👤 Xiumei 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 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, 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

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

Retraction Note: Interleukin-27 ameliorates coxsackievirus-B3-induced viral myocarditis by inhibiting Th17 cells.

Hengshan Zhu, Chuang Lou, Ping Liu · 2025 · Virology journal · BioMed Central · added 2026-04-24
📄 PDF DOI: 10.1186/s12985-025-02824-5
IL27

Emotional regulation and mental health profiles among Chinese junior middle school students: evidence for the dual-factor model.

Jichang Guo, Yanpei Pan, Yan Zhao +2 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study explored latent mental health profiles among adolescents in southwestern China and the association with emotional regulation using the dual-factor model framework. 1,682 junior middle schoo Show more
This study explored latent mental health profiles among adolescents in southwestern China and the association with emotional regulation using the dual-factor model framework. 1,682 junior middle school students completed the LPA revealed three profiles: Troubled (31.51%, high negative symptoms/low well-being), complete mental health (61.30%, low negative symptoms/high well-being), and more troubled (7.19%, severe negative symptoms/extremely low well-being). Cognitive reappraisal positively predicted complete mental health (vs. Troubled; Three distinct profiles emerged, differing from the traditional dual-factor model. Cognitive reappraisal protects mental health, while expressive suppression correlates with poorer outcomes, highlighting the need for targeted interventions promoting cognitive reappraisal. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1708381
LPA

A Multi-Task Self-Supervised Strategy for Predicting Molecular Properties and FGFR1 Inhibitors.

Xin Yang, Yang Wang, Ye Lin +4 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Studying the molecular properties of drugs and their interactions with human targets aids in better understanding the clinical performance of drugs and guides drug development. In computer-aided drug Show more
Studying the molecular properties of drugs and their interactions with human targets aids in better understanding the clinical performance of drugs and guides drug development. In computer-aided drug discovery, it is crucial to utilize effective molecular feature representations for predicting molecular properties and designing ligands with high binding affinity to targets. However, designing an effective multi-task and self-supervised strategy remains a significant challenge for the pretraining framework. In this study, a multi-task self-supervised deep learning framework is proposed, MTSSMol, which utilizes ≈10 million unlabeled drug-like molecules for pretraining to identify potential inhibitors of fibroblast growth factor receptor 1 (FGFR1). During the pretraining of MTSSMol, molecular representations are learned through a graph neural networks (GNNs) encoder. A multi-task self-supervised pretraining strategy is proposed to fully capture the structural and chemical knowledge of molecules. Extensive computational tests on 27 datasets demonstrate that MTSSMol exhibits exceptional performance in predicting molecular properties across different domains. Moreover, MTSSMol's capability is validated to identify potential inhibitors of FGFR1 through molecular docking using RoseTTAFold All-Atom (RFAA) and molecular dynamics simulations. Overall, MTSSMol provides an effective algorithmic framework for enhancing molecular representation learning and identifying potential drug candidates, offering a valuable tool to accelerate drug discovery processes. All of the codes are freely available online at https:// github.com/zhaoqi106/MTSSMol. Show less
📄 PDF DOI: 10.1002/advs.202412987
FGFR1

Multi-omics analysis of copper metabolism-related molecular subtypes and risk stratification for osteosarcoma.

Yang Zhang, Wen Liu, Dayong Liu +5 more · 2025 · Discover oncology · Springer · added 2026-04-24
As the most common primary malignant bone tumor, further investigation into risk stratification for osteosarcoma (OS) prognosis is of significant clinical importance. Copper is essential for bone meta Show more
As the most common primary malignant bone tumor, further investigation into risk stratification for osteosarcoma (OS) prognosis is of significant clinical importance. Copper is essential for bone metabolism; however, its specific role in OS remains unclear. The expression characteristics of copper metabolism related genes (CORGs) in OS were revealed by single cell sequencing. Prognosis-associated CORGs were identified, and a CORG-related scoring system and risk model were established using bioinformatics approaches, including univariate and multivariate Cox regression analyses and LASSO analysis. We further analyzed immune microenvironment infiltration, molecular subtypes and clinicopathological characteristics. The impact of selected CORG with high-risk coefficient on OS cells was tested by qRT-PCR, western blot, siRNA, colony formation analysis and Transwell in vitro. We successfully developed an OS scoring system related to copper metabolism and validated its independent prognostic value in patients with OS. The potential clinical value of CORG scoring system was analyzed. APOA4 was selected for in vitro experiments and its effect on the proliferation and invasion ability of OS cells was verified. We established a copper metabolism-related scoring system to effectively stratify the risk of OS patients. Our results provide a new basis for the role of copper metabolism in OS and provide new potential targets for the treatment of OS. Show less
📄 PDF DOI: 10.1007/s12672-025-02273-0
APOA4

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

NFIA-dependent upregulation of SMC4 promotes metastasis and metabolic reprogramming in glioma.

