👤 Jingde 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 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, 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
Mo Chen, Nan Zhu, Xiaochuan Liu +6 more · 2015 · Genes & development · Cold Spring Harbor Laboratory · added 2026-04-24
RUNX1-RUNX1T1 (formerly AML1-ETO), a transcription factor generated by the t(8;21) translocation in acute myeloid leukemia (AML), dictates a leukemic program by increasing self-renewal and inhibiting Show more
RUNX1-RUNX1T1 (formerly AML1-ETO), a transcription factor generated by the t(8;21) translocation in acute myeloid leukemia (AML), dictates a leukemic program by increasing self-renewal and inhibiting differentiation. Here we demonstrate that the histone demethylase JMJD1C functions as a coactivator for RUNX1-RUNX1T1 and is required for its transcriptional program. JMJD1C is directly recruited by RUNX1-RUNX1T1 to its target genes and regulates their expression by maintaining low H3K9 dimethyl (H3K9me2) levels. Analyses in JMJD1C knockout mice also establish a JMJD1C requirement for RUNX1-RUNX1T1's ability to increase proliferation. We also show a critical role for JMJD1C in the survival of multiple human AML cell lines, suggesting that it is required for leukemic programs in different AML cell types through its association with key transcription factors. Show less
📄 PDF DOI: 10.1101/gad.267278.115
JMJD1C
Rui Zhang, Peijuan Cao, Zhongzhou Yang +4 more · 2015 · PloS one · PLOS · added 2026-04-24
Glycosaminoglycans are important regulators of multiple signaling pathways. As a major constituent of the heart extracellular matrix, glycosaminoglycans are implicated in cardiac morphogenesis through Show more
Glycosaminoglycans are important regulators of multiple signaling pathways. As a major constituent of the heart extracellular matrix, glycosaminoglycans are implicated in cardiac morphogenesis through interactions with different signaling morphogens. Ext1 is a glycosyltransferase responsible for heparan sulfate synthesis. Here, we evaluate the function of Ext1 in heart development by analyzing Ext1 hypomorphic mutant and conditional knockout mice. Outflow tract alignment is sensitive to the dosage of Ext1. Deletion of Ext1 in the mesoderm induces a cardiac phenotype similar to that of a mutant with conditional deletion of UDP-glucose dehydrogenase, a key enzyme responsible for synthesis of all glycosaminoglycans. The outflow tract defect in conditional Ext1 knockout(Ext1f/f:Mesp1Cre) mice is attributable to the reduced contribution of second heart field and neural crest cells. Ext1 deletion leads to downregulation of FGF signaling in the pharyngeal mesoderm. Exogenous FGF8 ameliorates the defects in the outflow tract and pharyngeal explants. In addition, Ext1 expression in second heart field and neural crest cells is required for outflow tract remodeling. Our results collectively indicate that Ext1 is crucial for outflow tract formation in distinct progenitor cells, and heparan sulfate modulates FGF signaling during early heart development. Show less
📄 PDF DOI: 10.1371/journal.pone.0136518
EXT1
Jing Tang, Kang Luo, Yan Li +4 more · 2015 · International immunopharmacology · Elsevier · added 2026-04-24
Here, we investigated the role of LXRα in capsaicin mediated anti-inflammatory effects. Results revealed that capsaicin inhibits LPS-induced IL-1β, IL-6 and TNF-α production in a time- and dose-depend Show more
Here, we investigated the role of LXRα in capsaicin mediated anti-inflammatory effects. Results revealed that capsaicin inhibits LPS-induced IL-1β, IL-6 and TNF-α production in a time- and dose-dependent manner. Moreover, capsaicin increases LXRα expression through PPARγ pathway. Inhibition of LXRα activation by siRNA diminished the inhibitory action of capsaicin on LPS-induced IL-1β, IL-6 and TNF-α production. Additionally, LXRα siRNA abrogated the inhibitory action of capsaicin on p65 NF-κB protein expression. Thus, we propose that the anti-inflammatory effects of capsaicin are LXRα dependent, and LXRα may potentially link the capsaicin mediated PPARγ activation and NF-κB inhibition in LPS-induced inflammatory response. Show less
no PDF DOI: 10.1016/j.intimp.2015.06.007
NR1H3
Yu Zhang, Cheng Ge, Lin Wang +4 more · 2015 · FEBS letters · Elsevier · added 2026-04-24
Dickkopf1 (DKK1), a canonical Wnt/β-catenin pathway antagonist, is closely associated with cardiovascular disease and adipogenesis. We performed an in vitro study to determine whether oxidized low-den Show more
Dickkopf1 (DKK1), a canonical Wnt/β-catenin pathway antagonist, is closely associated with cardiovascular disease and adipogenesis. We performed an in vitro study to determine whether oxidized low-density lipoprotein (ox-LDL) increased the expression of DKK1 in macrophages and whether β-catenin and liver X receptor α (LXRα) were involved in this regulation. Induction of DKK1 expression by ox-LDL decreased the level of lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) via a Wnt/β-catenin pathway and increased ATP-binding cassette transporter A/G1 (ABCA/G1) levels via a signal transducer and activator of transcription 3 (STAT3) pathway. Lower LOX-1 and higher ABCA/G1 levels inhibited cholesterol loading in macrophages. In conclusion, ox-LDL may induce DKK1 expression in macrophages to inhibit the accumulation of lipids through a mechanism that involves downregulation of LOX-1-mediated lipid uptake and upregulation of ABCA/G1-dependent cholesterol efflux. Show less
no PDF DOI: 10.1016/j.febslet.2014.11.023
NR1H3
Byeong Hyeok Choi, Xun Che, Changyan Chen +2 more · 2015 · Genes & cancer · Impact Journals · added 2026-04-24
WWP2 is a ubiquitin E3 ligase belonging to the Nedd4-like family. Given that WWP2 target proteins including PTEN that are crucial for regulating cell proliferation or suppressing tumorigenesis, we hav Show more
WWP2 is a ubiquitin E3 ligase belonging to the Nedd4-like family. Given that WWP2 target proteins including PTEN that are crucial for regulating cell proliferation or suppressing tumorigenesis, we have asked whether WWP2 plays a role in controlling cell cycle progression. Here we report that WWP2 is necessary for normal cell cycle progression as its silencing significantly reduces the cell proliferation rate. We have identified that an isoform of WWP2 (WWP2-V4) is highly expressed in the M phase of the cell cycle. Silencing of WWP2 accelerates the turnover of cyclin E, which is accompanied by increased levels of phospho-histone H3 (p-H3) and cyclin B. Moreover, silencing of WWP2 results in compromised phosphorylation of Akt(S473), a residue whose phosphorylation is tightly associated with the activation of the kinase. Combined, these results strongly suggest that WWP2 is an important component in regulating the Akt signaling cascade, as well as cell cycle progression. Show less
