👤 Shu-Jen Chen

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2981
Articles
1996
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Also published as: Wen-Chau Chen, Jingzhao Chen, Dexi Chen, Haifeng Chen, Chung-Jen Chen, Bo-Jun Chen, Gao-Feng Chen, Changyan Chen, Weiwei Chen, Fenghua Chen, Xiaojiang S Chen, Xiu-Juan Chen, Jung-Sheng Chen, Xiao-Ying Chen, Chong Chen, Junyang Chen, YiPing Chen, Xiaohan Chen, Li-Zhen Chen, Jiujiu Chen, Shin-Wen Chen, Guangping Chen, Dapeng Chen, Ximei Chen, Renwei Chen, Jianfei Chen, Yulu Chen, Yu-Chi Chen, Jia-De Chen, Rongfang Chen, She Chen, Zetian Chen, Tianran Chen, Emily Chen, Baoxiang Chen, Ya-Chun Chen, Dongxue Chen, Wei-xian Chen, Danmei Chen, Ceshi Chen, Junling Chen, Xia Chen, Daoyuan Chen, Yongbin Chen, Chi-Yu Chen, Dian Chen, Xiuxiu Chen, Bo-Fang Chen, Fangyuan Chen, Jin-An Chen, Xiaojuan Chen, Zhuohui Chen, Junqi Chen, Lina Chen, Fangfang Chen, Hanwen Chen, Yilei Chen, Po-Han Chen, Xiaoxiang Chen, Jimei Chen, Guochong Chen, Yanyun Chen, Yifei Chen, Cheng-Yu Chen, Zi-Jiang Chen, Jiayuan Chen, Miaoran Chen, Junshi Chen, Yu-Ying Chen, Pengxiang Chen, Hui-Ru Chen, Yupeng Chen, Ida Y-D Chen, Xiaofeng Chen, Qiqi Chen, Shengnan Chen, Mao-Yuan Chen, Lizhu Chen, Weichan Chen, Xiang-Bin Chen, Hanxi Chen, Sulian Chen, Zoe Chen, Minghong Chen, Chi Chen, Yananlan Chen, Yanzhu Chen, Shiyi Chen, Ze-Xu Chen, Zhiheng Chen, Jia-Mei Chen, Shuqin Chen, Yi-Hau Chen, Danni Chen, Donglong Chen, Xiaomeng Chen, Yidong Chen, Keyu Chen, Hao Chen, Junmin Chen, Wenlong Chen, Yufei Chen, Wanbiao Chen, Mo Chen, Youjia Chen, Xin-Jie Chen, Lanlan Chen, Huapu Chen, Shuaiyin Chen, Jing-Hsien Chen, Hengsheng Chen, Bing-Bing Chen, Fa-Xi Chen, Zhiqiang Chen, Ming-Huang Chen, Liangkai Chen, Li-Jhen Chen, Zhi-Hao Chen, Yinzhu Chen, Guanghong Chen, Gaozhi Chen, Jiakang Chen, Yongke Chen, Guangquan Chen, Li-Hsien Chen, Yiduo Chen, Zongnan Chen, Jing Chen, Meilan Chen, Jin-Shuen Chen, Huanxiong Chen, Yann-Jang Chen, Guozhong Chen, Yu-Bing Chen, Xiaobin Chen, Catherine Qing Chen, Youhu Chen, Hui Mei Chen, L F Chen, Haiyang Chen, Ruilin Chen, Peng Chen, Kailang Chen, Chao Chen, Suipeng Chen, Zemin Chen, Jianlin Chen, Shang-Chih Chen, Yen-Hsieh Chen, Jia-Lin Chen, Chaojin Chen, Minglang Chen, Xiatian Chen, Zeyu Chen, Kang Chen, Mei-Chi Chen, Jihai Chen, Pei Chen, Defang Chen, Zhao Chen, Tianrui Chen, Tingtao Chen, Caressa Chen, Jiwei Chen, Xuerong Chen, Yizhi Chen, XueShu Chen, Mingyue Chen, Huichao Chen, Chun-Chi Chen, Xiaomin Chen, Hetian Chen, Yuxing Chen, Jie-Hua Chen, Chuck T Chen, Yuanjia Chen, Hong Chen, Jianxiong Chen, S Chen, D M Chen, Jiao-Jiao Chen, Gongbo Chen, Xufeng Chen, Xiao-Jun Chen, Harn-Shen Chen, Qiu Jing Chen, Tai-Heng Chen, Pei-Lung Chen, Kaifu Chen, Huang-Pin Chen, Tse-Wei Chen, Yanrong Chen, Xianfeng Chen, Chung-Yung Chen, Yuelei Chen, Qili Chen, Guanren Chen, TsungYen Chen, Yu-Si Chen, Junsheng Chen, Min-Jie Chen, Xin-Ming Chen, Jiabing Chen, Sili Chen, Qinying Chen, Yue Chen, Lin Chen, Xiaoli Chen, Zhuo Chen, Aoshuang Chen, Junyu Chen, Chunji Chen, Yian Chen, Shanchun Chen, Shuen-Ei Chen, Canrong Chen, Shih-Jen Chen, Yaowu Chen, Han Chen, Yih-Chieh Chen, Wei-Cong Chen, Yanfen Chen, Tao Chen, Huangtao Chen, Jingyi Chen, Sheng Chen, Jing-Wen Chen, Gao Chen, Lei-Lei Chen, Kecai Chen, Yao-Shen Chen, Haiyu Chen, W Chen, Xiaona Chen, Cheng-Sheng Chen, X R Chen, Shuangfeng Chen, Jingyuan Chen, Xinyuan Chen, Huanhuan Chen, Mengling Chen, Liang-Kung Chen, Ming-Huei Chen, Hongshan Chen, Cuncun Chen, Qingchao Chen, Yanzi Chen, Lingli Chen, Shiqian Chen, Liangwan Chen, Lexia Chen, Wei-Ting Chen, Zhencong Chen, Tzy-Yen Chen, Mingcong Chen, Honglei Chen, Yuyan Chen, Huachen Chen, Yu Chen, Li-Juan Chen, Aozhou Chen, Xinlin Chen, Wai Chen, Dake Chen, Bo-Sheng Chen, Meilin Chen, Kequan Chen, Hong Yang Chen, Yan Chen, Bowei Chen, Silian Chen, Jian Chen, Yongmei Chen, Ling Chen, Jinbo Chen, Yingxi Chen, Ge Chen, Max Jl Chen, C Z Chen, Weitao Chen, Xiaole L Chen, Yonglu Chen, Shih-Pin Chen, Jiani Chen, Huiru Chen, San-Yuan Chen, Bing Chen, Xiao-ping Chen, Feiyue Chen, Shuchun Chen, Zhaolin Chen, Qianxue Chen, Xiaoyang Chen, Bowang Chen, Yinghui Chen, Ting-Ting Chen, Xiao-Yang Chen, Chi-Yuan Chen, Zhi-zhe Chen, Ting-Tao Chen, Xiaoyun Chen, Min-Hsuan Chen, Kuan-Ting Chen, Yongheng Chen, Wenhao Chen, Shengyu Chen, Kai Chen, Yueh-Peng Chen, Guangju Chen, Minghua Chen, Hong-Sheng Chen, Qingmei Chen, Song-Mei Chen, Limei Chen, Yuqi Chen, Yuyang Chen, Yang-Ching Chen, Yu-Gen Chen, Peizhan Chen, Rucheng Chen, Jin-Xia Chen, Szu-Chieh Chen, Xiaojun Chen, Jialing Chen, Heni Chen, Yi Feng Chen, Sen Chen, Alice Ye A Chen, Wen Chen, Han-Chun Chen, Dawei Chen, Fangli Chen, Ai-Qun Chen, Zhaojun Chen, Gong Chen, Yishan Chen, Zhijing Chen, Qiuxuan Chen, Miao-Der Chen, Fengwu Chen, Weijie Chen, Weixin Chen, Mei-Ling Chen, Hung-Po Chen, Rui-Pei Chen, Nian-Ping Chen, Tielin Chen, Canyu Chen, Xiaotao Chen, Nan Chen, C Chen, Juanjuan Chen, Xinan Chen, Jiaping Chen, Xiao-Lin Chen, Jianping Chen, Yayun Chen, Le Qi Chen, Jen-Sue Chen, Mechi Chen, Miao-Yu Chen, Zhou Chen, Szu-Han Chen, Zhen Bouman Chen, Baihua Chen, Qingao Chen, Shao-Ke Chen, Feng Chen, Jiawen Chen, Lianmin Chen, Sifeng Chen, Mengxia Chen, Xueli Chen, Can Chen, Yibo Chen, Zinan Chen, Lei-Chin Chen, Carol Chen, Yanlin Chen, Zihang Chen, Zaozao Chen, Haiqin Chen, Lu Hua Chen, Zhiyuan Chen, Meiyu Chen, Du-Qun Chen, Keying Chen, Naifei Chen, Peixian Chen, Jin-Ran Chen, Yijun Chen, Yulin Chen, Fumei Chen, Zhanfei Chen, Zhe-Yu Chen, Xin-Qi Chen, Valerie Chen, Ru Chen, Mengqing Chen, Runsheng Chen, Tong Chen, Tan-Zhou Chen, Suet Nee Chen, Cuicui Chen, Yifan Chen, Tian Chen, XiangFan Chen, Lingyi Chen, Hsiao-Yun Chen, Kenneth L Chen, Ni Chen, Huishan Chen, Fang-Yu Chen, Ken Chen, Yongshen Chen, Qiong Chen, Mingfeng Chen, Shoudeng Chen, Qiao Chen, Qian Chen, Yuebing Chen, Xuehua Chen, Chang-Lan Chen, Min-Hu Chen, Hongbin Chen, Jingming Chen, Qing Chen, Yu-Fan Chen, Hao-Zhu Chen, Yunjia Chen, Zhongjian Chen, Mingyi Chen, Qianping Chen, Huaxin Chen, Dong-Mei Chen, Peize Chen, Leijie Chen, Ming-Yu Chen, Jiaxuan Chen, Xiao-chun Chen, Wei-Min Chen, Ruisen Chen, Xuanwei Chen, Guiquan Chen, Minyan Chen, Feng-Ling Chen, Yili Chen, Alvin Chen, Xiaodong Chen, Bohong Chen, Chih-Ping Chen, Xuanjing Chen, Shuhui Chen, Ming-Hong Chen, Tzu-Yu Chen, Brian Chen, Bowen Chen, Kai-En Chen, Szu-Chia Chen, Guangchun Chen, Fang Chen, Chuyu Chen, Haotian