👤 Hongmei 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, 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-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
Zhezhe Chen, Qiongjun Zhu, Hong Xu +8 more · 2025 · Nature communications · Nature · added 2026-04-24
Many patients are suffering from atherosclerosis without typical risk factors, which can cause severe cardiovascular complications. Trimethylamine N-oxide (TMAO), derived from gut microbes, is a key u Show more
Many patients are suffering from atherosclerosis without typical risk factors, which can cause severe cardiovascular complications. Trimethylamine N-oxide (TMAO), derived from gut microbes, is a key unconventional contributor to the development of atherosclerosis. Here we present a strategy performed by orally administered nano-functionalized probiotics (PDMF@LGG) to inhibit TMAO through the gut microbiota-trimethylamine (TMA)-TMAO axis. PDMF@LGG, composed of polydopamine-coated Lacticaseibacillus rhamnosus GG and nanoparticles based on a reactive oxygen species (ROS)-responsive polymeric prodrug of fluoromethylcholine (FMC), can promote the retention of probiotics and nanoparticles in the intestine to persistently scavenge elevated ROS and release drugs. This process suppresses TMA production and absorption, lowering plasma TMAO levels. The therapeutic effects on male ApoE Show less
📄 PDF DOI: 10.1038/s41467-025-66448-7
APOE
Yu Saito, Shuhai Chen, Tetsuya Ikemoto +4 more · 2025 · The journal of medical investigation : JMI · added 2026-04-24
Accelerating ammonium metabolism of hepatocyte like cells (HLCs) is critical for various functions of hepatocytes. The aim of the present study was to investigate whether Farnesoid X receptor (FXR) ag Show more
Accelerating ammonium metabolism of hepatocyte like cells (HLCs) is critical for various functions of hepatocytes. The aim of the present study was to investigate whether Farnesoid X receptor (FXR) agonist, obeticholic acid (OCA), accelerated ammonium metabolism of HLCs, which was derived from adipose derived mesenchymal stem cells (ADSCs). Human ADSCs were seed in flat bottom plate, then our differentiation protocol was used for 21 days. OCA treatment had been performed in Step3 for 10days. Then, 1) hepatic maturation, 2) urea cycle genes, 3) urea production, and 4) ammonium metabolism was compared depend on the presence or absence of OCA. HLCs had been successfully produced for 21 days. HLCs with OCA showed significantly higher mRNA expressions of AAT than those without OCA. HLCs with OCA showed significantly higher mRNA expressions of urea cycle genes such as SLC25A13, CPS1, and OTC. Urea production was also tended to be upregulated by OCA addition. HLCs with OCA showed significantly higher clearance of NH4Cl at 6hr and 24 hr after addition of NH4Cl. FXR agonist, OCA, accelerates ammonium metabolism of ADSCs derived HLCs. HLCs could be one of treatment options of hepatic encephalopathy of patients with liver failure or urea cycle disorder in the future. J. Med. Invest. 72 : 54-59, February, 2025. Show less
no PDF DOI: 10.2152/jmi.72.54
CPS1
Xian Chen, Hui Wang, Qianqian Li +4 more · 2025 · Discover oncology · Springer · added 2026-04-24
Renal clear cell carcinoma (RCC) is the most common type of kidney cancer, and its relationship with kidney fibrosis and inflammatory responses has attracted considerable attention. However, whether c Show more
Renal clear cell carcinoma (RCC) is the most common type of kidney cancer, and its relationship with kidney fibrosis and inflammatory responses has attracted considerable attention. However, whether causal relationships exist among these associations remains unclear, as traditional observational studies are susceptible to confounding factors. To evaluate causal relationships between kidney cancer, kidney fibrosis, and inflammatory factors using Mendelian randomization, and explore tumor microenvironment heterogeneity through single-cell analysis. Based on large-scale GWAS data, bidirectional Mendelian randomization analysis was performed to assess causal relationships between kidney cancer and kidney fibrosis, using MR Egger, inverse variance weighted (IVW), and weighted mode methods. Causal associations between kidney cancer and inflammatory factors including Axin-1, C-C motif chemokine 28, and interleukin-10 receptor subunit were analyzed. Single-cell RNA sequencing data from the GEO database (GSM4819725) was integrated for tumor microenvironment analysis. Bidirectional Mendelian randomization analysis revealed no significant causal relationship between kidney cancer and kidney fibrosis [kidney cancer→kidney fibrosis: IVW OR=0.992(95%CI: 0.913-1.077, P=0.842); kidney fibrosis→kidney cancer: IVW OR=0.922(95%CI: 0.824-1.030, P=0.151)]. However, significant positive causal associations were identified between kidney cancer and multiple inflammatory factors: Axin-1 levels [OR=1.448(95%CI: 1.107-1.894, P=0.007)], C-C motif chemokine 28 [OR=1.287(95%CI: 1.076-1.540, P=0.006)], and interleukin-10 receptor subunit [OR=1.135(95%CI: 1.032-1.248, P=0.009)]. Sensitivity analyses confirmed the robustness of results. Single-cell analysis revealed cellular heterogeneity in the tumor microenvironment, including various cell types such as immune cells, T cells, and NK cells, with pseudotime analysis demonstrating cell differentiation trajectories and dynamic gene expression changes. Mendelian randomization analysis provides genetic evidence for causal relationships between kidney cancer and inflammatory factors, while excluding direct causal associations between kidney cancer and kidney fibrosis. Show less
