👤 Wan-Di Liu

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

GIPR-Ab/GLP-1 peptide-antibody conjugate requires brain GIPR and GLP-1R for additive weight loss in obese mice.

Clarissa M Liu, Elizabeth A Killion, Rola Hammoud +15 more · 2025 · Nature metabolism · Nature · added 2026-04-24
Glucose-dependent insulinotropic polypeptide receptor (GIPR) and glucagon-like peptide 1 receptor (GLP-1R) are expressed in the central nervous system (CNS) and regulate food intake. Here, we demonstr Show more
Glucose-dependent insulinotropic polypeptide receptor (GIPR) and glucagon-like peptide 1 receptor (GLP-1R) are expressed in the central nervous system (CNS) and regulate food intake. Here, we demonstrate that a peptide-antibody conjugate that blocks GIPR while simultaneously activating GLP-1R (GIPR-Ab/GLP-1) requires both CNS GIPR and CNS GLP-1R for maximal weight loss in obese, primarily male, mice. Moreover, dulaglutide produces greater weight loss in CNS GIPR knockout (KO) mice, and the weight loss achieved with dulaglutide + GIPR-Ab is attenuated in CNS GIPR KO mice. Wild-type mice treated with GIPR-Ab/GLP-1 and CNS GIPR KO mice exhibit similar changes in gene expression related to tissue remodelling, lipid metabolism and inflammation in white adipose tissue and liver. Moreover, GIPR-Ab/GLP-1 is detected in circumventricular organs in the brain and activates c-FOS in downstream neural substrates involved in appetite regulation. Hence, both CNS GIPR and GLP-1R signalling are required for the full weight loss effect of a GIPR-Ab/GLP-1 peptide-antibody conjugate. Show less
📄 PDF DOI: 10.1038/s42255-025-01295-w
GIPR

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

Prenatal androgen exposure delays puberty onset in female offspring rats: possible roles of leptin and α-MSH.

Runfei Ge, Yongting Yuan, Jingqi Liu +7 more · 2025 · Endocrine · Springer · added 2026-04-24
To clarify the possible mechanism of leptin and α-MSH on the onset of puberty in female offspring rats after prenatal androgen exposure. Sixteen 8-week-old specific pathogen free (SPF) healthy Sprague Show more
To clarify the possible mechanism of leptin and α-MSH on the onset of puberty in female offspring rats after prenatal androgen exposure. Sixteen 8-week-old specific pathogen free (SPF) healthy Sprague Dawley (SD) pregnant rats were randomly divided into the testosterone-treated group (TG, female offspring termed PNA group) or the olive oil control group (OOG, female offspring termed VEH group). The female offspring rats of two groups were raised to 21 days (PND21) and weaned. Six female offspring rats at PND21 (VEH:PNA = 3:3) were randomly selected for transcriptome sequencing. Twenty-seven offspring female rats were randomly divided into three groups (VEHI:VEHII:PNA = 9:9:9). VEHI group was observed until the onset of puberty, VEHII and PNA groups were observed until the 8th week. Compared with VEH group, onset of puberty was not observed in PNA group, and hypothalamic Pomc gene expression at PND21 was lower. Compared with the VEHI group, the body weight, abdominal fat, serum testosterone (T), dehydroepiandrosterone (DHEA) and leptin (LEP) levels were upregulated in the PNA group, while serum gonadotropin-releasing hormone (GnRH), mRNA of hypothalamic estrogen receptor α (ERα), α-melanocyte stimulating hormone (α-MSH), melanocortin receptor-4 (MC4R), GnRH and adipose AR, and the protein of androgen receptor (AR) and leptin receptor (LEPR) in the hypothalamic arcuate nucleus (ARC) were decreased. In the PNA group, there were positive correlations between serum DHEA and mRNA of hypothalamic ERα, MC4R and AR, negative correlations between mRNA of adipose AR and serum T and free testosterone (FT). Prenatal androgen exposure delayed the onset of puberty in female offspring, the possible mechanism of which is that prenatal androgen exposure may increase the levels of androgen and LEP, decreases their sensitivity and the expression of AR, LEPR, and MC4R, reducing GnRH secretion. Show less
📄 PDF DOI: 10.1007/s12020-025-04388-4
MC4R

Association between red blood cell distribution width and genetic risk in patients with rheumatoid arthritis: a prospective cohort study and Mendelian randomization analysis.

Mingyang Chen, Jing Lei, Zhenqiu Liu +6 more · 2025 · BMC rheumatology · BioMed Central · added 2026-04-24
Elevated red blood cell distribution width (RDW) is associated with increased risk of rheumatoid arthritis (RA), but the potential interactions of RDW with genetic risk of incident RA remain unclear. Show more
Elevated red blood cell distribution width (RDW) is associated with increased risk of rheumatoid arthritis (RA), but the potential interactions of RDW with genetic risk of incident RA remain unclear. This study aimed to investigate the associations between RDW, genetics, and the risk of developing RA. We analysed data from 145,025 healthy participants at baseline in the UK Biobank. The endpoint was diagnosed rheumatoid arthritis (ICD-10 codes M05 and M06). Using previously reported results, we constructed a polygenic risk score for RA to evaluate the joint effects of RDW and RA-related genetic risk. Two-sample mendelian randomization and bayesian colocalization were used to infer the causal relation between them. A total of 675 patients with RA were enrolled and had a median followed up of 5.1 years, with an incidence rate of 0.57/1000 person-years. The hazard ratio of RA was 1.89 (95% CI: 1.45, 2.47) in highest RDW quartile group compared with the lowest RDW quartile group. Individuals within the top quintile of PRS showed a significantly high risk of RA. Moreover, Participants with high genetic risk and those in highest RDW group exhibited a significantly elevated hazard ratio (7.67, 95% CI: 3.98, 14.81), as opposed to participants with low genetic risk and those in lowest RDW group. Interactions between PRS and RDW on the multiplicative and additive scale were observed. Mendelian randomization provided suggestive evidence of a bi-directional causal relationship between RDW and RA. Loci near IL6R, IL1RN, FADS1/FADS2, UBE2L3 and HELZ2 showed colocalization. Increased RDW is associated with elevated risk of incident RA especially in the high genetic risk populations, but only suggestive evidence supports a causal relationship between them. Show less
📄 PDF DOI: 10.1186/s41927-024-00451-1
FADS1

