👤 Da 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-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, Yinghui Wang, Yingjie Wang, Yingmei Wang, Yingna Wang, Yingping Wang, Yingqiao Wang, Yingtai Wang, Yingte Wang, Yingwei Wang, Yingwen Wang, Yingxiong Wang, Yingxue Wang, Yingyi Wang, Yingying Wang, Yingzi Wang, Yinhuai Wang, Yining E Wang, Yinong Wang, Yinsheng Wang, Yintao Wang, Yinuo Wang, Yinxiong Wang, Yinyin Wang, Yiou Wang, Yipeng Wang, Yiping Wang, Yiqi Wang, Yiqiao Wang, Yiqin Wang, Yiqing Wang, Yiquan Wang, Yirong Wang, Yiru Wang, Yirui Wang, Yishan Wang, Yishu Wang, Yitao Wang, Yiting Wang, Yiwei Wang, Yiwen Wang, Yixi Wang, Yixian Wang, Yixuan Wang, Yiyan Wang, Yiyi Wang, Yiying Wang, Yizhe Wang, Yong Wang, Yong-Bo Wang, Yong-Gang Wang, Yong-Jie Wang, Yong-Jun Wang, Yong-Tang Wang, Yongbin Wang, Yongdi Wang, Yongfei Wang, Yongfeng Wang, Yonggang Wang, Yonghong Wang, Yongjie Wang, Yongjun Wang, Yongkang Wang, Yongkuan Wang, Yongli Wang, Yongliang Wang, Yonglun Wang, Yongmei Wang, Yongming Wang, Yongni Wang, Yongqiang Wang, Yongqing Wang, Yongrui Wang, Yongsheng Wang, Yongxiang Wang, Yongyi Wang, Yongzhong Wang, You Wang, Youhua Wang, Youji Wang, Youjie Wang, Youli Wang, Youzhao Wang, Youzhi Wang, Yu Qin Wang, Yu Tian Wang, Yu Wang, Yu'e Wang, Yu-Chen Wang, Yu-Fan Wang, Yu-Fen Wang, Yu-Hang Wang, Yu-Hui Wang, Yu-Ping Wang, Yu-Ting Wang, Yu-Wei Wang, Yu-Wen Wang, Yu-Ying Wang, Yu-Zhe Wang, Yu-Zhuo Wang, Yuan Wang, Yuan-Hung Wang, Yuanbo Wang, Yuanfan Wang, Yuanjiang Wang, Yuanli Wang, Yuanqiang Wang, Yuanqing Wang, Yuanyong Wang, Yuanyuan Wang, Yuanzhen Wang, Yubing Wang, Yubo Wang, Yuchen Wang, Yucheng Wang, Yuchuan Wang, Yudong Wang, Yue Wang, Yue-Min Wang, Yue-Nan Wang, YueJiao Wang, Yuebing Wang, Yuecong Wang, Yuegang Wang, Yuehan Wang, Yuehong Wang, Yuehu Wang, Yuehua Wang, Yuelong Wang, Yuemiao Wang, Yueshen Wang, Yueting Wang, Yuewei Wang, Yuexiang Wang, Yuexin Wang, Yueying Wang, Yueze Wang, Yufei Wang, Yufeng Wang, Yugang Wang, Yuh-Hwa Wang, Yuhan Wang, Yuhang Wang, Yuhua Wang, Yuhuai Wang, Yuhuan Wang, Yuhui Wang, Yujia Wang, Yujiao Wang, Yujie Wang, Yujiong Wang, Yulai Wang, Yulei Wang, Yuli Wang, Yuliang Wang, Yulin Wang, Yuling Wang, Yulong Wang, Yumei Wang, Yumeng Wang, Yumin Wang, Yuming Wang, Yun Wang, Yun Yong Wang, Yun-Hui Wang, Yun-Jin Wang, Yun-Xing Wang, Yunbing Wang, Yunce Wang, Yunchao Wang, Yuncong Wang, Yunduan Wang, Yunfang Wang, Yunfei Wang, Yunhan Wang, Yunhe Wang, Yunong Wang, Yunpeng Wang, Yunqiong Wang, Yuntai Wang, Yunzhang Wang, Yunzhe Wang, Yunzhi Wang, Yupeng Wang, Yuping Wang, Yuqi Wang, Yuqian Wang, Yuqiang Wang, Yuqin Wang, Yusha Wang, Yushe Wang, Yusheng Wang, Yutao Wang, Yuting Wang, Yuwei Wang, Yuwen Wang, Yuxiang Wang, Yuxing Wang, Yuxuan Wang, Yuxue Wang, Yuyan Wang, Yuyang Wang, Yuyin Wang, Yuying Wang, Yuyong Wang, Yuzhong Wang, Yuzhou Wang, Yuzhuo Wang, Z P Wang, Z Wang, Z-Y Wang, Zai Wang, Zaihua Wang, Ze Wang, Zechen Wang, Zehao Wang, Zehua Wang, Zekun Wang, Zelin Wang, Zeneng Wang, Zengtao Wang, Zeping Wang, Zexin Wang, Zeying Wang, Zeyu Wang, Zeyuan Wang, Zezhou Wang, Zhan Wang, Zhang Wang, Zhanggui Wang, Zhangshun Wang, Zhangying Wang, Zhanju Wang, Zhao Wang, Zhao-Jun Wang, Zhaobo Wang, Zhaofeng Wang, Zhaofu Wang, Zhaohai Wang, Zhaohui Wang, Zhaojing Wang, Zhaojun Wang, Zhaoming Wang, Zhaoqing Wang, Zhaosong Wang, Zhaotong Wang, Zhaoxi Wang, Zhaoxia Wang, Zhaoyu Wang, Zhe Wang, Zhehai Wang, Zhehao Wang, Zhen Wang, ZhenXue Wang, Zhenbin Wang, Zhenchang Wang, Zhenda Wang, Zhendan Wang, Zhendong Wang, Zheng Wang, Zhengbing Wang, Zhengchun Wang, Zhengdong Wang, Zhenghui Wang, Zhengkun Wang, Zhenglong Wang, Zhenguo Wang, Zhengwei Wang, Zhengxuan Wang, Zhengyang Wang, Zhengyi Wang, Zhengyu Wang, Zhenhua Wang, Zhenning Wang, Zhenqian Wang, Zhenshan Wang, Zhentang Wang, Zhenwei Wang, Zhenxi Wang, Zhenyu Wang, Zhenze Wang, Zhenzhen Wang, Zheyi Wang, Zheyue Wang, Zhezhi Wang, Zhi Wang, Zhi Xiao Wang, Zhi-Gang Wang, Zhi-Guo Wang, Zhi-Hao Wang, Zhi-Hong Wang, Zhi-Hua Wang, Zhi-Jian Wang, Zhi-Long Wang, Zhi-Qin Wang, Zhi-Wei Wang, Zhi-Xiao Wang, Zhi-Xin Wang, Zhibo Wang, Zhichao Wang, Zhicheng Wang, Zhicun Wang, Zhidong Wang, Zhifang Wang, Zhifeng Wang, Zhifu Wang, Zhigang Wang, Zhige Wang, Zhiguo Wang, Zhihao Wang, Zhihong Wang, Zhihua Wang, Zhihui Wang, Zhiji Wang, Zhijian Wang, Zhijie Wang, Zhijun Wang, Zhilun Wang, Zhimei Wang, Zhimin Wang, Zhipeng Wang, Zhiping Wang, Zhiqi Wang, Zhiqian Wang, Zhiqiang Wang, Zhiqing Wang, Zhiren Wang, Zhiruo Wang, Zhisheng Wang, Zhitao Wang, Zhiting Wang, Zhiwu Wang, Zhixia Wang, Zhixiang Wang, Zhixiao Wang, Zhixin Wang, Zhixing Wang, Zhixiong Wang, Zhixiu Wang, Zhiying Wang, Zhiyong Wang, Zhiyou Wang, Zhiyu Wang, Zhiyuan Wang, Zhizheng Wang, Zhizhong Wang, Zhong Wang, Zhong-Hao Wang, Zhong-Hui Wang, Zhong-Ping Wang, Zhong-Yu Wang, ZhongXia Wang, Zhongfang Wang, Zhongjing Wang, Zhongli Wang, Zhonglin Wang, Zhongqun Wang, Zhongsu Wang, Zhongwei Wang, Zhongyi Wang, Zhongyu Wang, Zhongyuan Wang, Zhongzhi Wang, Zhou Wang, Zhou-Ping Wang, Zhoufeng Wang, Zhouguang Wang, Zhuangzhuang Wang, Zhugang Wang, Zhulin Wang, Zhulun Wang, Zhuo Wang, Zhuo-Hui Wang, Zhuo-Jue Wang, Zhuo-Xin Wang, Zhuowei Wang, Zhuoying Wang, Zhuozhong Wang, Zhuqing Wang, Zi Wang, Zi Xuan Wang, Zi-Hao Wang, Zi-Qi Wang, Zi-Yi Wang, Zicheng Wang, Zifeng Wang, Zihan Wang, Ziheng Wang, Zihua Wang, Zihuan Wang, Zijian Wang, Zijie Wang, Zijue Wang, Zijun Wang, Zikang Wang, Zikun Wang, Ziliang Wang, Zilin Wang, Ziling Wang, Zilong Wang, Zining Wang, Ziping Wang, Ziqi Wang, Ziqian Wang, Ziqiang Wang, Ziqing Wang, Ziqiu Wang, Zitao Wang, Ziwei Wang, Zixi Wang, Zixia Wang, Zixian Wang, Zixiang Wang, Zixu Wang, Zixuan Wang, Ziyi Wang, Ziying Wang, Ziyu Wang, Ziyun Wang, Zongbao Wang, Zonggui Wang, Zongji Wang, Zongkui Wang, Zongqi Wang, Zongwei Wang, Zou Wang, Zulong Wang, Zumin Wang, Zun Wang, Zunxian Wang, Zuo Wang, Zuoheng Wang, Zuoyan Wang, Zusen Wang
articles
Le Yang, Ye Sun, Chuanning Li +9 more · 2026 · Frontiers in immunology · Frontiers · added 2026-04-24
Damp-heat gout (DHG) is a highly certified type of disease integrated with syndrome in TCM. The ambiguity of its pathomechanism and the lack of quantifiable indicators limit its clinical accurate diag Show more
Damp-heat gout (DHG) is a highly certified type of disease integrated with syndrome in TCM. The ambiguity of its pathomechanism and the lack of quantifiable indicators limit its clinical accurate diagnosis and treatment. This study aimed to elucidate the pathological mechanism of DHG and establish a symptom-centered diagnostic and therapeutic model. We recruited 136 participants, comprising healthy controls (HCs) and DHG patients. Serum metabolomics and proteomics analyses were performed to screen common pathways. Based on the biological significance of these common pathways, a symptom-pathway correlation network was constructed to clarify the pathological mechanisms driving DHG occurrence and progression. Enrichment scores and correlations with key DHG symptoms were used to identify critical pathways. Differential metabolites and proteins associated with these critical pathways served to establish a multi-index diagnostic model and identify potential therapeutic protein targets. Integrated metabolomic and proteomic analyses revealed 21 common pathways associated with DHG. Four crucial pathways, such as Bile secretion, Cholesterol metabolism, Purine metabolism, Arachidonic acid metabolism, were exhibited significant correlations with core DHG symptoms. Furthermore, six pathway-related biomarkers were identified: Hypoxanthine, Prostaglandin E2, Uric acid, Deoxycholic acid, Taurochenodeoxycholic acid, and Bilirubin. The combined diagnostic efficacy of these biomarkers was optimal (discovery cohort: AUC = 0.987; validation cohort: AUC = 0.997). Six protein targets were identified from the crucial pathways, including ATP1A1, APRT, ANGPTL4, GLUT1, PTGES3 and LIPA. This study establishes a symptom-centered diagnostic and therapeutic model for DHG utilizing the identified biomarkers and clarifies the involvement of critical metabolic pathways in DHG pathogenesis, providing novel targets for improved clinical diagnosis and therapy. Show less
📄 PDF DOI: 10.3389/fimmu.2026.1677920
ANGPTL4
Yingping Ma, Hongyu Wang, Xinman Dou +1 more · 2026 · Frontiers in immunology · Frontiers · added 2026-04-24
