Mitochondrial dysfunction and Purkinje cell loss in autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS)
Bibliographic record
Abstract
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a childhood-onset neurological disease resulting from mutations in the SACS gene encoding sacsin, a 4,579-aa protein of unknown function. Originally identified as a founder disease in Québec, ARSACS is now recognized worldwide. Prominent features include pyramidal spasticity and cerebellar ataxia, but the underlying pathology and pathophysiological mechanisms are unknown. We have generated an animal model for ARSACS, sacsin knockout mice, that display age-dependent neurodegeneration of cerebellar Purkinje cells. To explore the pathophysiological basis for this observation, we examined the cell biological properties of sacsin. We show that sacsin localizes to mitochondria in non-neuronal cells and primary neurons and that it interacts with dynamin-related protein 1, which participates in mitochondrial fission. Fibroblasts from ARSACS patients show a hyperfused mitochondrial network, consistent with defects in mitochondrial fission. Sacsin knockdown leads to an overly interconnected and functionally impaired mitochondrial network, and mitochondria accumulate in the soma and proximal dendrites of sacsin knockdown neurons. Disruption of mitochondrial transport into dendrites has been shown to lead to abnormal dendritic morphology, and we observe striking alterations in the organization of dendritic fields in the cerebellum of knockout mice that precedes Purkinje cell death. Our data identifies mitochondrial dysfunction/mislocalization as the likely cellular basis for ARSACS and indicates a role for sacsin in regulation of mitochondrial dynamics.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".