👤 Yufen Li

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Also published as: Xiaofeng Li, Jingwen Li, Jiajia Li, Zhaolun Li, Litao Li, Ruyi Li, Xiaocun Li, Jianyu Li, Wanxin Li, Jinsong Li, Xinzhi Li, Guanqiao Li, Ying-Lan Li, Zequn Li, Yulin Li, Shaojian Li, Guang-Xi Li, Yubo Li, Bugao Li, Mohan Li, Yan-Xue Li, Qingchao Li, Xikun Li, Enhong Li, Guobin Li, Hong-Tao Li, Xiangnan Li, Yong-Jun Li, Ziming Li, Hang Li, Rongqing Li, Xihao Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Yicun Li, Xiao-Lin Li, Jiajie Li, Zhao-Yang Li, Shunqin Li, Xinjia Li, K-L Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Peiwu Li, Youran Li, Yongmei Li, Changyu Li, Ran Li, Peilin Li, X Y Li, Chunshan Li, Ming Zhou Li, Yixiang Li, Ye Li, Guanglve Li, Z Li, Zili Li, Xinmei Li, Yihao Li, Liling Li, Qing Run Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Qiankun Li, Kailong Li, Shisheng Li, Shengxu Li, Sai Li, Guangwen Li, Xiuli Li, Hua Li, Yulong Li, Dongmei Li, Ru-Hao Li, Lanzhou Li, Zhi-Peng Li, Tingsong Li, Binjun Li, Chen Li, Yawei Li, Jiayang Li, Zunjiang Li, Chao Bo Li, Minglong Li, Donghua Li, Wenzhe Li, Siming Li, Fengli Li, Song Li, Zihan Li, Hsin-Hua Li, Jin-Long Li, Hongxin Li, Dongfeng Li, You Li, Xueyang Li, Xuelin Li, Zhen-Yuan Li, Fa-Hui Li, Caiyu Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Shiyu Li, Bao Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Xiaoqing Li, Jinlin Li, Linke Li, Shuaicheng Li, C Y Li, Thomas Li, Siting Li, Xuebiao Li, Yingyi Li, Yongnan Li, Maolin Li, Jiyang Li, Jinchen Li, Jin-Ping Li, Xuewen Li, Zhongxuan Li, R Li, Xianlong Li, Aixin Li, Linting Li, Zhong-Xin Li, Xuening Li, Enhao Li, Guang Li, Xiaoming Li, Shengliang Li, Z-H Li, Yongli Li, Baohong Li, Hujie Li, Yue-Ming Li, Shuyuan Li, Zhaohan Li, L Li, Yuanmei Li, Alexander Li, Yanwu Li, Hualing Li, Wen-juan Li, Sibing Li, Qinghe Li, Xining Li, Pilong Li, Yun-Peng Li, C X Li, Zonghua Li, Jingya Li, Huanan Li, Liqin Li, Youjun Li, Zheng-Dao Li, Zhenshu Li, Miao X Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wen-Ying Li, Wei Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Ming Li, Kangli Li, Runwen Li, Wenbo Li, Yarong Li, Side Li, Timmy Li, S E Li, Weidong Li, Xin-Tao Li, Ruotong Li, Shuguang Li, Xiuzhen Li, Chuan-Hai Li, Lingxi Li, Jiezhen Li, Qiuya Li, Haitao Li, Tingting Li, Guanghua Li, Qin Li, Zhongyu Li, Zhen-Yu Li, Deyu Li, Hansen Li, Annie Li, Wenge Li, Jinzhi Li, Xueren Li, Chun-Mei Li, Yijing Li, Kaifeng Li, Wen-Xing Li, Meng-Yao Li, Chung-I Li, Zhi-Bin Li, Qintong Li, Xiao Li, Junping Li, PeiQi Li, Naishi Li, Xiaobing Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Pan Li, Shengchao A Li, Jiaying Li, Jun-Jie Li, Ruonan Li, Cui-lan Li, Shuhao Li, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Suyan Li, Chengquan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, Xue Cheng Li, Ya-Jun Li, Wenyong Li, Ding-Biao Li, Tianjun Li, Desen Li, Yansong Li, Xiying Li, Weiyong Li, Zihao Li, Xinyang Li, Fadi Li, Huawei Li, Yu-quan Li, Cui Li, Xiaoyong Li, Y L Li, Xueyi Li, Jingxiang Li, Wenxue Li, Jihua Li, Jingping Li, Zhiquan Li, Zeyu Li, Yingpu Li, Jianglin Li, Jing-Yao Li, Yan-Hua Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, L K Li, Ya-Ting Li, Wan Jie Li, Aimin Li, Dongbiao Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, Peiyun Li, Xiuqi Li, L-Y Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Yu Li, Minhui Li, Yvonne Li, Yiwei Li, Jiayuan Li, Xiangzhe Li, Zhichao Li, Yige Li, Siguang Li, Minglun Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chiyang Li, Chunlan Li, Hulun Li, Juan-Juan Li, Hailong Li, Hua-Zhong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Jing Li, Si Li, Xiangyun Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Zijing Li, Dengke Li, Yuchuan Li, Wentao Li, Qingling Li, Rui-Han Li, Xuhong Li, Dong Li, Hongyun Li, Zhonggen Li, Xiong Li, Penghui Li, Xiaoxia Li, Dezhi Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Sheng-Jie Li, Defa Li, Ying-Qing Li, X L Li, Yuyan Li, Kawah Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Zhenfei Li, Shupeng Li, Sha-Sha Li, Mengxuan Li, Panyuan Li, Gang Li, Ziyu Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, Ji-Liang Li, Huaping Li, C H Li, Bohua Li, Bing Li, Pei-Ying Li, Huihuang Li, Shaobin Li, Yunmin Li, Yanying Li, Ronald Li, Gui Lin Li, Chenrui Li, Shi-Hong Li, Shilun Li, John Zhong Li, Xinyu Li, Lujiao Li, Song-Chao Li, Chenghong Li, Dengfeng Li, Nianfu Li, Baohua Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Jiao Li, Zhimei Li, Jun-Cheng Li, Yimeng Li, Jingming Li, Jinxia Li, De-Tao Li, Chunting Li, Shu Li, Julia Li, Chien-Feng Li, Huilan Li, Mei-Zhen Li, Xin-Ya Li, Zhengjie Li, Chunsheng Li, Yan-Yan Li, Liwei Li, Huijun Li, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Lijun Li, Supeng Li, Hening Li, Yiju Li, Yuanhe Li, Guangxiao Li, Fengxia Li, Xueqin Li, Peixin Li, Feng-Feng Li, Jialing Li, Zu-Ling Li, Xin Li, Yunjiu Li, Dayong Li, Zonghong Li, Ningyan Li, Lingjiang Li, Yuhan Li, Zhenghui Li, Fuyuan Li, Ailing Li, H-F Li, Chunxia Li, Chaochen Li, Zhen-Li Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Zhengying Li, Zhaoshui Li, Yali Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, Kaiyuan Li, Zengyang Li, Mangmang Li, Chunyan Li, Runzhen Li, Xiaopeng Li, Xi-Hai Li, MengGe Li, Xuezhong Li, Anan Li, Luying Li, Jiajv Li, Pei-Lin Li, Xiaoquan Li, Yanxi Li, Wan-Xin Li, Ning Li, Ruobing Li, Xia Li, Yongjing Li, Meitao Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Huixue Li, Jiqing Li, Boxuan Li, Hehua Li, Yucheng Li, Qingyuan Li, Yongqi Li, Fengqi Li, Zhigang Li, Yuqing Li, Guiyang Li, Guo-Qiang Li, Dujuan Li, Yanbo Li, Yuying Li, Shaofei Li, Sanqiang Li, Shaoguang Li, Min-Rui Li, Hongyu Li, Guangping Li, Shuqiang Li, Dan C Li, Huashun Li, Jinxin Li, Ganggang Li, Xinrong Li, Haoqi Li, Yayu Li, Handong Li, Huaixing Li, Yan-Nan Li, Xianglong Li, Minyue Li, Hong-Mei Li, Jing-Jing Li, Songhan Li, Mengxia Li, Jutang Li, Conglin Li, Qingli Li, Yongxiang Li, Miao Li, Songlin Li, Qilong Li, Dijie Li, Chenyu Li, Yizhe Li, Ke Li, Yan Bing Li, Jiani Li, Lianjian Li, Zhen-Hua Li, Yiliang Li, Chuan-Yun Li, Xinpeng Li, Hongxing Li, Wanyi Li, Gaoyuan Li, Youming Li, Mi Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Fengfeng Li, Yumiao Li, Jiexi Li, Qinggang Li, Huixia Li, Kecheng Li, Xiangjun Li, Xingye Li, Junxu Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Qingyang Li, Yuxi Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Zhaoping Li, Xingyu Li, Xiaolei Li, Zhenlu Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Zhenhui Li, Cheung Li, Zhenming Li, Xuelian Li, Shu-Fen Li, Chunjun Li, Changyan Li, Mulin Jun Li, Yinghua Li, Shangjia Li, Yanjie Li, Jingjing Li, Suhong Li, Xinping Li, Siyu Li, Chaoying Li, Qiu Li, Juanjuan Li, Xiangyan Li, Guangzhen Li, Kunlun Li, Xiaoyu Li, Shiyun Li, Yaobo Li, Shiquan Li, Xuewang Li, Mei Li, Xiangdong Li, Jifang Li, Zhenjia Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiao-Li Li, Xiaoya Li, Shan Li, Shitao Li, Zehan Li, Lijia Li, Chunqiong Li, Huiliang Li, Junjun Li, Chenlong Li, Shujin Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Weining Li, Wenxi Li, Wu-Jun Li, Chang-hai Li, Bin-Kui Li, Yuqiu Li, Yumao Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Chia Li, Y X Li, Yunyun Li, Zhen-Jia Li, Fu-Rong Li, Honghua Li, Lanjuan Li, Qiuxuan Li, Xiancheng Li, Man-Zhi Li, Yanmei Li, De-Jun Li, Junxian Li, Keqing Li, Zhihua Li, Shuwen Li, Danxi Li, Saijuan Li, Minqi Li, Lingjun Li, Mimi Li, Deheng Li, Si-Xing Li, Yingjie Li, Yaodong Li, Shigang Li, Yuan-Hai Li, Lujie Li, Gao-Fei Li, Minghao Li, Minle Li, Meifen Li, Yifeng Li, Le-Le Li, Huanqing Li, Ziwen Li, Yuhang Li, Yongqiu Li, Pu-Yu Li, Jianhua Li, Chanjuan Li, Nan-Nan Li, Hongming Li, Lan-Lan Li, Shuang Li, Yanchuan Li, Lingyi Li, Wanting Li, Bai-Qiang Li, Gong-Hua Li, Zhengyu Li, Chunmiao Li, Jiong-Ming Li, Yongqiang Li, Linsheng Li, Weiguang Li, Mingyao Li, Guoqing Li, Ze Li, Xiaomeng Li, R H L Li, Yuanze Li, Yunqi Li, Yuandong Li, Guisen Li, Jinglin Li, Dongyang Li, Mingfang Li, Honglong Li, Hanmei Li, Chenmeng Li, Changcheng Li, Shiyang Li, Shiyue Li, Hanbo Li, Jianing Li, Yinggao Li, Dingshan Li, Linlin Li, Xinsheng Li, Jin-Wei Li, Jin-Jiang Li, Cheng-Tian Li, Chang Li, Zhi-Xing Li, Yaxi Li, Ming-Han Li, Wei-Ming Li, Wenchao Li, Guangyan Li, Zhaosha Li, Xuesong Li, Jiwei Li, Chun-Quan Li, Yongzhen Li, Weifeng Li, Tao Li, Wenhui Li, Sichen Li, Xiankai Li, Qingsheng Li, Yaxuan Li, Liangji Li, Yuchan Li, Lixiang Li, Tian-wang Li, Jiaxi Li, Yalin Li, Jin-Liang Li, Pei-Zhi Li, You Ran Li, Xiaoqiong Li, Guanyu Li, Jinlan Li, Yixiao Li, Huizi Li, Jianping Li, Kathy H Li, Yun-Lin Li, Yadong Li, Yuhua Li, Sujing Li, Xuri Li, Wenzhuo Li, Deqiang Li, Y Li, Mingyue Li, Caixia Li, Zipeng Li, Hongli Li, Yun Li, Mengqiu Li, Ling-Ling Li, Yaqin Li, Yanfeng Li, Yu-He Li, Shasha Li, Xi Li, S-C Li, Siyi Li, Minmin Li, Manna Li, Chengwen Li, Dawei Li, Shu-Feng Li, Haojing Li, Xun Li, Ming-Jiang Li, Zhiyu Li, Sitao Li, Ziyang Li, Yaochen Li, Qian Li, Tinghua Li, Wenyang Li, Bohao Li, Zhenfen Li, Shuo Li, Wenming Li, Mingxuan Li, Si-Ying Li, Xinyi Li, Jenny J Li, Xue-zhi Li, Anqi Li, Bingsong Li, Shuai Li, Xiaoju Li, Ting Li, Zhenyu Li, Xiaonan Li, Duan Li, Xiang-Yu Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Yanchang Li, Xunjia Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, Zong-Xue Li, En-Min Li, Chunya Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Jinhua