👤 Xiao-ping 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, 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, 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
Huanhuan Liu, Long Yang, Erchen Zhang +11 more · 2017 · Acta biomaterialia · Elsevier · added 2026-04-24
Management of ligament/tendon-to-bone-junction healing remains a formidable challenge in the field of orthopedic medicine to date, due to deficient vascularity and multi-tissue transitional structure Show more
Management of ligament/tendon-to-bone-junction healing remains a formidable challenge in the field of orthopedic medicine to date, due to deficient vascularity and multi-tissue transitional structure of the junction. Numerous strategies have been employed to improve ligament-bone junction healing, including delivery of stem cells, bioactive factors, and synthetic materials, but these methods are often inadequate at recapitulating the complex structure-function relationships at native tissue interfaces. Here, we developed an easily-fabricated and effective biomimetic composite to promote the regeneration of ligament-bone junction by physically modifying the tendon extracellular matrix (ECM) into a Random-Aligned-Random composite using ultrasound treatment. The differentiation potential of rabbit bone marrow stromal cells on the modified ECM were examined in vitro. The results demonstrated that the modified ECM enhanced expression of chondrogenesis and osteogenesis-associated epigenetic genes (Jmjd1c, Kdm6b), transcription factor genes (Sox9, Runx2) and extracellular matrix genes (Col2a1, Ocn), resulting in higher osteoinductivity than the untreated tendon ECM in vitro. In the rabbit anterior cruciate ligament (ACL) reconstruction model in vivo, micro-computed tomography (Micro-CT) and histological analysis showed that the modified Random-Aligned-Random composite scaffold enhanced bone and fibrocartilage formation at the interface, more efficaciously than the unmodified tendon ECM. Therefore, these results demonstrated that the biomimetic Random-Aligned-Random composite could be a promising scaffold for ligament/tendon-bone junction repair. The native transitional region consists of several distinct yet contiguous tissue regions, composed of soft tissue, non-calcified fibrocartilage, calcified fibrocartilage, and bone. A stratified graft whose phases are interconnected with each other is essential for supporting the formation of functionally continuous multi-tissue regions. Various techniques have been attempted to improve adherence of the ligament/tendon graft to bone, including utilization of stem cells, growth factors and biomaterials, but these methods are often inadequate at recapitulating the complex structure-function relationships at native tissue interfaces. Here, we developed an easily-fabricated and effective biomimetic composite to promote the regeneration of ligament-bone junction by physically modifying the tendon extracellular matrix (ECM) into a Random-Aligned-Random composite using ultrasound treatment. The modified ECM enhanced expression of chondrogenesis and osteogenesis-associated epigenetic genes expression in vitro. In the rabbit anterior crucial ligament reconstruction model in vivo, results showed that the modified Random-Aligned-Random composite enhances the bone and fibrocartilage formation in the interface, proving to be more efficient than the unmodified tendon ECM. Therefore, these results demonstrated that the biomimetic Random-Aligned-Random composite could be a promising scaffold for ligament/tendon-bone junction repair. Show less
no PDF DOI: 10.1016/j.actbio.2017.05.027
JMJD1C
Yimin Zhu, DanDan Zhang, Dan Zhou +31 more · 2017 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
Metabolic syndrome (MetS), a cluster of metabolic disturbances that increase the risk for cardiovascular disease and diabetes, was because of genetic susceptibility and environmental risk factors. To Show more
Metabolic syndrome (MetS), a cluster of metabolic disturbances that increase the risk for cardiovascular disease and diabetes, was because of genetic susceptibility and environmental risk factors. To identify the genetic variants associated with MetS and metabolic components, we conducted a genome-wide association study followed by replications in totally 12,720 participants from the north, north-eastern and eastern China. In combined analyses, independent of the top known signal at rs651821 on APOA5, we newly identified a secondary triglyceride-associated signal at rs180326 on BUD13 (P Show less
📄 PDF DOI: 10.1111/jcmm.13042
APOA5
Meng-Chuan Huang, Wen-Tsan Chang, Hsin-Yu Chang +5 more · 2017 · International journal of environmental research and public health · MDPI · added 2026-04-24
Polyunsaturated fatty acids (PUFA) correlate with risk of dyslipidemia and cardiovascular diseases. Fatty acid desaturase (
📄 PDF DOI: 10.3390/ijerph14060572
FADS1
Qi Xiong, Jianlin Chen, Fei-Lin Li +8 more · 2017 · Scientific reports · Nature · added 2026-04-24
To develop a cost-effective molecular regulator to improve growth metabolism and immunity of animals, a recombinant plasmid co-expressing fatty acid desaturase (mFat-1) and pig insulin growth like fac Show more
