👤 Yan Yang

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Also published as: A Yang, A-Li Yang, Acong Yang, Ai-Lun Yang, Aige Yang, Airong Yang, Aiting Yang, Aizhen Yang, Albert C Yang, Alex J T Yang, An-Qi Yang, Andrew Yang, Angang Yang, Angela Wei Hong Yang, Anni Yang, Aram Yang, B Yang, Baigao Yang, Baixia Yang, Bangjia Yang, Bao Yang, Baofeng Yang, Baoli Yang, Baoxin Yang, Baoxue Yang, Bei Yang, Beibei Yang, Biao Yang, Bin Q Yang, Bin Yang, Bing Xiang Yang, Bing Yang, Bingyu Yang, Bo Yang, Bohui Yang, Boo-Keun Yang, Bowen Yang, Boya Yang, Burton B Yang, Byoung Chul Yang, Caimei Yang, Caixia Yang, Caixian Yang, Caixin Yang, Can Yang, Canchai Yang, Ce Yang, Celi Yang, Chan Mo Yang, Chan-Mo Yang, Chang Yang, Chang-Hao Yang, Changheng Yang, Changqing Yang, Changsheng Yang, Changwei Yang, Changyun Yang, Chanjuan Yang, Chao Yang, Chao-Yuh Yang, Chaobo Yang, Chaofei Yang, Chaogang Yang, Chaojie Yang, Chaolong Yang, Chaoping Yang, Chaoqin Yang, Chaoqun Yang, Chaowu Yang, Chaoyun Yang, Chaozhe Yang, Chen Die Yang, Chen Yang, Cheng Yang, Cheng-Gang Yang, Chengfang Yang, Chenghao Yang, Chengkai Yang, Chengkun Yang, Chengran Yang, Chenguang Yang, Chengyingjie Yang, Chengzhang Yang, Chensi Yang, Chensu Yang, Chenxi Yang, Chenyu Yang, Chenzi Yang, Chi Yang, Chia-Wei Yang, Chieh-Hsin Yang, Chien-Wen Yang, Chih-Hao Yang, Chih-Min Yang, Chih-Yu Yang, Chihyu Yang, Ching-Fen Yang, Ching-Wen Yang, Chongmeng Yang, Chuan He Yang, Chuan Yang, Chuanbin Yang, Chuang Yang, Chuanli Yang, Chuhu Yang, Chun Yang, Chun-Chun Yang, Chun-Mao Yang, Chun-Seok Yang, Chunbaixue Yang, Chung-Hsiang Yang, Chung-Shi Yang, Chung-Yi Yang, Chunhua Yang, Chunhui Yang, Chunjie Yang, Chunjun Yang, Chunlei Yang, Chunli Yang, Chunmao Yang, Chunping Yang, Chunqing Yang, Chunru Yang, Chunxiao Yang, Chunyan Yang, Chunyu Yang, Congyi Yang, Cui Yang, Cuiwei Yang, Cunming Yang, Dai-Qin Yang, Dan Yang, Dan-Dan Yang, Dan-Hui Yang, Dandan Yang, Danlu Yang, Danrong Yang, Danzhou Yang, Dapeng Yang, De-Hua Yang, De-Zhai Yang, Decao Yang, Defu Yang, Deguang Yang, Dehao Yang, Dehua Yang, Dejun Yang, Deli Yang, Dengfa Yang, Deok Chun Yang, Deshuang Yang, Di Yang, Dianqiang Yang, Ding Yang, Ding-I Yang, Diya Yang, Diyuan Yang, Dong Yang, Dong-Hua Yang, Dongfeng Yang, Dongjie Yang, Dongliang Yang, Dongmei Yang, Dongren Yang, Dongshan Yang, Dongwei Yang, Dongwen Yang, DuJiang Yang, Eddy S Yang, Edwin Yang, Ei-Wen Yang, Emily Yang, Enlu Yang, Enzhi Yang, Eric Yang, Eryan Yang, Ethan Yang, Eunho Yang, Fajun Yang, Fan Yang, Fang Yang, Fang-Ji Yang, Fang-Kun Yang, Fei Yang, Feilong Yang, Feiran Yang, Feixiang Yang, Fen Yang, Feng Yang, Feng-Ming Yang, Feng-Yun Yang, Fengjie Yang, Fengjiu Yang, Fengjuan Yang, Fenglian Yang, Fengling Yang, Fengping Yang, Fengying Yang, Fengyong Yang, Fu Yang, Fude Yang, Fuhe Yang, Fuhuang Yang, Fumin Yang, Fuquan Yang, Furong Yang, Fuxia Yang, Fuyao Yang, G Y Yang, G Yang, Gan Yang, Gang Yang, Gangyi Yang, Gao Yang, Gaohong Yang, Gaoxiang Yang, Ge Yang, Gong Yang, Gong-Li Yang, Grace H Y Yang, Guan Yang, Guang Yang, Guangdong Yang, Guangli Yang, Guangwei Yang, Guangyan Yang, Guanlin Yang, Gui-Zhi Yang, Guigang Yang, Guitao Yang, Guo Yang, Guo-Can Yang, Guobin Yang, Guofen Yang, Guojun Yang, Guokun Yang, Guoli Yang, Guomei Yang, Guoping Yang, Guoqi Yang, Guosheng Yang, Guotao Yang, Guowang Yang, Guowei Yang, H X Yang, H Yang, Hai Yang, Hai-Chun Yang, Haibo Yang, Haihong Yang, Haikun Yang, Hailei Yang, Hailing Yang, Haiming Yang, Haiping Yang, Haiqiang Yang, Haitao Yang, Haixia Yang, Haiyan Yang, Haiying Yang, Han Yang, Hanchen Yang, Handong Yang, Hang Yang, Hannah Yang, Hanseul Yang, Hanteng Yang, Hao Yang, Hao-Jan Yang, HaoXiang Yang, Haojie Yang, Haolan Yang, Haoqing Yang, Haoran Yang, Haoyu Yang, Harrison Hao Yang, Hee Joo Yang, Heng Yang, Hengwen Yang, Henry Yang, Heqi Yang, Heyi Yang, Heyun Yang, Hoe-Saeng Yang, Hong Yang, Hong-Fa Yang, Hong-Li Yang, HongMei Yang, Hongbing Yang, Hongbo Yang, Hongfa Yang, Honghong Yang, Hongjie Yang, Hongjun Yang, Hongli Yang, Hongling Yang, Hongqun Yang, Hongxia Yang, Hongxin Yang, Hongyan Yang, Hongyu Yang, Hongyuan Yang, Hongyue Yang, Howard H Yang, Howard Yang, Hsin-Chou Yang, Hsin-Jung Yang, Hsin-Sheng Yang, Hua Yang, Hua-Yuan Yang, Huabing Yang, Huafang Yang, Huaijie Yang, Huan Yang, Huanhuan Yang, Huanjie Yang, Huanming Yang, Huansheng Yang, Huanyi Yang, Huarong Yang, Huaxiao Yang, Huazhao Yang, Hui Yang, Hui-Ju Yang, Hui-Li Yang, Hui-Ting Yang, Hui-Yu Yang, Hui-Yun Yang, Huifang Yang, Huihui Yang, Huijia Yang, Huijie Yang, Huiping Yang, Huiran Yang, Huixia Yang, Huiyu Yang, Hung-Chih Yang, Hwai-I Yang, Hye Jeong Yang, Hyerim Yang, Hyun Suk Yang, Hyun-Sik Yang, Ill Yang, Ivana V Yang, J S Yang, J Yang, James Y Yang, Jaw-Ji Yang, Jee Sun Yang, Jenny J Yang, Jerry Yang, Ji Hye Yang, Ji Yang, Ji Yeong Yang, Ji-chun Yang, Jia Yang, Jia-Ling Yang, Jia-Ying Yang, Jiahong Yang, Jiahui Yang, Jiajia Yang, Jiakai Yang, Jiali Yang, Jialiang Yang, Jian Yang, Jian-Bo Yang, Jian-Jun Yang, Jian-Ming Yang, Jian-Ye Yang, JianHua Yang, JianJun Yang, Jianbo Yang, Jiang-Min Yang, Jiang-Yan Yang, Jianing Yang, Jianke Yang, Jianli Yang, Jianlou Yang, Jianmin Yang, Jianming Yang, Jianqi Yang, Jianwei Yang, Jianyu Yang, Jiao Yang, Jiarui Yang, Jiawei Yang, Jiaxin Yang, Jiayan Yang, Jiayi Yang, Jiaying Yang, Jiayue Yang, Jichun Yang, Jie Yang, Jie-Cheng Yang, Jie-Hong Yang, Jie-Kai Yang, Jiefeng Yang, Jiehong Yang, Jieping Yang, Jiexiang Yang, Jihong Yang, Jimin Yang, Jin Yang, Jin-Jian Yang, Jin-Kui Yang, Jin-gang Yang, Jin-ju Yang, Jinan Yang, Jinfeng Yang, Jing Yang, Jing-Quan Yang, Jing-Yu Yang, Jingang Yang, Jingfeng Yang, Jinggang Yang, Jinghua Yang, Jinghui Yang, Jingjing Yang, Jingmin Yang, Jingping Yang, Jingran Yang, Jingshi Yang, Jingwen Yang, Jingya Yang, Jingyan Yang, Jingyao Yang, Jingye Yang, Jingyu Yang, Jingyun Yang, Jingze Yang, Jinhua Yang, Jinhui Yang, Jinjian Yang, Jinpeng Yang, Jinru Yang, Jinshan Yang, Jinsong Yang, Jinsung Yang, Jinwen Yang, Jinzhao Yang, Jiong Yang, Ju Dong Yang, Ju Young Yang, Juan Yang, Juesheng Yang, Jumei Yang, Jun J Yang, Jun Yang, Jun-Hua Yang, Jun-Xia Yang, Jun-Xing Yang, Junbo Yang, Jung Dug Yang, Jung Wook Yang, Jung-Ho Yang, Junhan Yang, Junjie Yang, Junlin Yang, Junlu Yang, Junping Yang, Juntao Yang, Junyao Yang, Junyi Yang, Kai Yang, Kai-Chien Yang, Kai-Chun Yang, Kaidi Yang, Kaifeng Yang, Kaijie Yang, Kaili Yang, Kailin Yang, Kaiwen Yang, Kang Yang, Kang Yi Yang, Kangning Yang, Karen Yang, Ke Yang, Keming Yang, Keping Yang, Kexin Yang, Kuang-Yao Yang, Kui Yang, Kun Yang, Kunao Yang, Kunqi Yang, Kunyu Yang, Kuo Tai Yang, L Yang, Lamei Yang, Lan Yang, Le Yang, Lei Yang, Lexin Yang, Leyi Yang, Li Chun Yang, Li Yang, Li-Kun Yang, Li-Qin Yang, Li-li Yang, LiMan Yang, Lian-he Yang, Liang Yang, Liang-Yo Yang, Liangbin Yang, Liangle Yang, Liangliang Yang, Lichao Yang, Lichuan Yang, Licong Yang, Liehao Yang, Lihong Yang, Lihua Yang, Lihuizi Yang, Lijia Yang, Lijie Yang, Lijuan Yang, Lijun Yang, Lili Yang, Lin Sheng Yang, Lin Yang, Lina Yang, Ling Ling Yang, Ling Yang, Lingfeng Yang, Lingling Yang, Lingzhi Yang, Linlin Yang, Linnan Yang, Linqing Yang, Linquan Yang, Lipeng Yang, Liping Yang, Liting Yang, Liu Yang, Liu-Kun Yang, LiuMing Yang, Liuliu Yang, Liwei Yang, Lixian Yang, Lixue Yang, Long In Yang, Long Yang, Long-Yan Yang, Longbao Yang, Longjun Yang, Longyan Yang, Lu M Yang, Lu Yang, Lu-Hui Yang, Lu-Kun Yang, Lu-Qin Yang, Luda Yang, Man Yang, Manqing Yang, Maojie Yang, Maoquan Yang, Mei Yang, Meichan Yang, Meihua Yang, Meili Yang, Meiting Yang, Meixiang Yang, Meiying Yang, Meng Yang, Menghan Yang, Menghua Yang, Mengjie Yang, Mengli Yang, Mengliu Yang, Mengmeng Yang, Mengsu Yang, Mengwei Yang, Mengying Yang, Miaomiao Yang, Mickey Yang, Min Hee Yang, Min Yang, Mina Yang, Ming Yang, Ming-Hui Yang, Ming-Yan Yang, Minghui Yang, Mingjia Yang, Mingjie Yang, Mingjun Yang, Mingli Yang, Mingqian Yang, Mingshi Yang, Mingyan Yang, Mingyu Yang, Minyi Yang, Misun Yang, Mu Yang, Muh-Hwa Yang, Na Yang, Nan Yang, Nana Yang, Nanfei Yang, Neil V Yang, Ni Yang, Ning Yang, Ningjie Yang, Ningli Yang, Pan Yang, Pan-Chyr Yang, Paul Yang, Peichang Yang, Peiran Yang, Peiyan Yang, Peiying Yang, Peiyuan Yang, Peizeng Yang, Peng Yang, Peng-Fei Yang, PengXiang Yang, Pengfei Yang, Penghui Yang, Pengwei Yang, Pengyu Yang, Phillip C Yang, Pin Yang, Ping Yang, Ping-Fen Yang, Pinghong Yang, Pu Yang, Q H Yang, Q Yang, Qi Yang, Qi-En Yang, Qian Yang, Qian-Jiao Yang, Qian-Li Yang, QianKun Yang, Qiang Yang, Qianhong Yang, Qianqian Yang, Qianru Yang, Qiaoli Yang, Qiaorong Yang, Qiaoyuan Yang, Qifan Yang, Qifeng Yang, Qiman Yang, Qimeng Yang, Qiming Yang, Qin Yang, Qinbo Yang, Qing Yang, Qing-Cheng Yang, Qingcheng Yang, Qinghu Yang, Qingkai Yang, Qinglin Yang, Qingling Yang, Qingmo Yang, Qingqing Yang, Qingtao Yang, Qingwu Yang, Qingya Yang, Qingyan Yang, Qingyi Yang, Qingyu Yang, Qingyuan Yang, Qiong Yang, Qiu Yang, Qiu-Yan Yang, Qiuhua Yang, Qiuhui Yang, Qiulan