👤 Jia Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, Zhezhe Chen, Zhi Bin Chen, Zhi Chen, Zhi-Hao Chen, Zhi-bin Chen, Zhi-zhe Chen, Zhiang Chen, Zhichuan Chen, Zhifeng Chen, Zhigang Chen, Zhigeng Chen, Zhiguo Chen, Zhihai Chen, Zhihang Chen, Zhihao Chen, Zhiheng Chen, Zhihong Chen, Zhijian Chen, Zhijian J Chen, Zhijing Chen, Zhijun Chen, Zhimin Chen, Zhinan Chen, Zhiping Chen, Zhiqiang Chen, Zhiquan Chen, Zhishi Chen, Zhitao Chen, Zhiting Chen, Zhiwei Chen, Zhixin Chen, Zhixuan Chen, Zhixue Chen, Zhiyong Chen, Zhiyu Chen, Zhiyuan Chen, Zhiyun Chen, Zhizhong Chen, Zhong Chen, Zhongbo Chen, Zhonghua Chen, Zhongjian Chen, Zhongliang Chen, Zhongxiu Chen, Zhongzhu Chen, Zhou Chen, Zhouji Chen, Zhouliang Chen, Zhoulong Chen, Zhouqing Chen, Zhuchu Chen, Zhujun Chen, Zhuo Chen, Zhuo-Yuan Chen, ZhuoYu Chen, Zhuohui Chen, Zhuojia Chen, Zi-Jiang Chen, Zi-Qing Chen, Zi-Yang Chen, Zi-Yue Chen, Zi-Yun Chen, Zian Chen, Zifan Chen, Zihan Chen, Zihang Chen, Zihao Chen, Zihe Chen, Zihua Chen, Zijie Chen, Zike Chen, Zilin Chen, Zilong Chen, Ziming Chen, Zinan Chen, Ziqi Chen, Ziqing Chen, Zitao Chen, Zixi Chen, Zixin Chen, Zixuan Chen, Ziying Chen, Ziyuan Chen, Zoe Chen, Zongming E Chen, Zongnan Chen, Zongyou Chen, Zongzheng Chen, Zugen Chen, Zuolong Chen
articles
Xin-Hua Ye, Hong Chen, Qin Yu +1 more · 2017 · Medical science monitor : international medical journal of experimental and clinical research · added 2026-04-24
BACKGROUND Liver X receptor (LXR) is a nuclear receptor presenting in macrophages; it works indispensably in lipid metabolism control and also negatively regulates the expression of inflammatory genes Show more
BACKGROUND Liver X receptor (LXR) is a nuclear receptor presenting in macrophages; it works indispensably in lipid metabolism control and also negatively regulates the expression of inflammatory genes in macrophages. There are many LXR-related studies in adults with metabolic syndrome but rare reports in obese children with obstructive sleep apnea-hypopnea syndrome (OSAHS). The aim of this study was to investigate the expression of LXR, cholesterol ester transfer protein (CETP), and cyclooxygenase-2 (COX-2) genes in obese children with OSAHS compared with obese children without OSAHS and non-obese children. MATERIAL AND METHODS Sleep monitoring was conducted in 80 obese children with sleep disorders. Fasting morning blood samples from the 80 obese children and 51 normal children were collected and separated, so that macrophages were obtained after culture. Fluorescence quantitative real-time PCR (RT-PCR) was used to detect expression levels of the LXR, CETP, and COX-2 genes. RESULTS LXR, COX-2, and CETP levels in the OSAHS group were higher than those in the other two groups (P<0.05), and the LXR levels in the group of obese children without OSAHS were higher than those in control group (P<0.05). COX-2 expression in the group with moderate to severe OSAHS was higher than that in the group with mild OSAHS (P<0.05). Meanwhile, there were no significant differences in the LXR and CETP levels between the moderate to severe OSAHS group and the mild OSAHS group (P>0.05). CONCLUSIONS LXR gene expression was significantly increased in obese children with OSAHS. The severity of OSAHS was positively correlated with COX-2 levels. Show less
📄 PDF DOI: 10.12659/msm.900947
CETP
T Wang, X Ma, T Tang +13 more · 2017 · Nutrition & diabetes · Nature · added 2026-04-24
We aim to validate the effects of glucose-dependent insulinotropic polypeptide (GIP) on fat distribution and glucose metabolism in Han Chinese populations. We genotyped six tag single-nucleotide polym Show more
