👤 Yen-Ching Chen

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2981
Articles
1996
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Also published as: Wen-Chau Chen, Jingzhao Chen, Dexi Chen, Haifeng Chen, Chung-Jen Chen, Bo-Jun Chen, Gao-Feng Chen, Changyan Chen, Weiwei Chen, Fenghua Chen, Xiaojiang S Chen, Xiu-Juan Chen, Jung-Sheng Chen, Xiao-Ying Chen, Chong Chen, Junyang Chen, YiPing Chen, Xiaohan Chen, Li-Zhen Chen, Jiujiu Chen, Shin-Wen Chen, Guangping Chen, Dapeng Chen, Ximei Chen, Renwei Chen, Jianfei Chen, Yulu Chen, Yu-Chi Chen, Jia-De Chen, Rongfang Chen, She Chen, Zetian Chen, Tianran Chen, Emily Chen, Baoxiang Chen, Ya-Chun Chen, Dongxue Chen, Wei-xian Chen, Danmei Chen, Ceshi Chen, Junling Chen, Xia Chen, Daoyuan Chen, Yongbin Chen, Chi-Yu Chen, Dian Chen, Xiuxiu Chen, Bo-Fang Chen, Fangyuan Chen, Jin-An Chen, Xiaojuan Chen, Zhuohui Chen, Junqi Chen, Lina Chen, Fangfang Chen, Hanwen Chen, Yilei Chen, Po-Han Chen, Xiaoxiang Chen, Jimei Chen, Guochong Chen, Yanyun Chen, Yifei Chen, Cheng-Yu Chen, Zi-Jiang Chen, Jiayuan Chen, Miaoran Chen, Junshi Chen, Yu-Ying Chen, Pengxiang Chen, Hui-Ru Chen, Yupeng Chen, Ida Y-D Chen, Xiaofeng Chen, Qiqi Chen, Shengnan Chen, Mao-Yuan Chen, Lizhu Chen, Weichan Chen, Xiang-Bin Chen, Hanxi Chen, Sulian Chen, Zoe Chen, Minghong Chen, Chi Chen, Yananlan Chen, Yanzhu Chen, Shiyi Chen, Ze-Xu Chen, Zhiheng Chen, Jia-Mei Chen, Shuqin Chen, Yi-Hau Chen, Danni Chen, Donglong Chen, Xiaomeng Chen, Yidong Chen, Keyu Chen, Hao Chen, Junmin Chen, Wenlong Chen, Yufei Chen, Wanbiao Chen, Mo Chen, Youjia Chen, Xin-Jie Chen, Lanlan Chen, Huapu Chen, Shuaiyin Chen, Jing-Hsien Chen, Hengsheng Chen, Bing-Bing Chen, Fa-Xi Chen, Zhiqiang Chen, Ming-Huang Chen, Liangkai Chen, Li-Jhen Chen, Zhi-Hao Chen, Yinzhu Chen, Guanghong Chen, Gaozhi Chen, Jiakang Chen, Yongke Chen, Guangquan Chen, Li-Hsien Chen, Yiduo Chen, Zongnan Chen, Jing Chen, Meilan Chen, Jin-Shuen Chen, Huanxiong Chen, Yann-Jang Chen, Guozhong Chen, Yu-Bing Chen, Xiaobin Chen, Catherine Qing Chen, Youhu Chen, Hui Mei Chen, L F Chen, Haiyang Chen, Ruilin Chen, Peng Chen, Kailang Chen, Chao Chen, Suipeng Chen, Zemin Chen, Jianlin Chen, Shang-Chih Chen, Yen-Hsieh Chen, Jia-Lin Chen, Chaojin Chen, Minglang Chen, Xiatian Chen, Zeyu Chen, Kang Chen, Mei-Chi Chen, Jihai Chen, Pei Chen, Defang Chen, Zhao Chen, Tianrui Chen, Tingtao Chen, Caressa Chen, Jiwei Chen, Xuerong Chen, Yizhi Chen, XueShu Chen, Mingyue Chen, Huichao Chen, Chun-Chi Chen, Xiaomin Chen, Hetian Chen, Yuxing Chen, Jie-Hua Chen, Chuck T Chen, Yuanjia Chen, Hong Chen, Jianxiong Chen, S Chen, D M Chen, Jiao-Jiao Chen, Gongbo Chen, Xufeng Chen, Xiao-Jun Chen, Harn-Shen Chen, Qiu Jing Chen, Tai-Heng Chen, Pei-Lung Chen, Kaifu Chen, Huang-Pin Chen, Tse-Wei Chen, Yanrong Chen, Xianfeng Chen, Chung-Yung Chen, Yuelei Chen, Qili Chen, Guanren Chen, TsungYen Chen, Yu-Si Chen, Junsheng Chen, Min-Jie Chen, Xin-Ming Chen, Jiabing Chen, Sili Chen, Qinying Chen, Yue Chen, Lin Chen, Xiaoli Chen, Zhuo Chen, Aoshuang Chen, Junyu Chen, Chunji Chen, Yian Chen, Shanchun Chen, Shuen-Ei Chen, Canrong Chen, Shih-Jen Chen, Yaowu Chen, Han Chen, Yih-Chieh Chen, Wei-Cong Chen, Yanfen Chen, Tao Chen, Huangtao Chen, Jingyi Chen, Sheng Chen, Jing-Wen Chen, Gao Chen, Lei-Lei Chen, Kecai Chen, Yao-Shen Chen, Haiyu Chen, W Chen, Xiaona Chen, Cheng-Sheng Chen, X R Chen, Shuangfeng Chen, Jingyuan Chen, Xinyuan Chen, Huanhuan Chen, Mengling Chen, Liang-Kung Chen, Ming-Huei Chen, Hongshan Chen, Cuncun Chen, Qingchao Chen, Yanzi Chen, Lingli Chen, Shiqian Chen, Liangwan Chen, Lexia Chen, Wei-Ting Chen, Zhencong Chen, Tzy-Yen Chen, Mingcong Chen, Honglei Chen, Yuyan Chen, Huachen Chen, Yu Chen, Li-Juan Chen, Aozhou Chen, Xinlin Chen, Wai Chen, Dake Chen, Bo-Sheng Chen, Meilin Chen, Kequan Chen, Hong Yang Chen, Yan Chen, Bowei Chen, Silian Chen, Jian Chen, Yongmei Chen, Ling Chen, Jinbo Chen, Yingxi Chen, Ge Chen, Max Jl Chen, C Z Chen, Weitao Chen, Xiaole L Chen, Yonglu Chen, Shih-Pin Chen, Jiani Chen, Huiru Chen, San-Yuan Chen, Bing Chen, Xiao-ping Chen, Feiyue Chen, Shuchun Chen, Zhaolin Chen, Qianxue Chen, Xiaoyang Chen, Bowang Chen, Yinghui Chen, Ting-Ting Chen, Xiao-Yang Chen, Chi-Yuan Chen, Zhi-zhe Chen, Ting-Tao Chen, Xiaoyun Chen, Min-Hsuan Chen, Kuan-Ting Chen, Yongheng Chen, Wenhao Chen, Shengyu Chen, Kai Chen, Yueh-Peng Chen, Guangju Chen, Minghua Chen, Hong-Sheng Chen, Qingmei Chen, Song-Mei Chen, Limei Chen, Yuqi Chen, Yuyang Chen, Yang-Ching Chen, Yu-Gen Chen, Peizhan Chen, Rucheng Chen, Jin-Xia Chen, Szu-Chieh