👤 Wenwen 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, Yen-Ching 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, 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
Jingjing Guo, Haifan Qiu, Jianping Wang +3 more · 2025 · Frontiers in medicine · Frontiers · added 2026-04-24
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregn Show more
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregnancy women and 317 healthy non-pregnant women. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), lipoprotein (a) [Lp(a)], and hypersensitive C-reactive protein (hs-CRP) were measured in both groups. The mean and standard deviation of each index were calculated to establish the reference range of normal serum lipid levels in pregnant women in mid-to-late pregnancy. The associations between serum lipid levels and perinatal outcomes were assessed statistically. There were no significant differences in age, pregnancy, or parity between the adverse outcome and normal delivery groups, but the caesarean section rate was significantly higher in the adverse outcome group. The levels of hs-CRP, TG, TC, HDL-C, LDL-C, and ApoA1 were significantly higher in the adverse outcome group. Elevated hs-CRP, TG, and HDL-C levels were risk factors for adverse pregnancy outcomes. According to the receiver operating characteristic curve, the optimal threshold of the combined diagnosis of these three indicators to predict adverse pregnancy outcomes was 0.534, and the area under the curve was 0.822. The establishment of lipid reference intervals in the second and third trimesters of pregnancy can effectively evaluate lipid metabolism in pregnant women, and the measurement of lipid metabolism in pregnant women is helpful in predicting adverse pregnancy outcomes. Show less
📄 PDF DOI: 10.3389/fmed.2025.1530525
APOB
Jia-Ling Yang, Long-Huw Lee, Hsing-Chieh Wu +3 more · 2025 · Developmental and comparative immunology · Elsevier · added 2026-04-24
The seven-transmembrane (7TM) receptors are the largest superfamily of cell-surface receptors and are involved in various physiological processes of vertebrate species. In our previous study, a new ch Show more
The seven-transmembrane (7TM) receptors are the largest superfamily of cell-surface receptors and are involved in various physiological processes of vertebrate species. In our previous study, a new chicken 7TM receptor (Ch-7TM) was discovered in mononuclear phagocytes (MNPs) derived from chicken peripheral blood mononuclear cells (PBMCs). To explore the functions of Ch-7TM, RNA interference (RNAi) was used to silence the Ch-7TM messenger RNA (mRNA) of MNPs, using small interfering RNA (siRNA) designed with BLOCK-iT™ RNAi Designer. Herein we demonstrated that silencing of the Ch-7TM mRNA induced apoptosis of MNPs, suggesting that Ch-7TM contributed to the survival of MNPs. Moreover, chicken sera could inhibit the Ch-7TM-silencing-induced apoptosis in MNPs. The survival factor presented in fraction 16 (F16) of chicken sera was highly protective against the Ch-7TM-silencing-induced apoptosis in MNPs. The proteins from F16 were identified as vitamin D-binding protein (DBP) and apolipoprotein A-IV (ApoA-IV), which might be potential candidates for survival factors. The protective effect of vitamin D and ApoA-IV indicated that Ch-7TM might involve the intracellular oxidation-reduction balance, although more evidence is needed to confirm this function. The siRNA screening serves as an excellent model for studying the functions of chicken MNPs receptors. Show less
no PDF DOI: 10.1016/j.dci.2025.105423
APOA4
Zhengliang Li, Xiaokai Chen, Linlin Ren +4 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clin Show more
Cardiovascular disease (CVD) is the leading cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD), yet traditional risk predictors remain limited in clinical practice. To develop machine learning (ML) models for classifying prevalent atherosclerotic cardiovascular disease (ASCVD) risk in MASLD patients, and to enhance model interpretability using SHapley Additive exPlanations (SHAP). Methods: This retrospective study included 590 MASLD patients diagnosed at the Affiliated Hospital of Qingdao University between December 2019 and December 2024. Patients were randomly divided into a training set (n=413) and a validation set (n=177), and further stratified based on ASCVD status. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection. Six ML models were developed and evaluated using sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and F1 score. SHAP analysis was performed to interpret feature contributions. ASCVD was present in 434 of 590 patients (73.6%). The Gradient Boosting (GB) model achieved the best performance, with AUCs of 0.918 (95% CI: 0.890-0.944) in the training set and 0.817 (95% CI: 0.739-0.883) in the validation set. SHAP analysis identified the top predictors as the Cholesterol-HDL-Glucose (CHG) index, Castelli Risk Index II (CRI-II), lipoprotein(a) [Lp(a)], serum creatinine (Scr), and uric acid (UA). The GB model demonstrated strong high accuracy in identifying existing ASCVD in MASLD patients and may serve as a useful tool for early risk stratification in clinical settings. Show less
📄 PDF DOI: 10.3389/fendo.2025.1684558
LPA
Jun Wang, Kefen Zhang, Xiuming Tang +2 more · 2025 · Journal of cancer research and therapeutics · added 2026-04-24
Currently, understanding of the nonlinear relationship between age and hepatocellular carcinoma (HCC) prognosis is insufficient. Thus, this study aimed to analyze the relationship between age at HCC d Show more
