👤 Aimin 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, 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, 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

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

Biomedical potential of mammalian spectraplakin proteins: Progress and prospect.

Sarah A King, Han Liu, Xiaoyang Wu · 2019 · Experimental biology and medicine (Maywood, N.J.) · SAGE Publications · added 2026-04-24
The cytoskeleton is an essential element of a eukaryotic cell which informs both form and function and ultimately has physiological consequences for the organism. Equally as important as the major cyt Show more
The cytoskeleton is an essential element of a eukaryotic cell which informs both form and function and ultimately has physiological consequences for the organism. Equally as important as the major cytoskeletal networks are crosslinkers which coordinate and regulate their activities. One such category of crosslinker is the spectraplakins, a family of giant, evolutionarily conserved crosslinking proteins with the rare ability to interact with each of the three major cytoskeletal networks. In particular, a mammalian spectraplakin isotype called MACF1 (microtubule actin crosslinking factor 1), also known as ACF7 (actin crosslinking factor 7), has been of particular interest in the years since its discovery; MACF1 has come under such scrutiny due to the mounting list of biological phenomena in which it has been implicated. This review is an overview of the current knowledge on the structure and function of the known spectraplakin isotypes with an emphasis on MACF1, recent studies on MACF1, and finally, an analysis of the potential of MACF1 to advance medicine. Spectraplakins are a highly conserved group of proteins which have the rare ability to bind to each of the three major cytoskeletal networks. The mammalian spectraplakin MACF1/ACF7 has proven to be instrumental in many cellular processes (e.g. signaling and cell migration) since its identification and, as such, has been the focus of various research studies. This review is a synthesis of scientific reports on the structure, confirmed functions, and implicated roles of MACF1/ACF7 as of 2019. Based on what has been revealed thus far in terms of MACF1/ACF7’s role in complex pathologies such as metastatic cancers and inflammatory bowel disease, it appears that MACF1/ACF7 and the continued study thereof hold great potential to both enhance the design of future therapies for various diseases and vastly expand scientific understanding of organismal physiology as a whole. Show less
no PDF DOI: 10.1177/1535370219864920
MACF1

Müller Cells Stabilize Microvasculature through Hypoxic Preconditioning.

Kepeng Ou, Sonja Mertsch, Sofia Theodoropoulou +7 more · 2019 · Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology · added 2026-04-24
Hypoxia of the retina is a common pathogenic drive leading to vision loss as a result of tissue ischemia, increased vascular permeability and ultimately retinal neovascularisation. Here we tested the Show more
Hypoxia of the retina is a common pathogenic drive leading to vision loss as a result of tissue ischemia, increased vascular permeability and ultimately retinal neovascularisation. Here we tested the hypothesis that Müller cells stabilize the neurovascular unit, microvasculature by suppression of HIF-1α activation as a result of hypoxic preconditioning. Tube Formation Assay and In vitro Vascular Permeability Image Assay were used to analyze angiogenesis and vascular integrity. Seahorse XF Cell Mito Stress Test was used to measure mitochondrial respiration. Gene and protein expression were examined by qRTPCR, ELISA and western blot. Hypoxic insult induces a significant induction of proangiogenic factors including vascular endothelial growth factor (VEGF) and angiopoietinlike 4 (ANGPTL-4) resulting in angiogenesis and increased vascular permeability of vascular endothelial cells. Hypoxic preconditioning of a human retinal Müller glia cell line significantly attenuates HIF-1α activation through the inhibition of mTOR and concomitant induction of aerobic glycolysis, stabilizing endothelial cells. Hypoxic preconditioning of Müller cells confers a robust protection to endothelial cells, through the suppression of HIF1α activation and its downstream regulation of VEGF and ANGPTL-4. Show less
no PDF DOI: 10.33594/000000047
ANGPTL4

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome.

Zhenglin Du, Liang Ma, Hongzhu Qu +27 more · 2019 · Genomics, proteomics & bioinformatics · Elsevier · added 2026-04-24
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of Show more
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a "comfort" zone for a high frequency of 677T between latitudes of 35-45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine. Show less
📄 PDF DOI: 10.1016/j.gpb.2019.07.002
FADS1

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

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

Cholesterol depletion sensitizes gallbladder cancer to cisplatin by impairing DNA damage response.

