👤 Shuang 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, 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, 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

Genetic variations for bean color of duck beak revealed by genome-wide association study.

Jingjing Qi, Qian Hu, Yang Xi +5 more · 2025 · Animal genetics · Blackwell Publishing · added 2026-04-24
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed Show more
The beak bean, found only in waterfowl and Galliformes, aids in foraging, self-defense and pecking hard objects. Its rich coloration results from prolonged evolutionary adaptation. This study analyzed beak bean phenotypes of duck at 10, 20, 30 and 40 days of age, revealing that the most common type is the black beak bean, characterized by melanin deposition on the beak surface. This study performed single nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) to investigate the genetic basis of beak bean color, identifying signals on chromosome 1. The copy number variation region-based GWAS revealed a consistent candidate region overlapping with the SNP-based GWAS signals, further supporting the importance of this genomic region. Locus zoom analysis further refined the candidate regions to 48.5-50.5 and 50.8-52.8 Mb. Functional enrichment analysis highlighted six candidate genes within these regions: KITLG, DUSP6, GALNT4, MGAT4C, ATP2B1 and NTS. Notably, KITLG and DUSP6, which are linked to melanin production, were identified as key candidate genes for beak bean color. Our finding revealed the genetic basis of the bean color traits for the first time in ducks, providing a theoretical foundation and technological framework for enhancing duck beak coloration. Show less
no PDF DOI: 10.1111/age.70040
DUSP6

Accelerometer-measured intensity-specific physical activity, genetic susceptibility, and back pain risk: a UK biobank cohort study.

Yuanpeng Zhu, Di Liu, Xiangjie Yin +3 more · 2025 · The spine journal : official journal of the North American Spine Society · Elsevier · added 2026-04-24
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose Show more
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose-response relationships and interactions between PA and genetic susceptibility remains limited. To determine the relationships between accelerometer-measured total and intensity-specific PA and incident back pain, and to assess potential effect modification by polygenic risk scores (PRS). Prospective, large-scale, population-based study using UK Biobank data. UK Biobank participants who wore wrist accelerometers for 7 days (N=71,601). Incident back pain, defined as the first recorded ICD-10 dorsalgia code (M54). Total PA, light PA (LPA), and moderate-to-vigorous PA (MVPA) were derived using validated machine-learning algorithms from raw accelerometer data. Dose-response relationships were modeled using restricted cubic splines within Cox proportional hazards models, with adjustment for and stratification by a polygenic risk score (PRS). Point estimates for the population attributable fraction (PAF) were then calculated. Body mass index (BMI) mediation was assessed. Over a median follow-up of 7.0 years, total PA and MVPA exhibited nonlinear inverse associations with incident back pain, independent of genetic risk, with thresholds at approximately 35 milli-g (total PA) and 60 min/day (MVPA). The adjusted PAF was 15.9% for low MVPA and 9.9% for low total PA. Associations were strongest for MVPA, followed by total PA; no significant association was observed for LPA. Within both PRS strata, risk declined monotonically across PA quartiles, with similar effect sizes and no PA × PRS interaction. Notably, participants with high PRS and high PA had lower risk than those with low PRS and low PA. BMI mediated 26.2% of the total PA association and 15.5% of the MVPA association. Accelerometer-measured MVPA robustly reduces back-pain risk, independent of genetic predisposition. Future guidelines should provide clear, intensity-specific recommendations and account for the observed nonlinear dose-response to optimize prevention. Show less
no PDF DOI: 10.1016/j.spinee.2025.10.021
LPA

Oxymatrine regulates microglia to produce IFN-β by activating the STING/TBK1/IRF3 pathway against experimental autoimmune encephalomyelitis.

Shuang-Shuang Wang, Xin Jin, Wen-Di Ma +9 more · 2025 · European journal of pharmacology · Elsevier · added 2026-04-24
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple Show more
Oxymatrine is an alkaloid with the property of immunomodulation. Recent studies have demonstrated that oxymatrine inhibits experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis (MS), by promoting the production of interferon-β (IFN-β). However, the mechanism through which oxymatrine regulates the production of IFN-β remains unclear. The aim of this study was to investigate the pharmacological effects and related molecular mechanisms of oxymatrine in the treatment of EAE through in vivo and in vitro experiments. Oxymatrine alleviated neurological dysfunction, demyelination, and inflammation in EAE mice. It reduced microglia/macrophage infiltration and polarization, lowered pro-inflammatory cytokine levels (iNOS, TNF-α), and enhanced the expression of IL-10 and IL-27. Additionally, oxymatrine upregulated the STING/TBK1/IRF3 signaling pathway in EAE mice, promoting IFN-β production by microglia. Similarly, in LPS-induced BV2 cells, oxymatrine suppressed inflammatory factors and activated the STING/TBK1/IRF3 pathway to enhance IFN-β production. Notably, treatment with the STING inhibitor, C176, reversed these effects in both EAE mice and LPS-induced BV2 cells, confirming the pathway's critical role in the mechanism of oxymatrine therapy. Oxymatrine promotes IFN-β production in microglia by upregulating the STING/TBK1/IRF3 signaling pathway, thereby alleviating the neurological dysfunction of EAE and reducing pathological and inflammatory events. This study identifies a novel anti-EAE mechanism of oxymatrine: promoting IFN-β production in microglia by activating the STING/TBK1/IRF3 pathway. However, it lacks clinical sample verification. If validated later, oxymatrine may provide a more economical, convenient endogenous IFN-β induction regimen for MS patients. Show less
no PDF DOI: 10.1016/j.ejphar.2025.178380
IL27

