👤 Li-Zhen 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, Jiujiu Chen, Shin-Wen Chen, Guangping Chen, Dapeng Chen, Ximei Chen, Renwei Chen, Jianfei Chen, Yulu Chen, Yu-Chi Chen, Jia-De Chen, Rongfang Chen, She Chen, Zetian Chen, Tianran Chen, Emily Chen, Baoxiang Chen, Ya-Chun Chen, Dongxue Chen, Wei-xian Chen, Danmei Chen, Ceshi Chen, Junling Chen, Xia Chen, Daoyuan Chen, Yongbin Chen, Chi-Yu Chen, Dian Chen, Xiuxiu Chen, Bo-Fang Chen, Fangyuan Chen, Jin-An Chen, Xiaojuan Chen, Zhuohui Chen, Junqi Chen, Lina Chen, Fangfang Chen, Hanwen Chen, Yilei Chen, Po-Han Chen, Xiaoxiang Chen, Jimei Chen, Guochong Chen, Yanyun Chen, Yifei Chen, Cheng-Yu Chen, Zi-Jiang Chen, Jiayuan Chen, Miaoran Chen, Junshi Chen, Yu-Ying Chen, Pengxiang Chen, Hui-Ru Chen, Yupeng Chen, Ida Y-D Chen, Xiaofeng Chen, Qiqi Chen, Shengnan Chen, Mao-Yuan Chen, Lizhu Chen, Weichan Chen, Xiang-Bin Chen, Hanxi Chen, Sulian Chen, Zoe Chen, Minghong Chen, Chi Chen, Yananlan Chen, Yanzhu Chen, Shiyi Chen, Ze-Xu Chen, Zhiheng Chen, Jia-Mei Chen, Shuqin Chen, Yi-Hau Chen, Danni Chen, Donglong Chen, Xiaomeng Chen, Yidong Chen, Keyu Chen, Hao Chen, Junmin Chen, Wenlong Chen, Yufei Chen, Wanbiao Chen, Mo Chen, Youjia Chen, Xin-Jie Chen, Lanlan Chen, Huapu Chen, Shuaiyin Chen, Jing-Hsien Chen, Hengsheng Chen, Bing-Bing Chen, Fa-Xi Chen, Zhiqiang Chen, Ming-Huang Chen, Liangkai Chen, Li-Jhen Chen, Zhi-Hao Chen, Yinzhu Chen, Guanghong Chen, Gaozhi Chen, Jiakang Chen, Yongke Chen, Guangquan Chen, Li-Hsien Chen, Yiduo Chen, Zongnan Chen, Jing Chen, Meilan Chen, Jin-Shuen Chen, Huanxiong Chen, Yann-Jang Chen, Guozhong Chen, Yu-Bing Chen, Xiaobin Chen, Catherine Qing Chen, Youhu Chen, Hui Mei Chen, L F Chen, Haiyang Chen, Ruilin Chen, Peng Chen, Kailang Chen, Chao Chen, Suipeng Chen, Zemin Chen, Jianlin Chen, Shang-Chih Chen, Yen-Hsieh Chen, Jia-Lin Chen, Chaojin Chen, Minglang Chen, Xiatian Chen, Zeyu Chen, Kang Chen, Mei-Chi Chen, Jihai Chen, Pei Chen, Defang Chen, Zhao Chen, Tianrui Chen, Tingtao Chen, Caressa Chen, Jiwei Chen, Xuerong Chen, Yizhi Chen, XueShu Chen, Mingyue Chen, Huichao Chen, Chun-Chi Chen, Xiaomin Chen, Hetian Chen, Yuxing Chen, Jie-Hua Chen, Chuck T Chen, Yuanjia Chen, Hong Chen, Jianxiong Chen, S Chen, D M Chen, Jiao-Jiao Chen, Gongbo Chen, Xufeng Chen, Xiao-Jun Chen, Harn-Shen Chen, Qiu Jing Chen, Tai-Heng Chen, Pei-Lung Chen, Kaifu Chen, Huang-Pin Chen, Tse-Wei Chen, Yanrong Chen, Xianfeng Chen, Chung-Yung Chen, Yuelei Chen, Qili Chen, Guanren Chen, TsungYen Chen, Yu-Si Chen, Junsheng Chen, Min-Jie Chen, Xin-Ming Chen, Jiabing Chen, Sili Chen, Qinying Chen, Yue Chen, Lin Chen, Xiaoli Chen, Zhuo Chen, Aoshuang Chen, Junyu Chen, Chunji Chen, Yian Chen, Shanchun Chen, Shuen-Ei Chen, Canrong Chen, Shih-Jen Chen, Yaowu Chen, Han Chen, Yih-Chieh Chen, Wei-Cong Chen, Yanfen Chen, Tao Chen, Huangtao Chen, Jingyi Chen, Sheng Chen, Jing-Wen Chen, Gao Chen, Lei-Lei Chen, Kecai Chen, Yao-Shen Chen, Haiyu Chen, W Chen, Xiaona Chen, Cheng-Sheng Chen, X R Chen, Shuangfeng Chen, Jingyuan Chen, Xinyuan Chen, Huanhuan Chen, Mengling Chen, Liang-Kung Chen, Ming-Huei Chen, Hongshan Chen, Cuncun Chen, Qingchao Chen, Yanzi Chen, Lingli Chen, Shiqian Chen, Liangwan Chen, Lexia Chen, Wei-Ting Chen, Zhencong Chen, Tzy-Yen Chen, Mingcong Chen, Honglei Chen, Yuyan Chen, Huachen Chen, Yu Chen, Li-Juan Chen, Aozhou Chen, Xinlin Chen, Wai Chen, Dake Chen, Bo-Sheng Chen, Meilin Chen, Kequan Chen, Hong Yang Chen, Yan Chen, Bowei Chen, Silian Chen, Jian Chen, Yongmei Chen, Ling Chen, Jinbo Chen, Yingxi Chen, Ge Chen, Max Jl Chen, C Z Chen, Weitao Chen, Xiaole L Chen, Yonglu Chen, Shih-Pin Chen, Jiani Chen, Huiru Chen, San-Yuan Chen, Bing Chen, Xiao-ping Chen, Feiyue Chen, Shuchun Chen, Zhaolin Chen, Qianxue Chen, Xiaoyang Chen, Bowang Chen, Yinghui Chen, Ting-Ting Chen, Xiao-Yang Chen, Chi-Yuan Chen, Zhi-zhe Chen, Ting-Tao Chen, Xiaoyun Chen, Min-Hsuan Chen, Kuan-Ting Chen, Yongheng Chen, Wenhao Chen, Shengyu Chen, Kai Chen, Yueh-Peng Chen, Guangju Chen, Minghua Chen, Hong-Sheng Chen, Qingmei Chen, Song-Mei Chen, Limei Chen, Yuqi Chen, Yuyang Chen, Yang-Ching Chen, Yu-Gen Chen, Peizhan Chen, Rucheng Chen, Jin-Xia Chen, Szu-Chieh Chen, Xiaojun Chen, Jialing Chen, Heni Chen, Yi Feng Chen, Sen Chen, Alice Ye A Chen, Wen Chen, Han-Chun Chen, Dawei Chen, Fangli Chen, Ai-Qun Chen, Zhaojun Chen, Gong Chen, Yishan Chen, Zhijing Chen, Qiuxuan Chen, Miao-Der Chen, Fengwu Chen, Weijie Chen, Weixin Chen, Mei-Ling Chen, Hung-Po Chen, Rui-Pei Chen, Nian-Ping Chen, Tielin Chen, Canyu Chen, Xiaotao Chen, Nan Chen, C Chen, Juanjuan Chen, Xinan Chen, Jiaping Chen, Xiao-Lin Chen, Jianping Chen, Yayun Chen, Le Qi Chen, Jen-Sue Chen, Mechi Chen, Miao-Yu Chen, Zhou Chen, Szu-Han Chen, Zhen Bouman Chen, Baihua Chen, Qingao Chen, Shao-Ke Chen, Feng Chen, Jiawen Chen, Lianmin Chen, Sifeng Chen, Mengxia Chen, Xueli Chen, Can Chen, Yibo Chen, Zinan Chen, Lei-Chin Chen, Carol Chen, Yanlin Chen, Zihang Chen, Zaozao Chen, Haiqin Chen, Lu Hua Chen, Zhiyuan Chen, Meiyu Chen, Du-Qun Chen, Keying Chen, Naifei Chen, Peixian Chen, Jin-Ran Chen, Yijun Chen, Yulin Chen, Fumei Chen, Zhanfei Chen, Zhe-Yu Chen, Xin-Qi Chen, Valerie Chen, Ru Chen, Mengqing Chen, Runsheng Chen, Tong Chen, Tan-Zhou Chen, Suet Nee Chen, Cuicui Chen, Yifan Chen, Tian Chen, XiangFan Chen, Lingyi Chen, Hsiao-Yun Chen, Kenneth L Chen, Ni Chen, Huishan Chen, Fang-Yu Chen, Ken Chen, Yongshen Chen, Qiong Chen, Mingfeng Chen, Shoudeng Chen, Qiao Chen, Qian Chen, Yuebing Chen, Xuehua Chen, Chang-Lan Chen, Min-Hu Chen, Hongbin Chen, Jingming Chen, Qing Chen, Yu-Fan Chen, Hao-Zhu Chen, Yunjia Chen, Zhongjian Chen, Mingyi Chen, Qianping Chen, Huaxin Chen, Dong-Mei Chen, Peize Chen, Leijie Chen, Ming-Yu Chen, Jiaxuan Chen, Xiao-chun Chen, Wei-Min Chen, Ruisen Chen, Xuanwei Chen, Guiquan Chen, Minyan Chen, Feng-Ling Chen, Yili Chen, Alvin Chen, Xiaodong Chen, Bohong Chen, Chih-Ping Chen, Xuanjing Chen, Shuhui Chen, Ming-Hong Chen, Tzu-Yu Chen, Brian Chen, Bowen Chen, Kai-En Chen, Szu-Chia Chen, Guangchun Chen, Fang Chen, Chuyu Chen, Haotian Chen, Xiaoting Chen, Shaoliang Chen, Chun-Houh Chen, Shali Chen, Yu-Cheng Chen, Zhijun Chen, B Chen, Yuan Chen, Zhanglin Chen, Chaoran Chen, Xing-Long Chen, Zhinan Chen, Yu-Hui Chen, Yuquan Chen, Andrew Chen, Fengming Chen, Guangyong Chen, Jun Chen, Wenshuo Chen, Yi-Guang Chen, Jing-Yuan Chen, Kuangyang Chen, Mingyang Chen, Shaofei Chen, Weicong Chen, Gonghai Chen, Di-Long Chen, Limin Chen, Jishun Chen, Yunfei Chen, Caihong Chen, Tongsheng Chen, Ligang Chen, Wenqin Chen, Shiyu Chen, Xiaoyong Chen, Christina Y Chen, Yushan Chen, Ginny I Chen, Guo-Jun Chen, Xianzhen Chen, Wanling Chen, Kuan-Jen Chen, Maorong Chen, Kaijian Chen, Erqu Chen, Shen Chen, Quan Chen, Zian Chen, Yi-Lin Chen, Juei-Suei Chen, Yi-Ting Chen, Huaiyong Chen, Minjian Chen, Qianzhi Chen, Jiahao Chen, Xikun Chen, Juan-Juan Chen, Xiaobo Chen, Tianzhen Chen, Ziming Chen, Qianbo Chen, Jindong Chen, Jiu-Chiuan Chen, Yinwei Chen, Carl Pc Chen, Li-Hsin Chen, Jenny Chen, Ruoyan Chen, Yanqiu Chen, Yen-Fu Chen, Haiyan Chen, Zhebin Chen, Si Chen, Jian-Qiao Chen, Yang-Yang Chen, Ningning Chen, Zhifeng Chen, Zhenyi Chen, Hangang Chen, Zihe Chen, Mengdi Chen, Zhichuan Chen, Xu Chen, Huixi Chen, Weitian Chen, Bao-Sheng Chen, Tien-Hsing Chen, Junchen Chen, Yan-yan Chen, Xiangning Chen, Sijia Chen, Xinyan Chen, Kuan-Yu Chen, Qunxiang Chen, Guangliang Chen, Bing-Huei Chen, Fei Xavier Chen, Zhangcheng Chen, Qianming Chen, Xianze Chen, Yanhua Chen, Qinghao Chen, Yanting Chen, Sijuan Chen, Chen-Mei Chen, Qiankun Chen, Jianan Chen, Rong Chen, Xiankai Chen, Kaina Chen, Gui-Hai Chen, Y-D Ida Chen, Quanjiao Chen, Shuang Chen, Lichang Chen, Xinyi Chen, Yong-Jun Chen, Zhaoli Chen, Chunnuan Chen, Jui-Chang Chen, Zhiang Chen, Weirui Chen, Zhenguo Chen, Jennifer F Chen, Zhiguo Chen, Kunmei Chen, Huan-Xin Chen, Mengyan Chen, Dongrong Chen, Siyue Chen, Xianyue Chen, Chien-Lun Chen, YiChung Chen, Guang Chen, Quanwei Chen, Zongming E Chen, Ting-Huan Chen, Michael C Chen, Jinli Chen, Beth L Chen, Yuh-Lien Chen, Peihong Chen, Qiaoling Chen, Jiale Chen, Shufeng Chen, Xiaowan Chen, Xian-Kai Chen, Ling-Yan Chen, Yen-Ling Chen, Guiying Chen, Guangyi Chen, Yuling Chen, Xiangqiu Chen, Haiquan Chen, Cuie Chen, Gui-Lai Chen, R Chen, Heng-Yu Chen, Yongxun Chen, Fuxiang Chen, Mingmei Chen, Hua-Pu Chen, Yulong Chen, Zhitao Chen, Guohua Chen, Cheng-Yi Chen, Hongxu Chen, Yuanhao Chen, Qichen Chen, Hualin Chen, Guo-Rong Chen, Rongsheng Chen, Xuesong Chen, Wei-Fei Chen, Bao-Bao Chen, Anqi Chen, Yi-Han Chen, Ying-Jung Chen, Jinhuang Chen, Guochao Chen, Lei Chen, S N Chen, Songfeng Chen, Chenyang Chen, Xing Chen, Letian Chen, Meng Xuan Chen, Xiang-Mei Chen, Xiaoyan Chen, Yi-Heng Chen, D F Chen, Bang Chen, Jiaxu Chen, Wei Chen, Sihui Chen, Shu-Hua Chen, I-M Chen, Xuxin Chen, Zhangxin Chen, Jin Chen, Yin-Huai Chen, Wuyan Chen, Bingqing Chen, Bao-Fu Chen, Zhen-Hua Chen, Dan Chen, Zhe-Sheng Chen, Ranyun Chen, Wanyin Chen, Xueyan Chen, Xiaoyu Chen, Tai-Tzung Chen, Xiaofang Chen, Yongxing Chen, Yanghui Chen, Hekai Chen, Yuanwei Chen, Liang Chen, Hui-Jye Chen, Chengchun Chen, Han-Bin Chen, Shuaijie Chen, Yibing Chen, Kehui Chen, Shuhai Chen, Xueling Chen, Ying-Jie Chen, Qingxing Chen, Fang-Zhi Chen, Mei-Hua Chen, Yutong Chen, Lixian Chen, Alex Chen, Qiuhong Chen, Qiuxia Chen, Liping Chen, Hou-Tsung Chen, Zhanghua Chen, Chun-Fa Chen, Chian-Feng Chen, Benjamin P C Chen, Yewei Chen, Mu-Hong Chen, Jianshan Chen, Xiaguang Chen, Meiling Chen, Heng