Yonglong Zhang, Yanfeng Liu, Jinlin Duan +4 more · 2019 · Cell cycle (Georgetown, Tex.) · Taylor & Francis · added 2026-04-24
Gallbladder cancer (GBC) is the common malignancy of the bile tract system with extremely poor clinical outcomes, owing to its metastatic property and intrinsic resistance to the first-line drugs. Alt Show more
Gallbladder cancer (GBC) is the common malignancy of the bile tract system with extremely poor clinical outcomes, owing to its metastatic property and intrinsic resistance to the first-line drugs. Although it is well-established that cholesterol abnormity contributes to gallstone formation, a leading risk factor for GBC, the link of cholesterol homeostasis with GBC has not been investigated. The present study systematically examined the genes implicated in cholesterol homeostasis, and revealed altered gene expressions of Show less
no PDF DOI: 10.1080/15384101.2019.1676581
CETP

Cholesteryl Ester Transfer Protein Genetic Variants Associated with Risk for Type 2 Diabetes and Diabetic Kidney Disease in Taiwanese Population.

Yu-Chuen Huang, Shih-Yin Chen, Shih-Ping Liu +8 more · 2019 · Genes · MDPI · added 2026-04-24
Cholesteryl ester transfer protein (CETP) plays an important role in lipid metabolism. Low levels of high-density lipoprotein cholesterol (HDL-C) increase the risk of type 2 diabetes (T2D). This study Show more
Cholesteryl ester transfer protein (CETP) plays an important role in lipid metabolism. Low levels of high-density lipoprotein cholesterol (HDL-C) increase the risk of type 2 diabetes (T2D). This study investigated CETP gene variants to assess the risk of T2D and specific complications of diabetic kidney disease (DKD) and diabetic retinopathy. Towards this, a total of 3023 Taiwanese individuals (1383 without T2D, 1640 with T2D) were enrolled in this study. T2D mice (+Lepr Show less
📄 PDF DOI: 10.3390/genes10100782
CETP

Targeting BCAA Catabolism to Treat Obesity-Associated Insulin Resistance.

Meiyi Zhou, Jing Shao, Cheng-Yang Wu +17 more · 2019 · Diabetes · added 2026-04-24
Recent studies implicate a strong association between elevated plasma branched-chain amino acids (BCAAs) and insulin resistance (IR). However, a causal relationship and whether interrupted BCAA homeos Show more
Recent studies implicate a strong association between elevated plasma branched-chain amino acids (BCAAs) and insulin resistance (IR). However, a causal relationship and whether interrupted BCAA homeostasis can serve as a therapeutic target for diabetes remain to be established experimentally. In this study, unbiased integrative pathway analyses identified a unique genetic link between obesity-associated IR and BCAA catabolic gene expression at the pathway level in human and mouse populations. In genetically obese ( Show less
📄 PDF DOI: 10.2337/db18-0927
BCKDK

Cell division cycle 20 (CDC20) drives prostate cancer progression via stabilization of β-catenin in cancer stem-like cells.

Qin Zhang, Hai Huang, Ao Liu +7 more · 2019 · EBioMedicine · Elsevier · added 2026-04-24
Cell division cycle 20 (CDC20) is frequently overexpressed in malignant tumours and involved in the differentiation process of hematopoietic stem cells. However, the role of CDC20 in prostate cancer s Show more
Cell division cycle 20 (CDC20) is frequently overexpressed in malignant tumours and involved in the differentiation process of hematopoietic stem cells. However, the role of CDC20 in prostate cancer stem-like cells (CSCs) remains poorly understood. The expression of CDC20, CD44, β-catenin were examined in prostate cancer specimens by immunohistochemistry assay, the role of CDC20 on the stem-like properties of prostate CSCs was accessed by real-time quantitive PCR, spheroid formation, in vitro and in vivo limiting dilution assay. CDC20 was associated with malignant progression of prostate cancer, the patients with both high expression CDC20 and CD44 or β-catenin were associated with more aggressive clinicopathological features and poor prognosis. CDC20 was usually enriched in CD44 Our results indicated that CDC20 maintains the self-renewal ability of CD44 Show less
📄 PDF DOI: 10.1016/j.ebiom.2019.03.032
AXIN1

Identification of ApoA4 as a sphingosine 1-phosphate chaperone in ApoM- and albumin-deficient mice.