We aim to validate the effects of glucose-dependent insulinotropic polypeptide (GIP) on fat distribution and glucose metabolism in Han Chinese populations. We genotyped six tag single-nucleotide polymorphisms (SNPs) of GIP and four tag SNPs of glucose-dependent insulinotropic polypeptide receptor (GIPR) among 2884 community-based individuals from Han Chinese populations. Linear analysis was applied to test the associations of these variants with visceral fat area (VFA) and subcutaneous fat area (SFA) quantified by magnetic resonance imaging as well as glucose-related traits. We found that the C allele of rs4794008 of GIP tended to increase the VFA and the VFA/SFA ratio in all subjects (P=0.050 and P=0.054, respectively), and rs4794008 was associated with the VFA/SFA ratio in males (P=0.041) after adjusting for the BMI. The VFA-increasing allele of rs4794008 was not related to any glucose metabolism traits. However, rs9904288 of GIP was associated with the SFA in males as well as glucose-related traits in all subjects (P range, 0.004-0.049), and the GIPR variants displayed associations with both fat- and glucose-related traits. The results could provide the evidence that GIP might modulate visceral fat accumulation via incretin function or independent of incretin. Show less
📄 PDF DOI: 10.1038/nutd.2017.28
GIPR
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
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
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
Wen-Chi Hsueh, Anup K Nair, Sayuko Kobes +7 more · 2017 · Circulation. Cardiovascular genetics · added 2026-04-24
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment t Show more
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment the inherent genetic information that can be used for localization. Through identity-by-descent mapping, using ≈400 000 single-nucleotide polymorphisms (SNPs), of serum lipid profiles, we identified a major linkage signal for triglycerides in 1007 Pima Indians (LOD=9.23; Show less
📄 PDF DOI: 10.1161/CIRCGENETICS.117.001809
APOA5
Shui-ping ZHAO, Rong Li, Wen Dai +3 more · 2017 · PloS one · PLOS · added 2026-04-24
Xuezhikang (XZK), an extract of Chinese red yeast rice, is recommended as an optimal choice for patients with coronary heart disease (CHD) with markedly elevated triglyceride (TG) levels. This study w Show more
Xuezhikang (XZK), an extract of Chinese red yeast rice, is recommended as an optimal choice for patients with coronary heart disease (CHD) with markedly elevated triglyceride (TG) levels. This study was designed to compare the hypotriglyceridemic effects between XZK and simvastatin. The role of apolipoprotein A5 (apoA5), a key regulator of TG metabolism and a target gene of peroxisome proliferator-activated receptor α (PPARα), was to be identified in XZK-related hypotriglyceridemic actions. For these goals, hypertriglyceridemia of rats was induced by a high-fructose diet. In order to investigate the hypotriglyceridemic effects of XZK and simvastatin on these animals based on an equivalent low-density lipoprotein cholesterol (LDL-C) lowering power, we titrated their doses (XZK 80 mg/kg/d versus simvastatin 1 mg/kg/d) according to plasma LDL-C reduction of rats. Similarly, we titrated the target doses of the two agents (XZK 500 μg/ml versus simvastatin 10 μM) according to hepatocyte LDL receptor expressions, and then compared the effects of the two agents on TG and apoA5 of hepatocytes in vitro. Our results showed that XZK (80 mg/kg/d) had higher hypotriglyceridemic performance than simvastatin (1 mg/kg/d) on these animals albeit their equivalent LDL-C lowering power. Higher plasma apoA5 levels and hepatic apoA5 expressions were observed in rats treated with XZK (80 mg/kg/d) than simvastatin (1 mg/kg/d). Further, XZK (80 mg/kg/d) contributed to higher hepatic PPARα expressions of rats than simvastatin (1 mg/kg/d). Although the two agents led to an equivalent up-regulation of LDL receptors of hepatocytes, more TG reduction and apoA5 elevation were detected in hepatocytes treated with XZK (500 μg/ml) than simvastatin (10 μM). However, PPARα knockdown eliminated the above effects of XZK on hepatocytes. Therefore, our study indicates that XZK has greater hypotriglyceridemic performance than simvastatin in the setting of an equivalent LDL-C lowering power, which is attributed to more apoA5 up-regulation by this agent via the PPARα signaling pathway. Show less
