👤 Yinghui Wang

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Also published as: A Wang, Ai-Ling Wang, Ai-Ting Wang, Aihua Wang, Aijun Wang, Aili Wang, Aimin Wang, Aiting Wang, Aixian Wang, Aiyun Wang, Aizhong Wang, Alexander Wang, Alice Wang, Allen Wang, Anlai Wang, Anli Wang, Annette Wang, Anni Wang, Anqi Wang, Anthony Z Wang, Anxiang Wang, Anxin Wang, Ao Wang, Aoli Wang, B R Wang, B Wang, Baihan Wang, Baisong Wang, Baitao Wang, Bangchen Wang, Banghui Wang, Bangmao Wang, Bangshing Wang, Bao Wang, Bao-Long Wang, Baocheng Wang, Baofeng Wang, Baogui Wang, Baojun Wang, Baoli Wang, Baolong Wang, Baoming Wang, Baosen Wang, Baowei Wang, Baoying Wang, Baoyun Wang, Bei Bei Wang, Bei Wang, Beibei Wang, Beilan Wang, Beilei Wang, Ben Wang, Benjamin H Wang, Benzhong Wang, Bi Wang, Bi-Dar Wang, Biao Wang, Bicheng Wang, Bijue Wang, Bin Wang, Bin-Xue Wang, Binbin Wang, Bing Qing Wang, Bing Wang, Binghai Wang, Binghan Wang, Bingjie Wang, Binglong Wang, Bingnan Wang, Bingyan Wang, Bingyu Wang, Binquan Wang, Biqi Wang, Bo Wang, Bochu Wang, Boyu Wang, Bruce Wang, C Wang, C Z Wang, Cai Ren Wang, Cai-Hong Wang, Cai-Yun Wang, Cailian Wang, Caiqin Wang, Caixia Wang, Caiyan Wang, Can Wang, Cangyu Wang, Carol A Wang, Catherine Ruiyi Wang, Cenxuan Wang, Chan Wang, Chang Wang, Chang-Yun Wang, Changduo Wang, Changjing Wang, Changliang Wang, Changlong Wang, Changqian Wang, Changtu Wang, Changwei Wang, Changying Wang, Changyu Wang, Changyuan Wang, Changzhen Wang, Chao Wang, Chao-Jun Wang, Chao-Yung Wang, Chaodong Wang, Chaofan Wang, Chaohan Wang, Chaohui Wang, Chaojie Wang, Chaokui Wang, Chaomeng Wang, Chaoqun Wang, Chaoxian Wang, Chaoyi Wang, Chaoyu Wang, Chaozhan Wang, Charles C N Wang, Chau-Jong Wang, Chen Wang, Chen-Cen Wang, Chen-Ma Wang, Chen-Yu Wang, Chenchen Wang, Chenfei Wang, Cheng An Wang, Cheng Wang, Cheng-Cheng Wang, Cheng-Jie Wang, Cheng-zhang Wang, Chengbin Wang, Chengcheng Wang, Chenggang Wang, Chenghao Wang, Chenghua Wang, Chengjian Wang, Chengjun Wang, Chenglin Wang, Chenglong Wang, Chengniu Wang, Chengqiang Wang, Chengshuo Wang, Chenguang Wang, Chengwen Wang, Chengyan Wang, Chengyu Wang, Chengze Wang, Chenji Wang, Chenliang Wang, Chenwei Wang, Chenxi Wang, Chenxin Wang, Chenxuan Wang, Chenyang Wang, Chenyao Wang, Chenyin Wang, Chenyu Wang, Chenzi Wang, Chi Chiu Wang, Chi Wang, Chi-Ping Wang, Chia-Chuan Wang, Chia-Lin Wang, Chien-Hsun Wang, Chien-Wei Wang, Chih-Chun Wang, Chih-Hao Wang, Chih-Hsien Wang, Chih-Liang Wang, Chih-Yang Wang, Chih-Yuan Wang, Chijia Wang, Ching C Wang, Ching-Jen Wang, Chiou-Miin Wang, Chong Wang, Chongjian Wang, Chonglong Wang, Chongmin Wang, Chongze Wang, Christina Wang, Christine Wang, Chu Wang, Chuan Wang, Chuan-Chao Wang, Chuan-Hui Wang, Chuan-Jiang Wang, Chuan-Wen Wang, Chuang Wang, Chuanhai Wang, Chuansen Wang, Chuansheng Wang, Chuanxin Wang, Chuanyue Wang, Chuduan Wang, Chun Wang, Chun-Chieh Wang, Chun-Juan Wang, Chun-Li Wang, Chun-Lin Wang, Chun-Ting Wang, Chun-Xia Wang, Chung-Hsi Wang, Chung-Hsing Wang, Chung-Teng Wang, Chunguo Wang, Chunhong Wang, Chuning Wang, Chunjiong Wang, Chunjuan Wang, Chunle Wang, Chunli Wang, Chunlong Wang, Chunmei Wang, Chunsheng Wang, Chunting Wang, Chunxia Wang, Chunxue Wang, Chunyan Wang, Chunyang Wang, Chunyi Wang, Chunyu Wang, Chuyao Wang, Cindy Wang, Ciyang Wang, Cong Wang, Congcong Wang, Congrong Wang, Congrui Wang, Cui Wang, Cui-Fang Wang, Cui-Shan Wang, Cuili Wang, Cuiling Wang, Cuizhe Wang, Cun-Yu Wang, Cunchuan Wang, Cunyi Wang, D Wang, Da Wang, Da-Cheng Wang, Da-Li Wang, Da-Yan Wang, Da-Zhi Wang, Dadong Wang, Dai Wang, Daijun Wang, Daiwei Wang, Daixi Wang, Dajia Wang, Dake Wang, Dali Wang, Dalong Wang, Dalu Wang, Dan Wang, Dan-Dan Wang, Danan Wang, Dandan Wang, Danfeng Wang, Dang Wang, Dangfeng Wang, Danling Wang, Danqing Wang, Danxin Wang, Danyang Wang, Dao Wen Wang, Dao-Wen Wang, Dao-Xin Wang, Daolong Wang, Daoping Wang, Daozhong Wang, Dapeng Wang, Daping Wang, Daqi Wang, Daqing Wang, David Q H Wang, David Q-H Wang, David Wang, Dawei Wang, Dayan Wang, Dayong Wang, Dazhi Wang, De-He Wang, Dedong Wang, Dehao Wang, Deli Wang, Delin Wang, Delong Wang, Demin Wang, Deming Wang, Dengbin Wang, Dennis Qing Wang, Dennis Wang, Deqi Wang, Deshou Wang, Dezhong Wang, Di Wang, Dinghui Wang, Dingting Wang, Dingxiang Wang, Dong D Wang, Dong Hao Wang, Dong Wang, Dong-Dong Wang, Dong-Jie Wang, Dong-Mei Wang, DongWei Wang, Dongdong Wang, Donggen Wang, Donghao Wang, Donghong Wang, Donghui Wang, Dongliang Wang, Donglin Wang, Dongmei Wang, Dongqin Wang, Dongshi Wang, Dongxia Wang, Dongxu Wang, Dongyan Wang, Dongyang Wang, Dongyi Wang, Dongying Wang, Dongyu Wang, Doudou Wang, Du Wang, Duan Wang, Duanyang Wang, Duo-Ping Wang, E Wang, Edward Wang, En-bo Wang, En-hua Wang, Endi Wang, Enhua Wang, Er-Jin Wang, Erfei Wang, Erika Y Wang, Ermao Wang, Erming Wang, Ertao Wang, Eryao Wang, Eunice S Wang, Exing Wang, F Wang, Fa-Kai Wang, Fan Wang, Fanchang Wang, Fang Wang, Fang-Tao Wang, Fangfang Wang, Fangjie Wang, Fangjun Wang, Fangyan Wang, Fangyong Wang, Fangyu Wang, Fanhua Wang, Fanwen Wang, Fanxiong Wang, Fei Wang, Fei-Fei Wang, Fei-Yan Wang, Feida Wang, Feifei Wang, Feijie Wang, Feimiao Wang, Feixiang Wang, Feiyan Wang, Fen Wang, Feng Wang, Feng-Sheng Wang, Fengchong Wang, Fengge Wang, Fenghua Wang, Fengliang Wang, Fenglin Wang, Fengling Wang, Fengqiang Wang, Fengyang Wang, Fengying Wang, Fengyong Wang, Fengyun Wang, Fengzhen Wang, Fengzhong Wang, Fu Wang, Fu-Sheng Wang, Fu-Yan Wang, Fu-Zhen Wang, Fubao Wang, Fubing Wang, Fudi Wang, Fuhua Wang, Fuqiang Wang, Furong Wang, Fuwen Wang, Fuxin Wang, Fuyan Wang, G Q Wang, G Wang, G-W Wang, Gan Wang, Gang Wang, Ganggang Wang, Ganglin Wang, Gangyang Wang, Ganyu Wang, Gao T Wang, Gao Wang, Gaofu Wang, Gaopin Wang, Gavin Wang, Ge Wang, Geng Wang, Genghao Wang, Gengsheng Wang, Gongming Wang, Guan Wang, Guan-song Wang, Guandi Wang, Guanduo Wang, Guang Wang, Guang-Jie Wang, Guang-Rui Wang, Guangdi Wang, Guanghua Wang, Guanghui Wang, Guangliang Wang, Guangming Wang, Guangsuo Wang, Guangwen Wang, Guangyan Wang, Guangzhi Wang, Guanrou Wang, Guanru Wang, Guansong Wang, Guanyun Wang, Gui-Qi Wang, Guibin Wang, Guihu Wang, Guihua Wang, Guimin Wang, Guiping Wang, Guiqun Wang, Guixin Wang, Guixue Wang, Guiying Wang, Guo-Du Wang, Guo-Hua Wang, Guo-Liang Wang, Guo-Ping Wang, Guo-Quan Wang, Guo-hong Wang, GuoYou Wang, Guobin Wang, Guobing Wang, Guodong Wang, Guohang Wang, Guohao Wang, Guoliang Wang, Guoling Wang, Guoping Wang, Guoqian Wang, Guoqiang Wang, Guoqing Wang, Guorong Wang, Guowen Wang, Guoxiang Wang, Guoxiu Wang, Guoyi Wang, Guoying Wang, Guozheng Wang, H J Wang, H Wang, H X Wang, H Y Wang, H-Y Wang, Hai Bo Wang, Hai Wang, Hai Yang Wang, Hai-Feng Wang, Hai-Jun Wang, Hai-Long Wang, Haibin Wang, Haibing Wang, Haibo Wang, Haichao Wang, Haichuan Wang, Haifei Wang, Haifeng Wang, Haihe Wang, Haihong Wang, Haihua Wang, Haijiao Wang, Haijing Wang, Haijiu Wang, Haikun Wang, Hailei Wang, Hailin Wang, Hailing Wang, Hailong Wang, Haimeng Wang, Haina Wang, Haining Wang, Haiping Wang, Hairong Wang, Haitao Wang, Haiwei Wang, Haixia Wang, Haixin Wang, Haixing Wang, Haiyan Wang, Haiying Wang, Haiyong Wang, Haiyun Wang, Haizhen Wang, Han Wang, Hanbin Wang, Hanbing Wang, Hanchao Wang, Handong Wang, Hang Wang, Hangzhou Wang, Hanmin Wang, Hanping Wang, Hanqi Wang, Hanying Wang, Hanyu Wang, Hanzhi Wang, Hao Wang, Hao-Ching Wang, Hao-Hua Wang, Hao-Tian Wang, Hao-Yu Wang, Haobin Wang, Haochen Wang, Haohao Wang, Haohui Wang, Haojie Wang, Haolong Wang, Haomin Wang, Haoming Wang, Haonan Wang, Haoping Wang, Haoqi Wang, Haoran Wang, Haowei Wang, Haoxin Wang, Haoyang Wang, Haoyu Wang, Haozhou Wang, He Wang, He-Cheng Wang, He-Ling Wang, He-Ping Wang, He-Tong Wang, Hebo Wang, Hechuan Wang, Heling Wang, Hemei Wang, Heming Wang, Heng Wang, Heng-Cai Wang, Hengjiao Wang, Hengjun Wang, Hequn Wang, Hesuiyuan Wang, Heyong Wang, Hezhi Wang, Hong Wang, Hong Yi Wang, Hong-Gang Wang, Hong-Hui Wang, Hong-Kai Wang, Hong-Qin Wang, Hong-Wei Wang, Hong-Xia Wang, Hong-Yan Wang, Hong-Yang Wang, Hong-Ying Wang, Hongbin Wang, Hongbing Wang, Hongbo Wang, Hongcai Wang, Hongda Wang, Hongdan Wang, Hongfang Wang, Hongjia Wang, Hongjian Wang, Hongjie Wang, Hongjuan Wang, Hongkun Wang, Honglei Wang, Hongli Wang, Honglian Wang, Honglun Wang, Hongmei Wang, Hongpin Wang, Hongqian Wang, Hongshan Wang, Hongsheng Wang, Hongtao Wang, Hongwei Wang, Hongxia Wang, Hongxin Wang, Hongyan Wang, Hongyang Wang, Hongyi Wang, Hongyin Wang, Hongying Wang, Hongyu Wang, Hongyuan Wang, Hongyue Wang, Hongyun Wang, Hongze Wang, Hongzhan Wang, Hongzhuang Wang, Horng-Dar Wang, Houchun Wang, Hsei-Wei Wang, Hsueh-Chun Wang, Hu WANG, Hua Wang, Hua-Qin Wang, Hua-Wei Wang, Huabo Wang, Huafei Wang, Huai-Zhou Wang, Huaibing Wang, Huaili Wang, Huaizhi Wang, Huajin Wang, Huajing Wang, Hualin Wang, Hualing Wang, Huan Wang, Huan-You Wang, Huang Wang, Huanhuan Wang, Huanyu Wang, Huaquan Wang, Huating Wang, Huawei Wang, Huaxiang Wang, Huayang Wang, Huei Wang, Hui Miao Wang, Hui Wang, Hui-Hui Wang, Hui-Li Wang, Hui-Nan Wang, Hui-Yu Wang, HuiYue Wang, Huie Wang, Huiguo Wang, Huihua Wang, Huihui Wang, Huijie Wang, Huijun Wang, Huilun Wang, Huimei Wang, Huimin Wang, Huina Wang, Huiping Wang, Huiquan Wang, Huiqun Wang, Huishan Wang, Huiting Wang, Huiwen Wang, Huixia Wang, Huiyan Wang, Huiyang Wang, Huiyao Wang, Huiying Wang, Huiyu Wang, Huizhen Wang, Huizhi Wang, Huming Wang, I-Ching Wang, Iris X Wang, Isabel Z Wang, J J Wang, J P Wang, J Q Wang, J Wang, J Z Wang, J-Y Wang, Jacob E Wang, James Wang, Jeffrey Wang, Jen-Chun Wang, Jen-Chywan Wang, Jennifer E Wang, Jennifer T Wang, Jennifer X Wang, Jenny Y Wang, Jeremy R Wang, Jeremy Wang, Ji M Wang, Ji Wang, Ji-Nuo Wang, Ji-Yang Wang, Ji-Yao Wang, Ji-zheng Wang, Jia Bei Wang, Jia Bin Wang, Jia Wang, Jia-Liang Wang, Jia-Lin Wang, Jia-Mei Wang, Jia-Peng Wang, Jia-Qi Wang, Jia-Qiang Wang, Jia-Ying Wang, Jia-Yu Wang, Jiabei Wang, Jiabo Wang, Jiafeng Wang, Jiafu Wang, Jiahao Wang, Jiahui Wang, Jiajia Wang, Jiakun Wang, Jiale Wang, Jiali Wang, Jialiang Wang, Jialin Wang, Jialing Wang, Jiamin Wang, Jiaming Wang, Jian Wang, Jian'an Wang, Jian-Bin Wang, Jian-Guo Wang, Jian-Hong Wang, Jian-Long Wang, Jian-Wei Wang, Jian-Xiong Wang, Jian-Yong Wang, Jian-Zhi Wang, Jian-chun Wang, Jianan Wang, Jianbing Wang, Jianbo Wang, Jianding Wang, Jianfang Wang, Jianfei Wang, Jiang Wang, Jiangbin Wang, Jiangbo Wang, Jianghua Wang, Jianghui Wang, Jiangong Wang, Jianguo Wang, Jianhao Wang, Jianhua Wang, Jianhui Wang, Jiani Wang, Jianjiao Wang, Jianjie Wang, Jianjun Wang, Jianle Wang, Jianli Wang, Jianlin Wang, Jianliu Wang, Jianlong Wang, Jianmei Wang, Jianmin Wang, Jianning Wang, Jianping Wang, Jianqin Wang, Jianqing Wang, Jianqun Wang, Jianru Wang, Jianshe Wang, Jianshu Wang, Jiantao Wang, Jianwei Wang, Jianwu Wang, Jianxiang Wang, Jianxin Wang, Jianye Wang, Jianying Wang, Jianyong Wang, Jianyu Wang, Jianzhang Wang, Jianzhi Wang, Jiao Wang, Jiaojiao Wang, Jiapan Wang, Jiaping Wang, Jiaqi Wang, Jiaqian Wang, Jiatao Wang, Jiawei Wang, Jiawen Wang, Jiaxi Wang, Jiaxin Wang, Jiaxing Wang, Jiaxuan Wang, Jiayan Wang, Jiayang Wang, Jiayi Wang, Jiaying Wang, Jiayu Wang, Jiazheng Wang, Jiazhi Wang, Jie Jin Wang, Jie Wang, Jieda Wang, Jieh-Neng Wang, Jiemei Wang, Jieqi Wang, Jieyan Wang, Jieyu Wang, Jifei Wang, Jiheng Wang, Jihong Wang, Jiliang Wang, Jilin Wang, Jin Wang, Jin'e Wang, Jin-Bao Wang, Jin-Cheng Wang, Jin-Da Wang, Jin-E Wang, Jin-Juan Wang, Jin-Liang Wang, Jin-Xia Wang, Jin-Xing Wang, Jincheng Wang, Jindan Wang, Jinfei Wang, Jinfeng Wang, Jinfu Wang, Jing J Wang, Jing Wang, Jing-Hao Wang, Jing-Huan Wang, Jing-Jing