👤 Xingyi 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, 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, 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, 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
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
Qianqian Wang, Peize Chen, Xiaorong Wang +9 more · 2025 · Non-coding RNA research · Elsevier · added 2026-04-24
[This corrects the article DOI: 10.1016/j.ncrna.2022.12.004.].
no PDF DOI: 10.1016/j.ncrna.2025.02.002
DHX36
Lishan Zeng, Xin Chen, Kai Kang +12 more · 2025 · Cardiovascular research · Oxford University Press · added 2026-04-24
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. Thi Show more
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. This study aimed to explore the role and potential mechanisms of liver X receptor α (LXRα) in CAVD, which offers a promising approach for treating CAVD. Osteogenic stimulation was performed following which a substantial downregulation of LXRα was observed in human calcific aortic valves and valvular interstitial cells. Further functional investigations revealed that silencing LXRα exacerbated calcification both in vitro and in vivo. We showed that LXRα suppressed the protein kinase R-like endoplasmic reticulum kinase/eukaryotic initiation factor 2/activating transcription factor 4 pathway, which controls endoplasmic reticulum stress (ERS) and promotes osteogenic differentiation, thereby slowing the course of CAVD. Our research offers fresh perspectives on how LXRα controls the pathophysiology of CAVD via regulating ERS. The findings suggest that targeting LXRα is a potential treatment strategy for treating aortic valve calcification. Show less
no PDF DOI: 10.1093/cvr/cvaf044
NR1H3
Hongyu Kuang, Dan Li, Yunlin Chen +7 more · 2025 · Atherosclerosis · Elsevier · added 2026-04-24
Pathological cardiac hypertrophy is an independent risk factor for heart failure (HF). Early identification and timely treatment are crucial for significantly delaying the progression of HF. Targeted Show more
Pathological cardiac hypertrophy is an independent risk factor for heart failure (HF). Early identification and timely treatment are crucial for significantly delaying the progression of HF. Targeted amino acid metabolomics and RNA sequencing (RNA-seq) were combined to explore the underlying mechanism. In vitro, H9c2 cells were stimulated with angiotensin II (Ang II) or were incubated with extra valine after Ang II stimulation. The branched chain alpha-ketoate dehydrogenase kinase (Bckdk) inhibitor 3,6-dichlorobenzo[b]thiophene-2-carboxylic acid (BT2) and rapamycin were utilized to confirm the role of the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway in this process. A significant accumulation of valine was detected within hypertrophic hearts from spontaneously hypertensive rats (SHR). When branched chain amino acid (BCAA) degradation was increased by BT2, the most pronounced decrease was observed in the valine level (Δ = 0.185 μmol/g, p < 0.001), and cardiac hypertrophy was ameliorated. The role of imbalanced mitochondrial quality control (MQC), including the suppression of mitophagy and excessive mitochondrial fission, was revealed in myocardial hypertrophy. In vitro, high concentrations of valine exacerbated cardiomyocyte hypertrophy stimulated by Any II, resulting in the accumulation of impaired mitochondria and respiratory chain dysfunction. BT2, rapamycin, and mitochondrial division inhibitor 1 (Mdivi-1) all ameliorated MQC imbalance, mitochondrial damage and oxidative stress in hypertensive models with high valine concentration. Valine exacerbated pathological cardiac hypertrophy by causing a MQC imbalance, probably as an early biomarker for cardiac hypertrophy under chronic hypertension. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.119216
BCKDK
Ashley E Ciecko, Rabia Nabi, Amber Drewek +8 more · 2025 · iScience · Elsevier · added 2026-04-24
In the non-obese diabetic (NOD) mouse model of autoimmune diabetes, interleukin (IL)-27 stimulates interferon γ (IFNγ) production by CD4 and CD8 T cells and is essential for disease development. Here, Show more
In the non-obese diabetic (NOD) mouse model of autoimmune diabetes, interleukin (IL)-27 stimulates interferon γ (IFNγ) production by CD4 and CD8 T cells and is essential for disease development. Here, we tested the role of IL-27 in cellular communication. Single-cell RNA sequencing and T cell adoptive transfer showed that IL-27 intrinsically controlled the differentiation of islet-infiltrating CD4 T cells by driving them toward an IL-21 Show less
📄 PDF DOI: 10.1016/j.isci.2025.113537
IL27
Zhengliang Li, Xiaokai Chen, Linlin Ren +4 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clin Show more
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clinical practice. To develop machine learning (ML) models for classifying prevalent atherosclerotic cardiovascular disease (ASCVD) risk in MASLD patients, and to enhance model interpretability using SHapley Additive exPlanations (SHAP). Methods: This retrospective study included 590 MASLD patients diagnosed at the Affiliated Hospital of Qingdao University between December 2019 and December 2024. Patients were randomly divided into a training set (n=413) and a validation set (n=177), and further stratified based on ASCVD status. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. Six ML models were developed and evaluated using sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and F1 score. SHAP analysis was performed to interpret feature contributions. ASCVD was present in 434 of 590 patients (73.6%). The Gradient Boosting (GB) model achieved the best performance, with AUCs of 0.918 (95% CI: 0.890-0.944) in the training set and 0.817 (95% CI: 0.739-0.883) in the validation set. SHAP analysis identified the top predictors as the Cholesterol-HDL-Glucose (CHG) index, Castelli Risk Index II (CRI-II), lipoprotein(a) [Lp(a)], serum creatinine (Scr), and uric acid (UA). The GB model demonstrated strong high accuracy in identifying existing ASCVD in MASLD patients and may serve as a useful tool for early risk stratification in clinical settings. Show less
