CCN2 is required for bleomycin‐induced skin fibrosis in mice
Bibliographic record
Abstract
OBJECTIVE: No therapy for fibrotic disease is available. The proadhesive matricellular protein connective tissue growth factor CCN2 is a marker of fibrotic cells; however, the specific role of CCN2 in connective tissue biology in general and in fibrogenesis in particular is unclear. The aim of this study was to assess whether adult mice bearing a smooth muscle cell/fibroblast-specific deletion of CCN2 are resistant to bleomycin-induced skin scleroderma. METHODS: Cutaneous fibrosis was induced in mice by subcutaneous injection of bleomycin. Untreated control groups were injected with phosphate buffered saline. Mice bearing a fibroblast/smooth muscle cell-specific deletion of CCN2 were investigated for changes in dermal thickness, collagen content, and the number of α-smooth muscle actin (α-SMA)-positive cells. Dermal fibroblasts were isolated to assess whether the induction of collagen and α-SMA messenger RNA in response to transforming growth factor β (TGFβ) was impaired. RESULTS: The loss of CCN2 resulted in resistance to bleomycin-induced skin fibrosis. In response to bleomycin, wild-type mice possessed, but CCN2-deficient mice lacked, abundant α-SMA-expressing myofibroblasts within fibrotic lesions. Fibroblast responses to TGFβ, a potent inducer of myofibroblast differentiation, were not affected. Collectively, these results indicate that CCN2 is essential for bleomycin-induced skin fibrosis, likely due to a defect in myofibroblast recruitment. CONCLUSION: These data indicate that therapeutic strategies that involve blocking CCN2 in vivo may be of benefit in combating fibrotic skin disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".