Oral Sheep Milk-Derived Exosome Therapeutics for

Zhimin Wu, Shuo Yan, Huimin Zhang +6 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Cadmium (Cd) contamination in plants and soil poses significant risks to livestock, particularly sheep. Cd exposure often leads to severe gastrointestinal diseases in sheep that are difficult to treat Show more
Cadmium (Cd) contamination in plants and soil poses significant risks to livestock, particularly sheep. Cd exposure often leads to severe gastrointestinal diseases in sheep that are difficult to treat. Milk-derived exosomes, particularly those from sheep milk (SM-Exo), have shown potential in treating gastrointestinal disorders, though their efficacy in Cd-induced colitis remains unclear. In this study, we investigated the therapeutic potential of SM-Exo in a Cd-induced colitis model. Hu sheep were exposed to Cd, and their fecal microbiota were collected to prepare bacterial solutions for fecal microbiota transplantation (FMT) in mice. The changes in gut microbiota and gene expression were analyzed through microbiome and transcriptomics. Our results showed that prior to treatment, harmful bacteria (e.g., Show less
📄 PDF DOI: 10.3390/ijms26073299
ADCY3

A whole-animal phenotypic drug screen identifies suppressors of atherogenic lipoproteins.

Daniel J Kelpsch, Liyun Zhang, James H Thierer +9 more · 2025 · bioRxiv : the preprint server for biology · Cold Spring Harbor Laboratory · added 2026-04-24
Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which a Show more
Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which are responsible for transporting lipids to peripheral tissues. The cellular mechanisms that regulate ApoB and B-lp production, secretion, transport, and degradation remain to be fully defined. In humans, elevated levels of vascular B-lps play a causative role in cardiovascular disease. Previously, we have detailed that human B-lp biology is remarkably conserved in the zebrafish using an Show less
📄 PDF DOI: 10.1101/2024.11.14.623618
APOB

Impact of an extended light regimen imposed during nursery period on the performance and lipid metabolism of weanling pigs.

Guangfan Liu, Fen Su, Xingyue Zou +2 more · 2025 · Animal bioscience · added 2026-04-24
This study aimed to assess the impact of a prolonged photoperiod on the growth performance and lipid metabolism of weaned piglets. Twenty-four piglets weaned at 28 days of age were randomly dichotomiz Show more
This study aimed to assess the impact of a prolonged photoperiod on the growth performance and lipid metabolism of weaned piglets. Twenty-four piglets weaned at 28 days of age were randomly dichotomized into two groups that were alternatively subjected to either long photoperiod (LP) group (16 L:8 D) or short photoperiod (SP) group (10 L:14 D) for 42days. Four replicates of three animals per replicates were used per experimental treatment. Our results demonstrated that prolonged photoperiod increased piglet body weight, average daily weight gain (ADG), backfat thickness (BF), backfat index during the nursery period, and increased ADG, average daily feed intake (ADFI), and decreased the F/G of piglets during the experiment days 29 to 42. Meanwhile, we observed LP piglets' plasma melatonin, growth hormone and serotonin levels were decreased at 14 d and 42 d compared to SP piglets. Moreover, up-regulated mRNA or protein expression of PPARγ and CEBPα, and lower mRNA or protein expression of MTR1, ATGL, HSL, PPARα, and CPT1α, were observed in back subcutaneous fat of LP group compared with that of SP group. Significant increases were observed in the mRNA or protein contents of lipogenic genes, including C/EBPα, SREBP-1c, ACCα, and FAS, in the liver of LP piglets, whereas CPT1α and ACOX1 mRNA levels and PPARα and MTR1 protein expression were significantly downregulated in LP group compared to SP group. Extended photoperiod also increased lipid content in longissimus dorsi muscle that was associated with higher mRNA or protein levels of SREBP-1c, ACCα, FAS, Pref1, and LPL, decreased mRNA or protein contents of LeptinR, MTR1, HSL, and ACOX1. Together, these findings suggest that there is an advantage, in terms of growth performance and fat deposition, in imposing a prolonged light program (16-h light/d) on nursery piglets to alleviate the negative aspects of weaning stress. Show less
📄 PDF DOI: 10.5713/ab.24.0270
LPL

Single-cell transcriptomic profiling reveals liver fibrosis in colorectal cancer liver metastasis.

Yiqiao Deng, Chengyao Guo, Xiaomeng Liu +14 more · 2025 · Experimental & molecular medicine · Nature · added 2026-04-24
Tumor fibrosis is recognized as a malignant hallmark in various solid tumors; however, the clinical importance and associated molecular characteristics of tumor fibrosis in liver metastases (LM) from Show more
Tumor fibrosis is recognized as a malignant hallmark in various solid tumors; however, the clinical importance and associated molecular characteristics of tumor fibrosis in liver metastases (LM) from colorectal cancer (CRLM) remain poorly understood. Here we show that patients with CRLM whose liver metastases (LM) exhibited tumor fibrosis (Fibrosis+ LM) had significantly worse progression-free survival (P = 0.025) and overall survival (P = 0.008). Single-cell RNA sequencing revealed that the tumor microenvironment of the Fibrosis+ LM was characterized by T cells with an exhausted phenotype, macrophages displaying a profibrotic and suppressive phenotype and fibrosis-promoting fibroblasts. Further investigation highlighted the pivotal role of VCAN_eCAF in remodeling the tumor fibrosis in the tumor microenvironment of Fibrosis+ LM, emphasizing potential targetable interactions such as FGF23 or FGF3-FGFR1. Validation through multiplex immunohistochemistry/immunofluorescence and spatial transcriptomics supported these findings. Here we present a comprehensive single-cell atlas of tumor fibrosis in LM, revealing the intricate multicellular environment and molecular features associated with it. These insights deepen our understanding of tumor fibrosis mechanisms and inform improved clinical diagnosis and treatment strategies. Show less
📄 PDF DOI: 10.1038/s12276-025-01573-3
FGFR1

Illuminating the FGFR fusion landscape in Chinese patients: unveiling novel molecular insights and clinical implications.

