👤 Weirui 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, 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, Shu-Jen Chen, Li-Mien Chen, Xing-Lin Chen, Xuxiang Chen, Erbao Chen, Jiaqing Chen, Hsiang-Wen Chen, Jiaxin Chen
articles
Qiong Ye, Guo-Ping Tian, Hai-Peng Cheng +17 more · 2018 · Journal of atherosclerosis and thrombosis · added 2026-04-24
Atherosclerosis is the most common cause of cardiovascular disease, such as myocardial infarction and stroke. Previous study revealed that microRNA (miR)-134 promotes lipid accumulation and proinflamm Show more
Atherosclerosis is the most common cause of cardiovascular disease, such as myocardial infarction and stroke. Previous study revealed that microRNA (miR)-134 promotes lipid accumulation and proinflammatory cytokine secretion through angiopoietin-like 4 (ANGPTL4)/lipid lipoprotein (LPL) signaling in THP-1 macrophages. ApoE KO male mice on a C57BL/6 background were fed a high-fat/high-cholesterol Western diet, from 8 to 16 weeks of age. Mice were divided into four groups, and received a tail vein injection of miR-134 agomir, miR-134 antagomir, or one of the corresponding controls, respectively, once every 2 weeks after starting the Western diet. After 8 weeks we measured aortic atherosclerosis, LPL Activity, mRNA and protein levels of ANGPTL4 and LPL, LPL/ low-density lipoprotein receptor related protein 1 Complex Formation, proinflammatory cytokine secretion and lipid levels. Despite this finding, the influence of miR-134 on atherosclerosis in vivo remains to be determined. Using the well-characterized mouse atherosclerosis model of apolipoprotein E knockout, we found that systemic delivery of miR-134 agomir markedly enhanced the atherosclerotic lesion size, together with a significant increase in proinflammatory cytokine secretion and peritoneal macrophages lipid contents. Moreover, overexpression of miR-134 decreased ANGPTL4 expression but increased LPL expression and activity in both aortic tissues and peritoneal macrophages, which was accompanied by increased formation of LPL/low-density lipoprotein receptor-related protein 1 complexes in peritoneal macrophages. However, an opposite effect was observed in response to miR-134 antagomir. These findings suggest that miR-134 accelerates atherogenesis by promoting lipid accumulation and proinflammatory cytokine secretion via the ANGPTL4/LPL pathway. Therefore, targeting miR-134 may offer a promising strategy for the prevention and treatment of atherosclerotic cardiovascular disease. Show less
📄 PDF DOI: 10.5551/jat.40212
ANGPTL4
Hung-Chih Lin, Chong-Kuei Lii, Hui-Chun Chen +3 more · 2018 · The American journal of Chinese medicine · added 2026-04-24
oxLDL is involved in the pathogenesis of atherosclerotic lesions through cholesterol accumulation in macrophage foam cells. Andrographolide, the bioactive component of Andrographis paniculata, possess Show more
oxLDL is involved in the pathogenesis of atherosclerotic lesions through cholesterol accumulation in macrophage foam cells. Andrographolide, the bioactive component of Andrographis paniculata, possesses several biological activities such as anti-inflammatory, anti-oxidant, and anticancer functions. Scavenger receptors (SRs), including class A SR (SR-A) and CD36, are responsible for the internalization of oxLDL. In contrast, receptors for reverse cholesterol transport, including ABCA1 and ABCG1, mediate the efflux of cholesterol from macrophage foam cells. Transcription factor liver X receptor [Formula: see text] (LXR[Formula: see text] plays a key role in lipid metabolism and inflammation as well as in the regulation of ABCA1 and ABCG1 expression. Because of the contribution of inflammation to macrophage foam cell formation and the potent anti-inflammatory activity of andrographolide, we hypothesized that andrographolide might inhibit oxLDL-induced macrophage foam cell formation. The results showed that andrographolide reduced oxLDL-induced lipid accumulation in macrophage foam cells. Andrographolide decreased the mRNA and protein expression of CD36 by inducing the degradation of CD36 mRNA; however, andrographolide had no effect on SR-A expression. In contrast, andrographolide increased the mRNA and protein expression of ABCA1 and ABCG1, which were dependent on LXR[Formula: see text]. Andrographolide enhanced LXR[Formula: see text] nuclear translocation and DNA binding activity. Treatment with the LXR[Formula: see text] antagonist GGPP and transfection with LXR[Formula: see text] siRNA reversed the ability of andrographolide to stimulate ABCA1 and ABCG1 protein expression. In conclusion, inhibition of CD36-mediated oxLDL uptake and induction of ABCA1- and ABCG1-dependent cholesterol efflux are two working mechanisms by which andrographolide inhibits macrophage foam cell formation, which suggests that andrographolide could be a potential candidate to prevent atherosclerosis. Show less
no PDF DOI: 10.1142/S0192415X18500052
NR1H3
Michael C Chen, Ramreddy Tippana, Natalia A Demeshkina +4 more · 2018 · Nature · Nature · added 2026-04-24
Guanine-rich nucleic acid sequences challenge the replication, transcription, and translation machinery by spontaneously folding into G-quadruplexes, the unfolding of which requires forces greater tha Show more
Guanine-rich nucleic acid sequences challenge the replication, transcription, and translation machinery by spontaneously folding into G-quadruplexes, the unfolding of which requires forces greater than most polymerases can exert Show less
📄 PDF DOI: 10.1038/s41586-018-0209-9
DHX36
Eriko Negishi, Noboru Fukuda, Tomoyasu Otsuki +11 more · 2018 · American journal of physiology. Renal physiology · added 2026-04-24
