👤 J T 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, Guobin Li, Hong-Tao Li, Enhong 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, 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, Peilin Li, Ran Li, X Y 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, Shisheng Li, Shengxu Li, Sai Li, Guangwen Li, Xiuli Li, Hua Li, Yulong Li, Dongmei 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, You Li, Dongfeng Li, Xueyang Li, Xuelin Li, Caiyu Li, Fa-Hui Li, Zhen-Yuan Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Bao Li, Shiyu Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Mingxu Li, Chen-Xi Li, Panlong Li, Dejun Li, Changwei Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Jinlin Li, Xiaoqing Li, Linke Li, C Y Li, Shuaicheng Li, Thomas Li, Siting Li, Xuebiao Li, Yingyi Li, Yongnan Li, Maolin Li, Jiyang Li, Jinchen Li, Jin-Ping Li, Zhongxuan Li, Xuewen Li, R Li, Xianlong Li, Linting Li, Aixin Li, Zhong-Xin Li, Xuening Li, Enhao Li, Guang Li, Xiaoming Li, Shengliang Li, Yongli Li, Z-H Li, Baohong Li, Hujie Li, Yue-Ming Li, Shuyuan Li, Zhaohan Li, L Li, Yuanmei Li, Alexander Li, Yanwu Li, Hualing Li, Wen-juan Li, Sibing Li, Xining Li, Qinghe Li, Pilong Li, Yun-Peng Li, Zonghua Li, C X Li, Huanan Li, Jingya Li, Liqin Li, Youjun Li, Zheng-Dao Li, Miao X Li, Zhenshu Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wei Li, Wen-Ying Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Ming Li, Kangli Li, Wenbo Li, Runwen Li, Side Li, Yarong Li, Timmy Li, S E Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Chuan-Hai Li, Lingxi Li, Jiezhen Li, Qiuya 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, 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, 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, Ya-Ting Li, Wan Jie Li, Dongbiao Li, Aimin Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, Peiyun Li, Xiuqi Li, L-Y Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Yuxiu Li, Tian Li, YiPing Li, Beibei Li, 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, Chiyang Li, Chunlan Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Jing Li, Xiangyun Li, Si Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Dengke Li, Zijing Li, Yuchuan Li, Wentao 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, Zhenfei Li, Shupeng Li, Sha-Sha Li, Panyuan Li, Mengxuan Li, Gang Li, Ziyu Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, Huaping Li, Ji-Liang Li, C H Li, Bohua Li, Bing Li, Pei-Ying Li, Huihuang Li, Shaobin Li, Yunmin Li, Yanying Li, Gui Lin Li, Ronald Li, Chenrui Li, Shilun Li, Shi-Hong Li, Xinyu Li, John Zhong Li, Lujiao Li, Song-Chao Li, Chenghong Li, Dengfeng Li, Nianfu Li, Baohua Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Zhimei Li, Jiao Li, Jun-Cheng Li, Yimeng Li, Jingming Li, Jinxia Li, Chunting Li, De-Tao 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, Guangxiao Li, Fengxia Li, Peixin Li, Xueqin Li, Feng-Feng Li, Jialing Li, Zu-Ling Li, Xin Li, Yunjiu Li, Dayong Li, Zonghong 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, Ruobing Li, Yanxi Li, Wan-Xin Li, Xia Li, Meitao Li, Yongjing Li, Huayao Li, Ziqiang Li, Wen-Xi Li, Shenghao Li, Boxuan Li, Huixue 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, Jutang Li, Conglin 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, Xingye Li, Xiangjun Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Qingyang Li, Yuxi Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Zhaoping Li, Xingyu Li, Xiaolei Li, Zhenlu Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Cheung Li, Zhenhui Li, Zhenming Li, Xuelian Li, Chunjun Li, Shu-Fen Li, Changyan Li, Yinghua Li, Mulin Jun 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, Xiao-Li Li, Xiaoya Li, Shan Li, Shitao Li, Lijia Li, Zehan Li, Chunqiong Li, Huiliang Li, Junjun Li, Chenlong Li, Shujin Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Wenxi Li, Weining Li, Wu-Jun Li, Chang-hai Li, Bin-Kui Li, Yumao Li, Yuqiu Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Chia Li, Y X 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, Junxian Li, Zhihua Li, Keqing Li, Shuwen Li, Saijuan Li, Danxi 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, Le-Le Li, Yifeng Li, Huanqing Li, Ziwen Li, Yuhang Li, Yongqiu Li, Pu-Yu Li, Jianhua Li, Chanjuan Li, Nan-Nan 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, Liangji Li, Yaxuan Li, Yuchan Li, Tian-wang Li, Lixiang Li, Jiaxi Li, Yalin Li, Jin-Liang Li, Pei-Zhi Li, You Ran Li, Xiaoqiong Li, Guanyu Li, Jinlan Li, Yixiao Li, Huizi Li, Jianping Li, Kathy H Li, Yun-Lin Li, Yadong Li, Sujing Li, Yuhua Li, Xuri Li, Wenzhuo Li, Y Li, Deqiang Li, Caixia Li, Zipeng 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, Ziyang Li, Sitao 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, Anqi Li, Shuai Li, Bingsong Li, Xiaoju Li, Ting Li, Zhenyu Li, Xiaonan 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, Qian-Qian Li, Yuanheng Li, Chunxiao Li, Wenli Li, Shijun Li, Kuan Li, Mengze Li, Baoguang Li, Jie-Shou Li, Kaiwei Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, 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, JunBo Li, Xueying Li, Jun-Ru 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, Shihong Li, Ya-Pei Li, Rulin Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Wenjia Li, Min-Dian Li, Xiatian Li, Ding-Jian Li, Hongwei Li, Yangxue Li, Xiao-Qiang Li, Danni Li, Chengnan Li, Chuanyin Li, Min Li, Yiqiang Li, Pengyang Li, Zhenzhou Li, Kun-Xin Li, Xiawei Li, Binglan Li, Yutong Li, Zesong Li, Xiangpan Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Yinxiong Li, Boru 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, Huang Li, Shu-Fang Li, Qiusheng Li, Man Li, Juxue Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Nan Li, Gongda Li, 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, Suping Li, Long Shan Li, Yanze Li, Jason Li, Xiao-Feng Li, Monica M Li, Fengjuan Li, W Li, Xianlun Li, Qi Li, Hainan Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Fei Li, Xionghui Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Hongmei Li, Kang Li, Peilong Li, Yinghao Li, Xu-Wei Li, Mengsen Li, Lirong Li, Wenhong Li, Quanpeng Li, Audrey Li, Yijian Li, Yajiao Li, Guang Y Li, Xianyong Li, Qilan Li, Shilan Li, Qiuhong Li, Zongyun Li, Xiao-Yun Li, Guang-Li Li, Cheng-Lin Li, Bang-Yan Li, Enxiao Li, Jianrui Li, Yousheng Li, Wen-Ting Li, Guohua Li, Kezhen Li, Xingxing Li, Guoping Li, Ellen Li, A Li, Simin Li, Xue-Nan Li, Yijie Li, Weiguo Li, Xiaoying Li, Shengsheng Li, Suwei Li, Shuyu D Li, 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, Shihao Li, Yazhou Li, Jun-Ling Li, Caesar Z Li, Feng Li, Weiyang Li, Lang Li, Peihong Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Xinxiu Li, Kaibo Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Meng-Hua Li, Shaodan Li, Yongzheng Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Zheng Li, Donghe Li, Ming-Hao Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, 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, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zizhuo Li, Zhuorong Li, X-H Li, Lan-Juan Li, Dong Sheng Li, Xianrui Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Xiaoman Li, Bing-Heng Li, Huanqiu Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Jinhui Li, Zhifei Li, Ying Li, Jianlin Li, Yanshu Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Longyu Li, Jinku Li, Guiying Li, X B Li, Cuiling Li, Changgui Li, Zhisheng Li, Xuekun Li, Yuguang Li, Wenke Li, Jianguo Li, Jiayi Li, En Li, Ximei Li, Shaoyong Li, Peihua