Li, Min-jun Li, Qian-Qian Li, Yuanheng Li, Chunxiao Li, Wenli Li, Shijun Li, Mengze Li, Kuan Li, Baoguang Li, Kaiwei Li, Jie-Shou Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Junxin Li, Yu-Sheng Li, Wei-Jun Li, Guoyan Li, Fei-Lin Li, Junjie Li, Nuomin Li, Shanglai Li, Yanyan Li, Shulin Li, Taibo Li, Yue Li, Junqin Li, Zhongcai Li, Xueying Li, Jun-Ru Li, JunBo Li, Xiaoqi Li, Zhaobing Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, Chen-Chen Li, Shujing Li, Tsai-Kun Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Yi-Wen Li, Xiyun Li, Huifeng Li, Rulin Li, Ya-Pei Li, Shihong Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Min-Dian Li, Wenjia Li, Xiatian Li, Ding-Jian Li, Hongwei Li, Yangxue Li, Xiao-Qiang Li, Danni Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Yiqiang Li, Pengyang Li, Kun-Xin Li, Xiawei Li, Binglan Li, Yutong Li, Zesong Li, Xiangpan Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Boru Li, Yinxiong Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Hong-Yu Li, Chuanning Li, Weijian Li, Changhui Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Dechao Li, Chunxing Li, Wenxia Li, Guoxiang Li, Ziru Li, Qiao-Xin Li, Shu-Fang Li, Huang Li, Qiusheng Li, Juxue Li, Man Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Gongda Li, Nan Li, Wei-Ping Li, Yajun Li, Yipeng Li, Mingxing Li, Nanjun Li, Xin-Yu Li, Chunyu Li, P H Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Ranran Li, Suping Li, Long Shan Li, Yanze Li, Jason Li, Xiao-Feng Li, Monica M Li, Fengjuan Li, W Li, Xianlun Li, Qi Li, Hainan Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Fei Li, Xionghui Li, Ying-Bo Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Hongmei Li, Kang Li, Peilong Li, Yinghao Li, Xu-Wei Li, Mengsen Li, Lirong Li, Wenhong Li, Quanpeng Li, Audrey Li, Yijian Li, Yajiao Li, Guang Y Li, Xianyong Li, Qilan Li, Shilan Li, Qiuhong Li, Zongyun Li, Xiao-Yun Li, Guang-Li Li, Cheng-Lin Li, Bang-Yan Li, Enxiao Li, Jianrui Li, Yousheng Li, Wen-Ting Li, Guohua Li, Kezhen Li, Xingxing Li, Guoping Li, Ellen Li, A Li, Simin Li, Xue-Nan Li, Yijie Li, Weiguo Li, Xiaoying Li, Suwei Li, Shengsheng Li, Shuyu D Li, Jiandong Li, Ruiwen Li, Fangyong Li, Hong Li, Binru Li, Yuqi Li, Zihua Li, Yuchao Li, Hanlu Li, Jianang Li, Xue-Peng Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Feng Li, Weiyang Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Xinxiu Li, Kaibo Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Meng-Hua Li, Shaodan Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Zheng Li, Donghe Li, Ming-Hao Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Menghua Li, Jingqi Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Chong Li, Xiao-Kang Li, Hanqi Li, Fugen Li, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zizhuo Li, Zhuorong Li, X-H Li, Lan-Juan Li, Xianrui Li, Dong Sheng Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Xiaoman Li, Bing-Heng Li, Huanqiu Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Jinhui Li, Zhifei Li, Ying Li, Jianlin Li, Yanshu Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Jinku Li, Longyu Li, Guiying Li, X B Li, Changgui Li, Zhisheng Li, Cuiling Li, Xuekun Li, Yuguang Li, Wenke Li, Jianguo Li, Jiayi Li, En Li, Ximei Li, Shaoyong Li, Kai-Wen Li, Suwen Li, Peihua Li, Chang-Ping Li, Guangda Li, Yixue Li, Guandu Li, Junfeng Li, Xin-Chang Li, Jieming Li, Yue-Ying Li, Kongdong Li, Chunhui Li, Peiyu Li, Tongyao Li, Lian Li, Linfeng Li, Xinmiao Li, Yuzhe Li, Chenyang Li, Jiacheng Li, Chang-Yan Li, Qifang Li, Xiaohua Li, Vivian Li, Duanxiang Li, Xiaolin Li, Meiting Li, Justin Li, Xue-Er Li, Zhuangzhuang Li, Hongchang Li, Xiaohui Li, Cang Li, Xuepeng Li, Mingjiang Li, Youwei Li, Ronggui Li, Xingwang Li, Tiange Li, Yongjia Li, Dacheng Li, Zongyu Li, Xinmin Li, Luquan Li, Jianyong Li, Shujie Li, Guoxing Li, Zongchao Li, Yanbin Li, Shiliang Li, Jia Li, Haimin Li, Qinrui Li, Sheng-Qing Li, Yiming Li, Lingjie Li, Xiao-Tong Li, Yiwen Li, Tie Li, Baoqi Li, Wei-Bo Li, Leyao Li, Xiaoyi Li, Xiao-Qin Li, Liyan Li, Xiaokun Li, Xinke Li, Ming-Wei Li, Wenfeng Li, Minzhe Li, Jiajing Li, Karen Li, Yanlin Li, Liao-Yuan Li, X Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Li-Na Li, Hengguo Li, An-Qi Li, Xuehua Li, AnHai Li, Hui Li, Chenli Li, Rumei Li, Zhengrui Li, Fangqi Li, Xiaoguang Li, Xian Li, Danjie Li, Yan-Yu Li, Vivian S W Li, Qinqin Li, Lipeng Li, Qinghua Li, Leilei Li, Defu Li, Ranchang Li, Lianyong Li, Amy Li, Zhou Li, Q Li, Haoyu Li, Xiaoyao Li, M-J Li, Jiao-Jiao Li, Rongling Li, Zhu Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Guangqiang Li, Jian'an Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Yu-I Li, Shunhua Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Ziqi Li, Shen Li, Tianjiao Li, Gui-Rong Li, Shufen Li, Yunfeng Li, Yunpeng Li, Yueqi Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Xu Li, Pinghua Li, Shi-Fang Li, Shude Li, Zhibin Li, Yaxiong Li, Zhenli Li, Qing-Fang Li, Rosa J W Li, Yunxiao Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, Zhi Li, Zhankui Li, Zihai Li, Yue-Jia Li, Haihong Li, Peifen Li, Taixu Li, Mingzhou Li, Jiejing Li, Meng-Miao Li, Meiying Li, Chunlian Li, Zhijie Li, Meng Li, Huimin Li, Cun Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Cong Li, Yinghui Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Mengfan Li, Weiling Li, Jie Li, Shiyan Li, Lianbing Li, G Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, Wenjian Li, Jialin Li, He Li, Bichun Li, Hanqin Li, Xiong Bing Li, Wen Lan Li, Qingjie Li, Han Li, Guoge Li, Wen-Wen Li, Keying Li, Yutang Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Hankun Li, Hongling Li, Xiangrui Li, Chaojie Li, Michelle Li, Caolong Li, Zhifan Li, J Li, Zhi-Jian Li, Jianwei Li, Yan-Guang Li, Jiexin Li, Hongyan Li, Ji-Min Li, Zhen-Xi Li, Peipei Li, Guangdi Li, Tian-Yi Li, Xiaxia Li, Yuefeng Li, Nien Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Jieshou Li, Lin Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Mengqing Li, Ben-Shang Li, S L Li, Hong-Lan Li, Ming-Kai Li, Shunqing Li, Xionghao Li, Lan Li, Menglu Li, Huiqing Li, Yanwei Li, Yantao Li, Chien-Te Li, Wenyan Li, Xiaoheng Li, Zeyuan Li, Yongle Li, Ruolin Li, Hongqin Li, Zhenhao Li, Jonathan Z Li, Haying Li, Shao-Dan Li, Muzi Li, Yong-Liang Li, Gen Li, Dong-Ling Li, M Li, Chenwen Li, Jiehan Li, Yong-Jian Li, Le Li, Hongguo Li, Chenxin Li, Yongsen Li, Qingyun Li, Pengyu Li, Si-Wei Li, Ai-Qin Li, Zichao Li, Manru Li, Caili Li, Yingxi Li, Yuqian Li, Guannan Li, Wei-Dong Li, Cien Li, Qingyu Li, Xijing Li, Jingshang Li, Xingyuan Li, Dehua Li, Wenlong Li, Ya-Feng Li, Yanjiao Li, Jia-Huan Li, Yuna Li, Guoxi Li, Xudong Li, Xingfang Li, Shugang Li, Shengli Li, Jisheng Li, Rongyao Li, Xuan Li, Yongze Li, Yongxin Li, Ru Li, Lu Li, Jiangya Li, Yiche Li, Yilang Li, Zhuo-Rong Li, Bingbing Li, Qinglin Li, Runzhi Li, Yunshen Li, Jingchun Li, Qi-Jing Li, Hexin Li, Yanping Li, Zhenyan Li, H J Li, Ji Xia Li, Yu-Ye Li, Meizi Li, Qing-Wei Li, Yuezheng Li, Qiang Li, Hsiao-Hui Li, L I Li, Zhengnan Li, Jianglong Li, Hongzheng Li, Laiqing Li, Ningyang Li, Zhongxia Li, Guangquan Li, Xiaozheng Li, Shun Li, Hui-Jun Li, Guojun Li, Xuefei Li, Senlin Li, Hung Li, Jinping Li, Huili Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, P Li, Hongzhe K Li, Fulun Li, Xiao-Qiu Li, Jiejia Li, Yonghao Li, Mingli Li, Yehong Li, Yi-Yang Li, Zhihui Li, Fujun Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Ni Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Gan Li, Shichao Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Lihong Li, Chun Li, Jianan Li, Wenfang Li, Haixia Li, Sung-Chou Li, Xiangling Li, Lianhong Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Cheng Li, Zhao Li, Kui Li, Tiegang Li, Yunxu Li, Shuang-Ling Li, Zhong Li, Xiao-Long Li, Hung-Yuan Li, Xiaofei Li, Xuanfei Li, Zilin Li, Zhang Li, Jianxin Li, Mingqiang Li, H Li, Xiaojiao Li, Dongliang Li, Chenxiao Li, Yinzhen Li, Hongjia Li, Yunsheng Li, Xiao-Jing Li, Li-Min Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Baichuan Li, Daoyuan Li, Haibo Li, Wenqi Li, Zhenzhe Li, Xiao-Jun Li, Jian-Mei Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Xueling Li, Qiao Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Yike Li, Wanni Li, Yihan Li, Chitao Li, Haiyang Li, Jiayu Li, Xiaobai Li, Junsheng Li, Pingping Li, Mingquan Li, Wen-Ya Li, Suran Li, Yunlun Li, Rongxia Li, Yingqin Li, Yuanfang Li, Guoqin Li, Qiner Li, Huiqin Li, Shanhang Li, Jiafang Li, Han-Bing Li, Chunlin Li, Zongzhe Li, Jisen Li, Yikang Li, Si-Yuan Li, Caihong Li, Hongmin Li, Peng Peng Li, Yajing Li, Guanglu Li, Kenli Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Jian-Jun Li, Dongmin Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Xinxin Li, Jian-Shuang Li, You-Mei Li, Chenglan Li, Dazhi Li, Yubin Li, Beixu Li, Yuhong Li, Di Li, Fengqiao Li, Guiyuan Li, Yanbing Li, Suk-Yee Li, Yuanyuan Li, Shengjie Li, Jufang Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, Minghua Li, Jun Li, Xiyue Li, Tianchang Li, Zhuoran Li, Hongru Li, Shiqi Li, Mei-Ya Li, Wuyan Li, Mingzhe Li, Yi-Ling Li, Yingjian Li, Hongjuan Li, Zhirong Li, Wang Li, Mingyang Li, Weijun Li, Boyang Li, Senmao Li, Cai Li, Mingjie Li, Ling-Jie Li, Hong-Chun Li, Jingcheng Li, Ivan Li, Yaying Li, Mengshi Li, Liqun Li, Manxia Li, Ya Li, Changxian Li, Dan-Ni Li, Wen-Chao Li, Sunan Li, Zhencong Li, Chunqing Li, Jiong Li, Lai K Li, Yanni Li, Daiyue Li, Bingong Li, Xiujuan Li, Huifang Li, Yongsheng Li, Lingling Li, Chunxue