Currently, understanding of the nonlinear relationship between age and hepatocellular carcinoma (HCC) prognosis is insufficient. Thus, this study aimed to analyze the relationship between age at HCC diagnosis and overall survival (OS) and identify possible influencing mechanisms. Clinical data from the TCGA public database were analyzed. Restricted cubic spline and segmented logistic regression were employed to explore the nonlinear relationship between age at diagnosis and mortality risk following hepatectomy. Furthermore, bioinformatics methods were employed to understand the possible mechanisms of this nonlinear relationship at the genetic level. The results indicated a nonlinear relationship between age at diagnosis and OS, with the age of 60 years identified as a critical point. Segmented regression showed that age ≥60 years is an unfavorable prognostic factor. The "DNA mismatch repair" pathway was considerably enriched in patients aged <60 years. However, the gene mutation rate of "APOB," "MUC16," "ALB," and "PCLO" and the median tumor mutation burden were relatively more evident in patients aged ≥60 years. MGEA12 was more highly expressed in tumor tissues than in normal ones, particularly in patients aged ≥60 years. The survival rate of the high-expression group was lower than that of the low-expression group. At the mRNA level, the MGEA12 expression in Huh-7 and SUN449 was higher than that in the HSC-LX2 cell line. A nonlinear relationship was found between age at HCC diagnosis and OS, with the age of 60 years being the critical point. MGEA12 may affect the prognosis of elderly people. Show less
no PDF DOI: 10.4103/jcrt.jcrt_1690_24
APOB
Shenlong Mo, Zhenying Hu, Huaiyi Zhu +5 more · 2025 · Toxins · MDPI · added 2026-04-24
2-Amino-14,16-dimethyloctadecan-3-ol (AOD) is commonly found in foods contaminated with
📄 PDF DOI: 10.3390/toxins17080413
FADS3
Alexa Canchola, Keyuan Li, Kunpeng Chen +12 more · 2025 · ACS nano · ACS Publications · added 2026-04-24
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokine Show more
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokinetics, biodistribution, and cellular interactions. Yet systematic analyses are hampered by the absence of standardized, richly annotated data sets. Here, we introduce the Protein Corona Database (PC-DB), which compiles data from 83 studies (2000-2024) and integrates 817 NP formulations with quantitative profiles of 2497 adsorbed proteins. The PC-DB exposes pronounced heterogeneity in NP materials (metal 28.8%, silica 22.8%, lipid-based 14.8%), surface modifications, sizes (1-1400 nm), and ζ-potentials (-70 to +70 mV). Subsequent meta-analysis shows that silica, polystyrene, and lipid-based NPs smaller than 100 nm with moderately negative to neutral ζ-potentials preferentially bind the lipoproteins APOE and APOB-100, which are linked to receptor-mediated uptake and enhanced delivery efficiency. In contrast, metal and metal-oxide NPs carrying highly negative surface charge enrich complement component C3, indicating a greater likelihood of immune recognition and clearance. Interpretable machine learning models (LightGBM and XGBoost; ROC-AUC > 0.85) confirm NP size, ζ-potential, and incubation time as the most influential predictors of protein adsorption. These results delineate how physicochemical parameters dictate PC composition and illustrate the power of predictive modeling to guide rational NP design. Show less
📄 PDF DOI: 10.1021/acsnano.5c08608
APOB
Bing-Huei Chen, Chen-Te Jen, Chia-Chuan Wang +1 more · 2025 · Pharmaceutics · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/pharmaceutics17091200
BACE1
Baolong Wang, Peiyou Chen, Zhihao Jia +1 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
The purpose of this study is to explore the effect of physical activity on the executive function of 5-6-year-old children and to provide a theoretical and empirical basis for further research on impr Show more
The purpose of this study is to explore the effect of physical activity on the executive function of 5-6-year-old children and to provide a theoretical and empirical basis for further research on improvements in the executive function of children caused by physical activity. A total of 170 children (5-6 years old) from several kindergartens were selected via multistage stratified sampling. All the children wore 7-day accelerometers (ActiGraph GT3X) to measure their daily physical activities. Parents completed the preschool children's executive function questionnaire (BRIEF-P) to assess their daily executive function. (1) The total duration of physical activity (TPA) was 110.84 ± 22.52 min/day, the duration of low-intensity physical activity (LPA) was 36.23 ± 7.53 min/day, and the duration of medium- and high-intensity physical activity (MVPA) was 74.55 ± 16.77 min/day. A total of 82.6% of the children reached the recommended amount of MVPA. (2) After adjusting for body mass index (BMI), parents' highest educational background and parents' total monthly income, MVPA was negatively correlated with children's total executive function score ( Physical activity can improve the executive function of children aged 5-6 years to some extent. MVPA can improve children's executive function and subdomains, and there is a correlation between boys' physical activity and executive function. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1651806
LPA
Shuai Tian, Jing Han, Zhaomin Zhang +3 more · 2025 · European journal of applied physiology · Springer · added 2026-04-24
High-intensity exercise promotes visceral adipose tissue (VAT) breakdown in females via the hypothalamic ERα pathway, and exogenous lactate infusion combined with aerobic training (AT) mimics this eff Show more
High-intensity exercise promotes visceral adipose tissue (VAT) breakdown in females via the hypothalamic ERα pathway, and exogenous lactate infusion combined with aerobic training (AT) mimics this effect. However, whether lactate administration can independently mediate hypothalamic plasticity and VAT catabolism as a standalone nutritional strategy remains unexplored. Firstly, using a two-factor design (Lactate × AT) in female SD rats, we showed that long-term exogenous lactate infusion independently induced co-expression of Estrogen receptor α (ERα) and Brain-derived neurotrophic factor (BDNF) in the ventromedial hypothalamus (VMH) and elevated local field potential spectral power in specific bands. These neural adaptations were accompanied by increased resting metabolic rate, enhanced fat oxidation, and enhanced lipolysis, thereby preventing excessive VAT accumulation induced by a high-fat diet. Furthermore, pharmacological inhibition confirmed that Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-α (PGC-1α) acts as a co-upstream signal of ERα and BDNF mediating this process. Our findings reveal that standalone lactate administration induces functional plasticity and metabolic reprogramming through the VMH PGC-1α-ERα pathway, independent of exercise, and effectively suppresses pathological VAT accumulation in female rats. This study identifies potential nutritional interventions and mechanistic targets for preventing female-centered obesity. Show less
