👤 Kaifu Chen

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
2981
Articles
1996
Name variants
Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, Zhezhe Chen, Zhi Bin Chen, Zhi Chen, Zhi-Hao Chen, Zhi-bin Chen, Zhi-zhe Chen, Zhiang Chen, Zhichuan Chen, Zhifeng Chen, Zhigang Chen, Zhigeng Chen, Zhiguo Chen, Zhihai Chen, Zhihang Chen, Zhihao Chen, Zhiheng Chen, Zhihong Chen, Zhijian Chen, Zhijian J Chen, Zhijing Chen, Zhijun Chen, Zhimin Chen, Zhinan Chen, Zhiping Chen, Zhiqiang Chen, Zhiquan Chen, Zhishi Chen, Zhitao Chen, Zhiting Chen, Zhiwei Chen, Zhixin Chen, Zhixuan Chen, Zhixue Chen, Zhiyong Chen, Zhiyu Chen, Zhiyuan Chen, Zhiyun Chen, Zhizhong Chen, Zhong Chen, Zhongbo Chen, Zhonghua Chen, Zhongjian Chen, Zhongliang Chen, Zhongxiu Chen, Zhongzhu Chen, Zhou Chen, Zhouji Chen, Zhouliang Chen, Zhoulong Chen, Zhouqing Chen, Zhuchu Chen, Zhujun Chen, Zhuo Chen, Zhuo-Yuan Chen, ZhuoYu Chen, Zhuohui Chen, Zhuojia Chen, Zi-Jiang Chen, Zi-Qing Chen, Zi-Yang Chen, Zi-Yue Chen, Zi-Yun Chen, Zian Chen, Zifan Chen, Zihan Chen, Zihang Chen, Zihao Chen, Zihe Chen, Zihua Chen, Zijie Chen, Zike Chen, Zilin Chen, Zilong Chen, Ziming Chen, Zinan Chen, Ziqi Chen, Ziqing Chen, Zitao Chen, Zixi Chen, Zixin Chen, Zixuan Chen, Ziying Chen, Ziyuan Chen, Zoe Chen, Zongming E Chen, Zongnan Chen, Zongyou Chen, Zongzheng Chen, Zugen Chen, Zuolong Chen
articles
Tatenda Mahlokozera, Bhuvic Patel, Hao Chen +14 more · 2021 · Nature communications · Nature · added 2026-04-24
The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which are thought to underlie tumor growth, treatment resistance, and recurrence. To under Show more
The pluripotency transcription factor SOX2 is essential for the maintenance of glioblastoma stem cells (GSC), which are thought to underlie tumor growth, treatment resistance, and recurrence. To understand how SOX2 is regulated in GSCs, we utilized a proteomic approach and identified the E3 ubiquitin ligase TRIM26 as a direct SOX2-interacting protein. Unexpectedly, we found TRIM26 depletion decreased SOX2 protein levels and increased SOX2 polyubiquitination in patient-derived GSCs, suggesting TRIM26 promotes SOX2 protein stability. Accordingly, TRIM26 knockdown disrupted the SOX2 gene network and inhibited both self-renewal capacity as well as in vivo tumorigenicity in multiple GSC lines. Mechanistically, we found TRIM26, via its C-terminal PRYSPRY domain, but independent of its RING domain, stabilizes SOX2 protein by directly inhibiting the interaction of SOX2 with WWP2, which we identify as a bona fide SOX2 E3 ligase in GSCs. Our work identifies E3 ligase competition as a critical mechanism of SOX2 regulation, with functional consequences for GSC identity and maintenance. Show less
no PDF DOI: 10.1038/s41467-021-26653-6
WWP2
David R Murdock, Hongzheng Dai, Lindsay C Burrage +16 more · 2021 · The Journal of clinical investigation · added 2026-04-24
BACKGROUNDTranscriptome sequencing (RNA-seq) improves diagnostic rates in individuals with suspected Mendelian conditions to varying degrees, primarily by directing the prioritization of candidate DNA Show more
BACKGROUNDTranscriptome sequencing (RNA-seq) improves diagnostic rates in individuals with suspected Mendelian conditions to varying degrees, primarily by directing the prioritization of candidate DNA variants identified on exome or genome sequencing (ES/GS). Here we implemented an RNA-seq-guided method to diagnose individuals across a wide range of ages and clinical phenotypes.METHODSOne hundred fifteen undiagnosed adult and pediatric patients with diverse phenotypes and 67 family members (182 total individuals) underwent RNA-seq from whole blood and skin fibroblasts at the Baylor College of Medicine (BCM) Undiagnosed Diseases Network clinical site from 2014 to 2020. We implemented a workflow to detect outliers in gene expression and splicing for cases that remained undiagnosed despite standard genomic and transcriptomic analysis.RESULTSThe transcriptome-directed approach resulted in a diagnostic rate of 12% across the entire cohort, or 17% after excluding cases solved on ES/GS alone. Newly diagnosed conditions included Koolen-de Vries syndrome (KANSL1), Renpenning syndrome (PQBP1), TBCK-associated encephalopathy, NSD2- and CLTC-related intellectual disability, and others, all with negative conventional genomic testing, including ES and chromosomal microarray (CMA). Skin fibroblasts exhibited higher and more consistent expression of clinically relevant genes than whole blood. In solved cases with RNA-seq from both tissues, the causative defect was missed in blood in half the cases but none from fibroblasts.CONCLUSIONSFor our cohort of undiagnosed individuals with suspected Mendelian conditions, transcriptome-directed genomic analysis facilitated diagnoses, primarily through the identification of variants missed on ES and CMA.TRIAL REGISTRATIONNot applicable.FUNDINGNIH Common Fund, BCM Intellectual and Developmental Disabilities Research Center, Eunice Kennedy Shriver National Institute of Child Health & Human Development. Show less
no PDF DOI: 10.1172/JCI141500
KANSL1
Marlena S Fejzo, Hsiao-Wang Chen, Lee Anderson +4 more · 2021 · Gynecologic oncology · Elsevier · added 2026-04-24
There is an immunoreactive subtype of ovarian cancer with a favorable prognosis, but the majority of ovarian cancers have limited immune reactivity. The reason for this is poorly understood. This stud Show more
