Cardiac ryanodine receptors control heart rate and rhythmicity in adult mice
Bibliographic record
Abstract
AIMS: The molecular mechanisms controlling heart function and rhythmicity are incompletely understood. While it is widely accepted that the type 2 ryanodine receptor (Ryr2) is the major Ca(2+) release channel in excitation-contraction coupling, the role of these channels in setting a consistent beating rate remains controversial. Gain-of-function RYR2 mutations in humans and genetically engineered mouse models are known to cause Ca(2+) leak, arrhythmias, and sudden cardiac death. Embryonic stem-cell derived cardiomyocytes lacking Ryr2 display slower beating rates, but no supporting in vivo evidence has been presented. The aim of the present study was to test the hypothesis that RYR2 loss-of-function would reduce heart rate and rhythmicity in vivo. METHODS AND RESULTS: We generated inducible, tissue-specific Ryr2 knockout mice with acute ∼50% loss of RYR2 protein in the heart but not in other tissues. Echocardiography, working heart perfusion, and in vivo ECG telemetry demonstrated that deletion of Ryr2 was sufficient to cause bradycardia and arrhythmia. Our results also show that cardiac Ryr2 knockout mice exhibit functional and structural hallmarks of heart failure, including sudden cardiac death. CONCLUSION: These results illustrate that the RYR2 channel plays an essential role in pacing heart rate. Moreover, we find that RYR2 loss-of-function can lead to fatal arrhythmias typically associated with gain-of-function mutations. Given that RYR2 levels can be reduced in pathological conditions, including heart failure and diabetic cardiomyopathy, we predict that RYR2 loss contributes to disease-associated bradycardia, arrhythmia, and sudden death.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".