👤 Xiao-Wei Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, Zhezhe Chen, Zhi Bin Chen, Zhi Chen, Zhi-Hao Chen, Zhi-bin Chen, Zhi-zhe Chen, Zhiang Chen, Zhichuan Chen, Zhifeng Chen, Zhigang Chen, Zhigeng Chen, Zhiguo Chen, Zhihai Chen, Zhihang Chen, Zhihao Chen, Zhiheng Chen, Zhihong Chen, Zhijian Chen, Zhijian J Chen, Zhijing Chen, Zhijun Chen, Zhimin Chen, Zhinan Chen, Zhiping Chen, Zhiqiang Chen, Zhiquan Chen, Zhishi Chen, Zhitao Chen, Zhiting Chen, Zhiwei Chen, Zhixin Chen, Zhixuan Chen, Zhixue Chen, Zhiyong Chen, Zhiyu Chen, Zhiyuan Chen, Zhiyun Chen, Zhizhong Chen, Zhong Chen, Zhongbo Chen, Zhonghua Chen, Zhongjian Chen, Zhongliang Chen, Zhongxiu Chen, Zhongzhu Chen, Zhou Chen, Zhouji Chen, Zhouliang Chen, Zhoulong Chen, Zhouqing Chen, Zhuchu Chen, Zhujun Chen, Zhuo Chen, Zhuo-Yuan Chen, ZhuoYu Chen, Zhuohui Chen, Zhuojia Chen, Zi-Jiang Chen, Zi-Qing Chen, Zi-Yang Chen, Zi-Yue Chen, Zi-Yun Chen, Zian Chen, Zifan Chen, Zihan Chen, Zihang Chen, Zihao Chen, Zihe Chen, Zihua Chen, Zijie Chen, Zike Chen, Zilin Chen, Zilong Chen, Ziming Chen, Zinan Chen, Ziqi Chen, Ziqing Chen, Zitao Chen, Zixi Chen, Zixin Chen, Zixuan Chen, Ziying Chen, Ziyuan Chen, Zoe Chen, Zongming E Chen, Zongnan Chen, Zongyou Chen, Zongzheng Chen, Zugen Chen, Zuolong Chen
articles
Ying Zhang, Tianyi Qu, Fengming Wu +5 more · 2026 · Journal of materials chemistry. B · Royal Society of Chemistry · added 2026-04-24
Effective real-time monitoring and tracking of lipid droplets (LDs) are essential for the precise diagnosis of atherosclerotic plaques and the assessment of pathological progression. However, viable s Show more
Effective real-time monitoring and tracking of lipid droplets (LDs) are essential for the precise diagnosis of atherosclerotic plaques and the assessment of pathological progression. However, viable strategies for Show less
no PDF DOI: 10.1039/d5tb02936h
APOE
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
Yunjung Jin, Kai Chen, Alexander Q Wixom +14 more · 2026 · Acta neuropathologica · Springer · added 2026-04-24
Lewy body dementia (LBD), encompassing dementia with Lewy bodies and Parkinson's disease dementia, is neuropathologically defined by neuronal accumulation of α-synuclein encoded by the SNCA gene. Gene Show more
Lewy body dementia (LBD), encompassing dementia with Lewy bodies and Parkinson's disease dementia, is neuropathologically defined by neuronal accumulation of α-synuclein encoded by the SNCA gene. Genetic risk factors strongly influence LBD susceptibility, including SNCA multiplication, particularly triplication, and the apolipoprotein E ε4 allele (APOE4), the strongest common genetic risk factor for LBD. While SNCA is predominantly expressed in neurons and APOE primarily in glial cells, how these genetic factors converge to impact neuronal vulnerability and regional pathology in the human brain remains poorly understood. Here, we applied spatial transcriptomics to postmortem temporal cortex tissue from LBD cases with SNCA triplication or different APOE genotypes, alongside age- and sex-matched controls, to map gene expression within intact cortical architecture. We identified layer 5 of the gray matter as a particularly vulnerable region, characterized by elevated SNCA expression, pronounced synaptic and metabolic dysregulation, and exacerbation of these alterations in APOE4 carriers. Reelin signaling emerged as a core Lewy body-associated pathway disrupted across cortical layers, validated in independent postmortem cohorts and human-induced pluripotent stem cell (iPSC)-derived cortical organoids. In contrast, white matter exhibited distinct molecular alterations, including disrupted myelination pathways, with APOE4 carriers showing increased myelin debris and glial responses compared with non-carriers. Cell-type deconvolution informed by single-nucleus RNA sequencing further revealed APOE4-associated impairments in neuronal vulnerability and intercellular communication. Together, these findings define spatially and cell-type-specific mechanisms through which SNCA dosage and APOE4 genotype impact LBD pathology, providing insight into regionally distinct disease processes and potential targets for genetically stratified therapeutic interventions. Show less
📄 PDF DOI: 10.1007/s00401-026-02981-z
APOE
Zihan Yi, Chengchuan Chen, Zikejimu Sun +3 more · 2026 · Frontiers in public health · Frontiers · added 2026-04-24
This study aimed to identify heterogeneous profiles of self-neglect (ESN) and their associated factors among rural Chinese older adults with chronic diseases. A cross-sectional survey was conducted am Show more
This study aimed to identify heterogeneous profiles of self-neglect (ESN) and their associated factors among rural Chinese older adults with chronic diseases. A cross-sectional survey was conducted among 719 rural older adults with chronic diseases in Sichuan, China, from January to June 2020. The questionnaire included sociodemographic and health-related characteristics, as well as the Three-Item UCLA Loneliness Scale (UCLALS-3), the Social Support Rating Scale (SSRS), the Scale of Older Adults Self-Neglect (SESN), the Five-Item Geriatric Depression Scale (GDS-5), and the Short Portable Mental Status Questionnaire (SPMSQ). Latent profile analysis (LPA) was conducted to identify distinct patterns of patterns of self-neglect among older adults (ESN). Four profiles were identified: low-level neglect (35.0%), selective mild neglect (37.7%), moderate neglect (14.7%), and severe neglect (12.5%). Compared with the low-level neglect group, selective mild neglect was more common among participants with poorer economic status, poor sleep quality, and alcohol consumption. The moderate neglect profile was associated with older age, lack of regular physical