👤 Changya 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, 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

Unveiling the bioinformatic genes and their involved regulatory mechanisms in type 2 diabetes combined with osteoarthritis.

Guangming Mao, Wenhao Xu, Lingli Wan +8 more · 2024 · Frontiers in immunology · Frontiers · added 2026-04-24
Type 2 Diabetes Mellitus (T2D) and Osteoarthritis (OA) are both prevalent diseases that significantly impact the health of patients. Increasing evidence suggests that there is a big correlation betwee Show more
Type 2 Diabetes Mellitus (T2D) and Osteoarthritis (OA) are both prevalent diseases that significantly impact the health of patients. Increasing evidence suggests that there is a big correlation between T2D and OA, but the molecular mechanisms remain elusive. The aims of this study are to investigate the shared biomarkers and potential molecular mechanisms in T2D combined with OA. T2D and OA-related differentially expressed genes (DEGs) were identified via bioinformatic analysis on Gene Expression Omnibus (GEO) datasets GSE26168 and GSE114007 respectively. Subsequently, extensive target prediction and network analysis were finished with Gene Ontology (GO), protein-protein interaction (PPI), and pathway enrichment with DEGs. The transcription factors (TFs) and miRNAs coupled in co-expressed DEGs involved in T2D and OA were predicted as well. The key genes expressed both in the clinical tissues of T2D and OA were detected with western blot and qRT-PCR assay. Finally, the most promising candidate compounds were predicted with the Drug-Gene Interaction Database (DGIdb) and molecular docking. In this study, 209 shared DEGs between T2D and OA were identified. Functional analysis disclosed that these DEGs are predominantly related to ossification, regulation of leukocyte migration, extracellular matrix (ECM) structural constituents, PI3K/AKT, and Wnt signaling pathways. Further analysis via Protein-Protein Interaction (PPI) analysis and validation with external datasets emphasized MMP9 and ANGPTL4 as crucial genes in both T2D and OA. Our findings were validated through qRT-PCR and Western blot analyses, which indicated high expression levels of these pivotal genes in T2D, OA, and T2D combined with OA cases. Additionally, the analysis of Transcription Factors (TFs)-miRNA interactions identified 7 TFs and one miRNA that jointly regulate these important genes. The Receiver Operating characteristic (ROC) analysis demonstrated the significant diagnostic potential of MMP9 and ANGPTL4.Moreover, we identified raloxifene, ezetimibe, and S-3304 as promising agents for patients with both T2D and OA. This study uncovers the shared signaling pathways, biomarkers, potential therapeutics, and diagnostic models for individuals suffering from both T2D and OA. These findings not only present novel perspectives on the complex interplay between T2D and OA but also hold significant promise for improving the clinical management and prognosis of patients with this concurrent condition. Show less
📄 PDF DOI: 10.3389/fimmu.2024.1353915
ANGPTL4

Reprogramming of DNA methylation patterns mediates perfluorooctane sulfonate-induced fetal cardiac dysplasia.

Min Qiu, Jing Chen, Mingqin Liu +7 more · 2024 · The Science of the total environment · Elsevier · added 2026-04-24
Prenatal exposure to perfluorooctane sulfonate (PFOS) is associated with adverse health effects, including congenital heart disease, yet the underlying mechanisms remain elusive. Herein, we aimed to e Show more
Prenatal exposure to perfluorooctane sulfonate (PFOS) is associated with adverse health effects, including congenital heart disease, yet the underlying mechanisms remain elusive. Herein, we aimed to evaluate the embryotoxicity of PFOS using C57BL/6 J mice to characterize fetal heart defects after PFOS exposure, with the induction of human embryonic stem cells (hESC) into cardiomyocytes (CMs) as a model of early-stage heart development. We also performed DNA methylation analysis to clarify potential underlying mechanisms and identify targets of PFOS. Our results revealed that PFOS caused septal defects and excessive ventricular trabeculation cardiomyopathy at 5 mg/kg/day in embryonic mice and inhibited the proliferation and pluripotency of ESCs at concentrations >20 μM. Moreover, it decreased the beating rate and the population of CMs during cardiac differentiation. Decreases were observed in the abundances of NPPA+ trabecular and HEY2+ compact CMs. Additionally, DNA methyl transferases and ten-eleven translocation (TET) dioxygenases were regulated dynamically by PFOS, with TETs inhibitor treatment inducing significant decreases similar as PFOS. 850 K DNA methylation analysis combined with expression analysis revealed several potential targets of PFOS, including SORBS2, FHOD1, SLIT2, SLIT3, ADCY9, and HDAC9. In conclusion, PFOS may reprogram DNA methylation, especially demethylation, to induce cardiac toxicity, causing ventricular defects in vivo and abnormal cardiac differentiation in vitro. Show less
no PDF DOI: 10.1016/j.scitotenv.2024.170905
HEY2

Three-dimensional echocardiography reveals early mitral valve alterations in hypertrophic cardiomyopathy genetic mutation carriers.

Nianwei Zhou, Ao Liu, Haobo Weng +8 more · 2024 · International journal of cardiology · Elsevier · added 2026-04-24
The mitral valve undergoes structural modifications in response to cardiac functional changes, often predating cardiac decompensation and overt clinical signs. Our study assessed the potential of mitr Show more
The mitral valve undergoes structural modifications in response to cardiac functional changes, often predating cardiac decompensation and overt clinical signs. Our study assessed the potential of mitral valve morphological changes as early indicators for detecting carriers of hypertrophic cardiomyopathy (HCM)-associated gene mutations. We studied 505 participants: 189 without the pathogenic gene mutations and left ventricular hypertrophy (G-/LVH-), 149 carriers without LV hypertrophy (G+/LVH-), and 167 manifest HCM patients (G+/LVH+). We juxtaposed the mitral valve morphology and associated metrics across these groups, emphasizing those carrying MYH7 and MYBPC3 mutations. We discerned pronounced disparities in the mitral annulus and leaflet structures across the groups. The mitral valve apparatus in mutation carriers exhibited a tendency towards a flattened profile. Detailed analysis spotlighted MYBPC3 mutation carriers, whose mitral valves were notably flatter (with notably lower AHCWR values than non-carriers); this contrast was not evident in MYH7 mutation carriers. This mitral valve flattening, manifest in the mutation carriers, suggests it might be an adaptive response to incipient cardiac dysfunction in HCM's nascent stages. Three-dimensional echocardiography illuminates the initial mitral valve structural changes in HCM patients bearing pathogenic gene mutations. These morphological signatures hold promise as sensitive imaging markers, especially for asymptomatic carriers of the MYBPC3 mutation. Show less
no PDF DOI: 10.1016/j.ijcard.2023.131576
MYBPC3

Characterization of the regulatory network and pathways in duodenum affecting chicken abdominal fat deposition.

