👤 Jiheng Wang

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Also published as: Junli Wang, Xindi Wang, Junpeng Wang, Tingyu Wang, Guoqiang Wang, Yuxuan Wang, Hanzhi Wang, Zhi-Long Wang, Shanshan Wang, Wenfei Wang, Dengbin Wang, Yen-Sheng Wang, Chuanxin Wang, Zeyu Wang, Beibei Wang, Taicheng Wang, Xingguo Wang, Z P Wang, Yue-Min Wang, Chenghua Wang, Xianqiang Wang, Congrong Wang, Yanhai Wang, Du Wang, Xianzhe Wang, Zuoheng Wang, Yongyi Wang, Zhihui Wang, Yanhua Wang, Limeng Wang, H J Wang, Pei-Jian Wang, Yana Wang, Congrui Wang, Larry Wang, Yu-Zhuo Wang, Sihua Wang, Wanchun Wang, Jialin Wang, Xinying Wang, Shuguang Wang, Yinhuai Wang, Xiaobin Wang, Yuying Wang, Hebo Wang, Leli Wang, Jiayu Wang, Zhaojun Wang, Hai Wang, Si Wang, Re-Hua Wang, Xuping Wang, Bo Wang, Shubao Wang, Songjiao Wang, Hongjia Wang, Victoria Wang, Ling Wang, Jianjie Wang, Haining Wang, Dali Wang, Ji-Yang Wang, Cheng Wang, Weifan Wang, Yuanqiang Wang, Zhixiao Wang, Yaxian Wang, Zhigang Wang, Haochen Wang, Jia-Ying Wang, Shichao Wang, Ruosu Wang, N Wang, Haixing Wang, Guiqun Wang, Zhiting Wang, Dan Wang, Wangxia Wang, Jing-Long Wang, Yaqian Wang, Yafang Wang, Xing-Jun Wang, Dapeng Wang, Zhongyuan Wang, Junsheng Wang, Zhaohai Wang, He-Ping Wang, Minmin Wang, Wenzhou Wang, Zhaohui Wang, Yanfang Wang, Pengtao Wang, Leran Wang, Qianwen Wang, Hongkun Wang, Sa Wang, Y Alan Wang, Liyan Wang, Jou-Kou Wang, Mingda Wang, Chenfei Wang, Yuehan Wang, Simeng Wang, Yuhua Wang, Ruibin Wang, Haibo Wang, Ni Wang, Guoxiu Wang, Zhuangzhuang Wang, Yajie Wang, Zhixiang Wang, Sangui Wang, Xiantao Wang, Yan-Yang Wang, Mengjun Wang, Ruling Wang, Peihe Wang, Miao Wang, Zaihua Wang, Jun-Jie Wang, Mengyao Wang, Zhiyu Wang, Changzhen Wang, Xijun Wang, Chengjian Wang, Yiyi Wang, Mo Wang, Xiaolun Wang, Danan Wang, Fanchang Wang, Zilin Wang, Fanhua Wang, Supeng Perry Wang, Gavin Wang, Yi-Ying Wang, Yani Wang, Zhuowei Wang, Weiwei Wang, Haifeng Wang, Yi-Shiuan Wang, Yan-Chao Wang, Xiaotong Wang, Jia-Qi Wang, Yongliang Wang, Yongming Wang, Fengchong Wang, Jianyong Wang, Zeping Wang, Huaquan Wang, Xiaojia Wang, Tao Wang, Tianjun Wang, Siying Wang, Zhenze Wang, Zhijian Wang, Li Wang, Heming Wang, Jingtong Wang, Xuefei Wang, Yingqiao Wang, Xiao Qun Wang, Chun-Chieh Wang, Shuang-Xi Wang, Laiyuan Wang, Zhaoming Wang, Yinggui Wang, Qi-Jia Wang, Wen-Yan Wang, Mingming Wang, Peipei Wang, Chien-Hsun Wang, Qiuhong Wang, Monica Wang, Lexin Wang, Xiufen Wang, Yuehua Wang, Pingfeng Wang, Caiyan Wang, Weijie Wang, Yigang Wang, Jieyan Wang, Huiquan Wang, Chunsheng Wang, Yunhe Wang, Changtu Wang, Qingliang Wang, Guanghua Wang, Yongbin Wang, Zhaobo Wang, Minghui Wang, Junshi Wang, Jingyu Wang, Longsheng Wang, Fen Wang, Xianshu Wang, Jianwu Wang, Jun-Zhuo Wang, Zhixing Wang, Lei Wang, Yiyan Wang, Jinglin Wang, Jinhe Wang, Enhua Wang, Yuecong Wang, Xueying Wang, Jennifer T Wang, Xin-Hua Wang, Shijie Wang, Chun-Xia Wang, Yuanjiang Wang, Xiaojun Wang, Shunjun Wang, Chun-Juan Wang, M Wang, Jinfei Wang, Jinghuan Wang, Xuru Wang, Xiao-Lan Wang, Yu-Chen Wang, Zhi-Guo Wang, Luya Wang, Shuwei Wang, Pingchuan Wang, Qifan Wang, Xing-Quan Wang, Weiding Wang, Xuebin Wang, Yaling Wang, Chenyin Wang, Allen Wang, Liyuan Wang, Rong-Rong Wang, Wusan Wang, Wayseen Wang, Qianru Wang, Yi-Xin Wang, Hailin Wang, Yu-Hang Wang, Xuesong Wang, Haojie Wang, Wanxia Wang, Mengwen Wang, Hanping Wang, Yuhang Wang, Lueli Wang, Xinchang Wang, Oliver Wang, Shuge Wang, Jianhao Wang, Chong Wang, Kui Wang, Litao Wang, Zining Wang, Ming-Yang Wang, Hongxia Wang, Mingyi Wang, Hai Bo Wang, Bingnan Wang, Hongqian Wang, Jisheng Wang, Jiakun Wang, Maoju Wang, Xiaoqiu Wang, Dongyi Wang, Hai Yang Wang, Pengju Wang, Xiaofeng Wang, Huming Wang, Jian'an Wang, Qianrong Wang, Xiaowei Wang, Xiangkun Wang, Da Wang, Hongying Wang, Changying Wang, Changyu Wang, Xiaoqin Wang, Zhenxi Wang, Qiaoqiao Wang, Yu Tian Wang, Yupeng Wang, Xinli Wang, YueJiao Wang, Jian-chun Wang, Pengchao Wang, Xiao-Juan Wang, Siqing Wang, C Z Wang, Pengbo Wang, Baoli Wang, Yu-Zhe Wang, Gui-Qi Wang, Dazhi Wang, Yanwen Wang, Xingqin Wang, Shijin Wang, Wenming Wang, Fanxiong Wang, Tiansong Wang, Shuzhe Wang, Jie Wang, Jinling Wang, Yunfang Wang, Luyao Wang, Cun-Yu Wang, Zikang Wang, Quan-Ming Wang, Yingying Wang, Chia-Chuan Wang, Xintong Wang, Jufeng Wang, Xuejun Wang, Xiao-Qian Wang, Yijin Wang, Meng Yu Wang, Tianyi Wang, Chia-Lin Wang, Zhuo-Jue Wang, Yaohe Wang, Rong Wang, Hao-Hua Wang, Yong-Jun Wang, Xubo Wang, Dalong Wang, Yan-Ge Wang, Erika Y Wang, Ruixian Wang, Jin-Liang Wang, Shicung Wang, Saifei Wang, Jintao Wang, Zhenzhen Wang, Jiawei Wang, Beilei Wang, Huabo Wang, Huiyu Wang, Hongtao Wang, Chengjun Wang, Guo-Du Wang, Taoxia Wang, Zitao Wang, Jingwen Wang, Yibin Wang, Long Wang, Xinjing Wang, Qunzhi Wang, Liangliang Wang, Bangchen Wang, Yu-Fen Wang, Shibin Wang, Congcong Wang, Xiong Wang, Zhiren Wang, Xiaozhu Wang, Hong-Xia Wang, Qingyong Wang, Tianying Wang, Tammy C Wang, Huijie Wang, Tiansheng Wang, Mengzhao Wang, Jianshu Wang, Xinlong Wang, Benzhong Wang, Zhipeng Wang, Kaijie Wang, Xiaomin Wang, Peijun Wang, Zhiqiang Wang, Jundong Wang, Zheng Wang, Yueze Wang, Sujuan Wang, Qing-Yun Wang, Xiaoqing Wang, Zongqi Wang, Zhicun Wang, Fudi Wang, Seok Mui Wang, Wanbing Wang, Kejun Wang, Nanping Wang, Mingyang Wang, Wenxia Wang, Yaru Wang, Zikun Wang, Shidong Wang, Bei Bei Wang, Yu-Hui Wang, Rui Wang, Yige Wang, Tongxin Wang, Xiaohua Wang, Changjing Wang, Xingjin Wang, Bingjie Wang, Shaoyu Wang, Hui-Hui Wang, Zhenyu Wang, Baoying Wang, Yang-Yang Wang, Shi-Yao Wang, Lifei Wang, Fangfang Wang, Zhimei Wang, Kunpeng Wang, Binglong Wang, Daijun Wang, Qinghang Wang, Zi Wang, Shushu Wang, QingDong Wang, Qing K Wang, Fuhua Wang, Yanni Wang, Jianle Wang, Wenyan Wang, Jinning Wang, Ziqi Wang, Wei-Qi Wang, Yaolou Wang, Haoming Wang, Jian-Wei Wang, Tian Wang, Peixi Wang, Iris X Wang, Tongxia Wang, Mei-Xia Wang, Haiying Wang, Tielin Wang, Hongze Wang, Chung-Hsi Wang, Peiyao Wang, Linli Wang, Guanru Wang, Yuzhong Wang, Yunhan Wang, Jianan Wang, Menglong Wang, Yingxue Wang, Jiayi Wang, Dingxiang Wang, Ting Wang, Fenglin Wang, Jianqun Wang, Ran Wang, Kuan Hong Wang, Liusong Wang, Wen-Der Wang, Yixuan Wang, Feng Wang, Kaicen Wang, Eryao Wang, Yulei Wang, Huaibing Wang, Zhongzhi Wang, Jinrong Wang, Sujie Wang, Xiaozhong Wang, Xiao-Pei Wang, Li-Na Wang, H X Wang, Linjie Wang, Zhaosong Wang, Yafen Wang, Chuan-Wen Wang, Xiaoning Wang, Li-Xin Wang, Silas L Wang, Baocheng Wang, Hongyi Wang, Zhi-Xiao Wang, Shengjie Wang, Zhi-Hao Wang, Yaokun Wang, Shao-Kang Wang, Qunxian Wang, Jianghui Wang, Zhao Wang, Di Wang, Jianzhi Wang, Ruijing Wang, Ling Jie Wang, Qingshi Wang, Jianye Wang, Yuqiang Wang, Kangling Wang, Anxin Wang, Shengli Wang, Zhulin Wang, Hua-Wei Wang, Yiwen Wang, Yang Wang, Hanqi Wang, Changwei Wang, Honglei Wang, Yi Lei Wang, Wenkang Wang, Junjie Wang, Yazhou Wang, Peng-Cheng Wang, Chenzi Wang, Anqi Wang, Yuemiao Wang, Xuelin Wang, Rujie Wang, Dongyan Wang, Yuxue Wang, Wengong Wang, Qigui Wang, Junqing Wang, Ruhan Wang, Xinye Wang, Huihui Wang, Gengsheng Wang, Mark Wang, Zhidong Wang, Mengmeng Wang, Yuwen Wang, Liang Wang, Huaxiang Wang, Fangjun Wang, Huixia Wang, Haijiao Wang, Hong-Hui Wang, Yi-Shan Wang, Yunchao Wang, Junjun Wang, Binghai Wang, Xinguo Wang, Jun-Sing Wang, Lingzhi Wang, Yuexiang Wang, Hong-Gang Wang, Yen-Feng Wang, Xidi Wang, Jiawen Wang, Liangfu Wang, Lifeng Wang, Shihan Wang, Wentian Wang, Sa A Wang, Lee-Kai Wang, Yu-Wei Wang, Zumin Wang, Shau-Chun Wang, Jianjiao Wang, Tian-Tian Wang, Jiantao Wang, Edward Wang, Jianbo Wang, Qingfeng Wang, Wenran Wang, Xiaolin Wang, Fenghua Wang, Rongjia Wang, Shiqiang Wang, Caixia Wang, Guihu Wang, Xindong Wang, Wenxiu Wang, Xueguo Wang, YiLi Wang, Aizhong Wang, Qiqi Wang, Chengcheng Wang, D Wang, L Wang, Jianhua Wang, Qiuling Wang, Shaolian Wang, Wen-Qing Wang, Wenqing Wang, Yuchuan Wang, Guangdi Wang, Yiquan Wang, Huimei Wang, Genghao Wang, Zun Wang, Miranda C Wang, Annette Wang, Chi-Ping Wang, Hanmin Wang, Zhaoxi Wang, Shifeng Wang, Runze Wang, Mangju Wang, Junjiang Wang, Dong D Wang, Xiu-Ping Wang, Haijiu Wang, Linghuan Wang, Yiying Wang, Renqian Wang, Nana Wang, Xiangdong Wang, Shiyin Wang, Chaoyi Wang, Menghan Wang, Shuyue Wang, Yongmei Wang, Nanbu Wang, Lihua Wang, Hongyue Wang, Jianli Wang, Chunli Wang, Minghua Wang, Junkai Wang, Chenguang Wang, Siyue Wang, Jun Wang, Shu-Song Wang, Bingyan Wang, Qingping Wang, Zhong-Yu Wang, Fei-Fei Wang, Jennifer E Wang, Z-Y Wang, Dongxia Wang, Dang Wang, Zi-Hao Wang, Rihua Wang, Jutao Wang, Yanzhe Wang, Guohao Wang, Liming Wang, Yishu Wang, Xuemin Wang, Xianfeng Wang, Zixu Wang, Jingfan Wang, Guang-Jie Wang, Guixue Wang, Jiaojiao Wang, Yaxin Wang, Haibing Wang, Weizhong Wang, Hairong Wang, Hai-Jun Wang, Mingji Wang, Yongrui Wang, Huizhi Wang, Longfei Wang, Chongmin Wang, Jingyang Wang, Zhong-Ping Wang, Huanhuan Wang, Baisong Wang, Xiaohui Wang, Fengyang Wang, Wanliang Wang, Ziqiang Wang, Chuan Wang, Jeffrey Wang, Ying-Zi Wang, Ziwei Wang, Xian Wang, Hanyu Wang, Qiming Wang, Dedong Wang, Fengying Wang, Xiaoya Wang, Zhenhua Wang, Yanchun Wang, Keming Wang, Zi-Yi Wang, Dezhong Wang, Jingying Wang, Shouli Wang, Lan-lan Wang, Weiyu Wang, Yuhuai Wang, Jun Yi Wang, Wenying Wang, Xue-Feng Wang, Xing-Lei Wang, Yuehong Wang, Pengyu Wang, Yihe Wang, Guodong Wang, Weijian Wang, Wu-Wei Wang, Y Wang, Ruonan Wang, Jianbing Wang, Mian Wang, Dennis Qing Wang, Nannan Wang, Zuo Wang, Christine Wang, Ruixin Wang, Yaxiong Wang, Siwei Wang, Yuanzhen Wang, Wen-Chang Wang, Haijing Wang, X Wang, Melissa T Wang, Haixia Wang, Qianghu Wang, Hongsheng Wang, Xiurong Wang, Shaowei Wang, Shuo Wang, Zengtao Wang, Yun-Xing Wang, Songtao Wang, Mei Wang, Mengyun Wang, Qingming Wang, Ke-Feng Wang, Zhihao Wang, Haoqi Wang, X E Wang, Xin-Shang Wang, Dongmei Wang, Lingli Wang, Huai-Zhou Wang, Hua Wang, Kunzheng Wang, Mao-Xin Wang, Jingzhou Wang, Jiaqi Wang, Xingbang Wang, Wence Wang, Yongdi Wang, Xin-Qun Wang, Guoyi Wang, Jian-Guo Wang, Jiafu Wang, Pin Wang, Libo Wang, Junling Wang, J Z Wang, Haozhou Wang, Jing Wang, Hezhi Wang, T Q Wang, Xi-Hong Wang, Yuanfan Wang, Endi Wang, Hua-Qin Wang, Jeremy Wang, Songping Wang, Suyun Wang, Jiqing Wang, Shu-Ling Wang, Jennifer X Wang, Lily Wang, Yin-Hu Wang, Jen-Chywan Wang, Qingqing Wang, Shuangyuan Wang, Haihong Wang, Luyun Wang, Yake Wang, Ya-Nan Wang, Weicheng Wang, Jianxiang Wang, Zihua Wang, Lin Wang, Fu-Sheng Wang, Zongbao Wang, Tong-Hong Wang, Xianze Wang, Ting-Ting Wang, Haibin Wang, Xin-Yue Wang, Zhi-Gang Wang, Ziying Wang, Shukang Wang, Wen-Jun Wang, Delin Wang, Yating Wang, Xuehao Wang, Yefu Wang, Yi-Ning Wang, Cheng-zhang Wang, Jing J Wang, Xinglong Wang, Yanqing Wang, Tongyao Wang, Dongyang Wang, Deqi Wang, Qiao Wang, Alice Wang, Yunzhi Wang, Dayong Wang, Renxi Wang, Yeh-Han Wang, Mingya Wang, Longxiang Wang, Hualin Wang, Hailei Wang, Ao Wang, Wanyu Wang, Jiale Wang, Qiangcheng Wang, Huishan Wang, Yunqiong Wang, Xudong Wang, Xifu Wang, Wen-Xuan Wang, Dao Wen Wang, Zhi-Wei Wang, Xingchen Wang, Yanyang Wang, Yutao Wang, Huizhen Wang, Hu WANG, Y P Wang, Wen Wang, Qingsong Wang, Baofeng Wang, Ruo-Ran Wang, Yaobin Wang, Changliang Wang, Pintian Wang, Dai Wang, Su-Guo Wang, Ruting Wang, Fengzhen Wang, Qinrong Wang, HuiYue Wang, Baosen Wang, Shuhe Wang, Yifei Wang, Jiun-Ling Wang, Junhui Wang, Guangzhi Wang, Qijia Wang, Yushe Wang, Jinlong Wang, Zhouguang Wang, Huiyao Wang, Shuxin Wang, Yingyi Wang, Jing-Yi Wang, Yongxiang Wang, Zhi Wang, Dehao Wang, Yi-sheng Wang, Jiazhi Wang, Yunfei Wang, Mingjin Wang, Yaozhi Wang, Jinyu Wang, Jinmeng Wang, LiLi Wang, Shuai Wang, Yan Wang, Jun Kit Wang, Cui Wang, Zhan Wang, Dong-Jie Wang, Yangyang Wang, Xiangguo Wang, Runuo Wang, Ruimin Wang, Pengpu Wang, Nuan Wang, Guangyan Wang, Xin-Liang Wang, Minxiu Wang, Ruifang Wang, Hui Wang, Hongda Wang, Xiyan Wang, Jinxia Wang, Xinchen Wang, Haihua Wang, Delong Wang, Yayu Wang, Xue-Hua Wang, Xin-Peng Wang, Changqian Wang, Bei Wang, Ya-Han Wang, Chih-Liang Wang, P N Wang, Xiaoqian Wang, Xianshi Wang, Zhiruo Wang, Xueding Wang, Renxiao Wang, Yi-Ming Wang, Tianqi Wang, Ledan Wang, Rongyun Wang, Gan Wang, Qinqin