Greater Loss of White Matter Integrity in Postural Instability and Gait Difficulty Subtype of Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Patients with the postural instability and gait difficulty (PIGD) subtype of Parkinson disease (PD) are at a higher risk of dysfunction and are less responsive to dopamine replacement therapy. The PIGD subtype was found to largely associate with white matter lesions, but details of the diffusion changes within these lesions have not been fully investigated. Voxel-based analysis for diffusion tensor imaging data is one of the preferred measures to compare diffusion changes in each voxel in any part of the brain. METHODS: PD patients with the PIGD (n=12) and non-PIGD subtypes (n=12) were recruited to compare diffusion differences in fractional anisotropy, axial diffusivity, and radial diffusivity with voxel-based analysis. RESULTS: Significantly reduced fractional anisotropy in bilateral superior longitudinal fasciculus, bilateral anterior corona radiata, and the left genu of the corpus callosum were shown in the PIGD subtype compared with the non-PIGD subtype. Increased radial diffusivity in the left superior longitudinal fasciculus was found in the PIGD subtype with no statistical differences in axial diffusivity found. CONCLUSIONS: Our study confirms previous findings that white matter abnormalities were greater in the PIGD subtype than in the non-PIGD subtype. Additionally, our findings suggested: (1) compared with the non-PIGD subtype, loss of white matter integrity was greater in the PIGD subtype; (2) bilateral superior longitudinal fasciculus may play a critical role in microstructural white matter abnormalities in the PIGD subtype; and (3) reduced white matter integrity in the PIGD subtype could be mainly attributed to demyelination rather than axonal loss.
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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 | 0.001 |
| 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) | 0.003 | 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".