👤 Huan Li

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Also published as: Xiaofeng Li, Jingwen Li, Jiajia Li, Zhaolun Li, Litao Li, Ruyi Li, Xiaocun Li, Wanxin Li, Jianyu Li, Jinsong Li, Xinzhi Li, Guanqiao Li, Ying-Lan Li, Zequn Li, Yulin Li, Shaojian Li, Guang-Xi Li, Yubo Li, Bugao Li, Mohan Li, Yan-Xue Li, Qingchao Li, Xikun Li, Enhong Li, Guobin Li, Hong-Tao Li, Xiangnan Li, Yong-Jun Li, Ziming Li, Rongqing Li, Xihao Li, Hang Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Xiao-Lin Li, Yicun Li, Shunqin Li, Jiajie Li, Zhao-Yang Li, Xinjia Li, K-L Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Peiwu Li, Youran Li, Yongmei Li, Changyu Li, Ran Li, Peilin Li, X Y Li, Chunshan Li, Yixiang Li, Ming Zhou Li, Z Li, Ye Li, Guanglve Li, Zili Li, Xinmei Li, Yihao Li, Liling Li, Qing Run Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Qiankun Li, Kailong Li, Shengxu Li, Shisheng Li, Sai Li, Guangwen Li, Hua Li, Xiuli Li, Dongmei Li, Yulong Li, Ru-Hao Li, Lanzhou Li, Zhi-Peng Li, Tingsong Li, Binjun Li, Chen Li, Jiayang Li, Yawei Li, Zunjiang Li, Chao Bo Li, Minglong Li, Donghua Li, Wenzhe Li, Siming Li, Fengli Li, Song Li, Zihan Li, Hsin-Hua Li, Jin-Long Li, Hongxin Li, Dongfeng Li, You Li, Xueyang Li, Fa-Hui Li, Caiyu Li, Zhen-Yuan Li, Xuelin Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Bao Li, Shiyu Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Xiaoqing Li, Jinlin Li, Linke Li, 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, Liqin Li, Jingya Li, Huanan Li, Youjun Li, Zheng-Dao Li, Zhenshu Li, Miao X Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wen-Ying Li, Wei Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Ming Li, Kangli Li, Runwen Li, Wenbo Li, Yarong Li, Side Li, Timmy Li, S E Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Chuan-Hai Li, Lingxi Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Zhongyu Li, Qin Li, Deyu Li, Zhen-Yu Li, Hansen Li, Annie Li, Wenge Li, Jinzhi Li, Xueren Li, Chun-Mei Li, Yijing Li, Kaifeng Li, Wen-Xing Li, Meng-Yao Li, Chung-I Li, Zhi-Bin Li, Xiao Li, Junping Li, Qintong Li, PeiQi Li, Xiaobing Li, Naishi Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Pan Li, Shengchao A Li, Jiaying Li, Ruonan Li, Jun-Jie Li, Cui-lan Li, Shuhao Li, Huiqiong Li, Ruitong Li, Guigang Li, Lucia M Li, Chunzhu Li, Suyan Li, Chengquan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, Xue Cheng Li, Ya-Jun Li, Wenyong Li, Ding-Biao Li, Tianjun Li, Desen Li, Yansong Li, Xiying Li, Zihao Li, Weiyong Li, Xinyang Li, Fadi Li, Huawei Li, Yu-quan Li, Cui Li, Xiaoyong Li, Y L Li, Xueyi Li, Jingxiang Li, Jihua Li, Wenxue Li, Jingping Li, Zhiquan Li, Zeyu Li, Jianglin Li, Yingpu Li, Jing-Yao Li, Yan-Hua Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, L K Li, Ya-Ting Li, Wan Jie Li, Aimin Li, Dongbiao Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, Peiyun Li, Xiuqi Li, L-Y Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Tian Li, YiPing Li, Yuxiu Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Changhong Li, Ze-An Li, Jianmin Li, Minhui Li, Yu Li, Yvonne Li, Yiwei Li, Jiayuan Li, Xiangzhe Li, Zhichao Li, Minglun Li, Siguang 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, Si Li, Xiangyun Li, Jing 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, Shupeng Li, Zhenfei 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, Ronald Li, Gui Lin Li, Chenrui Li, Shi-Hong Li, Shilun Li, Xinyu Li, John Zhong Li, Song-Chao Li, Lujiao Li, Chenghong Li, Dengfeng Li, Nianfu Li, Baohua Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Jiao Li, Zhimei Li, Jun-Cheng Li, Yimeng Li, Jingming Li, Jinxia Li, De-Tao Li, Chunting Li, Shu Li, Julia Li, Chien-Feng Li, Huilan Li, Mei-Zhen Li, Xin-Ya Li, Zhengjie Li, Chunsheng Li, Yan-Yan Li, Liwei Li, Huijun Li, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Lijun Li, Supeng Li, Hening Li, Yiju Li, Yuanhe Li, Guangxiao Li, Fengxia Li, Xueqin Li, Peixin 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, Yu-Hui Li, Wenjing 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, Yongjing Li, Xia Li, Meitao Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Huixue Li, Jiqing Li, Boxuan Li, Hehua Li, Yucheng Li, Qingyuan Li, Yongqi Li, Fengqi Li, Zhigang Li, Yuqing Li, Guiyang Li, Guo-Qiang Li, Dujuan Li, Yanbo Li, Yuying Li, Shaofei Li, Sanqiang Li, Shaoguang Li, 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, Conglin Li, Mengxia 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, Youming Li, Mi Li, Qingrun Li, Dong-Yun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Yumiao Li, Fengfeng Li, Jiexi Li, Qinggang Li, Huixia Li, Kecheng Li, Junxu Li, Xingye Li, Xiangjun Li, Junya Li, Huiying Li, Jiang Li, Shengxian Li, Yuxi Li, Qingyang Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Xingyu Li, Zhaoping Li, Xiaolei Li, Zhenlu Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Zhenhui Li, Cheung Li, 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, Chaoying Li, Siyu Li, Qiu Li, Juanjuan Li, Xiangyan Li, Guangzhen Li, Kunlun Li, Shiyun Li, Xiaoyu Li, Yaobo Li, Shiquan Li, Xuewang Li, Mei