👤 Shi-Yi 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-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
Juan Wang, Jieping Zhang, Xin Chen +16 more · 2018 · Experimental eye research · Elsevier · added 2026-04-24
miRs play critical roles in oxidative stress-related retinopathy pathogenesis. miR-365 was identified in a previously constructed library from glyoxal-treated rat Müller cell. This report explores epi Show more
miRs play critical roles in oxidative stress-related retinopathy pathogenesis. miR-365 was identified in a previously constructed library from glyoxal-treated rat Müller cell. This report explores epigenetic alterations in Müller cells under oxidative stress to develop a novel therapeutic strategy. To examine the miR-365 expression pattern, in situ hybridization and quantitative RT-PCR were performed. Bioinformatical analysis and dual luciferase report assay were applied to identify and confirm target genes. Streptozotocin (STZ)-treated rats were used as the diabetic retinopathy (DR) model. Lentivirus-mediated anti-miR-365 was delivered subretinally and intravitreally into the rats' eyes. The functional and structural changes were evaluated by electroretinogram (ERG), histologically, and through examination of expression levels of metallopeptidase inhibitor 3 (Timp3), glial fibrillary acidic protein (Gfap), recoverin (Rcvrn) and vascular endothelia growth factor A (Vegfa). Oxidative stress factors and pro-inflammatory cytokines were analyzed. miR-365 expression was confirmed in the glyoxal-treated rat Müller cell line (glyoxal-treated rMC-1). In the retina, miR-365 mainly localized in the inner nuclear layer (INL). The increased miR-365 participated in Müller cell gliosis through oxidative stress aggravation, as observed in glyoxal-treated rMC-1 and DR rats before 6 weeks. Timp3 was a target and negatively regulated by miR-365. When miR-365 was inhibited, Timp3 expression was upregulated, Müller cell gliosis was alleviated, and retinal oxidative stress was attenuated. Visual function was also partially rescued as detected by ERG. miR-365 was found to be highly expressed in the retina and the abnormality of miR-365/Timp3 pathway is closely related to the pathology, like Müller gliosis, and the visual injury in DR. The mechanism might be through oxidative stress, and miR-365/Timp3 could be a potential therapeutic target for treating DR. Show less
no PDF DOI: 10.1016/j.exer.2017.11.006
RMC1
Tianliang Zhang, Haotai Chen, Linlin Qi +4 more · 2018 · Viruses · MDPI · added 2026-04-24
Foot-and-mouth disease (FMD) is a highly contagious disease that results in enormous economic loses worldwide. Although the protection provided by vaccination is limited during early infection, it is Show more
Foot-and-mouth disease (FMD) is a highly contagious disease that results in enormous economic loses worldwide. Although the protection provided by vaccination is limited during early infection, it is recognized as the best method to prevent FMD outbreaks. Furthermore, the mechanism of host early responses against foot-and-mouth disease virus (FMDV) infection remains unclear. In our study, a pig kidney cell line (PK-15) was used as a cell model to reveal the mechanism of early pig responses to FMDV infection. Four non-treated control and four FMDV-treated PK-15 cells were sequenced with RNA-seq technology, and the differentially expressed genes (DEGs) were analyzed. The results showed that 1212 DEGs were in the FMDV-infected PK-15 cells, including 914 up-regulated and 298 down-regulated genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched in the tumor necrosis factor (TNF), cytokine-cytokine receptor interaction, NOD-like receptor, toll-like receptor, NF-κB, and the chemokine signaling pathways. To verify the results of the DEGs, 30 immune-related DEGs (19 up-regulated and 11 down-regulated) were selected for Quantitative Reverse Transcriptase polymerase chain reaction (RT-qPCR) verification. The results showed that RT-qPCR-measured genes exhibited a similar pattern as the RNA-seq analyses. Based on bioinformatics analysis, during FMDV early infection, we found that a series of cytokines, such as interleukins (IL6), chemokines (CXCL2, CCL20 and CCL4), and transcription factors (ZFP36, FOS, NFKBIA, ZBTB3, ZNF503, ZNF283, dymeclin (DYM), and orthodenticle homeobox 1 (OTX1)) were involved in the battle between FMDV and the host. Combined with their features and functions, we propose inflammation as the main early mechanism by which the host responds to FMDV infection. These data provide an additional panel of candidate genes for deciphering the mechanisms of a host's early response against FMDV infection. Show less
📄 PDF DOI: 10.3390/v10070364
DYM
Olav B Smeland, Yunpeng Wang, Oleksandr Frei +10 more · 2018 · Schizophrenia bulletin · Oxford University Press · added 2026-04-24
Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, Show more
Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent. Show less
no PDF DOI: 10.1093/schbul/sbx148
DLG2
Qiong Ye, Guo-Ping Tian, Hai-Peng Cheng +17 more · 2018 · Journal of atherosclerosis and thrombosis · added 2026-04-24
Atherosclerosis is the most common cause of cardiovascular disease, such as myocardial infarction and stroke. Previous study revealed that microRNA (miR)-134 promotes lipid accumulation and proinflamm Show more
