👤 Jisen Li

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Also published as: Xiaocun Li, Jianyu Li, Xinzhi Li, Guanqiao Li, Zequn Li, Guang-Xi Li, Yubo Li, Bugao Li, Qingchao Li, Xikun Li, Hong-Tao Li, Guobin Li, Xihao Li, Rongqing Li, Chang-Da Li, Meng-Yue Li, DaZhuang Li, Shunqin Li, Jiajie Li, Yaqiong Li, Yuan-hao Li, Yongmei Li, X Y Li, Peilin Li, Ran Li, Chunshan Li, Yixiang Li, Guanglve Li, Ye Li, Zili Li, Yihao Li, Qing Run Li, Liling Li, Meng-Yang Li, Ziyun Li, Jun-Ying Li, Xinhai Li, Yongjiang Li, Wanru Li, Wenhao Li, Shisheng Li, Sai Li, Guangwen Li, Hua Li, Dongmei Li, Jiayang Li, Zunjiang Li, Minglong Li, Wenzhe Li, Zihan Li, Jin-Long Li, Hongxin Li, Caiyu Li, Fa-Hui Li, Guangpu Li, Teng Li, Wen-Jie Li, Hegen Li, Ang Li, Zhizong Li, Lu-Yun Li, Peng Li, Shiyu Li, Fang Li, Jiuke Li, Miyang Li, Mingxu Li, Chen-Xi Li, Panlong Li, Changwei Li, Biyu Li, Yaoqi Li, San-Feng Li, Jiaming Li, Jiyuan Li, Rongkai Li, Yani Li, Linke Li, C Y Li, Thomas Li, Siting Li, Yongnan Li, Jinchen Li, Jin-Ping Li, Xuewen Li, R Li, Xianlong Li, Aixin Li, Xuening Li, Guang Li, Xiaoming Li, Z-H Li, Yongli Li, Baohong Li, Shuyuan Li, L Li, Yuanmei Li, Yanwu Li, Hualing Li, Sibing Li, Xining Li, Qinghe Li, Zonghua Li, Liqin Li, Jingya Li, Youjun Li, Zheng-Dao Li, Zhenshu Li, Heng-Zhen Li, Yuhui Li, Wen-Ying Li, Wei Li, Shuanglong Li, Fei-feng Li, Letai Li, Kangli Li, Ming Li, Wenbo Li, Runwen Li, Yarong Li, Weidong Li, S E Li, Xin-Tao Li, Ruotong Li, Shuguang Li, Xiuzhen Li, Lingxi Li, Chuan-Hai Li, Tingting Li, Guanghua Li, Zhongyu Li, Zhen-Yu Li, Deyu Li, Hansen Li, Jinzhi Li, Yijing Li, Kaifeng Li, Wen-Xing Li, Qintong Li, Naishi Li, Xin-Ping Li, Han-Ni Li, Jiaying Li, Cui-lan Li, Ruonan Li, Jun-Jie Li, Shuhao Li, Ruitong Li, Suyan Li, Gen-Lin Li, Dianjie Li, Junhui Li, Ya-Jun Li, Xue Cheng Li, Ding-Biao Li, Xiying Li, Yansong Li, Weiyong Li, Xinyang Li, Cui Li, Xiaoyong Li, Y L Li, Xueyi Li, Jingxiang Li, Wenxue Li, Jianglin Li, Yingpu Li, Yan-Hua Li, Jing-Yao Li, Shawn Shun-Cheng Li, Xiao-Min Li, Wan Jie Li, Ya-Ting Li, Dongbiao Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Chunyi Li, Peiyun Li, Qinglan Li, Yue-Ting Li, Da Li, YiPing Li, Demin Li, Haipeng Li, Chuan Li, Ze-An Li, Jianmin Li, Minhui Li, Yu Li, Yiwei Li, Xiangzhe Li, Minglun Li, Xue-Min Li, Kenneth Kai Wang Li, Chunlan Li, Chiyang Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Jiaomei Li, Xiangyun Li, Jing Li, Yingshuo Li, Baixing Li, Dengke Li, Qingling Li, Rui-Han Li, Dong Li, Xiaoxia Li, Dezhi Li, Sheng-Jie Li, Ying-Qing Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Sha-Sha Li, Mengxuan Li, Ziyu Li, Gang Li, Panyuan Li, Hong-Wen Li, Xiaojuan Li, Dongnan Li, Huaiyuan Li, Ji-Liang Li, Huaping Li, C H Li, Bohua Li, Pei-Ying Li, Shaobin Li, Ronald Li, Shilun Li, Shi-Hong Li, John Zhong Li, Xinyu Li, Lujiao Li, Song-Chao Li, Chenghong Li, Baohua Li, Nianfu Li, Jun-Cheng Li, Yimeng Li, Chunting Li, Chien-Feng Li, Mei-Zhen Li, Zhengjie Li, Liwei Li, Yan-Yan Li, Huijun Li, Chengyun Li, Lijun Li, Hening Li, Fengxia Li, Jialing Li, Xin Li, Ningyan Li, Zhenghui Li, Ailing Li, Chaochen Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Wenjing Li, Jingshu Li, Han-Bo Li, Zengyang Li, Chunyan Li, Runzhen Li, Xi-Hai Li, Xuezhong Li, MengGe Li, Pei-Lin Li, Wan-Xin Li, Ruobing Li, Ning Li, Meitao Li, Xia Li, Ziqiang Li, Wen-Xi Li, Shenghao Li, Hehua Li, Yucheng Li, Dujuan Li, Yuying Li, Shaofei Li, Shaoguang Li, Min-Rui Li, Shuqiang Li, Dan C Li, Huashun Li, Ganggang Li, Haoqi Li, Handong Li, Yan-Nan Li, Xianglong Li, Jing-Jing Li, Songhan Li, Conglin Li, Qingli Li, Miao Li, Chenyu Li, Ke Li, Zhen-Hua Li, Chuan-Yun Li, Gaoyuan Li, Youming Li, Qingrun Li, Dong-Yun Li, Shuangfei Li, Fengfeng Li, Qinggang Li, Huixia Li, Xingye Li, Xiangjun Li, Huiying Li, Xingyu Li, Zhaoping Li, Wenying Li, Honghui Li, Cheung Li, Xuelian Li, Zhenming Li, Changyan Li, Mulin Jun Li, Shangjia Li, Jingjing Li, Suhong Li, Xinping Li, Siyu Li, Guangzhen Li, Xiangyan Li, Shiyun Li, Xiaoyu Li, Yaobo Li, Xuewang Li, Mei Li, Manjiang Li, Wan Li, Xiao-Li Li, Xiaoya Li, Shan Li, Shitao Li, Zehan Li, Lijia Li, Huiliang Li, Chunqiong Li, Junjun Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Wenxi Li, Chang-hai Li, Yuqiu Li, Xue-Yan Li, Yuan-Yuan Li, Xiang-Jun Li, Chia Li, Y X Li, Yunyun Li, Zhen-Jia Li, Qiuxuan Li, De-Jun Li, Keqing Li, Junxian Li, Shuwen Li, Lingjun Li, Deheng Li, Si-Xing Li, Yaodong Li, Shigang Li, Gao-Fei Li, Minle Li, Le-Le Li, Ziwen Li, Yongqiu Li, Pu-Yu Li, Nan-Nan Li, Lan-Lan Li, Hongming Li, Shuang Li, Wanting Li, Gong-Hua Li, Zhengyu Li, Weiguang Li, Guoqing Li, Xiaomeng Li, Yuanze Li, Yunqi Li, Yuandong Li, Changcheng Li, Shiyue Li, Hanbo Li, Yinggao Li, Dingshan Li, Linlin Li, Jin-Wei Li, Cheng-Tian Li, Yaxi Li, Wei-Ming Li, Ming-Han Li, Wenchao Li, Guangyan Li, Zhaosha Li, Xuesong Li, Chun-Quan Li, Yongzhen Li, Tao Li, Xiankai Li, Yaxuan Li, Tian-wang Li, Yuchan Li, Jiaxi Li, Yalin Li, Pei-Zhi Li, Guanyu Li, Jinlan Li, Huizi Li, Jianping Li, Yun-Lin Li, Yadong Li, Sujing Li, Wenzhuo Li, Xuri Li, Mengqiu Li, Yun Li, Ling-Ling Li, Chengwen Li, Shu-Feng Li, Haojing Li, Zhiyu Li, Ziyang Li, Yaochen Li, Qian Li, Bohao Li, Wenyang Li, Wenming Li, Mingxuan Li, Bingsong Li, Anqi Li, Shuai Li, Xiaoju Li, Na Li, Huibo Li, Chuanfang Li, Pengsong Li, Ruotian Li, Chunya Li, En-Min Li, Zong-Xue Li, Yan Ning Li, Honglin Li, Min-jun Li, Jinhua Li, Qian-Qian Li, Yuanheng Li, Chunxiao Li, Shijun Li, Kuan Li, Baoguang Li, Jie-Shou Li, Zimeng Li, Mengmeng Li, W-B Li, Binkui Li, Yu-Sheng Li, Junjie Li, Xiaoqi Li, Xiucui Li, Haihua Li, Yu-Lin Li, Tsai-Kun Li, Shujing Li, Mengyun Li, Mingna Li, Lanlan Li, Moyi Li, Xiyun Li, Ya-Pei Li, Zhongjie Li, Zhenbei Li, Shuangshuang Li, Hongwei Li, Ding-Jian Li, Xiao-Qiang Li, Danni Li, Min Li, Pengyang Li, Kun-Xin Li, Xiangpan Li, Zesong Li, Mingfei Li, Shuwei Li, Mingdan Li, Xihe Li, Jianfeng Li, Dexiong Li, Rongsong Li, Yinxiong Li, Hong-Yu Li, Weijian Li, Changhui Li, Dechao Li, Wenxia Li, Guoxiang Li, Ziru Li, Juxue Li, Man Li, Huayin Li, Xiao-yu Li, Jianyi Li, Guowei Li, Xingya Li, Gongda Li, Yajun Li, Wei-Ping Li, Nanjun Li, P H Li, Ranran Li, Suping Li, Jason Li, Monica M Li, Xianlun Li, Qi Li, Xiaoli Li, Xionghui Li, Fei Li, Hongmei Li, Xu-Wei Li, Mengsen Li, Quanpeng Li, Yajiao Li, Qilan Li, Qiuhong Li, Zongyun Li, Xiao-Yun Li, Cheng-Lin Li, Yousheng Li, Wen-Ting Li, Guoping Li, A Li, Simin Li, Weiguo Li, Xue-Nan Li, Xiaoying Li, Shengsheng Li, Hong Li, Yuqi Li, Zihua Li, Qing Li, Jiaping Li, Weiyang Li, Feng Li, Peihong Li, Jin-Mei Li, Lisha Li, Cuicui Li, Kaibo Li, Hanbing Li, Meng-Hua Li, J T Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Donghe Li, Zheng Li, Congfa Li, Wenrui Li, Yong Li, Xiuling Li, Jingqi Li, Zhiyong Li, Xiao-Kang Li, Hanqi Li, Yangyang Li, Dongfang Li, Zhuorong Li, X-H Li, Dong Sheng Li, Lan-Juan Li, Xianrui Li, Zhigao Li, Chenlin Li, Zihui Li, Guoli Li, Huanqiu Li, Zhan Li, Weisong Li, Xinglong Li, Xiaozhen Li, Zhiyang Li, Cunxi Li, Ying Li, Jianlin Li, Yanshu Li, Guiying Li, Jinku Li, Cuiling Li, Zhisheng Li, Changgui Li, Xuekun Li, Yuguang Li, Wenke Li, Jiayi Li, Suwen Li, Peihua Li, Chang-Ping Li, Guangda Li, Jieming Li, Chunhui Li, Tongyao Li, Peiyu Li, Linfeng Li, Yuzhe Li, Qifang Li, Chang-Yan Li, Xiaolin Li, Duanxiang Li, Vivian Li, Justin Li, Meiting Li, Xue-Er Li, Hongchang Li, Youwei Li, Ronggui Li, Xingwang Li, Tiange Li, Yongjia Li, Dacheng Li, Xinmin Li, Luquan Li, Guoxing Li, Jianyong Li, Zongchao Li, Jia Li, Haimin Li, Sheng-Qing Li, Lingjie Li, Yiwen Li, Baoqi Li, Leyao Li, Xiao-Qin Li, Jiajing Li, Yanlin Li, Liao-Yuan Li, Yongkai Li, Hangwen Li, Hengguo Li, An-Qi Li, Xuehua Li, AnHai Li, Chenli Li, Zhengrui Li, Rumei Li, Yan-Yu Li, Lipeng Li, Qinqin Li, Qinghua Li, Leilei Li, Lianyong Li, Zhou Li, Q Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Jian'an Li, Guangqiang Li, Sichong Li, Wenyi Li, Qing-Min Li, Meiyan Li, Yun-Da Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Shen Li, Ziqi Li, Yunfeng Li, Shufen Li, Yueqi Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Pinghua Li, Xu Li, Zhenli Li, Yunxiao Li, Rosa J W Li, Hsin-Yun Li, XiaoQiu Li, Zhankui Li, Zhi Li, Zhijie Li, Huimin Li, Ruifang Li, Xiao-xu Li, Man-Xiang Li, Cong Li, Chengbin Li, Yuping Li, G Li, Zhi-Yong Li, Yukun Li, Xiong Bing Li, Wen Lan Li, Qingjie Li, Han Li, Yutang Li, Hankun Li, Hongling Li, Zhifan Li, Yan-Guang Li, Ji-Min Li, Peipei Li, Tian-Yi Li, Zhihao Li, Yao Li, Zheyun Li, Zhonglin Li, Lin Li, Jinfang Li, Chenjie Li, Yanming Li, S L Li, Ben-Shang Li, Hong-Lan Li, Xionghao Li, Shunqing Li, Ming-Kai Li, Lan Li, Yanwei Li, Chien-Te Li, Wenyan Li, Xiaoheng Li, Zeyuan Li, Hongqin Li, Zhenhao Li, Jonathan Z Li, Yong-Liang Li, M Li, Jiehan Li, Hongguo Li, Chenxin Li, Yongsen Li, Qingyun Li, Pengyu Li, Ai-Qin Li, Zichao Li, Cien Li, Qingyu Li, Xijing Li, Jingshang Li, Xingyuan Li, Dehua Li, Yanjiao Li, Jia-Huan Li, Guoxi Li, Xudong Li, Xingfang Li, Jisheng Li, Rongyao Li, Ru Li, Jiangya Li, Yiche Li, Yilang Li, Yunshen Li, Jingchun Li, Hexin Li, H J Li, Yanping Li, Qing-Wei Li, Qiang Li, Hsiao-Hui Li, L I Li, Hongzheng Li, Laiqing Li, Ningyang Li, Zhongxia Li, Guangquan Li, Shun Li, Hui-Jun Li, Xuefei Li, Guojun Li, Hung Li, Senlin Li, Jinping Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, P Li, Fulun Li, Yonghao Li, Mingli Li, Yehong Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Gan Li, Shichao Li, Dapei Li, Zejian Li, Lihong Li, Haixia Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Zhao Li, Kui Li, Yunxu Li, Xuanfei Li, Zilin Li, Mingqiang Li, Xiaojiao Li, Yinzhen Li, Yunsheng Li, Li-Min Li, Xiangqi Li, Jia-Peng Li, Wenqi Li, Haibo Li, Xiao-Jun Li, Yan-Hong Li, Shi Li, Xueling Li, Conghui Li, Xiaoxiong Li, Wanni Li, Chitao Li, Haiyang Li, Xiaobai Li, Pingping Li, Mingquan Li, Suran Li, Yuanfang Li, Yingqin Li, Qiner Li, Jiafang Li, Shanhang Li, Han-Bing Li, Zongzhe Li, Yikang Li, Si-Yuan Li, Hongmin Li, Caihong Li, Yajing Li, Benyi Li, Yuquan Li, Hongzhi Li, Chengxin Li, Xiaojiaoyang Li, Xinxin Li, Jian-Shuang Li, Yubin