Do old HLA and mitochondrial DNA variants associate with demyelination types in young patients?
Bibliographic record
Abstract
Predicting disease progression with biomarkers can enhance care. Two articles from the Canadian Pediatric Demyelinating Disease Network in the current issue of Neurology ® consider the frequency of 2 different putative biomarkers. The investigators assessed nuclear (DRB1*1501)1 and mitochondrial (various)2 genetic variants in pediatric patients who present with acquired demyelinating syndromes. DRB1*1501 association with multiple sclerosis (MS) is confirmed, whereas associations of mitochondrial (mt)DNA polymorphisms are more ambiguous. In the present studies, samples were prospectively collected from all patients with acquired demyelinating syndromes and the genetic data were analyzed for association with conversion to MS. The results provide incremental evidence for association of these genetic variants with MS. Further, the unique ascertainment and design of these studies raise several issues, such as the putative differences between acquired demyelinating syndromes and MS, between pediatric and adult MS, and between genetic associations with susceptibility to MS (cases vs controls) vs early course of demyelinating disease (conversion to MS vs not). The first article deals with a genetic variant, DRB1*1501, that is undoubtedly associated with MS.1 Conversion to MS occurred in 64 of 266 children with acquired demyelinating syndrome, more commonly in those with 1 or 2 DRB1*1501 alleles, as previously reported in adults with isolated demyelinating events.3 …
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".