Li, Xiangdong Li, Zhenjia Li, Jifang Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiaoya Li, Xiao-Li Li, Shan Li, Shitao Li, Lijia Li, Zehan Li, Chunqiong Li, Huiliang Li, Junjun Li, Chenlong Li, Shujin Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Wenxi Li, Weining Li, Wu-Jun Li, Chang-hai Li, Bin-Kui Li, Yuqiu Li, Yumao Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Y X Li, Chia Li, Yunyun Li, Zhen-Jia Li, Fu-Rong Li, Honghua Li, Lanjuan Li, Qiuxuan Li, Xiancheng Li, Man-Zhi Li, Yanmei Li, De-Jun Li, Junxian Li, Zhihua Li, Keqing Li, Shuwen Li, Danxi Li, Saijuan Li, Minqi Li, Lingjun Li, Mimi Li, Si-Xing Li, Deheng 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, Yanchuan Li, Shuang Li, Lingyi Li, Wanting Li, Bai-Qiang Li, Gong-Hua Li, Zhengyu Li, Chunmiao Li, Jiong-Ming Li, Yongqiang Li, Linsheng Li, Weiguang Li, Mingyao Li, Guoqing Li, Ze Li, Xiaomeng Li, R H L Li, Yuanze Li, Yunqi Li, Guisen Li, Yuandong Li, Jinglin Li, Dongyang Li, Mingfang Li, Honglong Li, Hanmei Li, Chenmeng Li, Changcheng Li, Shiyang Li, Shiyue Li, Jianing Li, Hanbo Li, Dingshan Li, Yinggao Li, Linlin Li, Xinsheng Li, Jin-Wei Li, Jin-Jiang Li, Cheng-Tian Li, Chang Li, Zhi-Xing Li, Yaxi Li, Ming-Han Li, Wei-Ming Li, Wenchao Li, Guangyan Li, Xuesong Li, Zhaosha Li, Jiwei Li, Chun-Quan Li, Yongzhen Li, Weifeng Li, Tao Li, Wenhui Li, Sichen 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, Yixiao Li, Jinlan Li, Huizi Li, Jianping Li, Kathy H Li, Yun-Lin Li, Yadong Li, Sujing Li, Yuhua Li, Wenzhuo Li, Xuri Li, Deqiang Li, Y Li, Caixia Li, Zipeng Li, Mingyue Li, Hongli Li, Yun Li, Mengqiu Li, Ling-Ling Li, Yanfeng Li, Yaqin 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, Ziyang Li, Sitao Li, Yaochen Li, Qian 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, Zhenyu Li, Xiaonan Li, Ting Li, Duan Li, Xiang-Yu Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Xunjia Li, Yanchang Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, En-Min Li, Zong-Xue 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, Jie-Shou Li, Kaiwei Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Junxin Li, Yu-Sheng Li, Wei-Jun Li, Guoyan Li, Fei-Lin Li, Junjie Li, Nuomin Li, Shanglai Li, Shulin Li, Yanyan Li, Yue Li, Taibo Li, Junqin Li, Xueying Li, Jun-Ru Li, Zhongcai 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, Xiyun Li, Yi-Wen Li, Shihong Li, Huifeng Li, Rulin Li, Ya-Pei Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Min-Dian Li, Wenjia Li, Xiatian Li, Hongwei Li, Ding-Jian Li, Yangxue Li, Danni Li, Xiao-Qiang Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Pengyang Li, Yiqiang Li, Kun-Xin Li, Xiawei Li, Binglan Li, Zesong Li, Yutong Li, Xiangpan Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Boru Li, Yinxiong Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Hong-Yu Li, Chuanning Li, Weijian Li, Changhui Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Dechao Li, Chunxing Li, Wenxia Li, Guoxiang Li, Ziru Li, Qiao-Xin Li, Shu-Fang Li, Huang Li, Qiusheng Li, Juxue Li, Man Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Nan Li, Gongda Li, Wei-Ping Li, Yajun Li, Yipeng Li, Mingxing Li, Nanjun Li, Xin-Yu Li, Chunyu Li, P H Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Ranran Li, Suping Li, Long Shan Li, Yanze Li, Jason Li, Xiao-Feng Li, Monica M Li, Fengjuan Li, W Li, Xianlun Li, Qi Li, Hainan Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Xionghui Li, Ying-Bo Li, Fei Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Kang Li, Peilong Li, Hongmei 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, Weiguo Li, Yijie Li, Xiaoying Li, Suwei Li, Shengsheng Li, Shuyu D Li, Jiandong Li, Ruiwen Li, Fangyong Li, Hong Li, Binru Li, Yuqi Li, Zihua Li, Yuchao Li, Hanlu Li, Jianang Li, Xue-Peng Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Feng Li, Weiyang Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Xinxiu Li, Kaibo Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Meng-Hua Li, Shaodan Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Zheng Li, Donghe Li, Ming-Hao Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Jingqi Li, Menghua Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Chong Li, Xiao-Kang Li, Fugen Li, Hanqi Li, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zizhuo Li, Zhuorong 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, 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, Guiying Li, Jinku 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, Guandu Li, Yixue 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, Qifang Li, Chang-Yan 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, Mingjiang Li, Youwei 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, Tie Li, Yiwen Li, Baoqi Li, Leyao Li, Wei-Bo 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, X Li, Liao-Yuan Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Li-Na Li, Hengguo Li, An-Qi Li, Xuehua Li, Hui Li, AnHai Li, Chenli Li, Zhengrui Li, Rumei 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, Tianjiao Li, Shen 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, Yunxiao