👤 Yao 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, 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-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

Chicken cecal microbiota reduces abdominal fat deposition by regulating fat metabolism.

Yan Chen, Muhammad Akhtar, Ziyu Ma +9 more · 2023 · NPJ biofilms and microbiomes · Nature · added 2026-04-24
Cecal microbiota plays an essential role in chicken health. However, its contribution to fat metabolism, particularly in abdominal fat deposition, which is a severe problem in the poultry industry, is Show more
Cecal microbiota plays an essential role in chicken health. However, its contribution to fat metabolism, particularly in abdominal fat deposition, which is a severe problem in the poultry industry, is still unclear. Here, chickens at 1, 4, and 12 months of age with significantly (p < 0.05) higher and lower abdominal fat deposition were selected to elucidate fat metabolism. A significantly (p < 0.05) higher mRNA expression of fat anabolism genes (ACSL1, FADS1, CYP2C45, ACC, and FAS), a significantly (p < 0.05) lower mRNA expression of fat catabolism genes (CPT-1 and PPARα) and fat transport gene APOAI in liver/abdominal fat of high abdominal fat deposition chickens indicated that an unbalanced fat metabolism leads to excessive abdominal fat deposition. Parabacteroides, Parasutterella, Oscillibacter, and Anaerofustis were found significantly (p < 0.05) higher in high abdominal fat deposition chickens, while Sphaerochaeta was higher in low abdominal fat deposition chickens. Further, Spearman correlation analysis indicated that the relative abundance of cecal Parabacteroides, Parasutterella, Oscillibacter, and Anaerofustis was positively correlated with abdominal fat deposition, yet cecal Sphaerochaeta was negatively correlated with fat deposition. Interestingly, transferring fecal microbiota from adult chickens with low abdominal fat deposition into one-day-old chicks significantly (p < 0.05) decreased Parabacteroides and fat anabolism genes, while markedly increased Sphaerochaeta (p < 0.05) and fat catabolism genes (p < 0.05). Our findings might help to assess the potential mechanism of cecal microbiota regulating fat deposition in chicken production. Show less
📄 PDF DOI: 10.1038/s41522-023-00390-8
FADS1

Interleukin-17D produced by alveolar epithelial type II cells alleviates LPS-induced acute lung injury via the Nrf2 pathway.

Shuan Dong, Shasha Liu, Qiaoying Gao +10 more · 2023 · Clinical science (London, England : 1979) · added 2026-04-24
Sepsis engenders an imbalance in the body's inflammatory response, with cytokines assuming a pivotal role in its progression. A relatively recent addition to the interleukin-17 family, denominated int Show more
Sepsis engenders an imbalance in the body's inflammatory response, with cytokines assuming a pivotal role in its progression. A relatively recent addition to the interleukin-17 family, denominated interleukin-17D (IL-17D), is notably abundant within pulmonary confines. Nevertheless, its implication in sepsis remains somewhat enigmatic. The present study endeavors to scrutinize the participation of IL-17D in sepsis-induced acute lung injury (ALI). The levels of IL-17D in the serum and bronchoalveolar lavage fluid (BALF) of both healthy cohorts and septic patients were ascertained through an ELISA protocol. For the creation of a sepsis-induced ALI model, intraperitoneal lipopolysaccharide (LPS) injections were administered to male C57/BL6 mice. Subsequently, we examined the fluctuations and repercussions associated with IL-17D in sepsis-induced ALI, probing its interrelation with nuclear factor erythroid 2-related factor 2 (Nrf2), alveolar epithelial permeability, and heme oxygenase-1. IL-17D levels exhibited significant reduction both in the serum and BALF of septic patients (P<0.001). Similar observations manifested in mice subjected to LPS-induced acute lung injury (ALI) (P=0.002). Intraperitoneal administration of recombinant interleukin 17D protein (rIL-17D) prompted increased expression of claudin 18 and concomitant enhancement of alveolar epithelial permeability, thus, culminating in improved lung injury (P<0.001). Alveolar epithelial type II (ATII) cells were identified as the source of IL-17D, regulated by Nrf2. Furthermore, a deficiency in HO-1 yielded elevated IL-17D levels (P=0.004), albeit administration of rIL-17D ameliorated the exacerbated pulmonary damage resulting from HO-1 deficiency. Nrf2 fosters IL-17D production within AT II cells, thereby conferring a protective role in sepsis-induced ALI. Show less
no PDF DOI: 10.1042/CS20230354
IL27

Identification of novel urine proteomic biomarkers for high stamina in high-altitude adaptation.

Chunlei Liu, Ge Guo, Xin Li +6 more · 2023 · Frontiers in physiology · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fphys.2023.1153166
ACP2

USP10 strikes down β-catenin by dual-wielding deubiquitinase activity and phase separation potential.

Yinuo Wang, Aihua Mao, Jingwei Liu +21 more · 2023 · Cell chemical biology · Elsevier · added 2026-04-24
Wnt/β-catenin signaling is a conserved pathway crucially governing development, homeostasis, and oncogenesis. Discoveries of its regulators hold great values in both basic and translational research. Show more
Wnt/β-catenin signaling is a conserved pathway crucially governing development, homeostasis, and oncogenesis. Discoveries of its regulators hold great values in both basic and translational research. Through screening, we identified a deubiquitinase, USP10, as a critical modulator of β-catenin. Mechanistically, USP10 binds to key scaffold Axin1 via conserved motifs and stabilizes Axin1 through K48-linked deubiquitination. Surprisingly, USP10 physically tethers Axin1 and β-catenin and promotes the phase separation for β-catenin suppression regardless of the enzymatic activity. Function-wise, USP10 enzymatic activity preferably regulates embryonic development and both the enzymatic activity and physical function jointly control intestinal homeostasis by antagonizing β-catenin. In colorectal cancer, USP10 substantially represses cancer growth mainly through physical promotion of phase separation and correlates with Wnt/β-catenin magnitude clinically. Collectively, we discovered USP10 functioning in multiple biological processes against β-catenin and unearthed the enzyme-dependent and -independent "dual-regulating" mechanism. These two functions of USP10 work in parallel and are context dependent. Show less
no PDF DOI: 10.1016/j.chembiol.2023.07.016
AXIN1

FGF3 Directs the Pathfinding of Prethalamic GABAergic Axons.