Shen-Hong-Tong-Luo formula ameliorates atherosclerosis by enhancing macrophage efferocytosis through activating the PPARγ/mfge8 pathway.

Yanyu Shi, Zepeng Zhang, Jiaqi Liu +7 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Atherosclerosis (AS) is a chronic inflammatory disorder driven by dysregulated lipid metabolism and remains a leading cause of cardiovascular morbidity. The Shen-Hong-Tong-Luo (SHTL) preparation has d Show more
Atherosclerosis (AS) is a chronic inflammatory disorder driven by dysregulated lipid metabolism and remains a leading cause of cardiovascular morbidity. The Shen-Hong-Tong-Luo (SHTL) preparation has demonstrated clinical benefit in stabilizing atherosclerotic plaques, yet its molecular mechanisms are not fully defined. This research sought to elucidate the protective effects exerted by SHTL on AS progression. To investigate the impact of SHTL on macrophage function and plaque stability, we utilized ApoE SHTL markedly attenuated the progression of AS, demonstrated by reduced plaque formation within both the aortic root and aorta, diminished plasma lipid concentrations, and suppressed inflammatory responses. SHTL demonstrates significant anti-inflammatory and lipid-regulatory effects, attenuating AS progression through the PPARγ/Mfge8 pathway, thereby enhancing macrophage efferocytosis. These findings highlight a novel mechanism by which SHTL may contribute to preventing and treating atherosclerotic diseases. Show less
📄 PDF DOI: 10.3389/fimmu.2025.1727378
APOE

Dietary Supplementation with Whole-Fat or Defatted Antarctic Krill Powder Improves the Growth Performance, Body Coloration, and Immune Capability of Red-White Koi Carp (

Hongmei Song, Yixin Liang, Yexin Yang +4 more · 2025 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
This study was conducted to investigate the effects of replacing fish meal with either whole-fat or defatted krill powder on the growth, body color, immunity, and related gene expression of red-white Show more
This study was conducted to investigate the effects of replacing fish meal with either whole-fat or defatted krill powder on the growth, body color, immunity, and related gene expression of red-white koi carp. A total of 630 red-white koi carp with an initial body mass of 13.5 ± 0.05 g were randomly divided into seven groups with three replicates per group and 30 fish per replicate. The control group was fed a basic diet (C0). The other six diets were supplemented with different levels of whole krill meal or defatted krill meal as replacements (10% whole fat, 20% whole fat, 30% whole fat, 10% defatted, 20% defatted, and 30% defatted) in the experimental groups, named W10, W20, W30, D10, D20, and D30, respectively, for a total duration of 60 days. The growth, body color, immunity and gene expression indexes were measured in the koi after completion. The results indicate the following. (1) Compared with C0, the experimental groups of koi showed a significant increase in the specific growth rate (SGR) ( Show less
📄 PDF DOI: 10.3390/ani15111561
LPL

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

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

Cholesterol metabolism-related genes predict immune infiltration and prognosis in gastric cancer patients.

Wenxuan Liu, Li Liu, Tianrui Kuang +1 more · 2025 · Journal of Cancer · added 2026-04-24
📄 PDF DOI: 10.7150/jca.104389
APOC3

Retraction Notice to: circRAPGEF5 Contributes to Papillary Thyroid Proliferation and Metastatis by Regulation miR-198/FGFR1.

Weiwei Liu, Ji Zhao, Mingming Jin +1 more · 2025 · Molecular therapy. Nucleic acids · Elsevier · added 2026-04-24
[This retracts the article DOI: 10.1016/j.omtn.2019.01.003.].
📄 PDF DOI: 10.1016/j.omtn.2025.102613
FGFR1

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

Multisystem comorbidities and shared genetic pathways in calcific aortic stenosis: a phenome-wide and Mendelian randomisation analysis.

Zihao Zhou, Yidan Zheng, Shiyan Hu +13 more · 2025 · Heart (British Cardiac Society) · added 2026-04-24
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisyste Show more
Calcific aortic stenosis (CAS) is frequently accompanied by systemic comorbidities, but their causal relationships and shared genetic architecture remain poorly defined. We aimed to map the multisystem comorbidity network of CAS and clarify underlying genetic mechanisms. In 467 484 participants from the UK Biobank, observational and polygenic phenome-wide association studies evaluated associations between CAS and 1571 phenotypes, integrating disease-trajectory analyses to visualise temporal patterns. Associations replicated across observational and polygenic analyses were tested using two-sample Mendelian randomisation (MR) based on 22 CAS-related variants from FinnGen. Polygenic risk score (PRS) analyses excluding specific genes assessed their contributions, particularly LPA and plasma lipoprotein(a) (Lp(a)) levels. CAS was associated with higher risks of 42 cardiovascular and non-cardiovascular conditions, most prominently metabolic, endocrine, haematological and respiratory disorders. Temporal analyses showed that circulatory and metabolic diseases typically precede other comorbidities in CAS trajectories. MR findings were consistent with causal effects of CAS on multiple cardiovascular diseases, iron-deficiency anaemia, mental disorders and pleural effusion. When LPA variants were removed from the CAS PRS or plasma Lp(a) concentration was adjusted for, most associations lost significance, indicating a shared LPA/Lp(a)-mediated genetic pathway. CAS is embedded within a broad multisystem comorbidity network, driven largely by genetic variation at LPA and elevated Lp(a). These findings highlight pleiotropic mechanisms linking valvular calcification with systemic disease and support LPA-targeted therapies as a promising avenue for reducing the multisystem burden of CAS. Show less
no PDF DOI: 10.1136/heartjnl-2025-326058
LPA

