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Record W4405940693 · doi:10.1073/pnas.2412609121

X*Y females exhibit steeper reproductive senescence in the African pygmy mouse

2024· article· en· W4405940693 on OpenAlexaff
Jean‐François Lemaître, Yann Voituron, Léa Herpe, Frédéric Veyrunes

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité de Moncton
FundersAgence Nationale de la Recherche
KeywordsHeterogametic sexSenescenceBiologyGeneticsPhenotypeReproductionEvolutionary biologyZoologyChromosomeGene

Abstract

fetched live from OpenAlex

A wave of studies has recently emphasized the influence of sex chromosomes on both lifespan and actuarial senescence patterns across vertebrates and invertebrates. Basically, the heterogametic sex (XY males in XX/XY systems or ZW females in ZW/ZZ systems) typically displays a lower lifespan and a steeper rate of actuarial senescence than the homogametic sex. However, whether these effects extend to the senescence patterns of other phenotypic traits or physiological functions is yet to be determined. Here, we investigated whether sex chromosomes modulate reproductive senescence using females from the African pygmy mouse ( Mus minutoides ). This biological model exhibits an odd sex determining system with a third, feminizing sex chromosome, X*, resulting in three distinct female genotypes (XX, X*X, or X*Y) that coexist in natural populations. We found that the rate of senescence in litter size at birth is much more pronounced in heterogametic X*Y females than in homogametic XX or X*X females that may support the unguarded X or toxic Y hypotheses and can be directly linked to the complex and unique X*Y phenotype. A decrease in neonatal survival with mother’s age has also been found, but this decline is not different between the three female genotypes.

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 score0.002
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.301
Teacher spread0.225 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of Sciences→Same topicAnimal Behavior and Reproduction→French-language works237,207→