Wang, Jing-Long Wang, Jing-Min Wang, Jing-Shi Wang, Jing-Wen Wang, Jing-Xian Wang, Jing-Yi Wang, Jing-Zhai Wang, Jingang Wang, Jingchun Wang, Jingfan Wang, Jingfeng Wang, Jingheng Wang, Jinghong Wang, Jinghua Wang, Jinghuan Wang, Jingjing Wang, Jingkang Wang, Jinglin Wang, Jingmin Wang, Jingnan Wang, Jingqi Wang, Jingru Wang, Jingtong Wang, Jingwei Wang, Jingwen Wang, Jingxiao Wang, Jingyang Wang, Jingyi Wang, Jingying Wang, Jingyu Wang, Jingyue Wang, Jingyun Wang, Jingzhou Wang, Jinhai Wang, Jinhao Wang, Jinhe Wang, Jinhua Wang, Jinhuan Wang, Jinhui Wang, Jinjie Wang, Jinjin Wang, Jinkang Wang, Jinling Wang, Jinlong Wang, Jinmeng Wang, Jinning Wang, Jinping Wang, Jinqiu Wang, Jinrong Wang, Jinru Wang, Jinsong Wang, Jintao Wang, Jinxia Wang, Jinxiang Wang, Jinyang Wang, Jinyu Wang, Jinyue Wang, Jinyun Wang, Jinzhu Wang, Jiou Wang, Jipeng Wang, Jiqing Wang, Jiqiu Wang, Jisheng Wang, Jiu Wang, Jiucun Wang, Jiun-Ling Wang, Jiwen Wang, Jixuan Wang, Jiyan Wang, Jiying Wang, Jiyong Wang, Jizheng Wang, John Wang, Jou-Kou Wang, Joy Wang, Ju Wang, Juan Wang, Jue Wang, Jueqiong Wang, Jufeng Wang, Julie Wang, Juling Wang, Jun Kit Wang, Jun Wang, Jun Yi Wang, Jun-Feng Wang, Jun-Jie Wang, Jun-Jun Wang, Jun-Ling Wang, Jun-Sheng Wang, Jun-Sing Wang, Jun-Zhuo Wang, Jundong Wang, Junfeng Wang, Jung-Pan Wang, Junhong Wang, Junhua Wang, Junhui Wang, Junjiang Wang, Junjie Wang, Junjun Wang, Junkai Wang, Junke Wang, Junli Wang, Junlin Wang, Junling Wang, Junmei Wang, Junmin Wang, Junpeng Wang, Junping Wang, Junqin Wang, Junqing Wang, Junrui Wang, Junsheng Wang, Junshi Wang, Junshuang Wang, Junwen Wang, Junxiao Wang, Junya Wang, Junying Wang, Junyu Wang, Justin Wang, Jutao Wang, Juxiang Wang, K Wang, Kai Wang, Kai-Kun Wang, Kai-Wen Wang, Kaicen Wang, Kaihao Wang, Kaihe Wang, Kaihong Wang, Kaijie Wang, Kaijuan Wang, Kailu Wang, Kaiming Wang, Kaining Wang, Kaiting Wang, Kaixi Wang, Kaixu Wang, Kaiyan Wang, Kaiyuan Wang, Kaiyue Wang, Kan Wang, Kangli Wang, Kangling Wang, Kangmei Wang, Kangning Wang, Ke Wang, Ke-Feng Wang, KeShan Wang, Kehan Wang, Kehao Wang, Kejia Wang, Kejian Wang, Kejun Wang, Keke Wang, Keming Wang, Kenan Wang, Keqing Wang, Kesheng Wang, Kexin Wang, Keyan Wang, Keyi Wang, Keyun Wang, Kongyan Wang, Kuan Hong Wang, Kui Wang, Kun Wang, Kunhua Wang, Kunpeng Wang, Kunzheng Wang, L F Wang, L M Wang, L Wang, L Z Wang, L-S Wang, Laidi Wang, Laijian Wang, Laiyuan Wang, Lan Wang, Lan-Wan Wang, Lan-lan Wang, Lanlan Wang, Larry Wang, Le Wang, Le-Xin Wang, Ledan Wang, Lee-Kai Wang, Lei P Wang, Lei Wang, Lei-Lei Wang, Leiming Wang, Leishen Wang, Leli Wang, Leran Wang, Lexin Wang, Leying Wang, Li Chun Wang, Li Dong Wang, Li Wang, Li-Dong Wang, Li-E Wang, Li-Juan Wang, Li-Li Wang, Li-Na Wang, Li-San Wang, Li-Ting Wang, Li-Xin Wang, Li-Yong Wang, LiLi Wang, Lian Wang, Lianchun Wang, Liang Wang, Liang-Yan Wang, Liangfu Wang, Lianghai Wang, Liangli Wang, Liangliang Wang, Liangxu Wang, Lianshui Wang, Lianyong Wang, Libo Wang, Lichan Wang, Lichao Wang, Liewei Wang, Lifang Wang, Lifei Wang, Lifen Wang, Lifeng Wang, Ligang Wang, Lihong Wang, Lihua Wang, Lihui Wang, Lijia Wang, Lijin Wang, Lijing Wang, Lijuan Wang, Lijun Wang, Liling Wang, Lily Wang, Limeng Wang, Limin Wang, Liming Wang, Lin Wang, Lin-Fa Wang, Lin-Yu Wang, Lina Wang, Linfang Wang, Ling Jie Wang, Ling Wang, Ling-Ling Wang, Lingbing Wang, Lingda Wang, Linghua Wang, Linghuan Wang, Lingli Wang, Lingling Wang, Lingyan Wang, Lingzhi Wang, Linhua Wang, Linhui Wang, Linjie Wang, Linli Wang, Linlin Wang, Linping Wang, Linshu Wang, Linshuang Wang, Lintao Wang, Linxuan Wang, Linying Wang, Linyuan Wang, Liping Wang, Liqing Wang, Liqun Wang, Lirong Wang, Litao Wang, Liting Wang, Liu Wang, Liusong Wang, Liuyang Wang, Liwei Wang, Lixia Wang, Lixian Wang, Lixiang Wang, Lixin Wang, Lixing Wang, Lixiu Wang, Liyan Wang, Liyi Wang, Liying Wang, Liyong Wang, Liyuan Wang, Liyun Wang, Long Wang, Longcai Wang, Longfei Wang, Longsheng Wang, Longxiang Wang, Lou-Pin Wang, Lu Wang, Lu-Lu Wang, Lueli Wang, Lufang Wang, Luhong Wang, Luhui Wang, Lujuan Wang, Lulu Wang, Luofu Wang, Luping Wang, Luting Wang, Luwen Wang, Luxiang Wang, Luya Wang, Luyao Wang, Luyun Wang, Lynn Yuning Wang, M H Wang, M Wang, M Y Wang, M-J Wang, Maiqiu Wang, Man Wang, Mangju Wang, Manli Wang, Mao-Xin Wang, Maochun Wang, Maojie Wang, Maoju Wang, Mark Wang, Mei Wang, Mei-Gui Wang, Mei-Xia Wang, Meiding Wang, Meihui Wang, Meijun Wang, Meiling Wang, Meixia Wang, Melissa T Wang, Meng C Wang, Meng Wang, Meng Yu Wang, Meng-Dan Wang, Meng-Lan Wang, Meng-Meng Wang, Meng-Ru Wang, Meng-Wei Wang, Meng-Ying Wang, Meng-hong Wang, Mengge Wang, Menghan Wang, Menghui Wang, Mengjiao Wang, Mengjing Wang, Mengjun Wang, Menglong Wang, Menglu Wang, Mengmeng Wang, Mengqi Wang, Mengru Wang, Mengshi Wang, Mengwen Wang, Mengxiao Wang, Mengya Wang, Mengyao Wang, Mengying Wang, Mengyuan Wang, Mengyue Wang, Mengyun Wang, Mengze Wang, Mengzhao Wang, Mengzhi Wang, Mian Wang, Miao Wang, Mimi Wang, Min Wang, Min-sheng Wang, Ming Wang, Ming-Chih Wang, Ming-Hsi Wang, Ming-Jie Wang, Ming-Wei Wang, Ming-Yang Wang, Ming-Yuan Wang, Mingchao Wang, Mingda Wang, Minghua Wang, Minghuan Wang, Minghui Wang, Mingji Wang, Mingjin Wang, Minglei Wang, Mingliang Wang, Mingmei Wang, Mingming Wang, Mingqiang Wang, Mingrui Wang, Mingsong Wang, Mingxi Wang, Mingxia Wang, Mingxun Wang, Mingya Wang, Mingyang Wang, Mingyi Wang, Mingyu Wang, Mingzhi Wang, Mingzhu Wang, Minjie Wang, Minjun Wang, Minmin Wang, Minxian Wang, Minxiu Wang, Minzhou Wang, Miranda C Wang, Mo Wang, Mofei Wang, Monica Wang, Mu Wang, Mutian Wang, Muxiao Wang, Muxuan Wang, N Wang, Na Wang, Nan Wang, Nana Wang, Nanbu Wang, Nannan Wang, Nanping Wang, Neng Wang, Ni Wang, Niansong Wang, Ning Wang, Ningjian Wang, Ningli Wang, Ningyuan Wang, Nuan Wang, Oliver Wang, Ouchen Wang, P Jeremy Wang, P L Wang, P N Wang, P Wang, Pai Wang, Pan Wang, Pan-Pan Wang, Panfeng Wang, Panliang Wang, Pei Chang Wang, Pei Wang, Pei-Hua Wang, Pei-Jian Wang, Pei-Juan Wang, Pei-Wen Wang, Pei-Yu Wang, Peichang Wang, Peigeng Wang, Peihe Wang, Peijia Wang, Peijuan Wang, Peijun Wang, Peilin Wang, Peipei Wang, Peirong Wang, Peiwen Wang, Peixi Wang, Peiyao Wang, Peiyin Wang, Peng Wang, Peng-Cheng Wang, Pengbo Wang, Pengchao Wang, Pengfei Wang, Pengjie Wang, Pengju Wang, Penglai Wang, Penglong Wang, Pengpu Wang, Pengtao Wang, Pengxiang Wang, Pengyu Wang, Pin Wang, Ping Wang, Pingchuan Wang, Pingfeng Wang, Pingping Wang, Pintian Wang, Po-Jen Wang, Pu Wang, Q Wang, Q Z Wang, Qi Wang, Qi-Bing Wang, Qi-En Wang, Qi-Jia Wang, Qi-Qi Wang, Qian Wang, Qian-Liang Wang, Qian-Wen Wang, Qian-Zhu Wang, Qian-fei Wang, Qianbao Wang, Qiang Wang, Qiang-Sheng Wang, Qiangcheng Wang, Qianghu Wang, Qiangqiang Wang, Qianjin Wang, Qianliang Wang, Qianqian Wang, Qianrong Wang, Qianru Wang, Qianwen Wang, Qianxu Wang, Qiao Wang, Qiao-Ping Wang, Qiaohong Wang, Qiaoqi Wang, Qiaoqiao Wang, Qifan Wang, Qifei Wang, Qifeng Wang, Qigui Wang, Qihao Wang, Qihua Wang, Qijia Wang, Qiming Wang, Qin Wang, Qing Jun Wang, Qing K Wang, Qing Kenneth Wang, Qing Mei Wang, Qing Wang, Qing-Bin Wang, Qing-Dong Wang, Qing-Jin Wang, Qing-Liang Wang, Qing-Mei Wang, Qing-Yan Wang, Qing-Yuan Wang, Qing-Yun Wang, QingDong Wang, Qingchun Wang, Qingfa Wang, Qingfeng Wang, Qinghang Wang, Qingliang Wang, Qinglin Wang, Qinglu Wang, Qingming Wang, Qingping Wang, Qingqing Wang, Qingshi Wang, Qingshui Wang, Qingsong Wang, Qingtong Wang, Qingyong Wang, Qingyu Wang, Qingyuan Wang, Qingyun Wang, Qingzhong Wang, Qinqin Wang, Qinrong Wang, Qintao Wang, Qinwen Wang, Qinyun Wang, Qiong Wang, Qiqi Wang, Qirui Wang, Qishan Wang, Qiu-Ling Wang, Qiu-Xia Wang, Qiuhong Wang, Qiuli Wang, Qiuling Wang, Qiuning Wang, Qiuping Wang, Qiushi Wang, Qiuting Wang, Qiuyan Wang, Qiuyu Wang, Qiwei Wang, Qixue Wang, Qiyu Wang, Qiyuan Wang, Quan Wang, Quan-Ming Wang, Quanli Wang, Quanren Wang, Quanxi Wang, Qun Wang, Qunxian Wang, Qunzhi Wang, R Wang, Ran Wang, Ranjing Wang, Ranran Wang, Re-Hua Wang, Ren Wang, Rencheng Wang, Renjun Wang, Renqian Wang, Renwei Wang, Renxi Wang, Renxiao Wang, Renyuan Wang, Rihua Wang, Rikang Wang, Rixiang Wang, Robert Yl Wang, Rong Wang, Rong-Chun Wang, Rong-Rong Wang, Rong-Tsorng Wang, RongRong Wang, Rongjia Wang, Rongping Wang, Rongyun Wang, Ru Wang, RuNan Wang, Ruey-Yun Wang, Rufang Wang, Ruhan Wang, Rui Wang, Rui-Hong Wang, Rui-Min Wang, Rui-Ping Wang, Rui-Rui Wang, Ruibin Wang, Ruibing Wang, Ruibo Wang, Ruicheng Wang, Ruifang Wang, Ruijing Wang, Ruimeng Wang, Ruimin Wang, Ruiming Wang, Ruinan Wang, Ruining Wang, Ruiquan Wang, Ruiwen Wang, Ruixian Wang, Ruixin Wang, Ruixuan Wang, Ruixue Wang, Ruiying Wang, Ruizhe Wang, Ruizhi Wang, Rujie Wang, Ruling Wang, Ruming Wang, Runci Wang, Runuo Wang, Runze Wang, Runzhi Wang, Ruo-Nan Wang, Ruo-Ran Wang, Ruonan Wang, Ruosu Wang, Ruoxi Wang, Rurong Wang, Ruting Wang, Ruxin Wang, Ruxuan Wang, Ruyue Wang, S L Wang, S S Wang, S Wang, S X Wang, Sa A Wang, Sa Wang, Saifei Wang, Saili Wang, Sainan Wang, Saisai Wang, Sangui Wang, Sanwang Wang, Sasa Wang, Sen Wang, Seok Mui Wang, Seungwon Wang, Sha Wang, Shan Wang, Shan-Shan Wang, Shang Wang, Shangyu Wang, Shanshan Wang, Shao-Kang Wang, Shaochun Wang, Shaohsu Wang, Shaokun Wang, Shaoli Wang, Shaolian Wang, Shaoshen Wang, Shaowei Wang, Shaoyi Wang, Shaoying Wang, Shaoyu Wang, Shaozheng Wang, Shasha Wang, Shau-Chun Wang, Shawn Wang, Shen Wang, Shen-Nien Wang, Shenao Wang, Sheng Wang, Sheng-Min Wang, Sheng-Nan Wang, Sheng-Ping Wang, Sheng-Quan Wang, Sheng-Yang Wang, Shengdong Wang, Shengjie Wang, Shengli Wang, Shengqi Wang, Shengya Wang, Shengyao Wang, Shengyu Wang, Shengyuan Wang, Shenqi Wang, Sheri Wang, Shi Wang, Shi-Cheng Wang, Shi-Han Wang, Shi-Qi Wang, Shi-Xin Wang, Shi-Yao Wang, Shibin Wang, Shichao Wang, Shicung Wang, Shidong Wang, Shifa Wang, Shifeng Wang, Shih-Wei Wang, Shihan Wang, Shihao Wang, Shihua Wang, Shijie Wang, Shijin Wang, Shijun Wang, Shikang Wang, Shimiao Wang, Shiqi Wang, Shiqiang Wang, Shitao Wang, Shitian Wang, Shiwen Wang, Shixin Wang, Shixuan Wang, Shiyang Wang, Shiyao Wang, Shiyin Wang, Shiyu Wang, Shiyuan Wang, Shiyue Wang, Shizhi Wang, Shouli Wang, Shouling Wang, Shouzhi Wang, Shu Wang, Shu-Huei Wang, Shu-Jin Wang, Shu-Ling Wang, Shu-Na Wang, Shu-Song Wang, Shu-Xia Wang, Shu-qiang Wang, Shuai Wang, Shuaiqin Wang, Shuang Wang, Shuang-Shuang Wang, Shuang-Xi Wang, Shuangyuan Wang, Shubao Wang, Shudan Wang, Shuge Wang, Shuguang Wang, Shuhe Wang, Shuiliang Wang, Shuiyun Wang, Shujin Wang, Shukang Wang, Shukui Wang, Shun Wang, Shuning Wang, Shunjun Wang, Shunran Wang, Shuo Wang, Shuping Wang, Shuqi Wang, Shuqing Wang, Shuren Wang, Shusen Wang, Shusheng Wang, Shushu Wang, Shuu-Jiun Wang, Shuwei Wang, Shuxia Wang, Shuxin Wang, Shuya Wang, Shuye Wang, Shuyue Wang, Shuzhe Wang, Shuzhen Wang, Shuzhong Wang, Shyi-Gang P Wang, Si Wang, Sibo Wang, Sidan Wang, Sihua Wang, Sijia Wang, Silas L Wang, Silu Wang, Simeng Wang, Siqi Wang, Siqing Wang, Siwei Wang, Siyang Wang, Siyi Wang, Siying Wang, Siyu Wang, Siyuan Wang, Siyue Wang, Song Wang, Songjiao Wang, Songlin Wang, Songping Wang, Songsong Wang, Songtao Wang, Sophie H Wang, Stephani Wang, Su'e Wang, Su-Guo Wang, Su-Hua Wang, Sufang Wang, Sugai Wang, Sui Wang, Suiyan Wang, Sujie Wang, Sujuan Wang, Suli Wang, Sun Wang, Supeng Perry Wang, Suxia Wang, Suyun Wang, Suzhen Wang, T Q Wang, T Wang, T Y Wang, Taian Wang, Taicheng Wang, Taishu Wang, Tammy C Wang, Tao Wang, Taoxia Wang, Teng Wang, Tengfei Wang, Theodore Wang, Thomas T Y Wang, Tian Wang, Tian-Li Wang, Tian-Lu Wang, Tian-Tian Wang, Tian-Yi Wang, Tiancheng Wang, Tiange Wang, Tianhao Wang, Tianhu