no PDF DOI: 10.18632/genesandcancer.83
WWP2
Hsiang-Kuang Tseng, Tseng-Yu Huang, Alice Ying-Jung Wu +3 more · 2015 · Future microbiology · added 2026-04-24
Cryptococcus demonstrates predilection for invasion of the brain, but the mechanism by which Cryptococcus crosses the blood-brain barrier (BBB) to cause brain invasion is largely unknown. In order for Show more
Cryptococcus demonstrates predilection for invasion of the brain, but the mechanism by which Cryptococcus crosses the blood-brain barrier (BBB) to cause brain invasion is largely unknown. In order for Cryptococcus to cross the BBB, there must be a way to either cross human brain microvascular endothelial cells, which are the main constitute of the BBB, or go in between tight junctions. Recent evidence of human brain microvascular endothelial cell responses to transcellular brain invasions includes membrane rearrangements, intracellular signaling pathways and cytoskeletal activations. Several Cryptococcal genes related to the traversal of BBB have been identified, including CPS1, ITR1a, ITR3c, PLB1, MPR1, FNX1 and RUB1. In addition, Cryptococcus neoformans-derived microvesicles may contribute to cryptococcal brain invasion. Paracellularly, Cryptococcus may traverse across BBB using either routes utilizing plasmin, ammonia or macrophages in a Trojan horse mechanism. Show less
no PDF DOI: 10.2217/fmb.15.83
CPS1
Hua-Cheng Liu, Danyan Zhu, Chan Wang +8 more · 2015 · PloS one · PLOS · added 2026-04-24
Etomidate is a rapid hypnotic intravenous anesthetic agent. The major side effect of etomidate is the reduced plasma concentration of corticosteroids, leading to the abnormal reaction of adrenals. Cor Show more
Etomidate is a rapid hypnotic intravenous anesthetic agent. The major side effect of etomidate is the reduced plasma concentration of corticosteroids, leading to the abnormal reaction of adrenals. Cortisol and testosterone biosynthesis has similar biosynthetic pathway, and shares several common steroidogenic enzymes, such as P450 side chain cleavage enzyme (CYP11A1) and 3β-hydroxysteroid dehydrogenase 1 (HSD3B1). The effect of etomidate on Leydig cell steroidogenesis during the cell maturation process is not well established. Immature Leydig cells isolated from 35 day-old rats were cultured with 30 μM etomidate for 3 hours in combination with LH, 8Br-cAMP, 25R-OH-cholesterol, pregnenolone, progesterone, androstenedione, testosterone and dihydrotestosterone, respectively. The concentrations of 5α-androstanediol and testosterone in the media were measured by radioimmunoassay. Leydig cells were cultured with various concentrations of etomidate (0.3-30 μM) for 3 hours, and total RNAs were extracted. Q-PCR was used to measure the mRNA levels of following genes: Lhcgr, Scarb1, Star, Cyp11a1, Hsd3b1, Cyp17a1, Hsd17b3, Srd5a1, and Akr1c14. The testis mitochondria and microsomes from 35-day-old rat testes were prepared and used to detect the direct action of etomidate on CYP11A1 and HSD3B1 activity. In intact Leydig cells, 30 μM etomidate significantly inhibited androgen synthesis. Further studies showed that etomidate also inhibited the LH- stimulated androgen production. On purified testicular mitochondria and ER fractions, etomidate competitively inhibited both CYP11A1 and HSD3B1 activities, with the half maximal inhibitory concentration (IC50) values of 12.62 and 2.75 μM, respectively. In addition, etomidate inhibited steroidogenesis-related gene expression. At about 0.3 μM, etomidate significantly inhibited the expression of Akr1C14. At the higher concentration (30 μM), it also reduced the expression levels of Cyp11a1, Hsd17b3 and Srd5a1. In conclusion, etomidate directly inhibits the activities of CYP11A1 and HSD3B1, and the expression levels of Cyp11a1 and Hsd17b3, leading to the lower production of androgen by Leydig cells. Show less
📄 PDF DOI: 10.1371/journal.pone.0139311
HSD17B12
Jiahong Jiang, Nan Wang, Yafei Jiang +4 more · 2015 · FEBS letters · Elsevier · added 2026-04-24
WW domains harbor substrates containing proline-rich motifs, but the substrate specificity and binding mechanism remain elusive for those WW domains less amenable for structural studies, such as human Show more
WW domains harbor substrates containing proline-rich motifs, but the substrate specificity and binding mechanism remain elusive for those WW domains less amenable for structural studies, such as human WWP2 (hWWP2). Herein we have employed multiple techniques to investigate the second WW domain (WW2) in hWWP2. Our results show that hWWP2 is a specialized E3 for PPxY motif-containing substrates only and does not recognize other amino acids and phospho-residues. The strongest binding affinity of WW2, and the incompatibility between each WW domain, imply a novel relationship, and our SPR experiment reveals a dynamic binding mode in Class-I WW domains for the first time. The results from alanine-scanning mutagenesis and modeling further point to functionally conserved residues in WW2. Show less
no PDF DOI: 10.1016/j.febslet.2015.05.021
WWP2
H Ito, H Shiwaku, C Yoshida +24 more · 2015 · Molecular psychiatry · Nature · added 2026-04-24
Human mutations in PQBP1, a molecule involved in transcription and splicing, result in a reduced but architecturally normal brain. Examination of a conditional Pqbp1-knockout (cKO) mouse with microcep Show more
Human mutations in PQBP1, a molecule involved in transcription and splicing, result in a reduced but architecturally normal brain. Examination of a conditional Pqbp1-knockout (cKO) mouse with microcephaly failed to reveal either abnormal centrosomes or mitotic spindles, increased neurogenesis from the neural stem progenitor cell (NSPC) pool or increased cell death in vivo. Instead, we observed an increase in the length of the cell cycle, particularly for the M phase in NSPCs. Corresponding to the developmental expression of Pqbp1, the stem cell pool in vivo was decreased at E10 and remained at a low level during neurogenesis (E15) in Pqbp1-cKO mice. The expression profiles of NSPCs derived from the cKO mouse revealed significant changes in gene groups that control the M phase, including anaphase-promoting complex genes, via aberrant transcription and RNA splicing. Exogenous Apc4, a hub protein in the network of affected genes, recovered the cell cycle, proliferation, and cell phenotypes of NSPCs caused by Pqbp1-cKO. These data reveal a mechanism of brain size control based on the simple reduction of the NSPC pool by cell cycle time elongation. Finally, we demonstrated that in utero gene therapy for Pqbp1-cKO mice by intraperitoneal injection of the PQBP1-AAV vector at E10 successfully rescued microcephaly with preserved cortical structures and improved behavioral abnormalities in Pqbp1-cKO mice, opening a new strategy for treating this intractable developmental disorder. Show less
