👤 Wuping 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, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, 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

Kaili sour soup in alleviation of hepatic steatosis in rats via lycopene route: an experimental study.

Yi Li, Shuo Cong, Rui Chen +3 more · 2025 · Annals of medicine · Taylor & Francis · added 2026-04-24
Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases, with a range of manifestations, such as hepatic steatosis. Our previous study showed that Kaili Sour Soup Show more
Nonalcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases, with a range of manifestations, such as hepatic steatosis. Our previous study showed that Kaili Sour Soup (KSS) significantly attenuated hepatic steatosis in rats. This study explored the main components of KSS and the mechanisms by which it exerts its protective effects against NAFLD. Twenty-four 6-week-old male Sprague-Dowley (SD) rats were randomly assigned to three treatments: feeding a normal standard diet, a high-fat diet, or a high-fat diet plus gavage KSS. The effects of KSS treatment on hepatic lipid accumulation were assessed using biochemical, histological, and molecular experiments. The amounts of KSS ingredients were measured using biochemical assays. Network pharmacology analyses were performed to identify the hub genes of KSS targets and enriched pathways. CCK-8 assay was used to determine the effect of free fatty acids (FFA), lycopene, and estrogen on HepG2 viability. Quantitative Real-Time polymerase chain reaction (qRT-PCR) and Western blot assays were performed to determine the effect of KSS or lycopene on estrogen signaling and expression of lipid metabolism-related molecules. Statistical analyses were performed using GraphPad Prism and SPSS. KSS alleviated fat deposition in rat liver tissue and affected the expression of hepatic lipid synthesis, catabolism, and oxidative molecules. Lycopene was identified as the ingredient with the highest amount in KSS. Network pharmacology analyses showed that the hub genes were enriched in the estrogen signaling pathway. Cellular experiments showed that lycopene increased the expression of Estrogen Receptor α (ERα), Carnitine palmitoyltransferase 1 A ( KSS ameliorated abnormal lipid metabolism in patients with NAFLD. Lycopene was the major component of KSS, and it affected estrogen signaling and the expression of lipid metabolism molecules. In short, both KSS and LYC could change lipid metabolism by lowering lipid accumulation and raising lipolysis. Show less
📄 PDF DOI: 10.1080/07853890.2025.2479585
LPL

Social Isolation and Its Influencing Factors in Maintenance Haemodialysis Patients: A Latent Profile Analysis.

Luwen Zhang, Fangli Liu, Jinghui Liu +1 more · 2025 · Journal of advanced nursing · Blackwell Publishing · added 2026-04-24
To explore latent profiles of social isolation in maintenance haemodialysis (MHD) patients and to analyse the factors influencing different latent profiles. Multicentre cross-sectional study. Between Show more
To explore latent profiles of social isolation in maintenance haemodialysis (MHD) patients and to analyse the factors influencing different latent profiles. Multicentre cross-sectional study. Between November 2024 to March 2025, 305 MHD patients from the haemodialysis centres of three hospitals in Henan Province, China, were recruited using a convenience sampling method. All participants completed the general information questionnaire, Lubben Social Network Scale 6 (LSNS-6), UCLA Loneliness Scale-6 (ULS-6) and Personal Mastery Scale. Latent Profile Analysis (LPA) was used to classify the participants into potential subgroups with different types of social isolation. The influencing factors of profiles were explored by univariate analysis and multiple logistic regression analysis. Social isolation of 305 patients can be divided into three profiles: the family-friend dual isolation group (14.10%), friend isolation-only group (47.54%), and social network well-being group (38.36%). Multivariable logistic regression analysis revealed that monthly personal income, living arrangement, social participation, dialysis time, post-dialysis fatigue, number of comorbidities, loneliness and personal mastery were identified as factors influencing the profiles. There is heterogeneity in social isolation among MHD patients. It is therefore necessary to implement targeted intervention measures based on the distinct characteristics of each subgroup to facilitate their social reintegration. Nurses should identify differences in social isolation among MHD patients. It is necessary to establish tripartite connections between families, hospitals and communities, and develop personalised psychosocial interventions to alleviate social isolation. The study identified distinct subgroups of social isolation among MHD patients, while emphasising the impact of psychological resources such as loneliness and personal mastery on social isolation. This may offer critical insights for nurses to develop targeted interventions for patients' social health. The study followed the STROBE guidelines for cross-sectional studies. No patient or public involvement. Show less
no PDF DOI: 10.1111/jan.70452
LPA

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

APOE Lipoprotein Particles: Pathophysiology, Therapy, and the Crosstalk in Alzheimer's Disease and Cardiovascular Disease.

