Supratentorial and pontine <scp>MRI</scp> abnormalities characterize recessive spastic ataxia of <scp>C</scp>harlevoix‐<scp>S</scp>aguenay. A comprehensive study of an <scp>I</scp>talian series
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an early-onset neurodegenerative disorder caused by mutations in the SACS gene. The disease, first described in Canadian families from Québec, is characterized by cerebellar ataxia, pyramidal tract involvement and peripheral neuropathy. METHODS: Analysis of SACS gene allowed the identification of 14 patients with ARSACS from 13 unrelated Italian families. Clinical phenotype, gene mutations and magnetic resonance imaging (MRI) findings were analysed. RESULTS: We found 16 novel SACS gene mutations, including a large in-frame deletion. The age at onset was in infancy, but one patient presented the first symptoms at age 32. Progression of the disease was variable, and increased muscle tone was mostly recognized in later stages. Structural MRI showed atrophy of the superior cerebellar vermis, a bulky pons exhibiting T2-hypointense stripes, identified as the corticospinal tract (CST), thinning of the corpus callosum and a rim of T2-hyperintensity around the thalami in 100% of cases. The presence of iron or other paramagnetic substances was excluded. Diffusion tensor imaging (DTI) revealed grossly over-represented transverse pontine fibres (TPF), which prevented reconstruction of the CST at this level (100% of cases). In all patients, significant microstructural alterations were found in the supratentorial white matter of forceps, cingulum and superior longitudinal fasciculus. CONCLUSIONS: Our findings further enlarge the genetic spectrum of SACS mutations and widen the study of clinical phenotype. MRI characteristics indicate that pontine changes and supratentorial abnormalities are diagnostic. The over-representation of TPF on DTI suggests a developmental component in the pathogenesis of the disease.
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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 | 0.001 |
| 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) | 0.002 | 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".