Semaglutide Improves Myocardial Perfusion and Performance in a Large Animal Model of Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Coronary artery disease is the leading cause of death worldwide. It imposes an enormous symptomatic burden on patients, leaving many with residual disease despite optimal procedural therapy and up to one-thirds with debilitating angina amenable neither to procedures, nor to current pharmacological options. Semaglutide (SEM), a GLP-1 (glucagon-like peptide 1) agonist originally approved for management of diabetes, has garnered substantial attention for its capacity to attenuate cardiovascular risk. Although subgroup analyses in patients indicate promise, studies explicitly designed to isolate the impact of SEM on the sequelae of coronary artery disease, independently of comorbid diabetes or obesity, are lacking. METHODS: Yorkshire swine (n=17) underwent placement of an ameroid constrictor around the left circumflex coronary artery to induce coronary artery disease. Oral SEM was initiated postoperatively at 1.5 mg and scaled up in 2 weeks to 3 mg in treatment animals (n=8) for a total of 5 weeks, while control animals (n=9) received no drug. All then underwent myocardial harvest with acquisition of perfusion and functional data using microsphere injection and pressure-volume loop catheterization. Immunoblotting, immunohistochemistry, and immunofluorescence were performed on the most ischemic myocardial segments for mechanistic elucidation. RESULTS: SEM animals exhibited improved left ventricular ejection fraction, both at rest and during rapid myocardial pacing (both P <0.03), accompanied by increased perfusion to the most ischemic myocardial region at rest and during rapid pacing (both P <0.03); reduced perivascular and interstitial fibrosis (both P <0.03); and apoptosis ( P =0.008). These changes were associated with increased activation of the endothelial-protective AMPK (AMP-activated protein kinase) pathway ( P =0.005), coupled with downstream increases in eNOS (endothelial NO synthase; P =0.014). CONCLUSIONS: This study reveals the capacity of oral SEM to augment cardiac function in the chronically ischemic heart in a highly translational large animal model, likely through AMPK-mediated improvement in endothelial function and perfusion to the ischemic myocardium.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".