👤 Yajuan Liu

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3182
Articles
1983
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Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaowei Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, 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 reveals genetic mechanisms of cold resistance in Hezuo pig liver tissue.

Yali Zhang, Xiaoli Gao, Chao Liu +4 more · 2025 · Journal of proteomics · Elsevier · added 2026-04-24
Cold stress poses a significant challenge to pig farming in northern China, leading to reduced productivity and, in severe cases, even mortality. However, the mechanisms underlying cold resistance in Show more
Cold stress poses a significant challenge to pig farming in northern China, leading to reduced productivity and, in severe cases, even mortality. However, the mechanisms underlying cold resistance in pigs are not well understood. To explore the genetic mechanism of cold resistance in pigs under low-temperature conditions, the cold-tolerant Hezuo pig was selected as a model. DIA proteomics analysis was performed on liver tissues from Hezuo pigs after 24 h of exposure to low-temperature treatments. The results showed that approximately 149 differential abundance proteins (DAPs) were detected (95 up-regulated and 54 down-regulated). GO analysis showed that these DAPs were mainly associated with lipid metabolism, vesicle fusion, and membrane function. KEGG analysis showed that these DAPs were primarily enriched in lipid metabolism-related pathways such as cholesterol metabolism and vitamin digestion and absorption. Comprehensive analysis identified APOA4, APOA2, SREBF2, ATP23, STX2, USO1, ETFA, RAB11FIP1, ETNPPL, and SGMS1 as potential key proteins involved in cold resistance mechanisms. The mRNA expression of the genes for two key candidate proteins (APOA4 and SREBF2), which are involved in lipid metabolism, was analyzed using qRT-PCR, revealing a significant up-regulation after low-temperature treatment. These findings provide significant insights into the mechanisms of cold resistance in animals and may serve as candidate markers for further studies on cold tolerance. SIGNIFICANCE: Cold resistance is one of the key traits in pigs and involves multiple complex coordinated regulatory mechanisms. However, its genetic mechanisms are not completely understood. In this study, a DIA proteomics approach was used to identify proteins and pathways associated with cold resistance in the liver of low-temperature-treated Hezuo pigs. These findings offer novel candidate proteins and key pathways for investigating the molecular mechanisms of cold resistance in Hezuo pigs, providing a base for further elucidating the mechanisms of cold tolerance in pigs. Show less
no PDF DOI: 10.1016/j.jprot.2025.105420
APOA4

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

Triaptosis and Cancer: Next Hope?

Zi-Zhan Li, Kan Zhou, Jinmei Wu +5 more · 2025 · Research (Washington, D.C.) · added 2026-04-24
Cancer persists as one of the most formidable global public health crises and socioeconomic burdens of our era, compelling the scientific community to develop innovative and diversified therapeutic mo Show more
Cancer persists as one of the most formidable global public health crises and socioeconomic burdens of our era, compelling the scientific community to develop innovative and diversified therapeutic modalities to revolutionize clinical management and enhance patient outcomes. The recent seminal discovery by Swamynathan et al. has unveiled menadione, a vitamin K precursor, as a potent inducer of triaptosis-a novel regulated cell death pathway mediated through the oxidative modulation of phosphatidylinositol 3-kinase PIK3C3/VPS34. This mechanistically distinct cell death paradigm, characterized by its intimate association with endosomal dysfunction and oxidative stress-induced cellular catastrophe, has demonstrated remarkable therapeutic efficacy in preclinical prostate cancer models, outperforming conventional therapeutic regimens and emerging as a potential paradigm-shifting strategy in oncology. This comprehensive review provides a critical synthesis of the triaptosis discovery landscape, elucidating its molecular intricacies and pathophysiological implications. We systematically examine the multifaceted roles of endosomal biology in oncogenesis and tumor progression, while offering a nuanced perspective on redox homeostasis in malignant cells and the therapeutic potential of oxidative stress modulation. Furthermore, we address the inherent dichotomy of oxidative stress induction in cancer therapy, balancing its therapeutic promise against potential adverse effects. Looking toward the horizon of cancer research, we explore transformative therapeutic strategies leveraging triaptosis induction and its potential applications beyond oncology, aiming to catalyze a new era of precision medicine that ultimately enhances patient survival and quality of life. Show less
no PDF DOI: 10.34133/research.0880
PIK3C3

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

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

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

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

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

Hepatic ceramide synthesis links systemic inflammation to organelle dysfunction in cancer.

