👤 Hongli 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, Hong-Tao Li, Enhong Li, Xiangnan Li, Yong-Jun Li, Ziming Li, Hang Li, Rongqing Li, Xihao Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Yicun Li, Xiao-Lin Li, Jiajie Li, Zhao-Yang Li, Shunqin Li, Xinjia Li, K-L Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Youran Li, Peiwu Li, Yongmei Li, Changyu Li, Peilin Li, Ran 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, Lanzhou Li, Zhi-Peng Li, Tingsong Li, Binjun Li, Chen Li, Yawei Li, Jiayang Li, Zunjiang Li, Chao Bo Li, Minglong Li, Donghua Li, Siming Li, Wenzhe Li, Fengli Li, Song Li, Zihan Li, Hsin-Hua Li, Jin-Long Li, Hongxin Li, Dongfeng Li, You Li, Xueyang Li, Caiyu Li, Xuelin Li, Fa-Hui Li, Zhen-Yuan Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Shiyu Li, Bao Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Dejun Li, Changwei 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, Z-H Li, Yongli Li, Baohong Li, Hujie Li, Yue-Ming Li, Shuyuan Li, Zhaohan Li, L Li, Yuanmei Li, Alexander Li, Yanwu Li, Hualing Li, Wen-juan Li, Sibing Li, Qinghe Li, Xining Li, Pilong Li, Yun-Peng Li, Zonghua Li, C X Li, Jingya Li, Liqin Li, Huanan Li, Youjun Li, Zheng-Dao Li, Miao X Li, Zhenshu Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wei Li, Wen-Ying Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Ming Li, Kangli Li, Runwen Li, Wenbo Li, Yarong Li, Side Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Shuguang Li, Xiuzhen Li, Chuan-Hai Li, Lingxi Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Qin Li, Zhongyu Li, Zhen-Yu Li, Deyu 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, Junping Li, Xiao Li, PeiQi Li, Naishi Li, Xiaobing 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, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Suyan Li, Chengquan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, Xue Cheng Li, Ya-Jun Li, Wenyong Li, Ding-Biao Li, Tianjun Li, Desen Li, Xiying Li, Yansong 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, Yan-Hua Li, Jing-Yao Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, L K Li, Wan Jie 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, L-Y Li, Xiuqi Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Yu Li, Minhui Li, Yvonne Li, Yiwei Li, Jiayuan Li, Xiangzhe Li, Zhichao Li, Yige Li, Siguang Li, Minglun Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chiyang Li, Chunlan Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Jing Li, Si Li, Xiangyun Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Zijing Li, Dengke Li, Yuchuan Li, Wentao Li, Qingling Li, Rui-Han Li, Xuhong Li, Dong Li, Hongyun Li, Zhonggen Li, Xiong Li, Penghui Li, Xiaoxia Li, Dezhi Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Sheng-Jie Li, Defa Li, Ying-Qing Li, X L Li, Yuyan Li, Kawah Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Zhenfei Li, Shupeng Li, Sha-Sha Li, Ziyu Li, Panyuan Li, Gang Li, Mengxuan Li, Zhuo Li, Hong-Wen Li, Han-Wei Li, Weina Li, Xiaojuan 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, Shilun Li, Shi-Hong 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, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Supeng Li, Lijun Li, Hening Li, Yiju Li, Yuanhe Li, Guangxiao Li, Fengxia 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, Chaochen Li, Chunxia Li, Zhen-Li Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Zhengying Li, Yali Li, Zhaoshui Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, 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, Wan-Xin Li, Ning Li, Ruobing Li, Xia Li, Meitao Li, Yongjing Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Jiqing Li, Boxuan Li, Huixue 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, 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, Youming Li, Mi Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Fengfeng Li, Yumiao Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Xingye Li, Xiangjun Li, Junxu Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Yuxi Li, Qingyang Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Zhaoping Li, Xingyu Li, Xiaolei Li, Zhenlu Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Zhenhui Li, Cheung Li, Zhenming Li, Xuelian Li, Shu-Fen Li, Chunjun Li, Changyan Li, Mulin Jun Li, Yinghua Li, Shangjia Li, Yanjie Li, Jingjing Li, Suhong Li, Xinping Li, Siyu Li, Chaoying Li, Qiu Li, Juanjuan Li, Xiangyan Li, Guangzhen Li, Kunlun Li, Xiaoyu Li, Shiyun Li, Yaobo Li, Shiquan Li, Mei Li, Xuewang Li, Xiangdong Li, Jifang Li, Zhenjia Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiao-Li Li, Xiaoya Li, Shan Li, Shitao Li, 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, Man-Zhi Li, Xiancheng Li, Yanmei Li, De-Jun Li, Zhihua Li, Junxian Li, Keqing Li, Shuwen Li, Danxi Li, Saijuan Li, Minqi Li, Lingjun Li, Mimi Li, 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, Nan-Nan Li, Chanjuan Li, Hongming Li, Lan-Lan Li, Shuang Li, Yanchuan Li, Lingyi Li, Wanting Li, Bai-Qiang Li, Gong-Hua Li, Zhengyu Li, Chunmiao Li, Jiong-Ming Li, Yongqiang Li, Linsheng Li, Weiguang Li, Mingyao Li, Guoqing Li, Ze Li, Xiaomeng Li, R H L Li, Yuanze Li, Yunqi Li, Yuandong Li, Guisen Li, Jinglin Li, Dongyang Li, Mingfang Li, Honglong Li, Hanmei Li, Chenmeng Li, Changcheng Li, Shiyang Li, Shiyue Li, 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, Zhaosha Li, Xuesong 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, Sujing Li, Yuhua Li, Xuri Li, Wenzhuo Li, Y Li, Deqiang Li, Mingyue Li, Caixia Li, Zipeng 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, Bingsong Li, Shuai Li, Anqi Li, Ting Li, Zhenyu Li, Xiaonan Li, Xiaoju Li, Xiang-Yu Li, Duan Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Yanchang Li, Xunjia Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, Chunya Li, Zong-Xue Li, En-Min Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Jinhua Li, Min-jun Li, Qian-Qian Li, Yuanheng Li, Chunxiao Li, Wenli Li, Shijun Li, Kuan Li, Mengze Li, Baoguang Li, Jie-Shou Li, Kaiwei Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Yu-Sheng Li, Junxin Li, Wei-Jun Li, Guoyan Li, Junjie Li, Fei-Lin Li, Nuomin Li, Shanglai Li, Shulin Li, Yanyan Li, Yue Li, Taibo Li, Junqin Li, Zhongcai Li, Jun-Ru Li, Xueying Li, JunBo Li, Xiaoqi Li, Zhaobing Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, Tsai-Kun Li, Chen-Chen Li, Shujing Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Xiyun Li, Yi-Wen Li, Huifeng Li, Rulin Li, Ya-Pei Li, Shihong Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Wenjia Li, Min-Dian Li, Xiatian Li, Ding-Jian Li, Hongwei Li, Yangxue Li, Xiao-Qiang Li, Danni Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Yiqiang Li, Pengyang Li, Kun-Xin Li, Xiawei Li, Binglan Li, Yutong Li, Zesong Li, Xiangpan Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Boru Li, Yinxiong Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Hong-Yu Li, Chuanning Li, Weijian Li, Changhui Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Dechao Li, Chunxing Li, Wenxia Li, Guoxiang Li, Ziru Li, Qiao-Xin Li, Shu-Fang Li, Huang Li, Qiusheng Li, 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, 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, Ying-Bo Li, Fei Li, Xionghui Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Kang Li, Hongmei Li, Peilong Li, Yinghao Li, Xu-Wei Li, Mengsen Li, Lirong Li, Wenhong Li, Quanpeng Li, Audrey Li, Yijian Li, Yajiao Li, Guang Y Li, Xianyong Li, Qilan Li, Shilan Li, Qiuhong Li, Zongyun Li, Xiao-Yun Li, Guang-Li Li, Cheng-Lin Li, Bang-Yan Li, Enxiao Li, Jianrui Li, Yousheng Li, Wen-Ting Li, Guohua Li, Kezhen Li, Xingxing Li, Guoping Li, Ellen Li, A Li, Simin Li, Xue-Nan Li, Yijie Li, Weiguo Li, Xiaoying Li, Shengsheng Li, Suwei Li, Shuyu D Li, Ruiwen Li, Jiandong 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, 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, Shaodan Li, Meng-Hua Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Zheng Li, Ming-Hao Li, Donghe Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Jingqi Li, Menghua Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Xiao-Kang Li, Chong Li, Fugen Li, Hanqi Li, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zizhuo Li, Zhuorong Li, X-H Li, Dong Sheng Li, Xianrui Li, Lan-Juan Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Bing-Heng Li, Xiaoman Li, Huanqiu Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Jinhui Li, Zhifei Li, Ying Li, Jianlin Li, Yanshu Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Longyu Li, Jinku Li, Guiying Li, X B Li, Cuiling Li, Changgui Li, Zhisheng Li, Xuekun Li, Yuguang Li, Wenke Li, Jiayi Li, Jianguo Li, En Li, Ximei Li, Shaoyong Li, Kai-Wen Li, Suwen Li, Peihua Li, Chang-Ping Li, Guangda Li, Yixue Li, Guandu Li, Junfeng Li, Xin-Chang Li, Jieming