👤 Yifa 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, Haoting 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, 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
Yuan-Ke Liang, Hao-Yu Lin, Chun-Fa Chen +1 more · 2017 · Oncotarget · Impact Journals · added 2026-04-24
Chromobox (CBX) family proteins are canonical components in polycomb repressive complexes 1 (PRC1), with epigenetic regulatory function and transcriptionally repressing target genes via chromatin modi Show more
Chromobox (CBX) family proteins are canonical components in polycomb repressive complexes 1 (PRC1), with epigenetic regulatory function and transcriptionally repressing target genes via chromatin modification. A plethora of studies have highlighted the function specifications among CBX family members in various cancer, including lung cancer, colon cancer and breast cancer. Nevertheless, the functions and prognostic roles of distinct CBX family members in breast cancer (BC) remain elusive. In this study, we reported the prognostic values of CBX family members in patients with BC through analysis of a series of databases, including Show less
📄 PDF DOI: 10.18632/oncotarget.21325
CBX1
Vinit Shah, Michael E Lassman, Ying Chen +2 more · 2017 · Rapid communications in mass spectrometry : RCM · Wiley · added 2026-04-24
In quantitative analysis of protein biomarkers and therapeutic proteins by liquid chromatography/mass spectrometry (LC/MS), it is a preferred and well-established approach to digest with proteolytic e Show more
In quantitative analysis of protein biomarkers and therapeutic proteins by liquid chromatography/mass spectrometry (LC/MS), it is a preferred and well-established approach to digest with proteolytic enzymes to produce smaller peptide fragments which are more suitable for LC/MS analysis than the intact protein. In-solution digestion is one widely used method for protein digestion. Proteolytically resistant proteins often require digestion times that extend beyond normal working hours and prohibit same day analysis. We evaluated the performance of an immobilized enzyme reactor (IMER) to determine if this technology could reduce method development time, digestion time and increase throughput. We digested human plasma samples using a commercially available IMER, Flash Digest, and compared it to an in-solution digestion method for analysis of three different apolipoprotein biomarkers APOE, APOC2, and APOC3. The plasma digests were analyzed via LC/MS using electrospray ionization (ESI) and multiple reaction monitoring (MRM). Value assigned calibrators were selected over a relevant physiological concentration range for each protein of interest. Quality control samples (QCs) and 'unknown' human plasma samples were analyzed with both methods. Flash Digest significantly reduced digestion time for APOC3, the most proteolytically resistant of the three proteins, to 30 min compared with overnight used with in-solution digestion. The Flash Digest achieved comparable digestion efficiency with minimal method development and reduced sample preparation time. Both methods showed linearity over a physiologically relevant concentration range. Precision was evaluated and a percentage coefficient of variance (% CV) less than 8% was obtained during intra-day reproducibility evaluation for all three apolipoproteins with Flash Digest. Concentrations observed for QCs and unknown samples using Flash Digest were comparable to the in-solution method. An IMER such as Flash Digest may be a potential alternative to in-solution digestion to accelerate digestion of proteolytically resistant proteins in a quantitative proteomics experiments, reduce method development time and increase throughput. Copyright © 2016 John Wiley & Sons, Ltd. Show less
no PDF DOI: 10.1002/rcm.7778
APOC3
T Wang, X Ma, T Tang +13 more · 2017 · Nutrition & diabetes · Nature · added 2026-04-24
We aim to validate the effects of glucose-dependent insulinotropic polypeptide (GIP) on fat distribution and glucose metabolism in Han Chinese populations. We genotyped six tag single-nucleotide polym Show more
We aim to validate the effects of glucose-dependent insulinotropic polypeptide (GIP) on fat distribution and glucose metabolism in Han Chinese populations. We genotyped six tag single-nucleotide polymorphisms (SNPs) of GIP and four tag SNPs of glucose-dependent insulinotropic polypeptide receptor (GIPR) among 2884 community-based individuals from Han Chinese populations. Linear analysis was applied to test the associations of these variants with visceral fat area (VFA) and subcutaneous fat area (SFA) quantified by magnetic resonance imaging as well as glucose-related traits. We found that the C allele of rs4794008 of GIP tended to increase the VFA and the VFA/SFA ratio in all subjects (P=0.050 and P=0.054, respectively), and rs4794008 was associated with the VFA/SFA ratio in males (P=0.041) after adjusting for the BMI. The VFA-increasing allele of rs4794008 was not related to any glucose metabolism traits. However, rs9904288 of GIP was associated with the SFA in males as well as glucose-related traits in all subjects (P range, 0.004-0.049), and the GIPR variants displayed associations with both fat- and glucose-related traits. The results could provide the evidence that GIP might modulate visceral fat accumulation via incretin function or independent of incretin. Show less