Li, Kai-Wen Li, Suwen Li, Chang-Ping Li, Guangda Li, Yixue Li, Guandu Li, Junfeng Li, Xin-Chang Li, Jieming Li, Kongdong Li, Yue-Ying Li, Chunhui Li, Peiyu Li, Tongyao Li, Lian Li, Linfeng Li, Yuzhe Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Xiaohua Li, Chang-Yan 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, Shujie Li, Jianyong Li, Guoxing Li, Zongchao Li, Yanbin Li, Shiliang Li, Jia Li, Haimin Li, Qinrui Li, Sheng-Qing Li, Yiming Li, Lingjie Li, Xiao-Tong Li, Yiwen Li, Tie Li, Baoqi Li, Leyao Li, Wei-Bo Li, Xiaoyi Li, Liyan Li, Xiao-Qin Li, Xinke Li, Xiaokun 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, Lipeng Li, Qinqin Li, Leilei Li, Defu Li, Ranchang Li, Lianyong Li, Amy Li, Zhou Li, Q Li, Haoyu Li, Xiaoyao Li, M-J Li, Jiao-Jiao Li, Rongling Li, Zhu Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Guangqiang Li, Jian'an Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Yu-I Li, Shunhua Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Ziqi Li, Shen Li, Tianjiao Li, Gui-Rong Li, Shufen Li, Yunfeng Li, Yunpeng Li, Yueqi Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Pinghua Li, Xu Li, Shi-Fang Li, Shude Li, Yaxiong Li, Zhibin Li, Zhenli Li, Qing-Fang Li, Rosa J W Li, Yunxiao Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, Zhi Li, Zhankui Li, Zihai Li, Yue-Jia Li, Haihong Li, Peifen Li, Taixu Li, Mingzhou Li, Jiejing Li, Meng-Miao Li, Meiying Li, Chunlian Li, 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, Jialin Li, Wenjian Li, He Li, Bichun Li, Xiong Bing Li, Hanqin Li, Qingjie Li, Wen Lan Li, Guoge Li, Han Li, Wen-Wen Li, Keying Li, Yutang Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Hankun Li, Hongling Li, Xiangrui Li, 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, Nien Li, Yuefeng Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Lin Li, Jieshou Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, Hong-Lan Li, Mengqing Li, Ben-Shang Li, S L 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, Hongguo Li, Le Li, Chenxin Li, Yongsen Li, Qingyun Li, Pengyu Li, Si-Wei Li, Ai-Qin Li, Zichao Li, Manru Li, Caili Li, Yingxi Li, Yuqian Li, 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, H J Li, Yanping Li, Zhenyan Li, Ji Xia Li, Meizi Li, Yu-Ye Li, Qing-Wei Li, Qiang Li, Yuezheng Li, Hsiao-Hui Li, Zhengnan Li, L I Li, Jianglong Li, Hongzheng Li, Laiqing Li, Ningyang Li, Zhongxia Li, Guangquan Li, Xiaozheng Li, Hui-Jun Li, Shun Li, Guojun Li, Xuefei Li, Senlin Li, Hung Li, Jinping Li, Huili Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, P Li, Hongzhe K Li, Fulun Li, Xiao-Qiu Li, Jiejia Li, Yonghao Li, Mingli Li, Yehong Li, Zhihui Li, Yi-Yang Li, Fujun Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Ni Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Shichao Li, Gan Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Lihong Li, Chun Li, Jianan Li, Wenfang Li, Haixia Li, Xiangling Li, Sung-Chou Li, Lianhong Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Cheng Li, Kui Li, Zhao Li, Tiegang Li, Yunxu Li, Zhong Li, Shuang-Ling 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, 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, Yunlun Li, Rongxia Li, Suran Li, Yingqin Li, Yuanfang Li, Guoqin Li, Qiner Li, Huiqin Li, Shanhang Li, Jiafang Li, Chunlin Li, Han-Bing Li, Zongzhe Li, Yikang Li, Jisen Li, Si-Yuan Li, Caihong Li, Hongmin Li, Yajing Li, Peng Peng Li, Kenli Li, Guanglu Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Jian-Jun Li, Dongmin Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Jian-Shuang Li, Xinxin Li, You-Mei Li, Chenglan Li, Dazhi Li, Yubin Li, Yuhong Li, Beixu Li, Guiyuan Li, Di Li, Fengqiao Li, Suk-Yee Li, Yanbing Li, Jufang Li, Yuanyuan Li, Shengjie Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, Jun Li, Minghua Li, Xiyue Li, Tianchang Li, Zhuoran 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, Xiujuan Li, Yongsheng Li, Lingling Li, Chunxue Li, Yunlong Li, Xinhua Li, Jianshuang Li, Juanling Li, Minerva X Li, Xinbin Li, Alexander H Li, Xue-jing Li, Ding Li, Yuling Li, Wendeng Li, Yetian Li, Xianlin 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, Yushan Li, Ping'an Li, Juan Li, Huan Li, Weiping Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Weihai Li, Hsiao-Fen Li, Jiangan Li, Yu-Kun 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, Dandan Li, Yi-Ning Li, Yunan Li, Zechuan Li, Jiazhou Li, Sherly X Li, Zhijun 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, Yiyang Li, Jing-gao Li, Fengxiang Li, Xuejun Li, Nana Li, Shunwang Li, Chao Li, Yaqing Li, Jingui Li, Bingsheng Li, Yaqiao Li, Huamao Li, Xiankun Li, Jingke Li, Xiaowei Li, Tianyao Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Haoran Li, Hai-Yun 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, Zhengyao Li, Jin-Qiu Li, Qihua Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, Lin-Feng Li, Xutong Li, Ranwei Li, Kai Li, Ziqing Li, Keanning Li, Wei-Li Li, Yongjin Li, Shuangxiu Li, Chenhao Li, Ling Li, Weizu Li, Deming Li, Peiqin Li, Xiaodong Li, Nanxing Li, Qihang Li, Jianrong Li, Baoguo Li, Zhehui Li, Chenghao Li, Jiuyi Li, Chun-Xu Li, Luyao Li, Weike Li, Desheng Li, Zhixuan Li, Long-Yan Li, Chuanbao 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, S Li, Mengyuan Li, Wenqing Li, Wenhua Li, Caiyun Li, Congye Li, Xinrui Li, Dehai Li, Wensheng Li, Qingshang Li, Jiannan Li, Guanbin Li, Zhiyi Li, Hanbin 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, Jingfeng Li, Hai Li, Yanli Li, Zhi-Yuan Li, Kaibin Li, Yuan-Jing Li, Xuefeng Li, Xiaohu Li, Wenjie Li, Ruikai Li, Mengjuan Li, Xiao-Hong Li, Yinglin Li, Yaofu Li, Ren-Ke Li, Qiyong Li, Ruixi Li, Yi Li, Baosheng Li, Zhonglian Li, Yujun Li, Mian Li, Dalin Li, Lixi Li, Jin-Xiu Li, Kun Li, Qizhai Li, Jiwen Li, Pengju Li, Peifeng Li, Zhouhua Li, Ai-Jun Li, Qingqin S Li, Honglei Li, Guojin Li, Yueting Li, Xin-Yue Li, Dingchen Li, YaJie Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, Peining Li, Congjiao 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, Qun Li, Tianye Li, Cuiguang Li, Dongye Li, Zhen Li, F Li, Yuan Li, Chunhong Li, Mengling Li, Kunpeng Li, Jia-Da Li, Zhenghao Li, Chun-Bo Li, Zhantao Li, Baoqing Li, Pu Li, Xinle Li, Xingli Li, Bingkun Li, Nien-Chi Li, Wuguo Li, Tiewei Li, Bing-Hui Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Wei-Yang Li, Rong Li, Shikang Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Shishi Li, Hong-Lian Li, Bei-Bei Li, Haitong Li, Xiumei Li, Yuli Li, Melody M H Li, Ruibing Li, Qingfang Li, Peibo Li, Qibing Li, Huanjun Li, Heng Li, Wende Li, Chung-Hao Li, Liuzheng Li, Zhanjun Li, Yifei Li, Tianming Li, Chang-Sheng Li, Xiao-Na Li, Tianyou Li, Jipeng Li, Xidan Li, Yixing Li, Chengcheng Li, Yu-Jin Li, Baoting Li, Longxuan Li, Huiyou Li, Ka Wan Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Yu-Hao Li, Gui-xing Li, Niu Li, Shunle Li, Shilin 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, 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, Chunmei Li, Runbing Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Yanmin Li, Jingyi Li, Ji-Cheng 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, Yunze Li, Xu-Zhao Li, Yanzhong Li, Guohui Li, Kainan Li, Yongzhe Li, Qingfeng Li, Tianyi Li, Xiaoyan Li, Nanlong Li, Ping Li, Xu-Bo Li, Nien-Chen Li, Fangzhou Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Yuanchuang Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Hong-Yan Li, Shengbiao 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, Kaiyi Li, Junyi Li, Wenqun Li, Dongtao Li, Fengyuan Li, Guixia Li, Yinan Li, Aoxi Li, Chenxi Li, Zuo-Lin Li, Yuanjing Li, Zhengwei Li, Linqi Li, Xixi Li, Bingjue Li, Binghu Li, Yan-Chun Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Xiaotian Li, Zhenguang Li, Jia-Ru Li, Shuhui Li, Shu-Hong Li, Chun-Xiao Li, Pei-Qin Li, Shuyue Li, Mengying Li, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Duo Li, Yaxian Li, Dali Li, Zhiming Li, Xuemei Li, Hongxia Li, Yongting Li, Xueting Li, Danyang Li, Zhenjun Li, Tiandong Li, Ren Li, Lanfang Li, Hongye Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, Qiji Li, W J Li, Zhipeng Li, Zhijia Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu 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Chengjun Li, Keke Li, Jianbin Li, Chanyuan Li, Shiying Li, Jianxiong Li, Huaying Li, Ji Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Shaomin Li, Heying Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Jiahao Li, Hanxiao Li, Jiansheng Li, Shuying Li, Shibao Li, Xiaomei Li, Ruijin Li, Kunlong Li, Pengjie Li
