Glycosyltransferases and Glycosaminoglycans in Bleomycin and Transforming Growth Factor-β1–Induced Pulmonary Fibrosis
Bibliographic record
Abstract
Glycosaminoglycan (GAG) chains of proteoglycans (PGs) play important roles in fibrosis through cell-matrix interactions and growth factor binding in the extracellular matrix. We investigated the expression and regulation of PG core protein (versican) and key enzymes (xylosyltransferase [XT]-I, β1,3-glucuronosyltransferase [GlcAT]-I, chondroitin-4-sulfotransferase [C4ST]) implicated in synthesis and sulfation of GAGs in bleomycin (BLM) and adenovirus-transforming growth factor (TGF)-β1-induced lung fibrosis in rats. We also studied the role of GlcAT-I or TGF-β1 and the signaling pathways regulating PG-GAG production in primary lung fibroblasts isolated from saline- or BLM-instilled rats. The mRNA for XT-I, GlcAT-I, C4ST, and versican was increased in the lung 14 days after BLM injury. In vitro studies indicate that fibrotic lung fibroblasts (FLFs) expressed more XT-I, C4ST, and chondroitin sulfate (CS)-GAGs than did normal lung fibroblasts at baseline. TGF-β1 enhanced the expression of XT-I, C4ST-I, and versican in normal lung fibroblasts, whereas SB203580 or SB431542, by targeting p38 mitogen-activated protein kinase or TGF-β type-1 receptor/activin receptor-like kinase 5, respectively, attenuated the response to both TGF-β1 and FLFs on PG-GAG expression. Neutralizing anti-TGF-β1 antibody abrogated FLF-conditioned medium-stimulated expression of XT-I, GlcAT-I, versican, and CS-GAG. Forced expression of TGF-β1 in vivo enhanced versican, XT-I, GlcAT-I, and C4ST-I expression and PG-GAG deposition in rat lungs. Finally, induced expression of GlcAT-I gene in rat lung fibroblasts increased GAG synthesis by these cells. Together, our results provide new insights into the basis for increased PG-GAG deposition in lung fibrosis; inhibition of TGF-β1-mediated or fibrosis-induced PG-GAG production by activin receptor-like kinase 5/p38 inhibitors may contribute to antifibrotic activity.
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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".