👤 Bowen 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, 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, 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

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

Prefrontal FGF1 Signaling is Required for Accumbal Deep Brain Stimulation Treatment of Addiction.

Wan-Kun Gong, Xue Li, Le Wang +9 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Deep brain stimulation (DBS) has emerged as a prospective treatment for psychiatric disorders; for example, DBS targeting the nucleus accumbens (NAc) abolishes addictive behaviors. However, neither th Show more
Deep brain stimulation (DBS) has emerged as a prospective treatment for psychiatric disorders; for example, DBS targeting the nucleus accumbens (NAc) abolishes addictive behaviors. However, neither the core pathway nor the cellular mechanisms underlying these therapeutic effects are known. Here, morphine-induced conditioned place preference (CPP) in mice as an addiction model and NAc-DBS combined with adeno-associated virus gene delivery for activity-dependent tagging, transgenic and chemogenetic manipulation of recruited neuronal networks are used. It is reported that a cortical-accumbal pathway and local fibroblast growth factor 1 (FGF1) signaling in the medial prefrontal cortex (mPFC) are critical for NAc-DBS to be effective in altering morphine CPP. It is shown that NAc-DBS retrogradely activates mPFC neurons projecting to the NAc, and chemogenetic activation/inhibition of these DBS-activated neuron ensembles in the mPFC reproduces the NAc-DBS effects on CPP. Sustained therapeutic effects accompany reductions in local FGF1 binding to fibroblast growth factor receptor 1 (FGFR1) in these neurons. Additionally, overexpressing FGF1 in the mPFC-NAc pathway abolishes the therapeutic effects of NAc-DBS. These results demonstrate that the mPFC-NAc pathway forms a top-down motif to regulate the therapeutic effects of subcortical DBS on addiction. These results support the potential for addiction treatments involving FGF1 signaling and highlight the mPFC as a target for noninvasive brain stimulation. Show less
📄 PDF DOI: 10.1002/advs.202413370
FGFR1

D-Ala2-GIP (1-30) promotes angiogenesis by facilitating endothelial cell migration via the Epac/Rap1/Cdc42 signaling pathway.

Tuchen Guan, Wenxue Zhang, Mingxuan Li +11 more · 2025 · Cellular signalling · Elsevier · added 2026-04-24
Angiogenesis, a meticulously regulated process essential for both normal development and pathological conditions, necessitates a comprehensive understanding of the endothelial mechanisms governing its Show more
Angiogenesis, a meticulously regulated process essential for both normal development and pathological conditions, necessitates a comprehensive understanding of the endothelial mechanisms governing its progression. Leveraging the zebrafish model and NgAgo knockdown system to identify target genes influencing angiogenesis, our study highlights the significant role of gastric inhibitory polypeptide (GIP) and its receptor (GIPR) in this process. While GIP has been extensively studied for its insulinotropic and glucagonotropic effects, its role in angiogenesis remains unexplored. This study demonstrated that GIPR knockdown induced developmental delays, morphological abnormalities, and pronounced angiogenic impairments in zebrafish embryos. Conversely, exogenous D-Ala2-GIP administration enhanced blood vessel formation in the yolk sac membrane of chick embryos. Consistent with these findings, D-Ala2-GIP treatment promoted microvessel formation in the tube formation assays and rat aortic ring models. Further investigation revealed that D-Ala2-GIP facilitated human umbilical vein endothelial cell (HUVEC) migration, a key step in angiogenesis, through the cyclic adenosine monophosphate (cAMP)-mediated activation of the Epac/Rap1/Cdc42 signaling pathway. This study provides novel insights into the angiogenic functions of GIP and its potential implications for cardiovascular biology. Show less
no PDF DOI: 10.1016/j.cellsig.2025.111615
GIPR

Integrative genome-wide analysis unveils the genetic landscape of gallstone disease and highlights novel loci with therapeutic potential.

Haotian Chen, Zhengye Liu, Hanze Du +7 more · 2025 · BMJ open gastroenterology · added 2026-04-24
Gallstone disease (GD) is a common gastrointestinal disorder with a significant genetic component. Despite known risk factors, the genetic basis of GD remains incompletely understood. We aimed to iden Show more
Gallstone disease (GD) is a common gastrointestinal disorder with a significant genetic component. Despite known risk factors, the genetic basis of GD remains incompletely understood. We aimed to identify novel genetic loci associated with GD, explore their clinical implications and investigate their therapeutic potential. We conducted a genome-wide association study from the UK Biobank followed by a meta-analysis, integrating summary statistics from the FinnGen R11, with further replication from Biobank Japan. Using systematic bioinformatic approaches, we performed gene prioritisation, colocalisation analysis, transcriptome-wide association study, Mendelian randomisations, cross-trait genetic correlations, phenome-wide association study, clinical investigations and gene-environment interactions by leveraging data from the FinnGen, Genotype-Tissue Expression project and Liver Cell Atlas single-cell transcriptomics data set. Our study highlighted novel susceptibility loci near candidate genes (ie, This study provides new insights into the genetic basis of GD and highlights the role of hepatocytes in GD pathogenesis. These findings have implications for the personalised prevention strategies and new therapeutic interventions in individuals predisposed to GD. Show less
📄 PDF DOI: 10.1136/bmjgast-2025-001976
FADS1

Activation of AMPK by GLP-1R agonists mitigates Alzheimer-related phenotypes in transgenic mice.