Chan Liu, Juan Liu, Yan-Yang Wang +2 more · 2025 · Molecular neurobiology · Springer · added 2026-04-24
The APOE4 variant was the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Individuals with APOE4 have an increased risk of developing the disease at an early age of onset. Similar Show more
The APOE4 variant was the strongest genetic risk factor for sporadic Alzheimer's disease (AD). Individuals with APOE4 have an increased risk of developing the disease at an early age of onset. Similarly, APOE4 carriers are predisposed to high cholesterol levels and tend to have an increased risk of cardiovascular disease (CVD). The global allele frequency of APOE4 was 13.7%, underlining its widespread impact on global human health. Conversely, the relatively rare APOE2 allele was a genetic protective factor against AD and CVD. However, the mechanisms underlying this association remain to be elucidated. The apolipoprotein E (APOE) protein coats lipoprotein particles and mediates lipid transport and metabolism in the peripheral circulation and central nervous system (CNS). Although initial studies causally linked APOE lipoprotein particles (APOE particles) with lipid homeostasis, our understanding of the physiological and pathological effects of APOE particles has extended to amyloid-β (Aβ) accumulation, tau hyperphosphorylation and spread, as well as neuroinflammation in AD initiation and progression. Moreover, the most examined functions of APOE particles are reverse cholesterol transport, anti-inflammatory, anti-oxidation, and improvement of endothelial dysfunction in atherosclerotic CVD. This review outlines what is known about the structure and functions of APOE particles, emphasizing their involvement in AD and CVD pathogenesis, while also considering the crosstalk between the peripheral circulation and CNS. In addition, we discuss how these APOE particles act as therapeutic targets. Show less
📄 PDF DOI: 10.1007/s12035-025-05629-3
APOE

FGFR1 inhibition by carvacrol: A novel strategy for oral squamous cell carcinoma therapy.

Shuzhen Xiang, Hongyan Zhang, Qian Wang +7 more · 2025 · Genes & diseases · Elsevier · added 2026-04-24
📄 PDF DOI: 10.1016/j.gendis.2024.101479
FGFR1

Research status and future perspectives of IL‑27 in the treatment of stroke (Review).

Weiqin Liu, Zhenyou Zou, Wenyang Li +4 more · 2025 · International journal of molecular medicine · added 2026-04-24
Stroke is a life‑threatening cerebrovascular disorder categorized into two major subtypes: Ischemic and hemorrhagic. Characterized by high morbidity and mortality rates, its clinical management remain Show more
Stroke is a life‑threatening cerebrovascular disorder categorized into two major subtypes: Ischemic and hemorrhagic. Characterized by high morbidity and mortality rates, its clinical management remains challenging due to limited therapeutic options. Interleukin (IL)‑27, a pleiotropic cytokine with demonstrated neuroprotective potential, has emerged as a promising candidate for stroke intervention. IL‑27 exerts immunomodulatory effects within the central nervous system, including suppression of proinflammatory T‑cell proliferation and induction of regulatory T‑cell differentiation. These mechanisms collectively attenuate neuroinflammation, mitigate neuronal apoptosis and prevent neurodegenerative processes. The efficacy of IL‑27 in reducing cerebral damage in both ischemic and hemorrhagic stroke models has been validated, although clinical translation remains to be achieved. The present review summarizes: i) The epidemiology of stroke; ii) the immunoregulatory functions of IL‑27 and its neuroprotective mechanisms across stroke subtypes; iii) innovative brain‑targeted delivery approaches; iv) IL‑27 clinical applicability with supporting evidence; and v) possible risks and solutions in clinical applications. By collating the current knowledge, the present study provides a translational framework for advancing IL‑27‑based therapies in stroke management. Show less
📄 PDF DOI: 10.3892/ijmm.2025.5557
IL27

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

The role of serun lipid, cytokine production in sudden sensorineural hearing loss.

Xiaoqing Zhang, Zhihua Xu, Yehai Liu · 2025 · Cytotechnology · Springer · added 2026-04-24
Sudden sensorineural hearing loss (SSNHL) has serious harm to human hearing health, where blood lipid and inflammatory levels may play a key role in it. Thus, the purpose of this investigation was to Show more
Sudden sensorineural hearing loss (SSNHL) has serious harm to human hearing health, where blood lipid and inflammatory levels may play a key role in it. Thus, the purpose of this investigation was to assess the connection between inflammatory and lipid variables and SSNHL. Patients diagnosed with SSNHL had an analysis of serum lipid parameters, such as total cholesterol (TC), triglycerides, HDL-C, LDL-C, apolipoprotein A (apo A), apolipoprotein B (apo B), and lipoprotein A (Lp(a)), as well as inflammatory factors like TNF-α and IL-10. After that, risk factor analysis was carried out utilizing univariate, multivariate regression, and LASSO retrospective modeling. In all, 72 SSNHL patients and 67 healthy control individuals were involved. The LDL/HDL, total cholesterol, ApoB, LP(a), IL-10, TNF-α, and IFN-γ considerably higher in the SSNHL group than in the healthy control group, however, nervonic acid and coenzyme Q were decreased significantly in SSNHL than Control group. The multivariate logistic regression model's analysis using multifactorial retrospective modeling revealed significant changes in LDL, LDL/HDL, IL-10, and TNF-α. In addition, in the LASSO regression model, the model demonstrated high discrimination, as evidenced by the C-index for the cohort's prediction nomogram, which was 0.998 (95% CI, 0.154-1.115) and confirmed to be 0.925 following bootstrapping validation. Finally, IL-10 and LDL/HDL were the main risk factors in SSNHL. LDL/HDL and IL-10 may be closely related to SSNHL's progress and should be evaluated promptly before treating patients with SSNHL. Show less
no PDF DOI: 10.1007/s10616-025-00722-w
APOB

