👤 Shurong Yang

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
2090
Articles
1288
Name variants
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, 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 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
Jiang Wang, Yongchao Zhang, Yin Zhang +3 more · 2019 · Sensors (Basel, Switzerland) · MDPI · added 2026-04-24
Non-planar sun sensors can determine solar orientation by existing photodiodes or by reusing solar panels, without increasing the size and mass of spacecraft. However, a limiting factor for the improv Show more
Non-planar sun sensors can determine solar orientation by existing photodiodes or by reusing solar panels, without increasing the size and mass of spacecraft. However, a limiting factor for the improvement of the accuracy of orientation lies in the lack of a detailed performance assessment on interference suppression. In this paper, a new method that determines solar orientation in the frequency domain is developed for regular pyramid sun sensors, which are formed by regular pyramid arrays. Furthermore, two formulations are established to evaluate the errors of the solar azimuth and elevation angle in solar orientation determination based on the newly proposed frequency-domain method. With these formulations of performance evaluation, we discover the mathematical relationship between the interference spectrum, array geometry, solar irradiance, solar azimuth or elevation angle, and the error in solar orientation determination for the first time. This reveals that the internal interference from the detection system can be completely suppressed in solar orientation determination, and the constant interference can be eliminated in the estimation of solar azimuth angle. Simulation and field experiments validated the effectiveness of the new orientation method, error formulations and performance of each interference source. Show less
📄 PDF DOI: 10.3390/s19061424
DYM
Jingshuang Yu, Tong Yang, Jiewen Dai +1 more · 2019 · Orphanet journal of rare diseases · BioMed Central · added 2026-04-24
Both mandibular condylar hyperplasia and condylar osteochondroma can lead to maxillofacial skeletal asymmetry and malocclusion, although they exhibit different biological behavior. This study attempte Show more
Both mandibular condylar hyperplasia and condylar osteochondroma can lead to maxillofacial skeletal asymmetry and malocclusion, although they exhibit different biological behavior. This study attempted to compare the histological features of mandibular condylar hyperplasia and condylar osteochondroma using hematoxylin-and-eosin (H&E) staining, and immunohistochemistry staining of PCNA and EXT1 with quantitative analysis method. The H&E staining showed that condylar hyperplasia and condylar osteochondroma could be divided into four histological types and exhibited features of different endochondral ossification stages. There was evidence of a thicker cartilage cap in condylar osteochondroma as compared condylar hyperplasia (P = 0.018). The percentage of bone formation in condylar osteochondroma was larger than was found in condylar hyperplasia (P = 0.04). Immunohistochemical staining showed that PCNA was mainly located in the undifferentiated mesenchymal layer and the hypertrophic cartilage layer, and there were more PCNA positive cells in the condylar osteochondroma (P = 0.007). EXT1 was mainly expressed in the cartilage layer, and there was also a higher positive rate of EXT1 in condylar osteochondroma (P = 0.0366). The thicker cartilage cap, higher bone formation rate and higher PCNA positive rate indicated a higher rate of proliferative activity in condylar osteochondroma. The more significant positive rate of EXT1 in condylar osteochondroma implied differential biological characteristic as compared to condylar hyperplasia. These features might be useful in histopathologically distinguishing condylar hyperplasia and osteochondroma. Show less
📄 PDF DOI: 10.1186/s13023-019-1272-5
EXT1
Yi You, Shan Li, Bo Yang +1 more · 2019 · Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese journal of medical genetics · added 2026-04-24
To identify pathogenic variations of EXT1 and EXT2 genes in two Chinese pedigrees affected with hereditary multiple exostosis (HME). Genomic DNA was extracted from peripheral blood samples using a phe Show more
To identify pathogenic variations of EXT1 and EXT2 genes in two Chinese pedigrees affected with hereditary multiple exostosis (HME). Genomic DNA was extracted from peripheral blood samples using a phenol-chloroform method. PCR and Sanger sequencing was conducted to amplify the exons and the flanking intronic regions of the EXT1 and EXT2 genes. DNA sequencing has revealed a heterozygous missense variation c.812A>G (p.Tyr271Cys) in the exon 1 of EXT1 in pedigree 1, and a heterozygous frameshift variation c.1431dup (p.Ser478Leufs*43) in the exon 6 of EXT1 in the proband from pedigree 2. Both variations have co-segregated with the disease phenotype, which was also consistent with previous report. Two heterozygous pathogenic variations underlying HME have been identified. The result has facilitated genetic counseling and prenatal diagnosis for the affected pedigrees. Show less
no PDF DOI: 10.3760/cma.j.issn.1003-9406.2019.08.001
EXT1
Congyi Yang, Ruiqian Zhang, Hui Lin +1 more · 2019 · Journal of cellular biochemistry · Wiley · added 2026-04-24
Osteochondroma is a benign autosomal dominant hereditary disease characterized by abnormal proliferation of cartilage in the long bone. It is divided into solitary osteochondroma and hereditary multip Show more
