👤 Dongbiao Li

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Also published as: Xiaofeng Li, Jiajia Li, Jingwen Li, Zhaolun Li, Litao Li, Ruyi Li, Xiaocun Li, Wanxin Li, Jianyu Li, Jinsong Li, Xinzhi Li, Guanqiao Li, Ying-Lan Li, Zequn Li, Yulin Li, Shaojian Li, Guang-Xi Li, Yubo Li, Bugao Li, Mohan Li, Yan-Xue Li, Qingchao Li, Xikun Li, Enhong Li, Guobin Li, Hong-Tao Li, Xiangnan Li, Yong-Jun Li, Rongqing Li, Ziming Li, Hang Li, Xihao Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Xiao-Lin Li, Yicun Li, Shunqin Li, Jiajie Li, Zhao-Yang Li, K-L Li, Xinjia Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Youran Li, Peiwu Li, Yongmei Li, Changyu Li, Ran Li, Peilin Li, X Y Li, Chunshan Li, Yixiang Li, Ming Zhou Li, Z Li, Ye Li, Guanglve Li, Zili Li, Xinmei Li, Yihao Li, Liling Li, Qing Run Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Kailong Li, Qiankun Li, Shisheng Li, Shengxu Li, Sai Li, Guangwen Li, Hua Li, Xiuli Li, Yulong Li, Dongmei Li, Ru-Hao Li, Zhi-Peng Li, Lanzhou 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, Xuelin Li, Zhen-Yuan Li, Xueyang Li, Fa-Hui Li, Caiyu Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Bao Li, Shiyu Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Jinlin Li, Xiaoqing Li, Linke Li, Shuaicheng Li, C Y Li, Thomas Li, Siting Li, Xuebiao Li, Yingyi Li, Yongnan Li, Maolin Li, Jiyang Li, Jinchen Li, Jin-Ping Li, Zhongxuan Li, Xuewen Li, R Li, Xianlong Li, Aixin Li, Linting Li, Zhong-Xin Li, Xuening Li, Enhao Li, Guang Li, Xiaoming Li, Shengliang Li, Yongli Li, Z-H Li, Baohong Li, Hujie Li, Yue-Ming Li, Shuyuan Li, Zhaohan Li, L Li, Alexander Li, Yuanmei 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, Kangli Li, Ming Li, Runwen Li, Wenbo Li, Side Li, Yarong Li, Weidong Li, S E Li, Timmy Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Chuan-Hai Li, Lingxi Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Zhongyu Li, Qin Li, Zhen-Yu Li, Deyu 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, Qintong Li, Junping Li, PeiQi Li, Naishi Li, Xiaobing Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Pan Li, Shengchao A Li, Jiaying Li, Jun-Jie Li, Ruonan Li, Cui-lan Li, Shuhao Li, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Suyan Li, Chengquan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, Ya-Jun Li, Xue Cheng Li, Wenyong Li, Ding-Biao Li, Desen Li, Tianjun Li, Xiying Li, Yansong Li, Zihao Li, Weiyong Li, Xinyang Li, Fadi Li, Huawei Li, Yu-quan Li, Cui Li, Xiaoyong Li, Y L Li, Xueyi Li, Jingxiang Li, Wenxue Li, Jihua Li, Jingping Li, Zhiquan Li, Zeyu Li, Yingpu Li, Jianglin Li, Jing-Yao Li, Yan-Hua Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, Ya-Ting Li, L K Li, Wan Jie Li, Aimin 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, YiPing Li, Yuxiu Li, Tian Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Minhui Li, Yu Li, Yvonne Li, Yiwei Li, Xiangzhe Li, Zhichao Li, Jiayuan Li, Minglun Li, Yige Li, Siguang Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chiyang Li, Chunlan Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Si Li, Jing Li, Xiangyun Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Dengke Li, Zijing Li, Wentao Li, Yuchuan Li, Qingling Li, Rui-Han Li, Xuhong Li, Hongyun Li, Dong Li, Zhonggen Li, Xiong Li, Penghui Li, Xiaoxia Li, Dezhi Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Sheng-Jie Li, Defa Li, Ying-Qing Li, X L Li, Yuyan Li, Kawah Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Shupeng Li, Zhenfei Li, Sha-Sha Li, Panyuan Li, Gang Li, Mengxuan Li, Ziyu Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, Huaping Li, Ji-Liang Li, C H Li, Bohua Li, Pei-Ying Li, Bing Li, Huihuang Li, Yunmin Li, Shaobin Li, Yanying Li, Gui Lin Li, Ronald Li, Chenrui Li, Shi-Hong Li, Shilun Li, Xinyu Li, John Zhong Li, Lujiao Li, Song-Chao Li, Chenghong Li, Dengfeng Li, Baohua Li, Nianfu 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, Liwei Li, Yan-Yan Li, Huijun Li, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Lijun Li, Supeng Li, Hening Li, Yiju Li, Yuanhe Li, Fengxia Li, Guangxiao Li, Xueqin Li, Peixin Li, Feng-Feng Li, Jialing Li, Zu-Ling Li, Yunjiu Li, Xin Li, Zonghong Li, Dayong Li, Ningyan Li, Lingjiang Li, Yuhan Li, Zhenghui Li, Fuyuan Li, Ailing Li, H-F Li, Chunxia Li, Chaochen Li, Zhen-Li Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Zhengying Li, Yali Li, Zhaoshui Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, Zengyang Li, Kaiyuan Li, Mangmang Li, Chunyan Li, Runzhen Li, Xiaopeng Li, Xi-Hai Li, MengGe Li, Xuezhong Li, Anan Li, Luying Li, Jiajv Li, Pei-Lin Li, Xiaoquan Li, Ning Li, Yanxi Li, Ruobing Li, Wan-Xin Li, Xia Li, Yongjing Li, Meitao 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, Ganggang Li, Jinxin 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, Yiliang Li, Zhen-Hua Li, Chuan-Yun Li, Xinpeng Li, Hongxing Li, Wanyi Li, Gaoyuan Li, Youming Li, Mi Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Yumiao Li, Fengfeng Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Junxu Li, Xiangjun Li, Xingye Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Qingyang Li, Yuxi 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, 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, Chaoying Li, Siyu 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, Xiaoya Li, Xiao-Li Li, Shan Li, Shitao Li, Zehan Li, Lijia 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, Yumao Li, Bin-Kui Li, Yuqiu Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Y X Li, Chia Li, Yunyun Li, Zhen-Jia Li, Fu-Rong Li, Honghua Li, Lanjuan Li, Qiuxuan Li, Xiancheng Li, Man-Zhi Li, Yanmei Li, De-Jun Li, Zhihua Li, Junxian Li, Keqing Li, Shuwen Li, Minqi Li, Danxi Li, Saijuan Li, Lingjun Li, Mimi Li, Si-Xing Li, Deheng Li, Yingjie Li, Yaodong Li, Shigang Li, Yuan-Hai Li, Lujie Li, Minghao Li, Gao-Fei Li, Minle Li, Meifen Li, Yifeng Li, Le-Le Li, Huanqing Li, Ziwen Li, Yuhang Li, Yongqiu Li, Pu-Yu Li, Jianhua Li, Chanjuan Li, Nan-Nan Li, Hongming Li, Lan-Lan Li, Lingyi Li, Shuang Li, Yanchuan 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, Zhi-Xing Li, Chang Li, Yaxi Li, Ming-Han Li, Wei-Ming Li, Wenchao Li, Guangyan Li, Zhaosha Li, Xuesong Li, Jiwei Li, Chun-Quan Li, Yongzhen 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, 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, Caixia Li, Zipeng Li, Mingyue Li, Hongli Li, Yun Li, Mengqiu Li, Ling-Ling Li, Yanfeng Li, Yaqin Li, Yu-He Li, Shasha Li, Xi Li, S-C Li, Siyi Li, Minmin Li, Manna Li, Chengwen Li, Dawei Li, Shu-Feng Li, Haojing Li, Xun Li, Ming-Jiang Li, Zhiyu Li, Sitao Li, Ziyang Li, Yaochen Li, Qian Li, Tinghua Li, Zhenfen Li, Wenyang Li, Bohao Li, Shuo Li, Wenming Li, Mingxuan Li, Si-Ying Li, Xinyi Li, Jenny J Li, Xue-zhi Li, Shuai Li, Anqi Li, Bingsong Li, Xiaoju Li, Zhenyu Li, Xiaonan Li, Ting Li, Duan Li, Xiang-Yu Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Xunjia Li, Yanchang Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, 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, Kuan Li, Mengze 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, Fei-Lin Li, Junjie Li, Nuomin Li, Shulin Li, Shanglai Li, Yanyan Li, Yue Li, Taibo Li, Junqin Li, JunBo Li, Zhongcai Li, Xueying Li, Jun-Ru Li, Xiaoqi Li, Zhaobing Li, Xiucui Li, Haihua Li, Linxin Li, Yu-Lin Li, Jen-Ming Li, Tsai-Kun Li, Shujing Li, Chen-Chen Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Xiyun Li, Yi-Wen Li, Rulin Li, Huifeng Li, Shihong Li, Ya-Pei Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Shuangshuang Li, Long Li, Min-Dian Li, Wenjia 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, Xiangpan Li, Zesong Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Boru Li, Yinxiong Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Hong-Yu Li, Chuanning Li, Weijian Li, Changhui Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Dechao Li, Chunxing Li, Wenxia Li, Guoxiang Li, Ziru Li, Qiao-Xin Li, Shu-Fang Li, Huang Li, Qiusheng Li, Juxue Li, Man Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Nan Li, Gongda Li, Yajun Li, Wei-Ping Li, Yipeng Li, Mingxing Li, Nanjun Li, Xin-Yu Li, Chunyu Li, P H Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Ranran Li, 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, Wen-Ting Li, Guohua Li, Kezhen Li, Guoping Li, Xingxing Li, Ellen Li, A Li, Simin Li, Xue-Nan Li, Yijie Li, Weiguo Li, Xiaoying Li, Shengsheng Li, Suwei Li, Shuyu D Li, Jiandong Li, Ruiwen Li, Fangyong Li, Hong Li, Binru Li, Yuqi Li, Zihua Li, Yuchao Li, Hanlu Li, Xue-Peng