Chen, Xiaoting Chen, Shaoliang Chen, Chun-Houh Chen, Shali Chen, Yu-Cheng Chen, Zhijun Chen, B Chen, Yuan Chen, Zhanglin Chen, Chaoran Chen, Xing-Long Chen, Zhinan Chen, Yu-Hui Chen, Yuquan Chen, Andrew Chen, Fengming Chen, Guangyong Chen, Jun Chen, Wenshuo Chen, Yi-Guang Chen, Jing-Yuan Chen, Kuangyang Chen, Mingyang Chen, Shaofei Chen, Weicong Chen, Gonghai Chen, Di-Long Chen, Limin Chen, Jishun Chen, Yunfei Chen, Caihong Chen, Tongsheng Chen, Ligang Chen, Wenqin Chen, Shiyu Chen, Xiaoyong Chen, Christina Y Chen, Yushan Chen, Ginny I Chen, Guo-Jun Chen, Xianzhen Chen, Wanling Chen, Kuan-Jen Chen, Maorong Chen, Kaijian Chen, Erqu Chen, Shen Chen, Quan Chen, Zian Chen, Yi-Lin Chen, Juei-Suei Chen, Yi-Ting Chen, Huaiyong Chen, Minjian Chen, Qianzhi Chen, Jiahao Chen, Xikun Chen, Juan-Juan Chen, Xiaobo Chen, Tianzhen Chen, Ziming Chen, Qianbo Chen, Jindong Chen, Jiu-Chiuan Chen, Yinwei Chen, Carl Pc Chen, Li-Hsin Chen, Jenny Chen, Ruoyan Chen, Yanqiu Chen, Yen-Fu Chen, Haiyan Chen, Zhebin Chen, Si Chen, Jian-Qiao Chen, Yang-Yang Chen, Ningning Chen, Zhifeng Chen, Zhenyi Chen, Hangang Chen, Zihe Chen, Mengdi Chen, Zhichuan Chen, Xu Chen, Huixi Chen, Weitian Chen, Bao-Sheng Chen, Tien-Hsing Chen, Junchen Chen, Yan-yan Chen, Xiangning Chen, Sijia Chen, Xinyan Chen, Kuan-Yu Chen, Qunxiang Chen, Guangliang Chen, Bing-Huei Chen, Fei Xavier Chen, Zhangcheng Chen, Qianming Chen, Xianze Chen, Yanhua Chen, Qinghao Chen, Yanting Chen, Sijuan Chen, Chen-Mei Chen, Qiankun Chen, Jianan Chen, Rong Chen, Xiankai Chen, Kaina Chen, Gui-Hai Chen, Y-D Ida Chen, Quanjiao Chen, Shuang Chen, Lichang Chen, Xinyi Chen, Yong-Jun Chen, Zhaoli Chen, Chunnuan Chen, Jui-Chang Chen, Zhiang Chen, Weirui Chen, Zhenguo Chen, Jennifer F Chen, Zhiguo Chen, Kunmei Chen, Huan-Xin Chen, Mengyan Chen, Dongrong Chen, Siyue Chen, Xianyue Chen, Chien-Lun Chen, YiChung Chen, Guang Chen, Quanwei Chen, Zongming E Chen, Ting-Huan Chen, Michael C Chen, Jinli Chen, Beth L Chen, Yuh-Lien Chen, Peihong Chen, Qiaoling Chen, Jiale Chen, Shufeng Chen, Xiaowan Chen, Xian-Kai Chen, Ling-Yan Chen, Yen-Ling Chen, Guiying Chen, Guangyi Chen, Yuling Chen, Xiangqiu Chen, Haiquan Chen, Cuie Chen, Gui-Lai Chen, R Chen, Heng-Yu Chen, Yongxun Chen, Fuxiang Chen, Mingmei Chen, Hua-Pu Chen, Yulong Chen, Zhitao Chen, Guohua Chen, Cheng-Yi Chen, Hongxu Chen, Yuanhao Chen, Qichen Chen, Hualin Chen, Guo-Rong Chen, Rongsheng Chen, Xuesong Chen, Wei-Fei Chen, Bao-Bao Chen, Anqi Chen, Yi-Han Chen, Ying-Jung Chen, Jinhuang Chen, Guochao Chen, Lei Chen, S N Chen, Songfeng Chen, Chenyang Chen, Xing Chen, Letian Chen, Meng Xuan Chen, Xiang-Mei Chen, Xiaoyan Chen, Yi-Heng Chen, D F Chen, Bang Chen, Jiaxu Chen, Wei Chen, Sihui Chen, Shu-Hua Chen, I-M Chen, Xuxin Chen, Zhangxin Chen, Jin Chen, Yin-Huai Chen, Wuyan Chen, Bingqing Chen, Bao-Fu Chen, Zhen-Hua Chen, Dan Chen, Zhe-Sheng Chen, Ranyun Chen, Wanyin Chen, Xueyan Chen, Xiaoyu Chen, Tai-Tzung Chen, Xiaofang Chen, Yongxing Chen, Yanghui Chen, Hekai Chen, Yuanwei Chen, Liang Chen, Hui-Jye Chen, Chengchun Chen, Han-Bin Chen, Shuaijie Chen, Yibing Chen, Kehui Chen, Shuhai Chen, Xueling Chen, Ying-Jie Chen, Qingxing Chen, Fang-Zhi Chen, Mei-Hua Chen, Yutong Chen, Lixian Chen, Alex Chen, Qiuhong Chen, Qiuxia Chen, Liping Chen, Hou-Tsung Chen, Zhanghua Chen, Chun-Fa Chen, Chian-Feng Chen, Benjamin P C Chen, Yewei Chen, Mu-Hong Chen, Jianshan Chen, Xiaguang Chen, Meiling Chen, Heng Chen, Ying-Hsiang Chen, Longyun Chen, Dengpeng Chen, Jichong Chen, Shixuan Chen, Liaobin Chen, Everett H Chen, ZhuoYu Chen, Qihui Chen, Zhiyong Chen, Nuan Chen, Hongmei Chen, Guiqian Chen, Yan Q Chen, Fengling Chen, Hung-Chang Chen, Zhenghong Chen, Chengsheng Chen, Hegang Chen, Huei-Yan Chen, Liutao Chen, Meng-Lin Chen, Xi Chen, Qing-Juan Chen, Linna Chen, Xiaojing Chen, Lang Chen, Gengsheng Chen, Fengrong Chen, Weilun Chen, Shi Chen, Wan-Yi Chen, On Chen, Yufeng Chen, Benjamin Chen, Hui-Zhao Chen, Bo-Rui Chen, Kangyong Chen, Ruixiang Chen, Weiyong Chen, Ning-Hung Chen, Meng-Ping Chen, Huimei Chen, Ying Chen, Kang-Hua Chen, Pei-zhan Chen, Liujun Chen, Hanqing Chen, Chengchuan Chen, Guojun Chen, Yongfa Chen, Li Chen, Mingling Chen, Jacinda Chen, Jinlun Chen, Kun Chen, Yi Chen, Chiung Mei Chen, Shaotao Chen, Tianhong Chen, Chanjuan Chen, Yuhao Chen, Huizhi Chen, Chung-Hsing Chen, Qiuchi Chen, Haoting Chen, Luzhu Chen, Huanhua Chen, Long Chen, Jiang-hua Chen, Kai-Yang Chen, Jing-Zhou Chen, Yong-Syuan Chen, Lifang Chen, Ruonan Chen, Meimei Chen, Qingchuan Chen, Liugui Chen, Shaokun Chen, Yi-Yung Chen, Jintian Chen, Xuhui Chen, Dongyan Chen, Huei-Rong Chen, Xianmei Chen, Jinyan Chen, Yuxi Chen, Qingqing Chen, Weibo Chen, Qiwei Chen, Mingxia Chen, Hongmin Chen, Jiahui Chen, Yen-Jen Chen, Zihan Chen, Guozhou Chen, Fei Chen, Zhiting Chen, Denghui Chen, Gary Chen, Hongli Chen, Jack Chen, Zhigang Chen, Lie Chen, Siyuan Chen, Haojie Chen, Qing-Wei Chen, Maochong Chen, Mei-Jie Chen, Haining Chen, Xing-Zhen Chen, Weiqing Chen, Huanchun Chen, C-Y Chen, Tzu-An Chen, Jen-Hau Chen, Xiaojie Chen, Dongquan Chen, Gao B Chen, Daijie Chen, Zixi Chen, Lingfeng Chen, Jiayi Chen, Zan Chen, Shuming Chen, Mei-Hsiu Chen, Xueqin Chen, Huan Chen, Xiaoqing Chen, Hui-Xiong Chen, Ruoying Chen, Deying Chen, Huixian Chen, Zhezhe Chen, Lu Chen, Xiaolong Chen, Si-Yue Chen, Xinwei Chen, Wentao Chen, Yucheng Chen, Jiajing Chen, Allen Menglin Chen, Chixiang Chen, Shiqun Chen, Wenwu Chen, Chin-Chuan Chen, Ningbo Chen, Hsin-Hung Chen, Shenglan Chen, Jia-Feng Chen, Changya Chen, ZhaoHui Chen, Guo Chen, Juhai Chen, Xiao-Quan Chen, Cuimin Chen, Yongshuo Chen, Sai Chen, Fengyang Chen, Siteng Chen, Hualan Chen, Lian Chen, Yuan-Hua Chen, Minjie Chen, Shiyan Chen, Z Chen, Zhengzhi Chen, Jonathan Chen, H Chen, You-Yue Chen, Shu-Gang Chen, Hsuan-Yu Chen, Hongyue Chen, Weiyi Chen, Jiaqi Chen, Chengde Chen, Shufang Chen, Ze-Hui Chen, Xiuping Chen, Zhuojia Chen, Zhouji Chen, Lidian Chen, Yilan Chen, Kuan-Ling Chen, Alon Chen, Zi-Yue Chen, Hongmou Chen, Fang-Zhou Chen, Jianzhou Chen, Wenbiao Chen, Yujie Chen, Zhijian Chen, Zhouqing Chen, Xiuhui Chen, Qingguang Chen, Hanbei Chen, Qianyu Chen, Mengping Chen, Yongqi Chen, Sheng-Yi Chen, Siqi Chen, Yelin Chen, Shirui Chen, Yuan-Tsong Chen, Dongyin Chen, Lingxue Chen, Long-Jiang Chen, Yunshun Chen, Yahong Chen, Yaosheng Chen, Zhonghua Chen, Jingyao Chen, Pei-Yin Chen, Fusheng Chen, Xiaokai Chen, Shuting Chen, Miao-Hsueh Chen, Y-D I Chen, Zijie