Zhijie Liu, Sibei Cheng, Xing Zhang +8 more · 2024 · Poultry science · Elsevier · added 2026-04-24
The excessive accumulation of abdominal fat in chickens has resulted in a reduction in both the feed conversion efficiency and the slaughter yield. To elucidate the regulatory mechanisms and metabolic Show more
The excessive accumulation of abdominal fat in chickens has resulted in a reduction in both the feed conversion efficiency and the slaughter yield. To elucidate the regulatory mechanisms and metabolic pathways affecting abdominal fat deposition in the context of broiler breeding, a cohort of 400 Qingyuan partridge chickens with varying abdominal fat deposition was established. Whole transcriptome sequencing analyses were conducted on the duodenum of 20 representative chickens to ascertain the regulatory networks at this vital digestive and absorptive organ. Consequently, 116 differentially expressed genes were identified, exhibiting a trend of increasing or decreasing expression in correlation with the accumulation of abdominal fat. A total of 36 DEmRNAs, 170 DElncRNAs, 92 DEcircRNAs and 88 DEmiRNAs were identified as differentially expressed between chickens with extremely high and low abdominal fat deposition. The functional enrichment analyses demonstrated that the differentially expressed RNA in the duodenum were involved in the regulation of chicken abdominal fat deposition by mediating a series of metabolic pathways, including the Wnt signaling pathway, the PPAR signaling pathway, the Hippo signaling pathway, the FoxO signaling pathway, the MAPK signaling pathway and other signaling pathways that are involved in fatty acid metabolism and degradation. The construction of putative interaction pairs led to the suggestion of two lncRNA-miRNA-mRNA ceRNA networks comprising two mRNAs, two miRNAs, and 29 lncRNAs, as well as two circRNA-lncRNA-miRNA-mRNA ceRNA networks comprising 26 mRNAs, 12 miRNAs, 17 lncRNAs, and nine circRNAs, as core regulatory networks in the duodenum affecting chicken abdominal fat deposition. The aforementioned genes including TMEM150C, REXO1, PIK3C2G, ppp1cb, PARP12, SERPINE2, LRAT, CYP1A1, INSR and APOA4, were proposed as candidate genes, while the miRNAs, including miR-107-y, miR-22-y, miR-25-y, miR-2404-x and miR-16-x, as well as lncRNAs such as ENSGALT00000100291, TCONS₀₀₀₆₃₅₀₈, TCONS₀₀₀₆₁₂₀₁ and TCONS₀₀₀₇₉₄₀₂ were the candidate regulators associated with chicken abdominal fat deposition. The findings of this study provide a theoretical foundation for the molecular mechanisms of mRNAs and non-coding RNAs in duodenal tissues on abdominal fat deposition in chickens. Show less
📄 PDF DOI: 10.1016/j.psj.2024.104463
APOA4

Podocyte-specific Nup160 knockout mice develop nephrotic syndrome and glomerulosclerosis.

Yuanyuan Li, Chan Xu, Feng Zhao +10 more · 2024 · Human molecular genetics · Oxford University Press · added 2026-04-24
More than 60 monogenic genes mutated in steroid-resistant nephrotic syndrome (SRNS) have been identified. Our previous study found that mutations in nucleoporin 160 kD (NUP160) are implicated in SRNS. Show more
More than 60 monogenic genes mutated in steroid-resistant nephrotic syndrome (SRNS) have been identified. Our previous study found that mutations in nucleoporin 160 kD (NUP160) are implicated in SRNS. The NUP160 gene encodes a component of the nuclear pore complex. Recently, two siblings with homozygous NUP160 mutations presented with SRNS and a nervous system disorder. However, replication of nephrotic syndrome (NS)-associated phenotypes in a mammalian model following loss of Nup160 is needed to prove that NUP160 mutations cause SRNS. Here, we generated a podocyte-specific Nup160 knockout (Nup160podKO) mouse model using CRISPR/Cas9 and Cre/loxP technologies. We investigated NS-associated phenotypes in these Nup160podKO mice. We verified efficient abrogation of Nup160 in Nup160podKO mice at both the DNA and protein levels. We showed that Nup160podKO mice develop typical signs of NS. Nup160podKO mice exhibited progression of proteinuria to average albumin/creatinine ratio (ACR) levels of 15.06 ± 2.71 mg/mg at 26 weeks, and had lower serum albumin levels of 13.13 ± 1.34 g/l at 30 weeks. Littermate control mice had urinary ACR mean values of 0.03 mg/mg and serum albumin values of 22.89 ± 0.34 g/l at the corresponding ages. Further, Nup160podKO mice exhibited glomerulosclerosis compared with littermate control mice. Podocyte-specific Nup160 knockout in mice led to NS and glomerulosclerosis. Thus, our findings strongly support that mutations in NUP160 cause SRNS. The newly generated Nup160podKO mice are a reliable mammalian model for future study of the pathogenesis of NUP160-associated SRNS. Show less
no PDF DOI: 10.1093/hmg/ddad211
NUP160

The inflammatory microenvironment of nasal polyps in patients with chronic rhinosinusitis and the relationship of this microenvironment with the nasal microbiome.

Weigang Gan, Yu Xiang, Bo Wei +2 more · 2024 · Asian journal of surgery · Elsevier · added 2026-04-24
We investigated the characteristics of the microbial community of the nasal sinuses in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) and identified the correlations of the nasal micr Show more
We investigated the characteristics of the microbial community of the nasal sinuses in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) and identified the correlations of the nasal microbiome with the inflammatory microenvironment of the nasal cavity. We collected matched nasal secretion and polyp tissue samples from 77 CRSwNP patients. Then, we extracted microbial DNA from cotton swabs, used high-throughput sequencing technology based on 16S ribosomal RNA (rRNA) to detect the bacterial community composition, and detected cytokines such as interleukin (IL)-5, IL-8, IL-17a, IL-17e, IL-18, IL-27 and interferon (INF)-gamma in the polyp tissue samples using Luminex. Eosinophils and neutrophils in the peripheral blood and polyp tissue were counted, and the relationships between inflammatory factors or inflammatory cell counts and nasal microbial diversity were analyzed. Among the inflammatory factors evaluated, IL-5 had a positive rate of 32.47%, IFN-γ had a positive rate of 84.42%, IL-17A and IL-17E had positive rates of 75.32%, IL-18 had a positive rate of 94.81%, IL-27 had a positive rate of 68.83%, and IL-8 had a positive rate of 100%. IL-17a and IL-27 were negatively correlated with both Enterobacter and Anaerococcus, IL-8 was negatively correlated with both Enterobacter and Staphylococcus, IL-18 was positively correlated with Candidatus Arthromitus and negatively correlated with Haemophilus, and IL-27 was positively correlated with Faecalibaculum. Lactobacillus and Enterococcus were positively correlated with the degree of neutrophil infiltration in nasal polyp tissue. In Southwest China, inflammation of the nasal polyps exhibits a variety of patterns. Enterobacteria and anaerobic bacteria may be correlated with the inflammatory pattern of nasal polyps. The neutrophil-mediated inflammatory response plays an important role in patients with CRSwNP in Southwest China. Show less
no PDF DOI: 10.1016/j.asjsur.2023.08.096
IL27

Loss of GIPR in LEPR cells impairs glucose control by GIP and GIP:GLP-1 co-agonism without affecting body weight and food intake in mice.

