Activation of muscarinic receptor increases cardiac potassium hERG channel through phosphorylation of E3 ubiquitin ligase Nedd4–2
Bibliographic record
Abstract
The human ether‐a‐go‐go‐related gene (hERG) encodes the rapidly activating delayed rectifier potassium channel ( I Kr ) which is critical for repolarization of cardiac action potential. Loss of function of hERG channels due to gene mutations or drug blockade causes long QT syndrome. Presently, little is known about the restoration or enhancement of hERG channel function. In the present study, we found that muscarinic receptor agonist, carbachol, specifically increased hERG expression and I hERG , but had no effect on I Ks , I EAG and I Kv1.5 channels in HEK expression systems. Carbachol treatment decreased hERG‐ubiquitin interaction and hERG degradation. It is known that hERG channels are degraded by the Nedd4–2, we found that disrupting the binding sites of Nedd4–2 by the Y1078A point mutation or C‐terminal truncation Δ1073 mutation in hERG completely eliminated the effects of carbachol on hERG channels. Our data further indicate that carbachol treatment inhibited Nedd4–2 activity by enhancing its phosphorylation level. Another muscarinic receptor agonist, oxotremorine, increased hERG function, and the muscarinic receptor antagonist 4‐DAMP abolished the effects of both carbachol and oxotremorine on hERG channels. Enhancement of hERG function by muscarinic receptor activation represents a novel pathway in hERG regulation, and this finding may have potential for the management of long QT syndrome patients. Supported by: Canadian Institutes of Health Research (CIHR).
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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".