👤 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, 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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
Wenhua Zhang, Ruiming Wang, Fangying Shi · 2024 · Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · Elsevier · added 2026-04-24
The purpose of this study is to the relationship between peripheral apolipoproteins and the prognosis of patients with acute ischemic stroke (AIS) after thrombolysis. A total of 231 AIS patients with Show more
The purpose of this study is to the relationship between peripheral apolipoproteins and the prognosis of patients with acute ischemic stroke (AIS) after thrombolysis. A total of 231 AIS patients with thrombolysis was enrolled. Serum apolipoproteins were measured on admission after thrombolysis. All patients enrolled were followed up for 90 days. Their functional outcomes were assessed by the modified Rankin Scale (mRS). Good functional outcome was considered as mRS < 3. Logistic regression was applied to assess the association between serum apolipoproteins and the mRS at 90 days. In multivariate analysis,1) ApoB (OR=0.099, 95%CI=0.017∼0.575, p=0.010) and ApoB/ApoA-1(OR=0.113, 95%CI=0.015∼0.868, p=0.036) were independent risk factors of good functional outcome at 90 days. 2). there were significant differences in the mRS score distribution at 90 days in groups according to the ROC cutoff values of ApoB (0.85g/L) and ApoB/ApoA-1 ratio (0.61) (all p<0.05). Our findings demonstrated ApoB and ApoB/apoA-1 ratio were independent risk factors for good functional outcome at 90 days, and the ApoB level below 0.85g/L and ApoB/ApoA-1 ratio below 0.61 could be associated with a better functional outcome in this study population. Show less
no PDF DOI: 10.1016/j.jstrokecerebrovasdis.2024.107944
APOB
Min Wang, Yanbin Liang, Yuce Qin +4 more · 2024 · Current pharmaceutical design · Bentham Science · added 2026-04-24
Diabetic cardiomyopathy (DCM) is a common diabetes complication with limited medications. Gegen Qinlian decoction (GQD) has been used in the treatment of diabetes and its related complications in Chin Show more
Diabetic cardiomyopathy (DCM) is a common diabetes complication with limited medications. Gegen Qinlian decoction (GQD) has been used in the treatment of diabetes and its related complications in China for several decades. In this study, network pharmacology was employed to predict the active ingredients, key targets, and pathways involved in the treatment of DCM by GQD and to validate it by animal experiments. The active ingredients of GQD were retrieved from TCMSP and published literature. DCM-related gene targets were searched in Drugbank, Genecards, Disgenet, and OMIM disease databases. Protein-protein interaction networks were constructed using the STRING database and Cytoscape. GO analysis and KEGG pathway enrichment analysis were performed using the Metascape platform. Moreover, a diabetic mouse model was established to evaluate the therapeutic effects of GQD by measuring serum biochemical markers and inflammation levels. Finally, the expression of predicted key target genes was determined using real-time quantitative PCR. A total of 129 active ingredients were screened from GQD. Moreover, 146 intersecting genes related to DCM were obtained, with key targets, including AKT1, TNF, IL6, and VEGFA. Lipid and atherosclerosis, AGE-RAGE, PI3K-AKT, and MAPK pathways were identified. Blood glucose control, decreased inflammatory factors, and serum CK-MB levels were restored after GQD intervention, and the same occurred with the expressions of PPAR-γ, AKT1, APOB, and GSK3B genes. Quercetin, kaempferol, wogonin, 7-methoxy-2-methyl isoflavone, and formononetin may exert major therapeutic effects by regulating key factors, such as AKT1, APOB, and GSK3B, in the inflammatory reaction, glycolipid oxidation, and glycogen synthesis related signaling pathways. Show less
no PDF DOI: 10.2174/0113816128312242240722080551
APOB
Yanhua Zhao, He Zhang, Shanshan Liang +2 more · 2024 · Clinica chimica acta; international journal of clinical chemistry · Elsevier · added 2026-04-24
Serum lipid profiles play a crucial role in diagnosing and evaluating cardiovascular diseases. However, the presence of paraprotein can lead to inaccurate dyslipidemia results on automated analyzers. Show more
Serum lipid profiles play a crucial role in diagnosing and evaluating cardiovascular diseases. However, the presence of paraprotein can lead to inaccurate dyslipidemia results on automated analyzers. A 65-year-old woman whose combined concentrations of HDL-cholesterol (HDL-C) and LDL-cholesterol (LDL-C) consistently surpassed her total serum cholesterol levels over a period of three months presented with unusual lipid component detection. Further analysis revealed the presence of a monoclonal paraprotein, identified as an IgMλ band, with a concentration of 28.0 g/L. The patient was subsequently diagnosed with Waldenström macroglobulinemia. The use of abnormal reaction kinetic curves and the β quantification method, along with an alternative method that did not suffer from interference, revealed that the monoclonal paraprotein interfered with the measurements of HDL-C, LDL-C, apolipoprotein A-I (apoA-I), and apolipoprotein B (apoB) when using the Roche detection system. This interference led to spurious elevated HDL-C concentrations and falsely decreased apoA-I and apoB concentrations, while the LDL-C results were minimally affected. Although diluting the sample normalized the HDL-C and LDL-C measurements, the interference with the apoA-I and apoB assays persisted. No other common biochemical tests were interfered with this paraprotein. Caution is advised when using a homogenous method for direct measurement of HDL-C and LDL-C in patients with monoclonal paraprotein. Techniques to recognize and eliminate this interference are available. However, immunoturbidimetric detection of apoA-I and apoB levels is also susceptible to this interference, which is not readily removable. Show less
no PDF DOI: 10.1016/j.cca.2024.119900
APOB
Yufeng Jin, Xin Wang, Ke Chen +10 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Despite centuries of traditional use of silymarin for hepatoprotection, current randomized controlled trial (RCT) studies on the effectiveness of silymarin in managing metabolic dysfunction-associated Show more
