Surface‐ and voxel‐based brain morphologic study in Rett and Rett‐like syndrome with <i>MECP2</i> mutation
Bibliographic record
Abstract
Rett syndrome (RTT) is a rare congenital disorder which in most cases (95%) is caused by methyl-CpG binding protein 2 (MECP2) mutations. RTT is characterized by regression in global development, epilepsy, autistic features, acquired microcephaly, habitual hand clapping, loss of purposeful hand skills, and autonomic dysfunctions. Although the literature has demonstrated decreased volumes of the cerebrum, cerebellum, and the caudate nucleus in RTT patients, surface-based brain morphology including cortical thickness and cortical gyrification analyses are lacking in RTT. We present quantitative surface- and voxel-based morphological measurements in young children with RTT and Rett-like syndrome (RTT-l) with MECP2 mutations. The 8 structural T1-weighted MR images were obtained from 7 female patients with MECP2 mutations (3 classic RTT, 2 variant RTT, and 2 RTT-l) (mean age 5.2 [standard deviation 3.3] years old). Our analyses demonstrated decreased total volumes of the cerebellum in RTT/RTT-l compared to gender- and age-matched controls (t (22)=-2.93, p = .008, Cohen's d = 1.27). In contrast, global cerebral cortical surface areas, global/regional cortical thicknesses, the degree of global gyrification, and global/regional gray and white matter volumes were not statistically significantly different between the two groups. Our findings, as well as literature findings, suggest that early brain abnormalities associated with RTT/RTT-l (with MECP2 mutations) can be detected as regionally decreased cerebellar volumes. Decreased cerebellar volume may be helpful for understanding the etiology of RTT/RTT-l.
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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 | 0.000 |
| 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".