👤 Bowen Liu

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

Advances in multi-omics for esophageal squamous cell carcinoma: Diagnostic, prognostic, and therapeutic perspectives.

Dengyun Zhao, Xinyu He, Yaping Guo +3 more · 2026 · Protein & cell · Oxford University Press · added 2026-04-24
Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in radiotherapy, chemotherapy, and immunotherapy. The ma Show more
Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in radiotherapy, chemotherapy, and immunotherapy. The marked inter-patient and intra-tumor heterogeneity of ESCC underscores the need for molecularly informed diagnostic and therapeutic strategies. Recent high-throughput omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have substantially advanced our understanding of ESCC biology. Genomic profiling has revealed recurrent alterations such as TP53 and NOTCH1 mutations, as well as actionable targets including PIK3CA, FGFR1, and SOX2 amplifications, which provide new opportunities for precision therapy. Epigenomic and transcriptomic analyses have identified methylation-based early detection markers (e.g., PAX9, SIM2) and immune-related transcriptomic subtypes associated with prognosis and immunotherapy responsiveness. Proteomic and metabolomic studies have further uncovered cell cycle and spliceosome pathway activation and altered lactate metabolism, offering additional biomarker and therapeutic insights. In this review, we synthesize these multi-omics advances and highlight how they collectively inform improved diagnostic, prognostic, and therapeutic strategies for ESCC. Despite these developments, the clinical translation of multi-omics findings remains limited due to the lack of standardized analytical pipelines, insufficient multi-center validation, and the high cost and technical complexity of integrating multi-omics data into routine clinical workflows. Future research integrating artificial intelligence with multi-omics data holds promise for enhancing diagnostic accuracy and enabling more precise therapeutic decision-making in ESCC. Show less
no PDF DOI: 10.1093/procel/pwag005
FGFR1

Recent research progress in structural optimization and cancer treatment of novel selective FGFR inhibitors (2020-2025).

Rongfei Liu, Jinghui Qi, Yue Liu +4 more · 2026 · International immunopharmacology · Elsevier · added 2026-04-24
Abnormalities in protein tyrosine kinases (PTKs) are one of the primary drivers of cancer. As a receptor subfamily, fibroblast growth factor receptors (FGFRs) comprise four subtypes-FGFR1 to FGFR4. Th Show more
Abnormalities in protein tyrosine kinases (PTKs) are one of the primary drivers of cancer. As a receptor subfamily, fibroblast growth factor receptors (FGFRs) comprise four subtypes-FGFR1 to FGFR4. Their abnormal intracellular expression is a significant cause of tumorigenesis, making FGFRs key therapeutic targets in cancer treatment. This paper primarily summarizes the latest research advances in FGFR inhibitors, aiming to provide insights for future design and synthesis studies of FGFR inhibitors. Show less
no PDF DOI: 10.1016/j.intimp.2026.116249
FGFR1

Endogenous FGFs drive ERK-dependent cell fate patterning in 2D human gastruloids.

Kyoung Jo, Zong-Yuan Liu, Gauri Patel +6 more · 2026 · Development (Cambridge, England) · added 2026-04-24
The role of FGF is the least understood of the morphogens driving mammalian gastrulation. Here, we have investigated FGF function in a 2D gastruloid model for human gastrulation. We observed a ring of Show more
The role of FGF is the least understood of the morphogens driving mammalian gastrulation. Here, we have investigated FGF function in a 2D gastruloid model for human gastrulation. We observed a ring of FGF-dependent ERK activity that closely follows the emergence of primitive streak (PS)-like cells but expands further inward. This ERK activity pattern depends on localized activation of basolateral FGF receptor 1 (FGFR1) by endogenous FGF gradients and is required for PS-like differentiation, with loss of PS-like cells upon FGF receptor inhibition rescued by direct ERK activation. Single cell transcriptome analysis confirmed that, among the ligands, FGF2 is broadly expressed, FGF8 is transiently expressed during PS-like differentiation and FGF4/17 are specifically expressed in PS-like cells - similar to the human and monkey embryo but different from the mouse. FGF4 knockdown greatly reduced PS-like differentiation, while FGF17 knockdown primarily affected subsequent mesoderm differentiation. FGF8 expression was spatially and temporally displaced from PS markers and FGF4 expression, while knockdown expanded PS-like cells, suggesting FGF8 may limit PS-like differentiation. Thus, we have identified a previously unreported role for FGF-dependent ERK signaling in 2D gastruloids and possibly the human embryo, where FGF4 and FGF17 signal through basolateral FGFR1 to induce PS-like cells and derivatives, potentially restricted by FGF8. Show less
no PDF DOI: 10.1242/dev.205459
FGFR1

Bioinspired scaffold recapitulating chondrogenic ontogeny and microenvironment for functional cartilage regeneration.

Tianyu Yu, Xun Sun, Yang Liu +13 more · 2026 · Bioactive materials · Elsevier · added 2026-04-24
Focal articular cartilage defects often progress to osteoarthritis, imposing a substantial global health burden. Current neglect of cartilage developmental regulation and cartilage microenvironment co Show more
Focal articular cartilage defects often progress to osteoarthritis, imposing a substantial global health burden. Current neglect of cartilage developmental regulation and cartilage microenvironment compromises therapeutic efficacy. We developed an innovation CE-SKP/CPH/P2G3 scaffold which effectively repairs focal cartilage defects and emulates native cartilage ontogeny: the superficial CE-SKP hydrogel layer recruits SMSCs and promotes chondrogenesis; the middle CPH hydrogel layer induces chondrocyte hypertrophic calcification, forming cartilage calcified layer; and the basal P2G3 nanofiber membrane isolates subchondral cells, enforcing a top-down developmental sequence and preserving a localized hypoxic niche. Show less
📄 PDF DOI: 10.1016/j.bioactmat.2025.11.041
FGFR1

20(S)-PPD-HSA NPs enhance the recovery of intramedullary and extramedullary hematopoiesis in cyclophosphamide-treated mice through activation of the FGFR1/ERK pathway.

