Chlorthalidone inhibits the KvLQT1 potassium current in guinea‐pig ventricular myocytes and oocytes from<i>Xenopus laevis</i>
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Chlorthalidone is used for the treatment of hypertension as it produces a lengthening of the cardiac action potential. However, there is no experimental evidence that chlorthalidone has electrophysiological effects on the potassium currents involved in cardiac repolarization. EXPERIMENTAL APPROACH: Ventricular myocytes and oocytes, transfected with human ionic channels that produce IK current, were exposed to different concentrations of chlorthalidone. Action potentials and potassium currents were recorded using a patch clamp technique. To determine which component of the current was affected by chlorthalidone, human channel proteins (hERG, minK and KvLQT1) were used. KEY RESULTS: Chlorthalidone prolonged the ventricular action potential at 50 and 90% by 13 and 14%, respectively. The cardiac potassium currents I(to) and IK(1) were not affected by chlorthalidone at any concentration, whereas the delayed rectifier potassium current, IK, was blocked in a dose-response, voltage-independent fashion. In our preparation, 100 microM chlorthalidone blocked the two components of the delayed rectifier potassium current with the same potency (50.1+/-5% for IK(r) and 54.6+/-6% for IK(s)) (n=7, P<0.05). The chlorthalidone-sensitive current was slow and saturated at potentials greater than +30 mV. In our conditions only the KvLQT1 potassium current was affected by the drug, by 14%. CONCLUSIONS AND IMPLICATIONS: Chlorthalidone was demonstrated to have a direct effect on cardiac ventricular myocytes; it blocked the delayed rectifier potassium current (IK), specifically the KvLQT1 component of the potassium current. These results indicate that it has potential for use as an antiarrhythmic but further studies are needed.
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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".