📄 PDF DOI: 10.1007/s00421-025-06097-2
BDNF
Jia Zhang, Song Bin Huang, Dan Ni Peng +3 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study aimed to identify heterogeneous patterns of medical coping modes (MCM) and to examine the moderating role of social support in the relationship between these patterns and social disability Show more
This study aimed to identify heterogeneous patterns of medical coping modes (MCM) and to examine the moderating role of social support in the relationship between these patterns and social disability in young and middle-aged patients after percutaneous coronary intervention (PCI). A cross-sectional study was conducted among 129 post-PCI patients from a single center in China. Participants completed the Medical Coping Modes Questionnaire (MCMQ), the Social Support Rating Scale (SSRS), and the Social Disability Screening Schedule (SDSS). Latent profile analysis (LPA) was used to identify distinct coping patterns. The moderation effect of social support was tested using the Johnson-Neyman technique. Two distinct coping profiles were identified via LPA: "Adaptive Copers" (55.1%), characterized by higher confrontation and lower avoidance/resignation, and "Maladaptive Copers" (44.9%), showing the opposite pattern. A counterintuitive finding emerged, with the Maladaptive Copers reporting significantly lower social disability scores. Furthermore, beyond this profile differentiation, social support demonstrated a significant U-shaped moderating effect in the coping-disability relationship. Its moderating role was statistically significant only at very low (<39.884) and very high (>52.924) levels of support. This study reveals two key findings: first, post-PCI patients are heterogeneous in coping, comprising adaptive and maladaptive subgroups; second, the impact of these coping styles on social disability is non-linearly moderated by social support. Clinicians should assess both coping profiles and social support levels to tailor interventions effectively. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1731898
LPA
Yulong Fu, Canran Gao, Hailing Zhang +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection te Show more
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection techniques. Herein, a unique hydrogel incorporating extracellular matrix from fish swim bladder (FSB-ECM), which has distinct advantages over mammalian derived ECM, such as low antigenicity, bioactivity, and source safety, is developed. It consists of collagen, glycoproteins, and proteoglycans, including 13 proteins common in the myocardial matrix and three specific proteins: HSPG, Col12a1, and vWF. This hydrogel enhances cardiac cell adhesion and stretching while promoting angiogenesis and M2 macrophage polarization. In addition, its storage modulus (G') increases over time, reaching about 1000 Pa after 5 min, which facilitates transcatheter delivery and in situ gelling. Furthermore, this hydrogel provides sustained support for cardiac contractions, exhibiting superior longevity. In a rat model of ischemic heart failure, the ejection fraction significantly improves with FSB-ECM treatment, accompanied by increased angiogenesis, reduced inflammation, and decreased infarct size. Finally, RNA sequencing combined with in vitro assays identifies ANGPTL4 as a key protein involved in mediating the effects of FSB-ECM treatment. Overall, this new injectable hydrogel based on FSB-ECM is suitable for transcatheter delivery and possesses remarkable reparative capabilities for treating heart failure. Show less
📄 PDF DOI: 10.1002/advs.202500036
ANGPTL4
Sihua Huang, Yan Lan, Cheng Zheng +3 more · 2025 · BMC neurology · BioMed Central · added 2026-04-24
As inflammatory processes may be involved in the pathogenesis of diabetic distal sensorimotor polyneuropathy (DSPN), the first aim of the present study was to determine the clinical characteristics of Show more
As inflammatory processes may be involved in the pathogenesis of diabetic distal sensorimotor polyneuropathy (DSPN), the first aim of the present study was to determine the clinical characteristics of type 2 diabetes mellitus (T2DM) with distal sensorimotor polyneuorpathy (DSPN). Next goal was to investigate inflammatory biomarkers, insulin-like growth factor- 1 and lipid profile in these patients. Finally, we aimed to compare the renal function in these patients. In a cross-sectional study, we included 160 patients diagnosed with T2DM. The control group was included 22 non-diabetic healthy subjects (HC). The patients with diabetes were divided into four groups, absent (n = 74), mild (n = 38), moderate (n = 24), and severe (n = 24) using a nomogram based on the MNSI features for a DSPN severity grading probability. Patients with moderate and severe DSPN were a little older and had longer duration of diabetes compared to patients with absent and mild DSPNS (p < 0.05). Serum levels of interferon-gamma (INF-γ), interleukin (IL)-1β, IL-4, IL- 6 levels in patients with severe DSPN were significantly higher than HC, absent, mild and moderate of DSPN (p < 0.05). The circulating levels of insulin-like growth factor-1 (IGF-1) were significantly lower in patients with severe DSPN (p < 0.05) compared to absent, mild and moderate of DSPN and HC. Diabetic patients with moderate DSPN showed increased circulating levels of TC, LDL-C, APOB (p < 0.05) compared to HC and patients with absent, mild and severe DSPN. Moreover, APO-A1/APOB was significantly lower in patients with diabetes compared to HC. In addition, patients with severe DSPN showed increased Cystatin C (p < 0.05) compared to HC and absent, mild, and moderate DSPN. Multivariate ordered logistic regression analysis showed that the levels of IL-6 (OR = 3.166, 95%CI 1.461-6.860, p = 0.003, IL-1β(OR = 1.148, 95%CI 1.070-2.232; p = 0.000), TC (OR = 1.174, 95%CI 1.011-1.364; p = 0.035), LDL-C (OR = 1.246, 95%CI 1.098-3.618; p = 0.003), Cystatin C (OR = 1.867, 95%CI 1.245-3.434; p = 0.004), ages (OR = 1.043, 95%CI 1.009-1.078; p = 0.012), and duration of diabetes (OR = 1.157, 95%CI 1.049-1.277; p = 0.004) were positively associated with increasing the odds ration of DSPN in T2DM. Conversely, the level of IGF-1 (OR = 0.922, 95%CI 0.961-0.982; p = 0.000) and ratio of APO-A1/APOB (OR = 0.212, 95%CI 0.078-0.567; p = 0.002) were significantly associated with decreasing the odds ratio of DSPN in T2DM. The levels of inflammatory biomarkers such as INF-γ, IL-1β, IL-4, IL- 6 were increased in patients with severe DSPN in T2DM. Ages, duration of diabetes as well as high circulating levels of IL-6, IL-1β, TC, LDL-C and Cystatin C were positively associated with DSPN in T2DM. Conversely, the level of IGF-1 and the ratio of APOA1/APOB were independent protective factors for DSPN in T2DM. Our results emphasize the importance of addressing issues related to inflammatory biomarkers, lipids and early impaired renal function in T2DM with DSPN, as these may be of potential relevance for deteriorating DSPN. Show less
