👤 Didi Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, 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

CPS1-promoted the progression of lung adenocarcinoma via suppressing ammonia induced the activation of ROS/AMPK/P53/LKB1 signaling pathway.

Yanchao Luan, Liru Liu, Jiakun Liu +2 more · 2025 · Scientific reports · Nature · added 2026-04-24
This study aims to explore how CPS1 influences the progression of lung adenocarcinoma by affecting the ammonia-induced ROS/AMPK/P53/LKB1 signaling pathway. Bioinformatics analysis was conducted to ide Show more
This study aims to explore how CPS1 influences the progression of lung adenocarcinoma by affecting the ammonia-induced ROS/AMPK/P53/LKB1 signaling pathway. Bioinformatics analysis was conducted to identify differential gene expression in lung adenocarcinoma patients. A549 cells were infected with control (NC) or CPS1 knockdown (CPS1-KD) lentivirus. Cells were treated with or without AMPK agonists, AMPK inhibitors, P53 agonists, or P53 inhibitors, followed by Western blot analysis of CPS1, NOX2, NOX4, p-AMPK, p-P53, and LKB1 protein levels. The content of MDA and SOD was measured, and the expression of AMPK, caspase-3 and P53 in tumor cells was detected through immunofluorescence. Apoptosis-related protein expression and tumor cell apoptosis were assessed using Western blot and flow cytometry. Tumor cell proliferation was evaluated using CCK-8 assays and colony formation experiments. Tumor size was measured in xenograft models using nude mice. Bioinformatics analysis indicated that LKB1 positively regulates AMPK activity. CPS1 knockdown results in increased ammonia levels, with upregulated expression of NOX2, NOX4, p-AMPK, p-P53, and LKB1 in tumor cells. Elevated P53 levels, along with significant increases in Bax, Caspase-8,and Caspase-12 expression, were observed, promoting apoptosis and inhibiting tumor cell proliferation. AMPK and P53 act to inhibit lung adenocarcinoma progression. CPS1 promotes the progression of lung adenocarcinoma by suppressing ammonia-induced activation of the ROS/AMPK/P53/LKB1 signaling pathway. Show less
📄 PDF DOI: 10.1038/s41598-025-14443-9
CPS1

Correlation between Lipoprotein(a) and Endometrial Cancer Prognosis: a Retrospective Cohort Study.

Cong Liu, Zuommiao Xiao, Zhengting Liu +1 more · 2025 · Clinical laboratory · added 2026-04-24
Endometrial cancer (EC) is a malignant tumor arising from the endometrial epithelium and is among the most prevalent gynecological malignancies worldwide. Increasing evidence suggests that lipid profi Show more
Endometrial cancer (EC) is a malignant tumor arising from the endometrial epithelium and is among the most prevalent gynecological malignancies worldwide. Increasing evidence suggests that lipid profiles, hyperglycemia, and other metabolic factors play a role in EC pathogenesis. However, research on the association between lipoprotein(a) [Lp(a)] levels and EC prognosis remains limited. This retrospective cohort study analyzed Lp(a) levels in patients diagnosed with EC at Ganzhou Hospital, affiliated with Nanchang University, between January 2017 and January 2022. Lp(a) concentrations were measured post-admission, and patient prognosis was categorized as favorable or poor. Multivariate logistic regression analysis was performed to determine the adjusted odds ratio (OR) and 95% confidence interval (CI). The study included 296 EC patients, out of whom 72.3% (214/296) had a favorable prognosis, defined as no recurrence within five years post-surgery. The overall healing rate was 72.3% (214/296). When stratified by Lp(a) levels, patients in the first quantile (Q1 ≤ 122.2 g/L) had a favorable prognosis rate of 77.7% (115/148), whereas those in the second quantile (Q2 > 122.2 g/L) had a rate of 66.9% (99/148), with a statistically significant difference between groups (p < 0.05). In the multivariate regression model, the log2-transformed Lp(a) values and their corresponding ORs (95% CIs) for prognosis at two upper normal limits (ULN) were 1.7248 (1.0288 - 2.8918) and 2.0365 (1.1843 - 3.5018), respectively. Interaction analysis indicated that Lp(a) levels significantly influenced EC prognosis. Lp(a) is strongly associated with EC prognosis and holds potential clinical significance. Further studies are required to validate these findings. Show less
no PDF DOI: 10.7754/Clin.Lab.2025.250239
LPA

Patient-Specific In Vivo Gene Editing to Treat a Rare Genetic Disease.

Kiran Musunuru, Sarah A Grandinette, Xiao Wang +42 more · 2025 · The New England journal of medicine · added 2026-04-24
Base editors can correct disease-causing genetic variants. After a neonate had received a diagnosis of severe carbamoyl-phosphate synthetase 1 deficiency, a disease with an estimated 50% mortality in Show more
Base editors can correct disease-causing genetic variants. After a neonate had received a diagnosis of severe carbamoyl-phosphate synthetase 1 deficiency, a disease with an estimated 50% mortality in early infancy, we immediately began to develop a customized lipid nanoparticle-delivered base-editing therapy. After regulatory approval had been obtained for the therapy, the patient received two infusions at approximately 7 and 8 months of age. In the 7 weeks after the initial infusion, the patient was able to receive an increased amount of dietary protein and a reduced dose of a nitrogen-scavenger medication to half the starting dose, without unacceptable adverse events and despite viral illnesses. No serious adverse events occurred. Longer follow-up is warranted to assess safety and efficacy. (Funded by the National Institutes of Health and others.). Show less
📄 PDF DOI: 10.1056/NEJMoa2504747
CPS1

Advancing the clinical assessment of glomerular podocyte pathology in kidney biopsies via super-resolution microscopy and angiopoietin-like 4 staining.

Xiaojing Liu, Suxia Wang, Gang Liu +7 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.101498
ANGPTL4

Distinct FGF-FGFR sets regulate inhibitory presynaptic differentiation from parvalbumin- and somatostatin-positive interneurons.