Li, Rosa J W Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, Zhankui Li, Zhi Li, Zihai Li, Yue-Jia Li, Haihong Li, Peifen Li, Taixu Li, Mingzhou Li, Jiejing Li, Meng-Miao Li, Meiying Li, Chunlian Li, Meng Li, Zhijie Li, Cun Li, Huimin Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Cong Li, Yinghui Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Weiling Li, Mengfan Li, Jie Li, Shiyan Li, G Li, Lianbing Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, 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, Michelle Li, Chaojie Li, Caolong Li, Zhifan Li, J Li, Zhi-Jian Li, Jianwei Li, Yan-Guang Li, Jiexin Li, Hongyan Li, Ji-Min Li, Zhen-Xi Li, Guangdi Li, Peipei Li, Tian-Yi Li, Xiaxia Li, Nien Li, Yuefeng Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Jieshou Li, Lin Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Hong-Lan Li, S L Li, Mengqing Li, Ben-Shang Li, Ming-Kai Li, Shunqing Li, Xionghao Li, Lan Li, Menglu Li, Huiqing Li, Yanwei Li, Yantao Li, Chien-Te Li, Wenyan Li, Xiaoheng Li, Zeyuan Li, Ruolin Li, Yongle 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, Hongguo Li, Yong-Jian Li, Le Li, Chenxin Li, Yongsen Li, Qingyun Li, Pengyu Li, Si-Wei Li, Ai-Qin Li, Zichao Li, Manru Li, Caili Li, Yingxi Li, Yuqian Li, Wei-Dong Li, Guannan 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, 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, Yu-Ye Li, Meizi Li, Qing-Wei Li, Yuezheng Li, Qiang Li, Hsiao-Hui Li, Zhengnan Li, L I Li, Jianglong Li, Hongzheng Li, Laiqing Li, Zhongxia Li, Ningyang Li, Guangquan Li, Xiaozheng Li, Hui-Jun Li, Shun Li, Guojun Li, Xuefei Li, Senlin Li, Hung Li, Jinping Li, Huili Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, P Li, Hongzhe K Li, Xiao-Qiu Li, Fulun Li, Jiejia Li, Yonghao Li, Mingli Li, Yehong Li, Yi-Yang Li, Zhihui Li, Fujun Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Ni Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Shichao Li, Gan Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Chun Li, Lihong Li, Jianan Li, Haixia Li, Wenfang 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, Hung-Yuan Li, Xiaofei Li, Xuanfei Li, Zilin Li, Zhang Li, Jianxin Li, Mingqiang Li, H Li, Xiaojiao Li, Dongliang Li, Chenxiao Li, Yinzhen Li, Hongjia Li, Xiao-Jing Li, Li-Min Li, Yunsheng Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Baichuan Li, Daoyuan Li, Haibo Li, Wenqi Li, Zhenzhe Li, Jian-Mei Li, Xiao-Jun 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, Yihan Li, Chitao Li, Haiyang Li, Jiayu Li, Xiaobai Li, Junsheng Li, Pingping Li, Wen-Ya Li, Mingquan 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, Jian-Shuang Li, Xinxin Li, You-Mei Li, Chenglan Li, Dazhi Li, Yubin Li, Beixu Li, Yuhong Li, Di Li, Fengqiao Li, Guiyuan Li, Yanbing Li, Suk-Yee Li, Jufang Li, Yuanyuan Li, Shengjie Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, Minghua Li, Jun Li, Xiyue 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, Wen-Chao Li, Dan-Ni Li, Sunan Li, Zhencong Li, Chunqing Li, Lai K Li, Jiong Li, Yanni Li, Daiyue Li, Bingong Li, Yongsheng Li, Huifang 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, Yuling Li, Ding Li, Wendeng Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Linyan Li, Ming-Yang Li, Yanjun Li, Shengze Li, Jiequn Li, Zhongding Li, Hewei Li, Da-Jin Li, Jiangui Li, Zhengyang Li, Cyril Li, Xinghui Li, Yuefei Li, Xiao-kun Li, Xinyan Li, Yuanhao Li, Xiaoyun Li, Congcong Li, Ji-Lin Li, Ping'an Li, Yushan Li, Juan Li, Weiping Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Jinfeng Li, Wen Li, Shiheng Li, Jiangan Li, Yu-Kun Li, Weihai Li, Hsiao-Fen Li, Zhaojin Li, Bingxin Li, Mengjiao Li, Wenjuan Li, Wenyu Li, Meng-Meng Li, Chia-Yang Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Xi-Xi Li, Wenlei Li, Mei-Lan Li, Wenjun Li, Jiaxin Li, Haiyan Li, Ming D Li, Chenguang Li, Xujun Li, Ruyue Li, Chi-Ming Li, Xiaolian Li, Dandan Li, Yi-Ning Li, Yunan Li, Zechuan Li, Zhijun Li, Jiazhou Li, Sherly X Li, Wanling Li, Ya-Ge Li, Yinyan Li, Rujia Li, Guangli Li, Qijun Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Xiaohan Li, Wan-Shan Li, Zhongwen Li, Huijie Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Xuejun Li, Fengxiang Li, Shunwang Li, Nana Li, Chao Li, Yaqing 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, Hai-Yun Li, Haoran Li, Xiaoliang Li, Zhongxian Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Xinjian Li, Jialun Li, Zilu Li, Rui Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Xuyi Li, Binghua Li, Hanjun Li, Yunchu Li, Jin-Qiu Li, Zhengyao Li, Qihua 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, Desheng Li, Weike 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, 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, 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, Jiannan Li, Qingshang Li, Guanbin Li, Hanbin Li, Zhiyi Li, Xing Li, Wanwan Li, Jia Li Li, Zhaoyong Li, SuYun Li, Shiyi Li, Wan-Hong Li, Mingke Li, Suchun Li, Huanhuan Li, Xiaoyuan Li, Yanan Li, Zongfang Li, Yang Li, Jiayan Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Dongdong