Li, Yue-Ying Li, Kongdong Li, Chunhui Li, Peiyu Li, Tongyao Li, Lian Li, Linfeng Li, Yuzhe Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Qifang Li, Xiaohua Li, Chang-Yan Li, Vivian Li, Duanxiang Li, Xiaolin Li, Meiting Li, Justin Li, Xue-Er Li, Zhuangzhuang Li, Hongchang Li, Xiaohui 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, Shiliang Li, Jia Li, Haimin Li, Qinrui Li, Sheng-Qing Li, Yiming Li, Xiao-Tong Li, Lingjie Li, Yiwen Li, Tie Li, Baoqi Li, Wei-Bo Li, Leyao Li, Xiaoyi Li, Xiao-Qin Li, Liyan Li, Xiaokun Li, Xinke Li, Ming-Wei Li, Wenfeng Li, Minzhe Li, Jiajing Li, Karen Li, Yanlin Li, Liao-Yuan Li, X Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Li-Na Li, Hengguo Li, An-Qi Li, Xuehua Li, Hui Li, AnHai Li, Chenli Li, Rumei Li, Zhengrui Li, Fangqi Li, Xiaoguang Li, Xian Li, Danjie Li, Yan-Yu Li, Vivian S W Li, Qinghua Li, Qinqin Li, Lipeng Li, Leilei Li, Ranchang Li, Defu Li, Lianyong Li, Amy Li, Zhou Li, Q Li, Haoyu Li, Xiaoyao Li, M-J Li, Jiao-Jiao Li, Rongling Li, Zhu Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Guangqiang Li, Jian'an Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Yu-I Li, Shunhua Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Ziqi Li, Tianjiao Li, Shen Li, Gui-Rong Li, Yunfeng Li, Shufen Li, Yunpeng Li, Yueqi Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Xu Li, Pinghua Li, Shi-Fang Li, Shude Li, Zhibin Li, Yaxiong Li, Zhenli Li, Qing-Fang Li, Rosa J W Li, Yunxiao Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, 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, 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, Wenjian Li, Jialin Li, He Li, Bichun Li, Xiong Bing Li, Hanqin Li, Qingjie Li, Wen Lan Li, Han Li, Guoge Li, Wen-Wen Li, Keying Li, Yutang Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Hankun Li, Hongling Li, Xiangrui Li, Chaojie Li, Michelle Li, Caolong Li, Zhifan Li, J Li, Zhi-Jian Li, Jianwei Li, Yan-Guang Li, Jiexin Li, Hongyan Li, Ji-Min Li, Zhen-Xi Li, Peipei Li, Guangdi Li, Tian-Yi Li, Xiaxia Li, Yuefeng Li, Nien Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Lin Li, Jieshou Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Hong-Lan Li, Mengqing Li, S L Li, Ben-Shang Li, Shunqing Li, Ming-Kai Li, Xionghao Li, Lan Li, Menglu Li, Huiqing Li, Yantao Li, Yanwei 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, Si-Wei Li, Ai-Qin Li, Zichao Li, Manru Li, Caili Li, Yingxi Li, Yuqian Li, Guannan Li, Wei-Dong Li, Cien Li, Qingyu Li, Xijing Li, Jingshang Li, Xingyuan Li, Dehua Li, Wenlong Li, Ya-Feng Li, Yanjiao Li, Jia-Huan Li, Yuna Li, Xudong Li, Guoxi Li, Xingfang Li, Shugang Li, Shengli Li, Jisheng Li, Rongyao Li, Xuan Li, Yongze Li, Yongxin Li, Ru Li, Lu Li, Jiangya Li, Yiche Li, Yilang Li, Zhuo-Rong Li, Bingbing Li, Qinglin Li, Runzhi Li, Yunshen Li, Jingchun Li, Qi-Jing Li, Hexin Li, Yanping Li, Zhenyan Li, H J Li, Ji Xia Li, Meizi Li, Yu-Ye Li, Qing-Wei Li, Qiang Li, Yuezheng Li, Hsiao-Hui Li, Zhengnan Li, L I Li, Jianglong Li, Hongzheng Li, Laiqing Li, Ningyang Li, Zhongxia Li, Guangquan Li, Xiaozheng Li, Hui-Jun Li, Shun Li, Guojun Li, Xuefei Li, Senlin Li, Hung Li, Jinping Li, Sainan Li, Huili 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, 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, Gan Li, Shichao Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Lihong Li, Chun Li, Jianan Li, Wenfang Li, Haixia Li, Sung-Chou Li, Xiangling Li, Lianhong Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Cheng Li, Zhao Li, Kui Li, Tiegang Li, Yunxu Li, Shuang-Ling Li, Zhong Li, Xiao-Long Li, Hung-Yuan Li, Xiaofei Li, Xuanfei Li, Zilin Li, Zhang Li, Jianxin Li, Mingqiang Li, H Li, Xiaojiao Li, Dongliang Li, Yinzhen Li, Chenxiao Li, Hongjia Li, Xiao-Jing Li, Yunsheng Li, Li-Min Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Daoyuan Li, Baichuan Li, Wenqi Li, Haibo Li, Zhenzhe Li, Jian-Mei Li, Xiao-Jun Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Qiao Li, Xueling Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Wanni Li, Yike Li, Yihan Li, Chitao Li, Haiyang Li, Junsheng Li, Jiayu Li, Xiaobai Li, Pingping Li, Mingquan Li, Wen-Ya Li, Suran Li, Yunlun Li, Rongxia Li, Yuanfang Li, Yingqin Li, Guoqin Li, Qiner Li, Huiqin Li, Jiafang Li, Shanhang Li, Chunlin Li, Han-Bing Li, Zongzhe Li, Jisen Li, Yikang Li, Si-Yuan Li, Caihong Li, Hongmin Li, Yajing Li, Peng Peng 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, Dazhi Li, Yubin Li, Yuhong Li, Beixu Li, Guiyuan Li, Di Li, Fengqiao Li, Yanbing Li, Suk-Yee Li, Yuanyuan Li, Jufang Li, Shengjie 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, Hongjuan Li, Yingjian Li, Zhirong Li, Wang Li, Mingyang Li, Weijun Li, Boyang Li, Senmao Li, Cai Li, Mingjie Li, Ling-Jie Li, Hong-Chun Li, Jingcheng Li, Ivan Li, Yaying Li, Mengshi Li, Liqun Li, Manxia Li, Ya Li, Changxian Li, Dan-Ni Li, Wen-Chao Li, Sunan Li, Zhencong Li, Chunqing Li, Jiong Li, Lai K Li, Yanni Li, Daiyue Li, Bingong Li, Huifang Li, Yongsheng Li, Xiujuan Li, Lingling Li, Chunxue Li, Yunlong Li, Xinhua Li, Jianshuang Li, Juanling Li, Minerva X Li, Xinbin Li, Alexander H Li, Xue-jing Li, Ding Li, Yuling Li, Wendeng Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Linyan Li, Shengze Li, Yanjun 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, Weiping Li, Huan Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Jiangan Li, Weihai Li, Yu-Kun Li, Hsiao-Fen Li, Zhaojin Li, Mengjiao Li, Bingxin Li, Wenjuan Li, Wenyu Li, Chia-Yang Li, Meng-Meng Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Wenlei Li, Xi-Xi Li, Mei-Lan Li, Wenjun Li, Haiyan Li, Jiaxin Li, Ming D Li, Chenguang Li, Ruyue Li, Xujun Li, Chi-Ming Li, Xiaolian Li, Yi-Ning Li, Dandan Li, Yunan Li, Zechuan Li, Jiazhou Li, Sherly X Li, Zhijun Li, Ya-Ge Li, Wanling Li, Yinyan Li, Qijun Li, Rujia Li, Guangli Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Wan-Shan Li, Xiaohan Li, Huijie Li, Zhongwen Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Xuejun Li, Fengxiang Li, Nana Li, Shunwang Li, Chao Li, Yaqing Li, Yaqiao Li, Jingui Li, Bingsheng Li, Huamao Li, Xiankun Li, Jingke Li, Xiaowei Li, Tianyao Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Hai-Yun Li, Haoran Li, Zhongxian Li, Xiaoliang Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Xinjian Li, Jialun Li, Rui Li, Zilu Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Xuyi Li, Binghua Li, Hanjun Li, Yunchu Li, Zhengyao Li, Jin-Qiu 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, Luyao Li, Chun-Xu Li, Weike Li, Desheng Li, Chuanbao Li, Zhixuan Li, Long-Yan Li, Fuyu Li, Chuzhong Li, M D Li, Yuan-Tao Li, Lingzhi Li, Kening Li, Guilan Li, Wanshi Li, Hengtong Li, Ling-Zhi Li, Yifan Li, Ya-Li Li, Xiao-Sa Li, Songyun Li, Xiaoran Li, 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, Wensheng Li, Dehai Li, Jiannan Li, Qingshang Li, Guanbin Li, Hanbin Li, Zhiyi Li, Xing Li, Wanwan Li, Jia Li Li, Zhaoyong Li, SuYun Li, Shiyi Li, Wan-Hong Li, Mingke Li, Suchun Li, 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, Lihua Li, Yilong Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Zhi-Yuan Li, Yanli Li, Jingfeng Li, Hai Li, Yuan-Jing Li, Kaibin 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, Mian Li, Yujun Li, Dalin Li, Lixi Li, Jin-Xiu Li, Kun Li, Qizhai Li, Jiwen Li, Pengju Li, Peifeng Li, Zhouhua Li, Ai-Jun Li, Qingqin S Li, Honglei Li, Guojin Li, Yueting Li, Xin-Yue Li, Dingchen Li, YaJie Li, Xiaoling Li, Yanqing Li, Jixuan Li, Zijian Li, Zhandong Li, Xuejie Li, Congjiao Li, Peining Li, Meng-Jun Li, Gaizhen Li, Huilin Li, Songtao Li, Liang Li, Fusheng Li, Huafang Li, Dai Li, Meiyue Li, Keshen Li, Kechun Li, Chenlu Li, Nianyu Li, Yuxin Li, X-L Li, Shaoliang Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Dongye Li, Tianye Li, Qun Li, Cuiguang Li, Zhen Li, Yuan Li, Chunhong Li, F Li, Mengling Li, Kunpeng Li, Jia-Da Li, Zhenghao Li, Chun-Bo Li, Zhantao Li, Baoqing Li, Pu Li, Xinle Li, Xingli Li, Bingkun Li, Nien-Chi Li, Wuguo Li, Bing-Hui Li, Tiewei Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Rong Li, Shikang Li, Wei-Yang Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Shishi Li, Bei-Bei Li, Hong-Lian Li, Haitong Li, Xiumei Li, Ruibing Li, Yuli Li, Melody M H 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, Ka Wan Li, Huiyou Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Yu-Hao Li, Gui-xing Li, Shunle Li, Shilin Li, Niu Li, Siyue Li, Diyan Li, Mengyao Li, Shili Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Meiqing Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Zonglin Li, Yinhao Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, Xiaoqin Li, L P Li, Chunmei Li, Runbing 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, Kainan Li, Guohui Li, Yongzhe Li, Xiaoyan Li, Qingfeng Li, Tianyi