👤 Ke 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, 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
Qianqian Wang, Peize Chen, Xiaorong Wang +9 more · 2025 · Non-coding RNA research · Elsevier · added 2026-04-24
[This corrects the article DOI: 10.1016/j.ncrna.2022.12.004.].
no PDF DOI: 10.1016/j.ncrna.2025.02.002
DHX36
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
Lishan Zeng, Xin Chen, Kai Kang +12 more · 2025 · Cardiovascular research · Oxford University Press · added 2026-04-24
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. Thi Show more
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. This study aimed to explore the role and potential mechanisms of liver X receptor α (LXRα) in CAVD, which offers a promising approach for treating CAVD. Osteogenic stimulation was performed following which a substantial downregulation of LXRα was observed in human calcific aortic valves and valvular interstitial cells. Further functional investigations revealed that silencing LXRα exacerbated calcification both in vitro and in vivo. We showed that LXRα suppressed the protein kinase R-like endoplasmic reticulum kinase/eukaryotic initiation factor 2/activating transcription factor 4 pathway, which controls endoplasmic reticulum stress (ERS) and promotes osteogenic differentiation, thereby slowing the course of CAVD. Our research offers fresh perspectives on how LXRα controls the pathophysiology of CAVD via regulating ERS. The findings suggest that targeting LXRα is a potential treatment strategy for treating aortic valve calcification. Show less
no PDF DOI: 10.1093/cvr/cvaf044
NR1H3
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
Zhengliang Li, Xiaokai Chen, Linlin Ren +4 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clin Show more
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clinical practice. To develop machine learning (ML) models for classifying prevalent atherosclerotic cardiovascular disease (ASCVD) risk in MASLD patients, and to enhance model interpretability using SHapley Additive exPlanations (SHAP). Methods: This retrospective study included 590 MASLD patients diagnosed at the Affiliated Hospital of Qingdao University between December 2019 and December 2024. Patients were randomly divided into a training set (n=413) and a validation set (n=177), and further stratified based on ASCVD status. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. Six ML models were developed and evaluated using sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and F1 score. SHAP analysis was performed to interpret feature contributions. ASCVD was present in 434 of 590 patients (73.6%). The Gradient Boosting (GB) model achieved the best performance, with AUCs of 0.918 (95% CI: 0.890-0.944) in the training set and 0.817 (95% CI: 0.739-0.883) in the validation set. SHAP analysis identified the top predictors as the Cholesterol-HDL-Glucose (CHG) index, Castelli Risk Index II (CRI-II), lipoprotein(a) [Lp(a)], serum creatinine (Scr), and uric acid (UA). The GB model demonstrated strong high accuracy in identifying existing ASCVD in MASLD patients and may serve as a useful tool for early risk stratification in clinical settings. Show less
📄 PDF DOI: 10.3389/fendo.2025.1684558
LPA
Yan Chen, Yan Zhu, Zihu Tan +7 more · 2025 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive cognitive decline and behavioral impairments in the elderly. Microglia, the resident immune cells of the Show more
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by progressive cognitive decline and behavioral impairments in the elderly. Microglia, the resident immune cells of the central nervous system, play a crucial role in modulating the pathological processes associated with AD. Jiajian Shuyu Pills (JJSYP) are frequently employed in the treatment of AD, purportedly by enhancing the physiological functions of human tissues and organs to modulate the immune response. Nevertheless, the underlying mechanisms by which JJSYP exert their therapeutic effects in the context of AD remain inadequately elucidated. This study aimed to assess the effects of JJSYP on cognitive enhancement and the alleviation of neuroinflammation in the treatment of AD, as well as to explore the underlying mechanisms using mouse models. The components of JJSYP in serum were analyzed using HPLC-Q/TOF-MS. APP/PS1 transgenic mice served as AD models in this investigation. Cognitive function in the AD mice was assessed through the Mirror Water Maze Test and the Novel Object Recognition Test. The quantification of apoptotic hippocampal cells was conducted using Nissl staining and TUNEL staining. Immunofluorescence (IF) and Western blot (WB) analyses were employed to examine microglial activation and the expression of relevant proteins. Transcriptomic