Yu Lei

Chongqing Medical University, Ch’ung-ch’ing-shih, Chongqing Shi, China

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Publications (62)22.97 Total impact

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    ABSTRACT: Blood CXCR5+CD4+ T cells are defined as circulating T follicular helper (TFH) cells, which is required for effective humoral immunity. This study aimed to investigate the role of circulating TFH cells in patients with chronic hepatitis B virus (CHB) infection. The frequency and phenotype of circulating TFH cells were monitored by flow cytometry in CHB patients and in healthy controls (HC). The expression of BCL-6, IL-21, IL-4, CXCR5, and IL-6R mRNA was analyzed using real-time PCR. Serum HBsAg, HBeAg, HBeAb, HBV DNA loads, ALT and AST were determined. The potential association of the frequency of TFH cells and their surface markers with clinical parameters was assessed. The frequency of CXCR5+CD4+ T cells was increased in CHB patients and positively correlated with ALT and AST but not with HBV DNA loads. Moreover, an expansion of ICOS-, PD-1-, CD40L-, and IL-21R-expressing TFH cells occurred in CHB patients, but failed to correlate with ALT, AST and HBV DNA loads. Interestingly, the frequency of CXCR5+CD4+ T cells and ICOS+CXCR5+CD4+ T cells was significantly higher in HBeAg positive CHB patients than in HC. Additionally, the percentages of CXCR5+CD4+ T cells were positively correlated with AST, and ICOS-expressing CXCR5+CD4+ T cells were negatively correlated with HBV DNA loads. No significant differences in the frequency of CXCR5+CD4+ T cells were observed between inactive carrier (IC) patients and healthy controls. However, ICOS-, PD-1-, CD40L-expressing TFH cells were increased in IC patients and positively correlated with AST. Furthermore, the expression of BCL-6, IL-21, IL-4, CXCR5, and IL-6R mRNA in TFH cells was higher in CHB patients than in HC. These data demonstrate that circulating TFH cells may participate in HBV-related immune responses. In addition to the frequency of TFH cells, the phenotype of these cells plays an important role in CHB patients.
    Virology Journal 03/2014; 11(1):54. · 2.09 Impact Factor
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    ABSTRACT: To study the role of tumor necrosis factor-alpha (TNFalpha) in the anti-replication effects of tetracycline (Tet) on hepatitis B virus (HBV). The Tet-dependent regulatory fragment (TO) was PCR amplified from the pcDNA4TM/TO vector, inserted into the pUC118 cloning vector, and verified by sequencing. The counterpart fragment in the pVITRO3 expression vector, which contains two multiple cloning sites (MCSs), was replaced with the confirmed TO to generate a pVITRO3-TO vector. The Tet repressor (TR) gene from the pcDNA6/TR regulatory vector was incorporated into one MCS of pVITRO3-TO and the TNFalpha gene was subsequently incorporated into the other MCS. The resultant vector, pVITRO3-TOTR-TNFalpha, was transiently transfected into HepG2 cells. TNFalpha expression from the vector was induced by exposure to various concentrations of Tet and measured by enzyme-linked immunosorbent assay to determine the appropriate Tet concentration for experimentation. To investigate whether Tet inhibits TNFalpha expression as a mechanism of its anti-replication activity against HBV, the HepG2.2.15 cell line stably transfected with pVITRO3-TOTR-TNFalpha was used as an HBV replication model. Levels of hepatitis B e antigen (HBeAg) and hepatitis B surface antigen (HBsAg) were detected by immunoassay. HBV DNA level was detected by fluorescence quantitative PCR. The TNFalpha expression from the newly constructed pVITRO3-TOTR-TNFalpha vector was Tet-controllable in the eukaryotic cells examined. The optimal concentration of Tet for the experimental system was 1.0 mug/ml. HBsAg and HBeAg expression was down-regulated in the HepG2.2.15 cells stably transfected with the pVITRO3-TO-TR-TNFalpha vector. After incubation with Tet for 1, 3 and 5 days, the inhibition rate of HBsAg was 2%, 1.1% and 0, compared to 14.8%, 11.5% and 28.4% in the non-Tet control group. The corresponding inhibition rates of HBeAg were 50.0%, 26.7% and 47.9%, compared to 0.3%, 1.6% and 0.0%, in the control group. HBV DNA levels in the cells and the cell culture supernatants exposed to Tet were decreased by 70.3% and 79.9%, respectively. TNFalpha inhibited production of HBsAg mRNA. A Tet-dependent regulatory fragment double-expressing TNFalpha single vector system was constructed successfully, achieving controllable TNFalpha expression in both transiently transfected eukaryotic cells and stable cell lines. In this HBV cell model system, Tet-induced overexpression of human TNFalpha inhibited HBV DNA replication and reduced HBsAg and HBeAg expression. Inhibition of HBV transcription may be a key role of TNFalpha against HBV replication.
    Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology 03/2014; 22(3):213-8.
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    ABSTRACT: Some conflicting results have been reported on the comparison between t-way combinatorial testing and random testing. In this paper, we report a new study that applies t-way and random testing to the Siemens suite. In particular, we investigate the stability of the two techniques. We measure both code coverage and fault detection effectiveness. Each program in the Siemens suite has a number of faulty versions. In addition, mutation faults are used to better evaluate fault detection effectiveness in terms of both number and diversity of faults. The experimental results show that in most cases, t-way testing performed as good as or better than random testing. There are few cases where random testing performed better, but with a very small margin. Overall, the differences between the two techniques are not as significant as one would have probably expected. We discuss the practical implications of the results. We believe that more studies are needed to better understand the comparison of the two techniques.
    2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops (ICSTW); 03/2014
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    ABSTRACT: A t-way covering array can detect t-way faults, however they generally include other combinations beyond t-way as well. For example, a particular test set of all 5-way combinations is shown capable of detecting all seeded faults in a test program, despite the fact that it contains up to 9-way faults. This poster gives an overview of methods for estimating fault detection effectiveness of a test set based on combinatorial coverage for a class of software. Detection effectiveness depends on the distribution of t-way faults, which is not known. However based on past experience one could say for example the fraction of 1-way faults is F1 = 60 %, 2- way faults F2 = 25 % F3 = 10 % and F4 = 5 %. Such information could be used in determining the required strength t. It is shown that the fault detection effectiveness of a test set may be affected significantly by the t-way fault distribution, overall, simple coverage at each level of t, number of values per variable, and minimum t-way coverage. Using these results, we develop practical guidance for testers.
    2014 IEEE Seventh International Conference on Software Testing, Verification and Validation Workshops (ICSTW); 03/2014
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    ABSTRACT: A software product line is a set of software systems that share some common features. Several recent works have been reported that apply combinatorial testing, a very effective testing strategy, to software product lines. A unique challenge in these efforts is dealing with a potentially large number of constraints among different features. In this paper, we propose a novel constraint-handling strategy that uses minimum invalid tuples (MITs) as an alternative to traditional constraint solvers. Our approach systematically derives all MITs from a software product line, and uses them to quickly determine the validity of a test configuration during test generation. We implemented a test generation research tool called LOOKUP that integrates the proposed constraint-handling strategy with a general test generation algorithm called IPOG-C. Experimental results show that LOOKUP performs considerably better than two existing test generation tools in terms of test size and execution time.
    Proceedings of the 2014 IEEE 15th International Symposium on High-Assurance Systems Engineering; 01/2014
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    ABSTRACT: Security testing aims at detecting program security flaws through a set of test cases and has become an active area of research. The challenge is how to efficiently produce test cases that are highly effective in detecting security flaws. This paper presents a novel distributed demand-driven security testing system to address this challenge. It leverages how end users use the software to increase the coverage of essential paths for security testing. The proposed system consists of many client sites and one testing site. The software under test is installed at each client site. Whenever a new path is about to be exercised by a user input, it will be sent to the testing site for security testing. At the testing site, symbolic execution is used to check any potential vulnerability on this new path. If a vulnerability is detected, a signature is automatically generated and updated to all client sites for protection. The benefits are as follows. First, it allows us to focus testing on essential paths, i.e., the paths that are actually being explored by users or attackers. Second, it stops an attacker from exploiting an unreported vulnerability at the client site. A prototype system has been implemented to evaluate the performance of the proposed system. The results show that it is both effective and efficient in practice.
