Gli2 is necessary for migration of ventral Neural Stem Cells to demyelinated lesions
Bibliographic record
Abstract
SUMMARY Enhancing repair of myelin is an important therapeutic goal in many neurological disorders characterized by demyelination. In the healthy adult brain, ventral neural stem cells in the sub-ventricular zone are marked by Gli1 expression and do not generate oligodendrocytes. However, in response to demyelination they migrate to lesions and differentiate into oligodendrocytes. Inhibition of Gli1 further increases their contribution to remyelination. Gli1 and Gli2 are both transcriptional effectors of the Sonic Hedgehog pathway with highly conserved domains but the role of Gli2 in remyelination by ventral neural stem cells is not clear. Here we show that while genetic ablation of Gli1 in the ventral neural stem cells increases remyelination, loss of Gli2 in these cells decreases their migration to the white matter lesion and reduces their differentiation into mature oligodendrocytes. These studies indicate Gli1 and Gli2 have distinct, non-redundant functions in NSCs, including that Gli2 is essential for the enhanced remyelination mediated by Gli1 inhibition. They highlight the importance of designing specific Gli1 inhibitors that do not inhibit Gli2 as a strategy for therapies targeting the Shh pathway. Graphical Abstract
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".