📄 PDF DOI: 10.1038/nutd.2017.28
GIPR
Yong Wang, Yushe Wang, Hang Chen +1 more · 2017 · Journal of molecular neuroscience : MN · Springer · added 2026-04-24
The aim of the study is to investigate whether endothelial cells (ECs) promoted the capacity of stem-like cell formation in medulloblastoma (MB) and whether the mechanism of action was associated with Show more
The aim of the study is to investigate whether endothelial cells (ECs) promoted the capacity of stem-like cell formation in medulloblastoma (MB) and whether the mechanism of action was associated with mediation of Notch signaling pathway. Co-culture experiment was conducted to particularly understand the potential role of ECs in promoting phenotype and gene expression of MB stem-like cells. Self-renewal capacity and tumor cell population were measured by sphere-forming assay and flow cytometry, respectively. To further clarify the effects of ECs on the formation of MB stem-like cells, the expression of genes and protein in MB stem-like cells (CCND1, CDK6, c-MYC, and Bmi-1) and Notch (Notch2, Jagged 1, Hes-1, and Hey-2) was quantified by quantitative real-time PCR (qRT-PCR) and western blot, respectively. Also, observed mediation of ECs in regulation of tumor cell stemness by Notch activation was observed when the co-cultures were treated with γ-secretase inhibitor (N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butyl ester (DAPT)). Further investigation was conducted for the effects of ECs on the tumorigenesis in vivo of MB cells when co-cultures were inoculated into a nude mouse after treated with DAPT. Afterwards, tumor size and volume were measured. The sphere-forming rate and cell ratio of stem-like cells were significantly increased. Furthermore, the expression of genes and protein in stem-like cells and Notch was obviously upregulated although treated with γ-secretase inhibitor. Moreover, tumor size and volume were dramatically magnified. This study revealed that Notch pathway activation played a key role in the formation of stem-like cells in MB and had valuable meaning for further investigation of targeted therapies. Show less
no PDF DOI: 10.1007/s12031-017-0965-2
HEY2
Zhonghong Wei, Yunlong Shan, Li Tao +7 more · 2017 · Molecular carcinogenesis · Wiley · added 2026-04-24
Intratumoral hypoxia promotes the distant metastasis of cancer subclones. The clinical expression level of hypoxia-inducible factor-1α (HIF-1α) reflects the prognosis of a variety of cancers, especial Show more
Intratumoral hypoxia promotes the distant metastasis of cancer subclones. The clinical expression level of hypoxia-inducible factor-1α (HIF-1α) reflects the prognosis of a variety of cancers, especially breast cancer. Histone deacetylase (HDAC) inhibitors can target HIF-1α protein due to von Hippel-Lindau (VHL) protein-dependent degradation. Dietary organosulfur compounds, such as those in garlic, have been reported as HDAC inhibitors. The effects of diallyl sulfide (DAS), diallyl disulfide (DADS), and diallyl trisulfide (DATS) on the ratio of firefly/Renilla luciferase activity in hypoxic MDA-MB-231 cells were determined. The mRNA expressions of HIF-1α target genes ANGPTL4, LOXL4, and LOX in hypoxic MDA-MB-231 cells were significantly down-regulated by DATS. DATS attenuated the metastatic potential of MDA-MB-231 cells in hypoxia-induced embryonic zebrafish, xenograft, and orthotopic tumors. Endothelial cell-cancer cell adhesion, wound healing, transwell, and tube formation assays showed that DATS dose-dependently inhibited the migration and angiogenesis of MDA-MB-231 cells in vitro. The expressions of L1CAM, VEGF-A, and EMT-related proteins (Slug, Snail, MMP-2) were inhibited by DATS. DATS dose-dependently inhibited HIF-1α transcriptional activity and hypoxia-induced hematogenous metastasis of MDA-MB-231 cells. It reduced the protein expression of HIF-1α, which did not involve inhibition of HIF-1α mRNA expression or ubiquitin proteasome degradation. Efficient inhibition of HIF-1α expression was required for DATS to resist breast cancer. Show less
no PDF DOI: 10.1002/mc.22686
ANGPTL4
