Altered K<sup>+</sup> current profiles underlie cardiac action potential shortening in hyperkalemia and β-adrenergic stimulation
Bibliographic record
Abstract
Hyperkalemia is known to develop in various conditions including vigorous physical exercise. In the heart, hyperkalemia is associated with action potential (AP) shortening that was attributed to altered gating of K+ channels. However, it remains unknown how hyperkalemia changes the profiles of each K+ current under a cardiac AP. Therefore, we recorded the major K+ currents (inward rectifier K+ current, IK1; rapid and slow delayed rectifier K+ currents, IKr and IKs, respectively) using AP-clamp in rabbit ventricular myocytes. As K+ may accumulate at rapid heart rates during sympathetic stimulation, we also examined the effect of isoproterenol on these K+ currents. We found that IK1 was significantly increased in hyperkalemia, whereas the reduction of driving force for K+ efflux dominated over the altered channel gating in case of IKr and IKs. Overall, the markedly increased IK1 in hyperkalemia overcame the relative decreases of IKr and IKs during AP, resulting in an increased net repolarizing current during AP phase 3. β-Adrenergic stimulation of IKs also provided further repolarizing power during sympathetic activation, although hyperkalemia limited IKs upregulation. These results indicate that facilitation of IK1 in hyperkalemia and β-adrenergic stimulation of IKs represent important compensatory mechanisms against AP prolongation and arrhythmia susceptibility.
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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".