📄 PDF DOI: 10.3389/fendo.2025.1684558
LPA
Mei-Jun Lyu, Dong-Yu Min, Lian-Qun Jia +2 more · 2025 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
To explore the mechanism of astragaloside Ⅳ in regulating energy metabolic reprogramming, alleviating endothelial-to-mesenchymal transition(EndMT), and preventing atherosclerosis(AS) in ApoE~(-/-) AS Show more
To explore the mechanism of astragaloside Ⅳ in regulating energy metabolic reprogramming, alleviating endothelial-to-mesenchymal transition(EndMT), and preventing atherosclerosis(AS) in ApoE~(-/-) AS mice, ApoE~(-/-) AS mouse models were established by high-fat feeding and randomly divided into three groups: model group, astragaloside Ⅳ group, and blank control group. The mice in the astragaloside Ⅳ group were administered astragaloside Ⅳ via gavage at a dose of 40 mg·kg~(-1)·d~(-1), while mice in the blank control group and model group received an equal volume of normal saline via gavage for four consecutive weeks. The blood lipid levels of mice in each group were measured using an automatic biochemical analyzer. Hematoxylin-eosin(HE) staining was used to observe the pathomorphological changes in the mouse aorta. The degree of EndMT was detected by immunofluorescence, and the protein expression levels of α-smooth muscle actin(α-SMA) and vascular endothelial cadherin(VE-cadherin) in the aorta were detected by Western blot. Targeted energy metabolomics technology was used to qualitatively and quantitatively analyze the spectrum of serum energy metabolites in mice, followed by KEGG pathway enrichment analysis of differential metabolites. The expression of glycolysis-related genes was detected using RT-PCR. The results showed that astragaloside Ⅳ significantly reduced the levels of serum total cholesterol(TC), triglyceride(TG), and low-density lipoprotein cholesterol(LDL-C) while increasing high-density lipoprotein cholesterol(HDL-C) levels. It reduced atherosclerotic plaque formation, decreased the number of α-SMA and VE-cadherin double staining positive cells, downregulated the protein expression of mesenchymal cell surface antigen α-SMA, and upregulated the protein expression of endothelial cell surface antigen VE-cadherin. Targeted energy metabolomics analysis shows that astragaloside Ⅳ restored nine altered energy metabolites in the serum. The pathway enrichment analysis indicated that serum differential metabolites were mainly enriched in glycolytic pathways. RT-PCR detection revealed that astragaloside Ⅳ significantly downregulated the mRNA expression of key glycolytic enzymes, including hexokinase-Ⅱ(HK-Ⅱ), phosphofructokinase(PFKM), and pyruvate kinase M2(PKM2). These results suggest that astragaloside Ⅳ may ameliorate AS by inhibiting the excessive activation of glycolysis, modulating energy metabolic reprogramming, and alleviating EndMT. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20250711.501
APOE
Liqun Ling, Tianqi Hu, Chenkang Zhou +7 more · 2025 · Molecular cancer · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, demonstrates critical regulatory involvement of RNA-binding proteins (RBPs) and circular RNAs (circRNAs) Show more
Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, demonstrates critical regulatory involvement of RNA-binding proteins (RBPs) and circular RNAs (circRNAs) in tumorigenic processes. Emerging evidence highlights the circRNA-autophagy regulatory axis as a crucial modulator of cancer progression. This study systematically investigates the functional interplay within the RBP-circRNA-autophagy network in LUAD pathogenesis. Employing RNA pull down, mass spectrometry and RNA immunoprecipitation facilitated the exploration of the circRAPGEF5 binding protein. M6A methylation RNA immunoprecipitation-PCR was utilized for m6A analysis. Immunofluorescence (IF) and fluorescence in situ hybridization (FISH) assays were conducted to ascertain the subcellular localization of target genes. Employing mRFP-GFP-LC3 fluorescent lentivirus labelling facilitated the monitoring of autophagy flow levels. Xenografts in mice were instrumental in affirming the role of circRAPGEF5. Through comprehensive molecular profiling, we identified elevated circRAPGEF5 expression in LUAD cells, which significantly suppressed autophagic flux while promoting malignant phenotypes including enhanced proliferation, migration, and invasion. Mechanistic investigations revealed that circRAPGEF5 directly interacts with the KH3-4 functional domain of Insulin-like Growth Factor 2 mRNA-Binding Protein 2 (IGF2BP2), an m6A reader protein. This interaction facilitated IGF2BP2-mediated stabilization of NUP160 mRNA, a nuclear pore complex component. Genetic ablation of NUP160 through RNA interference effectively restored autophagic activity, thereby attenuating the aggressive biological behaviors of LUAD cells. In vivo validation using xenograft models demonstrated that the circRAPGEF5/IGF2BP2/NUP160 signaling axis promotes tumor growth and metastatic dissemination through autophagy suppression. Our findings reveal a novel epigenetic regulatory mechanism wherein m6A-modified circRAPGEF5 orchestrates autophagy inhibition via IGF2BP2-dependent stabilization of NUP160 transcripts, ultimately driving LUAD progression and metastasis. These results establish the circRAPGEF5/IGF2BP2/NUP160 axis as a potential therapeutic target for LUAD intervention. Show less
