👤 Xueyi Wang

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Also published as: A Wang, Ai-Ling Wang, Ai-Ting Wang, Aihua Wang, Aijun Wang, Aili Wang, Aimin Wang, Aiting Wang, Aixian Wang, Aiyun Wang, Aizhong Wang, Alexander Wang, Alice Wang, Allen Wang, Anlai Wang, Anli Wang, Annette Wang, Anni Wang, Anqi Wang, Anthony Z Wang, Anxiang Wang, Anxin Wang, Ao Wang, Aoli Wang, B R Wang, B Wang, Baihan Wang, Baisong Wang, Baitao Wang, Bangchen Wang, Banghui Wang, Bangmao Wang, Bangshing Wang, Bao Wang, Bao-Long Wang, Baocheng Wang, Baofeng Wang, Baogui Wang, Baojun Wang, Baoli Wang, Baolong Wang, Baoming Wang, Baosen Wang, Baowei Wang, Baoying Wang, Baoyun Wang, Bei Bei Wang, Bei Wang, Beibei Wang, Beilan Wang, Beilei Wang, Ben Wang, Benjamin H Wang, Benzhong Wang, Bi Wang, Bi-Dar Wang, Biao Wang, Bicheng Wang, Bijue Wang, Bin Wang, Bin-Xue Wang, Binbin Wang, Bing Qing Wang, Bing Wang, Binghai Wang, Binghan Wang, Bingjie Wang, Binglong Wang, Bingnan Wang, Bingyan Wang, Bingyu Wang, Binquan Wang, Biqi Wang, Bo Wang, Bochu Wang, Boyu Wang, Bruce Wang, C Wang, C Z Wang, Cai Ren Wang, Cai-Hong Wang, Cai-Yun Wang, Cailian Wang, Caiqin Wang, Caixia Wang, Caiyan Wang, Can Wang, Cangyu Wang, Carol A Wang, Catherine Ruiyi Wang, Cenxuan Wang, Chan Wang, Chang Wang, Chang-Yun Wang, Changduo Wang, Changjing Wang, Changliang Wang, Changlong Wang, Changqian Wang, Changtu Wang, Changwei Wang, Changying Wang, Changyu Wang, Changyuan Wang, Changzhen Wang, Chao Wang, Chao-Jun Wang, Chao-Yung Wang, Chaodong Wang, Chaofan Wang, Chaohan Wang, Chaohui Wang, Chaojie Wang, Chaokui Wang, Chaomeng Wang, Chaoqun Wang, Chaoxian Wang, Chaoyi Wang, Chaoyu Wang, Chaozhan Wang, Charles C N Wang, Chau-Jong Wang, Chen Wang, Chen-Cen Wang, Chen-Ma Wang, Chen-Yu Wang, Chenchen Wang, Chenfei Wang, Cheng An Wang, Cheng Wang, Cheng-Cheng Wang, Cheng-Jie Wang, Cheng-zhang Wang, Chengbin Wang, Chengcheng Wang, Chenggang Wang, Chenghao Wang, Chenghua Wang, Chengjian Wang, Chengjun Wang, Chenglin Wang, Chenglong Wang, Chengniu Wang, Chengqiang Wang, Chengshuo Wang, Chenguang Wang, Chengwen Wang, Chengyan Wang, Chengyu Wang, Chengze Wang, Chenji Wang, Chenliang Wang, Chenwei Wang, Chenxi Wang, Chenxin Wang, Chenxuan Wang, Chenyang Wang, Chenyao Wang, Chenyin Wang, Chenyu Wang, Chenzi Wang, Chi Chiu Wang, Chi Wang, Chi-Ping Wang, Chia-Chuan Wang, Chia-Lin Wang, Chien-Hsun Wang, Chien-Wei Wang, Chih-Chun Wang, Chih-Hao Wang, Chih-Hsien Wang, Chih-Liang Wang, Chih-Yang Wang, Chih-Yuan Wang, Chijia Wang, Ching C Wang, Ching-Jen Wang, Chiou-Miin Wang, Chong Wang, Chongjian Wang, Chonglong Wang, Chongmin Wang, Chongze Wang, Christina Wang, Christine Wang, Chu Wang, Chuan Wang, Chuan-Chao Wang, Chuan-Hui Wang, Chuan-Jiang Wang, Chuan-Wen Wang, Chuang Wang, Chuanhai Wang, Chuansen Wang, Chuansheng Wang, Chuanxin Wang, Chuanyue Wang, Chuduan Wang, Chun Wang, Chun-Chieh Wang, Chun-Juan Wang, Chun-Li Wang, Chun-Lin Wang, Chun-Ting Wang, Chun-Xia Wang, Chung-Hsi Wang, Chung-Hsing Wang, Chung-Teng Wang, Chunguo Wang, Chunhong Wang, Chuning Wang, Chunjiong Wang, Chunjuan Wang, Chunle Wang, Chunli Wang, Chunlong Wang, Chunmei Wang, Chunsheng Wang, Chunting Wang, Chunxia Wang, Chunxue Wang, Chunyan Wang, Chunyang Wang, Chunyi Wang, Chunyu Wang, Chuyao Wang, Cindy Wang, Ciyang Wang, Cong Wang, Congcong Wang, Congrong Wang, Congrui Wang, Cui Wang, Cui-Fang Wang, Cui-Shan Wang, Cuili Wang, Cuiling Wang, Cuizhe Wang, Cun-Yu Wang, Cunchuan Wang, Cunyi Wang, D Wang, Da Wang, Da-Cheng Wang, Da-Li Wang, Da-Yan Wang, Da-Zhi Wang, Dadong Wang, Dai Wang, Daijun Wang, Daiwei Wang, Daixi Wang, Dajia Wang, Dake Wang, Dali Wang, Dalong Wang, Dalu Wang, Dan Wang, Dan-Dan Wang, Danan Wang, Dandan Wang, Danfeng Wang, Dang Wang, Dangfeng Wang, Danling Wang, Danqing Wang, Danxin Wang, Danyang Wang, Dao Wen Wang, Dao-Wen Wang, Dao-Xin Wang, Daolong Wang, Daoping Wang, Daozhong Wang, Dapeng Wang, Daping Wang, Daqi Wang, Daqing Wang, David Q H Wang, David Q-H Wang, David Wang, Dawei Wang, Dayan Wang, Dayong Wang, Dazhi Wang, De-He Wang, Dedong Wang, Dehao Wang, Deli Wang, Delin Wang, Delong Wang, Demin Wang, Deming Wang, Dengbin Wang, Dennis Qing Wang, Dennis Wang, Deqi Wang, Deshou Wang, Dezhong Wang, Di Wang, Dinghui Wang, Dingting Wang, Dingxiang Wang, Dong D Wang, Dong Hao Wang, Dong Wang, Dong-Dong Wang, Dong-Jie Wang, Dong-Mei Wang, DongWei Wang, Dongdong Wang, Donggen Wang, Donghao Wang, Donghong Wang, Donghui Wang, Dongliang Wang, Donglin Wang, Dongmei Wang, Dongqin Wang, Dongshi Wang, Dongxia Wang, Dongxu Wang, Dongyan Wang, Dongyang Wang, Dongyi Wang, Dongying Wang, Dongyu Wang, Doudou Wang, Du Wang, Duan Wang, Duanyang Wang, Duo-Ping Wang, E Wang, Edward Wang, En-bo Wang, En-hua Wang, Endi Wang, Enhua Wang, Er-Jin Wang, Erfei Wang, Erika Y Wang, Ermao Wang, Erming Wang, Ertao Wang, Eryao Wang, Eunice S Wang, Exing Wang, F Wang, Fa-Kai Wang, Fan Wang, Fanchang Wang, Fang Wang, Fang-Tao Wang, Fangfang Wang, Fangjie Wang, Fangjun Wang, Fangyan Wang, Fangyong Wang, Fangyu Wang, Fanhua Wang, Fanwen Wang, Fanxiong Wang, Fei Wang, Fei-Fei Wang, Fei-Yan Wang, Feida Wang, Feifei Wang, Feijie Wang, Feimiao Wang, Feixiang Wang, Feiyan Wang, Fen Wang, Feng Wang, Feng-Sheng Wang, Fengchong Wang, Fengge Wang, Fenghua Wang, Fengliang Wang, Fenglin Wang, Fengling Wang, Fengqiang Wang, Fengyang Wang, Fengying Wang, Fengyong Wang, Fengyun Wang, Fengzhen Wang, Fengzhong Wang, Fu Wang, Fu-Sheng Wang, Fu-Yan Wang, Fu-Zhen Wang, Fubao Wang, Fubing Wang, Fudi Wang, Fuhua Wang, Fuqiang Wang, Furong Wang, Fuwen Wang, Fuxin Wang, Fuyan Wang, G Q Wang, G Wang, G-W Wang, Gan Wang, Gang Wang, Ganggang Wang, Ganglin Wang, Gangyang Wang, Ganyu Wang, Gao T Wang, Gao Wang, Gaofu Wang, Gaopin Wang, Gavin Wang, Ge Wang, Geng Wang, Genghao Wang, Gengsheng Wang, Gongming Wang, Guan Wang, Guan-song Wang, Guandi Wang, Guanduo Wang, Guang Wang, Guang-Jie Wang, Guang-Rui Wang, Guangdi Wang, Guanghua Wang, Guanghui Wang, Guangliang Wang, Guangming Wang, Guangsuo Wang, Guangwen Wang, Guangyan Wang, Guangzhi Wang, Guanrou Wang, Guanru Wang, Guansong Wang, Guanyun Wang, Gui-Qi Wang, Guibin Wang, Guihu Wang, Guihua Wang, Guimin Wang, Guiping Wang, Guiqun Wang, Guixin Wang, Guixue Wang, Guiying Wang, Guo-Du Wang, Guo-Hua Wang, Guo-Liang Wang, Guo-Ping Wang, Guo-Quan Wang, Guo-hong Wang, GuoYou Wang, Guobin Wang, Guobing Wang, Guodong Wang, Guohang Wang, Guohao Wang, Guoliang Wang, Guoling Wang, Guoping Wang, Guoqian Wang, Guoqiang Wang, Guoqing Wang, Guorong Wang, Guowen Wang, Guoxiang Wang, Guoxiu Wang, Guoyi Wang, Guoying Wang, Guozheng Wang, H J Wang, H Wang, H X Wang, H Y Wang, H-Y Wang, Hai Bo Wang, Hai Wang, Hai Yang Wang, Hai-Feng Wang, Hai-Jun Wang, Hai-Long Wang, Haibin Wang, Haibing Wang, Haibo Wang, Haichao Wang, Haichuan Wang, Haifei Wang, Haifeng Wang, Haihe Wang, Haihong Wang, Haihua Wang, Haijiao Wang, Haijing Wang, Haijiu Wang, Haikun Wang, Hailei Wang, Hailin Wang, Hailing Wang, Hailong Wang, Haimeng Wang, Haina Wang, Haining Wang, Haiping Wang, Hairong Wang, Haitao Wang, Haiwei Wang, Haixia Wang, Haixin Wang, Haixing Wang, Haiyan Wang, Haiying Wang, Haiyong Wang, Haiyun Wang, Haizhen Wang, Han Wang, Hanbin Wang, Hanbing Wang, Hanchao Wang, Handong Wang, Hang Wang, Hangzhou Wang, Hanmin Wang, Hanping Wang, Hanqi Wang, Hanying Wang, Hanyu Wang, Hanzhi Wang, Hao Wang, Hao-Ching Wang, Hao-Hua Wang, Hao-Tian Wang, Hao-Yu Wang, Haobin Wang, Haochen Wang, Haohao Wang, Haohui Wang, Haojie Wang, Haolong Wang, Haomin Wang, Haoming Wang, Haonan Wang, Haoping Wang, Haoqi Wang, Haoran Wang, Haowei Wang, Haoxin Wang, Haoyang Wang, Haoyu Wang, Haozhou Wang, He Wang, He-Cheng Wang, He-Ling Wang, He-Ping Wang, He-Tong Wang, Hebo Wang, Hechuan Wang, Heling Wang, Hemei Wang, Heming Wang, Heng Wang, Heng-Cai Wang, Hengjiao Wang, Hengjun Wang, Hequn Wang, Hesuiyuan Wang, Heyong Wang, Hezhi Wang, Hong Wang, Hong Yi Wang, Hong-Gang Wang, Hong-Hui Wang, Hong-Kai Wang, Hong-Qin Wang, Hong-Wei Wang, Hong-Xia Wang, Hong-Yan Wang, Hong-Yang Wang, Hong-Ying Wang, Hongbin Wang, Hongbing Wang, Hongbo Wang, Hongcai Wang, Hongda Wang, Hongdan Wang, Hongfang Wang, Hongjia Wang, Hongjian Wang, Hongjie Wang, Hongjuan Wang, Hongkun Wang, Honglei Wang, Hongli Wang, Honglian Wang, Honglun Wang, Hongmei Wang, Hongpin Wang, Hongqian Wang, Hongshan Wang, Hongsheng Wang, Hongtao Wang, Hongwei Wang, Hongxia Wang, Hongxin Wang, Hongyan Wang, Hongyang Wang, Hongyi Wang, Hongyin Wang, Hongying Wang, Hongyu Wang, Hongyuan Wang, Hongyue Wang, Hongyun Wang, Hongze Wang, Hongzhan Wang, Hongzhuang Wang, Horng-Dar Wang, Houchun Wang, Hsei-Wei Wang, Hsueh-Chun Wang, Hu WANG, Hua Wang, Hua-Qin Wang, Hua-Wei Wang, Huabo Wang, Huafei Wang, Huai-Zhou Wang, Huaibing Wang, Huaili Wang, Huaizhi Wang, Huajin Wang, Huajing Wang, Hualin Wang, Hualing Wang, Huan Wang, Huan-You Wang, Huang Wang, Huanhuan Wang, Huanyu Wang, Huaquan Wang, Huating Wang, Huawei Wang, Huaxiang Wang, Huayang Wang, Huei Wang, Hui Miao Wang, Hui Wang, Hui-Hui Wang, Hui-Li Wang, Hui-Nan Wang, Hui-Yu Wang, HuiYue Wang, Huie Wang, Huiguo Wang, Huihua Wang, Huihui Wang, Huijie Wang, Huijun Wang, Huilun Wang, Huimei Wang, Huimin Wang, Huina Wang, Huiping Wang, Huiquan Wang, Huiqun Wang, Huishan Wang, Huiting Wang, Huiwen Wang, Huixia Wang, Huiyan Wang, Huiyang Wang, Huiyao Wang, Huiying Wang, Huiyu Wang, Huizhen Wang, Huizhi Wang, Huming Wang, I-Ching Wang, Iris X Wang, Isabel Z Wang, J J Wang, J P Wang, J Q Wang, J Wang, J Z Wang, J-Y Wang, Jacob E Wang, James Wang, Jeffrey Wang, Jen-Chun Wang, Jen-Chywan Wang, Jennifer E Wang, Jennifer T Wang, Jennifer X Wang, Jenny Y Wang, Jeremy R Wang, Jeremy Wang, Ji M Wang, Ji Wang, Ji-Nuo Wang, Ji-Yang Wang, Ji-Yao Wang, Ji-zheng Wang, Jia Bei Wang, Jia Bin Wang, Jia Wang, Jia-Liang Wang, Jia-Lin Wang, Jia-Mei Wang, Jia-Peng Wang, Jia-Qi Wang, Jia-Qiang Wang, Jia-Ying Wang, Jia-Yu Wang, Jiabei Wang, Jiabo Wang, Jiafeng Wang, Jiafu Wang, Jiahao Wang, Jiahui Wang, Jiajia Wang, Jiakun Wang, Jiale Wang, Jiali Wang, Jialiang Wang, Jialin Wang, Jialing Wang, Jiamin Wang, Jiaming Wang, Jian Wang, Jian'an Wang, Jian-Bin Wang, Jian-Guo Wang, Jian-Hong Wang, Jian-Long Wang, Jian-Wei Wang, Jian-Xiong Wang, Jian-Yong Wang, Jian-Zhi Wang, Jian-chun Wang, Jianan Wang, Jianbing Wang, Jianbo Wang, Jianding Wang, Jianfang Wang, Jianfei Wang, Jiang Wang, Jiangbin Wang, Jiangbo Wang, Jianghua Wang, Jianghui Wang, Jiangong Wang, Jianguo Wang, Jianhao Wang, Jianhua Wang, Jianhui Wang, Jiani Wang, Jianjiao Wang, Jianjie Wang, Jianjun Wang, Jianle Wang, Jianli Wang, Jianlin Wang, Jianliu Wang, Jianlong Wang, Jianmei Wang, Jianmin Wang, Jianning Wang, Jianping