Li, Nanlong Li, Ping Li, Xu-Bo Li, Fangzhou Li, Nien-Chen Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Yuanchuang Li, Biao Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Hong-Yan Li, Shengbiao Li, Yue-Rui Li, Dalei Li, Ruidong Li, Zongjun Li, Y M Li, Changqing Li, Hanting Li, Dong-Jie Li, Xiaomin Li, Sijie Li, Dengxiong 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, Yixi Li, Chunjie Li, Shuyu Dan Li, S A Li, Tianfeng Li, Anna Fen-Yau Li, Minghui Li, Jiangfeng Li, Jinjie Li, Liming Li, Jie-Pin Li, Kaiyi Li, Junyi Li, Wenqun Li, Dongtao Li, Fengyuan Li, Guixia Li, Yinan Li, Aoxi Li, Zuo-Lin Li, Chenxi Li, Yuanjing Li, Zhengwei Li, Linqi Li, Xixi Li, Bingjue Li, Binghu Li, Yan-Chun Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Xiaotian Li, Zhenguang Li, Jia-Ru Li, Shuhui Li, Shu-Hong Li, Chun-Xiao Li, Pei-Qin Li, Shuyue Li, Mengying Li, Tongzheng Li, Fangyan Li, Quan-Zhong Li, Yihong Li, Duo Li, Yaxian Li, Dali Li, Zhiming Li, Xuemei Li, Hongxia Li, Yongting Li, Xueting Li, Danyang Li, Zhenjun Li, Ren Li, Tiandong Li, Hongye Li, Lanfang Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, Qiji Li, W J Li, Zhipeng Li, Zhijia Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaobo Li, Xiaoting Li, Ruotai Li, Meijia Li, Shujiao Li, Yaojia Li, Weirong Li, Xiao-Yao Li, Kun-Ping Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Runzhao Li, Yandong Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Yanxin Li, Yingjun Li, Xiufeng 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, Yueping Li, Changkai Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Rui-Jún Eveline Li, Xuanxuan 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, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Shaomin Li, Heying Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Hanxiao Li, Jiahao Li, Jiansheng Li, Shibao Li, Shuying Li, Kunlong Li, Xiaomei Li, Ruijin Li, Pengjie Li
articles
Boyang Zeng, Cong Ma, Shuaishuai Zhang +18 more · 2025 · Lipids in health and disease · BioMed Central · added 2026-04-24
Current evidence suggests that apolipoprotein E (APOE) is associated with lipid metabolism, cardiovascular diseases, and neurodegenerative disorders. However, the physiological pathways of APOE-mediat Show more
Current evidence suggests that apolipoprotein E (APOE) is associated with lipid metabolism, cardiovascular diseases, and neurodegenerative disorders. However, the physiological pathways of APOE-mediated inflammation remain incompletely elucidated, and a specific inflammatory marker that captures the pro-inflammatory activity of the APOE ε4 allele remains elusive. As a composite peripheral blood biomarker, Systemic immune-inflammation index (SII) is a novel marker of inflammation. This study aimed to investigate the association between APOE alleles and Systemic Immune-Inflammation Index. A total of 13,926 participants (9,098 males and 4,828 females) were recruited from The People’s Liberation Army General Hospital (November 2017 to July 2019). APOE alleles (ε2, ε3, and ε4) were determined by genotyping rs429358 and rs7412 SNPs. SII was calculated as (platelet count × neutrophil count)/lymphocyte count. Multivariable linear regression models (adjusted for demographics, lifestyle, and clinical covariates) and subgroup analyses were performed to assess the APOE-SII associations, with ε3 as the reference. The frequencies of APOE alleles ɛ3, ɛ2, and ɛ4 were70.7%, 13.8%, and 15.5% respectively in 13,926 Chinese patients. The mean SII was lower in ɛ2 carriers than in ɛ3 (373.74*10⁹/L vs. 403.53*10⁹/L, APOE contributes to elevated disease risk by inducing a state of chronic low-grade inflammation, resulting from modulation of both adaptive and innate immune responses. Show less
📄 PDF DOI: 10.1186/s12944-025-02842-w
APOE
Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB
Hong Tan, Li Li, YiPei Zhang +1 more · 2025 · Journal of multidisciplinary healthcare · added 2026-04-24
To identify distinct sleep quality profiles among patients undergoing maintenance hemodialysis (MHD) using latent profile analysis (LPA), and examine differences in perceived stigma across these sleep Show more
To identify distinct sleep quality profiles among patients undergoing maintenance hemodialysis (MHD) using latent profile analysis (LPA), and examine differences in perceived stigma across these sleep quality subtypes. From December 2024 to March 2025, a total of 334 MHD patients were recruited via convenience sampling from the nephrology departments of two tertiary hospitals in Xinjiang, China. Data were collected using structured questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), the Self-Rating Depression Scale (SDS), and the Social Impact Scale (SIS), along with sociodemographic and clinical information. LPA was employed to identify latent subgroups of sleep quality based on PSQI components. Multinomial logistic regression was used to determine predictors of sleep profile membership. Differences in stigma scores across sleep profiles were analyzed using non-parametric equivalents. Three distinct sleep profiles were identified: Class 1 - "overall better sleep", Class 2 - "short sleep duration and low efficiency", and Class 3 - "poor sleep quality with high medication use". Multinomial logistic regression identified comorbid heart failure (OR=2.867, Patients with MHD exhibit heterogeneous patterns of sleep disturbance, which are associated with varying levels of perceived stigma. Those with the poorest sleep quality and highest reliance on medication experience the most pronounced stigma. Tailored interventions addressing sleep-related issues and psychosocial factors may help reduce stigma and improve patient well-being. Show less
📄 PDF DOI: 10.2147/JMDH.S557424
LPA
Guoshuai Xu, Qinghong Zhang, Renjia Cheng +2 more · 2025 · Autophagy · Taylor & Francis · added 2026-04-24
Macropinocytosis is a nonselective form of endocytosis that allows cancer cells to largely take up the extracellular fluid and its contents, including nutrients, growth factors, etc. We first elaborat Show more
Macropinocytosis is a nonselective form of endocytosis that allows cancer cells to largely take up the extracellular fluid and its contents, including nutrients, growth factors, etc. We first elaborate meticulously on the process of macropinocytosis. Only by thoroughly understanding this entire process can we devise targeted strategies against it. We then focus on the central role of the MTOR (mechanistic target of rapamycin kinase) complex 1 (MTORC1) in regulating macropinocytosis, highlighting its significance as a key signaling hub where various pathways converge to control nutrient uptake and metabolic processes. The article covers a comprehensive analysis of the literature on the molecular mechanisms governing macropinocytosis, including the initiation, maturation, and recycling of macropinosomes, with an emphasis on how these processes are hijacked by cancer cells to sustain their growth. Key discussions include the potential therapeutic strategies targeting macropinocytosis, such as enhancing drug delivery via this pathway, inhibiting macropinocytosis to starve cancer cells, blocking the degradation and recycling of macropinosomes, and inducing methuosis - a form of cell death triggered by excessive macropinocytosis. Targeting macropinocytosis represents a novel and innovative approach that could significantly advance the treatment of cancers that rely on this pathway for survival. Through continuous research and innovation, we look forward to developing more effective and safer anti-cancer therapies that will bring new hope to patients. Show less
no PDF DOI: 10.1080/15548627.2025.2452149
PIK3C3
Yuanzhen Zhang, Xiaozhi Hu, Zhonglian Cao +10 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Metabolic dysfunction-associated fatty liver disease (MAFLD), driven by dyslipidemia and hepatic lipid deposition, has become a major public health concern. Angiopoietin-like protein 3 (ANGPTL3), a li Show more