no PDF DOI: 10.1186/s12943-025-02399-3
NUP160
Hongzheng Lu, Siqi Yang, Wei Li +3 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
Dietary interventions with food-derived natural products have emerged as a promising strategy to alleviate obesity. This study aims to investigate the anti-obesity effect of
📄 PDF DOI: 10.3390/foods14030459
LPL
Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB
Yuwei Bai, Jianglong Li, Xueqian Wu +8 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-l Show more
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-lowering effects, while Silybum marianum (L.) Gaertn, known as milk thistle, has hepatoprotective properties and exhibits antioxidant effects. To evaluate the effect of sea buckthorn and milk thistle solid beverage (H-S solid beverage) in alleviating hyperlipidemia in rats and explore the underlying mechanisms by analyzing plasma and liver metabolomics, lipidomics, and liver transcriptomics. A hyperlipidemic rat model was established after 2 weeks of high-fat diet (HFD) feeding in Sprague Dawley rats. The administered doses of H-S solid beverage were 0.30 g/kg/d, 0.15 g/kg/d and 0.075 g/kg/d. Serum biochemical parameter detection, histopathological section analysis, untargeted plasma and liver metabolomics, lipidomics, and liver transcriptomics were performed to determine the therapeutic effects of H-S solid beverage and predict the related pathways in rats with hyperlipidemia. Changes in genes and proteins related to lipid metabolism were detected using real-time quantitative polymerase chain reaction and western blotting. Eighty-nine components were identified in H-S solid beverage using ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry, with flavonoids being the major constituents. The H-S solid beverage significantly reduced body weight, liver index, body fat percentage, lipid accumulation, and liver injury in HFD-fed rats. Fatty acids (FA), bile acid, phosphatidyl ethanolamine, phosphatidylcholine, triglyceride, cholesterol ester, diglyceride and phosphatidylinositol levels were significantly altered in the liver and plasma. Moreover, the transcriptomic analysis suggested that H-S solid beverage significantly altered the hepatic gene expression of cholesterol synthesis (Pdk4, Hmgcs1, and Dhcr24), lipogenesis (Scd, Angptl4, and Angptl8), and FA β-oxidation (Cpt1α, Pparδ, Acsl, Pgc-1α, and Pla2g2d). The solid beverage of sea buckthorn and milk thistle was firstly demonstrated to ameliorate HFD-induced hyperlipidemia. The lipid-lowering and hepatoprotective effects of H-S solid beverage significantly regulated cholesterol synthesis and de novo lipogenesis, as well as FA β-oxidation. In summary, this study highlights the potential of H-S solid beverages for the treatment of hyperlipidemia. Show less
no PDF DOI: 10.1016/j.phymed.2025.156920
ANGPTL4
Fawang Du, Hanchao Wang, Zhihong Chen +7 more · 2025 · Journal of asthma and allergy · added 2026-04-24
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcript Show more
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcriptomics profile and promising biomarkers for asthma severity prediction. In discovery cohort, induced sputum cells from 3 non-severe and 3 severe asthma patients were collected and analyzed using RNA-seq. Multivariate analysis was performed to explore asthma severity-associated transcriptomics profile and differential expressed genes (DEGs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used for pathway enrichment analysis. Subsequently, based on the previous study and clinical experience, the mRNA expressions of 6 overlapped asthma severity-associated DEGs and Distinct asthma severity-associated transcriptomics profile was identified in induced sputum cells in discovery cohort. Then, 345 DEGs were found, of which 38 terms and 32 pathways were enriched using GO and KEGG, respectively. In validation cohort, the mRNA expressions of Collectively, this study provides the first identification of the association between induced sputum cells transcriptomics profile and asthma severity, indicating the potential value of transcriptomics for asthma management. The study also reveals the promising value of serum C3 for predicting asthma severity in clinical practice. Show less
no PDF DOI: 10.2147/JAA.S517140
NRXN3
Juexin Fan, Yuezhou Yao, Leli Wang +5 more · 2025 · The British journal of nutrition · added 2026-04-24
Tryptophan (Trp) is an essential amino acid acting as a key nutrition factor regulating animal growth and development. But how Trp modulates food intake in pigs is still not well known. Here, we inves Show more