articles
Zhaoyang Ye, Guangliang Bai, Ling Yang +7 more · 2025 · Microorganisms · MDPI · added 2026-04-24
Diabetes mellitus (DM) and tuberculosis (TB) are two global health challenges that significantly impact population health, with DM increasing susceptibility to TB infections. However, early risk predi Show more
Diabetes mellitus (DM) and tuberculosis (TB) are two global health challenges that significantly impact population health, with DM increasing susceptibility to TB infections. However, early risk prediction methods for DM patients complicated with TB (DM-TB) are lacking. This study mined transcriptome data of DM-TB patients from the GEO database (GSE181143 and GSE114192) and used differential analysis, weighted gene co-expression network analysis (WGCNA), intersecting immune databases, combined with ten machine learning algorithms, to identify immune biomarkers associated with DM-TB. An early alert model for DM-TB was constructed based on the identified core differentially expressed genes (DEGs) and validated through a prospective cohort study and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) for gene expression levels. Furthermore, we performed a detailed immune status analysis of DM-TB patients using the CIBERSORT algorithm. We identified 1090 DEGs associated with DM-TB and further pinpointed CETP (cholesteryl ester transfer protein) (AUC = 0.804, CI: 0.744-0.864), TYROBP (TYRO protein tyrosine kinase binding protein) (AUC = 0.810, CI: 0.752-0.867), and SECTM1 (secreted and transmembrane protein 1) (AUC = 0.811, CI: 0.757-0.864) as immune-related biomarkers for DM-TB patients. An early alert model was developed based on these three genes (AUC = 0.86, CI: 0.813-0.907), with a sensitivity of 0.80829 and a specificity of 0.75758 at a Youden index of 0.56587. External validation using the GSE114192 dataset showed an AUC of 0.901 (CI: 0.847-0.955). Population cohort research and RT-qPCR verified the expression levels of these three genes, demonstrating consistency with trends seen in the training set. KEGG enrichment analysis revealed that NF-κB and MAPK signaling pathways play crucial roles in the DM-TB pathogenic mechanism, and immune infiltration analysis showed significant suppression of certain adaptive immune cells and activation of inflammatory cells in DM-TB patients. This study identified three potential immune-related biomarkers for DM-TB, and the constructed risk assessment model demonstrated significant predictive efficiency, providing an early screening strategy for DM-TB. Show less
📄 PDF DOI: 10.3390/microorganisms13040919
CETP
Qianzhu Jiang, Huiting Li · 2025 · Journal of bioenergetics and biomembranes · Springer · added 2026-04-24
Myocardial fibrosis (MF) is a key pathological process driving heart failure, characterized by excessive extracellular matrix (ECM) deposition and impaired cardiac function. Although myocyte-specific Show more
Myocardial fibrosis (MF) is a key pathological process driving heart failure, characterized by excessive extracellular matrix (ECM) deposition and impaired cardiac function. Although myocyte-specific enhancer factor 2 A (MEF2A) is implicated in cardiac fibroblast activation, its role in MF remains unclear. We manipulated MEF2A expression in cardiac fibroblasts (CFs) through knockdown and overexpression, and assessed fibrosis markers, migration, and RhoA signaling. Binding of MEF2A to the Snail1 promoter was predicted using JASPAR and validated by chromatin immunoprecipitation (ChIP) and luciferase reporter assays. Rescue experiments with Snail1 overexpression and RhoA inhibition were performed. An angiotensin II (Ang II)-induced MF mouse model was used to evaluate cardiac function by echocardiography and to assess collagen deposition through picrosirius red (PSR) staining. MEF2A was significantly upregulated in Ang II-induced fibrotic hearts and CFs. MEF2A knockdown reduced α-SMA and Col1a1 expression, inhibited CF migration, and suppressed activation of the Snail1/RhoA/α-SMA pathway. ChIP and luciferase assays confirmed the direct binding of MEF2A to the Snail1 promoter. Inhibition of RhoA signaling reversed MEF2A-induced myofibroblast activation and migration. Rescue experiments showed that Snail1 overexpression restored the fibrotic phenotype suppressed by MEF2A knockdown. In vivo, MEF2A knockdown improved left ventricular function, reduced collagen deposition (PSR staining), and lowered heart weight/tibia length ratios. MEF2A promotes myocardial fibrosis by directly activating Snail1 and engages the RhoA/α-SMA pathway. Targeting MEF2A offers a promising therapeutic strategy to attenuate MF and improve heart function. Show less
no PDF DOI: 10.1007/s10863-025-10075-w
SNAI1
Yanping Wang, Xiaoru Ma, Zhixin Qiao +16 more · 2025 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, bu Show more
Astrocytes are key regulators of neuroinflammation in multiple sclerosis (MS). Electroacupuncture (EA), a safe and cost-effective adjuvant therapy, has shown benefits in neurodegenerative diseases, but its astrocyte-related mechanisms remain unclear. Here, we demonstrated that EA at ST36 alleviated blood-brain barrier (BBB) disruption and neuroinflammation during the peak period of experimental autoimmune encephalomyelitis (EAE). Additionally, EA at ST36 upregulated the expression of α-melanocyte-stimulating hormone (α-MSH) and its receptor melanocortin-4 receptor (MC4R) in spinal astrocytes. Pharmacological studies showed that MC4R agonist RO27-3225 mimicked the therapeutic effects of EA, whereas MC4R antagonist TCMCB07 weakened EA-mediated BBB protection and neuroinflammation suppression. Moreover, astrocyte-specific silencing of MC4R via adeno-associated virus (AAV) weakened EA-mediated BBB protection and neuroinflammation suppression. RNA-sequencing (RNA-seq) and western blot (WB) revealed that EA exerts neuroprotective effects by activating MC4R to inhibit MAPK and NF-κB signaling pathways. Moreover, in MC4R-overexpressing astrocytes, α-MSH and RO27-3225 reduced inflammation responses, while TCMCB07 reversed the effects by MAPK/NF-κB signaling pathways. Collectively, our findings identify astrocytic MC4R as a critical mediator of EA-driven neuroprotection by suppressing MAPK/NF-κB signaling, providing mechanistic insight and a promising therapeutic target for EAE and other neuroinflammatory disorders. Show less
📄 PDF DOI: 10.1186/s12974-025-03667-1
MC4R
Wei Li, Yu Cao, Chen Yu +5 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify sha Show more
