👤 Tianjia Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, 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, Yuanxing Liu, Yuanying Liu, Yuanyuan Liu, Yubin Liu, Yuchen Liu, Yue Liu, Yuecheng Liu, Yuefang Liu, Yuehong Liu, Yueli Liu, Yueping Liu, Yuetong Liu, Yuexi Liu, Yuexin Liu, Yuexing Liu, Yueyang Liu, Yueyun Liu, Yufan Liu, Yufei Liu, Yufeng Liu, Yuhao Liu, Yuhe Liu, Yujia Liu, Yujiang Liu, Yujie Liu, Yujun Liu, Yulan Liu, Yuling Liu, Yulong Liu, Yumei Liu, Yumiao Liu, Yun Liu, Yun-Cai Liu, Yun-Qiang Liu, Yun-Ru Liu, Yun-Zi Liu, Yunfen Liu, Yunfeng Liu, Yuning Liu, Yunjie Liu, Yunlong Liu, Yunqi Liu, Yunqiang Liu, Yuntao Liu, Yunuan Liu, Yunuo Liu, Yunxia Liu, Yunyun Liu, Yuping Liu, Yupu Liu, Yuqi Liu, Yuqiang Liu, Yuqing Liu, Yurong Liu, Yuru Liu, Yusen Liu, Yutao Liu, Yutian Liu, Yuting Liu, Yutong Liu, Yuwei Liu, Yuxi Liu, Yuxia Liu, Yuxiang Liu, Yuxin Liu, Yuxuan Liu, Yuyan Liu, Yuyi Liu, Yuyu Liu, Yuyuan Liu, Yuzhen Liu, Yv-Xuan Liu, Z H Liu, Z Q Liu, Z Z Liu, Zaiqiang Liu, Zan Liu, Zaoqu Liu, Ze Liu, Zefeng Liu, Zekun Liu, Zeming Liu, Zengfu Liu, Zeyu Liu, Zezhou Liu, Zhangyu Liu, Zhangyuan Liu, Zhansheng Liu, Zhao Liu, Zhaoguo Liu, Zhaoli Liu, Zhaorui Liu, Zhaotian Liu, Zhaoxiang Liu, Zhaoxun Liu, Zhaoyang Liu, Zhe Liu, Zhekai Liu, Zheliang Liu, Zhen Liu, Zhen-Lin Liu, Zhendong Liu, Zhenfang Liu, Zhenfeng Liu, Zheng Liu, Zheng-Hong Liu, Zheng-Yu Liu, ZhengYi Liu, Zhengbing Liu, Zhengchuang Liu, Zhengdong Liu, Zhenghao Liu, Zhengkun Liu, Zhengtang Liu, Zhengting Liu, Zhenguo Liu, Zhengxia Liu, Zhengye Liu, Zhenhai Liu, Zhenhao Liu, Zhenhua Liu, Zhenjiang Liu, Zhenjiao Liu, Zhenjie Liu, Zhenkui Liu, Zhenlei Liu, Zhenmi Liu, Zhenming Liu, Zhenna Liu, Zhenqian Liu, Zhenqiu Liu, Zhenwei Liu, Zhenxing Liu, Zhenxiu Liu, Zhenzhen Liu, Zhenzhu Liu, Zhi Liu, Zhi Y Liu, Zhi-Fen Liu, Zhi-Guo Liu, Zhi-Jie Liu, Zhi-Kai Liu, Zhi-Ping Liu, Zhi-Ren Liu, Zhi-Wen Liu, Zhi-Ying Liu, Zhicheng Liu, Zhifang Liu, Zhigang Liu, Zhiguo Liu, Zhihan Liu, Zhihao Liu, Zhihong Liu, Zhihua Liu, Zhihui Liu, Zhijia Liu, Zhijie Liu, Zhikui Liu, Zhili Liu, Zhiming Liu, Zhipeng Liu, Zhiping Liu, Zhiqian Liu, Zhiqiang Liu, Zhiru Liu, Zhirui Liu, Zhishuo Liu, Zhitao Liu, Zhiteng Liu, Zhiwei Liu, Zhixiang Liu, Zhixue Liu, Zhiyan Liu, Zhiying Liu, Zhiyong Liu, Zhiyuan Liu, Zhong Liu, Zhong Wu Liu, Zhong-Hua Liu, Zhong-Min Liu, Zhong-Qiu Liu, Zhong-Wu Liu, Zhong-Ying Liu, Zhongchun Liu, Zhongguo Liu, Zhonghua Liu, Zhongjian Liu, Zhongjuan Liu, Zhongmin Liu, Zhongqi Liu, Zhongqiu Liu, Zhongwei Liu, Zhongyu Liu, Zhongyue Liu, Zhongzhong Liu, Zhou Liu, Zhou-di Liu, Zhu Liu, Zhuangjun Liu, Zhuanhua Liu, Zhuo Liu, Zhuoyuan Liu, Zi Hao Liu, Zi-Hao Liu, Zi-Lun Liu, Zi-Ye Liu, Zi-wen Liu, Zichuan Liu, Zihang Liu, Zihao Liu, Zihe Liu, Ziheng Liu, Zijia Liu, Zijian Liu, Zijing J Liu, Zimeng Liu, Ziqian Liu, Ziqin Liu, Ziteng Liu, Zitian Liu, Ziwei Liu, Zixi Liu, Zixuan Liu, Ziyang Liu, Ziying Liu, Ziyou Liu, Ziyuan Liu, Ziyue Liu, Zong-Chao Liu, Zong-Yuan Liu, Zonghua Liu, Zongjun Liu, Zongtao Liu, Zongxiang Liu, Zu-Guo Liu, Zuguo Liu, Zuohua Liu, Zuojin Liu, Zuolu Liu, Zuyi Liu, Zuyun Liu
articles

The long noncoding RNA LINC00483 promotes lung adenocarcinoma progression by sponging miR-204-3p.

