👤 Mian-Mian Chen

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2981
Articles
1996
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Also published as: Ai-Qun Chen, Aiping Chen, Alex Chen, Alex F Chen, Alice P Chen, Alice Y Chen, Alice Ye A Chen, Allen Menglin Chen, Alon Chen, Alvin Chen, An Chen, Andrew Chen, Anqi Chen, Aoshuang Chen, Aozhou Chen, B Chen, B-S Chen, Baihua Chen, Ban Chen, Bang Chen, Bang-dang Chen, Bao-Bao Chen, Bao-Fu Chen, Bao-Sheng Chen, Bao-Ying Chen, Baofeng Chen, Baojiu Chen, Baolin Chen, Baosheng Chen, Baoxiang Chen, Beidong Chen, Beijian Chen, Ben-Kuen Chen, Benjamin Chen, Benjamin Jieming Chen, Benjamin P C Chen, Beth L Chen, Bihong T Chen, Bin Chen, Bing Chen, Bing-Bing Chen, Bing-Feng Chen, Bing-Huei Chen, Bingdi Chen, Bingqian Chen, Bingqing Chen, Bingyu Chen, Binlong Chen, Binzhen Chen, Bo Chen, Bo-Fang Chen, Bo-Jun Chen, Bo-Rui Chen, Bo-Sheng Chen, Bohe Chen, Bohong Chen, Bosong Chen, Bowang Chen, Bowei Chen, Bowen Chen, Boyu Chen, Brian Chen, C Chen, C Y Chen, C Z Chen, C-Y Chen, Cai-Long Chen, Caihong Chen, Can Chen, Cancan Chen, Canrong Chen, Canyu Chen, Caressa Chen, Carl Pc Chen, Carol Chen, Carol X-Q Chen, Catherine Qing Chen, Ceshi Chen, Chan Chen, Chang Chen, Chang-Lan Chen, Chang-Zheng Chen, Changjie Chen, Changya Chen, Changyan Chen, Chanjuan Chen, Chao Chen, Chao-Jung Chen, Chao-Wei Chen, Chaochao Chen, Chaojin Chen, Chaoli Chen, Chaoping Chen, Chaoqun Chen, Chaoran Chen, Chaoyi Chen, Chaoyue Chen, Chen Chen, Chen-Mei Chen, Chen-Sheng Chen, Chen-Yu Chen, Cheng Chen, Cheng-Fong Chen, Cheng-Sheng Chen, Cheng-Yi Chen, Cheng-Yu Chen, Chengchuan Chen, Chengchun Chen, Chengde Chen, Chengsheng Chen, Chengwei Chen, Chenyang Chen, Chi Chen, Chi-Chien Chen, Chi-Hua Chen, Chi-Long Chen, Chi-Yu Chen, Chi-Yuan Chen, Chi-Yun Chen, Chian-Feng Chen, Chider Chen, Chien-Hsiun Chen, Chien-Jen Chen, Chien-Lun Chen, Chien-Ting Chen, Chien-Yu Chen, Chih-Chieh Chen, Chih-Mei Chen, Chih-Ping Chen, Chih-Ta Chen, Chih-Wei Chen, Chih-Yi Chen, Chin-Chuan Chen, Ching Kit Chen, Ching-Hsuan Chen, Ching-Jung Chen, Ching-Wen Chen, Ching-Yi Chen, Ching-Yu Chen, Chiqi Chen, Chiung Mei Chen, Chiung-Mei Chen, Chixiang Chen, Chong Chen, Chongyang Chen, Christina Y Chen, Christina Yingxian Chen, Christopher S Chen, Chu Chen, Chu-Huang Chen, Chuanbing Chen, Chuannan Chen, Chuanzhi Chen, Chuck T Chen, Chueh-Tan Chen, Chujie Chen, Chun Chen, Chun-An Chen, Chun-Chi Chen, Chun-Fa Chen, Chun-Han Chen, Chun-Houh Chen, Chun-Wei Chen, Chun-Yuan Chen, Chung-Hao Chen, Chung-Hsing Chen, Chung-Hung Chen, Chung-Jen Chen, Chung-Yung Chen, Chunhai Chen, Chunhua Chen, Chunji Chen, Chunjie Chen, Chunlin Chen, Chunnuan Chen, Chunxiu Chen, Chuo Chen, Chuyu Chen, Cindi Chen, Constance Chen, Cuicui Chen, Cuie Chen, Cuilan Chen, Cuimin Chen, Cuncun Chen, D F Chen, D M Chen, D-F Chen, D. Chen, Dafang Chen, Daijie Chen, Daiwen Chen, Daiyu Chen, Dake Chen, Dali Chen, Dan Chen, Dan-Dan Chen, Dandan Chen, Danlei Chen, Danli Chen, Danmei Chen, Danna Chen, Danni Chen, Danxia Chen, Danxiang Chen, Danyang Chen, Danyu Chen, Daoyuan Chen, Dapeng Chen, Dawei Chen, Defang Chen, Dejuan Chen, Delong Chen, Denghui Chen, Dengpeng Chen, Deqian Chen, Dexi Chen, Dexiang Chen, Dexiong Chen, Deying Chen, Deyu Chen, Di Chen, Di-Long Chen, Dian Chen, Dianke Chen, Ding Chen, Diyun Chen, Dong Chen, Dong-Mei Chen, Dong-Yi Chen, Dongli Chen, Donglong Chen, Dongquan Chen, Dongrong Chen, Dongsheng Chen, Dongxue Chen, Dongyan Chen, Dongyin Chen, Du-Qun Chen, Duan-Yu Chen, Duo Chen, Duo-Xue Chen, Duoting Chen, E S Chen, Eleanor Y Chen, Elizabeth H Chen, Elizabeth S Chen, Elizabeth Suchi Chen, Emily Chen, En-Qiang Chen, Erbao Chen, Erfei Chen, Erqu Chen, Erzhen Chen, Everett H Chen, F Chen, F-K Chen, Fa Chen, Fa-Xi Chen, Fahui Chen, Fan Chen, Fang Chen, Fang-Pei Chen, Fang-Yu Chen, Fang-Zhi Chen, Fang-Zhou Chen, Fangfang Chen, Fangli Chen, Fangyan Chen, Fangyuan Chen, Faye H Chen, Fei Chen, Fei Xavier Chen, Feifan Chen, Feifeng Chen, Feilong Chen, Feixue Chen, Feiyang Chen, Feiyu Chen, Feiyue Chen, Feng Chen, Feng-Jung Chen, Feng-Ling Chen, Fenghua Chen, Fengju Chen, Fengling Chen, Fengming Chen, Fengrong Chen, Fengwu Chen, Fengyang Chen, Fred K Chen, Fu Chen, Fu-Shou Chen, Fumei Chen, Fusheng Chen, Fuxiang Chen, Gang Chen, Gao B Chen, Gao Chen, Gao-Feng Chen, Gaoyang Chen, Gaoyu Chen, Gaozhi Chen, Gary Chen, Gary K Chen, Ge Chen, Gen-Der Chen, Geng Chen, Gengsheng Chen, Ginny I Chen, Gong Chen, Gongbo Chen, Gonghai Chen, Gonglie Chen, Guan-Wei Chen, Guang Chen, Guang-Chao Chen, Guang-Yu Chen, Guangchun Chen, Guanghao Chen, Guanghong Chen, Guangjie Chen, Guangju Chen, Guangliang Chen, Guanglong Chen, Guangnan Chen, Guangping Chen, Guangquan Chen, Guangyao Chen, Guangyi Chen, Guangyong Chen, Guanjie Chen, Guanren Chen, Guanyu Chen, Guanzheng Chen, Gui Mei Chen, Gui-Hai Chen, Gui-Lai Chen, Guihao Chen, Guiqian Chen, Guiquan Chen, Guiying Chen, Guo Chen, Guo-Chong Chen, Guo-Jun Chen, Guo-Rong Chen, Guo-qing Chen, Guochao Chen, Guochong Chen, Guofang Chen, Guohong Chen, Guohua Chen, Guojun Chen, Guoliang Chen, Guopu Chen, Guoshun Chen, Guoxun Chen, Guozhong Chen, Guozhou Chen, H Chen, H Q Chen, H T Chen, Hai-Ning Chen, Haibing Chen, Haibo Chen, Haide Chen, Haifeng Chen, Haijiao Chen, Haimin Chen, Haiming Chen, Haining Chen, Haiqin Chen, Haiquan Chen, Haitao Chen, Haiyan Chen, Haiyang Chen, Haiyi Chen, Haiying Chen, Haiyu Chen, Haiyun Chen, Han Chen, Han-Bin Chen, Han-Chun Chen, Han-Hsiang Chen, Han-Min Chen, Hanbei Chen, Hang Chen, Hangang Chen, Hanjing Chen, Hanlin Chen, Hanqing Chen, Hanwen Chen, Hanxi Chen, Hanyong Chen, Hao Chen, Hao Yu Chen, Hao-Zhu Chen, Haobo Chen, Haodong Chen, Haojie Chen, Haoran Chen, Haotai Chen, Haotian Chen, Haoting Chen, Haoyun Chen, Haozhu Chen, Harn-Shen Chen, Haw-Wen Chen, He-Ping Chen, Hebing Chen, Hegang Chen, Hehe Chen, Hekai Chen, Heng Chen, Heng-Sheng Chen, Heng-Yu Chen, Hengsan Chen, Hengsheng Chen, Hengyu Chen, Heni Chen, Herbert Chen, Hetian Chen, Heye Chen, Hong Chen, Hong Yang Chen, Hong-Sheng Chen, Hongbin Chen, Hongbo Chen, Hongen Chen, Honghai Chen, Honghui Chen, Honglei Chen, Hongli Chen, Hongmei Chen, Hongmin Chen, Hongmou Chen, Hongqi Chen, Hongqiao Chen, Hongshan Chen, Hongxiang Chen, Hongxing Chen, Hongxu Chen, Hongyan Chen, Hongyu Chen, Hongyue Chen, Hongzhi Chen, Hou-Tsung Chen, Hou-Zao Chen, Hsi-Hsien Chen, Hsiang-Wen Chen, Hsiao-Jou Cortina Chen, Hsiao-Tan Chen, Hsiao-Wang Chen, Hsiao-Yun Chen, Hsin-Han Chen, Hsin-Hong Chen, Hsin-Hung Chen, Hsin-Yi Chen, Hsiu-Wen Chen, Hsuan-Yu Chen, Hsueh-Fen Chen, Hu Chen, Hua Chen, Hua-Pu Chen, Huachen Chen, Huafei Chen, Huaiyong Chen, Hualan Chen, Huali Chen, Hualin Chen, Huan Chen, Huan-Xin Chen, Huanchun Chen, Huang Chen, Huang-Pin Chen, Huangtao Chen, Huanhua Chen, Huanhuan Chen, Huanxiong Chen, Huaping Chen, Huapu Chen, Huaqiu Chen, Huatao Chen, Huaxin Chen, Huayu Chen, Huei-Rong Chen, Huei-Yan Chen, Huey-Miin Chen, Hui Chen, Hui Mei Chen, Hui-Chun Chen, Hui-Fen Chen, Hui-Jye Chen, Hui-Ru Chen, Hui-Wen Chen, Hui-Xiong Chen, Hui-Zhao Chen, Huichao Chen, Huijia Chen, Huijiao Chen, Huijie Chen, Huimei Chen, Huimin Chen, Huiqin Chen, Huiqun Chen, Huiru Chen, Huishan Chen, Huixi Chen, Huixian Chen, Huizhi Chen, Hung-Chang Chen, Hung-Chi Chen, Hung-Chun Chen, Hung-Po Chen, Hung-Sheng Chen, I-Chun Chen, I-M Chen, Ida Y-D Chen, Irwin Chen, Ivy Xiaoying Chen, J Chen, Jacinda Chen, Jack Chen, Jake Y Chen, Jason A Chen, Jeanne Chen, Jen-Hau Chen, Jen-Sue Chen, Jennifer F Chen, Jenny Chen, Jeremy J W Chen, Ji-ling Chen, Jia Chen, Jia Min Chen, Jia Wei Chen, Jia-De Chen, Jia-Feng Chen, Jia-Lin Chen, Jia-Mei Chen, Jia-Shun Chen, Jiabing Chen, Jiacai Chen, Jiacheng Chen, Jiade Chen, Jiahao Chen, Jiahua Chen, Jiahui Chen, Jiajia Chen, Jiajing Chen, Jiajun Chen, Jiakang Chen, Jiale