Identifying novel drug targets for calcific aortic valve disease through Mendelian randomization.

Dilin Xu, Jin Lu, Yanfang Yang +11 more · 2025 · Atherosclerosis · Elsevier · added 2026-04-24
Calcific aortic valve disease (CAVD) is characterized by progressive leaflet thickening and calcification, with no available pharmacological treatments. Plasma proteins play a pivotal role in disease Show more
Calcific aortic valve disease (CAVD) is characterized by progressive leaflet thickening and calcification, with no available pharmacological treatments. Plasma proteins play a pivotal role in disease regulation. This study aimed to uncover novel therapeutic targets for CAVD using Mendelian randomization (MR) integrated with transcriptomic analysis. Protein quantitative trait loci (pQTL) from the deCODE and UK Biobank Pharma Proteomics Project (UKB-PPP) plasma protein databases were used as exposure data. The FinnGen cohort (9870 cases, 402,311 controls) served as the discovery set, while the TARGET cohort (13,765 cases, 640,102 controls) provided validation. MR and summary data-based Mendelian randomization (SMR) were employed to screen for potential causal targets of CAVD. Colocalization analysis was conducted to assess whether CAVD and target proteins shared common causal SNPs. Additional analyses included trancriptomic profiling at multiple RNA levels. Protein-level validation was conducted via Western blot and immunostaining. Six proteins (ANGPTL4, PCSK9, ITGAV, CTSB, GNPTG, and FURIN) with strong genetic colocalization were identified by MR and SMR analysis. Among these, cellular trancriptomic analysis revealed ANGPTL4 and ITGAV with significantly greater expression in osteogenic group, which was further validated in calcified aortic valves and osteogenic valvular interstitial cells in protein level. This study identified six causal proteins with strong genetic colocalization for CAVD, with ANGPTL4 and ITGAV emerging as the most promising targets for further investigation. Show less
no PDF DOI: 10.1016/j.atherosclerosis.2025.119110
ANGPTL4

Branched-Chain α Keto-Acid Dehydrogenase Kinase-Mediated AKT Phosphorylation Promotes RCC Tumorigenesis and Drug Resistance.

Qin Tian, Jinxiang Wang, Qiji Li +16 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-ac Show more
Advanced renal cell carcinoma (RCC) primarily relies on targeted and immune-based therapies, yet these treatments often face limitations due to inefficacy and drug resistance. Branched-chain α-keto-acid dehydrogenase kinase (BCKDK) has been implicated in promoting RCC metastasis, but its specific substrates and the mechanisms underlying its regulation of RCC progression remain poorly understood. This study uncovers a novel mechanism whereby BCKDK-mediated AKT phosphorylation drives RCC tumorigenesis and drug resistance. Elevated BCKDK expression correlates with poor prognosis in RCC clinical samples. BCKDK deficiency inhibits RCC cell proliferation and tumorigenesis both in vitro and in vivo. Mechanistic investigations reveal that BCKDK directly binds to and regulates the phosphorylation of AKT. BCKDK-mediated phosphorylation of AKT decreases ubiquitin-mediated AKT protein degradation, and promotes tumorigenesis via activation of the AKT/mTOR signaling pathway. RNA sequencing identifies BCKDK's involvement in the drug metabolism network and apoptotic signaling pathways. The BCKDK/AKT/ABCB1 axis mediates doxorubicin resistance. Targeting BCKDK/AKT inhibits the growth of RCC patient-derived organoids (PDOs), enhances doxorubicin-induced apoptosis in RCC cells, and suppresses tumor growth in vivo. These findings identify a previously unrecognized phosphorylation substrate of BCKDK and highlight the critical role of the BCKDK/AKT signaling axis in RCC progression, offering a promising target for therapeutic intervention. Show less
📄 PDF DOI: 10.1002/advs.202411081
BCKDK

Depletion of Hepatic SREBP2 Protects Against Hypercholesterolemia and Atherosclerosis through the ANGPTL3-LPL Axis.

