👤 Xiao-Wei 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-Hua 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-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
Ruyi Liu, Miaomiao Fu, Pengxiang Chen +6 more · 2025 · International journal of oncology · added 2026-04-24
Angiopoietin‑like 4 (ANGPTL4), a member of the angiopoietin family, plays critical roles in angiogenesis, lipid metabolism and inflammation. It has been demonstrated that ANGPTL4 has significant influ Show more
Angiopoietin‑like 4 (ANGPTL4), a member of the angiopoietin family, plays critical roles in angiogenesis, lipid metabolism and inflammation. It has been demonstrated that ANGPTL4 has significant influence on various diseases. Accumulating evidence has highlighted the impacts of ANGPTL4 on human malignancies. ANGPTL4 is commonly overexpressed in various types of cancer, such as breast, non‑small cell lung, gastric and colorectal cancer. Its upregulation promotes tumor growth, invasion, metastasis and angiogenesis, as well as metabolic reprogramming and resistance to programmed cell death, radiotherapy and chemotherapy. However, ANGPTL4 has also exhibited antitumor effects under certain conditions, indicating its complex roles in tumor biology. The transcriptional regulation of ANGPTL4 is influenced by multiple factors, such as HIF‑1, PPARs, TGF‑β and long non‑coding RNAs. In terms of signaling pathways, STATs, PI3K/AKT and COX-2/PGE2 are important in regulating cellular processes. The present review summarizes the biological functions of ANGPTL4 in tumors and its association with patient prognosis. Furthermore, the key molecular mechanisms and potential reasons for its dual roles in cancer are also discussed. In conclusion, ANGPTL4 is a valuable diagnostic biomarker and a potential therapeutic target for human cancers. Show less
📄 PDF DOI: 10.3892/ijo.2024.5715
ANGPTL4
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
Lingyan Li, Xingjie Wu, Qianqian Guo +9 more · 2025 · Journal of pharmaceutical analysis · Elsevier · added 2026-04-24
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, over Show more
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in vascular endothelial cells and estrogen receptor alpha (ERα) protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation Show less
📄 PDF DOI: 10.1016/j.jpha.2024.101182
APOA5
Yi Li, Shuo Cong, Rui Chen +3 more · 2025 · Annals of medicine · Taylor & Francis · added 2026-04-24
Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases, with a range of manifestations, such as hepatic steatosis. Our previous study showed that Kaili Sour Soup Show more
Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases, with a range of manifestations, such as hepatic steatosis. Our previous study showed that Kaili Sour Soup (KSS) significantly attenuated hepatic steatosis in rats. This study explored the main components of KSS and the mechanisms by which it exerts its protective effects against NAFLD. Twenty-four 6-week-old male Sprague-Dowley (SD) rats were randomly assigned to three treatments: feeding a normal standard diet, a high-fat diet, or a high-fat diet plus gavage KSS. The effects of KSS treatment on hepatic lipid accumulation were assessed using biochemical, histological, and molecular experiments. The amounts of KSS ingredients were measured using biochemical assays. Network pharmacology analyses were performed to identify the hub genes of KSS targets and enriched pathways. CCK-8 assay was used to determine the effect of free fatty acids (FFA), lycopene, and estrogen on HepG2 viability. Quantitative Real-Time polymerase chain reaction (qRT-PCR) and Western blot assays were performed to determine the effect of KSS or lycopene on estrogen signaling and expression of lipid metabolism-related molecules. Statistical analyses were performed using GraphPad Prism and SPSS. KSS alleviated fat deposition in rat liver tissue and affected the expression of hepatic lipid synthesis, catabolism, and oxidative molecules. Lycopene was identified as the ingredient with the highest amount in KSS. Network pharmacology analyses showed that the hub genes were enriched in the estrogen signaling pathway. Cellular experiments showed that lycopene increased the expression of Estrogen Receptor α (ERα), Carnitine palmitoyltransferase 1 A ( KSS ameliorated abnormal lipid metabolism in patients with NAFLD. Lycopene was the major component of KSS, and it affected estrogen signaling and the expression of lipid metabolism molecules. In short, both KSS and LYC could change lipid metabolism by lowering lipid accumulation and raising lipolysis. Show less
📄 PDF DOI: 10.1080/07853890.2025.2479585