Despite centuries of traditional use of silymarin for hepatoprotection, current randomized controlled trial (RCT) studies on the effectiveness of silymarin in managing metabolic dysfunction-associated steatotic liver disease (MASLD) are limited and inconclusive, particularly when it is administered alone. The low bioavailability of silymarin highlights the possible influence of gut microbiota on the effectiveness of silymarin; however, no human studies have investigated this aspect. To determine the potential efficacy of silymarin in improving MASLD indicators and to investigate the underlying mechanisms related to gut microbiota. In this 24-week randomized, double-blind, placebo-controlled trial, 83 patients with MASLD were randomized to either placebo (n = 41) or silymarin (103.2 mg/d, n = 42). At 0, 12, and 24 weeks, liver stiffness and hepatic steatosis were assessed using FibroScan, and blood samples were gathered for biochemical detection, while faecal samples were collected at 0 and 24 weeks for 16S rRNA sequencing. Silymarin supplementation significantly reduced liver stiffness (LSM, -0.21 ± 0.17 vs. 0.41 ± 0.17, P = 0.015) and serum levels of γ-glutamyl transpeptidase (GGT, -8.21 ± 3.01 vs. 1.23 ± 3.16, P = 0.042) and ApoB (-0.02 ± 0.03 vs. 0.07 ± 0.03, P = 0.023) but had no significant effect on the controlled attenuation parameter (CAP), other biochemical indicators (aminotransferases, total bilirubin, glucose and lipid parameters, hsCRP, SOD, and UA), physical measurements (DBP, SBP, BMI, WHR, BF%, and BMR), or APRI and FIB-4 indices. Gut microbiota analysis revealed increased species diversity and enrichment of Oscillospiraceae in the silymarin group. These findings suggest that silymarin supplementation could improve liver stiffness in MASLD patients, possibly by modulating the gut microbiota. The trial was registered at the Chinese Clinical Trial Registry (ChiCTR2200059043). Show less
📄 PDF DOI: 10.1186/s12944-024-02220-y
APOB
Zhenqiu Liu, Huangbo Yuan, Yunzhi Wang +5 more · 2024 · Journal of proteome research · ACS Publications · added 2026-04-24
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint pot Show more
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection. Show less
no PDF DOI: 10.1021/acs.jproteome.4c00397
APOB
Danyang Zhao, Xiaoli Han, Qingshuang Mu +7 more · 2024 · Nutrition & metabolism · BioMed Central · added 2026-04-24
Apoprotein A-I (ApoA-I) and Apoprotein B (ApoB) have emerged as novel cardiovascular risk biomarkers influenced by feeding behavior. Hypothalamic appetite peptides regulate feeding behavior and impact Show more
Apoprotein A-I (ApoA-I) and Apoprotein B (ApoB) have emerged as novel cardiovascular risk biomarkers influenced by feeding behavior. Hypothalamic appetite peptides regulate feeding behavior and impact lipoprotein levels, which effects vary in different weight states. This study explores the intricate relationship between body mass index (BMI), hypothalamic appetite peptides, and apolipoproteins with emphasis on the moderating role of body weight in the association between neuropeptide Y (NPY), ghrelin, orexin A (OXA), oxytocin in cerebrospinal fluid (CSF) and peripheral ApoA-I and ApoB. In this cross-sectional study, we included participants with a mean age of 31.77 ± 10.25 years, categorized into a normal weight (NW) (n = 73) and an overweight/obese (OW/OB) (n = 117) group based on BMI. NPY, ghrelin, OXA, and oxytocin levels in CSF were measured. In the NW group, peripheral ApoA-I levels were higher, while ApoB levels were lower than in the OW/OB group (all p < 0.05). CSF NPY exhibited a positive correlation with peripheral ApoA-I in the NW group (r = 0.39, p = 0.001). Notably, participants with higher CSF NPY levels had higher peripheral ApoA-I levels in the NW group and lower peripheral ApoA-I levels in the OW/OB group, showing the significant moderating effect of BMI on this association (R This study provides hitherto undocumented evidence that BMI moderates the relationship between CSF NPY and peripheral ApoA-I levels. It also reveals the protective role of NPY in the NW population, contrasting with its risk factor role in the OW/OB population, which was associated with the at-risk for cardiovascular disease. Show less
📄 PDF DOI: 10.1186/s12986-024-00828-6
APOB
Li Sun, Jing-Xian Wang, Jing Ma +7 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Proprotein convertase subtilisins/kexin 6 (PCSK6) polymorphisms have been shown to be associated with atherosclerosis progression. This research aimed to evaluate the relationship of PCSK6 rs1531817 p Show more
Proprotein convertase subtilisins/kexin 6 (PCSK6) polymorphisms have been shown to be associated with atherosclerosis progression. This research aimed to evaluate the relationship of PCSK6 rs1531817 polymorphisms with coronary stenosis and the prognosis in premature myocardial infarction (PMI) patients. This prospective cohort analysis consecutively included 605 PMI patients who performed emergency percutaneous coronary intervention (PCI) at Tianjin Chest Hospital sequentially between January 2017 and August 2022, with major adverse cardiovascular events (MACEs) as the outcome. Analyses assessed the relationships among PCSK6 rs1531817 polymorphism, Gensini score (GS), triple vessel disease (TVD), and MACEs. 92 (16.8%) patients experienced MACEs with an average follow-up of 25.7 months. Logistic analysis revealed that the PCSK6 rs1531817 CA + AA genotype was an independent protective factor against high GS and TVD. Cox analysis revealed that the PCSK6 rs1531817 CA + AA genotype was an independent protective factor against MACEs. The mediation effect results showed that apolipoprotein A1/apolipoprotein B (ApoA1/ApoB) partially mediated the association between PCSK6 rs1531817 polymorphism and coronary stenosis and that total cholesterol/high-density lipoprotein (TC/HDL) and TVD partially and in parallel mediated the association between the PCSK6 rs1531817 polymorphism and MACEs. Patients with the PCSK6 CA + AA genotype have milder coronary stenosis and a better long-term prognosis; according to the mediation model, ApoA1/ApoB and TC/HDL partially mediate. These results may provide a new perspective on clinical therapeutic strategy for anti-atherosclerosis and improved prognosis in PMI patients. Show less
📄 PDF DOI: 10.1186/s12944-024-02206-w
APOB
