Air Pollution Relates to Airway Pathology in Children with Wheezing
Bibliographic record
Abstract
Abstract Rationale Outdoor air pollution contributes to asthma development and exacerbations, yet its effects on airway pathology have not been defined in children. Objectives To explore the possible link between air pollution and airway pathology, we retrospectively examined the relationship between environmental pollutants and pathological changes in bronchial biopsy specimens from children undergoing a clinically indicated bronchoscopy. Methods Structural and inflammatory changes (basement membrane [BM] thickness, epithelial loss, eosinophils, neutrophils, macrophages, mast cells, and lymphocytes) were quantified in biopsy specimens by using immunohistochemistry. The association between exposure to particulate matter less than 10 μm in aerodynamic diameter (PM10), SO2 and NO2 and biopsy findings was evaluated by using a generalized additive model with Gamma family to allow for overdispersion, adjusted for atmospheric pressure, temperature, humidity, and wheezing. Results Overall, 98 children were included (age 5.3 ± 2.9 yr; 53 with wheezing/45 without wheezing). BM thickness increased with prolonged exposure to PM10 (rate ratio [RR], 1.29; 95% confidence interval [CI], 1.09–1.52), particularly in children with wheezing. Prolonged exposure to PM10 was also associated with eosinophilic inflammation in children with wheezing (RR, 3.16; 95% CI, 1.35–7.39). Conversely, in children without wheezing, increased PM10 exposure was associated with a reduction of eosinophilic inflammation (RR, 0.12; 95% CI, 0.02–0.6) and neutrophilic inflammation (RR, 0.36; 95% CI, 0.14–0.89). Moreover, NO2 exposure was also linked to reductions in neutrophil infiltration (RR, 0.57; 95% CI, 0.34–0.93) and eosinophil infiltration (RR, 0.33; 95% CI, 0.14–0.77). Conclusions Different patterns of association were observed in children with wheezing and in children without wheezing. In children without wheezing, exposure to PM10 and NO2 was linked to reduced eosinophilic and neutrophilic inflammation. Conversely, in children with wheezing, prolonged exposure to PM10 was associated with increased BM thickness and eosinophilic inflammation, suggesting that it might contribute to asthma development by promoting airway remodeling and inflammation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".