👤 Mingsong Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, 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

miR-30a regulates endothelial tip cell formation and arteriolar branching.

Qiu Jiang, Mariana Lagos-Quintana, Dong Liu +4 more · 2013 · Hypertension (Dallas, Tex. : 1979) · added 2026-04-24
Microvascular rarefaction increases vascular resistance and pressure in systemic arteries and is a hallmark of fixed essential hypertension. Preventing rarefaction by activation of angiogenic processe Show more
Microvascular rarefaction increases vascular resistance and pressure in systemic arteries and is a hallmark of fixed essential hypertension. Preventing rarefaction by activation of angiogenic processes could lower blood pressure. Endothelial tip cells in angiogenic sprouts direct branching of microvascular networks; the process is regulated by microRNAs, particularly the miR-30 family. We investigated the contribution of miR-30 family members in arteriolar branching morphogenesis via delta-like 4 (Dll4)-Notch signaling in a zebrafish model. The miR-30 family consists of 5 members (miR-30a-e). Loss-of-function experiments showed that only miR-30a reduced growth of intersegmental arterioles involving impaired tip cell function. Overexpression of miR-30a stimulated tip cell behavior resulting in augmented branching of intersegmental arterioles. In vitro and in vivo reporter assays showed that miR-30a directly targets the Notch ligand Dll4, a key inhibitor of tip cell formation. Coadministration of a Dll4 targeting morpholino in miR-30a morphants rescued the branching defects. Conversely, conditional overexpression of Notch intracellular domain restored arteriolar branching in miR-30a gain-of-function embryos. In human endothelial cells, loss of miR-30a increased DLL4 protein levels, activated Notch signaling as indicated in Notch reporter assays, and augmented Notch downstream effector, HEY2 and EFNB2 (ephrin-B2), expression. In spheroid assays, miR-30a loss- and gain-of-function affected tip cell behavior, consistent with miR-30a targeting Dll4. Our data suggest that miR-30a stimulates arteriolar branching by downregulating endothelial Dll4 expression, thereby controlling endothelial tip cell behavior. These findings could have relevance to the rarefaction process and, therefore, to hypertension. Show less
no PDF DOI: 10.1161/HYPERTENSIONAHA.113.01767
HEY2

SLC1A2 variant associated with essential tremor but not Parkinson disease in Chinese subjects.

Eng-King Tan, Jia-Nee Foo, Louis Tan +7 more · 2013 · Neurology · added 2026-04-24
Essential tremor (ET) is characterized by postural and action tremor.(1-3) A genome-wide association study (GWAS) identified a LINGO1 gene variant to be associated with ET.(4) Subsequent GWAS further Show more
Essential tremor (ET) is characterized by postural and action tremor.(1-3) A genome-wide association study (GWAS) identified a LINGO1 gene variant to be associated with ET.(4) Subsequent GWAS further identified an intronic variant (rs3794087) of the main glial glutamate transporter (SLC1A2) gene to be associated with ET with an odds ratio (OR) of approximately 1.4.(5) We conducted a case-control study to examine the SLC1A2 gene variant in an Asian cohort of ET. In addition, we also investigated the variant in patients with Parkinson disease (PD) because the GWAS LINGO1 variant has been implicated in both ET and PD and etiologic links between the conditions have been suggested.(6.) Show less
no PDF DOI: 10.1212/WNL.0b013e31828f1903
LINGO1

Microtubule Actin Cross-linking Factor 1 regulates cardiomyocyte microtubule distribution and adaptation to hemodynamic overload.

John T Fassett, Xin Xu, Dongmin Kwak +5 more · 2013 · PloS one · PLOS · added 2026-04-24
Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Fac Show more
Aberrant cardiomyocyte microtubule growth is a feature of pressure overload induced cardiac hypertrophy believed to contribute to left ventricular (LV) dysfunction. Microtubule Actin Cross-linking Factor 1 (MACF1/Acf7) is a 600 kd spectraplakin that stabilizes and guides microtubule growth along actin filaments. MACF1 is expressed in the heart, but its impact on cardiac microtubules, and how this influences cardiac structure, function, and adaptation to hemodynamic overload is unknown. Here we used inducible cardiac-specific MACF1 knockout mice (MACF1 KO) to determine the impact of MACF1 on cardiac microtubules and adaptation to pressure overload (transverse aortic constriction (TAC).In adult mouse hearts, MACF1 expression was low under basal conditions, but increased significantly in response to TAC. While MACF1 KO had no observable effect on heart size or function under basal conditions, MACF1 KO exacerbated TAC induced LV hypertrophy, LV dilation and contractile dysfunction. Interestingly, subcellular fractionation of ventricular lysates revealed that MACF1 KO altered microtubule distribution in response to TAC, so that more tubulin was associated with the cell membrane fraction. Moreover, TAC induced microtubule redistribution into this cell membrane fraction in both WT and MACF1 KO mice correlated strikingly with the level of contractile dysfunction (r(2) = 0.786, p<.001). MACF1 disruption also resulted in reduction of membrane caveolin 3 levels, and increased levels of membrane PKCα and β1 integrin after TAC, suggesting MACF1 function is important for spatial regulation of several physiologically relevant signaling proteins during hypertrophy. Together, these data identify for the first time, a role for MACF1 in cardiomyocyte microtubule distribution and in adaptation to hemodynamic overload. Show less
📄 PDF DOI: 10.1371/journal.pone.0073887
MACF1

Proteomics-based identification of tumor relevant proteins in lung adenocarcinoma.

Xin Zhou, Liyan Xue, Lihong Hao +6 more · 2013 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Lung cancer has the highest mortality rate among malignant tumors. Proteomics is a powerful tool to identify protein biomarkers. The identification of protein biomarkers associated with lung adenocarc Show more
Lung cancer has the highest mortality rate among malignant tumors. Proteomics is a powerful tool to identify protein biomarkers. The identification of protein biomarkers associated with lung adenocarcinoma would have significance for making prognoses and designing targeted therapies. In our study, we applied a two-dimensional difference gel electrophoresis approach coupled to a matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis for the identification of proteins differentially expressed between lung adenocarcinoma and the paired normal bronchial epithelial tissues derived from seven patients (four of them developed distant metastasis after operation). In addition, we chose two candidate proteins and examine their expression levels in lung adenocarcinoma and adjacent normal tissues using immunohistochemistry methods, and their expression levels in serum of patients and healthy donors by ELISA. In this study, 173 proteins were found to be differentially expressed (ratio>1.5 or<-1.5, P≤0.05), and 22 of them were identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Thirteen proteins were at lower levels in the lung adenocarcinoma group, while nine proteins were at higher abundance. Immunohistochemistry analysis confirmed the expression levels of the two candidate proteins. The differential expression of the candidate secreted protein in serum from lung adenocarcinoma samples and healthy controls was showed by ELISA. Our results demonstrated a differential protein expression pattern for lung adenocarcinoma compared with the paired normal bronchial epithelial tissues. Further functional validation of candidate proteins is ongoing and might provide new insights in lung adenocarcinoma. Show less
no PDF DOI: 10.1016/j.biopha.2013.06.005
MACF1

Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes.