Li, Jianang Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Weiyang Li, Feng Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Kaibo Li, Xinxiu Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Shaodan Li, Meng-Hua Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Yueguo Li, Mo Li, Zheng Li, Ming-Hao Li, Donghe Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Menghua Li, Jingqi Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Chong Li, Xiao-Kang Li, Hanqi Li, Fugen Li, Yuwei Li, Yangyang Li, Dongfang Li, Xiaochen Li, Zizhuo Li, Zhuorong Li, X-H Li, Xianrui Li, Lan-Juan Li, Dong Sheng Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Xiaoman Li, Huanqiu Li, Bing-Heng Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Jinhui Li, Zhifei Li, Ying Li, Yanshu Li, Jianlin Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Longyu Li, Guiying Li, Jinku Li, X B Li, Changgui Li, Zhisheng Li, Cuiling Li, Xuekun Li, Yuguang Li, Wenke Li, Jianguo Li, Jiayi Li, En Li, Ximei Li, Shaoyong Li, Peihua Li, Kai-Wen Li, Suwen Li, Chang-Ping Li, Guangda Li, 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, Xiaohua Li, Qifang 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, Jianyong Li, Guoxing Li, Shujie Li, Zongchao Li, Yanbin Li, Jia Li, Shiliang Li, Haimin Li, Qinrui Li, Sheng-Qing Li, Yiming Li, Lingjie Li, Xiao-Tong Li, Yiwen Li, Tie Li, Baoqi Li, Wei-Bo Li, Leyao Li, Xiaoyi Li, Xiao-Qin Li, Liyan Li, Xinke Li, Xiaokun Li, Ming-Wei Li, Wenfeng Li, Minzhe Li, Jiajing Li, Karen Li, Yanlin Li, X Li, Liao-Yuan Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Li-Na Li, Hengguo Li, An-Qi Li, Xuehua Li, Hui Li, AnHai Li, Chenli Li, 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, Zhu Li, Rongling Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Guangqiang Li, Jian'an Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Shunhua Li, Yu-I Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Shen Li, Tianjiao Li, Ziqi 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, Zhankui Li, Zhi 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, Huimin Li, Cun Li, Ruifang Li, T Li, Xiao-xu Li, Man-Xiang Li, Yinghui Li, Cong Li, Chengbin Li, Feilong Li, Sin-Lun Li, Yuping 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, 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, Caolong Li, Michelle Li, Zhifan Li, J Li, Zhi-Jian Li, Jianwei Li, Yan-Guang Li, Jiexin Li, Hongyan Li, Ji-Min Li, Zhen-Xi Li, Guangdi Li, Peipei Li, Tian-Yi Li, Xiaxia Li, Nien Li, Yuefeng Li, Zhihao Li, Peiyuan Li, Yao Li, Tiansen Li, Zheyun Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Jieshou Li, Lin Li, Jinfang Li, Chenjie Li, Roger Li, Yanming Li, Mengqing Li, S L Li, Hong-Lan 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, 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, Shengli Li, Shugang 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, H J Li, Zhenyan Li, Ji Xia Li, Meizi Li, Yu-Ye Li, Qing-Wei Li, Yuezheng Li, Qiang Li, Hsiao-Hui Li, Zhengnan Li, L I Li, Jianglong Li, Hongzheng Li, Laiqing Li, Zhongxia Li, Ningyang Li, Guangquan Li, Xiaozheng Li, Shun Li, Hui-Jun 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, Xiangling Li, Sung-Chou 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, Xiaojiao Li, H Li, Dongliang Li, Chenxiao Li, Yinzhen Li, Hongjia Li, Li-Min Li, Xiao-Jing Li, Yunsheng Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Daoyuan Li, Baichuan Li, Haibo Li, Wenqi Li, Zhenzhe Li, Jian-Mei Li, Xiao-Jun Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Xueling Li, Qiao Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Yike Li, Wanni Li, Yihan Li, Chitao Li, Haiyang Li, Jiayu Li, Xiaobai Li, Junsheng Li, Pingping Li, Mingquan Li, Wen-Ya Li, Suran Li, Yunlun Li, Rongxia Li, Yuanfang Li, Yingqin Li, Guoqin Li, Qiner Li, Huiqin Li, Jiafang Li, Shanhang Li, Chunlin Li, Han-Bing Li, Zongzhe Li, Yikang Li, Jisen Li, Si-Yuan Li, Caihong Li, Hongmin Li, Peng Peng Li, Yajing Li, Kenli Li, Guanglu Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Jian-Jun Li, Dongmin Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Xinxin Li, Jian-Shuang Li, You-Mei Li, Yubin Li, Chenglan Li, Dazhi Li, Beixu Li, Yuhong Li, Di Li, Guiyuan Li, Fengqiao Li, Suk-Yee Li, Yanbing Li, Jufang Li, Shengjie Li, Yuanyuan 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, Lai K Li, Jiong Li, Yanni Li, Daiyue Li, Bingong Li, Yongsheng Li, Huifang Li, Xiujuan Li, Lingling Li, Chunxue Li, Yunlong Li, Xinhua Li, Jianshuang Li, Juanling Li, Minerva X Li, Xinbin Li, Alexander H Li, Xue-jing Li, Yuling Li, Ding Li, Wendeng Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Linyan Li, Yanjun Li, Shengze Li, Ming-Yang Li, Jiequn Li, Zhongding Li, Hewei Li, Da-Jin Li, Jiangui Li, Zhengyang Li, Cyril Li, Xinghui Li, Yuefei Li, Xiao-kun Li, Xinyan Li, Yuanhao Li, Xiaoyun Li, Congcong Li, Ji-Lin Li, Ping'an Li, Yushan Li, Juan Li, Huan Li, Weiping Li, Changjiang Li, Chengping Li, He-Zhen Li, G-P Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Weihai Li, Jiangan 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, 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, Yi-Ning Li, Xiaolian Li, Dandan Li, Yunan Li, Zechuan Li, Zhijun Li, Jiazhou Li, Sherly X Li, Wanling Li, Ya-Ge Li, Yinyan Li, Qijun Li, Rujia Li, Guangli Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Wan-Shan Li, Xiaohan Li, Zhongwen Li, Huijie Li, W W Li, Yalan Li, Jing-gao Li, Yiyang Li, Fengxiang Li, Xuejun Li, Shunwang Li, Nana Li, Chao Li, Yaqing Li, Bingsheng Li, Jingui Li, Yaqiao Li, Huamao Li, Xiankun Li, Jingke Li, Tianyao Li, Xiaowei Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Hai-Yun Li, Haoran Li, Zhongxian Li, Xiaoliang Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Xinjian Li, Jialun Li, Rui Li, Zilu Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Binghua Li, Xuyi Li, Hanjun Li, Yunchu Li, Zhengyao Li, Jin-Qiu Li, Qihua Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, 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, Baoguo Li, Jianrong 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, 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, Kunlin Li, Bolun Li, Linchuan Li, Jiachen Li, Shu-Qi Li, Haibin Li, Zehua Li, Huangbao Li, Guo-Chun Li, Xinli Li, S Li, Mengyuan Li, Wenqing Li, Wenhua Li, Caiyun Li, Congye Li, Xinrui Li, Dehai Li, Wensheng Li, Qingshang Li, Jiannan Li, Guanbin Li, Hanbin Li, Zhiyi Li, Xing Li, Wanwan Li, Jia Li Li, Zhaoyong Li, SuYun Li, Shiyi Li, Wan-Hong Li, Mingke Li, Suchun Li, Xiaoyuan Li, Huanhuan Li, Yanan Li, Zongfang Li, Jiayan Li, Yang Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Dongdong Li, Yimei Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Zhi-qiang Li, Shaojing Li, S S Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Tong Li, Lihua Li, Yilong Li, Xue-Lian Li, Zhiping Li, Yan-Li Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Yanli Li, Jingfeng Li, Zhi-Yuan Li, Hai Li, Kaibin Li, Yuan-Jing Li, Xuefeng Li, Xiaohu Li, Wenjie 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, Yujun Li, Mian Li, Dalin Li, Lixi Li, Jin-Xiu Li, Kun Li, Qizhai Li, Jiwen Li, Pengju Li, Peifeng Li, Zhouhua Li, Ai-Jun Li, Qingqin S Li, Honglei Li, Guojin Li, Yueting Li, Xin-Yue Li, Dingchen Li, YaJie Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, 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, Tianye Li, Cuiguang Li, Qun 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, Daniel Tian Li, Rong-Bing Li, Jingyong Li, Honggang Li, Rong Li, Shikang Li, Wei-Yang Li, Mingkun Li, Binxing Li, Shi-Ying Li, Ming Xing Li, Zixiao Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Bei-Bei Li, Shishi Li, Hong-Lian Li, Xiumei Li, Haitong Li, Yuli Li, Melody M H Li, Ruibing Li, Qingfang Li, Peibo Li, Qibing Li, Huanjun Li, Heng Li, Wende Li, Chung-Hao Li, Liuzheng Li, Zhanjun Li, Yifei Li, Tianming Li, Chang-Sheng Li, Xiao-Na Li, Tianyou Li, Jipeng Li, Xidan Li, Yixing Li, Chengcheng Li, Yu-Jin Li, Longxuan Li, Baoting Li, Huiyou Li, Ka Wan Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Yu-Hao Li, Gui-xing Li, Shunle Li, Niu Li, Shilin Li, Siyue Li, Diyan Li, Shili Li, Mengyao Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Meiqing Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Yinhao Li, Zonglin Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, 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, Kainan Li, Guohui Li, Yongzhe Li, Qingfeng Li, Xiaoyan Li, Tianyi Li, Nanlong Li, Ping Li, Xu-Bo Li, Nien-Chen