👤 Fengjuan Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaowei Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, Yajuan Liu, Yaling Liu, Yalu Liu, Yan Liu, Yan-Li Liu, Yanan Liu, Yanchao Liu, Yanchen Liu, Yandong Liu, Yanfei Liu, Yanfen Liu, Yanfeng Liu, Yang Liu, Yange Liu, Yangfan Liu, Yangfan P Liu, Yangjun Liu, Yangkai Liu, Yangruiyu Liu, Yangyang Liu, Yanhong Liu, Yanhua Liu, Yanhui Liu, Yanjie Liu, Yanju Liu, Yanjun Liu, Yankuo Liu, Yanli Liu, Yanliang Liu, Yanling Liu, Yanman Liu, Yanmin Liu, Yanping Liu, Yanqing Liu, Yanqiu Liu, Yanquan Liu, Yanru Liu, Yansheng Liu, Yansong Liu, Yanting Liu, Yanwu Liu, Yanxiao Liu, Yanyan Liu, Yanyao Liu, Yanying Liu, Yanyun Liu, Yao Liu, Yao-Hui Liu, Yaobo Liu, Yaoquan Liu, Yaou Liu, Yaowen Liu, Yaoyao Liu, Yaozhong Liu, Yaping Liu, Yaqiong Liu, Yarong Liu, Yaru Liu, Yating Liu, Yaxin Liu, Ye Liu, Ye-Dan Liu, Yehai Liu, Yen-Chen Liu, Yen-Chun Liu, Yen-Nien Liu, Yeqing Liu, Yi Liu, Yi-Chang Liu, Yi-Chien Liu, Yi-Han Liu, Yi-Hung Liu, Yi-Jia Liu, Yi-Ling Liu, Yi-Meng Liu, Yi-Ming Liu, Yi-Yun Liu, Yi-Zhang Liu, YiRan Liu, Yibin Liu, Yibing Liu, Yicun Liu, Yidan Liu, Yidong Liu, Yifan Liu, Yifu Liu, Yihao Liu, Yiheng Liu, Yihui Liu, Yijing Liu, Yilei Liu, Yili Liu, Yilin Liu, Yimei Liu, Yiming Liu, Yin Liu, Yin-Ping Liu, Yinchu Liu, Yinfang Liu, Ying Liu, Ying Poi Liu, Yingchun Liu, Yinghua Liu, Yinghuan Liu, Yinghui Liu, Yingjun Liu, Yingli Liu, Yingwei Liu, Yingxia Liu, Yingyan Liu, Yingyi Liu, Yingying Liu, Yingzi Liu, Yinhe Liu, Yinhui Liu, Yining Liu, Yinjiang Liu, Yinping Liu, Yinuo Liu, Yiping Liu, Yiqing Liu, Yitian Liu, Yiting Liu, Yitong Liu, Yiwei Liu, Yiwen Liu, Yixiang Liu, Yixiao Liu, Yixuan Liu, Yiyang Liu, Yiyi Liu, Yiyuan Liu, Yiyun Liu, Yizhi Liu, Yizhuo Liu, Yong Liu, Yong Mei Liu, Yong-Chao Liu, Yong-Hong Liu, Yong-Jian Liu, Yong-Jun Liu, Yong-Tai Liu, Yong-da Liu, Yongchao Liu, Yonggang Liu, Yonggao Liu, Yonghong Liu, Yonghua Liu, Yongjian Liu, Yongjie Liu, Yongjun Liu, Yongli Liu, Yongmei Liu, Yongming Liu, Yongqiang Liu, Yongshuo Liu, Yongtai Liu, Yongtao Liu, Yongtong Liu, Yongxiao Liu, Yongyue Liu, You Liu, You-ping Liu, Youan Liu, Youbin Liu, Youdong Liu, Youhan Liu, Youlian Liu, Youwen Liu, Yu Liu, Yu Xuan Liu, Yu-Chen Liu, Yu-Ching Liu, Yu-Hui Liu, Yu-Li Liu, Yu-Lin Liu, Yu-Peng Liu, Yu-Wei Liu, Yu-Zhang Liu, YuHeng Liu, Yuan Liu, Yuan-Bo Liu, Yuan-Jie Liu, Yuan-Tao Liu, YuanHua Liu, Yuanchu Liu, Yuanfa Liu, Yuanhang Liu, Yuanhui Liu, Yuanjia Liu, Yuanjiao Liu, Yuanjun Liu, Yuanliang Liu, Yuantao Liu, Yuantong Liu, Yuanxiang Liu, Yuanxin Liu, Yuanxing Liu, Yuanying Liu, Yuanyuan Liu, Yubin Liu, Yuchen Liu, Yue Liu, Yuecheng Liu, Yuefang Liu, Yuehong Liu, Yueli Liu, Yueping Liu, Yuetong Liu, Yuexi Liu, Yuexin Liu, Yuexing Liu, Yueyang Liu, Yueyun Liu, Yufan Liu, Yufei Liu, Yufeng Liu, Yuhao Liu, Yuhe Liu, Yujia Liu, Yujiang Liu, Yujie Liu, Yujun Liu, Yulan Liu, Yuling Liu, Yulong Liu, Yumei Liu, Yumiao Liu, Yun Liu, Yun-Cai Liu, Yun-Qiang Liu, Yun-Ru Liu, Yun-Zi Liu, Yunfen Liu, Yunfeng Liu, Yuning Liu, Yunjie Liu, Yunlong Liu, Yunqi Liu, Yunqiang Liu, Yuntao Liu, Yunuan Liu, Yunuo Liu, Yunxia Liu, Yunyun Liu, Yuping Liu, Yupu Liu, Yuqi Liu, Yuqiang Liu, Yuqing Liu, Yurong Liu, Yuru Liu, Yusen Liu, Yutao Liu, Yutian Liu, Yuting Liu, Yutong Liu, Yuwei Liu, Yuxi Liu, Yuxia Liu, Yuxiang Liu, Yuxin Liu, Yuxuan Liu, Yuyan Liu, Yuyi Liu, Yuyu Liu, Yuyuan Liu, Yuzhen Liu, Yv-Xuan Liu, Z H Liu, Z Q Liu, Z Z Liu, Zaiqiang Liu, Zan Liu, Zaoqu Liu, Ze Liu, Zefeng Liu, Zekun Liu, Zeming Liu, Zengfu Liu, Zeyu Liu, Zezhou Liu, Zhangyu Liu, Zhangyuan Liu, Zhansheng Liu, Zhao Liu, Zhaoguo Liu, Zhaoli Liu, Zhaorui Liu, Zhaotian Liu, Zhaoxiang Liu, Zhaoxun Liu, Zhaoyang Liu, Zhe Liu, Zhekai Liu, Zheliang Liu, Zhen Liu, Zhen-Lin Liu, Zhendong Liu, Zhenfang Liu, Zhenfeng Liu, Zheng Liu, Zheng-Hong Liu, Zheng-Yu Liu, ZhengYi Liu, Zhengbing Liu, Zhengchuang Liu, Zhengdong Liu, Zhenghao Liu, Zhengkun Liu, Zhengtang Liu, Zhengting Liu, Zhenguo Liu, Zhengxia Liu, Zhengye Liu, Zhenhai Liu, Zhenhao Liu, Zhenhua Liu, Zhenjiang Liu, Zhenjiao Liu, Zhenjie Liu, Zhenkui Liu, Zhenlei Liu, Zhenmi Liu, Zhenming Liu, Zhenna Liu, Zhenqian Liu, Zhenqiu Liu, Zhenwei Liu, Zhenxing Liu, Zhenxiu Liu, Zhenzhen Liu, Zhenzhu Liu, Zhi Liu, Zhi Y Liu, Zhi-Fen Liu, Zhi-Guo Liu, Zhi-Jie Liu, Zhi-Kai Liu, Zhi-Ping Liu, Zhi-Ren Liu, Zhi-Wen Liu, Zhi-Ying Liu, Zhicheng Liu, Zhifang Liu, Zhigang Liu, Zhiguo Liu, Zhihan Liu, Zhihao Liu, Zhihong Liu, Zhihua Liu, Zhihui Liu, Zhijia Liu, Zhijie Liu, Zhikui Liu, Zhili Liu, Zhiming Liu, Zhipeng Liu, Zhiping Liu, Zhiqian Liu, Zhiqiang Liu, Zhiru Liu, Zhirui Liu, Zhishuo Liu, Zhitao Liu, Zhiteng Liu, Zhiwei Liu, Zhixiang Liu, Zhixue Liu, Zhiyan Liu, Zhiying Liu, Zhiyong Liu, Zhiyuan Liu, Zhong Liu, Zhong Wu Liu, Zhong-Hua Liu, Zhong-Min Liu, Zhong-Qiu Liu, Zhong-Wu Liu, Zhong-Ying Liu, Zhongchun Liu, Zhongguo Liu, Zhonghua Liu, Zhongjian Liu, Zhongjuan Liu, Zhongmin Liu, Zhongqi Liu, Zhongqiu Liu, Zhongwei Liu, Zhongyu Liu, Zhongyue Liu, Zhongzhong Liu, Zhou Liu, Zhou-di Liu, Zhu Liu, Zhuangjun Liu, Zhuanhua Liu, Zhuo Liu, Zhuoyuan Liu, Zi Hao Liu, Zi-Hao Liu, Zi-Lun Liu, Zi-Ye Liu, Zi-wen Liu, Zichuan Liu, Zihang Liu, Zihao Liu, Zihe Liu, Ziheng Liu, Zijia Liu, Zijian Liu, Zijing J Liu, Zimeng Liu, Ziqian Liu, Ziqin Liu, Ziteng Liu, Zitian Liu, Ziwei Liu, Zixi Liu, Zixuan Liu, Ziyang Liu, Ziying Liu, Ziyou Liu, Ziyuan Liu, Ziyue Liu, Zong-Chao Liu, Zong-Yuan Liu, Zonghua Liu, Zongjun Liu, Zongtao Liu, Zongxiang Liu, Zu-Guo Liu, Zuguo Liu, Zuohua Liu, Zuojin Liu, Zuolu Liu, Zuyi Liu, Zuyun Liu
articles

