👤 Xiaofang Liu

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 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, 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, 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

Transcriptome analysis of postnatal mouse cardiac tissue growth and development.

Xiao-Cong Zhu, Sheng-Nan Wang, Lin Jiang +1 more · 2025 · Yi chuan = Hereditas · added 2026-04-24
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy h Show more
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy have not yet been fully elucidated. Therefore, phenotypic measurements and transcriptomic sequencing were performed on myocardial tissues from 7-day-old (P7) and 3-month-old (3m) female C57BL/6 mice to investigate changes in cardiomyocytes during growth and development and to identify key genes regulating myocardial growth and development. In comparison to 7-day-old mice, 3-month-old mice exhibited a significant increase in heart weight ( Show less
no PDF DOI: 10.16288/j.yczz.24-328
HEY2

GIPR agonism and antagonism decrease body weight and food intake via different mechanisms in male mice.

Robert M Gutgesell, Ahmed Khalil, Arkadiusz Liskiewicz +21 more · 2025 · Nature metabolism · Nature · added 2026-04-24
Agonists and antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR) enhance body weight loss induced by glucagon-like peptide-1 receptor (GLP-1R) agonism. However, while GIPR Show more
Agonists and antagonists of the glucose-dependent insulinotropic polypeptide receptor (GIPR) enhance body weight loss induced by glucagon-like peptide-1 receptor (GLP-1R) agonism. However, while GIPR agonism decreases body weight and food intake in a GLP-1R-independent manner via GABAergic GIPR Show less
📄 PDF DOI: 10.1038/s42255-025-01294-x
GIPR

Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele.

Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff +122 more · 2025 · Nature communications · Nature · added 2026-04-24
Xinruo Zhang, Jennifer A Brody, Mariaelisa Graff, Heather M Highland, Nathalie Chami, Hanfei Xu, Zhe Wang, Kendra R Ferrier, Geetha Chittoor, Navya Shilpa Josyula, Mariah Meyer, Shreyash Gupta, Xihao Li, Zilin Li, Matthew A Allison, Diane M Becker, Lawrence F Bielak, Joshua C Bis, Meher Preethi Boorgula, Donald W Bowden, Jai G Broome, Erin J Buth, Christopher S Carlson, Kyong-Mi Chang, Sameer Chavan, Yen-Feng Chiu, Lee-Ming Chuang, Matthew P Conomos, Dawn L DeMeo, Mengmeng Du, Ravindranath Duggirala, Celeste Eng, Alison E Fohner, Barry I Freedman, Melanie E Garrett, Xiuqing Guo, Chris Haiman, Benjamin D Heavner, Bertha Hidalgo, James E Hixson, Yuk-Lam Ho, Brian D Hobbs, Donglei Hu, Qin Hui, Chii-Min Hwu, Rebecca D Jackson, Deepti Jain, Rita R Kalyani, Sharon L R Kardia, Tanika N Kelly, Ethan M Lange, Michael LeNoir, Changwei Li, Loic Le Marchand, Merry-Lynn N McDonald, Caitlin P McHugh, Alanna C Morrison, Take Naseri, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Jeffrey O'Connell, Christopher J O'Donnell, Nicholette D Palmer, James S Pankow, James A Perry, Ulrike Peters, Michael H Preuss, D C Rao, Elizabeth A Regan, Sefuiva M Reupena, Dan M Roden, Jose Rodriguez-Santana, Colleen M Sitlani, Jennifer A Smith, Hemant K Tiwari, Ramachandran S Vasan, Zeyuan Wang, Daniel E Weeks, Jennifer Wessel, Kerri L Wiggins, Lynne R Wilkens, Peter W F Wilson, Lisa R Yanek, Zachary T Yoneda, Wei Zhao, Sebastian Zöllner, Donna K Arnett, Allison E Ashley-Koch, Kathleen C Barnes, John Blangero, Eric Boerwinkle, Esteban G Burchard, April P Carson, Daniel I Chasman, Yii-der Ida Chen, Joanne E Curran, Myriam Fornage, Victor R Gordeuk, Jiang He, Susan R Heckbert, Lifang Hou, Marguerite R Irvin, Charles Kooperberg, Ryan L Minster, Braxton D Mitchell, Mehdi Nouraie, Bruce M Psaty, Laura M Raffield, Alexander P Reiner, Stephen S Rich, Jerome I Rotter, M Benjamin Shoemaker, Nicholas L Smith, Kent D Taylor, Marilyn J Telen, Scott T Weiss, Yingze Zhang, Nancy Heard-Costa, Yan V Sun, Xihong Lin, L Adrienne Cupples, Leslie A Lange, Ching-Ti Liu, Ruth J F Loos, Kari E North, Anne E Justice Show less
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data fr Show more
Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10 Show less
no PDF DOI: 10.1038/s41467-025-58420-2
POC5

FGF22 Secreted by Hair Papilla Cells Regulates Hair Follicle Stem Cell Proliferation and Differentiation.

Yu Luo, Tong Xiao, Binpeng Xi +5 more · 2025 · Biomolecules · MDPI · added 2026-04-24
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine res Show more
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine research. Their dynamic interaction with dermal papilla cells (DPCs) plays a decisive role in HF development and cycling. Show less
📄 PDF DOI: 10.3390/biom15111560
FGFR1

The Impact of Cannabidiol (CBD) on Lipid Absorption and Lymphatic Transport in Rats.

Qi Zhu, Qing Yang, Ling Shen +2 more · 2025 · Nutrients · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/nu17061034
APOA4

Reactive Oxygen Species in Asthma: Regulators of Macrophage Polarization and Therapeutic Implications: A Narrative Review.

