👤 Hongyan 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, 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

Down-regulation of microRNA-31-5p inhibits proliferation and invasion of osteosarcoma cells through Wnt/β-catenin signaling pathway by enhancing AXIN1.

Xue Chen, Lili Zhong, Xijing Li +3 more · 2019 · Experimental and molecular pathology · Elsevier · added 2026-04-24
Recently, the role of microRNA-31-5p (miR-31-5p) in gene expression regulation has been reported in various cancers. Studies have shown that Wnt/β-catenin signaling pathway is involved in the prolifer Show more
Recently, the role of microRNA-31-5p (miR-31-5p) in gene expression regulation has been reported in various cancers. Studies have shown that Wnt/β-catenin signaling pathway is involved in the proliferation and invasion of osteosarcoma (OS) cells. Therefore, this study aims to probe into the regulatory role of miR-31-5p targeting AXIN1 in OS cells through Wnt/β-catenin signaling pathway. Firstly, microarray expression profiles were used to screen differentially expressed miRNAs associated with OS. Next, OS and normal fibrous connective tissues as well as OS cell lines were obtained for investigating the role of miR-31-5p on OS. Then, the putative binding sites between miR-31-5p and AXIN1 were predicted and verified. The regulatory effects of miR-31-5p on proliferation and invasion as well as tumorigenic potential of OS cells targeting AXIN1 were also analyzed. Besides, the relationship between miR-31-5p and Wnt/β-catenin signaling pathway was assessed by immunofluorescence staining. The microarray dataset GSE63939 showed that miR-31-5p and AXIN1 were involved in OS. miR-31-5p expression increased while the expression of AXIN1 decreased in OS tissues and cells. AXIN1 was identified as a target gene of miR-31-5p, intense expression of which inhibited the transcription of AXIN1. Down-regulated miR-31-5p suppressed proliferation, invasion and tumorigenicity of OS cells through promoting AXIN1. Decreased miR-31-5p activated Wnt/β-catenin signaling pathway, as reflected by increased β-catenin translocation into nuclei, through up-regulating the transcription of AXIN1. All in all, repression of miR-31-5p targets AXIN1 to activate the Wnt/β-catenin signaling pathway, thus suppressing proliferation, invasion and tumorigenicity of OS cells. Show less
no PDF DOI: 10.1016/j.yexmp.2019.03.001
AXIN1

High throughput circRNA sequencing analysis reveals novel insights into the mechanism of nitidine chloride against hepatocellular carcinoma.

Dan-Dan Xiong, Zhen-Bo Feng, Ze-Feng Lai +8 more · 2019 · Cell death & disease · Nature · added 2026-04-24
Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, Show more
Nitidine chloride (NC) has been demonstrated to have an anticancer effect in hepatocellular carcinoma (HCC). However, the mechanism of action of NC against HCC remains largely unclear. In this study, three pairs of NC-treated and NC-untreated HCC xenograft tumour tissues were collected for circRNA sequencing analysis. In total, 297 circRNAs were differently expressed between the two groups, with 188 upregulated and 109 downregulated, among which hsa_circ₀₀₈₈₃₆₄ and hsa_circ₀₀₉₀₀₄₉ were validated by real-time quantitative polymerase chain reaction. The in vitro experiments showed that the two circRNAs inhibited the malignant biological behaviour of HCC, suggesting that they may play important roles in the development of HCC. To elucidate whether the two circRNAs function as "miRNA sponges" in HCC, we identified circRNA-miRNA and miRNA-mRNA interactions by using the CircInteractome and miRwalk, respectively. Subsequently, 857 miRNA-associated differently expressed genes in HCC were selected for weighted gene co-expression network analysis. Module Eigengene turquoise with 423 genes was found to be significantly related to the survival time, pathology grade and TNM stage of HCC patients. Gene functional enrichment analysis showed that the 423 genes mainly functioned in DNA replication- and cell cycle-related biological processes and signalling cascades. Eighteen hubgenes (SMARCD1, CBX1, HCFC1, RBM12B, RCC2, NUP205, ECT2, PRIM2, RBM28, COPS7B, PRRC2A, GPR107, ANKRD52, TUBA1B, ATXN7L3, FUS, MCM8 and RACGAP1) associated with clinical outcomes of HCC patients were then identified. These findings showed that the crosstalk between hsa_circ₀₀₈₈₃₆₄ and hsa_circ₀₀₉₀₀₄₉ and their competing mRNAs may play important roles in HCC, providing interesting clues into the potential of circRNAs as therapeutic targets of NC in HCC. Show less
📄 PDF DOI: 10.1038/s41419-019-1890-9
CBX1

