In most cases, a much lower threshold is more than enough to infer design. 500 bits is simply an appropriate and safe value in the very general case.

    Your argument that many simple variations anywhere in the genome that contribute to fitness can gradually explain 500 bits of functional information is simply wrong, as I have clearly shown in all these comments, in particular #92.

    That system of many simple variations contributing independently to a generic fitness (but of course in many different and unrelated ways) has nothing to do with a 500 bit function: it is a simple system, with low FI. It is the same as the many small safes. It had nothing to do with finding the key to the big safe.

    Therefore your reasoning is wrong.

  105. 105
    ET says:

    I find it very telling that our opponents don’t feel they have any burden to demonstrate anything that supports the claims of their position. That very thing exposes their anti-science agenda.

    And if, as Joe Felsenstein says, that evolution starts with the existence of biological organisms then science is OK with Special Creation as the origins are unimportant and only the subsequent evolution matters.

  106. 106
    gpuccio says:

    To all:

    An interesting aspect of Focal Adhesions is that they are dissolved during mitosis. So, it was not clear how cells could keep their morphology and anchorage to ECM during mitosis.

    But recently, a new type of FAs has been discovered. They are called “reticular adhesions”, and they are somewhat atypical because:

    a) They are mediated by a specific integrin molecule, alpha v beta 5.

    b) They lack the usual components of the adhesome, including talin and the actin components.

    c) They persist during mitosis, ensuring the attachment of the cell to the ECM during that phase.

    Here is the recent paper that describes this special kind of FAs:

    Reticular adhesions are a distinct class of cell-matrix adhesions that mediate attachment during mitosis


    Adhesion to the extracellular matrix persists during mitosis in most cell types. However, while classical adhesion complexes, such as focal adhesions, do and must disassemble to enable mitotic rounding, the mechanisms of residual mitotic cell–extracellular matrix adhesion remain undefined. Here, we identify ‘reticular adhesions’, a class of adhesion complex that is mediated by integrin alpha v beta 5, formed during interphase, and preserved at cell–extracellular matrix attachment sites throughout cell division. Consistent with this role, integrin beta 5 depletion perturbs mitosis and disrupts spatial memory transmission between cell generations. Reticular adhesions are morphologically and dynamically distinct from classical focal adhesions. Mass spectrometry defines their unique composition, enriched in phosphatidylinositol-4,5-bisphosphate (PtdIns(4,5)P2)-binding proteins but lacking virtually all consensus adhesome components. Indeed, reticular adhesions are promoted by PtdIns(4,5)P2, and form independently of talin and F-actin. The distinct characteristics of reticular adhesions provide a solution to the problem of maintaining cell–extracellular matrix attachment during mitotic rounding and division.

  107. 107
    ET says:

    Right? If we exclude the clearly Supernatural origins related to Special Creation, then the Creation model of evolution, which has the extant species evolving via descent with modification from the starting populations, should be accepted.

    The only differences (between mainstream evolution and the Creation model) are those starting populations and the mechanisms- are they telic, non-telic or a mix?

  108. 108
    gpuccio says:


    I don’t believe that science can explain the evolution of species without a design paradigm, not any more than it can explain OOL.

    For me, the two aspects are one and the same. They both require a design approach.

  109. 109
    ET says:

    Agreed. The two are directly connected. How living organisms arose directly affects how it evolved. They cannot be separated although people try, as Joe Felsenstein is doing.

    To me it is a given that because organisms were intelligently designed they were so designed with the ability to adapt and evolve.

    (The flip side is if the opposite is true then Mayr is right and teleology is not required- meaning if living organisms did just spontaneously arise from, say, those alkaline vents (as Nick Lane imagines) then ID is a non-starter and Darwin, Mayr, Dawkins, et al., rule the day. But that is just an impossible scenario if there ever was one so it is the non-starter.)

  110. 110
    gpuccio says:

    Joe Felsestein (at TSZ):

    In a more recent comment gpuccio finally acknowledges that it is possible to choose fitness itself as the “function”.

    The point is that when the “function” is fitness itself, a particularly relevant function, there are many places in the genome where changes in sequence can affect that. There is no definitive requirement for the changes to all be concentrated in one gene. I’m glad that gpuccio has come around on this point.

    But I have never denied it!

    What I deny is that this is true in general of FI. Only a very generic definition of function (increse in fitness) allow for changes in different parts of the genome to contribute. In the general case, changes have to happen in a specific object. You initial statements was apparently about FI in generla.

    What I deny is that your example has anything to do with complex FI and with he 500 bits threshold, as clearly explained at #92 and at #104.

  111. 111
    jawa says:

    It seems like the distinguished professor JF at TSZ still doesn’t quite understand gpuccio’s clear point(s). Perhaps I was naively expecting that by now the distinguished professor JF at TSZ would at least get it. Now I see my expectations were too optimistic.
    Let’s keep waiting too see if the discussion somehow improves. So far they seem talking past one another and that’s kind of frustrating, isn’t it?
    How long can it take it for a distinguished academic personality to understand gpuccio’s clear explanations?

  112. 112
    gpuccio says:

    To all:

    The guys at TSZ are even below their usual level.

    DNA_Jock is a total disappointment. Maybe I was wrong thinking that he is not a fool. He says:

    His argument is that it is his empirical observation that such pathways (from low activity to the observed super-duper activity) do not exist.
    This is a burden shift, in that — for his technique to be valid — such pathways must be impossible.

    I will not even comment that. This is epistemological folly, and nothuing else.

    However, Joe Felsestein does comment:

    Well said.


    For those who don’t understand what we are talking about:

    These people are saying: “Even if it is true that there is absolutely no empirical support to our idea that those pathways exist, even if they have never been oberved, even if there is no conceptual reason for them to exist, they are a valid scientific explanation, unless you can demonstrate that they cannot exist, that their existence is impossible”.

    IOWs, anything that is not impossible must be accepted as a valid scientific explanation, even in the absolute absence of any empirical support.

    Shameful is really an understatement.

  113. 113
    gpuccio says:

    To all:

    DNA_Jock does even worse. He says:

    Finally, he protects himself against data that prove him wrong (Keefe & Szostak 2001, Hayashi et al 2006, etc.) by insisting that these studies were designed and therefore demonstrate the power of, I kid you not, “intelligent selection”. Nothing to do with what natural selection might be capable of. No siree.

    This is beyond credibility, beyond fairness and beyond any conceivable behaviour.

    He should know well, because I have discussed the topic with him in great detail, the reason why I say that Szostak’s paper is about artificial selection, and not about natural selection.

    The reason, of course, is not that the experiment is designed: all experiments are designed. Only DNA_Jock in his recent role as a fool could say such a thing.

    The reason is that the experiment is an experiment of protein engineering, because the original proteins found in the random library have been engineered by rounds of random mutations followed by artificial selection by the usual beads exhibiting ATP.

    This is artificial selection. It is not natural selection, and it is not a simulation of it.

    Maybe DNA_Jock could answer a very simple question, if he cared to drop for a moment his role as a fool:

    Is there any evidence that the ATP binding proteins found in the initial random library could have been naturally selected in any real biological context?

    But I already know what he would answer:

    “No, but it’s you who have the burden to demonstrate that it is impossible!”

    Again, shameful.

  114. 114
    gpuccio says:

    To all:

    Joe Felsestein insists in embarrassing himself:

    Unlikeliness “in certain protein configurations” is not the issue. A general proof of impossibility is the issue.

    No comment.

  115. 115
    gpuccio says:

    Joe Felsestein:

    My point, originally, was that changes in those places won’t, most of them, interact with each other strongly and act like a safe with a 200,000,000-bit key.

    Correct. And that’s exactly the reason why your argument is wrong. Those simple variation that don’t interact with each other are simple events. They have nothing to do with a single protein that has hundreds of AA sites that do interact and that generate a complex function of more than 500 bits of FI.

    Remember, you quoted changes happening anywhere in the genome as an argument to imply that they should be counted when considering the 500 bits of FI. That is wrong.

    As explained, I have no problems with simple variations happening anywhere in the genome and implementing simple functions like an increase in fitness. That has nothing to do with the design inference, and with my arguments.

  116. 116
    gpuccio says:

    Joe Felsestein:

    gpuccio, here, now says that in the cases he considers, the sequences below the threshold could have some nonzero function, but low enough that “a function below that threshold would be irrelevant in the system”, and not “naturally selectable”.

    How low is that? For example if we have a population of size 1,000,000 individuals, which is not unreasonably big for lots of organisms, how small can a selection coefficient be and still have the allele by “naturally selectable’?

    Maybe you live with evolutionary biology models, but I must remind you that those models are about real things.

    The selection coefficient has a meaning only if it can be derived from observed facts.

    For each function, there is a simple way to assess the minimum level that makes it visible to NS: some experiment.

    Do you really believe that the ATP binding proteins found in the random library by Szostak can be naturally selected in a real biological context?

    If yes, have you any evidence of that?

    Can I remind you that the only experiment of which I am aware was made not with the original random proteins, but with an highly engineered derived protein, and that not only it was in no way positively selected, it did indeed reduce fitness in a very detectable way?

    Or will you again object that it is my burden to demonstrate that it is impossible that those proteins be positively selected in some biological environment?

    Go on, say it!

  117. 117
    gpuccio says:

    To all:

    Well, while our friends at TSZ go on refining their epistemologic models where everything that is not impossible is true, let’s go back to real science for a momemt.

    We have discussed in detail the growth cone of axons as a basic tool to build the complex structure of the nervous system.

    But, of course, neuronal migration is another fundamental process. Neurons have to reach their correct sites, before reaching out to onther neurons by their axons.

    well, there is one extracellular protein rather specific to the ECM of the brain that strongly contributes to guiding that migration. Its name is reelin.

    From Wikipedia:

    Reelin (RELN)[5] is a large secreted extracellular matrix glycoprotein that helps regulate processes of neuronal migration and positioning in the developing brain by controlling cell-cell interactions. Besides this important role in early development, reelin continues to work in the adult brain.[6] It modulates synaptic plasticity by enhancing the induction and maintenance of long-term potentiation.[7][8] It also stimulates dendrite[9] and dendritic spine[10] development and regulates the continuing migration of neuroblasts generated in adult neurogenesis sites like subventricular and subgranular zones. It is found not only in the brain, but also in the liver, thyroid gland, adrenal gland, Fallopian tube, breast, and in comparatively lower levels across a range of anatomical regions.[11]

    Here is a recent paper about reelin:

    Control of Neuronal Migration and Aggregation by Reelin Signaling in the Developing Cerebral Cortex


    The mammalian cerebral neocortex has a well-organized laminar structure, achieved by the highly coordinated control of neuronal migration. During cortical development, excitatory neurons born near the lateral ventricle migrate radially to reach their final positions to form the cortical plate. During this process, dynamic changes are observed in the morphologies and migration modes, including multipolar migration, locomotion, and terminal translocation, of the newborn neurons. Disruption of these migration processes can result in neuronal disorders such as lissencephaly and periventricular heterotopia. The extracellular protein, Reelin, mainly secreted by the Cajal-Retzius neurons in the marginal zone during development, plays a crucial role in the neuronal migration and neocortical lamination. Reelin signaling, which exerts essential roles in the formation of the layered neocortex, is triggered by the binding of Reelin to its receptors, ApoER2 and VLDLR, followed by phosphorylation of the Dab1 adaptor protein. Accumulating evidence suggests that Reelin signaling controls multiple steps of neuronal migration, including the transition from multipolar to bipolar neurons, terminal translocation, and termination of migration beneath the marginal zone. In addition, it has been shown that ectopically expressed Reelin can cause neuronal aggregation via an N-cadherin-mediated manner. This review attempts to summarize our knowledge of the roles played by Reelin in neuronal migration and the underlying mechanisms.

  118. 118
    gpuccio says:


    You were too optimistic. The discussion is somehow getting worse.

  119. 119
    jawa says:

    gpuccio @117:

    “let’s go back to real science for a momemt.”

    Excellent decision!
    I like serious science.

  120. 120
    ET says:

    This gets better. Now “dazz” is saying that Keefe & Szostak 2001 was actually artificial selection. Clearly it doesn’t understand that the random library was all engineered. And then it conflates those ATP BINDING proteins with ATP synthase.

    Hilariously stupid, indeed, dazz.

  121. 121
    Mung says:


    Shameful is really an understatement.

    I thought you weren’t going to comment. 😀

  122. 122
    Mung says:


    To test if the neo-darwininian paradigm can generate complex functional information, we should define some function that can really be selected in some real biological environment.

    The belief appears to be that if it is artificially selectable it must be naturally selectable.

    For example, we would see all the various breeds of dogs even without artificial selection if only the natural environment were to mimic artificial selection.

  123. 123
    ET says:

    I love the tactic that we have to prove something is impossible all the while they don’t have to demonstrate anything.

  124. 124
    ET says:

    This is proof that dazz is clueless:

    When aerobic growth on citrate was achieved, did it start at a low level of function? or at a high level of function worth tons of FI?

    All that happened was the gene for the citrate transport gene was duplicated and the duplicate was put under the control of an existing binding site that just happened to be activated in the presence of O2.

    The function of citrate transport already existed. The function of utilizing citrate already existed. There wasn’t any new function added.

    And again there isn’t any justification with calling a gene duplication a blind and mindless event.

  125. 125
    jawa says:


    It’s a natural human condition to be in denial mood.

    When the Soviet army was near Berlin and WW2 was a few weeks from ending, the leader of the practicaly collapsed Nazi regime was in his bunker giving orders to a decimated and demoralized army. His generals were trying unsuccessfully to let him know that the noise they were hearing outside was from the soviet bombs exploding in the vicinity of the Reichstad.
    Perhaps we’re seeing an analogous situation with the still well entrenched neodarwinian regime. They’re in total denial mood, misinterpreting the avalanche of data coming out of leading edge biology research, which is bringing worse news for their already collapsed ideas, while increasing the support for the ID paradigm.
    Definitely it’s an exciting moment to watch what’s going on in serious science these days.
    As we have seen in recent science-related discussion threads here, particularly the ones where GP has been involved, a few distinguished academic personalities that have dared to debate GP have ended up retreating while writing off-topic nonsense.
    Let’s wait and see how this discussion proceeds from now on, but it seems like this is it. GP’s distinguished academic opponents ran out of valid arguments, but won’t at least try to understand GP’s point. Stubborn close mindedness is very common in the human race, regardless of educational level. We’re seeing it now.

  126. 126
    ET says:

    jawa, My apologies but you are mistaken as there isn’t any discussion going on. What we are seeing is gpuccio refining his arguments and adding to the evidence base that supports Intelligent Design. And what we need to do is to help gpuccio with constructive criticisms and real contributions to augment his points.

    When all they have to do is to actually demonstrate that they have a stochastic processes capable of producing what we infer was intelligently designed, it is very telling that they take a completely different tact and attack gpuccio and their straw man interpretation of what he says.

    Typical but still pathetic.

  127. 127
    bill cole says:


    Let’s wait and see how this discussion proceeds from now on, but it seems like this is it. GP’s distinguished academic opponents ran out of valid arguments, but won’t at least try to understand GP’s point. Stubborn close mindedness is very common in the human race, regardless of educational level. We’re seeing it now.

    The flakiness of this discussion is that Joe was originally talking about proof and now is moving the goal posts between proof and empirical evidence. Until his argument becomes one or the other proceeding seems unproductive. Proof is the argument that Eric is trying to make where gpuccio is making an empirical argument.

    ET properly flagged this in the beginning of the discussion. Joe then loosened the goal posts and when the going got tough yanked them back into the proof argument. The bottom line is the 500 bit argument is based on empirical evidence.

  128. 128
    ET says:

    rugrat posts:

    Any new protein that evolves will evolve from a DNA sequence that already exists, so your excuse here doesn’t work.

    With Lenski’s LTEE there wasn’t any new protein formed. So your ignorance here doesn’t work.

    And if it takes more than 2 mutations to get a new function out of the old sequence you are going to be pressed for time, especially if you are talking about sexually reproducing metazoans. See “Waiting for Two Mutations” and buy a vowel.

  129. 129
    john_a_designer says:


    “With Lenski’s LTEE there wasn’t any new protein formed.”

    Wasn’t? Lenski has ended his experiment? I thought it was ongoing.

  130. 130
    ET says:

    john_a_designer- The context was the duplication of the citrate transport gene. In that context there wasn’t any new protein being formed.

    And the fact that the duplicated gene just happened to fall under the control of a different promoter, that again just happened to be activated in the presence of oxygen- well let’s sum it up:

    1- You have duplicated the only possible gene that was designed for the purpose of transporting citrate through the membrane so that the cell can then utilize it. (lucky pick?)

    2- You have put that gene under the control of an existing binding site (lucky shot?)

    3- That binding site was activated in the presence of O2 (lucky guess?)

    Methinks it looks like the cell was responding to its environment and chance had little to do with it.

  131. 131
    john_a_designer says:

    So,his experiment is still ongoing? That’s all I’m asking.

  132. 132
    jawa says:

    I see your point. Thanks.

  133. 133
    jawa says:

    bill cole,
    Thanks for the clarifying commentary.

  134. 134
    ET says:

    Yes john_a_designer, no one has sprayed the plates with Lysol, yet. 😎

    The experiment continues. As far as I know it will continue across generations- human generations, until global climate warming change takes it all away.

  135. 135
    gpuccio says:


    According to Wikipedia, it’s still ongoing.

  136. 136
    gpuccio says:

    To all:

    I am too tired and too disenchanted to look at the last evolutions at TSZ now.

    So, I will just restate simply a few concepts:

    1) My argument is and has always been purely empirical. I have never tried to demonstrate that anything is logically impossible. Being true and false at the same time is probably logically impossible, but I will stop at that.

    2) Empirical science is about proposing credible explanation to known facts, and if possible choosing the best explanation (and that choice is often somewhat subjective).

    3) What empirical science certainly is not about is proposing theories that are not supported by any observed facts, and pretending that they are the only possible truth.

    4) Gradual pathways from simple functions to complex functions through simple steps, where each step is more functional than the previous one, are not observable anywhere. And there is no reason why they should exist, either in machines, in language, in software or in proteins.

    5) In proteins, in particular, they have never been observed as the result of NS (indeed, they have never been observed at all!). All the forms of NS in action that are known are simple transitions that optimize already existing functions, at most in the range of a few AAs, a few bits. There is no evidence at all that NS can generate a new and complex function. None at all.

    6) Biological proteins are complex machines. Most of them are well beyond the proposed threshold of 500 bits, whatever the method we use to evaluate indirectly their FI. That should however be obvious to anyone who is still capable of sound reasoning: how can anyone even imagine that a protein hundreds (or thousands) of AAs long, highly conserved, that folds in a very complex and specific way to generate extremely sophisticated molecular mechanisms, may be realized with less than 500 bits of information? When each specific AA site counts for 4.3 bits?

    7) A single complex protein falsifies the neo-darwinian theory. But of course there is much more than that in the biological worlds. Protein superfamilies are about 2000. Functional non coding RNAs are the true protagonists of the last years of research. Regulatory networks exhibit FI beyond our conceptions. And maybe if our intelrocutors took the time to read, say, the OP here, or anything else equivalent, without prejudice and dogma, they could start to consider questions that they have been avoiding in their whole life.

    8) However, everybody is free to think and believe as he likes. And to write the things that they write. It’s called free will. In this case, cognitive free will.

    9) One of them has written, I think, that we are “back” to Paley’s watch. That is not true. We have never moved away from Paleys wacth, simply because that is a true and powerful argument.

    The watch is designed, and we correctly infer design for it. There is no reason to move away from that simple truth, or to go back to it. We should simply stay in contact with what is true.

    What is not true is the blind whatcmaker, that exists only in the dogmatic imagination of our interlocutors.

    Of course, ID theory has been developed, and today we know in greater detail why we can correctly infer design for the watch, and why the same process is true for biological objects. But the basic idea is the same.

    So, I am very proud that my arguments are compared to Paley’s watch. That means they are very true.

    10) Finally, I will re-state here that my definition of FI is absoutely the same as Szostak’s. I am only surprised that DNA_Jock has not yet accused Szostak of the Texas Shooter Fallacy, with his cone and shifting thresholds.

    11) Speaking of Szostak, it is equally true that his definition of FI is good, and that his experiment about the ATP binding protein is very bad. At least, if it is used as an argument about what NS can do, which is apparently the case in all these discussions.

    If it is used merely as an example of what bottom up protein engineering can do, it’s perfectly acceptable. There are better examples, but one more is no problem.

    12) To the crowd that still declares that their theory is true if not proven impossible, that artificial selection is the same as natural selection, and that watches certainly can be generated by tornados in a junkyard, I can only wish good luck.

    For tonight, as said, I am tired.

  137. 137
    ET says:

    Just one more amusing post from Alan Fox:

    It’s not that we lack evidence or the ability to put it into compelling arguments and refutations.

    Yes, it is, Alan. You do lack the evidence and the ability to put it into compelling arguments and refutations. That much is obvious from your side’s complete FAILure to do so after decades, well since Darwin launched his evidence-free concept.

  138. 138
    PeterA says:

    gpuccio is tired of the evident lack of seriousness demonstrated by the TSZ folks that don’t seem interested in having a productive discussion. I agree with gpuccio and suggest it’s time to go back to the real science discussions. Before the JF/TSZ distraction, gpuccio was providing very interesting information associated with recent research papers that he posted. He kept posting references to interesting papers within the fascinating topic of this thread, but he got a little distracted and spent some time explaining over and over again important basic concepts that the TSZ folks still don’t seem to get right. Why is this happening?
    Can we go back to discussing the latest discoveries associated with the current OP topic?
    I’d rather see gpuccio and others contributing to this discussion thread and posting more OPs and starting new discussion threads on interesting topics. Time is priceless. There are so many interesting research papers out there presenting novel evidences that strengthen the ID paradigm, that we should not be too concerned about what some folks write in other websites.

  139. 139
    Ed George says:


    gpuccio is tired of the lack of seriousness seen in the TSZ folks that don’t seem interested in having a productive discussion. I agree with gpuccio and suggest it’s time to go back to the real science discussions.

    It is hard to disagree with this sentiment. But it is hard to fight against those willing to submit research manuscripts up for peer review when the ID side is hesitant to do so. Surely there has been enough research supporting ID that this can be done.

  140. 140

    the ID side is hesitant to do so

    What a misguided, and frankly ignorant, statement. The evidence for design in biology has been carefully recorded in the literature, and deeply embedded in the history of empirical science for more than 65 years, at a minimum. That history (and those observations) are routinely ignored and diminished among ideologues in the academy; indeed it is not even allowed up for discussion.

    If universal observations in settled science are not allowed to breach the unscientific practice of materialistic ideology, what does anyone really expect of another paper here or there? This, by the way, merely grants your equally ridiculous premise that ID proponents are “hesitant” to produce work, which is itself just another ideological smear.

  141. 141

    GP at #55

    Yes, symbols and semiosis become the absolute rule as soon as we climb the ladder of higher organizational layers.

    I would add that a semiotic mechanism is the first rung on that organizational ladder, since it’s the only way to specify something among alternatives in a medium of heritable information; the only way that an autonomous open-ended self-replicator can describe and preserve itself over time.

    Again, GP, wonderful OP.

  142. 142
    john_a_designer says:

    Over on another thread I cited a paper by Abel and Trevors. Is it peer reviewed? I find that they make some absolutely stunning claims that sound very ID friendly. Does anyone know where their sympathies lie?

  143. 143
    gpuccio says:


    Theoretical Biology and Medical Modelling is an open access peer-reviewed journal .

    Abel and Trevors are definitely wonderful ID thinkers and supporters. Abel has written very interesting papers and books about ID. See here:

    Dr. David L Abel

  144. 144
    gpuccio says:

    Ed George:

    “But it is hard to fight against those willing to submit research manuscripts up for peer review when the ID side is hesitant to do so. Surely there has been enough research supporting ID that this can be done.”

    Well, all the scientific papers I quote in the OP do support ID. With their facts, not with their ideology.

  145. 145
    gpuccio says:


    “I would add that a semiotic mechanism is the first rung on that organizational ladder, since it’s the only way to specify something among alternatives in a medium of heritable information; the only way that an autonomous open-ended self-replicator can describe and preserve itself over time.”

    Of course. And thank you for the kind words! 🙂

  146. 146
    gpuccio says:


    “The evidence for design in biology has been carefully recorded in the literature, and deeply embedded in the history of empirical science for more than 65 years, at a minimum.”

    How true! 🙂

  147. 147
    gpuccio says:

    To all:

    Neuronal migration is certainly an essential component of organism complexity, especially in vertebrates, where the brain structure and function reaches new levels of amazing organization.

