α1-Antitrypsin Determines the Pattern of Emphysema and Function in Tobacco Smoke–exposed Mice: Parallels with Human Disease
Bibliographic record
Abstract
Cigarette smoking in humans is associated with various patterns of emphysema and functional consequences. We tested the hypothesis that variations in alpha1-antitrypsin expression modulate the pattern of emphysema and functional consequences in cigarette smoke-exposed mice. We compared the effects of up to 6 months of cigarette smoke exposure in C57BL/6J (C57) mice and in low-alpha1-antitrypsin, C57BL/6J pa+/pa+ (pallid) mice. At the end of the experiment, we determined lung mechanical properties, the extent (mean linear intercept) and type of emphysema, and the cellular inflammatory response. After 4 months of cigarette smoking, pallid smoking mice, but not C57 smoking mice, had a significant increase in mean linear intercept. After 6 months of smoke exposure, C57 smoking mice and pallid smoking mice had similar degrees of emphysema. The pattern of emphysema in pallid smoking mice was more diffuse than in C57 smoking mice, affecting all airspaces. Pallid mice, but not C57 mice, developed a T cell inflammation in the alveolar wall after 6 months of smoking (p < 0.01). Although lung compliance was not changed in C57 smoking mice after smoke exposure, it increased significantly in pallid smoking mice over the 6 months of exposure (p < 0.0082). In summary, cigarette smoking induces emphysema in C57 and pallid mice, but the emphysema, inflammatory infiltrate, and resulting physiologic abnormalities were substantially different in the two strains, with the C57 and pallid mice exhibiting features similar to centrilobular and panlobular emphysema, respectively.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".