Brain metastasis significantly worsens prognosis in late-stage cancer., with Its treatment hindered by the blood-brain barrier (BBB) and an immunosuppressive tumor microenvironment. Within this enviro Show more
Brain metastasis significantly worsens prognosis in late-stage cancer., with Its treatment hindered by the blood-brain barrier (BBB) and an immunosuppressive tumor microenvironment. Within this environment, tumor-associated macrophages (TAMs) represent the predominant immune population. Through their roles in immune modulation, angiogenesis, and tumor invasion, TAMs are critical drivers of disease progression. TAMs are highly heterogeneous. While traditionally categorized into M1 (anti-tumor) or M2 (pro-tumor) phenotypes, this dichotomy is an oversimplification. Recent single-cell studies have revealed a spectrum of functional subpopulations, such as lipid-associated, interferon-responsive, and pro-angiogenic TAMs, with M2-like states typically prevailing to mediate immunosuppression. This review explores the diversity and functions of TAMs in brain metastasis. We first detail their biological characteristics, including origins, heterogeneous subtype classifications (e.g., lipid-associated macrophages that extend beyond the simple M1/M2 dichotomy), and polarization states. We further discuss how polarization is regulated by signaling pathways (e.g., STAT, NF-κB) and microenvironmental factors (e.g., hypoxia, metabolic reprogramming). We examine TAM roles from pre-metastatic niche formation to tumor colonization, using breast and lung cancer brain metastases to illustrate how TAMs disrupt the BBB and facilitate immune evasion through molecules like ANGPTL4 (angiopoietin-like 4) and MMP9. Key pathways of TAM-tumor cell interactions, including neuro-cancer interactions, immune-metabolic regulation, and exosome-mediated communication, are also discussed. Targeting TAMs offers promising therapeutic avenues. These strategies include reprogramming TAMs (e.g., using CSF1R inhibitors), combining TAM-targeted therapy with immune checkpoint inhibitors, and developing novel approaches such as nanotechnology and CAR-macrophages. However, several challenges remain, including TAM heterogeneity, lack of targeting specificity, and the obstacle of BBB delivery. Future research should leverage technologies like single-cell sequencing and spatial transcriptomics to decode TAM heterogeneity, and develop personalized treatments based on biomarkers such as GPNMB and TRAIL, aiming to improve patient outcomes in brain metastasis. Show less
📄 PDF DOI: 10.3389/fimmu.2026.1756299
ANGPTL4
Yiren Zhang, Wei Zeng, Yuanfa Liu +1 more · 2026 · Food research international (Ottawa, Ont.) · Elsevier · added 2026-04-24
Pine nut oil (PNO) is a candidate alternative to corn oil (CO) owing to comparable unsaturated fatty-acid profiles and enrichment in pinolenic acid (Δ5-18:3) and lipid-soluble micronutrients. We syste Show more
Pine nut oil (PNO) is a candidate alternative to corn oil (CO) owing to comparable unsaturated fatty-acid profiles and enrichment in pinolenic acid (Δ5-18:3) and lipid-soluble micronutrients. We systematically compared extraction routes (solvent, supercritical CO₂, pressing), established solvent extraction as the optimal balance of yield and bioactive retention, and then characterized solvent-extracted oils from eight provenances using a weighted composite score to nominate Pinus tabuliformis for in vivo testing. In diet-induced obese mice (12-week Western diet, then 12-week intervention, n = 10 per group), replacing CO with PNO lowered body-mass gain and liver weight and improved serum lipids (triglycerides ↓ ∼ 28 %, total cholesterol ↓ ∼ 15 %, LDL-C ↓ ∼ 20 %) without affecting HDL-C or glucose; ALT and AST fell by ∼30 %, indicating hepatoprotection. Hepatic multi-omics revealed coherent remodeling toward PUFA-rich phospholipid species, activation of PPAR-centered peroxisomal/mitochondrial fatty-acid degradation and circadian pathways, and integrative correlations implicating Cyp4a10/14, Ehhadh, Slc27a2, Fgf21, Angptl4, and Plin5. Collectively, PNO reoriented hepatic lipid flux toward oxidation and membrane remodeling, supporting its development as a nutritionally advantaged culinary oil. Show less
no PDF DOI: 10.1016/j.foodres.2025.118175
ANGPTL4
Linhui Zhai, Cui-Cui Liu, Lei Zhao +14 more · 2026 · Protein & cell · Oxford University Press · added 2026-04-24
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune s Show more
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune sites like lymph nodes remain elusive. Here, we performed an in-depth proteomic and phosphoproteomic analysis of a substantial series of breast cancer samples, alongside genomic and transcriptomic evaluations. This cohort encompasses 195 specimens: 65 primary breast tumors, their corresponding normal tissues, and metastatic axillary lymph nodes. We offer an overview of the molecular alterations at the transcriptomic, proteomic, and phosphoproteomic levels during lymph node metastasis. Notably, the findings indicate that regional lymph node metastasis is primarily influenced by proteomic and phosphoproteomic alterations, rather than genomic or transcriptomic changes. We found the ANGPTL4 and HMGB1 could serve as the biomarker of lymph node metastasis. Data analysis and cell experiments involving silencing of the alternative splicing factor HNRNPU demonstrated that alternative splicing plays a significant role in modulating protein expression, phosphorylation profiles and cell proliferation. The key phosphorylation sites, including MARCKSL1-S104 and FKBP15-S320, as well as the upstream kinase PRKCB, were identified as playing crucial roles in breast cancer lymph node metastasis. Targeted intervention of the kinase PRKCB resulted in effectively suppressing the proliferation and metastasis of breast cancer tumor cells. Immune profiling analysis and experimental validation of breast cancer cell cocultured with CD8+ T cell reveals correlations between phosphorylation of MARCKSL1-S104 and FKBP15-S320 with immune checkpoint PD-L1 expression, and their impact on tumor cell apoptosis, suggesting a potential mechanism of immune evasion in metastasis. This study systematically characterizes the molecular landscape and features of primary breast tumors and their matched metastatic lymph nodes. These insights enhance our understanding of early-stage breast cancer metastasis and may pave the way for improved diagnostic tools and targeted therapeutic strategies. Show less
no PDF DOI: 10.1093/procel/pwag002
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Meifang Zhao, Yuanchao Xiao, Qunzhi Wang · 2026 · The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · added 2026-04-24
Lung adenocarcinoma (LUAD) displays significant biological heterogeneity, with matrisome-related genes (MRGs) playing key roles in tumor progression and immune regulation. Understanding the interplay Show more
Lung adenocarcinoma (LUAD) displays significant biological heterogeneity, with matrisome-related genes (MRGs) playing key roles in tumor progression and immune regulation. Understanding the interplay between MRGs, the tumor microenvironment, and host immunity is critical for mechanistic insights. LUAD transcriptomic and clinical data were sourced from TCGA, GEO (GSE31210), and single-cell data (GSE189357). MRGs were analyzed Show less
no PDF DOI: 10.4196/kjpp.25.293
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Qiong Lu, Qiyue Zheng, Zhaokai Zhou +7 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Bone angiogenesis is important for bone formation and regeneration after bone injury. Endothelial-derived angiogenic factors are key signal transducers in the bone microenvironment and maintain vascul Show more
