Distinct forebrain regions define a dichotomous astrocytic profile in multiple system atrophy
Bibliographic record
Abstract
The growing recognition of a dichotomous role of astrocytes in neurodegenerative processes has heightened the need for unraveling distinct astrocytic subtypes in neurological disorders. In multiple system atrophy (MSA), a rare, rapidly progressing atypical Parkinsonian disease characterized by increased astrocyte reactivity. However the specific contribution of astrocyte subtypes to neuropathology remains elusive. Hence, we first set out to profile glial fibrillary acidic protein levels in astrocytes across the human post mortem motor cortex, putamen, and substantia nigra of MSA patients and observed an overall profound astrocytic response. Matching the post mortem human findings, a similar astrocytic phenotype was present in a transgenic MSA mouse model. Notably, MSA mice exhibited a decreased expression of the glutamate transporter 1 and glutamate aspartate transporter in the basal ganglia, but not the motor cortex. We developed an optimized astrocyte isolation protocol based on magnetic-activated cell sorting via ATPase Na+/K+ transporting subunit beta 2 and profiled the transcriptomic landscape of striatal and cortical astrocytes in transgenic MSA mice. The gene expression profile of astrocytes in the motor cortex displayed an anti-inflammatory signature with increased oligodendroglial and pro-myelinogenic expression pattern. In contrast, striatal astrocytes were defined by elevated pro-inflammatory transcripts accompanied by dysregulated genes involved in homeostatic functions for lipid and calcium metabolism. These findings provide new insights into a region-dependent, dichotomous astrocytic response-potentially beneficial in the cortex and harmful in the striatum-in MSA suggesting a differential role of astrocytes in MSA-related neurodegenerative processes.
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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 | 0.000 |
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".