👤 Mei-Hua Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, Zhezhe Chen, Zhi Bin Chen, Zhi Chen, Zhi-Hao Chen, Zhi-bin Chen, Zhi-zhe Chen, Zhiang Chen, Zhichuan Chen, Zhifeng Chen, Zhigang Chen, Zhigeng Chen, Zhiguo Chen, Zhihai Chen, Zhihang Chen, Zhihao Chen, Zhiheng Chen, Zhihong Chen, Zhijian Chen, Zhijian J Chen, Zhijing Chen, Zhijun Chen, Zhimin Chen, Zhinan Chen, Zhiping Chen, Zhiqiang Chen, Zhiquan Chen, Zhishi Chen, Zhitao Chen, Zhiting Chen, Zhiwei Chen, Zhixin Chen, Zhixuan Chen, Zhixue Chen, Zhiyong Chen, Zhiyu Chen, Zhiyuan Chen, Zhiyun Chen, Zhizhong Chen, Zhong Chen, Zhongbo Chen, Zhonghua Chen, Zhongjian Chen, Zhongliang Chen, Zhongxiu Chen, Zhongzhu Chen, Zhou Chen, Zhouji Chen, Zhouliang Chen, Zhoulong Chen, Zhouqing Chen, Zhuchu Chen, Zhujun Chen, Zhuo Chen, Zhuo-Yuan Chen, ZhuoYu Chen, Zhuohui Chen, Zhuojia Chen, Zi-Jiang Chen, Zi-Qing Chen, Zi-Yang Chen, Zi-Yue Chen, Zi-Yun Chen, Zian Chen, Zifan Chen, Zihan Chen, Zihang Chen, Zihao Chen, Zihe Chen, Zihua Chen, Zijie Chen, Zike Chen, Zilin Chen, Zilong Chen, Ziming Chen, Zinan Chen, Ziqi Chen, Ziqing Chen, Zitao Chen, Zixi Chen, Zixin Chen, Zixuan Chen, Ziying Chen, Ziyuan Chen, Zoe Chen, Zongming E Chen, Zongnan Chen, Zongyou Chen, Zongzheng Chen, Zugen Chen, Zuolong Chen
articles
Xiaoju Liu, Congcong Li, Qingyin Meng +7 more · 2025 · ACS infectious diseases · ACS Publications · added 2026-04-24
Derazantinib (DZB), a pan-fibroblast growth factor receptor (FGFR) inhibitor, exhibits potent activity against FGFR1-3 kinases and has been clinically approved for antitumor therapy. However, its anti Show more
Derazantinib (DZB), a pan-fibroblast growth factor receptor (FGFR) inhibitor, exhibits potent activity against FGFR1-3 kinases and has been clinically approved for antitumor therapy. However, its antibacterial properties remain unknown. Here, we demonstrated that DZB displays broad-spectrum activity against Show less
no PDF DOI: 10.1021/acsinfecdis.4c01020
FGFR1
Yuting Li, Mingrui Wang, Na Zhang +3 more · 2025 · Ginekologia polska · added 2026-04-24
This study investigates the relationship between serum homocysteine, blood lipids, and perinatal outcomes in patients with diet-controlled gestational diabetes mellitus (GDM) and those with normal glu Show more
This study investigates the relationship between serum homocysteine, blood lipids, and perinatal outcomes in patients with diet-controlled gestational diabetes mellitus (GDM) and those with normal glucose tolerance (NGT). A prospective cohort of 150 diet-controlled GDM patients and 150 pregnant women with NGT, all delivering at our hospital, were selected based on predefined criteria. Data on demographics, physical parameters, and perinatal outcomes were compiled. Blood samples for fasting plasma glucose (FPG), homocysteine (Hcy), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB), and apolipoprotein A1 (apoA1) were collected before delivery. GDM patients exhibited higher levels of FPG, Hcy, and the apoB/apoA1 ratio, but lower HDL-C and apoA1 levels compared to the NGT group. Adverse outcomes such as macrosomia, premature rupture of membranes, and postpartum hemorrhage were more prevalent in the GDM group. In GDM patients, neonatal birth weight positively correlated with FPG and TG levels. Stratified Hcy analysis in GDM showed no significant differences in perinatal outcomes. However, the third quartile of the apoB/apoA1 ratio had a lower incidence of macrosomia compared to the first quartile, and the second quartile showed a higher incidence of birth asphyxia. GDM patients demonstrated increased levels of Hcy, FPG, and the apoB/apoA1 ratio, correlating with more adverse perinatal outcomes than healthy pregnant individuals. The relationships between Hcy, lipids, and these outcomes remain inconclusive, highlighting the need for further research. Show less
no PDF DOI: 10.5603/gpl.101475
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
Yang-Hsiang Lin, Cheng-Yi Chen, Hsiang-Cheng Chi +3 more · 2025 · Translational oncology · Elsevier · added 2026-04-24
Liver cancer, encompassing hepatocellular carcinoma (HCC) and hepatoblastoma, the latter of which primarily occurs in early childhood, is the most common malignant tumor arising from liver and is resp Show more
Liver cancer, encompassing hepatocellular carcinoma (HCC) and hepatoblastoma, the latter of which primarily occurs in early childhood, is the most common malignant tumor arising from liver and is responsible for a significant number of cancer-related deaths worldwide. Targeted drugs have been used for anti-liver cancer treatment in the advanced stage, while their efficacy is greatly compromised by development of drug resistance. Drug resistance is a complicated process regulated by intrinsic and extrinsic signals and has been associated with poorer prognosis in cancer patients. In the current study, online available dataset analysis uncovered that angiopoietin-like protein 3 (ANGPTL3) manifested lower expression in sorafenib-resistant liver cancer cell lines. Additionally, ANGPTL3 was downregulated in HCC tissues, with its expression positively correlated with good prognosis. Functionally, ectopic expression of ANGPTL3 re-sensitized sorafenib-resistant cells, enhancing the sorafenib-induced reduction in cell viability and migration by suppressing zinc finger protein SNAI1 (SNAI1) expression and the protein stability of carnitine O-palmitoyltransferase 1, liver isoform (CPT1A). Clinical correlation analysis revealed that ANGPTL3 was negatively associated with SNAI1 expression. In conclusion, we identify a novel association between ANGPTL3, SNAI1 and CPT1A on sorafenib therapeutic response. Targeting ANGPTL3/SNAI1/CPT1A axis may serve as a therapeutic approach to improve prognosis of liver cancer patients with sorafenib resistance. Show less
no PDF DOI: 10.1016/j.tranon.2024.102250
SNAI1
Yilin Chen, Xiaofeng Ding, Sonalika Ray +10 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Despite effective viral suppression with antiretroviral therapy (ART), people living with HIV (PLWH) experience persistent inflammation, immune dysfunction, and premature onset of cardiovascular and a Show more
