👤 Shuang Chen

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧪 BiometalDB 🧬 Extraction
2981
Articles
1996
Name variants
Also published as: Wen-Chau Chen, Jingzhao Chen, Dexi Chen, Haifeng Chen, Chung-Jen Chen, Bo-Jun Chen, Gao-Feng Chen, Changyan Chen, Weiwei Chen, Fenghua Chen, Xiaojiang S Chen, Xiu-Juan Chen, Jung-Sheng Chen, Xiao-Ying Chen, Chong Chen, Junyang Chen, YiPing Chen, Xiaohan Chen, Li-Zhen Chen, Jiujiu Chen, Shin-Wen Chen, Guangping Chen, Dapeng Chen, Ximei Chen, Renwei Chen, Jianfei Chen, Yulu Chen, Yu-Chi Chen, Jia-De Chen, Rongfang Chen, She Chen, Zetian Chen, Tianran Chen, Emily Chen, Baoxiang Chen, Ya-Chun Chen, Dongxue Chen, Wei-xian Chen, Danmei Chen, Ceshi Chen, Junling Chen, Xia Chen, Daoyuan Chen, Yongbin Chen, Chi-Yu Chen, Dian Chen, Xiuxiu Chen, Bo-Fang Chen, Fangyuan Chen, Jin-An Chen, Xiaojuan Chen, Zhuohui Chen, Junqi Chen, Lina Chen, Fangfang Chen, Hanwen Chen, Yilei Chen, Po-Han Chen, Xiaoxiang Chen, Jimei Chen, Guochong Chen, Yanyun Chen, Yifei Chen, Cheng-Yu Chen, Zi-Jiang Chen, Jiayuan Chen, Miaoran Chen, Junshi Chen, Yu-Ying Chen, Pengxiang Chen, Hui-Ru Chen, Yupeng Chen, Ida Y-D Chen, Xiaofeng Chen, Qiqi Chen, Shengnan Chen, Mao-Yuan Chen, Lizhu Chen, Weichan Chen, Xiang-Bin Chen, Hanxi Chen, Sulian Chen, Zoe Chen, Minghong Chen, Chi Chen, Yananlan Chen, Yanzhu Chen, Shiyi Chen, Ze-Xu Chen, Zhiheng Chen, Jia-Mei Chen, Shuqin Chen, Yi-Hau Chen, Danni Chen, Donglong Chen, Xiaomeng Chen, Yidong Chen, Keyu Chen, Hao Chen, Junmin Chen, Wenlong Chen, Yufei Chen, Wanbiao Chen, Mo Chen, Youjia Chen, Xin-Jie Chen, Lanlan Chen, Huapu Chen, Shuaiyin Chen, Jing-Hsien Chen, Hengsheng Chen, Bing-Bing Chen, Fa-Xi Chen, Zhiqiang Chen, Ming-Huang Chen, Liangkai Chen, Li-Jhen Chen, Zhi-Hao Chen, Yinzhu Chen, Guanghong Chen, Gaozhi Chen, Jiakang Chen, Yongke Chen, Guangquan Chen, Li-Hsien Chen, Yiduo Chen, Zongnan Chen, Jing Chen, Meilan Chen, Jin-Shuen Chen, Huanxiong Chen, Yann-Jang Chen, Guozhong Chen, Yu-Bing Chen, Xiaobin Chen, Catherine Qing Chen, Youhu Chen, Hui Mei Chen, L F Chen, Haiyang Chen, Ruilin Chen, Peng Chen, Kailang Chen, Chao Chen, Suipeng Chen, Zemin Chen, Jianlin Chen, Shang-Chih Chen, Yen-Hsieh Chen, Jia-Lin Chen, Chaojin Chen, Minglang Chen, Xiatian Chen, Zeyu Chen, Kang Chen, Mei-Chi Chen, Jihai Chen, Pei Chen, Defang Chen, Zhao Chen, Tianrui Chen, Tingtao Chen, Caressa Chen, Jiwei Chen, Xuerong Chen, Yizhi Chen, XueShu Chen, Mingyue Chen, Huichao Chen, Chun-Chi Chen, Xiaomin Chen, Hetian Chen, Yuxing Chen, Jie-Hua Chen, Chuck T Chen, Yuanjia Chen, Hong Chen, Jianxiong Chen, S Chen, D M Chen, Jiao-Jiao Chen, Gongbo Chen, Xufeng Chen, Xiao-Jun Chen, Harn-Shen Chen, Qiu Jing Chen, Tai-Heng Chen, Pei-Lung Chen, Kaifu Chen, Huang-Pin Chen, Tse-Wei Chen, Yanrong Chen, Xianfeng Chen, Chung-Yung Chen, Yuelei Chen, Qili Chen, Guanren Chen, TsungYen Chen, Yu-Si Chen, Junsheng Chen, Min-Jie Chen, Xin-Ming Chen, Jiabing Chen, Sili Chen, Qinying Chen, Yue Chen, Lin Chen, Xiaoli Chen, Zhuo Chen, Aoshuang Chen, Junyu Chen, Chunji Chen, Yian Chen, Shanchun Chen, Shuen-Ei Chen, Canrong Chen, Shih-Jen Chen, Yaowu Chen, Han Chen, Yih-Chieh Chen, Wei-Cong Chen, Yanfen Chen, Tao Chen, Huangtao Chen, Jingyi Chen, Sheng Chen, Jing-Wen Chen, Gao Chen, Lei-Lei Chen, Kecai Chen, Yao-Shen Chen, Haiyu Chen, W Chen, Xiaona Chen, Cheng-Sheng Chen, X R Chen, Shuangfeng Chen, Jingyuan Chen, Xinyuan Chen, Huanhuan Chen, Mengling Chen, Liang-Kung Chen, Ming-Huei Chen, Hongshan Chen, Cuncun Chen, Qingchao Chen, Yanzi Chen, Lingli Chen, Shiqian Chen, Liangwan Chen, Lexia Chen, Wei-Ting Chen, Zhencong Chen, Tzy-Yen Chen, Mingcong Chen, Honglei Chen, Yuyan Chen, Huachen Chen, Yu Chen, Li-Juan Chen, Aozhou Chen, Xinlin Chen, Wai Chen, Dake Chen, Bo-Sheng Chen, Meilin Chen, Kequan Chen, Hong Yang Chen, Yan Chen, Bowei Chen, Silian Chen, Jian Chen, Yongmei Chen, Ling Chen, Jinbo Chen, Yingxi Chen, Ge Chen, Max Jl Chen, C Z Chen, Weitao Chen, Xiaole L Chen, Yonglu Chen, Shih-Pin Chen, Jiani Chen, Huiru Chen, San-Yuan Chen, Bing Chen, Xiao-ping Chen, Feiyue Chen, Shuchun Chen, Zhaolin Chen, Qianxue Chen, Xiaoyang Chen, Bowang Chen, Yinghui Chen, Ting-Ting Chen, Xiao-Yang Chen, Chi-Yuan Chen, Zhi-zhe Chen, Ting-Tao Chen, Xiaoyun Chen, Min-Hsuan Chen, Kuan-Ting Chen, Yongheng Chen, Wenhao Chen, Shengyu Chen, Kai Chen, Yueh-Peng Chen, Guangju Chen, Minghua Chen, Hong-Sheng Chen, Qingmei Chen, Song-Mei Chen, Limei Chen, Yuqi Chen, Yuyang Chen, Yang-Ching Chen, Yu-Gen Chen, Peizhan Chen, Rucheng Chen, Jin-Xia Chen, Szu-Chieh Chen, Xiaojun Chen, Jialing Chen, Heni Chen, Yi Feng Chen, Sen Chen, Alice Ye A Chen, Wen Chen, Han-Chun Chen, Dawei Chen, Fangli Chen, Ai-Qun Chen, Zhaojun Chen, Gong Chen, Yishan Chen, Zhijing Chen, Qiuxuan Chen, Miao-Der Chen, Fengwu Chen, Weijie Chen, Weixin Chen, Mei-Ling Chen, Hung-Po Chen, Rui-Pei Chen, Nian-Ping Chen, Tielin Chen, Canyu Chen, Xiaotao Chen, Nan Chen, C Chen, Juanjuan Chen, Xinan Chen, Jiaping Chen, Xiao-Lin Chen, Jianping Chen, Yayun Chen, Le Qi Chen, Jen-Sue Chen, Mechi Chen, Miao-Yu Chen, Zhou Chen, Szu-Han Chen, Zhen Bouman Chen, Baihua Chen, Qingao Chen, Shao-Ke Chen, Feng Chen, Jiawen Chen, Lianmin Chen, Sifeng Chen, Mengxia Chen, Xueli Chen, Can Chen, Yibo Chen, Zinan Chen, Lei-Chin Chen, Carol Chen, Yanlin Chen, Zihang Chen, Zaozao Chen, Haiqin Chen, Lu Hua Chen, Zhiyuan Chen, Meiyu Chen, Du-Qun Chen, Keying Chen, Naifei Chen, Peixian Chen, Jin-Ran Chen, Yijun Chen, Yulin Chen, Fumei Chen, Zhanfei Chen, Zhe-Yu Chen, Xin-Qi Chen, Valerie Chen, Ru Chen, Mengqing Chen, Runsheng Chen, Tong Chen, Tan-Zhou Chen, Suet Nee Chen, Cuicui Chen, Yifan Chen, Tian Chen, XiangFan Chen, Lingyi Chen, Hsiao-Yun Chen, Kenneth L Chen, Ni Chen, Huishan Chen, Fang-Yu Chen, Ken Chen, Yongshen Chen, Qiong Chen, Mingfeng Chen, Shoudeng Chen, Qiao Chen, Qian Chen, Yuebing Chen, Xuehua Chen, Chang-Lan Chen, Min-Hu Chen, Hongbin Chen, Jingming Chen, Qing Chen, Yu-Fan Chen, Hao-Zhu Chen, Yunjia Chen, Zhongjian Chen, Mingyi Chen, Qianping Chen, Huaxin Chen, Dong-Mei Chen, Peize Chen, Leijie Chen, Ming-Yu Chen, Jiaxuan Chen, Xiao-chun Chen, Wei-Min Chen, Ruisen Chen, Xuanwei Chen, Guiquan Chen, Minyan Chen, Feng-Ling Chen, Yili Chen, Alvin Chen, Xiaodong Chen, Bohong Chen, Chih-Ping Chen, Xuanjing Chen, Shuhui Chen, Ming-Hong Chen, Tzu-Yu Chen, Brian Chen, Bowen Chen, Kai-En Chen, Szu-Chia Chen, Guangchun Chen, Fang Chen, Chuyu Chen, Haotian Chen, Xiaoting Chen, Shaoliang Chen, Chun-Houh Chen, Shali Chen, Yu-Cheng Chen, Zhijun Chen, B Chen, Yuan Chen, Zhanglin Chen, Chaoran Chen, Xing-Long Chen, Zhinan Chen, Yu-Hui Chen, Yuquan Chen, Andrew Chen, Fengming Chen, Guangyong Chen, Jun Chen, Wenshuo Chen, Yi-Guang Chen, Jing-Yuan Chen, Kuangyang Chen, Mingyang Chen, Shaofei Chen, Weicong Chen, Gonghai Chen, Di-Long Chen, Limin Chen, Jishun Chen, Yunfei Chen, Caihong Chen, Tongsheng Chen, Ligang Chen, Wenqin Chen, Shiyu Chen, Xiaoyong Chen, Christina Y Chen, Yushan Chen, Ginny I Chen, Guo-Jun Chen, Xianzhen Chen, Wanling Chen, Kuan-Jen Chen, Maorong Chen, Kaijian Chen, Erqu Chen, Shen Chen, Quan Chen, Zian Chen, Yi-Lin Chen, Juei-Suei Chen, Yi-Ting Chen, Huaiyong Chen, Minjian Chen, Qianzhi Chen, Jiahao Chen, Xikun Chen, Juan-Juan Chen, Xiaobo Chen, Tianzhen Chen, Ziming Chen, Qianbo Chen, Jindong Chen, Jiu-Chiuan Chen, Yinwei Chen, Carl Pc Chen, Li-Hsin Chen, Jenny Chen, Ruoyan Chen, Yanqiu Chen, Yen-Fu Chen, Haiyan Chen, Zhebin Chen, Si Chen, Jian-Qiao Chen, Yang-Yang Chen, Ningning Chen, Zhifeng Chen, Zhenyi Chen, Hangang Chen, Zihe Chen, Mengdi Chen, Zhichuan Chen, Xu Chen, Huixi Chen, Weitian Chen, Bao-Sheng Chen, Tien-Hsing Chen, Junchen Chen, Yan-yan Chen, Xiangning Chen, Sijia Chen, Xinyan Chen, Kuan-Yu Chen, Qunxiang Chen, Guangliang Chen, Bing-Huei Chen, Fei Xavier Chen, Zhangcheng Chen, Qianming Chen, Xianze Chen, Yanhua Chen, Qinghao Chen, Yanting Chen, Sijuan Chen, Chen-Mei Chen, Qiankun Chen, Jianan Chen, Rong Chen, Xiankai Chen, Kaina Chen, Gui-Hai Chen, Y-D Ida Chen, Quanjiao Chen, Lichang Chen, Xinyi Chen, Yong-Jun Chen, Zhaoli Chen, Chunnuan Chen, Jui-Chang Chen, Zhiang Chen, Weirui Chen, Zhenguo Chen, Jennifer F Chen, Zhiguo Chen, Kunmei Chen, Huan-Xin Chen, Mengyan Chen, Dongrong Chen, Siyue Chen, Xianyue Chen, Chien-Lun Chen, YiChung Chen, Guang Chen, Quanwei Chen, Zongming E Chen, Ting-Huan Chen, Michael C Chen, Jinli Chen, Beth L Chen, Yuh-Lien Chen, Peihong Chen, Qiaoling Chen, Jiale Chen, Shufeng Chen, Xiaowan Chen, Xian-Kai Chen, Ling-Yan Chen, Yen-Ling Chen, Guiying Chen, Guangyi Chen, Yuling Chen, Xiangqiu Chen, Haiquan Chen, Cuie Chen, Gui-Lai Chen, R Chen, Heng-Yu Chen, Yongxun Chen, Fuxiang Chen, Mingmei Chen, Hua-Pu Chen, Yulong Chen, Zhitao Chen, Guohua Chen, Cheng-Yi Chen, Hongxu Chen, Yuanhao Chen, Qichen Chen, Hualin Chen, Guo-Rong Chen, Rongsheng Chen, Xuesong Chen, Wei-Fei Chen, Bao-Bao Chen, Anqi Chen, Yi-Han Chen, Ying-Jung Chen, Jinhuang Chen, Guochao Chen, Lei Chen, S N Chen, Songfeng Chen, Chenyang Chen, Xing Chen, Letian Chen, Meng Xuan Chen, Xiang-Mei Chen, Xiaoyan Chen, Yi-Heng Chen, D F Chen, Bang Chen, Jiaxu Chen, Wei Chen, Sihui Chen, Shu-Hua Chen, I-M Chen, Xuxin Chen, Zhangxin Chen, Jin Chen, Yin-Huai Chen, Wuyan Chen, Bingqing Chen, Bao-Fu Chen, Zhen-Hua Chen, Dan Chen, Zhe-Sheng Chen, Ranyun Chen, Wanyin Chen, Xueyan Chen, Xiaoyu Chen, Tai-Tzung Chen, Xiaofang Chen, Yongxing Chen, Yanghui Chen, Hekai Chen, Yuanwei Chen, Liang Chen, Hui-Jye Chen, Chengchun Chen, Han-Bin Chen, Shuaijie