FAK Is Required for TGFβ-induced JNK Phosphorylation in Fibroblasts: Implications for Acquisition of a Matrix-remodeling Phenotype
Bibliographic record
Abstract
Transforming growth factor beta (TGFbeta) plays a critical role in connective tissue remodeling by fibroblasts during development, tissue repair, and fibrosis. We investigated the molecular pathways in the transmission of TGFbeta signals that lead to features of connective tissue remodeling, namely formation of an alpha-smooth muscle actin (alpha-SMA) cytoskeleton, matrix contraction, and expression of profibrotic genes. TGFbeta causes the activation of focal adhesion kinase (FAK), leading to JNK phosphorylation. TGFbeta induces JNK-dependent actin stress fiber formation, matrix contraction, and expression of profibrotic genes in fak+/+, but not fak-/-, fibroblasts. Overexpression of MEKK1, a kinase acting upstream of JNK, rescues TGFbeta responsiveness of JNK-dependent transcripts and actin stress fiber formation in FAK-deficient fibroblasts. Thus we propose a FAK-MEKK1-JNK pathway in the transmission of TGFbeta signals leading to the control of alpha-SMA cytoskeleton reorganization, matrix contraction, and profibrotic gene expression and hence to the physiological and pathological effects of TGFbeta on connective tissue remodeling by fibroblasts.
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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".