Guoyin Li, Yukui Zhao, Yubo He +4 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Gliomas, particularly glioblastoma, are aggressive brain tumors with poor prognosis and unmet therapeutic needs. Structural maintenance of chromosomes 4 (SMC4), a core component of the condensin compl Show more
Gliomas, particularly glioblastoma, are aggressive brain tumors with poor prognosis and unmet therapeutic needs. Structural maintenance of chromosomes 4 (SMC4), a core component of the condensin complex, is dysregulated in multiple cancers, but its role in glioma metabolism and metastasis remains unclear. Using integrated multi-omics analyses of glioma datasets, we assessed SMC4 expression and its correlation with clinical outcomes. Functional studies in U-251MG and LN229 glioma cells including CCK-8, EdU, cell cycle, Transwell, and wound-healing assays were combined with subcutaneous xenograft and tail-vein metastasis mouse models to evaluate SMC4's effects on proliferation, migration, invasion, and metastasis. ECAR/OCR and rescue experiments validated SMC4's role in glycolysis. Luciferase reporter and ChIP assays identified nuclear factor I A (NFIA) as an upstream transcriptional regulator of SMC4. A prognostic model (SRRS) was developed via LASSO regression and validated across cohorts. SMC4 was significantly overexpressed in glioma tissues, with higher expression correlating with advanced tumor grades and poorer patient survival (AUC > 0.82). Mechanistically, SMC4 promoted G1/S cell cycle transition and proliferation SMC4 drives glioma progression through dual mechanisms TGF-β/SMAD-mediated metastasis and LDHA-dependent glycolysis regulated by NFIA. This extends beyond its known role in TGF-β activation by identifying NFIA as an upstream regulator and metabolic reprogramming as a novel function. The SRRS and nomogram provide robust tools for prognosis and personalized therapy, supporting the NFIA/SMC4 axis and downstream effectors as potential therapeutic targets for glioma. Show less
no PDF DOI: 10.3389/fonc.2025.1624370
SNAI1

Absence of the intracellular lipolytic inhibitor G0S2 enhances intravascular triglyceride clearance and abolishes diet-induced hypertriglyceridemia.

Yongbin Chen, Scott M Johnson, Stephanie D Burr +4 more · 2025 · The Journal of clinical investigation · added 2026-04-24
The interplay between intracellular and intravascular lipolysis is crucial for maintaining circulating lipid levels and systemic energy homeostasis. Adipose triglyceride lipase (ATGL) and lipoprotein Show more
The interplay between intracellular and intravascular lipolysis is crucial for maintaining circulating lipid levels and systemic energy homeostasis. Adipose triglyceride lipase (ATGL) and lipoprotein lipase (LPL), the primary triglyceride (TG) lipases responsible for these two spatially separate processes, are highly expressed in adipose tissue. Yet the mechanisms underlying their coordinated regulation remain undetermined. Here, we demonstrate that genetic ablation of G0S2, a specific inhibitory protein of ATGL, completely abolished diet-induced hypertriglyceridemia and significantly attenuated atherogenesis in mice. These effects were attributable to enhanced whole-body TG clearance, not altered hepatic TG secretion. Specifically, G0S2 deletion increased circulating LPL concentration and activity, predominantly through LPL production from white adipose tissue (WAT). Strikingly, transplantation of G0S2-deficient WAT normalized plasma TG levels in mice with hypertriglyceridemia. In conjunction with improved insulin sensitivity and decreased ANGPTL4 expression, the absence of G0S2 enhanced the stability of LPL protein in adipocytes, a phenomenon that could be reversed upon ATGL inhibition. Collectively, these findings highlight the pivotal role of adipocyte G0S2 in regulating both intracellular and intravascular lipolysis, and the possibility of targeting G0S2 as a viable pharmacological approach to reducing levels of circulating TGs. Show less
📄 PDF DOI: 10.1172/JCI181754
ANGPTL4

Chronic inflammation response as a key factor in polycystic ovary syndrome among patients with bipolar disorder.

Jieyu Liu, Zhuohui Chen, Ziwei Teng +8 more · 2025 · Journal of affective disorders · Elsevier · added 2026-04-24
This study aimed to investigate serum inflammatory factor levels of polycystic ovary syndrome (PCOS) in female patients with bipolar disorder (BD) to explore the related inflammatory molecular mechani Show more
This study aimed to investigate serum inflammatory factor levels of polycystic ovary syndrome (PCOS) in female patients with bipolar disorder (BD) to explore the related inflammatory molecular mechanisms preliminarily. The study recruited 72 female drug-naïve patients with BD and 98 female healthy controls (HCs). Demographic information, menstrual cycles, sex hormone levels, and ovarian ultrasound data were collected from them. Additionally, their serum inflammatory factor levels and the proteomics of peripheral blood mononuclear cells were analyzed. The levels of interleukin (IL)-8 and IL-13 were significantly higher in patients with BD than in HCs (p < 0.05), and the IL-8 level was higher in BD patients with PCOS than in those without (adjusted p = 0.07). Bioinformatics analysis revealed that downregulated genes with significant differences between the two groups were all involved in immune-inflammatory-related pathways, and the expression of downregulated genes BTN3A2, MAP2K5, JCHAIN-B, and DMAP1 showed substantial differences and consistent trends between the two groups. IL-8-related chronic inflammatory response is closely associated with PCOS in BD patients, and genes such as BTN3A2 may mediate this chronic inflammatory response by negatively regulating the abnormal differentiation of T helper 17 cells, serving as one of the mechanisms underlying its pathogenesis. Show less
no PDF DOI: 10.1016/j.jad.2025.02.072
MAP2K5

Isotemporal substitution from sedentary behavior or sleep to physical activity: associations with depression risk in older adults-a systematic review and meta-analysis.

Jiali Wang, Yilin Wang, Yue Wang +3 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
As global population aging intensifies, mental health issues in older adults are increasingly prominent, with depression being particularly prevalent and detrimental. The study investigated how substi Show more
As global population aging intensifies, mental health issues in older adults are increasingly prominent, with depression being particularly prevalent and detrimental. The study investigated how substituting sedentary behavior (SB) and sleep (SLP) with physical activity (PA) affects depression risk in this population. Meta-analysis was conducted by searching four databases: PubMed, Scopus, SPORTdiscus, and PsycINFO (via EBSCOhost platform) for relevant studies published until January 2025. Regression coefficients (β) with 95% confidence intervals (CIs) for depressive symptoms were estimated. Publication bias was assessed using funnel plots and Egger's tests, and heterogeneity was evaluated using Q tests and the I Among 18,912 participants (53.45% female, ≥60 years) across nine studies, replacing SB with MVPA significantly reduced depression (β = -0.12, 95% CI: -0.20, -0.04), subgroup analyses indicated that reallocating 10, 30 and 60 min/day of SB to MVPA ( Substituting SB and SLP with MVPA is significantly associated with a reduction in depression, whereas no significant association is observed when replaced by LPA. https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=546666, identifier CRD42024546666. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1682987
LPA

Quinolinic acid protects mouse liver from high-fat diet induced MASLD by inhibiting lipid uptake gene expression.