Hideru Obinata, Andrew Kuo, Yukata Wada +7 more · 2019 · Journal of lipid research · added 2026-04-24
HDL-bound ApoM and albumin are protein chaperones for the circulating bioactive lipid, sphingosine 1-phosphate (S1P); in this role, they support essential extracellular S1P signaling functions in the Show more
HDL-bound ApoM and albumin are protein chaperones for the circulating bioactive lipid, sphingosine 1-phosphate (S1P); in this role, they support essential extracellular S1P signaling functions in the vascular and immune systems. We previously showed that ApoM- and albumin-bound S1P exhibit differences in receptor activation and biological functions. Whether the physiological functions of S1P require chaperones is not clear. We examined ApoM-deficient, albumin-deficient, and double-KO (DKO) mice for circulatory S1P and its biological functions. In albumin-deficient mice, ApoM was upregulated, thus enabling S1P functions in embryonic development and postnatal adult life. The Show less
no PDF DOI: 10.1194/jlr.RA119000277
APOA4

Whole exome and target sequencing identifies MAP2K5 as novel susceptibility gene for familial non-medullary thyroid carcinoma.

Feng Ye, Hongwei Gao, Lin Xiao +19 more · 2019 · International journal of cancer · Wiley · added 2026-04-24
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNM Show more
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNMTC). The aim of this study is to screen and identify high-penetrate genes for FNMTC. A total of 34 families with more than two first-degree relatives diagnosed as papillary thyroid cancer without other familial syndrome were recruited. Whole exome and target gene sequencing were performed for candidate variants. These variants were screened and analyzed with ESP6500, ExAC, 1000 genomes project, and the Cancer Genome Atlas (TCGA) with SIFT score and Polyphen2 prediction. Finally, we identified recurrent genetic mutation of MAP2K5 variants c.G961A and c.T1100C (p. A321T and p.M367 T) as susceptibility loci for FNMTC. The frequencies of MAP2K5 c.G961A and c.T1100C were found, 0.0385 and 0.0259 in FNMTC and 0 and 0.00022523 in healthy Chinese controls (n = 2200, P < 0.001), respectively. Both variants were located in the protein kinase domain. The functional study showed that MAP2K5 A321T or M367 T could consistently phosphorylate downstream protein ERK5 on site Ser731 + Thr733 or Ser496, promoting nuclear translocation and subsequently altering target gene expressions. Our data revealed that MAP2K5 variants A321T or M367 T can activate MAP2K5-ERK5 pathway, alter downstream gene expression, and subsequently induce thyroid epithelial cell malignant transformation. While classic MAP2K1/2(MEK1/2)-ERK1/2 signaling is well known for driving sporadic NMTC, our research indicated that MAP2K5 (MEK5) is a susceptibility gene for FNMTC. These findings highlight the potential application of MAP2K5 for molecular diagnosis as well as early prevention. Show less
no PDF DOI: 10.1002/ijc.31825
MAP2K5

Oncogenic STRAP Supports Hepatocellular Carcinoma Growth by Enhancing Wnt/β-Catenin Signaling.

Wenhui Wang, Shan Li, Pengyu Liu +9 more · 2019 · Molecular cancer research : MCR · added 2026-04-24
Aberrant activation of Wnt/β-catenin signaling plays a key role in the onset and development of hepatocellular carcinomas (HCC), with about half of them acquiring mutations in either
no PDF DOI: 10.1158/1541-7786.MCR-18-0054
AXIN1

Novel Neonatal Variants of the Carbamoyl Phosphate Synthetase 1 Deficiency: Two Case Reports and Review of Literature.