Yang, Qiuli Yang, Qiuxia Yang, Qiwei Yang, Qiwen Yang, Quan Yang, Quanjun Yang, Quanli Yang, Qun-Fang Yang, R Yang, Ran Yang, Ren-Zhi Yang, Renchi Yang, Renhua Yang, Renjun Yang, Renqiang Yang, Renzhi Yang, Ri-Yao Yang, Richard K Yang, Robert Yang, Rong Yang, Rongrong Yang, Rongxi Yang, Rongyuan Yang, Rongze Yang, Rui Xu Yang, Rui Yang, Rui-Xu Yang, Rui-Yi Yang, Ruicheng Yang, Ruifang Yang, Ruihua Yang, Ruilan Yang, Ruili Yang, Ruiqin Yang, Ruirui Yang, Ruiwei Yang, Rulai Yang, Ruming Yang, Run Yang, Runjun Yang, Runxu Yang, Runyu Yang, Runzhou Yang, Ruocong Yang, Ruoyun Yang, Ruyu Yang, S J Yang, Se-Ran Yang, Sen Yang, Senwen Yang, Seung Yun Yang, Seung-Jo Yang, Seung-Ok Yang, Shan Yang, Shangchen Yang, Shanghua Yang, Shangwen Yang, Shanzheng Yang, Shao-Hua Yang, Shaobin Yang, Shaohua Yang, Shaoling Yang, Shaoqi Yang, Shaoqing Yang, Sheng Sheng Yang, Sheng Yang, Sheng-Huei Yang, Sheng-Qian Yang, Sheng-Wu Yang, ShengHui Yang, Shenglin Yang, Shengnan Yang, Shengqian Yang, Shengyong Yang, Shengzhuang Yang, Shenhui Yang, Shi-Ming Yang, Shiaw-Der Yang, Shifeng Yang, Shigao Yang, Shijie Yang, Shiming Yang, Shipeng Yang, Shiping Yang, Shiu-Ju Yang, Shiyi Yang, Shizhong Yang, Shizhuo Yang, Shu Yang, ShuSheng Yang, Shuai Yang, Shuaibing Yang, Shuaini Yang, Shuang Yang, Shuangshuang Yang, Shucai Yang, Shufang Yang, Shuhua Yang, Shujuan Yang, Shujun Yang, Shulan Yang, Shulin Yang, Shuming Yang, Shun-Fa Yang, Shuo Yang, Shuofei Yang, Shuping Yang, Shuqi Yang, Shuquan Yang, Shurong Yang, Shushen Yang, Shuye Yang, Shuyu Yang, Si Yang, Si-Fu Yang, Sibao Yang, Sibo Yang, Sichong Yang, Sihui Yang, Sijia Yang, Siqi Yang, Sirui Yang, Sisi Yang, Sitao Yang, Siwen Yang, Siyi Yang, Siyu Yang, Sizhen Yang, Sizhu Yang, Song Yang, Song-na Yang, Songpeng Yang, Songye Yang, Soo Hyun Yang, Su Yang, Su-Geun Yang, Suhong Yang, Sujae Yang, Sujuan Yang, Suk-Kyun Yang, Sun Kyung Yang, Suwol Yang, Suxia Yang, Suyi Yang, Suyu Yang, Tai-Hui Yang, Tailai Yang, Tao Yang, Tengyun Yang, Thomas P Yang, Ti Yang, Tian Yang, Tianbao Yang, Tianfeng Yang, Tianjie Yang, Tianmin Yang, Tianpeng Yang, Tianqiong Yang, Tiantian Yang, Tianxin Yang, Tianyou Yang, Tianyu Yang, Tianze Yang, Tianzhong Yang, Ting Yang, Ting-Xian Yang, Tingting Yang, Tingyu Yang, Tong Yang, Tong Yi Yang, Tong-Xin Yang, Tonglin Yang, Tongren Yang, Tuanmin Yang, Ueng-Cheng Yang, W Yang, Wan-Chen Yang, Wan-Jung Yang, Wang Yang, Wannian Yang, Wei Qiang Yang, Wei Yang, Wei-Fa Yang, Wei-Xin Yang, Weidong Yang, Weiguang Yang, Weihan Yang, Weijian Yang, Weili Yang, Weimin Yang, Weiran Yang, Weiwei Yang, Weixian Yang, Weizhong Yang, Wen Yang, Wen Z Yang, Wen-Bin Yang, Wen-Chin Yang, Wen-He Yang, Wen-Hsuan Yang, Wen-Ming Yang, Wen-Wen Yang, Wen-Xiao Yang, WenKai Yang, Wenbo Yang, Wenchao Yang, Wending Yang, Wenfei Yang, Wenhong Yang, Wenhua Yang, Wenhui Yang, Wenjian Yang, Wenjie Yang, Wenjing Yang, Wenjuan Yang, Wenjun Yang, Wenli Yang, Wenlin Yang, Wenming Yang, Wenqin Yang, Wenshan Yang, Wentao Yang, Wenwen Yang, Wenwu Yang, Wenxin Yang, Wenxing Yang, Wenying Yang, Wenzhi Yang, Wenzhu Yang, William Yang, Woong-Suk Yang, Wu Yang, Wu-de Yang, X Yang, X-J Yang, Xi Yang, Xi-You Yang, Xia Yang, Xian Yang, Xiang Yang, Xiang-Hong Yang, Xiang-Jun Yang, Xianggui Yang, Xianghong Yang, Xiangliang Yang, Xiangling Yang, Xiangqiong Yang, Xiangxiang Yang, Xiangyu Yang, Xiao Yang, Xiao-Dong Yang, Xiao-Fang Yang, Xiao-Hong Yang, Xiao-Jie Yang, Xiao-Juan Yang, Xiao-Meng Yang, Xiao-Ming Yang, Xiao-Qian Yang, Xiao-Yan Yang, Xiao-Ying Yang, Xiao-Yu Yang, Xiao-guang Yang, XiaoYan Yang, Xiaoao Yang, Xiaobin Yang, Xiaobo Yang, Xiaochen Yang, Xiaodan Yang, Xiaodi Yang, Xiaodong Yang, Xiaofei Yang, Xiaofeng Yang, Xiaohao Yang, Xiaohe Yang, Xiaohong R Yang, Xiaohong Yang, Xiaohuang Yang, Xiaohui Yang, Xiaojian Yang, Xiaojie Yang, Xiaojing Yang, Xiaojuan Yang, Xiaojun Yang, Xiaoli Yang, Xiaolu Yang, Xiaomeng Yang, Xiaoming Yang, Xiaonan Yang, Xiaoping Yang, Xiaoqian Yang, Xiaoqin Yang, Xiaoqun Yang, Xiaorong Yang, Xiaoshan Yang, Xiaoshi Yang, Xiaosong Yang, Xiaotian Yang, Xiaotong Yang, Xiaowei Yang, Xiaowen Yang, Xiaoxiao Yang, Xiaoxin Yang, Xiaoxu Yang, Xiaoyao Yang, Xiaoyi Yang, Xiaoyong Yang, Xiaoyu Yang, Xiaoyun Yang, Xiaozhen Yang, Xifei Yang, Xiling Yang, Ximan Yang, Xin Yang, Xin-He Yang, Xin-Yu Yang, Xin-Zhuang Yang, Xing Yang, Xinghai Yang, Xinglong Yang, Xingmao Yang, Xingming Yang, Xingsheng Yang, Xingyu Yang, Xingyue Yang, Xingzhi Yang, Xinjing Yang, Xinming Yang, Xinpu Yang, Xinwang Yang, Xinxin Yang, Xinyan Yang, Xinyi Yang, Xinyu Yang, Xinyue Yang, Xiong Ling Yang, Xiru Yang, Xitong Yang, Xiu Hong Yang, Xiuhua Yang, Xiulin Yang, Xiuna Yang, Xiuqin Yang, Xiurong Yang, Xiuwei Yang, Xiwen Yang, Xiyue Yang, Xu Yang, Xuan Yang, Xue Yang, Xue-Feng Yang, Xue-Ping Yang, Xuecheng Yang, Xuehan Yang, Xuejing Yang, Xuejun Yang, Xueli Yang, Xuena Yang, Xueping Yang, Xuesong Yang, Xuhan Yang, Xuhui Yang, Xuping Yang, Xuyang Yang, Y C Yang, Y F Yang, Y L Yang, Y P Yang, Y Q Yang, Y Yang, Y-T Yang, Ya Yang, Ya-Chen Yang, Yadong Yang, Yafang Yang, Yajie Yang, Yalan Yang, Yali Yang, Yaming Yang, Yan-Bei Yang, Yan-Ling Yang, Yanan Yang, Yanfang Yang, Yang Yang, Yangfan Yang, Yangyang Yang, Yanhui Yang, Yanjianxiong Yang, Yanling Yang, Yanmei Yang, Yanmin Yang, Yanping Yang, Yanru Yang, Yanting Yang, Yanyan Yang, Yanzhen Yang, Yaorui Yang, Yaping Yang, Yaqi Yang, Yaxi Yang, Ye Yang, Yefa Yang, Yefeng Yang, Yeqing Yang, Yexin Yang, Yi Yang, Yi-Chieh Yang, Yi-Fang Yang, Yi-Feng Yang, Yi-Liang Yang, Yi-Ping Yang, Yi-ning Yang, Yibing Yang, Yichen Yang, Yidong Yang, Yifan Yang, Yifang Yang, Yifei Yang, Yifeng Yang, Yihe Yang, Yijie Yang, Yilian Yang, Yimei Yang, Yimin Yang, Yiming Yang, Yimu Yang, Yin-Rong Yang, Yinfeng Yang, Ying Yang, Ying-Hua Yang, Ying-Ying Yang, Yingdi Yang, Yingjun Yang, Yingqing Yang, Yingrui Yang, Yingxia Yang, Yingyu Yang, Yinhua Yang, Yining Yang, Yinxi Yang, Yiping Yang, Yiting Yang, Yiyi Yang, Yiying Yang, Yong Yang, Yong-Yu Yang, Yongfeng Yang, Yongguang Yang, Yonghong Yang, Yonghui Yang, Yongjia Yang, Yongjie Yang, Yongkang Yang, Yongqiang Yang, Yongsan Yang, Yongxin Yang, Yongxing Yang, Yongzhong Yang, Yoon La Yang, Yoon Mee Yang, Youhua Yang, YoungSoon Yang, Yu Yang, Yu-Fan Yang, Yu-Feng Yang, Yu-Jie Yang, Yu-Shi Yang, Yu-Tao Yang, Yu-Ting Yang, Yuan Yang, Yuan-Han Yang, Yuan-Jian Yang, Yuanhao Yang, Yuanjin Yang, Yuanquan Yang, Yuanrong Yang, Yuanying Yang, Yuanzhang Yang, Yuanzhi Yang, Yuchen Yang, Yucheng Yang, Yue Yang, Yueh-Ning Yang, Yuejin Yang, Yuexiang Yang, Yueze Yang, Yufan Yang, Yuhan Yang, Yuhang Yang, Yuhua Yang, Yujie Yang, Yujing Yang, Yulin Yang, Yuling Yang, Yulong Yang, Yun Yang, YunKai Yang, Yunfan Yang, Yung-Li Yang, Yunhai Yang, Yunlong Yang, Yunmei Yang, Yunwen Yang, Yunyun Yang, Yunzhao Yang, Yupeng Yang, Yuqi Yang, Yuta Yang, Yutao Yang, Yuting Yang, Yutong Yang, Yuwei Yang, Yuxi Yang, Yuxing Yang, Yuxiu Yang, Yuyan Yang, Yuyao Yang, Yuying Yang, Z Yang, Zaibin Yang, Zaiming Yang, Zaiqing Yang, Zanhao Yang, Ze Yang, Zemin Yang, Zeng-Ming Yang, Zengqiang Yang, Zengqiao Yang, Zeyu Yang, Zhang Yang, Zhangping Yang, Zhanyi Yang, Zhao Yang, Zhao-Na Yang, Zhaojie Yang, Zhaoli Yang, Zhaoxin Yang, Zhaoyang Yang, Zhaoyi Yang, Zhehan Yang, Zheming Yang, Zhen Yang, Zheng Yang, Zheng-Fei Yang, Zheng-lin Yang, Zhenglin Yang, Zhengqian Yang, Zhengtao Yang, Zhenguo Yang, Zhengyan Yang, Zhengzheng Yang, Zhengzhong Yang, Zhenhua Yang, Zhenjun Yang, Zhenmei Yang, Zhenqi Yang, Zhenrong Yang, Zhenwei Yang, Zhenxing Yang, Zhenyun Yang, Zhenzhen Yang, Zheyu Yang, Zhi Yang, Zhi-Can Yang, Zhi-Hong Yang, Zhi-Jun Yang, Zhi-Min Yang, Zhi-Ming Yang, Zhi-Rui Yang, Zhibo Yang, Zhichao Yang, Zhifen Yang, Zhigang Yang, Zhihang Yang, Zhihong Yang, Zhikuan Yang, Zhikun Yang, Zhimin Yang, Zhiming Yang, Zhiqiang Yang, Zhitao Yang, Zhiwei Yang, Zhixin Yang, Zhiyan Yang, Zhiyong Yang, Zhiyou Yang, Zhiyuan Yang, Zhongan Yang, Zhongfang Yang, Zhonghua Yang, Zhonghui Yang, Zhongli Yang, Zhongshu Yang, Zhongzhou Yang, Zhou Yang, Zhuliang Yang, Zhuo Yang, Zhuoya Yang, Zhuoyu Yang, Zi F Yang, Zi Yang, Zi-Han Yang, Zi-Wei Yang, Zicong Yang, Zifeng Yang, Zihan Yang, Ziheng Yang, Zijiang Yang, Zishan Yang, Zixia Yang, Zixuan Yang, Ziying Yang, Ziyou Yang, Ziyu Yang, Zong-de Yang, Zongfang Yang, Zongyu Yang, Zunxian Yang, Zuozhen Yang
articles
Haruhiko Asakawa, Hui-Ju Yang, Takaharu G Yamamoto +7 more · 2014 · Nucleus (Austin, Tex.) · added 2026-04-24
The nuclear pore complex (NPC) is an enormous proteinaceous complex composed of multiple copies of about 30 different proteins called nucleoporins. In this study, we analyzed the composition of the NP Show more
