👤 Ke 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, Fengjuan 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-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

Qingre Sanjie Formula alleviates atherosclerosis by promoting LXR-α/ABCG5/G8-mediated reverse cholesterol transport and bile acid synthesis.

Xiao Li, Xianglong Huang, Keyan Song +5 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Show more
Atherosclerosis is the leading cause of cardiovascular disease-related morbidity and mortality. The traditional Chinese medicine Qingre Sanjie Formula (QRSJF), composed of Prunellae Spica, Sargassum, Fritillariae Thunbergii Bulbus, Leonuri Herba, and Forsythiae Fructus, has shown efficacy in treating cardiovascular diseases, although its mechanisms are unclear. This study aimed to explore the protective effects of QRSJF against atherosclerosis and the mechanisms involved. The composition of QRSJF was analyzed using Ultra Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry. An 8-week high-fat diet (HFD)-induced atherosclerosis model was established in ApoE Both low- and high-dose QRSJF effectively attenuated dyslipidemia and decreased serum inflammatory cytokine levels in HFD-fed ApoE QRSJF improves dyslipidemia and reduces atherosclerotic plaque in ApoE Show less
no PDF DOI: 10.1016/j.phymed.2025.156691
NR1H3

Multi-omics analysis reveals that alginate oligosaccharides mitigate ochratoxin A-induced renal impairment in mice and is relevant to the regulation of PPAR signaling.

Xueqing Ye, Yue Zhao, Qinghua Yao +3 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Ochratoxin A (OTA) is a core environmental toxin that induces kidney injury by interfering with glomerular filtration, antioxidant defense, and tubular transport functions. Alginate oligosaccharides ( Show more
Ochratoxin A (OTA) is a core environmental toxin that induces kidney injury by interfering with glomerular filtration, antioxidant defense, and tubular transport functions. Alginate oligosaccharides (AOS), as active substances from marine, carry natural antioxidant, anti-inflammatory and other biological activities. The purpose of this study is to explore the molecular network of AOS against nephrotoxicity caused by OTA. A total of 36 5-week male mice were randomly divided into three groups: the CON group, the OTA group (250 μg/kg B.W. OTA) and the AOS + OTA group (400 mg/kg B.W. AOS +250 μg/kg B.W. OTA). The treatment was continued for 21 d. OTA induced renal injury in mice, manifested by glomerular capsule blurring, lymphocytic infiltration, and mitochondrial damage in tubular epithelial cells. Treatment with AOS significantly alleviated these pathological changes. Multi‑omics analysis revealed that AOS activated the PPAR signaling pathway, upregulating key genes (Aldehyde Dehydrogenase 1 Family Member A3 ( This study reveal that AOS antagonizes OTA-induced nephrotoxicity in mice through PPAR signaling axis, thus providing new insight into the renal protection mechanism of marine active substances. Show less
📄 PDF DOI: 10.3389/fvets.2025.1702799
CPS1

Emerging roles of angiopoietin‑like 4 in human tumors (Review).

Ruyi Liu, Miaomiao Fu, Pengxiang Chen +6 more · 2025 · International journal of oncology · added 2026-04-24
Angiopoietin‑like 4 (ANGPTL4), a member of the angiopoietin family, plays critical roles in angiogenesis, lipid metabolism and inflammation. It has been demonstrated that ANGPTL4 has significant influ Show more
Angiopoietin‑like 4 (ANGPTL4), a member of the angiopoietin family, plays critical roles in angiogenesis, lipid metabolism and inflammation. It has been demonstrated that ANGPTL4 has significant influence on various diseases. Accumulating evidence has highlighted the impacts of ANGPTL4 on human malignancies. ANGPTL4 is commonly overexpressed in various types of cancer, such as breast, non‑small cell lung, gastric and colorectal cancer. Its upregulation promotes tumor growth, invasion, metastasis and angiogenesis, as well as metabolic reprogramming and resistance to programmed cell death, radiotherapy and chemotherapy. However, ANGPTL4 has also exhibited antitumor effects under certain conditions, indicating its complex roles in tumor biology. The transcriptional regulation of ANGPTL4 is influenced by multiple factors, such as HIF‑1, PPARs, TGF‑β and long non‑coding RNAs. In terms of signaling pathways, STATs, PI3K/AKT and COX-2/PGE2 are important in regulating cellular processes. The present review summarizes the biological functions of ANGPTL4 in tumors and its association with patient prognosis. Furthermore, the key molecular mechanisms and potential reasons for its dual roles in cancer are also discussed. In conclusion, ANGPTL4 is a valuable diagnostic biomarker and a potential therapeutic target for human cancers. Show less
📄 PDF DOI: 10.3892/ijo.2024.5715
ANGPTL4

Social Isolation and Its Influencing Factors in Maintenance Haemodialysis Patients: A Latent Profile Analysis.

Luwen Zhang, Fangli Liu, Jinghui Liu +1 more · 2025 · Journal of advanced nursing · Blackwell Publishing · added 2026-04-24
To explore latent profiles of social isolation in maintenance haemodialysis (MHD) patients and to analyse the factors influencing different latent profiles. Multicentre cross-sectional study. Between Show more
To explore latent profiles of social isolation in maintenance haemodialysis (MHD) patients and to analyse the factors influencing different latent profiles. Multicentre cross-sectional study. Between November 2024 to March 2025, 305 MHD patients from the haemodialysis centres of three hospitals in Henan Province, China, were recruited using a convenience sampling method. All participants completed the general information questionnaire, Lubben Social Network Scale 6 (LSNS-6), UCLA Loneliness Scale-6 (ULS-6) and Personal Mastery Scale. Latent Profile Analysis (LPA) was used to classify the participants into potential subgroups with different types of social isolation. The influencing factors of profiles were explored by univariate analysis and multiple logistic regression analysis. Social isolation of 305 patients can be divided into three profiles: the family-friend dual isolation group (14.10%), friend isolation-only group (47.54%), and social network well-being group (38.36%). Multivariable logistic regression analysis revealed that monthly personal income, living arrangement, social participation, dialysis time, post-dialysis fatigue, number of comorbidities, loneliness and personal mastery were identified as factors influencing the profiles. There is heterogeneity in social isolation among MHD patients. It is therefore necessary to implement targeted intervention measures based on the distinct characteristics of each subgroup to facilitate their social reintegration. Nurses should identify differences in social isolation among MHD patients. It is necessary to establish tripartite connections between families, hospitals and communities, and develop personalised psychosocial interventions to alleviate social isolation. The study identified distinct subgroups of social isolation among MHD patients, while emphasising the impact of psychological resources such as loneliness and personal mastery on social isolation. This may offer critical insights for nurses to develop targeted interventions for patients' social health. The study followed the STROBE guidelines for cross-sectional studies. No patient or public involvement. Show less
no PDF DOI: 10.1111/jan.70452
LPA

Cardiac-targeted FGF4 encapsulated nanoliposomes improve acute myocardial injury induced by ischemia-reperfusion and adriamycin in in vitro and in vivo models.