Li, Fangzhou Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Yuanchuang Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Qing-Chang Li, Hongliang Li, Shengbiao Li, Hong-Yan Li, Yue-Rui Li, Ruidong Li, Dalei Li, Zongjun Li, Y M Li, Changqing Li, Hanting Li, Dong-Jie Li, Sijie Li, Xiaomin 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, 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, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Yaxian Li, Duo Li, Dali Li, Zhiming Li, Xuemei Li, Yongting Li, Xueting Li, Hongxia Li, Danyang Li, Zhenjun Li, Ren Li, Tiandong Li, Lanfang Li, Hongye Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, W J Li, Qiji Li, Zhipeng Li, Zhijia Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaobo Li, Xiaoting Li, Ruotai Li, Meijia Li, Shujiao Li, Yaojia Li, Xiao-Yao Li, Weirong Li, Kun-Ping Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Yandong Li, Runzhao Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Yingjun Li, Xiufeng Li, Yanxin Li, Xiaohuan Li, Ying-Qin Li, Boya Li, Lamei Li, O Li, Fan Li, Jun Z Li, Joyce Li, Suheng Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Zhiqiang Li, Junru Li, Jiangchao Li, Hecheng Li, Haifeng Li, Changkai Li, Yueping Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Xuanxuan Li, Rui-Jún Eveline Li, Bing-Mei Li, Yunman Li, Chaoqian Li, Shuhua Li, Yu-Cheng Li, Chunying Li, Yirun Li, Haomiao Li, Weiheng Li, Leipeng Li, Qianqian Li, Baizhou Li, Zhengliang Li, YiQing Li, Han-Ru Li, Sheng Li, Wei-Qin Li, Weijie Li, Yaqiang Li, Guoyin Li, Qingxian Li, Zongyi Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Chengjun Li, Keke Li, Yongpeng 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, Jiahao Li, Hanxiao Li, Jiansheng Li, Shibao Li, Shuying Li, Kunlong Li, Xiaomei Li, Ruijin Li, Pengjie Li
articles
Xiaoli Shi, Xueli Jia, Wei Liu +5 more · 2025 · Stem cells translational medicine · Oxford University Press · added 2026-04-24
Zinc finger protein 750 (ZNF750) has been identified as a potential tumor suppressor across multiple malignancies. Nevertheless, the specific involvement of ZNF750 in the regulation of mesenchymal cel Show more
Zinc finger protein 750 (ZNF750) has been identified as a potential tumor suppressor across multiple malignancies. Nevertheless, the specific involvement of ZNF750 in the regulation of mesenchymal cell differentiation and bone homeostasis has yet to be elucidated. In the current study, we observed a substantial presence of ZNF750 in bone tissue and noted alterations in its expression during osteogenic differentiation of mesenchymal progenitor cells. Functional experiments indicated that ZNF750 promoted osteogenic differentiation while impeding adipogenic differentiation from mesenchymal stem/progenitor cells. Further mechanistic investigations revealed that ZNF750 transcriptionally suppressed the expression of Snail family transcriptional repressor 1 (SNAI1) by binding to the proximal promoter region of Snai1 gene, thereby activating Wnt/β-catenin signaling. SNAI1 exerted opposing effects on cell differentiation towards osteoblasts and adipocytes in comparison to ZNF750. The overexpression of SNAI1 counteracted the dysregulated osteogenic and adipogenic differentiation induced by ZNF750. Furthermore, the transplantation of Znf750-silenced bone marrow stromal cells into the marrow of wild-type mice resulted in a reduction in cancellous and cortical bone mass, alongside a decrease in osteoblasts and an increase in marrow adipocytes, while the number of osteoclasts remained unchanged. This study presents the first demonstration that ZNF750 regulates the differentiation of osteoblasts and adipocytes from mesenchymal stem/progenitor cells by transcriptionally deactivating SNAI1 signaling, thereby contributing to the maintenance of bone homeostasis. It suggests that ZNF750 may represent a promising therapeutic target for metabolic bone disorders such as osteoporosis. Show less
no PDF DOI: 10.1093/stcltm/szaf013
SNAI1
Liqun Wang, Honglei Li, Tianqi Qiao +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
This study investigates the heterogeneity in kindergarten teachers' perceptions of organizational climate and its impact on job burnout. Guided by the AGIL model from social systems theory and the Job Show more
This study investigates the heterogeneity in kindergarten teachers' perceptions of organizational climate and its impact on job burnout. Guided by the AGIL model from social systems theory and the Job Demands-Resources (JD-R) model, it addresses the need to move beyond variable-centered approaches to understand how distinct climate profiles are associated with teacher well-being. A person-centered latent profile analysis (LPA) was employed. A sample of 1,008 kindergarten teachers from China completed measures assessing organizational climate and burnout. The analysis aimed to identify distinct climate profiles and examine their relationships with demographic variables (kindergarten type, assessment level, teaching experience) and the three dimensions of burnout (emotional exhaustion, depersonalization, reduced personal accomplishment). The LPA revealed five distinct organizational climate profiles: Controlled, Moderate, Indifferent, Positive, and Authoritative. Profile membership was significantly predicted by kindergarten assessment level and teachers' years of experience, but not by kindergarten type. Crucially, the profiles differed significantly across all burnout dimensions. Teachers in Positive climates reported the lowest burnout levels, whereas those in Controlled and Indifferent climates experienced the highest. The findings underscore the structural diversity of organizational climates in early childhood settings and their profound psychological consequences. This study validates the application of social systems theory and the JD-R model in this context, revealing how different configurations of job demands and resources shape teacher well-being. The results provide a theoretical lens for understanding educational organizations and offer practical implications for developing tailored, climate-specific intervention strategies to mitigate burnout and support sustainable professional development. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1708777
LPA
Yingyi Wang, Haisu Wu, Ruijie Geng +4 more · 2025 · Alpha psychiatry · added 2026-04-24
To explore the molecular mechanisms underlying clozapine-induced metabolic syndrome (MetS) in schizophrenia patients, providing scientific evidence for clinicians to prevent and manage metabolic syndr Show more
To explore the molecular mechanisms underlying clozapine-induced metabolic syndrome (MetS) in schizophrenia patients, providing scientific evidence for clinicians to prevent and manage metabolic syndrome during the treatment of psychiatric disorders. Ten schizophrenia patients with MetS and ten matched controls were recruited from Shanghai Mental Health Center according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for schizophrenia and the 2016 Chinese Adult Dyslipidemia Prevention and Treatment Guidelines for MetS. Peripheral blood RNA sequencing was performed to identify differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to pinpoint hub genes. Mendelian randomization (MR) was conducted to validate causal relationship between serum brain-derived neurotrophic factor (BDNF) levels and MetS components. A total of 1019 DEGs were identified, grouped into eight mRNA modules through WGCNA. Key hub genes included Significant differences in gene expression are observed between schizophrenia patients with and without MetS. Individual variability in clozapine-induced MetS may be linked to DEGs. Show less
📄 PDF DOI: 10.31083/AP49352
BDNF
Yikai Zhang, Yi Xie, Shenglong Xia +9 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Colorectal cancer (CRC) is a leading cause of cancer mortality while diabetes is a recognized risk factor for CRC. Here we report that tirzepatide (TZP), a novel polypeptide/glucagon-like peptide 1 re Show more