📄 PDF DOI: 10.1007/s12672-025-03343-z
AXIN1
Qisheng Hu, Yongheng Zhang, Huawei Ming +5 more · 2025 · Medicine · added 2026-04-24
Periodontitis (PD) is a chronic inflammatory disease in which oxidative stress plays a crucial role in its progression. Mitophagy eliminates damaged mitochondria and alleviates oxidative stress; howev Show more
Periodontitis (PD) is a chronic inflammatory disease in which oxidative stress plays a crucial role in its progression. Mitophagy eliminates damaged mitochondria and alleviates oxidative stress; however, its specific regulatory mechanisms in PD remain unclear. This study utilized single-cell and bulk RNA sequencing data to identify core genes and investigate their potential roles. We utilized single-cell RNA sequencing data and applied 4 algorithms - area under the curve cell level enrichment, U-statistics-based single-cell signature scoring, single-sample gene set scoring, and AddModuleScore - to assess mitophagy activity and identify candidate genes. Subsequently, based on bulk RNA-seq data, 5 machine learning algorithms, including Least Absolute Shrinkage and Selection Operator Regression, random forest, Boruta, gradient boosting machine, and eXtreme Gradient Boosting, were employed to further screen core genes from the candidate gene set. Finally, immune infiltration analysis, cell communication analysis, and gene interaction network construction were integrated to systematically elucidate the regulatory mechanisms of core genes in the progression of PD. Single-cell RNA sequencing combined with multiple algorithms revealed significantly elevated mitophagy activity in PD tissues, particularly in monocytes/macrophages and endothelial cells. Additionally, we identified 4 core genes: BNIP3L, VPS13C, CTTN, and MAP1LC3B. BNIP3L and CTTN were downregulated in periodontitis, correlating negatively with disease prevalence, immune infiltration, and inflammatory pathways, whereas VPS13C and MAP1LC3B were upregulated, showing positive correlations. CellChat analysis highlighted monocytes/macrophages and endothelial cells with high core gene expression as key mediators of intercellular communication. This study identified BNIP3L, VPS13C, CTTN, and MAP1LC3B as core mitophagy-related genes associated with PD, and highlighted the pivotal roles of monocytes/macrophages and endothelial cells in disease progression. These findings provide new insights into the pathogenesis of PD and offer a theoretical foundation for mitophagy-targeted diagnosis, biomarker identification, and precision therapy. Show less
no PDF DOI: 10.1097/MD.0000000000044002
VPS13C
Haibo Yao, Mengmeng Song, Huan Zhang +5 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
The deer antler is a fully regenerable and the fastest-growing osseous organ. Circular RNA (circRNA), a novel member of the non-coding RNA family, has significant research potential and crucial roles Show more
The deer antler is a fully regenerable and the fastest-growing osseous organ. Circular RNA (circRNA), a novel member of the non-coding RNA family, has significant research potential and crucial roles in biological processes. This study aims to explore the impact and mechanisms of circRNA505 on antler chondrocytes. Functional experiments demonstrated that m5C-modified circRNA505 inhibits antler chondrocyte proliferation, enhances osteogenic differentiation, and facilitates cellular glycolysis. Mechanistically, dual luciferase and AGO2-RIP assays revealed a direct binding relationship between circRNA505, miR-127, and p53. Rescue assays further showed that circRNA505 affects cell proliferation and differentiation through the miR-127/p53 axis. Meanwhile, RNA Antisense Purification (RAP) screening and analysis of related proteins binding to circRNA505 demonstrated that circRNA505 binds to LDHA and increases the level of LDHA phosphorylation through FGFR1 to promote cellular glycolysis by FISH-IF, RIP, and Western blot experiments. Additionally, Me-RIP assays confirmed the m5C methylation modification of circRNA505. NSUN2 mediates the m5C modification of circRNA505, affecting its stability, while the m5C reader ALYREF promotes the nuclear export of circRNA505 in an ALYREF-dependent manner. This study provides new insights into the regulatory mechanisms underlying rapid antler development. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.142527