Wang, Yuxiang Wang, Feimiao Wang, Mengyuan Wang, Chaofan Wang, Linshuang Wang, Yanhui Wang, Zhenglong Wang, Zongkui Wang, Zhenwei Wang, Xiyue Wang, Yi Fan Wang, Xiao-Ai Wang, Po-Jen Wang, Xinyang Wang, Linying Wang, Fa-Kai Wang, Yimeng Wang, Dong-Mei Wang, Anli Wang, Hui-Li Wang, Jianqing Wang, Honglun Wang, Wei-Feng Wang, Kaihao Wang, Jialing Wang, Shuren Wang, Cui-Fang Wang, Wenqi Wang, Peilin Wang, Wen-Fei Wang, Guang-Rui Wang, T Wang, Weiqing Wang, Ciyang Wang, Biao Wang, Kaihe Wang, Jieh-Neng Wang, Tony Wang, Yuehu Wang, Zhicheng Wang, Tongtong Wang, Zi Xuan Wang, Yingtai Wang, Xin-Xin Wang, Chu Wang, Tianhao Wang, Shukui Wang, Ching C Wang, Yulin Wang, Chunyang Wang, Yeqi Wang, Yinbo Wang, Kongyan Wang, Weiling Wang, Linxuan Wang, Shengya Wang, Yaqi Wang, Huating Wang, Aiting Wang, Ya Xing Wang, Daoping Wang, Shasha Wang, Wei-Lien Wang, Quanli Wang, Yanru Wang, L M Wang, Bijue Wang, H Wang, Jipeng Wang, Xiaoxia Wang, Shuu-Jiun Wang, Baitao Wang, Haimeng Wang, Chung-Hsing Wang, Weining Wang, M Y Wang, Wenwen Wang, Zhongsu Wang, Xiaochen Wang, Ligang Wang, Shaohsu Wang, Bing Qing Wang, Jiangbin Wang, Yajun Wang, Chunting Wang, Hemei Wang, En-hua Wang, H-Y Wang, Zixi Wang, Wenjing Wang, Haikun Wang, Ruxin Wang, Jianru Wang, Yongqiang Wang, Ouchen Wang, Jianyu Wang, Shen Wang, Yixi Wang, Zhi-Hong Wang, Li Dong Wang, Zhou-Ping Wang, Wen-Yong Wang, Meng-Lan Wang, Xiaojie Wang, Leying Wang, Yi-Zhen Wang, Y Y Wang, Jianlin Wang, Guoqing Wang, Jiani Wang, Guan-song Wang, You Wang, Xiangding Wang, Ke Wang, Wendong Wang, Yue Wang, Zhe Wang, K Wang, Zhuo Wang, Su'e Wang, Cangyu Wang, Erfei Wang, Xiaoming Wang, Aijun Wang, Xiaoye Wang, Jun-Sheng Wang, Wenxiang Wang, Yanjun Wang, Qiangqiang Wang, Yachun Wang, Haitao Wang, Tiancheng Wang, Gangyang Wang, Jianmin Wang, Jiabo Wang, Yijing Wang, Mengzhi Wang, Yinuo Wang, Zhou Wang, Guiying Wang, Xuezheng Wang, Shan Wang, Aoli Wang, Fuqiang Wang, Yawei Wang, Xianxing Wang, Ya-Long Wang, Yuyang Wang, Dong Hao Wang, Y-S Wang, Zelin Wang, Liqun Wang, Cunyi Wang, Qian-Zhu Wang, Yinan Wang, Panfeng Wang, Guangwen Wang, J Q Wang, Guang Wang, Yu-Ping Wang, John Wang, Jiaping Wang, Zhisheng Wang, Xuan-Ren Wang, Xiaowu Wang, Zhengyu Wang, Baowei Wang, Zhijun Wang, Zhong-Hao Wang, Fengzhong Wang, Jin-Da Wang, Zhaoqing Wang, Yuanbo Wang, Haixin Wang, Yaping Wang, Lixiu Wang, Mingxia Wang, Neng Wang, Guozheng Wang, Yan-Feng Wang, Huafei Wang, Yuhan Wang, Xingxing Wang, Wenhe Wang, Xing-Huan Wang, Xiansong Wang, Yishan Wang, Ruming Wang, Ya Qi Wang, Yueying Wang, Chunle Wang, Shihua Wang, W Wang, Hengjun Wang, Meihui Wang, Huanyu Wang, Ruinan Wang, Qiwei Wang, Zhong Wang, Shiyao Wang, Jian-Zhi Wang, Ruimeng Wang, Jinxiang Wang, Jinsong Wang, Bin-Xue Wang, Fuwen Wang, Yiou Wang, Shifa Wang, Yin Wang, Yanzhu Wang, Jia Bin Wang, Siyang Wang, Zhanggui Wang, Yueting Wang, Qingyu Wang, Qianqian Wang, Xiu-Lian Wang, Fengling Wang, Chenxi Wang, Cheng An Wang, Yipeng Wang, Weipeng Wang, Zechen Wang, Shuaiqin Wang, Xueqian Wang, Chan Wang, Guohang Wang, Cai-Yun Wang, Jiang Wang, Huei Wang, Yufeng Wang, Heng Wang, Qing-Liang Wang, Chuang Wang, Xiaofang Wang, Hao-Ching Wang, Junying Wang, Jianwei Wang, Jinhai Wang, Hanchao Wang, Penglai Wang, I-Ching Wang, S L Wang, Tianhu Wang, Sheng-Min Wang, Pan-Pan Wang, Duan Wang, Xuqiao Wang, Minghuan Wang, Wei-Wei Wang, Xiaojian Wang, Shuping Wang, Jinfu Wang, Biqi Wang, Zhenguo Wang, Fangyan Wang, Sainan Wang, Peijuan Wang, Pei-Yu Wang, Yuyan Wang, Fuxin Wang, Ji M Wang, Yange Wang, Yali Wang, Wenhui Wang, Leishen Wang, Lichan Wang, Xianna Wang, Wenbin Wang, Kenan Wang, Chih-Yuan Wang, Yanlei Wang, Ju Wang, Yanliang Wang, Keqing Wang, Bangshing Wang, Dayan Wang, Yongsheng Wang, Dinghui Wang, Zheyue Wang, Xinke Wang, Daqing Wang, Yan Ming Wang, He-Ling Wang, Shengyao Wang, Jiwen Wang, Xizhi Wang, Luxiang Wang, Dandan Wang, RongRong Wang, Heng-Cai Wang, Jindan Wang, Xiaoding Wang, Yumeng Wang, Heling Wang, Xiao-Yun Wang, Meiding Wang, Zhilun Wang, Guo-hong Wang, Na Wang, Yanli Wang, Fubing Wang, Feixiang Wang, Zhiyuan Wang, Yi-Cheng Wang, Zhengwei Wang, Wenyuan Wang, Yu-Ying Wang, Jianqin Wang, Sijia Wang, Chuansen Wang, Huawei Wang, Kaiyan Wang, Qingyuan Wang, Yujia Wang, Lian Wang, Junrui Wang, Chao-Yung Wang, Zehao Wang, Ruixue Wang, Minjun Wang, Jin Wang, Xiaoxiao Wang, Jun-Feng Wang, Binquan Wang, Shuxia Wang, Donggen Wang, Deming Wang, Chenggang Wang, Chuduan Wang, Haichuan Wang, Catherine Ruiyi Wang, Hai-Feng Wang, Anthony Z Wang, Guanghui Wang, Jiahao Wang, Xiaosong Wang, Zijue Wang, Wenbo Wang, M-J Wang, Yu Wang, Yingping Wang, Zhengbing Wang, G Q Wang, Mengjing Wang, Zhendong Wang, Kailu Wang, Jinfeng Wang, Zhiguo Wang, Yusha Wang, Jianmei Wang, Kun Wang, Lihong Wang, Haoxin Wang, Haowei Wang, Ziqing Wang, Aihua Wang, Yuanyong Wang, Sanwang Wang, Doudou Wang, Hao-Yu Wang, Peirong Wang, Wenting Wang, Yibing Wang, He Wang, Jia-Peng Wang, Shixin Wang, En-bo Wang, Dong-Dong Wang, Hualing Wang, Hongyan Wang, Shaoying Wang, Yingjie Wang, Tianqing Wang, Guo-Hua Wang, Yongfei Wang, Lijing Wang, Hongli Wang, Zixian Wang, Niansong Wang, Liangxu Wang, Xinrong Wang, X-T Wang, Zhenning Wang, Dake Wang, Yu-Ting Wang, Zonggui Wang, Daping Wang, Joy Wang, Chenji Wang, Jingmin Wang, Yuyin Wang, Jin-Cheng Wang, Jiangbo Wang, Huiyang Wang, Chi Chiu Wang, He-Cheng Wang, Zhongjing Wang, Weina Wang, Qiaohong Wang, Qintao Wang, Jenny Y Wang, Zheyi Wang, Robert Yl Wang, Zhaotong Wang, Ya Wang, Fangyu Wang, Haobin Wang, Tianyuan Wang, Xinrui Wang, Zhehao Wang, Yihan Wang, Chuan-Jiang Wang, Jianjun Wang, Yongfeng Wang, Gaofu Wang, Ying-Piao Wang, Jingwei Wang, Mengjiao Wang, Chuyao Wang, Yanping Wang, Xinchun Wang, Shu Wang, Guibin Wang, Hong-Ying Wang, Linping Wang, Yugang Wang, Xinru Wang, Fengyun Wang, Heyong Wang, Ziping Wang, Yuegang Wang, Xiangyu Wang, Haoran Wang, Xiaomei Wang, Fang Wang, Lina Wang, Guowen Wang, Liyun Wang, Qingshui Wang, Baoyun Wang, Li-Juan Wang, Tongsong Wang, Jingyun Wang, Huiguo Wang, Zhibo Wang, Lou-Pin Wang, Renjun Wang, Huiting Wang, Junfeng Wang, Zihan Wang, Linhua Wang, Zhiji Wang, Fubao Wang, Eunice S Wang, Xiaojuan Wang, Yuewei Wang, Shuang Wang, Ruey-Yun Wang, Xiaoling Wang, Weihua Wang, Yanggan Wang, Jia Wang, Chaoqun Wang, Xiao-liang Wang, Manli Wang, Yongkang Wang, Huiwen Wang, Ting Chen Wang, Yixian Wang, Xinlin Wang, Shuya Wang, Bochu Wang, Kehao Wang, Sasa Wang, Mengshi Wang, Qiu-Ling Wang, Chengshuo Wang, Mengru Wang, Yiwei Wang, Xueyun Wang, Yijun Wang, Haomin Wang, Meng C Wang, Mengxiao Wang, Huan-You Wang, Jingheng Wang, Carol A Wang, Benjamin H Wang, Penglong Wang, Pei-Wen Wang, Jian-Long Wang, Wang Wang, Jinhui Wang, Yuanqing Wang, Jacob E Wang, Jian-Xiong Wang, Wenyu Wang, Chengze Wang, Hongmei Wang, Fengqiang Wang, Zijun Wang, Shaochun Wang, Qinwen Wang, Ruicheng Wang, Aixian Wang, Yanling Wang, Lu-Lu Wang, Linyuan Wang, Yeming Wang, Ye Wang, Tian-Yi Wang, Zhichao Wang, Dangfeng Wang, Jiucun Wang, Guo-Liang Wang, Guandi Wang, Zhuo-Xin Wang, Aili Wang, Fengliang Wang, Yingzi Wang, Lirong Wang, Xuekai Wang, Wei-En Wang, Jing-Xian Wang, Hesuiyuan Wang, Yuexin Wang, Suzhen Wang, Luping Wang, Xiuyu Wang, Zicheng Wang, Jiliang Wang, Rikang Wang, Xue Wang, Shudan Wang, Chun Wang, Hongxin Wang, Chenglong Wang, Junxiao Wang, Zhiqing Wang, Shawn Wang, Shunran Wang, Tiantian Wang, Youhua Wang, Xiao-Hui Wang, Qing-Yan Wang, Hanying Wang, Qiuping Wang, Yongzhong Wang, Jin-Xia Wang, Xiao-Tong Wang, Shun Wang, Xiaoqun Wang, Ching-Jen Wang, Xin Wang, Hanbin Wang, Yingwen Wang, Jia Bei Wang, Xiaodan Wang, Wenhan Wang, Jia-Yu Wang, Xiaozhi Wang, Xinkun Wang, Jinhao Wang, KeShan Wang, Shengdong Wang, Jinzhu Wang, Lihui Wang, Bicheng Wang, Chao-Jun Wang, Shaoyi Wang, Yajing Wang, Qing-Bin Wang, Feiyan Wang, Geng Wang, Chen Wang, Zhimin Wang, Cenxuan Wang, Wenjun Wang, Chuan-Chao Wang, Zexin Wang, Shu-Huei Wang, Yonggang Wang, Zhaoyu Wang, Xiaochuan Wang, Chuan-Hui Wang, Junshuang Wang, X F Wang, Li-Ting Wang, Chenxin Wang, Qiao-Ping Wang, Jingqi Wang, Xiongjun Wang, Shuang-Shuang Wang, Xu Wang, Houchun Wang, Yaodong Wang, Lujuan Wang, Jilin Wang, Peichang Wang, Keyun Wang, Ruixuan Wang, Zhangying Wang, Lianyong Wang, Dongyu Wang, Xinghui Wang, Binghan Wang, Guanduo Wang, Xian-e Wang, Guimin Wang, Xiaomeng Wang, Yuh-Hwa Wang, Jinru Wang, Mingyu Wang, Binbin Wang, Chaokui Wang, Linhui Wang, Youzhi Wang, Zhenqian Wang, Jialiang Wang, Sufang Wang, Haiyan Wang, Yankun Wang, Yingbo Wang, Zilong Wang, Xiao-Qun Wang, Lin-Fa Wang, Wenhao Wang, P Wang, Rui-Hong Wang, Xiao-jian WANG, Pei Chang Wang, Zhengkun Wang, Vivian Wang, Ying Wang, Zihuan Wang, Peiwen Wang, Chao Wang, Da-Zhi Wang, He-Tong Wang, Mofei Wang, Zezhou Wang, Liyong Wang, Bruce Wang, Hao-Tian Wang, Jin-Juan Wang, Yucheng Wang, Yong-Gang Wang, Saili Wang, Xiuwen Wang, Ruiquan Wang, Xinmei Wang, Zhezhi Wang, Xiao-Jie Wang, H Y Wang, Li-Dong Wang, Duanyang Wang, Kaiting Wang, Yikang Wang, Yichen Wang, Ting-Chen Wang, Meixia Wang, ZhenXue Wang, Juan Wang, Shouling Wang, Lan Wang, Li Chun Wang, Xingxin Wang, Ruibing Wang, Xue-Ying Wang, Bi-Dar Wang, Jiayang Wang, Suxia Wang, Yumin Wang, Qing Jun Wang, Xinbo Wang, Youli Wang, Yi-Ni Wang, Xinran Wang, Lixian Wang, Kan Wang, Ruiming Wang, Qing-Yuan Wang, Kai-Kun Wang, Yaoxian Wang, Qing-Jin Wang, Junmei Wang, Xin Wei Wang, J P Wang, Xufei Wang, Yuqin Wang, Handong Wang, Li-San Wang, Guoling Wang, Wenrui Wang, Zhongwei Wang, Shi-Han Wang, Ruoxi Wang, Huiping Wang, Mu Wang, Weihong Wang, Minzhou Wang, Yakun Wang, Da-Cheng Wang, Pengjie Wang, Qihua Wang, Ji-Nuo Wang, Deshou Wang, Xiaowen Wang, Yaochun Wang, Qihao Wang, Ruiying Wang, Tiange Wang, Xi Wang, Yindan Wang, Lixin Wang, Zhaofeng Wang, Guixin Wang, Erming Wang, Haoyu Wang, Kexin Wang, Yiqiao Wang, Qi-Qi Wang, Shuiyun Wang, Xi-Rui Wang, Cai-Hong Wang, Zhizheng Wang, Mingxun Wang, Liangli Wang, Theodore Wang, Alexander Wang, Huayang Wang, Yinyin Wang, Shuzhong Wang, Tingting Wang, Jiao Wang, Wenxian Wang, Jianghua Wang, Furong Wang, Shijun Wang, Le Wang, Guihua Wang, Xiaokun Wang, Xia Wang, Jiabei Wang, Guoying Wang, Zeyuan Wang, Jue Wang, Jin-E Wang, Jingru Wang, Chun-Li Wang, Xiaole Wang, Ermao Wang, Lanlan Wang, Ye-Ran Wang, Hao Wang, Xv Wang, Shikang Wang, Yufei Wang, Siyi Wang, Xiujuan Wang, Qinyun Wang, Xiangwei Wang, Jian-Hong Wang, David Q-H Wang, Chunjuan Wang, Weiyan Wang, Jia-Liang Wang, Yanxing Wang, Sheri Wang, Chenwei Wang, Haoping Wang, Sheng-Quan Wang, Xiangrong Wang, Xiao-Yi Wang, Huan Wang, Zhitao Wang, Xinyan Wang, J Wang, Kaixi Wang, Huihua Wang, Renwei Wang, Xiaoliang Wang, Xiao-Lin Wang, Tian-Lu Wang, Jiou Wang, Weiqin Wang, Jiamin Wang, Dennis Wang, Ji-Yao Wang, Pingping Wang, Jinyang Wang, Chen-Cen Wang, Chien-Wei Wang, Daolong Wang, Rong-Tsorng Wang, Yuwei Wang, Guo-Ping Wang, Zhentang Wang, F Wang, Xueju Wang, Saisai Wang, Zhehai Wang, Y B Wang, Xiao Wang, Guobing Wang, Kangmei Wang, Chunguo Wang, Longcai Wang, Haina Wang, Chih-Hsien Wang, Yuli Wang, Ling-Ling Wang, Zhangshun Wang, Xue-Lian Wang, Jianxin Wang, Da-Yan Wang, Xianghua Wang, Peng Wang, Yu Qin Wang, Zhao-Jun Wang, Rui-Rui Wang, Xingyue Wang, Man Wang, Daozhong Wang, Tian-Li Wang, Luhui Wang, Gaopin Wang, Mengze Wang, Jizheng Wang, Hong-Yan Wang, Dongying Wang, Wenkai Wang, Stephani Wang, Dan-Dan Wang, Yicheng Wang, Yusheng Wang, Junwen Wang, Gao Wang, Ruo-Nan Wang, Yifan Wang, Jueqiong Wang, Xuewei Wang, Jianning Wang, Yonglun Wang, Shiwen Wang, Lifang Wang, Fuyan Wang, Jian-Bin Wang, Chonglong Wang, Haiwei Wang, Yike Wang, Chunxia Wang, Kaijuan Wang, Minglei Wang, Jingxiao Wang, Luting Wang, David Wang, Ben Wang, Ji-zheng Wang, Yuncong Wang, Lei P Wang, Tingye Wang, Wenke Wang, Ping Wang, Min Wang, Qiang-Sheng Wang, Xuejing Wang, Zhanju Wang, Xixi Wang, Xiaodong Wang, Chaomeng Wang, Yanong Wang, Xinghao Wang, Jiaming Wang, Siyuan Wang, Jiu Wang, Ruizhi Wang, Qing Mei Wang, Wenyi Wang, Yiqing Wang, Cai Ren Wang, Lianchun Wang, Xing-Ping Wang, Xiaoman Wang, Yanjin Wang, Xueqin Wang, Chenliang Wang, Zhenshan Wang, Junhong Wang, Guiping Wang, Xianrong Wang, Xumeng Wang, Dajia Wang, Huang Wang, Huie Wang, Weiwen Wang, Ruiwen