Li, Yimei Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Zhi-qiang Li, Shaojing Li, S S Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Tong Li, Yilong Li, Lihua Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Jingfeng Li, Zhi-Yuan Li, Yanli 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, Yanqing Li, Zijian Li, Jixuan Li, Zhandong Li, Xuejie Li, Congjiao Li, Peining Li, Meng-Jun 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, X-L Li, Shaoliang Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Cuiguang Li, Dongye Li, Qun Li, Tianye Li, Zhen Li, Chunhong Li, Yuan 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, Jingyong Li, Honggang Li, Shikang Li, Wei-Yang Li, Rong Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Hong-Lian Li, Bei-Bei Li, Shishi Li, Xiumei Li, Haitong Li, Melody M H Li, Yuli Li, Ruibing Li, Qingfang Li, Peibo Li, Qibing Li, Huanjun Li, Wende Li, Heng 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, Longxuan Li, Baoting Li, Huiyou Li, Ka Wan Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Yu-Hao Li, Gui-xing Li, Shilin Li, Shunle Li, Niu Li, Siyue Li, Diyan Li, Mengyao Li, Shili Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Meiqing Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Zonglin Li, Yinhao Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, W Y Li, Li 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, Xiaoyan Li, Tianyi Li, Qingfeng Li, Nanlong Li, Ping Li, Xu-Bo Li, Fangzhou Li, Nien-Chen Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Yuanchuang Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Qing-Chang Li, Hongliang Li, Hong-Yan Li, Shengbiao Li, Yue-Rui Li, Dalei Li, Ruidong Li, Zongjun Li, Y M Li, Changqing Li, Hanting Li, Dong-Jie Li, Dengxiong Li, Sijie 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, Guixia Li, Fengyuan 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, Shu-Hong Li, Chun-Xiao Li, Pei-Qin Li, Shuyue Li, Mengying Li, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Dali Li, Duo Li, Yaxian Li, Zhiming Li, Xuemei Li, Hongxia Li, Yongting Li, Xueting Li, Danyang Li, Zhenjun Li, Ren Li, Tiandong Li, Lanfang Li, Hongye Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, W J Li, Qiji Li, Zhijia Li, Zhipeng Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaoting Li, Xiaobo Li, Ruotai Li, Meijia Li, Shujiao Li, Yaojia Li, Xiao-Yao Li, Weirong Li, Kun-Ping Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Yandong Li, Runzhao Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Yingjun Li, Xiufeng Li, Yanxin Li, Xiaohuan Li, Ying-Qin Li, Boya Li, Lamei Li, O Li, Fan Li, Jun Z Li, Suheng Li, Joyce Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Junru Li, Zhiqiang Li, Hecheng Li, Jiangchao Li, Haifeng Li, Changkai Li, Yueping Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Xuanxuan Li, Rui-Jún Eveline Li, Bing-Mei Li, Chaoqian Li, Yunman Li, Shuhua Li, Yu-Cheng Li, Chunying Li, Yirun Li, Haomiao Li, Weiheng Li, Leipeng Li, Qianqian Li, Baizhou Li, YiQing Li, Zhengliang Li, Han-Ru Li, Sheng Li, Wei-Qin Li, Weijie Li, Guoyin Li, Yaqiang Li, Zongyi Li, Qingxian Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Yongpeng Li, Chengjun Li, Keke Li, Jianbin Li, Chanyuan Li, Shiying Li, Jianxiong Li, Ji Li, Huaying Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Heying Li, Shaomin Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Hanxiao Li, Jiahao Li, Jiansheng Li, Shuying Li, Shibao Li, Pengjie Li, Xiaomei Li, Ruijin Li, Kunlong Li
articles
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
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
Jia Li, Deming Ren, Xiangxu Meng +4 more · 2025 · Virus research · Elsevier · added 2026-04-24
The genetic foundations underlying the observed disease resistance in certain indigenous pig breeds, notably the Min pigs of China, present a compelling underexplored subject of study. Exploring the m Show more
The genetic foundations underlying the observed disease resistance in certain indigenous pig breeds, notably the Min pigs of China, present a compelling underexplored subject of study. Exploring the mechanisms of disease resistance in these breeds could lay the groundwork for genetic improvements in pig immunity, potentially augmenting overall pig productivity. In this study, whole blood samples were collected from pre- and post- swine fever vaccinated Min and Large White pigs for transcriptome sequencing. The mRNA and lncRNA in both pig breeds were analyzed, and intra-group and inter-group comparisons were also conducted. The results indicated that a greater number of immune-related pathways such as the JAK-STAT and PI3K-AKT signaling were enriched in Min pigs. Furthermore, genes involved in inflammation and antiviral responses, including IL16, IL27, USP18, and DHX58, were upregulated in post-vaccination Min pigs compared to post-vaccination Large White pigs. This heightened immune responsiveness could contribute to the observed differences in disease resistance between Min pigs and Large White pigs. Show less
📄 PDF DOI: 10.1016/j.virusres.2025.199536