Despite effective viral suppression with antiretroviral therapy (ART), people living with HIV (PLWH) experience persistent inflammation, immune dysfunction, and premature onset of cardiovascular and aging-related comorbidities. To define the underlying mechanisms, we performed longitudinal transcriptomic profiling in peripheral blood mononuclear cells (PBMCs) from a cohort of simian immunodeficiency virus (SIV)-infected rhesus macaques spanning four key stages: pre-infection, acute infection, short-term ART, and long-term ART. Bulk RNA sequencing revealed dynamic immune remodeling across infection and treatment. Acute SIV infection induced robust antiviral and inflammatory programs, with upregulation of interferon-stimulated genes (ISGs), IL-27, JAK/STAT, and NF-κB signaling, coupled with suppression of T- and B-cell activation pathways. Short-term ART effectively reversed these transcriptional perturbations, restoring adaptive immune gene expression and reducing innate antiviral responses to near-baseline levels. In contrast, chronic SIV infection on long-term ART maintained viral suppression but was characterized by reactivation of innate immune pathways, including TLR2/TLR4/MYD88, NF-κB, and inflammasome (NLRP3/or NLRP12, caspase-1) signaling, along with sustained macrophage activation, platelet/coagulation signaling, and senescence-associated secretory phenotype. Protein analyses confirmed persistent CASPASE-1 and NF-κB activation in spleen tissue. Pathologic evaluation of a carotid artery from an SIV-infected, long-term ART-treated macaque revealed macrophage-rich plaques with p21 Show less
📄 PDF DOI: 10.1101/2025.11.05.686810
IL27
Yi Liu, Hanyuan Liu, Chenchen Zhu +5 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
High-grade serous ovarian cancer (HGSOC) is the most lethal type of gynecological cancer, and platinum-resistance is a serious challenge in its treatment. Long non-coding RNAs (lncRNAs) play critical Show more
High-grade serous ovarian cancer (HGSOC) is the most lethal type of gynecological cancer, and platinum-resistance is a serious challenge in its treatment. Long non-coding RNAs (lncRNAs) play critical regulatory roles in the occurrence and development of cancers. Here, using RNA sequencing of tumor small extracellular vesicles (sEVs) from HGSOC patients, the lncRNA CATED is identified as significantly upregulated in both tumors and tumor-derived sEVs in platinum-resistant HGSOC, and low CATED levels correlate with good prognosis. Functionally, CATED enhances cisplatin resistance by promoting cell proliferation and inhibiting apoptosis in vitro and in vivo. These effects could be transferred via CATED-overexpressing sEVs from donor cells and HGSOC tumor sEVs. Mechanistically, CATED binds to and upregulates DHX36 via PIAS1-mediated SUMOylation at the K105 site, and elevated DHX36 levels increase downstream RAP1A protein levels by enhancing RAP1A mRNA translation, consequently activating the MAPK pathway to promote platinum-resistance in HGSOC. Antisense oligonucleotide mediated knockdown of CATED reverse platinum-resistance in sEV-transmitted mouse models via the DHX36-RAP1A-MAPK pathway. This study newly identifies a sEV-transmitted lncRNA CATED in driving HGSOC platinum-resistance and elucidates the mechanism it regulates the interacting protein through SUMOylation. These findings also provide a novel strategy for improving chemotherapy in HGSOC by targeting CATED. Show less
📄 PDF DOI: 10.1002/advs.202505963
DHX36
Xuan-Ling Li, Zhi-Heng Lin, Si-Ru Chen +7 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, a Show more
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, and the increased risk of MCI and AD is associated with the lack of estrogen during menopause. Previous studies have shown that Tiao Geng Decoction (TGD) may have antioxidant and anti apoptotic properties, which may prevent neurodegenerative diseases. However, whether TGD is effective in improving mild cognitive impairment due to postmenopausal estrogen deficiency and its potential pharmacological mechanisms remain unclear. The aim of this study was to investigate the possible pharmacological mechanisms of TGD in preventing postmenopausal MCI. We utilized RNA-seq technology to screen for differentially expressed genes (DEGs) and enrichment pathways in the hippocampal tissue of different groups of mice. Additionally, we adopted single-cell sequencing technology to study the cell types of Alzheimer's disease (AD) group and Normal Control (NC) group, the differential marker genes of each cell subgroup, and the GO enrichment analysis of each cell type. Both RNA sequencing and single-cell sequencing results showed a significant correlation between TGD and NF-κb pathway in improving mild cognitive impairment in postmenopausal women. The experimental verification results showed that the spatial learning and memory abilities of APP/PS1 model mice were weakened after ovariectomy, and the reproductive cycle on vaginal smears was in the interphase of diestrus. The levels of serum E2, and P-tau181 in mice were significantly down regulated, while the levels of brain tissue homogenate A β 42, IL-1 β, and IL-18 were significantly up-regulated, indicating successful modeling. Combining Western blotting, RT-qPCR, and transmission electron microscopy analyses, it was found that the low estrogen environment induced by oophorectomy can activate the NF-κb signaling pathway, activate the expression of NLRP3 inflammasome and A β secretase BACE1, and induce neuroinflammatory damage in hippocampal astrocytes. These results conform to the modeling characteristics of MCI. After TGD intervention, the spatial learning and memory abilities of MCI mice were significantly improved. The pharmacological validation results indicated that high concentration doses of TGD had a more significant effect on MCI. Subsequently, we used high concentration TGD (0.32 g/ml) as the traditional Chinese medicine group for further validation, protein blotting and RT-qPCR results indicated that TGD can effectively stimulate the secretion of ER α and ER β, inhibit the NF-κb pathway, downregulate BACE1, and inhibit the expression of NLRP3 inflammasome related proteins. In addition, the immunofluorescence results of hippocampal astrocytes showed that TGD can effectively facilitate the expression of AQP1 and significantly lower the sedimentation of A β compared with the model group. Our research suggests that there is a high correlation between a low estrogen environment and the occurrence and development of MCI. TGD may regulate the ERs/NF - κ b/AQP1 signaling pathway, promote estrogen secretion, activate AQP1, reduce A β deposition, reverse MCI neuroinflammatory injury, improve mild cognitive impairment, and prevent the occurrence of AD. This study revealed for the first time that TGD may be a potential new alternative drug for preventing and improving menopausal MCI. Show less
