Dysferlin aggregation in limb‐girdle muscular dystrophy type 2B/myoshi myopathy necessitates mutational screen for diagnosis
Bibliographic record
Abstract
INTRODUCTION: Diagnosis of the limb-girdle muscular dystrophies (LGMDs) has been facilitated by the use of immunofluorescence microscopy, Western blot analysis, and rapid genetic testing. METHODS: We identified 7 patients with LGMD2B or Miyoshi myopathy (MM) phenotypes and performed detailed history, physical examination, and mutation analyses of genomic DNA. RESULTS: Ten disease-causing variants of the dysferlin gene (DYSF) were detected, 4 of which were novel and predicted to be pathogenic (IVS33+9G>T, c.1343T>C, c.4747T>G, and c.5066dupC). Two of these mutations (c.1343T>C and IVS33+9G>T) were associated with a reduction in sarcolemmal dysferlin expression, despite increased total mRNA and protein in mixed muscle homogenates, due to a pathological retention of the mutated polypeptide in the cytoplasm. CONCLUSIONS: Considering that protein-based assays may yield false negative test results and that dysferlin aggregation may be present in other LGMDs, mutational screening is necessary for specific diagnosis in primary dysferlinopathy patients exhibiting this phenotype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".