Yifan Wang, Jia You Sarafina Choe, Yu Shi +11 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Lipolysis of triglyceride-rich lipoproteins by peripheral lipoprotein lipase (LPL) plays an essential role in maintaining systemic cholesterol/lipid homeostasis. Human genetic studies have unequivocal Show more
Lipolysis of triglyceride-rich lipoproteins by peripheral lipoprotein lipase (LPL) plays an essential role in maintaining systemic cholesterol/lipid homeostasis. Human genetic studies have unequivocally demonstrated that activation of LPL pathway reduces risks for both coronary artery disease (CAD) and type 2 diabetes (T2D). Although sterol regulatory element-binding protein 2 (SREBP2) is well established as the master transcription factor that regulates the hepatic biosynthesis of both cholesterol and fatty acids, whether and how its activity in liver interacts with peripheral LPL pathway remains unknown. Here, it is demonstrated that acute liver-specific depletion of SREBP2 results in divergent effects on the regulation of peripheral LPL activity in mice, depending on the presence or absence of low-density lipoprotein receptors (LDLR). SREBP2 deficiency drastically elevates peripheral LPL activity through downregulation of plasma angiopoietin-related protein 3 (ANGPTL3) levels in LDLR-deficient mice. Moreover, in addition to SREBP2's transcriptional regulation of ANGPTL3, it is found that SREBP2 promotes proteasome-based degradation of ANGPTL3 in the presence of LDLR. Remarkably, acute depletion of hepatic SREBP2 protects against hypercholesterolemia and atherosclerosis, in which atherosclerotic lesions are reduced by 45% compared to control littermates. Taken together, these findings outline a liver-peripheral crosstalk mediated by SREBP2-ANGPTL3-LPL axis and suggest that SREBP2 inhibition can be an effective strategy to tackle homozygous familial hypercholesterolemia (HoFH). Show less
📄 PDF DOI: 10.1002/advs.202412677
LPL

CCL26-CX3CR1 Axis Mediates a Feedback Loop between Cancer Cell and PMN-MDSCs to Promote CD8

Xiaotao Jiang, Hui Wu, Ning Yan +14 more · 2025 · Research (Washington, D.C.) · added 2026-04-24
The development of an immunosuppressive microenvironment is a critical factor in stomach carcinogenesis. Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) serve a pivotal function in medi Show more
The development of an immunosuppressive microenvironment is a critical factor in stomach carcinogenesis. Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) serve a pivotal function in mediating immune suppression. However, the precise mechanisms underlying PMN-MDSCs infiltration into the tumor immune microenvironment (TIME) and their immunosuppressive functions remain poorly understood. In this investigation, we observed that PMN-MDSCs were up-regulated during stomach carcinogenesis, with gastric cancer (GC) cells secreting CCL26 to promote the infiltration of PMN-MDSCs into the TIME via the CX3CR1 receptor. The infiltrating CX3CR1 Show less
no PDF DOI: 10.34133/research.1002
SNAI1

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

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

Impact of dietary lysophospholipids supplementation on growth performance, meat quality, and lipid metabolism in finishing bulls fed diets varying in fatty acid saturation.

Meimei Zhang, Haixin Bai, Ruixue Wang +5 more · 2025 · Journal of animal science and biotechnology · BioMed Central · added 2026-04-24
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipi Show more
The objective of this study was to evaluate the effects of dietary fatty acids (FA) saturation and lysophospholipids supplementation on growth, meat quality, oxidative stability, FA profiles, and lipid metabolism of finishing beef bulls. Thirty-two Angus bulls (initial body weight: 623 ± 22.6 kg; 21 ± 0.5 months of age) were used. The experiment was a completely randomized block design with a 2 × 2 factorial arrangement of treatments: 2 diets with FA of different degree of unsaturation [high saturated FA diet (HSFA) vs. high unsaturated FA diet (HUFA)] combined with (0.075%, dry matter basis) and without lysophospholipids supplementation. The bulls were fed a high-concentrate diet (forage to concentrate, 15:85) for 104 d including a 14-d adaptation period and a 90-d data and sample collection period. No interactions were observed between dietary FA and lysophospholipids supplementation for growth and meat quality parameters. A greater dietary ratio of unsaturated FA (UFA) to saturated FA (SFA) from 1:2 to 1:1 led to lower DM intake and backfat thickness, but did not affect growth performance and other carcass traits. Compared with HSFA, bulls fed HUFA had greater shear force in Longissimus thoracis (LT) muscle, but had lower intramuscular fat (IMF) content and SOD content in LT muscle. Compared with HUFA, feeding the HSFA diet up-regulated expression of ACC, FAS, PPARγ, and SCD1, but down-regulated expression of CPT1B. Compared with feeding HSFA, the HUFA diet led to greater concentrations of c9-C18:1 and other monounsaturated FA in LT muscle. Feeding HUFA also led to lower plasma concentrations of cholesterol, but there were no interactions between FA and lysophospholipids detected. Feeding lysophospholipids improved growth and feed conversion ratio and altered meat quality by increasing muscle pH Results indicated that supplementing a high-concentrate diet with lysophospholipids to beef bulls can enhance growth rate, feed efficiency, meat quality, and beneficial FA. Increasing the dietary ratio of UFA to SFA reduced DM intake and backfat thickness without compromising growth, suggesting potential improvements in feed efficiency. Show less
📄 PDF DOI: 10.1186/s40104-024-01138-w
LPL