📄 PDF DOI: 10.1186/s12883-025-04379-y
APOB
Priyansh Shah, Sara King, Sophia Trabanino +3 more · 2025 · Current atherosclerosis reports · Springer · added 2026-04-24
This review aims to explore the epidemiology of lipoprotein(a) [Lp(a)] by its structural and genetic make-up variation amongst ancestry groups. Lipoprotein(a) [Lp(a)] is a genetically determined lipop Show more
This review aims to explore the epidemiology of lipoprotein(a) [Lp(a)] by its structural and genetic make-up variation amongst ancestry groups. Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein particle, causally implicated in atherosclerotic cardiovascular disease (ASCVD) and calcific aortic valve stenosis (CAVS). Given its genetic basis, studies have shown marked ancestry-related differences in different races and ethnicities. Lp(a) plasma concentrations vary by more than 100-fold among individuals, primarily due to LPA gene polymorphisms and the number of kringle-IV type 2 (KIV2) repeats, which define apolipoprotein(a) [apo(a)] isoform size. Individuals of African descent have the highest median concentrations, followed by South Asians, with Hispanics/Latinos and East Asians having lower levels. Admixed populations display heterogeneity reflecting genetic ancestry. Despite differences in absolute levels, the relative ASCVD risk per unit increase in Lp(a) is consistent across groups, highlighting the universal atherogenicity of elevated Lp(a). Small apo(a) isoforms are associated with higher Lp(a) concentrations and risk, though isoform size is mainly a surrogate for Lp(a) burden. Despite a strong genetic basis and disproportionate burden in some populations, ancestry-specific testing guidelines are limited and testing rates remain low. Therapies targeting LPA transcription are in development, with outcome trials underway. Integrating ancestry-informed perspectives with universal risk principles is essential for equitable prevention and treatment. Routine, one-time Lp(a) testing enables cost-effective early risk stratification as Lp(a)-directed therapies emerge. Show less
📄 PDF DOI: 10.1007/s11883-025-01365-0
LPA
Yu Liao, Mingchao Wang, Fuli Qin +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically Show more
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically identify Cpn's therapeutic targets and pathways in Western diet (WD)-induced obesity using integrated network pharmacology, transcriptomics, and experimental validation. A Western diet (WD)-induced mice model was used to evaluate the effectiveness of Cpn in ameliorating obesity. A network pharmacology analysis was then employed to identify the potential anti-obesity targets of Cpn. GO functional enrichment and KEGG pathway analysis were performed to elucidate the potential functions of the identified targets, followed by constructing a protein-protein interaction network to screen the core targets. Meanwhile, quantitative transcriptomics was conducted to validate and broaden the network pharmacology findings. Finally, molecular docking and quantitative real-time PCR assay were used for the core target validation. Cpn treatment effectively alleviated obesity-related symptoms in WD-induced mice. The metabolic pathway, insulin signaling pathway, HIF-1 signaling pathway, FoxO signaling pathway, lipid and atherosclerosis pathway, and core targets including CPS1, HRAS, MAPK14, PAH, ALDOB, AKT1, GSK3B, HSP90AA1, BHMT2, EGFR, CASP3, MAT1A, APOM, APOA2, APOC3, and APOA1 are involved in regulating the therapeutic effect of Cpn. This study comprehensively uncovers the potential mechanism of Cpn against obesity based on network pharmacology and quantitative transcriptomics, which provides evidence for revealing the pathogenesis of obesity, suggesting that Cpn is a possible lead compound for anti-obesity treatment. Show less
📄 PDF DOI: 10.3389/fphar.2025.1571480
APOC3
Jingxuan Lian, Xiaohui Duan, Wenjie Chen +6 more · 2025 · Cell death discovery · Nature · added 2026-04-24
Gastrointestinal (GI) cancers exhibit aberrant lipid metabolism, yet the causal mechanisms remain elusive. Here, we integrated Mendelian randomization (MR) and multi-omics data to dissect metabolic dr Show more
Gastrointestinal (GI) cancers exhibit aberrant lipid metabolism, yet the causal mechanisms remain elusive. Here, we integrated Mendelian randomization (MR) and multi-omics data to dissect metabolic drivers of 20 GI diseases. Focusing on colorectal (CC) and esophageal cancer (EC), we identified five metabolites (e.g., 1,2-di-palmitoyl-sn-glycero-3-phosphocholine) and arachidonic acid ethyl ester as causal drivers. Summary-data-based MR and colocalization analysis (PP.H4 > 0.75) revealed FADS1 as a master regulator of these metabolites, with genetic variants exhibiting tissue-specific lipidomic effects. Functional validation using FADS1-knockout cell lines and mouse models demonstrated that FADS1 inhibition suppresses tumor cell proliferation, migration, and invasion while promoting apoptosis. In vivo, FADS1 deletion reduced chemically induced CC/EC tumor burden by 62-75%, accompanied by decreased Ki-67/MMP-9 expression and inflammatory infiltration. Mechanistically, FADS1 ablation disrupted lipid metabolism (reduced linoleic acid and arachidonic acid) and attenuated PI3K/AKT and MAPK signaling. Multi-omics integration further corroborated FADS1-mediated epigenetic regulation (e.g., mQTL-driven DNA methylation). This study establishes FADS1 as a pivotal orchestrator of GI carcinogenesis via metabolic reprogramming and signaling dysregulation, offering a compelling therapeutic target for precision oncology in CC and EC. Regulatory mechanisms of FADS1 in CC and EC. Show less