Colorectal cancer (CRC) is a leading cause of cancer mortality while diabetes is a recognized risk factor for CRC. Here we report that tirzepatide (TZP), a novel polypeptide/glucagon-like peptide 1 receptor (GIPR/GLP-1R) agonist for the treatment of diabetes, has a role in attenuating CRC growth. TZP significantly inhibited colon cancer cell proliferation promoted apoptosis in vitro and induced durable tumor regression in vivo under hyperglycemic and nonhyperglycemic conditions across multiple murine cancer models. As glucose metabolism is known to critically regulate colon cancer progression, spatial metabolomics results revealed that glucose metabolites are robustly reduced in the colon cancer regions of the TZP-treated mice. TZP inhibited glucose uptake and destabilized hypoxia-inducible factor-1 alpha (HIF-1α) with reduced expression and activity of the rate-limiting enzymes 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3) and phosphofructokinase 1 (PFK-1). These effects contributed to the downregulation of glycolysis and the tricarboxylic acid (TCA) cycle. TZP also delayed tumor development in a patient-derived xenograft (PDX) mouse model accompanied by HIF-1α mediated PFKFB3-PFK-1 inhibition. Therefore, the study provides strong evidence that glycolysis-blocking TZP, besides its application in treating type 2 diabetes, has the potential for preclinical studies as a therapy for colorectal cancer used either as monotherapy or in combination with other anticancer therapies. Show less
📄 PDF DOI: 10.1002/advs.202411980
GIPR
Sijing Liu, Caixia Yang, Xiaotong Zhou +5 more · 2025 · Journal of medicinal food · SAGE Publications · added 2026-04-24
Cordyceps has been clinically used to treat atherosclerosis (AS) since the 1980s. However, the active components responsible for its effects and the underlying mechanisms remain poorly understood. In Show more
Cordyceps has been clinically used to treat atherosclerosis (AS) since the 1980s. However, the active components responsible for its effects and the underlying mechanisms remain poorly understood. In this study, we aimed to explore the anti-AS effects and mechanisms of action of wild Cordyceps polysaccharides (WCP). The molecular weight, monosaccharide composition, and structural characteristics of WCP were analyzed. Furthermore, the anti-AS effects of WCP were evaluated using apolipoprotein E knockout ( Show less
no PDF DOI: 10.1177/1096620X251380195
NR1H3
Jin Li, Jiawen Wang, Yaodong Li +7 more · 2025 · Biology · MDPI · added 2026-04-24
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, with current therapies offering only limited symptomatic relief and lacking disease-modifying ef Show more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, with current therapies offering only limited symptomatic relief and lacking disease-modifying efficacy. Addressing this critical therapeutic gap, natural multi-target compounds like mulberroside A (MsA)-a bioactive glycoside from Show less
📄 PDF DOI: 10.3390/biology14091114
BACE1
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
Chenming Liu, Sutong Xu, Hongkai Yao +7 more · 2025 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders characterized by β-amyloid (Aβ) deposition, neurofibrillary tangles, neuronal loss, and neuroinflammation. It represen Show more
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders characterized by β-amyloid (Aβ) deposition, neurofibrillary tangles, neuronal loss, and neuroinflammation. It represents a growing global health crisis. Although astrocytes contribute to neuroinflammatory cascades, their molecular regulators in AD progression remains elusive. Here, through single-cell transcriptomic analysis, we identified SerpinA3N as a disease-progressive modulator upregulated in AD astrocytes, with expression levels correlating with pathological severity. Astrocytic SerpinA3N knockdown in AD mice rescued cognitive deficits across multiple behavioral tests, and concurrently attenuated neuroinflammatory responses, as evidenced by decreased astrocytic/microglial activation and reduced cytotoxic substance release. Moreover, histopathological analyses demonstrated decreased neuronal loss and Aβ deposition following SerpinA3N knockdown. Mechanistically, we elucidated that SerpinA3N cooperated with APOE to exacerbate AD pathology through NFκB signaling activation. Our study uncovers a novel astrocyte-mediated pathogenic cascade driving AD progression and establishes SerpinA3N as a promising therapeutic target for neuroinflammation modulation in AD. Show less
📄 PDF DOI: 10.1186/s12974-025-03644-8
APOE
Yu-Hang Wang, Chang-Ping Li, Jing-Xian Wang +6 more · 2025 · Reviews in cardiovascular medicine · added 2026-04-24
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limi Show more
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limited. In this observational study, 1111 PMI patients (≤55 years) at Tianjin Chest Hospital from 2017 to 2022 were selected and divided according to their SYNTAX scores into a low-risk group (≤22) and medium-high-risk group (>22). These groups were further randomly assigned to a training or test set in a ratio of 7:3. Lasso-logistic was initially used to screen out target factors. Subsequently, Lasso-logistic, random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost) were used to establish prediction models based on the training set. After comparing prediction performance, the best model was chosen to build a prediction system for coronary artery severity in PMI patients. Glycosylated hemoglobin (HbA1c), angina, apolipoprotein B (ApoB), total bile acid (TBA), B-type natriuretic peptide (BNP), D-dimer, and fibrinogen (Fg) were associated with the severity of lesions. In the test set, the area under the curve (AUC) of Lasso-logistic, RF, KNN, SVM, and XGBoost were 0.792, 0.775, 0.739, 0.656, and 0.800, respectively. XGBoost showed the best prediction performance according to the AUC, accuracy, F1 score, and Brier score. In addition, we used decision curve analysis (DCA) to assess the clinical validity of the XGBoost prediction model. Finally, an online calculator based on the XGBoost was established to measure the severity of coronary artery lesions in PMI patients. In summary, we established a novel and convenient prediction system for the severity of lesions in PMI patients. This system can swiftly identify PMI patients who also have severe coronary artery lesions before the coronary intervention, thus offering valuable guidance for clinical decision-making. Show less
📄 PDF DOI: 10.31083/RCM26102
APOB
Qing Li, Zhenyu Zhou, Xiaoying Li +1 more · 2025 · Mutation research · Elsevier · added 2026-04-24
Cervical cancer (CC) is a major cause of morbidity and mortality in women, with complex etiology and progression. Diacylglycerol kinases (DGKs) are pivotal in lipid metabolism. Although diacylglycerol Show more
Cervical cancer (CC) is a major cause of morbidity and mortality in women, with complex etiology and progression. Diacylglycerol kinases (DGKs) are pivotal in lipid metabolism. Although diacylglycerol kinase beta (DGKβ) is well-studied in neurology, its role in cancer, especially CC, remains underexplored. This study aimed to explore DGKβ's role and mechanism in CC. Bioinformatics analysis was employed to identify genes differentially expressed in CC, with western blot confirming DGKβ expression in CC cells. The role of DGKβ was examined through small interfering RNA-mediated gene silencing, proliferation tests, migration and invasion assays, and angiogenesis studies. In-depth bioinformatics explored DGKβ-regulated downstream targets and pathways. Pathological assessment elucidated the impact of DGKβ and angiopoietin 4 (ANGPT4) on CC samples. Our data identified DGKβ as a promising candidate gene in the context of CC. This conclusion stemmed from the notable observation that DGKβ exhibited a heightened expression in CC cell lines. Notably, the silencing of DGKβ resulted in the suppression of CC cell proliferation, invasion, migration, as well as the epithelial-mesenchymal transition processes. Additional bioinformatics analysis delving into DGKβ-associated genes revealed ANGPT4 as a downstream target gene of DGKβ, which is capable of modulating angiogenesis and possesses multiple cellular functions related to cell survival, proliferation, and migration. Most significantly, our findings also demonstrated that both DGKβ and ANGPT4 were overexpressed in clinical specimens of CC. This study uncovered an oncogenic role for DGKβ in CC and identified a potential regulatory link between DGKβ and ANGPT4 in tumor angiogenesis. These findings provided promising directions for developing new diagnostic and therapeutic approaches for CC. Show less
no PDF DOI: 10.1016/j.mrfmmm.2025.111913
ANGPTL4
Qi He, Lin Jiang, Feng-Lei Chao +11 more · 2025 · Experimental neurology · Elsevier · added 2026-04-24
Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein 1 (LINGO-1) is a neuronal system-specific transmembrane protein that is highly expressed in the brains o Show more
Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein 1 (LINGO-1) is a neuronal system-specific transmembrane protein that is highly expressed in the brains of patients with Alzheimer's disease (AD), and our previous findings showed that LINGO-1 antagonism can improve cognitive function and protect hippocampal GABAergic interneurons in AD model mice. However, the specific mechanism underlying these effects is not clear. In this study, an adeno-associated virus (AAV) was used to directly interfere with hippocampal LINGO-1 in vivo, and LINGO-1 antagonists, cannabinoid type 1 receptor (CB1R) agonists, and CB1R antagonists were used to treat mouse hippocampal neurons (HT22 neurons) in vitro. We found that overexpressing hippocampal LINGO-1 in normal young mice impaired spatial learning and memory and reduced hippocampal CB1R protein levels, whereas silencing hippocampal LINGO-1 in AD model mice had the opposite effect. Additionally, antagonizing LINGO-1 increased CB1R/tyrosine kinase receptor B (TrkB) signalling and rescued CB1R- rich cholecystokinin-GABAergic (CCK-GABAergic) interneurons in HT22 neurons transduced with an APP/PS1-expressing virus. Competitive inhibition of LINGO-1 and CB1R was observed, and antagonizing LINGO-1 reversed the changes in HT22 neurons caused by the inhibition of CB1R, such as the decreases in the protein levels of doublecortin (DCX), TrkB, and phosphorylated TrkB (p-TrkB). These findings provide an important scientific basis for further exploration of the mechanism by which LINGO-1 regulates cognitive function and hippocampal GABAergic interneurons in AD model mice. Show less
no PDF DOI: 10.1016/j.expneurol.2025.115319
LINGO1
Defu Tie, Yuting Wang, Jieru Zhou +6 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18121786
BDNF
Fawang Du, Hanchao Wang, Zhihong Chen +7 more · 2025 · Journal of asthma and allergy · added 2026-04-24
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcript Show more
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcriptomics profile and promising biomarkers for asthma severity prediction. In discovery cohort, induced sputum cells from 3 non-severe and 3 severe asthma patients were collected and analyzed using RNA-seq. Multivariate analysis was performed to explore asthma severity-associated transcriptomics profile and differential expressed genes (DEGs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used for pathway enrichment analysis. Subsequently, based on the previous study and clinical experience, the mRNA expressions of 6 overlapped asthma severity-associated DEGs and Distinct asthma severity-associated transcriptomics profile was identified in induced sputum cells in discovery cohort. Then, 345 DEGs were found, of which 38 terms and 32 pathways were enriched using GO and KEGG, respectively. In validation cohort, the mRNA expressions of Collectively, this study provides the first identification of the association between induced sputum cells transcriptomics profile and asthma severity, indicating the potential value of transcriptomics for asthma management. The study also reveals the promising value of serum C3 for predicting asthma severity in clinical practice. Show less
no PDF DOI: 10.2147/JAA.S517140
NRXN3
Xiaolan Chen, Jin You, Qin Ma +7 more · 2025 · Nature communications · Nature · added 2026-04-24
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Al Show more
R-loop is a common chromatin feature consisting of a displaced single-stranded DNA and an RNA-DNA hybrid, and dysregulation of R-loop surveillance results in genomic and transcriptomic instability. Although the RNA moiety of most R-loops originates from linear transcripts, circular RNAs (circRNAs), outputs from back-splicing, can also hybridize with the complementary strand of a DNA duplex. However, how circRNA-associated R-loops (ciR-loops) are monitored remains elusive. Here, we identify the DEAD-box RNA helicase Brr2 as an evolutionarily-conserved ciR-loop repressor with dual roles in inhibiting circRNA generation and resolving harmful ciR-loops. Accumulation of ciR-loops caused by loss-of-function of this dual-action factor induces antisense transcription and premature transcription termination for many genes and generates significant DNA damage, which further leads to a series of defects in DNA replication, cell division and cell proliferation. We propose that functional integration of multilayered regulation by a single protein can be an efficient double protection against genome instability. Show less
📄 PDF DOI: 10.1038/s41467-025-64174-8
DHX36
Hongwei Wang, Yu-Nan Zhu, Sifan Zhang +5 more · 2025 · Molecular medicine (Cambridge, Mass.) · BioMed Central · added 2026-04-24
The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biologi Show more
The remodeling of the extracellular matrix (ECM) plays a pivotal role in tumor progression and drug resistance. However, the compositional patterns of ECM in breast cancer and their underlying biological functions remain elusive. Transcriptome and genome data of breast cancer patients from TCGA database was downloaded. Patients were classified into different clusters by using non-negative matrix factorization (NMF) based on signatures of ECM components and regulators. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify core genes related to ECM clusters. Additional 10 independent public cohorts including Metabric, SCAN_B, GSE12276, GSE16446, GSE19615, GSE20685, GSE21653, GSE58644, GSE58812, and GSE88770 were collected to construct Training or Testing cohort, following machine learning calculating ECM correlated index (ECI) for survival analysis. Pathway enrichment and correlation analysis were used to explore the relationship among ECM clusters, ECI and TME. Single-cell transcriptome data from GSE161529 was processed for uncovering the differences among ECM clusters. Using NMF, we identified three ECM clusters in the TCGA database: C1 (Neuron), C2 (ECM), and C3 (Immune). Subsequently, WGCNA was employed to pinpoint cluster-specific genes and develop a prognostic model. This model demonstrated robust predictive power for breast cancer patient survival in both the Training cohort (n = 5,392, AUC = 0.861) and the Testing cohort (n = 1,344, AUC = 0.711). Upon analyzing the tumor microenvironment (TME), we discovered that fibroblasts and B cell lineage were the core cell types associated with the ECM cluster phenotypes. Single-cell RNA sequencing data further revealed that angiopoietin like 4 (ANGPTL4) We identified distinct ECM clusters in breast cancer patients, irrespective of molecular subtypes. Additionally, we constructed an effective prognostic model based on these ECM clusters and recognized ANGPTL4 Show less
📄 PDF DOI: 10.1186/s10020-025-01237-y
ANGPTL4
Qingxing Xiao, Sibao Yang, Yuwei Yang +7 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Fatty liver hemorrhage syndrome (FLHS) is the most common metabolic diseases in laying hens during the late-laying period, and it causes a significant economic burden on the poultry industry. The comp Show more
Fatty liver hemorrhage syndrome (FLHS) is the most common metabolic diseases in laying hens during the late-laying period, and it causes a significant economic burden on the poultry industry. The competing endogenous RNA plays crucial roles in the occurrence and development of fatty liver. Based on the previously constructed lncRNA-miRNA-mRNA networks, we selected the axis of ENSGALT00000079786-LPL-miR-143-5p for further study to elucidate its mechanistic role in development of fatty liver. In this study, we identified a novel highly conserved lncRNA (ENSGALT00000079786) in poultry, which we designated as lncRNA A2ml2 based on its chromosomal location. Fluorescent in situ hybridization (FISH) revealed that lncRNA A2ml2 was localized in both the nucleus and cytoplasm. Dual-luciferase reporter assay validated the targeted relationship between lncRNA A2ml2, miR-143-5p, and the LPL gene. To further analyze the lncRNA A2ml2 and miR-143-5p function, lncRNA A2ml2 overexpression vector was successfully constructed and transfected into Leghorn male hepatocellular (LMH) cells, which could remarkably inhibit cellular lipid deposition was detected by oil red staining (P < 0.01), the opposite occurred for miR-143-5p (P < 0.01). qPCR demonstrated an inverse correlation between miR-143-5p expression and lncRNA A2ml2 expression, and confirmed that miR-143-5p directly target lncRNA A2ml2. Similarly, we found an inverse correlation between expression of LPL and the expression of miR-143-5p. To further investigate the interactions among these three factors and their effects on cellular lipid metabolism, we assessed the expression levels of LPL by co-transfecting lncRNA A2ml2 with miR-143-5p mimic and miR-143-5p mimic binding site mutants. Co-transfection experiments showed that miR-143-5p diminished the promoting effect of lncRNA A2ml2 on LPL. Meanwhile, miR-143-5p has the capacity to mitigate the suppressive impact of lncRNA A2ml2 overexpression on lipid accumulation in LMH cells. The results revealed that lncRNA A2ml2 attenuated hepatic lipid accumulation through negatively regulating miR-143-5p and enhancing LPL expression in LMH cells. Our findings offer novel insights into ceRNA-mediated in FLHS and identify a novel lncRNA as a potential molecular biomarker. Show less
