Repeat Expansions in a Chilean Cohort with Adult-Onset Cerebellar Ataxia
Bibliographic record
Abstract
Abstract INTRODUCTION: The diagnosis of hereditary ataxias caused by repeat expansions continue to present unique methodological challenges, especially for developing countries where genomic medicine services are not well established. The purpose of this work is to present a cohort of patients who presented with adult-onset ataxia of suspected genetic etiology, but had remained undiagnosed until now. They were analyzed for a set of repeat expansions including the genes causing the more recently identified types, SCA27B and RFC1 -related CANVAS. PATIENTS AND METHODS: We followed an IRB-approved protocol to recruit adult patients with a possible diagnosis of hereditary cerebellar ataxia. All individuals signed an informed consent form, and after a neurological evaluation, DNA samples from blood were obtained. In selected cases, a complete vestibular function evaluation and brain magnetic resonance imaging was acquired. RESULTS: In 17 of the 56 studied cases (including 11 of 43 index cases) we established a genetic diagnosis, which demonstrates that this is a promising approach to adult-onset ataxias in a population that remains underrepresented in worldwide genomic studies. We identified 9 individuals with SCA27B and 7 with CANVAS syndrome, highlighting the epidemiological relevance of these newly recognized etiologies, an information useful for planning the allocation of resources towards improving the access to genomic medicine in in our region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".