👤 Hang 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, Guobin Li, Enhong Li, Hong-Tao Li, Xiangnan Li, Yong-Jun Li, Ziming 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, Youran Li, Peiwu Li, Yongmei Li, Changyu Li, Peilin Li, Ran Li, X Y Li, Chunshan Li, Yixiang Li, Ming Zhou Li, Z Li, Ye Li, Guanglve Li, Zili Li, Xinmei Li, Yihao Li, Qing Run Li, Liling 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, 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, Siming Li, Wenzhe Li, Fengli Li, Song Li, Zihan Li, Hsin-Hua Li, Jin-Long Li, Hongxin Li, You Li, Dongfeng Li, Fa-Hui Li, Xueyang Li, Xuelin Li, Caiyu Li, Zhen-Yuan 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, Yaoqi Li, San-Feng 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, Yongli Li, Z-H 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, Zonghua Li, C X 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, Ming Li, Kangli Li, Runwen Li, Wenbo Li, Yarong Li, Side Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Chuan-Hai Li, Lingxi Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Qin Li, Zhongyu Li, Deyu Li, Zhen-Yu Li, Annie Li, Hansen 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, Xiao Li, Junping Li, Qintong 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, Cui-lan Li, Ruonan 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, Ya-Jun Li, Xue Cheng 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, Ya-Ting Li, Wan Jie Li, L K 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, L-Y Li, Xiuqi 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, Siguang Li, Minglun Li, Yige 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, 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, Gang Li, Ziyu Li, Mengxuan 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, Huaping Li, Ji-Liang Li, C H Li, Bohua Li, Bing Li, Pei-Ying Li, Huihuang Li, Shaobin Li, Yunmin Li, Yanying Li, Gui Lin Li, Ronald Li, Chenrui Li, Shilun Li, Shi-Hong 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, Fengxia Li, Guangxiao Li, Peixin Li, Xueqin Li, Feng-Feng Li, Zu-Ling Li, Jialing Li, Xin Li, Yunjiu Li, Zonghong Li, Dayong 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, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, Zengyang Li, Kaiyuan 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, Yanxi Li, Wan-Xin Li, Xia Li, Meitao Li, Yongjing Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Boxuan Li, Huixue Li, Jiqing Li, Hehua Li, Yucheng Li, Yongqi Li, Qingyuan Li, Fengqi Li, Zhigang Li, Yuqing Li, Guiyang Li, Guo-Qiang Li, Dujuan Li, Yanbo Li, Yuying Li, Shaofei Li, Sanqiang Li, Shaoguang Li, Hongyu Li, Min-Rui 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, Conglin Li, Jutang 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, Yumiao Li, Fengfeng Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Junxu Li, Xiangjun Li, Xingye 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, Cheung Li, Zhenhui Li, Xuelian Li, Zhenming 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, Mei Li, Xuewang Li, Xiangdong Li, Zhenjia Li, Jifang Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiao-Li Li, Xiaoya 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, Weining Li, Wenxi Li, Wu-Jun Li, Chang-hai Li, Yuqiu Li, Yumao Li, Bin-Kui Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Y X Li, Chia 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, Junxian Li, Keqing 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, Yuandong Li, Guisen Li, Dongyang Li, Jinglin Li, Mingfang Li, Honglong Li, Hanmei Li, Chenmeng Li, Changcheng Li, Shiyang Li, Shiyue Li, Jianing Li, Hanbo Li, Dingshan Li, Yinggao Li, Linlin Li, Xinsheng Li, Jin-Wei Li, Jin-Jiang Li, Cheng-Tian Li, Zhi-Xing Li, Chang Li, Yaxi Li, Ming-Han Li, Wei-Ming Li, Wenchao Li, Guangyan Li, Xuesong Li, Zhaosha Li, Jiwei Li, Yongzhen Li, Chun-Quan Li, Weifeng Li, Tao Li, Sichen Li, Wenhui Li, Xiankai Li, Qingsheng Li, Yaxuan Li, Liangji Li, Lixiang Li, Yuchan 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, Y Li, Deqiang Li, Caixia Li, Zipeng Li, Mingyue 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, 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, Xiang-Yu Li, Duan 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, Zong-Xue Li, En-Min Li, Chunya Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Jinhua Li, Min-jun Li, Yuanheng Li, Qian-Qian 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, Junjie Li, Fei-Lin Li, Nuomin Li, Shanglai Li, Shulin Li, Yanyan 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, Rulin Li, Shihong Li, Ya-Pei 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, Hongwei Li, Ding-Jian Li, Danni Li, Xiao-Qiang Li, Yangxue Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Yiqiang Li, Pengyang 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, Huang Li, Shu-Fang Li, Qiusheng Li, Man Li, Juxue 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, Yajun Li, Wei-Ping 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, Fengjuan Li, Monica M Li, W Li, Xianlun Li, Qi Li, Hainan Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Fei Li, Xionghui 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, Xue-Peng Li, Jianang Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Weiyang Li, Feng Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Kaibo Li, Xinxiu Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Shaodan Li, Meng-Hua 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, Ming-Hao Li, Donghe Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Jingqi Li, Menghua 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, Zhuorong Li, Zizhuo Li, X-H Li, Xianrui Li, Lan-Juan Li, Dong Sheng Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Bing-Heng Li, Xiaoman 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, Longyu Li, Jinku 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, Kongdong Li, Yue-Ying Li, Chunhui Li, Tongyao Li, Peiyu Li, Lian Li, Linfeng Li, Yuzhe Li, Xinmiao 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, 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, Shujie Li, Guoxing Li, Zongchao Li, Yanbin Li, Jia Li, Shiliang Li, Haimin Li, Qinrui Li, Sheng-Qing Li, Yiming Li, Lingjie Li, Xiao-Tong Li, Yiwen Li, Tie Li, Baoqi Li, Leyao Li, Wei-Bo Li, Xiaoyi Li, Xiao-Qin Li, Liyan Li, Xinke Li, Xiaokun 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, Shibo Li, Jin 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, 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, Meiyan Li, Qing-Min 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, Gui-Rong 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, 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, T Li, Ruifang Li, Xiao-xu Li, Man-Xiang Li, Yinghui Li, Cong Li, Chengbin Li, Feilong Li, Sin-Lun Li, Yuping Li, Mengfan Li, Weiling Li, Jie Li, Shiyan Li, G Li, Lianbing Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, Wenjian Li, Jialin Li, He Li, Bichun Li, Xiong Bing Li, Hanqin 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, Caolong Li, Chaojie Li, Michelle 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, Jinfang Li, Chenjie Li, Roger Li, Yanming Li, Hong-Lan Li, S L Li, Mengqing Li, Ben-Shang Li, Ming-Kai Li, Xionghao