Fish oil regulates blood fatty acid composition and oxylipin levels in healthy humans: A comparison of young and older men
Bibliographic record
Abstract
SCOPE: Increased consumption of fish oils rich in eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) is associated with improved cardiometabolic health and inflammatory status; however, age-related responses remain poorly described. METHODS AND RESULTS: In a placebo-controlled study, healthy young and older men consumed five fish oil capsules daily, providing 2.0 g/d EPA and 1.0g/d DHA, for three months. Both young and older men experienced a ∼30% reduction in blood triglycerides with fish oil supplementation. A significant group × time interaction was observed for DHA, with young men experiencing a ∼twofold increase in DHA in serum and RBCs, while older men showed negligible increases. Other fatty acids were differentially regulated between young and older men, most notably osbond acid and several saturates. Small changes were observed in serum oxylipins, with both groups of men responding similarly: 5-HETE was reduced, while PGF2α and 17-HDoHE were increased. Changes in oxylipins occurred independent of changes in whole blood expression of key genes regulating oxylipin production. CONCLUSION: Our study suggests that both young and older men experience the triglyceride-lowering benefits associated with fish oil supplements, but show differential responses in blood fatty acids. Additionally, fish oil promotes an improved oxylipin profile in both groups of men.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".