Transient Transgene Expression of Decorin in the Lung Reduces the Fibrotic Response to Bleomycin
Bibliographic record
Abstract
Pulmonary fibrosis is a chronic progressive disease with no effective therapy. Transforming growth factor beta (TGF-beta) is thought to be a key profibrotic mediator and blocking its activity is therefore one of the targets of new treatment strategies for fibrosis. Decorin is an endogenous proteoglycan and one of the known inhibitors of TGF-beta. The short half-life of peptide-based therapeutics makes gene transfer a promising approach to achieve prolonged protein levels in the lung. Replication-deficient adenovirus was used to deliver decorin transgene (AdDec) to the airways by a single intranasal injection in a murine bleomycin model of lung fibrosis. The ability of vector-derived decorin to inhibit TGF-beta was examined in a bioassay and its effect on bleomycin-induced pulmonary fibrosis was determined by histomorphology and lung hydroxyproline. In vitro, supernatant from cells infected with AdDec abrogated the bioactivity of TGF-beta in a dose-dependent manner whereas control virus (AdDL70) had no effect. In vivo, treatment of bleomycin-injected mice with AdDec substantially reduced the fibrogenic response compared with control virus (hydroxyproline: bleomycin/AdDec, 1.96 microg/mg; bleomycin/AdDL70, 3.05 microg/mg; p = 0.0005). These results suggest that a single administration of AdDec was able to generate a local pulmonary environment that effectively blocked the fibrogenic response to bleomycin by inhibition of TGF-beta.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".