no PDF DOI: 10.1038/mp.2014.69
ANAPC4
Lifang Hu, Peihong Su, Runzhi Li +4 more · 2015 · BMB reports · added 2026-04-24
Microtubule actin crosslinking factor 1 (MACF1), a widely expressed cytoskeletal linker, plays important roles in various cells by regulating cytoskeleton dynamics. However, its role in osteoblastic c Show more
Microtubule actin crosslinking factor 1 (MACF1), a widely expressed cytoskeletal linker, plays important roles in various cells by regulating cytoskeleton dynamics. However, its role in osteoblastic cells is not well understood. Based on our previous findings that the association of MACF1 with F-actin and microtubules in osteoblast-like cells was altered under magnetic force conditions, here, by adopting a stable MACF1-knockdown MC3T3-E1 osteoblastic cell line, we found that MACF1 knockdown induced large cells with a binuclear/multinuclear structure. Further, immunofluorescence staining showed disorganization of F-actin and microtubules in MACF1-knockdown cells. Cell counting revealed significant decrease of cell proliferation and cell cycle analysis showed an S phase cell cycle arrest in MACF1-knockdown cells. Moreover and interestingly, MACF1 knockdown showed a potential effect on cellular MTT reduction activity and mitochondrial content, suggesting an impact on cellular metabolic activity. These results together indicate an important role of MACF1 in regulating osteoblastic cell morphology and function. Show less
📄 PDF DOI: 10.5483/bmbrep.2015.48.10.098
MACF1
Lanlan Huang, Jian Chen, Peiqiu Cao +6 more · 2015 · Marine drugs · MDPI · added 2026-04-24
This study is to evaluate the anti-obese effects of glucosamine (GLC) and chitosan oligosaccharide (COS) on high-fat diet-induced obese rats. The rats were randomly divided into twelve groups: a norma Show more
This study is to evaluate the anti-obese effects of glucosamine (GLC) and chitosan oligosaccharide (COS) on high-fat diet-induced obese rats. The rats were randomly divided into twelve groups: a normal diet group (NF), a high-fat diet group (HF), Orlistat group, GLC high-, middle-, and low-dose groups (GLC-H, GLC-M, GLC-L), COS1 (COS, number-average molecular weight ≤1000) high-, middle-, and low-dose groups (COS1-H, COS1-M, COS1-L), and COS2 (COS, number-average molecular weight ≤3000) high-, middle-, and low-dose groups (COS2-H, COS2-M, COS2-L). All groups received oral treatment by gavage once daily for a period of six weeks. Rats fed with COS1 gained the least weight among all the groups (P < 0.01), and these rats lost more weight than those treated with Orlistat. In addition to the COS2-H and Orlistat groups, the serum total cholesterol (CHO) and low-density lipoprotein cholesterol (LDL-C) levels were significantly reduced in all treatment groups compared to the HF group (P < 0.01). The various doses of GLC, COS1 and COS2 reduced the expression levels of PPARγ and LXRα mRNA in the white adipose tissue. The results above demonstrated that GLC, COS1, and COS2 improved dyslipidemia and prevented body weight gains by inhibiting the adipocyte differentiation in obese rats induced by a high-fat diet. Thus, these agents may potentially be used to treat obesity. Show less
no PDF DOI: 10.3390/md13052732
NR1H3
Y Sun, R B Zhou, D M Chen · 2015 · Genetics and molecular research : GMR · added 2026-04-24
The aim of this study was to investigate correlations between apolipoprotein A-V (APOA5) -1131T>C and apolipoprotein C-III (APOC3) -455T>C polymorphisms and coronary heart disease (CHD). PubMed, Ovid, Show more
The aim of this study was to investigate correlations between apolipoprotein A-V (APOA5) -1131T>C and apolipoprotein C-III (APOC3) -455T>C polymorphisms and coronary heart disease (CHD). PubMed, Ovid, Cochrane Library, Embase, China National Knowledge Infrastructure, and Wanfang databases were searched using combinations of keywords relating to these polymorphisms and CHD. Studies retrieved from database searches were screened using our stringent inclusion and exclusion criteria, and Comprehensive Meta-Analysis Version 2.0 software was used for statistical analyses. In total, 115 studies were initially retrieved and after further selection, 11 were included in the meta-analysis. These 11 articles comprised 4840 patients with CHD in the case group and 4913 healthy participants in the control group. Meta-analysis revealed that APOA5 -1131T>C and APOC3 -455T>C polymorphisms increased CHD risk. In addition, subgroup analysis by ethnicity showed that while the -1131T>C polymorphism elevated the risk of CHD in the Caucasian population under both allelic and dominant models, this increased risk was observed only under a dominant model in the Asian population. The results of our meta-analysis point to a strong link between both APOA5 -1131T>C and APOC3 -455T>C polymorphisms and an increased risk of CHD. Thus, these polymorphisms constitute important predictive indicators of CHD susceptibility. Show less
no PDF DOI: 10.4238/2015.December.23.9
APOA5
Qianxi Fu, Xiaojun Tang, Juan Chen +5 more · 2015 · PloS one · PLOS · added 2026-04-24
Recent genome-wide association studies have identified several loci influencing lipid levels. The present study focused on the triglycerides (TG)-associated locus, the APOA4-APOA5-ZNF259-BUD13 gene cl Show more
Recent genome-wide association studies have identified several loci influencing lipid levels. The present study focused on the triglycerides (TG)-associated locus, the APOA4-APOA5-ZNF259-BUD13 gene cluster on chromosome 11, to explore the role of genetic variants in this gene cluster in the development of increasing TG levels and coronary heart disease (CHD). Six single nucleotide polymorphisms (SNPs), rs4417316, rs651821, rs6589566, rs7396835, rs964184 and rs17119975, in the APOA4-APOA5-ZNF259-BUD13 gene cluster were selected and genotyped in 5374 healthy Chinese subjects. There were strong significant associations between the six SNPs and TG levels (P < 1.0 × 10(-8)). Moreover, a weighted genotype score was found to be associated with TG levels (P = 3.28 × 10(-13)). The frequencies of three common haplotypes were observed to be significantly different between the high TG group and the low TG group (P < 0.05). However, no significant effects were found for the SNPs regarding susceptibility to CHD in the Chinese case-control populations. This study highlights the genotypes, genotype scores and haplotypes of the APOA4-APOA5-ZNF259-BUD13 gene cluster that were associated with TG levels in a Chinese population; however, the genetic variants in this gene cluster did not increase the risk of CHD in the Chinese population. Show less
📄 PDF DOI: 10.1371/journal.pone.0138652