Shengzhuang Yang, Tao Liu, Yu Sun +1 more · 2019 · Cellular & molecular biology letters · BioMed Central · added 2026-04-24
The expression of the long noncoding RNA LINC00483 is upregulated in lung adenocarcinoma (LUAD). However, its role in the progression of LUAD and the underlying mechanisms remain elusive. The expressi Show more
The expression of the long noncoding RNA LINC00483 is upregulated in lung adenocarcinoma (LUAD). However, its role in the progression of LUAD and the underlying mechanisms remain elusive. The expressions of LINC00483 and miR-204-3p were determined using quantitative real-time PCR. The correlation between the clinicopathological characteristics of LUAD patients and LINC00483 expression was analyzed using Pearson's χ LINC00483 was upregulated in LUAD tissues and cell lines. Higher LINC00483 levels closely correlated to shorter survival times, advanced TNM stage, larger tumor size and positive lymph node metastasis. Cell proliferation, migration and invasion were suppressed after LINC00483 knockdown. LINC00483 mainly localized in the cytoplasm, where it acted as a sponge of miR-204-3p. ETS1 was validated as a downstream target of miR-204-3p and is thus regulated by LINC00483. This study demonstrated that LINC00483 facilitates the proliferation, migration and invasion of LUAD cells by acting as a sponge for miR-204-3p, which in turn regulates ETS1. Show less
no PDF DOI: 10.1186/s11658-019-0192-7
SNAI1

Obesity-associated inflammation promotes angiogenesis and breast cancer via angiopoietin-like 4.

Ryan Kolb, Paige Kluz, Zhen Wei Tan +17 more · 2019 · Oncogene · Nature · added 2026-04-24
Obesity is a risk factor for breast cancer and also predicts poor clinical outcomes regardless of menopausal status. Contributing to the poor clinical outcomes is the suboptimal efficacy of standard t Show more
Obesity is a risk factor for breast cancer and also predicts poor clinical outcomes regardless of menopausal status. Contributing to the poor clinical outcomes is the suboptimal efficacy of standard therapies due to dose limiting toxicities and obesity-related complications, highlighting the need to develop novel therapeutic approaches for treating obese patients. We recently found that obesity leads to an increase in tumor-infiltrating macrophages with activated NLRC4 inflammasome and increased interleukin (IL)-1β production. IL-1β, in turn, leads to increased angiogenesis and cancer progression. Using Next Generation RNA sequencing, we identified an NLRC4/IL-1β-dependent upregulation of angiopoietin-like 4 (ANGPTL4), a known angiogenic factor in cancer, in tumors from obese mice. ANGPTL4-deficiency by genetic knockout or treatment with a neutralizing antibody led to a significant reduction in obesity-induced angiogenesis and tumor growth. At a mechanistic level, ANGPTL4 expression is induced by IL-1β from primary adipocytes in a manner dependent on NF-κB- and MAP kinase-activation, which is further enhanced by hypoxia. This report shows that adipocyte-derived ANGPTL4 drives disease progression under obese conditions and is a potential therapeutic target for treating obese breast cancer patients. Show less
📄 PDF DOI: 10.1038/s41388-018-0592-6
ANGPTL4

Mixed dysprosium-lanthanide nitride clusterfullerenes DyM

C Schlesier, F Liu, V Dubrovin +4 more · 2019 · Nanoscale · Royal Society of Chemistry · added 2026-04-24
Systematic exploration of the synthesis of mixed-metal Dy-M nitride clusterfullerenes (NCFs, M = Gd, Er, Tm, Lu) is performed, and the impact of the second metal on the relative yield is evaluated. We Show more
Systematic exploration of the synthesis of mixed-metal Dy-M nitride clusterfullerenes (NCFs, M = Gd, Er, Tm, Lu) is performed, and the impact of the second metal on the relative yield is evaluated. We demonstrate that the ionic radius of the metal appears to be the main factor allowing explanation of the relative yields in Dy-M mixed-metal systems with M = Sc, Lu, Er, and Gd. At the same time, Dy-Tm NCFs show anomalously low yields, which is not consistent with the relatively small ionic radius of Tm Show less
no PDF DOI: 10.1039/c9nr03593a
DYM

A multi-lock inhibitory mechanism for fine-tuning enzyme activities of the HECT family E3 ligases.

Zhen Wang, Ziheng Liu, Xing Chen +7 more · 2019 · Nature communications · Nature · added 2026-04-24
HECT E3 ligases control the degradation and functioning of numerous oncogenic/tumor-suppressive factors and signaling proteins, and their activities must be tightly regulated to prevent cancers and ot Show more
HECT E3 ligases control the degradation and functioning of numerous oncogenic/tumor-suppressive factors and signaling proteins, and their activities must be tightly regulated to prevent cancers and other diseases. Here we show that the Nedd4 family HECT E3 WWP1 adopts an autoinhibited state, in which its multiple WW domains sequester HECT using a multi-lock mechanism. Removing WW2 or WW34 led to a partial activation of WWP1. The structure of fully inhibited WWP1 reveals that many WWP1 mutations identified in cancer patients result in a partially active state with increased E3 ligase activity, and the WWP1 mutants likely promote cell migration by enhancement of ∆Np63α degradation. We further demonstrate that WWP2 and Itch utilize a highly similar multi-lock autoinhibition mechanism as that utilized by WWP1, whereas Nedd4/4 L and Smurf2 utilize a slightly variant version. Overall, these results reveal versatile autoinhibitory mechanisms that fine-tune the ligase activities of the HECT family enzymes. Show less
no PDF DOI: 10.1038/s41467-019-11224-7
WWP2

Variation in the Promoter Region of the

Girmay Shishay, Guiqiong Liu, Xunping Jiang +5 more · 2019 · International journal of molecular sciences · MDPI · added 2026-04-24
The
📄 PDF DOI: 10.3390/ijms20020240
MC4R

MACF1 links Rapsyn to microtubule- and actin-binding proteins to maintain neuromuscular synapses.

