👤 Jiaqing Chen

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2981
Articles
1996
Name variants
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, 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
Gang Huang, Jiani Liu, Zhipeng Cheng +11 more · 2026 · Frontiers in cell and developmental biology · Frontiers · added 2026-04-24
This study aims to elucidate the role of Enterococcusin the progression from inflammatory bowel disease to colorectal cancer (CRC), with a focus on identifying key metabolites and host genes regulated Show more
This study aims to elucidate the role of Enterococcusin the progression from inflammatory bowel disease to colorectal cancer (CRC), with a focus on identifying key metabolites and host genes regulated by Enterococcusand their influence on CRC development. Using the database gutMGene, gutMDisorder and MACdb, we mined the key metabolites and human genes. We acquired the activated genes (panel 1) and inhibited genes (panel 2), and metabolite associated genes (MAGs, panel 3). Subsequent analyses included protein-protein interaction (PPI) network construction, functional enrichment, differential expression and survival analysis in CRC, and immune infiltration assessment. We screened 12 activated genes (Panel1: Show less
📄 PDF DOI: 10.3389/fcell.2026.1793350
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Yue Shi, Yongkang Yang, Xianghao Guo +11 more · 2026 · EBioMedicine · Elsevier · added 2026-04-24
Early pregnancy loss (EPL), a spontaneous death of the embryo or foetus occurring within the first trimester, is a major challenge for human reproduction with profound adverse consequences for women's Show more
Early pregnancy loss (EPL), a spontaneous death of the embryo or foetus occurring within the first trimester, is a major challenge for human reproduction with profound adverse consequences for women's health. Currently, reliable blood-based biomarkers for EPL remain limited. Therefore, there is an urgent need to discover novel biomarkers for EPL using a multi-omics-based approach to facilitate early detection and timely management. In the discovery cohort, 40 patients with EPL and 40 healthy pregnancies (HP) at 7-13 weeks of gestation were enrolled. Serum proteins and metabolites were assayed by Olink® technology and ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS), respectively. Biomarkers were defined by false discovery rate (FDR) < 0.05 and fold change (FC) > 1.2. Random forest (RF) and logistic regression (LR) models incorporating selected biomarkers were employed to develop diagnostic models for EPL. In the external validation cohort, we prospectively enrolled 142 pregnancies at 7-10 gestational weeks, including 47 subjects who subsequently developed EPL and 95 pregnancies with full-term birth. Serum levels of selected biomarkers were quantified by ELISA. The combined proteomics and metabolomics screening identified 26 proteins and 21 metabolites significantly changed in the EPL group and tightly associated with EPL-related clinical phenotypes, with functional enrichment in immunoregulation and lipid oxidation processes. Moreover, integrating serum levels of angiopoietin-like 4 (ANGPTL4), programmed death-ligand 1 (PD-L1), neutrophil%, and lymphocyte% achieved an AUC of 0.944 (95% CI: 0.835-1.000) in the random forest model and 0.954 (95% CI: 0.875-1.000) in the logistic regression model to discriminate EPL from HP. Importantly, this four-biomarker model achieved an AUC of 0.857 (95% CI: 0.747-0.968) in the random survival forest model and a C-index of 0.804 (95% CI: 0.685-0.973) in the validation cohort for EPL prediction. Our integrative omics study reveals a panel of potential circulating biomarkers for EPL, which further offer mechanistic insights into EPL pathogenesis, including impaired maternal immune tolerance and dysregulated lipid metabolism pathways. Moreover, the newly identified biomarkers exhibit promising diagnostic and predictive performance for EPL, underscoring its clinical translational value for human reproduction and maternal-foetal health. This study was supported by Research Grants Council (RGC) Germany/Hong Kong Joint Research Scheme (G-CUHK415/25), 1+1+1 CUHK-CUHK(SZ)-GDST Joint Collaboration Fund (2025A0505000077), CUHK HOPE BWCH Collaborative Medical Research Fund (CF2025002), Shenzhen Medical Research Fund (C2501040), and Shenzhen Science and Technology Program (RCYX20210609104608036). Show less
📄 PDF DOI: 10.1016/j.ebiom.2026.106253
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Fei Zhu, Xingyun Xie, Cong Wang +4 more · 2026 · Frontiers in immunology · Frontiers · added 2026-04-24
PIK3CA is one of the most frequently mutated genes in cervical cancer (CC). However, its clinical utility is hampered by paradoxical treatment-dependent outcomes, restricting its application in precis Show more
PIK3CA is one of the most frequently mutated genes in cervical cancer (CC). However, its clinical utility is hampered by paradoxical treatment-dependent outcomes, restricting its application in precision oncology. To address this issue, we constructed a high-resolution single-cell transcriptomic atlas of the CC tumor microenvironment. It was found that PIK3CA mutations induce a dichotomous TME, simultaneously associated with marked T-cell inflammation and resistance to adaptive immune responses. Malignant epithelial subsets induce CD8 Show less
📄 PDF DOI: 10.3389/fimmu.2026.1780752
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Veerabrahma P Seshachalam, Ita N Sari, Kane Toh +35 more · 2026 · JHEP reports : innovation in hepatology · Elsevier · added 2026-04-24
Hepatocellular carcinoma (HCC) exhibits diverse aetiologies and molecular heterogeneity, with a median 5-year overall survival of <70% due to high recurrence rates following curative-intent surgery. T Show more