Metabolic dysfunction-associated fatty liver disease (MAFLD), driven by dyslipidemia and hepatic lipid deposition, has become a major public health concern. Angiopoietin-like protein 3 (ANGPTL3), a lipoprotein lipase (LPL) activity inhibitor, can inhibit triglycerides (TGs) decomposition, and fibroblast growth factor 21 (FGF21) enhances fatty acids' β-oxidation in liver. We constructed a novel fusion protein combining the anti-ANGPTL3 nanobody FD03 and FGF21 (FD03-FGF21), which exerted appropriate binding affinities to ANGPTL3 and β-Klotho respectively. Our results showed FD03-FGF21 restored bioactivity of LPL which inhibited by ANGPTL3 and activated downstream pathway of FGF21 in iLite FGF21 assay-ready cells. Next, FD03-FGF21 showed a significant therapeutic effect in MAFLD mice, including attenuation of metabolic dyslipidemia, hepatic lipid accumulation, and impaired glucose tolerance. Compared to other treatments, FD03-FGF21 achieved the most significant therapeutic effect with a 79.78 % attenuation of low-density lipoprotein cholesterol (LDL-C) and a 95.8 % reduction of hepatic lipid accumulation. Mechanistically, transcriptomic analysis revealed that differential expression genes (DEGs) were principally clustered into lipid metabolism and oxidative stress pathways after the fusion protein treatment, especially the key lipid metabolism genes of LDLR and CD36 were significantly upregulated and downregulated respectively, as confirmed by WB. Furthermore, lipidomic and metabolomic analysis indicated the fusion protein ameliorated disorders in lipid and protein metabolism mainly through the downregulation of DG and upregulation of PC. Hepatic oxidative stress and inflammation were significantly reduced after administration of the fusion protein in MAFLD mice. Collectively, FD03-FGF21 represents an effective therapeutic strategy for MAFLD therapy through ameliorating lipid metabolism and oxidative stress. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.148726
LPL
Wei Wang, Zhaosu Song, Ye Chen +6 more · 2025 · Journal of food science · Blackwell Publishing · added 2026-04-24
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi- Show more
Polygonum multiflorum Thunb., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi-component activity. The effectiveness of these botanical extracts is thought to involve complex interactions among diverse constituents; however, the molecular basis of such interactions remains insufficiently understood. In this study, we explored the anti-inflammatory properties of the ethanol extract of Polygonum multiflorum (PME) through a combination of chemical profiling and computational analysis. PME was found to reduce the production of nitric oxide, inducible nitric oxide synthase, and interleukin-6 in LPS-stimulated RAW 264.7 macrophages. Using HS-SPME-GC-MS in conjunction with network pharmacology, we identified 32 volatile constituents, among which five core compounds were predicted to be associated with three inflammation-related targets: ESR1, FASN, and NR1H3. Dual-ligand molecular docking and molecular dynamics simulations suggested that the sequence of ligand binding may influence the stability and interaction patterns of protein-ligand complexes, offering insights into possible mechanisms of synergy and antagonism mediated by key residues such as ARG394 in ESR1. Overall, these findings contribute to a better understanding of how binding order and structural context may shape constituent-target interactions, providing a basis for the further development of multi-component natural product strategies against inflammation. This study underscores the relevance of incorporating multi-ligand dynamics into natural product research and presents an integrated experimental-computational framework to investigate the cooperative or competitive behaviors of functional food constituents, thereby supporting the rational design of optimized multi-target formulations. Show less
no PDF DOI: 10.1111/1750-3841.70708
NR1H3
Yuwei Bai, Jianglong Li, Xueqian Wu +8 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-l Show more
Hyperlipidemia is a common metabolic disorder and a risk factor for cardiovascular disease. The traditional medicine herb, Hippophae rhamnoides L., known as sea buckthorn, has anti-obesity and lipid-lowering effects, while Silybum marianum (L.) Gaertn, known as milk thistle, has hepatoprotective properties and exhibits antioxidant effects. To evaluate the effect of sea buckthorn and milk thistle solid beverage (H-S solid beverage) in alleviating hyperlipidemia in rats and explore the underlying mechanisms by analyzing plasma and liver metabolomics, lipidomics, and liver transcriptomics. A hyperlipidemic rat model was established after 2 weeks of high-fat diet (HFD) feeding in Sprague Dawley rats. The administered doses of H-S solid beverage were 0.30 g/kg/d, 0.15 g/kg/d and 0.075 g/kg/d. Serum biochemical parameter detection, histopathological section analysis, untargeted plasma and liver metabolomics, lipidomics, and liver transcriptomics were performed to determine the therapeutic effects of H-S solid beverage and predict the related pathways in rats with hyperlipidemia. Changes in genes and proteins related to lipid metabolism were detected using real-time quantitative polymerase chain reaction and western blotting. Eighty-nine components were identified in H-S solid beverage using ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry, with flavonoids being the major constituents. The H-S solid beverage significantly reduced body weight, liver index, body fat percentage, lipid accumulation, and liver injury in HFD-fed rats. Fatty acids (FA), bile acid, phosphatidyl ethanolamine, phosphatidylcholine, triglyceride, cholesterol ester, diglyceride and phosphatidylinositol levels were significantly altered in the liver and plasma. Moreover, the transcriptomic analysis suggested that H-S solid beverage significantly altered the hepatic gene expression of cholesterol synthesis (Pdk4, Hmgcs1, and Dhcr24), lipogenesis (Scd, Angptl4, and Angptl8), and FA β-oxidation (Cpt1α, Pparδ, Acsl, Pgc-1α, and Pla2g2d). The solid beverage of sea buckthorn and milk thistle was firstly demonstrated to ameliorate HFD-induced hyperlipidemia. The lipid-lowering and hepatoprotective effects of H-S solid beverage significantly regulated cholesterol synthesis and de novo lipogenesis, as well as FA β-oxidation. In summary, this study highlights the potential of H-S solid beverages for the treatment of hyperlipidemia. Show less
no PDF DOI: 10.1016/j.phymed.2025.156920
ANGPTL4
Shuanghui Chen, Yan Lu, Hao Chen +6 more · 2025 · Molecular biology and evolution · Oxford University Press · added 2026-04-24
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins Show more
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins and admixture history remain largely unexplored. Here, we present the first comprehensive genomic study of Kirgiz populations from Xinjiang, China (XJ.KGZ, n = 36) and their counterparts in Kyrgyzstan (KRG), integrating genome-wide data of 2,406 global individuals. Our analyses reveal four primary ancestry components in XJ.KGZ: East Asian (41.7%), Siberian (25.6%), West Eurasian (25.2%), and South Asian (7.6%). Despite close genetic affinity (FST = 0.13%), XJ.KGZ and KRG diverged ∼447 years ago, with limited gene flow post-split. A two-wave admixture model elucidates their demographic history: an initial East-West Eurasian mixture ∼2,225 years ago, likely reflecting west-east contacts during the period of the Warring States and the Qin Dynasty, followed by secondary admixture events (∼875 to 425 years ago) linked to historical migrations under Mongol and post-Mongol rule. Local adaptation signatures implicate genes critical for cellular tight junction (e.g. PATJ), pathogen invasion (e.g. OR14I1), and cardiac functions (e.g. RYR2) with allele frequency deviations suggesting ancestry-specific selection. While no classical high-altitude adaptation genes (e.g. EPAS1) showed selection signals, RYR2 and C10orf67-implicated in hypoxia response in Tibetan fauna-displayed Western ancestry bias, hinting at convergent adaptation mechanisms. This study advances our understanding of the genetic makeup and admixture history of the Kirgiz people and provides novel insights into human dispersal in Central Asia. Show less
no PDF DOI: 10.1093/molbev/msaf196
PATJ
Xinqiao Chu, Yaning Biao, Hongzheng Li +9 more · 2025 · Lipids in health and disease · BioMed Central · added 2026-04-24
Lipid metabolism may be linked to chronic gastritis, but its causal role remains unclear. While current research emphasizes inflammation, mucosal changes, immune regulation, genetics, and the gut micr Show more
