Lower airway inflammatory responses to repeated very‐low‐dose allergen challenge in allergic rhinitis and asthma
Bibliographic record
Abstract
BACKGROUND: Low-dose allergen challenge (LDAC) may be a useful tool for studying the capacity of allergens to induce airway inflammation in atopic subjects. OBJECTIVE: To evaluate lower airway inflammatory changes following repeated inhalation of very low doses of allergen (VLDAC) in non-asthmatic subjects with allergic rhinitis (NAAR) compared with mild allergic asthmatic subjects (AA). METHODS: Fourteen NAAR and 11 AA were seen out of the pollen season and had skin prick tests with common aeroallergens. Baseline spirometry (S) and methacholine challenge (MC) were done and blood and induced sputum (IS) differential cell counts were obtained. Each subject underwent VLDAC on four consecutive mornings with a relevant allergen. S, MC, and blood and IS samplings were repeated 6 h after the second and fourth VLDAC and one week later. RESULTS: Although there were, as expected, no changes in FEV1 or PC20 in either group, mean percentage eosinophils on IS were significantly increased in NAAR on day 2 of VLDAC and decreased in all but one subject on day 4, with a tendency to return to baseline levels one week later. In AA, there was a non-significant trend for sputum eosinophils to increase on day 2; four subjects showed a decrease of eosinophils on day 4 of VLDAC. There was a correlation between eosinophil cationic protein (ECP) levels and eosinophil counts in NAAR throughout the study. There were no variations in other sputum cells or blood inflammatory cells. CONCLUSION: VLDAC can increase the percentage of eosinophils in IS of NAAR subjects without associated respiratory symptoms nor physiological modifications. A reduction in eosinophilic response despite repeated exposure, more common in NAAR subjects, suggests an adaptation process that needs to be further evaluated.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".