Chen, Yibing Chen, Kehui Chen, Shuhai Chen, Xueling Chen, Ying-Jie Chen, Qingxing Chen, Fang-Zhi Chen, Mei-Hua Chen, Yutong Chen, Lixian Chen, Alex Chen, Qiuhong Chen, Qiuxia Chen, Liping Chen, Hou-Tsung Chen, Zhanghua Chen, Chun-Fa Chen, Chian-Feng Chen, Benjamin P C Chen, Yewei Chen, Mu-Hong Chen, Jianshan Chen, Xiaguang Chen, Meiling Chen, Heng Chen, Ying-Hsiang Chen, Longyun Chen, Dengpeng Chen, Jichong Chen, Shixuan Chen, Liaobin Chen, Everett H Chen, ZhuoYu Chen, Qihui Chen, Zhiyong Chen, Nuan Chen, Hongmei Chen, Guiqian Chen, Yan Q Chen, Fengling Chen, Hung-Chang Chen, Zhenghong Chen, Chengsheng Chen, Hegang Chen, Huei-Yan Chen, Liutao Chen, Meng-Lin Chen, Xi Chen, Qing-Juan Chen, Linna Chen, Xiaojing Chen, Lang Chen, Gengsheng Chen, Fengrong Chen, Weilun Chen, Shi Chen, Wan-Yi Chen, On Chen, Yufeng Chen, Benjamin Chen, Hui-Zhao Chen, Bo-Rui Chen, Kangyong Chen, Ruixiang Chen, Weiyong Chen, Ning-Hung Chen, Meng-Ping Chen, Huimei Chen, Ying Chen, Kang-Hua Chen, Pei-zhan Chen, Liujun Chen, Hanqing Chen, Chengchuan Chen, Guojun Chen, Yongfa Chen, Li Chen, Mingling Chen, Jacinda Chen, Jinlun Chen, Kun Chen, Yi Chen, Chiung Mei Chen, Shaotao Chen, Tianhong Chen, Chanjuan Chen, Yuhao Chen, Huizhi Chen, Chung-Hsing Chen, Qiuchi Chen, Haoting Chen, Luzhu Chen, Huanhua Chen, Long Chen, Jiang-hua Chen, Kai-Yang Chen, Jing-Zhou Chen, Yong-Syuan Chen, Lifang Chen, Ruonan Chen, Meimei Chen, Qingchuan Chen, Liugui Chen, Shaokun Chen, Yi-Yung Chen, Jintian Chen, Xuhui Chen, Dongyan Chen, Huei-Rong Chen, Xianmei Chen, Jinyan Chen, Yuxi Chen, Qingqing Chen, Weibo Chen, Qiwei Chen, Mingxia Chen, Hongmin Chen, Jiahui Chen, Yen-Jen Chen, Zihan Chen, Guozhou Chen, Fei Chen, Zhiting Chen, Denghui Chen, Gary Chen, Hongli Chen, Jack Chen, Zhigang Chen, Lie Chen, Siyuan Chen, Haojie Chen, Qing-Wei Chen, Maochong Chen, Mei-Jie Chen, Haining Chen, Xing-Zhen Chen, Weiqing Chen, Huanchun Chen, C-Y Chen, Tzu-An Chen, Jen-Hau Chen, Xiaojie Chen, Dongquan Chen, Gao B Chen, Daijie Chen, Zixi Chen, Lingfeng Chen, Jiayi Chen, Zan Chen, Shuming Chen, Mei-Hsiu Chen, Xueqin Chen, Huan Chen, Xiaoqing Chen, Hui-Xiong Chen, Ruoying Chen, Deying Chen, Huixian Chen, Zhezhe Chen, Lu Chen, Xiaolong Chen, Si-Yue Chen, Xinwei Chen, Wentao Chen, Yucheng Chen, Jiajing Chen, Allen Menglin Chen, Chixiang Chen, Shiqun Chen, Wenwu Chen, Chin-Chuan Chen, Ningbo Chen, Hsin-Hung Chen, Shenglan Chen, Jia-Feng Chen, Changya Chen, ZhaoHui Chen, Guo Chen, Juhai Chen, Xiao-Quan Chen, Cuimin Chen, Yongshuo Chen, Sai Chen, Fengyang Chen, Siteng Chen, Hualan Chen, Lian Chen, Yuan-Hua Chen, Minjie Chen, Shiyan Chen, Z Chen, Zhengzhi Chen, Jonathan Chen, H Chen, You-Yue Chen, Shu-Gang Chen, Hsuan-Yu Chen, Hongyue Chen, Weiyi Chen, Jiaqi Chen, Chengde Chen, Shufang Chen, Ze-Hui Chen, Xiuping Chen, Zhuojia Chen, Zhouji Chen, Lidian Chen, Yilan Chen, Kuan-Ling Chen, Alon Chen, Zi-Yue Chen, Hongmou Chen, Fang-Zhou Chen, Jianzhou Chen, Wenbiao Chen, Yujie Chen, Zhijian Chen, Zhouqing Chen, Xiuhui Chen, Qingguang Chen, Hanbei Chen, Qianyu Chen, Mengping Chen, Yongqi Chen, Sheng-Yi Chen, Siqi Chen, Yelin Chen, Shirui Chen, Yuan-Tsong Chen, Dongyin Chen, Lingxue Chen, Long-Jiang Chen, Yunshun Chen, Yahong Chen, Yaosheng Chen, Zhonghua Chen, Jingyao Chen, Pei-Yin Chen, Fusheng Chen, Xiaokai Chen, Shuting Chen, Miao-Hsueh Chen, Y-D I Chen, Zijie Chen, Haozhu Chen, Haodong Chen, Xiong Chen, Wenxi Chen, Feng-Jung Chen, Shangwu Chen, Zhiping Chen, Zhang-Yuan Chen, Wentong Chen, Ou Chen, Ruiming Chen, Xiyu Chen, Shuqiu Chen, Xiaoling Chen, Ruimin Chen, Hsiao-Wang Chen, Dongli Chen, Haibo Chen, Yiyun Chen, Luming Chen, Wenting Chen, Chongyang Chen, Qingqiu Chen, Wen-Pin Chen, Yuhui Chen, Lingxia Chen, Jun-Long Chen, Xingyu Chen, Haotai Chen, Bang-dang Chen, Qiuwen Chen, Rui Chen, K C Chen, Zhixuan Chen, Gaoyu Chen, Yitong Chen, Tzu-Ju Chen, Jingqing Chen, Huiqun Chen, Runsen Chen, Michelle Chen, Hanyong Chen, Xiaolin Chen, Ke Chen, Yangchao Chen, Y D I Chen, Jinghua Chen, Jia Wei Chen, Man-Hua Chen, H T Chen, Zheyi Chen, Lihong Chen, Guangyao Chen, Rujun Chen, Ming-Fong Chen, Haiyun Chen, Dexiong Chen, Huiqin Chen, Ching Kit Chen, En-Qiang Chen, Wanjia Chen, Xiangliu Chen, Meiting Chen, Szu-Chi Chen, Yii-der Ida Chen, Jian-Hua Chen, Yanjie Chen, Yingying Chen, Paul Chih-Hsueh Chen, Si-Ru Chen, Mingxing Chen, Rui-Zhen Chen, Changjie Chen, Qu Chen, Yintong Chen, Jingde Chen, Mao Chen, Xinghai Chen, Mei-Chih Chen, Xueqing Chen, Chun-An Chen, Cheng Chen, Ruijing Chen, Huayu Chen, Yunqin Chen, Yan-Gui Chen, Ruibing Chen, Size Chen, Qi-An Chen, Yuan-Zhen Chen, J Chen, Heye Chen, T Chen, Junpeng Chen, Tan-Huan Chen, Shuaijun Chen, Hao Yu Chen, Fahui Chen, Lan Chen, Dong-Yi Chen, Xianqiang Chen, Shi-Sheng Chen, Qiao-Yi Chen, Pei-Chen Chen, Xueying Chen, Yi-Wen Chen, Guohong Chen, Zhiwei Chen, Zuolong Chen, Erfei Chen, Yuqing Chen, Zhenyue Chen, Qiongyun Chen, Jianghua Chen, Yingji Chen, Xiuli Chen, Xiaowei Chen, Hengyu Chen, Sheng-Xi Chen, Haiyi Chen, Shao-Peng Chen, Yi-Ru Chen, Zhaoran Chen, Xiuyan Chen, Jinsong Chen, Sunny Chen, Xiaolan Chen, S-D Chen, Ruofan Chen, Qiujing Chen, Yun Chen, Wei-Cheng Chen, Chun-Wei Chen, Liechun Chen, Lulu Chen, Hsiu-Wen Chen, Yanping Chen, Jiayao Chen, Xuejiao Chen, Guan-Wei Chen, Yusi Chen, Yijiang Chen, Chi-Hua Chen, Qixian Chen, Ziqing Chen, Peiyou Chen, Chunhai Chen, Zheren Chen, Qiuyun Chen, Xiaorong Chen, Chaoqun Chen, Dan-Dan Chen, Xuechun Chen, Yafang Chen, Mystie X Chen, Jina Chen, Wei-Kai Chen, Yule Chen, Bo Chen, Kaili Chen, Junqin Chen, Jia Min Chen, Chen Chen, Guoliang Chen, Xiaonan Chen, Guangjie Chen, Xiao Chen, Jeanne Chen, Danyang Chen, Minjiang Chen, Jiyuan Chen, Zheng-Zhen Chen, Shou-Tung Chen, Ouyang Chen, Xiu Chen, H Q Chen, Peiyu Chen, Yuh-Min Chen, Youmeng Chen, Shuoni Chen, Peiqin Chen, Xinji Chen, Chih-Ta Chen, Shang-Hung Chen, Robert Chen, Suet N Chen, Yun-Tzu Chen, Suming Chen, Ye Chen, Yao Chen, Yi-Fei Chen, Ruixue Chen, Tianhang Chen, Suning Chen, Jingnan Chen, Xiaohong Chen, Kun-Chieh Chen, Tuantuan Chen, Mei Chen, He-Ping Chen, Zhi Bin Chen, Yuewu Chen, Mengying Chen, Po-See Chen, Xue Chen, Jian-Jun Chen, Xiyao Chen, Jeremy J W Chen, Jiemei Chen, Daiwen Chen, Christina Yingxian Chen, Qinian Chen, Chih-Wei Chen, Wensheng Chen, Yingcong Chen, Zhishi Chen, Duo Chen, Jiansu Chen, Keping Chen, Min Chen, Yi-Hui Chen, Yun-Ju Chen, Gaoyang Chen, Renjin Chen, Kui Chen, Shuai-Ming Chen, Hui-Fen Chen, Zi-Yun Chen, Shao-Yu Chen, Meiyang Chen, Jiahua Chen, Zongyou Chen, Yen-Rong Chen, Huaping Chen, Yu-Xin Chen, Bohe Chen, Kehua Chen, Zilin Chen, Zhang-Liang Chen, Ziqi Chen, Yinglian Chen, Hui-Wen Chen, Peipei Chen, Baolin Chen, Zugen Chen, Kangzhen Chen, Yanhan Chen, Sung-Fang Chen, Zheping Chen, Zixuan Chen, Jiajia Chen, Yuanjian Chen, Lili Chen, Xiangli Chen, Ban Chen, Yuewen Chen, X Chen, Yan-Qiong Chen, Chider Chen, Yung-Hsiang Chen, Hanlin Chen, Xiangjun Chen, Haibing Chen, Le Chen, Xuan Chen, Xue-Ying Chen, Zexiao Chen, Chen-Yu Chen, Zhe-Ling Chen, Fan Chen, Hsin-Yi Chen, Feilong Chen, Zilong Chen, Yi-Jen Chen, Zhiyun Chen, Ning Chen, Wenxu Chen, Chuanbing Chen, Yaxi Chen, Yi-Hong Chen, Eleanor Y Chen, Yuexin Chen, Kexin Chen, Shoujun Chen, Yen-Ju Chen, Yu-Chuan Chen, Yen-Teen Chen, Bao-Ying Chen, Xiaopeng Chen, Danli Chen, Katharine Y Chen, Jingli Chen, Qianyi Chen, Zihua Chen, Ya-xi Chen, Xuanxu Chen, Chung-Hung Chen, Yajie Chen, Cindi Chen, Hua Chen, Shuliang Chen, Elizabeth H Chen, Gen-Der Chen, Bingyu Chen, Keyang Chen, Siyu S Chen, Xinpu Chen, Yau-Hung Chen, Hsueh-Fen Chen, Han-Hsiang Chen, Wei Ning Chen, Guopu Chen, Zhujun Chen, Yurong Chen, Yuxian Chen, Wanjun Chen, Qiu-Jing Chen, Qifang Chen, Yuhan Chen, Jingshen Chen, Zhongliang Chen, Ching-Hsuan Chen, Zhaoyao Chen, Yongning Chen, Marcus Y Chen, Ping Chen, Junfei Chen, Yung-Wu Chen, Xueting Chen, Yingchun Chen, Wan-Yan Chen, Yuxin Chen, Yisheng Chen, Chun-Yuan Chen, Yulian Chen, Yan-Jun Chen, Guoxun Chen, Ding Chen, Yu-Fen Chen, Jason A Chen, Shuyi Chen, Cuilan Chen, Ruijuan Chen, Kevin Chen, Xuanmao Chen, Shen-Ming Chen, Ya-Nan Chen, Sean Chen, Zhaowei Chen, Xixi Chen, Yu-Chia Chen, Xuemin Chen, Binlong Chen, Weina Chen, Xuemei Chen, Di Chen, P P Chen, Yubin Chen, Chunhua Chen, Li-Chieh Chen, Ping-Chung Chen, Zhihao Chen, Xinyang Chen, Chan Chen, Yan Jie Chen, Shi-Qing Chen, Ivy Xiaoying Chen, Ying-Cheng Chen, Jia-Shun Chen, Shao-Wei Chen, Aiping Chen, Dexiang Chen, Qianfen Chen, Hongyu Chen, Wei-Kung Chen, Danlei Chen, Hongen Chen, Shipeng Chen, Jake Y Chen, Dongsheng Chen, Chien-Ting Chen, Shouzhen Chen, Hehe Chen, Yu-Tung Chen, Yilin Chen, Joy J Chen, Zhong Chen, Zhenfeng Chen, Zhongzhu Chen, Feiyang Chen, Xingxing Chen, Keyan Chen, Huimin Chen, Guanyu Chen, D. Chen, Dianke Chen, Zhigeng Chen, Sien-Tsong Chen, Yii-Der Chen, Chi-Yun Chen, Beidong Chen, Wu-Xian Chen, Zhihang Chen, Yuanqi Chen, Jianhua Chen, Xian Chen, Xiangding Chen, Jingteng Chen, Shuaiyu Chen, Xue-Mei Chen, Yu-Han Chen, Hongqiao Chen, Weili Chen, Yunzhu Chen, Guo-qing Chen, Miao Chen, Zhi Chen, Junhui Chen, Jing-Xian Chen, Zhiquan Chen, Shuhuang Chen, Shaokang Chen, Irwin Chen, Xiang Chen, Chuo Chen, Siting Chen, Keyuan Chen, Xia-Fei Chen, Zhihai Chen, Yuanyu Chen, Po-Sheng Chen, Qingjiang Chen, Yi-Bing Chen, Rongrong Chen, Katherine C Chen, Shaoxing Chen, Lifen Chen, Luyi Chen, Sisi Chen, Ning-Bo Chen, Yihong Chen, Guanjie Chen, Li-Hua Chen, Xiao-Hui Chen, Ting Chen, Chun-Han Chen, Xuzhuo Chen, Junming Chen, Zheng Chen, Wen-Jie Chen, Bingdi Chen, Jiang Ye