There is an immunoreactive subtype of ovarian cancer with a favorable prognosis, but the majority of ovarian cancers have limited immune reactivity. The reason for this is poorly understood. This study aimed to approach this question by identifying prognostically relevant genes whose prognostic mRNA expression levels correlated with a genomic event. Expression microarray and 5-year survival data on 170 ovarian tumors and aCGH data on 45 ovarian cancer cell lines were used to identify amplified/deleted genes associated with prognosis. Three immune-response genes were identified mapping to epigenetically modified chromosome 6p21.3. Genes were searched for roles in epigenetic modification, identifying KANSL1. Genome-wide association studies were searched to identify genetic variants in KANSL1 associated with altered immune profile. Sensitivity to HDAC inhibition in cell lines with KANSL1 amplification/rearrangement was studied. Expression of 196 genes was statistically significantly associated with survival, and expression levels correlated with copy number variations for 82 of them. Among these, 3 immune-response genes (HCP5, PSMB8, PSMB9) clustered together at epigenetically modified chromosome 6p21.3 and their expression was inversely correlated to epigenetic modification gene KANSL1. KANSL1 is amplified/rearranged in ovarian cancer, associated with lymphocyte profile, a biomarker for response to HDAC inhibition, and may drive expression of immune-response genes. This study identifies 82 genes with prognostic relevance and genomic alteration in ovarian cancer. Among these, immune-response genes have correlated expression which is associated with 5-year survival. KANSL1 may be a master gene altering immune-response gene expression at 6p21.3 and drive response to HDAC inhibitors. Future research should investigate KANSL1 and determine whether targeting it alters the immune profile of ovarian cancer and improves survival, HDAC inhibition, and/or immunotherapy response. Show less
no PDF DOI: 10.1016/j.ygyno.2020.11.008
KANSL1
Yutian Li, Shan Deng, Xiaohong Wang +12 more · 2021 · Cardiovascular research · Oxford University Press · added 2026-04-24
Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) Show more
Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) has previously been implicated to regulate inflammatory responses, yet its role in inflammation-associated cardiac dysfunction is virtually unknown. Using the CRISPR/Cas9 system, we generated a global Sectm1a-knockout (KO) mouse model and observed significantly increased mortality and cardiac injury after lipopolysaccharide (LPS) injection, when compared with wild-type (WT) control. Further analysis revealed significantly increased accumulation of inflammatory macrophages in hearts of LPS-treated KO mice. Accordingly, ablation of Sectm1a remarkably increased inflammatory cytokines levels both in vitro [from bone marrow-derived macrophages (BMDMs)] and in vivo (in serum and myocardium) after LPS challenge. RNA-sequencing results and bioinformatics analyses showed that the most significantly down-regulated genes in KO-BMDMs were modulated by LXRα, a nuclear receptor with robust anti-inflammatory activity in macrophages. Indeed, we identified that the nuclear translocation of LXRα was disrupted in KO-BMDMs when treated with GW3965 (LXR agonist), resulting in higher levels of inflammatory cytokines, compared to GW3965-treated WT-cells. Furthermore, using chronic inflammation model of high-fat diet (HFD) feeding, we observed that infiltration of inflammatory monocytes/macrophages into KO-hearts were greatly increased and accordingly, worsened cardiac function, compared to WT-HFD controls. This study defines Sectm1a as a new regulator of inflammatory-induced cardiac dysfunction through modulation of LXRα signalling in macrophages. Our data suggest that augmenting Sectm1a activity may be a potential therapeutic approach to resolve inflammation and associated cardiac dysfunction. Show less
no PDF DOI: 10.1093/cvr/cvaa067
NR1H3
Rachel G Miller, Stuart J McGurnaghan, Suna Onengut-Gumuscu +5 more · 2021 · Journal of diabetes and its complications · Elsevier · added 2026-04-24
To examine candidate insulin resistance single nucleotide polymorphisms (SNPs) for associations with glycemic control, insulin resistance, BMI, and complications in an observational type 1 diabetes (T Show more
To examine candidate insulin resistance single nucleotide polymorphisms (SNPs) for associations with glycemic control, insulin resistance, BMI, and complications in an observational type 1 diabetes (T1D) cohort: the Pittsburgh Epidemiology of Diabetes Complications (EDC) study. In 422 European-ancestry participants, we assessed associations using additive models between 15 candidate SNPs and 25-year mortality, cardiovascular disease, microalbuminuria, overt nephropathy and proliferative retinopathy, and 25-year mean HbA1c, estimated glucose disposal rate (eGDR, inverse measure of insulin resistance), and BMI. The A allele of rs12970134 was associated with higher mean HbA1c (β = +0.34 ± 0.09, p = 0.00009) and nominally associated with worse eGDR (p = 0.02). Further analyses suggest the HbA1c association may be modified by diabetes therapy regimen: rs12970134 AA genotype was associated with higher HbA1c under non-intensive therapy conditions (<3 insulin injections/day or monitoring blood glucose<3 times/day [p = 0.004]), but not under intensive therapy (≥3 injections/day or insulin pump and monitoring glucose≥3 times/day [p = 0.71]). There were no significant associations between any SNPs and BMI or complications. rs12970134, near MC4R, is strongly associated with HbA1c in this cohort. Further exploration of this genomic region is warranted, as it may hold promise for discovering new therapeutic targets to improve glycemic control in T1D. Show less
📄 PDF DOI: 10.1016/j.jdiacomp.2020.107842
MC4R
Rong He, Wei Han, Xiaojie Song +3 more · 2021 · 3 Biotech · Springer · added 2026-04-24
The purpose of this study was to determine the dynamic changes of the Nogo-66 receptor 1 (NgR1) pathway during epileptogenesis and the potential beneficial of leucine-rich repeat and Ig-like domain-co Show more
The purpose of this study was to determine the dynamic changes of the Nogo-66 receptor 1 (NgR1) pathway during epileptogenesis and the potential beneficial of leucine-rich repeat and Ig-like domain-containing Nogo receptor interacting protein 1 (Lingo-1) inhibition on epilepsy rats. The hippocampal changes of the NgR1 pathway during epileptogenesis were determined by western blot analysis of multiple proteins, including neurite outgrowth inhibitor protein A (NogoA), myelin-associated glycoprotein (MAG), oligodendrocyte-myelin glycoprotein (OMgp), Lingo-1, ras homolog family member A (RhoA) and phosphorylated RhoA (p-RhoA). Lentivirus-mediated short hairpin RNA (shRNA) was used to knockdown the hippocampal expression of Lingo-1. Novel object recognition (NOR) test and Morris Water Maze (MWM) test were employed to determine the cognitive functions of rats. Hematoxylin and eosin (H&E) staining, protein expressions of RhoA, p-RhoA, and myelin basic protein (MBP), as well as convulsion susceptibility test were additionally performed. Our results showed that the NgR1 pathway was activated during epileptogenesis, characterized by up-regulation of NogoA, MAG, OMgp, and Lingo-1, which was especially significant at the chronic phase of epilepsy. The cognitive function, convulsion susceptibility and hippocampal neuronal survival of rats were impaired at the chronic phase of epileptogenesis but all improved by Lingo-1 inhibition; besides, the hippocampal protein expressions of p-RhoA and MBP were significantly decreased at the chronic phase of SC rats but increased after Lingo-1 inhibition. Our results demonstrated that Lingo-1 shRNA can improve epilepsy-induced cognitive impairment, which may be related with the pro-myelination and neuroprotection effects of Lingo-1 inhibition. Show less