no PDF DOI: 10.1016/j.phymed.2025.156391
BACE1
Yiming Tao, Zeyu Yang, Huimin Hou +4 more · 2025 · International journal of surgery (London, England) · added 2026-04-24
Sepsis remains a leading cause of mortality in critical care, with limited reliable biomarkers that reflect upstream pathophysiology and enable early risk stratification. Apolipoprotein E (ApoE), a li Show more
Sepsis remains a leading cause of mortality in critical care, with limited reliable biomarkers that reflect upstream pathophysiology and enable early risk stratification. Apolipoprotein E (ApoE), a lipid transporter with immune-regulatory functions, has shown inconsistent associations with sepsis outcomes. Its causal and clinically actionable role in sepsis risk requires clarification. We employed a multi-layered strategy integrating Mendelian randomization, colocalization, and phenome-wide association studies across five large proteogenomic cohorts (>500,000 individuals) to identify plasma proteins causally linked to sepsis. ApoE emerged as a top candidate and was validated in a clinical cohort of 291 ICU patients and in murine sepsis models. We assessed the relationship between ApoE levels and sepsis risk using logistic regression, restricted cubic spline models, and survival analyses, and explored underlying mechanisms via cytokine profiling, histopathology, and transcriptomics. ApoE was causally associated with sepsis risk in multiple independent datasets, supported by strong genetic colocalization (posterior probability for shared causal variant PP.H4 > 0.80). In ICU patients, both low (adjusted OR 12.74, 95% CI 5.72-28.36) and high ApoE levels (adjusted OR 4.54, 95% CI 2.25-9.16) were independently associated with increased sepsis risk compared to medium levels, forming a significant U-shaped pattern (P_nonlinear < 0.001). This biphasic risk was mirrored in murine models, where both hypo- and hyper-expression of ApoE aggravated systemic inflammation, organ injury, and mortality. LDL cholesterol mediated only ~ 20% of the ApoE-sepsis association, indicating lipid-independent mechanisms. Plasma ApoE functions as a biphasic, dose-sensitive modulator of host response to sepsis. Both deficiency and excess disturb immune homeostasis and increase susceptibility, underscoring the need for precision-guided ApoE modulation in sepsis management. These findings provide a mechanistically grounded biomarker candidate and highlight new avenues for personalized therapy. Prospective trials are warranted to evaluate ApoE-targeted strategies in sepsis care. Show less
no PDF DOI: 10.1097/JS9.0000000000004141
APOE
Xue Li, Luping Liu, Li Jiang +7 more · 2025 · Journal of molecular cell biology · Oxford University Press · added 2026-04-24
📄 PDF DOI: 10.1093/jmcb/mjae053
IL27
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Kang-Chih Fan, Szu-Chi Chen, I-Weng Yen +7 more · 2025 · Archives of medical science : AMS · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANG Show more
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANGPTL4 levels are observed in diabetic and obese individuals. However, the potential link between ANGPTL4 and diabetes- or obesity-related complications remains uncertain. This study aimed to explore whether plasma ANGPTL4 level could serve as a predictor of cancer mortality, cardiovascular mortality, and all-cause mortality in a community-based cohort. A community-based cohort study was conducted, where fasting plasma ANGPTL4 concentrations were measured at baseline, and vital status was ascertained through linkage with the National Health Insurance Research Database in Taiwan. During a 10.46-year follow-up period, 29 (2.49%) of the 1163 participants died. Subjects within the highest tertile of plasma ANGPTL4 levels exhibited the lowest survival rate. In unadjusted models, plasma ANGPTL4 significantly predicted all-cause mortality, cancer mortality, and cardiovascular or cancer-related mortality. Upon adjustment for confounders including age, sex, smoking, body mass index (BMI), hypertension, diabetes mellitus (DM), and renal function, each standard deviation increase in plasma ANGPTL4 was associated with HRs of 1.35 (95% CI: 1.01-1.80, Plasma ANGPTL4 emerges as a promising biomarker capable of predicting 10-year mortality and enhancing risk prediction beyond established risk factors. Show less
📄 PDF DOI: 10.5114/aoms/189504
ANGPTL4
Qin Tian, Jinxiang Wang, Qiji Li +16 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-ac Show more
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-acid dehydrogenase kinase (BCKDK) has been implicated in promoting RCC metastasis, but its specific substrates and the mechanisms underlying its regulation of RCC progression remain poorly understood. This study uncovers a novel mechanism whereby BCKDK-mediated AKT phosphorylation drives RCC tumorigenesis and drug resistance. Elevated BCKDK expression correlates with poor prognosis in RCC clinical samples. BCKDK deficiency inhibits RCC cell proliferation and tumorigenesis both in vitro and in vivo. Mechanistic investigations reveal that BCKDK directly binds to and regulates the phosphorylation of AKT. BCKDK-mediated phosphorylation of AKT decreases ubiquitin-mediated AKT protein degradation, and promotes tumorigenesis via activation of the AKT/mTOR signaling pathway. RNA sequencing identifies BCKDK's involvement in the drug metabolism network and apoptotic signaling pathways. The BCKDK/AKT/ABCB1 axis mediates doxorubicin resistance. Targeting BCKDK/AKT inhibits the growth of RCC patient-derived organoids (PDOs), enhances doxorubicin-induced apoptosis in RCC cells, and suppresses tumor growth in vivo. These findings identify a previously unrecognized phosphorylation substrate of BCKDK and highlight the critical role of the BCKDK/AKT signaling axis in RCC progression, offering a promising target for therapeutic intervention. Show less
