MétaCan
Menu
Back to cohort
Record W4393005305 · doi:10.3390/nu16060894

Methionine Supplementation Alleviates the Germ Cell Apoptosis Increased by Maternal Caffeine Intake in a C. elegans Model

2024· article· en· W4393005305 on OpenAlexfundno aff
Hyemin Min, Juhae Kim, Mi-Jin Lee, Sangwon Kang, Yhong‐Hee Shim

Bibliographic record

VenueNutrients · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersInstitute of GeneticsNational Institutes of HealthMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsMethionineCaffeineInternal medicineEndocrinologyApoptosisYolkBiologyVitellogenesisMedicineOocyteBiochemistryCell biologyFood scienceEmbryoAmino acid

Abstract

fetched live from OpenAlex

Caffeine (1,3,7-trimethylxanthine) is a widely consumed bioactive substance worldwide. Our recent study showed that a reduction in both reproduction and yolk protein production (vitellogenesis) caused by caffeine intake were improved by vitamin B12 supplementation, which is an essential co-factor in methionine metabolism. In the current study, we investigated the role of methionine in the reproduction of caffeine-ingested animals (CIAs). We assessed the effect of methionine metabolism on CIAs and found that caffeine intake decreased both methionine levels and essential enzymes related to the methionine cycle. Furthermore, we found that the caffeine-induced impairment of methionine metabolism decreased vitellogenesis and increased germ cell apoptosis in an LIN-35/RB-dependent manner. Interestingly, the increased germ cell apoptosis was restored to normal levels by methionine supplementation in CIAs. These results indicate that methionine supplementation plays a beneficial role in germ cell health and offspring development by regulating vitellogenesis.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueNutrientsSame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207