👤 Minjie 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, 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
Xinchao Guan, Tao Liu, Sili Chen +4 more · 2026 · The Journal of biological chemistry · Elsevier · added 2026-04-24
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to c Show more
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to cancer progression remain poorly understood. Here, we identified a lung cancer-specific chimeric RNA KANSL1-ARL17A (chKANSARL) and its circular variant fusion circular RNA KANSL1-ARL17 A (F-circKA), both derived from the fusion gene KANSARL. Functional assays revealed that overexpression of either chKANSARL or F-circKA significantly enhanced lung cancer cell proliferation, migration, and invasion, while their knockdown suppressed these malignant phenotypes. In vivo experiments demonstrated that chKANSARL overexpression accelerated tumor growth in immunodeficient mice. Notably, coexpression experiments uncovered a synergistic regulatory interaction between F-circKA and chKANSARL, amplifying oncogenic effects. Mechanistically, miRNA sequencing and dual-luciferase assays revealed that F-circKA acts as a molecular sponge for miR-6860, thereby derepressing chKANSARL expression. Rescue experiments further validated this regulatory axis, wherein miR-6860 inhibition reversed the tumor-suppressive effects of F-circKA knockdown. Collectively, our study identifies and characterizes a novel F-circKA/miR-6860/chKANSARL regulatory axis, revealing how dual transcriptional outputs from the KANSARL fusion gene can synergistically drive lung cancer progression. These findings highlight a previously unrecognized layer of cooperative regulation between linear and circular fusion RNAs in oncogenesis and provide a new framework for understanding fusion gene-mediated tumorigenesis. Show less
📄 PDF DOI: 10.1016/j.jbc.2026.111170
KANSL1
Huan Huang, Zhaojun Chen, Jiong Liu +4 more · 2026 · Journal of epidemiology and community health · added 2026-04-24
Older adults typically have higher sedentary behaviour (SB) and lower physical activity (PA) than younger adults. Studies on replacing SB with PA in relation to all-cause mortality in racially diverse Show more
Older adults typically have higher sedentary behaviour (SB) and lower physical activity (PA) than younger adults. Studies on replacing SB with PA in relation to all-cause mortality in racially diverse older adults remain limited. This study included 122 966 older adults from the China Kadoorie Biobank (CKB) and 207 212 older adults from the UK Biobank (UKB). SB and PA were assessed using baseline questionnaires, with PA classified as light (LPA), moderate (MPA) or vigorous (VPA) based on metabolic equivalents. Cox proportional hazards models and isotemporal substitution models were used to examine the associations between replacing SB with different PA intensities and all-cause mortality. Longer SB (per 30 min/day increase) was associated with a higher risk of all-cause mortality in both cohorts (CKB: HR 1.013, 95% CI 1.010 to 1.017; UKB: HR 1.012, 95% CI 1.009 to 1.015). PA of any intensity was associated with a reduced risk of all-cause mortality. In the CKB, replacing 30 min/day of SB with an equivalent duration of PA showed comparable protective associations (LPA: HR 0.963, 95% CI 0.958 to 0.968; MPA: HR 0.967, 95% CI 0.961 to 0.972; VPA: HR 0.965, 95% CI 0.960 to 0.971). In the UKB, replacing 30 min/day of SB with VPA was associated with the largest reduction in mortality risk (HR: 0.950, 95% CI 0.931 to 0.970). Replacing SB with PA of any intensity was associated with reduced all-cause mortality risk in older adults, with variations across populations. These findings highlight the need for population-specific PA recommendations to promote healthy ageing. Show less
no PDF DOI: 10.1136/jech-2025-225695
LPA
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
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
Bin Ma, Jingjing Wang, Mengyuan Zhang +2 more · 2026 · BMC nursing · BioMed Central · added 2026-04-24
To evaluate the current status and latent profiles of caregiver self-care contributions for patients with chronic obstructive pulmonary disease (COPD) and examine the associations between demographic Show more
