👤 Haoting 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, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, Mian-Mian Chen, Miao Chen, Miao-Der Chen, Miao-Hsueh Chen, Miao-Yu Chen, Miaomiao Chen, Miaoran Chen, Michael C Chen, Michelle Chen, Mien-Cheng Chen, Min Chen, Min-Hsuan Chen, Min-Hu Chen, Min-Jie Chen, Ming Chen, Ming-Fong Chen, Ming-Han Chen, Ming-Hong Chen, Ming-Huang Chen, Ming-Huei Chen, Ming-Yu Chen, Mingcong Chen, Mingfeng Chen, Minghong Chen, Minghua Chen, Minglang Chen, Mingling Chen, Mingmei Chen, Mingxia Chen, Mingxing Chen, Mingyang Chen, Mingyi Chen, Mingyue Chen, Minjian Chen, Minjiang Chen, Minjie Chen, Minyan Chen, Mo Chen, Mu-Hong Chen, Muh-Shy Chen, Mulan Chen, Mystie X Chen, Na Chen, Naifei Chen, Naisong Chen, Nan Chen, Ni Chen, Nian-Ping Chen, Ning Chen, Ning-Bo Chen, Ning-Hung Chen, Ning-Yuan Chen, Ningbo Chen, Ningning Chen, Nuan Chen, On Chen, Ou Chen, Ouyang Chen, P P Chen, Pan Chen, Paul Chih-Hsueh Chen, Pei Chen, Pei-Chen Chen, Pei-Chun Chen, Pei-Lung Chen, Pei-Yi Chen, Pei-Yin Chen, Pei-zhan Chen, Peihong Chen, Peipei Chen, Peiqin Chen, Peixian Chen, Peiyou Chen, Peiyu Chen, Peize Chen, Peizhan Chen, Peng Chen, Peng-Cheng Chen, Pengxiang Chen, Ping Chen, Ping-Chung Chen, Ping-Kun Chen, Pingguo Chen, Po-Han Chen, Po-Ju Chen, Po-Min Chen, Po-See Chen, Po-Sheng Chen, Po-Yu Chen, Qi Chen, Qi-An Chen, Qian Chen, Qianbo Chen, Qianfen Chen, Qiang Chen, Qiangpu Chen, Qiankun Chen, Qianling Chen, Qianming Chen, Qianping Chen, Qianqian Chen, Qianxue Chen, Qianyi Chen, Qianyu Chen, Qianyun Chen, Qianzhi Chen, Qiao Chen, Qiao-Yi Chen, Qiaoli Chen, Qiaoling Chen, Qichen Chen, Qifang Chen, Qihui Chen, Qili Chen, Qinfen Chen, Qing Chen, Qing-Hui Chen, Qing-Juan Chen, Qing-Wei Chen, Qingao Chen, Qingchao Chen, Qingchuan Chen, Qingguang Chen, Qinghao Chen, Qinghua Chen, Qingjiang Chen, Qingjie Chen, Qingliang Chen, Qingmei Chen, Qingqing Chen, Qingqiu Chen, Qingshi Chen, Qingxing Chen, Qingyang Chen, Qingyi Chen, Qinian Chen, Qinsheng Chen, Qinying Chen, Qiong Chen, Qiongyun Chen, Qiqi Chen, Qitong Chen, Qiu Jing Chen, Qiu-Jing Chen, Qiu-Sheng Chen, Qiuchi Chen, Qiuhong Chen, Qiujing Chen, Qiuli Chen, Qiuwen Chen, Qiuxia Chen, Qiuxiang Chen, Qiuxuan Chen, Qiuyun Chen, Qiwei Chen, Qixian Chen, Qu Chen, Quan Chen, Quanjiao Chen, Quanwei Chen, Qunxiang Chen, R Chen, Ran Chen, Ranyun Chen, Ray-Jade Chen, Ren-Hui Chen, Renjin Chen, Renwei Chen, Renyu Chen, Robert Chen, Roger Chen, Rong Chen, Rong-Hua Chen, Rongfang Chen, Rongfeng Chen, Rongrong Chen, Rongsheng Chen, Rongyuan Chen, Roufen Chen, Rouxi Chen, Ru Chen, Rucheng Chen, Ruey-Hwa Chen, Rui Chen, Rui-Fang Chen, Rui-Min Chen, Rui-Pei Chen, Rui-Zhen Chen, Ruiai Chen, Ruibing Chen, Ruijing Chen, Ruijuan Chen, Ruilin Chen, Ruimin Chen, Ruiming Chen, Ruiqi Chen, Ruisen Chen, Ruixiang Chen, Ruixue Chen, Ruiying Chen, Rujun Chen, Runfeng Chen, Runsen Chen, Runsheng Chen, Ruofan Chen, Ruohong Chen, Ruonan Chen, Ruoyan Chen, Ruoying Chen, S Chen, S N Chen, S Pl Chen, S-D Chen, Sai Chen, San-Yuan Chen, Sean Chen, Sen Chen, Shali Chen, Shan Chen, Shanchun Chen, Shang-Chih Chen, Shang-Hung Chen, Shangduo Chen, Shangsi Chen, Shangwu Chen, Shangzhong Chen, Shanshan Chen, Shanyuan Chen, Shao-Ke Chen, Shao-Peng Chen, Shao-Wei Chen, Shao-Yu Chen, Shao-long Chen, Shaofei Chen, Shaohong Chen, Shaohua Chen, Shaokang Chen, Shaokun Chen, Shaoliang Chen, Shaotao Chen, Shaoxing Chen, Shaoze Chen, Shasha Chen, She Chen, Shen Chen, Shen-Ming Chen, Sheng Chen, Sheng-Xi Chen, Sheng-Yi Chen, Shengdi Chen, Shenghui Chen, Shenglan Chen, Shengnan Chen, Shengpan Chen, Shengyu Chen, Shengzhi Chen, Shi Chen, Shi-Qing Chen, Shi-Sheng Chen, Shi-Yi Chen, Shi-You Chen, Shibo Chen, Shih-Jen Chen, Shih-Pin Chen, Shih-Yin Chen, Shih-Yu Chen, Shilan Chen, Shiming Chen, Shin-Wen Chen, Shin-Yu Chen, Shipeng Chen, Shiqian Chen, Shiqun Chen, Shirui Chen, Shiuhwei Chen, Shiwei Chen, Shixuan Chen, Shiyan Chen, Shiyao Chen, Shiyi Chen, Shiyu Chen, Shou-Tung Chen, Shoudeng Chen, Shoujun Chen, Shouzhen Chen, Shu Chen, Shu-Fen Chen, Shu-Gang Chen, Shu-Hua Chen, Shu-Jen Chen, Shuai Chen, Shuai-Bing Chen, Shuai-Ming Chen, Shuaijie Chen, Shuaijun Chen, Shuaiyin Chen, Shuaiyu Chen, Shuang Chen, Shuangfeng Chen, Shuanghui Chen, Shuchun Chen, Shuen-Ei Chen, Shufang Chen, Shufeng Chen, Shuhai Chen, Shuhong Chen, Shuhuang Chen, Shuhui Chen, Shujuan Chen, Shuliang Chen, Shuming Chen, Shunde Chen, Shuntai Chen, Shunyou Chen, Shuo Chen, Shuo-Bin Chen, Shuoni Chen, Shuqin Chen, Shuqiu Chen, Shuting Chen, Shuwen Chen, Shuyi Chen, Shuying Chen, Si Chen, Si-Ru Chen, Si-Yuan Chen, Si-Yue Chen, Si-guo Chen, Sien-Tsong Chen, Sifeng Chen, Sihui Chen, Sijia Chen, Sijuan Chen, Sili Chen, Silian Chen, Siping Chen, Siqi Chen, Siqin Chen, Sisi Chen, Siteng Chen, Siting Chen, Siyi Chen, Siyu Chen, Siyu S Chen, Siyuan Chen, Siyue Chen, Size Chen, Song Chen, Song-Mei Chen, Songfeng Chen, Suet N Chen, Suet Nee Chen, Sufang Chen, Suipeng Chen, Sulian Chen, Suming Chen, Sun Chen, Sung-Fang Chen, Suning Chen, Sunny Chen, Sy-Jou Chen, Syue-Ting Chen, Szu-Chi Chen, Szu-Chia Chen, Szu-Chieh Chen, Szu-Han Chen, Szu-Yun Chen, T Chen, Tai-Heng Chen, Tai-Tzung Chen, Tailai Chen, Tan-Huan Chen, Tan-Zhou Chen, Tania Chen, Tao Chen, Tian Chen, Tianfeng Chen, Tianhang Chen, Tianhong Chen, Tianhua Chen, Tianpeng Chen, Tianran Chen, Tianrui Chen, Tiantian Chen, Tianzhen Chen, Tielin Chen, Tien-Hsing Chen, Ting Chen, Ting-Huan Chen, Ting-Tao Chen, Ting-Ting Chen, Tingen Chen, Tingtao Chen, Tingting Chen, Tom Wei-Wu Chen, Tong Chen, Tongsheng Chen, Tse-Ching Chen, Tse-Wei Chen, TsungYen Chen, Tuantuan Chen, Tzu-An Chen, Tzu-Chieh Chen, Tzu-Ju Chen, Tzu-Ting Chen, Tzu-Yu Chen, Tzy-Yen Chen, Valerie Chen, W Chen, Wai Chen, Wan Jun Chen, Wan-Tzu Chen, Wan-Yan Chen, Wan-Yi Chen, Wanbiao Chen, Wanjia Chen, Wanjun Chen, Wanling Chen, Wantao Chen, Wanting Chen, Wanyin Chen, Wei Chen, Wei J Chen, Wei Ning Chen, Wei-Cheng Chen, Wei-Cong Chen, Wei-Fei Chen, Wei-Hao Chen, Wei-Hui Chen, Wei-Kai Chen, Wei-Kung Chen, Wei-Lun Chen, Wei-Min Chen, Wei-Peng Chen, Wei-Ting Chen, Wei-Wei Chen, Wei-Yu Chen, Wei-xian Chen, Weibo Chen, Weican Chen, Weichan Chen, Weicong Chen, Weihao Chen, Weihong Chen, Weihua Chen, Weijia Chen, Weijie Chen, Weili Chen, Weilun Chen, Weina Chen, Weineng Chen, Weiping Chen, Weiqin Chen, Weiqing Chen, Weirui Chen, Weisan Chen, Weitao Chen, Weitian Chen, Weiwei Chen, Weixian Chen, Weixin Chen, Weiyi Chen, Weiyong Chen, Wen Chen, Wen-Chau Chen, Wen-Jie Chen, Wen-Pin Chen, Wen-Qi Chen, Wen-Tsung Chen, Wen-Yi Chen, Wenbiao Chen, Wenbing Chen, Wenfan Chen, Wenfang Chen, Wenhao