Genome-wide chromatin accessibility and transcriptome analysis reveal the up-regulation of immunosuppressive genes in macrophages under simulated microgravity.

Sufang Wang, Nu Zhang, Guolin Shi +3 more · 2025 · Life sciences in space research · Elsevier · added 2026-04-24
Long-term space missions are of growing research interest because of the space exploration. However, plenty of works focused on the impaired immune response, less attention has been paid to the activa Show more
Long-term space missions are of growing research interest because of the space exploration. However, plenty of works focused on the impaired immune response, less attention has been paid to the activation of immunosuppressive or anti-inflammatory function. The molecular mechanism of immune disorder induced by microgravity still needs investigation. Here, we used a random positioning machine to generate a simulated microgravity environment and evaluated its effects on mouse RAW 264.7 macrophage cell line. We used ATAC-seq and RNA-seq for revealing the mechanism at chromatin level and gene level. From ATAC-seq, we obtained an average of 75,700,675 paired-end clean reads for each library and the mapping rates averaged at 96.8 %. The number of differential accessible regions were 510 for increased peaks, 638 for decreased peaks. From RNA-seq, we obtained 278 differentially expressed genes, of which 104 were down-regulated and 174 were up-regulated genes. Through ATAC-seq and RNA-seq multi-omics analysis, we identified a group of 17 genes. Then we chose 6 up-regulated genes (CD83, CEBPD, CXCR5, DUSP6, SEMA4B, TNFRSF22) that related to immunosuppressive function for further confirmation. The qRT-PCR results were consistent with sequencing results, which indicated that simulated microgravity leads to the up-regulated expression of immunosuppressive genes of macrophages. Taken together, our results offered novel insights for understanding the brief principles and mechanisms of simulated microgravity induced immune dysfunction to macrophage. Show less
no PDF DOI: 10.1016/j.lssr.2025.03.002
DUSP6

The Oncopromoting Gene RBM6 Inhibits Prostate Tumour Cell Migration During Epithelial-to-Mesenchymal Transition.

Ruoyang Liu, Yu Liu, Long Zhang +7 more · 2025 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
RBM6, implicated in the progression of multiple tumour types but unexplored in prostate tumours, was found to indicate potential therapeutic implications due to its elevated expression in prostate tum Show more
RBM6, implicated in the progression of multiple tumour types but unexplored in prostate tumours, was found to indicate potential therapeutic implications due to its elevated expression in prostate tumours. To elucidate its molecular function, scratch tests, transwell migration and invasion assays were conducted, with PCR and western blot analyses verifying molecular regulatory relationships. RNA pulldown and RNA immunoprecipitation tests were also employed to investigate underlying mechanisms. Results indicate that RBM6 enhances prostate cell migration by suppressing CDH1, yet ZEB1 overexpression alleviates this suppression. Notably, under these conditions, RBM6's inhibitory effect on MMP16 becomes more pronounced, reducing cell migration ability. Thus, under normal conditions, RBM6 promotes prostate tumour cell migration, but in the context of high ZEB1 expression, it inhibits migration. This shift in RBM6's regulatory capacity towards downstream genes underscores the importance of considering objective conditions in studying RBM6 molecules. Show less
no PDF DOI: 10.1111/jcmm.70397
RBM6

Study on the Efficacy and Pharmacological Mechanism of Innate Immune STING Pathway Regulators in the Treatment of Ischemic Brain Injury.

Chang Liu, Xiaoqing Wang, Yueru Zhang +2 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18121775
BDNF

Metabolome and transcriptome analyses reveal the mechanism underlying the differences in skin development between the two duck breeds during embryonic stage.

