The roles of K<sub>Ca</sub>, K<sub>ATP</sub>, and K<sub>V</sub> channels in regulating cutaneous vasodilation and sweating during exercise in the heat
Bibliographic record
Abstract
We recently showed the varying roles of Ca2+-activated (KCa), ATP-sensitive (KATP), and voltage-gated (KV) K+ channels in regulating cholinergic cutaneous vasodilation and sweating in normothermic conditions. However, it is unclear whether the respective contributions of these K+ channels remain intact during dynamic exercise in the heat. Eleven young (23 ± 4 yr) men completed a 30-min exercise bout at a fixed rate of metabolic heat production (400 W) followed by a 40-min recovery period in the heat (35°C, 20% relative humidity). Cutaneous vascular conductance (CVC) and local sweat rate were assessed at four forearm skin sites perfused via intradermal microdialysis with: 1) lactated Ringer solution (control); 2) 50 mM tetraethylammonium (nonspecific KCa channel blocker); 3) 5 mM glybenclamide (selective KATP channel blocker); or 4) 10 mM 4-aminopyridine (nonspecific KV channel blocker). Responses were compared at baseline and at 10-min intervals during and following exercise. KCa channel inhibition resulted in greater CVC versus control at end exercise ( P = 0.04) and 10 and 20 min into recovery (both P < 0.01). KATP channel blockade attenuated CVC compared with control during baseline ( P = 0.04), exercise (all P ≤ 0.04), and 10 min into recovery ( P = 0.02). No differences in CVC were observed with KV channel inhibition during baseline ( P = 0.15), exercise (all P ≥ 0.06), or recovery (all P ≥ 0.14). With the exception of KV channel inhibition augmenting sweating during baseline ( P = 0.04), responses were similar to control with all K+ channel blockers during each time period (all P ≥ 0.07). We demonstrated that KCa and KATP channels contribute to the regulation of cutaneous vasodilation during rest and/or exercise and recovery in the heat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".