Wang, Tianhui Wang, Tianjing Wang, Tianjun Wang, Tianlin Wang, Tiannan Wang, Tianpeng Wang, Tianqi Wang, Tianqin Wang, Tianqing Wang, Tiansheng Wang, Tiansong Wang, Tiantian Wang, Tianyi Wang, Tianying Wang, Tianyuan Wang, Tielin Wang, Tienju Wang, Tieqiao Wang, Timothy C Wang, Ting Chen Wang, Ting Wang, Ting-Chen Wang, Ting-Hua Wang, Ting-Ting Wang, Tingting Wang, Tingye Wang, Tingyu Wang, Tom J Wang, Tong Wang, Tong-Hong Wang, Tongsong Wang, Tongtong Wang, Tongxia Wang, Tongxin Wang, Tongyao Wang, Tony Wang, Tzung-Dau Wang, Victoria Wang, Vivian Wang, W Wang, Wanbing Wang, Wanchun Wang, Wang Wang, Wangxia Wang, Wanliang Wang, Wanxia Wang, Wanyao Wang, Wanyi Wang, Wanyu Wang, Wayseen Wang, Wei Wang, Wei-En Wang, Wei-Feng Wang, Wei-Lien Wang, Wei-Qi Wang, Wei-Ting Wang, Wei-Wei Wang, Weicheng Wang, Weiding Wang, Weidong Wang, Weifan Wang, Weiguang Wang, Weihao Wang, Weihong Wang, Weihua Wang, Weijian Wang, Weijie Wang, Weijun Wang, Weilin Wang, Weiling Wang, Weilong Wang, Weimin Wang, Weina Wang, Weining Wang, Weipeng Wang, Weiqin Wang, Weiqing Wang, Weirong Wang, Weiwei Wang, Weiwen Wang, Weixiao Wang, Weixue Wang, Weiyan Wang, Weiyu Wang, Weiyuan Wang, Weizhen Wang, Weizhi Wang, Weizhong Wang, Wen Wang, Wen-Chang Wang, Wen-Der Wang, Wen-Fei Wang, Wen-Jie Wang, Wen-Jun Wang, Wen-Qing Wang, Wen-Xuan Wang, Wen-Yan Wang, Wen-Ying Wang, Wen-Yong Wang, Wen-mei Wang, Wenbin Wang, Wenbo Wang, Wence Wang, Wenchao Wang, Wencheng Wang, Wendong Wang, Wenfei Wang, Wengong Wang, Wenhan Wang, Wenhao Wang, Wenhe Wang, Wenhui Wang, Wenjie Wang, Wenjing Wang, Wenju Wang, Wenjuan Wang, Wenjun Wang, Wenkai Wang, Wenkang Wang, Wenke Wang, Wenming Wang, Wenqi Wang, Wenqiang Wang, Wenqing Wang, Wenran Wang, Wenrui Wang, Wentao Wang, Wentian Wang, Wenting Wang, Wenwen Wang, Wenxia Wang, Wenxian Wang, Wenxiang Wang, Wenxiu Wang, Wenxuan Wang, Wenya Wang, Wenyan Wang, Wenyi Wang, Wenying Wang, Wenyu Wang, Wenyuan Wang, Wenzhou Wang, William Wang, Won-Jing Wang, Wu-Wei Wang, Wuji Wang, Wuqing Wang, Wusan Wang, X E Wang, X F Wang, X O Wang, X S Wang, X Wang, X-T Wang, Xi Wang, Xi-Hong Wang, Xi-Rui Wang, Xia Wang, Xian Wang, Xian-e Wang, Xianding Wang, Xianfeng Wang, Xiang Wang, Xiang-Dong Wang, Xiangcheng Wang, Xiangding Wang, Xiangdong Wang, Xiangguo Wang, Xianghua Wang, Xiangkun Wang, Xiangrong Wang, Xiangru Wang, Xiangwei Wang, Xiangyu Wang, Xianna Wang, Xianqiang Wang, Xianrong Wang, Xianshi Wang, Xianshu Wang, Xiansong Wang, Xiantao Wang, Xianwei Wang, Xianxing Wang, Xianze Wang, Xianzhe Wang, Xianzong Wang, Xiao Ling Wang, Xiao Qun Wang, Xiao Wang, Xiao-Ai Wang, Xiao-Fei Wang, Xiao-Hui Wang, Xiao-Jie Wang, Xiao-Juan Wang, Xiao-Lan Wang, Xiao-Li Wang, Xiao-Lin Wang, Xiao-Ming Wang, Xiao-Pei Wang, Xiao-Qian Wang, Xiao-Qun Wang, Xiao-Tong Wang, Xiao-Xia Wang, Xiao-Yi Wang, Xiao-Yun Wang, Xiao-jian WANG, Xiao-liang Wang, Xiaobin Wang, Xiaobo Wang, Xiaochen Wang, Xiaochuan Wang, Xiaochun Wang, Xiaodan Wang, Xiaoding Wang, Xiaodong Wang, Xiaofang Wang, Xiaofei Wang, Xiaofen Wang, Xiaofeng Wang, Xiaogang Wang, Xiaohong Wang, Xiaohu Wang, Xiaohua Wang, Xiaohui Wang, Xiaojia Wang, Xiaojian Wang, Xiaojiao Wang, Xiaojie Wang, Xiaojing Wang, Xiaojuan Wang, Xiaojun Wang, Xiaokun Wang, Xiaole Wang, Xiaoli Wang, Xiaoliang Wang, Xiaolin Wang, Xiaoling Wang, Xiaolong Wang, Xiaolu Wang, Xiaolun Wang, Xiaoman Wang, Xiaomei Wang, Xiaomeng Wang, Xiaomin Wang, Xiaoming Wang, Xiaona Wang, Xiaonan Wang, Xiaoning Wang, Xiaoqi Wang, Xiaoqian Wang, Xiaoqin Wang, Xiaoqing Wang, Xiaoqiu Wang, Xiaoqun Wang, Xiaorong Wang, Xiaorui Wang, Xiaoshan Wang, Xiaosong Wang, Xiaotang Wang, Xiaoting Wang, Xiaotong Wang, Xiaowei Wang, Xiaowen Wang, Xiaowu Wang, Xiaoxia Wang, Xiaoxiao Wang, Xiaoxin Wang, Xiaoxin X Wang, Xiaoxuan Wang, Xiaoya Wang, Xiaoyan Wang, Xiaoyang Wang, Xiaoye Wang, Xiaoying Wang, Xiaoyu Wang, Xiaozhen Wang, Xiaozhi Wang, Xiaozhong Wang, Xiaozhu Wang, Xichun Wang, Xidi Wang, Xietong Wang, Xifeng Wang, Xifu Wang, Xijun Wang, Xike Wang, Xin Wang, Xin Wei Wang, Xin-Hua Wang, Xin-Liang Wang, Xin-Ming Wang, Xin-Peng Wang, Xin-Qun Wang, Xin-Shang Wang, Xin-Xin Wang, Xin-Yang Wang, Xin-Yue Wang, Xinbo Wang, Xinchang Wang, Xinchao Wang, Xinchen Wang, Xincheng Wang, Xinchun Wang, Xindi Wang, Xindong Wang, Xing Wang, Xing-Huan Wang, Xing-Jin Wang, Xing-Jun Wang, Xing-Lei Wang, Xing-Ping Wang, Xing-Quan Wang, Xingbang Wang, Xingchen Wang, Xingde Wang, Xingguo Wang, Xinghao Wang, Xinghui Wang, Xingjie Wang, Xingjin Wang, Xinglei Wang, Xinglong Wang, Xingqin Wang, Xinguo Wang, Xingxin Wang, Xingxing Wang, Xingye Wang, Xingyu Wang, Xingyue Wang, Xingyun Wang, Xinhui Wang, Xinjing Wang, Xinjun Wang, Xinke Wang, Xinkun Wang, Xinli Wang, Xinlin Wang, Xinlong Wang, Xinmei Wang, Xinqi Wang, Xinquan Wang, Xinran Wang, Xinrong Wang, Xinru Wang, Xinrui Wang, Xinshuai Wang, Xintong Wang, Xinwen Wang, Xinxin Wang, Xinyan Wang, Xinyang Wang, Xinye Wang, Xinyi Wang, Xinying Wang, Xinyu Wang, Xinyue Wang, Xinzhou Wang, Xiong Wang, Xiongjun Wang, Xiru Wang, Xitian Wang, Xiu-Lian Wang, Xiu-Ping Wang, Xiufen Wang, Xiujuan Wang, Xiujun Wang, Xiurong Wang, Xiuwen Wang, Xiuyu Wang, Xiuyuan Hugh Wang, Xixi Wang, Xixiang Wang, Xiyan Wang, Xiyue Wang, Xizhi Wang, Xu Wang, Xu-Hong Wang, Xuan Wang, Xuan-Ren Wang, Xuan-Ying Wang, Xuanwen Wang, Xuanyi Wang, Xubo Wang, Xudong Wang, Xue Wang, Xue-Feng Wang, Xue-Hua Wang, Xue-Lei Wang, Xue-Lian Wang, Xue-Rui Wang, Xue-Yao Wang, Xue-Ying Wang, Xuebin Wang, Xueding Wang, Xuedong Wang, Xuefei Wang, Xuefeng Wang, Xueguo Wang, Xuehao Wang, Xuejie Wang, Xuejing Wang, Xueju Wang, Xuejun Wang, Xuekai Wang, Xuelai Wang, Xuelian Wang, Xuelin Wang, Xuemei Wang, Xuemin Wang, Xueping Wang, Xueqian Wang, Xueqin Wang, Xuesong Wang, Xueting Wang, Xuewei Wang, Xuewen Wang, Xuexiang Wang, Xueyan Wang, Xueyi Wang, Xueying Wang, Xueyun Wang, Xuezhen Wang, Xuezheng Wang, Xufei Wang, Xujing Wang, Xuliang Wang, Xumeng Wang, Xun Wang, Xuping Wang, Xuqiao Wang, Xuru Wang, Xusheng Wang, Xv Wang, Y Alan Wang, Y B Wang, Y H Wang, Y L Wang, Y P Wang, Y Wang, Y Y Wang, Y Z Wang, Y-H Wang, Y-S Wang, Ya Qi Wang, Ya Wang, Ya Xing Wang, Ya-Han Wang, Ya-Jie Wang, Ya-Long Wang, Ya-Nan Wang, Ya-Ping Wang, Ya-Qin Wang, Ya-Zhou Wang, Yachen Wang, Yachun Wang, Yadong Wang, Yafang Wang, Yafen Wang, Yahong Wang, Yahui Wang, Yajie Wang, Yajing Wang, Yajun Wang, Yake Wang, Yakun Wang, Yali Wang, Yalin Wang, Yaling Wang, Yalong Wang, Yan Ming Wang, Yan Wang, Yan-Chao Wang, Yan-Chun Wang, Yan-Feng Wang, Yan-Ge Wang, Yan-Jiang Wang, Yan-Jun Wang, Yan-Ming Wang, Yan-Yang Wang, Yan-Yi Wang, Yan-Zi Wang, Yana Wang, Yanan Wang, Yanbin Wang, Yanbing Wang, Yanchun Wang, Yancun Wang, Yanfang Wang, Yanfei Wang, Yanfeng Wang, Yang Wang, Yang-Yang Wang, Yange Wang, Yanggan Wang, Yangpeng Wang, Yangyang Wang, Yangyufan Wang, Yanhai Wang, Yanhong Wang, Yanhua Wang, Yanhui Wang, Yani Wang, Yanjin Wang, Yanjun Wang, Yankun Wang, Yanlei Wang, Yanli Wang, Yanliang Wang, Yanlin Wang, Yanling Wang, Yanmei Wang, Yanming Wang, Yanni Wang, Yanong Wang, Yanping Wang, Yanqing Wang, Yanru Wang, Yanting Wang, Yanwen Wang, Yanxia Wang, Yanxing Wang, Yanyang Wang, Yanyun Wang, Yanzhe Wang, Yanzhu Wang, Yao Wang, Yaobin Wang, Yaochun Wang, Yaodong Wang, Yaohe Wang, Yaokun Wang, Yaoling Wang, Yaolou Wang, Yaoxian Wang, Yaoxing Wang, Yaozhi Wang, Yapeng Wang, Yaping Wang, Yaqi Wang, Yaqian Wang, Yaqiong Wang, Yaru Wang, Yatao Wang, Yating Wang, Yawei Wang, Yaxian Wang, Yaxin Wang, Yaxiong Wang, Yaxuan Wang, Yayu Wang, Yazhou Wang, Ye Wang, Ye-Ran Wang, Yefu Wang, Yeh-Han Wang, Yehan Wang, Yeming Wang, Yen-Feng Wang, Yen-Sheng Wang, Yeou-Lih Wang, Yeqi Wang, Yezhou Wang, Yi Fan Wang, Yi Lei Wang, Yi Wang, Yi-Cheng Wang, Yi-Chuan Wang, Yi-Ming Wang, Yi-Ni Wang, Yi-Ning Wang, Yi-Shan Wang, Yi-Shiuan Wang, Yi-Shu Wang, Yi-Tao Wang, Yi-Ting Wang, Yi-Wen Wang, Yi-Xin Wang, Yi-Xuan Wang, Yi-Yi Wang, Yi-Ying Wang, Yi-Zhen Wang, Yi-sheng Wang, YiLi Wang, Yian Wang, Yibin Wang, Yibing Wang, Yichen Wang, Yicheng Wang, Yichuan Wang, Yifan Wang, Yifei Wang, Yigang Wang, Yige Wang, Yihan Wang, Yihao Wang, Yihe Wang, Yijin Wang, Yijing Wang, Yijun Wang, Yikang Wang, Yike Wang, Yilin Wang, Yilu Wang, Yimeng Wang, Yiming Wang, Yin Wang, Yin-Hu Wang, Yinan Wang, Yinbo Wang, Yindan Wang, Ying Wang, Ying-Piao Wang, Ying-Wei Wang, Ying-Zi Wang, Yingbo Wang, Yingcheng Wang, Yingchun Wang, Yingfei Wang, Yingge Wang, Yinggui Wang, Yingjie Wang, Yingmei Wang, Yingna Wang, Yingping Wang, Yingqiao Wang, Yingtai Wang, Yingte Wang, Yingwei Wang, Yingwen Wang, Yingxiong Wang, Yingxue Wang, Yingyi Wang, Yingying Wang, Yingzi Wang, Yinhuai Wang, Yining E Wang, Yinong Wang, Yinsheng Wang, Yintao Wang, Yinuo Wang, Yinxiong Wang, Yinyin Wang, Yiou Wang, Yipeng Wang, Yiping Wang, Yiqi Wang, Yiqiao Wang, Yiqin Wang, Yiqing Wang, Yiquan Wang, Yirong Wang, Yiru Wang, Yirui Wang, Yishan Wang, Yishu Wang, Yitao Wang, Yiting Wang, Yiwei Wang, Yiwen Wang, Yixi Wang, Yixian Wang, Yixuan Wang, Yiyan Wang, Yiyi Wang, Yiying Wang, Yizhe Wang, Yong Wang, Yong-Bo Wang, Yong-Gang Wang, Yong-Jie Wang, Yong-Jun Wang, Yong-Tang Wang, Yongbin Wang, Yongdi Wang, Yongfei Wang, Yongfeng Wang, Yonggang Wang, Yonghong Wang, Yongjie Wang, Yongjun Wang, Yongkang Wang, Yongkuan Wang, Yongli Wang, Yongliang Wang, Yonglun Wang, Yongmei Wang, Yongming Wang, Yongni Wang, Yongqiang Wang, Yongqing Wang, Yongrui Wang, Yongsheng Wang, Yongxiang Wang, Yongyi Wang, Yongzhong Wang, You Wang, Youhua Wang, Youji Wang, Youjie Wang, Youli Wang, Youzhao Wang, Youzhi Wang, Yu Qin Wang, Yu Tian Wang, Yu Wang, Yu'e Wang, Yu-Chen Wang, Yu-Fan Wang, Yu-Fen Wang, Yu-Hang Wang, Yu-Hui Wang, Yu-Ping Wang, Yu-Ting Wang, Yu-Wei Wang, Yu-Wen Wang, Yu-Ying Wang, Yu-Zhe Wang, Yu-Zhuo Wang, Yuan Wang, Yuan-Hung Wang, Yuanbo Wang, Yuanfan Wang, Yuanjiang Wang, Yuanli Wang, Yuanqiang Wang, Yuanqing Wang, Yuanyong Wang, Yuanyuan Wang, Yuanzhen Wang, Yubing Wang, Yubo Wang, Yuchen Wang, Yucheng Wang, Yuchuan Wang, Yudong Wang, Yue Wang, Yue-Min Wang, Yue-Nan Wang, YueJiao Wang, Yuebing Wang, Yuecong Wang, Yuegang Wang, Yuehan Wang, Yuehong Wang, Yuehu Wang, Yuehua Wang, Yuelong Wang, Yuemiao Wang, Yueshen Wang, Yueting Wang, Yuewei Wang, Yuexiang Wang, Yuexin Wang, Yueying Wang, Yueze Wang, Yufei Wang, Yufeng Wang, Yugang Wang, Yuh-Hwa Wang, Yuhan Wang, Yuhang Wang, Yuhua Wang, Yuhuai Wang, Yuhuan Wang, Yuhui Wang, Yujia Wang, Yujiao Wang, Yujie Wang, Yujiong Wang, Yulai Wang, Yulei Wang, Yuli Wang, Yuliang Wang, Yulin Wang, Yuling Wang, Yulong Wang, Yumei Wang, Yumeng Wang, Yumin Wang, Yuming Wang, Yun Wang, Yun Yong Wang, Yun-Hui Wang, Yun-Jin Wang, Yun-Xing Wang, Yunbing Wang, Yunce Wang, Yunchao Wang, Yuncong Wang, Yunduan Wang, Yunfang Wang, Yunfei Wang, Yunhan Wang, Yunhe Wang, Yunong Wang, Yunpeng Wang, Yunqiong Wang, Yuntai Wang, Yunzhang Wang, Yunzhe Wang, Yunzhi Wang, Yupeng Wang, Yuping Wang, Yuqi Wang, Yuqian Wang, Yuqiang Wang, Yuqin Wang, Yusha Wang, Yushe Wang, Yusheng Wang, Yutao Wang, Yuting Wang, Yuwei Wang, Yuwen Wang, Yuxiang Wang, Yuxing Wang, Yuxuan Wang, Yuxue Wang, Yuyan Wang, Yuyang Wang, Yuyin Wang, Yuying Wang, Yuyong Wang, Yuzhong Wang, Yuzhou Wang, Yuzhuo Wang, Z P Wang, Z Wang, Z-Y Wang, Zai Wang, Zaihua Wang, Ze Wang, Zechen Wang, Zehao Wang, Zehua Wang, Zekun Wang, Zelin Wang, Zeneng Wang, Zengtao Wang, Zeping Wang, Zexin Wang, Zeying Wang, Zeyu Wang, Zeyuan Wang, Zezhou Wang, Zhan Wang, Zhang Wang, Zhanggui Wang, Zhangshun Wang, Zhangying Wang, Zhanju Wang, Zhao Wang, Zhao-Jun Wang, Zhaobo Wang, Zhaofeng Wang, Zhaofu Wang, Zhaohai Wang, Zhaohui Wang, Zhaojing Wang, Zhaojun Wang, Zhaoming