👤 Zhezhe Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-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, 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
Dan Jiang, Yi-Ling Liu, Jian Liu +7 more · 2026 · Lipids in health and disease · BioMed Central · added 2026-04-24
Calcific aortic valve disease (CAVD) is a cardiovascular disease closely associated with aging. The role of lipoprotein(a) [Lp(a)] has attracted considerable attention in recent years. However, limite Show more
Calcific aortic valve disease (CAVD) is a cardiovascular disease closely associated with aging. The role of lipoprotein(a) [Lp(a)] has attracted considerable attention in recent years. However, limited research has simultaneously explored the relationships between Lp(a), age, and CAVD. This study sought to assess the relationship linking Lp(a), time-weighted Lp(a), and CAVD. A total of 5,156 inpatients with comprehensive clinical data were recruited for this study. The associations of Lp(a) and time-weighted Lp(a) with CAVD were examined via multivariate logistic regression analysis, alongside the application of restricted cubic spline analysis. The diagnostic utility of Lp(a) and time-weighted Lp(a) for CAVD was assessed by constructing receiver operating characteristic (ROC) curves. CAVD prevalence rose with age, whereas the rate of increase diminished with advancing age. The average Lp(a) level in the young populations with CAVD was more than twice that in the No-CAVD group, particularly among those aged 55 years or younger. The prevalence of CAVD in non-elderly populations was markedly 2–4 fold greater in the higher Lp(a) group (> 30 mg/dL) than in the lower Lp(a) group (≤ 30 mg/dL). Multivariate adjusted odds ratios ‌(ORs) for CAVD increased with advancing Lp(a) or age. Time-weighted Lp(a), which takes into account both age and Lp(a), was more strongly linked to elevated CAVD risk than Lp(a) alone. Time-weighted Lp(a) enhanced the diagnostic value of CAVD, improving both sensitivity and specificity. The risk of CAVD is strongly associated with both age and elevated Lp(a) levels. Time-weighted Lp(a), which integrates these factors, serves as a superior indicator that better captures cumulative long-term Lp(a) variation and yields stronger CAVD risk stratification. The online version contains supplementary material available at 10.1186/s12944-026-02884-8. Show less
📄 PDF DOI: 10.1186/s12944-026-02884-8
LPA
Li Zhang, Yuting Wang, Wei Min Gao +8 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Coronary restenosis remains a major challenge following percutaneous coronary intervention (PCI), necessitating the development of effective stent-eluting drugs. Previous studies indicate that scutell Show more
Coronary restenosis remains a major challenge following percutaneous coronary intervention (PCI), necessitating the development of effective stent-eluting drugs. Previous studies indicate that scutellarin protects vascular endothelial cells and exhibits anti-thrombotic and anti-platelet effects. Notably, our prior research demonstrated that scutellarin specifically counteracts oxidative stress-driven endothelial dysfunction, a key initiating event in restenosis. This combined evidence strongly suggests its potential against in-stent restenosis (ISR). Therefore, this study explores the efficacy of scutellarin in preventing ISR after PCI. We investigated scutellarin, derived from Erigeron breviscapus, for its potential to prevent ISR following PCI. The efficacy and mechanism of scutellarin were evaluated using both in vivo and in vitro models. An experimental atherosclerosis model was established in APOE In APOE This study establishes the efficacy of scutellarin in mitigating ISR using two complementary in vivo models. Scutellarin-eluting stents in atherosclerotic minipigs overcome translational barriers through full interventional simulation. Furthermore, scutellarin inhibits VSMCs proliferation, migration and promotes autophagy-coordinated apoptosis by the coordinated downregulation of both the Pl3K/AKT and lKKs/NF-κB cascades.These findings highlight scutellarin as a promising candidate for next-generation bioactive stent coatings, bridging phytopharmacology and precision interventional cardiology. Show less
no PDF DOI: 10.1016/j.phymed.2026.157948
APOE
Zhaoxu Lu, Jin Guo, Yihua Bao +13 more · 2026 · International journal of obesity (2005) · Nature · added 2026-04-24
To use compositional data analysis to examine the associations of daily movement behaviors with body composition, and to predict changes in body composition after reallocating time among behaviors in Show more
To use compositional data analysis to examine the associations of daily movement behaviors with body composition, and to predict changes in body composition after reallocating time among behaviors in preschool-aged children. 268 preschoolers were included in the cross-sectional study. An accelerometer was used to assess sedentary behavior (SB), light and moderate-to-vigorous physical activity (LPA and MVPA). A parental report was used to collect sleep time. Bioelectrical impedance analysis was employed to assess body composition. Compositional linear regression analysis was employed to explore how daily movement behaviors were associated with body composition. Compositional isotemporal substitution analysis was employed to estimate changes in body composition after reallocating time among behaviors. 24-h movement behaviors composition significantly predicted fat-free mass index (FFMI), soft lean mass index (SLMI), and skeletal muscle mass index (SMMI), but not fat mass index, percent body fat, and bone mineral content index. The compositional isotemporal substitution analyses consistently showed that increasing MVPA at the expenses of SB was positively associated with FFMI (+0.328 kg/m The findings highlight the importance of MVPA in improving preschoolers' body composition. Increasing MVPA at the expenses of SB may be a strategy to improve body composition in preschoolers. Show less
📄 PDF DOI: 10.1038/s41366-025-01939-7
LPA
Fang-Kun Yang, Rui Chen, Chen-Hui Zhou +7 more · 2026 · Analytical chemistry · ACS Publications · added 2026-04-24
Atherosclerotic plaque destabilization during acute infections such as pneumonia represents a critical clinical challenge, yet the underlying molecular dynamics remain poorly characterized. This study Show more
Atherosclerotic plaque destabilization during acute infections such as pneumonia represents a critical clinical challenge, yet the underlying molecular dynamics remain poorly characterized. This study introduces a furin-responsive photoacoustic/fluorescence dual-modal probe (FRP) to investigate intraplaque furin activity in ApoE Show less
no PDF DOI: 10.1021/acs.analchem.5c06962
