👤 Tse-Wei 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, 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, 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

Solanum lyratum-Derived Solalyraine A1 Suppresses Non-Small Cell Lung Cancer Through Regulation of Exosome Secretion and Related Protein Biomarkers.

Pu Jiang, Liangyu Liu, Lixian Chen +2 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18091280
APOB

A novel splicing variant of CNTRL::FGFR1 in myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1.

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

Protective functions of liver X receptor α on calcified aortic valve: involvement of regulating endoplasmic reticulum-mediated osteogenic differentiation.

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

A Multifaceted Giant Protein Microtubule-Actin Cross-Linking Factor 1.

Chung-Ming Lin, Ru-Huei Fu, Hui-Jye Chen · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Microtubule-actin cross-linking factor 1 (MACF1), also known as actin cross-linking family protein 7 (ACF7), is a giant cytolinker protein with multiple conserved domains that can orchestrate cytoskel Show more
Microtubule-actin cross-linking factor 1 (MACF1), also known as actin cross-linking family protein 7 (ACF7), is a giant cytolinker protein with multiple conserved domains that can orchestrate cytoskeletal networks of actin and microtubules. MACF1 is involved in various biological processes, including cell polarity, cell-cell connection, cell proliferation, migration, vesicle transport, signal transduction, and neuronal development. In this review, we updated the physiological and pathological roles of MACF1, highlighting the components and signaling pathways involved. Novel evidence showed that MACF1 is involved in diverse human diseases, including multiple neuronal diseases, congenital myasthenic syndrome, premature ovarian insufficiency, spectraplakinopathy, osteoporosis, proliferative diabetic retinopathy, and various types of cancer. We also reviewed the physiological roles of MACF1, including its involvement in adhesome formation, bone formation, neuronal aging, and tooth development. In addition, MACF1 plays other roles, functioning as a biomarker for the prediction of infections in patients with burns and as a marker for genome selection breeding. These studies reinforce the idea that MACF1 is a bona fide versatile, multifaceted giant protein. Identifying additional MACF1 functions would finally help with the treatment of diseases caused by MACF1 defects. Show less
📄 PDF DOI: 10.3390/ijms26073204
MACF1

An interleukin-27-centered cytokine circuit regulates macrophage and T cell interactions in autoimmune diabetes.

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

Corrigendum to "Selective degradation of FGFR1/2 overcomes antiestrogen resistance in ER+ breast cancer with FGFR1/2 alterations" [619 1 (2025) 217668 1-13].

Yasuaki Uemoto, Chang-Ching A Lin, Bingnan Wang +10 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.canlet.2025.217782
FGFR1

Corrigendum to "piR-36249 and DHX36 together inhibit testicular cancer cells progression by upregulating OAS2" [Noncoding RNA Research 2023 8 (2) 174-186].

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

[Mechanism of astragaloside Ⅳ intervention in endothelial-mesenchymal transition of ApoE~(-/-) atherosclerosis mice via energy metabolic reprogramming pathway].

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

Trofinetide Improves Cognitive Function in APP/PS1 Mice by Suppressing Inflammation and Apoptosis.

Meilin Chen, Yuye Ning, Hao Yang +1 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive impairment, neuroinflammation, and neuronal apoptosis. Trofinetide, an analog of insulin-like growth fac Show more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive impairment, neuroinflammation, and neuronal apoptosis. Trofinetide, an analog of insulin-like growth factor 1 (IGF-1), has shown neuroprotective effects in various neurological disorders, but its role in AD remains unclear. Six-month-old APP/PS1 transgenic mice received intraperitoneal trofinetide for 2 months. Cognitive function was assessed using the Morris water maze (MWM) test. Immunohistochemistry (IHC) and immunofluorescence (IF) evaluated β-amyloid (Aβ) pathology, microglial activation, and neuronal loss. In vitro, BV2 microglial cells and HT22 hippocampal neurons were treated with trofinetide against AβO-induced cytotoxicity. Western blot (WB) was used to analyze inflammation and apoptosis-related proteins. Trofinetide significantly improved cognitive deficits, reduced Aβ plaque deposition, and decreased microglial activation and neuronal loss in APP/PS1 mice. In vitro, it rescued AβO-induced cytotoxicity, suppressed inflammatory cytokines (TNF-α, IL-6, IL-1) in BV2 cells, and inhibited apoptosis in HT22 cells. Mechanistically, trofinetide upregulated PPAR-γ, reduced BACE1, suppressed NF-κB phosphorylation, inhibited caspase-3 activation, and restored Bax/Bcl-2 balance, alleviating neuroinflammation and apoptosis. This study provides the first evidence that trofinetide improves cognitive function and mitigates Aβ pathology, neuroinflammation, and apoptosis in APP/PS1 mice and AβO-treated cells, highlighting its therapeutic potential for AD. Show less
📄 PDF DOI: 10.1007/s12035-025-05500-5
BACE1

