👤 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

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

LPL-RH suppresses bone loss in ovariectomised rat models.

Wen-Jie Chen, Xin-Liang Wang, Yu-Fan Wang +6 more · 2024 · BMC microbiology · BioMed Central · added 2026-04-24
Evidence has revealed that oestrogen deprivation-induced osteolysis is microbiota-dependent and can be treated by probiotics. However, the underlying mechanism require further investigation. This stud Show more
Evidence has revealed that oestrogen deprivation-induced osteolysis is microbiota-dependent and can be treated by probiotics. However, the underlying mechanism require further investigation. This study aims to provide additional evidence supporting the use of probiotics as an adjuvant treatment and to explore the pathophysiology of oestrogen-deprived osteolysis. Forty-five SD rats were randomly divided into five groups (n = 9). Rats from four groups were ovariectomised and treated with NS, calcium, probiotics, or calcium + probiotics, while one group underwent a sham operation and was treated with NS. The osteometabolic effects were evaluated, and the mechanistic role of the probiotic supplement was explored. Intragastric administration of Bifidobacterium animalis subsp. lactis LPL-RH (LPL-RH) markedly suppressed osteoclastic activation and bone calcium loss by downregulating TRAP enzymatic activity, the OPG/RANKL ratio, and the downstream signalling pathway RANKL/TRAF6/NF-κB/NFATc1/TRAP in ovariectomised SD rats. LPL-RH also reduced CD4 Collectively, LPL-RH suppressed osteoclastogenesis and osteolysis by modulating type 17 immunity and gut microbiome. Show less
📄 PDF DOI: 10.1186/s12866-024-03683-w
LPL

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

The occurrence and development of abdominal aortic aneurysm may be related to the energy metabolism disorder and local inflammation.

Jun Li, Yang Liu, Zhitao Wei +2 more · 2024 · Heliyon · Elsevier · added 2026-04-24
The cellular mechanism of the formation of abdominal aortic aneurysm (AAA) is very complicated. A series of sophisticated events eventually led to significant pathological changes in the anatomical st Show more
The cellular mechanism of the formation of abdominal aortic aneurysm (AAA) is very complicated. A series of sophisticated events eventually led to significant pathological changes in the anatomical structure and function of the arterial wall and they are still not clear nowadays. We pooled publicly available GEO datasets (GSE57691 and GSE47472) to get a comprehensive comparisons between normal tissues and AAA tissues to try to reveal molecular mechanism underlying the disease. Total 63 AAA samples and 18 normal tissue samples were compared and we fond that there were 784 significantly different gene (DEGs, threshold set as adjusted In the pathway enrichment, we found that FOXP3 related signaling pathways, inflammation-related cytokine signaling pathways, interleukin-8-CXCR1 related signaling pathways and VEGFA and FGFR1 related signal pathway were significantly enrichmented. In Weighted gene co-expression network analysis (WGCNA), we found that the key hub genes were significantly related to lipid catabolic metabolism, which further verified the possibility that AAA might relate to energy metabolism disorders. Based on the comprehensive analysis of previous high-throughput data and the validation of basic experiments, we found that the occurrence of AAA may be related to energy metabolism disorders and local inflammation. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e27912
FGFR1

Pharmacological and Biological Targeting of FGFR1 in Cancer.

Shuai Fan, Yuxin Chen, Wenyu Wang +7 more · 2024 · Current issues in molecular biology · MDPI · added 2026-04-24
FGFR1 is a key member of the fibroblast growth factor receptor family, mediating critical signaling pathways such as RAS-MAPK and PI3K-AKT. which are integral to regulating essential cellular processe Show more
FGFR1 is a key member of the fibroblast growth factor receptor family, mediating critical signaling pathways such as RAS-MAPK and PI3K-AKT. which are integral to regulating essential cellular processes, including proliferation, differentiation, and survival. Alterations in FGFR1 can lead to constitutive activation of signaling pathways that drive oncogenesis by promoting uncontrolled cell division, inhibiting apoptosis, and enhancing the metastatic potential of cancer cells. This article reviews the activation mechanisms and signaling pathways of FGFR1 and provides a detailed exposition of the types of FGFR1 aberration. Furthermore, we have compiled a comprehensive overview of current therapies targeting FGFR1 aberration in cancer, aiming to offer new perspectives for future cancer treatments by focusing on drugs that address specific FGFR1 alterations. Show less
📄 PDF DOI: 10.3390/cimb46110783
FGFR1

TRAF2 decrease promotes the TGF-β-mTORC1 signal in MAFLD-HCC through enhancing AXIN1-mediated Smad7 degradation.

Zhonglin Li, Jinfang Zhao, Ya Wu +9 more · 2024 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
According to recent research, metabolic-associated fatty liver disease (MAFLD) has emerged as an important underlying etiology of hepatocellular carcinoma (HCC). However, the molecular mechanism of MA Show more
According to recent research, metabolic-associated fatty liver disease (MAFLD) has emerged as an important underlying etiology of hepatocellular carcinoma (HCC). However, the molecular mechanism of MAFLD-HCC is still unclear. Tumor necrosis factor receptor-associated factor 2 (TRAF2) is the key molecule to mediate the signal of inflammatory NF-κB pathway. This study aims to investigate the potential dysregulation of TRAF2 and its biological function in MAFLD-HCC. Huh7 TRAF2 Show less
no PDF DOI: 10.1096/fj.202302307R
AXIN1

PP2 suppresses proliferation and migration of C6 Glioma and MDA-MB-231 cells by targeting both fibroblast growth factor receptor 1 and Src.

