👤 Chenrui Li

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Also published as: Xiaofeng Li, Jiajia Li, Jingwen 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, Hong-Tao Li, Enhong Li, Guobin 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, Peiwu Li, Youran Li, Yongmei Li, Changyu Li, X Y Li, Ran Li, Peilin Li, Chunshan Li, Yixiang Li, Ming Zhou Li, Z Li, Ye Li, Guanglve Li, Zili Li, Xinmei Li, Yihao Li, Qing Run Li, Liling Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Qiankun Li, Kailong Li, Shengxu Li, Shisheng Li, Sai Li, Guangwen Li, 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, Xuelin Li, Xueyang Li, Fa-Hui Li, Caiyu Li, Zhen-Yuan Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Shiyu Li, Bao Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, 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, Jinlin Li, Xiaoqing Li, Linke Li, C Y Li, Shuaicheng Li, Thomas Li, Siting Li, Xuebiao Li, Yingyi Li, Maolin Li, Yongnan 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, L Li, Zhaohan Li, Yuanmei Li, Alexander Li, Yanwu Li, Hualing Li, Wen-juan Li, Sibing Li, Xining Li, Qinghe 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, Wenbo Li, Runwen Li, Yarong Li, Side Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Lingxi Li, Chuan-Hai Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Qin Li, Zhongyu Li, Deyu Li, Zhen-Yu Li, 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, Naishi Li, Xiaobing Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Shengchao A Li, Pan Li, Jiaying Li, Jun-Jie Li, Cui-lan Li, Ruonan Li, Shuhao Li, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Suyan Li, Chengquan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, 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, Jing-Yao Li, Yan-Hua Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, L K Li, Wan Jie Li, Ya-Ting Li, Aimin Li, Dongbiao Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, L-Y Li, Peiyun Li, Xiuqi Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Yu Li, Minhui Li, Yvonne Li, Yiwei Li, Jiayuan Li, Xiangzhe Li, Zhichao Li, Siguang Li, Minglun Li, Yige Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chunlan Li, Chiyang Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Jing Li, Xiangyun Li, Si Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Zijing Li, Dengke Li, Yuchuan Li, Wentao Li, Qingling Li, Rui-Han Li, Xuhong Li, Dong Li, Hongyun Li, Zhonggen Li, Xiong Li, Penghui Li, Xiaoxia Li, Dezhi Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Sheng-Jie Li, Defa Li, Ying-Qing Li, X L Li, Yuyan Li, Kawah Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Zhenfei Li, Shupeng Li, Sha-Sha Li, Panyuan Li, Ziyu Li, Gang Li, Mengxuan Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, Huaping Li, Ji-Liang Li, C H Li, Bohua Li, Bing Li, Pei-Ying Li, Huihuang Li, Shaobin Li, Yunmin Li, Yanying Li, Gui Lin Li, Ronald Li, Shi-Hong Li, Shilun Li, John Zhong Li, Xinyu Li, Lujiao Li, Song-Chao Li, Chenghong Li, Dengfeng Li, Nianfu Li, Baohua Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Jiao Li, Zhimei Li, Jun-Cheng Li, Yimeng Li, Jingming Li, Jinxia Li, De-Tao Li, Chunting Li, Shu Li, Julia Li, Chien-Feng Li, Huilan Li, Mei-Zhen Li, Xin-Ya Li, Zhengjie Li, Chunsheng Li, Yan-Yan Li, Liwei Li, Huijun Li, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Supeng Li, Lijun Li, Hening Li, Yiju Li, Yuanhe Li, Fengxia Li, Guangxiao Li, Peixin Li, Xueqin Li, Feng-Feng Li, Zu-Ling Li, Jialing Li, Xin Li, Yunjiu Li, Zonghong Li, Dayong Li, Ningyan Li, Lingjiang Li, Yuhan Li, Zhenghui Li, Fuyuan Li, Ailing Li, H-F Li, Chaochen Li, Chunxia Li, Zhen-Li Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Zhengying Li, Zhaoshui Li, Yali Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, 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, Yanxi Li, Ning Li, Ruobing Li, Wan-Xin Li, Xia Li, Meitao Li, Yongjing Li, Ziqiang Li, Huayao Li, Wen-Xi Li, Shenghao Li, Huixue Li, Boxuan Li, Jiqing Li, Hehua Li, Yucheng Li, Yongqi Li, Qingyuan Li, Fengqi Li, Zhigang Li, Yuqing Li, Guiyang Li, Guo-Qiang Li, Dujuan Li, Yanbo Li, Yuying Li, Shaofei Li, Sanqiang Li, Shaoguang Li, Hongyu Li, Min-Rui Li, Guangping Li, Shuqiang Li, Dan C Li, Huashun Li, Jinxin Li, Ganggang Li, Xinrong Li, Haoqi Li, Yayu Li, Handong Li, Huaixing Li, Yan-Nan Li, Xianglong Li, Minyue Li, Hong-Mei Li, Jing-Jing Li, Songhan Li, Mengxia Li, Conglin Li, Jutang Li, Qingli Li, Yongxiang Li, Miao Li, Songlin Li, Qilong Li, Dijie Li, Chenyu Li, Yizhe Li, Ke Li, Yan Bing Li, Jiani Li, Lianjian Li, Zhen-Hua Li, Yiliang Li, Chuan-Yun Li, Xinpeng Li, Hongxing Li, Wanyi Li, Gaoyuan Li, Youming Li, Mi Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, 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, Chenxuan Li, Xiao-Dong Li, Xinghuan Li, Zhaoping Li, Xingyu 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, Mei Li, Xuewang Li, Xiangdong Li, Jifang Li, Zhenjia Li, Manjiang Li, Wan 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, Man-Zhi Li, Xiancheng Li, Yanmei Li, De-Jun Li, Keqing Li, Junxian Li, Zhihua 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, Xuesong Li, Zhaosha Li, Jiwei Li, Yongzhen Li, Chun-Quan Li, Weifeng Li, Tao Li, Sichen Li, Wenhui Li, Xiankai Li, Qingsheng Li, Yaxuan Li, Liangji Li, Yuchan Li, Lixiang 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, Xuri Li, Wenzhuo Li, Y Li, Deqiang Li, Zipeng Li, Caixia Li, Mingyue Li, Hongli Li, Yun Li, Mengqiu Li, Ling-Ling Li, Yaqin Li, Yanfeng Li, Yu-He Li, Shasha Li, Xi Li, S-C Li, Siyi Li, Minmin Li, Manna Li, Chengwen Li, Dawei Li, Shu-Feng Li, Haojing Li, Xun Li, Ming-Jiang Li, Zhiyu Li, Sitao Li, Ziyang Li, Qian Li, Yaochen Li, Tinghua Li, Zhenfen Li, Wenyang Li, Bohao Li, Shuo Li, Wenming Li, Mingxuan Li, Si-Ying Li, Xinyi Li, Jenny J Li, Xue-zhi Li, Bingsong Li, Shuai Li, Anqi Li, Xiaoju Li, Zhenyu Li, Xiaonan Li, Ting Li, Xiang-Yu Li, Duan Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Xunjia Li, Yanchang Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, Zong-Xue Li, En-Min Li, Chunya Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Jinhua Li, Min-jun Li, Yuanheng Li, Qian-Qian Li, Chunxiao Li, Wenli Li, Shijun Li, Mengze Li, Kuan Li, Baoguang Li, Kaiwei Li, Jie-Shou Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Junxin Li, Yu-Sheng Li, Wei-Jun Li, Guoyan Li, Junjie Li, Fei-Lin Li, Nuomin Li, Shanglai Li, Shulin Li, Yanyan Li, Yue Li, Taibo Li, Junqin Li, Zhongcai Li, Xueying Li, Jun-Ru Li, JunBo Li, Xiaoqi Li, Zhaobing Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, Shujing Li, Tsai-Kun Li, Chen-Chen Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Xiyun Li, Yi-Wen Li, Huifeng Li, Rulin Li, Shihong Li, Ya-Pei Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Wenjia Li, Min-Dian Li, Xiatian Li, Hongwei Li, Ding-Jian Li, 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, 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, Man Li, Juxue Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Gongda Li, Nan Li, Wei-Ping Li, Yajun Li, Yipeng Li, Mingxing Li, Nanjun Li, Xin-Yu Li, Chunyu Li, P H Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Ranran Li, Long Shan Li, Suping Li, Yanze Li, Jason Li, Xiao-Feng Li, Monica M Li, Fengjuan Li, W Li, Xianlun Li, Hainan Li, Qi Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Fei Li, Xionghui Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Hongmei Li, Kang Li, Peilong Li, Yinghao Li, Xu-Wei Li, Mengsen Li, Lirong Li, Quanpeng Li, Wenhong 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, Guohua Li, Wen-Ting 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, Xue-Peng Li, Jianang Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Feng Li, Weiyang Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Kaibo Li, Xinxiu Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Shaodan Li, Meng-Hua Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Donghe Li, Zheng Li, Ming-Hao Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Menghua Li, Jingqi Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Chong Li, Xiao-Kang Li, Fugen Li, Hanqi Li, Yangyang Li, Yuwei Li, Xiaochen Li, Dongfang Li, Zhuorong Li, Zizhuo Li, X-H Li, Xianrui Li, Lan-Juan Li, Dong Sheng Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Huanqiu Li, Bing-Heng Li, Xiaoman Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Zhifei Li, Jinhui Li, Ying Li, Yanshu Li, Jianlin Li, Yuanyou