Decreasing the dietary n‐6/n‐3 fatty acid ratio uniquely increases eicosapentaenic acid in heart membrane phospholipids with no effect on GLUT 4 expression in piglets
Bibliographic record
Abstract
The omega 3 fatty acids (FA), alpha linolenic acid (ALA, 18:3n‐3), eicosapentaenoic acid (EPA, 20:5n‐3) and docosahexaenoic acid (DHA, 22:6n‐3) are associated with decreased cardiovascular (CVD) and inflammatory disease. The omega 6 linoleic acid (LA, 18:2n‐6) has favorable effects on CVD through effects on plasma lipids. However, high intakes of LA may inhibit ALA metabolism to EPA and DHA, resulting in decreased tissue n‐3 FA and increased arachidonic acid (ARA, 20:4n‐6) to EPA ratios. N‐6 and n‐3 FA also regulate expression of genes for proteins of FA and glucose metabolism, and in skeletal muscle n‐3 FA increase GLUT 4 expression, thus favoring glucose oxidation. The effect of dietary LA/ALA ratio on heart phospholipid (PL) FA and GLUT 4 expression is not known. We determined the effect of dietary n‐6 and n‐3 FA on heart membrane phospholipid FA and GLUT 4 expression. Piglets were fed (%energy) 1.5% LA+0.06% ALA, 1.5% LA+1.2% ALA, 9% LA+1.2% ALA, or 9% LA+1.2% ALA with 0.6% ARA+0.8% DHA for 30 days. Membrane PL and FA were determined by HPLC and GLC. GLUT 4 membrane and cytosol expression and distribution was determined by Western blot. Piglets fed 1.5%LA+1.2%ALA had higher EPA and lower ARA and ARA/EPA in all heart PL compared to the other diets, demonstrating the LA/ALA ratio, not ALA intake determines EPA incorporation. Regardless of the difference in membrane FA, we found no difference in GLUT 4 expression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".