Zhengdong Wei, Shasha Zhang, Keke Bai +11 more · 2025 · Development (Cambridge, England) · added 2026-04-24
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two la Show more
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two largest populations of neocortical interneurons, innervate the soma and/or proximal dendrites, and distal dendrites of pyramidal neurons, respectively. Using PV- and SST-specific knockout mouse models, we show that PV+ interneurons require FGFR2, which responds to FGF7, to drive PV+ inhibitory presynaptic maturation on perisomatic regions of Layer V pyramidal neurons. In contrast, SST+ interneurons rely on both FGFR1 and FGFR2, which respond to FGF10 or FGF22, to promote SST+ inhibitory presynaptic maturation on distal dendrites of pyramidal neurons in cortical Layer I. Mechanistically, FGF-FGFR signaling sustains VGAT protein levels in interneurons through PP2A and Akt pathways. Together, these findings demonstrate that distinct FGF ligand-receptor combinations regulate inhibitory presynaptic differentiation by PV+ and SST+ interneurons, contributing to the formation of compartment-specific synaptic patterns. Show less
no PDF DOI: 10.1242/dev.204532
FGFR1

Study on post-traumatic stress disorder and influencing factors in adult ICU patients on mechanical ventilation using latent profile analysis: a cross-sectional survey.

Yunting Li, Xiaoli Yuan, Mi Liu +2 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study aimed to explore the potential classification and influencing factors of post-traumatic stress disorder (PTSD) in intensive care unit (ICU) patients receiving mechanical ventilation to prov Show more
This study aimed to explore the potential classification and influencing factors of post-traumatic stress disorder (PTSD) in intensive care unit (ICU) patients receiving mechanical ventilation to provide a theoretical basis for formulating targeted intervention measures. A total of 229 patients on mechanical ventilation who were hospitalized in the intensive care unit of a Class III Grade A hospital in Zunyi from August 2023 to July 2024 were selected as research participants using a purposive sampling method. The General information questionnaire, Eysenck Personality Questionnaire Revised, Short Scale for Chinese (EPQ-RSC), Simplified Coping Style Questionnaire (SCSQ), Perceived Social Support Scale (PSSS), and Hospital Anxiety and Depression Scale (HADS) were used to assess the patients within 7 days after discharge from the ICU. One month after extubation, a cross-sectional survey was conducted using the Impact of Event Scale-Revised (IES-R). Latent profile analysis (LPA) was used to analyze the latent subtypes of PTSD, and univariate analysis and a disordered multivariate logistic regression model were used to evaluate the influencing factors associated with different types of PTSD. A total of 215 valid questionnaires were collected, and the effective recovery rate was 93.89%. The incidence of PTSD was 14.9% (95% CI: 10.12%-19.64%). There were three latent categories of PTSD among the ICU patients on mechanical ventilation: the "low-stress group" (56.8%, PTSD symptoms among mechanically ventilated ICU survivors manifest in three distinct profiles. Our findings strongly recommend early psychological screening, particularly focusing on anxiety and depression levels and patients' educational background. Medical staff should formulate targeted intervention plans based on the characteristics of different patient categories to lower the level of PTSD in patients. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1578276
LPA

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

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

From repetition to habit: how variability in daily physical activity relates to physical activity habits.

Jie Wen, Yujie Liu, Rui Cao +2 more · 2025 · Psychology & health · Taylor & Francis · added 2026-04-24
Repetition of physical activity (PA) contributes to the formation of PA habit. However, daily repetitions of PA of varied intensities might differ in their impact on PA habits. This study investigated Show more
Repetition of physical activity (PA) contributes to the formation of PA habit. However, daily repetitions of PA of varied intensities might differ in their impact on PA habits. This study investigated the effect of daily variability in PA on various facets of PA habits: lack of intention (LOI), lack of control (LOC) and efficiency of PA. Daily time spent on light-, moderate- and vigorous-intensity of PA (LPA, MPA and VPA) were assessed for 14 consecutive days among 182 college students. PA habits were measured afterwards. The results of mixed-effects random location-scale model showed that LOI was negatively predicted by variability in daily LPA; and that LOC was negatively predicted by daily variability in LPA and MPA. These findings suggest interventions of PA habit formation should focus on different facets of PA habits and consider the impact of daily repetition of PA of varied intensities. Show less
no PDF DOI: 10.1080/08870446.2025.2567333
LPA

Tigecycline modulates LPS-induced inflammatory response in sepsis via NF-κB signalling pathways: Experimental insights into immune regulation.

Lu Zhang, Jun Li, Meiqing Feng +8 more · 2025 · International journal of antimicrobial agents · Elsevier · added 2026-04-24
Sepsis is associated with high morbidity and high mortality and has strongly motivated intense studies into its mechanisms. Antibiotics, aimed to eradicate bacteria, have some impact on the immune sys Show more
Sepsis is associated with high morbidity and high mortality and has strongly motivated intense studies into its mechanisms. Antibiotics, aimed to eradicate bacteria, have some impact on the immune system due to anti-inflammatory properties. Tigecycline, an antibiotic of the glycylcycline class, is commonly used for severe infections. This study aimed to investigate tigecycline's mechanism on the inflammatory response of sepsis to find new targets for sepsis treatment. The objective included (i) to observe the changes in inflammatory factors in LPS (lipopolysaccharide) induced septic mice after tigecycline administration, (ii) to detect the effect of tigecycline on macrophages NF-κB (nuclear factor kappa B) signalling. For LPS-induced sepsis in mice and intervention with tigecycline, mice were first injected with tigecycline (6.5 mg/kg) via tail vein followed by LPS (15 mg/kg). Luminex analysis was performed on 16 mediators. NF-κB signalling pathway antibody chip detected the expression of target sites in macrophages of the LPS group and tigecycline + LPS group. Tigecycline has inhibitory effects on LPS-induced inflammatory response in septic mice, decreasing the concentrations of IL (interleukin)-6, IL-27, TNF-α (tumour necrosis factor-α), TNF RII, IFN-γ (interferon-gamma), CCL5/RANTES (CC Motif Chemokine Ligand) while increasing IL-6Rα, IL-10, and TWEAK (TNF-related weak inducer of apoptosis). Tigecycline downregulated phosphorylation levels of key sites JNK (c-Jun N-terminal kinase)1/2/3, p-p65 (s468) and p-p105/p50 (s907) in NF-κB signalling. Tigecycline may inhibit the excessive immune response induced by LPS in sepsis, which may cause a potential protective effect on the host through immune regulation. Show less
no PDF DOI: 10.1016/j.ijantimicag.2025.107496
IL27

Neurotrophin NGF/TrkA and BDNF/TrkB signaling orchestrates the immune microenvironment in osteosarcoma.