Wang, Qing Wang, Haohao Wang, Bao-Long Wang, P Jeremy Wang, Chengqiang Wang, Suli Wang, Lingyan Wang, Chi Wang, Meng Wang, Luwen Wang, Quan Wang, Yan-Jun Wang, Sen Wang, Ruining Wang, Xiaozhen Wang, Zhiping Wang, Xue-Yao Wang, Yuming Wang, Jingjing Wang, Jiazheng Wang, Yunong Wang, Chongze Wang, Rufang Wang, Qiuning Wang, Tiannan Wang, Liqing Wang, Wencheng Wang, Xuefeng Wang, Yongli Wang, Xinwen Wang, Runzhi Wang, Chaojie Wang, Wentao Wang, Zhifeng Wang, Yanan Wang, Mengqi Wang, Limin Wang, Donglin Wang, Shujin Wang, Chengbin Wang, Qiu-Xia Wang, Zhengxuan Wang, Yancun Wang, Yuhuan Wang, Wei Wang, G-W Wang, Bangmao Wang, Kejia Wang, Jinjin Wang, Qifei Wang, Guobin Wang, Chun-Lin Wang, Jing-Shi Wang, Huajing Wang, Yanlin Wang, Chuansheng Wang, Cailian Wang, Beilan Wang, Luofu Wang, Yangpeng Wang, Jieqi Wang, Weilin Wang, Xiaoxuan Wang, Yangyufan Wang, Xiao-Fei Wang, Chen-Ma Wang, Yun Yong Wang, Shizhi Wang, B Wang, Yuling Wang, Yi-Yi Wang, Fanwen Wang, Aiyun Wang, Jian Wang, Chengyu Wang, Jing-Huan Wang, Ning Wang, Yichuan Wang, L F Wang, Chau-Jong Wang, Xin-Yang Wang, Yunzhe Wang, Xuewen Wang, Sheng-Ping Wang, Bi Wang, Qiuting Wang, Yan-Jiang Wang, Dongshi Wang, Yingna Wang, Jingyue Wang, Hongshan Wang, Chunjiong Wang, Hong-Yang Wang, Yingmei Wang, Danfeng Wang, Zhongyi Wang, Teng Wang, Chih-Hao Wang, Mingchao Wang, Yi-Chuan Wang, Chuning Wang, Shihao Wang, Ming-Wei Wang, Menglu Wang, Zhulun Wang, Wuji Wang, Dao-Xin Wang, Han Wang, Jincheng Wang, Thomas T Y Wang, Qingyun Wang, Guoliang Wang, Jihong Wang, Hong-Qin Wang, G Wang, Hsei-Wei Wang, Linfang Wang, Xiao Ling Wang, Ganyu Wang, Zhengdong Wang, Cuizhe Wang, Hongyu Wang, Tieqiao Wang, Lijuan Wang, Jingchun Wang, Youzhao Wang, Zijian Wang, Ziheng Wang, Xingyu Wang, Shuning Wang, Shaokun Wang, Zhifu Wang, Xinqi Wang, Jinqiu Wang, ZhongXia Wang, Yanyun Wang, Dadong Wang, Xingjie Wang, Yiting Wang, Zhongli Wang, Junyu Wang, Jianding Wang, Meng-Wei Wang, Yingge Wang, Zhenchang Wang, Qun Wang, Jin-Xing Wang, Lijun Wang, Shuqing Wang, Fu-Yan Wang, Sheng-Nan Wang, Feijie Wang, Qiuyan Wang, Ying-Wei Wang, Shitao Wang, Meng-hong Wang, Zhengyang Wang, Jinghong Wang, Zhiying Wang, Pei Wang, Weixue Wang, Shiyue Wang, Xiaohong Wang, Daiwei Wang, Jinghua Wang, S X Wang, Jian-Yong Wang, Zeying Wang, Can Wang, Kehan Wang, Yunzhang Wang, Jinping Wang, Chenchen Wang, Chun-Ting Wang, Yujiao Wang, Xinxin Wang, Ji Wang, Sui Wang, Wenqiang Wang, Yingwei Wang, Shuzhen Wang, Daixi Wang, Yanming Wang, Lin-Yu Wang, Hongyin Wang, Zhongqun Wang, Er-Jin Wang, Yi Wang, Ziyi Wang, Lianghai Wang, Zhendan Wang, Xiao-Ming Wang, Chengyan Wang, Hui Miao Wang, Jingyi Wang, Ranran Wang, Banghui Wang, Huilun Wang, Ai-Ting Wang, Wenxuan Wang, Yuan-Hung Wang, Zixuan Wang, Hailing Wang, Xuan-Ying Wang, Jiqiu Wang, Yalong Wang, Xiaogang Wang, Shu-qiang Wang, Yun-Jin Wang, Zijie Wang, Tianlin Wang, Mingqiang Wang, Lufang Wang, Jin'e Wang, Xiru Wang, Cuili Wang, GuoYou Wang, Zhizhong Wang, Haifei Wang, Guorong Wang, Xinyue Wang, Pei-Juan Wang, Jiangong Wang, Yingte Wang, Huajin Wang, Ruibo Wang, Kejian Wang, Cheng-Cheng Wang, Xusheng Wang, Shu-Na Wang, Panliang Wang, Mingxi Wang, Shenqi Wang, Zifeng Wang, Chaozhan Wang, Xiuyuan Hugh Wang, Yuping Wang, Xujing Wang, Kai Wang, Hongbing Wang, Sheng-Yang Wang, Jianfei Wang, Hang Wang, Jing-Jing Wang, Weizhi Wang, Jixuan Wang, De-He Wang, P L Wang, Ningjian Wang, Chunyi Wang, Isabel Z Wang, Yong Wang, Yiming Wang, Mingzhi Wang, Jiying Wang, Qian-Wen Wang, Shusen Wang, Xiaoting Wang, Baogui Wang, Mingsong Wang, Zixia Wang, Demin Wang, Shiyuan Wang, Qiuli Wang, C Wang, Dongliang Wang, Weixiao Wang, Yinsheng Wang, Chunmei Wang, Huaili Wang, Xuelian Wang, Yongjun Wang, Zhi-Qin Wang, Jiaying Wang, Yulong Wang, Ren Wang, Jingnan Wang, Qishan Wang, Zeneng Wang, Guangsuo Wang, Chijia Wang, Huiqun Wang, Hongcai Wang, Donghao Wang, Xing-Jin Wang, Zongji Wang, Shenao Wang, Jiaqian Wang, Xiaoying Wang, Yilin Wang, Hangzhou Wang, Wenchao Wang, Jieyu Wang, Li-E Wang, Xuezhen Wang, Liuyang Wang, Zhiqian Wang, Fang-Tao Wang, Qiong Wang, Meng-Meng Wang, Youji Wang, Jiafeng Wang, Xiaojing Wang, William Wang, Junmin Wang, Laijian Wang, Xuexiang Wang, Huiyan Wang, T Y Wang, Zhaofu Wang, Wen-mei Wang, Yalin Wang, Xinshuai Wang, Daqi Wang, Zhen Wang, Shi-Cheng Wang, Anni Wang, Chunhong Wang, Hai-Long Wang, Pan Wang, Charles C N Wang, Pengxiang Wang, Xianzong Wang, Xike Wang, Qianliang Wang, Chunyan Wang, Xuan Wang, Xiaofen Wang, Zhi-Jian Wang, Feng-Sheng Wang, Xiangru Wang, R Wang, Yi-Shu Wang, Jia-Lin Wang, Yonghong Wang, Lintao Wang, Pai Wang, Yanfei Wang, Xuanwen Wang, Lei-Lei Wang, Chenxuan Wang, James Wang, Xinhui Wang, Shengqi Wang, Yueshen Wang, Shan-Shan Wang, Dingting Wang, Zhige Wang, Jingfeng Wang, Yongqing Wang, Chenyang Wang, Ziliang Wang, Bao Wang, Xueyan Wang, Liping Wang, Xingde Wang, Weijun Wang, Sibo Wang, Yaoling Wang, Donghong Wang, Chenyu Wang, Justin Wang, Baolong Wang, Yiqi Wang, Fengyong Wang, Lichao Wang, Yachen Wang, Quanren Wang, Shiyu Wang, Boyu Wang, Aimin Wang, Zhenghui Wang, Hengjiao Wang, Xiaoxin X Wang, Weimin Wang, Mutian Wang, Zhuo-Hui Wang, Xingye Wang, Zou Wang, Yu-Wen Wang, Shaoli Wang, Xin-Ming Wang, Weirong Wang, Kangli Wang, Yaoxing Wang, Xuejie Wang, Qifeng Wang, Xiaoxin Wang, Yinghui Wang, Jianzhang Wang, Tom J Wang, Yaqiong Wang, Zongwei Wang, Yun-Hui Wang, Haiyun Wang, Zhiyou Wang, Lijin Wang, Jifei Wang, Haiyong Wang, Xiao-Xia Wang, Shyi-Gang P Wang, Chih-Yang Wang, Zhixin Wang, Jun-Jun Wang, Tianjing Wang, Zhixia Wang, Chuanhai Wang, Zhijie Wang, Silu Wang, Jianguo Wang, Ming-Hsi Wang, Liling Wang, Yanting Wang, Haolong Wang, Xue-Lei Wang, Ru Wang, Qinglin Wang, Christina Wang, Mimi Wang, Menghui Wang, Wenju Wang, Junhua Wang, S S Wang, Fangyong Wang, Lifen Wang, Zhenbin Wang, Yapeng Wang, Shaoshen Wang, B R Wang, Sugai Wang, Hequn Wang, Songlin Wang, Wenjie Wang, Xiang-Dong Wang, Ting-Hua Wang, Mingliang Wang, Chengniu Wang, Guoxiang Wang, E Wang, Xiaochun Wang, Xueting Wang, Ming-Jie Wang, Zhaojing Wang, Dongxu Wang, Yirui Wang, Jiatao Wang, Jing-Min Wang, Shih-Wei Wang, Zhengchun Wang, Chaoxian Wang, Zehua Wang, Qiyu Wang, Shuye Wang, Baojun Wang, Qing Kenneth Wang, Xichun Wang, Jianliu Wang, Junping Wang, Yudong Wang, Mingzhu Wang, Kangning Wang, Wei-Ting Wang, Hongfang Wang, Chengwen Wang, Changduo Wang, Jinkang Wang, Junya Wang, Fengge Wang, Jianping Wang, Chang Wang, Zhifang Wang, Deli Wang, Linghua Wang, Shitian Wang, Lingling Wang, Zhihua Wang, Jun-Ling Wang, Keyi Wang, Lingbing Wang, Peijia Wang, Ruizhe Wang, X O Wang, Wanyi Wang, Ganggang Wang, Pei-Hua Wang, Kaiyue Wang, Xiaojiao Wang, Xun Wang, Shiyang Wang, Ya-Ping Wang, Yirong Wang, Lixing Wang, Danyang Wang, Xiaotang Wang, Taian Wang, Ming Wang, Xiangcheng Wang, Xuemei Wang, Zhixiong Wang, Mengying Wang, Li-Yong Wang, Xinchao Wang, Jianlong Wang, Jinjie Wang, Nan Wang, Weidong Wang, Mei-Gui Wang, L-S Wang, Wuqing Wang, Z Wang, Ya-Zhou Wang, Xincheng Wang, Jing-Wen Wang, Jinyue Wang, Hongyun Wang, Huaizhi Wang, Yan-Zi Wang, Danling Wang, Dongqin Wang, Hongzhuang Wang, Chung-Teng Wang, Yan-Chun Wang, Shi-Xin Wang, Muxuan Wang, Yujie Wang, Yunbing Wang, Yahui Wang, Zhihong Wang, Xiaoshan Wang, Tienju Wang, Chiou-Miin Wang, Yuqian Wang, Shengyuan Wang, Yumei Wang, Ningyuan Wang, Minjie Wang, Zhenda Wang, Qing-Dong Wang, Horng-Dar Wang, Siqi Wang, Kaihong Wang, Hong-Kai Wang, Meiling Wang, Jiaxing Wang, Xueyi Wang, Zhuozhong Wang, Anlai Wang, Julie Wang, Jin-Bao Wang, Keke Wang, Zhang Wang, Yintao Wang, Yong-Bo Wang, Bing Wang, Dalu Wang, Minxian Wang, Zulong Wang, Gao T Wang, Gang Wang, Sophie H Wang, Xinquan Wang, Yi-Ting Wang, Honglian Wang, Ruyue Wang, Jia-Qiang Wang, Seungwon Wang, Shusheng Wang, Yanbin Wang, Chang-Yun Wang, Le-Xin Wang, Juling Wang, Haohui Wang, Chuanyue Wang, Tianqin Wang, Danqing Wang, Keyan Wang, Yeou-Lih Wang, Qinglu Wang, Sun Wang, Rui-Min Wang, Yong-Tang Wang, Xianwei Wang, Lixia Wang, Tong Wang, Xiaonan Wang, Feida Wang, Jiaxuan Wang, Mingrui Wang, Zixiang Wang, Y Z Wang, Yuliang Wang, Ming-Chih Wang, J J Wang, Huina Wang, Jingang Wang, Jinyun Wang, Min-sheng Wang, Wanyao Wang, Ziqiu Wang, Guo-Quan Wang, Xueping Wang, Qixue Wang, Hechuan Wang, Shang Wang, Chaohan Wang, M H Wang, L Z Wang, Jianhui Wang, Xifeng Wang, Xiaorong Wang, Yinong Wang, Zhixiu Wang, Jiaxi Wang, Jiahui Wang, Xiaofei Wang, Feifei Wang, Kesheng Wang, Rong-Chun Wang, Zhi-Xin Wang, Chaoyu Wang, Yongkuan Wang, Zuoyan Wang, Hsueh-Chun Wang, Xixiang Wang, Guanrou Wang, Songsong Wang, Hongyuan Wang, Yubing Wang, Xuliang Wang, Wen-Ying Wang, Xinglei Wang, Dao-Wen Wang, Yun Wang, Ze Wang, Jiyan Wang, Zai Wang, Guan Wang, Chih-Chun Wang, Yiqin Wang, X S Wang, Hongzhan Wang, Exing Wang, Shu-Jin Wang, Shangyu Wang, Shouzhi Wang, Yunduan Wang, Jiyong Wang, Dongdong Wang, Qingzhong Wang, Zi-Qi Wang, Renyuan Wang, Siyu Wang, Donghui Wang, Ming-Yuan Wang, Juxiang Wang, Muxiao Wang, Fu Wang, Fei Wang, Qiuyu Wang, Ertao Wang, Zhi Xiao Wang, Zunxian Wang, Hui-Nan Wang, Rongping Wang, Won-Jing Wang, Leiming Wang, Pu Wang, Shen-Nien Wang, Xiaona Wang, Meng-Ying Wang, Wen-Jie Wang, Jiaxin Wang, RuNan Wang, Jiemei Wang, Ningli Wang, Zhong-Hui Wang, Hong Wang, Hui-Yu Wang, Ziqian Wang, Xinzhou Wang, Zhoufeng Wang, Weiguang Wang, Zusen Wang, Jiajia Wang, Bin Wang, Shu-Xia Wang, Yu'e Wang, Laidi Wang, Xiao-Li Wang, Lu Wang, Zhugang Wang, Maojie Wang, Ganglin Wang, Xinyu Wang, Junlin Wang, Dong Wang, Yao Wang, Ya-Jie Wang, Zhiwu Wang, DongWei Wang, Hongdan Wang, Yanxia Wang, Maiqiu Wang, Guansong Wang, Qingtong Wang, Yingcheng Wang, Wenjuan Wang, Liying Wang, Xiaolong Wang, Weihao Wang, Qiushi Wang, Yingfei Wang, Haoyang Wang, Li-Li Wang, Yanbing Wang, Yingchun Wang, Guangming Wang, Kaiyuan Wang, Shiqi Wang, Qi-En Wang, Song Wang, Jing-Hao Wang, Lynn Yuning Wang, Zekun Wang, Rui-Ping Wang, Yining E Wang, Yuzhou Wang, Liu Wang, Maochun Wang, Cindy Wang, Qian-Liang Wang, Duo-Ping Wang, Linlin Wang, Taishu Wang, Xiang Wang, Qirui Wang, Baoming Wang, Liting Wang, Jiapan Wang, Lingda Wang, Xietong Wang, Jia-Mei Wang, Liwei Wang, Shaozheng Wang, Q Wang, Timothy C Wang, Mengyue Wang, Xing Wang, Yahong Wang, Yuyong Wang, Yujiong Wang, Guangliang Wang, Ya-Qin Wang, Yezhou Wang, Hongjian Wang, Su-Hua Wang, Qian-fei Wang, Meng-Dan Wang, Yuchen Wang, Hongpin Wang, Pengfei Wang, Ge Wang, Meijun Wang, Yan-Ming Wang, Haichao Wang, Tzung-Dau Wang, Runci Wang, Yan-Yi Wang, Cheng-Jie Wang, Chen-Yu Wang, Cong Wang, Yaxuan Wang, Y H Wang, Yongjie Wang, Yuntai Wang, Ranjing Wang, Yiru Wang, Anxiang Wang, Q Z Wang, Shimiao Wang, Guoping Wang, Junke Wang, Xingyun Wang, Zhengyi Wang, Shi-Qi Wang, Yanfeng Wang, Danxin Wang, Chaodong Wang, Zhiqi Wang, Chunyu Wang, Lijia Wang, Chunlong Wang, Haiping Wang, Qingfa Wang, Yu-Fan Wang, Baihan Wang, Chunxue Wang, Liewei Wang, Xinyi Wang, Fu-Zhen Wang, Qing-Mei Wang, Sheng Wang, Yi-Tao Wang, Dawei Wang, Xiaoyu Wang, Ziling Wang, Zhonglin Wang, Rurong Wang, Qingchun Wang, Qiang Wang, Suiyan Wang, Xu-Hong Wang, Jie Jin Wang, Chenyao Wang, Fei-Yan Wang, Shi Wang, Zhiyong Wang, Jieda Wang, Xiaoqi Wang, Linshu Wang, Ruxuan Wang, Qian Wang, Qianxu Wang, Fangjie Wang, Zhaoxia Wang, Jeremy R Wang, Mingmei Wang, Jingkang Wang, Jen-Chun Wang, Changyuan Wang, Chenglin Wang, Meng-Ru Wang, Tianpeng Wang, Zhongfang Wang, Xuedong Wang, Zhuoying Wang, Bingyu Wang, Xuelai Wang, Weilong Wang, Mengge Wang, Qin Wang, Da-Li Wang, Xuanyi Wang, Hongjuan Wang, Zhi-Hua Wang, Hong-Wei Wang, Yulai Wang, Gongming Wang, Yongni Wang, Mengya Wang, Yadong Wang, Chenghao Wang, Hongbo Wang, Kaiming Wang, Haonan Wang, Guanyun Wang, Yilu Wang, Quanxi Wang, Weiyuan Wang, Xiujun Wang, Liang-Yan Wang, Jianshe Wang, Yingxiong Wang, Cunchuan Wang, Jing-Zhai Wang, Yuelong Wang, Yuqi Wang, Xiaorui Wang, Qianjin Wang, Huijun Wang, Xiaobo Wang, Guoqian Wang, Luhong Wang, Kaining Wang, Chaohui Wang, Yanhong Wang, J-Y Wang, Qi-Bing Wang, Xiaohu Wang, Jiayan Wang, Cui-Shan Wang, Lulu Wang, Yong-Jie Wang, Shixuan Wang, Yuanyuan Wang, Jianying Wang, Haizhen Wang, Shuiliang Wang, Qianbao Wang, Jung-Pan Wang, Rixiang Wang, A Wang, Hanbing Wang, Caiqin Wang, Peigeng Wang, Yuan Wang, Yuzhuo Wang, Yubo Wang, Xianding Wang, Qiaoqi Wang, Cuiling Wang, Ai-Ling Wang, Hailong Wang, Yihao Wang, Lan-Wan Wang, Haihe Wang, S Wang, Sha Wang, Xiaoli Wang, David Q H Wang, Jianfang Wang, Yuting Wang, Jinhuan Wang, Kaixu Wang, Hongwei Wang, Yi-Wen Wang, Yizhe Wang, Shengyu Wang, Yanmei Wang, Huimin Wang, Youjie Wang, Kunhua Wang, Chongjian Wang, Ziyun Wang, Tianhui Wang, Huiying Wang, Yue-Nan Wang, Peiyin Wang, Hongbin Wang, Hong Yi Wang, Xinjun Wang, Yian Wang, Liyi Wang, Yunce Wang, Yi-Xuan Wang, Yitao Wang, Jiali Wang, Junqin Wang, Yuebing Wang, Yiping Wang, Yunpeng Wang, Yuxing Wang, Shuqi Wang, Ziyu Wang, Hongjie Wang, Xiaoyan Wang, Lianshui Wang, Xiaolu Wang, Wenya Wang, Fan Wang, Jinhua Wang, Sidan Wang, Lixiang Wang, Y L Wang, Xue-Rui Wang, Kai-Wen Wang, Zhongyu Wang, Xiaoyang Wang, Hongyang Wang, Rencheng Wang, Yinxiong Wang, Yuanli Wang, Zhuqing Wang, Y-H Wang, Yuhui Wang, Xitian Wang, Weizhen Wang, Qi Wang, Qiyuan Wang, Changlong Wang, Yatao Wang, Tengfei Wang, Yehan Wang