Seun Akindehin, Arkadiusz Liskiewicz, Daniela Liskiewicz +28 more · 2024 · Molecular metabolism · Elsevier · added 2026-04-24
The glucose-dependent insulinotropic polypeptide (GIP) decreases body weight via central GIP receptor (GIPR) signaling, but the underlying mechanisms remain largely unknown. Here, we assessed whether Show more
The glucose-dependent insulinotropic polypeptide (GIP) decreases body weight via central GIP receptor (GIPR) signaling, but the underlying mechanisms remain largely unknown. Here, we assessed whether GIP regulates body weight and glucose control via GIPR signaling in cells that express the leptin receptor (Lepr). Hypothalamic, hindbrain, and pancreatic co-expression of Gipr and Lepr was assessed using single cell RNAseq analysis. Mice with deletion of Gipr in Lepr cells were generated and metabolically characterized for alterations in diet-induced obesity (DIO), glucose control and leptin sensitivity. Long-acting single- and dual-agonists at GIPR and GLP-1R were further used to assess drug effects on energy and glucose metabolism in DIO wildtype (WT) and Lepr-Gipr knock-out (KO) mice. Gipr and Lepr show strong co-expression in the pancreas, but not in the hypothalamus and hindbrain. DIO Lepr-Gipr KO mice are indistinguishable from WT controls related to body weight, food intake and diet-induced leptin resistance. Acyl-GIP and the GIPR:GLP-1R co-agonist MAR709 remain fully efficacious to decrease body weight and food intake in DIO Lepr-Gipr KO mice. Consistent with the demonstration that Gipr and Lepr highly co-localize in the endocrine pancreas, including the β-cells, we find the superior glycemic effect of GIPR:GLP-1R co-agonism over single GLP-1R agonism to vanish in Lepr-Gipr KO mice. GIPR signaling in cells/neurons that express the leptin receptor is not implicated in the control of body weight or food intake, but is of crucial importance for the superior glycemic effects of GIPR:GLP-1R co-agonism relative to single GLP-1R agonism. Show less
📄 PDF DOI: 10.1016/j.molmet.2024.101915
GIPR

Potential role of the P2X7 receptor in the proliferation of human diffused large B-cell lymphoma.

Xiao Yang, Yuanyuan Ji, Lin Mei +3 more · 2024 · Purinergic signalling · Springer · added 2026-04-24
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of invasive non-Hodgkin lymphoma. 60-70% of patients are curable with current chemoimmunotherapy, whereas the rest are refractory or re Show more
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of invasive non-Hodgkin lymphoma. 60-70% of patients are curable with current chemoimmunotherapy, whereas the rest are refractory or relapsed. Understanding of the interaction between DLBCL cells and tumor microenvironment raises the hope of improving overall survival of DLBCL patients. P2X7, a member of purinergic receptors P2X family, is activated by extracellular ATP and subsequently promotes the progression of various malignancies. However, its role in DLBCL has not been elucidated. In this study, the expression level of P2RX7 in DLBCL patients and cell lines was analyzed. MTS assay and EdU incorporation assay were carried out to study the effect of activated/inhibited P2X7 signaling on the proliferation of DLBCL cells. Bulk RNAseq was performed to explore potential mechanism. The results demonstrated high level expression of P2RX7 in DLBCL patients, typically in patients with relapse DLBCL. 2'(3')-O-(4-benzoylbenzoyl) adenosine 5-triphosphate (Bz-ATP), an agonist of P2X7, significantly accelerated the proliferation of DLBCL cells, whereas delayed proliferation was detected when administrated with antagonist A740003. Furthermore, a urea cycle enzyme named CPS1 (carbamoyl phosphate synthase 1), which up-regulated in P2X7-activated DLBCL cells while down-regulated in P2X7-inhibited group, was demonstrated to involve in such process. Our study reveals the role of P2X7 in the proliferation of DLBCL cells and implies that P2X7 may serve as a potential molecular target for the treatment of DLBCL. Show less
no PDF DOI: 10.1007/s11302-023-09947-w
CPS1

Understanding m6A changes in chromophobe renal cell carcinoma and predicting patient outcomes survival.

Zhigang Chen, Junbo Yang, Wei Zhang +10 more · 2024 · BMC cancer · BioMed Central · added 2026-04-24
N6-methyladenosine (m
📄 PDF DOI: 10.1186/s12885-024-12956-6
FGFR1

The histone demethylase JMJD1C regulates CPS1 expression and promotes the proliferation of paroxysmal nocturnal haemoglobinuria clones through cell metabolic reprogramming.

Yingying Chen, Hui Liu, Chaomeng Wang +6 more · 2024 · British journal of haematology · Blackwell Publishing · added 2026-04-24
Paroxysmal nocturnal haemoglobinuria (PNH) is a disorder resulting from erythrocyte membrane deficiencies caused by PIG-A gene mutations. While current treatments alleviate symptoms, they fail to addr Show more
Paroxysmal nocturnal haemoglobinuria (PNH) is a disorder resulting from erythrocyte membrane deficiencies caused by PIG-A gene mutations. While current treatments alleviate symptoms, they fail to address the underlying cause of the disease-the pathogenic PNH clones. In this study, we found that the expression of carbamoyl phosphate synthetase 1 (CPS1) was downregulated in PNH clones, and the level of CPS1 was negatively correlated with the proportion of PNH clones. Using PIG-A knockout K562 (K562 KO) cells, we demonstrated that CPS1 knockdown increased cell proliferation and altered cell metabolism, suggesting that CPS1 participates in PNH clonal proliferation through metabolic reprogramming. Furthermore, we observed an increase in the expression levels of the histone demethylase JMJD1C in PNH clones, and JMJD1C expression was negatively correlated with CPS1 expression. Knocking down JMJD1C in K562 KO cells upregulated CPS1 and H3K36me3 expression, decreased cell proliferation and increased cell apoptosis. Chromatin immunoprecipitation analysis further demonstrated that H3K36me3 regulated CPS1 expression. Finally, we demonstrated that histone demethylase inhibitor JIB-04 can suppressed K562 KO cell proliferation and reduced the proportion of PNH clones in PNH mice. In conclusion, aberrant regulation of the JMJD1C-H3K36me3-CPS1 axis contributes to PNH clonal proliferation. Targeting JMJD1C with a specific inhibitor unveils a potential strategy for treating PNH patients. Show less
no PDF DOI: 10.1111/bjh.19477
CPS1

APOA5 alleviates reactive oxygen species to promote oxaliplatin resistance in PIK3CA-mutated colorectal cancer.