📄 PDF DOI: 10.1371/journal.pone.0184949
APOA5
Zhonghong Wei, Yunlong Shan, Li Tao +7 more · 2017 · Molecular carcinogenesis · Wiley · added 2026-04-24
Intratumoral hypoxia promotes the distant metastasis of cancer subclones. The clinical expression level of hypoxia-inducible factor-1α (HIF-1α) reflects the prognosis of a variety of cancers, especial Show more
Intratumoral hypoxia promotes the distant metastasis of cancer subclones. The clinical expression level of hypoxia-inducible factor-1α (HIF-1α) reflects the prognosis of a variety of cancers, especially breast cancer. Histone deacetylase (HDAC) inhibitors can target HIF-1α protein due to von Hippel-Lindau (VHL) protein-dependent degradation. Dietary organosulfur compounds, such as those in garlic, have been reported as HDAC inhibitors. The effects of diallyl sulfide (DAS), diallyl disulfide (DADS), and diallyl trisulfide (DATS) on the ratio of firefly/Renilla luciferase activity in hypoxic MDA-MB-231 cells were determined. The mRNA expressions of HIF-1α target genes ANGPTL4, LOXL4, and LOX in hypoxic MDA-MB-231 cells were significantly down-regulated by DATS. DATS attenuated the metastatic potential of MDA-MB-231 cells in hypoxia-induced embryonic zebrafish, xenograft, and orthotopic tumors. Endothelial cell-cancer cell adhesion, wound healing, transwell, and tube formation assays showed that DATS dose-dependently inhibited the migration and angiogenesis of MDA-MB-231 cells in vitro. The expressions of L1CAM, VEGF-A, and EMT-related proteins (Slug, Snail, MMP-2) were inhibited by DATS. DATS dose-dependently inhibited HIF-1α transcriptional activity and hypoxia-induced hematogenous metastasis of MDA-MB-231 cells. It reduced the protein expression of HIF-1α, which did not involve inhibition of HIF-1α mRNA expression or ubiquitin proteasome degradation. Efficient inhibition of HIF-1α expression was required for DATS to resist breast cancer. Show less
no PDF DOI: 10.1002/mc.22686
ANGPTL4
Hongjuan He, Lei Lei, Erfei Chen +3 more · 2016 · Genetic testing and molecular biomarkers · added 2026-04-24
To explore the association of the APOA5 gene c.553G>T polymorphism with hypertriglyceridemia (HTG) susceptibility and altered triglyceride levels. We searched the PubMed, Google Scholar, and CNKI data Show more
To explore the association of the APOA5 gene c.553G>T polymorphism with hypertriglyceridemia (HTG) susceptibility and altered triglyceride levels. We searched the PubMed, Google Scholar, and CNKI databases for published studies relating to analyses of these associations. Case-control and comparative studies of the association between the APOA5 c.553G>T variant and altered triglyceride levels were included. In total, the meta-analysis involved 10 studies on HTG, which provided 2219 cases and 3401 controls. To measure the correlation between the c.553G>T polymorphism and HTG susceptibility, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The overall OR was calculated using a random-effects model. Compared with APOA5 c.553 GG carriers, c.553T carriers displayed an increased risk of HTG in the Asian population, with an overall random effects OR of 3.55 (95% CI: 2.46-5.13) in the dominant model. There was significant heterogeneity among the studies (P Our results suggest that APOA5 c. 553T is an independent risk factor for HTG and increased triglyceride levels in the Asian population. APOA5 c. 553T could be employed as a genetic risk marker for HTG and increased triglyceride levels. Show less
no PDF DOI: 10.1089/gtmb.2016.0047
APOA5
Junxiong Pang, Anna Lindblom, Thomas Tolfvenstam +8 more · 2016 · PloS one · PLOS · added 2026-04-24
Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue dis Show more
Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue disease in 2009. However, WS is limited in stratifying adult dengue patients at early infection (Day 1-3 post fever), who require close monitoring in hospitals to prevent severe dengue. The aim of this study is to identify and validate prognostic models, built with differentially expressed biomarkers, that enable the early identification of those with early dengue infection that require close clinical monitoring. RNA microarray and protein assays were performed to identify differentially expressed biomarkers of severity among 92 adult dengue patients recruited at early infection from years 2005-2008. This comprised 47 cases who developed WS after first presentation and required hospitalization (WS+Hosp), as well as 45 controls who did not develop WS after first presentation and did not require hospitalization (Non-WS+Non-Hosp). Independent validation was conducted with 80 adult dengue patients recruited from years 2009-2012. Prognostic models were developed based on forward stepwise and backward elimination estimation, using multiple logistic regressions. Prognostic power was estimated by the area under the receiver operating characteristic curve (AUC). The WS+Hosp group had significantly higher viral load (P<0.001), lower platelet (P<0.001) and lymphocytes counts (P = 0.004) at early infection compared to the Non-WS+Non-Hosp group. From the RNA microarray and protein assays, the top single RNA and protein prognostic models at early infection were CCL8 RNA (AUC:0.73) and IP-10 protein (AUC:0.74), respectively. The model with CCL8, VPS13C RNA, uPAR protein, and with CCL8, VPS13C RNA and platelets were the best biomarker models for stratifying adult dengue patients at early infection, with sensitivity and specificity up to 83% and 84%, respectively. These results were tested in the independent validation group, showing sensitivity and specificity up to 96% and 54.6%, respectively. At early infection, adult dengue patients who later presented WS and require hospitalization have significantly different pathophysiology compared with patients who consistently presented no WS and / or require no hospitalization. The molecular prognostic models developed and validated here based on these pathophysiology differences, could offer earlier and complementary indicators to the clinical WHO 2009 WS guide, in order to triage adult dengue patients at early infection. Show less
no PDF DOI: 10.1371/journal.pone.0155993
VPS13C
Tong-Hong Wang, Cheng-Chia Yu, Yong-Shiang Lin +6 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the fu Show more
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the function of lncRNAs in hepatocellular carcinoma (HCC) progression remains largely unknown. In this study, we performed a comprehensive microarray analysis of lncRNA expression using human HCC specimens. After validation in 119 human HCC tissues, we identified a novel tumor suppressor lncRNA, CPS1 intronic transcript 1 (CPS1-IT1). To elucidate the clinical significance of CPS1-IT1 in HCC, correlations between CPS1-IT1 levels, clinical parameters, and survival outcomes were analyzed. In vitro and in vivo functional assays were also performed to dissect the potential underlying mechanisms. Expression of CPS1-IT1 was significantly decreased in 73% of HCC tissues, and patients with low CPS1-IT1 expression had poor survival outcomes. Furthermore, in vitro functional assays indicated that CPS1-IT1 significantly reduced cell proliferation, migration and invasion capacities through reduced Hsp90 binding to and activation of HIF-1α, thereby suppressing the epithelial-mesenchymal transition (EMT). An in vivo animal model also demonstrated the tumor suppressor role of CPS1- IT1 via decreased tumor growth and metastasis. In conclusion, lncRNA CPS1-IT1 acts as a tumor suppressor in HCC by reducing HIF-1α activation and suppressing EMT. The findings of this study establish a function for CPS1-IT1 in HCC progression and suggest its potential as a new prognostic biomarker and target for HCC therapy. Show less
📄 PDF DOI: 10.18632/oncotarget.9635
CPS1
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
Yin-Feng Dong, Zheng-Zhen Chen, Zhan Zhao +4 more · 2016 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