Dalei Li, Mengjun Yan, Mingyan Yang +5 more · 2026 · International immunopharmacology · Elsevier · added 2026-04-24
Chemotherapy-induced myelosuppression (MYE) remains a major dose-limiting toxicity that severely compromises treatment efficacy and patient outcomes, while effective therapeutic agents are still lacki Show more
Chemotherapy-induced myelosuppression (MYE) remains a major dose-limiting toxicity that severely compromises treatment efficacy and patient outcomes, while effective therapeutic agents are still lacking. This study aimed to evaluate the therapeutic effects of 20(S)-protopanaxadiol-human serum albumin nanoparticles (20(S)-PPD-HSA NPs) on cyclophosphamide-induced MYE and to elucidate the underlying mechanisms. 20(S)-PPD-HSA NPs were characterized by electron microscopy, particle size, zeta potential, drug loading, and encapsulation efficiency. A cyclophosphamide-induced MYE mouse model was established. Hematopoietic recovery was evaluated via blood counts, ELISA for granulocyte colony-stimulating factor (G-CSF), and flow cytometry for Lin The 20(S)-PPD-HSA NPs exhibited a uniform nanostructure and excellent drug delivery performance. In vivo, the 20(S)-PPD-HSA NPs significantly alleviated cyclophosphamide-induced hematopoietic dysfunction, restored the structure of bone marrow and spleen tissues, and markedly increased the number of LSK cells, with their therapeutic effect being independent of elevated G-CSF levels. Further studies demonstrated that the 20(S)-PPD-HSA NPs activated the FGFR1/ERK signaling pathway, an effect that was partially blocked by FGFR1 or ERK inhibitors. In vitro, 20(S)-PPD-HSA NPs promoted the proliferation of OP9 cells and murine splenic stromal cells, inhibited apoptosis, DNA damage, and cellular senescence, and upregulated SCF and SDF-1 expression via activation of the FGFR1/ERK pathway. Co-culture experiments further confirmed that the NPs improved the hematopoietic microenvironment and enhanced the stromal cells' hematopoietic support function. 20(S)-PPD-HSA NPs effectively enhanced medullary and extramedullary hematopoietic functions in cyclophosphamide-induced MYE mice by activating the FGFR1/ERK pathway, independent of increased G-CSF levels. These findings highlight 20(S)-PPD-HSA NPs as a promising therapeutic strategy for chemotherapy-induced myelosuppression. Show less
no PDF DOI: 10.1016/j.intimp.2025.116073
FGFR1

Exposure-response analyses of pemigatinib in patients with myeloid/lymphoid neoplasms with fibroblast growth factor receptor 1 rearrangement.

Xiaohua Gong, Ayman Akil, Boris Grinshpun +6 more · 2026 · Journal of chemotherapy (Florence, Italy) · Taylor & Francis · added 2026-04-24
Pemigatinib is a selective, potent, orally administered inhibitor of fibroblast growth factor receptor (FGFR)1-3 with antitumor activity in multiple solid tumors. Pemigatinib is used to treat adults w Show more
Pemigatinib is a selective, potent, orally administered inhibitor of fibroblast growth factor receptor (FGFR)1-3 with antitumor activity in multiple solid tumors. Pemigatinib is used to treat adults with previously treated metastatic or surgically unresectable cholangiocarcinoma with Show less
no PDF DOI: 10.1080/1120009X.2025.2497641
FGFR1

GATA6 inhibits the periodontitis progression through regulating the Notch signaling pathway.

Wen-Wen Li, Qing-Wei Li, Jia Yu +4 more · 2026 · Odontology · Springer · added 2026-04-24
Periodontitis is a prevalent chronic infectious condition affecting the oral cavity. This research was conducted to analyze the role of GATA6 in LPS-stimulated human periodontal ligament cells (hPDLCs Show more
Periodontitis is a prevalent chronic infectious condition affecting the oral cavity. This research was conducted to analyze the role of GATA6 in LPS-stimulated human periodontal ligament cells (hPDLCs). Dysregulated genes associated with periodontitis were acquired from the GEO database (GSE23586). Cell viability was measured utilizing the MTT assay, while apoptosis was analyzed through flow cytometry. The expression levels of mRNA and proteins were examined using qRT-PCR and Western blot techniques, respectively. Levels of IL-1β, IL-6, and TNF-α were measured using specific ELISA kits. The mouse periodontitis model was established to evaluate the effect of GATA transcription factor 6 (GATA6) in vivo.The results demonstrated that GATA6 was downregulated in periodontitis and LPS-stimulated hPDLCs. Overexpression of GATA6 enhanced cell viability, while inhibited apoptosis in hPDLCs. It also reduced the levels of IL-1β, IL-6, and TNF-α in LPS-stimulated hPDLCs. Additionally, after transfection with a GATA6 overexpression vector, the expressions of Caspase 3 and Bax proteins were suppressed, while Bcl2 was upregulated. Furthermore, in LPS-stimulated hPDLCs, the protein levels of Notch1, Hey1, and Hey2 were enhanced after GATA6 overexpression. Silencing of Notch1 neutralized the effects of GATA6 in LPS-stimulated hPDLCs. In addition, GATA6 overexpression alleviated the progression of periodontitis in vivo. In conclusion, GATA6 alleviated the progression of periodontitis by activating the Notch signaling pathway. Show less
📄 PDF DOI: 10.1007/s10266-025-01173-7
HEY2

Transcriptomic and metabolomic analysis of metabolite changes and regulatory mechanisms associated with gonadal degeneration in yellow oil crab (Scylla paramamosain).

Biwei Wu, Jianye Chang, Hailin Liu +2 more · 2026 · BMC genomics · BioMed Central · added 2026-04-24
The yellow oil crab is a highly valuable aquatic species, with the accumulation of nutritional and flavor compounds closely linked to the degree of gonadal degeneration. However, the molecular mechani Show more
The yellow oil crab is a highly valuable aquatic species, with the accumulation of nutritional and flavor compounds closely linked to the degree of gonadal degeneration. However, the molecular mechanisms of gonadal degeneration remain unclear. In this study, we analyzed the differences in gene expression and metabolite accumulation across three gonadal degeneration stages (QX, GX, and TSX) in yellow oil crab using transcriptome and non-targeted metabolomics approaches, and identified key genes and metabolites involved. A total of 240 differential accumulated metabolites (DAMs) were identified, most of which were significantly more highly accumulated in GX and TSX than in QX. K-means clustering analysis of DAMs and gene expression data revealed distinct stage-specific expression patterns from QX to TSX stage. Moreover, the “steroid hormone biosynthesis” pathway was significantly enriched, with 15 highly expressed steroid hormones and their derivatives in GX and TSX. 7 types of key genes involved in steroid hormone biosynthesis (such as Therefore, the identified differential steroid hormones and seven key genes were positively associated with gonadal degeneration in yellow oil crab. These results offer a theoretical basis for understanding the formation and aquaculture of the yellow oil crab. The online version contains supplementary material available at 10.1186/s12864-026-12597-y. Show less
📄 PDF DOI: 10.1186/s12864-026-12597-y
HSD17B12

The lipid-metabolic enzyme HSD17B12 drives lysosomal degradation of PD-L1 potentiating anti-tumor immunity in a mouse model.