Kaihao Wang, Yipeng Du, Peixin Li +5 more · 2025 · Materials today. Bio · Elsevier · added 2026-04-24
Ischemia-reperfusion (IR) and adriamycin (also named doxorubicin, DOX)-induced acute myocardial injuries have a significant impact on health, causing serious economic and medical burdens. Therefore, w Show more
Ischemia-reperfusion (IR) and adriamycin (also named doxorubicin, DOX)-induced acute myocardial injuries have a significant impact on health, causing serious economic and medical burdens. Therefore, we need to explore and identify drugs with potential therapeutic value for treating I/R- and DOX-induced myocardial injury. In the present study, we explored the therapeutic potential of FGF4 for I/R and DOX-induced myocardial injury. We found that FGF4 showed good improvement in acute cardiac injury. However, due to the short half-life of FGF4, we further prepared a myocardial-targeted FGF4-sustained release nanoliposome (named FGF4-NANO-IMTP). We investigated the effect of FGF4-NANO-IMTP on myocardial injury caused by I/R and DOX. Show less
📄 PDF DOI: 10.1016/j.mtbio.2025.101984
FGFR1

Loss of C-Terminal Coiled-Coil Domains in SDCCAG8 Impairs Centriolar Satellites and Causes Defective Sperm Flagellum Biogenesis and Male Fertility.

Kecheng Li, Xiaoli Zhou, Wenna Liu +4 more · 2025 · Cells · MDPI · added 2026-04-24
Sperm flagellum defects are tightly associated with male infertility. Centriolar satellites are small multiprotein complexes that recruit satellite proteins to the centrosome and play an essential rol Show more
Sperm flagellum defects are tightly associated with male infertility. Centriolar satellites are small multiprotein complexes that recruit satellite proteins to the centrosome and play an essential role in sperm flagellum biogenesis, but the precise mechanisms underlying this role remain unclear. Show less
📄 PDF DOI: 10.3390/cells14151135
BBS4

Research Progress of Nattokinase in Reducing Blood Lipid.

Chuyang Wei, Ruitao Cai, Yingte Song +2 more · 2025 · Nutrients · MDPI · added 2026-04-24
The purpose of this paper is to comprehensively review the research progress of nattokinase in lowering blood lipid, including its source, structure and physicochemical properties, mechanisms of funct Show more
The purpose of this paper is to comprehensively review the research progress of nattokinase in lowering blood lipid, including its source, structure and physicochemical properties, mechanisms of functions, clinical research status, and safety considerations, so as to provide reference for further research on the application of nattokinase in the treatment of dyslipidemia. Natto is a traditional Japanese fermented food, which is made from soybeans fermented by Bacillus natto. During the fermentation process, natto will produce a variety of biologically active substances, including nattokinase. Nattokinase (NK) is a serine protease with stable enzyme activity and good freeze-thaw tolerance, which exerts lipid-lowering and anti-atherosclerotic effects by activating hormone-sensitive lipase (HSL), inhibiting hydroxymethylglutaryl monoacyl coenzyme A reductase (HMG-CoA reductase), and enhancing lipoprotein lipase (LPL) activity. Large-scale clinical trials have confirmed that nattokinase significantly improves the lipid profile and reduces the atherosclerotic plaque area and intima-media thickness with a favorable safety profile. Compared with traditional lipid-lowering drugs (e.g., statins and fibrates), nattokinase has a multifaceted lipid-lowering mechanism and lower risk of side effects, which makes it suitable for patients intolerant of traditional drugs; when combined with natural products such as statins, fibrates, red yeast, and lifestyle interventions, it can play a synergistic role and further reduce the risk of cardiovascular disease. There are various types of nattokinase preparations on the market, and consumers should choose regular products with high activity and purity, and pay attention to their safety and applicable population. Show less
📄 PDF DOI: 10.3390/nu17111784
LPL

Nutrient-Enriched Germinated Brown Rice Alters the Intestinal Ecological Network by Regulating Lipid Metabolism in Rats.

Chuanying Ren, Shuwen Lu, Shan Shan +7 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Metabolic diseases such as high blood lipids, high blood sugar, and disrupted gut microbiota pose a serious threat to people's physical health. The occurrence of these diseases is closely related to t Show more
Metabolic diseases such as high blood lipids, high blood sugar, and disrupted gut microbiota pose a serious threat to people's physical health. The occurrence of these diseases is closely related to the lack of nutrients in daily rice staple foods, but there is a lack of comprehensive analysis of the underlying mechanisms. This study used fully nutritious brown rice as raw material, and after germination under various stress conditions, it significantly increased the levels of gamma aminobutyric acid (GABA, four carbon non protein amino acid), resistant starch, flavonoids, and other components that regulate metabolic diseases. Using rats as experimental subjects, a model of hyperlipidemia and hyperglycemia was constructed, with rice consumption as the control. The experimental period was 8 weeks. Research has found that feeding sprouted brown rice can significantly improve the accumulation of white fat in the liver caused by a high-fat diet, significantly reduce TC, TG, LDL-C, apoB, HL, LPL, and LCAT, significantly increase HDL-C and apoA1, and significantly reduce the levels of inflammatory factors IL-6 and TNF-α. Therefore, consuming sprouted brown rice can reduce the risk of hyperlipidemia, inflammation, and tumor occurrence by promoting fat breakdown, and can also increase the abundance of metabolic-promoting microorganisms (especially Euryarchaeota and Lactobacillus) in the intestine, improving the entire metabolic ecological network of rats. Show less
📄 PDF DOI: 10.3390/ijms26167693
APOB

APOE Lipoprotein Particles: Pathophysiology, Therapy, and the Crosstalk in Alzheimer's Disease and Cardiovascular Disease.

