Mechanisms of cigarette smoke-induced COPD: insights from animal models
Bibliographic record
Abstract
Cigarette smoke-induced animal models of chronic obstructive pulmonary disease support the protease-antiprotease hypothesis of emphysema, although which cells and proteases are the crucial actors remains controversial. Inhibition of either serine or metalloproteases produces significant protection against emphysema, but inhibition is invariably accompanied by decreases in the inflammatory response to cigarette smoke, suggesting that these inhibitors do more than just prevent matrix degradation. Direct anti-inflammatory interventions are also effective against the development of emphysema, as are antioxidant strategies; the latter again decrease smoke-induced inflammation. There is increasing evidence for autoimmunity, perhaps directed against matrix components, as a driving force in emphysema. There is intriguing but controversial animal model evidence that failure to repair/failure of lung maintenance also plays a role in the pathogenesis of emphysema. Cigarette smoke produces small airway remodeling in laboratory animals, possibly by direct induction of fibrogenic growth factors in the airway wall, and also produces pulmonary hypertension, at least in part through direct upregulation of vasoactive mediators in the intrapulmonary arteries. Smoke exposure causes goblet cell metaplasia and excess mucus production in the small airways and proximal trachea, but these changes are not good models of either chronic bronchitis or acute exacerbations. Emphysema, small airway remodeling, pulmonary hypertension, and mucus production appear to be at least partially independent processes that may require different therapeutic approaches.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".