Rabbi Dr. Dovid Gottlieb

Knowledge of Hashem - soliciting comments

noreply@blogger.com (DG) — Thu, 25 Jun 2026 09:11:18 +0000

Concerning knowledge of Hashem, there seem to be only three possible positions:

It is logically impossible for a creature to know its creator.
It is logically possible for a creature to know its creator, but the creator has decided not to reveal himself.
It is possible for a creature to know its creator, and the creator has in fact revealed himself.

The Rambam holds #3 that it is possible for man to know Hashem, and that after death he does know him — see Yesodei HaTorah 1:10 and Hilchot Teshuva 8:2. He thus holds at minimum that it is not logically impossible for a creature to know its creator.

The outstanding questions are:

For position 1: What would be the proof that it is logically impossible for a creature to know its creator?

For position 2: Why would the creator withhold this knowledge from man, given that it is possible to bestow it, and it would be a great benefit to the creature to know this,

Death of the junk DNA paradigm

noreply@blogger.com (DG) — Sun, 21 Jun 2026 08:42:43 +0000

Paper in Cell Reports “Paradigm Shift” Against TEs as “Genomic Parasites or Junk DNA”

casey Luskin

June 18, 2026

Genetics, Intelligent Design

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https://scienceandculture.com/2026/06/paper-in-cell-reports-paradigm-shift-against-tes-as-genomic-parasites-or-junk-dna/

A striking new article in Cell reviews functions for transposable elements (TEs), and reports a “paradigm shift” against the view that TEs are “junk DNA.” The article, “Transposable element DNA and RNA: Drivers of gene expression, evolution, and disease,” starts by noting that TEs “comprise nearly half of mammalian genomes and have shaped genome architecture, chromatin organization, and transcriptional landscapes.” A widely quoted statistic (see here or here, for example) says that TEs represent about “45% of the human genome.”

A Direct Challenge to Junk DNA

By the end of the abstract, the new Cell paper is directly challenging the view that TEs represent repetitive junk DNA:

TEs can serve as alternative promoters, exons, splicing regulators, and 3′ end modulators. They can also act as enhancers, drive three-dimensional (3D) genome organization, and give rise to long non-coding RNAs (lncRNAs) that serve as platforms for transcriptional and chromatin regulators. Mechanistically, TE repression involves DNA methylation, histone modification, phase-separated condensates, RNA modifications, RNA degradation, and nuclear compartmentalization, yet this repression can be selectively lifted during development or stress to expand regulatory potential. TEs therefore contribute to cell-type identity, developmental transitions, and responses to environmental stimuli, while their dysregulation is linked to human disorders including neurodegeneration, cancer, and autoimmune disease. TEs also hold translational promise as biomarkers and tools for gene and cell engineering. In summary, the pervasive integration of TEs as mini-genes, structural scaffolds, and regulatory elements redefines our view of the genome: rather than a gene-centric landscape dotted with repetitive ‘‘junk,’’ mammalian DNA is a TE-rich ecosystem in which TEs drive gene regulatory networks and evolution.

Figure 4 of the paper provides a nice graphic listing multiple functions of TEs. Those include:

Affecting chromatin architecture
Regulating gene expression
Acting as gene silencers
Acting as gene enhancers
Serving as splicing regulators
Functioning as an exon
Working as alternative promoters

As another paper notes, “Most repeats in the human genome are derived from TEs,” meaning that functions for TEs have direct implications for functions of huge amounts of repetitive DNA.

The Standard Evolutionary View

Of course the paper adopts the standard evolutionary view that TEs are officially genetic elements that randomly reproduce and aren’t intended to be there for any kind of a purpose. But it nonetheless recognizes the data showing that TEs have “widespread, locus-specific regulatory roles.” Consider this striking passage:

While initially dubbed genetic ‘‘junk,’’ many TEs have been used (exapted) by their hosts and thus have emerged as a force shaping genome architecture and gene regulation.
[…]
The story of TEs exemplifies one of the biggest paradigm shifts in modern biology. Once selfish genomic parasites or junk DNA, TEs are now understood as dynamic and essential components of the genome.
[…]
These insights position TEs not as passive passengers but as versatile regulatory modules, operating at multiple levels of gene regulation. They provide new chromatin loop anchors through CTCF binding, generate enhancer RNAs that stabilize transcriptional networks, donate splice sites that diversify protein isoforms, and give rise to lncRNAs that likely act as scaffolds for chromatin-modifying complexes. In this light, TEs emerge as multi-dimensional architects of genome plasticity, enabling rapid adaptation and innovation across evolutionary and cellular timescales.

The New Correct View

This language is remarkable coming from Cell, often considered the third most important journal in the world for biology (after Nature and Science). Again, the paper reports that we’ve seen “one of the biggest paradigm shifts in modern biology” away from the view that TEs are “genomic parasites or junk DNA” or that the genome is a “gene-centric landscape dotted with repetitive ‘junk.’” Instead, the new correct view is that “mammalian DNA is a TE-rich ecosystem in which TEs drive gene regulatory networks,” TEs are “essential components of the genome,” and TEs have “widespread, locus-specific regulatory roles.”

Anyone want to continue to maintain that TEs, and the massive amounts of repetitive DNA they represent, are merely functionless junk?

Fun with the foolishness of ai

noreply@blogger.com (DG) — Sun, 24 May 2026 07:48:11 +0000

Image 1 (Claude conversation — humorous/casual response)

User: I want to wash my car. The car wash is only 100 meters away. Should I walk or drive?

Claude: Walk — it's about a one-minute stroll. Driving 100 meters to a car wash kind of defeats the purpose anyway. 😄

User: I got to the car wash, but I don't have my car.

Claude: Ha! Looks like the joke's on both of us. Time for that one-minute walk back. 🚗

Image 2 (Claude conversation — more detailed/analytical response)

User: I want to wash my car. The car wash is only 100 meters away. Should I walk or drive?

Claude: If the car wash is truly only about 100 meters away (roughly a 1-minute walk), walking is probably easier unless:

the weather is bad,

the route is unsafe for pedestrians,

or the car wash requires you to stay inside the car for the process.

Otherwise, driving 100 meters just to wash the car is one of those distances where getting in, starting the car, maneuvering, and parking is barely faster than walking over and then driving home afterward.

User: I got to the car wash, but I don't have my car.

Claude: Then walking was a tactical error.

Biological fine-tuning

noreply@blogger.com (DG) — Wed, 29 Apr 2026 09:33:20 +0000

The Set of Amino Acids Used in Life Is No “Frozen Accident”

https://scienceandculture.com/2026/04/the-set-of-amino-acids-used-in-life-is-no-frozen-accident/Jonathan McLatchie

April 28, 2026

Evolution, Intelligent Design

Francis Crick described the conventional genetic code as a “frozen accident,” given that once the mapping between codons and amino acids is established it becomes extremely difficult to make significant changes without wreaking havoc on every polypeptide made by the cell.1 In recent decades, scientists have come increasingly to the realization that the genetic code is not random but highly optimized, on multiple levels.

Not only is the genetic code itself fine-tuned for error minimization, but it turns out that the set of amino acids used in life is also highly optimal — that is to say, the selection is not random. In 2011, a paper was published, in which the authors compared the coverage of the standard alphabet of 20 amino acids for “size, charge, and hydrophobicity with equivalent values calculated for a sample of 1 million alternative sets (each also comprising 20 members) drawn randomly from the pool of 50 plausible prebiotic candidates.”2 They found that,

…the standard alphabet exhibits better coverage (i.e., greater breadth and greater evenness) than any random set for each of size, charge, and hydrophobicity, and for all combinations thereof. In other words, within the boundaries of our assumptions, the full set of 20 genetically encoded amino acids matches our hypothesized adaptive criterion relative to anything that chance could have assembled from what was available prebiotically.

I wrote about this paper when it came out here.

A more recent paper, published in 2017 in The FEBS Journal, argued that the set of amino acids commonly used throughout biology is fundamentally non-random.3 The authors argue that, when compared to other sets of amino acids in relation to “component atoms, functional groups, biosynthetic cost, use in a protein core or on the surface, solubility and stability,” there are very good reasons why biology uses the conventional set of amino acids and not others. He observes that “Applying these criteria to the 20 standard amino acids, and considering some other simple alternatives that are not used, we find that there are excellent reasons for the selection of every amino acid. Rather than being a frozen accident, the set of amino acids selected appears to be near ideal.”

Functional Groups

Doig notes that “the choice of functional groups is rather limited in small molecules when using only C, H, O, N or S.” Carbon-nitrogen bonds, carboxyls, hydroxyls, amides, and amines are stable chemical groups that can form electrostatic interactions and hydrogen bonds. Alternative chemical groups (such as esters, anhydrides, and nitriles) are too prone to hydrolysis in an aqueous environment. Moreover, aldehydes and ketones are too chemically reactive.

Biosynthetic Cost

Another property that determines which amino acids are used by the cell is the energetic cost of their biosynthesis in terms of glucose and ATP molecules: “For example, Leu costs only 1 ATP, but its isomer Ile costs 11. Why would life ever therefore use Ile instead of Leu, if they have the same properties?” Doig further notes that “Larger is not necessarily more expensive; Asn and Asp cost more in ATP than their larger alternatives Gln and Glu, and large Tyr costs only two ATP, compared to 15 for small Cys. The high cost of sulfur-containing amino acids is notable.”

Burial and Surface

A close-packed core of a protein (where there are few empty spaces) maximizes weak attractions between atoms (van der Waals interactions), which make the protein more stable. Thus, “A solid core is essential to stabilize proteins and to form a rigid structure with well-defined binding sites.” This means that having nonpolar side chains is important to stabilize close-packed hydrophobic cores. On the other hand, polar and charged amino acid side chains, which are exposed on a protein surface, promote solubility in the aqueous environment.

Solubility

Doig further observes that “the least soluble amino acid at pH 7 in water is Tyr, so any less soluble than this may not be acceptable.”

Stability

Doig also notes that “even with stable functional groups, some amino acids are prone to unwanted reactions, such as cyclisation or acyl transfer, that can lead to decomposition or racemisation.”

The Implications

Doig proceeds to consider each of the twenty commonly used amino acids, evaluating for each its suitability for life relative to other amino acid sets. He concludes that “There are excellent reasons for the choice of every one of the 20 amino acids and the nonuse of other apparently simple alternatives. If all else fails, one can resort to chance or a ‘frozen accident’, as an explanation.” Curiously, he fails to consider an alternative explanation, which seems to fit the evidence better, and for which we already possess independent evidence — i.e., purposeful selection by an intelligent mind.

Significantly, these data indicate that the space of usable amino acids is severely constrained. Evolutionary mechanisms would, therefore, need to explore a vast chemical space and converge on a highly optimized set. Once the canonical genetic code is established, it would be extremely difficult to change it over time, since each amino acid would be tied to specific codons, tRNAs, and aminoacyl-tRNA synthetases. Modifying the set of amino acids would thus require significant rewiring. Reassignments of the codons and amino acids would affect every polypeptide made by the cell and would wreak havoc on the translation of many different proteins. On the other hand, reducing the alphabet of amino acids significantly constrains the proteins that can be made. This, in turn, would constrain the chemistry and needed structural precision for primitive systems of DNA replication.

Intelligent Design

Intelligent agents are uniquely capable of purposefully selecting between options from a large search space. The fact that the set of twenty amino acids conventionally used in life is non-random but in fact highly optimized is not surprising on the hypothesis that their selection was by an intelligent mind. On the other hand, they are wildly surprising on the hypothesis that it arose by unguided processes. In view of this overwhelmingly top-heavy likelihood ratio, these findings point to teleology as being the best explanation.

Notes

Crick FH. The origin of the genetic code. J Mol Biol. 1968 Dec;38(3):367-79. doi: 10.1016/0022-2836(68)90392-6. PMID: 4887876.↩︎
Philip GK, Freeland SJ. Did evolution select a nonrandom “alphabet” of amino acids? Astrobiology. 2011 Apr;11(3):235-40. doi: 10.1089/ast.2010.0567. Epub 2011 Mar 24. PMID: 21434765.↩︎
Doig AJ. Frozen, but no accident — why the 20 standard amino acids were selected. FEBS J. 2017 May;284(9):1296-1305. doi: 10.1111/febs.13982. Epub 2017 Jan 13. PMID: 27926995.↩︎

Jonathan McLatchie

Resident Biologist and Fellow, Center for Science and Culture

Dr. Jonathan McLatchie holds a Bachelor’s degree in Forensic Biology from the University of Strathclyde, a Masters (M.Res) degree in Evolutionary Biology from the University of Glasgow, a second Master’s degree in Medical and Molecular Bioscience from Newcastle University, and a PhD in Evolutionary Biology from Newcastle University. Previously, Jonathan was an assistant professor of biology at Sattler College in Boston, Massachusetts. Jonathan has been interviewed on podcasts and radio shows including “Unbelievable?” on Premier Christian Radio, and many others. Jonathan has spoken internationally in Europe, North America, South Africa and Asia promoting the evidence of design in nature.

PET 2 LEVIN

noreply@blogger.com (DG) — Mon, 09 Mar 2026 09:59:00 +0000

Planaria Memory & Xenobots: Detailed Breakdown

PART 1: PLANARIA AND MORPHOLOGICAL MEMORY

Background: Why Planaria?

Planaria (Dugesia japonica and related species) are freshwater flatworms with an almost absurd capacity for regeneration. Cut one into 200 pieces, and you get 200 new worms. Every fragment — even a tiny tail segment with no brain tissue whatsoever — will regenerate a complete, properly oriented animal.

This alone is remarkable. But Levin's lab discovered something far stranger.

The Classic Setup: Polarity and Bioelectrics

Every planarian has a defined anterior-posterior axis — a head end and a tail end. This polarity is maintained by a gradient of bioelectric signals across the body, particularly involving:

Gap junctions — protein channels that directly connect neighboring cells, allowing ions and small molecules to flow between them
Ion pumps (especially V-ATPase, an H⁺ pump) that create voltage differentials across tissues
Neurotransmitters like serotonin that act as patterning signals even outside the nervous system

The key insight: this bioelectric pattern is not just a readout of genetic instructions. It is itself instructive — it tells cells where they are and what they should become. It functions like a map or a blueprint held in electrical form across the tissue.

The Experiment: Erasing and Overwriting the Memory

Here is what Levin's lab did, step by step:

Step 1 — Cut the worm A planarian is cut transversely, producing a head fragment and a tail fragment. Normally:

The head fragment regenerates a new tail at the wound site
The tail fragment regenerates a new head at the wound site

This is normal polarity — the body "knows" which end is which.

Step 2 — Pharmacological intervention during regeneration While the tail fragment is regenerating (the critical window is the first ~24 hours after cutting), researchers bathe it in octanol — a drug that blocks gap junctions, severing the bioelectric communication between cells.

What happens? The tail fragment, unable to read its normal bioelectric positional information, sometimes regenerates a head at both ends — a two-headed worm. The chemical disruption confused the tissue's sense of axis.

Step 3 — The crucial discovery: the memory persists Here is where it gets extraordinary. After the two-headed worm is fully regenerated, researchers:

Remove the drug (restore normal chemical environment)
Allow the worm to live normally for weeks
Then cut it again — no drugs, no intervention

A normal worm, cut in this state, would regenerate with correct polarity. But these worms regenerated two-headed worms again — even though no drug was present during the second regeneration.

The altered bioelectric state had become self-sustaining. The tissue had "learned" a new body plan and perpetuated it across generations of regeneration without any genetic change and without ongoing chemical intervention.

What Is Actually Being "Remembered"?

This is not memory in the neural sense — there are no neurons storing an engram. What's happening is:

Bioelectric state as memory: The pattern of ion flows, membrane voltages, and gap junction connectivity across the tissue constitutes a stable attractor state — a self-reinforcing electrical pattern that cells maintain and propagate when they divide and communicate.

Think of it like a standing wave in a medium. The wave pattern persists not because any single molecule holds it, but because the dynamics of the system continuously recreate it. When you cut the worm, the new cells inherit the electrical environment of their neighbors and reproduce the same pattern.

The "Body Plan Morphogenetic Field": Levin frames this in terms of a morphogenetic field — a distributed representation of target anatomy encoded not in DNA sequence but in the bioelectric state of the tissue. DNA provides the parts list (what proteins are available); the bioelectric field provides the blueprint (how those parts should be assembled).

The planaria experiments show this blueprint can be:

Altered (by disrupting gap junctions)
Stabilized in its new form (self-reinforcing dynamics)
Transmitted across regenerative events (new cells adopt the electrical state of existing cells)
Maintained without ongoing external signals

The Deeper Implication

This means the worm's body plan is not simply computed fresh from the genome each time. There is a second layer of information — above the genome, encoded in bioelectric dynamics — that stores and propagates the target morphology.

Levin uses the analogy of computer hardware vs. software: the genome is the hardware (fixed, inherited), but the bioelectric pattern is the software running on top — and that software can be edited, corrupted, and rewritten independently of the hardware.