Yun Zhang, Huaqiu Chen, Yijia Feng +14 more · 2025 · Nature aging · Nature · added 2026-04-24
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential Show more
Individuals with type 2 diabetes mellitus have an increased risk of developing Alzheimer's disease (AD). GLP-1 receptor agonists (GLP-1RAs) are used for glycemic control in diabetes and show potential neuroprotective properties, but their effects on AD and the underlying mechanisms are not well understood. Here we demonstrate that GLP-1RAs can alleviate AD-related phenotypes by activating 5' AMP-activated protein kinase (AMPK) signaling. We found that plasma GLP-1 levels were decreased in AD model mice and negatively correlated with amyloid-beta (Aβ) load in patients with AD. Enhancing GLP-1 signaling through GLP-1RAs increased CaMKK2-AMPK signaling, which subsequently reduced BACE1-mediated cleavage of amyloid precursor protein (APP) and Aβ generation. GLP-1RAs also increased AMPK activity in microglia, inhibiting neuroinflammation and promoting Aβ phagocytosis. Consequently, GLP-1RAs inhibited plaque formation and improved memory deficits in AD model mice. Our findings indicate that AMPK activation mediates the effects of GLP-1RAs on AD, highlighting the therapeutic potential of GLP-1RAs for the treatment of AD. Show less
📄 PDF DOI: 10.1038/s43587-025-00869-3
BACE1

Transcriptomics analysis provides new insights into the ovarian lipid droplet formation and lipid deposition in Plectropomus leopardus.

Changqing He, Youheng Huang, Silvana Rahayu +7 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
The leopard coral grouper (Plectropomus leopardus), an increasingly important species in marine aquaculture, has garnered significant research interest due to its high market value. Despite extensive Show more
The leopard coral grouper (Plectropomus leopardus), an increasingly important species in marine aquaculture, has garnered significant research interest due to its high market value. Despite extensive research on ovarian growth and development in fish, the molecular mechanisms governing lipid droplet formation and lipid deposition in P. leopardus remain poorly understood. In this study, we conducted transcriptomic analyses of P. leopardus ovaries at three developmental stages: primary growth (PG), pre-vitellogenesis (PV), and mid-vitellogenesis (MV). A total of 534,847,090 raw reads were obtained from nine cDNA libraries, leading to the identification of 19,155 genes with 13,817 genes expressed at all stages. Differential analysis showed that 1012, 2609, and 4039 genes were up-regulated, while 168, 277, and 577 genes were down-regulated in the three comparisons, respectively. Functional enrichment analyses highlighting the critical roles of differentially expressed genes (DEGs) in lipid transport (such as fatp1, fatp4, fatp6, apoeb, lpl and fabps), fatty acid metabolism (such as elovl6, acsl1, dgat2 and gpat4) and phospholipid metabolism (such as ept1, chka and pla2g15). These findings underscore their contribution to lipid droplet formation and deposition. Furthermore, key signaling pathways, including Wnt, mTOR, PPAR and PI3K/Akt, were implicated in regulating these processes. The reliability of the RNA-seq data was confirmed through qPCR validation of 10 lipid-related genes. Based on these results, we propose a model for lipid droplet formation and lipid deposition during ovarian development in P. leopardus. This study advances our understanding of ovarian development in P. leopardus and provides a foundation for future research on marine fish reproduction, with potential applications in species conservation and aquaculture management. Show less
no PDF DOI: 10.1016/j.cbd.2025.101534
LPL

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

A whole-animal phenotypic drug screen identifies suppressors of atherogenic lipoproteins.

Daniel J Kelpsch, Liyun Zhang, James H Thierer +9 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which a Show more
Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which are responsible for transporting lipids to peripheral tissues. The cellular mechanisms that regulate ApoB and B-lp production, secretion, transport, and degradation remain to be fully defined. In humans, elevated levels of vascular B-lps play a causative role in cardiovascular disease. Previously, we have detailed that human B-lp biology is remarkably conserved in the zebrafish using an Show less
📄 PDF DOI: 10.1101/2024.11.14.623618
APOB

DEF6 regulates renal ischemia reperfusion injury through suppressing the WWP2 mediated ubiquitination of PARP1.

