👤 Xiaowei Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, Yajuan Liu, Yaling Liu, Yalu Liu, Yan Liu, Yan-Li Liu, Yanan Liu, Yanchao Liu, Yanchen Liu, Yandong Liu, Yanfei Liu, Yanfen Liu, Yanfeng Liu, Yang Liu, Yange Liu, Yangfan Liu, Yangfan P Liu, Yangjun Liu, Yangkai Liu, Yangruiyu Liu, Yangyang Liu, Yanhong Liu, Yanhua Liu, Yanhui Liu, Yanjie Liu, Yanju Liu, Yanjun Liu, Yankuo Liu, Yanli Liu, Yanliang Liu, Yanling Liu, Yanman Liu, Yanmin Liu, Yanping Liu, Yanqing Liu, Yanqiu Liu, Yanquan Liu, Yanru Liu, Yansheng Liu, Yansong Liu, Yanting Liu, Yanwu Liu, Yanxiao Liu, Yanyan Liu, Yanyao Liu, Yanying Liu, Yanyun Liu, Yao Liu, Yao-Hui Liu, Yaobo Liu, Yaoquan Liu, Yaou Liu, Yaowen Liu, Yaoyao Liu, Yaozhong Liu, Yaping Liu, Yaqiong Liu, Yarong Liu, Yaru Liu, Yating Liu, Yaxin Liu, Ye Liu, Ye-Dan Liu, Yehai Liu, Yen-Chen Liu, Yen-Chun Liu, Yen-Nien Liu, Yeqing Liu, Yi Liu, Yi-Chang Liu, Yi-Chien Liu, Yi-Han Liu, Yi-Hung Liu, Yi-Jia Liu, Yi-Ling Liu, Yi-Meng Liu, Yi-Ming Liu, Yi-Yun Liu, Yi-Zhang Liu, YiRan Liu, Yibin Liu, Yibing Liu, Yicun Liu, Yidan Liu, Yidong Liu, Yifan Liu, Yifu Liu, Yihao Liu, Yiheng Liu, Yihui Liu, Yijing Liu, Yilei Liu, Yili Liu, Yilin Liu, Yimei Liu, Yiming Liu, Yin Liu, Yin-Ping Liu, Yinchu Liu, Yinfang Liu, Ying Liu, Ying Poi Liu, Yingchun Liu, Yinghua Liu, Yinghuan Liu, Yinghui Liu, Yingjun Liu, Yingli Liu, Yingwei Liu, Yingxia Liu, Yingyan Liu, Yingyi Liu, Yingying Liu, Yingzi Liu, Yinhe Liu, Yinhui Liu, Yining Liu, Yinjiang Liu, Yinping Liu, Yinuo Liu, Yiping Liu, Yiqing Liu, Yitian Liu, Yiting Liu, Yitong Liu, Yiwei Liu, Yiwen Liu, Yixiang Liu, Yixiao Liu, Yixuan Liu, Yiyang Liu, Yiyi Liu, Yiyuan Liu, Yiyun Liu, Yizhi Liu, Yizhuo Liu, Yong Liu, Yong Mei Liu, Yong-Chao Liu, Yong-Hong Liu, Yong-Jian Liu, Yong-Jun Liu, Yong-Tai Liu, Yong-da Liu, Yongchao Liu, Yonggang Liu, Yonggao Liu, Yonghong Liu, Yonghua Liu, Yongjian Liu, Yongjie Liu, Yongjun Liu, Yongli Liu, Yongmei Liu, Yongming Liu, Yongqiang Liu, Yongshuo Liu, Yongtai Liu, Yongtao Liu, Yongtong Liu, Yongxiao Liu, Yongyue Liu, You Liu, You-ping Liu, Youan Liu, Youbin Liu, Youdong Liu, Youhan Liu, Youlian Liu, Youwen Liu, Yu Liu, Yu Xuan Liu, Yu-Chen Liu, Yu-Ching Liu, Yu-Hui Liu, Yu-Li Liu, Yu-Lin Liu, Yu-Peng Liu, Yu-Wei Liu, Yu-Zhang Liu, YuHeng Liu, Yuan Liu, Yuan-Bo Liu, Yuan-Jie Liu, Yuan-Tao Liu, YuanHua Liu, Yuanchu Liu, Yuanfa Liu, Yuanhang Liu, Yuanhui Liu, Yuanjia Liu, Yuanjiao Liu, Yuanjun Liu, Yuanliang Liu, Yuantao Liu, Yuantong Liu, Yuanxiang Liu, Yuanxin Liu, Yuanxing Liu, Yuanying Liu, Yuanyuan Liu, Yubin Liu, Yuchen Liu, Yue Liu, Yuecheng Liu, Yuefang Liu, Yuehong Liu, Yueli Liu, Yueping Liu, Yuetong Liu, Yuexi Liu, Yuexin Liu, Yuexing Liu, Yueyang Liu, Yueyun Liu, Yufan Liu, Yufei Liu, Yufeng Liu, Yuhao Liu, Yuhe Liu, Yujia Liu, Yujiang Liu, Yujie Liu, Yujun Liu, Yulan Liu, Yuling Liu, Yulong Liu, Yumei Liu, Yumiao Liu, Yun Liu, Yun-Cai Liu, Yun-Qiang Liu, Yun-Ru Liu, Yun-Zi Liu, Yunfen Liu, Yunfeng Liu, Yuning Liu, Yunjie Liu, Yunlong Liu, Yunqi Liu, Yunqiang Liu, Yuntao Liu, Yunuan Liu, Yunuo Liu, Yunxia Liu, Yunyun Liu, Yuping Liu, Yupu Liu, Yuqi Liu, Yuqiang Liu, Yuqing Liu, Yurong Liu, Yuru Liu, Yusen Liu, Yutao Liu, Yutian Liu, Yuting Liu, Yutong Liu, Yuwei Liu, Yuxi Liu, Yuxia Liu, Yuxiang Liu, Yuxin Liu, Yuxuan Liu, Yuyan Liu, Yuyi Liu, Yuyu Liu, Yuyuan Liu, Yuzhen Liu, Yv-Xuan Liu, Z H Liu, Z Q Liu, Z Z Liu, Zaiqiang Liu, Zan Liu, Zaoqu Liu, Ze Liu, Zefeng Liu, Zekun Liu, Zeming Liu, Zengfu Liu, Zeyu Liu, Zezhou Liu, Zhangyu Liu, Zhangyuan Liu, Zhansheng Liu, Zhao Liu, Zhaoguo Liu, Zhaoli Liu, Zhaorui Liu, Zhaotian Liu, Zhaoxiang Liu, Zhaoxun Liu, Zhaoyang Liu, Zhe Liu, Zhekai Liu, Zheliang Liu, Zhen Liu, Zhen-Lin Liu, Zhendong Liu, Zhenfang Liu, Zhenfeng Liu, Zheng Liu, Zheng-Hong Liu, Zheng-Yu Liu, ZhengYi Liu, Zhengbing Liu, Zhengchuang Liu, Zhengdong Liu, Zhenghao Liu, Zhengkun Liu, Zhengtang Liu, Zhengting Liu, Zhenguo Liu, Zhengxia Liu, Zhengye Liu, Zhenhai Liu, Zhenhao Liu, Zhenhua Liu, Zhenjiang Liu, Zhenjiao Liu, Zhenjie Liu, Zhenkui Liu, Zhenlei Liu, Zhenmi Liu, Zhenming Liu, Zhenna Liu, Zhenqian Liu, Zhenqiu Liu, Zhenwei Liu, Zhenxing Liu, Zhenxiu Liu, Zhenzhen Liu, Zhenzhu Liu, Zhi Liu, Zhi Y Liu, Zhi-Fen Liu, Zhi-Guo Liu, Zhi-Jie Liu, Zhi-Kai Liu, Zhi-Ping Liu, Zhi-Ren Liu, Zhi-Wen Liu, Zhi-Ying Liu, Zhicheng Liu, Zhifang Liu, Zhigang Liu, Zhiguo Liu, Zhihan Liu, Zhihao Liu, Zhihong Liu, Zhihua Liu, Zhihui Liu, Zhijia Liu, Zhijie Liu, Zhikui Liu, Zhili Liu, Zhiming Liu, Zhipeng Liu, Zhiping Liu, Zhiqian Liu, Zhiqiang Liu, Zhiru Liu, Zhirui Liu, Zhishuo Liu, Zhitao Liu, Zhiteng Liu, Zhiwei Liu, Zhixiang Liu, Zhixue Liu, Zhiyan Liu, Zhiying Liu, Zhiyong Liu, Zhiyuan Liu, Zhong Liu, Zhong Wu Liu, Zhong-Hua Liu, Zhong-Min Liu, Zhong-Qiu Liu, Zhong-Wu Liu, Zhong-Ying Liu, Zhongchun Liu, Zhongguo Liu, Zhonghua Liu, Zhongjian Liu, Zhongjuan Liu, Zhongmin Liu, Zhongqi Liu, Zhongqiu Liu, Zhongwei Liu, Zhongyu Liu, Zhongyue Liu, Zhongzhong Liu, Zhou Liu, Zhou-di Liu, Zhu Liu, Zhuangjun Liu, Zhuanhua Liu, Zhuo Liu, Zhuoyuan Liu, Zi Hao Liu, Zi-Hao Liu, Zi-Lun Liu, Zi-Ye Liu, Zi-wen Liu, Zichuan Liu, Zihang Liu, Zihao Liu, Zihe Liu, Ziheng Liu, Zijia Liu, Zijian Liu, Zijing J Liu, Zimeng Liu, Ziqian Liu, Ziqin Liu, Ziteng Liu, Zitian Liu, Ziwei Liu, Zixi Liu, Zixuan Liu, Ziyang Liu, Ziying Liu, Ziyou Liu, Ziyuan Liu, Ziyue Liu, Zong-Chao Liu, Zong-Yuan Liu, Zonghua Liu, Zongjun Liu, Zongtao Liu, Zongxiang Liu, Zu-Guo Liu, Zuguo Liu, Zuohua Liu, Zuojin Liu, Zuolu Liu, Zuyi Liu, Zuyun Liu
articles

