Therapeutic Potential of Quercetin to Alleviate Endothelial Dysfunction in Age-Related Cardiovascular Diseases
Bibliographic record
Abstract
The vascular endothelium occupies a catalog of functions that contribute to the homeostasis of the cardiovascular system. It is a physically active barrier between circulating blood and tissue, a regulator of the vascular tone, a biochemical processor and a modulator of coagulation, inflammation, and immunity. Given these essential roles, it comes to no surprise that endothelial dysfunction is prodromal to chronic age-related diseases of the heart and arteries, globally termed cardiovascular diseases (CVD). An example would be ischemic heart disease (IHD), which is the main cause of death from CVD. We have made phenomenal advances in treating CVD, but the aging endothelium, as it senesces, always seems to out-run the benefits of medical and surgical therapies. Remarkably, many epidemiological studies have detected a correlation between a flavonoid-rich diet and a lower incidence of mortality from CVD. Quercetin, a member of the flavonoid class, is a natural compound ubiquitously found in various food sources such as fruits, vegetables, seeds, nuts, and wine. It has been reported to have a wide range of health promoting effects and has gained significant attention over the years. A growing body of evidence suggests quercetin could lower the risk of IHD by mitigating endothelial dysfunction and its risk factors, such as hypertension, atherosclerosis, accumulation of senescent endothelial cells, and endothelial-mesenchymal transition (EndoMT). In this review, we will explore these pathophysiological cascades and their interrelation with endothelial dysfunction. We will then present the scientific evidence to quercetin's anti-atherosclerotic, anti-hypertensive, senolytic, and anti-EndoMT effects. Finally, we will discuss the prospect for its clinical use in alleviating myocardial ischemic injuries in IHD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".