Wang, Jianqin Wang, Jianqing Wang, Jianqun Wang, Jianru Wang, Jianshe Wang, Jianshu Wang, Jiantao Wang, Jianwei Wang, Jianwu Wang, Jianxiang Wang, Jianxin Wang, Jianye Wang, Jianying Wang, Jianyong Wang, Jianyu Wang, Jianzhang Wang, Jianzhi Wang, Jiao Wang, Jiaojiao Wang, Jiapan Wang, Jiaping Wang, Jiaqi Wang, Jiaqian Wang, Jiatao Wang, Jiawei Wang, Jiawen Wang, Jiaxi Wang, Jiaxin Wang, Jiaxing Wang, Jiaxuan Wang, Jiayan Wang, Jiayang Wang, Jiayi Wang, Jiaying Wang, Jiayu Wang, Jiazheng Wang, Jiazhi Wang, Jie Jin Wang, Jie Wang, Jieda Wang, Jieh-Neng Wang, Jiemei Wang, Jieqi Wang, Jieyan Wang, Jieyu Wang, Jifei Wang, Jiheng Wang, Jihong Wang, Jiliang Wang, Jilin Wang, Jin Wang, Jin'e Wang, Jin-Bao Wang, Jin-Cheng Wang, Jin-Da Wang, Jin-E Wang, Jin-Juan Wang, Jin-Liang Wang, Jin-Xia Wang, Jin-Xing Wang, Jincheng Wang, Jindan Wang, Jinfei Wang, Jinfeng Wang, Jinfu Wang, Jing J Wang, Jing Wang, Jing-Hao Wang, Jing-Huan Wang, Jing-Jing Wang, Jing-Long Wang, Jing-Min Wang, Jing-Shi Wang, Jing-Wen Wang, Jing-Xian Wang, Jing-Yi Wang, Jing-Zhai Wang, Jingang Wang, Jingchun Wang, Jingfan Wang, Jingfeng Wang, Jingheng Wang, Jinghong Wang, Jinghua Wang, Jinghuan Wang, Jingjing Wang, Jingkang Wang, Jinglin Wang, Jingmin Wang, Jingnan Wang, Jingqi Wang, Jingru Wang, Jingtong Wang, Jingwei Wang, Jingwen Wang, Jingxiao Wang, Jingyang Wang, Jingyi Wang, Jingying Wang, Jingyu Wang, Jingyue Wang, Jingyun Wang, Jingzhou Wang, Jinhai Wang, Jinhao Wang, Jinhe Wang, Jinhua Wang, Jinhuan Wang, Jinhui Wang, Jinjie Wang, Jinjin Wang, Jinkang Wang, Jinling Wang, Jinlong Wang, Jinmeng Wang, Jinning Wang, Jinping Wang, Jinqiu Wang, Jinrong Wang, Jinru Wang, Jinsong Wang, Jintao Wang, Jinxia Wang, Jinxiang Wang, Jinyang Wang, Jinyu Wang, Jinyue Wang, Jinyun Wang, Jinzhu Wang, Jiou Wang, Jipeng Wang, Jiqing Wang, Jiqiu Wang, Jisheng Wang, Jiu Wang, Jiucun Wang, Jiun-Ling Wang, Jiwen Wang, Jixuan Wang, Jiyan Wang, Jiying Wang, Jiyong Wang, Jizheng Wang, John Wang, Jou-Kou Wang, Joy Wang, Ju Wang, Juan Wang, Jue Wang, Jueqiong Wang, Jufeng Wang, Julie Wang, Juling Wang, Jun Kit Wang, Jun Wang, Jun Yi Wang, Jun-Feng Wang, Jun-Jie Wang, Jun-Jun Wang, Jun-Ling Wang, Jun-Sheng Wang, Jun-Sing Wang, Jun-Zhuo Wang, Jundong Wang, Junfeng Wang, Jung-Pan Wang, Junhong Wang, Junhua Wang, Junhui Wang, Junjiang Wang, Junjie Wang, Junjun Wang, Junkai Wang, Junke Wang, Junli Wang, Junlin Wang, Junling Wang, Junmei Wang, Junmin Wang, Junpeng Wang, Junping Wang, Junqin Wang, Junqing Wang, Junrui Wang, Junsheng Wang, Junshi Wang, Junshuang Wang, Junwen Wang, Junxiao Wang, Junya Wang, Junying Wang, Junyu Wang, Justin Wang, Jutao Wang, Juxiang Wang, K Wang, Kai Wang, Kai-Kun Wang, Kai-Wen Wang, Kaicen Wang, Kaihao Wang, Kaihe Wang, Kaihong Wang, Kaijie Wang, Kaijuan Wang, Kailu Wang, Kaiming Wang, Kaining Wang, Kaiting Wang, Kaixi Wang, Kaixu Wang, Kaiyan Wang, Kaiyuan Wang, Kaiyue Wang, Kan Wang, Kangli Wang, Kangling Wang, Kangmei Wang, Kangning Wang, Ke Wang, Ke-Feng Wang, KeShan Wang, Kehan Wang, Kehao Wang, Kejia Wang, Kejian Wang, Kejun Wang, Keke Wang, Keming Wang, Kenan Wang, Keqing Wang, Kesheng Wang, Kexin Wang, Keyan Wang, Keyi Wang, Keyun Wang, Kongyan Wang, Kuan Hong Wang, Kui Wang, Kun Wang, Kunhua Wang, Kunpeng Wang, Kunzheng Wang, L F Wang, L M Wang, L Wang, L Z Wang, L-S Wang, Laidi Wang, Laijian Wang, Laiyuan Wang, Lan Wang, Lan-Wan Wang, Lan-lan Wang, Lanlan Wang, Larry Wang, Le Wang, Le-Xin Wang, Ledan Wang, Lee-Kai Wang, Lei P Wang, Lei Wang, Lei-Lei Wang, Leiming Wang, Leishen Wang, Leli Wang, Leran Wang, Lexin Wang, Leying Wang, Li Chun Wang, Li Dong Wang, Li Wang, Li-Dong Wang, Li-E Wang, Li-Juan Wang, Li-Li Wang, Li-Na Wang, Li-San Wang, Li-Ting Wang, Li-Xin Wang, Li-Yong Wang, LiLi Wang, Lian Wang, Lianchun Wang, Liang Wang, Liang-Yan Wang, Liangfu Wang, Lianghai Wang, Liangli Wang, Liangliang Wang, Liangxu Wang, Lianshui Wang, Lianyong Wang, Libo Wang, Lichan Wang, Lichao Wang, Liewei Wang, Lifang Wang, Lifei Wang, Lifen Wang, Lifeng Wang, Ligang Wang, Lihong Wang, Lihua Wang, Lihui Wang, Lijia Wang, Lijin Wang, Lijing Wang, Lijuan Wang, Lijun Wang, Liling Wang, Lily Wang, Limeng Wang, Limin Wang, Liming Wang, Lin Wang, Lin-Fa Wang, Lin-Yu Wang, Lina Wang, Linfang Wang, Ling Jie Wang, Ling Wang, Ling-Ling Wang, Lingbing Wang, Lingda Wang, Linghua Wang, Linghuan Wang, Lingli Wang, Lingling Wang, Lingyan Wang, Lingzhi Wang, Linhua Wang, Linhui Wang, Linjie Wang, Linli Wang, Linlin Wang, Linping Wang, Linshu Wang, Linshuang Wang, Lintao Wang, Linxuan Wang, Linying Wang, Linyuan Wang, Liping Wang, Liqing Wang, Liqun Wang, Lirong Wang, Litao Wang, Liting Wang, Liu Wang, Liusong Wang, Liuyang Wang, Liwei Wang, Lixia Wang, Lixian Wang, Lixiang Wang, Lixin Wang, Lixing Wang, Lixiu Wang, Liyan Wang, Liyi Wang, Liying Wang, Liyong Wang, Liyuan Wang, Liyun Wang, Long Wang, Longcai Wang, Longfei Wang, Longsheng Wang, Longxiang Wang, Lou-Pin Wang, Lu Wang, Lu-Lu Wang, Lueli Wang, Lufang Wang, Luhong Wang, Luhui Wang, Lujuan Wang, Lulu Wang, Luofu Wang, Luping Wang, Luting Wang, Luwen Wang, Luxiang Wang, Luya Wang, Luyao Wang, Luyun Wang, Lynn Yuning Wang, M H Wang, M Wang, M Y Wang, M-J Wang, Maiqiu Wang, Man Wang, Mangju Wang, Manli Wang, Mao-Xin Wang, Maochun Wang, Maojie Wang, Maoju Wang, Mark Wang, Mei Wang, Mei-Gui Wang, Mei-Xia Wang, Meiding Wang, Meihui Wang, Meijun Wang, Meiling Wang, Meixia Wang, Melissa T Wang, Meng C Wang, Meng Wang, Meng Yu Wang, Meng-Dan Wang, Meng-Lan Wang, Meng-Meng Wang, Meng-Ru Wang, Meng-Wei Wang, Meng-Ying Wang, Meng-hong Wang, Mengge Wang, Menghan Wang, Menghui Wang, Mengjiao Wang, Mengjing Wang, Mengjun Wang, Menglong Wang, Menglu Wang, Mengmeng Wang, Mengqi Wang, Mengru Wang, Mengshi Wang, Mengwen Wang, Mengxiao Wang, Mengya Wang, Mengyao Wang, Mengying Wang, Mengyuan Wang, Mengyue Wang, Mengyun Wang, Mengze Wang, Mengzhao Wang, Mengzhi Wang, Mian Wang, Miao Wang, Mimi Wang, Min Wang, Min-sheng Wang, Ming Wang, Ming-Chih Wang, Ming-Hsi Wang, Ming-Jie Wang, Ming-Wei Wang, Ming-Yang Wang, Ming-Yuan Wang, Mingchao Wang, Mingda Wang, Minghua Wang, Minghuan Wang, Minghui Wang, Mingji Wang, Mingjin Wang, Minglei Wang, Mingliang Wang, Mingmei Wang, Mingming Wang, Mingqiang Wang, Mingrui Wang, Mingsong Wang, Mingxi Wang, Mingxia Wang, Mingxun Wang, Mingya Wang, Mingyang Wang, Mingyi Wang, Mingyu Wang, Mingzhi Wang, Mingzhu Wang, Minjie Wang, Minjun Wang, Minmin Wang, Minxian Wang, Minxiu Wang, Minzhou Wang, Miranda C Wang, Mo Wang, Mofei Wang, Monica Wang, Mu Wang, Mutian Wang, Muxiao Wang, Muxuan Wang, N Wang, Na Wang, Nan Wang, Nana Wang, Nanbu Wang, Nannan Wang, Nanping Wang, Neng Wang, Ni Wang, Niansong Wang, Ning Wang, Ningjian Wang, Ningli Wang, Ningyuan Wang, Nuan Wang, Oliver Wang, Ouchen Wang, P Jeremy Wang, P L Wang, P N Wang, P Wang, Pai Wang, Pan Wang, Pan-Pan Wang, Panfeng Wang, Panliang Wang, Pei Chang Wang, Pei Wang, Pei-Hua Wang, Pei-Jian Wang, Pei-Juan Wang, Pei-Wen Wang, Pei-Yu Wang, Peichang Wang, Peigeng Wang, Peihe Wang, Peijia Wang, Peijuan Wang, Peijun Wang, Peilin Wang, Peipei Wang, Peirong Wang, Peiwen Wang, Peixi Wang, Peiyao Wang, Peiyin Wang, Peng Wang, Peng-Cheng Wang, Pengbo Wang, Pengchao Wang, Pengfei Wang, Pengjie Wang, Pengju Wang, Penglai Wang, Penglong Wang, Pengpu Wang, Pengtao Wang, Pengxiang Wang, Pengyu Wang, Pin Wang, Ping Wang, Pingchuan Wang, Pingfeng Wang, Pingping Wang, Pintian Wang, Po-Jen Wang, Pu Wang, Q Wang, Q Z Wang, Qi Wang, Qi-Bing Wang, Qi-En Wang, Qi-Jia Wang, Qi-Qi Wang, Qian Wang, Qian-Liang Wang, Qian-Wen Wang, Qian-Zhu Wang, Qian-fei Wang, Qianbao Wang, Qiang Wang, Qiang-Sheng Wang, Qiangcheng Wang, Qianghu Wang, Qiangqiang Wang, Qianjin Wang, Qianliang Wang, Qianqian Wang, Qianrong Wang, Qianru Wang, Qianwen Wang, Qianxu Wang, Qiao Wang, Qiao-Ping Wang, Qiaohong Wang, Qiaoqi Wang, Qiaoqiao Wang, Qifan Wang, Qifei Wang, Qifeng Wang, Qigui Wang, Qihao Wang, Qihua Wang, Qijia Wang, Qiming Wang, Qin Wang, Qing Jun Wang, Qing K Wang, Qing Kenneth Wang, Qing Mei Wang, Qing Wang, Qing-Bin Wang, Qing-Dong Wang, Qing-Jin Wang, Qing-Liang Wang, Qing-Mei Wang, Qing-Yan Wang, Qing-Yuan Wang, Qing-Yun Wang, QingDong Wang, Qingchun Wang, Qingfa Wang, Qingfeng Wang, Qinghang Wang, Qingliang Wang, Qinglin Wang, Qinglu Wang, Qingming Wang, Qingping Wang, Qingqing Wang, Qingshi Wang, Qingshui Wang, Qingsong Wang, Qingtong Wang, Qingyong Wang, Qingyu Wang, Qingyuan Wang, Qingyun Wang, Qingzhong Wang, Qinqin Wang, Qinrong Wang, Qintao Wang, Qinwen Wang, Qinyun Wang, Qiong Wang, Qiqi Wang, Qirui Wang, Qishan Wang, Qiu-Ling Wang, Qiu-Xia Wang, Qiuhong Wang, Qiuli Wang, Qiuling Wang, Qiuning Wang, Qiuping Wang, Qiushi Wang, Qiuting Wang, Qiuyan Wang, Qiuyu Wang, Qiwei Wang, Qixue Wang, Qiyu Wang, Qiyuan Wang, Quan Wang, Quan-Ming Wang, Quanli Wang, Quanren Wang, Quanxi Wang, Qun Wang, Qunxian Wang, Qunzhi Wang, R Wang, Ran Wang, Ranjing Wang, Ranran Wang, Re-Hua Wang, Ren Wang, Rencheng Wang, Renjun Wang, Renqian Wang, Renwei Wang, Renxi Wang, Renxiao Wang, Renyuan Wang, Rihua Wang, Rikang Wang, Rixiang Wang, Robert Yl Wang, Rong Wang, Rong-Chun Wang, Rong-Rong Wang, Rong-Tsorng Wang, RongRong Wang, Rongjia Wang, Rongping Wang, Rongyun Wang, Ru Wang, RuNan Wang, Ruey-Yun Wang, Rufang Wang, Ruhan Wang, Rui Wang, Rui-Hong Wang, Rui-Min Wang, Rui-Ping Wang, Rui-Rui Wang, Ruibin Wang, Ruibing Wang, Ruibo Wang, Ruicheng Wang, Ruifang Wang, Ruijing Wang, Ruimeng Wang, Ruimin Wang, Ruiming Wang, Ruinan Wang, Ruining Wang, Ruiquan Wang, Ruiwen Wang, Ruixian Wang, Ruixin Wang, Ruixuan Wang, Ruixue Wang, Ruiying Wang, Ruizhe Wang, Ruizhi Wang, Rujie Wang, Ruling Wang, Ruming Wang, Runci Wang, Runuo Wang, Runze Wang, Runzhi Wang, Ruo-Nan Wang, Ruo-Ran Wang, Ruonan Wang, Ruosu Wang, Ruoxi Wang, Rurong Wang, Ruting Wang, Ruxin Wang, Ruxuan Wang, Ruyue Wang, S L Wang, S S Wang, S Wang, S X Wang, Sa A Wang, Sa Wang, Saifei Wang, Saili Wang, Sainan Wang, Saisai Wang, Sangui Wang, Sanwang Wang, Sasa Wang, Sen Wang, Seok Mui Wang, Seungwon Wang, Sha Wang, Shan Wang, Shan-Shan Wang, Shang Wang, Shangyu Wang, Shanshan Wang, Shao-Kang Wang, Shaochun Wang, Shaohsu Wang, Shaokun Wang, Shaoli Wang, Shaolian Wang, Shaoshen Wang, Shaowei Wang, Shaoyi Wang, Shaoying Wang, Shaoyu Wang, Shaozheng Wang, Shasha Wang, Shau-Chun Wang, Shawn Wang, Shen Wang, Shen-Nien Wang, Shenao Wang, Sheng Wang, Sheng-Min Wang, Sheng-Nan Wang, Sheng-Ping Wang, Sheng-Quan Wang, Sheng-Yang Wang, Shengdong Wang, Shengjie Wang, Shengli Wang, Shengqi Wang, Shengya Wang, Shengyao Wang, Shengyu Wang, Shengyuan Wang, Shenqi Wang, Sheri Wang, Shi Wang, Shi-Cheng Wang, Shi-Han Wang, Shi-Qi Wang, Shi-Xin