Peroxisome proliferator‐activated receptor‐γ abrogates Smad‐dependent collagen stimulation by targeting the p300 transcriptional coactivator
Bibliographic record
Abstract
Ligands of peroxisome proliferator-activated receptor-gamma (PPAR-gamma) abrogate the stimulation of collagen gene transcription induced by transforming growth factor-beta (TGF-beta). Here, we delineate the mechanisms underlying this important novel physiological function for PPAR-gamma in connective tissue homeostasis. First, we demonstrated that antagonistic regulation of TGF-beta activity by PPAR-gamma ligands involves cellular PPAR-gamma, since 15-deoxy-Delta12,14-prostaglandin J(2) (15d-PGJ(2)) failed to block TGF-beta-induced responses in either primary cultures of PPAR-gamma-null murine embryonic fibroblasts, or in normal human skin fibroblasts with RNAi-mediated knockdown of PPAR-gamma. Next, we examined the molecular basis underlying the abrogation of TGF-beta signaling by PPAR-gamma in normal human fibroblasts in culture. The results demonstrated that Smad-dependent transcriptional responses were blocked by PPAR-gamma without preventing Smad2/3 activation. In contrast, the interaction between activated Smad2/3 and the transcriptional coactivator and histone acetyltransferase p300 induced by TGF-beta, and the accumulation of p300 on consensus Smad-binding DNA sequences and histone H4 hyperacetylation at the COL1A2 locus, were all prevented by PPAR-gamma. Wild-type p300, but not a mutant form of p300 lacking functional histone acetyltransferase, was able to restore TGF-beta-induced stimulation of COL1A2 in the presence of PPAR-gamma ligands. Collectively, these results indicate that PPAR-gamma blocked Smad-mediated transcriptional responses by preventing p300 recruitment and histone H4 hyperacetylation, resulting in the inhibition of TGF-beta-induced collagen gene expression. Pharmacological activation of PPAR-gamma thus may represent a novel therapeutic approach to target p300-dependent TGF-beta profibrotic responses such as stimulation of collagen gene expression.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".