We previously showed that complement 3 (C3) is highly expressed in mesenchymal tissues in spontaneously hypertensive rats (SHR). We targeted C3 gene by zinc-finger nuclease (ZFN) gene-editing technolo Show more
We previously showed that complement 3 (C3) is highly expressed in mesenchymal tissues in spontaneously hypertensive rats (SHR). We targeted C3 gene by zinc-finger nuclease (ZFN) gene-editing technology and investigated blood pressure and phenotype in SHR. Blood pressure was measured by tail-cuff and telemetry methods. Histology and expression of liver X receptor α (LXRα), renin, Krüppel-like factor 5 (KLF5), and E-cadherin were evaluated in kidneys. Mesangial cells (MCs) were removed from glomeruli from three strains, and we evaluated the phenotype in vitro. SHR showed the salt-sensitive hypertension that was abolished in C3 knockout (KO) SHR. Proliferation of MCs from SHR was higher than that from Wistar-Kyoto (WKY) rats and showed a synthetic phenotype. Renal injury scores were higher in SHR than in WKY rats and C3 KO SHR. Expression of E-cadherin was lower, and expression of renin was higher in the nephrotubulus from SHR than WKY rats and C3 KO SHR. Expression of C3 α-chain protein and α-smooth muscle actin protein was significantly higher in renal medulla from SHR than from WKY rats. Expression of angiotensinogen, LXRα, renin, and KLF5 mRNA was increased in kidney from SHR compared with C3 KO SHR. Intrarenal angiotensin II levels were significantly higher in kidney from SHR than WKY rats and C3 KO SHR. Urinary epinephrine and norepinephrine excretions were significantly higher in SHR than in WKY rats and C3 KO SHR. These findings showed that increased C3 induces salt-sensitive hypertension with increases in urinary catecholamine excretion and intrarenal activation of the renin-angiotensin system by the dedifferentiation of mesenchymal tissues in kidney from SHR. Show less
no PDF DOI: 10.1152/ajprenal.00370.2018
NR1H3
Wei-Jun Li, Rui-Xing Yin, Xiao-Li Cao +3 more · 2018 · Lipids in health and disease · BioMed Central · added 2026-04-24
Little is known about the association of the dedicator of cytokinesis 7 (DOCK7 rs1748195) and angiopoietin like 3 (ANGPTL3 rs12563308) single nucleotide polymorphisms (SNPs) and their haplotypes with Show more
Little is known about the association of the dedicator of cytokinesis 7 (DOCK7 rs1748195) and angiopoietin like 3 (ANGPTL3 rs12563308) single nucleotide polymorphisms (SNPs) and their haplotypes with serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese populations. This study aimed to detect such association in a Southern Chinese Han population. This study included 1728 subjects (CAD, 568; IS, 539; and controls, 621). Genotypes of the two SNPs were determined by the Snapshot technology. The genotypic and allelic frequencies of the rs1748195 SNP were different between CAD patients and controls (P < 0.05 for each), the rs1748195G allele frequency was higher in CAD patients than in controls (27.6% vs. 23.6%, P = 0.024). The genotypic frequencies of the rs12563308 SNP were also different between CAD patients and controls (P = 0.021). The rs1748195 SNP was associated with an increased risk of CAD after controlling for potential confounders and Bonferroni correction (P < 0.025 considered statistically significant; Recessive: OR = 1.79, 95% CI = 1.04-3.06, P = 0.017; Log-additive: OR = 1.27, 95% CI = 1.02-1.57, P = 0.014), whereas the rs12563308 SNP was associated with a decreased risk of CAD (Dominant: OR = 0.69, 95% CI = 0.45-0.94, P = 0.011; Log-additive: OR = 0.73, 95% CI = 0.49-0.89, P = 0.009). The rs1748195 SNP was also associated with an increased risk of severity to coronary artery atherosclerosis (Dominant: OR = 1.45, 95% CI = 1.07-2.11, P = 0.017; Log-additive: OR = 1.35, 95% CI = 1.09-1.82, P = 0.013). The interactions of SNP-environment on serum lipid levels and the risk of severity to coronary artery atherosclerosis, CAD and IS were noted. The rs1748195G-rs12563308T haplotype was associated with an increased angiographic severity to coronary artery atherosclerosis (OR = 1.46, 95% CI = 1.05-2.03), and the risk of CAD (OR = 1.37, 95% CI = 1.08-1.74). The interactions of haplotype-hypertension on the risk of CAD and haplotype-drinking on the risk of CAD/IS were observed. These results suggest that the DOCK-ANGPTL3 SNPs and their haplotypes were associated with the angiographic severity to coronary artery atherosclerosis and the risk of CAD and IS in the Southern Chinese Han population. Show less
📄 PDF DOI: 10.1186/s12944-018-0677-9
DOCK7

A novel

Zhonghua Chen, Qing Bi, Mingxiang Kong +2 more · 2018 · Oncology letters · added 2026-04-24
Multiple osteochondromas (MO) is an autosomal inherited disease that is characterized by benign bone tumors. However, the underlying mechanism of MO at a molecular level requires further investigation Show more
Multiple osteochondromas (MO) is an autosomal inherited disease that is characterized by benign bone tumors. However, the underlying mechanism of MO at a molecular level requires further investigation. The majority of mutations associated with MO occur in the exostosin glycosyltransferase genes ( Show less
📄 PDF DOI: 10.3892/ol.2018.9248
EXT1
Nan Wu, Guili Liu, Yi Huang +5 more · 2018 · Anatolian journal of cardiology · added 2026-04-24
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study e Show more