Zhihui Zhou, Ying Lu, Pan Li +5 more · 2026 · PLoS biology · PLOS · added 2026-04-24
The high prevalence of cancer immunotherapy resistance, coupled with substantial tumor heterogeneity, underscores the urgent need for innovative therapeutic targets. A deeper understanding of immunore Show more
The high prevalence of cancer immunotherapy resistance, coupled with substantial tumor heterogeneity, underscores the urgent need for innovative therapeutic targets. A deeper understanding of immunoregulatory mechanisms would provide new targets and combination therapeutic strategies for tumor therapy. In this study, we demonstrate that HSD17B12 enhances anti-tumor immunity and represents a promising therapeutic target. Mechanistically, HSD17B12 promotes lysosome-dependent degradation of PD-L1 via the VAC14 and ESCRT complexes across various malignancies, regardless of its 3-ketoacyl-CoA reductase activity. HSD17B12-deficient cells displayed PD-L1 accumulation in both tumor cells and exosomes, reducing T cell-mediated cytotoxicity. Notably, we found a significant negative correlation between HSD17B12 and PD-L1 expression in colorectal cancer tissues. Furthermore, high HSD17B12 expression in CRC correlated with increased infiltration of cytotoxic T cells. Based on these findings, we designed a peptide, HSD-CC1-NPGY, which effectively reduces PD-L1 expression in cells and suppresses tumor growth in a mouse model. Overall, our results establish HSD17B12 as an important regulator of anti-tumor immunity and a promising therapeutic target for cancer treatment. Show less
📄 PDF DOI: 10.1371/journal.pbio.3003603
HSD17B12

Interleukins in community-acquired pneumonia: from biomarkers to precision medicine.

Xiaoying Zhang, Tongshuo Zhang, Ruihui Geng +3 more · 2026 · Frontiers in immunology · Frontiers · added 2026-04-24
Community-acquired pneumonia (CAP) is still a leading cause of death due to infection globally, yet precise severity assessment remains a significant clinical problem. More than any other group of cyt Show more
Community-acquired pneumonia (CAP) is still a leading cause of death due to infection globally, yet precise severity assessment remains a significant clinical problem. More than any other group of cytokines, interleukins are central to the regulation of inflammation and shed light on this intricate pathology. In the present review we summarize the biological and clinical characteristics of some of the principal interleukins (ILs) in CAP, classified primarily according to their physiological activity as pro-inflammatory (IL-2, IL-6, IL-8 and IL-12), anti-inflammatory (IL-7, IL-10 and IL-37), dual-action (IL-4 and IL-17), and emerging factors (IL-3, IL-27 and IL-33). Additionally, recent multimodal approaches are discussed such as combining cytokines with organ dysfunction parameters (MR-proADM) or revealing host-response patterns to inform antibiotic and corticosteroid management. We propose that the field needs to transition to immunological endotyping, multi-omics (integrating genetics and lung microbiome), and artificial intelligence (AI) models based on dynamic patient data to achieve precision medicine in CAP management. Show less
📄 PDF DOI: 10.3389/fimmu.2026.1774731
IL27

Lactobacillus rhamnosus confers protection against enteropathogenic bacteria by enhancing mucosal immunity and epithelial barrier function.

Xuwen Gao, Jiangfei Zhou, Kai Yan +7 more · 2026 · Frontiers in cellular and infection microbiology · Frontiers · added 2026-04-24
Probiotics such as The intestinal colonization ability of CIQ249 was assessed using cFDA-SE labeling and flow cytometry. Growth performance and intestinal morphology were evaluated in mice. Antimicrob Show more
Probiotics such as The intestinal colonization ability of CIQ249 was assessed using cFDA-SE labeling and flow cytometry. Growth performance and intestinal morphology were evaluated in mice. Antimicrobial activity of CIQ249 cell-free supernatant was tested against various pathogens, and pathogen damage was visualized by scanning electron microscopy. Protective effects against CIQ249 demonstrated strong intestinal colonization and increased villus height and the villus-to-crypt ratio, contributing to improved growth performance. Its cell-free supernatant selectively inhibited enteropathogens and induced structural damage in CIQ249 enhances mucosal defense against enteropathogenic bacteria through a dual mechanism-strengthening the epithelial barrier and activating a coordinated DC-Tfh-IgA immune axis. These findings provide a multi-level mechanistic basis for its application as a microecological agent against intestinal infections. Show less
📄 PDF DOI: 10.3389/fcimb.2026.1769889
IL27

Interplay between obesity-associated insulin resistance and immune system through the lens of evolutionary medicine.

Maryam Moazzam-Jazi, Saeideh Jafarinejad-Farsangi, Leila Najd-Hassan-Bonab +4 more · 2026 · Molecular metabolism · Elsevier · added 2026-04-24
Insulin resistance (IR), commonly associated with obesity, is linked to a range of metabolic and immune-related disorders in the contemporary human population. Nevertheless, it is evolutionary well-co Show more
Insulin resistance (IR), commonly associated with obesity, is linked to a range of metabolic and immune-related disorders in the contemporary human population. Nevertheless, it is evolutionary well-conserved, suggesting its potential survival advantages to our ancestors. This review aims to explore the intricate interplay between IR and the immune system as well as its implications for the development of immune-metabolic and allergic diseases in the modern era. From an evolutionary medicine perspective, the longevity of ancient humans relied on energy storage to endure food shortages and effectively activate the immune system against various diseases. Under normal conditions, insulin induces glycogen and triglyceride synthesis in the liver and adipose tissues. However, IR directs more glucose to insulin-independent tissues, such as the immune system, which are critical for survival in adverse conditions. The persistent IR in our current lifestyle promotes low-grade inflammation, accompanied by various metabolic and allergic disorders. Critically, this evolutionary mismatch not only explains disease susceptibility but also informs therapeutic design to target immune-metabolic crosstalk. Moreover, our evolutionary analysis demonstrates that the genomic regions near the PTEN, IL27, and NUPR1 genes could play an important role in this interaction across diverse populations. Show less
📄 PDF DOI: 10.1016/j.molmet.2026.102335
IL27

IL-27 signaling mediates skin inflammation in experimental psoriasis and atopic dermatitis.