Tryptophan (Trp) is an essential amino acid acting as a key nutrition factor regulating animal growth and development. But how Trp modulates food intake in pigs is still not well known. Here, we investigated the effect of dietary supplementation of Trp with different levels on food intake of growing pigs. The data showed that dietary Trp supplementation with the standardised ileal digestibility (SID) Trp to lysine (Lys) ratio at both 0·18 and 0·20 significantly increased the food intake by activating the expression of orexigenic gene agouti-related peptide (AgRP) and inhibiting the expression of anorexigenic gene pro-opiomelanocortin (POMC), cocaine- and amphetamine-regulated transcript (CART) and melanocortin receptor 4 (MC4R) in the hypothalamus. Meanwhile, the level of anorexigenic hormones appetite-regulating peptide YY (PYY) in the duodenum and serum and leptin receptor in the duodenum were also significantly decreased. Importantly, both the kynurenine and serotonin metabolic pathways were activated upon dietary Trp supplementation to downregulate MC4R expression in the hypothalamus. Further mechanistic studies revealed that the reduced MC4R expression activated the hypothalamic AMP-activated protein kinase (AMPK) pathway, which in turn inhibited the mammalian target of rapamycin (mTOR)/S6 kinase 1 (S6K1) activity to stimulate food intake. Together, our study unravels the orexigenic effect of dietary Trp supplementation in pigs and expands its potential application in developing nutrition intervention strategy in pig production. Show less
no PDF DOI: 10.1017/S0007114524003210
MC4R
Xianqi Feng, Xueting Bai, Hong Zhang +7 more · 2025 · Journal of hematopathology · Springer · added 2026-04-24
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement Show more
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement in bone marrow hematopoietic stem cells, resulting in the transformation of myeloid/lymphoid cells into neoplastic growths. The clinical and laboratory features of affected individuals are influenced by the specific partner genes. Purpose This article aims to report a case of MLN-FGFR1 involving a novel CNTRL::FGFR1 splicing variant and to discuss its clinicopathological characteristics and treatment challenges. Methods/Results We report a case of MLN-FGFR1 in a 35-year-old male patient presenting with leukocytosis, lymphadenopathy, hepatosplenomegaly, and a mixed population of B lymphoblasts, T lymphoblasts, and monoblasts in the bone marrow and lymph nodes. Comprehensive molecular profiling, including chromosomal karyotyping, fluorescence in situ hybridization (FISH), targeted transcriptome sequencing, reverse transcription polymerase chain reaction (RT-PCR), and Sanger sequencing, identified a novel splicing variant of the CNTRL::FGFR1 fusion, resulting from a t(8;9)(p11;q33) translocation. This novel splicing variant involves an in-frame fusion between exon 38 of CNTRL and exon 11 of FGFR1, retaining the kinase domain of FGFR1 and leading to its constitutive activation. Despite multiple treatment regimens, the patient failed to achieve complete remission (CR). Conclusion The findings highlight the urgent need for targeted therapies, such as FGFR inhibitors, to improve outcomes in patients with FGFR1-rearranged malignancies. Show less
📄 PDF DOI: 10.1007/s12308-025-00670-6
FGFR1
Ting Yi, Shimeng Dai, Jingrui Tao +4 more · 2025 · Journal of professional nursing : official journal of the American Association of Colleges of Nursing · Elsevier · added 2026-04-24
Undergraduate nursing students face significant academic and practical challenges, with their responses reflecting their academic resilience. However, most studies have overlooked the differences in t Show more
Undergraduate nursing students face significant academic and practical challenges, with their responses reflecting their academic resilience. However, most studies have overlooked the differences in their levels of academic resilience and the factors contributing to these differences. To identify the latent profiles of undergraduate nursing students' academic resilience and to analyze their influencing factors. A cross-sectional study was carried out among 1795 undergraduate nursing students from November 2022 to October 2023 by employing the general information questionnaire, the academic resilience questionnaire for college students, and the brief 2-way social support scale. Latent profile analysis (LPA) was used to analyze the latent profiles of academic resilience, and multiple logistic regression was utilized to explore the factors associated with the identified profiles. Four potential profiles were identified: low academic resilience group, moderate academic resilience group, high academic resilience but low focus and dissociation group, and high academic resilience group. Residence, attitude towards the nursing profession, self-directed study duration, academic performance rank, received and provided instrumental support were found to be associated with the different profiles. These findings highlight the heterogeneity in academic resilience and support tailored educational interventions based on students' specific academic resilience profiles. Show less
no PDF DOI: 10.1016/j.profnurs.2025.09.014
LPA
Xinning Dong, Jing Xu, Kejun Du +3 more · 2025 · Neuroreport · added 2026-04-24
This study aimed to examine reticulon 4 (RTN4), neurite outgrowth inhibitor protein expression that changes in high-altitude traumatic brain injury (HA-TBI) and affects on blood-brain barrier's (BBB) Show more
