👤 Li-Na 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, Xiao-Lin Li, Yicun Li, Shunqin Li, Jiajie Li, Zhao-Yang Li, Xinjia Li, K-L Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Youran Li, Peiwu Li, Yongmei Li, Changyu Li, Ran Li, Peilin Li, X Y Li, Chunshan Li, Yixiang Li, Ming Zhou 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, Shengxu Li, Shisheng Li, Sai Li, Guangwen Li, Hua Li, Xiuli Li, Dongmei Li, Yulong Li, Ru-Hao Li, Lanzhou Li, Zhi-Peng Li, Tingsong Li, Binjun Li, Chen Li, Jiayang Li, Yawei 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, W H Li, Sha Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Xiaoqing Li, Jinlin Li, Linke Li, C Y Li, Shuaicheng 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, Hujie Li, Baohong Li, Yue-Ming Li, Shuyuan Li, Zhaohan Li, L Li, Alexander Li, Yuanmei 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, Miao X Li, Zhenshu Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wei Li, Wen-Ying Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Kangli Li, Ming Li, Runwen Li, Wenbo Li, Side Li, Yarong Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Lingxi Li, Chuan-Hai Li, Jiezhen Li, Qiuya Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Qin Li, Zhongyu Li, Deyu Li, Zhen-Yu 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, Junping Li, Xiao Li, PeiQi Li, Xiaobing Li, Naishi Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Shengchao A Li, Pan 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, Xiuqi Li, Peiyun Li, L-Y Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Yuancong Li, Da Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, Demin Li, Haipeng Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Yu Li, Yvonne Li, Minhui Li, Yiwei Li, Jiayuan Li, Xiangzhe Li, Zhichao Li, Siguang Li, Yige Li, Minglun Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chunlan Li, Chiyang Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong 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, Panyuan Li, Mengxuan Li, Gang Li, Ziyu Li, Zhuo Li, Hong-Wen Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Dongnan Li, Huaiyuan Li, Rui-Fang Li, Jianzhong Li, Huaping Li, Ji-Liang 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, Xinyu Li, John Zhong Li, Song-Chao Li, Lujiao 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, Peixin Li, Xueqin Li, Feng-Feng Li, Zu-Ling Li, Jialing Li, Yunjiu Li, Xin 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, Yali Li, Zhaoshui Li, Yu-Hui Li, Wenjing 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, Ning Li, Ruobing Li, Wan-Xin Li, Yanxi Li, Xia Li, Meitao Li, Yongjing 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, Yuqing Li, Zhigang 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, Jutang Li, Mengxia Li, Conglin Li, Qingli Li, Yongxiang Li, Miao Li, Qilong Li, Songlin 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, Yumiao Li, Fengfeng Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Xingye Li, Xiangjun Li, Junxu Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Yuxi Li, Qingyang Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Xingyu Li, Zhaoping 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, Yinghua Li, Mulin Jun Li, Shangjia Li, Yanjie Li, Jingjing Li, Suhong Li, Xinping Li, Siyu Li, Chaoying Li, Juanjuan Li, Qiu Li, Guangzhen Li, Xiangyan Li, Kunlun Li, Shiyun Li, Xiaoyu Li, Yaobo Li, Shiquan Li, Mei Li, Xuewang Li, Xiangdong Li, Jifang Li, Zhenjia Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiaoya Li, Xiao-Li Li, Shan Li, Shitao Li, Lijia Li, Zehan Li, Chunqiong Li, Huiliang Li, Junjun Li, Chenlong Li, Shujin Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Wenxi Li, Weining 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, Man-Zhi Li, Xiancheng Li, Yanmei Li, De-Jun Li, Zhihua Li, Keqing Li, Junxian 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, Minghao Li, Gao-Fei 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, Guisen Li, Yuandong 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, Yongzhen Li, Chun-Quan Li, Weifeng Li, Tao Li, Sichen Li, Wenhui 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, Sujing Li, Yuhua Li, Xuri Li, Wenzhuo Li, Y Li, Deqiang 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, S-C Li, Xi 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, Qian Li, Yaochen Li, Tinghua Li, Zhenfen Li, Wenyang Li, Bohao 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, Xunjia Li, Yanchang Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, En-Min Li, Chunya Li, Zong-Xue 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, Jie-Shou Li, Kaiwei Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Yu-Sheng Li, Junxin Li, Wei-Jun Li, Guoyan Li, Fei-Lin Li, Junjie Li, Nuomin Li, Shanglai Li, Yanyan Li, Shulin Li, Yue Li, Taibo Li, Junqin Li, Zhongcai Li, Xueying Li, Jun-Ru Li, JunBo Li, Zhaobing Li, Xiaoqi Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, Shujing Li, Tsai-Kun Li, Chen-Chen Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Yi-Wen Li, Xiyun Li, Huifeng Li, Shihong Li, Ya-Pei Li, Rulin Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Wenjia Li, Min-Dian Li, Xiatian Li, Ding-Jian Li, Hongwei Li, Danni Li, Xiao-Qiang Li, Yangxue Li, Chengnan Li, Chuanyin Li, Min Li, Yiqiang Li, Pengyang Li, Zhenzhou Li, Kun-Xin Li, Xiawei Li, Binglan Li, Zesong Li, Yutong 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, Nan Li, Gongda 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, Hainan Li, Qi Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Fei Li, Xionghui Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Peilong Li, Hongmei Li, Kang 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, Guoping Li, Xingxing 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, Xue-Peng Li, Jianang Li, Qing Li, Jiaping Li, Sheng-Tien Li, Shihao Li, Yazhou 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, Ming-Hao Li, Donghe Li, Zheng 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, Xiaochen Li, Dongfang Li, Zizhuo Li, Zhuorong Li, X-H Li, Dong Sheng Li, Xianrui Li, Lan-Juan 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, Zhifei Li, Jinhui Li, Ying Li, Yanshu Li, Jianlin Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Longyu Li, Guiying Li, Jinku Li, X B Li, Zhisheng Li, Changgui 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, Yuzhe Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Chang-Yan Li, Xiaohua Li, Qifang Li, Vivian Li, Duanxiang Li, Xiaolin Li, Meiting Li, Justin Li, Xue-Er Li, Zhuangzhuang Li, Xiaohui Li, Hongchang Li, Cang Li, Xuepeng Li, Youwei Li, Mingjiang Li, Ronggui Li, Xingwang Li, Tiange Li, Yongjia Li, Dacheng Li, Xinmin Li, Zongyu Li, Luquan Li, Jianyong Li, Guoxing Li, Shujie Li, Zongchao Li, Yanbin Li, Jia Li, Shiliang Li, Haimin Li, Sheng-Qing Li, Qinrui Li, Yiming Li, Xiao-Tong Li, Lingjie 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, X Li, Liao-Yuan Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Hengguo Li, An-Qi Li, Xuehua Li, Hui Li, AnHai Li, Chenli Li, Rumei Li, Zhengrui Li, Fangqi Li, Xiaoguang Li, Xian Li, Danjie Li, Yan-Yu Li, Vivian S W Li, Qinghua Li, Qinqin Li, Lipeng 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, Qing-Min Li, Meiyan Li, Yonghe Li, Yun-Da Li, Xinwei Li, Shunhua