    The following paper highlights the role of a specific protein in neuronal migration, Autism susceptibility candidate 2 (AUTS2):

    Neuronal Migration and AUTS2 Syndrome


    Neuronal migration is one of the pivotal steps to form a functional brain, and disorganization of this process is believed to underlie the pathology of psychiatric disorders including schizophrenia, autism spectrum disorders (ASD) and epilepsy. However, it is not clear how abnormal neuronal migration causes mental dysfunction. Recently, a key gene for various psychiatric diseases, the Autism susceptibility candidate 2 (AUTS2), has been shown to regulate neuronal migration, which gives new insight into understanding this question. Interestingly, the AUTS2 protein has dual functions: Cytoplasmic AUTS2 regulates actin cytoskeleton to control neuronal migration and neurite extension, while nuclear AUTS2 controls transcription of various genes as a component of the polycomb complex 1 (PRC1). In this review, we discuss AUTS2 from the viewpoint of human genetics, molecular function, brain development, and behavior in animal models, focusing on its role in neuronal migration.

    Emphasis mine.

    I think that this is a wonderful example of cross-talk between two fundamental complex regulatory networks: cewll migration and transcription regulation, with the same protein acting as a key protagonist in both.

    Again from the paper:

    The AUTS2 Gene and AUTS2 Syndrome

    AUTS2 is one of the largest genes in mammals, spanning 1.2 Mb and containing 19 exons (Figure 1A) [17]. The first six exons at the 5? end are separated with large introns, whereas the remaining 13 exons, which are highly conserved in vertebrates, are compact with smaller clustered introns at the 3? end. The main transcript of Auts2 encodes a relatively large protein (1259 aa for human (NM_015570) and 1261 aa for mus musculus (NM_177047)), but multiple alternatively spliced isoforms also exist.

    AUTS2 Functions in Cytoskeletal Regulation and Transcriptional Activation

    Recent studies conducted by two groups provided insight into the function of nuclear AUTS2 as a transcriptional regulator for neural development.

    In the cytoplasm, AUTS2 interacts with guanine nucleotide exchange factors (GEFs), P-Rex1 and Elmo2/Dock180 complex, to activate a Rho family small GTPase, Rac1, a key coordinator of actin polymerization and microtubule dynamics [18,26,27]. The cytoplasmic AUTS2 promotes lamellipodia formation in neuroblastoma cells and neurite extension of hippocampal primary cultured neurons in vitro. On the other hand, AUTS2 interacts with other GEFs, intersectin (ITSN) 1 and ITSN2, to suppress the activities of another Rho family GTPase, Cdc42, leading to repression of filopodia formation in the neurites and cell bodies of neurons

    Here is the “Function” section of the AUTS2 protein in Uniprot:

    Component of a Polycomb group (PcG) multiprotein PRC1-like complex, a complex class required to maintain the transcriptionally repressive state of many genes, including Hox genes, throughout development. PcG PRC1 complex acts via chromatin remodeling and modification of histones; it mediates monoubiquitination of histone H2A ‘Lys-119’, rendering chromatin heritably changed in its expressibility (PubMed:25519132). The PRC1-like complex that contains PCGF5, RNF2, CSNK2B, RYBP and AUTS2 has decreased histone H2A ubiquitination activity, due to the phosphorylation of RNF2 by CSNK2B (PubMed:25519132). As a consequence, the complex mediates transcriptional activation (PubMed:25519132). In the cytoplasm, plays a role in axon and dendrite elongation and in neuronal migration during embryonic brain development. Promotes reorganization of the actin cytoskeleton, lamellipodia formation and neurite elongation via its interaction with RAC guanine nucleotide exchange factors, which then leads to the activation of RAC1

    So, transcription regulation, chromatin remodeling, ubiquitination, control of the cytoskeleton! Not bad, for one protein. 🙂

    AUTS2 is 1259 AAs long in humans. Its evolutionary history is interestin. The human sequence is practically not detectable in prevertabrates:

    0.1509134 baa

    and appears in cartilaginous fish with a significant jump:

    0.8046068 (+0.6536934, +823 bits)

    Then the homology with the human form increases by three successive smaller jumps (bony fishes, amphibians, reptiles), reaching a value of about 1.5 baas, that remains practically the same in mammals (as usual, I am not considering primates here, for the methodological reasons that I have often explained: too short evolutionary separation from humans).

    So, this is a very specific vertebrate protein, at least in the form we observe in humans.

  148. 148
    PeterA says:

    “cross-talk between two fundamental complex regulatory networks”

    Wow! Incredible.

  149. 149
    PeterA says:

    What would be the interpretation of this paper from the ID perspective?

    The fitness landscape of the codon space across environments

    Fitness landscapes map the relationship between genotypes and fitness. However, most fitness landscape studies ignore the genetic architecture imposed by the codon table and thereby neglect the potential role of synonymous mutations. To quantify the fitness effects of synonymous mutations and their potential impact on adaptation on a fitness landscape, we use a new software based on Bayesian Monte Carlo Markov Chain methods and re-estimate selection coefficients of all possible codon mutations across 9 amino acid positions in Saccharomyces cerevisiae Hsp90 across 6 environments. We quantify the distribution of fitness effects of synonymous mutations and show that it is dominated by many mutations of small or no effect and few mutations of larger effect. We then compare the shape of the codon fitness landscape across amino acid positions and environments, and quantify how the consideration of synonymous fitness effects changes the evolutionary dynamics on these fitness landscapes. Together these results highlight a possible role of synonymous mutations in adaptation and indicate the potential mis-inference when they are neglected in fitness landscape studies.

  150. 150
    jawa says:

    “Well, all the scientific papers I quote in the OP do support ID. With their facts, not with their ideology.”


  151. 151
    jawa says:

    Was Copernicus a theoretical or empirical astronomer?

  152. 152
    ET says:

    jawa- He was both. His theory was based on his observations

  153. 153
    ET says:

    Joe Felsenstein still doesn’t get it. He doesn’t understand that the onus is on him to provide evidence that natural selection can produce 500 bits of specified information/ FI. The onus is not on anyone to prove that it cannot.

    Joe Felsenstein makes it very clear that his position has nothing but posturing and burden-shifting.

  154. 154
    Ed George says:


    Well, all the scientific papers I quote in the OP do support ID. With their facts, not with their ideology.

    To be fair, it is your opinion that they support ID. And I generally agree with you, But until things like this are submitted for publication and open to critical examination by those knowledgeable in the subject, I fear that ID will never advance beyond a fringe belief forever linked, unfairly, to religion.

    I am not knowledgable enough in the biological sciences to take on the task, and I respect your preference not to do so, but ID has several very intelligent people with knowledge in the subject and skilled at conducting publication quality research.

    I will admit that my belief in ID is largely due to faith, not a thorough examination of the data, but I do enjoy reading through your OPs and subsequent comments.

  155. 155
    ET says:

    Ed George- The point is to be able to take SCIENTIFIC research and come to an inference of Intelligent Design. And seeing that no one can take the same evidence and show how blind and mindless processes didit it seems that the design inference is safe.

    Faith has nothing to do with ID unless it is faith in what we observe and can test along with faith in our knowledge of cause and effect relationships.

    If someone else has a scientifically viable alternative to ID we would love to see it. That has not yet occurred and I doubt that it ever will.

  156. 156
    ET says:

    For example, Ed, take a look at the architecture and subunit composition of ATP synthase.

    If you take a look at ATP synthase you can see it consists of two major subunits (F0 & F1) that are connected together by an external tether. This tether doesn’t have anything to do with the functionality of either subunit but without it no ATP synthase. The problem for evolution by blind and mindless processes is exacerbated. Not only does it need to produce the two subunits but one has to be embedded in some membrane so that a gradient can be formed. And the other has to to be stably tethered to the membrane the proper distance away. The tether looks like the membrane subunit F0 somehow formed an external docking site the proper length with F1 forming an external mating site.

    Again these two different protein subunits, the tether and mate, have nothing to do with the function of the protein complexes they are attached to and tether together. And without them there is no way to get the two working subunits together to produce ATP.

    There you have it- A simple external tether that stably holds the major F1 subunit/ rotary motor the proper distance away from its F0 motor force is evidence for the Intelligent Design of ATP synthase. The two major subunits and how it works is just icing on the cake.

  157. 157
    Heartlander says:

    ET@156 – Good point.

    If we were to discover a highly efficient motor that performed a necessary functions with precisely arranged parts, would we be allowed to infer teleology? What would prevent anyone from making the inference?

  158. 158
    Ed George says:


    If we were to discover a highly efficient motor that performed a necessary functions with precisely arranged parts, would we be allowed to infer teleology? What would prevent anyone from making the inference?

    Inferences are like ideas. Our ability to make them is not dependent on their truth.

  159. 159
    ET says:

    Ed George:

    Inferences are like ideas. Our ability to make them is not dependent on their truth.

    Their strength is based on the evidence, the options that can explain it and the methodology to test those options.

    I would love to see someone try to refute the design inference by actually showing that natural selection can produce multi-protein machines like ATP synthase or any bacterial flagella. The point being is our opponents don’t have the methodology to test their claims whereas we do.

  160. 160
    PavelU says:

    The ID fans seem very confident, but they should not uncork the champagne bottles yet.
    There’s much literature that seems to weaken the ID concept.
    Here’s a small sample:

    Information theory in systems biology. Part I: Gene regulatory and metabolic networks

    “A Mathematical Theory of Communication”, was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein–protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory.

    Information theory in systems biology. Part II: protein–protein interaction and signaling networks

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein–protein interaction and signaling networks will be surveyed.

    Energy and information flows in biological systems: Bioenergy transduction of V1-ATPase rotary motor and dynamics of thermodynamic entropy in information flows

    We classify research fields in biology with respect to flows of materials, energy, and information. We investigate energy transducing mechanisms in biology, using as a representative the typical molecular rotary motor V1-ATPase from a bacterium Enterococcus hirae. The structures of several intermediates of the rotary motor are described and the molecular mechanism of the motor converting chemical energy into mechanical energy is discussed. Comments and considerations on the information flows in biology, especially on the thermodynamic entropy in quantum physical and biological systems, are presented in section 3 in a biologist friendly manner.

    Methods of information theory and algorithmic complexity for network biology

    We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon’s information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdös-Rényi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity.

     Analysis of cellular signal transduction from an information theoretic approach

    Signal transduction processes the information of various cellular functions, including cell proliferation, differentiation, and death. The information for controlling cell fate is transmitted by concentrations of cellular signaling molecules. However, how much information is transmitted in signaling pathways has thus far not been investigated. Shannon’s information theory paves the way to quantitatively analyze information transmission in signaling pathways. The theory has recently been applied to signal transduction, and mutual information of signal transduction has been determined to be a measure of information transmission. We review this work and provide an overview of how signal transduction transmits informational input and exerts biological output.

    Algorithmically probable mutations reproduce aspects of evolution, such as convergence rate, genetic memory and modularity

    Natural selection explains how life has evolved over millions of years from more primitive forms. The speed at which this happens, however, has sometimes defied formal explanations when based on random (uniformly distributed) mutations. Here, we investigate the application of a simplicity bias based on a natural but algorithmic distribution of mutations (no recombination) in various examples, particularly binary matrices, in order to compare evolutionary convergence rates. Results both on synthetic and on small biological examples indicate an accelerated rate when mutations are not statistically uniform but algorithmically uniform. We show that algorithmic distributions can evolve modularity and genetic memory by preservation of structures when they first occur sometimes leading to an accelerated production of diversity but also to population extinctions, possibly explaining naturally occurring phenomena such as diversity explosions (e.g. the Cambrian) and massive extinctions (e.g. the End Triassic) whose causes are currently a cause for debate. The natural approach introduced here appears to be a better approximation to biological evolution than models based exclusively upon random uniform mutations, and it also approaches a formal version of open-ended evolution based on previous formal results. These results validate some suggestions in the direction that computation may be an equally important driver of evolution. We also show that inducing the method on problems of optimization, such as genetic algorithms, has the potential to accelerate convergence of artificial evolutionary algorithms.

  161. 161
    Heartlander says:

    Ed George @158

    The questions were rhetorical – it is the presupposition of naturalism (no design) in biology that prevents the inference (regardless of the truth).

  162. 162
    gpuccio says:

    Ed George:

    “To be fair, it is your opinion that they support ID.”

    Sure. I usually express my opinions, not others’.

    And I try to explain my motivations.

    “But until things like this are submitted for publication”

    Being submitted (and approved) for publication is no guarantee of truth. In my opinion, of course.

    “and open to critical examination by those knowledgeable in the subject,”

    This is a public blog. What prevents knowledgeable people from reading it? Even our friends at TSZ read it, and they comment on their blog. I am sure many of them are knowledgeable.

    I am not knowledgeable. I just like to express my opinions. Bad habit, certainly.

    “I fear that ID will never advance beyond a fringe belief”

    If ID is true, as I do believe, it has no need to advance. It’s the scientific community that should advance, understanding what is true.

    Belief in what is true is a true belief, be it fringe or not.

    “forever linked, unfairly, to religion”

    Why? My arguments are certainly not linked to religion. ID is not linked to religion. If some IDists, or most of ID critics, want to link their imaginations about ID to religion, it’s just their problem.

    ID is true science. It is linked only to what is true.

    “I will admit that my belief in ID is largely due to faith,”

    Your choice. Many people have a strong religious faith, and still do not subscribe to ID. You could as well be a theistic evolutionist, if it’s only a question of faith.

    Most believers in neo-darwinism are men of faith too. It is really difficult to believe in neo-darwinism without a good amount of blind faith.

    I am a man of faith too. But that is not the reason why I firmly believe that ID is true. That belief is based on science.

    “not a thorough examination of the data,”

    I would invite you to examine the data thoroughly. It’s not necessarily a question of having a perfect knowledge of the details. It’s more a question of having an open mind, and a sincere desire for truth.

    But, in the end, it’s your choice.

    “but I do enjoy reading through your OPs and subsequent comments.”

    Thank you. I appreciate it.

  163. 163
    gpuccio says:


    Good thoughts on ATP synthase. Always a fascinating topic! 🙂

  164. 164
    gpuccio says:

    Ed George:

    “Inferences are like ideas.”

    Inferences are ideas.

    “Our ability to make them is not dependent on their truth.”

    But still, ideas (and inferences) are often true or false. And our ability to distinguish between the two certainly depends on our cognitive sincerity.

  165. 165
    gpuccio says:

    To all:

    Just a few additional thoughts.

    I like it when our adversaries criticize us because:

    “It’s Paley’s watch all over again”


    “It’s the old idea that it’s too complex and therefore it must be designed”.

    These are really good appreciations, not criticisms, as I have already said, because they are true.

    It’s really Paley’s watch all over again.

    And it’s really that certain things are too complex, and therefore they must have been designed.

    I don’t know what our interlocutors have in in mind, when they say those things as though they were criticisms.

    ID theory is about complexity as a key to infer design. What else?

    Of course, it has to be a specific type of complexity, functional complexity, or specified complexity.

    Of course, there has to be a quantitative approach.

    But in the end, it’s functional complexity that points to design. Be it in a wacth or in a protein, or in a regulatory network.

    Because only design is known to generate functional complexity beyond some trivial level.

    Joe Felsestein seems very happy that the neo-darwinian algorithm can explain trivial levels of functional complexity, like some simple increase in fitness, or many simple increases in fitness. I am happy that he is happy, but what has that to do with a design inference? Absolutely nothing.

    We have always known that RV + NS can generate trivial levels of functional complexity. I, certainly, have never denied it, indeed I have defended that idea against others.

    I write OPs like this one because I think that it is good to understand, myself, and to share with others, how functionally complex biological realities are, ad how our understanding of that complexity grows daily. That’s why I try to add new and very recent papers as often as I can.

    Some of our kind interlocutors, in the rare cases when they choose to comment on those OPs, briefly state that the things I say may be correct or even interesting, but that they do not understand how they support ID, or better how they may be a problem for neo darwinism.

    Well, are they kidding?

    Look, it’s really simple. There is not a lot of philosophy, or of intricate reasoning there.

    The more biological realities are shown to be functionally complex, the more it is simply ridiculous to believe that they can be explained by the neo-darwinian theory.

    Not difficult to understand.

    Because if neo-darwinism cannot even explain one single protein that has more than 500 bits of FI, how can it even start to try to explain Focal Adhesions? Or the Adhesome? Or neuron migration?

    It’s simple: the more things are functionally complex, the more we are certain that they are designed.

    Ah, and that’s just my opinion, of course! 🙂

  166. 166
    Ed George says:


    Being submitted (and approved) for publication is no guarantee of truth. In my opinion, of course.

    I don’t think that you will find anyone who would disagree. In the handful of papers I have published, there is not one that did not have errors.

    This is a public blog. What prevents knowledgeable people from reading it?

    Nothing. But with all due respect to the owners and participants of this site, the interest in it from the scientific community is almost nonexistent. But publications in reputable journals, and the responses to these publications, are taken seriously. But, again, I respect your preference not to use that route. But I don’t understand why that route isn’t used more effectively by ID researchers.

    ID is not linked to religion. If some IDists, or most of ID critics, want to link their imaginations about ID to religion, it’s just their problem.

    Sadly, to most scientists and decision makers, ID is most certainly linked to religion. The fact that this perception is wrong does not change this fact. And it is not just their problem. As long as this perception persists, public policy and our education system will continue to suffer.

    Inferences are ideas.


  167. 167
    jawa says:

    gpuccio @162:

    “Being submitted (and approved) for publication is no guarantee of truth. In my opinion, of course.”

    In my opinion too. 🙂

  168. 168
    jawa says:

    gpuccio @165:

    “It’s simple: the more things are functionally complex, the more we are certain that they are designed.
    Ah, and that’s just my opinion, of course!”

    And that’s my opinion too. 🙂

  169. 169
    jawa says:

    Ed George @166:

    “In the handful of papers I have published, there is not one that did not have errors.”

    Please, would you mind telling us what those papers are about? Thanks.

  170. 170
    gpuccio says:

    Ed George:

    “But with all due respect to the owners and participants of this site, the interest in it from the scientific community is almost nonexistent.”

    The problem is not the lack of interest for this site.

    The problem is the lack of interest for the ideas that are expressed on this site, and elsewhere.

    Let’s be frank: ID ideas are very much known around, Indeed, there has been a lot of debate about them. Not so much for the resources available to the few ID thinkers and sceintists, I would say, but rather for the vehement amount of opposition generated by those who have the real power.

    If most scientists are not “interested” in ID, I believe, it’s not because they don’t know about it.

    And I don’t think that a few more ID friendly papers in the peer reviewed literature would change much (indeed, there are already a few). They would just generate an exponential amount of counter-papers.

    The interest in ID is almost non existent for a very simple reason: most scientists have a blind faith in a wrong theory that has been proclaimed as absolute truth for decades.

    Of course, that will change. Human thought is usually able, in the end, to overcome those biases. But it takes time.

    You ask:

    “But I don’t understand why that route isn’t used more effectively by ID researchers.”

    Are you really so naive?

    A couple of answers, among many:

    a) Because they don’t have the resources to generate a lot of reasearch?

    b) Because a sincerely ID friendly paper has almost no hope to pass peer review?

    Luckily, as I have said, almost each single new paper that comes out in the literature supports ID: with facts.

    But, of course, we have to open our eyes and look at facts.

  171. 171
    ET says:

    Ed George:

    But with all due respect to the owners and participants of this site, the interest in it from the scientific community is almost nonexistent.

    Oh my. With all due respect scientists tend to have special interests, ie that of their line of work. And it is a given that whatever they do does not rely of spontaneous evolution. No one starts their research by saying “life arose on this planet just because the conditions allowed it to. And it’s diversity arose also just because it could. It had no choice given imperfect replication and all”

    Blind watchmaker evolution is a useless scientific heuristic.

    There isn’t anything in those journals that supports the concept. That is the whole point.

    Every peer-reviewed paper on ATP synthase provides evidence for ID. Peer-review has provided the scientific evidence for ID and ID has the only scientifically viable explanation for it.

    Sadly, to most scientists and decision makers, ID is most certainly linked to religion.

    There isn’t a cure for willful ignorance.

    Methinks Ed doesn’t understand what the word “inference” means in a scientific context.

  172. 172
    ET says:


    There’s much literature that seems to weaken the ID concept.
    Here’s a small sample

    I don’t understand how those weaken the ID concept. Could you please at least try to make your case based on your provided evidence?

  173. 173
    PeterA says:

    gpuccio @170:

    “most scientists have a blind faith in a wrong theory that has been proclaimed as absolute truth for decades.
    Of course, that will change. Human thought is usually able, in the end, to overcome those biases. But it takes time.”

    Copernicus was an empirical astronomer, whose ideas contradicted the long accepted ideas. However, eventually his revolutionary ideas, which were based on empirical observation, became accepted.

  174. 174
    PavelU says:

    ET @172:

    The papers cited @160 clearly explain how the biological complexity resulted from Darwinian evolution (i.e. RV+NS). I can’t repeat what it’s written there. You may read it yourself if you want to.

  175. 175
    Ed George says:


    Please, would you mind telling us what those papers are about? Thanks.

    Not at all. My first few were on marine zooplankton ecology. My latest few, following a 30 year hiatus, have been in analytical chemistry.

  176. 176
    jawa says:

    PavelU @174:

    Do you really believe that?

  177. 177
    jawa says:

    Ed George @175:

    That’s interesting. Thanks.

  178. 178
    Ed George says:


    The problem is not the lack of interest for this site.

    The problem is the lack of interest for the ideas that are expressed on this site, and elsewhere.

    I think that is what I was trying to express.

    If most scientists are not “interested” in ID, I believe, it’s not because they don’t know about it.

    True. It is that they don’t take what they have seen so far seriously.

    And I don’t think that a few more ID friendly papers in the peer reviewed literature would change much (indeed, there are already a few). They would just generate an exponential amount of counter-papers.

    Of course there would be criticism. And it would probably be vociferous. But the opposition to Darwin’s theory was also intense. As was the opposition to Wegener’s continental drift theory. And the dinosaur killing asteroid theory. And quantum mechanics. The examples are endless. But because there were people willing to put their necks out and publish on these, they gained traction. I don’t see this happening with ID. We just seem to be spinning our wheels. We have to stop blaming others for our failures.

  179. 179
    ET says:

    PavelU- You are sadly mistaken as not one of those papers pertains to Darwinian evolution.

    You can’t repeat what is written there because you don’t understand it and it doesn’t support your claim.

  180. 180
    ET says:

    Ed George- No one cares what those scientists take seriously as they definitely cannot offer a better explanation. Darwin’s theory does not pass muster as a scientific theory. For one he said we had to prove a negative to falsify it and for another he never devised a way to test it.

  181. 181
    Ed George says:


    Ed George- No one cares what those scientists take seriously as they definitely cannot offer a better explanation.

    That approach shows the same level of maturity as the kid who doesn’t get his way in the playground so he takes his ball and goes home. Is that really what you are recommending?

  182. 182
    ET says:

    Ed George- Your selective quoting says that clearly you need a nap. What you mined in no way shows what you say. You have obviously ignored everything else and decided to just snap when things are not going as you planned.

    YOU are being the petulant child here, Ed. The evidence is there and your scientists don’t have any explanation for it. Don’t blame me for invoking the Hitchen’s gambit.

    ID has the evidence, concept and a methodology to test it. Not only that ID’s concepts are being used in the form of genetic algorithms which use telic processes, ie evolution by design, to solve the problems they were designed to solve.

    What I am recommending, Ed, is those who don’t take us seriously ante up so we can take the Pepsi challenge. That is all we ask. Give us something to compare to. The only reason that probability arguments exist is because there isn’t anything else.

    So please, tell your scientists to give us something that can be tested. Then people may take them seriously.

    It isn’t as though doubting evolutionism will ever do any harm.

  183. 183
    bill cole says:

    Hi Pave

    Natural selection explains how life has evolved over millions of years from more primitive forms.

    Lets start with the first step. How does natural selection explain the emergence of thousands of new proteins that first appeared in eukaryotic cells along with exons introns a cell nucleus and the spliceosome. You are dealing with organizing almost infinite sequence space through a trial and error search. This is step one. Step two is at least as difficult.

    The truth is natural selection explains very little. You have to explain the emergence of enormous amounts of functional information and the only demonstrated cause large quantities of FI is conscious intelligence.

  184. 184

    Ed, the issue is that there is overwhelming evidence for ID already in the literature, carefully recorded there by theist and non-theist alike (just dutifully doing their work) over the course of many generations and disciplines.

    And it all comes to naught because the reigning materialist dogma demands that it not be acknowledged. Thus, it is simply not acknowledged.

    So, for instance, when we discover (through scientific investigation) that all life on Earth is organized by a system of symbols (an encoded language) – so what? If that discovery is further bolstered by the fact that it was successfully predicted to exist through logic and observation – so what? And if those observations are tested by time, and indeed, if they grow over and over again with each new discovery — so what?

    The modern will to power, even through the imprimatur of science, is a deliberate choice and action no different than any other time (or topic) in human history. Science is being abused by authority and self interest.

    All the incessant anti-ID bemoaning about definitions and mathematics and religious beliefs and quantum woo and scientific publications and our own bloody human history – the entire materialist sociopolitical project – is merely grist for the mill. It is not engaged in for scientific clarity, but for the sole purpose of dismissing the empirical evidence of design in biology. Design is simply not allowed, and that rule has been very effectively communicated to everyone.