📄 PDF DOI: 10.1002/advs.202411081
BCKDK
Sheng Zhang, Yijun Chen, Yaxue Lv +2 more · 2025 · Journal of animal science and biotechnology · BioMed Central · added 2026-04-24
Poor feather growth not only affects the appearance of the organism but also decreases the feed efficiency. Methionine (Met) is an essential amino acid required for feather follicle development; yet t Show more
Poor feather growth not only affects the appearance of the organism but also decreases the feed efficiency. Methionine (Met) is an essential amino acid required for feather follicle development; yet the exact mechanism involved remains insufficiently understood. A total of 180 1-day-old broilers were selected and randomly divided into 3 treatments: control group (0.45% Met), Met-deficiency group (0.25% Met), and Met-rescue group (0.45% Met in the pre-trial period and 0.25% Met in the post-trial period). The experimental period lasted for 56 d, with a pre-trial period of 1-28 d and a post-trial period of 29-56 d. In addition, Met-deficiency and Met-rescue models were constructed in feather follicle epidermal stem cell by controlling the supply of Met in the culture medium. Dietary Met-deficiency significantly (P < 0.05) reduced the ADG, ADFI and F/G, and inhibited feather follicle development. Met supplementation significantly (P < 0.05) improved growth performance and the feather growth in broilers. Met-rescue may promote feather growth in broilers by activating the Wnt/β-catenin signaling pathway (GSK-3β, CK1, Axin1, β-catenin, Active β-catenin, TCF4, and Cyclin D1). Compared with Met-deficiency group, Met-rescue significantly (P < 0.05) increased the activity of feather follicle epidermal stem cell and mitochondrial membrane potential, activated Wnt/β-catenin signaling pathway, and decreased the content of reactive oxygen species (P < 0.05). CO-IP confirmed that mitochondrial protein PGAM5 interacted with Axin1, the scaffold protein of the disruption complex of the Wnt/β-catenin signaling pathway, and directly mediated Met regulation of Wnt/β-catenin signaling pathway and feather follicle development. PGAM5 binding to Axin1 mediates the regulation of Wnt/β-catenin signaling pathway, and promotes feather follicle development and feather growth of broiler chickens through Met supplementation. These results provide theoretical support for the improvement of economic value and production efficiency of broiler chickens. Show less
📄 PDF DOI: 10.1186/s40104-025-01176-y
AXIN1
I-Weng Yen, Szu-Chi Chen, Chia-Hung Lin +9 more · 2025 · Journal of diabetes investigation · Blackwell Publishing · added 2026-04-24
The early detection of high-risk individuals is crucial to delay and reduce the incidence of type 2 diabetes. In this study, we aimed to explore the performance of a novel subgroup-specific biomarker Show more
The early detection of high-risk individuals is crucial to delay and reduce the incidence of type 2 diabetes. In this study, we aimed to explore the performance of a novel subgroup-specific biomarker strategy in the prediction of incident diabetes. In the Taiwan Lifestyle Cohort Study, adult subjects without diabetes were included and followed for the incidence of diabetes in 2006-2019. The biomarkers measured included blood secretogranin III (SCG3), vascular adhesion protein-1 (VAP-1), fibrinogen-like protein 1 (FGL1), angiopoietin-like protein 6 (ANGPTL6), and angiopoietin-like protein 4 (ANGPTL4). Among the 1,287 subjects, 12.2% developed diabetes during a 6 year follow-up. Blood VAP-1 was significantly associated with incident diabetes in the overall population (HR = 0.724, P < 0.05), participants under 65 years old (HR = 0.685, P < 0.05), those with a BMI of ≥24 kg/m Gender- and BMI-specific biomarker strategy can improve the prediction of incident diabetes. A subgroup-specific biomarker strategy is a novel approach in the prediction of incident diabetes. Show less
📄 PDF DOI: 10.1111/jdi.14311
ANGPTL4
Chung-Ming Lin, Ru-Huei Fu, Hui-Jye Chen · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Microtubule-actin cross-linking factor 1 (MACF1), also known as actin cross-linking family protein 7 (ACF7), is a giant cytolinker protein with multiple conserved domains that can orchestrate cytoskel Show more
Microtubule-actin cross-linking factor 1 (MACF1), also known as actin cross-linking family protein 7 (ACF7), is a giant cytolinker protein with multiple conserved domains that can orchestrate cytoskeletal networks of actin and microtubules. MACF1 is involved in various biological processes, including cell polarity, cell-cell connection, cell proliferation, migration, vesicle transport, signal transduction, and neuronal development. In this review, we updated the physiological and pathological roles of MACF1, highlighting the components and signaling pathways involved. Novel evidence showed that MACF1 is involved in diverse human diseases, including multiple neuronal diseases, congenital myasthenic syndrome, premature ovarian insufficiency, spectraplakinopathy, osteoporosis, proliferative diabetic retinopathy, and various types of cancer. We also reviewed the physiological roles of MACF1, including its involvement in adhesome formation, bone formation, neuronal aging, and tooth development. In addition, MACF1 plays other roles, functioning as a biomarker for the prediction of infections in patients with burns and as a marker for genome selection breeding. These studies reinforce the idea that MACF1 is a bona fide versatile, multifaceted giant protein. Identifying additional MACF1 functions would finally help with the treatment of diseases caused by MACF1 defects. Show less
📄 PDF DOI: 10.3390/ijms26073204
MACF1
Tong Zhou, Anqi Chen, Yuanyuan Sun +3 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Stroke, including cerebral ischemia and cerebral hemorrhage, is one of the leading causes of mortality worldwide. The narrow therapeutic window limits the efficacy and applicability of current treatme Show more