Study of the association of 17 lipid-related gene polymorphisms with coronary heart disease.

Nan Wu, Guili Liu, Yi Huang +5 more · 2018 · Anatolian journal of cardiology · added 2026-04-24
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study e Show more
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study examined with 784 CHD cases and 739 non-CHD controls. Genotyping was performed on the MassARRAY iPLEX® assay platform. Our analyses revealed a significant association of APOE rs7259620 with CHD (genotype: χ2=6.353, df=2, p=0.042; allele: χ2=5.05, df=1, p=0.025; recessive model: χ2=5.57, df=1, p=0.018). A further gender-based subgroup analysis revealed significant associations of APOE rs7259620 and PPAP2B rs72664392 with CHD in males (genotype: χ2=8.379, df=2, p=0.015; allele: χ2=5.190, df=1, p=0.023; recessive model: χ2=19.3, df=1, p<0.0001) and females (genotype: χ2=9.878, df=2, p=0.007), respectively. Subsequent breakdown analysis by age showed that CETP rs4783961, MLXIPL rs35493868, and PON2 rs12704796 were significantly associated with CHD among individuals younger than 55 years of age (CETP rs4783961: χ2=8.966, df=1, p=0.011 by genotype; MLXIPL rs35493868: χ2=4.87, df=1, p=0.027 by allele; χ2=4.88, df=1, p=0.027 by dominant model; PON2 rs12704796: χ2=6.511, df=2, p=0.039 by genotype; χ2=6.210, df=1, p=0.013 by allele; χ2=5.03, df=1, p=0.025 by dominant model). Significant allelic association was observed between LEPR rs656451 and CHD among individuals older than 65 years of age (χ2=4.410, df=1, p=0.036). Our study revealed significant associations of APOE, PPAP2B, CETP, MLXIPL, PON2, and LEPR gene polymorphisms with CHD among the Han Chinese. Show less
📄 PDF DOI: 10.14744/AnatolJCardiol.2018.23682
CETP

Insulin suppresses the AMPK signaling pathway to regulate lipid metabolism in primary cultured hepatocytes of dairy cows.

Xinwei Li, Yu Li, Hongyan Ding +7 more · 2018 · The Journal of dairy research · added 2026-04-24
Dairy cows with type II ketosis display hepatic fat accumulation and hyperinsulinemia, but the underlying mechanism is not completely clear. This study aimed to clarify the regulation of lipid metabol Show more
Dairy cows with type II ketosis display hepatic fat accumulation and hyperinsulinemia, but the underlying mechanism is not completely clear. This study aimed to clarify the regulation of lipid metabolism by insulin in cow hepatocytes. In vitro, cow hepatocytes were treated with 0, 1, 10, or 100 nm insulin in the presence or absence of AICAR (an AMP-activated protein kinase alpha (AMPKα) activator). The results showed that insulin decreased AMPKα phosphorylation. This inactivation of AMPKα increased the gene and protein expression levels of carbohydrate responsive element-binding protein (ChREBP) and sterol regulatory element-binding protein-1c (SREBP-1c), which downregulated the expression of lipogenic genes, thereby decreasing lipid biosynthesis. Furthermore, AMPKα inactivation decreased the gene and protein expression levels of peroxisome proliferator-activated receptor-α (PPARα), which upregulated the expression of lipid oxidation genes, thereby increasing lipid oxidation. In addition, insulin decreased the very low density lipoprotein (VLDL) assembly. Consequently, triglyceride content was significantly increased in insulin treated hepatocytes. Activation of AMPKα induced by AICAR could reverse the effect of insulin on PPARα, SREBP-1c, and ChREBP, thereby decreasing triglyceride content. These results indicate that insulin inhibits the AMPKα signaling pathway to increase lipid synthesis and decrease lipid oxidation and VLDL assembly in cow hepatocytes, thereby inducing TG accumulation. This mechanism could partly explain the causal relationship between hepatic fat accumulation and hyperinsulinemia in dairy cows with type II ketosis. Show less
no PDF DOI: 10.1017/S002202991800016X
MLXIPL

Neurexin gene family variants as risk factors for autism spectrum disorder.

Jia Wang, Jianhua Gong, Li Li +7 more · 2018 · Autism research : official journal of the International Society for Autism Research · Wiley · added 2026-04-24
Increasing evidence suggests that abnormal synaptic function leads to neuronal developmental disorders and is an important component of the etiology of autism spectrum disorder (ASD). Neurexins are pr Show more
Increasing evidence suggests that abnormal synaptic function leads to neuronal developmental disorders and is an important component of the etiology of autism spectrum disorder (ASD). Neurexins are presynaptic cell-adhesion molecules that affect the function of synapses and mediate the conduction of nerve signals. Thus, neurexins are attractive candidate genes for autism. Since gene families have greater power to reveal genetic association than single genes, we designed this case-control study to investigate six genetic variants in three neurexin genes (NRXN1, NRXN2, and NRXN3) in a Chinese population including 529 ASD patients and 1,923 healthy controls. We found that two SNPs were significantly associated with ASD after false discovery rate (FDR) adjustment for multiple comparisons. The NRXN2 rs12273892 polymorphism T allele and AT genotype were significantly associated with increased risk of ASD (respectively: OR = 1.328, 95% CI = 1.133-1.557, P < 0.001; OR = 1.528; 95% CI = 1.249-1.868, P < 0.001). The dominant model showed the same association (OR = 1.495, 95% CI = 1.231-1.816, P < 0.001). The NRXN3 rs12879016 polymorphism played a significant role in ASD susceptibility under the dominant model (OR = 0.747, 95% CI= 0.615-0.908, P = 0.023), with the same trend detected for the G allele and GT genotype (respectively: OR = 0.811, 95% CI = 0.699-0.941, P = 0.036; OR = 0.755, 95% CI = 0.615-0.928, P = 0.035). In conclusion, this study supports the importance of two genetic variants in the neurexin gene family in ASD susceptibility in China. Autism Res 2018, 11: 37-43. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is highly heritable, and studies have found a number of candidate genes that might contribute to ASD. Neurexins are presynaptic cell-adhesion molecules that affect the function of synapses and mediate the conduction of nerve signals, and they play an important role in normal brain development and become candidate genes for autism. The purpose of our study is to explore the association between variants of the neurexins gene family and ASD in a Chinese population through a case-control study. Show less
no PDF DOI: 10.1002/aur.1881
NRXN3

Molecular analysis of inherited cardiomyopathy using next generation semiconductor sequencing technologies.