Chen, Wenhua Chen, Wenjie Chen, Wenjun Chen, Wenlong Chen, Wenqin Chen, Wensheng Chen, Wenshuo Chen, Wentao Chen, Wenting Chen, Wentong Chen, Wenwen Chen, Wenwu Chen, Wenxi Chen, Wenxing Chen, Wenxu Chen, Willian Tzu-Liang Chen, Wu-Jun Chen, Wu-Xian Chen, Wuyan Chen, X Chen, X R Chen, X Steven Chen, Xi Chen, Xia Chen, Xia-Fei Chen, Xiaguang Chen, Xiameng Chen, Xian Chen, Xian-Kai Chen, Xianbo Chen, Xiancheng Chen, Xianfeng Chen, Xiang Chen, Xiang-Bin Chen, Xiang-Mei Chen, XiangFan Chen, Xiangding Chen, Xiangjun Chen, Xiangli Chen, Xiangliu Chen, Xiangmei Chen, Xiangna Chen, Xiangning Chen, Xiangqiu Chen, Xiangyu Chen, Xiankai Chen, Xianmei Chen, Xianqiang Chen, Xianxiong Chen, Xianyue Chen, Xianze Chen, Xianzhen Chen, Xiao Chen, Xiao-Chen Chen, Xiao-Hui Chen, Xiao-Jun Chen, Xiao-Lin Chen, Xiao-Qing Chen, Xiao-Quan Chen, Xiao-Wei Chen, Xiao-Yang Chen, Xiao-Ying Chen, Xiao-chun Chen, Xiao-he Chen, Xiao-ping Chen, Xiaobin Chen, Xiaobo Chen, Xiaochang Chen, Xiaochun Chen, Xiaodong Chen, Xiaofang Chen, Xiaofen Chen, Xiaofeng Chen, Xiaohan Chen, Xiaohong Chen, Xiaohua Chen, Xiaohui Chen, Xiaojiang S Chen, Xiaojie Chen, Xiaojing Chen, Xiaojuan Chen, Xiaojun Chen, Xiaokai Chen, Xiaolan Chen, Xiaole L Chen, Xiaolei Chen, Xiaoli Chen, Xiaolin Chen, Xiaoling Chen, Xiaolong Chen, Xiaolu Chen, Xiaomeng Chen, Xiaomin Chen, Xiaona Chen, Xiaonan Chen, Xiaopeng Chen, Xiaoping Chen, Xiaoqian Chen, Xiaoqing Chen, Xiaorong Chen, Xiaoshan Chen, Xiaotao Chen, Xiaoting Chen, Xiaowan Chen, Xiaowei Chen, Xiaowen Chen, Xiaoxiang Chen, Xiaoxiao Chen, Xiaoyan Chen, Xiaoyang Chen, Xiaoyin Chen, Xiaoyong Chen, Xiaoyu Chen, Xiaoyuan Chen, Xiaoyun Chen, Xiatian Chen, Xihui Chen, Xijun Chen, Xikun Chen, Ximei Chen, Xin Chen, Xin-Jie Chen, Xin-Ming Chen, Xin-Qi Chen, Xinan Chen, Xing Chen, Xing-Lin Chen, Xing-Long Chen, Xing-Zhen Chen, Xingdong Chen, Xinghai Chen, Xingxing Chen, Xingyi Chen, Xingyong Chen, Xingyu Chen, Xinji Chen, Xinlin Chen, Xinpu Chen, Xinqiao Chen, Xinwei Chen, Xinyan Chen, Xinyang Chen, Xinyi Chen, Xinyu Chen, Xinyuan Chen, Xinyue Chen, Xinzhuo Chen, Xiong Chen, Xiqun Chen, Xiu Chen, Xiu-Juan Chen, Xiuhui Chen, Xiujuan Chen, Xiuli Chen, Xiuping Chen, Xiuxiu Chen, Xiuyan Chen, Xixi Chen, Xiyao Chen, Xiyu Chen, Xu Chen, Xuan Chen, Xuancai Chen, Xuanjing Chen, Xuanli Chen, Xuanmao Chen, Xuanwei Chen, Xuanxu Chen, Xuanyi Chen, Xue Chen, Xue-Mei Chen, Xue-Qing Chen, Xue-Xin Chen, Xue-Yan Chen, Xue-Ying Chen, XueShu Chen, Xuechun Chen, Xuefei Chen, Xuehua Chen, Xuejiao Chen, Xuejun Chen, Xueli Chen, Xueling Chen, Xuemei Chen, Xuemin Chen, Xueqin Chen, Xueqing Chen, Xuerong Chen, Xuesong Chen, Xueting Chen, Xueyan Chen, Xueying Chen, Xufeng Chen, Xuhui Chen, Xujia Chen, Xun Chen, Xuxiang Chen, Xuxin Chen, Xuzhuo Chen, Y Chen, Y D I Chen, Y Eugene Chen, Y M Chen, Y P Chen, Y S Chen, Y U Chen, Y-D I Chen, Y-D Ida Chen, Ya Chen, Ya-Chun Chen, Ya-Nan Chen, Ya-Peng Chen, Ya-Ting Chen, Ya-xi Chen, Yafang Chen, Yafei Chen, Yahong Chen, Yajie Chen, Yajing Chen, Yajun Chen, Yalan Chen, Yali Chen, Yan Chen, Yan Jie Chen, Yan Q Chen, Yan-Gui Chen, Yan-Jun Chen, Yan-Ming Chen, Yan-Qiong Chen, Yan-yan Chen, Yanan Chen, Yananlan Chen, Yanbin Chen, Yanfei Chen, Yanfen Chen, Yang Chen, Yang-Ching Chen, Yang-Yang Chen, Yangchao Chen, Yanghui Chen, Yangxin Chen, Yanhan Chen, Yanhua Chen, Yanjie Chen, Yanjing Chen, Yanli Chen, Yanlin Chen, Yanling Chen, Yanming Chen, Yann-Jang Chen, Yanping Chen, Yanqiu Chen, Yanrong Chen, Yanru Chen, Yanting Chen, Yanyan Chen, Yanyun Chen, Yanzhu Chen, Yanzi Chen, Yao Chen, Yao-Shen Chen, Yaodong Chen, Yaosheng Chen, Yaowu Chen, Yau-Hung Chen, Yaxi Chen, Yayun Chen, Yazhuo Chen, Ye Chen, Ye-Guang Chen, Yeh Chen, Yelin Chen, Yen-Chang Chen, Yen-Chen Chen, Yen-Cheng Chen, Yen-Ching Chen, Yen-Fu Chen, Yen-Hao Chen, Yen-Hsieh Chen, Yen-Jen Chen, Yen-Ju Chen, Yen-Lin Chen, Yen-Ling Chen, Yen-Ni Chen, Yen-Rong Chen, Yen-Teen Chen, Yewei Chen, Yi Chen, Yi Feng Chen, Yi-Bing Chen, Yi-Chun Chen, Yi-Chung Chen, Yi-Fei Chen, Yi-Guang Chen, Yi-Han Chen, Yi-Hau Chen, Yi-Heng Chen, Yi-Hong Chen, Yi-Hsuan Chen, Yi-Hui Chen, Yi-Jen Chen, Yi-Lin Chen, Yi-Ru Chen, Yi-Ting Chen, Yi-Wen Chen, Yi-Yung Chen, YiChung Chen, YiPing Chen, Yian Chen, Yibing Chen, Yibo Chen, Yidan Chen, Yiding Chen, Yidong Chen, Yiduo Chen, Yifa Chen, Yifan Chen, Yifang Chen, Yifei Chen, Yih-Chieh Chen, Yihao Chen, Yihong Chen, Yii-Der Chen, Yii-Der I Chen, Yii-Derr Chen, Yii-der Ida Chen, Yijiang Chen, Yijun Chen, Yike Chen, Yilan Chen, Yilei Chen, Yili Chen, Yilin Chen, Yiming Chen, Yin-Huai Chen, Ying Chen, Ying-Cheng Chen, Ying-Hsiang Chen, Ying-Jie Chen, Ying-Jung Chen, Ying-Lan Chen, Ying-Ying Chen, Yingchun Chen, Yingcong Chen, Yinghui Chen, Yingji Chen, Yingjie Chen, Yinglian Chen, Yingting Chen, Yingxi Chen, Yingying Chen, Yingyu Chen, Yinjuan Chen, Yintong Chen, Yinwei Chen, Yinzhu Chen, Yiru Chen, Yishan Chen, Yisheng Chen, Yitong Chen, Yixin Chen, Yiyin Chen, Yiyun Chen, Yizhi Chen, Yong Chen, Yong-Jun Chen, Yong-Ping Chen, Yong-Syuan Chen, Yong-Zhong Chen, YongPing Chen, Yongbin Chen, Yongfa Chen, Yongfang Chen, Yongheng Chen, Yonghui Chen, Yongke Chen, Yonglu Chen, Yongmei Chen, Yongming Chen, Yongning Chen, Yongqi Chen, Yongshen Chen, Yongshuo Chen, Yongxing Chen, Yongxun Chen, You-Ming Chen, You-Xin Chen, You-Yue Chen, Youhu Chen, Youjia Chen, Youmeng Chen, Youran Chen, Youwei Chen, Yu Chen, Yu-Bing Chen, Yu-Cheng Chen, Yu-Chi Chen, Yu-Chia Chen, Yu-Chuan Chen, Yu-Fan Chen, Yu-Fen Chen, Yu-Fu Chen, Yu-Gen Chen, Yu-Han Chen, Yu-Hui Chen, Yu-Ling Chen, Yu-Ming Chen, Yu-Pei Chen, Yu-San Chen, Yu-Si Chen, Yu-Ting Chen, Yu-Tung Chen, Yu-Xia Chen, Yu-Xin Chen, Yu-Yang Chen, Yu-Ying Chen, Yuan Chen, Yuan-Hua Chen, Yuan-Shen Chen, Yuan-Tsong Chen, Yuan-Yuan Chen, Yuan-Zhen Chen, Yuanbin Chen, Yuanhao Chen, Yuanjia Chen, Yuanjian Chen, Yuanli Chen, Yuanqi Chen, Yuanwei Chen, Yuanwen Chen, Yuanyu Chen, Yuanyuan Chen, Yubin Chen, Yucheng Chen, Yue Chen, Yue-Lai Chen, Yuebing Chen, Yueh-Peng Chen, Yuelei Chen, Yuewen Chen, Yuewu Chen, Yuexin Chen, Yuexuan Chen, Yufei Chen, Yufeng Chen, Yuh-Lien Chen, Yuh-Ling Chen, Yuh-Min Chen, Yuhan Chen, Yuhang Chen, Yuhao Chen, Yuhong Chen, Yuhui Chen, Yujie Chen, Yule Chen, Yuli Chen, Yulian Chen, Yulin Chen, Yuling Chen, Yulong Chen, Yulu Chen, Yumei Chen, Yun Chen, Yun-Ju Chen, Yun-Tzu Chen, Yun-Yu Chen, Yundai Chen, Yunfei Chen, Yunfeng Chen, Yung-Hsiang Chen, Yung-Wu Chen, Yunjia Chen, Yunlin Chen, Yunn-Yi Chen, Yunqin Chen, Yunshun Chen, Yunwei Chen, Yunyun Chen, Yunzhong Chen, Yunzhu Chen, Yupei Chen, Yupeng Chen, Yuping Chen, Yuqi Chen, Yuqin Chen, Yuqing Chen, Yuquan