Lisandro D Colantonio, Zhixin Wang, Jenna Jones +7 more · 2024 · JACC. Advances · Elsevier · added 2026-04-24
Low-density lipoprotein cholesterol (LDL-C) is used to guide lipid-lowering therapy after a myocardial infarction (MI). Lack of LDL-C testing represents a missed opportunity for optimizing therapy and Show more
Low-density lipoprotein cholesterol (LDL-C) is used to guide lipid-lowering therapy after a myocardial infarction (MI). Lack of LDL-C testing represents a missed opportunity for optimizing therapy and reducing cardiovascular risk. The purpose of this study was to estimate the proportion of Medicare beneficiaries who had their LDL-C measured within 90 days following MI hospital discharge. We conducted a retrospective cohort study of Medicare beneficiaries ≥66 years of age with an MI hospitalization between 2016 and 2020. The primary analysis used data from all beneficiaries with fee-for-service coverage and pharmacy benefits (532,767 MI hospitalizations). In secondary analyses, we used data from a 5% random sample of beneficiaries with fee-for-service coverage without pharmacy benefits (10,394 MI hospitalizations), and from beneficiaries with Medicare Advantage (176,268 MI hospitalizations). The proportion of beneficiaries who had their LDL-C measured following MI hospital discharge was estimated accounting for the competing risk of death. In the primary analysis (mean age 76.9 years, 84.4% non-Hispanic White), 29.9% of beneficiaries had their LDL-C measured within 90 days following MI hospital discharge. Among Hispanic, Asian, non-Hispanic White, and non-Hispanic Black beneficiaries, the 90-day postdischarge LDL-C testing was 33.8%, 32.5%, 30.0%, and 26.0%, respectively. Postdischarge LDL-C testing within 90 days was highest in the Middle Atlantic (36.4%) and lowest in the West North Central (23.4%) U.S. regions. In secondary analyses, the 90-day postdischarge LDL-C testing was 26.9% among beneficiaries with fee-for-service coverage without pharmacy benefits, and 28.6% among beneficiaries with Medicare Advantage coverage. LDL-C testing following MI hospital discharge among Medicare beneficiaries was low. Show less
📄 PDF DOI: 10.1016/j.jacadv.2023.100753
APOB
Su-Guo Wang, Yong-Gang Wang, Guo-Wei Qian +8 more · 2024 · Current medical science · Springer · added 2026-04-24
To investigate the serum lipid profiles of patients with localized osteosarcoma around the knee joint before and after neoadjuvant chemotherapy. After retrospectively screening the data of 742 patient Show more
To investigate the serum lipid profiles of patients with localized osteosarcoma around the knee joint before and after neoadjuvant chemotherapy. After retrospectively screening the data of 742 patients between January 2007 and July 2020, 50 patients aged 13 to 39 years with Enneking stage II disease were included in the study. Serum lipid levels, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), lipoprotein-α [Lp(a)], and apolipoprotein A1, B, and E (ApoA1, ApoB, and ApoE), and clinicopathological characteristics were collected before and after neoadjuvant chemotherapy. The mean levels of TC, TG, and ApoB were significantly increased following neoadjuvant chemotherapy (16%, 38%, and 20%, respectively, vs. pretreatment values; P<0.01). The mean levels of LDL-C and ApoE were also 19% and 16% higher, respectively (P<0.05). No correlation was found between the pretreatment lipid profile and the histologic response to chemotherapy. An increase in Lp(a) was strongly correlated with the Ki-67 index (R=0.31, P=0.023). Moreover, a trend toward longer disease-free survival (DFS) was observed in patients with decreased TG and increased LDL-C following chemotherapy, although this difference was not statistically significant (P=0.23 and P=0.24, respectively). Significant elevations in serum lipids were observed after neoadjuvant chemotherapy in patients with localized osteosarcoma. There was no prognostic significance of pretreatment serum lipid levels on histologic response to neoadjuvant chemotherapy. The scale of increase in serum Lp(a) might have a potential prognostic role in osteosarcoma. Patients with increased LDL-C or reduced TG after chemotherapy seem to exhibit a trend toward favorable DFS. Show less
📄 PDF DOI: 10.1007/s11596-024-2852-8
APOB
Hari K Krishnamurthy, Imbaasree Rajavelu, Swarnkumar Reddy +7 more · 2024 · Cureus · added 2026-04-24
Background  The study aims to assess the association of apolipoprotein E (APOE) gene polymorphisms with serological lipid and inflammatory markers to determine their potential role in predicting the r Show more
Background  The study aims to assess the association of apolipoprotein E (APOE) gene polymorphisms with serological lipid and inflammatory markers to determine their potential role in predicting the risk of cardiovascular diseases (CVDs) and Alzheimer's disease (AD).  Methodology  A total of 915 individuals underwent testing for lipid and inflammatory biomarkers at Vibrant America Clinical Laboratory. Clinical data, blood lipid and inflammatory profiles, and APOE genotyping were analyzed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).  Results Compared to the E3/E3 genotype, individuals with E2/E3 genotypes showed higher levels of high-density lipoprotein (HDL), triglycerides, apolipoprotein A (APOA), high-sensitivity C-reactive protein (hs-CRP), and myeloperoxidase (MPO). E2/E4 genotype carriers had higher levels of HDL, triglycerides, Lp(a), and N-terminal pro b-type natriuretic peptide (BNPNT). E3/E4 genotypes were associated with elevated levels of total cholesterol, LDL, Lp(a), hs-CRP, small-density low-density lipoprotein (SDLDL), oxidized LDL (OXLDL), MPO, LDL-CAL, PLAC, and APOB. The E4/E4 group displayed higher concentrations of total cholesterol, LDL, APOB, Lp(a), hs-CRP, SDLDL, OXLDL, MPO, LDLCAL, and PLAC compared to E3/E3 carriers. These findings highlight the potential atherogenic effect of the ε4 allele and the protective effect of the ε2 allele based on lipid and inflammatory marker profiles.  Conclusions This study provides strong evidence linking APOE gene polymorphism to abnormal serum lipid and inflammatory profiles. Individuals carrying the ε4 alleles exhibited dysregulated lipid metabolism and abnormal inflammatory markers, increasing their risk of CVD and AD. Early detection and prompt diagnosis are crucial for implementing therapeutic, dietary, and lifestyle interventions to mitigate risks and prevent or delay lipid and inflammation-related disorders. Show less