📄 PDF DOI: 10.1016/j.psj.2025.105003
LPL
Xiaojing Liu, Suxia Wang, Gang Liu +7 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.101498
ANGPTL4
Changlong Zhang, Yuxuan Li, Yang Wang +6 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Polycystic ovary syndrome (PCOS) is frequently accompanied with metabolic dysfunctions, yet the causal relationships between metabolic factors and PCOS remain to be conclusively established and etiolo Show more
Polycystic ovary syndrome (PCOS) is frequently accompanied with metabolic dysfunctions, yet the causal relationships between metabolic factors and PCOS remain to be conclusively established and etiology-based therapies are lacking. To comprehensively identify the metabolic causal factors and potential drug targets for PCOS. This genetic association study was conducted using bidirectional two-sample Mendelian Randomization (MR), multivariable MR (MVMR) and drug-target MR. Considering metabolic sexual dimorphism, female-specific genome-wide association studies (GWASs) for metabolic factors were obtained. To ensure the robustness of the findings, an additional independent PCOS GWAS dataset was utilized for replication. The PCOS cohort included 10,074 PCOS cases (mean age 28 to 45 years) and 103,164 controls (mean age 27 to 60 years) of European ancestry. All participants were female. Employing two-sample MR analysis, we found that genetically proxied body mass index (BMI) (OR = 3.40 [95 % CI, 2.65-4.36]), triglyceride (TG) (OR = 1.54 [95 % CI, 1.17-2.04]), low-density lipoprotein cholesterol (LDL-c) (OR = 1.37 [95 % CI, 1.07-1.76]), and type 2 diabetes (T2D) (OR = 1.24 [95 % CI, 1.09-1.41]) were significantly associated with an increased risk of PCOS, whereas genetically predicted high-density lipoprotein cholesterol (HDL-c) (OR = 0.61 [95 % CI, 0.47-0.80]) decreased the odds of PCOS. Stepwise MVMR established a hierarchy of interactions among these metabolic factors, identifying BMI and HDL-c as the most prominent causal factors. Notably, drug-target MR analysis identified incretin-based therapeutics, PCSK9 inhibitors, LPL gene therapy, sulfonylureas, and thiazolidinediones as potential therapeutics for PCOS. All these findings were validated in an independent dataset. This study offered insights into the roles of obesity, diabetes, and dyslipidemia in PCOS etiology and therapeutics, underscoring the necessity for managing metabolic health in women and paving the way for tailored therapeutic strategies for PCOS based on its metabolic underpinnings. Show less
📄 PDF DOI: 10.1016/j.jare.2024.10.038
LPL
Zhengdong Wei, Shasha Zhang, Keke Bai +11 more · 2025 · Development (Cambridge, England) · added 2026-04-24
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two la Show more
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two largest populations of neocortical interneurons, innervate the soma and/or proximal dendrites, and distal dendrites of pyramidal neurons, respectively. Using PV- and SST-specific knockout mouse models, we show that PV+ interneurons require FGFR2, which responds to FGF7, to drive PV+ inhibitory presynaptic maturation on perisomatic regions of Layer V pyramidal neurons. In contrast, SST+ interneurons rely on both FGFR1 and FGFR2, which respond to FGF10 or FGF22, to promote SST+ inhibitory presynaptic maturation on distal dendrites of pyramidal neurons in cortical Layer I. Mechanistically, FGF-FGFR signaling sustains VGAT protein levels in interneurons through PP2A and Akt pathways. Together, these findings demonstrate that distinct FGF ligand-receptor combinations regulate inhibitory presynaptic differentiation by PV+ and SST+ interneurons, contributing to the formation of compartment-specific synaptic patterns. Show less
no PDF DOI: 10.1242/dev.204532
FGFR1
Mimi Li, Lichao Ye, Chunnuan Chen · 2025 · Scientific reports · Nature · added 2026-04-24
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contr Show more
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contributing to stroke remains poorly understood. This study aims to investigate the association between the apoB/apoA1 ratio and intracranial or extracranial atherosclerosis. We enrolled 408 patients with acute ischemic stroke who had never been treated with statins or fibrates. Based on the images from computed tomography angiography (CTA), the patients were categorized into four groups: intracranial atherosclerosis stenosis (ICAS, n = 136), extracranial carotid atherosclerosis stenosis (ECAS, n = 45), combined intracranial and extracranial atherosclerosis stenosis (COAS, n = 73), and non-cerebral atherosclerosis stenosis (NCAS, n = 154). Demographic characteristics, clinical factors, and serum lipid levels were collected and then compared across groups. The apoB/apoA1 ratio was significantly higher in patients with ICAS, ECAS and COAS compared to those in the NCAS group. Multivariable logistic regression analysis demonstrated that the ApoB/ApoA1 ratio was independently associated with ICAS, but not with ECAS. ROC curve analysis showed that the ApoB/ApoA1 ratio had a good diagnostic ability for ICAS, with an area under the curve (AUC) of 0.764, an optimal cut-off value of 0.8122, a sensitivity of 81.3%, and a specificity of 59.8%. An higher apoB/apoA1 ratio is associated with ICAS in ischemic stroke patients. Show less
📄 PDF DOI: 10.1038/s41598-025-97625-9
APOB
Lan Yang, Jinghua Yang, Hong Zhang +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. H Show more
Despite the critical role of e-Health literacy (eHL) in modern healthcare, current research predominantly concentrates on conditions such as cancer and diabetes, as well as outpatient care settings. However, there remains a significant gap in studies specifically addressing the eHL needs of patients with maintenance hemodialysis (MHD). This study aims to explore the latent categories of eHL among MHD patients and its impact on health-promoting lifestyle (HPL). A survey was conducted using a convenience sampling method involving 500 MHD patients from three tertiary hospitals in Baoding. Data were analyzed using latent profile analysis (LPA) and a mixed regression model. This study showed that MHD patients could be classified into low (23.17%), middle (49.78%), and high (27.05%) eHL groups, with the three-class model showing optimal fit (AIC = 2321.213, BIC = 2271.168, entropy = 0.967). MHD Patients in the high literacy group scored significantly higher in all dimensions of e-HL and overall HPL (119.58 ± 13.86) compared to those in the low literacy group (91.82 ± 11.73) (all The findings suggest a heterogeneous stratification of eHL among MHD patients, closely linked to HPL. Stratified intervention strategies should be developed for different patient groups to potentially improve their health behaviors. The study provides evidence-based support for personalized health management. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1630350
LPA
Fang Zhao, Guiying Chen, Jianfeng Pan +4 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Lung squamous cell carcinoma (LUSC) is a highly aggressive malignancy with limited targeted therapies and poor clinical outcomes. Ferroptosis, an iron-dependent form of regulated cell death, plays a c Show more