Julien Oury, Yun Liu, Ana Töpf +7 more · 2019 · The Journal of cell biology · added 2026-04-24
Complex mechanisms are required to form neuromuscular synapses, direct their subsequent maturation, and maintain the synapse throughout life. Transcriptional and post-translational pathways play impor Show more
Complex mechanisms are required to form neuromuscular synapses, direct their subsequent maturation, and maintain the synapse throughout life. Transcriptional and post-translational pathways play important roles in synaptic differentiation and direct the accumulation of the neurotransmitter receptors, acetylcholine receptors (AChRs), to the postsynaptic membrane, ensuring for reliable synaptic transmission. Rapsyn, an intracellular peripheral membrane protein that binds AChRs, is essential for synaptic differentiation, but how Rapsyn acts is poorly understood. We screened for proteins that coisolate with AChRs in a Rapsyn-dependent manner and show that microtubule actin cross linking factor 1 (MACF1), a scaffolding protein with binding sites for microtubules (MT) and actin, is concentrated at neuromuscular synapses, where it binds Rapsyn and serves as a synaptic organizer for MT-associated proteins, EB1 and MAP1b, and the actin-associated protein, Vinculin. MACF1 plays an important role in maintaining synaptic differentiation and efficient synaptic transmission in mice, and variants in Show less
📄 PDF DOI: 10.1083/jcb.201810023
MACF1

Identification of the miRNA-mRNA regulatory network of antler growth centers.

Baojin Yao, Mei Zhang, Meixin Liu +5 more · 2019 · Journal of biosciences · added 2026-04-24
Antler growth is a unique event compared to other growth and development processes in mammals. Antlers grow extremely fast during the rapid growth stage when growth rate peaks at 2 cm per day. Antler Show more
Antler growth is a unique event compared to other growth and development processes in mammals. Antlers grow extremely fast during the rapid growth stage when growth rate peaks at 2 cm per day. Antler growth is driven by a specific endochondral ossification process in the growth center that is in the distal region of the antler tip. In this study, we used state-of-art RNA-seq technology to analyze the expression profiles of mRNAs and miRNAs during antler growth. Our results indicated that the expression levels of multiple genes involved in chondrogenesis and endochondral ossification, including Show less
no PDF
WWP2

Mutations of

Lulu Kang, Yi Liu, Ying Jin +5 more · 2019 · Frontiers in neurology · Frontiers · added 2026-04-24
As a member of spectraplakin family of cytoskeletal crosslinking proteins, microtubule-actin crosslinking factor 1 (MACF1) controls cytoskeleton network dynamics. Knockout of
📄 PDF DOI: 10.3389/fneur.2019.01335
MACF1

Xiaoyaosan Ameliorates Chronic Immobilization Stress-Induced Depression-Like Behaviors and Anorexia in Rats: The Role of the Nesfatin-1-Oxytocin-Proopiomelanocortin Neural Pathway in the Hypothalamus.

Qingyu Ma, Xiaojuan Li, Zhiyi Yan +6 more · 2019 · Frontiers in psychiatry · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fpsyt.2019.00910
MC4R

Whole-genome resequencing from bulked-segregant analysis reveals gene set based association analyses for the Vibrio anguillarum resistance of turbot (Scophthalmus maximus).

Kai Zhang, Miao Han, Yuxiang Liu +6 more · 2019 · Fish & shellfish immunology · Elsevier · added 2026-04-24
Many achievements have been made to develop quantitative trait loci (QTLs) and gene-associated single nucleotide polymorphisms (SNPs) to facilitate practical marker-assisted selection (MAS) in aquatic Show more
Many achievements have been made to develop quantitative trait loci (QTLs) and gene-associated single nucleotide polymorphisms (SNPs) to facilitate practical marker-assisted selection (MAS) in aquatic animals. However, the systematic studies of SNPs associated with extreme threshold traits were poor in populations lacking of parental genomic information. Coupling next generation sequencing with bulked segregant analysis (BSA) should allow identification of numerous associated SNPs with extreme phenotypes. In the present study, using combination of SNP frequency difference and Euclidean distance, we conducted linkage analysis of SNPs located in genes involved in immune responses, and identified markers associated with Vibrio anguillarum resistance in turbot (Scophthalmus maximus). A total of 221 SNPs was found as candidate SNPs between resistant and susceptible individuals. Among these SNPs, 35 loci located in immune related genes were genotyped in verification population and 7 of them showed significant association with V. anguillarum resistance in both alleles and genotypes (P < 0.05). Among these 7 genes, PIK3CA-like, CYLD, VCAM1, RhoB and RhoGEF are involved in PI3K/Akt/mTOR pathway and NF-κB pathway, which influence the efficiency of bacteria entering the host and inflammation. SNP-SNP interaction analysis was performed by generalized multifactor dimensionality reduction (GMDR). The combination of SNP loci in RhoB, PIK3CA-like and ADCY3 showed a significant effect on V. anguillarum resistance with the verification rate in the sequencing population up to 70.8%. Taken all, our findings demonstrated the feasibility of BSA-seq approach in identifying genes responsible for the extreme phenotypes and will aid in performing MAS in turbot. Show less
no PDF DOI: 10.1016/j.fsi.2019.02.041
ADCY3

Circulating proteomic panels for diagnosis and risk stratification of acute-on-chronic liver failure in patients with viral hepatitis B.

