27 results on '"Sun, Fangfang"'
Search Results
2. Rectifying METTL4-Mediated N6-Methyladenine Excess in Mitochondrial DNA Alleviates Heart Failure
- Author
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Zhang, Fuyang, Zhang, Ling, Hu, Guangyu, Chen, Xiyao, Liu, Hui, Li, Congye, Guo, Xiong, Huang, Chong, Sun, Fangfang, Li, Tongzheng, Cui, Zhe, Guo, Yongzhen, Yan, Wenjun, Xia, Yunlong, Liu, Zhiyuan, Lin, Zhen, Duan, Weixun, Lu, Linhe, Wang, Xinyi, Wang, Zhengyang, Wang, Shan, and Tao, Ling
- Published
- 2024
- Full Text
- View/download PDF
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
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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
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- 2024
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4. The effects of manager sentiment in financial disclosure: Perspectives of operational efficiency and market reaction
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Wang, Chunlan, Xin, Jianxuan, Sun, Fangfang, Shi, Yan, and Du, Yuxuan
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- 2024
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5. Rectifying METTL4-Mediated N 6 -Methyladenine Excess in Mitochondrial DNA Alleviates Heart Failure
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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
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- 2024
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6. Exploration of the Effects of Cadmium Stress on Photosynthesis in Oenanthe javanica (Blume) DC
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Zhou, Ronghua, primary, Xu, Jun, additional, Li, Liangjun, additional, Yin, Yulai, additional, Xue, Bowen, additional, Li, Jingjing, additional, and Sun, Fangfang, additional
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- 2024
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7. The relationship between metabolic syndrome components and prostate cancer risk : a Mendelian randomization study
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Shen, Chaodong, primary, Zhu, Zhirong, additional, Zhang, Xiaolong, additional, Fang, Mengjie, additional, Chen, Jiajian, additional, Shao, Feng, additional, Sun, Fangfang, additional, and Tang, Guiliang, additional
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- 2024
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8. Meta-Learning Enhanced Trade Forecasting: A Neural Framework Leveraging Efficient Multicommodity STL Decomposition
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Ma, Bohan, primary, Xue, Yushan, additional, Chen, Jing, additional, and Sun, Fangfang, additional
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- 2024
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9. Targeting of KDM5A by miR-421 in Human Ovarian Cancer Suppresses the Progression of Ovarian Cancer Cells [Retraction]
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Ren, Fang, primary, Shrestha, Christina, additional, Shi, Huirong, additional, Sun, Fangfang, additional, Zhang, Minghui, additional, Cao, Yuan, additional, and Li, Gailing, additional
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- 2024
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10. Predicting the Risk of Fundus Lesions in Systemic Lupus Erythematosus: A Nomogram Model.
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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]
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- 2024
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11. Optimal development of apoptotic cells-mimicking liposomes targeting macrophages.
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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]
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- 2024
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12. General method to digitalize multi-layer woven structure.
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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]
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- 2024
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13. Controlled Reflected McKean–Vlasov SDEs and Neumann Problem for Backward SPDEs
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Ma, Li, primary, Sun, Fangfang, additional, and Han, Xinfang, additional
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- 2024
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14. Spatiotemporal Controllable Sono‐Nanovaccines Driven by Free‐Field Based Whole‐Body Ultrasound for Personalized Cancer Therapy
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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
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- 2024
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15. Epithelial thickness remodeling after small incision lenticule intrastromal keratoplasty in correcting hyperopia measured by RTVue OCT
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Dong, Yahui, primary, Hou, Jie, additional, Zhang, Jing, additional, Lei, Yulin, additional, Yang, Xinghua, additional, and Sun, Fangfang, additional
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- 2024
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16. Green and efficient method for realization of full-component recovery of LiFePO4 black powder
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Gao, Mai, primary, Sun, Fangfang, additional, Peng, Wenxiu, additional, Dai, Wenbin, additional, Zhang, Zaiwu, additional, Zhang, Lei, additional, Zhang, Hongzhou, additional, Ma, Yue, additional, Zhang, Lianqi, additional, and Song, Dawei, additional
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- 2024
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17. PD-1/PD-L1 governed cross-talk of exhausted CD8+T and memory B cells in systemic lupus erythematosus
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Wang, Kaiwen, primary, Zhao, Jiangfeng, additional, Feng, Xuemei, additional, He, Shuangjun, additional, Li, Jia, additional, Sun, Fangfang, additional, Xu, Zhangling, additional, Yang, Haiting, additional, Ye, Jiaer, additional, Cao, Liou, additional, and Ye, Shuang, additional
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- 2024
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18. The Effects of Manager Sentiment in Financial Disclosure: Perspectives of Operational Efficiency and Market Reaction
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Du, Yuxuan, primary, Wang, Chunlan, additional, Xin, Jianxuan, additional, Sun, Fangfang, additional, and Shi, Yan, additional
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- 2024
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19. 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
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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, 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, 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, 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, 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, Lin, 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, 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.