Li, Yu-I Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Ziqi Li, Shen Li, Tianjiao Li, Shufen Li, Yunfeng Li, Gui-Rong Li, Yunpeng Li, Yueqi Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Pinghua Li, Xu Li, Shi-Fang Li, Shude Li, Yaxiong Li, Zhibin 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, Meng Li, Zhijie Li, Cun Li, Huimin Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Yinghui Li, Cong Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Weiling Li, Mengfan Li, Jie Li, Shiyan Li, G Li, Lianbing Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, Jialin Li, Wenjian Li, He Li, Bichun Li, Hanqin Li, Xiong Bing Li, Qingjie Li, Wen Lan Li, Guoge Li, Han Li, Wen-Wen Li, Keying Li, Yutang Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Hankun Li, Hongling Li, Xiangrui Li, Michelle Li, Chaojie 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, Guangdi Li, Peipei 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, Lin Li, Jieshou Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Mengqing Li, S L Li, Hong-Lan Li, Ben-Shang 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, Ai-Qin Li, Si-Wei 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, Xudong Li, Guoxi Li, Xingfang Li, Shugang Li, Shengli Li, Jisheng Li, Rongyao Li, Xuan Li, Yongze Li, Ru Li, Yongxin 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, H J Li, Zhenyan Li, Ji Xia Li, Yu-Ye Li, Meizi Li, Qing-Wei Li, Qiang Li, Yuezheng Li, Hsiao-Hui Li, Zhengnan Li, L I Li, Jianglong Li, Hongzheng Li, Laiqing Li, Zhongxia Li, Ningyang Li, Guangquan Li, Xiaozheng Li, Hui-Jun Li, Shun 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, Zhihui Li, Yi-Yang 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, Shichao Li, Gan 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, Kui Li, Zhao Li, Tiegang Li, Yunxu Li, Zhong Li, Shuang-Ling 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, Wenqi Li, Haibo Li, Zhenzhe Li, Jian-Mei Li, Xiao-Jun Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Qiao Li, Xueling Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Yike Li, Wanni Li, Yihan Li, Chitao Li, Haiyang Li, Jiayu Li, Junsheng Li, Xiaobai Li, Pingping Li, Wen-Ya Li, Mingquan Li, Suran Li, Yunlun Li, Rongxia Li, Yingqin Li, Yuanfang Li, Guoqin Li, Qiner Li, Huiqin Li, Shanhang Li, Jiafang Li, Chunlin Li, Han-Bing Li, Zongzhe Li, Yikang Li, Jisen Li, Si-Yuan Li, Hongmin Li, Caihong Li, Yajing Li, Peng Peng Li, Kenli Li, Guanglu Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Dongmin Li, Jian-Jun Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Xinxin Li, Jian-Shuang Li, You-Mei Li, Dazhi Li, Chenglan Li, Yubin Li, Yuhong Li, Beixu Li, Di Li, Fengqiao Li, Guiyuan Li, Suk-Yee Li, Yanbing Li, Shengjie Li, Yuanyuan Li, Jufang Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, Jun Li, Minghua Li, Xiyue Li, Zhuoran Li, Tianchang 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, Huifang Li, Xiujuan 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, Yuling Li, Wendeng Li, Ding Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Yanjun Li, Linyan Li, Shengze Li, Ming-Yang 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, Ping'an Li, Yushan Li, Juan Li, Huan Li, Weiping Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yinliang Li, Yuehua Li, Wen Li, Jinfeng Li, Shiheng Li, Jiangan Li, Hsiao-Fen Li, Yu-Kun Li, Weihai Li, Zhaojin Li, Mengjiao Li, Bingxin Li, Wenjuan Li, Wenyu Li, Chia-Yang Li, Meng-Meng Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Xi-Xi Li, Wenlei Li, Mei-Lan Li, Wenjun Li, Jiaxin Li, Haiyan Li, Ming D Li, Chenguang Li, Ruyue Li, Xujun Li, Chi-Ming Li, Xiaolian Li, Dandan Li, Yi-Ning Li, Yunan Li, Jiazhou Li, Zechuan Li, Zhijun Li, Sherly X Li, Wanling Li, Ya-Ge Li, Yinyan Li, Qijun Li, Guangli Li, Rujia Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Wan-Shan Li, Xiaohan Li, Huijie Li, Zhongwen 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, Bingsheng Li, Jingui 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, Zhongxian Li, Xiaoliang 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, Rui Li, Zilu 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, Qihua Li, Zhengyao Li, Jin-Qiu Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, Xutong Li, Lin-Feng Li, Ranwei Li, Kai Li, Ziqing Li, Wei-Li Li, Keanning 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, Long-Yan Li, Zhixuan Li, Chuanbao Li, Fuyu Li, Chuzhong Li, M D Li, Lingzhi Li, Yuan-Tao Li, Kening Li, Guilan Li, Wanshi Li, Hengtong Li, Ling-Zhi Li, Yifan Li, Ya-Li Li, Xiao-Sa Li, Songyun Li, Xiaoran Li, Bolun Li, Kunlin Li, Linchuan Li, Jiachen Li, Haibin Li, Shu-Qi Li, Huangbao Li, Zehua Li, Guo-Chun Li, Xinli Li, S Li, Mengyuan Li, Wenqing Li, Wenhua Li, Caiyun Li, Xinrui Li, Congye Li, Dehai Li, Wensheng 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, Huanhuan Li, Xiaoyuan Li, Yanan Li, Zongfang Li, Yang Li, Jiayan Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Yimei Li, Dongdong 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, Lihua Li, Yilong Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Zhi-Yuan Li, Yuemei Li, Yanli Li, Jingfeng Li, Hai Li, Kaibin Li, Yuan-Jing Li, Xuefeng Li, Wenjie Li, Xiaohu Li, Ruikai Li, Mengjuan Li, Xiao-Hong Li, Yinglin Li, Yaofu Li, Ren-Ke Li, Qiyong Li, Ruixi Li, Yi Li, Zhonglian Li, Baosheng 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, Meng-Jun Li, Congjiao Li, Peining Li, Gaizhen Li, Huilin Li, Songtao Li, Liang Li, Fusheng Li, Huafang Li, Dai Li, Meiyue Li, Chenlu Li, Nianyu Li, Keshen Li, Kechun Li, Yuxin Li, X-L Li, Shaoliang Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Qun Li, Cuiguang Li, Dongye Li, Tianye Li, Zhen Li, F Li, Yuan Li, Chunhong 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, Tiewei Li, Bing-Hui Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Rong Li, Shikang Li, Wei-Yang 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, Hong-Lian Li, Shishi 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, Zonglin Li, Yinhao 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, Jingyi Li, Ji-Cheng Li, Yuxiang Li, Hao-Fei Li, Haolong Li, Xuanzheng Li, Peng-li Li, Quan Li, Yining Li, Xue-Ying Li, Xiurong Li, Huijuan Li, Haiyu Li, Xu-Zhao Li, Yunze Li, Yanzhong Li, Guohui Li, Kainan Li, Yongzhe Li, Qingfeng Li, Tianyi Li, Xiaoyan Li, Nanlong Li, Ping Li, Xu-Bo Li, Nien-Chen Li, Fangzhou Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Yuanchuang 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, Dengxiong Li, Xiaomin Li, Sijie Li, Meilan Li, D C Li, Andrew C Li, Jianye Li, Yi-Shuan J Li, Tinghao Li, Zhouxiang Li, Qiuyan 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, Kaiyi Li, Junyi 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, Yan-Chun Li, Binghu Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Zhenguang Li, Xiaotian Li, Jia-Ru Li, Shuhui Li, Shu-Hong Li, Pei-Qin Li, Chun-Xiao Li, Shuyue Li, Mengying Li, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Duo Li, Dali Li, Yaxian Li, Zhiming Li, Xuemei Li, Hongxia Li, Yongting Li, Xueting Li, Zhenjun Li, Danyang 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, Zhijia Li, Zhipeng 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, Shujiao Li, Yaojia Li, Xiao-Yao Li, Weirong Li, Kun-Ping 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, Yingjun Li, Xiufeng Li, Yanxin 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, Haifeng Li, Changkai Li, Yueping 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, Weiheng Li, Leipeng 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, Chanyuan Li, Jianbin Li, Shiying Li, Jianxiong Li, Ji Li, Huaying 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, Ruijin Li, Kunlong Li, Xiaomei Li