    To not grasp this fact is to be unnecessarily naïve, but to go further and suggest that adherents of the suppressed evidence must play the game at the pleasure of the dogma is patently ridiculous. If that is really what you consider a suitable response, we can at least hope you are not put in charge of anything important. 🙂

  185. 185
    Barry Arrington says:



    e can at least hope you are not put in charge of anything important

    It is rare that I write LOL and mean it literally. This is an exception. Thanks for the little dose of levity UB.

  186. 186
    gpuccio says:

    Ed George:

    I agree with you on one thing: the debate about functional information in biology should be separated from religion.

    The simple fact is that, in the form of ID theory, it is separated from religion. ID theory is completely independent from religion.

    That many IDists are religious and feel a connection between their religious views and ID is certainly understandable, but in no way that makes the theory dependent on religion. I have passionately defended ID theory here without ever recurring to any religious idea.

    Unfortunately, the same is not true for the other side (always my opinion, of course! 🙂 ).

    With all that is known today, with all the facts available, only a religious adherence to a specific ideology can make intelligent people still believe that “RV + NS can do it”.

    Call it materialism, reductionism, scientism, methodological naturalism, whatever: it’s ideology all the same. Simply put, it just means: we cannot accept a design explanation, however supported by facts, because it is contrary to our general worldview.

    That this is not true of religious people is demonstrated by the simple fact that a lot of religious people do accept neo-darwinism, probably unaware of the scientific reasons that falsify it.

    So, in brief:

    a) Religious people can accept neo-darwinism

    b) Non religious people seem to be completely unable to even consider design as an explanation

    I have never, never met one person from the other side who has been capable to seriously consider design as a possibility. I don’t mean accept it as the best explanation, but at least admit that it could be, in principle, an explanation.

    This is true of all of them, even the best. When the discussion becomes uncomfortable, they must always, always shift to some ideological defense.

    That’s why, in the end, the discussion is always frustrating. Those people, even the best, are reasonable and open minded until they feel confident that they can be reasonable and open minded, because they will easily destroy the silly arguments of IDists.

    As soon as they have to face arguments from IDists that are not silly at all, they lose all the reasonable attitude, all the pretended open mindedness, and they behave for what they are: dogmatists.

    That many of them act that way would not be surpising: it’s human nature.

    But that all of them, even the best, act that way is really disappointing.

    Again, I am not asking that they are convinced, or that they change their mind. But there is never, never a point where any of them is able to say: OK, there is something in what you say, you have some points, but still I consider my position a better explanation for these reasons.

    No. There is always, in the end, complete denial. In the best (few of them), it is respectful denial, sometimes even kind denial. But denial all the same.

    In the worst…

  187. 187
    jawa says:

    In the worst…

    Yes, leave it open for us to complete it, for we’ve seen it

  188. 188
    gpuccio says:

    To all:

    This is, again, about reelin and neuronal migration.

    With a lot of interesting details.

    How does Reelin signaling regulate the neuronal cytoskeleton during migration?


    Neuronal migration is an essential step in the formation of laminated brain structures. In the developing cerebral cortex, pyramidal neurons migrate toward the Reelin-containing marginal zone. Reelin is an extracellular matrix protein synthesized by Cajal-Retzius cells. In this review, we summarize our recent results and hypotheses on how Reelin might regulate neuronal migration by acting on the actin and microtubule cytoskeleton. By binding to ApoER2 receptors on the migrating neurons, Reelin induces stabilization of the leading processes extending toward the marginal zone, which involves Dab1 phosphorylation, adhesion molecule expression, cofilin phosphorylation and inhibition of tau phosphorylation. By binding to VLDLR and integrin receptors, Reelin interacts with Lis1 and induces nuclear translocation, accompanied by the ubiquitination of phosphorylated Dab1. Eventually Reelin induces clustering of its receptors resulting in the endocytosis of a Reelin/receptor complex (particularly VLDLR). The resulting decrease in Reelin contributes to neuronal arrest at the marginal zone.

  189. 189
    Mung says:

    PavelU, thanks for those links!

  190. 190
    PavelU says:


    You’re very welcome!

    BTW, do you agree that they seem to weaken the ID position?

  191. 191
    ET says:

    PavelU- Those papers in no way weaken the ID position. That is because those papers in no way support Darwinian evolution. Clearly you have not read them and clearly you cannot make a case against ID using them.

  192. 192
    OLV says:


    Excellent OP and follow-up comments. Thanks.

    The paper in #188 seems to shed much light on a very important topic.

    Other papers you have cited in this thread are very interesting too.

    Well done!

  193. 193
    Ed George says:


    Ed, the issue is that there is overwhelming evidence for ID already in the literature, carefully recorded there by theist and non-theist alike (just dutifully doing their work) over the course of many generations and disciplines.

    I have not followed the literature to the extent necessary to make a conclusion on this one way or the other. However, going on the premise that you are correct, most journals accept articles that draw evidence presented in other papers to support the hypothesis being presented in the submitted manuscript. Do you know if anyone has attempted to submit a manuscript to a journal that compiles the overwhelming evidence that already exists in the literature supporting ID? If such an attempt has been made, the follow-on responses to the published paper would be very informative. As would the responses from the reviewers should the paper have been rejected.

    To not grasp this fact is to be unnecessarily naïve, but to go further and suggest that adherents of the suppressed evidence must play the game at the pleasure of the dogma is patently ridiculous.

    We can either make attempts to advance the ID theory within the current scientific infrastructure or we can whine and complain that the science community is unfair. It has been my experience that whining and complaining only further isolates a person’s view, even if it is the correct one.

    If that is really what you consider a suitable response, we can at least hope you are not put in charge of anything important.

    I guess that depends on whether or not you believe the safety of your drinking water, environment, food, etc. is important. 🙂

  194. 194
    OLV says:

    ET (191):

    Agree with you on that. Those papers may actually provide additional support to the ID paradigm. Just read them carefully. Some articles are paywall though.

  195. 195
    ET says:

    Ed George:

    Do you know if anyone has attempted to submit a manuscript to a journal that compiles the overwhelming evidence that already exists in the literature supporting ID?

    No one has done such a thing for evolutionism, Ed. Why is it even considered by your alleged scientific community? Why does ID have to do something different?

    We can either make attempts to advance the ID theory within the current scientific infrastructure or we can whine and complain that the science community is unfair.

    Unbelievable. That alleged scientific community doesn’t have anything in peer-review that advances evolutionism. That alleged scientific community doesn’t have a scientifically viable alternative to ID

    It has been my experience that whining and complaining only further isolates a person’s view, even if it is the correct one.

    And yet that is all our opponents ever do- whine and complain.

    Methinks Ed George is a sock puppet of one Acartia Bogart/ William spearshake. The ignorance level is about the same as is their work place

  196. 196
    OLV says:

    These papers seem related to the paper cited in #188:

    Estradiol and the Development of the Cerebral Cortex: An Unexpected Role?

    The cerebral cortex undergoes rapid folding in an “inside-outside” manner during embryonic development resulting in the establishment of six discrete cortical layers. This unique cytoarchitecture occurs via the coordinated processes of neurogenesis and cell migration. In addition, these processes are fine-tuned by a number of extracellular cues, which exert their effects by regulating intracellular signaling pathways.

    In summary, many lines of evidence exist that suggest estradiol has many critical roles in corticogenesis (Figure 6). Hitherto, no clear mechanism has been established. Substantial evidence purports to show a connection between estradiol, migration, and neurogenesis. A strong body of evidence exists showing that estradiol influences the proliferative body within the subventricular zone, which increases the availability of NSCs. The mechanism underlying this action has not been established but may be associated with Pax-6, neurogenins, and nestin.

    Distal Dendritic Enrichment of HCN1 Channels in Hippocampal CA1 Is Promoted by Estrogen, but Does Not Require Reelin

    Mechanisms of learning and memory require a fine-tuned interplay between ion channels on hippocampal neurons.

    the dendritic localization of HCN1 channels, a critical determinant of their function, is influenced by estrogen (E2), thus bringing attention to the modulatory roles of sex hormones on hippocampal information processing, which are yet poorly understood.

     the subcellular distribution of HCN1 channels in CA1 is influenced by estradiol but does not require Reelin, as previously proposed (Kupferman et al., 2014).


    Complement C3 Affects Rac1 Activity in the Developing Brain

    The complement system, which is part of the innate immune response system, has been recently shown to participate in multiple key processes in the developing brain.

    Complement acts as a rapid and efficient immune surveillance system that has distinct effects on healthy and altered host cells and foreign intruders (reviews Walport, 2001a,bZipfel et al., 2007Ricklin et al., 2010Hawksworth et al., 2017). The complement system is composed of a large family of proteins, which are either secreted or membrane bound. These proteins are usually inactive until the system is triggered by stimuli. Complement is activated by three major routes: the classical, the alternative and the lectin pathways, all of which converge on complement component C3, a central molecule in the system that ultimately drives complement effector functions, including the elimination of pathogens, debris and cellular structures. Several complement proteins are cleaved during activation of the system; for example, C3 is cleaved into two fragments, C3a and C3b.

    Collectively, our findings implicate Rac1 as one of the important downstream mediators of complement activity within the developing brain of the mouse embryo.

    Reelin Signaling Inactivates Cofilin to Stabilize the Cytoskeleton of Migrating Cortical Neurons

    Neurons are highly polarized cells. They give rise to several dendrites but only one axon. In addition, many neurons show a preferred orientation.

    The student of the mammalian cerebral cortex is impressed by two phenomena pointing to a well-ordered, non-random structural organization. First, there is the arrangement of cortical neurons in layers as seen in Nissl-stained sections or in sections immunostained using layer specific markers. Second, there is an almost uniform vertical orientation of the vast majority of cortical neurons.

    From a cell biological point of view numerous questions arise after this short description of cortical organization. Numerous researchers have dealt intensely with these questions during the last decades.

    With the discovery of Reelin, the molecule deficient in the reeler mutant, research in this area has exploded and our understanding of layer formation in the cortex and of the different players involved has significantly improved.

    Hyperphosphorylation of Tau is a hallmark of Alzheimer’s disease, suggesting an involvement of the Reelin signaling cascade in the pathology of this disorder but further work is needed to obtain a clearer picture.

    Reelin-induced stabilization of the leading process, likely by the phosphorylation of cofilin, is an essential step in the proper orientation and migration directionality of late-generated cortical neurons.

    future studies need to find out how Reelin in the MZ induces both branching and stabilization of the actin cytoskeleton by cofilin phosphorylation.

    many other molecular players such as molecules of the tubulin cytoskeleton (e.g., Meseke et al., 2013Förster, 2014), proneural transcription factors such as Rnd proteins (Pacary et al., 2011), and CLASP2 (Dillon et al., 2017) are also known to control the cytoskeleton of neuronal cells and extension and orientation of the leading process, migration by nuclear translocation associated with a myosin II-dependent flow of actin filaments (He et al., 2010), and eventually layer formation in the cerebral cortex.

    Potential Role of Microtubule Stabilizing Agents in Neurodevelopmental Disorders

    Microtubules (MTs) hold a fundamental role in regulating all the steps of neurons and therefore brain development.

    MTs are basic elements of the cytoskeleton composed of ?- and ?-tubulin heterodimers. Together with actin microfilaments and intermediate filaments (called neurofilaments in neurons), they constitute the cytoskeleton, the dynamic structure that gives the cell its shape and mechanical resistance to deformation. ?- and ?-tubulin form linear protofilaments, the basis of MTs polar structure, where ?-tubulin monomer is pointing towards the fast growing “plus-end”, and ?-tubulin is located at the slower growing “minus-end” [8].

    Centrosome, MTs and MTs-related proteins are essential players in all the steps of brain development, from proliferation and migration to differentiation and synaptic network formation.



  197. 197
    gpuccio says:


    Acartia Bogart/ William spearshake?


    After all, it’s really true that old friends come back. Of all sorts! 🙂

  198. 198
    ET says:

    Ed George argues like Acartia/ Spearshake, and they just happen to work in the same type of facility. Also Acartia has boasted about having pro-ID sock puppets here.

  199. 199
    OldAndrew says:


    Natural selection explains how life has evolved over millions of years from more primitive forms

    There’s a disconnect in the meaning of the word “explain.” I think I understand what you mean, that in a general sense, natural selection describes a mechanism or process.

    The problem is that we can’t call something an explanation in a general sense unless it explains something in a specific sense.

    I’m not saying that we need a Darwinian explanation for every single thing that exists, or for most things. Just some things. In other words, in order to conclude that Darwinian evolution is likely a good explanation for ‘how life evolved from primitive forms,’ we need at least a handful of explanations showing how it explains something concrete.

    Research papers cited as such explanations tend to describe the differences themselves without any explanation whatsoever of how they came to be. They sprinkle assertions that the changes “evolved” or were “selected”, but fail to explain the basis for such assertions.

    They tend to follow a certain pattern. We’re going to show how X evolved from Y. Then they cite genetic and/or regulatory differences between X and Y, sprinkling in the words “evolved” and “selected.” No mention is made of other simultaneous changes which are required.

    Then comes the big misdirect: It’s asserted that our new understanding of the underlying differences between X and Y ‘increase our understanding’ of how Y “evolved.” It’s a misdirect because it magically asserts a previous understanding which has been ‘increased.’ It also equates increased understanding of the thing that they claim evolved by Darwinian mechanisms with how that thing evolved by Darwinian mechanisms.

    The result? More peer-reviewed research cited as evidence for Darwinian evolution. And more, and more, and more. It piles up. There’s no shortage of research to cite if you’re trying to prove that Darwinian evolution is supported by solid evidence. That is, as long as you don’t read any of it carefully.

  200. 200
    jawa says:

    That’s a clear explanation.
    Let’s hope PavelU understands it too.

  201. 201


    I have not followed the literature to the extent necessary to make a conclusion on this one way or the other.

    Enough said. Yet, oddly, you know the solution to the problem is for ID proponents to get to work.

    However, going on the premise that you are correct, most journals accept articles that draw evidence presented in other papers to support the hypothesis being presented in the submitted manuscript.

    There are no major journals that will publish a paper in open support of design in biology. This is a very old (and quite effective) head-in-sand tactic, with a rather long and repulsive societal history. And, frankly, it is always followed by the same line of counter argument as you have done:

    Do you know if anyone has attempted to submit a manuscript to a journal that compiles the overwhelming evidence that already exists in the literature supporting ID? If such an attempt has been made, the follow-on responses to the published paper would be very informative. As would the responses from the reviewers should the paper have been rejected.

    No sir! It’s not that the pearly-white good folk on the West side have stacked the jury, it’s that them negra folk on the East side just need to do a better job of defending themselves in our court, or better yet, just stay outta trouble to begin with.

    We can either make attempts to advance the ID theory within the current scientific infrastructure or we can whine and complain that the science community is unfair. It has been my experience that whining and complaining only further isolates a person’s view, even if it is the correct one.


    Let me ask you a question.

    In the 1860’s Charles Sanders Peirce suggested that any object that acted as a symbol (i.e. has a “stands for” relation) to convey meaning must logically be part of a triadic relationship between a) the symbol vehicle itself, b) its referent, and c) an interpretant, that must establish what is being specified by the token. This all made good sense, given the universally accepted fact that the Periodic Table contains no semantic measurement. Later, in the 1930’s, Alan Turing built-in this same triadic architecture (of representations, referents, and interpretants) into his programmable machine, which Jon Von Neumann then used to predict the material and organizational requirements of an autonomous open-ended self-replicator. Von Neumann’s predictions were then experimentally confirmed by Crick’s discovery of a linear code in DNA and his subsequent prediction that a set of Peircean constraints would be found at work in the system (which were themselves confirmed as by Hoagland and Zamecnik). Those Peircean constraints turned out to be the set of aminoacyl synthetases (aaRS) that perform a double-recognition and bind a particular amino acid to a particular tRNA adapter prior to the act of translation.

    Those aaRS are synthesized from nucleic memory, and it stands to reason that there was once a time in earth’s history that none of the set of aaRS had ever been synthesized from that memory. Here is my question: Regardless of what anyone thinks preceded that time, at the point in earth’s history that the first ever aaRS was successfully synthesized from memory, how many of the other aaRS had to be in place?

    I guess that depends on whether or not you believe the safety of your drinking water, environment, food, etc. is important.

    Let us say that neighbors in my area, young and old, kept falling ill with waterborne sicknesses, and the Water Commissioner did nothing but test and re-test the water quality at the treatment facility, even though advocates had produced ample evidence that the source of the problem was located downstream on property operated by the City’s largest (and most politically active) employer.

    Indeed, you might be the last person I want sitting on my city council.


  202. 202
    gpuccio says:


    I commend you for your deep knowledge of our kind interlocutors! 🙂

  203. 203
    ET says:

    It’s like finding shark teeth on the beach. Once you know what you are looking for they are actually hard to miss. 😎

  204. 204
    Ed George says:


    Enough said. Yet, oddly, you know the solution to the problem is for ID proponents to get to work.

    I am not claiming to know the solution. I am merely recommending an approach> Frankly, I think the problem is intractable, but I believe that action is better than inaction.

    There are no major journals that will publish a paper in open support of design in biology.

    All I asked is whether it had ever been done. If this has been attempted and rejected, I would dearly like to see the comments from the reviewers that rejected it. It would be very interesting to post them here (or elsewhere).

  205. 205
    PavelU says:

    ET @179:
    bill cole @183:
    OldAndrew @199:

    “By abandoning the uniform distribution assumption, questions ranging from the apparition of sudden major stages of evolution, the emergence of ‘subroutines’ in the form of modular persistent structures and the need of an evolving memory carrying information organized in such modules that drive evolution by selection may be explained.”

    Algorithmically probable mutations reproduce aspects of evolution, such as convergence rate, genetic memory and modularity

  206. 206
    PeterA says:


    Saying “may be explained” doesn’t help you much.

    They must explain it comprehensively and coherently well.


    That didn’t work. Try again.

  207. 207

    The answer, Ed, is that it takes all of them that are required to describe the constraint.

    – – – – – – – – – – – –

    I apologize that I am unwilling to spend my time trying to convince a skeptic of the rules surrounding journal publication, or even, offering ID any intellectual legitimacy whatsoever. Its hardly a secret. Frankly, I am just not interested in pretending its an assumption.

  208. 208
    ET says:

    PavelU- Natural selection is actually a process of elimination, so clearly your reference doesn’t support Darwinian evolution.

  209. 209
    PavelU says:

    ET @179:
    bill cole @183:
    OldAndrew @199:
    PeterA @206:
    ET @208:

    “The interplay of the evolvability of organisms from the persistence of such structures also explains two opposed phenomena, recurrent explosions of diversity and mass extinctions, phenomena which have occurred during the history of life on Earth that have not been satisfactorily explained under the uniform mutation assumption. The results suggest that extinction may be an intrinsic mechanism of biological evolution.

    In summary, taking the informational and computational aspects of life based on modern synthesis to the ultimate and natural consequences, the present approach based on weak assumptions of deterministic dynamic systems offers a novel framework of algorithmic evolution within which to study both biological and artificial evolution.”

    Algorithmically probable mutations reproduce aspects of evolution, such as convergence rate, genetic memory and modularity

  210. 210
    ET says:


    Intelligent Design is NOT anti-evolution so please stop with the equivocating already.

    And you have FAILed to make your case that your sited articles support your claim.

  211. 211
    jawa says:

    what’s going on here?

    is this PavelU a robot? It seems to behave like one.

    I don’t recall seeing more boring off-topic comments than his (or her?)

    and s/he doesn’t seem to react to what others tell him/her.

    buddy, wake up and smell the flowers!
    chill out!
    get a life!

  212. 212
    PeterA says:


    you may want to be nicer when addressing other people.

    just a friendly advice. Thanks.

  213. 213
    OldAndrew says:


    The paper you’ve cited twice doesn’t really add anything. Recalling your earlier point:

    Natural selection explains how life has evolved over millions of years from more primitive forms

    My response is that an explanation that purports to explain much must also explain little. It might make sense to accept natural selection as a general explanation if it explained something specific.

    I’d settle for something really, really small, provided that it includes some complex new function, as opposed to a convenient loss of function. I realize that’s vague. I’m not trying to set myself up to move the goalposts. I’m trying to be generous.

    Mathematical models (which by the way, also produce no new complex functionality) aren’t an answer. What is required is a Darwinian explanation of something, anything, which demonstrates that it can generate new complexity. And when I say a Darwinian explanation, I mean an explanation that includes the Darwinian mechanisms: what varied, and why was it selected, with no details glossed over?

    Is it not reasonable that a theory which explains everything can also explain something?

    One could set the bar even lower. Rather than providing a concrete example, provide a decent hypothesis. But if it doesn’t include the actual mechanisms of Darwinian evolution – the variation and the selection – then really, what is it? It’s just nothing.

    I’ve been down this road before, and I’m not enthusiastic. Typically the next step is that someone posts links to a bunch of papers along the lines of what I described at 199. Or examples that involve loss of existing function. Or, my favorite, papers the individual hasn’t actually read where the author explicitly says that what he observed contradicts Darwinian predictions.

    Then they say, “See, no matter how much evidence someone shows you, you won’t accept it.”

  214. 214
    bill cole says:

    Hi PavelU From the paper you cited

    Central to modern synthesis and general evolutionary theory is the understanding that evolution is gradual and is explained by small genetic changes in populations over time [1]. Genetic variation in populations can arise by chance through mutation, with these small changes leading to major evolutionary changes over time. Of interest in connection to the possible links between the theory of biological evolution and the theory of information is the place and role of randomness in the process that provides the variety necessary to allow organisms to change and adapt over time.

    Why would you expect that random changes to a sequence would do anything else but move it toward non function over deep time? Take your cell phone and make random changes to your friends numbers. Select by creating a new friend if the change finds another friend. How long do you think it will take for your direct dial not to work at all at 10 random changes per day?

    The problem for biology is hundreds if not thousands of orders of magnitude harder then this test which will fail every time.

    In biology this problem is avoided by purifying selection and dna repair. The problem is both these mechanisms minimize variation where the diversity of life requires lots of variation.

  215. 215
    gpuccio says:

    To all:

    As said, some adult cell types have a special need of cell migration tools and mechanosensing to implement their specific funtions.

    Immune cells are certainly in that group.

    Here is a recent review about mechanosensing in immune cells:

    Mechanosensing in the immune response


    Cells have a remarkable ability to sense and respond to the mechanical properties of their environment. Mechanosensing is essential for many phenomena from cell movements and tissue rearrangements to cell differentiation and the immune response. Cells of the immune system get activated when membrane receptors bind to cognate antigen on the surface of antigen presenting cells. Both T and B lymphocyte signaling has been shown to be responsive to physical forces and mechanical cues. Cytoskeletal forces exerted by cells likely mediate this mechanical modulation. Here we discuss recent advances in the field of immune cell mechanobiology at the molecular and cellular scale.

    5.2 Sensing substrate stiffness

    The functional consequences of mechanosensitivity are best highlighted by the findings that mesenchymal stem cells differentiate into specific cell lineages depending on substrate stiffness

    6. Summary and future perspectives

    Recent advances in the field have made it abundantly clear that the physical environment is a strong modulator of immune cell responses. The biophysical basis of mechanosensitivity remains unclear, but likely involves forces generated by actin polymerization and myosin-based contraction, interacting with the membrane, receptor-ligand bonds and microclusters. While the signaling function of microclusters is well studied, the mechanism of their formation and spatial organization is not completely understood. In adherent cells, integrin-ECM linkages lead to focal adhesions whose growth and signaling depend on locally applied cytoskeletal forces. Thus focal adhesions act as mechanosensors which couple integrin binding and actin flow with signaling. Whether TCR-associated signaling microclusters serve a similar role in T cells is not known, but it is interesting to speculate that they might do so given the similarities in the molecular players.

    In addition to stiffness and mobility, discussed here, the topography of the environment may be important in dictating immune cell function. T and B cells navigate complex topography in the lymph nodes and thymus with extensive membrane folds on APC surfaces or fibrillar structures on follicular dendritic networks. These structures present regions of high curvature, which might recruit curvature-sensing signaling proteins and actin regulators, thereby modulating cytoskeletal dynamics. The role of topography on immune cell signaling activation is an open question for future studies.

    Future work must also consider the crosstalk between different receptors (e.g. TCR and integrins) and co-stimulatory or inhibitory receptors in determining the global cellular response to physical cues. Finally, while we have a better knowledge of how cellular forces, proximal signaling and certain functional responses depend on the physical environment; mechanical modulation of gene expression in immune cells is completely unstudied and is open for future research. A recent study showed that the nucleus undergoes dramatic deformation by actin-based forces upon T cell activation [115], suggesting possible changes in gene expression that may be mechanically modulated.

  216. 216
    ET says:

    What is even more remarkable is there are some people who think that arose spontaneously, that is via stochastic processes.

  217. 217
    OLV says:

    gpuccio (215):

    Very interesting paper.

