Proteoglycans decorin and biglycan differentially modulate TGF-β-mediated fibrotic responses in the lung
Bibliographic record
Abstract
Transforming growth factor (TGF)-beta is a key cytokine in the pathogenesis of pulmonary fibrosis, and pharmacological interference with TGF-beta can ameliorate the fibrotic tissue response. The small proteoglycans decorin and biglycan are able to bind and inhibit TGF-beta activity in vitro. Although decorin has anti-TGF-beta properties in vivo, little is known about the physiological role of biglycan in vivo. Adenoviral gene transfer was used to overexpress active TGF-beta, decorin, and biglycan in cell culture and in murine lungs. Both proteoglycans were able to interfere with TGF-beta bioactivity in vitro in a dose-dependant manner. In vivo, overexpression of TGF-beta resulted in marked lung fibrosis, which was significantly reduced by concomitant overexpression of decorin. Biglycan, however, had no significant effect on lung fibrosis induced by TGF-beta. The data suggest that differences in tissue distribution are responsible for the different effects on TGF-beta bioactivity in vivo, indicating that decorin, but not biglycan, has potential therapeutic value in fibrotic disorders of the lung.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".