To develop a cost-effective molecular regulator to improve growth metabolism and immunity of animals, a recombinant plasmid co-expressing fatty acid desaturase (mFat-1) and pig insulin growth like factor 1 (IGF-1) genes was constructed by the 2 A self-cleavage technique. After entrapment within modified chitosan nanoparticles (chitosan modified with polyethyleneglycol-polyethylenimine, CPP), the recombinant plasmid was injected intramuscularly into mice. Compared with controls, co-expression of mFat-1 and IGF-1 significantly raised the level of serum IGF-1, and increased the liver and muscle docosa hexaenoic acid (DHA) content. Th and Tc cell levels were also elevated, as were expression levels of serum IL-4 and IL-6 genes. These results demonstrate that the immunity and metabolism of an animal can be effectively improved by co-expression of mFat-1 and IGF-1 genes in vivo, which may contribute to further development of novel immunomodulators with beneficial effects on growth metabolism and immunity. Show less
📄 PDF DOI: 10.1038/s41598-017-17341-x
FADS1
Fa Chen, Tao Lin, Lingjun Yan +8 more · 2017 · Oncotarget · Impact Journals · added 2026-04-24
The aim of this study was to investigate the independent and combined effects of fatty acid desaturase 1 (FADS1) gene polymorphism and fish consumption on oral cancer. A hospital-based case-control st Show more
The aim of this study was to investigate the independent and combined effects of fatty acid desaturase 1 (FADS1) gene polymorphism and fish consumption on oral cancer. A hospital-based case-control study was performed including 305 oral cancer patients and 579 cancer-free controls. The genotypes were determined by TaqMan genotyping assay. Non-conditional logistic regression model was used to assess the effects of FADS1 rs174549 polymorphism and fish intake. Subjects carrying A allele of rs174549 significantly reduced the risk of oral cancer (AA VS GG, OR: 0.65, 95% CI: 0.42-0.99; AA VS AG+GG, OR: 0.67, 95% CI: 0.46-0.98). Moreover, the statistically significant reverse associations were especially evident in men, smokers, alcohol drinkers and those age ≤ 60 years. Additionally, fish intake ≥7 times/week showed a 73% reduction in risk for oral cancer compared to those who ate fish less than 2 times/week (OR: 0.27, 95% CI: 0.18-0.42). Furthermore, a significant gene-diet multiplicative interaction was observed between FADS1 rs174549 polymorphism and fish intake for oral cancer (P=0.028). This preliminary study suggests that FADS1 rs174549 polymorphism and fish consumption may be protective factors for oral cancer, with a gene-diet multiplicative interaction. Functional studies with larger samples are required to confirm our findings. Show less
📄 PDF DOI: 10.18632/oncotarget.15069
FADS1
Wen-Chi Hsueh, Anup K Nair, Sayuko Kobes +7 more · 2017 · Circulation. Cardiovascular genetics · added 2026-04-24
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment t Show more
Identity-by-descent mapping using empirical estimates of identity-by-descent allele sharing may be useful for studies of complex traits in founder populations, where hidden relationships may augment the inherent genetic information that can be used for localization. Through identity-by-descent mapping, using ≈400 000 single-nucleotide polymorphisms (SNPs), of serum lipid profiles, we identified a major linkage signal for triglycerides in 1007 Pima Indians (LOD=9.23; Show less
📄 PDF DOI: 10.1161/CIRCGENETICS.117.001809
APOA5
Tara Jois, Weiyi Chen, Victor Howard +7 more · 2017 · Molecular metabolism · Elsevier · added 2026-04-24
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have lin Show more
Carbohydrate response element binding protein (ChREBP) is a transcription factor that responds to glucose and activates genes involved in the glycolytic and lipogenic pathways. Recent studies have linked adipose ChREBP to insulin sensitivity in mice. However, while ChREBP is most highly expressed in the liver, the effect of hepatic ChREBP on insulin sensitivity remains unknown. To clarify the importance of hepatic ChREBP on glucose homeostasis, we have generated a knockout mouse model that lacks this protein specifically in the liver (Liver-ChREBP KO). Using Liver-ChREBP KO mice, we investigated whether hepatic ChREBP deletion influences insulin sensitivity, glucose homeostasis and the development of hepatic steatosis utilizing various dietary stressors. Furthermore, we determined gene expression changes in response to fasted and fed states in liver, white, and brown adipose tissues. Liver-ChREBP KO mice had impaired insulin sensitivity as indicated by reduced glucose infusion to maintain euglycemia during hyperinsulinemic-euglycemic clamps on both chow (25% lower) and high-fat diet (33% lower) (p < 0.05). This corresponded with attenuated suppression of hepatic glucose production. Although Liver-ChREBP KO mice were protected against carbohydrate-induced hepatic steatosis, they displayed worsened glucose tolerance. Liver-ChREBP KO mice did not show the expected gene expression changes in liver in response to fasted and fed states. Interestingly, hepatic ChREBP deletion also resulted in gene expression changes in white and brown adipose tissues, suggesting inter-tissue communication. This included an almost complete abolition of BAT ChREBPβ induction in the fed state (0.15-fold) (p = 0.015) along with reduced lipogenic genes. In contrast, WAT showed inappropriate increases in lipogenic genes in the fasted state along with increased PEPCK1 in both fasted (3.4-fold) and fed (5.1-fold) states (p < 0.0001). Overall, hepatic ChREBP is protective in regards to hepatic insulin sensitivity and whole body glucose homeostasis. Hepatic ChREBP action can influence other peripheral tissues and is likely essential in coordinating the body's response to different feeding states. Show less
📄 PDF DOI: 10.1016/j.molmet.2017.07.006
MLXIPL
Huiyuan Jing, Yanrong Zhou, Liurong Fang +5 more · 2017 · Frontiers in immunology · Frontiers · added 2026-04-24
