👤 Mao 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, Jisen 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 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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, 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
Zihao Zhou, Yidan Zheng, Shiyan Hu +13 more · 2025 · Heart (British Cardiac Society) · added 2026-04-24
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisyste Show more
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisystem comorbidity network of CAS and clarify underlying genetic mechanisms. In 467 484 participants from the UK Biobank, observational and polygenic phenome-wide association studies evaluated associations between CAS and 1571 phenotypes, integrating disease-trajectory analyses to visualise temporal patterns. Associations replicated across observational and polygenic analyses were tested using two-sample Mendelian randomisation (MR) based on 22 CAS-related variants from FinnGen. Polygenic risk score (PRS) analyses excluding specific genes assessed their contributions, particularly LPA and plasma lipoprotein(a) (Lp(a)) levels. CAS was associated with higher risks of 42 cardiovascular and non-cardiovascular conditions, most prominently metabolic, endocrine, haematological and respiratory disorders. Temporal analyses showed that circulatory and metabolic diseases typically precede other comorbidities in CAS trajectories. MR findings were consistent with causal effects of CAS on multiple cardiovascular diseases, iron-deficiency anaemia, mental disorders and pleural effusion. When LPA variants were removed from the CAS PRS or plasma Lp(a) concentration was adjusted for, most associations lost significance, indicating a shared LPA/Lp(a)-mediated genetic pathway. CAS is embedded within a broad multisystem comorbidity network, driven largely by genetic variation at LPA and elevated Lp(a). These findings highlight pleiotropic mechanisms linking valvular calcification with systemic disease and support LPA-targeted therapies as a promising avenue for reducing the multisystem burden of CAS. Show less
no PDF DOI: 10.1136/heartjnl-2025-326058
LPA
Baoqi Li, Mingcong Xu, Bang An +8 more · 2025 · Materials horizons · Royal Society of Chemistry · added 2026-04-24
Dynamic responsive structural colored materials have drawn increased consideration in a wide range of applications, such as colorimetric sensors and high-safety tags. However, the sophisticated intera Show more
Dynamic responsive structural colored materials have drawn increased consideration in a wide range of applications, such as colorimetric sensors and high-safety tags. However, the sophisticated interactions among the individual responsive parts restrict the advanced design of multimodal responsive photonic materials. Inspired by stimuli-responsive color change in chameleon skin, a simple and effective photo-crosslinking strategy is proposed to construct hydroxypropyl cellulose (HPC) based hydrogels with multiple responsive structured colors. By controlling UV exposure time, the structural color of HPC hydrogels can be effectively controlled in a full-color spectrum. At the same time, HPC hydrogels showcase temperature and mechanical dual-responsive structural colors. In particular, the microstructure of HPC hydrogels undergoes a transition from the chiral nematic phase to the nematic phase under the action of external stretching, leading to a significant reflection of circularly polarized light (CPL) to linearly polarized light (LPL). Given the diverse responsiveness exhibited by HPC hydrogels and their unique structural transition properties under external forces, we have explored their potential applications as dynamic anti-counterfeiting labels and optical skins. This work reveals the great possibility of using structural colored cellulose hydrogels in multi-sensing and optical displays, opening up a new path for the exploration of next-generation flexible photonic devices. Show less
no PDF DOI: 10.1039/d4mh01646g
LPL
Wan Peng, Gao-Fei Li, Guo-Wang Lin +11 more · 2025 · Oncogene · Nature · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disorder primarily linked with mutations in Exostosin-1 (EXT1) and Exostosin-2 (EXT2) genes. However, not all HME cases can be exp Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disorder primarily linked with mutations in Exostosin-1 (EXT1) and Exostosin-2 (EXT2) genes. However, not all HME cases can be explained by these mutations, and its pathogenic mechanisms are not fully understood. Herein, utilizing whole-exome sequencing and genetic screening with a family trio design, we identify two novel rare mutations co-segregating with HME in a Chinese family, including a nonsense mutation (c.204G>A, p.Trp68*) in EXT1 and a missense mutation (c.893T>G, p.Phe298Cys) in FUT7. Functional assays reveal that the FUT7 mutation affects the cellular localization of FUT7 protein and regulates cell proliferation. Notably, the simultaneous loss of fut7 and ext1 in a zebrafish model results in severe chondrodysplasia, indicating a functional link between FUT7 and EXT1 in chondrocyte regulation. Additionally, we unveil that FUT7 p.Phe298Cys reduces EXT1 expression through IL6/STAT3/SLUG axis at the transcription level and through ubiquitination-related proteasomal degradation at the protein level. Together, our findings not only identify novel germline mutations in FUT7 and EXT1 genes, but also highlight the critical interaction between these genes, suggesting a potential 'second-hit' mechanism over EXT1 mutations in HME pathogenesis. This insight enhances our understanding of the mechanisms underlying HME and opens new avenues for potential therapeutic interventions. Show less
📄 PDF DOI: 10.1038/s41388-024-03254-3
EXT1
Huatao Zheng, Dan Li, Rentao Ma +3 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and phys Show more