FGFR1
Lin Ai, Yi Han, Ting Ge +14 more · 2025 · Acta pharmacologica Sinica · Nature · added 2026-04-24
Some individuals are more susceptible to developing or suffering from pain states than others. However, the brain mechanisms underlying the susceptibility to pain responses are unknown. In this study, Show more
Some individuals are more susceptible to developing or suffering from pain states than others. However, the brain mechanisms underlying the susceptibility to pain responses are unknown. In this study, we defined pain susceptibility by recapitulating inter-individual differences in pain responses in mice exposed to a paradigm of socially transferred allodynia (STA), and with a combination of chemogenetic, molecular, pharmacological and electrophysiological approaches, we identified GABA-ergic neurons in the dorsal raphe nucleus (DRN) as a cellular target for the development and maintenance of STA susceptibility. We showed that DRN GABA-ergic neurons were selectively activated in STA-susceptible mice when compared with the unsusceptible (resilient) or control mice. Chemogenetic activation of DRN GABA-ergic neurons promoted STA susceptibility; whereas inhibiting these neurons prevented the development of STA susceptibility and reversed established STA. In in vitro slice electrophysiological analysis, we demonstrated that melanocortin 4 receptor (MC4R) enriched in DRN GABA-ergic neurons was a molecular target for regulating pain susceptibility, possibly by affecting DRN GABA-ergic neuronal activity. These results establish the DRN GABA-ergic neurons as an essential target for controlling pain susceptibility, thus providing important information for developing conceptually innovative and more accurate analgesic strategies. Show less
no PDF DOI: 10.1038/s41401-025-01494-x
MC4R
Huihui Shi, Lei Chen, Juan Huang +6 more · 2025 · Oncology research · added 2026-04-24
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study aimed to identify key genes involved in HCC development and elucidate their molecular mech Show more
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study aimed to identify key genes involved in HCC development and elucidate their molecular mechanisms, with a particular focus on mitochondrial function and apoptosis. Differential expression analyses were performed across three datasets-The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma (LIHC), GSE36076, and GSE95698-to identify overlapping differentially expressed genes (DEGs). A prognostic risk model was then constructed. Cysteine/serine-rich nuclear protein 1 ( A six-gene prognostic model was established, comprising downregulated genes ( Show less
no PDF DOI: 10.32604/or.2025.068737
POC5
Bingye Zhang, Yanli Ren, Yang Huo +2 more · 2025 · Inorganic chemistry · ACS Publications · added 2026-04-24
A series of long-persistent luminescence (LPL) phosphors Zn
no PDF DOI: 10.1021/acs.inorgchem.5c01203
LPL
Hanyu Zhang, Zengyuan Zhou, Jie Gu +5 more · 2025 · Progress in neuro-psychopharmacology & biological psychiatry · Elsevier · added 2026-04-24
Lewy body dementia (LBD) is the second common dementia, with unclear mechanisms and limited treatment options. Dyslipidemia has been implicated in LBD, but the role of lipid-lowering drugs remains und Show more
Lewy body dementia (LBD) is the second common dementia, with unclear mechanisms and limited treatment options. Dyslipidemia has been implicated in LBD, but the role of lipid-lowering drugs remains underexplored. This study aims to investigate the association between lipid traits, drug targets, and LBD risk using Mendelian Randomization (MR) analysis. We performed univariable and multivariable MR analyses to evaluate the causal effects of lipid traits on the risk of LBD. Then, drug-target MR analysis and subtype analysis were conducted to evaluate the effects of lipid-lowering therapies on LBD. In univariable MR, genetically predicted low-density lipoprotein cholesterol (LDL-C) and remnant cholesterol (RC) levels were associated with an increased risk of LBD. Mediation analysis suggested a potential interaction between LDL-C and RC in influencing LBD risk. Drug-target MR analysis identified significant associations between genetically proxied inhibition of ANGPTL3, CETP, and HMGCR and LBD risk. This MR analysis provided evidence that elevated LDL-C and RC may increase the risk of LBD. Additionally, targeting ANGPTL3, CETP, and HMGCR may represent potential therapeutic strategies for the prevention or treatment of LBD. Show less
no PDF DOI: 10.1016/j.pnpbp.2025.111282
CETP
Tao Yang, Hong Liu, Jian Chen · 2025 · Genes & genomics · Springer · added 2026-04-24
Osteoarthritis (OA) is a common progressive joint disorder marked by synovial inflammation, cartilage degeneration, the formation of osteophytes, though its underlying molecular mechanisms remain uncl Show more
