👤 Chuyu Chen

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2981
Articles
1996
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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, 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, Shuang 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
Edin Muratspahić, David Feldman, David E Kim +43 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, yet the design of protein agonists and antagonists has been challenging as Show more
G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, yet the design of protein agonists and antagonists has been challenging as GPCRs are integral membrane proteins and conformationally dynamic. Here we describe computational Show less
📄 PDF DOI: 10.1101/2025.03.23.644666
GIPR
Yue Yao, Ting Shu, Xiying Guo +6 more · 2025 · ACS omega · ACS Publications · added 2026-04-24
Examining how hypoglycemic medications affect brain function is one of the best approaches to addressing cognitive impairment. In this study, trelagliptin, a dipeptidyl peptidase-4 (DPP4) inhibitor, w Show more
Examining how hypoglycemic medications affect brain function is one of the best approaches to addressing cognitive impairment. In this study, trelagliptin, a dipeptidyl peptidase-4 (DPP4) inhibitor, was utilized to assess memory loss in diabetic rats through fear conditioning tests. Trelagliptin restored fear memory in diabetic rats that had been disrupted over a relatively long period (24 h) or extended period (5 days). Moreover, trelagliptin treatment reduced the higher incidence of neuronal cell death in the cerebral cortex, as observed via Nissl or hematoxylin and eosin staining. Subsequent analyses revealed that diabetic rats exhibited elevated levels of inflammatory cytokines (p-IKKα and p-NFκB) and a trend toward oxidative damage, indicated by malondialdehyde (MDA), superoxide dismutase 2 (SOD2), and glutathione peroxidase 4 (GPX4) detection. However, administration of trelagliptin reversed these markers to baseline levels. Additionally, trelagliptin activated p-AMPK, p-AKT, and p-GSK-3β. Notably, trelagliptin upregulated the expression of postsynaptic density protein 95 (PSD95) and synaptotagmin 1 (SYT1) while downregulating amyloid precursor protein (APP) and beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). These findings suggest that trelagliptin alleviates cognitive impairment in diabetic rats, likely through AMPK-AKT-GSK-3β-mediated mitigation of oxidative stress, enhancement of synaptic plasticity, and reduction of Aβ accumulation. Show less
📄 PDF DOI: 10.1021/acsomega.5c00535
BACE1
Susan Adanna Ihejirika, Alexandra Huong Chiang, Aryaman Singh +3 more · 2025 · HGG advances · Elsevier · added 2026-04-24
Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unident Show more
Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unidentified gene-FOS interactions. To identify genetic factors that interact with FOS to alter the circulating levels of PUFAs, we performed a multi-level genome-wide interaction study (GWIS) of FOS on 14 plasma measurements in 200,060 unrelated European-ancestry individuals from the UK Biobank. From our single-variant tests, we identified genome-wide significant interacting SNPs (p < 5 × 10 Show less
📄 PDF DOI: 10.1016/j.xhgg.2025.100459
FADS1
Zhenwei Dai, Shu Jing, Haiyan Hu +8 more · 2025 · Brain and behavior · Wiley · added 2026-04-24
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult w Show more
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult women infected with HPV. This study aimed to adapt and validate the HPVsStigma scale (HPV-SS) in the Chinese context. A cross-sectional study was conducted from December 2024 to February 2025 among 501 HPV-infected women in Shenzhen, China. The HPV-SS was adapted from a 12-item HIV stigma scale. Demographic characteristics, HPV-related variables, and data on mental health were collected. Factor analyses (FA) were used to assess the scale's factorial structure, reliability, and validity. The bi-factor model was used to determine the score-reporting method of the scale. Item response theory (IRT) was employed to assess the relationship between participants' stigma levels and scale scores. Latent profile analysis (LPA) was conducted to classify the participants with different HPV stigma characteristics and determine the optimal cut-off value for HPV-SS. FA showed that the 3-factor model (personalized stigma, public-disclosure concerns, and negative self-image) had the best fit among the nested models, with good reliability and validity. The bi-factor model analysis indicated that the total scale score was more meaningful than dimension scores. IRT analysis confirmed that higher HPV-SS scores represented higher stigma levels. LPA identified a 2-class model as optimal, and the optimal cut-off value of the scale for high HPV stigma was 35. This study validated the 12-item HPV-SS for Chinese women infected with HPV, with good reliability and validity. The scale can be used to evaluate HPV stigma levels, facilitating targeted interventions to improve cervical cancer prevention and the psychological well-being of affected women. Show less
📄 PDF DOI: 10.1002/brb3.71044
LPA
Yu-Fan Chen, Chien-Wei Lee, Yi-Shuan J Li +8 more · 2025 · Experimental & molecular medicine · Nature · added 2026-04-24
Macrophages play a crucial role in coordinating the skeletal muscle repair response, but their phenotypic diversity and the transition of specialized subsets to resolution-phase macrophages remain poo Show more
Macrophages play a crucial role in coordinating the skeletal muscle repair response, but their phenotypic diversity and the transition of specialized subsets to resolution-phase macrophages remain poorly understood. Here, to address this issue, we induced injury and performed single-cell RNA sequencing on individual cells in skeletal muscle at different time points. Our analysis revealed a distinct macrophage subset that expressed high levels of Gpnmb and that coexpressed critical factors involved in macrophage-mediated muscle regeneration, including Igf1, Mertk and Nr1h3. Gpnmb gene knockout inhibited macrophage-mediated efferocytosis and impaired skeletal muscle regeneration. Functional studies demonstrated that GPNMB acts directly on muscle cells in vitro and improves muscle regeneration in vivo. These findings provide a comprehensive transcriptomic atlas of macrophages during muscle injury, highlighting the key role of the GPNMB macrophage subset in regenerative processes. Our findings suggest that modulating GPNMB signaling in macrophages may represent a promising avenue for future research into therapeutic strategies for enhancing skeletal muscle regeneration. Show less
