OBJECTIVE: To establish an artificial neural network (ANN) for predicting tacrolimus concentrations in kidney transplantation recipients. METHODS: Three hundred and twenty-two tacrolimus concentration data from 55 Chinese kidney transplantation recipients were collected. ANN was established after the network parameters were optimized by using momentum method combined with genetic algorithm. Furthermore, the performance of ANN was compared with that of multiple linear regression (MLR). RESULTS: When using the accumulated dose of tacrolimus in the 6 d before TDM as the input factor, the mean prediction error and mean absolute prediction error of ANN were (0.13±1.91) and (1.49±1.22) ng·L-1, respectively. The absolute prediction errors for 87.9% of the test data set were less than 3.0 ng·L-1. The accuracy and precision of ANN were superior to those of MLR. CONCLUSION: The correlation, accuracy and precision of ANN are good enough to predict tacrolimus concentration.

OBJECTIVE：To establ ish artificial neural netw orks（ANN）model to predict the interferon in the treatment of chronic hepatitis B （CHB），and to provide evidence for selecting suitable CHB therapy plan in clinic. METHODS ：The clinical data of 92 CHB patients treated by interferon ，from Guangzhou Eighth People ’s Hospital were retrospectively analyzed from Jul. 2011 to Dec. 2019. The basic information ，biochemical indexes ，blood routine indexes and virological markers of patients were collected. According to the effect of interferon ，the patients were divided into response group （73 cases）and non-response group （19 cases）. Minitab 18.0 software was used for multivariate Logistic regression analysis to screen the factors influencing the efficacy of interferon. Neurosolutions 5.0 software was used to randomly select 30％ of patients with CHB （27 cases）as the test group to establish and verify the ANN model. RESULTS ：The mean platelet volume ，platelet distribution width ，direct bilirubin ， hepatitis B e antigen and hepatitis B virus DNA more than 4×107 IU/mL had significant effect on interferon response （P＜0.05）. The accuracy ，specificity and area under characteristic curve of ANN test group were significantly higher than those of Logistic regression（P＜0.05）. CONCLUSIONS ：ANN model is accurate in predicting the efficacy of interferon in the treatment of CHB.

OBJECTIVEThe residual dentin thickness of first premolars were measured by anatomical methods before and after post preparation, the data from which can help clinicians to choose proper sizes of peeso drill.

METHODS30 first maxillary premolars and 30 first mandibular premolars were collected. Walls of 4 mm short of the apex were respectively measured before and after post preparation with peeso drills number 1-3.

RESULTSThe measurement results of all indexes assumed a normal distribution. For two-canal first maxillary premolars and single-canal first mandibular premolars, the average residual mesial and distal thickness of root walls 4 mm short of the apex were less than 1 mm after post preparation by number 3 peeso drill. The buccal root had nonsignificant differences (P>0.05). The palatine root and the first mandibular premolars had significant differences (P<0.05). For single-canal first maxillary premolars, the average residual mesial and distal thickness were less than 1 mm after post preparation by number 2 peeso drill. The distal wall had significant differences (P<0.05).

CONCLUSIONIn post preparation, for the buccal root of two-canal maxillary premolars, the maximum size of peeso drill was number 3, and for the palatine root and first mandibular premolars, the size was number 2, and for single-canal maxillary first premolars, the size was number 1.

Bicuspid ; Dental Pulp Cavity ; Dentin ; Humans ; Post and Core Technique ; Root Canal Preparation ; Tooth Root

This study is to establish an artificial neural network (ANN) for predicting blood tacrolimus concentration in liver transplantation recipients. Tacrolimus concentration samples (176 samples) from 37 Chinese liver transplantation recipients were collected. ANN established after network parameters were optimized by using momentum method combined with genetic algorithm. Furthermore, the performance of ANN was compared with that of multiple linear regression (MLR). When using accumulated dose of 4 days before therapeutic drug monitoring (TDM) of tacrolimus concentration as input factor, mean prediction error and mean absolute prediction error of ANN were 0.02 +/- 2.40 ng x mL(-1) and 1.93 +/- 1.37 ng x mL(-1), respectively. The absolute prediction error of 84.6% of testing data sets was less than 3.0 ng x mL(-1). Accuracy and precision of ANN are superior to those of MLR. The correlation, accuracy and precision of ANN are good enough to predict blood tacrolimus concentration.
Adult ; Aged ; Drug Monitoring ; methods ; Female ; Humans ; Immunosuppressive Agents ; blood ; Linear Models ; Liver Transplantation ; Male ; Middle Aged ; Neural Networks (Computer) ; Tacrolimus ; blood

Objective To analyze the effect of extracorporeal shock wave assisted drug therapy on clinical outcomes of patients with temporomandibular disorders(TMD).Methods A total of 86 TMD patients in our hospital from September 2018 to September 2019 were included and divided into group A(n=43)and group B(n=43)by random number table method.Group A(n=43)received oral glucosamine hydrochloride tablets on the basis of conventional treatment;group B(n=43)received extracorporeal shock wave therapy on the basis of group A.The pain degree,maximum mouth opening,temporomandibular joint function,temporomandibular joint bounce times,life quality and occurrence of adverse reactions were compared between the two groups.Results Compared with that before treatment,the visual analogue scale(VAS)scores,maximum mouth opening,temporomandibular joint dysfunction index(DI),palpation index(PI),Fricton craniomandibular index(CMI)level,joint bounce times and oral health impact scale(OHIP-14)score of two groups were significantly improved(P＜0.05),and all indexes in group B were significantly better than those in group A(P＜0.05).There was no significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion Extracorporeal shock wave assisted drug therapy can effectively reduce joint bounce in TMD patients,relieve patients'pain,improve patients'life quality and temporomandibular joint function,and has good safety.

At present,traditional Chinese medicine(TCM) has attracted more and more attention from the international community.The demand for TCM is increasing in the world.The hidden dangers of potential quality and safety of TCM are also becoming increasingly prominent.Aflatoxin contamination has become one of the important factors affecting the safety of Chinese herbal medicines,and it will fundamentally affect human health and life safety.A variety of methods are used to reduce aflatoxins,however,there are few suitable methods that can be widely used in the cost-effective and large-scale promotion of Chinese herbal medicines.Therefore,it is of great significance to continue to study measures to solve the pollution problems of Aspergillus flavus and its toxins.This article summarizes the hazards and contamination status of aflatoxin,the prevention and control of the growth of A. flavus, and the measures for reducing aflatoxin,and looks ahead to the future prevention and control of A. flavus and its toxins,aiming at providing ideas for the pollution problem of A. flavus and its toxin,to ensure the quality of Chinese herbal medicines,so as to ensure clinical safety medication.