Conversion ratios of<i>n</i>-3 fatty acids between plasma and erythrocytes: a systematic review and meta-regression
Bibliographic record
Abstract
As biomarkers of dietary intake or disease risk factor, n-3 fatty acid (FA) can be measured in plasma phospholipids (PL), total lipids (TL) or erythrocytes. However, the numeric relationships between n-3 FA in these lipid pools are not clear. Our goal was to derive conversion ratios for plasma and erythrocyte n-3 FA. Potential studies were identified through systematic literature search in PubMed, Embase and the Cochrane Library of Systematic reviews (1950 to October 2014). In all, fifty-six studies reporting n-3 in healthy individuals were included, of which thirty-four articles reported plasma PL and erythrocytes, and twenty-two reported plasma TL and erythrocytes. Meta-regressions were performed to quantify the ratio between plasma and erythrocyte n-3 FA weight percentages, controlling for covariates including age, sex and study design. The conversion ratios from plasma PL to erythrocytes for EPA, DHA, DPA and total n-3 PUFA are 0·75, 1·16, 2·32 and 1·22; the corresponding conversion ratios from plasma TL to erythrocytes are 1·00, 2·10, 3·85 and 2·08, respectively. The conversion ratios were validated using reported values from the literature and measured data from fifty individuals. The relative error of the predicted results were within 10 % of the mean reported values except for EPA, and the individual measured data except for DPA, in plasma TL. The conversion ratios between plasma PL and erythrocytes were more stable compared with plasma TL. Such conversion ratios will be useful for nutritionists or public health professionals to assess FA profiles of different populations using data collected with different methodologies.
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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 | 0.027 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.058 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".