β2‐adrenergic stimulation potentiates spontaneous calcium release by increasing signal mass and co‐activation of ryanodine receptor clusters
Bibliographic record
Abstract
AIMS: It is unknown how β-adrenergic stimulation affects calcium dynamics in individual RyR2 clusters and leads to the induction of spontaneous calcium waves. To address this, we analysed spontaneous calcium release events in green fluorescent protein (GFP)-tagged RyR2 clusters. METHODS: Cardiomyocytes from mice with GFP-tagged RyR2 or human right atrial tissue were subjected to immunofluorescent labelling or confocal calcium imaging. RESULTS: Spontaneous calcium release from single RyR2 clusters induced 91.4% ± 2.0% of all calcium sparks while 8.0% ± 1.6% were caused by release from two neighbouring clusters. Sparks with two RyR2 clusters had 40% bigger amplitude, were 26% wider, and lasted 35% longer at half maximum. Consequently, the spark mass was larger in two- than one-cluster sparks with a median and interquartile range for the cumulative distribution of 15.7 ± 20.1 vs 7.6 ± 5.7 a.u. (P < .01). β2-adrenergic stimulation increased RyR2 phosphorylation at s2809 and s2815, tripled the fraction of two- and three-cluster sparks, and significantly increased the spark mass. Interestingly, the amplitude and mass of the calcium released from a RyR2 cluster were proportional to the SR calcium load, but the firing rate was not. The spark mass was also higher in 33 patients with atrial fibrillation than in 36 without (22.9 ± 23.4 a.u. vs 10.7 ± 10.9; P = .015). CONCLUSIONS: Most sparks are caused by activation of a single RyR2 cluster at baseline while β-adrenergic stimulation doubles the mass and the number of clusters per spark. This mimics the shift in the cumulative spark mass distribution observed in myocytes from patients with atrial fibrillation.
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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".