Chen, Haozhu Chen, Haodong Chen, Xiong Chen, Wenxi Chen, Feng-Jung Chen, Shangwu Chen, Zhiping Chen, Zhang-Yuan Chen, Wentong Chen, Ou Chen, Ruiming Chen, Xiyu Chen, Shuqiu Chen, Xiaoling Chen, Ruimin Chen, Hsiao-Wang Chen, Dongli Chen, Haibo Chen, Yiyun Chen, Luming Chen, Wenting Chen, Chongyang Chen, Qingqiu Chen, Wen-Pin Chen, Yuhui Chen, Lingxia Chen, Jun-Long Chen, Xingyu Chen, Haotai Chen, Bang-dang Chen, Qiuwen Chen, Rui Chen, K C Chen, Zhixuan Chen, Gaoyu Chen, Yitong Chen, Tzu-Ju Chen, Jingqing Chen, Huiqun Chen, Runsen Chen, Michelle Chen, Hanyong Chen, Xiaolin Chen, Ke Chen, Yangchao Chen, Y D I Chen, Jinghua Chen, Jia Wei Chen, Man-Hua Chen, H T Chen, Zheyi Chen, Lihong Chen, Guangyao Chen, Rujun Chen, Ming-Fong Chen, Haiyun Chen, Dexiong Chen, Huiqin Chen, Ching Kit Chen, En-Qiang Chen, Wanjia Chen, Xiangliu Chen, Meiting Chen, Szu-Chi Chen, Yii-der Ida Chen, Jian-Hua Chen, Yanjie Chen, Yingying Chen, Paul Chih-Hsueh Chen, Si-Ru Chen, Mingxing Chen, Rui-Zhen Chen, Changjie Chen, Qu Chen, Yintong Chen, Jingde Chen, Mao Chen, Xinghai Chen, Mei-Chih Chen, Xueqing Chen, Chun-An Chen, Cheng Chen, Ruijing Chen, Huayu Chen, Yunqin Chen, Yan-Gui Chen, Ruibing Chen, Size Chen, Qi-An Chen, Yuan-Zhen Chen, J Chen, Heye Chen, T Chen, Junpeng Chen, Tan-Huan Chen, Shuaijun Chen, Hao Yu Chen, Fahui Chen, Lan Chen, Dong-Yi Chen, Xianqiang Chen, Shi-Sheng Chen, Qiao-Yi Chen, Pei-Chen Chen, Xueying Chen, Yi-Wen Chen, Guohong Chen, Zhiwei Chen, Zuolong Chen, Erfei Chen, Yuqing Chen, Zhenyue Chen, Qiongyun Chen, Jianghua Chen, Yingji Chen, Xiuli Chen, Xiaowei Chen, Hengyu Chen, Sheng-Xi Chen, Haiyi Chen, Shao-Peng Chen, Yi-Ru Chen, Zhaoran Chen, Xiuyan Chen, Jinsong Chen, Sunny Chen, Xiaolan Chen, S-D Chen, Ruofan Chen, Qiujing Chen, Yun Chen, Wei-Cheng Chen, Chun-Wei Chen, Liechun Chen, Lulu Chen, Hsiu-Wen Chen, Yanping Chen, Jiayao Chen, Xuejiao Chen, Guan-Wei Chen, Yusi Chen, Yijiang Chen, Chi-Hua Chen, Qixian Chen, Ziqing Chen, Peiyou Chen, Chunhai Chen, Zheren Chen, Qiuyun Chen, Xiaorong Chen, Chaoqun Chen, Dan-Dan Chen, Xuechun Chen, Yafang Chen, Mystie X Chen, Jina Chen, Wei-Kai Chen, Yule Chen, Bo Chen, Kaili Chen, Junqin Chen, Jia Min Chen, Chen Chen, Guoliang Chen, Xiaonan Chen, Guangjie Chen, Xiao Chen, Jeanne Chen, Danyang Chen, Minjiang Chen, Jiyuan Chen, Zheng-Zhen Chen, Shou-Tung Chen, Ouyang Chen, Xiu Chen, H Q Chen, Peiyu Chen, Yuh-Min Chen, Youmeng Chen, Shuoni Chen, Peiqin Chen, Xinji Chen, Chih-Ta Chen, Shang-Hung Chen, Robert Chen, Suet N Chen, Yun-Tzu Chen, Suming Chen, Ye Chen, Yao Chen, Yi-Fei Chen, Ruixue Chen, Tianhang Chen, Suning Chen, Jingnan Chen, Xiaohong Chen, Kun-Chieh Chen, Tuantuan Chen, Mei Chen, He-Ping Chen, Zhi Bin Chen, Yuewu Chen, Mengying Chen, Po-See Chen, Xue Chen, Jian-Jun Chen, Xiyao Chen, Jeremy J W Chen, Jiemei Chen, Daiwen Chen, Christina Yingxian Chen, Qinian Chen, Chih-Wei Chen, Wensheng Chen, Yingcong Chen, Zhishi Chen, Duo Chen, Jiansu Chen, Keping Chen, Min Chen, Yi-Hui Chen, Yun-Ju Chen, Gaoyang Chen, Renjin Chen, Kui Chen, Shuai-Ming Chen, Hui-Fen Chen, Zi-Yun Chen, Shao-Yu Chen, Meiyang Chen, Jiahua Chen, Zongyou Chen, Yen-Rong Chen, Huaping Chen, Yu-Xin Chen, Bohe Chen, Kehua Chen, Zilin Chen, Zhang-Liang Chen, Ziqi Chen, Yinglian Chen, Hui-Wen Chen, Peipei Chen, Baolin Chen, Zugen Chen, Kangzhen Chen, Yanhan Chen, Sung-Fang Chen, Zheping Chen, Zixuan Chen, Jiajia Chen, Yuanjian Chen, Lili Chen, Xiangli Chen, Ban Chen, Yuewen Chen, X Chen, Yan-Qiong Chen, Chider Chen, Yung-Hsiang Chen, Hanlin Chen, Xiangjun Chen, Haibing Chen, Le Chen, Xuan Chen, Xue-Ying Chen, Zexiao Chen, Chen-Yu Chen, Zhe-Ling Chen, Fan Chen, Hsin-Yi Chen, Feilong Chen, Zilong Chen, Yi-Jen Chen, Zhiyun Chen, Ning Chen, Wenxu Chen, Chuanbing Chen, Yaxi Chen, Yi-Hong Chen, Eleanor Y Chen, Yuexin Chen, Kexin Chen, Shoujun Chen, Yen-Ju Chen, Yu-Chuan Chen, Yen-Teen Chen, Bao-Ying Chen, Xiaopeng Chen, Danli Chen, Katharine Y Chen, Jingli Chen, Qianyi Chen, Zihua Chen, Ya-xi Chen, Xuanxu Chen, Chung-Hung Chen, Yajie Chen, Cindi Chen, Hua Chen, Shuliang Chen, Elizabeth H Chen, Gen-Der Chen, Bingyu Chen, Keyang Chen, Siyu S Chen, Xinpu Chen, Yau-Hung Chen, Hsueh-Fen Chen, Han-Hsiang Chen, Wei Ning Chen, Guopu Chen, Zhujun Chen, Yurong Chen, Yuxian Chen, Wanjun Chen, Qiu-Jing Chen, Qifang Chen, Yuhan Chen, Jingshen Chen, Zhongliang Chen, Ching-Hsuan Chen, Zhaoyao Chen, Yongning Chen, Marcus Y Chen, Ping Chen, Junfei Chen, Yung-Wu Chen, Xueting Chen, Yingchun Chen, Wan-Yan Chen, Yuxin Chen, Yisheng Chen, Chun-Yuan Chen, Yulian Chen, Yan-Jun Chen, Guoxun Chen, Ding Chen, Yu-Fen Chen, Jason A Chen, Shuyi Chen, Cuilan Chen, Ruijuan Chen, Kevin Chen, Xuanmao Chen, Shen-Ming Chen, Ya-Nan Chen, Sean Chen, Zhaowei Chen, Xixi Chen, Yu-Chia Chen, Xuemin Chen, Binlong Chen, Weina Chen, Xuemei Chen, Di Chen, P P Chen, Yubin Chen, Chunhua Chen, Li-Chieh Chen, Ping-Chung Chen, Zhihao Chen, Xinyang Chen, Chan Chen, Yan Jie Chen, Shi-Qing Chen, Ivy Xiaoying Chen, Ying-Cheng Chen, Jia-Shun Chen, Shao-Wei Chen, Aiping Chen, Dexiang Chen, Qianfen Chen, Hongyu Chen, Wei-Kung Chen, Danlei Chen, Hongen Chen, Shipeng Chen, Jake Y Chen, Dongsheng Chen, Chien-Ting Chen, Shouzhen Chen, Hehe Chen, Yu-Tung Chen, Yilin Chen, Joy J Chen, Zhong Chen, Zhenfeng Chen, Zhongzhu Chen, Feiyang Chen, Xingxing Chen, Keyan Chen, Huimin Chen, Guanyu Chen, D. Chen, Dianke Chen, Zhigeng Chen, Sien-Tsong Chen, Yii-Der Chen, Chi-Yun Chen, Beidong Chen, Wu-Xian Chen, Zhihang Chen, Yuanqi Chen, Jianhua Chen, Xian Chen, Xiangding Chen, Jingteng Chen, Shuaiyu Chen, Xue-Mei Chen, Yu-Han Chen, Hongqiao Chen, Weili Chen, Yunzhu Chen, Guo-qing Chen, Miao Chen, Zhi Chen, Junhui Chen, Jing-Xian Chen, Zhiquan Chen, Shuhuang Chen, Shaokang Chen, Irwin Chen, Xiang Chen, Chuo Chen, Siting Chen, Keyuan Chen, Xia-Fei Chen, Zhihai Chen, Yuanyu Chen, Po-Sheng Chen, Qingjiang Chen, Yi-Bing Chen, Rongrong Chen, Katherine C Chen, Shaoxing Chen, Lifen Chen, Luyi Chen, Sisi Chen, Ning-Bo Chen, Yihong Chen, Guanjie Chen, Li-Hua Chen, Xiao-Hui Chen, Ting Chen, Chun-Han Chen, Xuzhuo Chen, Junming Chen, Zheng Chen, Wen-Jie Chen, Bingdi Chen, Jiang Ye Chen, Yanbin Chen, Duoting Chen, Shunyou Chen, Shaohua Chen, Jien-Jiun Chen, Jiaohua Chen, Shaoze Chen, Yifang Chen, Chiqi Chen, Yen-Hao Chen, Rui-Fang Chen, Hung-Sheng Chen, Kuey Chu Chen, Y S Chen, Xijun Chen, Chaoyue Chen, Heng-Sheng Chen, Lianfeng Chen, Yen-Ching Chen, Yuhong Chen, Yixin Chen, Yuanli