Bao Wang, Delong Zhen, Jin Wei +4 more · 2025 · European journal of pharmacology · Elsevier · added 2026-04-24
Quinolinic acid (QA) is a metabolite of tryptophan catabolism involved in the biosynthesis of nicotinamide adenine dinucleotide (NAD). It has been extensively studied in the context of neuropsychiatri Show more
Quinolinic acid (QA) is a metabolite of tryptophan catabolism involved in the biosynthesis of nicotinamide adenine dinucleotide (NAD). It has been extensively studied in the context of neuropsychiatric disorders in the past decades. Recent studies have also linked high plasma QA levels to obesity, metabolic dysfunction-associated steatotic liver disease (MASLD) and diabetes. In the present study, we have explored the impact of long-term oral QA administration on glucose and lipid metabolism in mice. We observed a protective role for QA in preventing hepatic lipid accumulation in high-fat-diet fed mice, whereas oral administration of NAD showed opposite effects. We further demonstrated that QA reduces hepatic lipid uptake by inhibiting the expression of lipoprotein lipase (LPL) and fatty acid translocase (CD36) in liver, thereby mitigating liver lipid accumulation in the context of a high-fat diet. Our data suggest that QA is an important regulator of lipid homeostasis and has potential as a therapeutic target for MASLD. Show less
no PDF DOI: 10.1016/j.ejphar.2025.178065
LPL

DCTP-Net: Dual-Branch CLIP-Enhance Textual Prompt-Aware Network for Acute Ischemic Stroke Lesion Segmentation From CT Image.

Jiahao Liu, Hongqing Zhu, Ziying Wang +6 more · 2025 · IEEE journal of biomedical and health informatics · IEEE · added 2026-04-24
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, Show more
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemic stroke lesions in CT images, consisting of a segmentation branch and a prompt-aware branch. The segmentation branch uses an encoder-decoder network as the backbone to identify lesions, where the encoder fuses CT image features with prompt features from the prompt-aware branch. To enhance semantic feature extraction and reduce the impact of cerebral structural details, we introduce a cross-collaboration dynamic connection (CCDC) module to link the encoder and decoder. The prompt-aware branch includes a learnable prompt (LP) block to incorporate cerebral prior knowledge, and the prompt-aware encoder (PAE) combines the LP block with multi-level features from the segmentation branch for more precise representation. Additionally, we propose a CLIP-enhance textual prompt (CETP) module that utilizes the CLIP text encoder to generate specialized convolutional parameters for the segmentation head. These parameters are tailored to the unique characteristics of each input image, improving segmentation performance. Qualitative and quantitative studies reveal that DCTP-Net outperforms the current state-of-the-art, IS-Net, with Dice score increases of 3.9% on AISD and 3.8% on ISLES2018, demonstrating its superiority in EIL segmentation. Show less
no PDF DOI: 10.1109/JBHI.2024.3471627
CETP

Endothelial cells-derived SEMA3G suppresses glioblastoma stem cells by inducing c-Myc degradation.

Peng-Xiang Min, Li-Li Feng, Yi-Xuan Zhang +12 more · 2025 · Cell death and differentiation · Nature · added 2026-04-24
The poor prognosis of glioblastoma (GBM) patients is attributed mainly to abundant neovascularization and presence of glioblastoma stem cells (GSCs). GSCs are preferentially localized to the perivascu Show more
The poor prognosis of glioblastoma (GBM) patients is attributed mainly to abundant neovascularization and presence of glioblastoma stem cells (GSCs). GSCs are preferentially localized to the perivascular niche to maintain stemness. However, the effect of abnormal communication between endothelial cells (ECs) and GSCs on GBM progression remains unknown. Here, we reveal that ECs-derived SEMA3G, which is aberrantly expressed in GBM patients, impairs GSCs by inducing c-Myc degradation. SEMA3G activates NRP2/PLXNA1 in a paracrine manner, subsequently inducing the inactivation of Cdc42 and dissociation of Cdc42 and WWP2 in GSCs. Once released, WWP2 interacts with c-Myc and mediates c-Myc degradation via ubiquitination. Genetic deletion of Sema3G in ECs accelerates GBM growth, whereas SEMA3G overexpression or recombinant SEMA3G protein prolongs the survival of GBM bearing mice. These findings illustrate that ECs play an intrinsic inhibitory role in GSCs stemness via the SMEA3G-c-Myc distal regulation paradigm. Targeting SEMA3G signaling may have promising therapeutic benefits for GBM patients. Show less
no PDF DOI: 10.1038/s41418-025-01534-3
WWP2

Risk Assessment of Serum Biomarkers with Perioperative Neurocognitive Dysfunction in Elderly Patients Undergoing Thoracic Surgery: A Prospective Cohort Study.