Chaoxia Lu, Wei Wu, Fang Liu +9 more · 2018 · Journal of translational medicine · BioMed Central · added 2026-04-24
Cardiomyopathies are the most common clinical and genetic heterogeneity cardiac diseases, and genetic contribution in particular plays a major role in patients with primary cardiomyopathies. The aim o Show more
Cardiomyopathies are the most common clinical and genetic heterogeneity cardiac diseases, and genetic contribution in particular plays a major role in patients with primary cardiomyopathies. The aim of this study is to investigate cases of inherited cardiomyopathy (IC) for potential disease-causing mutations in 64 genes reported to be associated with IC. A total of 110 independent cases or families diagnosed with various primary cardiomyopathies, including hypertrophic cardiomyopathy, dilated cardiomyopathy, restrictive cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, left ventricular non-compaction, and undefined cardiomyopathy, were collected after informed consent. A custom designed panel, including 64 genes, was screened using next generation sequencing on the Ion Torrent PGM platform. The best candidate disease-causing variants were verified by Sanger sequencing. A total of 78 variants in 73 patients were identified. After excluding the variants predicted to be benign and VUS, 26 pathogenic or likely pathogenic variants were verified in 26 probands (23.6%), including a homozygous variant in the SLC25A4 gene. Of these variants, 15 have been reported in the Human Gene Mutation Database or ClinVar database, while 11 are novel. The majority of variants were observed in the MYH7 (8/26) and MYBPC3 (6/26) gene. Titin (TTN) truncating mutations account for 13% in our dilated cardiomyopathy cases (3/23). This study provides an overview of the genetic aberrations in this cohort of Chinese IC patients and demonstrates the power of next generation sequencing in IC. Genetic results can provide precise clinical diagnosis and guidance regarding medical care for some individuals. Show less
no PDF DOI: 10.1186/s12967-018-1605-5
MYBPC3

Long Non-coding RNA PVT1 Promotes Cell Proliferation and Migration by Silencing ANGPTL4 Expression in Cholangiocarcinoma.

Yang Yu, Mingjiong Zhang, Jie Liu +9 more · 2018 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
Cholangiocarcinoma (CCA) is the most common biliary tract malignancy, with a low survival rate and limited treatment options. Long non-coding RNAs (lncRNAs) have recently been verified to have signifi Show more
Cholangiocarcinoma (CCA) is the most common biliary tract malignancy, with a low survival rate and limited treatment options. Long non-coding RNAs (lncRNAs) have recently been verified to have significant regulatory functions in many kinds of human cancers. It was discovered in this study that the lncRNA PVT1, whose expression is significantly elevated in CCA, could be a molecular marker of CCA. Experiments indicated that PVT1 knockdown greatly inhibited cell migration and proliferation in vitro and in vivo. According to RNA sequencing (RNA-seq) analysis, PVT1 knockdown dramatically influenced target genes associated with cell angiogenesis, cell proliferation, and the apoptotic process. RNA immunoprecipitation (RIP) analysis demonstrated that, by binding to epigenetic modification complexes (PRC2), PVT1 could adjust the histone methylation of the promoter of ANGPTL4 (angiopoietin-like 4) and, thus, promote cell growth, migration, and apoptosis progression. The data verified the significant functions of PVT1 in CCA oncogenesis, and they suggested that PVT1 could be a target for CCA intervention. Show less
📄 PDF DOI: 10.1016/j.omtn.2018.10.001
ANGPTL4

Velvet Antler Mobilizes Endothelial Progenitor Cells to Promote Angiogenesis and Repair Vascular Endothelial Injury in Rats Following Myocardial Infarction.

Yanjun Li, Ziwei Wang, Min Mao +9 more · 2018 · Frontiers in physiology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fphys.2018.01940
HEY2

Molecular Mechanistic Insights into Drosophila DHX36-Mediated G-Quadruplex Unfolding: A Structure-Based Model.

Wei-Fei Chen, Stephane Rety, Hai-Lei Guo +8 more · 2018 · Structure (London, England : 1993) · Elsevier · added 2026-04-24
Helicase DHX36 plays essential roles in cell development and differentiation at least partially by resolving G-quadruplex (G4) structures. Here we report crystal structures of the Drosophila homolog o Show more
Helicase DHX36 plays essential roles in cell development and differentiation at least partially by resolving G-quadruplex (G4) structures. Here we report crystal structures of the Drosophila homolog of DHX36 (DmDHX36) in complex with RNA and a series of DNAs. By combining structural, small-angle X-ray scattering, molecular dynamics simulation, and single-molecule fluorescence studies, we revealed that positively charged amino acids in RecA2 and OB-like domains constitute an elaborate structural pocket at the nucleic acid entrance, in which negatively charged G4 DNA is tightly bound and partially destabilized. The G4 DNA is then completely unfolded through the 3'-5' translocation activity of the helicase. Furthermore, crystal structures and DNA binding assays show that G-rich DNA is preferentially recognized and in the presence of ATP, specifically bound by DmDHX36, which may cooperatively enhance the G-rich DNA translocation and G4 unfolding. On the basis of these results, a conceptual G4 DNA-resolving mechanism is proposed. Show less
no PDF DOI: 10.1016/j.str.2018.01.008
DHX36

Alteration of Hepatic Gene Expression along with the Inherited Phenotype of Acquired Fatty Liver in Chicken.

Yonghong Zhang, Zhen Liu, Ranran Liu +6 more · 2018 · Genes · MDPI · added 2026-04-24
Fatty liver is a widespread disease in chickens that causes a decrease in egg production and even death. The characteristics of the inherited phenotype of acquired fatty liver and the molecular mechan Show more
Fatty liver is a widespread disease in chickens that causes a decrease in egg production and even death. The characteristics of the inherited phenotype of acquired fatty liver and the molecular mechanisms underlying it, however, are largely unknown. In the current study, fatty liver was induced in 3 breeds by a high-fat (HF) diet and a methionine choline-deficient (MCD) diet. The results showed that the dwarf Jingxing-Huang (JXH) chicken was more susceptible to fatty liver compared with the layer White Leghorns (WL) and local Beijing-You (BJY) breeds. In addition, it was found that the paternal fatty livers induced by HF diet in JXH chickens were inherited. Compared to birds without fatty liver in the control group, both offsprings and their sires with fatty livers in the paternal group exhibited altered hepatic gene expression profiles, including upregulation of several key genes involved in fatty acid metabolism, lipid metabolism and glucose metabolism ( Show less
📄 PDF DOI: 10.3390/genes9040199
APOA4

Effect of FGF2 on the activity of SPRYs/DUSP6/ERK signaling pathway in endometrial glandular epithelial cells of endometriosis.