This study aimed to examine reticulon 4 (RTN4), neurite outgrowth inhibitor protein expression that changes in high-altitude traumatic brain injury (HA-TBI) and affects on blood-brain barrier's (BBB) function. C57BL/6J 6-8-week-old male mice were used for TBI model induction and randomized into the normal altitude group and the 5000-m high-altitude (HA) group, each group was divided into control (C) and 8h/12h/24h/48h-TBI according to different times post-TBI. Brain water content (BWC) and modified Neurological Severity Score were measured, RTN4 and autophagy-related indexes (Beclin1, LC3B, and SQSTM1/p62) were detected by western blot, immunofluorescence technique, and PCR in peri-injury cortical tissues. The expression of NgR1, Lingo-1, TROY, P75, PirB, S1PR2, and RhoA receptors' downstream of RTN4 was detected by PCR. HA-TBI caused increased neurological deficits including motor, sensory, balance and reflex deficits, increased BWC, earlier peak RTN4 expression and a longer duration of high expression in peri-injury cortical tissues, and enhanced levels of Beclin1, LC3B, and SQSTM1/p62 to varying degrees. Concurrently, the transcription of S1PR2 and PirB, the main signaling molecules downstream of RTN4, was significantly increased. In HA-TBI's early stages, the increased RTN4 may regulate enhanced autophagic initiation and impaired autolysosome degradation in vascular endothelial cells via S1PR2 receptor activation, thereby reducing BBB function. This suggests that autophagy could be a new target using RTN4 intervention as a clinical HA-TBI mechanism. Show less
no PDF DOI: 10.1097/WNR.0000000000002122
LINGO1
Wei Su, Houhua Lai, Xin Tang +4 more · 2025 · Nan fang yi ke da xue xue bao = Journal of Southern Medical University · added 2026-04-24
To investigate the role of apelin in regulating proliferation, migration and angiogenesis of bladder cancer cells and the possible regulatory mechanism. GEO database was used to screen the differentia Show more
To investigate the role of apelin in regulating proliferation, migration and angiogenesis of bladder cancer cells and the possible regulatory mechanism. GEO database was used to screen the differentially expressed genes in bladder cancer tissues and cells. Bladder cancer and paired adjacent tissues were collected from 60 patients for analysis of apelin expressions in relation to clinicopathological parameters. In cultured bladder cancer J82 cells and human umbilical vein endothelial cells (HUVECs), the effects of transfection with an apelin-overexpressing plasmid or specific siRNAs targeting apelin, fibroblast growth factor 2 (FGF2) and fibroblast growth factor receptor 1 (FGFR1) on proliferation and migration of J82 cells and tube formation in HUVECs were examined using plate cloning assay, Transwell assay, and angiogenesis assay; the changes in FGF2 expression and FGFR1 phosphorylation were detected using Western blotting. The expression level of apelin was significantly higher in bladder cancer tissues than adjacent tissues, and bladder cancer cell lines (T24 and J82) also expressed higher mRNA and protein levels of apelin than SV-HUC-1 cells. Apelin expression level in bladder cancer tissues was correlated with tumor invasion, distant metastasis and advanced TNM stages. Apelin knockdown significantly suppressed proliferation and migration of J82 cells and decreased the total angiogenic length of HUVECs. In contrast, apelin overexpression significantly promoted proliferation and migration and enhanced FGFR1 phosphorylation in J82 cells, and increased the total angiogenesis length in HUVECs, but this effects were effectively mitigated by transfection of the cells with FGF2 siRNA or FGFR1 siRNA. High expression of apelin promotes J82 cell proliferation and migration and HUVEC angiogenesis by promoting activation of the FGF2/FGFR1 pathway. Show less
no PDF DOI: 10.12122/j.issn.1673-4254.2025.06.18
FGFR1
Ting Wang, Hongkun Lin, Yan Deng +12 more · 2025 · The Journal of nutritional biochemistry · Elsevier · added 2026-04-24
Time-restricted feeding (TRF) is a dietary intervention that has been shown to have numerous health benefits. However, it is important to further investigate the potential effectiveness of TRF in addr Show more
Time-restricted feeding (TRF) is a dietary intervention that has been shown to have numerous health benefits. However, it is important to further investigate the potential effectiveness of TRF in addressing sarcopenic obesity (SO), which is characterized by a combination of age-related obesity and sarcopenia. In this study, 14-month-old C57BL/6J male mice were fed either regular chow diet or high-fat diet (HFD), and had either ad libitum or restricted access to food for 8 hours daily (Intervention for 7 months). For the human trial (ChiCTR2100052876), obese individuals (n=21) with a Body Mass Index ≥28 were recruited and instructed to adopt an 8-hour eating window and a 16-hour fasting period. Here, we found that the TRF intervention significantly reduced global fat mass (P < .001) and volume (P < .05), and increase lean mass compared to mice fed with HFD. Furthermore, TRF improved overall metabolic mobility (8h TRF+HFD vs. AL+HFD). This intervention also enhanced liver FGF21 protein levels (P < .01) and the expression of FGFR1 and FGF21 target genes in adipose and muscle tissues, thus improving mitochondrial quality control in these tissues. Notably, TRF interventions led to a significant decrease in serum FGF21 levels (P < .05). In the human trial, TRF intervention resulted in a significant reduction in weight (P < .001) and body fat levels (P < .001) among obese individuals, as well as a decrease in serum GLU (P < .001), insulin (P < .001), and TC levels (P < .05). Overall, the findings indicate that TRF intervention improves SO by regulating liver FGF21 expression, thereby enhancing FGF21 sensitivity in adipose and muscle tissues. Show less
no PDF DOI: 10.1016/j.jnutbio.2025.109893
FGFR1