Chan Liu, Juan Liu, Yan-Yang Wang +2 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
The APOE4 variant was the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Individuals with APOE4 have an increased risk of developing the disease at an early age of onset. Similar Show more
The APOE4 variant was the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Individuals with APOE4 have an increased risk of developing the disease at an early age of onset. Similarly, APOE4 carriers are predisposed to high cholesterol levels and tend to have an increased risk of cardiovascular disease (CVD). The global allele frequency of APOE4 was 13.7%, underlining its widespread impact on global human health. Conversely, the relatively rare APOE2 allele was a genetic protective factor against AD and CVD. However, the mechanisms underlying this association remain to be elucidated. The apolipoprotein E (APOE) protein coats lipoprotein particles and mediates lipid transport and metabolism in the peripheral circulation and central nervous system (CNS). Although initial studies causally linked APOE lipoprotein particles (APOE particles) with lipid homeostasis, our understanding of the physiological and pathological effects of APOE particles has extended to amyloid-β (Aβ) accumulation, tau hyperphosphorylation and spread, as well as neuroinflammation in AD initiation and progression. Moreover, the most examined functions of APOE particles are reverse cholesterol transport, anti-inflammatory, anti-oxidation, and improvement of endothelial dysfunction in atherosclerotic CVD. This review outlines what is known about the structure and functions of APOE particles, emphasizing their involvement in AD and CVD pathogenesis, while also considering the crosstalk between the peripheral circulation and CNS. In addition, we discuss how these APOE particles act as therapeutic targets. Show less
📄 PDF DOI: 10.1007/s12035-025-05629-3
APOE

CircSETD2 impairs hepatic lipid homeostasis in metabolic dysfunction-associated fatty liver disease by binding CPS1.

Xuancheng Xie, Hongjie Fan, Mengyao Zheng +8 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Dysregulation of hepatic lipid homeostasis constitutes a core pathogenic mechanism in metabolic dysfunction-associated fatty liver disease (MAFLD); however, the regulatory role of circular RNAs (circR Show more
Dysregulation of hepatic lipid homeostasis constitutes a core pathogenic mechanism in metabolic dysfunction-associated fatty liver disease (MAFLD); however, the regulatory role of circular RNAs (circRNAs) in this process remains unclear. In this study, hepatic circRNAs transcriptomic profiling of MAFLD patients identified circSETD2-generated from exons 16-18 of the SETD2 gene-as a stably expressed and significantly upregulated novel circRNA with a closed circular structure localized in the cytoplasm of MAFLD patient liver tissues. Silencing circSETD2 attenuated free fatty acid - induced lipid accumulation in vitro by reducing lipogenesis and enhancing fatty acid β-oxidation. In high fat diet - fed mice, hepatic circSETD2 silencing mitigated steatosis, improved liver function, and reversed dyslipidemia. Mechanistically, RNA pull-down coupled with LC-MS/MS identified carbamoyl phosphate synthetase 1 (CPS1) as a circSETD2-interacting protein, which was subsequently validated by RNA immunoprecipitation and fluorescence in situ hybridization. Pharmacological modulation of CPS1 enzymatic activity in circSETD2-silenced cells established its mediator role. Specifically, circSETD2 directly bound to CPS1, reducing its enzymatic activity and thereby exacerbating lipid metabolic disturbances and disease progression in MAFLD. In summary, circSETD2 drives MAFLD pathogenesis by impairing CPS1-mediated regulation of lipid homeostasis, positioning it as a promising prognostic biomarker and therapeutic target. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.148879
CPS1

Molecular Characterization and Functional Insights into Goose IGF2BP2 During Skeletal Muscle Development.

Cui Wang, Yi Liu, Jiuli Dai +2 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) is an RNA-binding protein known to play critical roles in metabolism, cell proliferation, and tumorigenesis. Although its involvement in m Show more
Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) is an RNA-binding protein known to play critical roles in metabolism, cell proliferation, and tumorigenesis. Although its involvement in muscle development has been documented in several species, the function of goose IGF2BP2 remains largely unexplored. In this study, we cloned and characterized the full-length cDNA and genomic DNA sequences of goose IGF2BP2. The cDNA is 2957 bp in length and contains a 1662 bp open reading frame encoding a 553-amino acid protein with five conserved RNA-binding domains. The genomic sequence spans 12,183 bp and consists of 12 exons and 11 introns. A total of 60 genetic variants were identified, including a deletion of a G base at position 2299 (g.2299delG) that results in a frameshift mutation. Expression analysis revealed high levels of IGF2BP2 mRNA in the liver, heart, and muscle tissues of female geese across embryonic (E25d), growing (A70d), and laying (L270d) stages, consistent with a potential role in muscle development ( Show less
📄 PDF DOI: 10.3390/ani16010058
MYBPC3

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
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB

Lipid-lowering drug targets associated with risk of respiratory disease: a Mendelian randomization study.

Zhipeng Gong, Dongsheng Wu, Yin Ku +4 more · 2025 · BMC pulmonary medicine · BioMed Central · added 2026-04-24
Observational studies have identified a possible connection between lipid-lowering medications and respiratory illnesses. However, it remains unclear whether lipid-lowering drugs is causative for resp Show more
Observational studies have identified a possible connection between lipid-lowering medications and respiratory illnesses. However, it remains unclear whether lipid-lowering drugs is causative for respiratory diseases, and we aimed to answer this question. We performed Mendelian randomization (MR) analyses by integrating data from genome-wide association studies (GWAS). Three statistical approaches were employed for MR analysis: inverse variance weighting (IVW), MR-Egger, and weighted median. The purpose was to evaluate the causal relationships between 10 drug targets that lower lipid levels and the likelihood of developing 7 respiratory diseases. Additional sensitivity analyses were conducted to ensure the robustness and validity of the results. After adjusting for multiple testing, our MR analysis identified APOB (odd ratios [OR]: 0.86; 95% confidence interval [CI]: 0.77 to 0.97; P Our findings suggest a likely causal relationship between respiratory diseases and lipid-lowering drug targets. Further mechanistic and clinical research is needed to confirm and validate these findings. Show less
📄 PDF DOI: 10.1186/s12890-025-03527-x
APOB

Joint associations of accelerometer-measured physical activity and cardiovascular-kidney-metabolic syndrome stages with the risks of cancer and all-cause mortality.

