Loss of peroxisome proliferator–activated receptor γ in mouse fibroblasts results in increased susceptibility to bleomycin‐induced skin fibrosis
Bibliographic record
Abstract
OBJECTIVE: There is increasing evidence that the transcription factor peroxisome proliferator-activated receptor gamma (PPARgamma) plays an important role in controlling cell differentiation, and that PPARgamma ligands can modify inflammatory and fibrotic responses. The aim of the present study was to examine the role of PPARgamma in a mouse model of skin scleroderma, in which mice bearing a fibroblast-specific deletion of PPARgamma were used. METHODS: Cutaneous sclerosis was induced by subcutaneous injection of bleomycin, while untreated control groups were injected with phosphate buffered saline. Mice bearing a fibroblast-specific deletion of PPARgamma were investigated for changes in dermal thickness, inflammation, collagen content, and the number of alpha-smooth muscle actin-positive cells. The quantity of the collagen-specific amino acid hydroxyproline was also measured. In addition, the effect of PPARgamma deletion on transforming growth factor beta1 (TGFbeta1) signaling in the fibroblasts was investigated. RESULTS: Bleomycin treatment induced marked cutaneous thickening and fibrosis in all treated mice. Deletion of PPARgamma resulted in enhanced susceptibility to bleomycin-induced skin fibrosis, as indicated by increases in all measures of skin fibrosis and enhanced sensitivity of fibroblasts to TGFbeta1 in PPAR-deficient mice. CONCLUSION: These results indicate that PPARgamma suppresses fibrogenesis. Specific agonists of PPARgamma may therefore alleviate the extent of the development of cutaneous sclerosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".