[Correlations of Melatonin and Glutathione Levels with Oxidative Stress Mechanism in Parkinson's Disease].
Bibliographic record
Abstract
Objective To investigate the changes of serum melatonin(MLT)and glutathione(GSH)levels in patients with Parkinson's disease(PD)and explore their relationships with disease severity,cognitive dysfunction,and sleep disorders. Methods Totally 50 PD patients treated in our center from September 2017 to February 2018 were enrolled as the PD group,and 50 healthy controls matched with age and sex as the control group.The improved Hoehn and Yahr scale was used to assess the severity of PD.The Montreal Cognitive Assessment Scale was used to assess the cognitive function and Pittsburgh's Sleep Quality Index was used to detect the patient's sleep.The serum levels of MLT and GSH were detected by enzyme-linked immunosorbent assay and the results were compared. Results Serum MLT level in the PD group was significantly higher than that in the control group [(84.12±6.58)pg/ml vs.(46.29±9.73)pg/ml,P=0.000],and serum GSH level was significantly lower than that in the control group [(21.07±12.05)μmol/L vs.(77.73±39.90)μmol/L,P=0.000].There was a positive correlation between serum MLT level and H-Y grade(r=0.537,P=0.000),and there was a negative correlation between serum GSH level and H-Y grade(r=-0.596,P=0.000).Serum MLT was negatively correlated with GSH level in PD patients(r=-0.842,P=0.000).The MLT level in PD patients with sleep disorders was significantly higher than in those without sleep disorders [(85.79±6.45)pg/ml vs.(78.84±3.54)pg/ml,P=0.001];the level of GSH in PD patients with cognitive dysfunction was significant lower than in the non-cognitive dysfunction group [(17.47±10.67)μmol/L vs.(26.09±12.23)μmol/L,P=0.011]. Conclusions Serum MLT level increases and GSH level decreases in PD patients.Both MLT and GSH are correlated with PD severity,and there is a negative correlation between MLT and GSH.In addition,PD patients with sleep disorders have higher MLT level and those with cognitive impairment tend to have lower GSH level.
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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 | 0.000 |
| 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".