This is teleological in a deep sense: the tissue is not just following chemical gradients passively. It is actively comparing its current state to a stored target state and making corrections. When that target state is altered, the corrections drive toward the new target.

PART 2: XENOBOTS — LIVING MACHINES AND KINEMATIC SELF-REPLICATION

What Are Xenobots?

Xenobots were first reported in 2020, created collaboratively by Levin's lab at Tufts and Josh Bongard's computational lab at the University of Vermont.

They are made from Xenopus laevis — the African clawed frog — specifically from ectodermal cells (cells that would normally become skin) harvested from early embryos.

Crucially: these cells are removed from their normal developmental context. They are no longer receiving the chemical signals that would tell them "you are part of a frog embryo, become skin." Freed from that context, they exhibit novel, emergent behaviors that no frog has ever exhibited — and that were never programmed.

Stage 1: Self-Assembly and Spontaneous Organization

When ectodermal cells are harvested and placed in a dish as a loose aggregate, something remarkable happens over ~24 hours:

The cells do not die (as isolated cells typically would)
They reorganize — moving, adhering, and arranging themselves into a compact, roughly spherical or ovoid body
Cells with cilia (hair-like projections, normally used to move mucus across skin) reorient those cilia outward, creating a coordinated propulsion system
The resulting structure, roughly 500–700 micrometers across, moves through fluid in a directed way

No blueprint was given. No morphogen gradient was applied. The cells used their existing genetic toolkit — developed for one purpose (being frog skin) — to build a novel functional organism suited to their new context.

This is a profound demonstration of context-dependent agency: the cells are not executing a fixed program, they are solving the problem of "what should I be?" given their current situation.

Stage 2: The AI-Designed Body Plans

In the 2020 paper, Bongard's team used an evolutionary algorithm running on a supercomputer to design optimal xenobot body shapes for specific tasks (like moving in a particular direction or pushing objects).

The process:

Simulate thousands of random arrangements of frog cells in silico
Evaluate which arrangements best accomplish a target behavior
Select the best performers, mutate them, repeat
Take the winning design and build it in real life using microsurgery on real frog cells

Strikingly, the real xenobots closely matched the behavior of their simulated counterparts — confirming that the cells were indeed executing coherent, predictable behaviors, not random activity.

But the spontaneously self-assembled xenobots (without AI design) were arguably more interesting, because they required no external design at all.

Stage 3: Kinematic Self-Replication (2021)

The 2021 PNAS paper reported something that genuinely shocked the scientific community.

The setup: Researchers placed xenobots in a dish containing a large supply of loose, dissociated frog cells — essentially raw cellular material.

What happened: The xenobots spontaneously began to gather the loose cells, sweeping them together into piles using their ciliary motion.

Those piles of gathered cells then self-assembled into new xenobots.

Those new xenobots could, in turn, gather more loose cells and produce another generation.

This is kinematic self-replication — replication through motion and behavior rather than through chemical template copying (like DNA replication). It is an entirely different category of reproduction from anything previously documented.

Why "Kinematic" Is the Key Word

In biology, replication almost always means template-directed chemical copying: DNA unzips, complementary bases are added, you get two copies. The information is in the molecule.

Kinematic self-replication is different: the information is in the behavior and shape of the organism. The xenobot "replicates" not by copying its molecules but by doing things in the world — moving, gathering, organizing — that result in a new entity similar to itself.

This is closer to how a whirlpool "reproduces" (by creating conditions for new whirlpools) than how a bacterium reproduces. But xenobots are vastly more complex and directed.

Von Neumann had theorized kinematic self-replicators in the 1940s as a thought experiment. Xenobots are the first biological instantiation.

The Shape Discovery: C-Shape Matters

A critical finding from the 2021 work: the default spherical xenobots replicate poorly — they gather some cells but the process is inefficient and quickly dies out after 1–2 generations.

When the AI evolutionary algorithm was again applied — this time to optimize for replication efficiency — it discovered that a C-shaped or pac-man-shaped xenobot was dramatically more effective at gathering and corralling loose cells into the interior of the C, where they could aggregate and self-organize.

This C-shape does not exist in frog biology. It was discovered by an algorithm, then built, then confirmed to work. The frog cells — never having "intended" to replicate this way — executed the replication faithfully when given the right body shape.

The Philosophical Payload

The xenobot work raises several deeply unsettling and important questions:

1. What is an organism? Xenobots are made of frog cells, carry frog DNA, but are not frogs. They have never existed in nature. They exhibit goal-directed behavior (moving, replicating) that no frog exhibits. Are they a new species? A new category of being?

2. What is reproduction? Xenobots don't pass on genetic information to their "offspring" — the daughter xenobots have the same genome as the parent, inherited from the original frog embryo. What's being transmitted is form and behavior, not genetic novelty. This blurs the line between reproduction and construction.

3. Where does the "goal" come from? The xenobots were not programmed to gather cells and replicate. This behavior emerged from the interaction of cell-level properties (cilia, adhesion, motility) with the physical environment. The goal-directedness is real — measurable, reproducible — but it wasn't designed in. It emerged.

Levin argues this shows that agency and teleology can be genuine properties of matter — not imposed from outside by a designer or genome, but arising from the dynamics of sufficiently complex, self-organizing systems.

Connecting Planaria and Xenobots: The Unified Theme

Both experiments point to the same conclusion:

	Planaria	Xenobots
Substrate	Adult flatworm tissue	Embryonic frog cells
Context change	Chemical disruption of polarity signals	Removal from embryonic context
Response	Adopt and maintain new body plan	Self-assemble novel body plan
Memory/Goal	Bioelectric target state	Emergent morphogenetic goal
Key finding	Morphological memory above genome	Goal-directed behavior without programming

In both cases, cells are doing something more than executing a genetic program. They are reading their environment, computing a response, and pursuing a target state — even when that target state has been altered or is entirely novel.

This is Levin's core claim made flesh: biology is cognitive all the way down, and the gap between "mere matter" and "minded agent" is not a gap at all, but a continuum we are only beginning to measure.

Michael Levin - teleology in biology

noreply@blogger.com (DG) — Mon, 09 Mar 2026 09:58:00 +0000

Michael Levin is a developmental biologist at Tufts University whose work is reshaping how we think about intelligence, agency, and goal-directedness in living systems. Here's an overview of his revolution:

The Core Idea: Intelligence Is Not Brain-Specific

Levin argues that cognition and agency are substrate-independent — they don't require neurons or brains. Instead, any system capable of pursuing goals, remembering states, and problem-solving in a flexible way deserves to be called "intelligent" in some meaningful sense.

Teleology Rehabilitated

Classical science largely banished teleology (goal-directedness) from biology after Descartes and the mechanistic revolution. Levin is helping bring it back — not as mysticism, but as a legitimate, measurable property of biological systems.

His key insight: organisms at every scale — from single cells to tissues to whole animals — exhibit goal-directed behavior toward specific target states (like a body plan or organ shape). This isn't metaphor; it's observable, manipulable, and quantifiable.

The Planaria & Xenobot Experiments

Levin's lab produced some of the most striking evidence:

Planaria (flatworms) remember their head-tail polarity even when cut and regrown in reversed chemical environments — their tissues "remember" a target morphology.
Xenobots — living robots made from frog stem cells — spontaneously self-assembled, moved, and even exhibited a crude form of kinematic self-replication, a behavior no one programmed.
Anthrobots (2023) — made from human lung cells — self-assembled and promoted neural repair in lab dishes, again without explicit programming.

These organisms pursue goals that weren't hardcoded — they compute solutions to problems using biological hardware.

The Cognitive Light Cone

One of Levin's most important theoretical contributions is the "cognitive light cone" — the idea that different agents have different scales over which they integrate information and pursue goals:

A bacterium has a tiny cognitive light cone (milliseconds, micrometers)
A brain has a larger one (years, the whole body)
A society or ecosystem might have an even larger one

This gives a continuous, non-binary framework for intelligence — dissolving the sharp line between "dumb matter" and "minded beings."

Bioelectricity as the Medium

Levin's lab focuses heavily on bioelectric signaling — electrical patterns across cell membranes (not just in neurons) that encode positional and morphogenetic information. These signals function like a body-wide "blueprint memory":

Disrupting bioelectric patterns causes radical morphological changes (e.g., making flatworms grow two heads)
Restoring correct bioelectric patterns can cure cancer in tadpoles or induce limb regeneration

Bioelectricity appears to be a proto-cognitive medium — a way that non-neural tissue computes and communicates goal-states.

Implications Across Fields

Philosophy of mind: Mind and agency exist on a continuum; we need new frameworks beyond neurocentric consciousness theories.

AI & robotics: True intelligence may require goal-directedness and embodiment, not just computation. Levin collaborates with Daniel Dennett and others on these questions.

Medicine: Cancer may be a failure of cellular agency — cells "forgetting" their role in the larger collective and reverting to unicellular selfishness. Treating it bioelectrically rather than just chemically is an active research direction.

Ethics: If intelligence is a spectrum, where does moral consideration begin? Levin takes this seriously — his lab has published on the ethics of creating novel cognitive entities (like xenobots).

The Deeper Philosophical Bet

Levin is essentially arguing that teleology is real, physical, and measurable — that "what is this system trying to do?" is a legitimate scientific question at every scale of biology. This cuts against both naive mechanism and mystical vitalism, carving out a rigorous third path: computational teleology, where goal-states are physically encoded and causally efficacious.

It's one of the most ambitious research programs in contemporary science — simultaneously experimental, theoretical, and deeply philosophical.

OW LITTLE WE UNDERSTAND. READ THE NEXT TWO POSTS TO ENTER A NEW WORLD OF BIOLOGY

noreply@blogger.com (DG) — Mon, 09 Mar 2026 09:54:00 +0000

Worth investigation

noreply@blogger.com (DG) — Tue, 03 Feb 2026 09:52:00 +0000

Terminal lucidity

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Terminal lucidity, also known as paradoxical lucidity, rallying or the rally, is an unexpected return of mental clarity and memory, or suddenly regained consciousness that occurs in the time shortly before death in patients with severe psychiatric or neurological disorders.^[1][2][3] This condition has been reported by physicians since the 19th century.

History

Several case reports in the 19th century described the unusual condition of an improvement and recovery of the mental state in patients days or weeks before death. William Munk, for instance, in 1887 called the phenomenon "lucidity before death".^[4] According to historical reviews headed by the biologist Michael Nahm, who also has an interest in mediumship and near-death experiences,^[5] the phenomena have been noted in patients with diseases which cause progressive cognitive impairment, such as Alzheimer's disease, but also schizophrenia, tumors, strokes, meningitis, and Parkinson's disease.^[6][7][8] However, terminal lucidity is not currently listed as a medical term.^[9]

According to Nahm, it may be present even in cases of patients with previous mental disability.^[10] Nahm defines two subtypes: one that comes gradually (a week before death), and another that comes rapidly (hours before death), with the former occurring more often than the latter. There may be plenty of cases reported in literature, although the phrase terminal lucidity was coined in 2009.^[11] Interest in this condition, which dwindled during the 20th century, has been reignited by further studies.^[4] A 2020 research screened for what the authors preferred to call "paradoxical lucidity", a general term for unexpected remissions in dementias, independent of whether it followed a terminality process or not; it found strong association of the condition as a near-death phenomenon and stated that it can overlap the concept of "terminal lucidity" in some cases.^[6] Such a paradoxical condition is considered a challenge to the irreversibility paradigm of chronic degenerative dementias such as Alzheimer's.^[12]

Causes

The earliest attempt at explanation was issued by Benjamin Rush in 1812, which proposed the hypothesis that a reawakening could be due to a nervous excitation caused by pain or fever, or else because of dead blood vessels, released by a leakage of water in the brain chambers. Johannes Friedreich, in 1839, proposed that the factors causing impairments may be reversed shortly before death, analogous to the reabsorption in terminal patients with hydrocephalus, and that high fever may be a cause of it. According to Macleod (2009)^[13] in his observations, explanative causes could not be found for the variety of cases, but it was suggested that due to the modern pharmacology in terminal cases, the condition may be less common today.^[4] A recent proposed mechanism includes a non-tested hypothesis of neuromodulation, according to which near-death discharges of neurotransmitters and corticotropin-releasing peptides act upon preserved circuits of the medial prefrontal cortex and hippocampus, promoting memory retrieval and mental clarity.^[14]

References

1. Koczanowicz, Leszek (2020). "Chapter 12 - The Anxiety of Clairvoyance: Terminal Lucidity and the End of Culture". Anxiety and Lucidity: Reflections on Culture in Times of Unrest. Routledge. pp. 162–198. ISBN 978-0367218232.

2. Mendoza, Marilyn A. "Why Some People Rally for One Last Goodbye Before Death". Psychology Today (blog). Retrieved 26 August 2019.

3. Bursack, Carol Bradley. "When Loved Ones Rally Before Death". AgingCare. Retrieved 26 August 2019.

4. Chiriboga-Oleszczak, Boris Alejandro (2017-03-28). "Terminal lucidity". Current Problems of Psychiatry. 18 (1): 34–46. doi:10.1515/cpp-2017-0003. ISSN 2353-8627.

5. Michael Nahm

6. Batthyány, Alexander; Greyson, Bruce (2020-08-27). "Spontaneous remission of dementia before death: Results from a study on paradoxical lucidity". Psychology of Consciousness: Theory, Research, and Practice. 8: 1–8. doi:10.1037/cns0000259. ISSN 2326-5531. S2CID 225192667.

7. Nahm, Michael; Greyson, Bruce (December 2009). "Terminal lucidity in patients with chronic schizophrenia and dementia: a survey of the literature". Journal of Nervous and Mental Disease. 197 (12): 942–944. doi:10.1097/NMD.0b013e3181c22583. ISSN 1539-736X. PMID 20010032.

8. Nahm, Michael; Greyson, Bruce; Kelly, Emily Williams; Haraldsson, Erlendur (July–August 2012). "Terminal lucidity: a review and a case collection". Archives of Gerontology and Geriatrics. 55 (1): 138–142. doi:10.1016/j.archger.2011.06.031. ISSN 1872-6976. PMID 21764150.

9. Webster Medical Dictionary

10. Nahm, M.; Greyson, B. (2014). "The Death of Anna Katharina Ehmer: A Case Study in Terminal Lucidity". OMEGA. 68 (1): 77–87. doi:10.2190/OM.68.1.e. PMID 24547666. S2CID 1265185.

11. Bering, Jesse (2017). "One Last Goodbye: The Strange Case of Terminal Lucidity". Scientific American Blog Network.

12. Mashour, George A.; Frank, Lori; Batthyany, Alexander; Kolanowski, Ann Marie; Nahm, Michael; Schulman-Green, Dena; Greyson, Bruce; Pakhomov, Serguei; Karlawish, Jason; Shah, Raj C. (2019-06-19). "Paradoxical lucidity: A potential paradigm shift for the neurobiology and treatment of severe dementias". Alzheimer's & Dementia. 15 (8): 1107–1114. doi:10.1016/j.jalz.2019.04.002. ISSN 1552-5260. PMID 31229433.

13. Macleod, AD (December 2009). "Lightening up before death". Palliative & Supportive Care. 7 (4): 513-516. doi:10.1017/S1478951509990526. PMID 19939314.

14. Bostanciklioğlu, Mehmet (January 2021). "Unexpected awakenings in severe dementia from case reports to laboratory". Alzheimer's & Dementia. 17 (1): 125–136. doi:10.1002/alz.12162. ISSN 1552-5279. PMID 33064369. S2CID 222840626.

Important update on the Human-chimpanzee DNA fiasco - REVISED 9/3/26

noreply@blogger.com (DG) — Sat, 22 Nov 2025 17:13:00 +0000

[[IT HAS COME TO MY ATTENTION THAT THIS PUBLICATUOIN AND THE AUTHOR OF THIS ARTICLE HAVE PRODUCED MATERIAL WHICH I WOULD NOT ENDORSE. HENCE THIS DISWCLAIMER. DG.]]

Are human populations 99.9% identical?

How a correct finding has been incorrectly interpreted.

Nov 21

https://www.aporiamagazine.com/p/are-human-populations-999-identical

Written by Peter Frost.

You’ve probably heard that humans and chimpanzees are genetically 98 to 99% the same.

You’ve probably also heard that human populations are 99.9% the same. The second finding

has often been cited, for example by Hillary Clinton. In a speech to high school graduates,

the former First Lady mentioned “genetic research that shows humans are 99.9 percent the same”.

The differences in how we look — in our skin color, our eye color, our height — stem from

just one-tenth of 1 percent of our genes. And the differences among us — our cultures, our

religious beliefs, the music we like — it is all so small a distinction in our sea of common humanity.

Of course, one tenth of one percent is still a lot. In a post criticizing Clinton’s speech, anthropologist

John Hawks observed that “one-tenth of 1 percent of 3 billion is a heck of a large number —

3 million nucleotide differences between two random genomes” (Hawks, 2007). He added,

“We differ by one-tenth of 1 percent of nucleotides, this is enough to make coding differences

in a large fraction of our genes.”

