👤 Haoting Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, Zhezhe Chen, Zhi Bin Chen, Zhi Chen, Zhi-Hao Chen, Zhi-bin Chen, Zhi-zhe Chen, Zhiang Chen, Zhichuan Chen, Zhifeng Chen, Zhigang Chen, Zhigeng Chen, Zhiguo Chen, Zhihai Chen, Zhihang Chen, Zhihao Chen, Zhiheng Chen, Zhihong Chen, Zhijian Chen, Zhijian J Chen, Zhijing Chen, Zhijun Chen, Zhimin Chen, Zhinan Chen, Zhiping Chen, Zhiqiang Chen, Zhiquan Chen, Zhishi Chen, Zhitao Chen, Zhiting Chen, Zhiwei Chen, Zhixin Chen, Zhixuan Chen, Zhixue Chen, Zhiyong Chen, Zhiyu Chen, Zhiyuan Chen, Zhiyun Chen, Zhizhong Chen, Zhong Chen, Zhongbo Chen, Zhonghua Chen, Zhongjian Chen, Zhongliang Chen, Zhongxiu Chen, Zhongzhu Chen, Zhou Chen, Zhouji Chen, Zhouliang Chen, Zhoulong Chen, Zhouqing Chen, Zhuchu Chen, Zhujun Chen, Zhuo Chen, Zhuo-Yuan Chen, ZhuoYu Chen, Zhuohui Chen, Zhuojia Chen, Zi-Jiang Chen, Zi-Qing Chen, Zi-Yang Chen, Zi-Yue Chen, Zi-Yun Chen, Zian Chen, Zifan Chen, Zihan Chen, Zihang Chen, Zihao Chen, Zihe Chen, Zihua Chen, Zijie Chen, Zike Chen, Zilin Chen, Zilong Chen, Ziming Chen, Zinan Chen, Ziqi Chen, Ziqing Chen, Zitao Chen, Zixi Chen, Zixin Chen, Zixuan Chen, Ziying Chen, Ziyuan Chen, Zoe Chen, Zongming E Chen, Zongnan Chen, Zongyou Chen, Zongzheng Chen, Zugen Chen, Zuolong Chen
articles
Yao Hu, Huaixing Li, Ling Lu +11 more · 2016 · Human molecular genetics · Oxford University Press · added 2026-04-24
Epidemiological studies suggest that levels of n-3 and n-6 long-chain polyunsaturated fatty acids are associated with risk of cardio-metabolic outcomes across different ethnic groups. Recent genome-wi Show more
Epidemiological studies suggest that levels of n-3 and n-6 long-chain polyunsaturated fatty acids are associated with risk of cardio-metabolic outcomes across different ethnic groups. Recent genome-wide association studies in populations of European ancestry have identified several loci associated with plasma and/or erythrocyte polyunsaturated fatty acids. To identify additional novel loci, we carried out a genome-wide association study in two population-based cohorts consisting of 3521 Chinese participants, followed by a trans-ethnic meta-analysis with meta-analysis results from 8962 participants of European ancestry. Four novel loci (MYB, AGPAT4, DGAT2 and PPT2) reached genome-wide significance in the trans-ethnic meta-analysis (log10(Bayes Factor) ≥ 6). Of them, associations of MYB and AGPAT4 with docosatetraenoic acid (log10(Bayes Factor) = 11.5 and 8.69, respectively) also reached genome-wide significance in the Chinese-specific genome-wide association analyses (P = 4.15 × 10(-14) and 4.30 × 10(-12), respectively), while associations of DGAT2 with gamma-linolenic acid (log10(Bayes Factor) = 6.16) and of PPT2 with docosapentaenoic acid (log10(Bayes Factor) = 6.24) were nominally significant in both Chinese- and European-specific genome-wide association analyses (P ≤ 0.003). We also confirmed previously reported loci including FADS1, NTAN1, NRBF2, ELOVL2 and GCKR. Different effect sizes in FADS1 and independent association signals in ELOVL2 were observed. These results provide novel insight into the genetic background of polyunsaturated fatty acids and their differences between Chinese and European populations. Show less
no PDF DOI: 10.1093/hmg/ddw002
FADS1
Qin Zhou, Chi Yang, Min-Jie Chen +1 more · 2016 · Molecular and clinical oncology · added 2026-04-24
Exostosin glycosyltransferase (EXT) 1 and EXT2 have been identified as causative genes in osteochondroma; however, it is not known whether these genes are also involved in condylar osteochondromas. Th Show more
Exostosin glycosyltransferase (EXT) 1 and EXT2 have been identified as causative genes in osteochondroma; however, it is not known whether these genes are also involved in condylar osteochondromas. The aim of this study was to identify EXT1 and EXT2 mutations in patients with non-hereditary osteochondromas of the mandibular condyle. DNA was obtained from resected tissues (cartilage cap) of 12 patients with solitary condylar osteochondromas. The exons, 3',5'-untranslated regions and intron-exon boundaries of EXT1 and EXT2 were amplified by polymerase chain reaction and the products were sequenced directly. Through direct sequencing, four genetic variations of EXT1 in 4 cases and three variations of EXT2 in 5 cases were identified. The intronic alteration of the EXT2 gene, occurring in 2 cases, was novel, whereas the other alterations had been previously reported. Nonsense somatic mutations were detected in tumor DNA. Our study extended the mutational spectrum in EXT1 and EXT2 and may facilitate a better understanding of the pathophysiology of condylar osteochondromas. Show less
no PDF DOI: 10.3892/mco.2016.955
EXT1
Y Chen, Y W Gong, X Q Zhou +3 more · 2016 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
To explore the association between the tag single nucleotide polymorphism (tag SNP) of the adenylyl cyclase 3 (ADCY3) and the essential hypertension (EH). From April to July 2013, a total of 1 061 sub Show more
To explore the association between the tag single nucleotide polymorphism (tag SNP) of the adenylyl cyclase 3 (ADCY3) and the essential hypertension (EH). From April to July 2013, a total of 1 061 subjects diagnosed with EH and 1 218 control subjects were recruited from Ningbo, Zhejiang Province. Information was collected by face-to-face interview. Twelve tag SNPs were detected by ligase detection reaction technique. After adjusted for age, gender, body mass index and other related factors, logistic regression analysis showed that 3 loci (rs11689546, rs7593130, rs2241759)were associated with EH. AG genotype of rs11689546 was associated with 0.494 times lower risk of EH (OR=0.494, 95%CI 0.246-0.993; compared with AA genotype). CT genotype of rs7593130 was associated with 1.596 times higher risk of EH (OR=1.596, 95%CI 1.009-2.524; compared with TT genotype), and CT/CC genotype of rs7593130 was associated with 1.627 times higher risk of EH (OR=1.627, 95%CI 1.034-2.559; compared with TT genotype). AG genotype of rs2241759 was associated with 0.669 times lower risk of EH (OR=0.669, 95%CI 0.503-0.891; compared with AA genotype), and CT/CC genotype of rs2241759 was associated with 0.687 times lower risk of EH (OR=0.687, 95%CI 0.518-0.911; compared with TT genotype). The polymorphisms of ADCY3 are associated with lower (G allele of the rs11689546 locus and G allele of the rs2241759 locus) or higher (C allele of the rs7593130 locus) risk of essential hypertension. Show less
