Negative Regulation of Myofibroblast Differentiation by PTEN (Phosphatase and Tensin Homolog Deleted on Chromosome 10)
Bibliographic record
Abstract
RATIONALE: Myofibroblasts are primary effector cells in idiopathic pulmonary fibrosis (IPF). Defining mechanisms of myofibroblast differentiation may be critical to the development of novel therapeutic agents. OBJECTIVE: To show that myofibroblast differentiation is regulated by phosphatase and tensin homolog deleted on chromosome 10 (PTEN) activity in vivo, and to identify a potential mechanism by which this occurs. METHODS: We used tissue sections of surgical lung biopsies from patients with IPF to localize expression of PTEN and alpha-smooth muscle actin (alpha-SMA). We used cell culture of pten(-/-) and wild-type fibroblasts, as well as adenoviral strategies and pharmacologic inhibitors, to determine the mechanism by which PTEN inhibits alpha-SMA, fibroblast proliferation, and collagen production. RESULTS: In human lung specimens of IPF, myofibroblasts within fibroblastic foci demonstrated diminished PTEN expression. Furthermore, inhibition of PTEN in mice worsened bleomycin-induced fibrosis. In pten(-/-) fibroblasts, and in normal fibroblasts in which PTEN was inhibited, alpha-SMA, proliferation, and collagen production was upregulated. Addition of transforming growth factor-beta to wild-type cells, but not pten(-/-) cells, resulted in increased alpha-SMA expression in a time-dependent fashion. In pten(-/-) cells, reconstitution of PTEN decreased alpha-SMA expression, proliferation, and collagen production, whereas overexpression of PTEN in wild-type cells inhibited transforming growth factor-beta-induced myofibroblast differentiation. It was observed that both the protein and lipid phosphatase actions of PTEN were capable of modulating the myofibroblast phenotype. CONCLUSIONS: The results indicate that in IPF, myofibroblasts have diminished PTEN expression. Inhibition of PTEN in vivo promotes fibrosis, and PTEN inhibits myofibroblast differentiation in vitro.
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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) | 0.002 | 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".