👤 Lijun Liu

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

Derazantinib Inhibits the Planktonic Growth and Biofilm Formation of

Xiaoju Liu, Congcong Li, Qingyin Meng +7 more · 2025 · ACS infectious diseases · ACS Publications · added 2026-04-24
Derazantinib (DZB), a pan-fibroblast growth factor receptor (FGFR) inhibitor, exhibits potent activity against FGFR1-3 kinases and has been clinically approved for antitumor therapy. However, its anti Show more
Derazantinib (DZB), a pan-fibroblast growth factor receptor (FGFR) inhibitor, exhibits potent activity against FGFR1-3 kinases and has been clinically approved for antitumor therapy. However, its antibacterial properties remain unknown. Here, we demonstrated that DZB displays broad-spectrum activity against Show less
no PDF DOI: 10.1021/acsinfecdis.4c01020
FGFR1

Latent profiles of death anxiety among young adults: associations with self-esteem, security, and perceived social support.

Jingxian Yu, Mingjie Wu, Yongqi Liang +3 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profil Show more
Death anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profiles of death anxiety in Chinese youth and examine the predictive roles of self-esteem, perceived social support, and security. We conducted a cross-sectional survey of 623 young adults ( Three latent death anxiety profiles emerged, High Death Anxiety (56.2%), Moderate Cognition and Low Death Anxiety (8.8%), and Low Cognition and Moderate Death Anxiety (35%). Higher self-esteem ( Death anxiety among young adults is heterogeneous, influenced by distinct psychological profiles and demographic factors. Interventions should prioritize enhancing self-esteem, social support networks, and security to mitigate death anxiety, especially in high-risk subgroups. Future research should employ longitudinal designs and cross-cultural samples to validate causal pathways and refine targeted strategies. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1594720
LPA

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

Social Bonds Retain Oxytocin-Mediated Brain-Liver Axis to Retard Atherosclerosis.

Seien Ko, Atsushi Anzai, Xueyuan Liu +15 more · 2025 · Circulation research · added 2026-04-24
Social interaction with others is essential to life. Although social isolation and loneliness have been implicated as increased risks of cardiometabolic and cardiovascular diseases and all-cause morta Show more
Social interaction with others is essential to life. Although social isolation and loneliness have been implicated as increased risks of cardiometabolic and cardiovascular diseases and all-cause mortality, the cellular and molecular mechanisms by which social connection maintains cardiometabolic and cardiovascular health remain largely unresolved. To investigate how social connection protects against cardiometabolic and cardiovascular diseases, atherosclerosis-prone, high-fat diet-fed These results identify a novel brain-liver axis that links sociality to hepatic lipid metabolism, thus proposing a potential therapeutic strategy for loneliness-associated atherosclerosis progression. Show less
no PDF DOI: 10.1161/CIRCRESAHA.124.324638
ANGPTL4

Molecular mechanism of phosphorylation-mediated impacts on the conformation dynamics of ligand-bound BACE1 probed by Gaussian accelerated molecular dynamics.

Chaoyue Jia, Yanqi Sun, Jianzhong Chen +1 more · 2025 · Physical chemistry chemical physics : PCCP · Royal Society of Chemistry · added 2026-04-24
Alzheimer's disease (AD) is a chronic neurodegenerative disorder predominantly affecting the elderly population. The pathogenesis of AD involves the production of highly neurotoxic amyloid-β peptide 1 Show more
Alzheimer's disease (AD) is a chronic neurodegenerative disorder predominantly affecting the elderly population. The pathogenesis of AD involves the production of highly neurotoxic amyloid-β peptide 1-42 (Aβ Show less
no PDF DOI: 10.1039/d5cp00895f
BACE1

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

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

New Insights into Genetic Diversity and Differentiation of 11 Buffalo Populations Using Validated SNPs for Dairy Improvement.

Alfredo Pauciullo, Giustino Gaspa, Carmine Versace +13 more · 2025 · Genes · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/genes16040400
LPL

Molecular mechanisms of synovial pathology in osteoarthritis: insights from CXCL10 and MC4R expression.