Identifying internet addiction profiles and bridge connectors among Chinese college students and evaluating CBT vs. CBT+MBI interventions via a randomized controlled trial.

Shuhong Liang, Yaxu Yu, Shuang Liu +2 more · 2025 · Journal of behavioral addictions · added 2026-04-24
The Interaction of Person-Affect-Cognition-Execution (I-PACE) model offers a framework for understanding the interplay between cognitive, affective, and behavioral factors in internet addiction (IA). Show more
The Interaction of Person-Affect-Cognition-Execution (I-PACE) model offers a framework for understanding the interplay between cognitive, affective, and behavioral factors in internet addiction (IA). Our study aims to explore the heterogeneity of IA, identify bridge connectors, and compare the efficacy of cognitive behavioral therapy combined with mindfulness-based intervention (CBT+MBI) versus CBT alone in reducing IA levels among Chinese college students. In study 1, 1,030 Chinese college students completed assessments of IA, automatic thoughts, self-control, and anxiety. Latent profile analysis (LPA) was employed to identify distinct symptom profiles of IA across individuals. Network analysis (NA) identified bridge connectors for targeted intervention. In study 2, 36 participants randomly selected from the high IA and low IA groups of study 1 were randomly assigned to CBT+MBI, CBT alone, or a control group. The CBT+MBI group received an 8-week dual-modality intervention and the CBT alone received an 8-week CBT intervention, both designed to target the bridge connectors identified via NA in Study 1, while the control group only completed basic questionnaires. In study 1, LPA identified four subgroups: regular, at-risk, low IA, and high IA groups. NA pinpointed automatic thoughts and anxiety as bridge connectors. In study 2, targeted interventions significantly reduced college students' levels of IA. CBT+MBI resulted in greater and more sustained improvements compared to CBT alone, with effects maintained for six-month post-intervention. Our study not only reinforces the I-PACE model but also provides actionable strategies for designing evidence-based, multidimensional interventions to reduce addictive behaviors among college students. Show less
📄 PDF DOI: 10.1556/2006.2025.00086
LPA

Macrophage marker gene-driven prognostic models for esophageal cancer: integrating multi-omics analysis and therapeutic strategies.

Zehan Li, Huazhen Wu, Chuzhong Wei +15 more · 2025 · 3 Biotech · Springer · added 2026-04-24
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORD Show more
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORDC1, and BCKDK). This signature effectively stratified patients into high- and low-risk groups with significantly different overall survival, achieving area under the curve (AUC) values greater than 0.7 for 1-, 2-, and 3-year survival prediction. A high-risk status correlated with an immunosuppressive tumor microenvironment, characterized by lower infiltration of B cells and CD8 + T cells, and was associated with reduced sensitivity to multiple chemotherapeutic agents, including Cisplatin and 5-Fluorouracil. Conversely, a low-risk status was linked to greater immune cell infiltration and higher predicted chemosensitivity. At the single-cell level, pseudotime analysis revealed that macrophage maturation significantly correlated with a decreasing risk score, suggesting that mature macrophages may contribute to a favorable prognosis. Furthermore, cell communication analysis identified high-risk macrophages as dominant drivers of a pro-tumorigenic microenvironment via signaling pathways, such as SPP1 and complement. In conclusion, this seven-gene signature is a robust prognostic biomarker that offers a new strategy for personalized risk assessment and treatment selection in ESCA. The online version contains supplementary material available at 10.1007/s13205-025-04452-w. Show less
no PDF DOI: 10.1007/s13205-025-04452-w
BCKDK

Atf3 + senescent chondrocytes mediate meniscus degeneration in aging.

Jing-Yi Wang, Yao-Hui Liu, Xiao Wang +7 more · 2025 · Arthritis research & therapy · BioMed Central · added 2026-04-24
Meniscus degeneration contributes to knee arthritis progression, but the cellular and molecular mechanisms of meniscus aging remain poorly understood. We aimed to characterize age-related changes in t Show more
Meniscus degeneration contributes to knee arthritis progression, but the cellular and molecular mechanisms of meniscus aging remain poorly understood. We aimed to characterize age-related changes in the rat meniscus using single-cell RNA sequencing (scRNA-seq) and identify key pathogenic cell populations and pathways. Meniscal tissues from young (12 weeks) and aged (24 months) rats were processed for histology, flow cytometry, and scRNA-seq. Bioinformatics tools, including Seurat, Monocle 2, and CellChat, were used to analyze cellular composition, pseudotime trajectories, and intercellular communication. Senescence-related features and signaling pathways were evaluated. Knee joint of aged rats exhibited higher Osteoarthritis Research Society International (OARSI) scores and synovial inflammation. scRNA-seq revealed three major chondrocyte subpopulations: Sox9 + stable chondrocytes, Fndc1 + fibrochondrocytes, and Atf3 + senescent chondrocytes. Aging caused a significant increase in Atf3 + senescent chondrocytes, characterized by the expression of senescence markers (Cdkn1a/Cdkn2a) and activation of inflammatory pathways such as tumor necrosis factor (TNF) and nuclear factor-κB (NF-κB). These cells were predominantly located at the endpoint of differentiation trajectories. CellChat analysis identified the ANGPTL4-SDC4 axis as a key signaling pathway mediated by Atf3 + cells. Immunostaining confirmed elevated Angiopoietin-Like Protein 4 (ANGPTL4) expression in aged menisci. We identified Atf3 + senescent chondrocytes as a key pathogenic population in the aging meniscus, driving degeneration via the ANGPTL4 pathway. Targeting Atf3 + cells or ANGPTL4 signaling may offer new therapeutic strategies for age-related meniscus degeneration and arthritis. Show less
📄 PDF DOI: 10.1186/s13075-025-03566-z
ANGPTL4