Chen, Yanbin Chen, Duoting Chen, Shunyou Chen, Shaohua Chen, Jien-Jiun Chen, Jiaohua Chen, Shaoze Chen, Yifang Chen, Chiqi Chen, Yen-Hao Chen, Rui-Fang Chen, Hung-Sheng Chen, Kuey Chu Chen, Y S Chen, Xijun Chen, Chaoyue Chen, Heng-Sheng Chen, Lianfeng Chen, Yen-Ching Chen, Yuhong Chen, Yixin Chen, Yuanli Chen, Cancan Chen, Yanming Chen, Yajun Chen, Chaoping Chen, F-K Chen, Menglan Chen, Zi-Yang Chen, Yongfang Chen, Hsin-Hong Chen, Hongyan Chen, Chao-Wei Chen, Jijun Chen, Xiaochun Chen, Yazhuo Chen, Zhixin Chen, YongPing Chen, Jui-Yu Chen, Mian-Mian Chen, Liqiang Chen, Y P Chen, D-F Chen, Jinhao Chen, Yanyan Chen, Chang-Zheng Chen, Shao-long Chen, Guoshun Chen, Lo-Yun Chen, Yen-Lin Chen, Bingqian Chen, Dafang Chen, Yi-Chung Chen, Liming Chen, Qiuli Chen, Shuying Chen, Chih-Mei Chen, Renyu Chen, Wei-Hao Chen, Lihua Chen, Hang Chen, Hai-Ning Chen, Hu Chen, Yu-Fu Chen, Yalan Chen, Wan-Tzu Chen, Benjamin Jieming Chen, Yingting Chen, Jiacai Chen, Ning-Yuan Chen, Shuo-Bin Chen, Yu-Ling Chen, Jian-Kang Chen, Hengsan Chen, Yu-Ting Chen, Y Chen, Qingjie Chen, Jiong Chen, Chaoyi Chen, Yunlin Chen, Gang Chen, Hui-Chun Chen, Li-Tzong Chen, Zhangliang Chen, Qiangpu Chen, Xianbo Chen, Jinxuan Chen, Hebing Chen, Ran Chen, Zhehui Chen, Carol X-Q Chen, Yuping Chen, Xiangyu Chen, Xinyu Chen, Qianyun Chen, Junyi Chen, B-S Chen, Zhesheng Chen, Man Chen, Dali Chen, Danyu Chen, Huijiao Chen, Naisong Chen, Qitong Chen, Chueh-Tan Chen, Kai-Ming Chen, Jiarou Chen, Huang Chen, Chunjie Chen, Weiping Chen, Po-Min Chen, Guang-Chao Chen, Danxia Chen, Youran Chen, Chuanzhi Chen, Peng-Cheng Chen, Wen-Tsung Chen, Linxi Chen, Si-guo Chen, Zike Chen, Zhiyu Chen, Wanting Chen, Jiangxia Chen, Wenhua Chen, Roufen Chen, Shi-You Chen, Fang-Pei Chen, Chu Chen, Feifeng Chen, Chunlin Chen, Yunwei Chen, Wenbing Chen, Xuejun Chen, Meizhen Chen, Li Jia Chen, Tianhua Chen, Xiangmei Chen, Kewei Chen, Yuh-Ling Chen, Dejuan Chen, Jiyan Chen, Xinzhuo Chen, Yue-Lai Chen, Hsiao-Jou Cortina Chen, Weiqin Chen, Huey-Miin Chen, Elizabeth Suchi Chen, Kai-Ting Chen, Lizhen Chen, Xiaowen Chen, Chien-Yu Chen, Lingjun Chen, Gonglie Chen, Jiao Chen, Zhuo-Yuan Chen, Wei-Peng Chen, Xiangna Chen, Jiade Chen, Lanmei Chen, Siyu Chen, Kunpeng Chen, Hung-Chi Chen, Jia Chen, Shuwen Chen, Siqin Chen, Zhenlei Chen, Wen-Yi Chen, Si-Yuan Chen, Yidan Chen, Tianfeng Chen, Fu Chen, Leqi Chen, Jiamiao Chen, Shasha Chen, Qingyi Chen, Ben-Kuen Chen, Haitao Chen, Qi Chen, Yihao Chen, Yunfeng Chen, Elizabeth S Chen, Yiming Chen, Youwei Chen, Lichun Chen, Yanfei Chen, Hongxing Chen, Muh-Shy Chen, Yingyu Chen, Weihong Chen, Ming Chen, Kelin Chen, Duan-Yu Chen, Shi-Yi Chen, Shih-Yu Chen, Yanling Chen, Shuanghui Chen, Ya Chen, Yusheng Chen, Yuting Chen, Shiming Chen, Xinqiao Chen, Hongbo Chen, Mien-Cheng Chen, Jiacheng Chen, Herbert Chen, Ji-ling Chen, Sun Chen, Chen-Sheng Chen, Na Chen, Chih-Yi Chen, Wenfang Chen, Yii-Der I Chen, Qinghua Chen, Shuai Chen, Hsi-Hsien Chen, F Chen, Guo-Chong Chen, Zhe Chen, Beijian Chen, Roger Chen, You-Ming Chen, Hongzhi Chen, Zhen-Yu Chen, Xianxiong Chen, Chang Chen, Chujie Chen, Chuannan Chen, Kan Chen, Lu-Biao Chen, Yupei Chen, Qiu-Sheng Chen, Shangduo Chen, Yuan-Yuan Chen, Yundai Chen, Binzhen Chen, Cai-Long Chen, Yen-Chen Chen, Xue-Xin Chen, Yanru Chen, Chunxiu Chen, Yifa Chen, Xingdong Chen, Ruey-Hwa Chen, Shangzhong Chen, Ching-Wen Chen, Danna Chen, Jingjing Chen, Yafei Chen, Dandan Chen, Pei-Yi Chen, Shan Chen, Guanghao Chen, Longqing Chen, Yen-Cheng Chen, Zhanjuan Chen, Jinguo Chen, Zhongxiu Chen, Rui-Min Chen, Shunde Chen, Xun Chen, Jianmin Chen, Linyi Chen, Ying-Ying Chen, Chien-Hsiun Chen, Li-Nan Chen, Yu-Ming Chen, Qianqian Chen, Xue-Yan Chen, Shengdi Chen, Huali Chen, Xinyue Chen, Ching-Yi Chen, Honghai Chen, Baosheng Chen, Pingguo Chen, Yike Chen, Yuxiang Chen, Qing-Hui Chen, Yuanwen Chen, Yongming Chen, Zongzheng Chen, Ruiying Chen, Huafei Chen, Tingen Chen, Zhouliang Chen, Shih-Yin Chen, Shanyuan Chen, Yiyin Chen, Feiyu Chen, Zitao Chen, Constance Chen, Zhoulong Chen, Haide Chen, Jiang Chen, Ray-Jade Chen, Shiuhwei Chen, Chih-Chieh Chen, Chaochao Chen, Lijuan Chen, Qianling Chen, Jian-Min Chen, Xihui Chen, Yuli Chen, Wu-Jun Chen, Diyun Chen, Alice P Chen, Jingxuan Chen, Chiung-Mei Chen, Shibo Chen, M L Chen, Lena W Chen, Xiujuan Chen, Christopher S Chen, Yeh Chen, Xingyong Chen, Feixue Chen, Boyu Chen, Weixian Chen, Tingting Chen, Bosong Chen, Junjie Chen, Han-Min Chen, Szu-Yun Chen, Qingliang Chen, Huatao Chen, Bin Chen, L B Chen, Xuanyi Chen, Chun Chen, Dong Chen, Yinjuan Chen, Jiejian Chen, Lu-Zhu Chen, Alex F Chen, Pei-Chun Chen, Chien-Jen Chen, Y M Chen, Xiao-Chen Chen, Tania Chen, Yang Chen, Yangxin Chen, Mark I-Cheng Chen, Haiming Chen, Shuo Chen, Yong Chen, Hsiao-Tan Chen, Erzhen Chen, Jiaye Chen, Fangyan Chen, Guanzheng Chen, Haoyun Chen, Jiongyu Chen, Baofeng Chen, Yuqin Chen, Juan Chen, Haobo Chen, Shuhong Chen, Fu-Shou Chen, Wei-Yu Chen, Haw-Wen Chen, Feifan Chen, Deqian Chen, Linlin Chen, Xiaoshan Chen, Hui Chen, Wenwen Chen, Yanli Chen, Yuexuan Chen, Xiaoyin Chen, Yen-Chang Chen, Tiantian Chen, Ruiai Chen, Alice Y Chen, Jinglin Chen, Zifan Chen, Wantao Chen, Shanshan Chen, Jianjun Chen, Xiaoyuan Chen, Xuefei Chen, Runfeng Chen, Weisan Chen, Guangnan Chen, Junpan Chen, An Chen, Lankai Chen, Yiding Chen, Tianpeng Chen, Ya-Ting Chen, Lijin Chen, Ching-Yu Chen, Y Eugene Chen, Guanglong Chen, Rongyuan Chen, Yali Chen, Yanan Chen, Liyun Chen, Shuai-Bing Chen, Zhixue Chen, Xiaolu Chen, Xiao-he Chen, Hongxiang Chen, Bing-Feng Chen, Gary K Chen, Xiaohui Chen, Jin-Wu Chen, Qiuxiang Chen, Huaqiu Chen, X Steven Chen, Xiaoqian Chen, Chao-Jung Chen, Zhengjun Chen, Yong-Ping Chen, Zhelin Chen, Xuancai Chen, Yi-Hsuan Chen, Daiyu Chen, Gui Mei Chen, Hongqi Chen, Zhizhong Chen, Mengting Chen, Guofang Chen, Jian-Guo Chen, Hou-Zao Chen, Yuyao Chen, Lixia Chen, Yu-Yang Chen, Zhengling Chen, Qinfen Chen, Jiajun Chen, Xue-Qing Chen, Shenghui Chen, Yii-Derr Chen, Linbo Chen, Yanjing Chen, S Pl Chen, Chi-Long Chen, Jiawei Chen, Rong-Hua Chen, Shu-Fen Chen, Yu-San Chen, Ying-Lan Chen, Xiaofen Chen, Weican Chen, Xin Chen, Yumei Chen, Ruohong Chen, You-Xin Chen, Tse-Ching Chen, Xiancheng Chen, Yu-Pei Chen, Weihao Chen, Baojiu Chen, Haimin Chen, Zhihong Chen, Jion Chen, Yi-Chun Chen, Ping-Kun Chen, Wan Jun Chen, Willian Tzu-Liang Chen, Qingshi Chen, Ren-Hui Chen, Weihua Chen, Hanjing Chen, Guihao Chen, Xiao-Qing Chen, Po-Yu Chen, Liangsheng Chen, Fred K Chen, Haiying Chen, Tzu-Chieh Chen, Wei J Chen, Zhen Chen, Shu Chen, Jie Chen, Chung-Hao Chen, Zi-Qing Chen, Yu-Xia Chen, Weijia Chen, Ming-Han Chen, Yaodong Chen, Yong-Zhong Chen, Jinquan Chen, Haijiao Chen, Tom Wei-Wu Chen, Jingzhou Chen, Ya-Peng Chen, Shiwei Chen, Xiqun Chen, Yingjie Chen, Wenjun Chen, Linjie Chen, Hung-Chun Chen, Xiaoping Chen, Haoran Chen, Qiang Chen, Sy-Jou Chen, Y U Chen, Weineng Chen, Li-hong Chen, Cheng-Fong Chen, Yajing Chen, Song Chen, Qiaoli Chen, Yiru Chen, Guang-Yu Chen, Zhi-bin Chen, Deyu Chen, C Y Chen, Junhong Chen, Yonghui Chen, Chaoli Chen, Syue-Ting Chen, Sufang Chen, I-Chun Chen, Shangsi Chen, Xiao-Wei Chen, Qinsheng Chen, Zhao-Xia Chen, Yun-Yu Chen, Chi-Chien Chen, Wenxing Chen, Meng Chen, Zixin Chen, Jianhui Chen, Yuanyuan Chen, Jiamin Chen, Wei-Wei Chen, Xingyi Chen, Yen-Ni Chen, Danxiang Chen, Po-Ju Chen, Mei-Ru Chen, Ziying Chen, E S Chen, Tailai Chen, Qingyang Chen, Miaomiao Chen, Shuntai Chen, Wei-Lun Chen, Xuanli Chen, Zhengwei Chen, Fengju Chen, Chengwei Chen, Xujia Chen, Faye H Chen, Xiaoxiao Chen, Shengpan Chen, Shin-Yu Chen, Shiyao Chen, Yuan-Shen Chen, Shengzhi Chen, Shaohong Chen, Ching-Jung Chen, Zihao Chen, Kaiquan Chen, Duo-Xue Chen, Xiaochang Chen, Siping Chen, Rongfeng Chen, Jiali Chen, Hsin-Han Chen, Xiaohua Chen, Delong Chen, Wenjie Chen, Huijia Chen, Yunn-Yi Chen, Siyi Chen, Zhengming Chen, Chu-Huang Chen, Zhuchu Chen, Yuanbin Chen, Jinyong Chen, Yunzhong Chen, Pan Chen, Bihong T Chen, Yunyun Chen, Shujuan Chen, M Chen, Mulan Chen, Jiaren Chen, Zechuan Chen, Jian-Qing Chen, Wei-Hui Chen, Lifeng Chen, Geng Chen, Yan-Ming Chen, Zhijian J Chen, Honghui Chen, Wenfan Chen, Zhongbo Chen, Rouxi Chen, Ye-Guang Chen, Zhimin Chen, Tzu-Ting Chen, Xiaolei Chen, Ziyuan Chen, Shilan Chen, Ruiqi Chen, Xiameng Chen, Huijie Chen, Jiankui Chen, Yuhang Chen, Jianzhong Chen, Wen-Qi Chen, Fa Chen, Shu-Jen Chen, Li-Mien Chen, Xing-Lin Chen, Xuxiang Chen, Erbao Chen, Jiaqing Chen, Hsiang-Wen Chen, Jiaxin Chen
articles
Xiaolu Chen, Yajiao Huang, Ban Chen +3 more · 2024 · European journal of medicinal chemistry · Elsevier · added 2026-04-24
Recently, FGFR4 has become a hot target for the treatment of cancer owing to its important role in cellular physiological processes. FGFR4 has been validated to be closely related to the occurrence of Show more
Recently, FGFR4 has become a hot target for the treatment of cancer owing to its important role in cellular physiological processes. FGFR4 has been validated to be closely related to the occurrence of cancers, such as hepatocellular carcinoma, rhabdomyosarcoma, breast cancer and colorectal cancer. Hence, the development of FGFR4 small-molecule inhibitors is essential to further understanding the functions of FGFR4 in cancer and the treatment of FGFR4-dependent diseases. Given the particular structures of FGFR1-4, the development of FGFR4 selective inhibitors presents significant challenges. The non-conserved Cys552 in the hinge region of the FGFR4 complex becomes the key to the selectivity of FGFR4 and FGFR1/2/3 inhibitors. In this review, we systematically introduce the close relationship between FGFR4 and cancer, and conduct an in-depth analysis of the developing methodology, binding mechanism, kinase selectivity, pharmacokinetic characteristics of FGFR4 selectivity inhibitors, and their application in clinical research. Show less