A Albrechtsen, N Grarup, Y Li +105 more · 2013 · Diabetologia · Springer · added 2026-04-24
Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) Show more
Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits. Show less
📄 PDF DOI: 10.1007/s00125-012-2756-1
MACF1

The Association Study between Twenty One Polymorphisms in Seven Candidate Genes and Coronary Heart Diseases in Chinese Han Population.

Barrak F Alobeidy, Cong Li, Alya A Alzobair +4 more · 2013 · PloS one · PLOS · added 2026-04-24
Previous genome-wide association studies (GWAS) in multiple populations identified several genetic loci for coronary heart diseases (CHD). Here we utilized a 2-stage candidate gene association strateg Show more
Previous genome-wide association studies (GWAS) in multiple populations identified several genetic loci for coronary heart diseases (CHD). Here we utilized a 2-stage candidate gene association strategy in Chinese Han population to shed light on the putative association between several metabolic-related candidate genes and CHD. At the 1(st) stage, 190 patients with CHD and 190 controls were genotyped through the MassARRAY platform. At the 2(nd) stage, a larger sample including 400 patients and 392 controls was genotyped by the High Resolution Melt (HRM) method to confirm or rule out the associations with CHD. MLXIP expression level was quantified by the real time PCR in 65 peripheral blood samples. From the 21 studied single nucleotide polymorphisms (SNPs) of seven candidate genes: MLXIPL, MLXIP, MLX, ADIPOR1, VDR, SREBF1 and NR1H3, only one tag SNP rs4758685 (T→C) was found to be statistically associated with CHD (P-value = 0.02, Odds ratio (OR) of 0.83). After adjustment for the age, sex, lipid levels and diabetes, the association remained significant (P-value = 0.03). After adjustment for the hypertension, P-value became 0.20 although there was a significant difference in the allele distribution between the CHD patients with hypertension and the controls (P-value = 0.04, 406 vs 582). In conclusion, among the 21 tested SNPs, we identified a novel association between rs4758685 of MLXIP gene and CHD. The C allele of common variant rs4758685 interacted with hypertension, and was found to be protective against CHD in both allelic and genotypic models in Chinese Han population. Show less
📄 PDF DOI: 10.1371/journal.pone.0066976
MLXIPL

Mutation spectrum in a large cohort of unrelated Chinese patients with hypertrophic cardiomyopathy.

Wen Liu, Wenling Liu, Dayi Hu +10 more · 2013 · The American journal of cardiology · Elsevier · added 2026-04-24
Hypertrophic cardiomyopathy (HC) is a hereditary heterogeneous cardiovascular disorder. Existing data have been of predominantly Caucasian samples, and a large study is needed in Chinese population. T Show more
Hypertrophic cardiomyopathy (HC) is a hereditary heterogeneous cardiovascular disorder. Existing data have been of predominantly Caucasian samples, and a large study is needed in Chinese population. The present study was intended to explore the genetic basis and clinical characteristics correlated with different genotypes in a large cohort of Chinese patients. Direct gene sequencing of β-myosin heavy chain (MYH7), myosin binding protein-C (MYBPC3), and cardiac troponin T (TNNT2) was performed in 136 unrelated Chinese HC patients. Clinical evaluations were conducted. In total, 32 mutations were identified in 36 patients (27%), including 10 novel ones. Distribution of mutations was 56% (MYBPC3), 31% (MYH7), and 13% (TNNT2), respectively. Double mutations were identified in 3% patients. The occurrence of HC-associated sarcomeric mutations was associated with an earlier age of onset, increased left ventricular hypertrophy, a higher incidence of syncope, previous family history, and sudden cardiac death. No statistical difference was identified in patients carrying MYBPC3 and MYH7 mutations with regard to clinical characteristics and outcomes. Patients with double mutations were associated with malignant progression in the study. In conclusion, MYBPC3 is the most predominant gene in HC. Multiple mutations are common in MYH7, MYBPC3, and TNNT2. The present study suggests a large diversity of HC and a prognostic role of genotype. Show less
no PDF DOI: 10.1016/j.amjcard.2013.04.021
MYBPC3

Progress in the molecular genetics of hypertrophic cardiomyopathy: a mini-review.

Tao Tian, Yaxin Liu, Xianliang Zhou +1 more · 2013 · Gerontology · added 2026-04-24
Hypertrophic cardiomyopathy (HCM), which is characterized by unexplained and asymmetric left ventricular hypertrophy in the absence of other cardiac or systemic diseases, is an inherited cardiovascula Show more
Hypertrophic cardiomyopathy (HCM), which is characterized by unexplained and asymmetric left ventricular hypertrophy in the absence of other cardiac or systemic diseases, is an inherited cardiovascular disease and presents rising penetrance with aging. The purpose of this review is to offer an outline of recent progress in the molecular genetics of HCM and to discuss characteristics of elderly HCM patients. Studies were analyzed which included disease genes related to HCM, relationships between genotype and phenotype, potential pathogenesis of HCM, and the features of elderly patients with HCM. HCM is caused by mutations in genes encoding myofilament proteins of the sarcomere, Z-disc proteins, Ca2+ -handling proteins, and other proteins related to the sarcomere. Phenotypic manifestations of HCM are not just determined by these genes; modifying genes and epigenetic factors also contribute to the complexity of the HCM phenotype. The potential pathogenesis of HCM involves dominant negative function, an imbalance of myocardial energetic metabolism, and haploinsufficiency. Late-onset HCM presents its own features in the distribution of causal genes. Mutations in MYBPC3 may be the most common cause of delayed expression of HCM, and the sarcomere gene screen is most likely to be negative in elderly HCM patients. Despite progress in the identification of genetic causes and pathogenesis of HCM, there are still some questions that need to be better understood. It remains a great challenge to identify the cause of 50% of HCM cases in patients without an identified mutation. The application of a new genetic study technology may completely uncover the genetic background of these cases. In addition, the influences of causal mutations on the function and signaling of cardiocytes are expected to be elucidated further. Show less
no PDF DOI: 10.1159/000346146
MYBPC3

Multiple gene mutations, not the type of mutation, are the modifier of left ventricle hypertrophy in patients with hypertrophic cardiomyopathy.