Bone angiogenesis is important for bone formation and regeneration after bone injury. Endothelial-derived angiogenic factors are key signal transducers in the bone microenvironment and maintain vascular-osteogenic coupling during bone regeneration. CGRP, a bone sensory neuron-derived peptide, contributes to bone formation, but the potential mechanism by which it improves bone regeneration via angiogenesis is unclear. Here, we demonstrate that CGRP may contribute to bone repair in the elderly, as human CGRP levels are inversely proportional to age and proportional to bone mass in clinical data and bulk transcriptome data. Based on single-cell RNA sequencing data and experimental analyses, CGRP is found to promote the angiogenesis of human microvascular endothelial cell line-1 in vitro through the FAK-AKT-VEGF pathway. CGRP gene deletion in mice reduced bone vascular density and bone mass, and delayed angiogenesis and bone regeneration at the bone defect site. Recombinant CGRP restored bone repair after defect introduction. It also promoted Angptl4 secretion by bone vascular endothelial cells, thereby driving osteogenic differentiation of bone marrow mesenchymal stem cells and enhancing bone regeneration after bone injury. Treatment with recombinant Angptl4 enhanced bone healing in a mouse bone defect model. These integrated analysis reveal the important role and mechanism of CGRP in vascular-mediated osteogenesis, suggesting a novel therapeutic strategy for promoting bone regeneration. Show less
📄 PDF DOI: 10.1002/advs.202522295
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Wensheng Chen, Qingshui Wang, Shuyuan Li · 2026 · Biochimica et biophysica acta. General subjects · Elsevier · added 2026-04-24
Lymph node metastasis is a critical prognostic factor in colorectal cancer (CRC). Identifying key genes associated with metastasis can improve risk stratification and treatment strategies. This study Show more
Lymph node metastasis is a critical prognostic factor in colorectal cancer (CRC). Identifying key genes associated with metastasis can improve risk stratification and treatment strategies. This study aimed to identify a gene signature related to lymph node metastasis and investigate the role of NPR3. We analyzed the GSE878211 dataset to identify differentially expressed genes in CRC tissues with and without lymph node metastasis. A lymph node metastasis-related gene signature (LNMRGS) was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The correlation between LNMRGS and clinical indicators, immune microenvironment, and signaling pathways was analyzed. The role of NPR3 was further investigated through in vitro and in vivo experiments. We identified 110 upregulated and 58 downregulated genes in CRC tissues with lymph node metastasis. The LNMRGS, consisting of Integrin Subunit Beta 3 (ITGB3), IQ Motif Containing with AAA Domain 1 (IQCA1), Angiopoietin-Like 4 (ANGPTL4), and Natriuretic Peptide Receptor 3 (NPR3), predicted overall survival in multiple datasets. High LNMRGS was associated with female sex, tumor recurrence, lymph node metastasis, distant metastasis, and KRAS mutations. NPR3 knockdown inhibited proliferation, migration, and invasion of CRC cells in vitro and in vivo, and reduced chemoresistance to 5-fluorouracil (5-FU) and oxaliplatin. The LNMRGS is a robust prognostic signature for CRC. NPR3 plays a key role in metastatic progression and chemoresistance, suggesting it as a potential therapeutic target. Show less
no PDF DOI: 10.1016/j.bbagen.2025.130895
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Yutong Lin, Danan Wang, Duanbin Li +8 more · 2026 · Atherosclerosis · Elsevier · added 2026-04-24
Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein (ANGPTL) family, is a physiological inhibitor of lipoprotein lipase (LPL), and plays a critical role in lipoprotein and Show more
Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein (ANGPTL) family, is a physiological inhibitor of lipoprotein lipase (LPL), and plays a critical role in lipoprotein and triglyceride metabolism in response to nutritional cues. ANGPTL8 is implicated in a wide range of systemic and cellular processes and is closely associated with metabolic and cardiovascular diseases (CVD). Circulating ANGPTL8 is primarily secreted by the liver, with adipose tissue as a secondary source. Its expression is regulated by multiple transcription factors and microRNAs, and is responsive to fasting/refeeding states, hormonal signals, and stress conditions. In lipid metabolism, ANGPTL8 forms complexes with ANGPTL3 and ANGPTL4 to modulate LPL activity under fasting and feeding conditions. In glucose metabolism, ANGPTL8 plays a complex role. While some studies suggest it may improve glucose tolerance and insulin resistance, others indicate it could exacerbate glucose metabolism disorders and diabetes, or have no effect. Cardiovascular diseases are intricately linked to metabolic disorders and diseases. Increasing evidence also links ANGPTL8 to various cardiovascular pathologies, including atherosclerosis, hypertension, cardiomyopathy, cardiac hypertrophy, aortic aneurysm, and dissection. Given the strong interplay between metabolic dysregulation and CVDs, elucidating the role of ANGPTL8 in these processes is of significant interest. This review provides a balanced assessment of ANGPTL8's roles in key pathophysiological processes, highlighting its established functions in metabolism alongside its emerging involvement in CVDs. Understanding the diverse functions of ANGPTL8 in various tissues and metabolic states will lead to new opportunities for therapeutic intervention in cardiometabolic disorders. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.120556
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Chunxiao Li, Qinyuan Zhu, Xinhang Cao +6 more · 2026 · Non-coding RNA research · Elsevier · added 2026-04-24
Aberrant differentiation of keratinocytes has been implicated in various skin diseases. However, the impact of lncRNA on keratinocyte differentiation and RNA alternative splicing remains poorly unders Show more
Aberrant differentiation of keratinocytes has been implicated in various skin diseases. However, the impact of lncRNA on keratinocyte differentiation and RNA alternative splicing remains poorly understood. The primary aim of this study was to delineate the landscape of differentially expressed lncRNAs in keratinocytes undergoing differentiation and to elucidate the underlying molecular mechanisms. Primary human keratinocytes (HKEn) were subjected to comprehensive microarray analysis to identify the differentially expressed lncRNAs upon calcium stimulation. Loss-of-function experiments were carried out to explore the role of NR037661 in keratinocyte differentiation. RNA sequencing analysis was performed to study the potential target genes of NR037761. RNA pull-down assay, SDS-PAGE, silver staining and mass spectrometry analysis were utilized to explore the potential proteins that interacted with NR037761 and participated in NR037761-mediated keratinocyte differentiation. The effects of NR037761 on the alternative splicing and expression of Angiopoietin-like 4 (ANGPTL4) were analyzed by RT-PCR and Western blot. NR037661 specifically interacts with the splicing factor Serine/arginine repetitive matrix protein 2 (SRRM2), facilitating its nuclear localization. This interaction modulates the alternative splicing (AS) of ANGPTL4 mRNA, ultimately influencing keratinocyte differentiation. Our findings illuminate a novel regulatory mechanism underlying keratinocyte differentiation, potentially revealing new therapeutic targets for skin diseases. Show less
📄 PDF DOI: 10.1016/j.ncrna.2025.10.003
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Qiang Li, Zhiqi Liao, Xinyao Hu +26 more · 2026 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Clinical application of mesenchymal stem cells for endometrial repair has been hampered by variability in cell quality, large-scale production, and uncertainty regarding the optimal delivery route. In Show more
Clinical application of mesenchymal stem cells for endometrial repair has been hampered by variability in cell quality, large-scale production, and uncertainty regarding the optimal delivery route. In this study, we investigated the therapeutic potential of clinical-grade human embryonic stem cell-derived immunity-and-matrix-regulatory cells (IMRCs) for treating refractory moderate-to-severe intrauterine adhesion (IUA). In a rabbit IUA model, sub-endometrial injection of IMRCs significantly reduced fibrosis and enhanced endometrial angiogenesis, outperforming uterine perfusion. Transcriptomic analysis revealed distinct pro-angiogenic gene expression profiles between the two delivery routes. In vitro, IMRCs co-cultured with endometrial stromal cells (ESCs) markedly enhanced angiogenic potential compared to either cell type alone. Protein array analysis of the co-culture supernatant showed elevated levels of angiogenic factors, with functional assays confirming that inhibition of ANGPTL4, a non-canonical pro-angiogenic mediator, impaired angiogenesis. In a first-in-human, single-center, phase 1 dose-escalation trial involving 18 patients with refractory IUA, high-dose sub-endometrial IMRC injection promoted angiogenesis, reduced uterine scarring, and improved pregnancy outcomes, with no safety concerns observed over 3 years of follow-up. These findings highlight the translational promise of IMRCs as a novel therapeutic strategy for endometrial regeneration in severe IUA. Show less