sequencing analysis and network pharmacology were administrated to explore the potential mechanisms of JJSYP in AD treatment. Inflammatory cytokine levels in the brain were measured using RT-PCR. A total of 74 absorbed prototype components from JJSYP were identified. JJSYP effectively improved cognitive function and neuroapoptosis in AD model mice by modulating the activation of microglia. The JJSYP intervention alleviated neuroinflammation by suppressing microglial activation and reducing the accumulation of amyloid β-protein. Through transcriptome sequencing and WB verification, 34 differentially expressed genes (DEGs) were identified, including ACKR3, NR1H3 and Adra1a. Following treatment with a high dose of JJSYP, both ACKR3 and NR1H3 showed a significant decrease compared to the model group. Conversely, ADRA1A expression was reduced in model group compared to the control group, but increased following high dose JJSYP treatment. Research involving RNA sequencing and network pharmacology indicated that JJSYP altered the activation of CXCL12/ACKR3 signaling pathways in the hippocampus. JJSYP exhibits potential anti-Alzheimer's Disease effects and warrants further investigation and development as a prosper treatment for AD. Show less
no PDF DOI: 10.1016/j.jep.2025.119508
NR1H3
Mei-Jun Lyu, Dong-Yu Min, Lian-Qun Jia +2 more · 2025 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
To explore the mechanism of astragaloside Ⅳ in regulating energy metabolic reprogramming, alleviating endothelial-to-mesenchymal transition(EndMT), and preventing atherosclerosis(AS) in ApoE~(-/-) AS Show more
To explore the mechanism of astragaloside Ⅳ in regulating energy metabolic reprogramming, alleviating endothelial-to-mesenchymal transition(EndMT), and preventing atherosclerosis(AS) in ApoE~(-/-) AS mice, ApoE~(-/-) AS mouse models were established by high-fat feeding and randomly divided into three groups: model group, astragaloside Ⅳ group, and blank control group. The mice in the astragaloside Ⅳ group were administered astragaloside Ⅳ via gavage at a dose of 40 mg·kg~(-1)·d~(-1), while mice in the blank control group and model group received an equal volume of normal saline via gavage for four consecutive weeks. The blood lipid levels of mice in each group were measured using an automatic biochemical analyzer. Hematoxylin-eosin(HE) staining was used to observe the pathomorphological changes in the mouse aorta. The degree of EndMT was detected by immunofluorescence, and the protein expression levels of α-smooth muscle actin(α-SMA) and vascular endothelial cadherin(VE-cadherin) in the aorta were detected by Western blot. Targeted energy metabolomics technology was used to qualitatively and quantitatively analyze the spectrum of serum energy metabolites in mice, followed by KEGG pathway enrichment analysis of differential metabolites. The expression of glycolysis-related genes was detected using RT-PCR. The results showed that astragaloside Ⅳ significantly reduced the levels of serum total cholesterol(TC), triglyceride(TG), and low-density lipoprotein cholesterol(LDL-C) while increasing high-density lipoprotein cholesterol(HDL-C) levels. It reduced atherosclerotic plaque formation, decreased the number of α-SMA and VE-cadherin double staining positive cells, downregulated the protein expression of mesenchymal cell surface antigen α-SMA, and upregulated the protein expression of endothelial cell surface antigen VE-cadherin. Targeted energy metabolomics analysis shows that astragaloside Ⅳ restored nine altered energy metabolites in the serum. The pathway enrichment analysis indicated that serum differential metabolites were mainly enriched in glycolytic pathways. RT-PCR detection revealed that astragaloside Ⅳ significantly downregulated the mRNA expression of key glycolytic enzymes, including hexokinase-Ⅱ(HK-Ⅱ), phosphofructokinase(PFKM), and pyruvate kinase M2(PKM2). These results suggest that astragaloside Ⅳ may ameliorate AS by inhibiting the excessive activation of glycolysis, modulating energy metabolic reprogramming, and alleviating EndMT. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20250711.501
APOE
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
Xueqian Wang, Shengzhuang Guan, Yiqing Gao +13 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Brachydactyly type E (BDE) is characterized by variable shortening of metacarpals or metatarsals, often involving phalanges. It may occur as an isolated anomaly or as part of congenital syndromes. Wit Show more