Li, Chongyang Li, Wanyan Li, Yumin Li, Longyu Li, Guiying Li, Jinku Li, X B Li, Changgui Li, Cuiling Li, Zhisheng Li, Xuekun Li, Yuguang Li, Wenke Li, Jianguo Li, Jiayi Li, En Li, Ximei Li, Shaoyong Li, Peihua Li, Kai-Wen Li, Suwen Li, Chang-Ping Li, Guangda Li, Yixue Li, Guandu Li, Junfeng Li, Xin-Chang Li, Jieming Li, Yue-Ying Li, Kongdong Li, Chunhui Li, Peiyu Li, Tongyao Li, Lian Li, Linfeng Li, Yuzhe Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Chang-Yan Li, Qifang Li, Xiaohua Li, Vivian Li, Duanxiang Li, Xiaolin Li, Meiting Li, Justin Li, Xue-Er Li, Zhuangzhuang Li, Xiaohui Li, Hongchang Li, Cang Li, Xuepeng Li, Mingjiang Li, Youwei Li, Ronggui Li, Xingwang Li, Tiange Li, Yongjia Li, Dacheng Li, Xinmin Li, Zongyu Li, Luquan Li, Guoxing Li, Jianyong Li, Shujie Li, Zongchao Li, Yanbin Li, Jia Li, Shiliang Li, Haimin Li, Sheng-Qing Li, Qinrui Li, Yiming Li, Xiao-Tong Li, Lingjie Li, Yiwen Li, Tie Li, Baoqi Li, 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, 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, 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, Jian'an Li, Guangqiang Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Shunhua Li, Yu-I Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Ziqi Li, Shen Li, Tianjiao Li, Shufen Li, Gui-Rong Li, Yunfeng Li, Yunpeng Li, Yueqi Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Xu Li, Pinghua Li, Shi-Fang Li, Shude Li, Yaxiong Li, Zhibin Li, Zhenli Li, Qing-Fang Li, Rosa J W Li, Yunxiao Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, Zhi Li, Zhankui Li, Zihai Li, Yue-Jia Li, Haihong Li, Peifen Li, Mingzhou Li, Taixu Li, Jiejing Li, Meng-Miao Li, Meiying Li, Chunlian Li, Meng Li, Zhijie Li, Cun Li, Huimin Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Yinghui Li, Cong Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Mengfan Li, Weiling 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, 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, 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, Guangdi Li, Peipei Li, Tian-Yi Li, Xiaxia Li, Yuefeng Li, Nien Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Lin Li, Jieshou Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Hong-Lan Li, Mengqing Li, S L Li, Ben-Shang Li, Ming-Kai Li, Shunqing Li, Xionghao Li, Lan Li, Menglu Li, Huiqing Li, Yanwei Li, Yantao Li, Chien-Te Li, Wenyan Li, Xiaoheng Li, Zeyuan Li, Yongle Li, Ruolin Li, Hongqin Li, Zhenhao Li, Jonathan Z Li, Haying Li, Shao-Dan Li, Muzi Li, Yong-Liang Li, Gen Li, M Li, Dong-Ling 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, 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, Zhihui Li, Yi-Yang Li, Fujun Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Ni Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Shichao Li, Gan Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Lihong Li, Chun Li, Jianan Li, Wenfang Li, Haixia Li, Sung-Chou Li, Xiangling Li, Lianhong Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Cheng Li, Kui Li, Zhao Li, Tiegang Li, Yunxu Li, Shuang-Ling Li, Zhong Li, Xiao-Long Li, 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, Li-Min Li, Yunsheng Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Daoyuan Li, Baichuan Li, Wenqi Li, Haibo Li, Zhenzhe Li, Xiao-Jun Li, Jian-Mei 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, Jiayu Li, Xiaobai Li, Junsheng Li, Pingping Li, Mingquan Li, Wen-Ya Li, Suran Li, Yunlun Li, Rongxia Li, Yingqin Li, Yuanfang Li, Guoqin Li, Qiner Li, Huiqin Li, Jiafang Li, Shanhang Li, Han-Bing Li, Chunlin Li, Zongzhe Li, Jisen Li, Yikang Li, Si-Yuan Li, Hongmin Li, Caihong Li, Yajing Li, Peng Peng Li, Guanglu Li, Kenli Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Dongmin Li, Jian-Jun Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Jian-Shuang Li, Xinxin Li, You-Mei Li, Chenglan Li, Yubin Li, Dazhi Li, Beixu Li, Yuhong 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, Xiyue Li, Minghua Li, Zhuoran Li, Tianchang Li, Hongru Li, Shiqi Li, Mei-Ya Li, Wuyan Li, Mingzhe Li, Yi-Ling Li, Hongjuan Li, Yingjian Li, Zhirong Li, Wang Li, Mingyang Li, Weijun Li, Boyang Li, Senmao Li, Cai Li, Mingjie Li, Ling-Jie Li, Hong-Chun Li, Jingcheng Li, Ivan Li, Yaying Li, Mengshi Li, Liqun Li, Manxia Li, Ya Li, Changxian Li, Wen-Chao Li, Dan-Ni 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, Wendeng Li, Yuling Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Shengze Li, Linyan 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, Yu-Kun Li, Hsiao-Fen Li, Jiangan Li, Weihai Li, Zhaojin Li, Mengjiao Li, Bingxin Li, Wenjuan Li, Wenyu Li, Chia-Yang Li, Meng-Meng Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Xi-Xi Li, Wenlei Li, Mei-Lan Li, Wenjun Li, Jiaxin Li, Haiyan Li, Ming D Li, Chenguang Li, Ruyue Li, Xujun Li, Chi-Ming Li, Xiaolian Li, Yi-Ning Li, Dandan Li, Yunan Li, Zechuan Li, Zhijun Li, Jiazhou Li, Sherly X Li, Wanling Li, Ya-Ge Li, Yinyan Li, Qijun Li, Guangli Li, Rujia Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Wan-Shan Li, Xiaohan Li, Huijie Li, Zhongwen Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Xuejun Li, Fengxiang Li, Nana Li, Shunwang Li, Chao Li, Yaqing Li, Yaqiao Li, Jingui Li, Bingsheng Li, Huamao Li, Xiankun Li, Jingke Li, Tianyao Li, Xiaowei Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Hai-Yun Li, Haoran Li, Zhongxian Li, Xiaoliang Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Jialun Li, Xinjian Li, Rui Li, Zilu Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Xuyi Li, Binghua Li, Hanjun Li, Yunchu Li, Qihua Li, Zhengyao Li, Jin-Qiu Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, 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, 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, Xiaoyuan Li, Huanhuan Li, Yanan Li, Zongfang Li, Yang Li, Jiayan Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Dongdong Li, Yimei Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Zhi-qiang Li, Shaojing Li, S S Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Tong Li, Lihua Li, Yilong Li, Xue-Lian Li, Zhiping Li, Yan-Li Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Yanli Li, Jingfeng Li, Zhi-Yuan Li, Hai Li, Yuan-Jing Li, Kaibin Li, Xuefeng Li, Wenjie Li, Xiaohu Li, Ruikai Li, Xiao-Hong Li, Mengjuan 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, YaJie Li, Dingchen 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, Dongye Li, Qun Li, Tianye 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, Tiewei Li, Bing-Hui Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Rong Li, Wei-Yang Li, Shikang Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Shishi Li, Bei-Bei Li, Hong-Lian Li, Xiumei Li, Haitong Li, Ruibing Li, Yuli Li, Melody M H 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, 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, 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, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, Xiaoqin Li, L P Li, Runbing Li, Chunmei Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Yanmin Li, 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, Qingfeng Li, Tianyi Li, Nanlong Li, Ping Li, Xu-Bo Li, Nien-Chen Li, Fangzhou Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Yuanchuang Li, Biao Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Shengbiao Li, Hong-Yan Li, Yue-Rui Li, 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, Chun-Xiao Li, Shu-Hong Li, Pei-Qin Li, Shuyue Li, Mengying Li, Tongzheng Li, Quan-Zhong Li, Fangyan Li, Yihong Li, Duo Li, Dali 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, Mingwei Li, Di-Jie Li, Bo Li, Jinliang Li, Wenxin Li, Qiji Li, W J Li, Zhijia Li, Zhipeng Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaobo Li, Xiaoting Li, Ruotai Li, Meijia Li, Shujiao Li, Yaojia Li, Weirong Li, Kun-Ping Li, Xiao-Yao Li, Weihua Li, Shangming Li, Yaqi Li, Yibo Li, Gui-Hua Li, Zhihong Li, Yandong Li, Runzhao Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Xiufeng Li, Yingjun Li, Yanxin Li, Xiaohuan Li, Boya Li, Ying-Qin Li, Lamei Li, O Li, Fan Li, Jun Z Li, Joyce Li, Suheng Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Zhiqiang Li, Junru Li, Jiangchao Li, Hecheng Li, Changkai Li, Yueping Li, Haifeng Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Xuanxuan Li, Rui-Jún Eveline Li, Bing-Mei Li, Yunman Li, Chaoqian Li, Shuhua Li, Yu-Cheng Li, Yirun Li, Chunying Li, Haomiao Li, Leipeng Li, Weiheng Li, Qianqian Li, Baizhou Li, YiQing Li, Zhengliang Li, Han-Ru Li, Weijie Li, Sheng Li, Wei-Qin Li, Guoyin Li, Yaqiang Li, Qingxian Li, Zongyi Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Chengjun Li, Keke Li, Yongpeng Li, Chanyuan Li, Jianbin Li, Shiying Li, Jianxiong Li, Ji Li, Huaying Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Shaomin Li, Heying Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Jiahao Li, Hanxiao Li, Jiansheng Li, Shibao Li, Shuying Li, Kunlong Li, Pengjie Li, Xiaomei Li, Ruijin Li