Chen, Xiaojun Chen, Jialing Chen, Heni Chen, Yi Feng Chen, Sen Chen, Alice Ye A Chen, Wen Chen, Han-Chun Chen, Dawei Chen, Fangli Chen, Ai-Qun Chen, Zhaojun Chen, Gong Chen, Yishan Chen, Zhijing Chen, Qiuxuan Chen, Miao-Der Chen, Fengwu Chen, Weijie Chen, Weixin Chen, Mei-Ling Chen, Hung-Po Chen, Rui-Pei Chen, Nian-Ping Chen, Tielin Chen, Canyu Chen, Xiaotao Chen, Nan Chen, C Chen, Juanjuan Chen, Xinan Chen, Jiaping Chen, Xiao-Lin Chen, Jianping Chen, Yayun Chen, Le Qi Chen, Jen-Sue Chen, Mechi Chen, Miao-Yu Chen, Zhou Chen, Szu-Han Chen, Zhen Bouman Chen, Baihua Chen, Qingao Chen, Shao-Ke Chen, Feng Chen, Jiawen Chen, Lianmin Chen, Sifeng Chen, Mengxia Chen, Xueli Chen, Can Chen, Yibo Chen, Zinan Chen, Lei-Chin Chen, Carol Chen, Yanlin Chen, Zihang Chen, Zaozao Chen, Haiqin Chen, Lu Hua Chen, Zhiyuan Chen, Meiyu Chen, Du-Qun Chen, Keying Chen, Naifei Chen, Peixian Chen, Jin-Ran Chen, Yijun Chen, Yulin Chen, Fumei Chen, Zhanfei Chen, Zhe-Yu Chen, Xin-Qi Chen, Valerie Chen, Ru Chen, Mengqing Chen, Runsheng Chen, Tong Chen, Tan-Zhou Chen, Suet Nee Chen, Cuicui Chen, Yifan Chen, Tian Chen, XiangFan Chen, Lingyi Chen, Hsiao-Yun Chen, Kenneth L Chen, Ni Chen, Huishan Chen, Fang-Yu Chen, Ken Chen, Yongshen Chen, Qiong Chen, Mingfeng Chen, Shoudeng Chen, Qiao Chen, Qian Chen, Yuebing Chen, Xuehua Chen, Chang-Lan Chen, Min-Hu Chen, Hongbin Chen, Jingming Chen, Qing Chen, Yu-Fan Chen, Hao-Zhu Chen, Yunjia Chen, Zhongjian Chen, Mingyi Chen, Qianping Chen, Huaxin Chen, Dong-Mei Chen, Peize Chen, Leijie Chen, Ming-Yu Chen, Jiaxuan Chen, Xiao-chun Chen, Wei-Min Chen, Ruisen Chen, Xuanwei Chen, Guiquan Chen, Minyan Chen, Feng-Ling Chen, Yili Chen, Alvin Chen, Xiaodong Chen, Bohong Chen, Chih-Ping Chen, Xuanjing Chen, Shuhui Chen, Ming-Hong Chen, Tzu-Yu Chen, Brian Chen, Bowen Chen, Kai-En Chen, Szu-Chia Chen, Guangchun Chen, Fang Chen, Chuyu Chen, Haotian Chen, Xiaoting Chen, Shaoliang Chen, Chun-Houh Chen, Shali Chen, Yu-Cheng Chen, Zhijun Chen, B Chen, Yuan Chen, Zhanglin Chen, Chaoran Chen, Xing-Long Chen, Zhinan Chen, Yu-Hui Chen, Yuquan Chen, Andrew Chen, Fengming Chen, Guangyong Chen, Jun Chen, Wenshuo Chen, Yi-Guang Chen, Jing-Yuan Chen, Kuangyang Chen, Mingyang Chen, Shaofei Chen, Weicong Chen, Gonghai Chen, Di-Long Chen, Limin Chen, Jishun Chen, Yunfei Chen, Caihong Chen, Tongsheng Chen, Ligang Chen, Wenqin Chen, Shiyu Chen, Xiaoyong Chen, Christina Y Chen, Yushan Chen, Ginny I Chen, Guo-Jun Chen, Xianzhen Chen, Wanling Chen, Kuan-Jen Chen, Maorong Chen, Kaijian Chen, Erqu Chen, Shen Chen, Quan Chen, Zian Chen, Yi-Lin Chen, Juei-Suei Chen, Yi-Ting Chen, Huaiyong Chen, Minjian Chen, Qianzhi Chen, Jiahao Chen, Xikun Chen, Juan-Juan Chen, Xiaobo Chen, Tianzhen Chen, Ziming Chen, Qianbo Chen, Jindong Chen, Jiu-Chiuan Chen, Yinwei Chen, Carl Pc Chen, Li-Hsin Chen, Jenny Chen, Ruoyan Chen, Yanqiu Chen, Yen-Fu Chen, Haiyan Chen, Zhebin Chen, Si Chen, Jian-Qiao Chen, Yang-Yang Chen, Ningning Chen, Zhifeng Chen, Zhenyi Chen, Hangang Chen, Zihe Chen, Mengdi Chen, Zhichuan Chen, Xu Chen, Huixi Chen, Weitian Chen, Bao-Sheng Chen, Tien-Hsing Chen, Junchen Chen, Yan-yan Chen, Xiangning Chen, Sijia Chen, Xinyan Chen, Kuan-Yu Chen, Qunxiang Chen, Guangliang Chen, Bing-Huei Chen, Fei Xavier Chen, Zhangcheng Chen, Qianming Chen, Xianze Chen, Yanhua Chen, Qinghao Chen, Yanting Chen, Sijuan Chen, Chen-Mei Chen, Qiankun Chen, Jianan Chen, Rong Chen, Xiankai Chen, Kaina Chen, Gui-Hai Chen, Y-D Ida Chen, Quanjiao Chen, Shuang Chen, Lichang Chen, Xinyi Chen, Yong-Jun Chen, Zhaoli Chen, Chunnuan Chen, Jui-Chang Chen, Zhiang Chen, Weirui Chen, Zhenguo Chen, Jennifer F Chen, Zhiguo Chen, Kunmei Chen, Huan-Xin Chen, Mengyan Chen, Dongrong Chen, Siyue Chen, Xianyue Chen, Chien-Lun Chen, YiChung Chen, Guang Chen, Quanwei Chen, Zongming E Chen, Ting-Huan Chen, Michael C Chen, Jinli Chen, Beth L Chen, Yuh-Lien Chen, Peihong Chen, Qiaoling Chen, Jiale Chen, Shufeng Chen, Xiaowan Chen, Xian-Kai Chen, Ling-Yan Chen, Yen-Ling Chen, Guiying Chen, Guangyi Chen, Yuling Chen, Xiangqiu Chen, Haiquan Chen, Cuie Chen, Gui-Lai Chen, R Chen, Heng-Yu Chen, Yongxun Chen, Fuxiang Chen, Mingmei Chen, Hua-Pu Chen, Yulong Chen, Zhitao Chen, Guohua Chen, Cheng-Yi Chen, Hongxu Chen, Yuanhao Chen, Qichen Chen, Hualin Chen, Guo-Rong Chen, Rongsheng Chen, Xuesong Chen, Wei-Fei Chen, Bao-Bao Chen, Anqi Chen, Yi-Han Chen, Ying-Jung Chen, Jinhuang Chen, Guochao Chen, Lei Chen, S N Chen, Songfeng Chen, Chenyang Chen, Xing Chen, Letian Chen, Meng Xuan Chen, Xiang-Mei Chen, Xiaoyan Chen, Yi-Heng Chen, D F Chen, Bang