To evaluate the current status and latent profiles of caregiver self-care contributions for patients with chronic obstructive pulmonary disease (COPD) and examine the associations between demographic characteristics, health literacy, confidence in self-care contributions, family intimacy, and profile membership. We recruited 275 dyads of patients with COPD and their family caregivers from five tertiary hospitals between May and November 2022 using convenience sampling. Latent profile analysis (LPA) was used to identify distinct profiles of caregiver self-care contributions. Univariate analysis and multinomial logistic regression were subsequently conducted to examine associations between participant characteristics and profile membership. LPA identified four distinct profiles of caregiver self-care contributions: low-contributing, under-monitored, maintenance-prioritized, and high-contributing. Significant differences were observed across these profiles in terms of patients' symptom severity, exacerbation frequency, number of hospitalizations, caregivers' education levels, caregiving duration, health literacy, confidence in self-management contributions, and family intimacy using univariate analysis. Multinomial logistic regression analysis revealed that caregivers' education levels, caregiving duration, confidence in self-management contributions, and health literacy were significant predictors of profile membership. Caregiver self-care contributions for patients with COPD can be characterized by four distinct profiles, with caregivers' educational level, health literacy, and confidence in self-management identified as key factors associated with profile membership. Show less
📄 PDF DOI: 10.1186/s12912-026-04503-4
LPA
Jihai Chen, Nuo Cheng, Ye Liu +4 more · 2026 · Rejuvenation research · SAGE Publications · added 2026-04-24
Agrin-mediated neuromuscular junction (NMJ) morphological alterations is one of the main pathogeneses of sarcopenia. The aim of this study was to observe the changes in serum agrin in patients with di Show more
Agrin-mediated neuromuscular junction (NMJ) morphological alterations is one of the main pathogeneses of sarcopenia. The aim of this study was to observe the changes in serum agrin in patients with different degrees of sarcopenia and the alterations in Agrin receptors in human skeletal muscle with age. A total of 236 elderly subjects were enrolled and categorized into nonsarcopenia, possible sarcopenia, sarcopenia, and severe sarcopenia groups. Serum levels of the C-terminal Agrin fragment were quantified using an Enzyme-Linked Immunosorbent Assay (ELISA) kit. In addition, in a distinct and smaller exploratory subgroup ( Show less
no PDF DOI: 10.1177/15491684251410100
RAPSN
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
Yayu Wang, Kai Li, Wei Chen +6 more · 2026 · Neuron · Elsevier · added 2026-04-24
Neurodegenerative diseases, which pose significant challenges for effective treatment, often involve risk variants of lysosomal gene products that disrupt lysosomal function, leading to the accumulati Show more
Neurodegenerative diseases, which pose significant challenges for effective treatment, often involve risk variants of lysosomal gene products that disrupt lysosomal function, leading to the accumulation of indigestible materials and damage to brain cells. The lysosome is a degradative organelle and a signaling hub that senses nutrient availability. How lysosomal dysfunction contributes to neurodegenerative diseases is an important open question. In this study, we identified CLN3 (ceroid lipofuscinosis, neuronal 3), an endolysosomal protein that is linked to Batten disease, as an evolutionarily conserved protein that facilitates lysosomal chloride efflux. Additionally, we report that a natural compound with anti-inflammatory properties-the curcumin analog C1, which is a TFEB (transcription factor EB) activator-could enhance CLN3 activity and improve lysosomal function. These findings provide new insight into the role of CLN3 in lysosomal ion homeostasis and raise the possibility that modulation of the TFEB-CLN3 signaling axis may hold therapeutic potential for lysosomal storage disorders. Show less