Atherosclerosis is the most common cause of cardiovascular disease, such as myocardial infarction and stroke. Previous study revealed that microRNA (miR)-134 promotes lipid accumulation and proinflammatory cytokine secretion through angiopoietin-like 4 (ANGPTL4)/lipid lipoprotein (LPL) signaling in THP-1 macrophages. ApoE KO male mice on a C57BL/6 background were fed a high-fat/high-cholesterol Western diet, from 8 to 16 weeks of age. Mice were divided into four groups, and received a tail vein injection of miR-134 agomir, miR-134 antagomir, or one of the corresponding controls, respectively, once every 2 weeks after starting the Western diet. After 8 weeks we measured aortic atherosclerosis, LPL Activity, mRNA and protein levels of ANGPTL4 and LPL, LPL/ low-density lipoprotein receptor related protein 1 Complex Formation, proinflammatory cytokine secretion and lipid levels. Despite this finding, the influence of miR-134 on atherosclerosis in vivo remains to be determined. Using the well-characterized mouse atherosclerosis model of apolipoprotein E knockout, we found that systemic delivery of miR-134 agomir markedly enhanced the atherosclerotic lesion size, together with a significant increase in proinflammatory cytokine secretion and peritoneal macrophages lipid contents. Moreover, overexpression of miR-134 decreased ANGPTL4 expression but increased LPL expression and activity in both aortic tissues and peritoneal macrophages, which was accompanied by increased formation of LPL/low-density lipoprotein receptor-related protein 1 complexes in peritoneal macrophages. However, an opposite effect was observed in response to miR-134 antagomir. These findings suggest that miR-134 accelerates atherogenesis by promoting lipid accumulation and proinflammatory cytokine secretion via the ANGPTL4/LPL pathway. Therefore, targeting miR-134 may offer a promising strategy for the prevention and treatment of atherosclerotic cardiovascular disease. Show less
📄 PDF DOI: 10.5551/jat.40212
ANGPTL4
Eriko Negishi, Noboru Fukuda, Tomoyasu Otsuki +11 more · 2018 · American journal of physiology. Renal physiology · added 2026-04-24
We previously showed that complement 3 (C3) is highly expressed in mesenchymal tissues in spontaneously hypertensive rats (SHR). We targeted C3 gene by zinc-finger nuclease (ZFN) gene-editing technolo Show more
We previously showed that complement 3 (C3) is highly expressed in mesenchymal tissues in spontaneously hypertensive rats (SHR). We targeted C3 gene by zinc-finger nuclease (ZFN) gene-editing technology and investigated blood pressure and phenotype in SHR. Blood pressure was measured by tail-cuff and telemetry methods. Histology and expression of liver X receptor α (LXRα), renin, Krüppel-like factor 5 (KLF5), and E-cadherin were evaluated in kidneys. Mesangial cells (MCs) were removed from glomeruli from three strains, and we evaluated the phenotype in vitro. SHR showed the salt-sensitive hypertension that was abolished in C3 knockout (KO) SHR. Proliferation of MCs from SHR was higher than that from Wistar-Kyoto (WKY) rats and showed a synthetic phenotype. Renal injury scores were higher in SHR than in WKY rats and C3 KO SHR. Expression of E-cadherin was lower, and expression of renin was higher in the nephrotubulus from SHR than WKY rats and C3 KO SHR. Expression of C3 α-chain protein and α-smooth muscle actin protein was significantly higher in renal medulla from SHR than from WKY rats. Expression of angiotensinogen, LXRα, renin, and KLF5 mRNA was increased in kidney from SHR compared with C3 KO SHR. Intrarenal angiotensin II levels were significantly higher in kidney from SHR than WKY rats and C3 KO SHR. Urinary epinephrine and norepinephrine excretions were significantly higher in SHR than in WKY rats and C3 KO SHR. These findings showed that increased C3 induces salt-sensitive hypertension with increases in urinary catecholamine excretion and intrarenal activation of the renin-angiotensin system by the dedifferentiation of mesenchymal tissues in kidney from SHR. Show less
no PDF DOI: 10.1152/ajprenal.00370.2018
NR1H3
Wei-Jun Li, Rui-Xing Yin, Xiao-Li Cao +3 more · 2018 · Lipids in health and disease · BioMed Central · added 2026-04-24
Little is known about the association of the dedicator of cytokinesis 7 (DOCK7 rs1748195) and angiopoietin like 3 (ANGPTL3 rs12563308) single nucleotide polymorphisms (SNPs) and their haplotypes with Show more
Little is known about the association of the dedicator of cytokinesis 7 (DOCK7 rs1748195) and angiopoietin like 3 (ANGPTL3 rs12563308) single nucleotide polymorphisms (SNPs) and their haplotypes with serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese populations. This study aimed to detect such association in a Southern Chinese Han population. This study included 1728 subjects (CAD, 568; IS, 539; and controls, 621). Genotypes of the two SNPs were determined by the Snapshot technology. The genotypic and allelic frequencies of the rs1748195 SNP were different between CAD patients and controls (P < 0.05 for each), the rs1748195G allele frequency was higher in CAD patients than in controls (27.6% vs. 23.6%, P = 0.024). The genotypic frequencies of the rs12563308 SNP were also different between CAD patients and controls (P = 0.021). The rs1748195 SNP was associated with an increased risk of CAD after controlling for potential confounders and Bonferroni correction (P < 0.025 considered statistically significant; Recessive: OR = 1.79, 95% CI = 1.04-3.06, P = 0.017; Log-additive: OR = 1.27, 95% CI = 1.02-1.57, P = 0.014), whereas the rs12563308 SNP was associated with a decreased risk of CAD (Dominant: OR = 0.69, 95% CI = 0.45-0.94, P = 0.011; Log-additive: OR = 0.73, 95% CI = 0.49-0.89, P = 0.009). The rs1748195 SNP was also associated with an increased risk of severity to coronary artery atherosclerosis (Dominant: OR = 1.45, 95% CI = 1.07-2.11, P = 0.017; Log-additive: OR = 1.35, 95% CI = 1.09-1.82, P = 0.013). The interactions of SNP-environment on serum lipid levels and the risk of severity to coronary artery atherosclerosis, CAD and IS were noted. The rs1748195G-rs12563308T haplotype was associated with an increased angiographic severity to coronary artery atherosclerosis (OR = 1.46, 95% CI = 1.05-2.03), and the risk of CAD (OR = 1.37, 95% CI = 1.08-1.74). The interactions of haplotype-hypertension on the risk of CAD and haplotype-drinking on the risk of CAD/IS were observed. These results suggest that the DOCK-ANGPTL3 SNPs and their haplotypes were associated with the angiographic severity to coronary artery atherosclerosis and the risk of CAD and IS in the Southern Chinese Han population. Show less