no PDF DOI: 10.3760/cma.j.issn.0253-3758.2016.07.008
ADCY3
Daqian Xu, Zheng Wang, Yan Chen · 2016 · Autophagy · Taylor & Francis · added 2026-04-24
As a central node of the macroautophagy/autophagy process, the BECN1/Beclin1-PIK3C3/VPS34 complex participates in different steps of autophagy by interacting with multiple molecules. The ATG14-associa Show more
As a central node of the macroautophagy/autophagy process, the BECN1/Beclin1-PIK3C3/VPS34 complex participates in different steps of autophagy by interacting with multiple molecules. The ATG14-associated PIK3C3 complex is involved in autophagy initiation, whereas the UVRAG-associated complex mainly modulates autophagosome maturation and endosome fusion. However, the molecular mechanism that coordinates the sequential execution of the autophagy program remains unknown. We have recently discovered that a Golgi-resident protein, PAQR3, regulates autophagy initiation as it preferentially facilitates the formation of the ATG14-linked PIK3C3 complex instead of the UVRAG-associated complex. Upon glucose starvation, AMPK directly phosphorylates T32 of PAQR3, which is crucial for the activation of the ATG14-associated class III PtdIns3K. Furthermore, Paqr3-deleted mice have a deficiency in exercise-induced autophagy as well as behavioral disorders. Thus, this work not only uncovers the regulatory mechanism of PAQR3 on autophagy initiation, but also provides a potential candidate therapeutic target for neurodegenerative diseases. Show less
no PDF DOI: 10.1080/15548627.2016.1163459
PIK3C3
Rui-Nan Zhang, Rui-Dan Zheng, Yu-Qiang Mi +6 more · 2016 · Digestive diseases and sciences · Springer · added 2026-04-24
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The Show more
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The aim of this study was to investigate the relationship between other polymorphisms of APOC3 and NAFLD in Chinese. Fifty-nine liver biopsy-proven NAFLD patients and 72 healthy control subjects were recruited to a cohort representing Chinese Han population. The polymorphisms in the exons and flanking regions of APOC3 and patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 polymorphisms were genotyped. Among the five SNPs (rs4225, rs4520, rs5128, rs2070666, and rs2070667) in APOC3, only rs2070666 (c.179 + 62 T/A) was significantly different in genotype and allele frequency (both p < 0.01) between groups of NAFLD and control. After adjusting for sex, age, serum triglycerides, total cholesterol, body mass index, and the PNPLA3 rs738409 polymorphism, the APOC3 rs2070666 A allele was an independent risk factor for NAFLD with an odds ratio (OR) of 3.683 and 95 % confidence interval (CI) of 1.037-13.084. The APOC3 rs2070666 A allele was linked to the fourth quartile of the controlled attenuation parameter values (OR 2.769, 95 % CI 1.002-7.651) in 131 subjects, and also linked to the significant histological steatosis (OR 4.986, 95 % CI 1.020-24.371), but neither to liver stiffness measurement values nor to hepatic histological activity and fibrosis in NAFLD patients. The APOC3 rs2070666 A allele is a risk factor for NAFLD independent of obesity, dyslipidemia, and PNPLA3 rs738409, and it might contribute to increased liver fat content in Chinese Han population. Show less
no PDF DOI: 10.1007/s10620-016-4120-7
APOC3
Zong-Bo Wei, Ye-Feng Yuan, Florence Jaouen +8 more · 2016 · Autophagy · Taylor & Francis · added 2026-04-24
Searching for new regulators of autophagy involved in selective dopaminergic (DA) neuron loss is a hallmark in the pathogenesis of Parkinson disease (PD). We here report that an endoplasmic reticulum Show more
Searching for new regulators of autophagy involved in selective dopaminergic (DA) neuron loss is a hallmark in the pathogenesis of Parkinson disease (PD). We here report that an endoplasmic reticulum (ER)-associated transmembrane protein SLC35D3 is selectively expressed in subsets of midbrain DA neurons in about 10% TH (tyrosine hydroxylase)-positive neurons in the substantia nigra pars compacta (SNc) and in about 22% TH-positive neurons in the ventral tegmental area (VTA). Loss of SLC35D3 in ros (roswell mutant) mice showed a reduction of 11.9% DA neurons in the SNc and 15.5% DA neuron loss in the VTA with impaired autophagy. We determined that SLC35D3 enhanced the formation of the BECN1-ATG14-PIK3C3 complex to induce autophagy. These results suggest that SLC35D3 is a new regulator of tissue-specific autophagy and plays an important role in the increased autophagic activity required for the survival of subsets of DA neurons. Show less
no PDF DOI: 10.1080/15548627.2016.1179402
PIK3C3
Ruiyang Zhang, Congle Shen, Lijun Zhao +4 more · 2016 · International journal of cancer · Wiley · added 2026-04-24
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possi Show more
