Upregulation of Neural Cell Adhesion Molecule 1 and Excessive Migration of Purkinje Cells in Cerebellar Cortex
Bibliographic record
Abstract
Purkinje cells (PCs) are large GABAergic projection neurons of the cerebellar cortex, endowed with elaborate dendrites that receive a multitude of excitatory inputs. Being the only efferent neuron of the cerebellar cortex, PCs project to cerebellar nuclei and control behaviors ranging from movement to cognition and social interaction. Neural cell adhesion molecule 1 (NCAM1) is widely expressed in the embryonic and postnatal development of the brain and plays essential roles in neuronal migration, axon pathfinding and synapse assembly. However, despite its high expression levels in cerebellum, little is known to date regarding the role(s) of NCAM1 in PCs development. Among other aspects, elucidating how the expression of NCAM1 in PCs could impact their postnatal migration would be a significant achievement. We analyzed the Acp2 mutant mouse (nax: naked and ataxia), which displays excessive PC migration into the molecular layer, and investigated how the excessive migration of PCs along Bergmann glia could correlate to NCAM1 expression pattern in early postnatal days. Our Western blot and RT-qPCR analysis of the whole cerebellum show that the protein and mRNA of NCAM1 in wild type are not different during PC dispersal from the cluster stage to monolayer formation. However, RT-qPCR analysis from FACS-based isolated PCs shows that Ncam1 is significantly upregulated when PCs fail to align and instead overmigrate into the molecular layer. Our results suggest two alternative interpretations: (1) NCAM1 promotes excessive PC migration along Bergmann glia, or (2) NCAM1 upregulation is an attempt to prevent PCs from invading the molecular layer. If the latter scenario proves true, NCAM1 may play a key role in PC monolayer formation.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".