📄 PDF DOI: 10.1016/j.neuron.2025.11.013
CLN3
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
Yuehan Wang, Junming Chen, Hua Yu +3 more · 2026 · Molecular nutrition & food research · Wiley · added 2026-04-24
Portulaca oleracea L. (purslane) is a widely cultivated herb with edible and medicinal value. Modern pharmacological studies have shown that purslane has potent anti-inflammatory effects. However, its Show more
Portulaca oleracea L. (purslane) is a widely cultivated herb with edible and medicinal value. Modern pharmacological studies have shown that purslane has potent anti-inflammatory effects. However, its potential role in ameliorating atherosclerosis remains unclear. This study aimed to investigate the efficacy of purslane extract in ameliorating atherosclerosis in apolipoprotein E(ApoE) knock-out (ApoE Show less
📄 PDF DOI: 10.1002/mnfr.70449
APOE
Jing Zhou, Benjamin H Wang, Jiangning Yu +9 more · 2026 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Post-stroke seizures are a common and debilitating complication with limited therapeutic options, underscoring the need to identify novel molecular targets. Disruption of chloride homeostasis via impa Show more
Post-stroke seizures are a common and debilitating complication with limited therapeutic options, underscoring the need to identify novel molecular targets. Disruption of chloride homeostasis via impaired potassium chloride cotransporter 2 (KCC2) activity is a key driver of neuronal hyperexcitability. While microglia are a predominant source of brain-derived neurotrophic factor (BDNF) in the acute phase after brain injury, the role of microglial BDNF and its signaling in KCC2 dysregulation and early post-stroke seizure susceptibility remain poorly defined. Using a middle cerebral artery occlusion-reperfusion (MCAO-R) mouse model and oxygen-glucose deprivation/reoxygenation (OGD/R) in hippocampal neurons, we assessed KCC2 function, neuronal excitability, and seizure susceptibility. Pharmacological tools, including the microglial inhibitor minocycline, the TrkB antagonist K252a, the loop diuretic furosemide (FUR), repurposed here as a KCC2-stabilizing agent, and the KCC2 activator CLP290, were employed. Techniques included immunofluorescence, Western blotting, patch-clamp electrophysiology, electroencephalography (EEG), and behavioral seizure assessment. MCAO-R and OGD/R significantly reduced membrane KCC2 expression, leading to a depolarizing shift in the GABA equilibrium potentials (E Our findings identify microglia-derived BDNF/TrkB signaling as a critical upstream pathway mediating KCC2 dysfunction in early post-stroke seizure. Targeting this axis by inhibiting microglial activation, blocking TrkB, or directly enhancing KCC2 function with activators like CLP290 represents a promising therapeutic strategy for stroke-related epilepsy. Show less
📄 PDF DOI: 10.1002/cns.70795
BDNF
Na Li, Keying Chen, Bin Nie +14 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Depression has emerged as a concerning factor in colon cancer progression and treatment, yet its underlying mechanisms and therapeutic targets remain poorly defined. This study aimed to elucidate how Show more
Depression has emerged as a concerning factor in colon cancer progression and treatment, yet its underlying mechanisms and therapeutic targets remain poorly defined. This study aimed to elucidate how depression affects colon cancer progression and chemotherapeutic response, and to explore potential molecular targets and therapeutic interventions involving the traditional Chinese medicine formula Sinisan (SNS) and its bioactive component Quercetin. A mouse model combining depression and colon cancer was established to evaluate behavioral alterations, tumor progression, and pathological features. RNA sequencing was performed to screen the differentially expressed genes. The effects of corticosterone (CORT) on proliferation, colony formation, migration, and GSTM2 expression were examined in HCT116 cells, followed by functional validation through GSTM2 overexpression and inhibition assays. Molecular docking, molecular dynamics simulations, and