DExD/H-box helicase 36 (DHX36) is known to be an ATP-dependent RNA helicase that unwinds the guanine-quadruplexes DNA or RNA, but emerging data suggest that it also functions as pattern recognition re Show more
DExD/H-box helicase 36 (DHX36) is known to be an ATP-dependent RNA helicase that unwinds the guanine-quadruplexes DNA or RNA, but emerging data suggest that it also functions as pattern recognition receptor in innate immunity. Porcine reproductive and respiratory syndrome virus (PRRSV) is an Show less
📄 PDF DOI: 10.3389/fimmu.2017.01365
DHX36
Jia Nee Foo, Louis C Tan, Ishak D Irwan +39 more · 2017 · Human molecular genetics · Oxford University Press · added 2026-04-24
Genome-wide association studies (GWAS) on Parkinson's disease (PD) have mostly been done in Europeans and Japanese. No study has been done in Han Chinese, which make up nearly a fifth of the world pop Show more
Genome-wide association studies (GWAS) on Parkinson's disease (PD) have mostly been done in Europeans and Japanese. No study has been done in Han Chinese, which make up nearly a fifth of the world population. We conducted the first Han Chinese GWAS analysing a total of 22,729 subjects (5,125 PD cases and 17,604 controls) from Singapore, Hong Kong, Malaysia, Korea, mainland China and Taiwan. We performed imputation, merging and logistic regression analyses of 2,402,394 SNPs passing quality control filters in 779 PD cases, 13,227 controls, adjusted for the first three principal components. 90 SNPs with association P < 10-4 were validated in 9 additional sample collections and the results were combined using fixed-effects inverse-variance meta-analysis. We observed strong associations reaching genome-wide significance at SNCA, LRRK2 and MCCC1, confirming their important roles in both European and Asian PD. We also identified significant (P < 0.05) associations at 5 loci (DLG2, SIPA1L2, STK39, VPS13C and RIT2), and observed the same direction of associations at 9 other loci including BST1 and PARK16. Allelic heterogeneity was observed at LRRK2 while European risk SNPs at 6 other loci including MAPT and GBA-SYT11 were non-polymorphic or very rare in our cohort. Overall, we replicate associations at SNCA, LRRK2, MCCC1 and 14 other European PD loci but did not identify Asian-specific loci with large effects (OR > 1.45) on PD risk. Our results also demonstrate some differences in the genetic contribution to PD between Europeans and Asians. Further pan-ethnic meta-analysis with European GWAS cohorts may unravel new PD loci. Show less
no PDF DOI: 10.1093/hmg/ddw379
DLG2
Deyi Zhang, Wei Wang, Xiujie Sun +8 more · 2016 · Autophagy · Taylor & Francis · added 2026-04-24
Macroautophagy/autophagy is a conserved catabolic process that recycles cytoplasmic material during low energy conditions. BECN1/Beclin1 (Beclin 1, autophagy related) is an essential protein for funct Show more
Macroautophagy/autophagy is a conserved catabolic process that recycles cytoplasmic material during low energy conditions. BECN1/Beclin1 (Beclin 1, autophagy related) is an essential protein for function of the class 3 phosphatidylinositol 3-kinase (PtdIns3K) complexes that play a key role in autophagy nucleation and elongation. Here, we show that AMP-activated protein kinase (AMPK) regulates autophagy by phosphorylating BECN1 at Thr388. Phosphorylation of BECN1 is required for autophagy upon glucose withdrawal. BECN1(T388A), a phosphorylation defective mutant, suppresses autophagy through decreasing the interaction between PIK3C3 (phosphatidylinositol 3-kinase catalytic subunit type 3) and ATG14 (autophagy-related 14). The BECN1(T388A) mutant has a higher affinity for BCL2 than its wild-type counterpart; the mutant is more prone to dimer formation. Conversely, a BECN1 phosphorylation mimic mutant, T388D, has stronger binding to PIK3C3 and ATG14, and promotes higher autophagy activity than the wild-type control. These findings uncover a novel mechanism of autophagy regulation. Show less
no PDF DOI: 10.1080/15548627.2016.1185576
PIK3C3
Linda M Polfus, Rajiv K Khajuria, Ursula M Schick +53 more · 2016 · American journal of human genetics · Elsevier · added 2026-04-24
Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. Show more
Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis. Show less
no PDF DOI: 10.1016/j.ajhg.2016.06.016
CPS1
Rui-Nan Zhang, Rui-Dan Zheng, Yu-Qiang Mi +6 more · 2016 · Digestive diseases and sciences · Springer · added 2026-04-24
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The Show more
The association between nonalcoholic fatty liver disease (NAFLD) and apolipoprotein C3 gene (APOC3) promoter region single-nucleotide polymorphisms (SNPs) rs2854117 and rs2854116 is controversial. The aim of this study was to investigate the relationship between other polymorphisms of APOC3 and NAFLD in Chinese. Fifty-nine liver biopsy-proven NAFLD patients and 72 healthy control subjects were recruited to a cohort representing Chinese Han population. The polymorphisms in the exons and flanking regions of APOC3 and patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 polymorphisms were genotyped. Among the five SNPs (rs4225, rs4520, rs5128, rs2070666, and rs2070667) in APOC3, only rs2070666 (c.179 + 62 T/A) was significantly different in genotype and allele frequency (both p < 0.01) between groups of NAFLD and control. After adjusting for sex, age, serum triglycerides, total cholesterol, body mass index, and the PNPLA3 rs738409 polymorphism, the APOC3 rs2070666 A allele was an independent risk factor for NAFLD with an odds ratio (OR) of 3.683 and 95 % confidence interval (CI) of 1.037-13.084. The APOC3 rs2070666 A allele was linked to the fourth quartile of the controlled attenuation parameter values (OR 2.769, 95 % CI 1.002-7.651) in 131 subjects, and also linked to the significant histological steatosis (OR 4.986, 95 % CI 1.020-24.371), but neither to liver stiffness measurement values nor to hepatic histological activity and fibrosis in NAFLD patients. The APOC3 rs2070666 A allele is a risk factor for NAFLD independent of obesity, dyslipidemia, and PNPLA3 rs738409, and it might contribute to increased liver fat content in Chinese Han population. Show less