Ying Liu, Mingyao Zhang, Tongtong Wang +1 more · 2025 · Journal of asthma and allergy · added 2026-04-24
As a vital component of the immune system, macrophages play a critical role in the progression of asthma. The two classic polarization states of macrophages, M1 and M2, exhibit distinct functions. M1- Show more
As a vital component of the immune system, macrophages play a critical role in the progression of asthma. The two classic polarization states of macrophages, M1 and M2, exhibit distinct functions. M1-polarized macrophages eliminate pathogens through the secretion of pro-inflammatory cytokines, while M2-polarized macrophages secrete anti-inflammatory factors to facilitate tissue repair. However, in asthma, the activation of M1 macrophages is often associated with excessive inflammatory responses, whereas M2 macrophages contribute to airway remodeling and chronic inflammation. These processes collectively exacerbate airway inflammation and remodeling, thereby aggravating asthma symptoms. Reactive oxygen species (ROS), as crucial signaling molecules, have been shown to regulate macrophage polarization and promote both M1 and M2 polarization states. This review summarizes the primary endogenous and exogenous sources of ROS in asthma and elaborates on the mechanisms by which ROS influence M1/M2 polarization of macrophages. Endogenous ROS arise chiefly from NOX2, xanthine oxidase, peroxisomes and mitochondria, whereas ozone and fine particulate matter are major exogenous sources. ROS activate MAPK, NF-κB and NLRP3 cascades, boosting IL-1β, IL-6 and IL-27 release by M1 cells, while low NOX2 flux or mitochondrial H Show less
📄 PDF DOI: 10.2147/JAA.S529371
IL27

POU6F2 promotes liver metastasis of gastric adenocarcinoma by dual mechanism of transcriptional upregulation of SNAI1 and IGF2/PI3K/AKT signaling-induced conversion of hepatic stellate cells into cancer-associated fibroblasts.

Chunxiao Yang, Zhiqing Gao, Ruiming Tang +16 more · 2025 · British journal of cancer · Nature · added 2026-04-24
Activation of cancer-associated fibroblasts (CAFs) plays an important role in tumor metastasis. The purpose of this study is to investigate the role of POU6F2 in conversion of hepatic stellate cells ( Show more
Activation of cancer-associated fibroblasts (CAFs) plays an important role in tumor metastasis. The purpose of this study is to investigate the role of POU6F2 in conversion of hepatic stellate cells (HSCs) into CAFs in liver metastasis of gastric adenocarcinoma (GAC). POU6F2 expression was examined by real-time PCR, Western blot and immunohistochemical staining. The functional roles of POU6F2 in GAC liver metastasis were investigated both cellular experiments in vitro and in vivo using a mouse model of subcutaneous splenic injection. ChIP and ELISA assays were used to explore the underlying molecular mechanism of POU6F2 in liver metastasis of GAC. Here we reported that POU6F2 was upregulated in GAC tissue with liver metastasis, which predicted poor early liver metastasis. Upregulating POU6F2 promoted EMT, invasion and migration of GAC cells in vitro, and the liver metastasis of GAC cells in vivo. Mechanic investigation further revealed that upregulating POU6F2 promoted the invasion and metastasis of GAC by transcriptional upregulation of EMT-inducer SNAI1, and promoting the conversion of HSCs into CAFs dependent on transcriptional upregulation of IGF2-induced activation of PI3K/AKT signaling. Our findings uncover a novel dual mechanism by which POU6F2 promotes liver metastasis of GAC. Show less
no PDF DOI: 10.1038/s41416-025-03017-1
SNAI1

Single-cell transcriptomic profiling of heart reveals ANGPTL4 linking fibroblasts and angiogenesis in heart failure with preserved ejection fraction.

Guoxing Li, Huilin Zhao, Zhe Cheng +3 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Despite the high morbidity and mortality, the effective therapies for heart failure with preserved fraction (HFpEF) are limited as the poor understand of its pathophysiological basis. This study was a Show more
Despite the high morbidity and mortality, the effective therapies for heart failure with preserved fraction (HFpEF) are limited as the poor understand of its pathophysiological basis. This study was aimed to characterize the cellular heterogeneity and potential mechanisms of HFpEF at single-cell resolution. An HFpEF mouse model was induced by a high-fat diet with N-nitro-L-arginine methyl ester. Cells from the hearts were subjected to single-cell sequencing. The key protein expression was measured with Immunohistochemistry and immunofluorescence staining. In HFpEF hearts, myocardial fibroblasts exhibited higher levels of fibrosis. Furthermore, an increased number of fibroblasts differentiated into high-metabolism and high-fibrosis phenotypes. The expression levels of genes encoding certain pro-angiogenic secreted proteins were decreased in the HFpEF group, as confirmed by bulk RNA sequencing. Additionally, the proportion of the endothelial cell (EC) lineages in the HFpEF group was significantly downregulated, with low angiogenesis and high apoptosis phenotypes observed in these EC lineages. Interestingly, the fibroblasts in the HFpEF heart might cross-link with the EC lineages via over-secretion of ANGPTL4, thus displaying an anti-angiogenic function. Immunohistochemistry and immunofluorescence staining then revealed the downregulation of vascular density and upregulation of ANGPTL4 expression in HFpEF hearts. Finally, we predicted ANGPTL4as a potential druggable target using DrugnomeAI. In conclusion, this study comprehensively characterized the angiogenesis impairment in HFpEF hearts at single-cell resolution and proposed that ANGPTL4 secretion by fibroblasts may be a potential mechanism underlying this angiogenic abnormality. Show less
📄 PDF DOI: 10.1016/j.jare.2024.02.006
ANGPTL4

Genome-wide analysis identifies susceptibility loci for heart failure and nonischemic cardiomyopathy subtype in the East Asian populations.