Chen, Yurong Chen, Yushan Chen, Yusheng Chen, Yusi Chen, Yuting Chen, Yutong Chen, Yuxi Chen, Yuxian Chen, Yuxiang Chen, Yuxin Chen, Yuxing Chen, Yuyan Chen, Yuyang Chen, Yuyao Chen, Z Chen, Zan Chen, Zaozao Chen, Ze-Hui Chen, Ze-Xu Chen, Zechuan Chen, Zemin Chen, Zetian Chen, Zexiao Chen, Zeyu Chen, Zhanfei Chen, Zhang-Liang Chen, Zhang-Yuan Chen, Zhangcheng Chen, Zhanghua Chen, Zhangliang Chen, Zhanglin Chen, Zhangxin Chen, Zhanjuan Chen, Zhao Chen, Zhao-Xia Chen, ZhaoHui Chen, Zhaojun Chen, Zhaoli Chen, Zhaolin Chen, Zhaoran Chen, Zhaowei Chen, Zhaoyao Chen, Zhe Chen, Zhe-Ling Chen, Zhe-Sheng Chen, Zhe-Yu Chen, Zhebin Chen, Zhehui Chen, Zhelin Chen, Zhen Bouman Chen, Zhen Chen, Zhen-Hua Chen, Zhen-Yu Chen, Zhencong Chen, Zhenfeng Chen, Zheng Chen, Zheng-Zhen Chen, Zhenghong Chen, Zhengjun Chen, Zhengling Chen, Zhengming Chen, Zhenguo Chen, Zhengwei Chen, Zhengzhi Chen, Zhenlei Chen, Zhenyi Chen, Zhenyue Chen, Zheping Chen, Zheren Chen, Zhesheng Chen, Zheyi Chen, 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
Lishan Zeng, Xin Chen, Kai Kang +12 more · 2025 · Cardiovascular research · Oxford University Press · added 2026-04-24
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. Thi Show more
Effective therapeutic drugs for calcific aortic valve disease (CAVD) are lacking, although its incidence has been increasing over the past decade and is predicted to continue rising in the future. This study aimed to explore the role and potential mechanisms of liver X receptor α (LXRα) in CAVD, which offers a promising approach for treating CAVD. Osteogenic stimulation was performed following which a substantial downregulation of LXRα was observed in human calcific aortic valves and valvular interstitial cells. Further functional investigations revealed that silencing LXRα exacerbated calcification both in vitro and in vivo. We showed that LXRα suppressed the protein kinase R-like endoplasmic reticulum kinase/eukaryotic initiation factor 2/activating transcription factor 4 pathway, which controls endoplasmic reticulum stress (ERS) and promotes osteogenic differentiation, thereby slowing the course of CAVD. Our research offers fresh perspectives on how LXRα controls the pathophysiology of CAVD via regulating ERS. The findings suggest that targeting LXRα is a potential treatment strategy for treating aortic valve calcification. Show less
no PDF DOI: 10.1093/cvr/cvaf044
NR1H3
Chengyu Wang, Hongyu Zhao, Yujie Zhou +10 more · 2025 · Frontiers in plant science · Frontiers · added 2026-04-24
The color of rice leaves are important agronomic traits that directly influence the proportion of sunlight energy utilization and ultimately affect the yield and quality, so it is crucial to excavate Show more
The color of rice leaves are important agronomic traits that directly influence the proportion of sunlight energy utilization and ultimately affect the yield and quality, so it is crucial to excavate the mechanism of regulating rice leave color. To investigate the molecular mechanism that triggers the purple color in rice leaf, phenotypic characterization and genome-wide transcriptome analysis were conducted using the japonica rice cultivar nipponbare (Nip) and its two purple leaf mutants, A total of 2247, 5484, 4525, 2103, 4375 and7029DEGs (differentially expressed genes) were identified in nip-a vs These results not only revealed the molecular mechanism triggering leaf purple color in the rice mutants Show less
📄 PDF DOI: 10.3389/fpls.2025.1584423
LPL
Zijian Wang, Radek Zenkl, Latifa Greche +33 more · 2025 · Plant phenomics (Washington, D.C.) · Elsevier · added 2026-04-24
Computer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimeter ground sampling distance enable the detection an Show more
Computer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimeter ground sampling distance enable the detection and tracking of plant features, including size, shape, and colour. Although today's AI-driven foundation models segment almost any object in an image, they still fail for complex plant canopies. To improve model performance, the global wheat dataset consortium assembled a diverse set of images from experiments around the globe. After the head detection dataset (GWHD), the new dataset targets a full semantic segmentation (GWFSS) of organs (leaves, stems and spikes) covering all developmental stages. Images were collected by 11 institutions using a wide range of imaging setups. Two datasets are provided: i) a set of 1096 diverse images in which all organs were labelled at the pixel level, and (ii) a dataset of 52,078 images without annotations available for additional training. The labelled set was used to train segmentation models based on DeepLabV3Plus and Segformer. Our Segformer model performed slightly better than DeepLabV3Plus with a mIOU for leaves and spikes of ca. 90 ​%. However, the precision for stems with 54 ​% was rather lower. The major advantages over published models are: i) the exclusion of weeds from the wheat canopy, ii) the detection of all wheat features including necrotic and senescent tissues and its separation from crop residues. This facilitates further development in classifying healthy vs. unhealthy tissue to address the increasing need for accurate quantification of senescence and diseases in wheat canopies. Show less
📄 PDF DOI: 10.1016/j.plaphe.2025.100084
LPA
Yuxin Fan, Jiandong Yuan, Lichun Dong +12 more · 2025 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims Show more
Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims to investigate its safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) in Chinese healthy volunteers. A randomized, double-blind, placebo-controlled and dose-escalation Phase I study was conducted as follows: a single dose (2.5 mg) and once-weekly administration for 2 weeks to reach target doses (5, 10 and 15 mg) by titration. A total of 40 volunteers received at least one dose of BGM0504 or placebo. The PK profile of BGM0504 was investigated over a wide dose range and supported once-weekly administration. It was observed that C BGM0504 was generally safe and well tolerated with favourable PK profile and potential role in weight loss was also confirmed. These findings support subsequent development of BGM0504 for type 2 diabetes mellitus (T2DM) and obesity. Show less
no PDF DOI: 10.1111/dom.16203
GIPR
Xin Lou, Yihua Shi, Yi Qin +13 more · 2025 · Cell death & disease · Nature · added 2026-04-24
Temozolomide (TMZ) is a first-class clinical drug for patients with pancreatic neuroendocrine tumors (pNETs). However, the therapeutic effects of TMZ are limited because of the chemoresistance of pNET Show more