Li, Shunqing 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, Ya-Feng Li, Wenlong Li, Yanjiao Li, Jia-Huan Li, Yuna Li, Xudong Li, Guoxi Li, Xingfang Li, Shengli Li, Shugang 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, Zhenyan Li, H J Li, Ji Xia Li, Meizi Li, Yu-Ye 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, Shun Li, Hui-Jun Li, Xuefei Li, Guojun 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, Zhao Li, Kui Li, Tiegang Li, Yunxu Li, Shuang-Ling Li, Zhong Li, Xiao-Long Li, Xiaofei Li, Hung-Yuan Li, Xuanfei Li, Zilin Li, Zhang Li, Jianxin Li, Mingqiang Li, H Li, Xiaojiao Li, Dongliang Li, Chenxiao Li, Yinzhen Li, Hongjia Li, Xiao-Jing Li, Li-Min Li, Yunsheng Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Daoyuan Li, Baichuan Li, Haibo Li, Wenqi 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, Xiaobai Li, Junsheng Li, Pingping Li, Mingquan Li, Wen-Ya Li, Suran Li, Yunlun Li, Rongxia Li, Yuanfang Li, Yingqin 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, Caihong Li, Hongmin Li, Yajing Li, Peng Peng Li, Kenli Li, Guanglu 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, Fengqiao Li, Di 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, Jun Li, Xiyue Li, Minghua Li, Zhuoran Li, Tianchang Li, Hongru Li, Shiqi Li, Mei-Ya Li, Wuyan Li, Mingzhe Li, Yi-Ling Li, Hongjuan Li, Yingjian 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, Yongsheng Li, Xiujuan 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, 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, He-Zhen Li, G-P Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Jiangan Li, Yu-Kun Li, Hsiao-Fen Li, Weihai Li, Zhaojin Li, Mengjiao Li, Bingxin Li, Wenjuan Li, Chia-Yang Li, Meng-Meng Li, Tianxiang Li, Wenyu 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, Yi-Ning Li, Dandan Li, Yunan Li, Zechuan Li, Zhijun Li, Jiazhou Li, Sherly X Li, Wanling Li, Ya-Ge Li, Yinyan Li, Qijun Li, Rujia Li, Guangli Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Xiaohan Li, Wan-Shan Li, Huijie Li, Zhongwen Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Fengxiang Li, Xuejun Li, Nana Li, Shunwang Li, Yaqing Li, Chao Li, Bingsheng Li, Yaqiao 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, Haoran Li, Hai-Yun 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, 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, Chun-Xu Li, Luyao Li, Weike Li, Desheng Li, Zhixuan Li, Long-Yan 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, Congye Li, Xinrui 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, Xiaoyuan Li, Huanhuan Li, Yanan Li, Zongfang Li, Yang Li, Jiayan 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, Lihua Li, Yilong Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Hai Li, Yuemei Li, Yanli Li, Jingfeng Li, Zhi-Yuan 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, Dingchen Li, YaJie Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, Congjiao Li, Meng-Jun Li, Peining Li, Gaizhen Li, Huilin Li, Liang Li, Songtao Li, Fusheng Li, Huafang Li, Dai Li, Meiyue Li, Chenlu Li, Keshen Li, Kechun Li, Nianyu Li, Yuxin Li, Shaoliang Li, X-L Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Qun Li, Tianye Li, Cuiguang Li, Dongye 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, Tiewei Li, Bing-Hui Li, Rong-Bing Li, Daniel Tian Li, Honggang Li, Jingyong 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, Shishi Li, Hong-Lian Li, Bei-Bei Li, Haitong Li, Xiumei Li, Melody M H Li, Yuli Li, Ruibing 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, Niu Li, Shilin 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, L P Li, Xiaoqin 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, 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, Yuanchuang Li, Biao Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Shengbiao Li, Hong-Yan 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, Zuo-Lin Li, Chenxi 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, Chun-Xiao Li, Shu-Hong Li, Pei-Qin Li, Shuyue Li, Mengying Li, Tongzheng Li, Quan-Zhong Li, Fangyan Li, Yihong Li, Duo Li, Yaxian Li, Dali Li, Zhiming Li, Xuemei Li, Xueting Li, Hongxia Li, Yongting Li, Danyang Li, Zhenjun Li, Tiandong Li, Ren 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, Kun-Ping Li, Xiao-Yao Li, Weirong Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Runzhao Li, Yandong 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, Joyce Li, Suheng Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Zhiqiang Li, Junru Li, Hecheng Li, Jiangchao Li, Haifeng Li, Yueping Li, Changkai 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, Weijie Li, Wei-Qin Li, Guoyin Li, Yaqiang Li, Qingxian Li, Zongyi Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Chengjun Li, Yongpeng Li, Keke Li, Chanyuan Li, Jianbin 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, Kunlong Li, Pengjie Li, Xiaomei Li, Ruijin Li
articles
Yu-Hang Wang, Chang-Ping Li, Jing-Xian Wang +6 more · 2025 · Reviews in cardiovascular medicine · added 2026-04-24
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limi Show more
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limited. In this observational study, 1111 PMI patients (≤55 years) at Tianjin Chest Hospital from 2017 to 2022 were selected and divided according to their SYNTAX scores into a low-risk group (≤22) and medium-high-risk group (>22). These groups were further randomly assigned to a training or test set in a ratio of 7:3. Lasso-logistic was initially used to screen out target factors. Subsequently, Lasso-logistic, random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost) were used to establish prediction models based on the training set. After comparing prediction performance, the best model was chosen to build a prediction system for coronary artery severity in PMI patients. Glycosylated hemoglobin (HbA1c), angina, apolipoprotein B (ApoB), total bile acid (TBA), B-type natriuretic peptide (BNP), D-dimer, and fibrinogen (Fg) were associated with the severity of lesions. In the test set, the area under the curve (AUC) of Lasso-logistic, RF, KNN, SVM, and XGBoost were 0.792, 0.775, 0.739, 0.656, and 0.800, respectively. XGBoost showed the best prediction performance according to the AUC, accuracy, F1 score, and Brier score. In addition, we used decision curve analysis (DCA) to assess the clinical validity of the XGBoost prediction model. Finally, an online calculator based on the XGBoost was established to measure the severity of coronary artery lesions in PMI patients. In summary, we established a novel and convenient prediction system for the severity of lesions in PMI patients. This system can swiftly identify PMI patients who also have severe coronary artery lesions before the coronary intervention, thus offering valuable guidance for clinical decision-making. Show less
📄 PDF DOI: 10.31083/RCM26102
APOB
Defu Tie, Yuting Wang, Jieru Zhou +6 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18121786
BDNF
Taotao Yan, Mingyang Jia, Jiaxi Li +6 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
The Huainan pig (HN) is known for its impressive litter size and exquisite meat quality. However, it also exhibits certain drawbacks such as excessive fat deposition, a relatively low percentage of le Show more