Wen-Chi Hsueh, Anup K Nair, Sayuko Kobes +7 more · 2017 · Circulation. Cardiovascular genetics · added 2026-04-24
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment t Show more
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment the inherent genetic information that can be used for localization. Through identity-by-descent mapping, using ≈400 000 single-nucleotide polymorphisms (SNPs), of serum lipid profiles, we identified a major linkage signal for triglycerides in 1007 Pima Indians (LOD=9.23; Show less
📄 PDF DOI: 10.1161/CIRCGENETICS.117.001809
APOA5
Tara Jois, Weiyi Chen, Victor Howard +7 more · 2017 · Molecular metabolism · Elsevier · added 2026-04-24
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have lin Show more
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have linked adipose ChREBP to insulin sensitivity in mice. However, while ChREBP is most highly expressed in the liver, the effect of hepatic ChREBP on insulin sensitivity remains unknown. To clarify the importance of hepatic ChREBP on glucose homeostasis, we have generated a knockout mouse model that lacks this protein specifically in the liver (Liver-ChREBP KO). Using Liver-ChREBP KO mice, we investigated whether hepatic ChREBP deletion influences insulin sensitivity, glucose homeostasis and the development of hepatic steatosis utilizing various dietary stressors. Furthermore, we determined gene expression changes in response to fasted and fed states in liver, white, and brown adipose tissues. Liver-ChREBP KO mice had impaired insulin sensitivity as indicated by reduced glucose infusion to maintain euglycemia during hyperinsulinemic-euglycemic clamps on both chow (25% lower) and high-fat diet (33% lower) (p < 0.05). This corresponded with attenuated suppression of hepatic glucose production. Although Liver-ChREBP KO mice were protected against carbohydrate-induced hepatic steatosis, they displayed worsened glucose tolerance. Liver-ChREBP KO mice did not show the expected gene expression changes in liver in response to fasted and fed states. Interestingly, hepatic ChREBP deletion also resulted in gene expression changes in white and brown adipose tissues, suggesting inter-tissue communication. This included an almost complete abolition of BAT ChREBPβ induction in the fed state (0.15-fold) (p = 0.015) along with reduced lipogenic genes. In contrast, WAT showed inappropriate increases in lipogenic genes in the fasted state along with increased PEPCK1 in both fasted (3.4-fold) and fed (5.1-fold) states (p < 0.0001). Overall, hepatic ChREBP is protective in regards to hepatic insulin sensitivity and whole body glucose homeostasis. Hepatic ChREBP action can influence other peripheral tissues and is likely essential in coordinating the body's response to different feeding states. Show less
📄 PDF DOI: 10.1016/j.molmet.2017.07.006
MLXIPL
C C Xu, Y Z Bai, X S Xu +5 more · 2017 · Fa yi xue za zhi · added 2026-04-24
To analyze the related pathogenicity gene mutations in a sudden death of hypertrophic cardiomyopathy (HCM) on whole exome level. Whole exome sequencing (WES) was been performed on a sudden death case Show more
To analyze the related pathogenicity gene mutations in a sudden death of hypertrophic cardiomyopathy (HCM) on whole exome level. Whole exome sequencing (WES) was been performed on a sudden death case sample with pathological features of HCM by Illumina® Hiseq 2500 platform. Using hg19 as the reference sequences, the sequencing data were analyzed. Suspicious single nucleotide variants (SNV) were screened, and the conservatism and function were analyzed by the software such as PhyloP, PolyPhen-2, SIFT, etc. After screening, a heterozygous mutation C719R was finally identified in the gene The molecular anatomy on whole exome level by second generation sequencing technology can help to define the molecular mechanism of HCM and provide a new mothed and thought for analysis of death cause. Show less
no PDF DOI: 10.3969/j.issn.1004-5619.2017.04.001
MYBPC3
Jingwen Zhu, Ani Manichaikul, Yao Hu +9 more · 2017 · European journal of nutrition · Springer · added 2026-04-24
We aimed to characterize common genetic variants that influence saturated fatty acid concentrations in East Asians. Meta-analysis of genome-wide association studies for circulating SFAs was conducted Show more
We aimed to characterize common genetic variants that influence saturated fatty acid concentrations in East Asians. Meta-analysis of genome-wide association studies for circulating SFAs was conducted in two population-based cohorts comprising 3521 participants of Chinese ancestry. We identified two novel 14:0-associated loci at LMX1A (LIM homeobox transcription factor 1) and AMPD3 (AMP deaminase 3) (P = 5.08 × 10 To our knowledge, this is the first GWAS analysis to examine SFA concentrations in East Asian populations. Our findings provide novel evidence that genetic variations of several genes from multiple pathways are associated with SFA concentrations in human body. Show less