Yanyan Yang, Ningning Tang, Yan Liu +5 more · 2024 · Chemico-biological interactions · Elsevier · added 2026-04-24
Fibroblast growth factor (FGF) is involved in the progression of glioma, a most common type of brain tumor, and breast tumors. In this study, we aim to evaluate the effects of the inhibitor PP2 on cel Show more
Fibroblast growth factor (FGF) is involved in the progression of glioma, a most common type of brain tumor, and breast tumors. In this study, we aim to evaluate the effects of the inhibitor PP2 on cell proliferation and migration in glioma and breast tumor cells, and to characterize the molecular mechanisms involved in these processes. The inhibitory effect of PP2 on the tumorigenic potential of C6 glioma and MDA-MB-231 cells was examined by proliferation, migration, and invasion assays, and apoptotic analysis. The molecular mechanism behind the anti-glioma activity of PP2 was investigated by immunoblotting, immunoprecipitation, phosphoprotein assay, cellular thermal shift assay (CETSA), and molecular docking modeling. PP2 suppressed the proliferation and migration of C6 glioma and MDA-MB-231 cells via FGF2. Moreover, PP2 directly blocked the enzyme activity of FGF receptor 1 (FGFR1) and Src, subsequently affecting the nuclear factor-κB and activator protein-1 signaling pathways. CETSA analysis and the docking model indicated that the TK1 domains (Val 492 ad Glu 486) of FGFR2 could be binding sites of PP2. Collectively, therefore, our findings suggest that PP2 mediates antitumor effects by targeting both FGFR1 and Src and may have applications as a therapeutic inhibitor for the treatment of glioma. Show less
no PDF DOI: 10.1016/j.cbi.2024.111252
FGFR1

Tryptophan metabolic pathway plays a key role in the stress-induced emotional eating.

Ying Zhu, Lifeng Yin, Qing Liu +4 more · 2024 · Current research in food science · Elsevier · added 2026-04-24
Chronic stress disrupts the emotional and energetic balance, which may lead to abnormal behaviors such as binge eating. This overeating behavior alleviating the negative emotions is called emotional e Show more
Chronic stress disrupts the emotional and energetic balance, which may lead to abnormal behaviors such as binge eating. This overeating behavior alleviating the negative emotions is called emotional eating, which may exacerbate emotional instability and lead to obesity. It is a complex and multifaceted process that has not yet been fully understood. In this study, we constructed an animal model of chronic mild stress (CMS)-induced emotional eating. The emotional eating mice were treated with tryptophan for 21 days to reveal the key role of tryptophan. Furthermore, serum-targeted metabolomics, immunohistochemical staining, qPCR and ELISA were performed. The results showed that CMS led to the binge eating behavior, accompanied by the disturbed intestinal tryptophan-derived serotonin (5-hydroxytryptamine; 5-HT) metabolic pathways. Then we found that tryptophan supplementation improved depression and anxiety-like behaviors as well as abnormal eating behaviors. Tryptophan supplementation improved the abnormal expression of appetite regulators (e.g., AgRP, OX1R, MC4R), and tryptophan supplementation also increased the tryptophan hydroxylase 2 (tph2) and 5-HT receptors in the hypothalamus of CMS mice, which indicates that the 5-HT metabolic pathway influences feeding behavior. Show less
📄 PDF DOI: 10.1016/j.crfs.2024.100754
MC4R

Multi-trait analysis reveals risk loci for heart failure and the shared genetic etiology with blood lipids, blood pressure, and blood glucose.

Yanchen Zhu, Yahui Wang, Zhaorui Cui +3 more · 2024 · Cell reports · Elsevier · added 2026-04-24
Phenotypic associations have been reported between heart failure (HF) and blood lipids (BLs), blood pressure (BP), and blood glucose (BG). However, the shared genetic etiology underlying these associa Show more
Phenotypic associations have been reported between heart failure (HF) and blood lipids (BLs), blood pressure (BP), and blood glucose (BG). However, the shared genetic etiology underlying these associations remains incompletely understood. Conducting a large-scale multi-trait association study for HF with these traits, we discovered 143 previously unreported genomic risk loci for HF. Results showed that 46, 35, and 14 colocalized loci were shared by HF with BLs, BP, and BG, respectively. Notably, the loci shared by HF with these traits rarely overlapped, indicating distinct mechanisms. The combination of gene-mapping, gene-based, and transcriptome-wide association analyses prioritized noteworthy candidate genes (such as lipoprotein lipase [LPL], G protein-coupled receptor kinase 5 [GRK5], and troponin C1, slow skeletal and cardiac type [TNNC1]) for HF. Enrichment analysis revealed that HF exhibited comparable characteristics to cardiovascular traits and metabolic traits correlated to BLs, BP, and BG. Finally, we reported drug repurposing candidates and plasma protein targets for HF. These results provide biological insights into the pathogenesis of these comorbidities of HF. Show less
no PDF DOI: 10.1016/j.celrep.2024.114735
LPL

EphB1 causes retinal damage through inflammatory pathways in the retina and retinal Müller cells.