X-Y Yu, X-T Wang, Y-L Chu +4 more · 2018 · European review for medical and pharmacological sciences · added 2026-04-24
We aimed at exploring the positive feedback loop in eutopic and ectopic endometrial glandular epithelial cells (EuECs and EECs) in endometriosis. Normal epithelial cells (NECs), EuECs and EECs were tr Show more
We aimed at exploring the positive feedback loop in eutopic and ectopic endometrial glandular epithelial cells (EuECs and EECs) in endometriosis. Normal epithelial cells (NECs), EuECs and EECs were treated with fibroblast growth factor (FGF)2, FGF2 neutralizing antibody, mitogen-activated protein kinases (MAPKs) inhibitors U0126 and PD98059. FGF2 protein level was detected by enzyme-linked immunosorbent assay (ELISA). The expressions of FGF2, FGF receptor 1 (FGFR1), extracellular signal-regulated kinase (ERK)1/2/pERK1/2 and Sproutys (SPRYs) (Sprouty1, Sprouty2, Sprouty4) and dual specificity phosphatase 6 (DUSP6) were detected by Western blot. The mRNA levels of FGF2, FGFR1 (FGF receptor 1), SPRYs (Sprouty1, Sprouty2, Sprouty4) and DUSP6 mRNA were detected by RT-PCR. Among treatment groups, the content of FGF2 in EuECs and EECs was significantly higher than that in NECs (p < 0.05). The mRNA and protein levels of FGF2, FGFR1, SPRYs (Sprouty1, Sprouty2, Sprouty4) and DUSP6 in EuECs and EECs were increased after adding FGF2 (p < 0.05), but decreased after adding FGF2 neutralizing antibody, no significant change was found in NECs (p > 0.05). The inhibitory effect of PD9805 on NECs was not significantly different from that of U0126 (p > 0.05); however, the inhibitory effects of PD9805 on EuECs and EECs were significantly lower than those of U0126 (p< 0.05). The positive feedback loop existed in EuECs and EECs, but maybe not in NECs. The results may provide the guideline to treat endometriosis patients. Show less
no PDF DOI: 10.26355/eurrev_201803_14560
DUSP6

In a pilot study, reduced fatty acid desaturase 1 function was associated with nonalcoholic fatty liver disease and response to treatment in children.

Valerio Nobili, Anna Alisi, Zhipeng Liu +6 more · 2018 · Pediatric research · Nature · added 2026-04-24
FADS1 gene encodes delta 5 desaturase, a rate-limiting enzyme in the metabolism of n-3 and n-6 polyunsaturated fatty acids (PUFAs). Minor alleles of FADS1 locus polymorphisms are associated with reduc Show more
FADS1 gene encodes delta 5 desaturase, a rate-limiting enzyme in the metabolism of n-3 and n-6 polyunsaturated fatty acids (PUFAs). Minor alleles of FADS1 locus polymorphisms are associated with reduced FADS1 expression and intra-hepatic fat accumulation. However, the relationship between FADS1 expression and pediatric nonalcoholic fatty liver disease (NAFLD) risk remains to be explored. We analyzed FADS1 transcription levels and their association with intra-hepatic fat and histology in children, and we performed pathway enrichment analysis on transcriptomic profiles associated with FADS1 polymorphisms. We also evaluated the weight of FADS1 alleles on the response to combined docosahexaenoic acid, choline, and vitamin E (DHA-CHO-VE) treatment. FADS1 mRNA level was significantly and inversely associated with intra-hepatic fat (p = 0.004), degree of steatosis (p = 0.03), fibrosis (p = 0.05), and NASH (p = 0.008) among pediatric livers. Transcriptomics demonstrated a significant enrichment of a number of pathways strongly related to NAFLD (e.g., liver damage, fibrosis, and hepatic stellate cell activation). Compared to children who are common allele homozygotes, children with FADS1 minor alleles had a greater reduction in steatosis, fibrosis, and NAFLD activity score after DHA-CHO-VE. This study suggests that decreased FADS1 expression may be associated with NAFLD in children but an increased response to DHA-CHO-VE. Show less
📄 PDF DOI: 10.1038/s41390-018-0132-7
FADS1

Dual Specificity Phosphatase 6 Protects Neural Stem Cells from β-Amyloid-Induced Cytotoxicity through ERK1/2 Inactivation.

Wang Liao, Yuqiu Zheng, Wenli Fang +6 more · 2018 · Biomolecules · MDPI · added 2026-04-24
Alzheimer's disease (AD) is a devastating neurodegenerative disease with limited treatment options and no cure. Beta-amyloid (Aβ) is a hallmark of AD that has potent neurotoxicity in neural stem cells Show more
Alzheimer's disease (AD) is a devastating neurodegenerative disease with limited treatment options and no cure. Beta-amyloid (Aβ) is a hallmark of AD that has potent neurotoxicity in neural stem cells (NSCs). Dual specificity phosphatase 6 (DUSP6) is a member of the mitogen-activated protein kinases (MAPKs), which is involved in regulating various physiological and pathological processes. Whether DUSP6 has a protective effect on Aβ-induced NSC injury remains to be explored. C17.2 neural stem cells were transfected with DUSP6-overexpressed plasmid. NSCs with or without DUSP6 overexpression were administrated with Aβ25⁻35 at various concentrations (i.e., 0, 2.5, 5 μM). DUSP6 expression after Aβ treatment was detected by Real-Time Polymerase Chain Reaction (RT-PCR) and Western blot and cell vitality was examined by the CCK8 assay. The oxidative stress (intracellular reactive oxygen species (ROS) and malondialdehyde (MDA)), endoplasmic reticulum stress (ER calcium level) and mitochondrial dysfunction (cytochrome c homeostasis) were tested. The expression of Show less
📄 PDF DOI: 10.3390/biom8040181
DUSP6

Dual Inhibition of PIK3C3 and FGFR as a New Therapeutic Approach to Treat Bladder Cancer.

Chun-Han Chen, Chun A Changou, Tsung-Han Hsieh +9 more · 2018 · Clinical cancer research : an official journal of the American Association for Cancer Research · added 2026-04-24
no PDF DOI: 10.1158/1078-0432.CCR-17-2066
PIK3C3

Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis.

Jun-Juan Zheng, Wen-Xing Li, Jia-Qian Liu +5 more · 2018 · Medicine · added 2026-04-24
Alzheimer disease (AD) is a common neurodegenerative disorder with distinct pathological features, with aging considered the greatest risk factor. We explored how aging contributes to increased AD ris Show more
Alzheimer disease (AD) is a common neurodegenerative disorder with distinct pathological features, with aging considered the greatest risk factor. We explored how aging contributes to increased AD risk, and determined concurrent and coordinate changes (including genetic and phenotypic modifications) commonly exhibited in both normal aging and AD. Using the Gene Expression Omnibus (GEO) database, we collected 1 healthy aging-related and 3 AD-related datasets of the hippocampal region. The normal aging dataset was divided into 3 age groups: young (20-40 years old), middle-aged (40-60 years old), and elderly (>60 years old). These datasets were used to analyze the differentially expressed genes (DEGs). The Gene Ontology (GO) terms, pathways, and function network analysis of these DEGs were analyzed. One thousand two hundred ninety-one DEGs were found to be shared in the natural aging groups and AD patients. Among the shared DEGs, ATP6V1E1, GNG3, NDUFV2, GOT1, USP14, and NAV2 have been previously found in both normal aging individuals and AD patients. Furthermore, using Java Enrichment of Pathways Extended to Topology (JEPETTO) analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we determined that changes in aging-related KEGG annotations may contribute to the aging-dependence of AD risk. Interestingly, NRXN3, the second most commonly deregulated gene identified in the present study, is known to carry a mutation in AD patients. According to functional network analysis, NRXN3 plays a critical role in synaptic functions involved in the cognitive decline associated with normal aging and AD. Our results indicate that the low expression of aging-related NRXN3 may increase AD risk, though the potential mechanism requires further clarification. Show less
no PDF DOI: 10.1097/MD.0000000000011343
NRXN3

Catechin supplemented in a FOS diet induces weight loss by altering cecal microbiota and gene expression of colonic epithelial cells.