The nuclear pore complex (NPC) is an enormous proteinaceous complex composed of multiple copies of about 30 different proteins called nucleoporins. In this study, we analyzed the composition of the NPC in the model organism Schizosaccharomyces pombe using strains in which individual nucleoporins were tagged with GFP. We identified 31 proteins as nucleoporins by their localization to the nuclear periphery. Gene disruption analysis in previous studies coupled with gene disruption analysis in the present study indicates that 15 of these nucleoporins are essential for vegetative cell growth and the other 16 nucleoporins are non-essential. Among the 16 non-essential nucleoporins, 11 are required for normal progression through meiosis and their disruption caused abnormal spore formation or poor spore viability. Based on fluorescence measurements of GFP-fused nucleoporins, we estimated the composition of the NPC in S. pombe and found that the organization of the S. pombe NPC is largely similar to that of other organisms; a single NPC was estimated as being 45.8-47.8 MDa in size. We also used fluorescence measurements of single NPCs and quantitative western blotting to analyze the composition of the Nup107-Nup160 subcomplex, which plays an indispensable role in NPC organization and function. Our analysis revealed low amounts of Nup107 and Nup131 and high amounts of Nup132 in the Nup107-Nup160 subcomplex, suggesting that the composition of this complex in S. pombe may differ from that in S. cerevisiae and humans. Comparative analysis of NPCs in various organisms will lead to a comprehensive understanding of the functional architecture of the NPC. Show less
no PDF DOI: 10.4161/nucl.28487
NUP160
Fengliang Wang, Yafang Yang, Ziyi Fu +6 more · 2014 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Breast cancer has been considered to be a multifactorial disease with a wide array of well-characterized gene mutations and chromosomal abnormalities. However, it is becoming evident that the onset or Show more
Breast cancer has been considered to be a multifactorial disease with a wide array of well-characterized gene mutations and chromosomal abnormalities. However, it is becoming evident that the onset or development of breast cancer also depends on epigenetic factors, although the mechanisms have not been fully elucidated. We performed a genome-wide analysis of DNA methylation of breast carcinomatous tissues and paired normal tissues to examine the differences in methylation between them. Methylation-specific polymerase chain reaction (MSP) was used to validate the hypermethylated genes screened out by DNA methylation microarray. We found that hypomethylation and hypermethylation occurred in 2753 and 1795 genes, respectively, in breast carcinomatous tissues. Meanwhile, gene ontology analysis and ingenuity pathway analysis revealed the function and pathway of several genes whose methylation status was altered in breast carcinomatous tissues. In addition, we investigated the promoter methylation status of four genes in breast carcinomatous tissue and paired normal tissues (n=30) by MSP. Promoter hypermethylation of CRABP1, HOXB13, IFNGR2, and PIK3C3 was found in 37% (11/30), 23% (7/30), 17% (5/30), and 2% (2/30) of the carcinomas, respectively. Mutation of these four important genes was critical to many types of cancer. Our results suggest that DNA methylation mechanisms may be involved in regulating the occurrence and development of breast cancer. Show less
no PDF DOI: 10.1016/j.biopha.2014.07.014
PIK3C3
Zhen Lu, Maria T Baquero, Hailing Yang +7 more · 2014 · Autophagy · added 2026-04-24
DIRAS3 is an imprinted tumor suppressor gene that is downregulated in 60% of human ovarian cancers. Re-expression of DIRAS3 at physiological levels inhibits proliferation, decreases motility, induces Show more
DIRAS3 is an imprinted tumor suppressor gene that is downregulated in 60% of human ovarian cancers. Re-expression of DIRAS3 at physiological levels inhibits proliferation, decreases motility, induces autophagy, and regulates tumor dormancy. Functional inhibition of autophagy with choroquine in dormant xenografts that express DIRAS3 significantly delays tumor regrowth after DIRAS3 levels are reduced, suggesting that autophagy sustains dormant ovarian cancer cells. This study documents a newly discovered role for DIRAS3 in forming the autophagosome initiation complex (AIC) that contains BECN1, PIK3C3, PIK3R4, ATG14, and DIRAS3. Participation of BECN1 in the AIC is inhibited by binding of BECN1 homodimers to BCL2. DIRAS3 binds BECN1, disrupting BECN1 homodimers and displacing BCL2. Binding of DIRAS3 to BECN1 increases the association of BECN1 with PIK3C3 and ATG14, facilitating AIC activation. Amino acid starvation of cells induces DIRAS3 expression, reduces BECN1-BCL2 interaction and promotes autophagy, whereas DIRAS3 depletion blocks amino acid starvation-induced autophagy. In primary ovarian cancers, punctate expression of DIRAS3, BECN1, and the autophagic biomarker MAP1LC3 are highly correlated (P<0.0001), underlining the clinical relevance of these mechanistic studies. Punctate expression of DIRAS3 and MAP1LC3 was detected in only 21-23% of primary ovarian cancers but in 81-84% of tumor nodules found on the peritoneal surface at second-look operations following primary chemotherapy. This reflects a 4-fold increase (P<0.0001) in autophagy between primary disease and post-treatment recurrence. We suggest that DIRAS3 not only regulates the AIC, but induces autophagy in dormant, nutrient-deprived ovarian cancer cells that remain after conventional chemotherapy, facilitating their survival. Show less
no PDF DOI: 10.4161/auto.28577
PIK3C3
Binbing Ling, Lifeng Chen, Qiang Liu +1 more · 2014 · BioMed research international · added 2026-04-24
Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in cons Show more
Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68 ≤ r ≤ 1.0) were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis. Show less
no PDF DOI: 10.1155/2014/253804
PIK3C3
Yanchao Jiang, Haibo Wang, David Culp +6 more · 2014 · Investigative ophthalmology & visual science · added 2026-04-24
To determine whether knockdown of Müller cell-derived VEGFA-splice variant, VEGF164, which is upregulated in the rat retinopathy of prematurity (ROP) model, safely inhibits intravitreal neovasculariza Show more
To determine whether knockdown of Müller cell-derived VEGFA-splice variant, VEGF164, which is upregulated in the rat retinopathy of prematurity (ROP) model, safely inhibits intravitreal neovascularization (IVNV). Short hairpin RNAs for VEGF164 (VEGF164.shRNAs) or luciferase.shRNA control were cloned into lentivectors with CD44 promoters that specifically target Müller cells. Knockdown efficiency, off-target effects, and specificity were tested in HEK reporter cell lines that expressed green fluorescent protein (GFP)-tagged VEGF164 or VEGF120 with flow cytometry or in rat Müller cells (rMC-1) by real-time PCR. In the rat oxygen-induced retinopathy (OIR) ROP model, pups received 1 μL subretinal lentivector-driven luciferase.shRNA, VEGFA.shRNA, or VEGF164.shRNA at postnatal day 8 (P8). Analyses at P18 and P25 included: IVNV and avascular retina (AVA); retinal and serum VEGF (ELISA); density of phosphorylated VEGFR2 (p-VEGFR2) in lectin-labeled retinal endothelial cells (ECs; immunohistochemistry); TUNEL staining and thickness of inner nuclear (INL) and outer nuclear layers (ONL) in retinal cryosections; and pup weight gain. In HEK reporter and in rMC-1 cells and in comparison to lucifferase.shRNA, VEGFA.shRNA reduced both VEGF120 and VEGF164, but VEGF164.shRNA only reduced VEGF164 and not VEGF120. Compared with luciferase.shRNA, VEGFA.shRNA and VEGF164.shRNA reduced retinal VEGF and IVNV without affecting AVA at P18 and P25. At P25, VEGF164.shRNA more effectively maintained IVNV inhibition than VEGFA.shRNA. VEGFA.shRNA and VEGF164.shRNA reduced pVEGFR2 in retinal ECs at P18, but VEGFA.shRNA increased it at P25. VEGFA.shRNA increased TUNEL+ cells at P18 and decreased ONL thickness at P18 and P25. VEGFA.shRNA and VEGF164.shRNA did not affect pup weight gain and serum VEGF. Short hairpin RNA to Müller cell VEGF164 maintained long-term inhibition of IVNV and limited cell death compared with shRNA to VEGFA. Show less
no PDF DOI: 10.1167/iovs.13-13755
RMC1
Xiaomu Kong, Xuelian Zhang, Qi Zhao +20 more · 2014 · PloS one · PLOS · added 2026-04-24
Obesity is a well-known risk factor for type 2 diabetes. Genome-wide association studies have identified a number of genetic loci associated with obesity. The aim of this study is to examine the contr Show more
