👤 Xing-Long 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, 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
Jing Xu, Ziyan He, Yaoxin Pan +2 more · 2026 · Biomaterials advances · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by excessive amyloid-β (Aβ) accumulation, neuroinflammation, and oxidative stress. Exosomes derived from human umbili Show more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by excessive amyloid-β (Aβ) accumulation, neuroinflammation, and oxidative stress. Exosomes derived from human umbilical cord mesenchymal stem cells (hUC-MSC@Exo) represent promising nanoscale carriers for targeted drug delivery. In this study, Baicalein (Bac), a potent antioxidant and anti-inflammatory flavonoid, was encapsulated into hUC-MSC-derived exosomes (Exo@Bac) to enhance its therapeutic efficacy. The neuroprotective potential of Exo@Bac was evaluated in a rat model of Aβ1-42-induced AD. Rats received intraperitoneal injections of Bac, hUC-MSC@Exo, or Exo@Bac, and cognitive performance was assessed using the passive avoidance test and Morris water maze. Exo@Bac treatment significantly improved memory deficits and elevated brain-derived neurotrophic factor (BDNF) expression compared to controls. Histopathological analyses revealed reduced neuronal damage and apoptosis, alongside decreased Aβ1-42 deposition in Exo@Bac-treated rats. Furthermore, Exo@Bac enhanced antioxidant defense (increased SOD), attenuated pro-inflammatory cytokines (TNF-α, IL-6, IL-1β), and lowered lipid peroxidation (MDA). Mechanistically, Exo@Bac promoted AMPK phosphorylation while suppressing NF-κB p65 signaling, indicating modulation of both oxidative stress and neuroinflammatory pathways. These findings demonstrate that Exo@Bac acts as a nanotherapeutic agent capable of mitigating AD pathology, highlighting its potential as a novel strategy for Alzheimer's disease therapy. Show less
no PDF DOI: 10.1016/j.bioadv.2025.214619
BDNF alzheimer's disease drug delivery exosomes nanotherapeutics neurodegenerative disorder neuroinflammation oxidative stress
Qing Li, Shasha Zhu, Guanyu Chen +5 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Protocatechuic acid (PCA), a natural compound found in a variety of Chinese herbal medicines and plant foods, has been documented to inhibit atherosclerosis partially by reducing inflammation burden i Show more
Protocatechuic acid (PCA), a natural compound found in a variety of Chinese herbal medicines and plant foods, has been documented to inhibit atherosclerosis partially by reducing inflammation burden in arterial endothelial cells. Interestingly, in vitro studies showed that PCA at physiologically reachable concentrations does not affect inflammation burden in TNF-α-stimulated aortic endothelial cells, whereas it increases the content of exosomal miR-10b secreted by macrophages that have engulfed apoptotic cells (efferocytic macrophages). This study was aimed at investigating whether the in vivo anti-inflammatory effect of PCA in arterial endothelial cells was due to the uptake of efferocytic macrophage exosomal miR-10b. A transwell co-culture system of aortic endothelial cells with efferocytic macrophages was used to evaluate the effect of PCA on NF-κB-mediated inflammation in aortic endothelial cells. An inhibitor of exosome secretion, GW4869, was applied to confirm the role of exosomes played in the anti-inflammatory effect of PCA. The aortic endothelial cells were administrated with exosomes isolated from PCA-treated efferocytic macrophages or miR-10b mimic or antagomir to ascertain the role of miR-10b in downregulating inflammation effect of PCA. Bioinformatics analyses, loss-of- and gain-of-function assays and luciferase reporter gene assays were performed to identify targeting relationship between miR-10b and mitogen-activated protein kinase kinase kinase 7 (MAP3K7)/β-transducin repeat-containing protein (β-TrCP). Besides, Apoe PCA at physiologically reachable concentrations inhibited NF-κB-mediated inflammation in TNF-α-stimulated aortic endothelial cells co-cultured with efferocytic macrophages, in which treatment of GW4869 reversed this effect. Exosomes isolated from PCA-treated efferocytic macrophages inhibited inflammation and increased miR-10b levels in aortic endothelial cells. Mechanistically, exosomal miR-10b post-transcriptionally repressed MAP3K7 and β-TrCP, both of which promote NF-κB activation. Knockdown of Map3k7 and Btrc with siRNA in aortic endothelial cells abolished the inhibitory effects of exosomes isolated from PCA-treated efferocytic macrophages on NF-κB-mediated inflammation. Consistently, oral administration of PCA increased miR-10b level and inhibited Map3k7 and Btrc mRNA expression as well as inflammation in aortic endothelial cells in Apoe Our current findings suggest that PCA could transfer exosomal miR-10b from efferocytic macrophages to endothelial cells and thus inhibit NF-κB-mediated inflammation in arterial endothelial cells through repressing MAP3K7 and β-TrCP, two new targets of miR-10b. Show less
no PDF DOI: 10.1016/j.phymed.2026.157939
APOE
Huanhuan Huang, Yetao Luo, Qi Huang +5 more · 2026 · BMC nursing · BioMed Central · added 2026-04-24
The COVID-19 pandemic has significantly disrupted educational style, potentially affecting the learning adaptation of nursing freshmen who are integral to the future nursing workforce. This study aime Show more
The COVID-19 pandemic has significantly disrupted educational style, potentially affecting the learning adaptation of nursing freshmen who are integral to the future nursing workforce. This study aimed to identify distinct subgroups of nursing freshmen based on their bioecological attributes related to learning adaptation during the pandemic. A multicenter, cross-sectional study was conducted of 1170 first-year nursing students from six higher education institutions in China. Learning adaptation, resilience, parental attachment, interaction anxiety, and mobile phone addiction, were investigated. Latent Profile Analysis (LPA) was utilized to identify distinct profiles. Descriptive statistics indicated a positive level of learning adaptation among participants, with an overall mean score of 3.51 ± 0.57. LPA revealed four distinct profiles: 'Struggling Learners' (5.47%), 'Moderate Engagers' (70.60%), 'Adaptable Strivers' (18.29%), and 'Optimal Adapters' (5.64%), which demonstrated significant differences in adaptation, resilience, parental attachment, interaction anxiety, and mobile phone addiction tendencies (P < 0.05). The study's findings emphasize the heterogeneity in learning adaptation among nursing freshmen and the importance of considering bioecological attributes when developing educational interventions during crisis. Recognizing these profiles can guide the development of targeted strategies to enhance student adaptation and academic achievement. Show less