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

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

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

LINGO-1 shRNA Loaded by Pluronic F-127 Promotes Functional Recovery After Ventral Root Avulsion.

Lu Ding, Zhe Zhu, Yuhui Wang +9 more · 2019 · Tissue engineering. Part A · added 2026-04-24
Spinal root avulsion typically leads to massive motoneuron death and severe functional deficits of the target muscles. Multiple pathological factors such as severe neuron loss, induction of inhibitory Show more
Spinal root avulsion typically leads to massive motoneuron death and severe functional deficits of the target muscles. Multiple pathological factors such as severe neuron loss, induction of inhibitory molecules, and insufficient regeneration are responsible for the poor functional recovery. Leucine-rich repeat and immunoglobulin-like domain-containing Nogo receptor-interacting protein 1 (LINGO-1), a central nervous system (CNS)-specific transmembrane protein that is selectively expressed on neurons and oligodendrocytes, serves as a potent negative mediator of axonal regeneration and myelination in CNS injuries and diseases. Although accumulating evidence has demonstrated improvement in axonal regeneration and neurological functions by LINGO-1 antagonism in CNS damage, the possible effects of LINGO-1 in spinal root avulsion remain undiscovered. In this study, a LINGO-1 knockdown strategy using lentiviral vectors encoding LINGO-1 short hairpin interfering RNA (shRNA) delivered by the Pluronic F-127 (PF-127) hydrogel was described after brachial plexus avulsion (BPA). We provide evidence that following BPA and immediate reimplantation, transplantation of LINGO-1 shRNA lentiviral vectors encapsulated by PF-127 rescued the injured motoneurons, enhanced axonal outgrowth and myelination, rebuilt motor endplates, facilitated the reinnervation of terminal muscles, improved angiogenesis, and promoted recovery of avulsed forelimbs. Altogether, these data suggest that delivery of LINGO-1 shRNA by a gel scaffold is a potential therapeutic approach for root avulsion. Impact Statement In this study, we attempted transplantation of lentivirus (LV)/leucine-rich repeat and immunoglobulin-like domain-containing Nogo receptor-interacting protein 1 (LINGO-1)-short hairpin interfering RNA (shRNA) encapsulated by the Pluronic F-127 (PF-127) hydrogel into a brachial plexus avulsion (BPA)-reimplantation model. We found that administration of LV/LINGO-1 shRNA facilitates neuron survival and axonal regeneration, attenuates muscle atrophy and motor endplate (MEP) loss, enhances neovascularization, and promotes functional recovery in BPA rats. Co-transplantation of LV/LINGO-1 shRNA and gel reinforces the survival-promoting effect, axonal outgrowth, and angiogenesis in comparison with LV/LINGO-1 shRNA application alone. Our research provides evidence that LV /LINGO-1 shRNA delivered by PF-127 represents a new treatment strategy for BPA repair. Show less
no PDF DOI: 10.1089/ten.TEA.2018.0282
LINGO1

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

A transcriptome-wide association study of high-grade serous epithelial ovarian cancer identifies new susceptibility genes and splice variants.

