Relationship between cutaneous allergen response and airway allergen‐induced eosinophilia
Bibliographic record
Abstract
BACKGROUND: Determinants of changes in airway caliber after allergen challenge include nonallergic airway responsiveness, immune response and dose of allergen given. However, determinants of the airway inflammatory response to allergens remain to be determined. AIM: To assess the relationship between skin reactivity to airborne allergens and lower airway eosinophilic response to allergen exposure in asthma and allergic rhinitis. METHODS: Forty-two subjects with mild allergic asthma (mean age 24 years) and 14 nonasthmatic subjects with allergic rhinitis (mean age 25 years) had allergen skin prick tests and titration with the allergen chosen for subsequent challenge. On a second visit, 31 asthmatic subjects had a conventional challenge while 11 asthmatic subjects and all rhinitic subjects had a low-dose allergen challenge over four subsequent days. Induced sputum samples were obtained at 6 and 24 h after the conventional challenge and at days 2 and 4 of the low-dose challenge. RESULTS: In the asthmatic group, there was a weak correlation between wheal diameter induced by the concentration used for challenge and increase in eosinophils 6 h postconventional challenge (r = 0.372, P = 0.05), but no correlation was observed following the low-dose challenge. Rhinitic subjects showed a correlation between wheal diameter with the allergen dose used for bronchoprovocation and increase in eosinophils at day 2 of low dose (r = 0.608, P = 0.02). CONCLUSION: This study suggests that immediate immune responsiveness to allergen, assessed by the magnitude of the skin response, is a significant determinant of allergen-induced airway eosinophilia and can help to predict the airway inflammatory response.
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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 | 0.002 |
| 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) | 0.004 | 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".