The calcium‐sensing receptor and integrins modulate cerebellar granule cell precursor differentiation and migration
Bibliographic record
Abstract
In the developing cerebellum granule cell precursors (GCPs) proliferate in the external granule cell layer before differentiating and migrating to the inner granule cell layer. Aberrant GCP proliferation leads to medulloblastoma, the most prevalent form of childhood brain cancer. Here, we demonstrate that the calcium-sensing receptor (CaSR), a homodimeric G-protein coupled receptor, functions in conjunction with cell adhesion proteins, the integrins, to enhance GCP migration and cell homing by promoting GCP differentiation. During the second postnatal week a robust peak in CaSR expression was observed in GCPs; reciprocal immunoprecipitation experiments conducted during this period established that the CaSR and β1 integrins are present together in a macromolecular protein complex. Analysis of cell-surface proteins demonstrated that activation of the CaSR by positive allosteric modulators promoted plasma membrane expression of β1 integrins via ERK2 and AKT phosphorylation and resulted in increased GCP migration toward an extracellular matrix protein. The results of in vivo experiments whereby CaSR modulators were injected i.c.v. revealed that CaSR activation promoted radial migration of GCPs by enhancing GCP differentiation, and conversely, a CaSR inhibitor disrupted GCP differentiation and promoted GCP proliferation. Our results demonstrate that an ion-sensing G-protein coupled receptor acts to promote neuronal differentiation and homing during cerebellar maturation. These findings together with those of others also suggest that CaSR/integrin complexes act to transduce extracellular calcium signals into cellular movement, and may function in this capacity as a universal cell migration/homing complex in the developing brain.
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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) | 0.000 | 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".