Ying Liu, Ting Miao, Alice Wang +10 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Paraneoplastic syndromes arise when tumor-derived cytokines reprogram distant organs. Although mediators such as Interleukin-6 have been implicated, how these signals impair host organ function remain Show more
Paraneoplastic syndromes arise when tumor-derived cytokines reprogram distant organs. Although mediators such as Interleukin-6 have been implicated, how these signals impair host organ function remains incompletely defined. Here, we identify a cytokine-lipid axis that drives hepatic autophagy dysfunction. Specifically, in Show less
📄 PDF DOI: 10.1101/2025.10.01.679814
LPL

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

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

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

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

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

Construction and validation of a lung adenocarcinoma prognostic model based on neutrophil extracellular traps and oxidative stress-related genes.

Long Xu, Yuanyuan Zhao, Shuxi Song +3 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor micro Show more
Lung adenocarcinoma (LUAD) is a major cause of cancer-related morbidity and mortality globally, with challenges in prognosis and treatment due to its complex pathogenesis and heterogeneous tumor microenvironment (TME). Neutrophil extracellular traps (NETs) and oxidative stress play critical roles in tumor progression: NETs promote tumor cell adhesion, migration, and immune suppression, while oxidative stress induces DNA damage and activates pro-tumor signaling pathways. Moreover, oxidative stress is an important inducer of NETs, and their crosstalk shapes the LUAD immune microenvironment. However, systematic exploration of LUAD immunotherapeutic response prediction based on NETs and oxidative stress-related genes remains lacking. The gene set related to oxidative stress was obtained from MSigDB. The gene set related to NETs was sourced from relevant literature. Transcriptomic and clinical data were integrated from The Cancer Genome Atlas (TCGA)-LUAD (training set) and GSE31210 (validation set). Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to screen gene modules and characteristic scores related to NETs and oxidative stress signatures. Differentially expressed genes (DEGs) were screened, and prognostic model was established using univariate and LASSO Cox regression. Immune infiltration was analyzed using ESTIMATE algorithm, MCP-counter and ssGSEA methods. And we developed a nomogram incorporating clinicopathological features and RiskScore model, and performed drug sensitivity analysis. Finally, the biological role of CPS1 in lung cancer cells was investigated through CCK-8, wound-healing, and Transwell experiments. 22 co-expression modules were screened, among which the brown module showed significant correlations with NETs and oxidative stress signature scores. This module was intersected with DEGs, yielding 624 overlapping genes implicated in immune-relevant pathways (like leukocyte differentiation, neutrophil activation involved in immune response). A prognostic model was established utilizing 8 key genes (ADGRE3, ARHGEF3, CD79A, CLEC7A, CPS1, EPHB2, LARGE2, and OAS3). In the TCGA database, the model demonstrated robust prognostic discrimination (area under the curve (AUC) > 0.6), with high-risk patients exhibiting shorter overall survival (OS) (p < 0.05). Its stability was validated in GSE31210 (AUC > 0.6). The RiskScore showed negative correlations with immune infiltration (like T cells, CD8 T cells, and natural killer cells) as well as immune/stromal scores. A nomogram model combining RiskScore with N staging was developed and validated, demonstrating strong predictive accuracy through calibration and decision curve analyses. High-risk patients were more sensitive to drugs like BI-2536, BMS-509744, and Pyrimethamine. Finally, in vitro tests showed that CPS1 knockdown markedly decreased the viability, migration, and invasion of lung cancer cells. The constructed prognostic model by NETs and oxidative stress-relevant genes effectively predicts LUAD prognosis, correlates with immune microenvironment characteristics, and guides drug sensitivity, providing novel insights for LUAD prognostic assessment and personalized therapy. Show less
📄 PDF DOI: 10.1186/s40001-025-03553-9
CPS1

Comprehensive dietary patterns explain acquired cystic kidney disease risk through genetic and metabolomic mechanisms.

