Heart DHA turnover is faster in female compared to male ALA- and EPA-fed mice
Bibliographic record
Abstract
C-n-3 PUFA values modeled by one-phase exponential decay. Compared to males, females exhibited slower turnover of ALA (48%-61% slower) and DPAn-3 (26%-73% slower) from dietary ALA or EPA in the heart, PRAT, and RBCs, resulting from longer half-lives and/or lower DPAn-3 concentrations. Conversely, females showed 26%-28% faster heart DHA turnover from dietary ALA or EPA, despite similar half-lives between sexes. Notably, sex-specific differences in DHA turnover were present only in the heart, whereas DPAn-3 turnover varied across multiple tissues, suggesting a heart-specific mechanism that enhances DHA metabolism in females under low DHA intake. Further research is needed to investigate the physiological significance of these metabolic differences and their potential health implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".