Yi Han, Yun Hong, Yan Gao +11 more · 2025 · PLoS genetics · PLOS · added 2026-04-24
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understandin Show more
Heart failure (HF) is a serious cardiovascular condition resulting from abnormalities in multiple biological processes, affecting over 64 million people worldwide. We sought to expand our understanding of the genetic basis of HF and more specific NICM subtype in the East Asian populations and evaluate the biological pathways underlying subclinical left ventricular dysfunction. We conducted a meta-analysis of genome-wide association studies (GWAS) for all-cause HF in the East Asian populations (N cases ~ 13,385) and a more precise definition of nonischemic cardiomyopathy (NICM) subtype in multi-ancestry populations (N cases~3,603). We identified a low-frequency East-Asian enriched coding variant near MYBPC3 and a NICM specific locus. Follow up analyses demonstrated male-specific HF association at the MYBPC3 locus, and highlighted SVIL as a candidate causal gene for NICM. Moreover, we demonstrated that SVIL deficiency aggravated cardiomyocyte hypertrophy, apoptosis and impaired cell viability in phenylephrine (PE)-treated H9C2 cells. In addition, the gene expression level of B-type natriuretic peptide (BNP) which was deemed as a hallmark for HF was further elevated by SVIL silencing in PE-stimulated H9C2 cells. RNA-sequencing analysis of H9C2 cells revealed that the function of SVIL might be mediated through pathways relevant to regulation and differentiation of heart muscle. These results enhance our understanding of the genetic architecture of HF in the East Asian populations, and provide important insight into the biological pathways underlying NICM and sex-specific relevance of the MYBPC3 locus that warrants further replication in another datasets. Show less
📄 PDF DOI: 10.1371/journal.pgen.1011897
MYBPC3

Exploring the Causal Relationships between Lipid Biomarkers and Anti-VEGF Treatment Response in Patients with Neovascular Age-related Macular Degeneration.

Feixiang He, Qifang Chen, Peilin Gu +4 more · 2025 · Ophthalmology science · Elsevier · added 2026-04-24
To identify the connections between lipid biomarkers and the anti-VEGF therapy response in patients with neovascular age-related macular degeneration (nAMD). A bidirectional and multivariable Mendelia Show more
To identify the connections between lipid biomarkers and the anti-VEGF therapy response in patients with neovascular age-related macular degeneration (nAMD). A bidirectional and multivariable Mendelian randomization study. The summary statistics for anti-VEGF nAMD treatment response included a total of 128 responders, 51 nonresponders, and 6 908 005 genetic variants available for analysis. The sample size of lipid biomarkers is 441 016 and 12 321 875 genetic variants available for analysis. Two-sample Mendelian randomization (MR) method was conducted to exhaustively appraise the causalities among 13 lipid biomarkers and the risk of different anti-VEGF treatment responses (including visual acuity [VA] and central retinal thickness [CRT]) for nAMD subtypes. Thirteen lipid biomarkers, VA, and CRT. A positive causal relationship was identified between triglycerides (TGs), apolipoproteins (Apos) E2, ApoE3, total cholesterol (TC), and VA response to anti-VEGF therapy in patients with nAMD, as confirmed by MR-Egger, weighted median, and weighted mode models. The MR-Egger model yielded statistically significant results for TC, ApoA-I, ApoB, and ApoA-V in relation to the CRT response to anti-VEGF treatment in patients with nAMD. In the reverse MR, the MR-Egger model identified significant causal relationships between ApoA-I, low-density lipoprotein cholesterol (LDL-c), ApoE3, and ApoF and the VA response. However, this was not the case in the weighted median and weighted mode models. In the MR-Egger model, ApoB, LDL-c, ApoE3, and ApoM were identified as significantly influencing the CRT response. In the multisample MR analysis, TC, high-density lipoprotein cholesterol, LDL-c, and TG were found to be causally related to VA response, and TC was also identified as being causally related to the CRT response to anti-VEGF therapy in patients with nAMD. This MR study suggests unidirectional causality between TG and ApoE3 and the response to anti-VEGF treatment in patients with nAMD. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Show less
📄 PDF DOI: 10.1016/j.xops.2025.100711
APOB

Dietary Se-enrich Cardamine violifolia supplementation decreases lipid deposition and improves antioxidant status in the liver of aging laying hens.

Mengke Yan, Xin Cong, Hui Wang +7 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Aging-related lipid metabolic disorder is related to oxidative stress. Selenium (Se)-enriched Cardamine violifolia (SEC) is known for its excellent antioxidant function. The objective of this study wa Show more
Aging-related lipid metabolic disorder is related to oxidative stress. Selenium (Se)-enriched Cardamine violifolia (SEC) is known for its excellent antioxidant function. The objective of this study was to evaluate the effects of SEC on antioxidant capacity and lipid metabolism in the liver of aged laying hens. A total of 450 sixty-five-wk-old Roman laying hens were randomly divided into 5 treatments: a basal diet (without Se supplementation, CON) and basal diets supplemented with 0.3 mg/kg Se from sodium selenite (SS), 0.3 mg/kg Se from Se-enriched yeast (SEY), 0.3 mg/kg Se from SEC (SEC), or 0.3 mg/kg Se from SEC and 0.3 mg/kg Se from SEY (SEC + SEY). The experiment lasted for 8 wk. The results showed that dietary SEC + SEY supplementation decreased (P < 0.05) triglyceride (in the plasma and liver) and total cholesterol levels (in the plasma), and increased (P < 0.05) HDL-C concentration in plasma compared to CON diet. Compared with CON diet, SEC and/or SEY supplementation decreased (P < 0.05) the mRNA expression of hepatic ACC, FAS and HMGCR, and increased (P < 0.05) PPARα, VTG-II, Apo-VLDL II and ApoB expression. Dietary SEC + SEY and SEY supplementation increased (P < 0.05) Se content in egg yolk and breast muscle compared to CON diet. Dietary SEC, SEY or SEC + SEY supplementation increased (P < 0.05) the activity of antioxidant enzymes (GSH-PX, T-AOC and T-SOD) in the plasma and liver and decreased (P < 0.05) MDA content in the plasma compared to CON diet. Dietary Se supplementation promoted (P < 0.05) mRNA expression of Nrf2 in the liver. In contrast, dietary SEY and SEC supplementation resulted in a decrease (P < 0.05) of hepatic Keap1 mRNA expression compared to CON diet. Dietary SEC + SEY and/or SEC supplementation increased (P < 0.05) mRNA expression of Selenof, GPX1 and GPX4 in the liver compared with CON diet. In conclusion, dietary SEC (0.3 mg/kg Se) or SEC (0.3 mg/kg Se) + SEY (0.3 mg/kg Se) improved the antioxidant capacity and the lipid metabolism in the liver of aged laying hens, which might be associated with regulating Nrf2/Keap1 signaling pathway. Show less
📄 PDF DOI: 10.1016/j.psj.2024.104620
APOB

CircSETD2 impairs hepatic lipid homeostasis in metabolic dysfunction-associated fatty liver disease by binding CPS1.