Osteochondroma is a benign autosomal dominant hereditary disease characterized by abnormal proliferation of cartilage in the long bone. It is divided into solitary osteochondroma and hereditary multiple exostoses (HMEs). The exostosin-1 (EXT-1) and exostosin-2 (EXT-2) gene mutations are well-defined molecular mechanisms in the pathogenesis of HME. EXT-1 and EXT-2 encode glycosyltransferases that are necessary for the synthesis of heparin sulfate. Accumulating evidence suggests that mutations in the EXT family induce changes in isolated hypogonadotropic hypogonadism-parathyroid hormone-related protein, bone morphogenetic protein, and fibroblast growth factor signaling pathways. Studies have also found that a large number of microRNAs (miRNAs) are abnormally expressed in osteochondroma tissues, and some of them also participate in several major signaling pathways. The regulation of miRNA expression could be another breakthrough in the treatment of osteochondroma. Although the pathogenesis of osteochondroma is very complicated, significant progress has been made in recent years. It is hoped that the pathogenesis of osteochondroma will be clearly understood and the most effective methods for the prevention and treatment of osteochondroma will be determined. This review provides an update on the recent progress in the interpretation of the underlying molecular mechanisms of osteochondroma. Show less
no PDF DOI: 10.1002/jcb.29155
EXT1
Aram Yang, Jinsup Kim, Ja-Hyun Jang +4 more · 2019 · Annals of human genetics · Blackwell Publishing · added 2026-04-24
Multiple osteochondromas (MOs) or hereditary multiple exostoses is a rare autosomal-dominant disease characterized by growths of MOs, which are benign cartilage-capped bone tumors that grow away from Show more
Multiple osteochondromas (MOs) or hereditary multiple exostoses is a rare autosomal-dominant disease characterized by growths of MOs, which are benign cartilage-capped bone tumors that grow away from the growth plates. Almost 90% of MOs have a molecular explanation and 10% are unexplained. MOs are genetically heterogeneous with two causal genes on 8q24.11 (EXT1) and 11p12 (EXT2), with a higher frequency in EXT1. MO is a very rare genetic disorder, and the genotype-phenotype of MO with EXT2 mutation has not been well investigated in Korea. We present the clinical radiographic and molecular analysis of a four-generation Korean family with 11 MO-affected members (seven males and four females). The affected members from the third generation available for molecular analysis and their detailed medical histories showed moderate-to-severe phenotypes (clinical classes II-III), including bony deformities and limb misalignment with pain requiring surgical correction. The x-rays showed MOs in multiple sites. A novel EXT2 frameshift mutation (c.590delC, p.P197Qfs*73) was revealed by targeted exome sequencing in the affected members of this family. In this article, we not only expand the phenotypic-genotypic spectrum of MOs but also highlight the phenotypic heterogeneity in a family with the same mutation. In addition, we compiled the mutation spectrum of EXT2 from a literature review and identified that exon 2 of EXT2 is a mutation hot spot. Early medical attention with diagnosis of MO through careful examination of the clinical manifestations and genetic analysis can provide the opportunity to establish coordinated multispecialty management of the patient. Show less
no PDF DOI: 10.1111/ahg.12298
EXT1
Kai Xing, Kejun Wang, Hong Ao +13 more · 2019 · Scientific reports · Nature · added 2026-04-24
Fatness traits are important in pigs because of their implications for fattening efficiency, meat quality, reproductive performance and immunity. Songliao black pigs and Landrace pigs show important d Show more
Fatness traits are important in pigs because of their implications for fattening efficiency, meat quality, reproductive performance and immunity. Songliao black pigs and Landrace pigs show important differences in production and meat quality traits, including fatness and muscle growth. Therefore, we used a high-throughput massively parallel RNA-seq approach to identify genes differentially expressed in backfat tissue between these two breeds (six pigs in each). An average of 37.87 million reads were obtained from the 12 samples. After statistical analysis of gene expression data by edgeR, a total of 877 differentially expressed genes were detected between the two pig breeds, 205 with higher expression and 672 with lower expression in Songliao pigs. Candidate genes (LCN2, CES3, DGKB, OLR1, LEP, PGM1, PCK1, ACACB, FADS1, FADS2, MOGAT2, SREBF1, PPARGC1B) with known effects on fatness traits were included among the DEGs. A total of 1071 lncRNAs were identified, and 85 of these lncRNAs were differentially expressed, including 53 up-regulated and 32 down-regulated lncRNAs, respectively. The differentially expressed genes and lncRNAs involved in glucagon signaling pathway, glycolysis/gluconeogenesis, insulin signaling pathway, MAPK signaling pathway and so on. Integrated analysis potential trans-regulating or cis-regulating relation between DEGs and DE lncRNAs, suggested lncRNA MSTRG.2479.1 might regulate the expressed level of VLDLR affecting porcine fat metabolism. These results provide a number of candidate genes and lncRNAs potentially involved in porcine fat deposition and provide a basis for future research on the molecular mechanisms underlying in fat deposition. Show less
📄 PDF DOI: 10.1038/s41598-019-49548-5
FADS1
Zhenglin Du, Liang Ma, Hongzhu Qu +27 more · 2019 · Genomics, proteomics & bioinformatics · Elsevier · added 2026-04-24
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of Show more
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a "comfort" zone for a high frequency of 677T between latitudes of 35-45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine. Show less
📄 PDF DOI: 10.1016/j.gpb.2019.07.002
FADS1
Marshall Lukacs, Jonathan Gilley, Yi Zhu +9 more · 2019 · Experimental neurology · Elsevier · added 2026-04-24
The three nicotinamide mononucleotide adenylyltransferase (NMNAT) family members synthesize the electron carrier nicotinamide adenine dinucleotide (NAD
📄 PDF DOI: 10.1016/j.expneurol.2019.112961
FADS1
So-Hye Hong, Seung Chul Kim, Mee-Na Park +8 more · 2019 · Molecular medicine reports · added 2026-04-24
Female sex steroid hormones, including estradiol (E2) and progesterone (P4), serve significant physiological roles in pregnancy. In particular, E2 and P4 influence placenta formation, maintain pregnan Show more
