👤 Xiaohong 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, 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
Tara Jois, Weiyi Chen, Victor Howard +7 more · 2017 · Molecular metabolism · Elsevier · added 2026-04-24
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have lin Show more
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have linked adipose ChREBP to insulin sensitivity in mice. However, while ChREBP is most highly expressed in the liver, the effect of hepatic ChREBP on insulin sensitivity remains unknown. To clarify the importance of hepatic ChREBP on glucose homeostasis, we have generated a knockout mouse model that lacks this protein specifically in the liver (Liver-ChREBP KO). Using Liver-ChREBP KO mice, we investigated whether hepatic ChREBP deletion influences insulin sensitivity, glucose homeostasis and the development of hepatic steatosis utilizing various dietary stressors. Furthermore, we determined gene expression changes in response to fasted and fed states in liver, white, and brown adipose tissues. Liver-ChREBP KO mice had impaired insulin sensitivity as indicated by reduced glucose infusion to maintain euglycemia during hyperinsulinemic-euglycemic clamps on both chow (25% lower) and high-fat diet (33% lower) (p < 0.05). This corresponded with attenuated suppression of hepatic glucose production. Although Liver-ChREBP KO mice were protected against carbohydrate-induced hepatic steatosis, they displayed worsened glucose tolerance. Liver-ChREBP KO mice did not show the expected gene expression changes in liver in response to fasted and fed states. Interestingly, hepatic ChREBP deletion also resulted in gene expression changes in white and brown adipose tissues, suggesting inter-tissue communication. This included an almost complete abolition of BAT ChREBPβ induction in the fed state (0.15-fold) (p = 0.015) along with reduced lipogenic genes. In contrast, WAT showed inappropriate increases in lipogenic genes in the fasted state along with increased PEPCK1 in both fasted (3.4-fold) and fed (5.1-fold) states (p < 0.0001). Overall, hepatic ChREBP is protective in regards to hepatic insulin sensitivity and whole body glucose homeostasis. Hepatic ChREBP action can influence other peripheral tissues and is likely essential in coordinating the body's response to different feeding states. Show less
📄 PDF DOI: 10.1016/j.molmet.2017.07.006
MLXIPL
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
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
Qi Xiong, Jianlin Chen, Fei-Lin Li +8 more · 2017 · Scientific reports · Nature · added 2026-04-24
To develop a cost-effective molecular regulator to improve growth metabolism and immunity of animals, a recombinant plasmid co-expressing fatty acid desaturase (mFat-1) and pig insulin growth like fac Show more
To develop a cost-effective molecular regulator to improve growth metabolism and immunity of animals, a recombinant plasmid co-expressing fatty acid desaturase (mFat-1) and pig insulin growth like factor 1 (IGF-1) genes was constructed by the 2 A self-cleavage technique. After entrapment within modified chitosan nanoparticles (chitosan modified with polyethyleneglycol-polyethylenimine, CPP), the recombinant plasmid was injected intramuscularly into mice. Compared with controls, co-expression of mFat-1 and IGF-1 significantly raised the level of serum IGF-1, and increased the liver and muscle docosa hexaenoic acid (DHA) content. Th and Tc cell levels were also elevated, as were expression levels of serum IL-4 and IL-6 genes. These results demonstrate that the immunity and metabolism of an animal can be effectively improved by co-expression of mFat-1 and IGF-1 genes in vivo, which may contribute to further development of novel immunomodulators with beneficial effects on growth metabolism and immunity. Show less
📄 PDF DOI: 10.1038/s41598-017-17341-x
FADS1
Yixia Wu, Lixin Zeng, Xueyan Chen +5 more · 2017 · Prostaglandins, leukotrienes, and essential fatty acids · Elsevier · added 2026-04-24
We investigated the association of single nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) gene cluster with coronary artery disease (CAD) in a case-control study and evaluated the Show more
We investigated the association of single nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) gene cluster with coronary artery disease (CAD) in a case-control study and evaluated the possible influence of genetic variation on total cholesterol (TC) and triglyceride concentrations in the controls. In total, 497 CAD patients and 495 unrelated controls were genotyped for eight SNPs in the FADS gene cluster, and the blood lipid levels of subjects were measured. Three genetic models, including codominant, dominant and recessive, were used to analyze the genotypic relationship with CAD and plasma lipid levels. Single locus genotypic analysis revealed that rs1000778 in FADS3 under a recessive model (AA vs. GG-GA) was significantly associated with CAD adjusted for risk factors. The rs1000778 minor allele AA was associated with a lower risk of CAD (OR =0.37, 95% CI: 0.15-0.89, P=0.025). In the control group, there were significant differences in TC concentrations under a recessive genetic model for rs174575 (C/G) in FADS2 and for rs174450 (A/C) and rs7115739 (G/T) in FADS3 (P=0.053, 0.016 and 0.018, respectively). The rs1000778-G variant in FADS3 may contribute to the susceptibility of CAD, but the result needs to be further confirmed because of small sample size in our study. Genetic variations in FADS2 and FADS3 influence TC concentration in the northern Chinese Han population. Show less