Chen, Jiali Chen, Jialing Chen, Jiamiao Chen, Jiamin Chen, Jian Chen, Jian-Guo Chen, Jian-Hua Chen, Jian-Jun Chen, Jian-Kang Chen, Jian-Min Chen, Jian-Qiao Chen, Jian-Qing Chen, Jianan Chen, Jianfei Chen, Jiang Chen, Jiang Ye Chen, Jiang-hua Chen, Jianghua Chen, Jiangxia Chen, Jianhua Chen, Jianhui Chen, Jiani Chen, Jianjun Chen, Jiankui Chen, Jianlin Chen, Jianmin Chen, Jianping Chen, Jianshan Chen, Jiansu Chen, Jianxiong Chen, Jianzhong Chen, Jianzhou Chen, Jiao Chen, Jiao-Jiao Chen, Jiaohua Chen, Jiaping Chen, Jiaqi Chen, Jiaqing Chen, Jiaren Chen, Jiarou Chen, Jiawei Chen, Jiawen Chen, Jiaxin Chen, Jiaxu Chen, Jiaxuan Chen, Jiayao Chen, Jiaye Chen, Jiayi Chen, Jiayuan Chen, Jichong Chen, Jie Chen, Jie-Hua Chen, Jiejian Chen, Jiemei Chen, Jien-Jiun Chen, Jihai Chen, Jijun Chen, Jimei Chen, Jin Chen, Jin-An Chen, Jin-Ran Chen, Jin-Shuen Chen, Jin-Wu Chen, Jin-Xia Chen, Jina Chen, Jinbo Chen, Jindong Chen, Jing Chen, Jing-Hsien Chen, Jing-Wen Chen, Jing-Xian Chen, Jing-Yuan Chen, Jing-Zhou Chen, Jingde Chen, Jinghua Chen, Jingjing Chen, Jingli Chen, Jinglin Chen, Jingming Chen, Jingnan Chen, Jingqing Chen, Jingshen Chen, Jingteng Chen, Jinguo Chen, Jingxuan Chen, Jingyao Chen, Jingyi Chen, Jingyuan Chen, Jingzhao Chen, Jingzhou Chen, Jinhao Chen, Jinhuang Chen, Jinli Chen, Jinlun Chen, Jinquan Chen, Jinsong Chen, Jintian Chen, Jinxuan Chen, Jinyan Chen, Jinyong Chen, Jion Chen, Jiong Chen, Jiongyu Chen, Jishun Chen, Jiu-Chiuan Chen, Jiujiu Chen, Jiwei Chen, Jiyan Chen, Jiyuan Chen, Jonathan Chen, Joy J Chen, Juan Chen, Juan-Juan Chen, Juanjuan Chen, Juei-Suei Chen, Juhai Chen, Jui-Chang Chen, Jui-Yu Chen, Jun Chen, Jun-Long Chen, Junchen Chen, Junfei Chen, Jung-Sheng Chen, Junhong Chen, Junhui Chen, Junjie Chen, Junling Chen, Junmin Chen, Junming Chen, Junpan Chen, Junpeng Chen, Junqi Chen, Junqin Chen, Junsheng Chen, Junshi Chen, Junyang Chen, Junyi Chen, Junyu Chen, K C Chen, Kai Chen, Kai-En Chen, Kai-Ming Chen, Kai-Ting Chen, Kai-Yang Chen, Kaifu Chen, Kaijian Chen, Kailang Chen, Kaili Chen, Kaina Chen, Kaiquan Chen, Kan Chen, Kang Chen, Kang-Hua Chen, Kangyong Chen, Kangzhen Chen, Katharine Y Chen, Katherine C Chen, Ke Chen, Kecai Chen, Kehua Chen, Kehui Chen, Kelin Chen, Ken Chen, Kenneth L Chen, Keping Chen, Kequan Chen, Kevin Chen, Kewei Chen, Kexin Chen, Keyan Chen, Keyang Chen, Keying Chen, Keyu Chen, Keyuan Chen, Kuan-Jen Chen, Kuan-Ling Chen, Kuan-Ting Chen, Kuan-Yu Chen, Kuangyang Chen, Kuey Chu Chen, Kui Chen, Kun Chen, Kun-Chieh Chen, Kunmei Chen, Kunpeng Chen, L B Chen, L F Chen, Lan Chen, Lang Chen, Lankai Chen, Lanlan Chen, Lanmei Chen, Le Chen, Le Qi Chen, Lei Chen, Lei-Chin Chen, Lei-Lei Chen, Leijie Chen, Lena W Chen, Leqi Chen, Letian Chen, Lexia Chen, Li Chen, Li Jia Chen, Li-Chieh Chen, Li-Hsien Chen, Li-Hsin Chen, Li-Hua Chen, Li-Jhen Chen, Li-Juan Chen, Li-Mien Chen, Li-Nan Chen, Li-Tzong Chen, Li-Zhen Chen, Li-hong Chen, Lian Chen, Lianfeng Chen, Liang Chen, Liang-Kung Chen, Liangkai Chen, Liangsheng Chen, Liangwan Chen, Lianmin Chen, Liaobin Chen, Lichang Chen, Lichun Chen, Lidian Chen, Lie Chen, Liechun Chen, Lifang Chen, Lifen Chen, Lifeng Chen, Ligang Chen, Lihong Chen, Lihua Chen, Lijin Chen, Lijuan Chen, Lili Chen, Limei Chen, Limin Chen, Liming Chen, Lin Chen, Lina Chen, Linbo Chen, Ling Chen, Ling-Yan Chen, Lingfeng Chen, Lingjun Chen, Lingli Chen, Lingxia Chen, Lingxue Chen, Lingyi Chen, Linjie Chen, Linlin Chen, Linna Chen, Linxi Chen, Linyi Chen, Liping Chen, Liqiang Chen, Liugui Chen, Liujun Chen, Liutao Chen, Lixia Chen, Lixian Chen, Liyun Chen, Lizhen Chen, Lizhu Chen, Lo-Yun Chen, Long Chen, Long-Jiang Chen, Longqing Chen, Longyun Chen, Lu Chen, Lu Hua Chen, Lu-Biao Chen, Lu-Zhu Chen, Lulu Chen, Luming Chen, Luyi Chen, Luzhu Chen, M Chen, M L Chen, Man Chen, Man-Hua Chen, Mao Chen, Mao-Yuan Chen, Maochong Chen, Maorong Chen, Marcus Y Chen, Mark I-Cheng Chen, Max Jl Chen, Mechi Chen, Mei Chen, Mei-Chi Chen, Mei-Chih Chen, Mei-Hsiu Chen, Mei-Hua Chen, Mei-Jie Chen, Mei-Ling Chen, Mei-Ru Chen, Meilan Chen, Meilin Chen, Meiling Chen, Meimei Chen, Meiting Chen, Meiyang Chen, Meiyu Chen, Meizhen Chen, Meng Chen, Meng Xuan Chen, Meng-Lin Chen, Meng-Ping Chen, Mengdi Chen, Menglan Chen, Mengling Chen, Mengping Chen, Mengqing Chen, Mengting Chen, Mengxia Chen, Mengyan Chen, Mengying Chen, 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
Jianmin Zhu, Liting Yang, Jing Xia +6 more · 2024 · Transplantation · added 2026-04-24
Stimulation of myeloid-derived suppressor cell (MDSC) formation represents a potential curative therapeutic approach for graft-versus-host disease (GVHD), which significantly impacts the prognosis of Show more
Stimulation of myeloid-derived suppressor cell (MDSC) formation represents a potential curative therapeutic approach for graft-versus-host disease (GVHD), which significantly impacts the prognosis of allogeneic hematopoietic stem cell transplantation. However, the lack of an effective strategy for inducing MDSC production in vivo has hindered their clinical application. In our previous study, MDSC expansion was observed in interleukin (IL)-27-treated mice. In this study, we overexpressed exogenous IL-27 in mice using a recombinant adeno-associated virus vector to investigate its therapeutic and exacerbating effects in murine GVHD models. In our study, we demonstrated that exogenous administration of IL-27 significantly suppressed GVHD development in a mouse model. We found that IL-27 treatment indirectly inhibited the proliferation and activation of donor T cells by rapidly expanding recipient and donor myeloid cells, which act as MDSCs after irradiation or under inflammatory conditions, rather than through regulatory T-cell expansion. Additionally, IL-27 stimulated MDSC expansion by enhancing granulocyte-monocyte progenitor generation. Notably, we verified that IL-27 signaling in donor T cells exerted an antagonistic effect on GVHD prevention and treatment. Further investigation revealed that combination therapy involving IL-27 and T-cell depletion exhibited remarkable preventive effects on GVHD in both mouse and xenogeneic GVHD models. Collectively, these findings suggest that IL-27 promotes MDSC generation to reduce the incidence of GVHD, whereas targeted activation of IL-27 signaling in myeloid progenitors or its combination with T-cell depletion represents a potential strategy for GVHD therapy. Show less
no PDF DOI: 10.1097/TP.0000000000005069
IL27
Nianwei Zhou, Ao Liu, Haobo Weng +8 more · 2024 · International journal of cardiology · Elsevier · added 2026-04-24
The mitral valve undergoes structural modifications in response to cardiac functional changes, often predating cardiac decompensation and overt clinical signs. Our study assessed the potential of mitr Show more
The mitral valve undergoes structural modifications in response to cardiac functional changes, often predating cardiac decompensation and overt clinical signs. Our study assessed the potential of mitral valve morphological changes as early indicators for detecting carriers of hypertrophic cardiomyopathy (HCM)-associated gene mutations. We studied 505 participants: 189 without the pathogenic gene mutations and left ventricular hypertrophy (G-/LVH-), 149 carriers without LV hypertrophy (G+/LVH-), and 167 manifest HCM patients (G+/LVH+). We juxtaposed the mitral valve morphology and associated metrics across these groups, emphasizing those carrying MYH7 and MYBPC3 mutations. We discerned pronounced disparities in the mitral annulus and leaflet structures across the groups. The mitral valve apparatus in mutation carriers exhibited a tendency towards a flattened profile. Detailed analysis spotlighted MYBPC3 mutation carriers, whose mitral valves were notably flatter (with notably lower AHCWR values than non-carriers); this contrast was not evident in MYH7 mutation carriers. This mitral valve flattening, manifest in the mutation carriers, suggests it might be an adaptive response to incipient cardiac dysfunction in HCM's nascent stages. Three-dimensional echocardiography illuminates the initial mitral valve structural changes in HCM patients bearing pathogenic gene mutations. These morphological signatures hold promise as sensitive imaging markers, especially for asymptomatic carriers of the MYBPC3 mutation. Show less
