👤 Meiyan 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, Rongqing Li, Xihao Li, Ziming Li, Hang Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Xiao-Lin Li, Yicun 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, Ran Li, Peilin Li, X Y Li, Chunshan Li, Ming Zhou Li, Yixiang Li, Ye Li, Guanglve Li, Z Li, Zili Li, Xinmei Li, Yihao Li, Liling Li, Qing Run Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Qiankun Li, Kailong Li, Shengxu Li, Shisheng Li, Sai Li, Guangwen Li, Hua Li, Xiuli Li, Dongmei Li, Yulong Li, Ru-Hao Li, Zhi-Peng Li, Lanzhou 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, Fa-Hui Li, Caiyu Li, Xueyang Li, Xuelin 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, Mingxu Li, Chen-Xi Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Xiaoqing Li, Jinlin Li, Linke Li, 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, 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, Huanan Li, Jingya 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, Wenbo Li, Runwen Li, Yarong Li, Side Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Lingxi Li, Chuan-Hai 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, Qintong Li, Xiao Li, Junping Li, PeiQi Li, Naishi Li, Xiaobing Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Pan Li, Shengchao A Li, Jiaying Li, Jun-Jie Li, Ruonan Li, Cui-lan Li, Shuhao Li, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Chengquan Li, Suyan 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, Wan Jie Li, L K Li, Ya-Ting Li, Dongbiao Li, Aimin Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, Peiyun Li, Xiuqi Li, L-Y Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, Demin Li, Haipeng Li, Chuan Li, Changhong Li, Ze-An Li, Jianmin Li, Yu Li, Minhui Li, Yvonne Li, Yiwei Li, Zhichao Li, Jiayuan Li, Xiangzhe Li, Minglun Li, Yige Li, Siguang 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, Xiangyun Li, Si Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Zijing Li, Dengke Li, Wentao Li, Yuchuan 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, Gang Li, Mengxuan Li, Panyuan Li, Ziyu Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, 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, 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, Zhimei Li, Jiao 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, Chengjian Li, Chengyun 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, Zhaoshui Li, Yali Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, Kaiyuan Li, Mangmang Li, Zengyang Li, Chunyan Li, Runzhen Li, Xiaopeng Li, Xi-Hai Li, MengGe Li, Xuezhong Li, Anan Li, Luying Li, Jiajv Li, Pei-Lin Li, Xiaoquan Li, Yanxi Li, Ning Li, Ruobing Li, Wan-Xin Li, Xia Li, Yongjing Li, Meitao Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Boxuan Li, Jiqing Li, Huixue 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, Min-Rui Li, Hongyu Li, Guangping Li, Shuqiang Li, Dan C Li, Huashun Li, Jinxin Li, Ganggang Li, Xinrong Li, Haoqi Li, Yayu Li, Handong Li, Huaixing Li, Yan-Nan Li, Xianglong Li, Minyue Li, Hong-Mei Li, Jing-Jing Li, Songhan Li, Mengxia Li, Conglin Li, Jutang 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, Mi Li, Youming Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Fengfeng Li, Yumiao Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Xiangjun Li, Junxu Li, Xingye Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Yuxi Li, Qingyang Li, Chenxuan Li, Xiao-Dong Li, Xinghuan Li, Zhaoping Li, Xingyu Li, Zhenlu Li, Xiaolei Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Zhenhui Li, Cheung Li, Zhenming Li, Xuelian Li, Chunjun Li, Shu-Fen 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, Guangzhen Li, Xiangyan Li, Kunlun Li, Xiaoyu Li, Shiyun 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, Yuqiu Li, Bin-Kui Li, Yumao 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, Keqing Li, Junxian Li, Shuwen Li, Minqi Li, Danxi Li, Saijuan Li, Lingjun Li, Mimi Li, Si-Xing Li, Deheng Li, Yingjie Li, Yaodong Li, Shigang Li, Yuan-Hai Li, Lujie Li, Gao-Fei Li, Minghao Li, Minle Li, Meifen Li, Yifeng Li, Le-Le Li, Huanqing Li, Ziwen Li, Yuhang Li, Yongqiu Li, Pu-Yu Li, Jianhua Li, Chanjuan Li, Nan-Nan Li, Lan-Lan Li, Hongming 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, Cheng-Tian Li, Jin-Jiang Li, Chang Li, Zhi-Xing 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, Wenhui Li, Sichen Li, Xiankai Li, Qingsheng Li, Yaxuan Li, Liangji Li, Yuchan Li, Lixiang Li, Tian-wang Li, Jiaxi Li, Yalin Li, Jin-Liang Li, Pei-Zhi Li, You Ran Li, Xiaoqiong Li, Guanyu Li, Jinlan Li, Yixiao Li, Huizi Li, Jianping Li, Kathy H Li, Yun-Lin Li, Yadong Li, Yuhua Li, Sujing Li, Wenzhuo Li, Xuri 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, Xi Li, S-C Li, Siyi Li, Minmin Li, Manna Li, Chengwen Li, Dawei Li, Shu-Feng Li, Haojing Li, Xun Li, Ming-Jiang Li, Zhiyu Li, Sitao Li, Ziyang Li, 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, Shuai Li, Anqi Li, Bingsong 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, Hongxue Li, Bingjie Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, Chunya Li, Zong-Xue Li, En-Min Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Min-jun Li, Jinhua Li, Yuanheng Li, Qian-Qian Li, Chunxiao Li, Wenli Li, Shijun Li, Kuan Li, Mengze Li, Baoguang Li, Kaiwei Li, Jie-Shou Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Yu-Sheng Li, Junxin Li, Wei-Jun Li, Guoyan Li, Junjie Li, Fei-Lin Li, Nuomin Li, Shulin Li, Yanyan Li, Shanglai Li, Yue Li, Taibo Li, Junqin Li, Zhongcai Li, Xueying Li, Jun-Ru Li, JunBo Li, Xiaoqi Li, Zhaobing Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, 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, Ding-Jian Li, Hongwei Li, Danni Li, Yangxue Li, Xiao-Qiang Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Yiqiang Li, Pengyang Li, Kun-Xin Li, Xiawei Li, Binglan Li, Yutong Li, Xiangpan Li, Zesong 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, Jiafei Li, Changhui 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, 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, 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, Fengjuan Li, W Li, Monica M 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, 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, 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, Feng Li, Weiyang Li, Peihong Li, Lang Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Xinxiu Li, Kaibo Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Meng-Hua Li, Shaodan Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Zheng Li, Ming-Hao Li, Donghe 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, Xiao-Kang Li, Chong Li, Hanqi Li, Fugen Li, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zhuorong Li, Zizhuo Li, X-H Li, Lan-Juan Li, Dong Sheng Li, Xianrui Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Xiaoman Li, Huanqiu Li, Bing-Heng 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, Yanshu Li, Jianlin Li, Yuanyou Li, Chongyang Li, Wanyan Li, Yumin 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, Peihua Li, Kai-Wen Li, Suwen 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, Xinmiao Li, Yuzhe Li, Chenyang Li, Jiacheng Li, Chang-Yan Li, Qifang Li, Xiaohua Li, Vivian Li, Duanxiang Li, Xiaolin Li, Justin Li, Meiting 