Relationship between decreased oxyhaemoglobin saturation and exhaled nitric oxide during exercise
Bibliographic record
Abstract
Decreases in oxyhaemoglobin saturation (SaO2) are frequently observed in highly trained male endurance athletes during heavy work and has been termed exercise-induced hypoxaemia (EIH). Ventilation perfusion (VA/Q) mismatching and diffusion limitations are thought to be responsible. Nitric oxide (NO), a potent vasodilator, is present in the exhaled air of resting and exercising humans. Endogenously produced NO is thought to play a role in VA/Q matching and maintenance of low pulmonary vascular resistance. The purpose of this study was to determine the relationship between exhaled NO and EIH. It was hypothesized that athletes with EIH would have lower NO levels compared with non-EIH athletes. Eighteen highly trained male cyclists (VO2max=67.7 +/- 5.2 mL kg-1 min-1, mean +/- SD) were divided into normal (NORM, n=12, SaO2= 93.9 +/- 0.8) or low (LOW, n=6, SaO2=90.3 +/- 1.0) group, based on significantly different peak exercise SaO2 values (P < 0.05). All other descriptive and physiological characteristics were similar between the groups. Subjects performed a ramped cycle test to exhaustion breathing NO-free gas. The concentration (CNO) and production rate (VNO) of NO were determined from mixed gas samples at rest and during exercise at 100, 200, 250, 300, 350, 400 and 450 W using a chemiluminescent analyser. CNO remained unchanged from resting values in all subjects. VNO increased significantly during exercise in all subjects but was not different between LOW and NORM groups. The correlation between change in SaO2 and VNO from rest to maximal exercise was not significant (r=-0.12, P > 0.05). Collectively, these data suggest that exhaled NO is not related to decreased SaO2 during heavy exercise in highly trained male cyclists.
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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) | 0.000 | 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) | 0.001 | 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".