Tao Yang, Hong Liu, Jian Chen · 2025 · Genes & genomics · Springer · added 2026-04-24
Osteoarthritis (OA) is a common progressive joint disorder marked by synovial inflammation, cartilage degeneration, the formation of osteophytes, though its underlying molecular mechanisms remain uncl Show more
Osteoarthritis (OA) is a common progressive joint disorder marked by synovial inflammation, cartilage degeneration, the formation of osteophytes, though its underlying molecular mechanisms remain unclear. This study integrated bioinformatics and experimental validation to identify key genes in OA synovium and their association with immune infiltration. Analysis of the GSE82107 dataset (10 OA, 7 controls) revealed 909 differentially expressed genes (525 upregulated, 384 downregulated). WGCNA identified the "midnightblue" module, and its intersection with DEGs yielded 122 genes enriched in cytokine-cytokine receptor interaction, JAK-STAT signaling, and autophagy pathways. Protein-protein interaction analysis highlighted FLT3LG, MC4R, CXCL10, CARTPT, and LHX2 as core genes (AUC 0.743-0.871). Immune infiltration analysis showed elevated M0 macrophages in OA, with CXCL10 showing a strong positive correlation with M1 macrophage infiltration (r = 0.74), and MC4R correlating with the presence of follicular helper T cells (r = 0.85). In vitro, OA-derived fibroblast-like synoviocytes exhibited CXCL10 upregulation, MC4R downregulation, and increased IL-6, IL-8, and TNF-α secretion, which were markedly reduced by CXCL10 knockdown or MC4R overexpression. Synovial tissue assays confirmed these expression patterns. CXCL10 and MC4R may represent promising diagnostic markers and therapeutic targets, offering new insights into OA immunopathogenesis and precision intervention. Show less
📄 PDF DOI: 10.1007/s13258-025-01679-y
MC4R

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

Talin1 modulates the Piezo1-YAP axis to regulate endothelial cell inflammation and atherosclerosis.

Yingzi Wang, Haozhong Huang, Zihao Liu +5 more · 2025 · Cellular and molecular life sciences : CMLS · Springer · added 2026-04-24
Atherosclerosis is a chronic vascular inflammatory disease caused by multiple factors. Anti-inflammatory treatment is an effective approach to treat atherosclerosis. Talin1 is a cell membrane-associat Show more
Atherosclerosis is a chronic vascular inflammatory disease caused by multiple factors. Anti-inflammatory treatment is an effective approach to treat atherosclerosis. Talin1 is a cell membrane-associated cytoskeletal protein that is widely expressed in mammals and plays essential roles in angiogenesis and endothelial cell barrier function. However, the role of Talin1 in atherosclerosis and the related mechanisms remains unclear. ApoE-KO mice were subjected to partial carotid artery ligation to establish an atherosclerosis model, and the expression of Talin1 in atherosclerotic plaques was verified in vivo. Human umbilical vein endothelial cells (HUVECs) and aortic endothelial cells (HAECs) were treated with tumour necrosis factor α (TNF-α) (10 ng/mL) and subjected to low oscillatory shear stress (OSS) (approximately ± 4 dyn/cm2) to establish cellular inflammation models. A lentivirus was used to regulate Talin1 expression in HUVECs and HAECs. Talin1 levels were increased in the serum of subjects with coronary heart disease (CHD) compared with those without CHD. We also found that Talin1 levels were increased in the serum of ApoE-KO mice in the operation group compared with the sham operation group. In addition, Talin1 expression was increased in endothelial cells in atherosclerotic plaques. In addition, neither TNF-α nor OSS promoted inflammation in endothelial cells with Talin1 knockdown. Moreover, we found that TNF-α and OSS could activate Piezo1 to mediate Ca²⁺ influx and subsequently activate Talin1 to regulate YAP and promote inflammation. The results of this study suggest that Talin1 plays a vital role in endothelial inflammation and may be a novel anti-inflammatory therapeutic target for atherosclerosis. Show less
📄 PDF DOI: 10.1007/s00018-025-06026-8
APOE

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

Pediatric diffuse low-grade glioma with oligodendroglioma-like features: A case report.