Wang, Zhaoqing Wang, Zhaosong Wang, Zhaotong Wang, Zhaoxi Wang, Zhaoxia Wang, Zhaoyu Wang, Zhe Wang, Zhehai Wang, Zhehao Wang, Zhen Wang, ZhenXue Wang, Zhenbin Wang, Zhenchang Wang, Zhenda Wang, Zhendan Wang, Zhendong Wang, Zheng Wang, Zhengbing Wang, Zhengchun Wang, Zhengdong Wang, Zhenghui Wang, Zhengkun Wang, Zhenglong Wang, Zhenguo Wang, Zhengwei Wang, Zhengxuan Wang, Zhengyang Wang, Zhengyi Wang, Zhengyu Wang, Zhenhua Wang, Zhenning Wang, Zhenqian Wang, Zhenshan Wang, Zhentang Wang, Zhenwei Wang, Zhenxi Wang, Zhenyu Wang, Zhenze Wang, Zhenzhen Wang, Zheyi Wang, Zheyue Wang, Zhezhi Wang, Zhi Wang, Zhi Xiao Wang, Zhi-Gang Wang, Zhi-Guo Wang, Zhi-Hao Wang, Zhi-Hong Wang, Zhi-Hua Wang, Zhi-Jian Wang, Zhi-Long Wang, Zhi-Qin Wang, Zhi-Wei Wang, Zhi-Xiao Wang, Zhi-Xin Wang, Zhibo Wang, Zhichao Wang, Zhicheng Wang, Zhicun Wang, Zhidong Wang, Zhifang Wang, Zhifeng Wang, Zhifu Wang, Zhigang Wang, Zhige Wang, Zhiguo Wang, Zhihao Wang, Zhihong Wang, Zhihua Wang, Zhihui Wang, Zhiji Wang, Zhijian Wang, Zhijie Wang, Zhijun Wang, Zhilun Wang, Zhimei Wang, Zhimin Wang, Zhipeng Wang, Zhiping Wang, Zhiqi Wang, Zhiqian Wang, Zhiqiang Wang, Zhiqing Wang, Zhiren Wang, Zhiruo Wang, Zhisheng Wang, Zhitao Wang, Zhiting Wang, Zhiwu Wang, Zhixia Wang, Zhixiang Wang, Zhixiao Wang, Zhixin Wang, Zhixing Wang, Zhixiong Wang, Zhixiu Wang, Zhiying Wang, Zhiyong Wang, Zhiyou Wang, Zhiyu Wang, Zhiyuan Wang, Zhizheng Wang, Zhizhong Wang, Zhong Wang, Zhong-Hao Wang, Zhong-Hui Wang, Zhong-Ping Wang, Zhong-Yu Wang, ZhongXia Wang, Zhongfang Wang, Zhongjing Wang, Zhongli Wang, Zhonglin Wang, Zhongqun Wang, Zhongsu Wang, Zhongwei Wang, Zhongyi Wang, Zhongyu Wang, Zhongyuan Wang, Zhongzhi Wang, Zhou Wang, Zhou-Ping Wang, Zhoufeng Wang, Zhouguang Wang, Zhuangzhuang Wang, Zhugang Wang, Zhulin Wang, Zhulun Wang, Zhuo Wang, Zhuo-Hui Wang, Zhuo-Jue Wang, Zhuo-Xin Wang, Zhuowei Wang, Zhuoying Wang, Zhuozhong Wang, Zhuqing Wang, Zi Wang, Zi Xuan Wang, Zi-Hao Wang, Zi-Qi Wang, Zi-Yi Wang, Zicheng Wang, Zifeng Wang, Zihan Wang, Ziheng Wang, Zihua Wang, Zihuan Wang, Zijian Wang, Zijie Wang, Zijue Wang, Zijun Wang, Zikang Wang, Zikun Wang, Ziliang Wang, Zilin Wang, Ziling Wang, Zilong Wang, Zining Wang, Ziping Wang, Ziqi Wang, Ziqian Wang, Ziqiang Wang, Ziqing Wang, Ziqiu Wang, Zitao Wang, Ziwei Wang, Zixi Wang, Zixia Wang, Zixian Wang, Zixiang Wang, Zixu Wang, Zixuan Wang, Ziyi Wang, Ziying Wang, Ziyu Wang, Ziyun Wang, Zongbao Wang, Zonggui Wang, Zongji Wang, Zongkui Wang, Zongqi Wang, Zongwei Wang, Zou Wang, Zulong Wang, Zumin Wang, Zun Wang, Zunxian Wang, Zuo Wang, Zuoheng Wang, Zuoyan Wang, Zusen Wang
articles
Wei Wang, Youwei Li, Liu Tang +8 more · 2024 · Cancer letters · Elsevier · added 2026-04-24
Branched-chain amino acid transferase 1 (BCAT1) is highly expressed in multiple cancers and is associated with poor prognosis, particularly in glioblastoma (GBM). However, the post-translational modif Show more
Branched-chain amino acid transferase 1 (BCAT1) is highly expressed in multiple cancers and is associated with poor prognosis, particularly in glioblastoma (GBM). However, the post-translational modification (PTM) mechanism of BCAT1 is unknown. Here, we investigated the cross-talk mechanisms between phosphorylation and ubiquitination modifications in regulating BCAT1 activity and stability. We found that BCAT1 is phosphorylated by branched chain ketoacid dehydrogenase kinase (BCKDK) at S5, S9, and T312, which increases its catalytic and antioxidant activity and stability. STUB1 (STIP1 homology U-box-containing protein 1), the first we found and reported E3 ubiquitin ligase of BCAT1, can also be phosphorylated by BCKDK at the S19 site, which disrupts the interaction with BCAT1 and inhibits its degradation. In addition, we demonstrate through in vivo and in vitro experiments that BCAT1 phosphorylation inhibiting its ubiquitination at multiple sites is associated with GBM proliferation and that inhibition of the BCKDK-BCAT1 axis enhances the sensitivity to temozolomide (TMZ). Overall, we identified novel mechanisms for the regulation of BCAT1 modification and elucidated the importance of the BCKDK-STUB1-BCAT1 axis in GBM progression. Show less
no PDF DOI: 10.1016/j.canlet.2024.216849
BCKDK
Aracely Acevedo, Anthony E Jones, Bezawit T Danna +10 more · 2024 · The Journal of biological chemistry · Elsevier · added 2026-04-24
Elevated levels of branched chain amino acids (BCAAs) and branched-chain α-ketoacids are associated with cardiovascular and metabolic disease, but the molecular mechanisms underlying a putative causal Show more
Elevated levels of branched chain amino acids (BCAAs) and branched-chain α-ketoacids are associated with cardiovascular and metabolic disease, but the molecular mechanisms underlying a putative causal relationship remain unclear. The branched-chain ketoacid dehydrogenase kinase (BCKDK) inhibitor BT2 (3,6-dichlorobenzo[b]thiophene-2-carboxylic acid) is often used in preclinical models to increase BCAA oxidation and restore steady-state BCAA and branched-chain α-ketoacid levels. BT2 administration is protective in various rodent models of heart failure and metabolic disease, but confoundingly, targeted ablation of Bckdk in specific tissues does not reproduce the beneficial effects conferred by pharmacologic inhibition. Here, we demonstrate that BT2, a lipophilic weak acid, can act as a mitochondrial uncoupler. Measurements of oxygen consumption, mitochondrial membrane potential, and patch-clamp electrophysiology show that BT2 increases proton conductance across the mitochondrial inner membrane independently of its inhibitory effect on BCKDK. BT2 is roughly sixfold less potent than the prototypical uncoupler 2,4-dinitrophenol and phenocopies 2,4-dinitrophenol in lowering de novo lipogenesis and mitochondrial superoxide production. The data suggest that the therapeutic efficacy of BT2 may be attributable to the well-documented effects of mitochondrial uncoupling in alleviating cardiovascular and metabolic disease. Show less
📄 PDF DOI: 10.1016/j.jbc.2024.105702
BCKDK
Li Chen, Hong Zhang, Mengyi Chi +14 more · 2024 · Molecular nutrition & food research · Wiley · added 2026-04-24
Branched chain amino acids (BCAAs) are essential amino acids and important nutrient signals for energy and protein supplementation. The study uses muscle-specific branched-chain α-keto acid dehydrogen Show more
Branched chain amino acids (BCAAs) are essential amino acids and important nutrient signals for energy and protein supplementation. The study uses muscle-specific branched-chain α-keto acid dehydrogenase kinase (Bckdk) conditional knockout (cKO) mice to reveal the contribution of BCAA metabolic dysfunction to muscle wasting. Muscle-specific Bckdk-cKO mice are generated through crossbreeding of Bckdk Dysfunctional BCAA metabolism contributes to the inhibition of protein synthesis and increases protein degradation in the cancer cachexia model of muscle-specific Bckdk-cKO mice bearing LLC tumors. The reprogramming of BCAA catabolism exerts therapeutic effects by stimulating protein synthesis and inhibiting protein degradation in skeletal muscle. Show less
no PDF DOI: 10.1002/mnfr.202300577
BCKDK
Liming Yu, Tao Huang, Jikai Zhao +10 more · 2024 · Free radical biology & medicine · Elsevier · added 2026-04-24
Metabolic reprogramming of vascular smooth muscle cell (VSMC) plays a critical role in the pathogenesis of thoracic aortic dissection (TAD). Previous researches have mainly focused on dysregulation of Show more
Metabolic reprogramming of vascular smooth muscle cell (VSMC) plays a critical role in the pathogenesis of thoracic aortic dissection (TAD). Previous researches have mainly focused on dysregulation of fatty acid or glucose metabolism, while the impact of amino acids catabolic disorder in VSMCs during the development of TAD remains elusive. Here, we identified branched-chain amino acid (BCAA) catabolic defect as a metabolic hallmark of TAD. The bioinformatics analysis and data from human aorta revealed impaired BCAA catabolism in TAD individuals. This was accompanied by upregulated branched-chain α-ketoacid dehydrogenase kinase (BCKDK) expression and BCKD E1 subunit alpha (BCKDHA) phosphorylation, enhanced vascular inflammation, and hyperactivation of mTOR signaling. Further in vivo experiments demonstrated that inhibition of BCKDK with BT2 (a BCKDK allosteric inhibitor) treatment dephosphorylated BCKDHA and re-activated BCAA catabolism, attenuated VSMCs phenotypic switching, alleviated aortic remodeling, mitochondrial reactive oxygen species (ROS) damage and vascular inflammation. Additionally, the beneficial actions of BT2 were validated in a TNF-α challenged murine VSMC cell line. Meanwhile, rapamycin conferred similar beneficial effects against VSMC phenotypic switching, cellular ROS damage as well as inflammatory response. However, co-treatment with MHY1485 (a classic mTOR activator) reversed the beneficial effects of BT2 by reactivating mTOR signaling. Taken together, the in vivo and in vitro evidence showed that impairment of BCAA catabolism resulted in aortic accumulation of BCAA and further caused VSMC phenotypic switching, mitochondrial ROS damage and inflammatory response via mTOR hyperactivation. BCKDK and mTOR signaling may serve as the potential drug targets for the prevention and treatment of TAD. Show less
no PDF DOI: 10.1016/j.freeradbiomed.2023.11.002
BCKDK
Zulfiqar Ahmed, Weixuan Xiang, Fuwen Wang +4 more · 2024 · Animal genetics · Blackwell Publishing · added 2026-04-24
Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattl Show more
Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattle breed remain elusive. This study utilized whole genome sequences of Kashmir cattle (n = 20; newly sequenced) alongside published whole genomes of 32 distinct breeds and seven core cattle populations (n = 135). The analysis identified ~25.87 million biallelic single nucleotide polymorphisms in Kashmir cattle, predominantly in intergenic and intron regions. Population structure analyses revealed distinct clustering patterns of Kashmir cattle with proximity to the South Asian, African and Chinese indicine cattle populations. Genetic diversity analysis of Kashmir cattle demonstrated lower inbreeding and greater nucleotide diversity than analyzed global breeds. Homozygosity runs indicated less consanguineous mating in Kashmir cattle compared with European taurine breeds. Furthermore, six selection sweep detection methods were used within Kashmir cattle and other cattle populations to identify genes associated with vital traits, including immunity (BOLA-DQA5, BOLA-DQB, TNFAIP8L, FCRL4, AOAH, HIF1AN, FBXL3, MPEG1, CDC40, etc.), reproduction (GOLGA4, BRWD1, OSBP2, LEO1 ADCY5, etc.), growth (ADPRHL1, NRG2, TCF12, TMOD4, GBP4, IGF2, RSPO3, SCD, etc.), milk composition (MRPS30 and CSF1) and high-altitude adaptation (EDNRA, ITPR2, AGBL4 and SCG3). These findings provide essential genetic insights into the characteristics and establish the foundation for the scientific conservation and utilization of Kashmir cattle breed. Show less
no PDF DOI: 10.1111/age.13434
BRWD1
Kang Xia, Yumin Hui, Long Zhang +6 more · 2024 · BMC biology · BioMed Central · added 2026-04-24
The role of histone methyltransferase SETDB1 in renal ischemia-reperfusion (I/R) injury has not been explored yet. This study aims to investigate the potential mechanism of SETDB1 in regulating renal Show more