Li, Dazhi Li, Chenglan Li, Yuhong Li, Fengqiao Li, Di Li, Yanbing Li, Jufang Li, Zecai Li, Qipei Li, Xiaoning Li, Xiyue Li, Minghua Li, Tianchang Li, Zhuoran Li, Hongru Li, Shiqi Li, Mei-Ya Li, Wuyan Li, Yi-Ling Li, Yingjian Li, Zhirong Li, Wang Li, Mingyang Li, Weijun Li, Boyang Li, Cai Li, Jingcheng Li, Ivan Li, Mengshi Li, Manxia Li, Ya Li, Dan-Ni Li, Wen-Chao Li, Sunan Li, Zhencong Li, Lai K Li, Jiong Li, Daiyue Li, Bingong Li, Chunxue Li, Yunlong Li, Jianshuang Li, Juanling Li, Xinbin Li, Xue-jing Li, Yuling Li, Yetian Li, Xianlin Li, Chuangpeng Li, Mingrui Li, Yanjun Li, Jiequn Li, Zhongding Li, Jiangui Li, Zhengyang Li, Cyril Li, Xinghui Li, Yuefei Li, Xinyan Li, Xiaoyun Li, Yushan Li, Ping'an Li, Weiping Li, Huan Li, Changjiang Li, Chengping Li, He-Zhen Li, G-P Li, Yinliang Li, Wen Li, Weihai Li, Yu-Kun Li, Jiangan Li, Zhaojin Li, Bingxin Li, Wenjuan Li, Chia-Yang Li, Wenyu Li, Hairong Li, Su Li, Mei-Lan Li, Wenjun Li, Jiaxin Li, Chenguang Li, Ming D Li, Ruyue Li, Xiaolian Li, Ya-Ge Li, Yinyan Li, Guangli Li, Rujia Li, Qijun Li, Lixia Li, Yunrui Li, Yuhuang Li, Shanshan Li, Wan-Shan Li, Jing-gao Li, Yiyang Li, Fengxiang Li, Nana Li, Jingui Li, Huamao Li, Xiankun Li, Jingke Li, Tianyao Li, Xiaowei Li, Junming Li, Hai-Yun Li, Zhongxian Li, H-J Li, Zhixiong Li, Lingyan Li, Xuhang Li, Chen-Lu Li, Jialun Li, Xinjian Li, Zilu Li, Sheng-Fu Li, Zezhi Li, Xue-Fei Li, Yudong Li, Hongjiang Li, Jingyun Li, Binghua Li, Hanjun Li, Qihua Li, Jin-Qiu Li, Jiaxuan Li, Guangjin Li, Xutong Li, Ranwei Li, Kai Li, Wei-Li Li, Keanning Li, Ling Li, Peiqin Li, Xiaodong Li, Nanxing Li, Qihang Li, Baoguo Li, Jianrong Li, Zhehui Li, Chenghao Li, Weike Li, Chuanbao Li, Zhixuan Li, Chuzhong Li, M D Li, Yuan-Tao Li, Kening Li, Guilan Li, Wanshi Li, Ling-Zhi Li, Hengtong Li, Yifan Li, Ya-Li Li, Songyun Li, Xiaoran Li, Bolun Li, Linchuan Li, Jiachen Li, Haibin Li, Huangbao Li, Guo-Chun Li, Xinli Li, S Li, Wenqing Li, Wenhua Li, Caiyun Li, Xinrui Li, Hanbin Li, Wanwan Li, Jia Li Li, Wan-Hong Li, Mingke Li, Huanhuan Li, Xiaoyuan Li, Zongfang Li, Yang Li, BoWen Li, Duoyun Li, Yimei Li, Zhi-qiang Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Zhiping Li, Yan-Li Li, Haiming Li, Gaijie Li, Yuemei Li, Xuefeng Li, Xiao-Hong Li, Mengjuan Li, Yinglin Li, Yaofu Li, Ren-Ke Li, Yi Li, Baosheng Li, Mian Li, Yujun Li, Lixi Li, Jin-Xiu Li, Jiwen Li, Zhouhua Li, Qingqin S Li, Honglei Li, Guojin Li, Xin-Yue Li, Dingchen Li, Xiaoling Li, Meng-Jun Li, Peining Li, Congjiao Li, Huilin Li, Songtao Li, Fusheng Li, Dai Li, Meiyue Li, Kechun Li, Keshen Li, Yuxin Li, Shaoliang Li, Shu-Xin Li, Hong-Zheng Li, Tianye Li, Qun Li, Zhen Li, Mengling Li, Jia-Da Li, Baoqing Li, Pu Li, Xingli Li, Bingkun Li, Nien-Chi Li, Tiewei Li, Daniel Tian Li, Rong-Bing Li, Wei-Yang Li, Rong Li, Mingkun Li, Binxing Li, Zixiao Li, Guixin Li, Quanzhang Li, Da-wei Li, Xiumei Li, Melody M H Li, Peibo Li, Huanjun Li, Chung-Hao Li, Liuzheng Li, Zhanjun Li, Yifei Li, Tianming Li, Chang-Sheng Li, Tianyou Li, Jipeng Li, Longxuan Li, Shi-Guang Li, Wenxiu Li, Zhuang Li, Yu-Hao Li, Shilin Li, Shili Li, Meiqing Li, Hengyu Li, Yinhao Li, Junying Li, Mufan Li, Chun-Lai Li, Shiya Li, Xiao-Jiao Li, Li Li, Hanxue Li, Lulu Li, L P Li, Xiaoqin Li, Chunmei Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Ji-Cheng Li, Haolong Li, Xuanzheng Li, Peng-li Li, Quan Li, Xue-Ying Li, Yongzhe Li, Tianyi Li, Qingfeng Li, Nanlong Li, Ping Li, Fangzhou Li, Nien-Chen Li, Yuanchuang Li, Haiying Li, Yunting Li, Hong-Yan Li, Shengbiao Li, Yue-Rui Li, Ruidong Li, Y M Li, Sijie Li, Meilan Li, D C Li, Andrew C Li, Jianye Li, Qiuyan Li, Tingguang Li, Xiangyang Li, Chunjie Li, Tianfeng Li, Anna Fen-Yau Li, Minghui Li, Jiangfeng Li, Jie-Pin Li, Kaiyi Li, Junyi Li, Dongtao Li, Fengyuan Li, Chenxi Li, Zuo-Lin Li, Zhengwei Li, Yan-Chun Li, Suiyan Li, Qiaoqiao Li, Xiaotian Li, Zhenguang Li, Jia-Ru Li, Pei-Qin Li, Chun-Xiao Li, Shu-Hong Li, Shuyue Li, Quan-Zhong Li, Tongzheng Li, Fangyan Li, Duo Li, Ren Li, Hongye Li, Lanfang Li, Mingwei Li, Wenxin Li, W J Li, Zhijia Li, Jingtong Li, Lucy Li, Zhengpeng Li, Xiayu Li, Baolin Li, Cuilan Li, Yuting Li, Xiaobo Li, Meijia Li, Shujiao Li, Kun-Ping Li, Weirong Li, Weihua Li, Runzhao Li, Xiang-Dong Li, Yanxin Li, Xiufeng Li, Yingjun Li, Xiaohuan Li, Ying-Qin Li, Fan Li, Jun Z Li, Yiheng Li, Taiwen Li, Xiaorong Li, Haifeng Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Rui-Jún Eveline Li, Xuanxuan Li, Bing-Mei Li, Yunman Li, Shuhua Li, Chunying Li, Leipeng Li, Weiheng Li, Baizhou Li, Han-Ru Li, Sheng Li, Yaqiang Li, Guoyin Li, Qiwei Li, Chengjun Li, Jianxiong Li, Ji Li, Huaying Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Xiang Li, Chaonan Li, Yu-Chia Li, Heying Li, Shaomin Li, Yuxuan Li, Xuan-Ling Li, Bingshan Li, Jiahao Li, Shibao Li, Ruijin Li, Kunlong Li, Xiaofeng Li, Zhaolun Li, Litao Li, Ruyi Li, Wanxin Li, Jinsong Li, Ying-Lan Li, Yulin Li, Shaojian Li, Mohan Li, Yan-Xue Li, Enhong Li, Xiangnan Li, Yong-Jun Li, Hang Li, Ziming Li, Jing-Ming Li, Yuanchang Li, Xiao-Lin Li, Yicun Li, Zhao-Yang Li, K-L Li, Xinjia Li, Bin Li, Jianhai Li, Peiwu Li, Youran Li, Changyu Li, Ming Zhou Li, Z Li, Xinmei Li, Wulan Li, Haoxian Li, Xiaozhao Li, Da-Lei Li, Jinming Li, Huihui Li, Kailong Li, Qiankun Li, Shengxu Li, Xiuli Li, Yulong Li, Ru-Hao Li, Zhi-Peng Li, Lanzhou Li, Tingsong Li, Binjun Li, Chen Li, Yawei Li, Chao Bo Li, Donghua Li, Siming Li, Fengli Li, Song Li, Hsin-Hua Li, You Li, Dongfeng Li, Zhen-Yuan Li, Xuelin Li, Xueyang Li, Bao Li, Yin Li, Cai-Hong Li, Dejun Li, Yufeng Li, Miaoxin Li, Hu Li, Bei Li, W H Li, Sha Li, Ya-Qiang Li, Xiushen Li, Jinlin Li, Xiaoqing Li, Shuaicheng Li, Xuebiao Li, Yingyi Li, Maolin Li, Jiyang Li, Zhongxuan Li, Linting Li, Zhong-Xin Li, Enhao Li, Shengliang Li, Hujie Li, Yue-Ming Li, Zhaohan Li, Alexander Li, Wen-juan Li, Pilong Li, Yun-Peng Li, C X Li, Huanan Li, Miao X Li, KeZhong Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yaokun Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Side Li, Timmy Li, Jiezhen Li, Qiuya Li, Haitao Li, Yufen Li, Qin Li, Annie Li, Wenge Li, Xueren Li, Chun-Mei Li, Meng-Yao Li, Chung-I Li, Zhi-Bin Li, Junping Li, Xiao Li, PeiQi Li, Xiaobing Li, Liangdong Li, Yan Li, Shengchao A Li, Pan Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Chengquan Li, Zexu Li, Zhilei Li, Tiantian Li, Wenyong Li, Desen Li, Tianjun Li, Zihao Li, Fadi Li, Huawei Li, Yu-quan Li, Jihua Li, Jingping Li, Zhiquan Li, Zeyu Li, Zongdi Li, Ming V Li, Aowen Li, L K Li, Aimin Li, Tiehua Li, Guohong Li, Botao Li, L-Y Li, Xiuqi Li, Zhenhua Li, Zhengda Li, Haotong Li, Luhan Li, Yuancong Li, Tian Li, Yuxiu Li, Beibei Li, Changhong Li, Yvonne Li, Zhichao Li, Jiayuan Li, Yige Li, Siguang Li, Chengqian Li, Weiye Li, Dong-fei Li, Xiangchun Li, Hailong Li, Kun-Peng Li, Haijun Li, Si Li, Ji-Feng Li, Wanqian Li, Zijing Li, Wentao Li, Yuchuan Li, Xuhong Li, Hongyun Li, Zhonggen Li, Xiong Li, Penghui Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Defa Li, X L Li, Yuyan Li, Kawah Li, Shupeng Li, Zhenfei Li, Zhuo Li, Han-Wei Li, Weina Li, Xiao-Hui Li, Rui-Fang Li, Jianzhong Li, Bing Li, Huihuang Li, Yunmin Li, Yanying Li, Gui Lin Li, Chenrui Li, Dengfeng Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Zhimei Li, Jiao Li, Jingming Li, Jinxia Li, De-Tao Li, Shu Li, Julia Li, Huilan Li, Xin-Ya Li, Chunsheng Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Supeng Li, Yiju Li, Yuanhe Li, Guangxiao Li, Xueqin Li, Peixin Li, Feng-Feng Li, Zu-Ling Li, Yunjiu Li, Dayong Li, Zonghong Li, Lingjiang Li, Yuhan Li, Fuyuan Li, H-F Li, Chunxia Li, Zhen-Li Li, Zhengying Li, Zhaoshui Li, Yali Li, Yu-Hui Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Stephen Li, Shuangding Li, Mangmang Li, Kaiyuan Li, Xiaopeng Li, Anan Li, Luying Li, Jiajv Li, Xiaoquan Li, Yanxi Li, Yongjing Li, Huayao Li, Jiqing Li, Huixue Li, Boxuan Li, Yongqi Li, Qingyuan Li, Fengqi Li, Yuqing Li, Zhigang Li, Guiyang Li, Guo-Qiang Li, Yanbo Li, Sanqiang Li, Hongyu Li, Guangping Li, Jinxin Li, Xinrong Li, Yayu Li, Huaixing Li, Minyue Li, Hong-Mei Li, Jutang Li, Mengxia Li, Yongxiang Li, Qilong Li, Songlin Li, Dijie Li, Yizhe Li, Yan Bing Li, Jiani Li, Lianjian Li, Yiliang Li, Xinpeng Li, Hongxing Li, Wanyi Li, Mi Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Yumiao Li, Jiexi Li, Kecheng Li, Junxu Li, Junya Li, Jiang Li, Shengxian Li, Qingyang Li, Yuxi Li, Chenxuan Li, Xiao-Dong Li, Xinghuan Li, Zhenlu Li, Xiaolei Li, Huilong Li, Xiao-Gang Li, Zhenhui Li, Chunjun Li, Shu-Fen Li, Yinghua Li, Yanjie Li, Chaoying Li, Juanjuan Li, Qiu Li, Kunlun Li, Shiquan Li, Xiangdong Li, Zhenjia Li, Jifang Li, Zhizhong Li, Ding Yang Li, Chenlong Li, Shujin Li, Weining Li, Wu-Jun Li, Yumao Li, Bin-Kui Li, Honglian Li, Ya-Zhou Li, Hongyi Li, Fu-Rong Li, Honghua Li, Lanjuan Li, Man-Zhi Li, Xiancheng Li, Yanmei Li, Zhihua Li, Minqi Li, Saijuan Li, Danxi Li, Mimi Li, Yingjie Li, Yuan-Hai Li, Lujie Li, Minghao Li, Meifen Li, Yifeng Li, Huanqing Li, Yuhang Li, Jianhua Li, Chanjuan Li, Lingyi Li, Yanchuan Li, Bai-Qiang Li, Chunmiao Li, Jiong-Ming Li, Yongqiang Li, Linsheng Li, Mingyao Li, Ze Li, R H L Li, Guisen Li, Dongyang Li, Jinglin Li, Honglong Li, Mingfang Li, Hanmei Li, Chenmeng Li, Shiyang Li, Jianing Li, Xinsheng Li, Jin-Jiang Li, Zhi-Xing Li, Chang Li, Jiwei Li, Weifeng Li, Wenhui Li, Sichen Li, Qingsheng Li, Liangji Li, Lixiang Li, Jin-Liang Li, Xiaoqiong Li, You Ran Li, Yixiao Li, Kathy H Li, Yuhua Li, Deqiang Li, Y Li, Mingyue Li, Zipeng Li, Caixia Li, Hongli Li, Yanfeng Li, Yaqin Li, Yu-He Li, Shasha Li, S-C Li, Xi Li, Siyi Li, Minmin Li, Manna Li, Dawei Li, Xun Li, Ming-Jiang Li, Sitao Li, Tinghua Li, Zhenfen Li, Shuo Li, Si-Ying Li, Xinyi Li, Jenny J Li, Xue-zhi Li, Xiaonan Li, Zhenyu Li, Ting Li, Xiang-Yu Li, Duan Li, Lei Li, Hongde Li, Fengqing Li, Yanchang Li, Xunjia Li, Ruixia Li, Nanzhen Li, Hongxue Li, Bingjie Li, Xiaojing Li, Xinlin Li, Yu-Ying Li, Wenli Li, Mengze Li, Kaiwei Li, Huangyuan Li, Lili Li, Junxin Li, Wei-Jun Li, Guoyan Li, Fei-Lin Li, Nuomin Li, Yanyan Li, Shulin Li, Shanglai Li, Taibo Li, Yue Li, Junqin