Hong Huang, Qingyi Chen, Zhengang Xu +1 more · 2023 · International journal of molecular sciences · MDPI · added 2026-04-24
The thalamus plays a crucial role in ensuring the faithful transfer of sensory information, except olfactory signals, to corresponding cortical areas. However, thalamic function is not simply restrict Show more
The thalamus plays a crucial role in ensuring the faithful transfer of sensory information, except olfactory signals, to corresponding cortical areas. However, thalamic function is not simply restricted to relaying information to and from the cerebral cortex. The ability to modulate the flow of sensory information is supported by a second abundant neuronal type in the prethalamus, the inhibitory gamma-aminobutyric acid (GABAergic) neurons, which project inhibitory GABAergic axons to dorsal thalamic glutamatergic neurons. Interestingly, during the trajectory of pioneer prethalamic axons, morphogen fibroblast growth factor (FGF)-3 is expressed in the ventral chick hypothalamus. Using in vitro analyses in chick explants, we identify a chemorepellent effect of FGF3 on nearby prethalamic GABAergic axons. Furthermore, inhibition of FGF3 guidance functions indicates that FGF3 signaling is necessary to navigate prethalamic axons correctly. Gene expression analyses and loss of function studies demonstrate that FGF3 mediates prethalamic axonal guidance through the downstream pathway of the FGF receptor (FGFR)-1. Together, these results suggest that FGF3 expressed in the hypothalamus functions as a chemorepellent molecule to direct the pathway selection of neighboring GABAergic axons. Show less
📄 PDF DOI: 10.3390/ijms241914998
FGFR1

Probing long COVID through a proteomic lens: a comprehensive two-year longitudinal cohort study of hospitalised survivors.

Xiaoying Gu, Siyuan Wang, Wanying Zhang +15 more · 2023 · EBioMedicine · Elsevier · added 2026-04-24
As a debilitating condition that can impact a whole spectrum of people and involve multi-organ systems, long COVID has aroused the most attention than ever. However, mechanisms of long COVID are not c Show more
As a debilitating condition that can impact a whole spectrum of people and involve multi-organ systems, long COVID has aroused the most attention than ever. However, mechanisms of long COVID are not clearly understood, and underlying biomarkers that can affect the long-term consequences of COVID-19 are paramount to be identified. Participants for the current study were from a cohort study of COVID-19 survivors discharged from hospital between Jan 7, and May 29, 2020. We profiled the proteomic of plasma samples from hospitalised COVID-19 survivors at 6-month, 1-year, and 2-year after symptom onset and age and sex matched healthy controls. Fold-change of >2 or <0.5, and false-discovery rate adjusted P value of 0.05 were used to filter differentially expressed proteins (DEPs). In-genuity pathway analysis was performed to explore the down-stream effects in the dataset of significantly up- or down-regulated proteins. Proteins were integrated with long-term consequences of COVID-19 survivors to explore potential biomarkers of long COVID. The proteomic of 709 plasma samples from 181 COVID-19 survivors and 181 matched healthy controls was profiled. In both COVID-19 and control group, 114 (63%) were male. The results indicated four major recovery modes of biological processes. Pathways related to cell-matrix interactions and cytoskeletal remodeling and hypertrophic cardiomyopathy and dilated cardiomyopathy pathways recovered relatively earlier which was before 1-year after infection. Majority of immune response pathways, complement and coagulation cascade, and cholesterol metabolism returned to similar status of matched healthy controls later but before 2-year after infection. Fc receptor signaling pathway still did not return to status similar to healthy controls at 2-year follow-up. Pathways related to neuron generation and differentiation showed persistent suppression across 2-year after infection. Among 98 DEPs from the above pathways, evidence was found for association of 11 proteins with lung function recovery, with the associations consistent at two consecutive or all three follow-ups. These proteins were mainly enriched in complement and coagulation (COMP, PLG, SERPINE1, SRGN, COL1A1, FLNA, and APOE) and hypertrophic/dilated cardiomyopathy (TPM2, TPM1, and AGT) pathways. Two DEPs (APOA4 and LRP1) involved in both neuron and cholesterol pathways showed associations with smell disorder. The study findings provided molecular insights into potential mechanism of long COVID, and put forward biomarkers for more precise intervention to reduce burden of long COVID. National Natural Science Foundation of China; Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences; Clinical Research Operating Fund of Central High Level Hospitals; the Talent Program of the Chinese Academy of Medical Science; Training Program of the Big Science Strategy Plan; Ministry of Science and Technology of the People's Republic of China; New Cornerstone Science Foundation; Peking Union Medical College Education Foundation; Research Funds from Health@InnoHK Program. Show less
📄 PDF DOI: 10.1016/j.ebiom.2023.104851
APOA4

Thermal cycling-hyperthermia ameliorates Aβ

Yu-Yi Kuo, Wei-Ting Chen, Guan-Bo Lin +3 more · 2023 · Neuroscience letters · Elsevier · added 2026-04-24
Despite continuation of some controversies, Alzheimer's disease (AD), the most common cause of dementia nowadays, has been widely believed to derive mainly from excessive β-amyloid (Aβ) aggregation, t Show more
Despite continuation of some controversies, Alzheimer's disease (AD), the most common cause of dementia nowadays, has been widely believed to derive mainly from excessive β-amyloid (Aβ) aggregation, that would increase reactive oxygen species (ROS) and induce neuroinflammation, leading to neuron loss and cognitive impairment. Existing drugs on Aβ have been ineffective or offer only temporary relief at best, due to blood-brain barrier or severe side effects. The study employed thermal cycling-hyperthermia (TC-HT) to ease the Aβ-induced cognitive impairments and compared its effect with continuous hyperthermia (HT) in vivo. It established an AD mice model via intracerebroventricular (i.c.v.) injection of Aβ Show less
no PDF DOI: 10.1016/j.neulet.2023.137337
BACE1

Baicalein self-microemulsion based on drug-phospholipid complex for the alleviation of cytokine storm.