    Here’s another related:

    Receptor-mediated cell mechanosensing

  218. 218


    You commented upthread that you enjoyed reading GP’s articles and follow on comments, I wholeheartedly agree with you on that point. GP is clearly one of the most insightful and respected contributors this website has ever had, and we are all damned lucky he is here. You also said something about the opportunistic unfairness of linking empirical ID observations to religious ideas. I assume, then, that you also appreciate the fact that GP rarely, if not ever, talks about religion on this site. (neither do I, by the way).

    We certainly agree about that as well.

  219. 219
    Ed George says:

    UB, I fully agree. My comment about ID being unfairly linked to religion was aimed at those who oppose ID, not at GP or the way he discusses it.

  220. 220


    Yes, that is how I understood you.


  221. 221
    kairosfocus says:


    for many, “Evolution” implies/is based on ideological, apriori commitment to evolutionary materialistic scientism — as Lewontin pointed out in that well-known cat out of the bag remark in NYRB.

    So, anything that suggests intelligence involved in origin of body plans (including the first living cell!) is AUTOMATICALLY “anti-evolution.” So, there is a knee-jerk reaction to reject and dismiss.

    Given the scientism, that implies also “anti-science”; i.e. the notion is that science corners the market on credible, serious knowledge (which, by implying a theory of warrant and its limits, is an epistemological, thus philosophical knowledge claim . . . it thus refutes itself).

    Evolutionary materialistic scientism is a non-starter.

    The problem is not evidence that configuration based functionally specific, complex organisation and/or associated quantifiable information [FSCO/I for short] exist — that is blatant, GP is ably laying out yet another case in point.

    The problem is not that the case of the cell includes D/RNA thus coded, multilayer, interwoven information with algoritmic function, thus language and goal/purpose-directed stepwise finite processes expressed in that language use.

    The problem is not that such things in our actual, uniform observational experience strongly indicate language-using, engineering, designing intelligence — we live in a world with trillions of cases in point.

    The problem is not that replication of cells and so wider reproduction involves processes manifesting a von Neumann kinematic self-replicator that uses coded stored information and so puts FSCO/I (and thus, design) at the heart of the OoL problem.

    It is not even that the fine tuned cosmos that we inhabits sits at a deeply isolated operating point that facilitates C-Chemistry, aqueous medium, terrestrial planet in galactic habitable zone life.

    No, the problem is ideological imposition of a self refuting but culturally dominant agenda of ideas and policies that make a suicidal march of folly seem plausible and even advantageous.

    We may have to go over the cliff for the power-centres pushing those agendas to sufficiently lose their grip, that a major re-think will have to happen.

    That, I do not look forward to, but I frankly fear it is what we are facing; with a lot of needless self-inflicted suffering, loss, chaos and massive loss of liberty under law as we face a fight to claw back our way out of the abyss.

    I don’t know if most of the agit prop foot-soldiers we see here understand the matches they are playing with and the hellish nature of the fires they are playing with.

    They need to stop, pause, and think again about the needless damage they are causing to science, knowledge and the sustainability of our civilisation.


  222. 222
    jawa says:

    Excellent commentary and timely warning. Thanks

  223. 223
    kairosfocus says:

    UB, regrettably, the heart of the debate we have is ideological, tracing to the institutionalised imposition of evolutionary materialistic scientism on science and culture alike. Thus also, the underlying worldview, which is the functional, substantial equivalent of a religion. So, when “religion” is brought up under a cloud of suspicion, what we really face is that an anti-theistic ideology seeks to monopolise not only institutions of science, education and linked public policy thus also the media (public opinion-shaping) but to discredit, marginalise and push out of the Overton Window whatever remains of ethical theism under the Judaeo-Christian, Biblical tradition in our civilisation. Massive questions are being begged, starting with the import of the moral government of our thought life and actions through known duties to truth, right reason, fairness etc, which point to the lurking IS-OUGHT gap and to the only level of reality where they can be soundly bridged and fused . . . the roots/source. Such implies, how can we have sufficient responsible, rational freedom to create, warrant and build up sustainable bodies of scientific and mathematical knowledge. Indeed, what is knowledge and how can it earn our trust. Therefore, it is necessary to go all the way back to first principles of right reason and address the logic and epistemology of science and of warranted knowledge more generally, and to address ideologies and associated worldviews, including issues on roots of reality. So, while empirical science and its implications are part of the picture, so are matters connected to the ugly, ideology, worldview and cultural agenda laced power games we face. KF

  224. 224
    kairosfocus says:

    Jawa, thanks. We sometimes need to pull back and take in the bigger picture. That will tell us WHY an extremely strong, empirically grounded case so predictably meets stiff resistance and too often unfair marginalisation dressed up in a lab coat. It’s not just science and it never was. We also have to realise that there are serious consequences that stem from imposition of a self-refuting (thus essentially irrational), inherently amoral (again irrational by undermining government of mind by duty to truth, right reason, fairness etc) ideology on science, education, media and public policy etc. Consequences that we must take boldness to put on the table despite the dismissiveness, closed-mindedness, marginalisation and scapegoating that seem to rule the roost today. Whatever slim hope of averting catastrophe hinges on this, and if we do go over the cliff, having had the courage to provide warning and analysis will help us begin to claw our way back out of the abyss. Of course, those advocating a march of folly will always deny that a cliff lies ahead. KF

  225. 225
    kairosfocus says:


    What is even more remarkable is there are some people who think that arose spontaneously, that is via stochastic processes.

    Because, their a priori commitment to ideological, institutionally dominant evolutionary materialistic scientism tells them that EVERYTHING has to reduce to blind chance and/or mechanical necessity acting on a material substrate. For, on this view, there is nothing else in reality that is there to act. So, they will cling regardless of exposing the inherent irrationality and irresponsibility.

    J B S Haldane, yet again:

    “It seems to me immensely unlikely that mind is a mere by-product of matter. For if my mental processes are determined wholly by the motions of atoms in my brain I have no reason to suppose that my beliefs are true. They may be sound chemically, but that does not make them sound logically. And hence I have no reason for supposing my brain to be composed of atoms. In order to escape from this necessity of sawing away the branch on which I am sitting, so to speak, I am compelled to believe that mind is not wholly conditioned by matter.” [“When I am dead,” in Possible Worlds: And Other Essays [1927], Chatto and Windus: London, 1932, reprint, p.209. (NB: DI Fellow, Nancy Pearcey brings this right up to date (HT: ENV) in a current book, Finding Truth.)]

    Philip Johnson’s reply to Lewontin’s cat out of the bag comments in NYRB are also right on the money:

    For scientific materialists the materialism comes first; the science comes thereafter. [Emphasis original] We might more accurately term them “materialists employing science.” And if materialism is true, then some materialistic theory of evolution has to be true simply as a matter of logical deduction, regardless of the evidence.

    [–> notice, the power of an undisclosed, question-begging, controlling assumption . . . often put up as if it were a mere reasonable methodological constraint; emphasis added. Let us note how Rational Wiki, so-called, presents it:

    “Methodological naturalism is the label for the required assumption of philosophical naturalism when working with the scientific method. Methodological naturalists limit their scientific research to the study of natural causes, because any attempts to define causal relationships with the supernatural are never fruitful, and result in the creation of scientific “dead ends” and God of the gaps-type hypotheses.” [NB: I am aware that Rational Wiki has backed away, un-announced, from the cat-out-of-the-bag direct phrasing that was in place a few years ago. That historic phrasing is still valid as a summary of what is going on.]

    Of course, this ideological imposition on science that subverts it from freely seeking the empirically, observationally anchored truth about our world pivots on the deception of side-stepping the obvious fact since Plato in The Laws Bk X, that there is a second, readily empirically testable and observable alternative to “natural vs [the suspect] supernatural.” Namely, blind chance and/or mechanical necessity [= the natural] vs the ART-ificial, the latter acting by evident intelligently directed configuration. [Cf Plantinga’s reply here and here.]

    And as for the god of the gaps canard, the issue is, inference to best explanation across competing live option candidates. If chance and necessity is a candidate, so is intelligence acting by art through design. And it is not an appeal to ever- diminishing- ignorance to point out that design, rooted in intelligent action, routinely configures systems exhibiting functionally specific, often fine tuned complex organisation and associated information. Nor, that it is the only observed cause of such, nor that the search challenge of our observed cosmos makes it maximally implausible that blind chance and/or mechanical necessity can account for such.]

    That theory will necessarily be at least roughly like neo-Darwinism, in that it will have to involve some combination of random changes and law-like processes capable of producing complicated organisms that (in Dawkins’ words) “give the appearance of having been designed for a purpose.”

    . . . . The debate about creation and evolution is not deadlocked . . . Biblical literalism is not the issue. The issue is whether materialism and rationality are the same thing. Darwinism is based on an a priori commitment to materialism, not on a philosophically neutral assessment of the evidence. Separate the philosophy from the science, and the proud tower collapses. [Emphasis added.] [The Unraveling of Scientific Materialism, First Things, 77 (Nov. 1997), pp. 22 – 25.]

    We must wake up and face the hard facts of why we are where we are and why we are heading for a cliff. Coming back to the focus of this thread, we can see why for too many, no amount of evidence, no facts about the cell and its FSCO/I will ever be enough. Empirical evidence and its import i/l/o best, empirically warranted ideologically unfettered scientific explanation was never the real issue.


  226. 226
    kairosfocus says:

    GP, pardon my wider context comments; in my view they were warranted by the meta-issues surfacing through the course of this thread, including reflections from the exchanges at TSZ. KF

  227. 227
    kairosfocus says:

    PS: Mechanosensing includes in part information-rich key-lock fitting and points to other cases such as the prong height patterns used to store coded biological information in D/RNA.

  228. 228
    PaoloV says:


    We must wake up and face the hard facts of why we are where we are and why we are heading for a cliff. Coming back to the focus of this thread, we can see why for too many, no amount of evidence, no facts about the cell and its FSCO/I will ever be enough. Empirical evidence and its import i/l/o best, empirically warranted ideologically unfettered scientific explanation was never the real issue.

    Glad you brought up this important reminder at this point, within this excellent scientific discussion thread that GP has started and directed so skillfully (as usual), which has generated an inter-website debate that eventually collapsed, for lack of reasonable communication between the two sides, basically due to the strong philosophical disparities -associated with a priori commitment to irreconcilably opposite worldview positions- that you pointed at so well, though those differences sometimes seem disguised in pseudo-scientific jargon.
    We have seen it in a few off-topic papers that PavelU has cited in this discussion lately. As GP has stated on different occasions, most scientific research papers provide facts that support the ID paradigm, though many times the text is sprinkled with pseudo-scientific terminology linked to the strong ideological/philosophical commitment of the authors -or their fear of the academic establishment that could punish any sign of heresy.

  229. 229
    gpuccio says:


    Thank you for your precious thoughts. You are always welcome! 🙂

  230. 230
    OLV says:

    gpuccio (215):

    Mechanoimmunology: molecular-scale forces govern immune cell functions

    Immune cell recognition of antigens is a pivotal process in initiating immune responses against injury, pathogens, and cancers. Breakthroughs over the past decade support a major role for mechanical forces in immune responses, laying the foundation for the emerging field of mechanoimmunology.

    immune receptor signaling is governed by a complex regulatory network involving cross-talk and feedback loops between chemical and physical signals.

    With the field of mechanoimmunology still in its infancy, further studies are required to elucidate the exact mechanisms that allow immune receptors to sense and regulate mechanical stimuli.

  231. 231
    gpuccio says:


    Thank you, from my heart, for your words.

  232. 232
    OLV says:

    This discussion thread GP has graciously produced here is strongly associated with leading-edge research on important medical-related topics. For example, the paper cited in #230 has this interesting health-related text under the “outlook” section:

    In recent years, immunotherapy has emerged as the biggest breakthrough in modern cancer treatment. With the development of chimeric antigen receptors (CARs), we are getting closer to achieving high specificity with reduced risks of off-tumor cytotoxicity, with clinical trials employing CAR T-cells achieving unprecedented remission rates (Frey and Porter, 2016). The role of mechanosensing in antigen discrimination is key to engineering improved CARs that will amplify minute differences in antigen structure to exclusively target tumor antigens. To this end, a deeper understanding of TCR-mediated mechanosensing is required. Key functional insights will no doubt continue to emerge with the design of ever-improving tension probes (Liuet al., 2017) and the development and refinement of novel biophysical tools. Improved in vivo imaging capabilities will likely be crucial, since immune cells move through and operate in such a variety of mechanically distinct 3D microenvironments within organisms. The ability to visualize cells in intact tissues directly will deepen our understanding of the unique mechanobiological mechanisms regulating immune cells and the influence of the mechanical landscape on their migration and functions. This is already becoming a reality, with Eric Betzig’s new adaptive optical-lattice light sheet microscope (AO-LLSM) allowing high-speed, high-resolution in vivo imaging of dynamic subcellular processes in 3D (Liu et al., 2018b). By combining this technology with genetically expressed force sensors, we may soon be able to map molecular-scale mechanical forces in and on cells deep within the complex tissues of living organisms.

  233. 233
    OLV says:

    gpuccio (215):

    Membrane Ultrastructure and T Cell Activation

    The immune system serves as a crucial line of defense from infection and cancer, while also contributing to tissue homeostasis. Communication between immune cells is mediated by small soluble factors called cytokines, and also by direct cellular interactions. Cell-cell interactions are particularly important for T cell activation. T cells direct the adaptive immune response and therefore need to distinguish between self and foreign antigens. Even though decades have passed since the discovery of T cells, exactly why and how they are able to recognize and discriminate between antigens is still not fully understood.

    we would like to know: (1) what is the typical resting organization of a receptor expressed by a T cell, and what do exceptions to this behavior imply; or is the distribution of receptors and signaling proteins on the resting T cell surface best described as random? (2) What sub diffraction-limited ultrastructural changes accompany and, perhaps, drive early signaling, if any? (3) How and why do microclusters form, and how do they relate to microvilli, if at all? (4) Are membrane protrusions essentially all the same structures? (5) Why do T cells interrogate their targets using membrane protrusions, in any case? We can expect more surprises.




  234. 234
    gpuccio says:


    Thank you for the very good contributions. I am looking at those papers with great interest.

    T cell function is another deep subject! 🙂

  235. 235
    ET says:

    Alan Fox chimes in with:

    Still seems the usual “ooh, how complex!” argument

    Whatever, Alan. We have noticed the total FAILure of you and yours to offer up anything that would support the claims of your position. It’s as if you don’t have anything beyond denial of the design inference, which is based on your willful ignorance.

  236. 236
    gpuccio says:

    To all (courtesy of OLV):

    Wow, mechanoinmmunology!


    To efficiently defend an organism against injury, infection, and cancer, leukocytes must orchestrate a complex multiscale chain of events. For decades, immunological research focused on identifying cellular and molecular players that mediate the intricate interplay between cells of the innate and adaptive arms during a concerted immune response.

    As for all animal cells, actin-mediated force generation is the main driver of migration in leukocytes, which navigate an array of barriers and tissues of differing architectures either by responding to complex guidance cues or by employing highly evolved search mechanisms (Munoz et al., 2014; Weninger et al., 2014). Leukocytes are therefore endowed with considerable plasticity in shape and migratory regulation (Renkawitz and Sixt, 2010), as they continually probe and respond to the geometry and mechanical cues provided by their environment (Hallmann et al., 2015). When an immune cell eventually encounters a target cell, it will physically “grasp” it and form a specialized synaptic interface, exerting forces on its conjugate in order to deliver its functions (Lim et al., 2011; Basu et al., 2016; Spillane and Tolar, 2017). In addition to these forces acting at the cellular level, recent progress in the field has demonstrated that immune receptors themselves respond to mechanical stimuli during antigen recognition, which is crucial for efficient discrimination of antigens. Indeed, mechanical forces acting directly on individual receptors influence receptor triggering and downstream intracellular signaling.

    In T-cells, this includes differentiation (O’Connor et al., 2012), gene expression, cell migration, morphology, and cytokine secretion (Saitakis et al., 2017), whereas in B-cells, proliferation, class switching, and antibody production are all influenced by substrate rigidity.


    These data support a model in which ICAM-1 molecules with reduced mobility resist tensile forces exerted by the T-cell through ICAM-1/LFA-1 interactions more strongly, which in turn promotes firmer adhesion and maturation of the immunological synapse.


    One of the most recent breakthroughs in the field of immune receptor triggering has been the discovery that the TCR forms ligand-induced “catch bonds” (Liu et al., 2014; Das et al., 2015). Catch bonds are characterized by lifetimes that lengthen with increasing force applied on the bond until a threshold force has been reached that results in increased frequency of bond rupture (Figure 1A). This is markedly different from “slip bonds,” which are immediately destabilized when they experience force. Catch bond behavior was first described for selectins (Marshall et al., 2003) and integrins (Kong et al., 2009) and shown to promote cellular adhesion.


    When these findings are considered as a whole, a unifying model emerges in which a force-induced mechanical switch occurs in the TCR upon receptor engagement, driving conformational changes and receptor clustering, and thus leading to robust intracellular signaling and effective cell activation. Receptor clustering has also been linked with activation in B-cells (Mattila et al., 2013) and NK cells (Pageon et al., 2013; Oszmiana et al., 2016).

  237. 237
    Mung says:

    gpuccio, you’d think those buggers were cooperating autonomous agents the way they talk about them. 🙂

  238. 238
    Mung says:

    I just assume that everyone here is an Alan Fox sock-puppet, including gpuccio (but excluding Erasmus Wiffball)!

    Makes things so much simpler.

  239. 239
    Mung says:


    BTW, do you agree that they seem to weaken the ID position?

    I’ll need to take a closer look. My initial impression is no.

    An oft lodged complaint against ID is that information theory is not applicable to biology. In that light the papers actually strengthen ID because they show the “critics” to be wrong about that.

  240. 240
    ET says:


    I just assume that everyone here is an Alan Fox sock-puppet, including gpuccio …

    What has gpuccio ever done to you to deserve that?

    The day Alan Fox can put together a coherent argument is the day I am going to start drinking, again.

  241. 241
    gpuccio says:


    Alan Fox chimes in with:

    Still seems the usual “ooh, how complex!” argument

    Why must they always confirm what I say?

    A quote from my comment #165:

    I write OPs like this one because I think that it is good to understand, myself, and to share with others, how functionally complex biological realities are, ad how our understanding of that complexity grows daily. That’s why I try to add new and very recent papers as often as I can.

    Some of our kind interlocutors, in the rare cases when they choose to comment on those OPs, briefly state that the things I say may be correct or even interesting, but that they do not understand how they support ID, or better how they may be a problem for neo darwinism.

    Well, are they kidding?

    Look, it’s really simple. There is not a lot of philosophy, or of intricate reasoning there.

    The more biological realities are shown to be functionally complex, the more it is simply ridiculous to believe that they can be explained by the neo-darwinian theory.

    Not difficult to understand.

    Because if neo-darwinism cannot even explain one single protein that has more than 500 bits of FI, how can it even start to try to explain Focal Adhesions? Or the Adhesome? Or neuron migration?

    It’s simple: the more things are functionally complex, the more we are certain that they are designed.

    So, Alan, it’s exactly that, you are right:

    “ooh, how complex!”

    That’s exactly the argument. Something we observe in biological beings is too complex for your theory, and by far, and we can certainly infer design for it.

    Because, you know, the theory that you spend so much time criticizing is called Intelligent Design Theory, and it is about inferring design from functional complexity.

    In case you have never noticed.

  242. 242
    gpuccio says:


    You must be confused: of course I am your sock-puppet! 🙂

  243. 243
    ET says:

    Alan Fox is most likely one of Mung’s sock puppets, too. 😎

    And yes, gpuccio, it is always better to try to mock then to actually engage. But they will continue to threaten us with upcoming contrary evidence and rational, refuting arguments. Just the anticipation is burning calories. 😎

  244. 244
    EugeneS says:

    Even to describe that mind-boggling functional complexity, creativity and functional complexity are required. No hope for a ‘stones colliding in space to produce life’ scenario.

  245. 245
    gpuccio says:


    Hi Eugene! A pleasure to hear from you. 🙂

  246. 246
    EugeneS says:

    PavelU re algorithmic mutations #205.

    Have a look here for a case study.

  247. 247
    EugeneS says:


    Thanks very much!
    I am snowed under many things these days but I make it here as often as I can.

  248. 248
    EugeneS says:

    ET 216

    Absolutely! They should start asking themselves questions. A first one perhaps is, why are we using the ‘stochastic process’ misnomer? ‘Process’ already means ‘telic’, which stochasticity is not by definition.

  249. 249
    ET says:

    Oh my- Now Alan says:

    I have no idea what “Intelligent Design Theory” is and have asked for a scientific ID hypothesis many times at UD when I could post there. I seriously doubt any “Intelligent Design” theory or hypothesis exists.

    Alan is either lying or he is willfully ignorant as such a thing has been posted here @ UD and over on TSZ. The problem is Alan cannot grasp any of it and he definitely cannot/ will not produce anything that we can compare that too- you know for evolution by means of blind and mindless processes.

  250. 250
    gpuccio says:


    Really he has no idea what Intelligent Design Theory is?

    But then why does he waste his time criticizing something he has no idea of?

  251. 251
    gpuccio says:

    Alan Fox at TSZ:

    In a nutshell:

    Objects exhibiting high FI levels (for example more than 500 bits) are always the result of a design process by a conscious agent.

    That’s what the theory is. Right or wrong, you now know what it is.

  252. 252
    ET says:

    In response to gpuccio Alan posts:

    I dunno, I’d hardly call that a theory. An untestable hypothesis, perhaps.

    I dunno, Alan. What do you have that is testable? Ante up or prove that you have nothing but whining.

    You have already admitted that no one knows how to test the claim that ATP synthase evolved by means of natural selection and drift.

    You have no clue how to test your version of evolution that has the environment designing such structures.

    We have said exactly how to test our claims and exactly what will falsify them. To say otherwise is a blatant lie

    You can continue to BS your way through this but everyone sees what you are doing- denying documented history and scientific evidence.

  253. 253
    gpuccio says:

    Alan Fox at TSZ:

    It’s more than a theory: it’s a general paradigm.

    And it is testable: you can test it with any object whose origin is independently known.

    And it is falsifiable: you just need to show one object exhibiting FI higher than 500 bits whose origin does not involve a design process.

  254. 254
    kairosfocus says:

    GP, yup. It is over a decade since I challenged, set up a network of PC’s to generate random text — use a Schottky diode noise source flattened into white noise [e.g. Johnson counter] then feeding text strings at demonstrable random — to form meaningful text in English of above 72 to 143 ASCII characters. BTW, that is a technique used in lotteries. That, properly documented, would kill ID on the bio side. Wiki reports, 19 – 24 ASCII characters, and it is well known from stat mech why the challenge is insuperable. Long functionally specific config based text strings are strong signs of intelligently directed configuration. Simple, and utterly unmet. Where, strings are WLOG as description languages like autocad reduce 3-d entities to strings of y/n q’s and a’s. Much of the onward objection we see is by way of finding alternative objections, this key one having collapsed. The “complexity” or “big number” dismissiveness too often comes across as a way of trying to make rhetorical silk from a sow’s ear. KF

  255. 255
    gpuccio says:


    Yes, simple and clear! 🙂

    And yet Alan Fox and others like him seem incapable to understand it!

    What’s the problem with them?

    Can’t they understand that complex functions do exist? Well beyond the threshold of 500 bits?

    Guys, just look at language, software, machines. From Paley’s wacth to Shakespeare’s sonnets to complex software, it’s a huge abundance of functional configurations well beyond the 500 bits.

    And guess what? They are all designed things.

    Or maybe they can’t accept the simple fact that complex proteins are exactly the same thing.

    But why? It is absolutely obvious.

    How can we doubt that the arrangement of thousands of AAs that makes up ATP syntase in the form of an ATP generating watermill, where “water” is a proton flux, is the same thing as a wacth, or any other machine? How can we doubt that a very complex choice of AA sequence, well beyond 500 bits of complexity, is necessary for that function to be present, even at low levels?

    So, like a watch would never come into existence without a design process, so ATP synthase would never come into existence without a design process.

    Alan, you got it without knowing:

    “ooh, how complex!”

    That’s exactly the point! 🙂

  256. 256
    gpuccio says:

    To all:

    This is about the role of calcium as second messenger, already mentioned at #81, and the neuronal growth cone:

    How does calcium interact with the cytoskeleton to regulate growth cone motility during axon pathfinding?


    • Calcium signaling regulates the cytoskeleton to control growth cone motility during axon guidance.

    • The source, amplitude and spatial regulation of calcium signals are thought to regulate the cytoskeleton at the growth cone.

    • Calcium-activated phosphorylation is the key signaling mechanism that links calcium and the growth cone cytoskeleton.

    • Direct links between the endoplasmic reticulum and the cytoskeleton are implicated in growth cone motility.


