Staufen 1 is expressed by neural precursor cells in the developing murine cortex but is dispensable for NPC self-renewal and neuronal differentiation in vitro
Bibliographic record
Abstract
BACKGROUND: Proper development of the cerebral cortex relies on asymmetric divisions of neural precursor cells (NPCs) to produce a recurring NPC and a differentiated neuron. Asymmetric divisions are promoted by the differential localization of cell-fate determinants, such as mRNA, between daughter cells. Staufen 1 (Stau1) is an RNA-binding protein known to localize mRNA in mature hippocampal neurons. Its expression pattern and role in the developing mammalian cortex remains unknown. RESULTS: Both stau1 mRNA and Stau1 protein were found to be expressed in all cells of the developing murine cortex. Stau1 protein expression was characterized spatially and temporally throughout cortical development and found to be present in all stages investigated. We observed expression in the nucleus, cytoplasm and distal processes of both NPCs and newly born neurons and found it to shuttle between the nucleus and the cytoplasm. Upon shRNA-mediated knock-down of Stau1 in primary cultures of the developing cortex, we did not observe any phenotype in NPCs. They were able to both self-renew and generate neurons in the absence of Stau1 expression. CONCLUSIONS: We propose that Stau1 is either dispensable for the development of the cerebral cortex or that its paralogue, Stau2, is able to compensate for its loss.
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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".