no PDF DOI: 10.1007/s10620-016-4120-7
APOC3
Wangshu Qin, Xinzhi Li, Liwei Xie +9 more · 2016 · Nucleic acids research · Oxford University Press · added 2026-04-24
Long non-coding RNAs (lncRNAs) have been shown to be critical biomarkers or therapeutic targets for human diseases. However, only a small number of lncRNAs were screened and characterized. Here, we id Show more
Long non-coding RNAs (lncRNAs) have been shown to be critical biomarkers or therapeutic targets for human diseases. However, only a small number of lncRNAs were screened and characterized. Here, we identified 15 lncRNAs, which are associated with fatty liver disease. Among them, APOA4-AS is shown to be a concordant regulator of Apolipoprotein A-IV (APOA4) expression. APOA4-AS has a similar expression pattern with APOA4 gene. The expressions of APOA4-AS and APOA4 are both abnormally elevated in the liver of ob/ob mice and patients with fatty liver disease. Knockdown of APOA4-AS reduces APOA4 expression both in vitro and in vivo and leads to decreased levels of plasma triglyceride and total cholesterol in ob/ob mice. Mechanistically, APOA4-AS directly interacts with mRNA stabilizing protein HuR and stabilizes APOA4 mRNA. Deletion of HuR dramatically reduces both APOA4-AS and APOA4 transcripts. This study uncovers an anti-sense lncRNA (APOA4-AS), which is co-expressed with APOA4, and concordantly and specifically regulates APOA4 expression both in vitro and in vivo with the involvement of HuR. Show less
📄 PDF DOI: 10.1093/nar/gkw341
APOA4
Tong-Hong Wang, Cheng-Chia Yu, Yong-Shiang Lin +6 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the fu Show more
Recently, increasing numbers of long noncoding RNAs (lncRNAs), with both oncogenic and tumor-suppressive potential, have been found to be aberrantly expressed in various human cancers. However, the function of lncRNAs in hepatocellular carcinoma (HCC) progression remains largely unknown. In this study, we performed a comprehensive microarray analysis of lncRNA expression using human HCC specimens. After validation in 119 human HCC tissues, we identified a novel tumor suppressor lncRNA, CPS1 intronic transcript 1 (CPS1-IT1). To elucidate the clinical significance of CPS1-IT1 in HCC, correlations between CPS1-IT1 levels, clinical parameters, and survival outcomes were analyzed. In vitro and in vivo functional assays were also performed to dissect the potential underlying mechanisms. Expression of CPS1-IT1 was significantly decreased in 73% of HCC tissues, and patients with low CPS1-IT1 expression had poor survival outcomes. Furthermore, in vitro functional assays indicated that CPS1-IT1 significantly reduced cell proliferation, migration and invasion capacities through reduced Hsp90 binding to and activation of HIF-1α, thereby suppressing the epithelial-mesenchymal transition (EMT). An in vivo animal model also demonstrated the tumor suppressor role of CPS1- IT1 via decreased tumor growth and metastasis. In conclusion, lncRNA CPS1-IT1 acts as a tumor suppressor in HCC by reducing HIF-1α activation and suppressing EMT. The findings of this study establish a function for CPS1-IT1 in HCC progression and suggest its potential as a new prognostic biomarker and target for HCC therapy. Show less
📄 PDF DOI: 10.18632/oncotarget.9635
CPS1
Yajun Zheng, Linghang Zhuang, Kristi Yi Fan +28 more · 2016 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based dru Show more
This article describes the application of Contour to the design and discovery of a novel, potent, orally efficacious liver X receptor β (LXRβ) agonist (17). Contour technology is a structure-based drug design platform that generates molecules using a context perceptive growth algorithm guided by a contact sensitive scoring function. The growth engine uses binding site perception and programmable growth capability to create drug-like molecules by assembling fragments that naturally complement hydrophilic and hydrophobic features of the protein binding site. Starting with a crystal structure of LXRβ and a docked 2-(methylsulfonyl)benzyl alcohol fragment (6), Contour was used to design agonists containing a piperazine core. Compound 17 binds to LXRβ with high affinity and to LXRα to a lesser extent, and induces the expression of LXR target genes in vitro and in vivo. This molecule served as a starting point for further optimization and generation of a candidate which is currently in human clinical trials for treating atopic dermatitis. Show less
no PDF DOI: 10.1021/acs.jmedchem.5b02029
NR1H3
Yun Ma, Shuai Tian, Shuya He +5 more · 2016 · Gene · Elsevier · added 2026-04-24
The biological effects of microRNAs (miRNAs) in the Fragile X Syndrome (FXS) have been widely studied. Dysregulation of miRNAs plays a critical role in the progression of nervous system diseases and i Show more