    The precision with which neurons form connections is crucial for the normal development and function of the nervous system. The development of neuronal circuitry in the nervous system is accomplished by axon pathfinding: a process where growth cones guide axons through the embryonic environment to connect with their appropriate synaptic partners to form functional circuits. Despite intense efforts over many years to understand how this process is regulated, the complete repertoire of molecular mechanisms that govern the growth cone cytoskeleton and hence motility, remain unresolved. A central tenet in the axon guidance field is that calcium signals regulate growth cone behaviours such as extension, turning and pausing by regulating rearrangements of the growth cone cytoskeleton. Here, we provide evidence that not only the amplitude of a calcium signal is critical for growth cone motility but also the source of calcium mobilisation. We provide an example of this idea by demonstrating that manipulation of calcium signalling via L-type voltage gated calcium channels can perturb sensory neuron motility towards a source of netrin-1. Understanding how calcium signals can be transduced to initiate cytoskeletal changes represents a significant gap in our current knowledge of the mechanisms that govern axon guidance, and consequently the formation of functional neural circuits in the developing nervous system.

    (Some section titles:)

    Intracellular and extracellular calcium signals guide growth cone motility

    How are the spatial localisation, amplitude and source of calcium integrated to determine growth cone motility?

    Calcium controls the growth cone cytoskeleton by regulating phosphorylation signalling cascades

    Calcium activated phosphorylation regulates plasma membrane remodelling

    The ER and SOCE: connecting calcium to the cytoskeleton?


    One of the most consistent and highly conserved signalling mechanisms in axon guidance described so far is the crucial role that cytosolic calcium plays in growth cone motility. However, the complete repertoire of biophysical mechanisms responsible for the unerring precision and fidelity of axon guidance have yet to be fully elucidated. Second messengers such as calcium effectively transduce guidance cues to the cytoskeleton by regulating the delicate interplay of opposing physical forces such as membrane exocytosis and endocytosis to drive growth cone motility. Many of the downstream phosphorylation events that activate cytoskeletal rearrangements have been elucidated, although the final links with actin and microtubules are still unclear. Interactions between the cytoskeleton and the ER suggest that more direct links between calcium signals and the cytoskeleton may regulate motility, however since much of this work has been done in non-neuronal cells, the significance of these mechanisms in neuronal growth cones remains unclear. Understanding how calcium interacts with the growth cone cytoskeleton will move us an important step closer to understanding the factors that govern circuit formation and nervous system plasticity.

    Just one thought. Calcium is one of the most important second messengers in the cytosol:

    Calcium signaling

    How can such a simple molecule be at the core of so many cell functions, at the crossroad of so many regulatory systems? And still act in such specific ways?

  257. 257
    jawa says:

    “How can such a simple molecule be at the core of so many cell functions, at the crossroad of so many regulatory systems? And still act in such specific ways?”

    Ask PavelU. 🙂

  258. 258
    jawa says:

    “How can such a simple molecule be at the core of so many cell functions, at the crossroad of so many regulatory systems? And still act in such specific ways?”

    PavelU’s most probable answer:

    “There’s abundant literature explaining that.”

    PU should comment at TSZ where AF and JF will agree with him.

    Maybe PU is a sock puppet of AF?


  259. 259
    gpuccio says:


    Being myself a sock-puppet of Mung’s, I cannot give judgements about colleagues! 🙂

  260. 260
    ET says:

    Joe Felsenstein still, doesn’t get it:

    A massive dismissal of natural selection which will not impress evolutionary biologists.

    We cannot dismiss that which doesn’t have any supporting evidence. The Hitchen’s gambit applies.

    If evolutionary biologists had the science and evidentiary support that natural selection was up to the task then it would be in peer-review. And yet peer-review is absent evidence for natural selection’s alleged ability to produce novel genes and multi-protein complexes.

    Don’t blame us for your obvious FAILures, Joe

  261. 261
    jawa says:

    That’s a valid point. I see what you mean.

  262. 262
    gpuccio says:


    Maybe it will not impress evolutionary biologists, but it could impress normal people with an open mind.

    The point is simply: if the function is complex, it is not there at all untill a great number of specific bits are found.

    If a function is not there, NS cannot act on it.

    This is not a “massive dismissal of natural selection”: it is simply inderstanding what it is and what it can do.

    NS is not magic. It cannot select something that is not there.

    So, it cannot select complex functions unless they are already there.

    For complex functions to be there, a great number of specific bits have to be found.

    For high complexity, that is empirically impossible.

    That’s why all the known examples of NS act on simple functional transitions: they select what happens often enough, they can’t select what does not happen because it is too improbable.

    No massive dimissal here. Simple scientific reasoning.

  263. 263
    Mung says:


    You must be confused: of course I am your sock-puppet!

    And I am an Alan Fox sock-puppet.


  264. 264
    john_a_designer says:

    gpuccio @ 186,

    I have never, never met one person from the other side who has been capable to seriously consider design as a possibility. I don’t mean accept it as the best explanation, but at least admit that it could be, in principle, an explanation.

    Never? How long have you been participating in these kind of discussions?

    This is true of all of them, even the best. When the discussion becomes uncomfortable, they must always, always shift to some ideological defense.

    That’s why, in the end, the discussion is always frustrating. Those people, even the best, are reasonable and open minded until they feel confident that they can be reasonable and open minded, because they will easily destroy the silly arguments of IDists.

    As soon as they have to face arguments from IDists that are not silly at all, they lose all the reasonable attitude, all the pretended open mindedness, and they behave for what they are: dogmatists. [emphasis added]

    That many of them act that way would not be surpising: it’s human nature.

    But that all of them, even the best, act that way is really disappointing.

    Where have all the fair minded atheists and agnostics gone? They’re not just a vanishing breed they are on the verge of extinction. That wasn’t true 12 ½ years ago when I first started commenting on the now defunct Telic Thoughts blog. Back then I did encounter open-minded skeptics who knew how to reason and argue in good faith. Sadly, like a plague, it now appears the trolls have taken over the internet. However, it’s not limited to sites like this. With political debate and discussion it’s even worse– not just on-line but on college campuses where the so-called rhetoric has evolved into an Orwellian PC brand of “newspeak.”

    The typical anti-ID troll appears to be someone who is motivated by an extreme antireligious prejudice. However, the problem with any kind of prejudice that is taken to the extreme it turns its advocate into the a bad reflection of what he (or she) hates: an incorrigible, irrational dogmatist– in other words, a fundamentalist.

    No one summed it up better than theoretical physicist and Nobel Laureate Peter Higgs, who himself is an atheist. He said this about Richard Dawkins:

    “What Dawkins does too often is to concentrate his attack on fundamentalists. But there are many believers who are just not fundamentalists,” Higgs said in an interview with the Spanish newspaper El Mundo. “Fundamentalism is another problem. I mean, Dawkins in a way is almost a fundamentalist himself, of another kind.”

    He agreed with some of Dawkins’ thoughts on the unfortunate consequences that have resulted from religious belief, but he was unhappy with the evolutionary biologist’s approach to dealing with believers and said he agreed with those who found Dawkins’ approach “embarrassing”.

    Some have suggested that the so-called new atheism is a dying trend. I don’t think so. I think after having done its damage it’s simply stopped propagating as fast. However, it’s still alive a well on-line with a lot of little Richard Dawkins clones. It’s been so successful that people of good will and good faith, whether they be atheist, agnostic or theist, do not want to be involved in the so-called discussion. Personally, it has limited my participation. I have better things to do than waste my time with self-centered pseudo intellectual trolls who have no interest in talking about fact based evidence– who think whatever they think and believe is true, because that’s what enlightened people like them think and believe. (Yes, that’s circular but the trolls don’t even understand that.)

  265. 265
    ET says:

    One has to wonder why there is a complete lack of peer-reviewed papers demonstrating that natural selection can take something with minimal function and optimize it, or whatever Joe Felsenstein is trying to claim. Jerry Coyne uses “optimize” when referring to what NS does/ can do.

    How many specific mutations are we talking about? That is how many specific mutations does it take to get a gene that codes for a protein with minimal functionality to one that is optimized for that function?

    I guess it doesn’t matter for evolutionists. Not only do they need those specific mutations but they also need those mutations to make it through the proof-reading and error-correction cycle.

    No wonder they never present any evidentiary support for their claims and it is always up to us to prove them wrong (even though there isn’t anything to disprove).

  266. 266
    ET says:

    One has to wonder why there is a complete lack of peer-reviewed papers demonstrating that natural selection can take something with minimal function and optimize it, or whatever Joe Felsenstein is trying to claim. Jerry Coyne uses “optimize” when referring to what NS does/ can do.

    How many specific mutations are we talking about? That is how many specific mutations does it take to get a gene that codes for a protein with minimal functionality to one that is optimized for that function?

    I guess it doesn’t matter for evolutionists. Not only do they need those specific mutations but they also need those mutations to make it through the proof-reading and error-correction cycle.

    No wonder they never present any evidentiary support for their claims and it is always up to us to prove them wrong (even though there isn’t anything to disprove).

  267. 267
    Mung says:


    Can’t they understand that complex functions do exist? Well beyond the threshold of 500 bits?

    It has been pointed out over there at TSZ a number of times, e.g. by no less a figure than Tom English, that FI was proposed as a measure of complexity.

    So complexity should not be the issue.

    Perhaps they know of all sorts of complex things that, when arranged in just such a way, the parts making up the whole, and the whole performing a function, came about by means that did not involve intelligent design.

    IOW, what they must challenge is the inference to design. Preferably by providing a better explanation.

  268. 268
    Mung says:


    And it is falsifiable

    If one were to find a shakespearean sonnet in the Cambrian?

    Is Alan Fox a Popperian? Does he think theories in biology ought to be treated the same way as theories in physics?

  269. 269
    ET says:

    gpuccio, kairosfocus, Mung, Upright Biped, JAD, et al:

    Lest we forget, they always can fall back on constructive neutral evolution– The scenario in which proteins diffusing through the cell can just hook up with another protein doing the same. That process continues until Voila! your complex multi-protein machine is at hand.

    The problem with that is it’s just a one-off solution which may never be repeated in any other organism.

    Which brings us to another point that Jonathon Wells brought up years ago- assembly instructions. Meaning not only is the part IC the assembly instructions are also IC. Do evolutionists think that the assembly instructions are also physical parts or do they say they don’t exist which would mean that there is a high degree of precision and accuracy in blind and mindless molecules diffusing through cells creating al of the necessary machinery it needs to function.

  270. 270
    Mung says:


    This is not a “massive dismissal of natural selection”: it is simply inderstanding what it is and what it can do.

    What if something with 500 bits of FI already exists? Could natural selection “optimize” it such that it has 1000 bits of FI?

    I apologize if you have already answered this question.

  271. 271
    Mung says:


    Lest we forget, they always can fall back on constructive neutral evolution…

    I never forget that. I regularly ask why evolutionary processe such as neutral evolution and random genetic drift cannot, according to the theory of evolution, bring about the appearance of design.

    The argument that creationists misunderstand the theory or misrepresent it as being a theory based on chance because they leave out natural selection, is a red herring.

  272. 272
  273. 273
    gpuccio says:


    Very good thoughts, thank you! 🙂

  274. 274
    gpuccio says:


    “It has been pointed out over there at TSZ a number of times, e.g. by no less a figure than Tom English, that FI was proposed as a measure of complexity.”

    Well, Joe Felsestein also acknowledges FI as a concept, even if he makes very ambiguous statements about it.

    However, there are many at TSZ (and here too, sometimes) who seem to deny the concept itself.

    And the scientific literatur, in particular, does not seem too interested to it. While some rarely acknowledge that functional complexity is a problem and requires some explanation (usually to introduce their personal and imaginary explanation which does not explain anything), and while Szostak’s paper is certainly a good start, I am not aware that relevant work has been done about the issue.

    After all, Szostak’s paper is of 2007. What has happened after?

    “IOW, what they must challenge is the inference to design. Preferably by providing a better explanation.”

    Am I unfair if I am not holding my breath?

  275. 275
    gpuccio says:


    Wow, constructive neutral evolution. Or simply neutral evolution. Old gimmicks! 🙂

    Yes, that’s the trend. You show them that NS cannot do it, and they mention neutral evolution, constructive or not.

    You show them that neutral evolution cannot do it, and they go back to NS.

    OK, no form of neutral evolution can change in any way the probabilistic barriers.

    IOWs, the reason why neutral evolution, in all its forms, cannot do it is exactly the same as the reasone why mere chance cannot do it: the probabilities are too low. It’s empirically impossible.

    I will just quote a paragraph from the page you linked. I suppose it’s Larry Moran speaking:

    Imagine an enzyme “A” that catalyzes a biochemical reaction as a single polypeptide chain. This enzyme binds protein “B” by accident in one particular species. That is, there is an interaction between A and B through fortuitous mutations on the surface of the two proteins. (Such interactions are common as confirmed by protein interaction databases.) The new heterodimer (two different subunits) doesn’t affect the activity of enzyme A. Since this interaction is neutral with respect to survival and reproduction, it could spread through the population by chance.

    Emphasis mine.

    The problem is all in that “could”. Yes, it’s not impossible. But any variation that is neutral, whatever it is, could spread thorugh the population by chance, and thereofre no variation is more likely to spread than any other.

    It’s rather simple, after all.

    Neutral variation just tests one of the possible states. It can expand, but all possible states, if neutral, have the same probability to expand. The random search/random walk remains the same.

    The “constructive” addition just measn: if we are very, very lucky, it will be constructive variations to expand.

    But that “very, very lucky” is beyond any empirical range of probabilistic resources, when the complexity of the result is high enough.

  276. 276
    gpuccio says:


    “What if something with 500 bits of FI already exists? Could natural selection “optimize” it such that it has 1000 bits of FI?”

    Very good question.

    I will answer in two parts:

    1) The answer is no. If the additional 500 bits of FI are necessary to generate a new function, even if it is a function that reutilizes the already existing 500 bits of FI, the reason for that answer is obvious. 500 bits of FI are always beyond the range of RV, for a new function. Or even for a basic re-engineering of an old, and already complex function.

    2) But what about simple optimization? Could an already existing function be optimized by adding 500 more bits of FI, while the function remains essentially the same?

    Again, the answer is no.

    Because optimization of an existing function is always a rather short path. That is clear in all the cases of optimization by NS that we know of, like penicillin resistance, where a few AAs at most are added to optimize the function, even if each single variation increses it and is therefore naturally selectable.

    While thi sis an empirical observation, there is of course a very good reason for it. The ways that a complex function can be optimized by simple variations are very limited. Even in experimental protein engineering (like in the Szostak ATP paper) only a few substitutions really add to the function in a continuous pathway.

    The rugged landscape experiment demonstrates the same thing. The pathways are rugged and different. There is no continuosu pathway that can generate a complex solution. The wildtype, the really complex sequence, cannot be reached by NS, even in the presence of a basic function that is conserved.

    So, the answer is no, twice.

    No for any new function, or basically re-engineered function.

    No for optimizations: they certainly happen, but they are always, in the end, rather simple.

  277. 277
    ET says:

    At least constructive neutral theory shows some imagination. It also shows “they” understand natural selection isn’t as Charles Darwin imagined. The only problem is imagination is neither science nor evidence.

  278. 278
    jawa says:

    gpuccio @275:

    The problem is all in that “could”.


    I could be an experienced astronaut easily.

    Just have to enroll in the astronauts training and travel to the international space station or just a couple of rounds in orbit. That’s all.
    Don’t laugh. It’s much much easier for me to be an experienced astronaut than for complex functional information to be added to a protein.

  279. 279
    Mung says:

    It all boils down to an argument from incredulity, even for evolutionists.

  280. 280
    gpuccio says:


    Again, the truth is simple.

    It is an argument from incredulity.

    I am incredulous at ideas and theories that are not reasonable and that are not supported by facts.

    Why shouldn’t I?

    But of course the incredulity is only about the foolish idea that RV + NS did it.

    The design inference has nothing to do with incredulity: it is based on facts. We know that conscious design can generate complex FI. We see it happening all the time.

    Including in this post. 🙂

  281. 281
    gpuccio says:


    An experienced astronaut? Why not?

    I must say that I don’t have to reach so far to find personal impossibilities: there are a lot of simple things that I could never do. 🙂

  282. 282
    ET says:


    It all boils down to an argument from incredulity, even for evolutionists.

    I would say ID is an argument from our current knowledge of cause and effect relationships. And that we do not deny that future research can either confirm or overturn the inference for intelligent design. There isn’t anything for us to disbelieve. We have said what will falsify ID and they haven’t produced. We have said what the positive criteria is for inferring design and we have produced.

    On the other hand theirs would be an argument from wishful thinking borne in imaginationland. They won’t consider the design inference as they will never be satisfied that they are out of options and their mechanisms fall far short of the mark.

    Someone is going to have to prove. beyond all doubt, that cells and organisms are governed by immaterial information- the “elan vital” of yore comes to light thanks to our technology and the integration of hardware with software to achieve specific results without our/ external intervention.

  283. 283
    OLV says:

    gpuccio (256):

    There’s a lot of calcium in this paper too:

    Regulation of neuronal development and function by ROS

    The importance of calcium?

    The mechanisms by which physiological levels of ROS support neurite outgrowth and axon specification appear to involve release of calcium from intracellular stores, a potent second messenger regulating cytoskeletal organisation and dynamics (reviewed in 3536).  Short respiratory bursts of NADPH oxidase?generated ROS promote calcium release by redox modification of ryanodine (RyRs) and inositol?3?phosphate receptors (IP3Rs). These in turn lead to increased expression of Rac1, an activator of the NOX2 complex, thus generating a positive feedback loop that can convert initially transient ROS bursts into sustained ROS activation and high levels of intracellular calcium 34; (Fig. 1).

    H2O2 also modifies RyRs and IP3Rs triggering release of calcium from internal stores in the ER. (4) Changes in intracellular calcium modify activities of cytoskeletal regulatory proteins, directly or indirectly, e.g. via the regulation of Calcium/calmodulin?dependent kinase II (CamKII) or the phosphatase calcineurin or activation of the protease calpain. Elevated calcium levels also lead to expression of the cytoskeletal and NADPH oxidase regulator Rac1, thus generating a positive feedback loop that can amplify and sustain transient respiratory bursts 34.

    NADPH oxidase activity is subject to complex regulatory pathways, of which many are associated with neuronal activation, such as elevated intracellular calcium levels, Protein kinases C and A, as well as calmodulin and calcium/calmodulin?dependent kinase II (CamKII) 34569598.

    Interestingly, in cerebellar Purkinje neurons superoxide is required for LTD, although in these cells synaptic depression (as opposed to potentiation) requires elevated intracellular calcium concentration 113.

    And also in this paper:

    Calcium, Reactive Oxygen Species, and Synaptic Plasticity

  284. 284
    OLV says:

    NOTCH1 is a mechanosensor in adult arteries

     in vivo increases of laminar blood flow elicit proportional Notch1 receptor signaling that promotes vascular endothelial cell elongation, while maintaining cell-to-cell junctional integrity and repressing proliferation. Of note, fluid shear stress-elicited Notch1 mechanosignaling protects hypercholesterolemic mice from atherosclerosis.

    Pulling mechanical forces exerted by the endocytosis of Delta ligands unfold Notch receptors, thus allowing their cleavage and signaling {1,2}.


     Emerging Role of Plasma Membranes in Vascular Endothelial Mechanosensing

    Vascular endothelial cells (ECs) maintain circulatory system homeostasis by changing their functions in response to changes in hemodynamic forces, including shear stress and stretching. However, it is unclear how ECs sense changes in shear stress and stretching and transduce these changes into intracellular biochemical signals.



  285. 285
  286. 286
    EugeneS says:

    GP 276,

    Excellent! Copying for my records! 🙂

    This is perfectly in line with my own observations in the world of combinatorial optimization. Local search is killed by constraints because it stagnates in optima. Unless you guide it by prior experience (expert knowledge of the problem domain), nothing can be done.

  287. 287
    OLV says:


    Here’s more “cross talk” associated with mechanotransduction!

    As UB said, the discoveries keep coming…

    New developments in mechanotransduction: Cross talk of the Wnt, TGF-? and Notch signalling pathways in reaction to shear stress

    Mechanotransduction, the ability of cells to detect and react to mechanical forces, is increasingly playing a critical role in a variety of physiological and pathophysiological processes. While the focus has previously been on the MAPK, NF-?B and ROS generating pathways, ancient embryological pathways have reached little attention. Recently, a surge of new studies have been published on these pathways and their role in mechanotransduction and this review paper aims to provide a concise overview on the latest studies and brings them in to a larger perspective. Special emphasis is on the non-canonical aspects of the Wnt, TGF-? and Notch pathways and their role in flow.

    the Notch, TGF? and Wnt signalling pathways are known to be up-regulated by laminar shear stress and to play a role in endothelial function and dysfunction. Although these pathways are shear-sensitive the mechanisms of mechanoactivation are unknown and may be mediated by i) upstream mechanosensor(s) that regulate the expression of the components of the pathways, ii) known mechanosensitive pathways e.g. MAPK5-KLF2 pathway, or iii) paracrine and autocrine release of co-factors that may modulate the pathways.

    the vast majority of the studies on crosstalk between these pathways in endothelial cellshave been targeted towards understanding vascular development and angiogenesis. The role of crosstalk between these pathways in adult endothelial cells is largely unknown. Furthermore, there have been no studies on the interaction between these pathways in combination with shear stress and as such this is an important area of future study.

  288. 288
    jawa says:


    It seems like PavelU hasn’t reacted to your comment @246 where you pointed to an interesting discussion based on your article on AI Sims?

  289. 289
    ET says:

    TSZ is clueless. Mung needs to tell them that the only reason there are probability arguments in the first place is because they don’t have any way of testing their claims.

    They do NOT have a theory of eye/ vision system evolution- regardless of what OM sez. They don’t even have testable hypotheses for such a thing.

  290. 290
    john_a_designer says:

    Mung and gpuccio @ 279 & 280,

    Here is an excerpt from Dawkins book The Blind Watchmaker where he explains the so-called Argument from Personal Incredulity– a term he apparently coined. He begins with a discussion of William Paley. Please notice that Dawkins argument is not really scientific, it’s theological– because an anti-theological argument is a theological argument.

    My aim has been in one respect identical to Paley’s aim I do not want the reader to underestimate… works of nature and the problems we face in explaining them… Paley rammed home his argument by multiplying up his examples. He went right through the body, from head to toe, showing how every part, every last detail, was like the interior of a beautifully fashioned watch. In many ways I should like to do the same, for there are wonderful stories to be told, and I love storytelling. But there is really no need to multiply examples. One or two will do. The hypothesis that can explain bat navigation is a good candidate for explaining anything in the world of life, and if Paley’s explanation for any one of his examples was wrong we can’t make it right by multiplying up examples.

    His hypothesis was that living watches were literally designed and built by a master watchmaker. Our modern hypothesis is that the job was done in gradual evolutionary stages by natural selection.

    Nowadays theologians aren’t quite so straightforward as Paley. They don’t point to complex living mechanisms and say that they are self-evidendy designed by a creator, just like a watch. But there is a tendency to point to them and say ‘It is impossible to believe’ that such complexity, or such perfection, could have evolved by natural selection… [For example] in a recent book called The Probability of God by the Bishop of Birmingham, Hugh Montefiore. I shall use this book for all my examples in the rest of this chapter, because it is a sincere and honest attempt, by a reputable and educated writer, to bring natural theology up to date. When I say honest, I mean honest. Unlike some of his theological colleagues, Bishop Montefiore is not afraid to state that the question of whether God exists is a definite question of fact. He has no truck with shifty evasions such as ‘Christianity is a way of life. The question of God’s existence is eliminated: it is a mirage created by the illusions of realism’…The Bishop believes in evolution, but cannot believe that natural selection is an adequate explanation for the course that evolution has taken (partiy because, like many others, he sadly misunderstands natural selection to be ‘random’ and ‘meaningless’).

    He makes heavy use of what may be called the Argument from Personal Incredulity. In the course of one chapter we find the following phrases, in this order:

    . . . there seems no explanation on Darwinian grounds … It is no easier to explain … It is hard to understand … It is not easy to understand … It is equally difficult to explain … I do not find it easy to comprehend … I do not find it easy to see … I find it hard to understand … it does not seem feasible to explain … I cannot see how . . . neo-Darwinism seems inadequate to explain many of the complexities of animal behaviour … it is not easy to comprehend how such behaviour could have evolved solely through natural selection … It is impossible . . . How could an organ so complex evolve? … It is not easy to see … It is difficult to see . . .

    The Argument from Personal Incredulity is an extremely weak argument, as Darwin himself noted. In some cases it is based upon simple ignorance…

    I’ll admit I’m guilty of the “logical fallacy” (at least the way Dawkins defines it) of arguing from personal incredulity. For example, I personally doubt that Bigfoot or Sasquatch really exists. However, my personal incredulity, is based on the lack of sufficient evidence. It’s not because the possible existence of Bigfoot threatens my worldview it’s because the evidence for its existence is not there. I am not alone in this view.

    Is my personal skepticism about the existence of Bigfoot warranted? I don’t see how that my “personal incredulity” about Darwinian evolution any different than my personal incredulity about Bigfoot?