Hepatocellular carcinoma (HCC) exhibits diverse aetiologies and molecular heterogeneity, with a median 5-year overall survival of <70% due to high recurrence rates following curative-intent surgery. This study investigated the complex tumour microenvironment (TME) in HCC and explored interactions between various cell types and their roles in disease recurrence. Using a multi-omics approach on multi-region samples of surgically resected HCC from the PLANet 1.0 cohort (NCT03267641), we performed spatial transcriptomics on 17 tissue samples from four patients and bulk RNA sequencing on 329 sectors from 90 patients. Findings were validated using immunofluorescence and multiplex immunohistochemistry. Our analysis revealed extensive intra- and intertumour gene expression heterogeneity and identified a specific subset of endothelial cells (ECs), INTS6 INTS6 The spatial co-localisation of cell types plays a significant role in the recurrence of hepatocellular carcinoma. In this study, we have pinpointed a particular group of endothelial cells, known as INTS6+ endothelial cells, which are spatially colocalised with tumour cells and enriched in microvascular invasion regions in patients experiencing recurrence. These discoveries highlight novel therapeutic targets that focus on endothelial cell interactions within the tumour microenvironment to prevent recurrence and enhance overall patient survival. Show less
📄 PDF DOI: 10.1016/j.jhepr.2026.101790
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Xinpeng Li, Siqi Jin, Hong Hu +18 more · 2026 · Frontiers in microbiology · Frontiers · added 2026-04-24
Protein feed resource shortage is a major constraint to the sustainable development of the livestock industry and a bottleneck problem hindering the growth of the Tibetan pig industry in China's Qingh Show more
Protein feed resource shortage is a major constraint to the sustainable development of the livestock industry and a bottleneck problem hindering the growth of the Tibetan pig industry in China's Qinghai-Tibet Plateau region. Walnut meal, rich in protein, holds promise as a substitute for soybean meal. However, the effects and underlying mechanisms of walnut meal substitution on Tibetan pigs in Diqing remain unclear. The study showed that substituting 50% of soybean meal with walnut meal in the diet of Diqing Tibetan pigs significantly reduced backfat thickness and increased intramuscular fat content ( This study reveals that walnut meal can serve as a substitute for soybean meal, and a 50% substitution ratio is conducive to intramuscular fat deposition in Diqing Tibetan pigs. The findings provide valuable insights for the development and application of unconventional protein feed resources, and offer new perspectives for the production of marbled pork. Show less
📄 PDF DOI: 10.3389/fmicb.2026.1794046
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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
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Xun Chen, Jian Wan, Zhengwu Jiang +4 more · 2026 · Neoplasia (New York, N.Y.) · Elsevier · added 2026-04-24
Hepatocellular carcinoma (HCC) exhibits high recurrence rates and limited therapeutic options. Endothelial cell-specific molecule 1 (ESM1) and angiopoietin-like 4 (ANGPTL4) are implicated in tumor pro Show more
Hepatocellular carcinoma (HCC) exhibits high recurrence rates and limited therapeutic options. Endothelial cell-specific molecule 1 (ESM1) and angiopoietin-like 4 (ANGPTL4) are implicated in tumor progression, yet their synergistic role in HCC lipid metabolism and angiogenesis remains unexplored. We integrated multi-omics approaches, including RNA sequencing, metabolomics, and immunoprecipitation-mass spectrometry, in HCC cell lines and patient-derived xenograft models. Key experiments involved Co-IP, Western blotting, tube formation assays, and clinical tissue microarray analysis to validate the ESM1-ANGPTL4-FASN-trioleate axis. ESM1 and ANGPTL4 formed a positive feedback loop, stabilizing fatty acid synthase (FASN) to promote trioleate synthesis. Trioleate activated the NF-κB/IL-17 pathway in HCC cells and upregulated CD99 in endothelial cells, driving angiogenesis. In vivo, ESM1/ANGPTL4 knockdown suppressed tumor growth, which was rescued by trioleate supplementation. Clinical data revealed elevated ESM1/ANGPTL4 expression in bevacizumab-resistant HCC, correlating with poor prognosis. The ESM1-ANGPTL4-FASN-trioleate axis orchestrates metabolic reprogramming and endothelial activation, representing a promising therapeutic target. Future studies should explore combination therapies targeting this axis and overcoming bevacizumab resistance in HCC. Show less
📄 PDF DOI: 10.1016/j.neo.2026.101298
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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
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Jia-Qi Lin, Xia-Fei Chen, Jia-Hao Zhu +4 more · 2026 · Experimental eye research · Elsevier · added 2026-04-24
Keratoconus (KC) is a progressive disorder of corneal thinning characterized by responses in the extracellular matrix and cellular interactions. This study used bioinformatics methods to identify key Show more
Keratoconus (KC) is a progressive disorder of corneal thinning characterized by responses in the extracellular matrix and cellular interactions. This study used bioinformatics methods to identify key genes involved in KC development and in anoikis and endoplasmic reticulum (ER) stress. KC and control datasets from the GEO database were analyzed to identify differentially expressed genes (DEGs). These were cross-referenced with anoikis and ER stress-related genes from Genecards. Functional enrichment, immune infiltration analysis, and machine learning techniques (LASSO, Random Forest) were used to identify candidate molecular signatures, which were then validated in an animal model. We identified 46 DEGs associated with anoikis and 41 DEGs related to ER stress. Functional analysis linked them to apoptosis and IL-17 signaling. Five key molecular signatures were identified: CDKN1A, MCL1, PTGS2, PTHLH, and ANGPTL4. The expression of ANGPTL4, CDKN1A, and MCL1 was consistent in the animal model. These genes are associated with inflammatory and oxidative stress responses. Twelve potential therapeutic drugs were predicted. This study identifies five candidate molecular signatures for KC related to anoikis and ER stress, offering insights into KC pathogenesis and potential targeted therapies. Show less