The Huainan pig (HN) is known for its impressive litter size and exquisite meat quality. However, it also exhibits certain drawbacks such as excessive fat deposition, a relatively low percentage of lean meat percentage, and a slower growth rate. Crossbreeding with lean-type breeds, such as Large White, Landrace, and Berkshire can enhance offspring traits, and increase genetic diversity. In this study we employed RNA-seq technology to identify differentially expressed genes (DEGs) in subcutaneous adipose tissue (SAT) samples from HN pigs and their crosses with multiple breeds (with three replicates per group). In the SAT of Huainan × Berkshire pigs (BH), Huainan × Yorkshire pigs (YH), and Huainan × Landrace pigs (LH), numerous key functional genes were identified, including In conclusion, these findings offer valuable insights and provide a foundation for future research on the molecular mechanisms underlying fat deposition in pigs. Show less
📄 PDF DOI: 10.3389/fvets.2025.1545694
ANGPTL4
Hui Lian, Yujie Zhang, Zhao Zhu +11 more · 2025 · Life science alliance · added 2026-04-24
Idiopathic pulmonary fibrosis is a progressive and lethal interstitial lung disease with an unclear etiology and limited treatment options. Fatty acid synthase (FASN) plays various roles in metabolic- Show more
Idiopathic pulmonary fibrosis is a progressive and lethal interstitial lung disease with an unclear etiology and limited treatment options. Fatty acid synthase (FASN) plays various roles in metabolic-related diseases. This study demonstrates that FASN expression is increased in fibroblasts from the lung tissues of patients with idiopathic pulmonary fibrosis and in bleomycin-treated mice. In MRC-5 cells, the inhibition of FASN using shRNA or the pharmacological inhibitor C75 resulted in the increased mRNA and protein expression of glycogen synthase kinase 3β and Axin1, both negative regulators of the Wnt/β-catenin signaling pathway, and promoted autophagy. This outcome led to a decrease in β-catenin protein and mRNA levels, effectively inhibiting the proliferation, migration, and differentiation of lung fibroblasts into myofibroblasts, while inducing the differentiation of fibroblasts into adipofibroblasts. In vivo experiments showed that C75 alleviated bleomycin-induced lung fibrosis in mice by inhibiting β-catenin. In conclusion, these findings suggest that inhibiting FASN in fibroblasts may diminish the activity of the Wnt/β-catenin signaling pathway, providing a potential therapeutic avenue for pulmonary fibrosis. Show less
📄 PDF DOI: 10.26508/lsa.202402805
AXIN1
Yingyi Wang, Haisu Wu, Ruijie Geng +4 more · 2025 · Alpha psychiatry · added 2026-04-24
To explore the molecular mechanisms underlying clozapine-induced metabolic syndrome (MetS) in schizophrenia patients, providing scientific evidence for clinicians to prevent and manage metabolic syndr Show more
To explore the molecular mechanisms underlying clozapine-induced metabolic syndrome (MetS) in schizophrenia patients, providing scientific evidence for clinicians to prevent and manage metabolic syndrome during the treatment of psychiatric disorders. Ten schizophrenia patients with MetS and ten matched controls were recruited from Shanghai Mental Health Center according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia and the 2016 Chinese Adult Dyslipidemia Prevention and Treatment Guidelines for MetS. Peripheral blood RNA sequencing was performed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to pinpoint hub genes. Mendelian randomization (MR) was conducted to validate causal relationship between serum brain-derived neurotrophic factor (BDNF) levels and MetS components. A total of 1019 DEGs were identified, grouped into eight mRNA modules through WGCNA. Key hub genes included Significant differences in gene expression are observed between schizophrenia patients with and without MetS. Individual variability in clozapine-induced MetS may be linked to DEGs. Show less
📄 PDF DOI: 10.31083/AP49352
BDNF
Dongliang Shi, Liang Chen, Chenhao Li +5 more · 2025 · Discover oncology · Springer · added 2026-04-24
This study aims to identify oxidative stress-related genes (OSGs) in papillary thyroid carcinoma (PTC) and their common targets with resveratrol. Oxidative stress-related differentially expressed gene Show more
This study aims to identify oxidative stress-related genes (OSGs) in papillary thyroid carcinoma (PTC) and their common targets with resveratrol. Oxidative stress-related differentially expressed genes (OS-DEGs) were identified by intersecting datasets. The screened core genes were utilized to construct a prognostic model, and their prognostic value, along with their associations with clinical pathological characteristics and immune infiltration, was assessed. Subsequently, the core targets at the intersection of resveratrol and oxidative stress (OS) in PTC were screened, and their binding properties with resveratrol were analyzed. By conducting cross-database analysis, 38 OS-DEGs were identified, and 3 core genes APOE、CDKN2A、APOD were determined. The prognostic model based on core genes exhibited robust prognostic capabilities. The core genes displayed significant correlations with various clinical pathological parameters and a range of immune cells. Additionally, 13 targets of resveratrol for antioxidative stress were screened from databases. 6 high-performing targets, JUN, TGFB1, BCL2, CDKN1A, FOS, ICAM1, were revealed by topological analysis, all exhibiting binding energies lower than - 5.0 kcal/mol. Our study is the pioneering research to provide new insights into the diagnosis, prognosis, and treatment of PTC through the analysis of OSGs, presenting potential clinical implications. Furthermore, this research reveals the molecular functions associated with resveratrol and its pharmacological targets regulating OS in PTC for the first time. Show less
📄 PDF DOI: 10.1007/s12672-025-04170-y
APOE
Jingxian Yu, Mingjie Wu, Yongqi Liang +3 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profil Show more
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profiles of death anxiety in Chinese youth and examine the predictive roles of self-esteem, perceived social support, and security. We conducted a cross-sectional survey of 623 young adults ( Three latent death anxiety profiles emerged, High Death Anxiety (56.2%), Moderate Cognition and Low Death Anxiety (8.8%), and Low Cognition and Moderate Death Anxiety (35%). Higher self-esteem ( Death anxiety among young adults is heterogeneous, influenced by distinct psychological profiles and demographic factors. Interventions should prioritize enhancing self-esteem, social support networks, and security to mitigate death anxiety, especially in high-risk subgroups. Future research should employ longitudinal designs and cross-cultural samples to validate causal pathways and refine targeted strategies. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1594720
LPA
Xiaolin Yu, Yujuan Yuan, Xiangyu Dong +5 more · 2025 · Annals of medicine · Taylor & Francis · added 2026-04-24
The association between low-density lipoprotein (LDL) cholesterol and increased mortality risk has been well-documented, yet apolipoprotein B (apoB) is regarded as a more precise risk indicator. Howev Show more
