Selective partitioning of dietary fatty acids into the VLDL TG pool in the early postprandial period
Bibliographic record
Abstract
Circulating triacylglycerol (TG) arises mainly from dietary fat. However, little is known about the entry of dietary fat into the major TG pool, very low-density lipoprotein (VLDL) TG. We used a novel method to study the specific incorporation of dietary fatty acids into postprandial VLDL TG in humans. Eight healthy volunteers (age 25.4 +/- 2.2 years, body mass index 22.1 +/- 2.3 kg/m2) were fed a mixed meal containing 30 g fish oil and 600 mg [1-13C]palmitic acid. Chylomicrons and VLDL were separated using immunoaffinity against apolipoprotein B-100. The fatty acid composition of lipoproteins was analyzed by gas chromatography/mass spectrometry. [1-13C]palmitic acid started to appear in VLDL TG 3 h after meal intake, and a similar delay was observed for eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Approximately 20% of dietary fatty acids entered the VLDL TG pool 6 h after meal intake. DHA was clearly overincorporated into this pool compared with [1-13C]palmitic acid and EPA. This seemed to depend on a marked elevation of this fatty acid in the nonesterified fatty acid pool. In summary, the contribution of dietary fatty acids to early postprandial VLDL TG is substantial. The role of DHA in VLDL TG production will require further investigation.
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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".