Temozolomide (TMZ) is a first-class clinical drug for patients with pancreatic neuroendocrine tumors (pNETs). However, the therapeutic effects of TMZ are limited because of the chemoresistance of pNET cells, which has not been fully elucidated. Here, we demonstrate that the reprogramming of lipid metabolism regulates TMZ resistance in patients with pNETs. Via integrated multiomics sequencing, apolipoprotein E (APOE), which is a critical lipid carrier, was identified to be highly increased in the tissue and blood plasma of patients in the TMZ treatment group compared with those in the control group. Further mechanistic studies revealed that TMZ treatment promotes the expression and secretion of APOE, which binds to its surface receptor known as scavenger receptor class B member 1 (SCARB1), thus leading to increased uptake of exogenous lipids to remodel cellular lipid metabolism and activation of the homologous recombination repair (HRR) pathway to repair DNA damage via the β-catenin-BRCA1/2 axis. The interruption of APOE-mediated lipid uptake via a SCARB1 inhibitor named as block lipid transport-1 (BLT-1), suppressed TMZ-induced HRR activation and sensitized tumor cells to TMZ treatment in preclinical models, including PDCs, PDOs, and PDXs. In addition, APOE expression levels were shown to be positively correlated with BRCA1/2 expression in clinical specimens and online databases. This study reveals a new functional role of APOE that leads to chemoresistance in patient treatment. Our findings suggest the potential of combined administration of BLT-1 to overcome TMZ chemoresistance and improve treatments for patients with pNETs. Show less
📄 PDF DOI: 10.1038/s41419-025-08317-1
APOE
Honglei Ji, Haijun Zhu, Ziliang Wang +7 more · 2025 · Environmental research · Elsevier · added 2026-04-24
Prenatal exposure to bisphenol analogs (BPs) may pose hazards to offspring's health; however, their underlying mechanisms remain to be elucidated. DNA methylation, a major epigenetic mechanism, may be Show more
Prenatal exposure to bisphenol analogs (BPs) may pose hazards to offspring's health; however, their underlying mechanisms remain to be elucidated. DNA methylation, a major epigenetic mechanism, may be involved in early programming following environmental disturbances. In this prospective study, we investigated associations between prenatal BPs exposure and the placental DNA methylation levels of 14 candidate genes in the peroxisome proliferator-activated receptor (PPAR) signaling pathway among 205 mother-infant pairs and explored the potential mediating role of the DNA methylation in the association of prenatal BPs exposure with anthropometric measurements of infants aged 1 year. We observed a general pattern that prenatal BPs exposure was associated with the DNA hypomethylation of candidate genes, with associations consistently and notably observed for PPAR α (PPARA), retinoid X receptor α (RXRA), acetyl-CoA acyltransferase 1, and acyl-CoA dehydrogenase medium chain (ACADM) in linear regression and Bayesian kernel machine regression. Both models identified bisphenol F (BPF) as the predominant compound. We found inverse associations between the placental DNA methylation levels of most candidate genes, such as PPARA, RXRA, ACADM, and nuclear receptor subfamily 1 group H member 3 (NR1H3), and the length-for-age z-score, arm circumference-for-age z-score, subscapular skinfold-for-age z-score, and abdominal skinfold thickness of the infants. The DNA methylation levels of RXRA and NR1H3 could mediate the associations between prenatal BPF exposure and increased infant anthropometric measurements, with mediating portions ranging from 23.02% to 30.53%. Our findings shed light on the potential mechanisms underlying the effects of prenatal BPs exposure on infant growth and call for urgent actions for risk assessment and regulation of BPF. Future cohort studies with larger sample sizes are warranted to confirm our findings. Show less
no PDF DOI: 10.1016/j.envres.2024.120476
NR1H3
Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB
Jun Chen, Xinyan Yang, Manman Cui +7 more · 2025 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
Male germline development is crucial for the proper establishment of spermatogonial stem cell pool and life-long production of spermatozoa, but the full-term developmental profiling of human male germ Show more
Male germline development is crucial for the proper establishment of spermatogonial stem cell pool and life-long production of spermatozoa, but the full-term developmental profiling of human male germline is not fully understood. Here, by integrating 92,488 human testicular cells spanning from six-week-old embryos to old men, we constructed a comprehensive human male germ cell atlas. Further analysis found that the precursor of undifferentiated spermatogonia underwent regulatory network reconfiguration starting from week 7 post-fertilization, accompanied by WNT6-FZD3/LRP6-JUN/MYC signaling axis. And JUN and MYC were revealed to be candidate core transcription factors that might inhibit spermatogonia differentiation. In addition, the activation of ANGPTL signaling played a role in the maintenance of human spermatogonial stem cells. Finally, by interrogating the scRNA-seq datasets from idiopathic non-obstructive azoospermia (iNOA) patients, we identified several iNOA-dysregulated genes such as CAPN3, FTMT, IZUMO2 and LACE1, which were significantly down-regulated in round spermatids of iNOA patients. Collectively, our work established an atlas of human male germ cell development, revealing the factors that might regulate male germline development and providing iNOA-dysregulated genes for future clinical diagnosis. Show less
no PDF DOI: 10.1016/j.bbadis.2025.167918
ANGPTL4
Muhammad Umar, Liping Tong, Hongting Jin +2 more · 2025 · Genes & diseases · Elsevier · added 2026-04-24
Clubfoot, medically termed congenital talipes equinovarus (CTEV), is a prevalent musculoskeletal birth defect, affecting approximately 0.3% of all live births. This serious congenital anomaly results Show more
Clubfoot, medically termed congenital talipes equinovarus (CTEV), is a prevalent musculoskeletal birth defect, affecting approximately 0.3% of all live births. This serious congenital anomaly results from structural abnormalities in the foot and lower leg, leading to abnormal positioning of the ankle and foot joints. This review provides a comprehensive overview of the causative factors associated with CTEV and evaluates current therapeutic approaches. Although variations in genes encoding contractile proteins of skeletal myofibers have been proposed as contributors to the etiology of CTEV, no definitive candidate genes have been conclusively linked to increased risk. However, genes such as Show less
