L-364,373 (R-L3) enantiomers have opposite modulating effects on <i>I</i><sub>Ks</sub> in mammalian ventricular myocytes
Bibliographic record
Abstract
Activators of the slow delayed rectifier K⁺ current (IKs) have been suggested as promising tools for suppressing ventricular arrhythmias due to prolongation of repolarization. Recently, L-364,373 (R-L3) was nominated to activate IKs in myocytes from several species; however, in some studies, it failed to activate IKs. One later study suggested opposite modulating effects from the R-L3 enantiomers as a possible explanation for this discrepancy. Therefore, we analyzed the effect of the RL-3 enantiomers on IKs in ventricular mammalian myocytes, by applying standard microelectrode and whole-cell patch-clamp techniques at 37 °C. We synthesized 2 substances, ZS_1270B (right) and ZS_1271B (left), the 2 enantiomers of R-L3. In rabbit myocytes, ZS_1270B enhanced the IKs tail current by approximately 30%, whereas ZS_1271B reduced IKs tails by 45%. In guinea pig right ventricular preparations, ZS_1270B shortened APD90 (action potential duration measured at 90% repolarization) by 12%, whereas ZS_1271B lengthened it by approximately 15%. We concluded that R-L3 enantiomers in the same concentration range indeed have opposite modulating effects on IKs, which may explain why the racemic drug R-L3 previously failed to activate IKs. ZS_1270B is a potent IKs activator, therefore, this substance is appropriate to test whether IKs activators are ideal tools to suppress ventricular arrhythmias originating from prolongation of action potentials.
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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) | 0.001 | 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".