📄 PDF DOI: 10.1186/s12912-025-04261-9
LPA
Donghui Zhu, Xiuxiu Chen · 2026 · Experimental gerontology · Elsevier · added 2026-04-24
This study aims to explore the shared transcriptomic features of caloric restriction (CR) and endurance exercise in skeletal muscle among older adults. As age increases, muscle atrophy gradually becom Show more
This study aims to explore the shared transcriptomic features of caloric restriction (CR) and endurance exercise in skeletal muscle among older adults. As age increases, muscle atrophy gradually becomes a common issue of functional decline in the elderly. Utilizing bioinformatics analysis, this research identified 101 overlapping differentially expressed genes (DEGs) involved in both CR and endurance exercise. These genes are primarily enriched in key biological pathways related to longevity, Apelin signaling, AMPK signaling, FoxO signaling, and cGMP-PKG signaling pathways. Additionally, we identified 10 key genes (such as LPL, PPARGC1A, and IGF1), 4 transcription factors (FOXC1, POU2F2, GATA2, and STAT3), and 4 microRNAs (miR-155-5p, miR-124-3p, miR-1-3p, and miR-16-5p) interacting with these genes. Drug-gene interaction analysis identified carotuximab as a compound with potential relevance for future investigation in the context of muscle aging. These findings provide new insights into the molecular mechanisms underlying muscle functional decline in the elderly and propose potential targets and drugs for intervention development. Show less
no PDF DOI: 10.1016/j.exger.2026.113083
LPL
Xiaohua Chen, Huan Liu, Yurong Liu +16 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospect Show more
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospective UK Biobank cohort, we evaluated the bidirectional associations by time-varying Cox proportional hazards regression models and assessed shared genetic architecture using genome-wide association study summary statistics. Additionally, we employed collagen-induced arthritis (CIA) and chronic social defeat stress (CSDS) mouse models to investigate the relationship between rheumatoid arthritis (RA) and depression. Over 5,226,841 person-years of follow-up, 23,534 incident MDD cases were identified. The presence of any IMD was associated with higher MDD risk (hazard ratio [HR]: 1.95; 95% CI: 1.89-2.01). Conversely, 59,742 incident cases of IMD were documented. MDD was associated with increased IMD risk (HR: 1.47; 95% CI: 1.40-1.54). We observed significant global genetic correlations between IMDs and MDD (r Show less
📄 PDF DOI: 10.1038/s41380-026-03459-w
BDNF
David Lukacsovich, Juan I Young, Lissette Gomez +8 more · 2026 · Research square · added 2026-04-24
Cognitive reserve (CR) refers to differences in the adaptability of cognitive processes that modify the impact of Alzheimer's disease (AD) pathology on cognitive performance. Currently there are no es Show more
Cognitive reserve (CR) refers to differences in the adaptability of cognitive processes that modify the impact of Alzheimer's disease (AD) pathology on cognitive performance. Currently there are no established blood-based biomarkers of CR in prodromal AD. In this study, we operationalize CR as memory reserve, defined as moderation (attenuation) of the CSF pTau181-memory association. DNA methylation (DNAm) integrates genetic and environmental influences and may capture biological processes that mitigate the impact of AD pathology on memory. We aimed to identify blood DNAm loci that moderate the association between cerebrospinal fluid (CSF) phosphorylated tau (pTau181) and memory in mild cognitive impairment (MCI). We also sought to determine if a DNAm-based signature of memory reserve predicts future memory decline. We analyzed 92 amyloid positive MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with blood DNAm, CSF pTau181, and memory scores (PHC_MEM) collected at the same visit. We first regressed memory scores on covariates (age, sex, number of After removing CpGs with low variability, we identified 6 CpGs with suggestive significance for DNAm×pTau181 interaction ( Blood DNAm patterns that moderate the pTau-memory relationship capture biology underlying memory reserve involving synaptic, vascular, immune, and metabolic pathways, and can be summarized into an MRS that predicts longitudinal memory trajectories in MCI. These findings support blood DNAm as a promising, non-invasive biomarker of cognitive resilience to AD pathology. Show less
📄 PDF DOI: 10.21203/rs.3.rs-8369919/v1
APOE
Luwen Hao, Xin Chen, Bo Qin · 2026 · Frontiers in cell and developmental biology · Frontiers · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a genetically heterogeneous cardiac disorder characterized by unexplained left ventricular hypertrophy and represents a leading cause of morbidity and sudden cardi Show more
Hypertrophic cardiomyopathy (HCM) is a genetically heterogeneous cardiac disorder characterized by unexplained left ventricular hypertrophy and represents a leading cause of morbidity and sudden cardiac death, particularly in young adults and athletes. Early studies focused on morphological features, but advances in molecular genetics have shifted emphasis toward genetic diagnosis, mechanistic insights, and family-based management. Pathogenic variants in sarcomeric genes, especially Show less
📄 PDF DOI: 10.3389/fcell.2026.1741252
MYBPC3
Xiaoxiao Li, Yanyan Jiao, Zhongqiang Guo +4 more · 2026 · Acta psychologica · Elsevier · added 2026-04-24
This study employed a latent profile analysis (LPA) to identify distinct subgroups of learned helplessness among Chinese breast cancer chemotherapy patients and examined influencing factors. Through c Show more
This study employed a latent profile analysis (LPA) to identify distinct subgroups of learned helplessness among Chinese breast cancer chemotherapy patients and examined influencing factors. Through convenience sampling, 260 breast cancer chemotherapy patients aged 18-74 years from a tertiary hospital in Henan Province were recruited between May 2024 and January 2025. Data were collected using a general demographic questionnaire, the Learned Helplessness Scale, the Brief Illness Perception Questionnaire, the Social Support Rating Scale, and the General Self-Efficacy Scale. An LPA was applied to classify learned helplessness patterns, followed by a multivariate logistic regression to determine the influencing factors. The latent profile analysis revealed three distinct profiles of learned helplessness among breast cancer patients undergoing chemotherapy: a "low helplessness-low hopelessness stable profile" (17.0%), a "moderate helplessness-moderate hopelessness fluctuating profile" (52.0%), and a "high helplessness-high hopelessness profile" (31.0%). The multivariable logistic regression revealed that age range 18-44 years, low monthly household income per capita, fatigue, and illness perception were significantly associated with the "high helplessness-high hopelessness profile" (P < 0.05). Conversely, the age range 45-59 years was significantly associated with the "moderate helplessness-moderate hopelessness fluctuating profile" (P < 0.001). Furthermore, experiencing ≤2 chemotherapy-related side effects, a higher level of perceived social support, and greater self-efficacy were significant predictors of membership in the "low helplessness-low hopelessness profile" (P < 0.05). Breast cancer chemotherapy patients were categorized into three distinct subgroups, which were influenced by age, income, fatigue, treatment side effects, illness perception, self-efficacy, and social support. Show less
