Nitroblue tetrazolium blocks BK channels in cerebrovascular smooth muscle cell membranes
Bibliographic record
Abstract
The effects of p-nitroblue tetrazolium (NBT) on large conductance, calcium-activated potassium channels (BK channels) in enzymatically dispersed rat cerebrovascular smooth muscle cells (CVSMCs) were examined. Patch clamp methods were employed to record single BK channel currents from inside-out patches of CVMC membrane maintained at 21 - 23 degrees C. When applied to the cytoplasmic face of inside-out membrane patches (internally applied NBT), micromolar concentrations of NBT reversible reduced the mean open time of BK channels, without changing channel conductance. NBT altered the frequency distribution of BK channel open times from a two exponential to a single exponential form. In the absence of NBT, mean channel open time increased on membrane depolarization. In the presence of internally applied NBT, mean channel open became essentially independent of membrane potential. Internally applied NBT also reduced the mean closed time of BK channels when measured at membrane potentials in the range -80 mV to +20 mV. The combined effects of internal NBT on mean open and closed times resulted in the suppression of BK channel open probability when measured at positive membrane potentials. When applied to the external membrane face, micromolar concentrations of NBT reduced mean channel open time progressively as the membrane was hyperpolarized, and also reduced open probability at negative membrane potentials. A model is proposed in which NBT alters channel gating by binding to a site at or near to the cytoplasmic membrane face. Externally applied NBT suppressed BK channel open probability at concentrations which also inhibit nitric oxide synthase (NOS). Therefore, the potential role of potassium channel block in NBT actions previously attributed to NOS inhibition is discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".