Zhuo Liu, Dandan Zhao, Baoming Wang +14 more · 2025 · The oncologist · Oxford University Press · added 2026-04-24
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusi Show more
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusion partner distribution, and unique kinase domain distribution. We conducted a multicenter study to comprehensively profile FGFR fusions in the largest Chinese pan-cancer cohort to date, comprising 118 FGFR fusions from 114 individuals. Both DNA- and RNA-based sequencing approaches were utilized to reveal novel and fundamental features of FGFR fusion. Our research reveals an incidence rate of 0.96% for FGFR rearrangements within this Chinese cohort, including a high incidence rate of FGFR fusions (40%) in parotid gland carcinoma. However, this is based on a small sample size of 5 tumors and should be interpreted cautiously pending validation in larger cohorts. We also uncovered distinct breakpoint distribution patterns across various FGFR rearrangements. For example, a primary breakpoint in intron17 of FGFR2 was predominant (21/22), while FGFR1/3 breakpoints displayed substantial diversity. For the first time, we identified "hot" breakpoints in FGFR1 intron17, exon18, and FGFR3's 3' untranslated region. These findings underline the importance of incorporating these regions in targeted sequencing to ensure comprehensive detection of FGFR1/3 fusions. Notably, we observed a predilection for intrachromosomal distribution in common FGFR1/2/3 fusions. In contrast, most novel fusions (12/15) exhibited an interchromosomal distribution pattern, indicating variations in the fusion formation mechanism. Importantly, our study demonstrates the substantial incremental value of RNA-NGS or other orthogonal methods in confirming the functionality of FGFR rearrangements initially identified by DNA sequencing. In our cohort, 46% (6/13) of rare FGFR1/2/3 fusions lacked detectable RNA transcripts; however, this does not definitively indicate non-functionality as factors such as low RNA quality, expression below detection limits, or nonsense-mediated decay may contribute. Therefore, RNA-based validation is critical for accurately identifying potentially targetable FGFR fusions and guiding therapy. Our findings offer critical novel insights into functional FGFR fusions and bear considerable clinical implications for identifying individuals whose tumors are most likely to respond favorably to FGFR-targeted therapies. Show less
📄 PDF DOI: 10.1093/oncolo/oyaf347
FGFR1

Discovery of First Branched-Chain Ketoacid Dehydrogenase Kinase (BDK) Inhibitor Clinical Candidate PF-07328948.

Kevin J Filipski, Luis A Martinez-Alsina, Matthew R Reese +31 more · 2025 · Journal of medicinal chemistry · ACS Publications · added 2026-04-24
Inhibition of branched-chain ketoacid dehydrogenase kinase (BDK or BCKDK), a negative regulator of branched-chain amino acid (BCAA) metabolism, is hypothesized to treat cardio-metabolic diseases. From Show more
Inhibition of branched-chain ketoacid dehydrogenase kinase (BDK or BCKDK), a negative regulator of branched-chain amino acid (BCAA) metabolism, is hypothesized to treat cardio-metabolic diseases. From a starting point with potential idiosyncratic toxicity risk, modification to a benzothiophene core and discovery of a cryptic pocket allowed for improved potency with 3-aryl substitution to arrive at PF-07328948, which was largely devoid of protein covalent binding liability. This BDK inhibitor was shown also to be a BDK degrader in cells and in vivo rodent studies. Plasma biomarkers, including BCAAs and branched-chain ketoacids (BCKAs), were lowered in vivo with enhanced pharmacodynamic effect upon chronic dosing due to BDK degradation. This molecule improves metabolic and heart failure end points in rodent models. PF-07328948 is the first known selective BDK inhibitor candidate to be examined in clinical studies, with Phase 1 single ascending dose data showing good tolerability and a pharmacokinetic profile commensurate with once-daily dosing. Show less
no PDF DOI: 10.1021/acs.jmedchem.4c02230
BCKDK

Emotional regulation and mental health profiles among Chinese junior middle school students: evidence for the dual-factor model.

Jichang Guo, Yanpei Pan, Yan Zhao +2 more · 2025 · Frontiers in psychology · Frontiers · added 2026-04-24
This study explored latent mental health profiles among adolescents in southwestern China and the association with emotional regulation using the dual-factor model framework. 1,682 junior middle schoo Show more
This study explored latent mental health profiles among adolescents in southwestern China and the association with emotional regulation using the dual-factor model framework. 1,682 junior middle school students completed the LPA revealed three profiles: Troubled (31.51%, high negative symptoms/low well-being), complete mental health (61.30%, low negative symptoms/high well-being), and more troubled (7.19%, severe negative symptoms/extremely low well-being). Cognitive reappraisal positively predicted complete mental health (vs. Troubled; Three distinct profiles emerged, differing from the traditional dual-factor model. Cognitive reappraisal protects mental health, while expressive suppression correlates with poorer outcomes, highlighting the need for targeted interventions promoting cognitive reappraisal. Show less
📄 PDF DOI: 10.3389/fpsyg.2025.1708381
LPA

Correlation between lipid metabolism levels and pregnancy outcomes.