Wang, Shi-Yao Wang, Shibin Wang, Shichao Wang, Shicung Wang, Shidong Wang, Shifa Wang, Shifeng Wang, Shih-Wei Wang, Shihan Wang, Shihao Wang, Shihua Wang, Shijie Wang, Shijin Wang, Shijun Wang, Shikang Wang, Shimiao Wang, Shiqi Wang, Shiqiang Wang, Shitao Wang, Shitian Wang, Shiwen Wang, Shixin Wang, Shixuan Wang, Shiyang Wang, Shiyao Wang, Shiyin Wang, Shiyu Wang, Shiyuan Wang, Shiyue Wang, Shizhi Wang, Shouli Wang, Shouling Wang, Shouzhi Wang, Shu Wang, Shu-Huei Wang, Shu-Jin Wang, Shu-Ling Wang, Shu-Na Wang, Shu-Song Wang, Shu-Xia Wang, Shu-qiang Wang, Shuai Wang, Shuaiqin Wang, Shuang Wang, Shuang-Shuang Wang, Shuang-Xi Wang, Shuangyuan Wang, Shubao Wang, Shudan Wang, Shuge Wang, Shuguang Wang, Shuhe Wang, Shuiliang Wang, Shuiyun Wang, Shujin Wang, Shukang Wang, Shukui Wang, Shun Wang, Shuning Wang, Shunjun Wang, Shunran Wang, Shuo Wang, Shuping Wang, Shuqi Wang, Shuqing Wang, Shuren Wang, Shusen Wang, Shusheng Wang, Shushu Wang, Shuu-Jiun Wang, Shuwei Wang, Shuxia Wang, Shuxin Wang, Shuya Wang, Shuye Wang, Shuyue Wang, Shuzhe Wang, Shuzhen Wang, Shuzhong Wang, Shyi-Gang P Wang, Si Wang, Sibo Wang, Sidan Wang, Sihua Wang, Sijia Wang, Silas L Wang, Silu Wang, Simeng Wang, Siqi Wang, Siqing Wang, Siwei Wang, Siyang Wang, Siyi Wang, Siying Wang, Siyu Wang, Siyuan Wang, Siyue Wang, Song Wang, Songjiao Wang, Songlin Wang, Songping Wang, Songsong Wang, Songtao Wang, Sophie H Wang, Stephani Wang, Su'e Wang, Su-Guo Wang, Su-Hua Wang, Sufang Wang, Sugai Wang, Sui Wang, Suiyan Wang, Sujie Wang, Sujuan Wang, Suli Wang, Sun Wang, Supeng Perry Wang, Suxia Wang, Suyun Wang, Suzhen Wang, T Q Wang, T Wang, T Y Wang, Taian Wang, Taicheng Wang, Taishu Wang, Tammy C Wang, Tao Wang, Taoxia Wang, Teng Wang, Tengfei Wang, Theodore Wang, Thomas T Y Wang, Tian Wang, Tian-Li Wang, Tian-Lu Wang, Tian-Tian Wang, Tian-Yi Wang, Tiancheng Wang, Tiange Wang, Tianhao Wang, Tianhu Wang, Tianhui Wang, Tianjing Wang, Tianjun Wang, Tianlin Wang, Tiannan Wang, Tianpeng Wang, Tianqi Wang, Tianqin Wang, Tianqing Wang, Tiansheng Wang, Tiansong Wang, Tiantian Wang, Tianyi Wang, Tianying Wang, Tianyuan Wang, Tielin Wang, Tienju Wang, Tieqiao Wang, Timothy C Wang, Ting Chen Wang, Ting Wang, Ting-Chen Wang, Ting-Hua Wang, Ting-Ting Wang, Tingting Wang, Tingye Wang, Tingyu Wang, Tom J Wang, Tong Wang, Tong-Hong Wang, Tongsong Wang, Tongtong Wang, Tongxia Wang, Tongxin Wang, Tongyao Wang, Tony Wang, Tzung-Dau Wang, Victoria Wang, Vivian Wang, W Wang, Wanbing Wang, Wanchun Wang, Wang Wang, Wangxia Wang, Wanliang Wang, Wanxia Wang, Wanyao Wang, Wanyi Wang, Wanyu Wang, Wayseen Wang, Wei Wang, Wei-En Wang, Wei-Feng Wang, Wei-Lien Wang, Wei-Qi Wang, Wei-Ting Wang, Wei-Wei Wang, Weicheng Wang, Weiding Wang, Weidong Wang, Weifan Wang, Weiguang Wang, Weihao Wang, Weihong Wang, Weihua Wang, Weijian Wang, Weijie Wang, Weijun Wang, Weilin Wang, Weiling Wang, Weilong Wang, Weimin Wang, Weina Wang, Weining Wang, Weipeng Wang, Weiqin Wang, Weiqing Wang, Weirong Wang, Weiwei Wang, Weiwen Wang, Weixiao Wang, Weixue Wang, Weiyan Wang, Weiyu Wang, Weiyuan Wang, Weizhen Wang, Weizhi Wang, Weizhong Wang, Wen Wang, Wen-Chang Wang, Wen-Der Wang, Wen-Fei Wang, Wen-Jie Wang, Wen-Jun Wang, Wen-Qing Wang, Wen-Xuan Wang, Wen-Yan Wang, Wen-Ying Wang, Wen-Yong Wang, Wen-mei Wang, Wenbin Wang, Wenbo Wang, Wence Wang, Wenchao Wang, Wencheng Wang, Wendong Wang, Wenfei Wang, Wengong Wang, Wenhan Wang, Wenhao Wang, Wenhe Wang, Wenhui Wang, Wenjie Wang, Wenjing Wang, Wenju Wang, Wenjuan Wang, Wenjun Wang, Wenkai Wang, Wenkang Wang, Wenke Wang, Wenming Wang, Wenqi Wang, Wenqiang Wang, Wenqing Wang, Wenran Wang, Wenrui Wang, Wentao Wang, Wentian Wang, Wenting Wang, Wenwen Wang, Wenxia Wang, Wenxian Wang, Wenxiang Wang, Wenxiu Wang, Wenxuan Wang, Wenya Wang, Wenyan Wang, Wenyi Wang, Wenying Wang, Wenyu Wang, Wenyuan Wang, Wenzhou Wang, William Wang, Won-Jing Wang, Wu-Wei Wang, Wuji Wang, Wuqing Wang, Wusan Wang, X E Wang, X F Wang, X O Wang, X S Wang, X Wang, X-T Wang, Xi Wang, Xi-Hong Wang, Xi-Rui Wang, Xia Wang, Xian Wang, Xian-e Wang, Xianding Wang, Xianfeng Wang, Xiang Wang, Xiang-Dong Wang, Xiangcheng Wang, Xiangding Wang, Xiangdong Wang, Xiangguo Wang, Xianghua Wang, Xiangkun Wang, Xiangrong Wang, Xiangru Wang, Xiangwei Wang, Xiangyu Wang, Xianna Wang, Xianqiang Wang, Xianrong Wang, Xianshi Wang, Xianshu Wang, Xiansong Wang, Xiantao Wang, Xianwei Wang, Xianxing Wang, Xianze Wang, Xianzhe Wang, Xianzong Wang, Xiao Ling Wang, Xiao Qun Wang, Xiao Wang, Xiao-Ai Wang, Xiao-Fei Wang, Xiao-Hui Wang, Xiao-Jie Wang, Xiao-Juan Wang, Xiao-Lan Wang, Xiao-Li Wang, Xiao-Lin Wang, Xiao-Ming Wang, Xiao-Pei Wang, Xiao-Qian Wang, Xiao-Qun Wang, Xiao-Tong Wang, Xiao-Xia Wang, Xiao-Yi Wang, Xiao-Yun Wang, Xiao-jian WANG, Xiao-liang Wang, Xiaobin Wang, Xiaobo Wang, Xiaochen Wang, Xiaochuan Wang, Xiaochun Wang, Xiaodan Wang, Xiaoding Wang, Xiaodong Wang, Xiaofang Wang, Xiaofei Wang, Xiaofen Wang, Xiaofeng Wang, Xiaogang Wang, Xiaohong Wang, Xiaohu Wang, Xiaohua Wang, Xiaohui Wang, Xiaojia Wang, Xiaojian Wang, Xiaojiao Wang, Xiaojie Wang, Xiaojing Wang, Xiaojuan Wang, Xiaojun Wang, Xiaokun Wang, Xiaole Wang, Xiaoli Wang, Xiaoliang Wang, Xiaolin Wang, Xiaoling Wang, Xiaolong Wang, Xiaolu Wang, Xiaolun Wang, Xiaoman Wang, Xiaomei Wang, Xiaomeng Wang, Xiaomin Wang, Xiaoming Wang, Xiaona Wang, Xiaonan Wang, Xiaoning Wang, Xiaoqi Wang, Xiaoqian Wang, Xiaoqin Wang, Xiaoqing Wang, Xiaoqiu Wang, Xiaoqun Wang, Xiaorong Wang, Xiaorui Wang, Xiaoshan Wang, Xiaosong Wang, Xiaotang Wang, Xiaoting Wang, Xiaotong Wang, Xiaowei Wang, Xiaowen Wang, Xiaowu Wang, Xiaoxia Wang, Xiaoxiao Wang, Xiaoxin Wang, Xiaoxin X Wang, Xiaoxuan Wang, Xiaoya Wang, Xiaoyan Wang, Xiaoyang Wang, Xiaoye Wang, Xiaoying Wang, Xiaoyu Wang, Xiaozhen Wang, Xiaozhi Wang, Xiaozhong Wang, Xiaozhu Wang, Xichun Wang, Xidi Wang, Xietong Wang, Xifeng Wang, Xifu Wang, Xijun Wang, Xike Wang, Xin Wang, Xin Wei Wang, Xin-Hua Wang, Xin-Liang Wang, Xin-Ming Wang, Xin-Peng Wang, Xin-Qun Wang, Xin-Shang Wang, Xin-Xin Wang, Xin-Yang Wang, Xin-Yue Wang, Xinbo Wang, Xinchang Wang, Xinchao Wang, Xinchen Wang, Xincheng Wang, Xinchun Wang, Xindi Wang, Xindong Wang, Xing Wang, Xing-Huan Wang, Xing-Jin Wang, Xing-Jun Wang, Xing-Lei Wang, Xing-Ping Wang, Xing-Quan Wang, Xingbang Wang, Xingchen Wang, Xingde Wang, Xingguo Wang, Xinghao Wang, Xinghui Wang, Xingjie Wang, Xingjin Wang, Xinglei Wang, Xinglong Wang, Xingqin Wang, Xinguo Wang, Xingxin Wang, Xingxing Wang, Xingye Wang, Xingyu Wang, Xingyue Wang, Xingyun Wang, Xinhui Wang, Xinjing Wang, Xinjun Wang, Xinke Wang, Xinkun Wang, Xinli Wang, Xinlin Wang, Xinlong Wang, Xinmei Wang, Xinqi Wang, Xinquan Wang, Xinran Wang, Xinrong Wang, Xinru Wang, Xinrui Wang, Xinshuai Wang, Xintong Wang, Xinwen Wang, Xinxin Wang, Xinyan Wang, Xinyang Wang, Xinye Wang, Xinyi Wang, Xinying Wang, Xinyu Wang, Xinyue Wang, Xinzhou Wang, Xiong Wang, Xiongjun Wang, Xiru Wang, Xitian Wang, Xiu-Lian Wang, Xiu-Ping Wang, Xiufen Wang, Xiujuan Wang, Xiujun Wang, Xiurong Wang, Xiuwen Wang, Xiuyu Wang, Xiuyuan Hugh Wang, Xixi Wang, Xixiang Wang, Xiyan Wang, Xiyue Wang, Xizhi Wang, Xu Wang, Xu-Hong Wang, Xuan Wang, Xuan-Ren Wang, Xuan-Ying Wang, Xuanwen Wang, Xuanyi Wang, Xubo Wang, Xudong Wang, Xue Wang, Xue-Feng Wang, Xue-Hua Wang, Xue-Lei Wang, Xue-Lian Wang, Xue-Rui Wang, Xue-Yao Wang, Xue-Ying Wang, Xuebin Wang, Xueding Wang, Xuedong Wang, Xuefei Wang, Xuefeng Wang, Xueguo Wang, Xuehao Wang, Xuejie Wang, Xuejing Wang, Xueju Wang, Xuejun Wang, Xuekai Wang, Xuelai Wang, Xuelian Wang, Xuelin Wang, Xuemei Wang, Xuemin Wang, Xueping Wang, Xueqian Wang, Xueqin Wang, Xuesong Wang, Xueting Wang, Xuewei Wang, Xuewen Wang, Xuexiang Wang, Xueyan Wang, 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
Miao Yu, Libin Yao, Sanjeev Shahi +12 more · 2026 · Radiology · added 2026-04-24
Background Although substantial evidence has demonstrated the impact of obesity on brain structure and cognition, the heterogeneity of adiposity-particularly in terms of fat distribution patterns-and Show more
Background Although substantial evidence has demonstrated the impact of obesity on brain structure and cognition, the heterogeneity of adiposity-particularly in terms of fat distribution patterns-and its differential neurologic effects remain poorly understood. Purpose To identify body fat distribution patterns with MRI and latent profile analysis (LPA) and their associations with brain structure measurements, cognition, and neurologic diseases. Materials and Methods This secondary analysis used prospective data from the UK Biobank, including health records and MRI scans of the brain, heart, and abdomen. Fat distribution profiles were classified using LPA based on eight body mass index (BMI)-adjusted MRI-derived fat quantification metrics. Differences in brain volume, white matter properties, cognition, and the risk of neurologic disorders were analyzed across profiles and relative to a benchmark lean profile; analyses were stratified by sex. Group differences were examined using analysis of covariance (ANCOVA) or rank-based ANCOVA. Results Among 25 997 participants (mean age, 55 years ± 7.4 [SD]; 13 536 female participants), LPA identified six profiles of body fat distribution in both sexes. Four high-adiposity patterns were identified, including the pancreatic-predominant profile (profile 1), with elevated proton density fat fraction (mean BMI-adjusted Show less
no PDF DOI: 10.1148/radiol.252610
LPA
Guogang Xin, Jiaqian Xu, Ling Jiang +5 more · 2026 · BMC psychology · BioMed Central · added 2026-04-24
Improved internet access has exposed rural adolescents in China to a greater risk of internet addiction. However, existing studies seldom examine the relationship between dynamic changes in internet a Show more
Improved internet access has exposed rural adolescents in China to a greater risk of internet addiction. However, existing studies seldom examine the relationship between dynamic changes in internet addiction and psychosocial maladjustment. This study aims to explore the transition patterns of internet addiction and its associations with emotional and interpersonal problems over time. A one-year longitudinal survey was conducted among 782 middle school students in rural China. Latent Profile Analysis (LPA) was conducted to identify internet addiction profiles at two time points. Latent Profile Transition Analysis (LPTA) was then used to examine the transition patterns between profiles over time. Subsequently, statistical analyses were conducted to explore how these transitions were associated with emotional and interpersonal problems. Three profiles of internet addiction were identified: minimal-internet addiction, low-internet addiction, and high-internet addiction. Based on LPTA, most adolescents with higher internet addiction at T1 shifted to lower-severity profiles over time (high → minimal: 35.3%; low → minimal: 39.8%; high → low: 33.3%), while some with initially lower levels transitioned to more severe profiles (minimal → high: 6.9%; low → high: 12.2%; minimal → low: 25.7%). Transition into higher addiction profiles predicted increased depression, anxiety, and poorer relationships with parents, peers, and teachers. Conversely, reductions in addiction were linked to improved depressive symptoms. Changes in internet addiction have an impact on adolescent psychosocial maladjustment. Early detection and flexible interventions are essential in rural settings. Show less