APOE
Chao Chen, Fang Lv · 2026 · British journal of hospital medicine (London, England : 2005) · added 2026-04-24
Lipoprotein(a) [Lp(a)] is recognized as a cardiovascular risk indicator; however, its connection to peripheral arterial disease (PAD) in individuals with type 2 diabetes mellitus (T2DM) is not well es Show more
Lipoprotein(a) [Lp(a)] is recognized as a cardiovascular risk indicator; however, its connection to peripheral arterial disease (PAD) in individuals with type 2 diabetes mellitus (T2DM) is not well established. This research seeks to explore how Lp(a) concentrations relate to the occurrence of PAD in T2DM patients. A retrospective analysis was conducted on 590 patients diagnosed with T2DM who were admitted to Hefei First People's Hospital from January 2022 to August 2024. Participants were grouped into tertiles according to their Lp(a) levels. The diagnosis of PAD was made using the ankle-brachial index (ABI), with an ABI <0.9 considered indicative of PAD. The association between Lp(a) concentrations and PAD was examined using multivariate logistic regression models, subgroup analyses, receiver operating characteristic (ROC) curves, and restricted cubic spline (RCS) plotting. Compared to lower Lp(a) levels, the group with higher Lp(a) levels exhibited a higher prevalence of PAD ( A significant correlation was observed between elevated Lp(a) levels and an increased risk of PAD in patients with T2DM. Show less
no PDF DOI: 10.31083/BJHM50381
LPA
Feng Zhang, Wei Chen, Huiying Wang +10 more · 2026 · Journal of advanced research · Elsevier · added 2026-04-24
Dual GIP/GLP-1 receptor agonists have gained significant attention in clinical applications because of their remarkable efficacy in reducing obesity and type 2 diabetes. However, the mechanisms by whi Show more
Dual GIP/GLP-1 receptor agonists have gained significant attention in clinical applications because of their remarkable efficacy in reducing obesity and type 2 diabetes. However, the mechanisms by which these dual agonists affect systemic metabolism remain elusive. To investigate the effects of a novel dual-receptor agonist, THDBH120, on systemic metabolism in obese individuals and the specific roles of GIPR and GLP-1R in modulating systemic and adipose tissue metabolism. To evaluate the intrinsic properties of THDBH120, we conducted a potency assay by using HEK293 cell lines overexpressing either human GIPR or GLP-1R and measured the accumulation of cAMP as a downstream second messenger following receptor activation. To evaluate the efficacy of THDBH120 on systemic metabolism, we used obese rodents and nonhuman primate species that received various doses and frequencies of THDBH120. To determine the metabolic roles of GLP-1R and GIPR in mediating the beneficial effects of THDBH120, we used GLP-1R- and GIPR-knockout mouse models treated with THDBH120, the GLP-1R agonist semaglutide, or the GIPR agonist LAGIPRA and performed transcriptomic sequencing analyses of adipose tissues. THDBH120 is a novel long-acting dual GIPR/GLP-1R agonist that has superior weight loss and metabolic improvement effects in rodents and mammals. The activation of GLP-1R by semaglutide or THDBH120 improved lipid metabolism, whereas the activation of GIPR by LAGIPRA or THDBH120 alleviated inflammation. THDBH120 improved lipid metabolism via GLP-1R-mediated pathways and mitigated inflammation by activating GIPR-associated pathways in the adipose tissues of obese mice. Both GLP-1R and GIPR are important in mediating the beneficial effects of dual receptors on systemic metabolism. THDBH120 is a novel long-acting dual GIPR/GLP-1R agonist that has potential clinical applications. Show less
no PDF DOI: 10.1016/j.jare.2026.02.006
GIPR
Xiaohua Chen, Huan Liu, Yurong Liu +16 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospect Show more
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospective UK Biobank cohort, we evaluated the bidirectional associations by time-varying Cox proportional hazards regression models and assessed shared genetic architecture using genome-wide association study summary statistics. Additionally, we employed collagen-induced arthritis (CIA) and chronic social defeat stress (CSDS) mouse models to investigate the relationship between rheumatoid arthritis (RA) and depression. Over 5,226,841 person-years of follow-up, 23,534 incident MDD cases were identified. The presence of any IMD was associated with higher MDD risk (hazard ratio [HR]: 1.95; 95% CI: 1.89-2.01). Conversely, 59,742 incident cases of IMD were documented. MDD was associated with increased IMD risk (HR: 1.47; 95% CI: 1.40-1.54). We observed significant global genetic correlations between IMDs and MDD (r Show less
📄 PDF DOI: 10.1038/s41380-026-03459-w
BDNF
Zhongshan Cheng, Sung-Liang Yu, Chih-Hsiang Yu +19 more · 2026 · Scientific reports · Nature · added 2026-04-24
The international consensus classification or the World Health Organization classifications underrepresented driver alterations enriched in pediatric acute myeloid leukemia (AML). To address this, we Show more
The international consensus classification or the World Health Organization classifications underrepresented driver alterations enriched in pediatric acute myeloid leukemia (AML). To address this, we retrospectively characterized the genomic landscape of 105 pediatric patients with AML of East Asian ancestry using transcriptome and whole-exome sequencing (WES). In addition to the common recurrent fusions such as RUNX1::RUNX1T1 and CBFB::MYH11, we identified rearrangements involving KMT2A, NUP98, GLIS, as well as FLT3 and UBTF tandem duplications. The median somatic mutation rate in AML was 0.97 per megabase, as estimated by WES. Frequently mutated pathways included signaling: 68.6% (72/105), transcription: 37.1% (39/105), epigenetic regulation: 26.7% (28/105), cohesin: 7.6% (8/105), RNA binding: 3.8% (4/105), and protein modification: 5.7% (6/105). When analyzed together, high-risk genetic subtypes including GLISr, UBTF tandem duplications, PICALM::MLLT10, and HOXr were significantly associated with poorer 5 year overall survival (OS) in multivariable analysis (p-value = 0.037). Although FLT3 internal tandem duplications were significantly associated with inferior 5 year OS in univariable analysis, this effect was not significant in multivariable analysis (p-value = 0.382). Patients with RUNX1 mutations had inferior 5 year OS in multivariable analysis (p-value = 0.009). These findings suggest specific genomic alterations that may refine risk stratification and guide future therapeutic protocols in Taiwanese pediatric patients with AML. Show less
📄 PDF DOI: 10.1038/s41598-025-34152-7
MLLT10
Gary Chen, Adrienne Sexton · 2026 · Patient education and counseling · Elsevier · added 2026-04-24
