Animal models of cigarette smoke-induced chronic obstructive pulmonary disease
Bibliographic record
Abstract
Chronic exposure of laboratory animals to cigarette smoke reproduces many of the anatomic/physiologic lesions (emphysema, small-airway remodeling and pulmonary hypertension) of human chronic obstructive pulmonary disease, although smoke-exposed laboratory animals are not good models of chronic bronchitis or acute exacerbations, as these are conditions based upon symptoms that are not recapitulated in animals. Many types of antiproteolytic and anti-inflammatory interventions, such as use of drugs or genetic modifications, are highly effective in preventing emphysema in these models, and some also prevent small-airway remodeling and pulmonary hypertension. However, the few attempts to translate these therapies into humans have been unsuccessful, probably because the animal models typically start therapy from day 1 of smoke exposure, whereas most humans are treated late in the course of their disease. Recent data from our laboratory suggest that the parenchyma can repair smoke-induced damage for some period, but then switches to a mode where it fails to repair; these observations suggest that the timing of an intervention in humans may be crucial to its success. The various different anatomic lesions induced by smoke appear to be largely independent effects and 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".