Xuancheng Xie, Hongjie Fan, Mengyao Zheng +8 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Dysregulation of hepatic lipid homeostasis constitutes a core pathogenic mechanism in metabolic dysfunction-associated fatty liver disease (MAFLD); however, the regulatory role of circular RNAs (circR Show more
Dysregulation of hepatic lipid homeostasis constitutes a core pathogenic mechanism in metabolic dysfunction-associated fatty liver disease (MAFLD); however, the regulatory role of circular RNAs (circRNAs) in this process remains unclear. In this study, hepatic circRNAs transcriptomic profiling of MAFLD patients identified circSETD2-generated from exons 16-18 of the SETD2 gene-as a stably expressed and significantly upregulated novel circRNA with a closed circular structure localized in the cytoplasm of MAFLD patient liver tissues. Silencing circSETD2 attenuated free fatty acid - induced lipid accumulation in vitro by reducing lipogenesis and enhancing fatty acid β-oxidation. In high fat diet - fed mice, hepatic circSETD2 silencing mitigated steatosis, improved liver function, and reversed dyslipidemia. Mechanistically, RNA pull-down coupled with LC-MS/MS identified carbamoyl phosphate synthetase 1 (CPS1) as a circSETD2-interacting protein, which was subsequently validated by RNA immunoprecipitation and fluorescence in situ hybridization. Pharmacological modulation of CPS1 enzymatic activity in circSETD2-silenced cells established its mediator role. Specifically, circSETD2 directly bound to CPS1, reducing its enzymatic activity and thereby exacerbating lipid metabolic disturbances and disease progression in MAFLD. In summary, circSETD2 drives MAFLD pathogenesis by impairing CPS1-mediated regulation of lipid homeostasis, positioning it as a promising prognostic biomarker and therapeutic target. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.148879
CPS1

Advanced Machine Learning to Predict Coronary Artery Disease Severity in Patients with Premature Myocardial Infarction.

Yu-Hang Wang, Chang-Ping Li, Jing-Xian Wang +6 more · 2025 · Reviews in cardiovascular medicine · added 2026-04-24
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limi Show more
Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limited. In this observational study, 1111 PMI patients (≤55 years) at Tianjin Chest Hospital from 2017 to 2022 were selected and divided according to their SYNTAX scores into a low-risk group (≤22) and medium-high-risk group (>22). These groups were further randomly assigned to a training or test set in a ratio of 7:3. Lasso-logistic was initially used to screen out target factors. Subsequently, Lasso-logistic, random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost) were used to establish prediction models based on the training set. After comparing prediction performance, the best model was chosen to build a prediction system for coronary artery severity in PMI patients. Glycosylated hemoglobin (HbA1c), angina, apolipoprotein B (ApoB), total bile acid (TBA), B-type natriuretic peptide (BNP), D-dimer, and fibrinogen (Fg) were associated with the severity of lesions. In the test set, the area under the curve (AUC) of Lasso-logistic, RF, KNN, SVM, and XGBoost were 0.792, 0.775, 0.739, 0.656, and 0.800, respectively. XGBoost showed the best prediction performance according to the AUC, accuracy, F1 score, and Brier score. In addition, we used decision curve analysis (DCA) to assess the clinical validity of the XGBoost prediction model. Finally, an online calculator based on the XGBoost was established to measure the severity of coronary artery lesions in PMI patients. In summary, we established a novel and convenient prediction system for the severity of lesions in PMI patients. This system can swiftly identify PMI patients who also have severe coronary artery lesions before the coronary intervention, thus offering valuable guidance for clinical decision-making. Show less
📄 PDF DOI: 10.31083/RCM26102
APOB

Multi-Angle Bioactivity Cartography for Computational Screening and Mechanistic Analysis of AChE Inhibitors From Yellow Gastrodia elata.

Ruijun Sun, Yuchi Zhang, Jingying Xu +7 more · 2025 · Archiv der Pharmazie · Wiley · added 2026-04-24
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-se Show more
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-serving as promising reservoirs of such inhibitors. Nevertheless, comprehensive screening and mechanistic characterization of their inhibitory potential remain limited. This study sought to identify potent AChE inhibitors from YGE, investigate their mechanisms of action, and assess their therapeutic prospects for AD. Methodologically, an integrated approach was employed, combining ultrafiltration-liquid chromatography (UF-LC) for rapid inhibitor screening, molecular docking and dynamics simulations for mechanistic insight, two-stage high-speed countercurrent chromatography for compound isolation, enzyme kinetics to delineate inhibition modalities, and network pharmacology to uncover relevant AD-related targets. The findings identified seven active constituents with notable AChE inhibition, among which parishins A and G were obtained at high purity (98.26% and 97.26%, respectively) and exhibited mixed-type inhibition with low IC Show less
no PDF DOI: 10.1002/ardp.70174
BACE1

Isotemporal substitution from sedentary behavior or sleep to physical activity: associations with depression risk in older adults-a systematic review and meta-analysis.