articles
Zhaoyang Ye, Guangliang Bai, Ling Yang +7 more · 2025 · Microorganisms · MDPI · added 2026-04-24
Diabetes mellitus (DM) and tuberculosis (TB) are two global health challenges that significantly impact population health, with DM increasing susceptibility to TB infections. However, early risk predi Show more
Diabetes mellitus (DM) and tuberculosis (TB) are two global health challenges that significantly impact population health, with DM increasing susceptibility to TB infections. However, early risk prediction methods for DM patients complicated with TB (DM-TB) are lacking. This study mined transcriptome data of DM-TB patients from the GEO database (GSE181143 and GSE114192) and used differential analysis, weighted gene co-expression network analysis (WGCNA), intersecting immune databases, combined with ten machine learning algorithms, to identify immune biomarkers associated with DM-TB. An early alert model for DM-TB was constructed based on the identified core differentially expressed genes (DEGs) and validated through a prospective cohort study and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) for gene expression levels. Furthermore, we performed a detailed immune status analysis of DM-TB patients using the CIBERSORT algorithm. We identified 1090 DEGs associated with DM-TB and further pinpointed CETP (cholesteryl ester transfer protein) (AUC = 0.804, CI: 0.744-0.864), TYROBP (TYRO protein tyrosine kinase binding protein) (AUC = 0.810, CI: 0.752-0.867), and SECTM1 (secreted and transmembrane protein 1) (AUC = 0.811, CI: 0.757-0.864) as immune-related biomarkers for DM-TB patients. An early alert model was developed based on these three genes (AUC = 0.86, CI: 0.813-0.907), with a sensitivity of 0.80829 and a specificity of 0.75758 at a Youden index of 0.56587. External validation using the GSE114192 dataset showed an AUC of 0.901 (CI: 0.847-0.955). Population cohort research and RT-qPCR verified the expression levels of these three genes, demonstrating consistency with trends seen in the training set. KEGG enrichment analysis revealed that NF-κB and MAPK signaling pathways play crucial roles in the DM-TB pathogenic mechanism, and immune infiltration analysis showed significant suppression of certain adaptive immune cells and activation of inflammatory cells in DM-TB patients. This study identified three potential immune-related biomarkers for DM-TB, and the constructed risk assessment model demonstrated significant predictive efficiency, providing an early screening strategy for DM-TB. Show less
📄 PDF DOI: 10.3390/microorganisms13040919
CETP
Shuang-Shuang Wang, Xin Jin, Wen-Di Ma +9 more · 2025 · European journal of pharmacology · Elsevier · added 2026-04-24
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple Show more
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS), by promoting the production of interferon-β (IFN-β). However, the mechanism through which oxymatrine regulates the production of IFN-β remains unclear. The aim of this study was to investigate the pharmacological effects and related molecular mechanisms of oxymatrine in the treatment of EAE through in vivo and in vitro experiments. Oxymatrine alleviated neurological dysfunction, demyelination, and inflammation in EAE mice. It reduced microglia/macrophage infiltration and polarization, lowered pro-inflammatory cytokine levels (iNOS, TNF-α), and enhanced the expression of IL-10 and IL-27. Additionally, oxymatrine upregulated the STING/TBK1/IRF3 signaling pathway in EAE mice, promoting IFN-β production by microglia. Similarly, in LPS-induced BV2 cells, oxymatrine suppressed inflammatory factors and activated the STING/TBK1/IRF3 pathway to enhance IFN-β production. Notably, treatment with the STING inhibitor, C176, reversed these effects in both EAE mice and LPS-induced BV2 cells, confirming the pathway's critical role in the mechanism of oxymatrine therapy. Oxymatrine promotes IFN-β production in microglia by upregulating the STING/TBK1/IRF3 signaling pathway, thereby alleviating the neurological dysfunction of EAE and reducing pathological and inflammatory events. This study identifies a novel anti-EAE mechanism of oxymatrine: promoting IFN-β production in microglia by activating the STING/TBK1/IRF3 pathway. However, it lacks clinical sample verification. If validated later, oxymatrine may provide a more economical, convenient endogenous IFN-β induction regimen for MS patients. Show less
no PDF DOI: 10.1016/j.ejphar.2025.178380
IL27
Hua-Xiong Zhang, Dilmurat Hamit, Qing Li +6 more · 2025 · Scientific reports · Nature · added 2026-04-24
Melatonin (MLT) can improve mitophagy, thereby ameliorating cognitive deficits in Alzheimer's disease (AD) patients. Hence, our research focused on the potential value of MLT-related genes (MRGs) in A Show more
Melatonin (MLT) can improve mitophagy, thereby ameliorating cognitive deficits in Alzheimer's disease (AD) patients. Hence, our research focused on the potential value of MLT-related genes (MRGs) in AD through bioinformatic analysis. First, the key cells in the single-cell dataset GSE138852 were screened out based on the proportion of annotated cells and Fisher's test between the AD and control groups. The differentially expressed genes (DEGs) in the key cell and GSE5281 datasets were identified, and the MRGs in GSE5281 were selected via weighted gene coexpression network analysis. After intersecting two sets of DEGs and MRGs, we performed Mendelian randomization analysis to identify the MRGs causally related to AD. Biomarkers were further ascertained through receiver operating characteristic curve (ROC) and expression analysis in GSE5281 and GSE48350. Furthermore, gene set enrichment analysis, immune infiltration analysis and correlation analysis with metabolic pathways were conducted, as well as construction of a regulator network and molecular docking. According to the Fisher test, oligodendrocytes were regarded as key cells due to their excellent abundance in the GSE138852 dataset, in which there were 281 DEGs between the AD and control groups. After overlapping with 3,490 DEGs and 550 MRGs in GSE5281, four genes were found to be causally related to AD, namely, G protein-coupled receptor, family C, group 5, member B (GPRC5B), Methyltransferase-like protein 7 A (METTL7A), NF-κB inhibitor alpha (NFKBIA) and RAS association domain family 4(RASSF4). Moreover, GPRC5B, NFKBIA and RASSF4 were deemed biomarkers, except for METTL7A, because of their indistinctive expression between the AD and control groups. Biomarkers might be involved in oxidative phosphorylation, adipogenesis and heme metabolism. Moreover, T helper type 17 cells, natural killer cells and CD56dim natural killer cells were significantly correlated with biomarkers. Transcription factors (GATA2, POU2F2, NFKB1, etc.) can regulate the expression of biomarkers. Finally, we discovered that all biomarkers could bind to MLT with a strong binding energy. Our study identified three novel biomarkers related to MLT for AD, namely, GPRC5B, NFKBIA and RASSF4, providing a novel approach for the investigation and treatment of AD patients. Show less