no PDF DOI: 10.1016/j.ejmech.2023.115947
FGFR1
Yalan Pu, Jie Yang, Qiuling Pan +6 more · 2024 · The Journal of biological chemistry · Elsevier · added 2026-04-24
Microsomal glutathione transferase 3 (MGST3) regulates eicosanoid and glutathione metabolism. These processes are associated with oxidative stress and apoptosis, suggesting that MGST3 might play a rol Show more
Microsomal glutathione transferase 3 (MGST3) regulates eicosanoid and glutathione metabolism. These processes are associated with oxidative stress and apoptosis, suggesting that MGST3 might play a role in the pathophysiology of Alzheimer's disease. Here, we report that knockdown (KD) of MGST3 in cell lines reduced the protein level of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) and the resulting amyloidogenesis. Interestingly, MGST3 KD did not alter intracellular reactive oxygen species level but selectively reduced the expression of apoptosis indicators which could be associated with the receptor of cysteinyl leukotrienes, the downstream metabolites of MGST3 in arachidonic acid pathway. We then showed that the effect of MGST3 on BACE1 was independent of cysteinyl leukotrienes but involved a translational mechanism. Further RNA-seq analysis identified that regulator of G-protein signaling 4 (RGS4) was a target gene of MGST3. Silencing of RGS4 inhibited BACE1 translation and prevented MGST3 KD-mediated reduction of BACE1. The potential mechanism was related to AKT activity, as the protein level of phosphorylated AKT was significantly reduced by silencing of MGST3 and RGS4, and the AKT inhibitor abolished the effect of MGST3/RGS4 on phosphorylated AKT and BACE1. Together, MGST3 regulated amyloidogenesis by controlling BACE1 protein expression, which was mediated by RGS4 and downstream AKT signaling pathway. Show less
📄 PDF DOI: 10.1016/j.jbc.2024.107530
BACE1
Bohong Chen, Lihui Wang, Shengyu Pu +7 more · 2024 · Scientific reports · Nature · added 2026-04-24
Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the managemen Show more
Hyperparathyroidism (HPT) manifests as a complex condition with a substantial disease burden. While advances have been made in surgical interventions and non-surgical pharmacotherapy for the management of hyperparathyroidism, radical options to halt underlying disease progression remain lacking. Identifying putative genetic drivers and exploring novel drug targets that can impede HPT progression remain critical unmet needs. A Mendelian randomization (MR) analysis was performed to uncover putative therapeutic targets implicated in hyperparathyroidism pathology. Cis-expression quantitative trait loci (cis-eQTL) data serving as genetic instrumental variables were obtained from the eQTLGen Consortium and Genotype-Tissue Expression (GTEx) portal. Hyperparathyroidism summary statistics for single nucleotide polymorphism (SNP) associations were sourced from the FinnGen study (5590 cases; 361,988 controls). Colocalization analysis was performed to determine the probability of shared causal variants underlying SNP-hyperparathyroidism and SNP-eQTL links. Five drug targets (CMKLR1, FSTL1, IGSF11, PIK3C3 and SLC40A1) showed significant causation with hyperparathyroidism in both eQTLGen and GTEx cohorts by MR analysis. Specifically, phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) and solute carrier family 40 member 1 (SLC40A1) showed strong evidence of colocalization with HPT. Multivariable MR and Phenome-Wide Association Study analyses indicated these two targets were not associated with other traits. Additionally, drug prediction analysis implies the potential of these two targets for future clinical applications. This study identifies PIK3C3 and SLC40A1 as potential genetically proxied druggable genes and promising therapeutic targets for hyperparathyroidism. Targeting PIK3C3 and SLC40A1 may offer effective novel pharmacotherapies for impeding hyperparathyroidism progression and reducing disease risk. These findings provide preliminary genetic insight into underlying drivers amenable to therapeutic manipulation, though further investigation is imperative to validate translational potential from preclinical models through clinical applications. Show less
no PDF DOI: 10.1038/s41598-024-57100-3
PIK3C3
Colette A Abbey, Camille L Duran, Zhishi Chen +8 more · 2024 · Arteriosclerosis, thrombosis, and vascular biology · added 2026-04-24
New blood vessel formation requires endothelial cells to transition from a quiescent to an invasive phenotype. Transcriptional changes are vital for this switch, but a comprehensive genome-wide approa Show more
New blood vessel formation requires endothelial cells to transition from a quiescent to an invasive phenotype. Transcriptional changes are vital for this switch, but a comprehensive genome-wide approach focused exclusively on endothelial cell sprout initiation has not been reported. Using a model of human endothelial cell sprout initiation, we developed a protocol to physically separate cells that initiate the process of new blood vessel formation (invading cells) from noninvading cells. We used this model to perform multiple transcriptomics analyses from independent donors to monitor endothelial gene expression changes. Single-cell population analyses, single-cell cluster analyses, and bulk RNA sequencing revealed common transcriptomic changes associated with invading cells. We also found that collagenase digestion used to isolate single cells upregulated the Fos proto-oncogene transcription factor. Exclusion of Fos proto-oncogene expressing cells revealed a gene signature consistent with activation of signal transduction, morphogenesis, and immune responses. Many of the genes were previously shown to regulate angiogenesis and included multiple tip cell markers. Upregulation of SNAI1 (snail family transcriptional repressor 1), PTGS2 (prostaglandin synthase 2), and JUNB (JunB proto-oncogene) protein expression was confirmed in invading cells, and silencing JunB and SNAI1 significantly reduced invasion responses. Separate studies investigated rounding 3, also known as RhoE, which has not yet been implicated in angiogenesis. Silencing rounding 3 reduced endothelial invasion distance as well as filopodia length, fitting with a pathfinding role for rounding 3 via regulation of filopodial extensions. Analysis of in vivo retinal angiogenesis in Validation of multiple genes, including rounding 3, revealed a functional role for this gene signature early in the angiogenic process. This study expands the list of genes associated with the acquisition of a tip cell phenotype during endothelial cell sprout initiation. Show less
no PDF DOI: 10.1161/ATVBAHA.123.320599
SNAI1
Danhua Ma, Jijun Chen, Yuyuan Shi +4 more · 2024 · Scientific reports · Nature · added 2026-04-24
In this study, we aimed to study the role of TCONS₀₀₀₀₆₀₉₁ in the pathogenesis of oral squamous cellular carcinoma (OSCC) transformed from oral lichen planus (OLP). This study recruited 108 OSCC pati Show more
In this study, we aimed to study the role of TCONS₀₀₀₀₆₀₉₁ in the pathogenesis of oral squamous cellular carcinoma (OSCC) transformed from oral lichen planus (OLP). This study recruited 108 OSCC patients which transformed from OLP as the OSCC group and 102 OLP patients with no sign of OSCC as the Control group. ROC curves were plotted to measure the diagnostic values of TCONS₀₀₀₀₆₀₉₁, miR-153, miR-370 and let-7g, and the changes in gene expressions were measured by RT-qPCR. Sequence analysis and luciferase assays were performed to analyze the molecular relationships among these genes. Cell proliferation and apoptosis were observed via MTT and FCM. TCONS₀₀₀₀₆₀₉₁ exhibited a better diagnosis value for OSCC transformed from OLP. OSCC group showed increased TCONS₀₀₀₀₆₀₉₁ expression and decreased expressions of miR-153, miR-370 and let-7g. The levels of SNAI1, IRS and HMGA2 was all significantly increased in OSCC patients. And TCONS₀₀₀₀₆₀₉₁ was found to sponge miR-153, miR-370 and let-7g, while these miRNAs were respectively found to targe SNAI1, IRS and HMGA2. The elevated TCONS₀₀₀₀₆₀₉₁ suppressed the expressions of miR-153, miR-370 and let-7g, leading to the increased expression of SNAI1, IRS and HMGA2. Also, promoted cell proliferation and suppressed apoptosis were observed upon the over-expression of TCONS₀₀₀₀₆₀₉₁. This study demonstrated that the expressions of miR-153, miR-370 and let-7g were down-regulated by the highly expressed TCONS₀₀₀₀₆₀₉₁ in OSCC patients, which accordingly up-regulated the expressions of SNAI1, IRS and HMGA2, resulting in the promoted cell proliferation and suppressed cell apoptosis. Show less
no PDF DOI: 10.1038/s41598-024-60310-4
SNAI1
Yu-Chen Liu, Sheng-Yi Chen, Ying-Ying Chen +3 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Patients may find it challenging to accept several FDA-approved drugs for Alzheimer's disease (AD) treatment due to their unaffordable prices and side effects. Despite the known antioxidant, anti-infl Show more