Yubao Zou, Jizheng Wang, Xuan Liu +19 more · 2013 · Molecular biology reports · Springer · added 2026-04-24
Genotype-phenotype correlation of hypertrophic cardiomyopathy (HCM) has been challenging because of the genetic and clinical heterogeneity. To determine the mutation profile of Chinese patients with H Show more
Genotype-phenotype correlation of hypertrophic cardiomyopathy (HCM) has been challenging because of the genetic and clinical heterogeneity. To determine the mutation profile of Chinese patients with HCM and to correlate genotypes with phenotypes, we performed a systematic mutation screening of the eight most commonly mutated genes encoding sarcomere proteins in 200 unrelated Chinese adult patients using direct DNA sequencing. A total of 98 mutations were identified in 102 mutation carriers. The frequency of mutations in MYH7, MYBPC3, TNNT2 and TNNI3 was 26.0, 18.0, 4.0 and 3.5 % respectively. Among the 200 genotyped HCM patients, 83 harbored a single mutation, and 19 (9.5 %) harbored multiple mutations. The number of mutations was positively correlated with the maximum wall thickness. We found that neither particular gene nor specific mutation was correlated to clinical phenotype. In summary, the frequency of multiple mutations was greater in Chinese HCM patients than in the Caucasian population. Multiple mutations in sarcomere protein may be a risk factor for left ventricular wall thickness. Show less
no PDF DOI: 10.1007/s11033-012-2474-2
MYBPC3

Programmed cell death-4 deficiency prevents diet-induced obesity, adipose tissue inflammation, and insulin resistance.

Qun Wang, Zhaojing Dong, Xianglan Liu +6 more · 2013 · Diabetes · added 2026-04-24
Programmed cell death-4 (PDCD4), a selective protein translation inhibitor, has shown proinflammatory effect in some inflammatory diseases, but its roles in obesity remain unestablished. This study ai Show more
Programmed cell death-4 (PDCD4), a selective protein translation inhibitor, has shown proinflammatory effect in some inflammatory diseases, but its roles in obesity remain unestablished. This study aims to investigate the effects of PDCD4 on obesity, inflammation, and insulin resistance. Surprisingly, high-fat diet (HFD)-fed PDCD4-deficient (PDCD4(-/-)) mice exhibited an absolutely lean phenotype together with improved insulin sensitivity. Compared with wild-type obese mice, HFD-fed PDCD4(-/-) mice showed higher energy expenditure, lower epididymal fat weight, and reduced macrophage infiltration inflammatory cytokine secretion in white adipose tissue (WAT). Alleviated hepatic steatosis along with decreased plasma levels of triglyceride and cholesterol was also observed in these mice. Importantly, PDCD4 appeared to disturb lipid metabolism via inhibiting the expression of liver X receptor (LXR)-α, a master modulator of lipid homeostasis, which was elevated in HFD-fed PDCD4(-/-) mice accompanied by upregulation of its target genes and relieved endoplasmic reticulum stress in WAT. These data demonstrate that PDCD4 deficiency protects mice against diet-induced obesity, WAT inflammation, and insulin resistance through restoring the expression of LXR-α, thereby proposing PDCD4 as a potential target for treating obesity-associated diseases. Show less
no PDF DOI: 10.2337/db13-0097
NR1H3

Rice protein exerts a hypocholesterolemic effect through regulating cholesterol metabolism-related gene expression and enzyme activity in adult rats fed a cholesterol-enriched diet.

Lin Yang, Guo Han, Qiao-Hong Liu +4 more · 2013 · International journal of food sciences and nutrition · added 2026-04-24
The major aim of this study is to elucidate the hypocholesterolemic mechanism exerted by rice protein (RP) in adult rats under cholesterol-enriched dietary condition. Compared with casein, the cholest Show more
The major aim of this study is to elucidate the hypocholesterolemic mechanism exerted by rice protein (RP) in adult rats under cholesterol-enriched dietary condition. Compared with casein, the cholesterol levels in plasma and the liver were significantly reduced by RP, accompanying significant inhibition of cholesterol absorption. RP increased the activity and mRNA level of cholesterol 7α-hydroxylase, whereas acyl-CoA:cholesterol acyltransferase activity and gene expression were significantly depressed with consumption of RP. Neither the activity nor gene expression of 3-hydroxy-3-methylglutaryl coenzyme A reductase of RP differed from that of casein. The gene expression of the peroxisome proliferator-activated receptor α and liver X receptor α were significantly activated by consumption of RP. RP did not modify the mRNA level of sterol regulatory element-binding protein-2 with respect to casein. These results suggest RP can induce a cholesterol-lowering effect through modifying cholesterol metabolism-related gene expression and enzyme activity in adult rats. Show less
no PDF DOI: 10.3109/09637486.2013.804038
NR1H3

SIRT1 prevents atherosclerosis via liver‑X‑receptor and NF‑κB signaling in a U937 cell model.

Hai-Tao Zeng, Yu-Cai Fu, Wei Yu +4 more · 2013 · Molecular medicine reports · added 2026-04-24
Atherosclerosis is a chronic immunoinflammatory disease associated with blood lipid disorders. Previous studies in mice have demonstrated that liver X receptor (LXR)‑ATP‑binding cassette (ABC) A1/ABCG1 Show more
Atherosclerosis is a chronic immunoinflammatory disease associated with blood lipid disorders. Previous studies in mice have demonstrated that liver X receptor (LXR)‑ATP‑binding cassette (ABC) A1/ABCG1/C‑C chemokine receptor type 7 (CCR7) and nuclear factor κB (NF‑κB) signaling pathways are important for atherosclerotic plaque formation. In addition, Sirtuin 1 (SIRT1) has been reported as a key regulator in the protection from risk of atherosclerosis. However, the exact mechanism by which SIRT1 prevents atherosclerosis remains largely unknown. To explore the possible mechanisms, the expression of SIRT1 and the association between SIRT1, LXR and NF‑κB in the process of foam cell formation was investigated in an in vitro human mononuclear U937 cell line. Monocyte‑derived foam cells were induced by palmitate and Ox‑LDL treatment. Oil Red O staining revealed an accumulation of a large number of lipid droplets in foam cells. Results of reverse transcription polymerase chain reaction (RT-PCR) revealed that SIRT1 expression was downregulated during foam cell formation. In addition, the expression of LXRα and its targets, ABCA1, ABCG1 and CCR7, were downregulated. However, NF‑κB and its targets, tumor necrosis factor α (TNFα) and interleukin (IL)‑1β, were upregulated in foam cells. Following activation of SIRT1 by SRT1720, the expression of LXRα and its targets increased, whereas expression of NF‑κB and its targets decreased. Furthermore, the formation of foam cells was blocked. The SIRT1 inhibitor, nicotinamide, was found to eliminate the effects of SRT1720. Results of the present study indicate that SIRT1 may prevent the formation and progression of atherosclerosis by enhancing the LXR‑ABCA1/ABCG1/CCR7 and inhibiting the NF‑κB pathways. Show less
no PDF DOI: 10.3892/mmr.2013.1460
NR1H3

Neopterin negatively regulates expression of ABCA1 and ABCG1 by the LXRα signaling pathway in THP-1 macrophage-derived foam cells.

