Resveratrol: a promising agent in promoting cardioprotection against coronary heart diseaseThis article is one of a selection of papers from the NATO Advanced Research Workshop on Translational Knowledge for Heart Health (published in part 2 of a 2-part Special Issue).
Bibliographic record
Abstract
The inverse association between alcohol intake and coronary heart disease has been consistently reported in cross-culture, case-control, and cohort studies. Over the past couple of decades, however, many studies have explained promising health benefits associated with wine consumption. Some studies suggest that red wine is more cardioprotective than white wine, possibly due to the increased content of flavanoid antioxidants found in red wine. Several experimental studies, including ours, support the evidence that these beneficial effects are due to resveratrol, the polyphenolic compound present in red wine. Many studies have provided evidence that resveratrol possesses antioxidant and antiapoptotic effects apart from activation of longevity proteins (such as SIRT-1). We have recently reported the angiogenic, antihypercholesterolemic, and antidiabetic effects of resveratrol and the mechanisms involved in reduced ventricular remodeling and increased cardiac functions. We have also shown different strategic target molecules involved in resveratrol-mediated cardioprotection. Therefore, this review discusses the potential effect of resveratrol and the mechanisms involved in resveratrol-mediated cardioprotection during myocardial infarction, hypercholesterolemia, and diabetes rendering its beneficial effects during health and disease.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".