Haochong Hu, Yiting Liu, Shangting Han +3 more · 2025 · Biochimica et biophysica acta. Molecular basis of disease · Elsevier · added 2026-04-24
Renal ischemia-reperfusion injury (RIRI) stands as an unavoidable complication arising from kidney surgery, profoundly intertwined with its prognosis. The role of differentially expressed in FDCP 6 ho Show more
Renal ischemia-reperfusion injury (RIRI) stands as an unavoidable complication arising from kidney surgery, profoundly intertwined with its prognosis. The role of differentially expressed in FDCP 6 homolog (DEF6) in RIRI remains elusive, despite its confirmation as a potential therapeutic target for diverse diseases. Here, we investigated the mechanism by which DEF6 regulated RIRI. RNA sequencing data and IP-MS were used to identify the expression and potential targets of DEF6 through bioinformatics analysis. To elucidate the impact of DEF6 on RIRI, both an in vivo model of RIRI in mice and an in vitro model of kidney cell hypoxia/reoxygenation were established. Biochemical and histological analyses were used to investigate the influence of DEF6 on kidney damage mediated by RIRI. We confirmed that DEF6 was upregulated during RIRI and had a close correlation with RIRI-related inflammation and apoptosis. Moreover, inhibition of DEF6 could mitigate RIRI-induced kidney damage, inflammation, and apoptosis. Through our comprehensive mechanistic investigation, we revealed that DEF6 interacts with poly ADP-ribose polymerase 1 (PARP1) and suppresses the ubiquitination of PARP1. Inhibition of DEF6 resulted in reduced cleaveage of PARP1, leading to a marked suppression of PARP1-mediated apoptosis activation. The aggravation effect on inflammation and apoptosis achieved through DEF6 was nullified by the inhibition of NF-κB and Bax/Bcl2 signaling activation through PARP1 deletion. The findings from our study indicate that DEF6 suppressed the WWP2 mediated ubiquitination of PARP1 and modulates the activation of NF-κB and Bax/Bcl2 pathway, thus involved in RIRI-induced inflammation and apoptosis. These results suggest that DEF6 holds promise as a potential therapeutic target for mitigating RIRI. Show less
no PDF DOI: 10.1016/j.bbadis.2025.167681
WWP2

Prediction of Interspecies Translation for Targeting Delivery Coefficients of GalNAc-siRNA Silencing Apolipoprotein C-III Using a Mechanistic Minimal Physiologically Based Pharmacokinetic/Pharmacodynamic Model.

Zhiteng Tian, Hui Luo, Yantao Chu +5 more · 2025 · Clinical pharmacokinetics · Springer · added 2026-04-24
The emerging N-acetylgalactosamine-small interfering RNA (GalNAc-siRNA) conjugates lead the way for liver-targeting delivery to exert gene-silencing therapeutic effects. To facilitate the drug develop Show more
The emerging N-acetylgalactosamine-small interfering RNA (GalNAc-siRNA) conjugates lead the way for liver-targeting delivery to exert gene-silencing therapeutic effects. To facilitate the drug development of GalNAc-siRNA, further detailed understanding of the key modality-specific mechanisms underlying the temporal discordance between pharmacokinetics and pharmacodynamics and how these processes can be extrapolated from animals to humans is needed. A mechanistic minimal physiologically based pharmacokinetic/pharmacodynamic (mPBPK-PD) model for an investigational new apolipoprotein C-III (APOC3)-silencing GalNAc-siRNA (RBD5044) was developed using available pharmacokinetic/pharmacodynamic (PK/PD) data. The aim was to explore hepatic-targeting delivery processes, the PK/PD relationship, and interspecies translation. First, multiple PK/PD datasets from mice were satisfactorily fitted using the mPBPK-PD model. Second, we translated the mice model to the monkey model, validated it, and then extrapolated from mice and monkeys to humans to simulate the PK/PD characteristics. We then mechanistically summarized and proposed the essential in vivo delivery processes of GalNAc-siRNA after subcutaneous administration (termed "ADUEB": Absorption [into system circulation], Disposition [distribution to liver target and elimination], Uptake [into hepatocytes], Escape [from endosome and lysosome compartments], and Binding [with argonaute2 to form RNA-induced silencing complex]). The targeting delivery coefficients of these processes achieved with the model using RBD5044 and the published data of another GalNAc-siRNA (fitusiran) quantitatively reflected the delivery efficiency and rate-limiting factors in targeted hepatocytes. This study successfully constructed the mPBPK-PD model and conducted interspecies extrapolation for a GalNAc-siRNA targeting APOC3. Promising quantitative insights into a hepatic-targeted GalNAc-siRNA delivery system are provided to characterize the unique temporal disconnection of PK/PD properties and evaluate the key in vivo delivery processes. It will promote model-informed strategies and quantitative mechanistic understanding to support efficient drug development, evaluation, and clinical application of this modality in the future. Show less
📄 PDF DOI: 10.1007/s40262-025-01513-4
APOC3

Potential of CETP inhibition in treating dyslipidemia in systemic lupus erythematosus: Novel and comprehensive evidence from clinical studies and Mendelian randomization.