📄 PDF DOI: 10.1038/s41598-024-80755-x
GPRC5B
Yanping Wang, Xiaoru Ma, Zhixin Qiao +16 more · 2025 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, bu Show more
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, but its astrocyte-related mechanisms remain unclear. Here, we demonstrated that EA at ST36 alleviated blood-brain barrier (BBB) disruption and neuroinflammation during the peak period of experimental autoimmune encephalomyelitis (EAE). Additionally, EA at ST36 upregulated the expression of α-melanocyte-stimulating hormone (α-MSH) and its receptor melanocortin-4 receptor (MC4R) in spinal astrocytes. Pharmacological studies showed that MC4R agonist RO27-3225 mimicked the therapeutic effects of EA, whereas MC4R antagonist TCMCB07 weakened EA-mediated BBB protection and neuroinflammation suppression. Moreover, astrocyte-specific silencing of MC4R via adeno-associated virus (AAV) weakened EA-mediated BBB protection and neuroinflammation suppression. RNA-sequencing (RNA-seq) and western blot (WB) revealed that EA exerts neuroprotective effects by activating MC4R to inhibit MAPK and NF-κB signaling pathways. Moreover, in MC4R-overexpressing astrocytes, α-MSH and RO27-3225 reduced inflammation responses, while TCMCB07 reversed the effects by MAPK/NF-κB signaling pathways. Collectively, our findings identify astrocytic MC4R as a critical mediator of EA-driven neuroprotection by suppressing MAPK/NF-κB signaling, providing mechanistic insight and a promising therapeutic target for EAE and other neuroinflammatory disorders. Show less
📄 PDF DOI: 10.1186/s12974-025-03667-1
MC4R
Jingshu Li, Xuanyi Du, Rui Zhang +7 more · 2025 · Scientific reports · Nature · added 2026-04-24
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challen Show more
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challenging. Accurate prediction can improve advanced care planning and patient outcomes. This study aimed to develop and validate a machine learning (ML) model for predicting progression within 25 weeks (approximately six months) of ESRD in patients with stage 4 CKD. Electronic health records (EHRs) of patients with stage 4 CKD were analyzed. Nine ML models including Ridge regression (Ridge), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to predict short-term progression to ESRD within 25 weeks. The models were trained and externally validated using the data of 346 and 105 patients. Of the 451 patients with stage 4 CKD, 219 developed ESRD. Among the evaluated models, XGBoost demonstrated the best overall performance. In the internal validation, it achieved an area under the curve (AUC) of 0.93, an accuracy of 0.90, and an F1 score of 0.89. In the external validation, XGBoost maintained the highest AUC (0.85), accuracy (0.79), and F1 score (0.79), along with the highest average precision (0.89) and a low log-loss (0.48), indicating strong discriminative ability and good generalizability. The top predictive features included high-density lipoprotein cholesterol, Alb, Cys C, ApoB, FGB, Bun, Neutrophil, and Total cholesterol. This study demonstrated the feasibility of ML for assessing ESRD prognosis based on easily accessible clinical features. XGBoost demonstrated superior performance in both internal and external validation, suggesting its potential for future patient screening. Show less
📄 PDF DOI: 10.1038/s41598-025-23037-4
APOB
Jingru Wang, Bo Yao, Yutian Zhang +13 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strat Show more
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strategy to prevent atherosclerosis (AS), and targeted nanotherapeutics represent one approach for implementing this strategy. To this end, we designed immunosuppressive oligodeoxynucleotide A151 functionalized selenium nanoparticles with a spearhead LacNAc (LN-A151-SeNPs) that target macrophage-like VSMCs. Nano characterization showed that the uniformity and stability of nanoparticles were optimized by modification with LacNAc and A151, resulting in an average diameter of 88.90 ± 1.45 nm, Zeta potentials of -21.1 ± 1.5 mV, a A151:Se molar ratio of 1:60 and mass ratio of 1.68:1. The effects of LN-A151-SeNPs on inhibiting VSMCs phenotype switching and attenuation of AS were investigated using [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03925-7. Show less
📄 PDF DOI: 10.1186/s12951-025-03925-7
APOE
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
Anjing Liu, Roulan Jiang, Ruixi Li +16 more · 2025 · Research square · added 2026-04-24
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyon Show more
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyond mean-level associations. Methods for detecting distributional effects have been developed for eQTL analysis, yet applications have focused on method demonstrations rather than large-scale biological discovery. We comprehensively mapped quantile, variance, and interaction QTLs across 34 data-set from 22 molecular contexts in >2,300 human brain donors, revealing that 48.7% of quantile QTLs (qQTLs) exhibit context-dependent regulation invisible to linear models, with enrichment at phenotypic extremes and in cell-type-specific regulatory elements, chromatin accessibility regions, and long-range chromosomal contacts. qQTL variants explained additional trait heritability beyond linear QTLs for brain-related traits. At Alzheimer's disease (AD) risk loci, qQTL analysis revealed complex regulatory architecture including variance effects at Show less
📄 PDF DOI: 10.21203/rs.3.rs-8219833/v1
APOE
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
Lan Yang, Jinghua Yang, Hong Zhang +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. H Show more
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. However, there remains a significant gap in studies specifically addressing the eHL needs of patients with maintenance hemodialysis (MHD). This study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL). A survey was conducted using a convenience sampling method involving 500 MHD patients from three tertiary hospitals in Baoding. Data were analyzed using latent profile analysis (LPA) and a mixed regression model. This study showed that MHD patients could be classified into low (23.17%), middle (49.78%), and high (27.05%) eHL groups, with the three-class model showing optimal fit (AIC = 2321.213, BIC = 2271.168, entropy = 0.967). MHD Patients in the high literacy group scored significantly higher in all dimensions of e-HL and overall HPL (119.58 ± 13.86) compared to those in the low literacy group (91.82 ± 11.73) (all The findings suggest a heterogeneous stratification of eHL among MHD patients, closely linked to HPL. Stratified intervention strategies should be developed for different patient groups to potentially improve their health behaviors. The study provides evidence-based support for personalized health management. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1630350
LPA
Shuzhi Zhao, Yili Zhang, Chenxin Li +2 more · 2025 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
The pyroptosis of retinal Müller cells is intricately linked to the pathogenesis of diabetic retinopathy (DR). Ubiquitin-fold modifier 1 (UFM1)-mediated UFMylation plays an important role in insulin a Show more
