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Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing

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Journal of Molecular Cell Biology 2019年第8期11卷 665-677页

作者： Yiyu Lu Zhaoyuan Fang Meiyi Li Chen Qian Tao Zeng Lina Lu Qilong Chen Hui Zhang Qianmei Zhou Yan Sun Xuefeng Xue Yiyang Hu Luonan Chen Shibing Su Institute of Interdisciplinary Integrative Medicine Research Shanghai University of Traditional Chinese Medicine Shanghai 201203 China Key Laboratory of Systems Biology Center for Excellence in Molecular Cell Science Institute of Biochemistry and Cell Biology Shanghai Institute of Biological Sciences Chinese Academy of Sciences Shanghai 200031 China Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming 650223 China Qidong Liver Cancer Institute Qidong People's Hospital Qidong 226200 China Institute of Liver Disease Shuguang Hospital Shanghai University of Traditional Chinese Medicine Shanghai 201203 China Minhang Branch Zhongshan Hospital/lnstitute of Fudan-Minhang Academic Health System Minhang Hospital Fudan University Shanghai 201199 China School of Life Science and Technology Shanghai Tech University Shanghai 201210 China Research Center for Brain Science and Brain-Inspired Intelligence Shanghai 201210 China

Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. coexpressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives.

关键词： hepatitis B virus hepatocellular carcinoma diagnosis and prognosis edge-based biomarker dynamic network biomarker

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A Discontinuous Galerkin Extension of the Vertex-Centered edge-based Finite Volume Method

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Communications in Computational Physics 2009年第2期5卷 456-468页

作者： Martin Berggren Sven-Erik Ekstrom Jan Nordstrom Department of Computing Science Ume˚a UniversitySE-90187 Ume˚a Sweden Division of Scientific Computing Department of Information TechnologyUppsala UniversityBox 337SE-75105 UppsalaSweden

The finite volume(FV)method is the dominating discretization technique for computational fluid dynamics(CFD),particularly in the case of compressible *** discontinuous Galerkin(DG)method has emerged as a promising highaccuracy *** standard DG method reduces to a cell-centered FV method at lowest ***,many of today’s CFD codes use a vertex-centered FV method in which the data structures are edge *** develop a new DG method that reduces to the vertex-centered FV method at lowest order,and examine here the new scheme for scalar hyperbolic ***,the method shows optimal-order accuracy for a smooth linear *** applying a basic hp-adaption strategy,the method successfully handles *** also discuss how to extend the FV edge-based data structure to support the new *** this way,it will in principle be possible to extend an existing code employing the vertex-centered and edge-based FV discretization to encompass higher accuracy through the new DG method.

关键词： Discontinuous Galerkin methods finite volume methods dual mesh vertex-centered edge-based CFD

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Cascading failures of overload behaviors using a new coupled network model between edges

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Chinese Physics B 2022年第1期31卷 704-710页

作者： Yu-Wei Yan Yuan Jiang Rong-Bin Yu Song-Qing Yang Cheng Hong School of Information Engineering Nanchang Hangkong UniversityNanchang 330063China

With the development of network science,the coupling between networks has become the focus of complex network ***,previous studies mainly focused on the coupling between nodes,while ignored the coupling between *** propose a novel cascading failure model of two-layer *** model considers the different loads and capacities of edges,as well as the elastic and coupling relationship between *** addition,a more flexible load-capacity strategy is adopted to verify the *** simulation results show that the model is *** networks have different behaviors for the same *** changing the load parameters,capacity parameters,overload parameters,and distribution parameters reasonably,the robustness of the model can be significantly improved.

关键词： cascade failure overload load distribution edge-based

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Corner-based Image Alignment using Pyramid Structure with Gradient Vector Similarity

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Journal of Signal and Information Processing 2013年第3期4卷 114-119页

作者： Chin-Sheng Chen Kang-Yi Peng Chien-Liang Huang Chun-Wei Yeh Department of Electronic Electrical & Computer Engineering University of Birmingham UK. Graduate Institute of Automation Technology National Taipei University of Technology

This paper presents a corner-based image alignment algorithm based on the procedures of corner-based template matching and geometric parameter estimation. This algorithm consists of two stages: 1) training phase, and 2) matching phase. In the training phase, a corner detection algorithm is used to extract the corners. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. A parabolic function is further applied to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against non-liner light changes. The accuracy and precision of the corner-based image alignment are competitive to that of edge-based image alignment under the same environment. In practice, the proposed algorithm demonstrates its precision, efficiency and robustness in image alignment for real world applications.

关键词： Corner-based Image Alignment Corner Detection edge-based Template Matching Gradient Vector

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