Next up, @LPiolopez and a remarkable finding about #aging. Preprint here: osf.io/preprints/osf/smzc4_v… Atavistic Genetic Expression Dissociation (AGED) during aging: meta-phylostratigraphic evidence of cellular- and tissue-levels phylogenetic dissociation Abstract: "Aging is commonly attributed to accumulated damage, or evolved antagonistic genetic trade-offs, which lead to an accumulation of genetic damage, noise, or DNA methylation causing the misexpression of key genes necessary for longevity. We propose an atavistic dysregulation of gene expression at cellular and tissue-levels during aging, which frames aging as a gradual regression toward ancestral cellular states. Similar to the atavistic model of cancer, in which cells revert to unicellular-like behavior, aging may result from a progressive breakdown of coordinated morphogenetic control, leading organs and tissues to revert towards less integrated, ancient unicellular states. This view suggests that aging may involve a progressive reversal of the well-known ontogenetic tracing of prior phylogenetic embryonic characteristics. Moreover, as in cancer, aging could involve a loss of large-scale coordination, with different tissues reverting to ancient gene expression to different degrees. We tested this hypothesis using a meta-phylostratigraphic analysis to ask: do older human tissues express more ancient genes, and does the variance of transcriptional phylogenetic age across tissues increase with organismal age? We found: (1) An atavistic over-representation of differential expression in the most ancient genes for two multi-tissue aging databases covering skin, ovarian, immune, senescent and mesenchymal-senescent cells; (2) No atavistic over-representation of the differential genet expression during aging of brain cells and mesenchymal stem cells; and (3) overall age-dependent increase of heterogeneity in the direction of the phylogenetic position of tissues’ transcriptional profiles. Our analyses suggest that aging involves uncoordinated and tissue-specific phylogenetic changes in gene expression. Understanding aging as a structured, heterogenous atavistic process opens new avenues for rejuvenation, focusing on restoring multicellular coherence with respect to evolutionarily-youthful gene expression." In other words, during aging, some tissues shift their gene expression toward more ancient genes, and, there arises a lack of concordance between body tissues with respect to the phylogenetic age of the genes they express. Thus, while I often talk about morphogenetic/cognitive systems dissociating and losing integration spatially, it appears that aging is a dissociative disorder with respect to time (evolutionary time). Lots more to do, but very exciting.

Mar 23, 2025 · 4:07 PM UTC

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Cells in developing organisms also go through these atavistic phases, in the other direction, aren't they? Is there a symmetry here?
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This is an extremely surprising and important finding.
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More coming! There's an important relationship between the cognitive aspect of maintaining morphogenetic goals in the body and the evolutionary and developmental forces of integration and dissociation, which impacts how we think about aging and design therapeutics.
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Any ideas on how to intervene in such state and revert it?
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Oh yes. stay tuned.
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Went right for the grok button to ELI5 but for some reason there is no grok. So weird why it is in some posts and not in others. No worries though I'll just ELI it directly against the paper.
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Hmm. We have tissues, cells, immune responses, metabolic states. There is an equilibrium and feedback that keeps these systems in check. As we age, various tissues begin degradation and changes. Cell signaling, hormones, immune, waste products, and genes on/off go whacky.
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@grok can you summarize the paper linked.
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Such fun research again! "existential boredom of the somatic self" Quoting you. Aging is by the seem of it mostly just what happens once the goals have been reached. New somatic goals.. Intra-lifespan evolution.. ? Perhaps the exercise thing simply keeps some subset of organism level goals functional. Maybe rejuvenation isn't staying young, its just going somewhere new.
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This sounds fascinating
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Back to back releases, keep them coming! However I was supposed to do some work this week
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Thoughts @LidskyPeter ?
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🙌🏻🤩🙌🏻 So cool!
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“meta-phylostratigraphic”
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I like it it when the term „integration“ comes up, because that is how I think about medicine all the time. Only on the macroscopic scale. Integration at the organism level can lead to better function. Now we need to tackle the microscopic scale to solve age associated disease.
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@ToKTeacher I think you will find this really interesting Aging is just communication breakdown down between cells
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Wow, so it is like somebody forked your DNA repository and now cells are having a fight in the Issues section.
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With the idealist view that a human brain is what consciousness "looks like" from an outside POV, it makes sense those cells don't show the same aging process as other cells. Consciousness doesn't "age" or have entropy. It's perceptual correlate shouldn't be aging/deteriorating.
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Micheal i remember you said you wanted something that finds programs. Maybe this helps when he creates an API ?
I apologize for the emotional vagueposts. I'll be direct now a major breakthrough took place today for a context, I'm working on the problem of synthesizing a program by examples. that is, given a set of tests, like: f(3, [0,1,2,0,2]) = [1,1,1,0,2] f(1, [4,2,3,7,7]) = [1,2,3,7,7] f(4, [9,5,1,8,7]) = [1,1,1,1,7] f(2, [5,4,3,2]) = [1,1,3,2] implement a function that passes them all. this is easy for a human, but it is very hard for computers. in fact, this problem is *the* cornerstone of AI - after all, NNs are just function approximators, which we combine to design programs capable of learning. yet, NNs are not efficient. what if there is a faster way to do it, by manipulating the equations directly, "symbolically"? many asked that question, yet, all past attempts failed, and NNs won the AI race. since a year ago, I've been investigating this problem from the lens of optimal λ-calculus evaluation. I've tried hundreds of things, most failures, some sporadic successes. in January, I presented SupGen: a synthesizer that outperformed similar solutions by up to 100x. yet, it still had an exponential factor: the number of pattern-matches today, that exponential has been broken it all started one week ago, when I rewrote the whole thing based on a new core. compared to SupGen, NeoGen was 3x smaller, 10x faster, and more capable: for the first time ever, it was able to synthesize sort()! yet, despite many optimizations, from V0 to V4, it still had the same exponential factor. that was yesterday. today, I had a realization, changed *1 character* in my code, and V5 was born. below, I share its benchmark, on 3 problems: - Draw: low pattern-match complexity - Max: medium pattern-match complexity - Mod5: high pattern-match complexity I'll now let the numbers speak for themselves (:
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Seems to corroborate information theory of aging. Creatures with negligeable scenesce must be good at topological/holographic encoding their internal state, then recalling the integrated history of their physiology. Cycling bioelectic and mechanical processes like an engine would
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your work once again has an incredible galvanizing effect on framing. As a side note, this proposition definitely changes the way one looks at the phrase 'from dust to dust'
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[typo? “No atavistic over-representation of the differential genet expression …” : is “genet” a word? Halfway between gene and genetic?]
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I'm a Specialised Kinesiologist & my practice has moved dramatically away from working on "carbon" body, bones, joints, muscles, into working with the cells as intelligence. Speaking directly to the DNA and asking it to switch off what isn't working and activate what it needs.
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The idea of human 'longevity' is poorly posed - it's pushing a rope. If even one clone of a human ever exists, we are a perennial species. And the secret lies in the fossilization of our DNA seed. humanism.substack.com
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