K<sup>+</sup> channel mechanisms underlying cholinergic cutaneous vasodilation and sweating in young humans: roles of K<sub>Ca</sub>, K<sub>ATP</sub>, and K<sub>V</sub> channels?
Bibliographic record
Abstract
Acetylcholine released from cholinergic nerves is involved in heat loss responses of cutaneous vasodilation and sweating. K(+) channels are thought to play a role in regulating cholinergic cutaneous vasodilation and sweating, though which K(+) channels are involved in their regulation remains unclear. We evaluated the hypotheses that 1) Ca(2+)-activated K(+) (KCa), ATP-sensitive K(+) (KATP), and voltage-gated K(+) (KV) channels all contribute to cholinergic cutaneous vasodilation; and 2) KV channels, but not KCa and KATP channels, contribute to cholinergic sweating. In 13 young adults (24 ± 5 years), cutaneous vascular conductance (CVC) and sweat rate were evaluated at intradermal microdialysis sites that were continuously perfused with: 1) lactated Ringer (Control), 2) 50 mM tetraethylammonium (KCa channel blocker), 3) 5 mM glybenclamide (KATP channel blocker), and 4) 10 mM 4-aminopyridine (KV channel blocker). At all sites, cholinergic cutaneous vasodilation and sweating were induced by coadministration of methacholine (0.0125, 0.25, 5, 100, and 2,000 mM, each for 25 min). The methacholine-induced increase in CVC was lower with the KCa channel blocker relative to Control at 0.0125 (1 ± 1 vs. 9 ± 6%max) and 5 (2 ± 5 vs. 17 ± 14%max) mM methacholine, whereas it was lower in the presence of KATP (69 ± 7%max) and KV (57 ± 14%max) channel blocker compared with Control (79 ± 6%max) at 100 mM methacholine. Furthermore, methacholine-induced sweating was lower at the KV channel blocker site (0.42 ± 0.17 mg·min(-1)·cm(-2)) compared with Control (0.58 ± 0.15 mg·min(-1)·cm(-2)) at 2,000 mM methacholine. In conclusion, we show that KCa, KATP, and KV channels play a role in cholinergic cutaneous vasodilation, whereas only KV channels contribute to cholinergic sweating in normothermic resting humans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".