With the aging population in China, research on preventing frailty is crucial. This study aims to investigate the independent and combined associations of the Dietary inflammatory index (DII) and physical activity (PA) with frailty among Chinese older adults. A total of 285 participants aged ≥60 years with 87 males and 186 females were recruited from Hunan Province. Daily moderate physical activity (MPA), vigorous physical activity (VPA) and light physical activity (LPA) were objectively measured using a triaxial accelerometer. A Food Frequency Questionnaire 25 (FFQ25) was used to assess the participants' dietary patterns, and DII was calculated. Six combined exposure groups were formed based on PA and DII: pro-inflammatory diet and insufficient PA group, neutral diet and insufficient PA group, anti-inflammatory diet and insufficient PA group, pro-inflammatory diet and sufficient PA group, neutral diet and sufficient PA group, and anti-inflammatory diet and sufficient PA group. Frailty was assessed using the Frailty Phenotype (FP), logistic regression analyzed the associations between dietary patterns, PA, and frailty. A total of 285 older adults participants were initially recruited, but 12 were excluded due to missing data. Consequently, 273 participants were included in the final analysis. Compared to individuals with insufficient PA, those with sufficient PA were associated with significantly lower odds of frailty (OR = 0.468, 95%CI = 0.242-0.907). Participants following an anti-inflammatory diet had significantly lower odds of frailty compared with those following a pro-inflammatory diet (OR = 0.467, 95%CI = 0.221-0.988). In the combined groups, frailty prevalence was significantly lower the group with anti-inflammatory diet and sufficient PA group (OR = 0.204, 95%CI = 0.072-0.583), compared with pro-inflammatory diet and insufficient PA group. The sensitivity analysis showed that the associations between anti-inflammatory diet and sufficient PA with frailty remained statistically significant, with the direction of the associations unchanged. These findings suggest that the results are robust. Our study indicates that adhering to an anti-inflammatory diet and maintaining sufficient PA may be associated with a lower likelihood of frailty. Achieving an adequate amount of PA and following a healthy dietary pattern may serve as potential preventive measures against frailty. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1739530
LPA
Xuan-Ling Li, Zhi-Heng Lin, Si-Ru Chen +7 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, a Show more
People with mild cognitive impairment (MCI) carry a considerable risk of developing dementia. Studies have shown that female sex hormones have long-lasting neuroprotective and anti-aging properties, and the increased risk of MCI and AD is associated with the lack of estrogen during menopause. Previous studies have shown that Tiao Geng Decoction (TGD) may have antioxidant and anti apoptotic properties, which may prevent neurodegenerative diseases. However, whether TGD is effective in improving mild cognitive impairment due to postmenopausal estrogen deficiency and its potential pharmacological mechanisms remain unclear. The aim of this study was to investigate the possible pharmacological mechanisms of TGD in preventing postmenopausal MCI. We utilized RNA-seq technology to screen for differentially expressed genes (DEGs) and enrichment pathways in the hippocampal tissue of different groups of mice. Additionally, we adopted single-cell sequencing technology to study the cell types of Alzheimer's disease (AD) group and Normal Control (NC) group, the differential marker genes of each cell subgroup, and the GO enrichment analysis of each cell type. Both RNA sequencing and single-cell sequencing results showed a significant correlation between TGD and NF-κb pathway in improving mild cognitive impairment in postmenopausal women. The experimental verification results showed that the spatial learning and memory abilities of APP/PS1 model mice were weakened after ovariectomy, and the reproductive cycle on vaginal smears was in the interphase of diestrus. The levels of serum E2, and P-tau181 in mice were significantly down regulated, while the levels of brain tissue homogenate A β 42, IL-1 β, and IL-18 were significantly up-regulated, indicating successful modeling. Combining Western blotting, RT-qPCR, and transmission electron microscopy analyses, it was found that the low estrogen environment induced by oophorectomy can activate the NF-κb signaling pathway, activate the expression of NLRP3 inflammasome and A β secretase BACE1, and induce neuroinflammatory damage in hippocampal astrocytes. These results conform to the modeling characteristics of MCI. After TGD intervention, the spatial learning and memory abilities of MCI mice were significantly improved. The pharmacological validation results indicated that high concentration doses of TGD had a more significant effect on MCI. Subsequently, we used high concentration TGD (0.32 g/ml) as the traditional Chinese medicine group for further validation, protein blotting and RT-qPCR results indicated that TGD can effectively stimulate the secretion of ER α and ER β, inhibit the NF-κb pathway, downregulate BACE1, and inhibit the expression of NLRP3 inflammasome related proteins. In addition, the immunofluorescence results of hippocampal astrocytes showed that TGD can effectively facilitate the expression of AQP1 and significantly lower the sedimentation of A β compared with the model group. Our research suggests that there is a high correlation between a low estrogen environment and the occurrence and development of MCI. TGD may regulate the ERs/NF - κ b/AQP1 signaling pathway, promote estrogen secretion, activate AQP1, reduce A β deposition, reverse MCI neuroinflammatory injury, improve mild cognitive impairment, and prevent the occurrence of AD. This study revealed for the first time that TGD may be a potential new alternative drug for preventing and improving menopausal MCI. Show less
no PDF DOI: 10.1016/j.phymed.2025.156391
BACE1
Nan Wang, Xin-Zhu Li, Xiao-Wen Jiang +10 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
no PDF DOI: 10.1007/s12035-025-05265-x
BACE1
Yu Gan, Kangning Wang, Xiang Chen +4 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Renal fibrosis is a common pathological process in various chronic kidney diseases. The accumulation of senescent renal tubular epithelial cells (TECs) in renal tissues plays an important role in the Show more
