Muscarinic Receptor Antagonism and Allergen Induced Airway Responses in Allergic Asthma: A Scoping Review
Bibliographic record
Abstract
PURPOSE: The purpose of this scoping review was to identify existing clinical and basic science knowledge surrounding the effect of muscarinic receptor antagonism on allergen-induced airway responses to inform future clinical research in this area. METHODS: Multiple advanced searches were performed using the National Library of Medicine PubMed search engine. Each search began with two terms; for example, "atropine and asthma" or "tiotropium and airway inflammation". Results were then further refined to include terms such as "allergen" or "ovalbumin (OVA)". Abstracts of refined searches were reviewed for relevance to allergic asthma and allergen-induced airway responses including the early and late asthmatic responses, airway inflammation and tissue remodelling. There was no restriction regarding publication date. Reference lists of selected papers were also reviewed for relevant publications. RESULTS: Nine human clinical trial publications and fourteen animal model publications were identified. In humans, single dose atropine (n=4), ipratropium (n=4) or oxitropium (n=1) administered pre-challenge produced equivocal effects on allergen-induced early asthmatic responses as reported but favored inhibition in eight of nine studies after re-analyses. Animal model investigations (n=14) showed mostly favorable results, especially with respect to airway inflammation and tissue remodelling, although two studies were negative, and one study showed a worsening in allergen induced airway inflammation following muscarinic receptor antagonism. CONCLUSION: Existing human and animal model data suggest muscarinic receptor antagonism may be beneficial in preventing allergen induced airway responses in those with allergic asthma. Additional human research utilizing current standardized methodologies is required.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".