no PDF DOI: 10.1007/s13205-021-02876-8
LINGO1
Suranjana Goswami, Xiaojun Hu, Qian Chen +6 more · 2021 · Journal of acquired immune deficiency syndromes (1999) · added 2026-04-24
Interleukin-27 (IL-27) is known as an anti-HIV cytokine. We have recently demonstrated that IL-27-pretreatment promotes phytohemagglutinin-stimulated CD4(+) T cells into HIV-1-resistant cells by inhib Show more
Interleukin-27 (IL-27) is known as an anti-HIV cytokine. We have recently demonstrated that IL-27-pretreatment promotes phytohemagglutinin-stimulated CD4(+) T cells into HIV-1-resistant cells by inhibiting an uncoating step. To further characterize the function of the HIV resistant T cells, we investigated profiles of microRNA in the cells using microRNA sequencing (miRNA-seq) and assessed anti-HIV effect of the microRNAs. Phytohemagglutinin-stimulated CD4(+) T cells were treated with or without IL-27 for 3 days. MicroRNA profiles were analyzed using miRNA-seq. To assess anti-HIV effect, T cells or macrophages were transfected with synthesized microRNA mimics and then infected with HIVNL4.3 or HIVAD8. Anti-HIV effect was monitored by a p24 antigen enzyme-linked immunosorbent assay kit. interferon (IFN)-α, IFN-β, or IFN-λ production was quantified using each subtype-specific enzyme-linked immunosorbent assay kit. A comparative analysis of microRNA profiles indicated that expression of known miRNAs was not significantly changed in IL-27-treated cells compared with untreated T cells; however, a total of 15 novel microRNAs (miRTC1 ∼ miRTC15) were identified. Anti-HIV assay using overexpression of each novel microRNA revealed that 10 nM miRTC14 (GenBank accession number: MF281439) remarkably suppressed HIV infection by (99.3 ± 0.27%, n = 9) in macrophages but not in T cells. The inhibition was associated through induction of >1000 pg/mL of IFN-αs and IFN-λ1. We discovered a total of 15 novel microRNAs in T cells and characterized that miRTC14, one of the novel microRNAs, was a potent IFN-inducing anti-HIV miRNA, implicating that regulation of the expression of miRTC14 may be a potent therapeutic tool for not only HIV but also other virus infection. Show less
📄 PDF DOI: 10.1097/QAI.0000000000002565
IL27
Guan Yang, Wenqiang Song, J Luke Postoak +5 more · 2021 · Autophagy · Taylor & Francis · added 2026-04-24
The PIK3C3/VPS34 subunit of the class III phosphatidylinositol 3-kinase (PtdIns3K) complex is a key early player in macroautophagy/autophagy. In this study, we assessed the contribution of PIK3C3 to T Show more
The PIK3C3/VPS34 subunit of the class III phosphatidylinositol 3-kinase (PtdIns3K) complex is a key early player in macroautophagy/autophagy. In this study, we assessed the contribution of PIK3C3 to T cell metabolism and function. We found that Show less
no PDF DOI: 10.1080/15548627.2020.1752979
PIK3C3
Lisha Chang, Jingyue Wang, Fuling Zhou +4 more · 2021 · Journal of neuro-oncology · Springer · added 2026-04-24
Long noncoding RNAs (LncRNAs) are essential epigenetic regulators with critical roles in tumor initiation and malignant progression; however, the mechanism by which aberrantly expressed lncRNA RP11-84 Show more
Long noncoding RNAs (LncRNAs) are essential epigenetic regulators with critical roles in tumor initiation and malignant progression; however, the mechanism by which aberrantly expressed lncRNA RP11-84E24.3 regulates the pathogenesis of glioma is not fully understood. Here, we investigate the function of lncRNA RP11-84E24.3 in glioma onset and progression as well as identify a molecular pathway regulated by this lncRNA. Differentially expressed lncRNAs related to glioma were identified. The aberrant expression of lncRNA RP11-84E24.3 was verified in samples from patients with glioma as well as glioma cell lines. The role of lncRNA RP11-8424.3 in proliferation, apoptosis, migration, and invasion was assessed using gain- and loss-of function approaches, EdU incorporation, flow cytometry, wound healing and Transwell invasion assays. Western blot analysis was utilized to examine the expression of proteins associated with epithelial-to-mesenchymal transition (EMT). The interaction between lncRNA RP11-84E24.3, TFAP2C and SNAI1 was confirmed using RNA pull-down, ChIP and luciferase reporter assays. LncRNA RP11-84E24.3 was up-regulated in both glioma tissues and cell lines. LncRNA RP11-84E24.3 overexpression enhanced the proliferation, migration and invasion of glioma cells while reducing apoptosis. This was associated with a decrease in E-cadherin expression and an increase in N-cadherin and Vimentin expression. LncRNA RP11-84E24.3 directly targeted TFAP2C protein, resulting in increased SNAI1 expression. Knockdown of TFAP2C or SNAI1 reversed the effects of lncRNA RP11-84E24.3 overexpression, while silencing lncRNA RP11-84E24.3 inhibited tumor formation of glioma cells in vivo. LncRNA RP11-84E24.3 increased SNAI1 expression by forming a complex with TFAP2C protein, promoting EMT in glioma cells and tumor formation. Show less
no PDF DOI: 10.1007/s11060-020-03624-3
SNAI1
XiaoYan Guo, Shunyou Chen, Mingrui Lin +3 more · 2021 · Genetic testing and molecular biomarkers · added 2026-04-24
no PDF DOI: 10.1089/gtmb.2021.0030
EXT1
Ying-Ting Wu, Si-Yu Ma, Wen-Qin Sun +4 more · 2021 · The Journal of clinical endocrinology and metabolism · added 2026-04-24