Li Liu, Youde Jiang, Mohamed Al-Shabrawey +3 more · 2024 · Molecular vision · added 2026-04-24
To examine whether increased ephrin type-B receptor 1 (EphB1) leads to inflammatory mediators in retinal Müller cells. Diabetic human and mouse retinal samples were examined for EphB1 protein levels. Show more
To examine whether increased ephrin type-B receptor 1 (EphB1) leads to inflammatory mediators in retinal Müller cells. Diabetic human and mouse retinal samples were examined for EphB1 protein levels. Rat Müller cells (rMC-1) were grown in culture and treated with EphB1 siRNA or ephrin B1-Fc to explore inflammatory mediators in cells grown in high glucose. An EphB1 overexpression adeno-associated virus (AAV) was used to increase EphB1 in Müller cells in vivo. Ischemia/reperfusion (I/R) was performed on mice treated with the EphB1 overexpression AAV to explore the actions of EphB1 on retinal neuronal changes in vivo. EphB1 protein levels were increased in diabetic human and mouse retinal samples. Knockdown of EphB1 reduced inflammatory mediator levels in Müller cells grown in high glucose. Ephrin B1-Fc increased inflammatory proteins in rMC-1 cells grown in normal and high glucose. Treatment of mice with I/R caused retinal thinning and loss of cell numbers in the ganglion cell layer. This was increased in mice exposed to I/R and treated with the EphB1 overexpressing AAVs. EphB1 is increased in the retinas of diabetic humans and mice and in high glucose-treated Müller cells. This increase leads to inflammatory proteins. EphB1 also enhanced retinal damage in response to I/R. Taken together, inhibition of EphB1 may offer a new therapeutic option for diabetic retinopathy. Show less
no PDF
RMC1

Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data.

Jingxian Tang, Hanfei Xu, Zihao Xin +6 more · 2024 · Human molecular genetics · Oxford University Press · added 2026-04-24
This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data. We conducted a meta-analysis to leverage information from a genome-wide associ Show more
This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data. We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction. We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21 genes in adipose tissue. Among these 21 genes, six genes, including FUS, STX4, CCNT2, FUBP1, NDUFS3, and RAPSN, were not reported to be BMI-associated in PubMed or GWAS Catalog. We also identified 11 genes that were significantly associated with BMI in both adipose and whole brain tissues. This study integrated three types of omics data and identified a group of genes that have not previously been reported to be associated with BMI. This strategy could provide new insights for future studies to identify molecular mechanisms contributing to BMI regulation. Show less
no PDF DOI: 10.1093/hmg/ddad212
RAPSN

Identification of four TTN variants in three families with fetal akinesia deformation sequence.

Lihong Fan, Haibo Li, Ying Xu +9 more · 2024 · BMC medical genomics · BioMed Central · added 2026-04-24
TTN is a complex gene with large genomic size and highly repetitive structure. Pathogenic variants in TTN have been reported to cause a range of skeletal muscle and cardiac disorders. Homozygous or co Show more
TTN is a complex gene with large genomic size and highly repetitive structure. Pathogenic variants in TTN have been reported to cause a range of skeletal muscle and cardiac disorders. Homozygous or compound heterozygous mutations tend to cause a wide spectrum of phenotypes with congenital or childhood onset. The onset and severity of the features were considered to be correlated with the types and location of the TTN variants. Whole-exome sequencing was performed on three unrelated families presenting with fetal akinesia deformation sequence (FADS), mainly characterized by reduced fetal movements and limb contractures. Sanger sequencing was performed to confirm the variants. RT-PCR analysis was performed. TTN c.38,876-2 A > C, a meta transcript-only variant, with a second pathogenic or likely pathogenic variant in trans, was observed in five affected fetuses from the three families. Sanger sequencing showed that all the fetal variants were inherited from the parents. RT-PCR analysis showed two kinds of abnormal splicing, including intron 199 extension and skipping of 8 bases. Here we report on three unrelated families presenting with FADS caused by four TTN variants. In addition, our study demonstrates that pathogenic meta transcript-only TTN variant can lead to defects which is recognizable prenatally in a recessive manner. Show less
📄 PDF DOI: 10.1186/s12920-024-01946-z
FADS1

Selection and Validation of Reference Genes in Sudan Grass (

Fangyan Wang, Peng Li, Qiuxu Liu +3 more · 2024 · Genes · MDPI · added 2026-04-24
Quantitative reverse transcription PCR (qRT-PCR) can screen applicable reference genes of species, and reference genes can be used to reduce experimental errors. Sudan grass (
📄 PDF DOI: 10.3390/genes15020210
ACP2

Using bioinformatics and artificial intelligence to map the cyclin-dependent kinase 4/6 inhibitor biomarker landscape in breast cancer.

Kim Wager, Yao Wang, Andrew Liew +5 more · 2024 · Future oncology (London, England) · Taylor & Francis · added 2026-04-24
A cyclin-dependent kinase 4/6 (CDK4/6) inhibitor combined with endocrine therapy is the standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative a Show more
A cyclin-dependent kinase 4/6 (CDK4/6) inhibitor combined with endocrine therapy is the standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer. However, not all patients respond to the treatment, resistance often occurs and efficacy outcomes from early breast cancer trials have been mixed. To identify biomarkers associated with CDK4/6 inhibitor response or resistance, we combined bioinformatic-database analyses, artificial intelligence-assisted literature review, and manual literature review (Embase and OVID Medline; search window: January 2012-October 2022) to compile data to comprehensively describe the CDK4/6 inhibitor biomarker landscape. Based on these results, and validation by external experts, we identified 15 biomarkers of clinical importance ( Show less
📄 PDF DOI: 10.1080/14796694.2024.2419352
FGFR1

Global RNA Interaction and Transcriptome Profiles Demonstrate the Potential Anti-Oncogenic Targets and Pathways of RBM6 in HeLa Cells.