Jia-Cheng Liu, Rui Yang, Zan-Fei Feng +9 more · 2025 · Journal of the National Cancer Institute · Oxford University Press · added 2026-04-24
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly u Show more
Cardiovascular-kidney-metabolic (CKM) syndrome significantly increases cancer and mortality risks, but the combined effects of CKM syndrome and physical activity (PA) on these outcomes remain poorly understood. This prospective study included 66,650 UK Biobank participants with accelerometry data. CKM syndrome was classified into five stages based on metabolic, kidney, and cardiovascular health. PA was categorized by intensity into light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) levels, and further divided into tertiles by daily duration. Multivariable Cox models were used to estimate hazard ratios. Over a median follow-up of 8.03 years, 4,301 incident cancer cases and 2,442 deaths occurred. Advancing CKM stages were associated with elevated risks of both cancer incidence and all cause mortality, while increasing PA levels reduced these risks. Significant interactions were observed between CKM syndrome and both MPA and MVPA on cancer and mortality risks (P interaction < 0.05). In participants with the lowest tertile of MPA or MVPA, those in stages 2 and 4 had higher cancer risk, while in the highest tertile, this risk was no longer elevated. For all-cause mortality, in participants with the lowest tertile of MPA or MVPA, CKM stage 3 exhibited higher risks, while those in the highest tertile did not. CKM stage 4 remained associated with higher mortality across all PA intensity levels, but risks decreased with increasing MVPA levels. Higher levels of MPA and MVPA may mitigate the elevated risks of both cancer incidence and all-cause mortality associated with CKM stages 2 to 4. Show less
no PDF DOI: 10.1093/jnci/djaf365
LPA

The role of serun lipid, cytokine production in sudden sensorineural hearing loss.

Xiaoqing Zhang, Zhihua Xu, Yehai Liu · 2025 · Cytotechnology · Springer · added 2026-04-24
Sudden sensorineural hearing loss (SSNHL) has serious harm to human hearing health, where blood lipid and inflammatory levels may play a key role in it. Thus, the purpose of this investigation was to Show more
Sudden sensorineural hearing loss (SSNHL) has serious harm to human hearing health, where blood lipid and inflammatory levels may play a key role in it. Thus, the purpose of this investigation was to assess the connection between inflammatory and lipid variables and SSNHL. Patients diagnosed with SSNHL had an analysis of serum lipid parameters, such as total cholesterol (TC), triglycerides, HDL-C, LDL-C, apolipoprotein A (apo A), apolipoprotein B (apo B), and lipoprotein A (Lp(a)), as well as inflammatory factors like TNF-α and IL-10. After that, risk factor analysis was carried out utilizing univariate, multivariate regression, and LASSO retrospective modeling. In all, 72 SSNHL patients and 67 healthy control individuals were involved. The LDL/HDL, total cholesterol, ApoB, LP(a), IL-10, TNF-α, and IFN-γ considerably higher in the SSNHL group than in the healthy control group, however, nervonic acid and coenzyme Q were decreased significantly in SSNHL than Control group. The multivariate logistic regression model's analysis using multifactorial retrospective modeling revealed significant changes in LDL, LDL/HDL, IL-10, and TNF-α. In addition, in the LASSO regression model, the model demonstrated high discrimination, as evidenced by the C-index for the cohort's prediction nomogram, which was 0.998 (95% CI, 0.154-1.115) and confirmed to be 0.925 following bootstrapping validation. Finally, IL-10 and LDL/HDL were the main risk factors in SSNHL. LDL/HDL and IL-10 may be closely related to SSNHL's progress and should be evaluated promptly before treating patients with SSNHL. Show less
no PDF DOI: 10.1007/s10616-025-00722-w
APOB

Design, synthesis, and biological evaluation of novel FGFR1 PROTACs.

Yu-Wei Wang, Yu-Hui Gao, Cheng Wang +6 more · 2025 · Bioorganic chemistry · Elsevier · added 2026-04-24
Dysregulation of the fibroblast growth factor receptor 1 (FGFR1) signaling has prompted efforts to develop therapeutic agents, which is a carcinogenic driver of many cancers, including breast, prostat Show more
Dysregulation of the fibroblast growth factor receptor 1 (FGFR1) signaling has prompted efforts to develop therapeutic agents, which is a carcinogenic driver of many cancers, including breast, prostate, bladder, and chronic myeloid leukemia. Despite significant progress in the development of potent and selective FGFR inhibitors, the long-term efficacy of these drugs in cancer therapy has been hampered by the rapid onset of acquired resistance. Therefore, more drug discovery strategies are needed to promote the development of FGFR-targeted drugs. Here, we discovered compound S2h, a compound that selectively and effectively degrades FGFR1 at nanomolar concentrations in KG1a cells (IC Show less
no PDF DOI: 10.1016/j.bioorg.2024.108109
FGFR1

Increased Sirtuin 6 Activity in Tumor Cells Can Prompt CD4-Positive T-Cell Differentiation Into Regulatory T Cells and Impede Immune Surveillance in the Microenvironment.