Yihong Gan, Yilin Zhang, Jingqun Liu +10 more · 2025 · International immunopharmacology · Elsevier · added 2026-04-24
Cardiovascular diseases from abnormal lipid metabolism significantly increase mortality in systemic lupus erythematosus (SLE). The causal link between dyslipidemia and SLE is unclear. Lipid metabolism Show more
Cardiovascular diseases from abnormal lipid metabolism significantly increase mortality in systemic lupus erythematosus (SLE). The causal link between dyslipidemia and SLE is unclear. Lipid metabolism in patients with SLE was evaluated based on clinical data from 511 patients with SLE and 706 healthy individuals. Bidirectional Mendelian randomization (MR) was employed to assess causal links between 179 plasma lipid metabolites, lipid-lowering drug targets, and SLE risk. Genetic instruments from GWAS and eQTL data were used to evaluate CETP and APOA4 effects. Peripheral blood CETP and apolipoprotein levels in SLE patients were validated via ELISA. SLE patients exhibited reduced HDL-C (P < 0.0001), APOA1 (P < 0.0001), and APOA4 (P < 0.0001), alongside elevated triglycerides (TG, P < 0.0001), APOC3, APOD, and APOF. MR identified three lipid metabolites-PC(18:2₂₀:4), TG(56:6), and TG(58:7)-as causal factors for SLE (P < 2.79E-5). CETP inhibition significantly reduced SLE risk via HDL-C modulation (OR = 0.72, P = 3.38E-08) and influenced LDL-C, TG, and apolipoproteins. Clinical validation confirmed elevated CETP and reduced APOA4 in SLE, correlating with disease activity. APOA4 activation showed protective effects, while PCSK9 inhibition lacked relevance. Bidirectional Mendelian randomization analyses confirmed dyslipidemia as a causal antecedent to SLE, with no evidence of reverse causation. A variety of MR analyses and clinical validation indicated that targeting HDL-C regulation offers significant advantages for managing dyslipidemia in patients with SLE, with CETP identified as the optimal pharmacological target. Show less
no PDF DOI: 10.1016/j.intimp.2025.114736
APOA4

Secretion and transfer of adipose lipoprotein lipase utilizes neutral sphingomyelinase 2 generated exosomes.

Terri A Pietka, Edward F Morris, Megan Basco +7 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Lipoprotein lipase (LPL) is critical for clearance of circulating triglycerides and for tissue fatty acid supply. LPL is primarily synthesized and secreted by adipocytes into the interstitium and must Show more
Lipoprotein lipase (LPL) is critical for clearance of circulating triglycerides and for tissue fatty acid supply. LPL is primarily synthesized and secreted by adipocytes into the interstitium and must traffic from there to the abluminal/basolateral side of capillary endothelial cells. There, LPL binds glycosylphosphatidylinositol-anchored protein 1, GPIHBP1, which stabilizes the protein and facilitates its movement across the endothelial cells to the luminal side where it functions in hydrolysis of lipoprotein triglycerides. Importance of LPL traffic is supported by findings that rare mutations in GPIHBP1 cause hypertriglyceridemia. However our understanding of how LPL is secreted by adipocytes and traffics to endothelial cells is incomplete. Here we examined the possibility that secretion and traffic of adipocyte LPL might involve generation of small extracellular vesicles (sEVs/exosomes) which often mediate cell-cell communication. Proteomic analysis of sEVs secreted by adipocytes showed them enriched in LPL. To study LPL secretion and transfer we generated human derived pre-adipocytes (HPA) that stably express tagged LPL (FLAG and His epitopes). LPL pulldown and sEV isolation from HPA conditioned media documented that greater than 70% of secreted LPL is present in sEVs. The mechanism for LPL secretion in sEVs was found to involve the ESCRT-independent neutral sphingomyelinase 2 (nSMase2) pathway, as treatment with the nSMase2 inhibitor GW4869 reduced secretion by 80%. The above observations were reproduced using highly sensitive nanoparticle flow cytometry. The sEV associated LPL has lipolytic activity and it is released by heparin addition indicating it is on the sEV surface. In addition, using human derived microvascular endothelial cells with stable lentiviral expression of GPIHBP1 we show that LPL positive sEVs transfer LPL to these cells, but not to control cells without GPIHBP1. Our findings suggest that sEV formation by nSMase2 controls adipocyte LPL secretion and traffic, that sEVs protect LPL activity and facilitate LPL transfer to GPIHBP1 on endothelial cells. Show less
📄 PDF DOI: 10.1101/2025.07.31.665751
LPL

L3MBTL3 and STAT3 collaboratively upregulate SNAIL expression to promote metastasis in female breast cancer.