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- 2024
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20. Green and efficient method for the realization of full-component recovery of LiFePO4 black powder.
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Gao, Mai, Sun, Fangfang, Peng, Wenxiu, Dai, Wenbin, Zhang, Zaiwu, Zhang, Lei, Zhang, Hongzhou, Ma, Yue, Zhang, Lianqi, and Song, Dawei
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- *
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]
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- 2024
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21. Mn Cluster-Embedded N/F Co-Doped Carbon toward Mild Aqueous Supercapacitors.
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Zheng, Chen, Han, Xu, Sun, Fangfang, Zhang, Yue, Huang, Zihang, and Ma, Tianyi
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SUPERCAPACITORS ,SUPERCAPACITOR electrodes ,ENERGY storage equipment ,DOPING agents (Chemistry) ,CARBON-based materials ,ENERGY density ,TRANSITION metals ,MANGANESE ,FULLERENES - Abstract
Aqueous supercapacitors have occupied a significant position among various types of stationary energy storage equipment, while their widespread application is hindered by the relatively low energy density. Herein, N/F co-doped carbon materials activated by manganese clusters (NCM) are constructed by the straightforward experimental routine. Benefiting from the elevated conductivity structure at the microscopic level, the optimized NCM-0.5 electrodes exhibited a remarkable specific capacitance of 653 F g
−1 at 0.4 A g−1 and exceptional cycling stability (97.39% capacity retention even after 40,000 cycles at the scanning rate of 100 mV s−1 ) in a neutral 5 M LiCl electrolyte. Moreover, we assembled an asymmetric device pairing with a VOx anode (NCM-0.5//VOx ), which delivered a durable life span of 95% capacity retention over 30,000 cycles and an impressive energy density of 77.9 Wh kg−1 . This study provides inspiration for transition metal element doping engineering in high-energy storage equipment. [ABSTRACT FROM AUTHOR]- Published
- 2024
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22. Global burden of diabetes mellitus from 1990 to 2019 attributable to dietary factors: An analysis of the Global Burden of Disease Study 2019.
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Hong, Ting, Sun, Fangfang, Wang, Qiwei, Chen, Xufeng, and Han, Kun
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- *
GLOBAL burden of disease , *MEAT , *FACTOR analysis , *DIABETES - Abstract
Aims: To analyse spatial and temporal changes in the global burden of diabetes mellitus (DM) attributable to dietary factors from 1990 to 2019. Materials and Methods: The burden of DM was analysed in terms of age‐standardized disability‐adjusted life‐year (DALY) rates and age‐standardized death rates (ASDRs), which were obtained from the Global Burden of Disease Study 2019, and their corresponding estimated annual percentage changes (EAPCs). Results: The ASDR exhibited a decreasing trend (EAPC = −0.02), while the age‐standardized DALY rate exhibited an increasing trend (EAPC = 0.65). Forty‐four percent of the burden of DM was attributable to dietary factors, with the three largest contributors being high intake of red meat, high intake of processed meat, and low intake of fruit. Residence in a region with a high sociodemographic index (SDI) was associated with a diet low in whole grains and high in red meat and processed meat, while residence in a low‐SDI region was associated with a diet low in whole grains and fruits, and high in red meat. Conclusions: The age‐standardized DALYs of DM attributable to dietary factors increased between 1990 and 2019 but differed among areas. The three largest dietary contributors to the burden of DM were high intake of red meat, high intake of processed meat, and low intake of fruit. [ABSTRACT FROM AUTHOR]
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- 2024
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23. Multifunctional Nanosystem Based on Ultrasmall Carbon Dots for the Treatment of Acute Kidney Injury
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Yao, Hanchun, Zhu, Zhihui, Liu, Mengyu, Sun, Fangfang, Du, Mengyu, Sun, Yilin, and Du, Bin
- Abstract
Acute kidney injury (AKI) is a critical medical condition characterized by high morbidity and mortality rates. The pathogenesis of AKI potentially involves bursts of reactive oxygen species (ROS) bursts and elevated levels of inflammatory mediators. Developing nanoparticles (NPs) that downregulate ROS and inflammatory mediators is a promising approach to treat AKI. However, such NPs would be affected by the glomerular filtration barrier (GFB). Typically, NPs are too large to penetrate the glomerular system and reach the renal tubules─the primary site of AKI injury. Herein, we report the development of ultrasmall carbon dots-gallic acid (CDs-GA) NPs (∼5 nm). These NPs exhibited outstanding biocompatibility and were shown not only to efficiently eliminate ROS and alleviate oxidative stress but also to suppress the activation of the NF-κB signaling pathway, leading to a reduction in the release of inflammatory factors. Importantly, CDs-GA NPs were shown to be able to rapidly accumulate rapidly in the renal tissues without the need for intricate targeting strategies. In vivo studies demonstrated that CDs-GA NPs significantly reduced the incidence of cisplatin (CDDP)-induced AKI in mice, surpassing the efficacy of the small molecular drug, N-acetylcysteine. This research provides an innovative strategy for the treatment of AKI.
