Contra-Directional Expression of Plasma Superoxide Dismutase with Lipoprotein Cholesterol and High-Sensitivity C-reactive Protein as Important Markers of Parkinson’s Disease Severity
Bibliographic record
Abstract
Aim: Oxidative stress and inflammation play critical roles in the neuropathogenesis of PD. We aimed to evaluate oxidative stress and inflammation status by measuring serum superoxide dismutase (SOD) with lipoprotein cholesterol and high-sensitivity C-reactive protein (hsCRP) respectively in PD patients, and explore their correlation with the disease severity. Methods: We performed a cross-sectional study that included 204 PD patients and 204 age-matched healthy controls (HC). Plasma levels of SOD, hsCRP, total cholesterol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) were measured. A series of neuropsychological assessments were performed to rate the severity of PD. Results: The plasma levels of SOD (135.7±20.14 vs. 147.2±24.34, P<0.0001), total cholesterol, HDL-C and LDL-C in PD were significantly lower than those in HCs; the hsCRP level was remarkably increased in PD compared to HC (2.766±3.242 vs. 1.637±1.597, P<0.0001). The plasma SOD was negatively correlated with the hsCRP, while positively correlated with total cholesterol, HDL-C and LDL-C in PD patients.The plasma SOD were negatively correlated with H&Y, total UPDRS, UPDRS(I), UPDRS(II), and UPDRS(III) scores, but positively correlated with MoCA and MMSE scores; Besides, hsCRP was negatively correlated with MoCA; while total cholesterol, HDL-C and LDL-C was positively correlated with the MoCA respectively. Conclusion: Our findings suggest that lower SOD along with cholesterol, HDL-C and LDL-C, and higher hsCRP levels might be important markers to assess the PD severity. A better understanding of SOD and hsCRP may yield insights into the pathogenesis of PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".