This scoping review aims to map the experiences and outcomes of patients and their families undergoing genetic testing and counseling regarding dementia to inform future research directions and clinic Show more
This scoping review aims to map the experiences and outcomes of patients and their families undergoing genetic testing and counseling regarding dementia to inform future research directions and clinical practice. Rigorous scoping review methodology was followed. Ovid Medline, Embase, PsycINFO, and CINAHL were searched with keywords and MeSH terms related to "genetic testing", "genetic counseling", "dementia", "decision making", and "patient outcomes" for peer-reviewed studies with adult participants published over the last ten years. Thirty-six articles met inclusion criteria. Narrative synthesis organized findings into temporal categories including motivations for genetic testing, experiences during the testing/counseling process, and outcomes after testing. Common motivators included reducing uncertainty, reproductive planning, life planning, and the prospect of a treatment becoming available in the future. A lack of current treatments and fear that knowledge of genetic risk would be difficult to cope with were common barriers to testing. Patient-centered communication improved satisfaction. Genetic testing was generally psychologically well tolerated, and a wide range of practical responses were reported including changes to lifestyle, diet, advanced care and financial planning, and engaging in clinical trials. This review maps the experiences and outcomes of genetic testing or counseling for people with or at potentially increased genetic risk of dementia. Genetic testing and counseling for directly causal dementia genes and APOE genotype appears well tolerated but long-term outcome data is lacking. Motivations, concerns and perceived benefits of knowing genetic results vary depending on personal, familial and cultural viewpoints. Genetic counseling can help patients and families prepare, reduce decisional regret, and adapt to results. Motivations varied, and a patient-centered approach addressing both information and psychological aspects improves satisfaction. Future longitudinal research should ascertain ways to support individuals from a wide range of demographics with understanding and adjusting to genetic risk information regarding dementia. Show less
no PDF DOI: 10.1016/j.pec.2025.109424
APOE
Jun An, Sihui Wu, Kexin Guo +4 more · 2026 · American journal of medical genetics. Part A · Wiley · added 2026-04-24
Molecular genetic testing was performed on a fetus with ectrodactyly of the right foot to clarify the pathogenic cause and provide evidence for prenatal counseling. Trio whole-exome sequencing (trio-W Show more
Molecular genetic testing was performed on a fetus with ectrodactyly of the right foot to clarify the pathogenic cause and provide evidence for prenatal counseling. Trio whole-exome sequencing (trio-WES) was performed on the fetus and his parents to identify the underlying genetic cause. Candidate variants were validated by Sanger sequencing, and their molecular effects were analyzed through minigene assays. Trio-WES identified a novel heterozygous variant (c.1977+1G>C) in FGFR1, which is consistent with FGFR1-related Hartsfield syndrome (HS; OMIM#615465). Sanger sequencing confirmed that this variant was de novo. The minigene assay revealed that all variants (c.1977+1G>C, c.1977+1G>A, and c.1977+1G>T) at the splice site generated two aberrant splicing events: (1) complete retention of intron 14, leading to a frameshift and premature termination codon; and (2) skipping of exon 14, causing an in-frame deletion of 41 amino acids. These events collectively impaired the function of the FGFR1 protein's tyrosine kinase domain. To our knowledge, prenatal reports of FGFR1-related HS remain extremely limited, and this is the first molecularly confirmed prenatal diagnosis of HS in China. The findings not only expand the mutational spectrum of HS but also provide genetic counseling and reproductive guidance for this family. Show less
no PDF DOI: 10.1002/ajmg.a.64226
FGFR1
De Xu, Ruijuan Duan, Ruiqi Zhu +2 more · 2026 · Journal of medical biochemistry · added 2026-04-24
To investigate the connection betweenischemic stroke (IS) patients' risk of dying after being discharged and their residual cholesterol (RC) levels uponadmission. 2021 IS patients between the ages of Show more
To investigate the connection betweenischemic stroke (IS) patients' risk of dying after being discharged and their residual cholesterol (RC) levels uponadmission. 2021 IS patients between the ages of 35 and 80were chosen as the study's subjects, and data on deathendpoints following discharge were gathered. The doseresponse association between the risk of death and the RCat admission was examined using restricted cubic spline(RCS) regression. The hazard ratio (HR) and 95% CI werecalculated via Cox regression to analyse the associationbetween the RC level at admission and the risk of deathafter discharge in patients with IS. According to the RCS model, RC levels were nonlinearly associated with deaths from IS and other causes(P<0.001). With the median RC level as the cutoff value,the subjects were divided into two groups: a low RC group(RC<0.72 mmol/L) and a high RC group (RC≥0.72mmol/L). Compared with those in the high RC group, theage and male ratio in the low RC group were significantlygreater. The fasting blood glucose (GLU), total cholesterol(TC), triglyceride (TG), low-density lipoprotein cholesterol(LDL-C), non-high-density lipoprotein cholesterol (nonHDL-C), apolipoprotein A-1 (ApoA-1), and apolipoproteinB (ApoB) levels, as well as diabetes rates, were lower (P=0.01). Cox regression analysis revealed that withoutadjusting for covariates, the high-level RC group presenteda lower risk of all-cause death than the low-level RC group(HR=0.765, 95% CI: 0.619~0.946, P=0.013) and alower risk of death from IS (HR = 0.638, 95% CI:0.435~0.936, P=0.022). After adjusting for sex, age,smoking status, drinking status, hypertension status, anddiabetes status, the high-level group still had a lower risk ofall-cause death (HR = 760, 95% CI: 0.614~0.941,P=0.012) and a lower risk of death from IS (HR=0.653,95% CI: 0.444-0.961, P=0.031). Male sex (HR=0.753,95% CI: 0.572~0.990, P=0.042). Age ≥65 years (HR=0.598, 95% CI: 0.391~0.916, P=0.018), nonsmokingstatus (HR=0.628, 95% CI: 0.408~0.967, P=0.035),nonalcoholic status (HR=0.656, 95% CI: 0.439~0.979,P=0.039), not complicated with hypertension (HR=0.321, 95% CI: 0.108~0.957, P=0.041), no diabetesmellitus (HR=0.607, 95% CI: 0.389~0.947, P=0.028).Compared with those in the high RC group, the IS patientsin the low RC group had a lower incidence of all-causedeath, IS death and other causes of death and a higher survival rate. An RC<0.72 mmol/L at admission is associated with an increased risk of all-cause death and longterm IS death after discharge. Show less