Endometriosis (EM) is a benign gynecological disease that shares some characteristics with malignancy, such as proliferation and invasion. So far, the pathogenesis of EM is still unclear. In this stud Show more
Endometriosis (EM) is a benign gynecological disease that shares some characteristics with malignancy, such as proliferation and invasion. So far, the pathogenesis of EM is still unclear. In this study, we investigated whether TRIM65 can play a role in the development of EM. TRIM65 expression levels in eutopic, ectopic, and normal endometrium were detected by quantitative real-time PCR and Western blot. Cell proliferation and invasion of primary endometrial stromal (EMS) cells were detected by CCK-8 and Transwell analysis. The interaction between TRIM65 and DUSP6 or C-myc was measured by coimmunoprecipitation, ubiquitylation, dual luciferase, and chromatin immunoprecipitation analysis. We found that TRIM65 was identified as an up-regulated gene in ectopic endometrial tissues and EMS cells compared with control groups without EM. TRIM65 expression was positively correlated with the levels of p-ERK1/2, C-myc, matrix metalloproteinase-2, and integrin β1 in ectopic endometrial tissues in patients and mice. TRIM65 promoted the cell proliferation and invasion of EMS cells via the ERK1/2/C-myc pathway through ubiquitination of DUSP6. C-myc promoted TRIM65 expression through inducing TRIM65 promoter activity. Additionally, the increased expression of TRIM65, C-myc, matrix metalloproteinase-2, integrin β1, and p-ERK1/2 and the decreased expression of DUSP6 in ectopic endometrial tissues were significantly suppressed by inhibition of ERK1/2 signaling pathway in ectopic endometrial tissues in experimental mice model. In conclusion, TRIM65 promotes invasion of ectopic EMS cells by activating a feedback loop with the ERK1/2/C-myc signaling pathway and may be a potential therapeutic target for EM. Show less
no PDF DOI: 10.1210/clinem/dgaa804
DUSP6
Liang Han, Zhe Chen, Kun Yu +12 more · 2021 · Frontiers in immunology · Frontiers · added 2026-04-24
The occurrence and development of rheumatoid arthritis (RA) is regulated by numerous cytokines. Interleukin 27 (IL-27) is a soluble cytokine that exerts biological effects by regulating the Janus tyro Show more
The occurrence and development of rheumatoid arthritis (RA) is regulated by numerous cytokines. Interleukin 27 (IL-27) is a soluble cytokine that exerts biological effects by regulating the Janus tyrosine kinase (JAK)/signal transducer and activator of the transcription (STAT) signaling pathway Show less
📄 PDF DOI: 10.3389/fimmu.2021.787252
IL27
Wei Wang, Yue-Jun Lin, Zhao-Xia Chen +1 more · 2021 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
The melanocortin-3 receptor (MC3R) and melanocortin-4 receptor (MC4R), known as neural melanocortin receptors, have been implicated to be critical components of the hypothalamic leptin-melanocortin pa Show more
The melanocortin-3 receptor (MC3R) and melanocortin-4 receptor (MC4R), known as neural melanocortin receptors, have been implicated to be critical components of the hypothalamic leptin-melanocortin pathway and related to obesity pathogenesis. In contrast to extensive evidence from physiologic, biological, genetic studies demonstrating that MC4R is a critical regulator in obesity, whether MC3R mutation causes obesity is still controversial. In the present study, we screened for coding variants in the MC3R gene of 176 obese individuals (mean BMI 34.84 ± 0.19 kg/m Show less
no PDF DOI: 10.1016/j.bbadis.2021.166107
MC4R
Yin-Huai Chen, Diane B Zastrow, Riley D Metcalfe +25 more · 2021 · The Journal of allergy and clinical immunology · Elsevier · added 2026-04-24
Biallelic variants in IL6ST, encoding GP130, cause a recessive form of hyper-IgE syndrome (HIES) characterized by high IgE level, eosinophilia, defective acute phase response, susceptibility to bacter Show more
Biallelic variants in IL6ST, encoding GP130, cause a recessive form of hyper-IgE syndrome (HIES) characterized by high IgE level, eosinophilia, defective acute phase response, susceptibility to bacterial infections, and skeletal abnormalities due to cytokine-selective loss of function in GP130, with defective IL-6 and IL-11 and variable oncostatin M (OSM) and IL-27 levels but sparing leukemia inhibitory factor (LIF) signaling. Our aim was to understand the functional and structural impact of recessive HIES-associated IL6ST variants. We investigated a patient with HIES by using exome, genome, and RNA sequencing. Functional assays assessed IL-6, IL-11, IL-27, OSM, LIF, CT-1, CLC, and CNTF signaling. Molecular dynamics simulations and structural modeling of GP130 cytokine receptor complexes were performed. We identified a patient with compound heterozygous novel missense variants in IL6ST (p.Ala517Pro and the exon-skipping null variant p.Gly484_Pro518delinsArg). The p.Ala517Pro variant resulted in a more profound IL-6- and IL-11-dominated signaling defect than did the previously identified recessive HIES IL6ST variants p.Asn404Tyr and p.Pro498Leu. Molecular dynamics simulations suggested that the p.Ala517Pro and p.Asn404Tyr variants result in increased flexibility of the extracellular membrane-proximal domains of GP130. We propose a structural model that explains the cytokine selectivity of pathogenic IL6ST variants that result in recessive HIES. The variants destabilized the conformation of the hexameric cytokine receptor complexes, whereas the trimeric LIF-GP130-LIFR complex remained stable through an additional membrane-proximal interaction. Deletion of this membrane-proximal interaction site in GP130 consequently caused additional defective LIF signaling and Stüve-Wiedemann syndrome. Our data provide a structural basis to understand clinical phenotypes in patients with IL6ST variants. Show less
no PDF DOI: 10.1016/j.jaci.2021.02.044
IL27
Lifang Hu, Chong Yin, Dong Chen +9 more · 2021 · Cell death and differentiation · Nature · added 2026-04-24
Osteoblast differentiation leading to bone formation requires a coordinated transcriptional program. Osteoblastic cells with low level of microtubule actin crosslinking factor 1 (MACF1) show reduced o Show more