Li, Yunlong Li, Xinhua Li, Jianshuang Li, Juanling Li, Minerva X Li, Xinbin Li, Alexander H Li, Xue-jing Li, Ding Li, Yuling Li, Wendeng Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Linyan Li, Yanjun Li, Ming-Yang Li, Shengze Li, Jiequn Li, Zhongding Li, Hewei Li, Da-Jin Li, Jiangui Li, Zhengyang Li, Cyril Li, Xinghui Li, Yuefei Li, Xiao-kun Li, Xinyan Li, Yuanhao Li, Xiaoyun Li, Congcong Li, Ji-Lin Li, Yushan Li, Ping'an Li, Juan Li, Weiping Li, Huan Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Yu-Kun Li, Jiangan Li, Weihai Li, Hsiao-Fen Li, Zhaojin Li, Bingxin Li, Mengjiao Li, Wenjuan Li, Wenyu Li, Chia-Yang Li, Meng-Meng Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Wenlei Li, Xi-Xi Li, Mei-Lan Li, Wenjun Li, Haiyan Li, Jiaxin Li, Ming D Li, Chenguang Li, Ruyue Li, Xujun Li, Chi-Ming Li, Dandan Li, Xiaolian Li, Yi-Ning Li, Yunan Li, Zechuan Li, Jiazhou Li, Sherly X Li, Zhijun Li, Wanling Li, Ya-Ge Li, Yinyan Li, Rujia Li, Guangli Li, Qijun Li, Zhiwei Li, Lixia Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Xiaohan Li, Wan-Shan Li, Zhongwen Li, Huijie Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Xuejun Li, Fengxiang Li, Nana Li, Shunwang Li, Chao Li, Yaqing Li, Yaqiao Li, Jingui Li, Bingsheng Li, Huamao Li, Xiankun Li, Jingke Li, Xiaowei Li, Tianyao Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Hai-Yun Li, Haoran Li, Xiaoliang Li, Zhongxian Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Xinjian Li, Jialun Li, Zilu Li, Rui Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Xuyi Li, Binghua Li, Hanjun Li, Yunchu Li, Zhengyao Li, Qihua Li, Jin-Qiu Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, Lin-Feng Li, Xutong Li, Ranwei Li, Kai Li, Ziqing Li, Keanning Li, Wei-Li Li, Yongjin Li, Shuangxiu Li, Chenhao Li, Ling Li, Weizu Li, Deming Li, Peiqin Li, Xiaodong Li, Nanxing Li, Qihang Li, Jianrong Li, Baoguo Li, Zhehui Li, Chenghao Li, Jiuyi Li, Luyao Li, Chun-Xu Li, Desheng Li, Weike Li, Zhixuan Li, Chuanbao Li, Long-Yan Li, Fuyu Li, Chuzhong Li, M D Li, Yuan-Tao Li, Lingzhi Li, Kening Li, Guilan Li, Wanshi Li, Hengtong Li, Ling-Zhi Li, Yifan Li, Ya-Li Li, Xiao-Sa Li, Songyun Li, Xiaoran Li, Kunlin Li, Bolun Li, Linchuan Li, Jiachen Li, Shu-Qi Li, Haibin Li, Huangbao Li, Zehua Li, Guo-Chun Li, Xinli Li, Mengyuan Li, S Li, Wenqing Li, Wenhua Li, Caiyun Li, Congye Li, Xinrui Li, Wensheng Li, Dehai Li, Jiannan Li, Qingshang Li, Guanbin Li, Hanbin Li, Zhiyi Li, Xing Li, Wanwan Li, Jia Li Li, Zhaoyong Li, SuYun Li, Shiyi Li, Wan-Hong Li, Mingke Li, Suchun Li, Xiaoyuan Li, Huanhuan Li, Yanan Li, Zongfang Li, Jiayan Li, Yang Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Dongdong Li, Yimei Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Zhi-qiang Li, Shaojing Li, S S Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Tong Li, Yilong Li, Lihua Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Yanli Li, Zhi-Yuan Li, Hai Li, Jingfeng Li, Kaibin Li, Yuan-Jing Li, Xuefeng Li, Xiaohu Li, Wenjie Li, Ruikai Li, Mengjuan Li, Xiao-Hong Li, Yinglin Li, Yaofu Li, Ren-Ke Li, Qiyong Li, Ruixi Li, Yi Li, Baosheng Li, Zhonglian Li, Mian Li, Yujun Li, Dalin Li, Lixi Li, Jin-Xiu Li, Kun Li, Qizhai Li, Jiwen Li, Pengju Li, Peifeng Li, Zhouhua Li, Ai-Jun Li, Qingqin S Li, Honglei Li, Yueting Li, Guojin Li, Xin-Yue Li, YaJie Li, Dingchen Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, Peining Li, Congjiao Li, Meng-Jun Li, Gaizhen Li, Huilin Li, Songtao Li, Liang Li, Fusheng Li, Huafang Li, Dai Li, Meiyue Li, Nianyu Li, Chenlu Li, Keshen Li, Kechun Li, Yuxin Li, X-L Li, Shaoliang Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Dongye Li, Qun Li, Tianye Li, Cuiguang Li, Zhen Li, Yuan Li, Chunhong Li, F Li, Mengling Li, Kunpeng Li, Jia-Da Li, Zhenghao Li, Chun-Bo Li, Zhantao Li, Baoqing Li, Pu Li, Xinle Li, Xingli Li, Bingkun Li, Nien-Chi Li, Wuguo Li, Bing-Hui Li, Tiewei Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Shikang Li, Wei-Yang Li, Rong Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Shishi Li, Hong-Lian Li, Bei-Bei Li, Haitong Li, Xiumei Li, Melody M H Li, Ruibing Li, Yuli Li, Qingfang Li, Peibo Li, Qibing Li, Huanjun Li, Heng Li, Wende Li, Chung-Hao Li, Liuzheng Li, Zhanjun Li, Yifei Li, Tianming Li, Chang-Sheng Li, Xiao-Na Li, Tianyou Li, Jipeng Li, Xidan Li, Yixing Li, Chengcheng Li, Yu-Jin Li, Baoting Li, Longxuan Li, Huiyou Li, Ka Wan Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Yu-Hao Li, Gui-xing Li, Shunle Li, Shilin Li, Niu Li, Siyue Li, Diyan Li, Mengyao Li, Shili Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Meiqing Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Yinhao Li, Zonglin Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, Xiaoqin Li, L P Li, Runbing Li, Chunmei Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Yanmin Li, Ji-Cheng Li, Jingyi Li, Yuxiang Li, Haolong Li, Hao-Fei Li, Xuanzheng Li, Peng-li Li, Quan Li, Yining Li, Xue-Ying Li, Xiurong Li, Haiyu Li, Huijuan Li, Xu-Zhao Li, Yunze Li, Yanzhong Li, Guohui Li, Kainan Li, Yongzhe Li, Qingfeng Li, Xiaoyan Li, Tianyi Li, Nanlong Li, Ping Li, Xu-Bo Li, Fangzhou Li, Nien-Chen Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Yuanchuang Li, Biao Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Hong-Yan Li, Shengbiao Li, Yue-Rui Li, Ruidong Li, Dalei Li, Zongjun Li, Y M Li, Changqing Li, Hanting Li, Dong-Jie Li, Sijie Li, Dengxiong Li, Xiaomin Li, Meilan Li, D C Li, Andrew C Li, Jianye Li, Yi-Shuan J Li, Tinghao Li, Qiuyan Li, Zhouxiang Li, Tingguang Li, Yun-tian Li, Jianliang Li, Xiangyang Li, Guangzhao Li, Chunjie Li, Yixi Li, Shuyu Dan Li, S A Li, Tianfeng Li, Anna Fen-Yau Li, Minghui Li, Jiangfeng Li, Jinjie Li, Liming Li, Jie-Pin Li, Junyi Li, Kaiyi Li, Wenqun Li, Dongtao Li, Fengyuan Li, Guixia Li, Yinan Li, Aoxi Li, Chenxi Li, Zuo-Lin Li, Yuanjing Li, Zhengwei Li, Linqi Li, Bingjue Li, Xixi Li, Binghu Li, Yan-Chun Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Zhenguang Li, Xiaotian Li, Jia-Ru Li, Shuhui Li, Pei-Qin Li, Shu-Hong Li, Chun-Xiao Li, Shuyue Li, Mengying Li, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Duo Li, Yaxian Li, Dali Li, Zhiming Li, Xuemei Li, Hongxia Li, Yongting Li, Xueting Li, Danyang Li, Zhenjun Li, Ren Li, Tiandong Li, Hongye Li, Lanfang Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, Qiji Li, W J Li, Zhipeng Li, Zhijia Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaobo Li, Xiaoting Li, Ruotai Li, Meijia Li, Yaojia Li, Shujiao Li, Xiao-Yao Li, Kun-Ping Li, Weirong Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Yandong Li, Runzhao Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Yanxin Li, Yingjun Li, Xiufeng Li, Xiaohuan Li, Ying-Qin Li, Boya Li, Lamei Li, O Li, Fan Li, Jun Z Li, Suheng Li, Joyce Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Junru Li, Zhiqiang Li, Hecheng Li, Jiangchao Li, Changkai Li, Yueping Li, Haifeng Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Xuanxuan Li, Rui-Jún Eveline Li, Bing-Mei Li, Yunman Li, Chaoqian Li, Shuhua Li, Yu-Cheng Li, Chunying Li, Yirun Li, Haomiao Li, Leipeng Li, Weiheng Li, Qianqian Li, Baizhou Li, Zhengliang Li, YiQing Li, Han-Ru Li, Sheng Li, Wei-Qin Li, Weijie Li, Guoyin Li, Yaqiang Li, Qingxian Li, Zongyi Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Yongpeng Li, Chengjun Li, Keke Li, Jianbin Li, Chanyuan Li, Shiying Li, Jianxiong Li, Huaying Li, Ji Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Shaomin Li, Heying Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Jiahao Li, Hanxiao Li, Jiansheng Li, Shuying Li, Shibao Li, Pengjie Li, Kunlong Li, Xiaomei Li, Ruijin Li
articles
Yingying Qiu, Xinjun Wei, Jian Cao +9 more · 2025 · Reproductive sciences (Thousand Oaks, Calif.) · Springer · added 2026-04-24
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver Show more
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver of AM progression. In this study, we investigated the role and underlying mechanisms of endometrial mesenchymal stem cell (eMSC)-derived exosomes in regulating AAM polarization and the subsequent EMT of endometrial epithelial cells (EECs). In vitro coculture studies revealed that AM eutopic eMSCs markedly induced M2 macrophage polarization via exosomes and promoted EMT of EECs. Differentially expressed microRNAs (DE-miRNAs) between exosomes derived from normal eMSCs (N-eMSCs) and AM eutopic eMSCs (A-eMSCs) were identified using miRNA sequencing and miR-4669 was found to be the most significantly upregulated miRNA. Internalization of exosomal miR-4669 by macrophages induced their polarization toward the M2 phenotype and promoted the EMT of EECs. Mechanistic analysis using luciferase assay, mRNA sequencing, and rescue experiments revealed that miR-4669 induced M2 macrophage polarization via downregulation of DUSP6 and activation of MAPK/ERK signaling. The polarized M2 macrophages promoted the EMT of ISK cells via TGF-β1 secretion. In an AM xenograft mouse model, miR-4669 depletion inhibited AM progression by targeting the DUSP6/ERK1/2 pathway in macrophages. Overall, AM A-eMSC-derived exosomal miR-4669 facilitates M2 macrophage polarization by targeting the DUSP6/ERK signaling pathway, thereby promoting EMT of EECs via TGF-β1 secretion. These findings open avenues for developing novel preventive and therapeutic strategies for AM. Show less
📄 PDF DOI: 10.1007/s43032-025-01944-1
DUSP6
Xianqi Shen, Zijian Li, Yuchuan Shi +5 more · 2025 · Translational andrology and urology · added 2026-04-24