Chen, Cancan Chen, Yanming Chen, Yajun Chen, Chaoping Chen, F-K Chen, Menglan Chen, Zi-Yang Chen, Yongfang Chen, Hsin-Hong Chen, Hongyan Chen, Chao-Wei Chen, Jijun Chen, Xiaochun Chen, Yazhuo Chen, Zhixin Chen, YongPing Chen, Jui-Yu Chen, Mian-Mian Chen, Liqiang Chen, Y P Chen, D-F Chen, Jinhao Chen, Yanyan Chen, Chang-Zheng Chen, Shao-long Chen, Guoshun Chen, Lo-Yun Chen, Yen-Lin Chen, Bingqian Chen, Dafang Chen, Yi-Chung Chen, Liming Chen, Qiuli Chen, Shuying Chen, Chih-Mei Chen, Renyu Chen, Wei-Hao Chen, Lihua Chen, Hang Chen, Hai-Ning Chen, Hu Chen, Yu-Fu Chen, Yalan Chen, Wan-Tzu Chen, Benjamin Jieming Chen, Yingting Chen, Jiacai Chen, Ning-Yuan Chen, Shuo-Bin Chen, Yu-Ling Chen, Jian-Kang Chen, Hengsan Chen, Yu-Ting Chen, Y Chen, Qingjie Chen, Jiong Chen, Chaoyi Chen, Yunlin Chen, Gang Chen, Hui-Chun Chen, Li-Tzong Chen, Zhangliang Chen, Qiangpu Chen, Xianbo Chen, Jinxuan Chen, Hebing Chen, Ran Chen, Zhehui Chen, Carol X-Q Chen, Yuping Chen, Xiangyu Chen, Xinyu Chen, Qianyun Chen, Junyi Chen, B-S Chen, Zhesheng Chen, Man Chen, Dali Chen, Danyu Chen, Huijiao Chen, Naisong Chen, Qitong Chen, Chueh-Tan Chen, Kai-Ming Chen, Jiarou Chen, Huang Chen, Chunjie Chen, Weiping Chen, Po-Min Chen, Guang-Chao Chen, Danxia Chen, Youran Chen, Chuanzhi Chen, Peng-Cheng Chen, Wen-Tsung Chen, Linxi Chen, Si-guo Chen, Zike Chen, Zhiyu Chen, Wanting Chen, Jiangxia Chen, Wenhua Chen, Roufen Chen, Shi-You Chen, Fang-Pei Chen, Chu Chen, Feifeng Chen, Chunlin Chen, Yunwei Chen, Wenbing Chen, Xuejun Chen, Meizhen Chen, Li Jia Chen, Tianhua Chen, Xiangmei Chen, Kewei Chen, Yuh-Ling Chen, Dejuan Chen, Jiyan Chen, Xinzhuo Chen, Yue-Lai Chen, Hsiao-Jou Cortina Chen, Weiqin Chen, Huey-Miin Chen, Elizabeth Suchi Chen, Kai-Ting Chen, Lizhen Chen, Xiaowen Chen, Chien-Yu Chen, Lingjun Chen, Gonglie Chen, Jiao Chen, Zhuo-Yuan Chen, Wei-Peng Chen, Xiangna Chen, Jiade Chen, Lanmei Chen, Siyu Chen, Kunpeng Chen, Hung-Chi Chen, Jia Chen, Shuwen Chen, Siqin Chen, Zhenlei Chen, Wen-Yi Chen, Si-Yuan Chen, Yidan Chen, Tianfeng Chen, Fu Chen, Leqi Chen, Jiamiao Chen, Shasha Chen, Qingyi Chen, Ben-Kuen Chen, Haitao Chen, Qi Chen, Yihao Chen, Yunfeng Chen, Elizabeth S Chen, Yiming Chen, Youwei Chen, Lichun Chen, Yanfei Chen, Hongxing Chen, Muh-Shy Chen, Yingyu Chen, Weihong Chen, Ming Chen, Kelin Chen, Duan-Yu Chen, Shi-Yi Chen, Shih-Yu Chen, Yanling Chen, Shuanghui Chen, Ya Chen, Yusheng Chen, Yuting Chen, Shiming Chen, Xinqiao Chen, Hongbo Chen, Mien-Cheng Chen, Jiacheng Chen, Herbert Chen, Ji-ling Chen, Sun Chen, Chen-Sheng Chen, Na Chen, Chih-Yi Chen, Wenfang Chen, Yii-Der I Chen, Qinghua Chen, Shuai Chen, Hsi-Hsien Chen, F Chen, Guo-Chong Chen, Zhe Chen, Beijian Chen, Roger Chen, You-Ming Chen, Hongzhi Chen, Zhen-Yu Chen, Xianxiong Chen, Chang Chen, Chujie Chen, Chuannan Chen, Kan Chen, Lu-Biao Chen, Yupei Chen, Qiu-Sheng Chen, Shangduo Chen, Yuan-Yuan Chen, Yundai Chen, Binzhen Chen, Cai-Long Chen, Yen-Chen Chen, Xue-Xin Chen, Yanru Chen, Chunxiu Chen, Yifa Chen, Xingdong Chen, Ruey-Hwa Chen, Shangzhong Chen, Ching-Wen Chen, Danna Chen, Jingjing Chen, Yafei Chen, Dandan Chen, Pei-Yi Chen, Shan Chen, Guanghao Chen, Longqing Chen, Yen-Cheng Chen, Zhanjuan Chen, Jinguo Chen, Zhongxiu Chen, Rui-Min Chen, Shunde Chen, Xun Chen, Jianmin Chen, Linyi Chen, Ying-Ying Chen, Chien-Hsiun Chen, Li-Nan Chen, Yu-Ming Chen, Qianqian Chen, Xue-Yan Chen, Shengdi Chen, Huali Chen, Xinyue Chen, Ching-Yi Chen, Honghai Chen, Baosheng Chen, Pingguo Chen, Yike Chen, Yuxiang Chen, Qing-Hui Chen, Yuanwen Chen, Yongming Chen, Zongzheng Chen, Ruiying Chen, Huafei Chen, Tingen Chen, Zhouliang Chen, Shih-Yin Chen, Shanyuan Chen, Yiyin Chen, Feiyu Chen, Zitao Chen, Constance Chen, Zhoulong Chen, Haide Chen, Jiang Chen, Ray-Jade Chen, Shiuhwei Chen, Chih-Chieh Chen, Chaochao Chen, Lijuan Chen, Qianling Chen, Jian-Min Chen, Xihui Chen, Yuli Chen, Wu-Jun Chen, Diyun Chen, Alice P Chen, Jingxuan Chen, Chiung-Mei Chen, Shibo Chen, M L Chen, Lena W Chen, Xiujuan Chen, Christopher S Chen, Yeh Chen, Xingyong Chen, Feixue Chen, Boyu Chen, Weixian Chen, Tingting Chen, Bosong Chen, Junjie Chen, Han-Min Chen, Szu-Yun Chen, Qingliang Chen, Huatao Chen, Bin Chen, L B Chen, Xuanyi Chen, Chun Chen, Dong Chen, Yinjuan Chen, Jiejian Chen, Lu-Zhu Chen, Alex F Chen, Pei-Chun Chen, Chien-Jen Chen, Y M Chen, Xiao-Chen Chen, Tania Chen, Yang Chen, Yangxin Chen, Mark I-Cheng Chen, Haiming Chen, Shuo Chen, Yong Chen, Hsiao-Tan Chen, Erzhen Chen, Jiaye Chen, Fangyan Chen, Guanzheng Chen, Haoyun Chen, Jiongyu Chen, Baofeng Chen, Yuqin Chen, Juan Chen, Haobo Chen, Shuhong Chen, Fu-Shou Chen, Wei-Yu Chen, Haw-Wen Chen, Feifan Chen, Deqian Chen, Linlin Chen, Xiaoshan Chen, Hui Chen, Wenwen Chen, Yanli Chen, Yuexuan Chen, Xiaoyin Chen, Yen-Chang Chen, Tiantian Chen, Ruiai Chen, Alice Y Chen, Jinglin Chen, Zifan Chen, Wantao Chen, Shanshan Chen, Jianjun Chen, Xiaoyuan Chen, Xuefei Chen, Runfeng Chen, Weisan Chen, Guangnan Chen, Junpan Chen, An Chen, Lankai Chen, Yiding Chen, Tianpeng Chen, Ya-Ting Chen, Lijin Chen, Ching-Yu Chen, Y Eugene Chen, Guanglong Chen, Rongyuan Chen, Yali Chen, Yanan Chen, Liyun Chen, Shuai-Bing Chen, Zhixue Chen, Xiaolu Chen, Xiao-he Chen, Hongxiang Chen, Bing-Feng Chen, Gary K Chen, Xiaohui Chen, Jin-Wu Chen, Qiuxiang Chen, Huaqiu Chen, X Steven Chen, Xiaoqian Chen, Chao-Jung Chen, Zhengjun Chen, Yong-Ping Chen, Zhelin Chen, Xuancai Chen, Yi-Hsuan Chen, Daiyu Chen, Gui Mei Chen, Hongqi Chen, Zhizhong Chen, Mengting Chen, Guofang Chen, Jian-Guo Chen, Hou-Zao Chen, Yuyao Chen, Lixia Chen, Yu-Yang Chen, Zhengling Chen, Qinfen Chen, Jiajun Chen, Xue-Qing Chen, Shenghui Chen, Yii-Derr Chen, Linbo Chen, Yanjing Chen, S Pl Chen, Chi-Long Chen, Jiawei Chen, Rong-Hua Chen, Shu-Fen Chen, Yu-San Chen, Ying-Lan Chen, Xiaofen Chen, Weican Chen, Xin Chen, Yumei Chen, Ruohong Chen, You-Xin Chen, Tse-Ching Chen, Xiancheng Chen, Yu-Pei Chen, Weihao Chen, Baojiu Chen, Haimin Chen, Zhihong Chen, Jion Chen, Yi-Chun Chen, Ping-Kun Chen, Wan Jun Chen, Willian Tzu-Liang Chen, Qingshi Chen, Ren-Hui Chen, Weihua Chen, Hanjing Chen, Guihao Chen, Xiao-Qing Chen, Po-Yu Chen, Liangsheng Chen, Fred K Chen, Haiying Chen, Tzu-Chieh Chen, Wei J Chen, Zhen Chen, Shu Chen, Jie Chen, Chung-Hao Chen, Zi-Qing Chen, Yu-Xia Chen, Weijia Chen, Ming-Han Chen, Yaodong Chen, Yong-Zhong Chen, Jinquan Chen, Haijiao Chen, Tom Wei-Wu Chen, Jingzhou Chen, Ya-Peng Chen, Shiwei Chen, Xiqun