Synergism between Transcription Factors TFE3 and Smad3 in Transforming Growth Factor-β-induced Transcription of theSmad7 Gene
Bibliographic record
Abstract
Activation of transforming growth factor-beta (TGF-beta) receptors triggers phosphorylation of Smad2 and Smad3. After binding to Smad4, the complex enters the nucleus and interacts with other transcription factors to activate gene transcription. Unlike other Smads, Smad7 inhibits phosphorylation of Smad2 and Smad3, and its transcription is induced by TGF-beta, suggesting a negative feedback loop. Here, we show that TFE3 and Smad3 synergistically mediate TGF-beta-induced transcription from the Smad7 promoter by binding to an E-box and two adjacent Smad binding elements (SBEs), respectively. A precise 3-base pair spacer between one SBE and the E-box is essential. Previously, we showed that a similar arrangement between a SBE and an E-box of an element is essential for TGF-beta-dependent transcription of the plasminogen activator inhibitor-1 gene (PAI-1) and that TGF-beta-induced phosphorylation of Smad3 triggers its association with TFE3. Thus, TFE3-Smad3 response elements may represent a common target for TGF-beta-induced gene expression.
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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".