Therapeutic potential of resveratrol in heart failure
Bibliographic record
Abstract
Despite existing therapies, patients with heart failure have a very poor quality of life and a high 1-year mortality rate. Given the impact of this syndrome on health outcomes, research is being directed toward identifying novel strategies to treat heart failure symptoms as well as to prolong survival. One molecule that has been tested in animal models for this purpose is resveratrol. Resveratrol is a naturally occurring polyphenol found in several plants, and administration of resveratrol has been shown to prevent and/or slow the progression of heart failure in animal models of heart failure induced by myocardial infarction, pressure overload, myocarditis, and chemotherapy-induced cardiotoxicity. In addition, some animal studies have shown that resveratrol improves cardiac function and survival when administered as a treatment for established heart failure. Furthermore, as heart failure induces alterations in skeletal muscle and vasculature that also contribute to certain heart failure symptoms, such as fatigue and exercise intolerance, it has also been shown that resveratrol acts on these peripheral tissues to improve skeletal muscle and endothelial/vascular function. Therefore, if these animal studies translate to humans, resveratrol may prove to be a novel therapy for the treatment of heart failure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".