Jiali Wang, Yilin Wang, Yue Wang +3 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
As global population aging intensifies, mental health issues in older adults are increasingly prominent, with depression being particularly prevalent and detrimental. The study investigated how substi Show more
As global population aging intensifies, mental health issues in older adults are increasingly prominent, with depression being particularly prevalent and detrimental. The study investigated how substituting sedentary behavior (SB) and sleep (SLP) with physical activity (PA) affects depression risk in this population. Meta-analysis was conducted by searching four databases: PubMed, Scopus, SPORTdiscus, and PsycINFO (via EBSCOhost platform) for relevant studies published until January 2025. Regression coefficients (β) with 95% confidence intervals (CIs) for depressive symptoms were estimated. Publication bias was assessed using funnel plots and Egger's tests, and heterogeneity was evaluated using Q tests and the I Among 18,912 participants (53.45% female, ≥60 years) across nine studies, replacing SB with MVPA significantly reduced depression (β = -0.12, 95% CI: -0.20, -0.04), subgroup analyses indicated that reallocating 10, 30 and 60 min/day of SB to MVPA ( Substituting SB and SLP with MVPA is significantly associated with a reduction in depression, whereas no significant association is observed when replaced by LPA. https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=546666, identifier CRD42024546666. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1682987
LPA

Effect of cholesterol on distribution, cell uptake, and protein corona of lipid microspheres at sites of cardiovascular inflammatory injury.

Lingyan Li, Xingjie Wu, Qianqian Guo +9 more · 2025 · Journal of pharmaceutical analysis · Elsevier · added 2026-04-24
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, over Show more
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in vascular endothelial cells and estrogen receptor alpha (ERα) protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation Show less
📄 PDF DOI: 10.1016/j.jpha.2024.101182
APOA5

Impact of chronic consumption of probiotics, oats, and apples on expression of genes related to bile acids, lipid, gut peptides, and inflammation in peripheral monocular cells - findings from the CABALA study.

Shouq Alzoufairi, Rose-Anna G Pushpass, L Liu +2 more · 2025 · European journal of nutrition · Springer · added 2026-04-24
Chronic intakes of functional foods (probiotics, apples and oats) have been reported to have beneficial effects on hepatic lipid regulation and glycaemic control, but mechanistic human studies humans Show more
Chronic intakes of functional foods (probiotics, apples and oats) have been reported to have beneficial effects on hepatic lipid regulation and glycaemic control, but mechanistic human studies humans are limited. An ex-vivo study was performed to determine the chronic effects of probiotics, oats, and apples on the expression of genes related to markers of cardiometabolic health in peripheral blood monocular cells (PBMC). In this CABALA sub-study (n = 59/61, age: 52 ± 12y), blood PBMC were also isolated before and 8 weeks after the daily consumption of either a probiotic with bile salt hydrolase activity (Lactobacillus reuteri), porridge oats, Renetta Canada apples or a control. Relative PBMC mRNA gene expression was determined and correlations performed between the fold change in response to the functional interventions and change in cardiometabolic disease risk markers. Relative to baseline, there was an upregulation in the PBMC TLR4 mRNA expression in the control compared with the probiotics and apples groups (p[Formula: see text]0.024). Moderate inverse correlations were found between the fold change in GPBAR1 mRNA expression and change in plasma total and secondary BAs, HMGCR and SREBF1 mRNA gene expressions and high-density lipoprotein-cholesterol, and SREBF1 and GIPR mRNA gene expressions and glucose. TLR4 and TNFSF14 mRNA gene expressions were associated with pro-inflammatory cytokines (p=0.05). Probiotic and apples interventions attenuated the upregulation in PBMC TLR4 mRNA expression observed with the control. Correlations between fold change in mRNA gene expression and changes in cardiometabolic disease risk markers in response to the functional interventions were in agreement with previous studies. The study was registered at clinical trials.gov (ref. NCT03369548). Show less
📄 PDF DOI: 10.1007/s00394-025-03694-x
GIPR

Branched-chain amino acid and cancer: metabolism, immune microenvironment and therapeutic targets.

Hao Xiong, Ruiqi Liu, Keke Xu +7 more · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
Cancer is one of the major diseases threatening human health in the world. According to the latest global cancer statistics from the International Agency for Research on Cancer (IARC), there were appr Show more
Cancer is one of the major diseases threatening human health in the world. According to the latest global cancer statistics from the International Agency for Research on Cancer (IARC), there were approximately 20 million new cancer cases and 10 million cancer deaths worldwide. Amidst this global health concern, branched chain amino acids have emerged as key players, playing an important role in the occurrence and development of cancer. In certain malignancies like colorectal cancer, the average level of BCAA in tumor tissues is twice that in normal tissues. BCAA metabolism is intricately associated with the progression of multiple tumors and is modulated by diverse enzymes, including BCAT, BCKDH, and BCKDK. The metabolism of BCAA involves multiple enzymes and biochemical processes via signaling pathways such as PI3K/AKT/mTOR and AMPK/mTOR, etc. In addition, mTOR inhibitors show potential value in cancer treatment by regulating the metabolism and signaling pathways of tumor cells, which provides a new direction for anticancer efforts. Simultaneously, BCAAs are closely associated with tumor immunity, including NK cells, CD4 Show less
📄 PDF DOI: 10.1186/s12967-025-06664-3
BCKDK

Exercise-Induced Changes in Brain-Derived Neurotrophic Factor in Neurodegenerative Diseases: A Bayesian Network Meta-Analysis.

Zhuolin Tang, Mingyue Yin, Kai Xu +4 more · 2025 · Journal of geriatric psychiatry and neurology · SAGE Publications · added 2026-04-24
ObjectivesThis study aimed to compare the effects of different exercise interventions on brain-derived neurotrophic factor (BDNF) levels in patients with neurodegenerative diseases and to explore regu Show more
ObjectivesThis study aimed to compare the effects of different exercise interventions on brain-derived neurotrophic factor (BDNF) levels in patients with neurodegenerative diseases and to explore regulatory factors.MethodsSearched PubMed, Scopus, Web of Science Core Collection, CNKI and Cochrane Library databases up to March 15, 2025. Bayesian network meta-analysis was conducted using R software, and meta-regression analyzed the moderating effects of training period and frequency.Results42 randomized controlled trials covering 1482 patients were included. The Surface Under the Cumulative Ranking (SUCRA) indicated that stretching training (SUCRA = 78.92) and high-intensity interval training (SUCRA = 69.73) were ranked higher than other exercise modalities and exhibited more favorable effect on BDNF enhancement, although neither demonstrated statistically significant superiority over the blank control. In contrast, combined training (SUCRA = 35.58), aerobic training (SUCRA = 35.17), and resistance training (SUCRA = 12.98) showed relatively lower potential for BDNF enhancement (blank control SUCRA = 67.62). Meta-regression analysis showed that the effect of combined training was significantly and positively correlated with intervention period ( Show less
no PDF DOI: 10.1177/08919887251409415
BDNF bayesian network meta-analysis brain-derived neurotrophic factor exercise interventions meta-regression neurodegenerative diseases neuroscience neurotrophic factors

Relationship Between Chronic Pain and Breast Cancer: Insight From Genetic Correlation Analyses and 2-Sample Mendelian Randomization.