LPL
Qin Jiang, Tao Yang, Hao Yang +9 more · 2025 · Biomolecules · MDPI · added 2026-04-24
(1) Objective: This study aimed to systematically elucidate the molecular mechanisms by which gypenosides (GP), a major active component of
📄 PDF DOI: 10.3390/biom15081205
APOB
X L Su, J W Wu, P L Wang +7 more · 2025 · Zhonghua bing li xue za zhi = Chinese journal of pathology · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112151-20250517-00349
FGFR1
Xiaona Li, Mei Lu, Xinkun Wang +6 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Despite preclinical evidence for berberine's antidepressant potential, its pharmacological effects remain controversial.This study therefore systematically reviews animal research to clarify its mecha Show more
Despite preclinical evidence for berberine's antidepressant potential, its pharmacological effects remain controversial.This study therefore systematically reviews animal research to clarify its mechanisms and support future clinical trials. We searched PubMed, Embase, Web of Science, Cochrane Library, and OVID for studies on berberine in depression models up to March 20, 2025. Analysis used STATA 15.0 and Review Manager 5.4, with study quality assessed via SYRCLE's risk of bias tool. The meta-analysis included 18 studies (338animals). Overall, berberine significantly reduced depression-like behaviors in animal models.Specifically, BBR increased total locomotor activity in the open field test (SMD=2.79, 95% CI: 1.55, 4.02) and time spent in the center zone (SMD=2.49, 95% CI:1.61, 3.37), reduced immobility time in both the forced swim test and tail suspension test (SMD =-4.42, 95% CI:-5.77,-3.07; SMD=-4.46, 95% CI:-6.21, -2.71), increased sucrose intake in the sucrose preference test (SMD = 3.72, 95% CI: 2.37, 5.07), and reduced feeding latency in the novelty-suppressed feeding test (SMD=-5.72, 95% CI:-7.63, -3.82). However, BBR did not significantly alter the number of square crossings (SMD=1.36, 95%CI:-0.07 , 2.79) or rearing frequency (SMD=1.66, 95% CI: -0.29, 3.61) in the open field test. BBR also increased the levels of body weight, brain-derived neurotrophic factor, dopamine, serotonin, and norepinephrine,while reducing the levels of pro-inflammatory cytokines including TNF-α, IL-1β, and IL-6. Preclinical studies suggest that berberine may represent a promising therapeutic agent for the treatment of depressive disorders. Its antidepressant effects appear to be closely associated with the modulation of neurotransmitter levels,reduction of oxidative stress, and inhibition of inflammatory responses.However, methodological limitations may constrain these findings. Larger, more rigorous preclinical studies are needed for confirmation. https://inplasy.com/inplasy-2025-6-0002, identifier INPLASY202560002. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1653929
BDNF
Xumin Zheng, Xinru Guo, Yuhao Chen +9 more · 2025 · Biomolecules · MDPI · added 2026-04-24
(1) Background: the epigenetic mechanisms underlying the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remain poorly understood; (2) Methods: to investigate this process, Show more
(1) Background: the epigenetic mechanisms underlying the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remain poorly understood; (2) Methods: to investigate this process, we conducted genome-wide DNA methylation sequencing to map the epigenetic changes during the AKI-CKD transition in a mouse model. By integrating DNA methylome and transcriptome analyses, we identified genes and signaling pathways regulated by DNA methylation throughout this progression; (3) Results: our analysis identified four candidate genes- Show less
📄 PDF DOI: 10.3390/biom15040498
LPL
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
Guanghao Chen, Kundi Tai, Guoyu Dai · 2025 · Clinical and experimental medicine · Springer · added 2026-04-24
This study aims to explore the plastic changes in cell lineages during the progression of osteoarthritis (OA) and their relationship with dysregulation of signaling pathways and provide new molecular Show more