examinations, smoking, pain, cognitive impairment, and lower social support. Severe neglect was marked by the absence of grandchild caregiving, higher loneliness, smoking, and depression. Pairwise comparisons indicated stage-dependent patterns, with reversed associations for social support (protective in moderate neglect but a risk marker in severe neglect) and pain (a risk factor in moderate neglect, whereas its absence indicated higher risk in severe neglect). ESN among older adults with chronic diseases in rural China is heterogeneous and comprises distinct latent profiles with stage-dependent risk factors. For selective mild neglect, interventions should emphasize economic and lifestyle support. For moderate neglect, priorities include routine monitoring, regular physical examinations, and health literacy promotion. For severe neglect, intensive psychosocial interventions should address depression and loneliness and promote alternative engagement in family roles, particularly among older adults who do not provide grandchild caregiving. Integrating these profile-specific strategies into rural primary care may help reduce self-neglect and improve health outcomes in this vulnerable population. Show less
📄 PDF DOI: 10.3389/fpubh.2026.1738418
LPA
Zhihao Zhao, Yutong Yang, Liu Zhang +12 more · 2026 · Scientific reports · Nature · added 2026-04-24
Pancreatic cancer (PC) is a common gastrointestinal malignancy whose initiation and progression may be closely linked to the gut microbiota. Previous research indicates that Scutellaria barbata D. Don Show more
Pancreatic cancer (PC) is a common gastrointestinal malignancy whose initiation and progression may be closely linked to the gut microbiota. Previous research indicates that Scutellaria barbata D. Don and Scleromitrion diffusum (Willd.) R.J. Wang (SB-SD) exhibit diverse biological activities, such as anti-inflammatory, antioxidant, and antitumor effects, though their precise regulatory mechanisms are not fully elucidated. Here, we treated PC cells with SB-SD to assess its impact on cell viability, apoptosis, migration, and cell cycle progression, while Western blotting analyzed the expression of HSP90AA1, MAPK3, p53, CDK1, and p21. We also established a pancreatic cancer xenograft model in nude mice to evaluate the in vivo inhibitory effect of SB-SD on tumor growth. Furthermore, we employed metagenomic sequencing, untargeted metabolomics, and quantitative proteomics to comprehensively profile changes in the gut microbiota, serum metabolites, and differentially expressed proteins, with Western blotting subsequently validating BCKDK, GATM and p53 expression. The results show that SB-SD significantly inhibited PC cell proliferation, promoted apoptosis, and induced S/G2 phase cell cycle arrest, potentially via modulation of the HSP90AA1/MAPK3 signaling pathway. Measurements of tumor volume and weight, complemented by histopathological analysis, confirmed that SB-SD effectively suppressed the growth of PANC-1 xenograft tumors. Integrated multi-omics analyses suggest that the antitumor effects of SB-SD may involve the modulation of key gut microbes like Bacteroides caccae and Lactobacillus, the promotion of choline metabolism, and the regulation of BCKDK and GATM. Together, these findings not only corroborate the direct antitumor activity of SB-SD against pancreatic cancer but also offer novel mechanistic insights by constructing a microbiota-metabolite-protein interaction network. Show less
📄 PDF DOI: 10.1038/s41598-026-45676-x
BCKDK
Guan-Wei Chen, Yi-Hung Liu, Chih-Chuan Pan +4 more · 2026 · Journal of Alzheimer's disease : JAD · SAGE Publications · added 2026-04-24
BackgroundPredicting cognitive function across dementia stages remains challenging. Plasma biomarkers and electroencephalogram (EEG) features may provide complementary information, but their combined Show more
BackgroundPredicting cognitive function across dementia stages remains challenging. Plasma biomarkers and electroencephalogram (EEG) features may provide complementary information, but their combined predictive value requires further study.ObjectiveTo evaluate the feasibility of integrating plasma biomarkers and EEG features to predict cognitive function in dementia and examine their correlations.MethodsFrom September 2023 to October 2024, 75 patients from two medical centers with mild cognitive impairment, mild dementia, or moderate dementia were enrolled. Resting-state 19-channel EEG data yielded 2737 time-frequency and connectivity features. Plasma biomarkers included tau, p-Tau181, Aβ Show less
no PDF DOI: 10.1177/13872877261429861
BDNF biomarkers cognitive function dementia eeg electroencephalogram mild cognitive impairment neurodegenerative diseases
Weijian Wang, Jiangping Ye, Xinyi Hu +3 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Coronary artery calcification (CAC), a hallmark of coronary atherosclerosis, links closely to dysregulated lipid metabolism and chronic inflammation. Proprotein convertase subtilisin/kexin type 9 (PCS Show more
Coronary artery calcification (CAC), a hallmark of coronary atherosclerosis, links closely to dysregulated lipid metabolism and chronic inflammation. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors exert potent lipid-lowering and anti-inflammatory effects, holding translational potential for vascular calcification intervention. However, evidence on PCSK9 inhibition's impact on vascular calcification remains inconsistent. Here, we combined genetic causal analysis with First, we used two-sample Mendelian randomization (MR) and multivariable Mendelian randomization to identify lipid profiles genetically associated with coronary artery calcification. Subsequently, we investigated the value of the PCSK9 gene as a potential therapeutic target for CAC through drug target MR and colocalization analysis, and screened for potential inflammatory mediators via Mediation MR analyses. Following the completion of the aforementioned analyses, we verified the beneficial effect of PCSK9 inhibitors on delaying vascular calcification through animal experiments and cell experiments. MR analysis revealed that genetic proxies for apolipoprotein B (ApoB) (OR=1.64; 95%CI: 1.42-1.90; Inhibition of PCSK9 may effectively slow the progression of coronary artery calcification, with inflammatory mediators such as FGF23 playing key regulatory roles in this process. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1767013