Poly(A) binding protein cytoplasmic 4 (PABPC4) has been regarded as a prognostic marker in many malignancies. In this study, we evaluated PABPC4 expression at both messenger ribonucleic acid (mRNA) an Show more
Poly(A) binding protein cytoplasmic 4 (PABPC4) has been regarded as a prognostic marker in many malignancies. In this study, we evaluated PABPC4 expression at both messenger ribonucleic acid (mRNA) and protein levels. The prognostic value of PABPC4 in patients with prostate cancer (PCa) was also investigated. The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, our analysis of Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA), and 65 pairs of ribonucleic acid (RNA) sequencing data from our center were employed to detect the expression of PABPC4 in PCa tissues. Tissue microarrays (TMAs) were utilized to detect the expression of the PABPC4 protein, and survival analysis as well as risk factor analysis were conducted. In the 65 pairs of sequencing data, the expression of PABPC4 in tumor tissues was significantly higher than that in paired adjacent tissues (P<0.001), and its expression also presented significant differences among different Gleason groups (P=0.041). In the CPGEA data, the expression of PABPC4 in tumor tissues was significantly higher than that in control tissues (P<0.001), and the expression of PABPC4 in M1 patients was higher than that in M0 patients, although no significant statistical difference was shown (P=0.051). In the TCGA data, the expression of PABPC4 in tumor tissues was significantly higher than that in control tissues (P<0.001). The expression of pT3/4 (pathological tumor stage 3 and pathological tumor stage 4) in high-stage tumor tissues was significantly higher than that in low-stage tumor tissues (pT2) (P=0.02), the expression of pT3/4 in GSE21034 and GSE32571 tumor tissues was significantly higher than that in control tissues (P<0.001), and the expression of pT3/4 in primary tumor tissues was higher than that in metastatic tissues in GSE6752 (P<0.001). The TCGA data revealed that patients with high PABPC4 expression had poorer overall survival (OS) than those with low PABPC4 expression (P=0.04), and the TMA data indicated that patients with high PABPC4 expression had a poor prognosis (P=0.004). Our study demonstrated that PABPC4 was overexpressed at mRNA and protein levels in PCa. We found that patients with high PABPC4 expression had a shorter biochemical recurrence (BCR)-free survival and OS, showing its value as a prognostic biomarker in patients with PCa. Show less
no PDF DOI: 10.21037/tau-2025-19
PABPC4
Yang Liu, Han-Yan Jin, Meng-Meng Li +6 more · 2025 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report t Show more
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report the fabrication of type II LPLs with enhanced light-responsive efficiency by tailoring the host's functionality for the first time. The functionality of light-responsive metal-organic cage (MOC-RL, constructed from dicopper and responsive ligands) is modified by introducing the second long-chain alkyl ligand, producing MOC-RL-AL as a new host. A spatially hindered solvent based on polyethylene glycol, IL-NTf Show less
no PDF DOI: 10.1002/anie.202501191
LPL
Xi-Xi Li, Pei Shi, Fei-Fei Wu +1 more · 2025 · Discover oncology · Springer · added 2026-04-24
With the sharp increase in the incidence of papillary thyroid carcinoma (PTC), the disease-specific survival rate has not improved significantly. Cholesterol metabolism plays a crucial role in tumor p Show more
With the sharp increase in the incidence of papillary thyroid carcinoma (PTC), the disease-specific survival rate has not improved significantly. Cholesterol metabolism plays a crucial role in tumor proliferation, regulation of tumor immune escape, and tumor drug resistance. However, there are few studies on the role of cholesterol metabolism in the occurrence and development of thyroid cancer (THCA). This study aimed to investigate the predictive value of cholesterol metabolism-related genes (CMRGs) in THCA and the relationship between immune invasion and drug sensitivity. Cholesterol metabolism-related genes we identified from the molecular signatures database, and univariate Cox regression and least absolute shrinkage and selection operator(LASSO) were used to construct a predictive model of cholesterol metabolism-related genes based on the TCGA-THCA dataset. The TCGA dataset was randomly divided into a training group and a validation group to verify the model's predictive value and independent prognostic effect. We then constructed a nomogram and performed enrichment analysis, immune cell infiltration, and drug sensitivity analysis. Finally, TCGA-THCA and GSE33630 datasets were used to detect the expression of signature genes, which was further verified by the HPA database. Six CMRGs (FADS1, NPC2, HSD17B7, ACSL4, APOE, HMGCS2) we identified by univariate Cox and LASSO regression to construct a prognostic model for 155 genes related to cholesterol metabolism. Their prognostic value was confirmed in the validation set, and a highly accurate nomogram was constructed combined with clinical features. We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced. Moreover, through drug sensitivity analysis, we obtained sensitive drugs for different risk groups. The GSE33630 dataset verified the expression of six CMRGs, and the HPA database verified the protein expression of the NPC2 gene. Cholesterol metabolism-related features are a promising biomarker for predicting THCA prognosis and can potentially guide personalized immunization and targeted therapy. Show less
📄 PDF DOI: 10.1007/s12672-025-03483-2
FADS1
Xiangyong Kong, Yanchen Cai, Yuwei Li +1 more · 2025 · Health information science and systems · Springer · added 2026-04-24
Atherosclerotic cardiovascular disease (ASCVD) is a major threat to human life and health, and dyslipidemia with elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor, and i Show more
Atherosclerotic cardiovascular disease (ASCVD) is a major threat to human life and health, and dyslipidemia with elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor, and in the optimal LDL-C scenario, apolipoprotein B (ApoB) has a more predictive value of ASCVD risk. The study is a genome-wide association study (GWAS) based on a European population. A large GWAS dataset for atherosclerotic cardiovascular diseases was targeted, including coronary heart disease (CHD), ischemic stroke (IS), large-artery atherosclerotic stroke (ISL), small-vessel stroke (ISS), and myocardial infarction (MI). Univariate two-sample mendelian randomization (MR) analyses of ApoB and the above cardiovascular diseases were performed separately, and the association was assessed mainly using the inverse variance weighted (IVW) method, with confidence intervals for the superiority ratios set at 95%. In addition, the experiment was supplemented using MR-Egger, weighted model and weighted median (WM). Based on the results of univariate two-sample mendelian randomisation analysis, it was shown that there was a causal relationship between ApoB and CHD (OR = 1.710, 95% CI 1.529-1.912, P = 0.010), ISL (OR = 1.430, 95% CI 1.231-1.661, P = 2.714E-06), ISS (OR = 1.221, 95% CI 1.062-1.405, P = 0.005) were causally related to each other and the disease prevalence ratio was positively correlated with ApoB concentration. This MR analysis demonstrated a causal relationship between ApoB and CHD, ISL, ISS, but not with the risk of developing IS and MI, which further validated the relationship between ApoB and the risk of ASCVD, and contributed to a better understanding of the genetic impact of ApoB on ASCVD, and to a certain extent, could improve the management of ApoB and reduce the prevalence of ASCVD. Show less
no PDF DOI: 10.1007/s13755-024-00323-5
APOB
Xiaoyu Yang, Wenlong Liang, Zhenchu Feng +3 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Polychlorinated biphenyls (PCBs) are environmental pollutants associated with various health issues, including breast cancer. This study investigates potential molecular mechanisms by which PCBs may i Show more
Polychlorinated biphenyls (PCBs) are environmental pollutants associated with various health issues, including breast cancer. This study investigates potential molecular mechanisms by which PCBs may influence breast cancer progression using computational and preliminary experimental approaches. We conducted a differential expression analysis using the TCGA-BRCA dataset. PCBs-related toxicological targets were collected from the Comparative Toxicogenomics Database (CTD). Enrichment and pathway analyses identified candidate biological processes and pathways. Protein-protein interaction (PPI) networks were constructed to identify hub genes. Single-cell expression levels of key targets were analyzed (GSE114727 dataset). Molecular docking predicted binding affinities of PCBs congeners with key targets. Cell experiments assessed gene expression changes upon PCBs exposure. We identified 52 upregulated and 24 downregulated PCBs-related toxicological targets in breast cancer. Enrichment analysis highlighted potential associations with pathways such as PI3K-Akt, MAPK, and HIF-1, including genes like BRCA1, FGFR1, IGF1, AKT1, and EGF. PPI network analysis identified key hub genes like EZH2, EGF, BRCA1, AKT1, IL6, and TNF. Single-cell analysis suggested variable expression of key targets across immune cell types. Molecular docking predicted strong binding affinities of PCB 105 with EZH2 and EGF Our integrated analysis proposes that PCBs exposure may perturb key molecular pathways in breast cancer. Computational findings implicate targets like EZH2 and EGF, while preliminary cell experiments support further investigation. These results highlight a need for mechanistic studies to confirm PCB-induced effects and their therapeutic relevance, underscoring environmental pollutants as potential risk factors in cancer. Show less