no PDF DOI: 10.1016/j.ijcard.2023.131576
MYBPC3
Soo Heon Kwak, Shylaja Srinivasan, Ling Chen +15 more · 2024 · Nature metabolism · Nature · added 2026-04-24
The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily
📄 PDF DOI: 10.1038/s42255-023-00970-0
MC4R
Shijin Yu, Zongjun Ma, Tao Chen +4 more · 2024 · Oral diseases · Blackwell Publishing · added 2026-04-24
E26 transformation-specific (ETS) factors have emerged as key mediators underlying human tumorigenesis. Here, we sought to characterize the expression pattern, biological roles, and clinical significa Show more
E26 transformation-specific (ETS) factors have emerged as key mediators underlying human tumorigenesis. Here, we sought to characterize the expression pattern, biological roles, and clinical significance of ETS Variant Transcription Factor 5 (ETV5) in head neck squamous cell carcinoma (HNSCC). ETV5 expression pattern in HNSCC was determined by bioinformatics interrogations and immunohistochemical staining in primary samples. The associations between its abundance with clinicopathological parameters, and patient survival were evaluated. Colony formation, CCK-8, flow cytometry, wound healing, and Transwell invasion assays, as well as xenograft models, were utilized to determine the phenotypic changes after ETV5 silencing in vitro and vivo. The potential binding of ETV5 in the Slug promoter was determined by ChIP-qPCR. ETV5 was significantly overexpressed in HNSCC samples. Its overexpression is significantly associated with aggressiveness features and reduced survival. ETV5 knockdown significantly inhibited cell proliferation, migration, invasion, and induced apoptosis in vitro, and impaired tumor growth in vivo. Moreover, ETV5-activated Slug transcription by binding its promoter region in HNSCC cells. Patients with ETV5 Our findings reveal that ETV5 serves as a novel prognostic biomarker and putative oncogene for HNSCC progression likely by activating Slug transcription. Show less
no PDF DOI: 10.1111/odi.14724
SNAI1
Zhiqiang Zha, Chunhong Jia, Ruisi Zhou +13 more · 2024 · NPJ biofilms and microbiomes · Nature · added 2026-04-24
Fetal growth restriction (FGR) is a common complication of pregnancy, which seriously endangers fetal health and still lacks effective therapeutic targets. Clostridium difficile (C. difficile) is asso Show more
Fetal growth restriction (FGR) is a common complication of pregnancy, which seriously endangers fetal health and still lacks effective therapeutic targets. Clostridium difficile (C. difficile) is associated with fetal birth weight, and its membrane vesicles (MVs) are pathogenic vectors. However, the role of C. difficile and its MVs in FGR remains unclear. Here we found that supplementation with C. difficile altered the characteristics of gut microbiota and reduced the birth weight in mice. Interestingly, C. difficile MVs entered placenta, inhibited trophoblast motility, and induced fetal weight loss in mice. Mechanistically, C. difficile MVs activated the PPAR pathway via enhancing the transcriptional activity of PPARγ promoter, consequently inhibiting trophoblast motility. Moreover, PPARγ expression was significantly elevated in FGR placenta, and negatively correlated with fetal birth weight. Together, our findings reveal the significance of C. difficile and its MVs in FGR, providing new insights into the mechanisms of FGR development. Show less
📄 PDF DOI: 10.1038/s41522-024-00630-5
ANGPTL4
You-Wang Lu, Rong-Jing Dong, Lu-Hui Yang +6 more · 2024 · Scientific reports · Nature · added 2026-04-24
Leprosy and psoriasis rarely coexist, the specific molecular mechanisms underlying their mutual exclusion have not been extensively investigated. This study aimed to reveal the underlying mechanism re Show more
Leprosy and psoriasis rarely coexist, the specific molecular mechanisms underlying their mutual exclusion have not been extensively investigated. This study aimed to reveal the underlying mechanism responsible for the mutual exclusion between psoriasis and leprosy. We obtained leprosy and psoriasis data from ArrayExpress and GEO database. Differential expression analysis was conducted separately on the leprosy and psoriasis using DEseq2. Differentially expressed genes (DEGs) with opposite expression patterns in psoriasis and leprosy were identified, which could potentially involve in their mutual exclusion. Enrichment analysis was performed on these candidate mutually exclusive genes, and a protein-protein interaction (PPI) network was constructed to identify hub genes. The expression of these hub genes was further validated in an external dataset to obtain the critical mutually exclusive genes. Additionally, immune cell infiltration in psoriasis and leprosy was analyzed using single-sample gene set enrichment analysis (ssGSEA), and the correlation between critical mutually exclusive genes and immune cells was also examined. Finally, the expression pattern of critical mutually exclusive genes was evaluated in a single-cell transcriptome dataset. We identified 1098 DEGs in the leprosy dataset and 3839 DEGs in the psoriasis dataset. 48 candidate mutually exclusive genes were identified by taking the intersection. Enrichment analysis revealed that these genes were involved in cholesterol metabolism pathways. Through PPI network analysis, we identified APOE, CYP27A1, FADS1, and SOAT1 as hub genes. APOE, CYP27A1, and SOAT1 were subsequently validated as critical mutually exclusive genes on both internal and external datasets. Analysis of immune cell infiltration indicated higher abundance of 16 immune cell types in psoriasis and leprosy compared to normal controls. The abundance of 6 immune cell types in psoriasis and leprosy positively correlated with the expression levels of APOE and CYP27A1. Single-cell data analysis demonstrated that critical mutually exclusive genes were predominantly expressed in Schwann cells and fibroblasts. This study identified APOE, CYP27A1, and SOAT1 as critical mutually exclusive genes. Cholesterol metabolism pathway illustrated the possible mechanism of the inverse association of psoriasis and leprosy. The findings of this study provide a basis for identifying mechanisms and therapeutic targets for psoriasis. Show less
📄 PDF DOI: 10.1038/s41598-024-52783-0
FADS1
Chen Yao, Hanyong Zhu, Binbin Ji +18 more · 2024 · Cellular and molecular life sciences : CMLS · Springer · added 2026-04-24
The metabolic reprogramming of macrophages is a potential therapeutic strategy for sepsis treatment, but the mechanism underlying this reprogramming remains unclear. Since glycolysis can drive macroph Show more
The metabolic reprogramming of macrophages is a potential therapeutic strategy for sepsis treatment, but the mechanism underlying this reprogramming remains unclear. Since glycolysis can drive macrophage phenotype switching, the rate-limiting enzymes in glycolysis may be key to treating sepsis. Here, we found that, compared with other isoenzymes, the expression of 6-phosphofructokinase, muscle type (PFKM) was the most upregulated in monocytes from septic patients. Recombinant thrombomodulin (rTM) treatment downregulated the protein expression of PFKM in macrophages. Both rTM treatment and Pfkm knockout protected mice from sepsis and reduced the production of the proinflammatory cytokines IL-1β, IL-6, TNF-α, and IL-27, whereas PFKM overexpression increased the production of these cytokines. Mechanistically, rTM treatment inhibited glycolysis in macrophages by decreasing PFKM expression in a hypoxia-inducible factor-1α (HIF-1α)-dependent manner. HIF-1α overexpression increased methyltransferase-like 3 (METTL3) expression, elevated the m Show less