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify shared diagnostic biomarkers and elucidate core pathways linking CHD and T2D pathogenesis. Integrated bioinformatics of CHD/T2D transcriptomes identified shared differentially expressed genes (DEGs) and co-expression modules via Weighted Gene Co-expression Network Analysis (WGCNA). Receiver operating characteristic (ROC) analysis selected CPD, GGCT, SUZ12, and ZMYM2 as top diagnostic biomarkers. These predictions were validated using C57BL/6 and ApoE Bioinformatics revealed 328 shared DEGs, with CPD, GGCT, SUZ12, and ZMYM2 showing high diagnostic efficacy. T2D mice exhibited persistent hyperglycemia. Aortic histopathology confirmed disease-specific changes: atherosclerotic plaques in CHD and vascular basement membrane thickening in T2D. Critically, all four biomarkers showed concurrent upregulation in diseased vessels at both protein (immunofluorescence, Western blot) and mRNA (RT-qPCR) levels. This study establishes CPD, GGCT, SUZ12, and ZMYM2 as shared CHD/T2D diagnostic biomarkers. Their validated co-upregulation highlights their dual-disease diagnostic and therapeutic potential. Show less
📄 PDF DOI: 10.3389/fgene.2025.1673303
APOE
Jingshu Li, Xuanyi Du, Rui Zhang +7 more · 2025 · Scientific reports · Nature · added 2026-04-24
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challen Show more
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challenging. Accurate prediction can improve advanced care planning and patient outcomes. This study aimed to develop and validate a machine learning (ML) model for predicting progression within 25 weeks (approximately six months) of ESRD in patients with stage 4 CKD. Electronic health records (EHRs) of patients with stage 4 CKD were analyzed. Nine ML models including Ridge regression (Ridge), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to predict short-term progression to ESRD within 25 weeks. The models were trained and externally validated using the data of 346 and 105 patients. Of the 451 patients with stage 4 CKD, 219 developed ESRD. Among the evaluated models, XGBoost demonstrated the best overall performance. In the internal validation, it achieved an area under the curve (AUC) of 0.93, an accuracy of 0.90, and an F1 score of 0.89. In the external validation, XGBoost maintained the highest AUC (0.85), accuracy (0.79), and F1 score (0.79), along with the highest average precision (0.89) and a low log-loss (0.48), indicating strong discriminative ability and good generalizability. The top predictive features included high-density lipoprotein cholesterol, Alb, Cys C, ApoB, FGB, Bun, Neutrophil, and Total cholesterol. This study demonstrated the feasibility of ML for assessing ESRD prognosis based on easily accessible clinical features. XGBoost demonstrated superior performance in both internal and external validation, suggesting its potential for future patient screening. Show less
📄 PDF DOI: 10.1038/s41598-025-23037-4
APOB
Jingru Wang, Bo Yao, Yutian Zhang +13 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strat Show more
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strategy to prevent atherosclerosis (AS), and targeted nanotherapeutics represent one approach for implementing this strategy. To this end, we designed immunosuppressive oligodeoxynucleotide A151 functionalized selenium nanoparticles with a spearhead LacNAc (LN-A151-SeNPs) that target macrophage-like VSMCs. Nano characterization showed that the uniformity and stability of nanoparticles were optimized by modification with LacNAc and A151, resulting in an average diameter of 88.90 ± 1.45 nm, Zeta potentials of -21.1 ± 1.5 mV, a A151:Se molar ratio of 1:60 and mass ratio of 1.68:1. The effects of LN-A151-SeNPs on inhibiting VSMCs phenotype switching and attenuation of AS were investigated using [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03925-7. Show less
📄 PDF DOI: 10.1186/s12951-025-03925-7
APOE
Hua-Xiong Zhang, Dilmurat Hamit, Qing Li +6 more · 2025 · Scientific reports · Nature · added 2026-04-24
Melatonin (MLT) can improve mitophagy, thereby ameliorating cognitive deficits in Alzheimer's disease (AD) patients. Hence, our research focused on the potential value of MLT-related genes (MRGs) in A Show more
Melatonin (MLT) can improve mitophagy, thereby ameliorating cognitive deficits in Alzheimer's disease (AD) patients. Hence, our research focused on the potential value of MLT-related genes (MRGs) in AD through bioinformatic analysis. First, the key cells in the single-cell dataset GSE138852 were screened out based on the proportion of annotated cells and Fisher's test between the AD and control groups. The differentially expressed genes (DEGs) in the key cell and GSE5281 datasets were identified, and the MRGs in GSE5281 were selected via weighted gene coexpression network analysis. After intersecting two sets of DEGs and MRGs, we performed Mendelian randomization analysis to identify the MRGs causally related to AD. Biomarkers were further ascertained through receiver operating characteristic curve (ROC) and expression analysis in GSE5281 and GSE48350. Furthermore, gene set enrichment analysis, immune infiltration analysis and correlation analysis with metabolic pathways were conducted, as well as construction of a regulator network and molecular docking. According to the Fisher test, oligodendrocytes were regarded as key cells due to their excellent abundance in the GSE138852 dataset, in which there were 281 DEGs between the AD and control groups. After overlapping with 3,490 DEGs and 550 MRGs in GSE5281, four genes were found to be causally related to AD, namely, G protein-coupled receptor, family C, group 5, member B (GPRC5B), Methyltransferase-like protein 7 A (METTL7A), NF-κB inhibitor alpha (NFKBIA) and RAS association domain family 4(RASSF4). Moreover, GPRC5B, NFKBIA and RASSF4 were deemed biomarkers, except for METTL7A, because of their indistinctive expression between the AD and control groups. Biomarkers might be involved in oxidative phosphorylation, adipogenesis and heme metabolism. Moreover, T helper type 17 cells, natural killer cells and CD56dim natural killer cells were significantly correlated with biomarkers. Transcription factors (GATA2, POU2F2, NFKB1, etc.) can regulate the expression of biomarkers. Finally, we discovered that all biomarkers could bind to MLT with a strong binding energy. Our study identified three novel biomarkers related to MLT for AD, namely, GPRC5B, NFKBIA and RASSF4, providing a novel approach for the investigation and treatment of AD patients. Show less
📄 PDF DOI: 10.1038/s41598-024-80755-x
GPRC5B
Yulong Fu, Canran Gao, Hailing Zhang +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection te Show more
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection techniques. Herein, a unique hydrogel incorporating extracellular matrix from fish swim bladder (FSB-ECM), which has distinct advantages over mammalian derived ECM, such as low antigenicity, bioactivity, and source safety, is developed. It consists of collagen, glycoproteins, and proteoglycans, including 13 proteins common in the myocardial matrix and three specific proteins: HSPG, Col12a1, and vWF. This hydrogel enhances cardiac cell adhesion and stretching while promoting angiogenesis and M2 macrophage polarization. In addition, its storage modulus (G') increases over time, reaching about 1000 Pa after 5 min, which facilitates transcatheter delivery and in situ gelling. Furthermore, this hydrogel provides sustained support for cardiac contractions, exhibiting superior longevity. In a rat model of ischemic heart failure, the ejection fraction significantly improves with FSB-ECM treatment, accompanied by increased angiogenesis, reduced inflammation, and decreased infarct size. Finally, RNA sequencing combined with in vitro assays identifies ANGPTL4 as a key protein involved in mediating the effects of FSB-ECM treatment. Overall, this new injectable hydrogel based on FSB-ECM is suitable for transcatheter delivery and possesses remarkable reparative capabilities for treating heart failure. Show less