📄 PDF DOI: 10.3389/fphar.2025.1604993
FGFR1
Ting He, Jinbo Zhao, Ling Hou +2 more · 2025 · International journal of general medicine · added 2026-04-24
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. Show more
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. The purpose of this research was to construct machine learning (ML) models for identifying undetected CKD in CHD patients. 1786 CHD patients undergoing coronary intervention were retrospectively included. Lasso regression and multifactor logistic regression were used to screen feature variables. Five ML models, ie, logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost), were constructed. Participants were divided into the training set and validation set in a 7:3 ratio. The evaluation metrics included the area under the curve, calibration curve, and decision curve. Totally, 1786 CHD patients were enrolled and split into training (70%) and validation (30%) sets. The prevalence of CKD was 21.8% (390/1786). Multivariate logistic regression analysis showed that men, advanced age, hypertension, diabetes mellitus, history of atrial fibrillation (AF), high Gensini, low hemoglobin, low plateletcrit (PCT), high triglycerides (TG), high lipoprotein(a) (Lp(a)), hyperkalemia, high uric acid to albumin ratio (UAR), high systemic inflammation response index (SIRI), low lymphocyte to monocyte ratio (LMR), and high apolipoprotein B to apolipoprotein A1 (ApoB/ApoA1) ratio were the key clinical and laboratory test indicators of CKD. The XGBoost model performed optimally in the validation set (AUC=0.909, 95% CI 0.881 -0.937). SHapley Additive explanation analysis identified UAR, hypertension, Gensini score, age, and SIRI as the top 5 key features. The XGBoost model constructed on routine clinical data was effective in identifying CKD risk in CHD patients, with UAR as a novel strong predictor. Decision curve analysis confirmed the clinical utility of the model, indicating that it may be used to guide decisions for enhanced monitoring and early intervention over a wide range of risk thresholds. Show less
📄 PDF DOI: 10.2147/IJGM.S558568
APOB
BoWen Li, Dan Shu, Shiguang Pang +7 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
Childhood cancer can disrupt family functioning, increase caregiver psychological distress, and impair caregiver quality of life. While family resilience is crucial for adaptation, most research has f Show more
Childhood cancer can disrupt family functioning, increase caregiver psychological distress, and impair caregiver quality of life. While family resilience is crucial for adaptation, most research has focused on individual-level factors, neglecting heterogeneity and multilevel influences on family resilience. Guided by the Social Ecological Model (SEM), this cross-sectional observational study used latent profile analysis (LPA) to identify distinct profiles of family resilience among caregivers of children with cancer and to explore factors associated with these profiles. Between July 2022 and March 2024, 292 caregivers were recruited. Family resilience was measured using the Family Resilience Assessment Scale. LPA was employed to identify resilience profiles, and binary logistic regression was used to explore influencing factors. Two latent profiles were identified: the Low Resources-Low Positivity profile (86%) and the High Internal Resilience profile (14%). The Low Resource-Low Positivity profile demonstrated generally lower scores, especially in utilizing social and economic resources and maintaining a positive outlook. The High Internal Resilience profile showed higher scores across all family resilience dimensions, particularly in communication/problem solving, positive outlook, and meaning-making, while the use of external social and economic resources remained relatively lower. Univariate analysis showed significant differences between profiles in residence, number of siblings, caregiver education, individual resilience, social support, caregivers' physical and psychological well-being and child communication (caregiver-reported). Binary logistic regression identified having more than one child (OR = 3.184, 95% CI: 1.437 ~ 7.057, P = 0.004) and higher individual resilience (OR = 1.095, 95% CI: 1.028 ~ 1.165, P = 0.005) as significant predictors of High Internal Resilience profile. This study identified two distinct family resilience profiles among caregivers of children with cancer. Limited use of social and economic resources was common, while caregiver resilience and having multiple children predicted higher family resilience. Interventions should enhance caregiver coping capacity, support one-child families through peer and family programs, and improve access to social support, flexible employment, and affordable care to strengthen family resilience. Not applicable. Show less
📄 PDF DOI: 10.1186/s12912-025-03444-8
LPA
Xingyu Fu, Ao Yin, Chao Wang +5 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous Show more
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous cap is ruptured, and atherosclerotic plaques become vulnerable. Efferocytosis is an important method for recognizing and eliminating apoptotic cells. Nevertheless, the specific effect of efferocytosis on atherosclerosis remains uncertain. This study aimed to identify and verify the relevant characteristics of efferocytosis for detecting atherosclerosis. The data of gene expression patterns of atherosclerosis were sourced from the Gene Expression Omnibus (GEO) database, and the differential expression analyses of efferocytosis-related genes (EFRGs) were performed between the atherosclerosis samples and the control samples. Subsequently, protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis were performed to reveal the interaction between molecules as well as their pathways. Machine learning (ML) was employed to determine hub genes to construct a clinical prediction model. At the same time, immune infiltration, single-cell transcriptome analysis, and cell experiments were conducted in both atherosclerosis and control samples to provide a reference for the immune cell landscape and the cell heterogeneity under this condition. The study revealed that 14 genes were closely related to efferocytosis in atherosclerosis. Among them, an ML model was used to screen 5 potential diagnostic biomarkers, including tumor necrosis factor (TNF), apolipoprotein E (ApoE), neutrophil cytosolic factor 1 (NCF1), triggering receptor expressed on myeloid cells 2 (TREM2), and chitinase-3 like-protein-1 (CHI3L1). Subsequent external validation indicated that, except for TNF, the other 4 genes were all upregulated. From the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, those 5 genes were all significantly associated with various immune cells. Further single-cell RNA sequencing (scRNA-seq) analysis demonstrated that those 5 genes were selectively upregulated in the macrophages of atherosclerosis lesions, which was supported by mRNA levels in cell experiments. This study clarified the association between atherosclerosis and efferocytosis, and established an effective diagnostic model. Moreover, potential treatment targets for atherosclerosis were identified, offering new insights into the potential mechanism of atherosclerosis. Show less
📄 PDF DOI: 10.1186/s40001-025-03669-y
APOE
Guile Zhao, Yike Li, Hongling Li +7 more · 2025 · Computational and structural biotechnology journal · Elsevier · added 2026-04-24
The malignant transformation of odontogenic keratocysts (OKC) into cancerous odontogenic keratocysts (COKC) is exceedingly rare, and its mechanisms remain poorly understood. Studies exploring the cell Show more
The malignant transformation of odontogenic keratocysts (OKC) into cancerous odontogenic keratocysts (COKC) is exceedingly rare, and its mechanisms remain poorly understood. Studies exploring the cellular heterogeneity, molecular pathways, and clinical features of COKC are limited. In this study, we performed single-cell RNA sequencing (scRNA-seq) on three COKC samples and integrated the data with a public OKC dataset, identifying 22,509 single cells. Two COKC-specific epithelial subpopulations, Basal-C0-EXT1 and Basal-C3-HIST1H3B, were identified. These subpopulations exhibited enhanced stemness and invasive potential, respectively, suggesting their roles as key drivers of OKC carcinogenesis. Fibroblasts underwent phenotypic transitions, particularly from inflammation-associated fibroblasts (IFBs) to myofibroblasts (MFBs). Similarly, macrophage phenotypic transformation may also play a role in OKC carcinogenesis. Clinical observations of severe lesion-area pain in COKC patients suggest potential neuroinvasiveness, Supported by single-cell transcriptomic data, imaging findings, and histopathological evidence. A review of clinical data revealed that none of the COKC patients exhibited cervical lymph node metastasis. Single-cell transcriptomics suggests that this phenomenon may be associated with an active immune microenvironment in COKC, reduced epithelial-mesenchymal transition (EMT) activity, lower VEGFC expression, and upregulated MAST4 expression as a potential regulator of lymphatic metastasis. In conclusion, COKC exhibits distinct molecular, cellular, and clinical characteristics compared to OKC, featuring potent neuroinvasiveness and low lymph node metastatic potential. These findings provide important insights into the mechanisms underlying COKC development and may guide novel diagnostic and therapeutic strategies. Show less