Haojie Yang, Xiaoyan Xie, Liling Lin +5 more · 2025 · Clinical breast cancer · Elsevier · added 2026-04-24
To evaluate potential genetic causal relationships between chronic pain subtypes like migraine and multi-site chronic pain (MCP) and their impact on breast cancer occurrence and survival rates. The as Show more
To evaluate potential genetic causal relationships between chronic pain subtypes like migraine and multi-site chronic pain (MCP) and their impact on breast cancer occurrence and survival rates. The association between chronic pain and breast cancer was reported before, yet the causal nature between them remained uncertain. Data on chronic pain and breast cancer were sourced from publicly available European genome-wide association study (GWAS) datasets. Genetic association between chronic pain and breast cancer phenotypes was assessed using linkage disequilibrium genetic correlation (LDSC). Colocalization analysis further identified potential shared causal variation. Based on Inverse variance weighted method, 2-sample Mendelian Randomization (MR) was conducted to investigate causal associations between migraine, MCP, and breast cancer or breast cancer survival. Sensitive analysis was conducted to ensure the absence of heterogeneity and horizontal pleiotropy. LDSC demonstrated significant genetic correlations between migraine and both estrogen receptor-negative (ER-) and overall breast cancer, while also revealing a notable genetic association between MCP and ER- and ER+ breast cancer, as well as overall breast cancer. Through colocalization analysis, potential involvement of rs2183271, located in MLLT10 gene, in regulating MCP and ER+ breast cancer was identified. MR analysis revealed the association between migraine and elevated risk of ER- breast cancer (IVW, P = 4.95 × 10 Our results provided new insights into the role of migraine and MCP in breast cancer, paving the way for targeted preventive strategies and future investigations. Show less
no PDF DOI: 10.1016/j.clbc.2025.02.004
MLLT10

Serum IL-27 and GDF15 levels in second trimester are associated with adverse pregnancy outcomes.

Xue Li, Luping Liu, Li Jiang +7 more · 2025 · Journal of molecular cell biology · Oxford University Press · added 2026-04-24
📄 PDF DOI: 10.1093/jmcb/mjae053
IL27

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

A new perspective on cognitive impairment in major depressive disorder: Changes in gut microbiota and their inflammatory regulatory mechanisms.

Xiaodong Song, Qilin Zhong, Rongxu Zhang +10 more · 2025 · Journal of affective disorders · Elsevier · added 2026-04-24
Cognitive impairments in major depressive disorder (MDD) affect patients' social functioning, with underlying mechanisms involving gut microbiota and inflammatory factors remaining unclear. The study Show more
Cognitive impairments in major depressive disorder (MDD) affect patients' social functioning, with underlying mechanisms involving gut microbiota and inflammatory factors remaining unclear. The study analyzed cognitive function, gut microbiota changes, and inflammatory factor levels in 39 unmedicated MDD patients and 41 healthy controls, employing correlation and moderation effect analysis. MDD patients scored lower than controls in cognitive functions like information processing speed, attention/vigilance, verbal learning, visual learning and social cognition. They showed reduced gut microbiota diversity and increased levels of inflammatory markers (TNF-α, IL-1, IL-6, IL-17, IL-27, IL-33). Sellimonas abundance correlated negatively with attention/vigilance, moderated by TNF-α, IL-27, and IL-33. This relationship was stronger at lower inflammation levels. MDD patients exhibit multi-domain cognitive dysfunction alongside pro-inflammatory states and disrupted gut microbiota. The abundance of Sellimonas significantly predicts attention/vigilance deficits. Inflammatory factors modulate the impact of gut microbiota on cognitive function, suggesting chronic low-grade inflammation as a key risk factor for cognitive impairment in MDD. Show less
no PDF DOI: 10.1016/j.jad.2025.119648
IL27

Selenium Nanoparticles vs Selenite Fertilizers: Implications for Toxicological Profiles, Antioxidant Defense, and Ferroptosis Pathways.

Qiting Fang, Zhonghua Liu, Kaixi Wang · 2025 · Journal of agricultural and food chemistry · ACS Publications · added 2026-04-24
Selenium (Se) foliar fertilizers enhance crop nutrition and address human selenium deficiency, while improper application may lead to excessive intake and residue accumulation. Our study comprehensive Show more
Selenium (Se) foliar fertilizers enhance crop nutrition and address human selenium deficiency, while improper application may lead to excessive intake and residue accumulation. Our study comprehensively assessed the toxicity and function of novel selenium nanoparticles and traditional sodium selenite fertilizers across cell, zebrafish, and murine models. Both fertilizers enhanced antioxidant pathways at low doses, but selenium nanoparticles exhibited stronger antioxidant and ferroptosis-modulating effects with lower toxicity at a high dose. Sodium selenite increased total and lipid ROS production, leading to decreased viability of cells and increased distortion and mortality of zebrafish. In mice, sodium selenite induced hepatic toxicity and decreased GPX4. Transcriptome analysis revealed that sodium selenite downregulated c-JUN and APOA4, weakening the antioxidant defense, whereas selenium nanoparticles promoted ferroptosis resistance through FGF21. These findings suggest selenium nanoparticles as a safer alternative for Se biofortification, mitigating health risks while supporting food security and environmental sustainability. Show less
no PDF DOI: 10.1021/acs.jafc.5c02034
APOA4

The joint predictive roles of achievement task values and academic achievement on trajectories of school satisfaction among elementary school students: A latent transition analysis.

