👤 Yuanxing Liu

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
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, Xiaowei 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, 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

Panoramic view of common fusion genes in a large cohort of Chinese de novo acute myeloid leukemia patients.

Xue Chen, Fang Wang, Yang Zhang +9 more · 2019 · Leukemia & lymphoma · Taylor & Francis · added 2026-04-24
Fusion genes are major molecular biological abnormalities in hematological malignancies. This study aimed to depict the common recurrent gene-fusion landscape in acute myeloid leukemia (AML). 3135 de Show more
Fusion genes are major molecular biological abnormalities in hematological malignancies. This study aimed to depict the common recurrent gene-fusion landscape in acute myeloid leukemia (AML). 3135 de novo AML cases were enrolled and 36 recurrent fusion genes were assessed using multiplex-nested RT-PCR. Twenty-three distinct fusion genes were detected in 1292 (41.21%) cases. The incidence of fusion genes was higher in pediatric AML than in adult cases. The pediatric patients had higher incidences of RUNX1-RUNX1T1, KMT2A-MLLT3, KMT2A-MLLT10, KMT2A-MLLT11, KMT2A-MLLT6, and FUS-ERG, whereas KMT2A-PTD was more common in adult patients. The occurrence of molecular abnormalities involving the KMT2A gene and CBFB-MYH11 was lower in Chinese pediatric AML compared to Western reports. The incidence of RUNX1-RUNX1T1 was higher in both pediatric and adult patients in our study than in Western countries. This study provides a genetic landscape of common fusion genes in Chinese AML and confirms different incidences between age groups and races. Show less
no PDF DOI: 10.1080/10428194.2018.1516876
MLLT10

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

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

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

IL6 blockade potentiates the anti-tumor effects of γ-secretase inhibitors in Notch3-expressing breast cancer.

Dong Wang, Jiahui Xu, Bingjie Liu +11 more · 2018 · Cell death and differentiation · Nature · added 2026-04-24
Notch pathways have important roles in carcinogenesis including pathways involving the Notch1 and Notch2 oncogenes. Pan-Notch inhibitors, such as gamma secretase inhibitors (GSIs), have been used in t Show more
Notch pathways have important roles in carcinogenesis including pathways involving the Notch1 and Notch2 oncogenes. Pan-Notch inhibitors, such as gamma secretase inhibitors (GSIs), have been used in the clinical trials, but the outcomes of these trials have been insufficient and have yielded unclear. In the present study, we demonstrated that GSIs, such as MK-0752 and RO4929097, inhibit breast tumor growth, but increase the breast cancer stem cell (BCSC) population in Notch3-expressing breast cancer cells, in a process that is coupled with IL6 induction and is blocked by the IL6R antagonist Tocilizumab (TCZ). IL6 induction results from inhibition of Notch3-Hey2 signaling through MK-0752. Furthermore, HIF1α upregulates Notch3 expression via direct binding to the Notch3 promoter and subsequently downregulates BCSCs by decreasing the IL6 levels in Notch3-expressing breast cancer cells. Utilizing both breast cancer cell line xenografts and patient-derived xenografts (PDX), we showed that the combination of MK-0752 and Tocilizumab significantly decreases BCSCs and inhibits tumor growth and thus might serve as a novel therapeutic strategy for treating women with Notch3-expressing breast cancers. Show less
no PDF DOI: 10.1038/cdd.2017.162
HEY2

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

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

microRNA-137 promotes endothelial progenitor cell proliferation and angiogenesis in cerebral ischemic stroke mice by targeting NR4A2 through the Notch pathway.