📄 PDF DOI: 10.1016/j.gendis.2025.101690
AXIN1
Xue Chen, Yuyue Ren, Yinglan Jin +7 more · 2025 · Annals of hematology · Springer · added 2026-04-24
Myeloid/lymphoid neoplasms with eosinophilia and tyrosine kinase gene fusions (MLN-TK) are rare hematologic malignancies defined by recurrent kinase gene rearrangements.
📄 PDF DOI: 10.1007/s00277-025-06481-0
FGFR1
Zhenwei Dai, Shu Jing, Haiyan Hu +8 more · 2025 · Brain and behavior · Wiley · added 2026-04-24
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult w Show more
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult women infected with HPV. This study aimed to adapt and validate the HPVsStigma scale (HPV-SS) in the Chinese context. A cross-sectional study was conducted from December 2024 to February 2025 among 501 HPV-infected women in Shenzhen, China. The HPV-SS was adapted from a 12-item HIV stigma scale. Demographic characteristics, HPV-related variables, and data on mental health were collected. Factor analyses (FA) were used to assess the scale's factorial structure, reliability, and validity. The bi-factor model was used to determine the score-reporting method of the scale. Item response theory (IRT) was employed to assess the relationship between participants' stigma levels and scale scores. Latent profile analysis (LPA) was conducted to classify the participants with different HPV stigma characteristics and determine the optimal cut-off value for HPV-SS. FA showed that the 3-factor model (personalized stigma, public-disclosure concerns, and negative self-image) had the best fit among the nested models, with good reliability and validity. The bi-factor model analysis indicated that the total scale score was more meaningful than dimension scores. IRT analysis confirmed that higher HPV-SS scores represented higher stigma levels. LPA identified a 2-class model as optimal, and the optimal cut-off value of the scale for high HPV stigma was 35. This study validated the 12-item HPV-SS for Chinese women infected with HPV, with good reliability and validity. The scale can be used to evaluate HPV stigma levels, facilitating targeted interventions to improve cervical cancer prevention and the psychological well-being of affected women. Show less
📄 PDF DOI: 10.1002/brb3.71044
LPA
Zuojian Hu, Yingji Chen, Jielin Lei +11 more · 2025 · Cell death and differentiation · Nature · added 2026-04-24
SIRT7, one of the least studied members of the Sirtuins family, is an NAD
no PDF DOI: 10.1038/s41418-025-01490-y
BCKDK
Bin Xiao, Junhao Xiao, Xiaoying Xiao +5 more · 2025 · Journal of inorganic biochemistry · Elsevier · added 2026-04-24
Amyloid deposition of human islet amyloid polypeptide (hIAPP) is closely linked to the pathogenesis and progression of type 2 diabetes mellitus (T2DM). Developing effective inhibitors to suppress hIAP Show more
Amyloid deposition of human islet amyloid polypeptide (hIAPP) is closely linked to the pathogenesis and progression of type 2 diabetes mellitus (T2DM). Developing effective inhibitors to suppress hIAPP aggregation holds significant therapeutic potential for the prevention and treatment of T2DM. Recent researches indicate that both heme and lithospermic acid (LPA) can inhibit hIAPP aggregation. However, heme is prone to induce protein damage under oxidative stress, while LPA exhibits limited inhibitory efficacy despite its antioxidant properties. To overcome these limitations, we aimed to develop a dual-component inhibitor comprising heme and LPA. thioflavin T (ThT) fluorescence, transmission electron microscopy (TEM), circular dichroism (CD) and gel electrophoresis were combined to observe the inhibitory efficacy of heme-LPA co-formulation on hIAPP aggregation. The results demonstrate that LPA and heme can synergistically inhibit hIAPP aggregation. The inhibitory effect of heme-LPA co-formulation on hIAPP aggregation is significantly stronger than that of either component alone. The heme-LPA not only prevents the complete conversion of hIAPP into β-sheet fibrillar structures but also maintains its active monomeric conformation for extended periods. Furthermore, peroxidase activity assays revealed that the presence of LPA significantly reduces the peroxidase activity of heme in a concentration-dependent manner and attenuates peptide nitration damage under H₂O₂-NO₂ Show less
no PDF DOI: 10.1016/j.jinorgbio.2025.113087
LPA
Karin Leander, Yan Q Chen, Max Vikström +4 more · 2025 · Arteriosclerosis, thrombosis, and vascular biology · added 2026-04-24
Binding of ANGPTL (angiopoietin-like protein)-3 to ANGPTL8 generates a protein complex (ANGPTL3/8) that strongly inhibits LPL (lipoprotein lipase) activity, as compared with ANGPTL3 alone, suggesting Show more
Binding of ANGPTL (angiopoietin-like protein)-3 to ANGPTL8 generates a protein complex (ANGPTL3/8) that strongly inhibits LPL (lipoprotein lipase) activity, as compared with ANGPTL3 alone, suggesting that ANGPTL3/8 concentrations are critical for the regulation of circulation lipoprotein concentrations and subsequent increased coronary heart disease (CHD) risk. To test this hypothesis in humans, we evaluated the associations of circulating free ANGPTL3 and ANGPTL3/8 complex concentrations with lipoprotein concentrations and CHD risk in 2 prospective cohort studies. Fasting blood samples were obtained in conjunction with the baseline evaluation of 9479 subjects from 2 population-based Swedish cohorts of middle-aged men and women. Standard biochemical blood analyses, including all lipid/lipoprotein measurements, were performed in these samples at baseline. Additional serum samples were stored at -80 °C and used at a later stage for ANGPTL3 and ANGPTL3/8 concentration measurements. Information about incident CHD was obtained for both cohorts by matching to the Swedish National Patient Register and the Cause of Death Register. ANGPTL3 concentrations showed modest, positive associations with all lipoprotein concentrations but were not associated with CHD risk. In contrast, ANGPTL3/8 concentrations were associated in both cohorts with an atherogenic lipoprotein profile (characterized by increased triglyceride and LDL [low-density lipoprotein] concentrations and reduced HDL [high-density lipoprotein] concentrations). In the combined cohort, ANGPTL3/8 was associated with increased CHD risk. Hazard ratio per 1 SD increase was 1.10 (95% CI, 1.03-1.17) after adjustment for age, sex, cohort, smoking, and hypertension. Elevated concentrations of ANGPTL3/8, but not ANGPTL3, are associated with an atherogenic lipoprotein profile and increased CHD risk in humans. Show less
