The Percentage of n‐3 Highly Unsaturated Fatty Acids in Total HUFA as a Biomarker for Omega‐3 Fatty Acid Status in Tissues
Bibliographic record
Abstract
A blood biomarker of omega-3 fatty acid intake and tissue status could serve as a modifiable risk factor for cardiovascular disease. The percentage of omega-3 highly unsaturated fatty acid (HUFA > or = 20 carbons and > or =3 double bonds) in the total HUFA pool (the n-3 HUFA score) was examined as a potential blood biomarker of omega-3 fatty acids in tissues. The fatty acid composition of total lipid extracts (TLE) and phospholipid (PL) fractions were determined for plasma and erythrocytes samples of human subjects (n = 20) and the n-3 HUFA score and the sum of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were compared. Omega-3 fatty acids in blood and tissues of rats (n = 31) and pigs (n = 48) were also determined and the associations were compared. The n-3 HUFA score is more consistent across plasma and erythrocytes, with strong correlations between TLE and PL in plasma (r = 0.93) and erythrocytes (r = 0.94). The n-3 HUFA score was less variable and blood levels correlated strongly with various animal tissues. The n-3 HUFA score is a useful blood biomarker that does not require the isolation of the PL class thereby supporting high throughput analyses. The strength of association between the n-3 HUFA score and disease risk needs to be examined.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".