Meiru Deng, E Scott Huebner, Wang Liu +1 more · 2025 · The British journal of educational psychology · Blackwell Publishing · added 2026-04-24
Exploring how different profiles of academic task values (ATVs) and academic achievement (AA) influence students' school satisfaction should enrich understanding of how school satisfaction develops in Show more
Exploring how different profiles of academic task values (ATVs) and academic achievement (AA) influence students' school satisfaction should enrich understanding of how school satisfaction develops in specific academic situations. This study aimed to identify profiles of ATV (attainment value [AV], utility value [UV]) and AA, as well as heterogeneous trajectories of school satisfaction, and then examine the joint predictive effects of ATV and AA on the development of school satisfaction. A total of 3548 Chinese elementary school students (M Data were collected through self-reports of ATVs and school satisfaction, while AA data were collected from final examination scores at the end of each semester. Latent profile analysis (LPA) and latent class growth analysis revealed six profiles of ATV and AA (i.e., congruent subgroups: congruent-low, congruent-high, congruent-moderate and incongruent subgroups: high ATV-low AA, lower UV-moderate AA, low ATV-moderate AA); and four heterogeneous trajectories of school satisfaction (i.e., high-decreasing, low-stable, high-stable, low-increasing). Latent transition analysis (LTA) indicated that students with congruent levels of AA and ATV were more likely to transition into the optimal school satisfaction groups (high-stable and low-increasing groups), whereas students with greater gaps between AA and ATV were more likely to transition into the adverse groups (i.e., low-stable and high-decreasing groups). These findings highlight the need for educators to tailor interventions to distinct groups to optimize students' school satisfaction. Show less
no PDF DOI: 10.1111/bjep.70054
LPA

Neural Mechanisms of the Impact of Rotated Terrain Symbols on Spatial Representation in Orienteers: Evidence from Eye-Tracking and Whole-Brain fNIRS Synchronization.

Shijia Ou, Tianyu Liu, Yang Liu · 2025 · Behavioral sciences (Basel, Switzerland) · MDPI · added 2026-04-24
Spatial representation is a core element of spatial cognition in orienteering, but the visual-spatial neural modulation mechanisms underlying spatial representations with differently oriented maps hav Show more
Spatial representation is a core element of spatial cognition in orienteering, but the visual-spatial neural modulation mechanisms underlying spatial representations with differently oriented maps have not yet been systematically elucidated. This study recruited 67 orienteering athletes as participants and employed a single-factor (map orientation: normal vs. rotated) between-subjects experimental design. Eye-tracking and functional near-infrared spectroscopy (fNIRS) techniques were used simultaneously to collect behavioral, eye movement, and brain activity data, investigating the effects of map orientation on visual attention and brain activity characteristics during terrain symbol representation processing in orienteering athletes. The results revealed that compared to the normal orientation, the rotated orientation led to significantly decreased task accuracy, significantly prolonged reaction times, and significantly increased saccade amplitude and pupil diameter. Brain activation analysis showed that the rotated orientation elicited significantly higher activation levels in the right dorsolateral prefrontal cortex (R-DLPFC), bilateral parietal lobe cortex (L-PL, R-PL), right temporal lobe (R-TL), and visual cortex (VC) compared to the normal orientation, along with enhanced functional connectivity. Correlation analysis revealed that under normal map orientation, accuracy was positively correlated with both saccade amplitude and pupil diameter; accuracy was positively correlated with activation in the R-DLPFC; saccade amplitude was positively correlated with activation in the R-DLPFC and R-PL; and pupil diameter was positively correlated with activation in the R-DLPFC. Under rotated map orientation, accuracy was positively correlated with saccade amplitude and pupil diameter, and pupil diameter was positively correlated with activation in both the L-PL and R-PL. The results indicate that map orientation significantly influences the visual search patterns and neural activity characteristics of orienteering athletes, impacting task performance through the coupling mode of visual-neural activity. Show less
📄 PDF DOI: 10.3390/bs15101314
LPL

Elevated serum lipoprotein(a) as a prognostic marker for reduced survival in pancreatic cancer.

Jinyue Liu, Yueping Jiang, Yueyi Xing +5 more · 2025 · BMC gastroenterology · BioMed Central · added 2026-04-24
This study aimed to assess the prognostic significance of serum lipoprotein(a) [Lp(a)] levels regarding overall survival (OS) and progression-free survival (PFS) among patients diagnosed with pancreat Show more
This study aimed to assess the prognostic significance of serum lipoprotein(a) [Lp(a)] levels regarding overall survival (OS) and progression-free survival (PFS) among patients diagnosed with pancreatic cancer (PC). A retrospective cohort of 364 pathologically confirmed PC patients treated at the Affiliated Hospital of Qingdao University between January 2019 and December 2022 was analyzed. The optimal cutoff for Lp(a) was identified using X-tile software, allowing categorization into high and low Lp(a) groups. To minimize selection bias, propensity score matching (PSM) was utilized. Survival outcomes were compared using Kaplan-Meier curves and log-rank tests. Cox proportional hazards models were applied to identify independent prognostic variables affecting OS and PFS. Patients with high Lp(a) had significantly shorter OS and PFS both before and after PSM (post-PSM OS: 12.28 vs. 27.67 months, P = 0.003; PFS: 7.00 vs. 11.30 months, P = 0.002). Multivariate Cox analysis confirmed high Lp(a) as an independent predictor of poor OS [HR = 2.11 (1.17-3.81), P = 0.013] and PFS [HR = 2.14 (1.20-3.83), P = 0.010]. In the surgical subgroup (n = 215), high Lp(a) was also associated with worse OS (16.43 vs. 35.47 months, P = 0.02) and PFS (8.40 vs. 11.77 months, P = 0.036). Multivariate analysis in this subgroup showed that high Lp(a) remained an independent risk factor for OS [HR = 2.82 (1.36-5.87), P = 0.006] and PFS [HR = 2.01 (1.06-3.86), P = 0.034]. Elevated serum Lp(a) is an independent predictor of reduced OS and PFS in patients with pancreatic cancer. In contrast to conventional lipid profiles, the genetic stability of Lp(a) makes it a reliable baseline prognostic marker. Show less
📄 PDF DOI: 10.1186/s12876-025-04573-9
LPA

Daily activity accumulation patterns and depressive symptoms among adolescents: a latent profile approach.