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, Zongyu Li, Xinmin Li, Luquan Li, Jianyong Li, Guoxing Li, Shujie 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, Wei-Bo Li, Leyao Li, Xiaoyi Li, Liyan Li, Xiao-Qin Li, Xiaokun Li, Xinke Li, Ming-Wei Li, Wenfeng Li, Minzhe Li, Jiajing Li, Karen Li, Yanlin Li, Liao-Yuan Li, X Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, 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, Lipeng Li, Qinghua Li, Qinqin 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, Zhu Li, Rongling Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Jian'an Li, Guangqiang Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Yu-I Li, Shunhua Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Shen Li, Ziqi 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, Zhijie Li, Meng Li, Huimin Li, Cun Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Cong Li, Yinghui Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Weiling Li, Mengfan Li, Jie Li, Shiyan Li, Lianbing Li, G Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, Jialin Li, Wenjian 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, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Hong-Lan Li, Mengqing Li, Ben-Shang Li, S L Li, Shunqing Li, Xionghao Li, Ming-Kai 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, Yong-Liang Li, Muzi 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, Yingxi Li, Caili 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, Zhenyan Li, H J Li, Ji Xia Li, Meizi Li, Yu-Ye Li, Qing-Wei Li, Qiang Li, Yuezheng Li, Hsiao-Hui Li, L I Li, Zhengnan Li, Jianglong Li, Hongzheng Li, Laiqing Li, Ningyang Li, Zhongxia Li, Guangquan Li, Xiaozheng Li, Hui-Jun Li, Shun Li, Guojun Li, Xuefei Li, Hung Li, Senlin Li, Jinping Li, Huili Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, Hongzhe K Li, P 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, 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, Yinzhen Li, Chenxiao Li, Hongjia Li, Li-Min Li, Yunsheng Li, Xiao-Jing Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Baichuan Li, Daoyuan Li, Wenqi Li, Haibo Li, Zhenzhe Li, Xiao-Jun Li, Jian-Mei Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Xueling Li, Qiao Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Wanni Li, Yike Li, Chitao Li, Yihan Li, Haiyang Li, Xiaobai Li, Jiayu Li, Junsheng Li, Pingping Li, Mingquan Li, Wen-Ya Li, Yunlun Li, Suran 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, Peng Peng Li, Yajing Li, Guanglu Li, Kenli Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Jian-Jun Li, Dongmin Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Jian-Shuang Li, Xinxin Li, You-Mei Li, Chenglan Li, Yubin Li, Dazhi Li, Beixu Li, Yuhong Li, Di Li, Fengqiao Li, Guiyuan Li, Yanbing Li, Suk-Yee Li, Yuanyuan Li, Shengjie Li, Jufang Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, 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, Wendeng Li, Ding Li, Yuling 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, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Weihai Li, Jiangan Li, Yu-Kun Li, Hsiao-Fen Li, Zhaojin Li, Bingxin Li, Mengjiao Li, Wenjuan Li, Chia-Yang Li, Meng-Meng Li, Wenyu 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, Chenguang Li, Ming D Li, Ruyue Li, Xujun Li, Chi-Ming Li, Xiaolian Li, Dandan Li, Yi-Ning Li, Yunan Li, Jiazhou Li, Sherly X Li, Zechuan Li, Zhijun Li, Wanling Li, Ya-Ge Li, Yinyan Li, Qijun Li, Guangli Li, Rujia Li, Zhiwei Li, Lixia 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, Xuejun Li, Fengxiang Li, Nana Li, Shunwang Li, Chao Li, Yaqing Li, Bingsheng Li, Jingui Li, Yaqiao Li, Huamao Li, Xiankun Li, Jingke Li, Tianyao Li, Xiaowei 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, Binghua Li, Xuyi Li, Hanjun Li, Yunchu Li, Zhengyao Li, Jin-Qiu Li, Qihua 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, Keanning Li, Wei-Li Li, Yongjin Li, Shuangxiu Li, Chenhao Li, Ling Li, Weizu Li, Deming Li, Peiqin Li, Xiaodong Li, Nanxing Li, Qihang Li, Jianrong Li, Baoguo Li, Zhehui Li, Chenghao Li, Jiuyi Li, Luyao Li, Chun-Xu Li, Weike Li, Desheng Li, Zhixuan Li, Chuanbao Li, Long-Yan Li, Fuyu Li, Chuzhong Li, M D Li, Lingzhi Li, Yuan-Tao Li, Kening Li, Guilan Li, Wanshi Li, Ling-Zhi Li, Hengtong 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, Zehua Li, Huangbao Li, Guo-Chun Li, Xinli Li, Mengyuan Li, S Li, Wenqing Li, Wenhua Li, Caiyun Li, Congye Li, Xinrui Li, Dehai Li, Wensheng Li, Qingshang Li, Jiannan 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, Zhiping Li, Yan-Li Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Yanli Li, Jingfeng Li, Zhi-Yuan 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, Baosheng Li, Zhonglian Li, Yujun Li, Mian 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, Guojin Li, Yueting Li, Xin-Yue Li, Dingchen Li, YaJie Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, Peining Li, Meng-Jun Li, Congjiao Li, Gaizhen Li, Huilin Li, Liang Li, Songtao 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, Dongye Li, Tianye Li, Cuiguang 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, Wei-Yang Li, Rong Li, Shikang 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, Bei-Bei Li, Hong-Lian Li, Haitong Li, Xiumei Li, Yuli Li, Melody M H 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, Shilin Li, Niu Li, Siyue Li, Diyan Li, Shili Li, Mengyao Li, Yixuan Li, Shan-Shan Li, Meiqing Li, Zhuanjian Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Yinhao Li, Zonglin Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, Xiaoqin Li, L P Li, Runbing Li, Chunmei Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Yanmin Li, 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, Xiaoyan Li, Tianyi 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, 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, Yan-Chun Li, Binghu Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Zhenguang Li, Xiaotian Li, Jia-Ru Li, Shuhui Li, Shu-Hong Li, Chun-Xiao Li, Pei-Qin 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, Xueting Li, Yongting Li, Zhenjun Li, Danyang Li, Tiandong Li, Ren Li, Lanfang Li, Hongye 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, Shujiao Li, Yaojia Li, Xiao-Yao Li, Weirong Li, Kun-Ping Li, Weihua Li, Shangming Li, Yaqi Li, Yibo 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, Suheng Li, Jun Z Li, Joyce Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Zhiqiang Li, Junru 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, Chaoqian Li, Yunman 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, Jianbin Li, Chanyuan Li, Shiying Li, Jianxiong Li, Huaying Li, Ji Li, Tuojian Li, Yixin Li, Ziyue Li, Zhongzhe Li, Juntong 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, Shibao Li, Shuying Li, Pengjie Li, Xiaomei Li, Kunlong Li, Ruijin Li
articles
Xi-Xi Li, Pei Shi, Fei-Fei Wu +1 more · 2025 · Discover oncology · Springer · added 2026-04-24
With the sharp increase in the incidence of papillary thyroid carcinoma (PTC), the disease-specific survival rate has not improved significantly. Cholesterol metabolism plays a crucial role in tumor p Show more