This study aims to explore the plastic changes in cell lineages during the progression of osteoarthritis (OA) and their relationship with dysregulation of signaling pathways and provide new molecular targets for precise treatment. Single-cell RNA sequencing (scRNA-seq) technology was utilized to perform high-resolution cell lineage analysis of OA patients. The mappings of distinct cell subpopulations were systematically constructed and revealed the changes in key cell types and their transformation trajectories throughout the progression of OA. Furthermore, KEGG and GO enrichment and pseudotime trajectory analysis were applied to elucidate the functional reprogramming of different cell types and the dynamic imbalance of their signaling networks in OA. Additionally, in vitro experiments were conducted to validate the biological functions of candidate genes in OA. Articular cartilage showed a transcriptional cellular heterogeneity in OA by scRNA-seq analysis; the annotated PreFC, FC, and PreHTC subsets accounted for the main part of OA samples. PreFC cells revealed transcription, signaling, and metabolic reprogramming in OA; pseudotime trajectory found that PreFC transformed to FC cells under the condition of hypoxia and metabolic reprogramming, while fibrosis and ECM degradation pathways showed intense upregulation in preHTC evolved from PreFC cells. HIF1A and ANGPTL4 were identified as key molecular regulators of OA progression, contributing to ECM degradation, inflammation, and apoptosis in chondrocytes, as confirmed through functional validation. The cellular trajectories of OA show significant plasticity changes which are influenced by the dysregulation of multiple signaling pathways. This research provides new insights into the pathological process of OA and offers potential targets for therapeutic strategies targeting these abnormal mechanisms. Show less
📄 PDF DOI: 10.1007/s10238-025-01947-x
ANGPTL4
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
Yi-Fang Ding, Kuo-Hao Ho, Wei-Jiunn Lee +8 more · 2025 · Cell death & disease · Nature · added 2026-04-24
The intricate involvement of the histaminergic system, encompassing histamine and histamine receptors, in the progression of diverse neoplasias has attracted considerable scrutiny. Histamine receptor Show more
The intricate involvement of the histaminergic system, encompassing histamine and histamine receptors, in the progression of diverse neoplasias has attracted considerable scrutiny. Histamine receptor H1 (HRH1) was reported to be overexpressed in several cancer types, but its specific functional implications in oral squamous cell carcinoma (OSCC) predominantly remain unexplored. Our findings indicate that dysregulated high levels of HRH1 were correlated with lymph node (LN) metastasis and poor prognoses in OSCC patients. We identified a disintegrin and metalloprotease 9 (ADAM9) as a critical downstream target of HRH1, promoting protumorigenic and prometastatic characteristics both in vitro and in vivo. Molecular investigations revealed that the cyclic increase in the HRH1-ADAM9-Snail/Slug axis promoted progression of the epithelial-to-mesenchymal transition (EMT). Clinical analyses demonstrated significant correlations of HRH1 expression with ADAM9 and with EMT-related markers, with elevated ADAM9 also associated with LN metastasis in OSCC patients. Regarding therapeutic aspects, we discovered that activated STAT3 acts as a compensatory pathway for the long-term HRH1 signaling blockade in OSCC cells. Combining inhibition of HRH1 and STAT3 using their respective inhibitors or short hairpin (sh)RNAs enhanced the tumor-suppressive effects compared to HRH1 inhibition/depletion alone in OSCC cells and a xenograft model. In summary, HRH1 has emerged as a valuable biomarker for predicting OSCC progression, and combined targeting of HRH1 and STAT3 may represent a promising strategy for preventing OSCC progression. Show less
no PDF DOI: 10.1038/s41419-025-07507-1
SNAI1
Yuxin Fan, Jiandong Yuan, Lichun Dong +12 more · 2025 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims Show more
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims to investigate its safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) in Chinese healthy volunteers. A randomized, double-blind, placebo-controlled and dose-escalation Phase I study was conducted as follows: a single dose (2.5 mg) and once-weekly administration for 2 weeks to reach target doses (5, 10 and 15 mg) by titration. A total of 40 volunteers received at least one dose of BGM0504 or placebo. The PK profile of BGM0504 was investigated over a wide dose range and supported once-weekly administration. It was observed that C BGM0504 was generally safe and well tolerated with favourable PK profile and potential role in weight loss was also confirmed. These findings support subsequent development of BGM0504 for type 2 diabetes mellitus (T2DM) and obesity. Show less
no PDF DOI: 10.1111/dom.16203
GIPR
Benedikt Praegel, Feng Chen, Adria Dym +3 more · 2025 · eLife · added 2026-04-24
Adolescence is a developmental period characterized by heightened plasticity. Yet, how ongoing development affects sensory processing and cognitive function is unclear. We investigated how adolescent Show more