no PDF DOI: 10.1016/j.exer.2026.110910
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Hisashi Makino, Masato Kasahara, Ryuzo Takashima +12 more · 2026 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
The precise mechanism of sodium glucose co-transporter 2 (SGLT2) inhibitor on reno-protective effect has been still unclear. In this study, we hypothesised that SGLT2 inhibitor prevents diabetic kidne Show more
The precise mechanism of sodium glucose co-transporter 2 (SGLT2) inhibitor on reno-protective effect has been still unclear. In this study, we hypothesised that SGLT2 inhibitor prevents diabetic kidney disease via reduction of hypoxia-induced factors. In this multicenter, prospective, randomised, double blinded clinical trial, people with type 2 diabetes and microalbuminuria were randomised equally to empagliflozin (10 mg/day) (n = 40) and placebo (n = 39) and followed 24 weeks. The primary endpoint was change in urinary albumin creatinine ratio (ACR) and urinary liver type fatty acid binding protein (L-FABP) excretion from baseline to 24 weeks. Major secondary outcome was change in serum vascular endothelial growth factor (VEGF), angiopoietin-like proteins 2 (ANGPTL2), angiopoietin-like proteins 4 (ANGPTL4), and adrenomedullin (AM) levels. Although the reduction of ACR was significantly greater in the empagliflozin group than the placebo group at 4 and 12 weeks, the difference of change at 24 weeks between the two groups was not statistically significant (Empagliflozin group-Placebo group: -0.3643, 95% CI: -0.7571 to 0.0285, p = 0.0686). There was no difference in urinary L-FABP excretion between the empagliflozin and placebo groups. Serum VEGF and ANGPTL2 decreased significantly more in the empagliflozin group, whereas there were no significant differences in AM and ANGPTL4. These results demonstrated that empagliflozin partially suppressed the hypoxia-induced angiogenic factors overproduction in addition to a declining trend in ACR in the early stage of diabetic kidney disease, which might contribute to the mechanisms of reno-protective effects of this agent (jRCTs051200147). Show less
📄 PDF DOI: 10.1111/dom.70485
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Muhai Deng, Yunsheng Jiang, Zhiyu Chen +5 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
The incidence of osteoarthritis (OA) is strongly correlated with aging. It has been shown that the accumulation of senescent cells in the synovium precedes chondrocyte senescence and cartilage degrada Show more
The incidence of osteoarthritis (OA) is strongly correlated with aging. It has been shown that the accumulation of senescent cells in the synovium precedes chondrocyte senescence and cartilage degradation, suggesting that synovial cell senescence plays a key role in OA pathogenesis. This study aimed to investigate the mechanisms underlying synovial cell senescence and its influence on intercellular communication within the joint. Using multiplex immunofluorescence, gene regulatory network reconstruction, and single-cell RNA sequencing analyses, we identified senescent cells and characterized the senescence-associated secretory phenotype in the synovium. A series of in vivo and in vitro functional experiments is conducted to elucidate the mechanisms of fibroblast senescence and its effects on macrophages and chondrocytes. We found that synovial intimal fibroblasts (SIF) display more marked premature senescence compared to other synovial cell types. A specific senescent subpopulation within SIF is identified, and we demonstrated that the transcription factors EGR1 and ATF3 regulate senescence-related pathways in these cells. Furthermore, we showed that senescent SIF promote M1 macrophage polarization and cartilage degeneration through paracrine secretion of ANGPTL4. Additionally, senescent SIF may facilitate OA progression through direct cell-cell contact with macrophages. Show less
📄 PDF DOI: 10.1002/advs.202518056
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Linhui Zhai, Cui-Cui Liu, Lei Zhao +14 more · 2026 · Protein & cell · Oxford University Press · added 2026-04-24
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune s Show more
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune sites like lymph nodes remain elusive. Here, we performed an in-depth proteomic and phosphoproteomic analysis of a substantial series of breast cancer samples, alongside genomic and transcriptomic evaluations. This cohort encompasses 195 specimens: 65 primary breast tumors, their corresponding normal tissues, and metastatic axillary lymph nodes. We offer an overview of the molecular alterations at the transcriptomic, proteomic, and phosphoproteomic levels during lymph node metastasis. Notably, the findings indicate that regional lymph node metastasis is primarily influenced by proteomic and phosphoproteomic alterations, rather than genomic or transcriptomic changes. We found the ANGPTL4 and HMGB1 could serve as the biomarker of lymph node metastasis. Data analysis and cell experiments involving silencing of the alternative splicing factor HNRNPU demonstrated that alternative splicing plays a significant role in modulating protein expression, phosphorylation profiles and cell proliferation. The key phosphorylation sites, including