Chen, Ying-Hsiang Chen, Longyun Chen, Dengpeng Chen, Jichong Chen, Shixuan Chen, Liaobin Chen, Everett H Chen, ZhuoYu Chen, Qihui Chen, Zhiyong Chen, Nuan Chen, Hongmei Chen, Guiqian Chen, Yan Q Chen, Fengling Chen, Hung-Chang Chen, Zhenghong Chen, Chengsheng Chen, Hegang Chen, Huei-Yan Chen, Liutao Chen, Meng-Lin Chen, Xi Chen, Qing-Juan Chen, Linna Chen, Xiaojing Chen, Lang Chen, Gengsheng Chen, Fengrong Chen, Weilun Chen, Shi Chen, Wan-Yi Chen, On Chen, Yufeng Chen, Benjamin Chen, Hui-Zhao Chen, Bo-Rui Chen, Kangyong Chen, Ruixiang Chen, Weiyong Chen, Ning-Hung Chen, Meng-Ping Chen, Huimei Chen, Ying Chen, Kang-Hua Chen, Pei-zhan Chen, Liujun Chen, Hanqing Chen, Chengchuan Chen, Guojun Chen, Yongfa Chen, Li Chen, Mingling Chen, Jacinda Chen, Jinlun Chen, Kun Chen, Yi Chen, Chiung Mei Chen, Shaotao Chen, Tianhong Chen, Chanjuan Chen, Yuhao Chen, Huizhi Chen, Chung-Hsing Chen, Qiuchi Chen, Haoting Chen, Luzhu Chen, Huanhua Chen, Long Chen, Jiang-hua Chen, Kai-Yang Chen, Jing-Zhou Chen, Yong-Syuan Chen, Lifang Chen, Ruonan Chen, Meimei Chen, Qingchuan Chen, Liugui Chen, Shaokun Chen, Yi-Yung Chen, Jintian Chen, Xuhui Chen, Dongyan Chen, Huei-Rong Chen, Xianmei Chen, Jinyan Chen, Yuxi Chen, Qingqing Chen, Weibo Chen, Qiwei Chen, Mingxia Chen, Hongmin Chen, Jiahui Chen, Yen-Jen Chen, Zihan Chen, Guozhou Chen, Fei Chen, Zhiting Chen, Denghui Chen, Gary Chen, Hongli Chen, Jack Chen, Zhigang Chen, Lie Chen, Siyuan Chen, Haojie Chen, Qing-Wei Chen, Maochong Chen, Mei-Jie Chen, Haining Chen, Xing-Zhen Chen, Weiqing Chen, Huanchun Chen, C-Y Chen, Tzu-An Chen, Jen-Hau Chen, Xiaojie Chen, Dongquan Chen, Gao B Chen, Daijie Chen, Zixi Chen, Lingfeng Chen, Jiayi Chen, Zan Chen, Shuming Chen, Mei-Hsiu Chen, Xueqin Chen, Huan Chen, Xiaoqing Chen, Hui-Xiong Chen, Ruoying Chen, Deying Chen, Huixian Chen, Zhezhe Chen, Lu Chen, Xiaolong Chen, Si-Yue Chen, Xinwei Chen, Wentao Chen, Yucheng Chen, Jiajing Chen, Allen Menglin Chen, Chixiang Chen, Shiqun Chen, Wenwu Chen, Chin-Chuan Chen, Ningbo Chen, Hsin-Hung Chen, Shenglan Chen, Jia-Feng Chen, Changya Chen, ZhaoHui Chen, Guo Chen, Juhai Chen, Xiao-Quan Chen, Cuimin Chen, Yongshuo Chen, Sai Chen, Fengyang Chen, Siteng Chen, Hualan Chen, Lian Chen, Yuan-Hua Chen, Minjie Chen, Shiyan Chen, Z Chen, Zhengzhi Chen, Jonathan Chen, H Chen, You-Yue Chen, Shu-Gang Chen, Hsuan-Yu Chen, Hongyue Chen, Weiyi Chen, Jiaqi Chen, Chengde Chen, Shufang Chen, Ze-Hui Chen, Xiuping Chen, Zhuojia Chen, Zhouji Chen, Lidian Chen, Yilan Chen, Kuan-Ling Chen, Alon Chen, Zi-Yue Chen, Hongmou Chen, Fang-Zhou Chen, Jianzhou Chen, Wenbiao Chen, Yujie Chen, Zhijian Chen, Zhouqing Chen, Xiuhui Chen, Qingguang Chen, Hanbei Chen, Qianyu Chen, Mengping Chen, Yongqi Chen, Sheng-Yi Chen, Siqi Chen, Yelin Chen, Shirui Chen, Yuan-Tsong Chen, Dongyin Chen, Lingxue Chen, Long-Jiang Chen, Yunshun Chen, Yahong Chen, Yaosheng Chen, Zhonghua Chen, Jingyao Chen, Pei-Yin Chen, Fusheng Chen, Xiaokai Chen, Shuting Chen, Miao-Hsueh Chen, Y-D I Chen, Zijie Chen, Haozhu Chen, Haodong Chen, Xiong Chen, Wenxi Chen, Feng-Jung Chen, Shangwu Chen, Zhiping Chen, Zhang-Yuan Chen, Wentong Chen, Ou Chen, Ruiming Chen, Xiyu Chen, Shuqiu Chen, Xiaoling Chen, Ruimin Chen, Hsiao-Wang Chen, Dongli Chen, Haibo Chen, Yiyun Chen, Luming Chen, Wenting Chen, Chongyang Chen, Qingqiu Chen, Wen-Pin Chen, Yuhui Chen, Lingxia Chen, Jun-Long Chen, Xingyu Chen, Haotai Chen, Bang-dang Chen, Qiuwen Chen, Rui Chen, K C Chen, Zhixuan Chen, Gaoyu Chen, Yitong Chen, Tzu-Ju Chen, Jingqing Chen, Huiqun Chen, Runsen Chen, Michelle Chen, Hanyong Chen, Xiaolin Chen, Ke Chen, Yangchao Chen, Y D I Chen, Jinghua Chen, Jia Wei Chen, Man-Hua Chen, H T Chen, Zheyi Chen, Lihong Chen, Guangyao Chen, Rujun Chen, Ming-Fong Chen, Haiyun Chen, Dexiong Chen, Huiqin Chen, Ching Kit Chen, En-Qiang Chen, Wanjia Chen, Xiangliu Chen, Meiting Chen, Szu-Chi Chen, Yii-der Ida Chen, Jian-Hua Chen, Yanjie Chen, Yingying Chen, Paul Chih-Hsueh Chen, Si-Ru Chen, Mingxing Chen, Rui-Zhen Chen, Changjie Chen, Qu Chen, Yintong Chen, Jingde Chen, Mao Chen, Xinghai Chen, Mei-Chih Chen, Xueqing Chen, Chun-An Chen, Cheng Chen, Ruijing Chen, Huayu Chen, Yunqin Chen, Yan-Gui Chen, Ruibing Chen, Size Chen, Qi-An Chen, Yuan-Zhen Chen, J Chen, Heye Chen, T Chen, Junpeng Chen, Tan-Huan Chen, Shuaijun Chen, Hao Yu Chen, Fahui Chen, Lan Chen, Dong-Yi Chen, Xianqiang Chen, Shi-Sheng Chen, Qiao-Yi Chen, Pei-Chen Chen, Xueying Chen, Yi-Wen Chen, Guohong Chen, Zhiwei Chen, Zuolong Chen, Erfei Chen, Yuqing Chen, Zhenyue Chen, Qiongyun Chen, Jianghua Chen, Yingji Chen, Xiuli Chen, Xiaowei Chen, Hengyu Chen, Sheng-Xi Chen, Haiyi Chen, Shao-Peng Chen, Yi-Ru Chen, Zhaoran Chen, Xiuyan Chen, Jinsong Chen, Sunny Chen, Xiaolan Chen, S-D Chen, Ruofan Chen, Qiujing Chen, Yun Chen, Wei-Cheng Chen, Chun-Wei Chen, Liechun Chen, Lulu Chen, Hsiu-Wen Chen, Yanping Chen, Jiayao Chen, Xuejiao Chen, Guan-Wei Chen, Yusi Chen, Yijiang Chen, Chi-Hua Chen, Qixian Chen, Ziqing Chen, Peiyou Chen, Chunhai Chen, Zheren Chen, Qiuyun Chen, Xiaorong Chen, Chaoqun Chen, Dan-Dan Chen, Xuechun Chen, Yafang Chen, Mystie X Chen, Jina Chen, Wei-Kai Chen, Yule Chen, Bo Chen, Kaili Chen, Junqin Chen, Jia Min Chen, Chen Chen, Guoliang Chen, Xiaonan Chen, Guangjie Chen, Xiao Chen, Jeanne Chen, Danyang Chen, Minjiang Chen, Jiyuan Chen, Zheng-Zhen Chen, Shou-Tung Chen, Ouyang Chen, Xiu Chen, H Q Chen, Peiyu Chen, Yuh-Min Chen, Youmeng Chen, Shuoni Chen, Peiqin Chen, Xinji Chen, Chih-Ta Chen, Shang-Hung Chen, Robert Chen, Suet N Chen, Yun-Tzu Chen, Suming Chen, Ye Chen, Yao Chen, Yi-Fei Chen, Ruixue Chen, Tianhang Chen, Suning Chen, Jingnan Chen, Xiaohong Chen, Kun-Chieh Chen, Tuantuan Chen, Mei Chen, He-Ping Chen, Zhi Bin Chen, Yuewu Chen, Mengying Chen, Po-See Chen, Xue Chen, Jian-Jun Chen, Xiyao Chen, Jeremy J W Chen, Jiemei Chen, Daiwen Chen, Christina Yingxian Chen, Qinian Chen, Chih-Wei Chen, Wensheng Chen, Yingcong Chen, Zhishi Chen, Duo Chen, Jiansu Chen, Keping Chen, Min Chen, Yi-Hui Chen, Yun-Ju Chen, Gaoyang Chen, Renjin Chen, Kui Chen, Shuai-Ming Chen, Hui-Fen Chen, Zi-Yun Chen, Shao-Yu Chen, Meiyang Chen, Jiahua Chen, Zongyou Chen, Yen-Rong Chen, Huaping Chen, Yu-Xin Chen, Bohe Chen, Kehua Chen, Zilin Chen, Zhang-Liang Chen, Ziqi Chen, Yinglian Chen, Hui-Wen Chen, Peipei Chen, Baolin Chen, Zugen Chen, Kangzhen Chen, Yanhan Chen, Sung-Fang Chen, Zheping Chen, Zixuan Chen, Jiajia Chen, Yuanjian Chen, Lili Chen, Xiangli Chen, Ban Chen, Yuewen Chen, X Chen, Yan-Qiong Chen, Chider Chen, Yung-Hsiang Chen, Hanlin Chen, Xiangjun Chen, Haibing Chen, Le Chen, Xuan Chen, Xue-Ying Chen, Zexiao Chen, Chen-Yu Chen, Zhe-Ling Chen, Fan Chen, Hsin-Yi Chen, Feilong Chen, Zilong Chen, Yi-Jen Chen, Zhiyun Chen, Ning Chen, Wenxu Chen, Chuanbing Chen, Yaxi Chen, Yi-Hong Chen, Eleanor Y Chen, Yuexin Chen, Kexin Chen, Shoujun Chen, Yen-Ju Chen, Yu-Chuan Chen, Yen-Teen Chen, Bao-Ying Chen, Xiaopeng Chen, Danli Chen, Katharine Y Chen, Jingli Chen, Qianyi Chen, Zihua Chen, Ya-xi Chen, Xuanxu Chen, Chung-Hung Chen, Yajie Chen, Cindi Chen, Hua Chen, Shuliang Chen, Elizabeth H Chen, Gen-Der Chen, Bingyu Chen, Keyang Chen, Siyu S Chen, Xinpu Chen, Yau-Hung Chen, Hsueh-Fen Chen, Han-Hsiang Chen, Wei Ning Chen, Guopu Chen, Zhujun Chen, Yurong Chen, Yuxian Chen, Wanjun Chen, Qiu-Jing Chen, Qifang Chen, Yuhan Chen, Jingshen Chen, Zhongliang Chen, Ching-Hsuan Chen, Zhaoyao Chen, Yongning Chen, Marcus Y Chen, Ping Chen, Junfei Chen, Yung-Wu Chen, Xueting Chen, Yingchun Chen, Wan-Yan Chen, Yuxin Chen, Yisheng Chen, Chun-Yuan Chen, Yulian Chen, Yan-Jun Chen, Guoxun Chen, Ding Chen, Yu-Fen Chen, Jason A Chen, Shuyi Chen, Cuilan Chen, Ruijuan Chen, Kevin Chen, Xuanmao Chen, Shen-Ming Chen, Ya-Nan Chen, Sean Chen, Zhaowei Chen, Xixi Chen, Yu-Chia Chen, Xuemin Chen, Binlong Chen, Weina Chen, Xuemei Chen, Di Chen, P P Chen, Yubin Chen, Chunhua Chen, Li-Chieh Chen, Ping-Chung Chen, Zhihao Chen, Xinyang Chen, Chan Chen, Yan Jie Chen, Shi-Qing Chen, Ivy Xiaoying Chen, Ying-Cheng Chen, Jia-Shun Chen, Shao-Wei Chen, Aiping Chen, Dexiang Chen, Qianfen Chen, Hongyu Chen, Wei-Kung Chen, Danlei Chen, Hongen Chen, Shipeng Chen, Jake Y Chen, Dongsheng Chen, Chien-Ting Chen, Shouzhen Chen, Hehe Chen, Yu-Tung Chen, Yilin Chen, Joy J Chen, Zhong Chen, Zhenfeng Chen, Zhongzhu Chen, Feiyang Chen, Xingxing Chen, Keyan Chen, Huimin Chen, Guanyu Chen, D. Chen, Dianke Chen, Zhigeng Chen, Sien-Tsong Chen, Yii-Der Chen, Chi-Yun Chen, Beidong Chen, Wu-Xian Chen, Zhihang Chen, Yuanqi Chen, Jianhua Chen, Xian Chen, Xiangding Chen, Jingteng Chen, Shuaiyu Chen, Xue-Mei Chen, Yu-Han Chen, Hongqiao Chen, Weili Chen, Yunzhu Chen, Guo-qing Chen, Miao Chen, Zhi Chen, Junhui Chen, Jing-Xian Chen, Zhiquan Chen, Shuhuang Chen, Shaokang Chen, Irwin Chen, Xiang Chen, Chuo Chen, Siting Chen, Keyuan Chen, Xia-Fei Chen, Zhihai Chen, Yuanyu Chen, Po-Sheng Chen, Qingjiang Chen, Yi-Bing Chen, Rongrong Chen, Katherine C Chen, Shaoxing Chen, Lifen Chen, Luyi Chen, Sisi Chen, Ning-Bo Chen, Yihong Chen, Guanjie Chen, Li-Hua Chen, Xiao-Hui Chen, Ting Chen, Chun-Han Chen, Xuzhuo Chen, Junming Chen, Zheng Chen, Wen-Jie Chen, Bingdi Chen, Jiang Ye Chen, Yanbin Chen, Duoting Chen, Shunyou Chen, Shaohua Chen, Jien-Jiun Chen, Jiaohua Chen, Shaoze Chen, Yifang Chen, Chiqi Chen, Yen-Hao Chen, Rui-Fang Chen, Hung-Sheng Chen, Kuey Chu Chen, Y S Chen, Xijun Chen, Chaoyue Chen, Heng-Sheng Chen, Lianfeng Chen, Yen-Ching Chen, Yuhong Chen, Yixin Chen, Yuanli Chen, Cancan Chen, Yanming