With the sharp increase in the incidence of papillary thyroid carcinoma (PTC), the disease-specific survival rate has not improved significantly. Cholesterol metabolism plays a crucial role in tumor proliferation, regulation of tumor immune escape, and tumor drug resistance. However, there are few studies on the role of cholesterol metabolism in the occurrence and development of thyroid cancer (THCA). This study aimed to investigate the predictive value of cholesterol metabolism-related genes (CMRGs) in THCA and the relationship between immune invasion and drug sensitivity. Cholesterol metabolism-related genes we identified from the molecular signatures database, and univariate Cox regression and least absolute shrinkage and selection operator(LASSO) were used to construct a predictive model of cholesterol metabolism-related genes based on the TCGA-THCA dataset. The TCGA dataset was randomly divided into a training group and a validation group to verify the model's predictive value and independent prognostic effect. We then constructed a nomogram and performed enrichment analysis, immune cell infiltration, and drug sensitivity analysis. Finally, TCGA-THCA and GSE33630 datasets were used to detect the expression of signature genes, which was further verified by the HPA database. Six CMRGs (FADS1, NPC2, HSD17B7, ACSL4, APOE, HMGCS2) we identified by univariate Cox and LASSO regression to construct a prognostic model for 155 genes related to cholesterol metabolism. Their prognostic value was confirmed in the validation set, and a highly accurate nomogram was constructed combined with clinical features. We found that the mortality rate of high-risk patients increased by 11.41 times, and the infiltration of immune cells in the high-risk group was significantly reduced. Moreover, through drug sensitivity analysis, we obtained sensitive drugs for different risk groups. The GSE33630 dataset verified the expression of six CMRGs, and the HPA database verified the protein expression of the NPC2 gene. Cholesterol metabolism-related features are a promising biomarker for predicting THCA prognosis and can potentially guide personalized immunization and targeted therapy. Show less
📄 PDF DOI: 10.1007/s12672-025-03483-2
FADS1
Xiangyong Kong, Yanchen Cai, Yuwei Li +1 more · 2025 · Health information science and systems · Springer · added 2026-04-24
Atherosclerotic cardiovascular disease (ASCVD) is a major threat to human life and health, and dyslipidemia with elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor, and i Show more
Atherosclerotic cardiovascular disease (ASCVD) is a major threat to human life and health, and dyslipidemia with elevated low-density lipoprotein cholesterol (LDL-C) is an important risk factor, and in the optimal LDL-C scenario, apolipoprotein B (ApoB) has a more predictive value of ASCVD risk. The study is a genome-wide association study (GWAS) based on a European population. A large GWAS dataset for atherosclerotic cardiovascular diseases was targeted, including coronary heart disease (CHD), ischemic stroke (IS), large-artery atherosclerotic stroke (ISL), small-vessel stroke (ISS), and myocardial infarction (MI). Univariate two-sample mendelian randomization (MR) analyses of ApoB and the above cardiovascular diseases were performed separately, and the association was assessed mainly using the inverse variance weighted (IVW) method, with confidence intervals for the superiority ratios set at 95%. In addition, the experiment was supplemented using MR-Egger, weighted model and weighted median (WM). Based on the results of univariate two-sample mendelian randomisation analysis, it was shown that there was a causal relationship between ApoB and CHD (OR = 1.710, 95% CI 1.529-1.912, P = 0.010), ISL (OR = 1.430, 95% CI 1.231-1.661, P = 2.714E-06), ISS (OR = 1.221, 95% CI 1.062-1.405, P = 0.005) were causally related to each other and the disease prevalence ratio was positively correlated with ApoB concentration. This MR analysis demonstrated a causal relationship between ApoB and CHD, ISL, ISS, but not with the risk of developing IS and MI, which further validated the relationship between ApoB and the risk of ASCVD, and contributed to a better understanding of the genetic impact of ApoB on ASCVD, and to a certain extent, could improve the management of ApoB and reduce the prevalence of ASCVD. Show less
no PDF DOI: 10.1007/s13755-024-00323-5
APOB
Yang Liu, Han-Yan Jin, Meng-Meng Li +6 more · 2025 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report t Show more
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report the fabrication of type II LPLs with enhanced light-responsive efficiency by tailoring the host's functionality for the first time. The functionality of light-responsive metal-organic cage (MOC-RL, constructed from dicopper and responsive ligands) is modified by introducing the second long-chain alkyl ligand, producing MOC-RL-AL as a new host. A spatially hindered solvent based on polyethylene glycol, IL-NTf Show less
no PDF DOI: 10.1002/anie.202501191
LPL
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
Xingyu Fu, Ao Yin, Chao Wang +5 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous Show more
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous cap is ruptured, and atherosclerotic plaques become vulnerable. Efferocytosis is an important method for recognizing and eliminating apoptotic cells. Nevertheless, the specific effect of efferocytosis on atherosclerosis remains uncertain. This study aimed to identify and verify the relevant characteristics of efferocytosis for detecting atherosclerosis. The data of gene expression patterns of atherosclerosis were sourced from the Gene Expression Omnibus (GEO) database, and the differential expression analyses of efferocytosis-related genes (EFRGs) were performed between the atherosclerosis samples and the control samples. Subsequently, protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis were performed to reveal the interaction between molecules as well as their pathways. Machine learning (ML) was employed to determine hub genes to construct a clinical prediction model. At the same time, immune infiltration, single-cell transcriptome analysis, and cell experiments were conducted in both atherosclerosis and control samples to provide a reference for the immune cell landscape and the cell heterogeneity under this condition. The study revealed that 14 genes were closely related to efferocytosis in atherosclerosis. Among them, an ML model was used to screen 5 potential diagnostic biomarkers, including tumor necrosis factor (TNF), apolipoprotein E (ApoE), neutrophil cytosolic factor 1 (NCF1), triggering receptor expressed on myeloid cells 2 (TREM2), and chitinase-3 like-protein-1 (CHI3L1). Subsequent external validation indicated that, except for TNF, the other 4 genes were all upregulated. From the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, those 5 genes were all significantly associated with various immune cells. Further single-cell RNA sequencing (scRNA-seq) analysis demonstrated that those 5 genes were selectively upregulated in the macrophages of atherosclerosis lesions, which was supported by mRNA levels in cell experiments. This study clarified the association between atherosclerosis and efferocytosis, and established an effective diagnostic model. Moreover, potential treatment targets for atherosclerosis were identified, offering new insights into the potential mechanism of atherosclerosis. Show less