IL27
Teng Wu, Tongsheng Huang, Honglin Ren +26 more · 2025 · Circulation research · added 2026-04-24
Individuals with diabetes are susceptible to cardiac dysfunction and heart failure, potentially resulting in mortality. Metabolic disorders frequently occur in patients with diabetes, and diabetes usu Show more
Individuals with diabetes are susceptible to cardiac dysfunction and heart failure, potentially resulting in mortality. Metabolic disorders frequently occur in patients with diabetes, and diabetes usually leads to remodeling of heart structure and cardiac dysfunction. However, the contribution and underlying mechanisms of metabolic and structural coupling in diabetic cardiac dysfunction remain elusive. Two mouse models of type 2 diabetes (T2DM) were used to assess alterations in glucose/lipid metabolism and cardiac structure. The potential metabolic-structural coupling molecule ACBP (acyl-coenzyme A-binding protein) was screened from 4 published datasets of T2DM-associated heart disease. In vivo loss-of-function and gain-of-function approaches were used to investigate the role of ACBP in diabetic cardiac dysfunction. The underlying mechanisms of metabolic and structural coupling were investigated by stable-isotope tracing metabolomics, coimmunoprecipitation coupled with mass spectrometry, and chromatin immunoprecipitation sequencing. Diabetic mouse hearts exhibit enhanced lipid metabolism and impaired ultrastructure with marked cardiac systolic and diastolic dysfunction. Analysis of 4 T2DM public datasets revealed that Our findings demonstrated that ACBP mediates the bidirectional regulation of cardiomyocyte metabolic and structural associations and identified a promising therapeutic target for ameliorating cardiac dysfunction in patients with T2DM. Show less
no PDF DOI: 10.1161/CIRCRESAHA.124.326044
MYBPC3
Xianqi Shen, Zijian Li, Yuchuan Shi +5 more · 2025 · Translational andrology and urology · added 2026-04-24
Poly(A) binding protein cytoplasmic 4 (PABPC4) has been regarded as a prognostic marker in many malignancies. In this study, we evaluated PABPC4 expression at both messenger ribonucleic acid (mRNA) an Show more
Poly(A) binding protein cytoplasmic 4 (PABPC4) has been regarded as a prognostic marker in many malignancies. In this study, we evaluated PABPC4 expression at both messenger ribonucleic acid (mRNA) and protein levels. The prognostic value of PABPC4 in patients with prostate cancer (PCa) was also investigated. The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, our analysis of Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA), and 65 pairs of ribonucleic acid (RNA) sequencing data from our center were employed to detect the expression of PABPC4 in PCa tissues. Tissue microarrays (TMAs) were utilized to detect the expression of the PABPC4 protein, and survival analysis as well as risk factor analysis were conducted. In the 65 pairs of sequencing data, the expression of PABPC4 in tumor tissues was significantly higher than that in paired adjacent tissues (P<0.001), and its expression also presented significant differences among different Gleason groups (P=0.041). In the CPGEA data, the expression of PABPC4 in tumor tissues was significantly higher than that in control tissues (P<0.001), and the expression of PABPC4 in M1 patients was higher than that in M0 patients, although no significant statistical difference was shown (P=0.051). In the TCGA data, the expression of PABPC4 in tumor tissues was significantly higher than that in control tissues (P<0.001). The expression of pT3/4 (pathological tumor stage 3 and pathological tumor stage 4) in high-stage tumor tissues was significantly higher than that in low-stage tumor tissues (pT2) (P=0.02), the expression of pT3/4 in GSE21034 and GSE32571 tumor tissues was significantly higher than that in control tissues (P<0.001), and the expression of pT3/4 in primary tumor tissues was higher than that in metastatic tissues in GSE6752 (P<0.001). The TCGA data revealed that patients with high PABPC4 expression had poorer overall survival (OS) than those with low PABPC4 expression (P=0.04), and the TMA data indicated that patients with high PABPC4 expression had a poor prognosis (P=0.004). Our study demonstrated that PABPC4 was overexpressed at mRNA and protein levels in PCa. We found that patients with high PABPC4 expression had a shorter biochemical recurrence (BCR)-free survival and OS, showing its value as a prognostic biomarker in patients with PCa. Show less
no PDF DOI: 10.21037/tau-2025-19
PABPC4
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
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
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
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
Xin Liu, Ting Du, Ruofan Xi +7 more · 2025 · Drug design, development and therapy · added 2026-04-24
Cyclophosphamide (CTX), a cornerstone in breast cancer combination chemotherapy, frequently induces adverse effects including myelosuppression, gastrointestinal disturbances, hepatic impairment, and a Show more