Li, JunBo Li, Jun-Ru Li, Xueying Li, Zhongcai Li, Zhaobing Li, Linxin Li, Jen-Ming Li, Chen-Chen Li, Hongquan Li, Chuan F Li, Yanxiang Li, Yi-Wen Li, Shihong Li, Rulin Li, Huifeng Li, Lijuan Li, Yuanhong Li, Shengbin Li, Jingyu Li, Xuewei Li, Long Li, Min-Dian Li, Wenjia Li, Xiatian Li, Yangxue Li, Chengnan Li, Chuanyin Li, Yiqiang Li, Zhenzhou Li, Xiawei Li, Binglan Li, Yutong Li, Yingnan Li, Ge Li, Xinzhong Li, Chenyao Li, Jun-Yan Li, Boru Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Chuanning Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Chunxing Li, Qiao-Xin Li, Huang Li, Shu-Fang Li, Qiusheng Li, Weiqin Li, Xinming Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Chenglong Li, Nan Li, Yipeng Li, Mingxing Li, Xin-Yu Li, Chunyu Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Long Shan Li, Yanze Li, Xiao-Feng Li, W Li, Fengjuan Li, Hainan Li, Yutian Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Peilong Li, Kang Li, Yinghao Li, Lirong Li, Wenhong Li, Audrey Li, Yijian Li, Guang Y Li, Xianyong Li, Shilan Li, Guang-Li Li, Bang-Yan Li, Enxiao Li, Jianrui Li, Guohua Li, Kezhen Li, Xingxing Li, Ellen Li, Yijie Li, Suwei Li, Shuyu D Li, Ruiwen Li, Jiandong Li, Fangyong Li, Binru Li, Yuchao Li, Hanlu Li, Jianang Li, Xue-Peng Li, Sheng-Tien Li, Shihao Li, Yazhou Li, Jun-Ling Li, Caesar Z Li, Lang Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Xinxiu Li, Chongyi Li, Yi-Ying Li, Shaodan Li, Yongzheng Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Yaoyao Li, Yueguo Li, Mo Li, Ming-Hao Li, Hongsen Li, Menghua Li, Ka Li, Kaixin Li, Fuping Li, Jianbo Li, Xing-Wang Li, Chong Li, Fugen Li, Yuwei Li, Xiaochen Li, Zizhuo Li, Xiaoxiao Li, Le-Ying Li, Pengcui Li, Bing-Heng Li, Xiaoman Li, Xiaohong Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhifei Li, Jinhui Li, Yuanyou Li, Chongyang Li, Wanyan Li, Yumin Li, Longyu Li, X B Li, Jianguo Li, En Li, Ximei Li, Shaoyong Li, Kai-Wen Li, Guandu Li, Yixue Li, Junfeng Li, Xin-Chang Li, Yue-Ying Li, Kongdong Li, Lian Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Xiaohua Li, Zhuangzhuang Li, Xiaohui Li, Cang Li, Xuepeng Li, Mingjiang Li, Zongyu Li, Shujie Li, Yanbin Li, Shiliang Li, Qinrui Li, Yiming Li, Xiao-Tong Li, Tie Li, Wei-Bo Li, Xiaoyi Li, Liyan Li, Xinke Li, Xiaokun Li, Ming-Wei Li, Minzhe Li, Wenfeng Li, Karen Li, X Li, Meifang Li, Yanjing Li, Maosheng Li, Ju-Rong Li, Shibo Li, Jin Li, Li-Na Li, Hui Li, Fangqi Li, Xiaoguang Li, Xian Li, Danjie Li, Vivian S W Li, Ranchang Li, Defu Li, Amy Li, Haoyu Li, Xiaoyao Li, M-J Li, Jiao-Jiao Li, Zhu Li, Rongling Li, Tong-Ruei Li, Ben Li, Yingxia Li, Yonghe Li, Xinwei Li, Yu-I Li, Shunhua Li, Mingxi Li, Qionghua Li, Guo-Li Li, Xingchen Li, Tianjiao Li, Gui-Rong Li, Yunpeng Li, Qiong Li, Songyu Li, Shi-Fang Li, Shude Li, Zhibin Li, Yaxiong Li, Qing-Fang Li, Shengwen Li, Gui-Bo Li, Xueer 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, Cun Li, T Li, Yinghui Li, Feilong Li, Sin-Lun Li, Weiling Li, Mengfan Li, Jie Li, Shiyan Li, Lianbing Li, Yanchun Li, Xuze Li, Jialin Li, Wenjian Li, He Li, Bichun Li, Hanqin Li, Guoge Li, Wen-Wen Li, Keying Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Xiangrui Li, Caolong Li, Michelle Li, Chaojie Li, J Li, Zhi-Jian Li, Jianwei Li, Jiexin Li, Hongyan Li, Zhen-Xi Li, Guangdi Li, Xiaxia Li, Nien Li, Yuefeng Li, Peiyuan Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Fen Li, Jieshou Li, Roger Li, Mengqing Li, Menglu Li, Huiqing Li, Yantao Li, Ruolin Li, Yongle Li, Haying Li, Shao-Dan Li, Muzi Li, Gen Li, Dong-Ling Li, Chenwen Li, Le Li, Yong-Jian Li, Si-Wei Li, Manru Li, Yingxi Li, Caili Li, Yuqian Li, Wei-Dong Li, Guannan Li, Ya-Feng Li, Wenlong Li, Yuna Li, Shengli Li, Shugang Li, Xuan Li, Yongze Li, Yongxin Li, Lu Li, Zhuo-Rong Li, Qinglin Li, Bingbing Li, Runzhi Li, Qi-Jing Li, Zhenyan Li, Ji Xia Li, Yu-Ye Li, Meizi Li, Yuezheng Li, Zhengnan Li, Jianglong Li, Xiaozheng Li, Huili Li, Hongzhe K Li, Xiao-Qiu Li, Jiejia Li, Yi-Yang Li, Zhihui Li, Fujun Li, Ni Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Chunliang Li, Ruiyang Li, Chun Li, Jianan Li, Wenfang Li, Xiangling Li, Sung-Chou Li, Lianhong Li, Cheng Li, Tiegang Li, Zhong Li, Shuang-Ling Li, Xiao-Long Li, Xiaofei Li, Hung-Yuan Li, Zhang Li, Jianxin Li, H Li, Dongliang Li, Chenxiao Li, Hongjia Li, Xiao-Jing Li, Y H Li, Jian Li, Daoyuan Li, Baichuan Li, Zhenzhe Li, Jian-Mei Li, Kaimi Li, Peiran Li, Qiao Li, Yi-Yun Li, Xiao-Cheng Li, Yike Li, Yihan Li, Junsheng Li, Jiayu Li, Wen-Ya Li, Rongxia Li, Yunlun Li, Guoqin Li, Huiqin Li, Chunlin Li, Peng Peng Li, Kenli Li, Guanglu Li, Xiushi Li, Dongmin Li, Jian-Jun Li, Fengyi Li, Yanling Li, Juanni Li, C Li, You-Mei Li, Beixu Li, Guiyuan Li, Suk-Yee Li, Shengjie Li, Yuanyuan Li, Xiaona Li, Shanyi Li, Chih-Chi Li, Hongbo Li, Xinhui Li, Jun Li, Mingzhe Li, Hongjuan Li, Senmao Li, Mingjie Li, Ling-Jie Li, Hong-Chun Li, Yaying Li, Liqun Li, Changxian Li, Chunqing Li, Yanni Li, Yongsheng Li, Xiujuan Li, Huifang Li, Lingling Li, Xinhua Li, Minerva X Li, Alexander H Li, Wendeng Li, Ding Li, Ming-Yang Li, Shengze Li, Linyan Li, Hewei Li, Da-Jin Li, Xiao-kun Li, Yuanhao Li, Ji-Lin Li, Congcong Li, Juan Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Jinfeng Li, Shiheng Li, Hsiao-Fen Li, Mengjiao Li, Tianxiang Li, Meng-Meng Li, Liangkui Li, Tian-chang Li, Yahui Li, Wenlei Li, Xi-Xi Li, Haiyan Li, Xujun Li, Chi-Ming Li, Yi-Ning Li, Dandan Li, Yunan Li, Sherly X Li, Jiazhou Li, Zhijun Li, Zechuan Li, Wanling Li, Zhiwei Li, Xueshan Li, Jiangbo Li, Xiaohan Li, Huijie Li, Zhongwen Li, W W Li, Yalan Li, Xuejun Li, Shunwang Li, Yaqing Li, Chao Li, Yaqiao Li, Bingsheng Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Haoran Li, Xiaoliang Li, Xinyuan Li, Maoquan Li, Chumei Li, Shijie Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xiaochun Li, Rui Li, Xuemin Li, Shanpeng Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Xuyi Li, Yunchu Li, Zhengyao Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Lin-Feng Li, Ziqing Li, Shuangxiu Li, Yongjin Li, Chenhao Li, Weizu Li, Deming Li, Jiuyi Li, Chun-Xu Li, Luyao Li, Desheng Li, Long-Yan Li, Fuyu Li, Lingzhi Li, Xiao-Sa Li, Kunlin Li, Shu-Qi Li, Zehua Li, Mengyuan Li, Congye Li, Wensheng Li, Dehai Li, Qingshang Li, Jiannan Li, Guanbin Li, Zhiyi Li, Xing Li, Zhaoyong Li, SuYun Li, Shiyi Li, Suchun Li, Yanan Li, Jiayan Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, Dongdong Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Shaojing Li, S S Li, Tong Li, Yilong Li, Lihua Li, Xue-Lian Li, Yansen Li, Hai Li, Zhi-Yuan Li, Jingfeng Li, Yanli Li, Yuan-Jing Li, Kaibin Li, Xiaohu Li, Wenjie Li, Ruikai Li, Qiyong Li, Ruixi Li, Zhonglian Li, Dalin Li, Kun Li, Qizhai Li, Pengju Li, Peifeng Li, Ai-Jun Li, Yueting Li, YaJie Li, Zijian Li, Yanqing Li, Jixuan Li, Zhandong Li, Xuejie Li, Gaizhen Li, Liang Li, Huafang Li, Nianyu Li, Chenlu Li, X-L Li, Shawn S C Li, Cuiguang Li, Dongye Li, F Li, Chunhong Li, Yuan Li, Kunpeng Li, Zhenghao Li, Chun-Bo Li, Zhantao Li, Xinle Li, Wuguo Li, Bing-Hui Li, Honggang Li, Jingyong Li, Shikang Li, Shi-Ying Li, Ming Xing Li, Ming-Xing Li, Marilyn Li, Bei-Bei Li, Hong-Lian Li, Shishi Li, Haitong Li, Yuli Li, Ruibing Li, Qingfang Li, Qibing Li, Wende Li, Heng Li, Xiao-Na Li, Xidan Li, Yixing Li, Chengcheng Li, Yu-Jin Li, Baoting Li, Ka Wan Li, Huiyou Li, Binbin Li, Xinyao Li, Gui-xing Li, Niu Li, Shunle Li, Siyue Li, Diyan Li, Mengyao Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Gerard Li, Yuyun Li, Zhiqiong Li, Zonglin Li, Pik Yi Li, Jingxin Li, Defeng Li, Zu-guo Li, Xin-Zhu Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Junhong Li, Youchen Li, W Y Li, Yi-Heng Li, Runbing Li, Yanmin Li, Jingyi Li, Yuxiang Li, Hao-Fei Li, Yining Li, Xiurong Li, Haiyu Li, Huijuan Li, Yunze Li, Xu-Zhao Li, Yanzhong Li, Kainan Li, Guohui Li, Xiaoyan Li, Xu-Bo Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Xiaoxuan Li, Anyao Li, Qing-Chang Li, Hongliang Li, Dalei Li, Zongjun Li, Changqing Li, Hanting Li, Dong-Jie Li, Xiaomin Li, Dengxiong Li, Yi-Shuan J Li, Tinghao Li, Zhouxiang Li, Yun-tian Li, Jianliang Li, Guangzhao Li, Yixi Li, Shuyu Dan Li, S A Li, Jinjie Li, Liming Li, Wenqun Li, Guixia Li, Yinan Li, Aoxi Li, Yuanjing Li, Linqi Li, Xixi Li, Bingjue Li, Binghu Li, Yu-Hang Li, Shuhui Li, Mengying Li, Yihong Li, Yaxian Li, Dali Li, Zhiming Li, Xuemei Li, Xueting Li, Yongting Li, Hongxia Li, Zhenjun Li, Danyang Li, Tiandong Li, Di-Jie Li, Bo Li, Jinliang Li, Qiji Li, Zhipeng Li, Xiaoping Li, Linhong Li, Taoyingnan Li, Lieyou Li, Huabin Li, Mao Li, Yongchao Li, Xiaoting Li, Ruotai Li, Yaojia Li, Xiao-Yao Li, Shangming Li, Yaqi Li, Yibo Li, Gui-Hua Li, Zhihong Li, Yandong Li, Chaowei Li, Huiyuan Li, Yuchun Li, Boya Li, Lamei Li, O Li, Joyce Li, Suheng Li, Hui-Ping Li, Junru Li, Zhiqiang Li, Jiangchao Li, Hecheng Li, Yueping Li, Changkai Li, Zhenglong Li, Yajuan Li, Chaoqian Li, Yu-Cheng Li, Yirun Li, Haomiao Li, Qianqian Li, YiQing Li, Zhengliang Li, Weijie Li, Wei-Qin Li, Zongyi Li, Qingxian Li, Dan-Dan Li, Yeshan Li, Zirui Li, Keke Li, Yongpeng Li, Chanyuan Li, Jianbin Li, Shiying Li, Zhongzhe Li, Yumei Li, Xiang-Ping Li, Wenqiang Li, Pei-Shan Li, Zaibo Li, Guangming Li, Xiaoqiang Li, Hanxiao Li, Jiansheng Li, Shuying Li, Xiaomei Li, Pengjie Li, Jiajia Li, Jingwen Li
articles
Yan Huang, Bo-Wen Yue, Yue-Qin Hu +5 more · 2025 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
Anxiety disorder is a highly prevalent psychological illness, and research has shown that obesity is a significant risk factor for its development. This study explored the ameliorative effects and mec Show more
