Oxidative Stress and Environmental Exposures are Associated with Multiple System Atrophy in Chinese Patients
Bibliographic record
Abstract
OBJECTIVE: Oxidative stress is involved in the pathogenesis of multiple system atrophy (MSA). The aim of this study is to examine oxidant biomarkers including homocysteine (Hcys), bilirubin, uric acid, lipids, and potential environmental risk factors and to ascertain whether these data correlate with MSA in a Chinese population. METHODS: In this study, serum levels of Hcys, bilirubin, uric acid, and lipids were studied in 55 MSA patients and 76 healthy controls (HCs). Education, anti-parkinsonian agent usage, smoking, drinking, farming, and living area of the subjects also were analyzed. The Unified MSA Rating Scale (UMSARS), Hoehn & Yahr stage, International Cooperative Ataxia Rating Scale, and Mini-Mental State Examination were used to assess the disease severity, the parkinsonism, ataxia, and the cognitive ability of MSA, respectively. RESULTS: The levels of Hcys were higher (p<0.001) and those of total bilirubin (p=0.007), indirect bilirubin (p=0.011), and total cholesterol (p=0.046) were lower in MSA patients than in healthy controls, whereas uric acid levels did not differ significantly between MSA and healthy controls. Moreover, Hcys levels in MSA patients had positive correlations with illness duration (r s =0.422, p=0.001) and UMSARS-I (r s =0.555, p<0.001), respectively. High-density lipoprotein cholesterol levels were negatively correlated with UMSARS-I (r s =-0.325, p=0.015). Farming was more frequent in MSA patients (1-20 years: odds ratio, 6.36; p20 years: odds ratio, 10.26; p=0.001), whereas current smoking was less frequent (odds ratio, 0.13, p=0.002). CONCLUSIONS: Elevated Hcys and decreased high-density lipoprotein cholesterol may be associated with the disease severity of MSA. Environmental exposures such as farming and smoking may contribute to the occurrence but not the progression of MSA.
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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 | 0.001 | 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) | 0.002 | 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".