Ping Peng, Qingqing Yin, Wei Sun +4 more · 2024 · Frontiers in bioscience (Landmark edition) · added 2026-04-24
The fate and functions of RNAs are coordinately regulated by RNA-binding proteins (RBPs), which are often dysregulated in various cancers. Known as a splicing regulator, RNA-binding motif protein 6 (R Show more
The fate and functions of RNAs are coordinately regulated by RNA-binding proteins (RBPs), which are often dysregulated in various cancers. Known as a splicing regulator, RNA-binding motif protein 6 (RBM6) harbors tumor-suppressor activity in many cancers; however, there is a lack of research on the molecular targets and regulatory mechanisms of RBM6. In this study, we constructed an Using The Cancer Genome Atlas dataset, we found that higher expression of In summary, our study highlights the important role of RBM6, as well as the downstream targets and regulated pathways, suggesting the potential regulatory mechanisms of RBM6 in the development of cancer. Show less
no PDF DOI: 10.31083/j.fbl2909330
RBM6

ANGPTL4-mediated microglial lipid droplet accumulation: Bridging Alzheimer's disease and obesity.

Nan Li, Xiaojun Wang, Ruilang Lin +8 more · 2024 · Neurobiology of disease · Elsevier · added 2026-04-24
Increasing evidence suggests that metabolic disorders such as obesity are implicated in the development of Alzheimer's disease (AD). The pathological buildup of lipids in microglia is regarded as a ke Show more
Increasing evidence suggests that metabolic disorders such as obesity are implicated in the development of Alzheimer's disease (AD). The pathological buildup of lipids in microglia is regarded as a key indicator in brain aging and the progression of AD, yet the mechanisms behind this process remain uncertain. The adipokine ANGPTL4 is strongly associated with obesity and is thought to play a role in the advancement of neurodegenerative diseases. This study utilized RNA sequencing to identify differential expression in lipid-accumulating BV2 microglia and investigated the potential mechanism through ANGPTL4 overexpression in BV2. Subsequently, animal models and clinical data were employed to further explore alterations in circulating ANGPTL4 levels in AD. RNA sequencing results indicated a correlation between ANGPTL4 and microglial lipid accumulation. The overexpression of ANGPTL4 in microglia resulted in increased secretion of inflammatory factors, elevated oxidative stress levels, and diminished antiviral capacity. Furthermore, when simulating the coexistence of AD and obesity through combined treatment with Amyloid-Beta 1-42 peptide (Aβ) and Free Fatty Acids (FFA) in vitro, we observed a notable upregulation of ANGPTL4 expression, highlighting its potential role in the interplay between AD and obesity. In vivo experiments, we also observed a significant increase in ANGPTL4 expression in the hippocampus and plasma of APP/PS1 mice compared to wild-type controls. This was accompanied by heightened microglial activation and reduced expression of longevity-related genes in the hippocampus. Clinical data from the UK Biobank indicated that plasma ANGPTL4 levels are elevated in patients with AD when compared to healthy controls. Moreover, significantly higher ANGPTL4 levels were observed in obese AD patients relative to their non-obese counterparts. Our findings suggest that ANGPTL4-mediated microglial aging may serve as a crucial link between AD and obesity, proposing ANGPTL4 as a potential biomarker for AD. Show less
no PDF DOI: 10.1016/j.nbd.2024.106741
ANGPTL4

IL27 and IL1RN are causally associated with acute pancreatitis: a Mendelian randomization study.

Qingxu Jing, Xuxu Liu, Zhenyi Lv +1 more · 2024 · Aging · Impact Journals · added 2026-04-24
The interleukin (IL) plays a role in the development of acute pancreatitis (AP). However, the specific IL in AP has not been fully revealed. Therefore, the association between prospective IL and AP wa Show more
The interleukin (IL) plays a role in the development of acute pancreatitis (AP). However, the specific IL in AP has not been fully revealed. Therefore, the association between prospective IL and AP was studied via Mendelian randomization (MR). The HUGO Gene nomenclature committee (HGNC) database provided 47 interleukin related genes (ILRGs). ILRGs and differentially expressed genes (DEGs) from GSE194331 were overlapped to create differently expressed ILRGs (DE-ILRGs). The integrative epidemiology unit (IEU) open genome-wide association study (GWAS) database provided exposure and outcome datasets. Univariate MR (UVMR) analysis using MR-Egger, IVW, simple mode, and weighted mode was done. UVMR results were verified using sensitivity analysis. Drug prediction, MVMR analysis, and PPI network development were also performed. Six DE-ILRGs were obtained. IL27 and IL1RN were substantially causally linked with AP by UVMR analysis (OR = 0.926, P < 0.001 and OR = 1.031, P = 0.023). Our sensitivity analysis showed the dependability of our results. Direct effect of IL27 was suggested by MVMR analysis. In the cytokine receptor binding pathway, IL27 and IL1RN interacted with IL36G and IL1R2. TAE-684, ARQ-680, and 12 other IL1RN and 14 IL27 medications were predicted. IL1RN was identified as a risk factor for acute pancreatitis (AP), but IL27 was found to be a protective factor for AP. Show less
📄 PDF DOI: 10.18632/aging.205825
IL27

Genome-wide association study identifies novel susceptible loci and evaluation of polygenic risk score for chronic obstructive pulmonary disease in a Taiwanese population.