no PDF DOI: 10.1016/j.plefa.2017.01.014
FADS3
Yanlei Ma, Jiping Yue, Yao Zhang +14 more · 2017 · Nature communications · Nature · added 2026-04-24
In the intestinal epithelium, the aberrant regulation of cell/cell junctions leads to intestinal barrier defects, which may promote the onset and enhance the severity of inflammatory bowel disease (IB Show more
In the intestinal epithelium, the aberrant regulation of cell/cell junctions leads to intestinal barrier defects, which may promote the onset and enhance the severity of inflammatory bowel disease (IBD). However, it remains unclear how the coordinated behaviour of cytoskeletal network may contribute to cell junctional dynamics. In this report, we identified ACF7, a crosslinker of microtubules and F-actin, as an essential player in this process. Loss of ACF7 leads to aberrant microtubule organization, tight junction stabilization and impaired wound closure in vitro. With the mouse genetics approach, we show that ablation of ACF7 inhibits intestinal wound healing and greatly increases susceptibility to experimental colitis in mice. ACF7 level is also correlated with development and progression of ulcerative colitis (UC) in human patients. Together, our results reveal an important molecular mechanism whereby coordinated cytoskeletal dynamics contributes to cell adhesion regulation during intestinal wound repair and the development of IBD. Show less
📄 PDF DOI: 10.1038/ncomms15375
MACF1
Huanhuan Liu, Long Yang, Erchen Zhang +11 more · 2017 · Acta biomaterialia · Elsevier · added 2026-04-24
Management of ligament/tendon-to-bone-junction healing remains a formidable challenge in the field of orthopedic medicine to date, due to deficient vascularity and multi-tissue transitional structure Show more
Management of ligament/tendon-to-bone-junction healing remains a formidable challenge in the field of orthopedic medicine to date, due to deficient vascularity and multi-tissue transitional structure of the junction. Numerous strategies have been employed to improve ligament-bone junction healing, including delivery of stem cells, bioactive factors, and synthetic materials, but these methods are often inadequate at recapitulating the complex structure-function relationships at native tissue interfaces. Here, we developed an easily-fabricated and effective biomimetic composite to promote the regeneration of ligament-bone junction by physically modifying the tendon extracellular matrix (ECM) into a Random-Aligned-Random composite using ultrasound treatment. The differentiation potential of rabbit bone marrow stromal cells on the modified ECM were examined in vitro. The results demonstrated that the modified ECM enhanced expression of chondrogenesis and osteogenesis-associated epigenetic genes (Jmjd1c, Kdm6b), transcription factor genes (Sox9, Runx2) and extracellular matrix genes (Col2a1, Ocn), resulting in higher osteoinductivity than the untreated tendon ECM in vitro. In the rabbit anterior cruciate ligament (ACL) reconstruction model in vivo, micro-computed tomography (Micro-CT) and histological analysis showed that the modified Random-Aligned-Random composite scaffold enhanced bone and fibrocartilage formation at the interface, more efficaciously than the unmodified tendon ECM. Therefore, these results demonstrated that the biomimetic Random-Aligned-Random composite could be a promising scaffold for ligament/tendon-bone junction repair. The native transitional region consists of several distinct yet contiguous tissue regions, composed of soft tissue, non-calcified fibrocartilage, calcified fibrocartilage, and bone. A stratified graft whose phases are interconnected with each other is essential for supporting the formation of functionally continuous multi-tissue regions. Various techniques have been attempted to improve adherence of the ligament/tendon graft to bone, including utilization of stem cells, growth factors and biomaterials, but these methods are often inadequate at recapitulating the complex structure-function relationships at native tissue interfaces. Here, we developed an easily-fabricated and effective biomimetic composite to promote the regeneration of ligament-bone junction by physically modifying the tendon extracellular matrix (ECM) into a Random-Aligned-Random composite using ultrasound treatment. The modified ECM enhanced expression of chondrogenesis and osteogenesis-associated epigenetic genes expression in vitro. In the rabbit anterior crucial ligament reconstruction model in vivo, results showed that the modified Random-Aligned-Random composite enhances the bone and fibrocartilage formation in the interface, proving to be more efficient than the unmodified tendon ECM. Therefore, these results demonstrated that the biomimetic Random-Aligned-Random composite could be a promising scaffold for ligament/tendon-bone junction repair. Show less
no PDF DOI: 10.1016/j.actbio.2017.05.027
JMJD1C
Tao Yang, Kai Zhao, Haifeng Shu +6 more · 2017 · Neuroreport · added 2026-04-24
Neuronal regeneration and axonal regrowth mechanisms in the injured mammalian central nervous system are largely unknown. As part of a major pathway for inhibiting axonal regeneration, activated neuro Show more