Cyclophosphamide (CTX), a cornerstone in breast cancer combination chemotherapy, frequently induces adverse effects including myelosuppression, gastrointestinal disturbances, hepatic impairment, and alopecia. Chemotherapy-induced alopecia severely impacts patients' quality of life and psychological well-being. Modified Huanjingjian (MHJJ), a traditional Chinese herbal formula, demonstrates clinical efficacy in alleviating chemotherapy-related side effects, yet its mechanisms against CTX-induced alopecia remain uncharacterized. And our main aim was to explore the efficacy and the mechanism of MHJJ in mice. UPLC-QE-Orbitrap-MS characterized MHJJ's chemical composition. A CTX-induced alopecia murine model was established. Systemic toxicity was evaluated through body weight monitoring, automated biochemical analysis (ALT/AST levels), and hematological profiling (WBC/PLT counts). Hair follicle histopathology was assessed via H&E staining. IHC and IF staining quantified proliferation markers and hair follicle stem cell (HFSC) biomarkers. Reduced representation bisulfite sequencing (RRBS) was used to map DNA methylation patterns. Wnt pathway dynamics were analyzed through qRT-PCR and IF staining. We identified 110 bioactive compounds in MHJJ. MHJJ intervention attenuated alopecia severity, restored follicular architecture, and increased follicular density compared to CTX monotherapy (p<0.05). HFSC proliferation markers (Ki67/CD34) showed significant upregulation, while apoptosis markers (Caspase-3) were suppressed. RRBS revealed MHJJ-mediated hypomethylation in differentially methylated regions, with gene body methylation constituting 60% of total methylation changes. Methylation-modulated genes predominantly localized to Wnt signaling pathways: MHJJ enhanced Wnt3/Wnt10a expression while suppressing Cer1/Axin1. Corresponding methylation reductions at promoter and gene body regions were confirmed at mRNA and protein levels. MHJJ mitigates CTX-induced alopecia through epigenetic regulation of HFSCs, specifically via DNA hypomethylation-mediated activation of Wnt3/Wnt10a and suppression of Cer1/Axin1. This mechanism promotes follicular regeneration by restoring Wnt signaling homeostasis, positioning MHJJ as a promising adjuvant for chemotherapy-induced alopecia management. Show less
📄 PDF DOI: 10.2147/DDDT.S523809
AXIN1
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
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
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
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
Wenwen Yin, Zhiwei Li, Wenhui Zheng +7 more · 2025 · European archives of psychiatry and clinical neuroscience · Springer · added 2026-04-24
The β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) gene polymorphism (rs638405) has been widely reported to be associated with Alzheimer's disease (AD) risk. However, studies on the relati Show more
The β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) gene polymorphism (rs638405) has been widely reported to be associated with Alzheimer's disease (AD) risk. However, studies on the relationship between BACE1 gene polymorphism (rs638405), brain volume, and cognition in AD patients remain scarce. To investigate the effect of genetic polymorphism in BACE1 on gray matter volume (GMV) and cognition in AD, this study recruited 111 cognitively unimpaired (CU) controls and 144 AD patients. The effect of BACE1 rs638405 polymorphism on cognition was explored in CU and AD groups. Then the interaction effect of the diagnosis and BACE1 rs638405 polymorphism on GMV was performed, following the post-hoc analysis of regions of interest (ROIs) in interaction analysis. Mediation analysis was used to elucidate the relationship among genotypes, ROIs and cognition. BACE1 rs638405 G carriers (BACE1 G+) showed significantly lower scores in global cognition and memory function than noncarriers (BACE1 G-) in AD group. Genotypes (G+/G-) and diagnosis (CU/AD) have interaction on GMV of medial temporal lobe (MTL) including the left parahippocampus and right hippocampus. Post-hoc analysis revealed that BACE1 G+ exhibited significantly lower GMV in ROIs compared to BACE1 G- in AD. Finally, mediation analysis further demonstrated that the GMV of ROIs mediated the effect of BACE1 rs638405 polymorphism on cognition in AD. Our results emphasize the BACE1 rs638405 gene polymorphisms may affect the GMV of MTL and cognition in AD, deepening the understanding of AD pathogenesis. Show less
📄 PDF DOI: 10.1007/s00406-024-01953-2
BACE1
Xiaoli Shi, Xueli Jia, Wei Liu +5 more · 2025 · Stem cells translational medicine · Oxford University Press · added 2026-04-24
Zinc finger protein 750 (ZNF750) has been identified as a potential tumor suppressor across multiple malignancies. Nevertheless, the specific involvement of ZNF750 in the regulation of mesenchymal cel Show more
