Lowering Dietary Fat Changes Plasma Lipids and the Fatty Acid Composition in Young Adults
Bibliographic record
Abstract
The aim of this study was to investigate the effects of reducing the amount of dietary total fat on serum lipids and the plasma fatty acid composition in young adults. Sixteen male and 18 female subjects (aged 20~30 years) were given experimental meals including lunch and dinner for a 4-week period, but on weekends and holidays, no meals were provided. The experimental meals were designed to provide 2200 kcal/d for each male subject and 1800 kcal/d for each female subject, including 58%~68% of energy from carbohydrates, 10%~14% of energy from protein, and 20%~30% of energy from fat. During the dietary intervention period, the energy intake of dietary fat significantly decreased from 35.0% to 28.7% in males and from 37.9% to 32.3% in females. In female subjects, serum total cholesterol, LDL-cholesterol, and HDL-cholesterol significantly decreased in a 4-week period of diet. The experimental meal intervention was associated with a significantly higher 18:3 n-3 level as the percentage of total plasma fatty acids and with a significantly lower 20:4 level and 18: 2/18:1 ratio as the percentage of total plasma fatty acids in females. In male subjects, the 18:2 and total n-6 polyunsaturated fatty acid levels as percentages of total plasma fatty acids significantly decreased compared with corresponding values at week 0. Thus, the benefits of lowering dietary fat intake to 5%~7% of energy intake may favor changes in serum lipids in females and plasma fatty acid composition in both males and females.
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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) | 0.001 | 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".