Zeyu Chen, Lian Cui, Zhiyi Lan +14 more · 2026 · Cell & bioscience · BioMed Central · added 2026-04-24
Psoriasis and atopic dermatitis (AD) are two prevalent inflammatory skin disorders, each characterized by distinct adaptive immune responses. However, recent evidence suggests that these diseases may Show more
Psoriasis and atopic dermatitis (AD) are two prevalent inflammatory skin disorders, each characterized by distinct adaptive immune responses. However, recent evidence suggests that these diseases may share overlapping immune mechanisms, especially concerning keratinocyte function. The specific cytokines that coordinate these inflammatory pathways remain largely undefined. The expression of IL-27 and its receptor was analyzed using data derived from GEO datasets. Imiquimod-induced psoriasis-like and MC903-induced AD-like skin inflammation models were established in wild-type and Il27ra knockout littermates. Skin inflammation was evaluated using clinical scoring, histology, and immunostaining. Flow cytometry was employed to characterize immune cell populations in skin. Expression of relevant cytokines and signaling molecules was assessed using quantitative PCR, bulk RNA sequencing, and Western blotting. We found significantly elevated expression of the IL-27 receptor in the lesional skin of patients with psoriasis or AD. IL-27 receptor-deficient mice exhibited markedly reduced skin inflammation in both psoriasis-like and AD-like murine models. Mechanistic investigations revealed that IL-27 induces tumor necrosis factor-α production via signal transducer and activator of transcription 1 activation in keratinocytes, thereby potentiating inflammatory responses. Our findings identify IL-27 signaling in keratinocytes as a pivotal regulator of skin inflammation in both psoriasis and AD. This highlights IL-27 as a promising therapeutic target for inflammatory skin diseases. Show less
📄 PDF DOI: 10.1186/s13578-025-01527-2
IL27

Endothelial JMJD1C drives pathological ocular neovascularization by activating SREBF2-dependent cholesterol biosynthesis.

Yang Yu, Zhangyu Liu, Jiayu Huang +6 more · 2026 · Free radical biology & medicine · Elsevier · added 2026-04-24
Pathological ocular neovascularization is closely linked to aberrant histone modifications, yet the underlying molecular mechanisms remain incompletely defined. This study investigates the role of the Show more
Pathological ocular neovascularization is closely linked to aberrant histone modifications, yet the underlying molecular mechanisms remain incompletely defined. This study investigates the role of the histone demethylase JMJD1C and its encoding gene Jmjd1c in driving pathological angiogenesis and evaluates its therapeutic potential in ocular proliferative vascular diseases. Jmjd1c expression was examined in mouse models of ocular neovascularization and in endothelial cells (ECs) using immunostaining, qRT-PCR, and Western blotting. The pro-angiogenic functions of JMJD1C were assessed through EdU incorporation, Transwell migration, tube-formation, and spheroid-sprouting assays in vitro, as well as retinal flat-mount isolectin-B4 staining and H&E staining in vivo. RNA sequencing, immunostaining, qPCR, Western blotting, and ChIP-qPCR were employed to dissect the molecular mechanisms by which JMJD1C regulates pathological angiogenesis. Endothelial-specific deletion of Jmjd1c markedly reduced pathological neovascularization in both oxygen-induced retinopathy (OIR) and laser-induced choroidal neovascularization (CNV) models. Loss of JMJD1C impaired endothelial cell proliferation, migration, tube formation, and sprouting angiogenesis. Mechanistically, Jmjd1c deletion suppressed Srebf2 transcription and cholesterol biosynthesis by increasing repressive H3K9me2 histone marks in endothelial cells. Pharmacological inhibition of JMJD1C similarly attenuated neovascularization in wild-type mice. JMJD1C acts as a key regulator of pathological ocular angiogenesis through histone demethylation-mediated control of endothelial cholesterol biosynthesis. These findings establish JMJD1C and the Jmjd1c-Srebf2 regulatory axis as promising therapeutic targets for ocular vascular diseases. Show less
no PDF DOI: 10.1016/j.freeradbiomed.2026.01.024
JMJD1C

Human blood cell traits and sporadic lymphangioleiomyomatosis: results from mediation joint multi-omics and eQTL Mendelian randomization analysis.

Tianshu Liu, Yiting Cai · 2026 · Orphanet journal of rare diseases · BioMed Central · added 2026-04-24
To investigate the genetic causality between Human blood cell (HBC) traits and sporadic lymphangioleiomyomatosis (sLAM) by mediation joint multi-omics and eQTL Mendelian randomization analysis. Qualit Show more
To investigate the genetic causality between Human blood cell (HBC) traits and sporadic lymphangioleiomyomatosis (sLAM) by mediation joint multi-omics and eQTL Mendelian randomization analysis. Quality control processes were followed to select eligible instrumental variables strongly associated with 35 kinds of HBC traits. Independent cohort of European ancestry with sLAM and lung function genome-wide association study (GWAS) summary statistics were used separately. We utilized a two-step MR approach to explore potential mediators and evaluate the proportion of effect mediated in the associations linking HBC trait candidates to sLAM. Finally MR analysis integrating single cell expression quantitative trait loci (sc-eQTL) from 14 immune cell types with GWAS of sLAM was conducted. Increased level of basophil count was positively associated with higher risk of sLAM (BASO#; OR = 3.878, 95%CI:1.137–13.221, For the first time, this study leverages mediation analysis and multi-omics MR integrated with sc-eQTL data to elucidate the roles of HBC traits, immune cells, inflammatory proteins, VEGF-related proteins and immune cell-specific genes in the pathogenesis of sLAM among the European populations. The online version contains supplementary material available at 10.1186/s13023-026-04224-6. Show less
📄 PDF DOI: 10.1186/s13023-026-04224-6
KANSL1

The KANSL1-ARL17A fusion gene generates oncogenic chKANSARL and F-circKA RNAs that synergistically drive lung cancer progression via a novel F-circKA/miR-6860/chKANSARL axis.

Xinchao Guan, Tao Liu, Sili Chen +4 more · 2026 · The Journal of biological chemistry · Elsevier · added 2026-04-24
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to c Show more
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to cancer progression remain poorly understood. Here, we identified a lung cancer-specific chimeric RNA KANSL1-ARL17A (chKANSARL) and its circular variant fusion circular RNA KANSL1-ARL17 A (F-circKA), both derived from the fusion gene KANSARL. Functional assays revealed that overexpression of either chKANSARL or F-circKA significantly enhanced lung cancer cell proliferation, migration, and invasion, while their knockdown suppressed these malignant phenotypes. In vivo experiments demonstrated that chKANSARL overexpression accelerated tumor growth in immunodeficient mice. Notably, coexpression experiments uncovered a synergistic regulatory interaction between F-circKA and chKANSARL, amplifying oncogenic effects. Mechanistically, miRNA sequencing and dual-luciferase assays revealed that F-circKA acts as a molecular sponge for miR-6860, thereby derepressing chKANSARL expression. Rescue experiments further validated this regulatory axis, wherein miR-6860 inhibition reversed the tumor-suppressive effects of F-circKA knockdown. Collectively, our study identifies and characterizes a novel F-circKA/miR-6860/chKANSARL regulatory axis, revealing how dual transcriptional outputs from the KANSARL fusion gene can synergistically drive lung cancer progression. These findings highlight a previously unrecognized layer of cooperative regulation between linear and circular fusion RNAs in oncogenesis and provide a new framework for understanding fusion gene-mediated tumorigenesis. Show less
📄 PDF DOI: 10.1016/j.jbc.2026.111170
KANSL1

AKAP12-LMOD1 signaling defines stromal CAF activation and epithelial junction loss in colorectal cancer.