Neuronal regeneration and axonal regrowth mechanisms in the injured mammalian central nervous system are largely unknown. As part of a major pathway for inhibiting axonal regeneration, activated neuronal glycosylphosphatidylinositol-anchored Nogo receptor (NgR) interacts with LINGO-1 and p75NTR to form a complex at the cell surface. However, it was found in our previous report that upregulation of NgR stimulated by injury plays a key role in neuronal regeneration in the neonatal cortex freeze-lesion model, but its downstream signalling remains elusive. In the present study, the novel regulatory role of NgR in a serine-threonine kinase WNK1 was identified. NgR's transcriptional regulation of WNK1 was identified by RT-qPCR and semiquantitative western blot after the overexpression or knockdown of NgR, and the regulation is specific to WNK1, which is not the same for its family members, WNK2, WNK3 and WNK4. Furthermore, NgR inhibition by NEP fails to affect WNK1, which indicates that WNK1 functions outside of the Nogo-A/NgR pathway. By performing a proliferation, migration and axonal extension assay, we also identified that overexpressed NgR critically regulated these processes and impairment by overexpressing NgR was rescued with coexpression of WNK1, indicating the partial role of WNK1 in NgR-mediated morphological regulation. Our study identifies a separation of functions for the NgR-regulated WNK1 in mediating proliferation, migration and axonal extension in PC12 cells as well as a specific regulatory role between NgR and WNK1 that is important for recovery from central nervous system injury. Show less
no PDF DOI: 10.1097/WNR.0000000000000800
LINGO1
Bei Zhao, Shouli Wang, Jinsong Chen +4 more · 2017 · Experimental and therapeutic medicine · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a common autosomal dominant cardiac disease, affecting 1 in 500 people. Myosin-binding protein C3 (
no PDF DOI: 10.3892/etm.2017.4089
MYBPC3
Xian-Bin Lin, Lei Jiang, Mao-Hua Ding +13 more · 2016 · Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · Springer · added 2026-04-24
Phenoxybenzamine hydrochloride (PHEN) is a selective antagonist of both α-adrenoceptor and calmodulin that exhibits anticancer properties. The aim of this study was to explore the anti-tumor function Show more
Phenoxybenzamine hydrochloride (PHEN) is a selective antagonist of both α-adrenoceptor and calmodulin that exhibits anticancer properties. The aim of this study was to explore the anti-tumor function of PHEN in glioma. Cell proliferation assay was used to assess glioma cell growth. Migration and invasion capacity of glioma cells was monitored by wound-healing and transwell assay, respectively. Neurosphere formation test was adopted for the tumorigenesis of glioma cells, which was also confirmed by soft agar cloning formation test in vitro and a nude mouse model in vivo. Finally, we explored the potential pathway utilized by PHEN using Western blot and immunofluoresce staining. PHEN exhibited a significant inhibitory effect on the proliferation of both U251 and U87MG glioma cell lines in a positive dose-dependent manner. PHEN apparently attenuated the malignancy of glioma in terms of migration and invasion and also suppressed the tumorigenic capacity both in vitro and in vivo. Mechanism study showed that PHEN promoted tumor suppression by inhibiting the TrkB-Akt pathway. The results of the present study demonstrated that PHEN suppressed the proliferation, migration, invasion, and tumorigenesis of glioma cells, induced LINGO-1 expression, and inhibited the TrkB-Akt pathway, which may prove to be the mechanisms underlying the anti-tumor effect of PHEN on glioma cells. Show less
no PDF DOI: 10.1007/s13277-015-4102-y
LINGO1
Nan Zhu, Mo Chen, Rowena Eng +13 more · 2016 · The Journal of clinical investigation · added 2026-04-24
Self-renewal is a hallmark of both hematopoietic stem cells (HSCs) and leukemia stem cells (LSCs); therefore, the identification of mechanisms that are required for LSC, but not HSC, function could pr Show more
Self-renewal is a hallmark of both hematopoietic stem cells (HSCs) and leukemia stem cells (LSCs); therefore, the identification of mechanisms that are required for LSC, but not HSC, function could provide therapeutic opportunities that are more effective and less toxic than current treatments. Here, we employed an in vivo shRNA screen and identified jumonji domain-containing protein JMJD1C as an important driver of MLL-AF9 leukemia. Using a conditional mouse model, we showed that loss of JMJD1C substantially decreased LSC frequency and caused differentiation of MLL-AF9- and homeobox A9-driven (HOXA9-driven) leukemias. We determined that JMJD1C directly interacts with HOXA9 and modulates a HOXA9-controlled gene-expression program. In contrast, loss of JMJD1C led to only minor defects in blood homeostasis and modest effects on HSC self-renewal. Together, these data establish JMJD1C as an important mediator of MLL-AF9- and HOXA9-driven LSC function that is largely dispensable for HSC function. Show less
no PDF DOI: 10.1172/JCI82978
JMJD1C
Aihui Fan, Qian Wang, Yongjun Yuan +7 more · 2016 · American journal of physiology. Cell physiology · added 2026-04-24
Recent studies have shown that activation of liver X receptors (LXRs) attenuates the development of atherosclerosis, not only by regulating lipid metabolism but also by suppressing inflammatory signal Show more