E3 ligase HERC5-catalyzed UGDH isgylation promotes SNAI1-mediated tumor metastasis and cisplatin resistance in oral squamous cell carcinoma.

Xu Zhang, Fayu Liu, Qigen Fang +2 more · 2025 · Biology direct · BioMed Central · added 2026-04-24
Oral squamous cell carcinoma (OSCC) is one of the leading causes of cancer-related mortality worldwide due to its high aggressive potential and drug resistance. Previous studies have revealed an impor Show more
Oral squamous cell carcinoma (OSCC) is one of the leading causes of cancer-related mortality worldwide due to its high aggressive potential and drug resistance. Previous studies have revealed an important function of HECT And RLD Domain Containing E3 Ubiquitin Protein Ligase 5 (HERC5) in cancer. Six GEO gene microarrays identified HERC5 as a significant upregulated gene in OSCC tissues or cells (log2 Fold change > 1 and adj.p < 0.05). This study aimed to explore the role and underlying mechanisms of HERC5 in OSCC development. High HERC5 expression in OSCC tissues was confirmed by our hospital validation cohort and positively correlated with primary tumor stages. Subsequent functional studies demonstrated that knockdown of HERC5 inhibited the migratory and invasive capabilities with decrease of Vimentin and increase of E-cadherin in OSCC cells. In cisplatin treatment, cell survival rates were significantly reduced in HERC5-silencing OSCC cells, accompanied by the increase in cytotoxicity, DNA damage and apoptosis. OSCC cell-derived tumor xenograft displayed that HERC5 depletion inhibited pulmonary metastasis as well as restored the cisplatin-induced tumor burden. In line with this, overexpression of HERC5 yielded the opposite alterations both in vivo and in vitro. Mechanistically, UDP-glucose 6-dehydrogenase (UGDH) was identified as a HERC5-binding protein. Cysteine residue at position 994 in the HECT domain of HERC5 catalyzed the conjugation of ubiquitin-like protein Interferon-induced 15 kDa protein (ISG15) to UGDH (ISGylation of UGDH) and facilitated its phosphorylation, therefore enhancing SNAI1 mRNA stability. SNAI1 depletion inhibited HERC5 overexpression-triggered invasion and cisplatin resistance of OSCC cells. Our study indicates that HERC5 may be a promising therapeutic target for OSCC. Show less
no PDF DOI: 10.1186/s13062-025-00622-1
SNAI1

Identifying a type of toxic effectors exported by the type VII secretion system to enhance competitive fitness in

Qiankun Bai, Jianan Liu, Jie Zhao +4 more · 2025 · Frontiers in cellular and infection microbiology · Frontiers · added 2026-04-24
Here, we identified a type of hypothetical T7SS effector in This alternative strategy facilitates effectors' delivery, even for fragmented substrates, highlighting its importance in ensuring the funct Show more
Here, we identified a type of hypothetical T7SS effector in This alternative strategy facilitates effectors' delivery, even for fragmented substrates, highlighting its importance in ensuring the functionality of T7SS. Show less
đź“„ PDF DOI: 10.3389/fcimb.2025.1685307
EXT1

FGF22 Secreted by Hair Papilla Cells Regulates Hair Follicle Stem Cell Proliferation and Differentiation.

Yu Luo, Tong Xiao, Binpeng Xi +5 more · 2025 · Biomolecules · MDPI · added 2026-04-24
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine res Show more
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine research. Their dynamic interaction with dermal papilla cells (DPCs) plays a decisive role in HF development and cycling. Show less
đź“„ PDF DOI: 10.3390/biom15111560
FGFR1

Macrophage marker gene-driven prognostic models for esophageal cancer: integrating multi-omics analysis and therapeutic strategies.

Zehan Li, Huazhen Wu, Chuzhong Wei +15 more · 2025 · 3 Biotech · Springer · added 2026-04-24
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORD Show more
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORDC1, and BCKDK). This signature effectively stratified patients into high- and low-risk groups with significantly different overall survival, achieving area under the curve (AUC) values greater than 0.7 for 1-, 2-, and 3-year survival prediction. A high-risk status correlated with an immunosuppressive tumor microenvironment, characterized by lower infiltration of B cells and CD8 + T cells, and was associated with reduced sensitivity to multiple chemotherapeutic agents, including Cisplatin and 5-Fluorouracil. Conversely, a low-risk status was linked to greater immune cell infiltration and higher predicted chemosensitivity. At the single-cell level, pseudotime analysis revealed that macrophage maturation significantly correlated with a decreasing risk score, suggesting that mature macrophages may contribute to a favorable prognosis. Furthermore, cell communication analysis identified high-risk macrophages as dominant drivers of a pro-tumorigenic microenvironment via signaling pathways, such as SPP1 and complement. In conclusion, this seven-gene signature is a robust prognostic biomarker that offers a new strategy for personalized risk assessment and treatment selection in ESCA. The online version contains supplementary material available at 10.1007/s13205-025-04452-w. Show less
no PDF DOI: 10.1007/s13205-025-04452-w
BCKDK

Low physical activity-related disease burden, 1990-2021: assessment of global trends and social determinants based on GBD 2021 data.