no PDF DOI: 10.1016/j.actpsy.2026.106392
LPA
Changle Zhao, Xiang Liu, Xi Peng +5 more · 2026 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, usi Show more
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, using a CRISPR/Cas9-mediated Show less
📄 PDF DOI: 10.3390/ani16030405
LPL
Shiqian Chen, Carolina B Lobato, Carissa Wong +13 more · 2026 · Molecular metabolism · Elsevier · added 2026-04-24
Internalisation of G protein-coupled receptors (GPCRs) can contribute to altered cellular responses by directing signalling from non-canonical locations, such as endosomes. If signalling processes are Show more
Internalisation of G protein-coupled receptors (GPCRs) can contribute to altered cellular responses by directing signalling from non-canonical locations, such as endosomes. If signalling processes are locally constrained, active receptors in different subcellular locations could produce different downstream effects. This phenomenon may be relevant to the optimal targeting of the glucagon-like peptide-1 receptor (GLP-1R), a type 2 diabetes and obesity target GPCR for which several ligands with varying internalisation tendency have been discovered. To investigate, we compared the signalling localisation effects of two prototypical GLP-1RAs with opposite signal bias and effects on GLP-1R trafficking: exendin-asp3 (ExD3), a full agonist that drives rapid internalisation, and exendin-phe1 (ExF1), which shows much slower internalisation. After using bioorthogonal labelling and fluorescent agonist conjugates to verify the divergent trafficking patterns of ExF1 and ExD3 in β-cell lines and primary pancreatic islets, we used live cell biosensors to monitor signalling at different subcellular locations. This revealed that cAMP/PKA/ERK signalling in β-cells is in fact distributed widely across the cell over short- (<5 min) and medium-term (up to 60 min) stimulation at pharmacological (>10 pM) concentrations, with no major differences in signal localisation that could be linked to internalised versus cell surface-bound GLP-1R. Moreover, washout experiments highlighted that, whilst fast-internalising ExD3 shows much greater accumulation and binding to GLP-1R in endosomes than slow-internalising ExF1, it is a rather inefficient driver of both cAMP production in β-cells and insulin secretion from perfused rat pancreata. These data provide a greater understanding of the cellular effects of biased GLP-1R agonism. Show less
📄 PDF DOI: 10.1016/j.molmet.2025.102304
GIPR
Mengshi Li, Yang Li, Lei Jiang +7 more · 2026 · Chinese medical journal · added 2026-04-24
📄 PDF DOI: 10.1097/CM9.0000000000003978
APOE
Li Li, Xiaoyan Chen, Jingke Li +4 more · 2026 · Blood advances · added 2026-04-24
Platelets must balance hemostatic function with pathological thrombosis, particularly under metabolic stress conditions. MAPKs are central to platelet responses, but how these platelet signals differe Show more
Platelets must balance hemostatic function with pathological thrombosis, particularly under metabolic stress conditions. MAPKs are central to platelet responses, but how these platelet signals differentially regulate hemostasis remains poorly understood. To investigate the role of Traf2/Nck-interacting kinase (TNIK), we generated megakaryocyte/platelet-specific TNIK knockout mice (Tnikf/fPF4-Cre+) and evaluated platelet function, hemostasis, and thrombosis under normal and hyperlipidemic conditions using chimeric Tnikf/fPF4-Cre+Apoe-/-mice fed high-fat diets. TNIK-deficient mice exhibited prolonged bleeding times, delayed arterial thrombosis and reduced platelet activation under normal conditions, primarily due to impaired dense granule secretion. Mechanistically, TNIK interacted with c-Jun N-terminal kinase interacting protein 1 to promote mixed lineage kinase 3/mitogen-activated protein kinase kinase 4/c-Jun N-terminal kinase pathway activation during hemostatic responses. Surprisingly, under hyperlipidemic conditions, TNIK deficiency accelerated thrombosis and enhanced platelet responses to oxidized low-density lipoprotein. In this context, TNIK specifically bound to protein kinase C ε and suppressed the NADPH oxidase 2/reactive oxygen species/extracellular signal-regulated kinase 5 pathway, thereby inhibiting excessive platelet activation. We conclude that TNIK functions as a molecular switch in platelets, promoting normal hemostasis while simultaneously preventing hyperlipidemia-associated thrombosis through distinct signaling pathways. This dual regulatory mechanism provides insight into how platelets balance hemostatic function with pathological thrombosis risk and identifies TNIK as a potential therapeutic target in metabolic thrombotic disorders. Show less
📄 PDF DOI: 10.1182/bloodadvances.2025017737
APOE
Bin Ma, Jingjing Wang, Mengyuan Zhang +2 more · 2026 · BMC nursing · BioMed Central · added 2026-04-24
To evaluate the current status and latent profiles of caregiver self-care contributions for patients with chronic obstructive pulmonary disease (COPD) and examine the associations between demographic Show more
To evaluate the current status and latent profiles of caregiver self-care contributions for patients with chronic obstructive pulmonary disease (COPD) and examine the associations between demographic characteristics, health literacy, confidence in self-care contributions, family intimacy, and profile membership. We recruited 275 dyads of patients with COPD and their family caregivers from five tertiary hospitals between May and November 2022 using convenience sampling. Latent profile analysis (LPA) was used to identify distinct profiles of caregiver self-care contributions. Univariate analysis and multinomial logistic regression were subsequently conducted to examine associations between participant characteristics and profile membership. LPA identified four distinct profiles of caregiver self-care contributions: low-contributing, under-monitored, maintenance-prioritized, and high-contributing. Significant differences were observed across these profiles in terms of patients' symptom severity, exacerbation frequency, number of hospitalizations, caregivers' education levels, caregiving duration, health literacy, confidence in self-management contributions, and family intimacy using univariate analysis. Multinomial logistic regression analysis revealed that caregivers' education levels, caregiving duration, confidence in self-management contributions, and health literacy were significant predictors of profile membership. Caregiver self-care contributions for patients with COPD can be characterized by four distinct profiles, with caregivers' educational level, health literacy, and confidence in self-management identified as key factors associated with profile membership. Show less