📄 PDF DOI: 10.1186/s40359-026-03992-x
LPA
Rahayu Zulkapli, Suhaila Abd Muid, Seok Mui Wang +4 more · 2026 · Scientific reports · Nature · added 2026-04-24
Coronary artery disease (CAD) has been associated with elevated Lp(a) levels, yet the mechanism driving the pro-atherogenic and inflammatory effects remains unclear. Proprotein convertase subtilisin/k Show more
Coronary artery disease (CAD) has been associated with elevated Lp(a) levels, yet the mechanism driving the pro-atherogenic and inflammatory effects remains unclear. Proprotein convertase subtilisin/kexin type 9 (PCSK9), a key regulator of lipid metabolism with emerging roles in vascular inflammation. This study explored the relationship between Lp (a) and PCSK9 in an Asian cohort with angiogram-proven premature CAD (AP-pCAD), with and without familial hypercholesterolemia (FH). Patients were recruited from Cardiology and Specialist Lipid Clinics; grouped into pCAD with FH ( Show less
📄 PDF DOI: 10.1038/s41598-026-36716-7
LPA
Zheng Xu, Ying Lu, Shuying Si +3 more · 2026 · Phytotherapy research : PTR · Wiley · added 2026-04-24
Lupus nephritis (LN) is a severe autoimmune disease often complicated by steroid resistance (SR), leading to treatment failure and poor prognosis like atherosclerosis (AS). Our study found that Panax Show more
Lupus nephritis (LN) is a severe autoimmune disease often complicated by steroid resistance (SR), leading to treatment failure and poor prognosis like atherosclerosis (AS). Our study found that Panax notoginseng saponins (PNS) improve lipid metabolism and prevent AS in steroid-resistant LN by up-regulating PPARγ, though mechanisms are unclear. Recent research highlights the roles of macrophages, with M1 Mø promoting inflammation and M2 Mø providing protection, as PPARγ influences Mø's polarization, linking it to inflammation and M2 polarization, necessitating further investigation. Therefore, we conduct this study to investigate the regulatory effect of PNS on the "Mø M2 polarization-PPARγ" positive regulation, endeavoring to elucidate its therapeutic potential of delaying AS and reversing SR in LN. PPARγ expression in polarized Mø was measured via PCR and WB, while M1/M2 biomarkers and cytokines, influenced by PPARγ modulation, were assessed using flow cytometry and ELISA. In mouse Mø treated with PNS, IL-4, or both, PPARγ and cytokines were measured. ICR and MRL/lpr mice were used to establish an in vivo SR model to confirm PNS's role in M2 polarization of Mø and AS protection by analyzing blood lipid levels, iNOS, Lp(a), and apoptosis rates through WB, immunohistochemistry, HE-staining, and TUNEL. PNS's efficacy in renal protection and SR reversal was evaluated through Scr, BUN, urine protein, renal pathology, and P-gp; MDR1 expression was assessed via biochemical detection, HE-staining, flow cytometry, and WB. This study confirmed that PNS upregulates PPARγ and promotes M2 polarization, improving abdominal aorta pathology and delaying AS. It also enhances renal function and reverses SR by reducing P-gp and MDR1. This study shows that PNS promotes Mø polarization to M2 and enhances PPARγ expression, effectively preventing AS, improving renal function, and reversing SR in LN, offering insights for LN treatment and expanding PNS's therapeutic benefits for future research. Show less
no PDF DOI: 10.1002/ptr.70192
LPA
Zenglei Zhang, Lin Zhao, Zeyu Wang +4 more · 2026 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
Conflicting data have explored the association between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease (ASCVD) among individuals with different glucose metabolism statuses. We aimed Show more
Conflicting data have explored the association between lipoprotein(a) [Lp(a)] and atherosclerotic cardiovascular disease (ASCVD) among individuals with different glucose metabolism statuses. We aimed to prospectively evaluate this association and to assess whether it is modified by C-reactive protein (CRP). This population-based cohort study was derived from the UK Biobank database. Lp(a) and CRP were measured between 2006 and 2010. Cox proportional hazards models and restricted cubic spline curves were employed to assess the relationship between Lp(a) levels and time to ASCVD events. A total of 307 269 participants without prevalent ASCVD were included, comprising 253 746 individuals with normal glucose regulation (NGR), 38 020 with prediabetes, and 15 503 with diabetes. The mean age was 57 years (Q1-Q3: 50-63), and 55.3% were female. Over a median follow-up of 13.2 years, 29 521 ASCVD events occurred. Higher Lp(a) levels were associated with an increased risk of ASCVD across all glucose metabolism statuses. In fully adjusted models, the hazard ratio (95% confidence interval) for ASCVD comparing participants in the top 10% of Lp(a) with those in the bottom 33% was 1.28 (1.22-1.34) among those with NGR, 1.23 (1.12-1.35) among those with prediabetes, and 1.16 (1.02-1.31) among those with diabetes. No significant interactions were observed after stratification by CRP (<2/≥2 mg/L) across glucose metabolism groups (P for interaction >0.05). Elevated Lp(a) levels were associated with a higher risk of ASCVD across different glucose metabolism statuses, particularly among individuals with NGR and prediabetes, independent of baseline CRP levels. Show less
no PDF DOI: 10.1111/dom.70491
LPA
Jiejia Li, Wenting Tang, Liyun Wang +9 more · 2026 · iScience · Elsevier · added 2026-04-24
Oxypeucedanin (OPD) showed anti-allodynia against neuropathic pain (NeuP) in our previous study. In the present study, we aimed to further investigate whether lysophosphatidic acid receptor (LPAR) sig Show more
Oxypeucedanin (OPD) showed anti-allodynia against neuropathic pain (NeuP) in our previous study. In the present study, we aimed to further investigate whether lysophosphatidic acid receptor (LPAR) signaling mediated OPD-induced antinociception against NeuP models. Single OPD treatment dose-dependently reduced pain hypersensitivity, and repeated OPD treatment maintained sustained antinociception without the development of tolerance. Importantly, OPD exhibited a significant curative effect on different stages of NeuP. ROCK and RhoA agonists prevented the therapeutic effect of OPD, while the inhibitors of LPAR, ROCK, and RhoA mimicked OPD-induced antinociception. Notably, OPD treatment attenuated the increases of LPA content and protein expression of LPAR1, RhoA, and Show less
📄 PDF DOI: 10.1016/j.isci.2025.114502
LPA
Muge Qile, Zhaofei Luo, Chao Wu +7 more · 2026 · Anesthesia and analgesia · added 2026-04-24
Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators rel Show more
Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators released during I/R contribute to myocardial damage, their mechanisms require further elucidation. We investigated whether lysophosphatidic acid (LPA), a bioactive phospholipid, mediates myocardial I/R injury by interacting with cardiac transient receptor potential vanilloid 1 (TRPV1). A TRPV1K710N knock-in mouse model was generated by CRISPR/Cas9, introducing a point mutation at K710, the known LPA-binding site on TRPV1. Langendorff perfused isolated hearts from TRPV1K710N and wild-type (WT) mice underwent global I/R injury with or without exogenous LPA (10 μM). Myocardial infarct size, coronary effluent LDH levels, and mitochondrial ultrastructure/function were assessed. Additionally, H9c2 cardiomyocytes were transfected with a pCMV6-entry plasmid carrying TRPV1-K710N or TRPV1-WT for mitochondrial calcium influx and cell viability assays. The V1-Cal peptide (1μM), targeting the K710 region, was applied ex vivo and in vitro to block LPA-TRPV1 interaction. TRPV1K710N hearts exhibited resistance to global I/R injury versus WT hearts, with reduced infarct size (28.3 ± 2.4% vs 39.9 ±2.3%, respectively, P= 0006), lower LDH levels, and attenuated mitochondrial damage. Exogenous LPA exacerbated I/R injury in WT hearts, increasing infarct size (63.7 ± 1.2% vs vehicle: 38.4 ± 2.4%; P <.0001), LDH release, and mitochondrial damage. TRPV1K710N hearts were resistant to LPA-induced injury, with no significant increase in infarct size after LPA treatment. Exogenous LPA induced pronounced swelling in mitochondria isolated from WT hearts, while mitochondria from TRPV1K710N hearts showed resistance to LPA challenge. In H9c2 cells, LPA significantly decreased viability in rTRPV1-WT cells and elevated mitochondrial calcium influx relative to rTRPV1-K710N cells. V1-Cal peptide attenuated LPA-mediated myocardial injury in WT hearts and reduced mitochondrial calcium overload in H9c2 cells. Blockade of the TRPV1 K710 site by K710N mutation or V1-Cal peptide mitigates LPA-mediated myocardial injury and mitochondrial damage/dysfunction in isolated mouse hearts. Targeting the cardiac LPA-TRPV1 interaction represents a promising therapeutic strategy against perioperative myocardial injury. Show less
no PDF DOI: 10.1213/ANE.0000000000007907
LPA
Hang Yi, Qian Hong, Yan Wang +4 more · 2026 · Surgical endoscopy · Springer · added 2026-04-24
Postoperative symptoms in lung cancer patients are complex and dynamic, yet recovery is highly heterogeneous. Traditional analyses often fail to capture individual recovery trajectories, limiting the Show more