📄 PDF DOI: 10.1016/j.ymthe.2025.09.035
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Shiqian Liu, Ruiyang Ding, Linyuan Huang +4 more · 2026 · Journal of advanced research · Elsevier · added 2026-04-24
Urban particulate matter (UPM) is a major air pollutant affecting public health, with maternal exposure potentially leading to cardiac developmental disorders in offspring. However, the exact mechanis Show more
Urban particulate matter (UPM) is a major air pollutant affecting public health, with maternal exposure potentially leading to cardiac developmental disorders in offspring. However, the exact mechanisms underlying the intergenerational effects of UPM remain unclear. This study aimed to investigate the molecular mechanisms involved in cardiac developmental defects caused by maternal UPM exposure in offspring zebrafish. Female zebrafish were exposed to UPM for 21 days to examine intergenerational effects. The results indicated that maternal zebrafish in the exposed group exhibited ovarian damage and a reduced number of embryos and fertilization rates. Zebrafish offspring exhibited abnormal cardiac development, including pericardial edema and pathological heart injury. Mechanistically, transcriptomic analysis of the offspring indicated that UPM exposure induced significant modifications in the mitochondrial biogenesis pathway, with altered expression of mitochondrial function-related genes. Maternal UPM exposure impaired respiration in zebrafish embryos and increased angiopoietin-like 4 (ANGPTL4) expression in offspring hearts. In vitro, Angptl4 knockdown alleviated UPM-induced mitochondrial membrane potential reduction and mitochondrial reactive oxygen species overproduction in cardiomyocytes, whereas Angptl4 overexpression exacerbated UPM-induced mitochondrial toxicity. These findings show that maternal UPM exposure disrupts mitochondrial homeostasis by upregulating ANGPTL4 expression, leading to abnormal cardiac development in zebrafish offspring. Show less
📄 PDF DOI: 10.1016/j.jare.2025.05.041
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Yiyu Liang, Xianlu Li, Yichen Zhang +9 more · 2026 · ACS nano · ACS Publications · added 2026-04-24
Modifying nanomedicines with targeting ligands represents an encouraging strategy for active tumor targeting, but its clinical failure underscores ongoing challenges. Herein, a series of liposomes wit Show more
Modifying nanomedicines with targeting ligands represents an encouraging strategy for active tumor targeting, but its clinical failure underscores ongoing challenges. Herein, a series of liposomes with different targeting ligands (e.g., PEGylation, folic acid, mannose, RGD peptide, and melittin) were rationally designed to investigate the principles and mechanisms governing tumor targeting and penetration profiles. In primary and lung metastatic breast cancer models, these liposomes exhibited a systematic tendency of intratumor distribution, with melittin-modified liposomes showing optimal tumor targeting and therapeutic performance. Further studies revealed that the ligand modifications in liposomes could modulate the composition of their protein corona, particularly the level of Apolipoprotein A4 (ApoA4), which, in turn, influenced tumor targeting and intratumor distribution, ultimately affecting the therapeutic outcome of tumor inhibition and survival prolongation. This research provided a distinct correlation between ligand modification of liposomes and their Show less
no PDF DOI: 10.1021/acsnano.5c19739
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Cunming Yang, Zhen Ma, Xiao Wang +6 more · 2026 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Xinjiang Brown cattle are an important beef breed in Northwest China. Although multigenerational selective breeding has improved their growth performance, the accompanying molecular adaptations and po Show more
Xinjiang Brown cattle are an important beef breed in Northwest China. Although multigenerational selective breeding has improved their growth performance, the accompanying molecular adaptations and potential physiological trade- ofs remain insufficiently elucidated at the systemic level. This study aimed to decipher the dynamic serum proteomic profiles shaped by both ontogeny and generational selection in Xinjiang Brown cattle, and to identify the associated key proteins and pathways. Serum samples from 18 bulls across three genera- tions (A, B, C) at 3 and 9 months of age were analyzed using Tandem Mass Tag (TMT)-based quantitative proteomics. Under stringent quality control (FDR < 1%), 583 high-confidence proteins were identified. Diferentially expressed proteins (DEPs) were screened using thresholds of |fold change| ≥ 1.2 and This study reveals that the breeding strategy for Xinjiang Brown cattle prioritizes shaping a proteomic landscape that promotes growth and metabolism, potentially at the cost of atten- uated immune-vascular reactivity. The identified panel of candidate proteins pro- vides a molecular framework for evaluating breeding outcomes and designing balanced selection strategies. Follow-up research should further investigate the functions of these candidate proteins and validate their predictive value for health and production performance in independent herds. Show less
📄 PDF DOI: 10.3389/fvets.2026.1723813
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Jie Cai, Aohuan Huang, Linghui You +10 more · 2026 · Food research international (Ottawa, Ont.) · Elsevier · added 2026-04-24
Diet-based modulation of the gut microbiota has emerged as a promising strategy to alleviate obesity and its related complications. Our previous study demonstrated that polysaccharide derived from Cor Show more
Diet-based modulation of the gut microbiota has emerged as a promising strategy to alleviate obesity and its related complications. Our previous study demonstrated that polysaccharide derived from Cordyceps militaris (CMP) exerts anti-obesity effects, yet the specific mechanism linking gut microbiota to its metabolic impact remains unclear. Herein, we utilized murine models with distinct gut microbial profiles created via antibiotic cocktails to investigate these mechanisms. The protective effects of CMP against high-fat diet (HFD)-induced obesity and associated metabolic disturbances were substantially impaired in mice depleted of neomycin-sensitive gut bacteria. Metagenomic analyses further established that CMP required these bacteria to restore gut microbial homeostasis. Notably, we observed that CMP elevated hepatic levels of brassicasterol in a manner dependent on neomycin-sensitive gut bacteria. Brassicasterol treatment alone replicated the anti-obesity effects of CMP, as indicated by reduced body weight gain, improved lipid and glucose metabolism, and decreased inflammation. Through transcriptomic and functional analyses, we identified hepatic Apoa4 as a key downstream effector of brassicasterol. Our results indicated that brassicasterol upregulated Apoa4, facilitating lipid transport and suppressing inflammation both in vitro and in vivo. Collectively, our findings indicate that CMP exerts its anti-obesity effects through a neomycin-sensitive gut bacteria-brassicasterol-Apoa4 pathway. This work expands the mechanistic understanding of CMP and highlights a novel microbiota-metabolite-host regulatory axis for dietary intervention in metabolic disorders. Show less
no PDF DOI: 10.1016/j.foodres.2026.118574
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Hongrui Cao, Zhengcheng Zeng, Huangwei Shi +5 more · 2026 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
This study examined how different photoperiods affect net energy partitioning and explored the mechanisms via blood biochemistry, gut microbiota, and fecal metabolites. Twelve healthy crossbred pigs ( Show more