Brachydactyly type E (BDE) is characterized by variable shortening of metacarpals or metatarsals, often involving phalanges. It may occur as an isolated anomaly or as part of congenital syndromes. With advancements in molecular diagnostic technologies, how genetic testing enhances the precise diagnosis of BDE remains unclear. Our aims were to establish an algorithm for molecular genetic diagnostics in Chinese children with BDE and to explore the phenotype-genotype correlations of Chinese patients with BDE. We reviewed left-hand wrist X-rays from children visiting Children's Hospital of Soochow University (Jun 2021-Dec 2023). From 60,650 films, 135 BDE cases were identified, and their comprehensive phenotypes were collected. Whole-exome sequencing (WES) with copy number variation (CNV) analysis was performed on 60 patients and their parents. Sanger sequencing was used to validate single nucleotide variants (SNV) and indels. Causative variants were found in 19 patients. SNVs and indels affecting 10 genes were identified in 15 patients, and CNVs in four. Through comprehensive evaluation of genotype-phenotype correlations, we propose a diagnostic algorithm for precise molecular diagnosis in Chinese children with BDE. Show less
📄 PDF DOI: 10.3389/fendo.2025.1571136
EXT1
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
Yuwei Bai, Jianglong Li, Xueqian Wu +8 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-l Show more
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-lowering effects, while Silybum marianum (L.) Gaertn, known as milk thistle, has hepatoprotective properties and exhibits antioxidant effects. To evaluate the effect of sea buckthorn and milk thistle solid beverage (H-S solid beverage) in alleviating hyperlipidemia in rats and explore the underlying mechanisms by analyzing plasma and liver metabolomics, lipidomics, and liver transcriptomics. A hyperlipidemic rat model was established after 2 weeks of high-fat diet (HFD) feeding in Sprague Dawley rats. The administered doses of H-S solid beverage were 0.30 g/kg/d, 0.15 g/kg/d and 0.075 g/kg/d. Serum biochemical parameter detection, histopathological section analysis, untargeted plasma and liver metabolomics, lipidomics, and liver transcriptomics were performed to determine the therapeutic effects of H-S solid beverage and predict the related pathways in rats with hyperlipidemia. Changes in genes and proteins related to lipid metabolism were detected using real-time quantitative polymerase chain reaction and western blotting. Eighty-nine components were identified in H-S solid beverage using ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry, with flavonoids being the major constituents. The H-S solid beverage significantly reduced body weight, liver index, body fat percentage, lipid accumulation, and liver injury in HFD-fed rats. Fatty acids (FA), bile acid, phosphatidyl ethanolamine, phosphatidylcholine, triglyceride, cholesterol ester, diglyceride and phosphatidylinositol levels were significantly altered in the liver and plasma. Moreover, the transcriptomic analysis suggested that H-S solid beverage significantly altered the hepatic gene expression of cholesterol synthesis (Pdk4, Hmgcs1, and Dhcr24), lipogenesis (Scd, Angptl4, and Angptl8), and FA β-oxidation (Cpt1α, Pparδ, Acsl, Pgc-1α, and Pla2g2d). The solid beverage of sea buckthorn and milk thistle was firstly demonstrated to ameliorate HFD-induced hyperlipidemia. The lipid-lowering and hepatoprotective effects of H-S solid beverage significantly regulated cholesterol synthesis and de novo lipogenesis, as well as FA β-oxidation. In summary, this study highlights the potential of H-S solid beverages for the treatment of hyperlipidemia. Show less
no PDF DOI: 10.1016/j.phymed.2025.156920
ANGPTL4
Fawang Du, Hanchao Wang, Zhihong Chen +7 more · 2025 · Journal of asthma and allergy · added 2026-04-24
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcript Show more
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcriptomics profile and promising biomarkers for asthma severity prediction. In discovery cohort, induced sputum cells from 3 non-severe and 3 severe asthma patients were collected and analyzed using RNA-seq. Multivariate analysis was performed to explore asthma severity-associated transcriptomics profile and differential expressed genes (DEGs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used for pathway enrichment analysis. Subsequently, based on the previous study and clinical experience, the mRNA expressions of 6 overlapped asthma severity-associated DEGs and Distinct asthma severity-associated transcriptomics profile was identified in induced sputum cells in discovery cohort. Then, 345 DEGs were found, of which 38 terms and 32 pathways were enriched using GO and KEGG, respectively. In validation cohort, the mRNA expressions of Collectively, this study provides the first identification of the association between induced sputum cells transcriptomics profile and asthma severity, indicating the potential value of transcriptomics for asthma management. The study also reveals the promising value of serum C3 for predicting asthma severity in clinical practice. Show less