surface plasmon resonance (SPR) were used to validate the binding of Quercetin to GSTM2. The therapeutic efficacy of SNS and Quercetin was assessed with respect to depressive symptoms, serum BDNF levels, NLRP3 inflammasome activity, and the potency of 5-fluorouracil (5-FU) chemotherapy. Mice with depression and colon cancer exhibited aggravated depressive behaviors and accelerated tumor progression. RNA-sequencing and network pharmacology analyses identified GSTM2 as a promising candidate target in colon cancer treatment, which was markedly down-regulated in the DP-CC group. CORT enhanced proliferation, colony formation, and migration of HCT116 cells while simultaneously suppressing GSTM2 expression. Conversely, GSTM2 levels negatively correlated with cell proliferation, colony formation, and chemoresistance in HCT116 cells. Treatment with SNS alleviated depressive symptoms, elevated serum BDNF, reduced NLRP3 inflammasome activity, and potentiated the efficacy of 5-FU chemotherapy. Quercetin, a bioactive component of SNS, bound to GSTM2 through hydrogen-bond and van-der-Waals interactions, up-regulated GSTM2 expression, and mitigated CORT-induced proliferation, colony formation, and chemoresistance. Our findings suggest that depression promotes colon-cancer progression by down-regulating GSTM2, whereas SNS restores GSTM2 expression and enhances chemotherapeutic response. Show less
no PDF DOI: 10.1016/j.phymed.2026.158113
BDNF cancer progression chemoresistance chemotherapy colon cancer depression gst
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
Yuecong Wang, Xin Wang, Chengcai Wen +6 more · 2026 · Frontiers in public health · Frontiers · added 2026-04-24
Occupational stress in nursing is a critical issue that can have significant implications for both workforce stability and personal health. This study aimed to identify subgroups of occupational stres Show more
Occupational stress in nursing is a critical issue that can have significant implications for both workforce stability and personal health. This study aimed to identify subgroups of occupational stress among Chinese female clinical nurses using latent profile analysis, compare sociodemographic differences across these subgroups, and examine their associations with premenstrual syndrome (PMS). A cross-sectional study was conducted among female nurses in tertiary hospitals in Huai'an City, Jiangsu Province, China, from November to December 2023. We recruited participants via convenience sampling, and 400 valid questionnaires were collected. Data were collected using a researcher-developed general information questionnaire, the standardized Chinese Nurses Stressor Scale (35 items), and the Premenstrual Syndrome Scale. Latent profile analysis (LPA) was performed with Mplus 8.0 to identify occupational stress subtypes. Sociodemographic predictors of these subtypes were explored using chi-square tests and multivariate logistic regression in SPSS 25.0. The association between stress subtypes and PMS symptoms was assessed using ANOVA. A Three clinical female nurse occupational stress subtypes were identified: overall low-stress (38.3%, This study identified significant heterogeneity in occupational stress among clinical female nurses, categorized into three distinct subtypes differing in stress levels and demographic characteristics. These findings highlight the importance of considering individual differences when developing interventions to address occupational stress. The study advocates for the implementation of intervention strategies targeting different types of stress in nursing education and organizational reform to better support nurses in fulfilling their responsibilities. Show less
📄 PDF DOI: 10.3389/fpubh.2026.1683290
LPA
Qianru Zhang, Mirenuer Aikebaier, Yefan Hu +5 more · 2026 · Biochemical pharmacology · Elsevier · added 2026-04-24
Atherosclerosis is a chronic and progressive inflammatory disease that can lead to adverse cardiovascular and cerebrovascular events. Phenotypic switching of vascular smooth muscle cells (VSMCs) plays Show more