Osteoblast differentiation leading to bone formation requires a coordinated transcriptional program. Osteoblastic cells with low level of microtubule actin crosslinking factor 1 (MACF1) show reduced osteoblast differentiation ability, however, the comprehensive mechanism of MACF1's action remains unexplored. In the current study, we found that MACF1 knockdown suppressed osteoblast differentiation by altering the transcriptome dynamics. We further identified two MACF1-interacted proteins, cyclin-dependent kinase 12 (CDK12) and MYST/Esa1-associated factor 6 (MEAF6), and two MACF1-interacted transcription factors (TFs), transcription factor 12 (TCF12) and E2F transcription factor 6 (E2F6), which repress osteoblast differentiation by altering the expression of osteogenic TFs and genes. Moreover, we found that MACF1 regulated cytoplasmic-nuclear localization of itself, TCF12 and E2F6 in a concentration-dependent manner. MACF1 oppositely regulates the expression of TCF12 and transcription factor 7 (TCF7), two TFs that drive osteoblast differentiation to opposite directions. This study reveals that MACF1, a cytoskeletal protein, acts as a sponge for repressors of osteoblast differentiation to promote osteoblast differentiation and contributes to a novel mechanistic insight of osteoblast differentiation and transcription dynamics. Show less
no PDF DOI: 10.1038/s41418-021-00744-9
MACF1
Yuan Hu, Yichen Wang, Chao Chen +4 more · 2021 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Kaixinsan (KXS) decoction, as an herbal formula, was used to treat the diseases, such as insomnia, amnesia, emotional disorders in ancient china. It has been demonstrated to be active in various anima Show more
Kaixinsan (KXS) decoction, as an herbal formula, was used to treat the diseases, such as insomnia, amnesia, emotional disorders in ancient china. It has been demonstrated to be active in various animal models resembling human depression with multitarget effects. However, effective verification on the clinical application of KXS is still lacking. Supplements in this knowledge field are urgently needed. This very first study evaluated the efficacy and tolerability of ShenZhiLing (SZL) tablets (KXS preparation), compared with fluoxetine (FLX, positive comparator), in patients with mild to moderate depressive disorder. In this randomized, double-blind, parallel-group study, 156 patients with mild to moderate depression without taken any antidepressants in the past 6 months or 4 continuous weeks were randomized to receive either 3.2 g/d SZL plus 20 mg/d FLX placebo (SZL group) or 20 mg/d FLX plus 3.2 g/d SZL placebo (FLX group), for 8 weeks. Their clinical presentations and some metabolic indexes were assessed during the 8 weeks' visiting period. Patients in SZL group showed a statistically significant improvement after 8 weeks of treatment in HAM-D17 score (18.79±2.09 to 4.43±4.71, p<0.001) and self-rating depression scale (SDS) score (58.49±8.89 to 39.84±12.09, p<0.001), but not in N-back total respond time (1145.55±608.26 to 1128.47±387.49, p>0.05). In addition, no significant difference at 8 weeks of treatment was found between SZL and FLX groups in SDS score (39.84±12.09 vs. 36.63±12.44) and N-back respond time (1128.47±387.49 vs. 1089.43±352.08) as well as reduction of HAM-D17 score (14.79±4.88 vs. 15.24±4.29) (p>0.05 for all). However, the serum APOB, APOC3 and ALB levels and LDL-C/HDL-C ratio decreased significantly in patients after SZL treatment, while only APOB/APOA1 ratio decreased significantly in FLX group. Other metabolic indexes did not alter significantly after treated with SZL or FLX. The efficacy and safety profile of SZL are comparable to that of fluoxetine in patients with mild to moderate depression. The beneficial effect of SZL is probably associated with improvement of lipid metabolic balance. Show less
no PDF DOI: 10.1016/j.jep.2021.114549
APOC3
Yong-Ping Chen, Xiao-Jing Gu, Wei Song +10 more · 2021 · Journal of Parkinson's disease · added 2026-04-24
Genetic studies have indicated that variants in several lysosomal genes are risk factors for idiopathic Parkinson's disease (PD). However, the role of lysosomal genes in PD in Asian populations is lar Show more
Genetic studies have indicated that variants in several lysosomal genes are risk factors for idiopathic Parkinson's disease (PD). However, the role of lysosomal genes in PD in Asian populations is largely unknown. This study aimed to analyze rare variants in lysosomal related genes in Chinese population with early-onset and familial PD. In total, 1,136 participants, including 536 and 600 patients with sporadic early-onset PD (SEOPD) and familial PD, respectively, underwent whole-exome sequencing to assess the genetic etiology. Rare variants in PD were investigated in 67 candidate lysosomal related genes (LRGs), including 15 lysosomal function-related genes and 52 lysosomal storage disorder genes. Compared with the autosomal dominant PD (ADPD) or SEOPD cohorts, a much higher proportion of patients with multiple rare damaging variants of LRGs were found in the autosomal recessive PD (ARPD) cohort. At a gene level, rare damaging variants in GBA and MAN2B1 were enriched in PD, but in SCARB2, MCOLN1, LYST, VPS16, and VPS13C were much less in patients. At an allele level, GBA p. Leu483Pro was found to increase the risk of PD. Genotype-phenotype correlation showed no significance in the clinical features among patients carrying a discrepant number of rare variants in LRGs. Our study suggests rare variants in LRGs might be more important in the pathogenicity of ARPD cases compared with ADPD or SEOPD. We further confirm rare variants in GBA are involve in PD pathogenecity and other genes associated with PD identified in this study should be supported with more evidence. Show less
no PDF DOI: 10.3233/JPD-212658
VPS13C
Yingying Yue, Chang Zhang, Xiaoyun Zhao +9 more · 2021 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Contraction-stimulated glucose uptake in skeletal muscle requires Rac1, but the molecular mechanism of its activation is not fully understood. Treadmill running was applied to induce C57BL/6 mouse hin Show more