Jingjing Guo, Haifan Qiu, Jianping Wang +3 more · 2025 · Frontiers in medicine · Frontiers · added 2026-04-24
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregn Show more
To establish the reference interval for the serum lipid index in pregnant women and to explore the relationship between lipid metabolism levels and pregnancy outcomes. Data were derived from 446 pregnancy women and 317 healthy non-pregnant women. Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), lipoprotein (a) [Lp(a)], and hypersensitive C-reactive protein (hs-CRP) were measured in both groups. The mean and standard deviation of each index were calculated to establish the reference range of normal serum lipid levels in pregnant women in mid-to-late pregnancy. The associations between serum lipid levels and perinatal outcomes were assessed statistically. There were no significant differences in age, pregnancy, or parity between the adverse outcome and normal delivery groups, but the caesarean section rate was significantly higher in the adverse outcome group. The levels of hs-CRP, TG, TC, HDL-C, LDL-C, and ApoA1 were significantly higher in the adverse outcome group. Elevated hs-CRP, TG, and HDL-C levels were risk factors for adverse pregnancy outcomes. According to the receiver operating characteristic curve, the optimal threshold of the combined diagnosis of these three indicators to predict adverse pregnancy outcomes was 0.534, and the area under the curve was 0.822. The establishment of lipid reference intervals in the second and third trimesters of pregnancy can effectively evaluate lipid metabolism in pregnant women, and the measurement of lipid metabolism in pregnant women is helpful in predicting adverse pregnancy outcomes. Show less
📄 PDF DOI: 10.3389/fmed.2025.1530525
APOB

D-Ala2-GIP (1-30) promotes angiogenesis by facilitating endothelial cell migration via the Epac/Rap1/Cdc42 signaling pathway.

Tuchen Guan, Wenxue Zhang, Mingxuan Li +11 more · 2025 · Cellular signalling · Elsevier · added 2026-04-24
Angiogenesis, a meticulously regulated process essential for both normal development and pathological conditions, necessitates a comprehensive understanding of the endothelial mechanisms governing its Show more
Angiogenesis, a meticulously regulated process essential for both normal development and pathological conditions, necessitates a comprehensive understanding of the endothelial mechanisms governing its progression. Leveraging the zebrafish model and NgAgo knockdown system to identify target genes influencing angiogenesis, our study highlights the significant role of gastric inhibitory polypeptide (GIP) and its receptor (GIPR) in this process. While GIP has been extensively studied for its insulinotropic and glucagonotropic effects, its role in angiogenesis remains unexplored. This study demonstrated that GIPR knockdown induced developmental delays, morphological abnormalities, and pronounced angiogenic impairments in zebrafish embryos. Conversely, exogenous D-Ala2-GIP administration enhanced blood vessel formation in the yolk sac membrane of chick embryos. Consistent with these findings, D-Ala2-GIP treatment promoted microvessel formation in the tube formation assays and rat aortic ring models. Further investigation revealed that D-Ala2-GIP facilitated human umbilical vein endothelial cell (HUVEC) migration, a key step in angiogenesis, through the cyclic adenosine monophosphate (cAMP)-mediated activation of the Epac/Rap1/Cdc42 signaling pathway. This study provides novel insights into the angiogenic functions of GIP and its potential implications for cardiovascular biology. Show less
no PDF DOI: 10.1016/j.cellsig.2025.111615
GIPR

Integrating Precision Medicine and Digital Health in Personalized Weight Management: The Central Role of Nutrition.

Xiaoguang Liu, Miaomiao Xu, Huiguo Wang +1 more · 2025 · Nutrients · MDPI · added 2026-04-24
Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical Show more
Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical biological variations in genetics, metabolic profiles, and gut microbiota composition, contributing to poor adherence and variable outcomes. Our primary aim is to identify key biological and behavioral effectors relevant to precision medicine for weight control, with a particular focus on nutrition, while also discussing their current and potential integration into digital health platforms. Thus, this review aligns more closely with the identification of influential factors within precision medicine (e.g., genetic, metabolic, and microbiome factors) but also explores how these factors are currently integrated into digital health tools. We synthesize recent advances in nutrigenomics, nutritional metabolomics, and microbiome-informed nutrition, highlighting how tailored dietary strategies-such as high-protein, low-glycemic, polyphenol-enriched, and fiber-based diets-can be aligned with specific genetic variants (e.g., FTO and MC4R), metabolic phenotypes (e.g., insulin resistance), and gut microbiota profiles (e.g., Show less
📄 PDF DOI: 10.3390/nu17162695
MC4R

Prefrontal FGF1 Signaling is Required for Accumbal Deep Brain Stimulation Treatment of Addiction.

Wan-Kun Gong, Xue Li, Le Wang +9 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Deep brain stimulation (DBS) has emerged as a prospective treatment for psychiatric disorders; for example, DBS targeting the nucleus accumbens (NAc) abolishes addictive behaviors. However, neither th Show more
Deep brain stimulation (DBS) has emerged as a prospective treatment for psychiatric disorders; for example, DBS targeting the nucleus accumbens (NAc) abolishes addictive behaviors. However, neither the core pathway nor the cellular mechanisms underlying these therapeutic effects are known. Here, morphine-induced conditioned place preference (CPP) in mice as an addiction model and NAc-DBS combined with adeno-associated virus gene delivery for activity-dependent tagging, transgenic and chemogenetic manipulation of recruited neuronal networks are used. It is reported that a cortical-accumbal pathway and local fibroblast growth factor 1 (FGF1) signaling in the medial prefrontal cortex (mPFC) are critical for NAc-DBS to be effective in altering morphine CPP. It is shown that NAc-DBS retrogradely activates mPFC neurons projecting to the NAc, and chemogenetic activation/inhibition of these DBS-activated neuron ensembles in the mPFC reproduces the NAc-DBS effects on CPP. Sustained therapeutic effects accompany reductions in local FGF1 binding to fibroblast growth factor receptor 1 (FGFR1) in these neurons. Additionally, overexpressing FGF1 in the mPFC-NAc pathway abolishes the therapeutic effects of NAc-DBS. These results demonstrate that the mPFC-NAc pathway forms a top-down motif to regulate the therapeutic effects of subcortical DBS on addiction. These results support the potential for addiction treatments involving FGF1 signaling and highlight the mPFC as a target for noninvasive brain stimulation. Show less
📄 PDF DOI: 10.1002/advs.202413370
FGFR1

Exercise-Induced Reduction of IGF1R Sumoylation Attenuates Neuroinflammation in APP/PS1 Transgenic Mice.

