Effect of transient stretch on intracellular Ca<sup>2+</sup>during triggered propagated contractions in intact trabeculae
Bibliographic record
Abstract
Transient stretch of cardiac muscle during a twitch contraction may dissociate Ca2+from myofilaments into the cytosol at the moment of quick release of the muscle. We studied the effect of stretch and quick release of trabeculae on changes in intracellular Ca2+([Ca2+]i) during triggered propagated contractions (TPCs). Trabeculae were dissected from the right ventricle of 9 rat hearts. [Ca2+]iwas measured using electrophoretically injected fura-2. Force was measured using a silicon strain gauge and sarcomere length was measured using laser diffraction techniques. Reproducible TPCs (n = 13) were induced by trains of electrical stimuli (378 ± 19 ms interval) for 7.5 s at [Ca2+]oof 2.0 mM (27.9 ± 0.2°C). The latency of the TPC force and the underlying increase in [Ca2+]iwas calculated from the time (TimeF) between the last stimulus and the peak of TPC force (PeakF), or the time (TimeCa) between the last stimulus and the peak of the increase in [Ca2+]iduring the TPCs (PeakCa). As a result of a 10% increase in muscle length for 150-200 ms during the last stimulated twitches, TimeFand TimeCadecreased and PeakFand PeakCaincreased significantly (n = 13). In addition, transient stretch sometimes induced a twitch contraction subsequent to the accelerated TPC and its underlying increase in [Ca2+]i. These results suggest that Ca2+binding and dissociation from the myofilaments by the stretch and quick release of muscle may modulate the TPC force and the underlying increases in [Ca2+]iand play an important role in the induction of arrhythmias.Key words: rat cardiac trabeculae, stretch, calcium transients.
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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 | 0.001 |
| 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".