Stroke, including cerebral ischemia and cerebral hemorrhage, is one of the leading causes of mortality worldwide. The narrow therapeutic window limits the efficacy and applicability of current treatments such as thrombolysis and endovascular thrombectomy. This urgent need for effective therapies has shifted the focus towards mitigating the secondary inflammation and tissue damage that follow intracerebral hemorrhage. Spatial transcriptomic analysis of mouse brains post-ischemia has revealed that the ApoE-TREM2 signaling pathway is central to the complex interactions between microglia and various surrounding cells, coordinating the formation of neuroglial scars, suggesting that TREM2 is a key participant in post-stroke pathology and a potential therapeutic target. This review aims to provide an insightful synthesis of TREM2, including its structure, signaling pathways, and the role of its soluble form, sTREM2, in the nervous system. We systematically summarize the signaling pathways and mechanisms by which TREM2 modulates microglial function, including promoting phagocytosis, exerting anti-inflammatory properties, modulating lipid metabolism, and enhancing cell survival. We also highlight the TREM2's interactions with other cell types post-stroke, such as macrophages and B cells. Furthermore, we discuss advancements in TREM2-targeted drug development, emphasizing the potential of TREM2 agonists and antibodies to modulate microglial function and inflammation, which sets the stage for future research and drug development. Show less
📄 PDF DOI: 10.1007/s12035-025-05622-w
APOE
Dan Zeng, Yunsheng Zhang, Hu Xia +4 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
To investigate the key regulatory genes and pathways related to growth traits in the Dongtingking crucian carp (Carassius auratus indigentiaus), the transcriptomes of brain, intestine, and muscle tiss Show more
To investigate the key regulatory genes and pathways related to growth traits in the Dongtingking crucian carp (Carassius auratus indigentiaus), the transcriptomes of brain, intestine, and muscle tissues were sequenced at early juvenile stage using RNA-Seq from two groups with extreme growth rates (fast-growing and slow-growing). A total of 65, 184, and 130 differentially expressed genes (DEGs) were detected in the brain, intestine, and muscle, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted that the PPAR signaling pathway, Insulin/PI3K/Akt/mTOR/FoxO/AMPK pathway, and Protein digestion and absorption pathways are crucial for growth in this species. Based on the transcriptome data, 32 key DEGs were identified, mainly participating in processes such as cell proliferation and differentiation, growth, development, and metabolism. Prominent examples are cyclic AMP-responsive element-binding protein 5 (creb5b), forkhead box protein O1-A (foxo1a), transcription factor AP-1-like (jun), lipoprotein lipase-like (lpl), angiopoietin-like 4 (angptl4), and egl nine homolog 3-like (egln3). This study enhances the understanding of the genetic factors and regulatory mechanisms responsible for variations in growth rates and provides a valuable basis for further studies on the regulatory mechanisms of growth in C. auratus indigentiaus. Show less
no PDF DOI: 10.1016/j.cbd.2025.101538
ANGPTL4
Wenjie Luo, Yubin Chen, Cheng Fang +2 more · 2025 · Journal of receptor and signal transduction research · Taylor & Francis · added 2026-04-24
Atherosclerosis is characterized by persistent inflammatory condition, leading to various cardiovascular complications. Foam cell formation, resulting from macrophage uptake of oxidized low-density li Show more
Atherosclerosis is characterized by persistent inflammatory condition, leading to various cardiovascular complications. Foam cell formation, resulting from macrophage uptake of oxidized low-density lipoprotein (ox-LDL), contributes significantly to atherosclerosis progression. This study was designed to investigate the involvement of bispecific phosphatase-6 (DUSP6) and its potential regulatory mechanisms in foam cell formation and atherosclerosis. We employed THP-1 cells to induce foam cell formation. The lipid droplet accumulation, cholesterol content, tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 levels were evaluated using Oil Red O staining, cholesterol assay, ELISA, and qRT-PCR techniques. We investigated DUSP6 ubiquitination via immunoprecipitation and western blot (WB) analysis. A bioinformatics approach identified FBXL14 as a potential E3 ligase involved in DUSP6 ubiquitination, further confirmed by siRNA and overexpression experiments. The impact of FBXL14 on the NRF2 signaling pathway was assessed using WB analysis. DUSP6 interference suppressed foam cell formation and inflammatory factor secretion. Upon ox-LDL treatment, DUSP6 underwent deubiquitylation, with FBXL14 emerging as the candidate E3 ligase. FBXL14 overexpression induced DUSP6 ubiquitination, leading to the NRF2 signaling pathway activation. It counteracted with DUSP6 overexpression on foam cell formation and inflammation. In ApoE-/- mice, sh-DUSP6 adenovirus injection mitigated atherosclerotic lesion progression and improved the lipid profile, with increased the proteins expression of NQO1, HO-1, and NRF2 in aortic tissue. DUSP6 and FBXL14 play vital roles in modulating foam cell formation and inflammatory responses in atherosclerosis. Targeting these molecules could offer therapeutic potential in attenuating atherosclerosis-related complications. Not applicable. Show less
no PDF DOI: 10.1080/10799893.2025.2466689
DUSP6
Qiong-Wen Lu, Shao-Yuan Liu, Xiu-Quan Liao +6 more · 2025 · Nucleic acids research · Oxford University Press · added 2026-04-24
Oocyte maturation-coupled mRNA post-transcriptional regulation is essential for the establishment of developmental potential. Previously, oocyte mRNA translation efficiencies focused on the trans-regu Show more
