Regulation of CCN2 mRNA expression and promoter activity in activated hepatic stellate cells
Bibliographic record
Abstract
The matricellular protein connective tissue growth factor (CCN2) is considered a faithful marker of fibroblast activation in wound healing and in fibrosis. CCN2 is induced during activation of hepatic stellate cells (HSC). Here, we investigate the molecular basis of CCN2 gene expression in HSC. Fluoroscence activated cell sorting was used to investigate CCN2 expression in HSC in vivo in mice treated with CCl(4). CCN2 and TGF-beta mRNA expression were assessed by polymerase chain reaction as a function of culture-induced activation of HSC. CCN2 promoter/reporter constructs were used to map cis-acting elements required for basal and TGFbeta-induced CCN2 promoter activity. Real-time polymerase chain reaction analysis was used to further clarify signaling pathways required for CCN2 expression in HSC. CCl(4) administration in vivo increased CCN2 production by HSC. In vitro, expression of CCN2 and TGF-beta mRNA were concommitantly increased in mouse HSC between days 0 and 14 of culture. TGFbeta-induced CCN2 promoter activity required the Smad and Ets-1 elements in the CCN2 promoter and was reduced by TGFbeta type I receptor (ALK4/5/7) inhibition. CCN2 overexpression in activated HSC was ALK4/5/7-dependent. As CCN2 overexpression is a faithful marker of fibrogenesis, our data are consistent with the notion that signaling through TGFbeta type I receptors such as ALK5 contributes to the activation of HSC and hence ALK4/5/7 inhibition would be expected to be an appropriate treatment for liver fibrosis.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".