Female sex steroid hormones, including estradiol (E2) and progesterone (P4), serve significant physiological roles in pregnancy. In particular, E2 and P4 influence placenta formation, maintain pregnancy and stimulate milk production. These hormones are produced by ovaries, adrenal glands and the placenta, of which the latter is a major endocrine organ during pregnancy. However, the mechanism of hormone production during pregnancy remains unclear. In the present study, the regulation of steroid hormones and steroidogenic enzymes was examined in human placenta according to gestational age. In human placental tissues, expression levels of steroidogenic enzymes were determined with reverse transcription‑quantitative polymerase chain reaction and western blotting. The mRNA and protein expression of CYP17A1, HSD17B3 and CYP19A1, which are associated with the synthesis of dehydroepiandrosterone (DHEA) and E2, was elevated at different gestational ages in human placenta. In addition, to evaluate the correlation between serum and placental‑produced hormones, steroid hormone levels, including pregnenolone (PG), DHEA, P4, testosterone (T) and E2, were examined in serum and placenta. Serum and placenta expression of DHEA and E2 increased with gestational age, whereas T and P4 were differently regulated in placenta and serum. To confirm the mechanism of steroidogenesis in vitro, placental BeWo cells were treated with E2 and P4, which are the most important hormones during pregnancy. The mRNA and protein expression of steroidogenic enzymes was significantly altered by E2 in vitro. These results demonstrated that concentration of steroid hormones was differently regulated by steroidogenic enzymes in the placenta depending on the type of the hormones, which may be critical to maintain pregnancy. Show less
no PDF DOI: 10.3892/mmr.2019.10048
HSD17B12
Wei-Ping Xiao, Li-Li-Qiang Ding, You-Jiang Min +6 more · 2019 · Neuropsychiatric disease and treatment · added 2026-04-24
To observe the changes of Nogo/NgR and Rho/ROCK signaling pathway-related gene and protein expression in rats with spinal cord injury (SCI) treated with electroacupuncture (EA) and to further investig Show more
To observe the changes of Nogo/NgR and Rho/ROCK signaling pathway-related gene and protein expression in rats with spinal cord injury (SCI) treated with electroacupuncture (EA) and to further investigate the possible mechanism of EA for treating SCI. Allen's method was used to create the SCI rat model. Sixty-four model rats were further subdivided into four subgroups, namely, the SCI model group (SCI), EA treatment group (EA), blocking agent Y27632 treatment group (Y27632) and EA+blocking agent Y27632 treatment group (EA+Y), according to the treatment received. The rats were subjected to EA and/or blocking agent Y27632 treatment. After 14 days, injured spinal cord tissue was extracted for analysis. The mRNA and protein expression levels were determined by real-time fluorescence quantitative PCR and Western blotting, respectively. Cell apoptosis changes in the spinal cord were evaluated by in situ hybridization. Hindlimb motor function in the rats was evaluated by Basso-Beattie-Bresnahan assessment methods. Except for RhoA protein expression, compared with the SCI model group, EA, blocking agent Y27632 and EA+blocking agent Y27632 treatment groups had significantly reduced mRNA and protein expression of Nogo-A, NgR, LINGO-1, RhoA and ROCK II in spinal cord tissues, increased mRNA and protein expression of MLCP, decreased p-MYPT1 protein expression and p-MYPT1/MYPT1 ratio, and caspase3 expression, and improved lower limb movement function after treatment for 14 days (P<0.01 or <0.05). The combination of EA and the blocking agent Y27632 was superior to EA or blocking agent Y27632 treatment alone (P < 0.01 or <0.05). EA may have an obvious inhibitory effect on the Nogo/NgR and Rho/ROCK signaling pathway after SCI, thereby reducing the inhibition of axonal growth, which may be a key mechanism of EA treatment for SCI. Show less
📄 PDF DOI: 10.2147/NDT.S216874
LINGO1
Zhong-Yuan Zhang, Jin Yang, Zhen-Hai Fan +5 more · 2019 · Neural regeneration research · added 2026-04-24
Suture and autologous nerve transplantation are the primary therapeutic measures for completely severed nerves. However, imbalances in the microenvironment and adhesion of surrounding tissues can affe Show more
Suture and autologous nerve transplantation are the primary therapeutic measures for completely severed nerves. However, imbalances in the microenvironment and adhesion of surrounding tissues can affect the quality of nerve regeneration and repair. Previous studies have shown that human amniotic membrane can promote the healing of a variety of tissues. In this study, the right common peroneal nerve underwent a 5-mm transection in rats. Epineural nerve repair was performed using 10/0 non-absorbable surgical suture. The repair site was wrapped with a two-layer amniotic membrane with α-cyanoacrylate rapid medical adhesive after suture. Hindlimb motor function was assessed using footprint analysis. Conduction velocity of the common peroneal nerve was calculated by neural electrical stimulation. The retrograde axoplasmic transport of the common peroneal nerve was observed using fast blue BB salt retrograde fluorescent staining. Hematoxylin-eosin staining was used to detect the pathological changes of the common peroneal nerve sputum. The mRNA expression of axon regeneration-related neurotrophic factors and inhibitors was measured using real-time polymerase chain reaction. The results showed that the amniotic membrane significantly improved the function of the injured nerve; the toe spread function rapidly recovered, the nerve conduction velocity was restored, and the number of fast blue BB salt particles were increased in the spinal cord. The amniotic membrane also increased the recovery rate of the tibialis anterior muscle and improved the tissue structure of the muscle. Meanwhile, mRNA expression of nerve growth factor, growth associated protein-43, collapsin response mediator protein-2, and brain-derived neurotrophic factor recovered to near-normal levels, while Lingo-1 mRNA expression decreased significantly in spinal cord tissues. mRNA expression of glial-derived neurotrophic factor did not change significantly. Changes in mRNA levels were more significant in amniotic-membrane-wrapping-treated rats compared with model and nerve sutured rats. These results demonstrate that fresh amniotic membrane wrapping can promote the functional recovery of sutured common peroneal nerve via regulation of expression levels of neurotrophic factors and inhibitors associated with axonal regeneration. The study was approved by the Committee on Animal Research and Ethics at the Affiliate Hospital of Zunyi Medical University, China (approval No. 112) on December 1, 2017. Show less
