Weak association between total alpha‐synuclein reflex tear levels and non‐motor symptoms burden in Parkinson's disease
Bibliographic record
Abstract
Abstract Background Alpha‐synuclein (αSyn) is critical to the pathogenesis of Parkinson's disease (PD). Recognition of non‐motor symptoms as clinical manifestations of PD suggests aggregation of αSyn in extranigral areas. Aim This study aimed to evaluate the association between total αSyn levels in reflex tears with non‐motor symptoms. Methods This cross‐sectional study included 25 people living with PD (PwP) and 38 age‐matched healthy controls (HC). Total αSyn reflex tear levels were measured using an enzyme‐linked immunosorbent assay. PwP were evaluated using the Non‐Motor Symptoms Scale (NMSS), the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS‐UPDRS), Hoehn and Yahr Stage (HY), and Montreal Cognitive Assessment (MoCA). Results Total αSyn reflex tear levels were significantly higher in PwP when compared with HC (1.77 pg/mL [IQR 1.75–1.79] vs. 1.73 pg/mL [IQR 1.70–1.75], p < 0.001). The urinary domain was negatively correlated with total αSyn levels in tears (r = −0.416, p = 0.048). No correlation was observed between total αSyn levels in reflex tears with MDS‐UPDRS, HY, or MoCA. Conclusions Total αSyn levels in reflex tears can differentiate PD from HC. In addition, total αSyn reflex tear levels were associated with the urinary domain of NMSS but are not associated with motor and cognitive symptoms, nor HY. Therefore, our findings suggest that it does not reflect ongoing dopaminergic neurodegeneration.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".