👤 Fang-Yu 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-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, 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
Jessica Jennings, Dongquan Chen, Dale Feldman · 2008 · Bioelectromagnetics · Wiley · added 2026-04-24
During the course of normal wound healing, fibroblasts at the wound edge are exposed to electric fields (EFs) ranging from 40 to 200 mV/mm. Various forms of EFs influence fibroblast migration, prolife Show more
During the course of normal wound healing, fibroblasts at the wound edge are exposed to electric fields (EFs) ranging from 40 to 200 mV/mm. Various forms of EFs influence fibroblast migration, proliferation, and protein synthesis. Thus, EFs may contribute to fibroblast activation during wound repair. To elucidate the role of EFs during the normal progression of healing, this study compares gene expression in normal adult dermal fibroblasts exposed to a 100 mV/mm EF for 1 h to non-stimulated controls. Significantly increased expression of 162 transcripts and decreased expression of 302 transcripts was detected using microarrays, with 126 transcripts above the level of 1.4-fold increases or decreases compared to the controls. Above the level of twofold, only 11 genes were significantly increased or decreased compared to controls. Many of these significantly regulated genes are associated with wound repair through the processes of matrix production, cellular signaling, and growth. Activity within specific cellular signaling pathways is noted, including TGF-beta, G-proteins, and inhibition of apoptosis. In addition, RT-PCR analysis of the expression of KLF6, FN1, RGS2, and JMJD1C over continued stimulation and at different field strengths suggests that there are specific windows of field characteristics for maximum induction of these genes. EFs thus appear to have an important role in controlling fibroblast activity in the process of wound healing. Show less
no PDF DOI: 10.1002/bem.20408
JMJD1C
Yu Bai, Kelly Markham, Fusheng Chen +10 more · 2008 · Molecular & cellular proteomics : MCP · American Society for Biochemistry and Molecular Biology · added 2026-04-24
Despite intense research efforts, the physiological function and molecular environment of the amyloid precursor protein has remained enigmatic. Here we describe the application of time-controlled tran Show more
Despite intense research efforts, the physiological function and molecular environment of the amyloid precursor protein has remained enigmatic. Here we describe the application of time-controlled transcardiac perfusion cross-linking, a method for the in vivo mapping of protein interactions in intact tissue, to study the interactome of the amyloid precursor protein (APP). To gain insights into the specificity of reported protein interactions the study was extended to the mammalian amyloid precursor-like proteins (APLP1 and APLP2). To rule out sampling bias as an explanation for differences in the individual datasets, a small scale quantitative iTRAQ (isobaric tags for relative and absolute quantitation)-based comparison of APP, APLP1, and APLP2 interactomes was carried out. An interactome map was derived that confirmed eight previously reported interactions of APP and revealed the identity of more than 30 additional proteins that reside in spatial proximity to APP in the brain. Subsequent validation studies confirmed a physiological interaction between APP and leucine-rich repeat and Ig domain-containing protein 1, demonstrated a strong influence of Ig domain-containing protein 1 on the proteolytic processing of APP, and consolidated similarities in the biology of APP and p75. Show less
no PDF DOI: 10.1074/mcp.M700077-MCP200
LINGO1
Ming V Li, Weiqin Chen, Naravat Poungvarin +2 more · 2008 · Molecular endocrinology (Baltimore, Md.) · added 2026-04-24
Carbohydrate response element-binding protein (ChREBP) is a basic helix-loop-helix/leucine zipper transcription factor that binds to the carbohydrate response element in the promoter of certain lipoge Show more
Carbohydrate response element-binding protein (ChREBP) is a basic helix-loop-helix/leucine zipper transcription factor that binds to the carbohydrate response element in the promoter of certain lipogenic and glycolytic genes. High glucose can activate ChREBP by releasing an intramolecular inhibition within the glucose-sensing module (GSM) that occurs in low glucose. We report here that the glucose response of GSM is mediated by cooperation between five conserved submodules known as Mondo conserved regions (MCRs) I through V within GSM. Deletion of individual MCRs leads to complete (for MCR II, III, and IV) or partial (MCR I) loss of glucose response of ChREBP. MCR IV is necessary and sufficient for inhibiting the transcriptional activity of ChREBP under low glucose. The roles of MCR II and III in glucose response of ChREBP are independent of and distinct from their function in controlling subcellular localization. We further demonstrate that, instead of inhibiting ChREBP activity as would be predicted from its cytoplasmic retentive function, 14-3-3 binding with MCR III is essential for the glucose responsiveness of ChREBP. The interaction between 14-3-3 and ChREBP is constitutive, indicating a permissive role of 14-3-3 in the glucose response of ChREBP. We further uncovered an unconventional 14-3-3 binding motif (residues 116-135) lacking phosphor-serine/threonine within MCR III, a predicted alpha-helix highly conserved in all Mondo proteins. We conclude that individual subdomains in the GSM (MCR I through V) play diverse but crucial roles in cooperation with essential trans-acting cofactors such as 14-3-3 proteins to mediate the glucose response of ChREBP. Show less
no PDF DOI: 10.1210/me.2007-0560
MLXIPL
Shuxia Wang, Yubao Zou, Chunyan Fu +8 more · 2008 · Clinical cardiology · Wiley · added 2026-04-24
No data are available on survival analysis and longitudinal evolution of patients with gene mutations of beta-myosin heavy chain (MYH7) and myosin binding protein C (MYBPC3) in Chinese. To prospective Show more
No data are available on survival analysis and longitudinal evolution of patients with gene mutations of beta-myosin heavy chain (MYH7) and myosin binding protein C (MYBPC3) in Chinese. To prospectively investigate whether different gene mutations confer distinct prognosis. We performed a prospective study in 70 HCM patients and 46 genetically affected family members without HCM-phenotype with direct DNA sequencing of MYH7 and MYBPC3, clinical assessments, and 5.8 +/- 1.8 years follow-up. After follow-up, more surgical intervention (8/52 versus 0/18, p < 0.001), higher sudden death risk (7/52 versus 0/18, p < 0.001) and shorter life span were found in patients with MYH7 mutations than in patients with MYBPC3 mutations (45.1 +/- 14.0 versus 73.5 +/- 7.5 years, p = 0.03). Seven of the 27 mutation carriers of MYH7 had clinical presentations of HCM, but no carriers of MYBPC3 mutations developed to HCM during follow-up. Maximal wall thickness was thicker in the patients carrying mutations in the global region of MYH7 than in those carrying mutations in the rod region of MYH7 (21.5 +/- 6.6 versus 15 +/- 6.1 mm, p < 0.05) at baseline. More sudden death (7/41 versus 0/11) and left ventricular dysfunction (NYHA Class III approximately IV, 17/32 versus 1/10) were identified in patients with mutations in the global region of MYH7 than in patients with other mutations. MYH7 mutations, especially in the global region, cause malignant clinical phenotypes. Show less