Jianming Luo, Lulu Han, Liu Liu +6 more · 2018 · Food & function · Royal Society of Chemistry · added 2026-04-24
Our previous study showed that catechin controlled rats' body weights and changed gut microbiota composition when supplemented into a high-fructo-oligosaccharide (FOS) diet. This experiment is devised Show more
Our previous study showed that catechin controlled rats' body weights and changed gut microbiota composition when supplemented into a high-fructo-oligosaccharide (FOS) diet. This experiment is devised to further confirm the relationship between specific bacteria in the colon and body weight gain, and to investigate how specific bacteria impact body weight by changing the expression of colonic epithelial cells. Forty obese rats were divided into four groups: three catechin-supplemented groups with a high-FOS diet (100, 400, and 700 mg kg-1 d-1 catechin, orally administered) and one group with a high-FOS diet only. Food consumption and body weights were recorded each week. After one month of treatment, rats' cecal content and colonic epithelial cells were individually collected and analyzed with MiSeq and gene expression profiling techniques, respectively. Results identified some specific bacteria at the genus level-including the increased Parabacteroides sp., Prevotella sp., Robinsoniella sp., [Ruminococcus], Phascolarctobacterium sp. and an unknown genus of YS2, and the decreased Lachnospira sp., Oscillospira sp., Ruminococcus sp., an unknown genus of Peptococcaceae and an unknown genus of Clostridiales in rats' cecum-and eight genes-including one downregulated Pla2g2a and seven upregulated genes: Apoa1, Apoa4, Aabr07073400.1, Fabp4, Pik3r5, Dgat2 and Ptgs2 of colonic epithelial cells-that were due to the consumption of catechin. Consequently, various biological functions in connection with energy metabolism in colonic epithelial cells were altered, including fat digestion and absorption and the regulation of lipolysis in adipocytes. In conclusion, catechin induces host weight loss by altering gut microbiota and gene expression and function in colonic epithelial cells. Show less
no PDF DOI: 10.1039/c8fo00035b
APOA4

PIK3C3/VPS34 control by acetylation.

Hua Su, Wei Liu · 2018 · Autophagy · Taylor & Francis · added 2026-04-24
PIK3C3/VPS34 (phosphatidylinositol 3-kinase catalytic subunit type 3) converts phosphatidylinositol (PtdIns) to phosphatidylinositol-3-phosphate (PtdIns3P), sustaining macroautophagy/autophagy and end Show more
PIK3C3/VPS34 (phosphatidylinositol 3-kinase catalytic subunit type 3) converts phosphatidylinositol (PtdIns) to phosphatidylinositol-3-phosphate (PtdIns3P), sustaining macroautophagy/autophagy and endosomal transport. So far, facilitating the assembly of the PIK3C3/VPS34-BECN1-PIK3R4/VPS15/p150 core complex at distinct membranes is the only known way to activate PIK3C3/VPS34 in cells. We have recently revealed a novel mechanism that regulates PIK3C3/VPS34 activation; cellular PIK3C3/VPS34 is repressed under nutrient-rich conditions by EP300/p300-mediated acetylation. Following nutrient-deprivation that drops EP300 activity, PIK3C3/VPS34 is liberated by deacetylation. Intriguingly, while deacetylation of the N-terminal K29 residue accounts for core complex formation, deacetylation at the C-terminal K771 site determines the binding of PIK3C3/VPS34 to its substrate PtdIns. In vitro and in cell evidence shows that EP300-dependent acetylation and deacetylation is a switch for turning off/on PIK3C3/VPS34 in which deacetylation of K771 is required for its full activation. This PIK3C3/VPS34 activation mechanism is utilized not only by starvation-induced autophagy but also by autophagy without the involvement of AMPK, MTORC1 or ULK1. These findings suggest an alternative circuit in cells for PIK3C3/VPS34 activation, which is involved in membrane transformations in response to metabolic and nonmetabolic cues. Show less
no PDF DOI: 10.1080/15548627.2017.1385676
PIK3C3

Shear stress promotes differentiation of stem cells from human exfoliated deciduous teeth into endothelial cells via the downstream pathway of VEGF-Notch signaling.

Penglai Wang, Shaoyue Zhu, Changyong Yuan +3 more · 2018 · International journal of molecular medicine · added 2026-04-24
Effects of shear stress on endotheliaxl differentiation of stem cells from human exfoliated deciduous teeth (SHEDs) were investigated. SHEDs were treated with shear stress, then reverse transcription- Show more
Effects of shear stress on endotheliaxl differentiation of stem cells from human exfoliated deciduous teeth (SHEDs) were investigated. SHEDs were treated with shear stress, then reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to analyse the mRNA expression of arterial markers and western blot analysis was performed to analyse protein expression of angiogenic markers. Additionally, in vitro matrigel angiogenesis assay was performed to evaluate vascular-like structure formation. The secreted protein expression levels of the vascular endothelial growth factor (VEGF) of SHEDs after shear stress was also quantified using corresponding ELISA kits. Untreated SHEDs seeded on Matrigel cannot form vessel-like structures at any time points, whereas groups treated with shear stress formed a few vessel-like structures at 4, 8 and 12 h. When SHEDs were treated with EphrinB2-siRNA for 24, the capability of vessel-like structure formation was suppressed. After being treated with shear stress, the expression of VEGF, VEGFR2, DLL4, Notch1, EphrinB2, Hey1 and Hey2 (arterial markers) gene expression was significantly upregulated, moreover, the protein levels of VEGFR2, EphrinB2, CD31, Notch1, DLL4, Hey1, and Hey2 were also significantly up-regulated. Both the mRNA and protein expression levels of EphB4 (venous marker) were downregulated. The average VEGF protein concentration in supernatants secreted by shear stress treated SHEDs groups increased significantly. In conclusion, shear stress was able to induce arterial endothelial differentiation of stem cells from human exfoliated deciduous teeth, and VEGF-DLL4/Notch‑EphrinB2 signaling was involved in this process. Show less
📄 PDF DOI: 10.3892/ijmm.2018.3761
HEY2

MicroRNA‑32 silences WWP2 expression to maintain the pluripotency of human amniotic epithelial stem cells and β islet‑like cell differentiation.

Gang Zou, Te Liu, Lihe Guo +3 more · 2018 · International journal of molecular medicine · added 2026-04-24
Human amniotic epithelial stem cells (HuAECs) exhibit pluripotent characteristics, which are similar to those of embryonic stem cells, and can differentiate into various adult tissues and cells throug Show more
Human amniotic epithelial stem cells (HuAECs) exhibit pluripotent characteristics, which are similar to those of embryonic stem cells, and can differentiate into various adult tissues and cells through directed induction. However, in culture, HuAECs tend to lose their pluripotency, and their directed differentiation capability declines with increasing passage number. The stem cell pluripotency factor octamer‑binding protein 4 (Oct4) is an important transcription factor that promotes stem cell self‑proliferation and maintains their pluripotency. Previous studies have demonstrated that WW domain containing E3 ubiquitin protein ligase 2 (WWP2) negatively regulates Oct4 expression and stem cell pluripotency. Therefore, the present study aimed to investigate the regulation of WWP2 by microRNAs (miRs), and to evaluate the expression of the downstream factor Oct4 and the maintenance of HuAEC pluripotency. Bioinformatics analysis identified a complementary binding site for miR‑32 in the 3'untranslated region of the WWP2 gene, thus suggesting that it may be a target gene of miR‑32. Post‑infection of HuAECs with a vector overexpressing miR‑32, the endogenous expression of WWP2 was significantly decreased, whereas Oct4 expression was significantly increased. Furthermore, miR‑32‑infected cells differentiated into β islet‑like cells by directed induction. The results indicated that after induction, HuAECs overexpressing miR‑32 also overexpressed the biomarkers of β islet‑like cells. In addition, the ability to secrete insulin was markedly enhanced in response to glucose stimulation, in cells overexpressing miR‑32. In conclusion, the present study suggested that miR‑32 may effectively inhibit WWP2 expression in HuAECs and promote Oct4 overexpression to maintain their pluripotency. Show less
no PDF DOI: 10.3892/ijmm.2018.3436
WWP2

Differentiated adipose-derived stem cell cocultures for bone regeneration in RADA16-I in vitro.

