Species-dependent differences in the inhibition of various potassium currents and in their effects on repolarization in cardiac ventricular muscle
Bibliographic record
Abstract
Even though rodents are accessible model animals, their electrophysiological properties are deeply different from those of humans, making the translation of rat studies to humans rather difficult. We compared the mechanisms of ventricular repolarization in various animal models to those of humans by measuring cardiac ventricular action potentials from ventricular papillary muscle preparations using conventional microelectrodes and applying selective inhibitors of various potassium transmembrane ion currents. Inhibition of the IK1 current (10 µmol/L barium chloride) significantly prolonged rat ventricular repolarization, but only slightly prolonged it in dogs, and did not affect it in humans. On the contrary, IKr inhibition (50 nmol/L dofetilide) significantly prolonged repolarization in humans, rabbits, and dogs, but not in rats. Inhibition of the IKur current (1 µmol/L XEN-D0101) only prolonged rat ventricular repolarization and had no effect in humans or dogs. Inhibition of the IKs (500 nmol/L HMR-1556) and Ito currents (100 µmol/L chromanol-293B) elicited similar effects in all investigated species. We conclude that dog ventricular preparations have the strongest translational value and rat ventricular preparations have the weakest translational value in cardiac electrophysiological experiments.
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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 | 0.001 | 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) | 0.002 | 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".