Yu-Lin Liu, Zhuo Xiang, Bo-Ya Zhang +7 more · 2024 · Aging · Impact Journals · added 2026-04-24
Although platinum-based chemotherapy is the frontline regimen for colorectal cancer (CRC), drug resistance remains a major challenge affecting its therapeutic efficiency. However, there is limited res Show more
Although platinum-based chemotherapy is the frontline regimen for colorectal cancer (CRC), drug resistance remains a major challenge affecting its therapeutic efficiency. However, there is limited research on the correlation between chemotherapy resistance and lipid metabolism, including PIK3CA mutant tumors. In this present study, we found that PIK3CA-E545K mutation attenuated cell apoptosis and increased the cell viability of CRC with L-OHP treatment Show less
📄 PDF DOI: 10.18632/aging.205872
APOA5

Exploring DIX-DIX Homo- and Hetero-Oligomers in Wnt Signaling with AlphaFold2.

Zehua Wen, Lei Wang, Shi-Wei Liu +3 more · 2024 · Cells · MDPI · added 2026-04-24
Wnt signaling is involved in embryo development and cancer. The binding between the DIX domains of Axin1/2, Dishevelled1/2/3, and Coiled-coil-DIX1 is essential for Wnt/β-catenin signaling. Structural Show more
Wnt signaling is involved in embryo development and cancer. The binding between the DIX domains of Axin1/2, Dishevelled1/2/3, and Coiled-coil-DIX1 is essential for Wnt/β-catenin signaling. Structural and biological studies have revealed that DIX domains are polymerized through head-to-tail interface interactions, which are indispensable for activating β-catenin Wnt signaling. Although different isoforms of Dvl and Axin proteins display both redundant and specific functions in Wnt signaling, the specificity of DIX-mediated interactions remains unclear due to technical challenges. Using AlphaFold2(AF2), we predict the structures of 6 homodimers and 22 heterodimers of DIX domains without templates and compare them with the reported X-ray complex structures. PRODIGY is used to calculate the binding affinities of these DIX complexes. Our results show that the Axin2 DIX homodimer has a stronger binding affinity than the Axin1 DIX homodimer. Among Dishevelled (Dvl) proteins, the binding affinity of the Dvl1 DIX homodimer is stronger than that of Dvl2 and Dvl3. The Coiled-coil-DIX1(Ccd1) DIX homodimer shows weaker binding than the Axin1 DIX homodimer. Generally, heterodimer interactions tend to be stronger than those of homodimers. Our findings provide insights into the mechanism of the Wnt signaling pathway and highlight the potential of AF2 and PRODIGY for studying protein-protein interactions in signaling pathways. Show less
📄 PDF DOI: 10.3390/cells13191646
AXIN1

Recent discoveries of Sino-Caucasian differences in the genetics of phaeochromocytomas and paragangliomas.

Jingjing Jiang, Yujun Liu · 2024 · Best practice & research. Clinical endocrinology & metabolism · Elsevier · added 2026-04-24
Pheochromocytomas and paragangliomas (PPGLs) represent the highest degree of heritability of any known tumor types in humans. Previous studies have characterized a dramatic difference between Chinese Show more
Pheochromocytomas and paragangliomas (PPGLs) represent the highest degree of heritability of any known tumor types in humans. Previous studies have characterized a dramatic difference between Chinese and European Caucasians with regards to both genetics and clinical features of PPGLs. The proportion of PGLs in Chinese patients was higher than in Caucasians, and the prevalence of metastasis was much lower in Chinese patients. Compared with Caucasians, there were more pathogenic variants (PVs) found in HRAS and FGFR1, but less in NF1 and SDHB. There were less germline PVs found in Chinese patients. Importantly, in Chinese patients, there was a large proportion of PGLs with PVs found in HRAS and FGFR1, mostly with epinephrine-producing capacity. This finding provided solid evidence that genetics (cluster 1 vs. 2), rather than location (PCC vs. PGL), determines the catecholamine-producing phenotype. Besides, the lower prevalence of SDHB partially explained lower occurrence of metastatic lesions in Chinese patients. These findings underscore the importance of considering ethnic differences when evaluating PPGLs and patient outcomes. Show less
no PDF DOI: 10.1016/j.beem.2024.101928
FGFR1

Single-Cell Multiomics Profiling Reveals Heterogeneity of Müller Cells in the Oxygen-Induced Retinopathy Model.

Xueming Yao, Ziqi Li, Yi Lei +9 more · 2024 · Investigative ophthalmology & visual science · added 2026-04-24
Retinal neovascularization poses heightened risks of vision loss and blindness. Despite its clinical significance, the molecular mechanisms underlying the pathogenesis of retinal neovascularization re Show more
Retinal neovascularization poses heightened risks of vision loss and blindness. Despite its clinical significance, the molecular mechanisms underlying the pathogenesis of retinal neovascularization remain elusive. This study utilized single-cell multiomics profiling in an oxygen-induced retinopathy (OIR) model to comprehensively investigate the intricate molecular landscape of retinal neovascularization. Mice were exposed to hyperoxia to induce the OIR model, and retinas were isolated for nucleus isolation. The cellular landscape of the single-nucleus suspensions was extensively characterized through single-cell multiomics sequencing. Single-cell data were integrated with genome-wide association study (GWAS) data to identify correlations between ocular cell types and diabetic retinopathy. Cell communication analysis among cells was conducted to unravel crucial ligand-receptor signals. Trajectory analysis and dynamic characterization of Müller cells were performed, followed by integration with human retinal data for pathway analysis. The multiomics dataset revealed six major ocular cell classes, with Müller cells/astrocytes showing significant associations with proliferative diabetic retinopathy (PDR). Cell communication analysis highlighted pathways that are associated with vascular proliferation and neurodevelopment, such as Vegfa-Vegfr2, Igf1-Igf1r, Nrxn3-Nlgn1, and Efna5-Epha4. Trajectory analysis identified a subset of Müller cells expressing genes linked to photoreceptor degeneration. Multiomics data integration further unveiled positively regulated genes in OIR Müller cells/astrocytes associated with axon development and neurotransmitter transmission. This study significantly advances our understanding of the intricate cellular and molecular mechanisms underlying retinal neovascularization, emphasizing the pivotal role of Müller cells. The identified pathways provide valuable insights into potential therapeutic targets for PDR, offering promising directions for further research and clinical interventions. Show less
no PDF DOI: 10.1167/iovs.65.13.8
NRXN3

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes.