Renal fibrosis is a common pathological process in various chronic kidney diseases. The accumulation of senescent renal tubular epithelial cells (TECs) in renal tissues plays an important role in the development of renal fibrosis. Eliminating senescent TECs has been proven to effectively reduce renal fibrosis. Procyanidin C1 (PCC1) plays a senolytic role by specifically eliminating senescent cells and extending its overall lifespan. However, whether PCC1 can alleviate unilateral ureteral obstruction (UUO)-induced renal fibrosis and the associated therapeutic mechanisms remains unclear. Here, we observed a marked increase in senescent TECs within obstructed human renal tissue and demonstrated the positive correlation between the accumulation of senescent TECs and renal fibrosis in UUO-induced renal fibrosis in mice. We found that PCC1 reduced the number of senescent TECs, restored the regenerative phenotype in kidneys with reduced fibrosis, and improved tubular repair after UUO-induced injury. In vitro, PCC1 effectively cleared senescent HK2 cells by inducing apoptosis via ANGPTL4/NOX4 signaling. Incubation with culture medium from senescent HK2 cells promoted fibroblast activation, whereas PCC1 impeded profibrotic effects by downregulating senescence-associated secretory phenotype (SASP) factors from senescent HK2 cells. Therefore, PCC1 alleviated interstitial renal fibrosis not only by clearing senescent TECs and improving tubular repair but also by indirectly attenuating myofibroblast activation by reducing the level of SASP. In summary, PCC1 may be a novel therapeutic senolytic agent for treating renal fibrosis. Show less
no PDF DOI: 10.1096/fj.202402558R
ANGPTL4
Zhen Guo, Jing Su, Lu Liu +8 more · 2025 · Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · Elsevier · added 2026-04-24
Precise differential diagnosis between lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) and marginal zone lymphoma (MZL) remains a challenging issue because of overlapping clinicopath Show more
Precise differential diagnosis between lymphoplasmacytic lymphoma/Waldenström macroglobulinemia (LPL/WM) and marginal zone lymphoma (MZL) remains a challenging issue because of overlapping clinicopathological and immunophenotypic features. In the present study, the differential diagnostic potential of CD180 was assessed by determining its expression patterns in patients with MZL and LPL/WM through flow cytometry. The results indicated that LPL/WM cases exhibited a complete absence of CD180 expression on malignant B cells, whereas MZL cases showed robust CD180 expression (P < .001). Receiver operating characteristic analysis demonstrated that CD180 expression percentage showed optimal diagnostic accuracy in LPL/WM and MZL cases (area under the curve = 0.998, sensitivity = 100%, and specificity = 98.0%), with a further improvement in differentiation potential by the CD180 mean fluorescence intensity ratio (lymphocytes/monocytes) of ≤ 0.47 (area under the curve = 0.937). Moreover, although the MYD88 Show less
no PDF DOI: 10.1016/j.modpat.2025.100919
LPL
Xiaolong Li, Fan Ding, Lu Zhang +7 more · 2025 · BMC public health · BioMed Central · added 2026-04-24
The incidence of Type 2 Diabetes Mellitus (T2DM) continues to rise steadily, significantly impacting human health. Early prediction of pre-diabetic risks has emerged as a crucial public health concern Show more
The incidence of Type 2 Diabetes Mellitus (T2DM) continues to rise steadily, significantly impacting human health. Early prediction of pre-diabetic risks has emerged as a crucial public health concern in recent years. Machine learning methods have proven effective in enhancing prediction accuracy. However, existing approaches may lack interpretability regarding underlying mechanisms. Therefore, we aim to employ an interpretable machine learning approach utilizing nationwide cross-sectional data to predict pre-diabetic risk and quantify the impact of potential risks. The LASSO regression algorithm was used to conduct feature selection from 30 factors, ultimately identifying nine non-zero coefficient features associated with pre-diabetes, including age, TG, TC, BMI, Apolipoprotein B, TP, leukocyte count, HDL-C, and hypertension. Various machine learning algorithms, including Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB), Artificial Neural Networks (ANNs), Decision Trees (DT), and Logistic Regression (LR), were employed to compare predictive performance. Employing an interpretable machine learning approach, we aimed to enhance the accuracy of pre-diabetes risk prediction and quantify the impact and significance of potential risks on pre-diabetes. From the China Health and Nutrition Survey (CHNS) data, a cohort of 8,277 individuals was selected, exhibiting a disease prevalence of 7.13%. The XGBoost model demonstrated superior performance with an AUC value of 0.939, surpassing RF, SVM, DT, ANNs, Naive Bayes, and LR models. Additionally, Shapley Additive Explanation (SHAP) analysis indicated that age, BMI, TC, ApoB, TG, hypertension, TP, HDL-C, and WBC may serve as risk factors for pre-diabetes. The constructed model comprises nine easily accessible predictive factors, which prove highly effective in forecasting the risk of pre-diabetes. Concurrently, we have quantified the specific impact of each predictive factor on the risk and ranked them based on their influence. This result may serve as a convenient tool for early identification of individuals at high risk of pre-diabetes, providing effective guidance for preventing the progression of pre-diabetes to T2DM. Show less
📄 PDF DOI: 10.1186/s12889-025-22419-7
APOB
Huang Hui, Yang Yu, Liang Yiwei +3 more · 2025 · BMC pediatrics · BioMed Central · added 2026-04-24
This study aimed to investigate the genetic etiology and clinical features of non-syndromic pediatric obesity in a large Chinese cohort, providing insights into the genetic profile and its correlation Show more
This study aimed to investigate the genetic etiology and clinical features of non-syndromic pediatric obesity in a large Chinese cohort, providing insights into the genetic profile and its correlation with clinical phenotypes. We enrolled 391 children, aged 7-14 years, diagnosed with non-syndromic pediatric obesity at Jiangxi Provincial Children's Hospital from January 2020 to June 2022. Whole-exome sequencing was employed to identify potential genetic causes, focusing on 79 candidate genes associated with obesity. Multivariate logistic regression analysis was performed on the clinical data of the non-syndromic obesity gene-positive group and the gene-negative group. Among the 391 patients, 32 (8.2%) carried 18 non-syndromic obesity genes, with UCP3 and MC4R being the most common. Seven cases (1.8%) were rated as likely pathogenic by the American College of Medical Genetics and Genomics (ACMG). Clinical phenotype and genetic correlation analysis revealed that urinary microalbumin, fT4, GGT, uric acid, serum phosphorus, paternal weight, family history, impaired glucose tolerance (IGT), non-HDL cholesterol (non-HDL-C), and metabolic syndrome (MetS) showed significant statistical differences (P < 0.05). Serum phosphorus is an independent risk factor associated with genetic predispositions to obesity in children and adolescents (P < 0.05). Our findings highlight the genetic heterogeneity of non-syndromic pediatric obesity and identify UCP3 and MC4R as potential hotspot genes in the Chinese population. The study underscores the potential of genetic testing for early diagnosis and personalized management of pediatric obesity. Show less