Jin-quan Yan, Chun-zhi Tan, Jin-hua Wu +8 more · 2013 · Molecular and cellular biochemistry · Springer · added 2026-04-24
To investigate the effects of neopterin on ABCA1 expression and cholesterol efflux in human THP-1 macrophage-derived foam cells, and to explore the role of the liver X receptor alpha (LXRα) involved. Show more
To investigate the effects of neopterin on ABCA1 expression and cholesterol efflux in human THP-1 macrophage-derived foam cells, and to explore the role of the liver X receptor alpha (LXRα) involved. In the present study, THP-1 cells were pre-incubated with ox-LDL to become foam cells. The protein and mRNA expression were examined by Western blot assays and real-time quantitative PCR, respectively. Liquid scintillation counting and high performance liquid chromatography assays were used to test cellular cholesterol efflux and cholesterol content. Neopterin decreased ABCA1 expression and cholesterol efflux in a time- and concentration-dependent manner in THP-1 macrophage-derived foam cells, and the LXRα siRNA can reverse the inhibitory effects induced by neopterin. Neoterin has a negative regulation on ABCA1 expression via the LXRα signaling pathway, which suggests the aggravated effects of neopterin on atherosclerosis. Show less
no PDF DOI: 10.1007/s11010-013-1634-6
NR1H3

Adiponectin increases macrophages cholesterol efflux and suppresses foam cell formation in patients with type 2 diabetes mellitus.

Min Wang, Duan Wang, Yuhua Zhang +3 more · 2013 · Atherosclerosis · Elsevier · added 2026-04-24
Low levels of blood adiponectin contribute to an increased risk of cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM). To determine the mechanism through which adiponectin d Show more
Low levels of blood adiponectin contribute to an increased risk of cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM). To determine the mechanism through which adiponectin deficiency mediates accelerated cardiovascular disease in patients with diabetes, we investigated the effects of adiponectin on macrophage cholesterol deposition. 35 diabetic patients and 35 nondiabetic healthy subjects were recruited in this study. Macrophages from patients with diabetes mellitus were cultured in adiponectin-free or adiponectin-supplemented media and exposed to oxidized low-density lipoprotein cholesterol (OxLDL). Adiponectin treatment markedly suppressed foam cell formation in OxLDL-treated macrophages from diabetic subjects only, which was mainly attributed to an increase in cholesterol efflux. Adiponectin treatment significantly increased ATP-binding cassette transporter (ABC) ABCG1 mRNA and protein levels but not ABCA1, without affecting protein expression of scavenger receptors, including scavenger receptor-A (SR-A) and CD36 in diabetics. Pharmacological or genetic inhibition of liver X receptor α (LXRα) blocks the adiponectin-mediated ABCG1 expression, suggesting that LXRα activation is necessary for the attenuation of lipid accumulation of macrophages by adiponectin. In addition, deletion of the adiponectin receptor (adipoR1) in macrophages from diabetic patients accelerated foam cell formation induced by OxLDL. Finally, a strong positive correlation was noted between decreased serum adiponectin levels and impaired cholesterol efflux capacity both before and after adjustment for HDL-C and ApoAI in diabetic patients (both P < 0.001). The present study identifies reduced adiopoR signaling as a critical mechanism underlying increased foam cell formation and accelerated cardiovascular disease in diabetic subjects. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2013.01.017
NR1H3

The tissue-specific RNA binding protein T-STAR controls regional splicing patterns of neurexin pre-mRNAs in the brain.

Ingrid Ehrmann, Caroline Dalgliesh, Yilei Liu +9 more · 2013 · PLoS genetics · PLOS · added 2026-04-24
The RNA binding protein T-STAR was created following a gene triplication 520-610 million years ago, which also produced its two parologs Sam68 and SLM-1. Here we have created a T-STAR null mouse to id Show more
The RNA binding protein T-STAR was created following a gene triplication 520-610 million years ago, which also produced its two parologs Sam68 and SLM-1. Here we have created a T-STAR null mouse to identify the endogenous functions of this RNA binding protein. Mice null for T-STAR developed normally and were fertile, surprisingly, given the high expression of T-STAR in the testis and the brain, and the known infertility and pleiotropic defects of Sam68 null mice. Using a transcriptome-wide search for splicing targets in the adult brain, we identified T-STAR protein as a potent splicing repressor of the alternatively spliced segment 4 (AS4) exons from each of the Neurexin1-3 genes, and exon 23 of the Stxbp5l gene. T-STAR protein was most highly concentrated in forebrain-derived structures like the hippocampus, which also showed maximal Neurexin1-3 AS4 splicing repression. In the absence of endogenous T-STAR protein, Nrxn1-3 AS4 splicing repression dramatically decreased, despite physiological co-expression of Sam68. In transfected cells Neurexin3 AS4 alternative splicing was regulated by either T-STAR or Sam68 proteins. In contrast, Neurexin2 AS4 splicing was only regulated by T-STAR, through a UWAA-rich response element immediately downstream of the regulated exon conserved since the radiation of bony vertebrates. The AS4 exons in the Nrxn1 and Nrxn3 genes were also associated with distinct patterns of conserved UWAA repeats. Consistent with an ancient mechanism of splicing control, human T-STAR protein was able to repress splicing inclusion of the zebrafish Nrxn3 AS4 exon. Although Neurexin1-3 and Stxbp5l encode critical synaptic proteins, T-STAR null mice had no detectable spatial memory deficits, despite an almost complete absence of AS4 splicing repression in the hippocampus. Our work identifies T-STAR as an ancient and potent tissue-specific splicing regulator that uses a concentration-dependent mechanism to co-ordinately regulate regional splicing patterns of the Neurexin1-3 AS4 exons in the mouse brain. Show less
no PDF DOI: 10.1371/journal.pgen.1003474
NRXN3

Association study of NRXN3 polymorphisms with schizophrenia and risperidone-induced bodyweight gain in Chinese Han population.