Xing-Li Liu, Gang Wang, Wei Song +3 more · 2018 · Journal of cellular physiology · Wiley · added 2026-04-24
Cerebral ischemic stroke (CIS) is one of the common causes of death and disability worldwide. This study aims to investigate effect of miR-137 on endothelial progenitor cells and angiogenesis in CIS b Show more
Cerebral ischemic stroke (CIS) is one of the common causes of death and disability worldwide. This study aims to investigate effect of miR-137 on endothelial progenitor cells and angiogenesis in CIS by targeting NR4A2 via the Notch pathway. Brain tissues were extracted from CIS and normal mice. Immunohistochemistry was used to determine positive rate of NR4A2 expression. Serum VEGF, Ang, HGF, and IκBα levels were determined by ELISA. RT-qPCR and Western blotting were used to determine expression of related factors. Endothelial progenitor cells in CIS mice were treated and grouped into blank, NC, miR-137 mimic, miR-137 inhibitor, siRNA-NR4A2, and miR-137 inhibitor + siRNA-NR4A2 groups, and cells in normal mice into normal group. Proliferation and apoptosis were determined by MTT and flow cytometry, respectively. NR4A2 protein expression was strongly positive in CIS mice, which showed higher serum levels of VEGF, Ang, and HGF but lower IκBα than normal mice. Compared with normal group, the rest groups (endothelial progenitor cells from CIS mice) showed decreased expressions of miR-137, Hes1, Hes5, and IκBα but elevated NR4A2, Notch, Jagged1, Hey-2, VEGF, Ang, and HGF, inhibited proliferation and enhanced apoptosis. Compared with blank and NC groups, the miR-137 mimic and siRNA-NR4A2 groups exhibited increased expression of miR-137, Hes1, Hes5, and IκBα, but decreased NR4A2, Notch, Jagged1, and Hey-2, with enhanced proliferation and attenuated apoptosis. The miR-137 inhibitor group reversed the conditions. miR-137 enhances the endothelial progenitor cell proliferation and angiogenesis in CIS mice by targeting NR4A2 through the Notch signaling pathway. Show less
no PDF DOI: 10.1002/jcp.26312
HEY2

Intensive genetic analysis for Chinese patients with very high triglyceride levels: Relations of mutations to triglyceride levels and acute pancreatitis.

Jing-Lu Jin, Di Sun, Ye-Xuan Cao +9 more · 2018 · EBioMedicine · Elsevier · added 2026-04-24
Severe hypertriglyceridemia (SHTG, TG ≥5·65 mmol/L), a disease, usually resulting from a combination of genetic and environmental factors, may increase the risk of acute pancreatitis (AP). However, pr Show more
Severe hypertriglyceridemia (SHTG, TG ≥5·65 mmol/L), a disease, usually resulting from a combination of genetic and environmental factors, may increase the risk of acute pancreatitis (AP). However, previous genetic analysis has been limited by lacking of related observation of gene to AP. The expanding genetic sequencing including 15 TG-related genes (LPL, LMF1, APOC2, GPIHBP1, GCKR, ANGPTL3, APOB, APOA1-A4-C3-A5, TRIB1, CETP, APOE, and LIPI) was performed within 103 patients who were diagnosed with primary SHTG and 46 age- and sex-matched normal controls. Rare variants were found in 46 patients and 12 controls. The detection rate of rare variants in SHTG group increased by 19·5% via intensive genetic analysis. Presence of rare variants in LPL, APOA5, five LPL molecular regulating genes and all the sequenced genes were found to be associated with SHTG (p < 0·05). Of noted, patients with history of AP presented higher frequency of rare variants in LPL gene and all the LPL molecular regulating genes (27·8% vs.4·7% and 50·0% vs. 20·0%). The risk scores for SHTG determined by common TG-associated variants were increased in subgroups according to the extent of SHTG when they were compared with that of controls. Finally, patients without rare variants within SHTG group also presented higher risk scores than control group (p < 0·05). Expanding genetic analysis had a higher detection rate of rare variants in patients with SHTG. Rare variants in LPL and its molecular regulating genes could increase the risk of AP among Chinese patients with SHTG. FUND: This work was partially supported by the Capital Health Development Fund (201614035) and CAMS. Major Collaborative Innovation Project (2016-I2M-1-011) awarded to Dr. Jian-Jun Li, MD, PhD. Show less
📄 PDF DOI: 10.1016/j.ebiom.2018.11.001
APOA5

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

Apolipoprotein A-IV enhances cholecystokinnin secretion.

