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Record W4416183021 · doi:10.1038/s41514-025-00278-1

Age, caste, and social context shape ovarian morphology and transcriptomic profiles in red harvester ants

2025· article· en· W4416183021 on OpenAlexfundno aff
María Fernanda Vergara-Martínez, Dennet Guerra-Sandoval, Berenice Otero-Díaz, Ernesto Samacá-Sáenz, Pedro Medina-Granados, Rafael Reynoso-Robles, Rosa María Vigueras‐Villaseñor, Angélica González-Maciel, Ingrid Fetter-Pruneda

Bibliographic record

Venuenpj Aging · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsnot available
FundersBuck Institute for Research on AgingEcho Foundation
KeywordsEusocialityTranscriptomeContext (archaeology)Bombus terrestrisOvaryDivision of labourReproductive successReproduction

Abstract

fetched live from OpenAlex

The reproductive division of labor defines eusocial insects like ants, where queens reproduce and workers remain sterile. Yet, some workers retain rudimentary ovaries, raising questions about latent reproductive potential. We examined morphological and transcriptomic differences in Pogonomyrmex barbatus queen and worker ovaries at different maturation stages and social contexts. Queens had large, yolk-rich oocytes, while worker ovaries showed regression. Callow workers (<5 days) had more developed ovaries than mature ones (>20 days), suggesting age-related regression, even without reproduction. Queenless workers exhibited greater ovarian regression than queenright ones, indicating factors beyond queen presence may limit reproductive activation. We found ~2000 caste-specific differentially expressed genes, including those involved in metabolism, hormonal signaling, and epigenetic regulation. Queenless workers upregulated a fertility-linked gene and downregulated lipid metabolism genes. Our results show that age and social environment influence ovarian state, highlighting complex regulation of reproductive suppression and offering insight into reproductive senescence in eusocial systems.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.380

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 science0.0000.000
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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.

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
Published2025
Admission routes1
Has abstractyes

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