Obesity is a well-known risk factor for type 2 diabetes. Genome-wide association studies have identified a number of genetic loci associated with obesity. The aim of this study is to examine the contribution of obesity-related genomic loci to type 2 diabetes in a Chinese population. We successfully genotyped 18 obesity-related single nucleotide polymorphisms among 5338 type 2 diabetic patients and 4663 controls. Both individual and joint effects of these single nucleotide polymorphisms on type 2 diabetes and quantitative glycemic traits (assessing β-cell function and insulin resistance) were analyzed using logistic and linear regression models, respectively. Two single nucleotide polymorphisms near MC4R and GNPDA2 genes were significantly associated with type 2 diabetes before adjusting for body mass index and waist circumference (OR (95% CI) = 1.14 (1.06, 1.22) for the A allele of rs12970134, P = 4.75×10(-4); OR (95% CI) = 1.10 (1.03, 1.17) for the G allele of rs10938397, P = 4.54×10(-3)). When body mass index and waist circumference were further adjusted, the association of MC4R with type 2 diabetes remained significant (P = 1.81×10(-2)) and that of GNPDA2 was attenuated (P = 1.26×10(-1)), suggesting the effect of the locus including GNPDA2 on type 2 diabetes may be mediated through obesity. Single nucleotide polymorphism rs2260000 within BAT2 was significantly associated with type 2 diabetes after adjusting for body mass index and waist circumference (P = 1.04×10(-2)). In addition, four single nucleotide polymorphisms (near or within SEC16B, BDNF, MAF and PRL genes) showed significant associations with quantitative glycemic traits in controls even after adjusting for body mass index and waist circumference (all P values<0.05). This study indicates that obesity-related genomic loci were associated with type 2 diabetes and glycemic traits in the Han Chinese population. Show less
no PDF DOI: 10.1371/journal.pone.0104486
SEC16B
Alison B Kohan, Fei Wang, Xiaoming Li +6 more · 2013 · American journal of physiology. Gastrointestinal and liver physiology · added 2026-04-24
Apolipoprotein A-IV (apoA-IV) is synthesized by the intestine and secreted when dietary fat is absorbed and transported into lymph associated with chylomicrons. We have recently demonstrated that loss Show more
Apolipoprotein A-IV (apoA-IV) is synthesized by the intestine and secreted when dietary fat is absorbed and transported into lymph associated with chylomicrons. We have recently demonstrated that loss of apoA-IV increases chylomicron size and delays its clearance from the blood. There is still uncertainty, however, about the precise role of apoA-IV on the transport of dietary fat from the intestine into the lymph. ApoA-IV knockout (KO) mice do not have a gross defect in dietary lipid absorption, as measured by oral fat tolerance and fecal fat measurements. Here, using the in vivo lymph fistula mouse model, we show that the cumulative secretion of triglyceride (TG) into lymph in apoA-IV KO mice is very similar to that of wild-type (WT) mice. However, the apoA-IV KO mice do have subtle changes in TG accumulation in the intestinal mucosa during a 6-h continuous, but not bolus, infusion of lipid. There are no changes in the ratio of esterified to free fatty acids in the intestinal mucosa of the apoA-IV KO, however. When we extended these findings, by giving a higher dose of lipid (6 μmol/h) and for a longer infusion period (8 h), we found no effect of apoA-IV KO on intestinal TG absorption. This higher lipid infusion most certainly stresses the intestine, as we see a drastically lower absorption of TG (in both WT and KO mice); however, the loss of A-IV does not exacerbate this effect. This supports our hypothesis that apoA-IV is not required for TG absorption in the intestine. Our data suggest that the mechanisms by which the apoA-IV KO intestine responds to intestinal lipid may not be different from their WT counterparts. We conclude that apoA-IV is not required for normal lymphatic transport of TG. Show less
no PDF DOI: 10.1152/ajpgi.00409.2012
APOA4
Y T Hui, Y Q Yang, R Y Liu +6 more · 2013 · Genetics and molecular research : GMR · added 2026-04-24
Apolipoprotein A5 (APOA5) and C3 (APOC3) genes are involved in the PPAR lipid metabolism pathway and thus associated with elevated triglyceride levels. However, whether APOA5 and APOC3 genetic polymor Show more
Apolipoprotein A5 (APOA5) and C3 (APOC3) genes are involved in the PPAR lipid metabolism pathway and thus associated with elevated triglyceride levels. However, whether APOA5 and APOC3 genetic polymorphisms affect intramuscular fat deposition and other meat quality traits remains unknown in pigs. One hundred and seventy-one Kele pigs were sampled to investigate genetic variants in the APOA5 and APOC3 genes and their association with seven pork quality traits. We identified 5 single nucleotide polymorphisms (SNPs) in the promoter region of the APOA5 gene and 17 SNPs in the APOC3 gene. Linkage disequilibrium analysis revealed 5 complete linkage disequilibria among these 22 SNPs. We found that 10 SNPs were significantly correlated with meat quality traits, including the mutation A5/-769 in the APOA5 gene, which was significantly associated with cooked weight percentage, and 9 SNPs in the APOC3 gene that were significantly associated with drip loss rate, meat color value of longissimus dorsi muscle and shear force. Therefore, these SNP markers will be useful for marker-assisted selection for improved pork quality. Show less
no PDF DOI: 10.4238/2013.September.13.8
APOA5
Jianqing Zhou, Limin Xu, Rong Stephanie Huang +10 more · 2013 · Molecular medicine reports · added 2026-04-24
Previous studies have shown that apolipoprotein A5 (APOA5) gene variants are genetic determinants of the concentration of triglycerides, which are a known risk factor for coronary heart disease (CHD). Show more
Previous studies have shown that apolipoprotein A5 (APOA5) gene variants are genetic determinants of the concentration of triglycerides, which are a known risk factor for coronary heart disease (CHD). Using the standardized coronary angiography method, 290 CHD patients and 198 non‑CHD controls were recruited from Ningbo Lihuili Hospital. In addition, 331 unrelated healthy volunteers were recruited as healthy controls from Ningbo Ximen Community residents. Three variants of the APOA5 gene, S19W, ‑1131T>C and 553G>T, were analyzed for their association with CHD. Under a dominant inheritance model, ‑1131CT>C was shown to be a CHD risk factor (P=0.030; OR, 1.422; 95% CI, 1.036‑1.952). The single nucleotide polymorphism, 553G>T, was found to correlate with the severity of CHD in males (P=0.032). Meta‑analysis showed that ‑1131T>C was significantly associated with CHD (P<0.0001). By contrast, negative correlations with CHD were observed for S19W and 553G>T. In the present case‑control study, APOA5 gene variants were not found to correlate with the risk of CHD in the populations studied; however, ‑1131CT>C was shown to be a CHD risk factor under a dominant inheritance model. Meta‑analysis showed a significant contribution of ‑1131T>C to the risk of CHD, implying an ethnic difference in APOA5 gene variants. Show less
📄 PDF DOI: 10.3892/mmr.2013.1642
APOA5
Shiyin Long, Zhijun Chen, Ying Han +4 more · 2013 · Clinical biochemistry · Elsevier · added 2026-04-24
This study aims to examine the possible associations between high density lipoprotein (HDL) subclass distribution and APOA5-1131T>C polymorphism in hypertriglyceridemia. The distribution of HDL subcla Show more
This study aims to examine the possible associations between high density lipoprotein (HDL) subclass distribution and APOA5-1131T>C polymorphism in hypertriglyceridemia. The distribution of HDL subclasses was quantified by 2-dimensional electrophoresis in conjunction with immunodetection method. The APOA5-1131T>C polymorphism was identified in 95 hypertriglyceridemic (HTG) patients and 102 healthy subjects by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP). The APOA5-1131C (C) allele frequency was higher in the HTG group than in the control group. Plasma triglycerides (TG) were significantly higher and apoA5 was significantly lower in patients with the C allele when compared to patients with the APOA5-1131T (T) allele, even more dramatically so in the APOA5-1131CC homozygote. In both the HTG group and the control group, the frequency of the C allele was positively correlated with levels of TG, total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) and apolipoprotein B100 (apoB100), and negatively correlated with levels of high density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (apoA1) and apolipoprotein A5 (apoA5) (P<0.001). In all subjects, the frequency of the C allele was positively correlated with the level of small-sized HDL (preβ(1)-HDL and HDL(3a)), and negatively correlated with levels of HDL(2a) and HDL(2b). Changes in HDL subclass distributions in HTG may be related to the APOA5-1131T>C polymorphism. This polymorphism leads to a general shift towards smaller-sized HDL. Show less
no PDF DOI: 10.1016/j.clinbiochem.2013.03.003
APOA5
Rui-Xing Yin, Yi-Yang Li, Jin-Zhen Wu +4 more · 2013 · Alcoholism, clinical and experimental research · Blackwell Publishing · added 2026-04-24
The interactions between apolipoprotein (Apo) A1/C3/A5 haplotypes and alcohol consumption on serum lipid profiles have not been previously explored. The present study was undertaken to detect the poly Show more