Nan Yang Zhang, Wen Yuan Liu, Ke Hua Fang +1 more · 2025 · World journal of oncology · added 2026-04-24
Sirtuin 6 (Sirt6) is expressed at increased levels in many tumors and may be involved in immunoregulation. The present study investigated how Sirt6 in tumor cells affects immune surveillance. The huma Show more
Sirtuin 6 (Sirt6) is expressed at increased levels in many tumors and may be involved in immunoregulation. The present study investigated how Sirt6 in tumor cells affects immune surveillance. The human tumor cell lines A2780, HeLa, Huh7, MBA-MD-231, SMMC-7721 and SW480 were incubated with UBCS039, a target-selective activator of Sirt6, to stimulate Sirt6 activity. These cells, following washing to remove residual UBCS039, were cultured with human naive CD4 Following culture with UBSC039-pretreated tumor cells, the proportion of Tregs among CD4 The present study suggested that increased Sirt6 expression and activity in tumor cells can suppress immune surveillance by increasing Treg, ADO, PD-1 and PD-L1 levels, decreasing IFN-γ production, and altering tumor-promoting and antitumor gene expression in the microenvironment. Show less
📄 PDF DOI: 10.14740/wjon2547
CPS1

Increased neuroplastic activity in the pathogenesis of Alzheimer's disease.

Corey J Bolton, Panpan Zhang, Sydney R Wilhoite +12 more · 2025 · Alzheimer's & dementia : the journal of the Alzheimer's Association · Wiley · added 2026-04-24
We test the hypothesis that high levels of neuroplasticity in the context of Alzheimer's disease (AD) risk factors are involved in AD pathogenesis by investigating interactions between cerebrospinal f Show more
We test the hypothesis that high levels of neuroplasticity in the context of Alzheimer's disease (AD) risk factors are involved in AD pathogenesis by investigating interactions between cerebrospinal fluid (CSF) levels of growth-associated protein-43 (GAP-43) and AD risk factors (female sex, cerebrovascular risk, mild cognitive impairment, apolipoprotein E [APOE] ε4 genotype, amyloid positivity) on CSF biomarkers of AD pathology (amyloid beta 42/40[Aβ42/40], phosphorylated tau (p-tau)) and neurodegeneration (tau). Baseline GAP-43 levels in 161 non-demented older adults were related to cross-sectional and longitudinal (mean follow-up = 4 years) CSF biomarkers of AD, adjusting for covariates, with GAP-43 x AD risk factor interaction terms. Higher GAP-43 was cross-sectionally related to all AD biomarkers (p-values < 0.0001) and predicted longitudinal reductions in Aβ42 (p < 0.0001). Associations were stronger in AD risk groups. We found strong support linking increased levels of neuroplasticity in the context of AD risk factors to the pathological cascade of AD over a 4-year mean follow-up period. Cerebrospinal fluid growth-associated protein-43 (GAP-43) is associated with Alzheimer's disease (AD) biomarkers cross-sectionally and longitudinally. GAP-43 interacts with AD risk factors to predict AD biomarkers. Increased neuroplastic activity may play a role in AD pathogenesis. Show less
📄 PDF DOI: 10.1002/alz.70897
APOE

LMOD2 interaction with ACTC1 regulates myogenic differentiation.

Kaiming Wang, Caihong Liu, Lei Yi +9 more · 2025 · BMC genomics · BioMed Central · added 2026-04-24
Skeletal muscle is the largest tissue in mammals, and it plays a crucial role in metabolism and homeostasis. Skeletal muscle development and regeneration consist of a series of carefully regulated cha Show more
Skeletal muscle is the largest tissue in mammals, and it plays a crucial role in metabolism and homeostasis. Skeletal muscle development and regeneration consist of a series of carefully regulated changes in gene expression. Leiomodin2 (LMOD2) gene is specifically expressed in the heart and skeletal muscle. But the physiological functions and mechanisms of LMOD2 on skeletal muscle development are unknown. In this study, we examined the expression levels of the LMOD2 in porcine tissues and C2C12 cells. LMOD2 is mainly expressed in the heart, followed by skeletal muscle. The expression level of LMOD2 gradually decreased with skeletal muscle growth, but increased after injury. LMOD2 expression levels increased gradually with C2C12 cells proliferation and differentiation. In terms of function, the muscle fiber types were altered after LMOD2 was knocked out in C2C12 cells, MyHC-I and MyHC-2b were inhibited, whereas MyHC-2a and MyHC-2x were promoted. LMOD2 knockout has different effects on LMOD family, LMOD1 expression level was promoted, while LMOD3 was inhibited. Loss of LMOD2 suppressed cell viability and PAX7 protein expression. At the transcriptome level, proliferation-related genes and muscle contraction-related genes were respectively inhibited after LMOD2 knockout. In terms of molecular networks, a series of experiments have shown that MyoG is a transcription factor for LMOD2, while miR-335-3p can negatively regulate LMOD2 expression. We screened ACTC1 as a candidate interacting protein for LMOD2 using protein prediction software and RNA-seq, and Co-IP experiments confirmed the relationship between LMOD2 and ACTC1. In vivo, Lentivirus-mediated LMOD2 knockdown reduces muscle mass. LMOD2 knockdown inhibited MyHC-I mRNA expression, but had no effect on MyHC-2b. The protein expression of MyHC-I, MyHC-2x, and MyHC-2b was suppressed after LMOD2 knockdown. Collectively, our data indicates that LMOD2 knockout inhibits myoblast proliferation and alters muscle fiber types. MyoG is a transcription factor for LMOD2, while miR-335-3p can negatively regulate LMOD2 expression. Moreover, LMOD2 and ACTC1 interact to regulate myogenic differentiation. Our study provides a new target for skeletal muscle development. Show less
📄 PDF DOI: 10.1186/s12864-025-11897-z
LMOD1

Research status and future perspectives of IL‑27 in the treatment of stroke (Review).