It is generally recognized that the inflammatory reaction in glia is one of the important pathological factors in brain ischemic injury. Our previous study has revealed that opening ATP-sensitive pota Show more
It is generally recognized that the inflammatory reaction in glia is one of the important pathological factors in brain ischemic injury. Our previous study has revealed that opening ATP-sensitive potassium (K-ATP) channels could attenuate glial inflammation induced by ischemic stroke. However, the detailed mechanisms are not well known. Primary cultured astrocytes separated from C57BL/6 mice were subjected to oxygen-glucose deprivation (OGD); cellular injuries were determined via observing the changes of cellular morphology and cell viability. MicroRNA (miR) and messenger RNA (mRNA) level was validated by real-time PCR. The interaction between microRNA and the target was confirmed via dual luciferase reporter gene assay. Expressions of proteins and inflammatory cytokines were respectively assessed by western blotting and enzyme-linked immunosorbent assay. OGD resulted in astrocytic damage, which was prevented by K-ATP channel opener nicorandil. Notably, we found that OGD significantly downregulated miR-7 and upregulated Herpud2. Our further study proved that miR-7 targeted Herpud2 3'UTR, which encoded endoplasmic reticulum (ER) stress protein-HERP2. Correspondingly, our results showed that OGD increased the levels of ER stress proteins along with significant elevations of pro-inflammatory cytokines, including tumor necrosis factor α (TNF-α) and interleukin 1β (IL-1β). Pretreatment with nicorandil could remarkably upregulate miR-7, depress the ER-related protein expressions including glucose-regulated protein 78 (GRP78), C/EBP-homologous protein (CHOP), and Caspase-12, and thereby attenuate inflammatory responses and astrocytic damages. These findings demonstrate that opening K-ATP channels protects astrocytes against OGD-mediated neuroinflammation. Potentially, miR-7-targeted ER stress acts as a key molecular brake on neuroinflammation. Show less
📄 PDF DOI: 10.1186/s12974-016-0527-5
HEY2
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
Wen-li Song, Yu Tian, Xian-e Wang +7 more · 2016 · Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · added 2026-04-24
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of agg Show more
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of aggressive periodontitis. A total of 353 patients with aggressive periodontitis (group AgP) and 125 matched controls (group HP) were recruited in the study. Genotyping of FADS1 rs174537 and serum biochemical indexes were tested at the study's start. The relationships between the levels of TP, GLB, ALB, A/G and genotyping were analyzed. (1) The detection rate of allele G in group AgP was higher than that in group HP(68.1% vs. 61.2%, P=0.046,OR=1.35,95% CI 1.00-1.83); the detection rate of genotype GG in group AgP was higher than in group HP(45.5% vs. 34.4%,P=0.029, OR=1.60, 95% CI 1.05-2.44). (2) In group AgP, the patients with GG genotype exhibited significantly lower TP, GLB than the patients with GT+TT genotype [(77.08 ± 7.88) g/L vs. (79.00 ± 4.66) g/L, P=0.007; (28.17 ± 7.63) g/L vs.(29.88 ± 3.49) g/L,P=0.007) and the higher A/G(1.72 ± 0.22 vs.1.67 ± 0.22, P=0.040), but there was no significant difference in ALB between the patients with GG genotype and the patients with GT+TT genotype. In group HP, there were no significant differences in TP, GLB, A/G and ALB between individuals with genotype GT+TT and with genotype GG. (3)Compared with individuals with genotype GT+TT in group HP, the AgP patients with genotype GT+TT exhibited significantly higher TP, GLB [(79.00 ± 4.66) g/L vs. (75.20 ± 4.53) g/L, P<0.01; (29.88 ± 3.49) g/L vs.(26.55 ± 2.94) g/L, P<0.01) and the lower A/G(1.67 ± 0.22 vs. 1.88 ± 0.30, P<0.01), but there was no significant difference in ALB. There were no significant differences in TP, GLB, A/G and ALB the between the AgP patients with genotype GG and the healthy subjects with the same genotype either. FADS1 rs174537 polymorphism is associated with aggressive periodontitis. The patients with genotype GG in group AgP had relatively lower TP,GLB and higher A/G. Genotype GG might be a risk indicator for aggressive periodontitis by reducing host defense capability and contributing to inflammatory response in the occurrence and development of aggressive periodontitis. Show less