📄 PDF DOI: 10.1186/s12887-025-05702-9
MC4R
Alexa Canchola, Keyuan Li, Kunpeng Chen +12 more · 2025 · ACS nano · ACS Publications · added 2026-04-24
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokine Show more
A comprehensive understanding of protein corona (PC) composition is critical for engineering nanoparticles (NPs) with optimal safety and therapeutic performance, because the PC governs NP pharmacokinetics, biodistribution, and cellular interactions. Yet systematic analyses are hampered by the absence of standardized, richly annotated data sets. Here, we introduce the Protein Corona Database (PC-DB), which compiles data from 83 studies (2000-2024) and integrates 817 NP formulations with quantitative profiles of 2497 adsorbed proteins. The PC-DB exposes pronounced heterogeneity in NP materials (metal 28.8%, silica 22.8%, lipid-based 14.8%), surface modifications, sizes (1-1400 nm), and ζ-potentials (-70 to +70 mV). Subsequent meta-analysis shows that silica, polystyrene, and lipid-based NPs smaller than 100 nm with moderately negative to neutral ζ-potentials preferentially bind the lipoproteins APOE and APOB-100, which are linked to receptor-mediated uptake and enhanced delivery efficiency. In contrast, metal and metal-oxide NPs carrying highly negative surface charge enrich complement component C3, indicating a greater likelihood of immune recognition and clearance. Interpretable machine learning models (LightGBM and XGBoost; ROC-AUC > 0.85) confirm NP size, ζ-potential, and incubation time as the most influential predictors of protein adsorption. These results delineate how physicochemical parameters dictate PC composition and illustrate the power of predictive modeling to guide rational NP design. Show less
📄 PDF DOI: 10.1021/acsnano.5c08608
APOB
Jie Sheng, Qin Lin, Yizhuo Sun +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Heart failure (HF) as the terminal stage of various cardiac diseases, its underlying molecular mechanisms still remain elusive. Emerging evidence have implicated long noncoding RNAs (lncRNAs) play a m Show more
Heart failure (HF) as the terminal stage of various cardiac diseases, its underlying molecular mechanisms still remain elusive. Emerging evidence have implicated long noncoding RNAs (lncRNAs) play a multifaceted role in the progression of cardiac hypertrophy and HF. Here, it is identified that a lncRNA forkhead box O6, opposite strand (Foxo6os) is significantly downregulated in murine HF model induced using transverse aortic constriction (TAC). Knockdown of Foxo6os accelerates cardiomyocyte hypertrophy, reflects as elevated expression of atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), and myosin heavy chain 7 (MYH7). Conversely, Foxo6os overexpression can improve cardiac function and alleviate adverse cardiac remodeling. Mechanistically, Foxo6os directly interacts with myosin-binding protein-C (MYBPC3), which then recruits protein kinase C alpha (PKC-α) to facilitate MYBPC3 phosphorylation, resulting in maintaining myocardial contractility and postponing HF progression. Therefore, these findings underscore the critical role of Foxo6os in preserving cardiomyocyte contractile function, suggesting a potential for Foxo6os as a novel therapeutic target of HF. Show less
📄 PDF DOI: 10.1002/advs.202507365
MYBPC3
Shengwang Jiang, Chaoyun Yang, Chen Ji +6 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Lia Show more
This study aims to investigate the effect of fermented onion on Liangshan black sheep's growth performance, health, meat quality, and rumen metabolite profiles. A total of 80 four-month-old female Liangshan black sheep were randomly divided into four groups of five replicate pens (four sheep per pen). Sheep were fed a basal diet supplemented with 0 (control), 10, 20% or 30% fermented onion. Compared to that of the control group, dietary supplementation with 20% fermented onion improved final body weight, ADG and ADFI; enhanced GPT and GOT activities and increased IgA, IgG, IgM, C3, and C4 levels; increased the levels of IL-4, IL-10, TGF- Show less
📄 PDF DOI: 10.3389/fvets.2025.1695023
LPL
Y H Wang, X X Zhang, Y H Guo +8 more · 2025 · Zhonghua wai ke za zhi [Chinese journal of surgery] · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112139-20250221-00088
IL27
Guofeng Xing, Li Chen, Lizhi Lv +5 more · 2025 · Journal of cardiovascular development and disease · MDPI · added 2026-04-24
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertroph Show more
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertrophic (HCM, 22), arrhythmogenic right ventricular (ARVC, 7), and restrictive (RCM, 2). Clinical data, imaging, labs, and family histories were collected, with whole-exome sequencing (WES) identifying disease-causing variants classified via ACMG guidelines. Statistical analysis revealed a median age of 11 years, a proportion of 58% male participants, and ethnic diversity (21 northern Han, 29 southern Han, 5 minorities). In the cohort, 13 cases had an LVEF below 35%. Pathogenic/likely pathogenic (P/LP) variants were found in 21.8% of the patients, and variants of uncertain significance (VUS) were present in 38.2%, with Show less
📄 PDF DOI: 10.3390/jcdd12120466
MYBPC3
Hao Xu, Junjie Ma, Nanjun Li +6 more · 2025 · NPJ precision oncology · Nature · added 2026-04-24
Thyroid cancer, the most common endocrine malignancy, is characterized by a unique and complex tumor microenvironment (TME). To unravel the high tumor heterogeneity and molecular mechanisms driving ca Show more