The biological effects of microRNAs (miRNAs) in the Fragile X Syndrome (FXS) have been widely studied. Dysregulation of miRNAs plays a critical role in the progression of nervous system diseases and in cell proliferation and differentiation. Our previous study validated that miR-19b-3p was associated with FXR1 (Fragile X related gene 1), one of homologous genes of FMR1 (Fragile X mental retardation 1). The purpose of this study was to investigate the relationship of FXR1 and miR-19b-3p, and the crucial role of miR-19b-3p in FXS and to validate whether miR-19b-3p could regulate the growth of SH-SY5Y cells. We determined that miR-19b-3p could regulate the expression of not only USP32, RAB18 and Dusp6 but also FXR1, and FXR1 could in turn regulate the expression of miR-19b-3p. What's more, the overexpression of miR-19b-3p significantly inhibited the proliferation, contributed the apoptosis and slowed down the cycle of SH-SY5Y cells. Taken together, our results indicate that miR-19b-3p plays a significant role in the molecular pathology of FXS by interacting with FXR1 and influencing the growth of SH-SY5Y cells. Show less
no PDF DOI: 10.1016/j.gene.2016.04.037
DUSP6
Lucas Goedert, Cristiano G Pereira, Jason Roszik +8 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Previous work identified RMEL3 as a lncRNA with enriched expression in melanoma. Analysis of The Cancer Genome Atlas (TCGA) data confirmed RMEL3 enriched expression in melanoma and demonstrated its as Show more
Previous work identified RMEL3 as a lncRNA with enriched expression in melanoma. Analysis of The Cancer Genome Atlas (TCGA) data confirmed RMEL3 enriched expression in melanoma and demonstrated its association with the presence of BRAFV600E. RMEL3 siRNA-mediated silencing markedly reduced (95%) colony formation in different BRAFV600E melanoma cell lines. Multiple genes of the MAPK and PI3K pathways found to be correlated with RMEL3 in TCGA samples were experimentally confirmed. RMEL3 knockdown led to downregulation of activators or effectors of these pathways, including FGF2, FGF3, DUSP6, ITGB3 and GNG2. RMEL3 knockdown induces gain of protein levels of tumor suppressor PTEN and the G1/S cyclin-Cdk inhibitors p21 and p27, as well as a decrease of pAKT (T308), BRAF, pRB (S807, S811) and cyclin B1. Consistently, knockdown resulted in an accumulation of cells in G1 phase and subG0/G1 in an asynchronously growing population. Thus, TCGA data and functional experiments demonstrate that RMEL3 is required for MAPK and PI3K signaling, and its knockdown decrease BRAFV600E melanoma cell survival and proliferation. Show less
📄 PDF DOI: 10.18632/oncotarget.9164
DUSP6
Jian Meng, Ming Feng, Weibing Dong +11 more · 2016 · Scientific reports · Nature · added 2026-04-24
Transcription factor carbohydrate responsive element binding protein (ChREBP) promotes glycolysis and lipogenesis in metabolic tissues and cancer cells. ChREBP-α and ChREBP-β, two isoforms of ChREBP t Show more
Transcription factor carbohydrate responsive element binding protein (ChREBP) promotes glycolysis and lipogenesis in metabolic tissues and cancer cells. ChREBP-α and ChREBP-β, two isoforms of ChREBP transcribed from different promoters, are both transcriptionally induced by glucose. However, the mechanism by which glucose increases ChREBP mRNA levels remains unclear. Here we report that hepatocyte nuclear factor 4 alpha (HNF-4α) is a key transcription factor for glucose-induced ChREBP-α and ChREBP-β expression. Ectopic HNF-4α expression increased ChREBP transcription while knockdown of HNF-4α greatly reduced ChREBP mRNA levels in liver cancer cells and mouse primary hepatocytes. HNF-4α not only directly bound to an E-box-containing region in intron 12 of the ChREBP gene, but also promoted ChREBP-β transcription by directly binding to two DR1 sites and one E-box-containing site of the ChREBP-β promoter. Moreover, HNF-4α interacted with ChREBP-α and synergistically promoted ChREBP-β transcription. Functionally, HNF-4α suppression reduced glucose-dependent ChREBP induction. Increased nuclear abundance of HNF-4α and its binding to cis-elements of ChREBP gene in response to glucose contributed to glucose-responsive ChREBP transcription. Taken together, our results not only revealed the novel mechanism by which HNF-4α promoted ChREBP transcription in response to glucose, but also demonstrated that ChREBP-α and HNF-4α synergistically increased ChREBP-β transcription. Show less
📄 PDF DOI: 10.1038/srep23944
MLXIPL
Rong Li, Lu-Zhu Chen, Wang ZHAO +2 more · 2016 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotrigly Show more
Apolipoprotein A5 (apoA5) is a key regulator of triglyceride (TG) metabolism. This study is to investigate the role of apoA5 in obesity-associated hypertriglyceridemia and metformin-related hypotriglyceridemic actions. Two obese mouse models, including high-fat diet-induced obese mice and ob/ob obese mice, were adopted. The effects of low- and high-dose metformin were determined on plasma and hepatic TG and apoA5 of these obese mice. Besides, the effects of metformin on TG and apoA5 were also detected in mouse and human hepatocytes in vitro. (1) Plasma apoA5 levels in the obese mice were markedly elevated and positively correlated with TG. Hepatic TG contents and apoA5 expressions were also remarkably increased in the obese mice. (2) Metformin dose-dependently decreased hepatic and plasma TG and apoA5 in the obese mice. Similarly, metformin dose-dependently reduced cellular TG contents and apoA5 expressions in hepatocytes in vitro. Compared to APOA5 knock-down (KD), metformin plus APOA5 KD resulted in more TG reduction of hepatocytes. Increased hepatic and plasma apoA5 could be a result of obesity-associated hypertriglyceridemia, and metformin displays hypotriglyceridemic effects on obese mice partly via the apoA5 pathway. Show less
no PDF DOI: 10.1016/j.bbrc.2016.08.087
APOA5
Rui-Ping Sun, Qian-Yun Xi, Jia-Jie Sun +8 more · 2016 · Scientific reports · Nature · added 2026-04-24