no PDF DOI: 10.1038/s12276-025-01467-4
NR1H3
Wei Wang, Zhaosu Song, Ye Chen +6 more · 2025 · Journal of food science · Blackwell Publishing · added 2026-04-24
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi- Show more
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi-component activity. The effectiveness of these botanical extracts is thought to involve complex interactions among diverse constituents; however, the molecular basis of such interactions remains insufficiently understood. In this study, we explored the anti-inflammatory properties of the ethanol extract of Polygonum multiflorum (PME) through a combination of chemical profiling and computational analysis. PME was found to reduce the production of nitric oxide, inducible nitric oxide synthase, and interleukin-6 in LPS-stimulated RAW 264.7 macrophages. Using HS-SPME-GC-MS in conjunction with network pharmacology, we identified 32 volatile constituents, among which five core compounds were predicted to be associated with three inflammation-related targets: ESR1, FASN, and NR1H3. Dual-ligand molecular docking and molecular dynamics simulations suggested that the sequence of ligand binding may influence the stability and interaction patterns of protein-ligand complexes, offering insights into possible mechanisms of synergy and antagonism mediated by key residues such as ARG394 in ESR1. Overall, these findings contribute to a better understanding of how binding order and structural context may shape constituent-target interactions, providing a basis for the further development of multi-component natural product strategies against inflammation. This study underscores the relevance of incorporating multi-ligand dynamics into natural product research and presents an integrated experimental-computational framework to investigate the cooperative or competitive behaviors of functional food constituents, thereby supporting the rational design of optimized multi-target formulations. Show less
no PDF DOI: 10.1111/1750-3841.70708
NR1H3
Jia-Ling Yang, Long-Huw Lee, Hsing-Chieh Wu +3 more · 2025 · Developmental and comparative immunology · Elsevier · added 2026-04-24
The seven-transmembrane (7TM) receptors are the largest superfamily of cell-surface receptors and are involved in various physiological processes of vertebrate species. In our previous study, a new ch Show more
The seven-transmembrane (7TM) receptors are the largest superfamily of cell-surface receptors and are involved in various physiological processes of vertebrate species. In our previous study, a new chicken 7TM receptor (Ch-7TM) was discovered in mononuclear phagocytes (MNPs) derived from chicken peripheral blood mononuclear cells (PBMCs). To explore the functions of Ch-7TM, RNA interference (RNAi) was used to silence the Ch-7TM messenger RNA (mRNA) of MNPs, using small interfering RNA (siRNA) designed with BLOCK-iT™ RNAi Designer. Herein we demonstrated that silencing of the Ch-7TM mRNA induced apoptosis of MNPs, suggesting that Ch-7TM contributed to the survival of MNPs. Moreover, chicken sera could inhibit the Ch-7TM-silencing-induced apoptosis in MNPs. The survival factor presented in fraction 16 (F16) of chicken sera was highly protective against the Ch-7TM-silencing-induced apoptosis in MNPs. The proteins from F16 were identified as vitamin D-binding protein (DBP) and apolipoprotein A-IV (ApoA-IV), which might be potential candidates for survival factors. The protective effect of vitamin D and ApoA-IV indicated that Ch-7TM might involve the intracellular oxidation-reduction balance, although more evidence is needed to confirm this function. The siRNA screening serves as an excellent model for studying the functions of chicken MNPs receptors. Show less
no PDF DOI: 10.1016/j.dci.2025.105423
APOA4
Liping Chen, Jiawei Wang, Kangyuan Li +6 more · 2025 · Journal of oleo science · added 2026-04-24
1,3-dilinoleoyl-2-palmitoylglycerol (LPL) is an important structural lipid in breast milk fat, which plays an important role in the health of infants, and therefore the development of an efficient met Show more
1,3-dilinoleoyl-2-palmitoylglycerol (LPL) is an important structural lipid in breast milk fat, which plays an important role in the health of infants, and therefore the development of an efficient method for the preparation of such compounds is necessary. In the present study, LPL was efficiently catalytically synthesized by immobilized lipase ANL-MARE as a biocatalyst using tripalmitate and linoleic acid in a solvent-free system, and its digestive properties were investigated. The optimal process conditions for the enzymatic acidolysis of LPL were optimized by response surface test: the molar ratio of PPP:LA was 1:10, the enzyme addition was 13.60%, the reaction temperature was 50℃, and the reaction time was 5 h. At this time, the relative content of LPL in the product was 67.78%, of which the relative content of sn-2 palmitic acid (sn-2 PA) accounted for 71.50%. In vitro gastrointestinal digestion of LPL resulted in the release of 59.69% of its fatty acids. The digested product contained higher levels of free unsaturated fatty acids and palmitic acid monoacylglycerols. In conclusion, the immobilized enzyme ANL-MARE has great potential to catalyze the preparation of LPL, which provides a new strategy and theoretical basis for the efficient preparation of human milk fat substitutes. Show less
no PDF DOI: 10.5650/jos.ess25025
LPL
Shenglong Tan, Xinghong Luo, Yifan Wang +9 more · 2025 · Biomaterials · Elsevier · added 2026-04-24
Traumatic defects or non-union fractures presents a substantial challenge in the fields of tissue engineering and regenerative medicine. Although synthetic calcium phosphate-based biomaterials (CaPs) Show more