Weiqin Liu, Zhenyou Zou, Wenyang Li +4 more · 2025 · International journal of molecular medicine · added 2026-04-24
Stroke is a life‑threatening cerebrovascular disorder categorized into two major subtypes: Ischemic and hemorrhagic. Characterized by high morbidity and mortality rates, its clinical management remain Show more
Stroke is a life‑threatening cerebrovascular disorder categorized into two major subtypes: Ischemic and hemorrhagic. Characterized by high morbidity and mortality rates, its clinical management remains challenging due to limited therapeutic options. Interleukin (IL)‑27, a pleiotropic cytokine with demonstrated neuroprotective potential, has emerged as a promising candidate for stroke intervention. IL‑27 exerts immunomodulatory effects within the central nervous system, including suppression of proinflammatory T‑cell proliferation and induction of regulatory T‑cell differentiation. These mechanisms collectively attenuate neuroinflammation, mitigate neuronal apoptosis and prevent neurodegenerative processes. The efficacy of IL‑27 in reducing cerebral damage in both ischemic and hemorrhagic stroke models has been validated, although clinical translation remains to be achieved. The present review summarizes: i) The epidemiology of stroke; ii) the immunoregulatory functions of IL‑27 and its neuroprotective mechanisms across stroke subtypes; iii) innovative brain‑targeted delivery approaches; iv) IL‑27 clinical applicability with supporting evidence; and v) possible risks and solutions in clinical applications. By collating the current knowledge, the present study provides a translational framework for advancing IL‑27‑based therapies in stroke management. Show less
📄 PDF DOI: 10.3892/ijmm.2025.5557
IL27

Machine learning models for predicting short-term progression in patients with stage 4 chronic kidney disease: a multi-center validation study.

Jingshu Li, Xuanyi Du, Rui Zhang +7 more · 2025 · Scientific reports · Nature · added 2026-04-24
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challen Show more
End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challenging. Accurate prediction can improve advanced care planning and patient outcomes. This study aimed to develop and validate a machine learning (ML) model for predicting progression within 25 weeks (approximately six months) of ESRD in patients with stage 4 CKD. Electronic health records (EHRs) of patients with stage 4 CKD were analyzed. Nine ML models including Ridge regression (Ridge), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to predict short-term progression to ESRD within 25 weeks. The models were trained and externally validated using the data of 346 and 105 patients. Of the 451 patients with stage 4 CKD, 219 developed ESRD. Among the evaluated models, XGBoost demonstrated the best overall performance. In the internal validation, it achieved an area under the curve (AUC) of 0.93, an accuracy of 0.90, and an F1 score of 0.89. In the external validation, XGBoost maintained the highest AUC (0.85), accuracy (0.79), and F1 score (0.79), along with the highest average precision (0.89) and a low log-loss (0.48), indicating strong discriminative ability and good generalizability. The top predictive features included high-density lipoprotein cholesterol, Alb, Cys C, ApoB, FGB, Bun, Neutrophil, and Total cholesterol. This study demonstrated the feasibility of ML for assessing ESRD prognosis based on easily accessible clinical features. XGBoost demonstrated superior performance in both internal and external validation, suggesting its potential for future patient screening. Show less
📄 PDF DOI: 10.1038/s41598-025-23037-4
APOB

Shared genetic architecture contributes to risk of major cardiovascular diseases.

Jun Qiao, Lei Jiang, Liuyang Cai +14 more · 2025 · Nature communications · Nature · added 2026-04-24
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations Show more
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations, suggesting a shared genetic basis. However, the precise genetic mechanisms underlying these associations remain elusive. By assessing genetic correlations, genetic overlap, and causal connections, we aim to shed light on common genetic underpinnings among major CVDs. Employing multi-trait analysis, we pursue diverse strategies to unveil shared genetic elements, encompassing SNPs, genes, gene sets, and functional categories with pleiotropic implications. Our study systematically quantifies genetic overlap beyond genome-wide genetic correlations across CVDs, while identifying a putative causal relationship between coronary artery disease (CAD) and heart failure (HF). We then pinpointed 38 genomic loci with pleiotropic influence across CVDs, of which the most influential pleiotropic locus is located at the LPA gene. Notably, 12 loci present high evidence of multi-trait colocalization and display congruent directional effects. Examination of genes and gene sets linked to these loci unveiled robust associations with circulatory system development processes. Intriguingly, distinct patterns predominantly driven by atrial fibrillation, coronary artery disease, and venous thromboembolism underscore the significant disparities between clinically defined CVD classifications and underlying shared biological mechanisms, according to functional annotation findings. Show less
📄 PDF DOI: 10.1038/s41467-025-62419-0
LPA

AAV9-mediated MYBPC3 gene therapy with optimized expression cassette enhances cardiac function and survival in MYBPC3 cardiomyopathy models.

Amara Greer-Short, Anna Greenwood, Elena C Leon +27 more · 2025 · Nature communications · Nature · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) affects approximately 600,000 people in the United States. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM, Show more
Hypertrophic cardiomyopathy (HCM) affects approximately 600,000 people in the United States. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM, with the majority of mutations resulting in haploinsufficiency. To restore cardiac MYBPC3, we use an adeno-associated virus (AAV9) vector and engineer an optimized expression cassette with a minimal promoter and cis-regulatory elements (TN-201) to enhance packaging efficiency and cardiomyocyte expression. Rather than simply preventing cardiac dysfunction preclinically, we demonstrate in a symptomatic MYBPC3-deficient murine model the ability of AAV gene therapy to reverse cardiac hypertrophy and systolic dysfunction, improve diastolic dysfunction, and prolong survival. Dose-ranging efficacy studies exhibit restoration of wild-type MYBPC3 protein levels and saturation of cardiac improvement at the clinically relevant dose of 3E13 vg/kg, outperforming a previously published construct. These findings suggest that TN-201 may offer therapeutic benefits in MYBPC3-associated cardiomyopathy, pending further validation in clinical settings. Show less
📄 PDF DOI: 10.1038/s41467-025-57481-7
MYBPC3

Loss of Nup160 dysregulates Cdc42 in the podocytes of podocyte-specific Nup160 knockout mice.