APOB
Ting Li, Ke Chen · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Internalizing and externalizing behavior problems co-occur frequently and there is heterogeneity in the co-occurrence of such symptoms; however, few studies have explored this heterogeneity and its de Show more
Internalizing and externalizing behavior problems co-occur frequently and there is heterogeneity in the co-occurrence of such symptoms; however, few studies have explored this heterogeneity and its developmental mechanisms from a person-centered perspective. The primary aim of this study is to employ Latent Profile Analysis (LPA) and Latent Transition Analysis (LTA)-person-centered statistical approaches-to explore this underlying heterogeneity, uncover its dynamic developmental trajectories, and further examine the key factors that influence class membership and transitions. A sample of 2232 Chinese college students from three universities in Chongqing was assessed at two time points spaced ten months apart. Latent Profile Analysis (LPA) and Latent Transition Analysis (LTA) were conducted on measures of internalizing and externalizing problems. LPA revealed three distinct profiles for both internalizing problems ("Low-Risk/Well-Adapted", "Moderate-Risk/Affective-Distress", "High-Risk/Comorbid") and externalizing problems ("Well-Adapted", "Adaptation Difficulties", "Maladaptive") at T1, with similar structures at T2. LTA indicated high stability for the low- and high-risk internalizing profiles, but significant fluidity in the middle, with nearly half of the moderate-risk group transitioning to the high-risk profile. For externalizing problems, there was a pronounced shift toward the "Maladaptive" profile over time. Negative parental rearing and PWU were significant risk factors for adverse transitions, while positive parenting, self-transcendence values, and objective social support served as protective factors. Co-occurring internalizing and externalizing problems among Chinese college students are heterogeneous and dynamic. The moderate-risk group represents a critical target for early intervention. Modifiable ecological factors across family, individual, and technological domains significantly predict longitudinal trajectories, informing targeted prevention strategies. Show less
no PDF DOI: 10.1016/j.jad.2025.120957
LPA
Changming Shao, Chunfa Cheng, Bing Chen · 2026 · Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists · SAGE Publications · added 2026-04-24
To construct a risk model for discriminating abdominal aortic aneurysm (AAA) rupture and explore its potential mechanism. Clinical data of AAA patients were obtained from the MIMIC-IV database. The mu Show more
To construct a risk model for discriminating abdominal aortic aneurysm (AAA) rupture and explore its potential mechanism. Clinical data of AAA patients were obtained from the MIMIC-IV database. The multivariable logistic analysis was performed to identify the independent risk factors associated with AAA rupture. The nomogram model was used, and its risk score was calculated. The clinical relevance of the model was assessed by receiver operating characteristic curve analysis and the Kaplan-Meier plotter. The potential mechanism was investigated by the enrichment and immune cell infiltration analyses using the GSE98278 dataset from the Gene Expression Omnibus (GEO) database. A total of 309 AAA patients were divided into rupture (n=39) and non-rupture (n=270) groups. White blood cell (WBC), hematocrit (HCT), platelets, and glucose were associated with the AAA rupture (all p<0.05). The risk score of the nomogram model (area under the curve [AUC]=0.746) was a promising index in discriminating AAA rupture. Besides, the high-risk score was related to patients' survival (1, 5 years) (HR The risk score of the nomogram model could discriminate AAA rupture, and it was also linked to the poor prognosis of AAA patients. Moreover, T cells CD4 memory activated may be related to AAA rupture by involving the immune environment.Clinical ImpactThis study identified risk factors associated with AAA rupture, constructed a risk model, and explored its underlying mechanisms. High-risk scores derived from the nomogram model were negatively associated with patient outcomes, indicating that this risk model can serve as a stratification tool to guide individualized intervention strategies. The risk model utilizing fewer indicators can be employed for initial screening, followed by application of composite scores for high-risk patients to optimize clinical decision-making and enhance the efficiency of healthcare resource allocation. Show less
no PDF DOI: 10.1177/15266028261420062
ANGPTL4
Luyue Chang, Junqi Xiang, Ting Zhang +11 more · 2026 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Vitiligo pathogenesis involves progressive melanocyte loss and keratinocyte dysfunction, which are driven primarily by oxidative stress resulting from excessive ROS accumulation. We engineered a tempo Show more
