Study of the impact of trans fatty acids from ruminants on blood lipids and other risk factors for cardiovascular disease
Bibliographic record
Abstract
While the intake of trans fatty acids from industrially hydrogenated oils (iTFA) is known to have deleterious effects on cardiovascular health, the effects of TFA from ruminants (rTFA) are unknown. The purpose of this study was to compare the effects of rTFA and iTFA on LDL‐C and other cardiovascular disease risk factors in human. In a double‐blind, randomized controlled crossover study, 38 healthy men were fed each of 4 experimental isoenergetic diets lasting 4 weeks each. The 4 diets were 1‐ high in rTFA (10.2 g/2500 kcal), 2‐ moderately high in rTFA (4.2 g/2500 kcal), 3‐ high in iTFA (10.2 g/2500 kcal) and 4‐ the control diet low in TFA from any sources (2.2 g/2500 kcal). LDL‐C levels were higher after the high rTFA diet than after the control (p=0.03) and the moderate rTFA diets (p=0.002). LDL‐C levels were also higher after the iTFA diet compared to the moderate rTFA diet (p=0.02). HDL‐C were lower after the high rTFA diet than after the moderate rTFA diet (p=0.02). All risk factors were comparable between the control and the moderate rTFA diets. While a very high dietary intake of TFA from ruminants may have a deleterious impact on cholesterol homeostasis, consumption of rTFA corresponding to the upper limit of current human consumption has neutral effects on plasma lipids and other cardiovascular risk factors. Financial support: Dairy Farmers of Canada, Novalait, 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".