📄 PDF DOI: 10.7759/cureus.60721
APOB
Shuqi Wang, Haina Gao, Mengmeng Zhang +1 more · 2024 · Diabetes, metabolic syndrome and obesity : targets and therapy · added 2026-04-24
To explore the relationship between vitamin D (VitD) deficiency and the apolipoprotein B/apolipoprotein A1 (apo B/A1) in type 2 diabetes mellitus (T2DM) patients. This was a retrospective study that l Show more
To explore the relationship between vitamin D (VitD) deficiency and the apolipoprotein B/apolipoprotein A1 (apo B/A1) in type 2 diabetes mellitus (T2DM) patients. This was a retrospective study that lasted 2 years and 6 months, collecting information and laboratory data from 784 patients with T2DM. Patients were divided into VitD deficiency group (n = 433) and non-VitD deficiency group (n = 351) based on VitD levels. Calculated apo B/A1 ratio, and patients were further divided into high-apo B/A1 group (n = 392) and low-apo B/A1 group (n = 392) based on the median of the apo B/A1. All data were analyzed using Prism 8.0.1 and R version 4.3.1 software. Apo B/A1 levels of T2DM patients combined with VitD deficiency was significantly higher than that of non-VitD deficiency patients, and the VitD levels of patients with high apo B/A1 was significantly lower than that patients with low apo B/A1 (all P<0.001). Spearman correlation analysis showed that VitD levels were negatively correlated with apo B/A1 (r=-0.238, P<0.001). Multiple linear regression analysis revealed after adjusting other factors, VitD levels were significantly negatively associated with apo B/A1 (β=-0.123, P=0.001). Binary logistic regression analysis showed apoB/A1 was an independent risk factor for VitD deficiency in T2DM patients. Restrictive cubic spline indicated a significant linear relationship between apoB/A1 and VitD deficiency (P general trend <0.0001, P nonlinear = 0.0896), after stratification of gender, the results showed that apo B/A1 was more susceptible to VitD deficiency in female patients. The receiver operating characteristic (ROC) curve analysis showed that the area under the curve, sensitivity and specificity of the apo B/A1 for VitD deficiency were 0.654, 66.3% and 59.8%, respectively. The apo B/A1 was significantly negatively associated with VitD levels and an independent risk factor for VitD deficiency in patients with T2DM. Show less
📄 PDF DOI: 10.2147/DMSO.S465391
APOB
Jiawen Lu, Yang Liu, Zhenqian Wang +4 more · 2024 · JACC. Asia · Elsevier · added 2026-04-24
Dyslipidemia is a recognized risk factor for type 2 diabetes (T2D), yet the genetic basis and causal nature remain unclear, particularly in Chinese populations. The authors investigated the causal eff Show more
Dyslipidemia is a recognized risk factor for type 2 diabetes (T2D), yet the genetic basis and causal nature remain unclear, particularly in Chinese populations. The authors investigated the causal effects of genetically predicted lipid levels on T2D risk and explored the potential effects of lipid-modifying drugs. Leveraging data from the Kunshan Community cohort in China, we analyzed the associations between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides (TGs) with T2D risk using genetic risk scores, 1-sample univariable, multivariable, and nonlinear Mendelian randomization (MR) analyses. Two-sample MR using summary-level data from Global Lipid Genetics Consortium and Biobank Japan was used for validation. Drug-target MR was used to examine the impact of lipid-modifying drug targets on T2D. Lower genetic risk scores of LDL-C (OR per SD: 0.97 [95% CI: 0.95-0.99]; Our findings suggested potential adverse effects of lower LDL-C, TG levels, as well as long-term use of APOC3 inhibitors on T2D risk in Chinese populations. These findings highlight the need for cautious lipid management strategies in T2D prevention. Show less
📄 PDF DOI: 10.1016/j.jacasi.2024.07.011
APOC3
Qianqian Xiao, Luyun Wang, Jing Wang +3 more · 2024 · Molecular metabolism · Elsevier · added 2026-04-24
Emerging evidence highlights the pivotal roles of long non-coding RNAs (lncRNAs) in lipid metabolism. Apoprotein C3 (ApoC3) is a well-established therapeutic target for hypertriglyceridemia and exhibi Show more
Emerging evidence highlights the pivotal roles of long non-coding RNAs (lncRNAs) in lipid metabolism. Apoprotein C3 (ApoC3) is a well-established therapeutic target for hypertriglyceridemia and exhibits a strong association with cardiovascular disease. However, the exact mechanisms via which the lncRNAs control ApoC3 expression remain unclear. We identified a novel long noncoding RNA (lncRNA), GM47544, within the ApoA1/C3/A4/A5 gene cluster. Subsequently, the effect of GM47544 on intracellular triglyceride metabolism was analyzed. The diet-induced mouse models of hyperlipidemia and atherosclerosis were established to explore the effect of GM47544 on dyslipidemia and plaque formation in vivo. The molecular mechanism was explored through RNA sequencing, immunoprecipitation, RNA pull-down assay, and RNA immunoprecipitation. GM47544 was overexpressed under high-fat stimulation. GM47544 effectively improved hepatic steatosis, reduced blood lipid levels, and alleviated atherosclerosis in vitro and in vivo. Mechanistically, GM47544 directly bound to ApoC3 and facilitated the ubiquitination at lysine 79 in ApoC3, thereby facilitating ApoC3 degradation via the ubiquitin-proteasome pathway. Moreover, we identified AP006216.5 as the human GM47544 transcript, which fulfills a comparable function in human hepatocytes. The identification of GM47544 as a lncRNA modulator of ApoC3 reveals a novel mechanism of post-translational modification, with significant clinical implications for the treatment of hypertriglyceridemia and atherosclerosis. Show less
📄 PDF DOI: 10.1016/j.molmet.2024.102011
APOC3
Lixuan Huang, Ying Sun, Chao Luo +5 more · 2024 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Schizophrenia significantly impacts cognitive and behavioral functions and is primarily treated with second-generation antipsychotics (SGAs) such as olanzapine. Despite their efficacy, these drugs are Show more
