The role of interleukin‐4Rα in the induction of glutamic acid decarboxylase in airway epithelium following acute house dust mite exposure
Bibliographic record
Abstract
Background Asthma is a disease characterized by airway inflammation, remodelling and dysfunction. Airway inflammation contributes to remodelling, a term that is used to describe structural changes including goblet cell metaplasia (GCM), matrix deposition, and smooth muscle hyperplasia/hypertrophy. GCM has been implicated in asthma mortality by contributing to mucus plugs and leading to asphyxiation. In animal models, this process is highly dependent on IL-13. Recently, we have described an IL-13-dependent up-regulation of a GABAergic signalling system in airway epithelium that contributes to GCM. The mechanism by which IL-13 up-regulates GABA signalling in airway epithelium is unknown. Objectives To test the hypothesis that IL-4Ralpha signalling is required for allergen induced up-regulation of GABAergic signalling and GCM. Methods BALB/c mice were exposed to an acute house dust mite (HDM) protocol and received vehicle, anti-IL-4Ralpha-monoclonal antibody, or control antibody. Outcomes included airway responses to inhaled methacholine (MCh), histology for eosinophilia and GCM, phosphorylated STAT6 levels using immunohistochemistry and immunoblot, and glutamic acid decarboxylase (GAD) 65/67 and GABA(A)beta(2/3) receptor subunit expression using confocal microscopy. Results Acute HDM exposure resulted in increased airway responses to MCh, lung eosinophilia, STAT6 phosphorylation, elevations in GAD65/67 and GABA(A)beta(2/3) receptor expression, and GCM that were inhibited with anti-IL-4Ralpha-monoclonal treatment. Control antibody had no effect. Conclusion The IL-4Ralpha is required for allergen-induced up-regulation of a GABAergic system in airway epithelium implicated in GCM following acute HDM exposure.
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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) | 0.000 | 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 | 0.001 |
| 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".