no PDF DOI: 10.1002/clc.20151
MYBPC3
Yoshikazu Naiki, Rosalinda Sorrentino, Michelle H Wong +15 more · 2008 · Journal of immunology (Baltimore, Md. : 1950) · added 2026-04-24
Experimental and clinical studies link Chlamydia pneumoniae infection to atherogenesis and atherothrombotic events, but the underlying mechanisms are unclear. We tested the hypothesis that C. pneumoni Show more
Experimental and clinical studies link Chlamydia pneumoniae infection to atherogenesis and atherothrombotic events, but the underlying mechanisms are unclear. We tested the hypothesis that C. pneumoniae-induced acceleration of atherosclerosis in apolipoprotein E (ApoE)(-/-) mice is reciprocally modulated by activation of TLR-mediated innate immune and liver X receptor alpha (LXRalpha) signaling pathways. We infected ApoE(-/-) mice and ApoE(-/-) mice that also lacked TLR2, TLR4, MyD88, or LXRalpha intranasally with C. pneumoniae followed by feeding of a high fat diet for 4 mo. Mock-infected littermates served as controls. Atherosclerosis was assessed in aortic sinuses and in en face preparation of whole aorta. The numbers of activated dendritic cells (DCs) within plaques and the serum levels of cholesterol and proinflammatory cytokines were also measured. C. pneumoniae infection markedly accelerated atherosclerosis in ApoE-deficient mice that was associated with increased numbers of activated DCs in aortic sinus plaques and higher circulating levels of MCP-1, IL-12p40, IL-6, and TNF-alpha. In contrast, C. pneumoniae infection had only a minimal effect on atherosclerosis, accumulation of activated DCs in the sinus plaques, or circulating cytokine increases in ApoE(-/-) mice that were also deficient in TLR2, TLR4, or MyD88. However, C. pneumoniae-induced acceleration of atherosclerosis in ApoE(-/-) mice was further enhanced in ApoE(-/-)LXRalpha(-/-) double knockout mice and was accompanied by higher serum levels of IL-6 and TNF-alpha. We conclude that C. pneumoniae infection accelerates atherosclerosis in hypercholesterolemic mice predominantly through a TLR/MyD88-dependent mechanism and that LXRalpha appears to reciprocally modulate and reduce the proatherogenic effects of C. pneumoniae infection. Show less
no PDF DOI: 10.4049/jimmunol.181.10.7176
NR1H3
Elizabeth A DiBlasio-Smith, Maya Arai, Elaine M Quinet +16 more · 2008 · Journal of translational medicine · BioMed Central · added 2026-04-24
LXRs (Liver X Receptor alpha and beta) are nuclear receptors that act as ligand-activated transcription factors. LXR activation causes upregulation of genes involved in reverse cholesterol transport ( Show more
LXRs (Liver X Receptor alpha and beta) are nuclear receptors that act as ligand-activated transcription factors. LXR activation causes upregulation of genes involved in reverse cholesterol transport (RCT), including ABCA1 and ABCG1 transporters, in macrophage and intestine. Anti-atherosclerotic effects of synthetic LXR agonists in murine models suggest clinical utility for such compounds. Blood markers of LXR agonist exposure/activity were sought to support clinical development of novel synthetic LXR modulators. Transcript levels of LXR target genes ABCA1 and ABCG1 were measured using quantitative reverse transcriptase/polymerase chain reaction assays (qRT-PCR) in peripheral blood from mice and rats (following a single oral dose) and monkeys (following 7 daily oral doses) of synthetic LXR agonists. LXRalpha, LXRbeta, ABCA1, and ABCG1 mRNA were measured by qRT-PCR in human peripheral blood mononuclear cells (PBMC), monocytes, T- and B-cells treated ex vivo with WAY-252623 (LXR-623), and protein levels in human PBMC were measured by Western blotting. ABCA1/G1 transcript levels in whole-blood RNA were measured using analytically validated assays in human subjects participating in a Phase 1 SAD (Single Ascending Dose) clinical study of LXR-623. A single oral dose of LXR agonists induced ABCA1 and ABCG1 transcription in rodent peripheral blood in a dose- and time-dependent manner. Induction of gene expression in rat peripheral blood correlated with spleen expression, suggesting LXR gene regulation in blood has the potential to function as a marker of tissue gene regulation. Transcriptional response to LXR agonist was confirmed in primates, where peripheral blood ABCA1 and ABCG1 levels increased in a dose-dependent manner following oral treatment with LXR-623. Human PBMC, monocytes, T- and B cells all expressed both LXRalpha and LXRbeta, and all cell types significantly increased ABCA1 and ABCG1 expression upon ex vivo LXR-623 treatment. Peripheral blood from a representative human subject receiving a single oral dose of LXR-623 showed significant time-dependent increases in ABCA1 and ABCG1 transcription. Peripheral blood cells express LXRalpha and LXRbeta, and respond to LXR agonist treatment by time- and dose-dependently inducing LXR target genes. Transcript levels of LXR target genes in peripheral blood are relevant and useful biological indicators for clinical development of synthetic LXR modulators. Show less
no PDF DOI: 10.1186/1479-5876-6-59
NR1H3
Kun L Ma, Xiong Z Ruan, Stephen H Powis +3 more · 2008 · Hepatology (Baltimore, Md.) · Wiley · added 2026-04-24
The prevailing theory in non-alcoholic fatty liver disease (NAFLD) is the "two-hit" hypothesis. The first hit mainly consists of lipid accumulation, and the second is subsequent systemic inflammation. Show more