📄 PDF DOI: 10.1002/advs.202500036
ANGPTL4
Zuojian Hu, Yingji Chen, Jielin Lei +11 more · 2025 · Cell death and differentiation · Nature · added 2026-04-24
SIRT7, one of the least studied members of the Sirtuins family, is an NAD
no PDF DOI: 10.1038/s41418-025-01490-y
BCKDK
Rongqing Li, Zikai Zhang, Xin Zhang +6 more · 2025 · BMC neurology · BioMed Central · added 2026-04-24
Symptom burden in primary brain tumor patients varies, emphasizing the need for comprehensive understanding to improve patient care. This study aims to identify distinct symptom clusters among brain t Show more
Symptom burden in primary brain tumor patients varies, emphasizing the need for comprehensive understanding to improve patient care. This study aims to identify distinct symptom clusters among brain tumor patients in Shanghai, China, using Latent Profile Analysis (LPA) to guide personalized diagnosis, treatment, and supportive care. A longitudinal study was conducted among 161 patients with primary brain tumors in Shanghai. Participants completed the MD Anderson Symptom Inventory Brain Tumor Module (MDASI-BT) at three intervals: the day of admission (T1), three days after surgery (T2), and two weeks after surgery (T3). Latent Profile Analysis (LPA) was used to identify subgroups with unique symptom patterns. Six distinct subgroups were identified (entropy = 0.964), ranging from low-burden to persistently severe patterns. Subgroup membership was partially associated with age, tumor grade, and diagnosis. These subgroups were: transient postoperative burden group, stable symptom with cognitive emergence group, distress-predominant, low burden group, elderly-high grade, persistently severe group, nausea-dominant recovery group, and distress-plus-nausea, younger urban group. Our findings reveal substantial heterogeneity in perioperative symptom experiences among brain tumor patients. Identifying subgroups with high and persistent symptom burden may help clinicians target interventions such as enhanced education, proactive monitoring, rehabilitation, psychological support, and antiemetic management. This subgroup-based approach may improve quality of life, reduce morbidity, and guide precision supportive care in neuro-oncology. Show less
📄 PDF DOI: 10.1186/s12883-025-04595-6
LPA
Anjing Liu, Roulan Jiang, Ruixi Li +16 more · 2025 · Research square · added 2026-04-24
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyon Show more
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyond mean-level associations. Methods for detecting distributional effects have been developed for eQTL analysis, yet applications have focused on method demonstrations rather than large-scale biological discovery. We comprehensively mapped quantile, variance, and interaction QTLs across 34 data-set from 22 molecular contexts in >2,300 human brain donors, revealing that 48.7% of quantile QTLs (qQTLs) exhibit context-dependent regulation invisible to linear models, with enrichment at phenotypic extremes and in cell-type-specific regulatory elements, chromatin accessibility regions, and long-range chromosomal contacts. qQTL variants explained additional trait heritability beyond linear QTLs for brain-related traits. At Alzheimer's disease (AD) risk loci, qQTL analysis revealed complex regulatory architecture including variance effects at Show less
📄 PDF DOI: 10.21203/rs.3.rs-8219833/v1
APOE
Hongzhi Li, Guangming Li, Xian Gao +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, c Show more
Cellular senescence is a hallmark for cancers, particularly in lung adenocarcinoma (LUAD). This study developed a risk model using senescence signature genes for LUAD patients. Based on the RNA-seq, clinical information and mutation data of LUAD patients collected from the TCGA and GEO database, we obtained 102 endotheliocyte senescence-related genes. The "ConsensusClusterPlus" R package was employed for unsupervised cluster analysis, and the "limma" was used for the differentially expressed gene (DEG) analysis. A prognosis model was created by univariate and multivariate Cox regression analysis combined with Lasso regression utilizing the "survival" and "glmnet" packages. KM survival and receiver operator characteristic curve analyses were conducted applying the "survival" and "timeROC" packages. "MCPcounter" package was used for immune infiltration analysis. Immunotherapy response analysis was performed based on the IMvigor210 and GSE78220 cohort, and drug sensitivity was predicted by the "pRRophetic" package. Cell invasion and migration were tested by carrying out Transwell and wound healing assays. According to the results, a total of 32 genes related to endotheliocyte senescence were screened to assign patients into C1 and C2 subtypes. The C2 subtype showed a significantly worse prognosis and an overall higher somatic mutation frequency, which was associated with increased activation of cancer pathways, including Myc_targets2 and angiogenesis. Then, based on the DEGs between the two subtypes, we constructed a five-gene RiskScore model with a strong classification effectiveness for short- and long-term OS prediction. High- and low-risk groups of LUAD patients were classified by the RiskScore. High-risk patients, characterized by lower immune infiltration, had poorer outcomes in both training and validation datasets. The RiskScore was associated with the immunotherapy response in LUAD. Finally, we found that potential drugs such as Cisplatin can benefit high-risk LUAD patients. In-vitro experiments demonstrated that silencing of Angiopoietin-like 4 (ANGPTL4), Gap Junction Protein Beta 3 (GJB3), Family with sequence similarity 83-member A (FAM83A), and Anillin (ANLN) reduced the number of invasive cells and the wound healing rate, while silencing of solute carrier family 34 member 2 (SLC34A2) had the opposite effect. This study, collectively speaking, developed a prognosis model with senescence signature genes to facilitate the diagnosis and treatment of LUAD. Show less
📄 PDF DOI: 10.1038/s41598-025-95551-4
ANGPTL4
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
Maoxia Fan, Na Li, Libin Huang +3 more · 2025 · Cardiovascular therapeutics · added 2026-04-24
📄 PDF DOI: 10.1155/cdr/5711316
ANGPTL4
Oriol Busquets, Hanqin Li, Khaja Mohieddin Syed +24 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Parkinson's disease (PD) is a neurodegenerative disorder caused by complex genetic and environmental factors. Genome-edited human pluripotent stem cells (hPSCs) offer a unique experimental platform to Show more
Parkinson's disease (PD) is a neurodegenerative disorder caused by complex genetic and environmental factors. Genome-edited human pluripotent stem cells (hPSCs) offer a unique experimental platform to advance our understanding of PD etiology by enabling the generation of disease-relevant cell types carrying patient mutations along with isogenic control cells. To facilitate this approach, we generated a collection of 65 human stem cell lines genetically engineered to harbor high risk or causal variants in genes associated with PD ( Show less