Hongyuan Liu, Guobing Wang, Chunxue Wang +4 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Neurotrophin signaling through NGF/TrkA and BDNF/TrkB is increasingly recognized as a driver of osteosarcoma (OS) progression and an organizer of its immune milieu, yet clinical translation has lagged Show more
Neurotrophin signaling through NGF/TrkA and BDNF/TrkB is increasingly recognized as a driver of osteosarcoma (OS) progression and an organizer of its immune milieu, yet clinical translation has lagged amid intratumoral heterogeneity and a myeloid-skewed, vasculature-aberrant tumor microenvironment (TME). Features that blunt immune competence include dominant tumor-associated macrophage programs, sparse and dysfunctional effector T cells, endothelial remodeling that restricts lymphocyte entry, and neuron-immune circuits that reinforce suppression. Within this context, NGF/TrkA promotes matrix remodeling, monocyte ingress, and macrophage polarization, while BDNF/TrkB modulates dendritic-cell maturation, supports survival and angiogenesis, and may condition T-cell priming-together positioning neurotrophins as coordinators of tumor persistence and immune exclusion. This review surveys these mechanisms and maps them to therapeutic strategies: kinase-level blockade with approved TRK inhibitors in NTRK fusion-positive disease; exploratory pathway inhibition in fusion-negative OS; ligand-directed approaches; and rational combinations with immunotherapy and vascular/stromal modulators. We highlight biomarker frameworks (receptor-ligand activity scores, phospho-Trk immunohistochemistry, NGF-MMP-2 readouts) and safety considerations that should structure early-phase trials. Clinical and preclinical signals collectively support testing neurotrophin-targeted strategies to recalibrate myeloid composition, enhance antigen presentation, and restore T-cell access to tumor beds. The purpose of this review is to synthesize current evidence and propose a translational roadmap for targeting NGF/TrkA and BDNF/TrkB to remodel antitumor immunity in osteosarcoma. Show less
📄 PDF DOI: 10.3389/fimmu.2025.1727434
BDNF

G3BP1, a stress granule core protein, ameliorates metabolic dysfunction-associated fatty liver disease by attenuating hepatocyte lipid deposition.

Xingjing Liu, Huimei Yu, Tongtong Hu +7 more · 2025 · Diabetes, obesity & metabolism · Blackwell Publishing · added 2026-04-24
Abnormal lipid accumulation is an important cause of metabolic dysfunction-associated fatty liver disease (MAFLD) progression and can induce several stress responses within cells. This study is the fi Show more
Abnormal lipid accumulation is an important cause of metabolic dysfunction-associated fatty liver disease (MAFLD) progression and can induce several stress responses within cells. This study is the first to explore the role and molecular mechanism of stress granules (SGs) in MAFLD. A gene knock-down model of G3BP1, a core SG molecule in mice and HepG2 cells, was constructed to explore the role of SGs in MAFLD induced in vivo by a high-fat diet or in vitro by palmitic acid (PA). Methods included metabolic phenotyping; western blotting; qPCR; and immunofluorescence, haematoxylin/eosin and masson staining. The downstream molecules of G3BP1 and its specific molecular mechanism were screened using RNA sequencing (RNA-seq). G3BP1 and TIA1 expression were upregulated in high-fat diet-fed mouse liver tissues and PA-induced HepG2 cells, and the two molecules showed significantly increased colocalisation. G3BP1 knock-down slightly increased TIA1 expression in the livers of obese mice but not in lean mice. G3BP1 deficiency aggravated liver lipid deposition and insulin resistance in obese mice, and this phenotype was confirmed in vitro in PA-induced hepatocytes. RNA-seq demonstrated that G3BP1 slowed down MAFLD progression by inhibiting APOC3, possibly through a mechanistic suppression of APOC3 entry into the nucleus. This study reveals for the first time a protective role for SGs in MAFLD. Specifically, knocking down the core G3BP1 molecule in SGs aggravated the progression of fatty acid-induced MAFLD through a mechanism that may involve the nuclear entry of APOC3. These findings provide a new therapeutic direction for MAFLD. Show less
no PDF DOI: 10.1111/dom.16302
APOC3

TAC-ECG: A task-adaptive classification method for electrocardiogram based on cross-modal contrastive learning and low-rank convolutional adapter.

Rongjia Wang, Xunde Dong, Xiuling Liu +5 more · 2025 · Computer methods and programs in biomedicine · Elsevier · added 2026-04-24
Cardiovascular diseases are one of the major health threats to humans. Researchers have proposed numerous deep learning-based methods for the automatic analysis of electrocardiogram (ECG), achieving e Show more
Cardiovascular diseases are one of the major health threats to humans. Researchers have proposed numerous deep learning-based methods for the automatic analysis of electrocardiogram (ECG), achieving encouraging results. However, many existing methods are limited to task-specific model training and require retraining or full fine-tuning when confronted with a new ECG classification task, thus lacking flexibility in clinical applications. In this study, we propose a Task-Adaptive Classification method for ECG (TAC-ECG) based on cross-modal contrastive learning and low-rank convolutional adapters. TAC-ECG comprises two main phases. In the first phase, inspired by the Contrastive Language-Image Pre-training, we design the Contrastive ECG-Text Pre-training (CETP) to pre-train a robust ECG encoder. In the second phase, the pre-trained ECG encoder is frozen and integrated with a lightweight plug-in, the Low-Rank Convolutional Adapter (LRC-Adapter), forming an extensible ECG classification model. The frozen encoder extracts more discriminative features from the ECG signal, while the LRC-Adapter enables task-specific adaptation. For diverse ECG classification tasks, TAC-ECG only requires training the LRC-Adapter. This mechanism enables TAC-ECG to efficiently perform different ECG classification tasks, significantly reducing resource consumption and deployment costs in multi-tasking scenarios compared to traditional fully fine-tuned methods. We conducted extensive experiments using six different network architectures as ECG encoders. Specifically, we performed ECG classification experiments on four datasets: CPSC2018, Cinc2017, PTB-XL, and Chapman, targeting 9-category, 3-category, 5-category, and 4-category classifications respectively. The TAC-ECG achieved highly competitive results using only approximately 3% of the trainable parameters and approximately 25% of the total parameters compared to the fully fine-tuned method. These results demonstrates the effectiveness and practicality of the TAC-ECG method. The TAC-ECG offers a flexible and efficient method for ECG classification, enabling rapid adaptation to diverse tasks and enhancing clinical diagnostic practicality. Show less
no PDF DOI: 10.1016/j.cmpb.2025.108918
CETP

VRK1 promotes epithelial-mesenchymal transition in hepatocellular carcinoma mediated by SNAI1 via phosphorylating CHD1L.