Deying Liu, Jiaxin Li, Chan Xu +7 more · 2025 · Human molecular genetics · Oxford University Press · added 2026-04-24
Mutations in four genes encoding the outer ring complex of nuclear pore complexes (NPCs), NUP85, NUP107, NUP133 and NUP160, cause monogenic steroid-resistant nephrotic syndrome (SRNS). Knockout of NUP Show more
Mutations in four genes encoding the outer ring complex of nuclear pore complexes (NPCs), NUP85, NUP107, NUP133 and NUP160, cause monogenic steroid-resistant nephrotic syndrome (SRNS). Knockout of NUP85, NUP107, or NUP133 in immortalized human podocytes activates CDC42, an important effector of SRNS pathogenesis. However, it is unknown whether or not loss of NUP160 dysregulates CDC42 in the podocytes. Here, we generated a podocyte-specific Nup160 knockout mouse model with double-fluorescent (mT/mG) Cre reporter genes using CRISPR/Cas9 and Cre/loxP technologies. We investigated nephrotic syndrome-associated phenotypes in the Nup160podo-/- mice, and performed single-cell transcriptomic and proteomic analysis of glomerular suspension cells and cultured primary podocytes, respectively. The Nup160podo-/- mice exhibited progressive proteinuria and fusion of podocyte foot processes. We found decreased Cdc42 protein and normal Cdc42 transcriptional level in the podocytes of the Nup160podo-/- mice using analysis of single-cell transcriptomes and proteomes. We subsequently observed that Cdc42 protein decreased in both kidney tissues and cultured primary podocytes of the Nup160podo-/- mice, although Cdc42 mRNA levels were elevated in the cultured primary podocytes of the Nup160podo-/- mice. We also found that Cdc42 activity was significantly reduced in the cultured primary podocytes of the Nup160podo-/- mice. In conclusion, loss of Nup160 dysregulated Cdc42 in the podocytes of the Nup160podo-/- mice with proteinuria and fusion of podocyte foot processes. Our findings suggest that the dysregulation of CDC42 may contribute to the pathogenesis of SRNS in patients with mutations in NUP160. Show less
no PDF DOI: 10.1093/hmg/ddaf064
NUP160

Osteoclast-derived arachidonic acid triggers dormant lung adenocarcinoma cell activation.

Xingyu Liu, Rong Qiu, Pengcheng Gui +7 more · 2025 · iScience · Elsevier · added 2026-04-24
Dormant lung adenocarcinoma (LUAD) cells in the bone microenvironment can re-emerge as metastatic disease through osteoclast interactions. Using a 3D dormancy model and a mouse bone metastasis model, Show more
Dormant lung adenocarcinoma (LUAD) cells in the bone microenvironment can re-emerge as metastatic disease through osteoclast interactions. Using a 3D dormancy model and a mouse bone metastasis model, this study reveals that arachidonic acid (AA) is the initiating molecule transferred from osteoclasts to dormant LUAD cells, triggering their activation. Dormant LUAD cells uptake AA through CD36, which activates the PPARγ-ANGPTL4 pathway and activates tumor cells. There is a dose-response relationship in the activation effect of AA, and inhibiting AA metabolism prevents this reactivation. The study also finds that the serum levels of AA and ANGPTL4 are significantly elevated in patients with clinical bone metastases compared to those without. This research confirms that osteoclasts transmit AA via the CD36-PPARγ-ANGPTL4 axis to activate dormant LUAD cells, suggesting that AA and ANGPTL4 may serve as valuable biomarkers and potential clinical applications in treatment and prediction of LUAD bone metastasis. Show less
📄 PDF DOI: 10.1016/j.isci.2025.112167
ANGPTL4

Lipids, apolipoproteins, carbohydrates, and risk of hematological malignancies.

Qianwei Liu, Dang Wei, Niklas Hammar +6 more · 2025 · European journal of epidemiology · Springer · added 2026-04-24
Previous studies have investigated the role of metabolic factors in risk of hematological malignancies with contradicting findings. Existing studies are generally limited by potential concern of rever Show more
Previous studies have investigated the role of metabolic factors in risk of hematological malignancies with contradicting findings. Existing studies are generally limited by potential concern of reverse causality and confounding by inflammation. Therefore, we aimed to investigate the associations of glucose, lipid, and apolipoprotein biomarkers with the risk of hematological malignancy. We performed a study of over 560,000 individuals of the Swedish AMORIS cohort, with measurements of biomarkers for carbohydrate, lipid, and apolipoprotein metabolism during 1985-1996 and follow-up until 2020. We conducted a prospective cohort study and used Cox models to investigate the association of nine different metabolic biomarkers (glucose, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), LDL-C/HDL-C, triglyceride (TG), apolipoprotein B (ApoB), apolipoprotein A-I (ApoA I), and ApoB/ApoA-I) with risk of hematological malignancy, after excluding the first five years of follow-up and adjustment for inflammatory biomarkers. We observed a decreased risk of hematological malignancy associated with one SD increase of TC (HR 0.93; 95% CI 0.91-0.96), LDL-C (HR 0.94; 95% CI 0.91-0.97), HDL-C (HR 0.92; 95% CI 0.86-0.99), and ApoA-I (HR 0.96; 95% CI 0.93-0.996). Our study highlights a decreased risk of hematological malignancy associated with a higher level of TC, LDL-C, HDL-C, and ApoA-I. Show less
📄 PDF DOI: 10.1007/s10654-025-01207-y
APOB

Enzymatic Synthesis and in vitro Digestion Characteristics of Human Milk Fat Substitutes 1,3-Dilinoleoyl-2-palmitoylglycerol.

Liping Chen, Jiawei Wang, Kangyuan Li +6 more · 2025 · Journal of oleo science · added 2026-04-24
1,3-dilinoleoyl-2-palmitoylglycerol (LPL) is an important structural lipid in breast milk fat, which plays an important role in the health of infants, and therefore the development of an efficient met Show more
1,3-dilinoleoyl-2-palmitoylglycerol (LPL) is an important structural lipid in breast milk fat, which plays an important role in the health of infants, and therefore the development of an efficient method for the preparation of such compounds is necessary. In the present study, LPL was efficiently catalytically synthesized by immobilized lipase ANL-MARE as a biocatalyst using tripalmitate and linoleic acid in a solvent-free system, and its digestive properties were investigated. The optimal process conditions for the enzymatic acidolysis of LPL were optimized by response surface test: the molar ratio of PPP:LA was 1:10, the enzyme addition was 13.60%, the reaction temperature was 50℃, and the reaction time was 5 h. At this time, the relative content of LPL in the product was 67.78%, of which the relative content of sn-2 palmitic acid (sn-2 PA) accounted for 71.50%. In vitro gastrointestinal digestion of LPL resulted in the release of 59.69% of its fatty acids. The digested product contained higher levels of free unsaturated fatty acids and palmitic acid monoacylglycerols. In conclusion, the immobilized enzyme ANL-MARE has great potential to catalyze the preparation of LPL, which provides a new strategy and theoretical basis for the efficient preparation of human milk fat substitutes. Show less
no PDF DOI: 10.5650/jos.ess25025
LPL

AMPK/SIRT1/PGC-1α Signaling Pathway: Molecular Mechanisms and Targeted Strategies From Energy Homeostasis Regulation to Disease Therapy.

