Impact of hydrogenated fat on high density lipoprotein subfractions and metabolism
Bibliographic record
Abstract
Relative to saturated fatty acids, trans-fatty acids/hydrogenated fat-enriched diets have been reported to increase low density lipoprotein (LDL) cholesterol levels and either decrease or have no effect on high density lipoprotein (HDL) cholesterol levels. To better understand the effect of trans-fatty acids/hydrogenated fat on HDL cholesterol levels and metabolism, 36 subjects (female, n = 18; male, n = 18) were provided with each of three diets containing, as the major sources of fat, vegetable oil-based semiliquid margarine, traditional stick margarine, or butter for 35-day periods. LDL cholesterol levels were 155 +/- 27, 168 +/- 30, and 177 +/- 32 mg/dl after subjects followed the semiliquid margarine, stick margarine, and butter-enriched diets, respectively. HDL cholesterol levels were 43 +/- 10, 42 +/- 9, and 45 +/- 10 mg/dl, respectively. Dietary response in apolipoprotein (apo) A-I levels was similar to that in HDL cholesterol levels. HDL(2) cholesterol levels were 12 +/- 7, 11 +/- 6, and 14 +/- 7 mg/dl, respectively. There was virtually no effect of dietary fat on HDL3 cholesterol levels. The dietary perturbations had a larger effect on particles containing apoA-I only (Lp A-I) than apoA-I and A-II (Lp A-I/A-II). Cholesterol ester transfer protein (CETP) activity was 13.28 +/- 5.76, 15.74 +/- 5.41, and 14.35 +/- 4.77 mmol x h(-1) x ml(-1), respectively. Differences in CETP, phospholipid transfer protein activity, or the fractional esterification rate of cholesterol in HDL did not account for the differences observed in HDL cholesterol levels. These data suggest that the saturated fatty acid component, rather than the trans- or polyunsaturated fatty acid component, of the diets was the putative factor in modulating HDL cholesterol response.
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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) | 0.002 | 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".