Jing Li, Zan Song, Xue Dong +12 more · 2025 · Cell death & disease · Nature · added 2026-04-24
Vaccinia-related kinase 1 (VRK1) is involved in numerous cellular processes, including DNA repair, cell cycle and cell proliferation. However, its roles and molecular mechanism underlying the progress Show more
Vaccinia-related kinase 1 (VRK1) is involved in numerous cellular processes, including DNA repair, cell cycle and cell proliferation. However, its roles and molecular mechanism underlying the progression of hepatocellular carcinoma (HCC) are yet largely unexplored. Here, we demonstrated that VRK1 expression is elevated in HCC tumor tissues, which is associated with high tumor stage and poor prognosis in HCC patients. In vitro and in vivo experiments manifested that VRK1 overexpression significantly promotes cell proliferation, colony formation, migration and tumor growth of HCC by inducing epithelial-mesenchymal transition (EMT) program. Mechanistically, immunoprecipitation combined with mass spectrometry analysis determined that VRK1 interacts with CHD1L, which mediates the phosphorylation of CHD1L at serine 122 site. RNA-seq revealed that one of the key downstream target genes of VRK1 is SNAI1, by which VRK1 promotes EMT process and HCC progression. Furthermore, VRK1 upregulates SNAI1 expression through phosphorylating CHD1L. In conclusion, these findings suggested that VRK1/CHD1L/SNAI1 axis acts as a cancer-driving pathway to promote the proliferation and EMT of HCC, indicating that targeting VRK1 may be an attractive therapeutic strategy of HCC. Show less
no PDF DOI: 10.1038/s41419-025-07641-w
SNAI1

Revealing the binding mechanism of BACE1 inhibitors through molecular dynamics simulations.

Yanjun Zhang, Dongqiang Miao, Senchen Liu +1 more · 2025 · Journal of biomolecular structure & dynamics · Taylor & Francis · added 2026-04-24
Alzheimer's disease is a debilitating neurodegenerative disorder, and the Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE1) is a key therapeutic target in its treatment. This study employs Show more
Alzheimer's disease is a debilitating neurodegenerative disorder, and the Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE1) is a key therapeutic target in its treatment. This study employs molecular dynamics simulations and binding energy analysis to investigate the binding interactions between BACE1 and four selected small molecules: CNP520, D9W, NB641, and NB360. The binding model analysis indicates that the binding of BACE1 with four molecules are stable, except the loop regions show significant fluctuation. The binding free energy analyses reveal that NB360 exhibits the highest binding affinity with BACE1, surpassing other molecules (CNP520, D9W, and NB641). Detailed energy component assessments highlight the critical roles of electrostatic interactions and van der Waals forces in the binding process. Furthermore, residue contribution analysis identifies key amino acids influencing the binding process across all systems. Hydrogen bond analysis reveals a limited number of bonds between BACE1 and each small molecule, highlighting the importance of structural modifications to enable more stable hydrogen bonds. This research provides valuable insights into the molecular mechanisms of potential Alzheimer's disease therapeutics, guiding the way for improved drug design and the development of effective treatments targeting BACE1. Show less
no PDF DOI: 10.1080/07391102.2024.2319676
BACE1

Exogenous lactate infusion enhanced VMH neuroplasticity and visceral fat reduction via PGC-1α-ERα pathway in female rats.

Shuai Tian, Jing Han, Zhaomin Zhang +3 more · 2025 · European journal of applied physiology · Springer · added 2026-04-24
High-intensity exercise promotes visceral adipose tissue (VAT) breakdown in females via the hypothalamic ERα pathway, and exogenous lactate infusion combined with aerobic training (AT) mimics this eff Show more
High-intensity exercise promotes visceral adipose tissue (VAT) breakdown in females via the hypothalamic ERα pathway, and exogenous lactate infusion combined with aerobic training (AT) mimics this effect. However, whether lactate administration can independently mediate hypothalamic plasticity and VAT catabolism as a standalone nutritional strategy remains unexplored. Firstly, using a two-factor design (Lactate × AT) in female SD rats, we showed that long-term exogenous lactate infusion independently induced co-expression of Estrogen receptor α (ERα) and Brain-derived neurotrophic factor (BDNF) in the ventromedial hypothalamus (VMH) and elevated local field potential spectral power in specific bands. These neural adaptations were accompanied by increased resting metabolic rate, enhanced fat oxidation, and enhanced lipolysis, thereby preventing excessive VAT accumulation induced by a high-fat diet. Furthermore, pharmacological inhibition confirmed that Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-α (PGC-1α) acts as a co-upstream signal of ERα and BDNF mediating this process. Our findings reveal that standalone lactate administration induces functional plasticity and metabolic reprogramming through the VMH PGC-1α-ERα pathway, independent of exercise, and effectively suppresses pathological VAT accumulation in female rats. This study identifies potential nutritional interventions and mechanistic targets for preventing female-centered obesity. Show less
📄 PDF DOI: 10.1007/s00421-025-06097-2
BDNF

Identification and validation of MMP1 as a biomarker associated with mitochondrial oxidative stress in liver hepatocellular carcinoma.

