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The Origins of Aging: Evidence that Aging is an Adaptive Phenotype

2016· review· en· W2328597900 on OpenAlexaff
Michael A. Singer

Bibliographic record

VenueCurrent Aging Science · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsMulticellular organismBiologyOrganismContext (archaeology)PhenotypeSenescenceMorphogenesisEvolutionary biologyProgrammed cell deathModel organismLongevityCellCell biologyGeneticsApoptosisGene

Abstract

fetched live from OpenAlex

BACKGROUND: Aging can be defined as the time-related decline in biological functions which ultimately results in organismal death. Beyond the stage of reproductive maturity as fertility declines, cell and tissue functions come under reduced selection pressure since organismal survival is considered no longer an evolutionary priority. Repair mechanisms become less robust and the resulting stochastic accumulation of tissue and genomic damage is believed to underlie the aging process. The objective of this review is to challenge this construct and to present evidence that aging represents a species-specific adaptive developmental program. METHODS: Through a review of published data, the cellular aging programs of both single cell and multicellular organisms are described. Since all organisms live in communities (ecosystems) of diverse species, the role of multi-level selection is discussed within this context and a proposal is advanced that aging represents an adaptive phenotype. RESULTS: Single cell organisms evolved an aging phenotype in which the primary feature was replicative arrest prior to cell death. The evolution of multicellularity represented the emergence of a new level of biological organization. Multicellularity required cell-cell cooperation as well as a division of labor. In simple multicellular organisms aging was rooted in an age-related decline in stem cell function (renewal and differentiation). In complex multicellular organisms cellular aging/ death programs (senescence, autophagy, apoptosis) were used as a form of cell "altruistic" suicide carried out for the benefit of the whole organism (morphogenesis, tissue repair and maintenance). Organisms do not live in isolation. Species occupy ecological niches and communities of diverse species comprise an ecosystem. Ecosystems are highly regulated and structured biological organizations. The effective functioning and productivity of an ecosystem is determined by its biological diversity and relative species densities. Multilevel selection acts to balance optimal functioning of both the whole ecosystem and its compositional species/organisms. CONCLUSIONS: Organismal aging and death programs are adaptive; these programs provide a mechanism for regulating species population densities within the constraints imposed by the ecosystem organization. A unique feature of humans has been the development of a second inheritance system, culture. Through cultural practices, humans have expanded our ecological niche to be global in size. Our technology enriched urban ecosystem is very different from natural ecosystems. Our future evolution, including aging and lifespan, will be determined by our unique urban ecosystem through geneculture co-evolution.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.383
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2016
Admission routes1
Has abstractyes

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