This study aims to investigate relationship between the level of uric acid (UA) and UA/creatinine ratios (UA/Cr) to the stage of Parkinson disease (PD).A total of 120 cases of PD patients who were admitted in our hospital between 2013 and 2015 were enrolled into this study; these 120 cases of PD patients were divided into 3 groups, according to Hoehn–Yahr (H-Y) classification: early stage (1–2 classification), medium stage (2.5–3 classification), and advanced stage (4–5 classification); UA and UA/Cr level in each group was compared. Then, factors including age, gender, dopamine dosage, UA, and UA/Cr levels were analyzed to find the independent predictive factors of PD by logistic regression.UA and UA/Cr levels in the early and medium stage PD patients were significantly higher than in the advanced stage ones. UA and UA/Cr levels in patients with good prognosis were significantly higher than in the poor ones.UA and UA/Cr levels are negatively correlated with the stages of PD and are independent negatively predicting biological indexes of PD incidence and progression.

Background: Glioblastoma (GBM) is the most common primary malignant tumor in adult central nervous system and results in disappointing survival outcomes. Although the diagnosis and therapy approach have been developed recently, the prognosis of GBM remains poor. A novel, minimally invasive biomarker for GBM is necessary for early diagnosis or prognosis prediction. Methods: All circRNAs were detected by qRT-PCR in GBM samples including training and validation sets. We used the risk score analysis to assume the diagnosis ability for GBM. The receiver operating characteristic curve was also employed. Results: Among the 14 candidates, circRNA, circNT5E, circFOXO3, circ_0001946, circ_0029426, circ-SHPRH, and circMMP9 were detected with increased levels in the training set. Further investigation in the validation set indicated that circFOXO3, circ_0029426, and circ-SHPRH might be the fingerprints for GBM compared with controls. The risk score analysis revealed that the combination of three circRNAs could distinguish the GBM from healthy control with the area under curve value of 0.980 and 0.906, respectively. Conclusion: The three circRNAs might be novel fingerprints for predicting the occurrence of GBM.

Parkinson’s disease (PD) is a chronic and progressive degenerative disease of the central nervous system. Degenerative neuropathy can occur in patients with PD even before typical clinical symptoms appear in the preclinical stage. Therefore, if the early diagnosis of degenerative diseases can be timely and the correlation with the disease progression can be explored, the disease progression will be slowed down and the quality of life of patients will be improved. In this study, the circRNA microarray was employed to screen the dysregulated circRNA in plasma samples of PD. Four circRNAs (circ_0085869, circ_0004381, circ_0017204, and circ_0090668) were obtained with increased levels in PD patients by cross comparison and preliminary verification in PD comparing with healthy controls. Further validation found the circRNA panel was consistent with the training set. The ROC curve also revealed a high diagnostic ability of circ_0004381 and circ_0017204 in predicting the early stage of PD from healthy controls. circ_0085869, circ_0004381, circ_0017204, and circ_0090668 also presented a high ability to distinguish the late stage of PD from early stage. In conclusion, circulating circRNA panel might be a potential fingerprint for predicting the early diagnosis of PD and may act as a biomarker for disease progression.