Mammalian Numb-interacting Protein 1/Dual Oxidase Maturation Factor 1 Directs Neuronal Fate in Stem Cells
Bibliographic record
Abstract
In this study, we describe a role for the mammalian Numb-interacting protein 1 (Nip1) in regulation of neuronal differentiation in stem cells. The expression of Nip1 was detected in the developing mouse brain, embryonic stem cells, primary neuronal stem cells, and retinoic acid-treated P19 embryonal carcinoma cells. The highest expression of Nip1 was observed in undifferentiated neuronal stem cells and was associated with Duox1-mediated reactive oxygen species ROS production. Ectopic nip1 expression in P19 embryonal carcinoma cells induced neuronal differentiation, and this phenotype was also linked to elevated ROS production. The neuronal differentiation in nip1-overexpressing P19 cells was achieved in a retinoic acid-independent manner and was corroborated by an increase in the expression of the neuronal basic helix-loop-helix transcription factors and neural-lineage cell markers. Furthermore, depletion of nip1 by short hairpin RNA led to a decrease in the expression of neuronal basic helix-loop-helix transcription factors and ROS. However, inhibition of ROS production in nip1-overexpressing P19 cells restricted but did not extinguish neuronal differentiation. Microarray and mass spectrometry analysis identified intermediate filaments as the principal cytoskeletal elements affected by up-regulation of nip1. We show here the first evidence for a functional interaction between Nip1 and a component of the nuclear lamina, lamin A/C. associated with a neuronal-specific phenotype. Taken together, our data reveal an important role for Nip1 in the guidance of neuronal differentiation through ROS generation and modulation of intermediate filaments and implicate Nip1 as a novel intrinsic regulator of neuronal cell fate.
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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) | 0.001 | 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".