Hengfeng Liao, Jun Ye, Yue Gao +10 more · 2023 · Bioengineering & translational medicine · Wiley · added 2026-04-24
Cytokine storm is a phenomenon whereby the overreaction of the human immune system leads to the release of inflammatory cytokines, which can lead to multiple organ dysfunction syndrome. At present, th Show more
Cytokine storm is a phenomenon whereby the overreaction of the human immune system leads to the release of inflammatory cytokines, which can lead to multiple organ dysfunction syndrome. At present, the existing drugs for the treatment of cytokine storm have limited efficacy and severe adverse effects. Here, we report a lymphatic targeting self-microemulsifying drug delivery system containing baicalein to effectively inhibit cytokine storm. Baicalein self-microemulsion with phospholipid complex as an intermediate carrier (BAPC-SME) prepared in this study could be spontaneously emulsified to form 12-nm oil-in-water nanoemulsion after administration. And then BAPC-SME underwent uptake by enterocyte through endocytosis mediated by lipid valve and clathrin, and had obvious characteristics of mesenteric lymph node targeting distribution. Oral administration of BAPC-SME could significantly inhibit the increase in plasma levels of 14 cytokines: TNF-α, IL-6, IFN-γ, MCP-1, IL-17A, IL-27, IL-1α, GM-CSF, MIG, IFN-β, IL-12, MIP-3α, IL-23, and RANTES in mice experiencing systemic cytokine storm. BAPC-SME could also significantly improve the pathological injury and inflammatory cell infiltration of lung tissue in mice experiencing local cytokine storm. This study does not only provide a new lymphatic targeted drug delivery strategy for the treatment of cytokine storm but also has great practical significance for the clinical development of baicalein self-microemulsion therapies for cytokine storm. Show less
📄 PDF DOI: 10.1002/btm2.10357
IL27

Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure.

Danielle Rasooly, Gina M Peloso, Alexandre C Pereira +32 more · 2023 · Nature communications · Nature · added 2026-04-24
We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European anc Show more
We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure. Show less
📄 PDF DOI: 10.1038/s41467-023-39253-3
APOC3

m6A modified BACE1-AS contributes to liver metastasis and stemness-like properties in colorectal cancer through TUFT1 dependent activation of Wnt signaling.

Xidi Wang, Yu Liu, Miao Zhou +2 more · 2023 · Journal of experimental & clinical cancer research : CR · BioMed Central · added 2026-04-24
Liver metastasis is one of the most important reasons for high mortality of colorectal cancer (CRC). Growing evidence illustrates that lncRNAs play a critical role in CRC liver metastasis. Here we des Show more
Liver metastasis is one of the most important reasons for high mortality of colorectal cancer (CRC). Growing evidence illustrates that lncRNAs play a critical role in CRC liver metastasis. Here we described a novel function and mechanisms of BACE1-AS promoting CRC liver metastasis. qRT-PCR and in situ hybridization were performed to examine the BACE1-AS level in CRC. IGF2BP2 binding to m6A motifs in BACE1-AS was determined by RIP assay and S1m-tagged immunoprecipitation. Transwell assay and liver metastasis mice model experiments were performed to examine the metastasis capabilities of BACE1-AS knockout cells. Stemness-like properties was examined by tumor sphere assay and the expression of stemness biomarkers. Microarray data were acquired to analyze the signaling pathways involved in BACE1-AS promoting CRC metastasis. BACE1-AS is the most up-regulated in metastatic CRC associated with unfavorable prognosis. Sequence blast revealed two m6A motifs in BACE1-AS. IGF2BP2 binding to these two m6A motifs is required for BACE1-AS boost in metastatic CRC. m6A modified BACE1-AS drives CRC cells migration and invasion and liver metastasis both in vitro and in vivo. Moreover, BACE1-AS maintains the stemness-like properties of CRC cells. Mechanically, BACE1-AS promoted TUFT1 expression by ceRNA network through miR-214-3p. CRC patients with such ceRNA network suffer poorer prognosis than ceRNA-negative patients. Depletion of TUFT1 mimics BACE1-AS loss. BACE1-AS activated Wnt signaling pathway in a TUFT1 dependent manner. BACE1-AS/miR-214-3p/TUFT1/Wnt signaling regulatory axis is essential for CRC liver metastasis. Pharmacologic inhibition of Wnt signaling pathway repressed liver metastasis and stemness-like features in BACE1-AS over-expressed CRC cells. Our study demonstrated BACE1-AS as a novel target of IGF2BP2 through m6A modification. m6A modified BACE1-AS promotes CRC liver metastasis through TUFT1 dependent activation of Wnt signaling pathway. Thus, targeting BACE1-AS and its downstream Wnt signaling pathways may provide a new opportunity for metastatic CRC intervention and treatment. Show less
📄 PDF DOI: 10.1186/s13046-023-02881-0
BACE1

Role of interleukins in the detection of neonatal sepsis: a network meta-analysis.

Wei Xing, Ying Wang, Jiao Liu +2 more · 2023 · Frontiers in pediatrics · Frontiers · added 2026-04-24
The purpose of the network meta-analysis was to make a more comprehensive comparison of different interleukins in the detection of neonatal sepsis and to pose clues in the field of clinical practice. Show more
The purpose of the network meta-analysis was to make a more comprehensive comparison of different interleukins in the detection of neonatal sepsis and to pose clues in the field of clinical practice. Electronic databases of PubMed, Web of Science and Embase were systematically searched. Eligible studies included diagnostic tests utilizing interleukins to detect neonatal sepsis. We calculated pooled sensitivity, specificity, positive Likelihood Ratio (PLR) and negative Likelihood Ratio (NLR), diagnostic odds ratio (DOR), and superiority index. Fifteen studies including 1,369 neonates diagnosed of sepsis were included in this meta-analysis. For the detection of early-onset sepsis in neonates, the pooled sensitivity was 0.91 (95% CI: 0.81, 0.97; Findings of this network meta-analysis suggest that interleukins including IL-6, IL-8, IL-10, and IL-27 may have favorable performance in the detection of neonatal sepsis. IL-8 was more accurate in the detection of early-onset sepsis in neonates. IL-27 was more accurate in the detection of late-onset neonatal sepsis. Show less
📄 PDF DOI: 10.3389/fped.2023.1267777
IL27

Integrative analysis of the prognostic value and immune microenvironment of mitophagy-related signature for multiple myeloma.

