Association between airway microbiota and systemic inflammation markers in non-small cell lung cancer patients by DanHui Huang, QianNan Ren, LingYan Xie, YueHua Chen, Cui Li, XiaoFang Su, LiShan Lin, LaiYu Liu, Haijin Zhao, Tingyue Luo, JianHua Wu, Shaoxi Cai, Hangming Dong

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CD133+PD-L1+ cancer cells confer resistance to adoptively transferred engineered macrophage-based therapy in melanoma by Jiaojiao Xu, Zhe Li, Qinli Tong, Sihang Zhang, Jianchen Fang, Aihua Wu, Guoguang Wei, Chen Zhang, Sheng Yu, Binbin Zheng, Hongzheng Lin, Xueling Liao, Zeyu Xiao, Wei Lu

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Novel Nanozyme-Based Multicomponent in situ Hydrogels with Antibacterial, Hypoxia-Relieving and Proliferative Properties for Promoting Gastrostomy Tube Tract Maturation by Xiao F, Yan B, Yuan T, He Y, Zhang X, He X, Peng W, Xu Y, Cao J

“…Feng Xiao,1,* Bisong Yan,2,* Tianwen Yuan,2 Yang He,2 Xiaojun Zhang,3 Xiaoyun He,1 Wei Peng,1 Ying Xu,3 Jun Cao1,4 1Shanghai Eighth People’s Hospital, Xuhui District, Shanghai, 200030, People’s Republic of China; 2Department of Interventional Oncology, Dahua Hospital, Xuhui District, Shanghai, 200237, People’s Republic of China; 3College of Pharmacy, Jiangsu University, Zhenjiang, 212013, People’s Republic of China; 4Shanghai University of Medicine and Health Science, Pudong New Area, Shanghai, 201318, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jun Cao, Shanghai Eighth People’s Hospital, Xuhui District, Shanghai, 200030, People’s Republic of China, Email juncao11@sina.com Ying Xu, College of Pharmacy, Jiangsu University, Zhenjiang, 212013, People’s Republic of China, Email ingyx@sina.com.cnPurpose: Gastrostomy is the commonly used enteral feeding technology. …”
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Efficacy and safety of SHR8554 on postoperative pain in subjects with moderate to severe acute pain following orthopedic surgery: A multicenter, randomized, double-blind, dose-expl... by Yanhua Zhao, Zhisheng Lu, Xuesong Song, Haihui Xie, Xungang Xiao, Guonian Wang, Qi Zhou, Qingmei Zhang, Liang Liu, Zhijian Lan, Ning Bai, Haiyan Wang, Zhihao Pan, Liang Dong, Xianzhong Lin, Gang Chen, Qinghui Wang, Jiangtao Dong, Jia Deng, Yongshan Nan, Jiaqiang Zhang, Xiaohua Zhou, Yanjuan Huang, Yongquan Chen, Huanzhong He, Ye Yang, Dengpan Yao, Jintai Jia, Shuan Jin, Yafeng Zhang, Zhonghui Luo, Jiangang Li, Linzhong Zhang, Fang Wang, Juehua Jing, Jiang Zhu, Lin Li, Guangda Wang, Huajing Guo, Qiang Wang, Diansan Su, Weifeng Yu, Xiyao Gu

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Investigating the Use of Generative Adversarial Networks-Based Deep Learning for Reducing Motion Artifacts in Cardiac Magnetic Resonance by Ma ZP, Zhu YM, Zhang XD, Zhao YX, Zheng W, Yuan SR, Li GY, Zhang TL

“…Ze-Peng Ma,1,2,* Yue-Ming Zhu,3,* Xiao-Dan Zhang,4 Yong-Xia Zhao,1 Wei Zheng,3 Shuang-Rui Yuan,1 Gao-Yang Li,1 Tian-Le Zhang1 1Department of Radiology, Affiliated Hospital of Hebei University/ Clinical Medical College, Hebei University, Baoding, 071000, People’s Republic of China; 2Hebei Key Laboratory of Precise Imaging of inflammation Tumors, Baoding, Hebei Province, 071000, People’s Republic of China; 3College of Electronic and Information Engineering, Hebei University, Baoding, Hebei Province, 071002, People’s Republic of China; 4Department of Ultrasound, Affiliated Hospital of Hebei University, Baoding, Hebei Province, 071000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiao-Dan Zhang, Department of Ultrasound, Affiliated Hospital of Hebei University, No. 212 of Yuhua East Road, Lianchi District, Baoding, 071000, People’s Republic of China, Tel +86 17325535302, Email xiaodanzhangzxd@126.comObjective: To evaluate the effectiveness of deep learning technology based on generative adversarial networks (GANs) in reducing motion artifacts in cardiac magnetic resonance (CMR) cine sequences.Methods: The training and testing datasets consisted of 2000 and 200 pairs of clear and blurry images, respectively, acquired through simulated motion artifacts in CMR cine sequences. …”
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