Alexander Gusev, Kate Lawrenson, Xianzhi Lin +16 more · 2019 · Nature genetics · Nature · added 2026-04-24
We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relev Show more
We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relevant tissue types (N = 2,169) and the largest genome-wide association study available for HGSOC (N = 13,037 cases and 40,941 controls). We identified 25 transcriptome-wide association study significant genes, 7 at the junction level only, including LRRC46 at 19q21.32, (P = 1 × 10 Show less
📄 PDF DOI: 10.1038/s41588-019-0395-x
KANSL1

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

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

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

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

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

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

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

Promoter DNA hypermethylation - Implications for Alzheimer's disease.

Yiyuan Liu, Minghui Wang, Edoardo M Marcora +2 more · 2019 · Neuroscience letters · Elsevier · added 2026-04-24
Recent methylome-wide association studies (MWAS) in humans have solidified the concept that aberrant DNA methylation is associated with Alzheimer's disease (AD). We summarize these findings to improve Show more
Recent methylome-wide association studies (MWAS) in humans have solidified the concept that aberrant DNA methylation is associated with Alzheimer's disease (AD). We summarize these findings to improve the understanding of mechanisms governing DNA methylation pertinent to transcriptional regulation, with an emphasis of AD-associated promoter DNA hypermethylation, which establishes an epigenetic barrier for transcriptional activation. By considering brain cell type specific expression profiles that have been published only for non-demented individuals, we detail functional activities of selected neuron, microglia, and astrocyte-enriched genes (AGAP2, DUSP6 and GPR37L1, respectively), which are DNA hypermethylated at promoters in AD. We highlight future directions in MWAS including experimental confirmation, functional relevance to AD, cell type-specific temporal characterization, and mechanism investigation. Show less
📄 PDF DOI: 10.1016/j.neulet.2019.134403
DUSP6

A Compound Heterozygous Mutation of Lipase Maturation Factor 1 is Responsible for Hypertriglyceridemia of a Patient.

Yihui Liu, Jiang Xu, Wanyun Tao +2 more · 2019 · Journal of atherosclerosis and thrombosis · added 2026-04-24
Dyslipidemia is the most common lipid metabolism disorder in humans, and its etiology remains elusive. Hypertriglyceridemia (HTG) is a type of dyslipidemia that contributes to atherosclerosis and coro Show more
Dyslipidemia is the most common lipid metabolism disorder in humans, and its etiology remains elusive. Hypertriglyceridemia (HTG) is a type of dyslipidemia that contributes to atherosclerosis and coronary heart disease. Previous studies have demonstrated that mutations in lipoprotein lipase (LPL), apolipoprotein CII (APOC2), apolipoprotein AV (APOA5), glycosylphosphatidylinositol anchored high-density lipoprotein-binding protein 1 (GPIHBP1), lipase maturation factor 1(LMF1), and glycerol-3 phosphate dehydrogenase 1 (GPD1) are responsible for HTG by using genomic microarrays and next-generation sequencing. The aim of this study was to identify genetic lesions in patients with HTG. Our study included a family of seven members from Jiangsu province across three generations. The proband was diagnosed with severe HTG, with a plasma triglyceride level of 38.70 mmol/L. Polymerase chain reaction (PCR) and Sanger sequencing were performed to explore the possible causative gene mutations for this patient. Furthermore, we measured the post-heparin LPL and hepatic lipase (HL) activities using an antiserum inhibition method. A compound heterozygous mutation in the LMF1 gene (c.257C＞T/p.P86L and c.1184C＞T/p.T395I) was identified and co-segregated with the affected patient in this family. Both mutations were predicted to be deleterious by three bioinformatics programs (Polymorphism Phenotyping-2, Sorting Intolerant From Tolerant, and MutationTaster). The levels of the plasma post-heparin LPL and HL activities in the proband (57 and 177 mU/mL) were reduced to 24% and 75%, respectively, compared with those assayed in the control subject with normal plasma triglycerides. A compound heterozygous mutation of LMF1 was identified in the presenting patient with severe HTG. These findings expand on the spectrum of LMF1 mutations and contribute to the genetic diagnosis and counseling of families with HTG. Show less
📄 PDF DOI: 10.5551/jat.44537
APOA5

Isorhamnetin inhibited migration and invasion via suppression of Akt/ERK-mediated epithelial-to-mesenchymal transition (EMT) in A549 human non-small-cell lung cancer cells.