📄 PDF DOI: 10.1186/s40001-025-03669-y
APOE
Xiang Lian, Xiaoyan Li, Kexin Wang +3 more · 2025 · Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese journal of medical genetics · added 2026-04-24
To investigate the gene detection results of 2 patients with familial hypercholesterolemia (FH) caused by complex heterozygous variation, and to clarify the relationship between clinical manifestation Show more
To investigate the gene detection results of 2 patients with familial hypercholesterolemia (FH) caused by complex heterozygous variation, and to clarify the relationship between clinical manifestations and gene variation. Two patients (patient 1 and 2) with FH who visited Beijing Anzhen Hospital Affiliated to Capital Medical University in 2018 were selected as research subjects. A retrospective study method was used to collect clinical and family history data of the two patients. And 2 mL of peripheral venous blood from each of the two patients was collected, and genomic DNA extraction was performed on the blood samples. Sanger sequencing was used to validate the variant sites of the two patients detected by whole-exome sequencing (WES). Pathogenicity of variants was classified based on the American College of Medical Genetics and Genomics (ACMG) Standards and Guidelines for the Classification of Genetic Variants (hereinafter referred to as the "ACMG Guidelines"), and the impact of variant was analyzed using multiple bioinformatics tools including SIFT, PolyPhen-2, and SWISS-MODEL. This study has been approved by Beijing Anzhen Hospital Affiliated to Capital Medical University (Ethics No. 2024215X). Patient 1 initially presented with early-onset coronary heart disease, with initial lipid levels of serum total cholesterol (TC) 9.86 mmol/L (normal reference value: 3.10~5.20 mmol/L) and serum low-density lipoprotein cholesterol (LDL-C) 8.37 mmol/L (normal reference value: 1.27~3.12 mmol/L) on admission. Patient 1 initially underwent treatment with rosuvastatin combined with ezetimibe for one month, but the lipid-lowering effect was not significant. The lipid-lowering therapy was then adjusted to atorvastatin combined with ezetimibe and probucol. After one year of treatment, the patient developed paroxysmal chest pain symptoms. A follow-up lipid profile showed a serum TC level of 4.50 mmol/L and a LDL-C level of 3.55 mmol/L. The lipid-lowering regimen was continued, and the serum LDL-C levels were maintained between 2.65 and 3.66 mmol/L. Patient 2 was found to have an abnormally high blood lipid level and carotid artery hardening during physical examination, with an initial blood lipid level of serum TC 11.82 mmol/L and serum LDL-C 9.63 mmol/L. After receiving rosuvastatain therapy, the lipid-lowering effect was significant. WES revealed that patient 1 carried the heterozygous variants c.1871₁₈₇₃del(p.Ile624del) and c.1747C>T (p.His583Tyr) in the LDLR gene (NM₀₀₀₅₂₇.4), while patient 2 carried the heterozygous variants c.1747C>T (p.His583Tyr) in the LDLR gene and c.6936₆₉₃₇inv (p.Ile2313Val) in the APOB gene (NM₀₀₀₃₈₄₎. According to the ACMG Guidelines, the LDLR gene c.1747C>T (p.His583Tyr) was classified as a pathogenic variant (PS3+PM1+PM2_supporting+PM5+PP2+PP3), and c.1871₁₈₇₃del (p.Ile624del) was classified as a pathogenic variant (PS3+PS4+PM2_supporting+PM1+PM4); the APOB gene c.6936₆₉₃₇inv (p.Ile2313Val) was classified as a variant of uncertain clinical significance (PM2_supporting BP4). Patients 1 and 2 in this study were patients with complex heterozygous variant FH, and their genotypic differences may be related to the differences in clinical serum LDL-C levels and the efficacy of hypolipidemic agents. Show less
no PDF DOI: 10.3760/cma.j.cn511374-20241026-00562
APOB
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
Ting He, Jinbo Zhao, Ling Hou +2 more · 2025 · International journal of general medicine · added 2026-04-24
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. Show more
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. The purpose of this research was to construct machine learning (ML) models for identifying undetected CKD in CHD patients. 1786 CHD patients undergoing coronary intervention were retrospectively included. Lasso regression and multifactor logistic regression were used to screen feature variables. Five ML models, ie, logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost), were constructed. Participants were divided into the training set and validation set in a 7:3 ratio. The evaluation metrics included the area under the curve, calibration curve, and decision curve. Totally, 1786 CHD patients were enrolled and split into training (70%) and validation (30%) sets. The prevalence of CKD was 21.8% (390/1786). Multivariate logistic regression analysis showed that men, advanced age, hypertension, diabetes mellitus, history of atrial fibrillation (AF), high Gensini, low hemoglobin, low plateletcrit (PCT), high triglycerides (TG), high lipoprotein(a) (Lp(a)), hyperkalemia, high uric acid to albumin ratio (UAR), high systemic inflammation response index (SIRI), low lymphocyte to monocyte ratio (LMR), and high apolipoprotein B to apolipoprotein A1 (ApoB/ApoA1) ratio were the key clinical and laboratory test indicators of CKD. The XGBoost model performed optimally in the validation set (AUC=0.909, 95% CI 0.881 -0.937). SHapley Additive explanation analysis identified UAR, hypertension, Gensini score, age, and SIRI as the top 5 key features. The XGBoost model constructed on routine clinical data was effective in identifying CKD risk in CHD patients, with UAR as a novel strong predictor. Decision curve analysis confirmed the clinical utility of the model, indicating that it may be used to guide decisions for enhanced monitoring and early intervention over a wide range of risk thresholds. Show less
📄 PDF DOI: 10.2147/IJGM.S558568
APOB
Ning Wei, Lulu Hu, Jian Li +1 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysi Show more
Traditional approaches to assessing sleep quality in clinical nurses often overlook population heterogeneity and the complex interplay of influencing factors. This study employs Latent Profile Analysis (LPA) and Association Rule Mining (ARM) to identify distinct sleep quality subgroups and uncover key factor combinations, thereby informing targeted intervention strategies. A total of 1,686 nurses from 123 hospitals in Shandong Province were recruited through multistage stratified sampling. LPA was used to classify participants based on seven sleep dimensions from the Pittsburgh Sleep Quality Index (PSQI), while ARM was applied to identify frequent itemsets of sleep disorder triggers. Key influencing factors were further examined using univariate analysis and multivariate logistic regression. Three latent sleep profiles were identified: high (63.11%), moderate (34.10%), and low (2.79%) sleep quality. The low-sleep subgroup was characterized by higher proportions of being unmarried/divorced (42.55%), low monthly income (≤ 3,000 CNY, 42.55%), non-permanent employment (76.60%), and severe psychological distress (44.68%). In contrast, the high-sleep subgroup featured higher rates of being married (85.62%), moderate income (3,001–7,000 CNY, 73.03%), and low psychological distress (51.32%). Key determinants included marital status (OR = 2.153/2.252), income (OR = 9.098), employment type (OR = 1.475), and psychological state (OR = 0.060–0.555). ARM revealed distinct risk combinations: “low income + non-permanent employment” (lift = 3.895) for the low-sleep group; “married + moderate income + non-permanent employment + patient conflict” for the moderate group; and “high income + low psychological distress” buffering night-shift effects in the high-sleep group. By integrating LPA and ARM, this study reveals the multidimensional heterogeneity and interactive mechanisms underlying clinical nurses’ sleep quality. The findings support a stratified intervention framework combining institutional safeguards with precision strategies to enhance sleep health management in nursing populations. Show less
