Institution
Sichuan University
Education•Chengdu, China•
About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.
Topics: Population, Catalysis, Cancer, Adsorption, Randomized controlled trial
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors discuss the current knowledge about the composition, activation, and regulation of the JAK/STAT pathway and highlight the role of the pathway and its inhibitors in various diseases.
Abstract: The Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway was discovered more than a quarter-century ago. As a fulcrum of many vital cellular processes, the JAK/STAT pathway constitutes a rapid membrane-to-nucleus signaling module and induces the expression of various critical mediators of cancer and inflammation. Growing evidence suggests that dysregulation of the JAK/STAT pathway is associated with various cancers and autoimmune diseases. In this review, we discuss the current knowledge about the composition, activation, and regulation of the JAK/STAT pathway. Moreover, we highlight the role of the JAK/STAT pathway and its inhibitors in various diseases.
273 citations
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TL;DR: The general purpose of this review is to give an exhaustive and clear picture in heteroaryl-heteroaryl bond formation as well as its application in the synthesis of natural products, pharmaceuticals, catalyst ligands, and materials.
Abstract: The biheteroaryl structural motif is prevalent in polymers, advanced materials, liquid crystals, ligands, molecules of medicinal interest, and natural products. Many types of synthetic transformations have been known for the construction of heteroaryl–heteroaryl linkages. Coupling reactions provide one of the most efficient ways to achieve these biheterocyclic structures. In this review, four types of coupling reactions are discussed: 1) transition-metal-catalyzed coupling reactions of heteroaryl halides or surrogates with heteroarylmetals; 2) direct inter- and intramolecular heteroarylations of CH bonds of heteroarenes with heteroaryl halides or pseudohalides; 3) oxidative CH/CH homo- and cross-couplings of two unpreactivated heteroarenes; and 4) transition-metal-catalyzed decarboxylative cross-coupling reactions between haloheteroarenes or heteroarenes and heteroarenecarboxylic acids. The general purpose of this review is to give an exhaustive and clear picture in heteroaryl–heteroaryl bond formation as well as its application in the synthesis of natural products, pharmaceuticals, catalyst ligands, and materials.
272 citations
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TL;DR: In this paper, low bandgap small molecules, BDTTNTTR and BDTSTNTTR, with benzo[1,2-b:4,5-b′]dithiophene (BDT) as the central donor unit and naphtho[1.2-c:5,6-c′]bis[ 1,2,5]thiadiazole (NT), which were also π-bridged with terthiophenes on both sides, and end-capped with 3-ethylrhodanine
Abstract: Low bandgap small molecules, BDTTNTTR and BDTSTNTTR, with benzo[1,2-b:4,5-b′]dithiophene (BDT) as the central donor unit and naphtho[1,2-c:5,6-c′]bis[1,2,5]thiadiazole (NT) as the second acceptor block, which were also π-bridged with terthiophenes on both sides, and end-capped with 3-ethylrhodanine electron-accepting groups, have been successfully synthesized for highly efficient small molecule solar cells (SM-OSCs). Based on tactful material design and device engineering, the resulting SM-OSCs processed with a halogen-free solvent of CS2 exhibited a high efficiency of 11.53% with a very small energy loss of 0.57 eV.
272 citations
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Fudan University1, Peking Union Medical College Hospital2, Xinjiang Medical University3, Sichuan University4, Anhui Medical University5, Shanghai Jiao Tong University6, China Medical University (PRC)7, Tianjin Medical University8, Sir Run Run Shaw Hospital9, Inner Mongolia Medical University10, Boston Children's Hospital11, Guangzhou Medical University12, Zhejiang University13, Chongqing Medical University14
TL;DR: The results indicate the importance of bacterial surveillance studies and show a marked decrease of methicillin resistance from 69% in 2005 to 44.6% in 2014 was observed for Staphylococcus aureus.
272 citations
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13 Jan 2020TL;DR: A new sequence-to-sequence pre-training model called ProphetNet is presented, which introduces a novel self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism that predicts the next n tokens simultaneously based on previous context tokens at each time step.
Abstract: This paper presents a new sequence-to-sequence pre-training model called ProphetNet, which introduces a novel self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism. Instead of optimizing one-step-ahead prediction in the traditional sequence-to-sequence model, the ProphetNet is optimized by n-step ahead prediction that predicts the next n tokens simultaneously based on previous context tokens at each time step. The future n-gram prediction explicitly encourages the model to plan for the future tokens and prevent overfitting on strong local correlations. We pre-train ProphetNet using a base scale dataset (16GB) and a large-scale dataset (160GB), respectively. Then we conduct experiments on CNN/DailyMail, Gigaword, and SQuAD 1.1 benchmarks for abstractive summarization and question generation tasks. Experimental results show that ProphetNet achieves new state-of-the-art results on all these datasets compared to the models using the same scale pre-training corpus.
271 citations
Authors
Showing all 108474 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jie Zhang | 178 | 4857 | 221720 |
Robin M. Murray | 171 | 1539 | 116362 |
Xiang Zhang | 154 | 1733 | 117576 |
Rui Zhang | 151 | 2625 | 107917 |
Xiaoyuan Chen | 149 | 994 | 89870 |
Yi Yang | 143 | 2456 | 92268 |
Xinliang Feng | 134 | 721 | 73033 |
Chuan He | 130 | 584 | 66438 |
Lei Zhang | 130 | 2312 | 86950 |
Jian Zhou | 128 | 3007 | 91402 |
Shaobin Wang | 126 | 872 | 52463 |
Yi Xie | 126 | 745 | 62970 |
Pak C. Sham | 124 | 866 | 100601 |
Wei Chen | 122 | 1946 | 89460 |
Bo Wang | 119 | 2905 | 84863 |