Schizophrenia significantly impacts cognitive and behavioral functions and is primarily treated with second-generation antipsychotics (SGAs) such as olanzapine. Despite their efficacy, these drugs are linked to serious metabolic side effects which can diminish patient compliance, worsen psychiatric symptoms and increase cardiovascular disease risk. This study explores the hypothesis that SGAs affect the molecular determinants of synaptic plasticity and brain activity, particularly focusing on the lateral septum (LS) and its interactions within hypothalamic circuits that regulate feeding and energy expenditure. Utilizing functional ultrasound imaging, RNA sequencing, and weighted gene co-expression network analysis, we identified significant alterations in the functional connection between the hypothalamus and LS, along with changes in gene expression in the LS of mice following prolonged olanzapine exposure. Our analysis revealed a module closely linked to increases in body weight and adiposity, featuring genes primarily involved in lipid metabolism pathways, notably Show less
📄 PDF DOI: 10.3389/fphar.2024.1419098
APOC3
Jiacheng Lyu, Lin BAI, Yumiao Li +12 more · 2024 · Nature communications · Nature · added 2026-04-24
Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitu Show more
Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT. Show less
📄 PDF DOI: 10.1038/s41467-024-47835-y
APOC3
Runhao Xu, Jianan Shen, Yan Song +5 more · 2024 · Scientific reports · Nature · added 2026-04-24
Analyzing blood lipid and bile acid profile changes in colorectal cancer (CRC) patients. Evaluating the integrated model's diagnostic significance for CRC. Ninety-one individuals with colorectal cance Show more
Analyzing blood lipid and bile acid profile changes in colorectal cancer (CRC) patients. Evaluating the integrated model's diagnostic significance for CRC. Ninety-one individuals with colorectal cancer (CRC group) and 120 healthy volunteers (HC group) were selected for comparison. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoproteins (Apo) A1, ApoA2, ApoB, ApoC2, and ApoC3 were measured using immunoturbidimetric and colorimetric methods. Additionally, LC-MS/MS was employed to detect fifteen bile acids in the serum, along with six tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigens (CA) 125, CA19-9, CA242, CA50, and CA72-4. Group comparisons utilized independent sample t-tests and Mann-Whitney U tests. A binary logistic regression algorithm was applied to fit the indicators and establish a screening model; the diagnostic accuracy of individual Indicators and the model was analyzed using receiver operating characteristic (ROC) curves. The CRC group showed significantly lower levels in eight serum lipid indicators and eleven bile acids compared to the HC group (P < 0.05). Conversely, serum levels of TG, CA19-9, and CEA were elevated (P < 0.05). Among the measured parameters, ApoA2 stands out for its strong correlation with the presence of CRC, showcasing exceptional screening efficacy with an area under the curve (AUC) of 0.957, a sensitivity of 85.71%, and a specificity of 93.33%. The screening model, integrating ApoA1, ApoA2, lithocholic acid (LCA), and CEA, attained an impressive AUC of 0.995, surpassing the diagnostic accuracy of individual lipids, bile acids, and tumor markers. CRC patients manifest noteworthy alterations in both blood lipids and bile acid profiles. A screening model incorporating ApoA1, ApoA2, LCA, and CEA provides valuable insights for detecting CRC. Show less
📄 PDF DOI: 10.1038/s41598-024-60867-0
APOC3
Shaoliang Zhu, Quan Cheng, Mengjie Zou +11 more · 2024 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the di Show more
Pancreatic ductal adenocarcinoma (PDAC), a very aggressive tumour, is currently the third leading cause of cancer-related deaths. Unfortunately, many patients face the issue of inoperability at the diagnostic phase leading to a quite dismal prognosis. The onset of metastatic processes has a crucial role in the elevated mortality rates linked to PDAC. Individuals with metastatic advances receive only palliative therapy and have a grim prognosis. It is essential to carefully analyse the intricacies of the metastatic process to enhance the prognosis for individuals with PDAC. Malignancy development is greatly impacted by the process of macrophage efferocytosis. Our current knowledge about the complete range of macrophage efferocytosis activities in PDAC and their intricate interactions with tumour cells is still restricted. This work aims to resolve communication gaps and pinpoint the essential transcription factor that is vital in the immunological response of macrophage populations. We analysed eight PDAC tissue samples sourced from the gene expression omnibus. We utilized several software packages such as Seurat, DoubletFinder, Harmony, Pi, GSVA, CellChat and Monocle from R software together with pySCENIC from Python, to analyse the single-cell RNA sequencing (scRNA-seq) data collected from the PDAC samples. This study involved the analysis of a comprehensive sample of 22,124 cells, which were classified into distinct cell types. These cell types encompassed endothelial and epithelial cells, PDAC cells, as well as various immune cells, including CD4+ T cells, CD8+ T cells, NK cells, B cells, plasma cells, mast cells, monocytes, DC cells and different subtypes of macrophages, namely C0 macrophage TGM2+, C1 macrophage PFN1+, C2 macrophage GAS6+ and C3 macrophage APOC3+. The differentiation between tumour cells and epithelial cells was achieved by the implementation of CopyKat analysis, resulting in the detection and categorization of 1941 PDAC cells. The amplification/deletion patterns observed in PDAC cells on many chromosomes differ significantly from those observed in epithelial cells. The study of Pseudotime Trajectories demonstrated that the C0 macrophage subtype expressing TGM2+ had the lowest level of differentiation. Additionally, the examination of gene set scores related to efferocytosis suggested that this subtype displayed higher activity during the efferocytosis process compared to other subtypes. The most active transcription factors for each macrophage subtype were identified as BACH1, NFE2, TEAD4 and ARID3A. In conclusion, the examination of human PDAC tissue samples using immunofluorescence analysis demonstrated the co-localization of CD68 and CD11b within regions exhibiting the presence of keratin (KRT) and alpha-smooth muscle actin (α-SMA). This observation implies a spatial association between macrophages, fibroblasts, and epithelial cells. There is variation in the expression of efferocytosis-associated genes between C0 macrophage TGM2+ and other macrophage cell types. This observation implies that the diversity of macrophage cells might potentially influence the metastatic advancement of PDAC. Moreover, the central transcription factor of different macrophage subtypes offers a promising opportunity for targeted immunotherapy in the treatment of PDAC. Show less