Yisheng Chen, Xiaofeng Chen, Zhiwen Luo +16 more · 2025 · Journal of advanced research · Elsevier · added 2026-04-24
Alzheimer's Disease (AD), a progressive neurodegenerative disorder, is marked by cognitive deterioration and heightened neuroinflammation. The influence of Insulin-like Growth Factor 1 Receptor (IGF1R Show more
Alzheimer's Disease (AD), a progressive neurodegenerative disorder, is marked by cognitive deterioration and heightened neuroinflammation. The influence of Insulin-like Growth Factor 1 Receptor (IGF1R) and its post-translational modifications, especially sumoylation, is crucial in understanding the progression of AD and exploring novel therapeutic avenues. This study investigates the impact of exercise on the sumoylation of IGF1R and its role in ameliorating AD symptoms in APP/PS1 mice, with a specific focus on neuroinflammation and innovative therapeutic strategies. APP/PS1 mice were subjected to a regimen of moderate-intensity exercise. The investigation encompassed assessments of cognitive functions, alterations in hippocampal protein expressions, neuroinflammatory markers, and the effects of exercise on IGF1R and SUMO1 nuclear translocation. Additionally, the study evaluated the efficacy of KPT-330, a nuclear export inhibitor, as an alternative to exercise. Exercise notably enhanced cognitive functions in AD mice, possibly through modulations in hippocampal proteins, including Bcl-2 and BACE1. A decrease in neuroinflammatory markers such as IL-1β, IL-6, and TNF-α was observed, indicative of reduced neuroinflammation. Exercise modulated the nuclear translocation of SUMO1 and IGF1R in the hippocampus, thereby facilitating neuronal regeneration. Mutant IGF1R (MT IGF1R), lacking SUMO1 modification sites, showed reduced SUMOylation, leading to diminished expression of pro-inflammatory cytokines and apoptosis. KPT-330 impeded the formation of the IGF1R/RanBP2/SUMO1 complex, thereby limiting IGF1R nuclear translocation, inflammation, and neuronal apoptosis, while enhancing cognitive functions and neuron proliferation. Moderate-intensity exercise effectively mitigates AD symptoms in mice, primarily by diminishing neuroinflammation, through the reduction of IGF1R Sumoylation. KPT-330, as a potential alternative to physical exercise, enhances the neuroprotective role of IGF1R by inhibiting SUMOylation through targeting XPO1, presenting a promising therapeutic strategy for AD. Show less
📄 PDF DOI: 10.1016/j.jare.2024.03.025
BACE1

SMURF2 inhibition attenuates cardiac hypertrophy through blocking ubiquitination degradation of AXIN1.

Ying Kang, Yan Zu, Qi-Yao Fan +6 more · 2025 · Acta pharmacologica Sinica · Nature · added 2026-04-24
Cardiac hypertrophy as one of the major predisposing factors for chronic heart failure lacks effective interventions. It has been shown that protein ubiquitination plays an important role in cardiac h Show more
Cardiac hypertrophy as one of the major predisposing factors for chronic heart failure lacks effective interventions. It has been shown that protein ubiquitination plays an important role in cardiac hypertrophy. SMURF2 (SMAD-specific E3 ubiquitin ligase 2) is an important member of NEDD4 (neuronal precursor cell expressed developmentally downregulated 4) family of HECT E3 ubiquitin ligases. In this study we investigated the regulatory role of SMURF2 in cardiac hypertrophy. Experiment models were established in mice by transverse aortic constriction (TAC) in vivo, as well as in neonatal rat cardiomyocytes (NRCMs) by treatment with angiotensin II (Ang II, 1 μM) in vitro. We showed that the expression levels of SMURF2 were significantly elevated in cardiac tissues from patients with cardiac hypertrophy and the two experiment models. In NRCMs, SMURF2 knockdown or treatment with a specific SMURF2 inhibitor heclin (8 μM) significantly inhibited Ang II-induced cardiomyocyte hypertrophy, evidenced by reduced mRNA levels of Anp, Bnp and β-Mhc as well as cell surface. Prophylactic or therapeutic administration of heclin (10 mg·kg Show less
no PDF DOI: 10.1038/s41401-025-01597-5
AXIN1

Cold-resistant lactic acid bacteria in Jerusalem artichoke silage: quality, microbiome and metabolome dynamics during aerobic exposure on the Qinghai-Tibet Plateau.

Xiaoqiang Wei, Lihui Wang, Haiwang Zhang +6 more · 2025 · Frontiers in microbiology · Frontiers · added 2026-04-24
Forage scarcity during the cold season poses a major challenge to livestock farming on the Qinghai-Tibet Plateau. Jerusalem artichoke (
📄 PDF DOI: 10.3389/fmicb.2025.1699658
LPL

Systemic angiogenic protein changes following propranolol therapy in infantile hemangioma: a multi-target perspective.

Lijun Liang, Yan Zhang, Yan Ma +3 more · 2025 · Frontiers in pharmacology · Frontiers · added 2026-04-24
Infantile hemangioma (IH) is a common benign vascular tumor in infants, often requiring intervention due to potential functional impairment and cosmetic concerns. Propranolol, a nonselective β-adrener Show more
Infantile hemangioma (IH) is a common benign vascular tumor in infants, often requiring intervention due to potential functional impairment and cosmetic concerns. Propranolol, a nonselective β-adrenergic receptor blocker, is the first-line therapy for IH, yet its mechanisms remain incompletely elucidated. This prospective study investigated the systemic angiogenic protein profile changes in response to propranolol in 14 treatment-naïve IH infants compared to 14 healthy controls using antibody array analysis. We identified twenty-six angiogenic proteins significantly downregulated in pretreatment IH patients compared to healthy controls. After 3 months of propranolol treatment, six proteins including HB-EGF, TGFα, ANGPTL4, Follistatin, Tie-1 and PLGF were significantly upregulated. Bioinformatic enrichment analysis revealed that these proteins are involved in key biological processes and signaling pathways, including epithelial cell proliferation, angiogenesis regulation, VEGF signaling, ERBB-EGFR axis, Ras-MAPK, and PI3K-Akt pathways. These results suggest that propranolol treatment is associated with a rebalancing of dysregulated angiogenic proteins in IH, through modulating both pro- and anti-angiogenic factors to rebalance vascular homeostasis. Our study provides novel insights into the systems-level pharmacological actions of propranolol and proposes potential biomarkers for treatment response evaluation. Show less
📄 PDF DOI: 10.3389/fphar.2025.1706048
ANGPTL4

Metabolic Risk Factors Evaluation of Obstructive Sleep Apnea Among Patients with Polycystic Ovary Syndrome.

