Role of Ca<sup>2+</sup>-activated Cl<sup>−</sup>channels and MLCK in slow IJP in opossum esophageal smooth muscle
Bibliographic record
Abstract
The possible contribution of Ca2+-activated Cl- channel [I(Cl(Ca))] and myosin light-chain kinase (MLCK) to nonadrenergic, noncholinergic slow inhibitory junction potentials (sIJP) was studied using conventional intracellular microelectrode recordings in circular smooth muscle of opossum esophageal body and guinea pig ileum perfused with Krebs solution containing atropine (3 microM), guanethidine (3 microM), and substance P (1 microM). In opossum esophageal circular smooth muscle, resting membrane potential (MP) was -51.9 +/- 0.7 mV (n = 89) with MP fluctuations of 1-3 mV. A single square-wave nerve stimulation of 0.5 ms duration and 80 V induced a sIJP with amplitude of 6.3 +/- 0.2 mV, half-amplitude duration of 635 +/- 19 ms, and rebound depolarization amplitude of 2.4 +/- 0.1 mV (n = 89). 9-Anthroic acid (A-9-C), niflumic acid (NFA), wortmannin, and 1-(5-chloronaphthalene-1-sulfonyl)-1H-hexahydro-1,4-diazepine (ML-9) abolished MP fluctuations, sIJP, and rebound depolarization in a concentration-dependent manner. A-9-C and NFA but not wortmannin and ML-9 hyperpolarized MP. In guinea pig ileal circular smooth muscle, nerve stimulation elicited an IJP composed of both fast (fIJP) and slow (sIJP) components, followed by rebound depolarization. NFA (200 microM) abolished sIJP and rebound depolarization but left the fIJP intact. These data suggest that in the tissues studied, activation of I(Cl(Ca)), which requires MLCK, contributes to resting MP, and that closing of I(Cl(Ca)) is responsible for sIJP.
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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) | 0.000 | 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".