The association between low-density lipoprotein (LDL) cholesterol and increased mortality risk has been well-documented, yet apolipoprotein B (apoB) is regarded as a more precise risk indicator. However, a comprehensive analysis integrating both markers in relation to mortality risk remains unreported. This study aimed to investigate the relationship between LDL cholesterol levels and mortality across varying apoB concentrations within the general population. Data from 15,380 participants in the 2005-2016 National Health and Nutrition Examination Survey (NHANES) were utilized to construct Cox regression models and apply restricted cubic splines, assessing the association between LDL cholesterol and mortality across distinct apoB stratifications. The study cohort had a median (IQR) age of 46.0 (32.0, 60.0) years, with 7949 (51.8%) males. During a median follow-up of 101.0 months (IQR: 67-137), 1771 (8.8%) all-cause mortality events were observed; 443 (2.1%) deaths were attributed to cardiovascular diseases, while 109 (0.5%) resulted from cerebrovascular diseases. Low apoB and LDL-cholesterol levels were independently linked to an elevated risk of all-cause and cardiovascular mortality. Compared with participants having apoB <90 mg/dL and LDL-cholesterol levels between 100-129 mg/dL, those with LDL-cholesterol <70 mg/dL (HR, 1.81; 95%CI: 1.39-2.36) and 70-99 mg/dL (HR, 1.28; 95%CI: 1.01-1.62) demonstrated a higher risk of all-cause mortality. Additionally, reduced apoB levels contributed to an increased risk of cardiovascular mortality among individuals with low LDL-cholesterol levels. Low apoB and LDL-cholesterol levels were associated with heightened all-cause and cardiovascular mortality risk in the general population. Conversely, high apoB and low LDL-cholesterol levels did not correlate with increased mortality risk. Show less
📄 PDF DOI: 10.1080/07853890.2025.2529565
APOB
Yu Liu, Xiaojia Fu, Jing Li +3 more · 2025 · Scientific reports · Nature · added 2026-04-24
Traumatic brain injury (TBI) is more common than ever and is becoming a global public health issue. A variety of secondary brain injuries occur after TBI, including ferroptosis characterized by iron-d Show more
Traumatic brain injury (TBI) is more common than ever and is becoming a global public health issue. A variety of secondary brain injuries occur after TBI, including ferroptosis characterized by iron-dependent lipid peroxidation. Gallic acid is a kind of traditional Chinese medicine, which has many biological effects such as anti-inflammatory and antioxidant. We further investigated whether Gallic acid can improve the neurological impairment caused by ferroptosis after TBI by targeting APOC3. Weighted gene coexpression network analyses (WGCNA) and 3 kinds of machine-learning algorithms were used to find the potential biomarkers. Then the HERB database was used to select the Chinese herb that acted on the target gene APOC3. Finally, we selected Gallic acid as a drug targeting APOC3 and verified by Western blotting. The effect of Gallic acid on the improvement of neurological function was studied by Nissl staining and FJB staining. Finally, the effect of Gallic acid on the cognitive ability of TBI mice was explored through behavioral experiments. Gallic acid can inhibit the expression level of APOC3 and thus inhibit the level of ferroptosis after TBI. It can also reduce the degeneration of nerve tissue by inhibiting ferroptosis and improve the neurological function deficit. The behavioral experiment proved that Gallic acid can alleviate the behavioral cognitive impairment caused by TBI. Gallic acid can reduce ferroptosis by inhibiting APOC3, and then alleviate neurological impairment after TBI. Show less
📄 PDF DOI: 10.1038/s41598-025-92383-0
APOC3
Xiaolin Zeng, Yuni Long, Gang Li +6 more · 2025 · Journal of cellular physiology · Wiley · added 2026-04-24
Excessive inflammation is a capital cause of scar formation and inflammation microenvironment that result in challenge of axonal regeneration after spinal cord injury (SCI). Macrophages and astrocytes Show more
Excessive inflammation is a capital cause of scar formation and inflammation microenvironment that result in challenge of axonal regeneration after spinal cord injury (SCI). Macrophages and astrocytes play important roles in the inflammatory response. Tip cells, a critical endothelial sub-population, play pivotal roles in post-injury vascular regeneration. Nevertheless, their characteristics in SCI remain poorly documented. This study based on single cell RNA sequencing (scRNA-seq) and in vitro experiment, investigates the effects of tip cells on astrocytes and macrophages. For astrocytes, tip cells can recruit astrocytes to migrant, contribute to the formation of fence-like structure of astrocytes, finally inhibit the diffusion of inflammation via the Angptl4-Sdc4 ligand-receptor pathway. For macrophages, similarly through the Angptl4-Sdc4 ligand-receptor pathway, tip cells can promote macrophages to polarize more toward the M2 phenotype and inhibit their polarization toward M1 phenotype, thus alleviate the inflammatory response. Tip cells after SCI exhibit conserved ribosomal protein expression, implicating ribosome-dependent signaling in their function. These finding highlight the critical role of tip cells in microenvironment after SCI, offering a potential treatment target for SCI. Show less
no PDF DOI: 10.1002/jcp.70088
ANGPTL4
Qing Li, Zhenyu Zhou, Xiaoying Li +1 more · 2025 · Mutation research · Elsevier · added 2026-04-24
Cervical cancer (CC) is a major cause of morbidity and mortality in women, with complex etiology and progression. Diacylglycerol kinases (DGKs) are pivotal in lipid metabolism. Although diacylglycerol Show more
Cervical cancer (CC) is a major cause of morbidity and mortality in women, with complex etiology and progression. Diacylglycerol kinases (DGKs) are pivotal in lipid metabolism. Although diacylglycerol kinase beta (DGKβ) is well-studied in neurology, its role in cancer, especially CC, remains underexplored. This study aimed to explore DGKβ's role and mechanism in CC. Bioinformatics analysis was employed to identify genes differentially expressed in CC, with western blot confirming DGKβ expression in CC cells. The role of DGKβ was examined through small interfering RNA-mediated gene silencing, proliferation tests, migration and invasion assays, and angiogenesis studies. In-depth bioinformatics explored DGKβ-regulated downstream targets and pathways. Pathological assessment elucidated the impact of DGKβ and angiopoietin 4 (ANGPT4) on CC samples. Our data identified DGKβ as a promising candidate gene in the context of CC. This conclusion stemmed from the notable observation that DGKβ exhibited a heightened expression in CC cell lines. Notably, the silencing of DGKβ resulted in the suppression of CC cell proliferation, invasion, migration, as well as the epithelial-mesenchymal transition processes. Additional bioinformatics analysis delving into DGKβ-associated genes revealed ANGPT4 as a downstream target gene of DGKβ, which is capable of modulating angiogenesis and possesses multiple cellular functions related to cell survival, proliferation, and migration. Most significantly, our findings also demonstrated that both DGKβ and ANGPT4 were overexpressed in clinical specimens of CC. This study uncovered an oncogenic role for DGKβ in CC and identified a potential regulatory link between DGKβ and ANGPT4 in tumor angiogenesis. These findings provided promising directions for developing new diagnostic and therapeutic approaches for CC. Show less