Osteoarthritis (OA) is a common progressive joint disorder marked by synovial inflammation, cartilage degeneration, the formation of osteophytes, though its underlying molecular mechanisms remain unclear. This study integrated bioinformatics and experimental validation to identify key genes in OA synovium and their association with immune infiltration. Analysis of the GSE82107 dataset (10 OA, 7 controls) revealed 909 differentially expressed genes (525 upregulated, 384 downregulated). WGCNA identified the "midnightblue" module, and its intersection with DEGs yielded 122 genes enriched in cytokine-cytokine receptor interaction, JAK-STAT signaling, and autophagy pathways. Protein-protein interaction analysis highlighted FLT3LG, MC4R, CXCL10, CARTPT, and LHX2 as core genes (AUC 0.743-0.871). Immune infiltration analysis showed elevated M0 macrophages in OA, with CXCL10 showing a strong positive correlation with M1 macrophage infiltration (r = 0.74), and MC4R correlating with the presence of follicular helper T cells (r = 0.85). In vitro, OA-derived fibroblast-like synoviocytes exhibited CXCL10 upregulation, MC4R downregulation, and increased IL-6, IL-8, and TNF-α secretion, which were markedly reduced by CXCL10 knockdown or MC4R overexpression. Synovial tissue assays confirmed these expression patterns. CXCL10 and MC4R may represent promising diagnostic markers and therapeutic targets, offering new insights into OA immunopathogenesis and precision intervention. Show less
📄 PDF DOI: 10.1007/s13258-025-01679-y
MC4R
Guangquan Chen, Qianqian Sun, Shiyi Xiong +6 more · 2025 · ACS nano · ACS Publications · added 2026-04-24
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is ach Show more
Gestational exposure to micro- and/or nanoparticles (M/NPs) may be closely associated with adverse maternal and offspring outcomes involving multiple organ dysfunctions. Organ functional change is achieved through metabolic adaptation in response to changes in the external environment; yet, intricacies of these organ dysfunctions and underlying metabolic changes remain poorly understood, particularly at spatial suborgan level. Using a pregnant mouse model exposed to polystyrene (PS)-M/NPs (sizes: 100 nm, 5 μm, 10 mg/L in drinking water) from gestation day 1 to 18, we construct a comprehensive multisub-organ lipid metabolic landscape. This analysis integrates MALDI-mass spectrometry imaging with histological assessment to monitor changes in maternal suborgans-placenta-fetus unit. Our findings reveal distinct metabolic responses between maternal and fetal organs to gestational PS-M/NPs exposure. We identify potential targeted suborgans and spatial biomarkers associated with PS-M/NPs exposure according to histological damage and metabolic remodeling, including placental junctional and labyrinth zone (e.g., phosphatidylserine, phosphatidylethanolamine [PE]), renal cortex of maternal kidney (e.g., ceramide [Cer], PE, sphingomyelin [SM], phosphatidylglycerol [PG], phosphatidylserine), ventricular muscular layer and interventricular septum of maternal heart (e.g., PE, lysophosphatidylethanolamine [LPE], lysophosphatidic acid [LPA]), fetal brain and spinal cord (e.g., Cer), and fetal liver (e.g., Cer). Furthermore, phosphatidylserine synthesis and glycolipid metabolism pathways are found to be exclusively enriched following PS-NP and PS-MP exposure in the multiorgan network, respectively. We propose an M/NPs scale-exposed suborgan effect framework, which provides a molecular foundation and potential spatial biomarkers for elucidating intersub-organ interactions in response to M/NPs exposure and their role in mediating pregnancy state. Show less
no PDF DOI: 10.1021/acsnano.5c13265
LPA
Chenwen Li, Yidan Chen, Yuan Li +9 more · 2025 · Acta pharmaceutica Sinica. B · Elsevier · added 2026-04-24
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate Show more
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate injection, which results in rapid elimination and poor patient compliance. Consequently, oral delivery strategies capable of targeting atherosclerotic plaques are imperative for nucleic acid therapeutics. Herein we report the development of yeast-derived capsules (YCs) packaging an antisense oligonucleotide (AM33) targeting microRNA-33 (miR-33) for the oral treatment of atherosclerosis. YCs provide stability for AM33, preventing its premature release in the gastrointestinal tract. AM33-containing YCs, defined as YAM33, showed high transfection in macrophages, thus promoting cholesterol efflux and inhibiting foam cell formation by regulating the target genes/proteins of miR-33. Orally delivered YAM33 effectively accumulated within atherosclerotic plaques in Show less
📄 PDF DOI: 10.1016/j.apsb.2025.07.039
APOE
Yi Chen, Munawar Anwar, Xiaoli Wang +2 more · 2025 · Discover oncology · Springer · added 2026-04-24
Interleukin-27 receptor alpha (IL27RA), a key subunit of the interleukin-27 receptor, plays an essential role in T cell-mediated immunity. However, its relevance in breast cancer and response to immun Show more