Patients may find it challenging to accept several FDA-approved drugs for Alzheimer's disease (AD) treatment due to their unaffordable prices and side effects. Despite the known antioxidant, anti-inflammatory, and microbiota-regulating effects of common buckwheat (Fagopyrum esculentum) polysaccharides (FEP), their specific role in preventing AD has not been determined. Here, this study investigated the preventive effects of FEP on AD development in AlCl Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.133898
BACE1
Ling Zeng, Zhikuan Yang, Wei Pan +5 more · 2024 · Journal of inflammation research · added 2026-04-24
In this study, we aimed to investigate the relationship between the intraocular levels of inflammatory factors and myopia-related retinal vascular and neuronal degeneration. One hundred and forty-seve Show more
In this study, we aimed to investigate the relationship between the intraocular levels of inflammatory factors and myopia-related retinal vascular and neuronal degeneration. One hundred and forty-seven patients with Implantable Collamer Lens (ICL) implantation were enrolled and all participants received comprehensive ophthalmic examination. About 100~150 ul of aqueous humor was collected immediately before ICL surgery. The levels of inflammatory factors including Aggrecan, April, BAFF, CCL5, CD163, Chi3l1, gp130, IL-6Rα, IL-8, IL-10, IL-11, IL-12, IL-19, IL-27, IL-28A, IL-34, IFN-β, IFN-γ, MMP-1, MMP-2, MMP-3 and PTX3 in the aqueous humor were measured using the Luminex Multiplexing system. Results showed that aqueous humor levels of pro-inflammatory factors Chi3l1, IL-6Rα, IL-8, IL-12, IL-27, inflammation-related cytokines April, BAFF and IL-34 progressively increased from the progression of myopic retinopathy. Conversely, the aqueous levels of IL-11 and Aggrecan gradually decreased from the progression of myopic retinopathy. Correlation analysis showed that the intraocular levels of Chi3l1, IL-6Rα, IL-8, IL-27 and BAFF were negatively correlated with retinal vascular density. The intraocular level of IL-6Rα was negatively correlated with retinal neuronal thickness. Protein-Protein Interaction (PPI) analysis revealed that Chi3l1 and Aggrecan were the upstream cytokines that affect IL-10 and IL-8 in the pathological myopic eyes. KEGG pathway analysis showed that cytokine-cytokine receptor interaction, JAK-STAT signaling pathway, rheumatoid arthritis, and chagas disease were influenced by these altered inflammatory factors (adjusted p-value<0.001). The production of inflammatory factors in the eyes of individuals with high myopia and pathological myopia was altered, and the elevated levels of intraocular pro-inflammatory factors such as Chi3l1, IL-6Rα, and IL-8 were closely associated with myopia-related retinal microvascular and neurodegeneration. Show less
📄 PDF DOI: 10.2147/JIR.S484338
IL27
Xinyue Ming, Shirui Chen, Huijuan Li +3 more · 2024 · Cellular signalling · Elsevier · added 2026-04-24
This study aimed to investigate the effects of hepatic microRNA-122 (miR-122) on Sortilin-mediated apolipoprotein B100 (apoB-100) secretion, and on aortic lipid deposition and atherosclerosis (AS) les Show more
This study aimed to investigate the effects of hepatic microRNA-122 (miR-122) on Sortilin-mediated apolipoprotein B100 (apoB-100) secretion, and on aortic lipid deposition and atherosclerosis (AS) lesions and to clarify the antiatherosclerotic mechanism of 6-methylcoumarin (6-MC) via the modulation of miR-122. Bioinformatics analysis revealed that miR-122 was putatively overexpressed in a liver-specific manner and was downregulated in steatotic livers. miR-122 was shown to suppress the expression of Sortilin by complementarily pairing to the 3'-untranslated region (3'-UTR) of Sortilin mRNA via bioinformatics and dual-luciferase reporter assays, impeding Sortilin-mediated apoB-100 secretion from HepG2 cells. Administration of 6-MC significantly upregulated hepatocellular miR-122 levels, reducing Sortilin expression and apoB-100 secretion in HepG2 cells. The miR-122 mimic vigorously enhanced 6-MC-depressed Sortilin expression, while miR-122 inhibitor repealed the inhibitory effect of 6-MC on Sortilin expression to some extent in HepG2 cells. After internal intervention with the miR-122 precursor, and 6-MC supplementation alone or in combination with the miR-122 sponge led to the reduction in blood triglyceride (TG) levels, low-density lipoprotein-cholesterol (LDL-C) and apoB-100 and a reduction in aortic lipid deposition and AS lesions in apolipoprotein E-deficient (ApoE Show less
no PDF DOI: 10.1016/j.cellsig.2024.111384
APOB
Huibin Huang, Juan Li, Tianhua Chen +5 more · 2024 · Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology · Taylor & Francis · added 2026-04-24
To analyse changes in lipid levels during the development of intrahepatic cholestasis of pregnancy (ICP) and identify new biomarkers for predicting ICP. A retrospective case-control study was conducte Show more
To analyse changes in lipid levels during the development of intrahepatic cholestasis of pregnancy (ICP) and identify new biomarkers for predicting ICP. A retrospective case-control study was conducted to analyse 473 pregnant women who underwent regular prenatal examinations and delivered at the Women and Children's Hospital, School of Medicine, Xiamen University, between June 2020 and June 2023, including 269 normal pregnancy controls and 204 pregnant women with cholestasis. Patients with ICP with gestational diabetes mellitus (GDM) have lower high-density lipoprotein (HDL) levels than in those without GDM. Total bile acid (TBA) levels were significantly higher in pregnant women with GDM than those without. The apolipoprotein A (APOA) level was lower in patients with ICP and hypothyroidism than those without hypothyroidism. TBA levels were significantly higher in pregnant women with hypothyroidism than those without. Triglyceride (TG) levels were significantly higher in patients with preeclampsia (PE) than those without. HDL and APOA levels were lower in women with ICP complicated by preterm delivery than those with normal delivery. The AUC (area under the curve) of the differential diagnosis of cholestasis of pregnancy for the APOA/APOB (apolipoprotein B) ratio was 0.727, with a sensitivity of 85.9% and specificity of 47.5%. The results suggested that dyslipidaemia is associated with an increased risk of ICP and its complications. The timely detection of blood lipid and bile acid levels can assist in the diagnosis of ICP and effectively prevent ICP and other complications. Show less
no PDF DOI: 10.1080/01443615.2024.2369929
APOB
Qianmeng Lin, Shuyan Dai, Lingzhi Qu +5 more · 2024 · Communications chemistry · Nature · added 2026-04-24
Acquired drug resistance poses a challenge for single-target FGFR inhibitors, leading to the development of dual- or multi-target FGFR inhibitors. Sulfatinib is a multi-target kinase inhibitor for tre Show more
Acquired drug resistance poses a challenge for single-target FGFR inhibitors, leading to the development of dual- or multi-target FGFR inhibitors. Sulfatinib is a multi-target kinase inhibitor for treating neuroendocrine tumors, selectively targeting FGFR1/CSF-1R. To elucidate the molecular mechanisms behind its binding and kinase selectivity, we determined the crystal structures of sulfatinib with FGFR1/CSF-1R. The results reveal common structural features and distinct conformational adaptability of sulfatinib in response to FGFR1/CSF-1R binding. Further biochemical and structural analyses disclose sensitivity of sulfatinib to FGFR/CSF-1R gatekeeper mutations. The insensitivity of sulfatinib to FGFR gatekeeper mutations highlights the indispensable interactions with the hydrophobic pocket for FGFR selectivity, whereas the rotatory flexibility may enable sulfatinib to overcome CSF-1R Show less
📄 PDF DOI: 10.1038/s42004-023-01084-0
FGFR1
Hao Meng, Zhiying Liao, Yanting Ji +15 more · 2024 · Signal transduction and targeted therapy · Nature · added 2026-04-24
The angiotensin-converting enzyme 2 (ACE2) is a primary cell surface viral binding receptor for SARS-CoV-2, so finding new regulatory molecules to modulate ACE2 expression levels is a promising strate Show more
The angiotensin-converting enzyme 2 (ACE2) is a primary cell surface viral binding receptor for SARS-CoV-2, so finding new regulatory molecules to modulate ACE2 expression levels is a promising strategy against COVID-19. In the current study, we utilized islet organoids derived from human embryonic stem cells (hESCs), animal models and COVID-19 patients to discover that fibroblast growth factor 7 (FGF7) enhances ACE2 expression within the islets, facilitating SARS-CoV-2 infection and resulting in impaired insulin secretion. Using hESC-derived islet organoids, we demonstrated that FGF7 interacts with FGF receptor 2 (FGFR2) and FGFR1 to upregulate ACE2 expression predominantly in β cells. This upregulation increases both insulin secretion and susceptibility of β cells to SARS-CoV-2 infection. Inhibiting FGFR counteracts the FGF7-induced ACE2 upregulation, subsequently reducing viral infection and replication in the islets. Furthermore, retrospective clinical data revealed that diabetic patients with severe COVID-19 symptoms exhibited elevated serum FGF7 levels compared to those with mild symptoms. Finally, animal experiments indicated that SARS-CoV-2 infection increased pancreatic FGF7 levels, resulting in a reduction of insulin concentrations in situ. Taken together, our research offers a potential regulatory strategy for ACE2 by controlling FGF7, thereby protecting islets from SARS-CoV-2 infection and preventing the progression of diabetes in the context of COVID-19. Show less