    Dawkins argument appears to be that since natural selection (NS + RV) can explain some evolutionary change that it explains all evolutionary change. But when or how was it proven that natural selection can explain all evolutionary change? Is it illegitimate to ask the question “how did this evolve?” For example, how did life evolve from non-life? How did DNA and RNA evolve? How did eukaryotes evolve from prokaryotes? How did metazoa evolve from protozoa? If the answer is “we don’t presently know,” aren’t I justified in remaining skeptical? Am I supposed to accept unanswered questions as answered even though they haven’t been answered? That it’s Darwinism all the way down?

    So how is the argument from personal incredulity a logical fallacy? What’s its opposite? The argument from credulity? I must believe Darwinian evolution to be a ubiquitous explanation for life even if there is insufficient evidence to accept that view?

  291. 291
    OLV says:

    Coordinated collective migration and asymmetric cell division in confluent human keratinocytes without wounding

    Epithelial sheet spreading is a fundamental cellular process that must be coordinated with cell division and differentiation to restore tissue integrity.

  292. 292
    gpuccio says:


    “I’ll admit I’m guilty of the “logical fallacy” (at least the way Dawkins defines it) of arguing from personal incredulity. For example, I personally doubt that Bigfoot or Sasquatch really exists. However, my personal incredulity, is based on the lack of sufficient evidence. It’s not because the possible existence of Bigfoot threatens my worldview it’s because the evidence for its existence is not there. I am not alone in this view.”

    Count me in!

    OK, maybe Bigfoot was credible, if compared to the magic of NS! 🙂

  293. 293
    gpuccio says:


    “So how is the argument from personal incredulity a logical fallacy? What’s its opposite? The argument from credulity?”

    Maybe blind faith. Something that seems to abound in a certain blog of kind interlocutors! 🙂

  294. 294
    OLV says:

    Notching a New Pathway in Vascular Flow Sensing

    Vascular barrier function is controlled at cell–cell junctions in response to blood flow, but how vascular endothelial cells sense and respond to flow remains to be understood. A recent study describes a flow-sensing pathway involving non-canonical Notch and cadherin signaling that sheds new light on mechanisms controlling the endothelial barrier.




  295. 295
    OLV says:

    Intrinsic Determinants of Axon Regeneration

    The failure of axons to regenerate in the damaged mammalian CNS is the main impediment to functional recovery. There are many molecules and structures in the environment of the injured nervous system that can inhibit regeneration, but even when these are removed or replaced with a permissive environment, most CNS neurons exhibit little regeneration of their axons. This contrasts with the extensive and vigorous axon growth that may occur when embryonic neurons are transplanted into the adult CNS. In the peripheral nervous system, the axons usually respond to axotomy with a vigorous regenerative response accompanied by a regenerative program of gene expression, usually referred to as the regeneration?associated gene (RAG) program. These different responses to axotomy in the mature and immature CNS and the PNS lead to the concept of the intrinsic regenerative response of axons. Analysis of the many mechanisms and issues that affect the intrinsic regenerative response is the topic of this special issue of Developmental Neurobiology. The review articles highlight the control of expression of growth and regeneration?associated genes, emphasizing the role of epigenetic mechanisms. The reviews also discuss changes within axons that lead to the developmental loss of regenerative ability. This is caused by changes in axonal transport and trafficking, in the cytoskeleton and in signaling pathways.


  296. 296
    gpuccio says:


    Interesting article at TSZ, Thank you for addressing this difficult problem. I will try to answer some of your points as I view them.

    I have done some work about counting the probabilities for mutations.

    In a post here, a lot of time ago, I tried to model the effect of NS, to demonstrate that, if true, and in the measure that it is true, it can really lower probabilistic barriers.

    This is a tricky issue, so please follow me with some patience. I will be as brief as possible, but we can deeped the details if you like.

    I must give some definitions.

    Let’s start with the probability of one event (a mutation). In general, it is accepted that the probability of mutation, especially in prokaryotes, is about 1e-10 per site per generation. I will assume this value for the following resonings.

    Then there is the probability of a certain result. In general, let’s assume a probability of 1/20 (0.05) for one specific AA.

    The number of necessary events to get some result with some probability can be computed using the binomial distribution. We consider “success” the defined result. The probability is the product of the probability of the result (for 1 AA, 0.05) by the probability of having one event in the interested sequence in one generation (for one AA, 1e-10).

    So, for one AA site, the probability of getting one specific AA at one specific site in one generation is:

    1e-10 * 0.05 = 5e-12

    Now I will use the binomial distribution to compute how many generations are necessary to have a good probability of observing the result. For all the following reasoning, I will consider as “good probability” 0.8 (80%). We could choose any other value, the reasoning would be essentially the same, with different numbers.

    So, with the assumptions I have made, the number of generations necessary to have a good probability of observing a specific AA at a specific site are:

    g1 = 3.3e11

    Let’s call it g1 for event 1 (in this case, one specific mutation at a specific site).

    It will be useful in the following reasoning to look at things from the point of view of time needed. So, we define as:


    the time needed in the system to have the necessary number of generations. In this case, for one specific AA at one specific site, it will be, in days:

    t1 = g1 / rd

    where rd are the probabilistic resources of the system for unit of time, IOWs the number of generations per day in the system.

    Now, an important point is that the system is not made of one organism or one line. The probabilisit resources are given by the average number of generarions per day multiplied by the number of reproducting organisms.

    So, just as an imaginary example, let’s say that we have a system of 1e9 bacteria, and that their average reproduction rate is 3 per day. In this case, rd will be:

    1e9 * 3 =3e9 reproductions per day

    So, the time to oberve the described event with 0.8 probability in this system is:

    t1 = g1 / rd = 3.3e11 / 3e9 = 110 days

    Now, let’s do the computation for two specific AA changes. Let’s call this defined result event 2.

    Now the probability of the result is 1/400:


    The probability of having one event in the relevant sequence (2 AAs) has now doubled, and it is:


    Therefore, the probability of having the defined result (event 2) per generation is:

    2e-10 * 0.0025 = 5e-13

    And the number of generations needed is:

    g2 = 3.3e12

    So, t2 will be:

    t2 = g2 / rd = 3.3e12 / 3e9 = 1100 days

    So, t2 is 10 times bigger than t1. That is due to the fact that the probability of the event is 20 times lower, but the number of events per generation has doubled.

    OK, I would stop here for the moment.

    A few caveats:

    a) The above computations are obviously generic schemes. I have not considered a lot of specific details, because I want here to focus on the general pattern.

    b) All the computations and the formal symbols are mine. They just mean what I have defined here.

    c) Of course, my reasoning can be wrong. I will be greatful for any detailed criticism and corrections. Consider this as a tentative formalization of the problem.

    d) Of course genome mutations are not the same thing as AA change. However, here I have discussed in terms of AA change for simplicity, not considering synonimous mutations.

    e) For the same reason, I have not considered in this simplified reasoning other important concepts, like Effective population size.

  297. 297
    PeterA says:

    gpuccio @292:

    “maybe Bigfoot was credible, if compared to the magic of NS!”

    That’s funny. 🙂

  298. 298
    PeterA says:

    gpuccio @296:

    That’s serious food for thoughts. Thanks.

  299. 299
    ET says:

    No evidence for the existence of Bigfoot? So thousands of people throughout history are lying or mistaken?

    I have never seen one but I am not going to baldly declare there isn’t any evidence for them given those thousands of accounts throughout history.

    Someone gets one on film, and try as they might no one has been able to show it was a hoax. No one can duplicate the alleged costume and movements- and the film was shot in 1967! So now the only option is to completely ignore its existence.

    Perhaps the skeptics should take up hiking and camping in remote wooded areas- places where sightings have occurred would be a start.

    I say the same about people who deny the existence of ghosts. Go spend a night or two in the allegedly haunted places and let us know how you fare.

    Just sayin’- at least bigfoot and ghosts are directly researchable whereas natural selection’s alleged ability to produce the appearance of design is not. That alleged capability only exists in the minds of evolutionists.

  300. 300
    PeterA says:

    this is funny to see this inter-website debate

    a few folks commute between the two sites while the rest remains in their respective sites

    I took a quick look at the comments that followed Mung’s article and noticed some theological nonsense by some people… do they know how to discuss science without digressing? Perhaps being clueless about the discussed topic makes them go off topic?
    Also noticed very little technical substance in many comments… are they serious?

  301. 301
    ET says:

    Alan Fox says:

    We observe that the genetic code is almost universal across all extant organisms. The parsimonious explanation is relatedness.

    Related via a common design, yes. You still need a mechanism capable of producing eukaryotes from the given populations of prokaryotes.

  302. 302
    ET says:

    Cumulative selection, as explained by Dawkins, is a telic process. Natural selection is just a process of elimination with whatever is good enough getting a chance to live and possibly leave offspring.

    There isn’t any force trying to make anything better. Evolution is not about progress. A loss of function can and does provide fitness benefits in certain scenarios.

    No one has ever tracked natural selection in the wild and observed it doing anything near what evolutionists imagine. Throwing time at the problem only proves the unscientific nature of the claims.

    The claims? Something or somethings happened in the past. Those that didn’t get eliminated were allowed to accumulate. Lather, rinse, repeat and here we are! The “theory” of evolution!

  303. 303
    PeterA says:

    ET @301:

    Assuming they have a mechanism to get the prokaryotes to begin with. Or you’re giving them the starting point for free? There’s no free lunch. 🙂

  304. 304
    ET says:

    PeterA- Evolutionists love to harp on the point that “evolution” is what happens after life appeared. So yes they have to be given starting populations. However when it is pointed out that if we eliminate the Special Creation of different Kinds then the Creation model of biological evolution is also valid, scientifically, they cannot handle it and revert to special pleading.

  305. 305
    es58 says:

    ET@304: ““evolution” is what happens after life appeared”

    1 problem here is they play quite loosely with the definition of life; they’ll usually say, with no evidence, that the first life was something far less complex than the simplest life we know of; perhaps a form that doesn’t (somehow) even contain the semiotic nature UB discusses; or, something that doesn’t have both DNA and RNA, just RNA etc; which then puts the full burden on “evolution” to, as its first task, move life into the earliest state of which we’re familiar. Which, given the burdens they already have trouble explaining (from our perspective) appears to be a massively larger task than even what they’re currently claiming. But, once you’re just waving your hands anyway, what’s one more hand wave, I guess?

  306. 306
    gpuccio says:

    Mung and all:

    So, let’s give a few more numbers.

    Always referring to the above mentioned system: 10^9 bacteria reproducing 3 times a day.

    Let’s see what happens for 3, 10, 50 and 100 specific mutations.

    3 specific mutations (let’s call this defined result event 3).

    Probability of the result per mutation in the interested sites:


    Probability of one mutation per generation:


    Probability of the result per generation:

    3e-10 * 0.000125 = 3.75e-14

    Generations needed to get 0.8 probability of the result:

    g3 = 4.3e13

    Time to oberve the result with 0.8 probability:

    t3 = 4.3e13 / 3e9 = 14333 days (about 39 years)

    Now, for 10 specific mutations:

    10 specific mutations (event 10).

    Probability of the result per mutation in the interested sites:


    Probability of one mutation per generation:


    Probability of the result per generation:

    1e-9 * 9.765625e-14 = 9.765625e-23

    Generations needed to get 0.8 probability of the result:

    g10 = 1.65e22

    Time to oberve the result with 0.8 probability:

    t10 = 1.65e22 / 3e9 = 5.5e+12 days (about 15 billion years)

    So, here we are at the age of our universe. Abundantly.

    Let’s go to 50 AAs:

    50 specific mutations (event 50).

    Probability of the result per mutation in the interested sites:


    Probability of one mutation per generation:


    Probability of the result per generation:

    5e-9 * 8.881784e-66 = 4.440892e-74

    Generations needed to get 0.8 probability of the result:

    g50 = 3.7e73

    Time to oberve the result with 0.8 probability:

    t50 = 3.7e73 / 3e9 = 1.233333e+64 days (about 3.378995e+61 years)

    And finally, for 100 specific AAs. Remember, we are still below the 500 bits threshold. 100 AAs are about 432 bits).

    100 specific mutations (event 100).

    Probability of the result per mutation in the interested sites:


    Probability of one mutation per generation:


    Probability of the result per generation:

    1e-8 * 7.888609e-131 = 7.888609e-139

    Generations needed to get 0.8 probability of the result:

    g100 = 2.05e138

    Time to oberve the result with 0.8 probability:

    t100 = 2.05e138 / 3e9 = 6.833333e+128 days (about 1.87+126 years)

    OK, that’s enough for the moment. I hope the numbers are right. Always happy for any correction.

  307. 307
    gpuccio says:

    Mung and all:

    Now, I will try to explain briefly why NS, if and when it happens, can significantly lower the probabilistic barriers. I want to clarify that because it is important, IMO, that NS is not an imaginary process. It is real, and it can be important. Recognizing its true nature and power is the necessary step to understand its severe limits.

    So, what does NS do?

    First of all, we must distinguish between negatife (or purifying) selection and positive selection.

    While both processes are based on differential reproduction (the classic survival of the fittest), they have different form.

    So, negative selection essentially keeps unchanged a variation that increses fitness, by eliminating possible further variations that could cancel the acquired advantage. Negative selection is a powerful force, and is always restrianing random variation to preserve acquired function. NS is the reason why highly functional proteins show high sequence conservation through long evolutionary times, andis the foundation that I use in measuring indirectly FI in proteins.

    Positive selection, instead, is the process that expands a newly appeared function to all the population, or to most of it. IOWs, the new functional trait appear forst in one individual and is passed to its direct descendants, but in time those descendants become the whole population, or most of it, because of their reproductive advantage.

    By the combined action of negative and positive selection the new trait becomes, in the ende, the dominant, or the only form of that protein (or function) in the population. That is called fixation. The process of fixation, however, depend mainly on positive selection, which expands the new trait, even if negative selection also contributes. Once the trait has been fixed, negative selection will act to preserve it in time.

    Now, I want to clarify that my reasonings in the precious posts deal simply with the probability of first appearance of a defined result. IOWs, the times I have computed are the times for the defined result to appear in the population.

    But of course the defined result must be fixed in the population to become a true new function in that organism.

    So, we must consider two new variables:

    a) The probability of fixation

    b) The time to fixation

    While those two parameters can be difficult to assess, a general rule states that:

    a) The probability of fixation for neutral mutations is about 1/Ne (1/2Ne for diploid populations). Ne is the effective population size, which is usually lower than the real population size. However, in the following reasonings we will assume that Ne = N, for simplicity.

    So, in our example, the probability of a neutral mutation to be fixed by drift should be approximately 1/1e9.

    Of course, if a mutation has a positive selection coefficient (IOWs, it increses fitness), its probability of fixation can be much greater, but in general it will not be 1 (IOWs, even beneficial mutations can be lost).

    b) The time to fixation, again for a neutral mutation, is in general stated to be, in generations, 4Ne. So, in our example, the time to fixation for a neutral mutation would be, approximately:

    4*1e9 = 4e9 generations

    Of course, again a positive mutation can be fixed in shorter times.

    So, let’s say that a beneficial mutation has higher probability of being fixed, and shorter time to fixation.

    In our example, time to fixation would be rather short. But in general, it depends on population size and reproduction rate, and in some cases it can be rather long. So, in general, let’s say that time to fixation has to be added to the time of appearance, and that not all beneficial mutations will be fixed.

    Again, there can be errors in my reasoning, and I am open to any correction.

    More in next post.

  308. 308
    gpuccio says:

    Mung and all:

    Now, let’s try to model what NS can do, if and when it happens.

    To do that, I will make a few extreme, non realistic assumtions, for the sake of simplicity.

    So, let’s start from out protein with 432 bits of FI (100 specific AAs) in the previous model. we know that the time for that result to appear is extremely long: about 1.87+126 years.

    Now, let’s imagine that there exists one perfect intermediate: one protein that shares 50 specific AA positions, and has some function that makes it naturally selectable.

    We know that the time needed for 50 specific AAs is about 3.38+61 years, a lot of time, but much less than in the previous case.

    Now let’s say that after that time we have our intermediate, and that by magic it undergoes perfect and instantaneous positive selection, so that it expands intsntaneously from one organism to the whole population. IOWs, it is fixed, and we are, for the moment, ignoring the probability of fixation and the time to fixation.

    Fixation has two important effects:

    1) Now we have 1e9 organisms with the 50 right AAs, and not one. IOWs, the probabilistic resources have been multiplied by 1e9.

    2) The 50 AAs that are already there will be preserved by negative NS, and will not change. Here too I am assuming a perfect effect of NS, always for the sake of simplicity. In the scenario without NS, instead, even after having found 50 correct AAs, each new mutation can equally find a new correct AAs or change one of those that have alredy been found, because there is no negative NS acting. That is a big difference.

    So, the situation with such a perfect selectable intermediate is not the same as the open scenario without selectable intermediates. It is certainlt more favourable to the final success.

    But how can we compute the probabilities in this new scenario?

    I believe that the new scenario (with all its unrealistic assumption,s, of course) can be modeled, again, by the binomial distribution.

    But this time we must not compute the number of events that is necessary to get a result with a probability of 1/20^100, but rather the number of events that is necessary to get a result with a probability of 1/10^50, twice.

    Why? Because, after we have the first event (the perfect intermediate), ad the magic fixation takes place, we are again in the same situation as at the beginning:

    a) The 50 AAs that are already there will not change any more

    b) We have the same probabilistic resources that we had at the beginning: 1e9 bacteria reproducing 3 times a day

    c) Again, we have to find 50 specific AAs.

    So, in the end, the same “success” has to happen twice.

    So, applying the binomial distribution for two successes, each of which has a probability of:

    5e-09 * 8.881784e-66 = 4.440892e-74

    (as in the case of one success of 50 specific AAs)

    the result in terms of number of events needed is:


    and in terms of time needed:

    6.8e73 / 3e9 = 2.266667e+64 days (about 6.21e+61 years)

    This is almost twice the time required for one single event, but a lot less than what is required to get 100 independent and specific AAs without any intermediates.

    So, NS is quite powerful.

    Of course, in reality things are different.

    The probability of fixation and the time to fixation will certainly make the scenario less favourable. Let’s say that we have to add an intermediate time to fixation to the computation, and that we have to consider the probability that even a favourable mutation can be lost.

    And of course, the result is still by far empirically impossible in our universe. A lot of perfect intermediates would be necessary to bring the whole process into the range of what RV can do.

    But the main point, IMO, is that such intermediates, perfect or less perfect, simply do not exist.

    There is no magic protein that shares a relevant sequence similarity with a complex function, but has nothing to do with that function, and still is naturally selectable. If we reason in terms of indepedent functional modules that can be assembled into a meta-function, that is theorically possible, even if a lot of FI is usually necessary to assemble existing modules for a new meta-function.

    But in the case of a new independent and complex function, like the function of the alpha and beta chians of ATP synthase, there is absolutely no reason for the esistence of such an ad hoc intermediate, and of course no empirical evidence of it. Leats of all of many such intermediates, each of them natirally selectable.

    So, to sum it up:

    a) NS, if and when it can happen, has a relevant power, and can lower the probabilistic barriers.

    b) However, when the probabilistic barriers are high, a lot of perfect intermediates would be necessary to change the scenario: IOWs. complex functions should be deconstructable into many simpler steps, each of them naturally selectable.

    c) There is no rationale and no empirical evidence to believe that such intermediates exist: IOWs, complex functions cannot be deconstructed into many simpler, naturally selecatble steps.

    Of course, our kind interlocutors will say again that it is my burden to demonstrate that this is impossible.

    That is simply not true, as discussed, so I will simply ignore them.

  309. 309
    gpuccio says:

    EugeneS at #286:

    “This is perfectly in line with my own observations in the world of combinatorial optimization. Local search is killed by constraints because it stagnates in optima. Unless you guide it by prior experience (expert knowledge of the problem domain), nothing can be done.”

    Absolutely true. Those smooth and long pathways to “optimization” simply don’t exist. All the available evidence (and reason itself) point to that! 🙂

  310. 310
    gpuccio says:

    OLV at #295:

    Very interesting paper. And it’s only the editorial of a whole special issue dedicated to axon regeneration.

    The interesting point is that, while CNS axons are perfectly able to grow during develoment, they apparently losa that ability after development, ar most of it. On the contrary, axons in the peripheral nervous system are capabke of very good regeneration.

    The topic is fascinating, and of course it has huge medical implications.

    Here is another paper from the special issue:

    The Virtuous Cycle of Axon Growth: Axonal Transport of Growth-Promoting Machinery as an Intrinsic Determinant of Axon Regeneration


    Injury to the brain and spinal cord has devastating consequences because adult central nervous system (CNS) axons fail to regenerate. Injury to the peripheral nervous system (PNS) has a better prognosis, because adult PNS neurons support robust axon regeneration over long distances. CNS axons have some regenerative capacity during development, but this is lost with maturity. Two reasons for the failure of CNS regeneration are extrinsic inhibitory molecules, and a weak intrinsic capacity for growth. Extrinsic inhibitory molecules have been well characterized, but less is known about the neuron?intrinsic mechanisms which prevent axon re?growth. Key signaling pathways and genetic/epigenetic factors have been identified which can enhance regenerative capacity, but the precise cellular mechanisms mediating their actions have not been characterized. Recent studies suggest that an important prerequisite for regeneration is an efficient supply of growth?promoting machinery to the axon; however, this appears to be lacking from non?regenerative axons in the adult CNS. In the first part of this review, we summarize the evidence linking axon transport to axon regeneration. We discuss the developmental decline in axon regeneration capacity in the CNS, and comment on how this is paralleled by a similar decline in the selective axonal transport of regeneration?associated receptors such as integrins and growth factor receptors. In the second part, we discuss the mechanisms regulating selective polarized transport within neurons, how these relate to the intrinsic control of axon regeneration, and whether they can be targeted to enhance regenerative capacity.

  311. 311
    EugeneS says:

    Jawa 288,

    Perhaps PavelU missed my comment.

  312. 312
    jawa says:


    No, I think he ignored it intentionally, because you presented a very interesting discussion topic where perhaps he wouldn’t even understand what’s all about.

    The guy writes nonsense here and there. He seems clueless.

    Unless it’s a robot? If that’s the case, then any hopes for someday having intelligent AI are gone. Poor thing.

  313. 313
    EugeneS says:

    GP #309


    And No Backdoor to the Summit of Mount Improbable either 🙂 because constraints cut out isolated pockets in the config space. The problem remains even if you define constraints as a function of time. It needs miraculous serendipity, in which they claim they don’t believe in other contexts OR, of course, conscious design.

  314. 314
    PeterA says:

    jawa @312:

    There’s no written rule in this website requiring that we respond to any comment that is addressed to us.
    Therefore it’s not of our business to speculate why somebody doesn’t respond to any given comment.
    We have more important issues to discuss here.

  315. 315
    PeterA says:

    gpuccio @296, 306-308:

    Excellent explanation (as usual).

  316. 316
    OLV says:

    gpuccio (310):

    Yes, they have a whole trove of interesting articles there.

    As UB said, it never stops.


  317. 317
    ET says:

    It’s as if our opponents have never heard of nor read Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution. Either that or they ignore its implications.

    I was once accused of presenting Creation baloney for referencing that article. The blogger wouldn’t read it because he said is was Creationists misrepresenting the probability arguments. Then he banned me before I could explain that he was so very wrong. 😎

    Given the above paper the evolution of color vision is out of the reach of natural selection and drift. That required duplications of an opsin gene, which would require building a new binding site. Then it took specific mutations to change the duplicated gene so that t was tuned to a different wavelength. Not that natural selection could put together such a tunable protein in the first place.

  318. 318
    gpuccio says:

    To all:

    An important aspect of axon growth or regeneration is transport.

    As axons are usually very long, transport of components (proteins, organelles) is vital for axon growth, because these resources are usually synthesized or assembled at the cell body, near the nucleus. So, they have a long way to go to reach the tip of the axon, where growth takes place.

    Transport from the nucleus and cell body to the tip of the axon is called anterograde, and is effectsed by kinesins. There exists also a retrograde transport, effected by dynein.

    And yes, kinesin and dynein are those big proteins that “walk” along microtubules, carrying heavy cargoes.

    Intriguingly, anterograde transport if of three different types; fast transport, slow component a, slow component b. Slow transport is characterized by frequent pauses.

    Here is a paper, form the already quoted special issue, about the importance of anterograde transport, especially slow component b, in axon regeneration:

    Neuronal Intrinsic Regenerative Capacity: The Impact of Microtubule Organization and Axonal Transport


    In the adult vertebrate central nervous system, axons generally fail to regenerate. In contrast, peripheral nervous system axons are able to form a growth cone and regenerate upon lesion. Among the multiple intrinsic mechanisms leading to the formation of a new growth cone and to successful axon regrowth, cytoskeleton organization and dynamics is central. Here we discuss how multiple pathways that define the regenerative capacity converge into the regulation of the axonal microtubule cytoskeleton and transport. We further explore the use of dorsal root ganglion neurons as a model to study the neuronal regenerative ability. Finally, we address some of the unanswered questions in the field, including the mechanisms by which axonal transport might be modulated by injury, and the relationship between microtubule organization, dynamics, and axonal transport.