Oocyte maturation-coupled mRNA post-transcriptional regulation is essential for the establishment of developmental potential. Previously, oocyte mRNA translation efficiencies focused on the trans-regulation of key RNA-binding protein (RBPs), rarely related to RNA structure. RNA G-quadruplexes (rG4s) are four-stranded RNA secondary structures involved in many different aspects of RNA metabolism. In this study, we have developed a low-input technique for rG4 detection (G4-LACE-seq) in mouse oocytes and found that rG4s were widely distributed in maternal transcripts, with enrichment in untranslated regions, and they underwent transcriptome-wide removal during meiotic maturation. The rG4-selective small-molecule ligand BYBX stabilized rG4s in the oocyte transcriptome and impaired spindle assembly and meiotic cell cycle progression. The proteomic spectrum results revealed that rG4 accumulation weakened the binding of a large number of RBPs to mRNAs, especially those associated with translational initiation. Ribosomal immunoprecipitation and translational reporter assays further proved that rG4s in the untranslated regions negatively affected the translational efficiency of key maternal mRNAs. Overexpression DEAH/RHA family helicase-36 partially reverses BYBX-induced oocyte developmental defects, suggesting its importance in rG4 regulation. Collectively, this study describes the distribution, dynamic changes, and regulation of rG4s in the mouse maternal transcriptome. Before meiosis resumption, a large number of rG4s in oocytes are necessary to maintain the translatome at a low level, and DHX36-mediated rG4 removal promotes a translational switch and is required for successful maternal-to-zygotic transition. Show less
📄 PDF DOI: 10.1093/nar/gkaf067
DHX36
Yuwei Liu, Nan Zheng, Huan Chen +3 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between the Show more
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between these groups and depressive symptoms. A total of 521 adolescents aged 13-18 years from Wuhan and Changsha, China, were included. Bouts of physical activity (PA) and sedentary behavior (SED) were measured using accelerometers. The Center for Epidemiologic Studies Depression Scale was used to assess participants' depressive symptoms. Latent profile analysis was employed to identify distinct groups based on their activity patterns. Three distinct groups were identified: "Prolonged sitters" ( The synergistic effect of strategies to reduce total SED duration by limiting SED bouts to 30 min or less and increasing light physical activity (LPA) may also be effective in alleviating depressive symptoms in adolescents. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1683685
LPA
Hongyu Kuang, Dan Li, Yunlin Chen +7 more · 2025 · Atherosclerosis · Elsevier · added 2026-04-24
Pathological cardiac hypertrophy is an independent risk factor for heart failure (HF). Early identification and timely treatment are crucial for significantly delaying the progression of HF. Targeted Show more
Pathological cardiac hypertrophy is an independent risk factor for heart failure (HF). Early identification and timely treatment are crucial for significantly delaying the progression of HF. Targeted amino acid metabolomics and RNA sequencing (RNA-seq) were combined to explore the underlying mechanism. In vitro, H9c2 cells were stimulated with angiotensin II (Ang II) or were incubated with extra valine after Ang II stimulation. The branched chain alpha-ketoate dehydrogenase kinase (Bckdk) inhibitor 3,6-dichlorobenzo[b]thiophene-2-carboxylic acid (BT2) and rapamycin were utilized to confirm the role of the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway in this process. A significant accumulation of valine was detected within hypertrophic hearts from spontaneously hypertensive rats (SHR). When branched chain amino acid (BCAA) degradation was increased by BT2, the most pronounced decrease was observed in the valine level (Δ = 0.185 μmol/g, p < 0.001), and cardiac hypertrophy was ameliorated. The role of imbalanced mitochondrial quality control (MQC), including the suppression of mitophagy and excessive mitochondrial fission, was revealed in myocardial hypertrophy. In vitro, high concentrations of valine exacerbated cardiomyocyte hypertrophy stimulated by Any II, resulting in the accumulation of impaired mitochondria and respiratory chain dysfunction. BT2, rapamycin, and mitochondrial division inhibitor 1 (Mdivi-1) all ameliorated MQC imbalance, mitochondrial damage and oxidative stress in hypertensive models with high valine concentration. Valine exacerbated pathological cardiac hypertrophy by causing a MQC imbalance, probably as an early biomarker for cardiac hypertrophy under chronic hypertension. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.119216
BCKDK
Eugene Lin, Yu-Ting Yan, Mu-Hong Chen +3 more · 2025 · Nature communications · Nature · added 2026-04-24
This pioneering genome-wide association study examined surrogate markers for insulin resistance (IR) in 147,880 Taiwanese individuals using data from the Taiwan Biobank. The study focused on two IR su Show more
This pioneering genome-wide association study examined surrogate markers for insulin resistance (IR) in 147,880 Taiwanese individuals using data from the Taiwan Biobank. The study focused on two IR surrogate markers: the triglyceride to high-density lipoprotein cholesterol (TG:HDL-C) ratio and the TyG index (the product of fasting plasma glucose and triglycerides). We identified genome-wide significance loci within four gene clusters: GCKR, MLXIPL, APOA5, and APOC1, uncovering 197 genes associated with IR. Transcriptome-wide association analysis revealed significant associations between these clusters and TyG, primarily in adipose tissue. Gene ontology analysis highlighted pathways related to Alzheimer's disease, glucose homeostasis, insulin resistance, and lipoprotein dynamics. The study identified sex-specific genes associated with TyG. Polygenic risk score analysis linked both IR markers to gout and hyperlipidemia. Our findings elucidate the complex relationships between IR surrogate markers, genetic predisposition, and disease phenotypes in the Taiwanese population, contributing valuable insights to the field of metabolic research. Show less
📄 PDF DOI: 10.1038/s41467-025-58506-x
APOA5
Chunming Cao, Qiyuan Hu, Xinyue Hu +6 more · 2025 · Journal of cardiothoracic surgery · BioMed Central · added 2026-04-24
