Effect of acute nitrate and citrulline supplementation on muscle microvascular response to ischemia–reperfusion in healthy humans
Bibliographic record
Abstract
Nitric oxide (NO) is implicated in vasomotor control mechanisms altering the diameter of the vessels under various physiological and pathological conditions. There are 2 main NO production pathways, 1 NO synthase (NOS) independent (nitrate–nitrite–NO) and the other is NOS dependent (citrulline–arginine–NO). The objective of the study was to evaluate the effect of acute nitrate and citrulline supplementation on post-ischemic vascular response in healthy subjects. Fourteen subjects performed 2-leg vascular occlusion tests, 3 days apart. They were randomly assigned to consume a drink containing 1200 mg (19.4 mmol) of nitrate and 6 g of citrulline (N+C) or a placebo (Pl). Changes in total hemoglobin (Hbtot) and oxyhemoglobin (HbO2) concentrations were recorded by near-infrared spectroscopy on the thigh and calf muscles. No differences between N+C and Pl were observed during the ischemic period. Hbtot increased to a larger extent during the reperfusion period for the thigh (e.g., area under the curve, 821 ± 324 vs. 627 ± 381 mmol·s−1, p = 0.003) and the calf (515 ± 285 vs. 400 ± 275 mmol·s−1, p = 0.029) in the N+C versus Pl conditions. Similar results were found regarding HbO2 for the thigh (e.g., area under the curve, 842 ± 502 vs. 770 ± 491 mmol·s−1, p = 0.077) and the calf (968 ± 536 vs. 865 ± 275 mmol·s−1, p = 0.075). The larger postocclusive Hbtot and HbO2 responses observed after N+C intake suggests a greater post-ischemic vasodilation, which may be due to increased NO availability, via the activation of the 2 main NO production pathways.
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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) | 0.001 | 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 | 0.001 | 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".