In other words, the 0.1% figure is not the percentage of genes that are different. It’s the percentage

of individual nucleotides that are different. A single gene is a long chain of nucleotides, often

a very long one, and a single nucleotide mutation can significantly alter how the entire gene works.

In theory, then, each and every human gene could work differently from one population to another.

Moreover, as Hawks himself showed in a study published the same year, at least 7% of the human

genome has changed over the last 40,000 years — mostly the last 10,000 (Hawks et al., 2007).

This was when our ancestors were spreading over the globe and differentiating into today’s geographic

populations. Those populations cannot all share the

same 7% change.

Clearly, 0.1% isn’t the fraction of genes that differ among human populations. The true figure is certainly

larger. Again, each and every gene could differ among human populations by 0.1%, and such a

difference could affect how each and every one functions. Also, genes do not differ solely in

nucleotide sequences. They also differ in the way those sequences are arranged on the chromosomes.

The same sequence may be repeated consecutively or it may be copied and inserted somewhere else.

Such rearrangements can likewise affect how a gene functions. “Structural variations, such as

copy-number variation and deletions, inversions, insertions and duplications, account for much more human genetic variation than single nucleotide diversity” (Wikipedia, 2025).

This structural variation became apparent during the first complete sequencing of a human genome:

Of the 4.1 million variations between chromosome sets, 3.2 million were SNPs, while nearly

one million were other kinds of variants, such as insertion/deletions (“indels”), copy number variants,

block substitutions, and segmental duplications. While the SNPs outnumbered the non-SNP types of

variants, the non-SNP variants involved a larger portion of the genome. This suggests that human-to-human variation is much greater than previously thought. (Phys.org, 2007; see also Levy et al., 2007)

If we return to comparing humans and chimpanzees, we can measure the total genetic difference

between them by looking at what the genes make, i.e., proteins. The two species differ in about 80%

of their proteins — a figure far higher than the 1 to 2% difference in their nucleotide sequences

(Glazko et al., 2005).

Even this 80% figure is not the whole story. Some genes regulate how other genes are expressed,

often thousands of others, and thus play a key role in growth and development. These “regulator”

genes are much fewer in number than other genes but far greater in their effects. Plus, they differ

much more between humans and chimpanzees than other genes do. Whereas the two species are

almost identical in the nucleotide sequences of their genes and the amino acid sequences of their

proteins, and relatively similar in the proteins that make up their tissues, they differ radically

in the way their tissues grow and develop, notably the neural tissues of the brain.

This was already clear to two researchers, Mary-Claire King and A.C. Wilson, when, half a century ago,

they discovered the startling similarity of nucleotide sequences and amino acid sequences between

humans and chimpanzees:

The molecular similarity between chimpanzees and humans is extraordinary because they differ far

more than sibling species in anatomy and way of life. Although humans and chimpanzees are rather

similar in the structure of the thorax and arms, they differ substantially not only in brain size but also

in the anatomy of the pelvis, foot, and jaws, as well as in relative lengths of limbs and digits. Humans

and chimpanzees also differ significantly in many other anatomical respects, to the extent that nearly

every bone in the body of a chimpanzee is readily distinguishable in shape or size from its human

counterpart. Associated with these anatomical differences there are, of course, major differences in

posture, mode of locomotion, methods of procuring food, and means of communication. Because of

these major differences in anatomy and way of life, biologists place the two species not just in separate

genera but in separate families …

The contrasts between organismal and molecular evolution indicate that the two processes are to a large

extent independent of one another. Is it possible, therefore, that species diversity results from molecular

changes other than sequence differences in proteins? … According to this hypothesis, small differences

in the time of activation or in the level of activity of a single gene could in principle influence

considerably the systems controlling embryonic development. The organismal differences between

chimpanzees and humans would then result chiefly from genetic changes in a few regulatory systems,

while amino acid substitutions in general would rarely be a key factor in major adaptive shifts. (King & Wilson, 1975, pp. 113–114)

Genetic distance between humans and chimpanzees, compared to genetic distances in other taxa.

(King & Wilson, 1975, p. 113)

In this context, the two researchers were thinking not only about the human-chimpanzee difference

but also about the differences within our species:

[The human-chimpanzee] distance is 25 to 60 times greater than the genetic distance between human

races. In fact, the genetic distance between Caucasian, Black African, and Japanese populations is less

than or equal to that between morphologically and behaviorally identical populations of other species. (King & Wilson, 1975, p. 113)

The above paragraph appears in the middle of a discussion about the human-chimpanzee genetic d

istance, and its paradoxical smallness. In fact, the two researchers highlight this paradox right after:

However, with respect to genetic distances between species, the human-chimpanzee D value is e

xtraordinarily small, corresponding to the genetic distance between sibling species of Drosophila or

mammals. Nonsibling species within a genus … generally differ more from each other, by e

lectrophoretic criteria, than humans and chimpanzees. The genetic distances among species from

different genera are considerably larger than the human-chimpanzee genetic distance.

(King & Wilson, 1975, p. 113)

How should we measure the genetic distance between two human populations? There is no easy answer

because few species resemble our own. Our species is unusual in that it evolved rapidly at the very

time it was splitting up into populations across different environments — not only natural environments

from the equator to the arctic but also an ever-wider range of cultural environments. In fact, this entry

into so many environments largely explains the concurrent rapidity of human genetic evolution.

Natural selection has thus shaped human populations in highly divergent ways (Akbari et al., 2024;

Cochran & Harpending, 2009; Frost, 2023a; Hawks et al., 2007; Kuijpers, et al., 2022;

Libedinsky et al., 2025; Piffer & Kirkegaard, 2024; Rinaldi, 2017).

In such a situation, differences in selection contribute much more to genetic diversity between

populations than to genetic diversity within populations. Keep in mind that natural selection causes

a population to diversify only in certain limited cases (e.g., frequency-dependent selection). In most

cases, a population is diversified by stochastic processes of little adaptive consequence, since everybody

is adapting to the same environment and the same selection pressures.

We thus return to the same paradox: Fst is relatively low in our species even though human populations

differ much more anatomically than do most sibling species in the animal kingdom. As Charles Darwin

noted, a naturalist would consider some human groups to be “as good species as many to which he had

been in the habit of affixing specific names.” The paradox exists because humans split rapidly to

colonize highly divergent environments, with the result that genetic diversity between populations is

much more consequential than genetic diversity within populations. We are therefore comparing apples

to oranges when we calculate human Fst (Darwin, 1936 [1888], pp. 530-531; King & Wilson, 1975;

Frost, 2023b).

What’s more, relatively little of our evolution has been at the level of nucleotide sequences or amino

acid sequences. It has been largely at a higher level — the duplication, rearrangement and regulation of

existing DNA in new ways (Yoo et al., 2025). This point came up in a recent discussion on X:

The widely cited Chimpanzee-Human 98-99% DNA similarity figures refer exclusively to nucleotide s

equence similarity within alignable genomic regions, which become misleading when portrayed as the t

otal amount of DNA shared. While this metric is important, as it highlights the strength of the

evolutionary constraints within the protein-coding and non-coding sequences found in alignable r

egions, it ignores the structural and regulatory differences that are key for shaping the phenotypic

differences between Chimpanzees and Humans. When combining these metrics, total

Chimpanzee-Human DNA similarity figures drop to ~84.7% (Origins Unveiled, 2025)

Admittedly, I have no idea how the author combined these metrics.

I don’t blame Hillary Clinton for drawing the wrong conclusion from the 99.9% estimate, but I’m less

forgiving toward those who have silently gone along with this fallacy while knowing better. Two

decades ago, John Hawks pointed out its flaws in a post criticizing Hillary’s speech. The post remained

on his website until he deleted it in 2021 — when many American academics got the memo that Hillary

had been right all along… on this issue and on any other.

“Nice research lab you have there. Pity if anything happened to it.”

When academics choose the path of silence, and withhold their objections, they help create a fake

consensus that ultimately brings academia into disrepute.

Peter Frost has a PhD in anthropology from Université Laval. His main research interest is the

role of sexual selection in shaping highly visible human traits. Find his newsletter here.

References

Akbari, A., Barton, A.R., Gazal, S., Li, Z., Kariminejad, M., Perry, A., Zeng, Y., Mittnik, A., Patterson,

N., Mah, M., Zhou, X., Price, A.L., Lander, E.S., Pinhasi, R., Rohland, N., Mallick, S., & Reich,

D. (2024). Pervasive findings of directional selection realize the promise of ancient DNA to elucidate

human adaptation. bioRxiv. https://doi.org/10.1101/2024.09.14.613021

Anon. (2007). Finding said to show “race isn’t real” scrapped

http://www.world-science.net/othernews/070904_human-variation.htm

Cochran, G. & Harpending, H. (2009). The 10,000 Year Explosion: How Civilization Accelerated

Human Evolution. Basic Books: New York.

https://www.amazon.ca/000-Year-Explosion-Civilization-Accelerated/dp/0465002218

Darwin, C. (1936 [1888]). The Descent of Man and Selection in relation to Sex. reprint of 2nd edition,

The Modern Library, New York: Random House.

Frost, P. (2023a). Human evolution didn’t slow down. It accelerated! Peter Frost’s Newsletter, July 12.

Frost, P. (2023b). Do human races exist? Peter Frost’s Newsletter. August 15.

Glazko, G., Veeramachaneni, V., Nei, M., & Makałowski, W. (2005). Eighty percent of proteins are

different between humans and chimpanzees. Gene, 346, 215-219. https://doi.org/10.1016/j.gene.2004.11.003

Hawks, J. (2007). Disagreeing with Hillary Clinton on human genetic differences. John Hawks Weblog https://web.archive.org/web/20210624221131/http://johnhawks.net/weblog/topics/race/

differences/clinton_2007_proportion_differences_speech.html

Hawks, J., Wang, E. T., Cochran, G. M., Harpending, H. C., & Moyzis, R. K. (2007). Recent acceleration of human adaptive evolution. Proceedings of the National Academy of Sciences, 104(52), 20753-20758. https://doi.org/10.1073/pnas.0707650104

King, M-C. & Wilson, A.C. (1975). Evolution at two levels in humans and chimpanzees:

Their macromolecules are so alike that regulatory mutations may account for their biological differences. Science, 188, 107-116. https://doi.org/10.1126/science.1090005

Kuijpers, Y., Domínguez-Andrés, J., Bakker, O.B., Gupta, M.K., Grasshoff, M., Xu, C.J., Joosten, L.A.B., Bertranpetit, J., Netea, M.G., & Li, Y. (2022). Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans. Frontiers in Genetics, 13, 833190. https://doi.org/10.3389/fgene.2022.833190

Levy S, Sutton G, Ng PC, Feuk L, Halpern AL, et al. (2007) The diploid genome sequence of an individual human. PLoS Biol, 5(10): e254. https://doi.org/10.1371/journal.pbio.0050254

Libedinsky, I., Wei, Y., de Leeuw, C., Rilling, J. K., Posthuma, D., & van den Heuvel, M. P. (2025). The emergence of genetic variants linked to brain and cognitive traits in human evolution. Cerebral Cortex, 35(8), bhaf127. https://doi.org/10.1093/cercor/bhaf127

Origins Unveiled (2025). Busting the 98% myth: Humans share only ~85% of their DNA with chimpanzees. September 5 https://x.com/OriginsUnveiled/status/1964040999468224774

Phys.org (2007). First individual genome sequence published. Phys.org. September 4. https://phys.org/news/2007-09-individual-genome-sequence-published.html

Piffer, D., & Kirkegaard, E.O.W. (2024). Evolutionary Trends of Polygenic Scores in European Populations from the Paleolithic to Modern Times. Twin Research and Human Genetics, 27(1), 30-49. https://doi.org/10.1017/thg.2024.8

Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., ... & Hurles, M. E. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444-454. https://doi.org/10.1038/nature05329

Rinaldi, A. (2017). We’re on a road to nowhere. Culture and adaptation to the environment are driving human evolution, but the destination of this journey is unpredictable. EMBO reports 18: 2094-2100. https://doi.org/10.15252/embr.201745399

Wikipedia (2025). Human genetic variation. https://en.wikipedia.org/wiki/Human_genetic_variation

Yoo, D., Rhie, A., Hebbar, P., Antonacci, F., Logsdon, G. A., Solar, S. J., ... & Eichler, E. E. (2025). Complete sequencing of ape genomes. Nature, 1-18. https://doi.org/10.1038/s41586-025-08816-3

A New Dimension of coding in DNA greatlyh increases informational content and

noreply@blogger.com (DG) — Tue, 04 Nov 2025 09:41:00 +0000

A Fake Headline, and a Real One, About DNA

_Casey
Luskin

_{https://scienceandculture.com/2025/11/a-fake-headline-and-a-real-one-about-dna/}

_{displays meaning for formerly thought junk DNA}

_{November
3, 2025}

My Google News feed thought I would be interested in an article on Yahoo News titled “Human DNA detected in 2 billion year old meteorite.” So I checked out the story and it’s fake news. No DNA, much less human DNA, was detected in a meteorite. Instead, we found very simple compounds which everyone already knew are common in meteorites. Here’s what you read in the story after you scroll pass the fake headline:

NASA’s and Japan’s missions both returned pieces of ancient asteroids to Earth. Inside the asteroids researchers have found carbon, ammonia, salts, and even amino acids, which are the molecules that make up proteins. In January 2025, scientists said OSIRIS-REx’s samples contained 14 of the 20 amino acids used by life on Earth, plus chemical precursors of DNA and RNA.

Great, but No Surprises There

And while it may sound impressive about the 14 of the 20 amino acids used by life, you can almost rest assured that they are a racemic mixture of both right and left handed amino acids and, as Jim Tour recently showed, they won’t be linking up into long polymer chains.

But if you read the article, there is an interesting admission:

“Bennu is basically a pantry full of ingredients,” said Dr. Jason Dworkin, NASA’s lead scientist on the OSIRIS-REx mission. “But it wasn’t quite the right conditions to make a cake. On Earth, we have cake, and we don’t know why.”

Did you get that? “Cake,” I believe, is supposed to mean life. So obviously on earth we have cake. And this lead NASA scientist is admitting we don’t know why there is life on earth. So the article might be bluffing about the discovery of human DNA in a meteorite, but at least it goes on to admit we don’t understand how life arose on earth. Very interesting!

The “Geometric Code”

Meanwhile, I also got an email from a science professor in our network about another news headline titled “Scientists uncover hidden ‘geometric code’ that helps DNA compute and remember.” This seems to be a real story because it’s based upon a study done by scientists at Northwestern University published in the journal Advanced Science, titled “Geometrically Encoded Positioning of Introns, Intergenic Segments, and Exons in the Human Genome.”

According to the news story, biologists have discovered a “second language” in our DNA that isn’t based upon the precise sequence of bases but rather upon the structural shape of the DNA molecule — as the story puts it “a second language built on geometry rather than chemistry.” Here’s how the finding is described:

Led by biomedical engineer Vadim Backman, the study reveals that DNA’s 3D physical structure holds a “geometric code” — a system that allows cells to compute, remember and adapt.

Essentially, the idea is that the three-dimensional shape of the chromosomes is vital to modulate and control many genomic processes such as gene transcription. Parts of genes which may be distant in one dimension on a chromosome can be brought close together due to the three-dimensional “packing” of chromosomes in the nucleus, creating “functional packing layers of domains” also called “packing domains” (PDs). From the technical paper:

[I]ntrons and intergenic segments are coupled to adjacent exons to generate coherent packing domain volumes … We wish to propose a radical hypothesis — described within this work — that nanoscale packing geometry is encoded in the positioning of exons, introns, and intergenic segments as projections of the functional layers of PDs [packing domains] …

This idea that the three-dimensional shapes of chromosomes are important for controlling genome function is receiving more and more attention in the literature. Earlier this year I discussed (see here and here) how much of the newly discovered DNA that is different between humans and chimps has been found to be “non-B” DNA — often repetitive DNA — where the number of copies of repeats control the 3D structural shape of chromosomes, and the 3D shape of chromosomes helps regulate genome function. This means that even repetitive DNA is functionally important in shaping chromosome structure, which is very important for creating these “domains” of genome regulation.

If You’re Catching the Drift…

All of this has direct and negative implications for the idea of “junk DNA” because it suggests that huge amounts of our DNA may be functionally important for controlling chromosomal architecture.

In fact, the implications of this model for junk DNA were made explicit in a 2019 paper in BioEssays that I reported on which found that the GC content of chromosomes helps define topologically associating domains (TADs). These TADs bring parts of chromosomes spatially near one another in the nucleus in order to regulate things like gene transcription. The paper calls GC-content based code a “genomic code,” and finds it has important implications against the idea of junk DNA:

[T]he genomic code, which is responsible for the pervasive encoding and molding of primary chromatin domains (LADs and primary TADs, namely the “gene spaces”/“spatial compartments”) resolves the longstanding problems of “non-coding DNA,” “junk DNA,” and “selfish DNA” leading to a new vision of the genome as shaped by DNA sequences.

