Traffic‐related air pollution induces non‐allergic eosinophilic airway inflammation and cough hypersensitivity in guinea‐pigs
Bibliographic record
Abstract
BACKGROUND: The pathogenesis and pathophysiology of eosinophilia-related chronic cough such as non-asthmatic eosinophilic bronchitis and cough variant asthma are still not clear. OBJECTIVE: This study is to examine the potential role of traffic-related air pollution (TRAP) in eosinophilic inflammation and cough responses. METHODS: Non-sensitized guinea-pigs were exposed to TRAP in an urban traffic tunnel or kept in a filtered air environment for 7 or 14 days. Reflexive cough was measured using citric acid and allyl isothiocyanate (AITC) challenges, respectively. Spontaneous cough counting was determined using audio recording and a waveform analysis. Airway inflammation was evaluated using differential cells in bronchoalveolar lavage fluid (BALF) and lung histopathology. To further elucidate the relationship between airway inflammation and cough hypersensitivity, a subgroup of those exposed for 14 days received a dexamethasone treatment. RESULTS: Compared to reflexive cough count (mean (95% confidence interval) in 10 minutes) provoked by the AITC challenge for the unexposed animals (3.1 (1.7-4.5)), those were increased significantly following both the 7-day (12.0 (6.8-17.2), P < 0.01) and the 14-day (12.0 (6.4-17.6), P < 0.01) TRAP exposure. The effect provoked by the citric acid challenge was more profound following the 14-day exposure (26.0 (19.5-32.5) vs 3.8 (1.5-6.0) for the control, P < 0.001). TRAP exposures enhanced spontaneous cough events, caused a significant increase of eosinophils and neutrophils in BALF and resulted in a dramatic eosinophilic infiltration in submucosal layer of trachea and bronchus, which can be inhibited significantly by dexamethasone treatment. CONCLUSIONS & CLINICAL RELEVANCE: TRAP exposures induced cough hypersensitivity and non-allergic eosinophilic inflammation of airways in guinea-pigs. This study highlights the potential mechanisms of eosinophilia-related chronic cough that can be induced by traffic-related air pollution.
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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 | 0.001 |
| 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 | 0.001 | 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".