articles
Yutong Jin, Zhengyang Li, Lin Qi +7 more · 2024 · Human & experimental toxicology · SAGE Publications · added 2026-04-24
The objective of this study was to investigate the potential of salidroside (SAL) (a major active compound in The expression of HIF-1 SAL enhanced the expression of HIF-1 SAL promotes osteoclast proli Show more
The objective of this study was to investigate the potential of salidroside (SAL) (a major active compound in The expression of HIF-1 SAL enhanced the expression of HIF-1 SAL promotes osteoclast proliferation, differentiation and bone resorption through HIF-1 Show less
no PDF DOI: 10.1177/09603271241269028
ANGPTL4
Guangming Mao, Wenhao Xu, Lingli Wan +8 more · 2024 · Frontiers in immunology · Frontiers · added 2026-04-24
Type 2 Diabetes Mellitus (T2D) and Osteoarthritis (OA) are both prevalent diseases that significantly impact the health of patients. Increasing evidence suggests that there is a big correlation betwee Show more
Type 2 Diabetes Mellitus (T2D) and Osteoarthritis (OA) are both prevalent diseases that significantly impact the health of patients. Increasing evidence suggests that there is a big correlation between T2D and OA, but the molecular mechanisms remain elusive. The aims of this study are to investigate the shared biomarkers and potential molecular mechanisms in T2D combined with OA. T2D and OA-related differentially expressed genes (DEGs) were identified via bioinformatic analysis on Gene Expression Omnibus (GEO) datasets GSE26168 and GSE114007 respectively. Subsequently, extensive target prediction and network analysis were finished with Gene Ontology (GO), protein-protein interaction (PPI), and pathway enrichment with DEGs. The transcription factors (TFs) and miRNAs coupled in co-expressed DEGs involved in T2D and OA were predicted as well. The key genes expressed both in the clinical tissues of T2D and OA were detected with western blot and qRT-PCR assay. Finally, the most promising candidate compounds were predicted with the Drug-Gene Interaction Database (DGIdb) and molecular docking. In this study, 209 shared DEGs between T2D and OA were identified. Functional analysis disclosed that these DEGs are predominantly related to ossification, regulation of leukocyte migration, extracellular matrix (ECM) structural constituents, PI3K/AKT, and Wnt signaling pathways. Further analysis via Protein-Protein Interaction (PPI) analysis and validation with external datasets emphasized MMP9 and ANGPTL4 as crucial genes in both T2D and OA. Our findings were validated through qRT-PCR and Western blot analyses, which indicated high expression levels of these pivotal genes in T2D, OA, and T2D combined with OA cases. Additionally, the analysis of Transcription Factors (TFs)-miRNA interactions identified 7 TFs and one miRNA that jointly regulate these important genes. The Receiver Operating characteristic (ROC) analysis demonstrated the significant diagnostic potential of MMP9 and ANGPTL4.Moreover, we identified raloxifene, ezetimibe, and S-3304 as promising agents for patients with both T2D and OA. This study uncovers the shared signaling pathways, biomarkers, potential therapeutics, and diagnostic models for individuals suffering from both T2D and OA. These findings not only present novel perspectives on the complex interplay between T2D and OA but also hold significant promise for improving the clinical management and prognosis of patients with this concurrent condition. Show less
📄 PDF DOI: 10.3389/fimmu.2024.1353915
ANGPTL4
Xiaomin Liu, Yiliang Zhang, Bingqian Han +10 more · 2024 · JCI insight · added 2026-04-24
Fuel substrate switching between carbohydrates and fat is essential for maintaining metabolic homeostasis. During aerobic exercise, the predominant energy source gradually shifts from carbohydrates to Show more
Fuel substrate switching between carbohydrates and fat is essential for maintaining metabolic homeostasis. During aerobic exercise, the predominant energy source gradually shifts from carbohydrates to fat. While it is well known that exercise mobilizes fat storage from adipose tissues, it remains largely obscure how circulating lipids are distributed tissue-specifically according to distinct energy requirements. Here, we demonstrate that aerobic exercise is linked to nutrient availability to regulate tissue-specific activities of lipoprotein lipase (LPL), the key enzyme catabolizing circulating triglyceride (TG) for tissue uptake, through the differential actions of angiopoietin-like (ANGPTL) proteins. Exercise reduced the tissue binding of ANGPTL3 protein, increasing LPL activity and TG uptake in the heart and skeletal muscle in the postprandial state specifically. Mechanistically, exercise suppressed insulin secretion, attenuating hepatic Angptl8 transcription through the PI3K/mTOR/CEBPα pathway, which is imperative for the tissue binding of its partner ANGPTL3. Constitutive expression of ANGPTL8 hampered lipid utilization and resulted in cardiac dysfunction in response to exercise. Conversely, exercise promoted the expression of ANGPTL4 in white adipose tissues, overriding the regulatory actions of ANGPTL8/ANGPTL3 in suppressing adipose LPL activity, thereby diverting circulating TG away from storage. Collectively, our findings show an overlooked bifurcated ANGPTL-LPL network that orchestrates fuel switching in response to aerobic exercise. Show less
📄 PDF DOI: 10.1172/jci.insight.181553
ANGPTL4
Rui Xie, Nan You, Wan-Yan Chen +21 more · 2024 · Research (Washington, D.C.) · added 2026-04-24
📄 PDF DOI: 10.34133/research.0409
ANGPTL4
Jian Xiao, Shuqing Cao, Jiawei Wang +8 more · 2024 · Cancer communications (London, England) · Wiley · added 2026-04-24
Lymph node metastasis (LNM) is the primary mode of metastasis in gastric cancer (GC). However, the precise mechanisms underlying this process remain elusive. Tumor cells necessitate lipid metabolic re Show more
Lymph node metastasis (LNM) is the primary mode of metastasis in gastric cancer (GC). However, the precise mechanisms underlying this process remain elusive. Tumor cells necessitate lipid metabolic reprogramming to facilitate metastasis, yet the role of lipoprotein lipase (LPL), a pivotal enzyme involved in exogenous lipid uptake, remains uncertain in tumor metastasis. Therefore, the aim of this study was to investigate the presence of lipid metabolic reprogramming during LNM of GC as well as the role of LPL in this process. Intracellular lipid levels were quantified using oil red O staining, BODIPY 493/503 staining, and flow cytometry. Lipidomics analysis was employed to identify alterations in intracellular lipid composition following LPL knockdown. Protein expression levels were assessed through immunohistochemistry, Western blotting, and enzyme-linked immunosorbent assays. The mouse popliteal LNM model was utilized to investigate differences in LNM. Immunoprecipitation and mass spectrometry were employed to examine protein associations. In vitro phosphorylation assays and Phos-tag sodium dodecyl-sulfate polyacrylamide gel electrophoresis assays were conducted to detect angiopoietin-like protein 4 (ANGPTL4) phosphorylation. We identified that an elevated intracellular lipid level represents a crucial characteristic of node-positive (N+) GC and further demonstrated that a high-fat diet can expedite LNM. LPL was found to be significantly overexpressed in N+ GC tissues and shown to facilitate LNM by mediating dietary lipid uptake within GC cells. Leptin, an obesity-related hormone, intercepted the effect exerted by ANGPTL4/Furin on LPL cleavage. Circulating leptin binding to the leptin receptor could induce the activation of inositol-requiring enzyme-1 (IRE1) kinase, leading to the phosphorylation of ANGPTL4 at the serine 30 residue and subsequently reducing its binding affinity with LPL. Moreover, our research revealed that LPL disrupted lipid homeostasis by elevating intracellular levels of arachidonic acid, which then triggered the cyclooxygenase-2/prostaglandin E2 (PGE2) pathway, thereby promoting tumor lymphangiogenesis. Leptin-induced phosphorylation of ANGPTL4 facilitates LPL-mediated lipid uptake and consequently stimulates the production of PGE2, ultimately facilitating LNM in GC. Show less
📄 PDF DOI: 10.1002/cac2.12583
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Meng-Jie Zhang, Ting-Ting Xue, Xiao-Ya Fei +9 more · 2024 · Clinical and experimental immunology · Oxford University Press · added 2026-04-24
Psoriasis is a chronic immune-mediated recurrent skin disease causing systemic damage. Increased angiogenesis has been reported to participate in the progression of psoriasis. However, angiogenesis-re Show more
Psoriasis is a chronic immune-mediated recurrent skin disease causing systemic damage. Increased angiogenesis has been reported to participate in the progression of psoriasis. However, angiogenesis-related genes (ARGs) in psoriasis have not been systematically elucidated. Therefore, we aim to identify potential biomarkers and subtypes using two algorithmsr. Transcriptome sequencing data of patients with psoriasis were obtained, in which differentially expressed genes were assessed by principal component analysis. A diagnostic model was developed using random forest algorithm and validated by receiver operating characteristic (ROC) curves. Subsequently, we performed consensus clustering to calculate angiogenesis-associated molecular subtypes of psoriasis. Additionally, a correlation analysis was conducted between ARGs and immune cell infiltration. Finally, validation of potential ARG genes was performed by quantitative real-time PCR (qRT-PCR). We identified 29 differentially expressed ARGs, including 13 increased and 16 decreased. Ten ARGs, CXCL8, ANG, EGF, HTATIP2, ANGPTL4, TNFSF12, RHOB, PML, FOXO4, and EMCN were subsequently sifted by the diagnostic model based on a random forest algorithm. Analysis of the ROC curve (area under the curve [AUC] = 1.0) indicated high diagnostic performance in internal validation. The correlation analysis suggested that CXCL8 has a high positive correlation with neutrophil (R =0.8, P < 0.0001) and interleukins pathway (R = 0.79, P < 0.0001). Furthermore, two ARG-mediated subtypes were obtained, indicating potential heterogeneity. Finally, the qRT-PCR demonstrated that the mRNA expression levels of CXCL8 and ANGPTL4 were elevated in psoriasis patients, with a reduced expression of EMCN observed. The current paper indicated potential ARG-related biomarkers of psoriasis, including CXCL8, ANGPTL4, and EMCN, with two molecular subtypes. Show less
no PDF DOI: 10.1093/cei/uxae052
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Jingying Zhao, Xuehai Ge, Tao Li +10 more · 2024 · Poultry science · Elsevier · added 2026-04-24
The quality and flavor of chicken are affected by muscle metabolites and related regulatory genes, and the molecular regulation mechanism of meat quality is different among different breeds of chicken Show more