The role of histone methyltransferase SETDB1 in renal ischemia-reperfusion (I/R) injury has not been explored yet. This study aims to investigate the potential mechanism of SETDB1 in regulating renal I/R injury and its impact on mitochondrial damage and oxidative stress. The in vivo model of renal I/R in mice and the in vitro model of hypoxia/reoxygenation (H/R) in human renal tubular epithelial cells (HK-2) were constructed to detect the expression of SETDB1. Next, the specific inhibitor (R,R)-59 and knockdown viruses were used to inhibit SETDB1 and verify its effects on mitochondrial damage and oxidative stress. Chromatin immunoprecipitation (ChIP) and coimmunoprecipitation (CoIP) were implemented to explore the in-depth mechanism of SETDB1 regulating renal I/R injury. The study found that SETDB1 had a regulatory role in mitochondrial damage and oxidative stress during renal I/R injury. Notably, SESN2 was identified as a target of SETDB1, and its expression was under the influence of SETDB1. Besides, SESN2 mediated the regulation of SETDB1 on renal I/R injury. Through deeper mechanistic studies, we uncovered that SETDB1 collaborates with heterochromatin HP1β, facilitating the labeling of H3K9me3 on the SESN2 promoter and impeding SESN2 expression. The SETDB1/HP1β-SESN2 axis emerges as a potential therapeutic strategy for mitigating renal I/R injury. Show less
📄 PDF DOI: 10.1186/s12915-024-02048-z
CBX1
Jinghuan Wang, Subei Tan, Yuyu Zhang +6 more · 2024 · Cell death and differentiation · Nature · added 2026-04-24
The aberrant expression of methyltransferase Set7/9 plays a role in various diseases. However, the contribution of Set7/9 in ischemic stroke remains unclear. Here, we show ischemic injury results in a Show more
The aberrant expression of methyltransferase Set7/9 plays a role in various diseases. However, the contribution of Set7/9 in ischemic stroke remains unclear. Here, we show ischemic injury results in a rapid elevation of Set7/9, which is accompanied by the downregulation of Sirt5, a deacetylase reported to protect against injury. Proteomic analysis identifies the decrease of chromobox homolog 1 (Cbx1) in knockdown Set7/9 neurons. Mechanistically, Set7/9 promotes the binding of Cbx1 to H3K9me2/3 and forms a transcription repressor complex at the Sirt5 promoter, ultimately repressing Sirt5 transcription. Thus, the deacetylation of Sirt5 substrate, glutaminase, which catalyzes the hydrolysis of glutamine to glutamate and ammonia, is decreased, promoting glutaminase expression and triggering excitotoxicity. Blocking Set7/9 eliminates H3K9me2/3 from the Sirt5 promoter and normalizes Sirt5 expression and Set7/9 knockout efficiently ameliorates brain ischemic injury by reducing the accumulation of ammonia and glutamate in a Sirt5-dependent manner. Collectively, the Set7/9-Sirt5 axis may be a promising epigenetic therapeutic target. Show less
no PDF DOI: 10.1038/s41418-024-01264-y
CBX1
Lingfeng Yang, Xiang Li, Yueze Wang +2 more · 2024 · IEEE transactions on pattern analysis and machine intelligence · IEEE · added 2026-04-24
Vision-Language Models (VLMs), such as CLIP, excel in zero-shot image-level visual understanding but struggle with object-based tasks requiring precise localization and recognition. Visual prompts, li Show more
Vision-Language Models (VLMs), such as CLIP, excel in zero-shot image-level visual understanding but struggle with object-based tasks requiring precise localization and recognition. Visual prompts, like colorful boxes or circles, are suggested to enhance local perception. However, these methods often include irrelevant and noisy pixels, leading to suboptimal performance. The design of better visual prompts and their collaboration with text prompting remains underexplored. This paper introduces Fine-Grained Visual Text Prompting (FGVTP), a new zero-shot framework for object-based tasks using precise semantic masks and reinforced image-text alignment. FGVTP comprises Fine-Grained Visual Prompting (FGVP) and Consistency-Enhanced Text Prompting (CETP). Specifically, we carefully study visual prompting designs by exploring more visual markings that vary in shape and form. FGVP uses semantic masks from a segmenter like the Segment Anything Model (SAM) and employs background blurring (Blur Reverse Mask) to highlight targets while maintaining spatial coherence. Further, CETP enhances image-text alignment by prompting captions based on FGVP-processed images. As a result, FGVTP achieves superior zero-shot referring expression comprehension on RefCOCO/+/g benchmarks, outperforming previous SOTA methods by 5.8% on average. Part detection experiments conducted on the PACO dataset further validate the preponderance of FGVTP over existing works. Code is available at https://github.com/ylingfeng/FGVP. Show less
no PDF DOI: 10.1109/TPAMI.2024.3504568
CETP
Lulu Sun, Qilu Zhang, Mengyao Shi +9 more · 2024 · Journal of the American Heart Association · added 2026-04-24
The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering dru Show more
The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering drug targets and the adverse prognosis of ischemic stroke patients remains unclear. Multiple single-nucleotide polymorphisms associated with 6 lipid-lowering drug targets were genotyped for patients with ischemic stroke. The primary outcome was death or major disability within 2 years after ischemic stroke. Genetic risk score was constructed from significant single-nucleotide polymorphisms identified via additive models, which was calculated by multiplying the number of risk alleles at each locus by the corresponding beta coefficient and then summing the products. The rs2006760-C of the rs2006760-C of Show less
📄 PDF DOI: 10.1161/JAHA.124.036544
CETP
Aernoud T L Fiolet, Michiel H F Poorthuis, Tjerk S J Opstal +25 more · 2024 · EClinicalMedicine · Elsevier · added 2026-04-24
Guidelines recommend low-dose colchicine for secondary prevention in cardiovascular disease, but uncertainty remains concerning its efficacy for stroke, efficacy in key subgroups and about uncommon bu Show more
Guidelines recommend low-dose colchicine for secondary prevention in cardiovascular disease, but uncertainty remains concerning its efficacy for stroke, efficacy in key subgroups and about uncommon but serious safety outcomes. In this trial-level meta-analysis, we searched bibliographic databases and trial registries form inception to May 16, 2024. We included randomised trials of colchicine for secondary prevention of ischaemic stroke and major adverse cardiovascular events (MACE: ischaemic stroke, myocardial infarction, coronary revascularisation, or cardiovascular death). Secondary outcomes were serious safety outcomes and mortality. A fixed-effect inverse-variance model was used to generate a pooled estimate of relative risk (RR) with 95% confidence intervals (CI). This study is registered with PROSPERO, CRD42024540320. Six trials involving 14,934 patients with prior stroke or coronary disease were included. In all patients, colchicine compared with placebo or no colchicine reduced the risk for ischaemic stroke by 27% (132 [1.8%] events versus 186 [2.5%] events, RR 0.73 [95% CI 0.58-0.90]) and MACE by 27% (505 [6.8%] events versus 693 [9.4%] events, with RR 0.73 [0.65-0.81]). Efficacy was consistent in key subgroups (females versus males, age below versus above 70, with versus without diabetes, statin versus non-statin users). Colchicine was not associated with an increase in serious safety outcomes: hospitalisation for pneumonia (109 [1.5%] versus 106 [1.5%], RR 0.99 [0.76-1.30]), cancer (247 [3.5%] versus 255 [3.6%], RR 0.97 [0.82-1.15]), and gastro-intestinal events (153 [2.1%] versus 135 [1.9%]), RR 1.15 [0.91-1.44]. There was no difference in all-cause death (201 [2.7%] versus 181 [2.4%], RR 1.09 [0.89-1.33]), cardiovascular death (70 [0.9%] versus 80 [1.1%], RR 0.89 [0.65-1.23]), or non-cardiovascular death (131 [1.8%] versus 101 [1.4%], RR 1.26 [0.98-1.64]). In patients with prior stroke or coronary disease, colchicine reduced ischaemic stroke and MACE, with consistent treatment effect in key subgroups, and did not increase serious safety events or death. There was no funding source for this study. Show less
📄 PDF DOI: 10.1016/j.eclinm.2024.102835
CETP
Frank Stappenbeck, Feng Wang, Satyesh K Sinha +8 more · 2024 · Cells · MDPI · added 2026-04-24
We previously reported that Oxy210, an oxysterol-based drug candidate, exhibits antifibrotic and anti-inflammatory properties. We also showed that, in mice, it ameliorates hepatic hallmarks of non-alc Show more
We previously reported that Oxy210, an oxysterol-based drug candidate, exhibits antifibrotic and anti-inflammatory properties. We also showed that, in mice, it ameliorates hepatic hallmarks of non-alcoholic steatohepatitis (NASH), including inflammation and fibrosis, and reduces adipose tissue inflammation. Here, we aim to investigate the effects of Oxy210 on atherosclerosis, an inflammatory disease of the large arteries that is linked to NASH in epidemiologic studies, shares many of the same risk factors, and is the major cause of mortality in people with NASH. Oxy210 was studied in vivo in APOE*3-Leiden.CETP mice, a humanized mouse model for both NASH and atherosclerosis, in which symptoms are induced by consumption of a high fat, high cholesterol "Western" diet (WD). Oxy210 was also studied in vitro using two cell types that are important in atherogenesis: human aortic endothelial cells (HAECs) and macrophages treated with atherogenic and inflammatory agents. Oxy210 reduced atherosclerotic lesion formation by more than 50% in hyperlipidemic mice fed the WD for 16 weeks. This was accompanied by reduced plasma cholesterol levels and reduced macrophages in lesions. In HAECs and macrophages, Oxy210 reduced the expression of key inflammatory markers associated with atherosclerosis, including interleukin-1 beta ( These findings suggest that Oxy210 could be a drug candidate for targeting both NASH and atherosclerosis, as well as chronic inflammation associated with the manifestations of metabolic syndrome. Show less
📄 PDF DOI: 10.3390/cells13191632
CETP
Yi Xie, Shuai Liu, Xinyue Wang +6 more · 2024 · Journal of the American Heart Association · added 2026-04-24
Serum lipids are causally involved in the occurrence of atherosclerosis, but their roles in cerebral small vessel disease remain unclear. This study aimed to investigate the causal roles of lipid or a Show more
Serum lipids are causally involved in the occurrence of atherosclerosis, but their roles in cerebral small vessel disease remain unclear. This study aimed to investigate the causal roles of lipid or apolipoprotein traits in cerebral small vessel disease and to determine the effects of lipid-lowering interventions on this disease. Data on genetic instruments of lipids/apolipoproteins, as well as characteristic cerebral small vessel disease manifestations, including small vessel stroke (SVS) and white matter hyperintensity (WMH), were obtained from publicly genome-wide association studies. Through 2-sample Mendelian randomization analyses, it was found that decreased levels of high-density lipoprotein cholesterol (odds ratio [OR], 0.85, The present Mendelian randomization study indicates that genetically determined hyperlipidemia is closely associated with a higher risk of cerebral small vessel disease, especially SVS. Lipid-lowering drugs could be potentially considered for the therapies and preventions of SVS rather than WMH. Show less
📄 PDF DOI: 10.1161/JAHA.123.032409
CETP
