P.082 White matter abnormalities suggestive of multiple sclerosis in Wolfram syndrome: report of two unrelated cases
Bibliographic record
Abstract
Background: Wolfram syndrome (WFS) is a genetic disorder clinically characterized by optic atrophy (OA), diabetes mellitus, sensorineural deafness, and diabetes insipidus. It is caused by mutations in WFS1 (mono- or biallelic) or CISD2 (biallelic) genes. Neuroradiological features include cerebellar and/or brainstem atrophy with visual pathway and white matter involvement. We report two subjects with WFS in which multifocal, progressive, and contrast-enhancing white matter abnormalities (WMA) led to the consideration of multiple sclerosis (MS). Methods: We retrospectively analyzed the clinical, genetic, and radiological data from two unrelated subjects with genetically confirmed WFS and multifocal WMA. Results: Subject I: a 43-year-old woman, heterozygous for a known WFS1 variant, had a history of congenital deafness and OA. The brain MRI documented progressive multifocal WMA including pericallosal lesions. Subject II: a 28-year-old woman, compound heterozygous for two WFS1 variants, was known for OA and diabetes mellitus. The brain MRI revealed multifocal periventricular, callosal, subcortical, and juxtacortical WMA, with some enhancing after gadolinium injection. Conclusions: Our report expands the WFS spectrum of white matter involvement to include progressive, seemingly inflammatory lesions. Although we cannot exclude a dual diagnosis, the roles of WFS1 and CISD2 in myelination suggest a selective white matter vulnerability in WFS.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".