Wei-De Lin, Wen-Ling Liao, Wei-Cheng Chen +3 more · 2024 · BMC genomics · BioMed Central · added 2026-04-24
Chronic Obstructive Pulmonary Disease (COPD) describes a group of progressive lung diseases causing breathing difficulties. While COPD development typically involves a complex interplay between geneti Show more
Chronic Obstructive Pulmonary Disease (COPD) describes a group of progressive lung diseases causing breathing difficulties. While COPD development typically involves a complex interplay between genetic and environmental factors, genetics play a role in disease susceptibility. This study used genome-wide association studies (GWAS) and polygenic risk score (PRS) to elucidate the genetic basis for COPD in Taiwanese patients. GWAS was performed on a Taiwanese COPD case-control cohort with a sample size of 5,442 cases and 17,681 controls. Additionally, the PRS was calculated and assessed in our target groups. GWAS results indicate that although there were no single nucleotide polymorphisms (SNPs) of genome-wide significance, prominent COPD susceptibility loci on or nearby genes such as WWTR1, EXT1, INTU, MAP3K7CL, MAMDC2, BZW1/CLK1, LINC01197, LINC01894, and CFAP95 (C9orf135) were identified, which had not been reported in previous studies. Thirteen susceptibility loci, such as CHRNA4, AFAP1, and DTWD1, previously reported in other populations were replicated and confirmed to be associated with COPD in Taiwanese populations. The PRS was determined in the target groups using the summary statistics from our base group, yielding an effective association with COPD (odds ratio [OR] 1.09, 95% confidence interval [CI] 1.02-1.17, p = 0.011). Furthermore, replication a previous lung function trait PRS model in our target group, showed a significant association of COPD susceptibility with PRS of Forced Expiratory Volume in one second (FEV Novel COPD-related genes were identified in the studied Taiwanese population. The PRS model, based on COPD or lung function traits, enables disease risk estimation and enhances prediction before suffering. These results offer new perspectives on the genetics of COPD and serve as a basis for future research. Show less
📄 PDF DOI: 10.1186/s12864-024-10526-5
EXT1

(Pro)renin receptor mediates tubular epithelial cell pyroptosis in diabetic kidney disease via DPP4-JNK pathway.

Shiying Xie, Shicong Song, Sirui Liu +4 more · 2024 · Journal of translational medicine · BioMed Central · added 2026-04-24
(Pro)renin receptor (PRR) is highly expressed in renal tubules, which is involved in physiological and pathological processes. However, the role of PRR, expressed in renal tubular epithelial cells, in Show more
(Pro)renin receptor (PRR) is highly expressed in renal tubules, which is involved in physiological and pathological processes. However, the role of PRR, expressed in renal tubular epithelial cells, in diabetic kidney disease (DKD) remain largely unknown. In this study, kidney biopsies, urine samples, and public RNA-seq data from DKD patients were used to assess PRR expression and cell pyroptosis in tubular epithelial cells. The regulation of tubular epithelial cell pyroptosis by PRR was investigated by in situ renal injection of adeno-associated virus9 (AAV9)-shRNA into db/db mice, and knockdown or overexpression of PRR in HK-2 cells. To reveal the underlined mechanism, the interaction of PRR with potential binding proteins was explored by using BioGrid database. Furthermore, the direct binding of PRR to dipeptidyl peptidase 4 (DPP4), a pleiotropic serine peptidase which increases blood glucose by degrading incretins under diabetic conditions, was confirmed by co-immunoprecipitation assay and immunostaining. Higher expression of PRR was found in renal tubules and positively correlated with kidney injuries of DKD patients, in parallel with tubular epithelial cells pyroptosis. Knockdown of PRR in kidneys significantly blunted db/db mice to kidney injury by alleviating renal tubular epithelial cells pyroptosis and the resultant interstitial inflammation. Moreover, silencing of PRR blocked high glucose-induced HK-2 pyroptosis, whereas overexpression of PRR enhanced pyroptotic cell death of HK-2 cells. Mechanistically, PRR selectively bound to cysteine-enrich region of C-terminal of DPP4 and augmented the protein abundance of DPP4, leading to the downstream activation of JNK signaling and suppression of SIRT3 signaling and FGFR1 signaling, and then subsequently mediated pyroptotic cell death. This study identified the significant role of PRR in the pathogenesis of DKD; specifically, PRR promoted tubular epithelial cell pyroptosis via DPP4 mediated signaling, highlighting that PRR could be a promising therapeutic target in DKD. Show less
📄 PDF DOI: 10.1186/s12967-023-04846-5
FGFR1

Genetically Proxied Therapeutic Effect of Lipid-Lowering Drugs Use, Breast Cancer, and Endometrial Cancer's Risk: A Drug Target-Based Mendelian Randomization Study.

Chunxiao Dang, Xiaofeng Wang, Pengfei Liu +2 more · 2024 · International journal of women's health · added 2026-04-24
Observational studies have investigated the association between lipid-lowering drugs and breast cancer (BC) and endometrial cancer (EC), but some controversy remains. This paper aims to explore the ca Show more
Observational studies have investigated the association between lipid-lowering drugs and breast cancer (BC) and endometrial cancer (EC), but some controversy remains. This paper aims to explore the causal relationship between genetic proxies for lipid-lowering drugs and breast and endometrial cancers using drug-target Mendelian randomization (MR). Analyses were mainly performed using inverse variance weighted (IVW), heterogeneity and horizontal pleiotropy tests, and sensitivity analysis to assess the robustness of the results and causal relationship. HMGCR, APOB, and NPC1L1 increased the risk of breast cancer, LPL increased the risk of endometrial cancer, and APOC3 decreased the risk of breast and endometrial cancer. No heterogeneity or horizontal pleiotropy was detected, and nor was there any evidence of an association between other lipid-lowering drugs and breast and endometrial cancer. Our study demonstrated genetically that HMGCR inhibition, APOB inhibition, and NPC1L1 inhibition decrease the risk of breast cancer, LPL agonist increases the risk of endometrial cancer, and APOC3 inhibition decreases the risk of breast cancer and endometrial cancer, and these findings provide genetic insights into the potential risks of lipid-lowering drug therapy. Show less
📄 PDF DOI: 10.2147/IJWH.S468733
APOB

Cancer-associated fibroblasts-secreted exosomal miR-92a-3p promotes tumor growth and stemness in hepatocellular carcinoma through activation of Wnt/β-catenin signaling pathway by suppressing AXIN1.