Jesse Zhan, Jonathan Weng, Brian G Hunt +3 more · 2018 · Physiology & behavior · Elsevier · added 2026-04-24
Cholecystokinin (CCK) and apolipoprotein A-IV (ApoA-IV) are gastrointestinal peptides that play an important role in controlling energy homeostasis. Lymphatic ApoA-IV and plasma CCK secretion are medi Show more
Cholecystokinin (CCK) and apolipoprotein A-IV (ApoA-IV) are gastrointestinal peptides that play an important role in controlling energy homeostasis. Lymphatic ApoA-IV and plasma CCK secretion are mediated via a chylomicron formation-dependent pathway during a dietary lipid infusion. Given their similar roles as satiating proteins, the present study examines how the two peptides interact in their function. Specifically, this study sought to understand how ApoA-IV regulates CCK secretion. For this purpose, Cck gene expression in the small intestines of ApoA-IV knockout (ApoA-IV-KO) and wild-type (WT) mice were compared under an array of feeding conditions. When fed with a chow or high-fat diet (HFD), basal levels of Cck transcripts were significantly reduced in the duodenum of ApoA-IV-KO mice compared to WT mice. Furthermore, after an oral gavage of a lipid mixture, Cck gene expression in the duodenum was significantly reduced in ApoA-IV-KO mice relative to the change seen in WT mice. To determine the mechanism by which ApoA-IV modulates Cck gene expression, STC-1 cells were transfected with predesigned mouse lysophosphatidic acid receptor 5 (LPAR5) small interfering RNA (siRNA) to knockdown Lpar5 gene expression. In this in-vitro study, mouse recombinant ApoA-IV protein increased Cck gene expression in enteroendocrine STC-1 cells and stimulated CCK release from the STC-1 cells. However, the levels of CCK protein and Cck expression were attenuated when Lpar5 was knocked down in the STC-1 cells. Together these observations suggest that dietary lipid-induced ApoA-IV is associated with Cck synthesis in the duodenum and that ApoA-IV protein directly enhances CCK release through the activation of a LPAR5-dependent pathway. Show less
📄 PDF DOI: 10.1016/j.physbeh.2018.01.019
APOA4

Genome-wide analysis reveals that altered methylation in specific CpG loci is associated with childhood obesity.

Yun Li, Yahui Zhou, Lijun Zhu +9 more · 2018 · Journal of cellular biochemistry · Wiley · added 2026-04-24
Over the past decades, the epidemic of childhood obesity has greatly increased, and it has recently become a global public health concern. Methylation, serving as a crucial regulator of the gene-envir Show more
Over the past decades, the epidemic of childhood obesity has greatly increased, and it has recently become a global public health concern. Methylation, serving as a crucial regulator of the gene-environment interaction, has exhibited a strong association with obesity. In this study, we aimed to evaluate the relationship between DNA methylation and childhood obesity, and further uncover the potential association of aberrantly methylated genes with obesity. DNA samples of peripheral blood leukocytes from three obese subjects (mean BMI: 21.67) and 4 age/sex matched controls (mean BMI: 14.92) were subjected to Infinium Human Methylation 450 Bead Array analysis. A total of more than 4 85 000 methylation sites were identified across the genome, and 226 methylated CpGs (DMCpGs) were differentially methylated between these two groups. Subsequent Gene Ontology (GO) and KEGG Pathway analyses showed that these DMCpGs were mainly engaged in immunity and lipoprotein metabolism, indicating their physiological significance. Further verification of the candidate CpG sites within the HDAC4, RAX2, APOA5, CES1, and SLC25A20 gene loci, were performed using bisulfite sequencing PCR (BSP) in a cohort of 42 controls and 39 obese cases. The results revealed that methylation levels within HDAC4 and RAX2 loci were positively associated with obesity, while the methylation levels of loci within APOA5 and CES1 loci were negatively correlated with obesity. Thus, alterations in methylation of CpG sites of specific genes may contribute to childhood obesity, which provide novel insights into the aetiology of obesity. Show less
no PDF DOI: 10.1002/jcb.27059
APOA5