no PDF DOI: 10.1101/2024.02.12.579917
VPS13C
Yanyan Zhang, Muzi Li, Zongyun Li +6 more · 2025 · Biomolecules · MDPI · added 2026-04-24
This study evaluated the protective effects of naringin (NG) against intestinal injury in 7-day-old piglets infected with porcine epidemic diarrhea virus (PEDV). Eighteen piglets (Duroc × Landrace × L Show more
This study evaluated the protective effects of naringin (NG) against intestinal injury in 7-day-old piglets infected with porcine epidemic diarrhea virus (PEDV). Eighteen piglets (Duroc × Landrace × Large, body weight = 2.58 ± 0.05 kg) were divided into three treatment groups based on similar body weights and equal numbers of males and females: the blank control group (CON group), the PEDV infection group (PEDV group), and the NG intervention + PEDV infection group (NG + PEDV group) ( Show less
📄 PDF DOI: 10.3390/biom16010048
APOA4
Junyu Zhou, Yong Kwan Kim, Chen Li +1 more · 2025 · Computers in biology and medicine · Elsevier · added 2026-04-24
This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict na Show more
This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential in Alzheimer's disease (AD) treatment. The NCs were identified based on activity related to seven AD-specific genes, including acetylcholinesterase (AChE), amyloid precursor protein (APP), beta-secretase 1 (BACE1), and presenilin-1 (PSEN1). We implemented a computational pipeline using SELFormer and deep learning techniques, conducted optimal clustering and quantitative structure-activity relationship (QSAR) analyses, and performed a uniform manifold approximation and projection (UMAP) to categorize compounds based on bioactivity levels. Molecular docking analysis was carried out on selected compounds. To validate the computational predictions, we conducted in vitro studies using nerve growth factor (NGF)-differentiated PC12 cells. Finally, we mapped the relationships between food sources containing the identified compounds and their target proteins. Optimal clustering analysis revealed five distinct groups of NCs, while QSAR analysis highlighted variations in molecular properties across clusters. The UMAP projection identified 17 highly active NCs (pIC This integrated computational and experimental approach offers a promising framework for identifying potential NCs for AD treatment. The results contribute to exploring effective therapeutic strategies against AD. Show less
no PDF DOI: 10.1016/j.compbiomed.2024.109523
BACE1
Mingxuan Guo, Huanxin Zhao, Nannan Song +5 more · 2025 · Fitoterapia · Elsevier · added 2026-04-24
Sepsis-associated acute lung injury (SA-ALI), a critical complication of sepsis, is characterized by immune dysregulation-induced pulmonary dysfunction. Shenmai Injection (SMI) is a standardized herba Show more
Sepsis-associated acute lung injury (SA-ALI), a critical complication of sepsis, is characterized by immune dysregulation-induced pulmonary dysfunction. Shenmai Injection (SMI) is a standardized herbal preparation consisting of Panax ginseng C.A.Mey (Hongshen) and Ophiopogon japonicus (Thunb.) Ker Gawl (Maidong), traditionally used for qi-replenishing, collapse-stabilizing, and lung-moistening therapy. Although clinically utilized in the management of SA-ALI, the specific mechanisms by which it acts against SA-ALI necessitate further investigation. The present study endeavors to comprehensively determine the therapeutic efficacy of SMI against SA-ALI through an integrated approach combining network pharmacology, metabolomics, metagenomic sequencing, and experimental validation. In this study, murine SA-ALI was established using lipopolysaccharide (LPS) and Poly(I:C). Results indicated that SMI administration significantly attenuated pulmonary inflammation, restored blood-gas barrier integrity, reduced serum pro-inflammatory cytokines and suppressed NF-κB pathway activation in SA-ALI mice. Network pharmacology elucidated the multi-targeted mechanism of SMI in modulating steroid hormone biosynthesis. Integrated metabolomics and target analysis revealed that ophiopogonin A/B and luteolin in SMI alleviates metabolic dysregulation by targeting key enzymes, including AKR1C3, HSD17B1/2, and SULT1E1. Metagenomic profiling demonstrated SMI-mediated gut microbiota remodeling, marked by suppression of pathogenic Chlamydiaceae (particularly Chlamydia abortus) and enrichment of commensal Lactobacillaceae. Correlation analysis showed that intestinal androstenedione and androsterone levels during SMI treatment recovery were negatively correlated with Chlamydia abortus abundance. In conclusion, SMI enhances the recovery from sepsis-associated SA-ALI by dual modulation of gut microbial ecology and host metabolic homeostasis, thereby establishing its potential as a multi-mechanistic therapeutic candidate for sepsis-related organ injury. Show less
no PDF DOI: 10.1016/j.fitote.2025.106935
HSD17B12
Binbin Gong, Xike Mao, Guoxiang Li +4 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
The objective of this study was to assess the correlation between the ApoB/ApoA ratio and the recurrence of kidney stones in a Chinese adult population. We collected electronic records of patients wit Show more
The objective of this study was to assess the correlation between the ApoB/ApoA ratio and the recurrence of kidney stones in a Chinese adult population. We collected electronic records of patients with kidney stones who underwent surgical treatment at our hospital from March 2016 to March 2022. These patients were followed up and categorized into groups based on the recurrence of kidney stones. Parameters related to routine blood and biochemical tests, as well as the history of hypertension and diabetes mellitus, were gathered. Multiple imputation was applied for missing data. Subsequently, differences between the recurrence and non-recurrence groups were assessed using the chi-square test, independent samples t test, or Wilcoxon rank sum test. Logistic regression analysis, subgroup analysis, and propensity-matched analysis were conducted to evaluate the relationship between the ApoB/ApoA ratio and kidney stone recurrence. The study included a total of 923 participants aged > 18 years, among whom 296 experienced kidney stone recurrence during the follow-up period. An elevated ApoB/ApoA ratio was identified as a risk factor for kidney stone recurrence (adjusted OR = 2.48, 95% CI 1.04, 5.92). Propensity-matched analyses further supported the association, showing that elevated ApoB/ApoA ratios were linked to a higher risk of renal stone recurrence (OR = 3.37, 95% CI 1.24-9.17). The dose-response curve illustrated a positive linear correlation between the ApoB/ApoA ratio and the risk of kidney stone recurrence. Increased ApoB/ApoA ratios are positively correlated with the risk of kidney stone recurrence. This association remains significant, although a causal relationship cannot be definitively established. Show less
📄 PDF DOI: 10.1186/s40001-025-03396-4
APOB
Zhuan Gao, Yue Li, Yu-Jie Yang +4 more · 2025 · Surgical and radiologic anatomy : SRA · Springer · added 2026-04-24
To clarify the anatomical characteristics of the lateral plantar ligament (LPL) of the transverse metatarsal arch (TMA) in the population of southwest Shandong Province, so as to complement the anatom Show more
