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Record W2156008341 · doi:10.1371/journal.pgen.1004752

Gene Pathways That Delay Caenorhabditis elegans Reproductive Senescence

2014· article· en· W2156008341 on OpenAlexfundno aff
Meng C. Wang, Holly D. Oakley, Christopher E. Carr, Jessica N. Sowa, Gary Ruvkun

Bibliographic record

VenuePLoS Genetics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersNational Institute on AgingSimon Fraser UniversityEllison Medical FoundationBurroughs Wellcome Fund
KeywordsBiologySenescenceLongevityCaenorhabditis elegansGeneticsGeneRNA interferenceSomatic cellKlothoCell biologyRNA

Abstract

fetched live from OpenAlex

Reproductive senescence is a hallmark of aging. The molecular mechanisms regulating reproductive senescence and its association with the aging of somatic cells remain poorly understood. From a full genome RNA interference (RNAi) screen, we identified 32 Caenorhabditis elegans gene inactivations that delay reproductive senescence and extend reproductive lifespan. We found that many of these gene inactivations interact with insulin/IGF-1 and/or TGF-β endocrine signaling pathways to regulate reproductive senescence, except nhx-2 and sgk-1 that modulate sodium reabsorption. Of these 32 gene inactivations, we also found that 19 increase reproductive lifespan through their effects on oocyte activities, 8 of them coordinate oocyte and sperm functions to extend reproductive lifespan, and 5 of them can induce sperm humoral response to promote reproductive longevity. Furthermore, we examined the effects of these reproductive aging regulators on somatic aging. We found that 5 of these gene inactivations prolong organismal lifespan, and 20 of them increase healthy life expectancy of an organism without altering total life span. These studies provide a systemic view on the genetic regulation of reproductive senescence and its intersection with organism longevity. The majority of these newly identified genes are conserved, and may provide new insights into age-associated reproductive senescence during human aging.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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 designBench or experimental
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

Citations52
Published2014
Admission routes1
Has abstractyes

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