The interactions between apolipoprotein (Apo) A1/C3/A5 haplotypes and alcohol consumption on serum lipid profiles have not been previously explored. The present study was undertaken to detect the polymorphisms of ApoA1 -75 bp G>A (rs1799837), ApoC3 3238C>G (rs5128), ApoA5 -1131T>C (rs662799), ApoA5 c.553G>T (rs2075291), and ApoA5 c.457G>A (rs3135507) and the interactions between their haplotypes and alcohol consumption on serum lipid levels. Genotyping was performed in 1,030 unrelated subjects (516 nondrinkers and 514 drinkers) aged 15 to 89. The interactions between ApoA1/C3/A5 haplotypes and alcohol consumption on serum lipid levels were detected by factorial regression analysis after controlling for potential confounders. The frequencies of ApoC3 3238 CG/GG genotypes and ApoA1 -75 bp A allele in nondrinkers were higher in females than in males (p < 0.05). The frequencies of ApoC3 3238 CG/GG genotypes and G allele in drinkers were higher in females than in males (p < 0.05). The frequencies of ApoA1 -75 bp GA/AA genotypes and A allele in males were higher, and those of ApoC3 3238 CG/GG genotypes were lower in drinkers than in nondrinkers (p < 0.05 to 0.01). The frequency of ApoC3 3238 GG genotype in male drinkers was also higher in ≥25 g/d than in <25 g/d subgroups (p < 0.05). There were 11 haplotypes with a frequency >1% in our study population. The haplotypes of G-G-T-C-G (in the order of c.553G>T, c.457G>A, -1131T>C, 3238C>G, and -75 bp G>A), G-G-T-C-A, and G-G-C-G-G were shown consistent interactions with alcohol consumption to increase serum total cholesterol, high-density lipoprotein cholesterol (HDL-C), and ApoA1 levels (p < 0.05 to 0.001). The interactions between G-G-T-G-G (HDL-C and ApoA1), G-G-C-C-A (ApoA1), G-A-T-C-G (triglyceride), G-G-T-C-G (ApoA1/ApoB ratio), and G-G-C-G-G (ApoB) haplotypes and alcohol consumption on serum lipid levels were also detected (p < 0.05 to 0.001); the levels of these serum lipid parameters were significantly higher in drinkers than in nondrinkers. The differences in serum lipid parameters between drinkers and nondrinkers might partly result from different interactions between the ApoA1/C3/A5 haplotypes and alcohol consumption. Show less
no PDF DOI: 10.1111/j.1530-0277.2012.01918.x
APOA5
W-M Yao, H-F Zhang, Z-Y Zhu +11 more · 2013 · Journal of human hypertension · Nature · added 2026-04-24
Elevated levels of circulating triglycerides and increased arterial stiffness are associated with cardiovascular disease. Numerous studies have reported an association between levels of circulating tr Show more
Elevated levels of circulating triglycerides and increased arterial stiffness are associated with cardiovascular disease. Numerous studies have reported an association between levels of circulating triglycerides and arterial stiffness. We used Mendelian randomization to test whether this association is causal. We investigated the association between circulating triglyceride levels, the apolipoprotein A-V (ApoA5) -1131T>C single nucleotide polymorphism and brachial-ankle pulse wave velocity (baPWV) by examining data from 4421 subjects aged 18-74 years who were recruited from the Chinese population. baPWV was significantly associated with the levels of circulating triglycerides after adjusting for age, sex, body mass index (BMI), systolic blood pressure, heart rate, waist-to-hip ratio, antihypertensive treatment and diabetes mellitus status. The -1131C allele was associated with a 5% (95% confidence interval 3-8%) increase in circulating triglycerides (adjusted for age, sex, BMI, waist-to-hip ratio, diabetes mellitus and antihypertensive treatment). Instrumental variable analysis showed that genetically elevated levels of circulating triglycerides were not associated with increased baPWV. These results do not support the hypothesis that levels of circulating triglycerides have a causal role in the development of arterial stiffness. Show less
no PDF DOI: 10.1038/jhh.2012.23
APOA5
Lian-he Yang, Yang Han, Guang Li +10 more · 2013 · BMC cancer · BioMed Central · added 2026-04-24
We previously reported that Axin1 (Axin) is down-regulated in many cases of lung cancer, and X-ray irradiation increased Axin expression and inhibited lung cancer cells. The mechanisms, however, were Show more
We previously reported that Axin1 (Axin) is down-regulated in many cases of lung cancer, and X-ray irradiation increased Axin expression and inhibited lung cancer cells. The mechanisms, however, were not clear. Four lung cancer cell lines were used to detect the methylation status of Axin with or without X-ray treatment. Real-time PCR was used to quantify the expression of Axin, and western blot analysis was applied to measure protein levels of Axin, β-catenin, Cyclin D1, MMP-7, DNMTS, MeCP2 and acetylated histones. Flow cytometric analysis, colony formation assay, transwell assay and xenograft growth experiment were used to study the biological behavior of the cells with hypermethylated or unmethylated Axin gene after X-ray treatment. Hypermethylated Axin gene was detected in 2 of 4 cell lines, and it correlated inversely with Axin expression. X-ray treatment significantly up-regulated Axin expression in H446 and H157 cells, which possess intrinsic hypermethylation of the Axin gene (P<0.01), but did not show up-regulation in LTE and H460 cells, which have unmethylated Axin gene. 2Gy X-ray significantly reduced colony formation (from 71% to 10.5%) in H157 cells, while the reduction was lower in LTE cells (from 71% to 20%). After X-ray irradiation, xenograft growth was significantly decreased in H157 cells (from 1.15 g to 0.28 g) in comparison with LTE cells (from 1.06 g to 0.65 g). Significantly decreased cell invasiveness and increased apoptosis were also observed in H157 cells treated with X-ray irradiation (P<0.01). Down-regulation of DNMTs and MeCP2 and up-regulation of acetylated histones could be detected in lung cancer cells. X-ray-induced inhibition of lung cancer cells may be mediated by enhanced expression of Axin via genomic DNA demethylation and histone acetylation. Lung cancer cells with a different methylation status of the Axin gene showed different radiosensitivity, suggesting that the methylation status of the Axin gene may be one important factor to predict radiosensitivity of the tumor. Show less
📄 PDF DOI: 10.1186/1471-2407-13-368
AXIN1
Dan Xu, Fu Yang, Ji-hang Yuan +6 more · 2013 · Hepatology (Baltimore, Md.) · Wiley · added 2026-04-24
In recent years, long noncoding RNAs (lncRNAs) have been investigated as a new class of regulators of biological function. A recent study reported that lncRNAs control cell proliferation in hepatocell Show more
In recent years, long noncoding RNAs (lncRNAs) have been investigated as a new class of regulators of biological function. A recent study reported that lncRNAs control cell proliferation in hepatocellular carcinoma (HCC). However, the role of lncRNAs in liver regeneration and the overall mechanisms remain largely unknown. To address this issue, we carried out a genome-wide lncRNA microarray analysis during liver regeneration in mice after 2/3 partial hepatectomy (PH) at various timepoints. The results revealed differential expression of a subset of lncRNAs, notably a specific differentially expressed lncRNA associated with Wnt/β-catenin signaling during liver regeneration (an lncRNA associated with liver regeneration, termed lncRNA-LALR1). The functions of lncRNA-LALR1 were assessed by silencing and overexpressing this lncRNA in vitro and in vivo. We found that lncRNA-LALR1 enhanced hepatocyte proliferation by promoting progression of the cell cycle in vitro. Furthermore, we showed that lncRNA-LALR1 accelerated mouse hepatocyte proliferation and cell cycle progression during liver regeneration in vivo. Mechanistically, we discovered that lncRNA-LALR1 facilitated cyclin D1 expression through activation of Wnt/β-catenin signaling by way of suppression of Axin1. In addition, lncRNA-LALR1 inhibited the expression of Axin1 mainly by recruiting CTCF to the AXIN1 promoter region. We also identified a human ortholog RNA of lncRNA-LALR1 (lncRNA-hLALR1) and found that it was expressed in human liver tissues. lncRNA-LALR1 promotes cell cycle progression and accelerates hepatocyte proliferation during liver regeneration by activating Wnt/β-catenin signaling. Pharmacological intervention targeting lncRNA-LALR1 may be therapeutically beneficial in liver failure and liver transplantation by inducing liver regeneration. Show less
no PDF DOI: 10.1002/hep.26361
AXIN1
Lian-he Yang, Hong-tao Xu, Qing-Chang Li +5 more · 2013 · Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · Springer · added 2026-04-24
Axin is an important negative regulator of Wnt pathway. We have reported that reduced expression of Axin could be detected in lung cancer tissues, but the mechanism is not clear. By analyzing the geno Show more