Xiaofeng Hu, Jishui Zhang, Chao Jin +16 more · 2013 · Progress in neuro-psychopharmacology & biological psychiatry · Elsevier · added 2026-04-24
Recent researches have implicated that mutations in the neurexin-3 (NRXN3) gene on chromosome 14q24.3-q31.1 might play a role in addiction, autism, and obesity. In order to explore the association of Show more
Recent researches have implicated that mutations in the neurexin-3 (NRXN3) gene on chromosome 14q24.3-q31.1 might play a role in addiction, autism, and obesity. In order to explore the association of NRXN3 polymorphisms with schizophrenia, we examined seven single nucleotide polymorphisms (SNPs) in NRXN3 spanning 1.33 Mb of this gene, in a Chinese Han sample of 1214 schizophrenic patients and 1517 healthy control subjects. Our results showed that three SNPs were associated with schizophrenia (rs7157669: A>C, p=0.006; rs724373: C>T, p=0.014; rs7154021: C>T, p=0.018). After being corrected for multiple tests, the association of rs7157669 remained significant but those for two others were modest. According to the linkage disequilibrium pattern, the 7 SNPs may construct 3 haplotype blocks. Several haplotypes were significantly associated with schizophrenia, constructed by rs11624704-rs7157669-rs724373 (AAC, p=0.003; ACT, p=0.007, both remained significant after permutation tests), rs7154021-rs7142344 (TT, p=0.024; CT, p=0.012), respectively. Among the patients, 326 ones at first onset have received 6-week monotherapy of risperidone. Further analyses showed that two SNPs were associated with percentage of bodyweight gain following a 6-week therapy of risperidone (rs11624704: p=0.03; rs7154021: p=0.008) and rs7154021 remained significant after permutation test. Our findings suggested that NRXN3 might represent a major susceptibility gene for schizophrenia and have a role in bodyweight gain related to therapy of risperidone in Chinese Han population. Show less
no PDF DOI: 10.1016/j.pnpbp.2012.12.007
NRXN3

Exome capture sequencing of adenoma reveals genetic alterations in multiple cellular pathways at the early stage of colorectal tumorigenesis.

Donger Zhou, Liu Yang, Liangtao Zheng +14 more · 2013 · PloS one · PLOS · added 2026-04-24
Most of colorectal adenocarcinomas are believed to arise from adenomas, which are premalignant lesions. Sequencing the whole exome of the adenoma will help identifying molecular biomarkers that can pr Show more
Most of colorectal adenocarcinomas are believed to arise from adenomas, which are premalignant lesions. Sequencing the whole exome of the adenoma will help identifying molecular biomarkers that can predict the occurrence of adenocarcinoma more precisely and help understanding the molecular pathways underlying the initial stage of colorectal tumorigenesis. We performed the exome capture sequencing of the normal mucosa, adenoma and adenocarcinoma tissues from the same patient and sequenced the identified mutations in additional 73 adenomas and 288 adenocarcinomas. Somatic single nucleotide variations (SNVs) were identified in both the adenoma and adenocarcinoma by comparing with the normal control from the same patient. We identified 12 nonsynonymous somatic SNVs in the adenoma and 42 nonsynonymous somatic SNVs in the adenocarcinoma. Most of these mutations including OR6X1, SLC15A3, KRTHB4, RBFOX1, LAMA3, CDH20, BIRC6, NMBR, GLCCI1, EFR3A, and FTHL17 were newly reported in colorectal adenomas. Functional annotation of these mutated genes showed that multiple cellular pathways including Wnt, cell adhesion and ubiquitin mediated proteolysis pathways were altered genetically in the adenoma and that the genetic alterations in the same pathways persist in the adenocarcinoma. CDH20 and LAMA3 were mutated in the adenoma while NRXN3 and COL4A6 were mutated in the adenocarcinoma from the same patient, suggesting for the first time that genetic alterations in the cell adhesion pathway occur as early as in the adenoma. Thus, the comparison of genomic mutations between adenoma and adenocarcinoma provides us a new insight into the molecular events governing the early step of colorectal tumorigenesis. Show less
no PDF DOI: 10.1371/journal.pone.0053310
NRXN3

Expression of autophagy and UPR genes in the developing brain during ethanol-sensitive and resistant periods.

Alexander Alimov, Haiping Wang, Mei Liu +4 more · 2013 · Metabolic brain disease · Springer · added 2026-04-24
Fetal alcohol spectrum disorders (FASD) results from ethanol exposure to the developing fetus and is the leading cause of mental retardation. FASD is associated with a broad range of neurobehavioral d Show more
Fetal alcohol spectrum disorders (FASD) results from ethanol exposure to the developing fetus and is the leading cause of mental retardation. FASD is associated with a broad range of neurobehavioral deficits which may be mediated by ethanol-induced neurodegeneration in the developing brain. An immature brain is more susceptible to ethanol neurotoxicity. We hypothesize that the enhanced sensitivity of the immature brain to ethanol is due to a limited capacity to alleviate cellular stress. Using a third trimester equivalent mouse model of ethanol exposure, we demonstrated that subcutaneous injection of ethanol induced a wide-spread neuroapoptosis in postnatal day 4 (PD4) C57BL/6 mice, but had little effect on the brain of PD12 mice. We analyzed the expression profile of genes regulating apoptosis, and the pathways of ER stress response (also known as unfolded protein response, UPR) and autophagy during these ethanol-sensitive and resistant periods (PD4 versus PD12) using PCR microarray. The expression of pro-apoptotic genes, such as caspase-3, was much higher on PD4 than PD12; in contrast, the expression of genes that regulate UPR and autophagy, such as atf6, atg4, atg9, atg10, beclin1, bnip3, cebpb, ctsb, ctsd, ctss, grp78, ire1α, lamp, lc3 perk, pik3c3, and sqstm1 was significantly higher on PD12 than PD4. These results suggest that the vulnerability of the immature brain to ethanol could result from high expression of pro-apoptotic proteins and a deficiency in the stress responsive system, such as UPR and autophagy. Show less
no PDF DOI: 10.1007/s11011-013-9430-2
PIK3C3

Control of stem cell homeostasis via interlocking microRNA and microProtein feedback loops.

Ronny Brandt, Yakun Xie, Thomas Musielak +5 more · 2013 · Mechanisms of development · Elsevier · added 2026-04-24
Stem cells in the shoot apex of plants produce cells required for the formation of new leaves. Adult leaves are composed of multiple tissue layers arranged along the dorso-ventral (adaxial/abaxial) ax Show more
Stem cells in the shoot apex of plants produce cells required for the formation of new leaves. Adult leaves are composed of multiple tissue layers arranged along the dorso-ventral (adaxial/abaxial) axis. Class III homeodomain leucine zipper (HD-ZIPIII) transcription factors play an important role in the set-up of leaf polarity in plants. Loss of HD-ZIPIII function results in strongly misshapen leaves and in severe cases fosters the consumption of the apical stem cells, thus causing a growth arrest in mutant plants. HD-ZIPIII mRNA is under tight control by microRNAs 165/166. In addition to the microRNA-action a second layer of regulation is established by LITTLE ZIPPER (ZPR)-type microProteins, which can interact with HD-ZIPIII proteins, forming attenuated protein complexes. Here we show that REVOLUTA (REV, a member of the HD-ZIPIII family) directly regulates the expression of ARGONAUTE10 (AGO10), ZPR1 and ZPR3. Because AGO10 was shown to dampen microRNA165/6 function, REV establishes a positive feedback loop on its own activity. Since ZPR-type microProteins are known to reduce HD-ZIPIII protein activity, REV concomitantly establishes a negative feedback loop. We propose that the interconnection of these microRNA/microProtein feedback loops regulates polarity set-up and stem cell activity in plants. Show less
no PDF DOI: 10.1016/j.mod.2012.06.007
ZPR1

Meta-analysis identifies common variants associated with body mass index in east Asians.