Zeyu Sun, Xiaoli Liu, Daxian Wu +10 more · 2019 · Theranostics · added 2026-04-24
Chronic HBV infection (CHB) can lead to acute-on-chronic liver failure (HBV-ACLF) characterized by high mortality. This study aimed to reveal ACLF-related proteomic alterations, from which protein bas Show more
Chronic HBV infection (CHB) can lead to acute-on-chronic liver failure (HBV-ACLF) characterized by high mortality. This study aimed to reveal ACLF-related proteomic alterations, from which protein based diagnostic and prognostic scores for HBV-ACLF were developed. Show less
📄 PDF DOI: 10.7150/thno.31991
APOC3

miR-192-5p Silencing by Genetic Aberrations Is a Key Event in Hepatocellular Carcinomas with Cancer Stem Cell Features.

Yuanzhuo Gu, Xiyang Wei, Yulin Sun +12 more · 2019 · Cancer research · added 2026-04-24
Various cancer stem cell (CSC) biomarkers have been identified for hepatocellular carcinoma (HCC), but little is known about the implications of heterogeneity and shared molecular networks within the Show more
Various cancer stem cell (CSC) biomarkers have been identified for hepatocellular carcinoma (HCC), but little is known about the implications of heterogeneity and shared molecular networks within the CSC population. Through miRNA profile analysis in an HCC cohort ( Show less
no PDF DOI: 10.1158/0008-5472.CAN-18-1675
PABPC4

Genetic variants in ELOVL2 and HSD17B12 predict melanoma-specific survival.

Wei Dai, Hongliang Liu, Xinyuan Xu +10 more · 2019 · International journal of cancer · Wiley · added 2026-04-24
Fatty acids play a key role in cellular bioenergetics, membrane biosynthesis and intracellular signaling processes and thus may be involved in cancer development and progression. In the present study, Show more
Fatty acids play a key role in cellular bioenergetics, membrane biosynthesis and intracellular signaling processes and thus may be involved in cancer development and progression. In the present study, we comprehensively assessed associations of 14,522 common single-nucleotide polymorphisms (SNPs) in 149 genes of the fatty-acid synthesis pathway with cutaneous melanoma disease-specific survival (CMSS). The dataset of 858 cutaneous melanoma (CM) patients from a published genome-wide association study (GWAS) by The University of Texas M.D. Anderson Cancer Center was used as the discovery dataset, and the identified significant SNPs were validated by a dataset of 409 CM patients from another GWAS from the Nurses' Health and Health Professionals Follow-up Studies. We found 40 noteworthy SNPs to be associated with CMSS in both discovery and validation datasets after multiple comparison correction by the false positive report probability method, because more than 85% of the SNPs were imputed. By performing functional prediction, linkage disequilibrium analysis, and stepwise Cox regression selection, we identified two independent SNPs of ELOVL2 rs3734398 T>C and HSD17B12 rs11037684 A>G that predicted CMSS, with an allelic hazards ratio of 0.66 (95% confidence interval = 0.51-0.84 and p = 8.34 × 10 Show less
📄 PDF DOI: 10.1002/ijc.32194
HSD17B12

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

MicroRNA-1181 supports the growth of hepatocellular carcinoma by repressing AXIN1.

Zewen Song, Zhaomei Yu, Limin Chen +3 more · 2019 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Micro-RNAs regulate multiple biological behaviors of cancers, making them potential targets of new cancer therapies. MiR-1181 has been demonstrated to perform oncogenic or tumor-suppressing function i Show more
Micro-RNAs regulate multiple biological behaviors of cancers, making them potential targets of new cancer therapies. MiR-1181 has been demonstrated to perform oncogenic or tumor-suppressing function in a tissue-dependent way, but its role in hepatocellular carcinoma (HCC) was unclear. Here, we showed that miR-1181 was significantly overexpressed in HCC tissues when compared with tumor-adjacent normal ones or normal liver tissues from donated organ, and that inhibition of miR-1181 could repress the growth of HCC cells. Through bioinformatics analysis and luciferase reporter assays, we found that axis inhibition protein 1 (AXIN1) was a direct target of miR-1181, and the expression of AXIN1 showed a negative correlation with that of miR-1181 in HCC. Therefore, these data indicated an oncogenic function of miRNA-1181 in the development of HCC and a potential target for the clinical treatment of HCC. Show less
no PDF DOI: 10.1016/j.biopha.2019.109397
AXIN1

Tumor Intrinsic Efficacy by SHP2 and RTK Inhibitors in KRAS-Mutant Cancers.

Huai-Xiang Hao, Hongyun Wang, Chen Liu +22 more · 2019 · Molecular cancer therapeutics · added 2026-04-24
no PDF DOI: 10.1158/1535-7163.MCT-19-0170
DUSP6

Identification of genetic factors underlying persistent pulmonary hypertension of newborns in a cohort of Chinese neonates.

