Precocious myelination in a mouse model of autism
Bibliographic record
Abstract
Autism spectrum disorder (ASD) has been hypothesized to be a result of altered connectivity in the brain. Recent imaging studies suggest accelerated maturation of the white matter in young children with ASD, with underlying mechanisms unknown. Myelin is an integral part of the white matter and critical for connectivity; however, its role in ASD remains largely unclear. Here, we investigated myelin development in a model of idiopathic ASD, the BTBR mice. Magnetic resonance imaging revealed that fiber tracts in the frontal brain of the BTBR mice had increased volume at postnatal day 6, but the difference reduced over time, reminiscent of the findings in young patients. We further identified that myelination in the frontal brain of both male and female neonatal BTBR mice was increased, associated with elevated levels of myelin basic protein. However, myelin pattern was unaltered in adult BTBR mice, revealing accelerated developmental trajectory of myelination. Consistently, we found that signaling of platelet-derived growth factor receptor alpha (PDGFRα) was reduced in the frontal brain of neonatal BTBR mice. However, levels of microRNA species known to regulate PDGFRα signaling and myelination were unaltered. Together, these results suggest that precocious myelination could potentially contribute to increased volume and connectivity of the white matter observed in young children with ASD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".