Hypoxia Reduces Mature HERG Channels through Calpain Up‐regulation and Activation
Bibliographic record
Abstract
Human ether‐à‐go‐go related gene (hERG) encodes the pore‐forming subunit of the I Kr channel, which is important for cardiac repolarization. Loss of function of the hERG channel causes long QT syndrome, a cardiac disorder with high risk of cardiac arrhythmias and sudden death. Patients with medical conditions, such as cardiac ischemia, are associated with prolonged QT intervals and arrhythmias. Since proteases, such as calpain, are upregulated and activated during cardiac ischemia and hypoxia, we investigated the role of calpain in hypoxia‐mediated hERG reduction. We demonstrate that hypoxic (0.5% O 2 ) culture of hERG‐expressing HEK cells and neonatal rat cardiomyocytes led to a significant reduction of mature hERG expression and a concomitant increase in calpain expression. Transfection of hERG‐HEK cells with calpain‐1 reduced mature hERG expression and was accompanied by a significant calpain expression in the cell culture media. Treatment of cells with media from calpain‐1 transfected cells reduced mature hERG channel expression and function. The calpain‐1‐mediated hERG reduction was completely prevented by the membrane‐impermeable calpain inhibitor peptide B27. Replacing the S5‐S6 pore linker of hERG with that of EAG completely eliminated the calpain‐1 and hypoxic culture‐induced hERG reduction. Application of a peptide (BeKm‐1), which binds specifically to hERG's extracellular S5‐pore linker, prevented calpain‐1 and hypoxic culture‐induced hERG reduction. We conclude that hypoxia decreases mature hERG expression by activating calpain, which cleaves the channel protein at the extracellular S5‐S6 pore linker leading to subsequent channel degradation. Supported by the Canadian Institutes of Health Research & the Heart and Stroke Foundation of Ontario
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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".