📄 PDF DOI: 10.1007/s00394-016-1193-1
FADS1
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
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
Changming Liu, Liangen Mao, Zepeng Ping +5 more · 2016 · Evidence-based complementary and alternative medicine : eCAM · added 2026-04-24
Yin-deficiency-heat (YDH) syndrome is a concept in Traditional Chinese Medicine (TCM) for describing subhealth status. However, there are few efficient diagnostic methods available for confirming YDH Show more
Yin-deficiency-heat (YDH) syndrome is a concept in Traditional Chinese Medicine (TCM) for describing subhealth status. However, there are few efficient diagnostic methods available for confirming YDH syndrome. To explore the novel method for diagnosing YDH syndrome, we applied iTRAQ to observe the serum protein profiles in YDH syndrome rats and confirmed protein levels by ELISA. A total of 92 differentially expressed proteins (63 upregulated proteins and 29 downregulated proteins), which were mainly involved in complement and coagulation cascades and glucose metabolism pathway, were identified by the proteomic experiments. Kininogen 1 (KNG1) was significantly increased ( Show less
📄 PDF DOI: 10.1155/2016/5176731
APOC3
Hongxiang Zeng, Hao Gu, Chiqi Chen +9 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the mainte Show more
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the maintenance of stemness in LICs, although the detailed mechanisms are poorly understood. Herein, we provide intriguing evidence showing that a glucose-responsive transcription factor, carbohydrate responsive element binding protein (ChREBP), served as a tumor suppressor rather than an oncogene, as previously described, to inhibit the development of acute myeloid leukemia by promoting the differentiation of LICs. Using an MLL-AF9-induced murine leukemia model, we demonstrated that the deletion of ChREBP resulted in the blockage of the differentiation of LICs and significantly reduced survival in ChREBP-null leukemic mice. However, ChREBP was not required for the normal repopulation abilities of hematopoietic stem cells. ChREBP promoted leukemia cell differentiation through the direct inhibition of RUNX1 or the transactivation of TXNIP to downregulate the RUNX1 level and ROS generation. Moreover, knockdown of ChREBP in human leukemia THP1 cells led to markedly enhanced proliferation and decreased differentiation upon PMA treatment. Collectively, we unraveled an unexpected role of ChREBP in leukemogenesis, which may provide valuable clues for developing novel metabolic strategies for leukemia treatment. Show less
📄 PDF DOI: 10.18632/oncotarget.9520
MLXIPL
Rui Yang, Yao He, Shanshan Chen +3 more · 2016 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Lung cancer has been a hot area of research because of its high incidence and mortality. In this study, WWP2, an E3 ubiquitin ligase, is proposed to be an oncoprotein contributing to lung tumorigenesi Show more
Lung cancer has been a hot area of research because of its high incidence and mortality. In this study, WWP2, an E3 ubiquitin ligase, is proposed to be an oncoprotein contributing to lung tumorigenesis. We attempted to determine if WWP2 gene expression is correlated with the development of human lung adenocarcinoma. Real-time PCR and western blotting were used to detect the expression of WWP2 in 65 paired lung adenocarcinoma and adjacent normal lung tissues. We found that WWP2 expression was elevated in lung adenocarcinoma tissues and was correlated with the tumor differentiation stage, TNM stage and presence of lymph node metastasis. We performed CCK-8 and colony formation assays and found that down-regulation of WWP2 inhibited proliferation in A549 and SPC-A-1 cells. A wound healing assay and trans-well invasion assays showed that down-regulation of WWP2 inhibited the migration and invasion of lung adenocarcinoma cells. It could be predicted from these data that elevated expression of WWP2 may play a role in facilitating the development of lung adenocarcinoma. Show less
no PDF DOI: 10.1016/j.bbrc.2016.07.084
WWP2
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
Jue Wang, Zhizhong Ye, Shuhui Zheng +4 more · 2016 · Brain research · Elsevier · added 2026-04-24
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spina Show more
