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Bei Liu
Researcher at Microsoft
Publications - 163
Citations - 7910
Bei Liu is an academic researcher from Microsoft. The author has contributed to research in topics: Endoplasmic reticulum & Photothermal therapy. The author has an hindex of 44, co-authored 148 publications receiving 5877 citations. Previous affiliations of Bei Liu include Ohio State University & Peking University.
Papers
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Journal ArticleDOI
Heat Shock Protein gp96 Is a Master Chaperone for Toll-like Receptors and Is Important in the Innate Function of Macrophages
TL;DR: It is demonstrated that gp96 is the master chaperone for TLRs and that macrophages, but not other myeloid cells, are the dominant source of proinflammatory cytokines during endotoxemia and Listeria infections.
Journal ArticleDOI
Rational design of true monomeric and bright photoactivatable fluorescent proteins
Mingshu Zhang,Hao Chang,Hao Chang,Yongdeng Zhang,Yongdeng Zhang,Junwei Yu,Junwei Yu,Lijie Wu,Wei Ji,Juanjuan Chen,Bei Liu,Bei Liu,Jingze Lu,Yingfang Liu,Jun-Long Zhang,Pingyong Xu,Tao Xu,Tao Xu +17 more
TL;DR: It is shown that mEos2 forms oligomers at high concentrations and forms aggregates when labeling membrane proteins, limiting its application as a fusion partner.
Journal ArticleDOI
Derivation of Pluripotent Stem Cells with In Vivo Embryonic and Extraembryonic Potency
Yang Yang,Bei Liu,Jun Xu,Jinlin Wang,Jun Wu,Cheng Shi,Yaxing Xu,Jiebin Dong,Chengyan Wang,Weifeng Lai,Jialiang Zhu,Liang Xiong,Dicong Zhu,Xiang Li,Weifeng Yang,Takayoshi Yamauchi,Atsushi Sugawara,Zhongwei Li,Fangyuan Sun,Xiangyun Li,Li Chen,Aibin He,Yaqin Du,Ting Wang,Chaoran Zhao,Haibo Li,Xiaochun Chi,Hongquan Zhang,Yifang Liu,Cheng Li,Shuguang Duo,Ming Yin,Huan Shen,Juan Carlos Izpisua Belmonte,Hongkui Deng +34 more
TL;DR: It is shown that a chemical cocktail enables the derivation of stem cells with unique functional and molecular features from mice and humans, designated as extended pluripotent stem (EPS) cells, which are capable of chimerizing both embryonic and extraembryonic tissues.
Posted Content
Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers
TL;DR: The Pixel-BERT which aligns semantic connection in pixel and text level solves the limitation of task-specific visual representation for vision and language tasks and relieves the cost of bounding box annotations and overcomes the unbalance between semantic labels in visual task and language semantic.
Journal ArticleDOI
808‐nm‐Light‐Excited Lanthanide‐Doped Nanoparticles: Rational Design, Luminescence Control and Theranostic Applications
TL;DR: In this review, the progress of 808 nm-excited LnNPs is reported, including their i) luminescence mechanism, ii) Luminescence enhancement, iii) color tuning, iv) diagnostic and v) therapeutic applications.