Qian-Wen Ye, Yuan-Jie Liu, Guo Xu +2 more · 2026 · Scientific reports · Nature · added 2026-04-24
Colorectal cancer (CRC) shows strong heterogeneity in tumor microenvironment (TME) dynamics, but the mechanisms that shape epithelial-stromal crosstalk are still unclear. Here we focus on A-kinase anc Show more
Colorectal cancer (CRC) shows strong heterogeneity in tumor microenvironment (TME) dynamics, but the mechanisms that shape epithelial-stromal crosstalk are still unclear. Here we focus on A-kinase anchor protein 12 (AKAP12) and Leiomodin 1 (LMOD1) and test a compartment-dependent model in which this program aligns with tight-junction features in epithelium but with a fibrotic, immune-suppressive program in stroma. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were employed to profile gene expression patterns in CRC tissues. Immunohistochemistry (IHC) and multiplex immunofluorescence (mIF) validated protein expression and localization. Cell-cell communication analysis and trajectory inference were used to dissect spatial interaction networks. Functional experiments were employed to validate the role of the AKAP12-LMOD1 axis in CAFs in regulating ECM remodeling and antitumor immunity. AKAP12-LMOD1 exhibited a compartment-dependent pattern in CRC. In ACTA2⁻ epithelial regions, the epithelial AKAP12-LMOD1 signal was lower in tumors than in matched normal epithelium and showed a positive association with the tight-junction marker CLDN1. In ACTA2⁺ stromal regions, AKAP12-LMOD1 was enriched, positively associated with the gap-junction marker GJA4, and higher in tumor stroma than matched normal stroma. In a CAF-macrophage non-contact co-culture model, AKAP12 overexpression supported CAF activation and collagen deposition, and shifted macrophages toward an M2-like phenotype; LMOD1 knockdown or SB-431542 partially reversed these effects. Stromal AKAP12-LMOD1-enriched regions also aligned with fibrosis- and M2-related features, and these stromal patterns were prominent in mucinous carcinoma. This study defines AKAP12-LMOD1 as a compartment-dependent stromal program in CRC that links ACTA2⁺ stroma to gap-junction features, fibrosis, and M2-like macrophage polarization, while showing a distinct epithelial association with tight-junction features. These findings support a stroma-centered working model for AKAP12-LMOD1 in CRC microenvironmental heterogeneity and suggest that stromal modulation of this program, together with targeting fibrosis and M2-like immune features, may be explored as hypothesis-level, subtype-oriented therapeutic directions in stroma-rich CRC. Show less
no PDF DOI: 10.1038/s41598-026-44680-5
LMOD1

Association between device-measured physical activity and aortic aneurysm risk: a prospective cohort study of 93165 UK biobank participants.

Shaohua Yan, Changyan Zhu, Yuqiu Hu +6 more · 2026 · Nutrition, metabolism, and cardiovascular diseases : NMCD · Elsevier · added 2026-04-24
Aortic aneurysm (AA) is a life-threatening vascular disease with high fatality upon rupture. While physical activity (PA) reduces cardiovascular risk, its role in AA prevention remains uncertain, part Show more
Aortic aneurysm (AA) is a life-threatening vascular disease with high fatality upon rupture. While physical activity (PA) reduces cardiovascular risk, its role in AA prevention remains uncertain, particularly when assessed objectively. We analyzed 93,165 UK Biobank participants (56% women; median age 57 years) with valid 7-day wrist-worn accelerometer data. PA was categorized as light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA). Diagnosed AA was ascertained through linked hospital, death, and primary care records. Cox models estimated hazard ratios (HRs) for AA across quartiles and per-standard deviation (SD) increments, with adjustment for demographic, lifestyle, and cardiometabolic factors. Over a median 7.9-year follow-up, 499 clinically recorded AA cases occurred. Higher accelerometer-measured PA was inversely associated with AA risk. Per-SD increments in total PA, MPA, VPA, and MVPA corresponded to 17%, 22%, 19%, and 23% lower risks, respectively. Compared with the lowest quartile, the highest MVPA quartile had a 44% lower AA risk (HR = 0.56, 95% CI 0.42-0.76). Subtype analyses revealed stronger protective effects for abdominal aortic aneurysm (AAA) than thoracic aortic aneurysm (TAA), while LPA was not significantly associated. These findings demonstrate that higher levels of accelerometer-measured MVPA are robustly associated with a decreased risk of clinically detected AA in a dose-dependent manner. The associations were particularly pronounced for AAA. This study provides objective evidence supporting the potential benefits of MVPA for aortic health. Show less
no PDF DOI: 10.1016/j.numecd.2026.104715
LPA

Associations of physical activity intensity with the non-high-density lipoprotein to high-density lipoprotein cholesterol ratio and mortality in middle-aged and older adults: New evidence from China.

Fangyu Zhao, Xuemin Peng, Yongbin Zhuang +4 more · 2026 · Experimental gerontology · Elsevier · added 2026-04-24
The non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a comprehensive lipid index reflecting the balance between atherogenic and anti-atherogenic lipopro Show more
The non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a comprehensive lipid index reflecting the balance between atherogenic and anti-atherogenic lipoproteins. However, evidence on how different intensities and durations of physical activity (PA) influence NHHR remains scarce, particularly in aging populations. Data were obtained from China Health and Retirement Longitudinal Study. PA was self-reported and categorized as high- (HPA), moderate- (MPA), or low-intensity (LPA). Multivariable linear regression models assessed associations between PA and NHHR, with subgroup, sensitivity, and dose-response analyses further exploring robustness. Cox regression and mediation analyses examined the associations of PA and NHHR with 10-year all-cause mortality. Higher levels of total, moderate-, and high-intensity PA were significantly associated with lower NHHR. The results were generally consistent with a graded pattern, with lower NHHR observed at higher activity durations, particularly for moderate-to-vigorous activity. Exploratory mediation analyses suggested that NHHR may partially account for the inverse association between PA and mortality. This study adds large-scale, population-based evidence on the associations between different PA intensities and NHHR. Regular moderate-to-vigorous PA is associated with more favorable lipid profiles and lower mortality risk. These findings highlight NHHR as a valuable biomarker linking physical activity to cardiometabolic health and longevity in middle-aged and older adults. Show less
no PDF DOI: 10.1016/j.exger.2026.113098
LPA

Levosimendan inhibits HIV-1 infection in myeloid cells in the RIOK1-dependent manner.