📄 PDF DOI: 10.4103/1673-5374.262596
LINGO1
Lulu Kang, Yi Liu, Ying Jin +5 more · 2019 · Frontiers in neurology · Frontiers · added 2026-04-24
As a member of spectraplakin family of cytoskeletal crosslinking proteins, microtubule-actin crosslinking factor 1 (MACF1) controls cytoskeleton network dynamics. Knockout of
📄 PDF DOI: 10.3389/fneur.2019.01335
MACF1
Feng Ye, Hongwei Gao, Lin Xiao +19 more · 2019 · International journal of cancer · Wiley · added 2026-04-24
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNM Show more
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNMTC). The aim of this study is to screen and identify high-penetrate genes for FNMTC. A total of 34 families with more than two first-degree relatives diagnosed as papillary thyroid cancer without other familial syndrome were recruited. Whole exome and target gene sequencing were performed for candidate variants. These variants were screened and analyzed with ESP6500, ExAC, 1000 genomes project, and the Cancer Genome Atlas (TCGA) with SIFT score and Polyphen2 prediction. Finally, we identified recurrent genetic mutation of MAP2K5 variants c.G961A and c.T1100C (p. A321T and p.M367 T) as susceptibility loci for FNMTC. The frequencies of MAP2K5 c.G961A and c.T1100C were found, 0.0385 and 0.0259 in FNMTC and 0 and 0.00022523 in healthy Chinese controls (n = 2200, P < 0.001), respectively. Both variants were located in the protein kinase domain. The functional study showed that MAP2K5 A321T or M367 T could consistently phosphorylate downstream protein ERK5 on site Ser731 + Thr733 or Ser496, promoting nuclear translocation and subsequently altering target gene expressions. Our data revealed that MAP2K5 variants A321T or M367 T can activate MAP2K5-ERK5 pathway, alter downstream gene expression, and subsequently induce thyroid epithelial cell malignant transformation. While classic MAP2K1/2(MEK1/2)-ERK1/2 signaling is well known for driving sporadic NMTC, our research indicated that MAP2K5 (MEK5) is a susceptibility gene for FNMTC. These findings highlight the potential application of MAP2K5 for molecular diagnosis as well as early prevention. Show less
no PDF DOI: 10.1002/ijc.31825
MAP2K5
Qingqing Xu, Suqin Yin, Yao Yao +10 more · 2019 · International immunopharmacology · Elsevier · added 2026-04-24
Via promoting synovitis, pannus growth and cartilage/bone destruction, fibroblast-like synovial cells (FLSs) play a significant role in the pathogenesis of rheumatoid arthritis (RA). In our study, rat Show more
Via promoting synovitis, pannus growth and cartilage/bone destruction, fibroblast-like synovial cells (FLSs) play a significant role in the pathogenesis of rheumatoid arthritis (RA). In our study, rats were induced with complete freund's adjuvant (CFA) to be animal models for studying the RA pathogenesis. Microtubule-associated Serine/Threonine-protein kinase 3 (MAST3) has been documented to play a critical role in regulating the immune response of IBD (Inflammatory bowel disease) and involved in the process of cytoskeleton organization, intracellular signal transduction and peptidyl-serine phosphorylation, but its role in the progression of RA remains unknown and is warranted for investigation. So, we tried our best to investigate the mechanism and signaling pathway of MAST3 in RA progression. In the synovial tissue and FLSs of AA rats, we have found that MAST3 was significantly up-regulated than normal. Furthermore, MAST3 overexpression could promote proliferation and inflammatory response of FLSs. In the aspect of mechanism, we discovered that the expression of MAST3 might involve in NF-κB signaling pathway in RA. On the whole, our results suggested that MAST3 might promote the proliferation and inflammation of FLSs by regulating NF-κB signaling pathway. Show less
no PDF DOI: 10.1016/j.intimp.2019.105900
MAST3
Xiaosheng Song, Liuliu Yang, Mingzhu Wang +5 more · 2019 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Chromosomal translocations of
no PDF DOI: 10.1073/pnas.1904672116
MLLT10
Ziyi Song, Hao Yang, Lei Zhou +1 more · 2019 · International journal of molecular sciences · MDPI · added 2026-04-24
The worldwide increase in type 2 diabetes (T2D) is becoming a major health concern, thus searching for novel preventive and therapeutic strategies has become urgent. In last decade, the paralogous tra Show more
The worldwide increase in type 2 diabetes (T2D) is becoming a major health concern, thus searching for novel preventive and therapeutic strategies has become urgent. In last decade, the paralogous transcription factors MondoA and carbohydrate response element-binding protein (ChREBP) have been revealed to be central mediators of glucose sensing in multiple metabolic organs. Under normal nutrient conditions, MondoA/ChREBP plays vital roles in maintaining glucose homeostasis. However, under chronic nutrient overload, the dysregulation of MondoA/ChREBP contributes to metabolic disorders, such as insulin resistance (IR) and T2D. In this review, we aim to provide an overview of recent advances in the understanding of MondoA/ChREBP and its roles in T2D development. Specifically, we will briefly summarize the functional similarities and differences between MondoA and ChREBP. Then, we will update the roles of MondoA/ChREBP in four T2D-associated metabolic organs (i.e., the skeletal muscle, liver, adipose tissue, and pancreas) in physiological and pathological conditions. Finally, we will discuss the opportunities and challenges of MondoA/ChREBP as drug targets for anti-diabetes. By doing so, we highlight the potential use of therapies targeting MondoA/ChREBP to counteract T2D and its complications. Show less