Zhihui Wang, Hao Zhou, Lie Zhang +2 more · 2025 · Scientific reports · Nature · added 2026-04-24
Mitochondrial oxidative stress plays a critical role in cancer development and progression. However, there is limited research on the relationship between mitochondrial oxidative stress and liver hepa Show more
Mitochondrial oxidative stress plays a critical role in cancer development and progression. However, there is limited research on the relationship between mitochondrial oxidative stress and liver hepatocellular carcinoma (LIHC). Mitochondrial oxidative stress-related genes were collected from Genecards Portal. Prognosis-linked genes (PLGs) were identified by univariate Cox regression analysis. A risk model was constructed based on the PLGs using least absolute shrinkage and selection operator (LASSO) analysis. Receiver operating characteristic (ROC) curves were used to determine the predictive ability of the model. The expression levels of the prognostic genes were verified in the cell lines. Cell proliferation, apoptosis, and invasion assays were conducted to investigate the functional role of the target gene. We constructed a novel risk model based on 9 prognostic genes (CYP2C19, CASQ2, LPL, TXNRD1, CACNA1S, SLC6A3, OXTR, BIRC5, and MMP1). Survival analysis showed that patients with a low-risk score had a much better overall survival (OS). Prognostic risk score was found to be an independent predictor of prognosis. Patients in the high-risk group had a less favorable tumor microenvironment characterized by a lower degree of immune cell infiltration. Among the nine prognostic genes, MMP1, identified as the most promising candidate, demonstrated the capacity to enhance tumor cell proliferation and invasion. Our investigation reveals the oncogenic role of mitochondrial oxidative stress in LIHC. For the first time, we established a risk prediction model for mitochondrial oxidative stress in patients with LIHC. MMP1 has the potential to function as a promising biomarker in LIHC. Show less
📄 PDF DOI: 10.1038/s41598-025-10076-0
LPL

Transcriptome analysis reveals reduced lipid accumulation and mitochondrial metabolic remodeling in ADCY3-overexpressing adipocytes.

Lu Liu, Houxue Cui, Zhongfang Xiang +2 more · 2025 · Functional & integrative genomics · Springer · added 2026-04-24
Excessive adipose tissue accumulation adversely impacts the health of both humans and livestock. Adenylyl cyclase 3 (ADCY3) is a promising anti-obesity target, yet its regulatory role in adipogenesis Show more
Excessive adipose tissue accumulation adversely impacts the health of both humans and livestock. Adenylyl cyclase 3 (ADCY3) is a promising anti-obesity target, yet its regulatory role in adipogenesis remains incompletely understood. Our findings revealed a dynamic pattern of ADCY3 expression during adipogenesis and lipid droplet (LDs) accumulation. Functional analyses demonstrated that ADCY3 overexpression impaired adipogenesis by downregulating adipogenic transcription factors CEBPα and PPARγ. Furthermore, it reduced both the number and size of LDs through suppressing triglyceride synthesis and fatty acid metabolism, concomitantly downregulating key genes involved in LDs formation (PLIN1, CIDEC, FIT2, and Seipin), as well as factors mediating glycerol ester synthesis and fatty acid metabolism (DGAT1, DGAT2, ACC, SCD, FASN, and ACSL1). Transcriptomic profiling revealed that ADCY3 overexpression suppressed PPARγ signaling, leading to the downregulation of oxidative phosphorylation genes encoded by both the nuclear and mitochondrial genomes. Our results implicate ADCY3 in the regulation of lipid metabolism, with the speculative involvement of mitochondrial metabolic remodeling. This perspective offers a framework for developing future interventions against excessive lipid deposition. Show less
no PDF DOI: 10.1007/s10142-025-01789-6
ADCY3

Dietary Exposure to 2,2',4,4'-Tetrabromodiphenyl Ether (BDE-47) Causes Inflammation in the Liver of Common Carp (

Shuhuang Chen, Nian Han, Yujie Huang +5 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
2,2',4,4'-tetrabromodiphenyl ether (BDE-47) is a common environmental contaminant and widely detected in aquatic surroundings, while only a few reports exist on the hazard mechanism in economic aquati Show more
2,2',4,4'-tetrabromodiphenyl ether (BDE-47) is a common environmental contaminant and widely detected in aquatic surroundings, while only a few reports exist on the hazard mechanism in economic aquatic animals. It has been shown that 40 and 4000 ng/g of BDE-47 dietary exposure over 42 days significantly increased the levels of blood triglycerides, glucose, and liver glycogen in carp ( Show less
📄 PDF DOI: 10.3390/ijms262010152
LPL

Integrating network pharmacology, quantitative transcriptomic analysis, and experimental validation revealed the mechanism of cordycepin in the treatment of obesity.

Yu Liao, Mingchao Wang, Fuli Qin +2 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically Show more
Evidence of the benefits of cordycepin (Cpn) for treating obesity is accumulating, but detailed knowledge of its therapeutic targets and mechanisms remains limited. This study aimed to systematically identify Cpn's therapeutic targets and pathways in Western diet (WD)-induced obesity using integrated network pharmacology, transcriptomics, and experimental validation. A Western diet (WD)-induced mice model was used to evaluate the effectiveness of Cpn in ameliorating obesity. A network pharmacology analysis was then employed to identify the potential anti-obesity targets of Cpn. GO functional enrichment and KEGG pathway analysis were performed to elucidate the potential functions of the identified targets, followed by constructing a protein-protein interaction network to screen the core targets. Meanwhile, quantitative transcriptomics was conducted to validate and broaden the network pharmacology findings. Finally, molecular docking and quantitative real-time PCR assay were used for the core target validation. Cpn treatment effectively alleviated obesity-related symptoms in WD-induced mice. The metabolic pathway, insulin signaling pathway, HIF-1 signaling pathway, FoxO signaling pathway, lipid and atherosclerosis pathway, and core targets including CPS1, HRAS, MAPK14, PAH, ALDOB, AKT1, GSK3B, HSP90AA1, BHMT2, EGFR, CASP3, MAT1A, APOM, APOA2, APOC3, and APOA1 are involved in regulating the therapeutic effect of Cpn. This study comprehensively uncovers the potential mechanism of Cpn against obesity based on network pharmacology and quantitative transcriptomics, which provides evidence for revealing the pathogenesis of obesity, suggesting that Cpn is a possible lead compound for anti-obesity treatment. Show less
📄 PDF DOI: 10.3389/fphar.2025.1571480
APOC3

Latent profiles of quality of life and their correlations with social support and self-efficacy of patients with hematologic malignancies.