The prevailing theory in non-alcoholic fatty liver disease (NAFLD) is the "two-hit" hypothesis. The first hit mainly consists of lipid accumulation, and the second is subsequent systemic inflammation. The current study was undertaken to investigate whether inflammatory stress exacerbates lipid accumulation in liver and its underlying mechanisms. We used interleukin-1beta (IL-1beta) and tumor necrosis factor alpha (TNF-alpha) stimulation in human hepatoblastoma cell line (HepG2) cells and primary hepatocytes in vitro, and casein injection in apolipoprotein E knockout mice in vivo to induce inflammatory stress. The effects of inflammatory stress on cholesterol accumulation were examined by histochemical staining and a quantitative intracellular cholesterol assay. The gene and protein expressions of molecules involved in cholesterol trafficking were examined by real-time polymerase chain reaction (PCR) and western blot. Cytokine production in the plasma of apolipoprotein E knockout mice was measured by enzyme-linked immunosorbent assay. Our results showed that inflammatory stress increased cholesterol accumulation in hepatic cells and in the livers of apolipoprotein E knockout mice. Further analysis showed that inflammatory stress increased the expression of low-density lipoprotein (LDL) receptor (LDLr), sterol regulatory element-binding protein (SREBP) cleavage activating protein (SCAP), and SREBP-2. Confocal microscopy showed that IL-1beta increased the translocation of SCAP/SREBP-2 complex from endoplasmic reticulum (ER) to Golgi in HepG2 cells, thereby activating LDLr gene transcription. IL-1beta, TNF-alpha, and systemic inflammation induced by casein injection also inhibited expression of adenosine triphosphate-binding cassette transporter A1 (ABCA1), peroxisome proliferator-activated receptor-alpha (PPAR-alpha), and liver X receptor-alpha (LXRalpha). This inhibitory effect may cause cholesterol efflux reduction. Inflammatory stress up-regulates LDLr-mediated cholesterol influx and down-regulates ABCA1-mediated cholesterol efflux in vivo and in vitro. This may exacerbate the progression of NAFLD by disrupting cholesterol trafficking control, especially during the second hit phase of liver damage. Show less
no PDF DOI: 10.1002/hep.22423
NR1H3
Jonathan T Pierce-Shimomura, Beth L Chen, James J Mun +3 more · 2008 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Alternative patterns of neural activity drive different rhythmic locomotory patterns in both invertebrates and mammals. The neuro-molecular mechanisms responsible for the expression of rhythmic behavi Show more
Alternative patterns of neural activity drive different rhythmic locomotory patterns in both invertebrates and mammals. The neuro-molecular mechanisms responsible for the expression of rhythmic behavioral patterns are poorly understood. Here we show that Caenorhabditis elegans switches between distinct forms of locomotion, or crawling versus swimming, when transitioning between solid and liquid environments. These forms of locomotion are distinguished by distinct kinematics and different underlying patterns of neuromuscular activity, as determined by in vivo calcium imaging. The expression of swimming versus crawling rhythms is regulated by sensory input. In a screen for mutants that are defective in transitioning between crawl and swim behavior, we identified unc-79 and unc-80, two mutants known to be defective in NCA ion channel stabilization. Genetic and behavioral analyses suggest that the NCA channels enable the transition to rapid rhythmic behaviors in C. elegans. unc-79, unc-80, and the NCA channels represent a conserved set of genes critical for behavioral pattern generation. Show less
no PDF DOI: 10.1073/pnas.0810359105
UNC79
Kuo-Hsuan Chang, Rong-Kuo Lyu, Mu-Yun Tseng +9 more · 2007 · Proteomics. Clinical applications · Wiley · added 2026-04-24
Guillain-Barré Syndrome (GBS) is a rare autoimmune inflammatory polyneuropathy with a high risk of respiratory failure and unclear pathogenesis. Currently, there are no valid biomarkers for diagnosis Show more
Guillain-Barré Syndrome (GBS) is a rare autoimmune inflammatory polyneuropathy with a high risk of respiratory failure and unclear pathogenesis. Currently, there are no valid biomarkers for diagnosis of GBS. We used 2-DE and MS to analyze the protein profiles of five pairs of cerebrospinal fluid (CSF) samples of the GBS patients and the patient controls. Three proteins (orosomucoid, haptoglobin and apolipoprotein A-IV) were up-regulated, and two proteins (prostaglandin D2 synthase and transthyretin) were down-regulated in the CSF of the GBS patients. The CSF haptoglobin level, quantified by enzyme-linked immunosorbent assay, was significantly higher in the GBS patients (12.44 ± 2.70 μg/mL) compared to the chronic inflammatory demyelinating polyradiculoneuropathy (2.82 ± 0.83 μg/mL), viral meningitis (3.57 ± 0.97 μg/mL) and control patients (1.44 ± 0.35 μg/mL, p<0.05). This study indicated that protein profile analysis using a combination of 2-DE and MS provides an effective strategy for elucidating the pathogenesis and identifying potential CSF biomarkers for GBS. The raised intrathecal synthesis of haptoglobin specifically only in GBS patients, but not in patients with other neurological diseases examined, provides evidence of central nervous system involvement in GBS, and may be used as a potential diagnostic marker for GBS. Show less
no PDF DOI: 10.1002/prca.200600949
APOA4
Y J La, C L Wan, H Zhu +5 more · 2007 · Journal of neural transmission (Vienna, Austria : 1996) · Springer · added 2026-04-24
This study aims to identify the effects of antipsychotics on plasma proteins, and on the proteins associated with schizophrenia. We applied proteomics technology to screen protein aberrations in Sprag Show more
This study aims to identify the effects of antipsychotics on plasma proteins, and on the proteins associated with schizophrenia. We applied proteomics technology to screen protein aberrations in Sprague-Dawley rats treated with antipsychotics and schizophrenic patients undergoing medication. ApoA-I was found significantly increased in the chlorpromazine-treated rats and decreased in the patients with treatment-resistant schizophrenia, which suggest that decreased levels of apoA-I might be associated with the pathology of schizophrenia and that chlorpromazine increases apoA-I levels as part of its therapeutic action. Show less
no PDF DOI: 10.1007/s00702-006-0607-2
APOA4
Guang-Hua Zhai, Ping Wen, Lan-Fang Guo +1 more · 2007 · Yi chuan = Hereditas · added 2026-04-24
The purpose of this study was to explore the frequency of apolipoprotein A5 (APOA5) -1131T/C polymorphism in Zhenjiang and its effects on lipid metabolism and insulin resistance in type II diabetes me Show more
The purpose of this study was to explore the frequency of apolipoprotein A5 (APOA5) -1131T/C polymorphism in Zhenjiang and its effects on lipid metabolism and insulin resistance in type II diabetes mellitus(DM) patients. The genotypes of APOA5 -1131T/C polymorphism were determined in 152 healthy individuals and 71 type II DM patients by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Serum levels of lipids, glucose and insulin in these subjects were also estimated by biochemical methods. The frequency of the APOA5-1131C allele in DM patients was significantly higher than that of the control group (0.430 vs 0.296, P = 0.006). When compared with the TT genotype, CC homozygotes had a significantly increased DM risk (OR=3.75, 95% CI: 1.57-8.92). In the DM group, the serum levels of triglyceride (TG) of C carriers (TC+CC) were significantly higher than those of non-C carriers (TT) (P 0.01), and serum levels of total cholesterol (TC) and low density lipoprotein cholesterol(LDL-c) in subjects with the CC genotype were also significantly higher than those with the TT genotype (P 0.05). However, there was no significance in profiles of insulin resistance in various genotypes in both groups. The APOA5 single nucleotide polymorphism was associ-ated with serum TG level in the population. The -1131C allele contributed to the increase of serum levels of TG, TC and LDL-c and but had no effect on profiles of insulin resistance in DM patients. The APOA5 -1131C allele may be associated with increased susceptibility to type II diabetes mellitus. Show less