no PDF DOI: 10.1016/j.mrfmmm.2025.111913
ANGPTL4
Juan Shen, Weiming Liang, Ruizhen Zhao +33 more · 2025 · iMeta · Wiley · added 2026-04-24
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and sp Show more
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and specific pathogen-free (SPF) mice using spatial transcriptomics, single-cell RNA sequencing, and targeted bile acid metabolomics across multiple organs, we systematically assessed how the gut microbiota's absence affected organ morphology, immune homeostasis, bile acid, and lipid metabolism. Through integrated analysis, we detect marked aberration in B, myeloid, and T/natural killer cells, altered mucosal zonation and nutrient uptake, and significant shifts in bile acid profiles in feces, liver, and circulation, with the alternate synthesis pathway predominant in GF mice and pronounced changes in bile acid enterohepatic circulation. Particularly, autophagy-driven lipid droplet breakdown in ileum epithelium and the liver's zinc finger and BTB domain-containing protein (ZBTB20)-Lipoprotein lipase (LPL) (ZBTB20-LPL) axis are key to plasma lipid homeostasis in GF mice. Our results unveil the complexity of microbiota-host interactions in the crosstalk between commensal gut bacteria and the host. Show less
📄 PDF DOI: 10.1002/imt2.272
LPL
Shan Geng, Shan Yang, Xuejiao Tang +10 more · 2025 · The EMBO journal · Nature · added 2026-04-24
Communication of gut hormones with the central nervous system is important to regulate systemic glucose homeostasis, but the precise underlying mechanism involved remain little understood. Nesfatin-1, Show more
Communication of gut hormones with the central nervous system is important to regulate systemic glucose homeostasis, but the precise underlying mechanism involved remain little understood. Nesfatin-1, encoded by nucleobindin-2 (NUCB2), a potent anorexigenic peptide hormone, was found to be released from the gastrointestinal tract, but its specific function in this context remains unclear. Herein, we found that gut nesfatin-1 can sense nutrients such as glucose and lipids and subsequently decreases hepatic glucose production. Nesfatin-1 infusion in the small intestine of NUCB2-knockout rats reduced hepatic glucose production via a gut - brain - liver circuit. Mechanistically, NUCB2/nesfatin-1 interacted directly with melanocortin 4 receptor (MC4R) through its H-F-R domain and increased cyclic adenosine monophosphate (cAMP) levels and glucagon-like peptide 1 (GLP-1) secretion in the intestinal epithelium, thus inhibiting hepatic glucose production. The intestinal nesfatin-1 -MC4R-cAMP-GLP-1 pathway and systemic gut-brain communication are required for nesfatin-1 - mediated regulation of liver energy metabolism. These findings reveal a novel mechanism of hepatic glucose production control by gut hormones through the central nervous system. Show less
📄 PDF DOI: 10.1038/s44318-024-00300-4
MC4R
Weiyao Zhu, Yu Wang, Ming Qin +3 more · 2025 · Aging and disease · added 2026-04-24
Alzheimer's disease (AD) represents a neurodegenerative condition characterized by steadily increasing prevalence and incidence, arising significant challenge to both patients and social insurance. Ho Show more
Alzheimer's disease (AD) represents a neurodegenerative condition characterized by steadily increasing prevalence and incidence, arising significant challenge to both patients and social insurance. However, the etiology of AD remains controversial so far, and pathogenesis is far more complicated. Presently, no definitive therapeutic methodologies were available for AD, and only partial symptomatic relief can be achieved. Consequently, early diagnosis and intervention are emergently needed for AD patients. The diagnostic criteria for AD are continuously evolving, and biomarker testing is becoming increasingly critical for diagnosis. Currently, the diagnosis of AD primarily relies on the detection of pathological proteins through cerebrospinal fluid (CSF) testing and positron emission tomography (PET). However, factors such as high costs, operational contraindications, and invasiveness limited the application of these technologies, making them particularly challenging to implement in large-scale clinical trials and screenings. Core fluid biomarkers for AD including β-amyloid (Aβ), phosphorylated tau protein (p-tau), total tau protein (t-tau), and their combinations were found in CSF. Although these biomarkers were demonstrated with significant specificity and sensitivity, challenges remain high concerning the collection of CSF. Blood-derived biomarkers for Aβ and tau proteins are essential for preliminary screening, diagnosis, and monitoring of AD. Additionally, other bodily fluids such as saliva, urine, and tears have been investigated for their potential as biomarkers, offering unique characteristics and applications. Emerging biomarkers, including neurofilament light chain (NfL), neurogranin (Ng), Beta-site APP cleaving enzyme 1 (BACE1), synaptosome associated protein 25 (SNAP-25), as well as inflammation-related and gene-related factors, provided valuable insights into the diagnosis and pathogenesis of AD from diverse perspectives. Despite the substantial progress made in AD biomarker research, there are still baskets of limitations concerning the complication of the disease. The current review focused on the reported literature to summarize the biomarkers associated with AD. By critically analyzing studies published over the past decade, we aimed to strengthen the recent research progress, theoretical frameworks, and unresolved challenges related to AD biomarkers. Show less
no PDF DOI: 10.14336/AD.2025.0761
BACE1
Chunyu Yang, Xin Chai, Yachen Wang +8 more · 2025 · Cardiovascular diabetology · BioMed Central · added 2026-04-24
Existing evidence suggests that elevated 1-hour post-load plasma glucose (1-h PG ≥ 8.6 mmol/L) during an oral glucose tolerance test (OGTT) is associated with atherogenic lipid parameters which are li Show more