Anxiety disorder is a highly prevalent psychological illness, and research has shown that obesity is a significant risk factor for its development. This study explored the ameliorative effects and mechanisms of saponins from Panax japonicus(SPJ) on anxiety disorder in mice fed a high-fat diet(HFD). Fifty C57BL/6J mice were randomly divided into normal control diet(NCD) group, HFD group, and low-and high-dose SPJ groups. At week 12, six mice from the HFD group were further divided into a control group(treated with DMSO) and an exogenous fibroblast growth factor 21(FGF21) group(administered rFGF21). The anxiety-like behavior of the mice was assessed using the open field test and elevated plus maze test. Hematoxylin-eosin(HE) staining and oil red O staining were performed to observe pathological changes in the liver and adipose tissue. Glucose metabolism was evaluated through the glucose tolerance test(GTT) and insulin tolerance test(ITT). Western blot analysis was performed to detect the expression of FGF21 and its downstream-related proteins in the liver and cortex, along with the expression of brain-derived neurotrophic factor(BDNF), disks large homolog 4(DLG4), and synaptophysin(SYP) in the cortex. Real-time quantitative fluorescent PCR(qPCR) was used to detect the expression of FGF21 and its receptor genes in the liver and cortex. Immunofluorescence staining was employed to examine the expression of neuronal activator c-Fos, FGF21, and the FGF21 co-receptor β-klotho in the cerebral cortex. The results showed that SPJ significantly improved the frequency of activity in the open arms of the elevated plus maze and the central area of the open field in HFD mice, up-regulated the expression of BDNF, DLG4, and SYP, and effectively alleviated anxiety-like behaviors in HFD mice. Compared with the NCD group, HFD mice exhibited up-regulated expression of FGF21 in the liver and cerebral cortex, while the expression of fibroblast growth factor receptor 1(FGFR1) and β-klotho was significantly down-regulated, suggesting that HFD mice exhibited FGF21 resistance. SPJ markedly up-regulated the β-klotho levels in HFD mice, reversing FGF21 resistance. Further comparison with exogenously administered FGF21 revealed that SPJ activates brain cortical regions in a consistent manner, and additionally, SPJ promotes the number and colocalization of c-Fos and β-klotho positive cells in the brain cortex. In summary, SPJ effectively alleviates anxiety-like behaviors in HFD mice. Its mechanism is associated with up-regulation of β-klotho expression in the brain, reversal of FGF21 resistance, and subsequent activation of neurons in the cerebral cortex and amygdala. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20240906.401
FGFR1
Li Zhou, Zhuo-Ma Luoreng, Xing-Ping Wang +2 more · 2025 · Research in veterinary science · Elsevier · added 2026-04-24
MicroRNAs (miRNAs) are a class of endogenous non-coding small RNAs that are widely found in organisms and play an important regulatory role in various biological processes, especially immune and infla Show more
MicroRNAs (miRNAs) are a class of endogenous non-coding small RNAs that are widely found in organisms and play an important regulatory role in various biological processes, especially immune and inflammatory responses. However, the function of miR-320b in the inflammatory responses of bovine mammary epithelial cells (bMECs) remains to be elucidated. In this study, we examined the miR-320b mimic transduction group (miR-320b_mimic) and negative control mimic transduction group (NC_mimic) of lipopolysaccharide-treated bMECs using data-independent acquisition (DIA) proteomics and untargeted metabolomics. Subsequently, we performed a joint analysis of the sequencing data. Proteomic analysis identified 330 differentially abundant proteins (DAPs) primarily related to PPAR, ferroptosis, arachidonic acid metabolism, IL-17, and complement and coagulation cascades. Metabolome analysis identified 128 and 66 differentially accumulated metabolites (DAMs) in the positive and negative ion mode primarily involved in linoleic acid metabolism, cholesterol metabolism, AMPK, MAPK, and chemokine. Integrated metabolomics and proteomics analysis revealed the co-enrichment of DAPs and DAMs in choline metabolism in cancer, endocrine resistance, glycerophospholipid metabolism, primary bile acid biosynthesis, and the ferroptosis signaling pathways. The results of quantitative real-time PCR (RT-qPCR) showed that compared with the NC_mimic group, mRNA expression levels of COX-2, IL-12 A, iNOS, MAPK1, and MAPK14 genes were significantly down-regulated, and the mRNA expression levels of PPARγ, CEBPα, CEBPβ, FABP4, and LPL genes were significantly up-regulated in the miR-320b_mimic group. These results provide crucial insights into the molecular regulatory functions of miR-320b and offer valuable data for further research on molecular breeding aimed at enhancing mastitis resistance in bovine animals. Show less
no PDF DOI: 10.1016/j.rvsc.2025.105682
LPL
Jingjing Qi, Qian Hu, Yang Xi +5 more · 2025 · Animal genetics · Blackwell Publishing · added 2026-04-24
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed Show more
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed beak bean phenotypes of duck at 10, 20, 30 and 40 days of age, revealing that the most common type is the black beak bean, characterized by melanin deposition on the beak surface. This study performed single nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) to investigate the genetic basis of beak bean color, identifying signals on chromosome 1. The copy number variation region-based GWAS revealed a consistent candidate region overlapping with the SNP-based GWAS signals, further supporting the importance of this genomic region. Locus zoom analysis further refined the candidate regions to 48.5-50.5 and 50.8-52.8 Mb. Functional enrichment analysis highlighted six candidate genes within these regions: KITLG, DUSP6, GALNT4, MGAT4C, ATP2B1 and NTS. Notably, KITLG and DUSP6, which are linked to melanin production, were identified as key candidate genes for beak bean color. Our finding revealed the genetic basis of the bean color traits for the first time in ducks, providing a theoretical foundation and technological framework for enhancing duck beak coloration. Show less
no PDF DOI: 10.1111/age.70040
DUSP6
Anyue Wu, Shengze Li, Chunyang Feng +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Metastatic spread of cancer is the leading cause of death in patients with epithelial ovarian cancer (EOC), and elucidation of the molecular mechanisms underlying this process is a major focus of canc Show more
Metastatic spread of cancer is the leading cause of death in patients with epithelial ovarian cancer (EOC), and elucidation of the molecular mechanisms underlying this process is a major focus of cancer research. Fibroblast growth factor-inducible 14 (Fn14) has been shown to regulate wound repair, inflammation, angiogenesis, and chemoresistance, but its functional role in metastasis in EOC is still unknown. Here it is reported that Fn14 is identified as a cancer metastasis suppressor that inhibits the migratory and invasive potential of EOC cells by down-regulating epithelial-mesenchymal transition (EMT). Mechanistically, it is identified that Fn14 promotes acetylation-dependent protein degradation of Slug, a key transcriptional factor associated with EMT. The deacetylase Sirtuin 2 (SIRT2) has been reported to be involved in the deacetylation of Slug protein to stabilize it and then prevent its degradation in the nucleus. The results showed that Fn14 alters the subcellular localization of (SIRT2) by interacting with SIRT2, leading to reduced SIRT2 shuttling into the nucleus and subsequently promoting the acetylated degradation of Slug. Collectively, the work has demonstrated for the first time that Fn14 inhibits EOC metastasis by regulating SIRT2-mediated Slug deacetylation, providing a new perspective and method for the development of future novel therapeutic strategies for the treatment of EOC metastasis. Show less
no PDF DOI: 10.1002/advs.202501552
SNAI1
Ang Li, Yuanyuan Shen, Zhenyan Li +1 more · 2025 · Journal of molecular cell biology · Oxford University Press · added 2026-04-24
The Wnt signaling pathway plays important roles in cardiomyocyte proliferation and cardiac regeneration after heart injury. Abnormal activation of the Wnt pathway causes a reduction in cardiomyocyte f Show more
The Wnt signaling pathway plays important roles in cardiomyocyte proliferation and cardiac regeneration after heart injury. Abnormal activation of the Wnt pathway causes a reduction in cardiomyocyte function, leading to hypertrophy, fibrosis, and heart failure. However, the mechanism through which Wnt signaling affects cardiomyocyte function during cardiac diseases is still unclear. In this study, we observed that activation of the Wnt/β-catenin pathway, but not the Wnt/Ca2+ pathway, leads to significant cytosol calcium enrichment. Such an effect can be inhibited by cycloheximide that blocks the downstream gene expression. By analyzing the transcriptome data, we found that activation of the Wnt/β-catenin pathway significantly upregulates the expression level of muscle-selective A kinase anchoring protein (mAKAP, also called AKAP6), a scaffold protein that can improve the interaction between protein kinase A (PKA) and its substrate ryanodine receptor 2 (RyR2) in cardiomyocytes. We further identified that AKAP6 is a target gene of the canonical Wnt pathway and increasing AKAP6 expression can enhance RyR2 phosphorylation by PKA, causing the sarcoplasmic reticulum calcium leakage and finally heart dysfunction. Our finding that the Wnt/β-catenin pathway affects cardiac calcium regulation via AKAP6 and RyR2 provides profound insights into heart diseases and sheds light on potential therapeutic strategies. Show less
📄 PDF DOI: 10.1093/jmcb/mjaf002
AKAP6
Taryn Diep, Wesley Zhou, Rachel E Reyes +12 more · 2025 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
Carbamoyl phosphate synthetase 1 (CPS1) deficiency, a urea-cycle disorder, results in hyperammonemia initiating a sequence of adverse events that can lead to coma and death if not treated rapidly. The Show more