no PDF DOI: 10.1360/yc-007-0541
APOA5
Michael Miller, Jeffrey Rhyne, Hegang Chen +5 more · 2007 · Archives of medical research · Elsevier · added 2026-04-24
Despite the growing epidemic of the metabolic syndrome (MetS), few studies have evaluated genetic polymorphisms associated with the MetS phenotype. One candidate, APOC3, modulates lipid and lipoprotei Show more
Despite the growing epidemic of the metabolic syndrome (MetS), few studies have evaluated genetic polymorphisms associated with the MetS phenotype. One candidate, APOC3, modulates lipid and lipoprotein metabolism and the promoter polymorphisms C-482T/T-455C are associated with loss of insulin downregulation. One hundred twenty two consecutive MetS cases were matched by age, sex and race in a 1:1 case-control design to evaluate the prevalence of common polymorphisms in the following candidate genes: APOC3, APOE, B3AR, FABP2, GNB3, LPL, and PPARalpha and PPARgamma. Compared to controls, MetS subjects exhibited a greater prevalence of APOC3 promoter polymorphisms. Specifically, the frequency of the variant C-482T and T-455C alleles was 70.5 and 81.9% of cases compared to 43.4 and 54.1% in controls, respectively (p <0.0001). Overall, APOC3 promoter variants were associated with a greater likelihood of MetS compared to wild type [C-482T (OR: 4.3; 95% CI: 2.2, 8.6 [p <0.0001]), T-455C (OR: 3.6; 95% CI: 2.0, 6.7 [p <0.0001])]. No material differences were identified between the other genetic variants tested and prevalence of MetS. These data, therefore, suggest that the APOC3 promoter polymorphisms C-482T and T-455C are associated with the MetS. Show less
no PDF DOI: 10.1016/j.arcmed.2006.10.013
APOC3
Debbie Y Dao, Xue Yang, Di Chen +2 more · 2007 · Annals of the New York Academy of Sciences · added 2026-04-24
Chondrocyte maturation during endochondral bone formation is regulated by a number of signals that either promote or inhibit maturation. Among these, two well-studied signaling pathways play crucial r Show more
Chondrocyte maturation during endochondral bone formation is regulated by a number of signals that either promote or inhibit maturation. Among these, two well-studied signaling pathways play crucial roles in modulating chondrocyte maturation: transforming growth factor-beta (TGF-beta)/Smad3 signaling slows the rate of chondrocyte maturation, while Wingless/INT-1-related (Wnt)/beta-catenin signaling enhances the rate of chondrocyte maturation. Axin1 and Axin2 are functionally equivalent and have been shown to inhibit Wnt/beta-catenin signaling and stimulate TGF-beta signaling. Here we show that while Wnt3a stimulates Axin2 in a negative feedback loop, TGF-beta suppresses the expression of both Axin1 and Axin2 and stimulates beta-catenin signaling. In Axin2 -/- chondrocytes, TGF-beta treatment results in a sustained increase in beta-catenin levels compared to wild-type chondrocytes. In contrast, overexpression of Axin enhanced TGF-beta signaling while overexpression of beta-catenin inhibited the ability of TGF-beta to induce Smad3-sensitive reporters. Finally, the suppression of the Axins is Smad3-dependent since the effect is absent in Smad3 -/- chondrocytes. Altogether these findings show that the Axins act to integrate signals between the Wnt/beta-catenin and TGF-beta/Smad pathways. Since the suppression Axin1 and Axin2 expression by TGF-beta reduces TGF-beta signaling and enhances Wnt/beta-catenin signaling, the overall effect is a shift from TGF-beta toward Wnt/beta-catenin signaling and an acceleration of chondrocyte maturation. Show less
no PDF DOI: 10.1196/annals.1402.082
AXIN1
Rugang Zhang, Wei Chen, Peter D Adams · 2007 · Molecular and cellular biology · added 2026-04-24
Senescence is characterized by an irreversible cell proliferation arrest. Specialized domains of facultative heterochromatin, called senescence-associated heterochromatin foci (SAHF), are thought to c Show more
Senescence is characterized by an irreversible cell proliferation arrest. Specialized domains of facultative heterochromatin, called senescence-associated heterochromatin foci (SAHF), are thought to contribute to the irreversible cell cycle exit in many senescent cells by repressing the expression of proliferation-promoting genes such as cyclin A. SAHF contain known heterochromatin-forming proteins, such as heterochromatin protein 1 (HP1) and the histone H2A variant macroH2A, and other specialized chromatin proteins, such as HMGA proteins. Previously, we showed that a complex of histone chaperones, histone repressor A (HIRA) and antisilencing function 1a (ASF1a), plays a key role in the formation of SAHF. Here we have further dissected the series of events that contribute to SAHF formation. We show that each chromosome condenses into a single SAHF focus. Chromosome condensation depends on the ability of ASF1a to physically interact with its deposition substrate, histone H3, in addition to its cochaperone, HIRA. In cells entering senescence, HP1gamma, but not the related proteins HP1alpha and HP1beta, becomes phosphorylated on serine 93. This phosphorylation is required for efficient incorporation of HP1gamma into SAHF. Remarkably, however, a dramatic reduction in the amount of chromatin-bound HP1 proteins does not detectably affect chromosome condensation into SAHF. Moreover, abundant HP1 proteins are not required for the accumulation in SAHF of histone H3 methylated on lysine 9, the recruitment of macroH2A proteins, nor other hallmarks of senescence, such as the expression of senescence-associated beta-galactosidase activity and senescence-associated cell cycle exit. Based on our results, we propose a stepwise model for the formation of SAHF. Show less
no PDF DOI: 10.1128/MCB.02019-06
CBX1
Ambrose Jong, Chun-Hua Wu, Han-Min Chen +6 more · 2007 · Eukaryotic cell · added 2026-04-24
Cryptococcus neoformans is a pathogenic yeast that often causes devastating meningoencephalitis in immunocompromised individuals. We have previously identified the C. neoformans CPS1 gene, which is re Show more