Zhigang Hu, Yingjie Cai, Chang Cao +5 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Skin color of poultry, an important economic trait, is related to breed, feed, environment, and other factors. In recent years, China's duck industry has developed rapidly, and duck products are welco Show more
Skin color of poultry, an important economic trait, is related to breed, feed, environment, and other factors. In recent years, China's duck industry has developed rapidly, and duck products are welcomed by consumers. Different skin colors of ducks have different cooking methods. Black skinned duck, such as Yulin black duck, is more popular in China because they are considered more suitable for making soup, while other skin colors, such as Pekin duck, is used for roasting. In order to gain a deeper understanding of the genetic factors associated with differences in duck skin color, the transcriptomes and metabolomes of skin between Yulin black duck and Pekin duck from 15 (BSE15 vs. PSE15), 21 (BSE21 vs. PSE21) and 27 (BSE27 vs. PSE27) days of incubation were compared and analyzed. The transcriptome results showed that a total of 187 (118 up-regulated and 69 down-regulated), 417 (91 up-regulated and 326 down-regulated) and 137 (55 up-regulated and 82 down-regulated) differentially expressed genes (DEGs) were identified from BSE15 vs. PSE15, BSE21 vs. PSE21 and BSE27 vs. PSE27, respectively. The significantly enriched GO terms of biological process were positive regulation of melanin biosynthetic process, melanin biosynthetic process, cuticle development, melanin biosynthetic process from tyrosine, and melanocyte differentiation, which were potentially related to skin growth and development. Eleven significant pathways, highly enriched by DCT, TYR, ASIP, TYRP1, KIT, PHOSPHO2, CERS3, SGPP2, SPTLC3, DEGS2, PATJ, RBP7, AOX1, ETNPPL, HPGDS, and GAD1, were melanogenesis, tyrosine metabolism, vitamin B6 metabolism, sphingolipid metabolism, protein digestion and absorption, tight junction, alpha-linolenic acid metabolism, arachidonic acid metabolism, linoleic acid metabolism, nicotinate and nicotinamide metabolism, and alanine, aspartate and glutamate metabolism, which participated in regulating the development of duck skin during embryonic stage. The significantly different metabolites (SDMs) were mainly organoheterocyclic compounds, lipids and lipid-like molecules, organic oxygen compounds, organic acids and derivatives, including L-tyrosine, N-arachidonyl maleimide, glycerophospho-N-palmitoyl ethanolamine, LPE 22:4, and PC(0:0/18:0). which were mainly enriched in glycerophospholipid metabolism, arachidonic acid metabolism, linoleic acid metabolism, alpha-linoleic acid metabolism, and melanogenesis in metabolome, suggesting that these pathways may play important roles in skin development of duck during embryonic stage. Besides, the analysis of integrated transcriptome and metabolome indicated that the pathways, including glycerophospholipid metabolism, arachidonic acid metabolism, linoleic acid metabolism, and alpha-linolenic acid metabolism, could contribute to regulating skin development in embryonic duck. Our findings could help elucidate the genetic mechanisms underlying the development differences in duck skin color. Furthermore, the candidate genes and metabolites can be used to provide a valuable breeding strategy for the selection of specific duck breeds with ideal skin coloration. Show less
no PDF DOI: 10.1016/j.psj.2025.105403
PATJ

Lipids, Lipid-Lowering Drug Target Genes, and COPD Risk: A Mendelian Randomization Study.

Guobing Jia, Tao Guo, Lei Liu +1 more · 2025 · Chronic obstructive pulmonary diseases (Miami, Fla.) · added 2026-04-24
Some studies suggest that statins could reduce the risk of chronic obstructive pulmonary disease (COPD), but it is unclear if this effect is related to their lipid-lowering properties. The causal link Show more
Some studies suggest that statins could reduce the risk of chronic obstructive pulmonary disease (COPD), but it is unclear if this effect is related to their lipid-lowering properties. The causal link between serum lipid levels and COPD risk remains uncertain. This study aims to clarify this potential causal relationship and evaluate the impact of lipid-lowering drug target genes on COPD. Mendelian randomization (MR) was used to investigate causal associations between lipid levels, lipid-lowering drug target genes, and COPD risk. Data were obtained from publicly available genome-wide association study databases. The inverse variance weighted method was the primary statistical approach for evaluating causal effects, complemented by various sensitivity analyses. MR analysis demonstrated a causal relationship between low-density lipoprotein cholesterol (LDL-C) and a reduced risk of COPD (odds ratio [OR]=0.90, 95% confidence interval [CI]=0.85-0.95, P=1.50×10⁻⁴). Causal relationships were also identified for 2 lipid-lowering drug target genes, This study genetically identified causal relationships between serum LDL-C levels, the 2 coding genes Show less
no PDF DOI: 10.15326/jcopdf.2025.0632
LPL

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

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

Oligodendrocyte-astrocyte crosstalk in Parkinson's disease mediates neuronal ferroptosis via the FGF signaling pathway.