Yachun Jia, Rui Liu, Luyi Shi +5 more · 2023 · BMC cancer · BioMed Central · added 2026-04-24
Multiple myeloma (MM) is a fatal malignant tumor in hematology. Mitophagy plays vital roles in the pathogenesis and drug sensitivity of MM. We acquired transcriptomic expression data and clinical inde Show more
Multiple myeloma (MM) is a fatal malignant tumor in hematology. Mitophagy plays vital roles in the pathogenesis and drug sensitivity of MM. We acquired transcriptomic expression data and clinical index of MM patients from NCI public database, and 36 genes involved in mitophagy from the gene set enrichment analysis (GSEA) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted to construct a risk score prognostic model. Kaplan-Meier survival analysis and receiver operation characteristic curves (ROC) were conducted to identify the efficiency of prognosis and diagnosis. ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) was performed to uncover the level of immune infiltration. QRT-PCR was performed to verify gene expression in clinical samples of MM patients. The sensitivity to chemotherapy drugs was evaluated upon the database of the genomics of drug sensitivity in cancer (GDSC). Fifty mitophagy-related genes were differently expressed in two independent cohorts. Ten out of these genes were identified to be related to MM overall survival (OS) rate. A prognostic risk signature model was built upon on these genes: VDAC1, PINK1, VPS13C, ATG13, and HUWE1, which predicted the survival of MM accurately and stably both in training and validation cohorts. MM patients suffered more adverse prognosis showed more higher risk core. In addition, the risk score was considered as an independent prognostic element for OS of MM patients by multivariate cox regression analysis. Functional pathway enrichment analysis of differentially expressed genes (DEGs) based on risk score showed terms of cell cycle, immune response, mTOR pathway, and MYC targets were obviously enriched. Furthermore, MM patients with higher risk score were observed lower immune scores and lower immune infiltration levels. The results of qRT-PCR verified VDAC1, PINK1, and HUWE1 were dysregulated in new diagnosed MM patients. Finally, further analysis indicated MM patients showed more susceptive to bortezomib, lenalidomide and rapamycin in high-risk group. Our research provided a neoteric prognostic model of MM based on mitophagy genes. The immune infiltration level based on risk score paved a better understanding of the participation of mitophagy in MM. Show less
no PDF DOI: 10.1186/s12885-023-11371-7
VPS13C

Activation of NR1H3 attenuates the severity of septic myocardial injury by inhibiting NLRP3 inflammasome.

Chao Deng, Qiong Liu, Huadong Zhao +9 more · 2023 · Bioengineering & translational medicine · Wiley · added 2026-04-24
Most sepsis deaths are due to the development of multiple organ failure, in which heart failure is a recognized manifestation of sepsis. To date, the role of liver X receptors α (NR1H3) in sepsis is s Show more
Most sepsis deaths are due to the development of multiple organ failure, in which heart failure is a recognized manifestation of sepsis. To date, the role of liver X receptors α (NR1H3) in sepsis is still uncertain. Here, we hypothesized that NR1H3 mediates multiple essential sepsis-related signalings to attenuate septic heart failure. Adult male C57BL/6 or Balbc mice and HL-1 myocardial cell line were performed for in vivo and in vitro experiments, respectively. NR1H3 knockout mice or NR1H3 agonist T0901317 was applied to evaluate the impact of NR1H3 on septic heart failure. We found decreased myocardial expression levels of NR1H3-related molecules while increased NLRP3 level in septic mice. NR1H3 knockout worsensed cardiac dysfunction and injury in mice subjected to cecal ligation and puncture (CLP), in association with exacerbated NLRP3-mediated inflammation, oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, and apoptosis-related markers. The administration of T0901317 reduced systemic infection and improve cardiac dysfunction in septic mice. Moreover, Co-IP assays, luciferase reporter assays, and chromatin immunoprecipitation analysis, confirmed that NR1H3 directly repressed NLRP3 activity. Finally, RNA-seq detection further clarified an overview of the roles of NR1H3 in sepsis. In general, our findings indicate that NR1H3 had a significant protective effect against sepsis and sepsis-induced heart failure. Show less
no PDF DOI: 10.1002/btm2.10517
NR1H3

A membrane-associated MHC-I inhibitory axis for cancer immune evasion.

Xufeng Chen, Qiao Lu, Hua Zhou +22 more · 2023 · Cell · Elsevier · added 2026-04-24
Immune-checkpoint blockade has revolutionized cancer treatment, but some cancers, such as acute myeloid leukemia (AML), do not respond or develop resistance. A potential mode of resistance is immune e Show more
Immune-checkpoint blockade has revolutionized cancer treatment, but some cancers, such as acute myeloid leukemia (AML), do not respond or develop resistance. A potential mode of resistance is immune evasion of T cell immunity involving aberrant major histocompatibility complex class I (MHC-I) antigen presentation (AP). To map such mechanisms of resistance, we identified key MHC-I regulators using specific peptide-MHC-I-guided CRISPR-Cas9 screens in AML. The top-ranked negative regulators were surface protein sushi domain containing 6 (SUSD6), transmembrane protein 127 (TMEM127), and the E3 ubiquitin ligase WWP2. SUSD6 is abundantly expressed in AML and multiple solid cancers, and its ablation enhanced MHC-I AP and reduced tumor growth in a CD8 Show less
no PDF DOI: 10.1016/j.cell.2023.07.016
WWP2

The deubiquitinase USP10 mediates crosstalk between the LKB1/AMPK axis and Wnt/β-catenin signaling in cancer.

Yinuo Wang, Jingwei Liu, Shaoqin Zheng +3 more · 2023 · FEBS letters · Wiley · added 2026-04-24
The liver kinase B1 (LKB1)/AMP-activated protein kinase (AMPK) axis pivotally controls cell metabolism and suppresses abnormal growth in various cancers. Wnt/β-catenin is a frequently dysregulated sig Show more
The liver kinase B1 (LKB1)/AMP-activated protein kinase (AMPK) axis pivotally controls cell metabolism and suppresses abnormal growth in various cancers. Wnt/β-catenin is a frequently dysregulated signaling pathway that drives oncogenesis. Here, we discovered a crosstalk mechanism between the LKB1/AMPK axis and Wnt/β-catenin signaling. Activated AMPK phosphorylates the deubiquitinase USP10 to potentiate the deubiquitination and stabilization of the key scaffold protein Axin1. This phosphorylation also strengthens the binding between USP10 and β-catenin and supports the phase transition of β-catenin. Both processes suppress Wnt/β-catenin amplitude in parallel and inhibit colorectal cancer growth in a clinically relevant manner. Collectively, we established a crosstalk route by which LKB1/AMPK regulates Wnt/β-catenin signaling in cancer. USP10 acts as the hub in this process, thus enabling LKB1/AMPK to suppress tumor growth via regulation of both metabolism and cell proliferation. Show less
no PDF DOI: 10.1002/1873-3468.14763
AXIN1

Genome-Wide Assessment of Runs of Homozygosity by Whole-Genome Sequencing in Diverse Horse Breeds Worldwide.