Thyroid cancer, the most common endocrine malignancy, is characterized by a unique and complex tumor microenvironment (TME). To unravel the high tumor heterogeneity and molecular mechanisms driving cancer progression, we performed single-cell RNA sequencing (scRNA-seq) analysis, enabling a comprehensive exploration of cellular diversity and molecular dynamics at single-cell resolution. We employed Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and subsequent identification of cellular clusters. Differential gene expression analysis across subclusters was conducted using the FindAllMarkers function, while the DoHeatmap function was utilized to visualize the distribution of differentially expressed genes. The AUCell algorithm was applied to evaluate pathway enrichment within specific cell subtypes. To decipher cellular communication networks, we integrated the CellChat and NicheNet algorithms, which revealed intricate intercellular signaling interactions. Finally, multiplex immunohistochemistry (mIHC) was performed to validate key cellular interactions identified in silico. By analyzing 405,077 single cells from 50 thyroid cancer samples (including papillary, anaplastic, and metastatic tumors) and 14 normal thyroid tissues, we identified four major cellular subpopulations through unbiased clustering based on gene expression patterns and representative cellular markers. The TME was found to encompass diverse immune, endothelial, and mesenchymal cell subtypes, including novel populations such as CD4 + HSPA1A + T cells. Functional pathway enrichment analysis highlighted the roles of abundant cell types in tumor progression. Cell-cell communication analysis uncovered potential immunotherapeutic targets and revealed critical crosstalk among hub niche cells, including APOE+ macrophages, EMT-like cancer-associated fibroblasts (CAFs), and RBP7+ endothelial cells. These findings were further validated by multiplex immunohistochemistry, confirming the spatial organization and interactions of these cell populations within the TME. Our study provides a comprehensive single-cell transcriptomic atlas of thyroid cancer, offering profound insights into tumor heterogeneity, the functional roles of key niche cells, and potential biomarkers for anticancer therapy. These findings not only enhance our understanding of thyroid cancer biology but also pave the way for the development of novel therapeutic strategies targeting the TME. Show less
📄 PDF DOI: 10.1038/s41698-025-00924-7
APOE
Yiqiao Wang, Shihao Huang, Yangbai Cai +5 more · 2025 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
Programmed cell death protein 5 (PDCD5) is involved in apoptosis and is regarded as a tumor suppressor in various tumors. However, its role and underlying molecular mechanisms in hepatocellular carcin Show more
Programmed cell death protein 5 (PDCD5) is involved in apoptosis and is regarded as a tumor suppressor in various tumors. However, its role and underlying molecular mechanisms in hepatocellular carcinoma (HCC) remain unclear. PDCD5-overexpressing cell and xenograft tumor models were developed. Cell Counting Kit-8, 5-Ethynyl-2'-deoxyuridine, wound healing, Transwell, flow cytometry, immunohistochemistry, and hematoxylin-eosin staining were employed to explore the effects of PDCD5 on HCC cell behaviors and tumor growth. The enzyme-linked immunosorbent assay and western blot were used to detect pyroptosis-related marker levels. The molecular mechanisms underlying PDCD5's role in HCC were investigated through transcriptome sequencing and coimmunoprecipitation. SRI-011381, a TGF-β signaling activator, was applied to evaluate the impact of PDCD5 in modulating the TGF-β/Smad2/3/Snail pathway. PDCD5 expression was reduced in HCC cells. Overexpression of PDCD5 inhibited HCC cell proliferation, migration, invasion, and xenograft tumor growth. Additionally, PDCD5 overexpression promoted apoptosis and pyroptosis, with corresponding increases in inflammatory factors and Caspase-1, GSDMD, and NLRP3 protein levels. Mechanistically, PDCD5 bound to receptor-regulated Smads (Smad2/3), inhibiting the TGF-β pathway. Treatment with the TGF-β pathway activator SRI-011381 significantly counteracted the inhibitory effects of PDCD5 overexpression on HCC progression. Our findings suggest that PDCD5 impedes the progression of HCC by promoting pyroptosis via regulation of TGF-β/Smad2/3/Snail pathway, which could be a possible therapeutic target for HCC. Show less
no PDF DOI: 10.1016/j.bbadis.2025.167696
SNAI1
Lan Zhou, Xin Li, Zihan Ji +9 more · 2025 · Molecular biotechnology · Springer · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are li Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are linked to HME pathogenesis, with EXT1 mutation being the most frequent. The aim of this study was to generate a mice model with Ext1 gene editing to simulate human EXT1 mutation and investigate the genetic pathogenicity of Ext1 through phenotypic analyses. We designed a pair of dual sgRNAs targeting exon 1 of the mice Ext1 gene for precise deletion of a 46 bp DNA fragment, resulting in frameshift mutation of the Ext1 gene. The designed dual sgRNAs and Cas9 proteins were injected into mice zygotes cytoplasm. A total of 14 mice were obtained via embryo transfer, among which two genotypic chimera mice had a deletion of the 46 bp DNA fragment in exon 1 of the Ext1 gene. By hybridization and breeding, we successfully generated heterozygous mice with edited Ext1 gene (Ext Show less
📄 PDF DOI: 10.1007/s12033-024-01325-0
EXT1
Xiangyang Li, Xiaomin Zhang, Nina Wei +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10. Show more
Hyperlipidemia and its associated hepatic steatosis pose significant global health burdens, necessitating novel therapeutic strategies. High-fat diet (HFD)-fed C57BL/6 mice received TAC (2.5, 5.0, 10.0 g/L) or simvastatin for 2 weeks. Metabolic parameters, serum lipid profiles, hepatic function markers, and histopathology were systematically analyzed. Molecular pathways were interrogated through qPCR, Western blot, and pharmacological inhibition of AMPK (Compound C) and PPARα (GW6471). TAC treatment demonstrated significant dose-dependent improvements across multiple parameters. Compared to HFD controls, TAC reduced body weight by 21.3% and liver index by 18.7%, while lowering fasting blood glucose levels by 32.4%. Serum analyses showed substantial reductions in total cholesterol (46.2%), triglycerides (38.5%), and LDL-cholesterol (52.1%), accompanied by a 29.8% increase in HDL-cholesterol. Hepatic function improved markedly, with ALT and AST levels decreasing by 57.3% and 49.6% respectively. Histopathological examination revealed a 68.4% reduction in hepatic lipid accumulation. At the molecular level, TAC treatment resulted in a 2.7-fold increase in AMPK phosphorylation while significantly reducing HMGCR expression by 63.1% and nuclear SREBP-1c levels by 71.5%. Concurrently, TAC upregulated PPARα and LXRα expression by 3.1-fold and 2.4-fold respectively, leading to enhanced expression of lipolytic enzymes LPL and HL by 2.8-fold and 2.1-fold. These beneficial effects were completely abolished by co-treatment with pathway-specific inhibitors. TAC ameliorates hyperlipidemia and hepatic steatosis through dual modulation of AMPK/SREBP-1c-mediated lipid synthesis and PPARα/LXRα-driven lipolysis, presenting a multifaceted therapeutic approach for metabolic disorders. Show less
