Skin Blood Flow Responses to Acetylcholine, Local Heating, and to 60% VO2max exercise with and without Nitric Oxide inhibition, in Boys vs. Girls
Bibliographic record
Abstract
PURPOSE: To determine sex-related differences in the skin blood flow (SkBF) response to exercise, local heating, and acetylcholine (ACh) in children, and to assess nitric oxide contribution to the SkBF response. METHODS: Forearm SkBF during local heating (44°C), ACh iontophoresis, and exercise (30-min cycling and 60% of maximum oxygen consumption) was assessed, using laser Doppler fluxmetry, in 12 boys and 12 girls (7-13 y old), with and without nitric oxide synthase inhibition, using Nω-nitro-L-arginine methyl ester iontophoresis. RESULTS: Local-heating-induced and ACh-induced SkBF increase were not different between boys and girls (local heating: 1445% [900%] and 1432% [582%] of baseline, P = .57; ACh: 673% [434%] and 558% [405%] of baseline, respectively, P = .18). Exercise-induced increase in SkBF was greater in boys than girls (528% [290%] and 374% [192%] of baseline, respectively, P = .03). Nω-nitro-L-arginine methyl ester blunted the SkBF response to ACh and during exercise (P < .001), with no difference between sexes. CONCLUSION: SkBF responses to ACh and local heat stimuli were similar in boys and girls, while the increase in SkBF during exercise was greater in boys. The apparent role of nitric oxide was not different between boys and girls. It is suggested that the greater SkBF response in boys during exercise was related to greater relative heat production and dissipation needs at this exercise intensity. The response to body size-related workload should be further examined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".