Requirement of transforming growth factor β–activated kinase 1 for transforming growth factor β–induced α‐smooth muscle actin expression and extracellular matrix contraction in fibroblasts
Bibliographic record
Abstract
OBJECTIVE: Fibrosis is believed to occur through normal tissue remodeling failing to terminate. Tissue repair intimately involves the ability of fibroblasts to contract extracellular matrix (ECM), and enhanced ECM contraction is a hallmark of fibrotic cells in various conditions, including scleroderma. Some fibrogenic transcriptional responses to transforming growth factor beta (TGFbeta), including alpha-smooth muscle actin (alpha-SMA) expression and ECM contraction, require focal adhesion kinase/Src (FAK/Src). The present study was undertaken to assess whether TGFbeta-activated kinase 1 (TAK1) acts downstream of FAK/Src to mediate fibrogenic responses in fibroblasts. METHODS: We used microarray, real-time polymerase chain reaction, Western blot, and collagen gel contraction assays to assess the ability of wild-type and TAK1-knockout fibroblasts to respond to TGFbeta1. RESULTS: The ability of TGF to induce TAK1 was blocked by the FAK/Src inhibitor PP2. JNK phosphorylation in response to TGFbeta1 was impaired in the absence of TAK1. TGFbeta could not induce matrix contraction or expression of a group of fibrotic genes, including alpha-SMA, in the absence of TAK1. CONCLUSION: These results suggest that TAK1 operates downstream of FAK/Src in mediating fibrogenic responses and that targeting of TAK1 may be a viable antifibrotic strategy in the treatment of certain disorders, including scleroderma.
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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".