📄 PDF DOI: 10.5937/jomb0-59233
APOB
Tingting Chen, Hongxia He, Fei Huang +3 more · 2026 · PloS one · PLOS · added 2026-04-24
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor Show more
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor (GABAAR) signaling contributes to ICH-induced neurotoxicity, presenting a promising therapeutic target. To assess the neurorestorative effects of the GABAAR α1-selective partial positive allosteric modulator (PAM) CL218872 and the α5-selective negative allosteric modulator (NAM) MRK-016 on synaptic plasticity and neural repair following ICH. An ICH mouse model was constructed using collagenase IV, and ICH mice were administered the GABAAR modulators CL218872 or MRK-016. Differences in inflammation and neurological deficit score were compared between different groups of mice. Morphologic and functional changes in mouse neuronal cells were next determined by Nissl and Golgi-Cox staining. Synaptic structural changes in ICH mice were visualized by transmission electron microscopy, and changes in synaptic plasticity-related molecules were quantified to assess the effects of GABAAR modulators on synapses in ICH mice. Treatment with CL218872 resulted in a reduction in hemorrhage and improved neurobehavioral outcomes in ICH mice. Additionally, CL218872 mitigated inflammation by downregulating phospho-p65, IL-6 and TNF-α expression. Histological analysis revealed an increase in neuronal density, preservation of cell morphology, and enhanced synaptic connectivity following CL218872 treatment. Furthermore, synaptic structure was restored, and there was an upregulation of brain-derived neurotrophic factor (BDNF), growth-associated protein-43 (GAP-43), postsynaptic density protein 95 (PSD-95), and synaptophysin in ICH mice. However, treatment with MRK-016 yielded the opposite result. The GABAAR α1-selective PAM CL218872 exerts neuroprotective and neurorestorative effects in ICH, suggesting its therapeutic potential for ICH management. Show less
📄 PDF DOI: 10.1371/journal.pone.0345025
BDNF
Xiaoqing Wang, Ruisen Chen, Panqin Ye +1 more · 2026 · Behavioral sciences (Basel, Switzerland) · MDPI · added 2026-04-24
This study explores the influence of congruence and incongruence in father-mother co-parenting on adolescent depression, as well as the mediating effect of self-esteem. A total of 1389 adolescents com Show more
This study explores the influence of congruence and incongruence in father-mother co-parenting on adolescent depression, as well as the mediating effect of self-esteem. A total of 1389 adolescents completed questionnaires assessing their levels of depression and self-esteem, while their fathers and mothers correspondingly reported on their own co-parenting behaviors using the Parental Co-parenting Scale in this cross-sectional study. Dates were analyzed using LPA, RSA, and mediation consecutively. The results show that: (1) We identified three distinct co-parenting profiles: positive parental co-parenting, negative parental co-parenting, and mixed parental co-parenting. (2) In cases of congruent parental co-parenting, high positive parental co-parenting was associated with lower adolescent depression, whereas high negative parental co-parenting was linked to higher depression, and the difference manifests in different forms among boys and girls. Girls showed nonlinear changes in depression while boys exhibited linear trends. (3) In cases of incongruence in parental co-parenting, mothers' co-parenting exerted a stronger influence on boys' depression, while girls were not affected by mothers' and fathers' discrepancies. (4) Self-esteem mediated the relationship between parental co-parenting (in)congruence and depression across both genders. This study provides evidence for the mechanism through which parental coparenting influences adolescent depression and offers a basis for future interventions targeting adolescent depression. Show less
📄 PDF DOI: 10.3390/bs16030448
LPA
Ziwei Hu, Jiahui Pang, Xinli Liu +13 more · 2026 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Neuropathic pain (NP), a chronic disorder caused by somatosensory nervous system lesions, severely impairs the quality of life. Microglial metabolic reprogramming and neuroinflammation drive NP progre Show more
Neuropathic pain (NP), a chronic disorder caused by somatosensory nervous system lesions, severely impairs the quality of life. Microglial metabolic reprogramming and neuroinflammation drive NP progression. Although ChREBP (key metabolic regulator) protects against NP, its specific mechanisms remain unclear. NP rat model was established via spared nerve injury (SNI) surgery, and mechanical allodynia was evaluated using Von Frey tests. ChREBP expression in microglia was detected through immunofluorescence, RT-qPCR, and western blot. Functional studies involved ChREBP knockdown/overexpression to assess effects on microglial polarization, neuroinflammation, neuronal excitability, pain behaviors, and fatty acid metabolism. Mechanisms were explored via dual-luciferase reporter and chromatin immunoprecipitation assays. Mechanical pain thresholds were significantly decreased on the ipsilateral side after SNI. ChREBP was upregulated in SDH microglia after SNI and in LPS-stimulated microglia in vitro. ChREBP knockdown inhibited anti-inflammatory microglial polarization, exacerbated neuroinflammation, and aggravated pain. Conversely, ChREBP overexpression promoted the anti-inflammatory phenotype, suppressed neuroinflammation, and alleviated pain. ChREBP enhanced microglial fatty acid oxidation and energy metabolism. Mechanistically, ChREBP bound to the TFBS1 site on the PGC-1α promoter to activate its transcription. PGC-1α overexpression rescued the impairments caused by ChREBP knockdown, including reduced fatty acid oxidation, suppressed anti-inflammatory polarization, elevated inflammatory factors, and increased neuronal excitability. The protective effects of ChREBP were attenuated by the fatty acid oxidation inhibitor Etomoxir. ChREBP alleviates NP by enhancing microglial fatty acid oxidation and anti-inflammatory phenotype via PGC-1α transcriptional activation, revealing a novel metabolic-immune axis for potential NP therapy. Show less
📄 PDF DOI: 10.1002/cns.70744
MLXIPL
Donghui Zhu, Xiuxiu Chen · 2026 · Experimental gerontology · Elsevier · added 2026-04-24
This study aims to explore the shared transcriptomic features of caloric restriction (CR) and endurance exercise in skeletal muscle among older adults. As age increases, muscle atrophy gradually becom Show more