David Teachey, Haley Newman, Shawn Lee +41 more · 2024 · Research square · added 2026-04-24
The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived Show more
The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including Show less
no PDF DOI: 10.21203/rs.3.rs-4858231/v1
MLLT10

Lp(a) and high-sensitivity C-reactive protein are predictive biomarkers for coronary heart disease in Chinese patients with type 2 diabetes mellitus.

Qinghan Meng, Haina Ma, Nannan Tian +12 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Type 2 diabetes (T2DM) is a significant risk factor for coronary heart disease (CHD). This study aimed to assess the variations in biomarkers associated with CHD in T2DM patients across different age Show more
Type 2 diabetes (T2DM) is a significant risk factor for coronary heart disease (CHD). This study aimed to assess the variations in biomarkers associated with CHD in T2DM patients across different age groups in the Han Chinese population. A strict selection process was employed, involving three groups: a control group (n = 300) with no medical history, a new-onset T2DM group (n = 300), and a new-onset T2DM + CHD group (n = 300). Participants in each group were further categorized based on age: Group 1 (<60 years), Group 2 (60-75 years), and Group 3 (>75 years). Fasting glucose, hemoglobin A1c (HbA1c), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), ApoB/ApoA1 ratio, lipoprotein(a) [Lp(a)], high-sensitivity C-reactive protein (hsCRP), and homocysteine (HCY) levels were analyzed in all groups. Both T2DM and T2DM + CHD groups exhibited elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, alongside decreased levels of HDL-C and ApoA1 in comparison to the control group. Notably, when comparing the T2DM to the T2DM + CHD groups, significant increases were noted in ApoB, Lp(a), and hsCRP levels in the T2DM + CHD group, whereas other biomarkers did not show significant differences. Across all age groups, the patterns remained consistent, with the T2DM and T2DM + CHD groups showing elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, and decreased levels of HDL-C and ApoA1 compared to their respective age-matched control groups. Furthermore, within each age category, significant increases in ApoB, Lp(a), and hsCRP were specifically observed with advancing age in the T2DM + CHD group, with Lp(a) and hsCRP levels showing particularly notable elevations, underscoring their potential as significant indicators of CHD risk in the T2DM population. Lp(a) and hsCRP may serve as valuable risk biomarkers for the development of CHD in T2DM patients. Understanding the variations in these biomarkers across different age groups can assist in risk assessment and the development of personalized management strategies for CHD in T2DM patients. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e40074
APOB

Acteoside relieves diabetic retinopathy through the inhibition of Müller cell reactive hyperplasia by regulating TXNIP and mediating Kir4.1 channels in a PI3K/Akt-dependent manner.

Xiaoting Xi, Xiaolei Liu, Qianbo Chen +5 more · 2024 · PloS one · PLOS · added 2026-04-24
Diabetic retinopathy (DR) is a severe microangiopathy of diabetes. Müller cells play an important role in the development of DR. Acteoside (ACT) has been reported to be effective in the treatment of D Show more
Diabetic retinopathy (DR) is a severe microangiopathy of diabetes. Müller cells play an important role in the development of DR. Acteoside (ACT) has been reported to be effective in the treatment of DR. In this study, we explored the molecular mechanism of ACT in the treatment of DR from the perspective of the reactive proliferation of Müller cells. The effect of ACT on DR was investigated via high-glucose (HG) treatment of Müller RMC-1 cells and an injection of streptozotocin (STZ) in constructed DR cells and animal models. The results showed that after ACT treatment, damage to the retinal structure in DR rats was alleviated, the number of hemangiomas was reduced, and the penetration of blood vessels was weakened. In addition, ACT treatment improved the hypertrophy and gliogenesis of Müller cells during DR, promoted the expression of Kir4.1 and activated the PI3K/Akt signaling pathway. ACT treatment inhibited the proliferation and migration of RMC-1 cells and promoted the expression of Kir4.1. TXNIP overexpression effectively reversed the inhibitory effect of ACT on the proliferation and migration of Müller cells and its induction of Kir4.1 expression. In addition, TXNIP knockdown effectively reversed the inhibitory effect of HG on the expression of p-PI3K and p-Akt, whereas TXNIP overexpression had the opposite effect, and treatment with the PI3K/AKT pathway inhibitor LY294002 effectively reversed the effect of TXNIP knockdown. Animal experiments also confirmed that the therapeutic effect of ACT on DR rats could be reversed by the overexpression of TXNIP or LY294002. In conclusion, ACT inhibits Müller cell reactive proliferation and alleviates diabetic retinopathy by regulating TXNIP and mediating the expression of Kir4.1 channels in a PI3K/Akt-dependent manner. Show less
no PDF DOI: 10.1371/journal.pone.0312565
RMC1

Haplotyping-based preimplantation genetic testing for inherited cardiovascular disease: a multidisciplinary approach.

Han Liu, Xiao Bao, Hao Shi +7 more · 2024 · Molecular genetics and genomics : MGG · Springer · added 2026-04-24
Given the high morbidity, mortality, and hereditary risk of cardiovascular diseases (CVDs), their prevention and control have garnered widespread attention and remain central to clinical research. Thi Show more
Given the high morbidity, mortality, and hereditary risk of cardiovascular diseases (CVDs), their prevention and control have garnered widespread attention and remain central to clinical research. This study aims to assess the feasibility and necessity of haplotyping-based preimplantation genetic testing for the prevention of inherited CVD. A total of 15 preimplantation genetic testing for monogenic defect (PGT-M) cycles were performed in 12 CVD families from January 2016 to July 2022. All couples were affected by CVDs and carried specific causative genes (including MYH7, MYBPC3, TTN, TPM1, LMNA, KCNQ1, FBN1 and LDLR). Among the 10 couples with adequate genetic pedigree information, we utilized the karyomapping assay to obtain single-nucleotide polymorphisms (SNPs) allele data. For the 2 couples who had no reference in their family, we used single sperm next-generation sequencing (NGS) to realize haplotype construction. Linkage analysis was performed to deduce embryonic genotype, and aneuploidy was screened simultaneously. Prenatal diagnostic testing via amniocentesis at 18-22 weeks of gestation was performed to verify the genetic conditions of transferred embryos. In total, 120 embryos were examined in this study, and the results showed that only 26.7% (32/120) were mutation-free and euploid-confirmed embryos. Additionally, for female CVD patients, we convened a multidisciplinary team (MDT) to advise the couple on their fertility concerns and management measures during pregnancy and delivery. With our cooperation, 10 couples successfully obtained healthy babies not carrying the pathogenic mutations. The results of prenatal diagnostics were consistent with the results of PGT-M. Our study demonstrates that PGT-M based on haplotype analysis is reliable and necessary for the prevention of inherited CVDs. It also highlights the important value of multidisciplinary collaboration for CVD prevention and treatment. Inherited cardiovascular diseases (CVDs) present as a huge challenge for modern medical and health systems. Hundreds of genetic variants have been reported to cause CVD and the number of people with the disease is enormous and still on the rise globally. Here we recruited twelve couples suffering from inherited CVD and provided them with effective pre-implantation genetic testing for monogenic defect (PGT-M) strategy to avoid the occurrence of genetic defects in the offspring. Specifically, after embryo biopsy, we utilized karyomapping assay (for 10 couples with a family history) or next-generation sequencing (NGS) (for 2 couples having no reference in their pedigree) to obtain single-nucleotide polymorphisms (SNPs) allele data and then performed linkage analysis to deduce embryonic genotype. A total of 120 embryos from 15 PGT-M cycles were examined and 12 variants in 8 genes linked to inherited CVD were identified. Thirty-two mutation-free and euploid confirmed embryos were considered suitable for embryo transfer. Besides, for female CVD patients, we called up a multidisciplinary team (MDT) advising the couple on their fertility concerns and management measures of pregnancy and delivery. With our cooperation, 10 couples successfully obtain healthy babies not carrying the pathogenic mutations. Our study further validated the reliability of PGT-M utilizing linkage analysis as a means to prevent the transmission of genetic disorders to future generations, and offered valuable insights for multidisciplinary clinical practices on CVD. Show less
📄 PDF DOI: 10.1007/s00438-024-02208-4
MYBPC3

