Effect of acute nitrate ingestion on <i>V</i>O<sub>2</sub> response at different exercise intensity domains
Bibliographic record
Abstract
While nitrate supplementation influences oxygen uptake (V̇O2) response to exercise, this effect may be intensity dependent. The purpose of this study was to investigate the effect of acute nitrate supplementation on V̇O2 response during different exercise intensity domains in humans. Eleven men ingested 10 mg·kg−1 body mass (8.76 ± 1.35 mmol) of sodium nitrate or sodium chloride (placebo) 2.5 h before cycling at moderate (90% of gas exchange threshold; GET), heavy (GET + 40% of the difference between GET and peak oxygen uptake (V̇O2peak), Δ 40) or severe (GET + 80% of the difference between GET and V̇O2peak, Δ 80) exercise intensities. Volunteers performed exercise for 10 min (moderate), 15 min (heavy) or until exhaustion (severe). Acute nitrate supplementation had no effect on any V̇O2 response parameters during moderate and severe exercise intensities. However, the V̇O2 slow amplitude (nitrate: 0.93 ± 0.36 L·min−1 vs. placebo: 1.13 ± 0.59 L·min−1, p = 0.04) and V̇O2 slow gain (nitrate: 5.81 ± 2.37 mL·min–1·W−1 vs. placebo: 7.09 ± 3.67 mL·min–1·W−1, p = 0.04) were significantly lower in nitrate than in placebo during the heavy exercise intensity. There was no effect of nitrate on plasma lactate during any exercise intensity (p > 0.05). Time to exhaustion during the severe exercise intensity was also not affected by nitrate (p > 0.05). In conclusion, acute nitrate supplementation reduced the slow component of V̇O2 only when performing heavy-intensity exercise, which might indicate an intensity-dependent effect of nitrate on V̇O2 response.
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 | 0.001 |
| 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 | 0.001 | 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".