Yuwei Liu, Nan Zheng, Huan Chen +3 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between the Show more
This study aims to identify and characterize daily activity accumulation patterns (bouts of physical activity and sedentary behavior) among adolescents and then to explore the associations between these groups and depressive symptoms. A total of 521 adolescents aged 13-18 years from Wuhan and Changsha, China, were included. Bouts of physical activity (PA) and sedentary behavior (SED) were measured using accelerometers. The Center for Epidemiologic Studies Depression Scale was used to assess participants' depressive symptoms. Latent profile analysis was employed to identify distinct groups based on their activity patterns. Three distinct groups were identified: "Prolonged sitters" ( The synergistic effect of strategies to reduce total SED duration by limiting SED bouts to 30 min or less and increasing light physical activity (LPA) may also be effective in alleviating depressive symptoms in adolescents. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1683685
LPA

Tracing the Genetic Heritage of the Kirgiz People: Dual-Wave Admixture and Ancestry-Biased Adaptation.

Shuanghui Chen, Yan Lu, Hao Chen +6 more · 2025 · Molecular biology and evolution · Oxford University Press · added 2026-04-24
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins Show more
The Kirgiz, a Turkic-speaking ethnic group with a rich nomadic heritage, represent a pivotal population for understanding human migration and adaptation in Central Asia. However, their genetic origins and admixture history remain largely unexplored. Here, we present the first comprehensive genomic study of Kirgiz populations from Xinjiang, China (XJ.KGZ, n = 36) and their counterparts in Kyrgyzstan (KRG), integrating genome-wide data of 2,406 global individuals. Our analyses reveal four primary ancestry components in XJ.KGZ: East Asian (41.7%), Siberian (25.6%), West Eurasian (25.2%), and South Asian (7.6%). Despite close genetic affinity (FST = 0.13%), XJ.KGZ and KRG diverged ∼447 years ago, with limited gene flow post-split. A two-wave admixture model elucidates their demographic history: an initial East-West Eurasian mixture ∼2,225 years ago, likely reflecting west-east contacts during the period of the Warring States and the Qin Dynasty, followed by secondary admixture events (∼875 to 425 years ago) linked to historical migrations under Mongol and post-Mongol rule. Local adaptation signatures implicate genes critical for cellular tight junction (e.g. PATJ), pathogen invasion (e.g. OR14I1), and cardiac functions (e.g. RYR2) with allele frequency deviations suggesting ancestry-specific selection. While no classical high-altitude adaptation genes (e.g. EPAS1) showed selection signals, RYR2 and C10orf67-implicated in hypoxia response in Tibetan fauna-displayed Western ancestry bias, hinting at convergent adaptation mechanisms. This study advances our understanding of the genetic makeup and admixture history of the Kirgiz people and provides novel insights into human dispersal in Central Asia. Show less
no PDF DOI: 10.1093/molbev/msaf196
PATJ

Genetic associations of metabolic factors and therapeutic drug targets with polycystic ovary syndrome.

Changlong Zhang, Yuxuan Li, Yang Wang +6 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Polycystic ovary syndrome (PCOS) is frequently accompanied with metabolic dysfunctions, yet the causal relationships between metabolic factors and PCOS remain to be conclusively established and etiolo Show more
Polycystic ovary syndrome (PCOS) is frequently accompanied with metabolic dysfunctions, yet the causal relationships between metabolic factors and PCOS remain to be conclusively established and etiology-based therapies are lacking. To comprehensively identify the metabolic causal factors and potential drug targets for PCOS. This genetic association study was conducted using bidirectional two-sample Mendelian Randomization (MR), multivariable MR (MVMR) and drug-target MR. Considering metabolic sexual dimorphism, female-specific genome-wide association studies (GWASs) for metabolic factors were obtained. To ensure the robustness of the findings, an additional independent PCOS GWAS dataset was utilized for replication. The PCOS cohort included 10,074 PCOS cases (mean age 28 to 45 years) and 103,164 controls (mean age 27 to 60 years) of European ancestry. All participants were female. Employing two-sample MR analysis, we found that genetically proxied body mass index (BMI) (OR = 3.40 [95 % CI, 2.65-4.36]), triglyceride (TG) (OR = 1.54 [95 % CI, 1.17-2.04]), low-density lipoprotein cholesterol (LDL-c) (OR = 1.37 [95 % CI, 1.07-1.76]), and type 2 diabetes (T2D) (OR = 1.24 [95 % CI, 1.09-1.41]) were significantly associated with an increased risk of PCOS, whereas genetically predicted high-density lipoprotein cholesterol (HDL-c) (OR = 0.61 [95 % CI, 0.47-0.80]) decreased the odds of PCOS. Stepwise MVMR established a hierarchy of interactions among these metabolic factors, identifying BMI and HDL-c as the most prominent causal factors. Notably, drug-target MR analysis identified incretin-based therapeutics, PCSK9 inhibitors, LPL gene therapy, sulfonylureas, and thiazolidinediones as potential therapeutics for PCOS. All these findings were validated in an independent dataset. This study offered insights into the roles of obesity, diabetes, and dyslipidemia in PCOS etiology and therapeutics, underscoring the necessity for managing metabolic health in women and paving the way for tailored therapeutic strategies for PCOS based on its metabolic underpinnings. Show less
📄 PDF DOI: 10.1016/j.jare.2024.10.038
LPL