Chen, Yajun Chen, Chaoping Chen, F-K Chen, Menglan Chen, Zi-Yang Chen, Yongfang Chen, Hsin-Hong Chen, Hongyan Chen, Chao-Wei Chen, Jijun Chen, Xiaochun Chen, Yazhuo Chen, Zhixin Chen, YongPing Chen, Jui-Yu Chen, Mian-Mian Chen, Liqiang Chen, Y P Chen, D-F Chen, Jinhao Chen, Yanyan Chen, Chang-Zheng Chen, Shao-long Chen, Guoshun Chen, Lo-Yun Chen, Yen-Lin Chen, Bingqian Chen, Dafang Chen, Yi-Chung Chen, Liming Chen, Qiuli Chen, Shuying Chen, Chih-Mei Chen, Renyu Chen, Wei-Hao Chen, Lihua Chen, Hang Chen, Hai-Ning Chen, Hu Chen, Yu-Fu Chen, Yalan Chen, Wan-Tzu Chen, Benjamin Jieming Chen, Yingting Chen, Jiacai Chen, Ning-Yuan Chen, Shuo-Bin Chen, Yu-Ling Chen, Jian-Kang Chen, Hengsan Chen, Yu-Ting Chen, Y Chen, Qingjie Chen, Jiong Chen, Chaoyi Chen, Yunlin Chen, Gang Chen, Hui-Chun Chen, Li-Tzong Chen, Zhangliang Chen, Qiangpu Chen, Xianbo Chen, Jinxuan Chen, Hebing Chen, Ran Chen, Zhehui Chen, Carol X-Q Chen, Yuping Chen, Xiangyu Chen, Xinyu Chen, Qianyun Chen, Junyi Chen, B-S Chen, Zhesheng Chen, Man Chen, Dali Chen, Danyu Chen, Huijiao Chen, Naisong Chen, Qitong Chen, Chueh-Tan Chen, Kai-Ming Chen, Jiarou Chen, Huang Chen, Chunjie Chen, Weiping Chen, Po-Min Chen, Guang-Chao Chen, Danxia Chen, Youran Chen, Chuanzhi Chen, Peng-Cheng Chen, Wen-Tsung Chen, Linxi Chen, Si-guo Chen, Zike Chen, Zhiyu Chen, Wanting Chen, Jiangxia Chen, Wenhua Chen, Roufen Chen, Shi-You Chen, Fang-Pei Chen, Chu Chen, Feifeng Chen, Chunlin Chen, Yunwei Chen, Wenbing Chen, Xuejun Chen, Meizhen Chen, Li Jia Chen, Tianhua Chen, Xiangmei Chen, Kewei Chen, Yuh-Ling Chen, Dejuan Chen, Jiyan Chen, Xinzhuo Chen, Yue-Lai Chen, Hsiao-Jou Cortina Chen, Weiqin Chen, Huey-Miin Chen, Elizabeth Suchi Chen, Kai-Ting Chen, Lizhen Chen, Xiaowen Chen, Chien-Yu Chen, Lingjun Chen, Gonglie Chen, Jiao Chen, Zhuo-Yuan Chen, Wei-Peng Chen, Xiangna Chen, Jiade Chen, Lanmei Chen, Siyu Chen, Kunpeng Chen, Hung-Chi Chen, Jia Chen, Shuwen Chen, Siqin Chen, Zhenlei Chen, Wen-Yi Chen, Si-Yuan Chen, Yidan Chen, Tianfeng Chen, Fu Chen, Leqi Chen, Jiamiao Chen, Shasha Chen, Qingyi Chen, Ben-Kuen Chen, Haitao Chen, Qi Chen, Yihao Chen, Yunfeng Chen, Elizabeth S Chen, Yiming Chen, Youwei Chen, Lichun Chen, Yanfei Chen, Hongxing Chen, Muh-Shy Chen, Yingyu Chen, Weihong Chen, Ming Chen, Kelin Chen, Duan-Yu Chen, Shi-Yi Chen, Shih-Yu Chen, Yanling Chen, Shuanghui Chen, Ya Chen, Yusheng Chen, Yuting Chen, Shiming Chen, Xinqiao Chen, Hongbo Chen, Mien-Cheng Chen, Jiacheng Chen, Herbert Chen, Ji-ling Chen, Sun Chen, Chen-Sheng Chen, Na Chen, Chih-Yi Chen, Wenfang Chen, Yii-Der I Chen, Qinghua Chen, Shuai Chen, Hsi-Hsien Chen, F Chen, Guo-Chong Chen, Zhe Chen, Beijian Chen, Roger Chen, You-Ming Chen, Hongzhi Chen, Zhen-Yu Chen, Xianxiong Chen, Chang Chen, Chujie Chen, Chuannan Chen, Kan Chen, Lu-Biao Chen, Yupei Chen, Qiu-Sheng Chen, Shangduo Chen, Yuan-Yuan Chen, Yundai Chen, Binzhen Chen, Cai-Long Chen, Yen-Chen Chen, Xue-Xin Chen, Yanru Chen, Chunxiu Chen, Yifa Chen, Xingdong Chen, Ruey-Hwa Chen, Shangzhong Chen, Ching-Wen Chen, Danna Chen, Jingjing Chen, Yafei Chen, Dandan Chen, Pei-Yi Chen, Shan Chen, Guanghao Chen, Longqing Chen, Yen-Cheng Chen, Zhanjuan Chen, Jinguo Chen, Zhongxiu Chen, Rui-Min Chen, Shunde Chen, Xun Chen, Jianmin Chen, Linyi Chen, Ying-Ying Chen, Chien-Hsiun Chen, Li-Nan Chen, Yu-Ming Chen, Qianqian Chen, Xue-Yan Chen, Shengdi Chen, Huali Chen, Xinyue Chen, Ching-Yi Chen, Honghai Chen, Baosheng Chen, Pingguo Chen, Yike Chen, Yuxiang Chen, Qing-Hui Chen, Yuanwen Chen, Yongming Chen, Zongzheng Chen, Ruiying Chen, Huafei Chen, Tingen Chen, Zhouliang Chen, Shih-Yin Chen, Shanyuan Chen, Yiyin Chen, Feiyu Chen, Zitao Chen, Constance Chen, Zhoulong Chen, Haide Chen, Jiang Chen, Ray-Jade Chen, Shiuhwei Chen, Chih-Chieh Chen, Chaochao Chen, Lijuan Chen, Qianling Chen, Jian-Min Chen, Xihui Chen, Yuli Chen, Wu-Jun Chen, Diyun Chen, Alice P Chen, Jingxuan Chen, Chiung-Mei Chen, Shibo Chen, M L Chen, Lena W Chen, Xiujuan Chen, Christopher S Chen, Yeh Chen, Xingyong Chen, Feixue Chen, Boyu Chen, Weixian Chen, Tingting Chen, Bosong Chen, Junjie Chen, Han-Min Chen, Szu-Yun Chen, Qingliang Chen, Huatao Chen, Bin Chen, L B Chen, Xuanyi Chen, Chun Chen, Dong Chen, Yinjuan Chen, Jiejian Chen, Lu-Zhu Chen, Alex F Chen, Pei-Chun Chen, Chien-Jen Chen, Y M Chen, Xiao-Chen Chen, Tania Chen, Yang Chen, Yangxin Chen, Mark I-Cheng Chen, Haiming Chen, Shuo Chen, Yong Chen, Hsiao-Tan Chen, Erzhen Chen, Jiaye Chen, Fangyan Chen, Guanzheng Chen, Haoyun Chen, Jiongyu Chen, Baofeng Chen, Yuqin Chen, Juan Chen, Haobo Chen, Shuhong Chen, Fu-Shou Chen, Wei-Yu Chen, Haw-Wen Chen, Feifan Chen, Deqian Chen, Linlin Chen, Xiaoshan Chen, Hui Chen, Wenwen Chen, Yanli Chen, Yuexuan Chen, Xiaoyin Chen, Yen-Chang Chen, Tiantian Chen, Ruiai Chen, Alice Y Chen, Jinglin Chen, Zifan Chen, Wantao Chen, Shanshan Chen, Jianjun Chen, Xiaoyuan Chen, Xuefei Chen, Runfeng Chen, Weisan Chen, Guangnan Chen, Junpan Chen, An Chen, Lankai Chen, Yiding Chen, Tianpeng Chen, Ya-Ting Chen, Lijin Chen, Ching-Yu Chen, Y Eugene Chen, Guanglong Chen, Rongyuan Chen, Yali Chen, Yanan Chen, Liyun Chen, Shuai-Bing Chen, Zhixue Chen, Xiaolu Chen, Xiao-he Chen, Hongxiang Chen, Bing-Feng Chen, Gary K Chen, Xiaohui Chen, Jin-Wu Chen, Qiuxiang Chen, Huaqiu Chen, X Steven Chen, Xiaoqian Chen, Chao-Jung Chen, Zhengjun Chen, Yong-Ping Chen, Zhelin Chen, Xuancai Chen, Yi-Hsuan Chen, Daiyu Chen, Gui Mei Chen, Hongqi Chen, Zhizhong Chen, Mengting Chen, Guofang Chen, Jian-Guo Chen, Hou-Zao Chen, Yuyao Chen, Lixia Chen, Yu-Yang Chen, Zhengling Chen, Qinfen Chen, Jiajun Chen, Xue-Qing Chen, Shenghui Chen, Yii-Derr Chen, Linbo Chen, Yanjing Chen, S Pl Chen, Chi-Long Chen, Jiawei Chen, Rong-Hua Chen, Shu-Fen Chen, Yu-San Chen, Ying-Lan Chen, Xiaofen Chen, Weican Chen, Xin Chen, Yumei Chen, Ruohong Chen, You-Xin Chen, Tse-Ching Chen, Xiancheng Chen, Yu-Pei Chen, Weihao Chen, Baojiu Chen, Haimin Chen, Zhihong Chen, Jion Chen, Yi-Chun Chen, Ping-Kun Chen, Wan Jun Chen, Willian Tzu-Liang Chen, Qingshi Chen, Ren-Hui Chen, Weihua Chen, Hanjing Chen, Guihao Chen, Xiao-Qing Chen, Po-Yu Chen, Liangsheng Chen, Fred K Chen, Haiying Chen, Tzu-Chieh Chen, Wei J Chen, Zhen Chen, Shu Chen, Jie Chen, Chung-Hao Chen, Zi-Qing Chen, Yu-Xia Chen, Weijia Chen, Ming-Han Chen, Yaodong Chen, Yong-Zhong Chen, Jinquan Chen, Haijiao Chen, Tom Wei-Wu Chen, Jingzhou Chen, Ya-Peng Chen, Shiwei Chen, Xiqun Chen, Yingjie Chen, Wenjun Chen, Linjie Chen, Hung-Chun Chen, Xiaoping Chen, Haoran Chen, Qiang Chen, Sy-Jou Chen, Y U Chen, Weineng Chen, Li-hong Chen, Cheng-Fong Chen, Yajing Chen, Song Chen, Qiaoli Chen, Yiru Chen, Guang-Yu Chen, Zhi-bin Chen, Deyu Chen, C Y Chen, Junhong Chen, Yonghui Chen, Chaoli Chen, Syue-Ting Chen, Sufang Chen, I-Chun Chen, Shangsi Chen, Xiao-Wei Chen, Qinsheng Chen, Zhao-Xia Chen, Yun-Yu Chen, Chi-Chien Chen, Wenxing Chen, Meng Chen, Zixin Chen, Jianhui Chen, Yuanyuan Chen, Jiamin Chen, Wei-Wei Chen, 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
Ying-Shuang Chang, Yu-Yu Kan, Tzu-Ning Chao +2 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Insulin supply is the golden standard for type 1 diabetes mellitus (T1DM) therapy. Is there a drug-reduction application for reversing glucose metabolism disabled and diabetic neuropathy (DN), and is Show more
Insulin supply is the golden standard for type 1 diabetes mellitus (T1DM) therapy. Is there a drug-reduction application for reversing glucose metabolism disabled and diabetic neuropathy (DN), and is it suitable for the young and elderly populations? Reducing T1DM-associated DN, and maintaining glucose metabolism require using the anti-aging gene Klotho to regulate specific signaling cascades. This study applied five 16:8 intermittent fasting (16-h fasting, 8-h eating; 168if) protocols by different executing times to young and elderly diabetic mice to evaluate whether 168if is age-dependent and how it alters Klotho-related signaling molecules. Blood glucose levels were efficiently reduced when 168if was implemented in the early stage of T1DM onset (DNf group) of young and elderly mice. Another four groups failed to reduce blood sugar. However, the DNf protocol was unsuitable for diabetic elderly mice because it posed a higher mortality risk for this population. Young DNf mice exhibited reduced thermal hyperalgesia and mechanical allodynia and reversed Klotho downregulation and protein kinase C epsilon (PKCε) upregulation compared with DN mice. Furthermore, young DNf mice exhibited normalization of fibroblast growth factor receptor 1 (FGFR1) and nuclear factor κB (NF-κB) expression, which is involved in Klotho-related glucose metabolism and anti-inflammation. The expression densities of PKCε, Klotho, FGFR1, and NF-κB were linear to neuropathic manifestations. This study demonstrated the effectiveness of 168if application in the early stage of T1DM onset, a straightforward and convenient dietary control method, as a blood glucose control for achieving pharmaceutical reduction and relieving neuropathic pain in young T1DM patients. Show less
no PDF DOI: 10.1007/s12035-025-04849-x
FGFR1
Yangqi Zhao, Yi Dong, Qingqing Zheng +7 more · 2025 · Investigative ophthalmology & visual science · added 2026-04-24
Fatty acid desaturase 1 (FADS1) is significantly and specifically upregulated following diabetic corneal injury. However, its role in diabetic keratopathy remains unclear. This study aimed to investig Show more