Interleukin-27 receptor alpha (IL27RA), a key subunit of the interleukin-27 receptor, plays an essential role in T cell-mediated immunity. However, its relevance in breast cancer and response to immunotherapy remains unexplored. We integrated bulk and single-cell RNA sequencing data from TCGA, GEO, and scRNA-seq datasets to analyze IL27RA expression, prognosis, immune infiltration, and treatment response. TIDE and immune checkpoint-treated clinical cohorts were used to assess immunotherapy responsiveness. Chemotherapy sensitivity was predicted using GDSC data, and IL27RA protein expression was validated by Western blot. IL27RA was downregulated in breast cancer but high expression correlated with favorable survival. It was primarily expressed in T cells, particularly CD8⁺ subsets, and associated with enriched immune infiltration and elevated checkpoint gene expression. IL27RA high-expression patients showed lower TIDE scores, better outcomes in ICI-treated cohorts, and higher sensitivity to multiple chemotherapeutic agents. IL27RA is a potential immune biomarker that reflects an inflamed tumor microenvironment and predicts benefit from immunotherapy and chemotherapy in breast cancer. These findings provide novel insights into immune-based stratification using single-cell transcriptomic data. Show less
📄 PDF DOI: 10.1007/s12672-025-02811-w
IL27
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
Shirui Jiang, Ailin Zhang, Jiegang Deng +5 more · 2025 · Frontiers in pediatrics · Frontiers · added 2026-04-24
Pediatric primary cardiomyopathies (PCMs) are rare diseases with complex causes and nonspecific treatment. The influence of electrolytes and amino acids (AAs) on cardiomyopathies has not been extensiv Show more
Pediatric primary cardiomyopathies (PCMs) are rare diseases with complex causes and nonspecific treatment. The influence of electrolytes and amino acids (AAs) on cardiomyopathies has not been extensively studied. This study aimed to explore clinical characteristics and the usage of electrolytes and AAs in children with PCMs. Children diagnosed with PCMs who had genetic test reports were included. Relevant information was collected and processed, and clinical characteristics and mutated genes were clarified. Gene databases were searched to explore related electrolytes and AAs in the treatment of PCMs. The effect of calcium was explored in children with DCM. Paired samples T tests and nonparametric Wilcoxon signed-rank tests were performed for comparison between before and after using calcium. In this study, 27 children with gene test results were enrolled to perform gene-related analysis. The median age was 2.5 years old. Mutated genes were collected, including pathogenic, likely pathogenic, uncertain significance, and other mutations. The most frequently mutated genes related to dilated cardiomyopathy (DCM) were For children with DCM, calcium supplements may be beneficial. AAs, including serine, cysteine, and arginine, could be used for supplementary treatment in children with DCM and HCM. Show less
📄 PDF DOI: 10.3389/fped.2025.1631632
MYBPC3
Jia Chen, Ying Yang, Shu Su +5 more · 2025 · International ophthalmology · Springer · added 2026-04-24
no PDF DOI: 10.1007/s10792-025-03522-5
ANGPTL4
Yingli Xu, Longkai Shi, Linlin Chen +2 more · 2025 · Scientific reports · Nature · added 2026-04-24
Little is known about the association between physical activity and the risk of pre-sarcopenic obesity (pre-SO) among adolescents. Hence, this study aimed to examine the association between physical a Show more
Little is known about the association between physical activity and the risk of pre-sarcopenic obesity (pre-SO) among adolescents. Hence, this study aimed to examine the association between physical activity and pre-SO in a sample of 2143 adolescents aged 12 to 18 years from Yinchuan, China. The pre-SO was defined by three criteria: low skeletal muscle mass adjusted by weight (SMM/W) combined with body mass index (BMI), fat mass percentage (FMP), and waist circumference (WC). After adjusting for age, smoking, drinking, sleep time, and high-fat food consumption, participants with high physical activity (HPA) had a lower risk of pre-SO compared to those with low physical activity (LPA) according to the obesity criteria of FMP (OR   0.63, 95% CI, 0.48-0.83, P < 0.05), and WC (OR 0.71, 95% CI, 0.52-0.96, P < 0.05). Additionally, restricted cubic spline models showed a linear dose-response association between total physical activity (TPA) and pre-SO no matter what obesity criteria were adopted (all P overall trend < 0.05, all P non-linear > 0.50). Subgroup analyses revealed that individuals with higher TPA levels exhibited a decreased risk of pre-SO in boys according to the obesity criteria of FMP, and WC. In conclusion, HPA is associated with a reduced risk of pre-SO in adolescents, especially among boys. Show less
📄 PDF DOI: 10.1038/s41598-025-28449-w
LPA
Mingyang Chen, Jing Lei, Zhenqiu Liu +6 more · 2025 · BMC rheumatology · BioMed Central · added 2026-04-24
