Cigarette Smoke Inhibits Human Bronchial Epithelial Cell Repair Processes
Bibliographic record
Abstract
By interfering with the ability of airway epithelial cells to support repair processes, cigarette smoke could contribute to alterations of airway structures and functions that characterize chronic obstructive pulmonary disease (COPD). The current study assessed the ability of cigarette smoke extract (CSE) to alter human airway epithelial cell chemotaxis, proliferation, and contraction of three-dimensional collagen gels, a model of extracellular matrix remodeling. The volatile components contained in cigarette smoke, acetaldehyde and acrolein, were able to inhibit all three processes. Nonvolatile components contained within lyophilized CSE also inhibited chemotaxis but displayed no activity in the other two bioassays. CSE also inhibited the ability of airway epithelial cells to release transforming growth factor (TGF)-beta and fibronectin. Exogenous fibronectin was unable to restore epithelial cell contraction of collagen gels. Exogenous TGF-beta partially restored the ability of airway epithelial cells to contract collagen gels and to produce fibronectin. This supports a role for inhibition of TGF-beta release in mediating the inhibitory effects of cigarette smoke. Taken together, the results of the current study suggest that epithelial cells present in the airways of smokers may be altered in their ability to support repair responses, which may contribute to architectural disruptions present in the airways in COPD associated with cigarette smoking.
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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 | 0.000 |
| 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".