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spinal cord injury (SCI). The Notch pathway inhibits the differentiation of neural stem/progenitor cells and Lingo-1 is a strong negative regulator for myelination and axon growth. While Lingo-1 shRNA and N-[N-(3, 5-difluorophenacetyl)-1-alanyl]-S-Phenylglycinet-butylester (DAPT), a Notch pathway inhibitor, have been used separately to help repair SCI, the results have been unsatisfactory. Here we investigated and elucidated the preliminary mechanism for the effect of Lingo-1 shRNA and DAPT on neural stem/progenitor cells differentiation. We found that neural stem/progenitor cells from E14 rat embryos expressed Nestin, Sox-2 and Lingo-1, and we optimized the transduction of neural stem/progenitor cells using lentiviral vectors encoding Lingo-1 shRNA. The addition of DAPT decreased the expression of Notch intracellular domain (NICD) as well as the downstream genes Hes1 and Hes5. Expression of NeuN, CNPase and GFAP in DAPT treated cells and expression of NeuN in Lingo-1 shRNA treated cells confirmed differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes. These results revealed that while Lingo-1 shRNA and Notch signaling inhibitor DAPT both promoted differentiation of neural stem cells into neurons, only DAPT was capable of driving neural stem/progenitor cells differentiation into oligodendrocytes and astrocytes. Since we were able to show that both Lingo-1 shRNA and DAPT could drive neural stem/progenitor cells differentiation, our data might aid the development of more effective SCI therapies using Lingo-1 shRNA and DAPT. Show less
no PDF DOI: 10.1016/j.brainres.2015.11.029
LINGO1
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
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
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
Chiung-Mei Chen, Yi-Chun Chen, Mu-Chun Chiang +4 more · 2016 · Neurobiology of aging · Elsevier · added 2026-04-24
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet Show more
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet to be examined in PD patients in Chinese or Asian population. Because ethnic-specific effect is an important concern for GWAS analysis, we genotyped single-nucleotide polymorphisms in the new genetic loci, GCH1 (rs11158026), SIPA1L2 (rs10797576), VPS13C (rs2414739), and MIR4697 (rs329648), to investigate their associations with risk of PD in Taiwan. Another single-nucleotide polymorphism GCH1 rs7155501, previously identified by GWAS listed at the top 20 genes in PDGene database was also included. A total of 1151 study subjects comprising 598 patients with PD and 553 unrelated healthy controls were recruited. The frequency of minor allele (C allele) of GCH1 rs11158026 was found to be significantly higher in PD cases than in controls (p = 0.003). The CC genotype of rs11158026 increased PD risk compared to TT genotype (odds ratio [OR] = 1.29, 95% confidence interval [CI] = 1.09, 1.53, p = 0.004). Under additive model, the GCH1 rs11158026 increased the risk of developing PD (OR = 1.30, 95% CI = 1.10, 1.54, p = 0.002). In recessive model, the genotype TT of MIR4697 rs329648 marginally decreased the PD risk (OR = 0.62, 95% CI = 0.43, 0.90, p = 0.01). The PD patients demonstrated similar genotypic and allelic frequencies in GCH1 rs7155501, SIPA1L2 rs10797576, and VPS13C rs2414739 with the controls. These findings suggest that the GCH1 and MIR4697 but not SIPA1L2 and VPS13C are genetic loci influencing risk of PD in Taiwan. Show less
no PDF DOI: 10.1016/j.neurobiolaging.2015.12.016
VPS13C
Xuanmao Chen, Jie Luo, Yihua Leng +4 more · 2016 · Biological psychiatry · Elsevier · added 2026-04-24
Although major depressive disorder (MDD) has low heritability, a genome-wide association study in humans has recently implicated type 3 adenylyl cyclase (AC3; ADCY3) in MDD. Moreover, the expression l Show more
Although major depressive disorder (MDD) has low heritability, a genome-wide association study in humans has recently implicated type 3 adenylyl cyclase (AC3; ADCY3) in MDD. Moreover, the expression level of AC3 in blood has been considered as a MDD biomarker in humans. Nevertheless, there is a lack of supporting evidence from animal studies. We employed multiple approaches to experimentally evaluate if AC3 is a contributing factor for major depression using mouse models lacking the Adcy3 gene. We found that conventional AC3 knockout (KO) mice exhibited phenotypes associated with MDD in behavioral assays. Electroencephalography/electromyography recordings indicated that AC3 KO mice have altered sleep patterns characterized by increased percentage of rapid eye movement sleep. AC3 KO mice also exhibit neuronal atrophy. Furthermore, synaptic activity at cornu ammonis 3-cornu ammonis 1 synapses was significantly lower in AC3 KO mice, and they also exhibited attenuated long-term potentiation as well as deficits in spatial navigation. To confirm that these defects are not secondary responses to anosmia or developmental defects, we generated a conditional AC3 floxed mouse strain. This enabled us to inactivate AC3 function selectively in the forebrain and to inducibly ablate it in adult mice. Both AC3 forebrain-specific and AC3 inducible knockout mice exhibited prodepression phenotypes without anosmia. This study demonstrates that loss of AC3 in mice leads to decreased neuronal activity, altered sleep pattern, and depression-like behaviors, providing strong evidence supporting AC3 as a contributing factor for MDD. Show less