Cryptococcus neoformans is a pathogenic yeast that often causes devastating meningoencephalitis in immunocompromised individuals. We have previously identified the C. neoformans CPS1 gene, which is required for a capsular layer on the outer cell wall. In this report, we investigate the function of the CPS1 gene and its pathogenesis. We demonstrated that treatment of yeast with either 4-methylumbelliferone or hyaluronidase resulted in a reduction of the level of C. neoformans binding to human brain microvascular endothelial cells (HBMEC). Yeast extracellular structures were also altered accordingly in hyaluronidase-treated cells. Furthermore, observation of yeast strains with different hyaluronic acid contents showed that the ability to bind to HBMEC is proportional to the hyaluronic acid content. A killing assay with Caenorhabditis elegans demonstrated that the CPS1 wild-type strain is more virulent than the cps1Delta strain. When CPS1 is expressed in Saccharomyces cerevisiae and Escherichia coli, hyaluronic acid can be detected in the cells. Additionally, we determined by fluorophore-assisted carbohydrate electrophoretic analysis that hyaluronic acid is a component of the C. neoformans capsule. The size of hyaluronic acid molecules is evaluated by gel filtration and transmission electron microscopy studies. Together, our results support that C. neoformans CPS1 encodes hyaluronic acid synthase and that its product, hyaluronic acid, plays a role as an adhesion molecule during the association of endothelial cells with yeast. Show less
no PDF DOI: 10.1128/EC.00120-07
CPS1
Jian Tang, Jing-Wen Niu, Dong-Hui Xu +3 more · 2007 · World journal of gastroenterology · added 2026-04-24
To investigate the association between the configurational and compositional changes of nuclear matrix and the differentiation of carcinoma cells. Cells cultured with or without 5 x 10(-3) mmol/L of h Show more
To investigate the association between the configurational and compositional changes of nuclear matrix and the differentiation of carcinoma cells. Cells cultured with or without 5 x 10(-3) mmol/L of hexamethylene bisacetamide (HMBA) on Nickel grids were treated by selective extraction and prepared for whole mount observation under electron microscopy. The samples were examined under transmission electron microscope. Nuclear matrix proteins were selectively extracted and subjected to subcellular proteomics study. The protein expression patterns were analyzed by PDQuest software. Spots of differentially expressed nuclear matrix proteins were excised and subjected to in situ digestion with trypsin. The peptides were analyzed by matrix-assisted laser-desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). Data were submitted for database searching using Mascot tool (www.matrixscience.com). The nuclear matrix (NM) and intermediate filament (IF) in SMMC-7721 hepatocarcinoma cells were found relatively sparse and arranged irregularly. The nuclear lamina was non-uniform, and two kinds of filaments were not tightly connected. After induction for differentiation by HMBA, the NM-IF filaments were concentrated and distributed uniformly. The heterogeneous population of filaments, including highly branched ultrathin filaments could also be seen in the regular meshwork. The connection between the two kinds of filaments and the relatively thin, condensed and sharply demarcated lamina composed of intermediate-sized filaments was relatively fastened. Meanwhile, 21 NM proteins changed remarkably during SMMC-7721 cell differentiation. Four proteins, i.e. mutant Pyst1, hypothetical protein, nucleophosmin 1, and LBP were downregulated, whereas four other proteins, eIF6, p44 subunit, beta-tubulin, and SIN3B were upregulated with the last one, SR2/ASF found only in the differentiated SMMC-7721 cells. The induced differentiation of SMMC-7721 cells by HMBA is accompanied by the configurational changes of nuclear matrix-intermediate filament (NM-IF) system and the compositional changes of nuclear matrix protein expression. These changes may be important morphological or functional indications of the cancer cell reversion. Show less
no PDF DOI: 10.3748/wjg.v13.i20.2791
DUSP6
Hsuan-Yu Chen, Sung-Liang Yu, Chun-Houh Chen +14 more · 2007 · The New England journal of medicine · added 2026-04-24
Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of pat Show more
Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of patients with NSCLC. We used computer-generated random numbers to assign 185 frozen specimens for microarray analysis, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis, or both. We studied gene expression in frozen specimens of lung-cancer tissue from 125 randomly selected patients who had undergone surgical resection of NSCLC and evaluated the association between the level of expression and survival. We used risk scores and decision-tree analysis to develop a gene-expression model for the prediction of the outcome of treatment of NSCLC. For validation, we used randomly assigned specimens from 60 other patients. Sixteen genes that correlated with survival among patients with NSCLC were identified by analyzing microarray data and risk scores. We selected five genes (DUSP6, MMD, STAT1, ERBB3, and LCK) for RT-PCR and decision-tree analysis. The five-gene signature was an independent predictor of relapse-free and overall survival. We validated the model with data from an independent cohort of 60 patients with NSCLC and with a set of published microarray data from 86 patients with NSCLC. Our five-gene signature is closely associated with relapse-free and overall survival among patients with NSCLC. Show less
no PDF DOI: 10.1056/NEJMoa060096
DUSP6
Wei-De Lin, Shuan-Pei Lin, Chih-Ping Chen +1 more · 2007 · Human genetics · added 2026-04-24
no PDF
EXT1
Yogesh Dwivedi, Hooriyah S Rizavi, Tara Teppen +6 more · 2007 · Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · Nature · added 2026-04-24
Extracellular signal-regulated kinase 5 (ERK5), the newest member of the mitogen-activated protein (MAP) kinase family, is regulated differently than the other MAP kinases. Emerging evidence suggest t Show more
Extracellular signal-regulated kinase 5 (ERK5), the newest member of the mitogen-activated protein (MAP) kinase family, is regulated differently than the other MAP kinases. Emerging evidence suggest the role of ERK5 signaling in promoting cell proliferation, differentiation, neuronal survival, and neuroprotection. The present study investigates whether suicide brain is associated with alterations in components of the ERK5 signaling cascade. In the prefrontal cortex (PFC) and hippocampus of suicide subjects (n=28) and nonpsychiatric control subjects (n=21), we examined the catalytic activities and protein levels of ERK5 and upstream MAP kinase kinase MEK5 in various subcellular fractions; mRNA levels of ERK5 in total RNA; and DNA-binding activity of myocyte enhancer factor (MEF)2C, a substrate of ERK5. In the hippocampus of suicide subjects, we observed that catalytic activity of ERK5 was decreased in cytosolic and nuclear fractions, whereas catalytic activity of MEK5 was decreased in the total fraction. Further, decreased mRNA and protein levels of ERK5, but no change in protein level of MEK5 were noted. A decrease in MEF2C-DNA-binding activity in the nuclear fraction was also observed. No significant alterations were noted in the PFC of suicide subjects. The observed changes were not related to a specific psychiatric diagnosis. Our findings of reduced activation and/or expression of ERK5 and MEK5, and reduced MEF2C-DNA-binding activity demonstrate abnormalities in ERK5 signaling in hippocampus of suicide subjects and suggest possible involvement of this aberrant signaling in pathogenic mechanisms of suicide. Show less