no PDF DOI: 10.2147/JAA.S517140
NRXN3
Hongzheng Lu, Siqi Yang, Wei Li +3 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
Dietary interventions with food-derived natural products have emerged as a promising strategy to alleviate obesity. This study aims to investigate the anti-obesity effect of
📄 PDF DOI: 10.3390/foods14030459
LPL
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
Xinning Dong, Jing Xu, Kejun Du +3 more · 2025 · Neuroreport · added 2026-04-24
This study aimed to examine reticulon 4 (RTN4), neurite outgrowth inhibitor protein expression that changes in high-altitude traumatic brain injury (HA-TBI) and affects on blood-brain barrier's (BBB) Show more
This study aimed to examine reticulon 4 (RTN4), neurite outgrowth inhibitor protein expression that changes in high-altitude traumatic brain injury (HA-TBI) and affects on blood-brain barrier's (BBB) function. C57BL/6J 6-8-week-old male mice were used for TBI model induction and randomized into the normal altitude group and the 5000-m high-altitude (HA) group, each group was divided into control (C) and 8h/12h/24h/48h-TBI according to different times post-TBI. Brain water content (BWC) and modified Neurological Severity Score were measured, RTN4 and autophagy-related indexes (Beclin1, LC3B, and SQSTM1/p62) were detected by western blot, immunofluorescence technique, and PCR in peri-injury cortical tissues. The expression of NgR1, Lingo-1, TROY, P75, PirB, S1PR2, and RhoA receptors' downstream of RTN4 was detected by PCR. HA-TBI caused increased neurological deficits including motor, sensory, balance and reflex deficits, increased BWC, earlier peak RTN4 expression and a longer duration of high expression in peri-injury cortical tissues, and enhanced levels of Beclin1, LC3B, and SQSTM1/p62 to varying degrees. Concurrently, the transcription of S1PR2 and PirB, the main signaling molecules downstream of RTN4, was significantly increased. In HA-TBI's early stages, the increased RTN4 may regulate enhanced autophagic initiation and impaired autolysosome degradation in vascular endothelial cells via S1PR2 receptor activation, thereby reducing BBB function. This suggests that autophagy could be a new target using RTN4 intervention as a clinical HA-TBI mechanism. Show less
no PDF DOI: 10.1097/WNR.0000000000002122
LINGO1
Yun Zhang, Huaqiu Chen, Yijia Feng +14 more · 2025 · Nature aging · Nature · added 2026-04-24
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential Show more
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential neuroprotective properties, but their effects on AD and the underlying mechanisms are not well understood. Here we demonstrate that GLP-1RAs can alleviate AD-related phenotypes by activating 5' AMP-activated protein kinase (AMPK) signaling. We found that plasma GLP-1 levels were decreased in AD model mice and negatively correlated with amyloid-beta (Aβ) load in patients with AD. Enhancing GLP-1 signaling through GLP-1RAs increased CaMKK2-AMPK signaling, which subsequently reduced BACE1-mediated cleavage of amyloid precursor protein (APP) and Aβ generation. GLP-1RAs also increased AMPK activity in microglia, inhibiting neuroinflammation and promoting Aβ phagocytosis. Consequently, GLP-1RAs inhibited plaque formation and improved memory deficits in AD model mice. Our findings indicate that AMPK activation mediates the effects of GLP-1RAs on AD, highlighting the therapeutic potential of GLP-1RAs for the treatment of AD. Show less
📄 PDF DOI: 10.1038/s43587-025-00869-3
BACE1
Ashley E Ciecko, Rabia Nabi, Amber Drewek +8 more · 2025 · iScience · Elsevier · added 2026-04-24
In the non-obese diabetic (NOD) mouse model of autoimmune diabetes, interleukin (IL)-27 stimulates interferon γ (IFNγ) production by CD4 and CD8 T cells and is essential for disease development. Here, Show more
In the non-obese diabetic (NOD) mouse model of autoimmune diabetes, interleukin (IL)-27 stimulates interferon γ (IFNγ) production by CD4 and CD8 T cells and is essential for disease development. Here, we tested the role of IL-27 in cellular communication. Single-cell RNA sequencing and T cell adoptive transfer showed that IL-27 intrinsically controlled the differentiation of islet-infiltrating CD4 T cells by driving them toward an IL-21 Show less
📄 PDF DOI: 10.1016/j.isci.2025.113537
IL27
Ting Yi, Shimeng Dai, Jingrui Tao +4 more · 2025 · Journal of professional nursing : official journal of the American Association of Colleges of Nursing · Elsevier · added 2026-04-24
Undergraduate nursing students face significant academic and practical challenges, with their responses reflecting their academic resilience. However, most studies have overlooked the differences in t Show more