    Given the highly polarized nature of neurons, axonal transport is pivotal to support neuronal function. Kinesins drive anterograde axonal transport whereas cytoplasmic dynein is the only motor driving retrograde axonal transport. While fast axonal transport carries vesicles and membrane-bound organelles moving at 50–300 mm/day, slow axonal transport moves components at 0.2–10 mm/day. Slow axonal transport can be further categorized into slow component a (the slowest), that moves cytoskeletal proteins such as tubulin, neurofilaments and microtubuleassociated proteins, and slow component b which includes various cytosolic molecules, metabolic enzymes, actin and cytoskeleton-associated proteins (Maday et al., 2014). In the course of axon growth and regeneration, multiple structural cytoskeleton components, cytosolic proteins, vesicles, and organelles need to be anterogradely transported to the axon tip. Interestingly, the speed of axon regeneration is similar to that of the slow component b of axonal transport

    And here is a paper about the strange “fast transport + pause” behaviour of slow component b:

    Rapid and Intermittent Cotransport of Slow Component-b Proteins

    After synthesis in neuronal perikarya, proteins destined for synapses and other distant axonal sites are transported in three major groups that differ in average velocity and protein composition: fast component (FC), slow component-a (SCa), and slow component-b (SCb). The FC transports mainly vesicular cargoes at average rates of ?200–400 mm/d. SCa transports microtubules and neurofilaments at average rates of ?0.2–1 mm/d, whereas SCb translocates ?200 diverse proteins critical for axonal growth, regeneration, and synaptic function at average rates of ?2–8 mm/d. Several neurodegenerative diseases are characterized by abnormalities in one or more SCb proteins, but little is known about mechanisms underlying SCb compared with FC and SCa. Here, we use live-cell imaging to visualize and quantify the axonal transport of three SCb proteins, ?-synuclein, synapsin-I, and glyceraldehyde-3-phosphate dehydrogenase in cultured hippocampal neurons, and directly compare their transport to synaptophysin, a prototypical FC protein. All three SCb proteins move rapidly but infrequently with pauses during transit, unlike synaptophysin, which moves much more frequently and persistently. By simultaneously visualizing the transport of proteins at high temporal and spatial resolution, we show that the dynamics of ?-synuclein transport are distinct from those of synaptophysin but similar to other SCb proteins. Our observations of the cotransport of multiple SCb proteins in single axons suggest that they move as multiprotein complexes. These studies offer novel mechanistic insights into SCb and provide tools for further investigating its role in disease processes.

    Very interesting.

  319. 319
    PavelU says:

    PeterA, thank you for criticizing the offensive tone of a comment posted by jawa, who should apologize for it.

    The scientific literature contains many articles supporting Darwinian evolution and undermining the ideas about design that you all defend so passionately here.

    For example, this paper describes in details the functional evolution of important proteins.

    Do you have a strong argument against this paper? Can you refute it by pointing to specific errors or weaknesses in the text? Generalized comments -filled with empty promises- may be common in politics, but should not be in serious science, where every statement must be supported with specific examples.

  320. 320
    PeterA says:


    I think discussions should be done in respectful terms, as gpuccio usually does here.

    Please, ignore any comment that may seem offensive or disrespectful. Sometimes the authors of those comments don’t know how to express their ideas in better terms. Sometimes their comments reflect anger produced by unpleasant past experiences. Many times we don’t know what we are doing. But we should not let anger make us treat others disrespectfully.

    I think I see your point about the paper you referenced in this case. However, since the paper you have cited apparently deals with “functional evolution of important proteins”, then perhaps gpuccio is more qualified than most of us here to look at this for us.

  321. 321
    gpuccio says:

    To all:

    This is more about axonal transport and its regulation. Fascinating.

    Look at Fig. 1 for a good (and rather funny) summary.



    Axonal transport is essential for neuronal function, and many neurodevelopmental and neurodegenerative diseases result from mutations in the axonal transport machinery. Anterograde transport supplies distal axons with newly synthesized proteins and lipids, including synaptic components required to maintain presynaptic activity. Retrograde transport is required to maintain homeostasis by removing aging proteins and organelles from the distal axon for degradation and recycling of components. Retrograde axonal transport also plays a major role in neurotrophic and injury response signaling. This review provides an overview of the axonal transport pathway and discusses its role in neuronal function.

    Consider that the longest axons in humans can be 1 meter long, and even more! That’s a lot of transport, for a cell. 🙂

  322. 322
    ET says:


    The scientific literature contains many articles supporting Darwinian evolution and undermining the ideas about design that you all defend so passionately here.

    We have heard that before but we have never seen the alleged articles.

    For example, this paper describes in details the functional evolution of important proteins.

    Your equivocation is duly noted as evolution is being debated. It’s the mechanisms that are being debated.

  323. 323
    ET says:

    I like this one from DNA Jock:

    I noted that there are 10^93 different ways for an 80mer to bind ATP.

    So there are many ways for an intelligently designed 80mer to bind ATP.

    How long would it take nature to produce an 80mer without the use of existing cellular systems? Could nature do that in the wild? Has anyone ever observed such a thing?

  324. 324
    gpuccio says:

    To all:

    This recent paper has almost everything:

    Polarity Acquisition in Cortical Neurons Is Driven by Synergistic Action of Sox9-Regulated Wwp1 and Wwp2 E3 Ubiquitin Ligases and Intronic miR-140


    • The ubiquitin ligases Wwp1 and Wwp2 are essential for neuronal polarity acquisition
    • Wwp2 and Wwp2-intron-encoded miR-140 synergistically regulate neuronal development
    • miR-140 represses Fyn expression during neuronal development
    • Sox9 drives expression of Wwp1, Wwp2, and miR-140 in neurons


    The establishment of axon-dendrite polarity is fundamental for radial migration of neurons during cortex development of mammals. We demonstrate that the E3 ubiquitin ligases WW-Containing Proteins 1 and 2 (Wwp1 and Wwp2) are indispensable for proper polarization of developing neurons. We show that knockout of Wwp1 and Wwp2 results in defects in axon-dendrite polarity in pyramidal neurons, and their aberrant laminar cortical distribution. Knockout of miR-140, encoded in Wwp2 intron, engenders phenotypic changes analogous to those upon Wwp1 and Wwp2 deletion. Intriguingly, transcription of the Wwp1 and Wwp2/miR-140 loci in neurons is induced by the transcription factor Sox9. Finally, we provide evidence that miR-140 supervises the establishment of axon-dendrite polarity through repression of Fyn kinase mRNA. Our data delineate a novel regulatory pathway that involves Sox9–[Wwp1/Wwp2/miR-140]-Fyn required for axon specification, acquisition of pyramidal morphology, and proper laminar distribution of cortical neurons.

    The paper highlights an interesting relationship between establishment of polarity, migration and axon growth in cortical neurons:

    Differentiating neurons undergo robust changes of their shape. Shortly after birth, multipolar (MP) neurons at the border between the SVZ and IZ alter their appearance to acquire a characteristic bipolar (BP) morphology.

    The acquisition of BP shape in migrating neurons is coupled to the emergence of neuronal polarity. The single leading process (LP) of a migrating nerve cell orients perpendicularly toward the pia, whereas the single trailing process (TP), emerging from the somatic antipode, lags behind the radially translocating neuron. Notably, pyramidal neurons derive axon-dendrite polarity from specification of the LP and the TP during migration (Barnes and Polleux, 2009). The neurite that extends in the radial direction becomes the LP, and the TP extends from the opposite pole of the nerve cell. Later in development, the LP establishes the fate of an apical endritic shaft, and the TP extends into the axon Hatanaka et al., 2012).

    So, the initial polarization that allow correct migration towards the cortes also defines the emergence of tha axon at the trailing edge.

    Who is implied in the polarization? Our old friends ubiquitin ligases, of course 🙂 .

    In the present study, we investigate the role of a subfamily of Nedd4-type E3 ligases, WW Domain Containing E3 Ubiquitin Protein Ligases 1 and 2 (Wwp1 and Wwp2; Wwp1/2), and their functional interplay with miR-140, encoded in a Wwp2 intron. We demonstrate synergistic roles of Wwp1/2 and miR-140 in the acquisition of axon-dendrite polarity and the laminar distribution of developing pyramidal neurons. Moreover, miR-140-mediated silencing of Fyn kinase is required for the proper acquisition of a BP morphology by developing neurons. Finally, the expression of Wwp1/2 and the intronic miR-140 is under the control of the transcription factor Sex Determining Region Y-Box 9 (Sox9) in developing neurons, and Sox9 is essential for the proper laminar distribution and polarity formation of cortical nerve cells. We propose that Sox9 supervises two collateral signaling pathways that are mediated by Wwp1/2 and miR-140, respectively, regulating proper polarity formation in developing cortical neurons.

    So, two E3 ubiquitin ligases have a central role in this very important process. No surprise here.

    But there is more: the third actor is a micro-RNA (yes, a non coding RNA) derived from an intron of the second ubiquitin ligase. And the general scenario is orchestrated by a master TF, Sox9. Interesting.

    We also learn that:

    microRNAs (miRNAs, miRs) regulate gene expression by binding, in most cases, 30 UTRs of mRNA transcripts. There is ample evidence for a key role of miRNAs in neuronal development (De Pietri Tonelli et al., 2008). Of note, approximately half of all identified human miRNAs are encoded in introns of protein-coding genes. This type of genomic structure enables the promoter-mediated co-regulation of the intronic miRNA and the host gene. Indeed, bioinformatic predictions indicate that intronic miRNAs and the protein products of their host gene loci often co-regulate the same cellular processes (Lutter et al., 2010). However, corresponding experimental validations and functional analyses of such putative synergistic interactions between miRNA and host gene products are largely lacking.

    Well, in this case the idea is well confirmed, it seems.

    What a beautiful coordination of coding and non coding DNA! Those junk introns seem to have some role, after all. 🙂

    Synergistic Activities of Host Wwp2 and Intronic miR-140 in Neurons

    The coordinated expression of host genes and their intragenic miRNAs is a known phenomenon, and functional reciprocity between the host gene and the intragenic miRNAs have been predicted (Lutter et al., 2010). The evolutionary emergence of miRNA loci residing within protein coding genes allows for the use of preexisting gene regulatory machineries and, in parallel, 1112 Neuron 100, 1097–1115, December 5, 2018, for the exposure of miRNAs to the same cellular context and molecular
    networks in which the host gene and its protein product operate (Franc¸ a et al., 2016). A genomic organization, like that between Wwp2 and miR-140, indicates critical functions of the linked genes in the control of similar fundamental cellular pathways, such as axon-dendrite polarity establishment. Nested transcriptional units, such as host Wwp2 and intronic miR-140, add an additional layer of regulation to the processes that control principal aspects of neuronal development. While the functional relevance of this type of genomic organization is generally rather poorly understood, our study provides experimental evidence for synergistic activities of host Wwp2 and miR-140 in neurodevelopment, which were previously only assumed and/or modeled.

  325. 325
    gpuccio says:


    I am not sure I am following. What is this discussion about 80mers?

  326. 326
    OLV says:


    The papers you cited in 310, 318, 321, 324 are fascinating indeed.

    Is there a foreseeable end to this avalanche of discoveries in Biology?

  327. 327
    PeterA says:

    ET @322:

    “We have heard that before but we have never seen the alleged articles.”

    Did you notice the link in PavelU’s comment @319?

    Did you read the last paragraph in my comment @320 in response to PavelU’s comment @319?

    I think the paper PavelU cited deserves a more careful consideration, though I’m not qualified to do it.

    Any discussion with ID deniers must be done seriously, at least by the ID proponents. gpuccio provides a good example to imitate. If they point to certain literature claiming that it supports their ideas, the least we can do is look at it and see what it is about.

  328. 328
    gpuccio says:


    Yes. Interesting paper about possible differention of regulation, but almost nothing on protein evolution.

    bcd seems to be a taxonomically restricted homoebox protein. And so?

    The homologies described are vague and unconcluding. The only interesting aspect is that in insects some proteins are highly specific of some species, like bcd in drosophila.

  329. 329
    OLV says:


    I opened the link PavelU provided in his comment at #319.

    As gpuccio indicated in #328, the paper seems interesting.

    I counted 18 instances of words with the root “evol” in the text of the article and 17 times in the list of referenced papers. However, that doesn’t prove anything, until the claims are comprehensively and coherently explained. That would represent a breakthrough for the neo_Darwinian dogma. Is that the case in the given paper? I don’t know. Would have to read it carefully and see if I understand it. I may have questions about it, though.

    All that said, my first impression after the first perusing of the text is that the article seems to point to functional complexity that strongly supports the ID paradigm. But it could be a biased misunderstanding on my part. 🙂

  330. 330
    OLV says:

    PeterA (327):

    Here’s what I found so far in the paper:

    A feed-forward relay integrates the regulatory activities of Bicoid and Orthodenticle via sequential binding to suboptimal sites

    In Drosophila melanogaster, another K50HD protein, Bicoid (Bcd), has evolved to replace Otd’s ancestral function in embryo patterning.

    The evolution of body plans is driven by alterations to these networks, including changes to cis-regulatory elements and neofunctionalization of transcription factors (TFs) after gene duplication (Thornton et al. 2003Carroll 2008Peter and Davidson 2011Tautz and Domazet-Loso 2011Abascal et al. 2013).

    Despite its critical functions in Drosophila, Bcd is not well conserved even within insects. Rather, Bcd arose after a recent gene duplication event and rapidly evolved to play an important role in embryonic patterning (Stauber et al. 1999Casillas et al. 2006).

    In Drosophilaotd has evolved to become a zygotic target gene of Bcd-dependent activation (Finkelstein and Perrimon 1990).

    This suggests that an important step in Bcd’s evolution was the conversion of Q50 in the ancestor to K50, which changed its DNA-binding preference and allowed it to usurp some of the anterior patterning roles played by Otd in ancestral insects.

    Our results define specific roles for Bcd and Otd in embryonic patterning in Drosophila and shed light on the molecular mechanisms that alter regulatory networks during evolution.

    This result is not surprising in view of the fact that the evolved Bcd- and Otd-coding regions show very little sequence conservation (38% sequence identity within their HDs) (Fig. 2A) and no detectable homology outside the HD.

    In this study, we compared the in vivo functions of two K50HD proteins (Bcd and Otd) within a framework of evolution.

    We showed that Otd and Bcd have evolved independent functions in vivo, and HD swaps between the two proteins indicated that the major structural differences mediating their distinct in vivo activities can be traced to their HDs.

    Bcd has evolved rapidly to become a powerful morphogen in Drosophila but is not well conserved even within Diptera (Stauber et al. 1999).

    In Drosophilaotd has evolved to become a zygotic target gene of Bcd (Finkelstein and Perrimon 1990).

    Convergent evolution and a robust core anterior patterning network

    some functional convergence of these proteins must have occurred during insect evolution.

    The evolution of Bcd likely involved the retention of the maternal promoter and the acquisition of three characteristics required for anterior embryonic patterning: (1) UTR sequences that control anterior mRNA localization, (2) protein motifs that mediate translational repression, and (3) amino acid substitutions that alter its DNA-binding preferences; namely, a Q50-to-K50 mutation in its HD.

    Such dramatic changes in these two genes may be attributed to reduced selective pressure on maternal genes (Barker et al. 2005Demuth and Wade 2007), which permits the exploration of the evolutionary landscape and the acquisition of new functional roles.

    Perhaps this set of target genes represents an ancestral core network that is well conserved in evolution.

    it is possible that the cis-regulatory motifs (and consequently the enhancers) are functionally robust in the evolution of anterior embryo patterning, while trans-acting factors can accumulate mutations.

    This allows for a conserved set of targets that makes up a canalized anterior patterning network that allows the regulating TFs to evolve.

    Emphasis added

    Let’s see how those “evolution”-related terms are technically supported in details.   I don’t see it, but we could investigate it carefully. Are they real or just wishful thinking? We may need gpuccio’s assistance with this.

  331. 331
    ET says:

    gpuccio- My apologies. The “80mer” pertains to Szostak and Keefe’s publication on the polypeptides with 80 amino acids that could bind ATP.

  332. 332
    ET says:

    PeterA @ 327-

    PavelU made a bald assertion and provided a link to a couple of papers. PavelU never made a case for his bald assertion so the Hitchens’ gambit applies: “That which can asserted without evidence can be dismissed without evidence”.

    Only a fool would think they can just point and then it is up to us to figure it out. And people who just post links without making a case can be ignored. Clearly, they are not interested in a serious discussion.

    That said, any paper espousing gene duplication as the mechanism is not talking about Darwinian evolution.

  333. 333
    ET says:

    To PeterA and PavelU- please read the following:

    Intelligent Design is NOT anti-evolution

  334. 334
    PeterA says:


    PavelU @319 claimed that the cited paper describes in details the functional evolution of important proteins. Are you saying that that’s not the case? I don’t expect it to be, but I’m not qualified to determine if that’s true.
    gpuccio wrote that the paper has almost nothing on protein evolution. Should PavelU quote or point to the exact text that proves his case?
    BTW, thanks for the linked OP @331.

  335. 335
    gpuccio says:


    “Is there a foreseeable end to this avalanche of discoveries in Biology?”

    It does not seem so.

  336. 336
    ET says:

    Ed George:

    PavelU @319 claimed that the cited paper describes in details the functional evolution of important proteins.

    Oh my. That does NOT mean it was DARWINIAN evolution. The adjective means something.

    PavelU has to make the case to supports its claim. Otherwise it is nothing but a bald assertion and as such can be ignored.

  337. 337
    jawa says:

    ET @336:

    You quoted Rd George’s comment on PavelU but I can’t find Ed George’s comment. Where is it?

  338. 338
    jawa says:

    Sorry, i meant Ed not Rd.

  339. 339
    jawa says:

    Never mind. It seems like you quoted PeterA’s comment @334 but changed the name. Been there, done that. ????

  340. 340
    jawa says:

    PeterA @334:
    “thanks for the linked OP @331”

    I don’t see any link @331.
    Did you mean @333?

  341. 341
    PeterA says:


    Yes, I was referring to the link ET posted @333.
    Detailed observation! Thanks.

  342. 342
    gpuccio says:

    To all:

    I would like to add some thoughts derived from the paper I already quoted at #51:

    Revisiting Netrin-1: One Who Guides (Axons)

    We already know that Metrin is one of the most important and well stidied guidance cues that contribute to axon growth and path finding.

    We already know that guidance cues can act as soluble ligands (chemotaxis) or as lignads bound to the ECM (haptotaxixs).

    We already know that guidancee cues can act both as attractants and repellents.

    The amazing thing is that Netric can doo all these different thins at the same time:

    a) It can act as a soluble ligand
    b) It can act as an ECM bound ligand
    c) It can act as an attractant
    d) It can act as a repellent

    in all the 4 possible combinations.

    Axon guidance by netrin-1 has been implicated in multiple developing brain regions and developing neuronal types, making it one of the most characterized, diversely functioning guidance cues. Fascinatingly, whereas many axon guidance cues have been found to act predominantly as either attractive or repulsive, and as either diffusible/chemotactic or adhesive/haptotactic molecules, evidence of the function of netrin-1 has never placed it squarely into one category (Figure ?Figure11). This diversity in function renders netrin-1 an ideal candidate for studies on mechanotransduction in axon guidance, as recent studies have emphasized the importance of substrate adhesion in netrin-1 function in vivo

    See Fig, 1 in the paper, which shows very clearly how those different actions of the same protein molecule can efficiently guide the axon in its path to the appropriate target, and even help it “turn”, changing direction when necessary.

    Now, of course the different “interpretations” of the signals coming from the same protein are based not only on the way Netrin presents itself in the environment, but also on different sets of receptors for Netrin.

    For example, Fig. 2 in the paper shows how different homodimers and heterodimers of receptor proteins, specifically expressed at the cell membrane, can give specific responses to Netrin signals, including further refinements of the signal, like “long range repulsion” and “short range repulsion”.


    Now, some comments about that:

    1) Of course, the way each individual neuron/axon responds to different signals at different times depends strictly on the process of cell differentiation, and its various epigenetic levels of control. IOWs, it is a functionality that is very much intrinsic to each cell.

    2) On the other hand, the way Netrin is distributed in the environment in its different forms depends strictly on the actions and behaviour of many other cells, and in general of the ECM.

    3) IOWs, we have a specificity of the complex and multiple signals implemented by Metrin in the environment, that must be set by the coopertaion of many different cells and structures, and a specificity of how the individula neuron/axon interprets the signals, that must be set by the intrinsic developmental processes in the interested cell.

    4) The final result of all those interactions is that billions of axons find their correct way towards their appropriate target, to form the synapses and the general structure that is the foundation for the ordered workings of the nervous system.

    5) And, of course, Netrin is only one of the many guidance gues implied in axon growth, as we have seen.

    6) Now, let me say it, even if I may seem repetitive: this scenario is highly, highly symbolic (UB, are you there? 🙂 )

    7) The complex network of signals and interpretations, with the amazing added feature of different and sometimes contrasting signals being implemented by the same molecule, and the integration of behaviours specified in many different cells and structures, is semiotic at its core. For example, Netrin of course has in itself no specific and unique action: it is not an enzyme, it is not a structural protein. It is, indeed, a symbol, a symbol that can assume different meanings in the same network. And that is true of all the other components of this system.

    8) The semiotic structure, as it often happens in these very complex and high level regulation networks, is pervasice, and is implemented by many different components of the system, as we have seen. That makes the system not only highly semiotic, but also irreducibly complex at many different levels.

    9) And the interactions in this pervasive semiotic system are, as we have seen, not only biochemical, but also mechanical. See for example Fig. 6 in the paper. IOWs, both complex biochemical interactions and subtle modulations of mechanical forces contribute to the ordered progression of our billions of axons in their many faceted and highly dynamic 3D world.

  343. 343
    jawa says:

    „The amazing thing is that Netric can doo all these different thins at the same time:

    a) It can act as a soluble ligand
    b) It can act as an ECM bound ligand
    c) It can act as an attractant
    d) It can act as a repellent

    in all the 4 possible combinations.”

    That is simply incredible.

  344. 344
    jawa says:

    “Now, let me say it, even if I may seem repetitive: this scenario is highly, highly symbolic (UB, are you there? “

    I don’t know if UB is seeing this but I’m speechless.

  345. 345
    jawa says:

    @342 excellent presentation! Wow!

    But the most amazing thing was not mentioned:

    All that biosemiotic complexity is obviously the product of…

    [drums… trumpets… ]

    RV+NS!!! Of course!!!

  346. 346
    PeterA says:

    jawa @345,

    Yeah, right.

  347. 347
    OLV says:

    gpuccio (335):

    This young scientist seems to share your opinion:

    mechanisms of synchronization of mitosis in the earlier phases of embryonic development

    As we keep uncovering fundamental principles in biology, it will become more and more important to bring together scientists from different fields to solve our greatest scientific challenges.

    There are many exciting questions in biology that will keep us busy for many decades to come.



  348. 348
    gpuccio says:


    Well, I don’t know if I will be able to witness the process for “many decades to come” (maybe too optimistic! 🙂 ), but I am very gratefull for all that I have seen and that I will still be able to see.

    Also, I must say that for me being part, however small, of such an important debate about science at a time when truth is still embraced by a minority has a special appeal.

    As I have often said, I am definitely a minority guy. 🙂

  349. 349
    OLV says:


    I like your comment.

    Unfortunately truth has always been embraced by a minority. Science is not an exception. But definitely it’s good to be on the side of truth. Let’s hope more will join as more evidences are available in the days to come. However, the evidences currently available, some of which you have presented and explained so clearly, are sufficient to persuade and even convince most people, as long as we are open-minded and willing to think seriously.

    PS. to all the readers:

    To the question:

    “Is there a foreseeable end to this avalanche of discoveries in Biology?”

    GP succinctly responded:

    “It does not seem so.”

    Cited a 2018 article where a young leading-edge science researcher affirmed this:

    “There are many exciting questions in biology that will keep us busy for many decades to come.”

    Which seems to strongly corroborate GP’s affirmation in #335.

  350. 350
    OLV says:

    Morphogens, modeling and patterning the neural tube

    Unlike some other signaling pathways, Hedgehog does not simply activate a latent activator, but instead converts a transcription factor that represses expression to one that activates gene expression. This adds another dimension, another level of complexity.

    Transcriptional networks tend to have lots of feedback in them and it is very difficult to understand how a network with feedback operates.


    can we start to identify design principles that go beyond such details and define common features, even though the details are going to differ between different tissues?

     it will be exciting over the next few years to see that more fundamental level of similarity.

    Apparently this article was written by the end of 2014.  How many years does the expression “the next few years” indicate?   Have they seen that “more fundamental level of similarity” yet?   Have they answered some outstanding questions?  Have new questions appeared?
    Also, what does Dr. Briscoe mean by “design principles“?
    Emphasis added.
    Here’s a more recent interview with the same British scientist.