📄 PDF DOI: 10.1186/s12912-026-04503-4
LPA
Xiaochen Qi, Guandu Li, Yuanxin Liu +8 more · 2026 · iScience · Elsevier · added 2026-04-24
Autophagy supports clear cell renal cell carcinoma (ccRCC) progression, yet its upstream regulatory mechanisms remain to be fully defined. Integrating bulk, single-cell, and spatial transcriptomics, w Show more
Autophagy supports clear cell renal cell carcinoma (ccRCC) progression, yet its upstream regulatory mechanisms remain to be fully defined. Integrating bulk, single-cell, and spatial transcriptomics, we identify a regulatory axis wherein the transcription factor ZBED6 activates the expression of the autophagy-initiating kinase PIK3C3 via the repression of IGF2, thereby driving pro-tumorigenic autophagy. Spatial analysis confirms the co-localization of ZBED6 and PIK3C3 in tumor tissues. Using genes associated with this axis, we develop a six-gene prognostic signature that stratifies patients with distinct survival outcomes and differential responses to immunotherapy and targeted therapy. Functional assays show that ZBED6 promotes ccRCC cell proliferation, migration, and invasion. This work elucidates a pathway governing autophagy in ccRCC and provides a framework for prognostic assessment and precision therapy. Show less
no PDF DOI: 10.1016/j.isci.2026.114952
PIK3C3
Dan Jiang, Yi-Ling Liu, Jian Liu +7 more · 2026 · Lipids in health and disease · BioMed Central · added 2026-04-24
Calcific aortic valve disease (CAVD) is a cardiovascular disease closely associated with aging. The role of lipoprotein(a) [Lp(a)] has attracted considerable attention in recent years. However, limite Show more
Calcific aortic valve disease (CAVD) is a cardiovascular disease closely associated with aging. The role of lipoprotein(a) [Lp(a)] has attracted considerable attention in recent years. However, limited research has simultaneously explored the relationships between Lp(a), age, and CAVD. This study sought to assess the relationship linking Lp(a), time-weighted Lp(a), and CAVD. A total of 5,156 inpatients with comprehensive clinical data were recruited for this study. The associations of Lp(a) and time-weighted Lp(a) with CAVD were examined via multivariate logistic regression analysis, alongside the application of restricted cubic spline analysis. The diagnostic utility of Lp(a) and time-weighted Lp(a) for CAVD was assessed by constructing receiver operating characteristic (ROC) curves. CAVD prevalence rose with age, whereas the rate of increase diminished with advancing age. The average Lp(a) level in the young populations with CAVD was more than twice that in the No-CAVD group, particularly among those aged 55 years or younger. The prevalence of CAVD in non-elderly populations was markedly 2–4 fold greater in the higher Lp(a) group (> 30 mg/dL) than in the lower Lp(a) group (≤ 30 mg/dL). Multivariate adjusted odds ratios ‌(ORs) for CAVD increased with advancing Lp(a) or age. Time-weighted Lp(a), which takes into account both age and Lp(a), was more strongly linked to elevated CAVD risk than Lp(a) alone. Time-weighted Lp(a) enhanced the diagnostic value of CAVD, improving both sensitivity and specificity. The risk of CAVD is strongly associated with both age and elevated Lp(a) levels. Time-weighted Lp(a), which integrates these factors, serves as a superior indicator that better captures cumulative long-term Lp(a) variation and yields stronger CAVD risk stratification. The online version contains supplementary material available at 10.1186/s12944-026-02884-8. Show less
📄 PDF DOI: 10.1186/s12944-026-02884-8
LPA
Zi-Han Lin, Zhaohui Wang, FenFen Wei +5 more · 2026 · Food research international (Ottawa, Ont.) · Elsevier · added 2026-04-24
Long-term alcohol consumption drives systemic damage through metabolites such as acetaldehyde, which trigger oxidative stress, inflammation, and gut dysbiosis. This study evaluated the protective effe Show more
Long-term alcohol consumption drives systemic damage through metabolites such as acetaldehyde, which trigger oxidative stress, inflammation, and gut dysbiosis. This study evaluated the protective effects of fermented red quinoa (FRQ) in an alcohol-exposed mouse model, with a focus on cognitive function. Male C57BL/6J mice were randomized into three groups for a 28-day study: a normal control, an alcohol-treated group gavaged with ethanol (1 mL/100 g·BW), and a group receiving the same ethanol dose co-administered with FRQ powder (human equivalent dose: 9 g/60 kg·BW). Our results demonstrated that fermentation with Lactobacillus kisonensis significantly increased the content of phenolic compounds (e.g., quercetin and veratric acid) in FRQ. FRQ intervention improved cognitive function, ameliorated synaptic structural impairment and blood-brain barrier disruption, and attenuated hepatic steatosis. The protective mechanisms involved three pathways: 1) The specific phenolic compounds in FRQ promoted alcohol metabolism by regulating ADH/ALDH activity, leading to reduced acetaldehyde levels. As a primary initiating pathway, this metabolic enhancement dominantly attenuated subsequent oxidative stress and inflammation, mitigating injury in the liver, brain, and colon. 2) It directly modulated AP-1 subunits (ΔFOSB/JUND), restored BDNF, and rebalanced the glutamate/GABA systems. 3) It regulated the gut-liver-brain axis by remodeling the gut microbiota (e.g., enriching butyrate-producing Butyricicoccus), reinforcing intestinal barrier integrity, and thereby suppressing systemic LPS translocation and inflammation. In conclusion, FRQ mitigates alcohol-induced cognitive and hepatic damage via multiple mechanisms, highlighting its promise as an integrative dietary intervention. Show less
no PDF DOI: 10.1016/j.foodres.2026.118547
BDNF alcohol consumption alcohol-induced cognitive impairment cognitive function fermented food gut dysbiosis hepatic steatosis inflammation
Tingting Chen, Hongxia He, Fei Huang +3 more · 2026 · PloS one · PLOS · added 2026-04-24
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor Show more