📄 PDF DOI: 10.1038/s41420-025-02768-3
FADS1
Ping Wang, Liping Zhu, Kecai Chen +6 more · 2025 · Ecotoxicology and environmental safety · Elsevier · added 2026-04-24
Oxidative deterioration of fish oil in aquafeeds poses a significant challenge to fish health and aquaculture sustainability, making it crucial to mitigate this issue through healthy and green nutriti Show more
Oxidative deterioration of fish oil in aquafeeds poses a significant challenge to fish health and aquaculture sustainability, making it crucial to mitigate this issue through healthy and green nutritional strategies. This study examined the potential of stevia chlorogenic acid (SCGA), a bioactive byproduct of stevia processing, to alleviate intestinal injury, gut microbiota dysbiosis, and lipid metabolism disorders induced by oxidized fish oil in turbot. Four diets with equal nitrogen and lipid contents were formulated: a control diet (PC) containing 5 % fresh fish oil, an oxidized fish oil diet (OFO) comprising 5 % oxidized fish oil, and two additional OFO diets supplemented with 200 mg/kg (OFO200) or 400 mg/kg (OFO400) of SCGA. Each dietary treatment was randomly assigned to three replicates, each containing 40 fish weighing approximately 16.99 ± 0.01 g, and administered over a 10-week period. Fish fed the OFO diet exhibited significantly compromised growth performance, as indicated by decreased WGR and SGR, along with reduced serum immune indices (IgM, C3, and C4) and lipid parameters (TC, HDL, LDL), and elevated serum D-LA levels (P < 0.05). Moreover, dietary OFO markedly suppressed antioxidant enzyme activities (serum SOD; intestinal SOD, GSH-Px, and CAT) and elevated MDA concentrations (P < 0.05). Additionally, OFO reduced intestinal expression of tight junction-associated genes (Claudin-4, Claudin-7, Occludin) while increasing expression levels of MLCK, Keap1, inflammatory mediators (IL-6, IL-1β, TNF-α2, NF-κB, IFN-γ), and Caspase7 (P < 0.05). Notably, the TLR signaling pathway-related genes were upregulated, accompanied by pronounced shifts in gut microbiota composition (P < 0.05). In hepatic tissue, lipogenesis-associated genes (FAS, ACC) were significantly increased, while key genes involved in lipid transport and β-oxidation (CD36, LPL, ACOX1, PPARγ) exhibited reduced expression (P < 0.05). Dietary supplementation with 200 and 400 mg/kg SCGA effectively mitigated these detrimental impacts. SCGA restored growth performance, serum immune parameters, and antioxidant enzyme activities to levels comparable to the PC group. It also normalized gene expression related to intestinal barrier function, inflammation, apoptosis, and hepatic lipid metabolism. Furthermore, SCGA supplementation modulated gut microbiota structure by increasing beneficial genera and decreasing potential pathogens. In conclusion, SCGA effectively improves growth performance, alleviates OFO-induced intestinal injury and microbial dysbiosis, and regulates lipid metabolism in turbot. These findings provide theoretical insights and technical support for the application of SCGA in aquaculture. Show less
no PDF DOI: 10.1016/j.ecoenv.2025.119321
LPL
Jun Qiao, Lei Jiang, Liuyang Cai +14 more · 2025 · Nature communications · Nature · added 2026-04-24
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations Show more
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations, suggesting a shared genetic basis. However, the precise genetic mechanisms underlying these associations remain elusive. By assessing genetic correlations, genetic overlap, and causal connections, we aim to shed light on common genetic underpinnings among major CVDs. Employing multi-trait analysis, we pursue diverse strategies to unveil shared genetic elements, encompassing SNPs, genes, gene sets, and functional categories with pleiotropic implications. Our study systematically quantifies genetic overlap beyond genome-wide genetic correlations across CVDs, while identifying a putative causal relationship between coronary artery disease (CAD) and heart failure (HF). We then pinpointed 38 genomic loci with pleiotropic influence across CVDs, of which the most influential pleiotropic locus is located at the LPA gene. Notably, 12 loci present high evidence of multi-trait colocalization and display congruent directional effects. Examination of genes and gene sets linked to these loci unveiled robust associations with circulatory system development processes. Intriguingly, distinct patterns predominantly driven by atrial fibrillation, coronary artery disease, and venous thromboembolism underscore the significant disparities between clinically defined CVD classifications and underlying shared biological mechanisms, according to functional annotation findings. Show less
📄 PDF DOI: 10.1038/s41467-025-62419-0
LPA
Dong-Yi Chen, Ming-Lung Tsai, Ming-Jer Hsieh +8 more · 2025 · European journal of preventive cardiology · Oxford University Press · added 2026-04-24
Recent evidence suggests that elevated lipoprotein(a) [Lp(a)] contributes to atherosclerotic cardiovascular disease (ASCVD). The predictive value of specific Lp(a) cutoff points of 30 mg/dL remains to Show more
Recent evidence suggests that elevated lipoprotein(a) [Lp(a)] contributes to atherosclerotic cardiovascular disease (ASCVD). The predictive value of specific Lp(a) cutoff points of 30 mg/dL remains to be established. This study investigated the relationship between Lp(a) concentrations and cardiovascular outcomes in Taiwanese individuals, stratified by pre-existing ASCVD status. We conducted a retrospective analysis of 51,934 subjects from the Chang Gung Research Database (January 2004 to June 2019), comprising 49,363 individuals without ASCVD and 2,571 with established ASCVD. The primary outcome was major adverse cardiovascular events (MACEs), encompassing acute myocardial infarction, ischemic stroke, revascularization procedures, peripheral arterial interventions, and cardiovascular mortality. Individuals were followed until their last visit to our institutions or December 31, 2019. During a mean follow-up of 6.6 years (standard deviation: 5.0 years), the study population demonstrated a median Lp(a) of 9.6 mg/dL (interquartile range: 4.6-18.5). In ASCVD-free individuals, Lp(a) concentrations ≥30 mg/dL were associated with increased MACE risk (adjusted subdistribution hazard ratio [aSHR]: 1.24; 95% confidence interval [CI]: 1.07-1.43). Similarly, in the ASCVD cohort, elevated Lp(a) predicted higher MACE occurrence (aSHR: 1.36; 95% CI: 1.07-1.74). Restricted cubic spline analysis confirmed a progressive risk elevation beyond the 30 mg/dL threshold in both groups. Lp(a) levels ≥30 mg/dL independently predicted adverse cardiovascular outcomes, regardless of baseline ASCVD status. This threshold appears suitable for cardiovascular risk stratification in both primary and secondary prevention settings. Show less