The novel anthraquinone compound Kanglexin prevents endothelial-to-mesenchymal transition in atherosclerosis by activating FGFR1 and suppressing integrin β1/TGFβ signaling.

Yixiu Zhao, Zhiqi Wang, Jing Ren +11 more · 2024 · Frontiers of medicine · Springer · added 2026-04-24
Endothelial-mesenchymal transition (EndMT) disrupts vascular endothelial integrity and induces atherosclerosis. Active integrin β1 plays a pivotal role in promoting EndMT by facilitating TGFβ/Smad sig Show more
Endothelial-mesenchymal transition (EndMT) disrupts vascular endothelial integrity and induces atherosclerosis. Active integrin β1 plays a pivotal role in promoting EndMT by facilitating TGFβ/Smad signaling in endothelial cells. Here, we report a novel anthraquinone compound, Kanglexin (KLX), which prevented EndMT and atherosclerosis by activating MAP4K4 and suppressing integrin β1/TGFβ signaling. First, KLX effectively counteracted the EndMT phenotype and mitigated the dysregulation of endothelial and mesenchymal markers induced by TGFβ1. Second, KLX suppressed TGFβ/Smad signaling by inactivating integrin β1 and inhibiting the polymerization of TGFβR1/2. The underlying mechanism involved the activation of FGFR1 by KLX, resulting in the phosphorylation of MAP4K4 and Moesin, which led to integrin β1 inactivation by displacing Talin from its β-tail. Oral administration of KLX effectively stimulated endothelial FGFR1 and inhibited integrin β1, thereby preventing vascular EndMT and attenuating plaque formation and progression in the aorta of atherosclerotic Apoe Show less
no PDF DOI: 10.1007/s11684-024-1077-3
FGFR1

Molecular mechanisms of hypothalamic-pituitary-ovarian/thyroid axis regulating age at first egg in geese.

Zhiyu He, Qingyuan Ouyang, Qingliang Chen +7 more · 2024 · Poultry science · Elsevier · added 2026-04-24
Age at first egg (AFE) has consistently garnered interest as a crucial reproductive indicator within poultry production. Previous studies have elucidated the involvement of the hypothalamic-pituitary- Show more
Age at first egg (AFE) has consistently garnered interest as a crucial reproductive indicator within poultry production. Previous studies have elucidated the involvement of the hypothalamic-pituitary-ovarian (HPO) and hypothalamic-pituitary-thyroid (HPT) axes in regulating poultry sexual maturity. Concurrently, there was evidence suggesting a potential co-regulatory relationship between these 2 axes. However, as of now, no comprehensive exploration of the key pathways and genes responsible for the crosstalk between the HPO and HPT axes in the regulation of AFE has been reported. In this study, we conducted a comparative analysis of morphological differences and performed transcriptomic analysis on the hypothalamus, pituitary, thyroid, and ovarian stroma between normal laying group (NG) and abnormal laying group (AG). Morphological results showed that the thyroid index difference (D-) value (thyroid index D-value=right thyroid index-left thyroid index) was significantly (P < 0.05) lower in the NG than in the AG, while the ovarian index was significantly (P < 0.01) higher in the NG than in the AG. Furthermore, between NG and AG, we identified 99, 415, 167, and 1182 differentially expressed genes (DEGs) in the hypothalamus, pituitary, thyroid, and ovarian stroma, respectively. Gene ontology (GO) analysis highlighted that DEGs from 4 tissues were predominantly enriched in the "biological processes" category. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that 16, 14, 3, and 26 KEGG pathways were significantly enriched (P < 0.05) in the hypothalamus, pituitary, thyroid, and ovarian stroma. The MAPK signaling pathway emerged as the sole enriched pathway across all 4 tissues. Employing an integrated analysis of the protein-protein interaction (PPI) network and correlation analysis, we found GREB1 emerged as a pivotal component within the HPO axis to regulate estrogen-related signaling in the HPT axis, meanwhile, the HPT axis influenced ovarian development by regulating thyroid hormone-related signaling mainly through OPN5. Then, 10 potential candidate genes were identified, namely IGF1, JUN, ERBB4, KDR, PGF, FGFR1, GREB1, OPN5, DIO3, and THRB. These findings establish a foundation for elucidating the physiological and genetic mechanisms by which the HPO and HPT axes co-regulate goose AFE. Show less
📄 PDF DOI: 10.1016/j.psj.2024.103478
FGFR1

Circ-VPS13C enhances cisplatin resistance in ovarian cancer via modulating the miR-106b-5p/YWHAZ axis.

Hairong Yao, Dantong Liu, Fangyuan Gao +2 more · 2024 · Archives of medical science : AMS · added 2026-04-24
Ovarian cancer (OC) is the malignant tumor with the highest mortality among gynecological cancers. Chemotherapy resistance is a major obstacle to OC therapy. Circular RNAs (circRNAs) play crucial role Show more
Ovarian cancer (OC) is the malignant tumor with the highest mortality among gynecological cancers. Chemotherapy resistance is a major obstacle to OC therapy. Circular RNAs (circRNAs) play crucial roles in cancer development and chemoresistance. However, the role and potential mechanism of has-circ-001567 (circ-VPS13C) in chemoresistance of OC remain unknown. The levels of circ-VPS13C, miR-106b-5p and 14-3-3 zeta (YWHAZ) were detected by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot assay. Cell Counting Kit-8 (CCK-8) assay was used to assess cell viability and calculate the half inhibition concentration (IC Circ-VPS13C and YWHAZ were up-regulated, while miR-106b-5p was down-regulated in DDP-resistant OC tissues and cells. Knockdown of circ-VPS13C enhanced DDP sensitivity by repressing autophagy in DDP-resistant cells. Circ-VPS13C increased DDP resistance via sponging miR-106b-5p. Moreover, miR-106b-5p directly targeted YWHAZ. Up-regulation of YWHAZ alleviated the decrease in DDP resistance caused by circ-VPS13C depletion. In addition, circ-VPS13C silencing decreased DDP resistance Circ-VPS13C knockdown enhanced DDP sensitivity of OC through modulation of autophagy via the miR-106b-5p/YWHAZ axis, providing a new biomarker for improving the efficacy of OC chemotherapy. Show less
no PDF DOI: 10.5114/aoms/133038
VPS13C

Single-cell RNA-sequencing reveals a unique landscape of the tumor microenvironment in obesity-associated breast cancer.