Fatty acid desaturase 1 (FADS1) is significantly and specifically upregulated following diabetic corneal injury. However, its role in diabetic keratopathy remains unclear. This study aimed to investigate the impact of FADS1 on wound healing and functional recovery of the diabetic corneal epithelium and explore its potential mechanisms. Using high-glucose-induced corneal epithelial cells and a streptozotocin-induced type 1 diabetic mouse model, FADS1 expression was suppressed via FADS1 small interfering RNA (siRNA). Cell migration was assessed using scratch and transwell assays. Wound healing and functional recovery of the corneal epithelium were evaluated using sodium fluorescein staining, anterior segment optical coherence tomography, hematoxylin and eosin staining, and immunofluorescence staining. FADS1 knockdown promoted wound healing and functional recovery of the diabetic corneal epithelium both in vivo and in vitro. Suppression of FADS1 enhanced high-glucose-induced corneal epithelial cell migration, which was dependent on elevated levels of the upstream metabolite γ-linolenic acid. This effect was mediated through the activation of the mitogen-activated protein kinase signaling pathway and the accumulation of autophagosomes. After diabetic corneal epithelial injury, FADS1 expression is specifically upregulated. Knockdown of FADS1 promotes wound healing and functional recovery, suggesting a novel therapeutic strategy for diabetic keratopathy. Show less
📄 PDF DOI: 10.1167/iovs.66.6.6
FADS1
Xia Chen, Shengkun Zhang, Yujuan Qi +17 more · 2025 · Human molecular genetics · Oxford University Press · added 2026-04-24
Mesenchymal cells constitute the primary structural support elements within endometriotic lesions, yet their pivotal roles in endometriotic pathogenesis remain largely uncharted. This study aimed to c Show more
Mesenchymal cells constitute the primary structural support elements within endometriotic lesions, yet their pivotal roles in endometriotic pathogenesis remain largely uncharted. This study aimed to construct a single-cell atlas of endometriosis using samples from three ovarian tissues affected by endometriosis and three normal ovarian tissues. Through the utilization of scRNA-seq, we have unveiled six distinct mesenchymal subclusters in normal and endometriosis-afflicted ovaries, elucidating the diverse functions of mesenchymal populations in endometriosis. Our comprehensive analysis has revealed that mesenchymal cells predominantly engage in three key functions: ribosome-mediated protein synthesis and processing, cell adhesion facilitating intercellular support and communication, and a range of metabolic processes. Furthermore, our findings have identified several pivotal differentially expressed genes (e.g. C3, FN1, COL3A1, COL1A1, NRXN3), primarily associated with the complement and coagulation cascades, extracellular matrix (ECM) regulation, ECM receptor interactions, and cell adhesion molecules. In essence, our study provides a comprehensive transcriptomic dataset and novel insights into adhesive molecule and integrin networks within mesenchymal subclusters in endometriosis. This, in effect, has deepened the understanding of the pathomechanisms governing this condition. Show less
no PDF DOI: 10.1093/hmg/ddaf065
NRXN3
Yu Liao, Mingchao Wang, Fuli Qin +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically Show more
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically identify Cpn's therapeutic targets and pathways in Western diet (WD)-induced obesity using integrated network pharmacology, transcriptomics, and experimental validation. A Western diet (WD)-induced mice model was used to evaluate the effectiveness of Cpn in ameliorating obesity. A network pharmacology analysis was then employed to identify the potential anti-obesity targets of Cpn. GO functional enrichment and KEGG pathway analysis were performed to elucidate the potential functions of the identified targets, followed by constructing a protein-protein interaction network to screen the core targets. Meanwhile, quantitative transcriptomics was conducted to validate and broaden the network pharmacology findings. Finally, molecular docking and quantitative real-time PCR assay were used for the core target validation. Cpn treatment effectively alleviated obesity-related symptoms in WD-induced mice. The metabolic pathway, insulin signaling pathway, HIF-1 signaling pathway, FoxO signaling pathway, lipid and atherosclerosis pathway, and core targets including CPS1, HRAS, MAPK14, PAH, ALDOB, AKT1, GSK3B, HSP90AA1, BHMT2, EGFR, CASP3, MAT1A, APOM, APOA2, APOC3, and APOA1 are involved in regulating the therapeutic effect of Cpn. This study comprehensively uncovers the potential mechanism of Cpn against obesity based on network pharmacology and quantitative transcriptomics, which provides evidence for revealing the pathogenesis of obesity, suggesting that Cpn is a possible lead compound for anti-obesity treatment. Show less
📄 PDF DOI: 10.3389/fphar.2025.1571480
APOC3
Zhigang Lei, Yu Wu, Weijie Xue +15 more · 2025 · Hepatology (Baltimore, Md.) · added 2026-04-24
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critica Show more
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critical homeostasis regulator, but its function in liver immune homeostasis is unknown. We aimed to clarify the role of hepatocyte FoxO1 in liver immune homeostasis and inflammation. Human liver FoxO1 expression and its association with inflammation were analyzed in patients with various inflammation-related liver diseases. Hepatocyte-specific Foxo1 knockout (FoxO1 △hepa ) mice were established. Hepatocyte-specific gene interference was employed in alcoholic hepatitis and hepatic schistosomiasis murine models. Transcriptomic, single-cell RNA sequencing, and CUT&Tag analyses were performed to elucidate the underlying mechanisms. Hepatocyte FoxO1 levels in human inflammatory livers declined prevalently and were inversely correlated with inflammation and fibrosis. Around 15-18 weeks after birth, FoxO1 △hepa mice exhibited mild spontaneous hepatic inflammation with natural killer T (NKT) cell and neutrophil accumulation. NKT cell depletion in FoxO1 △hepa mice with alcoholic hepatitis or hepatic schistosomiasis (HS) significantly reduced neutrophil accumulation and protected against liver inflammation and damage. Mechanistically, FoxO1 promoted retinoic acid synthesis to induce hepatocyte CD1d expression, which is necessary for regulating NKT cell apoptosis. Innovatively, decreased JMJD1C expression in hepatocytes caused histone H3 lysine 9 (H3K9) dimethylation at the Foxo1 promoter, repressing its transcription and disrupting local immune homeostasis. Our findings uncover a hitherto unrecognized mechanism for hepatocyte-based control of liver inflammation, in which hepatocyte FoxO1 maintained by JMJD1C restrains local NKT cells and neutrophils via CD1d induction, providing promising targets for inflammatory liver diseases. Show less
no PDF DOI: 10.1097/HEP.0000000000001590
JMJD1C
Chi Chen, Yimeng Gu, Junfei Xu +9 more · 2025 · Scientific reports · Nature · added 2026-04-24
Apolipoprotein B (apoB) can be measured directly and accurately, and better predicts atherogenic risk than conventional lipid profiles. We aimed to investigate whether total and regional (trunk or leg Show more
Apolipoprotein B (apoB) can be measured directly and accurately, and better predicts atherogenic risk than conventional lipid profiles. We aimed to investigate whether total and regional (trunk or leg) fat deposits are associated with apoB levels in general US adults. 4585 participants were enrolled from the US National Health and Nutritional Surveys from 2011 to 2016. Overall and regional body fat were measured using dual-energy X-ray absorptiometry. The associations of total and regional fat with apoB levels were evaluated using linear regression models. Following adjustment for demographic, lifestyle, and clinical risk factors, whole-body fat percentage was positively associated with apoB levels. Additionally, percent trunk fat was positively associated (highest vs. lowest tertile beta = 17.73 for men and 14.89 for women, respectively), whereas percent leg fat was inversely associated (highest vs. lowest tertile beta = - 4.84 for men and - 6.55 for women, respectively) with apoB levels in both sexes. The association for trunk fat and leg fat remained significant after further adjustment for body mass index or waist circumference. Higher percent trunk fat combined with lower percent leg fat was associated with particularly higher apoB. In conclusion, among general US adults, both elevated trunk fat and reduced leg fat are associated with higher levels of apoB. Further research is required to elucidate the underlying pathophysiological mechanisms. Show less
📄 PDF DOI: 10.1038/s41598-025-10502-3
APOB
Tong Li, Yang Zhang, Hong Hu +5 more · 2025 · Translational lung cancer research · added 2026-04-24
While most patients with stage I non-small cell lung cancer (NSCLC) remain recurrence-free after resection, some still develop recurrent disease. The surgical curative time window concept, defined as Show more