Blockage of CCL3 with neutralizing antibody reduces neuroinflammation and reverses Alzheimer disease phenotypes.

Chao Wei, Jing Liu, Bing Wu +8 more · 2025 · Brain, behavior, and immunity · Elsevier · added 2026-04-24
Accumulating evidence indicates that neuroinflammation is involved in the pathogenesis of Alzheimer's disease (AD). According to RNA sequencing and quantitative PCR (qPCR), we found that chemokine CCL Show more
Accumulating evidence indicates that neuroinflammation is involved in the pathogenesis of Alzheimer's disease (AD). According to RNA sequencing and quantitative PCR (qPCR), we found that chemokine CCL3 mRNA expression was abnormally upregulated in the brains of AD transgenic mice. Moreover, the levels of CCL3 in the serum of AD patients were significantly elevated and negatively correlated with their cognitive abilities. However, the role of CCL3 in AD neuroinflammation and pathological damages remains elusive. Using behavioral, histological, and biochemical methods, outcomes of CCL3 antibody treatment on neuropathology and cognitive deficits were studied in the APPswe/PS1dE9 mice. In the present study, we reported that CCL3 protein expression was increased in the APPswe/PS1dE9 mice, whereas blockage of CCL3 with neutralizing antibody potently inhibited CCL3 activation in the APPswe/PS1dE9 mice down to the levels of wild-type mice. Specifically, CCL3 antibody significantly improved the learning and memory abilities of APPswe/PS1dE9 mice. In addition, CCL3 antibody treatment decreased cerebral amyloid-β (Aβ) levels and plaque burden via inhibiting amyloid precursor protein (APP) processing by reducing beta-site APP cleaving enzyme 1 (BACE1) expression in the APPswe/PS1dE9 mice. We also found that CCL3 antibody treatment alleviated neuroinflammation and reduced synaptic defects in the APPswe/PS1dE9 mice. Furthermore, the activated NF-κB signaling pathway in APPswe/PS1dE9 mice was inhibited by CCL3 antibody treatment. Collectively, our findings provide evidence that CCL3 activation may contribute to the AD pathogenesis and may serve as a novel therapeutic target in the treatment of AD. Show less
no PDF DOI: 10.1016/j.bbi.2025.04.034
BACE1

Interleukin-27 is a multitarget regulator of fibroblast remodeling in thyroid-associated ophthalmopathy.

Pengbo Zhang, Xiaofang Wang, Nanji Lu +3 more · 2025 · iScience · Elsevier · added 2026-04-24
Thyroid-associated ophthalmopathy (TAO) is characterized by inflammation and tissue remodeling, including fibrosis and adipogenesis. Here, we identify interleukin-27 (IL-27) as a negative feedback imm Show more
Thyroid-associated ophthalmopathy (TAO) is characterized by inflammation and tissue remodeling, including fibrosis and adipogenesis. Here, we identify interleukin-27 (IL-27) as a negative feedback immunomodulator in TAO. Serum IL-27α levels were significantly elevated in patients with TAO compared with healthy and inflammatory disease controls. In orbital fibroblasts (OFs), exogenous IL-27 suppressed IL-1β-induced proinflammatory cytokines and reduced hypoxia-induced NLRP3 inflammasome activation. IL-27 also attenuated TGF-β-driven fibrosis via p38 MAPK signaling in CD90 Show less
📄 PDF DOI: 10.1016/j.isci.2025.113982
IL27

Ginsenoside Rh2(S) maintains cytoskeleton homeostasis and inhibits pyroptosis to resist cisplatin-induced cardiotoxicity through FGFR1/HRAS axis.

Hongbo Teng, Shuai Huang, Xialin Sun +8 more · 2025 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Patients with cancer undergoing cisplatin chemotherapy frequently experience cardiotoxic side effects that significantly affect their prognosis and survival rates. Our study found that Panax ginseng r Show more
Patients with cancer undergoing cisplatin chemotherapy frequently experience cardiotoxic side effects that significantly affect their prognosis and survival rates. Our study found that Panax ginseng root extract exerted a significant protective effect against cisplatin-induced myocardial cell injury. The present study aims to elucidate the underlying mechanisms by which the bioactive components of Panax ginseng mitigate cisplatin-induced cardiotoxicity (CIC). In vitro, the candidate active components were screened by network pharmacological prediction and in neonatal rat ventricular myocytes (NRVMs), and their mechanisms of action were verified by transcriptome sequencing, western blotting, gene overexpression, immunoprecipitation, immunofluorescence, and cellular thermal shift assays. A C57BL/6 CIC mouse model was established to verify the protective effects of the candidate components and the in vivo mechanism of the candidate components. Through network pharmacology prediction and cellular activity screening of ginseng root compounds, ginsenoside Rh2(S) (Rh2) was identified as a significant active component. Transcriptomic, in vitro, and in vivo experiments demonstrated that Rh2 can activate the Pak1/Limk1/cofilin phosphorylation pathway, thereby inactivating the actin-severing protein cofilin and protecting cardiomyocytes from cisplatin-induced actin depolymerization. Additionally, Rh2 suppressed the ROS/caspase-3/GSDME pathway to inhibit cisplatin-induced pyroptosis. Furthermore, co-immunoprecipitation and overexpression experiments confirmed that Rh2 activated the FGFR1/HRAS axis, thereby simultaneously regulating the two aforementioned pathways to combat CIC. This study demonstrated for the first time that Rh2 is the main active component in Panax ginseng that maintains cytoskeletal homeostasis and inhibits pyroptosis by regulating the FGFR1/HRAS pathway to resist CIC. This study aimed to provide a theoretical basis for expanding the targets and pathways of CIC treatment, and for the development of related drugs. Show less
no PDF DOI: 10.1016/j.phymed.2025.156425
FGFR1