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor (GABAAR) signaling contributes to ICH-induced neurotoxicity, presenting a promising therapeutic target. To assess the neurorestorative effects of the GABAAR α1-selective partial positive allosteric modulator (PAM) CL218872 and the α5-selective negative allosteric modulator (NAM) MRK-016 on synaptic plasticity and neural repair following ICH. An ICH mouse model was constructed using collagenase IV, and ICH mice were administered the GABAAR modulators CL218872 or MRK-016. Differences in inflammation and neurological deficit score were compared between different groups of mice. Morphologic and functional changes in mouse neuronal cells were next determined by Nissl and Golgi-Cox staining. Synaptic structural changes in ICH mice were visualized by transmission electron microscopy, and changes in synaptic plasticity-related molecules were quantified to assess the effects of GABAAR modulators on synapses in ICH mice. Treatment with CL218872 resulted in a reduction in hemorrhage and improved neurobehavioral outcomes in ICH mice. Additionally, CL218872 mitigated inflammation by downregulating phospho-p65, IL-6 and TNF-α expression. Histological analysis revealed an increase in neuronal density, preservation of cell morphology, and enhanced synaptic connectivity following CL218872 treatment. Furthermore, synaptic structure was restored, and there was an upregulation of brain-derived neurotrophic factor (BDNF), growth-associated protein-43 (GAP-43), postsynaptic density protein 95 (PSD-95), and synaptophysin in ICH mice. However, treatment with MRK-016 yielded the opposite result. The GABAAR α1-selective PAM CL218872 exerts neuroprotective and neurorestorative effects in ICH, suggesting its therapeutic potential for ICH management. Show less
📄 PDF DOI: 10.1371/journal.pone.0345025
BDNF
Jianming Xu, Yuelan Gao, Jun Yu +6 more · 2026 · Investigative ophthalmology & visual science · added 2026-04-24
To identify plasma proteins associated with glaucoma and assess the translational potential of key proteins as both biomarkers and therapeutic targets. Genome-wide association study data were obtained Show more
To identify plasma proteins associated with glaucoma and assess the translational potential of key proteins as both biomarkers and therapeutic targets. Genome-wide association study data were obtained from the UK Biobank Pharma Proteomics Project, FinnGen, and the Million Veteran Program. We used a four-stage analytical framework: Stage 1 applied Mendelian randomization and Bayesian colocalization to evaluate associations between 2923 plasma proteins and glaucoma; Stage 2 used summary-based Mendelian randomization to explore transcriptomic and epigenomic associations of the identified proteins with glaucoma risk; Stage 3 involved a prospective association analysis of protein levels and incident glaucoma in the UK Biobank cohort, including 40,170 glaucoma-free participants; and Stage 4 systematically evaluated the druggability of the prioritized protein targets. We identified 26 plasma proteins with putative causal associations with glaucoma, six of which were novel: COL24A1, KAZALD1, EBAG9, CSNK1D, AZI2, and AXIN1. COL24A1 (odds ratio [OR] = 0.85; 95% confidence interval [CI], 0.80-0.90; PFDR < 0.001; PP.H4 = 0.95) and EFEMP1 (OR = 0.88; 95% CI, 0.83-0.92; PFDR < 0.001; PP.H4 = 0.98) emerged as the most compelling candidates. To further elucidate the regulatory mechanisms, multiomics analyses indicated that epigenetic modifications and alternative splicing events affecting these genes were associated with elevated glaucoma risk. Notably, EFEMP1 was significantly associated with glaucoma incidence in the prospective cohort analysis (fully adjusted Cox model: hazard ratio = 1.61; 95% CI, 1.29-2.00; PFDR = 0.002), demonstrating strong predictive performance (C-index = 0.811, area under the curve = 0.806) and representing a promising therapeutic target. Our findings provide new insights into the proteomic basis of glaucoma and highlight promising opportunities for developing targeted therapies. Show less
📄 PDF DOI: 10.1167/iovs.67.2.4
AXIN1
Yongmei Wu, Wenjing Xia, Yang Yang +18 more · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroup Show more
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroups, risk factors, and symptom-level interactions underlying depression-anxiety comorbidity across adolescents and adults in multi-ethnic Southwest China. The study included a total of 41,394 adolescents (aged 9-19) and 17,345 adults (aged 18-80). Adolescents were recruited using multistage stratified cluster sampling, whereas adults were recruited by convenience sampling. All participants completed a self-designed sociodemographic questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). Latent profile analysis identified subgroups, logistic regression analyzed risk/protective factors, and network analysis mapped symptom interactions and bridge nodes. This study found that three adolescent profiles emerged: high (11.66 %), moderate (31.95 %), and low/no depression-anxiety (56.39 %). Adults were classified into low/no comorbidity (90.63 %) and comorbid depression-anxiety (9.37 %). Risk factors for adolescents included female gender (OR = 2.77, 95 %CI: 2.55-3.00; OR = 1.59, 95 %CI: 1.52-1.67), higher grade levels (OR = 3.45, 95 %CI: 3.10-3.84; OR = 3.56, 95 %CI: 3.33-3.80), smoking (OR = 1.72, 95 %CI: 1.51-1.96; OR = 1.28, 95 %CI: 1.17-1.41),drinking (OR = 2.45, 95 %CI: 2.23-2.70; OR = 1.66, 95 %CI: 1.55-1.77), family instability (OR = 1.16, 95 %CI: 1.02-1.31; OR = 1.33, 95 %CI: 1.14-1.56) and "other" ethnic minority (OR = 1.15, 95 %CI: 1.04-1.26). For adults, female gender(OR = 1.68; 95 %CI: 1.44-1.97), living alone(OR = 1.37; 95 %CI: 1.14-1.65), poor self-rated health (OR = 0.13, 95 %CI: 0.11-0.15), and Dai ethnicity (OR = 0.70, 95 %CI: 0.49-0.96) predicted comorbidity. Network analysis revealed distinct bridge symptoms: adolescents in the high depression-anxiety group had five symptoms: depressed or sad mood (phq2), psychomotor agitation/retardation (phq8), nervousness or anxiety (gad1), restlessness (gad5), and irritable (gad6); however, adults with comorbidity had one symptom: afraid something will happen (gad7). This study identified three patterns of depression-anxiety comorbidity in adolescents and two in adults. Efforts should prioritize adolescents from "other" ethnic minorities, strengthening family and peer support, as well as smoking and drinking interventions for adolescents, and addressing social isolation, physical health, and catastrophizing cognition in adults may mitigate the comorbidity burden. Show less
no PDF DOI: 10.1016/j.jad.2025.121112
LPA
Nan Zhang, Cui Wang, Yuling Ga +11 more · 2026 · BMC geriatrics · BioMed Central · added 2026-04-24