Recent studies have shown that activation of liver X receptors (LXRs) attenuates the development of atherosclerosis, not only by regulating lipid metabolism but also by suppressing inflammatory signaling. Sphingosine 1-phosphate receptor 2 (S1PR2), an important inflammatory gene product, plays a role in the development of various inflammatory diseases. It was proposed that S1PR2 might be regulated by LXR-α. In the present study, the effect of LXR-α on tumor necrosis factor-α (TNF-α)-induced S1PR2 expression in human umbilical vein endothelial cells (HUVECs) was investigated and the underlying mechanism was explored. The results demonstrated that TNF-α led to an increase in S1PR2 expression and triggered a downregulation of LXR-α expression in HUVECs as well. Downregulation of LXR-α with specific small interfering RNA (siRNA) remarkably enhanced the primary as well as TNF-α-induced expression of S1PR2 in HUVECs. Activation of LXR-α by agonist GW3965 inhibited both primary and TNF-α-induced S1PR2 expression. GW3965 also attenuated S1PR2-induced endothelial barrier dysfunction. The data further showed that TNF-α induced a significant decrease in miR-130a-3p expression. Overexpression of miR-130a-3p with mimic product reduced S1PR2 protein expression, and inhibition of miR-130a-3p by specific inhibitor resulted in an increase in S1PR2 protein expression. Furthermore, activation of LXRs with agonist enhanced the expression of miR-130a-3p, and knockdown of LXR-α by siRNA suppressed miR-130a-3p expression. These results suggest that LXR-α might downregulate S1PR2 expression via miR-130a-3p in quiescent HUVECs. Stimulation of TNF-α attenuates the activity of LXR-α and results in enhanced S1PR2 expression. Show less
no PDF DOI: 10.1152/ajpcell.00102.2015
NR1H3
Chiung-Mei Chen, Yi-Chun Chen, Mu-Chun Chiang +4 more · 2016 · Neurobiology of aging · Elsevier · added 2026-04-24
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet Show more
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet to be examined in PD patients in Chinese or Asian population. Because ethnic-specific effect is an important concern for GWAS analysis, we genotyped single-nucleotide polymorphisms in the new genetic loci, GCH1 (rs11158026), SIPA1L2 (rs10797576), VPS13C (rs2414739), and MIR4697 (rs329648), to investigate their associations with risk of PD in Taiwan. Another single-nucleotide polymorphism GCH1 rs7155501, previously identified by GWAS listed at the top 20 genes in PDGene database was also included. A total of 1151 study subjects comprising 598 patients with PD and 553 unrelated healthy controls were recruited. The frequency of minor allele (C allele) of GCH1 rs11158026 was found to be significantly higher in PD cases than in controls (p = 0.003). The CC genotype of rs11158026 increased PD risk compared to TT genotype (odds ratio [OR] = 1.29, 95% confidence interval [CI] = 1.09, 1.53, p = 0.004). Under additive model, the GCH1 rs11158026 increased the risk of developing PD (OR = 1.30, 95% CI = 1.10, 1.54, p = 0.002). In recessive model, the genotype TT of MIR4697 rs329648 marginally decreased the PD risk (OR = 0.62, 95% CI = 0.43, 0.90, p = 0.01). The PD patients demonstrated similar genotypic and allelic frequencies in GCH1 rs7155501, SIPA1L2 rs10797576, and VPS13C rs2414739 with the controls. These findings suggest that the GCH1 and MIR4697 but not SIPA1L2 and VPS13C are genetic loci influencing risk of PD in Taiwan. Show less
no PDF DOI: 10.1016/j.neurobiolaging.2015.12.016
VPS13C
Jue Wang, Zhizhong Ye, Shuhui Zheng +4 more · 2016 · Brain research · Elsevier · added 2026-04-24
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spina Show more
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spinal cord injury (SCI). The Notch pathway inhibits the differentiation of neural stem/progenitor cells and Lingo-1 is a strong negative regulator for myelination and axon growth. While Lingo-1 shRNA and N-[N-(3, 5-difluorophenacetyl)-1-alanyl]-S-Phenylglycinet-butylester (DAPT), a Notch pathway inhibitor, have been used separately to help repair SCI, the results have been unsatisfactory. Here we investigated and elucidated the preliminary mechanism for the effect of Lingo-1 shRNA and DAPT on neural stem/progenitor cells differentiation. We found that neural stem/progenitor cells from E14 rat embryos expressed Nestin, Sox-2 and Lingo-1, and we optimized the transduction of neural stem/progenitor cells using lentiviral vectors encoding Lingo-1 shRNA. The addition of DAPT decreased the expression of Notch intracellular domain (NICD) as well as the downstream genes Hes1 and Hes5. Expression of NeuN, CNPase and GFAP in DAPT treated cells and expression of NeuN in Lingo-1 shRNA treated cells confirmed differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes. These results revealed that while Lingo-1 shRNA and Notch signaling inhibitor DAPT both promoted differentiation of neural stem cells into neurons, only DAPT was capable of driving neural stem/progenitor cells differentiation into oligodendrocytes and astrocytes. Since we were able to show that both Lingo-1 shRNA and DAPT could drive neural stem/progenitor cells differentiation, our data might aid the development of more effective SCI therapies using Lingo-1 shRNA and DAPT. Show less
no PDF DOI: 10.1016/j.brainres.2015.11.029
LINGO1
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
Kyoko Hiragami-Hamada, Szabolcs Soeroes, Miroslav Nikolov +17 more · 2016 · Nature communications · Nature · added 2026-04-24
