Protein Tyrosine Phosphatase α Mediates Profibrotic Signaling in Lung Fibroblasts through TGF-β Responsiveness
Bibliographic record
Abstract
Fibrotic lung diseases represent a diverse group of progressive and often fatal disorders with limited treatment options. Although the pathogenesis of these conditions remains incompletely understood, receptor type protein tyrosine phosphatase α (PTP-α encoded by PTPRA) has emerged as a key regulator of fibroblast signaling. We previously reported that PTP-α regulates cellular responses to cytokines and growth factors through integrin-mediated signaling and that PTP-α promotes fibroblast expression of matrix metalloproteinase 3, a matrix-degrading proteinase linked to pulmonary fibrosis. Here, we sought to determine more directly the role of PTP-α in pulmonary fibrosis. Mice genetically deficient in PTP-α (Ptpra(-/-)) were protected from pulmonary fibrosis induced by intratracheal bleomycin, with minimal alterations in the early inflammatory response or production of TGF-β. Ptpra(-/-) mice were also protected from pulmonary fibrosis induced by adenoviral-mediated expression of active TGF-β1. In reciprocal bone marrow chimera experiments, the protective phenotype tracked with lung parenchymal cells but not bone marrow-derived cells. Because fibroblasts are key contributors to tissue fibrosis, we compared profibrotic responses in wild-type and Ptpra(-/-) mouse embryonic and lung fibroblasts. Ptpra(-/-) fibroblasts exhibited hyporesponsiveness to TGF-β, manifested by diminished expression of αSMA, EDA-fibronectin, collagen 1A, and CTGF. Ptpra(-/-) fibroblasts exhibited markedly attenuated TGF-β-induced Smad2/3 transcriptional activity. We conclude that PTP-α promotes profibrotic signaling pathways in fibroblasts through control of cellular responsiveness to TGF-β.
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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) | 0.002 | 0.001 |
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".