Huifang Yang, Nanrui Hong, Hsiaowei Liu +3 more · 2018 · Journal of cellular physiology · Wiley · added 2026-04-24
Craniofacial defects can cause morbidness. Adipose-derived stem cells (ADSCs) have shown great promise for osteogeneration and vascularization; therefore cocultures of differentiated ADSCs are explore Show more
Craniofacial defects can cause morbidness. Adipose-derived stem cells (ADSCs) have shown great promise for osteogeneration and vascularization; therefore cocultures of differentiated ADSCs are explored to increase bone and vessel formation. In this study, ADSCs were induced into osteogenic ADSCs (os-ADSCs) and endothelial ADSCs (endo-ADSCs) cells, which were then cocultured in variable proportions (os-ADSCs/endo-ADSCs = 2:1, 1:1, 1:2). The os-ADSCs in a ratio of 1:1 expressed more ALP, RUNX2 and COL-I, whereas VEGF, vWF and CD31 were upregulated in the endo-ADSCs of this group. Next generation RNA sequencing (RNA-seq) was performed to evaluate the molecular mechanisms of cocultured ADSCs. The os-ADSCs and endo-ADSCs interacted with each other during osteogenic and angiogenic differentiation, especially at the ratio of 1:1, and were regulated by vascular-related genes, cell-mediated genes, bone-related genes and the transforming growth factor β signaling pathway (TGF-β), mitogen-activated protein kinase signaling pathway (MAPK) and wnt signaling pathway (Wnt). Angptl4, apoe, mmp3, bmp6, mmp13 and fgf18 were detected to be up-regulated, and cxcl12 and wnt5a were down-regulated. The results showed that the gene expression levels were consistent with that in RNA-seq. The cells were then seeded into self-assembling peptide RADA16-I scaffolds as cocultures (1:1) and monocultures (ADSCs, os-ADSCs, endo-ADSCs). The results showed that the cells of all groups grew and proliferated well on the scaffolds, and the cocultured group exhibited better osteogeneration and vascularization. In conclusion, cocultured os-ADSCs and endo-ADSCs at the ratio of 1:1 showed strong osteogenic and angiogenic differentiation. There is a great potential for osteogenesis and vascularization by 3D culturing cells in a 1:1 ratio in self-assembling peptide RADA16-I scaffolds, which requires evaluation for bone regeneration in vivo. Show less
no PDF DOI: 10.1002/jcp.26838
ANGPTL4

The silencing of ApoC3 suppresses oxidative stress and inflammatory responses in placenta cells from mice with preeclampsia via inhibition of the NF-κB signaling pathway.

Fa-Hong Li, Yong Wang, Xiao-Ling Liu +1 more · 2018 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Preeclampsia is one of the three primary causes of maternal morbidity and mortality worldwide. This study evaluated ApoC3 in placenta cells of mice with preeclampsia to explore its therapeutic role in Show more
Preeclampsia is one of the three primary causes of maternal morbidity and mortality worldwide. This study evaluated ApoC3 in placenta cells of mice with preeclampsia to explore its therapeutic role in preeclampsia and assess its function on oxidative stress and inflammatory responses involving the NF-κB signaling pathway. A mouse model of preeclampsia was successfully established. APOC3-siRNA with the best silencing effect was screened out. The expression levels of ApoC3, p65, and IkBα were evaluated. The effect of ApoC3 silencing on metabolic activity and apoptosis was measured. The level of high-sensitivity C-reactive protein (hs-CPR), interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-α), the activity of matrix metalloproteinase (MMP)-2 and MMP-9, and the expression of malondialdehyde (MDA), 8-isoprostane and oxidized low-density lipoprotein (ox-LDL) were determined. ApoC3-siRNA-3 was the most effective siRNA. The mRNA expression of ApoC3 was scarcely observed, while the expression of p65 decreased and the expression of p-IkBα increased in the ApoC3-siRNA group. Compared with those in the model and empty vector groups, the cell apoptosis rate and the activities of invasion-related factors MMP-2 and MMP-9 increased, while the levels of hs-CPR, IL-6, TNF-α, MDA, 8-isoprostane, and ox-LDL decreased in the ApoC3-siRNA group. Silencing ApoC3 could suppress the NF-κB signaling pathway, thereby exercising a protective effect on cell injury induced by oxidative stress and reducing inflammatory responses. Show less
no PDF DOI: 10.1016/j.biopha.2018.08.122
APOC3

Profiling of G protein-coupled receptors in vagal afferents reveals novel gut-to-brain sensing mechanisms.

Kristoffer L Egerod, Natalia Petersen, Pascal N Timshel +5 more · 2018 · Molecular metabolism · Elsevier · added 2026-04-24
G protein-coupled receptors (GPCRs) act as transmembrane molecular sensors of neurotransmitters, hormones, nutrients, and metabolites. Because unmyelinated vagal afferents richly innervate the gastroi Show more
G protein-coupled receptors (GPCRs) act as transmembrane molecular sensors of neurotransmitters, hormones, nutrients, and metabolites. Because unmyelinated vagal afferents richly innervate the gastrointestinal mucosa, gut-derived molecules may directly modulate the activity of vagal afferents through GPCRs. However, the types of GPCRs expressed in vagal afferents are largely unknown. Here, we determined the expression profile of all GPCRs expressed in vagal afferents of the mouse, with a special emphasis on those innervating the gastrointestinal tract. Using a combination of high-throughput quantitative PCR, RNA sequencing, and in situ hybridization, we systematically quantified GPCRs expressed in vagal unmyelinated Na GPCRs for gut hormones that were the most enriched in Na Overall, this study provides a comprehensive description of GPCR-dependent sensing mechanisms in vagal afferents, including novel coexpression patterns, and conceivably coaction of key receptors for gut-derived molecules involved in gut-brain communication. Show less
📄 PDF DOI: 10.1016/j.molmet.2018.03.016
GIPR

Tetraspanin family identified as the central genes detected in gastric cancer using bioinformatics analysis.

Weiwei Qi, Libin Sun, Ning Liu +3 more · 2018 · Molecular medicine reports · added 2026-04-24
Gastric cancer has become a serious disease in the past decade. It has the second highest mortality rate among the four most common cancer types, leading to ~700,000 mortalities annually. Previous stu Show more
Gastric cancer has become a serious disease in the past decade. It has the second highest mortality rate among the four most common cancer types, leading to ~700,000 mortalities annually. Previous studies have attempted to elucidate the underlying biological mechanisms of gastric cancer. The present study aimed to obtain useful biomarkers and to improve the understanding of gastric cancer mechanisms at the genetic level. The present study used bioinformatics analysis to identify 1,829 differentially expressed genes (DEGs) which were obtained from the GSE54129 dataset. Using protein‑protein interaction information from the Search Tool for the Retrieval of Interacting Genes database, disease modules were constructed for gastric cancer using Cytoscape software. In the Gene Ontology analysis of biology processes, upregulated genes were significantly enriched in 'extracellular matrix organization', 'cell adhesion' and 'inflammatory response', whereas downregulated DEGs were significantly enriched in 'xenobiotic metabolic process', 'oxidation‑reduction process' and 'steroid metabolic process'. During Kyoto Encyclopedia of Genes and Genomes analysis, upregulated DEGs were significantly enriched in 'extracellular matrix‑receptor interaction', 'focal adhesion' and 'PI3K‑Akt signaling pathway', whereas the downregulated DEGs were significantly enriched in 'chemical carcinogenesis', 'metabolism of xenobiotics by cytochrome P450' and 'peroxisome'. The present study additionally identified 10 hub genes from the DEGs: Tumor protein p53 (TP53), C‑X‑C motif chemokine ligand 8 (CXCL8), tetraspanin 4 (TSPAN4), lysophosphatidic acid receptor 2 (LPAR2), adenylate cyclase 3 (ADCY3), phosphoinositide‑3‑kinase regulatory subunit 1 (PIK3R1), neuromedin U (NMU), C‑X‑C motif chemokine ligand (CXCL12), fos proto‑oncogene, AP‑1 transcription factor subunit (FOS) and sphingosine‑1‑phosphate receptor 1 (S1PR1), which have high degrees with other DEGs. The survival analysis revealed that the high expression of ADCY3, LPAR2, S1PR1, TP53 and TSPAN4 was associated with a lower survival rate, whereas high expression of CXCL8, FOS, NMU and PIK3R1 was associated with a higher survival rate. No significant association was identified between CXCL12 and survival rate. Additionally, TSPAN1 and TSPAN8 appeared in the top 100 DEGs. Finally, it was observed that 4 hub genes were highly expressed in gastric cancer tissue compared with para‑carcinoma tissue in the 12 patients; the increased TSPAN4 was significant (>5‑fold). Tetraspanin family genes may be novel biomarkers of gastric cancer. The findings of the present study may improve the understanding of the molecular mechanisms underlying the development of gastric cancer. Show less
📄 PDF DOI: 10.3892/mmr.2018.9360
ADCY3

Serum hepatokines in dairy cows: periparturient variation and changes in energy-related metabolic disorders.

