Impact of natural and industrial trans fatty acids consumption on HDL metabolism
Bibliographic record
Abstract
Unlike dietary industrial trans fatty acids (iTFA), which are known to increase the risk of cardiovascular disease (CVD) through adverse modifications of blood lipids, the impact of dietary trans fatty acids from ruminants (rTFA) remains unknown. The purpose of the present study was to compare the effects of iTFA and rTFA on in vivo HDL metabolism. According to a double‐blind, randomized crossover controlled study design, 9 healthy men were fed each of 3 experimental 5‐week isoenergetic diets: 1‐ high in iTFA (10.2 g/2500 kcal), 2‐ high in rTFA (10.2 g/2500 kcal) and 3‐ a control diet low in TFA (2.2 g/2500 kcal). Apolipoprotein (apo) A‐I kinetic was investigated after each diet after administration of D3‐Leucine in the fasted state. The fractional catabolic rate (FCR) and production rate (PR) of apo A‐I were significantly higher after the diet rich in iTFA than after the control diet (+12.9% and +12.6% respectively, p=0.03). No significant change in apo A‐I FCR and PR were observed after the diet rich in rTFA. When analysing all 3 diets, the apo A‐I FCR was a strong correlate of on‐diet plasma HDL‐C concentrations (r=−0.50, p=0.008). This kinetic study of apo A‐I suggested that a high consumption of rTFA may not significantly modify HDL in vivo kinetics. Supported by grants from the Dairy farmers of Canada, Novalait and the Canada Research Chair in nutrition and Cardiovascular Health.
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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) | 0.001 | 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) | 0.001 | 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".