Chen, Yingjie Chen, Wenjun Chen, Linjie Chen, Hung-Chun Chen, Xiaoping Chen, Haoran Chen, Qiang Chen, Sy-Jou Chen, Y U Chen, Weineng Chen, Li-hong Chen, Cheng-Fong Chen, Yajing Chen, Song Chen, Qiaoli Chen, Yiru Chen, Guang-Yu Chen, Zhi-bin Chen, Deyu Chen, C Y Chen, Junhong Chen, Yonghui Chen, Chaoli Chen, Syue-Ting Chen, Sufang Chen, I-Chun Chen, Shangsi Chen, Xiao-Wei Chen, Qinsheng Chen, Zhao-Xia Chen, Yun-Yu Chen, Chi-Chien Chen, Wenxing Chen, Meng Chen, Zixin Chen, Jianhui Chen, Yuanyuan Chen, Jiamin Chen, Wei-Wei Chen, Xingyi Chen, Yen-Ni Chen, Danxiang Chen, Po-Ju Chen, Mei-Ru Chen, Ziying Chen, E S Chen, Tailai Chen, Qingyang Chen, Miaomiao Chen, Shuntai Chen, Wei-Lun Chen, Xuanli Chen, Zhengwei Chen, Fengju Chen, Chengwei Chen, Xujia Chen, Faye H Chen, Xiaoxiao Chen, Shengpan Chen, Shin-Yu Chen, Shiyao Chen, Yuan-Shen Chen, Shengzhi Chen, Shaohong Chen, Ching-Jung Chen, Zihao Chen, Kaiquan Chen, Duo-Xue Chen, Xiaochang Chen, Siping Chen, Rongfeng Chen, Jiali Chen, Hsin-Han Chen, Xiaohua Chen, Delong Chen, Wenjie Chen, Huijia Chen, Yunn-Yi Chen, Siyi Chen, Zhengming Chen, Chu-Huang Chen, Zhuchu Chen, Yuanbin Chen, Jinyong Chen, Yunzhong Chen, Pan Chen, Bihong T Chen, Yunyun Chen, Shujuan Chen, M Chen, Mulan Chen, Jiaren Chen, Zechuan Chen, Jian-Qing Chen, Wei-Hui Chen, Lifeng Chen, Geng Chen, Yan-Ming Chen, Zhijian J Chen, Honghui Chen, Wenfan Chen, Zhongbo Chen, Rouxi Chen, Ye-Guang Chen, Zhimin Chen, Tzu-Ting Chen, Xiaolei Chen, Ziyuan Chen, Shilan Chen, Ruiqi Chen, Xiameng Chen, Huijie Chen, Jiankui Chen, Yuhang Chen, Jianzhong Chen, Wen-Qi Chen, Fa Chen, Li-Mien Chen, Xing-Lin Chen, Xuxiang Chen, Erbao Chen, Jiaqing Chen, Hsiang-Wen Chen, Jiaxin Chen
articles
Jiali Zhu, Xuemei Zhang, Xiu Chen +5 more · 2017 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Usnea is a lichen of Usnea diffracta Vain and Usnea longissima Ach, which belongs to the genus Usnea Adans of Usneaceae. Usnea exerts numerous pharmacological activities, while its lipid regulatory ac Show more
Usnea is a lichen of Usnea diffracta Vain and Usnea longissima Ach, which belongs to the genus Usnea Adans of Usneaceae. Usnea exerts numerous pharmacological activities, while its lipid regulatory activities remain unreported. This study aims to evaluate the effects of aqueous and ethanol extracts of Usnea on the regulation of lipid metabolism and to explore the possible mechanism. Hyperlipidemia rat model was established by feeding with high-fat diet for 45days. Therapy rats were intragastrically administered with simvastatin (0.004g/kg/d), Usnea aqueous extract (2.766g/kg/d), or Usnea ethanol extract (2.766g/kg/d) for 20days. Pharmacodynamic effects, including body weight, serum and liver lipid levels, total bile acid (TBA), aspartate aminotransferase (AST), alanine aminotransferase (ALT), liver index, and hepatic morphological changes were evaluated. To explore the mechanisms, the lipase activities and protein expressions related to lipid metabolism were detected. Compared with the model group, aqueous and ethanol extracts of Usnea can slow down the weight gain of rats, significantly reduce the serum levels of total cholesterol, triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and the liver contents of TG, LDL-C, as well as significantly increase the contents of high-density lipoprotein cholesterol in serum. In addition, aqueous and ethanol extracts of Usnea can significantly reduce the serum contents of AST and ALT. Furthermore, ethanol extract of Usnea can also significantly reduce the TBA content in serum and liver index. Liver tissue pathological observation showed that aqueous and ethanol extracts of Usnea can improve cell degeneration to a certain extent. Aqueous and ethanol extracts of Usnea can significantly reduce sterol regulatory element-binding proteins-1c, and liver X receptor α (LXR-α) protein expressions. Furthermore, aqueous extract of Usnea can significantly increase hepatic lipase activity and promote apoprotein A5 (ApoA5) protein expression. These findings strongly suggest that the aqueous and ethanol extracts of Usnea play significant roles in regulating lipid metabolism, and the ethanol extract exhibits higher activity than the aqueous extract. The mechanism of the regulation of lipid metabolism by Usnea aqueous extract may involve the increased ApoA5 protein expression via inhibition of the LXR-α signal pathway; however, the mechanism of the regulation of lipid metabolism by Usnea ethanol extract remains to be further studied. Show less
no PDF DOI: 10.1016/j.biopha.2017.08.012
APOA5
Yu-Chieh Lee, Chia-Yu Su, Yuan-Feng Lin +5 more · 2017 · Oncotarget · Impact Journals · added 2026-04-24
Colorectal cancer (CRC) is one of the leading cancers worldwide. Surgery is the main therapeutic modality for stage II CRC. However, the implementation of adjuvant chemotherapy remains controversial a Show more
Colorectal cancer (CRC) is one of the leading cancers worldwide. Surgery is the main therapeutic modality for stage II CRC. However, the implementation of adjuvant chemotherapy remains controversial and is not universally applied so far. In this study, we found that the protein expression of lysosomal acid phosphatase 2 (ACP2) was increased in CRC and that stage II CRC patients with high ACP2 expression showed a poorer outcome than those with low ACP2 expression (p = 0.004). To investigate this discrepancy, we analyzed the relation between ACP2 expression and several clinical cofactors.Among patients who received chemotherapy, those with an high expression of ACP2 showed better survival in both stage II and III CRC than those with low ACP2 expression. In stage II CRC patients, univariate analysis showed ACP2 expression and T stage to be cofactors significantly associated with overall survival (ACP2: p = 0.006; T stage: p = 0.034). Multivariate Cox proportion hazard model analysis also revealed ACP2 to be an independent prognostic factor for overall survival (ACP2: p = 0.006; T stage: p = 0.041). Furthermore, ACP2-knockdown CRC cells showed an increase in chemoresistance to 5-FU treatment and increased proliferation marker in the ACP2 knockdown clone.Taken together, our results suggested that ACP2 is an unfavorable prognostic factor for stage II CRC and may serve as a potential chemotherapy-sensitive marker to help identify a subset of stage II and III CRC patients for whom chemotherapy would improve survival.Highlights1. To the best of our knowledge, the study is the first report to show ACP2 overexpression in human colorectal cancer (CRC) and its association with poor outcome in stage II CRC.2. Patients with stage II and III CRCs with high expression of ACP2 were more sensitive to chemotherapy than those with a low expression.3. ACP2 expression may serve as a marker for CRC patients receiving chemotherapy and help identify the subset of CRC patients who would benefit from chemotherapy. Show less