Hao Liu, Zhenhao Liu, Yanqing Gong +6 more · 2025 · Journal of global health · added 2026-04-24
Low physical activity (LPA) is associated with cardiovascular and cerebrovascular pathologies. This study aimed to assess the prevalence of several noncommunicable diseases relating to LPA. Using the Show more
Low physical activity (LPA) is associated with cardiovascular and cerebrovascular pathologies. This study aimed to assess the prevalence of several noncommunicable diseases relating to LPA. Using the 2021 Global Burden of Disease data set, we modelled LPA-related disease burdens across 204 countries and territories, quantifying mortality counts, age-standardised mortality rates, and disability-adjusted life years (DALYs) for five noncommunicable diseases. We conducted multivariable stratification analyses to assess variations by gender, age, and sociodemographic index (SDI) quintiles. We used age-period-cohort modelling to project burden trajectories, while applying counterfactual decomposition frameworks to delineate synergistic interactions between LPA and risk factors. We found that LPA accounted for 555 101 related deaths globally in 2021 across the five studied pathologies, mostly among individuals aged 60-94 years. Association between LPA-related disease burden and SDI followed a U-shaped distribution across regions and diseases. Among individuals aged 60-89 years, LPA-related deaths were significantly higher in women than in men, indicating a disproportionate burden on elderly females. Ischaemic heart disease (IHD) trends stabilised in low- and middle-SDI regions but declined significantly in high-SDI regions, underscoring global health disparities. From 2007 to 2011, LPA DALYs and mortality risk ratios for IHD, stroke, and lower extremity peripheral arterial disease declined from >1 to <1, whereas diabetes mellitus exhibited an opposite trend, highlighting LPA's persistent and significant impact on diabetes-related morbidity. Demographic shifts and epidemiological transitions were primary drivers of LPA-related disease burden across five pathologies. In high-SDI regions, epidemiological changes predominated, whereas population growth was a key factor in low- and middle-SDI regions. Synergistic interaction of these factors with LPA is projected to substantially amplify future disease burden. Physical activity should be increased among elderly women to address health risks associated with LPA. Likewise, urgent public health interventions are needed for LPA-related diabetes. As IHD burden rises in low- and middle-SDI regions, vascular disease care strategies require optimisation. Moreover, high-SDI regions should strengthen nationwide physical activity promotion, while low- and middle-SDI areas must enhance healthcare infrastructure and manage population growth to reduce LPA-related disease burdens. Show less
đź“„ PDF DOI: 10.7189/jogh.15.04314
LPA

Latent Profile Analysis and Influencing Factors of Medication-Related Burden in Multidrug-Resistant Tuberculosis Patients in Chengdu, China.

Yuanyuan Li, Qiaolin Yu, Rong Yao +11 more · 2025 · Patient preference and adherence · added 2026-04-24
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that neg Show more
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that negatively impacts patients' adherence and quality of life. However, research on the heterogeneity of medication-related burden among MDR-TB patients and its influencing factors remains limited. This study aimed to identify latent profiles of medication-related burden among MDR-TB patients and examine differences in burden characteristics across these profiles, thereby providing evidence for tailored intervention strategies. A convenience sampling method was employed to recruit MDR-TB patients diagnosed at a tertiary infectious disease hospital in Chengdu between December 2024 and May 2025. Data were collected using a general information questionnaire, the Living with Medicines Questionnaire (LMQ), and the Health Literacy Management Scale (HeLMS). Latent profile analysis (LPA) was conducted to identify distinct profiles of medication-related burden, and multivariate logistic regression was used to explore associated factors for each profile. A total of 214 valid responses were analyzed. The LPA identified two distinct profiles of medication-related burden: C1 - "Low-Burden (Attitude & Practice-Dominated)" (44%) and C2 - "High-Burden (Daily Interference-Dominated)" (56%). Absence of side effects, not employing a caregiver, and higher levels of health literacy were positively associated with membership in the C1 group ( Medication-related burden among MDR-TB patients exhibits clear heterogeneity. Healthcare professionals should adopt stratified management and personalized interventions based on the identified influencing factors to alleviate the burden of medication in this population. Show less
đź“„ PDF DOI: 10.2147/PPA.S558068
LPA

GPIHBP1 increase accounts for rheumatic arthritis-related hypotriglyceridemia by facilitating lipids uptake of white adipose tissues.

Meng-Ke Song, Meng-Fan Gu, Ling Liu +7 more · 2025 · Arthritis research & therapy · BioMed Central · added 2026-04-24
Metabolism alteration is a common complication of rheumatic arthritis (RA). This work investigated the reason behind RA-caused triglyceride (TG) changes. Fresh RA patients' whole blood was transfused Show more
Metabolism alteration is a common complication of rheumatic arthritis (RA). This work investigated the reason behind RA-caused triglyceride (TG) changes. Fresh RA patients' whole blood was transfused into NOD-SCID mice. Metabolism-regulatory tissues were examined after sacrifice. To verify the findings, tissues of the rats with long-lasting adjuvant-induced arthritis (AIA) were analyzed. Some rats were injected with human plasma and GPIHBP1, and their blood TG was monitored. Various cells were stimulated by cytokines or rheumatic subjects' serum. Some pre-adipocytes were cultured by human serum or in the presence of HUVEC cells and GPIHBP1. TG decrease occurred in blood and white adipose tissues (WAT) of the RA blood-transfused NOD-SCID mice and chronic AIA rats. Fatty acids (FA) oxidation in muscles was accelerated a bit, while TG catabolism status in their livers was varied. TNF-α, IL-1β, IL-6 and RA/AIA serum promoted expression of TG utilization-related enzymes and FA uptake transporters in pre-adipocytes, but barely affected LPL. Mild IL-6 stimulus promoted GPIHBP1 release of HUVEC cells. GPIHBP1 was increased in RA serum. This change can decrease blood TG in rats, which was overshadowed by an injection of excessive GPIHBP1. RA serum slightly inhibited LPL secretion in pre-adipocytes. Both HUVEC cells co-culture and GPIHBP1 supplement reduced LPL distribution on pre-adipocytes, and eliminated LPL activity difference between normal and RA serum-treated cells. No TG uptake difference was observed in these circumstances. RA-associated inflammation induces GPIHBP1 secretion of endothelial cells, which facilitates blood TG hydrolysis and uptake to compensate the loss in WAT. Show less
đź“„ PDF DOI: 10.1186/s13075-025-03483-1
LPL

Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele.

Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff +122 more · 2025 · Nature communications · Nature · added 2026-04-24
Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff, Heather M Highland, Nathalie Chami, Hanfei Xu, Zhe Wang, Kendra R Ferrier, Geetha Chittoor, Navya Shilpa Josyula, Mariah Meyer, Shreyash Gupta, Xihao Li, Zilin Li, Matthew A Allison, Diane M Becker, Lawrence F Bielak, Joshua C Bis, Meher Preethi Boorgula, Donald W Bowden, Jai G Broome, Erin J Buth, Christopher S Carlson, Kyong-Mi Chang, Sameer Chavan, Yen-Feng Chiu, Lee-Ming Chuang, Matthew P Conomos, Dawn L DeMeo, Mengmeng Du, Ravindranath Duggirala, Celeste Eng, Alison E Fohner, Barry I Freedman, Melanie E Garrett, Xiuqing Guo, Chris Haiman, Benjamin D Heavner, Bertha Hidalgo, James E Hixson, Yuk-Lam Ho, Brian D Hobbs, Donglei Hu, Qin Hui, Chii-Min Hwu, Rebecca D Jackson, Deepti Jain, Rita R Kalyani, Sharon L R Kardia, Tanika N Kelly, Ethan M Lange, Michael LeNoir, Changwei Li, Loic Le Marchand, Merry-Lynn N McDonald, Caitlin P McHugh, Alanna C Morrison, Take Naseri, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Jeffrey O'Connell, Christopher J O'Donnell, Nicholette D Palmer, James S Pankow, James A Perry, Ulrike Peters, Michael H Preuss, D C Rao, Elizabeth A Regan, Sefuiva M Reupena, Dan M Roden, Jose Rodriguez-Santana, Colleen M Sitlani, Jennifer A Smith, Hemant K Tiwari, Ramachandran S Vasan, Zeyuan Wang, Daniel E Weeks, Jennifer Wessel, Kerri L Wiggins, Lynne R Wilkens, Peter W F Wilson, Lisa R Yanek, Zachary T Yoneda, Wei Zhao, Sebastian Zöllner, Donna K Arnett, Allison E Ashley-Koch, Kathleen C Barnes, John Blangero, Eric Boerwinkle, Esteban G Burchard, April P Carson, Daniel I Chasman, Yii-der Ida Chen, Joanne E Curran, Myriam Fornage, Victor R Gordeuk, Jiang He, Susan R Heckbert, Lifang Hou, Marguerite R Irvin, Charles Kooperberg, Ryan L Minster, Braxton D Mitchell, Mehdi Nouraie, Bruce M Psaty, Laura M Raffield, Alexander P Reiner, Stephen S Rich, Jerome I Rotter, M Benjamin Shoemaker, Nicholas L Smith, Kent D Taylor, Marilyn J Telen, Scott T Weiss, Yingze Zhang, Nancy Heard-Costa, Yan V Sun, Xihong Lin, L Adrienne Cupples, Leslie A Lange, Ching-Ti Liu, Ruth J F Loos, Kari E North, Anne E Justice Show less
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data fr Show more
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10 Show less
no PDF DOI: 10.1038/s41467-025-58420-2
POC5

New heights in CT differentiation of adrenal lesions and a rational definition of non-enhancement.

Lichun Liu, Fangmei Zhu, Zongfeng Niu +4 more · 2025 · BMC medical imaging · BioMed Central · added 2026-04-24
To explore the stratification and identification of adrenal lipid-poor adenomas (LPAs), adrenal cysts (ACs), and adrenal ganglioneuromas (AGNs) from each other using contrast-enhanced computed tomogra Show more
To explore the stratification and identification of adrenal lipid-poor adenomas (LPAs), adrenal cysts (ACs), and adrenal ganglioneuromas (AGNs) from each other using contrast-enhanced computed tomography (CT). Pathologically confirmed, 348 patients were categorized into Model 1 (260 LPAs, 34 ACs), Model 2 (260 LPAs, 54 AGNs), and Model 3 (34 ACs, 54 AGNs). Statistical analyses were performed on the differences in the degree of enhancement in the arterial/venous phase (DEap/DEvp) (in HU) and the corresponding graded variables for the arterial/venous phase (GVap/GVvp). Models were evaluated via receiver operating characteristic (ROC) curves, calibration curves, and the Hosmer‒Lemeshow (HL) test. The values of the area under the curve (AUC) for DEap, DEvp, GVap, and GVvp in Models 1-3 were 0.996, 1.000, 0.993, and 0.999; 0.980, 0.978, 0.961, and 0.975; and 0.734, 0.892, 0.725, and 0.883, respectively. The p values of the HL test were 0.984, 1.000, and 0.113, respectively. The DEvp interval values (in HU) for the LPAs, ACs, and AGNs were [4.9, 190.2] HU, [-3.7, 4.2] HU, and [-4.8, 41.8] HU, respectively. The GVap and GVvp ranges for the LPAs, ACs, and AGNs were [1, 6], [0, 2], and [0, 2] and [1, 6], [0, 1], and [0, 5], respectively. DEvp enhanced discrimination in Models 1 and 3, whereas DEap performed better in Model 2. Lesions with DEvp < 4.5 HU are likely represent non-enhancing pathology (e.g., cysts). When both GVap and GVvp are 0, when both GVap and GVvp are [2, 6], and when GVap is [3, 6] and GVvp is 6, LPA, AC, and AGN are excluded. Not applicable. Show less
đź“„ PDF DOI: 10.1186/s12880-025-01916-6
LPA

Comorbidity patterns and immune-metabolic differences in patients with acute-episode of schizophrenia spectrum disorders.

Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
đź“„ PDF DOI: 10.1038/s41537-025-00646-6
APOB

Genome-wide analysis identifies susceptibility loci for heart failure and nonischemic cardiomyopathy subtype in the East Asian populations.

Yi Han, Yun Hong, Yan Gao +11 more · 2025 · PLoS genetics · PLOS · added 2026-04-24
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understandin Show more
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understanding of the genetic basis of HF and more specific NICM subtype in the East Asian populations and evaluate the biological pathways underlying subclinical left ventricular dysfunction. We conducted a meta-analysis of genome-wide association studies (GWAS) for all-cause HF in the East Asian populations (N cases ~ 13,385) and a more precise definition of nonischemic cardiomyopathy (NICM) subtype in multi-ancestry populations (N cases~3,603). We identified a low-frequency East-Asian enriched coding variant near MYBPC3 and a NICM specific locus. Follow up analyses demonstrated male-specific HF association at the MYBPC3 locus, and highlighted SVIL as a candidate causal gene for NICM. Moreover, we demonstrated that SVIL deficiency aggravated cardiomyocyte hypertrophy, apoptosis and impaired cell viability in phenylephrine (PE)-treated H9C2 cells. In addition, the gene expression level of B-type natriuretic peptide (BNP) which was deemed as a hallmark for HF was further elevated by SVIL silencing in PE-stimulated H9C2 cells. RNA-sequencing analysis of H9C2 cells revealed that the function of SVIL might be mediated through pathways relevant to regulation and differentiation of heart muscle. These results enhance our understanding of the genetic architecture of HF in the East Asian populations, and provide important insight into the biological pathways underlying NICM and sex-specific relevance of the MYBPC3 locus that warrants further replication in another datasets. Show less
đź“„ PDF DOI: 10.1371/journal.pgen.1011897
MYBPC3

The integrated analysis of transcriptomics and metabolomics reveals the effects of tea polyphenols on lipid metabolism in lion-head geese.

