Nuclear Factor I/B: A Master Regulator of Cell Differentiation with Paradoxical Roles in Cancer
Bibliographic record
Abstract
Emerging evidence indicates that nuclear factor I/B (NFIB), a transcription factor required for proper development and regulation of cellular differentiation in several tissues, also plays critical roles in cancer. Despite being a metastatic driver in small cell lung cancer and melanoma, it has become apparent that NFIB also exhibits tumour suppressive functions in many malignancies. The contradictory contributions of NFIB to both the inhibition and promotion of tumour development and progression, corroborates its diverse and context-dependent roles in many tissues and cell types. Considering the frequent involvement of NFIB in cancer, a better understanding of its multifaceted nature may ultimately benefit the development of novel strategies for the management of a broad spectrum of malignancies. Here we discuss recent findings which bring to light NFIB as a crucial and paradoxical player in cancer.
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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".