Chen, Jiaxu Chen, Wei Chen, Sihui Chen, Shu-Hua Chen, I-M Chen, Xuxin Chen, Zhangxin Chen, Jin Chen, Yin-Huai Chen, Wuyan Chen, Bingqing Chen, Bao-Fu Chen, Zhen-Hua Chen, Dan Chen, Zhe-Sheng Chen, Ranyun Chen, Wanyin Chen, Xueyan Chen, Xiaoyu Chen, Tai-Tzung Chen, Xiaofang Chen, Yongxing Chen, Yanghui Chen, Hekai Chen, Yuanwei Chen, Liang Chen, Hui-Jye Chen, Chengchun Chen, Han-Bin Chen, Shuaijie Chen, Yibing Chen, Kehui Chen, Shuhai Chen, Xueling Chen, Ying-Jie Chen, Qingxing Chen, Fang-Zhi Chen, Mei-Hua Chen, Yutong Chen, Lixian Chen, Alex Chen, Qiuhong Chen, Qiuxia Chen, Liping Chen, Hou-Tsung Chen, Zhanghua Chen, Chun-Fa Chen, Chian-Feng Chen, Benjamin P C Chen, Yewei Chen, Mu-Hong Chen, Jianshan Chen, Xiaguang Chen, Meiling Chen, Heng Chen, Ying-Hsiang Chen, Longyun Chen, Dengpeng Chen, Jichong Chen, Shixuan Chen, Liaobin Chen, Everett H Chen, ZhuoYu Chen, Qihui Chen, Zhiyong Chen, Nuan Chen, Hongmei Chen, Guiqian Chen, Yan Q Chen, Fengling Chen, Hung-Chang Chen, Zhenghong Chen, Chengsheng Chen, Hegang Chen, Huei-Yan Chen, Liutao Chen, Meng-Lin Chen, Xi Chen, Qing-Juan Chen, Linna Chen, Xiaojing Chen, Lang Chen, Gengsheng Chen, Fengrong Chen, Weilun Chen, Shi Chen, Wan-Yi Chen, On Chen, Yufeng Chen, Benjamin Chen, Hui-Zhao Chen, Bo-Rui Chen, Kangyong Chen, Ruixiang Chen, Weiyong Chen, Ning-Hung Chen, Meng-Ping Chen, Huimei Chen, Ying Chen, Kang-Hua Chen, Pei-zhan Chen, Liujun Chen, Hanqing Chen, Chengchuan Chen, Guojun Chen, Yongfa Chen, Li Chen, Mingling Chen, Jacinda Chen, Jinlun Chen, Kun Chen, Yi Chen, Chiung Mei Chen, Shaotao Chen, Tianhong Chen, Chanjuan Chen, Yuhao Chen, Huizhi Chen, Chung-Hsing Chen, Qiuchi Chen, Haoting Chen, Luzhu Chen, Huanhua Chen, Long Chen, Jiang-hua Chen, Kai-Yang Chen, Jing-Zhou Chen, Yong-Syuan Chen, Lifang Chen, Ruonan Chen, Meimei Chen, Qingchuan Chen, Liugui Chen, Shaokun Chen, Yi-Yung Chen, Jintian Chen, Xuhui Chen, Dongyan Chen, Huei-Rong Chen, Xianmei Chen, Jinyan Chen, Yuxi Chen, Qingqing Chen, Weibo Chen, Qiwei Chen, Mingxia Chen, Hongmin Chen, Jiahui Chen, Yen-Jen Chen, Zihan Chen, Guozhou Chen, Fei Chen, Zhiting Chen, Denghui Chen, Gary Chen, Hongli Chen, Jack Chen, Zhigang Chen, Lie Chen, Siyuan Chen, Haojie Chen, Qing-Wei Chen, Maochong Chen, Mei-Jie Chen, Haining Chen, Xing-Zhen Chen, Weiqing Chen, Huanchun Chen, C-Y Chen, Tzu-An Chen, Jen-Hau Chen, Xiaojie Chen, Dongquan Chen, Gao B Chen, Daijie Chen, Zixi Chen, Lingfeng Chen, Jiayi Chen, Zan Chen, Shuming Chen, Mei-Hsiu Chen, Xueqin Chen, Huan Chen, Xiaoqing Chen, Hui-Xiong Chen, Ruoying Chen, Deying Chen, Huixian Chen, Zhezhe Chen, Lu Chen, Xiaolong Chen, Si-Yue Chen, Xinwei Chen, Wentao Chen, Yucheng Chen, Jiajing Chen, Allen Menglin Chen, Chixiang Chen, Shiqun Chen, Wenwu Chen, Chin-Chuan Chen, Ningbo Chen, Hsin-Hung Chen, Shenglan Chen, Jia-Feng Chen, Changya Chen, ZhaoHui Chen, Guo Chen, Juhai Chen, Xiao-Quan Chen, Cuimin Chen, Yongshuo Chen, Sai Chen, Fengyang Chen, Siteng Chen, Hualan Chen, Lian Chen, Yuan-Hua Chen, Minjie Chen, Shiyan Chen, Z Chen, Zhengzhi Chen, Jonathan Chen, H Chen, You-Yue Chen, Shu-Gang Chen, Hsuan-Yu Chen, Hongyue Chen, Weiyi Chen, Jiaqi Chen, Chengde Chen, Shufang Chen, Ze-Hui Chen, Xiuping Chen, Zhuojia Chen, Zhouji Chen, Lidian Chen, Yilan Chen, Kuan-Ling Chen, Alon Chen, Zi-Yue Chen, Hongmou Chen, Fang-Zhou Chen, Jianzhou Chen, Wenbiao Chen, Yujie Chen, Zhijian Chen, Zhouqing Chen, Xiuhui Chen, Qingguang Chen, Hanbei Chen, Qianyu Chen, Mengping Chen, Yongqi Chen, Sheng-Yi Chen, Siqi Chen, Yelin Chen, Shirui Chen, Yuan-Tsong Chen, Dongyin Chen, Lingxue Chen, Long-Jiang Chen, Yunshun Chen, Yahong Chen, Yaosheng Chen, Zhonghua Chen, Jingyao Chen, Pei-Yin Chen, Fusheng Chen, Xiaokai Chen, Shuting Chen, Miao-Hsueh Chen, Y-D I Chen, Zijie Chen, Haozhu Chen, Haodong Chen, Xiong Chen, Wenxi Chen, Feng-Jung Chen, Shangwu Chen, Zhiping Chen, Zhang-Yuan Chen, Wentong Chen, Ou Chen, Ruiming Chen, Xiyu Chen, Shuqiu Chen, Xiaoling Chen, Ruimin Chen, Hsiao-Wang Chen, Dongli Chen, Haibo Chen, Yiyun Chen, Luming Chen, Wenting Chen, Chongyang Chen, Qingqiu Chen, Wen-Pin Chen, Yuhui Chen, Lingxia Chen, Jun-Long Chen, Xingyu Chen, Haotai Chen, Bang-dang Chen, Qiuwen Chen, Rui Chen, K C Chen, Zhixuan Chen, Gaoyu Chen, Yitong Chen, Tzu-Ju Chen, Jingqing Chen, Huiqun Chen, Runsen Chen, Michelle Chen, Hanyong Chen, Xiaolin Chen, Ke Chen, Yangchao Chen, Y D I Chen, Jinghua Chen, Jia Wei Chen, Man-Hua Chen, H T Chen, Zheyi Chen, Lihong Chen, Guangyao Chen, Rujun Chen, Ming-Fong Chen, Haiyun Chen, Dexiong Chen, Huiqin Chen, Ching