Cerebrospinal Fluid Cytokines and Neurodegeneration‐Associated Proteins in Parkinson's Disease
Bibliographic record
Abstract
INTRODUCTION: Immune markers are altered in Parkinson's disease (PD), but relationships between cerebrospinal fluid (CSF) and plasma cytokines and associations with neurodegeneration-associated proteins remain unclear. METHODS: CSF and plasma samples and demographic/clinical measures were obtained from 35 PD patients. CSF samples were analyzed for cytokines (together with plasma) and for α-synuclein, amyloid β(1-42) peptide, total tau, and phospho(Thr231)-tau. RESULTS: There were no CSF-plasma cytokine correlations. Interleukin (IL)-8 was higher and interferon-γ, IL-10, and tumor necrosis factor-α were lower in CSF versus plasma. In CSF, total tau correlated positively with IL-8 and IL-1β, whereas α-synuclein correlated positively with amyloid β(1-42) and negatively with semantic fluency (a known marker of PD dementia risk). DISCUSSION: CSF and peripheral cytokine profiles in PD are not closely related. Associations between CSF IL-8 and IL-1β and tau suggest that CSF inflammatory changes may relate to tau pathology within PD. CSF α-synuclein/amyloid β may reflect the risk of developing PD dementia. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.001 | 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".