Axin is an important negative regulator of Wnt pathway. We have reported that reduced expression of Axin could be detected in lung cancer tissues, but the mechanism is not clear. By analyzing the genomic sequence, we note that Axin gene promoter is rich in CpGs. Little is known about the methylation status of Axin gene in lung cancer. So, nested MSP and RT-PCR were used to study the methylation status and mRNA expression of Axin gene in lung cancer tissues and cell lines. The results showed that hypermethylated Axin gene promoter and reduced mRNA expression level of Axin could be detected in lung cancer tissues but not in their paired autologous normal lung tissues (P < 0.01). The hypermethylated Axin gene promoter significantly correlated with the degree of differentiation (P = 0.03), lymph node metastasis (P = 0.048) and TNM classifications (P = 0.032). Demethylation reagent 5-aza-2-deoxycytidine significantly up-regulate Axin expression in BE1 cells (with hypermethylated Axin gene promoter) but not in H460 cells (with unmethylated Axin gene promoter). MTT (3(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) and transwell matrigel invasion assay showed that 5-aza-2-deoxycytidine treatment inhibited cell growth and invasion more significantly in BE1 cells than that in H460 cells. Our data indicate that hypermethylated Axin gene significantly correlates with the progression of lung cancer and might serve as a new target of clinical therapy for lung cancer patients in future. Show less
no PDF DOI: 10.1007/s13277-012-0604-z
AXIN1
Fenyong Sun, Qingyuan Yang, Wenhao Weng +5 more · 2013 · Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · Wiley · added 2026-04-24
Mouse embryonic fibroblasts (MEFs) differentiate into fully functional chondrocytes in response to bone morphogenetic protein-2 (BMP-2). However, the comprehensive proteomic aspect of BMP-2-induced ch Show more
Mouse embryonic fibroblasts (MEFs) differentiate into fully functional chondrocytes in response to bone morphogenetic protein-2 (BMP-2). However, the comprehensive proteomic aspect of BMP-2-induced chondrogenesis remains unknown. We took advantage of quantitative proteomic analysis based on isobaric tag for relative and absolute quantitation (iTRAQ) and on-line 2D nano-liquid chromatography/tandem mass spectrometry (LC/MS/MS) to identify proteins differentially expressed during BMP-2-induced chondrogenic differentiation of MEFs. We found 85 downregulated proteins, and ingenuity pathways analysis (IPA) revealed a protein-protein network with chromodomain-helicase-DNA-binding protein 4 (Chd4) in the center. Chromatin immunoprecipitation (ChIP) and nuclease hypersensitivity assays showed that Chd4, interacting with Hdac1/2, cooperates with its related proteins Kap1 and Cbx1 to bind at -207/-148 of the Sox9 promoter. We also provided evidence that let-7a targets the 3'UTR of Chd4 to promote chondrogenesis of MEFs. Together, our findings indicate that BMP-2 induced the upregulation of let-7a, targeting Chd4 and positively controlling the chondrogenic differentiation of MEFs. These findings illustrate epigenetic regulation of the chondrogenic differentiation process and also expand the understanding of the involved intracellular mechanisms. Show less
no PDF DOI: 10.1002/jbmr.1932
CBX1
Yang Yang, Xiao-Peng Jing, Shou-Peng Zhang +9 more · 2013 · PloS one · PLOS · added 2026-04-24
Zinc ions highly concentrate in hippocampus and play a key role in modulating spatial learning and memory. At a time when dietary fortification and supplementation of zinc have increased the zinc cons Show more
Zinc ions highly concentrate in hippocampus and play a key role in modulating spatial learning and memory. At a time when dietary fortification and supplementation of zinc have increased the zinc consuming level especially in the youth, the toxicity of zinc overdose on brain function was underestimated. In the present study, weaning ICR mice were given water supplemented with 15 ppm Zn (low dose), 60 ppm Zn (high dose) or normal lab water for 3 months, the behavior and brain zinc homeostasis were tested. Mice fed high dose of zinc showed hippocampus-dependent memory impairment. Unexpectedly, zinc deficiency, but not zinc overload was observed in hippocampus, especially in the mossy fiber-CA3 pyramid synapse. The expression levels of learning and memory related receptors and synaptic proteins such as NMDA-NR2A, NR2B, AMPA-GluR1, PSD-93 and PSD-95 were significantly decreased in hippocampus, with significant loss of dendritic spines. In keeping with these findings, high dose intake of zinc resulted in decreased hippocampal BDNF level and TrkB neurotrophic signaling. At last, increasing the brain zinc level directly by brain zinc injection induced BDNF expression, which was reversed by zinc chelating in vivo. These results indicate that zinc plays an important role in hippocampus-dependent learning and memory and BDNF expression, high dose supplementation of zinc induces specific zinc deficiency in hippocampus, which further impair learning and memory due to decreased availability of synaptic zinc and BDNF deficit. Show less
📄 PDF DOI: 10.1371/journal.pone.0055384
DLG2
Li Zhou, Meian He, Zengnan Mo +40 more · 2013 · PloS one · PLOS · added 2026-04-24
Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several Show more
Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52 × 10(-16), 1.38 × 10(-6) and 5.59 × 10(-9), respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population. Show less
📄 PDF DOI: 10.1371/journal.pone.0082420
DOCK7
Eun Kyung Lee, Ki-Wook Chung, Sun Kyung Yang +4 more · 2013 · Anticancer research · added 2026-04-24
The purpose of this study was to identify the DNA methylation status of the mitogen-activated protein kinase (MAPK) signal-inhibiting genes dual-specificity phosphatase 4 (DUSP4) and 6 (DUSP6); and se Show more
The purpose of this study was to identify the DNA methylation status of the mitogen-activated protein kinase (MAPK) signal-inhibiting genes dual-specificity phosphatase 4 (DUSP4) and 6 (DUSP6); and serpin peptidase inhibitor A member 5 (SERPINA5) in thyroid cancer. Using 76 papillary thyroid cancer(PTC) tissues and three thyroid cancer cell lines (TPC1, WRO82-1 and XTC), the expression of three genes and DNA methylation were determined by reverse transcription-PCR and methylation-specific PCR. In all cell lines, the expression of DUSP4 and DUSP6 increased; the corresponding gene promoters were unmethylated. However, SERPINA5 gene expression decreased and SERPINA5 DNA was methylated in the TPC1 cell line. With the de-methylating agent 5'-aza-2'-deoxycytidine, SERPINA5 gene expression was restored. In 82.9% of PTC tissues (63/76), the SERPINA5 DNA promoter was methylated, which was associated with a higher v-raf murine sarcoma viral oncogene homolog B1(BRAF) mutation rate in PTC tissues based on multivariate regression (odds ratio=3.573; 95% confidence interval=1.122-11.379; p=0.031). The expression of the MAPK signal-inhibiting gene SERPINA5 decreased in the TPC1 cell line, SERPINA5 expression was regulated by DNA methylation, which was associated with a higher BRAF mutation rate in PTC. Show less
no PDF
DUSP6
Feng Zhang, Jinlong Liang, Xiong Guo +9 more · 2013 · PloS one · PLOS · added 2026-04-24
Multiple osteochondromas (MO) is an inherited skeletal disorder, and the molecular mechanism of MO remains elusive. Exome sequencing has high chromosomal coverage and accuracy, and has recently been s Show more
Multiple osteochondromas (MO) is an inherited skeletal disorder, and the molecular mechanism of MO remains elusive. Exome sequencing has high chromosomal coverage and accuracy, and has recently been successfully used to identify pathogenic gene mutations. In this study, exome sequencing followed by Sanger sequencing validation was first used to screen gene mutations in two representative MO patients from a Chinese family. After filtering the data from the 1000 Genome Project and the dbSNP database (build 132), the detected candidate gene mutations were further validated via Sanger sequencing of four other members of the same MO family and 200 unrelated healthy subjects. Immunohistochemisty and multiple sequence alignment were performed to evaluate the importance of the identified causal mutation. A novel frameshift mutation, c.1457insG at codon 486 of exon 6 of EXT1 gene, was identified, which truncated the glycosyltransferase domain of EXT1 gene. Multiple sequence alignment showed that codon 486 of EXT1 gene was highly conserved across various vertebrates. Immunohistochemisty demonstrated that the chondrocytes with functional EXT1 in MO were less than those in extragenetic solitary chondromas. The novel c.1457insG deleterious mutation of EXT1 gene reported in this study expands the causal mutation spectrum of MO, and may be helpful for prenatal genetic screening and early diagnosis of MO. Show less
