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3. Lowering systolic blood pressure to less than 120 mm Hg versus less than 140 mm Hg in patients with high cardiovascular risk with and without diabetes or previous stroke: an open-label, blinded-outcome, randomised trial

Author

Ai, Xinyue, An, Chun, An, Yuhong, Bai, Shiru, Bai, Xueke, Bi, Jingao, Bin, Xiaoling, Bu, Miaomiao, Bu, Peili, Bu, Wei, Cai, Lvping, Cai, Nana, Cai, Shuhui, Cai, Ting, Cai, Wenjing, Cao, Bin, Cao, Bingbing, Cao, Huaping, Cao, Libo, Cao, Xiancun, Chai, Hui, Chai, Yonggui, Chai, Zhiyong, Chang, Chunduo, Chang, Jianbao, Chang, Shuyue, Chang, Yunling, Chao, Huanhuan, Che, Hang, Che, Qianqiu, Chen, Danlin, Chen, Dongsheng, Chen, Faxiu, Chen, Guang, Chen, Hairong, Chen, Hao, Chen, Huahua, Chen, Huijun, Chen, Jiafu, Chen, Jian, Chen, Jiasen, Chen, Jing, Chen, Jinzi, Chen, Junrong, Chen, lichun, Chen, Lijuan, Chen, Liyuan, Chen, Qun, Chen, Run, Chen, Shaoxing, Chen, Song, Chen, Tieshuang, Chen, Xianghong, Chen, Xiaowu, Chen, Xudong, Chen, Xue, Chen, Xunchun, Chen, Yao, Chen, Yongli, Chen, Yuanyue, Chen, Yuhong, Chen, Yuyi, Chen, Zhangying, Chen, Zhidong, Chen, Zuyi, Cheng, Caiming, Cheng, Jianbin, Cheng, Xiaoxia, Chu, Junjie, Cui, Ruifeng, Cui, Xiaolin, Cui, Xuechen, Cui, Yang, Cui, Zhonghua, Dai, Wanhong, Dai, Xing, Ding, Chunxia, Ding, Huihong, Ding, Qiuhong, Ding, Yaozong, Ding, Yingjie, Dong, Jiajia, Dong, Lei, Dong, Qi, Dong, Yumei, Du, Bing, Du, Hong, Du, Jie, Du, Laijing, Du, Meiling, Du, Qiong, Du, Tianmin, Du, Xue, Duan, Ru, Duan, Xiaojing, Duan, Xiaoting, Fan, Dandan, Fan, Xiaohong, Fan, Xin, Fang, Fang, Fang, Jing, Fang, Xibo, Fang, Yang, Feng, Erke, Feng, Hejin, Feng, Ling, Feng, Rui, Feng, Zhaohui, Fu, Hongmei, Fu, Qiuai, Gao, Haofei, Gao, Li, Gao, Lina, Gao, Liwei, Gao, Lu, Gao, Min, Gao, Qian, Gao, Yan, Gao, Yuan, Ge, Jinzhuo, Geng, Hongxu, Geng, Hui, Geng, Leijun, Geng, Lianqing, Gou, Hongyan, Gu, Qin, Guan, Lili, Guan, Shuo, Guan, Wenchi, Guan, Zheng, Guang, Bin, Guo, Anran, Guo, Changhong, Guo, Gaofeng, Guo, Lizhi, Guo, Qing, Guo, Qiue, Guo, Ying, Guo, Zhihua, Han, Aihong, Han, Meihong, Han, Suhui, Han, Xinru, Han, Yajun, Hao, Feng, Hao, Jingmin, Hao, Shiguo, He, Chuanhui, He, Dejian, He, Mengyuan, He, Miaomiao, He, Shaojuan, He, Wenkai, He, Xiaoyu, He, Yuxiang, Hong, Jige, Hou, Chuanxing, Hou, Jing, Hu, Danli, Hu, Jian, Hu, Jun, Hu, Lingai, Hu, Mengying, Hu, Zhiyuan, Huang, Anhui, Huang, Chunxia, Huang, Haolin, Huang, Jianlan, Huang, Sha, Huang, Siqi, Huang, Weijun, Huang, Wenxiu, Huang, Xinghe, Huang, Xinsheng, Huang, Xinxin, Hui, Jiliang, Hui, Lijun, Hui, Zhongsheng, Huo, Fangjie, Ji, Runqing, Jia, Guojiong, Jia, Hao, Jia, Jingjing, Jia, Jingmei, Jia, Xiaoling, Jiang, Hua, Jiang, Jingcheng, Jiang, Qian, Jiang, Xianyan, Jiang, Xiaoyuan, Jiang, Yanxiang, Jiao, Yunhong, Jie, Liying, Jin, Binbin, Jin, Lingjiao, Jin, Renshu, Jin, Rong, Jin, Xiang, Jin, Xianping, Jin, Yongfan, Jin, Zepu, Jin, Zhenan, Jing, Chengrong, Jing, Jiajie, Jing, Ruiling, Kang, Liping, Kang, Yu, Kong, Jianqiong, Kou, Shijie, Kou, Xianli, Kulaxihan, Lai, Jijia, Lei, Lubi, Li, Baoxiang, Li, Bin, Li, Bing, Li, Chaohui, Li, Cheng, Li, Chunmei, Li, Chunyan, Li, Daqing, Li, Deen, Li, Di, Li, Feng, Li, Guanyi, Li