no PDF DOI: 10.1093/eurjpc/zwaf649
LPA
Shenghui Su, Yu Zeng, Jiaxin Chen +1 more · 2025 · Oncology research · added 2026-04-24
Recent studies have shown glycerolipid metabolism played an essential role in multiple tumors, however, its function in osteosarcoma is unclear. This study aimed to explore the role of glycerolipid me Show more
Recent studies have shown glycerolipid metabolism played an essential role in multiple tumors, however, its function in osteosarcoma is unclear. This study aimed to explore the role of glycerolipid metabolism in osteosarcoma. We conducted bioinformatics analysis using data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and single-cell RNA sequencing. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to identify the Glycerolipid metabolism-related genes associated with the clinical outcome of osteosarcoma. Tumor-associated macrophages (TAMs) and their interactions with immune cells were examined through single-cell analysis and co-culture experiments. Virtual screening was employed to identify the potential lysophosphatidic acid receptor 6 (LPAR6) inhibitors. Glycerolipid metabolism-related genes 1-acylglycerol-3-phosphate O-acyltransferase 3 ( Show less
📄 PDF DOI: 10.32604/or.2025.070558
LPA
Sihua Xu, Yiyuan Xiao, Chaoyu Xu +6 more · 2025 · BMJ open sport & exercise medicine · added 2026-04-24
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health issue due to its high prevalence, yet the impact of accelerometer-measured physical activity on clinical outcomes re Show more
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health issue due to its high prevalence, yet the impact of accelerometer-measured physical activity on clinical outcomes remains unclear. This study aims to examine the associations of physical activity with the risk of liver cirrhosis, cancer, cardiovascular disease (CVD) incidence and mortality. 32 681 MASLD participants with accelerometer-derived physical activity data from the UK Biobank were analysed. Physical activity intensity was categorised into light (LPA), moderate (MPA) and vigorous (VPA) intensity. Cox proportional hazard and acceleration failure models were employed to assess associations between physical activity duration and outcomes. During a median follow-up of 7.5-7.9 years, 1883 deaths, 151 liver cirrhosis, 3312 cancers and 6657 CVD events were recorded. Physical activity, regardless of intensity, was consistently associated with a reduced risk of liver cirrhosis, CVD and all-cause mortality. Compared with non-MASLD individuals, our analysis indicates that longer duration of physical activity, specifically >1945 min/week of LPA or >383 min/week of MPA may theoretically eliminate the excess risk of mortality associated with MASLD. Among MASLD individuals, longer physical activity duration, regardless of intensity, was associated with reduced risks of liver cirrhosis and mortality. MPA and VPA were associated with lower CVD risk, while VPA was associated with reduced cancer risk, highlighting the potential benefits of increasing the intensity and duration of physical activity in MASLD management. Show less
📄 PDF DOI: 10.1136/bmjsem-2025-002702
LPA
Hung-Chin Tsai, Pei-Yun Chou, Hui-Min Chang +2 more · 2025 · Journal of the Chinese Medical Association : JCMA · added 2026-04-24
Apolipoprotein C3 (APOC3) was found to induce inflammation in human monocytes. Jarisch-Herxheimer reaction (JHR) was perceived to be caused by immune reactions of dividing spirochaetes to penicillin t Show more
Apolipoprotein C3 (APOC3) was found to induce inflammation in human monocytes. Jarisch-Herxheimer reaction (JHR) was perceived to be caused by immune reactions of dividing spirochaetes to penicillin treatment. The aim of this study was to investigate the role of APOC3 in patients with syphilis and JHR. This prospective cohort study enrolled adult patients with active syphilis with/without JHR. Serum samples were collected before and after administration of the first dose of benzathine penicillin and the serum levels of APOC3 were determined by enzyme-linked immunosorbent assay (ELISA). The APOC3 level and changes in APOC3 level before and after benzathine penicillin treatment in different groups were compared with the Mann-Whitney U test or Kruskal-Wallis test. Forty adult patients with syphilis and 32 controls were enrolled. All 40 patients with syphilis were men who have sex with men, and 30 (75%) were people living with human immunodeficiency virus (HIV). Overall, 19 patients (47%) developed JHR. The active syphilis group had a significantly higher serum APOC3 level (median 38.3 µg/mL, interquartile range [IQR]: 34.5-48.0 µg/mL) than the controls ( p = 0.020). The serum levels of APOC3 were higher in the 21 patients without JHR before and after benzathine penicillin treatment compared with the controls (38.9 µg/mL [IQR: 34.5-66.7 µg/mL] and 39.4 µg/mL [IQR: 33.7-62.9] µg/mL vs 31.8 µg/mL [IQR: 27.5-42.2 µg/mL]). Receiving operating characteristic curve analysis showed that the best cutoff value of APOC3 to predict the absence of JHR before benzathine penicillin therapy compared to the controls was 34.2 µg/mL (area under the curve 0.695, p = 0.017, CI = 0.544-0.846, sensitivity = 0.81, specificity = 0.406). A high baseline serum APOC3 level can predict the absence of JHR in patients with syphilis treated with the first dose of benzathine penicillin. Show less
📄 PDF DOI: 10.1097/JCMA.0000000000001238
APOC3
Xiaotao Jiang, Hui Wu, Ning Yan +14 more · 2025 · Research (Washington, D.C.) · added 2026-04-24
The development of an immunosuppressive microenvironment is a critical factor in stomach carcinogenesis. Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) serve a pivotal function in medi Show more
