Impact of R-Carvedilol on β2-Adrenergic Receptor-Mediated Spontaneous Calcium Release in Human Atrial Myocytes
Bibliographic record
Abstract
A hallmark of atrial fibrillation is an excess of spontaneous calcium release events, which can be mimicked by β1- or β2-adrenergic stimulation. Because β1-adrenergic receptor blockers (β1-blockers) are primarily used in clinical practice, we here examined the impact of β2-adrenergic stimulation on spontaneous calcium release and assessed whether the R- and S-enantiomers of the non-selective β- blocker carvedilol could reverse these effects. For this purpose, human atrial myocytes were isolated from patients undergoing cardiovascular surgery and subjected to confocal calcium imaging or immunofluorescent labeling of the ryanodine receptor (RyR2). Interestingly, the β2-adrenergic agonist fenoterol increased the incidence of calcium sparks and waves to levels observed with the non-specific β-adrenergic agonist isoproterenol. Moreover, fenoterol increased both the amplitude and duration of the sparks, facilitating their fusion into calcium waves. Subsequent application of the non β-blocking R-Carvedilol enantiomer reversed these effects of fenoterol in a dose-dependent manner. R-Carvedilol also reversed the fenoterol-induced phosphorylation of the RyR2 at Ser-2808 dose-dependently, and 1 µM of either R- or S-Carvedilol fully reversed the effect of fenoterol. Together, these findings demonstrate that β2-adrenergic stimulation alone stimulates RyR2 phosphorylation at Ser-2808 and spontaneous calcium release maximally, and points to carvedilol as a tool to attenuate the pathological activation of β2-receptors.
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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) | 0.000 | 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) | 0.001 | 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".