Yanfeng Liu, Liangying Deng, Feng Ding +7 more · 2024 · BMC chemistry · BioMed Central · added 2026-04-24
📄 PDF DOI: 10.1186/s13065-024-01222-2
CETP
Yumei Qiu, Mengdie Xie, Xiaoyun Ding +7 more · 2024 · Cureus · added 2026-04-24
Background and objectives Ginsenoside Re (Re), a protopanaxatriol-type saponin extracted from ginseng, is known to have potential cardioprotective effects; however, the mechanisms of Re in improving c Show more
Background and objectives Ginsenoside Re (Re), a protopanaxatriol-type saponin extracted from ginseng, is known to have potential cardioprotective effects; however, the mechanisms of Re in improving cardiac hypertrophy have not been fully elucidated. This study aimed to investigate the therapeutic effects and underlying mechanism of Re on isoproterenol (ISO)-induced cardiac hypertrophy Show less
📄 PDF DOI: 10.7759/cureus.59942
CETP
Xiaoke Ge, Bram Slütter, Joost M Lambooij +14 more · 2024 · iScience · Elsevier · added 2026-04-24
The liver X receptor (LXR) is considered a therapeutic target for atherosclerosis treatment, but synthetic LXR agonists generally also cause hepatic steatosis and hypertriglyceridemia. Desmosterol, a Show more
The liver X receptor (LXR) is considered a therapeutic target for atherosclerosis treatment, but synthetic LXR agonists generally also cause hepatic steatosis and hypertriglyceridemia. Desmosterol, a final intermediate in cholesterol biosynthesis, has been identified as a selective LXR ligand that suppresses inflammation without inducing lipogenesis. Δ24-Dehydrocholesterol reductase (DHCR24) converts desmosterol into cholesterol, and we previously showed that the DHCR24 inhibitor SH42 increases desmosterol to activate LXR and attenuate experimental peritonitis and metabolic dysfunction-associated steatotic liver disease. Here, we aimed to evaluate the effect of SH42 on atherosclerosis development in APOE∗3-Leiden.CETP mice and low-density lipoproteins (LDL) receptor knockout mice, models for lipid- and inflammation-driven atherosclerosis, respectively. In both models, SH42 increased desmosterol without affecting plasma lipids. While reducing liver lipids in APOE∗3-Leiden.CETP mice, and regulating populations of circulating monocytes in LDL receptor knockout mice, SH42 did not attenuate atherosclerosis in either model. Show less
📄 PDF DOI: 10.1016/j.isci.2024.109830
CETP
Xiaodi Yang, Jialin Zhu, Qingyun Wang +9 more · 2024 · mSystems · added 2026-04-24
A dysfunction of human host genes and proteins in coronavirus infectious disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key factor impacting clinic Show more
A dysfunction of human host genes and proteins in coronavirus infectious disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key factor impacting clinical symptoms and outcomes. Yet, a detailed understanding of human host immune responses is still incomplete. Here, we applied RNA sequencing to 94 samples of COVID-19 patients with and without hematological tumors as well as COVID-19 uninfected non-tumor individuals to obtain a comprehensive transcriptome landscape of both hematological tumor patients and non-tumor individuals. In our analysis, we further accounted for the human-SARS-CoV-2 protein interactome, human protein interactome, and human protein complex subnetworks to understand the mechanisms of SARS-CoV-2 infection and host immune responses. Our data sets enabled us to identify important SARS-CoV-2 (non-)targeted differentially expressed genes and complexes post-SARS-CoV-2 infection in both hematological tumor and non-tumor individuals. We found several unique differentially expressed genes, complexes, and functions/pathways such as blood coagulation (APOE, SERPINE1, SERPINE2, and TFPI), lipoprotein particle remodeling (APOC2, APOE, and CETP), and pro-B cell differentiation (IGHM, VPREB1, and IGLL1) during COVID-19 infection in patients with hematological tumors. In particular, APOE, a gene that is associated with both blood coagulation and lipoprotein particle remodeling, is not only upregulated in hematological tumor patients post-SARS-CoV-2 infection but also significantly expressed in acute dead patients with hematological tumors, providing clues for the design of future therapeutic strategies specifically targeting COVID-19 in patients with hematological tumors. Our data provide a rich resource for understanding the specific pathogenesis of COVID-19 in immunocompromised patients, such as those with hematological malignancies, and developing effective therapeutics for COVID-19. A majority of previous studies focused on the characterization of coronavirus infectious disease 2019 (COVID-19) disease severity in people with normal immunity, while the characterization of COVID-19 in immunocompromised populations is still limited. Our study profiles changes in the transcriptome landscape post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hematological tumor patients and non-tumor individuals. Furthermore, our integrative and comparative systems biology analysis of the interactome, complexome, and transcriptome provides new insights into the tumor-specific pathogenesis of COVID-19. Our findings confirm that SARS-CoV-2 potentially tends to target more non-functional host proteins to indirectly affect host immune responses in hematological tumor patients. The identified unique genes, complexes, functions/pathways, and expression patterns post-SARS-CoV-2 infection in patients with hematological tumors increase our understanding of how SARS-CoV-2 manipulates the host molecular mechanism. Our observed differential genes/complexes and clinical indicators of normal/long infection and deceased COVID-19 patients provide clues for understanding the mechanism of COVID-19 progression in hematological tumors. Finally, our study provides an important data resource that supports the increasing value of the application of publicly accessible data sets to public health. Show less
📄 PDF DOI: 10.1128/msystems.01385-23
CETP
Yanfeng Liu, Liangying Deng, Feng Ding +7 more · 2024 · BMC chemistry · BioMed Central · added 2026-04-24
Cholesteryl ester transfer protein (CETP) is a promising therapeutic target for cardiovascular diseases. It effectively lowers the low-density lipoprotein cholesterol levels and increases the high-den Show more
Cholesteryl ester transfer protein (CETP) is a promising therapeutic target for cardiovascular diseases. It effectively lowers the low-density lipoprotein cholesterol levels and increases the high-density lipoprotein cholesterol levels in the human plasma. This study identified novel and highly potent CETP inhibitors using virtual screening techniques. Molecular docking and molecular dynamics (MD) simulations revealed the binding patterns of these inhibitors, with the top 50 compounds selected according to their predicted binding affinity. Protein-ligand interaction analyses were performed, leading to the selection of 26 compounds for further evaluation. A CETP inhibition assay confirmed the inhibitory activities of the selected compounds. The results of the MD simulations revealed the structural stability of the protein-ligand complexes, with the binding site remaining significantly unchanged, indicating that the five compounds (AK-968/40709303, AG-690/11820117, AO-081/41378586, AK-968/12713193, and AN-465/14952302) identified have the potential as active CETP inhibitors and are promising leads for drug development. Show less
📄 PDF DOI: 10.1186/s13065-024-01192-5
CETP
Juanjuan Zou, Shengnan Qi, Xiaojing Sun +5 more · 2024 · Toxicology and applied pharmacology · Elsevier · added 2026-04-24
Obstructive sleep apnea (OSA) is considered to be an important contributor of dyslipidemia. However, there lacks observational studies focusing on the potential effect of lipid management on OSA risk. Show more
Obstructive sleep apnea (OSA) is considered to be an important contributor of dyslipidemia. However, there lacks observational studies focusing on the potential effect of lipid management on OSA risk. Thus, we aimed to investigate the genetic association of lipid-modifying therapy with risk of OSA. A drug-target mendelian randomization (MR) study using both cis-variants and cis-expression quantitative trait loci (eQTLs) of lipid-modifying drug targets was performed. The MR analyses used summary-level data of genome wide association studies (GWAS). Primary MR analysis was conducted using inverse-variance-weighted (IVW) method. Sensitivity analysis was performed using weighted median (WM) and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Genetically proxied low-density lipoprotein cholesterol (LDL-C)-lowering effect of cholesteryl ester transfer protein (CETP) was associated with reduced risk of OSA (odds ratio [OR] =0.75, 95% confidence interval [CI]: 0.60-0.94, false discovery rate [FDR] q value = 0.046). A significant MR association with risk of OSA was observed for CETP expression in subcutaneous adipose tissue (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049), lung (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049) and small intestine (OR = 0.96, 95%CI: 0.93-1.00, FDR q value = 0.049). No significant effects of high-density lipoprotein cholesterol (HDL-C)-raising effect of CETP inhibition, LDL-C-lowering and triglycerides-lowering effect of other drug targets on OSA risk were observed. The present study presented genetic evidence supporting the association of LDL-C-lowering therapy by CETP inhibition with reduced risk of OSA. These findings provided novel insights into the role of lipid management in patients with OSA and encouraged further clinical validations and mechanistic investigations. Show less
no PDF DOI: 10.1016/j.taap.2024.116909
CETP
Ying Ma, Xuesong Li, Jin Zhang +6 more · 2024 · Journal of leukocyte biology · Oxford University Press · added 2026-04-24
Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor response to all therapeutic modalities and dismal prognosis. The presence of tertiary lymphoid structures (TLSs) in various solid cance Show more
Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor response to all therapeutic modalities and dismal prognosis. The presence of tertiary lymphoid structures (TLSs) in various solid cancers is of crucial prognostic significance, highlighting the intricate interplay between the tumor microenvironment and immune cells aggregation. However, the extent to which TLSs and immune status affect PDAC prognosis remains incompletely understood. Here, we sought to unveil the unique properties of TLSs in PDAC by leveraging both single-cell and bulk transcriptomics, culminating in a risk model that predicts clinical outcomes. We used TLS scores based on a 12-gene (CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, and CXCL13) and 9-gene (PTGDS, RBP5, EIF1AY, CETP, SKAP1, LAT, CCR6, CD1D, and CD79B) signature, respectively, and examined their distribution in cell clusters of single-cell data from PDAC samples. The markers involved in these clusters were selected to develop a prognostic model using The Cancer Genome Atlas Program database as the training cohort and Gene Expression Omnibus database as the validation cohort. Further, we compared the immune infiltration, drug sensitivity, and enriched and differentially expressed genes between the high- and low-risk groups in our model. Therefore, we established a risk model that has significant implications for the prognostic assessment of PADC patients with remarkable differences in immune infiltration and chemosensitivity between the low- and high-risk groups. This paradigm established by TLS-related cell marker genes provides a prognostic prediction and a panel of novel therapeutic targets for exploring potential immunotherapy. Show less