📄 PDF DOI: 10.1371/journal.pone.0072316
EXT1
Yinan Wang, XiaoYan Yang, Sadako Yamagata +2 more · 2013 · Molecular and cellular biochemistry · Springer · added 2026-04-24
To know the involvement of glycosaminoglycans (GAGs) in the metastasis of mouse FBJ osteosarcoma cells, N(α)-lauroyl-O-(β-D-xylopyranosyl)-L-serinamide (Xyl-Ser-C12), which initiates elongation of GAG Show more
To know the involvement of glycosaminoglycans (GAGs) in the metastasis of mouse FBJ osteosarcoma cells, N(α)-lauroyl-O-(β-D-xylopyranosyl)-L-serinamide (Xyl-Ser-C12), which initiates elongation of GAG chains using the glycan biosynthesis system in cells, was administered to FBJ cells with different metastatic capacities. Production of glycosylated products derived from Xyl-Ser-C12, especially heparan sulfate (HS) GAG-type oligosaccharides such as GalNAc-GlcA-GlcNAc-GlcA-Gal-Gal-Xyl-Ser-C12, was indicated in poorly metastatic FBJ-S1 cells more than in highly metastatic FBJ-LL cells by LC-MS. The results of RT-PCR revealed that HS synthases, Ext1 and Ext2, were expressed in FBJ-S1 cells more than in FBJ-LL cells. Furthermore, siRNA against Ext1 suppressed the expression of HS and enhanced the motility of FBJ-S1 cells. In addition, the expression of heparanase (HPSE) was enhanced in Ext-1-knockdown FBJ-S1 cells, and responsible for the increase in cell motility caused by the down-regulation of Ext1 expression. Our data provide the first evidence that Ext1 regulates the expression of HPSE and also indicated that levels of Ext1 and HPSE influenced the motility of FBJ cells. Show less
no PDF DOI: 10.1007/s11010-012-1475-8
EXT1
Kuan-Min Fang, Tzu-Chien Lin, Ti-Chun Chan +7 more · 2013 · Glia · Wiley · added 2026-04-24
CD133 (Prominin-1/AC133) is generally treated as a cell surface marker found on multipotent stem cells and tumor stem-like cells, and its biological function remains debated. Genetically modified rat Show more
CD133 (Prominin-1/AC133) is generally treated as a cell surface marker found on multipotent stem cells and tumor stem-like cells, and its biological function remains debated. Genetically modified rat glioma cell lines were generated by lentiviral gene delivery of human CD133 into rat C6 glioma cells (hCD133(+) -C6) or by infection of C6 cells with control lentivirus (mock-C6). Stable hCD133 expression promoted the self-renewal ability of C6-formed spheres with an increase in the expression of the stemness markers, Bmi-1 and SOX2. Akt phosphorylation, Notch-1 activation, and Notch-1 target gene expression (Hes-1, Hey1 and Hey2) were increased in hCD133(+) -C6 when compared to mock-C6. The inhibition of Akt phosphorylation, Notch-1 activation, and Hes-1 in hCD133(+) -C6 cells effectively suppressed their clonogenic ability, indicating that these factors are involved in expanding the growth of hCD133(+) -C6. An elevated expression of GTPase-activating protein 27 (Arhgap27) was detected in hCD133(+) -C6. A decline in the invasion of hCD133(+) -C6 by knockdown of Arhgap27 expression indicated the critical role of Arhgap27 in promoting cell migration of hCD133(+) -C6. In vivo study further showed that hCD133(+) -C6 formed aggressive tumors in vivo compared to mock-C6. Exposure of hCD133(+) -C6 to arsenic trioxide not only reduced Akt phosphorylation, Notch-1 activation and Hes-1 expression in vitro, but also inhibited their tumorigenicity in vivo. The results show that C6 glioma cells with stable hCD133 expression enhanced their stemness properties with increased Notch-1/Hes-1 signaling, Akt activation, and Arhgap27 action, which contribute to increased cell proliferation and migration of hCD133(+) -C6 in vitro, as well as progressive tumor formation in vivo. Show less
no PDF DOI: 10.1002/glia.22521
HEY2
Xiao-Yan Yang, Wen-Juan Wu, Cheng Yang +4 more · 2013 · Dermatology (Basel, Switzerland) · added 2026-04-24
Acne vulgaris is a very common skin disorder. Previous studies have indicated that genetic background factors play key roles in the onset of acne. Our previous investigation implicated several genes i Show more
Acne vulgaris is a very common skin disorder. Previous studies have indicated that genetic background factors play key roles in the onset of acne. Our previous investigation implicated several genes in the androgen metabolism pathway with acne vulgaris in the Han Chinese population. Thus, we further investigated genes and genetic variants that play important roles in this pathway for their relationship with the pathology of acne. In this study, a total of 610 subjects, including 403 acne patients and 207 healthy controls, were genotyped for 15 single-nucleotide polymorphisms in HSD3B1 and HSD17B3 genes. This study shows that rs6428829 in HSD3B1 was associated with acne vulgaris in Han patients from Southwest China, even after adjusting for age and sex. The GG genotype was associated with an increased risk of acne vulgaris (p < 0.05) and G allele carriers were associated with an increased risk of acne vulgaris (p < 0.05). In addition, the haplotype AAT in HSD3B1 significantly increased the risk of acne vulgaris in the case-control study (p < 0.05). Furthermore, for another gene in this pathway, HSD17B3, the haplotype H8 was significantly associated with an increased risk of acne vulgaris. Based on these analyses, our study indicates that the cutaneous androgen metabolism-regulated genes HSD3B1 and HSD17B3 increase the susceptibility to acne vulgaris in Han Chinese from Southwest China. Show less
no PDF DOI: 10.1159/000353581
HSD17B12
Yong Liang, Chenzhang Shi, Jun Yang +6 more · 2013 · International journal of molecular medicine · added 2026-04-24
Colonic paracellular permeability is regulated by various factors, including dynamics of the cytoskeleton. Recently, ACF7 has been found to play a critical role in cytoskeletal dynamics as an essentia Show more
Colonic paracellular permeability is regulated by various factors, including dynamics of the cytoskeleton. Recently, ACF7 has been found to play a critical role in cytoskeletal dynamics as an essential integrator. To elucidate the physiological importance of ACF7 and paracellular permeability, we conditionally knocked out ACF7 in the intestinal mucosa of mice. Histopathological findings indicated that ACF7 deficiency resulted in significant interstitial proliferation and columnar epithelial cell rearrangement. Decreased colonic paracellular permeability was detected using a Ussing chamber and the FITC-inulin method. In order to clarify the underlying mechanism, we further analyzed the expression levels of three important tight junction proteins. Downregulation of ZO-1, occludin and claudin-1 was identified. Immunofluorescence provided strong evidence that ZO-1, occludin and claudin-1 were weakly stained. We hypothesized that ACF7 regulates cytoskeleton dynamics to alter mucosal epithelial arrangement and colonic paracellular permeability. Show less
no PDF DOI: 10.3892/ijmm.2013.1284
MACF1
Fuman Qiu, Lei Yang, Wenxiang Fang +8 more · 2013 · Mutagenesis · Oxford University Press · added 2026-04-24
Mitogen/extracellular signal-regulated kinase-5 (MEK5)/extracellular signal-regulated protein kinase-5 (ERK5) pathway plays a pro-oncogenic role in tumourigenesis by anticell apoptosis, promoting cell Show more
Mitogen/extracellular signal-regulated kinase-5 (MEK5)/extracellular signal-regulated protein kinase-5 (ERK5) pathway plays a pro-oncogenic role in tumourigenesis by anticell apoptosis, promoting cell proliferation and differentiation in response to extracellular stimuli. As overexpressed MEK5/ERK5 is involved in the development of lung cancer, we hypothesised that the single nucleotide polymorphisms (SNPs) in MEK5 and ERK5 genes may influence gene expression and thus be associated with lung cancer risk. Five putative functional polymorphisms (rs3743353T>C, rs7172582C>T and rs2278076A>G of MEK5 and rs3866958G>T and rs2233083C>T of ERK5) were genotyped in two independent case-control studies with a total of 1559 lung cancer patients and 1679 controls in southern and eastern Chinese population. We found the rs3866958G>T of ERK5 was significantly associated with lung cancer risk, while other SNPs were not. Compared with the rs3866958TG/TT genotypes, the GG genotype conferred an increased risk of lung cancer (odds ratio = 1.30, 95% confidence interval = 1.12-1.51, P = 5.0×10(-4)), and this effect was more pronounced in smokers, accompanying with a significant interaction with smoking (P interaction = 0.013). The GG genotype also had significant higher mRNA levels of ERK5 in lung cancer tissues than TG/TT genotypes (P = 1.0×10(-4)); the luciferase reporter with the G allele showed significant higher transcription activities than the T allele, especially after the treatment with tobacco extract in vitro. Our data indicated that the functional polymorphism rs3866958G>T in ERK5 was associated with an increased lung cancer risk in smokers by virtue of the positive interaction with smoking on promoting the ERK5 expression, which might be a valuable indicator for predicting lung cancer risk in smokers. Show less
