Bibliographic record
Abstract
The inactivation gating of hERG channels is important for the channel function and drug-channel interaction. Whereas hERG channels are highly selective for K+, we have found that inactivated hERG channels allow Na+ to permeate in the absence of K+. This provides a new way to directly monitor and investigate hERG inactivation. By using whole cell patch clamp method with an internal solution containing 135 mM Na+ and an external solution containing 135 mM NMG+, we recorded a robust Na+ current through hERG channels expressed in HEK 293 cells. Kinetic analyses of the hERG Na+ and K+ currents indicate that the channel experiences at least two states during the inactivation process, an initial fast, less stable state followed by a slow, more stable state. The Na+ current reflects Na+ ions permeating through the fast inactivated state but not through the slow inactivated state or open state. Thus the hERG Na+ current displayed a slow inactivation as the channels travel from the less stable, fast inactivated state into the more stable, slow inactivated state. Removal of fast inactivation by the S631A mutation abolished the Na+ current. Moreover, acceleration of fast inactivation by mutations T623A, F627Y, and S641A did not affect the hERG Na+ current, but greatly diminished the hERG K+ current. We also found that external Na+ potently blocked the hERG outward Na+ current with an IC50 of 3.5 mM. Mutations in the channel pore and S6 regions, such as S624A, F627Y, and S641A, abolished the inhibitory effects of external Na+ on the hERG Na+ current. Na+ permeation and blockade of hERG channels provide novel ways to extend our understanding of the hERG gating mechanisms.
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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".