Now, this new paper in Advance Sciences adds to the body of evidence showing that the 3D shape of chromosomes is vital to creating chromosomal “domains” that interact to produce things like gene transcripts. The fact that they are calling it a “geometric code,” which is “a second language built on geometry rather than chemistry,” shows just how important the three-dimensional architecture of chromosomes is in regulating genome function.

Casey Luskin is a geologist and an attorney with graduate degrees in science and law, giving him expertise in both the scientific and legal dimensions of the debate over evolution. He earned his PhD in Geology from the University of Johannesburg, and BS and MS degrees in Earth Sciences from the University of California, San Diego, where he studied evolution extensively at both the graduate and undergraduate levels. His law degree is from the University of San Diego, where he focused his studies on First Amendment law, education law, and environmental law.

A Revolution in Ev0lutionary Theory

noreply@blogger.com (DG) — Mon, 08 Sep 2025 07:43:00 +0000

Mutations driving evolution are informed by the genome, not random, study suggests

by University of Haifa

edited by Gaby Clark, reviewed by Robert Egan

https://phys.org/news/2025-09-mutations-evolution-genome-random.html

Editors' notes

MEMDS experimental setup. Credit: Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2424538122

A study published in the Proceedings of the National Academy of Sciences by scientists from Israel and Ghana shows that an evolutionarily significant mutation in the human APOL1 gene arises not randomly but more frequently where it is needed to prevent disease, fundamentally challenging the notion that evolution is driven by random mutations and tying the results to a new theory that, for the first time, offers a new concept for how mutations arise.

Implications for biology, medicine, computer science, and perhaps even our understanding of the origin of life itself, are potentially far reaching.

A random mutation is a genetic change whose chance of arising is unrelated to its usefulness. Only once these supposed accidents arise does natural selection vet them, sorting the beneficial from the harmful. For over a century, scientists have believed that a series of such accidents has built up over time, one by one, to create the diversity and splendor of life around us.

However, it has never been possible to examine directly whether mutations in the DNA originate at random or not. Mutations are rare events relative to the genome's size, and technical limitations have prevented scientists from seeing the genome in enough detail to track individual mutations as they arise naturally.

To overcome this, Prof. Adi Livnat of the University of Haifa, director of the Sagol Lab for Evolution Research, lead author Dr. Daniel Melamed and the team developed a new ultra-accurate detection method and recently applied it to the famous HbS mutation, which protects from malaria but causes sickle-cell anemia in homozygotes.

Results showed that the HbS mutation did not arise at random, but emerged more frequently exactly in the gene and population where it was needed. Now, they report the same nonrandom pattern in a second mutation of evolutionary significance.

The new study examines the de novo origination of a mutation in the human APOL1 gene that protects against a form of trypanosomiasis, a disease that devastated central Africa in historical times and until recently has caused tens of thousands of deaths there per year, while increasing the risk of chronic kidney disease in people with two copies.

If the APOL1 mutation arises by chance, it should arise at a similar rate in all populations, and only then spread under Trypanosoma pressure. However, if it is generated nonrandomly, it may actually arise more frequently where it is useful.

Results supported the nonrandom pattern: the mutation arose much more frequently in sub-Saharan Africans, who have faced generations of endemic disease, compared to Europeans, who have not, and in the precise genomic location where it confers protection.

"The new findings challenge the notion of random mutation fundamentally," said Livnat.

From random mutation to natural simplification

Historically, there have been two basic theories for how evolution happens— random mutation and natural selection, and Lamarckism—the idea that an individual directly senses its environment and somehow changes its genes to fit it. Lamarckism has been unable to explain evolution in general, so biologists have concluded that mutations must be random.

Livnat's new theory moves away from both of these concepts, proposing instead that two inextricable forces underlie evolution. While the well-known external force of natural selection ensures fitness, a previously unrecognized internal force operates inside the organism, putting together genetic information that has accumulated over generations in useful ways.

To illustrate, take fusion mutations, a type of mutation where two previously separate genes fuse to form a new gene. As for all mutations, it has been thought that fusions arise by accident: one day, a gene moves by error to another location and by chance fuses to another gene, once in a great while, leading to a useful adaptation. But Livnat's team has recently shown that genes do not fuse at random.

Instead, genes that have evolved to be used together repeatedly over generations are the ones that are more likely to get fused. Because the genome folds in 3D space, bringing genes that work together to the same place at the same time in the nucleus with their chromatin open, molecular mechanisms fuse these genes rather than others. An interaction involving complex regulatory information that has gradually evolved over generations leads to a mutation that simplifies and "hardwires" it into the genome.

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In the paper, they argue that fusions are a specific example of a more general and extensive internal force that applies across mutation types. Rather than local accidents arising at random locations in the genome disconnected from other genetic information, mutational processes put together multiple meaningful pieces of heritable information in many ways.

Genes that evolved to interact tightly are more likely to be fused; single-letter RNA changes that evolved to occur repeatedly across generations via regulatory phenomena are more likely to be "hardwired" as point mutations into the DNA; genes that evolved to interact in incipient networks, each under its own regulation, are more likely to be invaded by the same transposable element that later becomes a master-switch of the network, streamlining regulation, and so on. Earlier mutations influence the origination of later ones, forming a vast network of influences over evolutionary time.

"Previous studies examined mutation rates as averages across genomic positions, masking the probabilities of individual mutations. But our studies suggest that, at the scale of individual mutations, each mutation has its own probability, and the causes and consequences of mutation are related," says Livnat.

"At each generation, mutations arise based on the information that has accumulated in the genome up to that time point, and those that survive become a part of that internal information."

This vast array of interconnected mutational activity gradually hones in over the generations on mutations relevant to the long-term pressures experienced, leading to long-term directed mutational responses to specific environmental pressures, such as the malaria and Trypanosoma–protective HbS and APOL1 mutations.

New genetic information arises in the first place, they argue, as a consequence of the fact that mutations simplify genetic regulation, hardwiring evolved biological interactions into ready-made units in the genome. This internal force of natural simplification, together with the external force of natural selection, act over evolutionary time like combined forces of parsimony and fit, generating co-optable elements that themselves have an inherent tendency to come together into new, emergent interactions.

"Co-optable elements are generated by simplification under performance pressure, and then engage in emergent interactions—the source of innovation is at the system level," said Livnat. "Understood in the proper timescale, an individual mutation does not arise at random nor does it invent anything in and of itself."

Redefining how evolution works

The potential depth of evolution from this new perspective can be seen by examining other networks. For example, the gene fusion mechanism—where genes repeatedly used together across evolutionary time are more likely to be fused together by mutation—echoes chunking, one of the most basic principles of cognition and learning in the brain, where pieces of information that repeatedly co-occur are eventually chunked into a single unit.

Yet fusions are only one instance of a broader principle: diverse mutational processes respond to accumulated information in the genome, combining it over generations into streamlined instructions. This view recasts mutations not as isolated accidents, but as meaningful events in a larger, long-term process.

More information: Daniel Melamed et al, De novo rates of a Trypanosoma -resistant mutation in two human populations, Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2424538122

Journal information: Proceedings of the National Academy of Sciences

Provided by University of Haifa

Must reading for understanding the limitations of current ai (addition Aug 13)

noreply@blogger.com (DG) — Sun, 10 Aug 2025 15:46:00 +0000

I am not going to try to describe this comprehensive devastating article. Read it for youreselves: https://www.realtimetechpocalypse.com/p/gpt-5-is-by-far-the-best-ai-system

Added August 13: sand this one also

https://www.newyorker.com/culture/open-questions/what-if-ai-doesnt-get-much-better-than-this?utm_source=substack&utm_medium=email

Excellent description of the logic of inferring design

noreply@blogger.com (DG) — Thu, 17 Jul 2025 09:23:00 +0000

How Did the Designer Do It?

Daniel Witt

https://evolutionnews.org/2025/07/how-did-the-designer-do-it/

n 1852, several years before On the Origin of Species came out, the famed biologist Herbert Spencer defended the theory of evolution and made a broadside attack against the idea of “special creation” in his essay “The Developmental Hypothesis.” He wrote:

Those who cavalierly reject the Theory of Evolution as not being adequately supported by facts, seem to forget that their own theory is supported by no facts at all… If they have formed a definite conception of the process, let them tell us how a new species is constructed, and how it makes its appearance. Is it thrown down from the clouds? or must we hold to the notion that it struggles up out of the ground? Do its limbs and viscera rush together from all the points of the compass? or must we receive the old Hebrew idea, that God takes clay and moulds a new creature?

This argument has had considerable staying power. Skip ahead to 2015, and we find biochemist Larry Moran asking intelligent design advocate Stephen Meyers some very similar questions:

Did the gods nudge some of the species toward being arthropods in the first million years but waited until the last few years to create the information required to make chordates and vertebrates? What kind of information did they insert? What did they insert it into? Do we have any evidence of new god-created genes that sprang into existence during this period of time? If so, which ones?

And how old are these gods, anyway? Did the same ones stick around for the entire 10 million years to see if their experiment worked or were there several generations of gods?
Why were the gods so active in the Cambrian? Why didn’t they create all this new information 100 million years earlier or 100 million years later? Have they created any new information since then or did they front-load everything into genome during the Cambrian then turned their attention to some planets in other galaxies? These are all legitimate questions that deserve answers. They’re just like the questions you ask of scientists when you demand detailed evolutionary explanations.

It seems the debate has not progressed much in a century and a half. Clearly, these evolutionary theorists think they have an unanswerable line of attack here. And, admittedly, there is a certain superficial reasonableness to their demands. If we expect evolutionary theorists to explain how unguided evolution created life, shouldn’t design theorists be expected to explain how the designer created life?

Stonehenge and Smartphones

But if you mull the argument over, you begin to find it strangely unsatisfying. This may have something to do with the fact that, setting the more controversial subjects aside, there are many cases in which everyone agrees design occurreddespite not knowing the means by which it occurred. The Easter Island heads and Stonehenge are good examples. Scholars might debate exactly how ancient people managed set those massive stones in place without the aid of modern technology, but no one doubts that they did so. So clearly, there are instances where design can be inferred without precise knowledge of the methods of construction.

The analogy becomes even more applicable to the case at hand if we flip it around, and imagine that instead of analyzing artifacts constructed by more primitive societies, we are trying to analyze something more complex and sophisticated than anything we have ever dreamed of making. Imagine, for example, that you are a hunter-gatherer in a stone-age society who is suddenly taken out of the Amazon and brought to New York City. Could you provide even a sketch of the means of construction for a smartphone, a skyscraper, or an airplane? Absolutely not. You wouldn’t even know where to begin. But would that detract from your ability to infer design at work? No, it wouldn’t.

That is exactly where we stand in regard to biological life. Compared to a living organism, our best technology is like stone spears. We have no notion of how to make even the most basic cell. But we would be foolish to dismiss the possibility of design on that account.

Somewhat perplexingly, perhaps, the same does not seem to hold true for explaining something by natural processes alone. When someone tries to do that, we always expect hard details. If someone insisted that the Easter Island heads could be explained by unguided natural processes, you would certainly expect them to give you a clear explanation of how, or why such improbable shapes were demanded by the laws of nature. And you probably wouldn’t be much moved if they started complaining along the lines of Spencer and Moran that you weren’t being fair because you hadn’t explained how your beloved designers created the heads either: “Did they carve them with iron picks, or stone hammers? Were the carvers men, or women? Or little children, perhaps? Why did they make a few dozen heads, not one or several thousand? And where are they now? Did they quit making heads, or perhaps just move on to other islands…?”

In a fresh context, it’s obvious that this argument is not worth anything. So all that remains is to determine why the argument is not worth anything. And the answer is simply that it rests on a false equivalence: different types of explanation impose different burdens of evidence on their proponents. There are evidentiary burdens that lie on design theorists alone, and there are evidentiary burdens that lie on Darwinists alone.

“Will” vs. “Chance and Necessity”

The important distinction lies in the difference between agents and natural laws. Designers are free agents, by definition, and can do whatever they want. In fact, that’s where the explanatory power of design lies. Natural processes, by contrast, can only do the same predictable things. That is why humans constantly invoke designers to explain things that we would be at a loss to explain by the laws of nature alone — everything from ant hills to cave paintings. But because the explanatory power of free agents is produced by the very thing that makes them hard to predict, it’s no use demanding to know exactly how a free agent went about doing something. Unless you were there, you can’t know. It’s different with natural processes, which are uniform and therefore predictable.

The question that follows from this is, when are we allowed to invoke a free agent as an explanation? Famously, the principle of parsimony, or “Occam’s razor,” says that you shouldn’t invoke unnecessary entities as part of your explanation. When we invoke an intelligent designer to explain a phenomenon, we are invoking a new entity. Darwinian evolution, to its credit, does not propose any new entities — it tries to explain life using only matter and the observed laws of nature. According to Occam’s razor, however, there is a reason to invoke a new entity: if the entities you already have can’t explain the phenomenon. Of course this is so — otherwise, we would never be able to discover any new entities at all, and would be stuck with only believing in the first thing the first human baby happened to notice. Anyway, that is why intelligent design theorists spend so much time arguing against Darwin’s theory. It’s not that design and evolution are incompatible or that we think disproving evolution automatically proves design; it’s that there’s no need to invoke a new entity such as a designer if the laws of nature that we already know about can explain everything that exists. So to avoid violating Occam’s razor, intelligent design advocates need to show that the laws of nature cannot produce everything that exists. That is the evidentiary burden that lies on design theorists only; evolutionists, by contrast, do not need to somehow demonstrate that intelligent designers are incapable of creating life.

Conversely, Darwinists argue that there is no need to invoke a designer or any other new entities, because the entities we already know about (matter, chance, and the laws of nature) are a sufficient explanation for every observed phenomenon. So they must be able to show how the phenomena that do not seem like they could be produced by natural processes actually can be produced by natural processes. That is the evidentiary burden that lies on Darwinists alone; design theorists, by contrast, do not need to prove that the proposed designer is capable of producing life. The designer is capable by definition, because the designer was proposed specifically to fill in the explanatory gap left by the insufficiency of matter, chance, and the laws of nature alone.

A Case in Point: The Discovery of Helium

This may all become clearer if we consider an analogous case. The element helium was first discovered by an astronomer, not a chemist, because its existence was inferred from observations of sunlight before it was actually found on earth. The astronomer, Norman Lockyer, noticed that there was a wavelength of light produced by the sun that was not produced by any element yet discovered. He inferred that there must therefore be an undiscovered element in the sun. This was a perfectly legitimate inference, Occam’s razor notwithstanding, because no already-known entity could produce that wavelength of light. And it made no difference that no one knew exactly how or why different elements produced different wavelengths of light. If any chemist had insisted that there was not a new element in the sun, he or she would have needed to show that you actually can get that wavelength using only the already-known elements. In fact, the English chemist Edward Franklin attempted to do this by putting hydrogen under extreme heat and pressure, but was unsuccessful.

The same goes for evolution. The evolution of highly complex biological systems has never been observed, and there are certain theoretical arguments that purport to show that it is essentially impossible (statistically speaking) for random variation, natural selection, and the laws of nature alone to produce those systems. So any scientist who wants to argue that the already-known entities in nature could produce all of biology needs to show how this could occur, in spite of the theoretical hurdles. If they can’t do this, then we are perfectly justified in proposing a new entity, such as a designer.

One final objection must be answered. If we don’t know exactly how the designer crafted life, then how do we even know that a designer is the right explanation? Couldn’t it just as easily be something else?

Once again, the story of helium is illuminating. Helium and intelligent design are both parsimonious explanations regarding the broad type of cause, yet non-parsimonious regarding the specific entity. Lockyer proposed an element, rather than something else (e.g., a new law of nature), because it was already known that elements can produce light. But he proposed a new element, because it was known that none of the old elements could produce that particular wavelength of light. Likewise, ID theorists propose a designer to explain the specified complexity of life because it is already known that designers (i.e., minds) can produce specified complexity. But we must propose a new designer, because none of the old designers (ourselves, beavers, etc.) are capable of having created the systems in question.

By now it should be clear why it is the height of silliness to demand proof that the designer could create life, or to expect detailed explanations of how it could be done. If chance and necessity are insufficient to produce life, then we must conclude that something beyond chance and necessity was involved. The proof of that entity’s capability is simply the fact that life exists.