Jinshan He, Jie Ma, Youngmin Park +10 more · 2026 · bioRxiv : the preprint server for biology · added 2026-04-24
Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, includ Show more
Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, including circulating monocytes and tissue-resident macrophages, and integrates with host genomes to form stable viral reservoirs. To achieve a functional HIV cure, latency-promoting agents (LPAs) have been developed for the "block-and-lock" strategy to reinforce deep HIV-1 latency and permanently silence proviruses. However, most LPAs have been tested mainly in CD4 Show less
no PDF DOI: 10.64898/2026.04.08.717218
LPA

When high hopes meet low action: identifying the "Ambitious Procrastinator" profile in the physical activity intention-behavior gap and its mental health toll.

Xishan Liu, Peijun Wei · 2026 · Frontiers in psychology · Frontiers · added 2026-04-24
University students exhibit high rates of mental health problems alongside a significant gap between their physical activity (PA) intentions and actual behavior. To understand the psychological hetero Show more
University students exhibit high rates of mental health problems alongside a significant gap between their physical activity (PA) intentions and actual behavior. To understand the psychological heterogeneity within this intention-behavior gap (IBG) in high-pressure academic environments, a person-centered approach is essential. The present study aimed to identify distinct psychological profiles of students based on key self-regulatory constructs related to PA and to examine how these profiles longitudinally predict changes in mental health over an academic semester. A two-wave longitudinal survey was conducted with a cohort of 850 university students during the post-pandemic return to campus life, situated within a high-achieving Chinese higher education context. At baseline (T1), PA intention, action and coping planning, self-efficacy, maladaptive perfectionism, and procrastination were measured. At both T1 and the end of the semester (T2), PA behavior (IPAQ-SF) and mental health outcomes, including depression (PHQ-9), anxiety (GAD-7), and academic burnout (SBI) were assessed. Latent Profile Analysis (LPA) was employed to identify distinct profiles from the T1 psychological data. Longitudinal regression models were then used to test the predictive validity of these profiles on T2 mental health, controlling for T1 baseline mental health, demographic covariates, and critically, T1 baseline PA behavior. LPA revealed four distinct profiles: "Effective Planners" (25.0%), "Ambitious Procrastinators" (30.0%), "Cautious Doers" (24.9%), and "Indifferent & Sedentary" (20.1%). The "Ambitious Procrastinators" exhibited the largest intention-behavior gap. Even after controlling for baseline PA behavior, membership in this profile significantly predicted greater increases in depression ( The physical activity intention-behavior gap is not a monolithic phenomenon, and the "Ambitious Procrastinators" represent a particularly vulnerable subgroup. Findings suggest that university wellness programs should move beyond generic motivational campaigns and instead deliver tailored, skill-based interventions**, such as specific cognitive restructuring and behavioral activation, **targeting the specific self-regulatory deficits of these high-risk students. Show less
📄 PDF DOI: 10.3389/fpsyg.2026.1804409
LPA

Associations of psychological capital latent profiles with depression and anxiety: A cross-sectional study in Chinese college students.

Yi Liu, Lingeng Lu, Yongcheng Yao · 2026 · Public health · Elsevier · added 2026-04-24
The purposes of this study were to identify different psychological capital subtypes among college students through latent profile analysis (LPA) and to explore the associations of psychological capit Show more
The purposes of this study were to identify different psychological capital subtypes among college students through latent profile analysis (LPA) and to explore the associations of psychological capital subtypes, internet usage duration and physical exercise frequency with on both depression and anxiety. Cross-sectional study design was implemented. A cross-sectional survey was conducted using the "Questionnaire Star" platform. The questionnaires of Psychological Capital Scale, PHQ-9, and GAD-7 were administered to 1089 college students from a university in Zhengzhou, China. Latent profile analysis was applied to identify latent subtypes of psychological capital. Multivariate regression analysis was performed to investigate the associations of psychological capital subtypes with both depression and anxiety. Three psychological capital latent profiles were identified: low self-efficacy (11.7%), moderate (57.8%), and high psychological capital (30.5%) in Chinese college students. High psychological capital group showed significantly higher scores of self-efficacy, resilience, hope, and optimism than other two groups (P < 0.001). Internet usage time and physical exercise frequency exhibited positive associations with psychological capital subtypes. Compared with the low self-efficacy group, the moderate and high latent groups had significantly lower scores of both depression and anxiety. Older students had higher scores of both depression and anxiety than younger. Three latent profiles, low self-efficacy, moderate, and high psychological capital, were identified in Chinese college students. Self-efficacy is the key dimension distinguishing between the different subtypes. Adequate internet use and physical exercise frequency improved psychological capital profile. High psychological capital levels effectively reduced the scores of both depression and anxiety. Show less
no PDF DOI: 10.1016/j.puhe.2026.106275
LPA

Latent Profile Analysis of Depressive Symptoms and Their Associated Factors Among Older Adults in Chinese Nursing Homes: Identification of Three Distinct Symptom Profiles.

Jianlei Liu, Yaling Cui, Hongyu Wang +2 more · 2026 · Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · Blackwell Publishing · added 2026-04-24
With global population aging, the number of older adults in Chinese nursing homes is rising rapidly, and depression is the most prevalent mental health problem in this population. Most previous studie Show more
With global population aging, the number of older adults in Chinese nursing homes is rising rapidly, and depression is the most prevalent mental health problem in this population. Most previous studies assessed depression via total scale scores, ignoring individual heterogeneity of depressive symptoms. This study aimed to identify distinct depressive symptom profiles and their associated factors in this population. Data were derived from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), with 353 valid nursing home older adults included. Depressive symptoms, anxiety and functional status were assessed using the CESD-10, GAD-7 and IADL scales. Latent profile analysis (LPA), univariate tests and multinomial logistic regression were performed, with supplementary effect size and sensitivity analyses to verify result robustness. Three distinct depressive symptom profiles were identified: low level (39%, n = 135), medium level (52%, n = 187) and high level (9%, n = 31). Town residence and anxiety were risk factors for moderate depression, while good self-rated health, regular exercise and social activity participation were protective factors. Good self-rated health protected against severe depression, while occasional television/radio viewing and anxiety were risk factors. Anxiety was the only independent correlate of high-level versus medium-level depression (OR = 1.322, p < 0.001). Supplementary analyses confirmed the robustness of core findings. The CESD-10, as a screening tool, has limited diagnostic efficacy for clinical depression, and the cross-sectional design cannot confirm causal relationships. Depressive symptoms in Chinese nursing home older adults show significant heterogeneity with three distinct latent profiles. Early screening and targeted stratified interventions should be implemented for this population to improve quality of life and promote healthy aging. Show less
no PDF DOI: 10.1111/psyg.70166
LPA

Obesity, physical activity, and gene-environment interactions: a natural experiment framework.