To clarify the anatomical characteristics of the lateral plantar ligament (LPL) of the transverse metatarsal arch (TMA) in the population of southwest Shandong Province, so as to complement the anatomical structures of the midfoot and Lisfranc joint complexes. A total of 100 adult lower limbs were dissected and the types of LPL were divided according to their insertions, among them, 63 were (63%) and 37 were female (37%); 50 were on the left side (50%) and 50 were on the right side (50%). The fiber bundle length, origin width, insertion width, and thickness of the LPL were measured. (1) According to the insertions of the LPL, they were divided into: ① Type I, the LPL was inserted at the base of the second metatarsal (M2) in 47 cases; ② Type II, the LPL was inserted at the base of M2 and fused with tibialis posterior tendon (TPT) in 16 cases; ③ Type III, the LPL was absent in 16 cases; ④ Type IV, the LPL was inserted at TPT in 6 cases; ⑤ Type V, the LPL was inserted at the intermediate cuneiform (IC) in 1 case; ⑥ Type VI, bifid LPL with one bundle inserted at the base of M2, and the other bundle inserted at the medial cuneiform (MC) in 4 cases; ⑦ Type VII, two bundles of LPL inserted at the base of M2 in 8 cases; ⑧ Type VIII, the LPL consisted of 3 bundles; the distal, middle and proximal bundles was inserted at the base of M2, the TPT and the lateral side of navicular bone in 2 cases, respectively. (2) There was a statistical significance in the length of LPL between male (31.62 ± 3.83) mm and female (28.07 ± 3.46) mm (t=-3.050, P = 0.003). There was no statistical significance in the types of LPL between male and female (Z=-1.721, P > 0.05), and no statistical significance in the types between left and right sides (Z=-0.026, P > 0.05). According to our research, LPL originates from M5 and is divided into 8 types according to its insertion location, of which insertion at the base of M2 is the most common. In addition, we found that LPL has fibrous fusion with the long plantar ligament and the TPT, which may be involved in maintaining arch stability. The classification of LPL in this study is a supplement to the anatomical structure of the middle foot and Lisfranc joint complex, providing a new direction for the diagnosis and treatment of middle foot and arch injury in the future. Show less
📄 PDF DOI: 10.1007/s00276-025-03651-7
LPL
Shengfeng Deng, Guo Mu, Jun Li +3 more · 2025 · The journal of physiological sciences : JPS · Elsevier · added 2026-04-24
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, Show more
To investigate the mechanisms underlying sevoflurane-induced POCD, C57BL/6 J mice and SH-SY5Y cells were treated with sevoflurane for model establishment. After the treatment with sevoflurane, CCK-8, EdU and flow cytometry were employed to detect cell damage. The levels of N6-methyladenosine (m6A), METTL14 and DUSP6 were determined by qPCR and Western blot. The interaction between METTL14 and DUSP6 was analyzed using RIP-qPCR and Me-RIP methodologies. The cognitive function in mice were assessed by water maze test. After sevoflurane treatment, the cell viability, cell proliferation and METTL14 expression were markedly suppressed, while apoptosis was significantly enhanced. METTL14 overexpression elevated the levels of m6A and DUSP6, increased the binding level of METTL14 to DUSP6 mRNA, reducing damage to cells and cognitive dysfunction of mice. Knockdown of DUSP6 negated the beneficial effects observed with METTL14 overexpression. Sevoflurane induced POCD by regulating METTL14/DUSP6 through m6A methylation. Show less
📄 PDF DOI: 10.1016/j.jphyss.2025.100048
DUSP6
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
Tong Chen, Jiawei Zhou, Mengfan Li +9 more · 2025 · BMC genomics · BioMed Central · added 2026-04-24
Pork serves as a significant meat commodity, with intramuscular fat (IMF) content being a critical determinant of its quality. However, the epigenetic mechanism of porcine IMF deposition is still uncl Show more
Pork serves as a significant meat commodity, with intramuscular fat (IMF) content being a critical determinant of its quality. However, the epigenetic mechanism of porcine IMF deposition is still unclear. This study integrated proteomics and lactylation profiles from the longissimus thoracis (LT) muscles of pigs with extremely high (IMF_H) and extremely low (IMF_L) IMF content to clarify the association between lactylation and porcine fat deposition. Furthermore, an intramuscular preadipocyte induction and differentiation model was conducted to elucidate the changes in lactylation during adipocyte differentiation. Finally, the regulatory role of lactylation in adipocyte differentiation was explored by modulating lactate production during the induction and differentiation of preadipocytes. Proteomic analysis revealed significantly increased expression of key lipid metabolism related proteins (FASN, APOA4, FABP4, ACLY, PLIN1) in IMF_H pig muscle tissues compared with IMF_L tissues, along with substantial activation of lipid metabolism pathways. Lactylation profiling identified 95 differential lysine sites across 56 proteins, with most showing lower lactylation levels in the IMF_H group. The integrative omics analysis revealed differences in lactylation profiles in porcine LT tissues with varying efficiencies of IMF deposition, highlighted PGK1, PKM, and PYGM as central lactylation-modified proteins in porcine fat deposition regulation. Further in vitro study proved that lactate-mediated lactylation inhibited adipogenic differentiation of porcine intramuscular preadipocytes through PPARγ signaling pathway. This study clarified the changes in the lactylation profile in porcine LT tissues with varying efficiencies of IMF deposition, and demonstrated that lactate-mediated lactylation inhibits the PPARγ signaling pathway and the adipogenic differentiation of porcine intramuscular preadipocyte. This study provided a new insight to understanding the epigenetic regulation mechanisms of lipid deposition in pigs. Show less
📄 PDF DOI: 10.1186/s12864-025-12428-6
APOA4
Zhengliang Li, Xiaokai Chen, Juan Wang +6 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study inclu Show more
To investigate the risk factors associated with coronary heart disease (CHD) in patients with metabolic-associated fatty liver disease (MAFLD) and develop a nomogram prediction model. This study included 394 patients with MAFLD who underwent coronary angiography at The Affiliated Hospital of Qingdao University between December 2019 and December 2024. The study cohort was divided in a 7:3 ratio into training and validation sets comprising 277 and 117 cases, respectively. The training group was further divided into the MAFLD-only ( Of the 394 MAFLD cases, 313 had CHD-related complications. Of the 277 patients in the training set, 220 had CHD, and of the 117 patients in the validation set, 93 had CHD. LASSO regression analysis revealed that the following variables were associated with the risk of CHD: sex, lipoprotein(a) (Lp[a]), low-density lipoprotein cholesterol, white blood cell count (WBC), glycated triglyceride-glucose index (TyG), and atherosclerosis index (AIP). Multivariate logistic regression analysis revealed that sex, Lp(a), WBC, TyG, and AIP were independent risk factors for CHD in MAFLD cases. A nomogram was constructed and an ROC curve was plotted, based on which the optimal cutoff value was determined as 0.698. The area under the curve of the nomogram in the training and validation cohorts was 0.860 (95% CI = 0.807-0.913) and 0.843 (95% CI = 0.757-0.929), respectively. Calibration curves for CHD risk probability showed good agreement between the nomogram's predicted probabilities and the observed event rates. DCA demonstrated the net clinical benefit of the constructed nomogram. Sex, Lp(a), WBC, TyG, and AIP emerged as independent risk factors for CHD in patients with MAFLD and the nomogram prediction model constructed using these factors could effectively predict CHD occurrence. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1652321