This study aims to explore the shared transcriptomic features of caloric restriction (CR) and endurance exercise in skeletal muscle among older adults. As age increases, muscle atrophy gradually becomes a common issue of functional decline in the elderly. Utilizing bioinformatics analysis, this research identified 101 overlapping differentially expressed genes (DEGs) involved in both CR and endurance exercise. These genes are primarily enriched in key biological pathways related to longevity, Apelin signaling, AMPK signaling, FoxO signaling, and cGMP-PKG signaling pathways. Additionally, we identified 10 key genes (such as LPL, PPARGC1A, and IGF1), 4 transcription factors (FOXC1, POU2F2, GATA2, and STAT3), and 4 microRNAs (miR-155-5p, miR-124-3p, miR-1-3p, and miR-16-5p) interacting with these genes. Drug-gene interaction analysis identified carotuximab as a compound with potential relevance for future investigation in the context of muscle aging. These findings provide new insights into the molecular mechanisms underlying muscle functional decline in the elderly and propose potential targets and drugs for intervention development. Show less
no PDF DOI: 10.1016/j.exger.2026.113083
LPL
Xu Lu, Yan Xu, Jiaxin Liu +1 more · 2026 · Molecular genetics and genomics : MGG · Springer · added 2026-04-24
Diabetic foot ulcers (DFU) are a severe complication of diabetes. Although dysregulated M2 macrophage polarization is recognized as a key driver of chronic inflammation in DFU, the molecular checkpoin Show more
Diabetic foot ulcers (DFU) are a severe complication of diabetes. Although dysregulated M2 macrophage polarization is recognized as a key driver of chronic inflammation in DFU, the molecular checkpoints that can be therapeutically targeted to restore M2 bias remain poorly defined. Here, we aimed to determine whether the RNA-binding protein TAF15 acts as a post-transcriptional stabilizer of the M2-promoting CEBPB/APOE/PTX3 axis, thereby accelerating DFU healing. First, we confirmed that APOE positively regulates PTX3, which supports M2 polarization and the proliferation and migration of HDF. CEBPB transcriptionally activated APOE and promoted M2 macrophage polarization. TAF15 stabilized CEBPB mRNA and affected HDF cell proliferation and migration by promoting M2 macrophage polarization. Additionally, TAF15 overexpression partially counteracted the disruption of M2 macrophage polarization caused by APOE silencing and facilitated DFU wound healing. Collectively, our findings establish TAF15-driven stabilization of CEBPB mRNA as a target point that sequentially activates APOE/PTX3 signaling to enforce M2 polarization and accelerate DFU closure. This study provides a preclinical rationale for the development of TAF15-targeted oligonucleotides or small-molecule strategies to reprogram wound macrophages and improve DFU outcomes in patients with diabetes. Show less
no PDF DOI: 10.1007/s00438-026-02385-4
APOE
Changle Zhao, Xiang Liu, Xi Peng +5 more · 2026 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, usi Show more
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, using a CRISPR/Cas9-mediated Show less
📄 PDF DOI: 10.3390/ani16030405
LPL
Wen Chen, Yue Yang, Shan He +6 more · 2026 · Psychology of sport and exercise · Elsevier · added 2026-04-24
While mindfulness has demonstrated efficacy in enhancing executive function in non-athletes through improved present-moment awareness and acceptance of current experiences, particularly regarding atte Show more
While mindfulness has demonstrated efficacy in enhancing executive function in non-athletes through improved present-moment awareness and acceptance of current experiences, particularly regarding attention regulation and cognitive control, its neurocognitive mechanisms and the effects and underlying mechanisms of mindfulness-based intervention (MBI) on different executive functioning skills in athletic populations remain poorly understood. The purpose of this randomized controlled trial tackles a novel and important topic by investigating the beneficial effects of 12-week MBI on executive functioning skills in baseball players-a population that faces unique cognitive and physical demands, and the associated neurophysiological and biochemical regulation mechanisms. Thirty-four baseball players were randomly divided into the MBI group (11M/6F) and the control group (11M/6F). Executive functioning skills (N-back task for working memory, Stroop task for inhibitory control, and Switching task for cognitive flexibility) were tested before and after the intervention. Functional near-infrared spectroscopy (fNIRS) was used to record quantified hemodynamic responses in the prefrontal cortex through oxygenated hemoglobin concentration (Oxy-Hb) monitoring during the performance of executive function tasks. Biomarkers of cognitive function, including BDNF, IL-6, TNF-α, and Cortisol, were measured using enzyme-linked immunosorbent assays (ELISA). MBI partially improved all three executive function skills, with increased Oxy-Hb level in L-FPA during the task of working memory, increased Oxy-Hb level in R-VLPFC during the task of inhibitory control, and decreased Oxy-Hb level in R-FPA, M-FPA, and L-DLPFC during the task of cognitive flexibility. Furthermore, MBI increased circulating BDNF level and decreased IL-6 and Cortisol levels. In addition, our correlation analyses showed that improvement in executive function (improved behavioral performances and changes in Oxy-Hb levels) were associated with changes in Cortisol and inflammatory cytokines (TNF-α and IL-6). A 12-week MBI partially improved three components of executive function in baseball players. This enhancement may be attributed to the MBI-induced reductions in Cortisol and inflammatory cytokines (such as TNF-α and IL-6), which altered blood oxygen contents in specific brain regions, thereby promoting executive function. Show less
no PDF DOI: 10.1016/j.psychsport.2026.103061
BDNF biomarkers brain oxygenation cognitive function executive function mindfulness neurocognition
Parinaz Massoumzadeh, Savannah Tiemann Powles, Mahshid Naghashzadeh +9 more · 2026 · The British journal of radiology · Oxford University Press · added 2026-04-24
Given the heterogeneous nature of Alzheimer's disease (AD) and its higher prevalence in females, it is crucial to understand sex-related differences in AD presentation and changes in the brain. This s Show more