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study examined with 784 CHD cases and 739 non-CHD controls. Genotyping was performed on the MassARRAY iPLEX® assay platform. Our analyses revealed a significant association of APOE rs7259620 with CHD (genotype: χ2=6.353, df=2, p=0.042; allele: χ2=5.05, df=1, p=0.025; recessive model: χ2=5.57, df=1, p=0.018). A further gender-based subgroup analysis revealed significant associations of APOE rs7259620 and PPAP2B rs72664392 with CHD in males (genotype: χ2=8.379, df=2, p=0.015; allele: χ2=5.190, df=1, p=0.023; recessive model: χ2=19.3, df=1, p<0.0001) and females (genotype: χ2=9.878, df=2, p=0.007), respectively. Subsequent breakdown analysis by age showed that CETP rs4783961, MLXIPL rs35493868, and PON2 rs12704796 were significantly associated with CHD among individuals younger than 55 years of age (CETP rs4783961: χ2=8.966, df=1, p=0.011 by genotype; MLXIPL rs35493868: χ2=4.87, df=1, p=0.027 by allele; χ2=4.88, df=1, p=0.027 by dominant model; PON2 rs12704796: χ2=6.511, df=2, p=0.039 by genotype; χ2=6.210, df=1, p=0.013 by allele; χ2=5.03, df=1, p=0.025 by dominant model). Significant allelic association was observed between LEPR rs656451 and CHD among individuals older than 65 years of age (χ2=4.410, df=1, p=0.036). Our study revealed significant associations of APOE, PPAP2B, CETP, MLXIPL, PON2, and LEPR gene polymorphisms with CHD among the Han Chinese. Show less
📄 PDF DOI: 10.14744/AnatolJCardiol.2018.23682
CETP
Yuchan Li, Jian Wang, Jingyan Tang +6 more · 2018 · Medicine · added 2026-04-24
Hereditary multiple osteochondroma (HMO) is one of the most common genetic skeletal disorders. It is caused by mutations in either EXT1 or EXT2 resulting in abnormal skeletal growth and morphogenesis. Show more
Hereditary multiple osteochondroma (HMO) is one of the most common genetic skeletal disorders. It is caused by mutations in either EXT1 or EXT2 resulting in abnormal skeletal growth and morphogenesis. However, the spectrum and frequency of EXT1 and EXT2 mutations in Chinese patients with HMO was not previously investigated.Mutations were identified by performing Sanger sequencing analysis of the complete coding regions and flanking intronic sequences of EXT1 and EXT2, followed by multiplex ligation-dependent probe amplification (MLPA) analysis to detect gene deletions or duplications that could not be identified by the Sanger sequencing method.The present study identified pathogenic mutations in 93% (68/73) of unrelated HMO probands from 73 pedigrees. Mutations in EXT1 and EXT2 were identified in 53% (39/73) and 40% (29/73) of families. We identified 58 distinct mutations in EXT1 and EXT2, including 20 frameshift mutations, 16 nonsense mutations, 7 missense mutations, 9 splice site mutations, 5 large deletions, and 1 in-frame deletion mutation. Twenty-six of these mutations were novel and 32 were previously reported. Most of the mutations in EXT1 were base deletions or insertions (21/33), whereas the majority of those in EXT2 were single base substitution (18/25).Complete sequencing of both the EXT1 and EXT2 followed by MLPA analysis is recommended for genetic analysis of Chinese patients with HMO. This study provides a comprehensive characterization of the genetic aberrations found in Chinese patients with HMO and highlights the diagnostic value of molecular genetic analysis in this particular disease. Show less
📄 PDF DOI: 10.1097/MD.0000000000012855
EXT1
Wei-Fei Chen, Stephane Rety, Hai-Lei Guo +8 more · 2018 · Structure (London, England : 1993) · Elsevier · added 2026-04-24
Helicase DHX36 plays essential roles in cell development and differentiation at least partially by resolving G-quadruplex (G4) structures. Here we report crystal structures of the Drosophila homolog o Show more
Helicase DHX36 plays essential roles in cell development and differentiation at least partially by resolving G-quadruplex (G4) structures. Here we report crystal structures of the Drosophila homolog of DHX36 (DmDHX36) in complex with RNA and a series of DNAs. By combining structural, small-angle X-ray scattering, molecular dynamics simulation, and single-molecule fluorescence studies, we revealed that positively charged amino acids in RecA2 and OB-like domains constitute an elaborate structural pocket at the nucleic acid entrance, in which negatively charged G4 DNA is tightly bound and partially destabilized. The G4 DNA is then completely unfolded through the 3'-5' translocation activity of the helicase. Furthermore, crystal structures and DNA binding assays show that G-rich DNA is preferentially recognized and in the presence of ATP, specifically bound by DmDHX36, which may cooperatively enhance the G-rich DNA translocation and G4 unfolding. On the basis of these results, a conceptual G4 DNA-resolving mechanism is proposed. Show less
no PDF DOI: 10.1016/j.str.2018.01.008
DHX36
Olav B Smeland, Yunpeng Wang, Oleksandr Frei +10 more · 2018 · Schizophrenia bulletin · Oxford University Press · added 2026-04-24
Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, Show more
Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent. Show less
no PDF DOI: 10.1093/schbul/sbx148
DLG2
Chih-Yuan Fang, Mien-Cheng Chen, Tzu-Hao Chang +10 more · 2018 · International journal of molecular sciences · MDPI · added 2026-04-24
Lipid expression is increased in the atrial myocytes of mitral regurgitation (MR) patients. This study aimed to investigate key regulatory genes and mechanisms of atrial lipotoxic myopathy in MR. The Show more
Lipid expression is increased in the atrial myocytes of mitral regurgitation (MR) patients. This study aimed to investigate key regulatory genes and mechanisms of atrial lipotoxic myopathy in MR. The HL-1 atrial myocytes were subjected to uniaxial cyclic stretching for eight hours. Fatty acid metabolism, lipoprotein signaling, and cholesterol metabolism were analyzed by PCR assay (168 genes). The stretched myocytes had significantly larger cell size and higher lipid expression than non-stretched myocytes (all The Show less