no PDF DOI: 10.1038/sj.npp.1301372
MAP2K5
Li-Mien Chen, Wei-Wen Kuo, Jaw-Ji Yang +7 more · 2007 · Experimental physiology · added 2026-04-24
It is unclear whether cardiac hypertrophy and hypertrophy-related pathways will be induced by long-term intermittent hypoxia. Thirty-six Sprague-Dawley rats were randomly assigned into three groups: n Show more
It is unclear whether cardiac hypertrophy and hypertrophy-related pathways will be induced by long-term intermittent hypoxia. Thirty-six Sprague-Dawley rats were randomly assigned into three groups: normoxia, and long-term intermittent hypoxia (12% O(2), 8 h per day) for 4 weeks (4WLTIH) or for 8 weeks (8WLTIH). Myocardial morphology, trophic factors and signalling pathways in the three groups were determined by heart weight index, histological analysis, Western blotting and reverse transcriptase-polymerase chain reaction from the excised left ventricle. The ratio of whole heart weight to body weight, the ratio of left ventricular weight to body weight, the gross vertical cross-section of the heart and myocardial morphological changes were increased in the 4WLTIH group and were further augmented in the 8WLTIH group. In the 4WLTIH group, tumour necrosis factor-alpha(TNFalpha), insulin-like growth factor (IGF)-II, phosphorylated p38 mitogen-activated protein kinase (P38), signal transducers and activators of transcription (STAT)-1 and STAT-3 were significantly increased in the cardiac tissues. However, in the 8WLTIH group, in addition to the above factors, interleukin-6, mitogen-activated protein kinase (MEK)5 and extracellular signal-regulated kinase (ERK)5 were significantly increased compared with the normoxia group. We conclude that cardiac hypertrophy associated with TNFalpha and IGF-II was induced by intermittent hypoxia. The longer duration of intermittent hypoxia further activated the eccentric hypertrophy-related pathway, as well as the interleukin 6-related MEK5-ERK5 and STAT-3 pathways, which could result in the development of cardiac dilatation and pathology. Show less
no PDF DOI: 10.1113/expphysiol.2006.036590
MAP2K5
Ya-xi Chen, Ai-long Huang, Xiong-zhong Ruan · 2007 · Chinese medical journal · added 2026-04-24
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MLXIPL
E Warwick Daw, Suet Nee Chen, Grazyna Czernuszewicz +6 more · 2007 · Human molecular genetics · Oxford University Press · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a disease of mutant sarcomeric proteins (except for phenocopy). Cardiac hypertrophy is the clinical diagnostic hallmark of HCM and a major determinant of morbidity Show more
Hypertrophic cardiomyopathy (HCM) is a disease of mutant sarcomeric proteins (except for phenocopy). Cardiac hypertrophy is the clinical diagnostic hallmark of HCM and a major determinant of morbidity and mortality in various cardiovascular diseases. However, there is remarkable variability in expression of hypertrophy, even among HCM patients with identical causal mutations. We hypothesized modifier genes are partly responsible for the variation in hypertrophic expressivity. To map the modifier loci, we typed 811 short-tandem repeat markers ( approximately 5 cMdense) in 100 members of an HCM family including 36 with the InsG791 mutation in MYBPC3. We performed oligogenic simultaneous segregation and linkage analyses using Markov Chain Monte Carlo methods and detected linkage on 3q26.2 (180 cM), 10p13 (41 cM), 17q24 (108 cM) with log of the posterior placement probability ratio (LOP) of 3.51, 4.86 and 4.17, respectively, and suggestive linkage (LOP of 2.40) on 16q12.2 (73 cM). The effect sizes varied according to the modifier locus, age and sex. It ranged from approximately 8 g shift in left ventricular mass for 10p13 locus heterozygosity for the common allele to approximately 90 g shift for 3q26.2 locus homozygosity for the uncommon allele. Refining the 10p13 locus restricted the candidate modifier genes to ITGA8, C10orf97 (CARP) and PTER. ITGA8 and CARP are biologically plausible candidates as they are implicated in cardiac fibrosis and apoptosis, respectively. Since cardiac hypertrophy is a major determinant of total and cardiovascular mortality and morbidity, regardless of the etiology, identification of the specific modifier genes could have significant prognostic and therapeutic implications for various cardiovascular diseases. Show less
no PDF DOI: 10.1093/hmg/ddm202
MYBPC3
Shu-Xia Wang, Yu-bao Zou, Chun-Yan Fu +6 more · 2007 · Zhonghua yi xue za zhi · added 2026-04-24
To study the disease-causing gene mutation in Chinese patients with familial hypertrophic cardiomyopathy (FHC) and to analyze the correlation between the genotype and the phenotype. Peripheral blood s Show more
To study the disease-causing gene mutation in Chinese patients with familial hypertrophic cardiomyopathy (FHC) and to analyze the correlation between the genotype and the phenotype. Peripheral blood samples were collected from 40 members from a family affected with FHC, and 120 healthy volunteers. PCR was performed to analyze the exons and flanking introns of the cardiac troponin T gene (TNNT2), beta-myosin heavy chain gene (MYH7), and myosin-binding protein C gene (MYBPC3) and the products were sequenced. The clinical data including symptom, physical examination, echocardiography and electrocardiography were collected. A 14035c > t mutation, which causes a missense mutation (R130C) in exon 10 of TNNT2 gene were identified in 4 family members, including the proband, female, aged 53, with the onset at the age of 30. The 4 persons with the 14035c > t mutation, all FHC patients, presented left ventricular dysfunction with a penetrance of 100%. Two of the patients died of sudden cardiac death during follow-up. No mutation was identified in the MYH7 and MYBPC3 genes. The 14035c > t mutation of TNNT2 gene is the causal mutation of FHC which is associated with malignant phenotype with a penetrance of 100%. It is a reasonable procedure in HCM patients with malignant phenotype to screen mutation in the TNNT2 gene. Show less
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MYBPC3
Shu-Xia Wang, Yu-bao Zou, Chun-Yan Fu +5 more · 2007 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
To study the disease-causing gene mutation in Chinese patients with hypertrophic cardiomyopathy (HCM) and to analyze the genotype and phenotype correlation. One family (n = 27) affected with HCM were Show more