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Valérie Turcot, Yingchang Lu, Heather M Highland +408 more · 2018 · Nature genetics · Nature · added 2026-04-24
Valérie Turcot, Yingchang Lu, Heather M Highland, Claudia Schurmann, Anne E Justice, Rebecca S Fine, Jonathan P Bradfield, Tõnu Esko, Ayush Giri, Mariaelisa Graff, Xiuqing Guo, Audrey E Hendricks, Tugce Karaderi, Adelheid Lempradl, Adam E Locke, Anubha Mahajan, Eirini Marouli, Suthesh Sivapalaratnam, Kristin L Young, Tamuno Alfred, Mary F Feitosa, Nicholas G D Masca, Alisa K Manning, Carolina Medina-Gomez, Poorva Mudgal, Maggie C Y Ng, Alex P Reiner, Sailaja Vedantam, Sara M Willems, Thomas W Winkler, Gonçalo Abecasis, Katja K Aben, Dewan S Alam, Sameer E Alharthi, Matthew Allison, Philippe Amouyel, Folkert W Asselbergs, Paul L Auer, Beverley Balkau, Lia E Bang, Inês Barroso, Lisa Bastarache, Marianne Benn, Sven Bergmann, Lawrence F Bielak, Matthias Blüher, Michael Boehnke, Heiner Boeing, Eric Boerwinkle, Carsten A Böger, Jette Bork-Jensen, Michiel L Bots, Erwin P Bottinger, Donald W Bowden, Ivan Brandslund, Gerome Breen, Murray H Brilliant, Linda Broer, Marco Brumat, Amber A Burt, Adam S Butterworth, Peter T Campbell, Stefania Cappellani, David J Carey, Eulalia Catamo, Mark J Caulfield, John C Chambers, Daniel I Chasman, Yii-Der I Chen, Rajiv Chowdhury, Cramer Christensen, Audrey Y Chu, Massimiliano Cocca, Francis S Collins, James P Cook, Janie Corley, Jordi Corominas Galbany, Amanda J Cox, David S Crosslin, Gabriel Cuellar-Partida, Angela D'Eustacchio, John Danesh, Gail Davies, Paul I W Bakker, Mark C H Groot, Renée Mutsert, Ian J Deary, George Dedoussis, Ellen W Demerath, Martin Heijer, Anneke I Hollander, Hester M Ruijter, Joe G Dennis, Josh C Denny, Emanuele Di Angelantonio, Fotios Drenos, Mengmeng Du, Marie-Pierre Dubé, Alison M Dunning, Douglas F Easton, Todd L Edwards, David Ellinghaus, Patrick T Ellinor, Paul Elliott, Evangelos Evangelou, Aliki-Eleni Farmaki, I Sadaf Farooqi, Jessica D Faul, Sascha Fauser, Shuang Feng, Ele Ferrannini, Jean Ferrieres, Jose C Florez, Ian Ford, Myriam Fornage, Oscar H Franco, Andre Franke, Paul W Franks, Nele Friedrich, Ruth Frikke-Schmidt, Tessel E Galesloot, Wei Gan, Ilaria Gandin, Paolo Gasparini, Jane Gibson, Vilmantas Giedraitis, Anette P Gjesing, Penny Gordon-Larsen, Mathias Gorski, Hans-Jörgen Grabe, Struan F A Grant, Niels Grarup, Helen L Griffiths, Megan L Grove, Vilmundur Gudnason, Stefan Gustafsson, Jeff Haessler, Hakon Hakonarson, Anke R Hammerschlag, Torben Hansen, Kathleen Mullan Harris, Tamara B Harris, Andrew T Hattersley, Christian T Have, Caroline Hayward, Liang He, Nancy L Heard-Costa, Andrew C Heath, Iris M Heid, Øyvind Helgeland, Jussi Hernesniemi, Alex W Hewitt, Oddgeir L Holmen, G Kees Hovingh, Joanna M M Howson, Yao Hu, Paul L Huang, Jennifer E Huffman, M Arfan Ikram, Erik Ingelsson, Anne U Jackson, Jan-Håkan Jansson, Gail P Jarvik, Gorm B Jensen, Yucheng Jia, Stefan Johansson, Marit E Jørgensen, Torben Jørgensen, J Wouter Jukema, Bratati Kahali, René S Kahn, Mika Kähönen, Pia R Kamstrup, Stavroula Kanoni, Jaakko Kaprio, Maria Karaleftheri, Sharon L R Kardia, Fredrik Karpe, Sekar Kathiresan, Frank Kee, Lambertus A Kiemeney, Eric Kim, Hidetoshi Kitajima, Pirjo Komulainen, Jaspal S Kooner, Charles Kooperberg, Tellervo Korhonen, Peter Kovacs, Helena Kuivaniemi, Zoltán Kutalik, Kari Kuulasmaa, Johanna Kuusisto, Markku Laakso, Timo A Lakka, David Lamparter, Ethan M Lange, Leslie A Lange, Claudia Langenberg, Eric B Larson, Nanette R Lee, Terho Lehtimäki, Cora E Lewis, Huaixing Li, Jin Li, Ruifang