, Haiyang, Li, Hongwei, Li, Jia, Li, Jialin, Li, Jianan, Li, Jianguang, Li, Jiaying, Li, Jing, Li, Jinmei, Li, Lala, Li, Li, Li, Lijun, Li, Liping, Li, Lize, Li, Mingju, Li, Minglan, Li, Mingyan, Li, Na, Li, Nan, Li, Nana, Li, Qiang, Li, Qianru, Li, Rui, Li, Ruihong, Li, Shanshan, Li, Shilin, Li, Si, Li, Suwen, Li, Tongshe, Li, Tongying, Li, Wanke, Li, Wei, Li, Wenbo, Li, Wenjuan, Li, Xi, Li, Xiangxia, Li, Xiao, Li, Xiaohui, Li, Xingyan, Li, Xiujuan, Li, Yan, Li, Yanfang, Li, Yang, Li, Yanxia, Li, Yaona, Li, Yichong, Li, Ying, Li, Yuqing, Li, Zheng, Li, Zhengye, Liang, Chuanliang, Liang, Jihua, Liang, Jin, Liang, Ke, Liang, Linju, Liang, Tingchen, Liang, Xia, Liang, Xianfeng, Liang, Yanli, Liang, Zhenye, Lie, Zhenbang, Lin, Qingfei, Lin, Ruifang, Lin, Xiao, Lin, Zhiqiang, Liu, Aijun, Liu, Chao, Liu, Chunxia, Liu, Cong, Liu, Fang, Liu, Guaiyan, Liu, Hongjun, Liu, Jiamin, Liu, Jiangling, Liu, Jianqi, Liu, Jieyun, Liu, Jihong, Liu, Jing, Liu, Jinsha, Liu, Juan, Liu, Junfang, Liu, Liming, Liu, Lin, Liu, Ling, Liu, Lu, Liu, Qiang, Liu, Qiaoling, Liu, Qiaoxia, Liu, Qiuxia, Liu, Shaobo, Liu, Xiaobao, Liu, Xiaocheng, Liu, Xiaoyuan, Liu, Xinbo, Liu, Xu, Liu, Yang, Liu, Yanhu, Liu, Yanming, Liu, Yaqin, Liu, Yong, Liu, Zhihong, Long, Jing, Lu, Futang, Lu, Huamei, Lu, Jiapeng, Lu, Junhong, Lu, Weibin, Lu, Yanrong, Lu, Yuchun, Luan, Tianwei, Luo, Qingwei, Luo, Qun, Luo, Tian, Luo, Xia, Luo, Yongmei, Lv, Jing, Lv, Jinhai, Lv, Lei, Lv, Lili, Lv, Meng, Ma, Aiqing, Ma, Huaimin, Ma, Huihuang, Ma, Jie, Ma, Jinbao, Ma, Li, Ma, Lingzhen, Ma, Nan, Ma, Qiaojuan, Ma, Shumei, Ma, Tengfei, Ma, Xiange, Ma, Xiaowen, Ma, Yuehua, Mai, Lanxian, Mei, Xiao, Meng, Gen, Miao, Ruichao, Miao, Xue, Miao, Xuyan, Min, Tingting, Mo, Shubing, Morigentu, Nan, Tingyan, Ni, Jinyang, Ni, Shuguo, Nie, Yu, Ning, Benxing, Ning, Xiaowei, Niu, Manman, Niu, Qingying, Niu, Wentang, Niu, Xiaoxia, Ou, Fang, Pan, Biyun, Pan, Chengjie, Pan, Congming, Pan, Jieli, Pan, Xiaowen, Pan, Ziying, Pei, Guangzhong, Pei, Lingyu, Pei, Min, Pei, Yanzhen, Peng, Yinyu, Peng, Yuming, Pu, Zhaokun, Qi, Fengjun, Qi, Liwei, Qi, Meiqiong, Qi, Yan, Qian, Jun, Qin, Lei, Qin, Zhonghua, Qing, Lan, Qiu, Lixia, Qiu, Weiyu, Qiu, Xiaoling, Qu, Yueli, Quan, Minghua, Ren, Dingping, Ren, Hong, Ren, Lingzhi, Ren, Tingting, Ren, Wei, Ren, Yihui, Rong, Yufang, Ruan, Jiahui, Shang, Peiqin, Shao, Minyan, Shao, Xuefeng, Shao, Yuling, Shen, Junrong, Shen, Rui, Sheng, Lin, Shi, Jiangjie, Shi, Xun, Shi, Yanhong, Shi, Yeju, Shi, Yujiao, Shu, Bo, Song, Bingchun, Song, Dan, Song, Jinhui, Song, Jinwang, Song, Jinxian, Song, Wei, Song, Xiaoping, Song, Yawen, Su, He, Su, Qinfeng, Su, Shuhong, Su, Xiaozhou, Sun, Chengxiang, Sun, Fangfang, Sun, Gongping, Sun, Jiangnan, Sun, Mengmeng, Sun, Rongrong, Sun, Shuting, Sun, Songtao, Sun, Ying, Sun, Yongmiao, Sun, Yunhong, Sun, Zhiqiang, Suo, Mengying, Tan, Binghu, Tang, Chunyan, Tang, Zhongli, Tao, Yu, Tian, Changming, Tian, Hongmei, Tian, Jian, Tian, Xiaomin, Wan, Huaibin, Wan, Qin, Wan, Rongjun, Wang, Bobin, Wang, Chao, Wang, Chaoqun, Wang, Chengliang, Wang, Di, Wang, Enfang, Wang, Feng, Wang, Gang, Wang, Guangqiang, Wang, Guixiang, Wang, Haifeng, Wang, Haijun, Wang, Haiyang, Wang, Jianfang, Wang, Jianfeng, Wang, Jing, Wang