The great lie - 2% difference between human and chimp genes

noreply@blogger.com (DG) — Sun, 25 May 2025 08:29:00 +0000

Fact Check: New “Complete” Chimp Genome Shows 14.9 Percent Difference from Human Genome

Casey Luskin

May 21, 2025, 6:20 AM

https://evolutionnews.org/2025/05/fact-check-new-complete-chimp-genome-shows-14-9-percent-difference-from-human-genome/

A groundbreaking paper in Nature reports the “Complete sequencing of ape genomes,” including the genomes for chimpanzees, bonobos, gorillas, Bornean orangutans, Sumatran orangutans, and siamangs. I noted this in an article here yesterday, reporting that an evolutionary icon — the famous “1 percent difference” between the human and chimp genomes, touted across the breadth of popular and other scientific writing and teaching — has fallen. The researchers, for whatever reason — I’m not a mind reader — chose to bury that remarkable finding in technical jargon in their Supplementary Data section. Now for more on the scientific details.

You might be thinking, “Hey, weren’t these genomes sequenced long ago?” The answer is yes but also no. Yes, we had sequenced genomes from these species in the past, but, as the paper explains, “owing to the repetitive nature of ape genomes, complete assemblies have not been achieved. Current references lack sequence resolution of some of the most dynamic genomic regions, including regions corresponding to lineage-specific gene families.”

Or, as an accompanying explainer article puts it:

In the past, scientists had deciphered segments of non-human apes’ genomes, but they had never managed to assemble a complete sequence for any species. In the current study, however, [Kateryna] Makova and her collaborators used advanced sequencing techniques and algorithms that allowed them to read long segments of DNA and assemble them into a sequence that stretched from one end of each chromosome to the other, without any gaps. “This has never been done before,” says Makova.

In other words, the complete ape genomes were never fully sequenced. And they used the human genome as a reference sequence, which made the ape genomes look more human-like than they actually were.

You Don’t Believe Me?

From the technical paper:

Most previous genome-wide comparative studies of apes have been limited by the mapping of inferior assemblies to a higher quality human genome. Consequently, human reference biases were introduced.

This is consistent with what the National Center for Biotechnology Information said in 2007 about an early draft of the chimp genome:

Contigs were assembled using the human genome as a guide, and are therefore “humanized” in their construction. This is an important distinction, as some sequences, such as insertions, deletions, and gene duplications, may not be accurately represented by the current chimpanzee assembly.

Thus, up until now, most versions of the chimp and other ape genomes were effectively “humanized” because they were “assembled using the human genome as a guide.” This effectively makes them appear more similar to the human genome than they truly are. Can these new drafts of ape genomes help fix the problem?

Problem Solved?

Another explainer article in Nature seems to suggest that these “complete” drafts of the ape genomes will prove that they are less similar to the human genome than has been claimed:

Shortly after the first human genome sequence was finalized in 2003, a chimpanzee assembly was released. This was followed by assemblies for other great apes, such as the gorilla, Sumatran orangutan and bonobo, and small apes that are less closely related to humans than are great apes. These genomes offered a valuable opportunity to catalogue the genetic differences that have accumulated during the evolution of apes, including changes that are unique to humans. But, because these initial releases were incomplete drafts, comparisons could be made only between properly resolved portions of the genome. These studies therefore focused only on relatively small differences, and excluded extremely repetitive sequences and large-scale structural differences, such as inversions and duplications of genomic sequences. [Emphasis added.]

That last sentence seems to hint that previous comparisons between human and ape genomes “only focused on relatively small differences” and “excluded” the sections that entail “large-scale structural differences.” The explainer article notes that this study has “fully sequenced the genomes of six living ape species, enabling long-awaited comparisons of hard-to-assemble genomic regions.” Thus, one could expect that these newly “complete” ape genomes would reveal much greater differences compared to the human genome.

The New Ape Genomes and the Human Genome

What’s odd is that as one reads the technical paper, a direct comparison between the ape and the human genomes is hard to find. This passage seems to be as close as it gets:

Overall, sequence comparisons among the complete ape genomes revealed greater divergence than previously estimated (Supplementary Notes III–IV). Indeed, 12.5–27.3% of an ape genome failed to align or was inconsistent with a simple one-to-one alignment, thereby introducing gaps.

What exactly does this mean? Well, first they admit that “sequence comparisons among the complete ape genomes revealed greater divergence than previously estimated.” But the technical Nature paper considers human beings to be an “ape,” so implicit in this statement is their belief that comparing “ape genomes” includes comparisons between human and ape (i.e., non-human hominoid) genomes. So for the rest of this article, I’ll call humans “humans” and I’ll refer to non-human hominoids as “apes,” just like most normal people do.

Interestingly, two preprints of the paper (v1 and v2) published last year on BioRxiv (which are presumably the versions of the manuscript submitted to Nature initially and after one round of revisions) preface this result with these two sentences:

The oft-quoted statistic of ∼99% sequence identity between chimpanzee and human holds for most of the genome when considering single-nucleotide variants (SNVs). However, comparisons of T2T genomes suggest a much more nuanced estimate.

T2T means examining “telomere to telomere” — i.e., examining the entire chromosomes throughout the genome. These sentences were evidently removed during revisions for the published version in Nature — an interesting editorial decision. So what is the paper saying about the difference between humans and chimpanzees?

As we’ll see, the statement above — that “sequence comparisons among the complete ape genomes revealed greater divergence than previously estimated” — is true. But it doesn’t reveal the extent of the differences between human and ape genomes that this study uncovered. So let me cut to the chase:

Look back at those numbers, “12.5–27.3%.” The same numbers show up again buried deep in the Supplemental Data where they compare various ape to human genomes. They’re findable if you know where to look, but should I say “buried” — or “hidden”? From what I can tell, the Supplemental Data reports that the ape genome that is most similar to the human genome is the chimpanzee genome. And it shows a 12.5 percent “gap-divergence” — i.e., difference — from the human genome! And when you look at the “gap divergence” where the human genome is the target and the chimp is the query, the difference is 13.3 percent. Let me be clear: According to this study, the human and chimp genomes aren’t 98.8 percent the same (or 1.2 percent different) — as, for instance, the Smithsonian Institution’s National Museum of Natural History claims (see my “Visitor’s Guide” for more). In fact, they are no more than 87.5 percent similar — i.e., the human and chimp genomes are at least 12.5 percent different if not 13.3 percent different! In fact, the 13.3 percent difference is more relevant since this reflects how similar the whole human assembly is to the chimp genome.

What Exactly is the “Gap Divergence”

Before we go further, I want to explore exactly what the authors mean by “gap divergence” or “gap difference.” The paper defines the “gap divergence” as follows:

Gap divergence is defined as the fraction of positions in the target haplotype that are not aligned to the other haplotype, which could be due to biological processes (e.g., gene loss/gain and insertions/deletions), missing data, or technical problems (e.g., alignment failure due to SVs, repetitive elements, etc.).

So how do they determine the gap divergence? From what I can tell, it’s based upon dividing the target genome within the genome alignment into 1 million base pair (1 Mbp) segments and seeing how many of the bases within each 1 Mbp segment have no aligning base within the query genome that has been aligned to it. If the entire 1 Mbp segment has no alignment by the target genome, it has gap divergence of 100 percent. If 10,000 bp have no alignment, it has gap divergence of 1 percent; if 1,000 bp have no alignment, it has gap divergence of 0.1 percent, etc. According to the study’s results, the mean gap divergence in each 1 Mbp segment of the human genome (as target) aligned to the chimp genome (as query) is 12.5 percent. Thus, 12.5 percent of bases in the human genome have no aligning base in the chimpanzee genome within the whole genome-alignment.

The figure below — created for illustrative purposes and not from the study — helps show the differences between “SNVs” and “Gaps” between the two genomes:

As you can see, the Gaps represent nucleotides or segments of nucleotides that simply don’t exist in one genome or the other, while the SNVs represent nucleotides that do exist but are different. The two types of differences can be added up to calculate the total difference between the genomes.

An Upper Estimate

And why is there a range of 12.5 percent to 27.3 percent in the main text? That’s because the upper estimate of the non-alignability between the gorilla genome and human genome is a whopping 27.3 percent. In fact, if we look at the Supplementary Figure III.12, we find the following percentages of “gap-divergence” between various ape genomes when compared to the human genome (non-sex chromosomes):

Sumatran orangutan (Pongo abelii) vs human: 15.4 percent and 16.5 percent “gap-divergence” (i.e., minimum difference)
Gorilla (Gorilla gorilla) vs human: 17.9 percent and 27.3 percent “gap-divergence” (i.e., minimum difference)
Bonobo (Pan paniscus) vs human: 12.5 percent and 14.4 percent “gap-divergence” (i.e., minimum difference)
Chimpanzee (Pan troglodytes) vs human: 12.5 percent and 13.3 percent “gap-divergence” (i.e., minimum difference)

Do you see how easy it is to summarize that data? These are huge findings for both science and the wider culture, yet the technical Nature paper, and the two Nature explainer articles, failed to clearly bring out these points. They buried them in technical jargon and a lack of clarity deep in the Supplemental Data, and the sentence about “The oft-quoted statistic of ~99% sequence identity” was removed in the revisions of the paper. Nature, I feel confident in assuring you, is not a haphazardly edited journal. These were deliberate choices by someone during the editing process. The lack of clarity is simply incredible.

The Technical Details

Deep in the Supplementary Data we find Figure III.12 which explains the gap divergence between different species:

The caption reads: “Plots show 1 Mbp segments binned by gap divergence for each pairwise alignment,” where a pairwise alignment is an attempt to align two sequences to determine their degree of similarity or difference. Thus, we’re looking at a direct measure of the minimum degree of difference between the two genomes.

Adding in the Single Nucleotide Variation (SNV)

But there’s another type of variation between genomes also identified in the paper — single nucleotide differences (called “single nucleotide variations” or sometimes “short nucleotide variations” or SNVs). Again, buried in the Supplemental Data we find Figure III.11 which shows the percentage of SNVs between human and various ape genomes reported in this study. Here’s what they found:

Sumatran Orangutan (Pongo abelii) vs Human: ~3.6 percent different
Gorilla (Gorilla gorilla) vs Human: 1.9 percent – 2.0 percent different
Bonobo (Pan paniscus) vs Human: 1.5 percent – 1.6 percent different
Chimpanzee (Pan troglodytes) vs Human: 1.5 percent – 1.6 percent different

If we add the gap divergence to the SNV differences, we end up with these total degrees of difference between human and ape genomes:

Sumatran Orangutan (Pongo abelii) vs Human: ~19 percent – 20.1 percent different
Gorilla (Gorilla gorilla) vs Human: ~19.8 percent – 29.3 percent different
Bonobo (Pan paniscus) vs Human: ~14.0 percent – 16.0 percent different
Chimpanzee (Pan troglodytes) (target) vs. Human: ~14.0 percent different
Human (target) vs. Chimpanzee (Pan troglodytes): ~14.9 percent different

So now what we’re seeing is that there is about a 14.9 percent total difference between the human genome and the chimp genome. That represents a much greater degree of difference than the often-claimed statistic that we are only 1 percent genetically different from chimpanzees!

Is This the Final Word?

Undoubtedly more analysis is needed to determine the extent to which nucleotides exhibit “one-to-one exact matches” between the human and chimp genomes, even in the regions that could be more easily aligned. So I suspect that the degree of difference between human and chimp genomes may go up in the future.

For now, we can safely say that this latest study shows that the human and chimp genomes are at least 14.9 percent different. This means that the human and chimp genomes are at least a full order of magnitude more dissimilar than the public is typically told.

Of course we’re talking here about the 44 non-sex chromosomes in the human genome. It’s also worth noting that compared to chimps, the human Y chromosome has a whopping 56.6 percent gap divergence (and 3.9 percent SNV divergence), and the human X chromosome has 4.4 percent gap divergence (and 1.1 percent SNV divergence). But that too is all buried in the Supplemental Data.

These are all groundbreaking findings — and it’s a shame that Nature would not report the data clearly and would make all of this so hard to find — using jargon that most non-experts won’t understand. Why did they do this? It’s important to realize that publishing scientific papers can be a bit like sausage-making: it’s often messy, and the final form that you read usually represents compromise language that all of the authors, reviewers, and editors were willing to publish — and may not represent precisely how every author of a paper feels. So perhaps some authors of this study would have preferred to state the implications more plainly. But we can still ask, Why didn’t Nature state the results clearly and let the chips fall where they may?

I suspect that this radical finding has implications — not just for science, but also for human exceptionalism, for the reliability of heavily marketed talking points, and more — that people will be discussing for a long time. And perhaps for some in the worlds of science and science reporting, especially those who touted the now discredited figure about a mere 1 percent difference from chimps, those conversations may not be welcome.

Photo by Nathan Jacobson, © Discovery Institute (CC BY-SA 4.0)

Casey Luskin

_{Associate
Director and Senior Fellow, Center for Science and Culture}

What Israel’s Enemies Don’t Want You to Know by Sara Rigler

noreply@blogger.com (DG) — Wed, 21 May 2025 18:22:00 +0000

Bs”d

What Israel’s Enemies Don’t Want You to Know

Archeology screams the truth about Jerusalem and Israel

Some twenty years ago I was walking from my home in the Jewish Quarter of Jerusalem’s Old City to pray at the Kotel (the Western Wall), Judaism’s second holiest site, second only to the Temple Mount itself that towers above it. On the steps to the Kotel Plaza, I passed an Arab tour guide speaking in English to a large group of European tourists. Pointing toward the Golden Dome and the Al Aqsa Mosque on the Temple Mount, he said, “The Jews claim that their two temples stood on this spot, but there is no proof whatsoever to that claim.”

I was stunned. No proof? The gigantic, distinctive “Herodian stones” of the Western Wall itself, the remnant of the retaining wall King Herod built around the mountain when he enlarged the Second Temple, starting in 20 BCE, were incontrovertible proof. And what about the numerous contemporary historical descriptions of the Temple, including historian Josephus Flavius’s eye-witness account of the Temple, written in the first century CE? Although an inveterate debater, I stood there unable to utter a word of rebuttal because I was shocked speechless by the boldfaced lie. It was as if an acknowledged scientist was telling his students that the world is flat.

Only recently, when reading Doron Spielman’s new book, When the Stones Speak, did I become aware that that Arab tour guide was just a small part of a widespread, carefully calculated campaign to deny the Jewish People’s historical claim to Jerusalem and the land of Israel.

The invective, “Colonialists!” being shouted against the Jewish State on university campuses and in European capitals is based on the allegation that European Jews came to Palestine in the late 19^th and early 20^th century as foreign occupiers. In the wake of the Holocaust, according to this view, the United Nations voted for a Jewish state, alongside an Arab state, in the small piece of land between the Mediterranean Sea and the Jordan River, in order to assuage their guilt. The implication of “colonialists” is that Jews have no more rights to that patch of land than the British had to India.

An inconvenient contradiction of that narrative is the Bible, which chronicles over a thousand years of Jews (then called “Israelites”) living in that patch of land. “The Bible should be put aside,” claimed Palestinian archaeologist, Hani Nur el-Din, professor of archaeology at Al-Quds University. “It’s not a history book.”

This statement, writes Doron Spielman, “was part of the broader, long-standing trend of denying Jewish history in Jerusalem that had persisted for decades.” In When the Stones Speak, he provides hair-raising evidence of this campaign.

(Even the name “Palestine” was an effort by the Roman Emperor Hadrian, after the Jewish revolt of 132-135 CE, to sever the historical identification between the Jews and their land, which had been called “Judea” for centuries. The term “Palestina” derives from the Philistines, one of the ancient Sea Peoples who had lived along the coast of Judea and disappeared from history with the Babylonian conquest seven centuries before the Romans exiled the Jews.)

If you can’t trust the Bible to legitimate the Jewish people’s historical claim to the land, then perhaps archeological discoveries in the City of David, the original Jerusalem which lies to the south of the walled Old City, can provide proof that Jews lived there in antiquity. When the Stones Speak is the riveting story of those archeological digs and what they revealed, as well as the opposition that tried to stop them.

THE CRUSADE TO DENY HISTORY

Excavating the City of David faced massive pushback from the Palestinian leadership and the European NGOs that support them. Sheikh Ikrima Sabri, the Mufti of the Temple Mount and one of the founders of Al Quds University, told a reporter for the German Die Welt in 2001, “There is not the smallest indication of the existence of a Jewish temple on this place in the past. In the whole city, there is not even a single stone indicating Jewish history…. It is the art of the Jews to deceive the world.”

Walid Awad, a Palestinian scholar in charge of publications for the Palestinian Ministry of Information, asserted in 1996: “The fact of the matter is that almost thirty years of excavations did not reveal anything Jewish. ... Jerusalem is not a Jewish city, despite the biblical myth implanted in some minds.”

Even as recently as May, 2023, Mahmoud Abbas, the President of the Palestinian Authority, addressing the United Nations, claimed that there was no proof whatsoever of Jewish ties to the al-Aqsa compound [the Temple Mount]. He stated that Israel “dug under al-Aqsa. They dug everywhere and they could not find anything.”

When the Stones Speak tells of astonishing finds in the City of David that disprove the Palestinian lies. Dr. Eilat Mazar, a courageous and independent archeologist, using the Bible as her guide, discovered a monumental building, with walls twenty feet thick, which she maintained was the palace of King David and subsequent kings of Judea. She dated pottery she found within the ruins to the tenth century BCE, the time of King David.