📄 PDF DOI: 10.3390/ijms20205132
MLXIPL
Yakui Li, Dianqiang Yang, Na Tian +12 more · 2019 · The Journal of biological chemistry · American Society for Biochemistry and Molecular Biology · added 2026-04-24
The glucose-responsive transcription factor carbohydrate response element-binding protein (ChREBP) critically promotes aerobic glycolysis and cell proliferation in colorectal cancer cells. It has been Show more
The glucose-responsive transcription factor carbohydrate response element-binding protein (ChREBP) critically promotes aerobic glycolysis and cell proliferation in colorectal cancer cells. It has been reported that ubiquitination may be important in the regulation of ChREBP protein levels and activities. However, the ChREBP-specific E3 ligase and molecular mechanism of ChREBP ubiquitination remains unclear. Using database exploration and expression analysis, we found here that levels of the E3 ligase SMURF2 (Smad-ubiquitination regulatory factor 2) negatively correlate with those of ChREBP in cancer tissues and cell lines. We observed that SMURF2 interacts with ChREBP and promotes ChREBP ubiquitination and degradation via the proteasome pathway. Interestingly, ectopic SMURF2 expression not only decreased ChREBP levels but also reduced aerobic glycolysis, increased oxygen consumption, and decreased cell proliferation in colorectal cancer cells. Moreover, SMURF2 knockdown increased aerobic glycolysis, decreased oxygen consumption, and enhanced cell proliferation in these cells, mostly because of increased ChREBP accumulation. Furthermore, we identified Ser/Thr kinase AKT as an upstream suppressor of SMURF2 that protects ChREBP from ubiquitin-mediated degradation. Taken together, our results indicate that SMURF2 reduces aerobic glycolysis and cell proliferation by promoting ChREBP ubiquitination and degradation via the proteasome pathway in colorectal cancer cells. We conclude that the SMURF2-ChREBP interaction might represent a potential target for managing colorectal cancer. Show less
no PDF DOI: 10.1074/jbc.RA119.007508
MLXIPL
Simeng Gu, Shujuan Lin, Ding Ye +11 more · 2019 · Clinical epigenetics · BioMed Central · added 2026-04-24
Epigenetic alternation is a common contributing factor to neoplastic transformation. Although previous studies have reported a cluster of aberrant promoter methylation changes associated with silencin Show more
Epigenetic alternation is a common contributing factor to neoplastic transformation. Although previous studies have reported a cluster of aberrant promoter methylation changes associated with silencing of tumor suppressor genes, little is known concerning their sequential DNA methylation changes during the carcinogenetic process. The aim of the present study was to address a genome-wide search for identifying potentially important methylated changes and investigate the onset and pattern of methylation changes during the progression of colorectal neoplasia. A three-phase design was employed in this study. In the screening phase, DNA methylation profile of 12 pairs of colorectal cancer (CRC) and adjacent normal tissues was analyzed by using the Illumina MethylationEPIC BeadChip. Significant CpG sites were selected based on a cross-validation analysis from The Cancer Genome Atlas (TCGA) database. Methylation levels of candidate CpGs were assessed using pyrosequencing in the training dataset (tumor lesions and adjacent normal tissues from 46 CRCs) and the validation dataset (tumor lesions and paired normal tissues from 13 hyperplastic polyps, 129 adenomas, and 256 CRCs). A linear mixed-effects model was used to examine the incremental changes of DNA methylation during the progression of colorectal neoplasia. The comparisons between normal and tumor samples in the screening phase revealed an extensive CRC-specific methylomic pattern with 174,006 (21%) methylated CpG sites, of which 22,232 (13%) were hyermethylated and 151,774 (87%) were hypomethylated. Hypermethylation mostly occurred in CpG islands with an overlap of gene promoters, while hypomethylation tended to be mapped far away from functional regions. Further cross validation analysis from TCGA dataset confirmed 265 hypermethylated promoters coupling with downregulated gene expression. Among which, hypermethylated changes in MEEPD2 promoter was successfully replicated in both training and validation phase. Significant hypermethylation appeared since precursor lesions with an extensive modification in CRCs. The linear mixed-effects modeling analysis found that a cumulative pattern of MPPED2 methylation changes from normal mucosa to hyperplastic polyp to adenoma, and to carcinoma (P < 0.001). Our findings indicate that epigenetic alterations of MPPED2 promoter region appear sequentially during the colorectal neoplastic progression. It might be able to serve as a promising biomarker for early diagnosis and stage surveillance of colorectal tumorigenesis. Show less
📄 PDF DOI: 10.1186/s13148-019-0628-y
MPPED2
Linyuan Ma, Lydia Jang, Jian Chen +5 more · 2019 · Journal of visualized experiments : JoVE · added 2026-04-24
Gene editing nucleases, represented by CRISPR-associated protein 9 (Cas9), are becoming mainstream tools in biomedical research. Successful delivery of CRISPR/Cas9 elements into the target cells by tr Show more