Lei Liu, Xuxiu Zhuang, Haonan Zhou +4 more · 2026 · Journal of health, population, and nutrition · BioMed Central · added 2026-04-24
Obesity results from the interaction of polygenic susceptibility and environmental factors. Given this complex etiology, physical activity (PA) remains a cornerstone of cost-effective intervention str Show more
Obesity results from the interaction of polygenic susceptibility and environmental factors. Given this complex etiology, physical activity (PA) remains a cornerstone of cost-effective intervention strategies. This longitudinal natural experiment investigated how PA modifies the effects of genetic predisposition on obesity in Chinese youth. We conducted a 4-year natural experiment leveraging curriculum-driven PA disparities in a specialized arts school (n = 591), creating distinct high-PA (HPA) and low-PA (LPA) exposure groups. Weighted genetic risk scores (WGRSs) were calculated from 13 Asian-derived obesity-related single-nucleotide polymorphisms. Annual anthropometric, metabolic, and lifestyle data were analyzed using generalized linear mixed models to assess gene-PA interactions on obesity. The WGRS predicted baseline obesity measures, with each unit increase associated with a 0.21-kg/m² higher BMI. Over the natural experiment period, BMI increases in the HPA group were smaller than in the LPA group. After adjusting for age, sex, ethnicity, and dietary factors, significant WGRS-PA interactions were observed for BMI trajectories. Participants with higher genetic risk for obesity experienced greater BMI and weight reduction benefits from sustained long-term PA. In summary, the present study identified a significant interaction effect between PA levels and WGRS in modifying BMI trajectories. Genetic susceptibility significantly modifies the protective effects of long-term PA on BMI progression in this cohort of Chinese youth. Show less
no PDF DOI: 10.1186/s41043-026-01312-y
LPA

Quality of informal care among informal caregivers of people with dementia: A latent profile and ROC analysis.

Chan Cai, Bing Cheng, Chongqing Shi +4 more · 2026 · PloS one · PLOS · added 2026-04-24
The quality of informal care for people with dementia (PwD) has gained increasing importance, as most PwD prefer home-based care over institutional placement. However, evidence-based intervention prog Show more
The quality of informal care for people with dementia (PwD) has gained increasing importance, as most PwD prefer home-based care over institutional placement. However, evidence-based intervention programs tailored to distinct care quality profiles remain limited. Additionally, the absence of clear thresholds to identify PwD receiving low-quality informal care poses a challenge for research and clinical practice. Thus, this study aimed to identify the profiles of quality of care (QoC) among informal caregivers of PwD, explore influencing factors of different profile, and determine the optimal cut-off score of the Exemplary Care Scale (ECS). A cross-sectional survey was conducted. A total of 213 dyads of PwD and their informal caregivers were recruited from memory clinic, rehabilitation clinic, and neurological clinic of a tertiary hospitals and communities in Wuhan, Hubei, China, between July 15, 2023, and July 14, 2024. Latent profile analysis (LPA) was employed to identify QoC profiles. Multinomial logistic regression was performed to explore influencing factors of profile membership. Receiver Operating Characteristic (ROC) analysis was conducted to determine the ECS cut-off score. Three distinct QoC profiles were identified: high (24.41%), moderate (44.60%), and low (30.99%). Among informal caregivers, lower monthly income, insufficient social support, and higher perceived overload were associated with low QoC profile, whereas, better quality of pre-illness relationship with PwD and greater activities of daily living (ADL) of PwD were associated with high QoC. ROC analysis yielded an optimal ECS cut‑off score of 15, with high sensitivity (0.993) and specificity (0.955). This study identified three distinct QoC profiles among caregivers of PwD, underscoring the heterogeneity of informal care quality. The identified predictors and the validated ECS cut‑off score of 15 provide an empirical basis for developing tailored screening tools and targeted interventions for high‑risk caregiver subgroups. Show less
📄 PDF DOI: 10.1371/journal.pone.0346557
LPA

Lipoprotein(a) and the Risk of Heart Failure: A Dose-Response Meta-Analysis.

Yongmei He, Jun Liu, Jingwei Zhuang +1 more · 2026 · Clinical cardiology · Wiley · added 2026-04-24
Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein implicated in cardiovascular disease, but its role in heart failure (HF) remains uncertain. Observational studies indicate a link between Show more
Lipoprotein(a) [Lp(a)] is a genetically determined lipoprotein implicated in cardiovascular disease, but its role in heart failure (HF) remains uncertain. Observational studies indicate a link between elevated Lp(a) and HF risk, but the dose-response relationship remains unexplored. This meta-analysis aimed to quantify the association between circulating Lp(a) levels and HF incidence. A systematic search of PubMed, Embase, and Web of Science identified prospective cohort studies reporting hazard ratios (HRs) for HF incidence across different Lp(a) levels. A random-effects model was applied to pool effect estimates while accounting for heterogeneity, and restricted cubic splines assessed dose-response relationships. Five prospective cohort studies with 400 631 participants were included. During a mean follow-up duration of 11.0 years, 10 598 (2.6%) patients developed HF. A high Lp(a) level was associated with an increased HF risk (HR: 1.34, 95% CI: 1.14-1.59, p < 0.001), with moderate heterogeneity (I² = 69%). Subgroup analysis showed a stronger association in studies using an Lp(a) cutoff of ≥ 50 mg/dL (HR: 1.68) compared to those with a cutoff of < 50 mg/dL (HR: 1.16, p for subgroup difference < 0.01), which completely explained the heterogeneity. The dose-response analysis revealed a nonlinear association (p for non-linearity = 0.001). HF risk increased nearly linearly below 55 mg/dL, then slowed, and plateaued at 160 mg/dL. Elevated Lp(a) is associated with an increased HF risk in a nonlinear pattern, with risk escalation slowing at higher concentrations. Show less
📄 PDF DOI: 10.1002/clc.70289
LPA

Relationship between 24-h movement behaviors and frailty-a scoping review.