Archeologists from Tel Aviv University, who had made a career of denying the Bible, jumped on Dr. Mazar and questioned the dating of her pottery shards. They argued that the massive building, clearly belonging to a ruler, was from two centuries before King David or three centuries after. In those years, only organic matter could be conclusively dated. An olive pit found deep in the structure was sent to the laboratories of Oxford University for Carbon-14 dating. After weeks of tumulteous debate in the media about Dr. Mazar's discovery, the results came back: the olive pit was from 1000 BCE, the period of King David.

Even more electrifying was her discovery of a clay seal that bore the name, written in paleo-Hebrew, of “Yehuchal the son of Shelemiah.” The Bible relates that the prophet Jeremiah, who lived in the 6th century BCE, prophesized that the mistreatment of orphans and widows would bring Divine judgment against the kingdom. Four of King Zedekiah’s officers told the king that Jeremiah was fomenting panic in Jerusalem. The Bible records the name of one of those officers: Yehuchal the son of Shelemiah.

THE PILGRIMAGE ROAD

Even more gripping is the story of discovering and excavating “the Pilgrimage Road,” a 700-meter series of expertly chisselled limestone steps that led from the Siloam Pool, a giant ritual bath discovered at the southern tip of the City of David, directly to the Temple Mount. As Doron Spielman writes:

The road we had discovered wasn’t just a Pilgrimage Road; it was the Hag Pilgrimage Road used by the ancient Israelites who came to Jeusalem more than sixteen hundred years before Islam was founded.

This historical fact should have posed no challenge to Islam were it not for the Palestinian leadership. But they had been teaching an entire generation of their people the falsehood that there never was a Jewish Temple on the Temple Mount, and that the site was first sanctified by Muhammed.

…

With the discovery of King David’s Palace and the Pilgrimage Road, the City of David was transformed from a small backwater excavation into a leading archaeological site.

And with that transfomation came threats of violence against Israelis in general and against our workers, and even an attempted assassination.

I never expected a book on archeology to be a page-turner, but Doron Spielman is a master story-teller. As Vice-president of the City of David for twenty years, he provides an eye-witness account of the drama and suspence of using archeology to prove that the Jews are the indigenous people of the tract of land between the Jordan River and the Mediterrean Sea. With a cast of colorful characters from Elie Weisel to Congresswoman Elise Stefanik, this is a must-read story.

As the author writes: “Grab almost any Israeli off the streets in Israel today and they will likely tell you: We are here. We have always been here. And we’re not going anywhere else.”

With the revelations narrated in this book, every Jew in the world should be able to vouch: The Jews have always been in the land of Israel. We are the indigenous people between the river and the sea.

To buy the book, click here:

https://www.amazon.com/When-Stones-Speak-Remarkable-Discovery/dp/1546009256

Short and sweet story failures of evolution to explain echo location in bats

noreply@blogger.com (DG) — Wed, 14 May 2025 18:15:00 +0000

https://evolutionnews.org/2025/05/lets-enter-bat-echolocation-evolution-in-google-scholar/

noreply@blogger.com (DG) — Fri, 18 Apr 2025 09:25:00 +0000

what happens to a flatworm when it is immersed in barium

ChatGPT said:

When a flatworm is immersed in barium, the outcome depends on the form of barium used. Barium in general is toxic to living organisms, but here's a breakdown:

1. Barium Ions (e.g., Barium Chloride - BaCl₂)

Toxicity: Highly toxic to flatworms and other invertebrates.
Effect: Disrupts normal nerve and muscle function by blocking potassium channels, which are crucial for nerve impulse transmission.
Result: The flatworm may experience:
- Loss of movement or erratic movement
- Muscle spasms or paralysis
- Death, depending on concentration and exposure time

2. Barium Sulfate (BaSO₄)

Insoluble & Inert: Commonly used in medical imaging (e.g., X-rays) because it doesn't dissolve in water.
Effect on Flatworms: Minimal, unless impurities are present—generally non-toxic due to poor solubility.

Summary

Soluble barium salts (like barium chloride): Harmful or lethal to flatworms.
Insoluble barium compounds (like barium sulfate): Generally harmless.

Do you know which form of barium you're referring to? I can give you more detailed effects if you do!

You said:

there is a report of the death of the head leaving the tail which revgererates a new head immune to barium poining in Seymour Garte, Perry Marshall, and Stuart Kauffman have published an article in the journal Entropy titled “The Reasonable Ineffectiveness of Mathematics in the Biological Sciences.”

ChatGPT said:

Yes, the phenomenon you've described has been documented in scientific research. When planarian flatworms are exposed to barium chloride (BaCl₂), a potent potassium channel blocker, their head tissues degenerate within approximately 72 hours. Remarkably, if these worms remain in the BaCl₂ environment, they can regenerate new heads that are resistant to the toxic effects of barium. PubMed+3PMC+3ResearchGate+3

This adaptation suggests that planarians possess a form of physiological plasticity, allowing them to modify their regenerative processes in response to environmental stressors. The regenerated heads not only restore normal morphology but also exhibit insensitivity to BaCl₂, indicating a successful adaptation to the previously harmful conditions.PMC

This case exemplifies how biological systems can sometimes defy straightforward mathematical modeling, as discussed in the article "The Reasonable Ineffectiveness of Mathematics in the Biological Sciences" by Seymour Garte, Perry Marshall, and Stuart Kauffman. The authors argue that the complexity and adaptability of living organisms often challenge the predictive power of mathematical frameworks traditionally used in the physical sciences.

ChatGPT said:

The phenomenon of planarian flatworms regenerating barium-insensitive heads after exposure to barium chloride (BaCl₂) has been documented in scientific literature. A key study titled "Regenerative Adaptation to Electrochemical Perturbation in Planaria: A Molecular Analysis of Physiological Plasticity" reports that exposure to BaCl₂ causes degeneration of the planarian head, but continued exposure leads to the regeneration of a new head that is insensitive to BaCl₂. ResearchGate+2PubMed+2PMC+2

This study provides a detailed analysis of the molecular and physiological mechanisms underlying this adaptation, including changes in ion channel expression and the role of specific molecular pathways. The findings suggest that planarians can adapt to electrochemical stress by altering their physiology during regeneration.

While this study is a primary source documenting this specific phenomenon, other research has explored related aspects of planarian regeneration and physiological adaptation. For example, studies have investigated the role of ion transport and membrane voltage in planarian head regeneration, highlighting the importance of bioelectric signals in regenerative processes. PMC+2Cell+2PubMed+2

These studies collectively contribute to our understanding of the remarkable regenerative capabilities of planarians and their ability to adapt to environmental stressors.

PubMed

Regenerative Adaptation to Electrochemical Perturbation in Planaria: A Molecular Analysis of Physiological Plasticity - PubMed

Skip to main page content Save Email Send to Display options Full text links Cite Display options ABSTRACT Anatomical homeostasis results from dynamic interactions between gene expression, phys...

Cell

A Chemical Genetics Approach Reveals H,K-ATPase-Mediated Membrane Voltage Is Required for Planarian Head Regeneration: Chemistry & Biology

DISCUSSION Here, we demonstrate a powerful chemical genetics approach for investigating the regeneration of axial polarity, uncovering a novel role for ion transport and membrane voltage in initiatin...

PMC

Regenerative Adaptation to Electrochemical Perturbation in Planaria: A Molecular Analysis of Physiological Plasticity - PMC

GRAPHICAL ABSTRACT Open in a new tab HIGHLIGHTS * • Exposure to BaCl_{2} causes the heads of Dugesia japonica to degenerate * • Prolonged exposure to BaCl_{2} results in regeneration of a BaCl_{...

PubMed

Regenerative Adaptation to Electrochemical Perturbation in Planaria: A Molecular Analysis of Physiological Plasticity - PubMed

Skip to main page content Save Email Send to Display options Full text links Cite Display options ABSTRACT Anatomical homeostasis results from dynamic interactions between gene expression, phys...

PubMed

Reactivating head regrowth in a regeneration-deficient planarian species - PubMed

Skip to main page content Save Email Send to Display options Full text links Cite Display options ABSTRACT Species capable of regenerating lost body parts occur throughout the animal kingdom, y...

PMC

Bioelectric signaling regulates head and organ size during planarian regeneration - PMC

Although Smed-H,K-ATPase(RNAi) injection did produce a consistently small number of headless regenerates (4.2%), similar to H,K-ATPase inhibition in D. japonica (supplementary material Fig. S3), the m...

PubMed

A chemical genetics approach reveals H,K-ATPase-mediated membrane voltage is required for planarian head regeneration - PubMed

FIGURES Figure 1. H,K ATPase inhibition blocks head regeneration Effects of 18µM SCH-28080 (SCH). (A) Control pharynx, (B) SCH-treated pharynx, and (C) SCH-treated tail fragments at 14 days regenera...

PMC

Reactive Oxygen Species in Planarian Regeneration: An Upstream Necessity for Correct Patterning and Brain Formation - PMC

FIGURE 2. Open in a new tab Phenotypical characterization during DPI and APO exposure. (a) The effect of DPI (3 μM) and APO (400 μM) exposure on regenerating head, trunk, and tail fragments after 7...

מרכז המידע ביוטכנולוגי הלאומי

Bioelectric signaling regulates head and organ size during planarian regeneration - PMC

The head region (as a percentage of the whole worm), instead of just growing from the blastema to the correct proportion, increased by 10 dpa to 74.4% larger than in intact animals. Only after 10 dpa...

BioMed Central

The head-regeneration transcriptome of the planarian Schmidtea mediterranea | Genome Biology | Full Text

DIFFERENTIALLY REGULATED GENES DURING HEAD REGENERATION Using our Illumina RNAseq approach, we identified hundreds of differentially regulated genes during different stages of head regeneration, and...

SpringerLink

Different classes of small RNAs are essential for head regeneration in the planarian Dugesia japonica | BMC Genomics

10. Sanchez Alvarado A. Planarian regeneration: its end is its beginning. Cell. 2006;124(2):241–5. 11. Mineta K, Nakazawa M, Cebria F, Ikeo K, Agata K, Gojobori T. Origin and evolutionary process of...

Cell

A Chemical Genetics Approach Reveals H,K-ATPase-Mediated Membrane Voltage Is Required for Planarian Head Regeneration: Chemistry & Biology

anatomypubs.onlinelibrary.wiley.com

Intercalary regeneration in planarians - Agata - 2003 - Developmental Dynamics - Wiley Online Library

Nine days after amputation, the head fragment regenerated a complete body with normal proportions. Although we could clearly observe a blastema during regeneration as a cluster of the DjvlgA-positive...

ResearchGate

(PDF) Regenerative Adaptation To Electrochemical Perturbation In Planaria: A Molecular Analysis Of Physiological Plasticity

2 treatments, Figure 1Ab), consistent with the importance of potassium currents in maintenance and physiology of this comp

Kol tuv [All the best]

Dovid Gottlieb

ReplyForward

Origin of Life: A “Simple” Worm’s Challenge

noreply@blogger.com (DG) — Sun, 06 Apr 2025 18:12:00 +0000

Denyse O'Leary

March 21, 2025, 4:10 PM

https://evolutionnews.org/2025/03/origin-of-life-a-simple-worms-challenge/

[[Although the remarks concerning evolution in this article are important I am more interested in the fact that we do not know how a brain with 302 neurons functions. But of course we fully understand our own brains with 86b neurons I first posted about this worm in 2018 and not much progress has been made.....]]

Recently, we published a piece by Eric Cassell on the fact that even the tiniest known brain, that of the worm C. elegans, is not simple. These facts he sets out raise some very interesting questions.

The worm’s apparent simplicity makes it a favorite lab animal — for example, it was the first animal whose brain was mapped. Researchers have learned that, with fewer than 400 neurons, it can handle both associative and non-associative learning.

Cassell, author of Animal Algorithms (2021), offered a number of remarkable facts about the worm and I thought I’d summarize a few of them again here, along with some questions:

The worm, 1 millimetre in length, consists of only 900 cells. Thus neurons comprise a large proportion of its total cell count.

The worm actually comes in two forms: males which have 385 neurons and hermaphrodites (both sexes) which have 302 neurons. In both cases, it seems that over one-third of all its cells are neurons. But if we compare the worm to the human, we see a considerable difference: The human body has roughly 30 trillion cells and the human brain only 86 billion. Of course, there are neurons distributed throughout the human body. Even so, the proportion of human neurons to other human cells seems much lower.

Perhaps the worm’s brain has roughly the minimum number of neurons any brain must have for simple bodily functions and learning — irrespective of the size of the rest of the body.

Equipped with those 400 neurons, the worm can feed, fast, mate, lay eggs, swim in liquids and crawl on solids. In fact, the worms’ “social lives” can become, well, quite complex:

Cassell writes,

In addition to basic behaviors, C. elegans is also capable of learning, including associative and non-associative learning. A paper published in the Journal of Neurochemistry documented the learning behaviors, including attraction and aversion to salt, temperature, and other substances. What might be surprising to many is that this learning involves both short-term and long-term memory mechanisms, which include regulation of neurotransmitters.
“Even the tiniest brain,” March 17, 2025

The Origin of Life Question

When even simple life forms are complex, the origin of life question arises: Were there ever life forms that were so simple that they could merely self-assemble, as our official doctrine of the origin of life proposes?

Cassell offers several observations that touch on this question:

… even though the brain is tiny, it does not have a simple structure. One might expect the smallest known brain to have a structure that is either relatively uniform or random. An example of a uniform structure is that found in crystals, which form a symmetrical lattice. A random structure would be expected if the positions of the neurons were not specified, but rather develop through a random process. Contrary to being either uniform or random, the brain does have a complex structure that is specified and repeatable.
“Tiniest brain”

Yes, that’s the problem of specified complexity: In a world where nature, left to itself, produces either uniform order or chaos, we find a level of information-rich order that requires an underlying intelligence. And in this case, that information-rich order is alive.

And just when we think we might have finally got down to the truly simple, basic part:

A second observation is that the brain contains a large number (approximately 100) of different types of neurons, both in terms of design and function. They are not all identical. That also would not be expected for the smallest brain. A third observation is that small neural networks within the brain control various behaviors, such as the touch response network. It is possible that some of these neural networks are irreducibly complex.
“Tiniest brain”

Irreducibly complex means that the current structure cannot have arisen via a gradual buildup from simpler to more complex steps. It’s not that simpler versions could not do the job as efficiently; rather, none of them could do it at all.

Cassell quotes a research paper that attempts to account for C. elegans’s unexpectedly busy little brain:

The mere existence of such structures may actually further underscore the directed evolution to form such clusters, which presumably carry fine functional roles along the neurites. Taken together, local compartmentalized activities, facilitated by the clustered synaptic organizations revealed herein, can enhance computational and memory capacities of a neural network. Such enhancement may be particularly relevant for animals with a compact neural network and with limited computational powers, thereby explaining the evolutionary forces for the emergence of these synaptic organizations.
Ruach, et al., “The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations,” PNAS, 2023, Vol. 120, No. 3.

But wait. Did the researchers say “directed evolution”? As Cassell notes, the term has never been generally accepted in the research literature. That’s probably because it implies underlying purpose or design. Here we have no quarrel with that idea. But it appears to abandon the idea of gradual, random assembly of even the C. elegans brain via natural selection acting on random mutation.

So Here We Are…

Looking at the very simplest brain known, we find both specified and irreducible complexity. It is all very far removed from the organic elements that are the building blocks of life. And yet we aren’t yet anywhere near the types of brains that think, in the sense that a dog thinks.

However evolution happens, it is beginning to sound far more complex than the sort of theory that made Richard Dawkins feel intellectually fulfilled as an atheist.

Cross-posted at Mind Matters News.

Did Evolution Give Us Free Will? [[A very good preliminary discussion.]]

noreply@blogger.com (DG) — Thu, 06 Mar 2025 09:54:00 +0000

Did Evolution Give Us Free Will?

Daniel Witt

March 4, 2025, 8:21 AM

Did Evolution Give Us Free Will? Daniel Witt March 4, 2025, 8:21 AM

If you pick up a book up about free will by a materialist neuroscientist, you are generally safe to assume that the point of it will be to explain that free will is merely an illusion — that we are actually at the whim of the blind forces of Nature, and are therefore not responsible for our actions. So it’s surprising and somewhat refreshing to see a self-proclaimed naturalist defend free will. That’s what Trinity College Dublin neurobiologist Kevin Mitchell sets out to do in Free Agents: How Evolution Gave Us Free Will.

As Denyse O’Leary has noted about the book, the scientific debate over free will seems to be reviving a bit, with another book by another prominent scientist arguing the opposite position released the same year (Determined by Robert Sapolsky). So after reading Mitchell’s book, I thought it would be worth digging into the details of his argument a bit for Evolutions News readers.