Xu Liu, Mei Mei, Xiang Chen +8 more · 2019 · Respiratory research · BioMed Central · added 2026-04-24
Persistent pulmonary hypertension of the newborn (PPHN) is a severe clinical problem among neonatal intensive care unit (NICU) patients. The genetic pathogenesis of PPHN is unclear. Only a few genetic Show more
Persistent pulmonary hypertension of the newborn (PPHN) is a severe clinical problem among neonatal intensive care unit (NICU) patients. The genetic pathogenesis of PPHN is unclear. Only a few genetic polymorphisms have been identified in infants with PPHN. Our study aimed to investigate the potential genetic etiology of PPHN. This study recruited PPHN patients admitted to the NICU of the Children's Hospital of Fudan University from Jan 2016 to Dec 2017. Exome sequencing was performed for all patients. Variants in reported PPHN/pulmonary arterial hypertension (PAH)-related genes were assessed. Single nucleotide polymorphism (SNP) association and gene-level analyses were carried out in 74 PPHN cases and 115 non-PPHN controls with matched baseline characteristics. Among the patient cohort, 74 (64.3%) patients were late preterm and term infants (≥ 34 weeks gestation) and 41 (35.7%) were preterm infants (< 34 weeks gestation). Preterm infants with PPHN exhibited low birth weight and a high frequency of bronchopulmonary dysplasia, respiratory distress syndrome (RDS) and mortality. Nine patients (only one preterm infant) were identified as harboring genetic variants, including three with pathogenic/likely pathogenic variants in TBX4 and BMPR2 and six with variants of unknown significance in BMPR2, SMAD9, TGFB1, KCNA5 and TRPC6. Three SNPs (rs192759073, rs1047883 and rs2229589) in CPS1 and one SNP (rs1044008) in NOTCH3 were significantly associated with PPHN (p < 0.05). CPS1 and SMAD9 were identified as risk genes for PPHN (p < 0.05). In this study, we identified genetic variants in PPHN patients, and we reported CPS1, NOTCH3 and SMAD9 as risk genes for late preterm and term PPHN in a single-center Chinese cohort. Our findings provide additional genetic evidence of the pathogenesis of PPHN and new insight into potential strategies for disease treatment. Show less
📄 PDF DOI: 10.1186/s12931-019-1148-1
CPS1

Paternal chronic folate supplementation induced the transgenerational inheritance of acquired developmental and metabolic changes in chickens.

Shengru Wu, Wei Guo, Xinyi Li +5 more · 2019 · Proceedings. Biological sciences · The Royal Society · added 2026-04-24
Increasing evidence indicates that paternal diet can result in metabolic changes in offspring, but the definite mechanism remains unclear in birds. Here, we fed breeder cocks five different diets cont Show more
Increasing evidence indicates that paternal diet can result in metabolic changes in offspring, but the definite mechanism remains unclear in birds. Here, we fed breeder cocks five different diets containing 0, 0.25, 1.25, 2.50 and 5.00 mg kg Show less
no PDF DOI: 10.1098/rspb.2019.1653
ANGPTL4

Epigallocatechin-3-Gallate Attenuates Adriamycin-Induced Focal Segmental Glomerulosclerosis via Suppression of Oxidant Stress and Apoptosis by Targeting Hypoxia-Inducible Factor-1α/ Angiopoietin-Like 4 Pathway.

Guoyong Liu, Liyu He · 2019 · Pharmacology · added 2026-04-24
Focal and segmental glomerular sclerosis (FSGS) is a common cause of nephrotic syndrome and end-stage renal disease. It has been reported that overproduction of reactive oxygen species (ROS) and cell Show more
Focal and segmental glomerular sclerosis (FSGS) is a common cause of nephrotic syndrome and end-stage renal disease. It has been reported that overproduction of reactive oxygen species (ROS) and cell apoptosis are associated with the development of FSGS. Epigallocatechin-3-gallate (EGCG) is a bioactive constituent accounting for more than 50% of the total catechins in green tea, which have anti-oxidative and anti-apoptotic effects. Based on this, this study was designed to evaluate the renoprotective effect of EGCG treatment on Adriamycin-induced FSGS. -Methods: In C57BL/6 mice, Adriamycin nephropathy (AN) was induced by Adriamycin (10 mg/kg body weight, diluted in normal saline) via a tail vein on day 0. Then the mice were given with EGCG (20 mg/kg body weight) or YC-1 (Lificiguat, a specific inhibitor of hypoxia-inducible factor-1α [HIF-1α], 50 mg/kg body weight) or both intraperitoneally. Both the EGCG and YC-1 were given on the day of Adriamycin injection and continued for 6 weeks. The animals were organized into the following 5 groups for the animal experiments: the control group, the AN group, the AN + EGCG group, the AN + YC-1 group and the AN + EGCG + YC-1 group. At 6 weeks, the mice were sacrificed; kidneys and blood samples were collected for further analysis. The HIF-1α and the angiopoietin-like 4 (ANGPTL4) expression were detected by Western blot, real-time PCR, immunohistochemistry or immunofluorescence. Dihydroethidium staining and NADPH oxidase 1 (Nox1) measurement were used to detect ROS production. Terminal deoxynucleotide transferase-mediated dUTP nick end-labeling (TUNEL) staining and caspase-3 measurement was used to detect cell apoptosis. When the animals were treated with Adriamycin, both the ROS production and TUNEL positive cells increased. Besides, the expression of HIF-1α, ANGPTL4, and caspase-3 were also up-regulated, while EGCG treatment could attenuate these changes. Interestingly, compared with treatment with YC-1 or EGCG alone, more pronounced inhibition of ANGPTL4, caspase-3 and Nox1 were obtained when YC-1 and EGCG were administered simultaneously. EGCG attenuates FSGS through the suppression of Oxidant Stress and apoptosis by targeting the HIF-1α/ANGPTL4 pathway. Show less
no PDF DOI: 10.1159/000496799
ANGPTL4

Up-regulated of Angiopoietin-Like Protein 4 Predicts Poor Prognosis in Cervical Cancer.