Postoperative symptoms in lung cancer patients are complex and dynamic, yet recovery is highly heterogeneous. Traditional analyses often fail to capture individual recovery trajectories, limiting the ability to provide personalized care. This study aimed to identify distinct postoperative symptom trajectories and their clinical predictors using a person-centered approach. We conducted a prospective longitudinal study with 394 patients undergoing uniportal video-assisted thoracoscopic surgery (uniportal VATS) for early-stage non-small cell lung cancer. Patient-reported symptoms were collected at 1, 7, 14, and 30 days postoperatively. Latent Profile Analysis (LPA) was used to identify distinct symptom profiles, and Latent Transition Analysis (LTA) modeled the transitions between these profiles over time. Multinomial logistic regression was used to identify predictors of these transitions. LPA identified two distinct recovery profiles: a "Rapid Recovery" group (C1) and a "High-Symptom, Slow Recovery" group (C2). The first postoperative week was a critical window, with 73.0% of patients in the High-Symptom, Slow Recovery group transitioning to the Rapid Recovery group. This transition rate slowed significantly in subsequent weeks. A higher ASA classification, use of a thicker chest tube, and extensive lymph node dissection predicted a slower recovery. Conversely, better pulmonary function (FEV1%, MVV%) facilitated a faster transition, while postoperative complications were associated with a negative trajectory shift. Postoperative recovery in lung cancer patients follows predictable, heterogeneous trajectories. This person-centered approach enables the early identification of high-risk patients based on preoperative and surgical factors. Understanding these distinct pathways allows for a shift from a one-size-fits-all model to staged, personalized interventions designed to optimize symptom management and enhance patient recovery. Show less
📄 PDF DOI: 10.1007/s00464-025-12559-7
LPA
Jingran Yang, Fang Ma, Yu Wang +7 more · 2026 · BMC public health · BioMed Central · added 2026-04-24
Parents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, e Show more
Parents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, existing research predominantly measures general family resilience, neglecting heterogeneous resilience patterns and subgroup profiles. Our study uses person-centered Latent Profile Analysis (LPA) to identify latent family resilience classes in Chinese culture to provide tailored support. This study adopted a cross-sectional survey design. From October 2024 to July 2025, convenience sampling was used to recruit 426 eligible parents of children with CHD from two tertiary hospitals in Yunnan Province, China. Data were collected using the General Information Questionnaire, Family Hardiness Index (FHI), Simplified Coping Style Questionnaire (SCSQ), and Social Support Rating Scale (SSRS). LPA was applied to classify the family resilience levels of these parents. Subsequently, univariate and multivariate ordinal logistic regression analyses were conducted to explore the factors associated with different latent classes of family resilience. A total of 400 valid questionnaires were collected, with an effective response rate of 93.9%. The mean total score for family resilience in parents of children with CHD was 58.13 ± 5.79, suggesting a moderate overall level of family resilience in this group. The family resilience of parents of children with CHD was classified into three latent profiles: “High family resilience responsibility-anchored type” ( Parents of children with CHD demonstrate heterogeneity in family resilience. Healthcare professionals should pay attention to the family resilience differences among parents of children with CHD and implement targeted intervention measures based on the characteristics of different subgroups, thereby enhancing parents’ family resilience and further promoting family well-being. The online version contains supplementary material available at 10.1186/s12889-025-26143-0. Show less
📄 PDF DOI: 10.1186/s12889-025-26143-0
LPA
Yu Lu, Lin Wang, Shijie Liu +8 more · 2026 · BMC public health · BioMed Central · added 2026-04-24
To investigate the dose-response relationship between e-health literacy and light physical activity (LPA) in older adults is to provide evidence for targeted interventions that enhance e-health litera Show more
To investigate the dose-response relationship between e-health literacy and light physical activity (LPA) in older adults is to provide evidence for targeted interventions that enhance e-health literacy and promote LPA, thereby advancing healthy aging. This study used a convenience sampling method to select two residential neighborhoods. Subsequently, a random cluster sampling approach was employed, resulting in a total final sample of 105 community-dwelling older adults (aged 60 and above) from these neighborhoods. A three-axis accelerometer (ActiGraph wGT3X-BT) recorded the older adults' LPA, and the Electronic Health Literacy Scale assessed their e-health literacy. Multiple linear regression was used to explore the dose-response relationship between LPA and e-health literacy and sub-dimension scores. Multiple linear regression revealed that both the overall e-health literacy score and its components were positively associated with daily LPA (Tables 2 and 3). However, the empirical impact varied substantially across components. For each 1-point increase, LPA increased by 2.8 min for the overall score, 11 min for judgment ability, and 19.4 min for decision-making ability, whereas the effect of application ability was statistically significant but minimal. Notably, the effect sizes of all e-health literacy components were substantially smaller than that of educational attainment (β = 0.638-0.947), which was the strongest predictor in all models. This study provides empirical evidence that higher e-health literacy and its specific sub-dimensions are positively associated with light physical activity (LPA) among community-dwelling older adults, with educational attainment emerging as a key independent predictor. These findings suggest that public health interventions aimed at promoting LPA could be enhanced by incorporating strategies to improve e-health literacy, particularly targeting older adults with lower educational backgrounds. The development of tailored, theory-informed programs based on these insights holds promise for fostering healthy aging at the community level. Show less
📄 PDF DOI: 10.1186/s12889-025-26129-y
LPA
Yue Yu, Chengshi Zhang, Ziyu Jiang +4 more · 2026 · Pakistan journal of pharmaceutical sciences · added 2026-04-24
This study aimed to investigate the relationship between blood uric acid (UA), serum lipoprotein(a) [Lp(a)], and the severity of neurological damage in patients with acute penetrating artery occlusive Show more
This study aimed to investigate the relationship between blood uric acid (UA), serum lipoprotein(a) [Lp(a)], and the severity of neurological damage in patients with acute penetrating artery occlusive cerebral infarction combined with type 2 diabetes mellitus (T2DM). To evaluate the role of UA and Lp(a) levels as independent risk factors for neurological damage severity and poor prognosis, and to observe the therapeutic effect of tanshinone. Clinical data of patients were analyzed to compare differences in indicators between the mild and moderate groups, as well as between groups with good and poor prognosis. Patients in the moderate infarction group showed significantly higher levels of UA, Lp(a), and other biochemical markers, along with higher rates of unhealthy lifestyle habits and comorbidities. UA, Lp(a), and infarct diameter were independent risk factors for poor prognosis. Their combined prediction model demonstrated good sensitivity and specificity. Pre-treatment UA and Lp(a) levels were significantly positively correlated with pre-treatment NIHSS scores and post-treatment mRS scores, respectively. In patients with acute penetrating artery occlusive cerebral infarction combined with T2DM, blood uric acid and serum Lp(a) levels are associated with the severity of neurological damage and serve as independent risk factors for poor prognosis. Show less
no PDF DOI: 10.36721/PJPS.2026.39.1.REG.14895.1
LPA
Yiqing Zhou, Yongchun Zeng, Yu Chen +6 more · 2026 · Diabetologia · Springer · added 2026-04-24
We aimed to identify key molecules that can moderately enhance the compensatory capacity of beta cells during obesity. Single-cell RNA-seq was used to profile the RNA expression of islet cells from di Show more
We aimed to identify key molecules that can moderately enhance the compensatory capacity of beta cells during obesity. Single-cell RNA-seq was used to profile the RNA expression of islet cells from diet-induced obese mice and pregnant mice. The gene and protein expression levels of ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2) were verified by quantitative PCR and immunofluorescence, respectively. The roles of ENPP2 were investigated using gain-of-function and loss-of-function approaches in Min6 beta cells, global Enpp2-knockout mice and beta cell Enpp2-overexpressing transgenic (Enpp2-Tg) mice. Using single-cell RNA-seq, we demonstrated that proliferation is the primary and common mechanism for compensating for beta cell numbers during both mouse obesity and pregnancy, with proliferation being more pronounced in pregnancy than in obesity. Additionally, many differentially expressed genes were co-regulated in both conditions. Among these, the pro-proliferative phosphodiesterase ENPP2 showed the highest increase in beta cells of pregnant mice and a moderate increase in beta cells of obese mice. Overexpression or knockdown of ENPP2 in Min6 beta cells revealed that ENPP2 promoted beta cell proliferation, inhibited apoptosis and enhanced high-glucose-stimulated insulin secretion. These effects of ENPP2 were further validated in vivo using Enpp2-Tg mice. In Enpp2-knockout mice fed a high-fat diet, the deficiency of ENPP2 resulted in insufficient compensation of beta cells during obesity. The pro-proliferative role of ENPP2 in beta cells was mediated through the lysophosphatidic acid (LPA)-Akt/mammalian target of rapamycin (mTOR) signalling pathway via LPA receptor 2. However, the expression of ENPP2 was reduced in the mouse model of diabetes and in human participants with type 2 diabetes compared with non-diabetic control groups. Furthermore, ENPP2 was co-upregulated by a synergy of oestradiol and progesterone. ENPP2 may serve as a key regulator in beta cell compensation during obesity, and modulating its levels in beta cells could be a potential therapeutic target for mitigating beta cell deterioration in diabetes. Show less
📄 PDF DOI: 10.1007/s00125-025-06639-5
LPA
Xinyu Wang, Xu Zhang, Jane Jie Yu +3 more · 2026 · Journal of exercise science and fitness · Elsevier · added 2026-04-24