, Junping, Wang, Junying, Wang, Kang, Wang, Lei, Wang, Lin, Wang, Lize, Wang, Meng, Wang, Pan, Wang, Qi, Wang, Qiong, Wang, Qiuli, Wang, Qiuxue, Wang, Ran, Wang, Shaojin, Wang, Shuai, Wang, Tao, Wang, Tiantian, Wang, Tinghui, Wang, Tongyan, Wang, Wanhong, Wang, Wenjuan, Wang, Wenyan, Wang, Wenying, Wang, Wenzhuan, Wang, Xiaofei, Wang, Xiaoyan, Wang, Xitong, Wang, Xu, Wang, Yan, Wang, Yanfang, Wang, Yang, Wang, Yanping, Wang, Yanying, Wang, Yaoxin, Wang, Yingli, Wang, Yiting, Wang, Yue, Wang, Yumei, Wang, Yuzhuo, Wang, Zhenhua, Wang, Zhifang, Wang, Zhimin, Wei, Chunli, Wei, Lixia, Wei, Pei, Wei, Shuying, Wei, Xiqing, Wen, Hong, Wen, Yun, Wu, Chaoqun, Wu, Hairong, Wu, Lihua, Wu, Lingxiang, Wu, Qi, Wu, Shaorong, Wu, Wenting, Wu, Xueyi, Wu, Yongshuan, Wu, Zhihao, Wu, Zhuying, Wu, Zongyin, Wuhanbilige, Xia, Jun, Xia, Yang, Xiang, Jing, Xiao, Heliu, Xiao, Yaying, Xie, Meiling, Xie, Yinyan, Xin, Huiling, Xing, Jing, Xiu, Guoquan, Xu, Baohua, Xu, Chuangze, Xu, En, Xu, Jian, Xu, Shuli, Xu, Wei, Xu, Wen, Xue, Na, Xue, Tingting, Xue, Wei, Yan, Haiyan, Yan, Xiaofang, Yan, Yanqing, Yang, Bo, Yang, Hui, Yang, Huiyu, Yang, Jinhua, Yang, Kun, Yang, Man, Yang, Mengya, Yang, Ning, Yang, Ping, Yang, Xiajiao, Yang, Xiaomo, Yang, Xin, Yang, Xiujuan, Yang, Xuemei, Yang, Xuming, Yang, Yan, Yang, Yanhua, Yang, Yi, Yang, Yuanyuan, Yang, Zhimei, Yang, Zhiming, Yao, Hui, Yao, Lu, Ye, Jinling, Ye, Wenhua, Yi, Mingjiao, Yi, Shaowei, Yi, Wenyi, Yi, Zhimin, Yin, Guangxia, Yin, Guoyuan, Yu, Guibin, Yu, Hairong, Yu, Huaitao, Yu, Lijie, Yu, Lijun, Yu, Nana, Yu, Qin, Yu, Xinli, Yu, Yi, Yuan, Biao, Zeng, Chunmei, Zhai, Na, Zhai, Xiaojuan, Zhan, Hongju, Zhang, Aizhen, Zhang, Baohua, Zhang, Bin, Zhang, Caizhu, Zhang, Chaoying, Zhang, Chengbo, Zhang, Chunlai, Zhang, Churuo, Zhang, Fan, Zhang, Feiqin, Zhang, Ge, Zhang, Haibo, Zhang, Hailin, Zhang, Hanxue, Zhang, Huaixing, Zhang, Hui, Zhang, Huijuan, Zhang, Jinguo, Zhang, Jingyu, Zhang, Jinyun, Zhang, Jisheng, Zhang, Jun, Zhang, Lei, Zhang, Li, Zhang, Liang, Zhang, Lifeng, Zhang, Lina, Zhang, Liping, Zhang, Min, Zhang, Ping, Zhang, Qiang, Zhang, Rufang, Zhang, Ruifen, Zhang, Shengde, Zhang, Siqi, Zhang, Sufang, Zhang, Tingting, Zhang, Wanyue, Zhang, Weiliang, Zhang, Xiaohan, Zhang, Xiaohong, Zhang, Xiaojuan, Zhang, Xin, Zhang, Xue, Zhang, Xuewei, Zhang, Yachen, Zhang, Yang, Zhang, Yanyan, Zhang, Yaojie, Zhang, Yingyu, Zhang, Yuan, Zhang, Yun, Zhang, Yunfeng, Zhang, Zaozhang, Zhang, Zhichao, Zhao, Baihui, Zhao, Dan, Zhao, Fuxian, Zhao, Guizeng, Zhao, Haijie, Zhao, Honglei, Zhao, Huizhen, Zhao, Jindong, Zhao, Juan, Zhao, Liming, Zhao, Ling, Zhao, Lingshan, Zhao, Qingxia, Zhao, Qiuping, Zhao, Wanchen, Zhao, Wangxiu, Zhao, Weiyi, Zhao, Xiaodi, Zhao, Xiaojing, Zhao, Xiaoli, Zhao, Xiaoyan, Zhao, Xiling, Zhao, Yannan, Zhao, Yiyuan, Zheng, Shuzhen, Zheng, Xin, Zhi, Lixia, Zhong, Hui, Zhong, Qing, Zhong, Xin, Zhong, Yunzhi, Zhou, Jianfeng, Zhou, Jihu, Zhou, Ke, Zhou, Liangliang, Zhou, Ling, Zhou, Na, Zhou, Shengcheng, Zhou, Suyun, Zhou, Tao, Zhou, Wanren, Zhou, Weifeng, Zhou, Weijuan, Zhou, Xiaohong, Zhou, Yunke, Zhou, Yuquan, Zhou, Zhaohai, Zhou, Zhiming, Zhu, Bingpo, Zhu, Jifa, Zhu, Jing, Zhu, Mengnan, Zhu, Youcun, Zong, Dafei, Zuo, Hongbo, and Zuo, Zhaokai