Zhijing Zhang, Di Wang, Riguang Zhong +6 more · 2025 · Cellular and molecular neurobiology · Springer · added 2026-04-24
Perioperative neurocognitive disorder (PND) is a common complication following thoracic surgery and often leading to poor outcomes. Despite ongoing research, effective treatments for late PND remain l Show more
Perioperative neurocognitive disorder (PND) is a common complication following thoracic surgery and often leading to poor outcomes. Despite ongoing research, effective treatments for late PND remain limited. Identifying reliable biomarkers for early diagnosis is, therefore, essential. A prospective cohort study was conducted with 60 elderly patients undergoing thoracic surgery. Serum samples were collected within 10 minutes prior to anesthesia and following extubation to measure adiponectin (APN), cyclic adenosine monophosphate (cAMP), protein kinase A (PKA), aquaporin-4 (AQP4) and brain-derived neurotrophic factor (BDNF). Among PND patients, serum APN, PKA, AQP4, and BDNF levels were markedly decreased compared with the normal group. While serum cAMP (HR = 1.087, p = 0.695, 95% CI [0.284-4.166]) and PKA (HR = 0.996, p = 0.09, 95% CI [0.491-0.947]) were not significantly correlated with PND, serum APN (HR = 0.307, 95% CI [0.113-0.835], p = 0.021), AQP4 (HR = 0.204, 95% CI [0.060-0.697], p = 0.011), and BDNF (HR = 0.382, 95% CI [0.177-0.823], p = 0.014) were protective factors against PND. ROC analysis demonstrated that APN (AUC = 0.68, 95% CI [0.51-0.87]), AQP4 (AUC = 0.73, 95% CI [0.59-0.87]), BDNF (AUC = 0.73, 95% CI [0.59-0.87]), and the model of combining those biomarkers (AUC = 0.91, 95% CI [0.83-0.99]) could predict PND. PND patients exhibited a lower protective stress response to surgical trauma. High serum APN, AQP4, and BDNF levels were independent protective factors for PND, and a combined model of these biomarkers showed predictive potential for PND. Show less
📄 PDF DOI: 10.1007/s10571-025-01636-z
BDNF

Lymphatic Endothelial Branched-Chain Amino Acid Catabolic Defects Undermine Cardiac Lymphatic Integrity and Drive HFpEF.

Xiong Guo, Chong Huang, Ling Zhang +18 more · 2025 · Circulation · added 2026-04-24
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining Show more
Heart failure with preserved ejection fraction (HFpEF) has become the most prevalent type of heart failure, but effective treatments are lacking. Cardiac lymphatics play a crucial role in maintaining heart health by draining fluids and immune cells. However, their involvement in HFpEF remains largely unexplored. We examined cardiac lymphatic alterations in mice with HFpEF with comorbid obesity and hypertension, and in heart tissues from patients with HFpEF. Using genetically engineered mouse models and various cellular and molecular techniques, we investigated the role of cardiac lymphatics in HFpEF and the underlying mechanisms. In mice with HFpEF, cardiac lymphatics displayed substantial structural and functional anomalies, including decreased lymphatic endothelial cell (LEC) density, vessel fragmentation, reduced branch connections, and impaired capacity to drain fluids and immune cells. LEC numbers and marker expression levels were also decreased in heart tissues from patients with HFpEF. Stimulating lymphangiogenesis with an adeno-associated virus expressing an engineered variant of vascular endothelial growth factor C (VEGFC Our study provides evidence that cardiac lymphatic disruption, driven by impaired BCAA catabolism in LECs, is a key factor contributing to HFpEF. These findings unravel the crucial role of BCAA catabolism in modulating lymphatic biology, and suggest that preserving cardiac lymphatic integrity may present a novel therapeutic strategy for HFpEF. Show less
📄 PDF DOI: 10.1161/CIRCULATIONAHA.124.071741
BCKDK

Bioinformatic analysis identifies LPL as a critical gene in diabetic kidney disease via lipoprotein metabolism.

Qian Dong, Huan Xu, Pengjie Xu +2 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Diabetic kidney disease (DKD) is a common and serious complication of diabetes, affecting approximately 40% of patients with the condition. The pathogenesis of DKD is complex, involving multiple proce Show more
Diabetic kidney disease (DKD) is a common and serious complication of diabetes, affecting approximately 40% of patients with the condition. The pathogenesis of DKD is complex, involving multiple processes such as metabolism, inflammation, and fibrosis. Given its increasing incidence and associated mortality, there is an urgent need to identify novel pathogenic genes and therapeutic targets. This study systematically identified hub DKD-associated genes and their potential molecular mechanisms through bioinformatic analysis. Gene expression datasets from DKD patients and healthy controls were obtained from the GEO database. Hub genes were screened using differential expression analysis, weighted gene co-expression network analysis (WGCNA), LASSO regression, random forest (RF) algorithms, and consensus clustering for DKD patient classification. Additionally, immune cell infiltration analysis was performed on differentially expressed genes to explore the relationship between hub genes and the immune microenvironment. Potential drugs targeting LPL were predicted based on gene-drug interaction analysis. Immunohistochemistry was used to verify the expression of LPL and TNF-α in kidney tissues from patients with varying degrees of DKD severity, as well as their relationship with kidney function impairment. This study revealed that LPL, a lipoprotein metabolism gene, plays a crucial role in DKD, participating in cholesterol and glycerolipid metabolism as well as PPAR signaling. LPL expression was negatively correlated with pro-inflammatory M1 macrophages and various subsets of T cells, including naïve CD4 T cells and gamma delta T cells, while positively correlated with follicular helper T cells, suggesting its immune-regulation effects in DKD progression. Potential LPL-targeting drugs, such as Ibrolipim, anabolic steroid, and acarbose, might mitigate DKD. LPL expression was decreased with DKD severity and was correlated with TNF-α and kidney dysfunction markers, indicating its key role in DKD progression. LPL is a pivotal regulator of lipid metabolism and immune inflammation in DKD. Potential drugs targeting LPL offer new candidates for precision treatment of DKD. These findings lay a theoretical foundation for understanding the molecular mechanisms of DKD and developing LPL-based therapeutic strategies. Show less
📄 PDF DOI: 10.3389/fendo.2025.1620032
LPL

Epigenetic repression of hepatocyte FoxO1 disrupts local immune homeostasis and promotes liver inflammation.

