IL-9 Governs Allergen-induced Mast Cell Numbers in the Lung and Chronic Remodeling of the Airways
Bibliographic record
Abstract
RATIONALE: IL-9 is a pleiotropic cytokine that has multiple effects on structural as well as numerous hematopoietic cells, which are central to the pathogenesis of asthma. OBJECTIVES: The contribution of IL-9 to asthma pathogenesis has thus far been unclear, due to conflicting reports in the literature. These earlier studies focused on the role of IL-9 in acute inflammatory models; here we have investigated the effects of IL-9 blockade during chronic allergic inflammation. METHODS: Mice were exposed to either prolonged ovalbumin or house dust mite allergen challenge to induce chronic inflammation and airway remodeling. MEASUREMENTS AND MAIN RESULTS: We found that IL-9 governs allergen-induced mast cell (MC) numbers in the lung and has pronounced effects on chronic allergic inflammation. Anti-IL-9 antibody-treated mice were protected from airway remodeling with a concomitant reduction in mature MC numbers and activation, in addition to decreased expression of the profibrotic mediators transforming growth factor-β1, vascular endothelial growth factor, and fibroblast growth factor-2 in the lung. Airway remodeling was associated with impaired lung function in the peripheral airways and this was reversed by IL-9 neutralization. In human asthmatic lung tissue, we identified MCs as the main IL-9 receptor expressing population and found them to be sources of vascular endothelial growth factor and fibroblast growth factor-2. CONCLUSIONS: Our data suggest an important role for an IL-9-MC axis in the pathology associated with chronic asthma and demonstrate that an impact on this axis could lead to a reduction in chronic inflammation and improved lung function in patients with 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) | 0.000 | 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".