Promotion of cortical neuronal differentiation by groucho-related gene 6
Bibliographic record
Abstract
The Groucho/Transducin-like Enhancer of split (Gro/TLE) proteins are a family of transcriptional corepressors involved in a variety of cell differentiation mechanisms in both invertebrates and vertebrates. In particular, they act as negative regulators of neuronal development. Gro/TLEs can be recruited to DNA by forming complexes with a number of DNA-binding transcription factors and are thus involved in the regulation of numerous genes. The aim of this study was to characterize a new member of the Gro/TLE family named Groucho-related gene 6 (Grg6). It is reported here that Grg6 is expressed in selected regions of the murine embryonic nervous system in both mitotic progenitor cells and postmitotic neurons. Exogenous expression of Grg6 in cortical neural progenitor cells does not significantly affect neuronal differentiation. However, when co-expressed with Gro/TLE1 and the anti-neurogenic Gro/TLE-binding protein brain factor 1 (BF-1; also called Foxg1), Grg6 causes an increase in the number of differentiated neurons. In agreement with these findings, Grg6 interacts with BF-1 and decreases transcriptional repression mediated by BF1:Gro/TLE complexes. In addition, Grg6 disrupts the interaction between BF-1 and Gro/TLE1. Together, these results suggest that Grg6 acts as a negative regulator of BF1 activity and as a positive regulator of cortical neuronal differentiation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".