Animal models of<scp>COPD</scp>:<scp>W</scp>hat do they tell us?
Bibliographic record
Abstract
COPD is a major cause of global mortality and morbidity but current treatments are poorly effective. This is because the underlying mechanisms that drive the development and progression of COPD are incompletely understood. Animal models of disease provide a valuable, ethically and economically viable experimental platform to examine these mechanisms and identify biomarkers that may be therapeutic targets that would facilitate the development of improved standard of care. Here, we review the different established animal models of COPD and the various aspects of disease pathophysiology that have been successfully recapitulated in these models including chronic lung inflammation, airway remodelling, emphysema and impaired lung function. Furthermore, some of the mechanistic features, and thus biomarkers and therapeutic targets of COPD identified in animal models are outlined. Some of the existing therapies that suppress some disease symptoms that were identified in animal models and are progressing towards therapeutic development have been outlined. Further studies of representative animal models of human COPD have the strong potential to identify new and effective therapeutic approaches for COPD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".