Transforming Growth Factor-β Regulates House Dust Mite–induced Allergic Airway Inflammation but Not Airway Remodeling
Bibliographic record
Abstract
RATIONALE: It is now believed that both chronic airway inflammation and remodeling contribute significantly to airway dysfunction and clinical symptoms in allergic asthma. Transforming growth factor (TGF)-beta is a powerful regulator of both the tissue repair and inflammatory responses, and numerous experimental and clinical studies suggest that it may play an integral role in the pathogenesis of asthma. OBJECTIVES: We investigated the role of TGF-beta in the regulation of allergic airway inflammation and remodeling using a mouse model of house dust mite (HDM)-induced chronic allergic airway disease. METHODS: We have previously shown that intranasal administration of an HDM extract (5 d/wk for 5 wk) elicits robust Th2-polarized airway inflammation and remodeling that is associated with increased airway hyperreactivity. Here, Balb/c mice were similarly exposed to HDM and concurrently treated with a pan-specific TGF-beta neutralizing antibody. MEASUREMENTS AND MAIN RESULTS: We observed that anti-TGF-beta treatment in the context of either continuous or intermittent HDM exposure had no effect on the development of HDM-induced airway remodeling. To further confirm these findings, we also subjected SMAD3 knockout mice to 5 weeks of HDM and observed that knockout mice developed airway remodeling to the same extent as HDM-exposed littermate controls. Notably, TGF-beta neutralization exacerbated the eosinophilic infiltrate and led to increased airway hyperreactivity. CONCLUSIONS: Collectively, these data suggest that TGF-beta regulates HDM-induced chronic airway inflammation but not remodeling, and furthermore, caution against the use of therapeutic strategies aimed at interfering with TGF-beta activity in the treatment of this disease.
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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".