📄 PDF DOI: 10.1007/s00018-024-05489-5
IL27
Boaz Wong, Rayanna Birtch, Anabel Bergeron +9 more · 2024 · Scientific reports · Nature · added 2026-04-24
Strategies in genetic and pharmacological modulation of innate immunity to enhance oncolytic virotherapy (OV) efficacy are being explored. We have recently characterized the ability for vanadium-based Show more
Strategies in genetic and pharmacological modulation of innate immunity to enhance oncolytic virotherapy (OV) efficacy are being explored. We have recently characterized the ability for vanadium-based compounds, a class of pan-phosphatase (PP) inhibitors, to potentiate OVs. We next sought to identify PPs that could be targeted to enhance OVs, akin to vanadium. By conducting a high-throughput screen of a library of silencing RNA (siRNA) targeting human PPs, we uncovered several PPs that robustly enhanced infectivity and oncolysis of the oncolytic vesicular stomatitis virus (VSV∆51). Knockdown of our top validated hit, lysosomal acid phosphatase 2 (ACP2), increased VSV∆51 viral titers by over 20-fold. In silico analysis by RNA sequencing revealed ACP2 to regulate antiviral type I interferon (IFN-1) signaling pathways, similar to vanadium. To further exploit this mechanism for therapeutic gain, we encoded a short-hairpin RNA (shRNA) against ACP2 into oncolytic vesicular stomatitis virus (VSV∆51) under a miR-30 promoter. This bioengineered OV demonstrated expression of the miR-30 promoter, knockdown of ACP2, repression and ultimately, showed markedly enhanced viral VSV∆51 particle production compared to its non-targeting control counterpart. Altogether, this study identifies IFN-1 regulating PP targets, namely ACP2, that may prove instrumental in increasing the therapeutic efficacy of OVs. Show less
📄 PDF DOI: 10.1038/s41598-024-76855-3
ACP2
Zhuo Chen, Shengnan Liu, Junsheng Wang +1 more · 2024 · Journal of environmental pathology, toxicology and oncology : official organ of the International Society for Environmental Toxicology and Cancer · added 2026-04-24
Acute pancreatitis (AP) is a common digestive emergency, needs early prediction and recognition. The study examined the clinical value of long non-coding RNA SNHG1 in AP, and explored its related mech Show more
Acute pancreatitis (AP) is a common digestive emergency, needs early prediction and recognition. The study examined the clinical value of long non-coding RNA SNHG1 in AP, and explored its related mechanism for AP. A total of 288 AP cases and 150 healthy persons were recruited, the AP patients were grouped based on AP severity. AR42J cells were treated with 100nM caerulein to stimulate AP in vitro. qRT-PCR was performed for mRNA detection. Receiver operating characteristic (ROC) curve was drawn for diagnostic significance evaluation. The relationship of SNHG1 and miR-140-3p was verified via luciferase reporter and RNA immunoprecipitation (RIP) assay. AP cases had high expression of SNHG1, and it can differentiate AP cases from healthy people with the area under the curve (AUC) of 0.899. Severe AP cases had high values of SNHG1, which was independently related to AP severity. SNHG1 knockdown relieved caerulein-induced AR42J cell apoptosis and inflammatory response. miR-140-3p interacted with SNHG1, and reversed the role of SNHG1 in caerulein-induced AR42J cell injury. RAB21 was a candidate target of miR-140-3p, and was at high expression in AP cell models. SNHG1 may be a promising biomarker for the detection of AP, and serves as a potential biological marker for further risk stratification in the management of AP. SNHG1 knockdown can relieve inflammatory responses and pancreatic cell apoptosis by absorbing miR-140-3p. Show less
no PDF DOI: 10.1615/JEnvironPatholToxicolOncol.2024053229
RAB21
Yan Ren, Jie Wang, Wen-Wen Guo +4 more · 2024 · Toxicon : official journal of the International Society on Toxinology · Elsevier · added 2026-04-24
To date there are only pirfenidone (PFD) and nintedanib to be given conditional recommendation in idiopathic pulmonary fibrosis (IPF) therapies with slowing disease progression, but neither has prospe Show more
To date there are only pirfenidone (PFD) and nintedanib to be given conditional recommendation in idiopathic pulmonary fibrosis (IPF) therapies with slowing disease progression, but neither has prospectively shown a reduced mortality. It is one of the urgent topics to find effective drugs for pulmonary fibrosis in medicine. Previous studies have demonstrated that microcystin-RR (MC-RR) effectively alleviates bleomycin-induced pulmonary fibrosis, but the mechanism has not been fully elucidated yet. We further conducted a comparison of therapeutic effect on the model animals of pulmonary fibrosis between MC-RR and PFD with histopathology and the expression of the molecular markers involved in differentiation, proliferation and metabolism of myofibroblasts, a major effector cell of tissue fibrosis. The levels of the enzyme molecules for maintaining the stability of interstitial structure were also evaluated. Our results showed that MC-RR and PFD effectively alleviated pulmonary fibrosis in model mice with a decreased signaling and marker molecules associated with myofibroblast differentiation and lung fibrotic lesion. In the meantime, both MC-RR and PFD treatment are beneficial to restore molecular dynamics of interstitial tissue and maintain the stability of interstitial architecture. Unexpectedly, MC-RR, rather than PFD, showed a significant effect on inhibiting PKM2-HIF-1α signaling and reducing the level of p-STAT3. Additionally, MC-RR showed a better inhibition effect on FGFR1 expression. Given that PKM2-HIF-1α and activated STAT3 molecular present a critical role in promoting the proliferation of myofibroblasts, MC-RR as a new strategy for IPF treatment has potential advantage over PFD. Show less
no PDF DOI: 10.1016/j.toxicon.2024.107822
FGFR1
Xin Jin, Chunlan Fu, Jiahui Qi +1 more · 2024 · Clinical and experimental medicine · Springer · added 2026-04-24
Thyroid carcinoma (TC), the most commonly diagnosed malignancy of the endocrine system, has witnessed a significant rise in incidence over the past few decades. The integration of scRNA-seq with other Show more