Given the heterogeneous nature of Alzheimer's disease (AD) and its higher prevalence in females, it is crucial to understand sex-related differences in AD presentation and changes in the brain. This systematic review investigates sex differences in AD and summarizes key findings from neuroimaging studies over the past two decades to examine how genetics, hormones, and lifestyle factors influence neuroimaging biomarkers and their correlation with cognitive decline and AD progression. A comprehensive literature search was conducted across several databases for human studies from 2004 to 2024 related to AD, biological sex differences, and neuroimaging. After a 3-step review process, the final extraction included 120 peer-reviewed studies using various neuroimaging modalities, such as MRI, amyloid-beta PET, tau-PET, and fluorodeoxyglucose (FDG) PET, to investigate sex as a biological predictor variable in adults with or at risk for AD. Over 90% of the reviewed studies identified clear sex-specific patterns of imaging biomarkers related to cognitive reserve, hormonal changes, APOE-ɛ4 genotype, inflammation, vascular health, and lifestyle factors. Machine learning studies increasingly incorporate sex as a key variable, revealing sex-specific biomarkers and improving model performance in predicting disease status and progression. Considering biological sex in AD research is essential for improving diagnostic accuracy, tailoring interventions, and health outcomes. This systematic review identifies sex-specific patterns in neuroimaging biomarkers of AD, influenced by cognitive reserve, hormones, APOE-ɛ4 genotype, inflammation, vascular health, and lifestyle. Recognizing these differences is crucial for understanding, diagnosis, and treatment efficacy. Show less
📄 PDF DOI: 10.1093/bjr/tqag011
APOE
Wei Xia, Nan Shi, Yongjing Lai +12 more · 2026 · Nature communications · Nature · added 2026-04-24
Rodents are widely used in immunology but do not always recapitulate human immune functions. The tree shrew (Tupaia belangeri) is phylogenetically closer to primates than rodents and may help bridge t Show more
Rodents are widely used in immunology but do not always recapitulate human immune functions. The tree shrew (Tupaia belangeri) is phylogenetically closer to primates than rodents and may help bridge this gap, yet its immune system has not been comprehensively characterised at single-cell resolution. Here, we present a single-cell transcriptomic atlas of the tree shrew immune system, profiling 39 cell types across 12 tissues. We uncover human-like tonsillar structures and two transcriptionally distinct splenic macrophage subsets: an NR1H3 Show less
no PDF DOI: 10.1038/s41467-026-71218-0
NR1H3
Ge Lin, Ai-Qiu Chi, Sheng-Yang Cai +12 more · 2026 · Free radical biology & medicine · Elsevier · added 2026-04-24
Scavenger receptor B3/differentiation cluster 36 (SCARB3/CD36) has been established as a fatty acid transporter and genetic deficiency of CD36 in mice models shows decreased uptake of oxidized low-den Show more
Scavenger receptor B3/differentiation cluster 36 (SCARB3/CD36) has been established as a fatty acid transporter and genetic deficiency of CD36 in mice models shows decreased uptake of oxidized low-density lipoprotein (oxLDL) and reduced atherosclerosis. The present study proposes CD36 as a drug target inhibited by leonurine to alleviate inflammation and prohibit unstable atherosclerotic plaques. We showed that the anti-atherosclerotic effects of leonurine were dependent on CD36 in a mice model of arterial atherosclerosis induced by tandem stenosis surgery fed with Western diet (TS + WD) established in both wild type (WT) and Cd36 Show less
no PDF DOI: 10.1016/j.freeradbiomed.2026.03.077
APOE
Yu-Wei Liu, Chi-Jen Wu, Kai-Fu Chang +16 more · 2026 · Journal of Cancer · added 2026-04-24
Obstructive sleep apnea (OSA) is characterized by recurrent intermittent hypoxia (IH) and has been increasingly associated with lung cancer incidence and mortality. However, how IH-related biological Show more
Obstructive sleep apnea (OSA) is characterized by recurrent intermittent hypoxia (IH) and has been increasingly associated with lung cancer incidence and mortality. However, how IH-related biological programs relate to immune remodeling, stemness-associated phenotypes, and therapeutic resistance in lung cancer remains incompletely understood. We integrated single-cell RNA sequencing data from IH-exposed murine lung tissues (GSE301350) with bulk transcriptomic datasets from TCGA-LUAD and GSE31210 to examine hypoxia-associated cellular and transcriptional patterns. Stemness was quantified using CytoTRACE and transcriptome-based stemness scoring, and its associations with immune infiltration, immune checkpoint expression, TIDE scores, predicted drug sensitivity, and immunotherapy response were evaluated. A stemness-based prognostic model was constructed using LASSO Cox regression and validated in independent cohorts. Single-cell analysis revealed marked immune remodeling under intermittent hypoxia (IH), including expansion of effector T cells, and monocytes/macrophages, populations alongside reduced B cells and dendritic cells. In human LUAD cohorts, stemness-high tumors were associated with mitochondrial and metabolic stress-related transcriptional programs, and increased expression of immune checkpoint genes (PD-1, PD-L1, CTLA4, LAG3). Elevated stemness scores correlated with higher TIDE scores, poorer overall survival, and reduced predicted responsiveness to immunotherapy. LASSO modeling identified a six-gene stemness signature (EIF5A, MELTF, SEMA3C, CPS1, TCN1, SELENOK), that consistently stratified patients into high- and low-risk groups across TCGA and GSE31210 cohorts. Multivariate Cox regression confirmed the risk score as an independent prognostic factor. Drug sensitivity analyses further suggested that stemness-high tumors may exhibit increased susceptibility to selected kinase inhibitors (Dasatinib, A-770041) and metabolic modulators (Phenformin, Salubrinal). OSA-associated IH is linked to stemness-associated transcriptional plasticity, immune suppression, and adverse clinical outcomes in lung cancer. The identified stemness-based gene signature provides a robust prognostic biomarker and highlights potential therapeutic vulnerabilities, supporting integrative strategies that combine stemness and immune -targeted approaches with immunotherapy in OSA-associated lung cancer. Show less
📄 PDF DOI: 10.7150/jca.126708
CPS1
Shuang Xiang, Xiaojuan Chen, Jieying Lin +11 more · 2026 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
Alterations in the FGFR family act as oncogenic drivers for multiple pediatric and adult tumors, leading to the development and approval of several FGFR inhibitors. However, the on-target gatekeeper a Show more