no PDF DOI: 10.1093/mutage/get033
MAP2K5
Lifang Wu, Hanbei Chen, Yemin Zhu +7 more · 2013 · The international journal of biochemistry & cell biology · Elsevier · added 2026-04-24
The glucose-responsive transcription factor carbohydrate responsive element binding protein (ChREBP) plays an important role in regulating glucose metabolism in support of anabolic synthesis in both h Show more
The glucose-responsive transcription factor carbohydrate responsive element binding protein (ChREBP) plays an important role in regulating glucose metabolism in support of anabolic synthesis in both hepatocytes and cancer cells. In order to further investigate the molecular mechanism by which ChREBP regulates transcription, we used a proteomic approach to identify proteins interacting with ChREBP. We found several potential ChREBP-interacting partners, one of which, flightless I homolog (FLII) was verified to interact and co-localize with ChREBP in HCT116 colorectal cancer and HepG2 hepatocellular carcinoma cells. FLII is a member of the gelsolin superfamily of actin-remodeling proteins and can function as a transcriptional co-regulator. The C-terminal 227 amino acid region of ChREBP containing the DNA-binding domain interacted with FLII. Both the N-terminal leucine-rich repeat (LRR) domain and C-terminal gelsolin homolog domain (GLD) of FLII interacted and co-localized with ChREBP. ChREBP and FLII localized in both the cytoplasm and nucleus of cancer cells. Glucose increased expression and nuclear localization of ChREBP, and had minimal effect on the level and distribution of FLII. FLII knockdown using siRNAs increased mRNA and protein levels of ChREBP-activated genes and decreased transcription of ChREBP-repressed genes in cancer cells. Conversely, FLII overexpression negatively regulated ChREBP-mediated transcription in cancer cells. Our findings suggest that FLII is a component of the ChREBP transcriptional complex and negatively regulates ChREBP function in cancer cells. Show less
no PDF DOI: 10.1016/j.biocel.2013.09.004
MLXIPL
Yilu Wang, Zhimin Wang, Qi Yang +11 more · 2013 · PloS one · PLOS · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) due to mutations in genes encoding sarcomere proteins is most commonly inherited as an autosomal dominant trait. Since nearly 50% of HCM cases occur in the absence of Show more
Hypertrophic cardiomyopathy (HCM) due to mutations in genes encoding sarcomere proteins is most commonly inherited as an autosomal dominant trait. Since nearly 50% of HCM cases occur in the absence of a family history, a recessive inheritance pattern may be involved. A pedigree was identified with suspected autosomal recessive transmission of HCM. Twenty-six HCM-related genes were comprehensively screened for mutations in the proband with targeted second generation sequencing, and the identified mutation was confirmed with bi-directional Sanger sequencing in all family members and 376 healthy controls. A novel missense mutation (c.1469G>T, p.Gly490Val) in exon 17 of MYBPC3 was identified. Two siblings with HCM were homozygous for this mutation, whereas other family members were either heterozygous or wild type. Clinical evaluation showed that both homozygotes manifested a typical HCM presentation, but none of others, including 5 adult heterozygous mutation carriers up to 71 years of age, had any clinical evidence of HCM. Our data identified a MYBPC3 mutation in HCM, which appeared autosomal recessively inherited in this family. The absence of a family history of clinical HCM may be due to not only a de novo mutation, but also recessive mutations that failed to produce a clinical phenotype in heterozygous family members. Therefore, consideration of recessive mutations leading to HCM is essential for risk stratification and genetic counseling. Show less
no PDF DOI: 10.1371/journal.pone.0067087
MYBPC3
Wen Liu, Wenling Liu, Dayi Hu +10 more · 2013 · The American journal of cardiology · Elsevier · added 2026-04-24
Hypertrophic cardiomyopathy (HC) is a hereditary heterogeneous cardiovascular disorder. Existing data have been of predominantly Caucasian samples, and a large study is needed in Chinese population. T Show more
Hypertrophic cardiomyopathy (HC) is a hereditary heterogeneous cardiovascular disorder. Existing data have been of predominantly Caucasian samples, and a large study is needed in Chinese population. The present study was intended to explore the genetic basis and clinical characteristics correlated with different genotypes in a large cohort of Chinese patients. Direct gene sequencing of β-myosin heavy chain (MYH7), myosin binding protein-C (MYBPC3), and cardiac troponin T (TNNT2) was performed in 136 unrelated Chinese HC patients. Clinical evaluations were conducted. In total, 32 mutations were identified in 36 patients (27%), including 10 novel ones. Distribution of mutations was 56% (MYBPC3), 31% (MYH7), and 13% (TNNT2), respectively. Double mutations were identified in 3% patients. The occurrence of HC-associated sarcomeric mutations was associated with an earlier age of onset, increased left ventricular hypertrophy, a higher incidence of syncope, previous family history, and sudden cardiac death. No statistical difference was identified in patients carrying MYBPC3 and MYH7 mutations with regard to clinical characteristics and outcomes. Patients with double mutations were associated with malignant progression in the study. In conclusion, MYBPC3 is the most predominant gene in HC. Multiple mutations are common in MYH7, MYBPC3, and TNNT2. The present study suggests a large diversity of HC and a prognostic role of genotype. Show less
no PDF DOI: 10.1016/j.amjcard.2013.04.021
MYBPC3
Bei Zhao, Juan Li, Fan Yang +1 more · 2013 · Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · added 2026-04-24
To determine the associated mutations in myosin-binding protein C3 (MYBPC3) in Chinese patients with family hypertrophic cardiomyopathy (FHCM) and to analyze the genotype and phenotype correlation. On Show more
To determine the associated mutations in myosin-binding protein C3 (MYBPC3) in Chinese patients with family hypertrophic cardiomyopathy (FHCM) and to analyze the genotype and phenotype correlation. One family with 27 family members affected with FHCM was chosen for the study. The full encoding exons of MYBPC3 were amplified with PCR and the products were sequenced. The clinical data and echocardiography were collected. Two missense mutations in the family were identified: one was C.2526C>G mutation which caused a tyrosine (Tyr) to terminator exchange at amino acid residue 842 and the other was C.2971G>A mutation which resulted in a valine (Val) to methionine (Met) exchange at amino acid residue 991. Four patients in the family suffered from HCM with asymmetric interventricular septal hypertrophy. The left ventricular diastolic function was significantly reduced. Signs of regional diastolic abnormalities occurred in some mutation carriers. Severe hypertrophy and diastolic dysfunction of the disease are compatible with the presence of double mutations in MYBPC3. Signs of regional diastolic abnormalities suggest a primary response to the mutations of MYBPC3 expression. Show less
no PDF DOI: 10.3969/j.issn.1672-7347.2013.01.003
MYBPC3
Yun Hu, Yaqi Yang, Yanjun Yu +10 more · 2013 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
Alzheimer's disease (AD) is associated with impaired Aβ degradation in the brain. Enhancing the process of Aβ clearance is an attractive potential AD therapy. Treatment with LXR agonists may reduce Aβ Show more
Alzheimer's disease (AD) is associated with impaired Aβ degradation in the brain. Enhancing the process of Aβ clearance is an attractive potential AD therapy. Treatment with LXR agonists may reduce Aβ levels in vivo. However, the clinical potential of many LXR agonists is limited because of their nonselective actions on LXRα/β, which lead to undesired hepatic lipogenesis via LXRα-dependent pathways. In this study, ABCA1 up-regulators were identified from a series of flavonoids and were found to preferentially activate LXRβ and up-regulate expression of ABCA1 and apoE in different cell lines. Further investigations confirmed that these compounds facilitate intracellular Aβ clearance in Aβ-loaded BV2 cells. Administration of compound 19 reduced total brain Aβ and plaque burden in APP/PS1 double transgenic mice, associated with elevated ABCA1 and apoE expression. Compared with the nonselective LXR agonists, the active compounds reported here induced less accumulation of undesired lipids and triglycerides in HepG2 cells. Show less
no PDF DOI: 10.1021/jm301913k
NR1H3