The quality and flavor of chicken are affected by muscle metabolites and related regulatory genes, and the molecular regulation mechanism of meat quality is different among different breeds of chicken. In this study, 40 one-day-old Daweishan mini chicken (DM) and Cobb broiler (CB) were selected from each group, with 4 replicates and 10 chickens in each replicate. The chickens were reared until 90 d of age under the same management conditions. Then, metabolomics and transcriptomics data of 90-day-old DM (n = 4) and CB (n = 4) were integrated to analyze metabolites affecting breast muscle quality and flavor, and to explore the important genes regulating meat quality and flavor related metabolites. The results showed that a total of 38 significantly different metabolites (SDMs) and 420 differentially expressed genes (DEGs) were detected in the breast muscle of the 2 breeds. Amino acid and lipid metabolism may be the cause of meat quality and flavor difference between DM and CB chickens, involving metabolites such as L-methionine, betaine, N6, N6, N6-Trimethyl-L-lysine, L-anserine, glutathione, glutathione disulfide, L-threonine, N-Acetyl-L-aspartic acid, succinate, choline, DOPC, SOPC, alpha-linolenic acid, L-palmitoylcarnitine, etc. Important regulatory genes with high correlation with flavor amino acids (GATM, GSTO1) and lipids (PPARG, LPL, PLIN1, SCD, ANGPTL4, FABP7, GK, B4GALT6, UGT8, PLPP4) were identified by correlation analysis, and the gene-metabolite interaction network of breast muscle mass and flavor formation in DM chicken was constructed. This study showed that there were significant differences in breast metabolites between DM and CB chickens, mainly in amino acid and lipid metabolites. These 2 kinds of substances may be the main reasons for the difference in breast muscle quality and flavor between the 2 breeds. In general, this study could provide a theoretical basis for further research on the molecular regulatory mechanism of the formation of breast muscle quality and flavor differences between DM and CB chickens, and provide a reference for the development, utilization and genetic breeding of high-quality meat chicken breeds. Show less
📄 PDF DOI: 10.1016/j.psj.2024.103920
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Jeffrey Wang, Maaike Kockx, Magdalena Bolek +4 more · 2024 · Journal of lipid research · Elsevier · added 2026-04-24
Patients with schizophrenia show a disproportionally increased risk of cardiovascular disease. Hypertriglyceridemia is prevalent in this population; however, how this relates to levels of remnant chol Show more
Patients with schizophrenia show a disproportionally increased risk of cardiovascular disease. Hypertriglyceridemia is prevalent in this population; however, how this relates to levels of remnant cholesterol, triglyceride (TG)-rich lipoprotein (TRL) particle size and composition, TG turnover, and apolipoprotein (apo) and angiopoietin-like protein (ANGPTL) concentrations is unknown. Fasting levels of cholesterol (total [TC], LDL-C, HDL-C, non-HDL-C and remnant cholesterol) and TG were determined in 110 patients diagnosed with schizophrenia, and 46 healthy controls. TRL particle size, concentration and composition, and β-hydroxybutyrate (TG turnover marker) were assessed by NMR. Levels of apoCII, apoCIII, apoE, ANGPTL3, ANGPTL4, and ANGPTL8 were measured by ELISA, and apoCII, apoCIII and apoE were further evaluated in HDL and non-HDL fractions. Patients with schizophrenia had significantly elevated TG, TG:apoB ratio, non-HDL-C, remnant cholesterol, non-HDL-apoCII and non-HDL-apoCIII, and HDL-apoE (all P < 0.05), lower HDL-C and apoA-I (all P < 0.001), and comparable apoB, TC, TC:apoB ratio, LDL-C, β-hydroxybutyrate, ANGPTL3, ANGPTL4 and ANGPTL8 to healthy controls. Patients had a 12.0- and 2.5-fold increase in the concentration of large and medium TRL particles respectively, but similar cholesterol:TG ratio within each particle. Plasma TG, remnant cholesterol, and large and medium TRL particle concentrations correlated strongly with apoCII, apoCIII, and apoE in the non-HDL fraction, and with apoCIII and apoE in the HDL fraction in patients with schizophrenia. Differences in TG, HDL-C, TRL particle concentrations, apoCIII, and apoE persisted after adjustment for conventional risk factors. These results are consistent with impaired TRL lipolysis and clearance in patients with schizophrenia which may be responsive to targeting apoCIII. Show less
📄 PDF DOI: 10.1016/j.jlr.2024.100577
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Chun-Heng Kuo, Shu-Huei Wang, Hsien-Chia Juan +5 more · 2024 · BioFactors (Oxford, England) · Wiley · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is a secretory glycoprotein involved in regulating glucose homeostasis in non-pregnant subjects. However, its role in glucose metabolism during pregnancy and the Show more
Angiopoietin-like protein 4 (ANGPTL4) is a secretory glycoprotein involved in regulating glucose homeostasis in non-pregnant subjects. However, its role in glucose metabolism during pregnancy and the pathophysiology of gestational diabetes mellitus (GDM) remains elusive. Thus, this study aimed to clarify the relationship between ANGPTL4 and GDM and investigate the pathophysiology of placental ANGPTL4 in glucose metabolism. We investigated this issue using blood and placenta samples in 957 pregnant women, the human 3A-sub-E trophoblast cell line, and the L6 skeletal muscle cell line. We found that ANGPTL4 expression in the placenta was higher in obese pregnant women than in lean controls. Palmitic acid significantly induced ANGPTL4 expression in trophoblast cells in a dose-response manner. ANGPTL4 overexpression in trophoblast cells resulted in endoplasmic reticulum (ER) stress, which stimulated the expression and secretion of growth hormone-variant (GH2) but not human placental lactogen. In L6 skeletal muscle cells, soluble ANGPTL4 suppressed insulin-mediated glucose uptake through the epidermal growth factor receptor (EGFR)/extracellular signal-regulated kinases 1/2 (ERK 1/2) pathways. In pregnant women, plasma ANGPTL4 concentrations in the first trimester predicted the incidence of GDM and were positively associated with BMI, plasma triglyceride, and plasma GH2 in the first trimester. However, they were negatively associated with insulin sensitivity index ISI Show less
no PDF DOI: 10.1002/biof.2076
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Peigeng Wang, Zhencong Li, Dongping Ye · 2024 · BMC musculoskeletal disorders · BioMed Central · added 2026-04-24
Increasing studies have shown degeneration of nucleus pulposus cells (NPCs) as an critical part of the progression of intervertebral disc degeneration (IVDD). However, there are relatively few studies Show more
Increasing studies have shown degeneration of nucleus pulposus cells (NPCs) as an critical part of the progression of intervertebral disc degeneration (IVDD). However, there are relatively few studies on single-cell transcriptome contrasts in human degenerated NPCs. Moreover, differences in Wnt/Ca We performed bioinformatics analysis using our previously published findings to construct single cell expression profiles of normal and degenerated nucleus pulposus. Then, in-depth differential analysis was used to characterize the expression of Wnt/Ca The obtained cell data were clustered into five different chondrocytes clusters, which chondrocyte 4 and chondrocyte 5 mainly accounted for a high proportion in degenerated nucleus pulposus tissues, but rarely in normal nucleus pulposus tissues. Genes associated within the Wnt/Ca Single-cell RNA sequencing revealed differential expression of Wnt/Ca Show less
📄 PDF DOI: 10.1186/s12891-024-07368-3
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Chaojun Zhu, Lan Teng, Yihong Lai +14 more · 2024 · Cellular and molecular life sciences : CMLS · Springer · added 2026-04-24
Peritoneal metastasis, the third most common metastasis in colorectal cancer (CRC), has a poor prognosis for the rapid progression and limited therapeutic strategy. However, the molecular characterist Show more
Peritoneal metastasis, the third most common metastasis in colorectal cancer (CRC), has a poor prognosis for the rapid progression and limited therapeutic strategy. However, the molecular characteristics and pathogenesis of CRC peritoneal metastasis are poorly understood. Here, we aimed to elucidate the action and mechanism of adipose-derived stem cells (ADSCs), a prominent component of the peritoneal microenvironment, in CRC peritoneal metastasis formation. Database analysis indicated that ADSCs infiltration was increased in CRC peritoneal metastases, and high expression levels of ADSCs marker genes predicted a poor prognosis. Then we investigated the effect of ADSCs on CRC cells in vitro and in vivo. The results revealed that CRC cells co-cultured with ADSCs exhibited stronger metastatic property and anoikis resistance, and ADSCs boosted the intraperitoneal seeding of CRC cells. Furthermore, RNA sequencing was carried out to identify the key target gene, angiopoietin like 4 (ANGPTL4), which was upregulated in CRC specimens, especially in peritoneal metastases. Mechanistically, TGF-β1 secreted by ADSCs activated SMAD3 in CRC cells, and chromatin immunoprecipitation assay showed that SMAD3 facilitated ANGPTL4 transcription by directly binding to ANGPTL4 promoter. The ANGPTL4 upregulation was essential for ADSCs to promote glycolysis and anoikis resistance in CRC. Importantly, simultaneously targeting TGF-β signaling and ANGPTL4 efficiently reduced intraperitoneal seeding in vivo. In conclusion, this study indicates that tumor-infiltrating ADSCs promote glycolysis and anoikis resistance in CRC cells and ultimately facilitate peritoneal metastasis via the TGF-β1/SMAD3/ANGPTL4 axis. The dual-targeting of TGF-β signaling and ANGPTL4 may be a feasible therapeutic strategy for CRC peritoneal metastasis. Show less
📄 PDF DOI: 10.1007/s00018-024-05215-1
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Xiaojun Wang, Hung-Chen Chang, Xuchao Gu +8 more · 2024 · Mechanisms of ageing and development · Elsevier · added 2026-04-24
Renal tubular epithelial cells are vulnerable to stress-induced damage, including excessive lipid accumulation and aging, with ANGPTL4 potentially playing a crucial bridging role between these factors Show more
Renal tubular epithelial cells are vulnerable to stress-induced damage, including excessive lipid accumulation and aging, with ANGPTL4 potentially playing a crucial bridging role between these factors. In this study, RNA-sequencing was used to identify a marked increase in ANGPTL4 expression in kidneys of diet-induced obese and aging mice. Overexpression and knockout of ANGPTL4 in renal tubular epithelial cells (HK-2) was used to investigate the underlying mechanism. Subsequently, ANGPTL4 expression in plasma and kidney tissues of normal young controls and elderly individuals was analyzed using ELISA and immunohistochemical techniques. RNA sequencing results showed that ANGPTL4 expression was significantly upregulated in the kidney tissue of diet-induced obesity and aging mice. In vitro experiments demonstrated that overexpression of ANGPTL4 in HK-2 cells led to increased lipid deposition and senescence. Conversely, the absence of ANGPTL4 appears to alleviate the impact of free fatty acids (FFA) on aging in HK-2 cells. Additionally, aging HK-2 cells exhibited elevated ANGPTL4 expression, and stress response markers associated with cell cycle arrest. Furthermore, our clinical evidence revealed dysregulation of ANGPTL4 expression in serum and kidney tissue samples obtained from elderly individuals compared to young subjects. Our study findings indicate a potential association between ANGPTL4 and age-related metabolic disorders, as well as injury to renal tubular epithelial cells. This suggests that targeting ANGPTL4 could be a viable strategy for the clinical treatment of renal aging. Show less
no PDF DOI: 10.1016/j.mad.2024.111932