📄 PDF DOI: 10.1186/s12944-018-0677-9
DOCK7
Nan Wu, Guili Liu, Yi Huang +5 more · 2018 · Anatolian journal of cardiology · added 2026-04-24
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study e Show more
Blood lipids are well-known risk factors for coronary heart disease (CHD). The aim of this study was to explore the association between 17 lipid-related gene polymorphisms and CHD. The current study examined with 784 CHD cases and 739 non-CHD controls. Genotyping was performed on the MassARRAY iPLEX® assay platform. Our analyses revealed a significant association of APOE rs7259620 with CHD (genotype: χ2=6.353, df=2, p=0.042; allele: χ2=5.05, df=1, p=0.025; recessive model: χ2=5.57, df=1, p=0.018). A further gender-based subgroup analysis revealed significant associations of APOE rs7259620 and PPAP2B rs72664392 with CHD in males (genotype: χ2=8.379, df=2, p=0.015; allele: χ2=5.190, df=1, p=0.023; recessive model: χ2=19.3, df=1, p<0.0001) and females (genotype: χ2=9.878, df=2, p=0.007), respectively. Subsequent breakdown analysis by age showed that CETP rs4783961, MLXIPL rs35493868, and PON2 rs12704796 were significantly associated with CHD among individuals younger than 55 years of age (CETP rs4783961: χ2=8.966, df=1, p=0.011 by genotype; MLXIPL rs35493868: χ2=4.87, df=1, p=0.027 by allele; χ2=4.88, df=1, p=0.027 by dominant model; PON2 rs12704796: χ2=6.511, df=2, p=0.039 by genotype; χ2=6.210, df=1, p=0.013 by allele; χ2=5.03, df=1, p=0.025 by dominant model). Significant allelic association was observed between LEPR rs656451 and CHD among individuals older than 65 years of age (χ2=4.410, df=1, p=0.036). Our study revealed significant associations of APOE, PPAP2B, CETP, MLXIPL, PON2, and LEPR gene polymorphisms with CHD among the Han Chinese. Show less
📄 PDF DOI: 10.14744/AnatolJCardiol.2018.23682
CETP
Yuchan Li, Jian Wang, Jingyan Tang +6 more · 2018 · Medicine · added 2026-04-24
Hereditary multiple osteochondroma (HMO) is one of the most common genetic skeletal disorders. It is caused by mutations in either EXT1 or EXT2 resulting in abnormal skeletal growth and morphogenesis. Show more
Hereditary multiple osteochondroma (HMO) is one of the most common genetic skeletal disorders. It is caused by mutations in either EXT1 or EXT2 resulting in abnormal skeletal growth and morphogenesis. However, the spectrum and frequency of EXT1 and EXT2 mutations in Chinese patients with HMO was not previously investigated.Mutations were identified by performing Sanger sequencing analysis of the complete coding regions and flanking intronic sequences of EXT1 and EXT2, followed by multiplex ligation-dependent probe amplification (MLPA) analysis to detect gene deletions or duplications that could not be identified by the Sanger sequencing method.The present study identified pathogenic mutations in 93% (68/73) of unrelated HMO probands from 73 pedigrees. Mutations in EXT1 and EXT2 were identified in 53% (39/73) and 40% (29/73) of families. We identified 58 distinct mutations in EXT1 and EXT2, including 20 frameshift mutations, 16 nonsense mutations, 7 missense mutations, 9 splice site mutations, 5 large deletions, and 1 in-frame deletion mutation. Twenty-six of these mutations were novel and 32 were previously reported. Most of the mutations in EXT1 were base deletions or insertions (21/33), whereas the majority of those in EXT2 were single base substitution (18/25).Complete sequencing of both the EXT1 and EXT2 followed by MLPA analysis is recommended for genetic analysis of Chinese patients with HMO. This study provides a comprehensive characterization of the genetic aberrations found in Chinese patients with HMO and highlights the diagnostic value of molecular genetic analysis in this particular disease. Show less
📄 PDF DOI: 10.1097/MD.0000000000012855
EXT1
Nicola M McKeown, Hassan S Dashti, Jiantao Ma +47 more · 2018 · Diabetologia · Springer · added 2026-04-24
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormon Show more
Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10 In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study). Show less
📄 PDF DOI: 10.1007/s00125-017-4475-0
MLXIPL

A novel

Zhonghua Chen, Qing Bi, Mingxiang Kong +2 more · 2018 · Oncology letters · added 2026-04-24
Multiple osteochondromas (MO) is an autosomal inherited disease that is characterized by benign bone tumors. However, the underlying mechanism of MO at a molecular level requires further investigation Show more
Multiple osteochondromas (MO) is an autosomal inherited disease that is characterized by benign bone tumors. However, the underlying mechanism of MO at a molecular level requires further investigation. The majority of mutations associated with MO occur in the exostosin glycosyltransferase genes ( Show less
📄 PDF DOI: 10.3892/ol.2018.9248
EXT1
Chih-Yuan Fang, Mien-Cheng Chen, Tzu-Hao Chang +10 more · 2018 · International journal of molecular sciences · MDPI · added 2026-04-24
Lipid expression is increased in the atrial myocytes of mitral regurgitation (MR) patients. This study aimed to investigate key regulatory genes and mechanisms of atrial lipotoxic myopathy in MR. The Show more
