Serum and sputum MMP-9/TIMP-1 in winter sports athletes and swimmers: relationships with airway function
Bibliographic record
Abstract
Abstract Introduction Cross-country skiers and swimmers present characteristics of airway inflammation and remodeling of the extracellular matrix similar to what is observed in mild asthma. We aimed to compare serum and sputum MMP-9/TIMP-1 levels, to assess the balance between airway fibrogenesis and inflammation process in both categories of athletes, and to observe its seasonal variations in winter sports athletes. Methods Competitive winter sports athletes (n=41), swimmers (n=25) and healthy nonathletes (n=10) had blood sampling, lung function measurement, skin prick tests, eucapnic voluntary hyperpnea challenge, methacholine inhalation test (MIT), and induced sputum analysis. Twelve winter sport athletes performed the test during both summer and winter. Serum and sputum MMP-9 and TIMP-1 were measured by ELISA. Results No significant difference in serum or sputum MMP-9/TIMP-1 ratio was observed between groups, nor relationship with airway function or responsiveness. Serum MMP-9/TIMP-1 ratio was significantly higher during the summer in winter sport athletes compared with winter season (median [Interquartile range]: 3.65 [2.47-4.03] ng.ml -1 and 1.27 [0.97-1.62] ng.ml -1 , respectively, p=0.005). Sputum MMP-9 correlated with Methacholine PC 20 and serum CC16/SP-D ratio. Conclusion MMP-9/TIMP-1 ratio in sputum or serum may fluctuate with training or environment but does not correlate with airway lung function or responsiveness in competitive athletes.
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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 | 0.001 | 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".