Validation of the Chinese Version of the HPV Stigma Scale: A Multidimensional Analysis in Women With HPV.

Zhenwei Dai, Shu Jing, Haiyan Hu +8 more · 2025 · Brain and behavior · Wiley · added 2026-04-24
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult w Show more
Human papillomavirus (HPV) infection is a global public health issue, and HPV-related stigma can affect cervical cancer prevention. But no validated tools exist to assess HPV stigma in Chinese adult women infected with HPV. This study aimed to adapt and validate the HPVsStigma scale (HPV-SS) in the Chinese context. A cross-sectional study was conducted from December 2024 to February 2025 among 501 HPV-infected women in Shenzhen, China. The HPV-SS was adapted from a 12-item HIV stigma scale. Demographic characteristics, HPV-related variables, and data on mental health were collected. Factor analyses (FA) were used to assess the scale's factorial structure, reliability, and validity. The bi-factor model was used to determine the score-reporting method of the scale. Item response theory (IRT) was employed to assess the relationship between participants' stigma levels and scale scores. Latent profile analysis (LPA) was conducted to classify the participants with different HPV stigma characteristics and determine the optimal cut-off value for HPV-SS. FA showed that the 3-factor model (personalized stigma, public-disclosure concerns, and negative self-image) had the best fit among the nested models, with good reliability and validity. The bi-factor model analysis indicated that the total scale score was more meaningful than dimension scores. IRT analysis confirmed that higher HPV-SS scores represented higher stigma levels. LPA identified a 2-class model as optimal, and the optimal cut-off value of the scale for high HPV stigma was 35. This study validated the 12-item HPV-SS for Chinese women infected with HPV, with good reliability and validity. The scale can be used to evaluate HPV stigma levels, facilitating targeted interventions to improve cervical cancer prevention and the psychological well-being of affected women. Show less
📄 PDF DOI: 10.1002/brb3.71044
LPA

Genetic Evidence for GLP-1 and GIP Receptors as Targets for Treatment and Prevention of MASLD/MASH.

Ran Yan, Lu Liu, Ioanna Tzoulaki +4 more · 2025 · Liver international : official journal of the International Association for the Study of the Liver · Blackwell Publishing · added 2026-04-24
Glucagon-like peptide-1 receptor (GLP1R) agonists and glucose-dependent insulinotropic polypeptide receptor (GIPR) agonists may help treat metabolic dysfunction-associated steatotic liver disease (MAS Show more
Glucagon-like peptide-1 receptor (GLP1R) agonists and glucose-dependent insulinotropic polypeptide receptor (GIPR) agonists may help treat metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). However, their definitive effects are still unclear. Our study aims to clarify this uncertainty. We utilised conventional Mendelian randomisation (MR) analysis to explore potential causal links between plasma GLP-1/GIP concentrations and MASLD and its related traits. Next, we conducted drug-target MR analysis using highly expressed tissue data to assess the effects of corresponding drug perturbation on these traits. Finally, mediation analysis was performed to ascertain whether the potential causal effect is direct or mediated by other MASLD-related traits. Circulating 2-h GLP-1 and GIP concentrations measured during an oral glucose tolerance test showed hepatoprotective effects on MASLD risk (OR GLP-1/GIP receptor agonists offer promise in lowering MASLD/MASH risk. GIP receptor agonists can exert direct and indirect effects on MASLD mediated by weight reduction or glycemic control improvement. Show less
no PDF DOI: 10.1111/liv.16150
GIPR

Exploring the bidirectional relationships between alzheimer's disease and cerebral small vessel disease: Insights from mendelian randomization.