Lipid expression is increased in the atrial myocytes of mitral regurgitation (MR) patients. This study aimed to investigate key regulatory genes and mechanisms of atrial lipotoxic myopathy in MR. The HL-1 atrial myocytes were subjected to uniaxial cyclic stretching for eight hours. Fatty acid metabolism, lipoprotein signaling, and cholesterol metabolism were analyzed by PCR assay (168 genes). The stretched myocytes had significantly larger cell size and higher lipid expression than non-stretched myocytes (all The Show less
📄 PDF DOI: 10.3390/ijms19124094
APOA4
Yong Wang, Jing Su, Donghe Fu +6 more · 2018 · International journal of medical sciences · added 2026-04-24
no PDF DOI: 10.7150/ijms.25580
NRXN3
Lifang Hu, Peihong Su, Chong Yin +10 more · 2018 · Journal of cellular physiology · Wiley · added 2026-04-24
Osteoblast differentiation is a multistep process delicately regulated by many factors, including cytoskeletal dynamics and signaling pathways. Microtubule actin crosslinking factor 1 (MACF1), a key c Show more
Osteoblast differentiation is a multistep process delicately regulated by many factors, including cytoskeletal dynamics and signaling pathways. Microtubule actin crosslinking factor 1 (MACF1), a key cytoskeletal linker, has been shown to play key roles in signal transduction and in diverse cellular processes; however, its role in regulating osteoblast differentiation is still needed to be elucidated. To further uncover the functions and mechanisms of action of MACF1 in osteoblast differentiation, we examined effects of MACF1 knockdown (MACF1-KD) in MC3T3-E1 osteoblastic cells on their osteoblast differentiation and associated molecular mechanisms. The results showed that knockdown of MACF1 significantly suppressed mineralization of MC3T3-E1 cells, down-regulated the expression of key osteogenic genes alkaline phosphatase (ALP), runt-related transcription factor 2 (Runx2) and type I collagen α1 (Col Iα1). Knockdown of MACF1 dramatically reduced the nuclear translocation of β-catenin, decreased the transcriptional activation of T cell factor 1 (TCF1), and down-regulated the expression of TCF1, lymphoid enhancer-binding factor 1 (LEF1), and Runx2, a target gene of β-catenin/TCF1. In addition, MACF1-KD increased the active level of glycogen synthase kinase-3β (GSK-3β), which is a key regulator for β-catenin signal transduction. Moreover, the reduction of nuclear β-catenin amount and decreased expression of TCF1 and Runx2 were significantly reversed in MACF1-KD cells when treated with lithium chloride, an agonist for β-catenin by inhibiting GSK-3β activity. Taken together, these findings suggest that knockdown of MACF1 in osteoblastic cells inhibits osteoblast differentiation through suppressing the β-catenin/TCF1-Runx2 axis. Thus, a novel role of MACF1 in and a new mechanistic insight of osteoblast differentiation are uncovered. Show less
no PDF DOI: 10.1002/jcp.26059
MACF1
Zhao-Yang Wu, Yan Wang, Jing-Wen Wang +2 more · 2018 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Screening and identifying the gene mutation of EXT1, EXT2 and EXT3 associated with multiple exostosis (ME) and the expression in tumor tissues. Nine patients with multiple exostosis were collected and Show more
Screening and identifying the gene mutation of EXT1, EXT2 and EXT3 associated with multiple exostosis (ME) and the expression in tumor tissues. Nine patients with multiple exostosis were collected and genomic DNA was extracted. Polymerase chain reaction (PCR) amplification and direct sequencing techniques were used to screen all exons, 5' and 3' ends of the EXT1, EXT2 and EXT3 related causative genes. EXT1, EXT2 and EXT3 gene were screened and quantified by RNA-SEQ and RT-qPCR. The concentration of calcitonin gene-related peptide (CGRP) in peripheral blood of tumor patients and normal controls was detected by ELISA. Between the two patients with ME, the EXT1 gene was found in one patient to have c.79 T>A mutation, which caused the change of p.M27T, the non polar methionine was replaced by the high frequency mutation of polar threonine, and the rest of patients was found the splicing mutation c.1284 + 8 delAT of the heterozygosity of the EXT1 gene. The serum CGRP concentration of ME patients (623 + 49 pg/ml) was significantly higher than that of normal controls (196 + 68 pg/ml), and EXT1 mutation patients were also higher than non mutation patients. Show less
no PDF DOI: 10.1016/j.bbrc.2018.09.115
EXT1
Wenlu Zhang, Yu'e Wu, Wei Fan +3 more · 2018 · Animal models and experimental medicine · Wiley · added 2026-04-24
This study was conducted to measure the concentration of branched chain amino acid (BCAA) in different species and detect the expression pattern of the liver We measured the concentration of BCAA in G Show more
This study was conducted to measure the concentration of branched chain amino acid (BCAA) in different species and detect the expression pattern of the liver We measured the concentration of BCAA in GK rats, induced T2D cynomolgus monkeys and T2D humans by liquid chromatography tandem mass spectrometry, and used real-time quantitative PCR to analyze the gene expression of In this study, we showed that GK rat BCAA concentrations were significantly reduced at 4 and 8 weeks ( Our results showed that BCAA concentrations changed at different times and by different amounts in different species and during different periods of T2D progress, and the significant changes of BCAA concentration in the three species indicated that BCAA might participate in the progress of T2D. The results suggested that the increased expression of Show less
📄 PDF DOI: 10.1002/ame2.12038
BCKDK
Yan Chen, Yan-Jun Wang, Ying Zhao +1 more · 2018 · Bioscience reports · added 2026-04-24