no PDF
FADS1
Gu Jing, Junqin Chen, Guanlan Xu +1 more · 2016 · Molecular metabolism · Elsevier · added 2026-04-24
Carbohydrate-response element-binding protein (ChREBP) is the major transcription factor conferring glucose-induced gene expression in pancreatic islets, liver and adipose tissue. Recently, a novel Ch Show more
Carbohydrate-response element-binding protein (ChREBP) is the major transcription factor conferring glucose-induced gene expression in pancreatic islets, liver and adipose tissue. Recently, a novel ChREBP isoform, ChREBP-β, was identified in adipose tissue and found to be also expressed in islets and involved in glucose-induced beta cell proliferation. However, the physiological function of this less abundant β-isoform in the islet, and in diabetes, is largely unknown. The aims of the present study, therefore, were to determine how diabetes affects ChREBP-β and elucidate its physiological role in pancreatic beta cells. Non-obese diabetic and obese, diabetic ob/ob mice were used as models of T1D and T2D and human islets and the rat INS-1 beta cell line were exposed to low/high glucose and used for ChREBP isoform-specific gain-and-loss-of-function experiments. Changes in ChREBP-β and ChREBP-α were assessed by qRT-PCR, immunoblotting, promoter luciferase, and chromatin immunoprecipitation studies. Expression of the ChREBP-β isoform was highly induced in diabetes and by glucose, whereas ChREBP-α was downregulated. Interestingly, ChREBP-β gain-of-function experiments further revealed that it was ChREBP-β that downregulated ChREBP-α through a negative feedback loop. On the other hand, ChREBP-β knockdown led to unabated ChREBP-α activity and glucose-induced expression of target genes, suggesting that one of the physiological roles of this novel β-isoform is to help keep glucose-induced and ChREBP-α-mediated gene expression under control. We have identified a previously unappreciated negative feedback loop by which glucose-induced ChREBP-β downregulates ChREBP-α-signaling providing new insight into the physiological role of islet ChREBP-β and into the regulation of glucose-induced gene expression. Show less
📄 PDF DOI: 10.1016/j.molmet.2016.09.010
MLXIPL
Yajun Zheng, Linghang Zhuang, Kristi Yi Fan +28 more · 2016 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based dru Show more
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based drug design platform that generates molecules using a context perceptive growth algorithm guided by a contact sensitive scoring function. The growth engine uses binding site perception and programmable growth capability to create drug-like molecules by assembling fragments that naturally complement hydrophilic and hydrophobic features of the protein binding site. Starting with a crystal structure of LXRβ and a docked 2-(methylsulfonyl)benzyl alcohol fragment (6), Contour was used to design agonists containing a piperazine core. Compound 17 binds to LXRβ with high affinity and to LXRα to a lesser extent, and induces the expression of LXR target genes in vitro and in vivo. This molecule served as a starting point for further optimization and generation of a candidate which is currently in human clinical trials for treating atopic dermatitis. Show less
no PDF DOI: 10.1021/acs.jmedchem.5b02029
NR1H3
Y Chen, Y W Gong, X Q Zhou +3 more · 2016 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
To explore the association between the tag single nucleotide polymorphism (tag SNP) of the adenylyl cyclase 3 (ADCY3) and the essential hypertension (EH). From April to July 2013, a total of 1 061 sub Show more