Zhigang Lei, Yu Wu, Weijie Xue +15 more · 2025 · Hepatology (Baltimore, Md.) · added 2026-04-24
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critica Show more
Disrupting liver immune homeostasis drives inflammation. Recent evidence shifts immunoregulatory focus to hepatocytes, though the mechanisms remain poorly defined. Forkhead box O1 (FoxO1) is a critical homeostasis regulator, but its function in liver immune homeostasis is unknown. We aimed to clarify the role of hepatocyte FoxO1 in liver immune homeostasis and inflammation. Human liver FoxO1 expression and its association with inflammation were analyzed in patients with various inflammation-related liver diseases. Hepatocyte-specific Foxo1 knockout (FoxO1 △hepa ) mice were established. Hepatocyte-specific gene interference was employed in alcoholic hepatitis and hepatic schistosomiasis murine models. Transcriptomic, single-cell RNA sequencing, and CUT&Tag analyses were performed to elucidate the underlying mechanisms. Hepatocyte FoxO1 levels in human inflammatory livers declined prevalently and were inversely correlated with inflammation and fibrosis. Around 15-18 weeks after birth, FoxO1 △hepa mice exhibited mild spontaneous hepatic inflammation with natural killer T (NKT) cell and neutrophil accumulation. NKT cell depletion in FoxO1 △hepa mice with alcoholic hepatitis or hepatic schistosomiasis (HS) significantly reduced neutrophil accumulation and protected against liver inflammation and damage. Mechanistically, FoxO1 promoted retinoic acid synthesis to induce hepatocyte CD1d expression, which is necessary for regulating NKT cell apoptosis. Innovatively, decreased JMJD1C expression in hepatocytes caused histone H3 lysine 9 (H3K9) dimethylation at the Foxo1 promoter, repressing its transcription and disrupting local immune homeostasis. Our findings uncover a hitherto unrecognized mechanism for hepatocyte-based control of liver inflammation, in which hepatocyte FoxO1 maintained by JMJD1C restrains local NKT cells and neutrophils via CD1d induction, providing promising targets for inflammatory liver diseases. Show less
no PDF DOI: 10.1097/HEP.0000000000001590
JMJD1C

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

Lipids, Lipid-Lowering Drug Target Genes, and COPD Risk: A Mendelian Randomization Study.

Guobing Jia, Tao Guo, Lei Liu +1 more · 2025 · Chronic obstructive pulmonary diseases (Miami, Fla.) · added 2026-04-24
Some studies suggest that statins could reduce the risk of chronic obstructive pulmonary disease (COPD), but it is unclear if this effect is related to their lipid-lowering properties. The causal link Show more
Some studies suggest that statins could reduce the risk of chronic obstructive pulmonary disease (COPD), but it is unclear if this effect is related to their lipid-lowering properties. The causal link between serum lipid levels and COPD risk remains uncertain. This study aims to clarify this potential causal relationship and evaluate the impact of lipid-lowering drug target genes on COPD. Mendelian randomization (MR) was used to investigate causal associations between lipid levels, lipid-lowering drug target genes, and COPD risk. Data were obtained from publicly available genome-wide association study databases. The inverse variance weighted method was the primary statistical approach for evaluating causal effects, complemented by various sensitivity analyses. MR analysis demonstrated a causal relationship between low-density lipoprotein cholesterol (LDL-C) and a reduced risk of COPD (odds ratio [OR]=0.90, 95% confidence interval [CI]=0.85-0.95, P=1.50×10⁻⁴). Causal relationships were also identified for 2 lipid-lowering drug target genes, This study genetically identified causal relationships between serum LDL-C levels, the 2 coding genes Show less
no PDF DOI: 10.15326/jcopdf.2025.0632
LPL

Social Bonds Retain Oxytocin-Mediated Brain-Liver Axis to Retard Atherosclerosis.

Seien Ko, Atsushi Anzai, Xueyuan Liu +15 more · 2025 · Circulation research · added 2026-04-24
Social interaction with others is essential to life. Although social isolation and loneliness have been implicated as increased risks of cardiometabolic and cardiovascular diseases and all-cause morta Show more
Social interaction with others is essential to life. Although social isolation and loneliness have been implicated as increased risks of cardiometabolic and cardiovascular diseases and all-cause mortality, the cellular and molecular mechanisms by which social connection maintains cardiometabolic and cardiovascular health remain largely unresolved. To investigate how social connection protects against cardiometabolic and cardiovascular diseases, atherosclerosis-prone, high-fat diet-fed These results identify a novel brain-liver axis that links sociality to hepatic lipid metabolism, thus proposing a potential therapeutic strategy for loneliness-associated atherosclerosis progression. Show less
no PDF DOI: 10.1161/CIRCRESAHA.124.324638
ANGPTL4

Single-cell transcriptomic profiling of heart reveals ANGPTL4 linking fibroblasts and angiogenesis in heart failure with preserved ejection fraction.

Guoxing Li, Huilin Zhao, Zhe Cheng +3 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Despite the high morbidity and mortality, the effective therapies for heart failure with preserved fraction (HFpEF) are limited as the poor understand of its pathophysiological basis. This study was a Show more
Despite the high morbidity and mortality, the effective therapies for heart failure with preserved fraction (HFpEF) are limited as the poor understand of its pathophysiological basis. This study was aimed to characterize the cellular heterogeneity and potential mechanisms of HFpEF at single-cell resolution. An HFpEF mouse model was induced by a high-fat diet with N-nitro-L-arginine methyl ester. Cells from the hearts were subjected to single-cell sequencing. The key protein expression was measured with Immunohistochemistry and immunofluorescence staining. In HFpEF hearts, myocardial fibroblasts exhibited higher levels of fibrosis. Furthermore, an increased number of fibroblasts differentiated into high-metabolism and high-fibrosis phenotypes. The expression levels of genes encoding certain pro-angiogenic secreted proteins were decreased in the HFpEF group, as confirmed by bulk RNA sequencing. Additionally, the proportion of the endothelial cell (EC) lineages in the HFpEF group was significantly downregulated, with low angiogenesis and high apoptosis phenotypes observed in these EC lineages. Interestingly, the fibroblasts in the HFpEF heart might cross-link with the EC lineages via over-secretion of ANGPTL4, thus displaying an anti-angiogenic function. Immunohistochemistry and immunofluorescence staining then revealed the downregulation of vascular density and upregulation of ANGPTL4 expression in HFpEF hearts. Finally, we predicted ANGPTL4as a potential druggable target using DrugnomeAI. In conclusion, this study comprehensively characterized the angiogenesis impairment in HFpEF hearts at single-cell resolution and proposed that ANGPTL4 secretion by fibroblasts may be a potential mechanism underlying this angiogenic abnormality. Show less
📄 PDF DOI: 10.1016/j.jare.2024.02.006
ANGPTL4