Traumatic defects or non-union fractures presents a substantial challenge in the fields of tissue engineering and regenerative medicine. Although synthetic calcium phosphate-based biomaterials (CaPs) such as dibasic calcium phosphate anhydrate (DCPA) are commonly employed for bone repair, their inadequate cellular immune responses significantly impede sustained degradation and optimal osteogenesis. In this study, drawing inspiration from the key structure of an acidic non-collagenous protein-CaP complex (ANCPs-CaP) essential for natural bone formation, we prepared biomimetic mineralized dibasic calcium phosphate (MDCPA). This preparation utilized plant-derived non-collagenous protein Zein as the organic template and acidic artificial saliva as the mineralization medium. Physicochemical property analysis revealed that MDCPA is a complex of Zein and DCPA, which mimics the composite of the natural ANCP-CaP. Moreover, MDCPA exhibited enhanced biodegradability and osteogenic potential. Mechanistic insight revealed that MDCPA can be phagocytized and degraded by macrophages via the FCγRIII receptor, leading to the release of interleukin 27 (IL-27), which promotes osteogenic differentiation by osteoimmunomodulation. The critical role of IL-27 in osteogenesis is further confirmed using IL-27 gene knockout mice. Additionally, MDCPA demonstrates effective healing of critical-sized defects in rat cranial bones within only 4 w, providing a promising basis and valuable insights for critical-sized bone defects regeneration. Show less
no PDF DOI: 10.1016/j.biomaterials.2024.122917
IL27
Binzhen Chen, Jia Liu, Yaoxin Zhang +10 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Multiple myeloma (MM) remains an incurable disease primarily due to the emergence of drug resistance, and the underlying mechanisms remain unclear. Extrachromosomal circular DNAs (eccDNAs) are prevale Show more
Multiple myeloma (MM) remains an incurable disease primarily due to the emergence of drug resistance, and the underlying mechanisms remain unclear. Extrachromosomal circular DNAs (eccDNAs) are prevalent in cancer genomes of both coding and non-coding regions. However, the role of non-coding eccDNA regions that serve as enhancers has been largely overlooked. Here, genome-wide profiling of serum eccDNAs from donors and MM patients who responded well or poorly to bortezomib-lenalidomide-dexamethasone (VRd) therapy is characterized. A high copy number of eccDNA ANKRD28 (eccANKRD28) predicts poor therapy response and prognosis but enhanced transcriptional activity. Established VRd-resistant MM cell lines exhibit a higher abundance of eccANKRD28, and CRISPR/Cas9-mediated elevation of eccANKRD28 desensitizes bortezomib and lenalidomide treatment both in vitro and in vivo. Integrated multi-omics analysis (H3K27ac ChIP-seq, scRNA-seq, scATAC-seq, CUT&Tag, et al.) identifies eccANKRD28 as an active enhancer involved in drug resistance driven by the key transcription factor, POU class 2 homeobox 2 (POU2F2). POU2F2 interacts with sequence-specific eccANKRD28 as well as RUNX1 and RUNX2 motifs to form the protein complex, which activates the promoter of oncogenes, including IRF4, JUNB, IKZF3, RUNX3, and BCL2. This study elucidates the potential transcriptional network of enhancer eccANKRD28 in MM drug resistance from a previously unrecognized epigenetic perspective. Show less
📄 PDF DOI: 10.1002/advs.202415695
ANKRD28
Guanghao Chen, Kundi Tai, Guoyu Dai · 2025 · Clinical and experimental medicine · Springer · added 2026-04-24
This study aims to explore the plastic changes in cell lineages during the progression of osteoarthritis (OA) and their relationship with dysregulation of signaling pathways and provide new molecular Show more
This study aims to explore the plastic changes in cell lineages during the progression of osteoarthritis (OA) and their relationship with dysregulation of signaling pathways and provide new molecular targets for precise treatment. Single-cell RNA sequencing (scRNA-seq) technology was utilized to perform high-resolution cell lineage analysis of OA patients. The mappings of distinct cell subpopulations were systematically constructed and revealed the changes in key cell types and their transformation trajectories throughout the progression of OA. Furthermore, KEGG and GO enrichment and pseudotime trajectory analysis were applied to elucidate the functional reprogramming of different cell types and the dynamic imbalance of their signaling networks in OA. Additionally, in vitro experiments were conducted to validate the biological functions of candidate genes in OA. Articular cartilage showed a transcriptional cellular heterogeneity in OA by scRNA-seq analysis; the annotated PreFC, FC, and PreHTC subsets accounted for the main part of OA samples. PreFC cells revealed transcription, signaling, and metabolic reprogramming in OA; pseudotime trajectory found that PreFC transformed to FC cells under the condition of hypoxia and metabolic reprogramming, while fibrosis and ECM degradation pathways showed intense upregulation in preHTC evolved from PreFC cells. HIF1A and ANGPTL4 were identified as key molecular regulators of OA progression, contributing to ECM degradation, inflammation, and apoptosis in chondrocytes, as confirmed through functional validation. The cellular trajectories of OA show significant plasticity changes which are influenced by the dysregulation of multiple signaling pathways. This research provides new insights into the pathological process of OA and offers potential targets for therapeutic strategies targeting these abnormal mechanisms. Show less
📄 PDF DOI: 10.1007/s10238-025-01947-x
ANGPTL4
Jian Xu, Yuhan Wang, Weiqi Mao +9 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Acute respiratory distress syndrome (ARDS) is a severe clinical condition characterized by widespread inflammation and fluid accumulation in the lungs. Endothelial cell (EC) metabolic changes in acute Show more
Acute respiratory distress syndrome (ARDS) is a severe clinical condition characterized by widespread inflammation and fluid accumulation in the lungs. Endothelial cell (EC) metabolic changes in acute lung injury (ALI) and their relationship to injury remain unclear. Transcriptomic and lipidomic analyses revealed downregulation of PUFA synthesis pathways, particularly omega-3 PUFAs, in pulmonary ECs during LPS-induced ALI. Activation of the PUFA metabolic pathway, through FADS1/2 overexpression or omega-3 fatty acid supplementation, protected ECs from ferroptosis and restored barrier function. In vivo, pulmonary EC-specific overexpression of FADS1/2 contributed to the alleviation of ALI. Overexpression of whole lung FADS1/2, combined with alpha-linolenic acid (ALA) supplementation, also significantly mitigated ALI. PARK7 is identified as an endogenous regulator of FADS1/2, acting through the BMP-BMPR-SMAD1/5/9 signaling. Driven by histone H3K14 lactylation, which is also promoted by the downregulation of FADS1/2, PARK7 upregulation restored FADS1/2 expression and counteracted ferroptosis, thereby forming a protective feedback loop. This study elucidates a novel regulatory axis involving the two major metabolic changes-downregulation of PUFA synthesis and upregulation of histone lactylation-in ALI pathogenesis, which are interconnected through the PARK7-BMP signaling pathway. Targeting this axis offers potential therapeutic strategies for mitigating endothelial dysfunction and ferroptosis in ARDS/ALI. Show less