no PDF DOI: 10.1161/ATVBAHA.124.321308
LPL
X L Su, J W Wu, P L Wang +7 more · 2025 · Zhonghua bing li xue za zhi = Chinese journal of pathology · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112151-20250517-00349
FGFR1
Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff +122 more · 2025 · Nature communications · Nature · added 2026-04-24
Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff, Heather M Highland, Nathalie Chami, Hanfei Xu, Zhe Wang, Kendra R Ferrier, Geetha Chittoor, Navya Shilpa Josyula, Mariah Meyer, Shreyash Gupta, Xihao Li, Zilin Li, Matthew A Allison, Diane M Becker, Lawrence F Bielak, Joshua C Bis, Meher Preethi Boorgula, Donald W Bowden, Jai G Broome, Erin J Buth, Christopher S Carlson, Kyong-Mi Chang, Sameer Chavan, Yen-Feng Chiu, Lee-Ming Chuang, Matthew P Conomos, Dawn L DeMeo, Mengmeng Du, Ravindranath Duggirala, Celeste Eng, Alison E Fohner, Barry I Freedman, Melanie E Garrett, Xiuqing Guo, Chris Haiman, Benjamin D Heavner, Bertha Hidalgo, James E Hixson, Yuk-Lam Ho, Brian D Hobbs, Donglei Hu, Qin Hui, Chii-Min Hwu, Rebecca D Jackson, Deepti Jain, Rita R Kalyani, Sharon L R Kardia, Tanika N Kelly, Ethan M Lange, Michael LeNoir, Changwei Li, Loic Le Marchand, Merry-Lynn N McDonald, Caitlin P McHugh, Alanna C Morrison, Take Naseri, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Jeffrey O'Connell, Christopher J O'Donnell, Nicholette D Palmer, James S Pankow, James A Perry, Ulrike Peters, Michael H Preuss, D C Rao, Elizabeth A Regan, Sefuiva M Reupena, Dan M Roden, Jose Rodriguez-Santana, Colleen M Sitlani, Jennifer A Smith, Hemant K Tiwari, Ramachandran S Vasan, Zeyuan Wang, Daniel E Weeks, Jennifer Wessel, Kerri L Wiggins, Lynne R Wilkens, Peter W F Wilson, Lisa R Yanek, Zachary T Yoneda, Wei Zhao, Sebastian Zöllner, Donna K Arnett, Allison E Ashley-Koch, Kathleen C Barnes, John Blangero, Eric Boerwinkle, Esteban G Burchard, April P Carson, Daniel I Chasman, Yii-der Ida Chen, Joanne E Curran, Myriam Fornage, Victor R Gordeuk, Jiang He, Susan R Heckbert, Lifang Hou, Marguerite R Irvin, Charles Kooperberg, Ryan L Minster, Braxton D Mitchell, Mehdi Nouraie, Bruce M Psaty, Laura M Raffield, Alexander P Reiner, Stephen S Rich, Jerome I Rotter, M Benjamin Shoemaker, Nicholas L Smith, Kent D Taylor, Marilyn J Telen, Scott T Weiss, Yingze Zhang, Nancy Heard-Costa, Yan V Sun, Xihong Lin, L Adrienne Cupples, Leslie A Lange, Ching-Ti Liu, Ruth J F Loos, Kari E North, Anne E Justice Show less
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data fr Show more
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10 Show less
no PDF DOI: 10.1038/s41467-025-58420-2
POC5
Chi Chen, Yimeng Gu, Junfei Xu +9 more · 2025 · Scientific reports · Nature · added 2026-04-24
Apolipoprotein B (apoB) can be measured directly and accurately, and better predicts atherogenic risk than conventional lipid profiles. We aimed to investigate whether total and regional (trunk or leg Show more
Apolipoprotein B (apoB) can be measured directly and accurately, and better predicts atherogenic risk than conventional lipid profiles. We aimed to investigate whether total and regional (trunk or leg) fat deposits are associated with apoB levels in general US adults. 4585 participants were enrolled from the US National Health and Nutritional Surveys from 2011 to 2016. Overall and regional body fat were measured using dual-energy X-ray absorptiometry. The associations of total and regional fat with apoB levels were evaluated using linear regression models. Following adjustment for demographic, lifestyle, and clinical risk factors, whole-body fat percentage was positively associated with apoB levels. Additionally, percent trunk fat was positively associated (highest vs. lowest tertile beta = 17.73 for men and 14.89 for women, respectively), whereas percent leg fat was inversely associated (highest vs. lowest tertile beta = - 4.84 for men and - 6.55 for women, respectively) with apoB levels in both sexes. The association for trunk fat and leg fat remained significant after further adjustment for body mass index or waist circumference. Higher percent trunk fat combined with lower percent leg fat was associated with particularly higher apoB. In conclusion, among general US adults, both elevated trunk fat and reduced leg fat are associated with higher levels of apoB. Further research is required to elucidate the underlying pathophysiological mechanisms. Show less
📄 PDF DOI: 10.1038/s41598-025-10502-3
APOB
Jiahao Liu, Hongqing Zhu, Ziying Wang +6 more · 2025 · IEEE journal of biomedical and health informatics · IEEE · added 2026-04-24
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, Show more
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemic stroke lesions in CT images, consisting of a segmentation branch and a prompt-aware branch. The segmentation branch uses an encoder-decoder network as the backbone to identify lesions, where the encoder fuses CT image features with prompt features from the prompt-aware branch. To enhance semantic feature extraction and reduce the impact of cerebral structural details, we introduce a cross-collaboration dynamic connection (CCDC) module to link the encoder and decoder. The prompt-aware branch includes a learnable prompt (LP) block to incorporate cerebral prior knowledge, and the prompt-aware encoder (PAE) combines the LP block with multi-level features from the segmentation branch for more precise representation. Additionally, we propose a CLIP-enhance textual prompt (CETP) module that utilizes the CLIP text encoder to generate specialized convolutional parameters for the segmentation head. These parameters are tailored to the unique characteristics of each input image, improving segmentation performance. Qualitative and quantitative studies reveal that DCTP-Net outperforms the current state-of-the-art, IS-Net, with Dice score increases of 3.9% on AISD and 3.8% on ISLES2018, demonstrating its superiority in EIL segmentation. Show less
no PDF DOI: 10.1109/JBHI.2024.3471627
CETP
Meng-Wei Lin, Chung-Hao Li, Hung-Tsung Wu +4 more · 2025 · Journal of clinical medicine · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/jcm14217599
ANGPTL4