Jianguo Wang, Xiaoyan Zhu, Guanghui She +5 more · 2018 · BMC veterinary research · BioMed Central · added 2026-04-24
During peripartum period, dairy cows are highly susceptible to energy metabolism disorders such as fatty liver and ketosis. Angiopoietin-like protein 4 (ANGPTL4) and fibroblast growth factor 21 (FGF21 Show more
During peripartum period, dairy cows are highly susceptible to energy metabolism disorders such as fatty liver and ketosis. Angiopoietin-like protein 4 (ANGPTL4) and fibroblast growth factor 21 (FGF21), known as hepatokines, play important roles in lipid metabolism. The purposes of our study were to evaluate variations of serum ANGPTL4 and FGF21 concentrations in periparturient dairy cows and changes in these serum analyte concentrations of energy-related metabolic disorders in early lactation dairy cows. This study was divided into two experiments. Experiment I: Blood parameters were measured in healthy periparturient Holstein cows from 4 wk antepartum to 4 wk postpartum (n = 219). In this experiment, weekly blood samples were obtained from 4 wk before the expected calving date through 4 wk after calving. Experiment II: Blood parameters were measured in healthy cows (n = 30) and cows with clinical ketosis (n = 29) and fatty liver (n = 25) within the first 4 wk of lactation. In the present study, all blood samples were collected from the coccygeal vein in the early morning before feeding. Serum ANGPTL4 and FGF21 concentrations peaked at parturition, and declined rapidly over the following 2 wk Serum ANGPTL4 and FGF21 concentrations were positively correlated with serum non-esterified fatty acids (NEFA) concentration (r = 0.856, P = 003; r = 0.848, P = 0.004, respectively). Cows with clinical ketosis and fatty liver had significantly higher serum ANGPTL4 and FGF21 concentrations than healthy cows (P < 0.01). Serum ANGPTL4 and FGF21 concentrations were elevated during peripartum period, suggesting that energy balance changes that were associated with parturition contributed significantly to these effects. Although FGF21 and ANGPTL4 could play important roles in the adaptation of energy metabolism, they may be involved in the pathological processes of energy metabolism disorders of dairy cows in the peripartum period. Show less
📄 PDF DOI: 10.1186/s12917-018-1560-7
ANGPTL4

Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program.

Derek Klarin, Scott M Damrauer, Kelly Cho +46 more · 2018 · Nature genetics · Nature · added 2026-04-24
The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 Show more
The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease). Show less
📄 PDF DOI: 10.1038/s41588-018-0222-9
ANGPTL4

Evaluation of candidate genes associated with hepatitis A and E virus infection in Chinese Han population.

Maolin Gu, Jing Qiu, Daoxia Guo +4 more · 2018 · Virology journal · BioMed Central · added 2026-04-24
Recent GWAS-associated studies reported that single nucleotide polymorphisms (SNPs) in ABCB1, TGFβ1, XRCC1 genes were associated with hepatitis A virus (HAV) infection, and variants of APOA4 and APOE Show more
Recent GWAS-associated studies reported that single nucleotide polymorphisms (SNPs) in ABCB1, TGFβ1, XRCC1 genes were associated with hepatitis A virus (HAV) infection, and variants of APOA4 and APOE genes were associated with and hepatitis E virus (HEV) infection in US population. However, the associations of these loci with HAV or HEV infection in Chinese Han population remain unclear. A total of 3082 Chinese Han persons were included in this study. Anti-HAV IgG and anti-HEV IgG were detected by enzyme-linked immunosorbent assay (ELISA). Genotypes in ABCB1, TGFβ1, XRCC1, APOA4 and APOE SNPs were determined by TaqMan MGB technology. In Chinese Han population, rs1045642 C to T variation in ABCB1 was significantly associated with the decreased risk of HAV infection (P < 0.05). However, the effect direction was different with the previous US study. Rs1001581 A to G variation in XRCC1, which was not identified in US population, was significantly associated with the protection against HAV infection in our samples (P < 0.05). In addition, our results suggested that rs7412 C to T variation in APOE was significantly associated with lower risk of HEV infection in males (adjusted OR < 1.0, P < 0.05) but not in females. ABCB1 and XRCC1 genes variants are significantly associated with the protection against HAV infection. Additionally, Chinese Han males with rs7412 C to T variation in APOE gene are less prone to be infected by HEV. Show less
📄 PDF DOI: 10.1186/s12985-018-0962-2
APOA4

Habitual aerobic exercise, gene APOA5 named rs662799 SNP and response of blood lipid and lipoprotein phenotypes among older Chinese adult.

Xiangyun Liu, Guoyuan Huang, Zhanbin Niu +2 more · 2018 · Experimental gerontology · Elsevier · added 2026-04-24
The genetic component of dyslipidemia has been studied in adults but little in older population. It is remains unknown regarding influence and interaction of APOA5 gene single nucleotide polymorphism Show more
The genetic component of dyslipidemia has been studied in adults but little in older population. It is remains unknown regarding influence and interaction of APOA5 gene single nucleotide polymorphism (SNP) and habitual aerobic exercise (HAE) on changes of blood lipids and lipoprotein phenotypes in older Chinese adults. Four-hundred-twenty-three old Chinese individuals with HAE were divided into hyperlipidemia and normal groups. We genotyped polymorphic loci using matrix assisted laser desorption ionization time of flight mass spectrometry detection technology (MALDI-TOF). HAE level was assessed by International Physical Activity Questionnaire (IPAQ) scale. For three genotypes of rs662799 site, the AG + GG gene carriers presented higher risk of hyperlipidemia compared to the AA carriers, with the ratio of 1.676 (P = .018, 95% CI: 1.092-2.571) for the AG and 1.812 (P = .002, 95% CI: 1.247-2.632) for the GG, respectively. The rs662799 G allele was significantly associated with lower HDL-C but higher TG levels. In relation to different HAE levels, less interaction was observed between the AA carriers and different HAE levels on corresponding lipids changes. The AG + GG carriers with higher HAE levels had significantly lower TG responses compared to those with lower HAE levels (1.45 ± 0.74 mmol/L vs. 1.86 ± 1.15 mmol/L). Excess risk for low HDL-C and hyperlipidemia was associated with rs662799 genotype alleles of APOA5 SNPs in older Chinese adults. Interaction of gene-HAE and HAE levels may induce different responses of blood lipids and lipoprotein phenotypes. HAE levels have less influence on TG changes in the AA carriers; however, high HAE levels appeared to greatly impact TG responses in the AG + GG carriers. Show less
no PDF DOI: 10.1016/j.exger.2018.05.007
APOA5

Association of rs662799 in APOA5 with CAD in Chinese Han population.

Hua Chen, Shifang Ding, Mi Zhou +4 more · 2018 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24
CAD (Coronary Artery Disease) is a complex disease that influenced by various environmental and genetic factors. Previous studies have found many single nucleotide polymorphisms (SNPs) associated with Show more
CAD (Coronary Artery Disease) is a complex disease that influenced by various environmental and genetic factors. Previous studies have found many single nucleotide polymorphisms (SNPs) associated with the risk of CAD occurrence. However, the results are inconsistent. In this study, we aim to investigate genetic etiology in Chinese Han population by analysis of 7 SNPs in lipid metabolism pathway that previously has been reported to be associated with CAD. A total of 631 samples were used in this study, including 435 CAD cases and 196 normal healthy controls. SNP genotyping were conducted via multiplex PCR amplifying followed by NGS (next-generation sequencing). Rs662799 in APOA5 (Apolipoprotein A5) gene was associated with CAD in Chinese Han population (Odds-ratio = 1.374, P-value = 0.03). No significant association was observed between the rest of SNPs and CAD. Stratified association analysis revealed rs5882 was associated with CAD in non-hypertension group (Odds-ratio = 1.593, P-value = 0.023). Rs1800588 was associated with CAD in smoking group (Odds-ratio = 1.603, P-value = 0.035). The minor allele of rs662799 was the risk factor of CAD occurrences in Chinese Han population. Show less
📄 PDF DOI: 10.1186/s12872-017-0735-7
APOA5

In Silico Preliminary Association of Ammonia Metabolism Genes GLS, CPS1, and GLUL with Risk of Alzheimer's Disease, Major Depressive Disorder, and Type 2 Diabetes.