📄 PDF DOI: 10.1111/jcmm.18266
APOC3
Mei-Jie Chen, Yi-Tong Xu, Lu Sun +6 more · 2024 · Acta pharmacologica Sinica · Nature · added 2026-04-24
Within the context of residual cardiovascular risk in post-statin era, emerging evidence from epidemiologic and human genetic studies have demonstrated that triglyceride (TG)-rich lipoproteins and the Show more
Within the context of residual cardiovascular risk in post-statin era, emerging evidence from epidemiologic and human genetic studies have demonstrated that triglyceride (TG)-rich lipoproteins and their remnants are causally related to cardiovascular risk. While, carriers of loss-of-function mutations of ApoC3 have low TG levels and are protected from cardiovascular disease (CVD). Of translational significance, siRNAs/antisense oligonucleotide (ASO) targeting ApoC3 is beneficial for patients with atherosclerotic CVD. Therefore, animal models of atherosclerosis with both hypercholesterolemia and hypertriglyceridemia are important for the discovery of novel therapeutic strategies targeting TG-lowering on top of traditional cholesterol-lowering. In this study, we constructed a novel mouse model of familial combined hyperlipidemia through inserting a human ApoC3 transgene (hApoC3-Tg) into C57BL/6 J mice and injecting a gain-of-function variant of adeno-associated virus-proprotein convertase subtilisin/kexin type 9 (AAV-PCSK9)-D377Y concurrently with high cholesterol diet (HCD) feeding for 16 weeks. In the last 10 weeks, hApoC3-Tg mice were orally treated with a combination of atorvastatin (10 mg·kg Show less
no PDF DOI: 10.1038/s41401-024-01241-8
APOC3
Quanxin Su, Rui Wang, Yayin Luo +2 more · 2024 · Frontiers in endocrinology · Frontiers · added 2026-04-24
The effect of hypolipidemic drugs on male erectile function is still controversial. This Mendelian randomization (MR) study aimed to explore the potential impact of lipid-lowering drug targets on ED. Show more
The effect of hypolipidemic drugs on male erectile function is still controversial. This Mendelian randomization (MR) study aimed to explore the potential impact of lipid-lowering drug targets on ED. We collected seven genetic variants encoding lipid-lowering drug targets (LDLR, HMGCR, NPC1L1, PCSK9, APOB, APOC3 and LPL) from published genome-wide association study (GWAS) statistics, and performed drug target MR analysis. The risk of ED was defined as the primary outcome, sex hormone levels and other diseases as the secondary outcomes. Mediation analyses were performed to explore potential mediating factors. The results showed that LDLR, LPL agonists and APOC3 inhibitors were significantly associated with a reduced risk of ED occurrence. APOB inhibitors were associated with an increased risk of ED occurrence. In terms of sex hormone levels, LDLR and LPL agonists were significantly associated with increased TT levels, and HMGCR was associated with decreased TT and BT levels significantly. In terms of male-related disease, MR results showed that LDLR agonists and PCSK9 inhibitors were significantly associated with an elevated risk of PH; HMGCR, NPC1L1 inhibitors were associated with a reduced risk of PCa; and LDLR agonists were significantly associated with a reduced risk of AS and MI; in addition, HMGCR inhibitors were associated with a reduced risk of PCa. After performing drug-targeted MR analysis, we found that that there was a causal relationship between lipid-lowering drug targets and ED. APOC3, APOB, LDLR and LPL may be new candidate drug targets for the treatment of ED. Show less
📄 PDF DOI: 10.3389/fendo.2024.1362499
APOC3
Zhichen Pu, Wenhui Wang, Haitang Xie +1 more · 2024 · International immunopharmacology · Elsevier · added 2026-04-24
Respiratory failure caused by severe acute lung injury (ALI) is the main cause of mortality in patients with COVID-19.This study aimed to investigate the effects and underlying biological mechanism of Show more
Respiratory failure caused by severe acute lung injury (ALI) is the main cause of mortality in patients with COVID-19.This study aimed to investigate the effects and underlying biological mechanism of Apolipoprotein C3 (ApoC3) in ALI. To establish an in vivo model, C57BL/6 mice were exposed by lipopolysaccharide (LPS). For the in vitro model, murine bone marrow-derived macrophages (BMDMs) or RAW264.7 cells were stimulated with LPS + adenosine triphosphate (ATP). Serum levels of ApoC3 were found to be upregulated in patients with COVID-19 or pneumonia-induced ALI. Inhibition of ApoC3 reduced lung injury in an ALI model, while overexpression of ApoC3 promoted lung injury. ApoC3 induced mitochondrial damage-mediated pyroptosis in ALI through the activation of the NOD-like receptorprotein 3 (NLRP3) inflammasome. ApoC3 recombinant protein significantly increased SCIMP expression in the lung tissue of mice models with ALI. ApoC3 also facilitated the interaction between the SLP adapter and CSK-interacting membrane protein (SCIMP) protein and Spleen tyrosine kinase (SYK) protein in the ALI model. Moreover, ApoC3 accelerated calcium-dependent reactive oxygen species (ROS) production in the ALI model. The effects of ApoC3 on pyroptosis were mitigated by the use of a pyroptosis inhibitor or an ROS inhibitor in the ALI model. Furthermore, ApoC3 activated the expression of SYK, which in turn induced NLRP3 inflammasome-regulated pyroptosis in the ALI model. METTL3 was found to mediate the m6A mRNA expression of ApoC3. Overall, our study highlights the crucial role of ApoC3 in promoting macrophage pyroptosis in ALI through calcium-dependent ROS production and NLRP3 inflammasome activation via the SCIMP-SYK pathway, providing a potential therapeutic strategy for ALI and other inflammatory diseases. Show less
no PDF DOI: 10.1016/j.intimp.2024.111537
APOC3
Jiawei Liao, Yuhui Wang, Yao Wang +5 more · 2024 · Biochimica et biophysica acta. Molecular and cell biology of lipids · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.bbalip.2023.159449