Vitiligo pathogenesis involves progressive melanocyte loss and keratinocyte dysfunction, which are driven primarily by oxidative stress resulting from excessive ROS accumulation. We engineered a temporally controlled hydrogel microneedle system that integrates ginseng-derived exosomes (G-Exos) with biomimetic polydopamine nanoparticles (PDA@PEGs) to concurrently target the pathogenic triad of vitiligo, including oxidative stress, inflammation, and melanocyte deficiency. This system employs methacrylated hyaluronic acid (HAMA) hydrogel microneedles for rapid PDA@PEG release while utilizing glyceryl monostearate micelles to achieve matrix metalloproteinase-9 (MMP-9)-responsive G-Exo release at inflammatory foci, enabling intelligent spatiotemporal control. Functionally, G-Exos help restore redox homeostasis and suppress inflammation through bioactive constituents, thereby protecting melanocytes and enhancing keratinocyte proliferation. Moreover, PDA@PEG promotes repigmentation through the dual mechanisms of exogenous melanin deposition and endogenous melanogenesis stimulation. In murine models, this strategy achieves significant repigmentation within 3 weeks by activating follicular stem cells, upregulating melanogenic markers (Tyr/Mc1r), increasing antioxidant defense (ApoE), and suppressing inflammatory signaling (IL-17). This natural-biomimetic hybrid design leverages biocompatible materials to co-target multiple pathological axes, offering a novel self-adaptive approach for microenvironmental rehabilitation in vitiligo. Show less
📄 PDF DOI: 10.1186/s12951-026-04168-w
APOE
Yifeng Xia, Zhongyu Peng, Lingrui Zhao +6 more · 2026 · Scientific reports · Nature · added 2026-04-24
Osteoporosis (OP) is a metabolic bone disease characterized by low bone mineral density (BMD), and its pathogenesis involves endoplasmic reticulum (ER) stress-related cell death. This study aimed to i Show more
Osteoporosis (OP) is a metabolic bone disease characterized by low bone mineral density (BMD), and its pathogenesis involves endoplasmic reticulum (ER) stress-related cell death. This study aimed to identify diagnostic biomarkers associated with ER stress-related cell death in OP and explore their underlying mechanisms. The training dataset (GSE56815), validation dataset (GSE56814), and single-cell RNA sequencing (scRNA-seq) dataset (GSE147287) were downloaded. Differentially expressed genes (DEGs) between OP patients and controls were identified. Candidate genes were obtained by intersecting DEGs with ER stress-related genes and programmed cell death (PCD)-related genes. Machine learning was used to screen intersection genes, and biomarkers were determined via expression level analysis. Gene set enrichment analysis (GSEA), immune cell infiltration analysis, drug prediction and molecular docking, scRNA-seq analysis, key cell screening, cell communication analysis, and pseudotime analysis were performed. Finally, reverse transcription quantitative polymerase chain reaction (RT-qPCR) were further conducted. A total of 28 candidate genes were obtained by intersection. CAMKK2 and DAPK3 were confirmed as biomarkers, and were consistently down-regulated in both datasets and verified by RT-qPCR. GSEA analysis revealed that biomarkers were enriched in cytokine-cytokine receptor interaction. Correlations between biomarkers and activated dendritic cells were found via immune cell infiltration analysis. Preliminary computational analyses indicated that drugs including calcitriol and danazol may potentially interact with the biomarkers in a stable manner. Bone marrow-derived mesenchymal stem cells (BM-MSCs) were identified as potential key cells via scRNA-seq analysis. Complex interactions involving BM-MSCs, such as ANGPTL4-CDH11 mediating BM-MSC self-communication, were revealed by cell communication analysis. Dynamic expression of biomarkers during BM-MSC differentiation was shown by pseudotime analysis: CAMKK2 fluctuated with differentiation stages, while DAPK3 shifted from high to low then high expression. CAMKK2 and DAPK3 were confirmed as diagnostic biomarkers for OP, providing insights into OP diagnosis and potential therapeutic targets. Show less
📄 PDF DOI: 10.1038/s41598-026-43744-w
ANGPTL4
Ying Hou, Xin Zhang, Xia Sun +4 more · 2026 · Arteriosclerosis, thrombosis, and vascular biology · added 2026-04-24
Lipid-lowering therapy is a cornerstone in the treatment of atherosclerotic cardiovascular diseases. Although some lipid-lowering drugs have demonstrated positive effects in patients with atherosclero Show more
Lipid-lowering therapy is a cornerstone in the treatment of atherosclerotic cardiovascular diseases. Although some lipid-lowering drugs have demonstrated positive effects in patients with atherosclerotic cardiovascular diseases, their effects are limited in those with homozygous familial hypercholesterolemia. It is essential to seek new lipid-lowering targets. YAP (Yes-associated protein) may be involved in lipid metabolism in the liver; therefore, we investigated the function of hepatocyte YAP in hyperlipidemia and atherosclerosis. Hyperlipidemia models were generated in apoE knockout (apoE High-cholesterol diet-fed apoE Taken together, our findings revealed a novel role for the YAP-TEAD4-ANGPTL3 axis in lipid metabolism independent of LDLR. Inhibition of hepatocyte YAP may be an effective lipid-lowering strategy for homozygous familial hypercholesterolemia. Show less
no PDF DOI: 10.1161/ATVBAHA.125.324122
APOE
Ya Su, Zhiyuan Yu, Si Chen +2 more · 2026 · Nurse education in practice · Elsevier · added 2026-04-24
This study aims to identify distinct subgroups of digital resilience among nursing students and examine the factors associated with these subgroups. Digital resilience, the ability to adapt to technol Show more