Ling-Xia Ha, Jin-Juan Wang, Ying-Ying Yuan +2 more · 2025 · International journal of women's health · added 2026-04-24
Women diagnosed with PCOS exhibit a high prevalence of obstructive sleep apnea (OSA). This study aims to assess risk factors of OSA among patients with PCOS. This retrospective study included 126 pati Show more
Women diagnosed with PCOS exhibit a high prevalence of obstructive sleep apnea (OSA). This study aims to assess risk factors of OSA among patients with PCOS. This retrospective study included 126 patients with PCOS who were categorized into an OSA group (n = 30) and a non-OSA group (n = 96) according to the apnea-hypopnea index (AHI). A control group comprised 72 patients without PCOS who presented during the same period for infertility due to fallopian tube, pelvic, or male factors. Patients with PCOS A multivariate logistic regression model was used to analyze independent risk factors for OSA in the PCOS group. Patients with PCOS had significantly higher AHI values and elevated values for various physical indicators, including body mass index (BMI) and neck, waist, and hip circumferences; prolactin (PRL); fasting plasma glucose (FPG); insulin (FINS); triglycerides (TG); homeostasis model assessment of insulin resistance (HOMA-IR); 2-hour postprandial glucose (2-hPG) and insulin (2-hINS); AHI; and oxygen desaturation index (ODI). Conversely, levels of high-density lipoprotein cholesterol (HDL-C) and lowest oxygen saturation (LSaO OSA in PCOS patients is linked to metabolic indicators. High neck circumference and BMI levels were independent risk factors, highlighting the need for OSA in routine PCOS screening, particularly in the context of metabolic dysregulation. Show less
📄 PDF DOI: 10.2147/IJWH.S543184
APOB

Genetics of urinary bladder paragangliomas: a multi-center study of a Chinese cohort.

Jingjing Jiang, Yingxian Pang, Rongkui Luo +24 more · 2025 · Journal of endocrinological investigation · Springer · added 2026-04-24
Pheochromocytomas and paragangliomas (PPGLs) exhibit the highest degree of heritability among all human tumors, yet the genetics of urinary bladder paragangliomas (UBPGLs) remains poorly understood. T Show more
Pheochromocytomas and paragangliomas (PPGLs) exhibit the highest degree of heritability among all human tumors, yet the genetics of urinary bladder paragangliomas (UBPGLs) remains poorly understood. The present study aims to examine the characteristics of a cohort of Chinese patients with UBPGLs, focusing particularly on genetics. The study included 70 Chinese patients with UBPGLs from 15 centers in China, 240 patients with non-head and neck PGLs (non-HNPGLs) outside the urine bladder, and 16 Caucasian patients with UBPGLs. Tumor DNA samples were sequenced by next generation sequencing. All identified pathogenic variants (PVs) were confirmed by Sanger sequencing. Among the 70 Chinese patients, PVs were identified in 38 cases: 23 in cluster 1 A (13 SDHB, 1 SDHD, 1 SDHA, 4 IDH1, 2 SLC25A11, and 2 FH), 4 in cluster 1B (3 EPAS1 and 1 EGLN1), and 11 in cluster 2 genes (7 HRAS, 1 FGFR1, 2 NF1, and 1 H3F3A). Compared with other non-HNPGLs, UBPGLs had more PVs in cluster 1 A genes (32.9% vs. 14.2%, p < 0.001), but fewer in cluster 1B (5.7% vs. 19.2%, p = 0.002) and cluster 2 genes (15.7% vs. 42.5%, p < 0.001). PVs in SDHB (18.6%) was the most common in Chinese patients with UBPGLs, followed by HRAS (10.0%). No PVs was found in 45.7% of all UBPGLs. PVs in HRAS, SLC25A11, EPAS1, and FH were also identified in Caucasians with UBPGLs. Chinese patients with UBPGLs have a diverse genetic profile. PVs in cluster 1 A genes underlie nearly 1/3 of patients, highlighting the importance of genetic testing. Diverse germline and somatic PVs are also present in Caucasian patients with UBPGLs. Show less
📄 PDF DOI: 10.1007/s40618-024-02509-w
FGFR1

Mitochondrial dysfunction mediates the association between mercury exposure and lipid metabolism in children and adolescents.