While most patients with stage I non-small cell lung cancer (NSCLC) remain recurrence-free after resection, some still develop recurrent disease. The surgical curative time window concept, defined as no recurrence through 5-year follow-up, helps identify potentially cured patients, yet predictive clinicopathologic features in stage I invasive NSCLC need clarification. This study sought to identify such features to enable risk-adapted surveillance. We analyzed a prospectively collected dataset of patients with stage I invasive NSCLC who underwent R0 resection between 2008 and 2015. Cox regression analysis was used to evaluate the association between clinicopathologic features and disease recurrence, aiming to identify independent prognostic factors. A total of 1,817 patients met the inclusion criteria. The 5-year cumulative incidence of recurrence was 14.6%. Female sex, tumor size ≤2 cm, lepidic-predominant adenocarcinoma (LPA) histologic type, presence of a ground-glass opacity (GGO) component, and solid component size ≤10 mm were identified as independent prognostic factors. A risk stratification system was subsequently developed, classifying patients into two groups: a low-risk group (with ≥4 factors; n=341) and an elevated-risk group (with <4 factors; n=1,476). Kaplan-Meier analysis revealed statistically significant differences in recurrence-free survival (RFS), overall survival (OS), and lung cancer-specific survival (LCSS) between the two groups (P<0.001). The low-risk group is considered to represent the population within the surgical curative time window. Patients with stage I invasive NSCLC who meet at least four of the following five criteria-female sex, tumor size ≤2 cm, solid component ≤10 mm, presence of a GGO component, and LPA histologic type-may be considered within the "surgical curative time window" and may therefore qualify for reduced surveillance intensity. Show less
📄 PDF DOI: 10.21037/tlcr-2025-894
LPA
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
Xinghua Wu, Kai Lin, Chen Gao +4 more · 2025 · European journal of histochemistry : EJH · added 2026-04-24
In recent years, accumulating evidence has highlighted the critical role of miR-627-5p in the occurrence and progression of various cancers. However, its specific role and mechanism in cervical cancer Show more
In recent years, accumulating evidence has highlighted the critical role of miR-627-5p in the occurrence and progression of various cancers. However, its specific role and mechanism in cervical cancer (CC) remain unclear. This study aimed to elucidate the mechanism by which miR-627-5p inhibits the malignant progression of CC and assess its potential clinical implications. In C33A cells, the mRNA expression levels of ANGPTL4 and miR-627-5p were analyzed using qRT-PCR. The miR-627-5p mimics and their control (miR-NC) were transfected into C33A cells to determine whether miR-627-5p directly regulates ANGPTL4 expression. A comprehensive suite of assays, including CCK-8, migration, transwell, flow cytometry, and Western blotting, was conducted to evaluate how miR-627-5p modulates the malignant biological behavior of CC cells. Rescue experiments were performed by overexpressing ANGPTL4. In C33A cells, miR-627-5p expression was reduced, whereas ANGPTL4 expression was elevated. Further analysis confirmed that miR-627-5p negatively regulates ANGPTL4 by directly targeting its 3'-UTR. Functional assays demonstrated that miR-627-5p inhibits proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) while promoting apoptosis and S-phase arrest in C33A cells, effects that were reversed by ANGPTL4 overexpression. These findings highlight the potential of miR-627-5p as both a biomarker and a therapeutic target for CC. By inhibiting EMT and regulating ANGPTL4 expression, miR-627-5p may provide a novel avenue for improving therapeutic strategies, particularly in advanced or metastatic CC. Moreover, miRNA-based therapies, supported by advanced delivery systems such as nanoparticle carriers, could enhance the stability and precision of miR-627-5p applications. This study lays the groundwork for future research integrating miR-627-5p into precision medicine approaches for CC treatment. Show less
📄 PDF DOI: 10.4081/ejh.2025.4161
ANGPTL4
Xuan Bai, Dingzi Zhou, Jing Luo +14 more · 2025 · Medicine · added 2026-04-24
Lipid metabolism abnormalities and inflammation have been implicated in gallstone disease (GSD) development, but the causal relationships and potential mediation effects among lipid metabolites, infla Show more
Lipid metabolism abnormalities and inflammation have been implicated in gallstone disease (GSD) development, but the causal relationships and potential mediation effects among lipid metabolites, inflammatory factors, and GSD remain unclear. The aim of this study is to explore the causal relationships among these 3 factors. This study employed 2-sample Mendelian Randomization (TSMR) and 2-step MR to investigate the causal relationships and potential mediation effects among 91 inflammatory factors, 6 lipid metabolism-related molecules (HDL-C, LDL-C, TG, total cholesterol, ApoA1, and ApoB), and GSD. We opted for 4 distinct MR analysis methods including inverse variance weighted method, weighted median method, MR-Egger regression method and MR-PRESSO analysis. Sensitivity analyses included MR-Egger intercept tests, Cochran's Q statistic, Steiger tests, and leave-one-out analyses. Product of coefficients method was used to estimate mediation proportion. TSMR analysis revealed that every 1-unit increase in low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), the risk of GSD decreased by 16.5%, 10.2%, 8.4%, and 13.1%, respectively. Inflammatory factors such as Natural killer cell receptor 2B4 (CD244), Macrophage colony-stimulating factor 1 (CSF-1), and interleukin-18 receptor 1 (IL-18R1) were identified as risk factors for GSD, while Fibroblast growth factor 19 levels (FGF19), Interleukin-1-alpha levels (IL-1α), and Interleukin-8 levels (IL-8) were found to be protective. Mediation analysis through 2-step MR identified potential pathways involving ApoA1--IL-8--GSD (P = .084) and IL-1α--ApoB--GSD (P = .117). This study provides robust evidence of causal links between specific lipid metabolites and GSD, as well as suggestive causal associations for several inflammatory factors. However, mediation analysis did not support significant roles for lipids or inflammatory factors as mediators in GSD pathogenesis. Future research could be further pursued in areas such as drug target intervention and mechanistic studies. Show less
no PDF DOI: 10.1097/MD.0000000000044704
APOB
Shaohua Zheng, Changwang Zhang, Youjia Chen +1 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks Show more
The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks (GNNs) have demonstrated significant advantages in predicting molecular activity. However, their reliance on graph structures alone often neglects explicit sequence-level semantic information. To address this limitation, we proposed a Graph and multi-level Sequence Fusion Learning (GSFL) model for predicting the molecular activity of BACE-1 inhibitors. Firstly, molecular graph structures generated from SMILES strings were encoded using GNNs with an atomic-level characteristic attention mechanism. Next, substrings at functional group, ion level, and atomic level substrings were extracted from SMILES strings and encoded using a BiLSTM-Transformer framework equipped with a hierarchical attention mechanism. Finally, these features were fused to predict the activity of BACE-1 inhibitors. A dataset of 1548 compounds with BACE-1 activity measurements was curated from the ChEMBL database. In the classification experiment, the model achieved an accuracy of 0.941 on the training set and 0.877 on the test set. For the test set, it delivered a sensitivity of 0.852, a specificity of 0.894, a MCC of 0.744, an F1-score of 0.872, a PRC of 0.869, and an AUC of 0.915. Compared to traditional computer-aided drug design methods and other machine learning algorithms, the proposed model can effectively improve the accuracy of the molecular activity prediction of BACE-1 inhibitors and has a potential application value. Show less
📄 PDF DOI: 10.3390/ijms26041681
BACE1
Qing Wang, Wei He, Shilong Han +6 more · 2025 · Cancer medicine · Wiley · added 2026-04-24
Colorectal cancer (CRC) metastasis remains a major cause of mortality, driven by epithelial-to-mesenchymal transition (EMT) and invasion. Programmed cell death 4 (Pdcd4), a tumor suppressor, is known Show more
