Macrostructural Brain Abnormalities in Spinal Muscular Atrophy
Bibliographic record
Abstract
Background and Objectives: Most individuals with spinal muscular atrophy (SMA) on disease-modifying therapies continue to have chronic motor impairment. Insights into brain involvement in SMA may open new pathways for adjunctive therapies to optimize outcomes. We aimed to characterize macrostructural brain abnormalities detected by MRI in individuals with SMA compared with peer controls. Methods: copy number and motor function (Hammersmith Functional Motor Scale Expanded and Revised Upper Limb Module scores), were then correlated with neuroimaging findings. Results: copies (4/10, 40% and 2/6, 33% respectively), not reaching significance. We found no association between structural changes and motor function scores. Discussion: Individuals with SMA have higher rates of macrostructural brain abnormalities than their neurotypical peers, suggesting CNS involvement in SMA. Understanding changes in the brain architecture of the SMA population can inform the development of adjunct therapies targeting the CNS and potentially guide rehabilitation strategies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".