This study aims to identify distinct subgroups of digital resilience among nursing students and examine the factors associated with these subgroups. Digital resilience, the ability to adapt to technological changes and overcome challenges in higher education, is crucial for protecting students' psychological health and improving academic performance. In the context of Artificial Intelligence (AI) and digital transformation in nursing education, this resilience is essential for students to navigate virtual learning and integrate advanced technologies into their practice. A cross-sectional study. This study was conducted in eight universities in China guided by ecological systems theory and nursing students were recruited through convenience sampling. Latent profile analysis (LPA) identified subgroups and logistic regression examined related factors. A total of 331 (81.73 %) participants were included in the final analysis. The average age of participants was 20.41SD0.67 years, with 283 female (85.55 %). Latent profile analysis revealed two subgroups: the "High Digital Resilience Group" (n = 278, 83.99 %) and the "Low Digital Resilience Group" (n = 53, 16.01 %). Participants who were male (OR = 3.47, p = 0.02), had low household income (OR = 0.23, p = 0.01, low professional identity (OR = 0.86, p < 0.001) and low friend support (OR = 0.82, p < 0.001) were more likely to belong to the low digital resilience group. Educators should focus on enhancing students' professional identity and providing social support, especially for those with low digital resilience. The findings provide practical guidance for integrating AI into nursing education to enhance digital resilience. Show less
no PDF DOI: 10.1016/j.nepr.2025.104636
LPA
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
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
Peijun Tian, Renying Zou, Linhong Song +7 more · 2026 · Food & function · Royal Society of Chemistry · added 2026-04-24
Correction for 'Ingestion of
📄 PDF DOI: 10.1039/d6fo90015a
BDNF correction ingestion
Ying Zhang, Zhouting Tuo, Yuan Lin +10 more · 2026 · Cancer research · added 2026-04-24
Cancer-associated fibroblasts (CAF) are abundant stromal cells in the tumor microenvironment (TME) that play a vital role in promoting tumor progression and drug resistance. The mechanisms regulating Show more
Cancer-associated fibroblasts (CAF) are abundant stromal cells in the tumor microenvironment (TME) that play a vital role in promoting tumor progression and drug resistance. The mechanisms regulating heterogeneity of CAFs in renal cell carcinoma (RCC) could represent potential targets for reprogramming the TME. In this study, we conducted single-cell RNA sequence and flow cytometry analyses that identified a CAF subset overexpressing apolipoprotein E (ApoE), which was correlated with poor survival in patients with RCC. Mechanistically, NRF1 activation in CAFs induced formation of ApoEhigh CAFs and secretion of NRG1. ApoEhigh CAFs potentiated stemness properties in the surrounding RCC cells by secreting NRG1 and subsequently activating the HER2/NF-κB pathway. Interfering with NRG1 expression or inhibiting NF-κB signaling reduced ApoEhigh CAF-induced stemness of RCC cells. Furthermore, neutralizing NRG1 enhanced the efficacy of sunitinib in RCC models in vivo. Together, these findings highlight targeting the tumor-promoting functions of ApoEhigh CAFs as a promising approach for treating advanced RCC. NRF1 drives formation of ApoEhigh cancer-associated fibroblasts that secrete NRG1 to stimulate stemness of renal cell carcinoma, revealing a stromal-mediated mechanism that can be inhibited to improve treatment of advanced kidney cancer. Show less
no PDF DOI: 10.1158/0008-5472.CAN-25-0959
APOE
Xiaohua Gong, Ayman Akil, Boris Grinshpun +6 more · 2026 · Journal of chemotherapy (Florence, Italy) · Taylor & Francis · added 2026-04-24
Pemigatinib is a selective, potent, orally administered inhibitor of fibroblast growth factor receptor (FGFR)1-3 with antitumor activity in multiple solid tumors. Pemigatinib is used to treat adults w Show more
Pemigatinib is a selective, potent, orally administered inhibitor of fibroblast growth factor receptor (FGFR)1-3 with antitumor activity in multiple solid tumors. Pemigatinib is used to treat adults with previously treated metastatic or surgically unresectable cholangiocarcinoma with Show less
no PDF DOI: 10.1080/1120009X.2025.2497641
FGFR1
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
Yi Wei, Bo Ning, Shengjie Wang +5 more · 2026 · Journal of integrative neuroscience · added 2026-04-24
Premature ejaculation (PE) accompanied by anxiety or depression is a complex clinical condition at the intersection of male reproductive dysfunction and emotional disorders. Increasing evidence sugges Show more
Premature ejaculation (PE) accompanied by anxiety or depression is a complex clinical condition at the intersection of male reproductive dysfunction and emotional disorders. Increasing evidence suggests that serotonin (5-HT) and brain-derived neurotrophic factor (BDNF) play central and interrelated roles in its pathogenesis. In this review we examine the bidirectional functions of 5-HT and BDNF in both the reproductive and nervous systems, highlighting their importance in regulating ejaculation, emotional stability, and synaptic plasticity. A comprehensive literature search (2010-2025) was conducted across multiple databases using relevant Medical Subject Headings (MeSH) terms, including pertinent original research and review articles, to synthesize the roles and regulatory pathways of 5-HT and BDNF in PE with comorbid anxiety or depression. We summarize the shared and distinct roles of 5-HT and BDNF in maintaining physiological balance across these systems and focus on their involvement in the major pathological