Histone H3 trimethylation of lysine 9 (H3K9me3) and proteins of the heterochromatin protein 1 (HP1) family are hallmarks of heterochromatin, a state of compacted DNA essential for genome stability and Show more
Histone H3 trimethylation of lysine 9 (H3K9me3) and proteins of the heterochromatin protein 1 (HP1) family are hallmarks of heterochromatin, a state of compacted DNA essential for genome stability and long-term transcriptional silencing. The mechanisms by which H3K9me3 and HP1 contribute to chromatin condensation have been speculative and controversial. Here we demonstrate that human HP1β is a prototypic HP1 protein exemplifying most basal chromatin binding and effects. These are caused by dimeric and dynamic interaction with highly enriched H3K9me3 and are modulated by various electrostatic interfaces. HP1β bridges condensed chromatin, which we postulate stabilizes the compacted state. In agreement, HP1β genome-wide localization follows H3K9me3-enrichment and artificial bridging of chromatin fibres is sufficient for maintaining cellular heterochromatic conformation. Overall, our findings define a fundamental mechanism for chromatin higher order structural changes caused by HP1 proteins, which might contribute to the plastic nature of condensed chromatin. Show less
📄 PDF DOI: 10.1038/ncomms11310
CBX1
Tai-Heng Chen, Xia Tian, Pao-Lin Kuo +3 more · 2016 · Prenatal diagnosis · Wiley · added 2026-04-24
Fetal akinesia deformation sequence (FADS) refers to a broad spectrum of disorder with the absent fetal movement as the unifying feature. The etiology of FADS is heterogeneous, and the majority remain Show more
Fetal akinesia deformation sequence (FADS) refers to a broad spectrum of disorder with the absent fetal movement as the unifying feature. The etiology of FADS is heterogeneous, and the majority remains unknown. Prenatal diagnosis of FADS because of neuromuscular origin has relied on clinical features and fetal muscle pathology, which can be unrevealing. The recent advance of next-generation sequencing (NGS) can provide definitive molecular diagnosis effectively. An 18-week-old fetus presented with akinesia and multiple contractures of joints. The mother had two previously aborted similarly affected fetuses. Clinical diagnosis of FADS was made. Molecular diagnosis using cord blood by NGS of genes related to neuromuscular diseases revealed two compound heterozygous mutations; c.602G > A(p.W201*) and c.1516A > C(p.T506P), in the Kelch-like 40 (KLHL40) gene. Based on this information, prenatal diagnosis was performed on the CVS of the subsequent pregnancy that resulted in an unaffected female baby, heterozygous for the c.1516A > C(p.T506P) mutation. Identification of KLHL40 mutations in one of the aborted fetuses provided a confirmative diagnosis of FADS, facilitating the prenatal diagnosis of the subsequent pregnancy. This report underscores the importance of target NGS in providing FADS families with an affordable, precise molecular diagnosis for genetic counseling and options of prenatal diagnosis. © 2016 John Wiley & Sons, Ltd. Show less
no PDF DOI: 10.1002/pd.4949
FADS1
Hongxiang Zeng, Hao Gu, Chiqi Chen +9 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the mainte Show more
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the maintenance of stemness in LICs, although the detailed mechanisms are poorly understood. Herein, we provide intriguing evidence showing that a glucose-responsive transcription factor, carbohydrate responsive element binding protein (ChREBP), served as a tumor suppressor rather than an oncogene, as previously described, to inhibit the development of acute myeloid leukemia by promoting the differentiation of LICs. Using an MLL-AF9-induced murine leukemia model, we demonstrated that the deletion of ChREBP resulted in the blockage of the differentiation of LICs and significantly reduced survival in ChREBP-null leukemic mice. However, ChREBP was not required for the normal repopulation abilities of hematopoietic stem cells. ChREBP promoted leukemia cell differentiation through the direct inhibition of RUNX1 or the transactivation of TXNIP to downregulate the RUNX1 level and ROS generation. Moreover, knockdown of ChREBP in human leukemia THP1 cells led to markedly enhanced proliferation and decreased differentiation upon PMA treatment. Collectively, we unraveled an unexpected role of ChREBP in leukemogenesis, which may provide valuable clues for developing novel metabolic strategies for leukemia treatment. Show less
📄 PDF DOI: 10.18632/oncotarget.9520
MLXIPL
Zong-Bo Wei, Ye-Feng Yuan, Florence Jaouen +8 more · 2016 · Autophagy · Taylor & Francis · added 2026-04-24
Searching for new regulators of autophagy involved in selective dopaminergic (DA) neuron loss is a hallmark in the pathogenesis of Parkinson disease (PD). We here report that an endoplasmic reticulum Show more
Searching for new regulators of autophagy involved in selective dopaminergic (DA) neuron loss is a hallmark in the pathogenesis of Parkinson disease (PD). We here report that an endoplasmic reticulum (ER)-associated transmembrane protein SLC35D3 is selectively expressed in subsets of midbrain DA neurons in about 10% TH (tyrosine hydroxylase)-positive neurons in the substantia nigra pars compacta (SNc) and in about 22% TH-positive neurons in the ventral tegmental area (VTA). Loss of SLC35D3 in ros (roswell mutant) mice showed a reduction of 11.9% DA neurons in the SNc and 15.5% DA neuron loss in the VTA with impaired autophagy. We determined that SLC35D3 enhanced the formation of the BECN1-ATG14-PIK3C3 complex to induce autophagy. These results suggest that SLC35D3 is a new regulator of tissue-specific autophagy and plays an important role in the increased autophagic activity required for the survival of subsets of DA neurons. Show less