📄 PDF DOI: 10.1016/j.csbj.2025.03.027
EXT1
Ning Wei, Lulu Hu, Jian Li +1 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysi Show more
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysis (LPA) and Association Rule Mining (ARM) to identify distinct sleep quality subgroups and uncover key factor combinations, thereby informing targeted intervention strategies. A total of 1,686 nurses from 123 hospitals in Shandong Province were recruited through multistage stratified sampling. LPA was used to classify participants based on seven sleep dimensions from the Pittsburgh Sleep Quality Index (PSQI), while ARM was applied to identify frequent itemsets of sleep disorder triggers. Key influencing factors were further examined using univariate analysis and multivariate logistic regression. Three latent sleep profiles were identified: high (63.11%), moderate (34.10%), and low (2.79%) sleep quality. The low-sleep subgroup was characterized by higher proportions of being unmarried/divorced (42.55%), low monthly income (≤ 3,000 CNY, 42.55%), non-permanent employment (76.60%), and severe psychological distress (44.68%). In contrast, the high-sleep subgroup featured higher rates of being married (85.62%), moderate income (3,001–7,000 CNY, 73.03%), and low psychological distress (51.32%). Key determinants included marital status (OR = 2.153/2.252), income (OR = 9.098), employment type (OR = 1.475), and psychological state (OR = 0.060–0.555). ARM revealed distinct risk combinations: “low income + non-permanent employment” (lift = 3.895) for the low-sleep group; “married + moderate income + non-permanent employment + patient conflict” for the moderate group; and “high income + low psychological distress” buffering night-shift effects in the high-sleep group. By integrating LPA and ARM, this study reveals the multidimensional heterogeneity and interactive mechanisms underlying clinical nurses’ sleep quality. The findings support a stratified intervention framework combining institutional safeguards with precision strategies to enhance sleep health management in nursing populations. Show less
📄 PDF DOI: 10.1186/s12912-025-04026-4
LPA
Hui Yan, Rui Wang, Suryavathi Viswanadhapalli +35 more · 2025 · Science advances · Science · added 2026-04-24
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined r Show more
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined receptor signals, and assessed their regulatory capacities and specificities through in silico analysis of ligand-receptor interactions. Consequently, we identified a B cell subset that expressed cytokine interleukin-27 (IL-27) and chemokine CXCL10. Through the IL-27-IL-27 receptor interaction, these IL-27/CXCL10-producing B cells targeted CD40-activated B cells in vitro and, upon induction by immunization and viral infection, optimized antibody responses and antiviral immunity in vivo. Also present in breast cancer tumors and retained there through CXCL10-CXCR3 interaction-mediated self-targeting, these cells promoted B cell PD-L1 expression and immune evasion. Mechanistically, Show less
📄 PDF DOI: 10.1126/sciadv.adx9917
IL27
Xiaobin Mai, Le Wang, Juan Tu +13 more · 2025 · Genes & diseases · Elsevier · added 2026-04-24
📄 PDF DOI: 10.1016/j.gendis.2025.101681
ANGPTL4
Hongzhi Li, Guangming Li, Xian Gao +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, c Show more
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, clinical information and mutation data of LUAD patients collected from the TCGA and GEO database, we obtained 102 endotheliocyte senescence-related genes. The "ConsensusClusterPlus" R package was employed for unsupervised cluster analysis, and the "limma" was used for the differentially expressed gene (DEG) analysis. A prognosis model was created by univariate and multivariate Cox regression analysis combined with Lasso regression utilizing the "survival" and "glmnet" packages. KM survival and receiver operator characteristic curve analyses were conducted applying the "survival" and "timeROC" packages. "MCPcounter" package was used for immune infiltration analysis. Immunotherapy response analysis was performed based on the IMvigor210 and GSE78220 cohort, and drug sensitivity was predicted by the "pRRophetic" package. Cell invasion and migration were tested by carrying out Transwell and wound healing assays. According to the results, a total of 32 genes related to endotheliocyte senescence were screened to assign patients into C1 and C2 subtypes. The C2 subtype showed a significantly worse prognosis and an overall higher somatic mutation frequency, which was associated with increased activation of cancer pathways, including Myc_targets2 and angiogenesis. Then, based on the DEGs between the two subtypes, we constructed a five-gene RiskScore model with a strong classification effectiveness for short- and long-term OS prediction. High- and low-risk groups of LUAD patients were classified by the RiskScore. High-risk patients, characterized by lower immune infiltration, had poorer outcomes in both training and validation datasets. The RiskScore was associated with the immunotherapy response in LUAD. Finally, we found that potential drugs such as Cisplatin can benefit high-risk LUAD patients. In-vitro experiments demonstrated that silencing of Angiopoietin-like 4 (ANGPTL4), Gap Junction Protein Beta 3 (GJB3), Family with sequence similarity 83-member A (FAM83A), and Anillin (ANLN) reduced the number of invasive cells and the wound healing rate, while silencing of solute carrier family 34 member 2 (SLC34A2) had the opposite effect. This study, collectively speaking, developed a prognosis model with senescence signature genes to facilitate the diagnosis and treatment of LUAD. Show less
📄 PDF DOI: 10.1038/s41598-025-95551-4
ANGPTL4
Fiza Javed, Robert A Hegele, Abhimanyu Garg +6 more · 2025 · Journal of clinical lipidology · Elsevier · added 2026-04-24
Familial chylomicronemia syndrome (FCS) is a rare Mendelian autosomal recessive disorder (MIM 238600) characterized by extreme and sustained hypertriglyceridemia due to profound reduction of lipoprote Show more
Familial chylomicronemia syndrome (FCS) is a rare Mendelian autosomal recessive disorder (MIM 238600) characterized by extreme and sustained hypertriglyceridemia due to profound reduction of lipoprotein lipase (LPL) activity. This expert opinion statement synthesizes current knowledge on the definition, pathophysiology, genetics, prevalence, diagnosis, and management of FCS. FCS typically manifests at a young age with persistent severe hypertriglyceridemia-defined as ≥10 mmol/L (≥885 mg/dL), or ≥1000 mg/dL (≥11.2 mmol/L) depending on region and whether Systeme International (SI) units are utilized-in the absence of secondary factors, resistance to conventional lipid-lowering therapies, and a high lifetime risk of acute pancreatitis. It is caused by biallelic pathogenic variants in the LPL gene encoding LPL, or 1 of 4 other related genes that encode proteins that interact with LPL. Affected individuals require a strict, lifelong very low-fat diet with <15% of energy from fat. Emerging therapies inhibiting apolipoprotein C-III show promise in reducing serum triglycerides and pancreatitis risk in patients with FCS. A multidisciplinary approach, encompassing dietary management, pharmacotherapy, and patient education, is pivotal in mitigating the significant morbidity associated with FCS. Show less
no PDF DOI: 10.1016/j.jacl.2025.03.013
LPL
Ni Wang, Yanan Xu, Jiahui Li +7 more · 2025 · Journal of microbiology and biotechnology · added 2026-04-24
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metaboli Show more
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metabolism disorders. Studies have shown that the herb "Gualou-Xiebai" (GLXB) can effectively regulate the blood lipid levels of ApoE Show less
📄 PDF DOI: 10.4014/jmb.2510.10023
APOE
Biren Dave, Mikayla Machado, Robert Siddaway +13 more · 2025 · JCO precision oncology · added 2026-04-24
CNS tumors are a significant cause of death in the adolescent and young adult (AYA; age 15-39 years) population; however, these patients often lack standardized treatments. In Canada, we have establis Show more
