Impaired growth of the cerebellum in pediatric-onset acquired CNS demyelinating disease
Bibliographic record
Abstract
BACKGROUND: Acquired demyelinating syndromes (ADS) have the potential to negatively impact cerebellar growth, given the proclivity for infratentorial lesions in pediatric-onset multiple sclerosis (MS) and ADS. OBJECTIVE: To investigate cerebellar growth longitudinally in pediatric ADS. METHODS: Cerebellar volumes from 472 magnetic resonance imaging (MRI) scans of 98 patients with monophasic ADS (monoADS), monophasic acute disseminated encephalomyelitis (ADEM), and MS (49 girls; mean age: 11.4 years at first scan, mean follow-up: 3.1 years) imaged serially from onset and 897 MRI scans of 418 healthy children (223 girls, mean age: 11.3 years, mean follow-up: 2.9 years) were segmented automatically, analyzed with mixed-effect models, and compared with cerebral volume. RESULTS: Cerebellar developmental trajectories followed a U-shaped curve, showing larger volumes in boys (p < 0.001). Cerebellar volumes in all three patient groups failed to reach age-expected trajectories, leading to significantly smaller volumes, notably in the posterior lobes. Cerebellar volume reductions were of a similar magnitude to cerebral volume reductions. Cerebellar white matter volume declined in MS and ADEM patients over time, while in monoADS patients it remained similar to controls. Cerebellar volumes did not correlate either with lesion volumes at onset or with physical disability. CONCLUSION: MonoADS, ADEM, and MS in childhood lead to impaired age-expected growth of the cerebellum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".