Kinetic analysis of the effects of H<sup>+</sup>or Ni<sup>2+</sup>on Kv1.5 current shows that both ions enhance slow inactivation and induce resting inactivation
Bibliographic record
Abstract
External H+ and Ni2+ ions inhibit Kv1.5 channels by increasing current decay during a depolarizing pulse and reducing the maximal conductance. Although the former may be attributed to an enhancement of slow inactivation occurring from the open state, the latter cannot. Instead, we propose that the loss of conductance is due to the induction, by H+ or Ni2+, of a resting inactivation process. To assess whether the two inactivation processes are mechanistically related, we examined the time courses for the onset of and recovery from H+- or Ni2+-enhanced slow inactivation and resting inactivation. Compared to the time course of H+- or Ni2+-enhanced slow inactivation at +50 mV, the onset of resting inactivation induced at 80 mV with either ion involves a relatively slower process. Recovery from slow inactivation under control conditions was bi-exponential, indicative of at least two inactivated states. Recovery following H+- or Ni2+-enhanced slow inactivation or resting inactivation had time constants similar to those for recovery from control slow inactivation, although H+ and Ni2+ biased inactivation towards states from which recovery was fast and slow, respectively. The shared time constants suggest that the H+- and Ni2+-enhanced slow inactivated and induced resting inactivated states are similar to those visited during control slow inactivation at pH 7.4. We conclude that in Kv1.5 H+ and Ni2+ differentially enhance a slow inactivation process that involves at least two inactivated states and that resting inactivation is probably a close variant of slow inactivation.
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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".