articles
Baoqi Li, Mingcong Xu, Bang An +8 more · 2025 · Materials horizons · Royal Society of Chemistry · added 2026-04-24
Dynamic responsive structural colored materials have drawn increased consideration in a wide range of applications, such as colorimetric sensors and high-safety tags. However, the sophisticated intera Show more
Dynamic responsive structural colored materials have drawn increased consideration in a wide range of applications, such as colorimetric sensors and high-safety tags. However, the sophisticated interactions among the individual responsive parts restrict the advanced design of multimodal responsive photonic materials. Inspired by stimuli-responsive color change in chameleon skin, a simple and effective photo-crosslinking strategy is proposed to construct hydroxypropyl cellulose (HPC) based hydrogels with multiple responsive structured colors. By controlling UV exposure time, the structural color of HPC hydrogels can be effectively controlled in a full-color spectrum. At the same time, HPC hydrogels showcase temperature and mechanical dual-responsive structural colors. In particular, the microstructure of HPC hydrogels undergoes a transition from the chiral nematic phase to the nematic phase under the action of external stretching, leading to a significant reflection of circularly polarized light (CPL) to linearly polarized light (LPL). Given the diverse responsiveness exhibited by HPC hydrogels and their unique structural transition properties under external forces, we have explored their potential applications as dynamic anti-counterfeiting labels and optical skins. This work reveals the great possibility of using structural colored cellulose hydrogels in multi-sensing and optical displays, opening up a new path for the exploration of next-generation flexible photonic devices. Show less
no PDF DOI: 10.1039/d4mh01646g
LPL
Wan Peng, Gao-Fei Li, Guo-Wang Lin +11 more · 2025 · Oncogene · Nature · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disorder primarily linked with mutations in Exostosin-1 (EXT1) and Exostosin-2 (EXT2) genes. However, not all HME cases can be exp Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disorder primarily linked with mutations in Exostosin-1 (EXT1) and Exostosin-2 (EXT2) genes. However, not all HME cases can be explained by these mutations, and its pathogenic mechanisms are not fully understood. Herein, utilizing whole-exome sequencing and genetic screening with a family trio design, we identify two novel rare mutations co-segregating with HME in a Chinese family, including a nonsense mutation (c.204G>A, p.Trp68*) in EXT1 and a missense mutation (c.893T>G, p.Phe298Cys) in FUT7. Functional assays reveal that the FUT7 mutation affects the cellular localization of FUT7 protein and regulates cell proliferation. Notably, the simultaneous loss of fut7 and ext1 in a zebrafish model results in severe chondrodysplasia, indicating a functional link between FUT7 and EXT1 in chondrocyte regulation. Additionally, we unveil that FUT7 p.Phe298Cys reduces EXT1 expression through IL6/STAT3/SLUG axis at the transcription level and through ubiquitination-related proteasomal degradation at the protein level. Together, our findings not only identify novel germline mutations in FUT7 and EXT1 genes, but also highlight the critical interaction between these genes, suggesting a potential 'second-hit' mechanism over EXT1 mutations in HME pathogenesis. This insight enhances our understanding of the mechanisms underlying HME and opens new avenues for potential therapeutic interventions. Show less
📄 PDF DOI: 10.1038/s41388-024-03254-3
EXT1
Xuan-Ling Li, Zhi-Heng Lin, Si-Ru Chen +7 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, a Show more
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, and the increased risk of MCI and AD is associated with the lack of estrogen during menopause. Previous studies have shown that Tiao Geng Decoction (TGD) may have antioxidant and anti apoptotic properties, which may prevent neurodegenerative diseases. However, whether TGD is effective in improving mild cognitive impairment due to postmenopausal estrogen deficiency and its potential pharmacological mechanisms remain unclear. The aim of this study was to investigate the possible pharmacological mechanisms of TGD in preventing postmenopausal MCI. We utilized RNA-seq technology to screen for differentially expressed genes (DEGs) and enrichment pathways in the hippocampal tissue of different groups of mice. Additionally, we adopted single-cell sequencing technology to study the cell types of Alzheimer's disease (AD) group and Normal Control (NC) group, the differential marker genes of each cell subgroup, and the GO enrichment analysis of each cell type. Both RNA sequencing and single-cell sequencing results showed a significant correlation between TGD and NF-κb pathway in improving mild cognitive impairment in postmenopausal women. The experimental verification results showed that the spatial learning and memory abilities of APP/PS1 model mice were weakened after ovariectomy, and the reproductive cycle on vaginal smears was in the interphase of diestrus. The levels of serum E2, and P-tau181 in mice were significantly down regulated, while the levels of brain tissue homogenate A β 42, IL-1 β, and IL-18 were significantly up-regulated, indicating successful modeling. Combining Western blotting, RT-qPCR, and transmission electron microscopy analyses, it was found that the low estrogen environment induced by oophorectomy can activate the NF-κb signaling pathway, activate the expression of NLRP3 inflammasome and A β secretase BACE1, and induce neuroinflammatory damage in hippocampal astrocytes. These results conform to the modeling characteristics of MCI. After TGD intervention, the spatial learning and memory abilities of MCI mice were significantly improved. The pharmacological validation results indicated that high concentration doses of TGD had a more significant effect on MCI. Subsequently, we used high concentration TGD (0.32 g/ml) as the traditional Chinese medicine group for further validation, protein blotting and RT-qPCR results indicated that TGD can effectively stimulate the secretion of ER α and ER β, inhibit the NF-κb pathway, downregulate BACE1, and inhibit the expression of NLRP3 inflammasome related proteins. In addition, the immunofluorescence results of hippocampal astrocytes showed that TGD can effectively facilitate the expression of AQP1 and significantly lower the sedimentation of A β compared with the model group. Our research suggests that there is a high correlation between a low estrogen environment and the occurrence and development of MCI. TGD may regulate the ERs/NF - κ b/AQP1 signaling pathway, promote estrogen secretion, activate AQP1, reduce A β deposition, reverse MCI neuroinflammatory injury, improve mild cognitive impairment, and prevent the occurrence of AD. This study revealed for the first time that TGD may be a potential new alternative drug for preventing and improving menopausal MCI. Show less
no PDF DOI: 10.1016/j.phymed.2025.156391
BACE1
Huatao Zheng, Dan Li, Rentao Ma +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and phys Show more