The pyroptosis of retinal Müller cells is intricately linked to the pathogenesis of diabetic retinopathy (DR). Ubiquitin-fold modifier 1 (UFM1)-mediated UFMylation plays an important role in insulin and diabetes mellitus metabolism and regulates cell death such as apoptosis and pyroptosis. UFM1-specific protease 2 (UFSP2) mediates the maturation of the UFM1 precursor and thus affects UFMylation reaction. However, its role in DR remains unknown. The aim of our study was to determine the mechanism and upstream regulation of UFSP2 on the pyroptosis of rat retinal Müller cells. Pathological changes, UFSP2 expression and succinate accumulation were determined in retinal tissues of db/db diabetic mice via Hematoxylin and eosin and immunofluorescence staining and biochemical analysis. High glucose (HG) was used to construct a DR cell model using rat retinal Müller cells (rMC-1). Ufsp2 RNA interference and overexpression plasmids were constructed to determine the effects of UFSP2. Pyroptosis and reactive oxygen species (ROS) levels were assessed via flow cytometry. Inflammatory cytokine (IL-1β and IL-18) levels and key molecular markers related to pyroptosis (NLRP3, ASC, Caspase-1p20, GSDMD-N) were measured by enzyme linked immunosorbent assay and Western blot, respectively. Succinate-mediated H3K3me3 enrichment in Ufsp2 promoter region was measured by chromatin immunoprecipitation. In vivo experiments revealed that the UFSP2 expression and succinate levels were increased in retinal tissues of db/db diabetic mice with thinning of retinal thickness. Moreover, in vitro experiments showed that The mRNA and protein levels of Ufsp2 exhibited a time-dependent increase under HG conditions. Upon Ufsp2 knockdown, the elevated oxidative stress, inflammatory responses, and pyroptosis stimulated by HG were significantly suppressed. The effect of Ufsp2 overexpression on pyroptosis and inflammatory responses was consistent with the HG stimulation, whereas the UFSP2-induced heightened levels of pyroptosis as well as the inflammatory state were significantly reversed when co-administered with NLRP3 inhibitor or ROS inhibitor. Further activating NLRP3 inflammasome using LPS + ATP stimulation revealed that the knockdown of Ufsp2 resulted in inhibited pyroptosis levels and inflammatory responses, while the Ufsp2 overexpression markedly increased pyroptosis and inflammatory responses. Lastly, succinate was demonstrated to influence Ufsp2 transcription, as well as the expression of H3K3me3 and its enrichment in the Ufsp2 promoter region, ultimately affecting pyroptosis and inflammatory responses. Succinate-mediated Ufsp2 transcription promotes pyroptosis in rMC-1 cells by activating NLRP3 inflammasome and oxidative stress. Show less
no PDF DOI: 10.1016/j.bbrc.2025.152614
RMC1
Xiaolan Chen, Jin You, Qin Ma +7 more · 2025 · Nature communications · Nature · added 2026-04-24
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Al Show more
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Although the RNA moiety of most R-loops originates from linear transcripts, circular RNAs (circRNAs), outputs from back-splicing, can also hybridize with the complementary strand of a DNA duplex. However, how circRNA-associated R-loops (ciR-loops) are monitored remains elusive. Here, we identify the DEAD-box RNA helicase Brr2 as an evolutionarily-conserved ciR-loop repressor with dual roles in inhibiting circRNA generation and resolving harmful ciR-loops. Accumulation of ciR-loops caused by loss-of-function of this dual-action factor induces antisense transcription and premature transcription termination for many genes and generates significant DNA damage, which further leads to a series of defects in DNA replication, cell division and cell proliferation. We propose that functional integration of multilayered regulation by a single protein can be an efficient double protection against genome instability. Show less
📄 PDF DOI: 10.1038/s41467-025-64174-8
DHX36
Jun Teng, Chongwei Duan, Xinyi Zhang +9 more · 2025 · Journal of dairy science · added 2026-04-24
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation tr Show more
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation traits is essential for understanding their genetic basis. In this study, we conducted single-trait and multitrait GWAS for 20 body conformation traits using imputed sequence data in 7,674 Chinese Holstein individuals and identified 27 QTL regions. Leveraging these QTL regions, we performed multitrait Bayesian fine-mapping to identify 30 independent credible sets of putative causal variants. Incorporating GWAS and cis-acting expression QTL data, Mendelian randomization was used to infer 153 putative causal gene-trait relationships. The previously reported genes, such as CCND2, TMTC2, and NRG3, were confirmed in our study. Of note, several novel candidate causal genes were also identified, such as C1R, RIMS1, SERPINB8, NETO2, TTYH3, TTC3, ANAPC4, and PSMD13. Our results provide new insights into the regulatory mechanisms of body conformation traits in cattle. Show less
no PDF DOI: 10.3168/jds.2025-26361
ANAPC4
Jiahao Li, Yufeng Tang, Guangping Lu +7 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Lipid metabolism disorders have been confirmed to be closely related to kidney injury caused by adriamycin (ADR) and obesity, respectively. However, it has not been explored whether lipid metabolism d Show more
Lipid metabolism disorders have been confirmed to be closely related to kidney injury caused by adriamycin (ADR) and obesity, respectively. However, it has not been explored whether lipid metabolism disorders appear progressively more severe after ADR-based chemotherapy in the obese state, and the specific molecular mechanism needs to be further clarified. This study was designed to examine the role of p53-fibroblast growth factor 21 (FGF21) axis in ADR-induced renal injury aggravated by high-fat diet (HFD). We engineered Fgf21 KO mice and used long-term (4 months) and short-term (0.5 months) HFD feeding, and ADR-injected mice, as well as STZ-induced type 1 diabetic mice and type 2 (db/db) diabetic mice to produce an in vivo model of nephrotoxicity. The specific effects of p53/FGF21 on the regulation of lipid metabolism disorders and its downstream mediators in kidney were subsequently elucidated using a combination of functional and pathological analysis, RNA-sequencing, molecular biology, and in vitro approaches. Long-term HFD feeding mice exhibited compromised effects of FGF21 on alleviation of renal dysfunction and lipid accumulation following ADR administration. However, these impairments were reversed by p53 inhibitor (pifithrin-α, PFT-α). PFT-α sensitized FGF21 actions in kidney tissues, while knockout of Fgf21 impaired the protective effects of PFT-α on lipid metabolism. Mechanistically, p53 impaired the renal expression of FGF receptor-1 (FGFR1) and thereby developed gradually into FGF21 resistance via inhibiting hepatocyte nuclear factor 4 alpha (HNF4α)-mediated transcriptional activation of Fgfr1. More importantly, exogenous supplementation of FGF21 or PFT-α could not only alleviate ADR-induced lipid metabolism disorder aggravated by HFD, but also reduce lipid accumulation caused by diabetic nephropathy. Given the difficulties in developing the long-acting recombinant FGF21 analogs for therapeutic applications, sensitizing obesity-impaired FGF21 actions by suppression of p53 might be a therapeutic strategy for maintaining renal metabolic homeostasis during chemotherapy. Show less