Guanghui Zhao, Xiaodong Zhang, Liying Meng +5 more · 2024 · Oncogene · Nature · added 2026-04-24
As two diseases with rapidly increasing incidence, the molecular linkages between obesity and breast cancer (BC) are intriguing. Overall, obesity may be a negative prognostic factor for BC. Single-cel Show more
As two diseases with rapidly increasing incidence, the molecular linkages between obesity and breast cancer (BC) are intriguing. Overall, obesity may be a negative prognostic factor for BC. Single-cell RNA-sequencing (scRNA-seq) was performed on tumor tissues from 6 obese and non-obese BC patients. With 48,033 cells analyzed, we found heterogeneous tumor epithelium and microenvironment in these obese and lean BC patients. Interestingly, the obesity-associated epithelial cells exhibited specific expression signatures which linked tumor growth and hormone metabolism in BC. Notably, one population of obesity-specific macrophage up-regulated the nuclear receptor subfamily 1 group H member 3 (NR1H3), which acted a transcription factor and regulated FABP4 expression through its interaction with the DNA of SREBP1, and further increased the proliferation of tumor cells in BC. Using single-cell signatures, our study illustrate cell diversity and transcriptomic differences in tumors from obese and non-obese BC patients, and sheds light on potential molecular link between lipid metabolism and BC. Show less
no PDF DOI: 10.1038/s41388-024-03161-7
NR1H3

LXRα Promotes Abdominal Aortic Aneurysm Formation Through UHRF1 Epigenetic Modification of miR-26b-3p.

Xiao Guo, Jianmei Zhong, Yichao Zhao +6 more · 2024 · Circulation · added 2026-04-24
Abdominal aortic aneurysm (AAA) is a severe aortic disease without effective pharmacological approaches. The nuclear hormone receptor LXRα (liver X receptor α), encoded by the Through integrated analy Show more
Abdominal aortic aneurysm (AAA) is a severe aortic disease without effective pharmacological approaches. The nuclear hormone receptor LXRα (liver X receptor α), encoded by the Through integrated analyses of human and murine AAA gene expression microarray data sets, we identified Upregulated LXRα was observed in the aortas of patients with AAA and in angiotensin II- or CaCl Our study reveals a pivotal role of the LXRα/UHRF1/miR-26b-3p axis in AAA and provides potential biomarkers and therapeutic targets for AAA. Show less
no PDF DOI: 10.1161/CIRCULATIONAHA.123.065202
NR1H3

Bioinformatics analysis and identification of potential key genes and pathways in the pathogenesis of nonischemic cardiomyopathy.

Yan Jia, Rui-Ning Zhang, Yong-Jun Li +3 more · 2024 · Medicine · added 2026-04-24
Nonischemic cardiomyopathy (NICM) is a major cause of advanced heart failure, and the morbidity and mortality associated with NICM are serious medical problems. However, the etiology of NICM is comple Show more
Nonischemic cardiomyopathy (NICM) is a major cause of advanced heart failure, and the morbidity and mortality associated with NICM are serious medical problems. However, the etiology of NICM is complex and the related mechanisms involved in its pathogenesis remain unclear. The microarray datasets GSE1869 and GSE9128 retrieved from the Gene Expression Omnibus database were used to identify differentially expressed genes (DEGs) between NICM and normal samples. The co-expressed genes were identified using Venn diagrams. Kyoto Encyclopedia of Genes and Genomes pathway analyses and gene ontology enrichment were used to clarify biological functions and signaling pathways. Analysis of protein-protein interaction networks using Search Tool for the Retrieval of Interacting Genes/Proteins online to define the hub genes associated with NICM pathogenesis. A total of 297 DEGs were identified from GSE1869, 261 of which were upregulated genes and 36 were downregulated genes. A total of 360 DEGs were identified from GSE9128, 243 of which were upregulated genes and 117 were downregulated genes. In the 2 datasets, the screening identified 36 co-expressed DEGs. Kyoto Encyclopedia of Genes and Genomes pathway and gene ontology analysis showed that DEGs were mainly enriched in pantothenate and CoA biosynthesis, beta-alanine metabolism, kinetochore, G-protein beta/gamma-subunit complex, and other related pathways. The PPI network analysis revealed that DUSP6, EGR1, ZEB2, and XPO1 are the 4 hub genes of interest in the 2 datasets. Bioinformatics analysis of hub genes and key signaling pathways is an effective way to elucidate the mechanisms involved in the development of NICM. The results will facilitate further studies on the pathogenesis and therapeutic targets of NICM. Show less
📄 PDF DOI: 10.1097/MD.0000000000037898
DUSP6

Proteomics Analysis of Renal Cell Line Caki-2 with AFMID Overexpression and Potential Biomarker Discovery in Urine.

Jiameng Sun, Jinchun Chang, Zhengguang Guo +4 more · 2024 · Journal of proteome research · ACS Publications · added 2026-04-24
Aromatic caninurine formamase (AFMID) is an enzyme involved in the tryptophan pathway, metabolizing N-formylkynurenine to kynurenine. AFMID had been found significantly downregulated in clear cell ren Show more
Aromatic caninurine formamase (AFMID) is an enzyme involved in the tryptophan pathway, metabolizing N-formylkynurenine to kynurenine. AFMID had been found significantly downregulated in clear cell renal cell carcinoma (ccRCC) in both tissue and urine samples. Although ccRCC is characterized by a typical Warburg-like phenotype, mitochondrial dysfunction, and elevated fat deposition, it is unknown whether AFMID plays a role in tumorigenesis and the development of ccRCC. In the present study, AFMID overexpression had inhibitory effects for ccRCC cells, decreasing the rate of cell proliferation. Quantitative proteomics showed that AFMID overexpression altered cellular signaling pathways involved in cell growth and cellular metabolism pathways, including lipid metabolism and inositol phosphate metabolism. Further urine proteomic analysis indicated that cellular function dysfunction with AFMID overexpression could be reflected in the urine. The activity of predicted upregulators DDX58, TREX1, TGFB1, SMARCA4, and TNF in ccRCC cells and urine showed opposing change trends. Potential urinary biomarkers were tentatively discovered and further validated using an independent cohort. The protein panel of APOC3, UMOD, and CILP achieved an AUC value of 0.862 for the training cohort and 0.883 for the validation cohort. The present study is of significance in terms of highlighting various aspects of pathway changes associated with AFMID enzymes, discovering potential specific biomarkers for potential patient diagnosis, and therapeutic targeting. Show less
no PDF DOI: 10.1021/acs.jproteome.4c00431
APOC3

Redox-modulated SNX25 as a novel regulator of GPCR-G protein signaling from endosomes.

