Quercetin Reduces Vascular Senescence and Inflammation in Symptomatic Male but Not Female Coronary Artery Disease Patients
Bibliographic record
Abstract
Recent studies suggest that vascular senescence and its associated inflammation fuel the inflammaging to favor atherogenesis; whether these pathways can be therapeutically targeted in coronary artery disease (CAD) patients remains unknown. In a randomized, double-blind trial, 97 patients (78 men) undergoing coronary artery bypass graft surgery were treated with either quercetin (500 mg twice daily, 47 patients) or placebo (50 patients) for two days pre-surgery through hospital discharge. Primary outcomes were reduced inflammation and improved endothelial function ex vivo. Exploratory analyses included plasma proteomics and single-nuclei RNA sequencing of internal thoracic artery (ITA) samples. Quercetin treatment showed a trend toward reduced C-reactive protein at discharge (p = 0.073) and differentially modulated circulating inflammatory protein expression between men and women, with a pro-inflammatory effect of quercetin in females. Endothelial acetylcholine-induced relaxation improved significantly with quercetin (p = 0.049), with effects in men (p = 0.043) but not in women (p = 0.852). ITA transcriptomics revealed the overexpression of senescence and inflammaging pathways in male vascular cells, which quercetin reversed. In female cells, quercetin had minimal endothelial benefit and increased inflammaging in fibroblasts. In male cells, a candidate target of quercetin involves interactions between the receptor PLAUR and its ligands PLAU and SERPINE1. Post-operative atrial fibrillation incidence was significantly lower with quercetin, representing 4% of the patients compared to 18% in the placebo group (p = 0.033). In conclusion, short-term quercetin treatment effectively targeted vascular senescence in male CAD patients, improving inflammatory and functional outcomes. However, these benefits were not observed in female patients. Trial Registration: https://clinicaltrials.gov, NCT04907253.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".