Chujie Chen, Bo Zhu, Xiangwei Tang +5 more · 2023 · Genes · MDPI · added 2026-04-24
In the genomes of diploid organisms, runs of homozygosity (ROH), consecutive segments of homozygosity, are extended. ROH can be applied to evaluate the inbreeding situation of individuals without pedi Show more
In the genomes of diploid organisms, runs of homozygosity (ROH), consecutive segments of homozygosity, are extended. ROH can be applied to evaluate the inbreeding situation of individuals without pedigree data and to detect selective signatures via ROH islands. We sequenced and analyzed data derived from the whole-genome sequencing of 97 horses, investigated the distribution of genome-wide ROH patterns, and calculated ROH-based inbreeding coefficients for 16 representative horse varieties from around the world. Our findings indicated that both ancient and recent inbreeding occurrences had varying degrees of impact on various horse breeds. However, recent inbreeding events were uncommon, particularly among indigenous horse breeds. Consequently, the ROH-based genomic inbreeding coefficient could aid in monitoring the level of inbreeding. Using the Thoroughbred population as a case study, we discovered 24 ROH islands containing 72 candidate genes associated with artificial selection traits. We found that the candidate genes in Thoroughbreds were involved in neurotransmission ( Show less
📄 PDF DOI: 10.3390/genes14061211
HEY2

Genome-wide association analysis of nine reproduction and morphological traits in three goat breeds from Southern China.

Xiaoyan Sun, Jing Jiang, Gaofu Wang +7 more · 2023 · Animal bioscience · added 2026-04-24
This study aimed to investigate the significant single nucleotide polymorphisms (SNPs) and genes associated with nine reproduction and morphological traits in three breed populations of Chinese goats. Show more
This study aimed to investigate the significant single nucleotide polymorphisms (SNPs) and genes associated with nine reproduction and morphological traits in three breed populations of Chinese goats. The genome-wide association of nine reproduction and morphological traits (litter size, nipple number, wattle, skin color, coat color, black dorsal line, beard, beard length, and hind leg hair) were analyzed in three Chinese native goat breeds (n = 336) using an Illumina Goat SNP50 Beadchip. A total of 17 genome-wide or chromosome-wide significant SNPs associated with one reproduction trait (litter size) and six morphological traits (wattle, coat color, black dorsal line, beard, beard length, and hind leg hair) were identified in three Chinese native goat breeds, and the candidate genes were annotated. The significant SNPs and corresponding putative candidate genes for each trait are as follows: two SNPs located on chromosomes 6 (CSN3) and 24 (TCF4) for litter size trait; two SNPs located on chromosome 9 (KATNA1) and 1 (UBASH3A) for wattle trait; three SNPs located on chromosome 26 (SORCS3), 24 (DYM), and 20 (PDE4D) for coat color trait; two SNPs located on chromosome 18 (TCF25) and 15 (CLMP) for black dorsal line trait; four SNPs located on chromosome 8, 2 (PAX3), 5 (PIK3C2G), and 28 (PLA2G12B and OIT3) for beard trait; one SNP located on chromosome 18 (KCNG4) for beard length trait; three SNPs located on chromosome 17 (GLRB and GRIA2), 28 (PGBD5), and 4 for hind leg hair trait. In contrast, there were no SNPs identified for nipple number and skin color. The significant SNPs or genes identified in this study provided novel insights into the genetic mechanism underlying important reproduction and morphological traits of three local goat breeds in Southern China as well as further potential applications for breeding goats. Show less
📄 PDF DOI: 10.5713/ab.21.0577
DYM

Application of systemic inflammation indices and lipid metabolism-related factors in coronary artery disease.

Zhuoyan Zhao, Huan Lian, Yixiang Liu +2 more · 2023 · Coronary artery disease · added 2026-04-24
We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application Show more
We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application of these factors in CAD. We enrolled 284 consecutive inpatients with suspected CAD and divided them into a CAD group and a non-CAD group according to coronary angiography results. Serum levels of angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4), and tumor necrosis factor-α (TNF-α) levels were assessed using the ELISA and the systemic inflammation indices were calculated. Multivariate logistic regression was used to assess the risk factors of CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values. The neutrophil-to-high density lipoprotein cholesterol ratio (5.04 vs. 3.47), neutrophil-to-lymphocyte ratio (3.25 vs. 2.45), monocyte-to-high density lipoprotein cholesterol ratio (MHR) (0.46 vs. 0.36), monocyte-to-lymphocyte ratio (0.31 vs. 0.26), systemic immune-inflammation index (SII) (696.00 vs. 544.82), serum TNF-α (398.15 ng/l vs. 350.65 ng/l), FABP4 (1644.00 ng/l vs. 1553.00 ng/l), ANGPTL3 (57.60 ng/ml vs. 52.85 ng/ml), and ANGPTL4 (37.35 ng/ml vs. 35.20 ng/ml) values showed a significant difference between the CAD and non-CAD groups ( P  < 0.05). After adjusting for confounding factors, the following values were obtained: ANGPTL3 > 67.53 ng/ml [odds ratio (OR) = 8.108, 95% confidence interval (CI) (1.022-65.620)]; ANGPTL4 > 29.95 ng/ml [OR = 5.599, 95% CI (1.809-17.334)]; MHR > 0.47 [OR = 4.872, 95% CI (1.715-13.835)]; SII > 589.12 [OR = 5.131, 95% CI (1.995-13.200)]. These factors were found to be independently associated with CAD ( P  < 0.05). Diabetes combined with MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l had the highest diagnostic value for CAD [area under the curve: 0.921, 95% CI, (0.881-0.960), Sensitivity: 88.9%, Specificity: 82.2%, P  < 0.001]. MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l were identified as independent CAD risk factors and have valuable clinical implications in the diagnosis and treatment of CAD. Show less
📄 PDF DOI: 10.1097/MCA.0000000000001239
ANGPTL4

FAT4 overexpression promotes antitumor immunity by regulating the β-catenin/STT3/PD-L1 axis in cervical cancer.