Nicklas Brustad, Tingting Wang, Shizhen He +15 more · 2025 · Nature communications · Nature · added 2026-04-24
Early life air pollution exposure may play a role in development of respiratory infections, but underlying mechanisms are still not understood. We utilized data from two independent prospective birth Show more
Early life air pollution exposure may play a role in development of respiratory infections, but underlying mechanisms are still not understood. We utilized data from two independent prospective birth cohorts to investigate the influence of prenatal and postnatal ambient air pollution exposure of PM Show less
📄 PDF DOI: 10.1038/s41467-025-61392-y
AXIN1
Xueyi Sun, Shaolei Geng, Zeyuan Wang +1 more · 2025 · Human mutation · added 2026-04-24
Sepsis arises from a dysregulated host response to infection, leading to multiorgan inflammatory injury. Early diagnosis and treatment necessitate the identification of reliable immune biomarkers. Thi Show more
Sepsis arises from a dysregulated host response to infection, leading to multiorgan inflammatory injury. Early diagnosis and treatment necessitate the identification of reliable immune biomarkers. This study investigated the relationship between aging, immunity, and sepsis by analyzing six human aging-related gene sets (656 genes). We identified 16 aging-related differentially expressed genes (DEGs) in sepsis. Among these, ATP11B, RBBP7, DOCK10, and NUP160 demonstrated the strongest connectivity with other genes and exhibited significant predictive power. Functional enrichment analysis (GO and KEGG) revealed distinct signaling pathway profiles between high-risk and low-risk sepsis groups (stratified based on risk scores). These dysregulated pathways, associated with multiple immune cells, were primarily linked to transcriptional dysregulation in cellular processes and cancer-related pathways. Experimental validation assays corroborated the roles of ATP11B and RBBP7. Collectively, our bioinformatic and experimental findings indicate that ATP11B, RBBP7, DOCK10, and NUP160 are implicated in the pathogenesis and progression of sepsis. But their potential for sepsis biomarkers still requires further verification. Show less
no PDF DOI: 10.1155/humu/9789556
NUP160
Shaohua Zheng, Changwang Zhang, Youjia Chen +1 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks Show more
The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks (GNNs) have demonstrated significant advantages in predicting molecular activity. However, their reliance on graph structures alone often neglects explicit sequence-level semantic information. To address this limitation, we proposed a Graph and multi-level Sequence Fusion Learning (GSFL) model for predicting the molecular activity of BACE-1 inhibitors. Firstly, molecular graph structures generated from SMILES strings were encoded using GNNs with an atomic-level characteristic attention mechanism. Next, substrings at functional group, ion level, and atomic level substrings were extracted from SMILES strings and encoded using a BiLSTM-Transformer framework equipped with a hierarchical attention mechanism. Finally, these features were fused to predict the activity of BACE-1 inhibitors. A dataset of 1548 compounds with BACE-1 activity measurements was curated from the ChEMBL database. In the classification experiment, the model achieved an accuracy of 0.941 on the training set and 0.877 on the test set. For the test set, it delivered a sensitivity of 0.852, a specificity of 0.894, a MCC of 0.744, an F1-score of 0.872, a PRC of 0.869, and an AUC of 0.915. Compared to traditional computer-aided drug design methods and other machine learning algorithms, the proposed model can effectively improve the accuracy of the molecular activity prediction of BACE-1 inhibitors and has a potential application value. Show less
📄 PDF DOI: 10.3390/ijms26041681
BACE1
Hanxiao Xue, Sheng Bi, Zhigeng Chen +8 more · 2025 · EJNMMI research · BioMed Central · added 2026-04-24
Abnormal glymphatic system may play a critical role in amyloid-β (Aβ) accumulation in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. This study aims to use diffusion tensor ima Show more
Abnormal glymphatic system may play a critical role in amyloid-β (Aβ) accumulation in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. This study aims to use diffusion tensor image analysis along the perivascular space (DTI-ALPS) and perivascular space volume fraction (PVSVF) to investigate the aberrant glymphatic functions and the association between Aβ deposition and clinical symptoms in AD spectrum. The ALPS index was significantly lower in AD patients compared to MCI and normal controls (NC) groups. Additionally, the AD group showed a significantly higher PVSVF in hippocampus (HP) compared to NC group. No notable variations were observed in the ALPS index or PVSVF across various regions when comparing the MCI group to the NC group. Apolloprotein E (APOE) ε4 + group showed significantly higher PVSVF-HP and PVSVF in basal ganglia compared to APOE ε4 − group. All participants’ HP volume, lower cognitive scores, and higher Our findings demonstrate that glymphatic dysfunction is associated with cognitive decline, underscoring the critical roles of Aβ pathology and the APOE genotype in mediating this relationship. Further exploration of glymphatic function holds significantly promise for advancing research on AD pathogenesis. The online version contains supplementary material available at 10.1186/s13550-025-01339-y. Show less
📄 PDF DOI: 10.1186/s13550-025-01339-y