CNS tumors are a significant cause of death in the adolescent and young adult (AYA; age 15-39 years) population; however, these patients often lack standardized treatments. In Canada, we have established national multidisciplinary virtual AYA CNS tumor board rounds (national rounds) to improve and standardize care. From November 2021 to June 2024, 185 AYA patients with CNS tumors were presented from centers nationwide, including 138 patients with glioma. Before case presentation, 5.1% of patients with glioma were taking targeted agents or were enrolled in clinical trials. However, after national rounds, 72.6% of patients with pediatric-type glioma and 45.9% of patients with adult-type glioma were recommended clinical trials and/or targeted agents. Among the 44 patients with glioma who had received radiation therapy before national rounds, only 14 were recommended further radiation. Cumulatively, 68.9% of patients analyzed received a treatment recommendation that represented a change in clinical management compared with their previous treatments. Concurrently, we performed molecular review of 174 AYA CNS tumors during the study time frame. Using TruSight, we identified gene fusions involving Our results suggest that national rounds with centralized molecular review can direct AYA patients with CNS tumors toward targeted agents and clinical trials, while deferring radiation therapy. Taken together, our work details an ongoing effort to improve and standardize care of AYA patients with CNS tumors in Canada. Show less
📄 PDF DOI: 10.1200/PO-25-00557
FGFR1
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Kang-Chih Fan, Szu-Chi Chen, I-Weng Yen +7 more · 2025 · Archives of medical science : AMS · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANG Show more
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANGPTL4 levels are observed in diabetic and obese individuals. However, the potential link between ANGPTL4 and diabetes- or obesity-related complications remains uncertain. This study aimed to explore whether plasma ANGPTL4 level could serve as a predictor of cancer mortality, cardiovascular mortality, and all-cause mortality in a community-based cohort. A community-based cohort study was conducted, where fasting plasma ANGPTL4 concentrations were measured at baseline, and vital status was ascertained through linkage with the National Health Insurance Research Database in Taiwan. During a 10.46-year follow-up period, 29 (2.49%) of the 1163 participants died. Subjects within the highest tertile of plasma ANGPTL4 levels exhibited the lowest survival rate. In unadjusted models, plasma ANGPTL4 significantly predicted all-cause mortality, cancer mortality, and cardiovascular or cancer-related mortality. Upon adjustment for confounders including age, sex, smoking, body mass index (BMI), hypertension, diabetes mellitus (DM), and renal function, each standard deviation increase in plasma ANGPTL4 was associated with HRs of 1.35 (95% CI: 1.01-1.80, Plasma ANGPTL4 emerges as a promising biomarker capable of predicting 10-year mortality and enhancing risk prediction beyond established risk factors. Show less
📄 PDF DOI: 10.5114/aoms/189504
ANGPTL4
Xinling Zhang, Dongang Liu, Yuting Qiu +7 more · 2025 · Metabolites · MDPI · added 2026-04-24
Angiopoietin-like proteins (ANGPTLs) represent a family of secreted glycoproteins that are extensively expressed in vivo and are integral to various pathophysiological processes, including glucose and Show more
Angiopoietin-like proteins (ANGPTLs) represent a family of secreted glycoproteins that are extensively expressed in vivo and are integral to various pathophysiological processes, including glucose and lipid metabolism, stem cell proliferation, local inflammation, vascular permeability, and angiogenesis. Particularly interesting is ANGPTL4, which has been identified as a significant factor in the development and progression of diabetic retinopathy (DR), thus becoming a central focus of DR research. ANGPTLs modulate metabolic pathways, enhance vascular permeability, and facilitate pathological angiogenesis, in addition to causing intraocular inflammation. As promising molecular targets, ANGPTLs not only serve as biomarkers for predicting the onset and progression of DR but also present therapeutic potential through antibody-based interventions. This paper discusses the pathogenesis of DR and the potential applications of ANGPTLs in early diagnosis and targeted therapy. It provides references for advancing precision diagnosis and personalized treatment strategies through more profound ANGPTLs research in the future. Show less
📄 PDF DOI: 10.3390/metabo15060352
ANGPTL4
Yushan Zhou, Yuxuan Zhang, Yanli Li +3 more · 2025 · In vitro cellular & developmental biology. Animal · Springer · added 2026-04-24
Interleukin-27 (IL-27) is a cytokine that is reported to be highly expressed in the peripheral blood of patients with pulmonary tuberculosis (PTB). IL-27-mediated signaling pathways, which exhibit ant Show more
Interleukin-27 (IL-27) is a cytokine that is reported to be highly expressed in the peripheral blood of patients with pulmonary tuberculosis (PTB). IL-27-mediated signaling pathways, which exhibit anti- Mycobacterium tuberculosis (Mtb) properties, have also been demonstrated in macrophages infected with Mtb. However, the exact mechanism remains unclear. This study aimed to clarify the potential molecular mechanisms through which IL-27 enhances macrophage resistance to Mtb infection. Both normal and PTB patients provided bronchoalveolar lavage fluid (BALF). Peripheral blood mononuclear cells (PBMCs) were isolated from healthy individuals and stimulated with 50 ng/mL macrophage-colony stimulating factor (M-CSF) to obtain monocyte-derived macrophages (MDMs). Using 100 ng/mL phorbol 12-myristate 13-acetate (PMA), THP-1 cells were induced to differentiate into THP-1-derived macrophage-like cells (TDMs). Both MDMs and TDMs were subsequently infected with the Mtb strain H37Rv and treated with 50 ng/mL IL-27 prior to infection. The damage and inflammation of macrophages were examined using flow cytometry, enzyme-linked immunosorbent assay (ELISA), and Western blotting. Patients with PTB had elevated levels of IL-27 in their BALF. Preconditioning with IL-27 was shown to reduce H37Rv-induced MDMs and TDMs apoptosis while also decreasing the levels of Cleaved Caspase-3, Bax and the proinflammatory cytokines TNF-α, IL-1β, and IL-6, promoting the expression of Bcl-2 and the anti-inflammatory factors IL-10 and IL-4. Silencing of the IL-27 receptor IL-27Ra increased macrophage damage and inflammation triggered by H37Rv. Mechanistically, IL-27 activates autophagy by inhibiting TLR4/NF-κB signaling and activating the PI3K/AKT signaling pathway, thereby inhibiting H37Rv-induced macrophage apoptosis and the inflammatory response. Our study suggests that IL-27 alleviates H37Rv-induced macrophage injury and the inflammatory response by activating autophagy and that IL-27 may be a new target for the treatment of PTB. Show less
📄 PDF DOI: 10.1007/s11626-024-00989-x
IL27
Xiao Li, Xianglong Huang, Keyan Song +5 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Show more
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Fritillariae Thunbergii Bulbus, Leonuri Herba, and Forsythiae Fructus, has shown efficacy in treating cardiovascular diseases, although its mechanisms are unclear. This study aimed to explore the protective effects of QRSJF against atherosclerosis and the mechanisms involved. The composition of QRSJF was analyzed using Ultra Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry. An 8-week high-fat diet (HFD)-induced atherosclerosis model was established in ApoE Both low- and high-dose QRSJF effectively attenuated dyslipidemia and decreased serum inflammatory cytokine levels in HFD-fed ApoE QRSJF improves dyslipidemia and reduces atherosclerotic plaque in ApoE Show less
no PDF DOI: 10.1016/j.phymed.2025.156691
NR1H3
Shawn C Chafe, Kui Zhai, Nikoo Aghaei +37 more · 2025 · Science translational medicine · Science · added 2026-04-24
Brain metastasis occurs in up to 40% of patients with non-small cell lung cancer (NSCLC). Considerable genomic heterogeneity exists between the primary lung tumor and respective brain metastasis; howe Show more
Brain metastasis occurs in up to 40% of patients with non-small cell lung cancer (NSCLC). Considerable genomic heterogeneity exists between the primary lung tumor and respective brain metastasis; however, the identity of the genes capable of driving brain metastasis is incompletely understood. Here, we carried out an in vivo genome-wide CRISPR activation screen to identify molecular drivers of brain metastasis from an orthotopic xenograft model derived from a patient with NSCLC. We found that activating expression of the Alzheimer's disease-associated beta-secretase 1 (BACE1) led to a substantial increase in brain metastases. Furthermore, genetic and pharmacological inhibition of BACE1 blocked NSCLC brain metastasis. Mechanistically, we identified that BACE1 acts through epidermal growth factor receptor to drive this metastatic phenotype. Together, our data highlight the power of in vivo CRISPR activation screening to unveil molecular drivers and potential therapeutic targets of NSCLC brain metastasis. Show less
📄 PDF DOI: 10.1126/scitranslmed.adu2459
BACE1
Yuling Yang, Yingyan Liu, Limei Zhong +5 more · 2025 · Scientific reports · Nature · added 2026-04-24
Neonatal necrotizing enterocolitis (NEC) is a life-threatening gastrointestinal disease of premature infants, characterized by immune dysregulation and compromised intestinal barrier integrity. Interl Show more