Alterations in the FGFR family act as oncogenic drivers for multiple pediatric and adult tumors, leading to the development and approval of several FGFR inhibitors. However, the on-target gatekeeper and "molecular brake" mutations confer clinically acquired resistance to the FDA-approved FGFR inhibitors, which presents a significant unmet medical need. Herein, we report the first novel macrocycle-based FGFR inhibitors targeting both wild-type and clinically acquired variants of the FGFR family. The representative compound Show less
no PDF DOI: 10.1021/acs.jmedchem.5c02462
FGFR1
Dai-Jung Chung, Shao-Peng Chen, Wei-Hsuan Liu +10 more · 2026 · Journal of biomedical science · BioMed Central · added 2026-04-24
Despite therapeutic advances, atherosclerosis remains a major global health challenge. Most current treatments target systemic risk factors rather than the diseased vascular wall. Our previous work id Show more
Despite therapeutic advances, atherosclerosis remains a major global health challenge. Most current treatments target systemic risk factors rather than the diseased vascular wall. Our previous work identified genistein, a soy isoflavone, as a cannabinoid receptor 1 (CB1) antagonist capable of suppressing CB1-mediated vascular inflammation and atherosclerosis. However, its poor water solubility and low oral bioavailability limit clinical application. We aimed to develop water-soluble, orally bioavailable CB1 antagonists for atherosclerosis and to investigate the role of endothelial CB1 in hemodynamic regulation. RNA-sequencing datasets from the NCBI GEO repository were analyzed to assess CB1 expression in atherosclerotic patients. Apolipoprotein E-deficient (Apoe We found CB1 was upregulated in atherosclerotic lesions from patients and mice, and in endothelial cells exposed to disturbed flow. Mechanistically, this was driven by ZNF610 and Spi1 binding and KLF4 dissociation at the CB1 promoter. Daidzein, a soy isoflavone structurally similar to genistein, was identified as a novel CB1 antagonist. To enhance solubility and bioavailability, we developed genistein 7-O-phosphate (G7P) and daidzein 7-O-phosphate (D7P). Pharmacological treatment with these isoflavone monophosphates or genetic CB1 ablation reversed disturbed flow-induced endothelial dysfunction and endothelial-to-mesenchymal transition (EndMT). Oral administration of G7P and D7P significantly reduced atherosclerotic plaque formation in mice. This is the first study to identify transcriptional regulators that drive endothelial CB1 upregulation in response to disturbed flow. We further demonstrated that isoflavone monophosphates ameliorate disturbed flow-induced endothelial dysfunction and EndMT via CB1 inhibition, offering promising oral therapeutics for atherosclerosis. Show less
📄 PDF DOI: 10.1186/s12929-026-01214-5
APOE
Chunlong Wang, Yulong Hu, Junfei Chen +1 more · 2026 · Frontiers in physiology · Frontiers · added 2026-04-24
This study investigated the effects of high-intensity intermittent training (HIIT) Forty male Sprague-Dawley rats were randomly divided into two groups: standard diet (C, n = 10) and high-fat diet (HF Show more
This study investigated the effects of high-intensity intermittent training (HIIT) Forty male Sprague-Dawley rats were randomly divided into two groups: standard diet (C, n = 10) and high-fat diet (HFD, n = 30). After 8 weeks of HFD feeding, 24 obese rats were further randomised into three subgroups: HFD (H, n = 8), HFD + moderate-intensity training (HMT, n = 8), and HFD + HIIT (HHT, n = 8). The HMT and HHT groups underwent 8 week training interventions (six sessions/week). The HMT protocol included a 10 min warm-up (treadmill speed: 10 m/min), a 40 min moderate-intensity aerobic phase (60%-70% of maximum speed), and a 10 min recovery (10 m/min). The HHT protocol featured 10 min warm-up and recovery phases (10 m/min), with 40 min of alternating treadmill training: 3 min at 50% maximum speed followed by 3 min at 90% maximum speed. No significant differences in body weight were observed between the HHT and HMT groups. HHT rats displayed significantly lower plasma triglyceride levels than H and HMT rats. Compared with HMT, HHT reduced adipose mass and adipocyte size and increased mitochondrial succinate dehydrogenase and cytochrome c oxidase (COX) activities in adipose tissue. However, HHT rats displayed lower COX activity in visceral white adipose tissue than HMT rats. Training upregulated browning-related genes and uncoupling protein 1 (UCP1) in adipose tissue, with stronger effects in HHT than in HMT. Plasma and adipose tissue IL-27 levels, as well as p38 MAPK-PGC-1α signalling pathway activation, were significantly elevated in both training groups, with greater increases in HHT. HIIT promotes adipose tissue browning by activating the IL-27 signalling pathway and ameliorates obesity-associated metabolic disorders more effectively than MAIT, supporting its potential as a therapeutic strategy for obesity. Show less
📄 PDF DOI: 10.3389/fphys.2026.1745363
IL27
Ya Wang, Jinyi Fu, Jingyi Zhan +7 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Atherosclerosis (AS) is a central pathological driver underlying most cardiovascular diseases. Gut microbiota and related metabolites participate in regulating atherosclerosis. Fifty C57BL/6J ApoE Ath Show more
Atherosclerosis (AS) is a central pathological driver underlying most cardiovascular diseases. Gut microbiota and related metabolites participate in regulating atherosclerosis. Fifty C57BL/6J ApoE Atherosclerotic plaques accumulated in the aorta and aortic sinus after HFD, while statin and high-dose GP alleviated this burden. TC, TG, LDL-C, MCP-1, MCP-3 and IL-2 showed significant increase after HFD, while statin and GP decreased LDL-C, MCP-1 and MCP-3. The goblet cells, ZO-1 and Occludin decreased after HFD, while statin and GP increased them, indicating that the intestinal barrier integrity was improved. Additionally, the composition of gut microbiota was modulated by GP. Some candidate taxa were identified, such as This study suggests that GP is beneficial for alleviating atherosclerosis in HFD-induced ApoE Show less
📄 PDF DOI: 10.3389/fcvm.2026.1773819
APOE
Yifan Wu, Chijia Wang, Yu Zhou +6 more · 2026 · Journal of biomedical materials research. Part B, Applied biomaterials · Wiley · added 2026-04-24
Improving the patency rate of small-diameter vascular grafts in a pathological environment is the key to achieving their clinical translation and application. The current approach to in vivo implantat Show more