📄 PDF DOI: 10.3390/ijms19124094
APOA4
Nicola M McKeown, Hassan S Dashti, Jiantao Ma +47 more · 2018 · Diabetologia · Springer · added 2026-04-24
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormon Show more
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10 In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study). Show less
📄 PDF DOI: 10.1007/s00125-017-4475-0
MLXIPL
Zhenzhen Sun, Yujie Xie, Yintong Chen +4 more · 2018 · Molecular neurobiology · Springer · added 2026-04-24
γ-Secretase has been a therapeutical target for its key role in cleaving APP to generate β-amyloid (Aβ), the primary constituents of senile plaques and a hallmark of Alzheimer's disease (AD) pathology Show more
γ-Secretase has been a therapeutical target for its key role in cleaving APP to generate β-amyloid (Aβ), the primary constituents of senile plaques and a hallmark of Alzheimer's disease (AD) pathology. Recently, γ-secretase-associating proteins showed promising role in specifically modulating APP processing while sparing Notch signaling; however, the underlying mechanism is still unclear. A co-immunoprecipitation (Co-IP) coupled with mass spectrometry proteomic assay for Presenilin1 (PS1, the catalytic subunit of γ-secretase) was firstly conducted to find more γ-secretase-associating proteins. Gene ontology analysis of these results identified Rab21 as a potential PS1 interacting protein, and the interaction between them was validated by reciprocal Co-IP and immunofluorescence assay. Then, molecular and biochemical methods were used to investigate the effect of Rab21 on APP processing. Results showed that overexpression of Rab21 enhanced Aβ generation, while silencing of Rab21 reduced the accumulation of Aβ, which resulted due to change in γ-secretase activity rather than α- or β-secretase. Finally, we demonstrated that Rab21 had no effect on γ-secretase complex synthesis or metabolism but enhanced PS1 endocytosis and translocation to late endosome/lysosome. In conclusion, we identified a novel γ-secretase-associating protein Rab21 and illustrate that Rab21 promotes γ-secretase internalization and translocation to late endosome/lysosome. Moreover, silencing of Rab21 decreases the γ-secretase activity in APP processing thus production of Aβ. All these results open new gateways towards the understanding of γ-secretase-associating proteins in APP processing and make inhibition of Rab21 a promising strategy for AD therapy. Show less
no PDF DOI: 10.1007/s12035-017-0606-3
RAB21
Yang Cheng, Yun Zhu, Jiajia Xu +6 more · 2018 · Molecular cancer · BioMed Central · added 2026-04-24
Protein kinase N2 (PKN2) is a PKC-related serine/threonine-protein kinase. PKN2 is required for tumor cell migration, invasion and apoptosis. However, the functional role of PKN2 in regulating tumor a Show more
Protein kinase N2 (PKN2) is a PKC-related serine/threonine-protein kinase. PKN2 is required for tumor cell migration, invasion and apoptosis. However, the functional role of PKN2 in regulating tumor associated macrophages (TAMs) polarization in colon cancer has never been reported. PKN2 expression in human colon cancer tissues was examined with immunohistochemistry (IHC). M1/M2 macrophage signatures were evaluated by RT-PCR, IHC and flow cytometry. The effects of PKN2 on tumor growth and TAM polarization were investigated both in vitro and in vivo. PKN2 targeted cytokines/pathway were analyzed by gene expression analysis and further confirmed by PCR, luciferase assay or western blot. Correlations between PKN2 and transcriptional factors for IL4 and IL10 were confirmed by ChIP-qPCR. The catalytic activities of PKN2 and DUSP6 were determined by kinase activity assay. Interactions between PKN2 and DUSP6 were confirmed by Co-IP. The expression of PKN2 in colon cancer cells predicted a favorable prognosis and was associated with low M2 macrophage content in human colon cancer tissues. PKN2 inhibited tumor growth in mice xenograft model and inhibited M2 phenotype polarization both in vitro and in vivo. Mechanistically, PKN2 suppresses the expression of IL4 and IL10 from colon cancer cells by inhibiting Erk1/2 phosphorylation, which is required for phosphorylation and binding of CREB and Elk-1 to the promoters of IL4 and IL10. DUSP6, which is phosphorylated and activated through direct association with PKN2, suppresses Erk1/2 activation. The expression of PKN2 in colon cancer cells suppresses tumor associated M2 macrophage polarization and tumor growth. Targeting PKN2 signaling pathway may provide a potential therapeutic strategy for colon cancer. Show less
📄 PDF DOI: 10.1186/s12943-017-0747-z
DUSP6
Yong Wang, Jing Su, Donghe Fu +6 more · 2018 · International journal of medical sciences · added 2026-04-24
no PDF DOI: 10.7150/ijms.25580
NRXN3
Hao Wang, Xiao-Meng Zhang, Go Tomiyoshi +39 more · 2018 · Oncotarget · Impact Journals · added 2026-04-24
Transient ischemic attack (TIA) is a predictor for cerebral infarction (CI), and early diagnosis of TIA is extremely important for the prevention of CI. We set out to identify novel antibody biomarker Show more
Transient ischemic attack (TIA) is a predictor for cerebral infarction (CI), and early diagnosis of TIA is extremely important for the prevention of CI. We set out to identify novel antibody biomarkers for TIA and CI, and detected matrix metalloproteinase 1 (MMP1), chromobox homolog 1 (CBX1), and chromobox homolog 5 (CBX5) as candidate antigens using serological identification of antigens by recombinant cDNA expression cloning (SEREX) and Western blotting to confirm the presence of serum antibodies against the antigens. Amplified luminescent proximity homogeneous assay-linked immunosorbent assay (AlphaLISA) revealed that serum antibody levels were significantly higher in patients with TIA or acute-phase CI (aCI) compared with healthy donors ( Show less