MARCKSL1-S104 and FKBP15-S320, as well as the upstream kinase PRKCB, were identified as playing crucial roles in breast cancer lymph node metastasis. Targeted intervention of the kinase PRKCB resulted in effectively suppressing the proliferation and metastasis of breast cancer tumor cells. Immune profiling analysis and experimental validation of breast cancer cell cocultured with CD8+ T cell reveals correlations between phosphorylation of MARCKSL1-S104 and FKBP15-S320 with immune checkpoint PD-L1 expression, and their impact on tumor cell apoptosis, suggesting a potential mechanism of immune evasion in metastasis. This study systematically characterizes the molecular landscape and features of primary breast tumors and their matched metastatic lymph nodes. These insights enhance our understanding of early-stage breast cancer metastasis and may pave the way for improved diagnostic tools and targeted therapeutic strategies. Show less
no PDF DOI: 10.1093/procel/pwag002
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Qiong Lu, Qiyue Zheng, Zhaokai Zhou +7 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Bone angiogenesis is important for bone formation and regeneration after bone injury. Endothelial-derived angiogenic factors are key signal transducers in the bone microenvironment and maintain vascul Show more
Bone angiogenesis is important for bone formation and regeneration after bone injury. Endothelial-derived angiogenic factors are key signal transducers in the bone microenvironment and maintain vascular-osteogenic coupling during bone regeneration. CGRP, a bone sensory neuron-derived peptide, contributes to bone formation, but the potential mechanism by which it improves bone regeneration via angiogenesis is unclear. Here, we demonstrate that CGRP may contribute to bone repair in the elderly, as human CGRP levels are inversely proportional to age and proportional to bone mass in clinical data and bulk transcriptome data. Based on single-cell RNA sequencing data and experimental analyses, CGRP is found to promote the angiogenesis of human microvascular endothelial cell line-1 in vitro through the FAK-AKT-VEGF pathway. CGRP gene deletion in mice reduced bone vascular density and bone mass, and delayed angiogenesis and bone regeneration at the bone defect site. Recombinant CGRP restored bone repair after defect introduction. It also promoted Angptl4 secretion by bone vascular endothelial cells, thereby driving osteogenic differentiation of bone marrow mesenchymal stem cells and enhancing bone regeneration after bone injury. Treatment with recombinant Angptl4 enhanced bone healing in a mouse bone defect model. These integrated analysis reveal the important role and mechanism of CGRP in vascular-mediated osteogenesis, suggesting a novel therapeutic strategy for promoting bone regeneration. Show less
📄 PDF DOI: 10.1002/advs.202522295
ANGPTL4
Xi Cheng, Shuzhen Zhao, Mingyi Du +4 more · 2026 · Cytokine · Elsevier · added 2026-04-24
Angiopoietin-like 4 (ANGPTL4) is a hepatokine involved in metabolism and inflammation and has been implicated in oncogenesis, yet its relationship with cancer risk in humans remains unclear. We analyz Show more
Angiopoietin-like 4 (ANGPTL4) is a hepatokine involved in metabolism and inflammation and has been implicated in oncogenesis, yet its relationship with cancer risk in humans remains unclear. We analyzed 35,716 cancer-free UK Biobank participants with baseline plasma ANGPTL4. Multivariable Cox models and restricted cubic splines assessed associations with 24 site-specific incident cancers; bidirectional two-sample Mendelian randomization (MR) evaluated causality. During a median follow-up of 12.5 years, 9304 incident cancer cases occurred. Compared with the lowest quartile (Q1), the higher quartiles (Q2, Q3, and Q4) of ANGPTL4 levels were significantly associated with the risks of ten cancers, including cancers of the bladder, breast, cervix uteri, colorectum/anus, esophagus, kidney, liver, mesothelial/soft tissues, multiple myeloma, and ovary (hazard ratios ranging from 1.02 to 3.98). Risks generally increased across ANGPTL4 quartiles, and spline analyses supported approximately linear dose-response patterns. Adding ANGPTL4 to an age-sex model improved discrimination across several sites (ΔC-index 0-0.071), with statistical significance observed only for breast cancer. Associations were directionally consistent but heterogeneous by age, sex, and BMI. Forward MR provided no evidence that genetically proxied ANGPTL4 causally increases cancer risk. In reverse MR, genetic liability to liver cancer showed a nominal positive association with circulating ANGPTL4, suggesting ANGPTL4 may be elevated as part of tumor-related biology. Higher circulating ANGPTL4 is associated with increased risk of multiple cancers, with sex-and tissue-specific heterogeneity. Although MR does not support a universal causal role, ANGPTL4 remains a promising pan-cancer biomarker for risk stratification and early prevention. Show less
no PDF DOI: 10.1016/j.cyto.2025.157089
ANGPTL4
Wensheng Chen, Qingshui Wang, Shuyuan Li · 2026 · Biochimica et biophysica acta. General subjects · Elsevier · added 2026-04-24
Lymph node metastasis is a critical prognostic factor in colorectal cancer (CRC). Identifying key genes associated with metastasis can improve risk stratification and treatment strategies. This study Show more