📄 PDF DOI: 10.3389/fphar.2025.1662325
LPL
Yue Xu, Yuan Zhou, Kun Li +3 more · 2025 · Human genomics · BioMed Central · added 2026-04-24
Phosphorylation is a crucial post-translational modification mechanism that enhances proteomic diversity, and its malfunction has been confirmed to be associated with complex traits, especially brain Show more
Phosphorylation is a crucial post-translational modification mechanism that enhances proteomic diversity, and its malfunction has been confirmed to be associated with complex traits, especially brain disorders. One of the factors contributing to this malfunction is the missense mutations given that they may alter the peptides flanking the phosphorylated residues. However, the specific effects of these missense mutations on phosphorylation remain unclear. To ascertain these, a deep learning phosphorylation prediction model (DeepMEP), which is the first to be developed on a Chinese-brain-specific phosphorylation dataset (CBMAP), was established to bridge the phosphorylation and peptides. The impact of each missense mutation on phosphorylation was subsequently quantified based on the differences between the outputs of reference and mutant protein sequences. A permutation test adjusting for the confounding factors was finally employed to estimate the enrichment for high-impact mutations in disease-associated genomic loci. DeepMEP achieved superior predictive performance compared with other existing tools on both CBMAP and publicly available datasets. Enrichment analysis revealed the high-impact mutations were significantly enriched in GWAS signals for Alzheimer’s disease (AD) and Parkinson’s disease (PD). The corresponding genes of those missense mutations overlapping with GWAS included Our study demonstrated that DeepMEP effectively captured the impact of missense mutations on phosphorylation and highlighted an enrichment of high-impact mutations in AD- and PD-associated genomic loci. The online version contains supplementary material available at 10.1186/s40246-025-00898-4. Show less
📄 PDF DOI: 10.1186/s40246-025-00898-4
APOE
Jing Liu, Junshuang Wang, Shuang Lv +7 more · 2025 · PloS one · PLOS · added 2026-04-24
Radiation-induced brain injury (RIBI) is a significant complication following radiotherapy for brain tumors, leading to neurocognitive deficits and other neurological impairments. This study aims to i Show more
Radiation-induced brain injury (RIBI) is a significant complication following radiotherapy for brain tumors, leading to neurocognitive deficits and other neurological impairments. This study aims to identify potential biomarkers and therapeutic targets for RIBI by utilizing advanced proteomic techniques to explore the molecular mechanisms underlying RIBI. A rat model of RIBI was established and subjected to whole-brain irradiation (30 Gy). Tandem mass tagging (TMT)-based quantitative proteomics, combined with high-resolution mass spectrometry, was used to identify differentially expressed proteins (DEPs) in the brain tissues of irradiated rats. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to identify the biological processes and pathways involved. Protein-protein interaction (PPI) networks were constructed to identify key hub proteins. A total of 35 DEPs were identified, including PHLDA3, APOE and CPE. GO enrichment analysis revealed that the DEPs were mainly involved in lipid transport, cell adhesion, and metabolic processes. KEGG analysis highlighted the enrichment of pathways related to metabolism, tight junctions, and PPAR signaling. APOE was identified as a key hub protein through PPI network analysis, indicating its potential role in RIBI pathophysiology. Immunohistochemistry further validated the increased expression of PHLDA3, APOE, and CPE in the brain tissue of irradiated rats. This study provides valuable insights into the molecular mechanisms of RIBI by identifying key proteins and their associated pathways. The findings suggest that these proteins, particularly APOE and PHLDA3, could serve as potential biomarkers and therapeutic targets for clinical intervention in RIBI. These results not only enhance our understanding of RIBI's molecular pathology but also open new avenues for the development of targeted therapies to mitigate radiation-induced neurotoxicity. Show less
📄 PDF DOI: 10.1371/journal.pone.0337608
APOE
Ruotong Li, Wenye Zhao, Jiaxin Zhang +7 more · 2025 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
The global increase in muscle weakness poses a critical public health concern. Nutritional interventions that improve muscular function hold promise as a therapeutic potential. Vitamin A (VA) and its Show more
The global increase in muscle weakness poses a critical public health concern. Nutritional interventions that improve muscular function hold promise as a therapeutic potential. Vitamin A (VA) and its active metabolites have been implicated in muscle development and the transformation of muscle fiber types. However, conventional VA formulations are restricted by poor stability and low bioavailability. In this study, a stable Nano VA was utilized to systematically evaluate its effects on muscle development and exercise performance in mice, as well as to explore its underlying mechanisms. A total of 44 male C57BL/6J mice were randomly divided into four groups: (i) normal control (NC), (ii) 5 mg/kg Nano VA (5 NVA), (iii) 10 mg/kg Nano VA (10 NVA), and (iv) 10 mg/kg VA (10 VA). The 10 NVA group demonstrated significantly improved muscle strength and swimming endurance, compared with the NC group. Further examination suggested a significant increase in myofiber diameter, cross-sectional area, and the content of fast-twitch fibers. Additionally, Nano VA treatment improved glucose tolerance and insulin sensitivity. To elucidate the mechanism by which Nano VA enhances muscle locomotor ability, transcriptomics and metabolomics data identified 111 differentially expressed genes and 253 differential metabolites. Of these, Angptl4, Ppp1r3a, and Cyp26b1 were identified as candidate regulators of muscle development and myofiber type transformation. In conclusion, Nano VA regulates muscle development and promotes muscle fiber type conversion, thus improving muscle strength and endurance in mice. Moreover, Nano VA facilitates mitigating and improving myasthenia gravis-related conditions. Show less