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Yang Yang, Xinyu Yang, Shiqi Ren +3 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Colon adenocarcinoma (COAD) is a highly lethal gastrointestinal malignancy. The five-year survival rate of metastatic colorectal cancer remains low, at 14 percent. Numerous publications have suggested Show more
Colon adenocarcinoma (COAD) is a highly lethal gastrointestinal malignancy. The five-year survival rate of metastatic colorectal cancer remains low, at 14 percent. Numerous publications have suggested a role for peroxisome proliferator-activated receptors (PPARs) in malignancy. Recent studies have shown that PPARs, as nuclear transcription factors, may serve as potential targets for the treatment of metabolic syndrome tumors and their associated complications. However, the molecular mechanism has not been thoroughly investigated. Hence, in order to enhance the prediction of personalized medicine for PPAR-associated modulators in malignancy treatment, a timely review becomes essential. Utilizing TCGA-COAD expression profile data and patient overall survival (OS) information, this study systematically conducted investigations to identify and develop Hub stem cell-related diagnostic and prognostic identification models, aiming to enhance the multi-gene markers for COAD. Utilizing the differential expression profiles of stem cell-related genes, an 11-gene (SLC27A4, CPT1C, CPT1B, CPT2, CYP4A11, FABP3, FABP7, AQP7, MMP1, ACOX1, ANGPTL4) diagnostic and prognostic model was developed. This model demonstrated precise diagnostic and prognostic capabilities and holds the potential to characterize the clinicopathologic features of COAD. Univariate and multivariate Cox proportional hazards regression analyses were conducted to ascertain the independent factors influencing OS outcomes in COAD. The results revealed that CPT1B, SLC27A4, and FABP3 were identified as independent risk prognostic factors for OS in COAD, whereas ACOX1 and CPT2 served as independent protective prognostic factors. The hub genes associated with PPARs were identified through the differential expression of contrast agent COAD and normal tissues. Finally, the investigation of variations in immune infiltration and the analysis of relevant biological pathways validate the prognostic significance of the independent post-factors within this molecular model. This research aims to provide references for comprehending the mechanism of post-transcriptional regulation of COAD and molecular therapy. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e27388
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Zhiyu Ma, Nana Wang, Tingting Meng +3 more · 2024 · Journal of biochemical and molecular toxicology · Wiley · added 2026-04-24
Recent studies have shown that epithelial-mesenchymal transition (EMT) plays an important role in paraquat (PQ)-induced tissue fibrosis, which is the main cause of death in patients with PQ poisoning. Show more
Recent studies have shown that epithelial-mesenchymal transition (EMT) plays an important role in paraquat (PQ)-induced tissue fibrosis, which is the main cause of death in patients with PQ poisoning. However, no effective treatment for pulmonary interstitial fibrosis caused by PQ poisoning exists. It is of great significance for us to find new therapeutic targets through bioinformatics in PQ-induced EMT. We conducted transcriptome sequencing to determine the expression profiles of 1210 messenger RNAs (mRNAs), 558 long noncoding RNAs, 28 microRNAs (miRNAs), including 18 known-miRNAs, 10 novel-miRNAs and 154 circular RNAs in the PQ-exposed EMT group mice. Using gene ontology and Kyoto Encyclopaedia of Genes and Genomes analyses, we identified the pathways associated with signal transduction, cancers, endocrine systems and immune systems were involved in PQ-induced EMT. Furthermore, we constructed long noncoding RNA-miRNA-mRNA interrelated networks and found that upregulated genes included Il22ra2, Mdm4, Slc35e2 and Angptl4, and downregulated genes included RGS2, Gabpb2, Acvr1, Prkd3, Sp100, Tlr12, Syt15 and Camk2d. Thirteen new potential competitive endogenous RNA targets were also identified for further treatment of PQ-induced pulmonary tissue fibrosis. Through further study of the pathway and networks, we may identify new molecular targets in PQ-induced pulmonary EMT. Show less
no PDF DOI: 10.1002/jbt.23681
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Sijia Ma, Jia Wang, Zhiwei Cui +4 more · 2024 · Scientific reports · Nature · added 2026-04-24
Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and thei Show more
Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and theirs underlying mechanisms remain to be further elucidated. We intended to identify and validate classifiers of hub HRGs for chemoresistance, diagnosis, prognosis as well as immune microenvironment of OC, and to explore the function of the most crucial HRG in the development of the malignant phenotypes. The RNA expression and clinical data of HRGs were systematically evaluated in OC training group. Univariate and multivariate Cox regression analysis were applied to construct hub HRGs classifiers for prognosis and diagnosis assessment. The relationship between classifiers and chemotherapy response and underlying pathways were detected by GSEA, CellMiner and CIBERSORT algorithm, respectively. OC cells were cultured under hypoxia or transfected with HIF-1α or HIF-2α plasmids, and the transcription levels of TGFBI were assessed by quantitative PCR. TGFBI was knocked down by siRNAs in OC cells, CCK8 and in vitro migration and invasion assays were performed to examine the changes in cell proliferation, motility and metastasis. The difference in TGFBI expression was examined between cisplatin-sensitive and -resistant cells, and the effects of TGFBI interference on cell apoptosis, DNA repair and key signaling molecules of cisplatin-resistant OC cells were explored. A total of 179 candidate HRGs were extracted and enrolled into univariate and multivariate Cox regression analysis. Six hub genes (TGFBI, CDKN1B, AKAP12, GPC1, TGM2 and ANGPTL4) were selected to create a HRGs prognosis classifier and four genes (TGFBI, AKAP12, GPC1 and TGM2) were selected to construct diagnosis classifiers. The HRGs prognosis classifier could precisely distinguish OC patients into high-risk and low-risk groups and estimate their clinical outcomes. Furthermore, the high-risk group had higher percentage of Macrophages M2 and exhibited higher expression of immunecheckpoints such as PD-L2. Additionally, the diagnosis classifiers could accurately distinguish OC from normal samples. TGFBI was further verified as a specific key target and demonstrated that its high expression was closely correlated with poor prognosis and chemoresistance of OC. Hypoxia upregulated the expression level of TGFBI. The hypoxia-induced factor HIF-2α but not HIF-1α could directly bind to the promoter region of TGFBI, and facilitate its transcription level. TGFBI was upregulated in cisplatin-sensitive and resistant ovarian cancer cells in a cisplatin time-dependent manner. TGFBI interference downregulated DNA repair-related markers (p-p95/NBS1, RAD51, p-DNA-PKcs, DNA Ligase IV and Artemis), apoptosis-related marker (BCL2) and PI3K/Akt pathway-related markers (PI3K-p110 and p-Akt) in cisplatin-resistant OC cells. In summary, the HRGs prognosis risk classifier could be served as a predictor for OC prognosis and efficacy evaluation. TGFBI, upregulated by HIF-2α as an HRG, promoted OC chemoresistance through activating PI3K/Akt pathway to reduce apoptosis and enhance DNA damage repair pathway. Show less
📄 PDF DOI: 10.1038/s41598-024-53854-y
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Jie Wu, Yuting Zhang, Guoxing You +8 more · 2024 · Aging · Impact Journals · added 2026-04-24
Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasi Show more
Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasis. The aim of this study was to develop an anoikis-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for LUAD. Through differentially expressed analysis, univariate Cox, LASSO Cox regression, and random forest algorithm analysis, we established a 4 anoikis-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of LUAD patients in the TCGA and GEO databases, respectively. The low and high-risk score LUAD patients stratified by the model showed different tumor mutation burden, tumor microenvironment, gemcitabine sensitivity and immune checkpoint expressions. Through immunohistochemical analysis of clinical LUAD samples, we found that the 4 anoikis-related genes (PLK1, SLC2A1, ANGPTL4, CDKN3) were highly expressed in the tumor samples from clinical LUAD patients, and knockdown of these genes in LUAD cells by transfection with small interfering RNAs significantly inhibited LUAD cell proliferation and migration, and promoted anoikis. In conclusion, we developed an anoikis-based stratified model and a multivariable-based nomogram of LUAD, which could predict the survival of LUAD patients and guide clinical treatment. Show less
📄 PDF DOI: 10.18632/aging.205521
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Wei Li, Yongyi Wang, Ritai Huang +4 more · 2024 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24
Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. In this study, we aimed to investigate the relationship between coding variants in lipid met Show more
Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. In this study, we aimed to investigate the relationship between coding variants in lipid metabolism-related genes and CAD in a Chinese Han population. A total of 252 individuals were recruited for this study, including 120 CAD patients and 132 healthy control individuals. Rare and common coding variants in 12 lipid metabolism-related genes (ANGPTL3, ANGPTL4, APOA1, APOA5, APOC1, APOC3, CETP, LDLR, LIPC, LPL, PCSK9 and SCARB1) were detected via next-generation sequencing (NGS)-based targeted sequencing. Associations between common variants and CAD were evaluated by Fisher's exact test. A gene-based association test of rare variants was performed by the sequence kernel association test-optimal (SKAT-O test). We found 51 rare variants and 17 common variants in this study. One common missense variant, LIPC rs6083, was significantly associated with CAD after Bonferroni correction (OR = 0.47, 95% CI = 0.29-0.76, p = 1.9 × 10 Targeted sequencing is a powerful tool for identifying rare and common variants in CAD. The common missense variant LIPC rs6083 confers protection against CAD. The clinical relevance of rare variants in CAD aetiology needs to be investigated in larger sample sizes in the future. Show less
📄 PDF DOI: 10.1186/s12872-024-03759-5
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Ruicheng Yang, Xinyi Wang, Hulin Liu +4 more · 2024 · Cell communication and signaling : CCS · BioMed Central · added 2026-04-24
Bacterial meningitis remains a leading cause of infection-related mortality worldwide. Although Escherichia coli (E. coli) is the most common etiology of neonatal meningitis, the underlying mechanisms Show more
Bacterial meningitis remains a leading cause of infection-related mortality worldwide. Although Escherichia coli (E. coli) is the most common etiology of neonatal meningitis, the underlying mechanisms governing bacterial blood-brain barrier (BBB) disruption during infection remain elusive. We observed that infection of human brain microvascular endothelial cells with meningitic E. coli triggers the activation of early growth response 1 (Egr-1), a host transcriptional activator. Through integrated chromatin immunoprecipitation sequencing and transcriptome analysis, we identified Egr-1 as a crucial regulator for maintaining BBB integrity. Mechanistically, Egr-1 induced cytoskeletal changes and downregulated tight junction protein expression by directly targeting VEGFA, PDGFB, and ANGPTL4, resulting in increased BBB permeability. Meanwhile, Egr-1 also served as a master regulator in the initiation of neuroinflammatory response during meningitic E. coli infection. Our findings support an Egr-1-dependent mechanism of BBB disruption by meningitic E. coli, highlighting a promising therapeutic target for bacterial meningitis. Show less
