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Record W2953273419 · doi:10.1101/091199

Senescence gives insights into the morphogenetic evolution of anamniotes

2016· preprint· en· W2953273419 on OpenAlexafffund
Éric Villiard, Jean-François Denis, Faranak Sadat Hashemi, Sebastian Igelmann, Gerardo Ferbeyre, Stéphane Roy

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2016
Typepreprint
Languageen
FieldEnvironmental Science
TopicFish biology, ecology, and behavior
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéRéseau de Recherche en Santé Buccodentaire et Osseuse
KeywordsZebrafishBiologyPronephrosSenescenceYolk sacCell biologyMorphogenesisVertebrateEmbryonic stem cellAmphibianEmbryogenesisDevelopmental biologyAnatomyEmbryoGeneticsEcologyGene

Abstract

fetched live from OpenAlex

Summary statement We report the presence of senescent cells in several transient structures in developing amphibian and teleost fish, suggesting novel mechanisms of morphogenesis that appeared early in vertebrate evolution. Abstract Senescence represents a mechanism to avoid undesired cell proliferation that plays a role in tumor suppression, wound healing and embryonic development. In order to gain insight on the evolution of senescence, we looked at its presence in developing axolotls (urodele amphibians) and in zebrafish (teleost fish), which are both anamniotes. Our data indicate that cellular senescence is present in various developing structures in axolotls (pronephros, olfactory nerve fascicles, lateral organs, gums) and in zebrafish (epithelium of the yolk sac and in the lower part of the gut). Senescence was particularly associated with transient structures (pronephros in axolotls & yolk sac in zebrafish) suggesting that it plays a role in the elimination of these tissues. Our data supports the notion that cellular senescence evolved early in vertebrate evolution to influence embryonic development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2016
Admission routes2
Has abstractyes

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