Exosomal SNHG26 mediates immunosuppression by impairing NK cells in tongue cancer.

Qingkun Jiang, Yuqin Xin, Fei He +2 more · 2025 · NPJ precision oncology · Nature · added 2026-04-24
Cisplatin resistance in tongue squamous cell carcinoma (TSCC) correlates with poor prognosis, where natural killer (NK) cells in the tumor microenvironment (TME) play a crucial role. This study invest Show more
Cisplatin resistance in tongue squamous cell carcinoma (TSCC) correlates with poor prognosis, where natural killer (NK) cells in the tumor microenvironment (TME) play a crucial role. This study investigated the mechanism by which exosomes from cisplatin-resistant TSCC cells suppress NK cell function. We found that exosomal long non-coding RNA SNHG26, highly enriched in cisplatin-resistant TSCC cells and their exosomes, was transferred to NK cells. Within NK cells, SNHG26 acted as a scaffold promoting WWP2-mediated ubiquitination and degradation of the transcription factor SOX2, thereby inhibiting HLA-DRA transcription and subsequent IL-2/JAK-STAT5 signaling. Concurrently, SNHG26 competitively bound miR-515-5p, relieving its suppression of TGFB1 mRNA and activating the TGF-β1/Smad2 pathway. These dual mechanisms significantly impaired NK cell proliferation, activation, and cytotoxicity. SNHG26 depletion reversed NK cell suppression and cisplatin resistance in vitro and in vivo. Thus, our study identifies exosomal SNHG26 as a key mediator of cisplatin resistance and NK cell dysfunction in TSCC, suggesting its potential as a promising therapeutic target. Show less
no PDF DOI: 10.1038/s41698-025-01185-0
WWP2

The necessity of strengthening glycemic and lipid metabolism management for improving brain structure and cognitive function in people with diabetes: A retrospective study based on UK Biobank.

Li Han, Qijun Li, Lifan Zhang +7 more · 2025 · Diabetes research and clinical practice · Elsevier · added 2026-04-24
To investigate the relation of glycemic and lipid metabolism with brain structure and cognitive function in people with diabetes, so as to improve cognitive function in these individuals. Based on the Show more
To investigate the relation of glycemic and lipid metabolism with brain structure and cognitive function in people with diabetes, so as to improve cognitive function in these individuals. Based on the UK Biobank, 26,394 patients, who were diagnosed with diabetes by doctors between 2006 and 2010, were included in the study. The demographic information, clinical data of glycemic and lipid metabolism and cognitive function (brain MRI and cognitive function scores) were collected. Multiple linear regression and non-restricted cubic spline analyses were used to investigate the relations of glycemic and lipid metabolism with brain structure and cognitive function. In this study, the mean age of people with diabetes (containing 39 % females) was 59.58 ± 7.21 years. Higher random blood glucose (β = -0.116, p < 0.001) and glycosylated hemoglobin (HbA1c) (β = -0.062, p = 0.051) were associated with a smaller brain volume. Higher HbA1c (β = 0.036, p < 0.001; β = 0.023, p = 0.021) was related with worse cognitive function. Further analysis showed that HbA1c < 6.5 % had a protective effect on cognitive function, and HbA1c = 6.5 %∼8.5 % and >8.5 % was unrelated and negatively related with cognitive function, respectively. Different types of lipids had varying effects on cognitive function. Higher total cholesterol (TC) (β = 0.125, p = 0.008), low density lipoprotein-cholesterol (LDL-C) (β = 0.086, p = 0.025), and ApoB (β = 0.092, p = 0.026) were associated with more significant brain structural abnormalities. Conversely, triglyceride (TG) = 0.75∼8.0 mmol/L was positively correlated with cognitive function (β = -0.036, p < 0.001; β = -0.044, p < 0.001; β = 0.058, p = 0.001), and higher ApoA (β = -0.032, p < 0.001; β = -0.033, p < 0.001; β = 0.047, p = 0.004) was associated with better cognitive function. The age-stratified analysis revealed that the impact of lipids on cognitive function was age-dependent. TC and LDL-C were related to brain structural abnormalities in the 55-60 age group, while TG had a stronger protective effect on cognitive function in older adults, particularly those aged 65-70 years. In people with diabetes, higher HbA1c (>8.5 %), as well as elevated TC, LDL-C, and ApoB, are associated with worse brain structure and cognitive function. Conversely, HbA1c < 6.5 % and elevated TG within the range of 0.75∼8.0 mmol/L have a protective effect on cognitive function, and the later exhibited more evident impact in older adults. To prevent or delay the onset of dementia in people with diabetes, it may be necessary to intensify glycemic control, targeting an HbA1c level of <6.5 %. Additionally, the age-specific lipid-lowering strategies shall be considered, with more flexible triglyceride-lowering goals for elderly patients. Show less
no PDF DOI: 10.1016/j.diabres.2025.112366
APOB

Nuclear-Localized BCKDK Facilitates Homologous Recombination Repair to Support Breast Cancer Progression and Therapy Resistance.