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possible role for such integration-targeted cellular genes (ITGs) in cervical carcinogenesis. Therefore, a comprehensive analysis of HPV integration events was undertaken using data collected from 14 publications, with 499 integration loci on human chromosomes included. It revealed that HPV DNA preferred to integrate into intragenic regions and gene-dense regions of human chromosomes. Intriguingly, the host cellular genes nearby the integration sites were found to be more transcriptionally active compared with control. Furthermore, analysis of the integration sites in the human genome revealed that there were several integration hotspots although all chromosomes were represented. The ITGs identified were found to be enriched in tumor-related terms and pathways using gene ontology and KEGG analysis. In line with this, three of six ITGs tested were found aberrantly expressed in cervical cancer tissues. Among them, it was demonstrated for the first time that MPPED2 could induce HeLa cell and SiHa cell G1/S transition block and cell proliferation retardation. Moreover, "knocking out" the integrated HPV fragment in HeLa cell line decreased expression of MYC located ∼500 kb downstream of the integration site, which provided the first experimental evidence supporting the hypothesis that integrated HPV fragment influence MYC expression via long distance chromatin interaction. Overall, the results of this comprehensive analysis implicated that dysregulation of ITGs caused by viral integration as possibly having an etiological involvement in cervical carcinogenesis. Show less
📄 PDF DOI: 10.1002/ijc.29872
MPPED2
Jing Qu, Min Song, Jian Xie +9 more · 2016 · Molecular and cellular biochemistry · Springer · added 2026-04-24
Many studies have explored whether the Notch signaling pathway has a tumor-suppressive or an oncogenic role in various tumors; however, the role of the Notch signaling pathway in salivary adenoid cyst Show more
Many studies have explored whether the Notch signaling pathway has a tumor-suppressive or an oncogenic role in various tumors; however, the role of the Notch signaling pathway in salivary adenoid cystic carcinoma (SACC) is still unknown. In this study, we attempt to define the role of Notch2 signaling in cell growth, invasion, and migration in SACC. We compared Notch2 expression in clinical SACC samples with that of normal samples by using immunohistochemical staining. Then, we down-regulated Notch2 expression to observe the effect of Notch2 on proliferation, invasion, migration, and the expression of known target genes of Notch signal pathway. According to our results, Notch2 expression was higher in SACC tissues compared with normal tissues. Knockdown of Notch2 inhibited cell proliferation, invasion, and migration in vitro and down-regulated the expression of HEY2 and CCND1. The results of this study suggest that Notch2 has an essential role in the cell growth, invasion, and migration of SACC. Notch2 may therefore be a potential target gene for the treatment of SACC by interfering with cell growth and metastasis. Show less
no PDF DOI: 10.1007/s11010-015-2575-z
HEY2
Wangshu Qin, Xinzhi Li, Liwei Xie +9 more · 2016 · Nucleic acids research · Oxford University Press · added 2026-04-24
Long non-coding RNAs (lncRNAs) have been shown to be critical biomarkers or therapeutic targets for human diseases. However, only a small number of lncRNAs were screened and characterized. Here, we id Show more
Long non-coding RNAs (lncRNAs) have been shown to be critical biomarkers or therapeutic targets for human diseases. However, only a small number of lncRNAs were screened and characterized. Here, we identified 15 lncRNAs, which are associated with fatty liver disease. Among them, APOA4-AS is shown to be a concordant regulator of Apolipoprotein A-IV (APOA4) expression. APOA4-AS has a similar expression pattern with APOA4 gene. The expressions of APOA4-AS and APOA4 are both abnormally elevated in the liver of ob/ob mice and patients with fatty liver disease. Knockdown of APOA4-AS reduces APOA4 expression both in vitro and in vivo and leads to decreased levels of plasma triglyceride and total cholesterol in ob/ob mice. Mechanistically, APOA4-AS directly interacts with mRNA stabilizing protein HuR and stabilizes APOA4 mRNA. Deletion of HuR dramatically reduces both APOA4-AS and APOA4 transcripts. This study uncovers an anti-sense lncRNA (APOA4-AS), which is co-expressed with APOA4, and concordantly and specifically regulates APOA4 expression both in vitro and in vivo with the involvement of HuR. Show less
📄 PDF DOI: 10.1093/nar/gkw341
APOA4
Linda M Polfus, Rajiv K Khajuria, Ursula M Schick +53 more · 2016 · American journal of human genetics · Elsevier · added 2026-04-24
Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. Show more
Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis. Show less
no PDF DOI: 10.1016/j.ajhg.2016.06.016
CPS1
Tai-Heng Chen, Xia Tian, Pao-Lin Kuo +3 more · 2016 · Prenatal diagnosis · Wiley · added 2026-04-24
Fetal akinesia deformation sequence (FADS) refers to a broad spectrum of disorder with the absent fetal movement as the unifying feature. The etiology of FADS is heterogeneous, and the majority remain Show more
Fetal akinesia deformation sequence (FADS) refers to a broad spectrum of disorder with the absent fetal movement as the unifying feature. The etiology of FADS is heterogeneous, and the majority remains unknown. Prenatal diagnosis of FADS because of neuromuscular origin has relied on clinical features and fetal muscle pathology, which can be unrevealing. The recent advance of next-generation sequencing (NGS) can provide definitive molecular diagnosis effectively. An 18-week-old fetus presented with akinesia and multiple contractures of joints. The mother had two previously aborted similarly affected fetuses. Clinical diagnosis of FADS was made. Molecular diagnosis using cord blood by NGS of genes related to neuromuscular diseases revealed two compound heterozygous mutations; c.602G > A(p.W201*) and c.1516A > C(p.T506P), in the Kelch-like 40 (KLHL40) gene. Based on this information, prenatal diagnosis was performed on the CVS of the subsequent pregnancy that resulted in an unaffected female baby, heterozygous for the c.1516A > C(p.T506P) mutation. Identification of KLHL40 mutations in one of the aborted fetuses provided a confirmative diagnosis of FADS, facilitating the prenatal diagnosis of the subsequent pregnancy. This report underscores the importance of target NGS in providing FADS families with an affordable, precise molecular diagnosis for genetic counseling and options of prenatal diagnosis. © 2016 John Wiley & Sons, Ltd. Show less