Lymph node metastasis is a critical prognostic factor in colorectal cancer (CRC). Identifying key genes associated with metastasis can improve risk stratification and treatment strategies. This study aimed to identify a gene signature related to lymph node metastasis and investigate the role of NPR3. We analyzed the GSE878211 dataset to identify differentially expressed genes in CRC tissues with and without lymph node metastasis. A lymph node metastasis-related gene signature (LNMRGS) was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The correlation between LNMRGS and clinical indicators, immune microenvironment, and signaling pathways was analyzed. The role of NPR3 was further investigated through in vitro and in vivo experiments. We identified 110 upregulated and 58 downregulated genes in CRC tissues with lymph node metastasis. The LNMRGS, consisting of Integrin Subunit Beta 3 (ITGB3), IQ Motif Containing with AAA Domain 1 (IQCA1), Angiopoietin-Like 4 (ANGPTL4), and Natriuretic Peptide Receptor 3 (NPR3), predicted overall survival in multiple datasets. High LNMRGS was associated with female sex, tumor recurrence, lymph node metastasis, distant metastasis, and KRAS mutations. NPR3 knockdown inhibited proliferation, migration, and invasion of CRC cells in vitro and in vivo, and reduced chemoresistance to 5-fluorouracil (5-FU) and oxaliplatin. The LNMRGS is a robust prognostic signature for CRC. NPR3 plays a key role in metastatic progression and chemoresistance, suggesting it as a potential therapeutic target. Show less
no PDF DOI: 10.1016/j.bbagen.2025.130895
ANGPTL4
Yutong Lin, Danan Wang, Duanbin Li +8 more · 2026 · Atherosclerosis · Elsevier · added 2026-04-24
Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein (ANGPTL) family, is a physiological inhibitor of lipoprotein lipase (LPL), and plays a critical role in lipoprotein and Show more
Angiopoietin-like protein 8 (ANGPTL8), a member of the angiopoietin-like protein (ANGPTL) family, is a physiological inhibitor of lipoprotein lipase (LPL), and plays a critical role in lipoprotein and triglyceride metabolism in response to nutritional cues. ANGPTL8 is implicated in a wide range of systemic and cellular processes and is closely associated with metabolic and cardiovascular diseases (CVD). Circulating ANGPTL8 is primarily secreted by the liver, with adipose tissue as a secondary source. Its expression is regulated by multiple transcription factors and microRNAs, and is responsive to fasting/refeeding states, hormonal signals, and stress conditions. In lipid metabolism, ANGPTL8 forms complexes with ANGPTL3 and ANGPTL4 to modulate LPL activity under fasting and feeding conditions. In glucose metabolism, ANGPTL8 plays a complex role. While some studies suggest it may improve glucose tolerance and insulin resistance, others indicate it could exacerbate glucose metabolism disorders and diabetes, or have no effect. Cardiovascular diseases are intricately linked to metabolic disorders and diseases. Increasing evidence also links ANGPTL8 to various cardiovascular pathologies, including atherosclerosis, hypertension, cardiomyopathy, cardiac hypertrophy, aortic aneurysm, and dissection. Given the strong interplay between metabolic dysregulation and CVDs, elucidating the role of ANGPTL8 in these processes is of significant interest. This review provides a balanced assessment of ANGPTL8's roles in key pathophysiological processes, highlighting its established functions in metabolism alongside its emerging involvement in CVDs. Understanding the diverse functions of ANGPTL8 in various tissues and metabolic states will lead to new opportunities for therapeutic intervention in cardiometabolic disorders. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.120556
ANGPTL4
Cunming Yang, Zhen Ma, Xiao Wang +6 more · 2026 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Xinjiang Brown cattle are an important beef breed in Northwest China. Although multigenerational selective breeding has improved their growth performance, the accompanying molecular adaptations and po Show more
Xinjiang Brown cattle are an important beef breed in Northwest China. Although multigenerational selective breeding has improved their growth performance, the accompanying molecular adaptations and potential physiological trade- ofs remain insufficiently elucidated at the systemic level. This study aimed to decipher the dynamic serum proteomic profiles shaped by both ontogeny and generational selection in Xinjiang Brown cattle, and to identify the associated key proteins and pathways. Serum samples from 18 bulls across three genera- tions (A, B, C) at 3 and 9 months of age were analyzed using Tandem Mass Tag (TMT)-based quantitative proteomics. Under stringent quality control (FDR < 1%), 583 high-confidence proteins were identified. Diferentially expressed proteins (DEPs) were screened using thresholds of |fold change| ≥ 1.2 and This study reveals that the breeding strategy for Xinjiang Brown cattle prioritizes shaping a proteomic landscape that promotes growth and metabolism, potentially at the cost of atten- uated immune-vascular reactivity. The identified panel of candidate proteins pro- vides a molecular framework for evaluating breeding outcomes and designing balanced selection strategies. Follow-up research should further investigate the functions of these candidate proteins and validate their predictive value for health and production performance in independent herds. Show less
📄 PDF DOI: 10.3389/fvets.2026.1723813
APOA4
Ya-Xin Deng, Bao-Jun Ding, Hong-Chun Li +4 more · 2026 · Yi chuan = Hereditas · added 2026-04-24
The
no PDF DOI: 10.16288/j.yczz.25-190
APOA4
Ziyu Ge, Yang Yang, Pei Chen +12 more · 2026 · Biochemical pharmacology · Elsevier · added 2026-04-24
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive Show more
