NO-mediated activation of K<sub>ATP</sub> channels contributes to cutaneous thermal hyperemia in young adults
Bibliographic record
Abstract
Local skin heating to 42°C causes cutaneous thermal hyperemia largely via nitric oxide (NO) synthase (NOS)-related mechanisms. We assessed the hypothesis that ATP-sensitive K+ (KATP) channels interact with NOS to mediate cutaneous thermal hyperemia. In 13 young adults (6 women, 7 men), cutaneous vascular conductance (CVC) was measured at four intradermal microdialysis sites that were continuously perfused with 1) lactated Ringer solution (control), 2) 5 mM glibenclamide (KATP channel blocker), 3) 20 mM NG-nitro-l-arginine methyl ester (NOS inhibitor), or 4) a combination of KATP channel blocker and NOS inhibitor. Local skin heating to 42°C was administered at all four treatment sites to elicit cutaneous thermal hyperemia. Thirty minutes after the local heating, 1.25 mM pinacidil (KATP channel opener) and subsequently 25 mM sodium nitroprusside (NO donor) were administered to three of the four sites (each 25–30 min). The local heating-induced prolonged elevation in CVC was attenuated by glibenclamide (19%), but the transient initial peak was not. However, glibenclamide had no effect on the prolonged elevation in CVC in the presence of NOS inhibition. Pinacidil caused an elevation in CVC, but this response was abolished at the glibenclamide-treated skin site, demonstrating its effectiveness as a KATP channel blocker. The pinacidil-induced increase in CVC was unaffected by NOS inhibition, whereas the increase in CVC elicited by sodium nitroprusside was partly (15%) inhibited by glibenclamide. In summary, we showed an interactive effect of KATP channels and NOS for the plateau of cutaneous thermal hyperemia. This interplay may reflect a vascular smooth muscle cell KATP channel activation by NO.
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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) | 0.002 | 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".