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduc Show more
Ammonia detoxification, which takes place via the hepatic urea cycle, is essential for nitrogen homeostasis and physiological well-being. It has been reported that a reduction in dietary protein reduces urea nitrogen. MicroRNAs (miRNAs) are major regulatory non-coding RNAs that have significant effects on several metabolic pathways; however, little is known on whether miRNAs regulate hepatic urea synthesis. The objective of this study was to assess the miRNA expression profile in a low protein diet and identify miRNAs involved in the regulation of the hepatic urea cycle using a porcine model. Weaned 28-days old piglets were fed a corn-soybean normal protein diet (NP) or a corn-soybean low protein diet (LP) for 30 d. Hepatic and blood samples were collected, and the miRNA expression profile was assessed by sequencing and qRT-PCR. Furthermore, we evaluated the possible role of miR-19b in urea synthesis regulation. There were 25 differentially expressed miRNAs between the NP and LP groups. Six of these miRNAs were predicted to be involved in urea cycle metabolism. MiR-19b negatively regulated urea synthesis by targeting SIRT5, which is a positive regulator of CPS1, the rate limiting enzyme in the urea cycle. Our study presented a novel explanation of ureagenesis regulation by miRNAs. Show less
📄 PDF DOI: 10.1038/srep33291
CPS1
Juliet D French, Sharon E Johnatty, Yi Lu +75 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify ge Show more
Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression. Show less
📄 PDF DOI: 10.18632/oncotarget.7047
CCDC171
Jia Hu, Ge Li, Liujing Qu +10 more · 2016 · Cell death & disease · Nature · added 2026-04-24
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have Show more
The formation of the autophagosome is controlled by an orderly action of ATG proteins. However, how these proteins are recruited to autophagic membranes remain poorly clarified. In this study, we have provided a line of evidence confirming that EVA1A (eva-1 homolog A)/TMEM166 (transmembrane protein 166) is associated with autophagosomal membrane development. This notion is based on dotted EVA1A structures that colocalize with ZFYVE1, ATG9, LC3B, ATG16L1, ATG5, STX17, RAB7 and LAMP1, which represent different stages of the autophagic process. It is required for autophagosome formation as this phenotype was significantly decreased in EVA1A-silenced cells and Eva1a KO MEFs. EVA1A-induced autophagy is independent of the BECN1-PIK3C3 (phosphatidylinositol 3-kinase, catalytic subunit type 3) complex but requires ATG7 activity and the ATG12-ATG5/ATG16L1 complex. Here, we present a molecular mechanism by which EVA1A interacts with the WD repeats of ATG16L1 through its C-terminal and promotes ATG12-ATG5/ATG16L1 complex recruitment to the autophagic membrane and enhances the formation of the autophagosome. We also found that both autophagic and apoptotic mechanisms contributed to EVA1A-induced cell death while inhibition of autophagy and apoptosis attenuated EVA1A-induced cell death. Overall, these findings provide a comprehensive view to our understanding of the pathways involved in the role of EVA1A in autophagy and programmed cell death. Show less
no PDF DOI: 10.1038/cddis.2016.230
PIK3C3
Gu Jing, Junqin Chen, Guanlan Xu +1 more · 2016 · Molecular metabolism · Elsevier · added 2026-04-24
Carbohydrate-response element-binding protein (ChREBP) is the major transcription factor conferring glucose-induced gene expression in pancreatic islets, liver and adipose tissue. Recently, a novel Ch Show more
Carbohydrate-response element-binding protein (ChREBP) is the major transcription factor conferring glucose-induced gene expression in pancreatic islets, liver and adipose tissue. Recently, a novel ChREBP isoform, ChREBP-β, was identified in adipose tissue and found to be also expressed in islets and involved in glucose-induced beta cell proliferation. However, the physiological function of this less abundant β-isoform in the islet, and in diabetes, is largely unknown. The aims of the present study, therefore, were to determine how diabetes affects ChREBP-β and elucidate its physiological role in pancreatic beta cells. Non-obese diabetic and obese, diabetic ob/ob mice were used as models of T1D and T2D and human islets and the rat INS-1 beta cell line were exposed to low/high glucose and used for ChREBP isoform-specific gain-and-loss-of-function experiments. Changes in ChREBP-β and ChREBP-α were assessed by qRT-PCR, immunoblotting, promoter luciferase, and chromatin immunoprecipitation studies. Expression of the ChREBP-β isoform was highly induced in diabetes and by glucose, whereas ChREBP-α was downregulated. Interestingly, ChREBP-β gain-of-function experiments further revealed that it was ChREBP-β that downregulated ChREBP-α through a negative feedback loop. On the other hand, ChREBP-β knockdown led to unabated ChREBP-α activity and glucose-induced expression of target genes, suggesting that one of the physiological roles of this novel β-isoform is to help keep glucose-induced and ChREBP-α-mediated gene expression under control. We have identified a previously unappreciated negative feedback loop by which glucose-induced ChREBP-β downregulates ChREBP-α-signaling providing new insight into the physiological role of islet ChREBP-β and into the regulation of glucose-induced gene expression. Show less
📄 PDF DOI: 10.1016/j.molmet.2016.09.010
MLXIPL
Yan-Bei Yang, Jian-Qing Chen, Yu-Lin Zhao +6 more · 2016 · Frontiers in microbiology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fmicb.2016.01659
CPS1