Adolescence is a developmental period characterized by heightened plasticity. Yet, how ongoing development affects sensory processing and cognitive function is unclear. We investigated how adolescent (postnatal day 20-42) and adult (postnatal day 60-82) mice differ in performance on a pure tone Go/No-Go auditory discrimination task of varying difficulty. Using dense electrophysiological recordings, we measured spiking activity at single neuron resolution in the auditory cortex while mice were engaged in the task. As compared to adults, adolescent mice showed lower auditory discrimination performance in a difficult task. This difference in performance was due to higher response variability and weaker cognitive control expressed as higher lick bias. Adolescent and adult neuronal responses differed only slightly in representations of pure tones when measured outside the context of learning and the task. However, cortical representations after learning within the context of the task were markedly different. We found differences in stimulus- and choice-related activity at the single neuron level representations, as well as lower population-level decoding of the difficult task in adolescents. Overall, cortical decoding in adolescents was lower and slower, especially for difficult sound discrimination, reflecting immature cortical representations of sounds and choices. Notably, we found age-related differences, which were more pronounced after learning, reflecting the combined impact of age and learning. Our findings highlight distinct neurophysiological and behavioral profiles in adolescence, underscoring the ongoing development of cognitive control mechanisms and cortical plasticity during this sensitive developmental period. Show less
📄 PDF DOI: 10.7554/eLife.106387
DYM
Robert Chen, Ben Omega Petrazzini, Áine Duffy +4 more · 2025 · Genome biology · BioMed Central · added 2026-04-24
Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been Show more
Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and small sample sizes. We test associations of rare and ultra-rare coding variants with proton density fat fraction (PDFF) and MASLD case-control status in 736,010 participants of diverse ancestries from the UK Biobank, All of Us, and BioMe and performed a trans-ancestral meta-analysis. We then developed models to accurately predict PDFF and MASLD status in the UK Biobank and tested associations with these predicted phenotypes to increase statistical power. The trans-ancestral meta-analysis with PDFF and MASLD case-control status identifies two single variants and two gene-level associations in APOB, CDH5, MYCBP2, and XAB2. Association testing with predicted phenotypes, which replicates more known genetic variants from GWAS than true phenotypes, identifies 16 single variants and 11 gene-level associations implicating 23 additional genes. Two variants were polymorphic only among African ancestry participants and several associations showed significant heterogeneity in ancestry and sex-stratified analyses. In total, we identified 27 genes, of which 3 are monogenic causes of steatosis (APOB, G6PC1, PPARG), 4 were previously associated with MASLD (APOB, APOC3, INSR, PPARG), and 23 had supporting clinical, experimental, and/or genetic evidence. Our results suggest that trans-ancestral association analyses can identify ancestry-specific rare and ultra-rare coding variants in MASLD pathogenesis. Furthermore, we demonstrate the utility of machine learning in genetic investigations of difficult-to-phenotype diseases in trans-ancestral biobanks. Show less
📄 PDF DOI: 10.1186/s13059-025-03518-5
APOB
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
Feixiang He, Qifang Chen, Peilin Gu +4 more · 2025 · Ophthalmology science · Elsevier · added 2026-04-24
To identify the connections between lipid biomarkers and the anti-VEGF therapy response in patients with neovascular age-related macular degeneration (nAMD). A bidirectional and multivariable Mendelia Show more