Zenong Su, Chao Lu, Feifei Zhang +12 more · 2024 · Journal of cellular physiology · Wiley · added 2026-04-24
Cancer-associated fibroblasts (CAFs) are a major cellular component in the tumor microenvironment and have been shown to exhibit protumorigenic effects in hepatocellular carcinoma (HCC). This study ai Show more
Cancer-associated fibroblasts (CAFs) are a major cellular component in the tumor microenvironment and have been shown to exhibit protumorigenic effects in hepatocellular carcinoma (HCC). This study aimed to delve into the mechanisms underlying the tumor-promoting effects of CAFs in HCC. Small RNA sequencing was conducted to screen differential expressed microRNAs in exosomes derived from CAFs and normal fibroblasts (NFs). The miR-92a-3p expression was then measured using reverse transcriptase quantitative real-time PCR in CAFs, NFs, CAFs-derived exosomes (CAFs-Exo), and NF-derived exosomes (NFs-Exo). Compared to NFs or NF-Exo, CAFs and CAFs-Exo significantly promoted HCC cell proliferation, migration, and stemness. Additionally, compared to NFs or NF-Exo, miR-92a-3p level was notably higher in CAFs and CAFs-Exo, respectively. Exosomal miR-92a-3p was found to enhance HCC cell proliferation, migration, and stemness. Meanwhile, AXIN1 was targeted by miR-92a-3p. Exosomal miR-92a-3p could activate β-catenin/CD44 signaling in HCC cells by inhibiting AXIN1 messenger RNA. Furthermore, in vivo studies verified that exosomal miR-92a-3p notably promoted tumor growth and stemness through targeting AXIN1/β-catenin axis. Collectively, CAFs secreted exosomal miR-92a-3p was capable of promoting growth and stemness in HCC through activation of Wnt/β-catenin signaling pathway by suppressing AXIN1. Therefore, targeting CAFs-derived miR-92a-3p may be a potential strategy for treating HCC. Show less
no PDF DOI: 10.1002/jcp.31344
AXIN1

Ocular Mucous Membrane Pemphigoid Demonstrates a Distinct Autoantibody Profile from Those of Other Autoimmune Blistering Diseases: A Preliminary Study.

Yingzi Liu, Lei Bao, Dharm Sodha +8 more · 2024 · Antibodies (Basel, Switzerland) · MDPI · added 2026-04-24
no PDF DOI: 10.3390/antib13040091
SEC16B

Recurrent Cerebral Venous Sinus Thrombosis Occurred in an Acute Lymphoblastic Leukemia Child with Mutated Lipoprotein Lipase Gene during Asparaginase Therapy.

Shiyuan Wang, Jun Li, Ying Li +7 more · 2024 · Global medical genetics · added 2026-04-24
Cerebral venous sinus thrombosis (CVST) and hyperlipidemia are severe complications of L-Asparaginase (L-Asp) during the treatment of B-cell acute lymphoblastic leukemia (B-ALL). Herein, we reported a Show more
Cerebral venous sinus thrombosis (CVST) and hyperlipidemia are severe complications of L-Asparaginase (L-Asp) during the treatment of B-cell acute lymphoblastic leukemia (B-ALL). Herein, we reported a 9-year-old B-ALL boy who underwent abnormal hypertriglyceridemia and CVST presenting as seizures and disturbance of consciousness twice during the induction therapy. Fortunately, he survived treatment with anticoagulant and lipid-lowering therapy. No thrombophilia-related gene mutation was detected, but a heterozygous mutation in lipoprotein lipase (LPL) gene was identified. His neurological symptoms were managed with short-term anticoagulant therapy and long-term lipid-lowering therapy. This case illustrated the manifestation and potential pathogenesis of CVST and highlighted the essentiality of screening baseline lipid profile and dyslipidemia- and thrombophilia-related gene mutation. Show less
📄 PDF DOI: 10.1055/s-0044-1788043
LPL

Stable Long-Persistent Luminescence from Self-Activated CaSb

Yanbing Han, Qingqing Mo, Zhuangzhuang Ma +8 more · 2024 · Nano letters · ACS Publications · added 2026-04-24
Long-persistent luminescence (LPL) materials have attracted intensive attention due to their fascinating emission after excitation. However, current LPL materials typically depend on external doping t Show more
Long-persistent luminescence (LPL) materials have attracted intensive attention due to their fascinating emission after excitation. However, current LPL materials typically depend on external doping to introduce traps or emitting centers, resulting in a complex synthesis and controllability. For the first time, we develop another category of undoped LPL materials based on antimonate CaSb Show less
no PDF DOI: 10.1021/acs.nanolett.4c04471
LPL

[Correlation of lipid metabolism-related single nucleotide polymorphisms with abnormal semen quality in men].

