Sex Differences in Airway Remodeling in a Mouse Model of Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: After adjustment for the amount of smoking, women have a 50% increased risk of chronic obstructive pulmonary disease (COPD) compared with men. The anatomic basis and/or mechanism(s) of these sex-related differences in COPD are unknown. OBJECTIVES: To characterize the impact of female sex hormones on chronic cigarette smoke-induced airway remodeling and emphysema in a mouse model of COPD. METHODS: Airway remodeling and emphysema were determined morphometrically in male, female, and ovariectomized mice exposed to 6 months of cigarette smoke. Antioxidant- and transforming growth factor (TGF)-β-related genes were profiled in airway tissues. The selective estrogen receptor modulator tamoxifen was also administered during smoke exposure in a short-term model. Airway wall thickness of male and female human smokers at risk of or with mild COPD was measured using optical coherence tomography. MEASUREMENTS AND MAIN RESULTS: Small airway wall remodeling was increased in female but not male or ovariectomized mice and was associated with increased distal airway resistance, down-regulation of antioxidant genes, increased oxidative stress, and activation of TGF-β1. These effects were prevented by ovariectomy. Use of tamoxifen as a therapeutic intervention mitigated smoke-induced increase in oxidative stress in female mice. Compared with male human smokers, female human smokers had significantly thicker airway walls. CONCLUSIONS: The excess risk of small airway disease in female mice after chronic smoke exposure was associated with increased oxidative stress and TGF-β1 signaling and also was related to the effects of female sex hormones. Estrogen receptor antagonism might be of value in reducing oxidative stress in female smokers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".