Early nebivolol treatment is beneficial in myocardial infarction in rats partly through β3‐adrenoceptor remodelling
Bibliographic record
Abstract
Abstract It remains unknown whether β‐blockers are useful and safe in acute myocardial infarction (MI). Owing to its pharmacological profile and vasodilating action, nebivolol (N) is useful in MI. The aim of the present study was to assess in rat whether early nebivolol treatment could be beneficial in MI. It remains unknown whether β‐blockers are useful and safe in acute MI. On day (D) 0, male Sprague‐Dawley rats underwent left coronary artery ligation (MI) or simple thoracotomy (SHAM). On D1 and D2, the rats were treated with either nebivolol (5 mg.kg−1.day−1, MI‐N and Sham‐N) or vehicle (V, MI‐V and Sham‐V). On D3, heart rate, left ventricle (LV) intrinsic contractility (PESmid) and arterial elastance were measured. Cardiac and aortic β‐Adrenoceptor (AR) subtype mRNA were quantified using real time quantitative RT‐qPCR. Catecholamine response was assessed on isolated heart and aortic rings with isoproterenol. PESmid was decreased in MI without worsening the decrease nebivolol. In LV, β1‐ and β3‐AR mRNA were respectively decreased and increased in all MI. β3‐AR mRNA increase was partly limited by nebivolol. Ex vivo, basal contractility was less decreased in MI‐N than in MI‐V. Isoproterenol response was only altered in MI‐V. In MI aorta, Nebi prevented β2‐ and β3‐AR mRNA increases. In addition, Acetylcholine‐induced relaxation was lowered in MI‐V but preserved with nebivolol. We demonstrated an early modulation of cardiovascular β3‐AR transcription early MI. Despite its putative negative inotropic properties, nebivolol did not worsen cardiac function in basal conditions and preserved LV catecholamine response.
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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 | 0.000 |
| 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 | 0.002 |
| 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".