📄 PDF DOI: 10.18632/oncotarget.14552
ACP2
Cheng Wang, Na Qin, Meng Zhu +12 more · 2017 · Carcinogenesis · Oxford University Press · added 2026-04-24
Quantitative trait loci (QTLs) are widely used as instruments to infer causal risk factors of diseases based on the idea of mendelian randomization. Plasma metabolites can serve as risk factors of can Show more
Quantitative trait loci (QTLs) are widely used as instruments to infer causal risk factors of diseases based on the idea of mendelian randomization. Plasma metabolites can serve as risk factors of cancer, and the heritability of many circulating metabolites was high. We conducted a metabolome-wide association study (MWAS) to systematically investigate the effects of genetic variants on metabolites and lung cancer based on published genome-wide association study (GWASs) and metabolic-QTL (mQTL) study. Then we confirmed the results by subsequent genetic and metabolic validations and inferred the causal relationship between identified metabolites and lung cancer through genetic variant(s). We firstly identified six polyunsaturated fatty acids (PUFAs) represented by rs174548-linked haplotype were significantly associated with lung cancer risk in a Chinese GWAS (2311 cases and 3077 controls). Rs174548 was further confirmed to be associated with lung cancer in 13 821 Europeans and 18 471 Asians (ORmeta = 0.87, Pmeta = 1.76 × 10-15) and the effect was much stronger in females (Pinteraction = 6.00 × 10-4). We next validated rs174548-plasma PUFA association in 253 Chinese subjects (β = -0.57, P = 1.68 × 10-3). Rs174548 was also found associated with FADS1 (the major fatty acid desaturase of identified PUFAs) expression in liver tissues. Taken together, we found that rs174548 was associated with both PUFAs and lung cancer. Because rs174548 was the only mQTL variant of PUFAs reported by previous GWASs and explained a large proportion of heritability, we proposed that plasma PUFAs could be causally associated with lung cancer based on the idea of mendelian randomization. These findings provide a diet-related risk factor and may have important implications for prevention on lung cancer. Show less
no PDF DOI: 10.1093/carcin/bgx084
FADS1
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
Gen Li, Huidong Tang, Cheng Wang +4 more · 2017 · Sleep · Oxford University Press · added 2026-04-24
The aim of the study was to investigate the relationship between genetic factors and primary restless legs syndrome (RLS) in Chinese population. A total of 116 RLS patients and 200 controls were recru Show more
The aim of the study was to investigate the relationship between genetic factors and primary restless legs syndrome (RLS) in Chinese population. A total of 116 RLS patients and 200 controls were recruited and the diagnosis of RLS was based on the criteria of International RLS Study Group. Polymer chain reaction (PCR) and sequencing were used to detect 19 single nucleotide polymorphisms (SNPs) in six genetic loci (MEIS1, BTBD9, PTPRD, MAP2K5/SKOR1, TOX3, and Intergenic region of 2p14). Our study found that one SNP increased the risk of RLS in Chinese population: rs6494696 of MAP2K5/SKOR1 (odds ratio [OR] = 0.09, p < .0001, recessive model). A further meta-analysis of RLS in Asian population found that two SNPs of BTBD9 increased the risk of RLS: rs9296249 of BTBD9 (OR = 1.44, p = .000, T allele), rs9357271 of BTBD9 (OR = 1.38, p = .021, dominant model). Our results confirmed the association of BTBD9 and MAP2K5/SKOR1 with primary RLS in Chinese population. Show less
no PDF DOI: 10.1093/sleep/zsx028
MAP2K5
Keri L Tabb, Jacklyn N Hellwege, Nicholette D Palmer +18 more · 2017 · Annals of human genetics · Blackwell Publishing · added 2026-04-24
Family-based methods are a potentially powerful tool to identify trait-defining genetic variants in extended families, particularly when used to complement conventional association analysis. We utiliz Show more
Family-based methods are a potentially powerful tool to identify trait-defining genetic variants in extended families, particularly when used to complement conventional association analysis. We utilized two-point linkage analysis and single variant association analysis to evaluate whole exome sequencing (WES) data from 1205 Hispanic Americans (78 families) from the Insulin Resistance Atherosclerosis Family Study. WES identified 211,612 variants above the minor allele frequency threshold of ≥0.005. These variants were tested for linkage and/or association with 50 cardiometabolic traits after quality control checks. Two-point linkage analysis yielded 10,580,600 logarithm of the odds (LOD) scores with 1148 LOD scores ≥3, 183 LOD scores ≥4, and 29 LOD scores ≥5. The maximal novel LOD score was 5.50 for rs2289043:T>C, in UNC5C with subcutaneous adipose tissue volume. Association analysis identified 13 variants attaining genome-wide significance (P < 5 × 10 Show less
📄 PDF DOI: 10.1111/ahg.12184
APOA5
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
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
Rong-Quan He, Xiao-Jiao Li, Lu Liang +6 more · 2017 · BMC cancer · BioMed Central · added 2026-04-24
Non-small cell lung cancer (NSCLC) has led to the highest cancer-related mortality for decades. To enhance the efficiency of early diagnosis and therapy, more efforts are urgently needed to reveal the Show more
