Use of mouse models of allergic rhinitis to study the upper and lower airway link
Bibliographic record
Abstract
PURPOSE OF REVIEW: Allergic rhinitis and asthma are examples of a continuum of airway diseases with diverse clinical manifestations. This review examines the most recent work in mouse models studying upper and lower airway links and interactions. RECENT FINDINGS: The concept of united airways has been supported by investigative and epidemiological studies. Studies using mouse models of asthma and models of allergic rhinitis have demonstrated that analogous pathways lead to inflammation and airway hyperresponsiveness. Th2-type T cells and IL-13 play important immunopathologic roles. Recent studies have examined upper airway mucosal immune responses and development of both allergic and tolerant phenotypes. In a model of allergic airways disease, there is evidence of lower airway inflammation and airways hyperresponsiveness following application of allergen only to the nares, suggesting local stimulation can activate distal allergic responses. Immunomodulatory properties of the airway mucosa have also been explored. Allergen-specific tolerance can be induced by appropriate stimulation of airway mucosa and is associated with activation of IL-10-producing T cells. This effect is mediated by antigen presenting cells, especially dendritic cells. SUMMARY: Immune stimulation of the airway mucosa, both in the upper and lower airways, results in active T-cell-mediated immune responses leading toward tolerance or asthma and allergic rhinitis. Regulation of these T-cell responses is currently under investigation. It is clear from these studies that antigenic stimulation of any part of the respiratory mucosa can have ripple effects along the entire airway and supports the concept of united airways.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".