Wei Luo, Qingbin Liu, Nan Jiang +2 more · 2019 · Bioscience reports · added 2026-04-24
In the present study, we investigated the potential effects of Isorhamnetin on the growth and metastasis of A549 human lung cancer cells, as well as the underlying mechanism. Treatment with Isorhamnet Show more
In the present study, we investigated the potential effects of Isorhamnetin on the growth and metastasis of A549 human lung cancer cells, as well as the underlying mechanism. Treatment with Isorhamnetin exhibited a dose- and time-dependent inhibition on A549 cell proliferation. Furthermore, the cell adhesion and Transwell assay showed that treatment with Isorhamnetin (2.5, 5, and 10 μM) for 48 h resulted in a significant inhibition effect on cell adhesion, invasion and migration of A549 cells, depending on concentration, which was associated with the suppression of matrix metalloproteinase (MMP)-2 and MMP-9 activity and protein expression. Moreover, Isorhamnetin effectively suppressed the expressions of epithelial-to-mesenchymal transition (EMT) markers, as evidenced by the down-regulation of N-cadherin, vimentin and snail, as well as up-regulation of E-cadherin protein expression. Additionally, these inhibitions were mediated by interrupting AKT/ERK1/2 signaling pathways. Taken together, the results of the current study demonstrated that Isorhamnetin may become a good anti-metastastic agent against lung cancer A549 cell line by the suppression of EMT via interrupting Akt/ERK1/2 signaling pathway. Show less
no PDF DOI: 10.1042/BSR20190159
SNAI1

MAST3 modulates the inflammatory response and proliferation of fibroblast-like synoviocytes in rheumatoid arthritis.

Qingqing Xu, Suqin Yin, Yao Yao +10 more · 2019 · International immunopharmacology · Elsevier · added 2026-04-24
Via promoting synovitis, pannus growth and cartilage/bone destruction, fibroblast-like synovial cells (FLSs) play a significant role in the pathogenesis of rheumatoid arthritis (RA). In our study, rat Show more
Via promoting synovitis, pannus growth and cartilage/bone destruction, fibroblast-like synovial cells (FLSs) play a significant role in the pathogenesis of rheumatoid arthritis (RA). In our study, rats were induced with complete freund's adjuvant (CFA) to be animal models for studying the RA pathogenesis. Microtubule-associated Serine/Threonine-protein kinase 3 (MAST3) has been documented to play a critical role in regulating the immune response of IBD (Inflammatory bowel disease) and involved in the process of cytoskeleton organization, intracellular signal transduction and peptidyl-serine phosphorylation, but its role in the progression of RA remains unknown and is warranted for investigation. So, we tried our best to investigate the mechanism and signaling pathway of MAST3 in RA progression. In the synovial tissue and FLSs of AA rats, we have found that MAST3 was significantly up-regulated than normal. Furthermore, MAST3 overexpression could promote proliferation and inflammatory response of FLSs. In the aspect of mechanism, we discovered that the expression of MAST3 might involve in NF-κB signaling pathway in RA. On the whole, our results suggested that MAST3 might promote the proliferation and inflammation of FLSs by regulating NF-κB signaling pathway. Show less
no PDF DOI: 10.1016/j.intimp.2019.105900
MAST3

Identification of Differentially Expressed Genes and Pathways for Abdominal Fat Deposition in Ovariectomized and Sham-Operated Chickens.

Xiaopeng Mu, Xiaoyan Cui, Ranran Liu +7 more · 2019 · Genes · MDPI · added 2026-04-24
Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have Show more
Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have also been reported. In this study, the gene expression profiles of AF tissue in ovariectomized and sham-operated chickens were determined to identify differentially expressed genes (DEGs) and pathways to explore the molecular mechanisms underlying AF accumulation. Comparing the ovariectomized group and the sham-operated group, the abdominal fat weight (AFW) and abdominal fat percentage (AFP) were increased significantly ( Show less
📄 PDF DOI: 10.3390/genes10020155
CETP

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

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

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

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

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

Germ cell neoplasia in situ complicating 17β-hydroxysteroid dehydrogenase type 3 deficiency.