Jihong Shang, Tian Liu, Wen Gong +1 more · 2025 · Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · Elsevier · added 2026-04-24
This study aimed to elucidate the bidirectional causal relationships between Alzheimer's disease (AD), cerebral small vessel disease (CSVD), and the effect of inflammatory cytokines on AD and CSVD usi Show more
This study aimed to elucidate the bidirectional causal relationships between Alzheimer's disease (AD), cerebral small vessel disease (CSVD), and the effect of inflammatory cytokines on AD and CSVD using Mendelian randomization (MR). We employed publicly available summary-level data from genome-wide association studies for AD, CSVD, and 91 inflammatory cytokines. Genetic variants strongly associated with each risk factor were selected as instrumental variables. The inverse variance weighted (IVW) method was primarily used for causal inference, with sensitivity analyses including MR-Egger and weighted median estimators. MR analysis revealed that genetically predicted CSVD significantly increased the risk of AD (odds ratio [OR] = 1.035, 95% CI, 1.015-1.056, P = 0.001). Conversely, AD did not significantly influence CSVD risk (OR = 0.878, 95% CI, 0.701-1.100, P = 0.257). Among inflammatory cytokines, Axin1 (OR = 1.082, 95% CI, 1.009-1.159, P = 0.026) and bNGF (OR = 1.061, 95% CI, 1.001-1.125, P = 0.048) increased AD risk, while CD5 (OR = 0.937, 95% CI, 0.887-0.991, P = 0.022) and CXCL11 (OR = 0.951, 95% CI, 0.912-0.992, P = 0.019) decreased AD risk. FGF19 (OR = 0.560, 95% CI, 0.405-0.773, P < 0.001) and TNFSF14 (OR = 0.744, 95% CI, 0.580-0.954, P = 0.020) were protective against CSVD. Our findings suggest that CSVD may increase AD risk, while specific inflammatory cytokines exhibit differential associations with these conditions. Targeting vascular health and inflammation may offer promising therapeutic avenues for managing neurodegenerative diseases. Show less
no PDF DOI: 10.1016/j.jstrokecerebrovasdis.2025.108259
AXIN1

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

Fanqi Liang, Man Zheng, Jingjiu Lu +2 more · 2025 · Scientific reports · Nature · added 2026-04-24
Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic infection to severe sepsis, potentially culminatin Show more
Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic infection to severe sepsis, potentially culminating in septic shock and multiple organ dysfunction syndrome. A pivotal element in the pathogenesis and progression of sepsis involves the significant disruption of oncological metabolic networks, where cells within the pathological milieu exhibit metabolic functions that diverge from their healthy counterparts. Among these, purine metabolism plays a crucial role in nucleic acid synthesis. However, the contribution of Purine Metabolism Genes (PMGs) to the defense mechanisms against sepsis remains inadequately explored. Leveraging bioinformatics, this study aimed to identify and substantiate potential PMGs implicated in sepsis. The approach encompassed a differential expression analysis across a pool of 75 candidate PMGs. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were employed to assess the biological significance and pathways associated with these genes. Additionally, Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) methodologies were implemented to identify key hub genes and evaluate the diagnostic potential of nine selected PMGs in sepsis identification. The study also examined the correlation between these hub PMGs and related genes, with validation conducted through expression level analysis using the GSE13904 and GSE65682 datasets. The study identified twelve PMGs correlated with sepsis, namely AK9, ENTPD3, NUDT16, GMPR2, PKM, RRM2B, POLR2J, POLE3, ADCY3, ADCY4, ADSSL1, and AMPD1. Functional analysis revealed their involvement in critical processes such as purine nucleotide and ribose phosphate metabolism. The diagnostic capability of these PMGs to effectively differentiate sepsis cases underscored their potential as biomarkers. This research elucidates twelve PMGs associated with sepsis, providing valuable insights into novel biomarkers for this condition and facilitating the monitoring of its progression. These findings highlight the significance of purine metabolism in sepsis pathogenesis and open avenues for further investigation into therapeutic targets. Show less
📄 PDF DOI: 10.1038/s41598-024-82998-0
ADCY3

Unraveling cellular dynamic changes in tumor evolution induced by long-term low dose-rate radiation.

Wanshi Li, Weiwei Pei, Yiwei Wang +16 more · 2025 · British journal of cancer · Nature · added 2026-04-24
In recent years, there has been a steady increase in professionals engaged in radioactive work. The biological impacts of long-term exposure to low dose-rate radiation remain elusive, as there is a de Show more
In recent years, there has been a steady increase in professionals engaged in radioactive work. The biological impacts of long-term exposure to low dose-rate radiation remain elusive, as there is a dearth of systematic research in this field. BEAS-2B cells were used to establish a cell model with continuous passaging after radiation exposure, which was subsequently subjected to in vivo tumorigenesis assays and in vitro malignant phenotype experiments. By scRNA-seq, we conducted copy number variation analysis, cell trajectory analysis, and cell communication analysis. Furthermore, we used FACS, molecular docking, multiplex immunohistochemistry, qRT-PCR, and co-immunoprecipitation to validate and further explore the molecular mechanisms driving tumor evolution. Long-term low dose-rate exposure is associated with a higher degree of malignancy, as evidenced by the induction of more CNV and EMT events, as well as the delayed activation of DNA repair pathways, which trigger increased genomic instability. The long-term low dose-rate specific ligand-receptor pair, ANGPTL4-SDC4, enhances cell malignancy by promoting angiogenesis in newly formed lung tumor cells. This study not only provides the first evidence and mechanistic explanation that long-term low dose-rate radiation leads to increased cellular malignancy but also offers valuable theoretical insights into the dynamic processes of early tumor evolution in lung cancer within the realm of tumor biology. Show less
no PDF DOI: 10.1038/s41416-025-03128-9
ANGPTL4

E3 ligase HERC5-catalyzed UGDH isgylation promotes SNAI1-mediated tumor metastasis and cisplatin resistance in oral squamous cell carcinoma.