This study examined how different photoperiods affect net energy partitioning and explored the mechanisms via blood biochemistry, gut microbiota, and fecal metabolites. Twelve healthy crossbred pigs (47.7 ± 7.5 kg) were randomly allocated to two groups and subjected to a self-controlled crossover design. Following an 8-day baseline under a normal photoperiod (12L:12D, 12 h light:12 h dark), pigs were assigned to two photoperiod treatment groups: prolonged photoperiod (18L:6D, 18 h light:6 h dark; P group) and shortened photoperiod (6L:18D, 6 h light:18 h dark; S group). Measurements during the baseline (12L:12D) and treatment phases are designated as N1/P (for the P group) and N2/S (for the S group), respectively. The treatment periods were interspersed with the baseline 12L:12D photoperiod and repeated six times. It was observed that, compared to N2, shortened photoperiod (S) had significantly higher net energy deposition, net energy for protein deposition, and net energy for fat deposition ( Show less
📄 PDF DOI: 10.3390/ani16040688
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Na Huang, Heming Wang, Xiao Li +8 more · 2026 · Lipids in health and disease · BioMed Central · added 2026-04-24
Significant interindividual variability in radiosensitivity poses a major challenge to conventional radiation protection and radiotherapy. Current prediction strategies relying on DNA damage or genomi Show more
Significant interindividual variability in radiosensitivity poses a major challenge to conventional radiation protection and radiotherapy. Current prediction strategies relying on DNA damage or genomic analysis have inherent limitations, underscoring the need for minimally invasive serum biomarkers. While serum apolipoproteins are crucial regulators of lipid transport, metabolism, and cellular stress response, their role as biomarkers for radiosensitivity remains largely unexplored. A 7.3 Gy ⁶⁰Co γ-ray whole-body irradiation mouse model (with training and independent validation cohorts) was established to assess individual radiosensitivity. Pre-irradiation peripheral serum samples underwent high-throughput proteomics analysis to identify differential proteins (DEPs) linked to 30-day post-irradiation survival. KEGG and GO enrichment analyses were conducted to characterize DEP-associated pathways. An XGBoost machine learning model was built using candidate biomarkers, with SHAP analysis to define their predictive contributions; Cox proportional hazards and Pearson correlation analyses were applied to evaluate survival associations. DIA-based proteomics identified 580 DEPs in the training cohort and 449 in the validation cohort. KEGG and GO enrichment analyses confirmed that these DEPs were predominantly enriched in the cholesterol metabolism and reverse cholesterol transport pathways. The predictive model based on an apolipoprotein panel (ApoA1/ApoA2/ApoA4), established using the XGBoost algorithm, exhibited exceptional performance in the training cohort (AUC = 1) and maintained robust generalizability in an independent validation cohort (AUC = 0.833). Compared with non-survivors, survivors exhibited significantly elevated serum levels of ApoA1 and ApoA2 but markedly reduced levels of ApoA4. Cox proportional hazards regression analysis established ApoA1 and ApoA2 as independent protective factors, whereas high ApoA4 expression was an adverse prognostic indicator. Notably, ApoA4 levels also demonstrated a strong negative correlation with post-irradiation survival time. The serum apolipoprotein profile (ApoA1/ApoA2/ApoA4) serves not only as a promising minimally invasive biomarker for predicting individual radiosensitivity in mice but also reveals a critical link between the cholesterol metabolic pathway and radiation response. This finding lays a theoretical foundation for translating predictive, cholesterol metabolism-related biomarkers to support radiation response assessments. Given the limitations of animal models, subsequent studies are required to validate the clinical applicability of this panel in human cohorts, with the aim of offering an effective tool for personalized radiation protection and precise radiotherapy. The online version contains supplementary material available at 10.1186/s12944-026-02868-8. Show less
📄 PDF DOI: 10.1186/s12944-026-02868-8
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Ziyu Ge, Yang Yang, Pei Chen +12 more · 2026 · Biochemical pharmacology · Elsevier · added 2026-04-24
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive Show more
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive anthraquinone derived from Rheum palmatum, exhibits rapid and sustained antidepressant effects in both acute and chronic social defeat stress (CSDS) mouse models. Using quantitative proteomics on prefrontal cortex (PFC) samples from control, CSDS, Rhein-treated, and imipramine-treated cohorts, we identified differentially expressed proteins that revealed Rhein's multi-target regulatory profile. Functional enrichment and clustering analyses indicated that Rhein predominantly restores dysregulated pathways related to lipid metabolism, ribosomal translation, mitochondrial and endoplasmic reticulum (ER) function, and synaptic plasticity, forming a coherent mechanistic axis underlying its therapeutic effects. Comparative analysis with imipramine-treated mice further highlighted Rhein's distinct capacity to modulate organelle homeostasis and synaptic remodeling with greater breadth. Parallel reaction monitoring (PRM) and Western Blotting validated key proteins involved in mitochondrial functions (BNIP1, PISD, MRPL42, MRPS30, LRBA, IGHM), ER homeostasis (ACBD5, APOA4, RPL14), and synaptic plasticity (HDAC1, FAM3C, SSU72). These molecular findings suggest that Rhein exerts its antidepressant effects by restoring the functional integrity of mitochondria and the ER, thereby reprogramming synaptic plasticity. We inferred that this organelle-centered regulation further reinforces its potent modulation through multiple mechanisms and signaling pathways of synaptic plasticity, enabling Rhein to exert antidepressant effects through a coordinated, multi-layered mechanism. Collectively, our findings provide a systems-level mechanistic framework for Rhein's antidepressant efficacy and support its potential as a multi-pathway natural therapeutic, particularly for metabolic subtypes of depression. Show less
no PDF DOI: 10.1016/j.bcp.2025.117548
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Yuemiao Wang, Daren Wu, Dandan Sun +2 more · 2026 · Frontiers in pediatrics · Frontiers · added 2026-04-24
Wilson disease (WD) and familial hypertriglyceridemia (FHTG) are both genetic metabolic diseases, and their comorbidity is extremely rare. This article reports a case of WD with FHTG in a 12-year-old Show more
Wilson disease (WD) and familial hypertriglyceridemia (FHTG) are both genetic metabolic diseases, and their comorbidity is extremely rare. This article reports a case of WD with FHTG in a 12-year-old Chinese boy. The patient was diagnosed due to elevated transaminase levels, combined with clinical manifestations, copper metabolism indexes, lipid profile analysis, and genetic testing results (pathogenic mutations of Show less
📄 PDF DOI: 10.3389/fped.2026.1763338
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Yuwei Wang · 2026 · Nutrition & metabolism · BioMed Central · added 2026-04-24
Emerging evidence links the plasma lipidome to venous thromboembolism, but its causal relationship with portal vein thrombosis (PVT) remains unexplored. This study aimed to systematically screen for p Show more