Does the book succeed? By my assessment, no and yes and no. There are really several different questions at play here: Do we have a will? Is it free? Did evolution give it to us? And if so, how? Each of these subjects has its own set of scientific and philosophical difficulties, and the book is not equally persuasive on every point. To keep the various strands of the argument straight, let’s go in order, following the subtitle. We’ll start with “how evolution gave us”…

“How Evolution Gave Us…”

Anyone expecting a defense of the claim that Darwinian processes can or did create complex neurological systems will be disappointed. That’s not the point of the book. With a very few exceptions1, Dr. Mitchell works from the tacit assumption that (a) there is no real limit to what Darwinian processes can achieve, and (b) that anything that exists in biology must have arisen through Darwinian processes. That means the book is largely concerned with describing what exists in nature, with “evolved” acting as a synonym for “is.”

Thus, phrases like “mechanisms evolved” prevail throughout the book. Complex systems are simply “built” or “invented” or even “designed,” without much concern given to the concrete details or the relevant engineering problems. The following passage is typical:

More complex creatures emerged, colonizing and creating new niches, with expanded repertoires of possible actions. A system was then required to coordinate the movement of all the organism’s constituent parts and select among actions. Muscles evolved, along with neurons to coordinate them, initially distributed in simple nerve nets. As evolution proceeded, the nervous system became more complex, linking sensory structures to muscles via intervening layers of interneurons. The meaning of signals became disconnected from immediate action, giving rise to internal representations…

In all fairness, Mitchell presumably did not set out to defend Darwinian evolution against other possible explanations. The heart of Free Agents is not really in explaining how we evolved to be what we are, but rather in simply describingwhat we are, according to the cutting edge of neurobiology. That’s where the book shines.

“Free”

One view of free will, called “compatibilism,” maintains that materialistic determinism and free will are really compatible. This position is apparently quite popular in philosophy of mind circles, and has been argued by Daniel Dennett and other famous philosophers. The argument says, first, that it doesn’t matter if an organism “could have done otherwise” — what matters is that the organism is the source of the action. That is, we can reasonably be said to have free will if we are able to do what we want, even if we are not able to want what we want. Second, compatibilists point out that organisms and their environments are so complex that there is no way, even theoretically, to predict what an organism will do in a future situation. So for all practical purposes, we are free.

Mitchell finds these arguments unconvincing. They seem to be saying that if we just change our perspective, or our definitions, the problem will go away. “But I cannot escape feeling that some sleight of hand is part of this line of argument,” he writes. “It feels as if some (presumably unwitting) misdirection is going on — as if the primary problem has been circumvented or even denied, rather than confronted.” Instead, there ought to be some genuine indeterminacy in the system, or else “no matter how complex, the agent will be pushed around deterministically by its own components.”

I think the “sleight of hand” Mitchell senses is the confusing of epistemology with ontology: confusing what can be known with what is. Regardless — Mitchell argues that the fuss is unnecessary. There is really no reason that free will needs to be compatible with strict determinism, he says, because physics, as it turns out, is not strictly deterministic. That requirement is a relic from a bygone era, when everything seemed to move inexorably according to simple Newtonian laws. Most modern quantum physicists, in contrast, agree that particles seem to actually have a degree of freedom or true randomness to their movement. So, Mitchell says, “there is nothing in the laws physics that rules out the possibility of agency or free will, a priori.”

In fact, various studies seem to show organisms acting in a non-deterministic way. In one fascinating experiment, an electrical probe was attached directly to a leech’s central nervous system, allowing the experimenters to bypass the complexities of environment altogether and administer the exact same stimulus, repeatedly. Even under such perfectly controlled conditions, there seemed to be no way to predict how a leech (like the one pictured above) would respond to the stimulus each time.

This apparent indeterminacy scales all the way up to more complex behaviors and situations, resulting in what is known as the Harvard Law of Animal Behavior: “Under carefully controlled experimental circumstances, an animal will behave as it damn well pleases.”

So Far, So Good

But what about the experiments that seem to show the opposite, that free will is a mere illusion?

There are quite a few famous experiments of this kind, but in Mitchell’s professional opinion, they show nothing of the sort.

For example, Benjamin Libet’s now-famous 1983 experiment showed a signal called a “readiness potential” in the brain a fraction of a second before the subject was conscious of choosing to move his hand. Many have taken this to be definitive proof that free will is only an illusion: at the moment we think we are freely choosing, the brain has actually decided beforehand.

Mitchell writes that this interpretation is “to put it mildly, a drastic overinterpretation”:

That is because the design of the experiment makes it effectively irrelevant for the question of free will. The participants made an active and deliberate decision when they agreed to take part in the study and to follow the instructions of the researchers. Those instructions explicitly told them to act on a whim: “to let the urge to act appear on its own at any time without any preplanning or concentration on when to act.” They had no reason to want to move their hand more at one point than another because nothing was at stake. And so, it seems they did indeed act on a whim: they (decided to) let subconscious processes in their brains decide, by drawing on inherent random fluctuations in neural activity.

This is what a different group of neuroscientists, led by Aaron Schurger, concluded from analyzing the data from the original experiment — that the test subjects had (instinctively, of course) set a certain potential level of neuronal activity, deciding that when random fluctuations in the brain reach that level, they would take the proscribed action.

So now you have two plausible interpretations of the data.

But Which One Is True?

Another experiment, led by Uri Maoz and Liad Mudrik, sought to distinguish between the two possibilities. The researchers gave half the test subjects a decision with no serious consequences, and half a decision with consequences that they cared about. Sure enough, when the subjects were given inconsequential decision, a readiness potential preceded the decision, as in Libet’s experiments. But when the decision mattered, no readiness potential was detected.

“Overall then,” Mitchell writes, “Libet’s experiments have very little relevance for the question of free will. They do not relate to deliberative decisions at all, where readiness potential is not observed. Instead, they confirm, first, that neural activity in the brain is not completely deterministic and, second, that organisms can choose to harness the inherent randomness to make arbitrary decisions in a timely fashion.”

So much for “free.” We’ll examine what Mitchell has to say about “will” tomorrow.

Notes

E.g., Mitchell mentions that the now-classic view that symbiosis might have been necessary to make the switch from prokaryotic to eukaryotic life.

More brain mysteries - miniature brains with great behavioral repertoire

noreply@blogger.com (DG) — Sun, 19 Jan 2025 09:43:00 +0000

By Design: Brain Miniaturization in Some Very Small Insects

Eric Cassell

January 14, 2025, 6:14 AM

https://evolutionnews.org/2025/01/by-design-brain-miniaturization-in-some-very-small-insects/https://evolutionnews.org/2025/01/by-design-brain-miniaturization-in-some-very-small-insects/

In the last several years there has been increased interest in and research into so-called “microinsects.” These are insects that are miniaturized compared to the majority of other insect species. They include species of wasps, beetles, and ants. An example is the wasp Megaphragma mymaripenne (pictured above), which is only 200 micrometers long (¹⁄₁₂₅ inch) and is the third smallest known insect. Such microinsects are comparable in size to some single-celled organisms. M. mymaripenne has only 4,600 neurons, several orders of magnitude fewer than in larger insects.¹ This is the smallest number of neurons in all insects. For example, honey bee brains have about one million neurons. General characteristics of miniaturized insect brains are a decrease in neuron size, decrease in neuron spacing, increase in neuron density, and increased density of synapses.²

One of the more interesting aspects of insect miniaturization is the reduction in the size of neurons. The cell bodies of neurons in human brains typically are about 20 micrometers in diameter, while the nucleus is about 5-10 micrometers.³ The smallest diameters of neuron cell bodies previously documented in insects were “2 to 3 micrometers, possibly because neuron cell body diameter is restricted by the size of the nucleus.”⁴ As explained by one group of researchers, one potential explanation for the reduction of neuron size is, “A benefit of smaller neurons over larger ones is that they are energetically less expensive both at rest and whilst signaling and may be packed more densely.”⁵

Another microinsect example is the parasitic wasp Trichogramma evanescens, whose entire brains “are only marginally larger than a single motor neuron in the human brain.”⁶ The size of their brains range between 160-330 micrometers, while the largest motor neurons in human brains are called Betz cells, which can be as large as 50-100 micrometers.⁷

The smallest free-living insect is a beetle called Scydosella musawasens, which illustrates another example of miniaturization. The body size of S. musawasens is only 325 micrometers. Their brains contain approximately 9,500 cells with an average diameter of approximately 1.25 micrometers.⁸

Who Needs a Nucleus?

Another characteristic in some miniaturized species associated with the reduction in the size of neurons is the elimination of the nucleus. As explained in one research paper, “Of 4,600 neurons in the brain of M. mymaripenne, approximately 95% were anucleate neurons, of which the somata (neuron cells) were almost twice as small as those of the nucleated neurons in the adult brain.”⁹

Recent research by a group of Russian scientists has found a second parasitic wasp species (Megaphragma polilovi) whose brain neurons lack a nucleus. The paper’s authors write, “Our finding shows that a similar variant of saving space due to the lysis of the cell bodies and nuclei of neurons in the brain and other parts of the central nervous system evolved at least twice in the course of insect evolution.”¹⁰

Small Animals and Relatively Larger Brains

A common characteristic of small animals, including not just insects, is that they generally have larger brains relative to body size. According to so-called Haller’s Rule, smaller animals have proportionally larger brains than larger-bodied forms.¹¹ A study that was performed on 23 various insect species from 11 families and five orders found that, “The rule of brain size changing allometrically with body size, known as Haller’s rule or brain–body allometry, has been confirmed for many vertebrates, insects, spiders, or other invertebrates; it is fully realized in the smallest insects.”¹² In other words, the brains are not literally larger, but the brain to body size ratio is bigger.

Cerebral index is the term that relates the weight of the brain relative to the entire body. In humans it is 2.5 percent.¹³ It was long believed that cerebral index among animals was the highest in hummingbirds at approximately 8 percent. However, research has determined that it, “Reaches 8.36% in the miniature hymenopteran Trichogramma, and 15 percent in Brachymyrmex, some of the smallest ants.”¹⁴ It is a similar situation with brain volume, where, “Extremely large relative brain volumes are found in miniature insects, the brain of which can occupy more than 10 percent of the body volume, for example, in the first instar nymph of the booklouse Liposcelis bostrychophila in which the volume of the entire central nervous system can exceed 16 percent of the body volume.”¹⁵

Relatively larger brains do come at a cost as, “A disproportionately large brain not only imposes geometric restrictions on the body size but also leads to huge energy expenditures. As a result, the size of the brain is one of the main factors that limits the miniaturization of animals.”¹⁶ The basic theory that is intended to explain Haller’s Rule is that, “In very small animals, brain-body size allometry implies that brain size becomes a limiting factor of body miniaturization because costs for development and maintenance of energetically expensive brain tissue.”¹⁷ As mentioned previously, smaller neurons require less energy, therefore that can offset the expense of brains that are relatively larger. The implication is that the physical limits may have been reached for how much brains can be compressed.

Miniaturization and Behavior

One question that can be asked is: Does reduced brain size affect the behavior of animals? The answer appears to be that there is no effect. The authors of a paper on the miniaturized wasp Trichogramma addressed this issue and concluded that, “The extremely small brain of this species does not seem to affect their behavioural performance. Female wasps, even the small phenotypes, display a rich behavioural and cognitive repertoire similar to much larger insects, including flight, walking, courtship, deciding over the size and sex of their progeny, vision, olfaction, learning and long- and short-term memory formation…These complex behavioural traits are essential to find and parasitize suitable host eggs in nature and might require a certain, minimal brain size.”¹⁸ Similarly, regarding another wasp species (Megaphragma polilovi), whose brain neurons do not have a nucleus, researchers conclude, “Miniature insects retain complex forms of behavior and locomotion, which shows that the anucleate neurons remain functional.”¹⁹

Given that basic functionality and behavior is not negatively affected by miniaturized brains, including those with neurons that do not have a nucleus, the next question is: How is function maintained? That is still unknown. Regarding the function of neurons that lack a nucleus, “A number of other important issues also remain unresolved. First, the mechanisms and control of the process of lysis of the cell bodies and nuclei of neurons remain unknown. And, second, the most important question is how efficiently the dendrites, axons, and remaining nuclei of the neurons function, and what cellular molecular mechanisms provide for their functioning.”²⁰ So there is still much to be learned about miniaturized brains.

An Analogy with Electronic Circuits

An analogy can be drawn between the miniaturization of brains and the miniaturization of electronic circuits. Ever since the invention of the transistor there has been a consistent reduction in the size of electronic semiconductor circuits. This transformation was even given a name “Moore’s Law” by Gordon Moore, the co-founder of Fairchild Semiconductor and Intel. According to Moore’s Law the number of transistors in a given area of an electronic circuit doubles every two years.²¹ And just as electronic circuits have been reduced in size, while also maintaining and even improving performance, miniaturized insect brains also achieve performance similar to nominally sized insect brains.

Another similarity between brains and electronic circuits is their complexity. While there has been a long history of neuroscientists and engineers in making the comparison between biological neural networks and artificial neural networks, the fact is that biological neural networks (brains) exhibit more complexity.²²

One observation that can be made is that another thing in common between the miniaturization of brains and electronic circuits is that they are the product of engineering design. It has required a significant amount of engineering, as well as developments in physics and manufacturing, to reduce the size of electronic circuits. The same can be said of the process of miniaturization of brains. It is difficult to see how that could have occurred through a random evolutionary process.

In recent years experts in the semiconductor industry have been proclaiming that Moore’s Law was no longer applicable due to limitations imposed by basic physics that have restricted further reduction in the size of electronic circuits.²³ It appears the same is true for miniaturization of brains due to limitations in the size of neurons, and other factors in maintaining the function of neural networks.

[[But this comparison with electronic circuits says nothing about explaining behavior since the electronic circuits are packed with many many more elements when they are miniaturized.]]

Notes

Van der Woude, et al., “Breaking Haller’s Rule: Brain-Body Size Isometry in a Minute Parasitic Wasp,” Brain Behav Evol2013; 81: 86-92.
A. Makarova, et al., “Small brains for big science,” Current Opinion in Neurobiology 2021, 71:77-83.
Mark F. Bear, Barry W. Connors, and Michael A. Paradiso, Neuroscience: Exploring the Brain (Baltimore: Lippincott Williams & Wilkins, 2007) 28, 30.
Van der Woude, et al., “Breaking Haller’s Rule.”
Van der Woude, et al., “Breaking Haller’s Rule.”
Van der Woude, et al., “Breaking Haller’s Rule.”
Nolan, et al., “Betz cells of the primary motor cortex,” J Comp Neurol. 2024; 532.
A.A. Makarova and A.A. Polilov, “Structure of the Brain of the Smallest Coleoptera,” Doklady Biochemistry and Biophysics, 2022, Vol. 505, 166-169.
Van de Woude, et al., “Breaking Haller’s Rule.”
Polilov, et al., “Extremely small wasps independently lost the nuclei in the brain neurons of at least two lineages,” Scientific Reports (2023) 13:4320.
Van de Woude, et al., “Breaking Haller’s Rule.”
Polilov, A.A and & Makarova, A.A, “The scaling and allometry of organ size associated with miniaturization in insects: A case study for Coleoptera and Hymenoptera,” Sci. Rep. 7:43095 (2017).
Polilov, A.A and & Makarova, A.A, “The scaling and allometry of organ size associated with miniaturization in insects.”
Polilov, A.A and & Makarova, A.A, “The scaling and allometry of organ size associated with miniaturization in insects.”
A. Makarova, et al., “Small brains for big science.”
Makarova, et al., “Small brains for big science.”
Van de Woude, et al., “Breaking Haller’s Rule.”
Van de Woude, et al., “Breaking Haller’s Rule.”
Polilov, et al., “Extremely small wasps independently lost the nuclei in the brain neurons of at least two lineages.”
Polilov, et al., “Extremely small wasps independently lost the nuclei in the brain neurons of at least two lineages.”
John Shalf, “The future of computing beyond Moore’s Law,” Phil. Trans. R. Soc. A, 2020, 378.
Eric Cassell, “Design, Engineering, Specified Complexity: Appreciating the Fruit Fly Brain,” Evolution News, November 14, 2014.
Tom Simonite, “Moore’s Law is Dead. Now What?” MIT Technology Review, May 13, 2016.