Li-Gao, Honghuang Lin, Keng-Hung Lin, Li-An Lin, Xu Lin, Lars Lind, Jaana Lindström, Allan Linneberg, Ching-Ti Liu, Dajiang J Liu, Yongmei Liu, Ken S Lo, Artitaya Lophatananon, Andrew J Lotery, Anu Loukola, Jian'an Luan, Steven A Lubitz, Leo-Pekka Lyytikäinen, Satu Männistö, Gaëlle Marenne, Angela L Mazul, Mark I McCarthy, Roberta McKean-Cowdin, Sarah E Medland, Karina Meidtner, Lili Milani, Vanisha Mistry, Paul Mitchell, Karen L Mohlke, Leena Moilanen, Marie Moitry, Grant W Montgomery, Dennis O Mook-Kanamori, Carmel Moore, Trevor A Mori, Andrew D Morris, Andrew P Morris, Martina Müller-Nurasyid, Patricia B Munroe, Mike A Nalls, Narisu Narisu, Christopher P Nelson, Matt Neville, Sune F Nielsen, Kjell Nikus, Pål R Njølstad, Børge G Nordestgaard, Dale R Nyholt, Jeffrey R O'Connel, Michelle L O'Donoghue, Loes M Olde Loohuis, Roel A Ophoff, Katharine R Owen, Chris J Packard, Sandosh Padmanabhan, Colin N A Palmer, Nicholette D Palmer, Gerard Pasterkamp, Aniruddh P Patel, Alison Pattie, Oluf Pedersen, Peggy L Peissig, Gina M Peloso, Craig E Pennell, Markus Perola, James A Perry, John R B Perry, Tune H Pers, Thomas N Person, Annette Peters, Eva R B Petersen, Patricia A Peyser, Ailith Pirie, Ozren Polasek, Tinca J Polderman, Hannu Puolijoki, Olli T Raitakari, Asif Rasheed, Rainer Rauramaa, Dermot F Reilly, Frida Renström, Myriam Rheinberger, Paul M Ridker, John D Rioux, Manuel A Rivas, David J Roberts, Neil R Robertson, Antonietta Robino, Olov Rolandsson, Igor Rudan, Katherine S Ruth, Danish Saleheen, Veikko Salomaa, Nilesh J Samani, Yadav Sapkota, Naveed Sattar, Robert E Schoen, Pamela J Schreiner, Matthias B Schulze, Robert A Scott, Marcelo P Segura-Lepe, Svati H Shah, Wayne H-H Sheu, Xueling Sim, Andrew J Slater, Kerrin S Small, Albert V Smith, Lorraine Southam, Timothy D Spector, Elizabeth K Speliotes, John M Starr, Kari Stefansson, Valgerdur Steinthorsdottir, Kathleen E Stirrups, Konstantin Strauch, Heather M Stringham, Michael Stumvoll, Liang Sun, Praveen Surendran, Amy J Swift, Hayato Tada, Katherine E Tansey, Jean-Claude Tardif, Kent D Taylor, Alexander Teumer, Deborah J Thompson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Betina H Thuesen, Anke Tönjes, Gerard Tromp, Stella Trompet, Emmanouil Tsafantakis, Jaakko Tuomilehto, Anne Tybjaerg-Hansen, Jonathan P Tyrer, Rudolf Uher, André G Uitterlinden, Matti Uusitupa, Sander W Laan, Cornelia M Duijn, Nienke Leeuwen, Jessica van Setten, Mauno Vanhala, Anette Varbo, Tibor V Varga, Rohit Varma, Digna R Velez Edwards, Sita H Vermeulen, Giovanni Veronesi, Henrik Vestergaard, Veronique Vitart, Thomas F Vogt, Uwe Völker, Dragana Vuckovic, Lynne E Wagenknecht, Mark Walker, Lars Wallentin, Feijie Wang, Carol A Wang, Shuai Wang, Yiqin Wang, Erin B Ware, Nicholas J Wareham, Helen R Warren, Dawn M Waterworth, Jennifer Wessel, Harvey D White, Cristen J Willer, James G Wilson, Daniel R Witte, Andrew R Wood, Ying Wu, Hanieh Yaghootkar, Jie Yao, Pang Yao, Laura M Yerges-Armstrong, Robin Young, Eleftheria Zeggini, Xiaowei Zhan, Weihua Zhang, Jing Hua Zhao, Wei Zhao, Wei Zhou, Krina T Zondervan, CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Understanding Society Scientific Group, Jerome I Rotter, John A Pospisilik, Fernando Rivadeneira, Ingrid B Borecki, Panos Deloukas, Timothy M Frayling, Guillaume Lettre, Kari E North, Cecilia M Lindgren, Joel N Hirschhorn, Ruth J F Loos Show less
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding var Show more
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity. Show less
📄 PDF DOI: 10.1038/s41588-017-0011-x
GIPR