Kit Chen, En-Qiang Chen, Wanjia Chen, Xiangliu Chen, Meiting Chen, Szu-Chi Chen, Yii-der Ida Chen, Jian-Hua Chen, Yanjie Chen, Yingying Chen, Paul Chih-Hsueh Chen, Si-Ru Chen, Mingxing Chen, Rui-Zhen Chen, Changjie Chen, Qu Chen, Yintong Chen, Jingde Chen, Mao Chen, Xinghai Chen, Mei-Chih Chen, Xueqing Chen, Chun-An Chen, Cheng Chen, Ruijing Chen, Huayu Chen, Yunqin Chen, Yan-Gui Chen, Ruibing Chen, Size Chen, Qi-An Chen, Yuan-Zhen Chen, J Chen, Heye Chen, T Chen, Junpeng Chen, Tan-Huan Chen, Shuaijun Chen, Hao Yu Chen, Fahui Chen, Lan Chen, Dong-Yi Chen, Xianqiang Chen, Shi-Sheng Chen, Qiao-Yi Chen, Pei-Chen Chen, Xueying Chen, Yi-Wen Chen, Guohong Chen, Zhiwei Chen, Zuolong Chen, Erfei Chen, Yuqing Chen, Zhenyue Chen, Qiongyun Chen, Jianghua Chen, Yingji Chen, Xiuli Chen, Xiaowei Chen, Hengyu Chen, Sheng-Xi Chen, Haiyi Chen, Shao-Peng Chen, Yi-Ru Chen, Zhaoran Chen, Xiuyan Chen, Jinsong Chen, Sunny Chen, Xiaolan Chen, S-D Chen, Ruofan Chen, Qiujing Chen, Yun Chen, Wei-Cheng Chen, Chun-Wei Chen, Liechun Chen, Lulu Chen, Hsiu-Wen Chen, Yanping Chen, Jiayao Chen, Xuejiao Chen, Guan-Wei Chen, Yusi Chen, Yijiang Chen, Chi-Hua Chen, Qixian Chen, Ziqing Chen, Peiyou Chen, Chunhai Chen, Zheren Chen, Qiuyun Chen, Xiaorong Chen, Chaoqun Chen, Dan-Dan Chen, Xuechun Chen, Yafang Chen, Mystie X Chen, Jina Chen, Wei-Kai Chen, Yule Chen, Bo Chen, Kaili Chen, Junqin Chen, Jia Min Chen, Chen Chen, Guoliang Chen, Xiaonan Chen, Guangjie Chen, Xiao Chen, Jeanne Chen, Danyang Chen, Minjiang Chen, Jiyuan Chen, Zheng-Zhen Chen, Shou-Tung Chen, Ouyang Chen, Xiu Chen, H Q Chen, Peiyu Chen, Yuh-Min Chen, Youmeng Chen, Shuoni Chen, Peiqin Chen, Xinji Chen, Chih-Ta Chen, Shang-Hung Chen, Robert Chen, Suet N Chen, Yun-Tzu Chen, Suming Chen, Ye Chen, Yao Chen, Yi-Fei Chen, Ruixue Chen, Tianhang Chen, Suning Chen, Jingnan Chen, Xiaohong Chen, Kun-Chieh Chen, Tuantuan Chen, Mei Chen, He-Ping Chen, Zhi Bin Chen, Yuewu Chen, Mengying Chen, Po-See Chen, Xue Chen, Jian-Jun Chen, Xiyao Chen, Jeremy J W Chen, Jiemei Chen, Daiwen Chen, Christina Yingxian Chen, Qinian Chen, Chih-Wei Chen, Wensheng Chen, Yingcong Chen, Zhishi Chen, Duo Chen, Jiansu Chen, Keping Chen, Min Chen, Yi-Hui Chen, Yun-Ju Chen, Gaoyang Chen, Renjin Chen, Kui Chen, Shuai-Ming Chen, Hui-Fen Chen, Zi-Yun Chen, Shao-Yu Chen, Meiyang Chen, Jiahua Chen, Zongyou Chen, Yen-Rong Chen, Huaping Chen, Yu-Xin Chen, Bohe Chen, Kehua Chen, Zilin Chen, Zhang-Liang Chen, Ziqi Chen, Yinglian Chen, Hui-Wen Chen, Peipei Chen, Baolin Chen, Zugen Chen, Kangzhen Chen, Yanhan Chen, Sung-Fang Chen, Zheping Chen, Zixuan Chen, Jiajia Chen, Yuanjian Chen, Lili Chen, Xiangli Chen, Ban Chen, Yuewen Chen, X Chen, Yan-Qiong Chen, Chider Chen, Yung-Hsiang Chen, Hanlin Chen, Xiangjun Chen, Haibing Chen, Le Chen, Xuan Chen, Xue-Ying Chen, Zexiao Chen, Chen-Yu Chen, Zhe-Ling Chen, Fan Chen, Hsin-Yi Chen, Feilong Chen, Zilong Chen, Yi-Jen Chen, Zhiyun Chen, Ning Chen, Wenxu Chen, Chuanbing Chen, Yaxi Chen, Yi-Hong Chen, Eleanor Y Chen, Yuexin Chen, Kexin Chen, Shoujun Chen, Yen-Ju Chen, Yu-Chuan Chen, Yen-Teen Chen, Bao-Ying Chen, Xiaopeng Chen, Danli Chen, Katharine Y Chen, Jingli Chen, Qianyi Chen, Zihua Chen, Ya-xi Chen, Xuanxu Chen, Chung-Hung Chen, Yajie Chen, Cindi Chen, Hua Chen, Shuliang Chen, Elizabeth H Chen, Gen-Der Chen, Bingyu Chen, Keyang Chen, Siyu S Chen, Xinpu Chen, Yau-Hung Chen, Hsueh-Fen Chen, Han-Hsiang Chen, Wei Ning Chen, Guopu Chen, Zhujun Chen, Yurong Chen, Yuxian Chen, Wanjun Chen, Qiu-Jing Chen, Qifang Chen, Yuhan Chen, Jingshen Chen, Zhongliang Chen, Ching-Hsuan Chen, Zhaoyao Chen, Yongning Chen, Marcus Y Chen, Ping Chen, Junfei Chen, Yung-Wu Chen, Xueting Chen, Yingchun Chen, Wan-Yan Chen, Yuxin Chen, Yisheng Chen, Chun-Yuan Chen, Yulian Chen, Yan-Jun Chen, Guoxun Chen, Ding Chen, Yu-Fen Chen, Jason A Chen, Shuyi Chen, Cuilan Chen, Ruijuan Chen, Kevin Chen, Xuanmao Chen, Shen-Ming Chen, Ya-Nan Chen, Sean Chen, Zhaowei Chen, Xixi Chen, Yu-Chia Chen, Xuemin Chen, Binlong Chen, Weina Chen, Xuemei Chen, Di Chen, P P Chen, Yubin Chen, Chunhua Chen, Li-Chieh Chen, Ping-Chung Chen, Zhihao Chen, Xinyang Chen, Chan Chen, Yan Jie Chen, Shi-Qing Chen, Ivy Xiaoying Chen, Ying-Cheng Chen, Jia-Shun Chen, Shao-Wei Chen, Aiping Chen, Dexiang Chen, Qianfen Chen, Hongyu Chen, Wei-Kung Chen, Danlei Chen, Hongen Chen, Shipeng Chen, Jake Y Chen, Dongsheng Chen, Chien-Ting Chen, Shouzhen Chen, Hehe Chen, Yu-Tung Chen, Yilin Chen, Joy J Chen, Zhong Chen, Zhenfeng Chen, Zhongzhu Chen, Feiyang Chen, Xingxing Chen, Keyan Chen, Huimin