To identify the connections between lipid biomarkers and the anti-VEGF therapy response in patients with neovascular age-related macular degeneration (nAMD). A bidirectional and multivariable Mendelian randomization study. The summary statistics for anti-VEGF nAMD treatment response included a total of 128 responders, 51 nonresponders, and 6 908 005 genetic variants available for analysis. The sample size of lipid biomarkers is 441 016 and 12 321 875 genetic variants available for analysis. Two-sample Mendelian randomization (MR) method was conducted to exhaustively appraise the causalities among 13 lipid biomarkers and the risk of different anti-VEGF treatment responses (including visual acuity [VA] and central retinal thickness [CRT]) for nAMD subtypes. Thirteen lipid biomarkers, VA, and CRT. A positive causal relationship was identified between triglycerides (TGs), apolipoproteins (Apos) E2, ApoE3, total cholesterol (TC), and VA response to anti-VEGF therapy in patients with nAMD, as confirmed by MR-Egger, weighted median, and weighted mode models. The MR-Egger model yielded statistically significant results for TC, ApoA-I, ApoB, and ApoA-V in relation to the CRT response to anti-VEGF treatment in patients with nAMD. In the reverse MR, the MR-Egger model identified significant causal relationships between ApoA-I, low-density lipoprotein cholesterol (LDL-c), ApoE3, and ApoF and the VA response. However, this was not the case in the weighted median and weighted mode models. In the MR-Egger model, ApoB, LDL-c, ApoE3, and ApoM were identified as significantly influencing the CRT response. In the multisample MR analysis, TC, high-density lipoprotein cholesterol, LDL-c, and TG were found to be causally related to VA response, and TC was also identified as being causally related to the CRT response to anti-VEGF therapy in patients with nAMD. This MR study suggests unidirectional causality between TG and ApoE3 and the response to anti-VEGF treatment in patients with nAMD. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Show less
📄 PDF DOI: 10.1016/j.xops.2025.100711
APOB
Yangke Cai, Siyuan Xie, Liyi Xu +2 more · 2025 · Diabetology & metabolic syndrome · BioMed Central · added 2026-04-24
Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most common chronic liver disease worldwide, yet efficient therapeutic approaches are lacking. The advent of glucagon-li Show more
Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most common chronic liver disease worldwide, yet efficient therapeutic approaches are lacking. The advent of glucagon-like peptide-1 receptor (GLP-1R)-based multi-target agonists generated renewed optimism for MASLD. Building on preclinical and clinical data suggesting synergistic metabolic benefits, we hypothesized that combining glucose-dependent insulinotropic polypeptide receptor (GIPR) or glucagon receptor (GCGR) agonism with GLP-1R agonism would confer superior protective effects against MASLD and its complications. We identified genetic proxies of the effect of GLP-1R, GIPR, and GCGR by combining Mendelian randomization (MR), Bayesian colocalization, and linkage disequilibrium (LD) analyses. We then performed two-sample MR and colocalization analyses to estimate the causal effect of GLP-1R-based agonists on MASLD, its metabolic risk factors, and multi-organ complications. The MR analyses suggested genetically proxied GLP-1R-based agonists were causally associated with a reduced risk of MASLD (GIPR/GLP-1R agonist: OR: 0.17, 95%CI: 0.05-0.52, P = 2.07 × 10 We identified the causal role of GLP-1R-based agonists in reducing the risk of MASLD and its complications, probably by improving systemic metabolic disorders and partly independent of their weight-loss effect. Show less
📄 PDF DOI: 10.1186/s13098-025-01870-x
GIPR
Shaoyu Wang, Qiaomei Zheng, Lihong Chen · 2025 · International journal of general medicine · added 2026-04-24
Ovarian cancer (OC), a common fatal malignancy in women, has a poor prognosis. RNA modifications are associated with the development of OC. In this study, we aimed to identify and verify RNA modificat Show more
Ovarian cancer (OC), a common fatal malignancy in women, has a poor prognosis. RNA modifications are associated with the development of OC. In this study, we aimed to identify and verify RNA modifications-related prognostic genes in OC by integrating bulk and single-cell RNA sequencing (scRNA-seq) data. Transcriptome data came from public databases and RNA modifications-related genes (RMRGs) were obtained from literature. Candidate genes were identified by intersecting RMRGs with differentially expressed genes (DEGs) in OC patients. Prognostic genes were gained via machine learning techniques, particularly LASSO regression. A risk model was built to predict the prognosis. OC patients were divided into high-risk and low-risk groups according to risk score. Subsequent analyses covered enrichment analysis, immune microenvironment, mutation analysis, and chemotherapeutic drug sensitivity. In addition, scRNA-seq data was assessed for key cells and gene expression in them. Finally, RT-qPCR was applied to identify the expression of prognostic genes. We constructed an RNA modifications-related prognostic signature that can effectively predict clinical outcomes and therapeutic responses in patients with OC. Show less
no PDF DOI: 10.2147/IJGM.S523878