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and physical activity (PA) with frailty among Chinese older adults. A total of 285 participants aged ≥60 years with 87 males and 186 females were recruited from Hunan Province. Daily moderate physical activity (MPA), vigorous physical activity (VPA) and light physical activity (LPA) were objectively measured using a triaxial accelerometer. A Food Frequency Questionnaire 25 (FFQ25) was used to assess the participants' dietary patterns, and DII was calculated. Six combined exposure groups were formed based on PA and DII: pro-inflammatory diet and insufficient PA group, neutral diet and insufficient PA group, anti-inflammatory diet and insufficient PA group, pro-inflammatory diet and sufficient PA group, neutral diet and sufficient PA group, and anti-inflammatory diet and sufficient PA group. Frailty was assessed using the Frailty Phenotype (FP), logistic regression analyzed the associations between dietary patterns, PA, and frailty. A total of 285 older adults participants were initially recruited, but 12 were excluded due to missing data. Consequently, 273 participants were included in the final analysis. Compared to individuals with insufficient PA, those with sufficient PA were associated with significantly lower odds of frailty (OR = 0.468, 95%CI = 0.242-0.907). Participants following an anti-inflammatory diet had significantly lower odds of frailty compared with those following a pro-inflammatory diet (OR = 0.467, 95%CI = 0.221-0.988). In the combined groups, frailty prevalence was significantly lower the group with anti-inflammatory diet and sufficient PA group (OR = 0.204, 95%CI = 0.072-0.583), compared with pro-inflammatory diet and insufficient PA group. The sensitivity analysis showed that the associations between anti-inflammatory diet and sufficient PA with frailty remained statistically significant, with the direction of the associations unchanged. These findings suggest that the results are robust. Our study indicates that adhering to an anti-inflammatory diet and maintaining sufficient PA may be associated with a lower likelihood of frailty. Achieving an adequate amount of PA and following a healthy dietary pattern may serve as potential preventive measures against frailty. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1739530
LPA
Nan Wang, Xin-Zhu Li, Xiao-Wen Jiang +10 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
no PDF DOI: 10.1007/s12035-025-05265-x
BACE1
Yu Gan, Kangning Wang, Xiang Chen +4 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Renal fibrosis is a common pathological process in various chronic kidney diseases. The accumulation of senescent renal tubular epithelial cells (TECs) in renal tissues plays an important role in the Show more
Renal fibrosis is a common pathological process in various chronic kidney diseases. The accumulation of senescent renal tubular epithelial cells (TECs) in renal tissues plays an important role in the development of renal fibrosis. Eliminating senescent TECs has been proven to effectively reduce renal fibrosis. Procyanidin C1 (PCC1) plays a senolytic role by specifically eliminating senescent cells and extending its overall lifespan. However, whether PCC1 can alleviate unilateral ureteral obstruction (UUO)-induced renal fibrosis and the associated therapeutic mechanisms remains unclear. Here, we observed a marked increase in senescent TECs within obstructed human renal tissue and demonstrated the positive correlation between the accumulation of senescent TECs and renal fibrosis in UUO-induced renal fibrosis in mice. We found that PCC1 reduced the number of senescent TECs, restored the regenerative phenotype in kidneys with reduced fibrosis, and improved tubular repair after UUO-induced injury. In vitro, PCC1 effectively cleared senescent HK2 cells by inducing apoptosis via ANGPTL4/NOX4 signaling. Incubation with culture medium from senescent HK2 cells promoted fibroblast activation, whereas PCC1 impeded profibrotic effects by downregulating senescence-associated secretory phenotype (SASP) factors from senescent HK2 cells. Therefore, PCC1 alleviated interstitial renal fibrosis not only by clearing senescent TECs and improving tubular repair but also by indirectly attenuating myofibroblast activation by reducing the level of SASP. In summary, PCC1 may be a novel therapeutic senolytic agent for treating renal fibrosis. Show less
no PDF DOI: 10.1096/fj.202402558R
ANGPTL4
Zhen Guo, Jing Su, Lu Liu +8 more · 2025 · Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · Elsevier · added 2026-04-24
Precise differential diagnosis between lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) and marginal zone lymphoma (MZL) remains a challenging issue because of overlapping clinicopath Show more
Precise differential diagnosis between lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) and marginal zone lymphoma (MZL) remains a challenging issue because of overlapping clinicopathological and immunophenotypic features. In the present study, the differential diagnostic potential of CD180 was assessed by determining its expression patterns in patients with MZL and LPL/WM through flow cytometry. The results indicated that LPL/WM cases exhibited a complete absence of CD180 expression on malignant B cells, whereas MZL cases showed robust CD180 expression (P < .001). Receiver operating characteristic analysis demonstrated that CD180 expression percentage showed optimal diagnostic accuracy in LPL/WM and MZL cases (area under the curve = 0.998, sensitivity = 100%, and specificity = 98.0%), with a further improvement in differentiation potential by the CD180 mean fluorescence intensity ratio (lymphocytes/monocytes) of ≤ 0.47 (area under the curve = 0.937). Moreover, although the MYD88 Show less
no PDF DOI: 10.1016/j.modpat.2025.100919
LPL
Xiaolong Li, Fan Ding, Lu Zhang +7 more · 2025 · BMC public health · BioMed Central · added 2026-04-24
The incidence of Type 2 Diabetes Mellitus (T2DM) continues to rise steadily, significantly impacting human health. Early prediction of pre-diabetic risks has emerged as a crucial public health concern Show more
The incidence of Type 2 Diabetes Mellitus (T2DM) continues to rise steadily, significantly impacting human health. Early prediction of pre-diabetic risks has emerged as a crucial public health concern in recent years. Machine learning methods have proven effective in enhancing prediction accuracy. However, existing approaches may lack interpretability regarding underlying mechanisms. Therefore, we aim to employ an interpretable machine learning approach utilizing nationwide cross-sectional data to predict pre-diabetic risk and quantify the impact of potential risks. The LASSO regression algorithm was used to conduct feature selection from 30 factors, ultimately identifying nine non-zero coefficient features associated with pre-diabetes, including age, TG, TC, BMI, Apolipoprotein B, TP, leukocyte count, HDL-C, and hypertension. Various machine learning algorithms, including Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB), Artificial Neural Networks (ANNs), Decision Trees (DT), and Logistic Regression (LR), were employed to compare predictive performance. Employing an interpretable machine learning approach, we aimed to enhance the accuracy of pre-diabetes risk prediction and quantify the impact and significance of potential risks on pre-diabetes. From the China Health and Nutrition Survey (CHNS) data, a cohort of 8,277 individuals was selected, exhibiting a disease prevalence of 7.13%. The XGBoost model demonstrated superior performance with an AUC value of 0.939, surpassing RF, SVM, DT, ANNs, Naive Bayes, and LR models. Additionally, Shapley Additive Explanation (SHAP) analysis indicated that age, BMI, TC, ApoB, TG, hypertension, TP, HDL-C, and WBC may serve as risk factors for pre-diabetes. The constructed model comprises nine easily accessible predictive factors, which prove highly effective in forecasting the risk of pre-diabetes. Concurrently, we have quantified the specific impact of each predictive factor on the risk and ranked them based on their influence. This result may serve as a convenient tool for early identification of individuals at high risk of pre-diabetes, providing effective guidance for preventing the progression of pre-diabetes to T2DM. Show less
📄 PDF DOI: 10.1186/s12889-025-22419-7
APOB
Huang Hui, Yang Yu, Liang Yiwei +3 more · 2025 · BMC pediatrics · BioMed Central · added 2026-04-24
This study aimed to investigate the genetic etiology and clinical features of non-syndromic pediatric obesity in a large Chinese cohort, providing insights into the genetic profile and its correlation Show more