Thyroid carcinoma (TC), the most commonly diagnosed malignancy of the endocrine system, has witnessed a significant rise in incidence over the past few decades. The integration of scRNA-seq with other sequencing approaches offers researchers a distinct perspective to explore mechanisms underlying TC progression. Therefore, it is crucial to develop a prognostic model for TC patients by utilizing a multi-omics approach. We acquired and processed transcriptomic data from the TCGA-THCA dataset, including mRNA expression profiles, lncRNA expression profiles, miRNA expression profiles, methylation chip data, gene mutation data, and clinical data. We constructed a tumor-related risk model using machine learning methods and developed a consensus machine learning-driven signature (CMLS) for accurate and stable prediction of TC patient outcomes. 2 strains of undifferentiated TC cell lines and 1 strain of PTC cell line were utilized for in vitro validation. mRNA, protein levels of hub genes, epithelial-mesenchymal transition (EMT)-associated phenotypes were detected by a series of in vitro experiments. We identified 3 molecular subtypes of TC based on integrated multi-omics clustering algorithms, which were associated with overall survival and displayed distinct molecular features. We developed a CMLS based on 28 hub genes to predict patient outcomes, and demonstrated that CMLS outperformed other prognostic models. TC patients of relatively lower CMLS score had significantly higher levels of T cells, B cells, and macrophages, indicating an immune-activated state. Fibroblasts were predominantly enriched in the high CMLS group, along with markers associated with immune suppression and evasion. We identified several drugs that could be suitable for patients with high CMLS, including Staurosporine₁₀₃₄, Rapamycin₁₀₈₄, gemcitabine, and topotecan. SNAI1 was elevated in both undifferentiated TC cell lines, comparing to PTC cells. Knockdown of SNAI1 reduced the cell proliferation and EMT phenotypes of undifferentiated TC cells. Our findings highlight the importance of multi-omics analysis in understanding the molecular subtypes and immune characteristics of TC, and provide a novel prognostic model and potential therapeutic targets for this disease. Moreover, we identified SNAI1 in mediating TC progression through EMT in vitro. Show less
no PDF DOI: 10.1007/s10238-024-01387-z
SNAI1
Q Li, Z Chen, Y Zhang +7 more · 2024 · Hong Kong medical journal = Xianggang yi xue za zhi · added 2026-04-24
The coronavirus disease 2019 (COVID-19) pandemic has caused extensive disruption of public health worldwide. There were reports of COVID-19 patients having multiple complications. This study investiga Show more
The coronavirus disease 2019 (COVID-19) pandemic has caused extensive disruption of public health worldwide. There were reports of COVID-19 patients having multiple complications. This study investigated COVID-19 from a genetic perspective. We conducted RNA sequencing (RNA-Seq) analysis of respiratory tract samples from 24 patients with COVID-19. Eight patients receiving mechanical ventilation or extracorporeal membrane oxygenation were regarded as severe cases; the remaining 16 patients were regarded as non-severe cases. After quality control, statistical analyses were performed by logistic regression and the Kolmogorov-Smirnov test to identify genes associated with disease severity. Six genes were associated with COVID-19 severity in both statistical tests, namely RNA sequencing analysis showed that severe acute respiratory syndrome coronavirus 2 infection is associated with the overexpression of genes involved in nervous system disorders. Show less
no PDF DOI: 10.12809/hkmj2210178
BACE1
Xiaolu Chen, Yajiao Huang, Ban Chen +3 more · 2024 · European journal of medicinal chemistry · Elsevier · added 2026-04-24
Recently, FGFR4 has become a hot target for the treatment of cancer owing to its important role in cellular physiological processes. FGFR4 has been validated to be closely related to the occurrence of Show more
Recently, FGFR4 has become a hot target for the treatment of cancer owing to its important role in cellular physiological processes. FGFR4 has been validated to be closely related to the occurrence of cancers, such as hepatocellular carcinoma, rhabdomyosarcoma, breast cancer and colorectal cancer. Hence, the development of FGFR4 small-molecule inhibitors is essential to further understanding the functions of FGFR4 in cancer and the treatment of FGFR4-dependent diseases. Given the particular structures of FGFR1-4, the development of FGFR4 selective inhibitors presents significant challenges. The non-conserved Cys552 in the hinge region of the FGFR4 complex becomes the key to the selectivity of FGFR4 and FGFR1/2/3 inhibitors. In this review, we systematically introduce the close relationship between FGFR4 and cancer, and conduct an in-depth analysis of the developing methodology, binding mechanism, kinase selectivity, pharmacokinetic characteristics of FGFR4 selectivity inhibitors, and their application in clinical research. Show less
no PDF DOI: 10.1016/j.ejmech.2023.115947
FGFR1
Daniel T MacKeigan, Si-Yang Yu, Noa Chazot +10 more · 2024 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Platelets are small anucleate cells that play a key role in thrombosis and hemostasis. Our group previously identified apolipoprotein A-IV (apoA-IV) as an endogenous inhibitor of thrombosis by competi Show more
Platelets are small anucleate cells that play a key role in thrombosis and hemostasis. Our group previously identified apolipoprotein A-IV (apoA-IV) as an endogenous inhibitor of thrombosis by competitive blockade of the αIIbβ3 integrin on platelets. ApoA-IV inhibition of platelets was dependent on the N-terminal D5/D13 residues, and enhanced with absence of the C-terminus, suggesting it sterically hinders its N-terminal platelet binding site. The C-terminus is also the site of common apoA-IV polymorphisms apoA-IV-1a (T347S) and apoA-IV-2 (Q360H). Interestingly, both are linked with an increased risk of cardiovascular disease, however, the underlying mechanism remains unclear. Here, we generated recombinant apoA-IV and found that the Q360H or T347S polymorphisms dampened its inhibition of platelet aggregation in human platelet-rich plasma and gel-filtered platelets, reduced its inhibition of platelet spreading, and its inhibition of P-selectin on activated platelets. Using an ex vivo thrombosis assay, we found that Q360H and T347S attenuated its inhibition of thrombosis at both high (1800s Show less
no PDF DOI: 10.1016/j.bbrc.2024.149946
APOA4
Anqi Zhang, Ting Sun, Dandan Yu +15 more · 2024 · Clinical and experimental medicine · Springer · added 2026-04-24
Essential thrombocythemia (ET) and prefibrotic primary myelofibrosis (pre-PMF) are Philadelphia chromosome-negative myeloproliferative neoplasms. These conditions share overlapping clinical presentati Show more
Essential thrombocythemia (ET) and prefibrotic primary myelofibrosis (pre-PMF) are Philadelphia chromosome-negative myeloproliferative neoplasms. These conditions share overlapping clinical presentations; however, their prognoses differ significantly. Current morphological diagnostic methods lack reliability in subtype differentiation, underlining the need for improved diagnostics. The aim of this study was to investigate the multi-omics alterations in bone marrow biopsies of patients with ET and pre-PMF to improve our understanding of the nuanced diagnostic characteristics of both diseases. We performed proteomic analysis with 4D direct data-independent acquisition and microbiome analysis with 2bRAD-M sequencing technology to identify differential protein and microbe levels between untreated patients with ET and pre-PMF. Laboratory and multi-omics differences were observed between ET and pre-PMF, encompassing diverse pathways, such as lipid metabolism and immune response. The pre-PMF group showed an increased neutrophil-to-lymphocyte ratio and decreased high-density lipoprotein and cholesterol levels. Protein analysis revealed significantly higher CXCR2, CXCR4, and MX1 levels in pre-PMF, while APOC3, APOA4, FABP4, C5, and CFB levels were elevated in ET, with diagnostic accuracy indicated by AUC values ranging from 0.786 to 0.881. Microbiome assessment identified increased levels of Mycobacterium, Xanthobacter, and L1I39 in pre-PMF, whereas Sphingomonas, Brevibacillus, and Pseudomonas_E were significantly decreased, with AUCs for these genera ranging from 0.833 to 0.929. Our study provides preliminary insights into the proteomic and microbiome variations in the bone marrow of patients with ET and pre-PMF, identifying specific proteins and bacterial genera that warrant further investigation as potential diagnostic indicators. These observations contribute to our evolving understanding of the multi-omics variations and possible mechanisms underlying ET and pre-PMF. Show less