Atherosclerosis is a chronic and progressive inflammatory disease that can lead to adverse cardiovascular and cerebrovascular events. Phenotypic switching of vascular smooth muscle cells (VSMCs) plays a pivotal role in its development and progression, but the upstream regulatory mechanisms remain incompletely defined. Here, we identify ubiquitin-fold modifier 1 (UFM1), a ubiquitin-like protein, as a critical regulator of VSMCs plasticity and atherogenesis. In VSMCs stimulated with oxidized low-density lipoprotein (ox-LDL), UFM1 overexpression markedly attenuated phenotypic switching, restoring contractile features and suppressing synthetic activation, accompanied by reduced proliferation and migration. In contrast, UFM1 knockdown further exacerbated these phenotypic alterations. In ApoE Show less
no PDF DOI: 10.1016/j.bcp.2026.117957
APOE
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
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
Yongmei Wu, Wenjing Xia, Yang Yang +18 more · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroup Show more
Anxiety and depression are highly comorbid mental health disorders with heterogeneous symptom patterns and poorly understood transdiagnostic mechanisms. This study aims to characterize latent subgroups, risk factors, and symptom-level interactions underlying depression-anxiety comorbidity across adolescents and adults in multi-ethnic Southwest China. The study included a total of 41,394 adolescents (aged 9-19) and 17,345 adults (aged 18-80). Adolescents were recruited using multistage stratified cluster sampling, whereas adults were recruited by convenience sampling. All participants completed a self-designed sociodemographic questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7). Latent profile analysis identified subgroups, logistic regression analyzed risk/protective factors, and network analysis mapped symptom interactions and bridge nodes. This study found that three adolescent profiles emerged: high (11.66 %), moderate (31.95 %), and low/no depression-anxiety (56.39 %). Adults were classified into low/no comorbidity (90.63 %) and comorbid depression-anxiety (9.37 %). Risk factors for adolescents included female gender (OR = 2.77, 95 %CI: 2.55-3.00; OR = 1.59, 95 %CI: 1.52-1.67), higher grade levels (OR = 3.45, 95 %CI: 3.10-3.84; OR = 3.56, 95 %CI: 3.33-3.80), smoking (OR = 1.72, 95 %CI: 1.51-1.96; OR = 1.28, 95 %CI: 1.17-1.41),drinking (OR = 2.45, 95 %CI: 2.23-2.70; OR = 1.66, 95 %CI: 1.55-1.77), family instability (OR = 1.16, 95 %CI: 1.02-1.31; OR = 1.33, 95 %CI: 1.14-1.56) and "other" ethnic minority (OR = 1.15, 95 %CI: 1.04-1.26). For adults, female gender(OR = 1.68; 95 %CI: 1.44-1.97), living alone(OR = 1.37; 95 %CI: 1.14-1.65), poor self-rated health (OR = 0.13, 95 %CI: 0.11-0.15), and Dai ethnicity (OR = 0.70, 95 %CI: 0.49-0.96) predicted comorbidity. Network analysis revealed distinct bridge symptoms: adolescents in the high depression-anxiety group had five symptoms: depressed or sad mood (phq2), psychomotor agitation/retardation (phq8), nervousness or anxiety (gad1), restlessness (gad5), and irritable (gad6); however, adults with comorbidity had one symptom: afraid something will happen (gad7). This study identified three patterns of depression-anxiety comorbidity in adolescents and two in adults. Efforts should prioritize adolescents from "other" ethnic minorities, strengthening family and peer support, as well as smoking and drinking interventions for adolescents, and addressing social isolation, physical health, and catastrophizing cognition in adults may mitigate the comorbidity burden. Show less
no PDF DOI: 10.1016/j.jad.2025.121112
LPA
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
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
Yixuan Yuan, Yujie Xiao, Jie Zou +15 more · 2026 · Nature communications · Nature · added 2026-04-24
Hypertrophic scar (HS) is a fibroproliferative disorder characterized by fibroblast hyperactivation and aberrant extracellular matrix deposition. This study identifies macrophage-derived lactate as a Show more