Carbamoyl phosphate synthetase 1 (CPS1) deficiency, a urea-cycle disorder, results in hyperammonemia initiating a sequence of adverse events that can lead to coma and death if not treated rapidly. There is a high unmet need for an effective therapeutic for this disorder, especially in early neonatal patients where mortality is excessive. However, development of an adeno-associated virus (AAV)-based approach is hampered by large cDNA size and high protein requirement. We developed an oversized AAV vector as a gene therapy to treat Show less
📄 PDF DOI: 10.1016/j.omtn.2025.102470
CPS1
Ziyu Li, Guangyi Chen, Wei Li +10 more · 2025 · Frontiers in plant science · Frontiers · added 2026-04-24
To explore the optimal row-ratio in mechanized hybrid rice seed production, a field experiment was conducted in 2024 at Qionglai and Mianzhu using 'Tiantai A' × 'Taihui 808'. Three row-ratio treatment Show more
To explore the optimal row-ratio in mechanized hybrid rice seed production, a field experiment was conducted in 2024 at Qionglai and Mianzhu using 'Tiantai A' × 'Taihui 808'. Three row-ratio treatments (H1: 18:6, H2: 24:6, and H3: 30:6) were tested using agricultural unmanned aerial vehicles (AUAVs) for pollination assistance. The results showed that row-ratio had little effect on sterile line flowering dynamics. The index of flowers meeting (IFM) was 0.71-0.72 at Qionglai and 0.81-0.86 at Mianzhu, with 11 to 12 days of flowering duration. As the row-ratio increased, total pollen quantity in the panicle layer and grain filling rate (GFR) decreased, while grain infection rate (GIR) increased. The responses of grain blighted rate (GBR), grain empty rate (GER), and fertilization success rate (FSR) to row-ratio varied between sites. Pollen density and GFR followed the pattern of near region (NR) > central region (CR) > far region (FR). Within the panicle, pollen density was generally highest in the upper panicle layer (UPL), followed by the middle (MPL) and lower (LPL) layers, with partial exceptions observed in the H2 and H3 treatments at Mianzhu. The vertical distribution of GFR varied by site: at Qionglai, it was apical parts of panicle (APP) > median parts (MPP) > basal parts (BPP), whereas at Mianzhu the order was MPP > APP > BPP. With wider row-ratios, yield per unit area (YUA) and GFR declined (H1 > H2 > H3), while 1,000-grain weight increased or decreased and then increased. Under H1, yields reached 2,107.50 kg ha Show less
📄 PDF DOI: 10.3389/fpls.2025.1704773
LPL
Shuang-Shuang Wang, Xin Jin, Wen-Di Ma +9 more · 2025 · European journal of pharmacology · Elsevier · added 2026-04-24
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple Show more
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS), by promoting the production of interferon-β (IFN-β). However, the mechanism through which oxymatrine regulates the production of IFN-β remains unclear. The aim of this study was to investigate the pharmacological effects and related molecular mechanisms of oxymatrine in the treatment of EAE through in vivo and in vitro experiments. Oxymatrine alleviated neurological dysfunction, demyelination, and inflammation in EAE mice. It reduced microglia/macrophage infiltration and polarization, lowered pro-inflammatory cytokine levels (iNOS, TNF-α), and enhanced the expression of IL-10 and IL-27. Additionally, oxymatrine upregulated the STING/TBK1/IRF3 signaling pathway in EAE mice, promoting IFN-β production by microglia. Similarly, in LPS-induced BV2 cells, oxymatrine suppressed inflammatory factors and activated the STING/TBK1/IRF3 pathway to enhance IFN-β production. Notably, treatment with the STING inhibitor, C176, reversed these effects in both EAE mice and LPS-induced BV2 cells, confirming the pathway's critical role in the mechanism of oxymatrine therapy. Oxymatrine promotes IFN-β production in microglia by upregulating the STING/TBK1/IRF3 signaling pathway, thereby alleviating the neurological dysfunction of EAE and reducing pathological and inflammatory events. This study identifies a novel anti-EAE mechanism of oxymatrine: promoting IFN-β production in microglia by activating the STING/TBK1/IRF3 pathway. However, it lacks clinical sample verification. If validated later, oxymatrine may provide a more economical, convenient endogenous IFN-β induction regimen for MS patients. Show less
no PDF DOI: 10.1016/j.ejphar.2025.178380
IL27
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
Xingyu Fu, Ao Yin, Chao Wang +5 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous Show more
Atherosclerosis is a primary contributor to worldwide morbidity and mortality. Failure to timely clear apoptotic cells can trigger a cascade reaction, where the necrotic core expands until the fibrous cap is ruptured, and atherosclerotic plaques become vulnerable. Efferocytosis is an important method for recognizing and eliminating apoptotic cells. Nevertheless, the specific effect of efferocytosis on atherosclerosis remains uncertain. This study aimed to identify and verify the relevant characteristics of efferocytosis for detecting atherosclerosis. The data of gene expression patterns of atherosclerosis were sourced from the Gene Expression Omnibus (GEO) database, and the differential expression analyses of efferocytosis-related genes (EFRGs) were performed between the atherosclerosis samples and the control samples. Subsequently, protein-protein interaction (PPI), correlation analysis, and functional enrichment analysis were performed to reveal the interaction between molecules as well as their pathways. Machine learning (ML) was employed to determine hub genes to construct a clinical prediction model. At the same time, immune infiltration, single-cell transcriptome analysis, and cell experiments were conducted in both atherosclerosis and control samples to provide a reference for the immune cell landscape and the cell heterogeneity under this condition. The study revealed that 14 genes were closely related to efferocytosis in atherosclerosis. Among them, an ML model was used to screen 5 potential diagnostic biomarkers, including tumor necrosis factor (TNF), apolipoprotein E (ApoE), neutrophil cytosolic factor 1 (NCF1), triggering receptor expressed on myeloid cells 2 (TREM2), and chitinase-3 like-protein-1 (CHI3L1). Subsequent external validation indicated that, except for TNF, the other 4 genes were all upregulated. From the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, those 5 genes were all significantly associated with various immune cells. Further single-cell RNA sequencing (scRNA-seq) analysis demonstrated that those 5 genes were selectively upregulated in the macrophages of atherosclerosis lesions, which was supported by mRNA levels in cell experiments. This study clarified the association between atherosclerosis and efferocytosis, and established an effective diagnostic model. Moreover, potential treatment targets for atherosclerosis were identified, offering new insights into the potential mechanism of atherosclerosis. Show less
📄 PDF DOI: 10.1186/s40001-025-03669-y
APOE
Tongtong Zhang, Zhongming Cai, Haoran Li +3 more · 2025 · PloS one · PLOS · added 2026-04-24
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-s Show more
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-specific transcriptional regulatory networks underlying ADSC adipogenesis remain incompletely elucidated. In this study, we integrated bulk and single-cell RNA-seq datasets across multiple time points of ADSC adipogenesis to identify core regulators of differentiation and maturation. A total of 41 genes were consistently upregulated during early differentiation, among which eight hub genes (FABP4, FASN, FABP5, ADIPOQ, PLIN1, LPL, CIDEC, and ACSL1) formed a tightly connected protein-protein interaction (PPI) module associated with lipid metabolism, lipid droplet formation, and adipocyte maturation. Further integration of differentially expressed lncRNAs and miRNAs led to the construction of a ceRNA network involving 7 mRNAs, 9 miRNAs, and 4 lncRNAs, comprising 34 predicted lncRNA-miRNA-mRNA regulatory axes. To identify temporal transcriptional regulators, we defined five genes (TTC14, MBNL2, UBR3, ABCD2, and SORT1) as early-stage inducers of adipogenesis, and four genes (UQCR11, NDUFB4, S100A10, and PRDX3) as late-stage regulators involved in maintaining the mature phenotype. These stage-specific regulators showed distinct temporal expression patterns and were validated by qPCR. GeneMANIA network analysis further revealed that early-stage regulators were enriched in lipid transport and lipase activity regulation, while late-stage regulators were associated with mitochondrial electron transport and energy metabolism. These findings highlight the stage-dependent transcriptional landscape of ADSC adipogenesis and provide candidate regulatory targets for modulating adipocyte differentiation and stability. Show less
📄 PDF DOI: 10.1371/journal.pone.0335152
LPL
Huayun Huang, Longzhou Liu, Zhong Liang +5 more · 2025 · Scientific reports · Nature · added 2026-04-24
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanism Show more
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanisms that underlie its activity are not completely understood. Treatment of intramuscular fat (IMF) and subcutaneous fat (SCF) adipocytes with CNP led to decreased differentiation, promoted proliferation and lipolysis, and increased the expression of natriuretic peptide receptor B (NPRB) mRNA. Silencing natriuretic peptide C (NPPC) had the opposite results in IMF and SCF adipocytes. Transcriptome analysis found 665 differentially expressed genes (DEGs) in IMF adipocytes and 991 in SCF adipocytes. Seven genes in IMF adipocytes (FABP4, APOA1, ACOX2, ADIPOQ, CD36, FABP5, and LPL) and eight genes in SCF adipocytes (ACOX3, ACSL1, APOA1, CPT1A, CPT2, FABP4, PDPK1 and PPARα) are related to fat metabolism. Fifteen genes were found to be enriched in the peroxisome proliferator-activated receptor (PPAR) pathway. Integrated analysis identified 113 intersection genes in IMF and SCF adipocytes, two of which (APOA1 and FABP4) were enriched in the PPAR pathway. In conclusion, CNP may regulated lipid metabolism through the NPRB-PPAR pathway in both IMF and SCF adipocytes, FABP4 and APOA1 may be the key genes that mediated CNP regulation of fat deposition. Show less