no PDF DOI: 10.1096/fj.202501417RR
ANGPTL4
Zhigang Lei, Yu Wu, Weijie Xue +15 more · 2025 · Hepatology (Baltimore, Md.) · added 2026-04-24
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critica Show more
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critical homeostasis regulator, but its function in liver immune homeostasis is unknown. We aimed to clarify the role of hepatocyte FoxO1 in liver immune homeostasis and inflammation. Human liver FoxO1 expression and its association with inflammation were analyzed in patients with various inflammation-related liver diseases. Hepatocyte-specific Foxo1 knockout (FoxO1 △hepa ) mice were established. Hepatocyte-specific gene interference was employed in alcoholic hepatitis and hepatic schistosomiasis murine models. Transcriptomic, single-cell RNA sequencing, and CUT&Tag analyses were performed to elucidate the underlying mechanisms. Hepatocyte FoxO1 levels in human inflammatory livers declined prevalently and were inversely correlated with inflammation and fibrosis. Around 15-18 weeks after birth, FoxO1 △hepa mice exhibited mild spontaneous hepatic inflammation with natural killer T (NKT) cell and neutrophil accumulation. NKT cell depletion in FoxO1 △hepa mice with alcoholic hepatitis or hepatic schistosomiasis (HS) significantly reduced neutrophil accumulation and protected against liver inflammation and damage. Mechanistically, FoxO1 promoted retinoic acid synthesis to induce hepatocyte CD1d expression, which is necessary for regulating NKT cell apoptosis. Innovatively, decreased JMJD1C expression in hepatocytes caused histone H3 lysine 9 (H3K9) dimethylation at the Foxo1 promoter, repressing its transcription and disrupting local immune homeostasis. Our findings uncover a hitherto unrecognized mechanism for hepatocyte-based control of liver inflammation, in which hepatocyte FoxO1 maintained by JMJD1C restrains local NKT cells and neutrophils via CD1d induction, providing promising targets for inflammatory liver diseases. Show less
no PDF DOI: 10.1097/HEP.0000000000001590
JMJD1C
Juan Shen, Weiming Liang, Ruizhen Zhao +33 more · 2025 · iMeta · Wiley · added 2026-04-24
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and sp Show more
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and specific pathogen-free (SPF) mice using spatial transcriptomics, single-cell RNA sequencing, and targeted bile acid metabolomics across multiple organs, we systematically assessed how the gut microbiota's absence affected organ morphology, immune homeostasis, bile acid, and lipid metabolism. Through integrated analysis, we detect marked aberration in B, myeloid, and T/natural killer cells, altered mucosal zonation and nutrient uptake, and significant shifts in bile acid profiles in feces, liver, and circulation, with the alternate synthesis pathway predominant in GF mice and pronounced changes in bile acid enterohepatic circulation. Particularly, autophagy-driven lipid droplet breakdown in ileum epithelium and the liver's zinc finger and BTB domain-containing protein (ZBTB20)-Lipoprotein lipase (LPL) (ZBTB20-LPL) axis are key to plasma lipid homeostasis in GF mice. Our results unveil the complexity of microbiota-host interactions in the crosstalk between commensal gut bacteria and the host. Show less
📄 PDF DOI: 10.1002/imt2.272
LPL
Jiawei Li, Ximei Li, Jiamin Tian +5 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Lower intramuscular fat (IMF) and excessive abdominal fat reduce carcass quality in broilers. The study aimed to investigate the effects of dietary VD
📄 PDF DOI: 10.3389/fvets.2025.1542637
APOB
Rongrong Luo, Xiying Li, Ruyun Gao +13 more · 2025 · Genomics, proteomics & bioinformatics · Oxford University Press · added 2026-04-24
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for det Show more
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for detecting early-stage lung adenocarcinoma (Early-LUAD) by employing a multi-step approach, including Human Proteome Microarray (HuProtTM) discovery, focused microarray verification, and ELISA validation, on 1246 individuals consisting of 634 patients with Early-LUAD (stage 0-I), 280 patients with benign lung disease (BLD), and 332 normal healthy controls (NHCs). HuProtTM selected 417 IgG/IgM candidates, and focused microarray further verified 55 significantly elevated IgG/IgM autoantibodies targeting 32 tumor-associated antigens in Early-LUAD compared to BLD/NHC/BLD+NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and a specificity of 77.0% or 80.0% for distinguishing Early-LUAD from BLD or NHC in ELISA validation. Positive predictive values for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9-20 mm, and > 20 mm significantly increased from 47.27%, 52.00%, and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13%, and 87.88% (10-autoantibody panel combined with LDCT), respectively. The combined risk score (CRS), based on the 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified the risk for Early-LUAD. Individuals with 10 ≤ CRS ≤ 25 and CRS > 25 indicated a higher risk of Early-LUAD compared to the reference (CRS < 10), with adjusted odds ratios of 5.28 [95% confidence interval (CI): 3.18-8.76] and 9.05 (95% CI: 5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules. Show less
no PDF DOI: 10.1093/gpbjnl/qzae085
WWP2
Yifei Dou, Ying Li, Meng Zhang · 2025 · Wei sheng yan jiu = Journal of hygiene research · added 2026-04-24
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 p Show more