Contraction-stimulated glucose uptake in skeletal muscle requires Rac1, but the molecular mechanism of its activation is not fully understood. Treadmill running was applied to induce C57BL/6 mouse hind limb skeletal muscle contraction in vivo and electrical pulse stimulation contracted C2C12 myotube cultures in vitro. The protein levels or activities of AMPK or the Rac1-specific GEF, Tiam1, were manipulated by activators, inhibitors, siRNA-mediated knockdown, and adenovirus-mediated expression. Activated Rac1 was detected by a pull-down assay and immunoblotting. Glucose uptake was measured using the 2-NBD-glucose fluorescent analog. Electrical pulse stimulated contraction or treadmill exercise upregulated the expression of Tiam1 in skeletal muscle in an AMPK-dependent manner. Axin1 siRNA-mediated knockdown diminished AMPK activation and upregulation of Tiam1 protein expression by contraction. Tiam1 siRNA-mediated knockdown diminished contraction-induced Rac1 activation, GLUT4 translocation, and glucose uptake. Contraction increased Tiam1 gene expression and serine phosphorylation of Tiam1 protein via AMPK. These findings suggest Tiam1 is part of an AMPK-Tiam1-Rac1 signaling pathway that mediates contraction-stimulated glucose uptake in skeletal muscle cells and tissue. Show less
no PDF DOI: 10.1096/fj.202001312R
AXIN1
Shi Yao, Hao Wu, Jing-Miao Ding +5 more · 2021 · International journal of obesity (2005) · Nature · added 2026-04-24
Childhood obesity is one of the most common and costly nutritional problems with high heritability. The genetic mechanism of childhood obesity remains unclear. Here, we conducted a transcriptome-wide Show more
Childhood obesity is one of the most common and costly nutritional problems with high heritability. The genetic mechanism of childhood obesity remains unclear. Here, we conducted a transcriptome-wide association study (TWAS) to identify novel genes for childhood obesity. By integrating the GWAS summary of childhood body mass index (BMI), we conducted TWAS analyses with pre-computed gene expression weights in 39 obesity priority tissues. The GWAS summary statistics of childhood BMI were derived from the early growth genetics consortium with 35,668 children from 20 studies. We identified 15 candidate genes for childhood BMI after Bonferroni corrections. The most significant gene, ADCY3, was identified in 13 tissues, including adipose, brain, and blood. Interestingly, eight genes were only identified in the specific tissue, such as FAIM2 in the brain (P = 2.04 × 10 Our study identified multiple candidate genes for childhood BMI, providing novel clues for understanding the genetic mechanism of childhood obesity. Show less
no PDF DOI: 10.1038/s41366-021-00780-y
ADCY3
Miguel Gozalo-Marcilla, Jaap Buntjer, Martin Johnsson +8 more · 2021 · Genetics, selection, evolution : GSE · BioMed Central · added 2026-04-24
Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide assoc Show more
Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10 We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis. Show less
📄 PDF DOI: 10.1186/s12711-021-00671-w
MC4R
Yoav Peleg, Renaud Vincentelli, Brett M Collins +30 more · 2021 · Journal of molecular biology · Elsevier · added 2026-04-24
Recent years have seen a dramatic improvement in protein-design methodology. Nevertheless, most methods demand expert intervention, limiting their widespread adoption. By contrast, the PROSS algorithm Show more
Recent years have seen a dramatic improvement in protein-design methodology. Nevertheless, most methods demand expert intervention, limiting their widespread adoption. By contrast, the PROSS algorithm for improving protein stability and heterologous expression levels has been successfully applied to a range of challenging enzymes and binding proteins. Here, we benchmark the application of PROSS as a stand-alone tool for protein scientists with no or limited experience in modeling. Twelve laboratories from the Protein Production and Purification Partnership in Europe (P4EU) challenged the PROSS algorithm with 14 unrelated protein targets without support from the PROSS developers. For each target, up to six designs were evaluated for expression levels and in some cases, for thermal stability and activity. In nine targets, designs exhibited increased heterologous expression levels either in prokaryotic and/or eukaryotic expression systems under experimental conditions that were tailored for each target protein. Furthermore, we observed increased thermal stability in nine of ten tested targets. In two prime examples, the human Stem Cell Factor (hSCF) and human Cadherin-Like Domain (CLD12) from the RET receptor, the wild type proteins were not expressible as soluble proteins in E. coli, yet the PROSS designs exhibited high expression levels in E. coli and HEK293 cells, respectively, and improved thermal stability. We conclude that PROSS may improve stability and expressibility in diverse cases, and that improvement typically requires target-specific expression conditions. This study demonstrates the strengths of community-wide efforts to probe the generality of new methods and recommends areas for future research to advance practically useful algorithms for protein science. Show less
📄 PDF DOI: 10.1016/j.jmb.2021.166964
DYM
Ruimei Zhou, Jiashun Liao, Dunpeng Cai +5 more · 2021 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Renal interstitial fibrosis (RIF) is a pathological process that fibrotic components are excessively deposited in the renal interstitial space due to kidney injury, resulting in impaired renal functio Show more
Renal interstitial fibrosis (RIF) is a pathological process that fibrotic components are excessively deposited in the renal interstitial space due to kidney injury, resulting in impaired renal function and chronic kidney disease. The molecular mechanisms controlling renal fibrosis are not fully understood. In this present study, we identified Nuclear protein 1 (Nupr1), a transcription factor also called p8, as a novel regulator promoting renal fibrosis. Unilateral ureteral obstruction (UUO) time-dependently induced Nupr1 mRNA and protein expression in mouse kidneys while causing renal damage and fibrosis. Nupr1 deficiency (Nupr1 Show less
no PDF DOI: 10.1096/fj.202000926RR
SNAI1
Xuqian Fang, Xiaoqiong Wu, Enfei Xiang +5 more · 2021 · Oncology letters · added 2026-04-24
Carbamoyl phosphate synthetase 1 (CPS1), which is the antigen for the hepatocyte paraffin 1 antibody, exhibits focal immunoreactivity in adenocarcinoma from the gastrointestinal tract, but its express Show more