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Xue Zhang, Longtao Ji, Man Liu +11 more · 2024 · Journal of proteome research · ACS Publications · added 2026-04-24
Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benig Show more
Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity. Show less
no PDF DOI: 10.1021/acs.jproteome.3c00551
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Brandon M Lehrich, Evan R Delgado, Tyler M Yasaka +31 more · 2024 · Research square · added 2026-04-24
First-line immune checkpoint inhibitor (ICI) combinations show responses in subsets of hepatocellular carcinoma (HCC) patients. Nearly half of HCCs are Wnt-active with mutations in
📄 PDF DOI: 10.21203/rs.3.rs-5494074/v1
AXIN1
Jianding Wang, Wenwen Zhang, Rui Zhang +4 more · 2024 · Toxics · MDPI · added 2026-04-24
N-methyl-n'-nitroso-n'-nitroso guanidine (MNNG) can induce esophageal squamous cell carcinoma (ESCC), and microRNAs are associated with the development of ESCC and may serve as potential tumor prognos Show more
N-methyl-n'-nitroso-n'-nitroso guanidine (MNNG) can induce esophageal squamous cell carcinoma (ESCC), and microRNAs are associated with the development of ESCC and may serve as potential tumor prognostic markers. Thus, the aim of this study was to evaluate the potential function of miR-101-3p in MNNG-induced ESCC. An investigation of risk factors in patients with ESCC was carried out and the concentration of nine nitrosamines in urine samples was detected by the SPE-GC-MS technique. Then, we performed cancer tissue gene sequencing analysis, and RT-qPCR verified the expression level of miR-101-3p. Subsequently, the relationship between miR-101-3p potential target genes and the ESCC patients' prognosis was predicted. Finally, we investigated the function of miR-101-3p in MNNG-induced ESCC pathogenesis and the regulatory mechanism of the signaling pathway by in vivo and in vitro experiments. The results revealed that high dietary nitrosamine levels are high-risk factors for ESCC. MiR-101-3p is down-regulated in ESCC tissues and cells, and its potential target genes are enriched in cell migration and cancer-related pathways. MiR-101-3p target genes include AXIN1, CK1, and GSK3, which are involved in the regulation of the Wnt signaling pathway. MiR-101-3p overexpression promotes apoptosis and inhibits the proliferation and migration of Eca109 cells. The Wnt pathway is activated after subchronic exposure to MNNG, and the Wnt pathway is inhibited by the overexpression of miR-101-3p in Eca109 cells. Down-regulated miR-101-3p may exert tumor suppressive effects by regulating the Wnt pathway and may be a useful biomarker for predicting ESCC progression. Show less
📄 PDF DOI: 10.3390/toxics12110824
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Zehua Wen, Lei Wang, Shi-Wei Liu +3 more · 2024 · Cells · MDPI · added 2026-04-24
Wnt signaling is involved in embryo development and cancer. The binding between the DIX domains of Axin1/2, Dishevelled1/2/3, and Coiled-coil-DIX1 is essential for Wnt/β-catenin signaling. Structural Show more
Wnt signaling is involved in embryo development and cancer. The binding between the DIX domains of Axin1/2, Dishevelled1/2/3, and Coiled-coil-DIX1 is essential for Wnt/β-catenin signaling. Structural and biological studies have revealed that DIX domains are polymerized through head-to-tail interface interactions, which are indispensable for activating β-catenin Wnt signaling. Although different isoforms of Dvl and Axin proteins display both redundant and specific functions in Wnt signaling, the specificity of DIX-mediated interactions remains unclear due to technical challenges. Using AlphaFold2(AF2), we predict the structures of 6 homodimers and 22 heterodimers of DIX domains without templates and compare them with the reported X-ray complex structures. PRODIGY is used to calculate the binding affinities of these DIX complexes. Our results show that the Axin2 DIX homodimer has a stronger binding affinity than the Axin1 DIX homodimer. Among Dishevelled (Dvl) proteins, the binding affinity of the Dvl1 DIX homodimer is stronger than that of Dvl2 and Dvl3. The Coiled-coil-DIX1(Ccd1) DIX homodimer shows weaker binding than the Axin1 DIX homodimer. Generally, heterodimer interactions tend to be stronger than those of homodimers. Our findings provide insights into the mechanism of the Wnt signaling pathway and highlight the potential of AF2 and PRODIGY for studying protein-protein interactions in signaling pathways. Show less
📄 PDF DOI: 10.3390/cells13191646
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Zhiguo Wang, Kunlin Li, Conghua Lu +12 more · 2024 · Oncology research · added 2026-04-24
Metformin has pleiotropic effects beyond glucose reduction, including tumor inhibition and immune regulation. It enhanced the anti-tumor effects of programmed cell death protein 1 (PD-1) inhibitors in Show more
Metformin has pleiotropic effects beyond glucose reduction, including tumor inhibition and immune regulation. It enhanced the anti-tumor effects of programmed cell death protein 1 (PD-1) inhibitors in serine/threonine kinase 11 ( We performed untargeted metabolomics using liquid chromatography (LC)-mass spectrometry (MS)/MS system and conducted cell experiments to verify the results of bioinformatics analysis. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, most metabolites were annotated into metabolism, including nucleotide metabolism. Next, the differentially expressed metabolites in H460 (refers to H460 cells), H460_met (refers to metformin-treated H460 cells), and H460_KO_met (refers to metformin-treated Relying on AXIN1, metformin upregulated multiple nucleotide metabolites which promoted STING signaling and the killing of activated T cells in Show less
📄 PDF DOI: 10.32604/or.2024.052664
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Tiantian Wu, Hui Zhou, Lulu Wang +8 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Tripartite motif-containing protein 59 (TRIM59) is a biomarker for multiple tumors with crucial roles. However, the specific role of TRIM59 in germ cells remains largely unknown. Here, we investigated Show more