no PDF DOI: 10.1093/jleuko/qiae067
CETP
Hongxuan Du, Kaiying He, Jing Zhao +3 more · 2024 · PeerJ · added 2026-04-24
Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established Show more
Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM) that is closely related to aging. In this study, we found co-differential genes between DKD and aging and established a diagnostic model of DKD based on these genes. Differentially expressed genes (DEGs) in DKD were screened using GEO datasets. The intersection of the DEGs of DKD and aging-related genes revealed DKD and aging co-differential genes. Based on this, a genetic diagnostic model for DKD was constructed using LASSO regression. The characteristics of these genes were investigated using consensus clustering, WGCNA, functional enrichment, and immune cell infiltration. Finally, the expression of diagnostic model genes was analyzed using single-cell RNA sequencing (scRNA-seq) in DKD mice (model constructed by streptozotocin (STZ) injection and confirmed by tissue section staining). First, there were 159 common differential genes between DKD and aging, 15 of which were significant. These co-differential genes were involved in stress, glucolipid metabolism, and immunological functions. Second, a genetic diagnostic model (including IGF1, CETP, PCK1, FOS, and HSPA1A) was developed based on these genes. Validation of these model genes in scRNA-seq data revealed statistically significant variations in FOS, HSPA1A, and PCK1 gene expression between the early DKD and control groups. Validation of these model genes in the kidneys of DKD mice revealed that Igf1, Fos, Pck1, and Hspa1a had lower expression in DKD mice, with Igf1 expression being statistically significant. Our findings suggest that DKD and aging co-differential genes are significant in DKD diagnosis, providing a theoretical basis for novel research directions on DKD. Show less
📄 PDF DOI: 10.7717/peerj.17046
CETP
Xiong Gao, Wei Luo, Liyuan Qu +14 more · 2024 · European journal of preventive cardiology · Oxford University Press · added 2026-04-24
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA Show more
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA remains controversial. The study aimed to investigate the genetic association between lipid-lowering drugs and AA. Our research used publicly available data on genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) studies. Genetic instruments, specifically eQTLs related to drug-target genes and SNPs (single nucleotide polymorphisms) located near or within the drug-target loci associated with low-density lipoprotein cholesterol (LDL-C), have been served as proxies for lipid-lowering medications. Drug-Target Mendelian Randomization (MR) study is used to determine the causal association between lipid-lowering drugs and different types of AA. The MR analysis revealed that higher expression of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase) was associated with increased risk of AA (OR = 1.58, 95% CI = 1.20-2.09, P = 1.20 × 10-03) and larger lumen size (aortic maximum area: OR = 1.28, 95% CI = 1.13-1.46, P = 1.48 × 10-04; aortic minimum area: OR = 1.26, 95% CI = 1.21-1.42, P = 1.78 × 10-04). PCSK9 (proprotein convertase subtilisin/kexin type 9) and CETP (cholesteryl ester transfer protein) show a suggestive relationship with AA (PCSK9: OR = 1.34, 95% CI = 1.10-1.63, P = 3.07 × 10-03; CETP: OR = 1.38, 95% CI = 1.06-1.80, P = 1.47 × 10-02). No evidence to support genetically mediated NPC1L1 (Niemann-Pick C1-Like 1) and LDLR (low-density lipoprotein cholesterol receptor) are associated with AA. This study provides causal evidence for the genetic association between lipid-lowering drugs and AA. Higher gene expression of HMGCR, PCSK9, and CETP increases AA risk. Furthermore, HMGCR inhibitors may link with smaller aortic lumen size. Show less
no PDF DOI: 10.1093/eurjpc/zwae044
CETP
Jiwei Jiang, Yaou Liu, Anxin Wang +11 more · 2024 · Chinese medical journal · added 2026-04-24
Few evidence is available in the early prediction models of behavioral and psychological symptoms of dementia (BPSD) in Alzheimer's disease (AD). This study aimed to develop and validate a novel genet Show more
Few evidence is available in the early prediction models of behavioral and psychological symptoms of dementia (BPSD) in Alzheimer's disease (AD). This study aimed to develop and validate a novel genetic-clinical-radiological nomogram for evaluating BPSD in patients with AD and explore its underlying nutritional mechanism. This retrospective study included 165 patients with AD from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) cohort between June 1, 2021, and March 31, 2022. Data on demographics, neuropsychological assessments, single-nucleotide polymorphisms of AD risk genes, and regional brain volumes were collected. A multivariate logistic regression model identified BPSD-associated factors, for subsequently constructing a diagnostic nomogram. This nomogram was internally validated through 1000-bootstrap resampling and externally validated using a time-series split based on the CIBL cohort data between June 1, 2022, and February 1, 2023. Area under receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to assess the discrimination, calibration, and clinical applicability of the nomogram. Factors independently associated with BPSD were: CETP rs1800775 (odds ratio [OR] = 4.137, 95% confidence interval [CI]: 1.276-13.415, P  = 0.018), decreased Mini Nutritional Assessment score (OR = 0.187, 95% CI: 0.086-0.405, P  <0.001), increased caregiver burden inventory score (OR = 8.993, 95% CI: 3.830-21.119, P  <0.001), and decreased brain stem volume (OR = 0.006, 95% CI: 0.001-0.191, P  = 0.004). These variables were incorporated into the nomogram. The area under the ROC curve was 0.925 (95% CI: 0.884-0.967, P  <0.001) in the internal validation and 0.791 (95% CI: 0.686-0.895, P  <0.001) in the external validation. The calibration plots showed favorable consistency between the prediction of nomogram and actual observations, and the DCA showed that the model was clinically useful in both validations. A novel nomogram was established and validated based on lipid metabolism-related genes, nutritional status, and brain stem volumes, which may allow patients with AD to benefit from early triage and more intensive monitoring of BPSD. Chictr.org.cn , ChiCTR2100049131. Show less
📄 PDF DOI: 10.1097/CM9.0000000000002914
CETP
Xiaoyang Chen, Lijuan Yang, Muhammad Farhan Aslam +5 more · 2024 · Journal of biomolecular structure & dynamics · Taylor & Francis · added 2026-04-24
Cardiovascular disease (CVD) is a group of diseases, affecting the human heart and accounting for 30% of deaths worldwide. Major CVDs include heart failure, hypertension, stroke, etc. Various therapeu Show more
Cardiovascular disease (CVD) is a group of diseases, affecting the human heart and accounting for 30% of deaths worldwide. Major CVDs include heart failure, hypertension, stroke, etc. Various therapeutics are available against CVD, still there is a dire need to find out potential protein drug targets to reduce economic burden and mortality rate. Goal of the current study was to utilize sequential computational techniques to find the best cardiovascular drug targets and their inhibitors. Common human cardiovascular targets of both databases (GeneCards and Uniprot) were subjected to bioinformatics analyses. Purpose was to validate putative therapeutic targets employing the structure-based bioinformatics methods to determine their physiochemical properties and biological processes. Three stable proteins, that have 0 transmembrane helices, and possess biological processes were screened as potential protein-based therapeutic targets: Hemoglobin subunit beta (HBB), Gamma-enolase (ENO2), and Cholesteryl ester transfer protein (CETP). Tertiary structures of target proteins were retrieved from PDB, and molecular docking technique was utilized to evaluate a library of 5000 phytochemicals against the interacting residues of the target protein as well as their respective standard drugs through MOE and Pyrx software. Top five phytochemicals (d-Sesamin, 1,3-benzodioxole, Sativanone, Thiamine, and Cajanol) were identified based on their RMSD and docking scores as compared to their standard drugs. The docking studies were also validated by MM-GBSA binding free energy and molecular dynamics simulations. According to the study's findings, these phytochemicals may eventually be used as drugs to treat CVD. Further Show less
no PDF DOI: 10.1080/07391102.2023.2239926
CETP
He Hao, Mingdong Yao, Ying Wang +6 more · 2024 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Cell phase engineering can significantly impact protein synthesis and cell size, potentially enhancing the production of lipophilic products. This study investigated the impact of G1 phase extension o Show more
Cell phase engineering can significantly impact protein synthesis and cell size, potentially enhancing the production of lipophilic products. This study investigated the impact of G1 phase extension on resource allocation, metabolic functions, and the unfolded protein response (UPR) in yeast, along with the potential for enhancing the production of lipophilic compounds. In brief, the regulation of the G1 phase was achieved by deleting Show less
📄 PDF DOI: 10.1073/pnas.2413486121
CLN3
Tufikameni Brima, Edward G Freedman, Kevin D Prinsloo +7 more · 2024 · Journal of neurodevelopmental disorders · BioMed Central · added 2026-04-24
We interrogated auditory sensory memory capabilities in individuals with CLN3 disease (juvenile neuronal ceroid lipofuscinosis), specifically for the feature of "duration" processing. Given decrements Show more
We interrogated auditory sensory memory capabilities in individuals with CLN3 disease (juvenile neuronal ceroid lipofuscinosis), specifically for the feature of "duration" processing. Given decrements in auditory processing abilities associated with later-stage CLN3 disease, we hypothesized that the duration-evoked mismatch negativity (MMN) of the event related potential (ERP) would be a marker of progressively atypical cortical processing in this population, with potential applicability as a brain-based biomarker in clinical trials. We employed three stimulation rates (fast: 450 ms, medium: 900 ms, slow: 1800 ms), allowing for assessment of the sustainability of the auditory sensory memory trace. The robustness of MMN directly relates to the rate at which the regularly occurring stimulus stream is presented. As presentation rate slows, robustness of the sensory memory trace diminishes. By manipulating presentation rate, the strength of the sensory memory trace is parametrically varied, providing greater sensitivity to detect auditory cortical dysfunction. A secondary hypothesis was that duration-evoked MMN abnormalities in CLN3 disease would be more severe at slower presentation rates, resulting from greater demand on the sensory memory system. Data from individuals with CLN3 disease (N = 21; range 6-28 years of age) showed robust MMN responses (i.e., intact auditory sensory memory processes) at the medium stimulation rate. However, at the fastest rate, MMN was significantly reduced, and at the slowest rate, MMN was not detectable in CLN3 disease relative to neurotypical controls (N = 41; ages 6-26 years). Results reveal emerging insufficiencies in this critical auditory perceptual system in individuals with CLN3 disease. Show less
