Sixty patients who had hemodialysis over half year were randomly divided into 3 groups with 20 cases in each group:group A received conventional hemodialysis,group B received hemodialysis with oral administration of compound danshen (salvia miltiorrhiza bunge) tablets and vitamin E,group C had the same treatment as group B but the dialyzer was pretreated with solution containing 5 g vitamin C ; 20 healthy adults served as normal controls. Serum levels of advanced oxidation protein products (AOPP) and superoxide dismutase (SOD) were measured in all groups.The levels of AOPP in groups A,B,C were higher and SOD levels were lower than those of normal controls ( all P ＜ 0.01 ).The levels of AOPP in groups B,C were lower and SOD were higher than those in group A at the same time points (P ＜0.01 ).The levels of AOPP in group C were lower and SOD were higher than those in group B at the same time points (P ＜0.0l ).The results suggest that pretreatment of the dialyzer with high dose vitamin C plus vitamin E and compound danshen tablets can alleviate oxidative stress in patients with maintaining hemodialysis.

Objective:To prepare mesalazineβ-cyclodextrin inclusion compound and observe its properties. Methods:The struc-ture was characterized by UV, IR and DSC. The inclusion process of mesalazine andβ-cyclodextrin was simulated using molecular doc-king technique. The solubility and dissolution of inclusion compound were determined. Results:UV, IR and DSC were used to deter-mine the formation of inclusion complex. The inclusion ratio was 1: 1 and the phase solubility diagram was AL type. The solubility of inclusion compound in deionized water (25 ℃, pH 7. 0) was 7. 8 mg·ml-1 . The preparation of mesalazine β-cyclodextrin inclusion compound could significantly increase the dissolution rate and solubility of mesalazine. Conclusion:The prepared mesalazineβ-cyclo-dextrin inclusion compound can obviously improve the poor water solubility and dissolution of mesalazine.

A blood pressure measurement system based on internet of things and deep learning is proposed for continuous data acquisition and blood pressure prediction.The system adopts a hybrid neural network structure for processing the collected data and accurately predicting blood pressure,and the model consists of ResNet18,GRU and 3 fully connected layers.The data of 82 individuals are collected for training and testing.The mean absolute errors and standard deviations are 2.16 mmHg and 3.09 mmHg for diastolic blood pressure,3.15 mmHg and 5.14 mmHg for systolic blood pressure,according with AAMI standard and BHS standard.