Comorbidity patterns and immune-metabolic differences in patients with acute-episode of schizophrenia spectrum disorders.

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

Jiajian Shuyu pills effectively ameliorate cognitive impairment via regulating the inflammation of microglia in an Alzheimer's disease mouse model.

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

Dorsal raphe GABA-ergic neurons regulate the susceptibility to social transfer of pain in mice.

Lin Ai, Yi Han, Ting Ge +14 more · 2025 · Acta pharmacologica Sinica · Nature · added 2026-04-24
Some individuals are more susceptible to developing or suffering from pain states than others. However, the brain mechanisms underlying the susceptibility to pain responses are unknown. In this study, Show more
Some individuals are more susceptible to developing or suffering from pain states than others. However, the brain mechanisms underlying the susceptibility to pain responses are unknown. In this study, we defined pain susceptibility by recapitulating inter-individual differences in pain responses in mice exposed to a paradigm of socially transferred allodynia (STA), and with a combination of chemogenetic, molecular, pharmacological and electrophysiological approaches, we identified GABA-ergic neurons in the dorsal raphe nucleus (DRN) as a cellular target for the development and maintenance of STA susceptibility. We showed that DRN GABA-ergic neurons were selectively activated in STA-susceptible mice when compared with the unsusceptible (resilient) or control mice. Chemogenetic activation of DRN GABA-ergic neurons promoted STA susceptibility; whereas inhibiting these neurons prevented the development of STA susceptibility and reversed established STA. In in vitro slice electrophysiological analysis, we demonstrated that melanocortin 4 receptor (MC4R) enriched in DRN GABA-ergic neurons was a molecular target for regulating pain susceptibility, possibly by affecting DRN GABA-ergic neuronal activity. These results establish the DRN GABA-ergic neurons as an essential target for controlling pain susceptibility, thus providing important information for developing conceptually innovative and more accurate analgesic strategies. Show less
no PDF DOI: 10.1038/s41401-025-01494-x
MC4R

Hericium erinaceus Protein Alleviates High-Fat Diet-Induced Hepatic Lipid Accumulation and Oxidative Stress In Vivo.

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

Deficiency of EXT1 and FGFR3 genes promotes chondrocyte differentiation, leading to the induction of osteochondroma formation.

Hongrong Zhang, Zhencun Tang, Shiying Shen +6 more · 2025 · Bone · Elsevier · added 2026-04-24
This study aims to investigate the roles of the EXT1 and FGFR3 genes in the development of osteochondromas, focusing specifically on their potential interactions in chondrocyte proliferation, differen Show more
This study aims to investigate the roles of the EXT1 and FGFR3 genes in the development of osteochondromas, focusing specifically on their potential interactions in chondrocyte proliferation, differentiation, and tumor formation. In vitro, the ATDC5 chondroprogenitor cell line was used to examine the effects of inactivation of both EXT1 and FGFR3. In vivo, a mouse model with dual gene knockout of Ext1 and Fgfr3 was constructed to further explore these genes' roles in tumor formation by observing the incidence and distribution patterns of osteochondromas. The in vitro experiments demonstrated that ATDC5 cells with reduced expression of EXT1 and FGFR3 genes exhibited enhanced chondrogenic differentiation. In vivo, Fgfr3 The EXT1 and FGFR3 genes play crucial regulatory roles in the development of osteochondromas. Deficiencies in Ext1 and Fgfr3 can induce the formation of osteochondromas. Show less
no PDF DOI: 10.1016/j.bone.2024.117370
EXT1

Profiles of academic resilience and associated factors among undergraduate nursing students: A latent profile analysis.

