The new antiarrhythmic drug vernakalant: ex vivo study of human atrial tissue from sinus rhythm and chronic atrial fibrillation
Bibliographic record
Abstract
AIMS: Vernakalant is a newly developed antiarrhythmic drug against atrial fibrillation (AF). However, its electrophysiological actions on human myocardium are unknown. METHODS AND RESULTS: Action potentials (APs) and ion currents were recorded in right atrial trabeculae and cardiomyocytes from patients in sinus rhythm (SR) and chronic AF. Vernakalant prolonged early repolarization in SR and AF, but late only in AF. AP amplitude (APA) and dV/dtmax were reduced in a concentration- and frequency-dependent manner with IC50 < 10 µM at >3 Hz. Effective refractory period was increased more than action potential duration (APD) in SR and AF. INa was blocked with IC50s of 95 and 84 µM for SR and AF, respectively (0.5 Hz). Vernakalant did not reduce outward potassium currents compared with time-matched controls. However, area under the current-time curve was reduced due to acceleration of current decline with IC50s of 19 and 12 µM for SR and AF, respectively. Vernakalant had less effect on APD than the IKr blocker E-4031, blocked IK,ACh, and had a small inhibitory effect on IK1 at 30 µM. L-Type Ca(2+) currents (SR) were reduced with IC50 of 84 µM. CONCLUSION: Rate-dependent block of Na(+) channels represents the main antiarrhythmic mechanism of vernakalant in the fibrillating atrium. Open channel block of early transient outward currents and IK,ACh could also contribute.
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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".