Transcriptome analysis reveals the molecular mechanism of hepatic fat metabolism disorder caused by Muscovy duck reovirus infection.

Quanxi Wang, Mengxi Liu, Lihui Xu +2 more · 2018 · Avian pathology : journal of the W.V.P.A · Taylor & Francis · added 2026-04-24
The aim of this work was to clarify the molecular mechanism underlying the fatty degeneration of livers infected with Muscovy duck reovirus (MDRV), which produces obvious white necrotic foci in the li Show more
The aim of this work was to clarify the molecular mechanism underlying the fatty degeneration of livers infected with Muscovy duck reovirus (MDRV), which produces obvious white necrotic foci in the liver. Transcriptome data for MDRV-infected Muscovy duck livers and control livers were sequenced, assembled, and annotated with Illumina ABC: ATP binding cassette transport; ACADVL: acyl-CoA dehydrogenase, very long chain; ACAT: mitochondrial-like acetyl-CoA acetyltransferase A; ACAT2: acetyl-CoA acyltransferase 2; ACNAT2: acyl-coenzyme A amino acid N-acyltransferase 2-like; ACOT1: acyl-CoA thioesterase 1; ACOT7: acyl-CoA thioesterase 7; ACOX1: acyl-CoA oxidase 1, palmitoyl; ACSBG2: acyl-CoA synthetase bubblegum family member 2; ACSL1: acyl-CoA synthetase long-chain family member 1; ADH1: alcohol dehydrogenase 1; APOA4: apolipoprotein A-IV; ARV: avian reovirus; cDNA: complementary deoxyribonucleic acid; COG: Clusters of Orthologous Groups; DEG: differentially expressed gene; DGAT: diacylgycerol acyltransferase; DNA: deoxyribonucleic acid; ECI2: enoyl-CoA delta isomerase 2; EHHADH: enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase; FDR: false discovery rate; GCDH: Pseudopodoces humilis glutaryl-CoA dehydrogenase; GO: Gene Ontology; HADHA: hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase (trifunctional protein), alpha subunit; I-FABP: intestinal fatty acid binding protein; KEGG: Kyoto Encyclopedia of Genes and Genomes; L-FABP: liver fatty acid binding protein; MDRV: Muscovy duck reovirus; MOI: multiplicity of infection; NPC1L1: Niemann-Pick C1-like 1; qPCR: real-time quantitative polymerase chain reaction; RNA: ribonucleic acid; RNase: ribonuclease; RNA-seq: RNA sequencing technology; RPKM: reads per kilobase per million mapped reads; SR-B1: scavenger receptor class b type 1. Show less
no PDF DOI: 10.1080/03079457.2017.1380294
APOA4