📄 PDF DOI: 10.1016/j.jare.2024.07.014
FGFR1
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Jiangming Wei, Xiaobo Wei, Lexiu Deng +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Dysregulation of macrophage autophagy plays a critical role in sepsis-induced acute lung injury (ALI); however, its underlying mechanism remains unclear. In this study, we aimed to identify the regula Show more
Dysregulation of macrophage autophagy plays a critical role in sepsis-induced acute lung injury (ALI); however, its underlying mechanism remains unclear. In this study, we aimed to identify the regulatory pathway involving the PIK3C3-MAPK14 signaling axis that drives ALI progression by controlling autophagy and macrophage polarization. Using machine learning transcriptomic analysis, MAPK14 was identified as a core gene associated with ALI, and multi-omics integration confirmed its upregulated expression in ALI tissues. MAPK14 localization to pro-inflammatory macrophages was determined using single-cell sequencing. Furthermore, we observed a significant positive correlation between MAPK14 and autophagy-related genes. Molecular docking and kinetic simulations revealed high-affinity interactions between PIK3C3 and MAPK14 (ΔG-bind = -127.722 ± 33.269 kJ/mol). In vitro experiments followed by Western Blot(WB) and RT-q polymerase chain reaction (PCR) assays demonstrated that lipopolysaccharide stimulation upregulated MAPK14 expression through downregulation of PIK3C3 expression, resulting in impaired autophagic flux (LC3-II/Ⅰ↓, TOM20↑, P62↑, HSP60↑). Flow cytometry and enzyme-linked immunosorbent assay (ELISA) confirmed a shift toward pro-inflammatory (M1) macrophage polarization. RNA pull-down assay directly captured the PIK3C3-MAPK14 complex, and functional validation showed that PIK3C3 overexpression significantly inhibited MAPK14 protein expression, whereas PIK3C3 knockdown enhanced it. In conclusion, targeting the PIK3C3-MAPK14 axis is a promising therapeutic strategy for ALI. Show less
no PDF DOI: 10.1038/s41598-025-27088-5
PIK3C3
Hao Zheng, Yan Li, Wen-Wen Zhan +5 more · 2025 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Copper clusters with diverse luminescent properties are of particular interest. In this study, a series of Cu
no PDF DOI: 10.1002/anie.202423787
LPL
Mingxuan Guo, Huanxin Zhao, Nannan Song +5 more · 2025 · Fitoterapia · Elsevier · added 2026-04-24
Sepsis-associated acute lung injury (SA-ALI), a critical complication of sepsis, is characterized by immune dysregulation-induced pulmonary dysfunction. Shenmai Injection (SMI) is a standardized herba Show more
Sepsis-associated acute lung injury (SA-ALI), a critical complication of sepsis, is characterized by immune dysregulation-induced pulmonary dysfunction. Shenmai Injection (SMI) is a standardized herbal preparation consisting of Panax ginseng C.A.Mey (Hongshen) and Ophiopogon japonicus (Thunb.) Ker Gawl (Maidong), traditionally used for qi-replenishing, collapse-stabilizing, and lung-moistening therapy. Although clinically utilized in the management of SA-ALI, the specific mechanisms by which it acts against SA-ALI necessitate further investigation. The present study endeavors to comprehensively determine the therapeutic efficacy of SMI against SA-ALI through an integrated approach combining network pharmacology, metabolomics, metagenomic sequencing, and experimental validation. In this study, murine SA-ALI was established using lipopolysaccharide (LPS) and Poly(I:C). Results indicated that SMI administration significantly attenuated pulmonary inflammation, restored blood-gas barrier integrity, reduced serum pro-inflammatory cytokines and suppressed NF-κB pathway activation in SA-ALI mice. Network pharmacology elucidated the multi-targeted mechanism of SMI in modulating steroid hormone biosynthesis. Integrated metabolomics and target analysis revealed that ophiopogonin A/B and luteolin in SMI alleviates metabolic dysregulation by targeting key enzymes, including AKR1C3, HSD17B1/2, and SULT1E1. Metagenomic profiling demonstrated SMI-mediated gut microbiota remodeling, marked by suppression of pathogenic Chlamydiaceae (particularly Chlamydia abortus) and enrichment of commensal Lactobacillaceae. Correlation analysis showed that intestinal androstenedione and androsterone levels during SMI treatment recovery were negatively correlated with Chlamydia abortus abundance. In conclusion, SMI enhances the recovery from sepsis-associated SA-ALI by dual modulation of gut microbial ecology and host metabolic homeostasis, thereby establishing its potential as a multi-mechanistic therapeutic candidate for sepsis-related organ injury. Show less
no PDF DOI: 10.1016/j.fitote.2025.106935
HSD17B12
Yanyan Zhang, Muzi Li, Zongyun Li +6 more · 2025 · Biomolecules · MDPI · added 2026-04-24
This study evaluated the protective effects of naringin (NG) against intestinal injury in 7-day-old piglets infected with porcine epidemic diarrhea virus (PEDV). Eighteen piglets (Duroc × Landrace × L Show more
This study evaluated the protective effects of naringin (NG) against intestinal injury in 7-day-old piglets infected with porcine epidemic diarrhea virus (PEDV). Eighteen piglets (Duroc × Landrace × Large, body weight = 2.58 ± 0.05 kg) were divided into three treatment groups based on similar body weights and equal numbers of males and females: the blank control group (CON group), the PEDV infection group (PEDV group), and the NG intervention + PEDV infection group (NG + PEDV group) ( Show less
📄 PDF DOI: 10.3390/biom16010048
APOA4
Bayixiati Qianman, Tuomilisi Jiasharete, Ayinazi Badalihan +9 more · 2025 · Journal of proteome research · ACS Publications · added 2026-04-24
Spontaneous Achilles tendon rupture (SATR) predominantly affects middle-aged and elderly individuals with chronic injuries. However, the exact cause and mechanism of SATR remain elusive, and potential Show more
Spontaneous Achilles tendon rupture (SATR) predominantly affects middle-aged and elderly individuals with chronic injuries. However, the exact cause and mechanism of SATR remain elusive, and potential therapeutic intervention or prevention is still insufficient. The present study aimed to uncover the key pathological molecules by using iTRAQ proteomics. The results identified 2432 candidate proteins in SATR patients using iTRAQ proteomic analysis. A total of 307 differentially expressed proteins (DEPs) were identified and linked to 211 KEGG signaling pathways including Coronavirus disease (COVID-19), focal adhesion, and ribosomes. GO enrichment analysis highlighted significant enrichment in processes such as biological adhesion, ossification, lipid (APOA4) processes, and extracellular matrix (ECM) organization (collagen). PPI network analysis identified hub genes such as serum albumin (ALB), fibronectin (FN1), and actin cytoplasmic 1. The WB analysis confirmed that FN1 and the receptor for activated C kinase (RACK1) were downregulated in the SATR tendon. Immunohistochemical staining revealed that collagen I and III were suppressed, while collagen II and APOA4 expression were higher in the SATR pathological tissue ( Show less