Published
2024
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7. Development and validation of a new risk assessment model for immunomodulatory drug-associated venous thrombosis among Chinese patients with multiple myeloma

Author

Li, Xiaozhe, Sun, Xiuli, Fang, Baijun, Leng, Yun, Sun, Fangfang, Wang, Yaomei, Wang, Qing, Jin, Jie, Yang, Min, Xu, Bing, Fang, Zhihong, Chen, Lijuan, Chen, Zhi, Yang, Qimei, Zhang, Kejie, Ye, Yinhai, Geng, Hui, Sun, Zhiqiang, Hao, Dan, Huang, Hongming, Wang, Xiaotao, Jing, Hongmei, Ma, Lan, Pan, Xueyi, Chen, Wenming, and Li, Juan

Published
2023
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10. Riok3 inhibits the antiviral immune response by facilitating TRIM40-mediated RIG-I and MDA5 degradation

Author

Shen, Yong, Tang, Kejun, Chen, Dongdong, Hong, Mengying, Sun, Fangfang, Wang, SaiSai, Ke, Yuehai, Wu, Tingting, Sun, Ren, Qian, Jing, and Du, Yushen

Subjects
Prevention, Biodefense, Infectious Diseases, Genetics, Vaccine Related, Emerging Infectious Diseases, Aetiology, 2.1 Biological and endogenous factors, Infection, Inflammatory and immune system, Animals, Female, Male, Antiviral Agents, Cells, Cultured, Cytokines, DEAD Box Protein 58, Fibroblasts, Immunity, Interferon-Induced Helicase, IFIH1, Macrophages, Peritoneal, Mice, Inbred C57BL, Protein Binding, Protein Serine-Threonine Kinases, Proteolysis, RNA Viruses, Ubiquitin-Protein Ligases, Ubiquitination, Up-Regulation, Virus Replication, Biochemistry and Cell Biology, Medical Physiology
Abstract

The type I interferon (IFN) pathway is a key component of innate immune response upon invasion of foreign pathogens. It is also under precise control to prevent excessive upregulation and undesired inflammation cascade. In the present study, we report that Riok3, an atypical kinase, negatively regulates retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) sensing-induced type I IFN signaling. Riok3 deficiency selectively inhibits RNA viral replication in vitro, resulting from an upregulated type I IFN pathway. Mice with myeloid-specific Riok3 knockout also show a more robust induction of type I IFN upon RNA virus infection and are more resistant to RNA virus-induced pathogenesis. Mechanistically, Riok3 recruits and interacts with the E3 ubiquitin ligase TRIM40, leading to the degradation of RIG-I and melanoma differentiation-associated gene-5 (MDA5) via K48- and K27-linked ubiquitination. Collectively, our data reveal the mechanism that Riok3 employs to be a negative regulator of antiviral innate immunity.

Published
2021

17. Rectifying METTL4-Mediated N 6 -Methyladenine Excess in Mitochondrial DNA Alleviates Heart Failure

Author

Zhang, Fuyang, primary, Zhang, Ling, additional, Hu, Guangyu, additional, Chen, Xiyao, additional, Liu, Hui, additional, Li, Congye, additional, Guo, Xiong, additional, Huang, Chong, additional, Sun, Fangfang, additional, Li, Tongzheng, additional, Cui, Zhe, additional, Guo, Yongzhen, additional, Yan, Wenjun, additional, Xia, Yunlong, additional, Liu, Zhiyuan, additional, Lin, Zhen, additional, Duan, Weixun, additional, Lu, Linhe, additional, Wang, Xinyi, additional, Wang, Zhengyang, additional, Wang, Shan, additional, and Tao, Ling, additional

Published
2024
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29. Predicting the Risk of Fundus Lesions in Systemic Lupus Erythematosus: A Nomogram Model.

Author

Xie, Huan, Sun, Fangfang, Yang, Huimin, Li, Jin, and Raza, Faisal

Abstract

Objectives. This study aimed to use laboratory and clinical data of systemic lupus erythematosus (SLE) patients to construct prediction models for fundus complications in SLE. Methods. Routine blood test data and clinical information of 277 SLE patients were collected retrospectively. Based on their fundus examination, they were divided into two groups, with or without fundus lesions, defined as retinopathy and choroidopathy in this study. The data of the two groups were compared, and the prediction model was established using binary logistic regression analysis. Results. There were 85 patients in the fundus lesions' group and 192 patients in the control group. Between the two groups, age, SLEDAI, serositis, hypertension, diabetes, anticardiolipin antibody (ACA), anti‐Sm antibody, C‐reactive protein (CRP), hemoglobin (Hb), platelet count (PLT), albumin (Alb), serum creatinine(Scr), urea, uric acid(UA), and immunoglobulin G(IgG) were significantly different (p < 0.05). Besides, age, SLEDAI, serositis, hypertension, diabetes, anti‐SSB, CRP, Hb, PLT, FIB, Alb, Scr, urea, UA, GLU, and IgG were significantly correlated with SLE‐related fundus lesions. PLT, fibrinogen (FIB), IgG, and urea were independent risk factors of SLE‐related fundus lesions. The area under the curve (AUC) was 0.830 (p < 0.001; 95% CI = 0.762–0.898), and the nomogram was established with great evaluation efficiency demonstrated by the calibration curve and the Hosmer–Lemeshow test. The result of k‐fold cross‐validation also showed high prediction accuracy. Conclusions. We have found the independent risk factors of SLE‐related fundus lesions and developed a model to improve the prediction of fundus lesions in SLE. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Optimal development of apoptotic cells-mimicking liposomes targeting macrophages.

