Objective To analyze the associated factors on abnormal liver function(LF)in chronic schistosomiaisis japonica patients.MethodsThe clinical data of 120 inpationts with chronic schistosomiasis were collected and analyzed by logistic regression.The relevant treatment methods were summarized.ResultsThe associated factors on abnormal LF of the patients were hepatitis B,alcohol drinking,hyperlipidemia,nonalcoholic fatty liver disease(NAFLD),and obesity,respectively.The ordinary medication for improving liver function was effective to these causes.Praziquantal can be administrated successfully to these patients after LF normalized.ConclusionChronic schistosomiasis patients with abnormal LF but without severe vital organ diseases could be treated with praziquantal after their LF improving.

Objective:To explore the mediation effect of personality between negative life events and risky mentation of university students.Methods:A cross sectional investigation was conducted among 8 379 freshmen with the adolescent self-rating life events check list (ASLEC), the prodromal questionnaire(PQ-16) and the Eysenck personality questionnaire (EPQ). The data were analyzed by SPSS 23.0 and AMOS 24.0.Results:The total score of negative life events scale((31.16±0.58) vs (15.19±0.15)), the scores of neuroticism((58.20±0.36) vs (41.59±0.13)) and psychoticism((53.07±0.29) vs (47.71±0.08)) in the risk psychological state group were significantly higher ( t=26.611, 42.270, 17.286, all P<0.01), and the score of introversion-extroversion factor was significantly lower((49.83±0.42) vs (55.88±0.13), t=-13.634, P<0.01) than those in the risk-free psychological state group. There was a positive correlation between the scores of risk psychological state and negative life events( r=0.290, 0.334, both P<0.01), and the scores of risk psychological state and negative life events were positively correlated with the scores of personality neuroticism and psychoticism ( r=0.139-0.469, all P<0.01) in both risk psychological state and risk-free psychological state group.The risk psychological state score of college students was negatively correlated with the inside and outside personality score( r=-0.070, P<0.01), and the score of negative life events was not correlated with introversion-extroversion personality score in the risk psychological state group, while the score of risk psychological state, negative life events and introversion-extroversion personality score were negatively correlated in the risk-free psychological state group ( r=-0.177, -0.080, P<0.01). The personality of college students played a complete mediating role between negative life events and risk psychological state in the risk psychological state group, while the personality of college students in the risk-free psychological state group played a partial mediating role between negative life events and risk psychological state, accounted for 71.43% of the total effect. Conclusion:Negative life events not only directly lead to the risky mentation of college students, but also affect the risky mentation of college students by the mediation effect of introverted and extroverted tendency and unstable emotion.

Objective:To evaluate artificial intelligence constructed by deep convolutional neural network (DCNN) for the site identification in upper gastrointestinal endoscopy.Methods:A total of 21 310 images of esophagogastroduodenoscopy from the Cancer Hospital of Chinese Academy of Medical Sciences from January 2019 to June 2021 were collected. A total of 19 191 images of them were used to construct site identification model, and the remaining 2 119 images were used for verification. The performance differences of two models constructed by DCCN in the identification of 30 sites of the upper digestive tract were compared. One model was the traditional ResNetV2 model constructed by Inception-ResNetV2 (ResNetV2), the other was a hybrid neural network RESENet model constructed by Inception-ResNetV2 and Squeeze-Excitation Networks (RESENet). The main indices were the accuracy, the sensitivity, the specificity, positive predictive value (PPV) and negative predictive value (NPV).Results:The accuracy, the sensitivity, the specificity, PPV and NPV of ResNetV2 model in the identification of 30 sites of the upper digestive tract were 94.62%-99.10%, 30.61%-100.00%, 96.07%-99.56%, 42.26%-86.44% and 97.13%-99.75%, respectively. The corresponding values of RESENet model were 98.08%-99.95%, 92.86%-100.00%, 98.51%-100.00%, 74.51%-100.00% and 98.85%-100.00%, respectively. The mean accuracy, mean sensitivity, mean specificity, mean PPV and mean NPV of ResNetV2 model were 97.60%, 75.58%, 98.75%, 63.44% and 98.76%, respectively. The corresponding values of RESENet model were 99.34% ( P<0.001), 99.57% ( P<0.001), 99.66% ( P<0.001), 90.20% ( P<0.001) and 99.66% ( P<0.001). Conclusion:Compared with the traditional ResNetV2 model, the artificial intelligence-assisted site identification model constructed by RESENNet, a hybrid neural network, shows significantly improved performance. This model can be used to monitor the integrity of the esophagogastroduodenoscopic procedures and is expected to become an important assistant for standardizing and improving quality of the procedures, as well as an significant tool for quality control of esophagogastroduodenoscopy.