APOE
Hua Chen, Cailing Han, Chunfang Ha · 2025 · Applied biochemistry and biotechnology · Springer · added 2026-04-24
Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic tumors. Due to the high recurrence and metastasis of UCEC, it is crucial for patients to find new biomarkers for diagn Show more
Uterine corpus endometrial carcinoma (UCEC) is one of the most common gynecologic tumors. Due to the high recurrence and metastasis of UCEC, it is crucial for patients to find new biomarkers for diagnosis and therapy. In this study, R software and the TCGA database were used to screen candidate UCEC predictive markers. Western blot and RT-qPCR were performed to detect protein and mRNA expression of EXT1 in UCEC cell lines. In addition, MTT assay, flow cytometry, transwell assay, and wound healing assay were conducted to assess the cell viability, apoptosis, invasion, and migration in UCEC cells. Overlap-extension PCR technique was employed to construct the vector targeting the deletion of the methylated segment of EXT1. The results showed that a total of 11 candidate genes were obtained and EXT1 was identified as a potential target. The expression and methylation levels of EXT1 were both increased in UCEC tissues and cell lines, as well as elevated EXT1 was closely related to the poor prognosis of patients. Besides, the knockdown of EXT1 significantly inhibited the malignant biological behaviors in UCEC cells. Additionally, the current study also found that the deletion of 1559-2146 bp CpG island segment upregulated EXT1 expression and promoted malignant biological behaviors in UCEC cells. Furthermore, the presence of m7G RNA methylation in UCEC cells also was found. In conclusion, the methylation of EXT1 influenced the gene expression, thereby affecting the malignant biological behaviors in UCEC cells and regulating the pathological progression of UCEC. Show less
📄 PDF DOI: 10.1007/s12010-024-05116-w
EXT1
J Xia, X H Hu, Y Zhao +4 more · 2025 · Zhonghua nei ke za zhi · added 2026-04-24
A retrospective analysis of clinical data of 8 patients with PICALM::MLLT10 (P/M) fusion gene-positive acute myeloid leukemia (AML) diagnosed by transcriptome sequencing (RNA-seq) at the First Affilia Show more
A retrospective analysis of clinical data of 8 patients with PICALM::MLLT10 (P/M) fusion gene-positive acute myeloid leukemia (AML) diagnosed by transcriptome sequencing (RNA-seq) at the First Affiliated Hospital of Soochow University from June 2017 to March 2023 was performed. Laboratory findings and treatment status were analyzed, and survival analysis was performed using the Kaplan-Meier method. The 8 patients included 5 males and 3 females, aged 16-35 years, with a median age of 27 years. The platelet count of patients was normal, and 3 patients had mild to moderate anemia. Extramedullary infiltration was present in all patients with clinical manifestations, including 5 patients with mediastinal masses, 2 patients with hepatosplenomegaly, 1 patient with central nervous system leukemia, and 1 patient with cervical lymph node enlargement. Karyotypical analysis revealed 7 patients with an abnormal karyotype, including 6 cases of complex karyotypes. Of these, 4 patients harbored the t(10;11) translocation. The complete remission rate of induction chemotherapy in the patients was 7/8, and 2 patients experienced early recurrence. All patients subsequently underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT), The follow-up period ranged from 86 to 812 days, with a median of 330 days. Among the 8 patients, 3 survived and 5 died due to recurrence. Relapse and death only occurred in the P/M fusion gene-positive patients after transplantation. The overall survival rate at 1 year after transplantation was 37.5%. P/M Show less
no PDF DOI: 10.3760/cma.j.cn112138-20240913-00577
MLLT10
Xueli Chen, Li Dai · 2025 · Biochemical genetics · Springer · added 2026-04-24
Asthma is a common chronic respiratory disease in children, the incidence rate of which has increased in recent years. Wilms tumour 1-associated protein (WTAP) is an N6-methyladenosine (m6A) methyltra Show more
Asthma is a common chronic respiratory disease in children, the incidence rate of which has increased in recent years. Wilms tumour 1-associated protein (WTAP) is an N6-methyladenosine (m6A) methyltransferase. The purpose of this study was to explore the specific mechanism of WTAP in asthma progression, and clarify the intricate interplay between m6A modifications, WTAP, AXIN1, and their collective impact on airway smooth muscle cells (ASMCs) proliferation in asthma. Platelet-derived growth factor-BB (PDGF-BB)-treated ASMCs were used to establish an asthma model in vitro. The cell phenotype was tested using CCK-8, transwell, and wound healing assays. The expression of the Wnt signalling pathway was detected by western blotting. In addition, the relationship between WTAP/YTDHF2 and AXIN1 was assessed by a double luciferase reporter assay. Actinomycin D treatment and RT‒qPCR assays were performed to determine the mRNA stability of AXIN1. We found that WTAP was significantly increased in PDGF-BB-treated ASMCs. Knockdown of WTAP inhibited the excessive cell viability and migration of ASMCs induced by PDGF-BB. Furthermore, WTAP knockdown increased AXIN1 levels and inhibited the Wnt signalling pathway. Furthermore, WTAP knockdown decreased the m6A levels and enhanced the mRNA stability of AXIN1. WTAP overexpression showed the opposite effect. In addition, YTHDF2 was demonstrated to be the reader that recognizes the WTAP-mediated m6A modification of AXIN1. YTHDF2 knockdown enhanced the mRNA stability of AXIN1 and reversed the effect of WTAP overexpression on PDGF-BB-treated ASMCs. WTAP knockdown inhibited the excessive cell viability and migration of ASMCs by enhancing the m6A levels of AXIN1, which was further recognized by YTHDF2. The upregulation of AXIN1 mediated by the WTAP/YTHDF2 axis further inhibited the Wnt signalling pathway. Our study provides a new method for the treatment of asthma. This work not only deepens our understanding of the molecular underpinnings of asthma but also identifies potential therapeutic targets for the development of novel treatments aimed at inhibiting ASMC proliferation and alleviating asthma symptoms. Show less
