TGF-Beta Induced Erk Phosphorylation of Smad Linker Region Regulates Smad Signaling
Bibliographic record
Abstract
The Transforming Growth Factor-Beta (TGF-β) family is involved in regulating a variety of cellular processes such as apoptosis, differentiation, and proliferation. TGF-β binding to a Serine/Threonine kinase receptor complex causes the recruitment and subsequent activation of transcription factors known as smad2 and smad3. These proteins subsequently translocate into the nucleus to negatively or positively regulate gene expression. In this study, we define a second signaling pathway leading to TGF-β receptor activation of Extracellular Signal Regulated Kinase (Erk) in a cell-type dependent manner. TGF-β induced Erk activation was found in phenotypically normal mesenchymal cells, but not normal epithelial cells. By activating phosphotidylinositol 3-kinase (PI3K), TGF-β stimulates p21-activated kinase2 (Pak2) to phosphorylate c-Raf, ultimately resulting in Erk activation. Activation of Erk was necessary for TGF-β induced fibroblast replication. In addition, Erk phosphorylated the linker region of nuclear localized smads, resulting in increased half-life of C-terminal phospho-smad 2 and 3 and increased duration of smad target gene transcription. Together, these data show that in mesenchymal cell types the TGF-β/PI3K/Pak2/Raf/MEK/Erk pathway regulates smad signaling, is critical for TGF-β-induced growth and is part of an integrated signaling web containing multiple interacting pathways rather than discrete smad/non-smad pathways.
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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) | 0.003 | 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".