no PDF DOI: 10.1080/15548627.2016.1179402
PIK3C3
Xuanmao Chen, Jie Luo, Yihua Leng +4 more · 2016 · Biological psychiatry · Elsevier · added 2026-04-24
Although major depressive disorder (MDD) has low heritability, a genome-wide association study in humans has recently implicated type 3 adenylyl cyclase (AC3; ADCY3) in MDD. Moreover, the expression l Show more
Although major depressive disorder (MDD) has low heritability, a genome-wide association study in humans has recently implicated type 3 adenylyl cyclase (AC3; ADCY3) in MDD. Moreover, the expression level of AC3 in blood has been considered as a MDD biomarker in humans. Nevertheless, there is a lack of supporting evidence from animal studies. We employed multiple approaches to experimentally evaluate if AC3 is a contributing factor for major depression using mouse models lacking the Adcy3 gene. We found that conventional AC3 knockout (KO) mice exhibited phenotypes associated with MDD in behavioral assays. Electroencephalography/electromyography recordings indicated that AC3 KO mice have altered sleep patterns characterized by increased percentage of rapid eye movement sleep. AC3 KO mice also exhibit neuronal atrophy. Furthermore, synaptic activity at cornu ammonis 3-cornu ammonis 1 synapses was significantly lower in AC3 KO mice, and they also exhibited attenuated long-term potentiation as well as deficits in spatial navigation. To confirm that these defects are not secondary responses to anosmia or developmental defects, we generated a conditional AC3 floxed mouse strain. This enabled us to inactivate AC3 function selectively in the forebrain and to inducibly ablate it in adult mice. Both AC3 forebrain-specific and AC3 inducible knockout mice exhibited prodepression phenotypes without anosmia. This study demonstrates that loss of AC3 in mice leads to decreased neuronal activity, altered sleep pattern, and depression-like behaviors, providing strong evidence supporting AC3 as a contributing factor for MDD. Show less
📄 PDF DOI: 10.1016/j.biopsych.2015.12.012
ADCY3
Jiali Zhu, Keke Xu, Xuemei Zhang +7 more · 2016 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Valeriana jatamansi Jones, a plant with heart-shaped leaves in the Valeriana genus of Valerianaceae, is widely used in Chinese folk medicine. Iridoid is an important constituent of V. jatamansi that c Show more
Valeriana jatamansi Jones, a plant with heart-shaped leaves in the Valeriana genus of Valerianaceae, is widely used in Chinese folk medicine. Iridoid is an important constituent of V. jatamansi that contributes to the pharmacological efficacy of the herb. This study aims to investigate the regulation of lipid metabolism and its mechanism of the iridoids rich fraction in V. jatamansi (IRFV). A high fat diet was used to establish the hyperlipidemia rat model, with 2mg/kg/d of simvastatin as a positive control, fed with 7.5, 15, and 30mg/kg/d of IRFV for 20days to investigate the lipid regulation activity and mechanism of IRFV. Body weight, liver index, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in both serum and liver, as well as total bile acid (TBA), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) in serum were measured. The lipoprotein lipase (LPL) and hepatic lipase (HL) activities and the apoprotein A5 (ApoA5), peroxisome proliferator-activated receptor α (PPAR-α), sterol regulatory element-binding proteins (SREBP-1c), and liver X receptor α (LXR-α) protein expressions were observed. Liver pathology was described through hematoxylin-eosin (HE) staining. Compared with the model group, three different IRFV dosages can slow down the weight gain of rats, reduce the contents of TG, and increase the contents of HDL-C in serum. Low IRFV dosage can significantly reduce the AST and ALT contents in serum, liver index, and the TG contents in liver, enhance LPL activity. Medium IRFV dosage can significantly decrease the TG and LDL-C contents in liver. High IRFV dosage can significantly reduce LDL-C, TBA, AST, and ALT contents in serum, and enhance HL activity. Three different IRFV dosages can significantly increase the ApoA5 and PPAR-α protein expression and decrease the SREBP-1c protein expression. Furthermore, the LXR-α protein expression decreased in low- and high-dose groups. Liver tissue pathological observation showed that IRFV can improve cell degeneration to a certain extent. These results strongly suggest that IRFV play significant roles in regulating lipid metabolism, the mechanism may be related to the increased ApoA5 protein expression. Show less
no PDF DOI: 10.1016/j.biopha.2016.10.099
APOA5
Rui Chen, Hao Wang, Beibei Liang +11 more · 2016 · Cell death & disease · Nature · added 2026-04-24
Autophagy is an important catabolic process, which sustains intracellular homeostasis and lengthens cell survival under stress. Here we identify the ankyrin-repeat-containing, SH3-domain-containing, a Show more