Lung squamous cell carcinoma (LUSC) is a highly aggressive malignancy with limited targeted therapies and poor clinical outcomes. Ferroptosis, an iron-dependent form of regulated cell death, plays a crucial role in tumor progression, metabolic reprogramming, and immune modulation. Increasing evidence suggests that dysregulation of ferroptosis contributes to therapeutic resistance and immune escape in various cancers. MYO19, a mitochondrial trafficking protein, has recently been implicated in oxidative stress and metabolic control, but its role in ferroptosis and tumor immunity remains unclear. Meanwhile, microRNAs (miRNAs) are recognized as key post-transcriptional regulators in cancer biology. Among them, hsa-miR-520a-3p has been reported to exhibit tumor-suppressive functions in several malignancies. However, the interplay between hsa-miR-520a-3p and MYO19, and their potential involvement in ferroptosis regulation and immune modulation in LUSC, has not been systematically investigated. Data were collected from TCGA, UCSC XENA, ENCORI, HPA, and UALCAN public database. Differential expression, prognostic, correlation analyses and miRNA analyses were performed using bioinformatics tools including TIMER, TISIDB, Kaplan-Meier Plotter, and ENCORI. Ferroptosis-related analysis utilized Ze-Xian Liu's dataset. Functional assays, including CCK-8 viability, Transwell migration, and MDA/GSH measurements, were performed in NCI-H226 and NCI-H2170 cells after transfection with miR-520a-3p mimics/inhibitors or MYO19 knockdown/overexpression constructs. Ferroptosis sensitivity was further tested under RSL3 treatment, and ferroptosis protein markers as well as rescue experiments were analyzed by Western blotting. The result revealed that MYO19 was significantly upregulated in multiple tumor types and correlated with unfavorable prognosis. Especially in LUSC, elevated MYO19 expression was associated with advanced stage, reduced immune infiltration, and enrichment of ferroptosis-resistant transcriptional programs, whereas hsa-miR-520a-3p showed opposite patterns. Overexpression of hsa-miR-520a-3p in NCI-H226 and NCI-H2170 cells increased lipid peroxidation (MDA increased), reduced intracellular GSH, and enhanced RSL3-induced cytotoxicity, indicative of ferroptosis activation. Conversely, MYO19 knockdown elevated ACSL4 and reduced SLC7A11, changes that were partially reversed by MYO19 re-expression. These findings suggest that the hsa-miR-520a-3p/MYO19 axis is associated with ferroptosis susceptibility and may influence the immunosuppressive tumor microenvironment. Show less
no PDF DOI: 10.3389/fonc.2025.1727301
MYO19
Hongqin Li, Rong Xu, Liquan Xie +3 more · 2025 · Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research · SAGE Publications · added 2026-04-24
Bushen Huoxue Acupuncture shows potential in treating neurodegenerative diseases, but its mechanisms remain incompletely understood. Using the senescence-accelerated mouse-prone 8 (SAMP8) mouse model, Show more
Bushen Huoxue Acupuncture shows potential in treating neurodegenerative diseases, but its mechanisms remain incompletely understood. Using the senescence-accelerated mouse-prone 8 (SAMP8) mouse model, we assessed cognitive function via the Morris water maze test, hippocampal neuronal apoptosis with terminal deoxynucleotidyl transferase dUTP nick end labeling staining, and microglial activation through immunohistochemistry. Serum levels of inflammatory cytokines [tumor necrosis factor-alpha, interleukin (IL)-1β, and IL-6] were quantified by enzyme-linked immunosorbent assay. The expression of SIRT2 pathway-related proteins, along with Aβ deposition, was analyzed using Western blotting, immunohistochemistry, and immunofluorescence. The results demonstrated that Bushen Huoxue Acupuncture improved cognitive function in SAMP8 mice, reducing hippocampal neuronal apoptosis and decreasing serum levels of pro-inflammatory cytokines. Additionally, it reduced the levels of Aβ42, a more aggregation-prone and toxic Aβ subtype, in both hippocampal tissues and serum, as well as the number of CD68-positive cells in hippocampal tissues, suggesting the inhibition of amyloid pathology and neuroinflammatory. The treatment also downregulated SIRT2, BACE1, and APP-CTF while increasing RTN4B expression. Notably, Bushen Huoxue Acupuncture outperformed non-acupoint acupuncture in enhancing cognitive function and reducing inflammation. Our findings indicate that Bushen Huoxue Acupuncture alleviates cognitive deficits and neuroinflammation by suppressing the SIRT2-mediated RTN4B/BACE1 pathway, highlighting acupuncture as a promising therapy for neurodegenerative diseases. Show less
no PDF DOI: 10.1177/10799907251391519
BACE1
Ruibing Li, Jinyang Wang, Jianan Wang +7 more · 2025 · Journal of inflammation research · added 2026-04-24
Neuromyelitis optica spectrum disorder (NMOSD) is a group of immune-mediated disorders that often lead to severe disability. The diagnosis and monitoring of NMOSD can be challenging, particularly in s Show more
Neuromyelitis optica spectrum disorder (NMOSD) is a group of immune-mediated disorders that often lead to severe disability. The diagnosis and monitoring of NMOSD can be challenging, particularly in seronegative cases, highlighting the need for reliable biomarkers to enhance clinical management. This study aimed to identify serum lipid biomarkers for the diagnosis and monitoring of NMOSD and to assess their potential to improve clinical decision-making. We conducted a comprehensive serum proteomic analysis in a discovery cohort of NMOSD patients and controls to identify lipid-related proteins associated with NMOSD. Subsequently, we validated the candidate biomarkers in the retrospective cohort and developed diagnostic models using a random forest algorithm. The association between these lipid biomarkers and disease activity was further evaluated in longitudinal analysis. Our analysis identified a panel of serum lipid-related biomarkers that demonstrated significant differences between NMOSD patients and controls. The diagnostic models achieved the impressive accuracy of 72% for the full NMOSD spectrum, 72% for AQP4-IgG+ NMOSD, and 68% for double seronegative NMOSD. Importantly, these biomarkers showed a correlation with disease activity, with levels changing from relapse to remission. Additionally, a combination of these lipid biomarkers was found to predict relapse with the AUC of 0.861. A user-friendly smartphone application was developed to facilitate the straightforward "input-index, output-answer" screening process, enhancing both clinical decision-making and patient care. The diagnostic model based on the serum lipid-related indexes (TC, TG, LDL, HDL, ApoA1, and ApoB) may be the useful tool for NMOSD in diagnosis and monitoring of disease stage, thereby improving the treatment outcome for patients. Future studies should focus on integrating these biomarkers into routine clinical practice to realize their full potential in enhancing NMOSD management. Show less
📄 PDF DOI: 10.2147/JIR.S496018
APOB
Xiaolin Zeng, Yuni Long, Gang Li +6 more · 2025 · Journal of cellular physiology · Wiley · added 2026-04-24
Excessive inflammation is a capital cause of scar formation and inflammation microenvironment that result in challenge of axonal regeneration after spinal cord injury (SCI). Macrophages and astrocytes Show more
Excessive inflammation is a capital cause of scar formation and inflammation microenvironment that result in challenge of axonal regeneration after spinal cord injury (SCI). Macrophages and astrocytes play important roles in the inflammatory response. Tip cells, a critical endothelial sub-population, play pivotal roles in post-injury vascular regeneration. Nevertheless, their characteristics in SCI remain poorly documented. This study based on single cell RNA sequencing (scRNA-seq) and in vitro experiment, investigates the effects of tip cells on astrocytes and macrophages. For astrocytes, tip cells can recruit astrocytes to migrant, contribute to the formation of fence-like structure of astrocytes, finally inhibit the diffusion of inflammation via the Angptl4-Sdc4 ligand-receptor pathway. For macrophages, similarly through the Angptl4-Sdc4 ligand-receptor pathway, tip cells can promote macrophages to polarize more toward the M2 phenotype and inhibit their polarization toward M1 phenotype, thus alleviate the inflammatory response. Tip cells after SCI exhibit conserved ribosomal protein expression, implicating ribosome-dependent signaling in their function. These finding highlight the critical role of tip cells in microenvironment after SCI, offering a potential treatment target for SCI. Show less
no PDF DOI: 10.1002/jcp.70088
ANGPTL4
Chongyang Cai, Leipeng Li, Xiaohuan Lv +12 more · 2025 · Nature communications · Nature · added 2026-04-24
