Cigarette smoke exposure aggravates air space enlargement and alveolar cell apoptosis in<i>Smad3</i>knockout mice
Bibliographic record
Abstract
The concept of genetic susceptibility factors predisposing cigarette smokers to develop emphysema stems from the clinical observation that only a fraction of smokers develop clinically significant chronic obstructive pulmonary disease. We investigated whether Smad3 knockout mice, which develop spontaneous air space enlargement after birth because of a defect in transforming growth factor-β (TGF-β) signaling, develop enhanced alveolar cell apoptosis and air space enlargement following cigarette smoke exposure. We investigated Smad3(-/-) and Smad3(+/+) mice at different adult ages and determined air space enlargement, alveolar cell proliferation, and apoptosis. Furthermore, laser-capture microdissection and real-time PCR were used to measure compartment-specific gene expression. We then compared the effects of cigarette smoke exposure on Smad3(-/-) and littermate controls. Smad3 knockout resulted in the development of air space enlargement in the adult mouse and was associated with decreased alveolar VEGF levels and activity and increased alveolar cell apoptosis. Cigarette smoke exposure aggravated air space enlargement and alveolar cell apoptosis. We also found increased Smad2 protein expression and phosphorylation, which was enhanced following cigarette smoke exposure, in Smad3-knockout animals. Double immunofluorescence analysis revealed that endothelial apoptosis started before epithelial apoptosis. Our data indicate that balanced TGF-β signaling is not only important for regulation of extracellular matrix turnover, but also for alveolar cell homeostasis. Impaired signaling via the Smad3 pathway results in alveolar cell apoptosis and alveolar destruction, likely via increased Smad2 and reduced VEGF expression and might represent a predisposition for accelerated development of emphysema due to cigarette smoke 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".