APOA4
Yong Du, Shu-Mei Yan, Wan-Yi Gu +9 more · 2015 · Asian Pacific journal of cancer prevention : APJCP · added 2026-04-24
FADS1 (fatty acid desaturase 1) plays a crucial role in fatty acid metabolism, and it was recently reported to be involved in tumorigenesis. However, the role of FADS1 expression in esophageal squamou Show more
FADS1 (fatty acid desaturase 1) plays a crucial role in fatty acid metabolism, and it was recently reported to be involved in tumorigenesis. However, the role of FADS1 expression in esophageal squamous cell carcinoma (ESCC) remains unknown. In the current study, we investigated the expression and clinical pathologic and prognostic significance of FADS1 in ESCC. Immunohistochemical analyses revealed that 58.2% (146/251) of the ESCC tissues had low levels of FADS1 expression, whereas 41.8% (105/251) exhibited high levels of FADS1 expression. In positive cases, FADS1 expression was detected in the cytoplasm of cells. Correlation analyses demonstrated that FADS1 expression was significantly correlated with tumor location (p=0.025) but not with age, gender, histological grade, tumor status, nodal status or TNM staging. Furthermore, patients with tumors expressing high levels of FADS1had a longer disease-free survival time (p<0.001) and overall survival time (p<0.001). Univariate and multivariate analyses revealed that, along with nodal status, FADS1 expression was an independent and significant predictive factor (p<0.001). In conclusion, our study suggested that FADS1 might be a valuable biomarker and potential therapeutic target for ESCC. Show less
no PDF DOI: 10.7314/apjcp.2015.16.12.5089
FADS1
Xiaguang Chen, Cunshuan Xu · 2015 · Cell journal · added 2026-04-24
To investigate the transdifferentiation relationship between eight types of liver cell during rat liver regeneration (LR). 114 healthy Sprague-Dawley (SD) rats were used in this experimental study. Ei Show more
To investigate the transdifferentiation relationship between eight types of liver cell during rat liver regeneration (LR). 114 healthy Sprague-Dawley (SD) rats were used in this experimental study. Eight types of liver cell were isolated and purified with percoll density gradient centrifugation and immunomagentic bead methods. Marker genes for eight types of cell were obtained by retrieving the relevant references and databases. Expression changes of markers for each cell of the eight cell types were measured using microarray. The relationships between the expression profiles of marker genes and transdifferentiation among liver cells were analyzed using bioinformatics. Liver cell transdifferentiation was predicted by comparing expression profiles of marker genes in different liver cells. During LR hepatocytes (HCs) not only express hepatic oval cells (HOC) markers (including PROM1, KRT14 and LY6E), but also express biliary epithelial cell (BEC) markers (including KRT7 and KRT19); BECs express both HOC markers (including GABRP, PCNA and THY1) and HC markers such as CPS1, TAT, KRT8 and KRT18; both HC markers (KRT18, KRT8 and WT1) and BEC markers (KRT7 and KRT19) were detected in HOCs. Additionally, some HC markers were also significantly upregulated in hepatic stellate cells ( HSCs), sinusoidal endothelial cells (SECs) , Kupffer cells (KCs) and dendritic cells (DCs), mainly at 6-72 hours post partial hepatectomy (PH). Our findings indicate that there is a mutual transdifferentiation relationship between HC, BEC and HOC during LR, and a tendency for HSCs, SECs, KCs and DCs to transdifferentiate into HCs. Show less
📄 PDF DOI: 10.22074/cellj.2016.3756
CPS1
YongPing Chen, Bei Cao, Jing Yang +6 more · 2015 · Journal of neurology · Springer · added 2026-04-24
Whether polymorphisms rs11856808 and rs9652490 of the Leucine-rich repeat and Ig domain containing, Nogo receptor-interacting protein-1 (LINGO1) gene, as well as rs10968280, rs13362909 and rs7033345 o Show more
Whether polymorphisms rs11856808 and rs9652490 of the Leucine-rich repeat and Ig domain containing, Nogo receptor-interacting protein-1 (LINGO1) gene, as well as rs10968280, rs13362909 and rs7033345 of the LINGO2 gene, increase the risk for Parkinson's disease (PD) is controversial. Considering the overlap of the clinical and pathological characteristics among PD and multiple system atrophy (MSA), we explored the associations between these five polymorphisms and PD and MSA in a Chinese population. A total of 1055 PD patients, 320 MSA patients, and 810 healthy controls (HCs) were genotyped for these five polymorphisms in LINGO1 and LINGO 2 using Sequenom iPLEX Assay technology. Moreover, after combining our results with available published data, a meta-analysis was conducted to investigate the associations between LINGO 1 rs11856808 and rs9652490 and the risk of PD. The frequency of the minor alleles "T" of LINGO1 rs11856808 was significantly lower in PD than that in HCs (p = 0.011, OR 0.89, 95 % CI 0.81-0.97), but not in MSA. Moreover, there were no significant differences in the minor allele frequency distributions of the other four polymorphisms between PD and HCs, and between MSA and HCs. The meta-analysis showed a lack of association of rs9652490 and PD, regardless of the genetic model or ethnic origin. However, the rs11856808 allele decreased the risk of PD in patients of Asian origin in a dominant genetic model. Our findings suggest that rs11856808 plays a protective role by decreasing the risk for PD, but not for MSA, in Asian population, the other four polymorphisms do not contribute to the risk for PD and MSA. Show less
no PDF DOI: 10.1007/s00415-015-7870-9
LINGO1
Xiao-Li Xie, Xi Nie, Jun Wu +10 more · 2015 · Journal of molecular medicine (Berlin, Germany) · Springer · added 2026-04-24
Smooth muscle 22α (SM22α) is involved in stress fiber formation and enhances contractility in vascular smooth muscle cells (VSMCs). In many cases, SM22α acts as an adapter protein to assemble signalin Show more
Smooth muscle 22α (SM22α) is involved in stress fiber formation and enhances contractility in vascular smooth muscle cells (VSMCs). In many cases, SM22α acts as an adapter protein to assemble signaling complexes and regulate signaling, but whether SM22α regulates contractile signaling induced by angiotensin II (AngII) remains unclear. To address this issue, we established a hypertension model of Sm22α(-/-) mice, and demonstrated that hypertension induced by AngII was attenuated in Sm22α(-/-) mice. A decreased vasoconstriction was observed in aortic rings from Sm22α(-/-) mice. Furthermore, loss of SM22α resulted in a reduced contractile response to AngII in VSMCs in vitro. The phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2) induced by AngII was impaired following depletion of SM22α, in parallel with a reduced contractility. The decay of ERK1/2 activity was associated with increased expression of mitogen-activated protein kinase phosphatase 3 (MKP3). Inhibition of MKP3 activity rescued ERK1/2 activity. SM22α depletion caused an enhanced interaction of MKP3 with ERK1/2, and a reduced ubiquitination and degradation of MKP3. Knockdown of SM22α extended the half-life of MKP3. In conclusion, SM22α promotes AngII-induced contraction by maintenance of ERK1/2 signaling cascades through facilitating ubiquitination and degradation of MKP3. The vasoconstriction is attenuated in aortic rings from Sm22α(-/-) mice. MKP3 mediates dephosphorylation of ERK1/2 in AngII-induced VSMC contraction. SM22α inhibits the interaction of ERK1/2 with MKP3. SM22α promotes ubiquitination and degradation of MKP3. SM22α facilitates AngII-induced contraction by maintenance of ERK1/2 signaling. Show less