processes underlying PE with anxiety or depression, including neurotransmitter imbalance, neuroendocrine dysregulation, inflammation, and oxidative stress. Furthermore, we outline the related signaling pathways through which 5-HT and BDNF exert their effects and interact. We also evaluate current pharmacological and non-pharmacological interventions targeting these molecules, demonstrating their potential to improve both ejaculatory control and emotional symptoms, and critically appraise selective serotonin reuptake inhibitor (SSRI)-related risks and highlighted the need for individualized dosing and monitoring. Emerging evidence suggests that Traditional Chinese Medicine formulations can extend intravaginal ejaculatory latency and mitigate mood symptoms and may serve as stand-alone or adjunctive options to reduce reliance on selective serotonin reuptake inhibitors (SSRIs). Overall, 5-HT and BDNF are not only deeply involved in the biological mechanisms of PE with comorbid psychological disorders, but also represent promising biomarkers and therapeutic targets, and their integrative neuro-reproductive regulatory functions provide new insights into the diagnosis and treatment of this multifaceted condition. Show less
📄 PDF DOI: 10.31083/JIN45471
5-ht BDNF anxiety bdnf depression neurotrophic factor premature ejaculation serotonin
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
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
David Lukacsovich, Juan I Young, Lissette Gomez +8 more · 2026 · Research square · added 2026-04-24
Cognitive reserve (CR) refers to differences in the adaptability of cognitive processes that modify the impact of Alzheimer's disease (AD) pathology on cognitive performance. Currently there are no es Show more
Cognitive reserve (CR) refers to differences in the adaptability of cognitive processes that modify the impact of Alzheimer's disease (AD) pathology on cognitive performance. Currently there are no established blood-based biomarkers of CR in prodromal AD. In this study, we operationalize CR as memory reserve, defined as moderation (attenuation) of the CSF pTau181-memory association. DNA methylation (DNAm) integrates genetic and environmental influences and may capture biological processes that mitigate the impact of AD pathology on memory. We aimed to identify blood DNAm loci that moderate the association between cerebrospinal fluid (CSF) phosphorylated tau (pTau181) and memory in mild cognitive impairment (MCI). We also sought to determine if a DNAm-based signature of memory reserve predicts future memory decline. We analyzed 92 amyloid positive MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with blood DNAm, CSF pTau181, and memory scores (PHC_MEM) collected at the same visit. We first regressed memory scores on covariates (age, sex, number of After removing CpGs with low variability, we identified 6 CpGs with suggestive significance for DNAm×pTau181 interaction ( Blood DNAm patterns that moderate the pTau-memory relationship capture biology underlying memory reserve involving synaptic, vascular, immune, and metabolic pathways, and can be summarized into an MRS that predicts longitudinal memory trajectories in MCI. These findings support blood DNAm as a promising, non-invasive biomarker of cognitive resilience to AD pathology. Show less
📄 PDF DOI: 10.21203/rs.3.rs-8369919/v1
APOE
Ping Guo, Wenli Li, Shasha Chen +5 more · 2026 · Frontiers in immunology · Frontiers · added 2026-04-24
Long-term antigen-specific data in PMN among Chinese populations remain limited. This study evaluated six target antigens and their clinical significance during extended follow-up. We retrospectively Show more
Long-term antigen-specific data in PMN among Chinese populations remain limited. This study evaluated six target antigens and their clinical significance during extended follow-up. We retrospectively analyzed 132 treatment-naïve PMN patients diagnosed by biopsy (2010-2018) and followed for a median of 62.9 months. Renal tissue expression of PLA2R, THSD7A, NELL-1, PCDH7, EXT1, and EXT2 was assessed by immunohistochemistry, and serum anti-PLA2R antibodies were measured by ELISA. Associations between antigen profiles and 5-year outcomes (remission, renal survival, malignancy) were evaluated. PLA2R was the predominant antigen (84.1%), followed by THSD7A (5.3%) and NELL-1 (0.76%); no PCDH7, EXT1, or EXT2 positivity was detected. PLA2R-negative patients were more often female (71.4% vs. 36.0%, This >5-year Chinese PMN cohort provides the first comprehensive analysis of six target antigens. PLA2R remains predominant, while PLA2R-negative patients distinct immunopathologic features yet favorable long-term outcomes. A population-specific anti-PLA2R cutoff showed good diagnostic performance for predicting tissue antigen deposition. Rare antigens were infrequent and their malignancy associations require cautious interpretation. These findings provide long-term antigen-specific data supporting antigen-guided, population-adapted precision management of PMN. Show less
📄 PDF DOI: 10.3389/fimmu.2026.1761515
EXT1
Cheng Yi, Yunqing Lu, Xing Chang +15 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Breast cancer (BC) progression is intricately linked to the dysregulation of transfer RNA-derived fragments (tRFs). Through comprehensive analysis of The Cancer Genome Atlas (TCGA) data, it is demonst Show more