📄 PDF DOI: 10.1038/s41392-024-01790-8
FGFR1
Yanbing Han, Qingqing Mo, Zhuangzhuang Ma +8 more · 2024 · Nano letters · ACS Publications · added 2026-04-24
Long-persistent luminescence (LPL) materials have attracted intensive attention due to their fascinating emission after excitation. However, current LPL materials typically depend on external doping t Show more
Long-persistent luminescence (LPL) materials have attracted intensive attention due to their fascinating emission after excitation. However, current LPL materials typically depend on external doping to introduce traps or emitting centers, resulting in a complex synthesis and controllability. For the first time, we develop another category of undoped LPL materials based on antimonate CaSb Show less
no PDF DOI: 10.1021/acs.nanolett.4c04471
LPL
Lulu Sun, Qilu Zhang, Mengyao Shi +9 more · 2024 · Journal of the American Heart Association · added 2026-04-24
The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering dru Show more
The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering drug targets and the adverse prognosis of ischemic stroke patients remains unclear. Multiple single-nucleotide polymorphisms associated with 6 lipid-lowering drug targets were genotyped for patients with ischemic stroke. The primary outcome was death or major disability within 2 years after ischemic stroke. Genetic risk score was constructed from significant single-nucleotide polymorphisms identified via additive models, which was calculated by multiplying the number of risk alleles at each locus by the corresponding beta coefficient and then summing the products. The rs2006760-C of the rs2006760-C of Show less
📄 PDF DOI: 10.1161/JAHA.124.036544
CETP
Baotong Zhang, Mingcheng Liu, Fengyi Mai +13 more · 2024 · The Journal of clinical investigation · added 2026-04-24
Inactivation of phosphatase and tensin homolog (PTEN) is prevalent in human prostate cancer and causes high-grade adenocarcinoma with a long latency. Cancer-associated fibroblasts (CAFs) play a pivota Show more
Inactivation of phosphatase and tensin homolog (PTEN) is prevalent in human prostate cancer and causes high-grade adenocarcinoma with a long latency. Cancer-associated fibroblasts (CAFs) play a pivotal role in tumor progression, but it remains elusive whether and how PTEN-deficient prostate cancers reprogram CAFs to overcome the barriers for tumor progression. Here, we report that PTEN deficiency induced Krüppel-like factor 5 (KLF5) acetylation and that interruption of KLF5 acetylation orchestrated intricate interactions between cancer cells and CAFs that enhance FGF receptor 1 (FGFR1) signaling and promote tumor growth. Deacetylated KLF5 promoted tumor cells to secrete TNF-α, which stimulated inflammatory CAFs to release FGF9. CX3CR1 inhibition blocked FGFR1 activation triggered by FGF9 and sensitized PTEN-deficient prostate cancer to the AKT inhibitor capivasertib. This study reveals the role of KLF5 acetylation in reprogramming CAFs and provides a rationale for combined therapies using inhibitors of AKT and CX3CR1. Show less
📄 PDF DOI: 10.1172/JCI175949
FGFR1
Junming Huang, BoWen Li, Huangwei Wei +4 more · 2024 · Scientific reports · Nature · added 2026-04-24
Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Cu Show more
Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Currently, there are no definitive diagnostic indicators for PD. In this study, we aimed to identify potential diagnostic biomarkers for PD and analyzed the impact of immune cell infiltrations on disease pathogenesis. The PD expression profile data for human SN tissue, GSE7621, GSE20141, GSE20159, GSE20163 and GSE20164 were downloaded from the Gene Expression Omnibus (GEO) database for use in the training model. After normalization and merging, we identified differentially expressed genes (DEGs) using the Robust rank aggregation (RRA) analysis. Simultaneously, DEGs after batch correction were identified. Gene interactions were determined through venn Diagram analysis. Functional analyses and protein-protein interaction (PPI) networks were used to the identify hub genes, which were visualized through Cytoscape. A Lasso Cox regression model was employed to identify the potential diagnostic genes. The GSE20292 dataset was used for validation. The proportion of infiltrating immune cells in the samples were determined via the CIBERSORT method. Sixty-two DEGs were screened in this study. They were found to be enriched in nerve conduction, dopamine (DA) metabolism, and DA biosynthesis Gene Ontology (GO) terms. The PPI network and Lasso Cox regression analysis revealed seven potential diagnostic genes, namely SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1, were subsequently validated in peripheral blood samples obtained from healthy control (HC) and PD patients, as well as in the GSE20292 dataset. The results revealed the exceptional sensitivity and specificity of these genes in PD diagnosis and monitoring. Moreover, PD patients exhibited a higher number of plasma cells, compared to HC individuals. The SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1 are potential diagnostic biomarkers for PD. Our findings also reveal the essential roles of immune cell infiltration in both disease onset and trajectory. Show less
📄 PDF DOI: 10.1038/s41598-024-52276-0
AXIN1
Jun Gong, Alain C Mita, Zihan Wei +19 more · 2024 · JCO precision oncology · added 2026-04-24
Despite fibroblast growth factor receptor ( EAY131-K1 was an open-label, single-arm, phase II study with central confirmation of presence of Thirty-five patients were enrolled into this study with 18 Show more
Despite fibroblast growth factor receptor ( EAY131-K1 was an open-label, single-arm, phase II study with central confirmation of presence of Thirty-five patients were enrolled into this study with 18 included in the prespecified primary efficacy analysis. The median age of the 18 patients was 60 years, and 78% had received ≥3 previous lines of therapy. There were no confirmed responses to erdafitinib; however, five patients experienced stable disease (SD) as best response. One patient with an Erdafitinib did not meet its primary end point of efficacy as determined by ORR in treatment-refractory solid tumors harboring Show less
📄 PDF DOI: 10.1200/PO.23.00406
FGFR1
Lingang Dai, Dongwei An, Jiajin Huang +7 more · 2024 · International journal of biological macromolecules · Elsevier · added 2026-04-24
The kidding traits of goats are an important index of production. However, the molecular regulatory mechanisms of kidding traits in goats have not been fully elucidated. This study aimed to investigat Show more
The kidding traits of goats are an important index of production. However, the molecular regulatory mechanisms of kidding traits in goats have not been fully elucidated. This study aimed to investigate the molecular regulatory network of kidding traits in goats. Multi-omics revealed the enrichment of 10 signaling pathways, with fatty acid biosynthesis, biosynthesis of unsaturated fatty acids, and steroid hormone biosynthesis pathways being closely related to reproduction. Interestingly, the key rate-limiting enzymes, fatty acid synthase (FASN), stearoyl-CoA desaturase 5 (SCD5), fatty acid desaturase 1 (FADS1), 3β-hydroxysteroid dehydrogenase/isomerase (3BHSD), and steroidogenic acute regulatory protein (STAR) enriched in these pathways regulate changes in reproduction-related metabolites. In interference experiments, it was observed that suppressing these key rate-limiting enzymes inhibited the expression of CYP19A1, ESR2, and FSHR. Furthermore, interference inhibited granulosa cell proliferation, caused cell cycle arrest, and promoted apoptosis. Thus, these results suggest that the specific markers of nanny goats with multiple kids are the key rate-limiting enzymes FASN, SCD5, FADS1, 3BHSD, and STAR. These findings may greatly enhance the understanding of regulatory mechanisms that govern goat parturition. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.136737
FADS1
Chia-Hsuan Cheng, Hiromi Yatsuda, Han-Hsiang Chen +3 more · 2024 · Sensors (Basel, Switzerland) · MDPI · added 2026-04-24
Cardiovascular disease (CVD) represents the leading cause of death worldwide. For individuals at elevated risk for cardiovascular disease, early detection and monitoring of lipid status is imperative. Show more
Cardiovascular disease (CVD) represents the leading cause of death worldwide. For individuals at elevated risk for cardiovascular disease, early detection and monitoring of lipid status is imperative. The majority of lipid measurements conducted in hospital settings employ optical detection, which necessitates the use of relatively large-sized detection machines. It is, therefore, necessary to develop point-of-care testing (POCT) for lipoprotein in order to monitor CVD. To enhance the management and surveillance of CVD, this study sought to develop a POCT approach for apolipoprotein B (ApoB) utilizing a shear horizontal surface acoustic wave (SH-SAW) platform to assess the risk of heart disease. The platform employs a reflective SH-SAW sensor to reduce the sensor size and enhance the phase-shifted signals. In this study, the platform was utilized to monitor the impact of a weekly almond and oat milk or statins intervention on alterations in CVD risk. The SH-SAW ApoB test exhibited a linear range of 0 to 212 mg/dL, and a coefficient correlation (R) of 0.9912. Following a four-week intervention period, both the almond and oat milk intervention (-23.3%, Show less
