Elevated Production of Docosahexaenoic Acid in Females: Potential Molecular Mechanisms
Bibliographic record
Abstract
Observational evidence suggests that in populations consuming low levels of n-3 highly unsaturated fatty acids, women have higher blood levels of docosahexaenoic acid (DHA; 22:3n-6) as compared with men. Increased conversion of alpha-linolenic acid (ALA; 18:3n-3) to DHA by females has been confirmed in fatty acid stable isotope studies. This difference in conversion appears to be associated with estrogen and some evidence indicates that the expression of enzymes involved in synthesis of DHA from ALA, including desaturases and elongases, is elevated in females. An estrogen-associated effect may be mediated by peroxisome proliferator activated receptor-alpha (PPARalpha), as activation of this nuclear receptor increases the expression of these enzymes. However, because estrogens are weak ligands for PPARalpha, estrogen-mediated increases in PPARalpha activity likely occur through an indirect mechanism involving membrane-bound estrogen receptors and estrogen-sensitive G-proteins. The protein kinases activated by these receptors phosphorylate and increase the activity of PPARalpha, as well as phospholipase A(2) and cyclooxygenase 2 that increase the intracellular concentration of PPARalpha ligands. This review will outline current knowledge regarding elevated DHA production in females, as well as highlight interactions between estrogen signaling and PPARalpha activity that may mediate this effect.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".