📄 PDF DOI: 10.18632/oncotarget.23789
CBX1
Yan Zhang, Longcai Wang, Haiyang Jia +5 more · 2018 · Journal of the neurological sciences · Elsevier · added 2026-04-24
A recent study analyzed 2053 multiple sclerosis (MS) cases and 799 healthy controls to investigate whether five genetic variants (rs11039149, rs12221497, rs2279238, rs7120118 and rs7114704) in NR1H3 a Show more
A recent study analyzed 2053 multiple sclerosis (MS) cases and 799 healthy controls to investigate whether five genetic variants (rs11039149, rs12221497, rs2279238, rs7120118 and rs7114704) in NR1H3 are associated with MS risk. However this study reported negative results. It is very important that the appropriate samples and approach should be used in replication studies, which may provide the correct interpretation of the results. Here, we evaluated the above findings using large-scale MS genome-wide association studies with a total of 27,148 samples including 9772 MS cases and 17,376 controls, and multiple expression quantitative trait loci datasets. The results suggest that rs7120118 and rs2279238 variants are significantly associated with MS risk, and could significantly regulate NR1H3 expression in kinds of human tissues and cells. In summary, these findings provide important supplementary information about the association between NR1H3 variants and MS risk. Show less
no PDF DOI: 10.1016/j.jns.2018.04.037
NR1H3
Xiong-Bai Zhu, Wen-Jun Lin, Chen Lv +4 more · 2018 · Journal of cellular biochemistry · Wiley · added 2026-04-24
This study aims to explore the effects of miR-539 on osteoblast proliferation and differentiation and osteoclast apoptosis in a rat model of osteoporosis, and its mechanism involving the regulation of Show more
This study aims to explore the effects of miR-539 on osteoblast proliferation and differentiation and osteoclast apoptosis in a rat model of osteoporosis, and its mechanism involving the regulation of the AXIN1-mediated wingless-Int (Wnt) signaling pathway. A rat model of osteoporosis was successfully established by ovariectomy. With osteoblasts and osteoclasts of rats not receiving ovariectomy in the sham group as control, those of osteoporotic rats were treated with miR-539 inhibitor, miR-539 mimic, and AXIN1 shRNA. The expression of miR-53, AXIN1, the Wnt pathway related-genes, apoptosis related-genes, and osteogenic markers were measured by RT-qPCR and Western blot analysis, respectively. Alkaline phosphatase (ALP) activity in osteoblast and tartrate-resistant acid phosphatase (TRAP) activity in osteoclasts were determined after cell transfection. Osteoblast and osteoclast viability was assayed by CCK-8 assay. Cell cycle and apoptosis of osteoblasts and osteoclasts were detected by flow cytometry. Lastly, alizarin red S staining was used to detect mineralized nodules of osteoblasts. Firstly, we determined that miR-539 was down-regulated in osteoblast and osteoclast of osteoporotic rats and AXIN1 was negatively regulated by miR-539. Additionally, overexpression of miR-539 increased the expressions of β-catenin, LEF1, c-myc, cyclin D1, RUNX2, BGP, BMP-2 in osteoblast as well as β-catenin, RhoA, caspase-3, and Bcl-2 in osteoclasts. Finally, overexpression of miR-539 elevated ALP activity, proliferation, and mineralized nodules in osteoblast and osteoclast apoptosis, with reduced TRAP activity in osteoclasts. Our results demonstrate that miR-539 promotes osteoblast proliferation and differentiation as well as osteoclast apoptosis through the AXIN1-dependent Wnt signaling pathway in osteoporotic rats. Show less
no PDF DOI: 10.1002/jcb.26910
AXIN1
Tingting Feng, Peng Liu, Xiao Wang +12 more · 2018 · Atherosclerosis · Elsevier · added 2026-04-24
Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent protein deacetylase. Recent studies have demonstrated that enhancing SIRT1 expression or activity may modulate cholesterol and lipid Show more
Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent protein deacetylase. Recent studies have demonstrated that enhancing SIRT1 expression or activity may modulate cholesterol and lipid metabolism. However, pharmacological and molecular regulators for SIRT1 are scarce. Here, we aimed to find novel small molecule modulators of SIRT1 to regulate cholesterol and lipid metabolism. A high-throughput screening assay was established to identify SIRT1 activators. Surface plasmon resonance and immunoprecipitation were performed to confirm the interaction of E1231 with SIRT1. Cholesterol assay was performed to demonstrate the in vitro effect of E1231. The in vivo effect of E1231 was evaluated in experimental models. E1231, a piperazine 1,4-diamide compound, was identified as a SIRT1 activator with EC We identified a novel SIRT1 activator E1231 and elucidated its beneficial effects on lipid and cholesterol metabolism. Our study suggests that E1231 might be developed as a novel drug for treating atherosclerosis. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2018.04.039
NR1H3
Qi Yan, Ying Ding, Yi Liu +15 more · 2018 · Human molecular genetics · Oxford University Press · added 2026-04-24
Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful ex Show more
Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful examples of genome-wide association study. However, most genetic studies to date have focused on case-control studies of late AMD (choroidal neovascularization or geographic atrophy). The genetic influences on disease progression are largely unexplored. We assembled unique resources to perform a genome-wide bivariate time-to-event analysis to test for association of time-to-late-AMD with ∼9 million variants on 2721 Caucasians from a large multi-center randomized clinical trial, the Age-Related Eye Disease Study. To our knowledge, this is the first genome-wide association study of disease progression (bivariate survival outcome) in AMD genetic studies, thus providing novel insights to AMD genetics. We used a robust Cox proportional hazards model to appropriately account for between-eye correlation when analyzing the progression time in the two eyes of each participant. We identified four previously reported susceptibility loci showing genome-wide significant association with AMD progression: ARMS2-HTRA1 (P = 8.1 × 10-43), CFH (P = 3.5 × 10-37), C2-CFB-SKIV2L (P = 8.1 × 10-10) and C3 (P = 1.2 × 10-9). Furthermore, we detected association of rs58978565 near TNR (P = 2.3 × 10-8), rs28368872 near ATF7IP2 (P = 2.9 × 10-8) and rs142450006 near MMP9 (P = 0.0006) with progression to choroidal neovascularization but not geographic atrophy. Secondary analysis limited to 34 reported risk variants revealed that LIPC and CTRB2-CTRB1 were also associated with AMD progression (P < 0.0015). Our genome-wide analysis thus expands the genetics in both development and progression of AMD and should assist in early identification of high risk individuals. Show less
no PDF DOI: 10.1093/hmg/ddy002
POC5
Chao-Wen Cheng, Che-Chang Chang, Hsiu-Wen Chen +2 more · 2018 · European journal of clinical investigation · Blackwell Publishing · added 2026-04-24
Among multiple causes, diabetic nephropathy (DN) is the major underlying renal disease that leads to end-stage renal disease (ESRD), and early diagnosis can effectively prevent or delay the progressio Show more
Among multiple causes, diabetic nephropathy (DN) is the major underlying renal disease that leads to end-stage renal disease (ESRD), and early diagnosis can effectively prevent or delay the progression to ESRD. Therefore, the current study aimed to develop noninvasive, accurate detection markers. For this study, 62 diabetes mellitus (DM) patients, 59 DN patients and 21 healthy controls (HCs) were recruited. All participants' serum samples were subjected to concavanalin (Con) A affinity chromatography, which utilizes glycoproteins to discover potential markers. From nano LC-MS and Western blot analysis, apolipoprotein A-IV (ApoA4) was selected which featured a gradual, almost twofold increase in the order of HC, DM and DN. In the Con A-based ELISA, the DM group was 1.91-fold higher than the HC group, while the DN group was 2.56-fold higher than the HCs and 1.33-fold higher than the DM group. In addition, significant positive correlations were observed between ApoA4 and blood urea nitrogen levels and between ApoA4 and creatine levels, while significant negative correlations were seen between serum protein levels and between serum albumin levels in comparisons of DM and DN samples. Serum Con A-bound ApoA4 levels were higher in the DM group than in HCs, and further increased in the DN group. Levels of ApoA4 were positively correlated with blood urea nitrogen and creatine, but negatively correlated with serum protein and albumin. This evidence supports serum Con A-bound ApoA4 as a circulating marker for predicting the progression of renal impairment in DM patients. Show less
no PDF DOI: 10.1111/eci.12937
APOA4
Wenxin Luo, Panwen Tian, Yue Wang +15 more · 2018 · International journal of cancer · Wiley · added 2026-04-24
Non-small-cell lung cancer (NSCLC) has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. While never-smoker patients with NSCLC have been well Show more
Non-small-cell lung cancer (NSCLC) has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. While never-smoker patients with NSCLC have been well studied through next generation sequencing, we have yet to recognize the potentially unique molecular features of young never-smoker patients with NSCLC. In this study, we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients, who were diagnosed with lung adenocarcinoma (LUAD) at 45 years or younger. Besides the well-known gene mutations (e.g., TP53 and EGFR), our study identified several potential lung cancer-associated gene mutations that were rarely reported (e.g., HOXA4 and MST1). The lung cancer-related copy number variations (e.g., EGFR and CDKN2A) were enriched in our cohort (41.7%, 15/36) and the lung cancer-related structural variations (e.g., EML4-ALK and KIF5B-RET) were commonly observed (22.2%, 8/36). Notably, new fusion partners of ALK (SMG6-ALK) and RET (JMJD1C-RET) were found. Furthermore, we observed a high prevalence (63.9%, 23/36) of potentially targetable genomic alterations in our cohort. Finally, we identified germline mutations in BPIFB1 (rs6141383, p.V284M), CHD4 (rs74790047, p.D140E), PARP1 (rs3219145, p.K940R), NUDT1 (rs4866, p.V83M), RAD52 (rs4987207, p.S346*), and MFI2 (rs17129219, p.A559T) were significantly enriched in the young never-smoker patients with LUAD when compared with the in-house noncancer database (p < 0.05). Our study provides a detailed mutational portrait of LUAD occurring in young never-smokers and gives insights into the molecular pathogenesis of this distinct subgroup of NSCLC. Show less
📄 PDF DOI: 10.1002/ijc.31542
JMJD1C
Xihui Chen, Lijuan Yuan, Mao Sun +2 more · 2018 · Journal of clinical laboratory analysis · Wiley · added 2026-04-24