Qin Zhou, Chi Yang, Min-Jie Chen +1 more · 2016 · Molecular and clinical oncology · added 2026-04-24
Exostosin glycosyltransferase (EXT) 1 and EXT2 have been identified as causative genes in osteochondroma; however, it is not known whether these genes are also involved in condylar osteochondromas. Th Show more
Exostosin glycosyltransferase (EXT) 1 and EXT2 have been identified as causative genes in osteochondroma; however, it is not known whether these genes are also involved in condylar osteochondromas. The aim of this study was to identify EXT1 and EXT2 mutations in patients with non-hereditary osteochondromas of the mandibular condyle. DNA was obtained from resected tissues (cartilage cap) of 12 patients with solitary condylar osteochondromas. The exons, 3',5'-untranslated regions and intron-exon boundaries of EXT1 and EXT2 were amplified by polymerase chain reaction and the products were sequenced directly. Through direct sequencing, four genetic variations of EXT1 in 4 cases and three variations of EXT2 in 5 cases were identified. The intronic alteration of the EXT2 gene, occurring in 2 cases, was novel, whereas the other alterations had been previously reported. Nonsense somatic mutations were detected in tumor DNA. Our study extended the mutational spectrum in EXT1 and EXT2 and may facilitate a better understanding of the pathophysiology of condylar osteochondromas. Show less
no PDF DOI: 10.3892/mco.2016.955
EXT1
Salman M Tajuddin, Ursula M Schick, John D Eicher +94 more · 2016 · American journal of human genetics · Elsevier · added 2026-04-24
Salman M Tajuddin, Ursula M Schick, John D Eicher, Nathalie Chami, Ayush Giri, Jennifer A Brody, W David Hill, Tim Kacprowski, Jin Li, Leo-Pekka Lyytikäinen, Ani Manichaikul, Evelin Mihailov, Michelle L O'Donoghue, Nathan Pankratz, Raha Pazoki, Linda M Polfus, Albert Vernon Smith, Claudia Schurmann, Caterina Vacchi-Suzzi, Dawn M Waterworth, Evangelos Evangelou, Lisa R Yanek, Amber Burt, Ming-Huei Chen, Frank J A van Rooij, James S Floyd, Andreas Greinacher, Tamara B Harris, Heather M Highland, Leslie A Lange, Yongmei Liu, Reedik Mägi, Mike A Nalls, Rasika A Mathias, Deborah A Nickerson, Kjell Nikus, John M Starr, Jean-Claude Tardif, Ioanna Tzoulaki, Digna R Velez Edwards, Lars Wallentin, Traci M Bartz, Lewis C Becker, Joshua C Denny, Laura M Raffield, John D Rioux, Nele Friedrich, Myriam Fornage, He Gao, Joel N Hirschhorn, David C M Liewald, Stephen S Rich, Andre Uitterlinden, Lisa Bastarache, Diane M Becker, Eric Boerwinkle, Simon de Denus, Erwin P Bottinger, Caroline Hayward, Albert Hofman, Georg Homuth, Ethan Lange, Lenore J Launer, Terho Lehtimäki, Yingchang Lu, Andres Metspalu, Chris J O'Donnell, Rakale C Quarells, Melissa Richard, Eric S Torstenson, Kent D Taylor, Anne-Claire Vergnaud, Alan B Zonderman, David R Crosslin, Ian J Deary, Marcus Dörr, Paul Elliott, Michele K Evans, Vilmundur Gudnason, Mika Kähönen, Bruce M Psaty, Jerome I Rotter, Andrew J Slater, Abbas Dehghan, Harvey D White, Santhi K Ganesh, Ruth J F Loos, Tõnu Esko, Nauder Faraday, James G Wilson, Mary Cushman, Andrew D Johnson, Todd L Edwards, Neil A Zakai, Guillaume Lettre, Alex P Reiner, Paul L Auer Show less
White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise Show more
White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases. Show less
no PDF DOI: 10.1016/j.ajhg.2016.05.003
JMJD1C
Xiangchun Li, William K K Wu, Rui Xing +19 more · 2016 · Cancer research · added 2026-04-24
Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as m Show more
Gastric cancer is not a single disease, and its subtype classification is still evolving. Next-generation sequencing studies have identified novel genetic drivers of gastric cancer, but their use as molecular classifiers or prognostic markers of disease outcome has yet to be established. In this study, we integrated somatic mutational profiles and clinicopathologic information from 544 gastric cancer patients from previous genomic studies to identify significantly mutated genes (SMG) with prognostic relevance. Gastric cancer patients were classified into regular (86.8%) and hypermutated (13.2%) subtypes based on mutation burden. Notably, TpCpW mutations occurred significantly more frequently in regular, but not hypermutated, gastric cancers, where they were associated with APOBEC expression. In the former group, six previously unreported (XIRP2, NBEA, COL14A1, CNBD1, ITGAV, and AKAP6) and 12 recurrent mutated genes exhibited high mutation prevalence (≥3.0%) and an unexpectedly higher incidence of nonsynonymous mutations. We also identified two molecular subtypes of regular-mutated gastric cancer that were associated with distinct prognostic outcomes, independently of disease staging, as confirmed in a distinct patient cohort by targeted capture sequencing. Finally, in diffuse-type gastric cancer, CDH1 mutation was found to be associated with shortened patient survival, independently of disease staging. Overall, our work identified previously unreported SMGs and a mutation signature predictive of patient survival in newly classified subtypes of gastric cancer, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping. Cancer Res; 76(7); 1724-32. ©2016 AACR. Show less
no PDF DOI: 10.1158/0008-5472.CAN-15-2443
AKAP6
Chiung-Mei Chen, Yi-Chun Chen, Mu-Chun Chiang +4 more · 2016 · Neurobiology of aging · Elsevier · added 2026-04-24
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet Show more