Zhiqi Fu, Chunpeng Liu, Tao Zeng +5 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Tea polyphenols are a class of natural plant compounds with potent antioxidant properties, and their critical role in regulating lipid metabolism has been demonstrated in numerous studies. However, sy Show more
Tea polyphenols are a class of natural plant compounds with potent antioxidant properties, and their critical role in regulating lipid metabolism has been demonstrated in numerous studies. However, systematic research on the effects of tea polyphenols on lipid metabolism in lion-head geese remains limited. In this study, we examined the impact of tea polyphenols on lipid metabolism in geese through an integrative analysis of transcriptomics and metabolomics. A total of 240 healthy male lion-head geese with similar body weights at 1 day of age were randomly allocated into two treatment groups (6 replicates per group, with 20 geese per replicate). The control group received a basal diet, while the experimental group was supplemented with 1000 mg/kg of tea polyphenols (50.4 % catechin purity) in the basal diet for 18 weeks. The results indicated that serum total antioxidant capacity (T-AOC) and glutathione peroxidase (GSH-Px) activities were significantly increased (P < 0.05), while malondialdehyde (MDA) levels were significantly decreased (P < 0.05) in the tea polyphenol group compared to the control group. Additionally, serum triglycerides (TG), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) activities were significantly lower (P < 0.05) in the tea polyphenol group than in the control group. Hepatic transcriptomic analysis further revealed that tea polyphenols significantly modulated the expression of several genes involved in lipid metabolism, including angiopoietin-like 4 (ANGPTL4), which plays a role in regulating lipid homeostasis, as well as glycerophosphodiester phosphodiesterase domain containing 2 (GDPD2), immunoglobulin heavy chain (IGH), proto-oncogene protein c-fos (FOS), and matrix metallopeptidase 1 (MMP1), etc. Serum metabolomic analysis also demonstrated significant alterations in lipid metabolites induced by tea polyphenols, including the downregulation of fatty acyl metabolites such as L-Palmitoylcarnitine and Hexadecanal. Moreover, the combined analysis revealed a strong positive correlation between ANGPTL4 and the organic compounds of steroidal saponins, such as Glucoconvallasaponin B, and negative correlations with glycerophospholipid metabolites, such as LysoPC (P-16:0). The comprehensive analysis suggests that the inclusion of tea polyphenols in the diet enhances the antioxidant capacity of lion-head geese, improves hepatic lipid profiles, and regulates lipid metabolism via modulating lipid metabolism-related genes and metabolites. Show less
đź“„ PDF DOI: 10.1016/j.psj.2025.104958
ANGPTL4

TMEM106A mediates atherosclerosis progression through macrophage-centered immune responses and chemokine signaling.

Menglong Gao, Xingbang Liu, Zhen Fang +5 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Atherosclerosis (AS) remains a leading cause of cardiovascular morbidity and mortality, characterized by intricate interactions between immune dysregulation and lipid metabolism abnormalities-identify Show more
Atherosclerosis (AS) remains a leading cause of cardiovascular morbidity and mortality, characterized by intricate interactions between immune dysregulation and lipid metabolism abnormalities-identifying key mediators in its pathogenesis is critical for improving diagnostics and therapies. This study focuses on Transmembrane Protein 106A (TMEM106A) to clarify its role and clinical relevance in AS progression. Public transcriptomic datasets (GSE43292, GSE100927, GSE28829) were analyzed to assess TMEM106A expression and diagnostic value; single-cell RNA-seq data (GSE159677) defined its cellular localization. Immune infiltration (ssGSEA, Cibersort, xCell) and CellChat (intercellular communication) analyses explored its immune associations. TMEM106A was significantly upregulated in AS samples across datasets, with strong diagnostic efficacy (AUC 0.80-0.95). Single-cell analysis confirmed its specific enrichment in macrophages, with functional links to immune-related pathways. TMEM106A promoted macrophage infiltration, foam cell formation, oxidative stress, and inflammatory responses, while regulating PLCB2 in chemokine signaling; silencing TMEM106A alleviated these pro-atherosclerotic effects. TMEM106A contributes to AS progression by modulating macrophage-mediated immune responses and chemokine signaling, as validated in experimental models. These findings support its potential as a clinically relevant biomarker and promising therapeutic target for AS intervention. Show less
đź“„ PDF DOI: 10.3389/fimmu.2025.1681645
APOE

Single-cell transcriptomics reveals apolipoprotein A4-mediated metabolic-immune reprogramming in lymphocytes during early obesity-related chronic kidney disease.

Yang Wei, Ting Zhang, Yingying Jin +4 more · 2025 · Acta biochimica et biophysica Sinica · added 2026-04-24
Obesity-induced metabolic inflammation is a key driver of chronic kidney disease (CKD), with immune dysregulation, particularly among lymphocytes, contributing to early disease pathology. To explore t Show more
Obesity-induced metabolic inflammation is a key driver of chronic kidney disease (CKD), with immune dysregulation, particularly among lymphocytes, contributing to early disease pathology. To explore the role of apolipoprotein A4 (Apoa4) in regulating immune cell metabolism and function, we establish high-fat diet-induced obese (DIO) models using wild-type and Show less
đź“„ PDF DOI: 10.3724/abbs.2025171
APOA4

RNA-seq shows Angiopoietin-like 4 promotes hepatocellular carcinoma progression by inducing M2 polarization of tumor-associated macrophages.

Guanghua Cui, Wei Liu, Xiaoke Sun +8 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Hepatocellular carcinoma (HCC) represents a particularly aggressive form of cancer, characterized by its rapid progression and a complex interplay with the surrounding immune cellular environment. The Show more
Hepatocellular carcinoma (HCC) represents a particularly aggressive form of cancer, characterized by its rapid progression and a complex interplay with the surrounding immune cellular environment. The primary objective of this study was to comprehensively investigate the role of ANGPTL4 in the context of HCC, utilizing RNA sequencing (RNA-seq) techniques to explore its impact on the M2 polarization of tumor-associated macrophages (TAM) and to uncover potential mechanisms driving HCC progression. To achieve this, we performed a transcriptome analysis of HCC cell lines, alongside cells obtained after co-culturing these lines with macrophages. By comparing gene expression profiles between the experimental groups exposed to ANGPTL4 and control groups, we aimed to identify specific molecular pathways associated with ANGPTL4's function. In addition to gene expression analysis, we employed flow cytometry to assess the polarization status of TAM. Furthermore, we utilized immunohistochemistry to evaluate the distribution of macrophages within HCC tissues and to quantify the expression levels of M2 macrophage markers. The results derived from RNA-seq analysis were particularly revealing; treatment with ANGPTL4 led to a significant upregulation of genes linked to M2 polarization, notably including CD206 and Arg1. In subsequent experimental observations, it became evident that ANGPTL4 not only facilitated the M2 polarization of macrophages but also enhanced the proliferation and migratory capacity of HCC cells through the upregulation of these same cytokines. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.138523
ANGPTL4

Dietary Se-enrich Cardamine violifolia supplementation decreases lipid deposition and improves antioxidant status in the liver of aging laying hens.

Mengke Yan, Xin Cong, Hui Wang +7 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Aging-related lipid metabolic disorder is related to oxidative stress. Selenium (Se)-enriched Cardamine violifolia (SEC) is known for its excellent antioxidant function. The objective of this study wa Show more
Aging-related lipid metabolic disorder is related to oxidative stress. Selenium (Se)-enriched Cardamine violifolia (SEC) is known for its excellent antioxidant function. The objective of this study was to evaluate the effects of SEC on antioxidant capacity and lipid metabolism in the liver of aged laying hens. A total of 450 sixty-five-wk-old Roman laying hens were randomly divided into 5 treatments: a basal diet (without Se supplementation, CON) and basal diets supplemented with 0.3 mg/kg Se from sodium selenite (SS), 0.3 mg/kg Se from Se-enriched yeast (SEY), 0.3 mg/kg Se from SEC (SEC), or 0.3 mg/kg Se from SEC and 0.3 mg/kg Se from SEY (SEC + SEY). The experiment lasted for 8 wk. The results showed that dietary SEC + SEY supplementation decreased (P < 0.05) triglyceride (in the plasma and liver) and total cholesterol levels (in the plasma), and increased (P < 0.05) HDL-C concentration in plasma compared to CON diet. Compared with CON diet, SEC and/or SEY supplementation decreased (P < 0.05) the mRNA expression of hepatic ACC, FAS and HMGCR, and increased (P < 0.05) PPARα, VTG-II, Apo-VLDL II and ApoB expression. Dietary SEC + SEY and SEY supplementation increased (P < 0.05) Se content in egg yolk and breast muscle compared to CON diet. Dietary SEC, SEY or SEC + SEY supplementation increased (P < 0.05) the activity of antioxidant enzymes (GSH-PX, T-AOC and T-SOD) in the plasma and liver and decreased (P < 0.05) MDA content in the plasma compared to CON diet. Dietary Se supplementation promoted (P < 0.05) mRNA expression of Nrf2 in the liver. In contrast, dietary SEY and SEC supplementation resulted in a decrease (P < 0.05) of hepatic Keap1 mRNA expression compared to CON diet. Dietary SEC + SEY and/or SEC supplementation increased (P < 0.05) mRNA expression of Selenof, GPX1 and GPX4 in the liver compared with CON diet. In conclusion, dietary SEC (0.3 mg/kg Se) or SEC (0.3 mg/kg Se) + SEY (0.3 mg/kg Se) improved the antioxidant capacity and the lipid metabolism in the liver of aged laying hens, which might be associated with regulating Nrf2/Keap1 signaling pathway. Show less
đź“„ PDF DOI: 10.1016/j.psj.2024.104620
APOB

Multi-Angle Bioactivity Cartography for Computational Screening and Mechanistic Analysis of AChE Inhibitors From Yellow Gastrodia elata.