Xuan Liu, Yuan-Jing Li, Yue-Jia Li +4 more · 2024 · Zhonghua nan ke xue = National journal of andrology · added 2026-04-24
To explore the potential impact of lipid metabolism-related single nucleotide polymorphisms (SNP) on semen quality in men. We selected 284 semen samples from Xingtai Infertility Hospital and Hebei Hum Show more
To explore the potential impact of lipid metabolism-related single nucleotide polymorphisms (SNP) on semen quality in men. We selected 284 semen samples from Xingtai Infertility Hospital and Hebei Human Sperm Bank collected between February and October 2023, 33 from oligozoospermia (OS), 97 from asthenozoospermia (AS) and 54 from oligoasthenozoospermia (OAS) patients and the other 100 from normal men. We performed computer-assisted semen analysis (CASA) of the samples, extracted blood DNA and, using the MassARRAY System, genotyped the target genes, determined the genotypes of 13 SNPs and compared their distribution, their correlation with BMI and semen quality in different groups. The mutant homozygous (TT) genotype of the FADS2 rs2727270 gene seemed to be a risk factor for AS (OR = 4.420, P= 0.047), while the APOA2 rs5082-A allele and MC4R rs17782313 heterozygous (TC) genotype important protective factors for OS (OR = 0.422 and 0.389; P= 0.045 and 0.043, respectively). A significantly higher sperm concentration was found associated with the MC4R rs17782313 heterozygous (TC) genotype than with the homozygous (CC) genotype. Stratification analysis showed that the protective effect of the TC genotype was decreased with increased BMI and remained with the interaction of the rs5082 and rs17782313 genotypes. FADS2 rs2727270, APOA2 rs5082 and MC4R rs17782313 were significantly correlated with the risk of abnormal semen parameters. Show less
no PDF
MC4R

Metal ion stimulation-related gene signatures correlate with clinical and immunologic characteristics of glioma.

Chengzhi Jiang, Binbin Zhang, Wenjuan Jiang +4 more · 2024 · Heliyon · Elsevier · added 2026-04-24
Environmental factors serve as one of the important pathogenic factors for gliomas. Yet people focus only on the effect of electromagnetic radiation on its pathogenicity, while metals in the environme Show more
Environmental factors serve as one of the important pathogenic factors for gliomas. Yet people focus only on the effect of electromagnetic radiation on its pathogenicity, while metals in the environment are neglected. This study aimed to investigate the relationship between metal ion stimulation and the clinical characteristics and immune status of GM patients. Firstly, mRNA expression profiles of GM patients and normal subjects were obtained from Chinese GM Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) to identify differentially expressed metal ion stimulation-related genes(DEMISGs). Secondly, two molecular subtypes were identified and validated based on these DEMISGs using consensus clustering. Diagnostic and prognostic models for GM were constructed after screening these features based on machine learning. Finally, supervised classification and unsupervised clustering were combined to classify and predict the grade of GM based on SHAP values. GM patients are divided into two different response states to metal ion stimulation, M1 and M2, which are related to the grade and IDH status of the GM. Six genes with diagnostic value were obtained: SLC30A3, CRHBP, SYT13, DLG2, CDK1, and WNT5A. The AUC in the external validation set was higher than 0.90. The SHAP value improves the performance of classification prediction. The gene features associated with metal ion stimulation are related to the clinical and immune characteristics of transgenic patients. XGboost/LightGBM Kmeans has a higher classification prediction accuracy in predicting glioma grades compared to using purely supervised classification techniques. Show less
📄 PDF DOI: 10.1016/j.heliyon.2024.e27189
DLG2

Deubiquitinating enzyme OTUD4 regulates metastasis in triple-negative breast cancer by stabilizing Snail1.

Xiuqing Ma, Rui Wan, Yalei Wen +3 more · 2024 · Experimental cell research · Elsevier · added 2026-04-24
Metastasis is the primary cause of cancer-related deaths and remains poorly understood. Deubiquitinase OTU domain containing 4 (OTUD4) has been reported to regulate antiviral immune responses and resi Show more
Metastasis is the primary cause of cancer-related deaths and remains poorly understood. Deubiquitinase OTU domain containing 4 (OTUD4) has been reported to regulate antiviral immune responses and resistance to radio- or chemo-therapies in certain cancers. However, the role of OTUD4 in cancer metastasis remain unknown. Here, we demonstrate that the depletion of OTUD4 in triple-negative breast cancer (TNBC) cells markedly suppress cell clonogenic ability, migration, invasion and cancer stem cell population in vitro as well as metastasis in vivo. Mechanistically, the tumor promoting function of OTUD4 is mainly mediated by deuiquitinating and stabilizing Snail1, one key transcriptional factor in the epithelial-mesenchymal transition. The inhibitory effect of targeting OTUD4 could be largely reversed by the reconstitution of Snail1 in OTUD4-deficient cells. Overall, our study establishes the OTUD4-Snail1 axis as an important regulatory mechanism of breast cancer metastasis and provides a rationale for potential therapeutic interventions in the treatment of TNBC. Show less
no PDF DOI: 10.1016/j.yexcr.2023.113864
SNAI1

The PML1-WDR5 axis regulates H3K4me3 marks and promotes stemness of estrogen receptor-positive breast cancer.