Yinhu Tan, Hang Li, Shuangxin Zhang +5 more · 2026 · Frontiers in public health · Frontiers · added 2026-04-24
Frailty is associated with increased risks of falls, disability, hospitalization, and mortality. The 24-h movement behaviors (24HMB) framework conceptualizes sleep, sedentary behavior (SB), light-inte Show more
Frailty is associated with increased risks of falls, disability, hospitalization, and mortality. The 24-h movement behaviors (24HMB) framework conceptualizes sleep, sedentary behavior (SB), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) as mutually constrained components of daily time use and may inform frailty prevention and management. This scoping review maps evidence on associations between 24HMB and frailty and identifies methodological gaps to inform future research and nursing practice. This review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and follows Joanna Briggs Institute (JBI) guidance. We searched PubMed, Embase, CINAHL, and Web of Science. We included observational studies of adults aged ≥18 years. Exposures were objectively measured or validated self-reported sleep, SB, LPA, and MVPA, including step counts, breaks in SB, isotemporal substitution models (ISM), and compositional data analysis (CoDA). Outcomes were frailty or prefrailty assessed using validated instruments. Quality was appraised with JBI tools. Thirty-three studies showed good methodological quality. Longer SB, particularly prolonged, uninterrupted bouts, was associated with higher frailty. Greater MVPA was consistently associated with lower frailty. Light-intensity physical activity was generally beneficial but often attenuated when MVPA or total activity volume was modeled. Sleep fragmentation and poor sleep quality were associated with frailty. Isotemporal substitution models and compositional data analysis indicated that reallocating sedentary time to MVPA would yield the largest theoretical benefit, followed by reallocating to LPA. Higher daily step counts and more frequent or higher-intensity breaks in SB were associated with lower frailty. Evidence supports a 24-h integrated movement-behavior approach centered on MVPA, combined with reducing prolonged SB and improving sleep quality, for the prevention and nursing management of frailty. The study design and analytical protocol were prospectively registered on the Open Science Framework (OSF). The unique identifier is S39Y4, and the publicly accessible URL is https://doi.org/10.17605/OSF.IO/S39Y4. Show less
📄 PDF DOI: 10.3389/fpubh.2026.1780746
LPA

Heterogeneity of Academic Stress Profiles and Depression-Anxiety Symptom Networks in Left-Behind Children: A Latent Profile and Simulated Intervention Network Analysis.

Kuiliang Li, Lei Ren, Rui Lang +7 more · 2026 · Stress and health : journal of the International Society for the Investigation of Stress · Wiley · added 2026-04-24
Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the het Show more
Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the heterogeneity of academic stress profiles and their relationships with the symptom network remain insufficiently explored. To address this gap, a cross-sectional survey of 10,524 Chinese children compared LBC (n = 2487) and NLBC. Latent profile analysis (LPA) was first conducted to identify academic stress subgroups among LBC. Subsequently, depression-anxiety symptom networks were estimated using Ising and Gaussian graphical models (GGM), with edge weights derived from regularised logistic regression (Ising) and partial correlation (GGM). Simulated interventions were further evaluated via the NodeIdentifyR algorithm (NIRA). Overall, compared to NLBC, LBC exhibited higher levels of academic stress, depression, and anxiety (ps < 0.001, Cliff's δ = 0.076; Cohen's d = 0.067). LPA revealed three academic stress subgroups: moderate (31.44%), high (9.17%), and low (59.39%). The severity of depression and anxiety symptoms increased with the level of academic stress. The high stress subgroup displayed a sparse network with stronger edges (e.g., A1 'Sudden Fear'-A4 'Physical Symptoms', edge weight = 2.10) compared to moderate- and low-academic stress subgroups. Core nodes with the strongest expected influence were A8 ('Decision Hesitation', moderate subgroup), A2 ('Worry', high subgroup), and D1/D6 ('Sadness' and 'Failure', low subgroup). Simulated interventions indicated that alleviating A8 'Decision Hesitation' or A2 'Worry' most effectively reduced symptom risk (16.66%-30.76%), whereas D8 'Motor' and A7 'Early Departure' were associated with maximal symptom aggravation. Taken together, by integrating LPA-derived academic stress profiles with symptom network analysis, this study reveals distinct symptom associations across subgroups. In the high stress subgroup, symptom A2 ('Worry') is a core intervention target; in the low stress subgroup, A7 ('Early Departure') holds preventive potential. These findings underscore subgroup-specific interventions tailored to individual stress profiles. Show less
no PDF DOI: 10.1002/smi.70172
LPA

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

Zhenyan Wu, Xue Jiang, Yu Xin +3 more · 2026 · BMJ open · added 2026-04-24
To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-in Show more
To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-invasive tool for early CAD screening. A retrospective cross-sectional study. A single-centre study conducted at the Cardiovascular Center of Beijing Tongren Hospital, Capital Medical University, China, between January and October 2024. 417 patients with suspected angina undergoing their first coronary angiography (CAG) were enrolled. Inclusion criteria were age >18 years and high-quality fundus photography within 24 hours pre-CAG. Major exclusions were prior coronary interventions, severe systemic/valvular heart diseases and ocular conditions impairing retinal vascular visualisation. The primary outcome was the association between quantitative retinal vascular parameters and the presence of CAD (defined as ≥50% stenosis). Secondary outcomes included the diagnostic performance area under the receiver operating characteristic curve (AUROC) of three predictive models: one based on quantitative retinal vascular parameters alone, one based on traditional risk factors and a combined model integrating both retinal and clinical variables. This study enrolled 417 patients undergoing initial CAG. Compared with non-CAD controls (n=190), patients with CAD (n=227) had higher prevalence of hypertension, dyslipidaemia and diabetes, along with elevated levels of fasting blood glucose, lipoprotein(a) (Lp(a)), triglyceride (TG) and glycated haemoglobin (HbA1c) (all p<0.05). Quantitative fundus analysis revealed that multiple retinal vascular parameters were independently associated with CAD after multivariable adjustment, including fractal dimension (FD), vessel density (VD) and specific zonal measures of vessel diameter and tortuosity (all p<0.05). Multivariable logistic regression incorporating both fundus and clinical variables identified the following independent predictors of CAD: a decrease in FD (OR=0.26, 95% CI 0.16 to 0.41, p<0.01), reduced optic disc long-to-short axis ratio (OR=0.04, 95% CI 0.004 to 0.46, p=0.01) and optic disc-to-macula distance (OR=0.91, 95% CI 0.86 to 0.97, p<0.01), male sex, dyslipidaemia and elevated levels of Lp(a), TG, low-density lipoprotein cholesterol and HbA1c (all p<0.05). The final diagnostic model achieved an AUROC of 0.802 (95% CI 0.76 to 0.845), with a sensitivity of 0.797 and a specificity of 0.679 at the optimal cut-off. Internal validation via bootstrap resampling (1000 iterations) confirmed the robustness of the identified predictors. Our findings, derived from an artificial intelligence-based fully automated quantitative retinal vascular parameters measurement method, revealed that multiple quantitative fundus parameters-including FD, VD and other morphological parameters were significantly associated with CAD risk. The CAD diagnostic model we developed demonstrates strong performance and high interpretability, making it suitable for early CAD screening and diagnosis. Show less
📄 PDF DOI: 10.1136/bmjopen-2025-106135
LPA

Urea-based lysophosphatidic acid receptor 1 antagonists as potential migrastatics for triple-negative breast cancer.

Wenjie Liu, Amr A K Mousa, Guillem Dayer +7 more · 2026 · Bioorganic chemistry · Elsevier · added 2026-04-24
We previously described the discovery of carbamate-derived small molecules as potent and selective lysophosphatidic acid receptor 1 (LPA
no PDF DOI: 10.1016/j.bioorg.2026.109807
LPA