Pengwei Hou, Chengzhu Cai, Meiyan Liu +2 more · 2025 · Experimental and therapeutic medicine · added 2026-04-24
The present case report presents the diagnostic challenges of pediatric diffuse low-grade glioma (pDLGG) with oligodendroglioma-like features. The patient, an 11-year-old girl, presented with refracto Show more
The present case report presents the diagnostic challenges of pediatric diffuse low-grade glioma (pDLGG) with oligodendroglioma-like features. The patient, an 11-year-old girl, presented with refractory epilepsy and brain imaging did not provide a clear diagnosis. Intraoperatively, the tumor appeared gray-yellow to gray-red, with moderate texture and unclear borders, consistent with LGG. Postoperative pathology showed diffuse infiltrative growth of the tumor, with pleomorphic cell morphology and oligodendroglioma-like gliocyte proliferation. Staining was positive for markers such as glial fibrillary acidic protein and Olig-2. Genomic analysis revealed BRAF V600E, fibroblast growth factor receptor (FGFR)1 and FGFR4 mutations, but no IDH mutations or other related mutations. The final diagnosis was pDLGG with alterations in the MAPK pathway. The present case underscores the importance of molecular and histological features in the diagnosis of pDLGG, especially when clinical and imaging characteristics are atypical, as molecular diagnostics provide key insights for disease classification. Show less
📄 PDF DOI: 10.3892/etm.2025.12985
FGFR1

Unveiling circulating targets in pancreatic cancer: Insights from proteogenomic evidence and clinical cohorts.

Haokang Feng, Zhixue Chen, Jianang Li +13 more · 2025 · iScience · Elsevier · added 2026-04-24
Pancreatic cancer (PC), characterized by the absence of effective biomarkers and therapies, remains highly fatal. Data regarding the correlations between PC risk and individual plasma proteome known f Show more
Pancreatic cancer (PC), characterized by the absence of effective biomarkers and therapies, remains highly fatal. Data regarding the correlations between PC risk and individual plasma proteome known for minimally invasive biomarkers are scarce. Here, we analyzed 1,345 human plasma proteins using proteome-wide association studies, identifying 78 proteins significantly associated with PC risk. Of these, four proteins (ROR1, FN1, APOA5, and ABO) showed the most substantial causal link to PC, confirmed through Mendelian randomization and colocalization analyses. Data from two clinical cohorts further demonstrated that FN1 and ABO were notably overexpressed in both blood and tumor samples from PC patients, compared to healthy controls or para-tumor tissues. Additionally, elevated FN1 and ABO levels correlated with shorter median survival in patients. Multiple drugs targeting FN1 or ROR1 are available or in clinical trials. These findings suggest that plasma protein FN1 associated with PC holds potential as both prognostic biomarkers and therapeutic targets. Show less
📄 PDF DOI: 10.1016/j.isci.2024.111693
APOA5

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

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

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

Multivariate genome-wide analyses of insulin resistance unravel novel loci and therapeutic targets for cardiometabolic health.

Chaojie Ye, Chun Dou, Dong Liu +13 more · 2025 · Nature communications · Nature · added 2026-04-24
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide assoc Show more
Limited identification of insulin resistance-associated loci hinders understanding of its role in cardiometabolic health, impeding therapeutic strategies. We apply three multivariate genome-wide association study approaches on homeostatic model assessment for insulin resistance, insulin resistance index, fasting insulin, and ratio of triglycerides to high-density lipoprotein cholesterol from MAGIC and UK Biobank to develop a comprehensive phenotype ('mvIR'), and identify 217 independent loci, including 24 novel loci. The mvIR is causally associated with higher risks of 17 cardiometabolic diseases and five aging phenotypes, independent of adiposity and sarcopenia. We outline 21 of 2644 druggable genes for insulin resistance by Mendelian randomization and colocalization, where six genes (AKT1, ERBB3, FCGR1A, FGFR1, LPL, NR1H3) encode targets for approved drugs with consistent directions in alleviating insulin resistance, with no significant side effects revealed by phenome-wide association study. This study uncovers novel loci and therapeutic targets to inform strategies promoting insulin resistance-centered cardiometabolic health and longevity. Show less
📄 PDF DOI: 10.1038/s41467-025-64985-9
FGFR1

Relationship between serum ApoB-100 and lumbar bone mineral density in postmenopausal women: a retrospective analysis of a health screening population.