Chun-Peng Pai, Han Wang, Darcie D Seachrist +7 more · 2024 · Cell death and differentiation · Nature · added 2026-04-24
The alternative splicing of PML precursor mRNA gives rise to various PML isoforms, yet their expression profile in breast cancer cells remains uncharted. We discovered that PML1 is the most abundant i Show more
The alternative splicing of PML precursor mRNA gives rise to various PML isoforms, yet their expression profile in breast cancer cells remains uncharted. We discovered that PML1 is the most abundant isoform in all breast cancer subtypes, and its expression is associated with unfavorable prognosis in estrogen receptor-positive (ER+) breast cancers. PML depletion reduces cell proliferation, invasion, and stemness, while heterologous PML1 expression augments these processes and fuels tumor growth and resistance to fulvestrant, an FDA-approved drug for ER+ breast cancer, in a mouse model. Moreover, PML1, rather than the well-known tumor suppressor isoform PML4, rescues the proliferation of PML knockdown cells. ChIP-seq analysis reveals significant overlap between PML-, ER-, and Myc-bound promoters, suggesting their coordinated regulation of target gene expression, including genes involved in breast cancer stem cells (BCSCs), such as JAG1, KLF4, YAP1, SNAI1, and MYC. Loss of PML reduces BCSC-related gene expression, and exogenous PML1 expression elevates their expression. Consistently, PML1 restores the association of PML with these promoters in PML-depleted cells. We identified a novel association between PML1 and WDR5, a key component of H3K4 methyltransferase (HMTs) complexes that catalyze H3K4me1 and H3K4me3. ChIP-seq analyses showed that the loss of PML1 reduces H3K4me3 in numerous loci, including BCSC-associated gene promoters. Additionally, PML1, not PML4, re-establishes the H3K4me3 mark on these promoters in PML-depleted cells. Significantly, PML1 is essential for recruiting WDR5, MLL1, and MLL2 to these gene promoters. Inactivating WDR5 by knockdown or inhibitors phenocopies the effects of PML1 loss, reducing BCSC-related gene expression and tumorsphere formation and enhancing fulvestrant's anticancer activity. Our findings challenge the conventional understanding of PML as a tumor suppressor, redefine its role as a promoter of tumor growth in breast cancer, and offer new insights into the unique roles of PML isoforms in breast cancer. Show less
no PDF DOI: 10.1038/s41418-024-01294-6
SNAI1

Histone demethylase PHF8 promotes prostate cancer metastasis via the E2F1-SNAI1 axis.

Ze Wang, Peng Tang, Haiyang Xiao +16 more · 2024 · The Journal of pathology · Wiley · added 2026-04-24
Metastasis is the primary culprit behind cancer-related fatalities in multiple cancer types, including prostate cancer. Despite great advances, the precise mechanisms underlying prostate cancer metast Show more
Metastasis is the primary culprit behind cancer-related fatalities in multiple cancer types, including prostate cancer. Despite great advances, the precise mechanisms underlying prostate cancer metastasis are far from complete. By using a transgenic mouse prostate cancer model (TRAMP) with and without Phf8 knockout, we have identified a crucial role of PHF8 in prostate cancer metastasis. By complexing with E2F1, PHF8 transcriptionally upregulates SNAI1 in a demethylation-dependent manner. The upregulated SNAI1 subsequently enhances epithelial-to-mesenchymal transition (EMT) and metastasis. Given the role of the abnormally activated PHF8/E2F1-SNAI1 axis in prostate cancer metastasis and poor prognosis, the levels of PHF8 or the activity of this axis could serve as biomarkers for prostate cancer metastasis. Moreover, targeting this axis could become a potential therapeutic strategy for prostate cancer treatment. © 2024 The Pathological Society of Great Britain and Ireland. Show less
no PDF DOI: 10.1002/path.6325
SNAI1

Investigating the shared genetic architecture between attention-deficit/hyperactivity disorder and risk taking behavior: A large-scale genomewide cross-trait analysis.

Yanjing Chen, Ping Liu, Sijie Yi +3 more · 2024 · Journal of affective disorders · Elsevier · added 2026-04-24
This study aims to explore the genetic architecture shared between Attention-Deficit/Hyperactivity Disorder (ADHD) and risk behavior. Based on the latest large-scale Genome-wide association studies (G Show more
This study aims to explore the genetic architecture shared between Attention-Deficit/Hyperactivity Disorder (ADHD) and risk behavior. Based on the latest large-scale Genome-wide association studies (GWAS), we firstly employed Linkage disequilibrium score regression (LDSC) and Local Analysis of Variant Association (LAVA) to investigate the genetic correlation between risk behavior and ADHD. Then, we conducted cross-trait analysis to identified the Pleiotropic loci. Finally, bidirectional Mendelian randomization analysis (MR) was applied to examine the causal relationship. We found a significant positive genetic correlation between ADHD and risk-taking behavior (rg = 0.351, p = 6.50E-37). The cross-trait meta-analysis identified 27 significant SNPs shared between ADHD and risk behavior. The most significant locus, located near the CADM2 gene on chromosome 3, had been identified associated with this two trait (pADHD = 3.07E-05 and prisk-taking behavior = 2.47E-30). The same situation can also be observed near the FOXP2 gene on chromosome 7 (rs8180817, pmeta = 5.72E-21). We found CCDC171 gene and other genes played a significant role in ADHD and risk behavior in mRNA level. Bidirectional MR analysis found a causal relationship between them. The majority of our data sources were of European origin, which may limit the generalizability of our findings to other ethnic populations. This article reveals in depth the shared genetic structure between ADHD and risk-taking behavior, finding a significant positive genetic correlation between ADHD and risk-taking behavior. Providing insights for the future treatment and management of these two traits. Show less
no PDF DOI: 10.1016/j.jad.2024.03.107
CCDC171