Sen Zhang, Min Yan, Xing Jiang +7 more · 2025 · NPJ Parkinson's disease · Nature · added 2026-04-24
Parkinson's disease (PD), as a neurodegenerative disorder, is characterized primarily by damage to the central nervous system, accompanied by astrocyte dysfunction and the activation of ferroptosis. R Show more
Parkinson's disease (PD), as a neurodegenerative disorder, is characterized primarily by damage to the central nervous system, accompanied by astrocyte dysfunction and the activation of ferroptosis. Recent studies have shown that oligodendrocytes also exhibit functional abnormalities in the brains of PD patients and are involved in the ferroptotic process. However, it remains unclear whether there is an interaction between oligodendrocytes and astrocytes and how they induce neuronal ferroptosis. Here, we employed single-nucleus sequencing and spatial transcriptomics to characterize the intercellular communication network between oligodendrocytes and astrocytes in the PD environment. Among these, astrocytes are the primary recipients of signals sent by oligodendrocytes in the FGF (Fibroblast growth factors) signaling pathway. In PD, the communication intensity is weakened, involving FGF1 and FGF9 and their receptors FGFR1, FGFR2, and FGFR3. Subsequently, we further validated the significant activation of mitochondrial oxidative phosphorylation processes within oligodendrocytes and astrocytes in PD mice, and that astrocytes might also involve the interaction of Mt1 and Ca Show less
📄 PDF DOI: 10.1038/s41531-025-00995-0
FGFR1

Shared genetic architecture contributes to risk of major cardiovascular diseases.

Jun Qiao, Lei Jiang, Liuyang Cai +14 more · 2025 · Nature communications · Nature · added 2026-04-24
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations Show more
The extensive co-occurrence of cardiovascular diseases (CVDs), as evidenced by epidemiological studies, is supported by positive genetic correlations identified in comprehensive genetic investigations, suggesting a shared genetic basis. However, the precise genetic mechanisms underlying these associations remain elusive. By assessing genetic correlations, genetic overlap, and causal connections, we aim to shed light on common genetic underpinnings among major CVDs. Employing multi-trait analysis, we pursue diverse strategies to unveil shared genetic elements, encompassing SNPs, genes, gene sets, and functional categories with pleiotropic implications. Our study systematically quantifies genetic overlap beyond genome-wide genetic correlations across CVDs, while identifying a putative causal relationship between coronary artery disease (CAD) and heart failure (HF). We then pinpointed 38 genomic loci with pleiotropic influence across CVDs, of which the most influential pleiotropic locus is located at the LPA gene. Notably, 12 loci present high evidence of multi-trait colocalization and display congruent directional effects. Examination of genes and gene sets linked to these loci unveiled robust associations with circulatory system development processes. Intriguingly, distinct patterns predominantly driven by atrial fibrillation, coronary artery disease, and venous thromboembolism underscore the significant disparities between clinically defined CVD classifications and underlying shared biological mechanisms, according to functional annotation findings. Show less
📄 PDF DOI: 10.1038/s41467-025-62419-0
LPA

Precision targeting of β-catenin induces tumor reprogramming and immunity in hepatocellular cancers.

Brandon M Lehrich, Evan R Delgado, Tyler M Yasaka +32 more · 2025 · Nature communications · Nature · added 2026-04-24
First-line immune checkpoint inhibitor (ICI) combinations show responses in subsets of hepatocellular carcinoma (HCC) patients. Nearly half of HCCs are Wnt-active with mutations in CTNNB1 (encoding fo Show more
First-line immune checkpoint inhibitor (ICI) combinations show responses in subsets of hepatocellular carcinoma (HCC) patients. Nearly half of HCCs are Wnt-active with mutations in CTNNB1 (encoding for β-catenin), AXIN1/2, or APC, and demonstrate heterogeneous and limited benefit to ICI due to an immune excluded tumor microenvironment. We show significant tumor responses in multiple β-catenin-mutated immunocompetent HCC models to a novel siRNA encapsulated in lipid nanoparticle targeting CTNNB1 (LNP-CTNNB1). Both single-cell and spatial transcriptomics reveal cellular and zonal reprogramming, along with activation of immune regulatory transcription factors IRF2 and POU2F1, re-engaged type I/II interferon signaling, and alterations in both innate and adaptive immunity upon β-catenin suppression with LNP-CTNNB1 at early- and advanced-stage disease. Moreover, ICI enhances response to LNP-CTNNB1 in advanced-stage disease by preventing T cell exhaustion and through formation of lymphoid aggregates (LA). In fact, expression of an LA-like gene signature prognosticates survival for patients receiving atezolizumab plus bevacizumab in the IMbrave150 phase III trial and inversely correlates with CTNNB1-mutatational status in this patient cohort. In conclusion, LNP-CTNNB1 is efficacious as monotherapy and in combination with ICI in CTNNB1-mutated HCCs through impacting tumor cell-intrinsic signaling and remodeling global immune surveillance, providing rationale for clinical investigations. Show less
📄 PDF DOI: 10.1038/s41467-025-60457-2
AXIN1

Targeting WNT5A noncanonical signaling attenuates renal fibrosis progression in acute kidney injury.