Existing evidence suggests that elevated 1-hour post-load plasma glucose (1-h PG ≥ 8.6 mmol/L) during an oral glucose tolerance test (OGTT) is associated with atherogenic lipid parameters which are linked to an increased risk of cardiovascular disease (CVD). However, it remains unclear whether normal glucose tolerance (NGT) individuals with elevated 1-h PG (NGT-1hPG-high) should still be considered low-risk. Therefore, this study aims to demonstrate comprehensive lipid characteristics in individuals with different glycemic status stratified by 1-h PG, with a particular focus on those with NGT-1hPG-high. This cross-sectional study included individuals aged 25-55 years with high-risk of diabetes from the Daqing Diabetes Prevention Study II (Daqing DPS-II). Individuals were categorized into different glycemic status based on the World Health Organization's 1999 criteria and the International Diabetes Federation's 2024 position statement on 1-h PG. Traditional (TC, TG, HDL-C, LDL-C) and non-traditional lipid parameters [ApoA-1, ApoB, sdLDL-C, Lp(a), non-HDL-C, remnant cholesterol (RC), ApoB/ApoA-1, LDL-C/ApoB] were measured. Dyslipidemia was defined according to the 2023 Chinese Guidelines for Lipid Management. The China-PAR equation was used to estimate 10-year CVD risk. Spearman's correlation coefficients were calculated to evaluate the correlation between lipid parameters and 10-year CVD risk. Logistic and multiple linear regression models were performed to assess the association between 1-h PG and dyslipidemia as well as lipid parameters adjusting for covariates. Among 2 469 individuals, 22.7% had NGT with normal 1-h PG (NGT-1hPG-normal), 19.9% had NGT-1hPG-high, 2.6% had prediabetes with normal 1-h PG (PDM-1hPG-normal), 34.2% had prediabetes with elevated 1-h PG (PDM-1hPG-high), and 20.6% had newly diagnosed diabetes. The prevalence of dyslipidemia did not significantly differ between NGT-1hPG-high and PDM-1hPG-high (OR = 1.13, 95%CI: 0.88-1.44, P > 0.05). Higher 1-h PG levels were consistently associated with an atherogenic lipid profile, characterized by increased TC, TG, LDL-C, ApoB, sdLDL-C, non-HDL-C, RC and ApoB/ApoA-1, along with decreased ApoA-1, HDL-C and LDL-C/ApoB (all P < 0.05). Among lipid parameters, TG, sdLDL-C, RC, ApoB/ApoA-1, LDL-C/ApoB and HDL-C showed the strongest correlation with 10-year CVD risk, with Spearman's correlation coefficients of 0.41, 0.38, 0.35, 0.31, - 0.37 and - 0.36, respectively. In the NGT-1hPG-high, TG, sdLDL-C, and ApoB/ApoA-1 levels were significantly higher, while HDL-C and LDL-C/ApoB levels were significantly lower compared to counterparts with NGT-1hPG-normal (all P < 0.05). Moreover, except for TG and RC (both P < 0.01), the majority of lipid parameter levels in NGT-1hPG-high did not significantly differ from those in PDM (all P > 0.05). NGT-1hPG-high exhibited a similar atherogenic lipid profile to that observed in PDM. 1-h PG could serve as a potential indicator for the early identification of at-risk individuals who may otherwise go undetected among NGT population. Show less
📄 PDF DOI: 10.1186/s12933-025-02722-8
APOB
Yuemei Zhang, Yuxin Cao, Yongxin Sun +12 more · 2025 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
The activation of blood monocytes and the infiltration of monocyte-derived macrophages into the vessel walls are the central part of atherosclerosis. However, the mechanisms underlying the processes r Show more
The activation of blood monocytes and the infiltration of monocyte-derived macrophages into the vessel walls are the central part of atherosclerosis. However, the mechanisms underlying the processes remain unclear. Here, we report that G-protein signaling modulator 1 (GPSM1) plays a critical role in atherogenesis. We found that GPSM1 expression in lesional macrophages was increased during atherosclerosis development both in mice and humans. Myeloid-specific GPSM1 ablation protects mice against atherosclerosis and reduces aortic inflammation in both Show less
no PDF DOI: 10.1073/pnas.2517531122
APOE
Xiao-Jie Yang, Jiang Li, Jing-Yuan Chen +6 more · 2025 · Sheng li xue bao : [Acta physiologica Sinica] · added 2026-04-24
The current study aimed to clarify the roles of apolipoprotein A5 (ApoA5) and milk fat globule-epidermal growth factor 8 (Mfge8) in regulating myocardial lipid deposition and the regulatory relationsh Show more
The current study aimed to clarify the roles of apolipoprotein A5 (ApoA5) and milk fat globule-epidermal growth factor 8 (Mfge8) in regulating myocardial lipid deposition and the regulatory relationship between them. The serum levels of ApoA5 and Mfge8 in obese and healthy people were compared, and the obesity mouse model induced by the high-fat diet (HFD) was established. In addition, primary cardiomyocytes were purified and identified from the hearts of suckling mice. The 0.8 mmol/L sodium palmitate treatment was used to establish the lipid deposition cardiomyocyte model Show less
no PDF
APOA5
Guoshuai Xu, Qinghong Zhang, Renjia Cheng +2 more · 2025 · Autophagy · Taylor & Francis · added 2026-04-24
Macropinocytosis is a nonselective form of endocytosis that allows cancer cells to largely take up the extracellular fluid and its contents, including nutrients, growth factors, etc. We first elaborat Show more
Macropinocytosis is a nonselective form of endocytosis that allows cancer cells to largely take up the extracellular fluid and its contents, including nutrients, growth factors, etc. We first elaborate meticulously on the process of macropinocytosis. Only by thoroughly understanding this entire process can we devise targeted strategies against it. We then focus on the central role of the MTOR (mechanistic target of rapamycin kinase) complex 1 (MTORC1) in regulating macropinocytosis, highlighting its significance as a key signaling hub where various pathways converge to control nutrient uptake and metabolic processes. The article covers a comprehensive analysis of the literature on the molecular mechanisms governing macropinocytosis, including the initiation, maturation, and recycling of macropinosomes, with an emphasis on how these processes are hijacked by cancer cells to sustain their growth. Key discussions include the potential therapeutic strategies targeting macropinocytosis, such as enhancing drug delivery via this pathway, inhibiting macropinocytosis to starve cancer cells, blocking the degradation and recycling of macropinosomes, and inducing methuosis - a form of cell death triggered by excessive macropinocytosis. Targeting macropinocytosis represents a novel and innovative approach that could significantly advance the treatment of cancers that rely on this pathway for survival. Through continuous research and innovation, we look forward to developing more effective and safer anti-cancer therapies that will bring new hope to patients. Show less
no PDF DOI: 10.1080/15548627.2025.2452149
PIK3C3
Kuangyang Chen, Yifeng Pan, Yaqiong Wang +8 more · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
Atherosclerosis, a progressive inflammatory disease and the leading cause of cardiovascular disease (CVD), remains a global health burden due to the lack of effective early therapeutic interventions. Show more