Lipid metabolism may be linked to chronic gastritis, but its causal role remains unclear. While current research emphasizes inflammation, mucosal changes, immune regulation, genetics, and the gut microbiota, the contribution of lipid metabolism is understudied. This study aims to evaluate the impact of serum lipids and the mechanistic roles of lipid-lowering drug targets in chronic gastritis. We conducted a cross-sectional study using data from real world. Multivariable logistic regression was performed to assess the association between serum lipid profiles and gastritis. Mendelian randomization (MR) analyses based on genome-wide association study (GWAS) datasets were performed to detect the causal relationship of serum lipids, plasma lipid species, and lipid-lowering drug targets. Experimental validation was conducted using high-fat diet (HFD)-fed mice and chemically induced CAG rat models. Four thousand sixty one person, including 1,023 patients with chronic atrophic gastritis (CAG), 1,742 with non-atrophic gastritis (NAG), and 1,296 as healthy population were included in the analysis. Through covariates adjustment, TC, ApoA1, and HDL-C showed to be associated with an increased risk of chronic gastritis, whereas TG exhibited a protective effect. MR analysis confirmed a significant inverse causal relationship between TG and gastritis (OR = 0.889, 95% CI: 0.825-0.958). Ten plasma lipid species and lipid-lowering gene targets, including LPL and APOC3, were identified as causally associated with disease risk. Mediation analysis revealed six plasma lipid species as potential intermediaries linking genetic variation to gastritis. In vivo experiments demonstrated progressive hepatic steatosis and mild gastric mucosal changes in HFD-fed mice. Immunohistochemical analysis further revealed a significant reduction in LPL and APOC3 expression in gastric tissue (P < 0.05). In the CAG rat model, histological analysis revealed hepatocyte disarray, edema, and gastric mucosal atrophy. Elevated levels of TNF-α, IL-6, IL-1β and decreased levels of GAS-17 and PG I/II were also observed (P < 0.05). Western blot analyses further confirmed the downregulation of LPL and APOC3 expression in gastric tissue (P < 0.05). This study provides genetic and experimental evidence, supporting a causal role of lipid metabolism in chronic gastritis. LPL and APOC3 are implicated in its pathogenesis, highlighting potential lipid-targeted strategies for prevention and treatment. Show less
📄 PDF DOI: 10.1186/s12944-025-02782-5
APOC3
Zejun Fan, Zhenyu Li, Yiqing Jin +9 more · 2025 · Life medicine · Oxford University Press · added 2026-04-24
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-th Show more
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-throughput screening. However, automated methods for evaluating and characterizing blastoid morphology are lacking. We developed a deep-learning model-deepBlastoid-for automated classification of live human blastoids using only brightfield images. The model processes 273.6 images per second with an average accuracy of 87%, which is further improved to 97% by integrating a Confidence Rate metric. deepBlastoid outperformed human experts in throughput while matching accuracy in blastoid classification. We demonstrated the utility of the model in two use cases: (i) systematic assessment of the effect of lysophosphatidic acid (LPA) on blastoid formation and (ii) evaluating the impact of dimethyl sulfoxide (DMSO) on blastoid formation. The evaluation results of deepBlastoid using over 10,000 images were consistent with the known drug effects and showed subtle but significant effects that might have been overlooked in manual assessments. The publicly available deepBlastoid model enables researchers to train customized models based on their imaging and protocols, providing an efficient, automated tool for blastoid classification with broad applications in research, drug screening, and Show less
📄 PDF DOI: 10.1093/lifemedi/lnaf026
LPA
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
Weiyao Zhu, Yu Wang, Ming Qin +3 more · 2025 · Aging and disease · added 2026-04-24
Alzheimer's disease (AD) represents a neurodegenerative condition characterized by steadily increasing prevalence and incidence, arising significant challenge to both patients and social insurance. Ho Show more
Alzheimer's disease (AD) represents a neurodegenerative condition characterized by steadily increasing prevalence and incidence, arising significant challenge to both patients and social insurance. However, the etiology of AD remains controversial so far, and pathogenesis is far more complicated. Presently, no definitive therapeutic methodologies were available for AD, and only partial symptomatic relief can be achieved. Consequently, early diagnosis and intervention are emergently needed for AD patients. The diagnostic criteria for AD are continuously evolving, and biomarker testing is becoming increasingly critical for diagnosis. Currently, the diagnosis of AD primarily relies on the detection of pathological proteins through cerebrospinal fluid (CSF) testing and positron emission tomography (PET). However, factors such as high costs, operational contraindications, and invasiveness limited the application of these technologies, making them particularly challenging to implement in large-scale clinical trials and screenings. Core fluid biomarkers for AD including β-amyloid (Aβ), phosphorylated tau protein (p-tau), total tau protein (t-tau), and their combinations were found in CSF. Although these biomarkers were demonstrated with significant specificity and sensitivity, challenges remain high concerning the collection of CSF. Blood-derived biomarkers for Aβ and tau proteins are essential for preliminary screening, diagnosis, and monitoring of AD. Additionally, other bodily fluids such as saliva, urine, and tears have been investigated for their potential as biomarkers, offering unique characteristics and applications. Emerging biomarkers, including neurofilament light chain (NfL), neurogranin (Ng), Beta-site APP cleaving enzyme 1 (BACE1), synaptosome associated protein 25 (SNAP-25), as well as inflammation-related and gene-related factors, provided valuable insights into the diagnosis and pathogenesis of AD from diverse perspectives. Despite the substantial progress made in AD biomarker research, there are still baskets of limitations concerning the complication of the disease. The current review focused on the reported literature to summarize the biomarkers associated with AD. By critically analyzing studies published over the past decade, we aimed to strengthen the recent research progress, theoretical frameworks, and unresolved challenges related to AD biomarkers. Show less
no PDF DOI: 10.14336/AD.2025.0761
BACE1
Meng Wang, Zhao Liu, Shuxun Ren +16 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.105894
BCKDK
Keyan Wang, Haiyu Li, Yong Zhang +2 more · 2025 · Circulation. Cardiovascular imaging · added 2026-04-24
no PDF DOI: 10.1161/CIRCIMAGING.124.017837
MYBPC3
Ping Huang, Yong Zhao, Haiyan Wei +8 more · 2025 · International journal of chronic obstructive pulmonary disease · added 2026-04-24
In preliminary research and literature review, we identified a potential link between chronic obstructive pulmonary disease (COPD) and lipid metabolism. Therefore, this study employed Mendelian random Show more
In preliminary research and literature review, we identified a potential link between chronic obstructive pulmonary disease (COPD) and lipid metabolism. Therefore, this study employed Mendelian randomization (MR) analysis to investigate the potential causal connection between blood lipids and COPD. A genome-wide association study (GWAS) on COPD was conducted, encompassing a total of 112,583 European participants from the MRC-IEU. Additionally, extensive UK Biobank data pertaining to blood lipid profiles within European cohorts included measurements for low-density lipoprotein cholesterol (LDL-C) with 440,546 individuals, high-density lipoprotein cholesterol (HDL-C) with 403,943 individuals, triglycerides (TG) with 441,016 individuals, total cholesterol (TC) with 187,365 individuals, apolipoprotein A-I (apoA-I) with 393,193 individuals, and apolipoprotein B (apoB) with 439,214 individuals. Then, MR analyses were performed for lipids and COPD, respectively. The primary analytical technique employed was the inverse-variance weighted (IVW) approach, which included a 95% confidence interval (CI) to calculate the odds ratio (OR). Additionally, a sensitivity analysis was conducted to assess the dependability of the MR analysis outcomes. MR analysis was primarily based on IVW, unveiled a causal link between COPD and LDL-C (OR=0.994, 95% CI (0.989, 0.999), P=0.019), TG (OR=1.005, 95% CI (1.002, 1.009), P=0.006), and apoA-I (OR=0.995, 95% CI (0.992, 0.999), P=0.008), in addition, no causal link was found with HDL-C, TC, apoB. Sensitivity analysis demonstrated the robustness of these causal relationships. However, through multivariate MR(MVMR) and multiple testing correction, LDL-C and TG had no causal effect on the outcome. ApoA-I remained a protective factor for the risk of COPD (OR=0.994, 95% CI (0.990-0.999), P=0.008). Through MR analysis, this study offers evidence of a causal link between apoA-I with COPD. This further substantiates the potential role of lipid metabolism in COPD, and has significant clinical implications for the prevention and management of COPD. Show less
