Cannabinoid Receptor Agonist Inhibits Atrial Electrical Remodeling in a Tachypaced Ex Vivo Rat Model
Bibliographic record
Abstract
Introduction: Atrial fibrillation (AF) leads to rate-dependent atrial changes collectively defined as atrial remodelling (AR). Shortening of the atrial effective refractory period (AERP) and decreased conduction velocity are among the hallmarks of AR. Pharmacological strategies to inhibit AR, thereby reducing the self-perpetual nature of AF, are of great clinical value. Cannabinoid receptor (CBR) ligands may exert cardioprotective effects; CB13, a dual CBR agonist with limited brain penetration, protects cardiomyocytes from mitochondrial dysfunction induced by endothelin-1. Here, we examined the effects of CB13 on normal physiology of the rat heart and development of tachypacing-induced AR. Methods: Rat hearts were perfused in a Langendorff set-up with CB13 (1 µM) or vehicle. Hemodynamic properties of non-paced hearts were examined conventionally. In a different set of hearts, programmed stimulation protocol was performed before and after atrial tachypacing for 90 min using a mini-hook platinum quadrupole electrode inserted on the right atrium. Atrial samples were further assessed by western blot analysis. Results: CB13 had no effects on basal hemodynamic properties. However, the compound inhibited tachypacing-induced shortening of the AERP. Protein expression of PGC1α was significantly increased by CB13 compared to vehicle in paced and non-paced hearts. Phosphorylation of AMPKα at residue threonine 172 was increased suggesting upregulation of mitochondrial biogenesis. Connexin43 was downregulated by tachypacing. This effect was diminished in the presence of CB13. Conclusion: Our findings support the notion that peripheral activation of CBR may be a new treatment strategy to prevent AR in patients suffering from AF, and therefore warrants further study.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".