Preschool children's activity patterns differ between weekdays and weekends. Weekdays are constrained by structured educational activities and parental commitments, which limit flexibility, while week Show more
Preschool children's activity patterns differ between weekdays and weekends. Weekdays are constrained by structured educational activities and parental commitments, which limit flexibility, while weekends provide opportunities for extra sleep (SLP), physical activity (PA), and reduced sedentary behavior (SB). This study aims to estimate optimal activity durations for both weekdays and weekends, based on the development of executive function (EF), fundamental movement skills (FMS), and physical fitness (PF) in preschool children. A total of 289 preschool children aged 3-6 years from four kindergartens in Zhejiang Province participated. PA and SLP were objectively measured using accelerometers and the Children's Sleep Quality Questionnaire. EF, which includes working memory, inhibitory control, and cognitive flexibility, was measured using the Early Years Toolbox (EYT). FMS were assessed using the test of gross motor development-3rd edition (TGMD-3), and PF was evaluated according to the National Physical Fitness Measurement Manual (Preschool Children Section). Compositional data regression models were applied to examine the relationship between 24-h movement behaviors and health outcomes on weekdays and weekends. Optimal time-use compositions for each outcome were estimated, and 3D quaternary plots were generated to define the Goldilocks Day at the center of the overlapping regions. 24-h movement behaviors were significantly correlated with EF (weekdays: F = 5.4, This study provides recommendations for time allocation on weekdays and weekends to support the healthy development of preschool children. Show less
📄 PDF DOI: 10.1016/j.jesf.2025.11.004
LPA
Haoyang Sun, Zhaoxu Lu, Jin Guo +10 more · 2026 · Child: care, health and development · Blackwell Publishing · added 2026-04-24
Speed capability is critical for early childhood development, but troubling patterns are emerging in the motor fitness of Chinese preschoolers (3-6 years). This study investigated how compositional 24 Show more
Speed capability is critical for early childhood development, but troubling patterns are emerging in the motor fitness of Chinese preschoolers (3-6 years). This study investigated how compositional 24-h movement behaviours (sleep, sedentary behaviour [SB], light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) relate to speed capability. Via compositional data analysis and isotemporal substitution modelling, we assessed relationships between 24-h movement behaviours (sleep, SB, LPA and MVPA) and speed capability in 275 preschoolers (mean age 4.98 ± 0.76 years). Participants completed 20-m sprint tests and 7-day accelerometry. Time-reallocation effects were quantified through pairwise behavioural substitutions (5- to 30-min durations), with all models adjusted for age, sex and BMI z scores (z-BMI). Higher relative MVPA time significantly predicted faster sprint times (β = -1.302, p < 0.001), while higher LPA predicted slower times (β = 1.570, p = 0.003). Reallocating 15 min from sleep, SB or LPA to MVPA reduced sprint times by 0.176, 0.201 and 0.385 s, respectively (all p < 0.05). Conversely, reallocating MVPA to other behaviours worsened performance. The effects exhibited asymmetry: displacing time away from MVPA impaired speed capability to a greater extent than equivalent gains in MVPA time improved it. MVPA is the strongest positive predictor of speed capability in preschoolers. Optimizing 24-h movement patterns by reallocating time from LPA or SB to MVPA is associated with enhanced speed performance, supporting targeted interventions for early childhood development. Show less
no PDF DOI: 10.1111/cch.70218
LPA
Luomeng Qian, Zhiguang Fu, Ping Chen +11 more · 2026 · International journal of biological sciences · added 2026-04-24
📄 PDF DOI: 10.7150/ijbs.125483
LPA
Yan-Yan Li, Hui Wang, Yang-Yang Zhang · 2026 · The American journal of the medical sciences · Elsevier · added 2026-04-24
The Lipoprotein(a) (LPA) rs3798220 and rs10455872 polymorphisms have been indicated to be involved with the coronary heart disease (CHD) susceptibility. However, there are still differences between th Show more
The Lipoprotein(a) (LPA) rs3798220 and rs10455872 polymorphisms have been indicated to be involved with the coronary heart disease (CHD) susceptibility. However, there are still differences between the individual studies. To explore the correlation of LPA gene rs3798220 and rs10455872 polymorphisms and CHD, the current meta-analysis was performed. The random or fixed effect genetic models were used to calculate the pooled odds ratios (ORs) and their corresponding 95 % confidence intervals (CI). A significant association was found between LPA rs3798220 polymorphism and CHD under allelic (OR: 1.488), recessive (OR: 1.543), dominant (OR: 1.534), homozygous (OR: 1.544), heterozygous (OR: 1.498) and additive genetic models (OR: 1.531). There was also a significant association between LPA rs10455872 polymorphism and CHD under allelic (OR: 1.607), dominant (OR: 1.751), heterozygous (OR: 1.723) and additive genetic models (OR: 1.686). LPA rs3798220 and rs10455872 polymorphisms were significantly associated with increased CAD risk. The persons carrying C allele of LPA rs3798220 and G allele of LPA rs10455872 polymorphisms might have higher CHD risk than the T allele of rs3798220 or A allele of rs10455872 carriers. Show less
no PDF DOI: 10.1016/j.amjms.2025.12.002
LPA
Shengnan Sun, Daniel Dochtermann, Zhaoyu Wang +4 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Suicidal ideation (SI) and behavior are complex phenotypes, with multiple contributing risk-factors. This study used longitudinal data from the Million Veteran Program Mental Health Survey to identify Show more
Suicidal ideation (SI) and behavior are complex phenotypes, with multiple contributing risk-factors. This study used longitudinal data from the Million Veteran Program Mental Health Survey to identify SI profiles among Veterans based on trajectories of ideation and depression severity and compared them to a non-suicidal (no-SI) control group. Latent profile analysis (LPA) was performed to identify SI profiles using data from Veterans (n = 34,322) endorsing SI in their electronic health record. LPA identified four highly reproducible SI profiles: mild ideators with and without depression, variable ideators, and persistent ideators. Veterans across the SI profiles were significantly more likely to have diagnoses of suicidal ideation or behavior, mental disorders, and TBI compared to Veterans with no-SI. The variable ideators showed higher rates of comorbid conditions. The mild ideators without depression and persistent ideators had a significantly higher proportion of deaths by suicide than the no-SI Veterans. European and African American GWAS and pan-ancestry meta-analyses of SI profiles compared to no-SI controls were also performed, which identified genome-wide significant loci across all SI profiles proximal to genes implicated in auditory and vestibular functioning, Alzheimer's, diabetes, and asthma. In summary, SI profiles identified were associated with novel genetic variants not identified by previous suicide GWAS studies. Additionally, Veterans within the mild SI profile that did not present with high-risk comorbidities had the highest rate of suicide deaths, indicating the need for upstream suicide risk prevention interventions across the SI risk continuum. Show less
📄 PDF DOI: 10.1038/s41380-025-03332-2
LPA
Yanxiang Zou, Xiaochen Xiong, Ruxuan Wang +4 more · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Social isolation has emerged as an increasingly critical public health issue among adolescents with depression. This study aimed to identify latent subgroups of social isolation based on its manifesta Show more
Social isolation has emerged as an increasingly critical public health issue among adolescents with depression. This study aimed to identify latent subgroups of social isolation based on its manifestations among adolescent patients with depression and to explore the associated influencing factors. A cross-sectional study was conducted from August 2024 to March 2025 at a specialized psychiatric hospital in Nanjing, China. Data were collected using paper-based questionnaires, which included demographic characteristics, the General Social Alienation Scale (GSAS), the Patient Health Questionnaire for Adolescents (PHQ-A), and the Resilience Scale for Chinese Adolescents (RSCA). Latent profile analysis (LPA) was used to classify patterns of social isolation. Chi-square tests, analysis of variance (ANOVA), lasso regression, and multinomial logistic regression were used to analyze profile characteristics and their influencing factors. A total of 412 adolescent patients with depression were included. This study identified three distinct profiles of social isolation: "Low isolation - Fluctuating group" (24.7 %, n = 102), "Moderate isolation - Skeptical group" (39.6 %, n = 163), and "High isolation - Avoidant group" (35.7 %, n = 147). Patients were significantly more likely to be classified into the "High isolation - Avoidant group" if they had siblings, a longer duration of mental illness, more severe depressive symptoms, or lower psychological resilience (all p < 0.05). This study revealed the heterogeneity of social isolation among adolescents with depression through LPA and identified key influencing factors. These findings provide a theoretical foundation for the development of tailored intervention strategies. Show less
no PDF DOI: 10.1016/j.jad.2025.120769
LPA
Weili Lu, Ke Wang, Kim T Mueser +9 more · 2026 · Journal of mental health (Abingdon, England) · Taylor & Francis · added 2026-04-24
Complex PTSD (CPTSD) is often associated with prolonged or repeated trauma exposure and the experience of intimate partner and childhood abuse. CPTSD includes the criteria for PTSD (re-experiencing, a Show more