Elevated red blood cell distribution width (RDW) is associated with increased risk of rheumatoid arthritis (RA), but the potential interactions of RDW with genetic risk of incident RA remain unclear. Show more
Elevated red blood cell distribution width (RDW) is associated with increased risk of rheumatoid arthritis (RA), but the potential interactions of RDW with genetic risk of incident RA remain unclear. This study aimed to investigate the associations between RDW, genetics, and the risk of developing RA. We analysed data from 145,025 healthy participants at baseline in the UK Biobank. The endpoint was diagnosed rheumatoid arthritis (ICD-10 codes M05 and M06). Using previously reported results, we constructed a polygenic risk score for RA to evaluate the joint effects of RDW and RA-related genetic risk. Two-sample mendelian randomization and bayesian colocalization were used to infer the causal relation between them. A total of 675 patients with RA were enrolled and had a median followed up of 5.1 years, with an incidence rate of 0.57/1000 person-years. The hazard ratio of RA was 1.89 (95% CI: 1.45, 2.47) in highest RDW quartile group compared with the lowest RDW quartile group. Individuals within the top quintile of PRS showed a significantly high risk of RA. Moreover, Participants with high genetic risk and those in highest RDW group exhibited a significantly elevated hazard ratio (7.67, 95% CI: 3.98, 14.81), as opposed to participants with low genetic risk and those in lowest RDW group. Interactions between PRS and RDW on the multiplicative and additive scale were observed. Mendelian randomization provided suggestive evidence of a bi-directional causal relationship between RDW and RA. Loci near IL6R, IL1RN, FADS1/FADS2, UBE2L3 and HELZ2 showed colocalization. Increased RDW is associated with elevated risk of incident RA especially in the high genetic risk populations, but only suggestive evidence supports a causal relationship between them. Show less
📄 PDF DOI: 10.1186/s41927-024-00451-1
FADS1
Mina Ali, Martin Steen Mortensen, Ole Bæk +11 more · 2025 · Metabolites · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/metabo15100670
ANGPTL4
Guomei Yang, Luoquan Ao, Qing Zhao +10 more · 2025 · Cell communication and signaling : CCS · BioMed Central · added 2026-04-24
Sepsis, a life-threatening organ dysfunction caused by dysregulated host responses to infection, has emerged as a leading cause of mortality in ICU patients. Macrophages, crucial effector cells in inn Show more
Sepsis, a life-threatening organ dysfunction caused by dysregulated host responses to infection, has emerged as a leading cause of mortality in ICU patients. Macrophages, crucial effector cells in innate immunity, play pivotal regulatory roles in sepsis pathogenesis. While Programmed death-ligand 1 (PD-L1), a key immune checkpoint molecule, is traditionally believed to exert immunosuppressive effects through membrane anchoring, its involvement in macrophage polarization during sepsis remains unclear. This study investigated the spatial distribution of PD-L1 in macrophages and its regulatory effects on inflammatory responses during sepsis. This study investigated PD-L1’s regulatory role in macrophage polarization through RNA sequencing, Immunoprecipitation-mass spectrometry, molecular docking, and site-directed mutagenesis, with preliminary validation in C57BL/6 mice. Using GEO database analysis combined with qRT-PCR and Western blotting, we confirmed elevated PD-L1 expression in sepsis and M1-polarized macrophages. Laser scanning confocal microscopy demonstrated dual localization of PD-L1, appearing both on the plasma membrane and intracellularly within M1 macrophages. RNA sequencing revealed PD-L1’s promotion of M1 polarization through enhanced AIM2 expression in the NOD-like receptor pathway. Integrated analyses employing mass spectrometry, molecular docking, site-directed mutagenesis, and Western blotting demonstrated PD-L1 binding to AIM2, which augmented expression of downstream effector molecules (IL-18 and IFN-γ) and potentiated STAT1 activation. Silencing AIM2 by siRNA or IL-18 antagonism reversed PD-L1-induced M1 markers (IL-27, IL-6, iNOS/NO). PD-L1 was further shown to exacerbate pathological progression in septic mouse models. Our study demonstrated that sepsis-induced PD-L1 overexpression in macrophages exacerbates pathological progression by upregulating AIM2 expression, binding to AIM2 to enhance IL-18 production, which activates STAT1 to drive M1 polarization. The online version contains supplementary material available at 10.1186/s12964-025-02578-1. Show less
📄 PDF DOI: 10.1186/s12964-025-02578-1
IL27
Dong-Yi Chen, Ming-Lung Tsai, Ming-Jer Hsieh +8 more · 2025 · European journal of preventive cardiology · Oxford University Press · added 2026-04-24
Recent evidence suggests that elevated lipoprotein(a) [Lp(a)] contributes to atherosclerotic cardiovascular disease (ASCVD). The predictive value of specific Lp(a) cutoff points of 30 mg/dL remains to Show more