📄 PDF DOI: 10.1007/s10238-024-01350-y
APOA4
Xiaoyu Zheng, Hongcan Huang, Zhipeng Zhou +6 more · 2024 · Development (Cambridge, England) · added 2026-04-24
Hertwig's epithelial root sheath (HERS) interacts with dental apical mesenchyme and guides development of the tooth root, which is integral to the function of the whole tooth. However, the key genes i Show more
Hertwig's epithelial root sheath (HERS) interacts with dental apical mesenchyme and guides development of the tooth root, which is integral to the function of the whole tooth. However, the key genes in HERS essential for root development are understudied. Here, we show that Axin1, a scaffold protein that negatively regulates canonical Wnt signaling, is strongly expressed in the HERS. Axin1 ablation in the HERS of mice leads to defective root development, but in a manner independent of canonical Wnt signaling. Further studies reveal that Axin1 in the HERS negatively regulates the AKT1-mTORC1 pathway through binding to AKT1, leading to inhibition of ribosomal biogenesis and mRNA translation. Sonic hedgehog (Shh) protein, a morphogen essential for root development, is over-synthesized by upregulated mTORC1 activity upon Axin1 inactivation. Importantly, either haploinsufficiency of the mTORC1 subunit Rptor or pharmacological inhibition of Shh signaling can rescue the root defects in Axin1 mutant mice. Collectively, our data suggest that, independently of canonical Wnt signaling, Axin1 controls ribosomal biogenesis and selective mRNA translation programs via AKT1-mTORC1 signaling during tooth root development. Show less
no PDF DOI: 10.1242/dev.202899
AXIN1
Yan Li, Yuxiang Lin, Yali Tang +16 more · 2024 · Cell death & disease · Nature · added 2026-04-24
Tumour metabolic reprogramming is pivotal for tumour survival and proliferation. Investigating potential molecular mechanisms within the heterogeneous and clinically aggressive triple-negative breast Show more
Tumour metabolic reprogramming is pivotal for tumour survival and proliferation. Investigating potential molecular mechanisms within the heterogeneous and clinically aggressive triple-negative breast cancer (TNBC) subtype is essential to identifying novel therapeutic targets. Accordingly, we investigated the role of branched-chain α-keto acid dehydrogenase kinase (BCKDK) in promoting tumorigenesis in TNBC. We analysed The Cancer Genome Atlas dataset and immunohistochemically stained surgical specimens to investigate BCKDK expression and its prognostic implications in TNBC. The effects of BCKDK on tumorigenesis were assessed using cell viability, colony formation, apoptosis, and cell cycle assays, and subsequently validated in vivo. Metabolomic screening was performed via isotope tracer studies. The downstream target was confirmed using mass spectrometry and a co-immunoprecipitation experiment coupled with immunofluorescence analysis. Upstream transcription factors were also examined using chromatin immunoprecipitation and luciferase assays. BCKDK was upregulated in TNBC tumour tissues and associated with poor prognosis. BCKDK depletion led to reduced cell proliferation both in vitro and vivo. MYC-associated zinc finger protein (MAZ) was confirmed as the major transcription factor directly regulating BCKDK expression in TNBC. Mechanistically, BCKDK interacted with glucose-6-phosphate dehydrogenase (G6PD), leading to increased flux in the pentose phosphate pathway for macromolecule synthesis and detoxification of reactive oxygen species. Forced expression of G6PD rescued the growth defect in BCKDK-deficient cells. Notably, the small-molecule inhibitor of BCKDK, 3,6-dichlorobenzo(b)thiophene-2-carboxylic acid, exhibited anti-tumour effects in a patient-derived tumour xenograft model. Our findings hold significant promise for developing targeted therapies aimed at disrupting the MAZ/BCKDK/G6PD signalling pathway, offering potential advancements in treating TNBC through metabolic reprogramming. Show less
📄 PDF DOI: 10.1038/s41419-024-06835-y
BCKDK
Gerami D Seitzman, Jeremy D Keenan, Thomas M Lietman +11 more · 2024 · Cornea · added 2026-04-24
The purpose of this study was to identify conjunctival transcriptome differences in patients with Acanthamoeba keratitis compared with keratitis with no known associated pathogen. The host conjunctiva Show more
The purpose of this study was to identify conjunctival transcriptome differences in patients with Acanthamoeba keratitis compared with keratitis with no known associated pathogen. The host conjunctival transcriptome of 9 patients with Acanthamoeba keratitis (AK) is compared with the host conjunctival transcriptome of 13 patients with pathogen-free keratitis. Culture and/or confocal confirmed Acanthamoeba in 8 of 9 participants with AK who underwent metagenomic RNA sequencing as the likely pathogen. Cultures were negative in all 13 cases where metagenomic RNA sequencing did not identify a pathogen. Transcriptome analysis identified 36 genes differently expressed between patients with AK and patients with presumed sterile, or pathogen-free, keratitis. Gene enrichment analysis revealed that some of these genes participate in several biologic pathways important for cellular signaling, ion transport and homeostasis, glucose transport, and mitochondrial metabolism. Notable relatively differentially expressed genes with potential relevance to Acanthamoeba infection included CPS1 , SLC35B4 , STEAP2 , ATP2B2 , NMNAT3 , and AKAP12 . This research suggests that the local transcriptome in Acanthamoeba keratitis may be sufficiently robust to be detected in the conjunctiva and that corneas infected with Acanthamoeba may be distinguished from the inflamed cornea where no pathogen was identified. Given the low sensitivity for corneal cultures, identification of differentially expressed genes may serve as a suggestive transcriptional signature allowing for a complementary diagnostic technique to identify this blinding parasite. Knowledge of differentially expressed genes may also direct investigation of disease pathophysiology and suggest novel pathways for therapeutic targets. Show less
📄 PDF DOI: 10.1097/ICO.0000000000003545
CPS1
Rui Peng, Yan Chen, Liangnian Wei +6 more · 2024 · Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · Springer · added 2026-04-24
no PDF DOI: 10.1007/s10120-024-01489-3
FGFR1
Xiaoyu Wang, Yao Lin, Zheng Li +2 more · 2024 · Cancer informatics · SAGE Publications · added 2026-04-24
Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors. Whether APA regulatory factors affect the pr Show more
Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors. Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study. We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma. We also validated our APA model using independent GEO datasets (GSE29609, GSE76207). It was found that the expression levels of 5 APA regulatory factors (CPSF1, CPSF2, CSTF2, PABPC1, and PABPC4) were significantly associated with tumor gene mutation burden (TMB) score in renal clear cell carcinoma, and the risk score constructed using the expression level of 5 key APA regulatory factors could be used to predict the outcome of renal clear cell carcinoma. The TMB score is associated with the remodeling of the immune microenvironment. By identifying key APA regulatory factors in renal cell carcinoma and constructing risk scores for key APA regulatory factors, we showed that key APA regulators affect prognosis of renal clear cell carcinoma patients. In addition, the risk score level is associated with TMB, indicating that APA may affect the efficacy of immunotherapy through immune microenvironment-related genes. This helps us better understand the mRNA processing mechanism of renal clear cell carcinoma. Show less