Lisal J Folsom, Mariam Hjaige, Jiayan Liu +2 more · 2019 · Molecular and cellular endocrinology · Elsevier · added 2026-04-24
17β-hydroxysteroid dehydrogenase type 3 (17βHSD3) deficiency is an autosomal recessive disorder of male sex development that results in defective testosterone biosynthesis. Although mutations in the c Show more
17β-hydroxysteroid dehydrogenase type 3 (17βHSD3) deficiency is an autosomal recessive disorder of male sex development that results in defective testosterone biosynthesis. Although mutations in the cognate HSD17B3 gene cause a spectrum of phenotypic manifestations, the majority of affected patients are genetic males having female external genitalia. Many cases do not present until puberty, at which time peripheral conversion of androgen precursors causes progressive virilization. Measurement of the testosterone-to-androstenedione ratio is useful to screen for 17βHSD3 deficiency, and genetic analysis can confirm the diagnosis. As some individuals with 17βHSD3 deficiency transition from a female sex assignment to identifying as males, providers should ensure stable gender identity prior to recommending irreversible treatments. Gonadectomy is indicated to prevent further virilization if a female gender identity is established. The risk of testicular neoplasia is unknown, a point which should be discussed if patients elect to transition into a male gender role. Show less
📄 PDF DOI: 10.1016/j.mce.2018.11.014
HSD17B12

[Screening of pathogenic genes in a Chinese familial dilated cardiomyopathy pedigree from Inner Mongolia].

X P Liu, Y B Feng, Y Zeng +7 more · 2019 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
no PDF DOI: 10.3760/cma.j.issn.0253-3758.2019.03.004
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

Berberine alleviates insulin resistance by reducing peripheral branched-chain amino acids.

Shi-Jun Yue, Juan Liu, Ai-Ting Wang +6 more · 2019 · American journal of physiology. Endocrinology and metabolism · added 2026-04-24
Increased circulating branched-chain amino acids (BCAAs) have been involved in the pathogenesis of obesity and insulin resistance (IR). However, evidence relating berberine (BBR), gut microbiota, BCAA Show more
Increased circulating branched-chain amino acids (BCAAs) have been involved in the pathogenesis of obesity and insulin resistance (IR). However, evidence relating berberine (BBR), gut microbiota, BCAAs, and IR is limited. Here, we showed that BBR could effectively rectify steatohepatitis and glucose intolerance in high-fat diet (HFD)-fed mice. BBR reorganized gut microbiota populations under both the normal chow diet (NCD) and HFD. Particularly, BBR noticeably decreased the relative abundance of BCAA-producing bacteria, including order Clostridiales; families Streptococcaceae, Clostridiaceae, and Prevotellaceae; and genera Streptococcus and Prevotella. Compared with the HFD group, predictive metagenomics indicated a reduction in the proportion of gut microbiota genes involved in BCAA biosynthesis but the enrichment genes for BCAA degradation and transport by BBR treatment. Accordingly, the elevated serum BCAAs of HFD group were significantly decreased by BBR. Furthermore, the Western blotting results implied that BBR could promote the BCAA catabolism in the liver and epididymal white adipose tissues of HFD-fed mice by activation of the multienzyme branched-chain α-ketoacid dehydrogenase complex (BCKDC), whereas by inhibition of the phosphorylation state of BCKDHA (E1α subunit) and branched-chain α-ketoacid dehydrogenase kinase (BCKDK). The ex vivo assay further confirmed that BBR could increase BCAA catabolism in both AML12 hepatocytes and 3T3-L1 adipocytes. Finally, data from healthy subjects and diabetics confirmed that BBR could improve glycemic control and modulate circulating BCAAs. Together, our findings clarified BBR improving IR associated not only with gut microbiota alteration in BCAA biosynthesis but also with BCAA catabolism in liver and adipose tissues. Show less
no PDF DOI: 10.1152/ajpendo.00256.2018
BCKDK

Disentangling the genetics of lean mass.