Dan Nie, Qianwen Zheng, Ling Liu +2 more · 2019 · Journal of Cancer · added 2026-04-24
📄 PDF DOI: 10.7150/jca.29916
ANGPTL4

RNA-Binding Motif Protein 6 is a Candidate Serum Biomarker for Pancreatic Cancer.

Baojun Duan, Xiaoyan Hu, Meiyang Fan +9 more · 2019 · Proteomics. Clinical applications · Wiley · added 2026-04-24
Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers. The Show more
Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers. The serum proteome of 22 PC patients, 12 pancreatitis patients (PP), and 45 healthy controls (HC) are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Next, a supervised neural network (SNN) algorithm model is established by ClinProTools and the candidate biomarker identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Finally, the candidate biomarker is validated in tissue samples. The SNN algorithm model discriminates PC from HC with 92.97% sensitivity and 94.55% specificity. Seventy-six differentially expressed peptides are identified, seven of which are significantly different among PC, PP, and HC (p < 0.05). Only one peak (m/z: 1466.99) tends to be upregulated in samples from HC, PP, and PC, which is identified as region of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, it is verified that RBM6 expression is significantly higher in PC tissues than paracancerous tissue. The results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC. Methods used in this study could generate serum peptidome profiles of PC, PP, and HC, and present an approach to identify potential biomarkers for diagnosis of this malignancy. Show less
no PDF DOI: 10.1002/prca.201900048
RBM6

Precision Health Resource of Control iPSC Lines for Versatile Multilineage Differentiation.

Matthew R Hildebrandt, Miriam S Reuter, Wei Wei +25 more · 2019 · Stem cell reports · Elsevier · added 2026-04-24
Induced pluripotent stem cells (iPSC) derived from healthy individuals are important controls for disease-modeling studies. Here we apply precision health to create a high-quality resource of control Show more
Induced pluripotent stem cells (iPSC) derived from healthy individuals are important controls for disease-modeling studies. Here we apply precision health to create a high-quality resource of control iPSCs. Footprint-free lines were reprogrammed from four volunteers of the Personal Genome Project Canada (PGPC). Multilineage-directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users demonstrated versatility by generating kidney organoids, T lymphocytes, and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited the expected hypertrophic phenotype. Whole-genome sequencing-based annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harbored at least one pre-existing or acquired variant with cardiac, neurological, or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cells from six tissues for disease modeling, and variant-preferred healthy control lines were identified for specific disease settings. Show less
no PDF DOI: 10.1016/j.stemcr.2019.11.003
MYBPC3

Neurexin 3 transmembrane and soluble isoform expression and splicing haplotype are associated with neuron inflammasome and Alzheimer's disease.

Akitoyo Hishimoto, Olga Pletnikova, Doyle Lu Lang +3 more · 2019 · Alzheimer's research & therapy · BioMed Central · added 2026-04-24
Synaptic damage precedes neuron death in Alzheimer's disease (AD). Neurexins, NRXN1, NRXN2, and NRXN3, are presynaptic adhesion molecules that specify neuron synapses and regulate neurotransmitter rel Show more
Synaptic damage precedes neuron death in Alzheimer's disease (AD). Neurexins, NRXN1, NRXN2, and NRXN3, are presynaptic adhesion molecules that specify neuron synapses and regulate neurotransmitter release. Neurexins and postsynaptic neuroligins interact with amyloid beta oligomer (AβO) deposits in damaged synapses. NRXN3 gene variants have been associated with autism, addiction, and schizophrenia, however, not fully investigated in Alzheimer's disease. In the present study, we investigated an AD association of a 3'-splicing allele of rs8019381 that produces altered expression of transmembrane or soluble NRXN3 isoforms. We carried out RT-PCR (reverse transcription polymerase chain reaction), PCR-RFLP (PCR and restriction fragment length polymorphism), Sanger sequencing, and in situ hybridization (ISH) assays for NRXN3 neuron expression and genotyping. Genetic associations were analyzed by χ We previously identified a functional haplotype in the 3' region of neurexin 3 (NRXN3) gene that alters the expression ratios between NRXN3 transmembrane and soluble isoforms. In this study, we found that expression and ratio of transmembrane and soluble NRXN3 isoforms were reduced in AD postmortem brains and inversely correlated with inflammasome component NLRP3 in AD brain regions. The splicing haplotype related to the transmembrane and soluble NRXN3 expression was associated with AD samples with P = 6.3 × 10 We found that the SNP rs8019381 of NRXN3 that is located adjacent to splicing site #5 (SS#5) interacts with the APOE ε4 haplotype and alters NRXN3 transmembrane or soluble isoform expression in AD postmortem cortex. Dysregulation of presynaptic NRXN3 expression and splicing might increase neuron inflammation in AD brain. Show less
no PDF DOI: 10.1186/s13195-019-0475-2
NRXN3

Distinct role of Sirtuin 1 (SIRT1) and Sirtuin 2 (SIRT2) in inhibiting cargo-loading and release of extracellular vesicles.