📄 PDF DOI: 10.2147/COPD.S476833
APOB
Jun Cheng, Jiafan Cao, Yalan Yang +16 more · 2025 · Cancer letters · Elsevier · added 2026-04-24
Tumorigenesis is typically accompanied by cellular dedifferentiation and the acquisition of stem cell-like attributes. However, few studies have comprehensively evaluated the putative relationships be Show more
Tumorigenesis is typically accompanied by cellular dedifferentiation and the acquisition of stem cell-like attributes. However, few studies have comprehensively evaluated the putative relationships between these characteristics and various cancers. Here, we integrated gene expression and DNA methylation quantitative trait loci (cis-eQTL and cis-mQTL) data from the blood to perform multi-omics Mendelian randomization analysis. Our analyses revealed 967 stem cell-associated genes (P < 0.05) and 11,262 methylation sites (P < 0.01) significantly related to 12 cancers. SMAD7 (cg14321542) in colon cancer, IGF2 (cg13508136) in prostate cancer, and FADS1 (cg07005513) in rectal cancer were prioritized as candidate causal genes and regulatory elements. Notably, using cis-eQTL data from the corresponding tissue sites, we detected 16 stem cell-associated genes dramatically causally associated with six cancers (FDR<0.2). The gene THBS3 was particularly common in both blood and stomach tissues and exhibited prognostic significance. Furthermore, it was markedly associated with one microbial metabolic pathway and four immunophenotypes. Functional validation using the ECC12 gastric cancer cell line revealed that the inhibition of its expression could accelerate oxidative phosphorylation and reactive oxygen species production, reduce clonal proliferation ability, and promote the apoptosis of stomach tumor cells. Additionally, based on spatial transcriptomic data from gastrointestinal cancers, the results demonstrated the clusters enriched with the most stem cell-associated genes exhibited significantly enhanced tumor-promoting potency, and the THBS3-expressing cells displayed suppressed oxidative phosphorylation. Overall, this study enhances our understanding of tumorigenic mechanisms and aids in the identification of therapeutic targets. Show less
no PDF DOI: 10.1016/j.canlet.2025.217816
FADS1
Songfen Wu, Haicai Zhuang, Xidan Zhou +1 more · 2025 · Frontiers in behavioral neuroscience · Frontiers · added 2026-04-24
NRBF2, a component of autophagy-associated PIK3C3/VPS34-containing phosphatidylinositol 3-kinase complex, plays a crucial role in learning and memory processes, yet its specific impact on memory and t Show more
NRBF2, a component of autophagy-associated PIK3C3/VPS34-containing phosphatidylinositol 3-kinase complex, plays a crucial role in learning and memory processes, yet its specific impact on memory and the underlying molecular mechanisms remains unclear. Here, we utilized NRBF2 knockout mice to examine its influence on the time course of fear memory. Employing quantitative PCR, Western blot analysis, behavioral tests, and electrophysiology, we investigated the mechanisms through which NRBF2 affects memory processing. We observed an increase in This study offer new insights into the role of NRBF2 and highlight the potential of targeting NRBF2 as a therapeutic strategy for addressing cognitive deficits associated with various disorders. Show less
no PDF DOI: 10.3389/fnbeh.2025.1529522
PIK3C3
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
Xiaolan Jin, Huaying Cai, Zhengwei Li · 2025 · Frontiers in cellular and infection microbiology · Frontiers · added 2026-04-24
The gut-brain axis is increasingly recognized as a key regulator of neurological health, with microbial metabolites influencing neurotransmission, synaptic plasticity, and neuroinflammation. Probiotic Show more
The gut-brain axis is increasingly recognized as a key regulator of neurological health, with microbial metabolites influencing neurotransmission, synaptic plasticity, and neuroinflammation. Probiotics such as This study aimed to integrate microbial genomics, neurotranscriptomics, and Whole-genome functional annotation, metabolic pathway prediction, and biosynthetic gene cluster analysis were performed to identify neuroactive potential. Neuronal RNA-seq datasets (n = 3 biological replicates per condition) were analyzed using differential expression, WGCNA, and GSEA to capture transcriptomic responses. Multi-omics integration (CCA, DIABLO, SPIEC-EASI) linked microbial pathways with neuronal gene modules. Genomic analysis revealed that This multi-omics study demonstrates mechanistic evidence that probiotics exert complementary neuromodulatory effects: Show less
📄 PDF DOI: 10.3389/fcimb.2025.1732234
BDNF
Sijie Gu, Haoran Feng, Xiaomei Li +10 more · 2025 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Preventing the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remains a considerable clinical challenge. In this study, we elucidate the role of WNT5A in accelerating the A Show more
Preventing the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remains a considerable clinical challenge. In this study, we elucidate the role of WNT5A in accelerating the AKI-to-CKD transition and its underlying mechanisms. Renal biopsies from patients with AKI showed marked upregulation of WNT5A and its receptor, CD146, in proximal tubules, with higher expression in patients with CKD progression. In murine AKI models, Wnt5a knockdown attenuated CKD progression. Conversely, proximal tubular overexpression of Wnt5a exacerbated renal fibrosis in ischemia-reperfusion injury (IRI) mice, which was alleviated by Box5, a specific WNT5A antagonist. In vitro, WNT5A overexpression in transforming growth factor β (TGF-β)-stimulated HK-2 cells promoted CD146 upregulation, activated JNK phosphorylation, and enhanced SNAI1 expression. The genetic silencing of WNT5A/CD146 and JNK inhibition suppresses SNAI1 expression and attenuates fibrotic responses. Mechanistically, JNK-mediated c-JUN phosphorylation promoted its interaction with KLF5 at the SNAI1 promoter, driving renal fibrosis. Elevated serum levels of soluble CD146 correlated with renal function in patients with AKI and were higher in patients exhibiting CKD progression. Inhibition of WNT5A could serve as a therapeutic target for delaying renal fibrosis in AKI progression. Show less
no PDF DOI: 10.1016/j.ymthe.2025.06.039
SNAI1
Yi-Shan Sun, Lei Zhao, Cheng-Li Zheng +11 more · 2025 · Zoological research · added 2026-04-24
Mammalian scent glands mediate species-specific chemical communication, yet the mechanistic basis for convergent musk production remain incompletely understood. Forest musk deer and muskrat have indep Show more
Mammalian scent glands mediate species-specific chemical communication, yet the mechanistic basis for convergent musk production remain incompletely understood. Forest musk deer and muskrat have independently evolved specialized musk-secreting glands, representing a striking case of convergent evolution. Through an integrated multi-omics approach, this study identified cyclopentadecanone as a shared key metabolic precursor in musk from both forest musk deer and muskrat, although downstream metabolite profiles diverged between the two lineages. Single-cell RNA sequencing revealed that these specialized apocrine glands possessed unique secretory architecture and exhibited transcriptional profiles associated with periodic musk production, distinct from those in conventional apocrine glands. Convergent features were evident at the cellular level, where acinar, ductal, and basal epithelial subtypes showed parallel molecular signatures across both taxa. Notably, acinar cells in both species expressed common genes involved in fatty acid and glycerolipid metabolism (e.g., Show less
📄 PDF DOI: 10.24272/j.issn.2095-8137.2025.094
HSD17B12
Zhen Zhang, Rongyao Li, Yue Zhou +3 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Growing evidence indicates that healthy diets are associated with a slower progression of Alzheimer's disease (AD). Flavonoids are among the most abundant natural products in diets beneficial to AD, s Show more