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive anthraquinone derived from Rheum palmatum, exhibits rapid and sustained antidepressant effects in both acute and chronic social defeat stress (CSDS) mouse models. Using quantitative proteomics on prefrontal cortex (PFC) samples from control, CSDS, Rhein-treated, and imipramine-treated cohorts, we identified differentially expressed proteins that revealed Rhein's multi-target regulatory profile. Functional enrichment and clustering analyses indicated that Rhein predominantly restores dysregulated pathways related to lipid metabolism, ribosomal translation, mitochondrial and endoplasmic reticulum (ER) function, and synaptic plasticity, forming a coherent mechanistic axis underlying its therapeutic effects. Comparative analysis with imipramine-treated mice further highlighted Rhein's distinct capacity to modulate organelle homeostasis and synaptic remodeling with greater breadth. Parallel reaction monitoring (PRM) and Western Blotting validated key proteins involved in mitochondrial functions (BNIP1, PISD, MRPL42, MRPS30, LRBA, IGHM), ER homeostasis (ACBD5, APOA4, RPL14), and synaptic plasticity (HDAC1, FAM3C, SSU72). These molecular findings suggest that Rhein exerts its antidepressant effects by restoring the functional integrity of mitochondria and the ER, thereby reprogramming synaptic plasticity. We inferred that this organelle-centered regulation further reinforces its potent modulation through multiple mechanisms and signaling pathways of synaptic plasticity, enabling Rhein to exert antidepressant effects through a coordinated, multi-layered mechanism. Collectively, our findings provide a systems-level mechanistic framework for Rhein's antidepressant efficacy and support its potential as a multi-pathway natural therapeutic, particularly for metabolic subtypes of depression. Show less
no PDF DOI: 10.1016/j.bcp.2025.117548
APOA4
Ye Yang, Anne P Beigneux, Troy L Lowe +21 more · 2026 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
Apolipoprotein AV (APOA5) regulates intravascular triglyceride metabolism by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its ability to unfold the native conformat Show more
Apolipoprotein AV (APOA5) regulates intravascular triglyceride metabolism by binding to the angiopoietin-like protein 3/8 complex (ANGPTL3/8) and suppressing its ability to unfold the native conformation of lipoprotein lipase (LPL). LPL unfolding results in loss of catalytic activity and the detachment of LPL from the surface of cells. An Show less
no PDF DOI: 10.1073/pnas.2528664123
APOA5
Lu Cao, Gang Chen, Jing Zhou +5 more · 2026 · Biomedical reports · added 2026-04-24
Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disorder. Notably, the differences in lipid metabolism between bulbar- and limb-onset subtypes of ALS remain unclear, particula Show more
Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disorder. Notably, the differences in lipid metabolism between bulbar- and limb-onset subtypes of ALS remain unclear, particularly in non-Western populations. The present study investigated serum lipid profiles in a Chinese cohort of patients with ALS to explore their associations with disease severity and clinical subtypes. A retrospective, cross-sectional study was conducted, involving 158 patients with ALS and 62 matched healthy controls. Serum lipid parameters, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), small dense LDL cholesterol (sdLDL-c), apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB) and the TG/HDL ratio, were compared between the groups. Correlation analyses and multivariable linear regression models incorporating phenotype x lipid interaction terms were conducted after adjusting for age, sex, body mass index and disease duration. Patients with ALS exhibited significantly higher TC, TG, LDL, sdLDL-c, ApoA1, ApoB and TG/HDL ratios than controls. Subtype-specific analyses revealed different associations; in bulbar-onset ALS, higher sdLDL-c and TG/HDL ratios were associated with better functional status, whereas higher HDL and ApoA1 levels were negatively correlated with functional status. By contrast, in limb-onset ALS, higher sdLDL-c and ApoB levels were associated with worse function. Interaction analyses confirmed significant phenotype modification for sdLDL-c, TG/HDL ratio, HDL and ApoA1. These results suggest that lipid-severity relationships in ALS vary by subtype, indicating metabolic heterogeneity across phenotypes and supporting the potential of specific lipid parameters as exploratory markers for disease monitoring. Show less
📄 PDF DOI: 10.3892/br.2026.2141
APOB
Min Zuo, Haixia Xu, Yuying Yang +7 more · 2026 · Communications biology · Nature · added 2026-04-24
Adolescent Idiopathic Scoliosis (AIS) is the most common form of spinal deformity among adolescents. To explore its etiology of progression and scoliosis-modifying drugs, chondrocytic senescence was c Show more
Adolescent Idiopathic Scoliosis (AIS) is the most common form of spinal deformity among adolescents. To explore its etiology of progression and scoliosis-modifying drugs, chondrocytic senescence was confirmed in AIS facet joint cartilage by analyzing clinical specimen. Furthermore, through 4D/480 label-free proteomics analysis, we identified an exosome-mediated positive feedback loop during scoliosis progression, which driving the elevation of cholesterol flow between spinal cartilage and vertebra. To further investigate the pathological significance of the loop in vivo, high-cholesterol flow was reconstructed in C57BL/6 J mice by injecting with recombinant adeno-associated virus rAAV9-Runx2-HMGCR. Our results confirmed the important role of the positive feedback loop in the development of scoliosis. Meanwhile, Avasimibe or/and Corylin were used to delay the scoliosis progression by targeting the key exosomal proteins APOB (Apolipoprotein B-100) or/and HSP90β (Heat Shock Protein 90-beta). This research extends the etiology of scoliosis progression and provides an alternative perspective for scoliosis non-surgical treatment. Show less
📄 PDF DOI: 10.1038/s42003-026-09960-w
APOB
Wei Pan, Xiaozhao Lu, Ziwei Zhou +14 more · 2026 · Lipids in health and disease · BioMed Central · added 2026-04-24
Residual cardiovascular risk persists in statin-treated patients with coronary artery disease (CAD), even when low-density lipoprotein cholesterol (LDL-C) targets are met. Excess apolipoprotein B (apo Show more