Wanqing Wen, Yoon-Shin Cho, Wei Zheng +61 more · 2012 · Nature genetics · Nature · added 2026-04-24
Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We perf Show more
Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We performed a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 east Asians, which was followed by in silico and de novo replication studies in 37,691 and 17,642 additional east Asians, respectively. We identified ten BMI-associated loci at genome-wide significance (P < 5.0 × 10(-8)), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR-QPCTL, ADCY3-DNAJC27, BDNF and MAP2K5) and three novel loci in or near the CDKAL1, PCSK1 and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a newly identified signal near PAX6, all of which were associated with BMI with P < 5.0 × 10(-7). Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations. Show less
📄 PDF DOI: 10.1038/ng.1087
GIPR

Replication of 13 obesity loci among Singaporean Chinese, Malay and Asian-Indian populations.

R Dorajoo, A I F Blakemore, X Sim +8 more · 2012 · International journal of obesity (2005) · Nature · added 2026-04-24
Recent genome-wide association studies (GWAS) have identified 38 obesity-associated loci among European populations. However, their contribution to obesity in other ethnicities is largely unknown. We Show more
Recent genome-wide association studies (GWAS) have identified 38 obesity-associated loci among European populations. However, their contribution to obesity in other ethnicities is largely unknown. We utilised five GWAS (N=10 482) from Chinese (three cohorts, including one with type 2 diabetes and another one of children), Malay and Indian ethnic groups from Singapore. Data sets were analysed individually and subsequently in combined meta-analysis for Z-score body-mass index (BMI) associations. Variants at the FTO locus showed the strongest associations with BMI Z-score after meta-analysis (P-values 1.16 × 10(-7)-7.95 × 10(-7)). We further detected associations with nine other index obesity variants close to the MC4R, GNPDA2, TMEM18, QPCTL/GIPR, BDNF, ETV5, MAP2K5/SKOR1, SEC16B and TNKS/MSRA loci (meta-analysis P-values ranging from 3.58 × 10(-4)-1.44 × 10(-2)). Three other single-nucleotide polymorphisms (SNPs) from CADM2, PTBP2 and FAIM2 were associated with BMI (P-value ≤ 0.0418) in at least one dataset. The neurotrophin/TRK pathway (P-value=0.029) was highlighted by pathway-based analysis of loci that had statistically significant associations among Singaporean populations. Our data confirm the role of FTO in obesity predisposition among Chinese, Malays and Indians, the three major Asian ethnic groups. We additionally detected associations for 12 obesity-associated SNPs among Singaporeans. Thus, it is likely that Europeans and Asians share some of the genetic predisposition to obesity. Furthermore, the neurotrophin/TRK signalling may have a central role for common obesity among Asians. Show less
no PDF DOI: 10.1038/ijo.2011.86
GIPR

Genome-wide association study of major depressive disorder: new results, meta-analysis, and lessons learned.

N R Wray, M L Pergadia, D H R Blackwood +29 more · 2012 · Molecular psychiatry · Nature · added 2026-04-24
Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and Show more
Major depressive disorder (MDD) is a common complex disorder with a partly genetic etiology. We conducted a genome-wide association study of the MDD2000+ sample (2431 cases, 3673 screened controls and >1 M imputed single-nucleotide polymorphisms (SNPs)). No SNPs achieved genome-wide significance either in the MDD2000+ study, or in meta-analysis with two other studies totaling 5763 cases and 6901 controls. These results imply that common variants of intermediate or large effect do not have main effects in the genetic architecture of MDD. Suggestive but notable results were (a) gene-based tests suggesting roles for adenylate cyclase 3 (ADCY3, 2p23.3) and galanin (GAL, 11q13.3); published functional evidence relates both of these to MDD and serotonergic signaling; (b) support for the bipolar disorder risk variant SNP rs1006737 in CACNA1C (P=0.020, odds ratio=1.10); and (c) lack of support for rs2251219, a SNP identified in a meta-analysis of affective disorder studies (P=0.51). We estimate that sample sizes 1.8- to 2.4-fold greater are needed for association studies of MDD compared with those for schizophrenia to detect variants that explain the same proportion of total variance in liability. Larger study cohorts characterized for genetic and environmental risk factors accumulated prospectively are likely to be needed to dissect more fully the etiology of MDD. Show less
📄 PDF DOI: 10.1038/mp.2010.109
ADCY3

The Arabidopsis APC4 subunit of the anaphase-promoting complex/cyclosome (APC/C) is critical for both female gametogenesis and embryogenesis.

Yanbing Wang, Yingnan Hou, Hongya Gu +4 more · 2012 · The Plant journal : for cell and molecular biology · Blackwell Publishing · added 2026-04-24
The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase that is involved in regulating cell-cycle progression. It has been widely studied in yeast and animal cells, but the function Show more
The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase that is involved in regulating cell-cycle progression. It has been widely studied in yeast and animal cells, but the function and regulation of the APC/C in plant cells are largely unknown. The Arabidopsis APC/C comprises at least 11 subunits, only a few of which have been studied in detail. APC4 is proposed to be a connector in the APC/C in yeast and animals. Here, we report the functional characterization of the Arabidopsis APC4 protein. We examined three heterozygous plant lines carrying apc4 alleles. These plants showed pleiotropic developmental defects in reproductive processes, including abnormal nuclear behavior in the developing embryo sac and aberrant cell division in embryos; these phenotypes differ from those reported for mutants of other subunits. Some ovules and embryos of apc4/+ plants also accumulated cyclin B protein, a known substrate of APC/C, suggesting a compromised function of APC/C. Arabidopsis APC4 was expressed in meristematic cells of seedlings, ovules in pistils and embryos in siliques, and was mainly localized in the nucleus. Additionally, the distribution of auxin was distorted in some embryos of apc4/+ plants. Our results indicate that Arabidopsis APC4 plays critical roles in female gametogenesis and embryogenesis, possibly as a connector in APC/C, and that regulation of auxin distribution may be involved in these processes. Show less
no PDF DOI: 10.1111/j.1365-313X.2011.04785.x
ANAPC4

Apolipoprotein AIV requires cholecystokinin and vagal nerves to suppress food intake.

