Ca<sup>2+</sup>-dependent K<sup>+</sup>channels and Na<sup>+</sup>-K<sup>+</sup>-ATPase mediate H<sub>2</sub>O<sub>2</sub>- and superoxide-induced relaxations in canine trachealis
Bibliographic record
Abstract
We examined the ionic mechanisms underlying the responses of canine trachealis to superoxide (generated in vitro by using xanthine oxidase or added exogenously) and peroxide (generated spontaneously in vitro by the dismutation of superoxide or added exogenously). Although neither had any effect on resting tone, both triggered relaxations in carbachol-precontracted tissues. These relaxations were eliminated by catalase but were much less sensitive to the hydroxyl radical scavenger dimethylthiourea, indicating they were mediated primarily by peroxide. These relaxations were decreased in magnitude and/or slowed by nifedipine (10(-6) M), ouabain (10(-6) M), or tetraethylammonium (25 mM), but not by 4-aminopyridine (5 mM), and were small or absent in tissues precontracted with 30 mM KCl. Finally, peroxide triggered membrane hyperpolarization and elevated cytosolic concentration of Ca(2+) (primarily via release from the internal store). Thus peroxide-mediated relaxations seem to involve Ca(2+) release, opening of Ca(2+)-dependent K(+) channels, hyperpolarization, closure of Ca(2+) channels, and relaxation. In addition, some other free radical (hydroxyl radical?) may activate the Na(+)-K(+) pump, also hyperpolarizing the membrane and causing relaxation.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".