Autophagy is an important catabolic process, which sustains intracellular homeostasis and lengthens cell survival under stress. Here we identify the ankyrin-repeat-containing, SH3-domain-containing, and proline-rich region-containing protein 2 (ASPP2), a haploinsufficient tumor suppressor, as a molecular regulator of starvation-induced autophagy in hepatocellular carcinoma (HCC). ASPP2 expression is associated with an autophagic response upon nutrient deprivation and downregulation of ASPP2 facilitates autophagic flux, whereas overexpression of ASPP2 blocks this starvation-induced autophagy in HCC cells. Mechanistically, ASPP2 inhibits autophagy through regulating BECN1 transcription and formation of phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) complex. Firstly, ASPP2 inhibits p65/RelA-induced transcription of BECN1, directly by an ASPP2-p65/RelA-IκBα complex which inhibits phosphorylation of IκBα and the translocation of p65/RelA into the nucleus. Secondly, ASPP2 binds to BECN1, leading to decreased binding of PIK3C3 and UV radiation resistance-associated gene (UVRAG), and increased binding of Rubicon in PIK3C3 complex. Downregulation of ASPP2 enhances the pro-survival and chemoresistant property via autophagy in HCC cells in vitro and in vivo. Decreased ASPP2 expression was associated with increased BECN1 and poor survival in HCC patients. Therefore, ASPP2 is a key regulator of BECN1-dependent autophagy, and decreased ASPP2 may contribute to tumor progression and chemoresistance via promoting autophagy. Show less
no PDF DOI: 10.1038/cddis.2016.407
PIK3C3
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
Ningning Chen, Jing-Sheng Cen, Jingnan Wang +7 more · 2016 · Critical care medicine · added 2026-04-24
Leucine-rich repeat and immunoglobulin domain-containing protein (LINGO)-1 is expressed in neural stem cells, and its neutralization results in sustained neuronal immaturity. Thus, targeted inhibition Show more
Leucine-rich repeat and immunoglobulin domain-containing protein (LINGO)-1 is expressed in neural stem cells, and its neutralization results in sustained neuronal immaturity. Thus, targeted inhibition of LINGO-1 via RNA interference may enhance transplanted neural stem cell survival and neuronal differentiation in vivo. Furthermore, LINGO-1 RNA interference in neural stem cells represents a potential therapeutic strategy for spinal cord injury. Department of Spine Surgery, First Affiliated Hospital of Sun Yat-sen University. Translational Medicine Center Research Laboratory, First Affiliated Hospital of Sun Yat-sen University. Female Sprague-Dawley rats. The animals were divided into three groups that underwent laminectomy and complete spinal cord transection accompanied by transplantation of control-RNA interference-treated or LINGO-1-RNA interference-treated neural stem cells at the injured site in vivo. In vitro, neural stem cells were divided into four groups for the following treatments: control, control RNA interference lentivirus, LINGO-1 RNA interference lentivirus and LINGO-1 complementary DNA lentivirusand the Key Projects of the Natural Science Foundation of Guangdong Province (No. S2013020012818). Neural stem cells in each treatment group were examined for cell survival and neuronal differentiation in vitro and in vivo via immunofluorescence and Western blot analysis. Axonal regeneration and tissue repair were assessed via retrograde tracing using Fluorogold, electron microscopy, hematoxylin-eosin staining and MRI. Rats were also examined for functional recovery based on the measurement of spinal cord-evoked potentials and the Basso-Beattie-Bresnahan score. LINGO-1-RNA interference-treated neural stem cell transplantation increased tissue repair and functional recovery of the injured spinal cord in rats. Similarly, LINGO-1 RNA interference increased neural stem cell survival and neuronal differentiation in vitro. The mechanism underlying the effect of LINGO-1 RNA interference on the injured rat spinal cord may be that the significant inhibition of LINGO-1 expression in neural stem cells inactivated the RhoA and Notch signaling pathways, which act downstream of LINGO-1. Our findings indicate that transplantation of LINGO-1-RNA interference-treated neural stem cells facilitates functional recovery after spinal cord injury and represents a promising potential strategy for the repair of spinal cord injury. Show less
no PDF DOI: 10.1097/CCM.0000000000001351
LINGO1
Rong Li, Lu-Zhu Chen, Wang ZHAO +2 more · 2016 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotrigly Show more
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotriglyceridemic actions. Two obese mouse models, including high-fat diet-induced obese mice and ob/ob obese mice, were adopted. The effects of low- and high-dose metformin were determined on plasma and hepatic TG and apoA5 of these obese mice. Besides, the effects of metformin on TG and apoA5 were also detected in mouse and human hepatocytes in vitro. (1) Plasma apoA5 levels in the obese mice were markedly elevated and positively correlated with TG. Hepatic TG contents and apoA5 expressions were also remarkably increased in the obese mice. (2) Metformin dose-dependently decreased hepatic and plasma TG and apoA5 in the obese mice. Similarly, metformin dose-dependently reduced cellular TG contents and apoA5 expressions in hepatocytes in vitro. Compared to APOA5 knock-down (KD), metformin plus APOA5 KD resulted in more TG reduction of hepatocytes. Increased hepatic and plasma apoA5 could be a result of obesity-associated hypertriglyceridemia, and metformin displays hypotriglyceridemic effects on obese mice partly via the apoA5 pathway. Show less