Dongying Wang, Shuying Wu, Jiaxing He +7 more · 2023 · Journal of experimental & clinical cancer research : CR · BioMed Central · added 2026-04-24
FAT4 (FAT Atypical Cadherin 4) is a member of the cadherin-associated protein family, which has been shown to function as a tumor suppressor by inhibiting proliferation and metastasis. The Wnt/β-caten Show more
FAT4 (FAT Atypical Cadherin 4) is a member of the cadherin-associated protein family, which has been shown to function as a tumor suppressor by inhibiting proliferation and metastasis. The Wnt/β-catenin pathway activation is highly associated with PD-L1-associated tumor immune escape. Here, we report the mechanism by which FAT4 overexpression regulates anti-tumor immunity in cervical cancer by inhibiting PD-L1 N-glycosylation and cell membrane localization in a β-catenin-dependent manner. FAT4 expression was first detected in cervical cancer tissues and cell lines. Cell proliferation, clone formation, and immunofluorescence were used to determine the tumor suppressive impact of FAT4 overexpression in vitro, and the findings were confirmed in immunodeficient and immunocomplete mice xenografts. Through functional and mechanistic experiments in vivo and in vitro, we investigated how FAT4 overexpression affects the antitumor immunity via the β-catenin/STT3/PD-L1 axis. FAT4 is downregulated in cervical cancer tissues and cell lines. We determined that FAT4 binds to β-catenin and antagonizes its nuclear localization, promotes phosphorylation and degradation of β-catenin by the degradation complexes (AXIN1, APC, GSK3β, CK1). FAT4 overexpression decreases programmed death-ligand 1 (PD-L1) mRNA expression at the transcriptional level, and causes aberrant glycosylation of PD-L1 via STT3A at the post-translational modifications (PTMs) level, leading to its endoplasmic reticulum (ER) accumulation and polyubiquitination-dependent degradation. We found that FAT4 overexpression promotes aberrant PD-L1 glycosylation and degradation in a β-catenin-dependent manner, thereby increasing cytotoxic T lymphocyte (CTL) activity in immunoreactive mouse models. These findings address the basis of Wnt/β-catenin pathway activation in cervical cancer and provide combination immunotherapy options for targeting the FAT4/β-catenin/STT3/PD-L1 axis. Schematic cartoons showing the antitumor immunity mechanism of FAT4. (left) when Wnts bind to their receptors, which are made up of Frizzled proteins and LRP5/6, the cytoplasmic protein DVL is activated, inducing the aggregation of degradation complexes (AXIN, GSK3β, CK1, APC) to the receptor. Subsequently, stable β-catenin translocates into the nucleus and binds to TCF/LEF and TCF7L2 transcription factors, leading to target genes transcription. The catalytically active subunit of oligosaccharyltransferase, STT3A, enhances PD-L1 glycosylation, and N-glycosylated PD-L1 translocates to the cell membrane via the ER-to-Golgi pathway, resulting in immune evasion. (Right) FAT4 exerts antitumor immunity mainly through following mechanisms: (i) FAT4 binds to β-catenin and antagonizes its nuclear localization, promotes phosphorylation and degradation of β-catenin by the degradation complexes (AXIN1, APC, GSK3β, CK1); (ii) FAT4 inhibits PD-L1 and STT3A transcription in a β-catenin-dependent manner and induces aberrant PD-L1 glycosylation and ubiquitination-dependent degradation; (iii) Promotes activation of cytotoxic T lymphocytes (CTL) and infiltration into the tumor microenvironment. Show less
📄 PDF DOI: 10.1186/s13046-023-02758-2
AXIN1

miR-136 Regulates the Proliferation and Adipogenic Differentiation of Adipose-Derived Stromal Vascular Fractions by Targeting

Jianhua Liu, Yutong Che, Ke Cai +5 more · 2023 · International journal of molecular sciences · MDPI · added 2026-04-24
Fat deposition involves the continuous differentiation of adipocytes and lipid accumulation. Studies have shown that microRNA miR-136 and 17β-hydroxysteroid dehydrogenase type 12 (
📄 PDF DOI: 10.3390/ijms241914892
HSD17B12

Effect of dapagliflozin on proteomics and metabolomics of serum from patients with type 2 diabetes.

Jia Liu, Xiaona Chang, Xiaoyu Ding +3 more · 2023 · Diabetology & metabolic syndrome · BioMed Central · added 2026-04-24
Sodium-glucose co-transporter 2 (SGLT2) inhibitors reduced the risk of cardiovascular and renal outcomes in patients with type 2 diabetes (T2D), but the underlying mechanism has not been well elucidat Show more
Sodium-glucose co-transporter 2 (SGLT2) inhibitors reduced the risk of cardiovascular and renal outcomes in patients with type 2 diabetes (T2D), but the underlying mechanism has not been well elucidated. The circulating levels of proteins and metabolites reflect the overall state of the human body. This study aimed to evaluate the effect of dapagliflozin on the proteome and metabolome in patients with newly diagnosed T2D. A total of 57 newly diagnosed T2D patients were enrolled, and received 12 weeks of dapagliflozin treatment (10 mg/d, AstraZeneca). Serum proteome and metabolome were investigated at the baseline and after dapagliflozin treatment. Dapagliflozin significantly decreased HbA1c, BMI, and HOMA-IR in T2D patients (all p < 0.01). Multivariate models indicated clear separations of proteomics and metabolomics data between the baseline and after dapagliflozin treatment. A total of 38 differentially abundant proteins including 23 increased and 15 decreased proteins, and 35 differentially abundant metabolites including 17 increased and 18 decreased metabolites, were identified. In addition to influencing glucose metabolism (glycolysis/gluconeogenesis and pentose phosphate pathway), dapagliflozin significantly increased sex hormone-binding globulin, transferrin receptor protein 1, disintegrin, and metalloprotease-like decysin-1 and apolipoprotein A-IV levels, and decreased complement C3, fibronectin, afamin, attractin, xanthine, and uric acid levels. The circulating proteome and metabolome in newly diagnosed T2D patients were significantly changed after dapagliflozin treatment. These changes in proteins and metabolites might be associated with the beneficial effect of dapagliflozin on cardiovascular and renal outcomes. Show less
📄 PDF DOI: 10.1186/s13098-023-01229-0
APOA4

Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis.

Lin Mei, Zhiming Zhang, Ruiqi Chen +3 more · 2023 · Arthritis research & therapy · BioMed Central · added 2026-04-24
Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and Show more
Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and environmental factors. We conducted a transcriptome-wide association study (TWAS) and chemical-related gene set enrichment analysis (CGSEA) to investigate the susceptibility genes and environmental factors. TWAS analysis was conducted to identify the susceptibility genes by integrating the summary-level genome-wide association study data of knee OA (KOA) and hip OA (HOA) with the precomputed expression weights from the Genotype-Tissue Expression Project (Version 8). The FUSION software was used for both single-tissue and cross-tissue TWAS, which were combined using an aggregate Cauchy association test. The biological function and pathways of the TWAS genes were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, and the human cartilage mRNA expression profiles were utilized to validate the TWAS genes. CGSEA analysis was performed to scan the OA-associated chemicals by integrating the TWAS results with the chemical-related gene sets. There were 44 and 93 unique TWAS genes identified in 7 and 11 chromosomes for KOA and HOA, respectively, fourteen and four of which showed significantly differential expression in the mRNA profiles, such as CRHR1, LTBP1, WWP2, LMX1B, and PTHLH. OA-related pathways were found in the KEGG and GO analysis, such as TGF-beta signaling pathway, MAPK signaling pathway, hyaluronan metabolic process, and chondrocyte differentiation. Forty-five OA-associated chemicals were identified, including quercetin, bisphenol A, and cadmium chloride. Several candidate OA-associated genes and chemicals were identified through TWAS and CGSEA analysis, which expanded our understanding of the relationship between genes, chemicals, and their impact on OA. Show less
no PDF DOI: 10.1186/s13075-023-03164-x
WWP2

Mechanistic and therapeutic links between rheumatoid arthritis and diabetes mellitus.

