Proton block of the pore underlies the inhibition of hERG cardiac K<sup>+</sup>channels during acidosis
Bibliographic record
Abstract
Human ether-a-go-go-related gene (hERG) potassium channels are critical determinants of cardiac repolarization. Loss of function of hERG channels is associated with Long QT Syndrome, arrhythmia, and sudden death. Acidosis occurring as a result of myocardial ischemia inhibits hERG channel function and may cause a predisposition to arrhythmias. Acidic pH inhibits hERG channel maximal conductance and accelerates deactivation, likely by different mechanisms. The mechanism underlying the loss of conductance has not been demonstrated and is the focus of the present study. The data presented demonstrate that, unlike in other voltage-gated potassium (Kv) channels, substitution of individual histidine residues did not abolish the pH dependence of hERG channel conductance. Abolition of inactivation, by the mutation S620T, also did not affect the proton sensitivity of channel conductance. Instead, voltage-dependent channel inhibition (δ = 0.18) indicative of pore block was observed. Consistent with a fast block of the pore, hERG S620T single channel data showed an apparent reduction of the single channel current amplitude at low pH. Furthermore, the effect of protons was relieved by elevating external K(+) or Na(+) and could be modified by charge introduction within the outer pore. Taken together, these data strongly suggest that extracellular protons inhibit hERG maximal conductance by blocking the external channel pore.
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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".