Genetics of Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) and Role of Sacsin in Neurodegeneration
Bibliographic record
Abstract
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an early-onset neurodegenerative disease that was originally discovered in the population from the Charlevoix-Saguenay-Lac-Saint-Jean (CSLSJ) region in Quebec. Although the disease progression of ARSACS may start in early childhood, cases with later onset have also been observed. Spasticity and ataxia could be common phenotypes, and retinal optic nerve hypermyelination is detected in the majority of patients. Other symptoms, such as pes cavus, ataxia and limb deformities, are also frequently observed in affected individuals. More than 200 mutations have been discovered in the SACS gene around the world. Besides French Canadians, SACS genetics have been extensively studied in Tunisia or Japan. Recently, emerging studies discovered SACS mutations in several other countries. SACS mutations could be associated with pathogenicity either in the homozygous or compound heterozygous stages. Sacsin has been confirmed to be involved in chaperon activities, controlling the microtubule balance or cell migration. Additionally, sacsin may also play a crucial role in regulating the mitochondrial functions. Through these mechanisms, it may share common mechanisms with other neurodegenerative diseases. Further studies are needed to define the exact functions of sacsin. This review introduces the genetic mutations discovered in the SACS gene and discusses its pathomechanisms and its possible involvement in other neurodegenerative diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".