Nitric oxide decreases the excitability of interstitial cells of Cajal through activation of the BK channel
Bibliographic record
Abstract
Nitrergic nerves are structurally and functionally associated with ICC. To further understand mechanisms of communication, the hypothesis was investigated that NO might affect large conductance K channels. To that end, we searched for IbTX-sensitive currents in ICC obtained through explant cultures from the mouse small intestine and studied effects of the NOS inhibitor omega N-nitro-L-arginine (LNNA) and the NO donor sodium nitroprusside (SNP). IbTX-sensitive currents acquired in the whole-cell configuration through nystatin perforated patches exhibited high noise levels but relatively low amplitude, whereas currents obtained in the conventional whole-cell configuration exhibited less noise and higher amplitudes; depolarization from -80 to + 40 mV evoked 357 +/- 159 pA current in the nystatin perforated patch configuration and 1075 +/- 597 pA using the conventional whole-cell configuration. Immunohistochemistry showed that ICC associated with ganglia and Auerbach's plexus nerve fibers were immunoreactive to BK antibodies. The IbTX-sensitive currents were increased by SNP and inhibited by LNNA. BK blockers suppressed spontaneous transit outward currents in ICC. After block of BK currents, or before these currents became prominent, calcium currents were activated by depolarization in the same cells. Their peak amplitude occurred at -25 mV and the currents were increased with increasing extracellular calcium and inhibited by cobalt. The hypothesis is warranted that nitrergic innervation inhibits ICC excitability in part through activation of BK channels. In addition, NO is an intracellular regulator of ICC excitability.
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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".