Tripartite motif-containing protein 59 (TRIM59) is a biomarker for multiple tumors with crucial roles. However, the specific role of TRIM59 in germ cells remains largely unknown. Here, we investigated the effects and underlying regulatory mechanisms of TRIM59 on germ cells using the mouse spermatogonial cell line GC-1. Our results demonstrated that TRIM59 promoted proliferation and inhibited apoptosis of GC-1 cells. Mechanistically, TRIM59 maintained GC-1 cell behaviors through ubiquitination of AXIN1 to activate β-catenin signaling. Furthermore, activation of β-catenin signaling reversed the effects mediated by Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e36744
AXIN1
Shengxi Shen, Ping Wang, Pei Wu +4 more · 2024 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Wnt/β-catenin signaling is an attractive target for regenerative medicine. A powerful driver of stem cell activity and hence tissue regeneration, Wnt signaling can promote fibroblast proliferation and Show more
Wnt/β-catenin signaling is an attractive target for regenerative medicine. A powerful driver of stem cell activity and hence tissue regeneration, Wnt signaling can promote fibroblast proliferation and activation, leading to fibrosis, while prolonged Wnt signaling is potentially carcinogenic. Thus, to harness its therapeutic potential, the activation of Wnt signaling must be transient, reversible, and tissue specific. In the lung, Wnt signaling is essential for alveolar stem cell activity and alveolar regeneration, which is impaired in lung fibrosis. Activation of Wnt/β-catenin signaling in lung epithelium may have anti-fibrotic effects. Here, we used intratracheal adeno-associated virus 6 injection to selectively deliver CasRx into the lung epithelium, where it reversibly activates Wnt signaling by simultaneously degrading mRNAs encoding Axin1 and Axin2, negative regulators of Wnt/β-catenin signaling. Interestingly, CasRx-mediated Wnt activation specifically in lung epithelium not only promotes alveolar type II cell proliferation and alveolar regeneration but also inhibits lung fibrosis resulted from bleomycin-induced injury, relevant in both preventive and therapeutic settings. Our study offers an attractive strategy for treating pulmonary fibrosis, with general implications for regenerative medicine. Show less
📄 PDF DOI: 10.1016/j.ymthe.2024.09.008
AXIN1
Fangchen Gong, Wenbin Liu, Lei Pei +10 more · 2024 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Sepsis, a life-threatening condition, involves complex interactions among metabolic alterations, inflammatory mediators, and host responses. This study utilized a bidirectional Mendelian randomization Show more
Sepsis, a life-threatening condition, involves complex interactions among metabolic alterations, inflammatory mediators, and host responses. This study utilized a bidirectional Mendelian randomization approach to investigate the causal relationships between 1400 metabolites and sepsis, and the mediating role of inflammatory factors. We identified 36 metabolites significantly associated with sepsis (p < 0.05), with AXIN1, FGF-19, FGF-23, IL-4, and OSM showing an inverse association, suggesting a protective role, while IL-2 exhibited a positive correlation, indicating a potential risk factor. Among these metabolites, Piperine and 9-Hydroxystearate demonstrated particularly interesting protective effects against sepsis. Piperine's protective effect was mediated through its interaction with AXIN1, contributing to a 16.296% reduction in sepsis risk. This suggests a potential pathway where Piperine influences sepsis outcomes by modulating AXIN1 levels. 9-Hydroxystearate also exhibited a protective role against sepsis, mediated through its positive association with FGF-19 and negative association with IL-2, contributing 9.436% and 12.565%, respectively, to its protective effect. Experimental validation confirmed significantly elevated IL-2 levels and reduced FGF-19, AXIN1, piperine, and 9-hydroxyoctadecanoic acid levels in sepsis patients compared to healthy controls. Piperine levels positively correlated with AXIN1, while 9-hydroxyoctadecanoic acid levels negatively correlated with IL-2 and positively correlated with FGF-19, supporting the Mendelian randomization findings. Our findings provide insights into the molecular mechanisms of sepsis, highlighting the unique roles and contributions of specific metabolites and their interactions with inflammatory mediators. This study enhances our understanding of sepsis pathophysiology and opens avenues for targeted therapeutic interventions and biomarker development for sepsis management. However, further research is essential to validate these pathways across diverse populations and fully explore the roles of these metabolites in sepsis. Show less
📄 PDF DOI: 10.3389/fendo.2024.1377755
AXIN1
H Li, G Li, X Zhang +1 more · 2024 · Nan fang yi ke da xue xue bao = Journal of Southern Medical University · added 2026-04-24
H Li, G Li, X Zhang, Y Wang Show less
To explore the causal relationship between inflammatory protein markers and the risk of colorectal cancer using a Mendelian randomization (MR) approach. We obtained data pertaining to colorectal cance Show more
To explore the causal relationship between inflammatory protein markers and the risk of colorectal cancer using a Mendelian randomization (MR) approach. We obtained data pertaining to colorectal cancer from Genome-Wide Association Study (GWAS) datasets and used 91 inflammatory protein markers as the exposure variables. A two-sample MR analysis model was used to assess the causal link between the inflammatory markers and colorectal cancer risk. The robustness of the results was evaluated through heterogeneity, pleiotropy, and sensitivity analyses using 5 MR models: Inverse Variance Weighted (IVW), Weighted Median, MR Egger, Simple Mode, and Weighted Mode. We examined the mRNA expressions of Using the IVW model, MR analysis revealed significant causal associations between a reduced risk of colorectal cancer and lowered expressions of AXIN1 (OR=0.866, 95% Lowered expressions of inflammatory protein markers AXIN1, β-NGF, and PD-L1 are causally correlated with a reduced risk of colorectal cancer and their expression levels are associated with TNM staging and tumor differentiation. These markers may thus serve as potential targets for colorectal cancer treatment and prevention. Show less
no PDF DOI: 10.12122/j.issn.1673-4254.2024.07.16
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