Reduced head and brain size for age and disproportionately smaller thalami in child-onset MS
Bibliographic record
Abstract
OBJECTIVE: Whole brain and regional volume measurement methods were used to quantify white matter, gray matter, and deep gray matter structure volumes in a population of patients with pediatric-onset multiple sclerosis (MS). METHODS: Subjects included 38 patients (mean age 15.2 ± 2.4 years) and 33 age- and sex-matched healthy control (HC) participants. MRI measures included intracranial volume, normalized brain volume, normalized white and gray matter volume, and volumes of the thalamus, globus pallidus, putamen, and caudate. Because these volumes vary across age and sex in children, we normalized the volume measurements for MS and control groups by computing z scores using normative values obtained from healthy children enrolled in the MRI Study of Normal Brain Development. RESULTS: The intracranial volume z score was significantly lower in the patients with MS (-0.45 ± 1.16; mean ± SD) compared with the HC participants (+0.25 ± 0.98; p = 0.01). Patients with MS also demonstrated significant decreases in normalized brain volume z scores (-1.09 ± 1.49 vs -0.05 ± 1.22; p = 0.002). After correction for global brain volume, thalamic volumes in the MS population remained lower than those of HCs (-0.68 ± 1.72 vs 0.15 ± 1.35; p = 0.02), indicating an even greater loss of thalamic tissue relative to more global brain measures. Moderate correlations were found between T2-weighted lesion load and normalized thalamic volumes (r = -0.44, p < 0.01) and normalized brain volume (r = -0.47, p < 0.01) and between disease duration and normalized thalamic volume (r = -0.58, p < 0.001) and normalized brain volume (r = -0.46, p < 0.01). CONCLUSIONS: When compared with age- and sex-matched control subjects, the onset of MS during childhood is associated with a smaller overall head size, brain volume, and an even smaller thalamic volume.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".