no PDF DOI: 10.1007/s00109-014-1240-4
DUSP6
Yantao Lv, Wutai Guan, Hanzhen Qiao +4 more · 2015 · Omics : a journal of integrative biology · added 2026-04-24
Mammalian milk is a key source of lipids, providing not only important calories but also essential fatty acids. Veterinary medicine and omics systems sciences intersection, termed as "veterinomics" he Show more
Mammalian milk is a key source of lipids, providing not only important calories but also essential fatty acids. Veterinary medicine and omics systems sciences intersection, termed as "veterinomics" here, has received little attention to date but stands to offer much promise for building bridges between human and animal health. We determined the changes in porcine mammary genes and proteomics expression associated with milk triacylglycerol (TAG) synthesis and secretion from late pregnancy to lactation. TAG content and fatty acid (FA) composition were determined in porcine colostrum (the 1st day of lactation) and milk (the 17th day of lactation). The mammary transcriptome for 70 genes and 13 proteins involved in TAG synthesis and secretion from six sows, each at d -17(late pregnancy), d 1(early lactation), and d 17 (peak lactation) relative to parturition were analyzed using quantitative real-time PCR and Western blot analyses. The TAG content and the concentrations of de novo synthesized FAs, saturated FAs, and monounsaturated FAs were higher in milk than in colostrum (p<0.05). Robust upregulation with high relative mRNA abundance was evident during lactation for genes associated with FA uptake (VLDLR, LPL, CD36), FA activation (ACSS2, ACSL3), and intracellar transport (FABP3), de novo FA synthesis (ACACA, FASN), FA elongation (ELOVL1), FA desaturation (SCD, FADS1), TAG synthesis (GPAM, AGPAT1, LPIN1, DGAT1), lipid droplet formation (BTN2A1, XDH, PLIN2), and transcription factors and nuclear receptors (SREBP1, SCAP, INSIG1/2). In conclusion, a wide variety of lipogenic genes and proteins regulate the channeling of FAs towards milk TAG synthesis and secretion in porcine mammary gland tissue. These findings inform future omics strategies to increase milk fat production and lipid profile and attest to the rise of both veterinomics and lipidomics in postgenomics life sciences. Show less
no PDF DOI: 10.1089/omi.2015.0102
FADS1
Wei Chen, John M Brehm, Ani Manichaikul +20 more · 2015 · Annals of the American Thoracic Society · added 2026-04-24
Genome-wide association studies (GWAS) of chronic obstructive pulmonary disease (COPD) have identified disease-susceptibility loci, mostly in subjects of European descent. We hypothesized that by stud Show more
Genome-wide association studies (GWAS) of chronic obstructive pulmonary disease (COPD) have identified disease-susceptibility loci, mostly in subjects of European descent. We hypothesized that by studying Hispanic populations we would be able to identify unique loci that contribute to COPD pathogenesis in Hispanics but remain undetected in GWAS of non-Hispanic populations. We conducted a metaanalysis of two GWAS of COPD in independent cohorts of Hispanics in Costa Rica and the United States (Multi-Ethnic Study of Atherosclerosis [MESA]). We performed a replication study of the top single-nucleotide polymorphisms in an independent Hispanic cohort in New Mexico (the Lovelace Smokers Cohort). We also attempted to replicate prior findings from genome-wide studies in non-Hispanic populations in Hispanic cohorts. We found no genome-wide significant association with COPD in our metaanalysis of Costa Rica and MESA. After combining the top results from this metaanalysis with those from our replication study in the Lovelace Smokers Cohort, we identified two single-nucleotide polymorphisms approaching genome-wide significance for an association with COPD. The first (rs858249, combined P value = 6.1 × 10(-8)) is near the genes KLHL7 and NUPL2 on chromosome 7. The second (rs286499, combined P value = 8.4 × 10(-8)) is located in an intron of DLG2. The two most significant single-nucleotide polymorphisms in FAM13A from a previous genome-wide study in non-Hispanics were associated with COPD in Hispanics. We have identified two novel loci (in or near the genes KLHL7/NUPL2 and DLG2) that may play a role in COPD pathogenesis in Hispanic populations. Show less
no PDF DOI: 10.1513/AnnalsATS.201408-380OC
DLG2
Wei Wu, Chao-Xia Lu, Yi-Ning Wang +7 more · 2015 · Journal of the American Heart Association · added 2026-04-24
MYBPC3 dysfunctions have been proven to induce dilated cardiomyopathy, hypertrophic cardiomyopathy, and/or left ventricular noncompaction; however, the genotype-phenotype correlation between MYBPC3 an Show more
MYBPC3 dysfunctions have been proven to induce dilated cardiomyopathy, hypertrophic cardiomyopathy, and/or left ventricular noncompaction; however, the genotype-phenotype correlation between MYBPC3 and restrictive cardiomyopathy (RCM) has not been established. The newly developed next-generation sequencing method is capable of broad genomic DNA sequencing with high throughput and can help explore novel correlations between genetic variants and cardiomyopathies. A proband from a multigenerational family with 3 live patients and 1 unrelated patient with clinical diagnoses of RCM underwent a next-generation sequencing workflow based on a custom AmpliSeq panel, including 64 candidate pathogenic genes for cardiomyopathies, on the Ion Personal Genome Machine high-throughput sequencing benchtop instrument. The selected panel contained a total of 64 genes that were reportedly associated with inherited cardiomyopathies. All patients fulfilled strict criteria for RCM with clinical characteristics, echocardiography, and/or cardiac magnetic resonance findings. The multigenerational family with 3 adult RCM patients carried an identical nonsense MYBPC3 mutation, and the unrelated patient carried a missense mutation in the MYBPC3 gene. All of these results were confirmed by the Sanger sequencing method. This study demonstrated that MYBPC3 gene mutations, revealed by next-generation sequencing, were associated with familial and sporadic RCM patients. It is suggested that the next-generation sequencing platform with a selected panel provides a highly efficient approach for molecular diagnosis of hereditary and idiopathic RCM and helps build new genotype-phenotype correlations. Show less
