Load-induced changes in ventricular repolarization: evidence of autonomic modulation
Bibliographic record
Abstract
Augmented hemodynamic load increases the risk of arrhythmogenesis by modulating cardiac repolarization duration. We hypothesized that the intervention on the autonomic tone may affect the load-dependent changes in ventricular repolarization. Activation-recovery intervals were measured in unipolar electrograms simultaneously recorded from 64 ventricular epicardial leads, in a total of 26 chinchilla rabbits in resting conditions, and after 1 and 10 min of aortic stenosis. Eleven animals were given atropine and propranolol before the loading. The short-term stenosis decreased the activation-recovery intervals in the right ventricle, whereas the prolonged overload increased the repolarization duration in both ventricles. The treatment with the β-adrenergic and M-cholinergic blockers prolonged the activation-recovery intervals, especially at the left ventricle, attenuating the apicobasal and interventricular gradients of repolarization duration seen in the baseline state. Further ventricular loading shortened the repolarization duration in both ventricles in animals with autonomic blockade. Thus, the autonomic tone was shown to be essential for the development of repolarization heterogeneity across the ventricles. The autonomic blockade transformed the biphasic changes of activation-recovery intervals into their monophasic shortening at aortic stenosis.
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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".