Geriatric depression affects 12.95-28.4% of adults aged ≥ 60, yet treatment rates remain critically low globally. Lifestyle factors, particularly exercise and sleep demonstrate therapeutic potential, Show more
Geriatric depression affects 12.95-28.4% of adults aged ≥ 60, yet treatment rates remain critically low globally. Lifestyle factors, particularly exercise and sleep demonstrate therapeutic potential, integrated interventions may exert synergistic effects on geriatric depression, though such interventions remain scarce. The Geriatric Exercise-Sleep Optimization (GESO) project aims to evaluate the clinical efficacy and cost-effectiveness of a combined exercise and sleep health intervention in alleviating depressive symptoms among community-dwelling older adults with depression, and exploring the potential underlying mechanisms. This is a stepped-wedge cluster-randomized trial (SW-CRT). A 12-week integrated exercise and sleep intervention will be implemented to all eligible participants during the study period. The primary aim is to evaluate the clinical efficacy in alleviating depressive symptoms. Secondary aims are to evaluate the additional health outcomes (i.e., quality of life, physical activity level, daily step count, sleep quality, and anxiety symptom), cost-effectiveness, and potential mechanisms. Costs will be aggregated and analyzed for economic evaluation. Costs will be aggregated and analyzed for economic evaluation. Salivary measured BDNF and irisin levels, and EEG-based brain function connectivity will be collected to assess potential intervention mechanisms. Mixed-effect linear regression models will be used to evaluate the effects of the integrated exercise-sleep intervention on primary and secondary outcomes. This study is expected to provide an effective and practical mode for an integrated exercise and sleep intervention among community-dwelling older adults with depression. Intended outcomes of the trial will facilitate changes in best practice to improve outcomes for this population.Trial registration Chinese Clinical Trail Registry ChiCTR2500107641, Registration date: 15 August 2025. Show less
📄 PDF DOI: 10.1186/s12877-026-07071-z
BDNF
Chunlong Wang, Yulong Hu, Junfei Chen +1 more · 2026 · Frontiers in physiology · Frontiers · added 2026-04-24
This study investigated the effects of high-intensity intermittent training (HIIT) Forty male Sprague-Dawley rats were randomly divided into two groups: standard diet (C, n = 10) and high-fat diet (HF Show more
This study investigated the effects of high-intensity intermittent training (HIIT) Forty male Sprague-Dawley rats were randomly divided into two groups: standard diet (C, n = 10) and high-fat diet (HFD, n = 30). After 8 weeks of HFD feeding, 24 obese rats were further randomised into three subgroups: HFD (H, n = 8), HFD + moderate-intensity training (HMT, n = 8), and HFD + HIIT (HHT, n = 8). The HMT and HHT groups underwent 8 week training interventions (six sessions/week). The HMT protocol included a 10 min warm-up (treadmill speed: 10 m/min), a 40 min moderate-intensity aerobic phase (60%-70% of maximum speed), and a 10 min recovery (10 m/min). The HHT protocol featured 10 min warm-up and recovery phases (10 m/min), with 40 min of alternating treadmill training: 3 min at 50% maximum speed followed by 3 min at 90% maximum speed. No significant differences in body weight were observed between the HHT and HMT groups. HHT rats displayed significantly lower plasma triglyceride levels than H and HMT rats. Compared with HMT, HHT reduced adipose mass and adipocyte size and increased mitochondrial succinate dehydrogenase and cytochrome c oxidase (COX) activities in adipose tissue. However, HHT rats displayed lower COX activity in visceral white adipose tissue than HMT rats. Training upregulated browning-related genes and uncoupling protein 1 (UCP1) in adipose tissue, with stronger effects in HHT than in HMT. Plasma and adipose tissue IL-27 levels, as well as p38 MAPK-PGC-1α signalling pathway activation, were significantly elevated in both training groups, with greater increases in HHT. HIIT promotes adipose tissue browning by activating the IL-27 signalling pathway and ameliorates obesity-associated metabolic disorders more effectively than MAIT, supporting its potential as a therapeutic strategy for obesity. Show less
📄 PDF DOI: 10.3389/fphys.2026.1745363
IL27
Ming Chen, Yuchi Zhang, Jingying Xu +7 more · 2026 · Biophysical chemistry · Elsevier · added 2026-04-24
Current in vitro enzyme inhibition assays often involve subjective data analysis based on the researcher's experience. In this study, we developed a multi-dimensional quantitative integration platform Show more
Current in vitro enzyme inhibition assays often involve subjective data analysis based on the researcher's experience. In this study, we developed a multi-dimensional quantitative integration platform (MDQIP) that uses a model to objectively calculate and rank compound activities, addressing the limitations of traditional "experience-driven" evaluations, accelerates the screening and evaluation of potential AChE inhibitors from Red Gastrodia elata, offering a more efficient approach to drug discovery. Ultrafiltration-LC screening identified parishin A as having the most stable binding, with binding degree and recovery rates of 98.85% and 99.39%, respectively. Molecular docking revealed that parishins A and C were the strongest AChE inhibitors, exhibiting stable binding through hydrogen bonds, π-alkyl, and π-π interactions. Molecular dynamics simulations confirmed the stability of these compounds, with binding energies of -82.65 ± 4.24 and - 80.69 ± 4.19 kcal/mol. Enzyme kinetics showed that parishins A and C are mixed-type inhibitors, with IC Show less
no PDF DOI: 10.1016/j.bpc.2026.107617
BACE1
Ting Gao, Kang-Peng Zhong, Jun-Zhuo Wang +2 more · 2026 · World journal of gastroenterology · added 2026-04-24
Prior studies indicate that allyl isothiocyanate (AITC) alleviates metabolic dysfunction-associated steatotic liver disease (MASLD). The vitamin D receptor (VDR) is known to exert protective effects i Show more
Prior studies indicate that allyl isothiocyanate (AITC) alleviates metabolic dysfunction-associated steatotic liver disease (MASLD). The vitamin D receptor (VDR) is known to exert protective effects in MASLD; however, whether AITC alleviates MASLD through VDR remains unclear. To clarify the function and underlying mechanisms of AITC in MASLD AML-12 cells were exposed to 300 μM palmitate acid (PA) for 24 hours to establish an To establish an AITC provides a robust molecular basis for improving MASLD by activating hepatic VDR and driving the downstream HNF-4α/MTTP/ApoB signaling pathway. This pathway reduces hepatic lipid accumulation, promotes FA β-oxidation, and improves insulin resistance, establishing AITC as a promising treatment for MASLD. Show less