Undergraduate nursing students face significant academic and practical challenges, with their responses reflecting their academic resilience. However, most studies have overlooked the differences in their levels of academic resilience and the factors contributing to these differences. To identify the latent profiles of undergraduate nursing students' academic resilience and to analyze their influencing factors. A cross-sectional study was carried out among 1795 undergraduate nursing students from November 2022 to October 2023 by employing the general information questionnaire, the academic resilience questionnaire for college students, and the brief 2-way social support scale. Latent profile analysis (LPA) was used to analyze the latent profiles of academic resilience, and multiple logistic regression was utilized to explore the factors associated with the identified profiles. Four potential profiles were identified: low academic resilience group, moderate academic resilience group, high academic resilience but low focus and dissociation group, and high academic resilience group. Residence, attitude towards the nursing profession, self-directed study duration, academic performance rank, received and provided instrumental support were found to be associated with the different profiles. These findings highlight the heterogeneity in academic resilience and support tailored educational interventions based on students' specific academic resilience profiles. Show less
no PDF DOI: 10.1016/j.profnurs.2025.09.014
LPA
Wei Su, Houhua Lai, Xin Tang +4 more · 2025 · Nan fang yi ke da xue xue bao = Journal of Southern Medical University · added 2026-04-24
To investigate the role of apelin in regulating proliferation, migration and angiogenesis of bladder cancer cells and the possible regulatory mechanism. GEO database was used to screen the differentia Show more
To investigate the role of apelin in regulating proliferation, migration and angiogenesis of bladder cancer cells and the possible regulatory mechanism. GEO database was used to screen the differentially expressed genes in bladder cancer tissues and cells. Bladder cancer and paired adjacent tissues were collected from 60 patients for analysis of apelin expressions in relation to clinicopathological parameters. In cultured bladder cancer J82 cells and human umbilical vein endothelial cells (HUVECs), the effects of transfection with an apelin-overexpressing plasmid or specific siRNAs targeting apelin, fibroblast growth factor 2 (FGF2) and fibroblast growth factor receptor 1 (FGFR1) on proliferation and migration of J82 cells and tube formation in HUVECs were examined using plate cloning assay, Transwell assay, and angiogenesis assay; the changes in FGF2 expression and FGFR1 phosphorylation were detected using Western blotting. The expression level of apelin was significantly higher in bladder cancer tissues than adjacent tissues, and bladder cancer cell lines (T24 and J82) also expressed higher mRNA and protein levels of apelin than SV-HUC-1 cells. Apelin expression level in bladder cancer tissues was correlated with tumor invasion, distant metastasis and advanced TNM stages. Apelin knockdown significantly suppressed proliferation and migration of J82 cells and decreased the total angiogenic length of HUVECs. In contrast, apelin overexpression significantly promoted proliferation and migration and enhanced FGFR1 phosphorylation in J82 cells, and increased the total angiogenesis length in HUVECs, but this effects were effectively mitigated by transfection of the cells with FGF2 siRNA or FGFR1 siRNA. High expression of apelin promotes J82 cell proliferation and migration and HUVEC angiogenesis by promoting activation of the FGF2/FGFR1 pathway. Show less
no PDF DOI: 10.12122/j.issn.1673-4254.2025.06.18
FGFR1
Linjie Chen, Haojie Chen, Zinan Chen +4 more · 2025 · Respiratory medicine · Elsevier · added 2026-04-24
Observational studies have reported an association between visceral obesity and asthma. However, the causal direction of this relationship remains uncertain due to potential confounding and reverse ca Show more
