Cyclooxygenase inhibition does not alter methacholine-induced sweating
Bibliographic record
Abstract
Cholinergic agents (e.g., methacholine) induce cutaneous vasodilation and sweating. Reports indicate that either nitric oxide (NO), cyclooxygenase (COX), or both can contribute to cholinergic cutaneous vasodilation. Also, NO is reportedly involved in cholinergic sweating; however, whether COX contributes to cholinergic sweating is unclear. Forearm sweat rate (ventilated capsule) and cutaneous vascular conductance (CVC, laser-Doppler perfusion units/mean arterial pressure) were evaluated in 10 healthy young (24 ± 4 yr) adults (7 men, 3 women) at four skin sites that were continuously perfused via intradermal microdialysis with 1) lactated Ringer (control), 2) 10 mM ketorolac (a nonselective COX inhibitor), 3) 10 mM N(G)-nitro-l-arginine methyl ester (l-NAME, a nonselective NO synthase inhibitor), or 4) a combination of 10 mM ketorolac + 10 mM l-NAME. At the four skin sites, methacholine was simultaneously infused in a dose-dependent manner (1, 10, 100, 1,000, 2,000 mM). Relative to the control site, forearm CVC was not influenced by ketorolac throughout the protocol (all P > 0.05), whereas l-NAME and ketorolac + l-NAME reduced forearm CVC at and above 10 mM methacholine (all P < 0.05). Conversely, there was no main effect of treatment site (P = 0.488) and no interaction of methacholine dose and treatment site (P = 0.711) on forearm sweating. Thus forearm sweating (in mg·min(-1)·cm(-2)) from baseline up to the maximal dose of methacholine was not different between the four sites (at 2,000 mM, control 0.50 ± 0.23, ketorolac 0.44 ± 0.23, l-NAME 0.51 ± 0.22, and ketorolac + l-NAME 0.51 ± 0.23). We show that both NO synthase and COX inhibition do not influence cholinergic sweating induced by 1-2,000 mM methacholine.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".