no PDF DOI: 10.1002/pd.4949
FADS1
Juliet D French, Sharon E Johnatty, Yi Lu +75 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify ge Show more
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression. Show less
📄 PDF DOI: 10.18632/oncotarget.7047
CCDC171
Sarwat Fatima, Xiaoke Shi, Zesi Lin +9 more · 2016 · Molecular oncology · Elsevier · added 2026-04-24
5-Hydroxytryptamine (5-HT), a neurotransmitter and vasoactive factor, has been reported to promote proliferation of serum-deprived hepatocellular carcinoma (HCC) cells but the detailed intracellular m Show more
5-Hydroxytryptamine (5-HT), a neurotransmitter and vasoactive factor, has been reported to promote proliferation of serum-deprived hepatocellular carcinoma (HCC) cells but the detailed intracellular mechanism is unknown. As Wnt/β-catenin signalling is highly dysregulated in a majority of HCC, this study explored the regulation of Wnt/β-catenin signalling by 5-HT. The expression of various 5-HT receptors was studied by quantitative real-time polymerase chain reaction (qPCR) in HCC cell lines as well as in 33 pairs of HCC tumours and corresponding adjacent non-tumour tissues. Receptors 5-HT1D (21/33, 63.6%), 5-HT2B (12/33, 36.4%) and 5-HT7 (15/33, 45.4%) were overexpressed whereas receptors 5-HT2A (17/33, 51.5%) and 5-HT5 (30/33, 90.1%) were reduced in HCC tumour tissues. In vitro data suggests 5-HT increased total β-catenin, active β-catenin and decreased phosphorylated β-catenin protein levels in serum deprived HuH-7 and HepG2 cells compared to control cells under serum free medium without 5-HT. Activation of Wnt/β-catenin signalling was evidenced by increased expression of β-catenin downstream target genes, Axin2, cyclin D1, dickoppf-1 (DKK1) and glutamine synthetase (GS) by qPCR in serum-deprived HCC cell lines treated with 5-HT. Additionally, biochemical analysis revealed 5-HT disrupted Axin1/β-catenin interaction, a critical step in β-catenin phosphorylation. Increased Wnt/β-catenin activity was attenuated by antagonist of receptor 5-HT7 (SB-258719) in HCC cell lines and patient-derived primary tumour tissues in the presence of 5-HT. SB-258719 also reduced tumour growth in vivo. This study provides evidence of Wnt/β-catenin signalling activation by 5-HT and may represent a potential therapeutic target for hepatocarcinogenesis. Show less
no PDF DOI: 10.1016/j.molonc.2015.09.008
AXIN1
Tze-Kiong Er, Yu-Fa Su, Chun-Chieh Wu +9 more · 2016 · Journal of molecular medicine (Berlin, Germany) · Springer · added 2026-04-24
Recent molecular and pathological studies suggest that endometriosis may serve as a precursor of ovarian cancer (endometriosis-associated ovarian cancer, EAOC), especially of the endometrioid and clea Show more
Recent molecular and pathological studies suggest that endometriosis may serve as a precursor of ovarian cancer (endometriosis-associated ovarian cancer, EAOC), especially of the endometrioid and clear cell subtypes. Accordingly, this study had two cardinal aims: first, to obtain mutation profiles of EAOC from Taiwanese patients; and second, to determine whether somatic mutations present in EAOC can be detected in preneoplastic lesions. Formalin-fixed paraffin-embedded (FFPE) tissues were obtained from ten endometriosis patients with malignant transformation. Macrodissection was performed to separate four different types of cells from FFPE sections in six patients. The four types of samples included normal endometrium, ectopic endometriotic lesion, atypical endometriosis, and carcinoma. Ultra-deep (>1000×) targeted sequencing was performed on 409 cancer-related genes to identify pathogenic mutations associated with EAOC. The most frequently mutated genes were PIK3CA (6/10) and ARID1A (5/10). Other recurrently mutated genes included ETS1, MLH1, PRKDC (3/10 each), and AMER1, ARID2, BCL11A, CREBBP, ERBB2, EXT1, FANCD2, MSH6, NF1, NOTCH1, NUMA1, PDE4DIP, PPP2R1A, RNF213, and SYNE1 (2/10 each). Importantly, in five of the six patients, identical somatic mutations were detected in atypical endometriosis and tumor lesions. In two patients, genetic alterations were also detected in ectopic endometriotic lesions, indicating the presence of genetic alterations in preneoplastic lesion. Genetic analysis in preneoplastic lesions may help to identify high-risk patients at early stage of malignant transformation and also shed new light on fundamental aspects of the molecular pathogenesis of EAOC. Molecular characterization of endometriosis-associated ovarian cancer genes by targeted NGS. Candidate genes predictive of malignant transformation were identified. Chromatin remodeling, PI3K-AKT-mTOR, Notch signaling, and Wnt/β-catenin pathway may promote cell malignant transformation. Show less
no PDF DOI: 10.1007/s00109-016-1395-2
EXT1
Junxiong Pang, Anna Lindblom, Thomas Tolfvenstam +8 more · 2016 · PloS one · PLOS · added 2026-04-24
Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue dis Show more
Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue disease in 2009. However, WS is limited in stratifying adult dengue patients at early infection (Day 1-3 post fever), who require close monitoring in hospitals to prevent severe dengue. The aim of this study is to identify and validate prognostic models, built with differentially expressed biomarkers, that enable the early identification of those with early dengue infection that require close clinical monitoring. RNA microarray and protein assays were performed to identify differentially expressed biomarkers of severity among 92 adult dengue patients recruited at early infection from years 2005-2008. This comprised 47 cases who developed WS after first presentation and required hospitalization (WS+Hosp), as well as 45 controls who did not develop WS after first presentation and did not require hospitalization (Non-WS+Non-Hosp). Independent validation was conducted with 80 adult dengue patients recruited from years 2009-2012. Prognostic models were developed based on forward stepwise and backward elimination estimation, using multiple logistic regressions. Prognostic power was estimated by the area under the receiver operating characteristic curve (AUC). The WS+Hosp group had significantly higher viral load (P<0.001), lower platelet (P<0.001) and lymphocytes counts (P = 0.004) at early infection compared to the Non-WS+Non-Hosp group. From the RNA microarray and protein assays, the top single RNA and protein prognostic models at early infection were CCL8 RNA (AUC:0.73) and IP-10 protein (AUC:0.74), respectively. The model with CCL8, VPS13C RNA, uPAR protein, and with CCL8, VPS13C RNA and platelets were the best biomarker models for stratifying adult dengue patients at early infection, with sensitivity and specificity up to 83% and 84%, respectively. These results were tested in the independent validation group, showing sensitivity and specificity up to 96% and 54.6%, respectively. At early infection, adult dengue patients who later presented WS and require hospitalization have significantly different pathophysiology compared with patients who consistently presented no WS and / or require no hospitalization. The molecular prognostic models developed and validated here based on these pathophysiology differences, could offer earlier and complementary indicators to the clinical WHO 2009 WS guide, in order to triage adult dengue patients at early infection. Show less
no PDF DOI: 10.1371/journal.pone.0155993
VPS13C
Xiangchun Li, William K K Wu, Rui Xing +19 more · 2016 · Cancer research · added 2026-04-24
Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as m Show more
Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as molecular classifiers or prognostic markers of disease outcome has yet to be established. In this study, we integrated somatic mutational profiles and clinicopathologic information from 544 gastric cancer patients from previous genomic studies to identify significantly mutated genes (SMG) with prognostic relevance. Gastric cancer patients were classified into regular (86.8%) and hypermutated (13.2%) subtypes based on mutation burden. Notably, TpCpW mutations occurred significantly more frequently in regular, but not hypermutated, gastric cancers, where they were associated with APOBEC expression. In the former group, six previously unreported (XIRP2, NBEA, COL14A1, CNBD1, ITGAV, and AKAP6) and 12 recurrent mutated genes exhibited high mutation prevalence (≥3.0%) and an unexpectedly higher incidence of nonsynonymous mutations. We also identified two molecular subtypes of regular-mutated gastric cancer that were associated with distinct prognostic outcomes, independently of disease staging, as confirmed in a distinct patient cohort by targeted capture sequencing. Finally, in diffuse-type gastric cancer, CDH1 mutation was found to be associated with shortened patient survival, independently of disease staging. Overall, our work identified previously unreported SMGs and a mutation signature predictive of patient survival in newly classified subtypes of gastric cancer, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping. Cancer Res; 76(7); 1724-32. ©2016 AACR. Show less
no PDF DOI: 10.1158/0008-5472.CAN-15-2443
AKAP6
Jiping Yue, Yao Zhang, Wenguang G Liang +9 more · 2016 · Nature communications · Nature · added 2026-04-24
Turnover of focal adhesions allows cell retraction, which is essential for cell migration. The mammalian spectraplakin protein, ACF7 (Actin-Crosslinking Factor 7), promotes focal adhesion dynamics by Show more
Turnover of focal adhesions allows cell retraction, which is essential for cell migration. The mammalian spectraplakin protein, ACF7 (Actin-Crosslinking Factor 7), promotes focal adhesion dynamics by targeting of microtubule plus ends towards focal adhesions. However, it remains unclear how the activity of ACF7 is regulated spatiotemporally to achieve focal adhesion-specific guidance of microtubule. To explore the potential mechanisms, we resolve the crystal structure of ACF7's NT (amino-terminal) domain, which mediates F-actin interactions. Structural analysis leads to identification of a key tyrosine residue at the calponin homology (CH) domain of ACF7, whose phosphorylation by Src/FAK (focal adhesion kinase) complex is essential for F-actin binding of ACF7. Using skin epidermis as a model system, we further demonstrate that the phosphorylation of ACF7 plays an indispensable role in focal adhesion dynamics and epidermal migration in vitro and in vivo. Together, our findings provide critical insights into the molecular mechanisms underlying coordinated cytoskeletal dynamics during cell movement. Show less
📄 PDF DOI: 10.1038/ncomms11692
MACF1
Yajun Zheng, Linghang Zhuang, Kristi Yi Fan +28 more · 2016 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based dru Show more
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based drug design platform that generates molecules using a context perceptive growth algorithm guided by a contact sensitive scoring function. The growth engine uses binding site perception and programmable growth capability to create drug-like molecules by assembling fragments that naturally complement hydrophilic and hydrophobic features of the protein binding site. Starting with a crystal structure of LXRβ and a docked 2-(methylsulfonyl)benzyl alcohol fragment (6), Contour was used to design agonists containing a piperazine core. Compound 17 binds to LXRβ with high affinity and to LXRα to a lesser extent, and induces the expression of LXR target genes in vitro and in vivo. This molecule served as a starting point for further optimization and generation of a candidate which is currently in human clinical trials for treating atopic dermatitis. Show less
no PDF DOI: 10.1021/acs.jmedchem.5b02029
NR1H3