📄 PDF DOI: 10.1186/s12912-025-04026-4
LPA
Yicun Li, Yun Wu, Xiaolian Li +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Head and neck squamous cell carcinoma (HNSCC) poses a global health challenge. The management of HNSCC is complicated by the difficulty in detecting occult lymph node metastases, leading to dilemmas i Show more
Head and neck squamous cell carcinoma (HNSCC) poses a global health challenge. The management of HNSCC is complicated by the difficulty in detecting occult lymph node metastases, leading to dilemmas in elective neck dissection decisions, which will impair patients' quality of life without improving survival for nodal negative patients. We conducted a comparative analysis of the clinical features, genomic alterations, gene expression and methylation, tumor microenvironment and cellular states between the clinically N0 and pathologically N0 (cN0-pN0) patients and occult lymph node metastatic patients. Patients with occult lymph node metastases typically present with more poorly differentiated primary tumors and higher rates of angiolymphatic and perineural invasion. We identified a distinctive genomic mutation spectrum in the primary tumors of patients with occult metastases, notably in genes such as NSD1, ARHGAP15 and SMARCA4. A whole-genome DNA hypomethylation and altered gene expression profiles are identified in occult lymph node metastatic patients. Analysis of the tumor microenvironment revealed an enrichment of CARNS1 + NK cells and CBX1 + tumor cells in occult metastatic patients. In conclusion, patients with occult lymph node metastases exhibit distinct molecular and clinical features compared with cN0-pN0 patients. Show less
📄 PDF DOI: 10.1038/s41598-025-10320-7
CBX1
Fiza Javed, Robert A Hegele, Abhimanyu Garg +6 more · 2025 · Journal of clinical lipidology · Elsevier · added 2026-04-24
Familial chylomicronemia syndrome (FCS) is a rare Mendelian autosomal recessive disorder (MIM 238600) characterized by extreme and sustained hypertriglyceridemia due to profound reduction of lipoprote Show more
Familial chylomicronemia syndrome (FCS) is a rare Mendelian autosomal recessive disorder (MIM 238600) characterized by extreme and sustained hypertriglyceridemia due to profound reduction of lipoprotein lipase (LPL) activity. This expert opinion statement synthesizes current knowledge on the definition, pathophysiology, genetics, prevalence, diagnosis, and management of FCS. FCS typically manifests at a young age with persistent severe hypertriglyceridemia-defined as ≥10 mmol/L (≥885 mg/dL), or ≥1000 mg/dL (≥11.2 mmol/L) depending on region and whether Systeme International (SI) units are utilized-in the absence of secondary factors, resistance to conventional lipid-lowering therapies, and a high lifetime risk of acute pancreatitis. It is caused by biallelic pathogenic variants in the LPL gene encoding LPL, or 1 of 4 other related genes that encode proteins that interact with LPL. Affected individuals require a strict, lifelong very low-fat diet with <15% of energy from fat. Emerging therapies inhibiting apolipoprotein C-III show promise in reducing serum triglycerides and pancreatitis risk in patients with FCS. A multidisciplinary approach, encompassing dietary management, pharmacotherapy, and patient education, is pivotal in mitigating the significant morbidity associated with FCS. Show less
no PDF DOI: 10.1016/j.jacl.2025.03.013
LPL
Hui Yan, Rui Wang, Suryavathi Viswanadhapalli +35 more · 2025 · Science advances · Science · added 2026-04-24
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined r Show more
B cells express many protein ligands, yet their regulatory functions are incompletely understood. We profiled ligand expression across murine B sublineage cells, including those activated by defined receptor signals, and assessed their regulatory capacities and specificities through in silico analysis of ligand-receptor interactions. Consequently, we identified a B cell subset that expressed cytokine interleukin-27 (IL-27) and chemokine CXCL10. Through the IL-27-IL-27 receptor interaction, these IL-27/CXCL10-producing B cells targeted CD40-activated B cells in vitro and, upon induction by immunization and viral infection, optimized antibody responses and antiviral immunity in vivo. Also present in breast cancer tumors and retained there through CXCL10-CXCR3 interaction-mediated self-targeting, these cells promoted B cell PD-L1 expression and immune evasion. Mechanistically, Show less
📄 PDF DOI: 10.1126/sciadv.adx9917
IL27
Xiaobin Mai, Le Wang, Juan Tu +13 more · 2025 · Genes & diseases · Elsevier · added 2026-04-24
📄 PDF DOI: 10.1016/j.gendis.2025.101681
ANGPTL4
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
Xiao Li, Xianglong Huang, Keyan Song +5 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Show more
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Fritillariae Thunbergii Bulbus, Leonuri Herba, and Forsythiae Fructus, has shown efficacy in treating cardiovascular diseases, although its mechanisms are unclear. This study aimed to explore the protective effects of QRSJF against atherosclerosis and the mechanisms involved. The composition of QRSJF was analyzed using Ultra Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry. An 8-week high-fat diet (HFD)-induced atherosclerosis model was established in ApoE Both low- and high-dose QRSJF effectively attenuated dyslipidemia and decreased serum inflammatory cytokine levels in HFD-fed ApoE QRSJF improves dyslipidemia and reduces atherosclerotic plaque in ApoE Show less
no PDF DOI: 10.1016/j.phymed.2025.156691
NR1H3
Lu Wang, Xiao-Yong Xie, Qiu-Ling Pan +13 more · 2025 · Nature communications · Nature · added 2026-04-24
Biomolecular condensates, membrane-less assemblies formed by phase separation, are implicated in neurodegenerative disease, but their role in Alzheimer's disease (AD) remains unclear. Here, we report Show more
Biomolecular condensates, membrane-less assemblies formed by phase separation, are implicated in neurodegenerative disease, but their role in Alzheimer's disease (AD) remains unclear. Here, we report that in the brain of AD patients and animal models, an elevation of poly(C)-binding protein 2 (PCBP2) correlates with biomolecular condensation that involves phase separation. These condensates sequester large numbers of mitochondrial and mRNA-binding proteins, leading to the outside impairment of mitochondrial morphology and function, and BACE1 mRNA decay relative to amyloid deposition. We then identify a small molecule CN-0928 that inhibits the condensates by reducing PCBP2 protein level and mitigates AD pathology and cognitive decline, in which CN-0928 binding to a target protein integrator complex subunit 1 (INTS1) allows to regulate PCBP2 expression. Our findings place PCBP2 condensates as a key player that cooperates the seemingly disparate but important pathways, and show pharmacological modulation of PCBP2 as an effective approach for treating AD. Show less