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- 2024
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24. Blocking the utilization of carbon sources via two pathways to induce tumor starvation for cancer treatment.
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Zhu Z, Qiao P, Liu M, Sun F, Geng M, and Yao H
- Abstract
Glucose oxidase (GOx) is often used to starvation therapy. However, only consuming glucose cannot completely block the energy metabolism of tumor cells. Lactate can support tumor cell survival in the absence of glucose. Here, we constructed a nanoplatform (Met@HMnO
2 -GOx/HA) that can deplete glucose while inhibiting the compensatory use of lactate by cells to enhance the effect of tumor starvation therapy. GOx can catalyze glucose into gluconic acid and H2 O2 , and then HMnO2 catalyzes H2 O2 into O2 to compensate for the oxygen consumed by GOx, allowing the reaction to proceed sustainably. Furthermore, metformin (Met) can inhibit the conversion of lactate to pyruvate in a redox-dependent manner and reduce the utilization of lactate by tumor cells. Met@HMnO2 -GOx/HA nanoparticles maximize the efficacy of tumor starvation therapy by simultaneously inhibiting cellular utilization of two carbon sources. Therefore, this platform is expected to provide new strategies for tumor treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)- Published
- 2024
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25. Combination of anti-SSA/Ro60 and anti-dsDNA serotype is predictive of belimumab renal response in patients with lupus nephritis.
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Zhao L, Wang W, Wu L, Wu T, Tu J, Wu X, Sun F, Ding H, Shen N, Wu H, Zhu J, Sun L, and Ye S
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- Humans, Female, Male, Adult, Middle Aged, Treatment Outcome, Kidney physiopathology, Kidney drug effects, Kidney immunology, Biomarkers blood, Young Adult, Proteinuria drug therapy, DNA, Lupus Nephritis drug therapy, Lupus Nephritis immunology, Antibodies, Monoclonal, Humanized therapeutic use, Antibodies, Antinuclear blood, Immunosuppressive Agents therapeutic use, Glomerular Filtration Rate drug effects
- Abstract
Objectives: To investigate the effectiveness of belimumab on active lupus nephritis (LN) and explore the predictors, including serological biomarkers, of renal response to belimumab in a real-world setting., Methods: This multicentre, real-world observational study enrolled patients with active LN receiving intravenous belimumab as an add-on therapy with 24-hour urine protein≥1 g and estimated glomerular filtration rate≥30 mL/min/1.73 m
2 at baseline. Complete renal response (CRR), partial renal response (PRR), no renal response (NRR) and primary efficacy renal response (PERR) were evaluated. Multivariable logistic regression was used to identify risk factors for NRR to belimumab at 6 months., Results: Among the 122 patients enrolled, the proportions of patients achieving CRR, PRR, NRR and PERR were 35.9%, 17.1%, 47.0% and 44.4% at 6 months (n=117) and 55.6%, 19.4%, 26.4% and 58.3% at 12 months (n=72), respectively. Proteinuria, daily prednisone dosage and Systemic Lupus Erythematosus Disease Activity Index 2000 scores significantly decreased at 6 and 12 months (p<0.0001). NRR at 6 months (NRR6) was the strongest negative predictor of CRR at 12 months. Baseline anti-dsDNA positivity inversely predicted NRR6 (OR=0.32,95% CI=0.10 to 0.98, p=0.049), while anti-SSA/Ro60 positively predicted NRR6 (OR=3.16, 95% CI=1.14 to 8.74, p=0.027). The combination of anti-SSA/Ro60 and anti-dsDNA serotype quantitatively predicted belimumab renal response., Conclusion: The effectiveness of belimumab was reproducible in Chinese patients with active LN. The simple yet interesting serotype predictive model needs further validation and its possible underlying mechanistic relevance deserves further exploration., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)- Published
- 2024
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26. PD-1/PD-L1 governed cross-talk of exhausted CD8 + T and memory B cells in systemic lupus erythematosus.