Residual cardiovascular risk persists in statin-treated patients with coronary artery disease (CAD), even when low-density lipoprotein cholesterol (LDL-C) targets are met. Excess apolipoprotein B (apoB), defined as measured apoB minus LDL-C-predicted apoB, may capture atherogenic particle burden beyond LDL-C, but its prognostic value for long-term mortality in secondary prevention remains uncertain. We conducted a pooled analysis of two nationwide Chinese cohorts (CIN-II and RED-CARPET) comprising 68,616 statin-treated CAD patients. Excess apoB was calculated using an internal reference population (triglycerides ≤ 1.0 mmol/L). Associations with all-cause and cardiovascular mortality were assessed using multivariable Cox models, with adjustment for clinical covariates including nutritional status. External validation was performed in 13,702 participants from the UK Biobank. Over a median follow-up of 5.2 years, 10,835 deaths occurred (5,090 cardiovascular). Each 1-standard deviation (15.4 mg/dL) increase in excess apoB was associated with a 12% higher risk of all-cause mortality (adjusted hazard ratio [aHR] 1.12, 95% CI 1.06-1.18) and a 24% higher risk of cardiovascular mortality (aHR 1.24, 95% CI 1.15-1.34). Patients in the highest excess apoB quartile (≥ 11.5 mg/dL) had significantly worse survival. Notably, these associations persisted consistently across all achieved LDL-C strata (< 2.0 to > 4.0 mmol/L). These findings were robustly confirmed in the external validation cohort. Excess apoB is an independent predictor of long-term mortality in statin-treated CAD patients, even among those with well-controlled LDL-C. Its incorporation into risk assessment could improve prognostic stratification and guide personalized management in secondary prevention. CIN-II: ClinicalTrials.gov, NCT05050877 (Retrospectively registered, 21 September 2021); RED-CARPET: Chinese Clinical Trial Registry, ChiCTR2000039901 (Prospectively registered, 14 November 2020). The UK Biobank study is covered by generic ethical approval from the NHS National Research Ethics Service (Ref: 99231). Show less
no PDF DOI: 10.1186/s12944-026-02928-z
APOB
Yu Wang, Li Chen, Yingze Ma +8 more · 2026 · Nature communications · Nature · added 2026-04-24
Dietary fat absorption is among the most energy-demanding processes of nutrient uptake. Fatty acid activation, triglyceride synthesis, and the trafficking of chylomicrons through the secretory pathway Show more
Dietary fat absorption is among the most energy-demanding processes of nutrient uptake. Fatty acid activation, triglyceride synthesis, and the trafficking of chylomicrons through the secretory pathway - all require ATP. How enterocytes accommodate the surge in ATP consumption following fat uptake is unclear. We show that the purine biosynthesis/salvage pathway supplies necessary ATP and that Ankyrin Repeat Domain 9 (ANKRD9) couples ATP synthesis and lipoprotein trafficking. Ankrd9 regulates enzymes within the purine biosynthesis pathway to increase ATP synthesis and facilitate Golgi dynamics. Intracellular localization of ANKRD9 is lipid and ATP-dependent. Inactivation of Ankrd9 in mice reduces intestinal ATP despite intact mitochondrial and glycolytic function, alters Golgi morphology, delays ApoB/chylomicron trafficking, and causes lipid accumulation in enterocytes, along with a lean body phenotype. Taken together, the results reveal a previously unrecognized mechanism that regulates lipid absorption in enterocytes and identify ANKRD9 as a central component of this mechanism. Show less
no PDF DOI: 10.1038/s41467-026-70332-3
APOB
De Xu, Ruijuan Duan, Ruiqi Zhu +2 more · 2026 · Journal of medical biochemistry · added 2026-04-24
To investigate the connection betweenischemic stroke (IS) patients' risk of dying after being discharged and their residual cholesterol (RC) levels uponadmission. 2021 IS patients between the ages of Show more
To investigate the connection betweenischemic stroke (IS) patients' risk of dying after being discharged and their residual cholesterol (RC) levels uponadmission. 2021 IS patients between the ages of 35 and 80were chosen as the study's subjects, and data on deathendpoints following discharge were gathered. The doseresponse association between the risk of death and the RCat admission was examined using restricted cubic spline(RCS) regression. The hazard ratio (HR) and 95% CI werecalculated via Cox regression to analyse the associationbetween the RC level at admission and the risk of deathafter discharge in patients with IS. According to the RCS model, RC levels were nonlinearly associated with deaths from IS and other causes(P<0.001). With the median RC level as the cutoff value,the subjects were divided into two groups: a low RC group(RC<0.72 mmol/L) and a high RC group (RC≥0.72mmol/L). Compared with those in the high RC group, theage and male ratio in the low RC group were significantlygreater. The fasting blood glucose (GLU), total cholesterol(TC), triglyceride (TG), low-density lipoprotein cholesterol(LDL-C), non-high-density lipoprotein cholesterol (nonHDL-C), apolipoprotein A-1 (ApoA-1), and apolipoproteinB (ApoB) levels, as well as diabetes rates, were lower (P=0.01). Cox regression analysis revealed that withoutadjusting for covariates, the high-level RC group presenteda lower risk of all-cause death than the low-level RC group(HR=0.765, 95% CI: 0.619~0.946, P=0.013) and alower risk of death from IS (HR = 0.638, 95% CI:0.435~0.936, P=0.022). After adjusting for sex, age,smoking status, drinking status, hypertension status, anddiabetes status, the high-level group still had a lower risk ofall-cause death (HR = 760, 95% CI: 0.614~0.941,P=0.012) and a lower risk of death from IS (HR=0.653,95% CI: 0.444-0.961, P=0.031). Male sex (HR=0.753,95% CI: 0.572~0.990, P=0.042). Age ≥65 years (HR=0.598, 95% CI: 0.391~0.916, P=0.018), nonsmokingstatus (HR=0.628, 95% CI: 0.408~0.967, P=0.035),nonalcoholic status (HR=0.656, 95% CI: 0.439~0.979,P=0.039), not complicated with hypertension (HR=0.321, 95% CI: 0.108~0.957, P=0.041), no diabetesmellitus (HR=0.607, 95% CI: 0.389~0.947, P=0.028).Compared with those in the high RC group, the IS patientsin the low RC group had a lower incidence of all-causedeath, IS death and other causes of death and a higher survival rate. An RC<0.72 mmol/L at admission is associated with an increased risk of all-cause death and longterm IS death after discharge. Show less