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

[Apelin promotes proliferation, migration, and angiogenesis in bladder cancer by activating the FGF2/FGFR1 pathway].

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

Activation of AMPK by GLP-1R agonists mitigates Alzheimer-related phenotypes in transgenic mice.

Yun Zhang, Huaqiu Chen, Yijia Feng +14 more · 2025 · Nature aging · Nature · added 2026-04-24
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential Show more
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential neuroprotective properties, but their effects on AD and the underlying mechanisms are not well understood. Here we demonstrate that GLP-1RAs can alleviate AD-related phenotypes by activating 5' AMP-activated protein kinase (AMPK) signaling. We found that plasma GLP-1 levels were decreased in AD model mice and negatively correlated with amyloid-beta (Aβ) load in patients with AD. Enhancing GLP-1 signaling through GLP-1RAs increased CaMKK2-AMPK signaling, which subsequently reduced BACE1-mediated cleavage of amyloid precursor protein (APP) and Aβ generation. GLP-1RAs also increased AMPK activity in microglia, inhibiting neuroinflammation and promoting Aβ phagocytosis. Consequently, GLP-1RAs inhibited plaque formation and improved memory deficits in AD model mice. Our findings indicate that AMPK activation mediates the effects of GLP-1RAs on AD, highlighting the therapeutic potential of GLP-1RAs for the treatment of AD. Show less
📄 PDF DOI: 10.1038/s43587-025-00869-3
BACE1

Association of ApoB/apoA1 ratio with stenosis of intracranial and extracranial arteries in patients with ischaemic stroke.

Mimi Li, Lichao Ye, Chunnuan Chen · 2025 · Scientific reports · Nature · added 2026-04-24
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contr Show more
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contributing to stroke remains poorly understood. This study aims to investigate the association between the apoB/apoA1 ratio and intracranial or extracranial atherosclerosis. We enrolled 408 patients with acute ischemic stroke who had never been treated with statins or fibrates. Based on the images from computed tomography angiography (CTA), the patients were categorized into four groups: intracranial atherosclerosis stenosis (ICAS, n = 136), extracranial carotid atherosclerosis stenosis (ECAS, n = 45), combined intracranial and extracranial atherosclerosis stenosis (COAS, n = 73), and non-cerebral atherosclerosis stenosis (NCAS, n = 154). Demographic characteristics, clinical factors, and serum lipid levels were collected and then compared across groups. The apoB/apoA1 ratio was significantly higher in patients with ICAS, ECAS and COAS compared to those in the NCAS group. Multivariable logistic regression analysis demonstrated that the ApoB/ApoA1 ratio was independently associated with ICAS, but not with ECAS. ROC curve analysis showed that the ApoB/ApoA1 ratio had a good diagnostic ability for ICAS, with an area under the curve (AUC) of 0.764, an optimal cut-off value of 0.8122, a sensitivity of 81.3%, and a specificity of 59.8%. An higher apoB/apoA1 ratio is associated with ICAS in ischemic stroke patients. Show less
📄 PDF DOI: 10.1038/s41598-025-97625-9
APOB

Time-restricted feeding mitigates HFD-induced sarcopenic obesity in aging mice through improving the sensitivity of FGF21.

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

Air pollution-induced proteomic alterations increase the risk of child respiratory infections.

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

Aurora-A promotes lenvatinib resistance experimentally through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma.