Emerging evidence links the plasma lipidome to venous thromboembolism, but its causal relationship with portal vein thrombosis (PVT) remains unexplored. This study aimed to systematically screen for potential causal associations between 179 plasma lipid species and PVT risk, aiming to identify candidate biomarkers and explore underlying biological pathways. Using publicly available genome-wide association study (GWAS) data, we performed a two-sample Mendelian randomization (MR) analysis to assess the causal relationships between 179 plasma lipid species and PVT. Inverse-variance weighted (IVW) was the primary method, heterogeneity and pleiotropy were applied to evaluate potential pleiotropy and heterogeneity, and leave-one-out analysis verified result reliability. For lipid species showing nominally significant associations with PVT, lead SNPs were mapped to candidate genes to explore potential biological mechanisms. IVW analysis identified nominally significant associations ( Our study suggests potential links between specific plasma lipid species and PVT, although these associations did not survive rigorous multiple testing correction. It provides preliminary evidence that certain lipid species, notably phosphatidylcholine and sterol esters, may be implicated in PVT risk. The mapping of these lipids to candidate genes involved in lipid metabolism (FADS1, FADS2, APOE, APOA5, LIPC) offers mechanistic hypotheses for future research. Further studies are required to validate these preliminary associations and assess their translational potential. The online version contains supplementary material available at 10.1186/s12986-026-01084-6. Show less
📄 PDF DOI: 10.1186/s12986-026-01084-6
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Haoyu Wang, Jinling Yu, Fei Liang +5 more · 2026 · Journal of the American Nutrition Association · Taylor & Francis · added 2026-04-24
Controversies exist regarding the effects of calcium supplementation on lipid metabolism, and the time-specific effects and underlying mechanisms remain unclear. This study aims to elucidate the diffe Show more
Controversies exist regarding the effects of calcium supplementation on lipid metabolism, and the time-specific effects and underlying mechanisms remain unclear. This study aims to elucidate the differential impacts of calcium intervention at different times (morning/evening) on hepatic lipid metabolism and the molecular mechanisms involved. Forty female CD-1 (ICR) mice were randomly divided into four groups: Morning Control Group (MCN), Morning Calcium Intervention Group (MCI, intragastric administration of calcium carbonate at 08:00), Evening Control Group (ECN), and Evening Calcium Intervention Group (ECI, intragastric administration of calcium carbonate at 20:00). Mice were fed a normal calcium or low-calcium diet for 10 wk. Morning calcium intervention (MCI) in mice significantly increased serum and hepatic total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL) levels, and induced lipid droplet deposition and swelling in hepatocytes. Transcriptome and validation experiments showed upregulated hepatic PER1 expression in the MCI group, while PPARα and its downstream lipid metabolism genes (CPT1A, APOA5) were downregulated. In HepG2 cells, nighttime calcium incubation (NC) significantly increased intracellular TG and LDL contents, upregulated PER1 expression, and inhibited PPARα, CPT1A, and APOA5 expressions. Knocking down PER1 reversed the abnormal gene expression and lipid-elevating effects in the NC group. Collectively, our findings demonstrate that the circadian timing of calcium intake critically regulates hepatic lipid homeostasis Show less
no PDF DOI: 10.1080/27697061.2025.2557251
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Chang-Hao Sun, Xin-Yu Zhu, Zhi-Long Wang +5 more · 2026 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24
The ratio of uric acid to high-density lipoprotein cholesterol (UHR) is a novel comprehensive indicator related to dyslipidemia. However, the association between UHR and coronary artery disease (CAD) Show more
The ratio of uric acid to high-density lipoprotein cholesterol (UHR) is a novel comprehensive indicator related to dyslipidemia. However, the association between UHR and coronary artery disease (CAD) risk in patients with chronic kidney disease (CKD) remains unclear. After matching based on age and gender propensity scores, 2124 subjects were included and divided into the CKD group (708 cases) and the non-CKD group (1416 cases). The predictive performance of UHR for CAD was evaluated by the area under the curve (AUC), and the independent association between UHR and the risk of CAD onset was analyzed using a multivariate logistic regression model. The correlation and dose-response relationship between the ratio of uric acid to high-density lipoprotein cholesterol (UHR) and the risk of CAD were analyzed using LOESS fitting and restricted cubic spline (RCS) analysis. After matching, the multiple lipid-related indices (Triglycerides (TG), Remnant Cholesterol (RC), Atherogenic Index (AI), Atherogenic Index of Plasma (AIP), Triglyceride Glucose Index (TyG), Lipoprotein Composite Index (LCI), Triglyceride to High-Density Lipoprotein Cholesterol Ratio (TG/HDL-C), Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio (TC/HDL-C), Low-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio (LDL-C/HDL-C), UHR) in the CKD group were significantly higher than those in the non-CKD group. The AUC analysis showed that HDL-C, AIP, TG/HDL-C, and UHR had strong predictive performance in the overall cohort and the non-CKD group, while in the CKD group, HDL-C, AI, and TC/HDL-C are better predictive indicators. After adjusting for all confounding factors, multivariate regression analysis revealed that HDL-C, apolipoprotein A-1 (APOA-1), and the APOA-1/APOB ratio were independent protective factors for CAD in the entire cohort. Among them, the protective effect of HDL-C was the most stable (overall population aOR = 0.26, 95% CI: 0.17-0.39, p < 0.001), and it was significantly in both the CKD (aOR = 0.18, 95% CI: 0.09-0.40, p < 0.001) and non-CKD subgroups (aOR = 0.31, 95% CI: 0.18-0.52, p < 0.001). In CKD, UHR is significantly correlated with CAD (aOR = 6.23, 95% CI: 1.89-20.60, p = 0.003), and the association was more significant in the non-CKD group (aOR = 15.15, 95% CI: 4.20-54.72, p < 0.001). CKD status significantly modified the association between UHR and CAD (P for interaction = 0.015). LOESS fitting suggested that UHR was positively correlated with the probability of CAD occurrence (the correlation was more significant at low UHR, and it slowed down when UHR > 0.5, r = 0.2, p < 0.001), and negatively correlated with eGFR (r = -0.38, p < 0.001). RCS analysis confirmed a significant nonlinear association between UHR and CAD (overall P < 0.001, nonlinear P = 0.002), and the risk of CAD increased when UHR was > 0.41 in CKD patients. UHR is an independent risk factor for coronary heart disease, with higher adjusted OR values and more significant independent risk effects in non-CKD populations. Show less
no PDF DOI: 10.1186/s12872-026-05838-1
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Yaqun Fang, Zhiye Zhang, Qiqi Cao +20 more · 2026 · Arteriosclerosis, thrombosis, and vascular biology · added 2026-04-24
ApoB (apolipoprotein B)-containing lipoproteins are causal risk factors for atherosclerotic coronary artery disease (CAD). Since human cathelicidin LL-37 binds to ApoB-100 in this pathological context Show more
ApoB (apolipoprotein B)-containing lipoproteins are causal risk factors for atherosclerotic coronary artery disease (CAD). Since human cathelicidin LL-37 binds to ApoB-100 in this pathological context, we investigated whether the circulating LL-37-ApoB-100 complex could serve as a biomarker for CAD. We performed surface plasmon resonance and protein-protein docking to demonstrate the direct LL-37-ApoB-100 interaction. We developed a specific polyclonal antibody against the complex and measured its levels in human atherosclerotic plaques and plasma, as well as in We identified that LL-37 directly interacted with multiple distinct binding sites on ApoB-100. Plasma levels of LL-37-ApoB-100 complex were significantly elevated in human patients with atherosclerosis. Consistently, levels of this complex were positively correlated with atherosclerotic plaque area in Circulating LL-37-ApoB-100 levels are strongly associated with angiographically documented CAD, highlighting LL-37-ApoB-100 as an independent predictor for CAD. Show less
no PDF DOI: 10.1161/ATVBAHA.125.323486
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Tianfeng Zhang, Chenghua Wang, Zhenghui Wang +4 more · 2026 · International journal of cardiology. Cardiovascular risk and prevention · Elsevier · added 2026-04-24
This study aims to evaluate the association between multiple lipid indices and coronary collateral circulation (CCC) in patients diagnosed with acute ST-segment elevation myocardial infarction (STEMI) Show more