Lanthanides-doped luminescent materials have gathered considerable attention due to their application potential in stress sensing, lighting and display, anti-counterfeiting technology and so forth. Ho Show more
Lanthanides-doped luminescent materials have gathered considerable attention due to their application potential in stress sensing, lighting and display, anti-counterfeiting technology and so forth. However, existing materials mainly cover the 380-1540 nm range, with slight extension to the UV region, impeding their applications in solar-blind imaging, background-free tracking, concealed communication, etc. To address this challenge, here we propose guidelines for far-UVC (200-230 nm) optical design. Accordingly, we achieve multi-stimulated far-UVC luminescence at ~222 nm in Pr Show less
📄 PDF DOI: 10.1038/s41467-025-61522-6
LPL
Yingying Qiu, Xinjun Wei, Jian Cao +9 more · 2025 · Reproductive sciences (Thousand Oaks, Calif.) · Springer · added 2026-04-24
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver Show more
Adenomyosis (AM), a gynecological disorder that severely affects female reproductive health. AM-associated macrophage (AAM) polarization-induced epithelial-mesenchymal transition (EMT) is a key driver of AM progression. In this study, we investigated the role and underlying mechanisms of endometrial mesenchymal stem cell (eMSC)-derived exosomes in regulating AAM polarization and the subsequent EMT of endometrial epithelial cells (EECs). In vitro coculture studies revealed that AM eutopic eMSCs markedly induced M2 macrophage polarization via exosomes and promoted EMT of EECs. Differentially expressed microRNAs (DE-miRNAs) between exosomes derived from normal eMSCs (N-eMSCs) and AM eutopic eMSCs (A-eMSCs) were identified using miRNA sequencing and miR-4669 was found to be the most significantly upregulated miRNA. Internalization of exosomal miR-4669 by macrophages induced their polarization toward the M2 phenotype and promoted the EMT of EECs. Mechanistic analysis using luciferase assay, mRNA sequencing, and rescue experiments revealed that miR-4669 induced M2 macrophage polarization via downregulation of DUSP6 and activation of MAPK/ERK signaling. The polarized M2 macrophages promoted the EMT of ISK cells via TGF-β1 secretion. In an AM xenograft mouse model, miR-4669 depletion inhibited AM progression by targeting the DUSP6/ERK1/2 pathway in macrophages. Overall, AM A-eMSC-derived exosomal miR-4669 facilitates M2 macrophage polarization by targeting the DUSP6/ERK signaling pathway, thereby promoting EMT of EECs via TGF-β1 secretion. These findings open avenues for developing novel preventive and therapeutic strategies for AM. Show less
📄 PDF DOI: 10.1007/s43032-025-01944-1
DUSP6
Xinyue Yang, Shufen Li, Yuqing Feng +3 more · 2025 · Carbohydrate polymers · Elsevier · added 2026-04-24
Metabolic associated fatty liver disease (MAFLD) is a globally recognized chronic metabolic disorder characterized by lipid metabolism abnormalities. Accumulating evidence indicates that exopolysaccha Show more
Metabolic associated fatty liver disease (MAFLD) is a globally recognized chronic metabolic disorder characterized by lipid metabolism abnormalities. Accumulating evidence indicates that exopolysaccharides (EPS) could modulate the gut microbiota structure and function to prevent and treat MAFLD. Herein, a novel EPS designated BVP1 was isolated from Bacillus velezensis CGMCC 24752. Structural analysis revealed that BVP1 is a neutral α-mannan consisting of a backbone of 1,2,6-linked α-D-Manp, with branches composed of T-linked α-D-Manp, 1,2-linked α-D-Manp, and 1,3-linked α-D-Manp. Animal experiments showed that BVP1 significantly alleviated hepatic steatosis, liver injury and inflammation, and enhanced antioxidant activity in MAFLD mice. Single-nucleus RNA sequencing analysis revealed that BVP1 could restore HFD-induced imbalances in liver sinusoidal endothelial cells, hepatic stellate cells, macrophages and Kupffer cells by upregulating the expression of the lipid degradation gene Cps1 and downregulating the expression of the lipid synthesis gene Acsl1 in these cell subpopulations. Interestingly, BVP1 reshaped the gut microbiota and fecal metabolite profile by enriching beneficial bacteria and associated metabolites including salicylic acid, spermidine, and 4-hydroxyphenyl acetate. Fecal microbiota transplantation experiments verified that the anti-MAFLD effects are mediated by the BVP1-modified gut microbiota. Our findings highlight the potential of BVP1 as a promising therapeutic agent for MAFLD treatment. Show less
no PDF DOI: 10.1016/j.carbpol.2025.124150
CPS1
Tao Geng, Mengwei Feng, Kaiyan Wang +11 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
The uptake of modified lipoproteins by macrophages to form foam cells is a crucial step in atherosclerosis (AS) development. N7-methylguanosine (m7G) is frequently methylated internally in eukaryotic Show more
The uptake of modified lipoproteins by macrophages to form foam cells is a crucial step in atherosclerosis (AS) development. N7-methylguanosine (m7G) is frequently methylated internally in eukaryotic RNA transcripts and plays a crucial role in various processes. This study aimed to investigate the m7G RNA methylation profile in AS. We employed high-throughput sequencing to analyze the m7G methylome in foam cells induced by ox-LDL, using an in vitro AS model. Then, m7G-seq, RNA-seq, bioinformatic analysis, cell biological analyses, followed by qRT-PCR were performed. Additionally, the roles of SCARB2 and RASSF8 were investigated in an in vivo AS mouse model, and cells with SCARB2/RASSF8 overexpression/knockdown. In vitro and in vivo oil red O staining confirmed the successful establishment of the atherosclerotic foam cell and mouse models. We identified 1197 m7G peaks and 430 differentially expressed mRNAs during foam cell formation. Bioinformatics analyses revealed different m7G peaks associated with the gonadotropin-releasing hormone (GnRH) signaling pathway, cytoskeleton-dependent intracellular transport, and mitochondrial organization, regulating the processes of macrophage foaminess. Moreover, 28 key differentially expressed methylated genes were identified. m7G methyltransferases (WDR4, METTL1, WBSCR22) were upregulated in the AS cell model, and m7G modification genes (SCARB2 and RASSF8) associated with pathological processes were confirmed. Immunofluorescence staining showed that RASSF8 and SCARB2 were both expressed in AS mice plaque tissues. Finally, RASSF8/SCARB2 overexpression could promote apoptosis and lipid accumulation of ox-LDL-induced RAW264.7 cells. An m7G transcriptome-wide map of AS in vitro was created, and the differentially m7G methylated genes SCARB2 and RASSF8 may be crucial in macrophage foaminess. Our findings offer novel insights into the underlying mechanisms and potential treatments for AS. Show less
no PDF DOI: 10.1096/fj.202501027RR
APOE
Jingjing Guo, Haifan Qiu, Jianping Wang +3 more · 2025 · Frontiers in medicine · Frontiers · added 2026-04-24
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregn Show more
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregnancy women and 317 healthy non-pregnant women. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), lipoprotein (a) [Lp(a)], and hypersensitive C-reactive protein (hs-CRP) were measured in both groups. The mean and standard deviation of each index were calculated to establish the reference range of normal serum lipid levels in pregnant women in mid-to-late pregnancy. The associations between serum lipid levels and perinatal outcomes were assessed statistically. There were no significant differences in age, pregnancy, or parity between the adverse outcome and normal delivery groups, but the caesarean section rate was significantly higher in the adverse outcome group. The levels of hs-CRP, TG, TC, HDL-C, LDL-C, and ApoA1 were significantly higher in the adverse outcome group. Elevated hs-CRP, TG, and HDL-C levels were risk factors for adverse pregnancy outcomes. According to the receiver operating characteristic curve, the optimal threshold of the combined diagnosis of these three indicators to predict adverse pregnancy outcomes was 0.534, and the area under the curve was 0.822. The establishment of lipid reference intervals in the second and third trimesters of pregnancy can effectively evaluate lipid metabolism in pregnant women, and the measurement of lipid metabolism in pregnant women is helpful in predicting adverse pregnancy outcomes. Show less
📄 PDF DOI: 10.3389/fmed.2025.1530525
APOB