Byung Rho Lee, Bethany J Sanstrum, Yutao Liu +1 more · 2019 · Scientific reports · Nature · added 2026-04-24
Exosomes, vehicles for intercellular communication, are formed intracellularly within multivesicular bodies (MVBs) and are released upon fusion with the plasma membrane. For their biogenesis, proper c Show more
Exosomes, vehicles for intercellular communication, are formed intracellularly within multivesicular bodies (MVBs) and are released upon fusion with the plasma membrane. For their biogenesis, proper cargo loading to exosomes and vesicle traffic for extracellular release are required. Previously we showed that the L-type lectin, LMAN2, limits trans-Golgi Network (TGN)-to-endosomes traffic of GPRC5B, an exosome cargo protein, for exosome release. Here, we identified that the protein deacetylase sirtuin 2 (SIRT2) as a novel interactor of LMAN2. Loss of SIRT2 expression resulted in exosomal release of LMAN2, a Golgi resident protein, along with increased exosomal release of GPRC5B. Furthermore, knockout of SIRT2 increased total number of extracellular vesicles (EVs), indicating increased MVB-to-EV flux. While knockout of SIRT1 increased EV release with enlarged late endolysosome, knockout of SIRT2 did not exhibit endolysosome enlargement for increased EV release. Taken together, our study suggests that SIRT2 regulates cargo loading to MVBs and MVB-to-EV flux through a mechanism distinct from that of SIRT1. Show less
📄 PDF DOI: 10.1038/s41598-019-56635-0
GPRC5B

Novel phenotype-genotype correlations of hypertrophic cardiomyopathy caused by mutation in α-actin and myosin-binding protein genes in three unrelated Chinese families.

Qian-Li Yang, Yang-Yang Bian, Bo Wang +5 more · 2019 · Journal of cardiology · Elsevier · added 2026-04-24
The correlations between genotype and phenotype in hypertrophic cardiomyopathy (HCM) have not been established. Mutation of α-actin gene (ACTC1) is a rare cause of HCM. This study aimed to explore nov Show more
The correlations between genotype and phenotype in hypertrophic cardiomyopathy (HCM) have not been established. Mutation of α-actin gene (ACTC1) is a rare cause of HCM. This study aimed to explore novel genotype-phenotype correlations in HCM patients with the variants in ACTC1 and myosin-binding protein (MYBPC3) genes in three unrelated Chinese families. Clinical, electrocardiographic, and echocardiographic examinations were performed in three Han pedigrees. Exon and boarding intron analysis of 96 cardio-disease-related genes was performed using second-generation sequencing on three probands. The candidate variants were validated in 14 available family members and 300 unrelated healthy controls by bi-directional Sanger sequencing. The pathogenicity and conservation were calculated using MutationTaster, PolyPhen-2, SIFT, and Clustal X. Pathogenicity classification of the variants was based on American College of Medical Genetics and Genomics (ACMG) guidelines. Nine members fulfilled diagnostic criteria for HCM with clinical characteristics, electrocardiographic, and echocardiographic findings. Two candidate variants in ACTC1 p.Asp26Asn (ACTC1-D26N) and MYBPC3 p.Arg215Cys (MYBPC3-R215C) were identified in patients. Only ACTC1-D26N strongly co-segregated with the HCM phenotype. Seven patients who harbored variant ACTC-D26N only were diagnosed with non-obstructive HCM, and four of these patients exhibited a triphasic left ventricular (LV) filling pattern. Two patients carrying both ACTC1-D26N and MYBPC3-R215C variants showed a higher LV outflow tract pressure gradient. Bioinformatics analysis revealed that the two variants were deleterious and highly conserved across species. According to ACMG guidelines, ACTC1-D26N is classified as a likely pathogenic mutation. The second variation MYBPC3-R215C may function as a genetic modifier, which remains uncertain here. Novel p.(Asp26Asn) mutation of ACTC1 was associated with HCM phenotype, and the penetrance is extremely high (∼81.8%) in adults. The second variation, MYBPC3-R215C may function as a genetic modifier, which remains uncertain here. Show less
no PDF DOI: 10.1016/j.jjcc.2018.09.005
MYBPC3

Fibroblast growth factor 21 is required for the therapeutic effects of Lactobacillus rhamnosus GG against fructose-induced fatty liver in mice.

Cuiqing Zhao, Liming Liu, Qi Liu +9 more · 2019 · Molecular metabolism · Elsevier · added 2026-04-24
High fructose feeding changes fibroblast growth factor 21 (FGF21) regulation. Lactobacillus rhamnosus GG (LGG) supplementation reduces fructose-induced non-alcoholic fatty liver disease (NAFLD). The a Show more
High fructose feeding changes fibroblast growth factor 21 (FGF21) regulation. Lactobacillus rhamnosus GG (LGG) supplementation reduces fructose-induced non-alcoholic fatty liver disease (NAFLD). The aim of this study was to determine the role of FGF21 and underlying mechanisms in the protective effects of LGG. FGF21 knockout (KO) mice and C57BL/6 wild type (WT) mice were fed 30% fructose for 12 weeks. LGG was administered to the mice in the last 4 weeks during fructose feeding. FGF21-adiponectin (ADPN)-mediated hepatic lipogenesis and inflammation were investigated. FGF21 expression was robustly increased after 5-weeks of feeding and significantly decreased after 12-weeks of feeding in fructose-induced NAFLD mice. LGG administration reversed the depressed FGF21 expression, increased adipose production of ADPN, and reduced hepatic fat accumulation and inflammation in the WT mice but not in the KO mice. Hepatic nuclear carbohydrate responsive-element binding protein (ChREBP) was increased by fructose and reduced by LGG, resulting in a reduction in the expression of lipogenic genes. The methylated form of protein phosphatase 2A (PP2A) C, which dephosphorylates and activates ChREBP, was upregulated by fructose and normalized by LGG. Leucine carboxyl methyltransferase-1, which methylates PP2AC, was also increased by fructose and decreased by LGG. However, those beneficial effects of LGG were blunted in the KO mice. Hepatic dihydrosphingosine-1-phosphate, which inhibits PP2A, was markedly increased by LGG in the WT mice but attenuated in the KO mice. LGG decreased adipose hypertrophy and increased serum levels of ADPN, which regulates sphingosine metabolism. This beneficial effect was decreased in the KO mice. LGG administration increases hepatic FGF21 expression and serum ADPN concentration, resulting in a reduced ChREBP activation through dihydrosphingosine-1-phosphate-mediated PP2A deactivation, and subsequently reversed fructose-induced NAFLD. Thus, our data suggest that FGF21 is required for the beneficial effects of LGG in reversal of fructose-induced NAFLD. Show less
📄 PDF DOI: 10.1016/j.molmet.2019.08.020
MLXIPL