Ruijun Sun, Yuchi Zhang, Jingying Xu +7 more · 2025 · Archiv der Pharmazie · Wiley · added 2026-04-24
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-se Show more
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-serving as promising reservoirs of such inhibitors. Nevertheless, comprehensive screening and mechanistic characterization of their inhibitory potential remain limited. This study sought to identify potent AChE inhibitors from YGE, investigate their mechanisms of action, and assess their therapeutic prospects for AD. Methodologically, an integrated approach was employed, combining ultrafiltration-liquid chromatography (UF-LC) for rapid inhibitor screening, molecular docking and dynamics simulations for mechanistic insight, two-stage high-speed countercurrent chromatography for compound isolation, enzyme kinetics to delineate inhibition modalities, and network pharmacology to uncover relevant AD-related targets. The findings identified seven active constituents with notable AChE inhibition, among which parishins A and G were obtained at high purity (98.26% and 97.26%, respectively) and exhibited mixed-type inhibition with low IC Show less
no PDF DOI: 10.1002/ardp.70174
BACE1

Atf3 + senescent chondrocytes mediate meniscus degeneration in aging.

Jing-Yi Wang, Yao-Hui Liu, Xiao Wang +7 more · 2025 · Arthritis research & therapy · BioMed Central · added 2026-04-24
Meniscus degeneration contributes to knee arthritis progression, but the cellular and molecular mechanisms of meniscus aging remain poorly understood. We aimed to characterize age-related changes in t Show more
Meniscus degeneration contributes to knee arthritis progression, but the cellular and molecular mechanisms of meniscus aging remain poorly understood. We aimed to characterize age-related changes in the rat meniscus using single-cell RNA sequencing (scRNA-seq) and identify key pathogenic cell populations and pathways. Meniscal tissues from young (12 weeks) and aged (24 months) rats were processed for histology, flow cytometry, and scRNA-seq. Bioinformatics tools, including Seurat, Monocle 2, and CellChat, were used to analyze cellular composition, pseudotime trajectories, and intercellular communication. Senescence-related features and signaling pathways were evaluated. Knee joint of aged rats exhibited higher Osteoarthritis Research Society International (OARSI) scores and synovial inflammation. scRNA-seq revealed three major chondrocyte subpopulations: Sox9 + stable chondrocytes, Fndc1 + fibrochondrocytes, and Atf3 + senescent chondrocytes. Aging caused a significant increase in Atf3 + senescent chondrocytes, characterized by the expression of senescence markers (Cdkn1a/Cdkn2a) and activation of inflammatory pathways such as tumor necrosis factor (TNF) and nuclear factor-κB (NF-κB). These cells were predominantly located at the endpoint of differentiation trajectories. CellChat analysis identified the ANGPTL4-SDC4 axis as a key signaling pathway mediated by Atf3 + cells. Immunostaining confirmed elevated Angiopoietin-Like Protein 4 (ANGPTL4) expression in aged menisci. We identified Atf3 + senescent chondrocytes as a key pathogenic population in the aging meniscus, driving degeneration via the ANGPTL4 pathway. Targeting Atf3 + cells or ANGPTL4 signaling may offer new therapeutic strategies for age-related meniscus degeneration and arthritis. Show less
đź“„ PDF DOI: 10.1186/s13075-025-03566-z
ANGPTL4

A new perspective on cognitive impairment in major depressive disorder: Changes in gut microbiota and their inflammatory regulatory mechanisms.

Xiaodong Song, Qilin Zhong, Rongxu Zhang +10 more · 2025 · Journal of affective disorders · Elsevier · added 2026-04-24
Cognitive impairments in major depressive disorder (MDD) affect patients' social functioning, with underlying mechanisms involving gut microbiota and inflammatory factors remaining unclear. The study Show more
Cognitive impairments in major depressive disorder (MDD) affect patients' social functioning, with underlying mechanisms involving gut microbiota and inflammatory factors remaining unclear. The study analyzed cognitive function, gut microbiota changes, and inflammatory factor levels in 39 unmedicated MDD patients and 41 healthy controls, employing correlation and moderation effect analysis. MDD patients scored lower than controls in cognitive functions like information processing speed, attention/vigilance, verbal learning, visual learning and social cognition. They showed reduced gut microbiota diversity and increased levels of inflammatory markers (TNF-α, IL-1, IL-6, IL-17, IL-27, IL-33). Sellimonas abundance correlated negatively with attention/vigilance, moderated by TNF-α, IL-27, and IL-33. This relationship was stronger at lower inflammation levels. MDD patients exhibit multi-domain cognitive dysfunction alongside pro-inflammatory states and disrupted gut microbiota. The abundance of Sellimonas significantly predicts attention/vigilance deficits. Inflammatory factors modulate the impact of gut microbiota on cognitive function, suggesting chronic low-grade inflammation as a key risk factor for cognitive impairment in MDD. Show less
no PDF DOI: 10.1016/j.jad.2025.119648
IL27

Fish Swim Bladder-Derived ECM Hydrogels Effectively Treat Myocardial Ischemic Injury through Immunomodulation and Angiogenesis.

Yulong Fu, Canran Gao, Hailing Zhang +7 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection te Show more
Injectable hydrogel implants represent a promising therapeutic approach for ischemic heart failure; but their efficacy is often limited by low bioactivity, poor durability, and inadequate injection techniques. Herein, a unique hydrogel incorporating extracellular matrix from fish swim bladder (FSB-ECM), which has distinct advantages over mammalian derived ECM, such as low antigenicity, bioactivity, and source safety, is developed. It consists of collagen, glycoproteins, and proteoglycans, including 13 proteins common in the myocardial matrix and three specific proteins: HSPG, Col12a1, and vWF. This hydrogel enhances cardiac cell adhesion and stretching while promoting angiogenesis and M2 macrophage polarization. In addition, its storage modulus (G') increases over time, reaching about 1000 Pa after 5 min, which facilitates transcatheter delivery and in situ gelling. Furthermore, this hydrogel provides sustained support for cardiac contractions, exhibiting superior longevity. In a rat model of ischemic heart failure, the ejection fraction significantly improves with FSB-ECM treatment, accompanied by increased angiogenesis, reduced inflammation, and decreased infarct size. Finally, RNA sequencing combined with in vitro assays identifies ANGPTL4 as a key protein involved in mediating the effects of FSB-ECM treatment. Overall, this new injectable hydrogel based on FSB-ECM is suitable for transcatheter delivery and possesses remarkable reparative capabilities for treating heart failure. Show less
đź“„ PDF DOI: 10.1002/advs.202500036
ANGPTL4

Targeting VSMCs to suppress macrophage-like phenotype switching that restrains atherogenesis by immunosuppressive oligodeoxynucleotide (A151) functionalized selenium nanoparticles.