no PDF DOI: 10.1177/11769351231180789
PABPC4
Wei Ding, Liting Yan, Li Sheng +7 more · 2024 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
The fibroblast growth factor receptor (FGFR) signaling pathway plays important roles in cellular processes such as proliferation, differentiation, and migration. In this study, we highlighted the pote Show more
The fibroblast growth factor receptor (FGFR) signaling pathway plays important roles in cellular processes such as proliferation, differentiation, and migration. In this study, we highlighted the potential of FGFR inhibitors bearing the ( Show less
no PDF DOI: 10.1021/acs.jmedchem.3c02040
FGFR1
Ankang Liu, Xiaohong Liu, Yuanhao Wei +6 more · 2024 · Cardiovascular toxicology · Springer · added 2026-04-24
Previous observational studies have explored the association between serum lipids, apolipoproteins, and adverse ventricular/aortic structure and function. However, whether a causal link exists is unce Show more
Previous observational studies have explored the association between serum lipids, apolipoproteins, and adverse ventricular/aortic structure and function. However, whether a causal link exists is uncertain. This study employed a two-sample Mendelian randomization (MR), colocalization, reverse, and multivariable MR (MVMR) approach to examine the causal associations among five serum lipids, two apolipoproteins, and 32 cardiac magnetic resonance (CMR) traits. Utilizing single-nucleotide polymorphisms (SNPs) linked to serum lipids and apolipoproteins as instrumental variables. CMR traits from seven independent genome-wide association studies served as preclinical endophenotypes, offering insights into aortic and cardiac structure/function. The primary analysis utilized a random-effects inverse variance method (IVW), followed by sensitivity and validation analyses. In the primary IVW MR analyses, genetically predicted low-density lipoprotein cholesterol (LDL-C) levels were positively correlated with increased descending aorta strain (DAo strain) (β = 0.098; P = 2.69E-07) and ascending aorta strain (AAo strain) (β = 0.079; P = 5.19E-05). Genetically predicted high-density lipoprotein cholesterol (HDL-C) levels were positively correlated with left ventricular radial peak diastolic strain rate (LV-PDSRll) (β = 0.176; P = 2.89E-05) and the left ventricular longitudinal peak diastolic strain rate (LV-PDSRrr) (β = 0.059; P = 2.44E-06), and negatively correlated with left ventricular regional wall thickness (LVRWT). While apolipoprotein B (ApoB) levels were positively correlated with AAo strain (β = 0.076; P = 1.16E-05), DAo strain (β = 0.065; P = 2.77E-05). A shared causal variant was identified to demonstrate the associations of ApoB with AAo strain and DAo strain using colocalization analysis. Sensitivity analyses confirmed the robustness of these associations. Targeting lipid and apolipoprotein levels through interventions may provide novel strategies for the primary prevention of CVDs. Show less
📄 PDF DOI: 10.1007/s12012-024-09930-w
APOB
Hao Wu, Tianyu Lou, Mingxia Pan +13 more · 2024 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Nonalcoholic steatohepatitis (NASH) is a prominent cause of liver-related death that poses a threat to global health and is characterized by severe hepatic steatosis, lobular inflammation, and balloon Show more
Nonalcoholic steatohepatitis (NASH) is a prominent cause of liver-related death that poses a threat to global health and is characterized by severe hepatic steatosis, lobular inflammation, and ballooning degeneration. To date, no Food and Drug Administration-approved medicine is commercially available. The Chaihu Guizhi Ganjiang Decoction (CGGD) shows potential curative effects on regulation of blood lipids and blood glucose, mitigation of organism inflammation, and amelioration of hepatic function. However, the overall regulatory mechanisms underlying its effects on NASH remain unclear. This study aimed to investigate the efficiency of CGGD on methionine- and choline-deficient (MCD)-induced NASH and unravel its underlying mechanisms. A NASH model of SD rats was established using an MCD diet for 8 weeks, and the efficacy of CGGD was evaluated based on hepatic lipid accumulation, inflammatory response, and fibrosis. The effects of CGGD on the intestinal barrier, metabolic profile, and differentially expressed genes (DEGs) profile were analyzed by integrating gut microbiota, metabolomics, and transcriptome sequencing to elucidate its mechanisms of action. In MCD-induced NASH rats, pathological staining demonstrated that CGGD alleviated lipid accumulation, inflammatory cell infiltration, and fibrosis in the hepatic tissue. After CGGD administration, liver index, liver weight, serum alanine aminotransferase (ALT), and aspartate aminotransferase (AST) contents, liver triglycerides (TG), and free fatty acids (FFAs) were decreased, meanwhile, it down-regulated the level of proinflammatory mediators (TNF-α, IL-6, IL-1β, MCP-1), and up-regulated the level of anti-inflammatory factors (IL-4, IL-10), and the expression of liver fibrosis markers TGFβ, Acta2, Col1a1 and Col1a2 were weakened. Mechanistically, CGGD treatment altered the diversity of intestinal flora, as evidenced by the depletion of Allobaculum, Blautia, norank_f_Erysipelotrichaceae, and enrichment of the probiotic genera Roseburia, Lactobacillus, Lachnoclostridium, etc. The colonic histopathological results indicated that the gut barrier damage recovered in the CGGD treatment group, and the expression levels of colonic short-chain fatty acids (SCFAs)-specific receptors FFAR2, FFAR3, and tight junction (TJs) proteins ZO-1, Occludin, Claudin-1 were increased compared with those in the model group. Further metabolomic and transcriptomic analyses suggested that CGGD mitigated the lipotoxicity caused by glycerophospholipid and eicosanoid metabolism disorders by decreasing the levels of PLA2G4A, LPCAT1, COX2, and LOX5. In addition, CGGD could activate the inhibitory lipotoxic transcription factor PPARα, regulate the proteins of FABP1, APOC2, APOA2, and LPL to promote fatty acid catabolism, and suppress the TLR4/MyD88/NFκB pathway to attenuate NASH. Our study demonstrated that CGGD improved steatosis, inflammation, and fibrosis on NASH through enhancing intestinal barrier integrity and alleviating PPARα mediated lipotoxicity, which makes it an attractive candidate for potential new strategies for NASH prevention and treatment. Show less
no PDF DOI: 10.1016/j.jep.2024.117841
LPL
Jun Yi Liu, Yan Zhi Yi, Qi Wei Guo +10 more · 2024 · Lipids in health and disease · BioMed Central · added 2026-04-24
Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) poly Show more
Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) polymorphisms at angiotensin-converting enzyme gene (ACE) and T/C polymorphisms in the angiotensin type 1 receptor gene (AGTR1) are related to diabetes and lipid levels, but the associations are controversial. Thus, the current research aimed to explore the effects of ACE I/D, AGTR1 rs5182 and diabetes mellitus on serum lipid profiles in 385 Chinese participants with an average age of 75.01 years. The ACE I/D variant was identified using the polymerase chain reaction (PCR) method, whereas the AGTR1 rs5182 polymorphism was identified using the PCR-based restriction fragment length polymorphism (PCR-RFLP) method and verified with DNA sequencing. Total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured using routine methods, and the lipid ratios were calculated. ACE I/D, but not AGTR1 rs5182, was a predictor of TG/HDL-C for the whole study population. Both ACE I/D and AGTR1 rs5182 were predictors of HDL-C and LDL-C levels in females but not in males. Moreover, in females, diabetes mellitus and ACE I/D were identified as predictors of TG and TG/HDL-C, whereas AGTR1 rs5182 and diabetes mellitus were predictors of TG/HDL-C. Moreover, diabetes mellitus and the combination of ACE I/D and AGTR1 rs5182 variations were predictors of TG and TG/HDL-C exclusively in females. The results demonstrated the potential for gender-dependent interactions of ACE I/D, AGTR1 rs5182, and diabetes on lipid profiles. These findings may serve as an additional explanation for the inconsistent changes of blood lipids in individuals with diabetes mellitus, thereby offering a novel perspective for the clinical management of blood lipid levels in diabetic patients. Show less
