Comparison of the impact of <i>trans</i> fatty acids from ruminant and industrial sources on surrogate markers of cholesterol homeostasis in healthy men
Bibliographic record
Abstract
SCOPE: Mechanisms by which trans fatty acids (TFA) from industrial (iTFA) and ruminant (rTFA) sources alter cholesterol homeostasis are virtually unknown. We compared the impact of dietary iTFA and rTFA on surrogate markers of cholesterol absorption (β-sitosterol and campesterol) and synthesis (lathosterol) in healthy men. METHODS AND RESULTS: In a randomized, controlled double-blind crossover study, 38 healthy men consumed three experimental isoenergetic diets for 4 wk each. The three diets were (i) high in iTFA (10.2 g/2500 kcal), (ii) high in rTFA (10.2 g/2500 kcal) and (iii) control diet low in TFA from any source (2.2 g/2500 kcal). The sum of plasma β-sitosterol and campesterol concentrations was significantly reduced after the iTFA diet compared with the control diet (-12%, p=0.050). The reduction in combined β-sitosterol and campesterol levels was larger in magnitude after the rTFA diet (-29% versus the control diet and -20% versus the iTFA diet, p<0.0001). The TFA-rich diets had no impact on plasma lathosterol concentrations. CONCLUSIONS: Very high intakes of rTFA and iTFA decrease cholesterol absorption but have no impact on cholesterol synthesis. Consumption of rTFA reduces cholesterol absorption to a greater extent than iTFA, but this difference does not ultimately affect plasma cholesterol concentrations.
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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 | 0.001 |
| 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".