Gene editing nucleases, represented by CRISPR-associated protein 9 (Cas9), are becoming mainstream tools in biomedical research. Successful delivery of CRISPR/Cas9 elements into the target cells by transfection is a prerequisite for efficient gene editing. This protocol demonstrates that tube electroporation (TE) machine-mediated delivery of CRISPR/Cas9 ribonucleoprotein (RNP), along with single-stranded oligodeoxynucleotide (ssODN) donor templates to different types of mammalian cells, leads to robust precise gene editing events. First, TE was applied to deliver CRISPR/Cas9 RNP and ssODNs to induce disease-causing mutations in the interleukin 2 receptor subunit gamma (IL2RG) gene and sepiapterin reductase (SPR) gene in rabbit fibroblast cells. Precise mutation rates of 3.57%-20% were achieved as determined by bacterial TA cloning sequencing. The same strategy was then used in human iPSCs on several clinically relevant genes including epidermal growth factor receptor (EGFR), myosin binding protein C, cardiac (Mybpc3), and hemoglobin subunit beta (HBB). Consistently, highly precise mutation rates were achieved (11.65%-37.92%) as determined by deep sequencing (DeepSeq). The present work demonstrates that tube electroporation of CRISPR/Cas9 RNP represents an efficient transfection protocol for gene editing in mammalian cells. Show less
no PDF DOI: 10.3791/59512
MYBPC3
Haodi Wu, Huaxiao Yang, June-Wha Rhee +10 more · 2019 · European heart journal · Oxford University Press · added 2026-04-24
Diastolic dysfunction (DD) is common among hypertrophic cardiomyopathy (HCM) patients, causing major morbidity and mortality. However, its cellular mechanisms are not fully understood, and presently t Show more
Diastolic dysfunction (DD) is common among hypertrophic cardiomyopathy (HCM) patients, causing major morbidity and mortality. However, its cellular mechanisms are not fully understood, and presently there is no effective treatment. Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) hold great potential for investigating the mechanisms underlying DD in HCM and as a platform for drug discovery. In the present study, beating iPSC-CMs were generated from healthy controls and HCM patients with DD. Micropatterned iPSC-CMs from HCM patients showed impaired diastolic function, as evidenced by prolonged relaxation time, decreased relaxation rate, and shortened diastolic sarcomere length. Ratiometric Ca2+ imaging indicated elevated diastolic [Ca2+]i and abnormal Ca2+ handling in HCM iPSC-CMs, which were exacerbated by β-adrenergic challenge. Combining Ca2+ imaging and traction force microscopy, we observed enhanced myofilament Ca2+ sensitivity (measured as dF/Δ[Ca2+]i) in HCM iPSC-CMs. These results were confirmed with genome-edited isogenic iPSC lines that carry HCM mutations, indicating that cytosolic diastolic Ca2+ overload, slowed [Ca2+]i recycling, and increased myofilament Ca2+ sensitivity, collectively impairing the relaxation of HCM iPSC-CMs. Treatment with partial blockade of Ca2+ or late Na+ current reset diastolic Ca2+ homeostasis, restored diastolic function, and improved long-term survival, suggesting that disturbed Ca2+ signalling is an important cellular pathological mechanism of DD. Further investigation showed increased expression of L-type Ca2+channel (LTCC) and transient receptor potential cation channels (TRPC) in HCM iPSC-CMs compared with control iPSC-CMs, which likely contributed to diastolic [Ca2+]i overload. In summary, this study recapitulated DD in HCM at the single-cell level, and revealed novel cellular mechanisms and potential therapeutic targets of DD using iPSC-CMs. Show less
no PDF DOI: 10.1093/eurheartj/ehz326
MYBPC3
Robert J H Miller, Shahriar Heidary, Aleksandra Pavlovic +6 more · 2019 · PloS one · PLOS · added 2026-04-24
HCM is the most common inherited cardiomyopathy. Historically, there has been poor correlation between genotype and phenotype. However, CMR has the potential to more accurately assess disease phenotyp Show more
HCM is the most common inherited cardiomyopathy. Historically, there has been poor correlation between genotype and phenotype. However, CMR has the potential to more accurately assess disease phenotype. We characterized phenotype with CMR in a cohort of patients with confirmed HCM and high prevalence of genetic testing. Patients with a diagnosis of HCM, who had undergone contrast-enhanced CMR were identified. Left ventricular mass index (LVMI) and volumes were measured from steady-state free precession sequences. Late gadolinium enhancement (LGE) was quantified using the full width, half maximum method. All patients were prospectively followed for the development of septal reduction therapy, arrhythmia or death. We included 273 patients, mean age 51.2 ± 15.5, 62.9% male. Of those patients 202 (74.0%) underwent genetic testing with 90 pathogenic, likely pathogenic, or rare variants and 13 variants of uncertain significance identified. Median follow-up was 1138 days. Mean LVMI was 82.7 ± 30.6 and 145 patients had late gadolinium enhancement (LGE). Patients with beta-myosin heavy chain (MYH7) mutations had higher LV ejection fraction (68.8 vs 59.1, p<0.001) than those with cardiac myosin binding protein C (MYBPC3) mutations. Patients with MYBPC3 mutations were more likely to have LVEF < 55% (29.7% vs 4.9%, p = 0.005) or receive a defibrillator than those with MYH7 mutations (54.1% vs 26.8%, p = 0.020). We found that patients with MYBPC3 mutations were more likely to have impaired ventricular function and may be more prone to arrhythmic events. Larger studies using CMR phenotyping may be capable of identifying additional characteristics associated with less frequent genetic causes of HCM. Show less
no PDF DOI: 10.1371/journal.pone.0217612
MYBPC3
Zengrong Zhang, Huarui Du, Chaowu Yang +12 more · 2019 · Animal biotechnology · Taylor & Francis · added 2026-04-24
no PDF DOI: 10.1080/10495398.2018.1476377
MYBPC3
Qian-Li Yang, Yang-Yang Bian, Bo Wang +5 more · 2019 · Journal of cardiology · Elsevier · added 2026-04-24
The correlations between genotype and phenotype in hypertrophic cardiomyopathy (HCM) have not been established. Mutation of α-actin gene (ACTC1) is a rare cause of HCM. This study aimed to explore nov Show more