📄 PDF DOI: 10.1016/j.biopsych.2015.12.012
ADCY3
Niha Zubair, Mariaelisa Graff, Jose Luis Ambite +54 more · 2016 · Human molecular genetics · Oxford University Press · added 2026-04-24
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the geneti Show more
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies. Show less
no PDF DOI: 10.1093/hmg/ddw358
APOA5
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
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
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
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
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
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
Wen-li Song, Yu Tian, Xian-e Wang +7 more · 2016 · Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · added 2026-04-24
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of agg Show more
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of aggressive periodontitis. A total of 353 patients with aggressive periodontitis (group AgP) and 125 matched controls (group HP) were recruited in the study. Genotyping of FADS1 rs174537 and serum biochemical indexes were tested at the study's start. The relationships between the levels of TP, GLB, ALB, A/G and genotyping were analyzed. (1) The detection rate of allele G in group AgP was higher than that in group HP(68.1% vs. 61.2%, P=0.046,OR=1.35,95% CI 1.00-1.83); the detection rate of genotype GG in group AgP was higher than in group HP(45.5% vs. 34.4%,P=0.029, OR=1.60, 95% CI 1.05-2.44). (2) In group AgP, the patients with GG genotype exhibited significantly lower TP, GLB than the patients with GT+TT genotype [(77.08 ± 7.88) g/L vs. (79.00 ± 4.66) g/L, P=0.007; (28.17 ± 7.63) g/L vs.(29.88 ± 3.49) g/L,P=0.007) and the higher A/G(1.72 ± 0.22 vs.1.67 ± 0.22, P=0.040), but there was no significant difference in ALB between the patients with GG genotype and the patients with GT+TT genotype. In group HP, there were no significant differences in TP, GLB, A/G and ALB between individuals with genotype GT+TT and with genotype GG. (3)Compared with individuals with genotype GT+TT in group HP, the AgP patients with genotype GT+TT exhibited significantly higher TP, GLB [(79.00 ± 4.66) g/L vs. (75.20 ± 4.53) g/L, P<0.01; (29.88 ± 3.49) g/L vs.(26.55 ± 2.94) g/L, P<0.01) and the lower A/G(1.67 ± 0.22 vs. 1.88 ± 0.30, P<0.01), but there was no significant difference in ALB. There were no significant differences in TP, GLB, A/G and ALB the between the AgP patients with genotype GG and the healthy subjects with the same genotype either. FADS1 rs174537 polymorphism is associated with aggressive periodontitis. The patients with genotype GG in group AgP had relatively lower TP,GLB and higher A/G. Genotype GG might be a risk indicator for aggressive periodontitis by reducing host defense capability and contributing to inflammatory response in the occurrence and development of aggressive periodontitis. Show less
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FADS1
Haiying Chen, Hongli Yang, Chong Xu +8 more · 2016 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow- Show more
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow-derived mesenchymal stem cells (rBMSCs) transduced with a mutant caveolin-1(F92A-Cav1) could enhance endothelial nitric oxide synthase (eNOS) activity and improve pulmonary vascular remodeling, but the potential mechanism is not yet fully explored. The present study was to investigate the gene expression profile upon rBMSCs/F92A-Cav1delivered to PAH rat to evaluate the role of F92A-Cav1 in its regulation. PAH was induced with monocrotaline (MCT, 60mg/kg) prior to delivery of lentiviral vector transduced rBMSCs expressing Cav1 or F92A-Cav1. Gene expression profiling was performed using Rat Signal Transduction PathwayFinder array. The expression changes of 84 key genes representing 10 signal transduction pathways in rat following rBMSCs/F92A-Cav1 treatment was examined. Screening with the Rat Signal Transduction PathwayFinder R rBMSCs/F92A-Cav1 inhibits inflammation and cell proliferation by regulating signaling pathways that related to inflammation, proliferation, cell cycle and oxidative stress. Show less
no PDF DOI: 10.1016/j.biopha.2016.06.028
HEY2