Yulong Zhang, Zhijun Yu, Mingwei Sun +10 more · 2024 · Redox biology · Elsevier · added 2026-04-24
GPCR-G protein signaling from endosomes plays a crucial role in various physiological and pathological processes. However, the mechanism by which endosomal G protein signaling is terminated remains la Show more
GPCR-G protein signaling from endosomes plays a crucial role in various physiological and pathological processes. However, the mechanism by which endosomal G protein signaling is terminated remains largely unknown. In this study, we aimed to investigate the regulatory mechanisms involved in terminating the signaling of Gα subunits from endosomes. Through structural analysis and cell-based assays, we have discovered that SNX25, a protein that targets endosomes via its PXA or PXC domain, interacts with regulator of G protein signaling (RGS) proteins (including RGS2, RGS4, RGS8, and RGS17) in a redox-regulated manner. The interaction between SNX25 and these RGS proteins enhances their GTPase-accelerating activity towards Gα Show less
no PDF DOI: 10.1016/j.redox.2024.103253
RGS17

Lumbrokinase (LK) ameliorates diabetic kidney disease renal fibrosis through regulating snail via m6A RNA methyltransferase 3.

Fan Yang, Xiaoyun Zhang, Jiaan Huang +5 more · 2024 · Scientific reports · Nature · added 2026-04-24
The present study was undertaken to investigate the therapeutic effect and underlying mechanisms of lumbrokinase (LK) on diabetic kidney disease (DKD). Kidney tissue samples from DKD patients and norm Show more
The present study was undertaken to investigate the therapeutic effect and underlying mechanisms of lumbrokinase (LK) on diabetic kidney disease (DKD). Kidney tissue samples from DKD patients and normal controls were collected from hospitals. The type 2 diabetic nephropathy model was induced in db/db mice. The mice were then randomly divided into a model group (DM group) and an LK group. db/m mice were used as the control group (Con group). After 12 weeks of treatment with LK (234 KU/kg/day), biochemical parameters were tested, and pathological changes in the kidney were observed under a light microscope. The epithelial-to-mesenchymal transition (EMT), mRNA m6A methylation proteins, and activated TGF-β1/Smad pathway components were assessed by western blot or immunofluorescence in DKD patients, model mice, and high glucose-stimulated HK-2 cells. We found that the m6A eraser METTL3 was expressed at low levels in DKD patients, model mice, and high glucose-stimulated HK-2 cells. METTL3 overexpression reversed the high glucose-induced activation of the TGF-β1/Smad pathway and EMT through snail in vitro. However, LK can restore the expression of the m6A-modifying enzyme METTL3 in vivo and in vitro, suppressed EMT, and alleviated renal interstitial fibrosis by downregulating snail. Overall, LK ameliorated renal fibrosis through the regulation of Snail via m6A RNA METTL3. Show less
no PDF DOI: 10.1038/s41598-024-80168-w
SNAI1

Joint Genomic and Transcriptomic Analysis Reveals Candidate Genes Associated with Plumage Color Traits in Matahu Ducks.

Pengwei Ren, Liu Yang, Muhammad Zahoor Khan +8 more · 2024 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
Plumage color is a key trait for identifying waterfowl breeds with significant economic importance. A white-feathered group has recently emerged within the native Matahu duck population, presenting an Show more
Plumage color is a key trait for identifying waterfowl breeds with significant economic importance. A white-feathered group has recently emerged within the native Matahu duck population, presenting an opportunity for breeding new lines. However, the genetic basis for this plumage variation is still unknown, necessitating further research. This study aims to identify the genetic mechanisms underlying the emergence of white-feathered individuals in the Matahu duck population through combined genome and transcriptome analysis, providing insights for selective breeding and the development of new white-feathered lines. In this study, a total of 1344 selected genes and 1406 significantly differentially expressed genes were identified through selection signal analysis and transcriptomic analysis, respectively. The functional enrichment of these genes revealed several key signaling pathways, including those related to cGMP-PKG, cAMP, PI3K-Akt, and MAPK. Furthermore, important candidate genes involved in melanin biosynthesis, such as Show less
📄 PDF DOI: 10.3390/ani14213111
GPRC5B

Mapping and functional characterization of structural variation in 1060 pig genomes.

Liu Yang, Hongwei Yin, Lijing Bai +20 more · 2024 · Genome biology · BioMed Central · added 2026-04-24
Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. We present a comprehensive SV catalog based on the whole-genome sequence of 106 Show more
Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence. We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies. This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution. Show less
📄 PDF DOI: 10.1186/s13059-024-03253-3
FADS3

The CK1ε/SIAH1 axis regulates AXIN1 stability in colorectal cancer cells.

Mengfang Yan, Zijie Su, Xiaoyi Pang +8 more · 2024 · Molecular oncology · Wiley · added 2026-04-24
Casein kinase 1ε (CK1ε) and axis inhibitor 1 (AXIN1) are crucial components of the β-catenin destruction complex in canonical Wnt signaling. CK1ε has been shown to interact with AXIN1, but its physiol Show more
Casein kinase 1ε (CK1ε) and axis inhibitor 1 (AXIN1) are crucial components of the β-catenin destruction complex in canonical Wnt signaling. CK1ε has been shown to interact with AXIN1, but its physiological function and role in tumorigenesis remain unknown. In this study, we found that CK1δ/ε inhibitors significantly enhanced AXIN1 protein level in colorectal cancer (CRC) cells through targeting CK1ε. Mechanistically, CK1ε promoted AXIN1 degradation by the ubiquitin-proteasome pathway by promoting the interaction of E3 ubiquitin-protein ligase SIAH1 with AXIN1. Genetic or pharmacological inhibition of CK1ε and knockdown of SIAH1 downregulated the expression of Wnt/β-catenin-dependent genes, suppressed the viability of CRC cells, and restrained tumorigenesis and progression of CRC in vitro and in vivo. In summary, our results demonstrate that CK1ε exerted its oncogenic role in CRC occurrence and progression by regulating the stability of AXIN1. These findings reveal a novel mechanism by which CK1ε regulates the Wnt/β-catenin signaling pathway and highlight the therapeutic potential of targeting the CK1ε/SIAH1 axis in CRC. Show less
📄 PDF DOI: 10.1002/1878-0261.13624
AXIN1