Hypertrophic scar (HS) is a fibroproliferative disorder characterized by fibroblast hyperactivation and aberrant extracellular matrix deposition. This study identifies macrophage-derived lactate as a key mediator of fibroblast phenotypic remodeling via monocarboxylate transporter 1 (MCT1)-mediated histone H3 lysine 23 lactylation (H3K23la) in HS. Elevated lactate levels and MCT1 expression were observed in HS tissues, with macrophages in stiff mechanical microenvironments identified as the primary lactate source. Lactate influx through MCT1 upregulated H3K23la, thereby promoting transcriptional activation of profibrotic genes HEY2 and COL11A1. Mechanistically, HEY2 activated YAP1/SMAD2 signaling, while COL11A1 stabilized MCT1 to enhance lactate transport, forming a positive loop that amplified fibrosis. Fibroblast-specific Mct1 deletion or pharmacological inhibition of Mct1 in male mice reduced collagen deposition, accelerated wound healing, and attenuated scar formation. Our findings redefine the macrophage-fibroblast crosstalk in HS and establish the MCT1-H3K23la-HEY2/COL11A1 axis, particularly its self-reinforcing loop, as a novel therapeutic target. Show less
📄 PDF DOI: 10.1038/s41467-026-69388-y
HEY2
Meimei Chen, Ruina Huang, Zhaoyang Yang · 2026 · Nan fang yi ke da xue xue bao = Journal of Southern Medical University · added 2026-04-24
To investigate the causal relationship between inflammatory proteins and Alzheimer's disease (AD) and the mediating role of plasma metabolites therein. Using Mendelian mandomization (MR) methods and p Show more
To investigate the causal relationship between inflammatory proteins and Alzheimer's disease (AD) and the mediating role of plasma metabolites therein. Using Mendelian mandomization (MR) methods and publicly available genome-wide association study (GWAS) data, we selected 91 single nucleotide polymorphisms (SNPs) that were strongly linked to inflammatory proteins without reverse causality with AD as the outcome. A bidirectional two-sample MR analysis was performed. Inflammatory proteins with causal links to AD were identified via inverse variance weighted (IVW) analysis. A mediation MR analysis was then performed using 1400 plasma metabolites to assess their mediating role in this causal pathway. The preliminary bidirectional MR analysis identified 3 inflammatory proteins that had a potential positive causal association with AD without reverse causality: Axin-1, C-X-C motif chemokine ligand 11 (CXCL11), and interleukin-12β (IL-12β). Elevated levels of Axin-1 were positively causally associated with AD risk (OR=1.082, 95% This study reveals how specific inflammatory proteins influence AD risk via plasma metabolites and provides genetic evidence for inflammatory-metabolic interactions in AD to facilitate the identification of potential biomarkers and targets for early detection and intervention of AD. Show less
no PDF DOI: 10.12122/j.issn.1673-4254.2026.02.05
AXIN1
Linhui Zhai, Cui-Cui Liu, Lei Zhao +14 more · 2026 · Protein & cell · Oxford University Press · added 2026-04-24
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune s Show more
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune sites like lymph nodes remain elusive. Here, we performed an in-depth proteomic and phosphoproteomic analysis of a substantial series of breast cancer samples, alongside genomic and transcriptomic evaluations. This cohort encompasses 195 specimens: 65 primary breast tumors, their corresponding normal tissues, and metastatic axillary lymph nodes. We offer an overview of the molecular alterations at the transcriptomic, proteomic, and phosphoproteomic levels during lymph node metastasis. Notably, the findings indicate that regional lymph node metastasis is primarily influenced by proteomic and phosphoproteomic alterations, rather than genomic or transcriptomic changes. We found the ANGPTL4 and HMGB1 could serve as the biomarker of lymph node metastasis. Data analysis and cell experiments involving silencing of the alternative splicing factor HNRNPU demonstrated that alternative splicing plays a significant role in modulating protein expression, phosphorylation profiles and cell proliferation. The key phosphorylation sites, including MARCKSL1-S104 and FKBP15-S320, as well as the upstream kinase PRKCB, were identified as playing crucial roles in breast cancer lymph node metastasis. Targeted intervention of the kinase PRKCB resulted in effectively