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Record W4406432307 · doi:10.1038/s44319-025-00368-x

Male sex determination maintains proteostasis and extends lifespan of daf-18/PTEN deficient C. elegans

2025· article· en· W4406432307 on OpenAlexfundno aff
Zhi Qu, Lu Zhang, Xue Yin, Fangzhou Dai, Wei Huang, Yutong Zhang, Dongyang Ran, Shanqing Zheng

Bibliographic record

VenueEMBO Reports · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersHenan UniversityQueen's University
KeywordsProteostasisBiologyCaenorhabditis elegansPTENGeneticsCell biologyGeneApoptosis

Abstract

fetched live from OpenAlex

Although females typically have a survival advantage, those with PTEN functional abnormalities face a higher risk of developing tumors than males. However, the differences in how each sex responds to PTEN dysfunction have rarely been studied. We use Caenorhabditis elegans to investigate how male and hermaphrodite worms respond to dysfunction of the PTEN homolog daf-18. Our study reveals that male worms can counterbalance the negative effects of daf-18 deficiency, resulting in longer adult lifespan. The survival advantage depends on the loss of DAF-18 protein phosphatase activity, while its lipid phosphatase activity is dispensable. The deficiency in DAF-18 protein phosphatase activity leads to the failure of dephosphorylation of the endoplasmic reticulum membrane protein C18E9.2/SEC62, causing increased levels of unfolded and aggregated proteins in hermaphrodites. In contrast, males maintain proteostasis through a UNC-23/NEF-mediated protein ubiquitination and degradation process, providing them with a survival advantage. We find that sex determination is a key factor in regulating the differential expression of unc-23 between sexes in response to daf-18 loss. These findings highlight the unique role of the male sex determination pathway in regulating protein degradation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.599

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 head0.008
GPT teacher head0.258
Teacher spread0.249 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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