Diabetic nephropathy (DN) is one of the most devastating complications of diabetes mellitus. Carbohydrate response element binding protein (ChREBP) is a basic helix-loop-helix leucine zipper transcrip Show more
Diabetic nephropathy (DN) is one of the most devastating complications of diabetes mellitus. Carbohydrate response element binding protein (ChREBP) is a basic helix-loop-helix leucine zipper transcription factor that primarily mediates glucose homeostasis in the body. The present study investigated the role of ChREBP in the pathogenesis of DN. The expression of ChREBP was detected in patients with type 2 diabetes mellitus (T2DM), diabetic mice, and mesangial cells. ELISA was used to measure cytokine production in mesangial cells. Flow cytometry analysis was performed to detect the apoptosis of mesangial cells in the presence of high glucose. The expression levels of ChREBP and several cytokines (TNF-α, IL-1β, and IL-6) were up-regulated in T2DM patients. The mRNA and protein levels of ChREBP were also significantly elevated in the kidneys of diabetic mice. Moreover, glucose treatment promoted mRNA levels of TNF-α, IL-1β, and IL-6 in mesangial cells. Glucose stimulation induced significant apoptosis of SV40 MES 13 cells. In addition, transfection with ChREBP siRNA significantly inhibited ChREBP expression. Consequently, the inflammatory responses and apoptosis were inhibited in SV40 MES 13 cells. These results demonstrated that ChREBP could mediate the inflammatory response and apoptosis of mesangial cells, suggesting that ChREBP may be involved in the pathogenesis of DN. Show less
📄 PDF DOI: 10.1042/BSR20180767
MLXIPL
Xiao-Jie Song, Wei Han, Rong He +5 more · 2018 · Neurochemical research · Springer · added 2026-04-24
Seizure-induced brain damage is age-dependent, as evidenced by the different alterations of neural physiopathology in developing and mature brains. However, little is known about the age-dependent cha Show more
Seizure-induced brain damage is age-dependent, as evidenced by the different alterations of neural physiopathology in developing and mature brains. However, little is known about the age-dependent characteristics of myelinated fiber injury induced by seizures. Considering the critical functions of oligodendrocyte progenitor cells (OPCs) in myelination and Lingo-1 signaling in regulating OPCs' differentiation, the present study aimed to explore the effects of Lingo-1 on myelin and axon in immature and adult rats after status convulsion (SC) induced by lithium-pilocarpine, and the differences between immature and adult brains. Dynamic variations in electrophysiological activity and spontaneous recurrent seizures were recorded by electroencephalogram monitoring after SC. The impaired microstructures of myelin sheaths and decrease in myelin basic protein caused by SC were observed through transmission electron microscopy and western blot analysis respectively, which became more severe in adult rats, but improved gradually in immature rats. Aberrant axon sprouting occurred in adult rats, which was more prominent than in immature rats, as shown by a Timm stain. This damage was improved or negatively affected after down or upregulating Lingo-1 expression. These results demonstrated that in both immature and adult brains, Lingo-1 signaling plays important roles in seizure-induced damage to myelin sheaths and axon growth. The plasticity of the developing brain may provide a potential window of opportunity to prevent the brain from damage. Show less
no PDF DOI: 10.1007/s11064-018-2474-2
LINGO1
Xiaoqian Jing, Haoxuan Wu, Xi Cheng +6 more · 2018 · Scandinavian journal of gastroenterology · Taylor & Francis · added 2026-04-24
Colorectal cancer (CRC), one of the most aggressive gastrointestinal malignancies, is a frequently diagnosed life-threatening cancer worldwide. Most CRC patients have poor prognosis mainly because of Show more
Colorectal cancer (CRC), one of the most aggressive gastrointestinal malignancies, is a frequently diagnosed life-threatening cancer worldwide. Most CRC patients have poor prognosis mainly because of frequent metastasis and recurrence. Thus, it is crucial to find out some new biomarkers and to show deeper insights into the mechanisms of CRC. MLLT10, Myeloid/lymphoid or mixed-lineage leukemia translocated to 10, also known as AF10, a recurrent MLL partner. In this study, we found that MLLT10 promotes CRC tumor invasion and metastasis both in vitro and in vivo. Here, the expression of MLLT10 was evaluated by immunohistochemistry. Then, the plasmid and lentivirus particles for MLLT10 overexpression or knockdown were designed and constructed into SW620 and HT29 cells. Finally, cell proliferation assay, cell adhesion assay, transwell migration, and invasion assay were used to detect the migration and invasion ability of MLLT10 in CRC cells. A tail vein injection assay was employed to evaluate the role of MLLT10 in tumor metastases. MLLT10 expression was significantly higher in CRC tissues than in noncancerous tissues and was associated with some clinicopathological factors. In vitro, the overexpression of MLLT10 promoted CRC cell migration and invasion, while after MLLT10 was knocked down, the opposite results were observed. Furthermore, we used animal metastasis models to detect the function of MLLT10 in vivo, the results are same with the outcomes in vitro. In lung metastasis sites, the knockdown of MLLT10 in SW620 cells significantly inhibited Vimentin expression, whereas the E-Cadherin was increased. These results indicate that MLLT10 regulates the metastasis of CRC cells via EMT. Show less
no PDF DOI: 10.1080/00365521.2018.1481521
MLLT10
Qi Yan, Ying Ding, Yi Liu +15 more · 2018 · Human molecular genetics · Oxford University Press · added 2026-04-24
Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful ex Show more
Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful examples of genome-wide association study. However, most genetic studies to date have focused on case-control studies of late AMD (choroidal neovascularization or geographic atrophy). The genetic influences on disease progression are largely unexplored. We assembled unique resources to perform a genome-wide bivariate time-to-event analysis to test for association of time-to-late-AMD with ∼9 million variants on 2721 Caucasians from a large multi-center randomized clinical trial, the Age-Related Eye Disease Study. To our knowledge, this is the first genome-wide association study of disease progression (bivariate survival outcome) in AMD genetic studies, thus providing novel insights to AMD genetics. We used a robust Cox proportional hazards model to appropriately account for between-eye correlation when analyzing the progression time in the two eyes of each participant. We identified four previously reported susceptibility loci showing genome-wide significant association with AMD progression: ARMS2-HTRA1 (P = 8.1 × 10-43), CFH (P = 3.5 × 10-37), C2-CFB-SKIV2L (P = 8.1 × 10-10) and C3 (P = 1.2 × 10-9). Furthermore, we detected association of rs58978565 near TNR (P = 2.3 × 10-8), rs28368872 near ATF7IP2 (P = 2.9 × 10-8) and rs142450006 near MMP9 (P = 0.0006) with progression to choroidal neovascularization but not geographic atrophy. Secondary analysis limited to 34 reported risk variants revealed that LIPC and CTRB2-CTRB1 were also associated with AMD progression (P < 0.0015). Our genome-wide analysis thus expands the genetics in both development and progression of AMD and should assist in early identification of high risk individuals. Show less
no PDF DOI: 10.1093/hmg/ddy002
POC5
Ting-Ting Jiang, Li-Ying Shi, Jing Chen +9 more · 2018 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB pa Show more
This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy. Show less
no PDF DOI: 10.1016/j.bbrc.2018.06.147
APOA4
Iona Y Millwood, Derrick A Bennett, Michael V Holmes +21 more · 2018 · JAMA cardiology · added 2026-04-24
Increasing levels of high-density lipoprotein (HDL) cholesterol through pharmacologic inhibition of cholesteryl ester transfer protein (CETP) is a potentially important strategy for prevention and tre Show more
Increasing levels of high-density lipoprotein (HDL) cholesterol through pharmacologic inhibition of cholesteryl ester transfer protein (CETP) is a potentially important strategy for prevention and treatment of cardiovascular disease (CVD). To use genetic variants in the CETP gene to assess potential risks and benefits of lifelong lower CETP activity on CVD and other outcomes. This prospective biobank study included 151 217 individuals aged 30 to 79 years who were enrolled from 5 urban and 5 rural areas of China from June 25, 2004, through July 15, 2008. All participants had baseline genotype data, 17 854 of whom had lipid measurements and 4657 of whom had lipoprotein particle measurements. Median follow-up of 9.2 years (interquartile range, 8.2-10.1 years) was completed January 1, 2016, through linkage to health insurance records and death and disease registries. Five CETP variants, including an East Asian loss-of-function variant (rs2303790), combined in a genetic score weighted to associations with HDL cholesterol levels. Baseline levels of lipids and lipoprotein particles, cardiovascular risk factors, incidence of carotid plaque and predefined major vascular and nonvascular diseases, and a phenome-wide range of diseases. Among the 151 217 individuals included in this study (58.4% women and 41.6% men), the mean (SD) age was 52.3 (10.9) years. Overall, the mean (SD) low-density lipoprotein (LDL) cholesterol level was 91 (27) mg/dL; HDL cholesterol level, 48 (12) mg/dL. CETP variants were strongly associated with higher concentrations of HDL cholesterol (eg, 6.1 [SE, 0.4] mg/dL per rs2303790-G allele; P = 9.4 × 10-47) but were not associated with lower LDL cholesterol levels. Within HDL particles, cholesterol esters were increased and triglycerides reduced, whereas within very low-density lipoprotein particles, cholesterol esters were reduced and triglycerides increased. When scaled to 10-mg/dL higher levels of HDL cholesterol, the CETP genetic score was not associated with occlusive CVD (18 550 events; odds ratio [OR], 0.98; 95% CI, 0.91-1.06), major coronary events (5767 events; OR, 1.08; 95% CI, 0.95-1.22), myocardial infarction (3118 events; OR, 1.14; 95% CI, 0.97-1.35), ischemic stroke (13 759 events; OR, 0.94; 95% CI, 0.86-1.02), intracerebral hemorrhage (6532 events; OR, 0.94; 95% CI, 0.83-1.06), or other vascular diseases or carotid plaque. Similarly, rs2303790 was not associated with any vascular diseases or plaque. No associations with nonvascular diseases were found other than an increased risk for eye diseases with rs2303790 (4090 events; OR, 1.43; 95% CI, 1.13-1.80; P = .003). CETP variants were associated with altered HDL metabolism but did not lower LDL cholesterol levels and had no significant association with risk for CVD. These results suggest that in the absence of reduced LDL cholesterol levels, increasing HDL cholesterol levels by inhibition of CETP may not confer significant benefits for CVD. Show less
📄 PDF DOI: 10.1001/jamacardio.2017.4177
CETP
Wenxin Luo, Panwen Tian, Yue Wang +15 more · 2018 · International journal of cancer · Wiley · added 2026-04-24
Non-small-cell lung cancer (NSCLC) has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. While never-smoker patients with NSCLC have been well Show more
