The endothelial responses to low‐ and high‐intensity cycling with diesel exhaust exposure (1106.21)
Bibliographic record
Abstract
Outdoor exercisers are frequently exposed to air pollution. How the endothelium responds to exercise in air pollution, and how these responses change with exercise intensity is unknown. The purpose of this study was to determine the endothelial responses to low‐ and high‐intensity cycling with diesel exhaust (DE) exposure. Eighteen males aged 24.56.2 yrs performed 30‐minute trials of low (30% of power at VO 2peak ) and high‐intensity (60% of power at VO 2peak ) cycling, and rest. For each subject, each trial was performed once breathing filtered air (FA) and once breathing DE (300ug/m 3 of PM 2.5 ) for a total of six trials, each separated by 7‐days. Prior to, immediately following, and 1 hour, and 2 hours post‐exposure flow‐mediated dilation (FMD), plasma nitrite/nitrate (NOx), intercellular adhesion molecule (ICAM)‐1, and vascular cell adhesion molecule (VCAM)‐1 were measured. Data were analyzed using repeated‐measures ANOVA. There were no main or interaction effects for FMD. DE exposure did not affect plasma VCAM‐1. Compared to the FA exposure, DE led to lower ICAM‐1 levels following high‐intensity exercise (p<0.05), while plasma NOx was increased (p<0.05). DE exposure does not differentially affect FMD post‐exercise, yet there are significant differences in key biomarkers that warrant further investigation. Grant Funding Source : Supported by: CASEM, Health Canada, the Fraser Basin Council, NSERC
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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) | 0.000 | 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) | 0.002 | 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".