The <scp>S</scp>taufen<scp>1</scp>‐dependent cell cycle regulon or how a misregulated <scp>RNA‐</scp>binding protein leads to cancer
Bibliographic record
Abstract
In recent years, an increasing number of reports have linked the RNA-binding protein Staufen1 (STAU1) to the control of cell decision making. In non-transformed cells, STAU1 balances the expression of messenger RNA (mRNA) regulons that regulate differentiation and well-ordered cell division. Misregulation of STAU1 expression and/or functions changes the fragile balance in the expression of pro- and anti-proliferative and apoptotic genes and favours a novel equilibrium that supports cell proliferation and cancer development. The misregulation of STAU1 functions causes multiple coordinated modest effects in the post-transcriptional regulation of many RNA targets that code for cell cycle regulators, leading to dramatic consequences at the cellular level. The new tumorigenic equilibrium in STAU1-mediated gene regulation observed in cancer cells can be further altered by a slight increase in STAU1 expression that favours expression of pro-apoptotic genes and cell death. The STAU1-dependent cell cycle regulon is a good model to study how abnormal expression of an RNA-binding protein promotes cell growth and provides an advantageous selection of malignant cells in the first step of cancer development.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".