Jing Li, Yazhuo Chen, Qingyun Liu +2 more · 2023 · Clinical and experimental medicine · Springer · added 2026-04-24
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and irreversible cartilage and bone damage. Despite its predominant osteoarticular and peria Show more
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and irreversible cartilage and bone damage. Despite its predominant osteoarticular and periarticular manifestations, RA is also a systematic disease associated with organ-specific extra-articular manifestation. Increasing evidence indicates that RA patients are susceptible to diabetes mellitus (DM), and RA aggravates metabolic disordered in DM, indicating the close association between RA and DM. Many factors involved in RA stimulate insulin resistance and DM development. These factors include proinflammatory cytokines (such as TNF-α, IL-6, IL-1β), RA autoantibodies (such as rheumatoid factor, cyclic citrullinated peptide antibodies), excess RA related adipokines (such as leptin, resistin, ANGPTL4), C-creative protein, and other protein (such as TXNDC5, NLRP3, RBP4). Furthermore, commonly used RA drugs, such as conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), biological disease-modifying antirheumatic drugs (bDMARDs), and glucocorticoids, provide potential benefits in improving insulin resistance and inhibiting DM development. This review discusses the mechanistic and therapeutic links between RA and DM, aiming to provide valuable information for the prevention and treatment of DM in RA patients. Show less
📄 PDF DOI: 10.1007/s10238-022-00816-1
ANGPTL4

GDF15 deficiency hinders human trophoblast invasion to mediate pregnancy loss through downregulating Smad1/5 phosphorylation.

Yu-Ting Zeng, Wen-Fang Liu, Peng-Sheng Zheng +1 more · 2023 · iScience · Elsevier · added 2026-04-24
Growth differentiation factor 15 (GDF15) belongs to the Transforming growth factor β(TGF-β) superfamily. The decrease of GDF15 in the serum of pregnant women was associated with miscarriage. Both IHC Show more
Growth differentiation factor 15 (GDF15) belongs to the Transforming growth factor β(TGF-β) superfamily. The decrease of GDF15 in the serum of pregnant women was associated with miscarriage. Both IHC and ELISA assays showed that GDF15 in trophoblast tissue and serum of pregnant women who miscarried was significantly lower than in those who had a live birth. GDF15 deficiency was associated with embryo resorption in GDF15 knockout mice through CRIPSR editing. In addition, the migration and invasion ability of HTR-8/SVneo and JEG-3 cells were promoted by GDF15. Mechanistically, GDF15 increased Smad1/5 phosphorylation, resulting in upregulating SNAI1/2, VIMENTIN and downregulating E-CADHERIN. A dual-luciferase reporter assay confirmed that Smad-binding elements (SBE) and/or GC-rich motifs were activated and target genes such as SNAI1/2, SERPINE1, and TIMP3 were transcriptionally regulated by GDF15/Smad5 signaling. Therefore, our data revealed a crucial role of GDF15 on invasion of trophoblast by upregulating the activity of TGF-β/Smad1/5 pathway. Show less
no PDF DOI: 10.1016/j.isci.2023.107902
SNAI1

Research Note: Identification of core promoter region of the polyunsaturated fatty acid synthesis-related gene family in chicken.

Yongtong Liu, Dandan Sun, Xiaoqin Li +2 more · 2023 · Poultry science · Elsevier · added 2026-04-24
Chicken is considered an ideal model species to study the synthesis of polyunsaturated fatty acids (PUFAs) due to its appropriate proportions of fatty acids and abundant content of PUFAs, suitable for Show more
Chicken is considered an ideal model species to study the synthesis of polyunsaturated fatty acids (PUFAs) due to its appropriate proportions of fatty acids and abundant content of PUFAs, suitable for human consumption. However, the molecular mechanisms regulating poultry PUFA synthesis remain unclear. Here, we systematically explored the transcriptional regulation activity of the gene family related to PUFA synthesis in chicken by carrying out the Dual-Luciferase Reporter Assay. We identified the core promoter regions of members of the chicken PUFA synthesis-related gene family, including ELOVL1, ELOVL2, ELOVL3, ELOVL4, ELOVL5, ELOVL6, ELOVL7, FADS1, FADS2, FADS6, SCD, and SCD5. Additionally, changes in relative fluorescence values of different truncated segments in the upstream regulatory region of these genes indicate the existence of regulatory regions. Furthermore, we predicted the transcription factors that bind to the identified core promoter regions of multiple genes, including Sp1, NF-1, C/EBPalpha, etc. These findings provide a basis for the molecular mechanisms regulating poultry PUFA synthesis and offer new scientific insight into the potential improvement of poultry meat quality in the future. Show less
📄 PDF DOI: 10.1016/j.psj.2023.102857
FADS1

Adipocytes promote pancreatic cancer migration and invasion through fatty acid metabolic reprogramming.

Zhiwei Cai, Yang Li, Mingjian Ma +4 more · 2023 · Oncology reports · added 2026-04-24
Locally advanced and metastatic pancreatic cancer (PC) frequently grows in adipose tissue and has a poor prognosis. Although adipose tissue is largely composed of adipocytes, the mechanisms by which a Show more
Locally advanced and metastatic pancreatic cancer (PC) frequently grows in adipose tissue and has a poor prognosis. Although adipose tissue is largely composed of adipocytes, the mechanisms by which adipocytes impact PC are poorly understood. Using an Show less
📄 PDF DOI: 10.3892/or.2023.8578
ANGPTL4

Effects of Helicobacter pylori Infection on the Development of Chronic Gastritis.