    Journal of Systems and Software 01/2014; 87:60–73. · 1.25 Impact Factor
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    ABSTRACT: Mother-to-child transmission (MTCT) is the main mode of spread of hepatitis B virus (HBV) in China. We performed a meta-analysis to compare the effects of three measures for prevention of MTCT. A meta-analysis was performed on randomized controlled trials and non-randomized studies comparing the index of MTCT among five groups of pregnant women: hepatitis B immunoglobulin (HBIG) administration, antiviral treatment, placebo, elective caesarean section, and vaginal delivery. Compared with the control group, the incidence of HBV intrauterine infection (RR = 0.42, 95 % CI 0.27-0.64, P < 0.0001) and the number of chronic hepatitis B (CHB) infants (RR = 0.44, 95 % CI 0.32-0.61, P < 0.00001) were lower in the HBIG administration group. In the antiviral treatment group, serum HBV DNA levels were lower (MD = -4.01, 95 % CI -5.07 to -2.94, P < 0.00001) at the time of delivery, and normalization of ALT levels was better (RR = 1.11, 95 % CI 1.06-1.17, P < 0.0001). Infant serum HBsAg positivity (RR = 0.45, 95 % CI 0.22-0.91, P = 0.03) and incidence of infant HBV transmission RR = 0.06, 95 % CI 0.01-0.24, P < 0.0001) were reduced in antiviral the treatment group. Infant serum anti-HBs positivity at birth (RR = 1.24, 95 % CI 0.89-1.74, P = 0.2) or at 6-7 months (RR = 0.98, 95 % CI 0.86-1.11, P = 0.73) was not significantly different between the caesarean section and vaginal delivery groups. The incidence of infant CHB infection may have been higher in the vaginal delivery group (RR = 2.20, 95 % CI 1.02-4.74, P = 0.04). Administration of HBIG or antiviral therapy to HBV carrier mothers during pregnancy is effective in reducing MTCT.
    Digestive Diseases and Sciences 11/2013; · 2.26 Impact Factor
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    ABSTRACT: Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method.
    ACM Transactions on Knowledge Discovery from Data 11/2013; 7(4):17. · 1.15 Impact Factor
  • Measurement 11/2013; 46(9):3745-3752. · 1.53 Impact Factor
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    ABSTRACT: Trust prediction, which explores the unobserved relationships between online community users, is an emerging and important research topic in social network analysis and many web applications. Similar to other social-based recommender systems, trust relationships between users can be also modeled in the form of matrices. Recent study shows users generally establish friendship due to a few latent factors, it is therefore reasonable to assume the trust matrices are of low-rank. As a result, many recommendation system strategies can be applied here. In particular, trace norm minimization, which uses matrix's trace norm to approximate its rank, is especially appealing. However, recent articles cast doubts on the validity of trace norm approximation. In this paper, instead of using trace norm minimization, we propose a new robust rank-k matrix completion method, which explicitly seeks a matrix with exact rank. Moreover, our method is robust to noise or corrupted observations. We optimize the new objective function in an alternative manner, based on a combination of ancillary variables and Augmented Lagrangian Multiplier (ALM) Method. We perform the experiments on three real-world data sets and all empirical results demonstrate the effectiveness of our method.
    Proceedings of the Twenty-Third international joint conference on Artificial Intelligence; 08/2013
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    ABSTRACT: ISO/IEEE 11073 Personal Health Data (IEEE 11073 PHD) is a set of standards that addresses the interoperability of personal healthcare devices. As an important part of IEEE 11073 PHD, ISO/IEEE 1107-20601 optimized exchange protocol (IEEE 11073-20601) defines how personal healthcare devices communicate with computing resources like PCs and set-top boxes. In this paper, we propose a general conformance testing framework for IEEE 11073-20601 protocol stack. This framework can be used to ensure that different implementations of the protocol stack conform to the specification and are thus able to interoperate with each other. We are developing a prototype research tool that applies the proposed framework to Antidote, an open-sourced IEEE 11073-20601 protocol stack. We report some preliminary testing results.
    05/2013;
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    ABSTRACT: Empirical data demonstrate the value of t-way coverage, but in some testing situations, it is not practical to use covering arrays. However any set of tests covers at least some proportion of t-way combinations. This paper describes a variety of measures of combinatorial coverage that can be used in evaluating aspects of t-way coverage of a test suite. We also provide lower bounds on t-way coverage of several widely-used testing strategies, and describe a tool that analyzes test suites using the measures discussed in the paper.
    Software Testing, Verification and Validation Workshops (ICSTW), 2013 IEEE Sixth International Conference on; 01/2013
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    ABSTRACT: In this paper, we introduce a combinatorial test generation research tool called Advanced Combinatorial Testing System (or ACTS). ACTS supports t-way combinatorial test generation with several advanced features such as mixed-strength test generation and constraint handling. To facilitate its use and integration with other tools, ACTS provides three types of external interface, including a graphic user interface, a command line interface, and an application programming interface. ACTS is a freely distributed research tool and has been downloaded by more than 1200 companies and organizations.