Beibei Yan, Chao Wang, Kaihui Zhang +6 more · 2019 · Frontiers in genetics · Frontiers · added 2026-04-24
Carbamoyl phosphate synthetase I (CPS1) deficiency (CPS1D), is a rare autosomal recessive disorder, characterized by life-threatening hyperammonemia. In this study, we presented the detailed clinical Show more
Carbamoyl phosphate synthetase I (CPS1) deficiency (CPS1D), is a rare autosomal recessive disorder, characterized by life-threatening hyperammonemia. In this study, we presented the detailed clinical features and genetic analysis of two patients with neonatal-onset CPS1D carrying two compound heterozygous variants of c.1631C > T (p.T544M)/c.1981G > T (p.G661C), and c.2896G > T (p.E966X)/c622-3C > G in Show less
📄 PDF DOI: 10.3389/fgene.2019.00718
CPS1

Demyelination contributes to depression comorbidity in a rat model of chronic epilepsy via dysregulation of Olig2/LINGO-1 and disturbance of calcium homeostasis.

Teng Ma, Baichuan Li, Yifan Le +7 more · 2019 · Experimental neurology · Elsevier · added 2026-04-24
Depression is the most common comorbidity among patients with epilepsy. Despite prior assumptions that antiepileptic drugs are to blame, more and more pathological studies have shown that latent neuro Show more
Depression is the most common comorbidity among patients with epilepsy. Despite prior assumptions that antiepileptic drugs are to blame, more and more pathological studies have shown that latent neurological alterations associated with white matter injury and demyelination may underlie this link. However, whether disturbances in cerebral myelination contribute to the initiation of depression in epilepsy remains unclear. In the present study, we investigated the connection between demyelination disorders and the development of depression comorbidity in epilepsy. We first induced spontaneous recurrent epilepticus seizure (SRS) in young rats with pilocarpine. We then established depressive behaviors by recurrent forced swimming test and evaluate the depression state by sucrose preference test. The ratio of depression comorbidity in SRS rats was then calculated. Next, myelination in SRS-Depressed (SRS-D) rats was explored via PCR, western blotting, and immunohistochemistry for the key myelin promotion factor, Olig2 and inhibition factor, LINGO-1. Finally, in situ RNA hybridization of NCX3, one of the dominant Ca Show less
no PDF DOI: 10.1016/j.expneurol.2019.113034
LINGO1

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
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WWP2

JMJD1C-mediated metabolic dysregulation contributes to HOXA9-dependent leukemogenesis.

Jennifer R Lynch, Basit Salik, Patrick Connerty +13 more · 2019 · Leukemia · Nature · added 2026-04-24
Abnormal metabolism is a fundamental hallmark of cancer and represents a therapeutic opportunity, yet its regulation by oncogenes remains poorly understood. Here, we uncover that JMJD1C, a jumonji C ( Show more
Abnormal metabolism is a fundamental hallmark of cancer and represents a therapeutic opportunity, yet its regulation by oncogenes remains poorly understood. Here, we uncover that JMJD1C, a jumonji C (JmjC)-containing H3K9 demethylase, is a critical regulator of aberrant metabolic processes in homeobox A9 (HOXA9)-dependent acute myeloid leukemia (AML). JMJD1C overexpression increases in vivo cell proliferation and tumorigenicity through demethylase-independent upregulation of a glycolytic and oxidative program, which sustains leukemic cell bioenergetics and contributes to an aggressive AML phenotype in vivo. Targeting JMJD1C-mediated metabolism via pharmacologic inhibition of glycolysis and oxidative phosphorylation led to ATP depletion, induced necrosis/apoptosis and decreased tumor growth in vivo in leukemias co-expressing JMJD1C and HOXA9. The anti-metabolic therapy effectively diminished AML stem/progenitor cells and reduced tumor burden in a primary AML patient-derived xenograft. Our data establish a direct link between drug responses and endogenous expression of JMJD1C and HOXA9 in human AML cell line- and patient-derived xenografts. These findings demonstrate a previously unappreciated role for JMJD1C in counteracting adverse metabolic changes and retaining the metabolic integrity during tumorigenesis, which can be exploited therapeutically. Show less
📄 PDF DOI: 10.1038/s41375-018-0354-z
JMJD1C

Heat Stress-Responsive Transcriptome Analysis in the Liver Tissue of Hu Sheep.

