CCN2 Is Necessary for Adhesive Responses to Transforming Growth Factor-β1 in Embryonic Fibroblasts
Bibliographic record
Abstract
CCN2 is induced by transforming growth factor-beta (TGFbeta) in fibroblasts and is overexpressed in connective tissue disease. CCN2 has been proposed to be a downstream mediator of TGFbeta action in fibroblasts; however, the role of CCN2 in regulating this process unclear. By using embryonic fibroblasts isolated from ccn2-/- mice, we showed that CCN2 is required for a subset of responses to TGFbeta. Affymetrix genome-wide expression profiling revealed that 942 transcripts were induced by TGFbeta greater than 2-fold in ccn2+/+ fibroblasts, of which 345 were not induced in ccn2-/- fibroblasts, including pro-adhesive and matrix remodeling genes. Whereas TGFbeta properly induced a generic Smad3-responsive promoter in ccn2-/- fibroblasts, TGFbeta-induced activation of focal adhesion kinase (FAK) and Akt was reduced in ccn2-/- fibroblasts. Emphasizing the importance of FAK and Akt activation in CCN2-dependent transcriptional responses to TGFbeta in fibroblasts, CCN2-dependent transcripts were not induced by TGFbeta in fak-/- fibroblasts and were reduced by wortmannin in wild-type fibroblasts. Akt1 overexpression in ccn2-/- fibroblasts rescued the TGFbeta-induced transcription of CCN2-dependent mRNA. Finally, induction of TGFbeta-induced fibroblast adhesion to fibronectin and type I collagen was significantly diminished in ccn2-/- fibroblasts. Thus in embryonic fibroblasts, CCN2 is a necessary cofactor required for TGFbeta to activate the adhesive FAK/Akt/phosphatidylinositol 3-kinase cascade, FAK/Akt-dependent genes, and adhesion to matrix.
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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) | 0.002 | 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".