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 police officers were selected using cluster random sampling in the Inner Mongolia Autonomous Region between September and December 2021. Participants completed a basic information questionnaire and the Pittsburgh sleep quality index(PSQI). Latent profile analysis(LPA) was employed to examine heterogeneity in sleep quality, and multinomial Logistic regression was used to identify associated factors of the latent profiles. The mean age of participants was(43.08±8.98) years. The sample comprised 920 males(79.2%) and 242 females(20.8%), 987(84.9%) were married and 175(15.1%) were single, 644(55.4%) had a high school education or below, and 518(44.6%) had college education or above. By department, 607(52.2%) worked in grassroots police stations, 200(17.2%) were criminal police, and 355(30.6%) served in other units. Significant heterogeneity in sleep quality was identified, revealing four distinct latent classes: good sleep group(n=821, 70.6%), moderate sleep group(n=46, 4.0%), sleep-disordered group(n=249, 21.4%), and medication-assisted sleep group(n=46, 4.0%). Using the good sleepers as the reference group, multinomial Logistic regression indicated that older age was a significant risk factor for belonging to the medication-assisted sleep group(OR=1.348, 95%CI 1.078-1.822). Higher education level was a protective factor against membership in the moderate sleep group(OR=4.101, 95%CI 1.304-12.893). Serving as a grassroots police station officer or criminal police officer was a significant risk factor for membership in both the moderate sleep group(OR = 3.329, 95%CI 1.338-8.284; OR=4.188, 95%CI 1.415-12.396) and sleep-disordered group(OR=1.701, 95%CI 1.196-2.420; OR=1.587, 95%CI 1.073-2.533). Sleep quality among police officers demonstrates significant heterogeneity. Age, police department assignment, and educational level are key associated factors of distinct latent classes of sleep quality. Show less
no PDF DOI: 10.19813/j.cnki.weishengyanjiu.2025.05.015
LPA
Tianrui Liu, Feixiang Yang, Zhige Wang +7 more · 2025 · Prostate international · Elsevier · added 2026-04-24
The causal relationships between the gut microbiota and prostate cancer, prostatitis, and benign prostatic hyperplasia remain uncertain. We intend to identify the causal connections between the gut mi Show more
The causal relationships between the gut microbiota and prostate cancer, prostatitis, and benign prostatic hyperplasia remain uncertain. We intend to identify the causal connections between the gut microbiota and prostatic diseases and investigate the potential mechanisms involved. A two-sample Mendelian randomization (MR) analysis was conducted to elucidate the impact of 196 gut microbiota on prostatic diseases risk. Reverse MR, linkage disequilibrium regression score (LDSC), and colocalization analyses were performed to strengthen causal evidence. Phenome-wide MR (Phe-MR) analysis was used to evaluate the potential side effects of targeting the detected gut microbiota. We designed a two-step MR study to assess the mediating effects of sex hormones, blood metabolites, and proteins. According to the MR analyses, 31 bacterial taxa were causally associated with prostatic diseases, of which 23 types were newly identified. In addition, Our study represents the first comprehensive exploration of the causal effects of the gut microbiota on prostatic diseases and reveals the mediating effects of sex hormones and blood metabolites on the "gut-prostate axis." Show less
📄 PDF DOI: 10.1016/j.prnil.2024.11.004
FGFR1
Chaojie Ye, Chun Dou, Dong Liu +13 more · 2025 · Nature communications · Nature · added 2026-04-24
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide assoc Show more
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide association study approaches on homeostatic model assessment for insulin resistance, insulin resistance index, fasting insulin, and ratio of triglycerides to high-density lipoprotein cholesterol from MAGIC and UK Biobank to develop a comprehensive phenotype ('mvIR'), and identify 217 independent loci, including 24 novel loci. The mvIR is causally associated with higher risks of 17 cardiometabolic diseases and five aging phenotypes, independent of adiposity and sarcopenia. We outline 21 of 2644 druggable genes for insulin resistance by Mendelian randomization and colocalization, where six genes (AKT1, ERBB3, FCGR1A, FGFR1, LPL, NR1H3) encode targets for approved drugs with consistent directions in alleviating insulin resistance, with no significant side effects revealed by phenome-wide association study. This study uncovers novel loci and therapeutic targets to inform strategies promoting insulin resistance-centered cardiometabolic health and longevity. Show less
📄 PDF DOI: 10.1038/s41467-025-64985-9
FGFR1
Dan Li, Mi Zhou, Xiaomei Song · 2025 · Frontiers in aging · Frontiers · added 2026-04-24
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity beh Show more
Cognitive decline is prevalent among older adults and may be associated with their daily activity behaviours. However, no studies have examined how cognitive decline affects older adults' activity behaviours within a 24-h framework. This study investigates the relationship between cognitive function and 24-h activity behaviours in older adults, further exploring whether these associations differ by sex. This study analyses data from the eighth wave of the Survey of Health, Ageing and Retirement in Europe, conducting a cross-sectional analysis of 814 older adults. Cognitive function was assessed using the SHARE-Cog tool, encompassing 10-word immediate recall, 10-word delayed recall, verbal fluency, and self-reported memory. 24-h activity behaviours (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], sedentary behaviour [SB], and sleep) were objectively measured with thigh-worn accelerometers. Compositional multivariate linear regression models were constructed using compositional data as the response variable, with cognitive function measures as predictors. Higher MVPA was linked to better cognitive outcomes (verbal fluency, 10-word immediate recall, and 10-word delayed recall) while SB and longer sleep related to poorer performance, with these associations being stronger in women (model p ≤ 0.001). Among women, cognitive outcomes were significantly associated with all activity behaviours (p range = 0.010-0.045). Women who self-reported poor memory and scored 0 on the verbal fluency spent approximately 45% of their day in SB, whereas those reporting excellent memory and scoring 60 spent 40.06% (37.18%, 42.86%) and 36.41% (31.53%, 41.10%) of their day sedentary, respectively. In contrast, men's 24-h activity composition did not vary significantly with cognitive function (p range = 0.051-0.845). Older adults with better cognitive function tend to engage in more PA and reduce sedentary and sleep time. This relationship differed by sex, with females' activity behaviours being more sensitive to cognitive function changes. These findings suggest that interventions promoting healthy lifestyles in older adults should account for cognitive function, particularly in females. Show less
📄 PDF DOI: 10.3389/fragi.2025.1686847
LPA