Effects of Carbohydrate and Dietary Fiber Intake, Glycemic Index and Glycemic Load on HDL Metabolism in Asian Populations
Bibliographic record
Abstract
High-density lipoprotein (HDL) is a lipoprotein which has anti-atherogenic property by reverse cholesterol transport from the peripheral tissues to liver. Low HDL-cholesterol (HDL-C) levels are associated with the development of coronary artery diseases (CADs). Various epidemiological studies have suggested that the development of CAD increase in individuals with less than 40 mg/dL of HDL-C. In spite of accumulation of evidences which suggest a significant association between low HDL-C and cardiovascular diseases, effects of dietary factors on HDL metabolism remained largely unknown. There may be interracial differences in effects of dietary factors on HDL metabolism. Here we reviewed published articles about effects of carbohydrate and dietary fiber intake, glycemic index (GI) and glycemic load (GL), on HDL-C metabolism, regarding meta-analyses and clinical studies performed in Asian population as important articles. Low carbohydrate intake, GI and GL may be beneficially associated with HDL metabolism. Dietary fiber intake may be favorably associated with HDL metabolism in Asian populations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".