Observational studies have reported an association between visceral obesity and asthma. However, the causal direction of this relationship remains uncertain due to potential confounding and reverse causality. Furthermore, the underlying mediating factors and potential therapeutic targets underlying this association are poorly understood. This study aimed to investigate the causal effect of visceral adipose tissue (VAT) on asthma risk, identify potential mediators, and quantify their effects using a Mendelian randomization (MR) framework. In this study, we employed MR approach to elucidate the impact of VAT on asthma and to assess the potential mediators. Subsequently, the association between seven lipid-lowering medication targets and asthma risk was investigated using the drug target MR method. Lastly, we conducted an observational study involving 12,120 participants to evaluate the relationship between visceral adiposity index (VAI) and asthma. The univariable MR analysis demonstrated that each standard deviation increase in genetically predicted VAT was associated with a 46 % higher risk of asthma (IVW: OR = 1.460, 95 % CI: 1.351-1.578, p = 1.471E-21). This association remained significant after adjusting for BMI in multivariable MR (OR = 1.137, 95 % CI: 1.023-1.262, p = 0.017). Mediation analysis revealed that HDL-C accounted for 4.3 % of this effect (OR = 1.016, 95 % CI: 1.001-1.033, p = 0.038). Drug-target MR indicated that activation of HMGCR and LDLR reduced asthma risk (OR = 0.846 and 0.866, respectively; both p < 0.01), whereas LPL activation increased risk (OR = 1.080, p = 0.015). Observational analysis of NHANES data (n = 12,120) confirmed that higher VAI was associated with increased asthma prevalence (OR = 1.290, 95 % CI: 1.101-1.479, p = 0.010). Our results reveal a significant association between increased visceral adipose tissue and elevated risk of asthma, which is partially mediated by high-density lipoprotein cholesterol. 3-hydroxy-3-methylglutaryl coenzyme A reductase, low-density lipoprotein receptor, and lipoprotein lipase exhibit potential as therapeutic targets for asthma. Show less
no PDF DOI: 10.1016/j.rmed.2025.108482
LPL
Ting Wang, Hongkun Lin, Yan Deng +12 more · 2025 · The Journal of nutritional biochemistry · Elsevier · added 2026-04-24
Time-restricted feeding (TRF) is a dietary intervention that has been shown to have numerous health benefits. However, it is important to further investigate the potential effectiveness of TRF in addr Show more
Time-restricted feeding (TRF) is a dietary intervention that has been shown to have numerous health benefits. However, it is important to further investigate the potential effectiveness of TRF in addressing sarcopenic obesity (SO), which is characterized by a combination of age-related obesity and sarcopenia. In this study, 14-month-old C57BL/6J male mice were fed either regular chow diet or high-fat diet (HFD), and had either ad libitum or restricted access to food for 8 hours daily (Intervention for 7 months). For the human trial (ChiCTR2100052876), obese individuals (n=21) with a Body Mass Index ≥28 were recruited and instructed to adopt an 8-hour eating window and a 16-hour fasting period. Here, we found that the TRF intervention significantly reduced global fat mass (P < .001) and volume (P < .05), and increase lean mass compared to mice fed with HFD. Furthermore, TRF improved overall metabolic mobility (8h TRF+HFD vs. AL+HFD). This intervention also enhanced liver FGF21 protein levels (P < .01) and the expression of FGFR1 and FGF21 target genes in adipose and muscle tissues, thus improving mitochondrial quality control in these tissues. Notably, TRF interventions led to a significant decrease in serum FGF21 levels (P < .05). In the human trial, TRF intervention resulted in a significant reduction in weight (P < .001) and body fat levels (P < .001) among obese individuals, as well as a decrease in serum GLU (P < .001), insulin (P < .001), and TC levels (P < .05). Overall, the findings indicate that TRF intervention improves SO by regulating liver FGF21 expression, thereby enhancing FGF21 sensitivity in adipose and muscle tissues. Show less
no PDF DOI: 10.1016/j.jnutbio.2025.109893
FGFR1
Nicklas Brustad, Tingting Wang, Shizhen He +15 more · 2025 · Nature communications · Nature · added 2026-04-24
Early life air pollution exposure may play a role in development of respiratory infections, but underlying mechanisms are still not understood. We utilized data from two independent prospective birth Show more
Early life air pollution exposure may play a role in development of respiratory infections, but underlying mechanisms are still not understood. We utilized data from two independent prospective birth cohorts to investigate the influence of prenatal and postnatal ambient air pollution exposure of PM Show less
📄 PDF DOI: 10.1038/s41467-025-61392-y
AXIN1
Hanxiao Xue, Sheng Bi, Zhigeng Chen +8 more · 2025 · EJNMMI research · BioMed Central · added 2026-04-24
Abnormal glymphatic system may play a critical role in amyloid-β (Aβ) accumulation in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. This study aims to use diffusion tensor ima Show more