Author

Zhang, Li, Li, Yujiao, Liu, Xing, He, Xiaolu, Zhang, Jieyu, Zhou, Jun, Qiao, Youbei, Wu, Hong, Sun, Fangfang, and Zhou, Qing

Subjects
RENAL circulation, DRUG utilization, LIPOSOMES, DRUG carriers, PHOSPHATIDYLSERINES, PATTERN perception receptors
Abstract

Macrophages are multifunctional innate immune cells that play indispensable roles in homeostasis, tissue repair, and immune regulation. However, dysregulated activation of macrophages is implicated in the pathogenesis of various human disorders, making them a potential target for treatment. Through the expression of pattern recognition and scavenger receptors, macrophages exhibit selective uptake of pathogens and apoptotic cells. Consequently, the utilization of drug carriers that mimic pathogenic or apoptotic signals shows potential for targeted delivery to macrophages. In this study, a series of mannosylated or/and phosphatidylserine (PS) -presenting liposomes were developed to target macrophages via the design of experiment (DoE) strategy and the trial-and-error (TaE) approach. The optimal molar ratio for the liposome formulation was DOPC: DSPS: Chol: PEG-PE = 20:60:20:2 based on the results of cellular uptake and cytotoxicity evaluation on RAW 264.7 and THP-1 in vitro. Results from in vivo distribution showed that, in the DSS-induced colitis model and collagen II-induced rheumatoid arthritis model, PS-presenting liposomes (PS-Lipo) showed the highest accumulation in intestine and paws respectively, which holds promising potential for macrophage target therapy since macrophages are abundant at inflammatory sites and contribute to the progression of corresponding diseases. Organs such as the heart, liver, spleen, lung, and kidney did not exhibit histological alterations such as inflammation or necrosis when exposed to PC-presenting liposomes (PC-Lipo) or PS-Lipo. In addition, liposomes demonstrated hemobiocompatibility and no toxicity to liver or kidney for circulation and did not induce metabolic injury in the animals. Thus, the well-designed PS-Lipo demonstrated the most potential for macrophage target therapy. [ABSTRACT FROM AUTHOR]

Published
2024
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31. General method to digitalize multi-layer woven structure.

Author

Sun, Fangfang, Zhou, Haili, Gu, Lijun, Han, Chenchen, Huang, Jian, Li, Chao, Zhang, Liquan, and Zhao, Qian

Abstract

As an advanced composite reinforcement, multi-layer woven fabrics are widely used in industries. However, for most nonprofessional engineers and researchers, the complexity of the spatial architecture of multi-layer woven structure (MLWS) makes it difficult to understand and apply. In order to fully utilize the advantage of the designability of MLWS, a digitalization expression is used to define the design variable of MLWS by 8 parameters. This expression has wide universality and practicability, which can parametrize all kinds of MLWSs, and characterize full-scale complex preforms. Based on this expression, a general method and process for constructing novel and complex MLWS architectures are also proposed and developed. Furthermore, a method to generate the preform jacquard pattern for the electronic jacquard system is also developed to demonstrate the application in manufacturing. This digitalization expression can be considered as the key point to connect the material design and automatic manufacturing, which can improve the design technology of multi-layer woven composite material. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Spatiotemporal Controllable Sono‐Nanovaccines Driven by Free‐Field Based Whole‐Body Ultrasound for Personalized Cancer Therapy

Author

Wang, Yang, primary, Li, Guangzhe, additional, Su, Jianlong, additional, Liu, Yiming, additional, Zhang, Xiaomai, additional, Zhang, Guanyi, additional, Wu, Zhihao, additional, Li, Jinrong, additional, Zhang, Yuxuan, additional, Wang, Xu, additional, Yang, Zejia, additional, Wang, Ruimin, additional, Wang, Chengdong, additional, Wang, Liu, additional, Sun, Fangfang, additional, Zhao, Weijie, additional, Wang, Xuejian, additional, Peng, Xiaojun, additional, and Shao, Kun, additional

Published
2024
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41. Disparate Antibiotic Resistance Gene Quantities Revealed across 4 Major Cities in California: A Survey in Drinking Water, Air, and Soil at 24 Public Parks

Author

Echeverria-Palencia, Cristina M, Thulsiraj, Vanessa, Tran, Nghi, Ericksen, Cody A, Melendez, Isabel, Sanchez, Michael G, Walpert, Devin, Yuan, Tony, Ficara, Elizabeth, Senthilkumar, Niru, Sun, Fangfang, Li, Renjie, Hernandez-Cira, Marisol, Gamboa, Demi, Haro, Heather, Paulson, Suzanne E, Zhu, Yifang, and Jay, Jennifer A

Subjects
Antimicrobial Resistance, Genetics, Chemical Engineering, Materials Engineering
Abstract

Widespread prevalence of multidrug and pandrug-resistant bacteria has prompted substantial concern over the global dissemination of antibiotic resistance genes (ARGs). Environmental compartments can behave as genetic reservoirs and hotspots, wherein resistance genes can accumulate and be laterally transferred to clinically relevant pathogens. In this work, we explore the ARG copy quantities in three environmental media distributed across four cities in California and demonstrate that there exist city-to-city disparities in soil and drinking water ARGs. Statistically significant differences in ARGs were identified in soil, where differences in blaSHV gene copies were the most striking; the highest copy numbers were observed in Bakersfield (6.0 × 10-2 copies/16S-rRNA gene copies and 2.6 × 106 copies/g of soil), followed by San Diego (1.8 × 10-3 copies/16S-rRNA gene copies and 3.0 × 104 copies/g of soil), Fresno (1.8 × 10-5 copies/16S-rRNA gene copies and 8.5 × 102 copies/g of soil), and Los Angeles (5.8 × 10-6 copies/16S-rRNA gene copies and 5.6 × 102 copies/g of soil). In addition, ARG copy numbers in the air, water, and soil of each city are contextualized in relation to globally reported quantities and illustrate that individual genes are not necessarily predictors for the environmental resistome as a whole.