To study the disease-causing gene mutation in Chinese patients with hypertrophic cardiomyopathy (HCM) and to analyze the genotype and phenotype correlation. One family (n = 27) affected with HCM were chosen for the study. The full encoding exons and flanking sequences of beta-myosin heavy chain gene (MYH7) and cardiac myosin-binding protein C gene (MYBPC3) were amplified with PCR and the products were sequenced. The clinical data including symptom, physical, echocardiography and electrocardiography examinations were collected. We identified a 13261 G > A mutation, which causes a missense mutation (G758D) in exon 23 of MYBPC3 in 9 family members. One mutation carrier suffered from dilated cardiomyopathy (DCM) with asymmetric interventricular septal hypertrophy (14 mm). Another mutation carrier was diagnosed as HCM. The 13261 G > A mutation is associated with a DCM-like HCM and HCM phenotype in this Chinese family affected with HCM. Show less
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MYBPC3
Adriana Osio, Lily Tan, Suet N Chen +6 more · 2007 · Circulation research · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a genetic disorder caused by mutations in sarcomeric proteins (excluding phenocopy). The causal genes in approximately one-third of the cases remain unknown. We id Show more
Hypertrophic cardiomyopathy (HCM) is a genetic disorder caused by mutations in sarcomeric proteins (excluding phenocopy). The causal genes in approximately one-third of the cases remain unknown. We identified a family comprised of 6 clinically affected members. The phenotype was characterized by early onset of symptoms, pronounced cardiac hypertrophy, and cardiac arrhythmias. We excluded MYH7, MYBPC3, TNNT2, and ACTC1 as the causal gene either by direct sequencing or by haplotype analysis. To map the putative candidate sarcomeric gene, we perforbold locus-specific haplotyping to detect cosegregation of the locus haplotype with the phenotype, followed by mutation screening. We genotyped 5 short-tandem-repeat markers that spanned a 4.4-centimorgan region on 4q26-q27 locus and encompassed myozenin 2 (MYOZ2), a Z-disk protein. The maximum logarithm of odds score was 2.03 (P=0.005). All affected members shared a common haplotype, implicating MYOZ2 as the causal gene. To detect the causal mutation, we sequenced all exons and exon-intron boundaries of MYOZ2 in 10 family members and identified a T-->C missense mutation corresponding to S48P substitution, which cosegregated with inheritance of HCM (N=6). It was absent in 4 clinically normal family members and in 658 additional normal individuals. To determine frequency of the MYOZ2 mutations in HCM, we sequenced MYOZ2 in 516 HCM probands and detected another missense mutation (I246M). It was absent in 2 normal family members and 517 controls. Both mutations affect highly conserved amino acids. We conclude MYOZ2 is a novel causal gene for human HCM. Show less
no PDF DOI: 10.1161/01.RES.0000263008.66799.aa
MYBPC3
Guangyu Zhu, Jia Chen, Jay Liu +8 more · 2007 · The EMBO journal · Nature · added 2026-04-24
APPL1 is an effector of the small GTPase Rab5. Together, they mediate a signal transduction pathway initiated by ligand binding to cell surface receptors. Interaction with Rab5 is confined to the amin Show more
APPL1 is an effector of the small GTPase Rab5. Together, they mediate a signal transduction pathway initiated by ligand binding to cell surface receptors. Interaction with Rab5 is confined to the amino (N)-terminal region of APPL1. We report the crystal structures of human APPL1 N-terminal BAR-PH domain motif. The BAR and PH domains, together with a novel linker helix, form an integrated, crescent-shaped, symmetrical dimer. This BAR-PH interaction is likely conserved in the class of BAR-PH containing proteins. Biochemical analyses indicate two independent Rab-binding sites located at the opposite ends of the dimer, where the PH domain directly interacts with Rab5 and Rab21. Besides structurally supporting the PH domain, the BAR domain also contributes to Rab binding through a small surface region in the vicinity of the PH domain. In stark contrast to the helix-dominated, Rab-binding domains previously reported, APPL1 PH domain employs beta-strands to interact with Rab5. On the Rab5 side, both switch regions are involved in the interaction. Thus we identified a new binding mode between PH domains and small GTPases. Show less
no PDF DOI: 10.1038/sj.emboj.7601771
RAB21
Ling-Jin Huang, Sheng-Xi Chen, Wan-Jun Luo +3 more · 2006 · Ai zheng = Aizheng = Chinese journal of cancer · added 2026-04-24
Secreted proteins from cancer cells may be potential serologic biomarkers of cancer. It's important to globally identify secreted proteins of cancer cells. This study was to identify secreted proteins Show more
Secreted proteins from cancer cells may be potential serologic biomarkers of cancer. It's important to globally identify secreted proteins of cancer cells. This study was to identify secreted proteins of lung cancer cells. Proteins in the conditioned medium of non-small cell lung cancer (NSCLC) cell line A549 was collected and the proteome analysis was subsequently performed. Specific protein spots in A549 cells were identified by peptide mass fingerprints using mass spectrometry and through searching database. The expression of identified secreted proteins was detected by reverse transcription-polymerase chain reaction (RT-PCR) in 15 specimens of NSCLC tissue and paired distant lung tissue. Manganese superoxide dismutase (Mn-SOD) activity in serum and conditioned medium was detected by spectrophotometry. Fourteen secreted proteins were identified, which included peptidyl-prolyl cis-trans isomerase A (PPIA), Mn-SOD, peroxiredoxin 1 (PDX1), phosphatidylethanolamine binding protein (PEBP), glutathione S-transferase P (GSTP1-1), glucose-dependent insulinotropic protein receptor (GIPR), ubiquitin carboxyl-terminal hydrolase isozyme L1 (PGP9.5), alpha enolase (ENO1), dihydrodiol dehydrogenase (DDH), phosphoglycerate mutase 1 (PGAM1), galectin-1 (GAL1). PPIA, DDH, PGAM1, PDX1, PGP9.5, ENO1, and PEBP were overexpressed in cancer tissues. Higher level of Mn-SOD activity was detected in conditioned medium than in control. Serum Mn-SOD activity was significantly higher in NSCLC patients than in healthy controls (P<0.01). Multiple secreted proteins of A549 cells were identified in this study and the overexpression of ENO1 and PEBP in NSCLC was revealed for the first time. Mn-SOD is secreted serologic marker of NSCLC. The results presented here would provide clues to identify new serologic biomarkers of NSCLC. Show less
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GIPR
D Michael Hallman, Sathanur R Srinivasan, Wei Chen +2 more · 2006 · Metabolism: clinical and experimental · Elsevier · added 2026-04-24
Polymorphisms in the APOC3 and APOA5 genes, from the APOA1/APOC3/APOA4/APOA5 gene cluster on chromosome 11q23, have been associated with interindividual variation in plasma triglycerides. APOA5 polymo Show more