This study aimed to investigate the genetic etiology and clinical features of non-syndromic pediatric obesity in a large Chinese cohort, providing insights into the genetic profile and its correlation with clinical phenotypes. We enrolled 391 children, aged 7-14 years, diagnosed with non-syndromic pediatric obesity at Jiangxi Provincial Children's Hospital from January 2020 to June 2022. Whole-exome sequencing was employed to identify potential genetic causes, focusing on 79 candidate genes associated with obesity. Multivariate logistic regression analysis was performed on the clinical data of the non-syndromic obesity gene-positive group and the gene-negative group. Among the 391 patients, 32 (8.2%) carried 18 non-syndromic obesity genes, with UCP3 and MC4R being the most common. Seven cases (1.8%) were rated as likely pathogenic by the American College of Medical Genetics and Genomics (ACMG). Clinical phenotype and genetic correlation analysis revealed that urinary microalbumin, fT4, GGT, uric acid, serum phosphorus, paternal weight, family history, impaired glucose tolerance (IGT), non-HDL cholesterol (non-HDL-C), and metabolic syndrome (MetS) showed significant statistical differences (P < 0.05). Serum phosphorus is an independent risk factor associated with genetic predispositions to obesity in children and adolescents (P < 0.05). Our findings highlight the genetic heterogeneity of non-syndromic pediatric obesity and identify UCP3 and MC4R as potential hotspot genes in the Chinese population. The study underscores the potential of genetic testing for early diagnosis and personalized management of pediatric obesity. Show less
📄 PDF DOI: 10.1186/s12887-025-05702-9
MC4R
Alexa Canchola, Keyuan Li, Kunpeng Chen +12 more · 2025 · ACS nano · ACS Publications · added 2026-04-24
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokine Show more
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokinetics, biodistribution, and cellular interactions. Yet systematic analyses are hampered by the absence of standardized, richly annotated data sets. Here, we introduce the Protein Corona Database (PC-DB), which compiles data from 83 studies (2000-2024) and integrates 817 NP formulations with quantitative profiles of 2497 adsorbed proteins. The PC-DB exposes pronounced heterogeneity in NP materials (metal 28.8%, silica 22.8%, lipid-based 14.8%), surface modifications, sizes (1-1400 nm), and ζ-potentials (-70 to +70 mV). Subsequent meta-analysis shows that silica, polystyrene, and lipid-based NPs smaller than 100 nm with moderately negative to neutral ζ-potentials preferentially bind the lipoproteins APOE and APOB-100, which are linked to receptor-mediated uptake and enhanced delivery efficiency. In contrast, metal and metal-oxide NPs carrying highly negative surface charge enrich complement component C3, indicating a greater likelihood of immune recognition and clearance. Interpretable machine learning models (LightGBM and XGBoost; ROC-AUC > 0.85) confirm NP size, ζ-potential, and incubation time as the most influential predictors of protein adsorption. These results delineate how physicochemical parameters dictate PC composition and illustrate the power of predictive modeling to guide rational NP design. Show less
📄 PDF DOI: 10.1021/acsnano.5c08608
APOB
Jie Sheng, Qin Lin, Yizhuo Sun +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Heart failure (HF) as the terminal stage of various cardiac diseases, its underlying molecular mechanisms still remain elusive. Emerging evidence have implicated long noncoding RNAs (lncRNAs) play a m Show more
Heart failure (HF) as the terminal stage of various cardiac diseases, its underlying molecular mechanisms still remain elusive. Emerging evidence have implicated long noncoding RNAs (lncRNAs) play a multifaceted role in the progression of cardiac hypertrophy and HF. Here, it is identified that a lncRNA forkhead box O6, opposite strand (Foxo6os) is significantly downregulated in murine HF model induced using transverse aortic constriction (TAC). Knockdown of Foxo6os accelerates cardiomyocyte hypertrophy, reflects as elevated expression of atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), and myosin heavy chain 7 (MYH7). Conversely, Foxo6os overexpression can improve cardiac function and alleviate adverse cardiac remodeling. Mechanistically, Foxo6os directly interacts with myosin-binding protein-C (MYBPC3), which then recruits protein kinase C alpha (PKC-α) to facilitate MYBPC3 phosphorylation, resulting in maintaining myocardial contractility and postponing HF progression. Therefore, these findings underscore the critical role of Foxo6os in preserving cardiomyocyte contractile function, suggesting a potential for Foxo6os as a novel therapeutic target of HF. Show less
📄 PDF DOI: 10.1002/advs.202507365
MYBPC3
Shengwang Jiang, Chaoyun Yang, Chen Ji +6 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Lia Show more
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Liangshan black sheep were randomly divided into four groups of five replicate pens (four sheep per pen). Sheep were fed a basal diet supplemented with 0 (control), 10, 20% or 30% fermented onion. Compared to that of the control group, dietary supplementation with 20% fermented onion improved final body weight, ADG and ADFI; enhanced GPT and GOT activities and increased IgA, IgG, IgM, C3, and C4 levels; increased the levels of IL-4, IL-10, TGF- Show less
📄 PDF DOI: 10.3389/fvets.2025.1695023
LPL
Y H Wang, X X Zhang, Y H Guo +8 more · 2025 · Zhonghua wai ke za zhi [Chinese journal of surgery] · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112139-20250221-00088
IL27
Hao Xu, Junjie Ma, Nanjun Li +6 more · 2025 · NPJ precision oncology · Nature · added 2026-04-24
Thyroid cancer, the most common endocrine malignancy, is characterized by a unique and complex tumor microenvironment (TME). To unravel the high tumor heterogeneity and molecular mechanisms driving ca Show more
Thyroid cancer, the most common endocrine malignancy, is characterized by a unique and complex tumor microenvironment (TME). To unravel the high tumor heterogeneity and molecular mechanisms driving cancer progression, we performed single-cell RNA sequencing (scRNA-seq) analysis, enabling a comprehensive exploration of cellular diversity and molecular dynamics at single-cell resolution. We employed Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and subsequent identification of cellular clusters. Differential gene expression analysis across subclusters was conducted using the FindAllMarkers function, while the DoHeatmap function was utilized to visualize the distribution of differentially expressed genes. The AUCell algorithm was applied to evaluate pathway enrichment within specific cell subtypes. To decipher cellular communication networks, we integrated the CellChat and NicheNet algorithms, which revealed intricate intercellular signaling interactions. Finally, multiplex immunohistochemistry (mIHC) was performed to validate key cellular interactions identified in silico. By analyzing 405,077 single cells from 50 thyroid cancer samples (including papillary, anaplastic, and metastatic tumors) and 14 normal thyroid tissues, we identified four major cellular subpopulations through unbiased clustering based on gene expression patterns and representative cellular markers. The TME was found to encompass diverse immune, endothelial, and mesenchymal cell subtypes, including novel populations such as CD4 + HSPA1A + T cells. Functional pathway enrichment analysis highlighted the roles of abundant cell types in tumor progression. Cell-cell communication analysis uncovered potential immunotherapeutic targets and revealed critical crosstalk among hub niche cells, including APOE+ macrophages, EMT-like cancer-associated fibroblasts (CAFs), and RBP7+ endothelial cells. These findings were further validated by multiplex immunohistochemistry, confirming the spatial organization and interactions of these cell populations within the TME. Our study provides a comprehensive single-cell transcriptomic atlas of thyroid cancer, offering profound insights into tumor heterogeneity, the functional roles of key niche cells, and potential biomarkers for anticancer therapy. These findings not only enhance our understanding of thyroid cancer biology but also pave the way for the development of novel therapeutic strategies targeting the TME. Show less
📄 PDF DOI: 10.1038/s41698-025-00924-7
APOE
Guofeng Xing, Li Chen, Lizhi Lv +5 more · 2025 · Journal of cardiovascular development and disease · MDPI · added 2026-04-24
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertroph Show more