David Karasik, M Carola Zillikens, Yi-Hsiang Hsu +154 more · 2019 · The American journal of clinical nutrition · Oxford University Press · added 2026-04-24
David Karasik, M Carola Zillikens, Yi-Hsiang Hsu, Ali Aghdassi, Kristina Akesson, Najaf Amin, Inês Barroso, David A Bennett, Lars Bertram, Murielle Bochud, Ingrid B Borecki, Linda Broer, Aron S Buchman, Liisa Byberg, Harry Campbell, Natalia Campos-Obando, Jane A Cauley, Peggy M Cawthon, John C Chambers, Zhao Chen, Nam H Cho, Hyung Jin Choi, Wen-Chi Chou, Steven R Cummings, Lisette C P G M de Groot, Phillip L De Jager, Ilja Demuth, Luda Diatchenko, Michael J Econs, Gudny Eiriksdottir, Anke W Enneman, Joel Eriksson, Johan G Eriksson, Karol Estrada, Daniel S Evans, Mary F Feitosa, Mao Fu, Christian Gieger, Harald Grallert, Vilmundur Gudnason, Launer J Lenore, Caroline Hayward, Albert Hofman, Georg Homuth, Kim M Huffman, Lise B Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John-Olov Jansson, Toby Johnson, Reiner Biffar, Joanne M Jordan, Antti Jula, Magnus Karlsson, Kay-Tee Khaw, Tuomas O Kilpeläinen, Norman Klopp, Jacqueline S L Kloth, Daniel L Koller, Jaspal S Kooner, William E Kraus, Stephen Kritchevsky, Zoltán Kutalik, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente L Langdahl, Markus M Lerch, Joshua R Lewis, Christina Lill, Lars Lind, Cecilia Lindgren, Yongmei Liu, Gregory Livshits, Östen Ljunggren, Ruth J F Loos, Mattias Lorentzon, Jian'an Luan, Robert N Luben, Ida Malkin, Fiona E McGuigan, Carolina Medina-Gomez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Karl Michaëlsson, Braxton D Mitchell, Andrew P Morris, Leif Mosekilde, Maria Nethander, Anne B Newman, Jeffery R O'Connell, Ben A Oostra, Eric S Orwoll, Aarno Palotie, Munro Peacock, Markus Perola, Annette Peters, Richard L Prince, Bruce M Psaty, Katri Räikkönen, Stuart H Ralston, Samuli Ripatti, Fernando Rivadeneira, John A Robbins, Jerome I Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Sabine Schipf, Chan Soo Shin, Albert V Smith, Shad B Smith, Nicole Soranzo, Timothy D Spector, Alena Stancáková, Kari Stefansson, Elisabeth Steinhagen-Thiessen, Lisette Stolk, Elizabeth A Streeten, Unnur Styrkarsdottir, Karin M A Swart, Patricia Thompson, Cynthia A Thomson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Emmi Tikkanen, Gregory J Tranah, André G Uitterlinden, Cornelia M Van Duijn, Natasja M van Schoor, Liesbeth Vandenput, Peter Vollenweider, Henry Völzke, Jean Wactawski-Wende, Mark Walker, Nicholas J Wareham, Dawn Waterworth, Michael N Weedon, H-Erich Wichmann, Elisabeth Widen, Frances M K Williams, James F Wilson, Nicole C Wright, Laura M Yerges-Armstrong, Lei Yu, Weihua Zhang, Jing Hua Zhao, Yanhua Zhou, Carrie M Nielson, Tamara B Harris, Serkalem Demissie, Douglas P Kiel, Claes Ohlsson Show less
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce Show more
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection. In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass. Show less
no PDF DOI: 10.1093/ajcn/nqy272
MC4R