Mubalake Abudoureyimu, Ni Sun, Weiwei Chen +3 more · 2025 · International journal of immunopathology and pharmacology · SAGE Publications · added 2026-04-24
This study aimed to investigate whether the dysregulation of Aurora-A is involved in lenvatinib resistance in hepatocellular carcinoma. Bioinformatics tools and drug sensitivity assays were used to in Show more
This study aimed to investigate whether the dysregulation of Aurora-A is involved in lenvatinib resistance in hepatocellular carcinoma. Bioinformatics tools and drug sensitivity assays were used to investigate the association between Aurora-A expression level and lenvatinib resistance in hepatocellular carcinoma cell lines. Cell function experiments had performed after treatment with lenvatinib and/or a selective Aurora-A inhibitor (MLN-8237). CircRNA microarray, RIP, RNA pull-down, and dual-luciferace reporter assay were performed to identify the downstream molecular mechanism of Aurora-A dysregulation. Aurora-A expression was positively correlated with lenvatinib resistance in hepatocellular carcinoma cells. The Aurora-A selective inhibitor MLN-8237, in combination with lenvatinib, synergistically inhibited hepatocellular carcinoma cell proliferation in vitro and vivo, suggesting the Aurora-A might be a potential therapeutic target for lenvatinib resistance. Mechanistically, Aurora-A induced FGFR1 expression through the hsa-circ-0058046/miR-424-5p/FGFR1 axis. Aurora-A promotes lenvatinib resistance through hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma cells. The simultaneous inhibition of FGFR1 by the Aurora-A inhibitor MLN-8237 and lenvatinib overcame lenvatinib resistance in hepatocellular carcinoma cells. Collectively, our findings indicate that Aurora-A promotes lenvatinib resistance through the hsa-circ-0058046/miR-424-5p/FGFR1 axis in hepatocellular carcinoma (HCC) cells. These results suggest that Aurora-A may serve as a therapeutic target for HCC patients exhibiting lenvatinib resistance. Furthermore, the combination of lenvatinib and MLN-8237 shows potential for clinical trials aimed at overcoming lenvatinib resistance. Show less
📄 PDF DOI: 10.1177/03946320251316692
FGFR1

Age-Related Meat Flavor Precursors of Naturally Grazed Sunit Sheep: Metabolomics and Transcriptomics Approaches.

Yajuan Huang, Xige He, Yunfei Han +6 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
This study elucidated the regulatory mechanisms of age-related meat flavor precursors in naturally grazed Sunit sheep of different ages (6, 18, and 30 months) by analyzing their metabolite and mRNA pr Show more
This study elucidated the regulatory mechanisms of age-related meat flavor precursors in naturally grazed Sunit sheep of different ages (6, 18, and 30 months) by analyzing their metabolite and mRNA profiles. The longissimus dorsi muscle was sampled from each group and subjected to metabolomics and transcriptomics analyses. A total of 395 differential metabolites (DMs) and 1482 differentially expressed genes (DEGs) were detected across the age groups. As the age increased, the expression levels of Show less
📄 PDF DOI: 10.3390/foods14091616
FADS1

Explainable machine learning model for classifying atherosclerotic cardiovascular disease in patients with metabolic dysfunction-associated steatotic liver disease.

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

Correlation between lipid metabolism levels and pregnancy outcomes.

Jingjing Guo, Haifan Qiu, Jianping Wang +3 more · 2025 · Frontiers in medicine · Frontiers · added 2026-04-24
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregn Show more
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregnancy women and 317 healthy non-pregnant women. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), lipoprotein (a) [Lp(a)], and hypersensitive C-reactive protein (hs-CRP) were measured in both groups. The mean and standard deviation of each index were calculated to establish the reference range of normal serum lipid levels in pregnant women in mid-to-late pregnancy. The associations between serum lipid levels and perinatal outcomes were assessed statistically. There were no significant differences in age, pregnancy, or parity between the adverse outcome and normal delivery groups, but the caesarean section rate was significantly higher in the adverse outcome group. The levels of hs-CRP, TG, TC, HDL-C, LDL-C, and ApoA1 were significantly higher in the adverse outcome group. Elevated hs-CRP, TG, and HDL-C levels were risk factors for adverse pregnancy outcomes. According to the receiver operating characteristic curve, the optimal threshold of the combined diagnosis of these three indicators to predict adverse pregnancy outcomes was 0.534, and the area under the curve was 0.822. The establishment of lipid reference intervals in the second and third trimesters of pregnancy can effectively evaluate lipid metabolism in pregnant women, and the measurement of lipid metabolism in pregnant women is helpful in predicting adverse pregnancy outcomes. Show less
📄 PDF DOI: 10.3389/fmed.2025.1530525
APOB

WTAP Promotes the Excessive Proliferation of Airway Smooth Muscle Cells in Asthma by Enhancing AXIN1 Levels Through the Recognition of YTHDF2.