Yaokun Li, Lingxuan Kong, Ming Deng +6 more · 2019 · Genes · MDPI · added 2026-04-24
Heat stress has a severe effect on animal health and can reduce the productivity and reproductive efficiency; it is therefore necessary to explore the molecular mechanism involved in heat stress respo Show more
Heat stress has a severe effect on animal health and can reduce the productivity and reproductive efficiency; it is therefore necessary to explore the molecular mechanism involved in heat stress response, which is helpful for the cultivation of an animal breed with resistance to heat stress. However, little research about heat stress-responsive molecular analysis has been reported in sheep. Therefore, in this study, RNA sequencing (RNA-Seq) was used to investigate the transcriptome profiling in the liver of Hu sheep with and without heat stress. In total, we detected 520 and 22 differentially expressed mRNAs and lncRNAs, respectively. The differentially expressed mRNAs were mainly associated with metabolic processes, the regulation of biosynthetic processes, and the regulation of glucocorticoid; additionally, they were significantly enriched in the heat stress related pathways, including the carbon metabolism, the PPAR signaling pathway, and vitamin digestion and absorption. The co-located differentially expressed lncRNA Lnc₀₀₁₇₈₂ might positively influence the expression of the corresponding genes APOA4 and APOA5, exerting co-regulative effects on the liver function. Thus, we made the hypothesis that Lnc₀₀₁₇₈₂, APOA4 and APOA5 might function synergistically to regulate the anti-heat stress ability in Hu sheep. This study provides a catalog of Hu sheep liver mRNAs and lncRNAs, and will contribute to a better understanding of the molecular mechanism underlying heat stress responses. Show less
📄 PDF DOI: 10.3390/genes10050395
APOA4

Comprehensive Analysis of Aberrantly Expressed ceRNA network in gastric cancer with and without

Aining Chu, Jingwei Liu, Yuan Yuan +1 more · 2019 · Journal of Cancer · added 2026-04-24
📄 PDF DOI: 10.7150/jca.27803
APOC3

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

Axin-1 binds to Caveolin-1 to regulate the LPS-induced inflammatory response in AT-I cells.

Yongjuan Zhang, Haihua Luo, Xuejun Lv +5 more · 2019 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Caveolin-1 has been reported to play an important role in the pathogenesis of acute respiratory distress syndrome (ARDS). This study was designed to identify Caveolin-1-interacting proteins to reveal Show more
Caveolin-1 has been reported to play an important role in the pathogenesis of acute respiratory distress syndrome (ARDS). This study was designed to identify Caveolin-1-interacting proteins to reveal the molecular mechanisms of ARDS. Yeast two-hybrid screening was performed using Caveolin-1 as the bait, and Axin-1 was identified as a binding partner for Caveolin-1. Co-immunoprecipitation demonstrated that the binding domains were located in the N-terminal region (1-100 aa) of Caveolin-1 and the C-terminal region (710-797 aa) of Axin-1. Caveolin-1 gene knockout or Axin-1 knockdown significantly decreased the levels of TNF-α and IL-6 in the supernatants of alveolar type I (AT-I) epithelial cells treated with LPS. Disrupting the interaction between Caveolin-1 and Axin-1 using CRISPR/Cas9 technology led to a significant increase in TNF-α and IL-6 from AT-I cells, along with a significant reduction in β-catenin expression. In conclusion, Axin-1 functions as an adaptor of Caveolin-1 and affects the production of inflammatory cytokines in AT-I cells challenged with LPS via β-catenin-mediated negative regulation. Show less
no PDF DOI: 10.1016/j.bbrc.2019.03.153
AXIN1

Severe biallelic loss-of-function mutations in nicotinamide mononucleotide adenylyltransferase 2 (NMNAT2) in two fetuses with fetal akinesia deformation sequence.

Marshall Lukacs, Jonathan Gilley, Yi Zhu +9 more · 2019 · Experimental neurology · Elsevier · added 2026-04-24
The three nicotinamide mononucleotide adenylyltransferase (NMNAT) family members synthesize the electron carrier nicotinamide adenine dinucleotide (NAD
📄 PDF DOI: 10.1016/j.expneurol.2019.112961
FADS1

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

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

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

Genome-Wide Assessment for Resting Heart Rate and Shared Genetics With Cardiometabolic Traits and Type 2 Diabetes.