Qing-Wu Wu, Shi-Li Gu, Yang-Yang Chen +4 more · 2025 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Postmenopausal women are at elevated risk for osteoporosis and dysregulated lipid metabolism. While the relationship between conventional lipid markers and bone mineral density (BMD) remains controver Show more
Postmenopausal women are at elevated risk for osteoporosis and dysregulated lipid metabolism. While the relationship between conventional lipid markers and bone mineral density (BMD) remains controversial, the association between apolipoprotein B-100 (ApoB-100) (an established independent predictor of atherosclerosis) and bone metabolism in postmenopausal women remains poorly understood. This study investigated the relationship between ApoB-100 and lumbar BMD in postmenopausal women, with specific focus on potential inflammatory and platelet-mediated pathways. We conducted a cross-sectional study of 1,429 postmenopausal women who underwent health screening at the First Affiliated Hospital of Xinxiang Medical University between January 2022 and December 2024. ApoB-100 levels were measured by immunoturbidimetry, and lumbar BMD was assessed using low-dose chest CT imaging. Participants were stratified into tertiles based on ApoB-100 levels. We employed univariate and multivariate regression analyses to evaluate the relationship between lumbar BMD and ApoB-100. Generalized additive models with smooth curve fitting were used to characterize the linear relationship. Subgroup analyses assessed the consistency of associations across different populations, while mediation models quantified the intermediary roles of the neutrophil-to-lymphocyte ratio (NLR) and platelet count. After multivariate adjustment, ApoB-100 demonstrated a significant independent negative correlation with lumbar BMD (β=-6.37, 95%CI: -9.26 to -3.49). This association was more pronounced in women younger than 60 years (β=-10.18, 95%CI: -13.94 to -6.42), those with BMI≥28kg/m² (β=-10.73, 95%CI: -15.31 to -0.86), and those without hypertension (β=-7.3, 95%CI: -10.42 to -4.19). Mediation analysis revealed that NLR accounted for 8.17% of the negative association between ApoB-100 and lumbar BMD, while platelet count showed a suppressive indirect association (20.60%). ApoB-100 exhibits an independent negative association with lumbar BMD in postmenopausal women, partially mediated through inflammatory and platelet pathways. These findings support the potential utility of ApoB-100 as a biomarker for osteoporosis risk assessment in postmenopausal women, particularly within specific high-risk subgroups. Show less
📄 PDF DOI: 10.3389/fendo.2025.1667161
APOB

Genetically Predicted Gene Expression Effects on Changes in Red Blood Cell and Plasma Polyunsaturated Fatty Acids.

Nikhil K Khankari, Timothy Su, Qiuyin Cai +8 more · 2025 · Genetic epidemiology · Wiley · added 2026-04-24
Polyunsaturated fatty acids (PUFAs) including omega-3 and omega-6 are obtained from diet and can be measured objectively in plasma or red blood cells (RBCs) membrane biomarkers, representing different Show more
Polyunsaturated fatty acids (PUFAs) including omega-3 and omega-6 are obtained from diet and can be measured objectively in plasma or red blood cells (RBCs) membrane biomarkers, representing different dietary exposure windows. In vivo conversion of omega-3 and omega-6 PUFAs from short- to long-chain counterparts occurs via a shared metabolic pathway involving fatty acid desaturases and elongase. This analysis leveraged genome-wide association study (GWAS) summary statistics for RBC and plasma PUFAs, along with expression quantitative trait loci (eQTL) to estimate tissue-specific genetically predicted gene expression effects for delta-5 desaturase (FADS1), delta-6 desaturase (FADS2), and elongase (ELOVL2) on changes in RBC and plasma biomarkers. Using colocalization, we identified shared variants associated with both increased gene expression and changes in RBC PUFA levels in relevant PUFA metabolism tissues (i.e., adipose, liver, muscle, and whole blood). We observed differences in RBC versus plasma PUFA levels for genetically predicted increase in FADS1 and FADS2 gene expression, primarily for omega-6 PUFAs linoleic acid (LA) and arachidonic acid (AA). The colocalization analysis identified rs102275 to be significantly associated with a 0.69% increase in total RBC membrane-bound LA levels (p = 5.4 × 10 Show less
📄 PDF DOI: 10.1002/gepi.22613
FADS1

Rational Design and Identification of ISM7594 as a Tissue-Agnostic FGFR2/3 Inhibitor.