Junyang Chen, Boya Liu, Xinlei Yao +8 more · 2025 · CNS neuroscience & therapeutics · Blackwell Publishing · added 2026-04-24
The AMPK/SIRT1/PGC-1α pathway serves as a central regulator of cellular energy homeostasis, coordinating metabolic stress responses, epigenetic modifications, and transcriptional programs. Its dysfunc Show more
The AMPK/SIRT1/PGC-1α pathway serves as a central regulator of cellular energy homeostasis, coordinating metabolic stress responses, epigenetic modifications, and transcriptional programs. Its dysfunction is implicated in the pathogenesis of a wide spectrum of complex modern diseases, spanning neurodegeneration, metabolic syndromes, and chronic inflammatory conditions. This review examines the pathway's role as an integrative hub and its potential as a therapeutic target. We synthesize current mechanistic evidence from molecular, cellular, and preclinical studies to elucidate the pathway's operational logic and the consequences of its dysregulation. The analysis is structured around key disease paradigms-including Alzheimer's disease, Parkinson's disease, diabetes, cardiovascular injury, stroke, and chronic kidney disease-to dissect its tissue-specific pathophysiological impacts. The AMPK/SIRT1/PGC-1α axis operates through a core positive feedback loop: AMPK activation elevates NAD+, thereby activating SIRT1, which in turn deacetylates and activates PGC-1α to drive mitochondrial biogenesis and function, further reinforcing SIRT1 activity. Disruption of this cascade manifests in disease-specific mechanisms: promoting Aβ production via BACE1/γ-secretase in Alzheimer's; impairing α-synuclein clearance in Parkinson's; disrupting GLUT4 translocation and insulin signaling in diabetes; exacerbating oxidative damage and mitochondrial dysfunction in cardiovascular and neuronal injury; and accelerating fibrosis and sustained inflammation in renal and pulmonary diseases via NLRP3 and TGF-β/Smad3 signaling. The AMPK/SIRT1/PGC-1α pathway represents a cornerstone target at the intersection of metabolism, aging, and disease. Current therapeutic strategies-including pharmacological activators (e.g., metformin, SRT1720), natural compounds (e.g., resveratrol), lifestyle interventions (e.g., exercise, caloric restriction), and emerging technologies (e.g., gene editing, exosomal miRNAs)-offer multidimensional avenues for intervention. Future research must prioritize elucidating tissue-specific regulatory mechanisms, such as AMPK isoform diversity and PGC-1α interactome dynamics, to enable precision therapeutics and successful clinical translation for a range of complex disorders. Show less
📄 PDF DOI: 10.1111/cns.70657
BACE1

NSP6 regulates calcium overload-induced autophagic cell death and is regulated by KLHL22-mediated ubiquitination.

Xingyu Tao, Yanan Wang, Jiangbo Jin +10 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a substantial global threat. SARS-CoV-2 nonstructural proteins (NSPs) are essential for impeding the host replication mechanism while Show more
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a substantial global threat. SARS-CoV-2 nonstructural proteins (NSPs) are essential for impeding the host replication mechanism while also assisting in the production and organization of new viral components. However, NSPs are not incorporated into viral particles, and their subsequent fate within host cells remains poorly understood. Additionally, their role in viral pathogenesis requires further investigation. This study aimed to discover the ultimate fate of NSP6 in host cells and to elucidate its role in viral pathogenesis. We investigated the effects of NSP6 on cell death and explored the underlying mechanism; moreover, we examined the degradation mechanism of NSP6 in human cells, along with analysing its correlation with coronavirus disease 2019 (COVID-19) severity in patient peripheral blood mononuclear cells (PBMCs). NSP6 was demonstrated to induce cell death. Specifically, NSP6 interacted with EI24 autophagy-associated transmembrane protein (EI24) to increase intracellular Ca This study reveals that KLHL22-mediated ubiquitination controls NSP6 stability and that NSP6 induces autophagic cell death via calcium overload, highlighting its cytotoxic role and suggesting therapeutic strategies that target calcium signaling or promote NSP6 degradation as potential interventions against COVID-19. Show less
no PDF DOI: 10.1016/j.jare.2025.05.031
PIK3C3

PNPLA3-I148M is a neomorph that interferes with two primary hepatic triglyceride clearance pathways.

David J Sherman, Lei Liu, Edward L LaGory +8 more · 2025 · Cell reports · Elsevier · added 2026-04-24
The common variant PNPLA3-I148M, globally, is the most significant genetic risk factor for fatty liver disease. However, it is unclear precisely how I148M drives disease risk. Using human hepatoma cel Show more
The common variant PNPLA3-I148M, globally, is the most significant genetic risk factor for fatty liver disease. However, it is unclear precisely how I148M drives disease risk. Using human hepatoma cells expressing endogenous I148M, we find that the variant impairs cellular secretion of apolipoprotein B (ApoB), the scaffolding protein of very-low-density lipoprotein (VLDL). This is not due to loss-of-function of wild-type PNPLA3. Expression of human I148M in primary hepatocytes and mice also hinders VLDL secretion. Lipidomic profiling reveals a shift from polyunsaturated phosphatidylcholine to polyunsaturated triglycerides in I148M cells, reducing membrane fluidity and, concomitantly, VLDL biogenesis. ApoB secretion is substantially rescued in I148M cells overexpressing ABHD5/CGI-58, an I148M-binding partner that normally activates ATGL/PNPLA2-mediated triglyceride lipolysis. Conversely, knocking down CGI-58 or PNPLA2 mimics I148M. We propose that I148M is a neomorph that exacerbates fatty liver risk by simultaneously impeding two major CGI-58-dependent pathways for liver triglyceride clearance: lipolysis and secretion. Show less
no PDF DOI: 10.1016/j.celrep.2025.116371
APOB