Complex PTSD (CPTSD) is often associated with prolonged or repeated trauma exposure and the experience of intimate partner and childhood abuse. CPTSD includes the criteria for PTSD (re-experiencing, avoidance, and sense of threat) in addition to three criteria for self-organization disturbances (affective dysregulation, negative self-concept, and relational disturbance). This study aimed to assess profiles of CPTSD symptoms and their association with psychiatric distress among people with co-occurring Serious Mental Illness (SMI; schizophrenia/schizoaffective, bipolar, and treatment-refractory major depression). Treatment-seeking participants ( A model with three classes best fit the data with the most parsimonious interpretation: 26.7% ( The results demonstrate the heterogeneity in symptom presentation across the PTSD classes and that, despite similar diagnoses, individuals may present with varying symptom patterns. This emphasizes the importance of studying CPTSD in subpopulations of persons with SMI. Show less
no PDF DOI: 10.1080/09638237.2025.2585203
LPA
Ya Su, Zhiyuan Yu, Si Chen +2 more · 2026 · Nurse education in practice · Elsevier · added 2026-04-24
This study aims to identify distinct subgroups of digital resilience among nursing students and examine the factors associated with these subgroups. Digital resilience, the ability to adapt to technol Show more
This study aims to identify distinct subgroups of digital resilience among nursing students and examine the factors associated with these subgroups. Digital resilience, the ability to adapt to technological changes and overcome challenges in higher education, is crucial for protecting students' psychological health and improving academic performance. In the context of Artificial Intelligence (AI) and digital transformation in nursing education, this resilience is essential for students to navigate virtual learning and integrate advanced technologies into their practice. A cross-sectional study. This study was conducted in eight universities in China guided by ecological systems theory and nursing students were recruited through convenience sampling. Latent profile analysis (LPA) identified subgroups and logistic regression examined related factors. A total of 331 (81.73 %) participants were included in the final analysis. The average age of participants was 20.41SD0.67 years, with 283 female (85.55 %). Latent profile analysis revealed two subgroups: the "High Digital Resilience Group" (n = 278, 83.99 %) and the "Low Digital Resilience Group" (n = 53, 16.01 %). Participants who were male (OR = 3.47, p = 0.02), had low household income (OR = 0.23, p = 0.01, low professional identity (OR = 0.86, p < 0.001) and low friend support (OR = 0.82, p < 0.001) were more likely to belong to the low digital resilience group. Educators should focus on enhancing students' professional identity and providing social support, especially for those with low digital resilience. The findings provide practical guidance for integrating AI into nursing education to enhance digital resilience. Show less
no PDF DOI: 10.1016/j.nepr.2025.104636
LPA
Yubi Gan, Die Meng, Lei Lang +11 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Tumor-related metabolites in the tumor microenvironment may induce immune dysfunction, leading to malignant progression and metastasis of tumors. Here, it is demonstrated that tumoral PLA2G16, a phosp Show more
Tumor-related metabolites in the tumor microenvironment may induce immune dysfunction, leading to malignant progression and metastasis of tumors. Here, it is demonstrated that tumoral PLA2G16, a phospholipase catalyzes phospholipids to generate free fatty acid (FFA) or lysophosphatidic acid (LPA), is an important contributor to triple-negative breast cancer (TNBC) lung metastasis in an immune-dependent pattern by improving tetracosatetraenoic acid (C24:4 (n-6)) accumulation in the early metastatic niche of lung and impairing immune function of pulmonary CD8 Show less
📄 PDF DOI: 10.1002/advs.202510224
LPA
Mei Xue, Zi-Feng Zhang, Zu-Xuan Zhang +5 more · 2026 · Sleep medicine · Elsevier · added 2026-04-24
Childhood overweight/obesity poses a significant public health burden, closely linked to time allocation across various movement behaviors. We aimed to clarify the compositional associations between 2 Show more
Childhood overweight/obesity poses a significant public health burden, closely linked to time allocation across various movement behaviors. We aimed to clarify the compositional associations between 24-h time allocation to sleep, sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) and overweight/obesity risk among children aged 2-6 years. This cross-sectional study enrolled 5372 children aged 2-6 years from Beijing. Isotemporal substitution modeling and weighted quantile sum (WQS) regression were adopted. Among all children (mean age 4.52 years; 49.9 % girls), 26.13 % were overweight or obese. Each additional 5 min of daily SB was associated with a higher odds of overweight/obesity (odds ratio [OR] = 1.10, 95 % confidence interval [CI]: 1.02-1.19, p = 0.02), while each 5-min increment in sleep was linked to reduced odds (OR = 0.91, 95 % CI: 0.84-0.98, p = 0.02). Isotemporal substitution analyses indicated that replacing 5 min of SB with sleep (OR = 0.81, 95 % CI: 0.67-0.97, p = 0.02), LPA (OR = 0.84, 95 % CI: 0.72-0.98, p = 0.03), or MVPA (OR = 0.87, 95 % CI: 0.76-1.01, p = 0.06) was associated with lower overweight/obesity risk. Replacing SB with sleep or physical activities reduced the risk. Further WQS analyses revealed that sleep exerted the strongest weight in the behavioral mixture influencing childhood overweight/obesity. This study provides evidence that theoretical reallocation of sedentary time to sleep or physical activities was associated with a significantly lower risk of overweight/obesity in children aged 2-6 years. Importantly, sleep appears to be the most potent component in the behavioral mixture, reinforcing the importance of holistic, multi-behavioral approaches in early childhood obesity prevention strategies. Show less
no PDF DOI: 10.1016/j.sleep.2025.108667
LPA
Xin-Xin Wang, Wei-Hong Zheng, Jing Zhang +3 more · 2026 · Heart & lung : the journal of critical care · Elsevier · added 2026-04-24
Physical activity (PA) is an important non-pharmacological intervention that can slow the progression of Chronic Obstructive Pulmonary Disease (COPD). Unfortunately, PA levels in older adults with COP Show more
Physical activity (PA) is an important non-pharmacological intervention that can slow the progression of Chronic Obstructive Pulmonary Disease (COPD). Unfortunately, PA levels in older adults with COPD remain low, and there is substantial heterogeneity within this population. Therefore, identifying potential subgroups is essential for developing targeted interventions. The purpose of this study is to identify latent profiles of PA, and explore the associated factors to inform personalized interventions for this population. This multicenter cross-sectional study was conducted from November 2024 to March 2025 at a tertiary hospital and four community health service centers in the Changning District of Shanghai. The revised International Physical Activity Questionnaire-Long (IPAQ-L) was utilized to assess PA and sedentary behavior. Latent profile analysis (LPA) was employed to classify the subgroups, followed by multinomial logistic regression to explore influencing factors. A total of 423 older adults with COPD (male N = 383; aged 60-89) were included in this study. LPA identified three distinct PA profiles, named the "moderate activity-moderate sedentary-low barrier (C1) group", the "low activity-high sedentary-high barrier (C2) group", and the "high activity-low sedentary-moderate barrier (C3) group". The factors were significantly associated with PA, including Body Mass Index (BMI), disease duration, number of hospitalizations, GOLD stage, COPD Assessment Test (CAT) score, exercise self-efficacy, and exercise social support (p < 0.05). LPA identified three subgroups of PA in older adults with COPD. The results of this research will facilitate targeted interventions for each of the identified subgroups with distinct characteristics, thereby enhancing the management of COPD and reducing healthcare burdens. Show less
no PDF DOI: 10.1016/j.hrtlng.2025.11.007
LPA
Bowen Tan, Hewanmeng Geng, Zeyu Hao +9 more · 2026 · The journal of nutrition, health & aging · Elsevier · added 2026-04-24
Accelerometer-derived physical activity is associated with reduced stroke risk. The biological pathways underpinning this relationship, however, are not yet understood. Herein, we aim to identify meta Show more
Accelerometer-derived physical activity is associated with reduced stroke risk. The biological pathways underpinning this relationship, however, are not yet understood. Herein, we aim to identify metabolic signatures associated with accelerometer-measured PA and investigate their relationships with reduced stroke incidence. Utilizing UK Biobank accelerometer data, we derived physical activity into total physical activity (TPA), moderate-to-vigorous physical activity (MVPA), and light physical activity (LPA) and linked them to 249 NMR-quantified plasma metabolites. The metabolomic signatures (TPA-/MVPA-/LPA-metabolomic signatures) were developed through internal validation followed by elastic-net regression modeling. Cox proportional hazards models evaluated activity-stroke associations (adjusted for sociodemographic/genetic factors), followed by mediation analysis to quantify metabolomic signature effects. Through UK Biobank study (N = 29445; 14.1-year follow-up with 513 stroke events), we identified 195 TPA, 173 MVPA, and 164 LPA metabolite associations (FDR < 0.05), with 107, 92, and 15 validated, respectively. Elastic net-derived physical activity-metabolomic signatures (TPA-/MVPA-metabolomic signatures) correlated with physical activity intensities (r = 0.20-0.30, P < 0.001) and were associated with reduced stroke risk: TPA-metabolomic signatures (HR = 0.61, 95% CI: 0.44-0.87); MVPA-metabolomic signatures (HR = 0.50, 95%CI: 0.29-0.88). Mediation analyses showed TPA-metabolomic signatures and MVPA-metabolomic signatures explained 12.2% and 8.5% of physical activity-stroke associations (P < 0.001), implicating specific lipoprotein subclasses and lipids as key mediators. TPA-metabolomic signatures and MVPA-metabolomic signatures, particularly the 11 key metabolites included, significantly mediate the association between accelerometer-derived physical activity and stroke risk. Show less
📄 PDF DOI: 10.1016/j.jnha.2025.100715
LPA
Zhaoxu Lu, Jin Guo, Yihua Bao +13 more · 2026 · International journal of obesity (2005) · Nature · added 2026-04-24
To use compositional data analysis to examine the associations of daily movement behaviors with body composition, and to predict changes in body composition after reallocating time among behaviors in Show more
