Mechanisms underlying the antiarrhythmic effect of ARumenamide-787 in experimental models of the J wave syndromes and hypothermia
Bibliographic record
Abstract
BACKGROUND: Brugada (BrS) and early repolarization syndromes (ERS), the so-called J wave syndromes (JWS), are associated with life-threatening ventricular arrhythmias. Pharmacologic approaches to therapy are currently limited. In this study, we examine the effects of ARumenamide-787 (AR-787) to suppress the electrocardiographic and arrhythmic manifestations of JWS and hypothermia. METHODS: We studied the effects of AR-787 on INa and IKr in HEK-293 cells stably expressing the α- and β1-subunits of the cardiac (NaV1.5) sodium channel and hERG channel, respectively. In addition, we studied its effect on Ito, INa and ICa in dissociated canine ventricular myocytes along with action potentials and ECG from coronary-perfused right (RV) and left (LV) ventricular wedge preparations. The Ito agonist, NS5806 (5-10 μM), ICa blocker, verapamil (2.5 μM), and INa blocker, ajmaline (2.5 μM), were used to mimic the genetic defects associated with JWS and to induce the electrocardiographic and arrhythmic manifestations of JWS (prominent J waves/ST segment elevation, phase 2 reentry and polymorphic VT/VF) in canine ventricular wedge preparations. RESULTS: AR-787 (1, 10 and 50 μM) exerted pleiotropic effects on cardiac ion channels. The predominant effect was inhibition of the transient outward current (Ito) and enhancement of the sodium channel current (INa), with lesser effects to inhibit IKr and augment calcium channel current (ICa). AR-787 diminished the electrocardiographic J wave and prevented and/or suppressed all arrhythmic activity in canine RV and LV experimental models of BrS, ERS and hypothermia. CONCLUSIONS: Our findings point to AR-787 as promising candidate for the pharmacologic treatment of JWS and hypothermia.
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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".