📄 PDF DOI: 10.1186/s12944-024-02222-w
APOB
Niels Pietsch, Christina Yingxian Chen, Svenja Kupsch +15 more · 2024 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
no PDF DOI: 10.1101/2023.05.25.542365
MYBPC3
Peter J Metzger, Aileen Zhang, Bradley A Carlson +11 more · 2024 · The Journal of clinical investigation · added 2026-04-24
Melanocortin 4 receptor (MC4R) mutations are the most common cause of human monogenic obesity and are associated with hyperphagia and increased linear growth. While MC4R is known to activate Gsα/cAMP Show more
Melanocortin 4 receptor (MC4R) mutations are the most common cause of human monogenic obesity and are associated with hyperphagia and increased linear growth. While MC4R is known to activate Gsα/cAMP signaling, a substantial proportion of obesity-associated MC4R mutations do not affect MC4R/Gsα signaling. To further explore the role of specific MC4R signaling pathways in the regulation of energy balance, we examined the signaling properties of one such mutant, MC4R (F51L), as well as the metabolic consequences of MC4RF51L mutation in mice. The MC4RF51L mutation produced a specific defect in MC4R/Gq/11α signaling and led to obesity, hyperphagia, and increased linear growth in mice. The ability of a melanocortin agonist to acutely inhibit food intake when delivered to the paraventricular nucleus (PVN) was lost in MC4RF51L mice, as well as in WT mice in which a specific Gq/11α inhibitor was delivered to the PVN; this provided evidence that a Gsα-independent signaling pathway, namely Gq/11α, significantly contributes to the actions of MC4R on food intake and linear growth. These results suggest that a biased MC4R agonist that primarily activates Gq/11α may be a potential agent to treat obesity with limited untoward cardiovascular and other side effects. Show less
📄 PDF DOI: 10.1172/JCI165418
MC4R
Hui Chen, Isabelle Martins, Guido Kroemer · 2024 · Autophagy · Taylor & Francis · added 2026-04-24
DBI/ACBP (diazepam binding inhibitor, acyl-CoA binding protein) is produced by multiple cell types and detectable in blood plasma. DBI acts on GABRA (gamma-aminobutyric acid type A receptor) complexes Show more
DBI/ACBP (diazepam binding inhibitor, acyl-CoA binding protein) is produced by multiple cell types and detectable in blood plasma. DBI acts on GABRA (gamma-aminobutyric acid type A receptor) complexes containing GABRG2 (gamma-aminobutyric acid type A receptor, subunit gamma 2) to inhibit macroautophagy/autophagy and hence can be considered as an "autophagy checkpoint". In patients with poor-prognosis anorexia nervosa, as well as in mice developing stress-induced anorexia, circulating DBI levels are reduced. Using a chemical-genetic system that makes it possible to control DBI secretion by hepatocytes, we showed that increasing DBI levels suffices to prevent anorexia induced by chronic restraint stress or chemotherapy with cisplatin, doxorubicin or paclitaxel in mice. At the mechanistic level, DBI administration acts through GABRA outside of the central nervous system and reduces the plasma levels of anorexigenic factors such as GDF15 (growth differentiation factor 15) and LCN2 (lipocalin 2), as well as anorexigenic signaling via the LCN2 receptor MC4R (melanocortin 4 receptor) in the hypothalamus. Accordingly, DBI supplementation stimulates food intake and normalizes whole body weight, body composition and metabolism in mouse models of anorexia. This normalization extends to the liver transcriptome and metabolome. Altogether, it appears that enhancing DBI levels constitutes a promising strategy for combating anorexia. Show less
no PDF DOI: 10.1080/15548627.2024.2402162
MC4R
Huan Zhang, Yuxi Chen, Peng Xu +4 more · 2024 · Chronic diseases and translational medicine · Wiley · added 2026-04-24
Genome-wide association studies (GWAS) have identified more than a thousand loci for blood pressure (BP). Functional genes in these loci are cell-type specific. The aim of this study was to elucidate Show more
Genome-wide association studies (GWAS) have identified more than a thousand loci for blood pressure (BP). Functional genes in these loci are cell-type specific. The aim of this study was to elucidate potentially functional genes associated with BP in the aorta through the utilization of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs). Utilizing large-scale genetic data of 757,601 individuals from the UK Biobank and International Consortium of Blood Pressure consortium, we identified associations between RNAm-SNPs and BP. The association between RNAm-SNPs, gene expression, and BP were examined. A total of 355 RNAm-SNPs related to m The present study identified RNAm-SNPs in BP loci and elucidated the associations between the RNAm-SNPs, gene expression, and BP. The identified BP-associated genes in aortic cells were associated with AD. Show less
📄 PDF DOI: 10.1002/cdt3.124
MLXIPL
Jie-Pin Li, Yuan-Jie Liu, Yang Li +7 more · 2024 · Journal of translational medicine · BioMed Central · added 2026-04-24
Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknow Show more
Cellular communication (CC) influences tumor development by mediating intercellular junctions between cells. However, the role and underlying mechanisms of CC in malignant transformation remain unknown. Here, we investigated the spatiotemporal heterogeneity of CC molecular expression during malignant transformation. It was found that although both tight junctions (TJs) and gap junctions (GJs) were involved in maintaining the tumor microenvironment (TME), they exhibited opposite characteristics. Mechanistically, for epithelial cells (parenchymal component), the expression of TJ molecules consistently decreased during normal-cancer transformation and is a potential oncogenic factor. For fibroblasts (mesenchymal component), the expression of GJs consistently increased during normal-cancer transformation and is a potential oncogenic factor. In addition, the molecular profiles of TJs and GJs were used to stratify colorectal cancer (CRC) patients, where subtypes characterized by high GJ levels and low TJ levels exhibited enhanced mesenchymal signals. Importantly, we propose that leiomodin 1 (LMOD1) is biphasic, with features of both TJs and GJs. LMOD1 not only promotes the activation of cancer-associated fibroblasts (CAFs) but also inhibits the Epithelial-mesenchymal transition (EMT) program in cancer cells. In conclusion, these findings demonstrate the molecular heterogeneity of CC and provide new insights into further understanding of TME heterogeneity. Show less
📄 PDF DOI: 10.1186/s12967-024-05369-3
LMOD1
Zhenqiu Liu, Huangbo Yuan, Yunzhi Wang +5 more · 2024 · Journal of proteome research · ACS Publications · added 2026-04-24
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint pot Show more
Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection. Show less
no PDF DOI: 10.1021/acs.jproteome.4c00397
APOB