📄 PDF DOI: 10.1002/advs.202508725
FADS1
Kaiming Wang, Caihong Liu, Lei Yi +9 more · 2025 · BMC genomics · BioMed Central · added 2026-04-24
Skeletal muscle is the largest tissue in mammals, and it plays a crucial role in metabolism and homeostasis. Skeletal muscle development and regeneration consist of a series of carefully regulated cha Show more
Skeletal muscle is the largest tissue in mammals, and it plays a crucial role in metabolism and homeostasis. Skeletal muscle development and regeneration consist of a series of carefully regulated changes in gene expression. Leiomodin2 (LMOD2) gene is specifically expressed in the heart and skeletal muscle. But the physiological functions and mechanisms of LMOD2 on skeletal muscle development are unknown. In this study, we examined the expression levels of the LMOD2 in porcine tissues and C2C12 cells. LMOD2 is mainly expressed in the heart, followed by skeletal muscle. The expression level of LMOD2 gradually decreased with skeletal muscle growth, but increased after injury. LMOD2 expression levels increased gradually with C2C12 cells proliferation and differentiation. In terms of function, the muscle fiber types were altered after LMOD2 was knocked out in C2C12 cells, MyHC-I and MyHC-2b were inhibited, whereas MyHC-2a and MyHC-2x were promoted. LMOD2 knockout has different effects on LMOD family, LMOD1 expression level was promoted, while LMOD3 was inhibited. Loss of LMOD2 suppressed cell viability and PAX7 protein expression. At the transcriptome level, proliferation-related genes and muscle contraction-related genes were respectively inhibited after LMOD2 knockout. In terms of molecular networks, a series of experiments have shown that MyoG is a transcription factor for LMOD2, while miR-335-3p can negatively regulate LMOD2 expression. We screened ACTC1 as a candidate interacting protein for LMOD2 using protein prediction software and RNA-seq, and Co-IP experiments confirmed the relationship between LMOD2 and ACTC1. In vivo, Lentivirus-mediated LMOD2 knockdown reduces muscle mass. LMOD2 knockdown inhibited MyHC-I mRNA expression, but had no effect on MyHC-2b. The protein expression of MyHC-I, MyHC-2x, and MyHC-2b was suppressed after LMOD2 knockdown. Collectively, our data indicates that LMOD2 knockout inhibits myoblast proliferation and alters muscle fiber types. MyoG is a transcription factor for LMOD2, while miR-335-3p can negatively regulate LMOD2 expression. Moreover, LMOD2 and ACTC1 interact to regulate myogenic differentiation. Our study provides a new target for skeletal muscle development. Show less
📄 PDF DOI: 10.1186/s12864-025-11897-z
LMOD1
Haoyu Deng, Wan Yi Liang, Leqi Chen +6 more · 2025 · Journal of lipid research · Elsevier · added 2026-04-24
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death fro Show more
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death from sepsis, and increasing levels of HDL by inhibition of cholesteryl ester transfer protein (CETP) has been shown to decrease mortality in mouse models of sepsis. The objective of this study was to investigate the cellular mechanisms by which CETP inhibition and HDL lead to improved survival during sepsis. We found that HDL inhibits lipopolysaccharide (LPS)-induced activation of IL-1β in a mouse model of sepsis. The activation of IL-1β was dependent on the activity of scavenger receptor class B type 1 (SR-B1), and knockdown of SR-B1 significantly attenuated LPS-induced production of IL-1β in macrophages. Additionally, we found that LPS-induced SR-B1 internalization occurs through the endosome-lysosome pathway, which is also likely responsible for LPS degradation in the macrophages. Furthermore, we revealed that raising HDL by CETP inhibition markedly enhanced HDL-mediated anti-inflammatory effects in response to LPS stimulation, and these effects were not due to CETP itself but rather were HDL-dependent. Finally, we show that pharmacological inhibition of CETP significantly improved endotoxemia-induced mortality by inhibiting IL-1β production in the liver and circulation after LPS injection. Pathologically, CETP inhibition attenuated LPS-induced diffuse alveolar damage and hepatocyte necrosis, which may contribute to the improved mortality in mice treated with the CETP inhibitor anacetrapib. Taken together, our findings uncover a cellular mechanism by which HDL attenuates LPS-induced pro-inflammatory response via SR-B1-mediated LPS degradation. Show less
📄 PDF DOI: 10.1016/j.jlr.2025.100858
CETP
Ziming Chen, Weiqiang Guo, Yahan Gao +6 more · 2025 · Anti-cancer agents in medicinal chemistry · Bentham Science · added 2026-04-24
Ursolic acid (UA) exhibits antitumor activity; however, its effects and mechanisms on triple-negative breast cancer (TNBC) cells are not well understood. The present study aimed to explore the anti- T Show more
Ursolic acid (UA) exhibits antitumor activity; however, its effects and mechanisms on triple-negative breast cancer (TNBC) cells are not well understood. The present study aimed to explore the anti- TNBC mechanisms of UA by network pharmacology and experimental validation. TNBC cell lines MDA-MB-231 and BT-549 cells were treated with UA. A CCK-8 assay was performed to detect cell growth, while flow cytometry assessed cell cycle arrest and apoptosis. The underlying mechanism and potential targets of UA for TNBC treatment were investigated by network pharmacology, including PharmMapper database, GO, KEGG enrichment, and PPI analysis. The protein expressions and phosphorylation levels of FGFR1, AKT, and ERK were measured by western blot. Pull-down assay, cellular thermal shift assay (CETSA), and molecular docking were used to analyze the interaction between UA and FGFR1. Xenograft models were established to examine the effect of UA on TNBC tumor growth. UA effectively reduced cell viability, induced apoptosis, and arrested cell cycle in TNBC cells. Moreover, UA significantly regulated the expression of Bcl-2 and Bax to induce apoptosis. The results of network pharmacology and western blot suggested that UA reduced FGFR1/AKT/ERK pathway. Furthermore, pull-down, CETSA, and molecular docking results revealed that UA directly bound to FGFR1. In the xenograft model, UA inhibited the growth by suppressing FGFR1. In this study, we employed network pharmacology and experimental approaches to elucidate the mechanism of UA on TNBC. The results demonstrated that UA targeted FGFR1 to inhibit TNBC via mediating FGFR1/AKT/ERK pathway. Our findings demonstrate that UA inhibits the FGFR1/AKT/ERK pathway by directly targeting FGFR1, thereby suppressing TNBC progression and supporting its potential as a therapeutic agent for TNBC treatment. Show less