Carbamoyl phosphate synthetase 1 deficiency (CPS1D) is a rare autosomal recessive disorder of the urea cycle, mostly characterized by hyperammonemia and the concomitant leukodystrophy. The onset of CP Show more
Carbamoyl phosphate synthetase 1 deficiency (CPS1D) is a rare autosomal recessive disorder of the urea cycle, mostly characterized by hyperammonemia and the concomitant leukodystrophy. The onset of CPS1D can be at any age, and the clinical manifestations are variable and atypical. Genetic tests are indispensable for accurate diagnosis of CPS1D on the basis of biochemical tests. Blood tandem mass spectrometric analysis and urea organic acidemia screening were performed on a Chinese neonatal patient with low activity, recurrent seizures, and hyperammonemia. Next-generation sequencing and Sanger sequencing were followed up for making a definite diagnosis. Bioinformatics tools were used for the conservation analysis and pathogenicity predictions of the identified mutations. Increased lactate in urea and decreased citrulline in blood were detected in the patient. Two novel mutations (c.173G>T, p.G58V in exon 2 and c.796G>A, p.G266R in exon 8) in CPS1 identified in the neonatal patient were found through coseparation verification. Both of the two mutations were predicted to be deleterious, and the two relevant amino acids exerted highly evolutionarily conserved. The final diagnosis of the patient was compound heterozygous CPS1D. This study described the specific clinical characteristics and the variations of physiological and biochemical indices in a Chinese neonatal patient with CPS1D, which facilitated the diagnosis and mechanism research of the disease. Two novel causative missense mutations were identified, which enriched the mutation spectrum of CPS1D in China and worldwide. Advice of prenatal diagnosis was given to the family for a new pregnancy. Show less
no PDF DOI: 10.1002/jcla.22375
CPS1
Xiao-Jie Song, Wei Han, Rong He +5 more · 2018 · Neurochemical research · Springer · added 2026-04-24
Seizure-induced brain damage is age-dependent, as evidenced by the different alterations of neural physiopathology in developing and mature brains. However, little is known about the age-dependent cha Show more
Seizure-induced brain damage is age-dependent, as evidenced by the different alterations of neural physiopathology in developing and mature brains. However, little is known about the age-dependent characteristics of myelinated fiber injury induced by seizures. Considering the critical functions of oligodendrocyte progenitor cells (OPCs) in myelination and Lingo-1 signaling in regulating OPCs' differentiation, the present study aimed to explore the effects of Lingo-1 on myelin and axon in immature and adult rats after status convulsion (SC) induced by lithium-pilocarpine, and the differences between immature and adult brains. Dynamic variations in electrophysiological activity and spontaneous recurrent seizures were recorded by electroencephalogram monitoring after SC. The impaired microstructures of myelin sheaths and decrease in myelin basic protein caused by SC were observed through transmission electron microscopy and western blot analysis respectively, which became more severe in adult rats, but improved gradually in immature rats. Aberrant axon sprouting occurred in adult rats, which was more prominent than in immature rats, as shown by a Timm stain. This damage was improved or negatively affected after down or upregulating Lingo-1 expression. These results demonstrated that in both immature and adult brains, Lingo-1 signaling plays important roles in seizure-induced damage to myelin sheaths and axon growth. The plasticity of the developing brain may provide a potential window of opportunity to prevent the brain from damage. Show less
no PDF DOI: 10.1007/s11064-018-2474-2
LINGO1
Fei Luo, Chenyang Chen, Shenglan Chen +2 more · 2018 · International journal of cardiology · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.ijcard.2017.10.054
ANGPTL4
Cuilan Chen, Guisheng Zeng, Yue Wang · 2018 · Molecular microbiology · Blackwell Publishing · added 2026-04-24
Candida albicans is an opportunistic fungal pathogen. In immunocompromised individuals, it can cause bloodstream infections with high mortality rates. The ability to switch between yeast and hyphal mo Show more
Candida albicans is an opportunistic fungal pathogen. In immunocompromised individuals, it can cause bloodstream infections with high mortality rates. The ability to switch between yeast and hyphal morphologies is a critical virulence factor of C. albicans. In response to diverse environmental cues, several signaling pathways are activated resulting in filamentous growth. Interestingly, cell cycle arrest can also trigger filamentous growth although the pathways involved are not well-understood. Here, we demonstrate that the cAMP-PKA pathway is involved in the filamentous growth caused by G1 arrest due to the depletion of the G1 cyclin Cln3 and S phase arrest due to hydroxyurea treatment. The downstream mechanisms involved in filamentation are different between the two cell cycle arrest phenomena. Cln3-depleted cells require HGC1 and UME6 for filamentous growth, but hydroxyurea-induced filamentation does not. Also, the hyphal repressor Nrg1 is not involved in the suppression of Cln3-depletion and hydroxyurea-induced filamentous growth. The findings highlight the complexity of the signaling networks that control filamentous growth in which different mechanisms downstream of the cAMP-PKA pathway are activated based on the nature of the inducing signals. Show less
no PDF DOI: 10.1111/mmi.14097
CLN3
Xiaoyao Li, Qi Yang, Xiaolei Shi +4 more · 2018 · Lipids in health and disease · BioMed Central · added 2026-04-24