Chenhao Xu, Junjie Zhao, Kan Wu +9 more · 2025 · Frontiers in nutrition · Frontiers · added 2026-04-24
Acquired renal cysts (ARC) are associated with kidney function decline, necessitating novel dietary pattern (DP) analyses in large cohorts. This UK Biobank prospective cohort study (2006-2010) include Show more
Acquired renal cysts (ARC) are associated with kidney function decline, necessitating novel dietary pattern (DP) analyses in large cohorts. This UK Biobank prospective cohort study (2006-2010) included participants with ≥2 dietary records, excluding those with severe kidney damage. The constructed comprehensive dietary pattern integration (CDPI) utilized reduced rank regression (RRR) and latent profile analysis (LPA). ARC cases (ICD-10: N28.1) were assessed via Cox regression for risk and dose-response, with NMR metabolites examined as mediators. Among 119,709 participants (median follow-up: 10.57 years), 850 ARC cases were identified. Lipid-rich and hyperglycemic diets increased ARC risk [e.g., HRs for G1.DP1: 1.080 (1.024, 1.139); G1.DP2: 1.144 (1.048, 1.249)], while micronutrient-rich diets showed weak protective effects [G4.DP1: 0.943 (0.892, 0.998)]. LPA confirmed RRR findings, and 7/251 NMR metabolites had significant mediating effects. Diets high in fat (cheese, butter, pizza) and sugar (chocolate, sugary drinks) elevated ARC risk, whereas micronutrient- and fiber-rich diets (vegetables, fruit, lean poultry, nuts, eggs) were protective. Key mediators included branched-chain amino acids, IGF-1, and RBC distribution width. Show less
📄 PDF DOI: 10.3389/fnut.2025.1611656
LPA

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

Multi-Target Inhibitor of ZJQ- 3 F Against AChE/BACE1/GSK3β Targets Improves the Cognitive Impairment of APP/PS1/Tau Triple-Transgenic Mouse Models of Alzheimer's Disease.

Nan Wang, Xin-Zhu Li, Xiao-Wen Jiang +10 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
Alzheimer's disease (AD) is a multifactorial neuropathology characterized by the accumulation of amyloid-beta (Aβ) plaques, neurofibrillary tangles (NFTs) and cholinergic system dysfunction. At presen Show more
Alzheimer's disease (AD) is a multifactorial neuropathology characterized by the accumulation of amyloid-beta (Aβ) plaques, neurofibrillary tangles (NFTs) and cholinergic system dysfunction. At present, there is no effective treatment strategy for AD. Our previous research showed that ZJQ-3F acts as an inhibitor of AChE/BACE1/GSK3β, and showed good blood-brain barrier permeability, appropriate bioavailability and oral safety. In order to further study, the protective effect of ZJQ-3F on APP/PS1/Tau transgenic mice was determined. APP/PS1/Tau transgenic mice model of AD was treated with ZJQ-3F from the age of 8 to 12 months, and then behavioral tests was conducted. Western blot, immunohistochemistry and immunofluorescence staining were used to evaluate the level of tau protein, Aβ plaques and synaptic function. Our results revealed that administration of ZJQ-3F could improve the cognitive function of APP/PS1/Tau transgenic mice. In addition, compared with APP/PS1/Tau mice, the protein expression levels of tau protein phosphorylation site at Ser396, Thr212 and Thr181 in the cortex and hippocampus of ZJQ-3F treated mice was significantly decreased. Moreover, the results showed that ZJQ-3F significantly reduced the deposition of Aβ in the cortex and hippocampus. Furthermore, the results indicated that the protein expression levels of PSD95, SYP and SYT in the cortex and hippocampus were increased markedly after ZJQ-3F was given. Our studies suggest that the chronic administration of ZJQ-3F can improve learning and memory ability, reduce tau protein phosphorylation, reduce Aβ deposition and improve synaptic dysfunction in APP/PS1/Tau transgenic model of AD, indicating that ZJQ-3F can be used as a multi-target inhibitor to slow down the progress of AD. Show less
📄 PDF DOI: 10.1007/s12035-025-04982-7
BACE1

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

FGF19-Activated Hepatic Stellate Cells Release ANGPTL4 that Promotes Colorectal Cancer Liver Metastasis.