Chen, Guanyu Chen, D. Chen, Dianke Chen, Zhigeng Chen, Sien-Tsong Chen, Yii-Der Chen, Chi-Yun Chen, Beidong Chen, Wu-Xian Chen, Zhihang Chen, Yuanqi Chen, Jianhua Chen, Xian Chen, Xiangding Chen, Jingteng Chen, Shuaiyu Chen, Xue-Mei Chen, Yu-Han Chen, Hongqiao Chen, Weili Chen, Yunzhu Chen, Guo-qing Chen, Miao Chen, Zhi Chen, Junhui Chen, Jing-Xian Chen, Zhiquan Chen, Shuhuang Chen, Shaokang Chen, Irwin Chen, Xiang Chen, Chuo Chen, Siting Chen, Keyuan Chen, Xia-Fei Chen, Zhihai Chen, Yuanyu Chen, Po-Sheng Chen, Qingjiang Chen, Yi-Bing Chen, Rongrong Chen, Katherine C Chen, Shaoxing Chen, Lifen Chen, Luyi Chen, Sisi Chen, Ning-Bo Chen, Yihong Chen, Guanjie Chen, Li-Hua Chen, Xiao-Hui Chen, Ting Chen, Chun-Han Chen, Xuzhuo Chen, Junming Chen, Zheng Chen, Wen-Jie Chen, Bingdi Chen, Jiang Ye Chen, Yanbin Chen, Duoting Chen, Shunyou Chen, Shaohua Chen, Jien-Jiun Chen, Jiaohua Chen, Shaoze Chen, Yifang Chen, Chiqi Chen, Yen-Hao Chen, Rui-Fang Chen, Hung-Sheng Chen, Kuey Chu Chen, Y S Chen, Xijun Chen, Chaoyue Chen, Heng-Sheng Chen, Lianfeng Chen, Yuhong Chen, Yixin Chen, Yuanli Chen, Cancan Chen, Yanming Chen, Yajun Chen, Chaoping Chen, F-K Chen, Menglan Chen, Zi-Yang Chen, Yongfang Chen, Hsin-Hong Chen, Hongyan Chen, Chao-Wei Chen, Jijun Chen, Xiaochun Chen, Yazhuo Chen, Zhixin Chen, YongPing Chen, Jui-Yu Chen, Mian-Mian Chen, Liqiang Chen, Y P Chen, D-F Chen, Jinhao Chen, Yanyan Chen, Chang-Zheng Chen, Shao-long Chen, Guoshun Chen, Lo-Yun Chen, Yen-Lin Chen, Bingqian Chen, Dafang Chen, Yi-Chung Chen, Liming Chen, Qiuli Chen, Shuying Chen, Chih-Mei Chen, Renyu Chen, Wei-Hao Chen, Lihua Chen, Hang Chen, Hai-Ning Chen, Hu Chen, Yu-Fu Chen, Yalan Chen, Wan-Tzu Chen, Benjamin Jieming Chen, Yingting Chen, Jiacai Chen, Ning-Yuan Chen, Shuo-Bin Chen, Yu-Ling Chen, Jian-Kang Chen, Hengsan Chen, Yu-Ting Chen, Y Chen, Qingjie Chen, Jiong Chen, Chaoyi Chen, Yunlin Chen, Gang Chen, Hui-Chun Chen, Li-Tzong Chen, Zhangliang Chen, Qiangpu Chen, Xianbo Chen, Jinxuan Chen, Hebing Chen, Ran Chen, Zhehui Chen, Carol X-Q Chen, Yuping Chen, Xiangyu Chen, Xinyu Chen, Qianyun Chen, Junyi Chen, B-S Chen, Zhesheng Chen, Man Chen, Dali Chen, Danyu Chen, Huijiao Chen, Naisong Chen, Qitong Chen, Chueh-Tan Chen, Kai-Ming Chen, Jiarou Chen, Huang Chen, Chunjie Chen, Weiping Chen, Po-Min Chen, Guang-Chao Chen, Danxia Chen, Youran Chen, Chuanzhi Chen, Peng-Cheng Chen, Wen-Tsung Chen, Linxi Chen, Si-guo Chen, Zike Chen, Zhiyu Chen, Wanting Chen, Jiangxia Chen, Wenhua Chen, Roufen Chen, Shi-You Chen, Fang-Pei Chen, Chu Chen, Feifeng Chen, Chunlin Chen, Yunwei Chen, Wenbing Chen, Xuejun Chen, Meizhen Chen, Li Jia Chen, Tianhua Chen, Xiangmei Chen, Kewei Chen, Yuh-Ling Chen, Dejuan Chen, Jiyan Chen, Xinzhuo Chen, Yue-Lai Chen, Hsiao-Jou Cortina Chen, Weiqin Chen, Huey-Miin Chen, Elizabeth Suchi Chen, Kai-Ting Chen, Lizhen Chen, Xiaowen Chen, Chien-Yu Chen, Lingjun Chen, Gonglie Chen, Jiao Chen, Zhuo-Yuan Chen, Wei-Peng Chen, Xiangna Chen, Jiade Chen, Lanmei Chen, Siyu Chen, Kunpeng Chen, Hung-Chi Chen, Jia Chen, Shuwen Chen, Siqin Chen, Zhenlei Chen, Wen-Yi Chen, Si-Yuan Chen, Yidan Chen, Tianfeng Chen, Fu Chen, Leqi Chen, Jiamiao Chen, Shasha Chen, Qingyi Chen, Ben-Kuen Chen, Haitao Chen, Qi Chen, Yihao Chen, Yunfeng Chen, Elizabeth S Chen, Yiming Chen, Youwei Chen, Lichun Chen, Yanfei Chen, Hongxing Chen, Muh-Shy Chen, Yingyu Chen, Weihong Chen, Ming Chen, Kelin Chen, Duan-Yu Chen, Shi-Yi Chen, Shih-Yu Chen, Yanling Chen, Shuanghui Chen, Ya Chen, Yusheng Chen, Yuting Chen, Shiming Chen, Xinqiao Chen, Hongbo Chen, Mien-Cheng Chen, Jiacheng Chen, Herbert Chen, Ji-ling Chen, Sun Chen, Chen-Sheng Chen, Na Chen, Chih-Yi Chen, Wenfang Chen, Yii-Der I Chen, Qinghua Chen, Shuai Chen, Hsi-Hsien Chen, F Chen, Guo-Chong Chen, Zhe Chen, Beijian Chen, Roger Chen, You-Ming Chen, Hongzhi Chen, Zhen-Yu Chen, Xianxiong Chen, Chang Chen, Chujie Chen, Chuannan Chen, Kan Chen, Lu-Biao Chen, Yupei Chen, Qiu-Sheng Chen, Shangduo Chen, Yuan-Yuan Chen, Yundai Chen, Binzhen Chen, Cai-Long Chen, Yen-Chen Chen, Xue-Xin Chen, Yanru Chen, Chunxiu Chen, Yifa Chen, Xingdong Chen, Ruey-Hwa Chen, Shangzhong Chen, Ching-Wen Chen, Danna Chen, Jingjing Chen, Yafei Chen, Dandan Chen, Pei-Yi Chen, Shan Chen, Guanghao Chen, Longqing Chen, Yen-Cheng Chen, Zhanjuan Chen, Jinguo Chen, Zhongxiu Chen, Rui-Min Chen, Shunde Chen, Xun Chen, Jianmin Chen, Linyi Chen, Ying-Ying Chen, Chien-Hsiun Chen, Li-Nan Chen, Yu-Ming Chen, Qianqian Chen, Xue-Yan Chen, Shengdi Chen, Huali Chen, Xinyue Chen, Ching-Yi Chen, Honghai Chen, Baosheng