SnoN signaling in proliferating cells and postmitotic neurons
Bibliographic record
Abstract
The transcriptional regulator SnoN plays a fundamental role as a modulator of transforming growth factor beta (TGFβ)-induced signal transduction and biological responses. In recent years, novel functions of SnoN have been discovered in both TGFβ-dependent and TGFβ-independent settings in proliferating cells and postmitotic neurons. Accumulating evidence suggests that SnoN plays a dual role as a corepressor or coactivator of TGFβ-induced transcription. Accordingly, SnoN exerts oncogenic or tumor-suppressive effects in epithelial tissues. At the cellular level, SnoN antagonizes or mediates the ability of TGFβ to induce cell cycle arrest in a cell-type specific manner. SnoN also exerts key effects on epithelial-mesenchymal transition (EMT), with implications in cancer biology. Recent studies have expanded SnoN functions to postmitotic neurons, where SnoN orchestrates key aspects of neuronal development in the mammalian brain, from axon growth and branching to neuronal migration and positioning. In this review, we will highlight our understanding of SnoN biology at the crossroads of cancer biology and neurobiology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".