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertrophic (HCM, 22), arrhythmogenic right ventricular (ARVC, 7), and restrictive (RCM, 2). Clinical data, imaging, labs, and family histories were collected, with whole-exome sequencing (WES) identifying disease-causing variants classified via ACMG guidelines. Statistical analysis revealed a median age of 11 years, a proportion of 58% male participants, and ethnic diversity (21 northern Han, 29 southern Han, 5 minorities). In the cohort, 13 cases had an LVEF below 35%. Pathogenic/likely pathogenic (P/LP) variants were found in 21.8% of the patients, and variants of uncertain significance (VUS) were present in 38.2%, with Show less
📄 PDF DOI: 10.3390/jcdd12120466
MYBPC3
Lan Zhou, Xin Li, Zihan Ji +9 more · 2025 · Molecular biotechnology · Springer · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are li Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are linked to HME pathogenesis, with EXT1 mutation being the most frequent. The aim of this study was to generate a mice model with Ext1 gene editing to simulate human EXT1 mutation and investigate the genetic pathogenicity of Ext1 through phenotypic analyses. We designed a pair of dual sgRNAs targeting exon 1 of the mice Ext1 gene for precise deletion of a 46 bp DNA fragment, resulting in frameshift mutation of the Ext1 gene. The designed dual sgRNAs and Cas9 proteins were injected into mice zygotes cytoplasm. A total of 14 mice were obtained via embryo transfer, among which two genotypic chimera mice had a deletion of the 46 bp DNA fragment in exon 1 of the Ext1 gene. By hybridization and breeding, we successfully generated heterozygous mice with edited Ext1 gene (Ext Show less
📄 PDF DOI: 10.1007/s12033-024-01325-0
EXT1
Yiqiao Wang, Shihao Huang, Yangbai Cai +5 more · 2025 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
Programmed cell death protein 5 (PDCD5) is involved in apoptosis and is regarded as a tumor suppressor in various tumors. However, its role and underlying molecular mechanisms in hepatocellular carcin Show more
Programmed cell death protein 5 (PDCD5) is involved in apoptosis and is regarded as a tumor suppressor in various tumors. However, its role and underlying molecular mechanisms in hepatocellular carcinoma (HCC) remain unclear. PDCD5-overexpressing cell and xenograft tumor models were developed. Cell Counting Kit-8, 5-Ethynyl-2'-deoxyuridine, wound healing, Transwell, flow cytometry, immunohistochemistry, and hematoxylin-eosin staining were employed to explore the effects of PDCD5 on HCC cell behaviors and tumor growth. The enzyme-linked immunosorbent assay and western blot were used to detect pyroptosis-related marker levels. The molecular mechanisms underlying PDCD5's role in HCC were investigated through transcriptome sequencing and coimmunoprecipitation. SRI-011381, a TGF-β signaling activator, was applied to evaluate the impact of PDCD5 in modulating the TGF-β/Smad2/3/Snail pathway. PDCD5 expression was reduced in HCC cells. Overexpression of PDCD5 inhibited HCC cell proliferation, migration, invasion, and xenograft tumor growth. Additionally, PDCD5 overexpression promoted apoptosis and pyroptosis, with corresponding increases in inflammatory factors and Caspase-1, GSDMD, and NLRP3 protein levels. Mechanistically, PDCD5 bound to receptor-regulated Smads (Smad2/3), inhibiting the TGF-β pathway. Treatment with the TGF-β pathway activator SRI-011381 significantly counteracted the inhibitory effects of PDCD5 overexpression on HCC progression. Our findings suggest that PDCD5 impedes the progression of HCC by promoting pyroptosis via regulation of TGF-β/Smad2/3/Snail pathway, which could be a possible therapeutic target for HCC. Show less
no PDF DOI: 10.1016/j.bbadis.2025.167696
SNAI1
Xiangyang Li, Xiaomin Zhang, Nina Wei +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10. Show more
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10.0 g/L) or simvastatin for 2 weeks. Metabolic parameters, serum lipid profiles, hepatic function markers, and histopathology were systematically analyzed. Molecular pathways were interrogated through qPCR, Western blot, and pharmacological inhibition of AMPK (Compound C) and PPARα (GW6471). TAC treatment demonstrated significant dose-dependent improvements across multiple parameters. Compared to HFD controls, TAC reduced body weight by 21.3% and liver index by 18.7%, while lowering fasting blood glucose levels by 32.4%. Serum analyses showed substantial reductions in total cholesterol (46.2%), triglycerides (38.5%), and LDL-cholesterol (52.1%), accompanied by a 29.8% increase in HDL-cholesterol. Hepatic function improved markedly, with ALT and AST levels decreasing by 57.3% and 49.6% respectively. Histopathological examination revealed a 68.4% reduction in hepatic lipid accumulation. At the molecular level, TAC treatment resulted in a 2.7-fold increase in AMPK phosphorylation while significantly reducing HMGCR expression by 63.1% and nuclear SREBP-1c levels by 71.5%. Concurrently, TAC upregulated PPARα and LXRα expression by 3.1-fold and 2.4-fold respectively, leading to enhanced expression of lipolytic enzymes LPL and HL by 2.8-fold and 2.1-fold. These beneficial effects were completely abolished by co-treatment with pathway-specific inhibitors. TAC ameliorates hyperlipidemia and hepatic steatosis through dual modulation of AMPK/SREBP-1c-mediated lipid synthesis and PPARα/LXRα-driven lipolysis, presenting a multifaceted therapeutic approach for metabolic disorders. Show less
📄 PDF DOI: 10.3389/fphar.2025.1662325
LPL
Yue Xu, Yuan Zhou, Kun Li +3 more · 2025 · Human genomics · BioMed Central · added 2026-04-24
Phosphorylation is a crucial post-translational modification mechanism that enhances proteomic diversity, and its malfunction has been confirmed to be associated with complex traits, especially brain Show more
Phosphorylation is a crucial post-translational modification mechanism that enhances proteomic diversity, and its malfunction has been confirmed to be associated with complex traits, especially brain disorders. One of the factors contributing to this malfunction is the missense mutations given that they may alter the peptides flanking the phosphorylated residues. However, the specific effects of these missense mutations on phosphorylation remain unclear. To ascertain these, a deep learning phosphorylation prediction model (DeepMEP), which is the first to be developed on a Chinese-brain-specific phosphorylation dataset (CBMAP), was established to bridge the phosphorylation and peptides. The impact of each missense mutation on phosphorylation was subsequently quantified based on the differences between the outputs of reference and mutant protein sequences. A permutation test adjusting for the confounding factors was finally employed to estimate the enrichment for high-impact mutations in disease-associated genomic loci. DeepMEP achieved superior predictive performance compared with other existing tools on both CBMAP and publicly available datasets. Enrichment analysis revealed the high-impact mutations were significantly enriched in GWAS signals for Alzheimer’s disease (AD) and Parkinson’s disease (PD). The corresponding genes of those missense mutations overlapping with GWAS included Our study demonstrated that DeepMEP effectively captured the impact of missense mutations on phosphorylation and highlighted an enrichment of high-impact mutations in AD- and PD-associated genomic loci. The online version contains supplementary material available at 10.1186/s40246-025-00898-4. Show less
📄 PDF DOI: 10.1186/s40246-025-00898-4
APOE
Jing Liu, Junshuang Wang, Shuang Lv +7 more · 2025 · PloS one · PLOS · added 2026-04-24
Radiation-induced brain injury (RIBI) is a significant complication following radiotherapy for brain tumors, leading to neurocognitive deficits and other neurological impairments. This study aims to i Show more