Non-small-cell lung cancer (NSCLC) has been recognized as a highly heterogeneous disease with phenotypic and genotypic diversity in each subgroup. While never-smoker patients with NSCLC have been well studied through next generation sequencing, we have yet to recognize the potentially unique molecular features of young never-smoker patients with NSCLC. In this study, we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients, who were diagnosed with lung adenocarcinoma (LUAD) at 45 years or younger. Besides the well-known gene mutations (e.g., TP53 and EGFR), our study identified several potential lung cancer-associated gene mutations that were rarely reported (e.g., HOXA4 and MST1). The lung cancer-related copy number variations (e.g., EGFR and CDKN2A) were enriched in our cohort (41.7%, 15/36) and the lung cancer-related structural variations (e.g., EML4-ALK and KIF5B-RET) were commonly observed (22.2%, 8/36). Notably, new fusion partners of ALK (SMG6-ALK) and RET (JMJD1C-RET) were found. Furthermore, we observed a high prevalence (63.9%, 23/36) of potentially targetable genomic alterations in our cohort. Finally, we identified germline mutations in BPIFB1 (rs6141383, p.V284M), CHD4 (rs74790047, p.D140E), PARP1 (rs3219145, p.K940R), NUDT1 (rs4866, p.V83M), RAD52 (rs4987207, p.S346*), and MFI2 (rs17129219, p.A559T) were significantly enriched in the young never-smoker patients with LUAD when compared with the in-house noncancer database (p < 0.05). Our study provides a detailed mutational portrait of LUAD occurring in young never-smokers and gives insights into the molecular pathogenesis of this distinct subgroup of NSCLC. Show less
📄 PDF DOI: 10.1002/ijc.31542
JMJD1C
Fei Luo, Chenyang Chen, Shenglan Chen +2 more · 2018 · International journal of cardiology · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.ijcard.2017.10.054
ANGPTL4
Lu-Chen Weng, Weihua Guan, Lyn M Steffen +7 more · 2018 · Thrombosis research · Elsevier · added 2026-04-24
Data from epidemiological studies and clinical trials suggest an influence of dietary and circulating polyunsaturated fatty acids (PUFAs) on the hemostasis profile. Genome-wide association studies (GW Show more
Data from epidemiological studies and clinical trials suggest an influence of dietary and circulating polyunsaturated fatty acids (PUFAs) on the hemostasis profile. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) related to plasma PUFAs levels. We aimed to investigate whether the SNPs related to plasma PUFAs levels were also associated with plasma levels of hemostatic variables. We tested the associations between 9 PUFA-related SNPs and 6 hemostatic variables in 9035 European Americans (EAs) and 2702 African Americans (AAs) in the Atherosclerosis Risk in Communities (ARIC) Study. We then conducted a replication study by looking-up our novel observed associations in three published GWAS for hemostatic factors in different EA populations. We observed a novel linoleic acid-related locus at the JMJD1C region associated with factor VII activity (FVIIc): rs10740118 and rs1935, Beta (p) = -1.31 (1 × 10 Our study identified a novel association for FVIIc at JMJD1C, a histone demethylase that plays a role in DNA repair and possibly transcription regulation and RNA processing. Show less
📄 PDF DOI: 10.1016/j.thromres.2018.05.032
JMJD1C
Shih-Pin Chen, Jong-Ling Fuh, Ming-Yi Chung +15 more · 2018 · Cephalalgia : an international journal of headache · SAGE Publications · added 2026-04-24
Background Susceptibility genes for migraine, despite it being a highly prevalent and disabling neurological disorder, have not been analyzed in Asians by genome-wide association study (GWAS). Methods Show more
Background Susceptibility genes for migraine, despite it being a highly prevalent and disabling neurological disorder, have not been analyzed in Asians by genome-wide association study (GWAS). Methods We conducted a two-stage case-control GWAS to identify susceptibility genes for migraine without aura in Han Chinese residing in Taiwan. In the discovery stage, we genotyped 1005 clinic-based Taiwanese migraine patients and 1053 population-based sex-matched controls using Axiom Genome-Wide CHB Array. In the replication stage, we genotyped 27 single-nucleotide polymorphisms with p < 10 Show less
no PDF DOI: 10.1177/0333102417695105
DLG2
Tingting Feng, Peng Liu, Xiao Wang +12 more · 2018 · Atherosclerosis · Elsevier · added 2026-04-24
Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent protein deacetylase. Recent studies have demonstrated that enhancing SIRT1 expression or activity may modulate cholesterol and lipid Show more
Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent protein deacetylase. Recent studies have demonstrated that enhancing SIRT1 expression or activity may modulate cholesterol and lipid metabolism. However, pharmacological and molecular regulators for SIRT1 are scarce. Here, we aimed to find novel small molecule modulators of SIRT1 to regulate cholesterol and lipid metabolism. A high-throughput screening assay was established to identify SIRT1 activators. Surface plasmon resonance and immunoprecipitation were performed to confirm the interaction of E1231 with SIRT1. Cholesterol assay was performed to demonstrate the in vitro effect of E1231. The in vivo effect of E1231 was evaluated in experimental models. E1231, a piperazine 1,4-diamide compound, was identified as a SIRT1 activator with EC We identified a novel SIRT1 activator E1231 and elucidated its beneficial effects on lipid and cholesterol metabolism. Our study suggests that E1231 might be developed as a novel drug for treating atherosclerosis. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2018.04.039
NR1H3
