Brain atrophy in primary lateral sclerosis
Bibliographic record
Abstract
BACKGROUND: Primary lateral sclerosis (PLS) is an idiopathic upper motor neuron degenerative disorder. The aim of this study was to compare brain volumes in patients with PLS and controls and determine whether differences were due to loss of gray matter (GM), white matter (WM), or both. METHODS: T1-weighted images were acquired in patients with PLS and controls. Freesurfer was used for volumetric segmentation of whole brain, cortical GM, precentral and postcentral cortex, WM, corpus callosum, basal ganglia, thalamus, cerebellum, and CSF. Relationships were sought between disease severity, disease duration, age and brain volumes. RESULTS: Eleven patients with PLS and 10 age-matched healthy controls were included in this study. Compared to control subjects, patients with PLS had significantly smaller whole brain (p = 0.043), frontal lobe (p = 0.036), precentral cortex (p = 0.016), and corpus callosum (p = 0.036) volumes. There was a trend toward a smaller thalamus (p = 0.051). Disease severity correlated with ventricular CSF volume (rho = -0.604, p = 0.025) and precentral cortex volume loss (rho = 0.599, p = 0.026). Disease duration tended to correlate with a loss of WM (rho = -0.636, p = 0.063). CONCLUSIONS: Our results suggest that there is focal atrophy in patients with primary lateral sclerosis compared with controls especially in the precentral cortex and the corpus callosum, specifically where there is transfer of motor fibers.
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 | 0.001 |
| 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) | 0.003 | 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".