SNRPC
Yu Ding, Haoyang Ling, Xiuyan Chen +6 more · 2025 · Medicine · added 2026-04-24
Myocardial infarction (MI) is one of the most serious cardiovascular diseases in the world. Nevertheless, the majority of diagnostic procedures conducted subsequent to the illness do not provide any m Show more
Myocardial infarction (MI) is one of the most serious cardiovascular diseases in the world. Nevertheless, the majority of diagnostic procedures conducted subsequent to the illness do not provide any means to prevent several risks associated with MI. Blood and urine tests are frequently employed in clinical examinations to detect cardiovascular diseases at an early stage. Mendelian randomization (MR) is commonly employed to explore disease-trait relationships and uncover therapeutic targets. Our goal was to explore the genetic links between 35 blood and urine biomarkers and MI. Blood and urine biomarker MR correlations with MI risk were studied. In version R10, the UK Biobank and Finnish databases included blood and urine marker data and MI data (26,060 cases and 343,079 controls). We performed bidirectional 2-sample MR with 4 methods: inverse variance weighted, MR-Egger, weighted median, and weighted mode. Final causal associations were determined by inverse variance weighted. Sensitivity analyses (heterogeneity, pleiotropy) were conducted. MR-PRESSO and PhenoScanner were used to exclude invalid instruments. We used multivariate MR to filter the most important genes without including other positive genes. To identify positive gene pathways and gene networks that cause MI, we employed GeneMANIA for gene prediction. The findings revealed a positive genetic association between the 8 blood and urine biomarker levels and an elevated risk of MI. There are apolipoprotein B (APOB), glycated hemoglobin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, sex hormone-binding globulin, triglycerides, and urate. Moreover, APOB, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol selectively affect MI through the rejection of other positive gene stems. Finally, APOB and numerous genes strongly impact MI development. APOB collaborates with related genes to regulate plasma lipoprotein particle levels, sterol homeostasis, organization, lipid homeostasis, and remodeling in MI. Our research further reveals the causal relationship between MI and blood/urine biomarkers, providing a new perspective for the prevention, diagnosis, and treatment of MI. Blood and urine marker tests can subsequently be conducted based on these results to detect MI and study the underlying mechanisms linking these metabolites to MI. Show less
no PDF DOI: 10.1097/MD.0000000000046146
APOB
Yian Chen, Haining Ding, Jiaqing Song +1 more · 2025 · Cancer cell international · BioMed Central · added 2026-04-24
A crucial aspect of the association involving inflammation and the development of cancer is the ability of cancer cells to undergo a transition into mesenchymal cells. The process is referred to as ep Show more
A crucial aspect of the association involving inflammation and the development of cancer is the ability of cancer cells to undergo a transition into mesenchymal cells. The process is referred to as epithelial-mesenchymal transition (EMT). Cytokines and chemokines, which are inflammatory agents found in the carcinoma microenvironment, induce epithelial-mesenchymal transition (EMT) changes in malignant cells. Evaluating the role of cytokines in EMT in breast carcinoma and investigating their potential therapeutic implications is the objective of this comprehensive research report. The following search criteria were applied to the Cochrane, Embase, PubMed, and Web of Science databases: "cytokines," "the cytokines," "chemokines," "EMT," "epithelial-mesenchymal transition or transformation," "breast tumor," "breast carcinoma," and "breast cancer." A body of research comprising 54 articles has demonstrated that a number of cytokines, including TNF-α, TGF-β, and IL-6, contribute to the promotion of EMT alterations in breast tumors. The epithelial markers E-cadherin and β-catenin were downregulated as a consequence of morphological changes induced by EMT; conversely, the mesenchymal markers N-cadherin, vimentin, and fibronectin were upregulated. The EMT transforming factors (EMT-TF) TWIST/ZEB/SNAI1/SNAI2 were upregulated. Pharmaceuticals with the capacity to specifically target cytokines or their epithelial-mesenchymal transition (EMT) signalling pathways have the potential to significantly reduce treatment resistance, impede the progression of cancer, and prevent the recurrence of breast cancer. Epithelial-mesenchymal transition (EMT) induced by cytokines is a factor in breast cancer progression and metastasis. Show less
