Objective To study the feasibility of using rough set and support vector machines to detect Parkinson disease. Methods The reduction algorithm based on the importance of the attributes in the rough set theory was used to reduce the common diagnosis features in the clinical practice. The support vector machines were applied for classification with the linear, polynomial and RBF kernel, and the Results were compare with that of BP neural network. Results The algorism combined attributes reduction and support vector machines appeared the highest accuracy of 92.71% in the classification, which seemed greater advantage in accuracy and stability than BP neural network. Conclusion Improving the accuracy of the classification as well as saving the resources, rough set and support vector machines are proved to be an effective method to assist the clinical diagnosis of Parkinson disease.

Objective:To observe the expression of long-chain noncoding RNA (lncRNA) SCAMP1-AS1 in esophageal cancer tissues, and explore the effect of SCAMP1-AS1 on the proliferation and migration of esophageal cancer cells and the possible molecular mechanism.Methods:Real-time fluorescent quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression level of SCAMP1-AS1 in 37 cases of esophageal cancer tissues and adjacent tissues surgically resected in Huangshi Central Hospital of Edong Medical Group from March 2017 to August 2020. RT-qPCR was also used to detect the expression level of SCAMP1-AS1 in 4 types of esophageal cancer cells (EC9706, TE-13, KYSE30, Eca109) and normal esophageal epithelial cells HET-1A. The cells with the lowest expression were selected, the negative control lentivirus (LV-NC) infection was used as the control group, and the recombinant lentivirus carrying SCAMP1-AS1 sequence (LV-SCAMP1-AS1) infection was used as the experimental group. RT-qPCR was used to detect the expression of SCAMP1-AS1 in esophageal cancer cells after infection. Cell counting kit 8 (CCK-8) and Transwell chamber method were used to detect the proliferation and migration ability of esophageal cancer cells. Bioinformatics methods predicted the target genes of SCAMP1-AS1, and dual luciferase reporter experiments verified the interaction of SCAMP1-AS1 with target gene. RT-qPCR detected the expression of target genes. Western blotting detected the expression of cell proliferation and migration phenotype proteins.Results:The relative expression level of SCAMP1-AS1 in esophageal cancer tissue was significantly lower than that in adjacent tissues (1.26 ± 0.48 vs. 8.03 ± 1.17, P<0.01). The relative expression levels of SCAMP1-AS1 in esophageal cancer cells EC9706, TE-13, KYSE30, Eca109 were all lower than that in normal esophageal epithelial cells (0.54 ± 0.05, 0.14 ± 0.02, 0.46 ± 0.07, 0.77 ± 0.05 vs.1.00 ± 0.06, P<0.05), and the expression of SCAMP1-AS1 in TE-13 cells was the lowest ( P<0.01). Compared with the control group, the expression of SCAMP1-AS1 in TE-13 cells in the experimental group was up-regulated ( P<0.01), the proliferation ability of the cells was reduced ( P<0.01), and the migration ability of the cells was reduced ( P<0.01). miR-483-5p was the direct target of SCAMP1-AS1. Compared with the control group, the expression of miR-483-5p was down-regulated in TE-13 cells in the experimental group ( P<0.01), and the expression of cell proliferation and migration phenotype proteins was down-regulated. Conclusions:The expression of lncRNA SCAMP1-AS1 is down-regulated in esophageal cancer. SCAMP1-AS1 can inhibit the proliferation and migration of esophageal cancer TE-13 cells by targeting the expression of miR-483-5p. SCAMP1-AS1 is expected to become a potential molecular therapeutic target for esophageal cancer.