Variants in the lipoprotein lipase (LPL), apolipoprotein C-II (APOC2), apolipoprotein A-V (APOA5), GPIHBP1 and LMF1 genes may cause severe hypertriglyceridemia (HTG), which is now the second-leading a Show more
Variants in the lipoprotein lipase (LPL), apolipoprotein C-II (APOC2), apolipoprotein A-V (APOA5), GPIHBP1 and LMF1 genes may cause severe hypertriglyceridemia (HTG), which is now the second-leading aetiology of acute pancreatitis in China. The patient and his family were assessed for gene variants by Sanger sequencing of exons and exon-intron junctions of the LPL, GPIHBP1, APOA5, APOC2, and LMF1 genes. Post-heparin blood was collected for LPL mass and activity detection. The patient had suffered from long-term severe hypertriglyceridemia and recurrent abdominal pain for over 30 years, since age 26, and 3 bouts of acute pancreatitis. Two heterozygous LPL single-nucleotide polymorphisms (SNPs) were compound but dislinked: a single-nucleotide substitution (c.42G > A) resulting in the substitution of tryptophan with a stop codon (p.W14X) in one allele, and a single-nucleotide substitution (c.835C > G) resulting in a leucine-to-valine substitution (p.L279 V) in another allele. Only one SNP, p.L279 V, was detected in his son. Post-heparin LPL activity and mass were also lower in the patient. Two heterozygous LPL SNPs, W14X and L279 V, were newly found to be compound but dislinked, which may cause long-term severe hypertriglyceridemia and recurrent acute pancreatitis. Show less
📄 PDF DOI: 10.1186/s12944-018-0789-2
APOA5
Michelle Fodor, Edmund Price, Ping Wang +23 more · 2018 · ACS chemical biology · ACS Publications · added 2026-04-24
SHP2 is a cytoplasmic protein tyrosine phosphatase encoded by the PTPN11 gene and is involved in cell proliferation, differentiation, and survival. Recently, we reported an allosteric mechanism of inh Show more
SHP2 is a cytoplasmic protein tyrosine phosphatase encoded by the PTPN11 gene and is involved in cell proliferation, differentiation, and survival. Recently, we reported an allosteric mechanism of inhibition that stabilizes the auto-inhibited conformation of SHP2. SHP099 (1) was identified and characterized as a moderately potent, orally bioavailable, allosteric small molecule inhibitor, which binds to a tunnel-like pocket formed by the confluence of three domains of SHP2. In this report, we describe further screening strategies that enabled the identification of a second, distinct small molecule allosteric site. SHP244 (2) was identified as a weak inhibitor of SHP2 with modest thermal stabilization of the enzyme. X-ray crystallography revealed that 2 binds and stabilizes the inactive, closed conformation of SHP2, at a distinct, previously unexplored binding site-a cleft formed at the interface of the N-terminal SH2 and PTP domains. Derivatization of 2 using structure-based design resulted in an increase in SHP2 thermal stabilization, biochemical inhibition, and subsequent MAPK pathway modulation. Downregulation of DUSP6 mRNA, a downstream MAPK pathway marker, was observed in KYSE-520 cancer cells. Remarkably, simultaneous occupation of both allosteric sites by 1 and 2 was possible, as characterized by cooperative biochemical inhibition experiments and X-ray crystallography. Combining an allosteric site 1 inhibitor with an allosteric site 2 inhibitor led to enhanced pharmacological pathway inhibition in cells. This work illustrates a rare example of dual allosteric targeted protein inhibition, demonstrates screening methodology and tactics to identify allosteric inhibitors, and enables further interrogation of SHP2 in cancer and related pathologies. Show less
no PDF DOI: 10.1021/acschembio.7b00980
DUSP6
Yan Chen, Yan-Jun Wang, Ying Zhao +1 more · 2018 · Bioscience reports · added 2026-04-24
Diabetic nephropathy (DN) is one of the most devastating complications of diabetes mellitus. Carbohydrate response element binding protein (ChREBP) is a basic helix-loop-helix leucine zipper transcrip Show more
Diabetic nephropathy (DN) is one of the most devastating complications of diabetes mellitus. Carbohydrate response element binding protein (ChREBP) is a basic helix-loop-helix leucine zipper transcription factor that primarily mediates glucose homeostasis in the body. The present study investigated the role of ChREBP in the pathogenesis of DN. The expression of ChREBP was detected in patients with type 2 diabetes mellitus (T2DM), diabetic mice, and mesangial cells. ELISA was used to measure cytokine production in mesangial cells. Flow cytometry analysis was performed to detect the apoptosis of mesangial cells in the presence of high glucose. The expression levels of ChREBP and several cytokines (TNF-α, IL-1β, and IL-6) were up-regulated in T2DM patients. The mRNA and protein levels of ChREBP were also significantly elevated in the kidneys of diabetic mice. Moreover, glucose treatment promoted mRNA levels of TNF-α, IL-1β, and IL-6 in mesangial cells. Glucose stimulation induced significant apoptosis of SV40 MES 13 cells. In addition, transfection with ChREBP siRNA significantly inhibited ChREBP expression. Consequently, the inflammatory responses and apoptosis were inhibited in SV40 MES 13 cells. These results demonstrated that ChREBP could mediate the inflammatory response and apoptosis of mesangial cells, suggesting that ChREBP may be involved in the pathogenesis of DN. Show less
📄 PDF DOI: 10.1042/BSR20180767
MLXIPL
Ting-Ting Jiang, Li-Ying Shi, Jing Chen +9 more · 2018 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB pa Show more
This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy. Show less
no PDF DOI: 10.1016/j.bbrc.2018.06.147
APOA4