Human-specific features of cerebellar astrocytes and Purkinje cells: an anatomical comparison with mice and macaques
Bibliographic record
Abstract
Abstract Little is known about the morphological diversity and distribution of cerebellar astrocytes in the human brain and how or if these features differ from those of cerebellar astrocytes in species used to model human illnesses. To address this, we performed a comparative post-mortem examination of cerebellar astrocytes and Purkinje cells (PCs) in healthy humans, macaques, and mice using microscopy-based techniques. Visualizing with canonical astrocyte markers glial fibrillary acidic protein (GFAP) and aldehyde dehydrogenase-1 family member L1 (ALDH1L1), we mapped astrocytes within a complete cerebellar hemisphere. Astrocytes were observed to be differentially distributed across the cerebellar layers, displayed overall increases in area coverages with evolution, and showed features uniquely hominoid. Stereological quantifications in 3 functionally distinct cerebellar lobules demonstrated opposing trends for the canonical astrocyte markers across species with ALDH1L1+ astrocytes increasing with evolution and GFAP+ astrocytes decreasing. PC analyses revealed that while humans have the lowest PC densities, their cell body sizes were the largest with more ALDH1L1 immunoreactive astrocytes surrounding. Notably, the cognitive lobule crus I displayed the highest ratio of Bergmann glia to PC in all species. These findings align with the growing literature for astrocyte and PC heterogeneity and suggest cerebellar astrocyte and PC divergence both within and across species, possibly indicative of a role for these cells in higher-order cerebellar processing.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".