📄 PDF DOI: 10.1038/s41467-025-65547-9
BACE1
Guile Zhao, Yike Li, Hongling Li +7 more · 2025 · Computational and structural biotechnology journal · Elsevier · added 2026-04-24
The malignant transformation of odontogenic keratocysts (OKC) into cancerous odontogenic keratocysts (COKC) is exceedingly rare, and its mechanisms remain poorly understood. Studies exploring the cell Show more
The malignant transformation of odontogenic keratocysts (OKC) into cancerous odontogenic keratocysts (COKC) is exceedingly rare, and its mechanisms remain poorly understood. Studies exploring the cellular heterogeneity, molecular pathways, and clinical features of COKC are limited. In this study, we performed single-cell RNA sequencing (scRNA-seq) on three COKC samples and integrated the data with a public OKC dataset, identifying 22,509 single cells. Two COKC-specific epithelial subpopulations, Basal-C0-EXT1 and Basal-C3-HIST1H3B, were identified. These subpopulations exhibited enhanced stemness and invasive potential, respectively, suggesting their roles as key drivers of OKC carcinogenesis. Fibroblasts underwent phenotypic transitions, particularly from inflammation-associated fibroblasts (IFBs) to myofibroblasts (MFBs). Similarly, macrophage phenotypic transformation may also play a role in OKC carcinogenesis. Clinical observations of severe lesion-area pain in COKC patients suggest potential neuroinvasiveness, Supported by single-cell transcriptomic data, imaging findings, and histopathological evidence. A review of clinical data revealed that none of the COKC patients exhibited cervical lymph node metastasis. Single-cell transcriptomics suggests that this phenomenon may be associated with an active immune microenvironment in COKC, reduced epithelial-mesenchymal transition (EMT) activity, lower VEGFC expression, and upregulated MAST4 expression as a potential regulator of lymphatic metastasis. In conclusion, COKC exhibits distinct molecular, cellular, and clinical characteristics compared to OKC, featuring potent neuroinvasiveness and low lymph node metastatic potential. These findings provide important insights into the mechanisms underlying COKC development and may guide novel diagnostic and therapeutic strategies. Show less
📄 PDF DOI: 10.1016/j.csbj.2025.03.027
EXT1
Kang-Chih Fan, Szu-Chi Chen, I-Weng Yen +7 more · 2025 · Archives of medical science : AMS · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANG Show more
Angiopoietin-like protein 4 (ANGPTL4) is a hepatokine implicated in fat metabolism regulation. Its genetic inactivation has been associated with improved glucose homeostasis, while elevated plasma ANGPTL4 levels are observed in diabetic and obese individuals. However, the potential link between ANGPTL4 and diabetes- or obesity-related complications remains uncertain. This study aimed to explore whether plasma ANGPTL4 level could serve as a predictor of cancer mortality, cardiovascular mortality, and all-cause mortality in a community-based cohort. A community-based cohort study was conducted, where fasting plasma ANGPTL4 concentrations were measured at baseline, and vital status was ascertained through linkage with the National Health Insurance Research Database in Taiwan. During a 10.46-year follow-up period, 29 (2.49%) of the 1163 participants died. Subjects within the highest tertile of plasma ANGPTL4 levels exhibited the lowest survival rate. In unadjusted models, plasma ANGPTL4 significantly predicted all-cause mortality, cancer mortality, and cardiovascular or cancer-related mortality. Upon adjustment for confounders including age, sex, smoking, body mass index (BMI), hypertension, diabetes mellitus (DM), and renal function, each standard deviation increase in plasma ANGPTL4 was associated with HRs of 1.35 (95% CI: 1.01-1.80, Plasma ANGPTL4 emerges as a promising biomarker capable of predicting 10-year mortality and enhancing risk prediction beyond established risk factors. Show less
📄 PDF DOI: 10.5114/aoms/189504
ANGPTL4
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Zheyi Wang, Yize Sun, Zetai Bai +3 more · 2025 · Movement disorders : official journal of the Movement Disorder Society · Wiley · added 2026-04-24
Mitochondrial dysfunction is increasingly recognized as a key factor in neurodegenerative diseases (NDDs), underscoring the therapeutic potential of targeting mitochondria-related genes. This study ai Show more
Mitochondrial dysfunction is increasingly recognized as a key factor in neurodegenerative diseases (NDDs), underscoring the therapeutic potential of targeting mitochondria-related genes. This study aimed to identify novel biomarkers and drug targets for these diseases through a comprehensive analysis that integrated genome-wide Mendelian randomization (MR) with genes associated with mitochondrial function. Using existing publicly available genome-wide association studies (GWAS) summary statistics and comprehensive data on 1136 mitochondria-related genes, we initially identified a subset of genes related to mitochondrial function that exhibited significant associations with NDDs. We then conducted colocalization and summary-data-based Mendelian randomization (SMR) analyses using expression quantitative trait loci (eQTL) to validate the causal role of these candidate genes. Additionally, we assessed the druggability of the encoded proteins to prioritize potential therapeutic targets for further exploration. Genetically predicted levels of 10 genes were found to be significantly associated with the risk of NDDs. Elevated DMPK and LACTB2 levels were associated with increased Alzheimer's disease risk. Higher expression of NDUFAF2, BCKDK, and MALSU1, along with lower TTC19, raised Parkinson's disease risk. Higher ACLY levels were associated with both amyotrophic lateral sclerosis and multiple sclerosis (MS) risks, while decreased MCL1, TOP3A, and VWA8 levels raised MS risk. These genes primarily impact mitochondrial function and energy metabolism. Notably, several druggable protein targets identified are being explored for potential NDDs treatment. This data-driven MR study demonstrated the causal role of mitochondrial dysfunction in NDDs. Additionally, this study identified candidate genes that could serve as potential pharmacological targets for the prevention and treatment of NDDs. © 2025 International Parkinson and Movement Disorder Society. Show less
no PDF DOI: 10.1002/mds.30123
BCKDK
Wenxiu Wang, Rui Li, Zimin Song +4 more · 2025 · JAMA cardiology · added 2026-04-24
Despite substantial progress in low-density lipoprotein cholesterol (LDL-C)-lowering strategies, residual cardiovascular risk remains. Apolipoprotein C3 (APOC3) has emerged as a novel target for lower Show more