📄 PDF DOI: 10.1186/s12964-024-01488-y
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Zhongyi Wang, Fengqi Li, Chunjing Feng +9 more · 2024 · Advanced biology · Wiley · added 2026-04-24
In vitro cell culturing witnessed its applications in scientific research and industrial activities. Attempts to shorten the doubling time of cultured cells have never ceased. In plants, auxin is appl Show more
In vitro cell culturing witnessed its applications in scientific research and industrial activities. Attempts to shorten the doubling time of cultured cells have never ceased. In plants, auxin is applied to promote plant growth, the synthetic derivative 1-Naphthaleneacetic acid (NAA) is a good example. Despite the auxin's naturally occurring receptors are not present in mammalian cells, studies suggested they may affect cell culturing. Yet the effects and mechanisms are still unclear. Here, an up to 2-fold increase in the yield of in vitro cultured human cells is observed. Different types of human cell lines and primary cells are tested and found that NAA is effective in all the cells tested. The PI staining followed by FACS suggested that NAA do not affect the cell cycling. Apoptosis-specific dye staining analysis implicated that NAA rescued cell death. Further bulk RNA sequencing is done and it is identified that the lipid metabolism-engaging and anti-apoptosis gene, ANGPTL4, is enhanced in expression upon NAA treatment. Studies on ANGPTL4 knockout cells indicated that ANGPTL4 is required for NAA-mediated response. Thus, the data identified a beneficial role of NAA in human cell culturing and highlighted its potency in in vitro cell culturing. Show less
no PDF DOI: 10.1002/adbi.202300593
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I-Weng Yen, Shin-Yu Lin, Ming-Wei Lin +12 more · 2024 · Clinica chimica acta; international journal of clinical chemistry · Elsevier · added 2026-04-24
Large-for-gestational-age (LGA) neonates have increased risk of adverse pregnancy outcomes and adult metabolic diseases. We aimed to investigate the relationship between plasma angiopoietin-like prote Show more
Large-for-gestational-age (LGA) neonates have increased risk of adverse pregnancy outcomes and adult metabolic diseases. We aimed to investigate the relationship between plasma angiopoietin-like protein 4 (ANGPTL4), a protein involved in lipid and glucose metabolism during pregnancy, placental function, growth factors, and the risk of LGA. We conducted a prospective cohort study and recruited women with singleton pregnancies at the National Taiwan University Hospital between 2013 and 2018. First trimester maternal plasma ANGPTL4 concentrations were measured. Among 353 pregnant women recruited, the LGA group had higher first trimester plasma ANGPTL4 concentrations than the appropriate-for-gestational-age group. Plasma ANGPTL4 was associated with hemoglobin A1c, post-load plasma glucose, plasma triglyceride, plasma free fatty acid concentrations, plasma growth hormone variant (GH-V), and birth weight, but was not associated with cord blood growth factors. After adjusting for age, body mass index, hemoglobin A1c, and plasma triglyceride concentrations, plasma ANGPTL4 concentrations were significantly associated with LGA risk, and its predictive performance, as measured by the area under the receiver operating characteristic curve, outperformed traditional risk factors for LGA. Plasma ANGPTL4 is associated with glucose and lipid metabolism during pregnancy, plasma GH-V, and birth weight, and is an early biomarker for predicting the risk of LGA. Show less
no PDF DOI: 10.1016/j.cca.2024.117775
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Chao Xue, Liqing Jiang, Bin Zhang +12 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Aortic dissection (AD) is a critical emergency in cardiovascular disease. AD occurs only in specific sites of the aorta, and the variation of shear stress in different aortic segments is a possible ca Show more
Aortic dissection (AD) is a critical emergency in cardiovascular disease. AD occurs only in specific sites of the aorta, and the variation of shear stress in different aortic segments is a possible cause not reported. This study investigated the key molecules involved in shear stress-induced AD through quantitative bioinformatic analysis of a public RNA sequencing database and clinical tissue sample validation. Gene expression data from the GSE153434, GSE147026, and GSE52093 datasets were downloaded from the Gene Expression Omnibus. Next, differently expressed genes (DEGs) in each dataset were identified and integrated to identify common AD DEGs. STRING, Cytoscape, and MCODE were used to identify hub genes and crucial clustering modules, and Connectivity Map (CMap) was used to identify positive and negative agents. The same procedure was performed for the GSE160611 dataset to obtain shear stress-induced human aortic endothelial cell (HAEC) DEGs. After the integration of these two DEGs sets to identify shear stress-associated hub DEGs in AD, Gene Ontology Enrichment Analysis was performed. The common chemokine receptors and ligands in AD were identified by analyzing AD's three RNA sequencing datasets. Their origin was verified by analyzing AD single-cell sequencing data and validated by immunoblotting and immunofluorescence. We identified 100 down-regulated and 50 up-regulated AD common DEGs. Enrichment results showed that common DEGs were closely related to blood vessel morphogenesis, muscle structure development, muscle tissue development, and chemotaxis. Among those DEGs, MYC, CCL2, and SPP1 are the three molecules with the highest degree. A crucial cluster of 15 genes was identified using MCODE, which contained inflammation-related genes with elevated expression and muscle cell-related genes with decreased expression, and CCL2 is central to immune-related genes. CMap confirmed MEK inhibitors and ALK inhibitors as possible therapeutic agents for AD. Moreover, 366 shear stress-associated DEGs in HAEC were identified in the GSE160611 dataset. After taking the intersection, we identified five shear stress-associated hub DEGs in AD (ANGPTL4, SNAI2, CCL2, GADD45B, and PROM1), and the enrichment analysis indicated they were related to the endothelial cell apoptotic process. Chemokine CCL2 was the molecule with a high degree in both DEG sets. Besides CCL2, CXCL5 was the only chemokine ligand differentially expressed in the three datasets. Additionally, immunoblotting confirmed the increased expression of CCL2 and CXCL5 in clinical tissue samples. Further research at the single-cell level revealed that CCL2 has multiple origins, and CXCL5 is macrophage-derived. Through integrative analysis, we identified core common AD DEGs and possible therapeutic agents based on these DEGs. We elucidated that the chemokine CCL2 and CXCL5-mediated "Endothelial-Monocyte-Neutrophil" axis may contribute to the development of shear stress-induced AD. These findings provide possible therapeutic targets for the prevention and treatment of AD. Show less
📄 PDF DOI: 10.1016/j.heliyon.2023.e23312
ANGPTL4
Qi Zhang, Shounan Qi, Jiaxin You +1 more · 2024 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Macular edema (ME) has emerged as a leading cause of visual impairment, representing a critical clinical manifestation and complication associated with many eye diseases. In the occurrence and develop Show more
Macular edema (ME) has emerged as a leading cause of visual impairment, representing a critical clinical manifestation and complication associated with many eye diseases. In the occurrence and development of ME, retinal glial cells like Müller cells and microglial cells play vital roles. Moreover, growth factor and cytokines associated with them, such as vascular endothelial growth factor (VEGF), pigment epithelium-derived factor (PEDF), hypoxia-inducible factor-1α (HIF-1α), angiopoietin-like protein 4 (ANGPTL4), interleukin-6(IL-6), interleukin-8 (IL-8), monocyte chemoattractant protein-1 (MCP-1), prostaglandin, etc., also take part in the pathogenesis of ME. Changes in these cytokines can lead to retinal angiogenesis, increased vascular permeability, blood-retinal barrier (BRB) breakdown, and fluid leakage, further causing ME to occur or deteriorate. Research on the role of retinal glial cells and related cytokines in ME will provide new therapeutic directions and effective remedies. This article is a literature review on the role of Müller cells, microglial cells and related factors in ME pathogenesis. Show less
no PDF DOI: 10.1016/j.bbrc.2023.149415
ANGPTL4
Hongling Hu, Sheng Luo, Pinglin Lai +18 more · 2024 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Leptin protein was thought to be unique to leptin receptor (LepR), but the phenotypes of mice with mutation in LepR [
📄 PDF DOI: 10.1073/pnas.2310685120
ANGPTL4
Hung-Chen Chang, Xiaojun Wang, Xuchao Gu +6 more · 2024 · Experimental gerontology · Elsevier · added 2026-04-24
Secretory factors linked to lymphogenesis, such as vascular endothelial growth factor C (VEGF-C), angiopoietin like protein 4 (ANGPTL4), and activin A (ACV-A), have been recognized as potential marker Show more
Secretory factors linked to lymphogenesis, such as vascular endothelial growth factor C (VEGF-C), angiopoietin like protein 4 (ANGPTL4), and activin A (ACV-A), have been recognized as potential markers of chronic inflammatory status and age-related diseases. Furthermore, these factors may also be linked to frailty. The primary objective of this study was to examine the serum VEGF-C, ANGPTL4, and ACV-A levels in young individuals, healthy older individuals, and older individuals with pre-frailty and frailty, and to determine their association with pro-inflammatory factor levels. We conducted an observational study, enrolling a total of 210 older individuals and 20 young healthy volunteers. Participants were divided into four groups based on the Freid frailty phenotype: healthy young group, older patients without frailty group, pre-frail older group, and frail older group. Plasma and peripheral blood mononuclear cells (PBMCs) were collected from all four groups. ELISA was used to measure the serum levels of VEGF-C, ANGPTL4, ACV-A, and pro-inflammatory cytokines, while RT-qPCR was used to measure the transcription level of VEGF-C, ANGPTL4 and ACV-A in PBMCs. In comparison to healthy young individuals and older participants without frailty, older participants with frailty exhibited lower renal function, higher serum levels and transcription levels of VEGF-C, ANGPTL4, ACV-A, and elevated levels of pro-inflammatory cytokines (CRP, IL-1β, and TNF-α). Multiple linear regression analysis revealed that serum levels of VEGF-C, ANGPTL4, and ACV-A were positively correlated with the frailty index, independent of age, eGFR, and comorbidities. Furthermore, the receiver operating characteristic (ROC) curve analysis demonstrated that serum levels of VEGF-C, ANGPTL4, and ACV-A have great accuracy in predicting frailty. Elevated serum levels of VEGF-C, ANGPTL4, and ACV-A are associated with frailty status. Show less
no PDF DOI: 10.1016/j.exger.2023.112345
ANGPTL4
Yiyun Liu, Naima Hamid, Rakia Manzoor +4 more · 2024 · The Science of the total environment · Elsevier · added 2026-04-24
Di-2-ethylhexyl phthalic acid (DEHP) is one of the most widely used plasticizers in the industry, which can improve the flexibility and durability of plastics. It is prone to migrate from various dail Show more
