Adding carbohydrate to a high-fat meal blunts postprandial lipemia in women and reduces meal-derived fatty acids in systemic circulation
Bibliographic record
Abstract
The lipemic response to a meal is an important independent risk factor for the development of cardiovascular disease. The purpose of this study was to determine the effect of adding carbohydrate (CHO) to a fat meal on the bioavailability of ingested fat in different blood lipid fractions in men and women. On two separate occasions, 18 healthy adults (9 women, 9 men) ate either a high-fat meal (0.7 grams fat per kilogram) (FAT), or the same meal with added CHO (1 gram CHO per kilogram) (FAT+CHO) in the morning after a 12 h fast. Both meals were supplemented with [13C]-palmitate (25 mg.kg(-1)). Plasma concentrations of triglyceride (TG), fatty acids, insulin, and glucose were measured in blood samples taken hourly from 0 to 8 h after the meal. In addition, we measured TG concentrations in chylomicron (CHYLO-TG) and in very-low-density lipoprotein (VLDL-TG) fractions. The addition of CHO to the fat meal increased plasma glucose and insulin concentrations identically in men and women. In contrast, adding CHO to the fat meal reduced the plasma TG concentration in the 5 h after the meal in women (average 5 h [TG]: 1.27 +/- 0.11 and 1.01 +/- 0.09 mmol.L(-1); p <0.05), but not in men (1.25 +/- 0.23 and 1.24 +/- 0.20 mmol.L(-1)). Despite differences in the lipemic response to the meals between men and women, we found that adding carbohydrate to a fat meal decreased the bioavailability of meal-derived [13C]-palmitate in the systemic fatty acid pool, and decreased the incorporation of [13C]-palmitate into VLDL-TG in both men and women. In summary, adding CHO to a fat meal markedly blunted the plasma TG response in women, but not in men, which may augment the atherogenic potential after each meal in men.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".