Neural stem cell self‐renewal requires the Mrj co‐chaperone
Bibliographic record
Abstract
The Mrj co-chaperone is expressed throughout the mouse conceptus, yet its requirement for placental development has prohibited a full understanding of its embryonic function. Here, we show that Mrj(-/-) embryos exhibit neural tube defects independent of the placenta phenotype, including exencephaly and thin-walled neural tubes. Molecular analyses revealed fewer proliferating cells and a down-regulation of early neural progenitor (Pax6, Olig2, Hes5) and neuronal (Nscl2, SCG10) cell markers in Mrj(-/-) neuroepithelial cells. Furthermore, Mrj(-/-) neurospheres are significantly smaller and form fewer secondary neurospheres indicating that Mrj is necessary for self-renewal of neural stem cells. However, the molecular function of Mrj in this context remains elusive because Mrj does not colocalize with Bmi-1, a self-renewal protein. Furthermore, unlike in Mrj(-/-) placentas, intermediate filament-containing aggregates do not accumulate in Mrj(-/-) neuroepithelium, ruling out nestin as a substrate for Mrj. Regardless, Mrj plays an important role in neural stem cell self-renewal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".