Improving the patency rate of small-diameter vascular grafts in a pathological environment is the key to achieving their clinical translation and application. The current approach to in vivo implantation evaluations of small-diameter vascular grafts is predominantly based on healthy animal models. However, the majority of patients who undergo vascular transplantation are afflicted with vascular diseases, such as hyperlipidaemia or atherosclerosis. In this study, we constructed an ApoE gene knockout atherosclerotic mouse model and investigated the patency and regenerative performance of small-diameter vascular grafts in a diseased environment. We prepared heparinized Poly (ε-caprolactone) (PCL) vascular grafts (PCL-Hep) using electrospinning technology. By taking advantage of the physical adsorption of heparin, rapamycin (RM) was loaded onto the surface of grafts to obtain PCL-Hep-RM vascular grafts, which exhibited exceptional mechanical properties and drug sustained-release characteristics. Subsequently, the PCL-Hep-RM vascular grafts were implanted into the carotid arteries of atherosclerotic mice. The results demonstrated that PCL-Hep-RM significantly enhanced the patency rate and suppressed intimal hyperplasia in comparison with the PCL control group. This study offers novel concepts and methodologies for addressing challenges such as the low long-term patency rate and luminal stenosis of vascular grafts in a diseased environment, thereby promoting the translational medicine research of small-diameter vascular grafts. Show less
no PDF DOI: 10.1002/jbm.b.70041
APOE
Ye Yang, Anne P Beigneux, Troy L Lowe +21 more · 2026 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Apolipoprotein AV (APOA5) regulates intravascular triglyceride metabolism by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its ability to unfold the native conformat Show more
Apolipoprotein AV (APOA5) regulates intravascular triglyceride metabolism by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its ability to unfold the native conformation of lipoprotein lipase (LPL). LPL unfolding results in loss of catalytic activity and the detachment of LPL from the surface of cells. An Show less
no PDF DOI: 10.1073/pnas.2528664123
APOA5
Dehao Yang, Shiyue Wang, Yangguang Lu +8 more · 2026 · Alzheimer's research & therapy · BioMed Central · added 2026-04-24
The clinical interpretation of Alzheimer's disease (AD) is frequently complicated by the prevalence of missense variants designated as being of uncertain significance within associated genes. Conventi Show more
The clinical interpretation of Alzheimer's disease (AD) is frequently complicated by the prevalence of missense variants designated as being of uncertain significance within associated genes. Conventional computational prediction tools often overlook disease-specific pathophysiological contexts and lack pertinence and interpretability. Therefore, the present study aimed to develop a novel, interpretable framework for predicting the pathogenicity of AD missense variants by integrating transcriptomic and proteomic data enrichment patterns with machine learning methods. A cross-sectional variant-level analysis was performed using publicly available databases. Missense variants in APOE, APP, PSEN1, PSEN2, SORL1, and TREM2 reported in AD patients were retrieved from Alzforum and compared with missense variants from individuals without neurological diseases, as cataloged in the gnomAD v2.1.1 non-neuro subset. Variants were annotated with tissue-specific expression, secondary structure, relative solvent accessibility, and other functional features using tools like AlphaFold. Enrichment of specific features was assessed with Fisher's exact tests with Bonferroni correction for multiple comparisons. Given that PSEN1 showed the strongest enrichment signals, six machine-learning algorithms were trained on PSEN1 variants to distinguish AD-associated variants from gnomAD variants, using a 10 × 5 nested cross-validation scheme. External validation was conducted using PSEN1 missense variants from ClinVar annotated as pathogenic/likely pathogenic or benign/likely benign. Model performance was compared with SIFT and PolyPhen-2, and interpretability was evaluated by feature ablation and SHapley Additive exPlanations analyses. AD-associated variants exhibited statistically significant enrichment within some transcriptomic or proteomic features, with PSEN1 contributing significantly to the enrichment observed across these features. Random forest and gradient boosting models achieved high performance in the internal training dataset and maintained high recall in the external validation dataset, outperforming SIFT and approaching the performance of PolyPhen-2. Relative solvent accessibility was the most discriminative individual feature, while regional and topological features provided complementary discriminative power. This integrative, multi-omics framework links disease-specific enrichment patterns with interpretable gene-level machine learning for AD missense variants. The results highlight the importance of expression level, structural context, etc. for PSEN1 variant pathogenicity and may help prioritize variants for functional studies. Further validation in additional genes and independent cohorts is warranted prior to any clinical application. Show less
📄 PDF DOI: 10.1186/s13195-025-01950-0
APOE
Mei Li, Zeqing Xu, Jiarui Zeng +6 more · 2026 · International journal of medical microbiology : IJMM · Elsevier · added 2026-04-24
Staphylococcus aureus is a significant pathogen that poses a threat to both human and animal health. Its pathogenicity in humans has been extensively studied, however, the signaling pathways and key g Show more
Staphylococcus aureus is a significant pathogen that poses a threat to both human and animal health. Its pathogenicity in humans has been extensively studied, however, the signaling pathways and key genes in Koi Carp responding to S. aureus from human rhinitis remain unclear. In this study, we established an intraperitoneal infection model in koi carp (Cyprinus carpio) using an S. aureus isolate from patients with rhinitis and integrated RNA-seq, qPCR, and ELISA to dissect the host response. Our findings reveal a dual-module immune evasion strategy employed by S. aureus in koi carp. Module I: The pathogen down-regulated the entire complement coagulation cascade (C3, C9, CFH, F7/9/10) and apolipoprotein-mediated opsonins (APOA1, APOB, APOC1/2), thereby crippling innate clearance. Module II: The host mounted a restricted but potent counter-response, characterized by type I IFN signalling (gvin1, MHC-I), NK/T-cell co-stimulation (CD244, SLAMF5), and the selective induction of IL-8 and IL-1β, while IL-6, IL-10, and TNF-α remained unchanged. Functionally, serum superoxide dismutase (SOD), catalase (CAT), and lysozyme (LZM) activities surged, confirming an oxidative burst, whereas splenic CD22R protein decreased, indicating B-cell disinhibition. These results establish a molecular basis for understanding the interaction between human-derived S. aureus and the immune system of aquatic organisms. Show less
no PDF DOI: 10.1016/j.ijmm.2026.151707
APOB