Airway Remodeling in the Smoke Exposed Guinea Pig Model
Bibliographic record
Abstract
Although small airway remodeling (SAR) leading to airflow obstruction is a common consequence of human cigarette smoking, the airways have been largely ignored in animal models of chronic obstructive pulmonary disease (COPD). We examined lung structure in a guinea pig model of chronic cigarette smoke exposure to ascertain whether smoke induced SAR, and to evaluate how these anatomic lesions correlate with physiologic changes. We used tissue from guinea pigs exposed to cigarette smoke or air for 6 mo. Pulmonary function tests were performed, and histologic sections were prepared. Airspace size (Lm) and changes in the structure of the small airways were evaluated by morphometric analysis. Chronic smoke exposure was associated with increased airway wall thickness and increased amounts of thick collagen fibers in the walls of the small airways, as well as with increased Lm. The increase in thick collagen fibers related negatively to peak expiratory volume (PEF) and the ratio of forced expiratory volume in 1 s to forced ventilatory capacity (FEV(0.1)/FVC), and positively to airway resistance. Physiologic lung volumes were predicted by airspace size, but residual volume (RV) and total lung capacity (TLC) also were related to airway wall thickness. Amounts of smooth muscle were not changed and did not predict any physiologic abnormalities. We conclude that cigarette smoke exposure results in SAR in the guinea pig, alterations that are reflected in increased airways resistance with diminished airflow and air trapping, mimicking human disease. This model should prove useful in further investigations into the mechanisms of airway remodeling.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".