no PDF DOI: 10.1021/acs.jproteome.4c00357
APOA4
Shengfeng Deng, Guo Mu, Jun Li +3 more · 2025 · The journal of physiological sciences : JPS · Elsevier · added 2026-04-24
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, Show more
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, EdU and flow cytometry were employed to detect cell damage. The levels of N6-methyladenosine (m6A), METTL14 and DUSP6 were determined by qPCR and Western blot. The interaction between METTL14 and DUSP6 was analyzed using RIP-qPCR and Me-RIP methodologies. The cognitive function in mice were assessed by water maze test. After sevoflurane treatment, the cell viability, cell proliferation and METTL14 expression were markedly suppressed, while apoptosis was significantly enhanced. METTL14 overexpression elevated the levels of m6A and DUSP6, increased the binding level of METTL14 to DUSP6 mRNA, reducing damage to cells and cognitive dysfunction of mice. Knockdown of DUSP6 negated the beneficial effects observed with METTL14 overexpression. Sevoflurane induced POCD by regulating METTL14/DUSP6 through m6A methylation. Show less
📄 PDF DOI: 10.1016/j.jphyss.2025.100048
DUSP6
Dan Li, Mi Zhou, Xiaomei Song · 2025 · Frontiers in aging · Frontiers · added 2026-04-24
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity beh Show more
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity behaviours within a 24-h framework. This study investigates the relationship between cognitive function and 24-h activity behaviours in older adults, further exploring whether these associations differ by sex. This study analyses data from the eighth wave of the Survey of Health, Ageing and Retirement in Europe, conducting a cross-sectional analysis of 814 older adults. Cognitive function was assessed using the SHARE-Cog tool, encompassing 10-word immediate recall, 10-word delayed recall, verbal fluency, and self-reported memory. 24-h activity behaviours (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], sedentary behaviour [SB], and sleep) were objectively measured with thigh-worn accelerometers. Compositional multivariate linear regression models were constructed using compositional data as the response variable, with cognitive function measures as predictors. Higher MVPA was linked to better cognitive outcomes (verbal fluency, 10-word immediate recall, and 10-word delayed recall) while SB and longer sleep related to poorer performance, with these associations being stronger in women (model p ≤ 0.001). Among women, cognitive outcomes were significantly associated with all activity behaviours (p range = 0.010-0.045). Women who self-reported poor memory and scored 0 on the verbal fluency spent approximately 45% of their day in SB, whereas those reporting excellent memory and scoring 60 spent 40.06% (37.18%, 42.86%) and 36.41% (31.53%, 41.10%) of their day sedentary, respectively. In contrast, men's 24-h activity composition did not vary significantly with cognitive function (p range = 0.051-0.845). Older adults with better cognitive function tend to engage in more PA and reduce sedentary and sleep time. This relationship differed by sex, with females' activity behaviours being more sensitive to cognitive function changes. These findings suggest that interventions promoting healthy lifestyles in older adults should account for cognitive function, particularly in females. Show less
📄 PDF DOI: 10.3389/fragi.2025.1686847
LPA
Yamin Guo, Xinmiao Wu, Huimin Zhen +5 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Our previous investigations identified miR-30a-3p as a differentially expressed miRNA in ovine mammary tissue across sheep breeds with distinct lactation performance and different physiological stages Show more
Our previous investigations identified miR-30a-3p as a differentially expressed miRNA in ovine mammary tissue across sheep breeds with distinct lactation performance and different physiological stages. However, its regulatory mechanisms controlling mammary gland development and lactation remain unexplored. In this study, the effect of miR-30a-3p on the proliferation of ovine mammary epithelial cells (MECs) and the target genes of miR-30a-3p were investigated. The regulatory effects of miR-30a-3p on the expression of the target genes and the content of triglycerides in ovine MECs were also analyzed. The transfection of miR-30a-3p mimic was found to promote cell viability and the number of proliferated ovine MECs using CCK8 and Edu assays. On the contrary, the miR-30a-3p inhibitor showed the opposite results with the miR-30a-3p mimic. These results suggest that miR-30a-3p promotes the proliferation of ovine MECs. The dual luciferase assay revealed that Phosphatase and Tensin Homolog ( Show less
📄 PDF DOI: 10.3390/ani15081180
LPL
Zhengliang Li, Xiaokai Chen, Juan Wang +6 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study inclu Show more
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study included 394 patients with MAFLD who underwent coronary angiography at The Affiliated Hospital of Qingdao University between December 2019 and December 2024. The study cohort was divided in a 7:3 ratio into training and validation sets comprising 277 and 117 cases, respectively. The training group was further divided into the MAFLD-only ( Of the 394 MAFLD cases, 313 had CHD-related complications. Of the 277 patients in the training set, 220 had CHD, and of the 117 patients in the validation set, 93 had CHD. LASSO regression analysis revealed that the following variables were associated with the risk of CHD: sex, lipoprotein(a) (Lp[a]), low-density lipoprotein cholesterol, white blood cell count (WBC), glycated triglyceride-glucose index (TyG), and atherosclerosis index (AIP). Multivariate logistic regression analysis revealed that sex, Lp(a), WBC, TyG, and AIP were independent risk factors for CHD in MAFLD cases. A nomogram was constructed and an ROC curve was plotted, based on which the optimal cutoff value was determined as 0.698. The area under the curve of the nomogram in the training and validation cohorts was 0.860 (95% CI = 0.807-0.913) and 0.843 (95% CI = 0.757-0.929), respectively. Calibration curves for CHD risk probability showed good agreement between the nomogram's predicted probabilities and the observed event rates. DCA demonstrated the net clinical benefit of the constructed nomogram. Sex, Lp(a), WBC, TyG, and AIP emerged as independent risk factors for CHD in patients with MAFLD and the nomogram prediction model constructed using these factors could effectively predict CHD occurrence. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1652321
LPA
Tao Yang, Xiaohu Hu, Fei Cao +15 more · 2025 · Nature · Nature · added 2026-04-24
The mammalian gut harbours trillions of commensal bacteria that interact with their hosts through various bioactive molecules
📄 PDF DOI: 10.1038/s41586-025-08990-4
APOB
Junyu Zhou, Yong Kwan Kim, Chen Li +1 more · 2025 · Computers in biology and medicine · Elsevier · added 2026-04-24
This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict na Show more