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Wang K, Zhao J, Feng X, He S, Li J, Sun F, Xu Z, Yang H, Ye J, Cao L, and Ye S
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- Humans, Programmed Cell Death 1 Receptor metabolism, Memory B Cells, B7-H1 Antigen physiology, Ligands, Rituximab, CD8-Positive T-Lymphocytes metabolism, Lupus Erythematosus, Systemic complications
- Abstract
Background: Indeterminate readout of the quantitative interferon-γ release test (QFT) for Mycobacterium tuberculosis screening is a specific laboratory finding for systemic lupus erythematosus (SLE), which may be due to T-cell exhaustion and abnormal programmed death receptor 1 (PD-1)/programmed death-ligand 1 (PD-L1) signalling., Methods: We enrolled 104 patients with SLE and 225 with other rheumatic musculoskeletal diseases (RMDs) who presented to the outpatient clinic between 2020 and 2023. Twenty healthy donors served as the controls. The QFT was performed in all participants, and those with indeterminate results were compared among the groups. Immunophenotyping and functional assays were performed using blood mononuclear cells. Interferon (IFN)-γ was detected in vitro and ex vivo in patients with SLE with indeterminate or negative QFT results, before or after rituximab therapy., Results: 104 patients with SLE had a significantly higher rate of indeterminate QFT results was significantly higher (17.31%) than that of 225 patients with RMD (3.56%). Patients with SLE with indeterminate QFT had more active disease (SLEDAI-2K, mean 10.94 vs 4.02, p<0.0001), including a higher incidence of active nephritis (55.56% vs 29.07%). Indeterminate QFT in SLE is mainly caused by an insufficient IFN-γ response in CD8+T cells with exhausted immunophenotypes. The abnormal interaction between exhausted PD-1 high CD8
+ T cells and activated PD-L1 low memory B cells in SLE can be reversed with a PD-1 agonist or increased PD-L1 expression. Rituximab treatment indirectly reversed this IFN-γ response., Conclusion: The PD-1/PD-L1 signalling pathway, which governs the crosstalk between exhausted CD8+ T cells and activated memory B cells, is a mechanistic explanation for insufficient interferon-γ response in patients with SLE., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)- Published
- 2024
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27. Detection of microvascular damage of membranous nephropathy by MicroFlow imaging: a novel ultrasound technique.
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Lu R, Sun F, Zhang L, Zhang C, Du J, Hao J, and Zhao L
- Abstract
Background: MicroFlow imaging (MFI) is a novel noninvasive ultrasound (US) technique that depicts microcirculatory blood vessels in the kidney while filtering out tissue motion and enhancing blood flow signals. We aimed to investigate the value of MFI for the detection of renal microvascular perfusion in chronic kidney disease caused by stage I-II membranous nephropathy (MN)., Methods: Seventy-six participants including biopsy-proven MN (n=38) and healthy volunteers (n=38) were prospectively examined using MFI from March 2020 to December 2020. In addition, patients with MN were subdivided into a mild group, a moderate group, and a severe group based on the results of vascular pathology evaluation. All MFI images were analyzed by Image Pro Plus to obtain a cortical vascular index (VI). Basic patient information, relative US parameters and laboratory results were then acquired for each participant. Finally, after the univariate analysis among multiple groups, binary logistic regression (forward LR) and ordered logistic regression were used for multivariate analysis. Significance was set at P<0.05., Results: VI was significantly lower in MN patients compared with that of healthy controls (0.65±0.09 vs. 0.35±0.18, P<0.001). After multivariate analysis, we found that the exploratory diagnostic performance of VI [area under the curve (AUC): 0.94; 95% confidence interval (CI): 0.89-0.99] outperformed that of serum creatinine (Scr) (AUC: 0.87; 95% CI: 0.79-0.95) in identifying MN. We also observed considerable differences among MN groups in parameters including VI (P=0.006), estimated glomerular filtration rate (eGFR) (P=0.037), shape (P=0.013), and impression (P=0.007). In addition, in the group with mild vascular damage, the exploratory diagnostic performance of VI (AUC: 0.79; 95% CI: 0.64-0.94) was better than other parameters, such as eGFR (AUC: 0.63; 95% CI: 0.43-0.84)., Conclusions: MFI detected abnormal renal microvascular perfusion in patients with MN (particularly in those with early vascular damage or preserved renal function) without the use of a contrast agent. Combining MFI with B-mode US can improve the predictive performance of traditional kidney US., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1010/coif). The authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)
- Published
- 2024
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