Zinc finger protein 750 (ZNF750) has been identified as a potential tumor suppressor across multiple malignancies. Nevertheless, the specific involvement of ZNF750 in the regulation of mesenchymal cell differentiation and bone homeostasis has yet to be elucidated. In the current study, we observed a substantial presence of ZNF750 in bone tissue and noted alterations in its expression during osteogenic differentiation of mesenchymal progenitor cells. Functional experiments indicated that ZNF750 promoted osteogenic differentiation while impeding adipogenic differentiation from mesenchymal stem/progenitor cells. Further mechanistic investigations revealed that ZNF750 transcriptionally suppressed the expression of Snail family transcriptional repressor 1 (SNAI1) by binding to the proximal promoter region of Snai1 gene, thereby activating Wnt/β-catenin signaling. SNAI1 exerted opposing effects on cell differentiation towards osteoblasts and adipocytes in comparison to ZNF750. The overexpression of SNAI1 counteracted the dysregulated osteogenic and adipogenic differentiation induced by ZNF750. Furthermore, the transplantation of Znf750-silenced bone marrow stromal cells into the marrow of wild-type mice resulted in a reduction in cancellous and cortical bone mass, alongside a decrease in osteoblasts and an increase in marrow adipocytes, while the number of osteoclasts remained unchanged. This study presents the first demonstration that ZNF750 regulates the differentiation of osteoblasts and adipocytes from mesenchymal stem/progenitor cells by transcriptionally deactivating SNAI1 signaling, thereby contributing to the maintenance of bone homeostasis. It suggests that ZNF750 may represent a promising therapeutic target for metabolic bone disorders such as osteoporosis. Show less
no PDF DOI: 10.1093/stcltm/szaf013
SNAI1
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
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
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Xinling Zhang, Dongang Liu, Yuting Qiu +7 more · 2025 · Metabolites · MDPI · added 2026-04-24
Angiopoietin-like proteins (ANGPTLs) represent a family of secreted glycoproteins that are extensively expressed in vivo and are integral to various pathophysiological processes, including glucose and Show more
Angiopoietin-like proteins (ANGPTLs) represent a family of secreted glycoproteins that are extensively expressed in vivo and are integral to various pathophysiological processes, including glucose and lipid metabolism, stem cell proliferation, local inflammation, vascular permeability, and angiogenesis. Particularly interesting is ANGPTL4, which has been identified as a significant factor in the development and progression of diabetic retinopathy (DR), thus becoming a central focus of DR research. ANGPTLs modulate metabolic pathways, enhance vascular permeability, and facilitate pathological angiogenesis, in addition to causing intraocular inflammation. As promising molecular targets, ANGPTLs not only serve as biomarkers for predicting the onset and progression of DR but also present therapeutic potential through antibody-based interventions. This paper discusses the pathogenesis of DR and the potential applications of ANGPTLs in early diagnosis and targeted therapy. It provides references for advancing precision diagnosis and personalized treatment strategies through more profound ANGPTLs research in the future. Show less
📄 PDF DOI: 10.3390/metabo15060352
ANGPTL4
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
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
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
Yunqi Xie, Haochen Wang, Yajie Zhang +5 more · 2025 · Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · Elsevier · added 2026-04-24
Smoking is harmful to health. Cigarette smoke (CS) contains a variety of toxic substances. Studies have found that nicotine, tar, polycyclic aromatic hydrocarbons, etc. in CS can pass through the bloo Show more
Smoking is harmful to health. Cigarette smoke (CS) contains a variety of toxic substances. Studies have found that nicotine, tar, polycyclic aromatic hydrocarbons, etc. in CS can pass through the blood-brain barrier and enter the brain to exert their effects. Moreover, some existing studies have pointed out that CS exposure is closely related to the accelerated pathology of Alzheimer's disease (AD). Transgenic mice with the five familial AD mutations (5xFAD), which are 1-month-old, were used for chronic CS exposure for 100 days. Subsequently, cognitive function and behavioral changes were evaluated through morris water maze and new object recognition tests. The acceleration of pathological changes due to CS exposure was assessed by HE, Tunel and Aβ immunohistochemical staining. Differential expression proteins and metabolites were screened through hippocampal proteomics and metabolomics analyses. Finally, the expression levels of key proteins were verified by Western blot. Compared with unexposed 5xFAD mice, the behavioral results of mice showed that FAD mice after CS exposure exhibited poorer cognitive abilities, with longer latencies in the Morris water maze, and decreased time spent and entries in the target quadrant. The results of pathological sections indicated that the total nuclei density in the DG and CA3 regions of the hippocampus of 5xFAD mice decreased significantly after chronic CS exposure, the number of TUNEL-positive cells increased, and the expression of Aβ42 increased. Multi - omics analysis revealed that CS exposure up - regulated the expression of 46 proteins and down - regulated the expression of 80 proteins in the hippocampus of 5xFAD mice, and caused changes in 92 metabolites. Analysis of the correlation between differential proteins and differential metabolites revealed six key cross-node proteins: Kng1, Hbb-b1, Fabp3, Apoa1, Ilk, and Apoa4. CS exposure may accelerate pathological changes and cognitive impairment in 5xFAD mice by affecting energy metabolism through the PPAR signaling pathway. Show less