Di-2-ethylhexyl phthalic acid (DEHP) is one of the most widely used plasticizers in the industry, which can improve the flexibility and durability of plastics. It is prone to migrate from various daily plastic products through wear and leaching into the surrounding environment and decompose into the more toxic metabolite mono-2-ethylhexyl phthalic acid (MEHP) after entering the human body. However, the impacts and mechanisms of MEHP on neuroblastoma are unclear. We exposed MYCN-amplified neuroblastoma SK-N-BE(2)C cells to an environmentally related concentration of MEHP and found that MEHP increased the proliferation and migration ability of tumor cells. The peroxisome proliferator-activated receptor (PPAR) β/δ pathway was identified as a pivotal signaling pathway in neuroblastoma, mediating the effects of MEHP through transcriptional sequencing analysis. Because MEHP can bind to the PPARβ/δ protein and initiate the expression of the downstream gene angiopoietin-like 4 (ANGPTL4), the PPARβ/δ-specific agonist GW501516 and antagonist GSK3787, the recombinant human ANGPTL4 protein, and the knockdown of gene expression confirmed the regulation of the PPARβ/δ-ANGPTL4 axis on the malignant phenotype of neuroblastoma. Based on the critical role of PPARβ/δ and ANGPTL4 in the metabolic process, a non-targeted metabolomics analysis revealed that MEHP altered multiple metabolic pathways, particularly lipid metabolites involving fatty acyls, glycerophospholipids, and sterol lipids, which may also be potential factors promoting tumor progression. We have demonstrated for the first time that MEHP can target binding to PPARβ/δ and affect the progression of neuroblastoma by activating the PPARβ/δ-ANGPTL4 axis. This mechanism confirms the health risks of plasticizers as tumor promoters and provides new data support for targeted prevention and treatment of neuroblastoma. Show less
no PDF DOI: 10.1016/j.scitotenv.2023.168949
ANGPTL4
Zehuan Liao, Joseph Jing Heng Lim, Jeannie Xue Ting Lee +12 more · 2024 · Advanced healthcare materials · Wiley · added 2026-04-24
Epithelial-to-mesenchymal transition (EMT) plays a crucial role in metastatic cancer progression, and current research, which relies heavily on 2D monolayer cultures, falls short in recapitulating the Show more
Epithelial-to-mesenchymal transition (EMT) plays a crucial role in metastatic cancer progression, and current research, which relies heavily on 2D monolayer cultures, falls short in recapitulating the complexity of a 3D tumor microenvironment. To address this limitation, a transcriptomic meta-analysis is conducted on diverse cancer types undergoing EMT in 2D and 3D cultures. It is found that mechanotransduction is elevated in 3D cultures and is further intensified during EMT, but not during 2D EMT. This analysis reveals a distinct 3D EMT gene signature, characterized by extracellular matrix remodeling coordinated by angiopoietin-like 4 (Angptl4) along with other canonical EMT regulators. Utilizing hydrogel-based 3D matrices with adjustable mechanical forces, 3D cancer cultures are established at varying physiological stiffness levels. A YAP:EGR-1 mediated up-regulation of Angptl4 expression is observed, accompanied by an upregulation of mesenchymal markers, at higher stiffness during cancer EMT. Suppression of Angptl4 using antisense oligonucleotides or anti-cAngptl4 antibodies leads to a dose-dependent abolishment of EMT-mediated chemoresistance and tumor self-organization in 3D, ultimately resulting in diminished metastatic potential and stunted growth of tumor xenografts. This unique programmable 3D cancer cultures simulate stiffness levels in the tumor microenvironment and unveil Angptl4 as a promising therapeutic target to inhibit EMT and impede cancer progression. Show less
no PDF DOI: 10.1002/adhm.202303481
ANGPTL4
Baoluo Ma, Linghui Qin, Zhou Sun +6 more · 2024 · Environmental toxicology · Wiley · added 2026-04-24
Clear cell renal cell carcinoma (ccRCC) is the most prevalent and aggressive subtype of renal cell carcinoma, originating from renal tubular epithelial cells in the kidney. Hypoxia proves to be a feat Show more
Clear cell renal cell carcinoma (ccRCC) is the most prevalent and aggressive subtype of renal cell carcinoma, originating from renal tubular epithelial cells in the kidney. Hypoxia proves to be a feature commonly observed in solid tumors, leading to increased resistance to treatment and tumor progression. scRNA-seq data were procured from GSE159115 data set. We utilized UMAP and NMF algorithm for clustering and dimensionality reduction. The FindAllMarkers function was used to compare various groups and identify potential hypoxia marker genes. A series of in vitro experiments, including CFA, flow cytometry targeting cell cycle, CCK-8, and EDU, was applied to investigate how ANGPTL4 regulated the ccRCC progression. Two cell lines of ccRCC cells, 786-O and Caki, were used for si-ANGPTL4 transfection. We annotated a total of a total of 6 cell clusters, namely ccRCC malignant cells, T cells, endothelial cells, myeloid cells, smooth muscle cells, and B cells. We observed higher levels of hypoxia-score in the ccRCC malignant cells, while lowest hypoxia-score in T and B cells. We detected multiple hypoxia-related subclusters of TME cells in ccRCC, among which S100A4 CD8+ T cells and nonhypoxia CD8+ T cells were found with a marked elevation of T cell inhibitory gene score. We identified that ANGPTL4+ endothelial cells might function as an integrative role in tumor angiogenesis. Multiple TME subclusters showed high potency in stratification of the prognosis of ccRCC patients. Moreover, by a series of in vitro experiment, we found ANGPTL4 regulated the ccRCC cell proliferation, probably through ERK/P38 pathway. We discerned multiple hypoxia-related subclusters of TME cells in ccRCC, which displayed distinct functional features and great potency in predicting prognosis of ccRCC patients. We identified the role of ANGPTL4 in regulating ccRCC proliferation via ERK/p38 pathway. Show less
no PDF DOI: 10.1002/tox.24009
ANGPTL4
Baisheng Sun, Lina Bai, Qinglin Li +5 more · 2024 · Toxicology in vitro : an international journal published in association with BIBRA · Elsevier · added 2026-04-24
Sepsis-induced acute lung injury (ALI) is a life-threatening disease. Macrophage pyroptosis has been reported to exert function in ALI. We aimed to investigate the mechanisms of ANGPTL4-mediated cell Show more
Sepsis-induced acute lung injury (ALI) is a life-threatening disease. Macrophage pyroptosis has been reported to exert function in ALI. We aimed to investigate the mechanisms of ANGPTL4-mediated cell pyroptosis in sepsis-induced ALI, thus providing new insights into the pathogenesis and prevention and treatment measures of sepsis-induced ALI. In vivo animal models and in vitro cell models were established by cecal ligation and puncture (CLP) method and lipopolysaccharide-induced macrophages RAW264.7. ANGPTL4 was silenced in CLP mice or macrophages, followed by the determination of ANGPTL4 expression in bronchoalveolar lavage fluid (BALF) or macrophages. Lung histopathology was observed by H&E staining, with pathological injury scores evaluated and lung wet and dry weight ratio recorded. M1/M2 macrophage marker levels (iNOS/CD86/Arg1), inflammatory factor (TNF-α/IL-6/IL-1β/iNOS) expression in BALF, cell death and pyroptosis, NLRP3 inflammasome, cell pyroptosis-related protein (NLRP3/Cleaved-caspase-1/caspase-1/GSDMD-N) levels, NF-κB pathway activation were assessed by RT-qPCR/ELISA/flow cytometry/Western blot, respectively. ANGPTL4 was highly expressed in mice with sepsis-induced ALI, and ANGPTL4 silencing ameliorated sepsis-induced ALI in mice. In vivo, ANGPTL4 silencing repressed M1 macrophage polarization and macrophage pyroptosis in mice with sepsis-induced ALI. In vitro, ANGPTL4 knockout impeded LPS-induced activation and pyroptosis of M1 macrophages and hindered LPS-induced activation of the NF-κB pathway in macrophages. Knockdown of ANGPTL4 blocks the NF-κB pathway activation, hinders macrophage M1 polarization and pyroptosis, thereby suppressing sepsis-induced ALI. Show less
no PDF DOI: 10.1016/j.tiv.2023.105709
ANGPTL4
Wei Zhang, Junhui Liu, Xin Ren +7 more · 2024 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
Peroxisome proliferator-activated receptors (PPARs) are essential for cellular physiological processes. However, there is less research on the PPAR-related genes in lung adenocarcinoma (LUAD). Open-ac Show more
Peroxisome proliferator-activated receptors (PPARs) are essential for cellular physiological processes. However, there is less research on the PPAR-related genes in lung adenocarcinoma (LUAD). Open-access data were get from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases. All the analysis were conducted in the R software based on different R packages. In this study, we gauged the PPAR score employing a set of 72 PPAR-associated genes and probed the biological impact of this score on lung adenocarcinoma (LUAD). Subsequently, we established a unique signature composed of eight PPAR-related genes (ANGPTL4, ACSL3, ADIPOQ, FABP1, SLC27A1, ACOX2, PPARD and OLR1) to forecast the prognosis of LUAD. The signature's effectiveness in predicting survival was validated through the receiver operating characteristic curve in the TCGA-LUAD cohort. As per the pathway enrichment analysis, several crucial oncogenic pathways and metabolic processes were enriched in high-risk individuals. Further, we observed that these high-risk patients exhibited heightened genomic instability. Additionally, compared to the low-risk cohort, high-risk patients demonstrated diminished immune components and function. Intriguingly, high-risk patients exhibited a potential heightened sensitivity to immunotherapy and certain drugs, including Gefitinib, Afatinib, Erlotinib, IAP₅₆₂₀, Sapitinib, LCL161, Lapatinib and AZD3759. The prognosis model based on eight PPAR-related genes has satisfactory prognosis prediction efficiency. Meanwhile, our results can provide direction for future studies in the relevant aspects. Show less
📄 PDF DOI: 10.1111/jcmm.17877
ANGPTL4
Guoyi Wang, Jinwen Zhao, Min Zhou +2 more · 2024 · Aging · Impact Journals · added 2026-04-24
Diabetic nephropathy (DN) is a severe complication of diabetes that affects the kidneys. Disulfidptosis, a newly defined type of programmed cell death, has emerged as a potential area of interest, yet Show more
Diabetic nephropathy (DN) is a severe complication of diabetes that affects the kidneys. Disulfidptosis, a newly defined type of programmed cell death, has emerged as a potential area of interest, yet its significance in DN remains unexplored. This study utilized single-cell sequencing data GSE131882 from GEO database combined with bulk transcriptome sequencing data GSE30122, GSE30528 and GSE30529 to investigate disulfidptosis in DN. Single-cell sequencing analysis was performed on samples from DN patients and healthy controls, focusing on cell heterogeneity and communication. Weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were employed to identify disulfidptosis-related gene sets and pathways. A diagnostic model was constructed using machine learning techniques based on identified genes, and immunocorrelation analysis was conducted to explore the relationship between key genes and immune cells. PCR validation was performed on blood samples from DN patients and healthy controls. The study revealed significant disulfidptosis heterogeneity and cell communication differences in DN. Specific targets related to disulfidptosis were identified, providing insights into the pathogenesis of DN. The diagnostic model demonstrated high accuracy in distinguishing DN from healthy samples across multiple datasets. Immunocorrelation analysis highlighted the complex interactions between immune cells and key disulfidptosis-related genes. PCR validation supported the differential expression of model genes VEGFA, MAGI2, THSD7A and ANKRD28 in DN. This research advances our understanding of DN by highlighting the role of disulfidptosis and identifying potential biomarkers for early detection and personalized treatment. Show less
📄 PDF DOI: 10.18632/aging.205982
ANKRD28