The modulation of large airway smooth muscle phenotype and effects of epidermal growth factor receptor inhibition in the repeatedly allergen-challenged rat
Bibliographic record
Abstract
Allergen challenges induce airway hyperresponsiveness (AHR) and increased airway smooth muscle (ASM) mass in the sensitized rat. Whether the remodeled ASM changes its phenotype is uncertain. We examined, in sensitized Brown Norway rats, the effects of multiple ovalbumin (Ova) challenges on ASM remodeling and phenotype and the role of the epidermal growth factor receptor (EGFR) in these processes. Rats were sensitized with Ova and challenged three times at 5-day intervals with phosphate-buffered saline or Ova and pretreated with the EGFR inhibitor AG-1478 (5 mg/kg) or its vehicle dimethyl sulfoxide. Ova challenges increased ASM mass in all-sized airways and in large airway mRNA expression of smooth muscle myosin heavy chain (sm-MHC), assessed by laser capture. Myosin light chain kinase and the fast myosin isoform SM-B mRNA expressions were not affected. Ova induced AHR to methacholine, and, based on the constant-phase model, this was largely attributable to the small airways and lung derecruitment at 48 h that recovered by 1 wk. The EGFR ligands amphiregulin and heparin-binding epidermal growth factor (HB-EGF) were increased in bronchoalveolar lavage fluid at 48 h after Ova exposure. AG-1478 inhibited AHR and prevented ASM growth. Epithelial gene expression of EGFR, HB-EGF, matrix metalloproteinase (MMP)-9, Gro-α, and transforming growth factor-β was unaffected by Ova challenges. We conclude that EGFR drives remodeling of ASM, which results from repeated Ova challenge. Furthermore, the latter results in excessive small airway and, to a lesser degree, large airway narrowing to methacholine, and large airway gene expression of contractile protein is conserved.
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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) | 0.001 | 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".