Polymorphisms in the APOC3 and APOA5 genes, from the APOA1/APOC3/APOA4/APOA5 gene cluster on chromosome 11q23, have been associated with interindividual variation in plasma triglycerides. APOA5 polymorphisms implicated include 2 in the promoter region (-1131 T/C and -3 A/G) and 1 in exon 2 (+56 C/G). APOC3 polymorphisms implicated include 1 (SstI) in the 3' untranslated region and 1 (-2854 G/T) in the APOC3-APOA4 intergenic region. We analyzed the associations of haplotypes and multilocus genotypes of these polymorphisms on longitudinal serum triglyceride profiles in 360 African American and 823 white subjects from the Bogalusa Heart Study. Subjects were examined from 2 to 8 times (mean +/- SD, 5.4 +/- 1.3) between 1973 and 1996, at ages ranging from 4 to 38 years, with 1978 observations in African Americans and 4465 in whites. Serum triglycerides were significantly higher among whites across all ages. Allele frequencies differed significantly between African Americans and whites at all but the APOA5 +56 C/G locus. Linkage disequilibrium among the loci was higher in whites and haplotype diversity lower: 6 haplotypes had estimated frequencies of more than 1% in African Americans, 5 in whites. Individually, all polymorphisms except APOC3 -2854 G/T showed significant associations with triglyceride levels in the full sample. However, genotype models including all 5 loci showed significant triglyceride associations for only 3 (APOC3 SstI, APOA5 -1131 T/C, and APOA5 +56 C/G); significant interactions among them indicated their effects were not independent. Neither APOC3 -2854 G/T nor APOA5 -3 A/G had significant effects when the other 3 loci were in the models. The EM algorithm was used to estimate haplotype frequencies and assign haplotype probabilities to individuals, which is conditional on their genotypes; individuals' haplotype probability vectors were then used as predictors in multilevel mixed models of longitudinal triglyceride profiles. Of haplotypes comprising, in order, APOC3 SstI and -2854 G/T and APOA5 -1131 T/C, -3 A/G, and +56 C/G, 3 were significantly associated with higher triglycerides, even after adjusting for multiple tests: GGTAG (P = .002), GTTAG (P < .0001), and CGCGC (P = .0002). Each GGTAG haplotype carried would be expected to raise triglyceride levels (relative to those of GTTAC homozygotes) by approximately 19 mg/dL, each GTTAG haplotype by approximately 15 mg/dL, and each CGCGC haplotype by approximately 7 mg/dL. Haplotypes comprising the 3 loci implicated by genotype analyses (SstI, -1131 T/C, and +56 C/G) were also tested: haplotypes C_C_C and G_T_G significantly raised triglycerides, even after adjustment for multiple comparisons (P < .002 for both), with each copy of C_C_C expected to raise triglycerides by approximately 7 mg/dL and each copy of G_T_G by approximately 15 mg/dL. Overall, our findings support those of others in associating specific polymorphisms and haplotypes in the APOA1/C3/A4/A5 gene cluster with higher serum triglyceride levels. However, the degree to which polymorphisms in the APOC3 and APOA5 genes may be independently associated with triglyceride levels remains to be determined. Show less
no PDF DOI: 10.1016/j.metabol.2006.07.018
APOA4
Yifeng Yang, Chunling Wan, Huafang Li +7 more · 2006 · Analytical chemistry · ACS Publications · added 2026-04-24
Schizophrenia is a relatively common psychiatric syndrome that affects virtually all brain functions. We investigated the plasma proteome of 22 schizophrenia male patients and 20 healthy male controls Show more
Schizophrenia is a relatively common psychiatric syndrome that affects virtually all brain functions. We investigated the plasma proteome of 22 schizophrenia male patients and 20 healthy male controls using two-dimensional gel electrophoresis and mass spectrometry. In total, we have identified 66 protein spots in human plasma and found that seven of them showed altered changes in schizophrenia patients, as compared to healthy controls, which mainly were acute phase proteins (APPs). Among these APPs, haptoglobin alpha2 chain (p < 0.001), haptoglobin beta chain (p < 0.001), alpha1-antitrypsin (p = 0.001), and complement factor B precursor (p = 0.022) showed overexpression in schizophrenia patients, whereas apolipoprotein A-I (p = 0.034) and transthyretin (p = 0.035) were found to be significantly decreased in patients. In addition, the expression of apolipoprotein A-IV (p = 0.018) was significantly up-regulated in schizophrenia patients, as compared to controls. We also found these APP genes, which were differentially expressed in this study, overlap in the schizophrenia susceptibility loci. Our findings further support the hypothesis that the inflammatory response system is linked to the pathophysiology of schizophrenia. Show less
no PDF DOI: 10.1021/ac051916x
APOA4
Guanghua Zhai, Ping Wen, Lanfang Guo +1 more · 2006 · Clinical chemistry and laboratory medicine · added 2026-04-24
Several independent population studies have reported that c.553G>T polymorphism of the apolipoprotein A5 gene (APOA5) is associated with hypertriglyceridaemia. The aim of this study is to investigate Show more
Several independent population studies have reported that c.553G>T polymorphism of the apolipoprotein A5 gene (APOA5) is associated with hypertriglyceridaemia. The aim of this study is to investigate the association between this genetic variation and the risk of type 2 diabetes mellitus. In this study, APOA5 c.553G>T polymorphisms in 152 healthy individuals and 71 type 2 diabetes mellitus patients were detected by PCR-restriction fragment length polymorphism and agarose electrophoresis methods, and serum levels of lipids were also estimated by biochemical methods. The frequency of T alleles in the diabetes and control groups was 0.085 and 0.049, respectively. Compared with controls, there was no significant difference in the distribution of genotype and allele frequencies of c.553G>T polymorphic sites in diabetic patients (p=0.27 and p=0.15, respectively). However, the frequency of GT and TT genotypes and the T allele in the subgroup with hypertriglyceridaemia was significantly higher than that in the subgroup with normal triglyceridaemia in both the control group (p=0.034 and p=0.014, respectively) and the diabetes group (p=0.037 and p=0.007, respectively). In the diabetes and control groups, triglyceride levels in (GT+TT) genotype individuals were significantly higher than in GG genotype individuals (p=0.001 and p=0.003, respectively), and levels of low-density lipoprotein cholesterol were also significantly higher (p=0.044 and p=0.022, respectively). APOA5 c.553G>T polymorphism is not significantly associated with susceptibility to type 2 diabetes mellitus, but is associated with plasma triglyceride and low-density lipoprotein cholesterol levels. Show less
no PDF DOI: 10.1515/CCLM.2006.255
APOA5