Despite substantial progress in low-density lipoprotein cholesterol (LDL-C)-lowering strategies, residual cardiovascular risk remains. Apolipoprotein C3 (APOC3) has emerged as a novel target for lowering triglycerides. Multiple clinical trials of small-interfering RNA therapeutics targeting APOC3 are currently underway. To investigate whether genetically predicted lower APOC3 is associated with a reduction in cardiovascular risk and if the combined exposure to APOC3 and LDL-C-lowering variants is associated with a reduction in the risk of coronary heart disease (CHD). This was a population-based genetic association study with 2 × 2 factorial mendelian randomization. Included were participants of European ancestry in the UK Biobank. Data were analyzed from November 2023 to July 2024. Genetic scores were constructed to mimic the effects of APOC3, 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), and proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors. Plasma lipid and lipoprotein levels, CHD, and type 2 diabetes (T2D). This study included 401 548 UK Biobank participants (mean [SD] age, 56.9 [8.0] years; 216 901 female [54.0%]). Genetically predicted lower APOC3 was associated with a lower risk of CHD (odds ratio [OR], 0.96; 95% CI, 0.93-0.98) and T2D (0.97; 95% CI, 0.95-0.99). Genetically lower APOC3 and PCSK9 were associated with a similar magnitude of risk reduction in CHD per 10-mg/dL decrease in apolipoprotein B (ApoB) level (APOC3: 0.70; 95% CI, 0.59-0.83; PCSK9: 0.71; 95% CI, 0.65-0.77). Combined exposure to genetically lower APOC3 and PCSK9 was associated with an additive lower risk of CHD (APOC3: 0.96; 95% CI, 0.92-0.99; PCSK9: 0.93; 95% CI, 0.90-0.97; combined: 0.90; 95% CI, 0.86-0.93). Genetically lower HMGCR was also associated with a lower risk of CHD, and the risk was further reduced when combined with APOC3 (0.93; 95% CI, 0.90-0.97). Genetically predicted lower APOC3 was associated with a reduced risk of CHD that is comparable with that associated with lower PCSK9 per unit decrease in ApoB. Combined exposure to APOC3 and LDL-C-lowering variants was associated with an additive reduction in CHD risk. Future studies are warranted to investigate the therapeutic potential of these combined therapies, particularly among high-risk patients who cannot achieve therapeutic targets with existing lipid-lowering therapies. Show less
no PDF DOI: 10.1001/jamacardio.2025.0195
APOB
Yuping Huang, Junguang Liao, Panpan Shen +7 more · 2025 · JCI insight · added 2026-04-24
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molec Show more
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molecular scaffolds coordinating these processes remain incompletely defined. Here, we identify neurofibromin 2 (Nf2) as a critical regulator to direct CNC-derived skull morphogenesis. Genetic ablation of Nf2 in murine CNCs causes severe craniofacial anomalies, featuring declined proliferation and increased apoptosis in osteoprogenitors, impaired type I collagen biosynthesis and trafficking, and aberrant osteogenic mineralization. Mechanistically, we uncover that Nf2 serves as a molecular linker that individually interacts with FGF receptor 1 (FGFR1) and Akt through spatially segregated phosphor-sites, and structural modeling and mutagenesis identified Ser10 and Thr230 as essential residues, with Thr230 mutation selectively ablating Akt binding while preserving FGFR1 association. Strikingly, Akt inhibition phenocopied Nf2 deficiency, reducing collagen production and Nf2 phosphorylation, whereas phospho-mimetic Nf2 (T230D) rescued CNC-derived osteogenic defects in Nf2-mutant animals. Our findings underscore the physiological significance of Nf2 as a phosphorylation-operated scaffold licensing the FGFR1/AKT axis to regulate collagen type I biogenesis and trafficking, ensuring normal CNC-derived osteogenesis and craniofacial bone development, thus exposing the Nf2/FGFR1/AKT signaling axis as a therapeutic target and promising advancements in treatment of craniofacial anomalies. Show less
📄 PDF DOI: 10.1172/jci.insight.191112
FGFR1
Shawn C Chafe, Kui Zhai, Nikoo Aghaei +37 more · 2025 · Science translational medicine · Science · added 2026-04-24
Brain metastasis occurs in up to 40% of patients with non-small cell lung cancer (NSCLC). Considerable genomic heterogeneity exists between the primary lung tumor and respective brain metastasis; howe Show more
Brain metastasis occurs in up to 40% of patients with non-small cell lung cancer (NSCLC). Considerable genomic heterogeneity exists between the primary lung tumor and respective brain metastasis; however, the identity of the genes capable of driving brain metastasis is incompletely understood. Here, we carried out an in vivo genome-wide CRISPR activation screen to identify molecular drivers of brain metastasis from an orthotopic xenograft model derived from a patient with NSCLC. We found that activating expression of the Alzheimer's disease-associated beta-secretase 1 (BACE1) led to a substantial increase in brain metastases. Furthermore, genetic and pharmacological inhibition of BACE1 blocked NSCLC brain metastasis. Mechanistically, we identified that BACE1 acts through epidermal growth factor receptor to drive this metastatic phenotype. Together, our data highlight the power of in vivo CRISPR activation screening to unveil molecular drivers and potential therapeutic targets of NSCLC brain metastasis. Show less
📄 PDF DOI: 10.1126/scitranslmed.adu2459
BACE1
Long Xu, Yuanyuan Zhao, Shuxi Song +3 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor micro Show more
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor microenvironment (TME). Neutrophil extracellular traps (NETs) and oxidative stress play critical roles in tumor progression: NETs promote tumor cell adhesion, migration, and immune suppression, while oxidative stress induces DNA damage and activates pro-tumor signaling pathways. Moreover, oxidative stress is an important inducer of NETs, and their crosstalk shapes the LUAD immune microenvironment. However, systematic exploration of LUAD immunotherapeutic response prediction based on NETs and oxidative stress-related genes remains lacking. The gene set related to oxidative stress was obtained from MSigDB. The gene set related to NETs was sourced from relevant literature. Transcriptomic and clinical data were integrated from The Cancer Genome Atlas (TCGA)-LUAD (training set) and GSE31210 (validation set). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to screen gene modules and characteristic scores related to NETs and oxidative stress signatures. Differentially expressed genes (DEGs) were screened, and prognostic model was established using univariate and LASSO Cox regression. Immune infiltration was analyzed using ESTIMATE algorithm, MCP-counter and ssGSEA methods. And we developed a nomogram incorporating clinicopathological features and RiskScore model, and performed drug sensitivity analysis. Finally, the biological role of CPS1 in lung cancer cells was investigated through CCK-8, wound-healing, and Transwell experiments. 