Objective To explore the application value of real-time shear wave elastography (SWE) technique in diagnosing and staging of chronic viral hepatitis B and hepatic fibrosis and to establish Young's modulus reference range for diagnosing and staging of hepatic fibrosis.Methods Forty-eight patients with chronic hepatitis B and fifty-eight healthy adults were enrolled and their Young's modulus values of S5 and S6 segments of liver were measured.Histopathologic examination was performed on 48 patients with chronic hepatitis B.Comparative analysis was conducted between the pathological findings and Young's modulus values,by means of which Young's modulus reference range for diagnosis and staging of hepatic fibrosis was obtained.Results There was significant difference in Young's modulus values of S5 and S6 segments of liver between chronic hepatitis B group and the normal control group (P＜0.05).Young's modulus values of S5 and S6 segments of liver in chronic hepatitis B group were (11.7 ± 2.9) kPa and (12.1 ± 3.2) kPa respectively,which were significantly higher than those in the normal control group,(5.7 ± 1.1) kPa and (5.8 ± 1.3) kPa respectively.Significant differences of Young's modulus values were detected in every staging of hepatic fibrosis (P＜0.05).S5 segment of liver Young's modulus values in S0-S4 stages were (5.8 ± 2.2) kPa,(7.3 ± 1.9) kPa,(10.3 ± 2.8) kPa,(10.3 ± 2.8) kPa,and (25.3 ± 3.6) kPa,respectively.S6 segment of liver Young's modulus values in S0-S4 stages were (5.7 ± 2.3) kPa,(9.2±2.1) kPa,(10.5±2.1) kPa,(14.7±4.5) kPa,and (26.1 ±2.1) kPa,respectively.Young's modulus value of the liver rose with the increase of S stage.Conclusion SWE technique can establish the Young's modulus reference range for hepatic fibrosis stage.Besides,it features high sensitivity,specificity and accuracy.

Objective:To explore the current situation of evidence-based practice competence of nurses with master's degree at Class Ⅲ hospitals in Henan Province and its influencing factors so as to provide a reference for managers to formulate the targeted continuing education plan.Methods:From March 2019 to April 2019, we selected 133 nurses with master's degree of 6 ClassⅢ hospitals in Zhengzhou City of Henan Province as subjects by purposive sampling. All of nurses were investigated with the Chinese version of Evidence Based Practice Evaluation Competence Questionnaire (EBP-COQ) and the Barriers to Research Utilization Scale. Multiple linear regression was used to analyze the influencing factors.Results:Among 133 nurses with master's degree, the total scores of the EBP-COQ and the Barriers to Research Utilization Scale were (98.57±11.01) and (79.66±20.46) respectively. Multiple linear regression analysis showed that the influencing factors of evidence-based practice competence of nurses with master's degree included the working lives, positional titles, attending evidence-based nursing training, awareness to evidence-based practice, accessibility of research funding and resource conditions of evidence-based nursing ( P<0.05) . Conclusions:Nurses with master's degree in Henan Province have the intermediate level of evidence-based practice competence and positive attitudes to evidence-based practice, but their evidence-based knowledge and skills need to be improved. Nursing managers should pay more attention to evidence-based practice competence training of nurses with master's degree, provide many supportive resources and environments, promote evidence-based practice skills training so as to boost the development of specialist nursing practice.

BACKGROUND:At present,the dental composite resin filling material composed of resin matrix monomer is the first choice material for the filling treatment of dental defects,but with the increase of its use time in the oral environment,the dental tissue will develop secondary caries and the filling material will wear and break.The main cause of these problems is the polymerization shrinkage of the filling material and its mismatch with the mechanical properties of the dental tissue. OBJECTIVE:To synthesize a new type of dental composite resin monomer by adding initiators with different components,to improve the traditional double bond conversion rate of the system and further improve the mechanical properties of the material. METHODS:A new composite resin matrix system was prepared by adding different initiators to the monomer of 3,3′,5,5′-tetramethoxybiphenyl-4,4′-diol epoxy acrylate resin.In group A,camphorquinone with a mass fraction of 1.1%was added.In group B,1-phenyl-1,2-propanedione with a mass fraction of 2.1%was added.In group C,a mixture of camphorquinone and 1-phenyl-1,2-propanedione(a mass ratio of the two was 1:1)with a mass fraction of 3.1%was added.The double bond conversion,polymerization shrinkage and mechanical properties of the samples were determined. RESULTS AND CONCLUSION:(1)The double bond conversion rate of groups B and C was higher than that of group A(P<0.05).The polymerization shrinkage of group B was higher than that of group A(P<0.05),while that of group C was lower than that of group A(P<0.05).(2)The flexural strength,elastic modulus and compressive strength of groups B and C were higher than those of group A(P<0.05,P<0.01).Vickers hardness of group B was higher than that of group A(P<0.05),and the Vickers hardness of group C was lower than that of group A(P<0.01).(3)These findings suggest that 1-phenyl-1,2-propanedione is an initiator with ideal performance.The combined application of 1-phenyl-1,2-propanedione and camphorquinone can effectively improve the double bond conversion rate of the resin matrix system and further improve the mechanical property of the resin.

Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.