📄 PDF DOI: 10.1038/s41598-025-86433-w
LPL
Ting He, Jinbo Zhao, Ling Hou +2 more · 2025 · International journal of general medicine · added 2026-04-24
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. Show more
Coronary heart disease (CHD) has a significant co-morbid association with chronic kidney disease (CKD), but identification tools for the risk of concomitant CKD in patients with CHD are still lacking. The purpose of this research was to construct machine learning (ML) models for identifying undetected CKD in CHD patients. 1786 CHD patients undergoing coronary intervention were retrospectively included. Lasso regression and multifactor logistic regression were used to screen feature variables. Five ML models, ie, logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost), were constructed. Participants were divided into the training set and validation set in a 7:3 ratio. The evaluation metrics included the area under the curve, calibration curve, and decision curve. Totally, 1786 CHD patients were enrolled and split into training (70%) and validation (30%) sets. The prevalence of CKD was 21.8% (390/1786). Multivariate logistic regression analysis showed that men, advanced age, hypertension, diabetes mellitus, history of atrial fibrillation (AF), high Gensini, low hemoglobin, low plateletcrit (PCT), high triglycerides (TG), high lipoprotein(a) (Lp(a)), hyperkalemia, high uric acid to albumin ratio (UAR), high systemic inflammation response index (SIRI), low lymphocyte to monocyte ratio (LMR), and high apolipoprotein B to apolipoprotein A1 (ApoB/ApoA1) ratio were the key clinical and laboratory test indicators of CKD. The XGBoost model performed optimally in the validation set (AUC=0.909, 95% CI 0.881 -0.937). SHapley Additive explanation analysis identified UAR, hypertension, Gensini score, age, and SIRI as the top 5 key features. The XGBoost model constructed on routine clinical data was effective in identifying CKD risk in CHD patients, with UAR as a novel strong predictor. Decision curve analysis confirmed the clinical utility of the model, indicating that it may be used to guide decisions for enhanced monitoring and early intervention over a wide range of risk thresholds. Show less
📄 PDF DOI: 10.2147/IJGM.S558568
APOB
Yisheng Chen, Xiaofeng Chen, Zhiwen Luo +16 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Alzheimer's Disease (AD), a progressive neurodegenerative disorder, is marked by cognitive deterioration and heightened neuroinflammation. The influence of Insulin-like Growth Factor 1 Receptor (IGF1R Show more
Alzheimer's Disease (AD), a progressive neurodegenerative disorder, is marked by cognitive deterioration and heightened neuroinflammation. The influence of Insulin-like Growth Factor 1 Receptor (IGF1R) and its post-translational modifications, especially sumoylation, is crucial in understanding the progression of AD and exploring novel therapeutic avenues. This study investigates the impact of exercise on the sumoylation of IGF1R and its role in ameliorating AD symptoms in APP/PS1 mice, with a specific focus on neuroinflammation and innovative therapeutic strategies. APP/PS1 mice were subjected to a regimen of moderate-intensity exercise. The investigation encompassed assessments of cognitive functions, alterations in hippocampal protein expressions, neuroinflammatory markers, and the effects of exercise on IGF1R and SUMO1 nuclear translocation. Additionally, the study evaluated the efficacy of KPT-330, a nuclear export inhibitor, as an alternative to exercise. Exercise notably enhanced cognitive functions in AD mice, possibly through modulations in hippocampal proteins, including Bcl-2 and BACE1. A decrease in neuroinflammatory markers such as IL-1β, IL-6, and TNF-α was observed, indicative of reduced neuroinflammation. Exercise modulated the nuclear translocation of SUMO1 and IGF1R in the hippocampus, thereby facilitating neuronal regeneration. Mutant IGF1R (MT IGF1R), lacking SUMO1 modification sites, showed reduced SUMOylation, leading to diminished expression of pro-inflammatory cytokines and apoptosis. KPT-330 impeded the formation of the IGF1R/RanBP2/SUMO1 complex, thereby limiting IGF1R nuclear translocation, inflammation, and neuronal apoptosis, while enhancing cognitive functions and neuron proliferation. Moderate-intensity exercise effectively mitigates AD symptoms in mice, primarily by diminishing neuroinflammation, through the reduction of IGF1R Sumoylation. KPT-330, as a potential alternative to physical exercise, enhances the neuroprotective role of IGF1R by inhibiting SUMOylation through targeting XPO1, presenting a promising therapeutic strategy for AD. Show less
📄 PDF DOI: 10.1016/j.jare.2024.03.025
BACE1
Ming-Yan Yang, Dong Qi, Meng-Ying Wang +5 more · 2025 · The Journal of steroid biochemistry and molecular biology · Elsevier · added 2026-04-24
To date, glucocorticoids remain the mainstay of treatment of nephrotic syndrome (NS). However, serious side effects and development of drug-resistance following long-term use limit the application of Show more
To date, glucocorticoids remain the mainstay of treatment of nephrotic syndrome (NS). However, serious side effects and development of drug-resistance following long-term use limit the application of glucocorticoids. Protopanaxadiol (PPD) possesses activity of dissociating transactivation from transrepression by glucocorticoid receptor (GR), which may serve as a potential selective GR modulator. However, steroid-like effects of PPD in vivo are unclear and not defined. How to translate PPD into clinical practice remains to be explored. The current study explored the renoprotection and potential mechanism of PPD and its combination with steroid hormones using adriamycin-induced NS rats. Adriamycin was given intravenously to rats to induce nephropathy. The determination of proteinuria, biochemical changes and inflammatory cytokines were performed, and pathological changes were examined by histopathological examination. Immunostaining and PCR were used to analyze the expression of interesting proteins and genes. The results showed that PPD, alone and in combination with prednisone, efficiently alleviate the symptoms of NS, attenuate nephropathy, improve adriamycin-induced podocyte injury by reducing desmin and increasing synaptopodin expression. In addition, the combined treatment reduced the expression of NF-κB protein and mRNA, as well as cytokine levels, and yet increased the expression of GR protein and mRNA. PPD modulated the transactivation of GR, manifested as repressing TAT, PEPCK and ANGPTL4 mRNA expressions mediated by GR. Meanwhile, PPD inhibited elevation of blood glucose and immune organ atrophy induced by prednisone. In summary, PPD increases the therapeutic effect of prednisone in NS while effectively prevents or decreases the appearance of side effects of glucocorticoids. Show less
no PDF DOI: 10.1016/j.jsbmb.2024.106628
ANGPTL4
Ai Qian, Kexin Hu, Yawen Zhu +3 more · 2025 · Lupus science & medicine · added 2026-04-24
To investigate the effects of Qihuang Jianpi Zishen Granules (QJZG) on renal injury in SLE mice, focusing on macrophage M1/M2 polarisation mediated by the AMPK/ULK1 signalling pathway. Parameters of r Show more
To investigate the effects of Qihuang Jianpi Zishen Granules (QJZG) on renal injury in SLE mice, focusing on macrophage M1/M2 polarisation mediated by the AMPK/ULK1 signalling pathway. Parameters of renal function and proteinuria were assessed. Pathological changes in the kidney were examined using H&E, periodic acid-Schiff and Masson's trichrome staining. Serum inflammatory factor levels were quantified using ELISA. The expression levels of the glycolysis rate-limiting enzymes hexokinase 2 (HK2) and glucose transporter 1 (GLUT1) were determined, and the transcriptional levels of AMPK/ULK1 pathway components were measured using quantitative PCR. The abundance of proteins associated with AMPK/ULK1 signalling was assessed via immunoblotting. Flow cytometry was used to quantify CD86+ M1 type and CD206+ M2 type macrophage populations. Dual immunofluorescence staining was employed to visualise F4/80+CD86+ and F4/80+CD206+ coexpression patterns. Compared with the Untreated group, mice in the PRED (prednisone acetate), QJZG and 2-Deoxy-D-glucose groups exhibited improved renal histopathology, reduced levels of creatinine, blood urea nitrogen, 24-hour RRO (24-hour urinary protein), ACR (Albumin-to-Creatinine Ratio), TPCR (Urine Total Protein-to-Creatinine Ratio), tumour necrosis factor alpha, interleukin (IL)-1β, IL-12, IL-23, IL-27, HK2, GLUT1, mTOR, CD86 and iNOS messenger RNA (mRNA), CD86 and iNOS proteins, M1 macrophages, M1/M2 macrophages and F4/80+CD86 expression (p<0.05). They also displayed increased expression of transforming growth factor-beta, IL-4, IL-10, C-C motif chemokine ligand 18, AMPK, ULK1, Atg13, CD206 and Arg-1 mRNA, AMPK, ULK1, CD206 and Arg-1 proteins, M2 macrophages and F4/80+CD206 (p<0.05). QJZG effectively improved renal injury in SLE by reducing inflammation and modulating the AMPK/ULK1 signalling pathway to suppress M1 macrophage polarisation. Show less
📄 PDF DOI: 10.1136/lupus-2025-001639
IL27
Helen Williams, Habib Francis, Jasmin Huang +4 more · 2025 · Atherosclerosis plus · Elsevier · added 2026-04-24
Familial Hypercholesterolaemia (FH) is characterised by high cholesterol and premature cardiovascular disease. While hypercholesterolaemia and inflammation are both key drivers in the formation of ath Show more
