CFTR dysfunction in smooth muscle drives TGFβ dependent airway hyperreactivity
Bibliographic record
Abstract
BACKGROUND: The primary underlying defect in cystic fibrosis (CF) is disrupted ion transport in epithelia throughout the body. It is unclear if symptoms such as airway hyperreactivity (AHR) and increased airway smooth muscle (ASM) volume in people with CF are due to inherent abnormalities in smooth muscle or are secondary to epithelial dysfunction. Transforming Growth Factor beta 1 (TGFβ) is an established genetic modifier of CF lung disease and a known driver of abnormal ASM function. Prior studies have demonstrated that CF mice develop greater AHR, goblet cell hyperplasia, and ASM hypertrophy after pulmonary TGFβ exposure. However, the mechanism driving these abnormalities in CF lung disease, specifically the contribution of CFTR loss in ASM, was unknown. METHODS: ; SM-Cre mice) were exposed to pulmonary TGFβ. The impact on lung pathology and physiology was investigated through examination of lung mechanics, Western blot analysis, and pulmonary histology. RESULTS: ; SM-Cre mice did not develop increased inflammation, ASM area, or goblet cell hyperplasia relative to controls following TGFβ exposure. CONCLUSIONS: These results demonstrate a direct smooth muscle contribution to CF airway obstruction mediated by TGFβ. Dysfunction in non-epithelial tissues should be considered in the development of CF therapeutics, including potential genetic therapies.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".