suppressing the proliferation and metastasis of breast cancer tumor cells. Immune profiling analysis and experimental validation of breast cancer cell cocultured with CD8+ T cell reveals correlations between phosphorylation of MARCKSL1-S104 and FKBP15-S320 with immune checkpoint PD-L1 expression, and their impact on tumor cell apoptosis, suggesting a potential mechanism of immune evasion in metastasis. This study systematically characterizes the molecular landscape and features of primary breast tumors and their matched metastatic lymph nodes. These insights enhance our understanding of early-stage breast cancer metastasis and may pave the way for improved diagnostic tools and targeted therapeutic strategies. Show less
no PDF DOI: 10.1093/procel/pwag002
ANGPTL4
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
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
Shangming Li, Bocheng Xiong, Nan Xu +7 more · 2026 · Molecular neurobiology · Springer · added 2026-04-24
Alzheimer's disease (AD), the most prevalent form of dementia, is characterized as a slowly progressing neurodegenerative disease marked by senile plaques and neurofibrillary tangles due to the buildu Show more
Alzheimer's disease (AD), the most prevalent form of dementia, is characterized as a slowly progressing neurodegenerative disease marked by senile plaques and neurofibrillary tangles due to the buildup of amyloid-beta peptide (Aβ) and phosphorylated tau in the brain. It is reported that arctigenin (ATG) reduces the level of the enzyme 1 that cleaves β-site amyloid precursor protein and increases Aβ clearance by enhancing autophagy. Compound ARC-18 is a derivative of ATG. The main objective of this study is to investigate whether ARC-18 could improve cognitive function and disease progression by promoting autophagy in Alzheimer-like animal models. Three-month-old 5 × FAD mice were orally treated with the drug for three consecutive months. Water maze and novel object recognition were used to assess cognitive abilities of 5 × FAD mice. In the hippocampus of the mice' brain, APP processing-related proteins (sAPP Show less
📄 PDF DOI: 10.1007/s12035-026-05731-0
BACE1
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
Ya-Xin Deng, Bao-Jun Ding, Hong-Chun Li +4 more · 2026 · Yi chuan = Hereditas · added 2026-04-24
The
no PDF DOI: 10.16288/j.yczz.25-190
APOA4
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
Shun Li, Xinrui Li, Shuanglong Li +2 more · 2026 · Bioorganic & medicinal chemistry · Elsevier · added 2026-04-24
The multifaceted nature of Alzheimer's disease (AD) spurred growing interest in developing multi-target-directed ligands (MTDLs) for its prevention and treatment. Coumarin and quinoline scaffolds, rec Show more
The multifaceted nature of Alzheimer's disease (AD) spurred growing interest in developing multi-target-directed ligands (MTDLs) for its prevention and treatment. Coumarin and quinoline scaffolds, recognized for their broad spectrum of AD-related biological activities including amyloid-β (Aβ) aggregation regulation, cholinesterase (ChE) inhibition, β-secretase 1 (BACE1) inhibition and neuroprotection, were identified as potential building blocks. Here in this study, 24 novel coumarin-quinoline hybrid compounds were rationally designed and synthesized. Inhibition studies targeting Aβ, ChE and BACE1 identified compound B8 as a promising lead compound. B8 exhibited effective binding to Aβ, and significantly attenuated Aβ-induced SH-SY5Y cell death by lowering oxidative stress and decreasing cellular apoptosis. Crucially, B8 demonstrated excellent blood-brain barrier (BBB) permeability, and intragastric administration of B8 to 7-month-old APP/PS1 transgenic mice resulted in improved cognitive function. This improvement was supported by the protection of hippocampal and cortical neurons from necrosis, attenuation of oxidative stress and inflammation in these brain regions, as well as a reduction in Aβ deposition. These findings highlight the potential of coumarin-quinoline hybrids as a novel class of AD therapeutics, with B8 emerging as a promising lead candidate warranting further investigation. Show less
no PDF DOI: 10.1016/j.bmc.2025.118499
BACE1