Spatial non-uniformity of excitation-contraction coupling can enhance arrhythmogenic-delayed afterdepolarizations in rat cardiac muscle
Bibliographic record
Abstract
AIMS: We examined whether non-uniform muscle contraction affects delayed afterdepolarizations (DADs) by dissociating Ca(2+) from myofilaments within the border zone (BZ) between contracting and stretched regions. METHODS AND RESULTS: Force, sarcomere length (SL), membrane potential, and [Ca(2+)](i) dynamics were measured in 31 ventricular trabeculae from rat hearts. Non-uniform muscle contraction was produced by exposing a restricted region of muscle to a jet of solution containing 20 mmol/L 2,3-butanedione monoxime (BDM). DADs were induced by 7.5 s-2 Hz stimulus trains at an SL of 2.0 microm (24 degrees C, [Ca(2+)](o) 2.0 mmol/L). The BDM jet enhanced DADs (n = 6, P < 0.05) and aftercontractions (n = 6, P < 0.05) with or without 100 micromol/L streptomycin and occasionally elicited an action potential. A stretch pulse from an SL of 2.0 microm to 2.1 or 2.2 microm during the last stimulated twitch of the trains accelerated Ca(2+) waves in proportion to the increment of force by the stretch (P < 0.01) with or without streptomycin. In the presence of 1 mmol/L caffeine, rapid shortening of the muscle after the stretch pulse increased [Ca(2+)](i) within the BZ, whose amplitude correlated with the increment of force by the stretch (n = 15, P < 0.01). CONCLUSION: These results suggest that non-uniform muscle contraction can enhance DADs by dissociating Ca(2+) from myofilaments within the BZ and thereby cause triggered arrhythmias.
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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".