Lei Chen, Lingxin Zheng, Yuan Qin +5 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Cardiac hypertrophy is an independent risk factor and the primary predictor of heart failure (HF). Mitochondria are crucial for the shift from hypertrophy to heart failure. The expression of fibroblas Show more
Cardiac hypertrophy is an independent risk factor and the primary predictor of heart failure (HF). Mitochondria are crucial for the shift from hypertrophy to heart failure. The expression of fibroblast growth factor 21 (FGF21), a cardioprotective factor, is increased in patients with cardiac hypertrophy but fails to prevent heart failure. Additionally, the molecular mechanism through which FGF21 exerts its beneficial effects on hypertrophic myocardial mitochondria remains unclear. Our study investigated the effect of FGF21 on cardiac hypertrophy, elucidating its mechanism of action through the enhancement of mitophagy-mediated cardioprotection. A transverse aortic constriction (TAC) model and a phenylephrine (PE) model were applied to explore the effect and mechanism of FGF21. P62-mediated mitophagy inducer (PMI) and rapamycin (Rapa) were used to confirm that FGF21-regulated mitophagy under overload pressure conditions. FGF21 knockout markedly exacerbated TAC-induced cardiac function damage, mitochondrial damage, and mitophagy impairment. In vitro, FGF21 knockdown aggravated PE-induced cardiomyocyte hypertrophy and mitophagy dysfunction. FGF21 treatment promoted mitophagy in the TAC and PE models, but this effect was abolished in the absence of PTEN-induced putative kinase 1 (PINK1). The increase in PINK1 expression induced by Rapa can rescue impaired cardiac function and mitophagy impairment in FGF21-deficient TAC mice. Similarly, PMI enhances mitophagy, which inhibits damage to cardiac functions. A further study revealed that the expression of fibroblast growth factor receptor 1 (FGFR1) and FGF21 was opposite in heart failure. Knockdown of FGFR1 inhibited FGF21-mediated mitophagy. FGF21 promotes PINK1-mediated mitophagy to attenuate cardiac hypertrophy, and mismatched FGFR1 expression may hamper the beneficial effect of FGF21 on cardiac hypertrophy. Show less
no PDF DOI: 10.1016/j.jare.2025.10.053
FGFR1
Eiki Kimura, Sharif Ahmed, Haijiao Chen +1 more · 2025 · Journal of applied toxicology : JAT · Wiley · added 2026-04-24
For workers in the industry, occupational exposure to indium compounds induces pulmonary disorders, such as interstitial pneumonia. Moreover, lung cancer has been reported in both humans and rodents e Show more
For workers in the industry, occupational exposure to indium compounds induces pulmonary disorders, such as interstitial pneumonia. Moreover, lung cancer has been reported in both humans and rodents exposed to indium compounds by inhalation. However, the biological mechanism underlying indium-induced disorders is poorly understood. Epithelial-mesenchymal transition (EMT)-the cellular process of losing epithelial and acquiring mesenchymal characteristics-is linked to fibrosis and cancer progression. Therefore, we examined whether indium exposure elicits EMT in vitro. A549 human alveolar epithelial cells treated with indium chloride at doses of 0-500 μg/mL for 24 h were used to analyze EMT marker expression and cytoarchitecture. Significant downregulation of CDH1 mRNA expression as an epithelial marker after treatments at 125, 250, and 500 μg/mL occurred dose-dependently; conversely, the mesenchymal marker SNAI1 was upregulated. Consistent with mRNAs, the expression levels of EMT marker proteins (i.e., E-cadherin, ZO1, SNAIL, and Vimentin) were changed significantly by treatment. While NF-κB signaling was activated in treated cells, indium-dependent changes of CDH1 and SNAI1 mRNA expression were not affected by BAY 11-7082, an NF-κB inhibitor, suggesting that NF-κB activation may be dispensable for indium-induced EMT. Fibroblast-like morphological characteristics, such as actin stress fiber formation and cell elongation, along with deconstruction of cell-cell adhesion complexes, were observed in treated cells. Overall, our study is the first to demonstrate that EMT is caused by indium compounds. This will contribute biologically to understanding the mechanism of EMT induction and clinically to unveiling the pathophysiology of indium lung disease. Show less
no PDF DOI: 10.1002/jat.4848
SNAI1
Maozhong Yao, Keyan Zhong, Xinbin Zheng +4 more · 2025 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
Endothelial-to-mesenchymal transition (EndMT) induced by dysfunctional pulmonary artery endothelial cells (PAECs) is regarded as an initiating and pivotal factor in pulmonary hypertension (PH). This s Show more
Endothelial-to-mesenchymal transition (EndMT) induced by dysfunctional pulmonary artery endothelial cells (PAECs) is regarded as an initiating and pivotal factor in pulmonary hypertension (PH). This study focuses on identifying a novel therapeutic target for regulating EndMT in PH. A comprehensive analysis of 2 hypoxic PAECs datasets yielded 310 overlapping upregulated and 229 downregulated differentially expressed genes (DEGs). These upregulated DEGs were primarily enriched in HIF-1 signalling pathway and glycolysis/gluconeogenesis, while downregulated only in spliceosome, as indicated by KEGG. Through PPI network analysis and the application of MCC algorithms, 5 hub genes were identified among these upregulated DEGs: GAPDH, LDHA, ALDOA, PFKL, and PFKP. Their enrichment in the 2 aforementioned pathways was confirmed by cross-pathway DEGs analysis and ClueGo. Among the hub genes, LDHA was chosen as the key gene based upon expression and correlation analysis of the validation set from PH patients. Subsequent GSEA also revealed the enrichment of LDHA in these 2 pathways. Additionally, the increased expression of LDHA protein in tissues and cells was confirmed, and the elevated enzymatic activity of LDHA in clinical serum samples was also verified. From 2 online databases, 4 LDHA inhibitors were filtered out, and the stable binding between the inhibitors and the LDHA protein was confirmed through molecular docking and molecular dynamics simulation. Finally, the experimental results indicated that one of the inhibitors FX11 reversed EndMT by inhibiting the lactate-SNAI1 axis, thereby alleviating hypoxia-induced PH. The potential of LDHA as a therapeutic target for PH by modulating EndMT was proposed in this study. Show less
no PDF DOI: 10.1111/jcmm.70692
SNAI1
Ruze Tang, Yanming Chen, Dong Wan +9 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
[This corrects the article DOI: 10.3389/fonc.2025.1694881.].
