L
Lei Wang
Researcher at Changsha University
Publications - 171
Citations - 2224
Lei Wang is an academic researcher from Changsha University. The author has contributed to research in topics: Wireless sensor network & Linear network coding. The author has an hindex of 19, co-authored 158 publications receiving 1466 citations. Previous affiliations of Lei Wang include Beijing Normal University & Lakehead University.
Papers
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Journal ArticleDOI
Graphene Oxide Induces Toll-like Receptor 4 (TLR4)-Dependent Necrosis in Macrophages
Guangbo Qu,Sijin Liu,Shuping Zhang,Lei Wang,Xiaoyan Wang,Bingbing Sun,Nuoya Yin,Xiang Gao,Tian Xia,Jane-Jane Chen,Guibin Jiang +10 more
TL;DR: The combined data reveal that interaction of GO with TLR4 is the predominant molecular mechanism underlying GO-induced macrophagic necrosis; also, cytoskeletal damage and oxidative stress contribute to decreased viability and function of macrophages upon GO treatment.
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Estrogen regulates iron homeostasis through governing hepatic hepcidin expression via an estrogen response element
Yanli Hou,Shuping Zhang,Lei Wang,Junping Li,Guangbo Qu,Jiuyang He,Haiqin Rong,Hong Ji,Sijin Liu +8 more
TL;DR: Estrogen greatly contributes to iron homeostasis by regulating hepatic hepcidin expression directly through a functional ERE in the promoter region of hePCidin gene, which might help build a better understanding towards the etiology of postmenopausal osteoporosis accompanied by excess tissue iron.
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Significant reduction of PM 2.5 in eastern China due to regional-scale emission control: evidence from SORPES in 2011–2018
Aijun Ding,Xin Huang,Wei Nie,Xuguang Chi,Zheng Xu,Longfei Zheng,Zhengning Xu,Yuning Xie,Ximeng Qi,Yicheng Shen,Peng Sun,Jiaping Wang,Lei Wang,Jianning Sun,Xiu-Qun Yang,Wei Qin,Xiangzhi Zhang,Wei Cheng,Weijing Liu,Liangbao Pan,Congbin Fu +20 more
TL;DR: In this article, the authors reported long-term continuous measurements of PM 2.5, chemical components, and their precursors at a regional background station, the Station for Observing Regional Processes of the Earth System (SORPES), in Beijing, eastern China, since 2011.
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A Novel Method for LncRNA-Disease Association Prediction Based on an lncRNA-Disease Association Network
TL;DR: A bipartite network based on known lncRNA-disease associations is constructed and a novel model for inferring potential lncRNAs associations is proposed, which significantly outperformed previous state-of-the-art models.
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A Novel Probability Model for LncRNA–Disease Association Prediction Based on the Naïve Bayesian Classifier
TL;DR: A novel approach was proposed based on the naïve Bayesian classifier to predict potential lncRNA–disease associations (NBCLDA) that can achieve a reliable performance with effective area under ROC curve (AUCs)in leave-one-out cross validation and demonstrated that NBCLDA can be an excellent tool for biomedical research in the future.