Allergen inhalation challenge in smoking compared with non-smoking asthmatic subjects
Bibliographic record
Abstract
BACKGROUND: Smoking asthmatics experience more severe symptoms, require more rescue medication and have more asthma-related hospitalizations than non-smoking asthmatics. However, studies in mice suggest that mainstream cigarette smoke may reduce airway inflammation and may attenuate airway hyperresponsiveness. A comparison of allergen-induced airway inflammatory responses of smoking and non-smoking atopic asthmatics has not been examined previously. OBJECTIVES: To determine whether allergen-induced airway responses and inflammatory profiles are attenuated in smoking when compared with non-smoking mild allergic asthmatic subjects. METHODS: Allergen inhalation challenges were performed in 13 smoking and 19 non-smoking mild allergic asthmatic subjects. The forced expired volume in 1 s (FEV(1) ) was measured up to 7 h after allergen inhalation. Methacholine airway responsiveness was measured before and at 24 h after allergen and sputum was induced before and at 7 and 24 h after allergen. RESULTS: Both the smoking and non-smoking groups developed similar allergen-induced falls in FEV(1) during the early and late asthmatic responses and similar increases in allergen-induced airway eosinophils. The mean maximum fall in FEV(1) during the late response was 16.3 ± 4.3% in non-smokers and 12.9 ± 7.2% in smokers. The smoking asthmatics, however, did not develop allergen-induced methacholine airway hyperresponsiveness, whereas the non-smoking controls developed a 1.18 doubling dose shift in methacholine PC(20) (P < 0.05). CONCLUSIONS AND CLINICAL RELEVANCE: Mild allergic asthmatic subjects, who were current smokers with a mean 6-year pack history, develop allergen-induced eosinophilic airway inflammation and late responses, similar in magnitude to non-smoking asthmatics, but do not develop methacholine airway hyperresponsiveness associated with the allergen-induced airway eosinophilia.
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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 | 0.001 | 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".