The objective was to assess the clinical efficacy of long non-coding RNA (lncRNA) alpha-2-macroglobulin-antisense 1 (A2M-AS1) in acute myocardial infarction (AMI). One hundred patients with AMI and ei Show more
The objective was to assess the clinical efficacy of long non-coding RNA (lncRNA) alpha-2-macroglobulin-antisense 1 (A2M-AS1) in acute myocardial infarction (AMI). One hundred patients with AMI and eighty patients with chest pain were recruited in the case-control study. A2M-AS1 expression was examined by quantitative real-time polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) analysis was utilized for evaluating the diagnostic value. Pearson's correlation analysis was used to analyze the correlation between A2M-AS1 and conventional AMI biomarkers. AMI-associated risk indicators were identified using logistic regression analysis. A significant reduction of serum A2M-AS1 was measured in AMI patients relative to chest pain patients. A2M-AS1 had an area under the curve (AUC) of 0.927 to distinguish AMI patients from those with chest pain. Pearson's correlation analysis showed that A2M-AS1 was adversely correlated with white blood cell (WBC) (r=-0.6682, P < 0.001), low density lipoprotein cholesterol (LDL-C) (r=-0.5795, P < 0.001), creatine kinase MB (CK-MB) (r=-0.6022, P < 0.001) and cTnl (r=-0.5473; P < 0.001), while positively correlated with high density lipoprotein cholesterol (HDL-C) (r = 0.6445, P < 0.001). Relative to non-Major Adverse Cardiovascular Events (non-MACE) group, serum A2M-AS1 was obviously declined in the MACE group of AMI patients with high capacity to distinguish the MACE group from the non-MACE patients (AUC = 0.802). Additionally, A2M-AS1 (P = 0.013; OR = 0.268; 95%CI = 0.095-0.760) was a risk indicator for predicting MACE with AMI patients, as well as age (P = 0.014; OR = 3.478; 95%CI = 1.285-9.414). A reduction in A2M-AS1 expression was observed in AMI patients, suggesting its potential as an underlying indicator for AMI diagnosis. Show less
📄 PDF DOI: 10.1186/s13019-025-03381-2
APOB
Mei-Zhen Zhang, Jing Zheng, Li-Ting Cai +9 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
Scatophagus argus is a highly valuable aquaculture fish. Its artificial breeding faces problems in the induction of high quality eggs, thus necessitating studies on the regulation of ovarian developme Show more
Scatophagus argus is a highly valuable aquaculture fish. Its artificial breeding faces problems in the induction of high quality eggs, thus necessitating studies on the regulation of ovarian development. As the centre of nutrient metabolism in fish, the liver provides the material basis for ovarian development. However, the molecular mechanism of the liver in ovarian development in S. argus is still unclear. In this study, a transcriptome analysis of adult S. argus livers at different stages of ovarian development (stages II, III and IV) was performed. 410, 1025 and 1867 differentially expressed genes (DEGs) were obtained between stages II and III, stages II and IV and stages III and IV, respectively. In GO and KEGG analyses, DEGs were mostly involved in vitellogenesis and egg envelope formation (e.g., erα, erβ1, vtga, vtgb, vtgc, zp3, zp4a and zp4b), lipid metabolism and energy metabolism (e.g., dagt1, dagt2, lpl, apob, hk1, acly, ogdh, pc, and fbp1), and hormone signaling (e.g., lepa and igfbp1). Additionally, genes that were significantly upregulated in the liver at stage IV of ovarian development, compared to stages II and III, were markedly enriched in steroid biosynthesis and metabolism pathways. These findings provide clues to understanding the mechanisms of liver action in teleost ovarian development. Show less
no PDF DOI: 10.1016/j.cbd.2025.101550
APOB
Yadong Zheng, Kaili Chen, Shuo Zhang +6 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Atherosclerosis (AS), a chronic inflammatory condition of the vasculature, is a major contributor to cardiovascular morbidity. Yaoshi Tongyuan Tablet (YTT) is a food-medicine homology (FMH) formulatio Show more
Atherosclerosis (AS), a chronic inflammatory condition of the vasculature, is a major contributor to cardiovascular morbidity. Yaoshi Tongyuan Tablet (YTT) is a food-medicine homology (FMH) formulation containing A combination of network pharmacology, ultra-performance liquid chromatography coupled with Q Exactive Orbitrap mass spectrometry (UPLC-QE-MS), and molecular docking was employed to predict potential bioactive compounds and their molecular targets. ApoE Integrated analyses revealed kaempferol, isorhamnetin, and quercetin as central bioactive molecules acting on AKT1, a key node within the PI3K/Akt signaling cascade. YTT ameliorates atherosclerosis by counteracting dyslipidemia and inflammation, primarily through modulation of the PI3K/Akt/NF-κB pathway. This study offers novel integrative insights into the anti-atherogenic properties of YTT and pinpoint crucial bioactive constituents worthy of further pharmacological investigation. Show less
📄 PDF DOI: 10.3389/fphar.2025.1710585
APOE
Aleksandra Babicheva, Ibrahim Elmadbouh, Shanshan Song +19 more · 2025 · American journal of physiology. Lung cellular and molecular physiology · added 2026-04-24
Endothelial-to-mesenchymal transition (EndMT) is a biological process that converts endothelial cells to mesenchymal cells with increased proliferative and migrative abilities. EndMT has been implicat Show more
Endothelial-to-mesenchymal transition (EndMT) is a biological process that converts endothelial cells to mesenchymal cells with increased proliferative and migrative abilities. EndMT has been implicated in the development of pulmonary vascular remodeling in pulmonary arterial hypertension (PAH), a fatal and progressive lung vascular disease. Transforming growth factor β Show less
no PDF DOI: 10.1152/ajplung.00400.2024
SNAI1
Qi Chen, Yuan-Shu Peng, Qian Zhong +11 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Atherosclerosis (AS) is a chronic inflammatory disorder characterized by foam cell formation and persistent inflammation as central pathological drivers. Although colchicine (Col) exhibits potent anti Show more