📄 PDF DOI: 10.3390/s24206517
APOB
Yan Q Chen, Ye Yang, Eugene Y Zhen +18 more · 2024 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Apolipoprotein AV (APOA5) lowers plasma triglyceride (TG) levels by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its capacity to inhibit lipoprotein lipase (LPL) ca Show more
Apolipoprotein AV (APOA5) lowers plasma triglyceride (TG) levels by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its capacity to inhibit lipoprotein lipase (LPL) catalytic activity and its ability to detach LPL from binding sites within capillaries. However, the sequences in APOA5 that are required for suppressing ANGPTL3/8 activity have never been defined. A clue to the identity of those sequences was the presence of severe hypertriglyceridemia in two patients harboring an Show less
📄 PDF DOI: 10.1073/pnas.2322332121
APOA5
Xiong Gao, Wei Luo, Liyuan Qu +14 more · 2024 · European journal of preventive cardiology · Oxford University Press · added 2026-04-24
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA Show more
The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA remains controversial. The study aimed to investigate the genetic association between lipid-lowering drugs and AA. Our research used publicly available data on genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) studies. Genetic instruments, specifically eQTLs related to drug-target genes and SNPs (single nucleotide polymorphisms) located near or within the drug-target loci associated with low-density lipoprotein cholesterol (LDL-C), have been served as proxies for lipid-lowering medications. Drug-Target Mendelian Randomization (MR) study is used to determine the causal association between lipid-lowering drugs and different types of AA. The MR analysis revealed that higher expression of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase) was associated with increased risk of AA (OR = 1.58, 95% CI = 1.20-2.09, P = 1.20 × 10-03) and larger lumen size (aortic maximum area: OR = 1.28, 95% CI = 1.13-1.46, P = 1.48 × 10-04; aortic minimum area: OR = 1.26, 95% CI = 1.21-1.42, P = 1.78 × 10-04). PCSK9 (proprotein convertase subtilisin/kexin type 9) and CETP (cholesteryl ester transfer protein) show a suggestive relationship with AA (PCSK9: OR = 1.34, 95% CI = 1.10-1.63, P = 3.07 × 10-03; CETP: OR = 1.38, 95% CI = 1.06-1.80, P = 1.47 × 10-02). No evidence to support genetically mediated NPC1L1 (Niemann-Pick C1-Like 1) and LDLR (low-density lipoprotein cholesterol receptor) are associated with AA. This study provides causal evidence for the genetic association between lipid-lowering drugs and AA. Higher gene expression of HMGCR, PCSK9, and CETP increases AA risk. Furthermore, HMGCR inhibitors may link with smaller aortic lumen size. Show less
no PDF DOI: 10.1093/eurjpc/zwae044
CETP
Caibo Ning, Meng Jin, Yimin Cai +28 more · 2024 · BMC medicine · BioMed Central · added 2026-04-24
The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysi Show more
The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus's high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential. We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits. Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10 These findings highlight the extensive distribution of pleiotropic genetic determinants between HASVs and neuropsychiatric traits. Moreover, they suggest a significant potential for effectively managing and intervening in these diseases during their early stages. Show less
📄 PDF DOI: 10.1186/s12916-024-03682-8
KANSL1
Zekun Xin, Lijun Dong, Guojun Chen +1 more · 2024 · Asian journal of surgery · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.asjsur.2024.11.010
FADS3
Chen Chen, Vanessa G Lee · 2024 · Attention, perception & psychophysics · added 2026-04-24
Attention is tuned towards locations that frequently contain a visual search target (location probability learning; LPL). Peripheral vision, covering a larger field than the fovea, often receives info Show more
Attention is tuned towards locations that frequently contain a visual search target (location probability learning; LPL). Peripheral vision, covering a larger field than the fovea, often receives information about the target. Yet what is the role of peripheral vision in attentional learning? Using gaze-contingent eye tracking, we examined the impact of simulated peripheral vision loss on location probability learning. Participants searched for a target T among distractor Ls. Unbeknownst to them, the T appeared disproportionately often in one quadrant. Participants searched with either intact vision or "tunnel vision," restricting the visible search items to the central 6.7º (in diameter) of the current gaze. When trained with tunnel vision, participants in Experiment 1 acquired LPL, but only if they became explicitly aware of the target's location probability. The unaware participants were not faster finding the target in high-probability than in low-probability locations. When trained with intact vision, participants in Experiment 2 successfully acquired LPL, regardless of whether they were aware of the target's location probability. Thus, whereas explicit learning may proceed with central vision alone, implicit LPL is strengthened by peripheral vision. Consistent with Guided Search (Wolfe, 2021), peripheral vision supports a nonselective pathway to guide visual search. Show less
📄 PDF DOI: 10.3758/s13414-023-02808-z
LPL
Jianmin Zhu, Liting Yang, Jing Xia +6 more · 2024 · Transplantation · added 2026-04-24
Stimulation of myeloid-derived suppressor cell (MDSC) formation represents a potential curative therapeutic approach for graft-versus-host disease (GVHD), which significantly impacts the prognosis of Show more
Stimulation of myeloid-derived suppressor cell (MDSC) formation represents a potential curative therapeutic approach for graft-versus-host disease (GVHD), which significantly impacts the prognosis of allogeneic hematopoietic stem cell transplantation. However, the lack of an effective strategy for inducing MDSC production in vivo has hindered their clinical application. In our previous study, MDSC expansion was observed in interleukin (IL)-27-treated mice. In this study, we overexpressed exogenous IL-27 in mice using a recombinant adeno-associated virus vector to investigate its therapeutic and exacerbating effects in murine GVHD models. In our study, we demonstrated that exogenous administration of IL-27 significantly suppressed GVHD development in a mouse model. We found that IL-27 treatment indirectly inhibited the proliferation and activation of donor T cells by rapidly expanding recipient and donor myeloid cells, which act as MDSCs after irradiation or under inflammatory conditions, rather than through regulatory T-cell expansion. Additionally, IL-27 stimulated MDSC expansion by enhancing granulocyte-monocyte progenitor generation. Notably, we verified that IL-27 signaling in donor T cells exerted an antagonistic effect on GVHD prevention and treatment. Further investigation revealed that combination therapy involving IL-27 and T-cell depletion exhibited remarkable preventive effects on GVHD in both mouse and xenogeneic GVHD models. Collectively, these findings suggest that IL-27 promotes MDSC generation to reduce the incidence of GVHD, whereas targeted activation of IL-27 signaling in myeloid progenitors or its combination with T-cell depletion represents a potential strategy for GVHD therapy. Show less
no PDF DOI: 10.1097/TP.0000000000005069
IL27
Haoran E, Lei Zhang, Zhenhua Yang +11 more · 2024 · Journal of experimental & clinical cancer research : CR · BioMed Central · added 2026-04-24
Thymic epithelial tumors (TETs) are infrequent malignancies that arise from the anterior mediastinum. Therapeutic options for TETs, especially thymic carcinoma (TC), remain relatively constrained. Thi Show more