Xiaochuan Liu, Aoli Wang, Xiaofei Liang +23 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
PI3Kδ has been found to be over-expressed in B-Cell-related malignancies. Despite the clinical success of the first selective PI3Kδ inhibitor, CAL-101, inhibition of PI3Kδ itself did not show too much Show more
PI3Kδ has been found to be over-expressed in B-Cell-related malignancies. Despite the clinical success of the first selective PI3Kδ inhibitor, CAL-101, inhibition of PI3Kδ itself did not show too much cytotoxic efficacy against cancer cells. One possible reason is that PI3Kδ inhibition induced autophagy that protects the cells from death. Since class III PI3K isoform PIK3C3/Vps34 participates in autophagy initiation and progression, we predicted that a PI3Kδ and Vps34 dual inhibitor might improve the anti-proliferative activity observed for PI3Kδ-targeted inhibitors. We discovered a highly potent ATP-competitive PI3Kδ/Vps34 dual inhibitor, PI3KD/V-IN-01, which displayed 10-1500 fold selectivity over other PI3K isoforms and did not inhibit any other kinases in the kinome. In cells, PI3KD/V-IN-01 showed 30-300 fold selectivity between PI3Kδ and other class I PI3K isoforms. PI3KD/V-IN-01 exhibited better anti-proliferative activity against AML, CLL and Burkitt lymphoma cell lines than known selective PI3Kδ and Vps34 inhibitors. Interestingly, we observed FLT3-ITD AML cells are more sensitive to PI3KD/V-IN-01 than the FLT3 wt expressing cells. In AML cell inoculated xenograft mouse model, PI3KD/V-IN-01 exhibited dose-dependent anti-tumor growth efficacies. These results suggest that dual inhibition of PI3Kδ and Vps34 might be a useful approach to improve the PI3Kδ inhibitor's anti-tumor efficacy. Show less
no PDF DOI: 10.18632/oncotarget.10650
PIK3C3
Rui-Ping Sun, Qian-Yun Xi, Jia-Jie Sun +8 more · 2016 · Scientific reports · Nature · added 2026-04-24
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduc Show more
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduces urea nitrogen. MicroRNAs (miRNAs) are major regulatory non-coding RNAs that have significant effects on several metabolic pathways; however, little is known on whether miRNAs regulate hepatic urea synthesis. The objective of this study was to assess the miRNA expression profile in a low protein diet and identify miRNAs involved in the regulation of the hepatic urea cycle using a porcine model. Weaned 28-days old piglets were fed a corn-soybean normal protein diet (NP) or a corn-soybean low protein diet (LP) for 30 d. Hepatic and blood samples were collected, and the miRNA expression profile was assessed by sequencing and qRT-PCR. Furthermore, we evaluated the possible role of miR-19b in urea synthesis regulation. There were 25 differentially expressed miRNAs between the NP and LP groups. Six of these miRNAs were predicted to be involved in urea cycle metabolism. MiR-19b negatively regulated urea synthesis by targeting SIRT5, which is a positive regulator of CPS1, the rate limiting enzyme in the urea cycle. Our study presented a novel explanation of ureagenesis regulation by miRNAs. Show less
📄 PDF DOI: 10.1038/srep33291
CPS1
Hongjuan He, Lei Lei, Erfei Chen +3 more · 2016 · Genetic testing and molecular biomarkers · added 2026-04-24
To explore the association of the APOA5 gene c.553G>T polymorphism with hypertriglyceridemia (HTG) susceptibility and altered triglyceride levels. We searched the PubMed, Google Scholar, and CNKI data Show more
To explore the association of the APOA5 gene c.553G>T polymorphism with hypertriglyceridemia (HTG) susceptibility and altered triglyceride levels. We searched the PubMed, Google Scholar, and CNKI databases for published studies relating to analyses of these associations. Case-control and comparative studies of the association between the APOA5 c.553G>T variant and altered triglyceride levels were included. In total, the meta-analysis involved 10 studies on HTG, which provided 2219 cases and 3401 controls. To measure the correlation between the c.553G>T polymorphism and HTG susceptibility, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The overall OR was calculated using a random-effects model. Compared with APOA5 c.553 GG carriers, c.553T carriers displayed an increased risk of HTG in the Asian population, with an overall random effects OR of 3.55 (95% CI: 2.46-5.13) in the dominant model. There was significant heterogeneity among the studies (P Our results suggest that APOA5 c. 553T is an independent risk factor for HTG and increased triglyceride levels in the Asian population. APOA5 c. 553T could be employed as a genetic risk marker for HTG and increased triglyceride levels. Show less
no PDF DOI: 10.1089/gtmb.2016.0047
APOA5
Xiao-Jun Chen, Hong Zhang, Zhi-Ping Tan +2 more · 2016 · Molecular medicine reports · added 2026-04-24
Multiple osteochondromas (MO), also known as hereditary multiple exostoses, is an autosomal dominant bone disorder. Mutations in exostosin glycosyl transferase‑1 (EXT1) and exostosin glycosyl transfer Show more
Multiple osteochondromas (MO), also known as hereditary multiple exostoses, is an autosomal dominant bone disorder. Mutations in exostosin glycosyl transferase‑1 (EXT1) and exostosin glycosyl transferase‑2 (EXT2), including missense, nonsense, frameshift and splice‑site mutations, account for up to 80% of reported cases. The proteins EXT1 and EXT2 form a hetero‑oligomeric complex that functions in heparan sulfate proteoglycan biosynthesis. A heterozygous EXT2 mutation, c.939+1G>T, was identified in a five‑generation 33‑member MO family, and was present in all 13 affected members. The mutation results in deletion of exon 5 in the mRNA, producing a frameshift that leads to a premature termination codon. The present study extends the mutational spectrum of EXT2. Show less
📄 PDF DOI: 10.3892/mmr.2016.5814
EXT1
Xian-Bin Lin, Lei Jiang, Mao-Hua Ding +13 more · 2016 · Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · Springer · added 2026-04-24