Xueying Fan, Baoting Li, Fan Zhang +4 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Liver and lung are the most common metastatic sites in colorectal cancer (CRC), where the tumor microenvironment (TME) plays a crucial role in the progression and metastasis of CRC. Understanding the Show more
Liver and lung are the most common metastatic sites in colorectal cancer (CRC), where the tumor microenvironment (TME) plays a crucial role in the progression and metastasis of CRC. Understanding the interactions between various types of cells in the TME can suggest innovative therapeutic strategies. Using single-cell RNA sequencing (scRNA-Seq) and clinical samples, fibroblast growth factor-19 (FGF19, rodent FGF15) is found to mediate a significant interaction between CRC cells and cancer-associated fibroblasts (CAFs), activating the hepatic stellate cells (HSCs)-to-CAFs differentiation. In various CRC metastatic mouse models, it is shown that FGF15 has a more pronounced effect on liver metastasis compared to pulmonary metastasis. More importantly, the differentially expressed genes (DEGs) are also identified from the RNA-Seq dataset upon the activation of HSCs by FGF19 and compared the DEGs in matched primary and metastatic mRNA samples from patients with CRC liver metastasis (CRCLM), it is found that the ANGPTL4 gene is significantly associated with HSCs activation. Different mouse models also demonstrated the impact of the FGF19/ANGPTL4 axis on the severity of CRCLM. Importantly, disruption of this axis significantly inhibits CRCLM in vivo. This study is among the first to demonstrate the impact of the FGF19/ANGPTL4 axis on CRCLM, offering a novel therapeutic strategy. Show less
📄 PDF DOI: 10.1002/advs.202413525
ANGPTL4

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

Stationary screen time, blood lipids, and atherosclerotic cardiovascular disease incidence.

Yunjie Liu, Lanjin Xu, Panting Liu +2 more · 2025 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24
The associations between screen time exposure, blood lipids, and Atherosclerotic Cardiovascular Disease (ASCVD) incidence have been less studied. We aimed to examine the associations of exposure to sc Show more
The associations between screen time exposure, blood lipids, and Atherosclerotic Cardiovascular Disease (ASCVD) incidence have been less studied. We aimed to examine the associations of exposure to screen time with blood total cholesterol (TC), HDL-C, LDL-C, triglycerides (TG), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and ASCVD risk score, and risk of subsequent ASCVD incidence. A nationwide sample of 7124 China Health and Nutrition Survey 2009 participants were followed up to 2015 for ASCVD incidence. The stationary screen time exposure was assessed through self-reported daily hours of using television, and computers. A total of 292 ASCVD events occurred during 35,310 follow-up person-years. Per 1-h increases in daily screen time exposure were associated with a higher 0.34% (0.12% to 0.56%), 0.47% (0.09% to 0.86%), and 0.51% (0.19% to 0.83%) increases in blood TC, LDL-C, and ApoB levels. A higher risk of incident ASCVD was associated with per log-transformed unit increase in blood LDL-C (adjusted HR = 1.51, 95% CI 1.04 to 2.18), and ApoB (adjusted HR = 1.80, 95% CI 1.12 to 2.92). The elevated blood TC, blood LDL-C, blood ApoA1 and ApoB levels significantly mediated the association between screen time exposure and ASCVD incidence. Urban dwellers, middle-aged adults, and females were particularly associated with a higher ASCVD risk with screen time exposure. The results of this nationwide cohort supported the associations of screen time exposure with elevated blood LDL-C, and ApoB levels, which consistently contributed to an increased risk of subsequent ASCVD incidence. Show less
📄 PDF DOI: 10.1186/s12872-025-04568-0
APOB

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

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

Effect of lutein supplementation on blood lipids and advanced glycation end products in adults with central obesity: a double-blind randomized controlled trial.

Juan Zhou, Shanshan Wang, Qiang Wang +11 more · 2025 · Food & function · Royal Society of Chemistry · added 2026-04-24
Central obesity poses a significant health threat. Lutein-rich fruits and vegetables may help manage obesity. Limited evidence suggests that lutein exerts health effects by inhibiting advanced glycati Show more
Central obesity poses a significant health threat. Lutein-rich fruits and vegetables may help manage obesity. Limited evidence suggests that lutein exerts health effects by inhibiting advanced glycation end products (AGEs), but data on its effects in centrally obese individuals are sparse. Thus, we aimed to investigate the effects of lutein supplementation in subjects with central obesity. A double-blind, randomized controlled trial was conducted involving patients with central obesity. Anthropometric indices, dietary intake, metabolic parameters, carotenoid and AGEs levels were compared between those receiving a 32-week intervention of 10 mg d Show less
no PDF DOI: 10.1039/d4fo05578k
APOB

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