Abnormal glymphatic system may play a critical role in amyloid-β (Aβ) accumulation in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. This study aims to use diffusion tensor image analysis along the perivascular space (DTI-ALPS) and perivascular space volume fraction (PVSVF) to investigate the aberrant glymphatic functions and the association between Aβ deposition and clinical symptoms in AD spectrum. The ALPS index was significantly lower in AD patients compared to MCI and normal controls (NC) groups. Additionally, the AD group showed a significantly higher PVSVF in hippocampus (HP) compared to NC group. No notable variations were observed in the ALPS index or PVSVF across various regions when comparing the MCI group to the NC group. Apolloprotein E (APOE) ε4 + group showed significantly higher PVSVF-HP and PVSVF in basal ganglia compared to APOE ε4 − group. All participants’ HP volume, lower cognitive scores, and higher Our findings demonstrate that glymphatic dysfunction is associated with cognitive decline, underscoring the critical roles of Aβ pathology and the APOE genotype in mediating this relationship. Further exploration of glymphatic function holds significantly promise for advancing research on AD pathogenesis. The online version contains supplementary material available at 10.1186/s13550-025-01339-y. Show less
📄 PDF DOI: 10.1186/s13550-025-01339-y
APOE
Mackenzie K Fitzpatrick, Christina Dyson, Angela Beeson +8 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
We have previously demonstrated that a transmembrane domain mutation in
no PDF DOI: 10.1101/2025.03.28.645767
ADCY3
Xueli Chen, Li Dai · 2025 · Biochemical genetics · Springer · added 2026-04-24
Asthma is a common chronic respiratory disease in children, the incidence rate of which has increased in recent years. Wilms tumour 1-associated protein (WTAP) is an N6-methyladenosine (m6A) methyltra Show more
Asthma is a common chronic respiratory disease in children, the incidence rate of which has increased in recent years. Wilms tumour 1-associated protein (WTAP) is an N6-methyladenosine (m6A) methyltransferase. The purpose of this study was to explore the specific mechanism of WTAP in asthma progression, and clarify the intricate interplay between m6A modifications, WTAP, AXIN1, and their collective impact on airway smooth muscle cells (ASMCs) proliferation in asthma. Platelet-derived growth factor-BB (PDGF-BB)-treated ASMCs were used to establish an asthma model in vitro. The cell phenotype was tested using CCK-8, transwell, and wound healing assays. The expression of the Wnt signalling pathway was detected by western blotting. In addition, the relationship between WTAP/YTDHF2 and AXIN1 was assessed by a double luciferase reporter assay. Actinomycin D treatment and RT‒qPCR assays were performed to determine the mRNA stability of AXIN1. We found that WTAP was significantly increased in PDGF-BB-treated ASMCs. Knockdown of WTAP inhibited the excessive cell viability and migration of ASMCs induced by PDGF-BB. Furthermore, WTAP knockdown increased AXIN1 levels and inhibited the Wnt signalling pathway. Furthermore, WTAP knockdown decreased the m6A levels and enhanced the mRNA stability of AXIN1. WTAP overexpression showed the opposite effect. In addition, YTHDF2 was demonstrated to be the reader that recognizes the WTAP-mediated m6A modification of AXIN1. YTHDF2 knockdown enhanced the mRNA stability of AXIN1 and reversed the effect of WTAP overexpression on PDGF-BB-treated ASMCs. WTAP knockdown inhibited the excessive cell viability and migration of ASMCs by enhancing the m6A levels of AXIN1, which was further recognized by YTHDF2. The upregulation of AXIN1 mediated by the WTAP/YTHDF2 axis further inhibited the Wnt signalling pathway. Our study provides a new method for the treatment of asthma. This work not only deepens our understanding of the molecular underpinnings of asthma but also identifies potential therapeutic targets for the development of novel treatments aimed at inhibiting ASMC proliferation and alleviating asthma symptoms. Show less
📄 PDF DOI: 10.1007/s10528-024-10947-7
AXIN1
Chaoyue Jia, Yanqi Sun, Jianzhong Chen +1 more · 2025 · Physical chemistry chemical physics : PCCP · Royal Society of Chemistry · added 2026-04-24
Alzheimer's disease (AD) is a chronic neurodegenerative disorder predominantly affecting the elderly population. The pathogenesis of AD involves the production of highly neurotoxic amyloid-β peptide 1 Show more
Alzheimer's disease (AD) is a chronic neurodegenerative disorder predominantly affecting the elderly population. The pathogenesis of AD involves the production of highly neurotoxic amyloid-β peptide 1-42 (Aβ Show less
no PDF DOI: 10.1039/d5cp00895f
BACE1
Wenli Zhang, Jinhong Zhu, Mengzhen Zhang +7 more · 2025 · Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · added 2026-04-24
Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings. Previous genome-wide association studies (GWASs) have identified many loci associated with Show more