Jeddidiah W D Griffin, Ying Liu, Patrick C Bradshaw +1 more · 2018 · Journal of molecular neuroscience : MN · Springer · added 2026-04-24
Ammonia is a toxic by-product of protein catabolism and is involved in changes in glutamate metabolism. Therefore, ammonia metabolism genes may link a range of diseases involving glutamate signaling s Show more
Ammonia is a toxic by-product of protein catabolism and is involved in changes in glutamate metabolism. Therefore, ammonia metabolism genes may link a range of diseases involving glutamate signaling such as Alzheimer's disease (AD), major depressive disorder (MDD), and type 2 diabetes (T2D). We analyzed data from a National Institute on Aging study with a family-based design to determine if 45 single nucleotide polymorphisms (SNPs) in glutaminase (GLS), carbamoyl phosphate synthetase 1 (CPS1), or glutamate-ammonia ligase (GLUL) genes were associated with AD, MDD, or T2D using PLINK software. HAPLOVIEW software was used to calculate linkage disequilibrium measures for the SNPs. Next, we analyzed the associated variations for potential effects on transcriptional control sites to identify possible functional effects of the SNPs. Of the SNPs that passed the quality control tests, four SNPs in the GLS gene were significantly associated with AD, two SNPs in the GLS gene were associated with T2D, and one SNP in the GLUL gene and three SNPs in the CPS1 gene were associated with MDD before Bonferroni correction. The in silico bioinformatic analysis suggested probable functional roles for six associated SNPs. Glutamate signaling pathways have been implicated in all these diseases, and other studies have detected similar brain pathologies such as cortical thinning in AD, MDD, and T2D. Taken together, these data potentially link GLS with AD, GLS with T2D, and CPS1 and GLUL with MDD and stimulate the generation of testable hypotheses that may help explain the molecular basis of pathologies shared by these disorders. Show less
no PDF DOI: 10.1007/s12031-018-1035-0
CPS1

The E3 ligases Itch and WWP2 cooperate to limit T

Daisuke Aki, Hui Li, Wen Zhang +5 more · 2018 · Nature immunology · Nature · added 2026-04-24
The mechanisms by which the sensitivity of naive CD4
no PDF DOI: 10.1038/s41590-018-0137-8
WWP2

Fish Oil Supplementation Alleviates the Altered Lipid Homeostasis in Blood, Liver, and Adipose Tissues in High-Fat Diet-Fed Rats.

Chen-Yuan Chiu, Lou-Pin Wang, Shing-Hwa Liu +1 more · 2018 · Journal of agricultural and food chemistry · ACS Publications · added 2026-04-24
This study investigated the effects of dietary supplementation of fish oil on the signals of lipid metabolism involved in hepatic cholesterol and triglyceride influx and excretion in high-fat diet (HF Show more
This study investigated the effects of dietary supplementation of fish oil on the signals of lipid metabolism involved in hepatic cholesterol and triglyceride influx and excretion in high-fat diet (HFD)-fed rats. Fish oil (FO) repressed body (HFD, 533 ± 18.2 g; HFD+FO, 488 ± 28.0 g, p < 0.05) and liver weights (HFD, 5.7 ± 0.6 g/100 g of body weight; HFD+FO, 4.8 ± 0.4 g/100 g of body weight, p < 0.05) in HFD-fed rats. Fish oil could also improve HFD-induced imbalance of lipid metabolism in blood, liver, and adipose tissues including the significant decreases in plasma and liver total cholesterol (TC) (plasma-HFD, 113 ± 33.6 mg/dL; HFD+FO, 50.0 ± 5.95 mg/dL, p < 0.05; liver-HFD, 102 ± 13.0 mg/g liver; [corrected] HFD+FO, 86.6 ± 7.81 mg/g liver, [corrected] p < 0.05), blood, liver, and adipose triglyceride (TG) (blood-HFD, 52.5 ± 20.4 mg/dL; HFD+FO, 29.8 ± 4.30 mg/dL, p < 0.05; liver-HFD, 56.2 ± 10.0 mg/g liver; [corrected] HFD+FO, 30.3 ± 5.28 mg/g liver, [corrected] p < 0.05; adipose-HFD, 614 ± 73.2 mg/g liver, [corrected] HFD+FO, 409 ± 334 mg/g of adipose tissue, [corrected] p < 0.05), and low density (HFD, 79.8 ± 40.9 mg/dL; HFD+FO, 16.6 ± 5.47 mg/dL, p < 0.05) and very-low-density (HFD, 49.7 ± 33.3 mg/dL; HFD+FO, 10.4 ± 3.45 mg/dL, p < 0.05) lipoprotein and the significant increases in fecal TC (HFD, 12.2 ± 0.67 mg/g feces; [corrected] HFD+FO, 16.3 ± 2.04 mg/g feces, [corrected] < 0.05) and TG (HFD, 2.09 ± 0.10 mg/g feces; [corrected] HFD+FO, 2.38 ± 0.22 mg/g feces, [corrected] p < 0.05) and lipoprotein lipase activity of adipose tissues (HFD, 16.6 ± 3.64 μM p-nitrophenol; HFD+FO, 24.5 ± 4.19 μM p-nitrophenol, p < 0.05). Moreover, fish oil significantly activated the protein expressions of hepatic lipid metabolism regulators (AMPKα and PPARα) and significantly regulated the lipid-transport-related signaling molecules (ApoE, MTTP, ApoB, Angptl4, ApoCIII, ACOX1, and SREBPF1) in blood or liver of HFD-fed rats. These results suggest that fish oil supplementation improves HFD-induced imbalance of lipid homeostasis in blood, liver, and adipose tissues in rats. Show less
no PDF DOI: 10.1021/acs.jafc.8b00529
ANGPTL4

Efatutazone and T0901317 exert synergistically therapeutic effects in acquired gefitinib-resistant lung adenocarcinoma cells.

Jie Ni, Lei-Lei Zhou, Li Ding +9 more · 2018 · Cancer medicine · Wiley · added 2026-04-24
The development of acquired EGFR-TKI therapeutic resistance is still a serious clinical problem in the management of lung adenocarcinoma. Peroxisome proliferator activated receptor gamma (PPARγ) agoni Show more
The development of acquired EGFR-TKI therapeutic resistance is still a serious clinical problem in the management of lung adenocarcinoma. Peroxisome proliferator activated receptor gamma (PPARγ) agonists may exhibit anti-tumor activity by transactivating genes which are closely associated with cell proliferation, apoptosis, and differentiation. However, it remains not clear whether efatutazone has similar roles in lung adenocarcinoma cells of gefitinib resistant such as HCC827-GR and PC9-GR. It has been demonstrated by us that efatutazone prominently increased the mRNA and protein expression of PPARγ, liver X receptor alpha (LXRα),as well as ATP binding cassette subfamily A member 1 (ABCA1). In the presence of GW9662 (a specific antagonist of PPARγ) or GGPP (a specific antagonist of LXRα), efatutazone (40 μmol/L) restored the proliferation of both HCC827-GR and PC9-GR cells and obviously inhibited the increased protein and mRNA expression of PPAR-gamma, LXR-alpha, and ABCA1 induced by efatutazone. LXRα knockdown by siRNA (si-LXRα) significantly promoted the HCC827-GR and PC9-GR cells proliferation, whereas incubation efatutazone with si-LXRα restored the proliferation ability compared with the control group. In addition, combination of efatutazone and LXRα agonist T0901317 showed a synergistic therapeutic effect on lung adenocarcinoma cell proliferation and PPAR gamma, LXR A and ABCA1 protein expression. These results indicate that efatutazone could inhibit the cells proliferation of HCC827-GR and PC9-GR through PPARγ/LXRα/ABCA1 pathway, and synergistic therapeutic effect is achieved when combined with T0901317. Show less
no PDF DOI: 10.1002/cam4.1440
NR1H3