Yanjun Guo, Wonil Chung, Zhaozhong Zhu +4 more · 2019 · Journal of the American College of Cardiology · Elsevier · added 2026-04-24
High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no Show more
High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no study has been conducted to investigate the shared mechanisms underlying these associations. The objective of this study was to understand the genetic basis of the association between resting heart rate and cardiometabolic disorders/T2D. This study examined the genetic correlation, causality, and shared genetics between RHR and T2D using LD Score regression, generalized summary data-based Mendelian randomization, and transcriptome wide association scan (TWAS) in UK Biobank data (n = 428,250) and summary-level data for T2D (74,124 cases and 824,006 control subjects) and 8 cardiometabolic traits (sample size ranges from 51,750 to 236,231). Significant genetic correlation between RHR and T2D (r These findings provide evidence of significant genetic correlations and causation between RHR and T2D/cardiometabolic traits, advance our understanding of RHR, and provide insight into shared etiology for high RHR and T2D. Show less
no PDF DOI: 10.1016/j.jacc.2019.08.1055
FADS1

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

Immune regulation by protein ubiquitination: roles of the E3 ligases VHL and Itch.

Daisuke Aki, Qian Li, Hui Li +2 more · 2019 · Protein & cell · Springer · added 2026-04-24
Protein ubiquitination is an important means of post-translational modification which plays an essential role in the regulation of various aspects of leukocyte development and function. The specificit Show more
Protein ubiquitination is an important means of post-translational modification which plays an essential role in the regulation of various aspects of leukocyte development and function. The specificity of ubiquitin tagging to a protein substrate is determined by E3 ubiquitin ligases via defined E3-substrate interactions. In this review, we will focus on two E3 ligases, VHL and Itch, to discuss the latest progress in understanding their roles in the differentiation and function of CD4 Show less
no PDF DOI: 10.1007/s13238-018-0586-8
WWP2

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

Long noncoding RNA CPS1-IT1 suppresses melanoma cell metastasis through inhibiting Cyr61 via competitively binding to BRG1.

Xiaobo Zhou, Yamin Rao, Qilin Sun +3 more · 2019 · Journal of cellular physiology · Wiley · added 2026-04-24
Long noncoding RNA CPS1-IT1 is recently recognized as a tumor suppressor in several cancers. Here, we investigate the role of CPS1-IT1 in human melanoma. Presently, our study reveals the low expressio Show more
Long noncoding RNA CPS1-IT1 is recently recognized as a tumor suppressor in several cancers. Here, we investigate the role of CPS1-IT1 in human melanoma. Presently, our study reveals the low expression of CPS1-IT1 in human melanoma tissues and cell lines, which is significantly associated with metastasis and tumor stage. Besides, the potential of CPS1-IT1 as a prognosis-predictor is strongly indicated. Functionally, CPS1-IT1 overexpression inhibits cell migration, invasion, epithelial-mesenchymal transition, and angiogenesis in melanoma cells. CYR61, an angiogenic factor that participates in tumor metastasis as well as a recognized oncogene in melanoma, is shown to be confined under CPS1-IT1 overexpression in melanoma cells. Furthermore, enforced expression of Cyr61 in CPS1-IT1-silenced melanoma cells dramatically normalized the protein level of Cyr61 and that of its downstream targets vascular endothelial growth factor and matrix metalloproteinase-9, as well as the repressive effect of CPS1-IT1 overexpression on melanoma cell metastasis. BRG1, a core component of SWI/SNF complex, is implied to interact with both CPS1-IT1 and Cyr61 in melanoma cells. Moreover, CPS1-IT1 negatively regulates Cyr61 expression by blocking the binding of BRG1 to Cyr61 promoter. Jointly, CPS1-IT1 controls melanoma metastasis through impairing Cyr61 expression via competitively binding with BRG1, uncovering a novel potential therapeutic and prognostic biomarker for patients with melanoma. Show less
no PDF DOI: 10.1002/jcp.28764
CPS1