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

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

Chromatin-remodeling factor OsINO80 is involved in regulation of gibberellin biosynthesis and is crucial for rice plant growth and development.

Chao Li, Yuhao Liu, Wen-Hui Shen +2 more · 2018 · Journal of integrative plant biology · Blackwell Publishing · added 2026-04-24
The phytohormone gibberellin (GA) plays essential roles in plant growth and development. Here, we report that OsINO80, a conserved ATP-dependent chromatin-remodeling factor in rice (Oryza sativa), fun Show more
The phytohormone gibberellin (GA) plays essential roles in plant growth and development. Here, we report that OsINO80, a conserved ATP-dependent chromatin-remodeling factor in rice (Oryza sativa), functions in both GA biosynthesis and diverse biological processes. OsINO80-knockdown mutants, derived from either T-DNA insertion or RNA interference, display typical GA-deficient phenotypes, including dwarfism, reduced cell length, late flowering, retarded seed germination and impaired reproductive development. Consistently, transcriptome analyses reveal that OsINO80 knockdown results in downregulation by more than two-fold of over 1,000 genes, including the GA biosynthesis genes CPS1 and GA3ox2, and the dwarf phenotype of OsINO80-knockdown mutants can be rescued by the application of exogenous GA3. Chromatin immunoprecipitation (ChIP) experiments show that OsINO80 directly binds to the chromatin of CPS1 and GA3ox2 loci. Biochemical assays establish that OsINO80 specially interacts with histone variant H2A.Z and the H2A.Z enrichments at CPS1 and GA3ox2 are decreased in OsINO80-knockdown mutants. Thus, our study identified a rice chromatin-remodeling factor, OsINO80, and demonstrated that OsINO80 is involved in regulation of the GA biosynthesis pathway and plays critical functions for many aspects of rice plant growth and development. Show less
no PDF DOI: 10.1111/jipb.12603
CPS1

Adipose-Derived Exosomes Exert Proatherogenic Effects by Regulating Macrophage Foam Cell Formation and Polarization.