Xu Zhang, Fayu Liu, Qigen Fang +2 more · 2025 · Biology direct · BioMed Central · added 2026-04-24
Oral squamous cell carcinoma (OSCC) is one of the leading causes of cancer-related mortality worldwide due to its high aggressive potential and drug resistance. Previous studies have revealed an impor Show more
Oral squamous cell carcinoma (OSCC) is one of the leading causes of cancer-related mortality worldwide due to its high aggressive potential and drug resistance. Previous studies have revealed an important function of HECT And RLD Domain Containing E3 Ubiquitin Protein Ligase 5 (HERC5) in cancer. Six GEO gene microarrays identified HERC5 as a significant upregulated gene in OSCC tissues or cells (log2 Fold change > 1 and adj.p < 0.05). This study aimed to explore the role and underlying mechanisms of HERC5 in OSCC development. High HERC5 expression in OSCC tissues was confirmed by our hospital validation cohort and positively correlated with primary tumor stages. Subsequent functional studies demonstrated that knockdown of HERC5 inhibited the migratory and invasive capabilities with decrease of Vimentin and increase of E-cadherin in OSCC cells. In cisplatin treatment, cell survival rates were significantly reduced in HERC5-silencing OSCC cells, accompanied by the increase in cytotoxicity, DNA damage and apoptosis. OSCC cell-derived tumor xenograft displayed that HERC5 depletion inhibited pulmonary metastasis as well as restored the cisplatin-induced tumor burden. In line with this, overexpression of HERC5 yielded the opposite alterations both in vivo and in vitro. Mechanistically, UDP-glucose 6-dehydrogenase (UGDH) was identified as a HERC5-binding protein. Cysteine residue at position 994 in the HECT domain of HERC5 catalyzed the conjugation of ubiquitin-like protein Interferon-induced 15 kDa protein (ISG15) to UGDH (ISGylation of UGDH) and facilitated its phosphorylation, therefore enhancing SNAI1 mRNA stability. SNAI1 depletion inhibited HERC5 overexpression-triggered invasion and cisplatin resistance of OSCC cells. Our study indicates that HERC5 may be a promising therapeutic target for OSCC. Show less
no PDF DOI: 10.1186/s13062-025-00622-1
SNAI1

Dysregulated serum lipid profile and atherosclerosis in untreated female Takayasu arteritis patients: a propensity score-matched analysis.

Q Zang, F Li, Y Ju +6 more · 2025 · Scandinavian journal of rheumatology · Taylor & Francis · added 2026-04-24
Recent studies suggest that dyslipidaemia may play a critical role in the progression of cardiovascular disease in Takayasu arteritis (TA), although the exact relationship between dyslipidaemia and TA Show more
Recent studies suggest that dyslipidaemia may play a critical role in the progression of cardiovascular disease in Takayasu arteritis (TA), although the exact relationship between dyslipidaemia and TA disease activity remains unclear, which is the focus of this study. We evaluated dyslipidaemia and atherosclerosis in a cohort of untreated female patients. Fifty untreated female patients with TA (median age 30 years) and 98 healthy controls matched for age and body mass index (median age 30 years) were assessed for lipid profiles [total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), ApoB, ApoE, lipoprotein(a)], inflammatory markers [C-reactive protein (CRP), erythrocyte sedimentation rate (ESR)], and atherosclerotic plaque frequency. TA patients exhibited significantly higher levels of TG and the non-HDL-C/HDL-C ratio than the control group, whereas TC, HDL-C, LDL-C, and ApoA1 levels were significantly lower. Pearson's correlation analysis indicated a positive correlation between CRP and ApoB, as well as the non-HDL-C/HDL-C ratio, and negative correlations with TG, HDL-C, and ApoA1. Atherosclerotic plaques were detected in 14.3% of the TA patients. Multivariate regression analysis revealed that the presence of atherosclerotic plaques was associated only with age, independent of inflammatory markers and lipoprotein levels. The results of this study indicate that untreated female TA patients exhibit a markedly dysregulated serum lipid profile. Atherosclerosis in early TA was not related to lipids or markers of inflammation. Show less
no PDF DOI: 10.1080/03009742.2025.2488096
APOB

Gut Microbiota and Metabolomics Insights into the Gualou-Xiebai Herb Pair for Dyslipidemia and Atherosclerosis.

Ni Wang, Yanan Xu, Jiahui Li +7 more · 2025 · Journal of microbiology and biotechnology · added 2026-04-24
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metaboli Show more
As a chronic lipid driven arterial disease, dyslipidemia is one of the most critical risk factors for atherosclerosis (AS). The gut microbiota plays an important role in regulating host lipid metabolism disorders. Studies have shown that the herb "Gualou-Xiebai" (GLXB) can effectively regulate the blood lipid levels of ApoE Show less
📄 PDF DOI: 10.4014/jmb.2510.10023
APOE

Hesperetin-Enhanced Metformin to Alleviate Cognitive Impairment via Gut-Brain Axis in Type 2 Diabetes Rats.

Danyang Zhang, Xiaoshi He, Yinbo Wang +8 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Diabetes constitutes a risk factor for cognitive impairment, whereas insulin resistance serves as the shared pathogenesis underlying both diabetes and cognitive decline. The use of metformin for treat Show more
Diabetes constitutes a risk factor for cognitive impairment, whereas insulin resistance serves as the shared pathogenesis underlying both diabetes and cognitive decline. The use of metformin for treating cognitive impairment remains controversial. The present study found that hesperetin, a flavanone derived from citrus peel, enhanced metformin's efficacy in reducing blood sugar levels, improving insulin sensitivity, and ameliorating cognitive impairment in diabetic rats. Additionally, it reduced the required dosage of metformin to one-third of its conventional dose. Transcriptome analysis and 16S rRNA sequencing revealed that the activation of insulin and cyclic-adenosine monophosphate response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) pathways benefited from the regulation of gut microbiota and the promotion of short-chain fatty acid (SCFA) producers such as Show less
📄 PDF DOI: 10.3390/ijms26051923
BACE1

Blood and urine biomarkers and myocardial infarction: A 2-sample and multivariate combination of Mendelian randomization.