The development of an immunosuppressive microenvironment is a critical factor in stomach carcinogenesis. Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) serve a pivotal function in mediating immune suppression. However, the precise mechanisms underlying PMN-MDSCs infiltration into the tumor immune microenvironment (TIME) and their immunosuppressive functions remain poorly understood. In this investigation, we observed that PMN-MDSCs were up-regulated during stomach carcinogenesis, with gastric cancer (GC) cells secreting CCL26 to promote the infiltration of PMN-MDSCs into the TIME via the CX3CR1 receptor. The infiltrating CX3CR1 Show less
no PDF DOI: 10.34133/research.1002
SNAI1
Yuping Huang, Junguang Liao, Panpan Shen +7 more · 2025 · JCI insight · added 2026-04-24
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molec Show more
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molecular scaffolds coordinating these processes remain incompletely defined. Here, we identify neurofibromin 2 (Nf2) as a critical regulator to direct CNC-derived skull morphogenesis. Genetic ablation of Nf2 in murine CNCs causes severe craniofacial anomalies, featuring declined proliferation and increased apoptosis in osteoprogenitors, impaired type I collagen biosynthesis and trafficking, and aberrant osteogenic mineralization. Mechanistically, we uncover that Nf2 serves as a molecular linker that individually interacts with FGF receptor 1 (FGFR1) and Akt through spatially segregated phosphor-sites, and structural modeling and mutagenesis identified Ser10 and Thr230 as essential residues, with Thr230 mutation selectively ablating Akt binding while preserving FGFR1 association. Strikingly, Akt inhibition phenocopied Nf2 deficiency, reducing collagen production and Nf2 phosphorylation, whereas phospho-mimetic Nf2 (T230D) rescued CNC-derived osteogenic defects in Nf2-mutant animals. Our findings underscore the physiological significance of Nf2 as a phosphorylation-operated scaffold licensing the FGFR1/AKT axis to regulate collagen type I biogenesis and trafficking, ensuring normal CNC-derived osteogenesis and craniofacial bone development, thus exposing the Nf2/FGFR1/AKT signaling axis as a therapeutic target and promising advancements in treatment of craniofacial anomalies. Show less
📄 PDF DOI: 10.1172/jci.insight.191112
FGFR1
Mimi Li, Lichao Ye, Chunnuan Chen · 2025 · Scientific reports · Nature · added 2026-04-24
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contr Show more
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contributing to stroke remains poorly understood. This study aims to investigate the association between the apoB/apoA1 ratio and intracranial or extracranial atherosclerosis. We enrolled 408 patients with acute ischemic stroke who had never been treated with statins or fibrates. Based on the images from computed tomography angiography (CTA), the patients were categorized into four groups: intracranial atherosclerosis stenosis (ICAS, n = 136), extracranial carotid atherosclerosis stenosis (ECAS, n = 45), combined intracranial and extracranial atherosclerosis stenosis (COAS, n = 73), and non-cerebral atherosclerosis stenosis (NCAS, n = 154). Demographic characteristics, clinical factors, and serum lipid levels were collected and then compared across groups. The apoB/apoA1 ratio was significantly higher in patients with ICAS, ECAS and COAS compared to those in the NCAS group. Multivariable logistic regression analysis demonstrated that the ApoB/ApoA1 ratio was independently associated with ICAS, but not with ECAS. ROC curve analysis showed that the ApoB/ApoA1 ratio had a good diagnostic ability for ICAS, with an area under the curve (AUC) of 0.764, an optimal cut-off value of 0.8122, a sensitivity of 81.3%, and a specificity of 59.8%. An higher apoB/apoA1 ratio is associated with ICAS in ischemic stroke patients. Show less
📄 PDF DOI: 10.1038/s41598-025-97625-9
APOB
Xiong Guo, Chong Huang, Ling Zhang +18 more · 2025 · Circulation · added 2026-04-24
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining Show more
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining heart health by draining fluids and immune cells. However, their involvement in HFpEF remains largely unexplored. We examined cardiac lymphatic alterations in mice with HFpEF with comorbid obesity and hypertension, and in heart tissues from patients with HFpEF. Using genetically engineered mouse models and various cellular and molecular techniques, we investigated the role of cardiac lymphatics in HFpEF and the underlying mechanisms. In mice with HFpEF, cardiac lymphatics displayed substantial structural and functional anomalies, including decreased lymphatic endothelial cell (LEC) density, vessel fragmentation, reduced branch connections, and impaired capacity to drain fluids and immune cells. LEC numbers and marker expression levels were also decreased in heart tissues from patients with HFpEF. Stimulating lymphangiogenesis with an adeno-associated virus expressing an engineered variant of vascular endothelial growth factor C (VEGFC Our study provides evidence that cardiac lymphatic disruption, driven by impaired BCAA catabolism in LECs, is a key factor contributing to HFpEF. These findings unravel the crucial role of BCAA catabolism in modulating lymphatic biology, and suggest that preserving cardiac lymphatic integrity may present a novel therapeutic strategy for HFpEF. Show less
📄 PDF DOI: 10.1161/CIRCULATIONAHA.124.071741
BCKDK
Min Wang, Chong Xu, Xiaoshan Du +7 more · 2025 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
Ischemic stroke (IS) is a major cause of disability and mortality, but its genetic basis remains poorly understood. This study integrates data from three large-scale genome-wide association studies (G Show more
Ischemic stroke (IS) is a major cause of disability and mortality, but its genetic basis remains poorly understood. This study integrates data from three large-scale genome-wide association studies (GWASs), the GWAS Catalog, MEGASTROKE, and Open GWAS, to identify novel genetic loci linked to IS. Our meta-analysis revealed 124 new IS-associated loci, with enrichment in genes involved in cerebrovascular function, inflammation, and metabolism. Candidate genes like Show less
📄 PDF DOI: 10.1016/j.omtn.2025.102633
HSD17B12
Yasuaki Uemoto, Chang-Ching A Lin, Bingnan Wang +10 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