no PDF DOI: 10.2174/0118715206379579250722053647
FGFR1
Yi Wen, Hongxia Li, Sydney Smith +9 more · 2025 · Journal of clinical lipidology · Elsevier · added 2026-04-24
Cholesteryl ester transfer protein (CETP) mediates the exchange of triglycerides (TG) from apolipoprotein B (ApoB)-containing lipoproteins to high-density lipoproteins (HDL) and the reciprocal exchang Show more
Cholesteryl ester transfer protein (CETP) mediates the exchange of triglycerides (TG) from apolipoprotein B (ApoB)-containing lipoproteins to high-density lipoproteins (HDL) and the reciprocal exchange of cholesterol (C) from HDL to ApoB-containing lipoproteins. CETP inhibition increases HDL-C and decreases low-density lipoprotein cholesterol (LDL-C) while modestly decreasing TG. Considering that CETP inhibitors block removal of TG from TG-rich lipoproteins (TRL), it is interesting that CETP inhibition decreases TG concentrations. TG levels are largely regulated by lipoprotein lipase (LPL), the enzyme primarily responsible for hydrolyzing TG. The angiopoietin-like 3/8 complex (ANGPTL3/8) is the most potent circulating LPL inhibitor, while the TG-lowering apolipoprotein A5 (ApoA5) acts by suppressing ANGPTL3/8-mediated LPL inhibition. To better understand CETP biology, we studied the effects of CETP overexpression and CETP inhibition on the levels of ANGPTL3/8 and ApoA5 in circulation using dedicated immunoassays. CETP-overexpressing transgenic mice had increased TG and normal ANGPTL3/8 levels but manifested dramatically reduced ApoA5 concentrations. Administration of the CETP inhibitor evacetrapib had no effect on ANGPTL3/8 levels in CETP-overexpressing mice or in humans. However, evacetrapib administration increased ApoA5 concentrations in both species. In human subjects, evacetrapib treatment increased circulating ApoA5 levels in the late-stage ACCELERATE and ACCENTUATE studies by 160.1% and 204.7%, respectively. Our results uncover a previously unrecognized link between CETP and ApoA5 by showing that CETP overexpression reduces ApoA5 levels while CETP inhibition increases ApoA5 concentrations. Show less
no PDF DOI: 10.1016/j.jacl.2025.06.008
APOA5
Youjia Qiu, Bingyi Song, Ziqian Yin +7 more · 2025 · European stroke journal · SAGE Publications · added 2026-04-24
Different serum lipid and lipid-lowering agents are reported to be related to the occurrence of intracerebral aneurysm (IA). However, the causal relationship between them requires further investigatio Show more
Different serum lipid and lipid-lowering agents are reported to be related to the occurrence of intracerebral aneurysm (IA). However, the causal relationship between them requires further investigation. Mendelian randomization (MR) analysis was performed on IA and its subtypes by using instrumental variants associated with six serum lipids, 249 lipid metabolic traits, and 10 lipid-lowering agents that were extracted from the largest genome-wide association study. Phenome-wide MR analyses were conducted to identify potential phenotypes associated with significant lipid-lowering agents. After multiple comparison adjustments ( This study not only supports that serum lipids (TG and HDL-C) are associated with IA but also confirms the positive effect and absence of safety concerns of intervening Show less
no PDF DOI: 10.1177/23969873241265019
CETP
Qinfei Zhao, Weiquan Hu, Yu Xia +7 more · 2025 · Scientific reports · Nature · added 2026-04-24
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tool Show more
Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality rates. The development of reliable prognostic tools is critical for advancing personalized treatment strategies. However, identifying robust gene signatures to predict osteosarcoma outcomes remains a significant challenge. In this study, we analyzed gene expression data from 138 osteosarcoma samples across two multicenter cohorts and identified 14 consensus prognosis-associated genes via univariate Cox regression analysis. Using 66 combinations of 10 machine learning (ML) algorithms, we developed a machine learning-derived prognostic signature (MLDPS) optimized by the average C-index across TARGET, GSE21257, and merged cohorts. The MLDPS effectively stratified osteosarcoma patients into high- and low-risk score groups, achieving strong predictive performance for 1-, 3-, and 5-year overall survival (AUC range: 0.852 - 0.963). The MLDPS, comprising seven genes (CTNNBIP1, CORT, DLX2, TERT, BBS4, SLC7A1, NKX2-3), exhibited superior predictive accuracy compared to 10 established gene signatures. The findings of the MLDPS carry significant clinical implications for osteosarcoma treatment. Patients with a high-risk score demonstrated worse prognosis, increased metastasis risk, reduced immune infiltrations, and greater sensitivity to immunotherapy. Conversely, low-risk patients exhibited prolonged survival and distinct drug sensitivities. These findings underscore the potential of MLDPS to guide risk stratification, inform personalized therapeutic strategies, and improve clinical management in osteosarcoma. Show less
📄 PDF DOI: 10.1038/s41598-025-00179-z
BBS4
Boyang Zeng, Cong Ma, Shuaishuai Zhang +18 more · 2025 · Lipids in health and disease · BioMed Central · added 2026-04-24
Current evidence suggests that apolipoprotein E (APOE) is associated with lipid metabolism, cardiovascular diseases, and neurodegenerative disorders. However, the physiological pathways of APOE-mediat Show more