Colorectal cancer (CRC) metastasis remains a major cause of mortality, driven by epithelial-to-mesenchymal transition (EMT) and invasion. Programmed cell death 4 (Pdcd4), a tumor suppressor, is known to inhibit translation via interaction with eukaryotic initiation factor 4A (eIF4A). Previous studies have established that Pdcd4 suppresses stress-activated protein kinase 1-interacting protein 1 (Sin1) translation through the mTORC2-Akt axis, thereby downregulating Snail expression and EMT in CRC cells. However, whether Pdcd4 directly regulates Slug, another critical EMT transcription factor, remains unexplored. PDCD4 shRNA and SLUG siRNA were used to knock down Pdcd4 and Slug in colorectal cancer cells, respectively. The sucrose gradient fractionation was performed to determine SLUG translation. A luciferase reporter assay was used to determine the role of the SLUG 5' untranslated region (5'UTR) on Pdcd4 inhibition. The effect of Slug on promoting invasion was determined by Matrigel invasion assays. Knockdown of Pdcd4 in colorectal cancer cells increased Slug protein levels without altering SLUG mRNA abundance. Sucrose gradient fractionation revealed that Pdcd4 knockdown elevated the proportion of SLUG mRNA in polysome fractions, demonstrating Pdcd4-mediated suppression of SLUG translation. To validate the mechanism, the SLUG 5'UTR was cloned and fused to a luciferase reporter and named SLUG-5'UTR-Luc. Pdcd4 knockdown markedly enhanced SLUG-5'UTR-Luc activity; whereas, ectopic Pdcd4 expression suppressed it, indicating that the SLUG 5'UTR is critical for Pdcd4-mediated translational repression. Treatment with the eIF4A inhibitor silvestrol substantially reduced Slug protein levels and SLUG-5'UTR-Luc activity. In addition, Pdcd4 overexpression decreased Slug protein abundance and restored E-cadherin expression. Notably, Slug knockdown in Pdcd4-deficient cells rescued E-cadherin expression and abrogated the invasive phenotype. These findings suggest that up-regulation of Slug translation by Pdcd4 knockdown contributes to enhanced invasion. Pdcd4 suppresses colorectal cancer invasion by translationally downregulating Slug expression. Show less
no PDF DOI: 10.1002/cam4.71145
SNAI1
Shenglong Tan, Xinghong Luo, Yifan Wang +9 more · 2025 · Biomaterials · Elsevier · added 2026-04-24
Traumatic defects or non-union fractures presents a substantial challenge in the fields of tissue engineering and regenerative medicine. Although synthetic calcium phosphate-based biomaterials (CaPs) Show more
Traumatic defects or non-union fractures presents a substantial challenge in the fields of tissue engineering and regenerative medicine. Although synthetic calcium phosphate-based biomaterials (CaPs) such as dibasic calcium phosphate anhydrate (DCPA) are commonly employed for bone repair, their inadequate cellular immune responses significantly impede sustained degradation and optimal osteogenesis. In this study, drawing inspiration from the key structure of an acidic non-collagenous protein-CaP complex (ANCPs-CaP) essential for natural bone formation, we prepared biomimetic mineralized dibasic calcium phosphate (MDCPA). This preparation utilized plant-derived non-collagenous protein Zein as the organic template and acidic artificial saliva as the mineralization medium. Physicochemical property analysis revealed that MDCPA is a complex of Zein and DCPA, which mimics the composite of the natural ANCP-CaP. Moreover, MDCPA exhibited enhanced biodegradability and osteogenic potential. Mechanistic insight revealed that MDCPA can be phagocytized and degraded by macrophages via the FCγRIII receptor, leading to the release of interleukin 27 (IL-27), which promotes osteogenic differentiation by osteoimmunomodulation. The critical role of IL-27 in osteogenesis is further confirmed using IL-27 gene knockout mice. Additionally, MDCPA demonstrates effective healing of critical-sized defects in rat cranial bones within only 4 w, providing a promising basis and valuable insights for critical-sized bone defects regeneration. Show less
no PDF DOI: 10.1016/j.biomaterials.2024.122917
IL27
Azad Mojahedi, On Chen, Hal A Skopicki +2 more · 2025 · Reviews in cardiovascular medicine · added 2026-04-24
Despite advancements in treatment, coronary artery disease (CAD) remains a significant global health concern. Although lipoprotein(a) [Lp(a)] is recognized as a crucial cardiovascular risk factor asso Show more
Despite advancements in treatment, coronary artery disease (CAD) remains a significant global health concern. Although lipoprotein(a) [Lp(a)] is recognized as a crucial cardiovascular risk factor associated with increased risk, the prognostic value of using Lp(a) levels in patients with acute coronary syndrome (ACS) who have undergone percutaneous coronary intervention (PCI) remains debatable. This review aimed to investigate the association between Lp(a) levels and recurrent ischemic events in patients with ACS undergoing PCI. This systematic review included studies with individuals aged ≥18 years diagnosed with ACS who underwent PCI and had Lp(a) measurements. The included studies were sourced from the PubMed database, with a focus on articles published between January 2020 and January 2025. Keywords related to Lp(a) and cardiovascular diseases were used in the search. Data extraction involved a review of titles and abstracts followed by quality assessment using the QUADAS-2 tool. The final analysis included 10 studies with a combined population of 20,896 patients from diverse regions, including Japan, India, Egypt, China, and South Korea. Key findings indicate that elevated Lp(a) levels are significantly associated with adverse cardiovascular outcomes, including myocardial infarction and mortality, both in hospital and during long-term follow-up. This review highlights Lp(a) as a critical biomarker for predicting recurrent cardiovascular events in ACS patients post-PCI. The consistent correlation between elevated Lp(a) levels and adverse outcomes underscores the necessity of routine monitoring and targeted management of Lp(a) to mitigate residual cardiovascular risk. Show less
📄 PDF DOI: 10.31083/RCM42784
LPA
Ruijun Sun, Yuchi Zhang, Jingying Xu +7 more · 2025 · Archiv der Pharmazie · Wiley · added 2026-04-24
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-se Show more
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-serving as promising reservoirs of such inhibitors. Nevertheless, comprehensive screening and mechanistic characterization of their inhibitory potential remain limited. This study sought to identify potent AChE inhibitors from YGE, investigate their mechanisms of action, and assess their therapeutic prospects for AD. Methodologically, an integrated approach was employed, combining ultrafiltration-liquid chromatography (UF-LC) for rapid inhibitor screening, molecular docking and dynamics simulations for mechanistic insight, two-stage high-speed countercurrent chromatography for compound isolation, enzyme kinetics to delineate inhibition modalities, and network pharmacology to uncover relevant AD-related targets. The findings identified seven active constituents with notable AChE inhibition, among which parishins A and G were obtained at high purity (98.26% and 97.26%, respectively) and exhibited mixed-type inhibition with low IC Show less
no PDF DOI: 10.1002/ardp.70174
BACE1
Béatrice Bréart, Katherine Williams, Stellanie Krimm +34 more · 2025 · Nature · Nature · added 2026-04-24
Although cytotoxic CD8
📄 PDF DOI: 10.1038/s41586-024-08510-w
IL27
Yaozhong Liu, Huilun Wang, Minzhi Yu +19 more · 2025 · Circulation · added 2026-04-24
Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease with no effective pharmacological treatments. The causal role of triglycerides (TGs) in AAA development remains unclear and contr Show more
Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease with no effective pharmacological treatments. The causal role of triglycerides (TGs) in AAA development remains unclear and controversial. Mendelian randomization was applied to assess causal relationships between lipoproteins, circulating proteins, metabolites, and the risk of AAA. To test the hypothesis that elevated plasma TG levels accelerate AAA development, we used Mendelian randomization analyses integrating genetic, proteomic, and metabolomic data identified causal relationships between elevated TG-rich lipoproteins, TG metabolism-related proteins/metabolites, and AAA risk. In the angiotensin II infusion AAA model, most These findings identify hypertriglyceridemia as a key contributor to AAA pathogenesis and suggest that targeting TG-rich lipoproteins may be a promising therapeutic strategy for AAA. Show less
📄 PDF DOI: 10.1161/CIRCULATIONAHA.125.074737
APOA5
Roshni Jaffery, Yuhang Zhao, Sarfraz Ahmed +11 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Mutations in the Leucine-rich repeat kinase 2 ( We investigated the levels of soluble immune regulators in the serum (n=651) and cerebrospinal fluid (CSF, n=129) of In this extensive discovery cohort, Show more
Mutations in the Leucine-rich repeat kinase 2 ( We investigated the levels of soluble immune regulators in the serum (n=651) and cerebrospinal fluid (CSF, n=129) of In this extensive discovery cohort, we identified several elevated serum immune regulatory factors associated with This study highlights distinct immune profiles associated with LRRK2 mutations and PD in the periphery and CNS. Serum levels of SDF-1alpha and TNF-RII were elevated in LRRK2 mutation carriers, while CSF immune markers were reduced. In PD, irrespective of LRRK2 status, reduced CSF inflammatory analytes and weak serum signals were observed. These results provide insight into immune dysregulation linked to LRRK2 mutations. If replicable in independent datasets, they offer potential avenues for biomarker and therapeutic exploration. Show less
📄 PDF DOI: 10.1101/2025.03.20.644460
IL27
Guangquan Chen, Qianqian Sun, Shiyi Xiong +6 more · 2025 · ACS nano · ACS Publications · added 2026-04-24
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is ach Show more
