Does chronic physical activity level modify the airway inflammatory response to an acute bout of exercise in the postprandial period?
Bibliographic record
Abstract
Recent studies have confirmed that a single high-fat meal (HFM) leads to increased airway inflammation. However, exercise is a natural anti-inflammatory and may modify postprandial airway inflammation. The postprandial airway inflammatory response is likely to be modified by chronic physical activity (PA) level. This study investigated whether chronic PA modifies the airway inflammatory response to an acute bout of exercise in the postprandial period in both insufficiently active and active subjects. Thirty-nine nonasthmatic subjects (20 active, 13 males/7 females) who exceeded PA guidelines (≥150 min moderate-vigorous PA/week) and 19 insufficiently active (6 males/13 females) underwent an incremental treadmill test to exhaustion to determine peak oxygen uptake. Subjects were then randomized to a condition (COND), either remaining sedentary (CON) or exercising (EX) post-HFM. Exercise was performed at the heart rate corresponding to 60% peak oxygen uptake on a treadmill for 1 h post-HFM (63% fat, 10 kcal/kg body weight). Blood lipids and exhaled nitric oxide (eNO: marker of airway inflammation) were measured at baseline and 2 h and 4 h post-HFM. Sputum differential cell counts were performed at baseline and 4 h post-HFM. The mean eNO response for all groups increased at 2 h post-HFM (∼6%) and returned to baseline by 4 h (p = 0.03). There was a time × COND interaction (p = 0.04), where EX had a greater eNO response at 4 h compared with CON. Sputum neutrophils increased at 4 h post-HFM (p < 0.05). These findings suggest that airway inflammation occurs after an HFM when exercise is performed in the postprandial period, regardless of habitual activity level.
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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) | 0.001 | 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".