no PDF DOI: 10.1161/JAHA.115.001879
MYBPC3
Hui-Ying Liu, Hai-Hua Qian, Xiao-Feng Zhang +6 more · 2015 · World journal of gastroenterology · added 2026-04-24
To improve an asialoglycoprotein receptor (ASGPR)-based enrichment method for detection of circulating tumor cells (CTCs) of hepatocellular carcinoma (HCC). Peripheral blood samples were collected fro Show more
To improve an asialoglycoprotein receptor (ASGPR)-based enrichment method for detection of circulating tumor cells (CTCs) of hepatocellular carcinoma (HCC). Peripheral blood samples were collected from healthy subjects, patients with HCC or various other cancers, and patients with hepatic lesions or hepatitis. CTCs were enriched from whole blood by extracting CD45-expressing leukocytes with monoclonal antibody coated-beads following density gradient centrifugation. The remaining cells were cytocentrifuged on polylysine-coated slides. Isolated cells were treated by triple immunofluorescence staining with CD45 antibody and a combination of antibodies against ASGPR and carbamoyl phosphate synthetase 1 (CPS1), used as liver-specific markers, and costained with DAPI. The cell slide was imaged and stained tumor cells that met preset criteria were counted. Recovery, sensitivity and specificity of the detection methods were determined and compared by spiking experiments with various types of cultured human tumor cell lines. Expression of ASGPR and CPS1 in cultured tumor cells and tumor tissue specimens was analyzed by flow cytometry and triple immunofluorescence staining, respectively. CD45 depletion of leukocytes resulted in a significantly greater recovery of multiple amounts of spiked HCC cells than the ASGPR(+) selection (Ps < 0.05). The expression rates of either ASGPR or CPS1 were different in various liver cancer cell lines, ranging between 18% and 99% for ASGPR and between 9% and 98% for CPS1. In both human HCC tissues and liver cancer cell lines, there were a few HCC cells that did not stain positive for ASGPR or CPS1. The mixture of monoclonal antibodies against ASGPR and CPS1 identified more HCC cells than either antibody alone. However, these antibodies did not detect any tumor cells in blood samples spiked with the human breast cancer cell line MCF-7 and the human renal cancer cell line A498. ASGPR(+) or/and CPS1(+) CTCs were detected in 29/32 (91%) patients with HCC, but not in patients with any other kind of cancer or any of the other test subjects. Furthermore, the improved method detected a higher CTC count in all patients examined than did the previous method (P = 0.001), and consistently achieved 12%-21% higher sensitivity of CTC detection in all seven HCC patients with more than 40 CTCs. Negative depletion enrichment combined with identification using a mixture of antibodies against ASGPR and CPS1 improves sensitivity and specificity for detecting circulating HCC cells. Show less
no PDF DOI: 10.3748/wjg.v21.i10.2918
CPS1
Neil R Adames, P Logan Schuck, Katherine C Chen +3 more · 2015 · Molecular biology of the cell · American Society for Cell Biology · added 2026-04-24
The cell cycle is composed of bistable molecular switches that govern the transitions between gap phases (G1 and G2) and the phases in which DNA is replicated (S) and partitioned between daughter cell Show more
The cell cycle is composed of bistable molecular switches that govern the transitions between gap phases (G1 and G2) and the phases in which DNA is replicated (S) and partitioned between daughter cells (M). Many molecular details of the budding yeast G1-S transition (Start) have been elucidated in recent years, especially with regard to its switch-like behavior due to positive feedback mechanisms. These results led us to reevaluate and expand a previous mathematical model of the yeast cell cycle. The new model incorporates Whi3 inhibition of Cln3 activity, Whi5 inhibition of SBF and MBF transcription factors, and feedback inhibition of Whi5 by G1-S cyclins. We tested the accuracy of the model by simulating various mutants not described in the literature. We then constructed these novel mutant strains and compared their observed phenotypes to the model's simulations. The experimental results reported here led to further changes of the model, which will be fully described in a later article. Our study demonstrates the advantages of combining model design, simulation, and testing in a coordinated effort to better understand a complex biological network. Show less
📄 PDF DOI: 10.1091/mbc.E15-06-0358
CLN3
Fei Xue, Rui Shen, Xianzhen Chen · 2015 · Tumori · added 2026-04-24
To explore the potential molecular mechanisms involved in migratory glioma cells. The gene expression profiles of GSE28167, employing human malignant glioma U251MG cells cultured on strictly aligned v Show more
To explore the potential molecular mechanisms involved in migratory glioma cells. The gene expression profiles of GSE28167, employing human malignant glioma U251MG cells cultured on strictly aligned versus randomly oriented electrospun nanofibers of polycaprolactone, were downloaded from the Gene Expression Omnibus database. Gene differential expression analysis was carried out by the package of Gene Expression Omnibus query and limma in R language. The Gene Set Analysis Toolkit V2 was used for pathway analysis. Gene set enrichment analysis was used to screen for target sites of transcription factors, miRNA and small drug molecules. Totally 586 differentially expressed genes were identified and the differentially expressed genes were mainly enriched in the pathway of muscle cell TarBase, MAPK cascade, adipogenesis and epithelium TarBase. Thirty-two significant target sites of transcription factors, such as hsa_RTAAACA_V$FREAC2₀₁, were screened. The top 20 potential miRNAs including MIR-124A, MIR-34A and MIR-34C were screened for a constructing gene-miRNA interaction network. Small molecules that can inhibit the motility of glioma cells such as diclofenamide and valinomycin were mined. By integrating the regulatory relationships among transcription factors, miRNAs and differentially expressed genes, we found that 7 differentially expressed genes, including SOX4, ANKRD28 and CCND1, might play crucial roles in the migration of glioma cells. The screened migration-associated genes, significant pathways, and small molecules give us new insight for the mechanism of migratory glioma cells. Interest in such genes as potential target genes in the treatment of glioblastoma justifies functional validation studies. Show less
