Epidemiological, clinical, and molecular characterization of Cuban families with spinocerebellar ataxia type 3/Machado-Joseph disease
Bibliographic record
Abstract
BACKGROUND: Spinocerebellar Ataxia Type 3/Machado-Joseph Disease (SCA3/MJD) is a hereditary neurodegenerative disorder resulting from the expansion of CAG repeats in the ATXN3 gene. It is the most common autosomal dominant ataxia in the world, but its frequency prevalence in Cuba remains uncertain. We undertook a national study in order to characterize the ATXN3 gene and to determine the prevalence of SCA3/MJD in Cuba. RESULTS: Twenty-two individuals belonging to 8 non-related families were identified as carriers of an expanded ATXN3 allele. The affected families come from the central and western region of the country. Ataxia of gait was the initial symptom in all of the cases. The normal alleles ranged between 14 and 33 CAG repeats while the expanded ones ranged from 63 to 77 repeats. The mean age at onset was 40 ± 9 years and significantly correlated with the number of CAG repeats in the expanded alleles. CONCLUSIONS: This disorder was identified as the second most common form of spinocerebellar ataxia (SCA) in Cuba based on molecular testing, and showing a different geographical distribution from that of SCA2. This research constitutes the first clinical and molecular characterization of Cuban SCA3 families, opening the way for the implementation of predictive diagnosis for at risk family members.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".