Xuran Cao, Yaxin Du, Chuanxin Liu · 2025 · Scientific reports · Nature · added 2026-04-24
Quality of life (QoL) subtypes were identified via latent profile analysis (LPA), and their correlations with social support and self-efficacy were assessed in 284 patients with hematologic malignanci Show more
Quality of life (QoL) subtypes were identified via latent profile analysis (LPA), and their correlations with social support and self-efficacy were assessed in 284 patients with hematologic malignancies (HMs). The results were as follows: (1) LPA revealed three QoL subtypes of patients with HMs, namely, the high-QoL group, the medium-QoL group, and the low-QoL group. (2) The high-QoL group had higher levels of social support than the medium-QoL group did, and they also had higher levels of self-efficacy than both the medium- and low-QoL groups did. These results contribute to the identification of heterogeneous QoL features among patients with HMs and their correlations with social support and self-efficacy. Moreover, this study has clinical implications for improving the QoL of patients with HMs and promoting their physical and mental health. Show less
📄 PDF DOI: 10.1038/s41598-025-99662-w
LPA

A novel splicing variant of CNTRL::FGFR1 in myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1.

Xianqi Feng, Xueting Bai, Hong Zhang +7 more · 2025 · Journal of hematopathology · Springer · added 2026-04-24
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement Show more
Background Myeloid/lymphoid neoplasm with eosinophilia and rearrangement of FGFR1(MLN-FGFR1), also referred to as 8p11 myeloproliferative syndrome (EMS), arises from aberrant FGFR1 gene rearrangement in bone marrow hematopoietic stem cells, resulting in the transformation of myeloid/lymphoid cells into neoplastic growths. The clinical and laboratory features of affected individuals are influenced by the specific partner genes. Purpose This article aims to report a case of MLN-FGFR1 involving a novel CNTRL::FGFR1 splicing variant and to discuss its clinicopathological characteristics and treatment challenges. Methods/Results We report a case of MLN-FGFR1 in a 35-year-old male patient presenting with leukocytosis, lymphadenopathy, hepatosplenomegaly, and a mixed population of B lymphoblasts, T lymphoblasts, and monoblasts in the bone marrow and lymph nodes. Comprehensive molecular profiling, including chromosomal karyotyping, fluorescence in situ hybridization (FISH), targeted transcriptome sequencing, reverse transcription polymerase chain reaction (RT-PCR), and Sanger sequencing, identified a novel splicing variant of the CNTRL::FGFR1 fusion, resulting from a t(8;9)(p11;q33) translocation. This novel splicing variant involves an in-frame fusion between exon 38 of CNTRL and exon 11 of FGFR1, retaining the kinase domain of FGFR1 and leading to its constitutive activation. Despite multiple treatment regimens, the patient failed to achieve complete remission (CR). Conclusion The findings highlight the urgent need for targeted therapies, such as FGFR inhibitors, to improve outcomes in patients with FGFR1-rearranged malignancies. Show less
📄 PDF DOI: 10.1007/s12308-025-00670-6
FGFR1

FGFR1-related congenital hypogonadotropic hypogonadism: a case report and literature review.

Miao Sun, Yan Liu, Maolin Liu +5 more · 2025 · Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology · Taylor & Francis · added 2026-04-24
Congenital hypogonadotropic hypogonadism (CHH) is a rare condition characterized by incomplete pubertal development, infertility, and gonadotropin-releasing hormone deficiency, associated with mutatio Show more
Congenital hypogonadotropic hypogonadism (CHH) is a rare condition characterized by incomplete pubertal development, infertility, and gonadotropin-releasing hormone deficiency, associated with mutations in more than 50 genes. We aimed to conduct an etiological analysis of a CHH Chinese family and summarize the clinical presentations and genetic changes of reported similar cases. Whole-exome sequencing (WES) was performed to identify the molecular cause in the proband. In silico tools were employed to analyze the pathogenicity of the variants. Reported cases with similar clinical features and associated genes were summarized by searching through PubMed/MEDLINE using keywords 'FGFR1,' 'CHH,' and 'Kallmann syndrome (KS).' Genetic analysis revealed a novel likely pathogenic deletion mutation in the FGFR1 gene (NM₀₂₃₁₁₀.3: c.263₂₆₄del (Val88Alafs*22)) in a Chinese family exhibiting micropenis and underdeveloped testes. A total of 38 cases with CHH or KS have been previously reported. This study identified a novel FGFR1 deletion variant responsible for CHH, expanding the known mutational spectrum of FGFR1. Typical manifestations include delayed puberty and diverse presentations. The genotype-phenotype correlation in CHH remains unclear and may involve oligogenic effects and epigenetic regulation. Show less
no PDF DOI: 10.1080/09513590.2025.2571656
FGFR1

Precision engineering of anti-atherosclerotic herbal nanomedicine: from machine learning-aided active components screening to optimized metal-phenolic network codelivery.

Yao Chen, Meiting Lu, Lu Zhang +9 more · 2025 · Drug delivery and translational research · Springer · added 2026-04-24
Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditional herbs Salvia miltiorrhiza and Carthamus tinctori Show more
Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditional herbs Salvia miltiorrhiza and Carthamus tinctorius exhibit multi-target anti-AS potential, yet their compositional complexity limits clinical translation. This study aimed to systematically identify core anti-AS components from these herbs and enhance their anti-AS efficacy via machine learning-aided screening and nanotechnology-driven codelivery. We initially pioneered a machine learning-aided hybrid strategy integrating network pharmacology and quantitative activity relationship (QSAR) modeling to identify four core anti-AS polyphenols (i.e., salvianic acid A, salvianolic acid B, protocatechuic acid, and hydroxysafflor yellow A). Subsequently, a quaternary metal-phenolic network (SSPH-MPN) was engineered for plaque-targeted codelivery, optimized via the median-effect principle for achieving a synergistic effect based on ROS scavenging efficacy. The optimized SSPH-MPN was characterized by a series of studies, including molecular dynamics simulations, UV, DLS, TEM, FTIR, XPS, and ICP-MS. The anti-AS effect of the optimized SSPH-MPN was evaluated by monitoring oxidative status (ROS levels, antioxidant enzymes SOD, GSH-Px, MDA, T-AOC), inflammatory markers (IL-1β, IL-6, TNF-α), lipid metabolism (DiI-oxLDL uptake, cholesterol efflux, blood lipid levels, lipid accumulation), and plaque areas. The results demonstrated that the optimized SSPH-MPN showed great efficiency in inhibiting lipid uptake and accumulation, and mediating cholesterol efflux in RAW 264.7 cells, and exhibited improved lipid metabolism, attenuated oxidative stress and inflammation, thus acquired diminished plaque area in apoE Show less
📄 PDF DOI: 10.1007/s13346-025-02023-3
APOE

Post-genome-wide association study dissects genetic vulnerability and risk gene expression of Sjögren's disease for cardiovascular disease.