Atherosclerosis, a progressive inflammatory disease and the leading cause of cardiovascular disease (CVD), remains a global health burden due to the lack of effective early therapeutic interventions. Although growing evidence highlights the involvement of plasma proteins in atherogenesis, their causal contributions to disease pathogenesis are poorly understood. To address this gap, we conducted a proteome-wide Mendelian randomization (MR) analysis using cis-pQTLs (cis-protein quantitative trait loci) from the deCODE and UKB-PPP cohorts (~90,000 individuals) as instrumental variables. We integrated colocalization analysis, summary-data-based MR (SMR), and HEIDI tests to systematically prioritize causal plasma proteins. Key findings were replicated in the CARDIOGRAMplusC4D (coronary artery disease, CAD) and FinnGen (CVD) cohorts. Functional validation was performed through phenome-wide association studies (PheWAS), single-cell transcriptomics, histological staining, and ELISA assays to characterize protein expression patterns in specific cell types and tissues. Among 2,711 plasma proteins analyzed, 28 showed strong genetic associations with atherosclerosis. Of these, five proteins (ADK, ANGPTL4, CD4, MGAT1, SYT11) met strict validation criteria through colocalization (posterior probability of colocalization, PP.H4 > 0.8) and SMR. Subsequent replication using MR and PheWAS further confirmed the causal roles of ADK, CALB2, and COMT in CAD and other CVD outcomes. Notably, CALB2 was specifically enriched in mast cells within atherosclerotic plaques and adipose tissue, and plasma levels were significantly elevated in patients with severe carotid artery stenosis (CAS). This study identifies 28 novel therapeutic targets for atherosclerosis using a rigorous multi-omics approach. Our findings establish CALB2 as a promising biomarker and therapeutic target, particularly in severe CAS, by linking genetic evidence to cell-type-specific expression and clinical phenotypes. These insights pave the way for precision medicine approaches in the prevention and treatment of CVD. The online version contains supplementary material available at 10.1186/s12967-025-07269-6. Show less
📄 PDF DOI: 10.1186/s12967-025-07269-6
ANGPTL4
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
Ping Huang, Yong Zhao, Haiyan Wei +8 more · 2025 · International journal of chronic obstructive pulmonary disease · added 2026-04-24
In preliminary research and literature review, we identified a potential link between chronic obstructive pulmonary disease (COPD) and lipid metabolism. Therefore, this study employed Mendelian random Show more
In preliminary research and literature review, we identified a potential link between chronic obstructive pulmonary disease (COPD) and lipid metabolism. Therefore, this study employed Mendelian randomization (MR) analysis to investigate the potential causal connection between blood lipids and COPD. A genome-wide association study (GWAS) on COPD was conducted, encompassing a total of 112,583 European participants from the MRC-IEU. Additionally, extensive UK Biobank data pertaining to blood lipid profiles within European cohorts included measurements for low-density lipoprotein cholesterol (LDL-C) with 440,546 individuals, high-density lipoprotein cholesterol (HDL-C) with 403,943 individuals, triglycerides (TG) with 441,016 individuals, total cholesterol (TC) with 187,365 individuals, apolipoprotein A-I (apoA-I) with 393,193 individuals, and apolipoprotein B (apoB) with 439,214 individuals. Then, MR analyses were performed for lipids and COPD, respectively. The primary analytical technique employed was the inverse-variance weighted (IVW) approach, which included a 95% confidence interval (CI) to calculate the odds ratio (OR). Additionally, a sensitivity analysis was conducted to assess the dependability of the MR analysis outcomes. MR analysis was primarily based on IVW, unveiled a causal link between COPD and LDL-C (OR=0.994, 95% CI (0.989, 0.999), P=0.019), TG (OR=1.005, 95% CI (1.002, 1.009), P=0.006), and apoA-I (OR=0.995, 95% CI (0.992, 0.999), P=0.008), in addition, no causal link was found with HDL-C, TC, apoB. Sensitivity analysis demonstrated the robustness of these causal relationships. However, through multivariate MR(MVMR) and multiple testing correction, LDL-C and TG had no causal effect on the outcome. ApoA-I remained a protective factor for the risk of COPD (OR=0.994, 95% CI (0.990-0.999), P=0.008). Through MR analysis, this study offers evidence of a causal link between apoA-I with COPD. This further substantiates the potential role of lipid metabolism in COPD, and has significant clinical implications for the prevention and management of COPD. Show less
📄 PDF DOI: 10.2147/COPD.S476833
APOB
Yanting Zhang, Fei Cheng, Lixia Li · 2025 · Medicine · added 2026-04-24
Prostate cancer is epithelial malignant prostate hyperplasia caused by a tumor. We found prostate cancer GSE141551 and GSE200879 profiles from gene expression omnibus database, followed by differentia Show more
Prostate cancer is epithelial malignant prostate hyperplasia caused by a tumor. We found prostate cancer GSE141551 and GSE200879 profiles from gene expression omnibus database, followed by differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis, protein-protein interaction analysis, gene function enrichment analysis, and comparative toxicology database analysis. Finally, the gene expression heat map was drawn, and miRNA information regulating core DEGs was retrieved. A total of 1151 DEGs were found, most of them focusing on systematic development, cell development, cell differentiation, regulation of multicellular biological processes, anatomical morphogenesis, MAPK signaling pathway, proteoglycans in cancer, fluid shear stress, and atherosclerosis. The core genes (MYL9, TAGLN, SMTN, CNN1, MYH11, MYLK, MYOCD, ACTC1, LMOD1, and TPM2) obtained in end are all lowly expressed in prostate cancer samples and are associated with hypertension, tumor metastasis, prostate tumors, and tumor aggressiveness. LMOD1 and SMTN are lowly expressed in prostate cancer and may be used as markers in prostate cancer nursing. Show less
📄 PDF DOI: 10.1097/MD.0000000000041357
LMOD1
Yajie Zhang, Yang Li, Wentao Huang +7 more · 2025 · International journal of surgery (London, England) · added 2026-04-24
Gastroesophageal reflux disease (GERD) and asthma are commonly co-occurring conditions, with shared genetic factors identified. However, the specific loci and the influence of common genetic architect Show more
Gastroesophageal reflux disease (GERD) and asthma are commonly co-occurring conditions, with shared genetic factors identified. However, the specific loci and the influence of common genetic architecture remain undefined. We obtained genome-wide association study (GWAS) summary statistics for GERD (71 522 cases and 261 079 controls) and asthma (56 167 cases and 352 255 controls). Using linkage disequilibrium score regression (LDSC), we assessed genetic correlations between GERD and asthma. Bidirectional Mendelian randomization (MR) was performed to investigate potential causal relationships, followed by cross-trait GWAS meta-analysis and colocalization analysis to identify shared risk loci. Additionally, summary-data-based MR and transcriptome-wide association study were conducted to pinpoint common functional genes. Finally, we analyzed gene expression profiles in both healthy individuals and GERD patients using esophageal single-cell RNA sequencing (scRNA-seq) data. We identified a significant genetic correlation between GERD and asthma ( rg  = 0.37, P = 6.19 × 10 -38 ) and a significant causal effect of GERD on asthma [odds ratio (OR) = 1.22, P = 1.54 × 10 -5 ]. Cross-trait meta-analyses revealed 56 shared risk loci between GERD and asthma, including 51 loci that were newly identified. Three loci (rs61937247, rs7960225, and rs769670) exhibited evidence of colocalization. Gene-level analyses pinpointed three novel shared genes ( RBM6, SUOX , and MPHOSPH9 ) between GERD and asthma. scRNA-seq analysis uncovered heightened expression of these genes in immune cells of patients diagnosed with GERD. Our study has discovered novel shared genetic loci and candidate genes between GERD and asthma, providing further insights into the genetic susceptibility of comorbidity and potential mechanisms of the two diseases. Show less