Phenoxybenzamine hydrochloride (PHEN) is a selective antagonist of both α-adrenoceptor and calmodulin that exhibits anticancer properties. The aim of this study was to explore the anti-tumor function Show more
Phenoxybenzamine hydrochloride (PHEN) is a selective antagonist of both α-adrenoceptor and calmodulin that exhibits anticancer properties. The aim of this study was to explore the anti-tumor function of PHEN in glioma. Cell proliferation assay was used to assess glioma cell growth. Migration and invasion capacity of glioma cells was monitored by wound-healing and transwell assay, respectively. Neurosphere formation test was adopted for the tumorigenesis of glioma cells, which was also confirmed by soft agar cloning formation test in vitro and a nude mouse model in vivo. Finally, we explored the potential pathway utilized by PHEN using Western blot and immunofluoresce staining. PHEN exhibited a significant inhibitory effect on the proliferation of both U251 and U87MG glioma cell lines in a positive dose-dependent manner. PHEN apparently attenuated the malignancy of glioma in terms of migration and invasion and also suppressed the tumorigenic capacity both in vitro and in vivo. Mechanism study showed that PHEN promoted tumor suppression by inhibiting the TrkB-Akt pathway. The results of the present study demonstrated that PHEN suppressed the proliferation, migration, invasion, and tumorigenesis of glioma cells, induced LINGO-1 expression, and inhibited the TrkB-Akt pathway, which may prove to be the mechanisms underlying the anti-tumor effect of PHEN on glioma cells. Show less
no PDF DOI: 10.1007/s13277-015-4102-y
LINGO1
Yan-Bei Yang, Jian-Qing Chen, Yu-Lin Zhao +6 more · 2016 · Frontiers in microbiology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fmicb.2016.01659
CPS1
Rong Li, Lu-Zhu Chen, Wang ZHAO +2 more · 2016 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotrigly Show more
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotriglyceridemic actions. Two obese mouse models, including high-fat diet-induced obese mice and ob/ob obese mice, were adopted. The effects of low- and high-dose metformin were determined on plasma and hepatic TG and apoA5 of these obese mice. Besides, the effects of metformin on TG and apoA5 were also detected in mouse and human hepatocytes in vitro. (1) Plasma apoA5 levels in the obese mice were markedly elevated and positively correlated with TG. Hepatic TG contents and apoA5 expressions were also remarkably increased in the obese mice. (2) Metformin dose-dependently decreased hepatic and plasma TG and apoA5 in the obese mice. Similarly, metformin dose-dependently reduced cellular TG contents and apoA5 expressions in hepatocytes in vitro. Compared to APOA5 knock-down (KD), metformin plus APOA5 KD resulted in more TG reduction of hepatocytes. Increased hepatic and plasma apoA5 could be a result of obesity-associated hypertriglyceridemia, and metformin displays hypotriglyceridemic effects on obese mice partly via the apoA5 pathway. Show less
no PDF DOI: 10.1016/j.bbrc.2016.08.087
APOA5
Rui Chen, Hao Wang, Beibei Liang +11 more · 2016 · Cell death & disease · Nature · added 2026-04-24
Autophagy is an important catabolic process, which sustains intracellular homeostasis and lengthens cell survival under stress. Here we identify the ankyrin-repeat-containing, SH3-domain-containing, a Show more
Autophagy is an important catabolic process, which sustains intracellular homeostasis and lengthens cell survival under stress. Here we identify the ankyrin-repeat-containing, SH3-domain-containing, and proline-rich region-containing protein 2 (ASPP2), a haploinsufficient tumor suppressor, as a molecular regulator of starvation-induced autophagy in hepatocellular carcinoma (HCC). ASPP2 expression is associated with an autophagic response upon nutrient deprivation and downregulation of ASPP2 facilitates autophagic flux, whereas overexpression of ASPP2 blocks this starvation-induced autophagy in HCC cells. Mechanistically, ASPP2 inhibits autophagy through regulating BECN1 transcription and formation of phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) complex. Firstly, ASPP2 inhibits p65/RelA-induced transcription of BECN1, directly by an ASPP2-p65/RelA-IκBα complex which inhibits phosphorylation of IκBα and the translocation of p65/RelA into the nucleus. Secondly, ASPP2 binds to BECN1, leading to decreased binding of PIK3C3 and UV radiation resistance-associated gene (UVRAG), and increased binding of Rubicon in PIK3C3 complex. Downregulation of ASPP2 enhances the pro-survival and chemoresistant property via autophagy in HCC cells in vitro and in vivo. Decreased ASPP2 expression was associated with increased BECN1 and poor survival in HCC patients. Therefore, ASPP2 is a key regulator of BECN1-dependent autophagy, and decreased ASPP2 may contribute to tumor progression and chemoresistance via promoting autophagy. Show less
no PDF DOI: 10.1038/cddis.2016.407
PIK3C3
Jia Hu, Ge Li, Liujing Qu +10 more · 2016 · Cell death & disease · Nature · added 2026-04-24
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have Show more
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have provided a line of evidence confirming that EVA1A (eva-1 homolog A)/TMEM166 (transmembrane protein 166) is associated with autophagosomal membrane development. This notion is based on dotted EVA1A structures that colocalize with ZFYVE1, ATG9, LC3B, ATG16L1, ATG5, STX17, RAB7 and LAMP1, which represent different stages of the autophagic process. It is required for autophagosome formation as this phenotype was significantly decreased in EVA1A-silenced cells and Eva1a KO MEFs. EVA1A-induced autophagy is independent of the BECN1-PIK3C3 (phosphatidylinositol 3-kinase, catalytic subunit type 3) complex but requires ATG7 activity and the ATG12-ATG5/ATG16L1 complex. Here, we present a molecular mechanism by which EVA1A interacts with the WD repeats of ATG16L1 through its C-terminal and promotes ATG12-ATG5/ATG16L1 complex recruitment to the autophagic membrane and enhances the formation of the autophagosome. We also found that both autophagic and apoptotic mechanisms contributed to EVA1A-induced cell death while inhibition of autophagy and apoptosis attenuated EVA1A-induced cell death. Overall, these findings provide a comprehensive view to our understanding of the pathways involved in the role of EVA1A in autophagy and programmed cell death. Show less
