Increased plasma GPNMB levels in patients with parkinson’s disease and cognitive impairment
Bibliographic record
Abstract
Glycoprotein nonmetastatic melanoma protein B (GPNMB) is a glycosylated type I transmembrane protein that forms soluble GPNMB upon maturation. This study aimed to explore the relationship between plasma GPNMB levels in patients with Parkinson's disease (PD) and their clinical manifestations, as well as their correlations with specific brain regions identified through imaging analysis. This study included patients with PD and healthy control subjects whose plasma GPNMB levels measured by enzyme-linked immunosorbent assay (ELISA). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) scale. The imaging analysis employed voxel-based morphometry (VBM) to detect changes in gray matter volume, with the left lentiform nucleus identified as the region of interest (ROI). The results showed that plasma GPNMB levels were significantly correlated with PD-related cognitive impairment. Specifically, elevated plasma GPNMB levels were associated with deficits in scores for MoCA subitems related to delayed memory. The imaging analysis revealed a moderate negative correlation between plasma GPNMB levels and the gray matter volume in the left putamen, suggesting that this area may be a potential site of action for GPNMB in the pathology of PD. This study is the first comprehensive investigation into the interrelationships between plasma GPNMB levels and the clinical symptoms and imaging characteristics of PD.
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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) | 0.001 | 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".