Preserved BK Channel Function in Vasospastic Myocytes from a Dog Model of Subarachnoid Hemorrhage
Bibliographic record
Abstract
Cerebral vasospasm after subarachnoid hemorrhage (SAH) is due to contraction of smooth muscle cells in the cerebral arteries. The mechanism of this contraction, however, is not well understood. Smooth muscle contraction is regulated in part by membrane potential, which is determined by K+ conductance in smooth muscle. Voltage-gated (Kv) and large-conductance, Ca2+-activated K+ (BK) channels dominate arterial smooth muscle K+ conductance. Vasospastic smooth muscle cells are depolarized relative to normal cells, but whether this is due to altered Kv or BK channel function has not been determined. This study determined if BK channels are altered during vasospasm after SAH in dogs. We first characterized BK channels in basilar-artery smooth muscle using whole-cell patch clamping and single-channel recordings. Next, we compared BK channel function between normal and vasospastic cells. There were no significant differences between normal and vasospastic cells in BK current density, kinetics, Ca2+ and voltage sensitivity, single-channel conductance or apparent Ca2+ affinity. Basilar-artery myocytes had no, small- or intermediate-conductance, Ca2+-activated K+ channels. The lack of difference in BK channels between vasospastic and control cells suggests alteration(s) in other K+ channels or other ionic conductances may underlie the membrane depolarization and vasoconstriction observed during vasospasm after SAH.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".