Current evidence suggests that apolipoprotein E (APOE) is associated with lipid metabolism, cardiovascular diseases, and neurodegenerative disorders. However, the physiological pathways of APOE-mediated inflammation remain incompletely elucidated, and a specific inflammatory marker that captures the pro-inflammatory activity of the APOE ε4 allele remains elusive. As a composite peripheral blood biomarker, Systemic immune-inflammation index (SII) is a novel marker of inflammation. This study aimed to investigate the association between APOE alleles and Systemic Immune-Inflammation Index. A total of 13,926 participants (9,098 males and 4,828 females) were recruited from The People’s Liberation Army General Hospital (November 2017 to July 2019). APOE alleles (ε2, ε3, and ε4) were determined by genotyping rs429358 and rs7412 SNPs. SII was calculated as (platelet count × neutrophil count)/lymphocyte count. Multivariable linear regression models (adjusted for demographics, lifestyle, and clinical covariates) and subgroup analyses were performed to assess the APOE-SII associations, with ε3 as the reference. The frequencies of APOE alleles ɛ3, ɛ2, and ɛ4 were70.7%, 13.8%, and 15.5% respectively in 13,926 Chinese patients. The mean SII was lower in ɛ2 carriers than in ɛ3 (373.74*10⁹/L vs. 403.53*10⁹/L, APOE contributes to elevated disease risk by inducing a state of chronic low-grade inflammation, resulting from modulation of both adaptive and innate immune responses. Show less
📄 PDF DOI: 10.1186/s12944-025-02842-w
APOE
Ya-Ting Chen, Jing Sui, Yu Yang +16 more · 2025 · BMC medicine · BioMed Central · added 2026-04-24
Pentadecanoic acid (PEA), an odd-chain fatty acid derived from diet by the gut microbiome, has garnered increasing attention for its systemic health-promoting properties. Its potential role in bladder Show more
Pentadecanoic acid (PEA), an odd-chain fatty acid derived from diet by the gut microbiome, has garnered increasing attention for its systemic health-promoting properties. Its potential role in bladder cancer (BC) occurrence and invasion, however, remains unclear. Large-scale cohorts' analyses were performed to assess the association between dietary PEA and BC occurrence and invasion. In vitro and in vivo experiments, including EJ and T24 BC cell assays and a BBN-induced mouse model, were conducted to experimentally assess the impact of PEA on BC. Serum proteomics, gut microbiome, and targeted fecal lipidomics analyses were employed to explore the underlying mechanisms. Dietary PEA was negatively associated with BC occurrence and invasion in cohort analyses. PEA suppressed EJ and T24 BC cell migration, invasion, and proliferation, while inhibiting BC development in a BBN-induced mouse model. In vivo serum proteomics identified differentially expressed lipid-related proteins (e.g., Apoe and Apob) following PEA treatment, implicating its modulation of lipid metabolism pathways. Considering the essential role of the gut-bladder axis, the gut microbiome analysis exhibited that PEA markedly altered bacteria (e.g., g_Alistipes) and fungi (e.g., o_Erysiphales, g_Teberdinia, and g_Gibberella), with concomitant lipid metabolism changes. Furthermore, targeted fecal lipidomics demonstrated the shifts in key lipids, such as phosphatidylethanolamines (PE) involved in essential lipid clusters, suggesting regulation by gut microbiome linked to BC development. Collectively, our findings demonstrate that PEA mitigates BC by reshaping the gut microbiome and modulating lipid metabolism, providing new insights into its molecular and therapeutic potential. Show less
📄 PDF DOI: 10.1186/s12916-025-04554-5
APOB
Pu Jiang, Liangyu Liu, Lixian Chen +2 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18091280
APOB
Yifei Lu, Tian Xia, Yongjia Jin +8 more · 2025 · Pediatric surgery international · Springer · added 2026-04-24
Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma. FOXO1 fusion indicates poor prognosis and lead to dysregulation of transcriptioanal network. This study aims to investigate cli Show more
Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma. FOXO1 fusion indicates poor prognosis and lead to dysregulation of transcriptioanal network. This study aims to investigate clinical characteristics and therapeutic targets concerning FOXO1 fusion status. 65 pediatric RMS patients were enrolled. Clinical data were analyzed using Kaplan-Meier estimates and Cox regression. Surgically resected tumor tissues were subject to single-cell RNA sequencing (scRNA-seq). Patient-derived xenograft (PDX) was establish and dissociated to cells for high-throughput drug screening. Among the 65 patinets (36 patients with embryonal RMSs (ERMSs), 15 patients with alveolar RMSs (ARMSs) and 14 patients with other types of RMSs), 73.3% of ARMSs were defined as fusion positive (FP) while 6 ERMS (ERMS)s were also FP. Cox regression analysis identified FOXO1 fusion as a risk factor alone and combined with pathologic subtype, sex and age or metastasis status. scRNA-seq revealed distinct transcription factor networks between FP and FN RMS, showing up-regulated activity of OLIG2, NHLH1, SNAI1, TFF3 and other TFs related to neural development and differentiation. MAPK, PI3K-Akt, and mTOR pathways were enriched in FP-RMS tumor cells. High-throughput drug screening of PDX-derived cells identified sensitive drugs targeting FP-RMS specific signatures. AMG-337 was selected and validated for its anti-tumor effect. FOXO1 fusion status influences RMS clinical outcomes, including rare FP-ERMS cases. scRNA-seq combined with drug screening identified MET as a promising therapeutic target in FP-RMS. Show less
no PDF DOI: 10.1007/s00383-025-06241-1
SNAI1
Xinxin Xiong, Danyang Wang, Liping Xu +7 more · 2025 · Journal for immunotherapy of cancer · added 2026-04-24
The highly organized structures of the immunological synapse (IS) are crucial for T cell activation. PDZ domains might be involved in the formation of the IS by serving as docking sites for protein in Show more
The highly organized structures of the immunological synapse (IS) are crucial for T cell activation. PDZ domains might be involved in the formation of the IS by serving as docking sites for protein interactions. In this study, we investigate the role of the PALS1-associated tight junction protein (PATJ), which contains 10 PDZ domains, in the formation of IS and its subsequent impact on T cell activation. To elucidate the function of PATJ, we generated murine models with conditional T cell-specific knockout of We observed a rapid increase in PATJ expression during T cell activation. Conditional knockout of Our study reveals an important role of PATJ in the formation of IS and provides an approach to improve the efficacy of CAR-T therapy. Show less
no PDF DOI: 10.1136/jitc-2024-010966