The correlations between genotype and phenotype in hypertrophic cardiomyopathy (HCM) have not been established. Mutation of α-actin gene (ACTC1) is a rare cause of HCM. This study aimed to explore novel genotype-phenotype correlations in HCM patients with the variants in ACTC1 and myosin-binding protein (MYBPC3) genes in three unrelated Chinese families. Clinical, electrocardiographic, and echocardiographic examinations were performed in three Han pedigrees. Exon and boarding intron analysis of 96 cardio-disease-related genes was performed using second-generation sequencing on three probands. The candidate variants were validated in 14 available family members and 300 unrelated healthy controls by bi-directional Sanger sequencing. The pathogenicity and conservation were calculated using MutationTaster, PolyPhen-2, SIFT, and Clustal X. Pathogenicity classification of the variants was based on American College of Medical Genetics and Genomics (ACMG) guidelines. Nine members fulfilled diagnostic criteria for HCM with clinical characteristics, electrocardiographic, and echocardiographic findings. Two candidate variants in ACTC1 p.Asp26Asn (ACTC1-D26N) and MYBPC3 p.Arg215Cys (MYBPC3-R215C) were identified in patients. Only ACTC1-D26N strongly co-segregated with the HCM phenotype. Seven patients who harbored variant ACTC-D26N only were diagnosed with non-obstructive HCM, and four of these patients exhibited a triphasic left ventricular (LV) filling pattern. Two patients carrying both ACTC1-D26N and MYBPC3-R215C variants showed a higher LV outflow tract pressure gradient. Bioinformatics analysis revealed that the two variants were deleterious and highly conserved across species. According to ACMG guidelines, ACTC1-D26N is classified as a likely pathogenic mutation. The second variation MYBPC3-R215C may function as a genetic modifier, which remains uncertain here. Novel p.(Asp26Asn) mutation of ACTC1 was associated with HCM phenotype, and the penetrance is extremely high (∼81.8%) in adults. The second variation, MYBPC3-R215C may function as a genetic modifier, which remains uncertain here. Show less
no PDF DOI: 10.1016/j.jjcc.2018.09.005
MYBPC3
Timon Seeger, Rajani Shrestha, Chi Keung Lam +16 more · 2019 · Circulation · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is frequently caused by mutations in myosin-binding protein C3 ( MYBPC3) resulting in a premature termination codon (PTC). The underlying mechanisms of how PTC mutati Show more
Hypertrophic cardiomyopathy (HCM) is frequently caused by mutations in myosin-binding protein C3 ( MYBPC3) resulting in a premature termination codon (PTC). The underlying mechanisms of how PTC mutations in MYBPC3 lead to the onset and progression of HCM are poorly understood. This study's aim was to investigate the molecular mechanisms underlying the pathogenesis of HCM associated with MYBPC3 PTC mutations by utilizing human isogenic induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Isogenic iPSC lines were generated from HCM patients harboring MYBPC3 PTC mutations (p.R943x; p.R1073P_Fsx4) using genome editing. Comprehensive phenotypic and transcriptome analyses were performed in the iPSC-CMs. We observed aberrant calcium handling properties with prolonged decay kinetics and elevated diastolic calcium levels in the absence of structural abnormalities or contracile dysfunction in HCM iPSC-CMs as compared to isogenic controls. The mRNA expression levels of MYBPC3 were significantly reduced in mutant iPSC-CMs, but the protein levels were comparable among isogenic iPSC-CMs, suggesting that haploinsufficiency of MYBPC3 does not contribute to the pathogenesis of HCM in vitro. Furthermore, truncated MYBPC3 peptides were not detected. At the molecular level, the nonsense-mediated decay pathway was activated, and a set of genes involved in major cardiac signaling pathways was dysregulated in HCM iPSC-CMs, indicating an HCM gene signature in vitro. Specific inhibition of the nonsense-mediated decay pathway in mutant iPSC-CMs resulted in reversal of the molecular phenotype and normalization of calcium-handling abnormalities. iPSC-CMs carrying MYBPC3 PTC mutations displayed aberrant calcium signaling and molecular dysregulations in the absence of significant haploinsufficiency of MYBPC3 protein. Here we provided the first evidence of the direct connection between the chronically activated nonsense-mediated decay pathway and HCM disease development. Show less
no PDF DOI: 10.1161/CIRCULATIONAHA.118.034624
MYBPC3
Meng Xu, Licong Yang, Yanping Zhu +5 more · 2019 · Food & function · Royal Society of Chemistry · added 2026-04-24
To investigate the mechanism of the combined effects of chlorogenic acid (CGA) and caffeine on lipid metabolism in high-fat diet-induced obese mice, eighty female ICR mice were randomly divided into e Show more
To investigate the mechanism of the combined effects of chlorogenic acid (CGA) and caffeine on lipid metabolism in high-fat diet-induced obese mice, eighty female ICR mice were randomly divided into eight groups and fed with a high-fat diet with/without CGA and/or caffeine for 14 weeks. The combination of CGA and caffeine effectively decreased body weight gain, intraperitoneal adipose tissue weight, serum LDL-c, FFA, TC, TG, leptin, IL-6 concentrations, and hepatic TG and TC levels and increased the serum adiponectin level. The CGA and caffeine combination also promoted the phosphorylation of AMPKα, inhibited the expressions of transcriptional regulators (SREBP-1c and LXRα), and decreased the expressions of FAS and HMGR. Besides, the expressions of ACO, ATGL and HSL were increased by the CGA and caffeine combinations. The results indicated that the combination of CGA and caffeine had anti-obesity effects and regulated lipid metabolism in high-fat diet-induced obese mice via the AMPKα-LXRα/SREBP-1c signaling pathway. Thus, chronic CGA and caffeine intakes may be potent for preventing obesity. Show less
no PDF DOI: 10.1039/c9fo00502a
NR1H3
Liu Yang, Tie Li, Shuiping Zhao +1 more · 2019 · Molecular medicine reports · added 2026-04-24
Niacin is currently the most effective drug that increases HDL‑C levels. Apolipoprotein M (ApoM) in humans is mainly found in plasma high‑density lipoprotein (HDL). Little is known about the role play Show more