Recent evidence suggests that elevated lipoprotein(a) [Lp(a)] contributes to atherosclerotic cardiovascular disease (ASCVD). The predictive value of specific Lp(a) cutoff points of 30 mg/dL remains to be established. This study investigated the relationship between Lp(a) concentrations and cardiovascular outcomes in Taiwanese individuals, stratified by pre-existing ASCVD status. We conducted a retrospective analysis of 51,934 subjects from the Chang Gung Research Database (January 2004 to June 2019), comprising 49,363 individuals without ASCVD and 2,571 with established ASCVD. The primary outcome was major adverse cardiovascular events (MACEs), encompassing acute myocardial infarction, ischemic stroke, revascularization procedures, peripheral arterial interventions, and cardiovascular mortality. Individuals were followed until their last visit to our institutions or December 31, 2019. During a mean follow-up of 6.6 years (standard deviation: 5.0 years), the study population demonstrated a median Lp(a) of 9.6 mg/dL (interquartile range: 4.6-18.5). In ASCVD-free individuals, Lp(a) concentrations ≥30 mg/dL were associated with increased MACE risk (adjusted subdistribution hazard ratio [aSHR]: 1.24; 95% confidence interval [CI]: 1.07-1.43). Similarly, in the ASCVD cohort, elevated Lp(a) predicted higher MACE occurrence (aSHR: 1.36; 95% CI: 1.07-1.74). Restricted cubic spline analysis confirmed a progressive risk elevation beyond the 30 mg/dL threshold in both groups. Lp(a) levels ≥30 mg/dL independently predicted adverse cardiovascular outcomes, regardless of baseline ASCVD status. This threshold appears suitable for cardiovascular risk stratification in both primary and secondary prevention settings. Show less
no PDF DOI: 10.1093/eurjpc/zwaf649
LPA
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
Hongzhi Li, Guangming Li, Xian Gao +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, c Show more
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, clinical information and mutation data of LUAD patients collected from the TCGA and GEO database, we obtained 102 endotheliocyte senescence-related genes. The "ConsensusClusterPlus" R package was employed for unsupervised cluster analysis, and the "limma" was used for the differentially expressed gene (DEG) analysis. A prognosis model was created by univariate and multivariate Cox regression analysis combined with Lasso regression utilizing the "survival" and "glmnet" packages. KM survival and receiver operator characteristic curve analyses were conducted applying the "survival" and "timeROC" packages. "MCPcounter" package was used for immune infiltration analysis. Immunotherapy response analysis was performed based on the IMvigor210 and GSE78220 cohort, and drug sensitivity was predicted by the "pRRophetic" package. Cell invasion and migration were tested by carrying out Transwell and wound healing assays. According to the results, a total of 32 genes related to endotheliocyte senescence were screened to assign patients into C1 and C2 subtypes. The C2 subtype showed a significantly worse prognosis and an overall higher somatic mutation frequency, which was associated with increased activation of cancer pathways, including Myc_targets2 and angiogenesis. Then, based on the DEGs between the two subtypes, we constructed a five-gene RiskScore model with a strong classification effectiveness for short- and long-term OS prediction. High- and low-risk groups of LUAD patients were classified by the RiskScore. High-risk patients, characterized by lower immune infiltration, had poorer outcomes in both training and validation datasets. The RiskScore was associated with the immunotherapy response in LUAD. Finally, we found that potential drugs such as Cisplatin can benefit high-risk LUAD patients. In-vitro experiments demonstrated that silencing of Angiopoietin-like 4 (ANGPTL4), Gap Junction Protein Beta 3 (GJB3), Family with sequence similarity 83-member A (FAM83A), and Anillin (ANLN) reduced the number of invasive cells and the wound healing rate, while silencing of solute carrier family 34 member 2 (SLC34A2) had the opposite effect. This study, collectively speaking, developed a prognosis model with senescence signature genes to facilitate the diagnosis and treatment of LUAD. Show less
📄 PDF DOI: 10.1038/s41598-025-95551-4
ANGPTL4
Xuan Tie, Zhiang Chen, Shulei Yao +6 more · 2025 · Frontiers in bioscience (Landmark edition) · added 2026-04-24
Primary membranous nephropathy (pMN) often progresses to end-stage renal disease (ESRD) in the absence of immunosuppressive therapy. The immunological mechanisms driving pMN progression remain insuffi Show more