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is achieved through metabolic adaptation in response to changes in the external environment; yet, intricacies of these organ dysfunctions and underlying metabolic changes remain poorly understood, particularly at spatial suborgan level. Using a pregnant mouse model exposed to polystyrene (PS)-M/NPs (sizes: 100 nm, 5 μm, 10 mg/L in drinking water) from gestation day 1 to 18, we construct a comprehensive multisub-organ lipid metabolic landscape. This analysis integrates MALDI-mass spectrometry imaging with histological assessment to monitor changes in maternal suborgans-placenta-fetus unit. Our findings reveal distinct metabolic responses between maternal and fetal organs to gestational PS-M/NPs exposure. We identify potential targeted suborgans and spatial biomarkers associated with PS-M/NPs exposure according to histological damage and metabolic remodeling, including placental junctional and labyrinth zone (e.g., phosphatidylserine, phosphatidylethanolamine [PE]), renal cortex of maternal kidney (e.g., ceramide [Cer], PE, sphingomyelin [SM], phosphatidylglycerol [PG], phosphatidylserine), ventricular muscular layer and interventricular septum of maternal heart (e.g., PE, lysophosphatidylethanolamine [LPE], lysophosphatidic acid [LPA]), fetal brain and spinal cord (e.g., Cer), and fetal liver (e.g., Cer). Furthermore, phosphatidylserine synthesis and glycolipid metabolism pathways are found to be exclusively enriched following PS-NP and PS-MP exposure in the multiorgan network, respectively. We propose an M/NPs scale-exposed suborgan effect framework, which provides a molecular foundation and potential spatial biomarkers for elucidating intersub-organ interactions in response to M/NPs exposure and their role in mediating pregnancy state. Show less
no PDF DOI: 10.1021/acsnano.5c13265
LPA
Edin Muratspahić, David Feldman, David E Kim +43 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, yet the design of protein agonists and antagonists has been challenging as Show more
G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, yet the design of protein agonists and antagonists has been challenging as GPCRs are integral membrane proteins and conformationally dynamic. Here we describe computational Show less
📄 PDF DOI: 10.1101/2025.03.23.644666
GIPR
Susan Adanna Ihejirika, Alexandra Huong Chiang, Aryaman Singh +3 more · 2025 · HGG advances · Elsevier · added 2026-04-24
Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unident Show more
Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unidentified gene-FOS interactions. To identify genetic factors that interact with FOS to alter the circulating levels of PUFAs, we performed a multi-level genome-wide interaction study (GWIS) of FOS on 14 plasma measurements in 200,060 unrelated European-ancestry individuals from the UK Biobank. From our single-variant tests, we identified genome-wide significant interacting SNPs (p < 5 × 10 Show less
📄 PDF DOI: 10.1016/j.xhgg.2025.100459
FADS1
Shuanghui Chen, Yan Lu, Hao Chen +6 more · 2025 · Molecular biology and evolution · Oxford University Press · added 2026-04-24
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins Show more
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins and admixture history remain largely unexplored. Here, we present the first comprehensive genomic study of Kirgiz populations from Xinjiang, China (XJ.KGZ, n = 36) and their counterparts in Kyrgyzstan (KRG), integrating genome-wide data of 2,406 global individuals. Our analyses reveal four primary ancestry components in XJ.KGZ: East Asian (41.7%), Siberian (25.6%), West Eurasian (25.2%), and South Asian (7.6%). Despite close genetic affinity (FST = 0.13%), XJ.KGZ and KRG diverged ∼447 years ago, with limited gene flow post-split. A two-wave admixture model elucidates their demographic history: an initial East-West Eurasian mixture ∼2,225 years ago, likely reflecting west-east contacts during the period of the Warring States and the Qin Dynasty, followed by secondary admixture events (∼875 to 425 years ago) linked to historical migrations under Mongol and post-Mongol rule. Local adaptation signatures implicate genes critical for cellular tight junction (e.g. PATJ), pathogen invasion (e.g. OR14I1), and cardiac functions (e.g. RYR2) with allele frequency deviations suggesting ancestry-specific selection. While no classical high-altitude adaptation genes (e.g. EPAS1) showed selection signals, RYR2 and C10orf67-implicated in hypoxia response in Tibetan fauna-displayed Western ancestry bias, hinting at convergent adaptation mechanisms. This study advances our understanding of the genetic makeup and admixture history of the Kirgiz people and provides novel insights into human dispersal in Central Asia. Show less
no PDF DOI: 10.1093/molbev/msaf196
PATJ
Jiahao Liu, Hongqing Zhu, Ziying Wang +6 more · 2025 · IEEE journal of biomedical and health informatics · IEEE · added 2026-04-24
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, Show more
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemic stroke lesions in CT images, consisting of a segmentation branch and a prompt-aware branch. The segmentation branch uses an encoder-decoder network as the backbone to identify lesions, where the encoder fuses CT image features with prompt features from the prompt-aware branch. To enhance semantic feature extraction and reduce the impact of cerebral structural details, we introduce a cross-collaboration dynamic connection (CCDC) module to link the encoder and decoder. The prompt-aware branch includes a learnable prompt (LP) block to incorporate cerebral prior knowledge, and the prompt-aware encoder (PAE) combines the LP block with multi-level features from the segmentation branch for more precise representation. Additionally, we propose a CLIP-enhance textual prompt (CETP) module that utilizes the CLIP text encoder to generate specialized convolutional parameters for the segmentation head. These parameters are tailored to the unique characteristics of each input image, improving segmentation performance. Qualitative and quantitative studies reveal that DCTP-Net outperforms the current state-of-the-art, IS-Net, with Dice score increases of 3.9% on AISD and 3.8% on ISLES2018, demonstrating its superiority in EIL segmentation. Show less
no PDF DOI: 10.1109/JBHI.2024.3471627
CETP
Liqun Ling, Tianqi Hu, Chenkang Zhou +7 more · 2025 · Molecular cancer · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, demonstrates critical regulatory involvement of RNA-binding proteins (RBPs) and circular RNAs (circRNAs) Show more
Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, demonstrates critical regulatory involvement of RNA-binding proteins (RBPs) and circular RNAs (circRNAs) in tumorigenic processes. Emerging evidence highlights the circRNA-autophagy regulatory axis as a crucial modulator of cancer progression. This study systematically investigates the functional interplay within the RBP-circRNA-autophagy network in LUAD pathogenesis. Employing RNA pull down, mass spectrometry and RNA immunoprecipitation facilitated the exploration of the circRAPGEF5 binding protein. M6A methylation RNA immunoprecipitation-PCR was utilized for m6A analysis. Immunofluorescence (IF) and fluorescence in situ hybridization (FISH) assays were conducted to ascertain the subcellular localization of target genes. Employing mRFP-GFP-LC3 fluorescent lentivirus labelling facilitated the monitoring of autophagy flow levels. Xenografts in mice were instrumental in affirming the role of circRAPGEF5. Through comprehensive molecular profiling, we identified elevated circRAPGEF5 expression in LUAD cells, which significantly suppressed autophagic flux while promoting malignant phenotypes including enhanced proliferation, migration, and invasion. Mechanistic investigations revealed that circRAPGEF5 directly interacts with the KH3-4 functional domain of Insulin-like Growth Factor 2 mRNA-Binding Protein 2 (IGF2BP2), an m6A reader protein. This interaction facilitated IGF2BP2-mediated stabilization of NUP160 mRNA, a nuclear pore complex component. Genetic ablation of NUP160 through RNA interference effectively restored autophagic activity, thereby attenuating the aggressive biological behaviors of LUAD cells. In vivo validation using xenograft models demonstrated that the circRAPGEF5/IGF2BP2/NUP160 signaling axis promotes tumor growth and metastatic dissemination through autophagy suppression. Our findings reveal a novel epigenetic regulatory mechanism wherein m6A-modified circRAPGEF5 orchestrates autophagy inhibition via IGF2BP2-dependent stabilization of NUP160 transcripts, ultimately driving LUAD progression and metastasis. These results establish the circRAPGEF5/IGF2BP2/NUP160 axis as a potential therapeutic target for LUAD intervention. Show less
no PDF DOI: 10.1186/s12943-025-02399-3
NUP160
Zhenwei Dai, Shu Jing, Haiyan Hu +8 more · 2025 · Brain and behavior · Wiley · added 2026-04-24
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult w Show more