Niacin is currently the most effective drug that increases HDL‑C levels. Apolipoprotein M (ApoM) in humans is mainly found in plasma high‑density lipoprotein (HDL). Little is known about the role played by niacin in ApoM expression. In this study, the effects of niacin on ApoM expression were assessed as well as the associated mechanism. Human liver cancer cell line HepG2 was treated with niacin alone or with liver X receptor‑α (LXRα) inhibitor at multiple concentrations. The mRNA and protein expression of ApoM were assessed by qRT‑PCR and western blotting. Specific LXRα shRNA was transfected into HepG2 cells to further evaluate the regulatory effects of LXRα on ApoM. An in vivo model was also established to investigate the LXRα inhibitor on the mouse ApoM levels. The comparisons among groups were evaluated using one‑way ANOVA and Student‑Newman‑Keuls test. It was revealed that in HepG2 cells, niacin dose‑dependently increased ApoM gene and protein expression levels. Niacin‑induced upregulation of ApoM was attenuated by an LXRα inhibitor or LXRα shRNA, indicating that LXRα mediated this effect. Moreover, niacin treatment resulted in increased LXRα mRNA levels, in vivo and in vitro; niacin treatment resulted in increased ApoM gene and protein expression levels in mice. In conclusion, niacin upregulates ApoM expression by increasing LXRα expression in vivo and in vitro. Show less
no PDF DOI: 10.3892/mmr.2019.10557
NR1H3
Xiaoling Zhou, Hong Yang, Qiongxian Yan +6 more · 2019 · Nutrition & metabolism · BioMed Central · added 2026-04-24
Maternal undernutrition programs fetal energy homeostasis and increases the risk of metabolic disorders later in life. This study aimed to identify the signs of hepatic metabolic programming in utero Show more
Maternal undernutrition programs fetal energy homeostasis and increases the risk of metabolic disorders later in life. This study aimed to identify the signs of hepatic metabolic programming in utero and during the juvenile phase after intrauterine undernutrition during midgestation. Fifty-three pregnant goats were assigned to the control (100% of the maintenance requirement) or restricted (60% of the maintenance requirement from day 45 to day 100 of midgestation and realimentation thereafter) group to compare hepatic energy metabolism in the fetuses (day 100 of gestation) and kids (postnatal day 90). Undernutrition increased the glucagon concentration and hepatic hexokinase activity, decreased the body weight, liver weight and hepatic expression of Maternal undernutrition affects the metabolic status in a sex- and stage-specific manner by changing the metabolic profile, expression of genes involved in glucose homeostasis and enzyme activities in the liver of the fetuses. The changes in the hormone levels in the male fetuses and kids, but not the female offspring, represent a potential sign of metabolic programming. Show less
no PDF DOI: 10.1186/s12986-019-0346-7
NR1H3
KeShan Wang, TianBo Xu, HaiLong Ruan +13 more · 2019 · Cell death & disease · Nature · added 2026-04-24
Notwithstanding the researches on biomarkers and targeted therapies in renal cell carcinomas (RCC) have made progress in the last decades, the application of the biomarkers and targeted therapy agents Show more
Notwithstanding the researches on biomarkers and targeted therapies in renal cell carcinomas (RCC) have made progress in the last decades, the application of the biomarkers and targeted therapy agents for RCC in clinic are restricted because of their limitation or side effects. Liver X receptors (LXRs) and the NLRP3 inflammasome have been the research hotspots in recent years. In our study, we integrated bioinformatics analysis, molecular biology experiments and biological function experiments to study the roles of LXRα and the NLRP3 inflammasome in RCC. The study demonstrated that the elevated LXRα expression is correlated with a poor prognosis in RCC. Furthermore, our study revealed the expression levels and roles of the NLRP3 inflammasome in RCC for the first time. This research demonstrated that LXRα could promote the metastasis of RCC cells by suppressing the expression of the NLRP3 inflammasome. In Brief, LXRα had the possibility to be a novel diagnostic and prognostic biomarker and therapeutic target in renal cell cancer and LXRα could regulate the metastasis of renal cell cancer via NLRP3 inflammamsome. Show less
no PDF DOI: 10.1038/s41419-019-1345-3
NR1H3

24(

Spyridon Theofilopoulos, Willy Antoni Abreu de Oliveira, Shanzheng Yang +9 more · 2019 · The Journal of biological chemistry · American Society for Biochemistry and Molecular Biology · added 2026-04-24
The liver X receptors Lxrα/NR1H3 and Lxrβ/NR1H2 are ligand-dependent nuclear receptors critical for midbrain dopaminergic (mDA) neuron development. We found previously that 24(
no PDF DOI: 10.1074/jbc.RA118.005639
NR1H3
Qi Yang, Rui Wang, Bo Wei +5 more · 2019 · DNA and cell biology · added 2026-04-24
This study was aimed to identify hub genes associated with the development of glioblastoma (GBM) by conducting a bioinformatic analysis. The raw gene expression data were downloaded from the Gene Expr Show more
This study was aimed to identify hub genes associated with the development of glioblastoma (GBM) by conducting a bioinformatic analysis. The raw gene expression data were downloaded from the Gene Expression Omnibus database and The Cancer Genome Atlas project. After the differentially expressed genes (DEGs) were identified, the functional enrichment analysis of DEGs was conducted. Subsequently, the protein-protein interaction (PPI) network, molecular complex detection clusters, and transcriptional factor (TF)-miRNA-target regulatory network were constructed, respectively. Furthermore, the survival analysis of prognostic outcomes and genes was analyzed. In addition, the expression of key genes was validated by quantitative real-time PCR (qRT-PCR) analysis. A total of 884 DEGs, including 418 upregulated and downregulated genes, were identified between GBM and normal samples. The PPI network comprised a set of 3418 pairs involving 751 nodes, and Show less
no PDF DOI: 10.1089/dna.2018.4353
NRXN3