📄 PDF DOI: 10.1186/s11689-023-09515-8
CLN3
Siyuan Chen, Qin Tang, Manqiu Hu +13 more · 2024 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Numerous studies have shown that metabolic reprogramming is crucial for the development of HCC. Carbamoyl phosphate synthase Show more
Hepatocellular carcinoma (HCC) is one of the most lethal cancers worldwide. Numerous studies have shown that metabolic reprogramming is crucial for the development of HCC. Carbamoyl phosphate synthase 1 (CPS1), a rate-limiting enzyme in urea cycle, is an abundant protein in normal hepatocytes, however, lacking systemic research in HCC. It is found that CPS1 is low-expressed in HCC tissues and circulating tumor cells, negatively correlated with HCC stage and prognosis. Further study reveals that CPS1 is a double-edged sword. On the one hand, it inhibits the activity of phosphatidylcholine-specific phospholipase C to block the biosynthesis of diacylglycerol (DAG), leading to the downregulation of the DAG/protein kinase C pathway to inhibit invasion and metastasis of cancer cells. On the other hand, CPS1 promotes cell proliferation by increasing intracellular S-adenosylmethionin to enhance the m6A modification of solute carrier family 1 member 3 mRNA, a key transporter for aspartate intake. Finally, CPS1 overexpressing adeno-associated virus can dampen HCC progression. Collectively, this results uncovered that CPS1 is a switch between HCC proliferation and metastasis by increasing intracellular aspartate level. Show less
📄 PDF DOI: 10.1002/advs.202402703
CPS1
Siyu Quan, Na Li, Shihai Lian +6 more · 2024 · International immunopharmacology · Elsevier · added 2026-04-24
Altered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD Show more
Altered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD) immunotherapy and prognosis was not entirely clear. We analyzed SLC4A4 expression in LUAD tissues and cell lines using quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. The effects of SLC4A4 overexpression on angiogenesis, cell migration, invasion, and epithelial-mesenchymal transition were examined. Public databases helped construct a risk model evaluating SLC4A4's expression on LUAD prognosis and immunotherapy response. Additionally, a xenograft model, flow cytometry, and enzyme-linked immunosorbent assay further explored SLC4A4's role in tumor immune microenvironment infiltration. Upregulation of SLC4A4 promoted apoptosis in the LUAD cell line and significantly inhibited the migration and invasive ability of cancer cells (P<0.01). A total of 10 key genes (including SIGLEC6, RHOV, PIR, MOB3B, MIR3135B, LPAR6, KRT8, ITGA2, CPS1, and C6) were screened according to SLC4A4 expression, immune score and stromal score, and a prognostic model with good outcome was constructed (AUC values of which in the training cohort at 1,3, and 5 years reached 0.73, 0.73, and 0.72, respectively). Importantly, we demonstrated that high expression of SLC4A4 was able to increase the proliferation level and cytokine secretion of CD8+ T cells for the purpose of promoting the immune system response to LUAD. Our study revealed that SLC4A4 can serve as a prognostic indicator for LUAD, providing new insights into the treatment and diagnosis of LUAD. Show less
no PDF DOI: 10.1016/j.intimp.2024.112756
CPS1
Ke Wang, Yuankui Zhu, Mengqing Li +7 more · 2024 · Biomaterials research · added 2026-04-24
Acute liver failure (ALF) is a complex syndrome that impairs the liver's function to detoxify bilirubin, ammonia, and other toxic metabolites. Bioartificial liver (BAL) aims to help ALF patients to pa Show more
Acute liver failure (ALF) is a complex syndrome that impairs the liver's function to detoxify bilirubin, ammonia, and other toxic metabolites. Bioartificial liver (BAL) aims to help ALF patients to pass through the urgent period by temporarily undertaking the liver's detoxification functions and promoting the recovery of the injured liver. We genetically modified the hepatocellular cell line HepG2 by stably overexpressing genes encoding UGT1A1, OATP1B1, OTC, ARG1, and CPS1. The resulting SynHeps-II cell line, encapsulated by Cytopore microcarriers, dramatically reduced the serum levels of bilirubin and ammonia, as demonstrated both in vitro using patient plasma and in vivo using ALF animal models. More importantly, we have also completed the 3-dimensional (3D) culturing of cells to meet the demands for industrialized rapid and mass production, and subsequently assembled the plasma-cell contacting BAL (PCC-BAL) system to fulfill the requirements of preclinical experiments. Extracorporeal blood purification of ALF rabbits with SynHeps-II-embedded PCC-BAL saved more than 80% of the animals from rapid death. Mechanistically, SynHeps-II therapy ameliorated liver and brain inflammation caused by high levels of bilirubin and ammonia and promoted liver regeneration by modulating the nuclear factor κB (NF-κB) and signal transducer and activator of transcription 3 (STAT3) pathways. Also, SynHeps-II treatment reduced cerebral infiltration of neutrophils, reduced reactive oxygen species (ROS) levels, and mitigated hepatic encephalopathy. Taken together, SynHeps-II cell-based BAL was promising for the treatment of ALF patients and warrants clinical trials. Show less
📄 PDF DOI: 10.34133/bmr.0043
CPS1
Yu Chen, Yupeng Jiang, Xionghui Li +6 more · 2024 · Translational lung cancer research · added 2026-04-24
Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung ade Show more
Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung adenocarcinoma (LUAD) has rarely been reported. Here, we established a novel prognostic model based on vitamin metabolism-related genes in LUAD. In this research, we aimed to identify vitamin metabolism associated with differentially expressed genes (DEGs) in LUAD utilizing The Cancer Genome Atlas (TCGA)-LUAD, GSE68465 and GSE72094 data. Unsupervised clustering classified patients into distinct subgroups. By utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis, vitamin metabolism-related genes could be used to construct prognostic model. Then the vitamin metabolism gene-related risk score (VRS) was calculated based on best cut-off splitting. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) analysis, univariate and multivariate Cox analyses, chemotherapeutic drugs sensitivity analysis, immune infiltration analysis and nomogram were conducted to verify our models' accuracy. Finally, CPS1 was identified as a relevant diagnostic marker using Random Forests algorithms, single-cell RNA sequencing data was used to confirm its expression. We investigated the relationship between vitamin metabolism patterns, overall survival (OS), and immune infiltration levels of patients with LUAD. A prognostic signature consisting of 11 genes was developed, which was able to classify patients into high and low VRS groups. Through gene enrichment analysis, cell cycle was mainly enriched. Compared to the low VRS group, the high VRS group exhibited poorer OS, as demonstrated by the Kaplan-Meier survival analysis. Furthermore, VRS was identified as an independent predictor of poor prognosis and poor OS, as indicated by both univariate and multivariate Cox regression analyses. Additionally, a nomogram was constructed to improve the accuracy of survival predictions in LUAD patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. CPS1 was identified as a relevant diagnostic marker and the expression was also as confirmed by single-cell RNA sequencing data. Overall, our findings suggest that vitamin metabolism can influence the prognosis of LUAD patients, and our prognostic signature represents a potentially helpful resource for predicting patient outcomes and informing clinical decision-making. Show less
📄 PDF DOI: 10.21037/tlcr-24-245
CPS1
Weizheng Liang, Xiangyu Yang, Xiushen Li +6 more · 2024 · Aging · Impact Journals · added 2026-04-24
Colon adenocarcinoma (COAD), a frequently encountered and highly lethal malignancy of the digestive system, has been the focus of intensive research regarding its prognosis. The intricate immune micro Show more
Colon adenocarcinoma (COAD), a frequently encountered and highly lethal malignancy of the digestive system, has been the focus of intensive research regarding its prognosis. The intricate immune microenvironment plays a pivotal role in the pathological progression of COAD; nevertheless, the underlying molecular mechanisms remain incompletely understood. This study aims to explore the immune gene expression patterns in COAD, construct a robust prognostic model, and delve into the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby providing critical support for individualized treatment strategies and prognostic evaluation. Initially, we curated a comprehensive dataset by screening 2600 immune-related genes (IRGs) from the ImmPort and InnateDB databases, successfully obtaining a rich data resource. Subsequently, the COAD patient cohort was classified using the non-negative matrix factorization (NMF) algorithm, enabling accurate categorization. Continuing on, utilizing the weighted gene co-expression network analysis (WGCNA) method, we analyzed the top 5000 genes with the smallest p-values among the differentially expressed genes (DEGs) between immune subtypes. Through this rigorous screening process, we identified the gene modules with the strongest correlation to the COAD subpopulation, and the intersection of genes in these modules with DEGs (COAD vs COAD vs Normal colon tissue) is referred to as Differentially Expressed Immune Genes Associated with COAD (DEIGRC). Employing diverse bioinformatics methodologies, we successfully developed a prognostic model (DPM) consisting of six genes derived from the DEIGRC, which was further validated across multiple independent datasets. Not only does this predictive model accurately forecast the prognosis of COAD patients, but it also provides valuable insights for formulating personalized treatment regimens. Within the constructed DPM, we observed a downregulation of CALB2 expression levels in COAD tissues, whereas NOXA1, KDF1, LARS2, GSR, and TIMP1 exhibited upregulated expression levels. These genes likely play indispensable roles in the initiation and progression of COAD and thus represent potential therapeutic targets for patient management. Furthermore, our investigation into the molecular mechanisms and therapeutic targets for COAD liver metastasis revealed associations with relevant processes such as fat digestion and absorption, cancer gene protein polysaccharides, and nitrogen metabolism. Consequently, genes including CAV1, ANXA1, CPS1, EDNRA, and GC emerge as promising candidates as therapeutic targets for COAD liver metastasis, thereby providing crucial insights for future clinical practices and drug development. In summary, this study uncovers the immune gene expression patterns in COAD, establishes a robust prognostic model, and elucidates the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby possessing significant theoretical and clinical implications. These findings are anticipated to offer substantial support for both the treatment and prognosis management of COAD patients. Show less
📄 PDF DOI: 10.18632/aging.205763
CPS1