no PDF DOI: 10.1097/JS9.0000000000003283
RBM6
Zhaowei Zhu, Rui Kuang, Shouwen Su +9 more · 2025 · Cellular & molecular biology letters · BioMed Central · added 2026-04-24
Phenotypic transformation of Schwann cells (SCs) plays a crucial role in nerve regeneration. Previous studies have demonstrated that Runx2 significantly influences the biological behavior of SCs. None Show more
Phenotypic transformation of Schwann cells (SCs) plays a crucial role in nerve regeneration. Previous studies have demonstrated that Runx2 significantly influences the biological behavior of SCs. Nonetheless, the regulatory mechanisms that govern its epigenetic regulation are not yet fully elucidated. To facilitate this investigation, an adenovirus for the overexpression of Runx2 was constructed. Healthy adult Sprague-Dawley rats, weighing between 100 and 150 g and irrespective of sex, were randomly selected for the study. After establishing a model of sciatic nerve crush injury, tissue samples were harvested for histological analysis at both 4 and 7 days post-injury. In vitro, an Runx2-overexpressing SC line was established. Thorough analysis of transcriptome data, coupled with CUT&Tag sequencing of histones and transcription factors in SCs following Runx2 overexpression, was conducted. Additionally, single-cell RNA sequencing data from GSE216665 were incorporated to elucidate the mechanistic role of Runx2. The findings were subsequently validated through dual-luciferase assays. Following nerve crush injury, Runx2-positive SCs were identified at the injury site. Through comprehensive multiomics analysis, we discovered that lipid metabolism was disrupted in Runx2-overexpressing SCs. Further investigation established a detailed super-silencer landscape in these cells, revealing that elevated Runx2 levels form a super-silencer within the transcriptional regulatory region of the Lpl gene, thereby downregulating Lpl expression. Runx2 can modulate the biological behavior of SCs by forming super-silencers that interfere with the expression of lipid metabolism genes, such as Lpl, thereby altering the metabolic capacity of SCs. Show less
📄 PDF DOI: 10.1186/s11658-025-00796-6
LPL
Changqing He, Youheng Huang, Silvana Rahayu +7 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
The leopard coral grouper (Plectropomus leopardus), an increasingly important species in marine aquaculture, has garnered significant research interest due to its high market value. Despite extensive Show more
The leopard coral grouper (Plectropomus leopardus), an increasingly important species in marine aquaculture, has garnered significant research interest due to its high market value. Despite extensive research on ovarian growth and development in fish, the molecular mechanisms governing lipid droplet formation and lipid deposition in P. leopardus remain poorly understood. In this study, we conducted transcriptomic analyses of P. leopardus ovaries at three developmental stages: primary growth (PG), pre-vitellogenesis (PV), and mid-vitellogenesis (MV). A total of 534,847,090 raw reads were obtained from nine cDNA libraries, leading to the identification of 19,155 genes with 13,817 genes expressed at all stages. Differential analysis showed that 1012, 2609, and 4039 genes were up-regulated, while 168, 277, and 577 genes were down-regulated in the three comparisons, respectively. Functional enrichment analyses highlighting the critical roles of differentially expressed genes (DEGs) in lipid transport (such as fatp1, fatp4, fatp6, apoeb, lpl and fabps), fatty acid metabolism (such as elovl6, acsl1, dgat2 and gpat4) and phospholipid metabolism (such as ept1, chka and pla2g15). These findings underscore their contribution to lipid droplet formation and deposition. Furthermore, key signaling pathways, including Wnt, mTOR, PPAR and PI3K/Akt, were implicated in regulating these processes. The reliability of the RNA-seq data was confirmed through qPCR validation of 10 lipid-related genes. Based on these results, we propose a model for lipid droplet formation and lipid deposition during ovarian development in P. leopardus. This study advances our understanding of ovarian development in P. leopardus and provides a foundation for future research on marine fish reproduction, with potential applications in species conservation and aquaculture management. Show less
no PDF DOI: 10.1016/j.cbd.2025.101534
LPL
Pallav Bhatnagar, Nadia N Ahmad, Xuan Li +3 more · 2025 · Nature medicine · Nature · added 2026-04-24
The magnitude of weight reduction in the SURMOUNT-1 trial of the dual GLP-1 and GIP receptor agonist tirzepatide suggests that this treatment may be particularly effective in addressing the treatment Show more
The magnitude of weight reduction in the SURMOUNT-1 trial of the dual GLP-1 and GIP receptor agonist tirzepatide suggests that this treatment may be particularly effective in addressing the treatment needs of people with severe obesity (body mass index >40 kg m Show less
📄 PDF DOI: 10.1038/s41591-025-03913-2
MC4R
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
Lingyan Li, Xingjie Wu, Qianqian Guo +9 more · 2025 · Journal of pharmaceutical analysis · Elsevier · added 2026-04-24
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, over Show more
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in vascular endothelial cells and estrogen receptor alpha (ERα) protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation Show less
📄 PDF DOI: 10.1016/j.jpha.2024.101182
APOA5
Wei Zhang, Na Li · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Individuals with bipolar disorder (BD) exhibit a significantly increased risk of cardiovascular disease, yet the specific mechanisms linking heart failure (HF) and BD remain poorly understood. This st Show more
Individuals with bipolar disorder (BD) exhibit a significantly increased risk of cardiovascular disease, yet the specific mechanisms linking heart failure (HF) and BD remain poorly understood. This study aimed to identify common potential diagnostic biomarkers associated with both conditions. Differentially expressed genes (DEGs) were analyzed separately in HF (GSE57338) and BD (GSE5389) datasets. Key module genes for each condition were identified through co-expression network analysis and intersected with DEGs to pinpoint candidate genes. Subsequently, a protein-protein interaction (PPI) network, receiver operating characteristic (ROC) analysis, and expression validation were employed to identify potential diagnostic biomarkers. Gene set enrichment analysis (GSEA) and drug predictions were also conducted. Clinical validation of biomarker expression was performed via quantitative polymerase chain reaction (qPCR). A total of 44 candidate genes were identified as being associated with both HF and BD. Six potential diagnostic biomarkers ( This study preliminarily explored the common molecular mechanisms between HF and BD, and identified 6 potential biomarkers for early detection, providing a solid theoretical basis for future research on HF and BD. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1627105
EXT1
Meng Wang, Zhao Liu, Shuxun Ren +16 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.105894
BCKDK