Brief Report: Fibrosis Caused by Loss of PTEN Expression in Mouse Fibroblasts Is Crucially Dependent on CCN2
Bibliographic record
Abstract
OBJECTIVE: Protein phosphatase and tensin homolog (PTEN) expression is reduced in dermal fibroblasts isolated from patients with diffuse cutaneous systemic sclerosis, a fibrotic autoimmune disease. In support of this finding, deletion of the PTEN gene in the dermal fibroblasts of mice has been shown to result in skin fibrosis and in vivo overexpression of connective tissue growth factor (CTGF; CCN2), a proadhesive matricellular protein; however, whether CCN2 is required for the fibrosis caused by loss of PTEN is unclear. This study was undertaken to investigate the role of CCN2 in fibrosis caused by reduced PTEN expression. METHODS: We generated conditional knockout mice in which PTEN was deleted in fibroblasts, either alone or in combination with CCN2. Skin samples were collected for histologic examination, immunohistochemical analysis, and collagen assay. RESULTS: Loss of CCN2 resulted in resistance to the increases in collagen production and myofibroblast recruitment that are caused by loss of PTEN. CCN2 deficiency did not impair Akt phosphorylation or the increases in the intensity of proliferating cell nuclear antigen staining that were caused by loss of PTEN. CONCLUSION: These data are consistent with the notion that CCN2 is required for particular aspects of the fibroproliferative response; therapeutic strategies blocking CCN2 may be of clinical benefit in combating fibrotic disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".