Sijie Gu, Haoran Feng, Xiaomei Li +10 more · 2025 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Preventing the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remains a considerable clinical challenge. In this study, we elucidate the role of WNT5A in accelerating the A Show more
Preventing the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remains a considerable clinical challenge. In this study, we elucidate the role of WNT5A in accelerating the AKI-to-CKD transition and its underlying mechanisms. Renal biopsies from patients with AKI showed marked upregulation of WNT5A and its receptor, CD146, in proximal tubules, with higher expression in patients with CKD progression. In murine AKI models, Wnt5a knockdown attenuated CKD progression. Conversely, proximal tubular overexpression of Wnt5a exacerbated renal fibrosis in ischemia-reperfusion injury (IRI) mice, which was alleviated by Box5, a specific WNT5A antagonist. In vitro, WNT5A overexpression in transforming growth factor β (TGF-β)-stimulated HK-2 cells promoted CD146 upregulation, activated JNK phosphorylation, and enhanced SNAI1 expression. The genetic silencing of WNT5A/CD146 and JNK inhibition suppresses SNAI1 expression and attenuates fibrotic responses. Mechanistically, JNK-mediated c-JUN phosphorylation promoted its interaction with KLF5 at the SNAI1 promoter, driving renal fibrosis. Elevated serum levels of soluble CD146 correlated with renal function in patients with AKI and were higher in patients exhibiting CKD progression. Inhibition of WNT5A could serve as a therapeutic target for delaying renal fibrosis in AKI progression. Show less
no PDF DOI: 10.1016/j.ymthe.2025.06.039
SNAI1

Advancing the clinical assessment of glomerular podocyte pathology in kidney biopsies via super-resolution microscopy and angiopoietin-like 4 staining.

Xiaojing Liu, Suxia Wang, Gang Liu +7 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.101498
ANGPTL4

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

Letter by Shi et al Regarding Article "Associations of Circulating ANGPTL3, C-Terminal Domain-Containing ANGPTL4, and ANGPTL3/8 and ANGPTL4/8 Complexes with LPL Activity, Diabetes, Inflammation, and Cardiovascular Mortality".

Feng Shi, Bin Zheng, Yubin Liu · 2025 · Circulation · added 2026-04-24
no PDF DOI: 10.1161/CIRCULATIONAHA.125.074117
ANGPTL4

A Multi-Task Self-Supervised Strategy for Predicting Molecular Properties and FGFR1 Inhibitors.

Xin Yang, Yang Wang, Ye Lin +4 more · 2025 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Studying the molecular properties of drugs and their interactions with human targets aids in better understanding the clinical performance of drugs and guides drug development. In computer-aided drug Show more
Studying the molecular properties of drugs and their interactions with human targets aids in better understanding the clinical performance of drugs and guides drug development. In computer-aided drug discovery, it is crucial to utilize effective molecular feature representations for predicting molecular properties and designing ligands with high binding affinity to targets. However, designing an effective multi-task and self-supervised strategy remains a significant challenge for the pretraining framework. In this study, a multi-task self-supervised deep learning framework is proposed, MTSSMol, which utilizes ≈10 million unlabeled drug-like molecules for pretraining to identify potential inhibitors of fibroblast growth factor receptor 1 (FGFR1). During the pretraining of MTSSMol, molecular representations are learned through a graph neural networks (GNNs) encoder. A multi-task self-supervised pretraining strategy is proposed to fully capture the structural and chemical knowledge of molecules. Extensive computational tests on 27 datasets demonstrate that MTSSMol exhibits exceptional performance in predicting molecular properties across different domains. Moreover, MTSSMol's capability is validated to identify potential inhibitors of FGFR1 through molecular docking using RoseTTAFold All-Atom (RFAA) and molecular dynamics simulations. Overall, MTSSMol provides an effective algorithmic framework for enhancing molecular representation learning and identifying potential drug candidates, offering a valuable tool to accelerate drug discovery processes. All of the codes are freely available online at https:// github.com/zhaoqi106/MTSSMol. Show less
📄 PDF DOI: 10.1002/advs.202412987
FGFR1

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

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

Loss of C-Terminal Coiled-Coil Domains in SDCCAG8 Impairs Centriolar Satellites and Causes Defective Sperm Flagellum Biogenesis and Male Fertility.

Kecheng Li, Xiaoli Zhou, Wenna Liu +4 more · 2025 · Cells · MDPI · added 2026-04-24
Sperm flagellum defects are tightly associated with male infertility. Centriolar satellites are small multiprotein complexes that recruit satellite proteins to the centrosome and play an essential rol Show more
Sperm flagellum defects are tightly associated with male infertility. Centriolar satellites are small multiprotein complexes that recruit satellite proteins to the centrosome and play an essential role in sperm flagellum biogenesis, but the precise mechanisms underlying this role remain unclear. Show less
📄 PDF DOI: 10.3390/cells14151135
BBS4