Isoform dependent regulation of human HCN channels by cholesterol
Bibliographic record
Abstract
Cholesterol has been shown to regulate numerous ion channels. HCN channels represent the molecular correlate of If or Ih in sinoatrial node (SAN) and neuronal cells. Previous studies have implicated a role for cholesterol in the regulation of rabbit HCN4 channels with effects on pacing in the rabbit SAN. Using electrophysiological and biochemical approaches, we examined the effect of cholesterol modulation on human HCN1, HCN2 and HCN4 isoforms. Patch-clamp experiments uncovered isoform specific differences in the effect of cholesterol on gating kinetics upon depletion by MβCD or mevastatin or enrichment using MβCD/cholesterol. Most dramatically cholesterol had isoform specific effects on mode-shifting, which has been suggested to play a key role in stabilizing firing rate and preventing arrhythmic firing in SAN cells and neurons. Mode-shifting in HCN1 channels was insensitive to cholesterol manipulation, while HCN2 and HCN4 were strongly affected. Trafficking of each isoform to the plasma membrane was also affected by cholesterol modulation differentially between isoforms, however, each isoform remained localized in lipid raft domains after cholesterol depletion. These effects may contribute to the side effects of cholesterol reducing therapies including disrupted heart rhythm and neuropathic pain, as well as the susceptibility of sinus dysfunction in patients with elevated cholesterol.
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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".