no PDF DOI: 10.1016/j.fct.2025.115596
APOA4
Meng Wang, Zhao Liu, Shuxun Ren +16 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.105894
BCKDK
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
Xiaolei Song, Chenchen Wang, Qin Ding +8 more · 2025 · Journal of controlled release : official journal of the Controlled Release Society · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disorder. The vicious circle between amyloid-β peptide (Aβ) overgeneration and microglial dysfunction is an important path Show more
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disorder. The vicious circle between amyloid-β peptide (Aβ) overgeneration and microglial dysfunction is an important pathological event that promotes AD progression. However, therapeutic strategies toward only Aβ or microglial modulation still have many problems. Herein, inspired by the Aβ transportation, an Aβ-derived peptide (CKLVFFAED) engineered biomimetic nanodelivery system (MK@PC-R NPs) is reported for realizing BBB penetration and reprogram neuron and microglia in AD lesion sites. This hollow mesoporous Prussian blue-based MK@PC-R NPs carrying curcumin and miRNA-124 can down-regulate β secretase expression, thereby inhibiting Aβ production and reducing Aβ-induced neurotoxicity. Meanwhile, MK@PC-R NPs with excellent antioxidant and anti-inflammatory properties could normalize the microglial phenotype and promote Aβ degradation, providing neuroprotection. As expected, after treatment with MK@PC-R NPs, the Aβ burdens, neuron damages, neuroinflammation, and memory deficits of transgenic AD mice (APP/PS1 mice) are significantly attenuated. Overall, this biomimetic nanodelivery system with anti-Aβ and anti-inflammatory properties provides a promising strategy for the multi-target therapy of early AD. Show less
no PDF DOI: 10.1016/j.jconrel.2024.12.060
BACE1
Chenwen Li, Yidan Chen, Yuan Li +9 more · 2025 · Acta pharmaceutica Sinica. B · Elsevier · added 2026-04-24
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate Show more
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate injection, which results in rapid elimination and poor patient compliance. Consequently, oral delivery strategies capable of targeting atherosclerotic plaques are imperative for nucleic acid therapeutics. Herein we report the development of yeast-derived capsules (YCs) packaging an antisense oligonucleotide (AM33) targeting microRNA-33 (miR-33) for the oral treatment of atherosclerosis. YCs provide stability for AM33, preventing its premature release in the gastrointestinal tract. AM33-containing YCs, defined as YAM33, showed high transfection in macrophages, thus promoting cholesterol efflux and inhibiting foam cell formation by regulating the target genes/proteins of miR-33. Orally delivered YAM33 effectively accumulated within atherosclerotic plaques in Show less
📄 PDF DOI: 10.1016/j.apsb.2025.07.039
APOE
Lu Shen, Wenqing Zhai, Ping Jiang +6 more · 2025 · American journal of preventive cardiology · Elsevier · added 2026-04-24
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether syst Show more
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether systemic inflammation modulates Lp(a)-associated coronary stenosis in chronic coronary syndromes (CCS). A total of 1513 participants undergoing angiography at a tertiary cardiology center in China were included in our retrospective, cross-sectional study. Participants were categorized into normal, mild, and severe groups based on the Gensini Scores, which quantitatively assess stenosis severity. Multinomial logistic models were calculated according to accompanying systemic inflammation concentration. Participants with elevated Lp(a) levels had a high coronary stenosis risk: fully adjusted model odds ratios (ORs) [95% confidence intervals (CIs)] for the mild vs. normal and severe vs. normal groups were 1.47 (1.11-1.96) and 1.68 (1.21-2.33). Notably, the strongest Lp(a)-coronary stenosis associations after multi-variable adjustment persisted only in low inflammation concentration [systemic inflammation response index (SIRI) < 0.64)] [mild vs. normal, OR 2.03, 95% CI 1.17-3.54, Elevated Lp(a) correlates with coronary stenosis only in low inflammation concentration. Considering systemic inflammation in personalized Lp(a)-lowering therapies is more conducive for CCS managements. Show less
📄 PDF DOI: 10.1016/j.ajpc.2025.101324
LPA