Recently, a large-scale meta-analysis of genome-wide association study (GWAS) data identified several new risk loci that can modulate the risk of Parkinson's disease (PD). These associations have yet to be examined in PD patients in Chinese or Asian population. Because ethnic-specific effect is an important concern for GWAS analysis, we genotyped single-nucleotide polymorphisms in the new genetic loci, GCH1 (rs11158026), SIPA1L2 (rs10797576), VPS13C (rs2414739), and MIR4697 (rs329648), to investigate their associations with risk of PD in Taiwan. Another single-nucleotide polymorphism GCH1 rs7155501, previously identified by GWAS listed at the top 20 genes in PDGene database was also included. A total of 1151 study subjects comprising 598 patients with PD and 553 unrelated healthy controls were recruited. The frequency of minor allele (C allele) of GCH1 rs11158026 was found to be significantly higher in PD cases than in controls (p = 0.003). The CC genotype of rs11158026 increased PD risk compared to TT genotype (odds ratio [OR] = 1.29, 95% confidence interval [CI] = 1.09, 1.53, p = 0.004). Under additive model, the GCH1 rs11158026 increased the risk of developing PD (OR = 1.30, 95% CI = 1.10, 1.54, p = 0.002). In recessive model, the genotype TT of MIR4697 rs329648 marginally decreased the PD risk (OR = 0.62, 95% CI = 0.43, 0.90, p = 0.01). The PD patients demonstrated similar genotypic and allelic frequencies in GCH1 rs7155501, SIPA1L2 rs10797576, and VPS13C rs2414739 with the controls. These findings suggest that the GCH1 and MIR4697 but not SIPA1L2 and VPS13C are genetic loci influencing risk of PD in Taiwan. Show less
no PDF DOI: 10.1016/j.neurobiolaging.2015.12.016
VPS13C
Ruiyang Zhang, Congle Shen, Lijun Zhao +4 more · 2016 · International journal of cancer · Wiley · added 2026-04-24
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possi Show more
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possible role for such integration-targeted cellular genes (ITGs) in cervical carcinogenesis. Therefore, a comprehensive analysis of HPV integration events was undertaken using data collected from 14 publications, with 499 integration loci on human chromosomes included. It revealed that HPV DNA preferred to integrate into intragenic regions and gene-dense regions of human chromosomes. Intriguingly, the host cellular genes nearby the integration sites were found to be more transcriptionally active compared with control. Furthermore, analysis of the integration sites in the human genome revealed that there were several integration hotspots although all chromosomes were represented. The ITGs identified were found to be enriched in tumor-related terms and pathways using gene ontology and KEGG analysis. In line with this, three of six ITGs tested were found aberrantly expressed in cervical cancer tissues. Among them, it was demonstrated for the first time that MPPED2 could induce HeLa cell and SiHa cell G1/S transition block and cell proliferation retardation. Moreover, "knocking out" the integrated HPV fragment in HeLa cell line decreased expression of MYC located ∼500 kb downstream of the integration site, which provided the first experimental evidence supporting the hypothesis that integrated HPV fragment influence MYC expression via long distance chromatin interaction. Overall, the results of this comprehensive analysis implicated that dysregulation of ITGs caused by viral integration as possibly having an etiological involvement in cervical carcinogenesis. Show less
📄 PDF DOI: 10.1002/ijc.29872
MPPED2
Wen-li Song, Yu Tian, Xian-e Wang +7 more · 2016 · Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · added 2026-04-24
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of agg Show more
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of aggressive periodontitis. A total of 353 patients with aggressive periodontitis (group AgP) and 125 matched controls (group HP) were recruited in the study. Genotyping of FADS1 rs174537 and serum biochemical indexes were tested at the study's start. The relationships between the levels of TP, GLB, ALB, A/G and genotyping were analyzed. (1) The detection rate of allele G in group AgP was higher than that in group HP(68.1% vs. 61.2%, P=0.046,OR=1.35,95% CI 1.00-1.83); the detection rate of genotype GG in group AgP was higher than in group HP(45.5% vs. 34.4%,P=0.029, OR=1.60, 95% CI 1.05-2.44). (2) In group AgP, the patients with GG genotype exhibited significantly lower TP, GLB than the patients with GT+TT genotype [(77.08 ± 7.88) g/L vs. (79.00 ± 4.66) g/L, P=0.007; (28.17 ± 7.63) g/L vs.(29.88 ± 3.49) g/L,P=0.007) and the higher A/G(1.72 ± 0.22 vs.1.67 ± 0.22, P=0.040), but there was no significant difference in ALB between the patients with GG genotype and the patients with GT+TT genotype. In group HP, there were no significant differences in TP, GLB, A/G and ALB between individuals with genotype GT+TT and with genotype GG. (3)Compared with individuals with genotype GT+TT in group HP, the AgP patients with genotype GT+TT exhibited significantly higher TP, GLB [(79.00 ± 4.66) g/L vs. (75.20 ± 4.53) g/L, P<0.01; (29.88 ± 3.49) g/L vs.(26.55 ± 2.94) g/L, P<0.01) and the lower A/G(1.67 ± 0.22 vs. 1.88 ± 0.30, P<0.01), but there was no significant difference in ALB. There were no significant differences in TP, GLB, A/G and ALB the between the AgP patients with genotype GG and the healthy subjects with the same genotype either. FADS1 rs174537 polymorphism is associated with aggressive periodontitis. The patients with genotype GG in group AgP had relatively lower TP,GLB and higher A/G. Genotype GG might be a risk indicator for aggressive periodontitis by reducing host defense capability and contributing to inflammatory response in the occurrence and development of aggressive periodontitis. Show less
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FADS1