Chen, Pingguo Chen, Yike Chen, Yuxiang Chen, Qing-Hui Chen, Yuanwen Chen, Yongming Chen, Zongzheng Chen, Ruiying Chen, Huafei Chen, Tingen Chen, Zhouliang Chen, Shih-Yin Chen, Shanyuan Chen, Yiyin Chen, Feiyu Chen, Zitao Chen, Constance Chen, Zhoulong Chen, Haide Chen, Jiang Chen, Ray-Jade Chen, Shiuhwei Chen, Chih-Chieh Chen, Chaochao Chen, Lijuan Chen, Qianling Chen, Jian-Min Chen, Xihui Chen, Yuli Chen, Wu-Jun Chen, Diyun Chen, Alice P Chen, Jingxuan Chen, Chiung-Mei Chen, Shibo Chen, M L Chen, Lena W Chen, Xiujuan Chen, Christopher S Chen, Yeh Chen, Xingyong Chen, Feixue Chen, Boyu Chen, Weixian Chen, Tingting Chen, Bosong Chen, Junjie Chen, Han-Min Chen, Szu-Yun Chen, Qingliang Chen, Huatao Chen, Bin Chen, L B Chen, Xuanyi Chen, Chun Chen, Dong Chen, Yinjuan Chen, Jiejian Chen, Lu-Zhu Chen, Alex F Chen, Pei-Chun Chen, Chien-Jen Chen, Y M Chen, Xiao-Chen Chen, Tania Chen, Yang Chen, Yangxin Chen, Mark I-Cheng Chen, Haiming Chen, Shuo Chen, Yong Chen, Hsiao-Tan Chen, Erzhen Chen, Jiaye Chen, Fangyan Chen, Guanzheng Chen, Haoyun Chen, Jiongyu Chen, Baofeng Chen, Yuqin Chen, Juan Chen, Haobo Chen, Shuhong Chen, Fu-Shou Chen, Wei-Yu Chen, Haw-Wen Chen, Feifan Chen, Deqian Chen, Linlin Chen, Xiaoshan Chen, Hui Chen, Wenwen Chen, Yanli Chen, Yuexuan Chen, Xiaoyin Chen, Yen-Chang Chen, Tiantian Chen, Ruiai Chen, Alice Y Chen, Jinglin Chen, Zifan Chen, Wantao Chen, Shanshan Chen, Jianjun Chen, Xiaoyuan Chen, Xuefei Chen, Runfeng Chen, Weisan Chen, Guangnan Chen, Junpan Chen, An Chen, Lankai Chen, Yiding Chen, Tianpeng Chen, Ya-Ting Chen, Lijin Chen, Ching-Yu Chen, Y Eugene Chen, Guanglong Chen, Rongyuan Chen, Yali Chen, Yanan Chen, Liyun Chen, Shuai-Bing Chen, Zhixue Chen, Xiaolu Chen, Xiao-he Chen, Hongxiang Chen, Bing-Feng Chen, Gary K Chen, Xiaohui Chen, Jin-Wu Chen, Qiuxiang Chen, Huaqiu Chen, X Steven Chen, Xiaoqian Chen, Chao-Jung Chen, Zhengjun Chen, Yong-Ping Chen, Zhelin Chen, Xuancai Chen, Yi-Hsuan Chen, Daiyu Chen, Gui Mei Chen, Hongqi Chen, Zhizhong Chen, Mengting Chen, Guofang Chen, Jian-Guo Chen, Hou-Zao Chen, Yuyao Chen, Lixia Chen, Yu-Yang Chen, Zhengling Chen, Qinfen Chen, Jiajun Chen, Xue-Qing Chen, Shenghui Chen, Yii-Derr Chen, Linbo Chen, Yanjing Chen, S Pl Chen, Chi-Long Chen, Jiawei Chen, Rong-Hua Chen, Shu-Fen Chen, Yu-San Chen, Ying-Lan Chen, Xiaofen Chen, Weican Chen, Xin Chen, Yumei Chen, Ruohong Chen, You-Xin Chen, Tse-Ching Chen, Xiancheng Chen, Yu-Pei Chen, Weihao Chen, Baojiu Chen, Haimin Chen, Zhihong Chen, Jion Chen, Yi-Chun Chen, Ping-Kun Chen, Wan Jun Chen, Willian Tzu-Liang Chen, Qingshi Chen, Ren-Hui Chen, Weihua Chen, Hanjing Chen, Guihao Chen, Xiao-Qing Chen, Po-Yu Chen, Liangsheng Chen, Fred K Chen, Haiying Chen, Tzu-Chieh Chen, Wei J Chen, Zhen Chen, Shu Chen, Jie Chen, Chung-Hao Chen, Zi-Qing Chen, Yu-Xia Chen, Weijia Chen, Ming-Han Chen, Yaodong Chen, Yong-Zhong Chen, Jinquan Chen, Haijiao Chen, Tom Wei-Wu Chen, Jingzhou Chen, Ya-Peng Chen, Shiwei Chen, Xiqun Chen, Yingjie Chen, Wenjun Chen, Linjie Chen, Hung-Chun Chen, Xiaoping Chen, Haoran Chen, Qiang Chen, Sy-Jou Chen, Y U Chen, Weineng Chen, Li-hong Chen, Cheng-Fong Chen, Yajing Chen, Song Chen, Qiaoli Chen, Yiru Chen, Guang-Yu Chen, Zhi-bin Chen, Deyu Chen, C Y Chen, Junhong Chen, Yonghui Chen, Chaoli Chen, Syue-Ting Chen, Sufang Chen, I-Chun Chen, Shangsi Chen, Xiao-Wei Chen, Qinsheng Chen, Zhao-Xia Chen, Yun-Yu Chen, Chi-Chien Chen, Wenxing Chen, Meng Chen, Zixin Chen, Jianhui Chen, Yuanyuan Chen, Jiamin Chen, Wei-Wei Chen, Xingyi Chen, Yen-Ni Chen, Danxiang Chen, Po-Ju Chen, Mei-Ru Chen, Ziying Chen, E S Chen, Tailai Chen, Qingyang Chen, Miaomiao Chen, Shuntai Chen, Wei-Lun Chen, Xuanli Chen, Zhengwei Chen, Fengju Chen, Chengwei Chen, Xujia Chen, Faye H Chen, Xiaoxiao Chen, Shengpan Chen, Shin-Yu Chen, Shiyao Chen, Yuan-Shen Chen, Shengzhi Chen, Shaohong Chen, Ching-Jung Chen, Zihao Chen, Kaiquan Chen, Duo-Xue Chen, Xiaochang Chen, Siping Chen, Rongfeng Chen, Jiali Chen, Hsin-Han Chen, Xiaohua Chen, Delong Chen, Wenjie Chen, Huijia Chen, Yunn-Yi Chen, Siyi Chen, Zhengming Chen, Chu-Huang Chen, Zhuchu Chen, Yuanbin Chen, Jinyong Chen, Yunzhong Chen, Pan Chen, Bihong T Chen, Yunyun Chen, Shujuan Chen, M Chen, Mulan Chen, Jiaren Chen, Zechuan Chen, Jian-Qing Chen, Wei-Hui Chen, Lifeng Chen, Geng Chen, Yan-Ming Chen, Zhijian J Chen, Honghui Chen, Wenfan Chen, Zhongbo Chen, Rouxi Chen, Ye-Guang Chen, Zhimin Chen, Tzu-Ting Chen, Xiaolei Chen, Ziyuan Chen, Shilan Chen, Ruiqi Chen, Xiameng Chen, Huijie Chen, Jiankui Chen, Yuhang Chen, Jianzhong Chen, Wen-Qi Chen, Fa Chen, Shu-Jen Chen, Li-Mien Chen, Xing-Lin Chen, Xuxiang Chen, Erbao Chen, Jiaqing Chen, Hsiang-Wen Chen, Jiaxin Chen