Non-small cell lung cancer (NSCLC) has led to the highest cancer-related mortality for decades. To enhance the efficiency of early diagnosis and therapy, more efforts are urgently needed to reveal the origins of NSCLC. In this study, we explored the effect of miR-542-5p in NSCLC with clinical samples and in vivo models and further explored the prospective function of miR-542-5p though bioinformatics methods. A total of 125 NSCLC tissue samples were collected, and the expression of miR-542-5p was detected by qRT-PCR. The relationship between miR-542-5p level and clinicopathological features was analyzed. The effect of miR-542-5p on survival time was also explored with K-M survival curves and Cox's regression. The effect of miR-542-5p on the tumorigenesis of NSCLC was verified with a chick chorioallantoic membrane (CAM) model. The potential target genes were predicted by bioinformatics tools, and relevant pathways were analyzed by GO and KEGG. Several hub genes were validated by Proteinatlas. The expression of miR-542-5p was down-regulated in NSCLC tissues, and consistent results were also found in the subgroups of adenocarcinoma and squamous cell carcinoma. Down-regulation of miR-542-5p was found to be connected with advanced TNM stage, vascular invasion, lymphatic metastasis and EGFR. Survival analyses showed that patients with lower miR-542-5p levels had markedly poorer prognosis. Both tumor growth and angiogenesis were significantly suppressed by miR-542-5p mimic in the CAM model. The potential 457 target genes of miR-542-5p were enriched in several key cancer-related pathways, such as morphine addiction and the cAMP signaling pathway from KEGG. Interestingly, six genes (GABBR1, PDE4B, PDE4C, ADCY6, ADCY1 and GIPR) from the cAMP signaling pathway were confirmed to be overexpressed in NSCLCs tissues. This evidence suggests that miR-542-5p is a potential tumor-suppressed miRNA in NSCLC, which has the potential to act as a diagnostic and therapeutic target of NSCLC. Show less
📄 PDF DOI: 10.1186/s12885-017-3646-1
GIPR
Li-Ting Deng, Yu-Ling Wu, Jun-Cheng Li +8 more · 2016 · PloS one · PLOS · added 2026-04-24
Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associ Show more
Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associated with important agronomical traits. Here, we screened reliable reference genes for accurately quantifying the expression of target genes using the technique of real-time quantitative polymerase chain reaction (RT-qPCR) in M. oleifera. Eighteen candidate reference genes were selected from a transcriptome database, and their expression stabilities were examined in 90 samples collected from the pods in different developmental stages, various tissues, and the roots and leaves under different conditions (low or high temperature, sodium chloride (NaCl)- or polyethyleneglycol (PEG)- simulated water stress). Analyses with geNorm, NormFinder and BestKeeper algorithms revealed that the reliable reference genes differed across sample designs and that ribosomal protein L1 (RPL1) and acyl carrier protein 2 (ACP2) were the most suitable reference genes in all tested samples. The experiment results demonstrated the significance of using the properly validated reference genes and suggested the use of more than one reference gene to achieve reliable expression profiles. In addition, we applied three isotypes of the superoxide dismutase (SOD) gene that are associated with plant adaptation to abiotic stress to confirm the efficacy of the validated reference genes under NaCl and PEG water stresses. Our results provide a valuable reference for future studies on identifying important functional genes from their transcriptional expressions via RT-qPCR technique in M. oleifera. Show less
📄 PDF DOI: 10.1371/journal.pone.0159458
ACP2
Tong-Hong Wang, Cheng-Chia Yu, Yong-Shiang Lin +6 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the fu Show more
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the function of lncRNAs in hepatocellular carcinoma (HCC) progression remains largely unknown. In this study, we performed a comprehensive microarray analysis of lncRNA expression using human HCC specimens. After validation in 119 human HCC tissues, we identified a novel tumor suppressor lncRNA, CPS1 intronic transcript 1 (CPS1-IT1). To elucidate the clinical significance of CPS1-IT1 in HCC, correlations between CPS1-IT1 levels, clinical parameters, and survival outcomes were analyzed. In vitro and in vivo functional assays were also performed to dissect the potential underlying mechanisms. Expression of CPS1-IT1 was significantly decreased in 73% of HCC tissues, and patients with low CPS1-IT1 expression had poor survival outcomes. Furthermore, in vitro functional assays indicated that CPS1-IT1 significantly reduced cell proliferation, migration and invasion capacities through reduced Hsp90 binding to and activation of HIF-1α, thereby suppressing the epithelial-mesenchymal transition (EMT). An in vivo animal model also demonstrated the tumor suppressor role of CPS1- IT1 via decreased tumor growth and metastasis. In conclusion, lncRNA CPS1-IT1 acts as a tumor suppressor in HCC by reducing HIF-1α activation and suppressing EMT. The findings of this study establish a function for CPS1-IT1 in HCC progression and suggest its potential as a new prognostic biomarker and target for HCC therapy. Show less
📄 PDF DOI: 10.18632/oncotarget.9635
CPS1
Xiao-Qin He, Yue-Qiang Song, Rui Liu +10 more · 2016 · PloS one · PLOS · added 2026-04-24
Axin-1, a negative regulator of Wnt signaling, is a versatile scaffold protein involved in centrosome separation and spindle assembly in mitosis, but its function in mammalian oogenesis remains unknow Show more
Axin-1, a negative regulator of Wnt signaling, is a versatile scaffold protein involved in centrosome separation and spindle assembly in mitosis, but its function in mammalian oogenesis remains unknown. Here we examined the localization and function of Axin-1 during meiotic maturation in mouse oocytes. Immunofluorescence analysis showed that Axin-1 was localized around the spindle. Knockdown of the Axin1 gene by microinjection of specific short interfering (si)RNA into the oocyte cytoplasm resulted in severely defective spindles, misaligned chromosomes, failure of first polar body (PB1) extrusion, and impaired pronuclear formation. However, supplementing the culture medium with the Wnt pathway activator LiCl improved spindle morphology and pronuclear formation. Downregulation of Axin1 gene expression also impaired the spindle pole localization of γ-tubulin/Nek9 and resulted in retention of the spindle assembly checkpoint protein BubR1 at kinetochores after 8.5 h of culture. Our results suggest that Axin-1 is critical for spindle organization and cell cycle progression during meiotic maturation in mouse oocytes. Show less
📄 PDF DOI: 10.1371/journal.pone.0157197
