Brain magnetic resonance imaging in the DE50-MD dog model of Duchenne muscular dystrophy reveals regional reductions in cerebral gray matter
Bibliographic record
Abstract
BACKGROUND: Duchenne muscular dystrophy is a X-linked disease characterized by severe and progressive muscle weakness, alongside cognitive impairment and a range of neurobehavioral disorders secondary to brain dystrophin deficiency. Duchenne muscular dystrophy patients have reduced cerebral gray matter and altered white matter ultrastructure (detected by magnetic resonance imaging) compared to age-matched controls. METHODS: We studied the DE50-MD canine model of Duchenne muscular dystrophy, which is deficient in full length brain dystrophin (Dp427) isoforms and has a neurocognitive phenotype. Eight DE50-MD and 6 age-matched littermate wild type male dogs underwent serial brain magnetic resonance imaging from 14 to 33 months of age. RESULTS: Reduced regional gray matter was detected in DE50-MD dogs compared with wildtype, including the piriform lobe, hippocampus and cingulate gyrus. Lateral ventricle volume was larger in DE50-MD dogs. Differences did not progress over time. White matter volume did not differ between DE50-MD and wildtype dogs. There was no difference in brain nor cranial vault volume between DE50-MD and wildtype dogs. CONCLUSION: Dystrophin deficiency in the canine brain results in structural changes that likely contribute to the neurocognitive phenotype.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".