Radiation-induced brain injury (RIBI) is a significant complication following radiotherapy for brain tumors, leading to neurocognitive deficits and other neurological impairments. This study aims to identify potential biomarkers and therapeutic targets for RIBI by utilizing advanced proteomic techniques to explore the molecular mechanisms underlying RIBI. A rat model of RIBI was established and subjected to whole-brain irradiation (30 Gy). Tandem mass tagging (TMT)-based quantitative proteomics, combined with high-resolution mass spectrometry, was used to identify differentially expressed proteins (DEPs) in the brain tissues of irradiated rats. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to identify the biological processes and pathways involved. Protein-protein interaction (PPI) networks were constructed to identify key hub proteins. A total of 35 DEPs were identified, including PHLDA3, APOE and CPE. GO enrichment analysis revealed that the DEPs were mainly involved in lipid transport, cell adhesion, and metabolic processes. KEGG analysis highlighted the enrichment of pathways related to metabolism, tight junctions, and PPAR signaling. APOE was identified as a key hub protein through PPI network analysis, indicating its potential role in RIBI pathophysiology. Immunohistochemistry further validated the increased expression of PHLDA3, APOE, and CPE in the brain tissue of irradiated rats. This study provides valuable insights into the molecular mechanisms of RIBI by identifying key proteins and their associated pathways. The findings suggest that these proteins, particularly APOE and PHLDA3, could serve as potential biomarkers and therapeutic targets for clinical intervention in RIBI. These results not only enhance our understanding of RIBI's molecular pathology but also open new avenues for the development of targeted therapies to mitigate radiation-induced neurotoxicity. Show less
📄 PDF DOI: 10.1371/journal.pone.0337608
APOE
Ruotong Li, Wenye Zhao, Jiaxin Zhang +7 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
The global increase in muscle weakness poses a critical public health concern. Nutritional interventions that improve muscular function hold promise as a therapeutic potential. Vitamin A (VA) and its Show more
The global increase in muscle weakness poses a critical public health concern. Nutritional interventions that improve muscular function hold promise as a therapeutic potential. Vitamin A (VA) and its active metabolites have been implicated in muscle development and the transformation of muscle fiber types. However, conventional VA formulations are restricted by poor stability and low bioavailability. In this study, a stable Nano VA was utilized to systematically evaluate its effects on muscle development and exercise performance in mice, as well as to explore its underlying mechanisms. A total of 44 male C57BL/6J mice were randomly divided into four groups: (i) normal control (NC), (ii) 5 mg/kg Nano VA (5 NVA), (iii) 10 mg/kg Nano VA (10 NVA), and (iv) 10 mg/kg VA (10 VA). The 10 NVA group demonstrated significantly improved muscle strength and swimming endurance, compared with the NC group. Further examination suggested a significant increase in myofiber diameter, cross-sectional area, and the content of fast-twitch fibers. Additionally, Nano VA treatment improved glucose tolerance and insulin sensitivity. To elucidate the mechanism by which Nano VA enhances muscle locomotor ability, transcriptomics and metabolomics data identified 111 differentially expressed genes and 253 differential metabolites. Of these, Angptl4, Ppp1r3a, and Cyp26b1 were identified as candidate regulators of muscle development and myofiber type transformation. In conclusion, Nano VA regulates muscle development and promotes muscle fiber type conversion, thus improving muscle strength and endurance in mice. Moreover, Nano VA facilitates mitigating and improving myasthenia gravis-related conditions. Show less
no PDF DOI: 10.1096/fj.202501417RR
ANGPTL4
Zhigang Lei, Yu Wu, Weijie Xue +15 more · 2025 · Hepatology (Baltimore, Md.) · added 2026-04-24
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critica Show more
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critical homeostasis regulator, but its function in liver immune homeostasis is unknown. We aimed to clarify the role of hepatocyte FoxO1 in liver immune homeostasis and inflammation. Human liver FoxO1 expression and its association with inflammation were analyzed in patients with various inflammation-related liver diseases. Hepatocyte-specific Foxo1 knockout (FoxO1 △hepa ) mice were established. Hepatocyte-specific gene interference was employed in alcoholic hepatitis and hepatic schistosomiasis murine models. Transcriptomic, single-cell RNA sequencing, and CUT&Tag analyses were performed to elucidate the underlying mechanisms. Hepatocyte FoxO1 levels in human inflammatory livers declined prevalently and were inversely correlated with inflammation and fibrosis. Around 15-18 weeks after birth, FoxO1 △hepa mice exhibited mild spontaneous hepatic inflammation with natural killer T (NKT) cell and neutrophil accumulation. NKT cell depletion in FoxO1 △hepa mice with alcoholic hepatitis or hepatic schistosomiasis (HS) significantly reduced neutrophil accumulation and protected against liver inflammation and damage. Mechanistically, FoxO1 promoted retinoic acid synthesis to induce hepatocyte CD1d expression, which is necessary for regulating NKT cell apoptosis. Innovatively, decreased JMJD1C expression in hepatocytes caused histone H3 lysine 9 (H3K9) dimethylation at the Foxo1 promoter, repressing its transcription and disrupting local immune homeostasis. Our findings uncover a hitherto unrecognized mechanism for hepatocyte-based control of liver inflammation, in which hepatocyte FoxO1 maintained by JMJD1C restrains local NKT cells and neutrophils via CD1d induction, providing promising targets for inflammatory liver diseases. Show less
no PDF DOI: 10.1097/HEP.0000000000001590
JMJD1C
Juan Shen, Weiming Liang, Ruizhen Zhao +33 more · 2025 · iMeta · Wiley · added 2026-04-24
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and sp Show more
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and specific pathogen-free (SPF) mice using spatial transcriptomics, single-cell RNA sequencing, and targeted bile acid metabolomics across multiple organs, we systematically assessed how the gut microbiota's absence affected organ morphology, immune homeostasis, bile acid, and lipid metabolism. Through integrated analysis, we detect marked aberration in B, myeloid, and T/natural killer cells, altered mucosal zonation and nutrient uptake, and significant shifts in bile acid profiles in feces, liver, and circulation, with the alternate synthesis pathway predominant in GF mice and pronounced changes in bile acid enterohepatic circulation. Particularly, autophagy-driven lipid droplet breakdown in ileum epithelium and the liver's zinc finger and BTB domain-containing protein (ZBTB20)-Lipoprotein lipase (LPL) (ZBTB20-LPL) axis are key to plasma lipid homeostasis in GF mice. Our results unveil the complexity of microbiota-host interactions in the crosstalk between commensal gut bacteria and the host. Show less
📄 PDF DOI: 10.1002/imt2.272
LPL
Jiawei Li, Ximei Li, Jiamin Tian +5 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Lower intramuscular fat (IMF) and excessive abdominal fat reduce carcass quality in broilers. The study aimed to investigate the effects of dietary VD
📄 PDF DOI: 10.3389/fvets.2025.1542637
APOB
Rongrong Luo, Xiying Li, Ruyun Gao +13 more · 2025 · Genomics, proteomics & bioinformatics · Oxford University Press · added 2026-04-24
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for det Show more
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for detecting early-stage lung adenocarcinoma (Early-LUAD) by employing a multi-step approach, including Human Proteome Microarray (HuProtTM) discovery, focused microarray verification, and ELISA validation, on 1246 individuals consisting of 634 patients with Early-LUAD (stage 0-I), 280 patients with benign lung disease (BLD), and 332 normal healthy controls (NHCs). HuProtTM selected 417 IgG/IgM candidates, and focused microarray further verified 55 significantly elevated IgG/IgM autoantibodies targeting 32 tumor-associated antigens in Early-LUAD compared to BLD/NHC/BLD+NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and a specificity of 77.0% or 80.0% for distinguishing Early-LUAD from BLD or NHC in ELISA validation. Positive predictive values for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9-20 mm, and > 20 mm significantly increased from 47.27%, 52.00%, and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13%, and 87.88% (10-autoantibody panel combined with LDCT), respectively. The combined risk score (CRS), based on the 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified the risk for Early-LUAD. Individuals with 10 ≤ CRS ≤ 25 and CRS > 25 indicated a higher risk of Early-LUAD compared to the reference (CRS < 10), with adjusted odds ratios of 5.28 [95% confidence interval (CI): 3.18-8.76] and 9.05 (95% CI: 5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules. Show less
no PDF DOI: 10.1093/gpbjnl/qzae085
WWP2