Xinglin Yi, Erxiong Liu, Yong Wang · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
This study aims to clarify the genetic associations between Sjögren's Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibil Show more
This study aims to clarify the genetic associations between Sjögren's Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibility genes. We performed two-sample and multivariable Mendelian randomization (MR) analysis to investigate the association between SD and the risk of ischemic heart disease (IHD) and stroke. Linkage disequilibrium score regression (LDSC) and Bayesian co-localization analyses were employed to assess the genetic associations between traits. Cross-phenotype analyses were employed to identify shared variants and genes, followed by a Transcriptome-Wide Association Study (TWAS) and Multi-marker Analysis of Genomic Annotation (MAGMA) based on Multi-Trait Analysis of GWAS (MTAG) results. To validate the pleiotropic genes, we further analyzed tissue-specific differentially expressed genes (DEGs) related to SD using RNA sequencing data. The two-sample and multivariable MR analyses revealed that SD confers a genetic vulnerability to IHD and stroke. LDSC and co-localization analyses indicated a strong genetic linkage between SD and CVDs. Cross-phenotype analyses identified 38 and 37 pleiotropic single nucleotide polymorphisms (SNPs) for SD-Stroke and SD-IHD, respectively, primarily located within the MHC class region on 6p21.32:33 loci. Additionally, TWAS and MAGMA analyses identified pleiotropic genes located outside the MHC regions-seven associated with stroke (UHRF1BP1, SNRPC, BLK, FAM167A, ARHGAP27, C8orf12, and PLEKHM1) and two associated with IHD (UHRF1BP1 and SNRPC). Proxy variants within these genes in SD suggested an increased causal risk for stroke or IHD. Co-localization analysis further reinforced that SD and stroke share significant SNPs within the loci of FAM167A, BLK, C8orf12, SNRPC, and UHRF1BP1. DEG analysis revealed a significant up-regulation of the identified genes in SD-specific tissues. SD appears genetically predisposed to an increased risk of CVDs. Moreover, this research not only identified pleiotropic genes shared between SD and CVDs, but also, for the first time, detected key gene expressions that elevate CVD risk in SD patients-findings that may offer promising therapeutic targets for patient management. Show less
no PDF DOI: 10.1186/s12967-025-06568-2
SNRPC

Pterostilbene mitigates experimental pulmonary arterial hypertension by inhibiting endothelial-to-mesenchymal transition.

Jie Wang, Yu Zhang, Junjun Liu +3 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
The natural compound pterostilbene (PTE) has multiple cardiovascular protective effects. However, its effects on pulmonary arterial hypertension (PAH)-associated vascular remodeling remain to be eluci Show more
The natural compound pterostilbene (PTE) has multiple cardiovascular protective effects. However, its effects on pulmonary arterial hypertension (PAH)-associated vascular remodeling remain to be elucidated. This study investigated the effects of PTE on monocrotaline (MCT)-induced PAH in rats Experimental PAH was established by subcutaneous injection of MCT (50 mg/kg) in Sprague-Dawley rats, which were then randomly divided into vehicle or PTE (15 mg/kg via gavage) treatment groups. Endothelial-to-mesenchymal transition (EndMT) was modeled in hPAECs by treating with transforming growth factor-β, tumor necrosis factor-α, and interleukin-1β in combination. In rats with MCT-induced PAH, administration of PTE resulted in a reduction in right ventricular systolic pressure, thereby alleviating right ventricular hypertrophy. This was accompanied by mitigation of the remodeling of pulmonary arteries. PTE mitigates MCT-induced PAH and vascular remodeling in rats, at least in part, by inhibiting HMGA-mediated EndMT, suggesting that PTE may be a useful complementary medicine in the treatment of PAH. Show less
no PDF DOI: 10.3389/fphar.2025.1621700
SNAI1

Super-enhancers and Mef2c: Novel regulators of cardiac hypertrophy via the Hey2/Notch/p38 signaling pathway.

Ruixuan Wang, Lina Ba, Rui Wang +6 more · 2025 · European journal of pharmacology · Elsevier · added 2026-04-24
Cardiac hypertrophy (CH), a pathological response to stress, is intricately regulated by the dynamic control of gene expression. This study explored the role of super-enhancers (SEs) and the transcrip Show more
Cardiac hypertrophy (CH), a pathological response to stress, is intricately regulated by the dynamic control of gene expression. This study explored the role of super-enhancers (SEs) and the transcription factor Mef2c in CH regulation. Using a transverse aortic constriction (TAC) mouse model, we demonstrated that inhibition of SEs with JQ-1, a BET inhibitor, significantly attenuated hypertrophic responses, as evidenced by reduced heart weight indices, enhanced cardiac function, and decreased expression of hypertrophic marker proteins BNP and β-MHC. Further analysis revealed that Mef2c, a key transcription factor, is driven by SEs in CH. In vivo and in vitro overexpression of Mef2c promotes CH, while deletion of the Mef2c SE region alleviates this condition. Mechanistically, we identified Hey2 as a downstream target of Mef2c and demonstrated that Mef2c regulates CH through the Hey2/Notch/p38 signaling pathway. Our findings provide novel insights into the molecular mechanisms underlying CH and suggest potential therapeutic targets for its treatment. Show less
no PDF DOI: 10.1016/j.ejphar.2025.177771
HEY2

Hypertrophic Cardiomyopathy: Genes and Mechanisms.

Jinli Chen, Yang Xing, Jie Sun +4 more · 2025 · Frontiers in bioscience (Landmark edition) · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is a hereditary disease of the myocardium characterized by asymmetric hypertrophy (mainly the left ventricle) not caused by pressure or volume load. Most cases of HCM Show more
Hypertrophic cardiomyopathy (HCM) is a hereditary disease of the myocardium characterized by asymmetric hypertrophy (mainly the left ventricle) not caused by pressure or volume load. Most cases of HCM are caused by genetic mutations, particularly in the gene encoding cardiac myosin, such as Show less
no PDF DOI: 10.31083/FBL25714
MYBPC3

Adipocyte heparan sulfate determines type 2 diabetes susceptibility in mice via FGF1-Mediated glucose regulation.

