Spectrum of centrosome autoantibodies in childhood varicella and post-varicella acute cerebellar ataxia
Bibliographic record
Abstract
BACKGROUND: Sera from children with post-varicella infections have autoantibodies that react with centrosomes in brain and tissue culture cells. We investigated the sera of children with infections and post-varicella ataxia and related conditions for reactivity to five recombinant centrosome proteins: gammagamma-enolase, pericentrin, ninein, PCM-1, and Mob1. METHODS: Sera from 12 patients with acute post-varicella ataxia, 1 with post-Epstein Barr virus (EBV) ataxia, 5 with uncomplicated varicella infections, and other conditions were tested for reactivity to cryopreserved cerebellum tissue and recombinant centrosome proteins. The distribution of pericentrin in the cerebellum was studied by indirect immunofluorescence (IIF) using rabbit antibodies to the recombinant protein. Antibodies to phospholipids (APL) were detected by ELISA. RESULTS: Eleven of 12 children with post-varicella ataxia, 4/5 children with uncomplicated varicella infections, 1/1 with post-EBV ataxia, 2/2 with ADEM, 1/2 with neuroblastoma and ataxia, and 2/2 with cerebellitis had antibodies directed against 1 or more recombinant centrosome antigens. Antibodies to pericentrin were seen in 5/12 children with post-varicella ataxia but not in any of the other sera tested. IIF demonstrated that pericentrin is located in axons and centrosomes of cerebellar cells. APL were detected in 75% of the sera from children with post-varicella ataxia and 50% of children with varicella without ataxia and in none of the controls. CONCLUSION: This is the first study to show the antigen specificity of anti-centrosome antibodies in children with varicella. Our data suggest that children with post-varicella ataxia have unique autoantibody reactivity to pericentrin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".