📄 PDF DOI: 10.3748/wjg.v32.i4.113647
APOB
Xuesong Yang, Fan Jiang, Yanqiong Wu +2 more · 2026 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Neuropathic pain (NP) frequently co-occurs with depression (DP), exhibiting complex pathogenesis and limited clinical treatment options. This study aims to investigate the efficacy of Eupalinolide B ( Show more
Neuropathic pain (NP) frequently co-occurs with depression (DP), exhibiting complex pathogenesis and limited clinical treatment options. This study aims to investigate the efficacy of Eupalinolide B (EB) in alleviating NP co-occurring with DP and its potential molecular mechanisms. Combining network pharmacology, molecular docking, and molecular dynamics simulations to screen potential targets for EB, validated through transcriptomic data. Using a sciatic nerve branch-preserving injury (SNI) mouse model, we assessed pain and depression-like behaviors through von Frey testing, hot plate testing, tail suspension testing, forced swimming testing, and open field testing. Concurrently, Western blotting, immunofluorescence, and Nissl staining were employed to analyze relevant molecules and neuropathological alterations. Network pharmacology and bioinformatics analysis identified EGFR, PTGS2, and JUN as the key targets for EB in treating NP combined with DP. Behavioral studies showed that 20 mg/kg of EB significantly alleviated pain in SNI mice and improved depressive-like behaviors. Mechanism research indicated that EB downregulated the expression of EGFR and PTGS2, inhibited the activation of microglia and astrocytes, and reduced neuronal damage. Additionally, EB could upregulate the expression of synaptic proteins (PSD95, SYN1, and BDNF) in the hippocampus. EB alleviates neuroinflammation by reducing EGFR and PTGS2 protein expression, modulates synaptic plasticity, and improves pain-depression comorbidity. EB may represent a promising therapeutic approach for pain-related depression. Show less
📄 PDF DOI: 10.1002/cns.70872
BDNF
Ying Zhang, Zhouting Tuo, Yuan Lin +10 more · 2026 · Cancer research · added 2026-04-24
Cancer-associated fibroblasts (CAF) are abundant stromal cells in the tumor microenvironment (TME) that play a vital role in promoting tumor progression and drug resistance. The mechanisms regulating Show more
Cancer-associated fibroblasts (CAF) are abundant stromal cells in the tumor microenvironment (TME) that play a vital role in promoting tumor progression and drug resistance. The mechanisms regulating heterogeneity of CAFs in renal cell carcinoma (RCC) could represent potential targets for reprogramming the TME. In this study, we conducted single-cell RNA sequence and flow cytometry analyses that identified a CAF subset overexpressing apolipoprotein E (ApoE), which was correlated with poor survival in patients with RCC. Mechanistically, NRF1 activation in CAFs induced formation of ApoEhigh CAFs and secretion of NRG1. ApoEhigh CAFs potentiated stemness properties in the surrounding RCC cells by secreting NRG1 and subsequently activating the HER2/NF-κB pathway. Interfering with NRG1 expression or inhibiting NF-κB signaling reduced ApoEhigh CAF-induced stemness of RCC cells. Furthermore, neutralizing NRG1 enhanced the efficacy of sunitinib in RCC models in vivo. Together, these findings highlight targeting the tumor-promoting functions of ApoEhigh CAFs as a promising approach for treating advanced RCC. NRF1 drives formation of ApoEhigh cancer-associated fibroblasts that secrete NRG1 to stimulate stemness of renal cell carcinoma, revealing a stromal-mediated mechanism that can be inhibited to improve treatment of advanced kidney cancer. Show less
no PDF DOI: 10.1158/0008-5472.CAN-25-0959
APOE
Shasha Zhu, Qiuhui Xu, Yihan Wang +4 more · 2026 · Molecular nutrition & food research · Wiley · added 2026-04-24
Dietary protocatechuic acid (PCA) inhibits atherosclerosis development in male ApoE-/- mice. However, its anti-atherosclerotic property in genetically unmodified (wild-type) male or female mice remain Show more
Dietary protocatechuic acid (PCA) inhibits atherosclerosis development in male ApoE-/- mice. However, its anti-atherosclerotic property in genetically unmodified (wild-type) male or female mice remains unknown.Five-week-old C57BL/6J mice (half males and females) were divided into negative (fed a chow diet), positive (fed an atherogenic diet), or 5, 25, 50, 100, or 200 mg/kg BW/d of PCA (fed an atherogenic diet) groups. Oral gavage with PCA between 25-100 mg/kg BW/d for 25 weeks significantly attenuated atherogenic diet-induced plaque formation in a dose-dependent manner, whereas the anti-atherosclerotic efficiency of 200 mg/kg BW/d of PCA was comparable with that of 50 mg/kg BW/d. PCA did not affect serum lipids (total triglyceride, total cholesterol, HDL cholesterol), pro-inflammatory cytokines (tumor necrosis factor alpha, IL-1b, IL-6), oxidized LDL, and total antioxidant capacity, and acetylcholine or sodium nitroprusside-induced aortic relaxation. Instead, PCA (≥25 mg/kg BW/d) reduced macrophage accumulation and content of tumor necrosis factor alpha, superoxide, and 4-hydroxynonenal within plaques, and inhibited monocyte adhesion to aortic endothelium in both male and female mice.PCA inhibits early atherosclerosis formation in both male and female C57BL/6J mice with a "U-shaped" dose-response relationship, possibly by reducing inflammation burden and oxidative stress within atherosclerotic plaques. Show less
no PDF DOI: 10.1002/mnfr.70447
APOE
Shoupei Liu, Xiangting Cao, Haibin Wu +7 more · 2026 · Stem cells (Dayton, Ohio) · Oxford University Press · added 2026-04-24
Human embryonic stem cell (hESC)-derived hepatocytes (hEHs) display functional deficits, particularly impaired albumin secretion and ammonia metabolism, compared to primary human hepatocytes (PHHs). H Show more
Human embryonic stem cell (hESC)-derived hepatocytes (hEHs) display functional deficits, particularly impaired albumin secretion and ammonia metabolism, compared to primary human hepatocytes (PHHs). Here, we investigated the regulatory role of CCAAT/enhancer-binding protein beta (C/EBPβ) in hepatocyte maturation. Forced C/EBPβ expression enhanced hepatocyte functionality and upregulated hepatocyte-specific genes, while suppressing epithelial-mesenchymal transition (EMT) via downregulating canonical EMT markers. Mechanistically, CUT&Tag and luciferase reporter assays confirmed C/EBPβ directly binds to the promoter regions of CDH1 (E-cadherin) and CPS1 (carbamoyl phosphate synthetase 1). Co-immunoprecipitation identified an interaction between C/EBPβ and the MAPK pathway. RNA interference combined with Western blot analysis revealed that MAPK1-mediated phosphorylation of C/EBPβ at Thr-235 augmented its transactivation activity, accelerating hepatocyte maturation. Our findings establish C/EBPβ as a master regulator that coordinates transcriptional networks and post-translational modifications during hEHs maturation, providing novel insights for generating mature hepatocytes for disease modeling and regenerative medicine applications. The transcriptional activity of C/EBPβ is regulated by MAPK1 protein within the ERK/MAPK signaling pathway. MAPK1 moves from the cytoplasm into the nucleus and transfers phosphate groups to C/EBPβ. This process reverses the "self-inhibition" state of C/EBPβ and enhances its transcriptional activity on downstream target genes. Show less