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

The heart-brain axis: unraveling the interconnections between cardiovascular and Alzheimer's diseases.

Aili Toyli, Anjum Shaik, Chen Zhao +3 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Cardiovascular disease (CVD) and Alzheimer's disease (AD) are leading causes of death and disability worldwide, and recent research has increasingly illuminated a complex, bidirectional relationship b Show more
Cardiovascular disease (CVD) and Alzheimer's disease (AD) are leading causes of death and disability worldwide, and recent research has increasingly illuminated a complex, bidirectional relationship between the two. This review synthesizes epidemiological, mechanistic, imaging, and genetic evidence linking CVD and AD through the heart-brain axis-a network of interrelated physiological and demographic pathways. We detail how cerebral hypoperfusion, inflammation, blood-brain barrier dysfunction, imbalance of the autonomic nervous system, and systemic amyloidosis contribute to shared neurodegenerative and cardiovascular outcomes. Multi-organ imaging studies, including MRI and PET, reveal that dysfunction of the cardiovascular system correlates with brain atrophy, white matter lesions, glymphatic impairment, and accumulation of AD-related proteinopathies. Genetic analyses further support overlapping risk architectures, particularly involving APOE and loci associated with lipid metabolism, vascular integrity, and inflammation. Age and sex are critical modifiers, with midlife CVD exerting the strongest influence on later cognitive decline, and sex-specific physiological responses shaping disease susceptibility. Finally, we explore how modifiable lifestyle factors, pharmacologic interventions, and precision medicine approaches targeting inflammatory and vascular pathways can jointly reduce the burden of both CVD and AD. Multidisciplinary collaboration to understand the interconnected biology of the heart and brain is essential for advancing integrated prevention and treatment strategies in aging populations. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1685461
APOE

Bayesian fine-mapping and Mendelian randomization leveraging expression quantitative trait loci reveal novel candidate causal genes for body conformation traits in cattle.

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

Clinical characteristics of 41 children with hypertrophic cardiomyopathy: A single-center retrospective study.

Shi-Guang Li, Chang-Qing Wei, Dan-Yan Su +4 more · 2025 · The Journal of international medical research · SAGE Publications · added 2026-04-24
ObjectiveTo analyze the clinical characteristics, etiological composition, genetic variations, and survival outcomes of children with hypertrophic cardiomyopathy.Materials and methodsThis retrospectiv Show more
ObjectiveTo analyze the clinical characteristics, etiological composition, genetic variations, and survival outcomes of children with hypertrophic cardiomyopathy.Materials and methodsThis retrospective study included 41 pediatric patients diagnosed with hypertrophic cardiomyopathy at The First Affiliated Hospital of Guangxi Medical University from 2013 to 2024. Clinical data were reviewed, including symptoms, echocardiography, electrocardiography, genetic testing, and follow-up outcomes. Comparisons were made between patients with primary and secondary hypertrophic cardiomyopathy.ResultsAmong the 41 patients, 27 were men and 14 were women, with a median age at onset of 4 years and 3 months. Genetic testing was performed in 24 cases, identifying 13 cases of primary hypertrophic cardiomyopathy and 11 cases of secondary hypertrophic cardiomyopathy, most commonly associated with Noonan syndrome. The most frequent symptoms were fatigue (28.95%) and dyspnea (23.68%). Common pathogenic genes in primary hypertrophic cardiomyopathy included Show less
📄 PDF DOI: 10.1177/03000605251399040
MYBPC3

Reproductive concerns in young women with cervical cancer: latent profiles and key influencing factors.

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

Improving neuroblastoma risk prediction through a polygenic risk score derived from genome-wide association study-identified loci.

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