Xihui Chen, Lijuan Yuan, Mao Sun +2 more · 2018 · Journal of clinical laboratory analysis · Wiley · added 2026-04-24
Carbamoyl phosphate synthetase 1 deficiency (CPS1D) is a rare autosomal recessive disorder of the urea cycle, mostly characterized by hyperammonemia and the concomitant leukodystrophy. The onset of CP Show more
Carbamoyl phosphate synthetase 1 deficiency (CPS1D) is a rare autosomal recessive disorder of the urea cycle, mostly characterized by hyperammonemia and the concomitant leukodystrophy. The onset of CPS1D can be at any age, and the clinical manifestations are variable and atypical. Genetic tests are indispensable for accurate diagnosis of CPS1D on the basis of biochemical tests. Blood tandem mass spectrometric analysis and urea organic acidemia screening were performed on a Chinese neonatal patient with low activity, recurrent seizures, and hyperammonemia. Next-generation sequencing and Sanger sequencing were followed up for making a definite diagnosis. Bioinformatics tools were used for the conservation analysis and pathogenicity predictions of the identified mutations. Increased lactate in urea and decreased citrulline in blood were detected in the patient. Two novel mutations (c.173G>T, p.G58V in exon 2 and c.796G>A, p.G266R in exon 8) in CPS1 identified in the neonatal patient were found through coseparation verification. Both of the two mutations were predicted to be deleterious, and the two relevant amino acids exerted highly evolutionarily conserved. The final diagnosis of the patient was compound heterozygous CPS1D. This study described the specific clinical characteristics and the variations of physiological and biochemical indices in a Chinese neonatal patient with CPS1D, which facilitated the diagnosis and mechanism research of the disease. Two novel causative missense mutations were identified, which enriched the mutation spectrum of CPS1D in China and worldwide. Advice of prenatal diagnosis was given to the family for a new pregnancy. Show less
no PDF DOI: 10.1002/jcla.22375
CPS1
Xiyue Yang, Jing Wang, Zewei Zhou +8 more · 2018 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Phagocytosis of silicon dioxide (SiO
no PDF DOI: 10.1096/fj.201701118R
ZC3H4
Xiaoyao Li, Qi Yang, Xiaolei Shi +4 more · 2018 · Lipids in health and disease · BioMed Central · added 2026-04-24
Variants in the lipoprotein lipase (LPL), apolipoprotein C-II (APOC2), apolipoprotein A-V (APOA5), GPIHBP1 and LMF1 genes may cause severe hypertriglyceridemia (HTG), which is now the second-leading a Show more
Variants in the lipoprotein lipase (LPL), apolipoprotein C-II (APOC2), apolipoprotein A-V (APOA5), GPIHBP1 and LMF1 genes may cause severe hypertriglyceridemia (HTG), which is now the second-leading aetiology of acute pancreatitis in China. The patient and his family were assessed for gene variants by Sanger sequencing of exons and exon-intron junctions of the LPL, GPIHBP1, APOA5, APOC2, and LMF1 genes. Post-heparin blood was collected for LPL mass and activity detection. The patient had suffered from long-term severe hypertriglyceridemia and recurrent abdominal pain for over 30 years, since age 26, and 3 bouts of acute pancreatitis. Two heterozygous LPL single-nucleotide polymorphisms (SNPs) were compound but dislinked: a single-nucleotide substitution (c.42G > A) resulting in the substitution of tryptophan with a stop codon (p.W14X) in one allele, and a single-nucleotide substitution (c.835C > G) resulting in a leucine-to-valine substitution (p.L279 V) in another allele. Only one SNP, p.L279 V, was detected in his son. Post-heparin LPL activity and mass were also lower in the patient. Two heterozygous LPL SNPs, W14X and L279 V, were newly found to be compound but dislinked, which may cause long-term severe hypertriglyceridemia and recurrent acute pancreatitis. Show less
📄 PDF DOI: 10.1186/s12944-018-0789-2
APOA5
Huanhuan Yang, Guochong Chen, Chunli Song +4 more · 2018 · Medicine · added 2026-04-24
Presently noninvasive methods were employed to the diagnosis of nonalcoholic fatty liver disease (NAFLD), including fatty liver index (FLI), hepatic steatosis index (HSI), product of fasting triglycer Show more
Presently noninvasive methods were employed to the diagnosis of nonalcoholic fatty liver disease (NAFLD), including fatty liver index (FLI), hepatic steatosis index (HSI), product of fasting triglyceride and glucose levels (TyG), and single nucleotide polymorphism (SNP), whereas the accuracy of those indexes need to be improved. Our study aimed to investigate the feasibility of a new index comprehensive index (CI), consisting of 6 serum biomarkers and anthropometric parameters through multivariate logistic regression analysis, to the earlier detection of NAFLD, and the diagnostic value of 5 SNPs (S1: rs2854116 of apolipoprotein C3 [APOC3], S2: rs4149267 of ATP-binding cassette transporter [ABCA1], S3: rs13702 of lipoprotein lipase [LPL], S4: rs738409 of protein 3 [patatin-like phospholipase domain containing protein 3 (PNPLA3)], S5: rs780094 of glucokinase regulatory protein gene [GCKR]) for NAFLD were also explored. Area under the receiver operating characteristic curves (AUROC) and Youden index (YI) were calculated to assess the diagnostic value. The AUROC of CI was higher than FLI, HSI, and TyG (CI: 0.897, FLI: 0.873, HSI: 0.855, TyG: 0.793). Therefore, CI might be a better index for the diagnosis of NAFLD. Although there had no statistical significance (P = .123), the AUROC and YI were increased when CI combined with rs2854116 (S1) (AUROC = 0.902, YI = 0.6844). The combination of CI with S1 showed even better diagnostic accuracy than CI, which suggests the potential value of rs2854116 for the diagnosis of NAFLD. Show less
📄 PDF DOI: 10.1097/MD.0000000000010272
APOC3