Resveratrol Improves Myocardial Perfusion in a Swine Model of Hypercholesterolemia and Chronic Myocardial Ischemia
Bibliographic record
Abstract
BACKGROUND: Resveratrol may provide protection against coronary artery disease. We hypothesized that supplemental resveratrol will improve cardiac perfusion in the ischemic territory of swine with hypercholesterolemia and chronic myocardial ischemia. METHODS AND RESULTS: Yorkshire swine were fed either a normal diet (control, n=7), a hypercholesterolemic diet (HCC, n=7), or a hypercholesterolemic diet with supplemental resveratrol (100 mg/kg/d orally, HCRV, n=7). Four weeks later, an ameroid constrictor was placed on the left circumflex artery. Animals underwent cardiac MRI and coronary angiography 7 weeks later before euthanasia and tissue harvest. Total cholesterol was lowered about 30% in HCRV animals (P<0.001). Regional wall motion analysis demonstrated a significant decrease in inferolateral function from baseline to 7 weeks in HCC swine (P=0.04). There was no significant change in regional function in HCRV swine from baseline to 7 weeks (P=0.32). Tissue blood flow during stress was 2.8-fold greater in HCRV swine when compared with HCC swine (P=0.04). Endothelium-dependent microvascular relaxation response to Substance P was diminished in HCC swine, which was rescued by resveratrol treatment (P=0.004). Capillary density (PECAM-1 staining) demonstrated fewer capillaries in both HCC and HCRV swine versus control swine (P=0.02). Immunoblot analysis demonstrated significantly greater expression in HCRV versus HCC swine of the following markers of angiogenesis: VEGF (P=0.002), peNOS (ser1177) (P=0.04), NFkB (P=0.004), and pAkt (thr308) (P=0.001). CONCLUSIONS: Supplemental resveratrol attenuates regional wall motion abnormalities, improves myocardial perfusion in the collateral dependent region, preserves endothelium-dependent coronary vessel function, and upregulates markers of angiogenesis associated with the VEGF signaling pathway.
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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".