Effects of E4031 and quinidine on atrial and ventricular refractoriness in rabbits in vivo.
Bibliographic record
Abstract
This study assessed the effects of E4031 and quinidine on refractoriness (ERP) in a new in vivo model in rabbits. Following sinoatrial (SAN) and atrioventricular node (AVN) ablation ERP was determined in atria and ventricles with the shortest S1-S2 interval eliciting a second electrogram defined as the ERP. The effects of E4031 and quinidine (dose ranges 1-8 micromol/kg) were compared. E4031 dose-dependently increased ERP. The maximum change from pre-drug values with E4031 was 27+/-8 msec (a 36+/-12% increase) at 2 Hz in atria and 51+/-9 msec (27+/-5%) at 2 Hz in ventricles. Negative frequency-dependence was observed only in ventricles. Quinidine dose-dependently increased ERP. The maximum increase for quinidine was 23+/-3 msec (28+/-4%) at 2 Hz in atria and 25+/-10 msec (22+/-10%) at 6 Hz in ventricles, but without frequency-dependence in either tissue. In comparison to E4031, quinidine produced smaller changes in ERP and showed minimal frequency dependence. Thus, the added presence of sodium blocking actions with quinidine did not produce greater effects on ERP than I(Kr) blockade alone with E4031. However, quinidine also blocks other potassium currents, such as Ito, and the degree of I(Kr) blockade with E4031 was probably greater than that with the same dose of quinidine. This model may have clinical utility for testing multi-ion channel blocking drugs.
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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 | 0.001 |
| 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".