Jianpeng Xiao, Jie Wang, Jialun Li +11 more · 2025 · Nature communications · Nature · added 2026-04-24
The STAT3 pathway promotes epithelial-mesenchymal transition, migration, invasion and metastasis in cancer. STAT3 upregulates the transcription of the key epithelial-mesenchymal transition transcripti Show more
The STAT3 pathway promotes epithelial-mesenchymal transition, migration, invasion and metastasis in cancer. STAT3 upregulates the transcription of the key epithelial-mesenchymal transition transcription factor SNAIL in a DNA binding-independent manner. However, the mechanism by which STAT3 is recruited to the SNAIL promoter to upregulate its expression is still elusive. In our study, the lysine methylation binding protein L3MBTL3 is positively associated with metastasis and poor prognosis in female patients with breast cancer. L3MBTL3 also promotes epithelial-mesenchymal transition and metastasis in breast cancer. Mechanistic analysis reveals that L3MBTL3 interacts with STAT3 and recruits STAT3 to the SNAIL promoter to increase SNAIL transcription levels. The interaction between L3MBTL3 and STAT3 is required for SNAIL transcription upregulation and metastasis in breast cancer, while the methylated lysine binding activity of L3MBTL3 is not required for these functions. In conclusion, L3MBTL3 and STAT3 synergistically upregulate SNAIL expression to promote breast cancer metastasis. Show less
no PDF DOI: 10.1038/s41467-024-55617-9
SNAI1

Clinical Relationship Between Serum ApoB, HER2, and Myocardial Ischemia Risk in Breast Cancer Patients.

Yeyan Lei, Dongmei Li, Shuang Bai +3 more · 2025 · Cancer reports (Hoboken, N.J.) · Wiley · added 2026-04-24
The risk factors and clinical prediction of cardiovascular comorbidities in patients with breast cancer have not been fully clarified. This retrospective case-control study was designed to investigate Show more
The risk factors and clinical prediction of cardiovascular comorbidities in patients with breast cancer have not been fully clarified. This retrospective case-control study was designed to investigate the factors affecting myocardial ischemia occurrence in breast cancer patients. A total of 194 cases (144 breast cancer and 50 benign breast tumor patients) were included. Univariate and multivariable Cox regression found that ApoB, age, and HER2 were significant factors responsible for the myocardial ischemia occurrence in breast cancer patients. By comparing the significance of ApoB in breast cancer patients versus benign breast tumor patients, it was observed that ApoB and HER2 were crucial predictors of myocardial ischemia in breast cancer patients compared to those with benign breast tumors. These factors were utilized to construct the clinical prediction model, achieving a combined area under the curve (AUC) of 0.583. The decision curve analysis (DCA) indicated that the model-predicted population, within a threshold ranging from 0.35 to 0.70, would experience a therapeutically clinical net benefit. Kaplan-Meier plot indicated that ApoB We demonstrated that ApoB and HER2 were potential factors in predicting the myocardial ischemia occurrence in breast cancer patients. This study will help provide clinical evidence for the early prediction of cardiovascular comorbidities in breast cancer patients. Show less
📄 PDF DOI: 10.1002/cnr2.70075
APOB

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

Dietary Supplementation with Whole-Fat or Defatted Antarctic Krill Powder Improves the Growth Performance, Body Coloration, and Immune Capability of Red-White Koi Carp (

Hongmei Song, Yixin Liang, Yexin Yang +4 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
This study was conducted to investigate the effects of replacing fish meal with either whole-fat or defatted krill powder on the growth, body color, immunity, and related gene expression of red-white Show more
This study was conducted to investigate the effects of replacing fish meal with either whole-fat or defatted krill powder on the growth, body color, immunity, and related gene expression of red-white koi carp. A total of 630 red-white koi carp with an initial body mass of 13.5 ± 0.05 g were randomly divided into seven groups with three replicates per group and 30 fish per replicate. The control group was fed a basic diet (C0). The other six diets were supplemented with different levels of whole krill meal or defatted krill meal as replacements (10% whole fat, 20% whole fat, 30% whole fat, 10% defatted, 20% defatted, and 30% defatted) in the experimental groups, named W10, W20, W30, D10, D20, and D30, respectively, for a total duration of 60 days. The growth, body color, immunity and gene expression indexes were measured in the koi after completion. The results indicate the following. (1) Compared with C0, the experimental groups of koi showed a significant increase in the specific growth rate (SGR) ( Show less
📄 PDF DOI: 10.3390/ani15111561
LPL

Genotype and phenotype correlation analysis in 27 families with multiple osteochondroma and validation by ATDC5 chondrocyte models.