FGFR1 amplification and FGFR1/2 activating mutations have been associated with antiestrogen resistance in estrogen receptor-positive (ER+) breast cancer. However, there are no approved FGFR1-targeted Show more
FGFR1 amplification and FGFR1/2 activating mutations have been associated with antiestrogen resistance in estrogen receptor-positive (ER+) breast cancer. However, there are no approved FGFR1-targeted therapies for breast cancers harboring these alterations. In this study, we investigated the selective degradation of FGFR1/2 using the proteolysis-targeting chimera (PROTAC) DGY-09-192 as a novel therapeutic strategy in ER + breast cancers harboring FGFR1/2 somatic alterations. Treatment of ER+/FGFR1-amplified breast cancer cells and patient-derived xenografts with DGY-09-192 resulted in sustained degradation of FGFR1 in a proteasome-dependent manner and suppressed downstream signal transduction. The combination of DGY-09-192 and the ERα degrader fulvestrant resulted in complete cell growth arrest and tumor regression of ER+/FGFR1-amplified patients-derived xenografts. In addition, we tested the effect of DGY-09-192 on breast cancer cells expressing FGFR1 Show less
no PDF DOI: 10.1016/j.canlet.2025.217668
FGFR1
Jun He, Brenda Cabrera-Mendoza, Dan Qiu +7 more · 2025 · medRxiv : the preprint server for health sciences · added 2026-04-24
While previous genome-wide association studies (GWAS) identified multiple risk loci for suicide ideation (SI) and suicide attempt (SA), there is still a limited understanding of the genetic predisposi Show more
While previous genome-wide association studies (GWAS) identified multiple risk loci for suicide ideation (SI) and suicide attempt (SA), there is still a limited understanding of the genetic predisposition underlying suicidal behaviors in diverse populations. This study aimed to conduct a large-scale investigation of the suicidality spectrum (SP) to generate new insights into its biology and epidemiology. Leveraging ancestrally diverse participants (SI N This study provides convergent genetic evidence for both shared and phenotype-specific components of suicidal behaviors and delineates their associated factors spanning from proximal clinical and behavioral traits to more distal social determinants. These findings refine our understanding of the etiology of suicidal behaviors and may inform targeted strategies for suicide prevention in both clinical and public health settings. Show less
no PDF DOI: 10.64898/2025.12.15.25342298
BRWD1
Haoyu Deng, Wan Yi Liang, Leqi Chen +6 more · 2025 · Journal of lipid research · Elsevier · added 2026-04-24
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death fro Show more
Sepsis is the dysregulated immune response to an infection and is a leading cause of mortality. Low levels of high-density lipoprotein (HDL) cholesterol are associated with increased risk of death from sepsis, and increasing levels of HDL by inhibition of cholesteryl ester transfer protein (CETP) has been shown to decrease mortality in mouse models of sepsis. The objective of this study was to investigate the cellular mechanisms by which CETP inhibition and HDL lead to improved survival during sepsis. We found that HDL inhibits lipopolysaccharide (LPS)-induced activation of IL-1β in a mouse model of sepsis. The activation of IL-1β was dependent on the activity of scavenger receptor class B type 1 (SR-B1), and knockdown of SR-B1 significantly attenuated LPS-induced production of IL-1β in macrophages. Additionally, we found that LPS-induced SR-B1 internalization occurs through the endosome-lysosome pathway, which is also likely responsible for LPS degradation in the macrophages. Furthermore, we revealed that raising HDL by CETP inhibition markedly enhanced HDL-mediated anti-inflammatory effects in response to LPS stimulation, and these effects were not due to CETP itself but rather were HDL-dependent. Finally, we show that pharmacological inhibition of CETP significantly improved endotoxemia-induced mortality by inhibiting IL-1β production in the liver and circulation after LPS injection. Pathologically, CETP inhibition attenuated LPS-induced diffuse alveolar damage and hepatocyte necrosis, which may contribute to the improved mortality in mice treated with the CETP inhibitor anacetrapib. Taken together, our findings uncover a cellular mechanism by which HDL attenuates LPS-induced pro-inflammatory response via SR-B1-mediated LPS degradation. Show less
📄 PDF DOI: 10.1016/j.jlr.2025.100858
CETP
Megan E Capozzi, David Bouslov, Ashot Sargsyan +21 more · 2025 · The Journal of clinical investigation · added 2026-04-24
The incretin peptides glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptors coordinate β cell secretion that is proportional to nutrient intake. This effect permits consis Show more
The incretin peptides glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptors coordinate β cell secretion that is proportional to nutrient intake. This effect permits consistent and restricted glucose excursions across a range of carbohydrate intake. The canonical signaling downstream of ligand-activated incretin receptors involves coupling to Gαs protein and generation of intracellular cAMP. However, recent reports have highlighted the importance of additional signaling nodes engaged by incretin receptors, including other G proteins and β-arrestin proteins. Here, the importance of Gαs signaling was tested in mice with conditional, postdevelopmental β cell deletion of Gnas (encoding Gαs) under physiological and pharmacological conditions. Deletion of Gαs/cAMP signaling induced immediate and profound hyperglycemia that responded minimally to incretin receptor agonists, a sulfonylurea, or bethanechol. While islet area and insulin content were not affected in Gnasβcell-/-, perifusion of isolated islets demonstrated impaired responses to glucose, incretins, acetylcholine, and IBMX In the absence of Gαs, incretin-stimulated insulin secretion was impaired but not absent, with some contribution from Gαq signaling. Collectively, these findings validate a central role for cAMP in mediating incretin signaling, but also demonstrate broad impairment of insulin secretion in the absence of Gαs that causes both fasting hyperglycemia and glucose intolerance. Show less
📄 PDF DOI: 10.1172/JCI183741
GIPR