Chunmin C Lo, Wolfgang Langhans, Maria Georgievsky +6 more · 2012 · Endocrinology · added 2026-04-24
Apolipoprotein AIV (apo AIV) and cholecystokinin (CCK) are gastrointestinal satiation signals that are stimulated by fat consumption. Previous studies have demonstrated that peripheral apo AIV cannot Show more
Apolipoprotein AIV (apo AIV) and cholecystokinin (CCK) are gastrointestinal satiation signals that are stimulated by fat consumption. Previous studies have demonstrated that peripheral apo AIV cannot cross the blood-brain barrier. In the present study, we hypothesized that peripheral apo AIV uses a CCK-dependent system and intact vagal nerves to relay its satiation signal to the hindbrain. To test this hypothesis, CCK-knockout (CCK-KO) mice and Long-Evan rats that had undergone subdiaphragmatic vagal deafferentation (SDA) were used. Intraperitoneal administration of apo AIV at 100 or 200 μg/kg suppressed food intake of wild-type (WT) mice at 30, 60, and 90 min. In contrast, the same dose did not reduce food intake in the CCK-KO mice. Blockade of the CCK 1 receptor by lorglumide, a CCK 1 receptor antagonist, attenuated apo AIV-induced satiation. Apo AIV at 100 μg/kg reduced food intake in SHAM rats but not in SDA rats. Furthermore, apo AIV elicited an increase in c-Fos-positive cells in the nucleus of the solitary tract (NTS), area postrema, dorsal motor nucleus of the vagus, and adjacent areas of WT mice but elicited only an attenuated increase in these same regions in CCK-KO mice. Apo AIV-induced c-Fos positive cells in the NTS and area postrema of WT mice were reduced by lorglumide. Lastly, apo AIV increased c-Fos positive cells in the NTS of SHAM rats but not in SDA rats. These observations imply that peripheral apo AIV requires an intact CCK system and vagal afferents to activate neurons in the hindbrain to reduce food intake. Show less
no PDF DOI: 10.1210/en.2012-1427
APOA4

Effect of peripheral administration of cholecystokinin on food intake in apolipoprotein AIV knockout mice.

Go Yoshimichi, Chunmin C Lo, Kellie L K Tamashiro +8 more · 2012 · American journal of physiology. Gastrointestinal and liver physiology · added 2026-04-24
Apolipoprotein AIV (apo AIV) and cholecystokinin (CCK) are satiation factors secreted by the small intestine in response to lipid meals. Apo AIV and CCK-8 has an additive effect to suppress food intak Show more
Apolipoprotein AIV (apo AIV) and cholecystokinin (CCK) are satiation factors secreted by the small intestine in response to lipid meals. Apo AIV and CCK-8 has an additive effect to suppress food intake relative to apo AIV or CCK-8 alone. In this study, we determined whether CCK-8 (1, 3, or 5 μg/kg ip) reduces food intake in fasted apo AIV knockout (KO) mice as effectively as in fasted wild-type (WT) mice. Food intake was monitored by the DietMax food system. Apo AIV KO mice had significantly reduced 30-min food intake following all doses of CCK-8, whereas WT mice had reduced food intake only at doses of 3 μg/kg and above. Post hoc analysis revealed that the reduction of 10-min and 30-min food intake elicited by each dose of CCK-8 was significantly larger in the apo AIV KO mice than in the WT mice. Peripheral CCK 1 receptor (CCK1R) gene expression (mRNA) in the duodenum and gallbladder of the fasted apo AIV KO mice was comparable to that in WT mice. In contrast, CCK1R mRNA in nodose ganglia of the apo AIV KO mice was upregulated relative to WT animals. Similarly, upregulated CCK1R gene expression was found in the brain stem of apo AIV KO mice by in situ hybridization. Although it is possible that the increased satiating potency of CCK in apo AIV KO mice is mediated by upregulation of CCK 1R in the nodose ganglia and nucleus tractus solitarius, additional experiments are required to confirm such a mechanism. Show less
no PDF DOI: 10.1152/ajpgi.00325.2010
APOA4

Proteomic identification of serum biomarkers for gastric cancer using multi-dimensional liquid chromatography and 2D differential gel electrophoresis.

Wentao Liu, Bingya Liu, Qu Cai +3 more · 2012 · Clinica chimica acta; international journal of clinical chemistry · Elsevier · added 2026-04-24
Early diagnosis and treatment of gastric cancer patients is essential for improving prognosis. However, no available serum-based test provides sufficient sensitivity or specificity for widespread use. Show more
Early diagnosis and treatment of gastric cancer patients is essential for improving prognosis. However, no available serum-based test provides sufficient sensitivity or specificity for widespread use. Therefore, in this study we aimed to identify cancer biomarkers in human sera using 2-dimensional difference gel electrophoresis (2D-DIGE), and to characterize protein biomarkers with tandem mass spectrometry. We compared the serum proteomic profiles of 20 gastric cancer patients and 10 healthy volunteers. Serum samples were first chromatographed using an immunoaffinity high-performance liquid chromatography (HPLC) column to selectively remove albumin, immunoglobulins, transferrin, haptoglobin, and antitrypsin. Differential protein analysis was then performed using DIGE. Significantly increased and decreased protein spot features were excised, trypsin digested, and analyzed by tandem matrix-assisted laser desorption/ionization (MALDI) time of flight (TOF)/TOF and a linear trap quadrupole (LTQ) mass spectrometer. Seventeen protein spot features were significantly increased and 7 were significantly decreased in cancer serum samples compared to healthy controls. We identified 7 unique proteins that were upregulated, including plasminogen, apolipoprotein A-IV, Kininogen-1, complex-forming glycoprotein HC, complement component C4A, apolipoprotein J, and clusterin, and 5 that were decreased. These results suggest that the combination of multi-dimensional HPLC and 2D-DIGE provides a valuable tool for serum proteomics in gastric cancer. Show less
no PDF DOI: 10.1016/j.cca.2012.03.003
APOA4

Proteomic analysis of amniotic fluid of pregnant rats with spina bifida aperta.