Chung-Jui Yu, Ariane R Pessentheiner, Sihao Liu +21 more · 2025 · Molecular metabolism · Elsevier · added 2026-04-24
Obesity is the principal driver of insulin resistance, and lipodystrophy is also linked with insulin resistance, emphasizing the vital role of adipose tissue in glucose homeostasis. The quality of adi Show more
Obesity is the principal driver of insulin resistance, and lipodystrophy is also linked with insulin resistance, emphasizing the vital role of adipose tissue in glucose homeostasis. The quality of adipose tissue expansion is a critical determinant of insulin resistance predisposition, with individuals suffering from metabolic unhealthy adipose expansion exhibiting greater risk. Adipocytes are pivotal in orchestrating metabolic adjustments in response to nutrient intake and cell intrinsic factors that positively regulate these adjustments are key to prevent Type-2 diabetes. Employing unique genetic mouse models, we established the critical involvement of heparan sulfate (HS), a fundamental element of the adipocyte glycocalyx, in upholding glucose homeostasis during dietary stress. Genetic models that compromise adipocyte HS accelerate the development of high-fat diet-induced hyperglycemia and insulin resistance, independent of weight gain. Mechanistically, we show that perturbations in adipocyte HS disrupts endogenous FGF1 signaling, a key nutrient-sensitive effector. Furthermore, compromising adipocyte HS composition detrimentally impacts FGF1-FGFR1-mediated endocrinization, with no significant improvement observed in glucose homeostasis. Our data establish adipocyte HS composition as a determinant of Type 2 diabetes susceptibility and the critical dependency of the endogenous adipocyte FGF1 metabolic pathway on HS. Show less
📄 PDF DOI: 10.1016/j.molmet.2025.102267
FGFR1

LXRα agonists ameliorates acute rejection after liver transplantation via ABCA1/MAPK and PI3K/AKT/mTOR signaling axis in macrophages.

Xiaoyan Qin, Dingheng Hu, Qi Li +6 more · 2025 · Molecular medicine (Cambridge, Mass.) · BioMed Central · added 2026-04-24
Liver X receptor α (LXRα) plays an important role in inflammatory immune response induced by hepatic ischemia-reperfusion injury (IRI) and acute rejection (AR). Macrophage M1-polarization play an impo Show more
Liver X receptor α (LXRα) plays an important role in inflammatory immune response induced by hepatic ischemia-reperfusion injury (IRI) and acute rejection (AR). Macrophage M1-polarization play an important role in the occurrence and development of AR. Although the activation of LXR has anti-inflammatory effects, the role of LXRα in AR after liver transplantation (LT) has not been elucidated. We aimed to investigate LXRα anti-inflammatory and macrophage polarization regulation effects and mechanisms in acute rejection rat models. LXRα anti-inflammatory and liver function protective effects was initially measured in primary Kupffer cells and LT rat models. Subsequently, a flow cytometry assay was used to detect the regulation effect of LXRα in macrophage polarization. HE staining, TUNEL and ELISA were used to evaluate the co-treatment effects of TO901317 and tacrolimus on hepatic apoptosis and liver acute rejection after LT. In this study, we found that LPS can inhibit the expression of LXRα and activate MAPK pathway and PI3K/AKT/mTOR. We also found that LXRα agonist (TO901317) could improve liver function and rat survival after LT by activating the level of ABCA1 and inhibiting MAPK. TO901317 could inhibit macrophage M1-polarization by activating PI3K/AKT/mTOR signal pathway to improve the liver lesion of AR rats after liver transplantation. Additionally, co-treatment with TO901317 and tacrolimus more effectively alleviated the damaging effects of AR following LT than either drug alone. Our results suggest that the activation of LXRα can improve liver function and rat survival after LT by regulate ABCA1/MAPK and PI3K/AKT/mTOR signaling axis in macrophages. Show less
no PDF DOI: 10.1186/s10020-025-01153-1
NR1H3

Multi-omics integration deciphers immune-metabolic heterogeneity in CRC: A prognostic model and therapeutic strategies targeting ANGPTL4/FABP4/RBP7.

Ning Ding, Meimei Jiang, Guiyun Jia +6 more · 2025 · Computers in biology and medicine · Elsevier · added 2026-04-24
The heterogeneity of the tumor immune microenvironment (TIME) and therapeutic resistance in Colorectal cancer (CRC) present substantial clinical challenges. In this study, 1136 CRC samples from TCGA a Show more
The heterogeneity of the tumor immune microenvironment (TIME) and therapeutic resistance in Colorectal cancer (CRC) present substantial clinical challenges. In this study, 1136 CRC samples from TCGA and GEO were utilized for the overall research design, and tumor subtype classification (Immunity_High and Immunity_Low) was specifically performed on the TCGA cohort (n = 568) using single-sample gene set enrichment analysis (ssGSEA) and t-SNE dimensionality reduction; t-SNE was selected because the study focused on distinguishing local clustering features of immune subtypes-it excels in enhancing sample aggregation within subtypes and highlighting local differences, which aligns with classification needs, so UMAP (prioritizing global structure preservation) was not used. The GEO cohort (n = 568) was used for subsequent validation of the prognostic model and results. A 12-gene prognostic model, comprising ANGPTL4, FABP4, RBP7, and 9 additional non-core genes (CCL22, NOS2, TGFB3, APOD, CHGB, CX3CL1, APOBEC3F, LCN12, BST2), was developed using Least Absolute Shrinkage and Selection Operator-Cox regression (LASSO-Cox regression) regression.The functions of the core genes and potential therapeutic candidates were investigated via single-cell sequencing, molecular docking, dynamics simulations, drug sensitivity analysis, Human Protein Atlas (HPA) and quantitative Real - time Polymerase Chain Reaction (qPCR). The Immunity_High subtype, characterized by the presence of CD8 This multi-omics study integrates multi-omics data to elucidate the immune-metabolic heterogeneity in CRC, establishing a precise prognostic model and providing bioinformatic evidence for key roles of ANGPTL4, FABP4, and RBP7 in the tumor microenvironment, thereby suggesting novel strategies to overcome immunotherapy resistance. Show less
no PDF DOI: 10.1016/j.compbiomed.2025.111271
ANGPTL4