no PDF DOI: 10.5301/tj.5000226
ANKRD28
H Sun, E S Calipari, T J R Beveridge +2 more · 2015 · Neuroscience · Elsevier · added 2026-04-24
Persistent neuroadaptations following chronic psychostimulant exposure include reduced striatal dopamine D2 receptor (D2R) levels. The signaling of D2Rs is initiated by Gαi/o proteins and terminated b Show more
Persistent neuroadaptations following chronic psychostimulant exposure include reduced striatal dopamine D2 receptor (D2R) levels. The signaling of D2Rs is initiated by Gαi/o proteins and terminated by regulator of G protein signaling (RGS) proteins. The purpose of this study is to examine the association of the drug taking behavior and gene expression profile of D2/D3Rs, and their associated signaling proteins in the ventral tegmental area (VTA) and nucleus accumbens (NAc) using a rodent model of amphetamine (AMPH) self-administration. Rats were allowed to self-administer AMPH (0.187 mg/kg/infusion for a maximum of 40 injections in 6h daily sessions) for 5 days during which rats showed an escalated rate of AMPH intake across days. AMPH self-administration induced profound brain region-dependent alterations of the targeted genes. There was a positive correlation of the messenger ribonucleic acid (mRNA) levels of RGS10 between the VTA and the NAc in the control animals, which was abolished by AMPH self-administration. AMPH self-administration also produced a negative correlation of the mRNA levels of RGS7 and RGS19 between the two brain regions, which was not present in the control group. Furthermore, AMPH taking behavior was associated with changes in certain gene expression levels. The mRNA levels of RGS2 and RGS4 in both the VTA and NAc were positively correlated with the rate of AMPH intake. Additionally, the rate of AMPH intake was also positively correlated with RGS10 and negatively correlated with RGS17 and the short form of D2Rs mRNA level in the VTA. Although there were significant changes in the mRNA levels of RGS7 and RGS8 in the NAc, none of these measures were correlated with the rate of AMPH intake. The present study suggested that short-term AMPH self-administration produced pronounced changes in the VTA that were more associated with AMPH taking behavior than changes in the NAc. Show less
no PDF DOI: 10.1016/j.neuroscience.2015.08.053
RGS17
Wei Shang, Xuejing Yu, Honglian Wang +7 more · 2015 · Molecular medicine reports · added 2026-04-24
Fibroblast growth factor 21 (FGF21) is a novel metabolic regulator. The present study aimed to investigate the effect of FGF21 on cholesterol efflux and the expression of ATP binding cassette (ABC) A1 Show more
Fibroblast growth factor 21 (FGF21) is a novel metabolic regulator. The present study aimed to investigate the effect of FGF21 on cholesterol efflux and the expression of ATP binding cassette (ABC) A1 and G1 in human THP-1 macrophage-derived foam cells. Furthermore, the present study aimed to investigate the role of the liver X receptor (LXR) α in this process. A model of oxidized low-density lipoprotein-induced foam cells from human THP-1 cells was established. The effect of FGF21 on cholesterol efflux was analyzed using a liquid scintillation counter. The expression of ABCA1 and ABCG1 was determined using quantitative polymerase chain reaction and western blot analyses. FGF21 was found to enhance apolipoprotein A1- and high-density lipoprotein-mediated cholesterol efflux. FGF21 was also observed to increase the mRNA and protein expression of ABCA1 and ABCG1. Furthermore, LXRα-short interfering RNA attenuated the stimulatory effects induced by FGF21. These findings suggest that FGF21 may have a protective effect against atherosclerosis by enhancing cholesterol efflux through the induction of LXRα-dependent ABCA1 and ABCG1 expression. Show less
no PDF DOI: 10.3892/mmr.2014.2731
NR1H3
C H Li, Y Gao, S Wang +7 more · 2015 · Genetics and molecular research : GMR · added 2026-04-24
Cell reprogramming mediated by histone methylation and demethylation is crucial for the activation of the embryonic genome in early embryonic development. In this study, we employed quantitative real- Show more
Cell reprogramming mediated by histone methylation and demethylation is crucial for the activation of the embryonic genome in early embryonic development. In this study, we employed quantitative real-time polymerase chain reaction (qRT-PCR) to detect mRNA levels and expression patterns of all known histone demethylases in early germinal vesicle stage and in vitro-matured metaphase II (MII) oocytes (which are commonly used as donor cells for nuclear transfer). On screening, the Jumonji domain containing 1C (JMJD1C) gene had the highest level of expression and hence was used for subsequent experiments. We also found that JMJD1C was primarily expressed in the nucleus and showed relatively high levels of expression at the 2-cell, 4-cell, 8-cell, 16-cell, morula, and blastocyst stages of embryos developed from MII oocytes fertilized in vitro. Further, we knocked down the JMJD1C gene in MII oocytes using siRNA and monitored the cleavage of zygotes and development of early embryos after in vitro fertilization. The results showed that the zygote cleavage and blastocyst rates of the transfection group were reduced by 57.1 ± 0.07 and 50 ± 0.01% respectively, which were significantly lower than those of the negative control group (P < 0.05). These data suggest that JMJD1C plays a key role in the normal development of early bovine embryos. Our results also provide a theoretical basis for the investigation of the role and molecular mechanism of histone demethylation in the early development of bovine embryos. Show less
no PDF DOI: 10.4238/2015.December.23.12
JMJD1C
Qian Yang, Rui-Xing Yin, Xiao-Li Cao +3 more · 2015 · International journal of clinical and experimental pathology · added 2026-04-24
Little is known about the association of the FADS1/FADS2 SNPs and serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese southern population. The pres Show more