Zulong Xie, Xuedong Wang, Xinxin Liu +8 more · 2018 · Journal of the American Heart Association · added 2026-04-24
Obesity is causally associated with atherosclerosis, and adipose tissue (AT)-derived exosomes may be implicated in the metabolic complications of obesity. However, the precise role of AT-exosomes in a Show more
Obesity is causally associated with atherosclerosis, and adipose tissue (AT)-derived exosomes may be implicated in the metabolic complications of obesity. However, the precise role of AT-exosomes in atherogenesis remains unclear. We herein aimed to assess the effect of AT-exosomes on macrophage foam cell formation and polarization and subsequent atherosclerosis development. Four types of exosomes isolated from the supernatants of ex vivo subcutaneous AT and visceral AT (VAT) explants that were derived from wild-type mice and high-fat diet (HFD)-induced obese mice were effectively taken up by RAW264.7 macrophages. Both treatment with wild-type VAT exosomes and HFD-VAT exosomes, but not subcutaneous AT exosomes, markedly facilitated macrophage foam cell generation through the downregulation of ATP-binding cassette transporter (ABCA1 and ABCG1)-mediated cholesterol efflux. Decreased expression of liver X receptor-α was also observed. Among the 4 types of exosomes, only HFD-VAT exosomes significantly induced M1 phenotype transition and proinflammatory cytokine (tumor necrosis factor α and interleukin 6) secretion in RAW264.7 macrophages, which was accompanied by increased phosphorylation of NF-κB-p65 but not the cellular expression of NF-κB-p65 or IκB-α. Furthermore, systematic intravenous injection of HFD-VAT exosomes profoundly exacerbated atherosclerosis in hyperlipidemic apolipoprotein E-deficient mice, as indicated by the M1 marker (CD16/32 and inducible nitric oxide synthase)-positive areas and the Oil Red O/Sudan IV-stained area, without affecting the plasma lipid profile and body weight. This study demonstrated a proatherosclerotic role for HFD-VAT exosomes, which is exerted by regulating macrophage foam cell formation and polarization, indicating a novel link between AT and atherosclerosis in the context of obesity. Show less
no PDF DOI: 10.1161/JAHA.117.007442
NR1H3

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

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

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

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

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

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

Apolipoprotein A-IV binds αIIbβ3 integrin and inhibits thrombosis.

Xiaohong Ruby Xu, Yiming Wang, Reheman Adili +34 more · 2018 · Nature communications · Nature · added 2026-04-24
Platelet αIIbβ3 integrin and its ligands are essential for thrombosis and hemostasis, and play key roles in myocardial infarction and stroke. Here we show that apolipoprotein A-IV (apoA-IV) can be iso Show more
Platelet αIIbβ3 integrin and its ligands are essential for thrombosis and hemostasis, and play key roles in myocardial infarction and stroke. Here we show that apolipoprotein A-IV (apoA-IV) can be isolated from human blood plasma using platelet β3 integrin-coated beads. Binding of apoA-IV to platelets requires activation of αIIbβ3 integrin, and the direct apoA-IV-αIIbβ3 interaction can be detected using a single-molecule Biomembrane Force Probe. We identify that aspartic acids 5 and 13 at the N-terminus of apoA-IV are required for binding to αIIbβ3 integrin, which is additionally modulated by apoA-IV C-terminus via intra-molecular interactions. ApoA-IV inhibits platelet aggregation and postprandial platelet hyperactivity. Human apoA-IV plasma levels show a circadian rhythm that negatively correlates with platelet aggregation and cardiovascular events. Thus, we identify apoA-IV as a novel ligand of αIIbβ3 integrin and an endogenous inhibitor of thrombosis, establishing a link between lipoprotein metabolism and cardiovascular diseases. Show less
📄 PDF DOI: 10.1038/s41467-018-05806-0
APOA4

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

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

The G-quadruplex (G4) resolvase DHX36 efficiently and specifically disrupts DNA G4s via a translocation-based helicase mechanism.

Philip M Yangyuoru, Devin A Bradburn, Zhonghua Liu +2 more · 2018 · The Journal of biological chemistry · American Society for Biochemistry and Molecular Biology · added 2026-04-24
Single-stranded DNA (ssDNA) and RNA regions that include at least four closely spaced runs of three or more consecutive guanosines strongly tend to fold into stable G-quadruplexes (G4s). G4s play key Show more
Single-stranded DNA (ssDNA) and RNA regions that include at least four closely spaced runs of three or more consecutive guanosines strongly tend to fold into stable G-quadruplexes (G4s). G4s play key roles as DNA regulatory sites and as kinetic traps that can inhibit biological processes, but how G4s are regulated in cells remains largely unknown. Here, we developed a kinetic framework for G4 disruption by DEAH-box helicase 36 (DHX36), the dominant G4 resolvase in human cells. Using tetramolecular DNA and RNA G4s with four to six G-quartets, we found that DHX36-mediated disruption is highly efficient, with rates that depend on G4 length under saturating conditions ( Show less
no PDF DOI: 10.1074/jbc.M117.815076
DHX36

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