Jingru Wang, Bo Yao, Yutian Zhang +13 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strat Show more
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strategy to prevent atherosclerosis (AS), and targeted nanotherapeutics represent one approach for implementing this strategy. To this end, we designed immunosuppressive oligodeoxynucleotide A151 functionalized selenium nanoparticles with a spearhead LacNAc (LN-A151-SeNPs) that target macrophage-like VSMCs. Nano characterization showed that the uniformity and stability of nanoparticles were optimized by modification with LacNAc and A151, resulting in an average diameter of 88.90 ± 1.45 nm, Zeta potentials of -21.1 ± 1.5 mV, a A151:Se molar ratio of 1:60 and mass ratio of 1.68:1. The effects of LN-A151-SeNPs on inhibiting VSMCs phenotype switching and attenuation of AS were investigated using [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03925-7. Show less
đź“„ PDF DOI: 10.1186/s12951-025-03925-7
APOE

Genetic association of circulating lipids and lipid-lowering drug targets with vascular calcification.

Pengfei Zhang, Wenting Wang, Qian Xu +5 more · 2025 · Atherosclerosis · Elsevier · added 2026-04-24
Vascular calcification (VC) significantly increases the incidence and mortality of many diseases. The causal relationships of dyslipidaemia and lipid-lowering drug use with VC severity remain unclear. Show more
Vascular calcification (VC) significantly increases the incidence and mortality of many diseases. The causal relationships of dyslipidaemia and lipid-lowering drug use with VC severity remain unclear. This study explores the genetic causal associations of different circulating lipids and lipid-lowering drug targets with coronary artery calcification (CAC) and abdominal aortic artery calcification (AAC). We obtained single-nucleotide polymorphisms (SNPs) and expression quantitative trait loci (eQTLs) associated with seven circulating lipids and 13 lipid-lowering drug targets from publicly available genome-wide association studies and eQTL databases. Causal associations were investigated by univariable, multivariable, drug-target, and summary data-based Mendelian randomization (MR) analyses. Potential mediation effects of metabolic risk factors were evaluated. MR analysis revealed that genetic proxies for low-density lipoprotein cholesterol (LDL-C), triglycerides (TC) and Lipoprotein (a) (Lp(a)) were causally associated with CAC severity, and apolipoprotein B (apoB) level was causally associated with AAC severity. A significant association was detected between hepatic Lipoprotein(A) (LPA) gene expression and CAC severity. Colocalisation analysis supported the hypothesis that the association between LPA expression and CAC quantity is driven by different causal variant sites within the ±1 Mb flanking region of LPA. Serum calcium and phosphorus had causal associations with CAC severity. Inhibitors targeting LPA might represent CAC drug candidates. Moreover, T2DM, hypercalcemia, and hyperphosphatemia are positively causally associated with CAC severity, while chronic kidney disease and estimated glomerular filtration rate are not. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.119136
APOB

Role of GNL3L in lung cancer: Mediating proliferation and progression through NF-ÎşB pathway activation and upregulation of Slug, MMP2, and MMP9.

Qian Wang, Xiao-Qi Zhang, Shan-Shan Liu +4 more · 2025 · Experimental cell research · Elsevier · added 2026-04-24
The precise involvement of Guanine Nucleotide-Binding Protein-Like 3-Like Protein (GNL3L) in lung cancer progression and invasion remains unclear. In this study, we explored the impact and underlying Show more
The precise involvement of Guanine Nucleotide-Binding Protein-Like 3-Like Protein (GNL3L) in lung cancer progression and invasion remains unclear. In this study, we explored the impact and underlying mechanisms of GNL3L on the proliferation, migration, and invasion of lung adenocarcinoma (LUAD), and evaluated the therapeutic potential of targeting GNL3L. Inhibition of GNL3L expression led to a notable decrease in the in vitro proliferation, migration, and invasion of A549 and H1299 non-small cell lung cancer (NSCLC) cells. Meanwhile, GNL3L silencing could significantly reduce the tumor volume of the nude mice and improve the outcomes of tumor-bearing mice in vivo. Additionally, inhibition of GNL3L expression dramatically suppressed NF-ÎşB activation and Slug, MMP2, and MMP9 expression. Overexpression of Slug or treatment of the GNL3L-deficient cells with NF-ÎşB activator can partially restore the growth suppressed by GNL3L deficiency, and combined treatment with Slug overexpression and NF-ÎşB activator could totally restore the suppressed cell growth caused by GNL3L deficiency. Moreover, the overexpression of MMP2 or MMP9 could partially enhance the reduced migration and invasion caused by GNL3L deficiency, and this GNL3L-deficiency-caused suppression of migration and invasion can be totally restored by the overexpression of MMP2 and MMP9 together. These results strongly indicated that GNL3L has the capability to activate the NF-ÎşB and increase Slug, MMP2, and MMP9 expression, which in turn could stimulate the proliferation, migration, and invasion of lung cancer cells. NF-ÎşB activation and Slug, MMP2, and MMP9 expression enhanced by GNL3L, leading to the promotion of proliferation, migration, and invasion of lung cancer cells, indicating the therapeutic implications and potential significance of these pathways in the progression and invasion of NSCLCs that overexpress GNL3L protein. Show less
no PDF DOI: 10.1016/j.yexcr.2025.114630
SNAI1

GATA2 decommissioning of enhancers: A mechanism to constrain inflammatory signaling.

Mabel M Jung, Vu L Tran, Yue Xiong +4 more · 2025 · Cell reports · Elsevier · added 2026-04-24
GATA2 establishes transcriptomes governing hematopoietic stem/progenitor cell development. In progenitors, GATA2 represses inflammatory genes (Il6st and Il6ra) encoding IL6ST/GP130 and IL6RA receptor Show more
GATA2 establishes transcriptomes governing hematopoietic stem/progenitor cell development. In progenitors, GATA2 represses inflammatory genes (Il6st and Il6ra) encoding IL6ST/GP130 and IL6RA receptor subunits mediating IL-6 signaling. While IL6ST heterodimerizes with IL6RA, IL-11, IL-27, oncostatin M, and leukemia inhibitory factor receptors, IL6RA heterodimerizes exclusively with IL6ST to confer IL-6 signaling. As GATA2-dependent repression is not well understood, we devised a multi-omics strategy to elucidate mechanisms underlying repression and applied the approach to the cytokine/chemokine receptor gene family. Identifying accessible distal and intronic chromatin sites in GATA2-deficient (GATA2 Show less
đź“„ PDF DOI: 10.1016/j.celrep.2025.116344
IL27

LncRNA BACE1-AS delays the propagation of

Shuang Huang, Xin Yang, Ting-Li Liu +5 more · 2025 · Microbiology spectrum · added 2026-04-24
đź“„ PDF DOI: 10.1128/spectrum.02022-24
BACE1

Association between 24-hour movement behaviors and depressive symptoms among urban older adults in china: a compositional isotemporal substitution analysis.