no PDF DOI: 10.1186/s12935-025-03973-x
SNAI1
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
Xianbing Bai, Hongmei Du, Xiangxuan Liu +9 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Sleep Deprivation (SD) severely disrupts emotional regulation, predisposing individuals to mood disturbances and anxiety. However, the precise mechanisms underlying anxiety triggered by sleep loss rem Show more
Sleep Deprivation (SD) severely disrupts emotional regulation, predisposing individuals to mood disturbances and anxiety. However, the precise mechanisms underlying anxiety triggered by sleep loss remain elusive. In this study, a mouse model of chronic SD was established using a continuously running treadmill paradigm for 28 days. SD induced anxiety-like behaviors and hippocampal ApoE downregulation. Furthermore, SD downregulated the expression of the autophagy-related protein ATG5 and upregulated p62. In addition, SD inhibited AMPK phosphorylation and induced mTOR phosphorylation. Levels of pro-inflammatory cytokines, including TNF-α, IL-1β, and IL-18, were markedly increased. Immunofluorescence staining revealed a notable increase in the activation of microglia and astrocytes in the hippocampi of SD mice. Either hippocampal overexpression of ApoE via bilateral AAV injection or rapamycin treatment significantly alleviated anxiety-like behaviors, enhanced autophagy, and reduced neuroinflammation in SD mice. Thus, SD induces anxiety by suppressing autophagy level. This effect is mediated through the inhibition of ApoE-dependent AMPK phosphorylation and the concomitant promotion of mTOR phosphorylation, revealing a potential therapeutic target. Show less
no PDF DOI: 10.1007/s12035-025-05610-0
APOE
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
Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB
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
Hui Yan, Rui Wang, Suryavathi Viswanadhapalli +35 more · 2025 · Science advances · Science · added 2026-04-24
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined r Show more
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined receptor signals, and assessed their regulatory capacities and specificities through in silico analysis of ligand-receptor interactions. Consequently, we identified a B cell subset that expressed cytokine interleukin-27 (IL-27) and chemokine CXCL10. Through the IL-27-IL-27 receptor interaction, these IL-27/CXCL10-producing B cells targeted CD40-activated B cells in vitro and, upon induction by immunization and viral infection, optimized antibody responses and antiviral immunity in vivo. Also present in breast cancer tumors and retained there through CXCL10-CXCR3 interaction-mediated self-targeting, these cells promoted B cell PD-L1 expression and immune evasion. Mechanistically, Show less
📄 PDF DOI: 10.1126/sciadv.adx9917
IL27
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
Yicun Li, Yun Wu, Xiaolian Li +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Head and neck squamous cell carcinoma (HNSCC) poses a global health challenge. The management of HNSCC is complicated by the difficulty in detecting occult lymph node metastases, leading to dilemmas i Show more
Head and neck squamous cell carcinoma (HNSCC) poses a global health challenge. The management of HNSCC is complicated by the difficulty in detecting occult lymph node metastases, leading to dilemmas in elective neck dissection decisions, which will impair patients' quality of life without improving survival for nodal negative patients. We conducted a comparative analysis of the clinical features, genomic alterations, gene expression and methylation, tumor microenvironment and cellular states between the clinically N0 and pathologically N0 (cN0-pN0) patients and occult lymph node metastatic patients. Patients with occult lymph node metastases typically present with more poorly differentiated primary tumors and higher rates of angiolymphatic and perineural invasion. We identified a distinctive genomic mutation spectrum in the primary tumors of patients with occult metastases, notably in genes such as NSD1, ARHGAP15 and SMARCA4. A whole-genome DNA hypomethylation and altered gene expression profiles are identified in occult lymph node metastatic patients. Analysis of the tumor microenvironment revealed an enrichment of CARNS1 + NK cells and CBX1 + tumor cells in occult metastatic patients. In conclusion, patients with occult lymph node metastases exhibit distinct molecular and clinical features compared with cN0-pN0 patients. Show less
📄 PDF DOI: 10.1038/s41598-025-10320-7
CBX1