This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential in Alzheimer's disease (AD) treatment. The NCs were identified based on activity related to seven AD-specific genes, including acetylcholinesterase (AChE), amyloid precursor protein (APP), beta-secretase 1 (BACE1), and presenilin-1 (PSEN1). We implemented a computational pipeline using SELFormer and deep learning techniques, conducted optimal clustering and quantitative structure-activity relationship (QSAR) analyses, and performed a uniform manifold approximation and projection (UMAP) to categorize compounds based on bioactivity levels. Molecular docking analysis was carried out on selected compounds. To validate the computational predictions, we conducted in vitro studies using nerve growth factor (NGF)-differentiated PC12 cells. Finally, we mapped the relationships between food sources containing the identified compounds and their target proteins. Optimal clustering analysis revealed five distinct groups of NCs, while QSAR analysis highlighted variations in molecular properties across clusters. The UMAP projection identified 17 highly active NCs (pIC This integrated computational and experimental approach offers a promising framework for identifying potential NCs for AD treatment. The results contribute to exploring effective therapeutic strategies against AD. Show less
no PDF DOI: 10.1016/j.compbiomed.2024.109523
BACE1
Binbin Gong, Xike Mao, Guoxiang Li +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
The objective of this study was to assess the correlation between the ApoB/ApoA ratio and the recurrence of kidney stones in a Chinese adult population. We collected electronic records of patients wit Show more
The objective of this study was to assess the correlation between the ApoB/ApoA ratio and the recurrence of kidney stones in a Chinese adult population. We collected electronic records of patients with kidney stones who underwent surgical treatment at our hospital from March 2016 to March 2022. These patients were followed up and categorized into groups based on the recurrence of kidney stones. Parameters related to routine blood and biochemical tests, as well as the history of hypertension and diabetes mellitus, were gathered. Multiple imputation was applied for missing data. Subsequently, differences between the recurrence and non-recurrence groups were assessed using the chi-square test, independent samples t test, or Wilcoxon rank sum test. Logistic regression analysis, subgroup analysis, and propensity-matched analysis were conducted to evaluate the relationship between the ApoB/ApoA ratio and kidney stone recurrence. The study included a total of 923 participants aged > 18 years, among whom 296 experienced kidney stone recurrence during the follow-up period. An elevated ApoB/ApoA ratio was identified as a risk factor for kidney stone recurrence (adjusted OR = 2.48, 95% CI 1.04, 5.92). Propensity-matched analyses further supported the association, showing that elevated ApoB/ApoA ratios were linked to a higher risk of renal stone recurrence (OR = 3.37, 95% CI 1.24-9.17). The dose-response curve illustrated a positive linear correlation between the ApoB/ApoA ratio and the risk of kidney stone recurrence. Increased ApoB/ApoA ratios are positively correlated with the risk of kidney stone recurrence. This association remains significant, although a causal relationship cannot be definitively established. Show less
📄 PDF DOI: 10.1186/s40001-025-03396-4
APOB
Tong Chen, Jiawei Zhou, Mengfan Li +9 more · 2025 · BMC genomics · BioMed Central · added 2026-04-24
Pork serves as a significant meat commodity, with intramuscular fat (IMF) content being a critical determinant of its quality. However, the epigenetic mechanism of porcine IMF deposition is still uncl Show more
Pork serves as a significant meat commodity, with intramuscular fat (IMF) content being a critical determinant of its quality. However, the epigenetic mechanism of porcine IMF deposition is still unclear. This study integrated proteomics and lactylation profiles from the longissimus thoracis (LT) muscles of pigs with extremely high (IMF_H) and extremely low (IMF_L) IMF content to clarify the association between lactylation and porcine fat deposition. Furthermore, an intramuscular preadipocyte induction and differentiation model was conducted to elucidate the changes in lactylation during adipocyte differentiation. Finally, the regulatory role of lactylation in adipocyte differentiation was explored by modulating lactate production during the induction and differentiation of preadipocytes. Proteomic analysis revealed significantly increased expression of key lipid metabolism related proteins (FASN, APOA4, FABP4, ACLY, PLIN1) in IMF_H pig muscle tissues compared with IMF_L tissues, along with substantial activation of lipid metabolism pathways. Lactylation profiling identified 95 differential lysine sites across 56 proteins, with most showing lower lactylation levels in the IMF_H group. The integrative omics analysis revealed differences in lactylation profiles in porcine LT tissues with varying efficiencies of IMF deposition, highlighted PGK1, PKM, and PYGM as central lactylation-modified proteins in porcine fat deposition regulation. Further in vitro study proved that lactate-mediated lactylation inhibited adipogenic differentiation of porcine intramuscular preadipocytes through PPARγ signaling pathway. This study clarified the changes in the lactylation profile in porcine LT tissues with varying efficiencies of IMF deposition, and demonstrated that lactate-mediated lactylation inhibits the PPARγ signaling pathway and the adipogenic differentiation of porcine intramuscular preadipocyte. This study provided a new insight to understanding the epigenetic regulation mechanisms of lipid deposition in pigs. Show less
📄 PDF DOI: 10.1186/s12864-025-12428-6
APOA4
Xue Li, Luping Liu, Li Jiang +7 more · 2025 · Journal of molecular cell biology · Oxford University Press · added 2026-04-24
📄 PDF DOI: 10.1093/jmcb/mjae053
IL27
Lu Shen, Wenqing Zhai, Ping Jiang +6 more · 2025 · American journal of preventive cardiology · Elsevier · added 2026-04-24
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether syst Show more
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether systemic inflammation modulates Lp(a)-associated coronary stenosis in chronic coronary syndromes (CCS). A total of 1513 participants undergoing angiography at a tertiary cardiology center in China were included in our retrospective, cross-sectional study. Participants were categorized into normal, mild, and severe groups based on the Gensini Scores, which quantitatively assess stenosis severity. Multinomial logistic models were calculated according to accompanying systemic inflammation concentration. Participants with elevated Lp(a) levels had a high coronary stenosis risk: fully adjusted model odds ratios (ORs) [95% confidence intervals (CIs)] for the mild vs. normal and severe vs. normal groups were 1.47 (1.11-1.96) and 1.68 (1.21-2.33). Notably, the strongest Lp(a)-coronary stenosis associations after multi-variable adjustment persisted only in low inflammation concentration [systemic inflammation response index (SIRI) < 0.64)] [mild vs. normal, OR 2.03, 95% CI 1.17-3.54, Elevated Lp(a) correlates with coronary stenosis only in low inflammation concentration. Considering systemic inflammation in personalized Lp(a)-lowering therapies is more conducive for CCS managements. Show less
📄 PDF DOI: 10.1016/j.ajpc.2025.101324
LPA