22 co-expression modules were screened, among which the brown module showed significant correlations with NETs and oxidative stress signature scores. This module was intersected with DEGs, yielding 624 overlapping genes implicated in immune-relevant pathways (like leukocyte differentiation, neutrophil activation involved in immune response). A prognostic model was established utilizing 8 key genes (ADGRE3, ARHGEF3, CD79A, CLEC7A, CPS1, EPHB2, LARGE2, and OAS3). In the TCGA database, the model demonstrated robust prognostic discrimination (area under the curve (AUC) > 0.6), with high-risk patients exhibiting shorter overall survival (OS) (p < 0.05). Its stability was validated in GSE31210 (AUC > 0.6). The RiskScore showed negative correlations with immune infiltration (like T cells, CD8 T cells, and natural killer cells) as well as immune/stromal scores. A nomogram model combining RiskScore with N staging was developed and validated, demonstrating strong predictive accuracy through calibration and decision curve analyses. High-risk patients were more sensitive to drugs like BI-2536, BMS-509744, and Pyrimethamine. Finally, in vitro tests showed that CPS1 knockdown markedly decreased the viability, migration, and invasion of lung cancer cells. The constructed prognostic model by NETs and oxidative stress-relevant genes effectively predicts LUAD prognosis, correlates with immune microenvironment characteristics, and guides drug sensitivity, providing novel insights for LUAD prognostic assessment and personalized therapy. Show less
📄 PDF DOI: 10.1186/s40001-025-03553-9
CPS1
Shaoshen Wang, Xiangxiang Shi, Xiaoqi Li +9 more · 2025 · International journal of nanomedicine · added 2026-04-24
The early, precise, and safe management of vulnerable atherosclerotic plaques (VAPs) remains a formidable clinical challenge. Here, we present a targeted nanotherapeutic approach in which osteopontin- Show more
The early, precise, and safe management of vulnerable atherosclerotic plaques (VAPs) remains a formidable clinical challenge. Here, we present a targeted nanotherapeutic approach in which osteopontin-targeted nanoparticles encapsulate luteolin (NPs-Lut) for the precise delivery and treatment of VAPs. This engineered system enables site-specific accumulation and sustained release of luteolin at plaque sites. We innovatively constructed an osteopontin-targeted drug delivery system designed for vulnerable atherosclerotic plaques, in which luteolin and atorvastatin were successfully encapsulated. The system demonstrated sustained-release capability in vitro, and its biosafety and histocompatibility were comprehensively evaluated both in vitro and in vivo. Moreover, therapeutic efficacy was further assessed in ApoE In vivo evaluation in ApoE This work provides a robust and translationally promising nanoplatform for the precision treatment of VAPs, offering a novel strategy for safe and effective intervention in atherosclerotic cardiovascular disease. Show less
📄 PDF DOI: 10.2147/IJN.S566896
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
Ni Wang, Yanan Xu, Jiahui Li +7 more · 2025 · Journal of microbiology and biotechnology · added 2026-04-24
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metaboli Show more
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metabolism disorders. Studies have shown that the herb "Gualou-Xiebai" (GLXB) can effectively regulate the blood lipid levels of ApoE Show less
📄 PDF DOI: 10.4014/jmb.2510.10023
APOE
Bo-Yi Pan Lulji Taraqaz, Yu-Ting Hsu, Ping-Hsuan Tsai +4 more · 2025 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Dyslipidemia exacerbates pancreatic β-cell apoptosis, heightening the risk of type 2 diabetes (T2DM). Kansuinine A (KA), a diterpene from Euphorbia roots, exhibits antiapoptotic properties, suggestive Show more
Dyslipidemia exacerbates pancreatic β-cell apoptosis, heightening the risk of type 2 diabetes (T2DM). Kansuinine A (KA), a diterpene from Euphorbia roots, exhibits antiapoptotic properties, suggestive of its therapeutic potential against T2DM. In this study, we evaluated the protective effects of KA against apolipoprotein C3 (ApoC3)-rich low-density lipoprotein (LDL) (AC3RL)-induced β-cell apoptosis and its underlying mechanism of action. ApoE Show less
no PDF DOI: 10.1016/j.biopha.2025.118066
APOC3
Da-Ao Nie, Jiangkun Yu, Wenshan Huang +3 more · 2025 · Molecular immunology · Elsevier · added 2026-04-24
As resident immune surveillance cells within the central nervous system (CNS), microglia exert pivotal biological functions in maintaining CNS homeostasis through dynamic modulation of their prolifera Show more
As resident immune surveillance cells within the central nervous system (CNS), microglia exert pivotal biological functions in maintaining CNS homeostasis through dynamic modulation of their proliferative capacity, chemotactic motility, efferocytosis activity, and biphasic secretory mechanisms involving both neuromodulatory factors and pro-inflammatory mediators. These specialized macrophages not only serve as the first line of defense in innate immunity but also orchestrate the regulation of adaptive immune responses; whose functional status directly governs both the physiological integrity of neural circuits and the progression of pathological outcomes. Notably, in neurodegenerative disease models, microglial functional states exhibit pronounced heterogeneity and are tightly regulated by microenvironmental cues. Upon encountering sustained hyperactivation or functional impairment, these cells precipitate a cascade of deleterious events within the neurovascular unit. Building upon these pathophysiological mechanisms, targeted modulation of microglial polarization equilibrium has emerged as a pivotal research focus in developing innovative neuroprotective therapeutic strategies. This review systematically integrates empirical evidence derived from cutting-edge methodologies-including molecular imaging, single-cell multi-omics profiling, and conditional genetic ablation-to mechanistically dissect the dual regulatory roles of microglia in orchestrating neural homeostatic maintenance and driving pathological progression in neurological disorders. Show less
no PDF DOI: 10.1016/j.molimm.2025.07.014
IL27
Wei Li, Yu Cao, Chen Yu +5 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify sha Show more
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify shared diagnostic biomarkers and elucidate core pathways linking CHD and T2D pathogenesis. Integrated bioinformatics of CHD/T2D transcriptomes identified shared differentially expressed genes (DEGs) and co-expression modules via Weighted Gene Co-expression Network Analysis (WGCNA). Receiver operating characteristic (ROC) analysis selected CPD, GGCT, SUZ12, and ZMYM2 as top diagnostic biomarkers. These predictions were validated using C57BL/6 and ApoE Bioinformatics revealed 328 shared DEGs, with CPD, GGCT, SUZ12, and ZMYM2 showing high diagnostic efficacy. T2D mice exhibited persistent hyperglycemia. Aortic histopathology confirmed disease-specific changes: atherosclerotic plaques in CHD and vascular basement membrane thickening in T2D. Critically, all four biomarkers showed concurrent upregulation in diseased vessels at both protein (immunofluorescence, Western blot) and mRNA (RT-qPCR) levels. This study establishes CPD, GGCT, SUZ12, and ZMYM2 as shared CHD/T2D diagnostic biomarkers. Their validated co-upregulation highlights their dual-disease diagnostic and therapeutic potential. Show less
📄 PDF DOI: 10.3389/fgene.2025.1673303
APOE