Primary membranous nephropathy (pMN) often progresses to end-stage renal disease (ESRD) in the absence of immunosuppressive therapy. The immunological mechanisms driving pMN progression remain insufficiently understood. We developed a single-cell transcriptomic profile of peripheral blood mononuclear cells (PBMCs) from 11 newly-diagnosed pMN patients and 5 healthy donors. Through correlation analysis, we identified potential biomarkers for disease stratification and poor prognosis. Expression levels of several proinflammatory factors were significantly increased in patients compared to healthy donors, such as interleukins ( Our study provides insight into the immunological mechanism of pMN and identifies numerous biomarkers and signaling pathways as potential therapeutic targets for managing the progression of high-risk pMN. Show less
no PDF DOI: 10.31083/FBL36332
DHX36
Wenqin Chen, Bin Gao, Yang Zhou +1 more · 2025 · Behavioral sciences (Basel, Switzerland) · MDPI · added 2026-04-24
In school settings, nomophobia-a newly identified form of problematic mobile phone use characterized by anxiety and discomfort experienced when an individual is unable to use or access their smartphon Show more
In school settings, nomophobia-a newly identified form of problematic mobile phone use characterized by anxiety and discomfort experienced when an individual is unable to use or access their smartphone-poses significant challenges to students' learning and daily life. Prior research on nomophobia has predominantly adopted a variable-centered perspective. However, if nomophobia is heterogeneous across subgroups, acknowledging this heterogeneity may inform the advancement of more tailored and productive therapeutic methods. Latent profile analysis (LPA) was conducted separately among high school students (N = 446) and college students (N = 667) to identify potential subgroup heterogeneity in nomophobia. To examine cross-group similarities in nomophobia profiles, a multi-group LPA was employed. Based on multiple model fit criteria, a three-profile solution-high nomophobia, moderate nomophobia, and low nomophobia-was identified for both groups. However, the multi-group LPA provided only partial support for the similarity of nomophobia profiles across educational stages, specifically in terms of configural and dispersion similarity. While similar nomophobia profiles emerged across groups, the partial equivalence suggests that intervention strategies for nomophobia may not be universally applicable across different educational levels. Additional studies should investigate the mechanisms underlying students' nomophobia profiles and to inform differentiated interventions for educators, institutions, and policymakers. Show less
📄 PDF DOI: 10.3390/bs15091282
LPA
Zhizhong Wang, Zhiyong Li, Ailong Lin +4 more · 2025 · PloS one · PLOS · added 2026-04-24
Amyloid cerebrovascular disease, primarily driven by the accumulation of amyloid-beta (Aβ) peptides, is intricately linked to neurodegenerative disorders like Alzheimer's disease. BACE1 (beta-site amy Show more
Amyloid cerebrovascular disease, primarily driven by the accumulation of amyloid-beta (Aβ) peptides, is intricately linked to neurodegenerative disorders like Alzheimer's disease. BACE1 (beta-site amyloid precursor protein cleaving enzyme 1) plays a critical role in the production of Aβ, making it a key therapeutic target. In the current work, a CNS library of ChemDiv database containing 44085 compounds was screened against the BACE1 protein. Initially, a structure-based pharmacophore hypothesis was constructed, followed by virtual screening, with the screened hits docked to the BACE1 protein to determine the optimal binding modes. The docking results were examined using the glide gscore and chemical interactions of the docked molecules. The cutoff value of -5 kcal/mol was used to select hits with high binding affinities. A total of seven hits were chosen based on the glide g score. Furthermore, the possible binding mechanisms of the docked ligands were investigated, and it was discovered that all seven selected ligands occupied the same site in the predicted binding pocket of protein. The bioactivity scores of the compounds demonstrated that the chosen compounds possess the features of lead compounds. The toxicity risks and ADMET features of the selected hits were anticipated, and four compounds, J032-0080, SC13-0774, V030-0915, and V006-5608 were chosen for stability analysis. The selected hits were extremely stable and strongly bound to the BACE1 pocket, and conformational changes caused by RMSD, RMSF, and protein-ligand interactions were assessed using MD modeling. Similarly, principal component analysis revealed a large static number of hydrogen bonds. The MM/GBSA binding free energies maps revealed a significant energy contribution in the binding of selected hits to BACE1. The binding free energy landscapes indicated that the hits were bound with a high binding affinity. Thus, the hits could serve as lead compounds in biophysical investigations to limit the biological activity of the BACE1 protein. Show less
📄 PDF DOI: 10.1371/journal.pone.0317716
BACE1
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
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
Kirk Habegger, Alejandra Tomas, Roger Chen +3 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fendo.2025.1710843
GIPR