Xiaoming Zhou, Yongming Zhu, Jiayu Liu +1 more · 2023 · The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · added 2026-04-24
Based on the gene expression profiles of gastric epithelial tissue at different stages of Helicobacter pylori-infected gastritis, key long noncoding RNAs and genes in the development of Helicobacter p Show more
Based on the gene expression profiles of gastric epithelial tissue at different stages of Helicobacter pylori-infected gastritis, key long noncoding RNAs and genes in the development of Helicobacter pylori infection-induced gastritis were screened to provide a basis for early diagnosis and treatment. We downloaded 2 sets of sample data from the database, including gastric epithelial tissue samples from gastritis patients from Bhutan and Dominican, and screened mRNAs in the differentially expressed RNAs of the 2 regions. Mfuzz clustering algorithm was used to screen RNAs related to the 3 stages of chronic gastritis. The competing endogenous RNA (ceRNA) regulation network was constructed, and the selected key RNAs were verified. Samples from Bhutan and Dominican were subdivided into the chronic gastritis/ normal comparison groups, and the differentially expressed RNAs were screened to obtain 1067 overlapping RNAs, containing 21 long noncoding RNAs and 1046 mRNAs. Thirty-eight significant gene ontology functional nodes and 6 expression pattern clusters were obtained. Two ceRNA regulatory networks were constructed, and 4 shared miRNAs (hsa-miR-320b, hsa-miR-320c, hsa-miR-320d, and hsa-miR-155-5p) were obtained. Eleven important long noncoding RNAs (AFAP1-AS1, MIR155HG, LINC00472, and FAM201A) and mRNAs (CASP10, SLC26A2, TRIB1, BMP2K, SCAMP1, TNKS1BP1, and MBOAT2) regulated by these 4 miRNAs were obtained. These results indicated that Helicobacter pylori infection had a certain influence on the development of gastritis. The 11 key RNAs can provide a target for the early diagnosis and treatment of chronic gastritis following Helicobacter pylori infection. Show less
no PDF DOI: 10.5152/tjg.2023.22316
TNKS1BP1

A nomogram based on the expression level of angiopoietin-like 4 to predict the severity of community-acquired pneumonia.

Siqin Chen, Jia Jiang, Minhong Su +9 more · 2023 · BMC infectious diseases · BioMed Central · added 2026-04-24
The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therap Show more
The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therapeutic target for pneumonia. This study aimed to develop a more objective, specific, accurate, and individualized scoring system to predict the severity of CAP. Totally, 31 non-severe community-acquired pneumonia (nsCAP) patients and 14 severe community-acquired pneumonia (sCAP) patients were enrolled in this study. The CURB-65 and pneumonia severity index (PSI) scores were calculated from the clinical data. Serum ANGPTL4 level was measured by enzyme-linked immunosorbent assay (ELISA). After screening factors by univariate analysis and receiver operating characteristic (ROC) curve analysis, multivariate logistic regression analysis of ANGPTL4 expression level and other risk factors was performed, and a nomogram was developed to predict the severity of CAP. This nomogram was further internally validated by bootstrap resampling with 1000 replications through the area under the ROC curve (AUC), the calibration curve, and the decision curve analysis (DCA). Finally, the prediction performance of the new nomogram model, CURB-65 score, and PSI score was compared by AUC, net reclassification index (NRI), and integrated discrimination improvement (IDI). A nomogram for predicting the severity of CAP was developed using three factors (C-reactive protein (CRP), procalcitonin (PCT), and ANGPTL4). According to the internal validation, the nomogram showed a great discrimination capability with an AUC of 0.910. The Hosmer-Lemeshow test and the approximately fitting calibration curve suggested a satisfactory accuracy of prediction. The results of DCA exhibited a great net benefit. The AUC values of CURB-65 score, PSI score, and the new prediction model were 0.857, 0.912, and 0.940, respectively. NRI comparing the new model with CURB-65 score was found to be statistically significant (NRI = 0.834, P < 0.05). A robust model for predicting the severity of CAP was developed based on the serum ANGPTL4 level. This may provide new insights into accurate assessment of the severity of CAP and its targeted therapy, particularly in the early-stage of the disease. Show less
📄 PDF DOI: 10.1186/s12879-023-08648-4
ANGPTL4

Mitophagy in Astrocytes Is Required for the Health of Optic Nerve.

Meysam Yazdankhah, Sayan Ghosh, Haitao Liu +3 more · 2023 · Cells · MDPI · added 2026-04-24
Mitochondrial dysfunction in astrocytes has been implicated in the development of various neurological disorders. Mitophagy, mitochondrial autophagy, is required for proper mitochondrial function by p Show more
Mitochondrial dysfunction in astrocytes has been implicated in the development of various neurological disorders. Mitophagy, mitochondrial autophagy, is required for proper mitochondrial function by preventing the accumulation of damaged mitochondria. The importance of mitophagy, specifically in the astrocytes of the optic nerve (ON), has been little studied. We introduce an animal model in which two separate mutations act synergistically to produce severe ON degeneration. The first mutation is in Show less
📄 PDF DOI: 10.3390/cells12202496
BCKDK

Sustained remission of type 2 diabetes in rodents by centrally administered fibroblast growth factor 4.

Hongbin Sun, Wei Lin, Yu Tang +17 more · 2023 · Cell metabolism · Elsevier · added 2026-04-24
Type 2 diabetes (T2D) is a major health and economic burden worldwide. Despite the availability of multiple drugs for short-term management, sustained remission of T2D is currently not achievable phar Show more
Type 2 diabetes (T2D) is a major health and economic burden worldwide. Despite the availability of multiple drugs for short-term management, sustained remission of T2D is currently not achievable pharmacologically. Intracerebroventricular administration of fibroblast growth factor 1 (icvFGF1) induces sustained remission in T2D rodents, propelling intense research efforts to understand its mechanism of action. Whether other FGFs possess similar therapeutic benefits is currently unknown. Here, we show that icvFGF4 also elicits a sustained antidiabetic effect in both male db/db mice and diet-induced obese mice by activating FGF receptor 1 (FGFR1) expressed in glucose-sensing neurons within the mediobasal hypothalamus. Specifically, FGF4 excites glucose-excited (GE) neurons while inhibiting glucose-inhibited (GI) neurons. Moreover, icvFGF4 restores the percentage of GI neurons in db/db mice. Importantly, intranasal delivery of FGF4 alleviates hyperglycemia in db/db mice, paving the way for non-invasive therapy. We conclude that icvFGF4 holds significant therapeutic potential for achieving sustained remission of T2D. Show less
no PDF DOI: 10.1016/j.cmet.2023.04.018
FGFR1