no PDF DOI: 10.1093/stmcls/sxag016
CPS1
Yongqi Huang, Huimin Xiong, Xia Tian +4 more · 2026 · Asia-Pacific journal of oncology nursing · Elsevier · added 2026-04-24
This study aims to identify the latent profiles of sense of coherence (SOC) in patients with advanced cancer and explore its influencing factors encompassing sociodemographic and clinical characterist Show more
This study aims to identify the latent profiles of sense of coherence (SOC) in patients with advanced cancer and explore its influencing factors encompassing sociodemographic and clinical characteristics, and generalized resistance resources (GRRs). A cross-sectional study of 262 patients with advanced cancer was conducted by convenience sampling in Guangzhou, China, from September 2023 to July 2024. Data were collected including sociodemographic and clinical characteristics, SOC-13, Revised Life Orientation Test (LOT-R), Rosenberg Self-Esteem Scale (RSES), Inner Peace State Scale (IPSS), Gratitude Questionnaire-6 (GQ-6), and Social Support Rating Scale (SSRS). Statistical analysis was performed using latent profile analysis (LPA) and multivariate logistic regression analysis. Three latent profiles of SOC were identified: low SOC and low comprehensibility group (29.01%), moderate SOC and high meaningfulness group (40.08%), and high SOC and high manageability group (30.91%). This study found that SOC was impacted by self-perceived severity of the disease and GRRs including optimism, self-esteem, and inner peace ( SOC in patients with advanced cancer exhibited different characteristics. Enhancing positive disease perception and GRRs including optimism, self-esteem, and inner peace may be effective strategies for improving their SOC. Healthcare professionals can formulate strategies such as tailored health education, symptom management, and positive psychological interventions to enhance SOC in patients with advanced cancer. Show less
📄 PDF DOI: 10.1016/j.apjon.2025.100848
LPA
Jing Zhang, Yi-Heng Li, Jin-Jing Zhang +4 more · 2026 · Brain research bulletin · Elsevier · added 2026-04-24
Retigabine (RTG) shows notable neuroprotective efficacy in multiple brain injury models; however, its interplay with endoplasmic reticulum stress (ERS) is poorly understood. This study was designed to Show more
Retigabine (RTG) shows notable neuroprotective efficacy in multiple brain injury models; however, its interplay with endoplasmic reticulum stress (ERS) is poorly understood. This study was designed to explore the therapeutic potential of RTG against CRS-induced depression-like behaviors and cognitive deficits in mice and to uncover the associated molecular mechanisms. A depression-like and cognitive impairment model was established in C57BL/6 male mice using chronic restraint stress (CRS). Six-week-old C57BL/6 male mice were randomly assigned to the following groups: control (Con), model (CRS), RTG (10 mg/kg), XE-991 (2 mg/kg) or tunicamycin (Tm, 2 mg/kg). Behavioral tests were conducted to assess depression-like behaviors and cognitive function. Hippocampal neuronal morphology was examined by H&E and immunofluorescence staining, while changes in endoplasmic reticulum stress (ERS)-related signaling pathways were analyzed by Western blot. Retigabine treatment reduced hippocampal neuronal damage and the expression of ERS-related factors (GRP78, CHOP) and the pro-apoptotic factor BAX in CRS-induced mice, while it increased the levels of BDNF. These effects were antagonized by XE-991 and the ERS agonist tunicamycin (Tm). Retigabine may alleviate CRS-induced depressive-like behaviors and cognitive impairment by inhibiting ERS-mediated apoptosis, suggesting its potential as a novel therapeutic strategy for depression. Show less
no PDF DOI: 10.1016/j.brainresbull.2026.111798
BDNF apoptosis behaviors cognitive impairment depression endoplasmic reticulum stress neuroprotection stress
Ting Li, Ke Chen · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Internalizing and externalizing behavior problems co-occur frequently and there is heterogeneity in the co-occurrence of such symptoms; however, few studies have explored this heterogeneity and its de Show more
Internalizing and externalizing behavior problems co-occur frequently and there is heterogeneity in the co-occurrence of such symptoms; however, few studies have explored this heterogeneity and its developmental mechanisms from a person-centered perspective. The primary aim of this study is to employ Latent Profile Analysis (LPA) and Latent Transition Analysis (LTA)-person-centered statistical approaches-to explore this underlying heterogeneity, uncover its dynamic developmental trajectories, and further examine the key factors that influence class membership and transitions. A sample of 2232 Chinese college students from three universities in Chongqing was assessed at two time points spaced ten months apart. Latent Profile Analysis (LPA) and Latent Transition Analysis (LTA) were conducted on measures of internalizing and externalizing problems. LPA revealed three distinct profiles for both internalizing problems ("Low-Risk/Well-Adapted", "Moderate-Risk/Affective-Distress", "High-Risk/Comorbid") and externalizing problems ("Well-Adapted", "Adaptation Difficulties", "Maladaptive") at T1, with similar structures at T2. LTA indicated high stability for the low- and high-risk internalizing profiles, but significant fluidity in the middle, with nearly half of the moderate-risk group transitioning to the high-risk profile. For externalizing problems, there was a pronounced shift toward the "Maladaptive" profile over time. Negative parental rearing and PWU were significant risk factors for adverse transitions, while positive parenting, self-transcendence values, and objective social support served as protective factors. Co-occurring internalizing and externalizing problems among Chinese college students are heterogeneous and dynamic. The moderate-risk group represents a critical target for early intervention. Modifiable ecological factors across family, individual, and technological domains significantly predict longitudinal trajectories, informing targeted prevention strategies. Show less
no PDF DOI: 10.1016/j.jad.2025.120957
LPA