Evaluation of the association of

Ke Liu, Li Ma, Timothy Y Y Lai +5 more · 2019 · Eye and vision (London, England) · BioMed Central · added 2026-04-24
Neovascular age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) are sight-threatening maculopathies with both environmental and genetic risk factors. We have previously Show more
Neovascular age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) are sight-threatening maculopathies with both environmental and genetic risk factors. We have previously shown relative risks posed by genes of the complement pathways to neovascular AMD and PCV. In this study, we investigated the haplotype-tagging single nucleotide polymorphisms (SNPs) in the The results revealed none of the six tagging SNPs of the This study showed no statistical significance in the genetic association of Show less
📄 PDF DOI: 10.1186/s40662-019-0161-2
CETP

Dysregulated expressions of PTEN, NF-κB, WWP2, p53 and c-Myc in different subtypes of B cell lymphoma and reactive follicular hyperplasia.

Huan Fu, Chenghao Jin, Qingxiu Zhu +4 more · 2019 · American journal of translational research · added 2026-04-24
This study aimed to investigate the value of PTEN, NF-κB, WWP2, p53 and c-Myc expressions in distinguishing B cell lymphomas from reactive follicular hyperplasia (RFH), and their abilities to discrimi Show more
This study aimed to investigate the value of PTEN, NF-κB, WWP2, p53 and c-Myc expressions in distinguishing B cell lymphomas from reactive follicular hyperplasia (RFH), and their abilities to discriminate different B cell lymphoma subtypes. Lymphoma tissue samples were obtained from 30 follicular lymphoma (FL) patients, 30 germinal center B-cell like (GCB) diffuse large B cell lymphoma (DLBCL) patients, 30 non-GCB DLBCL patients and 30 Burkitt's lymphoma (BL) patients. And hyperplasia tissue samples were obtained from and 30 RFH patients. Immunohistochemistry was used to quantify the expressions of PTEN, NF-κB, WWP2, P53 and c-Myc. PTEN expression was elevated in GCB DLBCL and BL compared with RFH, and in GCB DLBCL, non-GCB DLBCL and BL than that in FL; WWP2 expression was higher in FL, GCB DLBCL, non-GCB DLBCL and BL compared with RFH; p53 expression increased in non-GCB DLBCL compared with RFH, and in BL compared with RFH, FL or GCB DLBCL; c-Myc expression was higher in GCB DLBCL, non-GCB DLBCL and BL compared with RFH; c-Myc expression was elevated in GCB DLBCL, non-GCB DLBCL and BL compared with FL. Additionally, PTEN negatively correlated with p53 expression in FL and CGB DLBCL, whereas NF-κB negatively correlated with WWP2 in GCB DLBCL, but positively associated with PTEN in RFH and c-Myc in BL. PTEN, WWP2, p53 and c-Myc expressions might be served as biomarkers for identification of B cell lymphomas from RFH as well as distinguishing different B cell lymphoma subtypes. Show less
no PDF
WWP2

Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model.

Zhe Zhang, Morten Kargo, Aoxing Liu +3 more · 2019 · Heredity · Nature · added 2026-04-24
Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. Show more
Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits. Show less
📄 PDF DOI: 10.1038/s41437-019-0192-4
MC4R

Effects of lysine deficiency or excess on growth and the expression of lipid metabolism genes in slow-growing broilers.

D L Tian, R J Guo, Y M Li +8 more · 2019 · Poultry science · added 2026-04-24
This experiment was conducted to evaluate the effects of lysine deficiency or excess on growth and the expression of lipid metabolism genes in slow-growing birds. A total of 360 one-day-old chicks wer Show more
This experiment was conducted to evaluate the effects of lysine deficiency or excess on growth and the expression of lipid metabolism genes in slow-growing birds. A total of 360 one-day-old chicks were randomly divided into 3 groups, with 6 replicates of 20 birds each. The birds fed the basal diet with a total lysine 0.60% (LL), 1.00% (ML), or 1.40% (HL). The amount of lysine (ML) as the control group, LL and HL as the experimental group, the trial period last 3 wk. The results showed that compared with ML, LL significantly decreased average daily gain and average daily feed intake and remarkably increased feed conversion ratio of birds at 21 day old (P < 0.01), while the above indices in HL had no significant effects (P > 0.05). Besides, LL reduced the pectoral muscle rate (P < 0.01) and decreased the percentage of abdominal fat significantly (P < 0.05). In addition, compared with ML, the expression of fatty acid binding protein 1 (FABP1), acetyl-CoA carboxylase (ACC), malic enzyme (ME), and sterol regulatory element binding protein 1 (SREBP1c) mRNA of liver in LL was significantly decreased (P < 0.05), and the expression of cholesteryl ester transfer protein (CETP) mRNA was significantly increased (P < 0.01), whereas LL had no significant effects on the expression of peroxisome proliferator activated receptor alpha (PPARα) mRNA (P > 0.05). Moreover, compared with ML, HL significantly reduced the expression of FABP1, ACC, ME, SREBP-1c, and PPARα mRNA in the liver (P < 0.05), and had no significant effects on the expression of CETP mRNA (P > 0.05). The results of current research suggest that dietary lysine deficiency could reduce the growth and fat deposition of slow-growing broilers mainly by downregulating the expression of lipid synthesis genes. Show less
no PDF DOI: 10.3382/ps/pez041
CETP