Effect of autonomic neurotransmitters on excitable gap composition in canine atrial flutter
Bibliographic record
Abstract
Atrial arrhythmias are believed to be influenced by autonomic nervous system tone. We evaluated the effects of sympathetic and parasympathetic activation on atrial flutter (AFl) by determining the effects of norepinephrine (NE) and acetylcholine (ACh) on the composition of the excitable gap. A model of reentry around the tricuspid valve was produced in 17 chloralose anesthetized dogs using a Y-shaped lesion in the intercaval area that extended to the right atrial appendage. Excitable gap characteristics were determined during AFl by scanning diastole with a single premature extrastimulus at progressively shorter coupling intervals to define the reset-response curve. Measurements were made during a constant infusion of NE (15 µg/min) into the right coronary artery and repeated during ACh infusion (2 µg/min) following a 15 min recovery period. The excitable gap (27 ± 1 ms) was significantly (P < 0.001) increased by NE (34 ± 1 ms) and ACh (50 ± 2 ms). The fully excitable portion (7 ± 1 ms) was also significantly (P < 0.001) increased by NE (17 ± 1 ms) and ACh (43 ± 2 ms). We conclude that both neurotransmitters increase the safety margin of full excitability ahead of the wavefront, demonstrating that parasympathetic and sympathetic activation can facilitate the persistence of this refractory atrial arrhythmia.Key words: atrial flutter, acetylcholine, norepinephrine, excitable gap.
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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) | 0.000 | 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 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".