To introduce a method of classification with high precision-the artificial neural network (ANN),and to compare the results using logistic method. Using data from 1070 landless peasants'mental health survey,the artificial neural network models and logistic regression model were built and compared on their advantages and disadvantages of the two models.The prediction accuracy for artificial neural network was 94.229% and for logistic regression it was 51.028%. ANN appeared to have had good ability on generalization. ANN displayed advantages when conditions of classical statistical techniques could not be met or the predictive effect appeared to be unsatisfactory. Hence, ANN would make a better facture of its application in medical researche.

Objective To analyze the spatial point pattern distribution characteristics of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou city, Hubei province during the two seasons spring- summer and autumn-winter of 2017, to discuss its high incidence area and reason, and to provide basis for the resource allocation of public health. Methods The analytical data was collected from Infectious Disease Reporting Information System in China, and the spring-summer season was from March to August of 2017, while the autumn-winter was from the September of 2017 to the February of 2018. The Ripley's K-function and kernel density estimation were applied to analyze the spatial point pattern distribution and compare the distribution characteristics of spatial point pattern between the two seasons. Results In 2017, 133 cases of HFRS were reported in Jingzhou city, including the spring- summer and autumn-winter two pick incidences. The strongest aggregation distance was 17.77km in spring-summer season, and 14.40 km in autumn-winter season. The spatial gathering center was located in the north of Jianli County in spring-summer, and it moved to the south of Jiangling County and Shashi District in autumn-winter. Conclusions The key areas for the prevention and control of HFRS in Jingzhou City are Jiangling County, the southern part of Shashi District and the northern part of jianli county. The key groups are the residents of the urban-rural junction in the southern part of Shashi City, residents along the route of large-scale projects, and farmers engaged in agricultural planting or crayfish breeding in the gathering areas.

OBJECTIVE: A strain of Aspergillus niger (A. niger), capable of releasing bound phenolic acids from wheat bran, was isolated. This strain was identified by gene sequence identification. The antioxidant and anti-inflammatory capacity of ferulic acid released from wheat bran by this A. niger strain (FA-WB) were evaluated. METHODS: Molecular identification techniques based on PCR analysis of specific genomic sequences were conducted; antioxidant ability was examined using oxygen radical absorbance capacity (ORAC), cellular antioxidant activity (CAA) assays, and erythrocyte hemolysis assays. RAW264.7 cells were used as a model to detect anti-inflammatory activity. RESULTS: The filamentous fungal isolate was identified to be A. niger. ORAC and CAA assay showed that FA-WB had better antioxidant activity than that of the ferulic acid standard. The erythrocyte hemolysis assay results suggested that FA-WB could attenuate AAPH-induced oxidative stress through inhibition of reactive oxy gen species (ROS) generation. FA-WB could significantly restore the AAPH-induced increase in intracellular antioxidant enzyme activities to normal levels as well as inhibit the intracellular malondialdehyde formation. TNF-a, IL-6, and NO levels indicated that FA-WB can inhibit the inflammation induced by lipopolysaccharide (LPS). CONCLUSION Ferulic acid released from wheat bran by a new strain of A. niger had good anti-inflammatory activity and better antioxidant ability than standard ferulic acid.
Animals ; Anti-Inflammatory Agents ; metabolism ; pharmacology ; Antioxidants ; metabolism ; pharmacology ; Aspergillus niger ; genetics ; isolation & purification ; metabolism ; Coumaric Acids ; metabolism ; pharmacology ; DNA, Fungal ; analysis ; Dietary Fiber ; microbiology ; Erythrocytes ; drug effects ; metabolism ; Fermentation ; Hep G2 Cells ; Humans ; Interleukin-6 ; metabolism ; Lipopolysaccharides ; pharmacology ; Mice ; RAW 264.7 Cells ; Sheep ; Tumor Necrosis Factor-alpha ; metabolism