AXIN1
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
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
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
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
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
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
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
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
no PDF
FADS1
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
Zan Chen, Stefani N Thomas, David M Bolduc +4 more · 2016 · Biochemistry · ACS Publications · added 2026-04-24
PTEN is a lipid phosphatase that converts phosphatidylinositol 3,4,5-phosphate (PIP3) to phosphatidylinositol 4,5-phosphate (PIP2) and plays a critical role in the regulation of tumor growth. PTEN is Show more
PTEN is a lipid phosphatase that converts phosphatidylinositol 3,4,5-phosphate (PIP3) to phosphatidylinositol 4,5-phosphate (PIP2) and plays a critical role in the regulation of tumor growth. PTEN is subject to regulation by a variety of post-translational modifications, including phosphorylation on a C-terminal cluster of four Ser/Thr residues (380, 382, 383, and 385) and ubiquitylation by various E3 ligases, including NEDD4-1 and WWP2. It has previously been shown that C-terminal phosphorylation of PTEN can increase its cellular half-life. Using in vitro ubiquitin transfer assays, we show that WWP2 is more active than NEDD4-1 in ubiquitylating unphosphorylated PTEN. The mapping of ubiquitylation sites in PTEN by mass spectrometry showed that both NEDD4-1 and WWP2 can target a broad range of Lys residues in PTEN, although NEDD4-1 versus WWP2 showed a stronger preference for ubiquitylating PTEN's C2 domain. Whereas tetraphosphorylation of PTEN did not significantly affect its ubiquitylation by NEDD4-1, it inhibited PTEN ubiquitylation by WWP2. Single-turnover and pull-down experiments suggested that tetraphosphorylation of PTEN appears to weaken its interaction with WWP2. These studies reveal how the PTEN E3 ligases WWP2 and NEDD4-1 exhibit distinctive properties in Lys selectivity and sensitivity to PTEN phosphorylation. Our findings also provide a molecular mechanism for the connection between PTEN Ser/Thr phosphorylation and PTEN's cellular stability. Show less
no PDF DOI: 10.1021/acs.biochem.6b00448
WWP2
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
Deyi Zhang, Wei Wang, Xiujie Sun +8 more · 2016 · Autophagy · Taylor & Francis · added 2026-04-24
Macroautophagy/autophagy is a conserved catabolic process that recycles cytoplasmic material during low energy conditions. BECN1/Beclin1 (Beclin 1, autophagy related) is an essential protein for funct Show more
Macroautophagy/autophagy is a conserved catabolic process that recycles cytoplasmic material during low energy conditions. BECN1/Beclin1 (Beclin 1, autophagy related) is an essential protein for function of the class 3 phosphatidylinositol 3-kinase (PtdIns3K) complexes that play a key role in autophagy nucleation and elongation. Here, we show that AMP-activated protein kinase (AMPK) regulates autophagy by phosphorylating BECN1 at Thr388. Phosphorylation of BECN1 is required for autophagy upon glucose withdrawal. BECN1(T388A), a phosphorylation defective mutant, suppresses autophagy through decreasing the interaction between PIK3C3 (phosphatidylinositol 3-kinase catalytic subunit type 3) and ATG14 (autophagy-related 14). The BECN1(T388A) mutant has a higher affinity for BCL2 than its wild-type counterpart; the mutant is more prone to dimer formation. Conversely, a BECN1 phosphorylation mimic mutant, T388D, has stronger binding to PIK3C3 and ATG14, and promotes higher autophagy activity than the wild-type control. These findings uncover a novel mechanism of autophagy regulation. Show less
no PDF DOI: 10.1080/15548627.2016.1185576
PIK3C3
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
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
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
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
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
Yin-Feng Dong, Zheng-Zhen Chen, Zhan Zhao +4 more · 2016 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
It is generally recognized that the inflammatory reaction in glia is one of the important pathological factors in brain ischemic injury. Our previous study has revealed that opening ATP-sensitive pota Show more
It is generally recognized that the inflammatory reaction in glia is one of the important pathological factors in brain ischemic injury. Our previous study has revealed that opening ATP-sensitive potassium (K-ATP) channels could attenuate glial inflammation induced by ischemic stroke. However, the detailed mechanisms are not well known. Primary cultured astrocytes separated from C57BL/6 mice were subjected to oxygen-glucose deprivation (OGD); cellular injuries were determined via observing the changes of cellular morphology and cell viability. MicroRNA (miR) and messenger RNA (mRNA) level was validated by real-time PCR. The interaction between microRNA and the target was confirmed via dual luciferase reporter gene assay. Expressions of proteins and inflammatory cytokines were respectively assessed by western blotting and enzyme-linked immunosorbent assay. OGD resulted in astrocytic damage, which was prevented by K-ATP channel opener nicorandil. Notably, we found that OGD significantly downregulated miR-7 and upregulated Herpud2. Our further study proved that miR-7 targeted Herpud2 3'UTR, which encoded endoplasmic reticulum (ER) stress protein-HERP2. Correspondingly, our results showed that OGD increased the levels of ER stress proteins along with significant elevations of pro-inflammatory cytokines, including tumor necrosis factor α (TNF-α) and interleukin 1β (IL-1β). Pretreatment with nicorandil could remarkably upregulate miR-7, depress the ER-related protein expressions including glucose-regulated protein 78 (GRP78), C/EBP-homologous protein (CHOP), and Caspase-12, and thereby attenuate inflammatory responses and astrocytic damages. These findings demonstrate that opening K-ATP channels protects astrocytes against OGD-mediated neuroinflammation. Potentially, miR-7-targeted ER stress acts as a key molecular brake on neuroinflammation. Show less
📄 PDF DOI: 10.1186/s12974-016-0527-5
HEY2