Breast cancer (BC) progression is intricately linked to the dysregulation of transfer RNA-derived fragments (tRFs). Through comprehensive analysis of The Cancer Genome Atlas (TCGA) data, it is demonstrated that 5'tRF-GlyGCC is overexpressed in BC tissues and negatively associated with patients' survival. Mechanistically, 5'tRF-GlyGCC binds to lactate dehydrogenase A (LDHA), enhancing its enzymatic activity and promoting glycolysis, which drives BC cell malignancy. This binding is mediated by the phosphorylation of LDHA at tyrosine 10, and facilitated by fibroblast growth factor receptor 1 (FGFR1), through the formation of a ternary complex that amplifies oncogenic signaling. Furthermore, 5'tRF-GlyGCC/LDHA axis induces macrophage infiltration and polarization toward an M2 phenotype, mediated by the chemokine CCL7, thereby reshaping the tumor microenvironment. Additionally, it is uncovered that the biogenesis of 5'tRF-GlyGCC is regulated by ALKBH3 and ANG, which also modulate LDHA activity. In vivo, targeting 5'tRF-GlyGCC/LDHA signaling significantly suppresses tumor growth and enhances the efficacy of immunotherapy. Collectively, these findings elucidate the pivotal role of 5'tRF-GlyGCC in BC progression, highlighting its potential as therapeutic target for BC treatment. Show less
📄 PDF DOI: 10.1002/advs.202514031
FGFR1
Yue Liang, Ying-Lin Zhang, Tian-Yu Cheng +7 more · 2026 · Pharmacological research · Elsevier · added 2026-04-24
Pharmacological preconditioning of mesenchymal stem cells (MSCs) is a promising strategy to enhance their therapeutic efficacy for end-stage liver disease; however, maximizing this benefit remains a m Show more
Pharmacological preconditioning of mesenchymal stem cells (MSCs) is a promising strategy to enhance their therapeutic efficacy for end-stage liver disease; however, maximizing this benefit remains a major clinical challenge. Senkyunolide H (SNH), a small-molecule compound derived from Angelica sinensis, exhibits anti-inflammatory, antioxidant, and anti-apoptotic properties. Nevertheless, its capacity to optimize MSCs-based therapy for liver disease has not been fully elucidated. Here, we demonstrate that SNH preconditioning significantly enhances the therapeutic efficacy of bone marrow mesenchymal stem cells (BMSCs) in a murine model of liver cirrhosis. Specifically, SNH-pretreated BMSCs markedly alleviated hepatocellular injury, promoted hepatocyte proliferation, and attenuated collagen deposition. Mechanistically, SNH augments the therapeutic potency of BMSCs by partly binding to macrophage erythroblast attacher (MAEA), a subunit of the E3 ubiquitin ligase complex. This interaction stabilizes MAEA, which in turn facilitates the ubiquitination and proteasomal degradation of dual specificity phosphatase 6 (DUSP6), thereby activating ERK/STAT3 signaling and upregulating the secretion of hepatocyte growth factor (HGF). Collectively, our findings highlight SNH preconditioning as a robust approach to enhance the paracrine function and therapeutic potential of BMSCs, and identify MAEA as a novel therapeutic target for BMSCs-based interventions in liver cirrhosis. Show less
no PDF DOI: 10.1016/j.phrs.2026.108160
DUSP6
Litong Wu, Dicheng Luo, Biao Wang +5 more · 2026 · The journal of sexual medicine · Oxford University Press · added 2026-04-24
Premature ejaculation (PE) is one of the most common forms of male sexual dysfunction, yet its underlying neurobiological mechanisms remain unclear. This study aims to explore the role of S100 calcium Show more
Premature ejaculation (PE) is one of the most common forms of male sexual dysfunction, yet its underlying neurobiological mechanisms remain unclear. This study aims to explore the role of S100 calcium-binding protein B (S100B) in PE and its regulatory relationship with brain-derived neurotrophic factor (BDNF) and serotonin (5-HT) signaling. A rat model of PE was established using behavioral screening criteria. Sexual behavior parameters were recorded, and the expression levels of S100B, BDNF, and 5-HT in brain tissues were measured using enzyme-linked immunosorbent assay, quantitative real-time PCR, Western blotting, immunohistochemistry, and immunofluorescence. The impact of S100B knockdown on PE-related behaviors and molecular expression was evaluated. The primary outcome was the effect of S100B regulation on PE-related behaviors and its interaction with the BDNF/5-HT signaling pathway. PE rats exhibited classical behavioral features, including shortened ejaculation latency and increased ejaculation frequency. Transcriptomic and protein analyses showed that S100B expression was significantly upregulated, while BDNF and 5-HT levels were markedly reduced in PE rats. S100B expression increased across several brain regions. Knockdown of S100B restored 5-HT and BDNF levels, prolonged ejaculation latency, and alleviated PE behaviors. BDNF overexpression elevated 5-HT levels and improved sexual behavior. Importantly, BDNF silencing reversed the beneficial effects of S100B knockdown, suggesting that S100B regulates ejaculation via the BDNF/5-HT pathway. Targeting S100B and its regulation of the BDNF/5-HT pathway may provide potential therapeutic strategies for managing premature ejaculation. Strengths include comprehensive molecular and behavioral analyses in a rat model provide insights into PE pathophysiology. Although this effect has been demonstrated in animal models, these models may not fully recapitulate the pathophysiological processes of human PE, and further clinical validation is required. Our findings indicate that S100B is upregulated in PE and may contribute to the pathophysiology of PE by modulating the BDNF/5-HT signaling pathway. This study provides a molecular basis for the development of therapeutic strategies targeting PE. Show less
no PDF DOI: 10.1093/jsxmed/qdag054
5-ht pathway BDNF bdnf calcium-binding protein neurobiological mechanisms premature ejaculation sexual dysfunction
Ting Fang, Xinyu Yang, Xiaoqing Deng +5 more · 2026 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Excessive fructose intake is strongly associated with metabolic diseases, with the carbohydrate response element-binding protein (ChREBP) playing a key role in its metabolism, particularly in renal tu Show more