Growing evidence indicates that healthy diets are associated with a slower progression of Alzheimer's disease (AD). Flavonoids are among the most abundant natural products in diets beneficial to AD, such as the Mediterranean diet. However, the effect and mechanism of these dietary flavonoids on AD remains incompletely understood. Here, we found that a representative dietary natural flavonoid, chrysin (Chr), significantly ameliorated cognitive impairment and AD pathology in APP/PS1 mice. Furthermore, mechanistic studies showed that Chr significantly reduced the levels of amyloid-β (Aβ) and phosphorylated tau (p-tau), along with dual inhibitory activity against β-site amyloid precursor protein cleaving enzyme 1 (BACE1) and glycogen synthase kinase 3β (GSK3β). Moreover, the effect of Chr was further confirmed by EW233, a structural analog of Chr that exhibited an improved pharmacokinetic profile. To further verify the role of Chr and EW233, we utilized our previously established chimeric human cerebral organoid (chCO) model for AD, in which astrogenesis was promoted to mimic the neuron-astrocyte ratio in human brain tissue, and similar dual inhibition of Aβ and p-tau was also observed. Altogether, our study not only reveals the molecular mechanisms through which dietary flavonoids, such as Chr, mitigate AD pathology, but also suggests that identifying a specific constituent that mimics some of the benefits of these healthy diets could serve as a promising approach to discover new treatments for AD. Show less
📄 PDF DOI: 10.1007/s12035-024-04557-y
BACE1
Chaoping Chen, Chenhao Li, Qingru Zhu +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metaboli Show more
Lifestyle improvement may help reverse prediabetes. Indicators such as Life's Essential 8 (LE8) and biological aging measures (phenotypic age, cardiovascular biological age) partially reflect metabolic status in prediabetes, but their predictive value for cardiovascular mortality and stroke in this population remains unclear. We analyzed data from 74,678 White participants with prediabetes in the UK Biobank, defined by either HbA1c (5.7-6.4%) or fasting glucose (6.1-6.9 mmol/L). Follow-up continued until October 10, 2023. Cox regression was used to examine associations between LE8, phenotypic age (PhenoAge), cardiovascular biological age (CBA), and outcomes of cardiovascular (CVD) mortality and stroke. Restricted cubic spline (RCS) models identified biological age risk thresholds. Mediation analysis assessed whether proteins such as CST3, EFEMP1, FES, IGFBP2, IGFBP6, LPA, PCSK9, and TIMP1 mediated these effects. Over a median follow-up of 13.4 years, 2263 participants died from CVD causes. Each 1-year increase in CBA or PhenoAge was associated with a ~ 10% higher risk of CVD mortality (CBA aHR = 1.10; PhenoAge aHR = 1.09; both P < 0.001), while each 1-point increase in LE8 score was linked to a 3% lower risk (HR = 0.97, P < 0.001). The risk biological ages for these two indicators were also identified: PhenoAge ≥ 58.52 years and CBA ≥ 62.42 years. Similar trends were observed for stroke. Mediation analysis revealed that CST3, TIMP1, IGFBP2, and IGFBP6 contributed to the biological pathways between aging/lifestyle and CVD outcomes. The combined LE8 and PhenoAge model showed the strongest predictive performance for CVD mortality (AUC = 0.716) and stroke (AUC = 0.638) over 15 years. LE8 combined with phenotypic age provides prognostic value for CVD outcomes in prediabetes. These findings highlight the potential of lifestyle modification and delayed biological aging in reversing prediabetes and underscore comorbidity-related proteins as promising therapeutic targets. Show less
📄 PDF DOI: 10.1186/s40001-025-03218-7
LPA
Mei Wang, Ruihua Yan, Wenbo Xia +8 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Low physical activity (LPA) significantly heightens the susceptibility of both type 2 diabetes mellitus (T2DM) and chronic renal disease. Nearly half of population diagnosed with T2DM globally worsen Show more
Low physical activity (LPA) significantly heightens the susceptibility of both type 2 diabetes mellitus (T2DM) and chronic renal disease. Nearly half of population diagnosed with T2DM globally worsen into diabetic kidney disease (DKD). Focusing on physically inactive populations, we aimed to comprehensively evaluate the trends over time and regional changes in T2DM-associated DKD attributable to LPA burden. We utilized data of the 2021 Global Burden of Disease (GBD) Study to initially assess the worldwide effects of T2DM-associated DKD attributable to LPA by computing the numbers and age-standardized rates (ASRs) of death, disability-adjusted life years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs), categorized by subtypes in 2021. Linear regression model was applied to analyze the illness burden from 1990 to 2021. Furthermore, cluster analysis was performed to assess the regional differences in disease burden across GBD regions. Lastly, to forecast the illness burden for the next 25 years, we utilized the autoregressive Integrated Moving Average (ARIMA) and Excess Risk (ER) models. In 2021, the fatalities attributed to T2DM-related DKD attributable to LPA amounted to 30835 (95%UI: 12346-51646) cases, with 698484 (95%UI: 275039-1158032) DALYs. The ASRs of death and DALYs were 0.38 (95%UI: 0.15-0.63) and 8.19 (95%UI: 3.21-13.6) per 100000 individuals, respectively. Between 1990 and 2021, there was a notable escalation in deaths, DALYs, YLDs, and YLLs, as well as their ASRs. The highest burden was observed among males, older adults (aged 70 years and above), and middle Socio-demographic Index (SDI). Significant differences were noted in the disease burden among various regions and countries as defined by the GBD study. Predictive analyses indicate a continued escalation of this burden by the year 2050. The global impact of DKD attributable to LPA remains considerable, with significant disparities noted across different genders, ages, and regions. To mitigate this burden, it is crucial to implement effective interventions aimed at addressing physical inactivity, specifically designed for targeted demographic groups. Show less
📄 PDF DOI: 10.3389/fendo.2025.1625973
LPA
Bobo Yuan, Jianrui Li, Qing Shu +3 more · 2025 · The journal of headache and pain · BioMed Central · added 2026-04-24
Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by hyperglycemia and insulin resistance, Migraine is a common chronic neurological disease caused by increased excitability of the Show more
Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by hyperglycemia and insulin resistance, Migraine is a common chronic neurological disease caused by increased excitability of the central nervous system, both exerting substantial health burdens. However, the shared genetic basis and underlying molecular mechanisms remain largely unexplored. This study integrates single-cell data and Mendelian randomization (MR) analysis to identify comorbidity-associated genes and elucidate potential mechanistic links between these two conditions. Single-cell datasets from T2DM and migraine were analyzed to identify differentially expressed genes (DEGs). MR analysis was employed to prioritize key causal genes, followed by network-based functional characterization, disease-drug association analysis, cell annotation, and pseudo-time trajectory modeling. Analysis of single-cell data identified 2,128 migraine-associated and 3,833 T2DM-associated genes, with 714 genes shared between the two diseases. MR analysis highlighted AP4E1 and HSD17B12 as key regulators implicated in both conditions. Network analysis further linked these genes to lipid metabolism and vesicle transport pathways. Computational predictions revealed common comorbidities, including metabolic dysregulation and chemical-induced liver injury, as well as potential therapeutic agents such as valproic acid and bisphenol A. Single-cell annotation identified six major immune cell types in T2DM (T cells, NK cells, B cells, CD14 monocytes, CD16 monocytes, and dendritic cells), with T cells emerging as central players. In migraine, five immune cell types were identified (CD4 T cells, CD8 T cells, B cells, NK cells, and monocytes), with monocytes being the predominant cell type. Pseudo-time analysis delineated seven subpopulations of T cells and four subpopulations of monocytes, suggesting distinct functional trajectories in disease pathogenesis. However, due to the use of peripheral blood-derived single-cell data, genes primarily expressed in the central nervous system, such as CALCA and RAMP1, could not be detected, limiting the identification of certain migraine-specific pathways. This single-cell data and MR analysis investigation identifies AP4E1 and HSD17B12 as pivotal genetic determinants in T2DM-migraine comorbidity, shedding light on their molecular interplay and potential therapeutic relevance. Show less
📄 PDF DOI: 10.1186/s10194-025-02090-4
HSD17B12
Jiahao Guo, Hao Xie, Quanting Yin +8 more · 2025 · Discover oncology · Springer · added 2026-04-24
Although studies have suggested a potential link between the nervous system and prostate cancer, the underlying regulatory mechanisms remain unclear. Therefore, it is crucial to identify the genes inv Show more