Published
2017

42. Lowering systolic blood pressure to less than 120 mm Hg versus less than 140 mm Hg in patients with high cardiovascular risk with and without diabetes or previous stroke: an open-label, blinded-outcome, randomised trial

Author

Liu, Jiamin, Li, Yan, Ge, Jinzhuo, Yan, Xiaofang, Zhang, Haibo, Zheng, Xin, Lu, Jiapeng, Li, Xi, Gao, Yan, Lei, Lubi, Liu, Jing, Li, Jing, Ai, Xinyue, An, Chun, An, Yuhong, Bai, Shiru, Bai, Xueke, Bi, Jingao, Bin, Xiaoling, Bu, Miaomiao, Bu, Peili, Bu, Wei, Cai, Lvping, Cai, Nana, Cai, Shuhui, Cai, Ting, Cai, Wenjing, Cao, Bin, Cao, Bingbing, Cao, Huaping, Cao, Libo, Cao, Xiancun, Chai, Hui, Chai, Yonggui, Chai, Zhiyong, Chang, Chunduo, Chang, Jianbao, Chang, Shuyue, Chang, Yunling, Chao, Huanhuan, Che, Hang, Che, Qianqiu, Chen, Danlin, Chen, Dongsheng, Chen, Faxiu, Chen, Guang, Chen, Hairong, Chen, Hao, Chen, Huahua, Chen, Huijun, Chen, Jiafu, Chen, Jian, Chen, Jian, Chen, Jiasen, Chen, Jing, Chen, Jinzi, Chen, Junrong, Chen, lichun, Chen, Lijuan, Chen, Liyuan, Chen, Qun, Chen, Run, Chen, Shaoxing, Chen, Song, Chen, Tieshuang, Chen, Xianghong, Chen, Xiaowu, Chen, Xudong, Chen, Xue, Chen, Xunchun, Chen, Yao, Chen, Yongli, Chen, Yuanyue, Chen, Yuhong, Chen, Yuyi, Chen, Zhangying, Chen, Zhidong, Chen, Zuyi, Cheng, Caiming, Cheng, Jianbin, Cheng, Xiaoxia, Chu, Junjie, Cui, Ruifeng, Cui, Xiaolin, Cui, Xuechen, Cui, Yang, Cui, Zhonghua, Dai, Wanhong, Dai, Xing, Ding, Chunxia, Ding, Huihong, Ding, Qiuhong, Ding, Yaozong, Ding, Yingjie, Dong, Jiajia, Dong, Lei, Dong, Qi, Dong, Yumei, Du, Bing, Du, Hong, Du, Jie, Du, Laijing, Du, Meiling, Du, Qiong, Du, Tianmin, Du, Xue, Duan, Ru, Duan, Xiaojing, Duan, Xiaoting, Fan, Dandan, Fan, Xiaohong, Fan, Xin, Fang, Fang, Fang, Jing, Fang, Xibo, Fang, Yang, Feng, Erke, Feng, Hejin, Feng, Ling, Feng, Rui, Feng, Zhaohui, Fu, Hongmei, Fu, Qiuai, Gao, Haofei, Gao, Li, Gao, Lina, Gao, Liwei, Gao, Lu, Gao, Min, Gao, Min, Gao, Qian, Gao, Yan, Gao, Yuan, Ge, Jinzhuo, Geng, Hongxu, Geng, Hui, Geng, Leijun, Geng, Lianqing, Gou, Hongyan, Gu, Qin, Guan, Lili, Guan, Shuo, Guan, Wenchi, Guan, Zheng, Guang, Bin, Guo, Anran, Guo, Changhong, Guo, Gaofeng, Guo, Lizhi, Guo, Qing, Guo, Qiue, Guo, Ying, Guo, Zhihua, Han, Aihong, Han, Meihong, Han, Suhui, 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Li, Bing, Li, Chaohui, Li, Cheng, Li, Chunmei, Li, Chunyan, Li, Daqing, Li, Deen, Li, Di, Li, Feng, Li, Guanyi, Li, Haiyang, Li, Hongwei, Li, Jia, Li, Jialin, Li, Jianan, Li, Jianguang, Li, Jiaying, Li, Jing, Li, Jing, Li, Jinmei, Li, Lala, Li, Li, Li, Lijun, Li, Liping, Li, Lize, Li, Mingju, Li, Minglan, Li, Mingyan, Li, Na, Li, Na, Li, Nan, Li, Nana, Li, Qiang, Li, Qianru, Li, Rui, Li, Ruihong, Li, Shanshan, Li, Shilin, Li, Si, Li, Suwen, Li, Tongshe, Li, Tongying, Li, Wanke, Li, Wei, Li, Wenbo, Li, Wenjuan, Li, Xi, Li, Xiangxia, Li, Xiao, Li, Xiaohui, Li, Xingyan, Li, Xiujuan, Li, Yan, Li, Yanfang, Li, Yang, Li, Yanxia, Li, Yaona, Li, Yichong, Li, Ying, Li, Yuqing, Li, Zheng, Li, Zhengye, Liang, Chuanliang, Liang, Jihua, Liang, Jin, Liang, Ke, Liang, Linju, Liang, Tingchen, Liang, Xia, Liang, Xianfeng, Liang, Yanli, Liang, Zhenye, Lie, Zhenbang, Lin, Qingfei, Lin, Ruifang, Lin, Xiao, Lin, Zhiqiang, Liu, Aijun, Liu, Chao, Liu, Chunxia, Liu, Cong, Liu, Fang, Liu, Fang, Liu, Guaiyan, 