Haiying Liu, Jiaqian Feng, Tingting Pan +10 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Homologous recombination repair (HRR) is crucial for maintaining genomic stability by repairing DNA damage. Despite its importance, HRR's role in cancer progression is not fully elucidated. Here, this Show more
Homologous recombination repair (HRR) is crucial for maintaining genomic stability by repairing DNA damage. Despite its importance, HRR's role in cancer progression is not fully elucidated. Here, this work shows that nuclear-localized branched-chain α-ketoacid dehydrogenase kinase (BCKDK) acts as a modulator of HRR, promoting cell resistance against DNA damage-inducing therapy in breast cancer. Mechanistically, this work demonstrates that BCKDK is localized in the nucleus and phosphorylates RNF8 at Ser157, preventing the ubiquitin-mediated degradation of RAD51, thereby facilitating HRR-mediated DNA repair under replication stress. Notably, aberrant expression of the BCKDK/p-RNF8/RAD51 axis correlates with breast cancer progression and poor patient survival. Furthermore, this work identifies a small molecule inhibitor of BCKDK, GSK180736A, that disrupts its HRR function and exhibits strong tumor suppression when combined with DNA damage-inducing drugs. Collectively, this study reveals a new role of BCKDK in regulating HRR, independent of its metabolic function, presenting it as a potential therapeutic target and predictive biomarker in breast cancer. Show less
📄 PDF DOI: 10.1002/advs.202416590
BCKDK

GIPR agonism and antagonism decrease body weight and food intake via different mechanisms in male mice.

Robert M Gutgesell, Ahmed Khalil, Arkadiusz Liskiewicz +21 more · 2025 · Nature metabolism · Nature · added 2026-04-24
Agonists and antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR) enhance body weight loss induced by glucagon-like peptide-1 receptor (GLP-1R) agonism. However, while GIPR Show more
Agonists and antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR) enhance body weight loss induced by glucagon-like peptide-1 receptor (GLP-1R) agonism. However, while GIPR agonism decreases body weight and food intake in a GLP-1R-independent manner via GABAergic GIPR Show less
📄 PDF DOI: 10.1038/s42255-025-01294-x
GIPR

Identification of SEC16B as a novel regulator of glucose homeostasis.

Ruo-Xin Zhang, An-Qi Li, Xin-Yuan Zhao +7 more · 2025 · Diabetologia · Springer · added 2026-04-24
Glucose homeostasis, essential for metabolic health, requires coordinated insulin and glucagon activity to maintain blood glucose balance. Dysregulation of glucose homeostasis causes hyperglycaemia an Show more
Glucose homeostasis, essential for metabolic health, requires coordinated insulin and glucagon activity to maintain blood glucose balance. Dysregulation of glucose homeostasis causes hyperglycaemia and glucose intolerance, hallmark features of type 2 diabetes. While SEC16 homologue B (SEC16B), an endoplasmic reticulum export factor, has been linked to obesity, type 2 diabetes and lipid metabolism, its role in glucose regulation remains poorly defined. This study aims to investigate SEC16B's contribution to glucose homeostasis by systematically dissecting its conserved physiological mechanisms across species. To interrogate SEC16B's role, we combined Drosophila genetics (RNA interference-mediated dSec16 knockdown) with murine models (Sec16b deletion) under standard or high-fat diet conditions. Glucose and insulin tolerance tests assessed glucose homeostasis. Mechanistic insights into beta cell dysfunction were derived from immunostaining, glucose-stimulated insulin secretion assays and RNA-seq profiling of murine pancreatic islets. Both disruption of dSec16 in Drosophila and Sec16b deletion in mice triggered glucose intolerance under standard diet conditions, recapitulating conserved metabolic dysfunction. In addition, Sec16b loss impaired glycaemic control in mice fed a high-fat diet. Mechanistically, Sec16b deficiency impairs insulin secretion by downregulating cholinergic signalling and compromising intracellular Ca Our study reveals SEC16B, a genome-wide association study-identified obesity risk gene, as an evolutionarily conserved regulator of glucose homeostasis. By linking SEC16B to cholinergic-driven insulin secretion and calcium dynamics, we resolve a mechanistic gap in beta cell dysfunction and metabolic disease. This finding provides novel insights into the mechanisms underlying glucose homeostasis and may enhance our understanding of potential treatments for metabolic diseases. Show less
no PDF DOI: 10.1007/s00125-025-06501-8
SEC16B

Comprehensive identification of NRG1 fusions in 25,203 patients with solid tumors.

Shui Xiang, Yiwen Zheng, Mengxiao Wang +6 more · 2025 · NPJ precision oncology · Nature · added 2026-04-24
NRG1 fusion is an emerging oncogenic driver, and the FDA has approved drugs for the treatment of non-small cell lung cancer and pancreatic cancer associated with NRG1 fusions. This study retrospective Show more
NRG1 fusion is an emerging oncogenic driver, and the FDA has approved drugs for the treatment of non-small cell lung cancer and pancreatic cancer associated with NRG1 fusions. This study retrospectively analyzed data from 25,203 patients with solid tumors who underwent next-generation sequencing (NGS) and identified 49 patients with NRG1 fusions. The mutation profiles and actionable therapeutic targets were analyzed among patients with fusions. In this study, 0.2% (49/25,203) of patients harbored NRG1 fusions. The frequencies of NRG1 fusions across various cancer types were as follows: prostate cancer, 0.65%; breast cancer, 0.47%; lung cancer, 0.29%; esophageal cancer, 0.25%; colorectal cancer, 0.17%; gastric cancer, 0.13%; pancreatic cancer, 0.11%; and hepatocellular carcinoma, 0.05%). A total of 36 fusion partners were detected, among which CD74 was predominant, accounting for 29.3% of cases. Patients with NRG1 fusions presented a greater frequency of FGFR1 mutations and RET fusions, compared with non-NRG1 fusion patients. Most lung cancer and colorectal cancer patients with NRG1 fusions harbored FDA-approved or potential drug targets, whereas those diagnosed with breast cancer harbored fewer such targets. NRG1 fusion-related drugs can provide additional treatment options. Our study expands the NRG1 fusion gene landscape and provides a valuable reference for the comprehensive treatment of patients with NRG1 fusions. Show less
📄 PDF DOI: 10.1038/s41698-025-01044-y
FGFR1

Genetic Reasons for Phenotypic Diversity in Neuronal Ceroid Lipofuscinoses and High-Resolution Imaging as a Marker of Retinal Disease.

