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4,936 results on '"Liu, Hongbo"'

170. Real-world tobacco cessation practice in China: findings from the prospective, nationwide multicenter China National Tobacco Cessation Cohort Study (CNTCCS)

Author

Liu, Zhao, Qin, Rui, Hu, Xue-Jun, Liu, Li-Jun, Xu, Su-Qin, Shi, Guo-Chao, Zhou, Hong, Bai, Jing, Zhang, Chun-Mei, Qi, Yong, Zhou, Wei, Lan, Shu-Hua, Tong, Jin, Su, Tong-Sheng, Wang, Qiang, Yang, Xin-Yan, Sun, De-Jun, Zhu, Li-Ming, Chen, Xiao-Yang, Chen, Hong, Xie, Yu-Peng, Xiao, Zhi-Hua, Chen, Yan-Bin, Zhao, Bo, Wu, Qiu-Ge, Chen, Wen-Li, Li, Dong-Yan, Liu, Hongbo, Cheng, An-Qi, Cui, Zi-Yang, Zhao, Liang, Li, Jin-Xuan, Wei, Xiao-Wen, Zhou, Xin-Mei, Su, Zheng, Chung, Kian Fan, Chen, Zheng-Ming, Xiao, Dan, and Wang, Chen

Published
2023
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175. A multicentre, prospective, double-blind study comparing the accuracy of autoantibody diagnostic assays in myasthenia gravis: the SCREAM study

Author

Shi, Fu-Dong, Li, Zhiguo, Zhang, Chao, Yang, Chunsheng, Li, Huining, Li, Minshu, Zheng, Pei, Yao, Nan, Wu, Siting, Ding, Xuelu, Chang, Guoqiang, Yang, Li, Fan, Moli, Liu, Xin, Wang, Qiuyu, Chang, Ruan, Zhang, Wang, Tian, Pan, Yang, Gao, Feng, Lv, Jie, Feng, Jinzhou, Liu, Hongbo, Chen, Sheng, Wang, Lihua, Kong, Xiaodan, Wang, Yu, Palace, Jacqueline, Chang, Ting, Zhang, Xinghu, Yang, Huan, and Pan, Yuesong

Published
2023
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186. Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease

Author

Sheng, Xin, Qiu, Chengxiang, Liu, Hongbo, Gluck, Caroline, Hsu, Jesse Y, He, Jiang, Hsu, Chi-yuan, Sha, Daohang, Weir, Matthew R, Isakova, Tamara, Raj, Dominic, Rincon-Choles, Hernan, Feldman, Harold I, Townsend, Raymond, Li, Hongzhe, and Susztak, Katalin

Subjects
Diabetes, Clinical Research, Biotechnology, Kidney Disease, Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Renal and urogenital, Bayes Theorem, Cohort Studies, DNA Methylation, Diabetes Mellitus, Diabetic Nephropathies, Epigenesis, Genetic, Female, Gene Expression, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genomics, Genotype, Humans, Male, Phenotype, Quantitative Trait Loci, methylation quantitative trait loci, epigenetics, multiomics integration analysis, multitrait colocalization analysis, chronic kidney disease
Abstract

Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis.

Published
2020

190. Topology-based multi-jammer localization in wireless networks

Author

Liu Hongbo, Chen Yingying, Xu Wenyuan, Liu Zhenhua, and Su Yuchen

Subjects
jammer localization, wireless networks, topology, Electronic computers. Computer science, QA75.5-76.95
Abstract

Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks. Unlike the traditional approaches focusing on developing jamming defense techniques without considering the location of jammers, we take a different viewpoint that the jammers’ position should be identified and exploited for building a wide range of defense strategies to alleviate jamming. In this paper, we address the problem of localizing multiple jamming attackers coexisting in wireless networks by leveraging the network topology changes caused by jamming. We systematically analyze the jamming effects and develop a framework that can partition network topology into clusters and can successfully estimate the positions of multiple jammers even when their jamming areas are overlapping. Our experiments on a multi-hop network setup using MicaZ sensor nodes validate the feasibility of real-time collection of network topology changes under jamming and our extensive simulation results demonstrate that our approach is highly effective in localizing multiple attackers with or without the prior knowledge of the order that the jammers are turned on.

Published
2024
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200. ACNN: Drug-Drug Interaction Prediction Through CNN and Attention Mechanism

Author

Wang, Weiwei, Liu, Hongbo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, Jing, Junfeng, editor, Premaratne, Prashan, editor, Bevilacqua, Vitoantonio, editor, and Hussain, Abir, editor

Published
2022
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