Excessive fructose intake is strongly associated with metabolic diseases, with the carbohydrate response element-binding protein (ChREBP) playing a key role in its metabolism, particularly in renal tubules. However, the role of its active form, ChREBP-β, was previously unclear. In this study, ChREBP-β overexpression and ChREBP knockout mouse models were utilized to investigate the effects of excessive fructose intake in vivo. In addition, primary renal tubular epithelial cells from mice and human kidney-2 (HK2) cells were applied for further validation in vitro. We found that ChREBP-β leads to increased transcription to mediate endoplasmic reticulum stress and mitochondrial dysfunction, which ultimately impairs renal function. Our findings underscore the critical role of ChREBP-β in fructose-related renal disorders. Show less
📄 PDF DOI: 10.1096/fj.202600490R
MLXIPL
Jianyi Li, Luyao Zhang, Jiapei Xu +7 more · 2026 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Chronic stress is associated with inflammatory activation and oxidative stress responses leading to endothelial dysfunction, which promotes the development of atherosclerosis (AS). SGLT2 inhibitors, s Show more
Chronic stress is associated with inflammatory activation and oxidative stress responses leading to endothelial dysfunction, which promotes the development of atherosclerosis (AS). SGLT2 inhibitors, such as Dapagliflozin (DAPA), exhibit a protective effect against cardiovascular diseases. However, the effects and mechanisms of DAPA on chronic stress-induced AS are largely unknown. The aim of this study was to determine whether DAPA confers a protective effect against chronic stress-induced AS and to elucidate its further molecular mechanisms. The combined high-fat diet-fed and chronic unpredictable mild stress in ApoE-/- mice and lipopolysaccharides- and corticosterone-induced human umbilical vein endothelial cells (HUVECs) were employed to evaluate the antiatherosclerotic effect of DAPA under chronic stress in vivo and in vitro. Histological staining, western blot analysis, siRNA transfection, reactive oxygen species (ROS) staining, and apoptosis assessment were used to investigate the potential mechanisms of DAPA against AS under chronic stress. The results indicate that DAPA significantly improved plaque size and increased plaque stability in the aorta under chronic stress and reduced inflammation and oxidative stress and inhibited apoptosis in the aorta and HUVECs. Chronic stress upregulated regulated in development and DNA damage response 1 (REDD1) expression, which exacerbated cellular inflammation, oxidative stress, and apoptosis levels, leading to endothelial dysfunction. In contrast, DAPA downregulated REDD1 expression and activated the AKT/FoxO1 pathway. In addition, p53 was a transcriptional regulator of REDD1 under chronic stress. More importantly, p53 agonists prevented DAPA from downregulating REDD1 and inhibited AKT/FoxO1 activation, thereby exacerbating chronic stress-induced endothelial dysfunction. These results suggest that DAPA effectively attenuates chronic stress-induced endothelial dysfunction and AS by downregulating REDD1 to activate the AKT/FoxO1 pathway. Show less
no PDF DOI: 10.1096/fj.202502868R
APOE
Jiaming Ji, Jinyan Guo, Yin Huang +11 more · 2026 · The Journal of nutritional biochemistry · Elsevier · added 2026-04-24
Electroconvulsive therapy (ECT) stands as the most effective intervention for treatment-resistant depression; however, its interaction with dietary regulation of the gut-brain axis has not been thorou Show more
Electroconvulsive therapy (ECT) stands as the most effective intervention for treatment-resistant depression; however, its interaction with dietary regulation of the gut-brain axis has not been thoroughly explored. This study aimed to elucidate the mechanistic link between ECT, gut microbiota remodeling, short-chain fatty acid (SCFA) production, and neural plasticity. In this study, mice were subjected to chronic restraint stress (6 h/d for 28 consecutive days) to establish a depression-like model. Utilizing a translational approach that incorporated behavioral assessments, multimodal neuroimaging techniques such as PET-CT and laser speckle contrast imaging, along with multiomics analyses including metagenomics, metabolomics, and transcriptomics in rodent models, we demonstrated that ECT induced significant gut microbiota remodeling, characterized by an enrichment of SCFA-producing genera like Lactobacillus and Bifidobacterium. This remodeling was associated with restored intestinal barrier integrity and elevated plasma SCFA levels. Mechanistically, these microbial metabolites activated hippocampal Wnt/β-catenin signaling pathways, enhancing synaptic plasticity restoration, while concurrent probiotic supplementation further amplified brain-derived neurotrophic factor (BDNF) expression via SCFA-dependent epigenetic mechanisms. Neuroimaging corroborated the normalization of cerebral glucose metabolism and hemodynamic function post-ECT. In conclusion, our findings unveil a novel gut-brain communication pathway by which ECT exerts its antidepressant effects, positioning SCFAs as vital mediators connecting microbial metabolic alterations to neural plasticity. This research not only redefines the role of nutritional biochemistry in neuromodulation but also suggests the potential of microbial metabolite monitoring to tailor antidepressant therapies for enhanced efficacy. Show less
no PDF DOI: 10.1016/j.jnutbio.2025.110240
BDNF bdnf signaling brain plasticity depression dietary regulation electroconvulsive therapy gut microbiota neural plasticity