Nucleocytoplasmic transport of the RNA-binding protein CELF2 regulates neural stem cell fates
Bibliographic record
Abstract
The development of the cerebral cortex requires balanced expansion and differentiation of neural stem/progenitor cells (NPCs), which rely on precise regulation of gene expression. Because NPCs often exhibit transcriptional priming of cell-fate-determination genes, the ultimate output of these genes for fate decisions must be carefully controlled in a timely fashion at the post-transcriptional level, but how that is achieved is poorly understood. Here, we report that de novo missense variants in an RNA-binding protein CELF2 cause human cortical malformations and perturb NPC fate decisions in mice by disrupting CELF2 nucleocytoplasmic transport. In self-renewing NPCs, CELF2 resides in the cytoplasm, where it represses mRNAs encoding cell fate regulators and neurodevelopmental disorder-related factors. The translocation of CELF2 into the nucleus releases mRNA for translation and thereby triggers NPC differentiation. Our results reveal that CELF2 translocation between subcellular compartments orchestrates mRNA at the translational level to instruct cell fates in cortical 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 | 0.000 |
| 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 | 0.000 |
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 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".