The spinal and cerebral profile of adult spinal-muscular atrophy: A multimodal imaging study
Bibliographic record
Abstract
Spinal muscular atrophy (SMA) type III and IV are autosomal recessive, slowly progressive lower motor neuron syndromes. Nevertheless, wider cerebral involvement has been consistently reported in mouse models. The objective of this study is the characterisation of spinal and cerebral pathology in adult forms of SMA using multimodal quantitative imaging. METHODS: Twenty-five type III and IV adult SMA patients and 25 age-matched healthy controls were enrolled in a spinal cord and brain imaging study. Structural measures of grey and white matter involvement and diffusion parameters of white matter integrity were evaluated at each cervical spinal level. Whole-brain and region-of-interest analyses were also conducted in the brain to explore cortical thickness, grey matter density and tract-based white matter alterations. RESULTS: In the spinal cord, considerable grey matter atrophy was detected between C2-C6 vertebral levels. In the brain, increased grey matter density was detected in motor and extra-motor regions of SMA patients. No white matter pathology was identified neither at brain and spinal level. CONCLUSIONS: Adult forms of SMA are associated with selective grey matter degeneration in the spinal cord with preserved white matter integrity. The observed increased grey matter density in the motor cortex may represent adaptive reorganisation.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".