To explore the association between the tag single nucleotide polymorphism (tag SNP) of the adenylyl cyclase 3 (ADCY3) and the essential hypertension (EH). From April to July 2013, a total of 1 061 subjects diagnosed with EH and 1 218 control subjects were recruited from Ningbo, Zhejiang Province. Information was collected by face-to-face interview. Twelve tag SNPs were detected by ligase detection reaction technique. After adjusted for age, gender, body mass index and other related factors, logistic regression analysis showed that 3 loci (rs11689546, rs7593130, rs2241759)were associated with EH. AG genotype of rs11689546 was associated with 0.494 times lower risk of EH (OR=0.494, 95%CI 0.246-0.993; compared with AA genotype). CT genotype of rs7593130 was associated with 1.596 times higher risk of EH (OR=1.596, 95%CI 1.009-2.524; compared with TT genotype), and CT/CC genotype of rs7593130 was associated with 1.627 times higher risk of EH (OR=1.627, 95%CI 1.034-2.559; compared with TT genotype). AG genotype of rs2241759 was associated with 0.669 times lower risk of EH (OR=0.669, 95%CI 0.503-0.891; compared with AA genotype), and CT/CC genotype of rs2241759 was associated with 0.687 times lower risk of EH (OR=0.687, 95%CI 0.518-0.911; compared with TT genotype). The polymorphisms of ADCY3 are associated with lower (G allele of the rs11689546 locus and G allele of the rs2241759 locus) or higher (C allele of the rs7593130 locus) risk of essential hypertension. Show less
no PDF DOI: 10.3760/cma.j.issn.0253-3758.2016.07.008
ADCY3
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
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
Haiying Chen, Hongli Yang, Chong Xu +8 more · 2016 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow- Show more
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow-derived mesenchymal stem cells (rBMSCs) transduced with a mutant caveolin-1(F92A-Cav1) could enhance endothelial nitric oxide synthase (eNOS) activity and improve pulmonary vascular remodeling, but the potential mechanism is not yet fully explored. The present study was to investigate the gene expression profile upon rBMSCs/F92A-Cav1delivered to PAH rat to evaluate the role of F92A-Cav1 in its regulation. PAH was induced with monocrotaline (MCT, 60mg/kg) prior to delivery of lentiviral vector transduced rBMSCs expressing Cav1 or F92A-Cav1. Gene expression profiling was performed using Rat Signal Transduction PathwayFinder array. The expression changes of 84 key genes representing 10 signal transduction pathways in rat following rBMSCs/F92A-Cav1 treatment was examined. Screening with the Rat Signal Transduction PathwayFinder R rBMSCs/F92A-Cav1 inhibits inflammation and cell proliferation by regulating signaling pathways that related to inflammation, proliferation, cell cycle and oxidative stress. Show less
no PDF DOI: 10.1016/j.biopha.2016.06.028
HEY2
Jiping Yue, Yao Zhang, Wenguang G Liang +9 more · 2016 · Nature communications · Nature · added 2026-04-24
Turnover of focal adhesions allows cell retraction, which is essential for cell migration. The mammalian spectraplakin protein, ACF7 (Actin-Crosslinking Factor 7), promotes focal adhesion dynamics by Show more
Turnover of focal adhesions allows cell retraction, which is essential for cell migration. The mammalian spectraplakin protein, ACF7 (Actin-Crosslinking Factor 7), promotes focal adhesion dynamics by targeting of microtubule plus ends towards focal adhesions. However, it remains unclear how the activity of ACF7 is regulated spatiotemporally to achieve focal adhesion-specific guidance of microtubule. To explore the potential mechanisms, we resolve the crystal structure of ACF7's NT (amino-terminal) domain, which mediates F-actin interactions. Structural analysis leads to identification of a key tyrosine residue at the calponin homology (CH) domain of ACF7, whose phosphorylation by Src/FAK (focal adhesion kinase) complex is essential for F-actin binding of ACF7. Using skin epidermis as a model system, we further demonstrate that the phosphorylation of ACF7 plays an indispensable role in focal adhesion dynamics and epidermal migration in vitro and in vivo. Together, our findings provide critical insights into the molecular mechanisms underlying coordinated cytoskeletal dynamics during cell movement. Show less
