Thalamic free water elevation and its association with glymphatic dysfunction in Parkinson’s disease: A cross-sectional and longitudinal study
Bibliographic record
Abstract
Free Water (FW) is considered an indicator of neuroinflammation, while the Index of Diffusivity along the Perivascular Space (ALPS) is a recently introduced measure of glymphatic function. However, no study has yet investigated the specific relationships between these factors simultaneously. This study aimed to examine changes in FW in the thalamic midline and lateral nuclei in Parkinson's disease (PD), with a particular focus on the potential influence of glymphatic system dysfunction. MRI data and clinical information were obtained from 32 healthy controls (HC), 32 participants with prodromal PD (pPD), and 90 participants with PD, sourced from the Parkinson's Progression Markers Initiative (PPMI) database. The ALPS index and Free Water fractional volume (FWF) were calculated based on diffusion tensor images. Intergroup comparisons of and correlations among MRI measures and clinical assessments were analyzed. FWF was elevated in the bilateral thalamic midline and right lateral nuclei of PD and in right midline nuclei of pPD compared to HC. In the PD group, the right ALPS index was significantly and negatively associated with FWF in the bilateral thalamic lateral nuclei, and mean ALPS index was negatively correlated to FWF in right lateral nuclei. Moreover, FWF in the right lateral thalamic nuclei of PD was correlated with follow-up Montreal Cognitive Assessment (MoCA) scores and its 2-years decrease rate. We provided indirect evidence to support that thalamic FW was significantly increased in PD participants, potentially exacerbated by glymphatic system dysfunction.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".