An Improvement of Cardiovascular Risk Factors by Omega-3 Polyunsaturated Fatty Acids
Bibliographic record
Abstract
An epidemiological survey in the Northwest Greenland reported that the Greenlanders have a lower frequency of acute myocardial infarction and diabetes mellitus. The very low incidence of ischemic heart disease in the Greenlanders was explained by consumption of a diet rich in omega-3 polyunsaturated fatty acids (PUFAs). Possible anti-atherothrombotic effects of omega-3 PUFA include an improvement of lipid metabolism such as a reduction of triglyceride and an increase of high-density lipoprotein-cholesterol (HDL-C), and glucose metabolism, anti-platelet activity, anti-inflammatory effects, an improvement of endothelial function and stabilization of atherosclerotic plaque. The present study reviews an improvement of cardiovascular risk factors such as dyslipidemia and diabetes due to consumption of omega-3 PUFA. A sufficient number of studies suggest that omega-3 PUFA supplementation reduces serum triglyceride and increases HDL-cholesterol. The mechanisms for omega-3 PUFA-mediated improvements of lipid metabolism have been partially elucidated. The studies using experimental animals, part of trials in humans, have shown the beneficial effects of omega-3 PUFA on glucose metabolism and insulin sensitivity. The meta-analysis showed that omega-3 PUFA might prevent development of diabetes in part of population. Further studies should be performed to elucidate the association of omega-3 PUFA supplementation with diabetes, in the future.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".