Yu Ding, Haoyang Ling, Xiuyan Chen +6 more · 2025 · Medicine · added 2026-04-24
Myocardial infarction (MI) is one of the most serious cardiovascular diseases in the world. Nevertheless, the majority of diagnostic procedures conducted subsequent to the illness do not provide any m Show more
Myocardial infarction (MI) is one of the most serious cardiovascular diseases in the world. Nevertheless, the majority of diagnostic procedures conducted subsequent to the illness do not provide any means to prevent several risks associated with MI. Blood and urine tests are frequently employed in clinical examinations to detect cardiovascular diseases at an early stage. Mendelian randomization (MR) is commonly employed to explore disease-trait relationships and uncover therapeutic targets. Our goal was to explore the genetic links between 35 blood and urine biomarkers and MI. Blood and urine biomarker MR correlations with MI risk were studied. In version R10, the UK Biobank and Finnish databases included blood and urine marker data and MI data (26,060 cases and 343,079 controls). We performed bidirectional 2-sample MR with 4 methods: inverse variance weighted, MR-Egger, weighted median, and weighted mode. Final causal associations were determined by inverse variance weighted. Sensitivity analyses (heterogeneity, pleiotropy) were conducted. MR-PRESSO and PhenoScanner were used to exclude invalid instruments. We used multivariate MR to filter the most important genes without including other positive genes. To identify positive gene pathways and gene networks that cause MI, we employed GeneMANIA for gene prediction. The findings revealed a positive genetic association between the 8 blood and urine biomarker levels and an elevated risk of MI. There are apolipoprotein B (APOB), glycated hemoglobin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, sex hormone-binding globulin, triglycerides, and urate. Moreover, APOB, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol selectively affect MI through the rejection of other positive gene stems. Finally, APOB and numerous genes strongly impact MI development. APOB collaborates with related genes to regulate plasma lipoprotein particle levels, sterol homeostasis, organization, lipid homeostasis, and remodeling in MI. Our research further reveals the causal relationship between MI and blood/urine biomarkers, providing a new perspective for the prevention, diagnosis, and treatment of MI. Blood and urine marker tests can subsequently be conducted based on these results to detect MI and study the underlying mechanisms linking these metabolites to MI. Show less
no PDF DOI: 10.1097/MD.0000000000046146
APOB

Sex Differences in the Relationship Between Lipid Ratios and the Risk of Carotid Plaque.

Ling-Ling Wang, Zi-Xiang Xu, Bo-Qian Sun +3 more · 2025 · Angiology · SAGE Publications · added 2026-04-24
Lipid ratio is a balance between atherogenesis and antiatherogenesis. it is an important predictive marker of carotid plaque. The lipid ratios, which include non-high-density lipoprotein cholesterol ( Show more
Lipid ratio is a balance between atherogenesis and antiatherogenesis. it is an important predictive marker of carotid plaque. The lipid ratios, which include non-high-density lipoprotein cholesterol (non-HDL-C)/high-density lipoprotein cholesterol (HDL-C), remnant cholesterol (RC)/HDL-C, apolipoprotein B (ApoB)/apolipoprotein A1 (ApoA1), low-density lipoprotein cholesterol (LDL-C)/HDL-C, ApoB/HDL-C, total cholesterol (TC)/HDL-C, triglycerides (TG)/HDL-C, were included and analyzed. Sex differences in the relationship between lipid ratios and carotid plaque were discussed. The risk of carotid plaque was found to be significantly associated with the Non-HDL-C /HDL-C, RC/HDL-C, ApoB/ApoA1, LDL-C /HDL-C, ApoB/HDL-C, TC/HDL-C in females but not in males. The ApoB/HDL risk presented the highest relationship with carotid plaque in females only. The predictive value of the aforementioned lipid ratios for carotid plaque was observed in females only. Show less
no PDF DOI: 10.1177/00033197251316624
APOB

4,4-Diaponeurosporene regulated lactoferrin expression in neutrophils by IL-27 secreted dendritic cells.

Peng Liu, Jinjiao Zuo, Hui Lu +2 more · 2025 · Journal of reproductive immunology · Elsevier · added 2026-04-24
Sow colostrum is rich in lactoferrin (LF), which can be orally administered to protect piglets from porcine epidemic diarrhea virus (PEDV) infection, thereby reducing piglet mortality. Previous study Show more
Sow colostrum is rich in lactoferrin (LF), which can be orally administered to protect piglets from porcine epidemic diarrhea virus (PEDV) infection, thereby reducing piglet mortality. Previous study has shown that sows fed with recombinant B. subtilis expressing 4,4-diaponeurosporene (B.S-Dia) have significantly higher LF levels in their colostrum compared to sows fed with B. subtilis. This suggests that 4,4-diaponeurosporene (DNP) produced by B.S-Dia may influence LF content in sow colostrum. In this study, we first extracted DNP expressed by the recombinant probiotic using acetone-hexane extraction. Flow cytometry, RT-qPCR, and ELISA analyses demonstrated that DNP promoted dendritic cell (DCs) maturation and increased the expression of IL-1β and IL-27. We then established a method for isolating neutrophils from sow colostrum and set up a co-culture system of neutrophils and DCs to investigate factors regulating LF secretion. The results indicated that DCs secretions enhanced LF expression in neutrophils. Finally, the application of IL-27 inhibitors confirmed that IL-27 produced by DCs upregulates LF secretion in neutrophils. These findings elucidate the mechanism by which DNP promotes LF production in colostrum and provide a theoretical foundation for using B.S-Dia to prevent and control PEDV infection in piglets. Show less
no PDF DOI: 10.1016/j.jri.2025.104800
IL27