articles
Paul R Marshall, Joshua Davies, Qiongyi Zhao +18 more · 2024 · The Journal of neuroscience : the official journal of the Society for Neuroscience · Society for Neuroscience · added 2026-04-24
The conformational state of DNA fine-tunes the transcriptional rate and abundance of RNA. Here, we report that G-quadruplex DNA (G4-DNA) accumulates in neurons, in an experience-dependent manner, and Show more
The conformational state of DNA fine-tunes the transcriptional rate and abundance of RNA. Here, we report that G-quadruplex DNA (G4-DNA) accumulates in neurons, in an experience-dependent manner, and that this is required for the transient silencing and activation of genes that are critically involved in learning and memory in male C57/BL6 mice. In addition, site-specific resolution of G4-DNA by dCas9-mediated deposition of the helicase DHX36 impairs fear extinction memory. Dynamic DNA structure states therefore represent a key molecular mechanism underlying memory consolidation. Show less
no PDF DOI: 10.1523/JNEUROSCI.0093-23.2024
DHX36
Zekun Xin, Lijun Dong, Guojun Chen +1 more · 2024 · Asian journal of surgery · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.asjsur.2024.11.010
FADS3
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
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
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
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
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
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
Christopher J Schwartz, Nikka Khorsandi, Amie Blanco +3 more · 2024 · Breast cancer research and treatment · Springer · added 2026-04-24
Germline pathogenic variants in checkpoint kinase 2 (CHEK2) are associated with a moderately increased risk of breast cancer (BC). The spectrum of clinicopathologic features and genetics of these tumo Show more
Germline pathogenic variants in checkpoint kinase 2 (CHEK2) are associated with a moderately increased risk of breast cancer (BC). The spectrum of clinicopathologic features and genetics of these tumors has not been fully established. We characterized the histopathologic and clinicopathologic features of 44 CHEK2-associated BCs from 35 women, and assessed responses to neoadjuvant chemotherapy. A subset of cases (n = 23) was additionally analyzed using targeted next-generation DNA sequencing (NGS). Most (94%, 33/35) patients were heterozygous carriers for germline CHEK2 variants, and 40% had the c.1100delC allele. Two patients were homozygous, and five had additional germline pathogenic variants in ATM (2), PALB2 (1), RAD50 (1), or MUTYH (1). CHEK2-associated BCs occurred in younger women (median age 45 years, range 25-75) and were often multifocal (20%) or bilateral (11%). Most (86%, 38/44) were invasive ductal carcinomas of no special type (IDC-NST). Almost all (95%, 41/43) BCs were ER + (79% ER + HER2-, 16% ER + HER2 + , 5% ER-HER2 +), and most (69%) were luminal B. Nottingham grade, proliferation index, and results of multiparametric molecular testing were heterogeneous. Biallelic CHEK2 alteration with loss of heterozygosity was identified in most BCs (57%, 13/23) by NGS. Additional recurrent alterations included GATA3 (26%), PIK3CA (226%), CCND1 (22%), FGFR1 (22%), ERBB2 (17%), ZNF703 (17%), TP53 (9%), and PPM1D (9%), among others. Responses to neoadjuvant chemotherapy were variable, but few patients (21%, 3/14) achieved pathologic complete response. Most patients (85%) were without evidence of disease at time of study (n = 34). Five patients (15%) developed distant metastasis, and one (3%) died (mean follow-up 50 months). Almost all CHEK2-associated BCs were ER + IDC-NST, with most classified as luminal B with or without HER2 overexpression. NGS supported the luminal-like phenotype and confirmed CHEK2 as an oncogenic driver in the majority of cases. Responses to neoadjuvant chemotherapy were variable but mostly incomplete. Show less
📄 PDF DOI: 10.1007/s10549-023-07176-8
FGFR1
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
Ting Yang, Yan-Li Liu, Hai-Long Guo +8 more · 2024 · International immunopharmacology · Elsevier · added 2026-04-24
Colorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD Show more
Colorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD), which plays a pivotal role in tumor progression. This study aimed to investigate the role of the anoikis related genes (ARGs) in colon cancer. Consensus unsupervised clustering, differential expression analysis, tumor mutational burden analysis, and analysis of immune cell infiltration were utilized in the study. For the analysis of RNA sequences and clinical data of COAD patients, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were obtained. A prognostic scoring system for overall survival (OS) prediction was developed using Cox regression and LASSO regression analysis. Furthermore, loss-of-function assay was utilized to explore the role of RAD9A played in the progression of colon cancer. The prognostic value of a risk score composed of NTRK2, EPHA2, RAD9A, CDC25C, and SNAI1 genes was significant. Furthermore, these findings suggested potential mechanisms that may influence prognosis, supporting the development of individualized treatment plans and management of patient outcomes. Further experiments confirmed that RAD9A could promote proliferation and metastasis of colon cancer cells. These effects may be achieved by affecting the phosphorylation of AKT. Differences in survival time and the tumor immune microenvironment (TIME) were observed between two gene clusters associated with ARGs. In addition, a prognostic risk model was established and confirmed as an independent risk factor. Furthermore, our data indicated that RAD9A promoted tumorigenicityby activating AKT in colon cancer. Show less
no PDF DOI: 10.1016/j.intimp.2024.112874
SNAI1
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
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
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
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
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
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
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
Manabu Niimi, Yajie Chen, Huanyu Zhao +8 more · 2024 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Apolipoprotein E (apoE) acts as a binding molecule for both the low-density lipoprotein receptor and the lipoprotein receptor-related protein and this function is essential for facilitating the hepato Show more
Apolipoprotein E (apoE) acts as a binding molecule for both the low-density lipoprotein receptor and the lipoprotein receptor-related protein and this function is essential for facilitating the hepatocyte uptake of lipoproteins containing apoB. The absence of apoE leads to increased atherogenicity in both humans and mice, although the precise molecular mechanisms remain incompletely understood. This study aimed to investigate the susceptibility of apoE knockout (KO) rabbits, in comparison with wild-type (WT) rabbits, to diet-induced hyperlipidemia and atherosclerosis. ApoE KO rabbits and WT rabbits were fed a diet containing 0.3% cholesterol for 16 weeks. Plasma lipid levels, lipoproteins, and apolipoproteins were analyzed. Atherosclerosis was evaluated at the endpoint of experiments. In addition, we evaluated the oxidizability of those lipoproteins containing apoB to investigate the possible mechanisms of atherosclerosis. Male apoE KO rabbits showed significantly elevated levels of total cholesterol and triglycerides compared to WT rabbits, while female apoE KO rabbits displayed similar high total cholesterol levels, albeit with significantly higher triglycerides levels than WT controls. Notably, both male (2.1-fold increase) and female (1.6-fold increase) apoE KO rabbits exhibited a significantly augmented aortic lesion area compared to WT controls. Pathological examination showed that the increased intimal lesions in apoE KO rabbits were featured by heightened infiltration of macrophages (2.7-fold increase) and smooth muscle cells (2.5-fold increase). Furthermore, coronary atherosclerotic lesions were also increased by 1.3-fold in apoE KO rabbits. Lipoprotein analysis revealed that apoB48-rich beta-very-low-density lipoproteins were notably abundant in apoE KO rabbits, suggesting that these remnant lipoproteins of intestinal origin serve as the primary atherogenic lipoproteins. Moreover, apoB48-rich remnant lipoproteins isolated from apoE KO rabbits exhibited heightened susceptibility to copper-induced oxidation. The findings indicate that apoB48-rich remnant lipoproteins, resulting from apoE deficiency, possess greater atherogenic potential than apoB100-rich remnant lipoproteins, regardless of plasma TC levels. Show less
📄 PDF DOI: 10.3389/fcvm.2024.1424064
APOB
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