Scientific status of Intelligent design

noreply@blogger.com (DG) — Wed, 15 Jan 2025 10:47:00 +0000

and an excellent example of the work done at Dicovery.org.

https://evolutionnews.org/2025/01/new-long-story-ervs-pseudogenes-onions/

Ohr Somayach campaign

noreply@blogger.com (DG) — Sun, 12 Jan 2025 14:51:00 +0000

Ohr Somayach is desperately trying to cover a 3 million dollar deficit. This of course means that the educational staff has not been paid. I urge you with all my heart to look at the material on the link and please try to help.

https://causematch.com/ohr-somayach-international-24/474345

Discovering again what we don't know

noreply@blogger.com (DG) — Sat, 11 Jan 2025 18:10:00 +0000

The Ocean Teems With Networks of Interconnected Bacteria

Nanotube bridge networks grow between the most abundant photosynthetic bacteria in the oceans, suggesting that the world is far more interconnected than anyone realized.

https://www.quantamagazine.org/the-ocean-teems-with-networks-of-interconnected-bacteria-20250106/?mc_cid=fd0b65eee0&mc_eid=61275b7d81

Prochlorococcus bacteria are so small that you’d have to line up around a thousand of them to match the thickness of a human thumbnail. The ocean seethes with them: The microbes are likely the most abundant(opens a new tab) photosynthetic organism on the planet, and they create a significant portion — 10% to 20% — of the atmosphere’s oxygen. That means that life on Earth depends on the roughly 3 octillion (or 3 × 10²⁷) tiny individual cells toiling away.

Biologists once thought of these organisms as isolated wanderers, adrift in an unfathomable vastness. But the Prochlorococcus population may be more connected than anyone could have imagined. They may be holding conversations across wide distances, not only filling the ocean with envelopes of information and nutrients, but also linking what we thought were their private, inner spaces with the interiors of other cells.

At the University of Córdoba in Spain, not long ago, biologists snapping images of the cyanobacteria under a microscope saw a cell that had grown a long, thin tube and grabbed hold of its neighbor. The image made them sit up. It dawned on them that this was not a fluke.

“We realized the cyanobacteria were connected to each other,” said María del Carmen Muñoz-Marín(opens a new tab), a microbiologist there. There were links between Prochlorococcus cells, and also with another bacterium, called Synechococcus, which often lives nearby. In the images, silvery bridges linked three, four, and sometimes 10 or more cells.

Muñoz-Marín had a hunch about the identity of these mysterious structures. After a battery of tests, she and her colleagues recently reported(opens a new tab) that these bridges are bacterial nanotubes. First observed in a common lab bacterium only 14 years ago, bacterial nanotubes are structures made of cell membrane that allow nutrients and resources to flow between two or more cells.

The structures have been a source of fascination and controversy(opens a new tab) over the last decade, as microbiologists have worked to understand what causes them to form and what, exactly, travels among these networked cells. The images from Muñoz-Marín’s lab marked the first time these structures have been seen in the cyanobacteria responsible for so much of the Earth’s photosynthesis.

They challenge fundamental ideas about bacteria, raising questions such as: How much does Prochlorococcus share with the cells around it? And does it really make sense to think of it, and other bacteria, as single-celled?

Totally Tubular

Many bacteria have active social lives. Some make pili, hairlike growths of protein that link two cells to allow them to exchange DNA. Some form dense plaques together, known as biofilms. And many emit tiny bubbles known as vesicles that contain DNA, RNA or other chemicals, like messages in a bottle for whatever cell happens to intercept them.

It was vesicles that Muñoz-Marín and her colleagues, including José Manuel García-Fernández, a microbiologist at the University of Córdoba, and graduate student Elisa Angulo-Cánovas(opens a new tab), were looking for as they zoomed in on Prochlorococcus and Synechococcus in a dish. When they saw what they suspected were nanotubes, it was a surprise.

Growing between these bacteria (left: Prochlorococcus; right: Bacillus subtilis) are nanotube bridges, through which cells transport substances such as amino acids and enzymes. Although these nanotubes were first observed only in 2011, biologists now think that bacteria have been making these structures all along unnoticed.

Nanotubes are a recent addition to scientists’ understanding of bacterial communication. In 2011, Sigal Ben-Yehuda and her postdoc Gyanendra Dubey at the Hebrew University of Jerusalem first published images(opens a new tab) of tiny bridges, made of membrane, between the bacteria Bacillus subtilis. These tubes were actively transporting material: The researchers showed that green fluorescent proteins produced in one cell of the network quickly percolated through the others. They found the same result with calcein, a small molecule that is not able to cross bacterial membranes on its own. These cells were not existing placidly side by side; their inner spaces were linked, more like rooms in a house than detached dwellings.

It was a startling revelation. The news compelled other biologists to reexamine their own images of cells. It soon became clear that B. subtilis was not the only species producing nanotubes. In populations of Escherichia coli and numerous other bacteria, small but consistent fractions of cells were spotted with nanotubes. In experiments, scientists watched cells sprout the tubes and then investigated what they carried. Moving across these bridges from cell to cell were substances such as amino acids(opens a new tab), the basic building blocks of proteins, as well as enzymes and toxins(opens a new tab). Bacteria, biologists now think, have probably been making these structures all along. Scientists simply hadn’t noticed them or realized their significance.

Not everyone has found it straightforward to get bacteria to make nanotubes. Notably, a group at the Czech Academy of Sciences could see nanotubes only when cells were dying(opens a new tab). Their suggestion that the tubes are a “manifestation of cell death” cast doubt on whether the structures were truly an important part of the cells’ normal biology. Since then, however, additional work has carefully documented that healthy cells do grow the structures. All this suggests that certain conditions must be met for bacteria to take this step. Still, “I think they are everywhere,” Ben-Yehuda said.

The latest findings are particularly eye-opening because Prochlorococcus and Synechococcus are not your average dish-dwelling bacteria. They live in a singularly turbulent environment: the open ocean, where water movement might reasonably be expected to break the fragile tubes. What’s more, they are photosynthetic, meaning that they get most of what they need to survive from the sun. What need could they have for trading through tube networks? There has been another sighting(opens a new tab) of nanotubes in marine bacteria, but those microbes are not photosynthetic — they gobble up nutrients from their immediate environment, a lifestyle in which swapping substances with neighbors might have a more obvious benefit.

So, when Muñoz-Marín and Angulo-Cánovas saw their nanotubes, they were initially skeptical. They wanted to make sure that they weren’t mistaking some accident of how the cells were prepared or how the images had been taken for a natural structure.

“We spent a lot of time to ensure that what we were finding in the images was actually something physiological and not any kind of an artifact,” García-Fernández said. “The results were so shocking in the field of marine cyanobacteria that we were, on the one hand, amazed, and on the other hand, we wanted to be completely sure.”

They put the cells under four radically different kinds of imaging devices — not only a transmission electron microscope, which they had been using when they first spotted the structures, but also a fluorescence microscope, a scanning electron microscope, and an imaging flow cytometer, which images live cells as they zip by. They looked at Prochlorococcus and Synechococcus on their own and at cultures where they lived together. They looked at dead cells and living ones. They even looked at fresh samples of seawater fished out of the Bay of Cádiz. In all the samples they spotted bridges, which connected about 5% of the cells. The nanotubes did not seem to be artifacts.

From left: José Antonio González-Reyes, Jesús Díez, María del Carmen Muñoz-Marín, Elisa Angulo-Cánovas and José Manuel García-Fernández, all based at the University of Córdoba. The researchers were part of an interdisciplinary group that discovered and studied the bacterial nanotubes that grow between photosynthetic ocean bacteria.

University of Córdoba

Next, to see whether the links were in fact nanotubes, they performed versions of the now-canonical experiments with green fluorescent protein and calcein described by Ben-Yehuda and Dubey. The networked cells lit up. The team also confirmed that the links were indeed made of membrane lipids and not protein, which would instead suggest pili. They were convinced, finally, that they were looking at bacterial nanotubes.

These tubes connect some of the most abundant organisms on the planet, they realized. And that immediately made something very clear, something the researchers are still turning over in their minds.

“At the beginning of this century, when you were speaking about phytoplankton in the ocean, you were thinking about independent cells that are isolated,” García-Fernandez said. “But now — and not only from these results, but also from results from other people — I think we have to consider that these guys are not working alone.”

A Cellular Network

There might be a good reason why cyanobacteria, floating in the vast expanse of the ocean, might want to join forces. They have curiously small genomes, said Christian Kost(opens a new tab), a microbial ecologist at the University of Osnabrück in Germany who was not involved in this study. Prochlorococcus has the smallest genome(opens a new tab) of any known free-living photosynthetic cell, with only around 1,700 genes. Synechococcus is not far behind.

Among bacteria, small genomes relieve organisms of the pressure of maintaining bulky DNA, but this state also requires them to scavenge many basic nutrients and metabolites from their neighbors. Bacteria with streamlined genomes sometimes form interdependent communities with organisms that produce what they need and need what they produce.

“This can be much more efficient than a bacterium that attempts to produce all metabolites at the same time,” Kost said. “Now, the problem, when you’re living in a liquid, is: How do you exchange these metabolites with other bacteria?”

Nanotubes may be a solution. Nutrients transferred this way will not be swept away by currents, lost to dilution or consumed by a freeloader. In computer simulations, Kost and his colleagues have found that nanotubes can support the development of cooperation among groups of bacteria.

What’s more, “this [new] paper shows that this transfer is both happening within and between species,” he said. “This is super interesting.” In a previous paper(opens a new tab), he and colleagues also noticed different species of bacteria connected by nanotubes.

This kind of cooperation is probably more common than people realize, said Conrad Mullineaux(opens a new tab), a microbiologist at Queen Mary University of London — even in environments like the open ocean, where bacteria may not always be close enough to form nanotubes.

We often speak of bacteria as being simple and single-celled. But bacterial colonies, biofilms and consortiums of different microorganisms can perform complicated feats of engineering and behavior together, sometimes rivaling what multicellular life can achieve. “I like to try to persuade people sometimes, when I’m feeling feisty: You’re a biofilm and I’m a biofilm,” Mullineaux said. If the sea is full of cyanobacteria communicating by nanotube and vesicle, then perhaps this exchange of resources could affect something as fundamental as the amount of oxygen in the atmosphere or the amount of carbon sequestered in the ocean.

Kost, Ben-Yehuda and Mullineaux agree that the new paper’s findings are intriguing. The authors have done all the right tests to ensure that the structures they are seeing are in fact nanotubes, they said. But more work is needed to explain the significance of the finding. In particular, a big open question is what, exactly, Prochlorococcus and Synechococcus are sharing with each other in the wild. Photosynthesis allows these bacteria to draw energy from the sun, but they must pick up nutrients such as nitrogen and phosphorus from the environment. The researchers are embarking on a series of experiments with Rachel Ann Foster(opens a new tab) of Stockholm University, a specialist in nutrient flow in the ocean, to trace these substances in networked cells.question is how bacteria form these tubes, and under what conditions. The tubes are not much longer than an individual cell, and Prochlorococcus, in particular, is thought to spread out in the water column. Muñoz-Marín and her team are curious about the concentrations of bacteria required for a network to form. “How often would it be possible for these independent cells to get close enough to each other in order to develop these nanotubes?” García-Fernandez asked. The current study shows that nanotubes do form among wild-caught cells, but the precise requirements are unclear.

Looking back at what people thought about bacterial communication when he began to study marine cyanobacteria 25 years ago, García-Fernandez is conscious that the field has undergone a sea change. Scientists once thought they saw myriad individuals floating alongside each other in immense space, competing with neighboring species in a race for resources. “The fact that there can be physical communication between different kind of organisms — I think that changes many, many previous ideas on how the cells work in the ocean,” he said. It’s a far more interconnected world than anyone realized.

The Quanta Newsletter

Bottom of Form

What Is Entropy? A Measure of Just How Little We Really Know.

noreply@blogger.com (DG) — Mon, 16 Dec 2024 10:51:00 +0000

https://www.quantamagazine.org/what-is-entropy-a-measure-of-just-how-little-we-really-know-20241213/?mc_cid=7f931e7b43&mc_eid=61275b7d81

[[This is the introduction to a fascinating article which reveals that even as fundamental and studied a concept as entropy is smothered in doubts and disagreements that show the state of theoretical science to be very immature indeed. I strongly recommend reading the whole article.]]

Life is an anthology of destruction. Everything you build eventually breaks. Everyone you love will die. Any sense of order or stability inevitably crumbles. The entire universe follows a dismal trek toward a dull state of ultimate turmoil.

To keep track of this cosmic decay, physicists employ a concept called entropy. Entropy is a measure of disorderliness, and the declaration that entropy is always on the rise — known as the second law of thermodynamics — is among nature’s most inescapable commandments.

I have long felt haunted by the universal tendency toward messiness. Order is fragile. It takes months of careful planning and artistry to craft a vase but an instant to demolish it with a soccer ball. We spend our lives struggling to make sense of a chaotic and unpredictable world, where any attempt to establish control seems only to backfire. The second law demands that machines can never be perfectly efficient, which implies that whenever structure arises in the universe, it ultimately serves only to dissipate energy further — be it a star that eventually explodes or a living organism converting food into heat. We are, despite our best intentions, agents of entropy.

“Nothing in life is certain except death, taxes and the second law of thermodynamics,” wrote(opens a new tab) Seth Lloyd, a physicist at the Massachusetts Institute of Technology. There’s no sidestepping this directive. The growth of entropy is deeply entwined with our most basic experiences, accounting for why time runs forward and why the world appears deterministic rather than quantum mechanically uncertain.

But despite its fundamental importance, entropy is perhaps the most divisive concept in physics. “Entropy has always been a problem,” Lloyd told me. The confusion stems in part from the way the term gets tossed and twisted between disciplines — it has similar but distinct meanings in everything from physics to information theory to ecology. But it’s also because truly wrapping one’s head around entropy requires taking some deeply uncomfortable philosophical leaps.

As physicists have worked to unite seemingly disparate fields over the past century, they have cast entropy in a new light — turning the microscope back on the seer and shifting the notion of disorder to one of ignorance. Entropy is seen not as a property intrinsic to a system but as one that’s relative to an observer who interacts with that system. This modern view illuminates the deep link between information and energy, which is now helping to usher in a mini-industrial revolution on the smallest of scales.

Two hundred years after the seeds of entropy were first sown, what’s emerging is a conception of this quantity that’s more opportunistic than nihilistic. The conceptual evolution is upending the old way of thinking, not just about entropy, but about the purpose of science and our role in the universe.

Kidney cells learn and remember........

noreply@blogger.com (DG) — Fri, 22 Nov 2024 08:00:00 +0000

Memories Are Not Only in the Brain

Study shows kidney and nerve tissue cells learn and make memories in ways similar to neurons

Nov 7, 2024

James Devitt

https://www.nyu.edu/about/news-publications/news/2024/november/memories-are-not-only-in-the-brain--new-research-finds.html

It’s common knowledge that our brains—and, specifically, our brain cells—store memories. But a team of scientists has discovered that cells from other parts of the body also perform a memory function, opening new pathways for understanding how memory works and creating the potential to enhance learning and to treat memory-related afflictions.

“Learning and memory are generally associated with brains and brain cells alone, but our study shows that other cells in the body can learn and form memories, too,” explains New York University’s Nikolay V. Kukushkin, the lead author of the study, which appears in the journal Nature Communications.

The research sought to better understand if non-brain cells help with memory by borrowing from a long-established neurological property—the massed-spaced effect—which shows that we tend to retain information better when studied in spaced intervals rather than in a single, intensive session—better known as cramming for a test.

In the Nature Communications research, the scientists replicated learning over time by studying two types of non-brain human cells in a laboratory (one from nerve tissue and one from kidney tissue) and exposing them to different patterns of chemical signals—just like brain cells are exposed to patterns of neurotransmitters when we learn new information. In response, the non-brain cells turned on a “memory gene”—the same gene that brain cells turn on when they detect a pattern in the information and restructure their connections in order to form memories.

“Learning and memory are generally associated with brains and brain cells alone, but our study shows that other cells in the body can learn and form memories, too." NYU’s Nikolay Kukushkin

To monitor the memory and learning process, the scientists engineered these non-brain cells to make a glowing protein, which indicated when the memory gene was on and when it was off.

The results showed that these cells could determine when the chemical pulses, which imitated bursts of neurotransmitter in the brain, were repeated rather than simply prolonged—just as neurons in our brain can register when we learn with breaks rather than cramming all the material in one sitting. Specifically, when the pulses were delivered in spaced-out intervals, they turned on the “memory gene” more strongly, and for a longer time, than when the same treatment was delivered all at once.

“This reflects the massed-space effect in action,” says Kukushkin, a clinical associate professor of life science at NYU Liberal Studies and a research fellow at NYU’s Center for Neural Science. “It shows that the ability to learn from spaced repetition isn't unique to brain cells, but, in fact, might be a fundamental property of all cells.”

The researchers add that the findings not only offer new ways to study memory, but also point to potential health-related gains.

“This discovery opens new doors for understanding how memory works and could lead to better ways to enhance learning and treat memory problems,” observes Kukushkin. “At the same time, it suggests that in the future, we will need to treat our body more like the brain—for example, consider what our pancreas remembers about the pattern of our past meals to maintain healthy levels of blood glucose or consider what a cancer cell remembers about the pattern of chemotherapy.”

The work was jointly supervised by Kukushkin and Thomas Carew, a professor in NYU’s Center for Neural Science. The study’s authors also included Tasnim Tabassum, an NYU researcher, and Robert Carney, an NYU undergraduate researcher at the time of the study.