📄 PDF DOI: 10.3389/fonc.2025.1748919
FGFR1
Yadong Zheng, Kaili Chen, Shuo Zhang +6 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Atherosclerosis (AS), a chronic inflammatory condition of the vasculature, is a major contributor to cardiovascular morbidity. Yaoshi Tongyuan Tablet (YTT) is a food-medicine homology (FMH) formulatio Show more
Atherosclerosis (AS), a chronic inflammatory condition of the vasculature, is a major contributor to cardiovascular morbidity. Yaoshi Tongyuan Tablet (YTT) is a food-medicine homology (FMH) formulation containing A combination of network pharmacology, ultra-performance liquid chromatography coupled with Q Exactive Orbitrap mass spectrometry (UPLC-QE-MS), and molecular docking was employed to predict potential bioactive compounds and their molecular targets. ApoE Integrated analyses revealed kaempferol, isorhamnetin, and quercetin as central bioactive molecules acting on AKT1, a key node within the PI3K/Akt signaling cascade. YTT ameliorates atherosclerosis by counteracting dyslipidemia and inflammation, primarily through modulation of the PI3K/Akt/NF-κB pathway. This study offers novel integrative insights into the anti-atherogenic properties of YTT and pinpoint crucial bioactive constituents worthy of further pharmacological investigation. Show less
📄 PDF DOI: 10.3389/fphar.2025.1710585
APOE
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Kang-Chih Fan, Szu-Chi Chen, I-Weng Yen +7 more · 2025 · Archives of medical science : AMS · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANG Show more
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANGPTL4 levels are observed in diabetic and obese individuals. However, the potential link between ANGPTL4 and diabetes- or obesity-related complications remains uncertain. This study aimed to explore whether plasma ANGPTL4 level could serve as a predictor of cancer mortality, cardiovascular mortality, and all-cause mortality in a community-based cohort. A community-based cohort study was conducted, where fasting plasma ANGPTL4 concentrations were measured at baseline, and vital status was ascertained through linkage with the National Health Insurance Research Database in Taiwan. During a 10.46-year follow-up period, 29 (2.49%) of the 1163 participants died. Subjects within the highest tertile of plasma ANGPTL4 levels exhibited the lowest survival rate. In unadjusted models, plasma ANGPTL4 significantly predicted all-cause mortality, cancer mortality, and cardiovascular or cancer-related mortality. Upon adjustment for confounders including age, sex, smoking, body mass index (BMI), hypertension, diabetes mellitus (DM), and renal function, each standard deviation increase in plasma ANGPTL4 was associated with HRs of 1.35 (95% CI: 1.01-1.80, Plasma ANGPTL4 emerges as a promising biomarker capable of predicting 10-year mortality and enhancing risk prediction beyond established risk factors. Show less
📄 PDF DOI: 10.5114/aoms/189504
ANGPTL4
Shirui Jiang, Ailin Zhang, Jiegang Deng +5 more · 2025 · Frontiers in pediatrics · Frontiers · added 2026-04-24
Pediatric primary cardiomyopathies (PCMs) are rare diseases with complex causes and nonspecific treatment. The influence of electrolytes and amino acids (AAs) on cardiomyopathies has not been extensiv Show more
Pediatric primary cardiomyopathies (PCMs) are rare diseases with complex causes and nonspecific treatment. The influence of electrolytes and amino acids (AAs) on cardiomyopathies has not been extensively studied. This study aimed to explore clinical characteristics and the usage of electrolytes and AAs in children with PCMs. Children diagnosed with PCMs who had genetic test reports were included. Relevant information was collected and processed, and clinical characteristics and mutated genes were clarified. Gene databases were searched to explore related electrolytes and AAs in the treatment of PCMs. The effect of calcium was explored in children with DCM. Paired samples T tests and nonparametric Wilcoxon signed-rank tests were performed for comparison between before and after using calcium. In this study, 27 children with gene test results were enrolled to perform gene-related analysis. The median age was 2.5 years old. Mutated genes were collected, including pathogenic, likely pathogenic, uncertain significance, and other mutations. The most frequently mutated genes related to dilated cardiomyopathy (DCM) were For children with DCM, calcium supplements may be beneficial. AAs, including serine, cysteine, and arginine, could be used for supplementary treatment in children with DCM and HCM. Show less
📄 PDF DOI: 10.3389/fped.2025.1631632
MYBPC3
Jia Min Chen, Yan Wang, Yan Shi · 2025 · Clinical, cosmetic and investigational dermatology · added 2026-04-24
Omega-3 polyunsaturated fatty acids (PUFAs) are potential targets for the treatment of skin diseases due to their anti-inflammatory and immunomodulatory effects. By leveraging a genetic approach known Show more
Omega-3 polyunsaturated fatty acids (PUFAs) are potential targets for the treatment of skin diseases due to their anti-inflammatory and immunomodulatory effects. By leveraging a genetic approach known as Mendelian randomization (MR), we sought to determine the causal impact of PUFAs on the likelihood of developing skin diseases among individuals of European ancestry. We integrated GWAS data from the CHARGE consortium and UK Biobank to identify genetic instruments for omega-3 PUFAs and desaturase activity, using two-sample MR to assess their associations with six skin diseases. Elevated levels of omega-3 fatty acids were found to substantially lower the probability of experiencing atopic dermatitis (0.92, [0.85,0.98]), while increased DPA levels correlated with a substantial increase in the probability of squamous cell carcinoma occurrence (2.25, [1.29,3.92]). Increased DHA levels were also associated with a reduced risk of atopic dermatitis (0.90, [0.84,0.96]) but increased the risk of solar dermatitis (1.38, [1.09,1.73]). In addition, tissue-type specific MR analysis revealed that elevated FADS1 expression in fibroblasts significantly inhibited atopic dermatitis development (β = -0.181, [-0.276,-0.0853]), while elevated FADS2 expression in non-sun-exposed skin tissues was associated with a reduced risk of squamous cell carcinoma (β = -0.562, [-0.833,-0.029]). Conversely, heightened FADS2 expression was strongly linked to a greater likelihood of developing atopic dermatitis in both sun-exposed and sun-protected skin areas (β = 0.107, [0.0348,0.179]; β = 0.192, [0.114,0.0270], respectively). This study reveals the causal role of omega-3 PUFAs and FADS expression in specific tissues and blood in skin diseases. These findings underscore the potential of PUFA biosynthesis pathways as therapeutic targets for skin disease interventions. Show less
📄 PDF DOI: 10.2147/CCID.S524519
FADS1
Deying Liu, Jiaxin Li, Chan Xu +7 more · 2025 · Human molecular genetics · Oxford University Press · added 2026-04-24
Mutations in four genes encoding the outer ring complex of nuclear pore complexes (NPCs), NUP85, NUP107, NUP133 and NUP160, cause monogenic steroid-resistant nephrotic syndrome (SRNS). Knockout of NUP Show more
Mutations in four genes encoding the outer ring complex of nuclear pore complexes (NPCs), NUP85, NUP107, NUP133 and NUP160, cause monogenic steroid-resistant nephrotic syndrome (SRNS). Knockout of NUP85, NUP107, or NUP133 in immortalized human podocytes activates CDC42, an important effector of SRNS pathogenesis. However, it is unknown whether or not loss of NUP160 dysregulates CDC42 in the podocytes. Here, we generated a podocyte-specific Nup160 knockout mouse model with double-fluorescent (mT/mG) Cre reporter genes using CRISPR/Cas9 and Cre/loxP technologies. We investigated nephrotic syndrome-associated phenotypes in the Nup160podo-/- mice, and performed single-cell transcriptomic and proteomic analysis of glomerular suspension cells and cultured primary podocytes, respectively. The Nup160podo-/- mice exhibited progressive proteinuria and fusion of podocyte foot processes. We found decreased Cdc42 protein and normal Cdc42 transcriptional level in the podocytes of the Nup160podo-/- mice using analysis of single-cell transcriptomes and proteomes. We subsequently observed that Cdc42 protein decreased in both kidney tissues and cultured primary podocytes of the Nup160podo-/- mice, although Cdc42 mRNA levels were elevated in the cultured primary podocytes of the Nup160podo-/- mice. We also found that Cdc42 activity was significantly reduced in the cultured primary podocytes of the Nup160podo-/- mice. In conclusion, loss of Nup160 dysregulated Cdc42 in the podocytes of the Nup160podo-/- mice with proteinuria and fusion of podocyte foot processes. Our findings suggest that the dysregulation of CDC42 may contribute to the pathogenesis of SRNS in patients with mutations in NUP160. Show less
no PDF DOI: 10.1093/hmg/ddaf064
NUP160
Binlong Chen, Zhiying Huang, Zhongkun Cai +5 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
For small ruminants, meat quality-an economically significant characteristic-results from the combined effects of genetic, dietary, and physiological elements. However, the contribution of gastrointes Show more
For small ruminants, meat quality-an economically significant characteristic-results from the combined effects of genetic, dietary, and physiological elements. However, the contribution of gastrointestinal (GI) tract gene expression to meat quality remains unclear. Here, we performed bulk RNA-seq on 130 samples from Liangshan Black Sheep and Meigu Black Goats, including 10 GI tract segments and semitendinosus muscle, integrating these data with measurements of amino acid composition, fatty acid profiles, and volatile flavor compounds. We found distinct, segment-specific transcriptional programs across the GI tract, with major functional shifts at the rumen-reticulum, omasum-abomasum, and abomasum-duodenum transitions. In the ileum and jejunum, genes involved in lipid metabolism showed links to fatty acid profiles, whereas genes governing amino acid metabolism in the small intestine were connected to the amino acid composition of muscle. Cecum- and colon-enriched genes were linked to flavor precursor biosynthesis. Species-specific differences revealed that sheep muscle contained higher levels of key amino acids (Asp, Glu, Hyp, Cys, Tyr), whereas goats showed higher α-linolenic acid and other polyunsaturated fatty acids. This work establishes a gut-muscle transcriptomic axis in small ruminants, identifying candidate genes (e.g., Show less
📄 PDF DOI: 10.3389/fvets.2025.1687258
APOC3