Hu Ji, Glenn Roswal, Jing Min Liu +2 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
To examine the association between 24-hour movement behaviors and depressive symptoms in older adults using compositional data analysis, and to investigate the dose-response characteristics of time re Show more
To examine the association between 24-hour movement behaviors and depressive symptoms in older adults using compositional data analysis, and to investigate the dose-response characteristics of time reallocations between movement behaviors in relation to depressive symptoms. A cross-sectional study was conducted among 1093 urban-dwelling older adults aged 60 years and above in selected communities of Jinan City, Shandong Province, China, between April 2024 and September 2024. The Chinese version of the International Physical Activity Questionnaire-Long Form (IPAQ-LF) was used to estimate time spent in moderate to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), sedentary behavior (SB), and sleep (SLP) across a typical 24-hour day. The Chinese version of the Patient Health Questionnaire Depression Scale-9 item (PHQ-9) was applied to assess depressive symptoms. Compositional isotemporal substitution models were employed to explore the associations between time reallocations among 24-hour movement behaviors and depressive symptoms, accounting for the co-dependent nature of time-use data. (1) The geometric means of time spent in MVPA, LPA, SB, and SLP were 25.33 minutes, 141.26 minutes, 738.10 minutes, and 455.15 minutes, respectively. Variation matrix analysis revealed the highest log-ratio variance between MVPA and SB (0.168), and the lowest between SLP and SB (0.031). (2) The prevalence of screening-positive depressive symptoms was 16.29% among Chinese urban older adults. (3) Results from compositional linear regression models showed that time allocated to MVPA, LPA, and SLP (relative to the remaining movement behaviors) was negatively associated with depressive symptoms, while time spent in SB was positively associated. (4) Dose-response analysis further indicated that: (a) MVPA substitutions with other movement behaviors exhibited nonlinear and markedly asymmetric effects on depressive symptoms; (b) replacing MVPA with LPA, SB, or SLP resulted in increasingly larger changes in predicted scores as substitution duration increased, whereas the reverse substitution (MVPA for other movement behaviors) produced progressively smaller changes; and (c) substitutions between SB and LPA displayed linear and symmetrical effects. The findings provide evidence of an association between 24-hour movement behaviors and depressive symptoms in Chinese urban-dwelling older adults and reinforce the importance of achieving a balance between different types of movement behaviors over a 24-hour period for mental health. Show less
đź“„ PDF DOI: 10.3389/fpsyt.2025.1706591
LPA

Selenium Nanoparticles vs Selenite Fertilizers: Implications for Toxicological Profiles, Antioxidant Defense, and Ferroptosis Pathways.

Qiting Fang, Zhonghua Liu, Kaixi Wang · 2025 · Journal of agricultural and food chemistry · ACS Publications · added 2026-04-24
Selenium (Se) foliar fertilizers enhance crop nutrition and address human selenium deficiency, while improper application may lead to excessive intake and residue accumulation. Our study comprehensive Show more
Selenium (Se) foliar fertilizers enhance crop nutrition and address human selenium deficiency, while improper application may lead to excessive intake and residue accumulation. Our study comprehensively assessed the toxicity and function of novel selenium nanoparticles and traditional sodium selenite fertilizers across cell, zebrafish, and murine models. Both fertilizers enhanced antioxidant pathways at low doses, but selenium nanoparticles exhibited stronger antioxidant and ferroptosis-modulating effects with lower toxicity at a high dose. Sodium selenite increased total and lipid ROS production, leading to decreased viability of cells and increased distortion and mortality of zebrafish. In mice, sodium selenite induced hepatic toxicity and decreased GPX4. Transcriptome analysis revealed that sodium selenite downregulated c-JUN and APOA4, weakening the antioxidant defense, whereas selenium nanoparticles promoted ferroptosis resistance through FGF21. These findings suggest selenium nanoparticles as a safer alternative for Se biofortification, mitigating health risks while supporting food security and environmental sustainability. Show less
no PDF DOI: 10.1021/acs.jafc.5c02034
APOA4

Impact of dietary lysophospholipids supplementation on growth performance, meat quality, and lipid metabolism in finishing bulls fed diets varying in fatty acid saturation.

Meimei Zhang, Haixin Bai, Ruixue Wang +5 more · 2025 · Journal of animal science and biotechnology · BioMed Central · added 2026-04-24
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipi Show more
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipid metabolism of finishing beef bulls. Thirty-two Angus bulls (initial body weight: 623 ± 22.6 kg; 21 ± 0.5 months of age) were used. The experiment was a completely randomized block design with a 2 × 2 factorial arrangement of treatments: 2 diets with FA of different degree of unsaturation [high saturated FA diet (HSFA) vs. high unsaturated FA diet (HUFA)] combined with (0.075%, dry matter basis) and without lysophospholipids supplementation. The bulls were fed a high-concentrate diet (forage to concentrate, 15:85) for 104 d including a 14-d adaptation period and a 90-d data and sample collection period. No interactions were observed between dietary FA and lysophospholipids supplementation for growth and meat quality parameters. A greater dietary ratio of unsaturated FA (UFA) to saturated FA (SFA) from 1:2 to 1:1 led to lower DM intake and backfat thickness, but did not affect growth performance and other carcass traits. Compared with HSFA, bulls fed HUFA had greater shear force in Longissimus thoracis (LT) muscle, but had lower intramuscular fat (IMF) content and SOD content in LT muscle. Compared with HUFA, feeding the HSFA diet up-regulated expression of ACC, FAS, PPARγ, and SCD1, but down-regulated expression of CPT1B. Compared with feeding HSFA, the HUFA diet led to greater concentrations of c9-C18:1 and other monounsaturated FA in LT muscle. Feeding HUFA also led to lower plasma concentrations of cholesterol, but there were no interactions between FA and lysophospholipids detected. Feeding lysophospholipids improved growth and feed conversion ratio and altered meat quality by increasing muscle pH Results indicated that supplementing a high-concentrate diet with lysophospholipids to beef bulls can enhance growth rate, feed efficiency, meat quality, and beneficial FA. Increasing the dietary ratio of UFA to SFA reduced DM intake and backfat thickness without compromising growth, suggesting potential improvements in feed efficiency. Show less
đź“„ PDF DOI: 10.1186/s40104-024-01138-w
LPL

Comparative analysis between physical activities and circulating lipids from pregnant individuals in Wuhan, from July 2024 to March 2025.

Xiaodan He, Yang Liu, Chaoli Chen +1 more · 2025 · Frontiers in sports and active living · Frontiers · added 2026-04-24
Maternal circulating lipid concentrations impact the risk of pregnancy complications and infant health outcomes. The associations between physical activity and circulating lipids during pregnancy rema Show more
Maternal circulating lipid concentrations impact the risk of pregnancy complications and infant health outcomes. The associations between physical activity and circulating lipids during pregnancy remain inadequately understood. A study was conducted from July 2024 to March 2025, involving the recruitment of 520 pregnant women in Wuhan, China. The Pregnancy Physical Activity Questionnaire (PPAQ) scores were evaluated in trimesters. Circulating lipid profiles, including total triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), apolipoprotein A1 (APOA1) and apolipoprotein B (APOB) concentrations, were assessed at each trimester. The daily energy expenditure of physical activity (EEPA) during the first, second, and third trimesters was recorded as 11.35, 9.07, and 9.48 metabolic equivalents-hour/day (METs-h/d). The EEPA in the first trimester was significantly greater than that in the second ( This study suggests that increased physical activity during pregnancy is associated with lower lipid levels. Moreover, maternal age appears to have a significant impact on physical activity and the metabolism of circulating lipids during pregnancy. Show less
đź“„ PDF DOI: 10.3389/fspor.2025.1621665
APOB

Retraction of "Design, Synthesis, and Biological Evaluation of Notopterol Derivatives as Triple Inhibitors of AChE/BACE1/GSK3β for the Treatment of Alzheimer's Disease".

Nan Wang, Wenjie Liu, Lijun Zhou +11 more · 2025 · ACS omega · ACS Publications · added 2026-04-24
[This retracts the article DOI: 10.1021/acsomega.2c03368.].
đź“„ PDF DOI: 10.1021/acsomega.5c06137
BACE1