no PDF DOI: 10.1038/cddis.2016.230
PIK3C3
Kyoko Hiragami-Hamada, Szabolcs Soeroes, Miroslav Nikolov +17 more · 2016 · Nature communications · Nature · added 2026-04-24
Histone H3 trimethylation of lysine 9 (H3K9me3) and proteins of the heterochromatin protein 1 (HP1) family are hallmarks of heterochromatin, a state of compacted DNA essential for genome stability and Show more
Histone H3 trimethylation of lysine 9 (H3K9me3) and proteins of the heterochromatin protein 1 (HP1) family are hallmarks of heterochromatin, a state of compacted DNA essential for genome stability and long-term transcriptional silencing. The mechanisms by which H3K9me3 and HP1 contribute to chromatin condensation have been speculative and controversial. Here we demonstrate that human HP1β is a prototypic HP1 protein exemplifying most basal chromatin binding and effects. These are caused by dimeric and dynamic interaction with highly enriched H3K9me3 and are modulated by various electrostatic interfaces. HP1β bridges condensed chromatin, which we postulate stabilizes the compacted state. In agreement, HP1β genome-wide localization follows H3K9me3-enrichment and artificial bridging of chromatin fibres is sufficient for maintaining cellular heterochromatic conformation. Overall, our findings define a fundamental mechanism for chromatin higher order structural changes caused by HP1 proteins, which might contribute to the plastic nature of condensed chromatin. Show less
📄 PDF DOI: 10.1038/ncomms11310
CBX1
Jiali Zhu, Keke Xu, Xuemei Zhang +7 more · 2016 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Valeriana jatamansi Jones, a plant with heart-shaped leaves in the Valeriana genus of Valerianaceae, is widely used in Chinese folk medicine. Iridoid is an important constituent of V. jatamansi that c Show more
Valeriana jatamansi Jones, a plant with heart-shaped leaves in the Valeriana genus of Valerianaceae, is widely used in Chinese folk medicine. Iridoid is an important constituent of V. jatamansi that contributes to the pharmacological efficacy of the herb. This study aims to investigate the regulation of lipid metabolism and its mechanism of the iridoids rich fraction in V. jatamansi (IRFV). A high fat diet was used to establish the hyperlipidemia rat model, with 2mg/kg/d of simvastatin as a positive control, fed with 7.5, 15, and 30mg/kg/d of IRFV for 20days to investigate the lipid regulation activity and mechanism of IRFV. Body weight, liver index, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in both serum and liver, as well as total bile acid (TBA), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) in serum were measured. The lipoprotein lipase (LPL) and hepatic lipase (HL) activities and the apoprotein A5 (ApoA5), peroxisome proliferator-activated receptor α (PPAR-α), sterol regulatory element-binding proteins (SREBP-1c), and liver X receptor α (LXR-α) protein expressions were observed. Liver pathology was described through hematoxylin-eosin (HE) staining. Compared with the model group, three different IRFV dosages can slow down the weight gain of rats, reduce the contents of TG, and increase the contents of HDL-C in serum. Low IRFV dosage can significantly reduce the AST and ALT contents in serum, liver index, and the TG contents in liver, enhance LPL activity. Medium IRFV dosage can significantly decrease the TG and LDL-C contents in liver. High IRFV dosage can significantly reduce LDL-C, TBA, AST, and ALT contents in serum, and enhance HL activity. Three different IRFV dosages can significantly increase the ApoA5 and PPAR-α protein expression and decrease the SREBP-1c protein expression. Furthermore, the LXR-α protein expression decreased in low- and high-dose groups. Liver tissue pathological observation showed that IRFV can improve cell degeneration to a certain extent. These results strongly suggest that IRFV play significant roles in regulating lipid metabolism, the mechanism may be related to the increased ApoA5 protein expression. Show less
no PDF DOI: 10.1016/j.biopha.2016.10.099
APOA5
Yun Ma, Shuai Tian, Shuya He +5 more · 2016 · Gene · Elsevier · added 2026-04-24
The biological effects of microRNAs (miRNAs) in the Fragile X Syndrome (FXS) have been widely studied. Dysregulation of miRNAs plays a critical role in the progression of nervous system diseases and i Show more
The biological effects of microRNAs (miRNAs) in the Fragile X Syndrome (FXS) have been widely studied. Dysregulation of miRNAs plays a critical role in the progression of nervous system diseases and in cell proliferation and differentiation. Our previous study validated that miR-19b-3p was associated with FXR1 (Fragile X related gene 1), one of homologous genes of FMR1 (Fragile X mental retardation 1). The purpose of this study was to investigate the relationship of FXR1 and miR-19b-3p, and the crucial role of miR-19b-3p in FXS and to validate whether miR-19b-3p could regulate the growth of SH-SY5Y cells. We determined that miR-19b-3p could regulate the expression of not only USP32, RAB18 and Dusp6 but also FXR1, and FXR1 could in turn regulate the expression of miR-19b-3p. What's more, the overexpression of miR-19b-3p significantly inhibited the proliferation, contributed the apoptosis and slowed down the cycle of SH-SY5Y cells. Taken together, our results indicate that miR-19b-3p plays a significant role in the molecular pathology of FXS by interacting with FXR1 and influencing the growth of SH-SY5Y cells. Show less
no PDF DOI: 10.1016/j.gene.2016.04.037
DUSP6