XiaoYan Guo, Mingrui Lin, Shan Xu +4 more · 2025 · Bone & joint research · added 2026-04-24
This study aimed to explore the genotype and phenotype correlation of patients with multiple osteochondroma (MO), and validate phenotypic differences in ATDC5 cell model with Mutation analysis was emp Show more
This study aimed to explore the genotype and phenotype correlation of patients with multiple osteochondroma (MO), and validate phenotypic differences in ATDC5 cell model with Mutation analysis was employed in 27 families with MO using polymerase chain reaction (PCR)-Sanger sequencing and targeted next-generation sequencing (t-NGS). ATDC5 cell model with A total of 27 pathogenic mutations were identified in Clinical research identified nine novel mutations in Show less
📄 PDF DOI: 10.1302/2046-3758.1410.BJR-2024-0477.R1
EXT1

Shared Plasma Metabolites Mediate Causal Effects of Metabolic Diseases on Colorectal Cancer: A Two-Step Mendelian Randomization Study.

Xinyi Shi, Yuxin Tang, Yu Zhang +4 more · 2025 · Biomedicines · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/biomedicines13102433
FADS1

Inhibitory role of arecaidine on PPARγ signaling in oral mucosa: Mechanistic insights from transcriptome and experimental analysis.

Fanzuo Zeng, Zhenkui Liu, Jian Yi +5 more · 2025 · Toxicon : official journal of the International Society on Toxinology · Elsevier · added 2026-04-24
This study aims to elucidate the effects of arecaidine on oral mucosa through RNA sequencing (RNA-Seq) combined with in vivo and in vitro experimental validation. Based on transcriptomic analysis, we Show more
This study aims to elucidate the effects of arecaidine on oral mucosa through RNA sequencing (RNA-Seq) combined with in vivo and in vitro experimental validation. Based on transcriptomic analysis, we preliminarily explored the molecular targets and mechanisms by which arecaidine influences oral mucosa. Subsequent validation was performed using arecaidine-treated human primary oral mucosal fibroblasts. In vivo experiments revealed that the arecaidine-treated group exhibited significantly restricted oral cavity opening compared to the control group, with markedly reduced mouth-opening values. Histopathological analysis via HE staining and Masson staining demonstrated fibrotic lesions in the arecaidine-treated group. RNA-Seq libraries constructed from oral mucosal tissues identified 100 significantly differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that arecaidine influenced multiple pathways, including autoimmune thyroid disease, allograft rejection, type I diabetes, graft-versus-host disease, and the PPAR-γ signaling pathway. Notably, arecaidine significantly downregulated PPAR-γ, PCK1, pdk4, plin5, Hmgcs2, UCP3, and Angptl4, while upregulating TGF-β1, FOS, and other genes associated with the PPAR pathway. In vitro experiments confirmed that arecaidine induced substantial damage to fibroblasts, suppressing proliferation and promoting the secretion of inflammatory cytokines (e.g., IL-6, TGF-β, TNF-α) after 48 h exposure to high concentrations. Furthermore, arecaidine significantly altered the expression of molecules linked to the PPAR-γ signaling pathway. This study delineates the transcriptomic response of oral mucosa to arecaidine through integrated in vivo and in vitro experiments, confirming its role in inducing submucosal fibrosis. The underlying mechanism is associated with dysregulation of the PPAR-γ signaling pathway. Show less
no PDF DOI: 10.1016/j.toxicon.2025.108403
ANGPTL4

The Batten disease gene Cln3 is required for the activation of intestinal stem cell during regeneration via JAK/STAT signaling in

Zihua Yu, Jinhua Yan, Zhiming Liu +3 more · 2025 · Frontiers in cell and developmental biology · Frontiers · added 2026-04-24
CLN3 mutation causes Juvenile neuronal ceroid lipofuscinosis (JNCL, also known as Batten disease), an early onset neurodegenerative disorder. Patients who suffer from Batten disease often die at an ea Show more
CLN3 mutation causes Juvenile neuronal ceroid lipofuscinosis (JNCL, also known as Batten disease), an early onset neurodegenerative disorder. Patients who suffer from Batten disease often die at an early age. However, the mechanisms underlying how CLN3 loss develops Batten disease remain largely unclear. Here, using Show less
📄 PDF DOI: 10.3389/fcell.2025.1508714
CLN3

Transcriptome analysis of postnatal mouse cardiac tissue growth and development.