Jennifer Huey, Pankhuri Gupta, Benjamin Wendel +9 more · 2024 · Ophthalmology science · Elsevier · added 2026-04-24
To describe the clinical characteristics, natural history, genetic landscape, and phenotypic spectrum of neuronal ceroid lipofuscinosis (NCL)-associated retinal disease. Multicenter retrospective coho Show more
To describe the clinical characteristics, natural history, genetic landscape, and phenotypic spectrum of neuronal ceroid lipofuscinosis (NCL)-associated retinal disease. Multicenter retrospective cohort study complemented by a cross-sectional examination. Twelve pediatric subjects with biallelic variants in 5 NCL-causing genes (CLN3 lysosomal/endosomal transmembrane protein [ Review of clinical notes, retinal imaging, electroretinography (ERG), and molecular genetic testing. Two subjects underwent a cross-sectional examination comprising adaptive optics scanning laser ophthalmoscopy imaging of the retina and optoretinography (ORG). Clinical/demographic data, multimodal retinal imaging data, electrophysiology parameters, and molecular genetic testing. Our cohort included a diverse set of subjects with Our cohort data demonstrates that the underlying genetic variants drive the phenotypic diversity in different forms of NCL. Genetic testing can provide molecular diagnosis and ensure appropriate disease management and support for children and their families. With intravitreal enzyme replacement therapy on the horizon as a potential treatment option for NCL-associated retinal degeneration, precise structural and functional measures will be required to more accurately monitor disease progression. We show that adaptive optics imaging and ORG can be used as highly sensitive methods to track early retinal changes, which can be used to establish eligibility for future therapies and provide metrics for determining the efficacy of interventions on a cellular scale. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article. Show less
📄 PDF DOI: 10.1016/j.xops.2024.100560
CLN3

Potent and Protease Resistant Azapeptide Agonists of the GLP-1 and GIP Receptors.

Tristan C Dinsmore, Jamie Liu, Jiayuan Miao +5 more · 2024 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
The gut-derived peptide hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) play important physiological roles including glucose homeostasis and appetite su Show more
The gut-derived peptide hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) play important physiological roles including glucose homeostasis and appetite suppression. Stabilized agonists of the GLP-1 receptor (GLP-1R) and dual agonists of GLP-1R and GIP receptor (GIPR) for the management of type 2 diabetes and obesity have generated widespread enthusiasm and have become blockbuster drugs. These therapeutics are refractory to the action of dipeptidyl peptidase-4 (DPP4), that catalyzes rapid removal of the two N-terminal residues of the native peptides, in turn severely diminishing their activity profiles. Here we report that a single atom change from carbon to nitrogen in the backbone of the entire peptide makes them refractory to DPP4 action while still retaining full potency and efficacy at their respective receptors. This was accomplished by use of aza-amino acids, that are bioisosteric replacements for α-amino acids that perturb the structural backbone and local side chain conformations. Molecular dynamics simulations reveal that aza-amino acid can populate the same conformational space that GLP-1 adopts when bound to the GLP-1R. The insertion of an aza-amino acid at the second position from the N-terminus in semaglutide and in a dual agonist of GLP-1R and GIPR further demonstrates its capability as a viable alternative to current DPP4 resistance strategies while offering additional structural variation that may influence downstream signaling. Show less
no PDF DOI: 10.1002/anie.202410237
GIPR

Development of Neuroprotective Agents for the Treatment of Alzheimer's Disease using Conjugates of Serotonin with Sesquiterpene Lactones.

Margarita Neganova, Junqi Liu, Yulia Aleksandrova +7 more · 2024 · Current medicinal chemistry · Bentham Science · added 2026-04-24
Sesquiterpene lactones are secondary plant metabolites with a wide variety of biological activities. The process of lactone conjugation to other pharmacophores can increase the efficacy and specificit Show more
Sesquiterpene lactones are secondary plant metabolites with a wide variety of biological activities. The process of lactone conjugation to other pharmacophores can increase the efficacy and specificity of the conjugated agent effect on molecular targets in various diseases, including brain pathologies. Derivatives of biogenic indoles, including neurotransmitter serotonin, are of considerable interest as potential pharmacophores. Most of these compounds have neurotropic activity and, therefore, can be used in the synthesis of new drugs with neuroprotective properties. The aim of this experimental synthesis was to generate potential treatment agents for Alzheimer's disease using serotonin conjugated with natural sesquiterpene lactones. Three novel compounds were obtained via the Michael reaction and used for biological testing. The obtained conjugates demonstrated complex neuroprotective activities. Serotonin conjugated to isoalantolactone exhibited strong antioxidant and mitoprotective activities. The agent was also found to inhibit β-site amyloid precursor protein cleaving enzyme 1 (BACE-1), prevent the aggregation of β-amyloid peptide 1-42, and protect SH-SY5Y neuroblastoma cells from neurotoxins such as glutamate and H In conclusion, the obtained results indicate that serotonin conjugates to sesquiterpene lactones are promising agents for the treatment of symptoms associated with Alzheimer's disease. Show less
no PDF DOI: 10.2174/0929867330666221125105253
BACE1