no PDF DOI: 10.1016/j.bbrc.2016.08.087
APOA5
Ye Tian, Wei Zhang, Shigang Zhao +11 more · 2016 · Scientific reports · Nature · added 2026-04-24
Dyslipidemia is common in polycystic ovary syndrome (PCOS). This study was aimed to investigate whether fatty acid desaturase genes (FADS), a dyslipidemia-related gene cluster, are associated with PCO Show more
Dyslipidemia is common in polycystic ovary syndrome (PCOS). This study was aimed to investigate whether fatty acid desaturase genes (FADS), a dyslipidemia-related gene cluster, are associated with PCOS. We scanned variations of FADS genes using our previous data of genome-wide association study (GWAS) for PCOS and selected rs174570 for further study. The case-control study was conducted in an independent cohort of 1918 PCOS cases and 1889 age-matched controls and family-based study was conducted in a set of 243 core family trios with PCOS probands. Minor allele frequency (allele T) of rs174570 was significantly lower in PCOS cases than that in age-matched controls (P = 2.17E-03, OR = 0.85), even after adjustment of BMI and age. PCOS subjects carrying CC genotype had higher testosterone level and similar lipid/glucose level compared with those carrying TT or TC genotype. In trios, transmission disequilibrium test (TDT) analysis revealed risk allele C of rs174570 was significantly over-transmitted (P = 2.00E-04). Decreased expression of FADS2 was detected in PCOS cases and expression quantitative trait loci (eQTL) analysis revealed the risk allele C dosage was correlated with the decline of FADS2 expression (P = 0.002). Our results demonstrate that FADS1-FADS2 are susceptibility genes for PCOS. Show less
📄 PDF DOI: 10.1038/srep21195
FADS1
Jia Hu, Ge Li, Liujing Qu +10 more · 2016 · Cell death & disease · Nature · added 2026-04-24
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have Show more
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have provided a line of evidence confirming that EVA1A (eva-1 homolog A)/TMEM166 (transmembrane protein 166) is associated with autophagosomal membrane development. This notion is based on dotted EVA1A structures that colocalize with ZFYVE1, ATG9, LC3B, ATG16L1, ATG5, STX17, RAB7 and LAMP1, which represent different stages of the autophagic process. It is required for autophagosome formation as this phenotype was significantly decreased in EVA1A-silenced cells and Eva1a KO MEFs. EVA1A-induced autophagy is independent of the BECN1-PIK3C3 (phosphatidylinositol 3-kinase, catalytic subunit type 3) complex but requires ATG7 activity and the ATG12-ATG5/ATG16L1 complex. Here, we present a molecular mechanism by which EVA1A interacts with the WD repeats of ATG16L1 through its C-terminal and promotes ATG12-ATG5/ATG16L1 complex recruitment to the autophagic membrane and enhances the formation of the autophagosome. We also found that both autophagic and apoptotic mechanisms contributed to EVA1A-induced cell death while inhibition of autophagy and apoptosis attenuated EVA1A-induced cell death. Overall, these findings provide a comprehensive view to our understanding of the pathways involved in the role of EVA1A in autophagy and programmed cell death. Show less
no PDF DOI: 10.1038/cddis.2016.230
PIK3C3
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
Rui-Nan Zhang, Rui-Dan Zheng, Yu-Qiang Mi +6 more · 2016 · Digestive diseases and sciences · Springer · added 2026-04-24
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The Show more
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The aim of this study was to investigate the relationship between other polymorphisms of APOC3 and NAFLD in Chinese. Fifty-nine liver biopsy-proven NAFLD patients and 72 healthy control subjects were recruited to a cohort representing Chinese Han population. The polymorphisms in the exons and flanking regions of APOC3 and patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 polymorphisms were genotyped. Among the five SNPs (rs4225, rs4520, rs5128, rs2070666, and rs2070667) in APOC3, only rs2070666 (c.179 + 62 T/A) was significantly different in genotype and allele frequency (both p < 0.01) between groups of NAFLD and control. After adjusting for sex, age, serum triglycerides, total cholesterol, body mass index, and the PNPLA3 rs738409 polymorphism, the APOC3 rs2070666 A allele was an independent risk factor for NAFLD with an odds ratio (OR) of 3.683 and 95 % confidence interval (CI) of 1.037-13.084. The APOC3 rs2070666 A allele was linked to the fourth quartile of the controlled attenuation parameter values (OR 2.769, 95 % CI 1.002-7.651) in 131 subjects, and also linked to the significant histological steatosis (OR 4.986, 95 % CI 1.020-24.371), but neither to liver stiffness measurement values nor to hepatic histological activity and fibrosis in NAFLD patients. The APOC3 rs2070666 A allele is a risk factor for NAFLD independent of obesity, dyslipidemia, and PNPLA3 rs738409, and it might contribute to increased liver fat content in Chinese Han population. Show less
no PDF DOI: 10.1007/s10620-016-4120-7
APOC3
Niha Zubair, Mariaelisa Graff, Jose Luis Ambite +54 more · 2016 · Human molecular genetics · Oxford University Press · added 2026-04-24
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the geneti Show more
Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies. Show less
no PDF DOI: 10.1093/hmg/ddw358
APOA5