Xiao-Cong Zhu, Sheng-Nan Wang, Lin Jiang +1 more · 2025 · Yi chuan = Hereditas · added 2026-04-24
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy h Show more
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy have not yet been fully elucidated. Therefore, phenotypic measurements and transcriptomic sequencing were performed on myocardial tissues from 7-day-old (P7) and 3-month-old (3m) female C57BL/6 mice to investigate changes in cardiomyocytes during growth and development and to identify key genes regulating myocardial growth and development. In comparison to 7-day-old mice, 3-month-old mice exhibited a significant increase in heart weight ( Show less
no PDF DOI: 10.16288/j.yczz.24-328
HEY2

TRAF3IP3::FGFR1: a novel FGFR1 fusion identified in an aggressive case of acute myeloid leukemia.

Xue Chen, Lili Yuan, Xiaoli Ma +8 more · 2025 · Annals of hematology · Springer · added 2026-04-24
Myeloid/lymphoid neoplasms with tyrosine kinase gene fusions (MLN-TK) are rare hematologic malignancies characterized by recurrent kinase rearrangements, including
📄 PDF DOI: 10.1007/s00277-025-06494-9
FGFR1

Sparstolonin B and Curcumin alleviate atherogenesis by modulating T helper 17-stromal cell interactions associated with interleukin-17 receptor A (IL-17RA) - transforming growth factor-β-activated kinase 1 (TAK1) - nuclear factor-kappa B (NF-κB) signaling.

Guofu Zhong, Qingqing Liu, Qing Zhang +11 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Sparstolonin B (SSNB) and Curcumin (Cur), from a pair of compatible herbs, were previously identified as anti-inflammation and T helper 17 (Th17) modulation reagents. However, their compatible roles i Show more
Sparstolonin B (SSNB) and Curcumin (Cur), from a pair of compatible herbs, were previously identified as anti-inflammation and T helper 17 (Th17) modulation reagents. However, their compatible roles in atherosclerosis (AS) and underlying mechanisms remain uninvestigated. In vivo, the apoE The gene-disease interaction and hub gene network reveals Th17-associated genes in the pathogenesis of atherosclerosis. In vitro, SSNB and Cur reduced oxLDL-induced BMDC activation by downregulating CD36. SSNB showed stronger inhibition to inflammatory activation of DC, while Cur more intensively suppressed co-stimulatory molecules. For the Th17/Treg bias in co-culture of BMDC and CD4 Our findings reveal, for the first time, that SSNB and Cur alleviate AS by modulating Th17-stromal cell interactions, with the IL-17RA-TAK1-NF-κB pathway as a related mediator. Notably, SSNB and Cur exhibit distinct anti-atherogenic roles. SSNB primarily targets TLR4/CD36 to inhibit DC activation, Th17 differentiation, VSMC inflammation and mainly inhibited TAK1 phosphorylation, while Cur more significant inhibited macrophage inflammation, and more directly inhibited NF-κB P65 phosphorylation. This study will be valuable for developing novel and precise adjuvant therapies for AS. Show less
no PDF DOI: 10.1016/j.phymed.2025.157578
APOE

Integrated Transcriptomic Analysis of Liver and Muscle Tissues Reveals Candidate Genes and Pathways Regulating Intramuscular Fat Deposition in Beef Cattle.

Siwei Wang, Tingting Liu, Peng Peng +6 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Intramuscular fat (IMF) content in beef cattle is a critical determinant of beef meat quality, as it positively influences juiciness, tenderness, and palatability. In China, the crossbreeding of Wagyu Show more
Intramuscular fat (IMF) content in beef cattle is a critical determinant of beef meat quality, as it positively influences juiciness, tenderness, and palatability. In China, the crossbreeding of Wagyu and Angus is a prevalent method for achieving a better marbling level. However, the molecular mechanisms governing IMF regulation in these crossbreeds remain poorly understood. To elucidate the mechanism of IMF deposition in these crossbred cattle, we conducted a comparative transcriptomic analysis of Show less
📄 PDF DOI: 10.3390/ani15091306
LPL

Integrated Bioinformatics Analysis and Cellular Experimental Validation Identify Lipoprotein Lipase Gene as a Novel Biomarker for Tumorigenesis and Prognosis in Lung Adenocarcinoma.

Wanwan He, Meilian Wei, Yan Huang +8 more · 2025 · Biology · MDPI · added 2026-04-24
Lung adenocarcinoma (LUAD) is one of the leading causes of death worldwide, and thus, more biomarker and therapeutic targets need to be explored. Herein, we aimed to explore new biomarkers of LUAD by Show more
Lung adenocarcinoma (LUAD) is one of the leading causes of death worldwide, and thus, more biomarker and therapeutic targets need to be explored. Herein, we aimed to explore new biomarkers of LUAD by integrating bioinformatics analysis with cell experiments. We firstly identified 266 druggable genes that were significantly differentially expressed between LUAD tissues and adjacent normal lung tissues. Among these genes, SMR analysis with Show less
📄 PDF DOI: 10.3390/biology14050566
LPL

C-type natriuretic peptide regulates lipid metabolism through a NPRB-PPAR pathway in the intramuscular and subcutaneous adipocytes in chickens.