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult women infected with HPV. This study aimed to adapt and validate the HPVsStigma scale (HPV-SS) in the Chinese context. A cross-sectional study was conducted from December 2024 to February 2025 among 501 HPV-infected women in Shenzhen, China. The HPV-SS was adapted from a 12-item HIV stigma scale. Demographic characteristics, HPV-related variables, and data on mental health were collected. Factor analyses (FA) were used to assess the scale's factorial structure, reliability, and validity. The bi-factor model was used to determine the score-reporting method of the scale. Item response theory (IRT) was employed to assess the relationship between participants' stigma levels and scale scores. Latent profile analysis (LPA) was conducted to classify the participants with different HPV stigma characteristics and determine the optimal cut-off value for HPV-SS. FA showed that the 3-factor model (personalized stigma, public-disclosure concerns, and negative self-image) had the best fit among the nested models, with good reliability and validity. The bi-factor model analysis indicated that the total scale score was more meaningful than dimension scores. IRT analysis confirmed that higher HPV-SS scores represented higher stigma levels. LPA identified a 2-class model as optimal, and the optimal cut-off value of the scale for high HPV stigma was 35. This study validated the 12-item HPV-SS for Chinese women infected with HPV, with good reliability and validity. The scale can be used to evaluate HPV stigma levels, facilitating targeted interventions to improve cervical cancer prevention and the psychological well-being of affected women. Show less
📄 PDF DOI: 10.1002/brb3.71044
LPA
Fabricio Ferreira de Oliveira, Sandro Soares de Almeida, Elizabeth Suchi Chen +2 more · 2025 · Sao Paulo medical journal = Revista paulista de medicina · added 2026-04-24
Lipid profiles are largely determined by genetic variants, and lipid metabolism plays a crucial role in Alzheimer's disease. To investigate whether lipid profile variability in response to diverse sta Show more
Lipid profiles are largely determined by genetic variants, and lipid metabolism plays a crucial role in Alzheimer's disease. To investigate whether lipid profile variability in response to diverse statins could be affected by cholesterol metabolism-related genetic variants in Alzheimer's disease.. This prospective observational pharmacogenetic study was conducted at the Universidade Federal de São Paulo (Unifesp), Brazil. Consecutive outpatients were prospectively followed for lipid profile variations over one year, estimated by the associations between statin therapy and the following variants: rs2695121 (NR1H2), rs3846662 (HMGCR), rs11669576 (LDLR8), rs5930 (LDLR10), rs5882 and rs708272 (CETP), rs7412 and rs429358 (APOE), and ACE insertion/deletion polymorphism. All polymorphisms in the 189 patients were in Hardy-Weinberg equilibrium. Statins resulted in lower total cholesterol and LDL cholesterol levels, whereas the effects on HDL cholesterol varied according to the statin used. Atorvastatin resulted in lower triglyceride level variations than simvastatin. APOE-ε4 carriers showed a better response to atorvastatin in elevating HDL-cholesterol than APOE-ε4 non-carriers. Carriers of the ACE insertion allele had cumulatively lower total cholesterol and LDL-cholesterol levels, regardless of statin therapy, but lower triglyceride levels when using atorvastatin. Carriers of rs11669576-G had lower total cholesterol and LDL-cholesterol levels when using simvastatin, and lower total cholesterol and triglycerides when using atorvastatin. Concerning CETP haplotypes, carriers of rs5882-A and rs708272-A benefitted the most from statins, which lowered total cholesterol and increased HDL-cholesterol levels, and from atorvastatin lowering triglycerides; however, the effects of atorvastatin lowering total cholesterol and LDL-cholesterol were more pronounced for carriers of rs5882-GG/rs708272-GG. Lipid profile variations may be pharmacogenetically mediated in Alzheimer's disease, thus, confirming their high heritability. Show less
📄 PDF DOI: 10.1590/1516-3180.2024.0160.27112024
CETP
Wei Wang, Zhaosu Song, Ye Chen +6 more · 2025 · Journal of food science · Blackwell Publishing · added 2026-04-24
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi- Show more
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi-component activity. The effectiveness of these botanical extracts is thought to involve complex interactions among diverse constituents; however, the molecular basis of such interactions remains insufficiently understood. In this study, we explored the anti-inflammatory properties of the ethanol extract of Polygonum multiflorum (PME) through a combination of chemical profiling and computational analysis. PME was found to reduce the production of nitric oxide, inducible nitric oxide synthase, and interleukin-6 in LPS-stimulated RAW 264.7 macrophages. Using HS-SPME-GC-MS in conjunction with network pharmacology, we identified 32 volatile constituents, among which five core compounds were predicted to be associated with three inflammation-related targets: ESR1, FASN, and NR1H3. Dual-ligand molecular docking and molecular dynamics simulations suggested that the sequence of ligand binding may influence the stability and interaction patterns of protein-ligand complexes, offering insights into possible mechanisms of synergy and antagonism mediated by key residues such as ARG394 in ESR1. Overall, these findings contribute to a better understanding of how binding order and structural context may shape constituent-target interactions, providing a basis for the further development of multi-component natural product strategies against inflammation. This study underscores the relevance of incorporating multi-ligand dynamics into natural product research and presents an integrated experimental-computational framework to investigate the cooperative or competitive behaviors of functional food constituents, thereby supporting the rational design of optimized multi-target formulations. Show less
no PDF DOI: 10.1111/1750-3841.70708
NR1H3
Lei Xia, Junjie Li, Yayan Pang +12 more · 2025 · Science advances · Science · added 2026-04-24
β-Site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) is the rate-limiting enzyme for amyloid-β (Aβ) generation and is considered promising drug target for Alzheimer's disease (AD). The co- Show more
β-Site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) is the rate-limiting enzyme for amyloid-β (Aβ) generation and is considered promising drug target for Alzheimer's disease (AD). The co-chaperone BAG3 (Bcl-2-associated athanogene 3) plays an important role in maintaining intracellular protein homeostasis by regulating heat shock protein 70 (HSP70). Here, we reported that BAG3 expression was significantly elevated in AD. It interacted with and stabilized BACE1 by delaying its degradation through ubiquitin-proteasome and autophagy-lysosomal pathways. BAG3 Show less
📄 PDF DOI: 10.1126/sciadv.adt7981
BACE1
Miao Sun, Yan Liu, Maolin Liu +5 more · 2025 · Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology · Taylor & Francis · added 2026-04-24
Congenital hypogonadotropic hypogonadism (CHH) is a rare condition characterized by incomplete pubertal development, infertility, and gonadotropin-releasing hormone deficiency, associated with mutatio Show more
Congenital hypogonadotropic hypogonadism (CHH) is a rare condition characterized by incomplete pubertal development, infertility, and gonadotropin-releasing hormone deficiency, associated with mutations in more than 50 genes. We aimed to conduct an etiological analysis of a CHH Chinese family and summarize the clinical presentations and genetic changes of reported similar cases. Whole-exome sequencing (WES) was performed to identify the molecular cause in the proband. In silico tools were employed to analyze the pathogenicity of the variants. Reported cases with similar clinical features and associated genes were summarized by searching through PubMed/MEDLINE using keywords 'FGFR1,' 'CHH,' and 'Kallmann syndrome (KS).' Genetic analysis revealed a novel likely pathogenic deletion mutation in the FGFR1 gene (NM₀₂₃₁₁₀.3: c.263₂₆₄del (Val88Alafs*22)) in a Chinese family exhibiting micropenis and underdeveloped testes. A total of 38 cases with CHH or KS have been previously reported. This study identified a novel FGFR1 deletion variant responsible for CHH, expanding the known mutational spectrum of FGFR1. Typical manifestations include delayed puberty and diverse presentations. The genotype-phenotype correlation in CHH remains unclear and may involve oligogenic effects and epigenetic regulation. Show less
no PDF DOI: 10.1080/09513590.2025.2571656
FGFR1
Jun He, Brenda Cabrera-Mendoza, Dan Qiu +7 more · 2025 · medRxiv : the preprint server for health sciences · added 2026-04-24
While previous genome-wide association studies (GWAS) identified multiple risk loci for suicide ideation (SI) and suicide attempt (SA), there is still a limited understanding of the genetic predisposi Show more
While previous genome-wide association studies (GWAS) identified multiple risk loci for suicide ideation (SI) and suicide attempt (SA), there is still a limited understanding of the genetic predisposition underlying suicidal behaviors in diverse populations. This study aimed to conduct a large-scale investigation of the suicidality spectrum (SP) to generate new insights into its biology and epidemiology. Leveraging ancestrally diverse participants (SI N This study provides convergent genetic evidence for both shared and phenotype-specific components of suicidal behaviors and delineates their associated factors spanning from proximal clinical and behavioral traits to more distal social determinants. These findings refine our understanding of the etiology of suicidal behaviors and may inform targeted strategies for suicide prevention in both clinical and public health settings. Show less
no PDF DOI: 10.64898/2025.12.15.25342298
BRWD1