Brief Report: CD109 Overexpression Ameliorates Skin Fibrosis in a Mouse Model of Bleomycin‐Induced Scleroderma
Bibliographic record
Abstract
OBJECTIVE: Transforming growth factor β (TGFβ) is a profibrotic cytokine, and its aberrant function is implicated in several types of fibrotic pathologies including scleroderma (systemic sclerosis [SSc]). Multiple lines of evidence show that increased TGFβ signaling contributes to progressive fibrosis in SSc by promoting fibroblast activation, excessive extracellular matrix (ECM) deposition, and dermal thickening. We have previously identified CD109 as a TGFβ coreceptor and have shown that it antagonizes TGFβ signaling and TGFβ-induced ECM expression in vitro in human keratinocytes and fibroblasts. The aim of the present study was to examine the ability of CD109 to prevent skin fibrosis in a mouse model of bleomycin-induced SSc. METHODS: Transgenic mice overexpressing CD109 in the epidermis and their wild-type (WT) littermates were injected with bleomycin in phosphate buffered saline (PBS) or with PBS alone every other day for 21 days or 28 days. Dermal thickness and collagen deposition were determined histologically using Masson's trichrome and picrosirius red staining. In addition, collagen and fibronectin content was analyzed using Western blotting, and activation of TGFβ signaling was examined by determining phospho-Smad2 and phospho-Smad3 levels using Western blotting and immunohistochemistry. RESULTS: Transgenic mice overexpressing CD109 in the epidermis showed resistance to bleomycin-induced skin fibrosis, as evidenced by a significant decrease in dermal thickness, collagen crosslinking, collagen and fibronectin content, and phospho-Smad2/3 levels, as compared to their WT littermates. CONCLUSION: Our findings suggest that CD109 inhibits TGFβ signaling and fibrotic responses in experimental murine scleroderma. They also suggest that CD109 regulates dermal-epidermal interactions to decrease extracellular matrix synthesis in the dermis. Thus, CD109 is a potential molecular target for therapeutic intervention in scleroderma.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".