Striatal pathology in Spinocerebellar Ataxia Type 1 mice: A comparative study with Huntington’s disease
Bibliographic record
Abstract
ABSTRACT Spinocerebellar ataxia type 1 (SCA1) and Huntington’s disease (HD), are motor diseases caused by CAG expansions in ATXN1 and HTT , where SCA1 shows prominent cerebellar neurodegeneration and HD shows prominent striatal neurodegeneration, particularly in the Medium Spiny Neurons (MSNs). Since human and mouse studies demonstrate progressive striatal vulnerability in SCA1, we examined age-dependent molecular, cellular and functional striatal attributes in SCA1 (f-ATXN1 146Q/2Q ) knockin mice, by assessing RNA-sequencing, immunohistochemistry and electrophysiology. Striatal mRNAs are downregulated in SCA1 mice, many in common with HD mice, and specificity in MSNs is supported by the rescue of transcriptomic dysregulation with deletion of mutant Ataxin1 from MSNs. Immunohistochemistry assessed dopamine receptor 1 (D1R) and 2 (D2R) expression in indirect and direct MSNs. In HD mice ( Htt Q175/Q7 ), expression of both D1R and D2R proteins in MSNs decreased with age in parallel with their RNA levels. In the SCA1 mouse striatum, D1R protein expression decreased with age as seen in murine HD striatum. In contrast, while D2R protein level was decreased similar to D1R protein at 5-weeks of age, by 40-weeks expression of D2R protein recovered to levels recorded in WT mice. Electrophysiological assessment showed a reduction of excitatory synaptic transmission in SCA1 mouse MSNs, indicating functional deficits early in disease. In contrast to cerebellar and many other aspects of SCA1 pathology known to depend on proper nuclear localization of ATXN1 with an expanded polyglutamine, mutating ATXN1’s nuclear localization failed to correct striatal MSN RNA and protein downregulations, indicating a difference in how ATXN1 exerts its pathological effects between the cerebellum and the striatum. Together, these data provide a molecular and cellular basis of striatal pathology in SCA1.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".