Neonatal necrotizing enterocolitis (NEC) is a life-threatening gastrointestinal disease of premature infants, characterized by immune dysregulation and compromised intestinal barrier integrity. Interleukin-27 receptor α (IL-27Ra), a critical component of the JAK-STAT signaling pathway, exhibits dual pro- and anti-inflammatory roles in various inflammatory conditions. However, its role in NEC pathogenesis remains unclear. To elucidate the functional role of IL-27Ra in NEC development and assess its potential as a therapeutic target. A multi-tiered approach was employed, including integrative analysis of clinical NEC specimens by single-cell and bulk RNA sequencing, and a neonatal mouse NEC model. NEC was induced in mice via hyperosmolar formula feeding combined with LPS gavage, intermittent hypoxia, and cold stress. Additional experiments included immunofluorescence staining for IL-27Ra, cytokine profiling (ELISA, quantitative real-time PCR (qPCR)), use of IL-27Ra knockout (IL-27Ra Show less
📄 PDF DOI: 10.1038/s41598-025-26899-w
IL27
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
Wenxiu Wang, Rui Li, Zimin Song +4 more · 2025 · JAMA cardiology · added 2026-04-24
Despite substantial progress in low-density lipoprotein cholesterol (LDL-C)-lowering strategies, residual cardiovascular risk remains. Apolipoprotein C3 (APOC3) has emerged as a novel target for lower Show more
Despite substantial progress in low-density lipoprotein cholesterol (LDL-C)-lowering strategies, residual cardiovascular risk remains. Apolipoprotein C3 (APOC3) has emerged as a novel target for lowering triglycerides. Multiple clinical trials of small-interfering RNA therapeutics targeting APOC3 are currently underway. To investigate whether genetically predicted lower APOC3 is associated with a reduction in cardiovascular risk and if the combined exposure to APOC3 and LDL-C-lowering variants is associated with a reduction in the risk of coronary heart disease (CHD). This was a population-based genetic association study with 2 × 2 factorial mendelian randomization. Included were participants of European ancestry in the UK Biobank. Data were analyzed from November 2023 to July 2024. Genetic scores were constructed to mimic the effects of APOC3, 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), and proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors. Plasma lipid and lipoprotein levels, CHD, and type 2 diabetes (T2D). This study included 401 548 UK Biobank participants (mean [SD] age, 56.9 [8.0] years; 216 901 female [54.0%]). Genetically predicted lower APOC3 was associated with a lower risk of CHD (odds ratio [OR], 0.96; 95% CI, 0.93-0.98) and T2D (0.97; 95% CI, 0.95-0.99). Genetically lower APOC3 and PCSK9 were associated with a similar magnitude of risk reduction in CHD per 10-mg/dL decrease in apolipoprotein B (ApoB) level (APOC3: 0.70; 95% CI, 0.59-0.83; PCSK9: 0.71; 95% CI, 0.65-0.77). Combined exposure to genetically lower APOC3 and PCSK9 was associated with an additive lower risk of CHD (APOC3: 0.96; 95% CI, 0.92-0.99; PCSK9: 0.93; 95% CI, 0.90-0.97; combined: 0.90; 95% CI, 0.86-0.93). Genetically lower HMGCR was also associated with a lower risk of CHD, and the risk was further reduced when combined with APOC3 (0.93; 95% CI, 0.90-0.97). Genetically predicted lower APOC3 was associated with a reduced risk of CHD that is comparable with that associated with lower PCSK9 per unit decrease in ApoB. Combined exposure to APOC3 and LDL-C-lowering variants was associated with an additive reduction in CHD risk. Future studies are warranted to investigate the therapeutic potential of these combined therapies, particularly among high-risk patients who cannot achieve therapeutic targets with existing lipid-lowering therapies. Show less
no PDF DOI: 10.1001/jamacardio.2025.0195
APOB
Long Xu, Yuanyuan Zhao, Shuxi Song +3 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor micro Show more
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor microenvironment (TME). Neutrophil extracellular traps (NETs) and oxidative stress play critical roles in tumor progression: NETs promote tumor cell adhesion, migration, and immune suppression, while oxidative stress induces DNA damage and activates pro-tumor signaling pathways. Moreover, oxidative stress is an important inducer of NETs, and their crosstalk shapes the LUAD immune microenvironment. However, systematic exploration of LUAD immunotherapeutic response prediction based on NETs and oxidative stress-related genes remains lacking. The gene set related to oxidative stress was obtained from MSigDB. The gene set related to NETs was sourced from relevant literature. Transcriptomic and clinical data were integrated from The Cancer Genome Atlas (TCGA)-LUAD (training set) and GSE31210 (validation set). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to screen gene modules and characteristic scores related to NETs and oxidative stress signatures. Differentially expressed genes (DEGs) were screened, and prognostic model was established using univariate and LASSO Cox regression. Immune infiltration was analyzed using ESTIMATE algorithm, MCP-counter and ssGSEA methods. And we developed a nomogram incorporating clinicopathological features and RiskScore model, and performed drug sensitivity analysis. Finally, the biological role of CPS1 in lung cancer cells was investigated through CCK-8, wound-healing, and Transwell experiments. 22 co-expression modules were screened, among which the brown module showed significant correlations with NETs and oxidative stress signature scores. This module was intersected with DEGs, yielding 624 overlapping genes implicated in immune-relevant pathways (like leukocyte differentiation, neutrophil activation involved in immune response). A prognostic model was established utilizing 8 key genes (ADGRE3, ARHGEF3, CD79A, CLEC7A, CPS1, EPHB2, LARGE2, and OAS3). In the TCGA database, the model demonstrated robust prognostic discrimination (area under the curve (AUC) > 0.6), with high-risk patients exhibiting shorter overall survival (OS) (p < 0.05). Its stability was validated in GSE31210 (AUC > 0.6). The RiskScore showed negative correlations with immune infiltration (like T cells, CD8 T cells, and natural killer cells) as well as immune/stromal scores. A nomogram model combining RiskScore with N staging was developed and validated, demonstrating strong predictive accuracy through calibration and decision curve analyses. High-risk patients were more sensitive to drugs like BI-2536, BMS-509744, and Pyrimethamine. Finally, in vitro tests showed that CPS1 knockdown markedly decreased the viability, migration, and invasion of lung cancer cells. The constructed prognostic model by NETs and oxidative stress-relevant genes effectively predicts LUAD prognosis, correlates with immune microenvironment characteristics, and guides drug sensitivity, providing novel insights for LUAD prognostic assessment and personalized therapy. Show less
📄 PDF DOI: 10.1186/s40001-025-03553-9
CPS1
Bo-Yi Pan Lulji Taraqaz, Yu-Ting Hsu, Ping-Hsuan Tsai +4 more · 2025 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Dyslipidemia exacerbates pancreatic β-cell apoptosis, heightening the risk of type 2 diabetes (T2DM). Kansuinine A (KA), a diterpene from Euphorbia roots, exhibits antiapoptotic properties, suggestive Show more
Dyslipidemia exacerbates pancreatic β-cell apoptosis, heightening the risk of type 2 diabetes (T2DM). Kansuinine A (KA), a diterpene from Euphorbia roots, exhibits antiapoptotic properties, suggestive of its therapeutic potential against T2DM. In this study, we evaluated the protective effects of KA against apolipoprotein C3 (ApoC3)-rich low-density lipoprotein (LDL) (AC3RL)-induced β-cell apoptosis and its underlying mechanism of action. ApoE Show less
no PDF DOI: 10.1016/j.biopha.2025.118066
APOC3
Meng Wang, Zhao Liu, Shuxun Ren +16 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.105894
BCKDK
Da-Ao Nie, Jiangkun Yu, Wenshan Huang +3 more · 2025 · Molecular immunology · Elsevier · added 2026-04-24
As resident immune surveillance cells within the central nervous system (CNS), microglia exert pivotal biological functions in maintaining CNS homeostasis through dynamic modulation of their prolifera Show more
As resident immune surveillance cells within the central nervous system (CNS), microglia exert pivotal biological functions in maintaining CNS homeostasis through dynamic modulation of their proliferative capacity, chemotactic motility, efferocytosis activity, and biphasic secretory mechanisms involving both neuromodulatory factors and pro-inflammatory mediators. These specialized macrophages not only serve as the first line of defense in innate immunity but also orchestrate the regulation of adaptive immune responses; whose functional status directly governs both the physiological integrity of neural circuits and the progression of pathological outcomes. Notably, in neurodegenerative disease models, microglial functional states exhibit pronounced heterogeneity and are tightly regulated by microenvironmental cues. Upon encountering sustained hyperactivation or functional impairment, these cells precipitate a cascade of deleterious events within the neurovascular unit. Building upon these pathophysiological mechanisms, targeted modulation of microglial polarization equilibrium has emerged as a pivotal research focus in developing innovative neuroprotective therapeutic strategies. This review systematically integrates empirical evidence derived from cutting-edge methodologies-including molecular imaging, single-cell multi-omics profiling, and conditional genetic ablation-to mechanistically dissect the dual regulatory roles of microglia in orchestrating neural homeostatic maintenance and driving pathological progression in neurological disorders. Show less
no PDF DOI: 10.1016/j.molimm.2025.07.014
IL27