This study aims to evaluate the association between multiple lipid indices and coronary collateral circulation (CCC) in patients diagnosed with acute ST-segment elevation myocardial infarction (STEMI). This was a cross-sectional retrospective study involving 421 patients with STEMI who underwent coronary angiography between January 2022 and December 2024. Participants were categorized into a poor CCC group (Rentrop grade 0-1) and a good CCC group (Rentrop grade 2-3) according to Rentrop grading criteria. The following lipid parameters were evaluated as both continuous and categorical variables: total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), lipoprotein(a) [Lp(a)], apolipoprotein B (ApoB), apolipoprotein A-I (ApoA-I), non-HDL-C/HDL-C, ApoB/ApoA-I, atherogenic index of plasma (AIP), and lipoprotein composite index (LCI). The associations between these lipid indices and CCC status were assessed using multivariate logistic regression and receiver operating characteristic (ROC) curve analysis. Multivariate logistic regression analysis revealed that higher HDL-C quartiles were significantly associated with reduced odds of poor CCC (odds ratio [OR]: 0.544, 95% confidence interval [CI]: 0.351-0.771, P < 0.05), whereas elevated LDL-C (OR: 29.299, 95% CI: 3.562-240.976, P < 0.05), non-HDL-C (OR: 50.140, 95% CI: 5.408-464.834, P < 0.01), and non-HDL-C/HDL-C (OR: 4.510, 95% CI: 1.186-25.368, P < 0.05) quartiles were significantly associated with increased odds of poor CCC. Receiver operating characteristic (ROC) curve analysis demonstrated that LDL-C (cutoff: 3.265, AUC: 0.647, 95% CI: 0.573-0.721, P < 0.001), non-HDL-C (cutoff: 2.735, AUC: 0.752, 95% CI: 0.688-0.816, P < 0.001), and non-HDL-C/HDL-C (cutoff: 2.393, AUC: 0.686, 95% CI: 0.611-0.761, P < 0.001) exhibited favorable predictive performance for poor CCC. Stratification analysis showed that the highest prevalence of poor CCC was observed in patients with concurrently elevated levels of LDL-C, non-HDL-C, and non-HDL-C/HDL-C. Several lipid indices-including LDL-C, non-HDL-C, and the non-HDL-C/HDL-C ratio-are significantly associated with impaired CCC in patients with STEMI. Notably, non-HDL-C exhibits the strongest association with CCC dyscrasia and therefore warrants early clinical attention. Show less
📄 PDF DOI: 10.1016/j.ijcrp.2026.200615
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An-Xin Wu, Xing-Jin Wang, Chen Zhao +5 more · 2026 · Pharmacological research · Elsevier · added 2026-04-24
Elevated lipoprotein(a) [Lp(a)] is a genetically determined and independent risk factor for atherosclerotic cardiovascular disease (ASCVD) that is largely resistant to conventional lipid-lowering ther Show more
Elevated lipoprotein(a) [Lp(a)] is a genetically determined and independent risk factor for atherosclerotic cardiovascular disease (ASCVD) that is largely resistant to conventional lipid-lowering therapies. Novel Lp(a)-targeted agents, including small interfering RNA (siRNA), antisense oligonucleotides (ASO), and the oral small-molecule inhibitor muvalaplin, have shown potent efficacy in early trials. We conducted a systematic review and network meta-analysis to comprehensively compare their efficacy and safety. A total of 25 randomized controlled trials (RCTs) involving 7715 participants were included, evaluating six siRNA agents, four ASO agents, and one small-molecule inhibitor. The primary outcome was percentage change from baseline in Lp(a). Secondary outcomes included absolute change in Lp(a), percentage changes in apolipoprotein B (apoB) and low-density lipoprotein cholesterol (LDL-C), and adverse events. SiRNA therapies achieved the greatest Lp(a) reductions (olpasiran: mean difference [MD] -92.1%, 95% CI -100.1 to -84.0%; zerlasiran: -80.6%, 95% CI -87.7 to -73.5%), followed by muvalaplin (-76.8%, 95% CI -90.3 to -63.2%) and ASO therapy (pelacarsen: -54.2%, 95% CI -72.2 to -36.2%; all P < 0.001). Most agents achieved absolute Lp(a) reductions exceeding 105 nmol/L, suggesting clinically meaningful benefit. Baseline Lp(a) levels significantly modified treatment response (P < 0.001), and concomitant proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor use further enhanced LDL-C reduction (P = 0.024). All therapies were well tolerated, with injection-site reactions most frequent for injectables, while muvalaplin was well tolerated. These findings indicate that targeted Lp(a)-lowering therapies substantially reduce circulating Lp(a), with siRNA showing the greatest potency and muvalaplin offering a convenient oral alternative for personalized ASCVD risk reduction. Show less
no PDF DOI: 10.1016/j.phrs.2026.108178
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Min Zuo, Haixia Xu, Yuying Yang +7 more · 2026 · Communications biology · Nature · added 2026-04-24
Adolescent Idiopathic Scoliosis (AIS) is the most common form of spinal deformity among adolescents. To explore its etiology of progression and scoliosis-modifying drugs, chondrocytic senescence was c Show more
Adolescent Idiopathic Scoliosis (AIS) is the most common form of spinal deformity among adolescents. To explore its etiology of progression and scoliosis-modifying drugs, chondrocytic senescence was confirmed in AIS facet joint cartilage by analyzing clinical specimen. Furthermore, through 4D/480 label-free proteomics analysis, we identified an exosome-mediated positive feedback loop during scoliosis progression, which driving the elevation of cholesterol flow between spinal cartilage and vertebra. To further investigate the pathological significance of the loop in vivo, high-cholesterol flow was reconstructed in C57BL/6 J mice by injecting with recombinant adeno-associated virus rAAV9-Runx2-HMGCR. Our results confirmed the important role of the positive feedback loop in the development of scoliosis. Meanwhile, Avasimibe or/and Corylin were used to delay the scoliosis progression by targeting the key exosomal proteins APOB (Apolipoprotein B-100) or/and HSP90β (Heat Shock Protein 90-beta). This research extends the etiology of scoliosis progression and provides an alternative perspective for scoliosis non-surgical treatment. Show less
📄 PDF DOI: 10.1038/s42003-026-09960-w
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Liting Pang, Chaoyi Wang, Wenjing Zhao +4 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Cardiovascular and renal diseases exhibit a close bidirectional interaction, which often leads to the development of cardio-renal syndrome (CRS)-a clinical condition in which cardiac dysfunction furth Show more
Cardiovascular and renal diseases exhibit a close bidirectional interaction, which often leads to the development of cardio-renal syndrome (CRS)-a clinical condition in which cardiac dysfunction further aggravates renal injury. Type I CRS is characterized by acute kidney injury secondary to acute heart failure, and this sub-type is closely related to elevated morbidity and mortality in patients with coronary artery disease (CAD). Despite the availability of traditional biomarkers, there is an unmet need for more sensitive indicators to identify high-risk patients for Type I CRS in CAD patients. The apolipoprotein B (ApoB)/apolipoprotein A1 (ApoA1) ratio has emerged as a promising predictor of cardiovascular risk, yet its role in CRS remains unclear. This study aimed to evaluate the association between the ApoB/ApoA1 ratio and Type I CRS in patients with CAD, and to assess its value as a biomarker for identifying high-risk patients. A retrospective cohort study was carried out on 269 CAD patients complicated with heart failure who were hospitalized in our hospital from 2022 to 2024. According to the estimated glomerular filtration rate (eGFR) results, the enrolled patients were divided into two subgroups: the simple heart failure (SHF) group and the type I CRS group. Data on demographics, clinical history, biochemical measurements, echocardiographic and coronary angiography assessments, and renal function were collected. A multivariable logistic regression model was used to assess the association between the ApoB/ApoA1 ratio and CRS, adjusting for potential confounders. Correlation analyses were performed to explore the relationships between key variables and the occurrence of type I CRS. A multivariable logistic regression model was used to assess the association between the ApoB/ApoA1 ratio and CRS. Furthermore, a receiver operating characteristic (ROC) curve was constructed to evaluate the predictive accuracy of the ApoB/ApoA1 ratio for type I CRS. A total of 269 patients were enrolled. Significant differences were observed between the simple heart failure (SHF) group and the CRS group in terms of age, history of diabetes mellitus, levels of triglycerides (TG), apolipoprotein A1 (apo-A1), apolipoprotein B (apo-B), ApoB/ApoA1 ratio, and serum creatinine (Scr). Patients in the CRS group were older, had a higher proportion of diabetes mellitus, higher levels of TG, apo-B, and Scr, a higher ApoB/ApoA1 ratio, but lower levels of apo-A1 compared to the SHF group. Multivariable logistic regression analysis identified age and the ApoB/ApoA1 ratio as independent risk factors for CRS. The receiver operating characteristic (ROC) curve analysis showed that the ApoB/ApoA1 ratio had a moderate level of predictive accuracy for Type I CRS, with an area under the curve (AUC) of 0.782. The ApoB/ApoA1 ratio is moderately associated with the risk of developing Type I CRS in patients with CAD. This ratio could serve as a clinically relevant biomarker for early identification of in-hospital Type I CRS risk in CAD patients with acute heart failure, potentially aiding in the implementation of early and targeted interventions to improve patient outcomes. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1754713
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Jiaqiang Hu, Jun Wang, Haixia Zhang +4 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Lipoprotein(a)-targeted therapies are emerging approaches for lowering lipoprotein(a) [lp(a)]. We conducted a systematic review and network meta-analysis to evaluate the efficacy and safety of lipopro Show more
Lipoprotein(a)-targeted therapies are emerging approaches for lowering lipoprotein(a) [lp(a)]. We conducted a systematic review and network meta-analysis to evaluate the efficacy and safety of lipoprotein(a)-targeted therapies in patients. We searched PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) up to May 6, 2025, for randomized controlled trials (RCTs) with intervention duration of at least 12 weeks. The primary outcomes were percentage and absolute changes in Lp(a). Secondary outcomes included changes in low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (apoB), and safety outcomes including adverse events (AEs), serious adverse events (SAEs), and injection-site reactions. A frequentist framework network meta- analysis was performed. Nine studies involving 1,432 participants were included. All six Lp(a)-targeted therapies significantly reduced Lp(a) levels. Compared with placebo, Olpasiran was the most effective therapy for both percentage [mean difference: -92.06, 95% (-109.80; -74.32), Lp(a)-targeted therapies achieved substantial reductions in Lp(a). Olpasiran was the most effective agent in lowering Lp(a) levels. These therapies also improved LDL-C and apoB. The majority of Lp(a)-targeted therapies demonstrate generally favorable safety profiles; However, injection-site reactions, particularly with Zerlasiran, warrant careful consideration. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251069288, PROSPERO CRD420251069288. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1758366
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Hechuan Wang, Yunuo Liu, Ke Jiang +6 more · 2026 · Poultry science · Elsevier · added 2026-04-24
Clutch length is a key determinant of reproductive efficiency in geese and strongly positively correlates with egg production. We recorded daily egg production in 280 individually housed Zi geese, cal Show more
Clutch length is a key determinant of reproductive efficiency in geese and strongly positively correlates with egg production. We recorded daily egg production in 280 individually housed Zi geese, calculated clutch-related indices, and selected 12 geese to form long-clutch (LC) and short-clutch (SC) groups for ovarian transcriptomic, proteomic, and metabolomic analyses. The results showed that egg number, large clutch length, large clutch number, average clutch length, and average clutch number were significantly higher in LC than in SC groups (P < 0.0001). Transcriptomic analysis identified 885 differentially expressed genes enriched in oocyte development and ovarian steroidogenesis, with APOB, PLA2G4C, MMP2, MMP9, and NOBOX as key genes; proteomic analysis identified 437 differentially abundant proteins enriched in arachidonic acid metabolism and mitophagy, with CXCL12, RARB, and MAD2L1 as key proteins; and metabolomic analysis identified 35 differentially abundant metabolites enriched in glycolysis/gluconeogenesis, with lactic acid, guanidinoacetic acid, and 3-hydroxybutyrylcarnitine as key metabolites. Integration of multi-omics datasets highlighted a lactate-associated cross-omics signature supported by YWHAZ at the protein level and by the lactate transporter SLC16A3. Collectively, these findings deepen our understanding of the molecular basis underlying clutch-length variation in goose ovaries and highlight candidate genes, proteins, and metabolites for future functional validation. Show less
📄 PDF DOI: 10.1016/j.psj.2026.106731
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Yu Wang, Li Chen, Yingze Ma +8 more · 2026 · Nature communications · Nature · added 2026-04-24
Dietary fat absorption is among the most energy-demanding processes of nutrient uptake. Fatty acid activation, triglyceride synthesis, and the trafficking of chylomicrons through the secretory pathway Show more
Dietary fat absorption is among the most energy-demanding processes of nutrient uptake. Fatty acid activation, triglyceride synthesis, and the trafficking of chylomicrons through the secretory pathway - all require ATP. How enterocytes accommodate the surge in ATP consumption following fat uptake is unclear. We show that the purine biosynthesis/salvage pathway supplies necessary ATP and that Ankyrin Repeat Domain 9 (ANKRD9) couples ATP synthesis and lipoprotein trafficking. Ankrd9 regulates enzymes within the purine biosynthesis pathway to increase ATP synthesis and facilitate Golgi dynamics. Intracellular localization of ANKRD9 is lipid and ATP-dependent. Inactivation of Ankrd9 in mice reduces intestinal ATP despite intact mitochondrial and glycolytic function, alters Golgi morphology, delays ApoB/chylomicron trafficking, and causes lipid accumulation in enterocytes, along with a lean body phenotype. Taken together, the results reveal a previously unrecognized mechanism that regulates lipid absorption in enterocytes and identify ANKRD9 as a central component of this mechanism. Show less
no PDF DOI: 10.1038/s41467-026-70332-3
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Weijian Wang, Jiangping Ye, Xinyi Hu +3 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Coronary artery calcification (CAC), a hallmark of coronary atherosclerosis, links closely to dysregulated lipid metabolism and chronic inflammation. Proprotein convertase subtilisin/kexin type 9 (PCS Show more
Coronary artery calcification (CAC), a hallmark of coronary atherosclerosis, links closely to dysregulated lipid metabolism and chronic inflammation. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors exert potent lipid-lowering and anti-inflammatory effects, holding translational potential for vascular calcification intervention. However, evidence on PCSK9 inhibition's impact on vascular calcification remains inconsistent. Here, we combined genetic causal analysis with First, we used two-sample Mendelian randomization (MR) and multivariable Mendelian randomization to identify lipid profiles genetically associated with coronary artery calcification. Subsequently, we investigated the value of the PCSK9 gene as a potential therapeutic target for CAC through drug target MR and colocalization analysis, and screened for potential inflammatory mediators via Mediation MR analyses. Following the completion of the aforementioned analyses, we verified the beneficial effect of PCSK9 inhibitors on delaying vascular calcification through animal experiments and cell experiments. MR analysis revealed that genetic proxies for apolipoprotein B (ApoB) (OR=1.64; 95%CI: 1.42-1.90; Inhibition of PCSK9 may effectively slow the progression of coronary artery calcification, with inflammatory mediators such as FGF23 playing key regulatory roles in this process. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1767013
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