Huayun Huang, Longzhou Liu, Zhong Liang +5 more · 2025 · Scientific reports · Nature · added 2026-04-24
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanism Show more
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanisms that underlie its activity are not completely understood. Treatment of intramuscular fat (IMF) and subcutaneous fat (SCF) adipocytes with CNP led to decreased differentiation, promoted proliferation and lipolysis, and increased the expression of natriuretic peptide receptor B (NPRB) mRNA. Silencing natriuretic peptide C (NPPC) had the opposite results in IMF and SCF adipocytes. Transcriptome analysis found 665 differentially expressed genes (DEGs) in IMF adipocytes and 991 in SCF adipocytes. Seven genes in IMF adipocytes (FABP4, APOA1, ACOX2, ADIPOQ, CD36, FABP5, and LPL) and eight genes in SCF adipocytes (ACOX3, ACSL1, APOA1, CPT1A, CPT2, FABP4, PDPK1 and PPARα) are related to fat metabolism. Fifteen genes were found to be enriched in the peroxisome proliferator-activated receptor (PPAR) pathway. Integrated analysis identified 113 intersection genes in IMF and SCF adipocytes, two of which (APOA1 and FABP4) were enriched in the PPAR pathway. In conclusion, CNP may regulated lipid metabolism through the NPRB-PPAR pathway in both IMF and SCF adipocytes, FABP4 and APOA1 may be the key genes that mediated CNP regulation of fat deposition. Show less
📄 PDF DOI: 10.1038/s41598-025-86433-w
LPL

Association of

Na Liu, Hongli Zeng, Xiangsheng Cai +6 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
To investigate the association between polymorphisms of the A case-control study was conducted, enrolling 100 HTG patients and 100 age-matched controls with normal triglyceride levels from the physica Show more
To investigate the association between polymorphisms of the A case-control study was conducted, enrolling 100 HTG patients and 100 age-matched controls with normal triglyceride levels from the physical examination cohort at Guangzhou 11th People's Hospital (January-December 2023) The observation group showed significant differences in genotype frequencies of Show less
📄 PDF DOI: 10.3389/fgene.2025.1654501
APOA5

A new species of the genus

Tao Zhang, Siyu Yang, Haijun Jiang +7 more · 2025 · ZooKeys · added 2026-04-24
The genus
📄 PDF DOI: 10.3897/zookeys.1262.164459
APOB

Rationale and Design of the EPISODE Trial: A Randomized Controlled Trial on the Effect of PCSK9 Inhibitors in Calcific Aortic Valve Stenosis.

Yang Zheng, Qiuxuan Li, Yuxiu Yang +4 more · 2025 · Journal of the American Heart Association · added 2026-04-24
Calcific aortic valve stenosis (CAVS) can lead to cardiac adverse outcomes; however, currently, no effective pharmacological interventions are available to prevent or delay disease progression. Emergi Show more
Calcific aortic valve stenosis (CAVS) can lead to cardiac adverse outcomes; however, currently, no effective pharmacological interventions are available to prevent or delay disease progression. Emerging evidence has identified significant associations between CAVS and key biomarkers, including Lp(a) (lipoprotein [a]), low-density lipoprotein cholesterol, and PCSK9 (proprotein convertase subtilisin/kexin type 9). However, robust evidence from randomized controlled trials is still lacking to substantiate these associations. The EPISODE (Effect of PCSK9 Inhibitors on Calcific Aortic Valve Stenosis) trial is a prospective, evaluator-blinded, randomized controlled trial designed to assess the therapeutic efficacy of PCSK9 inhibitors in patients with CAVS. A total of 160 patients with mild-to-moderate or asymptomatic severe CAVS will be randomly assigned to receive either statin monotherapy or a combination of statins and PCSK9 inhibitors. Participants will undergo follow-up assessments at 3-month intervals for 24 months, including transthoracic ultrasonic cardiogram, computed tomography, and quality-of-life evaluations using the EuroQol-5 Dimension-3 Level questionnaire. The primary end point is the annualized change in peak aortic jet velocity, whereas secondary end points encompass changes in aortic valve area, calcification score, incidence of heart valve surgery, and quality of life. Safety end points include all-cause mortality and cardiovascular events. The trial aims to evaluate the efficacy of PCSK9 inhibitors in modulating disease progression, reducing adverse cardiovascular events, and improving clinical outcomes in patients with CAVS. The anticipated findings are expected to provide critical insights for developing novel therapeutic strategies for early intervention in CAVS. URL: https://www.clinicaltrials.gov; Unique Identifier: NCT04968509. Show less
📄 PDF DOI: 10.1161/JAHA.125.042112
LPA

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