PATJ
Chaoping Chen, Chenhao Li, Qingru Zhu +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metaboli Show more
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metabolic status in prediabetes, but their predictive value for cardiovascular mortality and stroke in this population remains unclear. We analyzed data from 74,678 White participants with prediabetes in the UK Biobank, defined by either HbA1c (5.7-6.4%) or fasting glucose (6.1-6.9 mmol/L). Follow-up continued until October 10, 2023. Cox regression was used to examine associations between LE8, phenotypic age (PhenoAge), cardiovascular biological age (CBA), and outcomes of cardiovascular (CVD) mortality and stroke. Restricted cubic spline (RCS) models identified biological age risk thresholds. Mediation analysis assessed whether proteins such as CST3, EFEMP1, FES, IGFBP2, IGFBP6, LPA, PCSK9, and TIMP1 mediated these effects. Over a median follow-up of 13.4 years, 2263 participants died from CVD causes. Each 1-year increase in CBA or PhenoAge was associated with a ~ 10% higher risk of CVD mortality (CBA aHR = 1.10; PhenoAge aHR = 1.09; both P < 0.001), while each 1-point increase in LE8 score was linked to a 3% lower risk (HR = 0.97, P < 0.001). The risk biological ages for these two indicators were also identified: PhenoAge ≥ 58.52 years and CBA ≥ 62.42 years. Similar trends were observed for stroke. Mediation analysis revealed that CST3, TIMP1, IGFBP2, and IGFBP6 contributed to the biological pathways between aging/lifestyle and CVD outcomes. The combined LE8 and PhenoAge model showed the strongest predictive performance for CVD mortality (AUC = 0.716) and stroke (AUC = 0.638) over 15 years. LE8 combined with phenotypic age provides prognostic value for CVD outcomes in prediabetes. These findings highlight the potential of lifestyle modification and delayed biological aging in reversing prediabetes and underscore comorbidity-related proteins as promising therapeutic targets. Show less
📄 PDF DOI: 10.1186/s40001-025-03218-7
LPA
Zijian Wang, Radek Zenkl, Latifa Greche +33 more · 2025 · Plant phenomics (Washington, D.C.) · Elsevier · added 2026-04-24
Computer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimeter ground sampling distance enable the detection an Show more
Computer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimeter ground sampling distance enable the detection and tracking of plant features, including size, shape, and colour. Although today's AI-driven foundation models segment almost any object in an image, they still fail for complex plant canopies. To improve model performance, the global wheat dataset consortium assembled a diverse set of images from experiments around the globe. After the head detection dataset (GWHD), the new dataset targets a full semantic segmentation (GWFSS) of organs (leaves, stems and spikes) covering all developmental stages. Images were collected by 11 institutions using a wide range of imaging setups. Two datasets are provided: i) a set of 1096 diverse images in which all organs were labelled at the pixel level, and (ii) a dataset of 52,078 images without annotations available for additional training. The labelled set was used to train segmentation models based on DeepLabV3Plus and Segformer. Our Segformer model performed slightly better than DeepLabV3Plus with a mIOU for leaves and spikes of ca. 90 ​%. However, the precision for stems with 54 ​% was rather lower. The major advantages over published models are: i) the exclusion of weeds from the wheat canopy, ii) the detection of all wheat features including necrotic and senescent tissues and its separation from crop residues. This facilitates further development in classifying healthy vs. unhealthy tissue to address the increasing need for accurate quantification of senescence and diseases in wheat canopies. Show less
📄 PDF DOI: 10.1016/j.plaphe.2025.100084
LPA
Bing-Huei Chen, Chen-Te Jen, Chia-Chuan Wang +1 more · 2025 · Pharmaceutics · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/pharmaceutics17091200
BACE1
Haixiong Tang, Lin Fu, Changyun Yang +9 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Cadherin-11 (CDH11), a specialized cell-cell adhesion protein, plays an essential role in tissue injury, inflammation and repair. This study aimed to investigate the role of CDH11 in severe asthma. Br Show more
Cadherin-11 (CDH11), a specialized cell-cell adhesion protein, plays an essential role in tissue injury, inflammation and repair. This study aimed to investigate the role of CDH11 in severe asthma. Bronchial biopsy specimens were obtained from healthy subjects and patients with severe asthma. Two murine models of severe asthma were established using either TDI (toluene diisocyanate) or OVA (ovalbumin)/CFA (complete Freund's adjuvants). A selective CDH11 antagonist SD133 (100 mg/kg) was given to allergen-exposed mice after airway challenge. The effects of recombinant CDH11 were also tested in vivo, and FGFR1 inhibition was used to explore a possible mechanism for CDH11-induced inflammatory responses in the lung. We detected upregulated expression of CDH11 in the airway mucosa of severe asthma patients when compared with the healthy control. In the OVA/CFA-induced model, though CDH11 expression in the lung remained unchanged, pharmacological antagonism of CDH11 with SD133 dramatically decreased airway neutrophil accumulation, as well as IL-6 production, but had no effect on eosinophilic infiltration, type 2 inflammation (IL-4 and IL-5) nor airway hyperresponsiveness. In the TDI model, pulmonary CDH11 expression was upregulated. Treatment with SD133 inhibited TDI-induced airway hyperresponsiveness and neutrophilic inflammation, decreased IL-6 and TNF-α production, with no effect on airway eosinophil counts and type 2 inflammatory cytokines. In addition, intratracheal instillation of recombinant CDH11 led to neutrophil recruitment in the lungs of mice, which could be attenuated by inhibition of FGFR1 signaling. CDH11 contributes to airway neutrophilic inflammation in severe asthma through the FGFR1 pathway. Show less
no PDF DOI: 10.1096/fj.202501899RR
FGFR1
Haoran Guo, Junjie Chen · 2025 · Discover oncology · Springer · added 2026-04-24
Growth Factor Receptor-Binding Protein 10 (GRB10) is an adaptor protein implicated in tyrosine kinase signaling, yet its pan-cancer role and clinical impact remain incompletely characterized. This stu Show more