Ping Cheng, Chen Liu, Jie Xiang +2 more · 2025 · Lipids in health and disease · BioMed Central · added 2026-04-24
Mercury (Hg) is a widespread environmental pollutant with known neurotoxic and cardiometabolic effects, and its influence on lipid metabolism during childhood remains insufficiently understood. Mitoch Show more
Mercury (Hg) is a widespread environmental pollutant with known neurotoxic and cardiometabolic effects, and its influence on lipid metabolism during childhood remains insufficiently understood. Mitochondrial dysfunction is proposed as a potential mechanism linking Hg exposure to metabolic disruption. Mitochondrial DNA copy number (mtDNA-CN) is regarded as an indicator of mitochondrial biogenesis and functional capacity, where lower levels generally suggest mitochondrial damage or dysfunction. In contrast, ribosomal DNA (rDNA) and relative telomere length (RTL) reflect genomic stability and cellular aging. This study investigated the associations between blood Hg levels and serum lipid profiles in children and adolescents and assessed the mediating roles of mtDNA-CN, rDNA, and RTL. A cross-sectional study was performed among 352 children and adolescents aged 6–17 years in eastern China. Blood Hg levels were determined using inductively coupled plasma mass spectrometry (ICP-MS), and serum lipid markers, namely total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a), were assessed along with the genomic indicators such as mtDNA-CN, rDNA, and RTL. Multivariable linear regression and mediation analyses were conducted. Higher Hg levels were significantly related with increased TC (β = 0.144, Hg exposure in children and adolescents is linked to an atherogenic lipid profile, potentially through mitochondrial dysfunction. MtDNA-CN appears to be a sensitive molecular mediator of Hg-induced lipid disturbances, which highlights the relevance of mitochondrial health in early-life environmental epidemiology and cardiovascular risk prevention. The findings support early prevention strategies and environmentally focused health policies that reduce toxicant exposure and thus promote long-term cardiometabolic health in young populations. Show less
📄 PDF DOI: 10.1186/s12944-025-02843-9
APOB

Development of a novel targeted LC-MS/MS methods for the typing of cardiac amyloidosis.

Kaijuan Wang, Ruichen Liu, Li Li +7 more · 2025 · Analytica chimica acta · Elsevier · added 2026-04-24
The treatment and prognosis of cardiac amyloidosis (CA) depend heavily on the accurate identification of amyloid protein types. Histopathological methods are the most commonly used approach, but often Show more
The treatment and prognosis of cardiac amyloidosis (CA) depend heavily on the accurate identification of amyloid protein types. Histopathological methods are the most commonly used approach, but often produce inconclusive results. The application of mass spectrometry with laser microdissection mass spectrometry based on non-targeted proteomics in CA diagnosis is gradually being recognized, but it is expensive, time-consuming, and still in the early stages of scientific research applications. This study aims to establish a novel typing method based on targeted semi-quantitative proteomics to address the shortcomings of existing methods. Formalin-fixed, paraffin-embedded (FFPE) myocardial tissue samples from 52 CA and 52 hypertrophic cardiomyopathy (HCM) patients were analyzed. A semi-quantitative typing method was developed using triple quadrupole mass spectrometry, with laser microdissection mass spectrometry (LMD-MS) serving as the reference standard. A total of 52 peptides were analyzed. Key amyloid-associated proteins (AAPs) -apolipoprotein A-IV (apo A-IV), apolipoprotein E (apo E), and serum amyloid P component (SAP) - showed high diagnostic accuracy, with AUC values of 0.964, 0.999, and 0.923, respectively. Transthyretin (TTR), immunoglobulin light chains- κ (IGL - κ), and IGL-λ were semi-quantified using normalized scores (NS) adjusted for microdissection and peptide peak areas. An NS This targeted semi-quantitative mass spectrometry method has high consistency with non-targeted LMD-MS typing, with an accuracy higher than IHC (100 % vs. 30.8 %), while compensating for the shortcomings of non-targeted proteomics. It provides a practical method for CA typing in routine clinical laboratories and may help identify rare subtypes of amyloidosis in the future. Show less
no PDF DOI: 10.1016/j.aca.2025.344453
APOA4

Targeting ApoA5-Associated Hypertriglyceridemia to Ameliorate Acute Pancreatitis: Insights From a Knockout Hamster Model.

Sijing Shi, Kaikai Lu, Yijun Tao +6 more · 2025 · MedComm · Wiley · added 2026-04-24
📄 PDF DOI: 10.1002/mco2.70555
APOA5

Neuroinflammation in an Optimized Model of Lysophosphatidic Acid (LPA)-Induced Post-hemorrhagic Hydrocephalus.

Paloma Sánchez-Pavón, Carter R Palmer, Christine S Liu +3 more · 2025 · Neurochemical research · Springer · added 2026-04-24
Post-hemorrhagic hydrocephalus (PHH) is a neurological disease that primarily affects premature infants and involves infiltration of blood into the brain's ventricles followed by excessive accumulatio Show more
Post-hemorrhagic hydrocephalus (PHH) is a neurological disease that primarily affects premature infants and involves infiltration of blood into the brain's ventricles followed by excessive accumulation of cerebrospinal fluid (CSF), leading to ventricular enlargement and increased intracranial pressure. The precise mechanisms driving PHH development and persistence are incompletely understood and lack disease-modifying treatments. Using a mouse model of PHH, we have identified transcriptomic, proteomic, and cellular features of PHH involving neuroimmune and neurovascular alterations recapitulating those reported in human disease. Improvement upon a lysophosphatidic acid (LPA)-induced PHH mouse model was combined with unbiased proteomic and single-nucleus transcriptomics that identified microglial molecular pathways propagating PHH. Pharmacological depletion of microglia in vivo significantly reduced PHH-associated ventriculomegaly. These data identify microglial and neurovascular elements in the development of PHH, implicating them as other potentially tractable therapeutic targets beyond LPA receptors, towards developing medical treatments for PHH. Show less
📄 PDF DOI: 10.1007/s11064-025-04542-4
LPA

Gene-Lifestyle Interactions in Renal Dysfunction: Polygenic Risk Modulation via Plant-Based Diets, Coffee Intake, and Bioactive Compound Interactions.

Meiling Liu, Da-Sol Kim, Sunmin Park · 2025 · Nutrients · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/nu17050916
CPS1

Role of GNL3L in lung cancer: Mediating proliferation and progression through NF-κB pathway activation and upregulation of Slug, MMP2, and MMP9.