To use compositional data analysis to examine the associations of daily movement behaviors with body composition, and to predict changes in body composition after reallocating time among behaviors in preschool-aged children. 268 preschoolers were included in the cross-sectional study. An accelerometer was used to assess sedentary behavior (SB), light and moderate-to-vigorous physical activity (LPA and MVPA). A parental report was used to collect sleep time. Bioelectrical impedance analysis was employed to assess body composition. Compositional linear regression analysis was employed to explore how daily movement behaviors were associated with body composition. Compositional isotemporal substitution analysis was employed to estimate changes in body composition after reallocating time among behaviors. 24-h movement behaviors composition significantly predicted fat-free mass index (FFMI), soft lean mass index (SLMI), and skeletal muscle mass index (SMMI), but not fat mass index, percent body fat, and bone mineral content index. The compositional isotemporal substitution analyses consistently showed that increasing MVPA at the expenses of SB was positively associated with FFMI (+0.328 kg/m The findings highlight the importance of MVPA in improving preschoolers' body composition. Increasing MVPA at the expenses of SB may be a strategy to improve body composition in preschoolers. Show less
📄 PDF DOI: 10.1038/s41366-025-01939-7
LPA
Xinjun Liu, Qiqi Wang, Tingting Qiu +4 more · 2026 · Annals of vascular surgery · Elsevier · added 2026-04-24
This study aimed to assess the knowledge, attitudes, and practices (KAP) of patients with lower limb arteriosclerosis obliterans (ASO) toward their disease. This cross-sectional study was conducted at Show more
This study aimed to assess the knowledge, attitudes, and practices (KAP) of patients with lower limb arteriosclerosis obliterans (ASO) toward their disease. This cross-sectional study was conducted at 3 tertiary hospitals in Chengdu between August 2023 and January 2024 and included patients with lower limb ASO. Data were collected using an interviewer-administered questionnaire that captured demographic information and KAP scores. A latent profile analysis (LPA) was used to identify the KAP patterns among participants. A total of 515 nonproblematic questionnaires were collected, yielding an effective response rate of 95.72%. Among the respondents, 395 (76.85%) were male, with a disease course of 15.96 ± 17.55 months. The knowledge, attitude, and practice scores were 5.27 ± 4.69 (possible range: 0-22), 17.65 ± 2.86 (possible range: 5-25), and 107.63 ± 17.15 (possible range: 33-165), respectively. LPA identified 4 participant profiles: Profile 1 (high attitude, low practice), Profile 2 (low attitude, high practice), Profile 3 (low attitude, low practice), and Profile 4 (high attitude, high practice). Significant differences were found among profiles in residence (P = 0.028), medical insurance (P = 0.043), self-efficacy (P < 0.001), and patient activation (P < 0.001). Patients with lower limb ASO demonstrated inadequate knowledge but moderate levels of attitude and practice. Residence, medical insurance, self-efficacy, and patient activation may affect the KAP patterns of the patients. These findings suggest that tailored interventions targeting distinct patient profiles, while considering broader social determinants of health, may be critical to improving self-management and outcomes. Show less
no PDF DOI: 10.1016/j.avsg.2025.10.022
LPA
Hanning Lei, Zhiqian Zhang, Yun Wang +3 more · 2026 · Journal of youth and adolescence · Springer · added 2026-04-24
Although many studies have indicated that problematic smartphone use and depressive symptoms are closely associated and frequently co-occur in adolescence, little is known about their heterogeneous co Show more
Although many studies have indicated that problematic smartphone use and depressive symptoms are closely associated and frequently co-occur in adolescence, little is known about their heterogeneous co-occurrence profiles and how these profiles evolve over time. Using person-centered approaches (LPA and RT-LTA), this study identified the co-occurrence patterns of problematic smartphone use and depressive symptoms, examined their transitions, and investigated the roles of social support and self-control on transitions. A total of 8969 Chinese adolescents (49.3% girls; T1: M Show less
no PDF DOI: 10.1007/s10964-025-02253-1
LPA
Yu-Jen Wei, Yung-Chieh Lin, Yen-Ju Chen +2 more · 2026 · Pediatric research · Nature · added 2026-04-24
In premature infants, patent ductus arteriosus (PDA) can lead to hemodynamic instability and prematurity-related complications. The conventional left atrial-to-aortic (LA/Ao) ratio for evaluating hemo Show more
In premature infants, patent ductus arteriosus (PDA) can lead to hemodynamic instability and prematurity-related complications. The conventional left atrial-to-aortic (LA/Ao) ratio for evaluating hemodynamically significant PDA (hsPDA) has demonstrated limited accuracy. We aimed to investigate the correlation between mitral inflow E-wave velocity, left pulmonary artery (LPA) end-diastolic velocity, and hsPDA in preterm infants. Single-center, retrospective cohort study included neonates born at a gestational age (GA) between 24 and 30 weeks. The echocardiographic parameters, including mitral E-wave velocity, LPA end-diastolic velocity and LA/Ao ratio were assessed with hsPDA requiring treatment. Forty-nine infants were included, of whom 30 were diagnosed with hsPDA. The mitral E-wave (95% CI: 4.6-18.2, p = 0.0016) and LPA end-diastolic velocities (95% CI: 4.14-15.15, p = 0.0010) were significantly higher in infants with hsPDA, while the LA/Ao ratio exhibited no difference. Multivariate analysis revealed that lower GA, higher mitral E-wave, and LPA end-diastolic velocities were predictive of hsPDA. The receiver operating characteristic (ROC) analysis showed that these parameters offered better diagnostic accuracy than the LA/Ao ratio. Our findings suggest that mitral E wave and LPA end-diastolic velocities are more reliable echocardiographic markers for evaluating hsPDA in preterm infants than the conventional LA/Ao ratio. Assessment of dynamic blood flow is more reliable than the left atrium chamber size in evaluating the hemodynamic status of a PDA. Our result provides new criteria for assessing the hemodynamic significance of PDA. Utilizing this technique may yield evidence to assist clinical decision-making regarding PDA treatment. Multifactorial assessment, including birth gestational age and increased intracardiac or pulmonary blood flow velocity, provides more accurate prediction for a hsPDA. Show less
no PDF DOI: 10.1038/s41390-025-04449-4
LPA
Jiabei Wang, Jianhao Wang, Hongyu Chen +16 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Accumulating research has demonstrated a significant association between early-life inflammation and behavioral disorders later in life. However, the effects of early-life inflammation on aggressive b Show more
Accumulating research has demonstrated a significant association between early-life inflammation and behavioral disorders later in life. However, the effects of early-life inflammation on aggressive behavior in adulthood remain poorly understood. Here, we show that early-life inflammation induced by lipopolysaccharide (LPS) upregulated neuronal dynamin-related protein 1 (DRP1) and impaired mitochondrial function in medial prefrontal cortex (mPFC) of adult mice, thereby increasing aggressive behavior in adulthood. We further identify that CCAAT/enhancer binding protein β (C/EBPβ) is the transcription factor of Dnm1l, which was activated by an increased release of lysophosphatidic acid (LPA) induced by early-life inflammation. Moreover, the overproduction of LPA was due to a specific increase in astrocyte-secreted autotaxin (ATX). Specific knockdown of astrocytic ATX reduced early-life inflammation-induced aggression in wild-type mice, but not in Thy1-C/EBPβ transgenic mice. Remarkably, coenzyme Q10 decreased early-life inflammation-induced aggressive behavior in adult mice. Altogether, these findings provide new insights into the molecular mechanisms by which early inflammation promotes aggressive behavior in adulthood. Show less
📄 PDF DOI: 10.1038/s41380-025-03260-1
LPA
Mengyao Zhu, Xu Guo, Yingying Chen +6 more · 2026 · Journal of food science · Blackwell Publishing · added 2026-04-24
The polyphenols in grains are highly active, but some polyphenols in highland barley are in a bound form and have extremely low bioavailability. Fermentation by lactic acid bacteria (LAB) is capable o Show more
The polyphenols in grains are highly active, but some polyphenols in highland barley are in a bound form and have extremely low bioavailability. Fermentation by lactic acid bacteria (LAB) is capable of altering the functionality of foods. This research investigated the effects of fermentation with different LAB, such as Lactobacillus acidophilus (LAC), Lactobacillus casei (LCA), Lactobacillus rhamnosus (LRH), Lactobacillus plantarum (LPL), and Lactobacillus bulgaricus (LBU), on the hypoglycemic activity and mechanism of polyphenols in highland barley. The hypoglycemic activity of the fermentation products was measured by in vitro antioxidant, enzyme activity, and glucose consumption experiments. Untargeted metabolomic analysis used UHPLC-Q Exactive HF-X/MS to reveal distinct metabolic profiles among the fermented groups. Molecular docking and western blot experiments were conducted to elucidate the mechanism underlying the hypoglycemic effect of fermentation products. Polyphenolic antioxidant activity in highland barley and its inhibitory activities against α-glucosidase and α-amylase were increased after LAC fermentation. Furthermore, the fermented extracts improved glucose consumption in HepG2 cells. The content determination and metabolomic analysis showed that fermented highland barley polyphenols were increased, and 113 differential phenolic metabolites were identified and annotated, among which 44 exhibited a significant upregulation compared with raw highland barley polyphenols. At the molecular level, the polyphenol extract upregulated PI3K and phosphorylated Akt expression in HepG2 cells. Overall, the results indicate that fermentation by LAC biotransformed highland barley polyphenols into smaller molecules with improved hypoglycemic activities, thereby enhancing their bioavailability. Show less
no PDF DOI: 10.1111/1750-3841.71061
LPL