  351. 351
    OLV says:

    Morphogens, modeling and patterning the neural tube (2)

    the fundamental question in developmental biology is how the right cells are produced in the right place, at the right time and in the right amounts in a developing tissue.

    Addressing these issues covers some of the most basic questions in biology. How is gene activity controlled? How is cell function determined? How are tissues shaped and organised from cells?

    how the cells make the key decisions and how this guides the assembly of a functional, well-organised neural tube?

  352. 352
    gpuccio says:

    To all:

    This is brand new, and again about immunity:

    Role of Mechanotransduction and Tension in T Cell Function


    T cell migration from blood to, and within lymphoid organs and tissue, as well as, T cell activation rely on complex biochemical signaling events. But T cell migration and activation also take place in distinct mechanical environments and lead to drastic morphological changes and reorganization of the acto-myosin cytoskeleton. In this review we discuss how adhesion proteins and the T cell receptor act as mechanosensors to translate these mechanical contexts into signaling events. We further discuss how cell tension could bring a significant contribution to the regulation of T cell signaling and function.


    To mount a proper adaptive immune response and establish immune memory, T cells carry out many distinct cellular processes. In a simplified view, these processes can be grouped in three categories. (a) The adhesion cascade, during which circulating T cells exit the blood flow to roll, adhere and eventually extravasate through the endothelial cell layer. (b) Migration, on the wall of blood or lymph vessels, within lymph nodes and inflamed or cancerous tissues. And (c), activation, which primes naïve T cells and triggers cytotoxicity and cytokine secretion from effector cells. The molecular interactions and signaling pathways associated with T cell activation (1), migration through venular walls (2) and T cell migration in general (3) have been extensively characterized and are comprehensively described in these recent reviews. But the emergence of novel biophysical approaches has allowed to shine light on a previously neglected aspect of these processes: they all generate mechanical stimuli.

    During the adhesion cascade, the blood flow applies an external shear stress on T cells binding and migrating on and through endothelial cells (2). T cell migration in tissues is driven by morphological changes, constantly fluctuating actin polymerization and molecular motors-driven contractions, which all generate internal mechanical tension (4). It goes the same with T cell activation, which involves a tight contact between T cells and antigen-presenting cells or target cells, acto-myosin contractions and a sustained actin retrograde flow (5). Adding to the multiplicity of these mechanical contexts, T cells interact with substrates displaying various and changing stiffness (6) and with adhesion molecules that are either diffusive or firmly anchored to cortical actin (7). Hence, the idea that force plays an essential role in the T cell-mediated immune response has matured from an exciting hypothesis to a well-established field of T cell biology (8–11).

    In this review we first focus on demonstrated mechanotransduction events in T cells. We discuss how adhesion proteins—selectins and integrins—and the T cell receptor (TCR) act as mechanosensors during the adhesion cascade and during T cell activation, respectively. In the second part of the review, we get inspiration from other cell types and systems to picture how cell tension might contribute to the cellular signaling that regulates T cell migration and activation.

    T cells do recirculate throughout the whole organism continuously. That makes immune response a really “omnipresent” function. Of course adhesion and migration play a fundamental role here.

  353. 353
    PeterA says:


    Very interesting indeed. Thanks.

  354. 354
    gpuccio says:

    To all:

    Again about T cell function.

    One of the points I mentioned in the OP is the extreme specificity of function of the different integrin combinations.

    From a paper quoted in the OP:

    Each of the 24 integrins shown in Figure 1 appears to have a specific, nonredundant function. In part, this is evident from the details of their ligand specificities (not shown in Figure 1) but is most clearly shown by the phenotypes of knockout mice (Table 1). Genes for the ? subunits and all but four of the ? subunits have been knocked out and each phenotype is distinct, reflecting the different roles of the various integrins.

    Now, one example of very specific integrin is the alpha L – beta 2 integrin, also called lymphocyte function-associated antigen 1 (LFA-1). This particular integrin binds the ICAM proteins (1,2 and 3), special transmembrane glycoproteins expressed by endothelial cells. It is therefore implied in a form of intercellular adhesion, with a fundamental role in the adhesion of T cells to the endothelium, and their migration out of blood vessels into tissues.

    Here is a very recent paper about that:

    Crk adaptor proteins mediate actin-dependent T cell migration and mechanosensing induced by the integrin LFA-1.


    T cell entry into inflamed tissue involves firm adhesion, spreading, and migration of the T cells across endothelial barriers. These events depend on “outside-in” signals through which engaged integrins direct cytoskeletal reorganization. We investigated the molecular events that mediate this process and found that T cells from mice lacking expression of the adaptor protein Crk exhibited defects in phenotypes induced by the integrin lymphocyte function-associated antigen 1 (LFA-1), namely, actin polymerization, leading edge formation, and two-dimensional cell migration. Crk protein was an essential mediator of LFA-1 signaling-induced phosphorylation of the E3 ubiquitin ligase c-Cbl and its subsequent interaction with the phosphatidylinositol 3-kinase (PI3K) subunit p85, thus promoting PI3K activity and cytoskeletal remodeling. In addition, we found that Crk proteins were required for T cells to respond to changes in substrate stiffness, as measured by alterations in cell spreading and differential phosphorylation of the force-sensitive protein CasL. These findings identify Crk proteins as key intermediates coupling LFA-1 signals to actin remodeling and provide mechanistic insights into how T cells sense and respond to substrate stiffness.

    Again, we have it all here: very specific integrins, cell migration by specific mediators (CRK), E3 ubiqutin ligases and their activation by phosphorilation events, complex intracellular signalings, actin remodeling, mechanosensing. Higher integration of the best type! 🙂

  355. 355
    PeterA says:

    “Again, we have it all here: very specific integrins, cell migration by specific mediators (CRK), E3 ubiqutin ligases and their activation by phosphorilation events, complex intracellular signalings, actin remodeling, mechanosensing. Higher integration of the best type!“


  356. 356
    gpuccio says:

    To all:

    This “Epub ahead of print” paper is a very clear discussion about the possible mechanisms of mechanosnsing and mechanotransduction:

    Cellular machinery for sensing mechanical force.


    For mechanical force to induce changes in cellular behaviors, two main processes are inevitable; perception of the force and response to it. Perception of mechanical force by cells, or mechanosensing, requires mechanical force-induced conformational changes in mechanosensors. For this, at least one end of the mechanosensors should be anchored to relatively fixed structures, such as extracellular matrices or the cytoskeletons, while the other end should be pulled along the direction of the mechanical force. Alternatively, mechanosensors may be positioned in lipid bilayers, so that conformational changes in the embedded sensors can be induced by mechanical force-driven tension in the lipid bilayer. Responses to mechanical force by cells, or mechanotransduction, require translation of such mechanical force-induced conformational changes into biochemical signaling. For this, protein-protein interactions or enzymatic activities of mechanosensors should be modulated in response to force-induced structural changes. In the last decade, several molecules that met the required criteria of mechanosensors have been identified and proven to directly sense mechanical force. The present review introduces examples of such mechanosensors and summarizes their mechanisms of action.

    How then, can cells sense and respond to mechanical force? The mechanical force acting on cells eventually results in deformations of cellular structure. To be recognized by cells as a signal, the deformation must be converted into a biochemical signal, such as a change in enzymatic activity or a protein-protein interaction. Two major hypotheses have been suggested to explain as for how cells recognize such deformations (10). In one hypothesis, proteins tethered to either cell-cell or cell-extracellular matrix (ECM) contacts are suggested to work as “mechanosensors” that can “feel” the force and translate it into a biochemical signal. When the tethered proteins are pulled by mechanical force in the opposite direction from the tethered site, the molecules undergo stretching resulting in conformational changes. These changes can expose a binding site for other proteins to interact with (Fig. 1A) or disrupt an existing protein-protein interaction (Fig. 1B), which can turn on signaling in a manner similar to protein-protein interactions involved in various cellular signaling pathways initiated by growth factors or hormones (11). Alternatively, conformational changes resulting from mechanical force-induced stretch can directly modulate the enzymatic activities of the proteins (Fig. 1C), such as ion channels, resulting in the initiation of cell signaling (12). Since this explanation relies on proteins tethered to adhesive structures, this explanation is termed as the “tethered model”.

    In the other explanation, lipid bilayers are important in sensing mechanical stress. The force acting upon cells can cause deformation to entire cells, inducing stretching and/or bending of the lipid bilayer in the cellular membrane. The conformation of integral membrane proteins, especially their membrane-spanning regions or transmembrane domains (TMDs), is largely determined by interactions with nearby lipid bilayers (13). This allows the mechanical forceinduced changes in the physical properties of the lipid bilayer to influence the conformation of integral membrane proteins, enabling them to adapt to the altered environment within the lipid bilayer (14). Subsequently, the resulting conformational change induces changes in proteinprotein interactions or enzymatic activity (Fig. 1E-F). This explanation has been termed as the “lipid bilayer model” and is widely accepted as the opening mechanism for mechano-gated ion channels (15).

    Then follows an updated list of proteins that are possible candidates for mechanosensing/transduction, starting with the well studied talin.

    I still wonder how mechanisms such as hidden sites for vinculin inside a folded structure, that become active only when a mechanical force stretches the molecule, and then activate biochemical responses that are appropriate to the original mechanical stimulation, could ever arise out of a designed plan. How can anyone believe that stuff?

    OK, OK: this is an argument from incredulity. It definitely is! 🙂

  357. 357
    PavelU says:


    All those mechanisms that appear designed are pure physics and chemistry. How can anyone think they are designed? Their apparent complexity is the results of many years of evolutionary trials and errors. Don’t you see it? It has been extensively documented in scientific literature for years. Haven’t you seen it? I just posted -in another topic (feathers) discussion- several examples of publications that show that evolution is true and the ID ideas aren’t.

  358. 358
    jawa says:

    Do yourself a big favor: wake up and smell the coffee!
    Get a life buddy! Chill out!

  359. 359
    ET says:


    All those mechanisms that appear designed are pure physics and chemistry.

    That is your unsupportable opinion, anyway.

  360. 360
    gpuccio says:

    To all:

    A separate class of mechanosensor molecules, different from the Focal Adhesions system described in detail in the OP, is represented by Mechanosensitive Channels (MSCs). These are membrane proteins that seem to work as ion channels, but they are able to sense mechanical deformations of the membrane, and tranform those stimuli into modifications of their channel function. Here is a recent paper about them, and their roles in stem cells:

    Mechanosensitive channels and their functions in stem cell differentiation.


    Stem cells continuously perceive and respond to various environmental signals during development, tissue homeostasis, and pathological conditions. Mechanical force, one of the fundamental signals in the physical world, plays a vital role in the regulation of multiple functions of stem cells. The importance of cell adhesion to the extracellular matrix (ECM), cell-cell junctions, and a mechanoresponsive cell cytoskeleton has been under intensive study in the fields of stem cell biology and mechanobiology. However, the involvement of mechanosensitive (MS) ion channels in the mechanical regulation of stem cell activity has just begun to be realized. Here, we review the diversity and importance of mechanosensitive channels (MSCs), and discuss recently discovered functions of MSCs in stem cell regulation, especially in the determination of cell fate

    These proteins are not yet well understood. Among the best studies, and intriguing, there are the two Piezo proteins, Piezo 1 and Piezo 2, two long proteins (2521 and 2752 AAs in humans), differentially expressed in different tissues and with different range of functions, both highly engineered in the transition to vertebrates (especially Piezo 2), sharing 43% identity, highly conserved from cartilaginuous fishes to humans (57% and 66% respectively, 2788 and 3625 bits).

    Here is a very interesting and recent paper about Piezo 1 and its strange 3D structure, very similar to a three-bladed propeller embedded in the cell membrane:

    The mechanosensitive Piezo1 channel: a three-bladed propeller-like structure and a lever-like mechanogating mechanism


    The evolutionarily conserved Piezo proteins, including Piezo1 and Piezo2, constitute a bona fide class of mechanosensitive (MS) cation channels, which play critical roles in various mammalian physiologies, including sensation of touch, proprioception and regulation of vascular development, and blood pressure. Furthermore, mutations in Piezos have been linked to various human genetic diseases, validating their potential as therapeutic targets. Thus, it is pivotal to understand how Piezo channels effectively convert mechanical force into selective cation permeation, and therefore precisely control the various mechanotransduction processes. On the basis of our recently determined cryoelectron microscopy structures of the full-length 2547-residue mouse Piezo1, structure-guided mutagenesis, and electrophysiological and pharmacological characterizations, here we focus on reviewing the key structural features and functional components that enable Piezo1 to employ a lever-like mechanogating mechanism to function as a sophisticated mechanotransduction channel.

    Watermills, three-bladed propellers… What else? 🙂

  361. 361
    jawa says:

    “Watermills, three-bladed propellers… What else?”

    According to PavelU all that stuff may appear designed but it isn’t.

    Poor guy. Totally oblivious to reality.

    Could it be that PavelU is just a robot? It that’s the case then AI still needs a lot of improvement.

  362. 362
    gpuccio says:

    To all:

    For those who still believe that axon growth could be a relatively simple process, here is a very recent and stimulating review:

    An Integrated Cytoskeletal Model of Neurite Outgrowth


    Neurite outgrowth underlies the wiring of the nervous system during development and regeneration. Despite a significant body of research, the underlying cytoskeletal mechanics of growth and guidance are not fully understood, and the relative contributions of individual cytoskeletal processes to neurite growth are controversial. Here, we review the structural organization and biophysical properties of neurons to make a semi-quantitative comparison of the relative contributions of different processes to neurite growth. From this, we develop the idea that neurons are active fluids, which generate strong contractile forces in the growth cone and weaker contractile forces along the axon. As a result of subcellular gradients in forces and material properties, actin flows rapidly rearward in the growth cone periphery, and microtubules flow forward in bulk along the axon. With this framework, an integrated model of neurite outgrowth is proposed that hopefully will guide new approaches to stimulate neuronal growth.

    Conclusion and Outlook:

    In conclusion, we propose here an integrated cytoskeletal model of neurite outgrowth (Figure ?(Figure2), that does not pinpoint a single dynamic process as the sole driving force of elongation. We suggest that gradients in force generation and adhesions along the axon and growth cone determine whether axons elongate, retract, or stall. If the growth cone produces stronger traction forces and adhesions than the axon, the net result will be increased neurite growth. The second significant aspect of our model involves the idea that axons are active fluids and that viscosity controls the rate of material flow. In addition to force generation, cross-linkers between different types of filaments affect viscosity and control how quickly flow occurs in response to forces. Since cross-links are lost when filaments undergo disassembly, the dynamics of MTs and actin filaments impacts viscosity. In general, for fast growth to occur, the density of cross-linkers needs to be minimized, and the dynamics of filaments increased. On the other hand, if the density of cross-linkers drops too much, the forces generated by these systems may be less directed (Figure ?(Figure 7).

    Viewing neurons as an active fluid leads to a model of elongation that is useful for understanding how growth occurs and further suggests principles for prompting rapid neurite growth for example during regeneration following injury. To promote rapid elongation, one needs to increase net contractile force generation and adhesions in front of the central domain, decrease net contractile force generation and adhesions along the axon, and lower viscosity ?(Figures2,6). As forces, adhesions, and viscosity are influenced by multiple processes; many approaches could lead to fast elongation. What complicates the development of therapies for neurite growth is that any given component is typically involved in several processes that often have opposing effects on elongation. However, without an integrated model, it will be challenging to come up with better approaches to increase neurite growth. We hope that this review will stimulate new developments in this area.

  363. 363
    PeterA says:


    “those who still believe that axon growth could be a relatively simple process” also believe that it was not designed and that the moon is made of cheese. Basically they believe anything. It’s sad.

  364. 364
    PeterA says:

    PavelU @357:

    “All those mechanisms that appear designed are pure physics and chemistry.”

    FYI – in case you didn’t know it, the engines of all the cars, buses, trains, airplanes, ships, are pure physics and chemistry too. Actually, maybe more physics than chemistry. But they are all intelligently designed. Otherwise they wouldn’t exist. They are the product of conscious understanding of meaning and purpose. Do you understand this?

    BTW, gpuccio has presented a substantial number of cases of enormous jumps in complex functional specified information in proteins which have been empirically observed. gpuccio has concluded that those extravagant jumps in complexity can be attributed exclusively to conscious design. However, having those complex proteins doesn’t solve the biological complexity issue. Remember that all of king’s horses and all of king’s men couldn’t put Humpty together again. Do you realize the magnitude of the mystery we are facing in biology? It’s complex control systems on excessive doses of strong steroids.

  365. 365
    OLV says:

    PavelU (357):

    Please, try to understand this well:

    None of the papers you have cited in this website provide any support for neo-Darwinian evolution. Perhaps they vaguely refer to adaptive changes that could be associated with the so-called micro-evolutionary processes, but that’s it.

    Any questions?

  366. 366
    OLV says:

    I greatly appreciate your citing and scientifically commenting on all those very interesting papers in your excellent (as usual) OP and discussion thread. Please, keep delighting us with your OPs. As you can see, they seem to attract a relatively substantial number of anonymous readers. Well done!
    Have a wonderful Christmas and a blessed new year.

  367. 367
    PeterA says:

    To PavelU, JF (TSZ), AH (UK), LM (UT) et al.

    The overwhelming biology-related research literature is increasingly presenting a picture that definitely confirms the ID paradigm without doubt.
    What gpuccio has done in his latest OPs is point in very clear terms to that undeniable fact. The unstoppable avalanche of bad news for the decrepit neo-Darwinian dogmas will continue in the foreseeable future and beyond.
    GP has done an excellent work presenting those amazing facts to the delight of many of us here. His latest OPs have covered fundamental issues of modern biology research.
    We’re thankful to have gpuccio here and look forward to reading newer OPs on the fascinating scientific topics he chooses.
    Merry Christmas and peaceful new year to all.
    PS. Let’s hope that jawa will calm down and be less critical and more gracious in the new year. 🙂

  368. 368
    gpuccio says:

    OLV, PeterA:

    Thank you for your contribution and for your kind words. My best wishes of merry Christmas and a wonderful New year! 🙂

  369. 369
    ET says:

    A couple or few weeks ago Alan Fox proclaimed that they had the evidence and arguments to refute ID’s claims.

    Does anyone have any idea what he is waiting for?

    First he would have to understand what natural selection is, what it has been proposed to do and what it actually does. It’s tough to refute your opponent’s claims when you don’t even understand the mainstream concept they are opposing. 😛

  370. 370
    ET says:

    Meanwhile, over on peaceful science they are actually trying to argue that the genetic code isn’t really a code. They are too stupid to understand that the mRNA codon represents the respective amino acids, which make the mRNA the abstract symbol and the genetic code the same type of code as Morse code.

    Those guys are very pathetic

  371. 371
    gpuccio says:


    I have seen that before.

    It’s simply a problem of definitions.

    They seem to think (when it is usefult to them) that a code implies, in its same definition, a conscious origin.

    But that’s not the case. A code implies an inference to a conscious origin for empirical reasons only, IOWs, because we cannot observe codes arising from non conscious systems. It’s an empirical argument, similar (but not identical) to the argument of design inference from complex functional information.

    But a code can be easily defined without any reference to a conscious intervention.

    A code is a symbolic mapping of a set of configurations to another set of object or events. The mapping has to be symbolic: IOWs, it is arbitrary, and does not depend on cause-effect relationships acting in the system. Another way to say that is that the mapping is set arbitrarily by some specific, contingent configuration of the system itself.

    So, the genetic code is an arbitrary, symbolic mapping of 3-nucleotide configurations to 20 AA-objects. It is completely symbolic, because no biochemical law can put the right AA in the right place in the new protein simply because the mRNA has a certain sequence of nucleotides. We need a specific translation machinery, especially the 20 aaRNA sinthetases, to build any proteins from any mRNA. It cannot be done in any other way.

    So, the genetic code is a code. Of course. That’s why it was called a code. Becuase it is a code.

  372. 372
    ET says:

    The following is a huge problem as it went unchallenged:

    Sorry but that is just wrong. ASCII uses symbols as abstract representations of the information to be passed. There is no abstraction in DNA –> protein process, none at all. It’s just a complex chemical reaction following the laws of chemistry and physics. If you don’t believe it, try creating a gene from Lego or Tinkertoys, see if if produces a Lego or Tinkertoy amino acid.

    Starting from last, I would love to see a Morse code message made up of Legos transmitted over telegraph lines.

    But it starts off all wrong, too. The abstraction in the genetic code is in the fact that mRNA codons REPRESENT their amino acid counterparts. They do NOT chemically transform into them.

    And the genetic code is arbitrary in that it is not determined by physical or chemical processes.

    The person writing that doesn’t have any training at all in any of the sciences. He doesn’t even appear to have taken a high school biology course. And yet what he posted was allowed to stand.

    The clincher is because someone wrote that tree rings encode information this same guy thinks that tree rings are a code. Yet no one supports that claim- no one with any academic background in trees.

  373. 373
    gpuccio says:


    That person does not know what he is speaking of.

    Tree rings are he result of processes that happen in the tree. Of course they are a source of information, but that information is not coded. The observer derives the information from his knowledge of the processes that cause the tree rings.

    In the same way an object that falls down bears information about the gravitational filed. But it is not coded information.

    Those who deny that the genetic code is a code have no idea of what they are speaking of.

    The Lego analogy is pure idiocy, of course.

  374. 374
    ET says:

    Unfortunately that is what passes for science over on Peaceful Science.

    Joshua Swamidass would be ashamed if he wasn’t so unaware…

  375. 375
    PeterA says:

    To all:
    Function of Junk: Pericentromeric Satellite DNA in Chromosome Maintenance
    Article?in?Cold Spring Harbor Symposia on Quantitative Biology 82:034504 · April 2018?with?56 Reads
    DOI: 10.1101/sqb.2017.82.034504

    Funny title “function of junk” isn’t it?

  376. 376
    PeterA says:

    Do you think the authors of that paper are trying to send out a wake up call message by using such a contrasting title “function of junk” ?

  377. 377
    PeterA says:

    Here’s more on the functional junk topic:

    As gpuccio says, the plot thickens.

    The neo-Darwinian folks say they see the light at the end of the tunnel, but it’s a fast train going their way.

  378. 378
    gpuccio says:


    Very interesting indeed, thank you.

    So, another piece of “junk” (Pericentromeric Satellite DNA) seems to acquire function. And what a function: “preserving the entire chromosomal complement in a single nucleus, a fundamental and unquestioned feature of eukaryotic genomes”!

    Not bad, not bad. 🙂

  379. 379
    PeterA says:

    When it rains. It pours… 🙂

    The modular mechanism of chromocenter formation in Drosophila
    Madhav Jagannathan, Ryan Cummings, View ORCID Profile Yukiko M Yamashita

    Another game changer…

    I feel sorry for the Darwinian crowd.

    BTW, the first author of the cited paper got an offer for a leading position in Switzerland

    He was working in Yukiko Yamashita’s team

  380. 380
    PeterA says:


    Exactly, not bad at all.

    These are the scientists in that research team in the LSI at the UMich.

    These folks seem busy cooking delightful things for us to enjoy 🙂

  381. 381
    jawa says:

    Any comments on the functional “junk” by professors LM (UTor), AH (UKen), JF (TSZ)? 🙂

  382. 382
    jawa says:

    Just trying The new settings.

    The editing tool is available longer than in the old theme/settings

  383. 383
    jawa says:

    It shows: 382 leave a reply

  384. 384
    jawa says:

    383: my next comment

  385. 385
    jawa says:

    384: ok it’s more clear now
    Just noticed the sort options:
    Newest Oldest. Most voted
    Definitely an improvement
    The edit works better too

  386. 386
    jawa says:

    Replying to my one day old post

  387. 387
    jawa says:

    386: leave a reply

    The number 386 includes a reply to a post.

  388. 388
    jawa says:

    Just a reply

  389. 389
    jawa says:

    386 comment threads
    2 thread replies

  390. 390
    jawa says:


  391. 391
    gpuccio says:

    Now it seems comments are again all in one page, from oldest to newest. Better for me.
    I like many things of the new look. The thing I miss most is the numbering of comments, because I did use it to specify what comment I was answering to. This way, we should use date and time, which is less practical.

  392. 392
    jawa says:

    Now I see post numbers.

  393. 393
    gpuccio says:

    Jawa at #392:

    Yes, definitely! 🙂

  394. 394
    jawa says:


    The topic you chose for this OP seems so important that it’s worth even a special conference this coming summer?

    Symposium Overview

    The symposium aims at bringing together world-leading experts in the fields of mechanobiology, cell biology and developmental biology studying the mechanical basis of cell and tissue morphogenesis. Particular emphasis will be given to quantitative approaches analysing how force production, transduction and reception drive cell and tissue morphogenesis from the molecular scale to the organismal scale. The field is currently expanding rapidly and we aim to provide a comprehensive overview of both experimental and theoretical advances providing insight into the molecular, cellular and biophysical mechanisms by which cells, tissues and entire organisms take shape.

    Session Topics

    Force generation
    Force transduction
    Cell and tissue morphogenesis

  395. 395
    gpuccio says:


    Yes, it is definitely a hot topic! 🙂

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