📄 PDF DOI: 10.1007/s10528-024-10947-7
AXIN1
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
Xian Chen, Sichen Xia, Xue Han +4 more · 2025 · Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · Springer · added 2026-04-24
Cervical cancer incidence in China has risen to 13.83/100,000, particularly affecting younger women. Following recent family policy changes, reproductive concerns among cervical cancer patients have i Show more
Cervical cancer incidence in China has risen to 13.83/100,000, particularly affecting younger women. Following recent family policy changes, reproductive concerns among cervical cancer patients have intensified. While fertility-sparing treatments show good survival rates, many patients still experience significant anxiety about future fertility. This study aims to examine distinct reproductive concern profiles and their influencing factors in cervical cancer patients of childbearing age. We studied 247 patients from a Nanjing tertiary hospital between October 2023 and October 2024. Participants completed surveys including a demographic questionnaire, Reproductive Concerns After Cancer Scale, Patient Health Questionnaire-9, Benefit Finding Scale, and Fear of Cancer Recurrence Scale. Latent profile analysis (LPA) was conducted to identify reproductive concerns. Latent profile analysis revealed three distinct reproductive concern profiles: (1) a low-concern group with reproductive expectations (27.94%), (2) a moderate-concern group with self and child health preoccupations (49.39%), and (3) a high-concern group with impaired reproductive adaptation (22.67%). Significant influencing factors included age, number of children, residential location, depressive symptoms, and fear of cancer recurrence. These cross-sectional findings emphasize the need for careful consideration of individualized, multiple-disciplinary care for young women with cervical cancer. Benefit finding was associated with lower reproductive concerns. Show less
📄 PDF DOI: 10.1007/s00520-025-10125-4
LPA
Jun Teng, Chongwei Duan, Xinyi Zhang +9 more · 2025 · Journal of dairy science · added 2026-04-24
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation tr Show more
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation traits is essential for understanding their genetic basis. In this study, we conducted single-trait and multitrait GWAS for 20 body conformation traits using imputed sequence data in 7,674 Chinese Holstein individuals and identified 27 QTL regions. Leveraging these QTL regions, we performed multitrait Bayesian fine-mapping to identify 30 independent credible sets of putative causal variants. Incorporating GWAS and cis-acting expression QTL data, Mendelian randomization was used to infer 153 putative causal gene-trait relationships. The previously reported genes, such as CCND2, TMTC2, and NRG3, were confirmed in our study. Of note, several novel candidate causal genes were also identified, such as C1R, RIMS1, SERPINB8, NETO2, TTYH3, TTC3, ANAPC4, and PSMD13. Our results provide new insights into the regulatory mechanisms of body conformation traits in cattle. Show less
no PDF DOI: 10.3168/jds.2025-26361
ANAPC4
Wenli Zhang, Jinhong Zhu, Mengzhen Zhang +7 more · 2025 · Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · added 2026-04-24
Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings. Previous genome-wide association studies (GWASs) have identified many loci associated with Show more
Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings. Previous genome-wide association studies (GWASs) have identified many loci associated with neuroblastoma susceptibility; however, their application in risk prediction for Chinese children has not been systematically explored. This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models. We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children, consisting of 402 neuroblastoma patients and 473 healthy controls. Genotyping these polymorphisms was conducted via the TaqMan method. Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk. We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve (AUC) analysis. We also established a polygenic risk scoring (PRS) model for risk prediction by adopting the PLINK method. Fourteen loci, including ten protective polymorphisms from Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models, particularly the PRS, in improving risk prediction. These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children. Show less
no PDF DOI: 10.21147/j.issn.1000-9604.2025.01.01
HSD17B12
Mackenzie K Fitzpatrick, Christina Dyson, Angela Beeson +8 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
We have previously demonstrated that a transmembrane domain mutation in
no PDF DOI: 10.1101/2025.03.28.645767
ADCY3