Carbamoyl phosphate synthetase 1 (CPS1), which is the antigen for the hepatocyte paraffin 1 antibody, exhibits focal immunoreactivity in adenocarcinoma from the gastrointestinal tract, but its expression profiles and roles in gastric cancer (GC) remain largely unknown. The present study aimed to determine the expression pattern and prognostic value of CPS1 in Correa's cascade using tissues from 32 patients with chronic atrophic gastritis with intestinal metaplasia (IM), 62 patients with low- or high-grade intraepithelial neoplasia (IN) and 401 patients with GC. The expression of CPS1 was diffuse and strongly positive in 32 cases (100%) of IM of the glandular epithelium, and gradually downregulated in Correa's cascade, with a strongly positive ratio of 21 (70%) in low-grade IN and 4 (12.5%) in high-grade IN. The levels of CPS1 expression were significantly higher in diffuse-type GC, with 37 (26%) cases strongly positive for CPS1, compared with 14 (8%) in intestinal-type and 11 (13%) cases in mixed-type GC. In intestinal-type GC, CPS1 expression was completely lost in 107 (62%) of cases, which was associated with an advanced Tumor-Node-Metastasis stage (P=0.031) and depth of invasion (P=0.037). Kaplan-Meier analysis suggested that low CPS1 expression levels were independently associated with a short overall survival (OS) time in the three types of GC (P<0.001 in intestinal-type, P=0.003 in diffuse-type and P=0.018 in mixed-type GC). Furthermore, low levels of CPS1 mRNA and high methylation levels in the CPS1 promoter were associated with a short OS time in patients with GC. These results suggested that the expression of CPS1 was progressively downregulated in Correa's cascade, and that CPS1 may serve as a prognostic marker for patients with GC, regardless of tumor type. Show less
📄 PDF DOI: 10.3892/ol.2021.12702
CPS1
Bin Li, Guihu Zhao, Qiao Zhou +19 more · 2021 · Frontiers in neuroscience · Frontiers · added 2026-04-24
Parkinson's disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is Show more
Parkinson's disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is no database that integrate different type of genetic data, and support analyzing of PD-associated genes (PAGs). By systematic review and curation of multiple lines of public studies, we integrate multiple layers of genetic data (rare variants and copy-number variants identified from patients with PD, associated variants identified from genome-wide association studies, differentially expressed genes, and differential DNA methylation genes) and age at onset in PD. We integrated five layers of genetic data (8302 terms) with different levels of evidences from more than 3,000 studies and prioritized 124 PAGs with strong or suggestive evidences. These PAGs were identified to be significantly interacted with each other and formed an interconnected functional network enriched in several functional pathways involved in PD, suggesting these genes may contribute to the pathogenesis of PD. Furthermore, we identified 10 genes were associated with a juvenile-onset (age ≤ 30 years), 11 genes were associated with an early-onset (age of 30-50 years), whereas another 10 genes were associated with a late-onset (age > 50 years). Notably, the AAOs of patients with loss of function variants in five genes were significantly lower than that of patients with deleterious missense variants, while patients with Show less
no PDF DOI: 10.3389/fnins.2021.679568
VPS13C
Guohua Chen, Xiaobing He, Huaijie Jia +6 more · 2021 · Virology journal · BioMed Central · added 2026-04-24
Orf virus (ORFV) is a member of the genus Parapoxvirus and family Poxviridae. The virus has a worldwide distribution and infects sheep, goats, humans, and wild animals. However, due to the complex str Show more
Orf virus (ORFV) is a member of the genus Parapoxvirus and family Poxviridae. The virus has a worldwide distribution and infects sheep, goats, humans, and wild animals. However, due to the complex structure of the poxvirus, the underlying mechanism of the entry and infection by ORFV remains largely unknown. ORFV ORF047 encodes a protein named L1R. Poxviral L1R serves as the receptor-binding protein and blocks virus binding and entry independently of glycosaminoglycans (GAGs). The study aimed to identify the host interaction partners of ORFV ORF047. Yeast two-hybrid cDNA library of sheep testicular cells was applied to screen the host targets with ORF047 as the bait. ORF047 was cloned into a pBT3-N vector and expressed in the NMY51 yeast strain. Then, the expression of bait proteins was validated by Western blot analysis. Sheep SERP1and PABPC4 were identified as host target proteins of ORFV ORF047, and a Co-IP assay further verified their interaction. New host cell proteins SERP1and PABPC4 were found to interact with ORFV ORF047 and might involve viral mRNA translation and replication. Show less
no PDF DOI: 10.1186/s12985-021-01499-y
PABPC4
Xin-Ya Qin, Qing-Hong Shan, Hui Fang +5 more · 2021 · Acta neuropathologica · Springer · added 2026-04-24
Since the discovery of ketamine anti-depressant effects in last decade, it has effectively revitalized interest in investigating excitatory synapses hypothesis in the pathogenesis of depression. In th Show more
Since the discovery of ketamine anti-depressant effects in last decade, it has effectively revitalized interest in investigating excitatory synapses hypothesis in the pathogenesis of depression. In the present study, we aimed to reveal the excitatory synaptic regulation of corticotropin-releasing hormone (CRH) neuron in the hypothalamus, which is the driving force in hypothalamic-pituitary-adrenal (HPA) axis regulation. This study constitutes the first observation of an increased density of PSD-93-CRH co-localized neurons in the hypothalamic paraventricular nucleus (PVN) of patients with major depression. PSD-93 overexpression in CRH neurons in the PVN induced depression-like behaviors in mice, accompanied by increased serum corticosterone level. PSD-93 knockdown relieved the depression-like phenotypes in a lipopolysaccharide (LPS)-induced depression model. Electrophysiological data showed that PSD-93 overexpression increased CRH neurons synaptic activity, while PSD-93 knockdown decreased CRH neurons synaptic activity. Furthermore, we found that LPS induced increased the release of glutamate from microglia to CRH neurons resulted in depression-like behaviors using fiber photometry recordings. Together, these results show that PSD-93 is involved in the pathogenesis of depression via increasing the synaptic activity of CRH neurons in the PVN, leading to the hyperactivity of the HPA axis that underlies depression-like behaviors. Show less
