The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation...The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation for the establishment of prevention and control systems to protect citizens’property.However,the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime platforms have some apparent drawbacks.For instance,the methods suffer from data-distribution differences and tremendous manual efforts spent on data labeling.Therefore,a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed.This method first identifies the text data and their tags,and then performs migration training based on a pre-training model.Finally,the method uses the fine-tuned model to predict and classify new cyber-telecom crimes.Experimental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method,compared with the deep-learning method.展开更多
The landscape of hepatitis B virus(HBV)integration in the plasma cell-free DNA(cfDNA)of HBV-infected patients with different stages of liver diseases[chronic hepatitis B(CHB),liver cirrhosis(LC),and hepatocellular car...The landscape of hepatitis B virus(HBV)integration in the plasma cell-free DNA(cfDNA)of HBV-infected patients with different stages of liver diseases[chronic hepatitis B(CHB),liver cirrhosis(LC),and hepatocellular carcinoma(HCC)]remains unclear.In this study,we developed an improved strategy for detecting HBV DNA integration in plasma cfDNA,based on DNA probe capture and next-generation sequencing.Using this optimized strategy,we successfully detected HBV integration events in chimeric artificial DNA samples and HBV-infected HepG2-NTCP cells at day one post infection,with high sensitivity and accuracy.The characteristics of HBV integration events in the HBV-infected HepG2-NTCP cells and plasma cfDNA from HBV-infected individuals(CHB,LC,and HCC)were further investigated.A total of 112 and 333 integration breakpoints were detected in the HepG2-NTCP cells and 22 out of 25(88%)clinical HBV-infected samples,respectively.In vivo analysis showed that the normalized number of support unique sequences(nnsus)in HCC was significantly higher than in CHB or LC patients(P values<0.05).All integration breakpoints are randomly distributed on human chromosomes and are enriched in the HBV genome around nt 1800.The majority of integration breakpoints(61.86%)are located in the gene-coding region.Both non-homologous end-joining(NHEJ)and microhomology-mediated end-joining(MMEJ)interactions occurred during HBV integration across the three different stages of liver diseases.Our study provides evidence that HBV DNA integration can be detected in the plasma cfDNA of HBV-infected patients,including those with CHB,LC,or HCC,using this optimized strategy.展开更多
基金supported in part by the Basic Public Welfare Research Program of Zhejiang Province under Grant LGF20G030001.
文摘The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation for the establishment of prevention and control systems to protect citizens’property.However,the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime platforms have some apparent drawbacks.For instance,the methods suffer from data-distribution differences and tremendous manual efforts spent on data labeling.Therefore,a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed.This method first identifies the text data and their tags,and then performs migration training based on a pre-training model.Finally,the method uses the fine-tuned model to predict and classify new cyber-telecom crimes.Experimental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method,compared with the deep-learning method.
基金supported by the National Key Research and Development Program of China(2018YFE0107500)the CQMU Program for Youth Innovation in Future Medicine(W0160)to Yuan Hu+3 种基金Scientific and Technological Research Program of Chongqing Municipal Education Commission(KJQN202100422)Scientific Research Projects in Yuzhong District of Chongqing(20210116)to HaiJun Dengthe 111 Project(D20028)to AiLong Huangand the Natural Science Foundation of Chongqing(cstc2021jcyjmsxmX0202)to Hongchun Luo.
文摘The landscape of hepatitis B virus(HBV)integration in the plasma cell-free DNA(cfDNA)of HBV-infected patients with different stages of liver diseases[chronic hepatitis B(CHB),liver cirrhosis(LC),and hepatocellular carcinoma(HCC)]remains unclear.In this study,we developed an improved strategy for detecting HBV DNA integration in plasma cfDNA,based on DNA probe capture and next-generation sequencing.Using this optimized strategy,we successfully detected HBV integration events in chimeric artificial DNA samples and HBV-infected HepG2-NTCP cells at day one post infection,with high sensitivity and accuracy.The characteristics of HBV integration events in the HBV-infected HepG2-NTCP cells and plasma cfDNA from HBV-infected individuals(CHB,LC,and HCC)were further investigated.A total of 112 and 333 integration breakpoints were detected in the HepG2-NTCP cells and 22 out of 25(88%)clinical HBV-infected samples,respectively.In vivo analysis showed that the normalized number of support unique sequences(nnsus)in HCC was significantly higher than in CHB or LC patients(P values<0.05).All integration breakpoints are randomly distributed on human chromosomes and are enriched in the HBV genome around nt 1800.The majority of integration breakpoints(61.86%)are located in the gene-coding region.Both non-homologous end-joining(NHEJ)and microhomology-mediated end-joining(MMEJ)interactions occurred during HBV integration across the three different stages of liver diseases.Our study provides evidence that HBV DNA integration can be detected in the plasma cfDNA of HBV-infected patients,including those with CHB,LC,or HCC,using this optimized strategy.