Neuroblastoma is the most common extracranial solid tumor in children and has complex genetic underpinnings. Previous genome-wide association studies (GWASs) have identified many loci associated with neuroblastoma susceptibility; however, their application in risk prediction for Chinese children has not been systematically explored. This study seeks to enhance neuroblastoma risk prediction by validating these loci and evaluating their performance in polygenic risk models. We validated 35 GWAS-identified neuroblastoma susceptibility loci in a cohort of Chinese children, consisting of 402 neuroblastoma patients and 473 healthy controls. Genotyping these polymorphisms was conducted via the TaqMan method. Univariable and multivariable logistic regression analyses revealed the genetic loci significantly associated with neuroblastoma risk. We constructed polygenic risk models by combining these loci and assessed their predictive performance via area under the curve (AUC) analysis. We also established a polygenic risk scoring (PRS) model for risk prediction by adopting the PLINK method. Fourteen loci, including ten protective polymorphisms from Our findings validate multiple loci as neuroblastoma risk factors in Chinese children and demonstrate the utility of polygenic risk models, particularly the PRS, in improving risk prediction. These results suggest that integrating multiple genetic variants into a PRS can enhance neuroblastoma risk stratification and potentially improve early diagnosis by guiding targeted screening programs for high-risk children. Show less
no PDF DOI: 10.21147/j.issn.1000-9604.2025.01.01
HSD17B12
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
Xian Chen, Sichen Xia, Xue Han +4 more · 2025 · Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · Springer · added 2026-04-24
Cervical cancer incidence in China has risen to 13.83/100,000, particularly affecting younger women. Following recent family policy changes, reproductive concerns among cervical cancer patients have i Show more
Cervical cancer incidence in China has risen to 13.83/100,000, particularly affecting younger women. Following recent family policy changes, reproductive concerns among cervical cancer patients have intensified. While fertility-sparing treatments show good survival rates, many patients still experience significant anxiety about future fertility. This study aims to examine distinct reproductive concern profiles and their influencing factors in cervical cancer patients of childbearing age. We studied 247 patients from a Nanjing tertiary hospital between October 2023 and October 2024. Participants completed surveys including a demographic questionnaire, Reproductive Concerns After Cancer Scale, Patient Health Questionnaire-9, Benefit Finding Scale, and Fear of Cancer Recurrence Scale. Latent profile analysis (LPA) was conducted to identify reproductive concerns. Latent profile analysis revealed three distinct reproductive concern profiles: (1) a low-concern group with reproductive expectations (27.94%), (2) a moderate-concern group with self and child health preoccupations (49.39%), and (3) a high-concern group with impaired reproductive adaptation (22.67%). Significant influencing factors included age, number of children, residential location, depressive symptoms, and fear of cancer recurrence. These cross-sectional findings emphasize the need for careful consideration of individualized, multiple-disciplinary care for young women with cervical cancer. Benefit finding was associated with lower reproductive concerns. Show less
📄 PDF DOI: 10.1007/s00520-025-10125-4
LPA
Jun Teng, Chongwei Duan, Xinyi Zhang +9 more · 2025 · Journal of dairy science · added 2026-04-24
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation tr Show more
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation traits is essential for understanding their genetic basis. In this study, we conducted single-trait and multitrait GWAS for 20 body conformation traits using imputed sequence data in 7,674 Chinese Holstein individuals and identified 27 QTL regions. Leveraging these QTL regions, we performed multitrait Bayesian fine-mapping to identify 30 independent credible sets of putative causal variants. Incorporating GWAS and cis-acting expression QTL data, Mendelian randomization was used to infer 153 putative causal gene-trait relationships. The previously reported genes, such as CCND2, TMTC2, and NRG3, were confirmed in our study. Of note, several novel candidate causal genes were also identified, such as C1R, RIMS1, SERPINB8, NETO2, TTYH3, TTC3, ANAPC4, and PSMD13. Our results provide new insights into the regulatory mechanisms of body conformation traits in cattle. Show less
no PDF DOI: 10.3168/jds.2025-26361
ANAPC4