    Software Testing, Verification and Validation (ICST), 2013 IEEE Sixth International Conference on; 01/2013
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    ABSTRACT: To investigate the impact of interferon-stimulated exonuclease 20 kDa (ISG20) on replication of genotype 2a hepatitis C virus (HCV) subgenomic replicon RNA and infectivity of the cell culture-derived HCV strain JFH1 to determine the potential of exogenously expressed ISG20 as an anti-viral therapy of chronic hepatitis C. Plasma vectors containing wild-type (WT) ISG20 or a catalytically-inactive mutant ISG20m were transiently transfected into Huh7, Huh7.5 and HEK293 cells, and the replication of a monocistronic subgenomic JFH1 RNA replicon, SGRm-JFH1BlaRL, was measured. Huh7.5 cells stably expressing ISG20, ISG20m, or the control vector were established by transducing replication incompetent pCX4-Bsr-myc retroviruses encoding WT ISG20, D94G mutant ISG20, or the empty vector, respectively, and selecting with 5 mug/mL of blasticidin for approximately three weeks. The stable Huh7.5 cells were then transfected with HCV replicon RNA and infected with cell culture-derived HCV to investigate inhibition capacity of ISG20 against HCV. Huh7.5-ISG20, Huh7.5-ISG20m, and Huh7.5-Bsr controls cells stably expressing ISG20, ISG20m, or the control vector, respectively, were constructed successfully; the ectopically expressed ISG20 and ISG20m were distributed in both nucleus and cytoplasm, as detected by immuno uorescence. SGRm-JFH1BlaRL replicated efficiently and with similar kinetics in the Huh7.5-Bsr and Huh7.5-ISG20m cells, with expression levels plateauing at 48-96 h post-transfection. In contrast, at all time points examined, SGRm-JFH1BlaRL replication was 9.1% to 16.7% in the Huh7.5-ISG20 cells. The Huh7, Huh7.5 and HEK293 cells transiently expressing ISG20 also showed 16.7% to 25.0% of HCV replication that the respective controls. In addition, the amount of infectious progeny JFH1 virus released in culture supernatants was 9.1% to 12.5% from the Huh7.5-ISG20 cells than from the Huh7.5-Bsr and Huh7.5-ISG20m cells at 48-72 h post-infection, and the latter two cultures produced similar JFH1 virus yields. Finally, the expression of HCV core protein was also lower in the Huh7.5-ISG20 cells, as detected by immunoblot analysis. Exogenous expression of ISG20, either in a transient or stable manner, suppresses not only replication of genotype 2a HCV RNA replicons but also JFH1 virus propagation in cultured hepatocytes. The exonuclease activity of ISG20 is required for its antiviral activities against HCV.
    Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology 01/2013; 21(1):33-7.
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    ABSTRACT: Combinatorial testing has attracted a lot of attention from both industry and academia. A number of reports suggest that combinatorial testing can be effective for practical applications. However, there are few systematic, controlled studies on the effectiveness of combinatorial testing. In particular, input parameter modeling is a key step in the combinatorial testing process. But most studies do not report the details of the modeling process. In this paper, we report an experiment that applies combinatorial testing to the Siemens suite. The Siemens suite has been used as a benchmark to evaluate the effectiveness of many testing techniques. Each program in the suite has a number of faulty versions. The effectiveness of combinatorial testing is measured in terms of the number of faulty versions that are detected. The experimental results show that combinatorial testing is effective in terms of detecting most of the faulty versions with a small number of tests. In addition, we report the details of our modeling process, which we hope to shed some lights on this critical, yet often ignored step, in the combinatorial testing process.
    Software Testing, Verification and Validation Workshops (ICSTW), 2013 IEEE Sixth International Conference on; 01/2013
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    ABSTRACT: The input space of a system must be modeled before combinatorial testing can be applied to this system. The effectiveness of combinatorial testing to a large extent depends on the quality of the input space model. In this paper we introduce an input space modeling methodology for combinatorial testing. The main idea is to consider the process of input space modeling as two steps, namely, input structure modeling and input parameter modeling. The first step tries to capture the structural relationship among different components in the input space. The second step tries to identify parameters, values, relations and constraints for individual components. We also suggest strategies about how to perform unit and integration testing based on the input space structure. We applied the proposed methodology to two real-life programs. We report our experience and results that demonstrate the effectiveness of the proposed methodology.