Little is known about the association of the FADS1/FADS2 SNPs and serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese southern population. The present study aimed to determine such association in the Chinese southern population. A total of 1,669 unrelated subjects (CAD, 534; IS, 553; and healthy controls, 582) were recruited in the study. Genotypes of the FADS1 rs174546 SNP and the FADS2 rs174601 SNP were determined by the SNaPshot Multiplex Kit. The T allele and TT genotype frequencies of the two SNPs were predominant in our study population. The T alleles were associated with increased risk of CAD and IS. Correspondingly, the C alleles were associated with reduced risk of CAD and IS. Haplotype analyses showed that the haplotype of T-T (rs174546-rs174601) was associated with an increased risk for IS, and the haplotype of C-C (rs174546-rs174601) was associated with a reduced risk for CAD and IS. The two SNPs were likely to influence serum lipid levels. The T allele carriers of the two SNPs and rs174601 TT genotype were associated with decreased serum HDL-C and ApoAI levels in the patient groups and with an increased risk of CAD and IS. The present study suggests that the FADS1 rs174546 SNP and the FADS2 rs174601 SNP are associated with the risk of CAD and IS, and are likely to influence serum lipid levels. However, further functional studies are needed to clarify how the two SNPs actually affect serum lipid levels and the risk of CAD and IS. Show less
no PDF
FADS1
Zhengyan Yang, Liang Guo, Dan Liu +8 more · 2015 · Oncotarget · Impact Journals · added 2026-04-24
In the present study, we demonstrate that prolonged treatment by trastuzumab induced resistance of NCI-N87 gastric cancer cells to trastuzumab. The resistant cells possessed typical characteristics of Show more
In the present study, we demonstrate that prolonged treatment by trastuzumab induced resistance of NCI-N87 gastric cancer cells to trastuzumab. The resistant cells possessed typical characteristics of epithelial to mesenchymal transition (EMT)/cancer stem cells and acquired more invasive and metastatic potentials both in vitro and in vivo. Long term treatment with trastuzumab dramatically inhibited the phosphorylation of Akt, but triggered the activation of STAT3. The level of IL-6 was remarkably increased, implicating that the release of IL-6 that drives the STAT3 activation initiates the survival signaling transition. Furthermore, the Notch activities were significantly enhanced in the resistant cells, companied by upregulation of the Notch ligand Jagged-1 and the Notch responsive genes Hey1 and Hey2. Inhibiting the endogenous Notch pathway reduced the IL-6 expression and restored the sensitivities of the resistant cells to trastuzumab. Blocking of the STAT3 signaling abrogated IL-6-induced Jagged-1 expression, effectively inhibited the growth of the trastuzumab resistant cells, and enhanced the anti-tumor activities of trastuzumab in the resistant cells. These findings implicate that the IL-6/STAT3/Jagged-1/Notch axis may be a useful target and that combination of the Notch or STAT3 inhibitors with trastuzumab may prevent or delay clinical resistance and improve the efficacy of trastuzumab in gastric cancer. Show less
📄 PDF DOI: 10.18632/oncotarget.3241
HEY2
Wenyuan Zhao, Tieqiang Zhao, Yuanjian Chen +6 more · 2015 · PloS one · PLOS · added 2026-04-24
Familial hypertrophic cardiomyopathy (HCM) is attributed to mutations in genes that encode for the sarcomere proteins, especially Mybpc3 and Myh7. Genotype-phenotype correlation studies show significa Show more
Familial hypertrophic cardiomyopathy (HCM) is attributed to mutations in genes that encode for the sarcomere proteins, especially Mybpc3 and Myh7. Genotype-phenotype correlation studies show significant variability in HCM phenotypes among affected individuals with identical causal mutations. Morphological changes and clinical expression of HCM are the result of interactions with modifier genes. With the exceptions of angiotensin converting enzyme, these modifiers have not been identified. Although mouse models have been used to investigate the genetics of many complex diseases, natural murine models for HCM are still lacking. In this study we show that the DBA/2J (D2) strain of mouse has sequence variants in Mybpc3 and Myh7, relative to widely used C57BL/6J (B6) reference strain and the key features of human HCM. Four-month-old of male D2 mice exhibit hallmarks of HCM including increased heart weight and cardiomyocyte size relative to B6 mice, as well as elevated markers for cardiac hypertrophy including β-myosin heavy chain (MHC), atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), and skeletal muscle alpha actin (α1-actin). Furthermore, cardiac interstitial fibrosis, another feature of HCM, is also evident in the D2 strain, and is accompanied by up-regulation of type I collagen and α-smooth muscle actin (SMA)-markers of fibrosis. Of great interest, blood pressure and cardiac function are within the normal range in the D2 strain, demonstrating that cardiac hypertrophy and fibrosis are not secondary to hypertension, myocardial infarction, or heart failure. Because D2 and B6 strains have been used to generate a large family of recombinant inbred strains, the BXD cohort, the D2 model can be effectively exploited for in-depth genetic analysis of HCM susceptibility and modifier screens. Show less
no PDF DOI: 10.1371/journal.pone.0133132
MYBPC3
Mingxiang Kong, L I Cao, Qiong Zhang +7 more · 2015 · Oncology letters · added 2026-04-24
Hereditary multiple osteochondromas (HMO) is an autosomal dominant bone disorder characterised by the presence of multiple benign cartilage-capped tumours. Exostosin-1 (EXT1) and EXT2 are the major mo Show more
Hereditary multiple osteochondromas (HMO) is an autosomal dominant bone disorder characterised by the presence of multiple benign cartilage-capped tumours. Exostosin-1 (EXT1) and EXT2 are the major morbigenous genes associated with HMO, mutations in which are responsible for 90% of all HMO cases. In patients with HMO, osteochondromas arise adjacent to the metaphysis and typically remain in the metaphyseal region of the long bones. Therefore, it is rare for osteochondromas to be identified intra-articularly, although they may manifest as loose bodies. The present study describes a rare case of HMO manifesting as limited flexing range in the right knee joint of a 27-year-old male patient. Computed tomography and magnetic resonance imaging (MRI) revealed three intra-articular osteochondromas located in the intercondylar fossa of the patient's right knee. The intra-articular osteochondromas and protuberant extra-articular osteochondromas around the right knee were resected, resulting in improved right knee function and no postoperative recurrence. Pathological analysis revealed that the intra-articular osteochondromas had a thinner cartilage cap layer than the extra-articular osteochondromas. In addition, genetic analysis of the patient and the patient's mother was conducted. From this, it was determined that a nonsense mutation, c.115G>T (p.E39X) in exon 1 of the EXT1 gene, was the cause of HMO in this case. Thus, it is proposed that osteochondromas with a pedicle within the knee, may tear and become loose intra-articular bodies, resulting in limited joint function and thereby contributing to the progression of HMO. Show less
no PDF DOI: 10.3892/ol.2015.3284
EXT1