Effects of Dietary Fat Intake on HDL Metabolism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High-density lipoprotein (HDL) is a lipoprotein which has anti-atherogenic property by reversing cholesterol transport from the peripheral tissues to liver. Low HDL-cholesterol (HDL-C) as well as high low-density lipoprotein-cholesterol (LDL-C) is associated with the development of coronary heart diseases (CHD). Various epidemiological studies have suggested that the development of CHD increase in individuals with less than 40 mg/dL of HDL-C. In spite of accumulation of evidences suggesting a significant association between low HDL-C and CHD, effects of dietary factors on HDL metabolism remained largely unknown. We reviewed published articles about effects of dietary fat intake on HDL metabolism. The substitution of fatty acids (FA) for carbohydrates is beneficially associated with HDL metabolism. Monounsaturated FA intake may not affect HDL-C. Trans-FA is significantly associated with reduction of HDL-C, and is also adversely related with total cholesterol/HDL-C. Fish oils consumption, especially docosahexaenoic acid consumption, may be favorably associated with HDL metabolism. Although plant sterols and stanols may not affect HDL-C, policosanol intake is associated with a clinically significant decrease in the LDL/HDL ratio.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.012 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it