    Software Testing, Verification and Validation Workshops (ICSTW), 2013 IEEE Sixth International Conference on; 01/2013
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    ABSTRACT: This poster presents some measures of combinatorial coverage that can be helpful in estimating residual risk related to insufficient testing of rare interactions, and a tool for computing these measures.
    Empirical Software Engineering and Measurement, 2013 ACM / IEEE International Symposium on; 01/2013
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    ABSTRACT: Combinatorial testing has been shown to be a very effective testing strategy. After a failure is detected, the next task is to identify the fault that causes the failure. In this paper, we present an approach to fault localization that leverages the result of combinatorial testing. Our approach is based on a notion called failure-inducing combinations. A combination is failure-inducing if it causes any test in which it appears to fail. Given a failure-inducing combination, our approach derives a group of tests that are likely to exercise similar traces but produce different outcomes. These tests are then analyzed to locate the faults. We conducted an experiment in which our approach was applied to the Siemens suite as well as the grep program from the SIR repository that has 10068 lines of code. The experimental results show that our approach can effectively and efficiently localize the faults in these programs.
    Software Reliability Engineering (ISSRE), 2013 IEEE 24th International Symposium on; 01/2013
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    ABSTRACT: Combinatorial testing has been shown to be a very effective testing strategy. An important problem in combinatorial testing is dealing with constraints, i.e., restrictions that must be satisfied in order for a test to be valid. In this paper, we present an efficient algorithm, called IPOG-C, for constraint handling in combinatorial testing. Algorithm IPOG-C modifies an existing combinatorial test generation algorithm called IPOG to support constraints. The major contribution of algorithm IPOG-C is that it includes three optimizations to improve the performance of constraint handling. These optimizations can be generalized to other combinatorial test generation algorithms. We implemented algorithm IPOG-C in a combinatorial test generation tool called ACTS. We report experimental results that demonstrate the effectiveness of algorithm IPOG-C. The three optimizations increased the performance by one or two orders of magnitude for most subject systems in our experiments. Furthermore, a comparison of ACTS to three other tools suggests that ACTS can perform significantly better for systems with more complex constraints.
    Software Testing, Verification and Validation (ICST), 2013 IEEE Sixth International Conference on; 01/2013
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    ABSTRACT: The current study explored the characteristics of γδ T cells in the blood of HBV-associated acute-on-chronic liver failure (HBV-ACLF) patients and examined the relationship between γδ T cells and the clinical parameters. Blood samples were obtained from 26 patients with HBV-ACLF, 40 patients with chronic hepatitis B virus (HBV) infection (CHBV), and 25 healthy controls (HC). The frequencies of γδ T cells, subtype Vδ1T or Vδ2T, and CD45RO(+)γδ T cells were determined using flow cytometry. Intracellular cytokine staining analysis was used to evaluate the proportion of the IFN-γ-, TNF-α-, or IL-17-producing γδ T cells, and CD107a- or granzyme B-positive γδ T cells. We found that the proportion of γδ T cells in blood samples from HBV-ACLF patients was much lower than in samples from CHBV patients or healthy controls. After stimulation with PMA and ionomycin, γδ T cells from HBV-ACLF patients produced the greatest amount of TNF-α or IL-17 among the three groups. Granzyme B- or CD107a-positive γδ T cells were significantly more frequent than in CHBV or control samples. There was a negative correlation between the percent of TNF-α(+)γδ T cells and ALT or AST levels, and between the percent of CD107a(+)γδ T cells and TBiL or DBiL levels. These results suggest that γδ T cells might participate in liver injury in HBV-ACLF patients by producing increased amounts of inflammatory cytokines and/or cytotoxicity ability. These findings provide novel information regarding the pathogenesis of HBV-ACLF.
    Journal of Clinical Immunology 03/2012; 32(4):877-85. · 2.65 Impact Factor

Publication Stats

616 Citations
22.97 Total Impact Points

Institutions

  • 2012–2013
    • Chongqing Medical University
      Ch’ung-ch’ing-shih, Chongqing Shi, China
  • 2002–2013
    • University of Texas at Arlington
      • Department of Computer Sciences & Engineering
      Arlington, Texas, United States
    • North Carolina State University
      • Department of Computer Science
      Raleigh, NC, United States
  • 2010
    • University of Texas at Austin
      • Department of Computer Science
      Austin, Texas, United States