Allergen Inhalation Challenge: A Human Model of Asthma Exacerbation
Bibliographic record
Abstract
Allergen challenge by inhalation is a very useful clinical and research tool for evaluating allergic airway disease. Inhalation of allergen leads to cross-linking of allergen-specific IgE bound to IgE receptors on mast cells and basophils. This is followed by activation of secretory pathways to release preformed and newly generated mediators of bronchoconstriction and vascular permeability. The onset of bronchoconstriction, representing the early phase of the asthmatic response, can be detected within 10 min of the inhalation, reaches a maximum within 30 min, and resolves within 3 h. The late-phase asthmatic response starts between 4 and 8 h, and is characterized by cellular inflammation of the airway, increased bronchiovascular permeability, and mucus secretion. The late-phase asthmatic response is also associated with increased airway responsiveness to nonallergic stimuli. Approximately half of the allergic asthmatic patients develop a late-phase response after allergen inhalation challenge. There has been a tremendous interest in trying to understand the differences between the pathways leading to the dual response and those leading to the early response alone. The current hypotheses are discussed in this chapter. Our understanding of the allergen inhalation challenge model and the complex interplay between leukocytes, tissue and inflammatory mediators will doubtlessly help to define novel and relevant targets for new drugs for the treatment of allergic 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".