Atherosclerosis (AS) is a chronic inflammatory disorder characterized by foam cell formation and persistent inflammation as central pathological drivers. Although colchicine (Col) exhibits potent anti-inflammatory activities, its clinical application is limited by a narrow therapeutic window. In the present study, we developed phosphatidylserine-exposing nanovesicles (Col@PSVs) that leverage the innate phagocytic capacity of macrophage-derived foam cells by presenting surface "eat-me" signals, thereby enabling targeted immune modulation. The synergistic collaboration between Col and PSVs allows low-dose Col to retain robust anti-inflammatory efficacy while mitigating dose-dependent toxicity. Mechanistically, Col@PSVs potently suppress CCR7-mediated NF-κB signaling activation in foam cells, leading to a marked downregulation of pro-inflammatory cytokine and disruption of inflammatory cascades. In ApoE Show less
📄 PDF DOI: 10.1186/s12951-025-03840-x
APOE
Lin Chen, Mingzhu Xu, Yan Zhu +1 more · 2025 · American journal of translational research · added 2026-04-24
To identify risk factors for heart failure (HF) within one year after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) and to develop a predictive nomogram model Show more
To identify risk factors for heart failure (HF) within one year after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) and to develop a predictive nomogram model. A retrospective analysis was performed on 492 patients with ACS treated at Suzhou Municipal Hospital between January 2020 and October 2023. Patients were divided into the HF group and the non-HF group according to the occurrence of HF within one year after PCI. 70% of the cases were randomly assigned to the training set and 30% to the validation set. Univariate and multivariate logistic regression analyses were conducted to screen independent predictors, and a nomogram model was subsequently established. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Among the 492 patients, the incidence of HF within one year after PCI was 26.42% (n = 130). Logistic regression identified type 2 diabetes mellitus (T2DM), left ventricular ejection fraction (LVEF), lipoprotein(a) [LP(a)], B-type natriuretic peptide (BNP), and high-sensitivity C-reactive protein (Hs-CRP) as independent predictors of HF, with odds ratios of 5.756, 0.904, 1.427, 1.012, and 1.666, respectively (all P < 0.05). The model demonstrated excellent discrimination, with areas under the ROC curve of 0.946 in the training set and 0.958 in the validation set. DCA indicated that the model provided greater net clinical benefit than the "treat-all" or "treat-none" strategies, and its predictive performance surpassed that of each individual factor (P < 0.05). The nomogram model incorporating T2DM, LVEF, LP(a), BNP and Hs-CRP provides an effective tool for predicting HF risk within one year after PCI in patients with ACS, offering valuable guidance for early clinical identification and risk stratification of high-risk individuals. Show less
no PDF DOI: 10.62347/DTOE6334
LPA
Zihao Zhou, Yidan Zheng, Shiyan Hu +13 more · 2025 · Heart (British Cardiac Society) · added 2026-04-24
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisyste Show more
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisystem comorbidity network of CAS and clarify underlying genetic mechanisms. In 467 484 participants from the UK Biobank, observational and polygenic phenome-wide association studies evaluated associations between CAS and 1571 phenotypes, integrating disease-trajectory analyses to visualise temporal patterns. Associations replicated across observational and polygenic analyses were tested using two-sample Mendelian randomisation (MR) based on 22 CAS-related variants from FinnGen. Polygenic risk score (PRS) analyses excluding specific genes assessed their contributions, particularly LPA and plasma lipoprotein(a) (Lp(a)) levels. CAS was associated with higher risks of 42 cardiovascular and non-cardiovascular conditions, most prominently metabolic, endocrine, haematological and respiratory disorders. Temporal analyses showed that circulatory and metabolic diseases typically precede other comorbidities in CAS trajectories. MR findings were consistent with causal effects of CAS on multiple cardiovascular diseases, iron-deficiency anaemia, mental disorders and pleural effusion. When LPA variants were removed from the CAS PRS or plasma Lp(a) concentration was adjusted for, most associations lost significance, indicating a shared LPA/Lp(a)-mediated genetic pathway. CAS is embedded within a broad multisystem comorbidity network, driven largely by genetic variation at LPA and elevated Lp(a). These findings highlight pleiotropic mechanisms linking valvular calcification with systemic disease and support LPA-targeted therapies as a promising avenue for reducing the multisystem burden of CAS. Show less
no PDF DOI: 10.1136/heartjnl-2025-326058
LPA
Jiao Gong, Huiru Sun, Kaiyuan Wang +26 more · 2025 · Nature communications · Nature · added 2026-04-24
Genomic structural variants (SVs) are a major source of genetic diversity in humans. Here, through long-read sequencing of 945 Han Chinese genomes, we identify 111,288 SVs, including 24.56% unreported Show more
Genomic structural variants (SVs) are a major source of genetic diversity in humans. Here, through long-read sequencing of 945 Han Chinese genomes, we identify 111,288 SVs, including 24.56% unreported variants, many with predicted functional importance. By integrating human population-level phenotypic and multi-omics data as well as two humanized mouse models, we demonstrate the causal roles of two SVs: one SV that emerges at the common ancestor of modern humans, Neanderthals, and Denisovans in GSDMD for bone mineral density and one modern-human-specific SV in WWP2 impacting height, weight, fat, craniofacial phenotypes and immunity. Our results suggest that the GSDMD SV could serve as a rapid and cost-effective biomarker for assessing the risk of cisplatin-induced acute kidney injury. The functional conservation from human to mouse and widespread signals of positive natural selection suggest that both SVs likely influence local adaptation, phenotypic diversity, and disease susceptibility across diverse human populations. Show less
no PDF DOI: 10.1038/s41467-025-56661-9
WWP2