Yazhou Wang, Jinxin Liu, Yihong Zhang +14 more · 2025 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
The selective inhibition of fibroblast growth factor receptors (FGFR) presents a significant challenge due to the high degree of sequence and the close structural similarity of the subtypes. Herein, w Show more
The selective inhibition of fibroblast growth factor receptors (FGFR) presents a significant challenge due to the high degree of sequence and the close structural similarity of the subtypes. Herein, we designed selective dual FGFR2/3 inhibitors based on the in-depth understanding of protein-ligand interaction contributions. We efficiently identified ISM7594 ( Show less
no PDF DOI: 10.1021/acs.jmedchem.5c00928
FGFR1

PIK3C3 influences immune cell function by modulating autophagy to exert anti-inflammatory effects in sepsis.

Jiangming Wei, Fanghua Xu, Xiaobo Wei +2 more · 2025 · Gene · Elsevier · added 2026-04-24
Sepsis is a syndrome caused by an imbalance in the host's immune response to pathogen infection, which can lead to systemic multiple organ dysfunction. Its pathological mechanisms are complex, and the Show more
Sepsis is a syndrome caused by an imbalance in the host's immune response to pathogen infection, which can lead to systemic multiple organ dysfunction. Its pathological mechanisms are complex, and there are no specific biomarkers or targeted therapeutic drugs available. Recent investigations have revealed that phosphatidylinositol 3-kinase class III (PIK3C3/VPS34), a key regulator of autophagy, plays a critical immunomodulatory role. Specifically, PIK3C3 influences the activation, proliferation, survival, and apoptosis of immune cells. However, the precise mechanistic contribution of PIK3C3 to the pathogenesis of sepsis remains incompletely understood, with existing studies largely emphasizing its autophagy-related functions. Therefore, this review provides a comprehensive overview of PIK3C3 expression and function in immune cells, focusing on elucidating the molecular signaling pathways through which it modulates cellular metabolism and function via autophagy. By integrating our current understanding of immune cell involvement in the pathophysiology of sepsis, we propose that targeting PIK3C3 may represent a promising immunotherapeutic strategy to restore immune homeostasis and improve clinical outcomes in sepsis. This approach may offer novel avenues for the prevention and management of this life-threatening condition. Show less
no PDF DOI: 10.1016/j.gene.2025.149732
PIK3C3

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

Targeted delivery of BACE1 siRNA for synergistic treatment of Alzheimer's disease.

Zhaohan Li, Jun Yang, Jianan Li +10 more · 2025 · Translational neurodegeneration · BioMed Central · added 2026-04-24
The deposition of toxic aggregated amyloid-β (Aβ), resulting from continuous cleavage of amyloid precursor protein (APP) by β-site APP cleaving enzyme 1 (BACE1) and γ-secretase, is a key pathogenic ev Show more
The deposition of toxic aggregated amyloid-β (Aβ), resulting from continuous cleavage of amyloid precursor protein (APP) by β-site APP cleaving enzyme 1 (BACE1) and γ-secretase, is a key pathogenic event in Alzheimer's disease (AD). Small interfering RNAs (siRNA) have shown great potential for disease treatment by specifically silencing target genes. However, the poor brain delivery efficiency of siRNAs limits their therapeutic efficacy against AD. We designed a simplified and effective BACE1 siRNA (siBACE1) delivery system, namely, dendritic polyamidoamine modified with the neurotropic virus-derived peptide RVG29 and polyethylene glycol (PPR@siBACE1). PPR@siBACE1 crossed the blood-brain barrier efficiently and entered brain parenchyma in large amount, with subsequent neurotropism and potential microglia-targeting ability. Both in vitro and in vivo studies validated the effective brain delivery of siBACE1 and strong BACE1 silencing efficiency. Treatment of AD mice with PPR@siBACE1 inhibited the production of Aβ, potentiated Aβ phagocytosis by microglia, improved the memory deficits and reduced neuroinflammatory response in AD mice. This study provides a reliable delivery platform for gene therapies for AD. Show less
📄 PDF DOI: 10.1186/s40035-025-00503-7
BACE1

RNA G-quadruplex removal promotes a translational switch after meiosis resumption.