📄 PDF DOI: 10.1038/ncomms11692
MACF1
Juliet D French, Sharon E Johnatty, Yi Lu +75 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify ge Show more
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression. Show less
📄 PDF DOI: 10.18632/oncotarget.7047
CCDC171
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
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
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
Rui-Ping Sun, Qian-Yun Xi, Jia-Jie Sun +8 more · 2016 · Scientific reports · Nature · added 2026-04-24
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduc Show more
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduces urea nitrogen. MicroRNAs (miRNAs) are major regulatory non-coding RNAs that have significant effects on several metabolic pathways; however, little is known on whether miRNAs regulate hepatic urea synthesis. The objective of this study was to assess the miRNA expression profile in a low protein diet and identify miRNAs involved in the regulation of the hepatic urea cycle using a porcine model. Weaned 28-days old piglets were fed a corn-soybean normal protein diet (NP) or a corn-soybean low protein diet (LP) for 30 d. Hepatic and blood samples were collected, and the miRNA expression profile was assessed by sequencing and qRT-PCR. Furthermore, we evaluated the possible role of miR-19b in urea synthesis regulation. There were 25 differentially expressed miRNAs between the NP and LP groups. Six of these miRNAs were predicted to be involved in urea cycle metabolism. MiR-19b negatively regulated urea synthesis by targeting SIRT5, which is a positive regulator of CPS1, the rate limiting enzyme in the urea cycle. Our study presented a novel explanation of ureagenesis regulation by miRNAs. Show less
📄 PDF DOI: 10.1038/srep33291
CPS1
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
Jian Meng, Ming Feng, Weibing Dong +11 more · 2016 · Scientific reports · Nature · added 2026-04-24
Transcription factor carbohydrate responsive element binding protein (ChREBP) promotes glycolysis and lipogenesis in metabolic tissues and cancer cells. ChREBP-α and ChREBP-β, two isoforms of ChREBP t Show more
Transcription factor carbohydrate responsive element binding protein (ChREBP) promotes glycolysis and lipogenesis in metabolic tissues and cancer cells. ChREBP-α and ChREBP-β, two isoforms of ChREBP transcribed from different promoters, are both transcriptionally induced by glucose. However, the mechanism by which glucose increases ChREBP mRNA levels remains unclear. Here we report that hepatocyte nuclear factor 4 alpha (HNF-4α) is a key transcription factor for glucose-induced ChREBP-α and ChREBP-β expression. Ectopic HNF-4α expression increased ChREBP transcription while knockdown of HNF-4α greatly reduced ChREBP mRNA levels in liver cancer cells and mouse primary hepatocytes. HNF-4α not only directly bound to an E-box-containing region in intron 12 of the ChREBP gene, but also promoted ChREBP-β transcription by directly binding to two DR1 sites and one E-box-containing site of the ChREBP-β promoter. Moreover, HNF-4α interacted with ChREBP-α and synergistically promoted ChREBP-β transcription. Functionally, HNF-4α suppression reduced glucose-dependent ChREBP induction. Increased nuclear abundance of HNF-4α and its binding to cis-elements of ChREBP gene in response to glucose contributed to glucose-responsive ChREBP transcription. Taken together, our results not only revealed the novel mechanism by which HNF-4α promoted ChREBP transcription in response to glucose, but also demonstrated that ChREBP-α and HNF-4α synergistically increased ChREBP-β transcription. Show less
📄 PDF DOI: 10.1038/srep23944
MLXIPL