Liping Shan, Yang Fan, Hui Li +4 more · 2012 · Journal of proteomics · Elsevier · added 2026-04-24
Congenital spina bifida aperta is a common congenital malformation in children and has an incidence of 1‰ to 5‰ in China. However, we currently lack specific biomarkers for screening or prenatal diagn Show more
Congenital spina bifida aperta is a common congenital malformation in children and has an incidence of 1‰ to 5‰ in China. However, we currently lack specific biomarkers for screening or prenatal diagnosis and there is no method to entirely cure or prevent such defects. In this study, we used two-dimensional gel electrophoresis (2-DE)/mass spectrometry (MS) to characterize differentially expressed proteins in amniotic-fluid samples (AFSs) of embryonic day (E) 17.5 rat fetuses with spina bifida aperta induced by retinoic acid (RA). We identified five proteins differentially expressed in AFSs of spina bifida aperta, including three upregulated proteins (transferrin, alpha-1 antiproteinase and signal recognition particle receptor, B subunit [SRPRB] 55 kDa), two downregulated proteins (apolipoprotein A IV [APO A4] and Srprb 77 kDa). Specifically, we found 11 alpha-1 fetoprotein (AFP) fragments that were downregulated and 35 AFP fragments that were upregulated in AFSs from embryos with spina bifida aperta. Of the downregulated AFP fragments, 72.7% (8/11) were confined to the AFP N-terminus (amino acids [aas] 25-440) and 77.1% (27/35) of upregulated AFP fragments were confined to the AFP C-terminus (aas 340-596). We also confirmed APO A4 and AFP by immunoblot analysis. This is the first comparative proteomic study of AFSs from rat fetuses with spina bifida aperta. We demonstrate proteomic alterations in the AFS of spina bifida aperta, which may provide new insights in neural tube defects and contribute to the prenatal screening. Show less
no PDF DOI: 10.1016/j.jprot.2011.10.033
APOA4

Apolipoprotein a5 gene polymorphism and risk for metabolic syndrome: a meta-analysis.

Cun-Fei Liu, Qun-Fang Yang, Xing-Lin Chen +1 more · 2012 · Genetic testing and molecular biomarkers · added 2026-04-24
Many studies have focused on the association between the apolipoprotein A5 (ApoA5) polymorphism and the risk of metabolic syndrome (MetS). However, these studies drew inconsistent conclusions. The aim Show more
Many studies have focused on the association between the apolipoprotein A5 (ApoA5) polymorphism and the risk of metabolic syndrome (MetS). However, these studies drew inconsistent conclusions. The aim of this study was to evaluate the exact association between the ApoA5 polymorphism and MetS in a large-scale meta-analysis. The PubMed, Embase, and Science Citation Index (ISI Web of Science) databases were searched to collect all publications on the association between the ApoA5 polymorphism and MetS. Two common variants of ApoA5 (namely -1131T>C in the promoter region and c.56C>G in the coding region) with the risk of MetS were analyzed. The overall odd ratios (ORs) and 95% confidence intervals (CIs) for -1131T>C (CC+TC) versus TT genotype and c.C56G (GG+GC) versus CC were assessed between the MetS and control group. Subgroup analysis was further performed by ethnicity. The meta-analysis was performed by Stata11.0. Twelve studies from 10 publications were chosen in our meta-analysis. The combined results showed that C allele carriers (CC+TC) of -1131T>C had a significantly higher risk of MetS for the overall (OR=1.32; 95% CI: 1.14-1.53; p=0.000) with moderate heterogeneity (I2=54.9%, p=0.014). Subgroup analysis was further performed according to ethnicity, and the association was still significant in Asians (OR=1.42; 95% CI: 1.25-1.62; p=0.000), but not in white populations (OR=1.25; 95% CI: 0.97-1.61; p=0.087). When analyzing the association between c.C56G and MetS, the G allele carrier (GG+GC) genotype significantly increased the risk of MetS (OR=1.32; 95% CI: 1.15-1.50; p=0.000) in white populations. No significant publication bias was observed in either -1131T>C or c.C56G. Our study suggested that the ApoA5 -1131T>C polymorphism was significantly associated with the risk of MetS in Asians, but not in white populations. However, the c.C56G polymorphism was significantly associated with MetS in white populations. Show less
no PDF DOI: 10.1089/gtmb.2012.0183
APOA5

Apolipoprotein A5 internalized by human adipocytes modulates cellular triglyceride content.

Xiao-Yan Zheng, Shui-ping ZHAO, Bi-Lian Yu +2 more · 2012 · Biological chemistry · added 2026-04-24
Apolipoprotein A5 (apoA5), an important determinant of plasma triglyceride (TG) levels, has been recently reported to modulate TG metabolism in hepatocytes. In this study, we investigated whether apoA Show more
Apolipoprotein A5 (apoA5), an important determinant of plasma triglyceride (TG) levels, has been recently reported to modulate TG metabolism in hepatocytes. In this study, we investigated whether apoA5 can be internalized by adipocytes and regulate cellular TG storage. Human preadipocytes, derived from subcutaneous adipose tissue of patients undergoing abdominal surgery, were differentiated into mature adipocytes. Pulse-chase experiments revealed that apoA5 was internalized into human adipocytes, and ∼70% of the apoA5 internalized during the pulse remained intracellular within a 24-h chase, while 30% was degraded. Preincubation with heparin and the receptor-associated protein, both of which prevented the apoA5 interaction with members of the low-density lipoprotein receptor gene family, markedly reduced the uptake of apoA5 by 61% and 52%, respectively, which were subsequently confirmed by Western blot analysis. Using confocal microscopy, we demonstrated that labeled apoA5 surrounded lipid droplets in human adipocytes and colocalized with the known lipid droplet protein perilipin. Importantly, treatment of adipocytes with apoA5 significantly decreased cellular TG storage. In conclusion, apoA5 can be internalized by human adipocytes and may act as a novel regulator to control TG storage in human adipocytes. Show less
no PDF DOI: 10.1515/hsz-2011-0259
APOA5

Rapid genotyping of APOA5 -1131T>C polymorphism using high resolution melting analysis with unlabeled probes.

Song-Mei Liu, Feng-Xia Xu, Fan Shen +1 more · 2012 · Gene · Elsevier · added 2026-04-24
The APOA5 -1131 T/C polymorphism (rs662799) exhibits a very strong association with elevated TG levels in different racial groups. High resolution melting (HRM) analysis with the use of unlabeled prob Show more
The APOA5 -1131 T/C polymorphism (rs662799) exhibits a very strong association with elevated TG levels in different racial groups. High resolution melting (HRM) analysis with the use of unlabeled probes has shown to be a convenient and reliable tool to genotyping, but not yet been used for detecting rs662799 polymorphism. We applied the unlabeled probe HRM analysis and direct DNA sequencing to assay the -1131T>C SNP in 130 cases DNA samples blindly. This HRM analysis can be completed in <3 min for each sample. The two melting peaks were displayed at 66.1±0.4°C for CC homozygote and 68.7±0.2°C for TT homozygote; TC heterozygote showed the both melting peaks. The genotyping results by HRM method were completely concordant with direct DNA sequencing. The distribution of CC, TC, and TT genotypes for the -1131T>C SNP was 9.2, 49.2, and 41.5%, respectively. This assay was sensitive enough to detect C allele down to 20% and 10% for T allele. The limit of detection for C and T allele was 6.2 and 2.5 ng/μL DNA, respectively. The developed unlabeled probe HRM method provides an alternative mean to detect ApoA5 -1131T>C SNP rapidly and accurately. Show less
no PDF DOI: 10.1016/j.gene.2012.02.025
APOA5