Qian Wang, Xiao-Qi Zhang, Shan-Shan Liu +4 more · 2025 · Experimental cell research · Elsevier · added 2026-04-24
The precise involvement of Guanine Nucleotide-Binding Protein-Like 3-Like Protein (GNL3L) in lung cancer progression and invasion remains unclear. In this study, we explored the impact and underlying Show more
The precise involvement of Guanine Nucleotide-Binding Protein-Like 3-Like Protein (GNL3L) in lung cancer progression and invasion remains unclear. In this study, we explored the impact and underlying mechanisms of GNL3L on the proliferation, migration, and invasion of lung adenocarcinoma (LUAD), and evaluated the therapeutic potential of targeting GNL3L. Inhibition of GNL3L expression led to a notable decrease in the in vitro proliferation, migration, and invasion of A549 and H1299 non-small cell lung cancer (NSCLC) cells. Meanwhile, GNL3L silencing could significantly reduce the tumor volume of the nude mice and improve the outcomes of tumor-bearing mice in vivo. Additionally, inhibition of GNL3L expression dramatically suppressed NF-κB activation and Slug, MMP2, and MMP9 expression. Overexpression of Slug or treatment of the GNL3L-deficient cells with NF-κB activator can partially restore the growth suppressed by GNL3L deficiency, and combined treatment with Slug overexpression and NF-κB activator could totally restore the suppressed cell growth caused by GNL3L deficiency. Moreover, the overexpression of MMP2 or MMP9 could partially enhance the reduced migration and invasion caused by GNL3L deficiency, and this GNL3L-deficiency-caused suppression of migration and invasion can be totally restored by the overexpression of MMP2 and MMP9 together. These results strongly indicated that GNL3L has the capability to activate the NF-κB and increase Slug, MMP2, and MMP9 expression, which in turn could stimulate the proliferation, migration, and invasion of lung cancer cells. NF-κB activation and Slug, MMP2, and MMP9 expression enhanced by GNL3L, leading to the promotion of proliferation, migration, and invasion of lung cancer cells, indicating the therapeutic implications and potential significance of these pathways in the progression and invasion of NSCLCs that overexpress GNL3L protein. Show less
no PDF DOI: 10.1016/j.yexcr.2025.114630
SNAI1

[Allogeneic hematopoietic stem cell transplantation for pediatric acute leukemia harboring the

Yu Chen, Yong-Bing Zhu, Jia-Si Zhang +4 more · 2025 · Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · added 2026-04-24
A retrospective analysis was conducted on the clinical course of two children with
no PDF DOI: 10.7499/j.issn.1008-8830.2503092
MLLT10

Angiopoietin-Like Protein Family-Mediated Functions in Modulating Triglyceride Metabolism and Related Metabolic Diseases.

Sen Yang, Xin Su, Min Lai +2 more · 2025 · Frontiers in bioscience (Landmark edition) · added 2026-04-24
Hypertriglyceridemia, characterized by increased triglyceride (TG) concentrations, is considered the most important risk factor for cardiometabolic disorders, including dyslipidemia, atherosclerotic c Show more
Hypertriglyceridemia, characterized by increased triglyceride (TG) concentrations, is considered the most important risk factor for cardiometabolic disorders, including dyslipidemia, atherosclerotic cardiovascular diseases, and non-alcoholic fatty liver disease (NAFLD). Recently, the angiopoietin-like protein (ANGPTL) family, which comprises ANGPTL1 to ANGPTL8, was confirmed to play an important role in modulating lipoprotein lipase (LPL) activity. However, understanding of the underlying mechanisms remains limited. Importantly, emerging evidence has linked several transcriptional and post-transcriptional factors to the potential alteration of TG metabolism via ANGPTL proteins. This review focused on the similarities and differences in the expression, structural features, and modulatory profile of three ANGPTLs: ANGPTL3, ANGPTL4, and ANGPTL8. In addition, the regulatory functions of those three ANGPTLs in modulating LPL were summarized to provide potential therapeutic and clinical strategies for hypertriglyceridemia and its related cardiometabolic disorders. Show less
no PDF DOI: 10.31083/FBL25862
ANGPTL4

Unveiling Biomarkers and Therapeutic Targets in Systemic Sclerosis and Lupus Erythematosus Through Transcriptomic Profiling.

Ang-Jun Liu, Jian-Ruei Ciou, Po-Chang Wu +3 more · 2025 · International journal of rheumatic diseases · Blackwell Publishing · added 2026-04-24
This study aims to investigate the molecular differences and commonalities between systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) by analyzing RNA-sequencing (RNA-seq) data. By focusi Show more
This study aims to investigate the molecular differences and commonalities between systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) by analyzing RNA-sequencing (RNA-seq) data. By focusing on differentially expressed genes and enriched pathways, the investigation seeks to identify unique biomarkers, shared pathways, and potential therapeutic targets for these autoimmune diseases. This study involved 10 patients with SSc and 24 with SLE who did not receive immunosuppressants. RNA-seq data from patients with SSc and SLE were analyzed using DESeq2 to identify differentially expressed genes. Functional and pathway enrichment analyses were conducted and comparative analyses were performed. We identified 2055 differentially expressed genes (DEGs) between patients with SSc and controls. Notably, the expression of the shared gene RGS5 was significantly downregulated in both SLE and SSc, with a more pronounced downregulation in SSc. Additionally, the expression of the key transcription factor EGR1 was upregulated in SSc, whereas that of BLK, ITGAM, and IFNG was upregulated in SLE. Network analysis identified hub genes-AP3D1, FTX, USP47, CUX1, ZC3H4, CAND1, INTS1, TRNT1, MTERF1, and SETD1B-that may play critical roles in the progression of both SLE and SSc. These findings suggest that RGS5 could serve as a shared biomarker for vascular dysfunction, while EGR1 and BLK may represent therapeutic targets in SSc and SLE. Overall, this analysis enhances understanding of distinct and overlapping gene expression signatures in SSc and SLE, providing a foundation for future targeted treatment strategies and requiring further validation in larger cohorts. Show less
no PDF DOI: 10.1111/1756-185X.70308
ZC3H4

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