The pulmonary and autonomic effects of high-intensity and low-intensity exercise in diesel exhaust
Bibliographic record
Abstract
BACKGROUND: Exposure to air pollution impairs aspects of pulmonary and autonomic function and causes pulmonary inflammation. However, how exercising in air pollution affects these indices is poorly understood. Therefore, the purpose of this study was to determine the effects of low-intensity and high-intensity cycling with diesel exhaust (DE) exposure on pulmonary function, heart rate variability (HRV), fraction of exhaled nitric oxide (FeNO), norepinephrine and symptoms. METHODS: , six trials in total). Pulmonary function, FeNO, HRV, norepinephrine and symptoms were measured prior to, immediately post, 1 h and 2 h post-exposure. Data were analyzed using repeated-measures ANOVA. RESULTS: Throat and chest symptoms were significantly greater immediately following DE exposure than following FA (p < 0.05). FeNO significantly increased 1 h following high-intensity exercise in DE (21.9 (2.4) vs. 19.3 (2.2) ppb) and FA (22.7 (1.7) vs. 19.9 (1.4)); however, there were no differences between the exposure conditions. All HRV indices significantly decreased following high-intensity exercise (p < 0.05) in DE and FA. The exception to this pattern was LF (nu) and LF/HF ratio, which significantly increased following high-intensity exercise (p < 0.05). Plasma norepinephrine (NE) significantly increased following high-intensity exercise in DE and FA, and this increase was greater than following rest and low-intensity exercise (p < 0.05). DE exposure did not modify any effects of exercise intensity on HRV or norepinephrine. CONCLUSIONS: Healthy individuals may not experience greater acute pulmonary and autonomic effects from exercising in DE compared to FA; therefore, it is unclear if such individuals will benefit from reducing vigorous activity on days with high concentrations on particulate matter.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".