Familial Hypercholesterolaemia (FH) is characterised by high cholesterol and premature cardiovascular disease. While hypercholesterolaemia and inflammation are both key drivers in the formation of atherosclerotic plaques, inflammation remains understudied in FH. Inflammatory (M1) macrophages contribute to plaque destabilisation and macrophage precursors, monocytes, can be skewed towards an inflammatory state. Aims: Determine; whether monocytes of FH individuals are inflammatory, if they readily form inflammatory macrophages, and whether this remains so in statin-treated individuals. Blood samples were collected from people with FH (statin-treated and untreated) and healthy controls. Lipid profile was obtained and monocyte inflammatory marker expression was determined by whole blood flow cytometry. Monocytes were cultured with autologous serum and resultant macrophage profile determined by flow cytometry. Total cholesterol and low-density lipoprotein cholesterol (LDL-C) were higher in the Untreated-FH group compared to the Treated-FH group and controls. In both Treated-FH and Untreated-FH groups, monocytes were inflammatory with high CD86 (M1). The ratio of inflammatory/anti-inflammatory markers (CD86/CD163) significantly correlated with LDL-C and ApoB/ApoA1 ratio across the cohort, indicating the high LDL-C of FH may promote an inflammatory monocyte profile. Monocyte-derived-macrophages from (Treated) FH individuals also had a more inflammatory profile (CD86 and CD86/CD163). Overall, monocytes show inflammatory skewing in FH individuals, even those with moderately-reduced cholesterol levels. These monocytes readily become inflammatory macrophages. This, along with subsequent inflammatory macrophage formation, could contribute to plaque destabilisation and downstream clinical events. This supports inflammatory monocyte targeting as a potential approach to reduce residual risk in FH individuals. Show less
📄 PDF DOI: 10.1016/j.athplu.2025.09.002
APOB
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
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
Ying-Ying Zhu, Shi-Yue Qin, Hai Xie +5 more · 2025 · International journal of ophthalmology · added 2026-04-24
To investigate the effects and the underlying mechanism(s) of conbercept on the phagocytosis of hard exudates (HEs) by Müller glia in diabetic retinopathy (DR). Twenty-one eyes from 17 patients with d Show more
To investigate the effects and the underlying mechanism(s) of conbercept on the phagocytosis of hard exudates (HEs) by Müller glia in diabetic retinopathy (DR). Twenty-one eyes from 17 patients with diabetic macular edema (DME) underwent optical coherence tomography (OCT) imaging to examine the changes of HEs before and after intravitreal conbercept injection (IVC). The area of HEs showed minimal change after the first IVC (1.39±1.41 to 1.38±1.3 mm Conbercept reduces HEs in DR by enhancing Müller glia phagocytosis possibly through activating PPARγ-CD36 axis, which is mediated by inhibition of VEGF signaling. Modulation of Müller glia phagocytic capacity might provide a novel therapeutic strategy to treat DR and DME. Show less
no PDF DOI: 10.18240/ijo.2025.07.07
RMC1
Long Xu, Yuanyuan Zhao, Shuxi Song +3 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor micro Show more
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor microenvironment (TME). Neutrophil extracellular traps (NETs) and oxidative stress play critical roles in tumor progression: NETs promote tumor cell adhesion, migration, and immune suppression, while oxidative stress induces DNA damage and activates pro-tumor signaling pathways. Moreover, oxidative stress is an important inducer of NETs, and their crosstalk shapes the LUAD immune microenvironment. However, systematic exploration of LUAD immunotherapeutic response prediction based on NETs and oxidative stress-related genes remains lacking. The gene set related to oxidative stress was obtained from MSigDB. The gene set related to NETs was sourced from relevant literature. Transcriptomic and clinical data were integrated from The Cancer Genome Atlas (TCGA)-LUAD (training set) and GSE31210 (validation set). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to screen gene modules and characteristic scores related to NETs and oxidative stress signatures. Differentially expressed genes (DEGs) were screened, and prognostic model was established using univariate and LASSO Cox regression. Immune infiltration was analyzed using ESTIMATE algorithm, MCP-counter and ssGSEA methods. And we developed a nomogram incorporating clinicopathological features and RiskScore model, and performed drug sensitivity analysis. Finally, the biological role of CPS1 in lung cancer cells was investigated through CCK-8, wound-healing, and Transwell experiments. 22 co-expression modules were screened, among which the brown module showed significant correlations with NETs and oxidative stress signature scores. This module was intersected with DEGs, yielding 624 overlapping genes implicated in immune-relevant pathways (like leukocyte differentiation, neutrophil activation involved in immune response). A prognostic model was established utilizing 8 key genes (ADGRE3, ARHGEF3, CD79A, CLEC7A, CPS1, EPHB2, LARGE2, and OAS3). In the TCGA database, the model demonstrated robust prognostic discrimination (area under the curve (AUC) > 0.6), with high-risk patients exhibiting shorter overall survival (OS) (p < 0.05). Its stability was validated in GSE31210 (AUC > 0.6). The RiskScore showed negative correlations with immune infiltration (like T cells, CD8 T cells, and natural killer cells) as well as immune/stromal scores. A nomogram model combining RiskScore with N staging was developed and validated, demonstrating strong predictive accuracy through calibration and decision curve analyses. High-risk patients were more sensitive to drugs like BI-2536, BMS-509744, and Pyrimethamine. Finally, in vitro tests showed that CPS1 knockdown markedly decreased the viability, migration, and invasion of lung cancer cells. The constructed prognostic model by NETs and oxidative stress-relevant genes effectively predicts LUAD prognosis, correlates with immune microenvironment characteristics, and guides drug sensitivity, providing novel insights for LUAD prognostic assessment and personalized therapy. Show less
📄 PDF DOI: 10.1186/s40001-025-03553-9
CPS1
Yuping Huang, Junguang Liao, Panpan Shen +7 more · 2025 · JCI insight · added 2026-04-24
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molec Show more
Cranial neural crest cells (CNCs) play a critical role in craniofacial bone morphogenesis, engaging in intricate interactions with various molecular signals to ensure proper development, yet the molecular scaffolds coordinating these processes remain incompletely defined. Here, we identify neurofibromin 2 (Nf2) as a critical regulator to direct CNC-derived skull morphogenesis. Genetic ablation of Nf2 in murine CNCs causes severe craniofacial anomalies, featuring declined proliferation and increased apoptosis in osteoprogenitors, impaired type I collagen biosynthesis and trafficking, and aberrant osteogenic mineralization. Mechanistically, we uncover that Nf2 serves as a molecular linker that individually interacts with FGF receptor 1 (FGFR1) and Akt through spatially segregated phosphor-sites, and structural modeling and mutagenesis identified Ser10 and Thr230 as essential residues, with Thr230 mutation selectively ablating Akt binding while preserving FGFR1 association. Strikingly, Akt inhibition phenocopied Nf2 deficiency, reducing collagen production and Nf2 phosphorylation, whereas phospho-mimetic Nf2 (T230D) rescued CNC-derived osteogenic defects in Nf2-mutant animals. Our findings underscore the physiological significance of Nf2 as a phosphorylation-operated scaffold licensing the FGFR1/AKT axis to regulate collagen type I biogenesis and trafficking, ensuring normal CNC-derived osteogenesis and craniofacial bone development, thus exposing the Nf2/FGFR1/AKT signaling axis as a therapeutic target and promising advancements in treatment of craniofacial anomalies. Show less
📄 PDF DOI: 10.1172/jci.insight.191112
FGFR1
Ziling Huang, Leyao Li, Xu Cai +3 more · 2025 · Thoracic cancer · Blackwell Publishing · added 2026-04-24
Fibroblast Growth Factor (FGF) ligands and their receptor have been identified as the potent target in non-small cell lung cancer (NSCLC). However, the clinicopathological and microenvironmental chara Show more
Fibroblast Growth Factor (FGF) ligands and their receptor have been identified as the potent target in non-small cell lung cancer (NSCLC). However, the clinicopathological and microenvironmental characteristics of FGF/FGFR in NSCLC remain poorly elucidated. Here, we summarize 4656 NSCLCs and analyze clinicopathological features in 478 FGF/FGFR altered cases. AI analysis and multiplex immunofluorescence staining are used to reveal microenvironment features. First, around 10.27% NSCLC carry FGF/FGFR variant. Squamous cell carcinoma (41.95%) is much more than adenocarcinoma (8.32%). In 118 pathogenic variant (PV) cases, the most frequent variant is FGF/FGFR copy number increase (83.05%), the second is FGFR gene fusion (11.86%). Surprisingly, CCND1 always co-amplifies with FGF19 (100.00%). Furthermore, FGF PV is an independent risk factor for poor outcomes (overall survival: HR = 3.781, disease-free survival: HR = 3.340). And one-third of FGFR3-TACC3 fusion cases show clear cytoplasm in histology. Either CCND1/FGF19 co-amplification or KRAS co-mutation is closely related to cigarette exposure, and KRAS co-mutation acts as an independent factor of poor prognosis. Finally, the FGF/FGFR1/NOTCH1 within RB1 variant group has a remarkably high ratio of inner-tumor CD8+ T cell infiltration, non-exhausted T cells, exhausted T Show less
📄 PDF DOI: 10.1111/1759-7714.70016
FGFR1
Wei Jia, Huimin Wang, Ting Feng +5 more · 2025 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
FVPB1, a novel heteropolysaccharide, was extracted from the
📄 PDF DOI: 10.3390/foods14193452
APOB
Chenlu He, Zejian Li, Hao Jiang +3 more · 2025 · Advanced materials (Deerfield Beach, Fla.) · Wiley · added 2026-04-24
Halide perovskite nanomaterials have emerged as a transformative platform for generating and manipulating polarized luminescence, offering unprecedented opportunities for next-generation optoelectroni Show more