no PDF DOI: 10.1007/s00401-021-02371-7
DLG2
Hongyan Cui, Yue Wang, Lili Chen +8 more · 2021 · Journal of controlled release : official journal of the Controlled Release Society · Elsevier · added 2026-04-24
Molecular insights into tumorigenesis have uncovered intimate correlation of SNAI1 with tumor malignancy. Herein, to explore merits of SNAI1-knockdown in tumor therapy, we harnessed RNA interference t Show more
Molecular insights into tumorigenesis have uncovered intimate correlation of SNAI1 with tumor malignancy. Herein, to explore merits of SNAI1-knockdown in tumor therapy, we harnessed RNA interference tool (shSNAI1), together with chemotherapeutic doxorubicin. Owing to abundant hydroxyl groups, pullulan was attempted to be covalently conjugated with a multiple of functional moieties, including positively-charged oligoethylenimine components for electrostatic entrapment of polyanionic shSNAI1 and hydrophobic components for entrapment of lipophilic doxorubicin. Notably, the aforementioned covalent conjugations were tailored to be detachable in response to intracellular reducing microenvironment owing to redox disulfide linkage, thereby accounting for selective intracellular liberation of the therapeutic payloads. Moreover, the surface of nanomedicine was modified with hyaluronic acid, endowing not only excellent biocompatibilities but active tumor-targeting function due to its receptors (CD44) overexpressed on tumor cells. Subsequent investigations approved appreciably targeted co-delivery of shSNAI1 and doxorubicin into solid lung tumors via systemic administration and demonstrated critical contribution of SNAI1-knockdown in amplifying chemotherapeutic potencies. Show less
no PDF DOI: 10.1016/j.jconrel.2021.07.039
SNAI1
Sufang Peng, Hang Su, Tianzhen Chen +4 more · 2021 · Frontiers in genetics · Frontiers · added 2026-04-24
To explore the long-term influence of methamphetamine abuse on metabolomics character, with gas chromatography-mass spectrometry (GS-MS) technology, and the potential regulatory network using the bioi Show more
To explore the long-term influence of methamphetamine abuse on metabolomics character, with gas chromatography-mass spectrometry (GS-MS) technology, and the potential regulatory network using the bioinformatics method. Forty withdrawal methamphetamine abusers (WMA) were recruited from Shanghai Gaojing Forced Isolation Detoxification Institute. Forty healthy controls (HC) were recruited from society. GS-MS technology was used to detect metabolic products in serum. A bioinformatics method was used to build a regulatory network. Q-PCR was used to detect the candidate gene expressions, and ELISA was used to detect the regulatory enzyme expressions. Four pathways were significantly changed in the MA compared to the HC: (1) the arginine synthesis pathway, (2) alanine, aspartic acid and glutamate metabolic pathway, (3) cysteine and methionine metabolic pathway, and (4) the ascorbate and aldarate pathway (enrichment analysis Methamphetamine abuse influences the metabolic process in the long term, and Show less
📄 PDF DOI: 10.3389/fgene.2021.653443
DLG2
Wangyang Ji, Li E Hou, Xiaoya Yuan +7 more · 2021 · Scientific reports · Nature · added 2026-04-24
Anser cygnoides has a spherical crest on the beak roof, which is described as knob. However, the mechanisms affecting knob morphology are unclear. Here, we investigated the phenotypic characteristics Show more
Anser cygnoides has a spherical crest on the beak roof, which is described as knob. However, the mechanisms affecting knob morphology are unclear. Here, we investigated the phenotypic characteristics and molecular basis of knob-size differences in Yangzhou geese. Anatomically, the knob was identified as frontal hump in the frontal area of the skull, rather than hump of upper beak. Although the frontal hump length, and height varied greatly in geese with different knob phenotypes, little was changed in the width. Histologically, knob skin in large-size knobs geese have a greater length in the stratum corneum, stratum spinosum, and stratum reticular than that in small-size knobs geese. Moveover, the 415 differentially expressed genes were found between the large knobs and small ones through transcriptome profiling. In addition, GO enrichment and KEGG pathway analysis revealed 455 significant GO terms and 210 KEGG pathways were enriched, respectively. Among these, TGF-β signaling and thyroid hormone synthesis-signaling pathways were identified to determine knob-size phenotype. Furthermore, BMP5, DCN, TSHR and ADCY3 were recognized to involve in the growth and development of knob. Our data provide comprehensive molecular determinants of knob size phenotype, which can potentially promote the genetic improvement of goose knobs. Show less
📄 PDF DOI: 10.1038/s41598-021-91269-1
ADCY3
Ming-Jiang Liu, Hu Jin, Yu-Bing Chen +4 more · 2021 · International journal of clinical and experimental pathology · added 2026-04-24
Non-alcoholic steatohepatitis (NASH) is a common liver disease in the western world. The mechanisms behind NASH formation are poorly understood, but there may be multiple targets considering the disea Show more
Non-alcoholic steatohepatitis (NASH) is a common liver disease in the western world. The mechanisms behind NASH formation are poorly understood, but there may be multiple targets considering the disease's multifactorial nature. To explore the genes related to the pathogenesis of NASH, we downloaded clinical data and gene expression of NASH patients from the Gene Expression Omnibus database (GEO). We identified 281 genes with a common expression in two NASH-related datasets (GSE89632 and GSE83452), suggesting that they may be related to NASH. Further study showed that Show less
no PDF
ANGPTL4