Thymic epithelial tumors (TETs) are infrequent malignancies that arise from the anterior mediastinum. Therapeutic options for TETs, especially thymic carcinoma (TC), remain relatively constrained. This study aims to investigate the oncogenic hub gene and its underlying mechanisms in TETs, as well as to identify potential therapeutic targets. Weighted gene co-expression network analysis (WGCNA) and differential gene expression (DEG) analysis were utilized to identify significant oncogenes using The Cancer Genome Atlas (TCGA) database. LASSO logistic regression analysis was performed to assess the association between hub genes and clinical parameters. The influence of the hub gene on promoting epithelial-mesenchymal transition (EMT), tumor progression, and regulating cancer stem cell-like properties was assessed both in vitro and in vivo. Single-cell RNA sequencing (scRNA-seq) was utilized to analyze the alterations in the tumor and its microenvironment following the administration of the hub gene's inhibitor. Multiplex immunohistochemistry (mIHC) was employed to validate the results. The potential mechanism was further elucidated through the utilization of Cleavage Under Targets and Tagmentation (CUT&Tag), RNA-sequencing, chromatin immunoprecipitation (ChIP), CUT&RUN, luciferase reporter assay, co-immunoprecipitation (Co-IP), mass spectrometry (MS) and phosphoproteomic assays. SNAI1 was identified as a hub transcription factor for TETs, and its positive correlation with the invasiveness of the disease was confirmed. Subsequent experiments revealed that the upregulation of SNAI1 augmented the migration, invasion, and EMT of TET cell lines. Furthermore, we observed that the overexpression of SNAI1 sustained cancer stem cell-like properties. ScRNA-seq demonstrated that the use of a SNAI1 inhibitor inhibited the transition of macrophages from M1 to M2 phenotype, a finding further validated by multiplex immunohistochemistry (mIHC). Phosphoinositide-3-kinase regulatory subunit 2 (PIK3R2) was identified as one of the downstream targets of SNAI1 through CUT&Tag and RNA-sequencing, a finding validated by ChIP-qPCR, CUT&RUN-qPCR, luciferase reporter and immunofluorescence assays. Co-IP, MS and phosphoproteomic assays further confirmed that PIK3R2 directly interacted with phosphorylated EphA2 (p-EphA2), facilitating downstream GSK3β/β-catenin signaling pathway. The tumorigenic role of SNAI1 through the PIK3R2/p-EphA2 axis was preliminarily validated in TETs. A potential therapeutic strategy for TETs may involve the inhibition of SNAI1. Show less
no PDF DOI: 10.1186/s13046-024-03243-0
SNAI1
Soo Heon Kwak, Shylaja Srinivasan, Ling Chen +15 more · 2024 · Nature metabolism · Nature · added 2026-04-24
The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily
📄 PDF DOI: 10.1038/s42255-023-00970-0
MC4R
You-Wang Lu, Rong-Jing Dong, Lu-Hui Yang +6 more · 2024 · Scientific reports · Nature · added 2026-04-24
Leprosy and psoriasis rarely coexist, the specific molecular mechanisms underlying their mutual exclusion have not been extensively investigated. This study aimed to reveal the underlying mechanism re Show more
Leprosy and psoriasis rarely coexist, the specific molecular mechanisms underlying their mutual exclusion have not been extensively investigated. This study aimed to reveal the underlying mechanism responsible for the mutual exclusion between psoriasis and leprosy. We obtained leprosy and psoriasis data from ArrayExpress and GEO database. Differential expression analysis was conducted separately on the leprosy and psoriasis using DEseq2. Differentially expressed genes (DEGs) with opposite expression patterns in psoriasis and leprosy were identified, which could potentially involve in their mutual exclusion. Enrichment analysis was performed on these candidate mutually exclusive genes, and a protein-protein interaction (PPI) network was constructed to identify hub genes. The expression of these hub genes was further validated in an external dataset to obtain the critical mutually exclusive genes. Additionally, immune cell infiltration in psoriasis and leprosy was analyzed using single-sample gene set enrichment analysis (ssGSEA), and the correlation between critical mutually exclusive genes and immune cells was also examined. Finally, the expression pattern of critical mutually exclusive genes was evaluated in a single-cell transcriptome dataset. We identified 1098 DEGs in the leprosy dataset and 3839 DEGs in the psoriasis dataset. 48 candidate mutually exclusive genes were identified by taking the intersection. Enrichment analysis revealed that these genes were involved in cholesterol metabolism pathways. Through PPI network analysis, we identified APOE, CYP27A1, FADS1, and SOAT1 as hub genes. APOE, CYP27A1, and SOAT1 were subsequently validated as critical mutually exclusive genes on both internal and external datasets. Analysis of immune cell infiltration indicated higher abundance of 16 immune cell types in psoriasis and leprosy compared to normal controls. The abundance of 6 immune cell types in psoriasis and leprosy positively correlated with the expression levels of APOE and CYP27A1. Single-cell data analysis demonstrated that critical mutually exclusive genes were predominantly expressed in Schwann cells and fibroblasts. This study identified APOE, CYP27A1, and SOAT1 as critical mutually exclusive genes. Cholesterol metabolism pathway illustrated the possible mechanism of the inverse association of psoriasis and leprosy. The findings of this study provide a basis for identifying mechanisms and therapeutic targets for psoriasis. Show less
📄 PDF DOI: 10.1038/s41598-024-52783-0
FADS1
Yajing Shen, Jiajun Chen, Jinyu Wu +6 more · 2024 · Cancer prevention research (Philadelphia, Pa.) · added 2026-04-24
The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. Show more
The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. This study was divided into four phases: discovery, verification, validation, and modeling. A total of four candidate tumor-associated autoantibodies (TAAb; anti-ZIC2, anti-PCNA, anti-CDC37L1, and anti-DUSP6) were identified by human proteome microarray (52 samples) and bioinformatics analysis. Subsequently, these candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts (120 samples for verification and 663 samples for validation). The AUC for these four TAAbs to identify patients with HBV-HCC from chronic hepatitis B (CHB) patients ranged from 0.693 to 0.739. Finally, a diagnostic panel with three TAAbs (anti-ZIC2, anti-CDC37L1, and anti-DUSP6) was developed. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with alpha-fetoprotein (AFP), with an AUC of 0.834 [95% confidence interval (CI), 0.772-0.897] for this panel and 0.727 (95% CI, 0.642-0.812) for AFP (P = 0.0359). In addition, the AUC for this panel to identify AFP-negative patients with HBV-HCC was 0.796 (95% CI, 0.734-0.858), with a sensitivity of 52.4% and a specificity of 89.0%. Importantly, the panel in combination with AFP significantly increased the positive rate for early HBV-HCC to 84.1% (P = 0.005) and for late HBV-HCC to 96.3% (P < 0.001). Our findings suggest that AFP and the autoantibody panel may be independent but complementary serologic biomarkers for HBV-HCC detection. We developed a robust diagnostic panel for identifying patients with HBV-HCC from patients with CHB. This autoantibody panel provided superior diagnostic performance for HBV-HCC at an early stage and/or with negative AFP results. Our findings suggest that AFP and the autoantibody panel may be independent but complementary biomarkers for HBV-HCC detection. Show less
no PDF DOI: 10.1158/1940-6207.CAPR-23-0311
DUSP6
Zhiqiang Zha, Chunhong Jia, Ruisi Zhou +13 more · 2024 · NPJ biofilms and microbiomes · Nature · added 2026-04-24
Fetal growth restriction (FGR) is a common complication of pregnancy, which seriously endangers fetal health and still lacks effective therapeutic targets. Clostridium difficile (C. difficile) is asso Show more
Fetal growth restriction (FGR) is a common complication of pregnancy, which seriously endangers fetal health and still lacks effective therapeutic targets. Clostridium difficile (C. difficile) is associated with fetal birth weight, and its membrane vesicles (MVs) are pathogenic vectors. However, the role of C. difficile and its MVs in FGR remains unclear. Here we found that supplementation with C. difficile altered the characteristics of gut microbiota and reduced the birth weight in mice. Interestingly, C. difficile MVs entered placenta, inhibited trophoblast motility, and induced fetal weight loss in mice. Mechanistically, C. difficile MVs activated the PPAR pathway via enhancing the transcriptional activity of PPARγ promoter, consequently inhibiting trophoblast motility. Moreover, PPARγ expression was significantly elevated in FGR placenta, and negatively correlated with fetal birth weight. Together, our findings reveal the significance of C. difficile and its MVs in FGR, providing new insights into the mechanisms of FGR development. Show less
📄 PDF DOI: 10.1038/s41522-024-00630-5
ANGPTL4
Chen Yao, Hanyong Zhu, Binbin Ji +18 more · 2024 · Cellular and molecular life sciences : CMLS · Springer · added 2026-04-24
The metabolic reprogramming of macrophages is a potential therapeutic strategy for sepsis treatment, but the mechanism underlying this reprogramming remains unclear. Since glycolysis can drive macroph Show more
The metabolic reprogramming of macrophages is a potential therapeutic strategy for sepsis treatment, but the mechanism underlying this reprogramming remains unclear. Since glycolysis can drive macrophage phenotype switching, the rate-limiting enzymes in glycolysis may be key to treating sepsis. Here, we found that, compared with other isoenzymes, the expression of 6-phosphofructokinase, muscle type (PFKM) was the most upregulated in monocytes from septic patients. Recombinant thrombomodulin (rTM) treatment downregulated the protein expression of PFKM in macrophages. Both rTM treatment and Pfkm knockout protected mice from sepsis and reduced the production of the proinflammatory cytokines IL-1β, IL-6, TNF-α, and IL-27, whereas PFKM overexpression increased the production of these cytokines. Mechanistically, rTM treatment inhibited glycolysis in macrophages by decreasing PFKM expression in a hypoxia-inducible factor-1α (HIF-1α)-dependent manner. HIF-1α overexpression increased methyltransferase-like 3 (METTL3) expression, elevated the m Show less
📄 PDF DOI: 10.1007/s00018-024-05489-5
IL27