Directed differentiation of human hindbrain neuroepithelial stem cells recapitulates cerebellar granule neurogenesis
Bibliographic record
Abstract
Abstract Cerebellar granule neurons (CGNs) are the most abundant neurons in the human brain and modulate cerebellar output to the motor cortex. Dysregulation of CGN development underlies movement disorders and medulloblastomas. It is suspected that these disorders arise in progenitor states of the CGN lineage, for which human models are lacking. Here, we have differentiated human hindbrain neuroepithelial stem (hbNES) cells to CGNs in vitro using soluble growth factors, recapitulating key progenitor states in the lineage. We show that hbNES cells are not lineage committed and retain rhombomere 1 (r1) regional identity. Upon differentiation, hbNES cells first transit through a rhombic lip (RL) progenitor state at day 7, demonstrating human specific sub-ventricular cell identities. This RL state is followed by an ATOH1 + CGN progenitor state at day 14. By the end of a 56-day differentiation procedure, we obtain mature neurons expressing CGN markers GABA A a6 and vGLUT2. These neurons generate spontaneous and evoked action potentials. A small fraction of endpoint neurons were unipolar brush cells (UBC). We noted maintenance of a RL population throughout differentiation, as is consistent with human development. We show that sonic hedgehog (SHH) promotes γ-aminobutyric acid (GABA)-ergic lineage specification and is a positive regulator of CGN progenitor proliferation. Interestingly, we observed that functional neuronal maturation is impaired by either elevated or absent SHH signaling. Impaired maturation under high SHH levels represents the potential of our system to model cerebellar tumorigenesis. Further, our data suggest a potential pro-differentiation role of SHH within a certain concentration range. Our work is, to our knowledge, the first detailed temporal characterization of the complete human CGN lineage in vitro . Our system recapitulates developmentally relevant progenitor states and is a new tool to model this specific cerebellar lineage, and how it may be disrupted to cause human disease.
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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 | 0.001 |
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".