Growth Factor Receptor-Binding Protein 10 (GRB10) is an adaptor protein implicated in tyrosine kinase signaling, yet its pan-cancer role and clinical impact remain incompletely characterized. This study aims to define the pan-cancer landscape of GRB10 dysregulation and its clinical implications for prognosis and immunotherapy response. Multi-omics analysis of 33 TCGA cancers and validation in GEO cohorts assessed GRB10 expression, prognostic impact (Cox regression, Kaplan-Meier), functional enrichment (Gene Set Enrichment Analysis, Gene Set Variation Analysis), immune correlates (Spearman with immune genes, ESTIMATE/CIBERSORT/EPIC/TIMER/xCell infiltration), tumor mutational burden (TMB), and immunotherapy predictive power. In the TCGA pan-cancer cohort, GRB10 was significantly elevated in 11 cancer types (CHOL, COAD, ESCA, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC, STAD, THCA) and downregulated in 4 (BLCA, BRCA, CESC, UCEC). Aberrant GRB10 expression was strongly associated with adverse prognosis in LGG, CESC, COAD, and LUAD for OS, DSS, and PFI, a finding validated externally in GEO colon cancer cohorts. Conversely, it served as a protective factor in KIRC. Functionally, GRB10 was implicated in epithelial-mesenchymal transition (EMT), evidenced by positive correlations with EMT pathway scores and key regulators (ZEB1, ZEB2, SNAI1, SNAI2). GRB10 expression robustly correlated with an immunosuppressive tumor microenvironment (TME), evidenced by negative enrichment of immune response pathways (e.g., IFN-α/γ) and complex associations with immune-related genes. Immune infiltration analysis revealed consistent positive correlations with CD4⁺ memory-resting T cells and negative correlations with CD4⁺ effector memory T cells across most cancers. Critically, high GRB10 expression predicted significantly shorter survival and poorer response rates in multiple immunotherapy-treated cohorts (urothelial carcinoma, melanoma, gastric cancer). GRB10 also showed significant associations with TMB in several cancers, and its protein interaction network was enriched in PI3K-Akt, FoxO, and Rap1 signaling pathways. Our pan-cancer analysis establishes GRB10 as a key facilitator of tumor progression, linked to EMT and an immunosuppressive microenvironment, and nominates it as a novel biomarker for adverse prognosis and resistance to immune checkpoint blockade therapy. The online version contains supplementary material available at 10.1007/s12672-025-04333-x. Show less
no PDF DOI: 10.1007/s12672-025-04333-x
SNAI1
Juan Chen, Jing Feng, Yuping Zhu +2 more · 2025 · RNA biology · Taylor & Francis · added 2026-04-24
Accumulation of various genetics and epigenetics alterations are accepted to result in the initiation and progression of hepatocellular carcinoma (HCC), and its high metastasis is viewed as a critical Show more
Accumulation of various genetics and epigenetics alterations are accepted to result in the initiation and progression of hepatocellular carcinoma (HCC), and its high metastasis is viewed as a critical bottleneck leading to its treatment failure. Amongst them, the microRNAs arising from the lack of the antioxidant transcription factor Nrf2 lead to cancer metastasis. However, much less is known about the regulation of microRNAs by Nrf1, even though it acts as an essential determinon of cell homoeostasis by governing the transcriptional expression of those driver genes contributing to the EMT involved in its metastasis. In this study, distinct EMT phenotypes resulted from specific knockouts of Nrf1 and Nrf2 in HepG2 cells, as accompanied by their differential migratory and invasive capabilities. The Show less
no PDF DOI: 10.1080/15476286.2025.2548628
SNAI1
Yan Chen, Yan Zhu, Zihu Tan +7 more · 2025 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive cognitive decline and behavioral impairments in the elderly. Microglia, the resident immune cells of the Show more
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive cognitive decline and behavioral impairments in the elderly. Microglia, the resident immune cells of the central nervous system, play a crucial role in modulating the pathological processes associated with AD. Jiajian Shuyu Pills (JJSYP) are frequently employed in the treatment of AD, purportedly by enhancing the physiological functions of human tissues and organs to modulate the immune response. Nevertheless, the underlying mechanisms by which JJSYP exert their therapeutic effects in the context of AD remain inadequately elucidated. This study aimed to assess the effects of JJSYP on cognitive enhancement and the alleviation of neuroinflammation in the treatment of AD, as well as to explore the underlying mechanisms using mouse models. The components of JJSYP in serum were analyzed using HPLC-Q/TOF-MS. APP/PS1 transgenic mice served as AD models in this investigation. Cognitive function in the AD mice was assessed through the Mirror Water Maze Test and the Novel Object Recognition Test. The quantification of apoptotic hippocampal cells was conducted using Nissl staining and TUNEL staining. Immunofluorescence (IF) and Western blot (WB) analyses were employed to examine microglial activation and the expression of relevant proteins. Transcriptomic sequencing analysis and network pharmacology were administrated to explore the potential mechanisms of JJSYP in AD treatment. Inflammatory cytokine levels in the brain were measured using RT-PCR. A total of 74 absorbed prototype components from JJSYP were identified. JJSYP effectively improved cognitive function and neuroapoptosis in AD model mice by modulating the activation of microglia. The JJSYP intervention alleviated neuroinflammation by suppressing microglial activation and reducing the accumulation of amyloid β-protein. Through transcriptome sequencing and WB verification, 34 differentially expressed genes (DEGs) were identified, including ACKR3, NR1H3 and Adra1a. Following treatment with a high dose of JJSYP, both ACKR3 and NR1H3 showed a significant decrease compared to the model group. Conversely, ADRA1A expression was reduced in model group compared to the control group, but increased following high dose JJSYP treatment. Research involving RNA sequencing and network pharmacology indicated that JJSYP altered the activation of CXCL12/ACKR3 signaling pathways in the hippocampus. JJSYP exhibits potential anti-Alzheimer's Disease effects and warrants further investigation and development as a prosper treatment for AD. Show less
no PDF DOI: 10.1016/j.jep.2025.119508
NR1H3