Impact of combined NO and PG blockade on rapid vasodilation in a forearm mild-to-moderate exercise transition in humans
Bibliographic record
Abstract
We tested the hypothesis that nitric oxide (NO) and prostaglandins (PGs) contribute to the rapid vasodilation that accompanies a transition from mild to moderate exercise. Nine healthy volunteers (2 women and 7 men) lay supine with forearm at heart level. Subjects were instrumented for continuous brachial artery infusion of saline (control condition) or combined infusion of N(G)-nitro-L-arginine methyl ester (L-NAME) and ketorolac (drug condition) to inhibit NO synthase and cyclooxygenase, respectively. A step increase from 5 min of steady-state mild (5.4 kg) rhythmic, dynamic forearm handgrip exercise (1 s of contraction followed by 2 s of relaxation) to moderate (10.9 kg) exercise for 30 s was performed. Steady-state forearm blood flow (FBF; Doppler ultrasound) and forearm vascular conductance (FVC) were attenuated in drug compared with saline (control) treatment: FBF = 196.8 +/- 30.8 vs. 281.4 +/- 34.3 ml/min and FVC = 179.3 +/- 29.4 vs. 277.8 +/- 34.8 ml.min(-1).100 mmHg(-1) (both P < 0.01). FBF and FVC increased from steady state after release of the initial contraction at the higher workload in saline and drug conditions: DeltaFBF = 72.4 +/- 8.7 and 52.9 +/- 7.8 ml/min, respectively, and DeltaFVC = 66.3 +/- 7.3 and 44.1 +/- 7.0 ml.min(-1).100 mmHg(-1), respectively (all P < 0.05). The percent DeltaFBF and DeltaFVC were not different during saline infusion or combined inhibition of NO and PGs: DeltaFBF = 27.2 +/- 3.1 and 28.1 +/- 3.8%, respectively (P = 0.78) and DeltaFVC = 25.7 +/- 3.2 and 26.0 +/- 4.0%, respectively (P = 0.94). The data suggest that NO and vasodilatory PGs are not obligatory for rapid vasodilation at the onset of a step increase from mild- to moderate-intensity forearm exercise. Additional vasodilatory mechanisms not dependent on NO and PG release contribute to the immediate and early increase in blood flow in an exercise-to-exercise transition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".