Although studies have suggested a potential link between the nervous system and prostate cancer, the underlying regulatory mechanisms remain unclear. Therefore, it is crucial to identify the genes involved in regulating prostate cancer within the nervous system. We utilized eQTL data from eight neural cell types as exposure factors and GWAS data for prostate cancer as outcome events. Mendelian randomization (MR) analyses were performed to identify causative genes associated with prostate, bladder, and renal cancers in Astrocytes, Endothelial cells, Excitatory neurons, Inhibitory neurons, Microglia, Oligodendrocytes, OPCs/COPs, and Pericytes. Bladder and renal cancers were used as controls. Sensitivity analyses (heterogeneity, pleiotropy, and leave-one-out tests) were conducted to ensure reliability. In astrocytes, seven positive genes were identified as being causally related to prostate cancer: KANSL1, AC005670.2, ARL17B, LRRC37A2, LRRC37A, MAPT, and LINC02210. In. Endothelial cells, Inhibitory neuron and Microglia, three genes (LRRC37A2, ARL17B, and KANSL1) were identified as risk genes that are associated with prostate cancer. Four protective genes were identified in excitatory neurons, including LRRC37A2, ARL17B, KANSL1 and LINC02210. In oligodendrocytes, eight genes were identified, with LRRC37A2, ARL17B, and KANSL1 acting as protective factors, while OR2L13, OR2L3, OR2L5, OR2L2, and OR2M4 were identified as risk factors. Additionally, sensitivity analyses showed no heterogeneity or horizontal pleiotropy in the MR results, confirming their reliability and stability. In addition, no positive genes were found in bladder cancer and renal cancer. Our study highlights the role of the nervous system, particularly astrocytes, in regulating prostate cancer. We identified three genes, with LRRC37A2, ARL17B, and KANSL1 emerging as key protective factors. These findings provide potential targets for prostate cancer diagnosis and treatment. The online version contains supplementary material available at 10.1007/s12672-025-03711-9. Show less
📄 PDF DOI: 10.1007/s12672-025-03711-9
KANSL1
Peilu She, Bangjun Gao, Dongliang Li +18 more · 2025 · Nature communications · Nature · added 2026-04-24
Energy deprivation and metabolic rewiring of cardiomyocytes are widely recognized hallmarks of heart failure. Here, we report that HEY2 (a Hairy/Enhancer-of-split-related transcriptional repressor) is Show more
Energy deprivation and metabolic rewiring of cardiomyocytes are widely recognized hallmarks of heart failure. Here, we report that HEY2 (a Hairy/Enhancer-of-split-related transcriptional repressor) is upregulated in hearts of patients with dilated cardiomyopathy. Induced Hey2 expression in zebrafish hearts or mammalian cardiomyocytes impairs mitochondrial respiration, accompanied by elevated ROS, resulting in cardiomyocyte apoptosis and heart failure. Conversely, Hey2 depletion in adult mouse hearts and zebrafish enhances the expression of mitochondrial oxidation genes and cardiac function. Multifaceted genome-wide analyses reveal that HEY2 enriches at the promoters of genes known to regulate metabolism (including Ppargc1, Esrra and Cpt1) and colocalizes with HDAC1 to effectuate histone deacetylation and transcriptional repression. Consequently, restoration of PPARGC1A/ESRRA in Hey2- overexpressing zebrafish hearts or human cardiomyocyte-like cells rescues deficits in mitochondrial bioenergetics. Knockdown of Hey2 in adult mouse hearts protects against doxorubicin-induced cardiac dysfunction. These studies reveal an evolutionarily conserved HEY2/HDAC1-Ppargc1/Cpt transcriptional module that controls energy metabolism to preserve cardiac function. Show less
📄 PDF DOI: 10.1038/s41467-024-55557-4
HEY2
Zhiling Cheng, Meiling Gao, Yang Liu +4 more · 2025 · Nutrition, metabolism, and cardiovascular diseases : NMCD · Elsevier · added 2026-04-24
To evaluate the efficacy and safety of inclisiran in the treatment of hypercholesterolemia. Randomized controlled trials comparing inclisiran with a placebo were searched until April 2024. Overall, 8 Show more
To evaluate the efficacy and safety of inclisiran in the treatment of hypercholesterolemia. Randomized controlled trials comparing inclisiran with a placebo were searched until April 2024. Overall, 8 studies involving 4947 patients were included. Inclisiran reduced low-density lipoprotein cholesterol (mean difference [MD]: -46.95 %; 95 % confidence interval [CI]: -53.26 to -40.46; P < 0.05), proprotein convertase subtilisin/kexin type 9 (MD: -70.80 %; 95 % CI: -76.52 to -65.08; P < 0.05), serum total cholesterol (MD: -29.47 %; 95 % CI: -32.56 to -26.39; P < 0.05), non-high-density lipoprotein cholesterol (MD: -40.46 %; 95 % CI: -45.24 to -35.68; P < 0.05), apolipoprotein B (MD: -36.77 %; 95 % CI: -40.94 to -32.61; P < 0.05), and lipoprotein(a) (MD: -20.04 %; 95 % CI: -24.2 to -15.87; P < 0.05) levels but increased high-density lipoprotein cholesterol level (MD: 6.09 %; 95 % CI: 3.63 to 8.55; P < 0.05). The incidences of adverse events, serious adverse events, headache, nasopharyngitis, and muscular adverse reactions were not significantly different between the inclisiran and placebo groups. Inclisiran reduced the incidence of cardiovascular adverse reactions (odds ratio [OR] = 0.79; 95 % CI: 0.65 to 0.96; P = 0.02) and increased the incidence of injection-site reactions (OR = 4.79; 95 % CI: 2.18 to 10.52; P < 0.05). Inclisiran is effective in treating hypercholesterolemia and has a good safety profile. Show less
no PDF DOI: 10.1016/j.numecd.2024.10.017
APOB
Qin Tian, Jinxiang Wang, Qiji Li +16 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-ac Show more
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-acid dehydrogenase kinase (BCKDK) has been implicated in promoting RCC metastasis, but its specific substrates and the mechanisms underlying its regulation of RCC progression remain poorly understood. This study uncovers a novel mechanism whereby BCKDK-mediated AKT phosphorylation drives RCC tumorigenesis and drug resistance. Elevated BCKDK expression correlates with poor prognosis in RCC clinical samples. BCKDK deficiency inhibits RCC cell proliferation and tumorigenesis both in vitro and in vivo. Mechanistic investigations reveal that BCKDK directly binds to and regulates the phosphorylation of AKT. BCKDK-mediated phosphorylation of AKT decreases ubiquitin-mediated AKT protein degradation, and promotes tumorigenesis via activation of the AKT/mTOR signaling pathway. RNA sequencing identifies BCKDK's involvement in the drug metabolism network and apoptotic signaling pathways. The BCKDK/AKT/ABCB1 axis mediates doxorubicin resistance. Targeting BCKDK/AKT inhibits the growth of RCC patient-derived organoids (PDOs), enhances doxorubicin-induced apoptosis in RCC cells, and suppresses tumor growth in vivo. These findings identify a previously unrecognized phosphorylation substrate of BCKDK and highlight the critical role of the BCKDK/AKT signaling axis in RCC progression, offering a promising target for therapeutic intervention. Show less
📄 PDF DOI: 10.1002/advs.202411081
BCKDK
Yi Han, Yun Hong, Yan Gao +11 more · 2025 · PLoS genetics · PLOS · added 2026-04-24
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understandin Show more
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understanding of the genetic basis of HF and more specific NICM subtype in the East Asian populations and evaluate the biological pathways underlying subclinical left ventricular dysfunction. We conducted a meta-analysis of genome-wide association studies (GWAS) for all-cause HF in the East Asian populations (N cases ~ 13,385) and a more precise definition of nonischemic cardiomyopathy (NICM) subtype in multi-ancestry populations (N cases~3,603). We identified a low-frequency East-Asian enriched coding variant near MYBPC3 and a NICM specific locus. Follow up analyses demonstrated male-specific HF association at the MYBPC3 locus, and highlighted SVIL as a candidate causal gene for NICM. Moreover, we demonstrated that SVIL deficiency aggravated cardiomyocyte hypertrophy, apoptosis and impaired cell viability in phenylephrine (PE)-treated H9C2 cells. In addition, the gene expression level of B-type natriuretic peptide (BNP) which was deemed as a hallmark for HF was further elevated by SVIL silencing in PE-stimulated H9C2 cells. RNA-sequencing analysis of H9C2 cells revealed that the function of SVIL might be mediated through pathways relevant to regulation and differentiation of heart muscle. These results enhance our understanding of the genetic architecture of HF in the East Asian populations, and provide important insight into the biological pathways underlying NICM and sex-specific relevance of the MYBPC3 locus that warrants further replication in another datasets. Show less
📄 PDF DOI: 10.1371/journal.pgen.1011897
MYBPC3