LPA
Tao Yang, Xiaohu Hu, Fei Cao +15 more · 2025 · Nature · Nature · added 2026-04-24
The mammalian gut harbours trillions of commensal bacteria that interact with their hosts through various bioactive molecules
📄 PDF DOI: 10.1038/s41586-025-08990-4
APOB
Zhengyue Cao, Tiantian Wang, Fumin Tai +7 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Long noncoding RNAs (lncRNAs), non-protein-coding transcripts exceeding 200 nucleotides, are critical regulators of gene expression through chromatin remodeling, transcriptional modulation, and post-t Show more
Long noncoding RNAs (lncRNAs), non-protein-coding transcripts exceeding 200 nucleotides, are critical regulators of gene expression through chromatin remodeling, transcriptional modulation, and post-transcriptional modifications. While ionizing radiation (IR) induces cellular damage through direct DNA breaks, reactive oxygen species (ROS)-mediated oxidative stress, and bystander effects, the functional involvement of lncRNAs in the radiation response remains incompletely characterized. Here, through genome-wide CRISPR activation (CRISPRa) screening in non-small cell lung cancer (NSCLC) cells, we identified LOC401312 as a novel radiosensitizing lncRNA, the stable overexpression of which significantly enhanced IR sensitivity. Transcriptomic profiling revealed that LOC401312 transcriptionally upregulates carbamoyl-phosphate synthase 1 (CPS1), a mitochondrial enzyme involved in pyrimidine biosynthesis. Notably, CPS1 overexpression recapitulated the radiosensitization phenotype observed with LOC401312 activation. Mechanistic investigations revealed that CPS1 suppresses the phosphorylation of ATM kinase (Ser1981) protein, which is a key mediator of DNA damage checkpoint activation. This study established the LOC401312-CPS1-ATM axis as a previously unrecognized regulatory network governing radiation sensitivity, highlighting the potential of lncRNA-directed metabolic rewiring to impair DNA repair fidelity. Our findings not only expand the functional landscape of lncRNAs in DNA damage response but also provide a therapeutic rationale for targeting the LOC401312-CPS1 axis to improve radiotherapy efficacy in NSCLC. Show less
📄 PDF DOI: 10.3390/ijms26125865
CPS1
Jia Li, Deming Ren, Xiangxu Meng +4 more · 2025 · Virus research · Elsevier · added 2026-04-24
The genetic foundations underlying the observed disease resistance in certain indigenous pig breeds, notably the Min pigs of China, present a compelling underexplored subject of study. Exploring the m Show more
The genetic foundations underlying the observed disease resistance in certain indigenous pig breeds, notably the Min pigs of China, present a compelling underexplored subject of study. Exploring the mechanisms of disease resistance in these breeds could lay the groundwork for genetic improvements in pig immunity, potentially augmenting overall pig productivity. In this study, whole blood samples were collected from pre- and post- swine fever vaccinated Min and Large White pigs for transcriptome sequencing. The mRNA and lncRNA in both pig breeds were analyzed, and intra-group and inter-group comparisons were also conducted. The results indicated that a greater number of immune-related pathways such as the JAK-STAT and PI3K-AKT signaling were enriched in Min pigs. Furthermore, genes involved in inflammation and antiviral responses, including IL16, IL27, USP18, and DHX58, were upregulated in post-vaccination Min pigs compared to post-vaccination Large White pigs. This heightened immune responsiveness could contribute to the observed differences in disease resistance between Min pigs and Large White pigs. Show less
📄 PDF DOI: 10.1016/j.virusres.2025.199536
IL27
Nolan Priedigkeit, Beth Harrison, Robert Shue +27 more · 2025 · Clinical cancer research : an official journal of the American Association for Cancer Research · added 2026-04-24
Inflammatory breast cancer (IBC) is a rare and clinically distinct form of breast cancer associated with poor outcomes. The biological mechanisms driving IBC remain poorly understood, partly due to li Show more
Inflammatory breast cancer (IBC) is a rare and clinically distinct form of breast cancer associated with poor outcomes. The biological mechanisms driving IBC remain poorly understood, partly due to limited large-scale genomic studies that directly compare IBC with non-IBC cases. We conducted a retrospective analysis of 140 patients with IBC (68 primary tumors and 72 metastatic tumors) and 2,317 patients with non-IBC (700 primary tumors, 65 local recurrences, and 1,552 metastases). We compared clinicopathologic features, single-nucleotide variants, copy-number variants, tumor mutational burden, and exploratory survival outcomes between IBC and non-IBC tumors. The most frequent somatic alterations in IBC were detected in TP53 (72%), ERBB2 (32%), PIK3CA (24%), CCND1 (12%), MYC (9%), FGFR1 (8%), and GATA3 (8%). Multivariate logistic regression revealed a significant enrichment of TP53 single-nucleotide variants in IBC, particularly in HER2+ and hormone receptor-positive disease. Tumor mutational burden did not differ between IBC and non-IBC cases. In HER2+ disease, a pathway analysis revealed an enrichment of NOTCH pathway alterations. TP53, CCND1, and RB1 alterations were associated with poor outcomes in IBC. This study provides a comprehensive resource of somatic alterations in a large cohort of patients with metastatic IBC and non-IBC, highlighting genomic features associated with worse outcomes. Our findings reveal a significant enrichment of TP53 mutations, reinforcing its critical role in IBC pathogenesis. Few other distinct differences in IBC were observed, suggesting further investigations-beyond bulk sequencing of the somatic genome-are required to better understand the biology driving this aggressive disease. Show less
📄 PDF DOI: 10.1158/1078-0432.CCR-24-2081
FGFR1
Xue Li, Luping Liu, Li Jiang +7 more · 2025 · Journal of molecular cell biology · Oxford University Press · added 2026-04-24
📄 PDF DOI: 10.1093/jmcb/mjae053
IL27
Jun Teng, Chongwei Duan, Xinyi Zhang +9 more · 2025 · Journal of dairy science · added 2026-04-24
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation tr Show more
Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation traits is essential for understanding their genetic basis. In this study, we conducted single-trait and multitrait GWAS for 20 body conformation traits using imputed sequence data in 7,674 Chinese Holstein individuals and identified 27 QTL regions. Leveraging these QTL regions, we performed multitrait Bayesian fine-mapping to identify 30 independent credible sets of putative causal variants. Incorporating GWAS and cis-acting expression QTL data, Mendelian randomization was used to infer 153 putative causal gene-trait relationships. The previously reported genes, such as CCND2, TMTC2, and NRG3, were confirmed in our study. Of note, several novel candidate causal genes were also identified, such as C1R, RIMS1, SERPINB8, NETO2, TTYH3, TTC3, ANAPC4, and PSMD13. Our results provide new insights into the regulatory mechanisms of body conformation traits in cattle. Show less
no PDF DOI: 10.3168/jds.2025-26361
ANAPC4