Influence of Natural Exposure to Pollens and Domestic Animals on Airway Responsiveness and Inflammation in Sensitized Non-Asthmatic Subjects
Bibliographic record
Abstract
BACKGROUND: Atopy may be a risk factor in the development of asthma. Indoor allergens are considered to be more potent asthma inducers than outdoor ones such as pollens. Lower airway inflammation may be present in non-asthmatic subjects during natural exposure to relevant allergens and may eventually lead to the development of asthma. AIMS: To document seasonal variation in lower airway responsiveness and inflammation in sensitized non-asthmatic subjects, during natural exposure to allergens, and to determine whether it is more marked in those exposed to animals to which they are sensitized. METHODS: Twenty-two atopic subjects were seen during and out of the pollen season. All (but the controls) were sensitized to domestic animals, and to trees, grasses or ragweed. Eleven were not exposed to animals at home and 8 were exposed. They were compared with 3 normal controls. A respiratory questionnaire was administered, allergy skin prick tests, spirometry, methacholine challenge, blood and induced sputum with differential cell counts were obtained during the pollen season for all subjects. These tests were repeated out of the pollen season. RESULTS: Throughout the study, none of the subjects had asthma symptoms. Mean PC(20) was significantly lower in subjects exposed to animals compared with unexposed subjects or controls, both during and out of the pollen season. In season, subjects exposed to animals had significantly higher sputum eosinophil numbers than unexposed or normal control subjects. CONCLUSIONS: Non-asthmatic atopic subjects show variable degrees of airway responsiveness and inflammation. However, subjects exposed to animals show higher airway eosinophilia, which may suggest they are at increased risk of developing airway hyperresponsiveness and asthma.
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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 | 0.000 | 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) | 0.002 | 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".