Qiong-Wen Lu, Shao-Yuan Liu, Xiu-Quan Liao +6 more · 2025 · Nucleic acids research · Oxford University Press · added 2026-04-24
Oocyte maturation-coupled mRNA post-transcriptional regulation is essential for the establishment of developmental potential. Previously, oocyte mRNA translation efficiencies focused on the trans-regu Show more
Oocyte maturation-coupled mRNA post-transcriptional regulation is essential for the establishment of developmental potential. Previously, oocyte mRNA translation efficiencies focused on the trans-regulation of key RNA-binding protein (RBPs), rarely related to RNA structure. RNA G-quadruplexes (rG4s) are four-stranded RNA secondary structures involved in many different aspects of RNA metabolism. In this study, we have developed a low-input technique for rG4 detection (G4-LACE-seq) in mouse oocytes and found that rG4s were widely distributed in maternal transcripts, with enrichment in untranslated regions, and they underwent transcriptome-wide removal during meiotic maturation. The rG4-selective small-molecule ligand BYBX stabilized rG4s in the oocyte transcriptome and impaired spindle assembly and meiotic cell cycle progression. The proteomic spectrum results revealed that rG4 accumulation weakened the binding of a large number of RBPs to mRNAs, especially those associated with translational initiation. Ribosomal immunoprecipitation and translational reporter assays further proved that rG4s in the untranslated regions negatively affected the translational efficiency of key maternal mRNAs. Overexpression DEAH/RHA family helicase-36 partially reverses BYBX-induced oocyte developmental defects, suggesting its importance in rG4 regulation. Collectively, this study describes the distribution, dynamic changes, and regulation of rG4s in the mouse maternal transcriptome. Before meiosis resumption, a large number of rG4s in oocytes are necessary to maintain the translatome at a low level, and DHX36-mediated rG4 removal promotes a translational switch and is required for successful maternal-to-zygotic transition. Show less
📄 PDF DOI: 10.1093/nar/gkaf067
DHX36

Improving Light-Responsive Efficiency of Type II Porous Liquid by Tailoring the Functionality of Host.

Yang Liu, Han-Yan Jin, Meng-Meng Li +6 more · 2025 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report t Show more
Light-responsive porous liquids (LPLs) attract significant attention for their controllable gas uptake under light irradiation, while their preparation has remained a great challenge. Here we report the fabrication of type II LPLs with enhanced light-responsive efficiency by tailoring the host's functionality for the first time. The functionality of light-responsive metal-organic cage (MOC-RL, constructed from dicopper and responsive ligands) is modified by introducing the second long-chain alkyl ligand, producing MOC-RL-AL as a new host. A spatially hindered solvent based on polyethylene glycol, IL-NTf Show less
no PDF DOI: 10.1002/anie.202501191
LPL

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

Orally deliverable biomimetic nucleic acid therapies for targeted treatment of atherosclerosis.

Chenwen Li, Yidan Chen, Yuan Li +9 more · 2025 · Acta pharmaceutica Sinica. B · Elsevier · added 2026-04-24
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate Show more
Accumulating evidence has demonstrated that nucleic acid-based therapies are promising for atherosclerosis. However, nearly all nucleic acid delivery systems developed for atherosclerosis necessitate injection, which results in rapid elimination and poor patient compliance. Consequently, oral delivery strategies capable of targeting atherosclerotic plaques are imperative for nucleic acid therapeutics. Herein we report the development of yeast-derived capsules (YCs) packaging an antisense oligonucleotide (AM33) targeting microRNA-33 (miR-33) for the oral treatment of atherosclerosis. YCs provide stability for AM33, preventing its premature release in the gastrointestinal tract. AM33-containing YCs, defined as YAM33, showed high transfection in macrophages, thus promoting cholesterol efflux and inhibiting foam cell formation by regulating the target genes/proteins of miR-33. Orally delivered YAM33 effectively accumulated within atherosclerotic plaques in Show less
📄 PDF DOI: 10.1016/j.apsb.2025.07.039
APOE

Comorbidity patterns and immune-metabolic differences in patients with acute-episode of schizophrenia spectrum disorders.

Guoping Wu, Zhe Dong, Zhongcai Li +12 more · 2025 · Schizophrenia (Heidelberg, Germany) · Nature · added 2026-04-24
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause Show more
Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15-20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20-F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width-coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = -0.173) and hematocrit (HCT; β = -35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = -9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research. Show less
📄 PDF DOI: 10.1038/s41537-025-00646-6
APOB

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