Normal-sized basal ganglia perivascular space related to motor phenotype in Parkinson freezers
Bibliographic record
Abstract
Changes in basal ganglia (BG) perivascular spaces (PVSs) are related to motor and cognitive behaviors in Parkinson's disease (PD). However, the correlation between the initial motor phenotype and PVSs distribution/burden in PD freezing of gait (FOG) remains unclear. In addition, the normal-sized PVSs (nPVSs) have not been well-studied. With high-resolution 7T-MRI, we studied nPVSs burden in BG, thalamus, midbrain and centrum semiovale. The numbers and volume of nPVSs were assessed in 10 healthy controls, 10 PD patients without FOG, 20 with FOG [10 tremor dominant (TD), 10 non-TD subtype]. Correlation analyses were further performed in relation to clinical parameters. In this proof of concept study, we found that the nPVS burden of bilateral and right BG were significantly higher in freezers. A negative correlation existed between the tremor score and BG-nPVSs count. A positive correlation existed between the levodopa equivalent daily dose and BG-nPVSs count. The nPVS burden correlated with the progression to FOG in PD, but the distribution and burden of nPVS differ in TD vs. non-TD subtypes. High resolution 7T-MRI is a sensitive and reliable tool to evaluate BG-nPVS, and may be a useful imaging marker for predicting gait impairment that may evolve into FOG in PD.
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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".