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Mengying, Tan, Binghu, Tang, Chunyan, Tang, Zhongli, Tao, Yu, Tian, Changming, Tian, Hongmei, Tian, Jian, Tian, Xiaomin, Wan, Huaibin, Wan, Qin, Wan, Rongjun, Wang, Bobin, Wang, Chao, Wang, Chaoqun, Wang, Chengliang, Wang, Di, Wang, Enfang, Wang, Feng, Wang, Gang, Wang, Guangqiang, Wang, Guixiang, Wang, Haifeng, Wang, Haijun, Wang, Haiyang, Wang, Jianfang, Wang, Jianfeng, Wang, Jing, Wang, Junping, Wang, Junying, Wang, Kang, Wang, Lei, Wang, Lei, Wang, Lin, Wang, Lize, Wang, Meng, Wang, Pan, Wang, Qi, Wang, Qiong, Wang, Qiuli, Wang, Qiuxue, Wang, Ran, Wang, Shaojin, Wang, Shuai, Wang, Tao, Wang, Tiantian, Wang, Tinghui, Wang, Tongyan, Wang, Wanhong, Wang, Wenjuan, Wang, Wenyan, Wang, Wenying, Wang, Wenzhuan, Wang, Xiaofei, Wang, Xiaoyan, Wang, Xitong, Wang, Xu, Wang, Yan, Wang, Yan, Wang, Yan, Wang, Yanfang, Wang, Yang, Wang, Yang, Wang, Yanping, Wang, Yanying, Wang, Yaoxin, Wang, Yingli, Wang, Yiting, Wang, Yue, Wang, Yumei, Wang, Yuzhuo, Wang, Zhenhua, Wang, Zhifang, Wang, Zhimin, Wei, Chunli, Wei, Lixia, Wei, Pei, Wei, Shuying, Wei, Xiqing, Wen, Hong, Wen, Yun, Wu, Chaoqun, Wu, Hairong, Wu, Lihua, Wu, Lingxiang, Wu, Qi, Wu, Shaorong, Wu, Wenting, Wu, Xueyi, Wu, Yongshuan, Wu, Zhihao, Wu, Zhuying, Wu, Zongyin, Wuhanbilige, Xia, Jun, Xia, Yang, Xiang, Jing, Xiao, Heliu, Xiao, Yaying, Xie, Meiling, Xie, Yinyan, Xin, Huiling, Xing, Jing, Xiu, Guoquan, Xu, Baohua, Xu, Chuangze, Xu, En, Xu, Jian, Xu, Shuli, Xu, Wei, Xu, Wen, Xue, Na, Xue, Tingting, Xue, Wei, Yan, Haiyan, Yan, Xiaofang, Yan, Yanqing, Yang, Bo, Yang, Hui, Yang, Huiyu, Yang, Jinhua, Yang, Kun, Yang, Man, Yang, Mengya, Yang, Ning, Yang, Ping, Yang, Xiajiao, Yang, Xiaomo, Yang, Xin, Yang, Xiujuan, Yang, Xuemei, Yang, Xuming, Yang, Yan, Yang, Yanhua, Yang, Yi, Yang, Yuanyuan, Yang, Zhimei, Yang, Zhiming, Yao, Hui, Yao, Lu, Ye, Jinling, Ye, Wenhua, Yi, Mingjiao, Yi, Shaowei, Yi, Wenyi, Yi, Zhimin, Yin, Guangxia, Yin, Guoyuan, Yu, Guibin, Yu, Hairong, Yu, Huaitao, Yu, Lijie, Yu, Lijun, Yu, Nana, Yu, Qin, Yu, Xinli, Yu, Yi, Yuan, Biao, Zeng, Chunmei, Zhai, Na, Zhai, Xiaojuan, Zhan, Hongju, Zhang, Aizhen, Zhang, Baohua, Zhang, Bin, Zhang, Caizhu, Zhang, Chaoying, Zhang, Chengbo, Zhang, Chunlai, Zhang, Churuo, Zhang, Fan, Zhang, Feiqin, Zhang, Ge, Zhang, Haibo, Zhang, Hailin, Zhang, Hanxue, Zhang, Huaixing, Zhang, Hui, Zhang, Huijuan, Zhang, Jinguo, Zhang, Jingyu, Zhang, Jinyun, Zhang, Jisheng, Zhang, Jun, Zhang, Lei, Zhang, Li, Zhang, Li, Zhang, Liang, Zhang, Lifeng, Zhang, Lina, Zhang, Liping, Zhang, Liping, Zhang, Min, Zhang, Ping, Zhang, Qiang, Zhang, Rufang, Zhang, Ruifen, Zhang, Shengde, Zhang, Siqi, Zhang, Sufang, Zhang, Tingting, Zhang, Wanyue, Zhang, Weiliang, Zhang, Xiaohan, Zhang, Xiaohong, Zhang, Xiaojuan, Zhang, Xin, Zhang, Xin, Zhang, Xue, Zhang, Xuewei, Zhang, Yachen, Zhang, Yang, Zhang, Yanyan, Zhang, Yaojie, Zhang, Yingyu, Zhang, Yuan, Zhang, Yun, Zhang, Yunfeng, Zhang, Zaozhang, Zhang, Zhichao, Zhao, Baihui, Zhao, Dan, Zhao, Fuxian, Zhao, Guizeng, Zhao, Haijie, Zhao, Honglei, Zhao, Huizhen, Zhao, Jindong, Zhao, Juan, Zhao, Liming, Zhao, Ling, Zhao, Lingshan, Zhao, Qingxia, Zhao, Qiuping, Zhao, Wanchen, Zhao, Wangxiu, Zhao, Weiyi, Zhao, Xiaodi, Zhao, Xiaojing, Zhao, Xiaoli, Zhao, Xiaoyan, Zhao, Xiling, Zhao, Yannan, Zhao, Yiyuan, Zheng, Shuzhen, Zheng, Xin, Zhi, Lixia, Zhong, Hui, Zhong, Qing, Zhong, Xin, Zhong, Yunzhi, Zhou, Jianfeng, Zhou, Jihu, Zhou, Ke, Zhou, Liangliang, Zhou, Ling, Zhou, Na, Zhou, Shengcheng, Zhou, Suyun, Zhou, Tao, Zhou, Wanren, Zhou, Weifeng, Zhou, Weijuan, Zhou, Xiaohong, Zhou, Yunke, Zhou, Yuquan, Zhou, Zhaohai, Zhou, Zhiming, Zhu, Bingpo, Zhu, Jifa, Zhu, Jing, Zhu, Mengnan, Zhu, Youcun, Zong, Dafei, Zuo, Hongbo, and Zuo, Zhaokai