Yifei Dou, Ying Li, Meng Zhang · 2025 · Wei sheng yan jiu = Journal of hygiene research · added 2026-04-24
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 p Show more
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 police officers were selected using cluster random sampling in the Inner Mongolia Autonomous Region between September and December 2021. Participants completed a basic information questionnaire and the Pittsburgh sleep quality index(PSQI). Latent profile analysis(LPA) was employed to examine heterogeneity in sleep quality, and multinomial Logistic regression was used to identify associated factors of the latent profiles. The mean age of participants was(43.08±8.98) years. The sample comprised 920 males(79.2%) and 242 females(20.8%), 987(84.9%) were married and 175(15.1%) were single, 644(55.4%) had a high school education or below, and 518(44.6%) had college education or above. By department, 607(52.2%) worked in grassroots police stations, 200(17.2%) were criminal police, and 355(30.6%) served in other units. Significant heterogeneity in sleep quality was identified, revealing four distinct latent classes: good sleep group(n=821, 70.6%), moderate sleep group(n=46, 4.0%), sleep-disordered group(n=249, 21.4%), and medication-assisted sleep group(n=46, 4.0%). Using the good sleepers as the reference group, multinomial Logistic regression indicated that older age was a significant risk factor for belonging to the medication-assisted sleep group(OR=1.348, 95%CI 1.078-1.822). Higher education level was a protective factor against membership in the moderate sleep group(OR=4.101, 95%CI 1.304-12.893). Serving as a grassroots police station officer or criminal police officer was a significant risk factor for membership in both the moderate sleep group(OR = 3.329, 95%CI 1.338-8.284; OR=4.188, 95%CI 1.415-12.396) and sleep-disordered group(OR=1.701, 95%CI 1.196-2.420; OR=1.587, 95%CI 1.073-2.533). Sleep quality among police officers demonstrates significant heterogeneity. Age, police department assignment, and educational level are key associated factors of distinct latent classes of sleep quality. Show less
no PDF DOI: 10.19813/j.cnki.weishengyanjiu.2025.05.015
LPA
Tianrui Liu, Feixiang Yang, Zhige Wang +7 more · 2025 · Prostate international · Elsevier · added 2026-04-24
The causal relationships between the gut microbiota and prostate cancer, prostatitis, and benign prostatic hyperplasia remain uncertain. We intend to identify the causal connections between the gut mi Show more
The causal relationships between the gut microbiota and prostate cancer, prostatitis, and benign prostatic hyperplasia remain uncertain. We intend to identify the causal connections between the gut microbiota and prostatic diseases and investigate the potential mechanisms involved. A two-sample Mendelian randomization (MR) analysis was conducted to elucidate the impact of 196 gut microbiota on prostatic diseases risk. Reverse MR, linkage disequilibrium regression score (LDSC), and colocalization analyses were performed to strengthen causal evidence. Phenome-wide MR (Phe-MR) analysis was used to evaluate the potential side effects of targeting the detected gut microbiota. We designed a two-step MR study to assess the mediating effects of sex hormones, blood metabolites, and proteins. According to the MR analyses, 31 bacterial taxa were causally associated with prostatic diseases, of which 23 types were newly identified. In addition, Our study represents the first comprehensive exploration of the causal effects of the gut microbiota on prostatic diseases and reveals the mediating effects of sex hormones and blood metabolites on the "gut-prostate axis." Show less
📄 PDF DOI: 10.1016/j.prnil.2024.11.004
FGFR1
Chaojie Ye, Chun Dou, Dong Liu +13 more · 2025 · Nature communications · Nature · added 2026-04-24
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide assoc Show more
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide association study approaches on homeostatic model assessment for insulin resistance, insulin resistance index, fasting insulin, and ratio of triglycerides to high-density lipoprotein cholesterol from MAGIC and UK Biobank to develop a comprehensive phenotype ('mvIR'), and identify 217 independent loci, including 24 novel loci. The mvIR is causally associated with higher risks of 17 cardiometabolic diseases and five aging phenotypes, independent of adiposity and sarcopenia. We outline 21 of 2644 druggable genes for insulin resistance by Mendelian randomization and colocalization, where six genes (AKT1, ERBB3, FCGR1A, FGFR1, LPL, NR1H3) encode targets for approved drugs with consistent directions in alleviating insulin resistance, with no significant side effects revealed by phenome-wide association study. This study uncovers novel loci and therapeutic targets to inform strategies promoting insulin resistance-centered cardiometabolic health and longevity. Show less
📄 PDF DOI: 10.1038/s41467-025-64985-9
FGFR1
Dan Li, Mi Zhou, Xiaomei Song · 2025 · Frontiers in aging · Frontiers · added 2026-04-24
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity beh Show more
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity behaviours within a 24-h framework. This study investigates the relationship between cognitive function and 24-h activity behaviours in older adults, further exploring whether these associations differ by sex. This study analyses data from the eighth wave of the Survey of Health, Ageing and Retirement in Europe, conducting a cross-sectional analysis of 814 older adults. Cognitive function was assessed using the SHARE-Cog tool, encompassing 10-word immediate recall, 10-word delayed recall, verbal fluency, and self-reported memory. 24-h activity behaviours (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], sedentary behaviour [SB], and sleep) were objectively measured with thigh-worn accelerometers. Compositional multivariate linear regression models were constructed using compositional data as the response variable, with cognitive function measures as predictors. Higher MVPA was linked to better cognitive outcomes (verbal fluency, 10-word immediate recall, and 10-word delayed recall) while SB and longer sleep related to poorer performance, with these associations being stronger in women (model p ≤ 0.001). Among women, cognitive outcomes were significantly associated with all activity behaviours (p range = 0.010-0.045). Women who self-reported poor memory and scored 0 on the verbal fluency spent approximately 45% of their day in SB, whereas those reporting excellent memory and scoring 60 spent 40.06% (37.18%, 42.86%) and 36.41% (31.53%, 41.10%) of their day sedentary, respectively. In contrast, men's 24-h activity composition did not vary significantly with cognitive function (p range = 0.051-0.845). Older adults with better cognitive function tend to engage in more PA and reduce sedentary and sleep time. This relationship differed by sex, with females' activity behaviours being more sensitive to cognitive function changes. These findings suggest that interventions promoting healthy lifestyles in older adults should account for cognitive function, particularly in females. Show less
📄 PDF DOI: 10.3389/fragi.2025.1686847
LPA
Huimin Yu, Shihong Li, Jian Wu +1 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
Breast cancer (BC) is one of the most prevalent malignant diseases affecting women. Cytochrome c (Cyt c) plays a critical role in various pathological processes, however, its precise mechanism in BC r Show more
Breast cancer (BC) is one of the most prevalent malignant diseases affecting women. Cytochrome c (Cyt c) plays a critical role in various pathological processes, however, its precise mechanism in BC remains unclear. This study aimed to identify prognostic genes linked to Cyt c in BC and explore their underlying mechanisms. Transcriptome data related to BC were initially obtained from TCGA and GEO database. Prognostic genes were identified through differential expression analysis, univariate Cox regression, and LASSO analysis. A risk model was subsequently developed and validated. Additionally, enrichment analysis, immune microenvironment analysis, and the construction of a TFs-mRNA network were conducted. Finally, the expression levels of prognostic genes were examined in both tumor and normal tissue samples, with confirmation through RT-qPCR. Eight prognostic genes ( Show less
📄 PDF DOI: 10.3389/fgene.2025.1627134
CETP