Comparison between conventional and "clinical" assessment of experimental lung fibrosis
Bibliographic record
Abstract
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a treatment resistant disease with poor prognosis. Numerous compounds have been demonstrated to efficiently prevent pulmonary fibrosis (PF) in animal models but only a few were successful when given to animals with established fibrosis. Major concerns of current PF models are spontaneous resolution and high variability of fibrosis, and the lack of assessment methods that can allow to monitor the effect of drugs in individual animals over time. We used a model of experimental PF in rats and compare parameters obtained in living animals with conventional assessment tools that require removal of the lungs. METHODS: PF was induced in rats by adenoviral gene transfer of transforming growth factor-beta. Morphological and functional changes were assessed for up to 56 days by micro-CT, lung compliance (measured via a mechanical ventilator) and VO2max and compared to histomorphometry and hydroxyproline content. RESULTS: Standard histological and collagen assessment confirmed the persistent fibrotic phenotype as described before. The histomorphological scores correlated both to radiological (r2 = 0.29, p < 0.01) and functional changes (r2 = 0.51, p < 0.0001). VO2max did not correlate with fibrosis. CONCLUSION: The progression of pulmonary fibrosis can be reliably assessed and followed in living animals over time using invasive, non-terminal compliance measurements and micro-CT. This approach directly translates to the management of patients with IPF and allows to monitor therapeutic effects in drug intervention studies.
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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 | 0.004 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".