Abstract

Uncertainty exists about whether lowering systolic blood pressure to less than 120 mm Hg is superior to that of less than 140 mm Hg, particularly in patients with diabetes and patients with previous stroke.

Published
2024
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45. Effects of concentrated sulfuric acid etching durations on the shear bond strength between polyether-ketone-ketone and dentin

Author

WANG Chenwei, SUN Fangfang, YANG Chuncheng, DING Ling, CHEN Xi, ZHANG Jiaqi, and WU Guofeng

Subjects
polyether-ketone-ketone, surface treatment, dentin, bonding, primer, relyxtm ultimate, shear bond strength, scanning electron microscope, Medicine
Abstract

Objective To study the effects of different concentrated sulfuric acid etching durations on the shear bond strength between polyether-ketone-ketone (PEKK) and dentin, providing a scientific basis for the clinical bonding procedures of PEKK prosthesis. Methods Forty-four PEKK specimens were prepared and randomly divided into four groups: group A was the control group, which was only polished with abrasive papers, group B, group C and group D were experimental groups, which were etched by 98% concentrated sulfuric acid for 5 s, 30 s and 60 s, respectively. In addition, one sample was randomly selected from each group, and the profile was prepared by a slow cutting machine. The surface morphology of the profile was observed under SEM. After the four groups of specimens and dentin were bonded by resin, they were soaked in distilled water at 37 ℃ for 24 h. After the shear bonding strengths were measured, the fracture interfaces of the specimens were examined by the scanning electron microscopy and stereomicroscopy, and failure models of bonding were analyzed. Results After acid etching treatments, the cross-sectional images in group B presented uniform spongy shapes, while the cross-sectional images in group C and group D showed destructive pore structures. The shear bond strengths of group B (16.84 ± 1.84) MPa, group C (12.33 ± 1.22) MPa and group D (6.44 ± 1.18) MPa were higher than that of group A (3.99 ± 1.06) MPa (P < 0.05). The highest shear bond strength was observed in group B (16.84 ± 1.84) MPa. Conclusion The surface treatment of 98% sulfuric acid etching for 5 s manifested the best bond strength between PEKK and dentin.

Published
2021
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46. Green and efficient method for the realization of full-component recovery of LiFePO4 black powder.

Author

Gao, Mai, Sun, Fangfang, Peng, Wenxiu, Dai, Wenbin, Zhang, Zaiwu, Zhang, Lei, Zhang, Hongzhou, Ma, Yue, Zhang, Lianqi, and Song, Dawei

Subjects
*WASTE recycling, *LIQUID waste, *POLLUTION, *WASTE gases, *POWDERS, *GEOLOGICAL carbon sequestration
Abstract

With regard to retired LiFePO4 batteries, resource treatment has become a matter of public concern. The currently used wet recycling process causes secondary environmental pollution and has the difficulty of full-component recovery. Therefore, a green and efficient recovery process for the realization of full-component recovery of LiFePO4 black powder is proposed in this work. In this closed-loop process with liquid flow circulation, no waste liquid and gas emission is generated, and the purity of recycled Li2CO3 can reach up to 99.4%. Moreover, battery-grade FePO4 can be obtained after simple treatment, solving the problem of lithium tailings and slag in the traditional wet recycling process. The performances of recycled Li2CO3 and FePO4 are similar to commercialization products according to electrochemical tests. More importantly, the resynthesized LiFePO4 cathode displays high-capacity retention of 97.5% after 200 cycles at 0.5 C, indicating the superiority of our strategy. Furthermore, the pouch cell with 5.2 A h presents outstanding performance, and high-capacity retentions of 96% and 95.2% can be observed after 500 cycles at 0.5 C and 1 C, respectively. The aforementioned results indicate the attractive prospects of this green and efficient lithium extraction and full-component recovery process. [ABSTRACT FROM AUTHOR]

Published
2024
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