📄 PDF DOI: 10.5937/jomb0-59233
APOB
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
Lingzhi Wu, Jianqin Wang, Yawei Wang +20 more · 2026 · Nature · Nature · added 2026-04-24
Orchestration of lipid production, storage and mobilization is vital for cellular and systemic homeostasis
📄 PDF DOI: 10.1038/s41586-026-10161-y
APOB
Kun Wang, Ying Qin, Xian-Cheng Jiang +1 more · 2026 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Apolipoprotein B-100 (apoB-100) is the main structural protein of apoB-containing lipoproteins including low-density lipoprotein (LDL). Its organization or lipidation process in an apoB-containing lip Show more
Apolipoprotein B-100 (apoB-100) is the main structural protein of apoB-containing lipoproteins including low-density lipoprotein (LDL). Its organization or lipidation process in an apoB-containing lipoprotein particle is still unclear. To understand its organization in a LDL particle, the combination of atomic force microscopy (AFM) with lipid depletion by Nonidet P-40 (NP-40) or methyl-β-cyclodextrin (MβCD) was utilized for the first time to in situ visualize LDL delipidation process and lipid-poor/-free apoB-100 at a physiological condition. During LDL delipidation process, different morphologies/structures were visualized successively including spheroidal structure with a smaller size than native LDL, spheroidal structure with one or more holes, closed annular/circular structure, opened annular/circular structure, C/U-shaped (or horseshoe-shaped) structure, and V/S/I-shaped structure. Based on the concentration-dependent structural distributions, these structures probably reflect 5 stages of LDL delipidation (e.g., a slightly delipidated LDL stage, a partially delipidated LDL stage, a neutral lipid-poor/-free apoB-100 stage, a lipid-poor apoB-100 stage, and a lipid-free apoB-100 stage, respectively). Our findings could provide structural evidence to reconcile the previous controversy and provide potential evidence/clues/implications for understanding apoB-100 lipidation and the organization of apoB-100 in apoB-containing lipoprotein particles. Potentially, this study also can provide new structural insights into the design of food-grade lipid carriers. Moreover, the combination of AFM with lipid depletion, which has many advantages over traditional electron microscopy (e.g., label-free, in situ, and real-time imaging under physiological conditions, etc.), is a potentially ideal novel strategy for studying the structure of apolipoproteins or lipoproteins. Show less
no PDF DOI: 10.1016/j.ijbiomac.2026.151070
APOB
Fanrong Zeng, Xinyi Zhang, Meng Zhang +6 more · 2026 · Frontiers in endocrinology · Frontiers · added 2026-04-24
This study investigated the impact of This retrospective case-control study involved 628 CAD patients and 628 matched controls without CAD. ApoE genotyping was conducted using PCR-chip technology, and Show more
This study investigated the impact of This retrospective case-control study involved 628 CAD patients and 628 matched controls without CAD. ApoE genotyping was conducted using PCR-chip technology, and genotype and allele frequencies were compared between groups. Multivariate logistic regression analyzed the link between ApoE polymorphisms and CAD risk in populations at middle and high altitudes. The data revealed significant differences in These findings validated that the Show less
📄 PDF DOI: 10.3389/fendo.2026.1765770
APOB
Qinying Chen, Dali Chen, Zhihao Liu +12 more · 2026 · Journal of controlled release : official journal of the Controlled Release Society · Elsevier · added 2026-04-24
Rapid platelet inhibition is essential for effective management during emergency percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS). However, the oral dosage form Show more
Rapid platelet inhibition is essential for effective management during emergency percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS). However, the oral dosage form of clopidogrel (CLP) commonly used in clinical practice shows a delayed onset due to gastrointestinal absorption, first-pass metabolism, and the requirement for hepatic cytochrome P450 (CYP450)-mediated bioactivation, which limits its applications in urgent scenarios and complicating post-PCI bleeding management. To address these challenges, we developed an intravenous micellar formulation (CLP/PM) using FDA-approved mPEG-PLA copolymers to promote rapid hepatic exposure and metabolic activation. By tuning the PLA chain length, micellar core density and PEG conformation were modulated, thereby influencing protein corona (PC) formation and liver-affinity interactions. Proteomic profiling revealed that micelles with intermediate PLA length selectively recruited liver-affinity apolipoproteins (ApoM, ApoH, ApoA1, and ApoB), which are known ligands of LDLR and SR-BI, while minimizing adsorption of inflammatory and opsonization proteins. The optimized CLP/PM (3.9 k) exhibited a hepatotropic-like PC that was associated with hepatocyte-enriched uptake in primary liver cell analyses. In vivo biodistribution showed rapid liver-level signal, and pharmacokinetic studies supported enhanced CYP450-mediated activation, achieving a higher C Show less
no PDF DOI: 10.1016/j.jconrel.2026.114727
APOB