Halide perovskite nanomaterials have emerged as a transformative platform for generating and manipulating polarized luminescence, offering unprecedented opportunities for next-generation optoelectronic technologies. This review comprehensively examines recent advances in engineering both linearly polarized luminescence (LPL) and circularly polarized luminescence (CPL) from perovskite nanostructures, focusing on structural design principles, chirality transfer mechanisms, and performance optimization strategies. Methods are systematically analyzed to achieve polarized emission, including anisotropic nanocrystal growth, chiral ligand functionalization, and liquid crystal-mediated alignment, while highlighting critical optical factors such as dissymmetry factors and photoluminescence quantum yield. Key challenges in enhancing the precision control over perovskite nanostructures, room-temperature CPL efficiency, and scalable assembly are discussed, with a forward-looking perspective on the integration of artificial intelligence (AI) to accelerate progress in the development of perovskite nanomaterials with customized polarized luminescence. By bridging fundamental insights with technological applications, this review outlines a roadmap for developing perovskite-based polarized light sources that combine high performance, stability, and manufacturability, which are key enablers for the future of quantum photonics, ultra-secure communication, and intelligent optical systems. Show less
no PDF DOI: 10.1002/adma.202507400
LPL
Xiaofan Wei, Baiwan Zhou, Juanling Li +2 more · 2025 · Frontiers in aging neuroscience · Frontiers · added 2026-04-24
To explore neurodynamic bases underlying subjective cognitive decline (SCD) based on edge-centric functional network. 211 SCD patients and 210 healthy controls (HC) were recruited from the Alzheimer's Show more
To explore neurodynamic bases underlying subjective cognitive decline (SCD) based on edge-centric functional network. 211 SCD patients and 210 healthy controls (HC) were recruited from the Alzheimer's Disease Neuroimaging Initiative. Edge time series (ETS) were obtained based on resting-state functional magnetic resonance data. The top 10% co-fluctuation signals of all time points in ETS were extracted to construct the high-amplitude frame networks, and the co-fluctuation signals from the remaining time points were used to construct the low-amplitude frame networks. In both network states, the graph theory and network-based statistics (NBS) analyses were used to compare SCD and HC. The correlation of the imaging indicators with cognitive scores and apolipoprotein E (APOE) ε4 genes was performed by Spearman correlation analysis. SCD exhibited lower peak amplitude and longer trough-to-trough duration (TTD) compared to HC. In both network states, the normalized clustering coefficient, normalized characteristic path length, small-worldness, and global efficiency of SCD were significantly reduced, and the altered nodal centralities of SCD predominantly exhibited a decreasing trend. However, the high-amplitude frame network identified more altered brain regions compared to the low-amplitude frame network. Furthermore, a SCD-related subnetwork was found in the high-amplitude frame network, which was composed of 11 brain regions and 13 edges. TTD was positively related to the number of APOE ε4 genes; the normalized characteristic path length, the betweenness centrality of right postcentral gyrus, and the connection between bilateral angular gyrus were correlated with cognitive scores. Our findings demonstrate that the edge-centric network framework reveals details of brain network alterations in SCD through different perspectives, and these alterations hold potential as novel biomarkers for SCD. Show less
📄 PDF DOI: 10.3389/fnagi.2025.1596537
APOE
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
Weidong Qin, Danxi Li, Jiawei Zhang +5 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by the absence of estrogen receptor, progesterone receptor, and HER2 expression, which limits the availability of targeted t Show more
Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by the absence of estrogen receptor, progesterone receptor, and HER2 expression, which limits the availability of targeted therapies and results in poor prognosis. Immune checkpoint blockade (ICB) therapies have emerged as promising treatments by enhancing anti-tumor immunity; however, a substantial proportion of patients with TNBC exhibit primary or acquired resistance. This resistance is largely influenced by the tumor microenvironment (TME). This study uses integrated single-cell and spatial transcriptomics to elucidate key cellular mechanisms of resistance, with particular emphasis on lipid-mediated stromal-immune interactions within the TNBC TME. This investigation encompassed analysis of single-cell RNA sequencing (scRNA-seq) data from three TNBC datasets and spatial transcriptomic data from 43 TNBC samples. Spatial niches and cell-cell interactions were identified using the Multimodal Intersection Analysis (MIA) algorithm. Experimentally, adipose-derived mesenchymal stem cells (AD-SCs) were co-cultured with MDA-MB-231 TNBC cells to generate lipid-processing CAFs (lpCAFs) and subsequently co-cultured with THP-1 macrophages. Lipid metabolism and M2 polarization of macrophages were assessed using BODIPY staining, Oil Red O, qPCR, flow cytometry and Western blotting techniques. ABCA8 ABCA8 Show less
📄 PDF DOI: 10.3389/fonc.2025.1729275
APOE
Xuehao Cui, Chao Sun, Dejia Wen +2 more · 2025 · Global heart · added 2026-04-24
Cardiovascular diseases (CVDs) are the leading global cause of mortality and disability, with prevalence increasing due to aging and risk factors like obesity and hypertension. The retina, rich in mic Show more
Cardiovascular diseases (CVDs) are the leading global cause of mortality and disability, with prevalence increasing due to aging and risk factors like obesity and hypertension. The retina, rich in microvasculature, provides a unique opportunity to investigate microvascular dysfunction linked to CVDs and other systemic vascular diseases. This study used a multifaceted approach to assess the genetic correlation and causal relationship between retinal characteristics and CVDs. Linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) analyses were conducted using genome-wide association study (GWAS) data from the UK Biobank and FinnGen datasets. A cross-sectional study was also conducted to validate the findings, collecting optical coherence tomography (OCT) images from 124 eyes (89 with CVDs and 35 healthy controls). A prediction model is based on least absolute shrinkage and selection operator (LASSO) regression to assess the risk of CVD. Using LDSC and two-sample MR, we found genetic evidence consistent with a causal effect whereby genetically proxied thinner retinal nerve fiber layer (RNFL) was associated with higher risks of hypertension and myocardial infarction (MI), while genetically proxied thicker photoreceptor inner segment/outer segment (PR-IS/OS) was associated with coronary heart disease and MI (false discovery rate [FDR] thresholds as reported). Genetically proxied thinner retinal pigment epithelium (RPE) showed an inverse association with stroke risk. Several circulating biomarkers-including lipoprotein(a) [Lp(a)], low-density lipoprotein cholesterol (LDL-C), and ApoB-exhibited MR evidence of association with multiple CVDs. In a cross-sectional cohort, retinal layer differences and their relationships with lipids were directionally consistent with the genetic findings. Retinal structural traits measured by OCT-particularly RNFL, PR-IS/OS, and RPE thickness-are best interpreted as non-invasive markers that reflect systemic vascular biology. Our MR analyses support shared etiologic pathways between retinal microstructure and CVDs rather than implying that retinal damage clinically causes cardiovascular events. Findings warrant validation in larger and more diverse populations and should not be considered definitive proof of causality. Show less
📄 PDF DOI: 10.5334/gh.1493
APOB
Xinyuan Qiu, Ruo-Ran Wang, Qing-Qian Wu +27 more · 2025 · The Journal of clinical investigation · added 2026-04-24
Impaired glucose-stimulated insulin secretion (GSIS) is a hallmark of β cell dysfunction in diabetes. Epigenetic mechanisms govern cellular glucose sensing and GSIS by β cells, but they remain incompl Show more
Impaired glucose-stimulated insulin secretion (GSIS) is a hallmark of β cell dysfunction in diabetes. Epigenetic mechanisms govern cellular glucose sensing and GSIS by β cells, but they remain incompletely defined. Here, we found that BAF60a functions as a chromatin regulator that sustains biphasic GSIS and preserves β cell function under metabolic stress conditions. BAF60a was downregulated in β cells from obese and diabetic mice, monkeys, and humans. β cell-specific inactivation of BAF60a in adult mice impaired GSIS, leading to hyperglycemia and glucose intolerance. Conversely, restoring BAF60a expression improved β cell function and systemic glucose homeostasis. Mechanistically, BAF60a physically interacted with Nkx6.1 to selectively modulate chromatin accessibility and transcriptional activity of target genes critical for GSIS coupling in islet β cells. A BAF60a V278M mutation associated with decreased β cell GSIS function was identified in human donors. Mice carrying this mutation, which disrupted the interaction between BAF60a and Nkx6.1, displayed β cell dysfunction and impaired glucose homeostasis. In addition, GLP-1R and GIPR expression was significantly reduced in BAF60a-deficient islets, attenuating the insulinotropic effect of GLP-1R agonists. Together, these findings support a role for BAF60a as a component of the epigenetic machinery that shapes the chromatin landscape in β cells critical for glucose sensing and insulin secretion. Show less
📄 PDF DOI: 10.1172/JCI177980
GIPR