👤 Yongqiang 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-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaowei Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, Yajuan Liu, Yaling Liu, Yalu Liu, Yan Liu, Yan-Li Liu, Yanan Liu, Yanchao Liu, Yanchen Liu, Yandong Liu, Yanfei Liu, Yanfen Liu, Yanfeng Liu, Yang Liu, Yange Liu, Yangfan Liu, Yangfan P Liu, Yangjun Liu, Yangkai Liu, Yangruiyu Liu, Yangyang Liu, Yanhong Liu, Yanhua Liu, Yanhui Liu, Yanjie Liu, Yanju Liu, Yanjun Liu, Yankuo Liu, Yanli Liu, Yanliang Liu, Yanling Liu, Yanman Liu, Yanmin Liu, Yanping Liu, Yanqing Liu, Yanqiu Liu, Yanquan Liu, Yanru Liu, Yansheng Liu, Yansong Liu, Yanting Liu, Yanwu Liu, Yanxiao Liu, Yanyan Liu, Yanyao Liu, Yanying Liu, Yanyun Liu, Yao Liu, Yao-Hui Liu, Yaobo Liu, Yaoquan Liu, Yaou Liu, Yaowen Liu, Yaoyao Liu, Yaozhong Liu, Yaping Liu, Yaqiong Liu, Yarong Liu, Yaru Liu, Yating Liu, Yaxin Liu, Ye Liu, Ye-Dan Liu, Yehai Liu, Yen-Chen Liu, Yen-Chun Liu, Yen-Nien Liu, Yeqing Liu, Yi Liu, Yi-Chang Liu, Yi-Chien Liu, Yi-Han Liu, Yi-Hung Liu, Yi-Jia Liu, Yi-Ling Liu, Yi-Meng Liu, Yi-Ming Liu, Yi-Yun Liu, Yi-Zhang Liu, YiRan Liu, Yibin Liu, Yibing Liu, Yicun Liu, Yidan Liu, Yidong Liu, Yifan Liu, Yifu Liu, Yihao Liu, Yiheng Liu, Yihui Liu, Yijing Liu, Yilei Liu, Yili Liu, Yilin Liu, Yimei Liu, Yiming Liu, Yin Liu, Yin-Ping Liu, Yinchu Liu, Yinfang Liu, Ying Liu, Ying Poi Liu, Yingchun Liu, Yinghua Liu, Yinghuan Liu, Yinghui Liu, Yingjun Liu, Yingli Liu, Yingwei Liu, Yingxia Liu, Yingyan Liu, Yingyi Liu, Yingying Liu, Yingzi Liu, Yinhe Liu, Yinhui Liu, Yining Liu, Yinjiang Liu, Yinping Liu, Yinuo Liu, Yiping Liu, Yiqing Liu, Yitian Liu, Yiting Liu, Yitong Liu, Yiwei Liu, Yiwen Liu, Yixiang Liu, Yixiao Liu, Yixuan Liu, Yiyang Liu, Yiyi Liu, Yiyuan Liu, Yiyun Liu, Yizhi Liu, Yizhuo Liu, Yong Liu, Yong Mei Liu, Yong-Chao Liu, Yong-Hong Liu, Yong-Jian Liu, Yong-Jun Liu, Yong-Tai Liu, Yong-da Liu, Yongchao Liu, Yonggang Liu, Yonggao Liu, Yonghong Liu, Yonghua Liu, Yongjian Liu, Yongjie Liu, Yongjun Liu, Yongli Liu, Yongmei Liu, Yongming Liu, Yongshuo Liu, Yongtai Liu, Yongtao Liu, Yongtong Liu, Yongxiao Liu, Yongyue Liu, You Liu, You-ping Liu, Youan Liu, Youbin Liu, Youdong Liu, Youhan Liu, Youlian Liu, Youwen Liu, Yu Liu, Yu Xuan Liu, Yu-Chen Liu, Yu-Ching Liu, Yu-Hui Liu, Yu-Li Liu, Yu-Lin Liu, Yu-Peng Liu, Yu-Wei Liu, Yu-Zhang Liu, YuHeng Liu, Yuan Liu, Yuan-Bo Liu, Yuan-Jie Liu, Yuan-Tao Liu, YuanHua Liu, Yuanchu Liu, Yuanfa Liu, Yuanhang Liu, Yuanhui Liu, Yuanjia Liu, Yuanjiao Liu, Yuanjun Liu, Yuanliang Liu, Yuantao Liu, Yuantong Liu, Yuanxiang Liu, Yuanxin Liu, Yuanxing Liu, Yuanying Liu, Yuanyuan Liu, Yubin Liu, Yuchen Liu, Yue Liu, Yuecheng Liu, Yuefang Liu, Yuehong Liu, Yueli Liu, Yueping Liu, Yuetong Liu, Yuexi Liu, Yuexin Liu, Yuexing Liu, Yueyang Liu, Yueyun Liu, Yufan Liu, Yufei Liu, Yufeng Liu, Yuhao Liu, Yuhe Liu, Yujia Liu, Yujiang Liu, Yujie Liu, Yujun Liu, Yulan Liu, Yuling Liu, Yulong Liu, Yumei Liu, Yumiao Liu, Yun Liu, Yun-Cai Liu, Yun-Qiang Liu, Yun-Ru Liu, Yun-Zi Liu, Yunfen Liu, Yunfeng Liu, Yuning Liu, Yunjie Liu, Yunlong Liu, Yunqi Liu, Yunqiang Liu, Yuntao Liu, Yunuan Liu, Yunuo Liu, Yunxia Liu, Yunyun Liu, Yuping Liu, Yupu Liu, Yuqi Liu, Yuqiang Liu, Yuqing Liu, Yurong Liu, Yuru Liu, Yusen Liu, Yutao Liu, Yutian Liu, Yuting Liu, Yutong Liu, Yuwei Liu, Yuxi Liu, Yuxia Liu, Yuxiang Liu, Yuxin Liu, Yuxuan Liu, Yuyan Liu, Yuyi Liu, Yuyu Liu, Yuyuan Liu, Yuzhen Liu, Yv-Xuan Liu, Z H Liu, Z Q Liu, Z Z Liu, Zaiqiang Liu, Zan Liu, Zaoqu Liu, Ze Liu, Zefeng Liu, Zekun Liu, Zeming Liu, Zengfu Liu, Zeyu Liu, Zezhou Liu, Zhangyu Liu, Zhangyuan Liu, Zhansheng Liu, Zhao Liu, Zhaoguo Liu, Zhaoli Liu, Zhaorui Liu, Zhaotian Liu, Zhaoxiang Liu, Zhaoxun Liu, Zhaoyang Liu, Zhe Liu, Zhekai Liu, Zheliang Liu, Zhen Liu, Zhen-Lin Liu, Zhendong Liu, Zhenfang Liu, Zhenfeng Liu, Zheng Liu, Zheng-Hong Liu, Zheng-Yu Liu, ZhengYi Liu, Zhengbing Liu, Zhengchuang Liu, Zhengdong Liu, Zhenghao Liu, Zhengkun Liu, Zhengtang Liu, Zhengting Liu, Zhenguo Liu, Zhengxia Liu, Zhengye Liu, Zhenhai Liu, Zhenhao Liu, Zhenhua Liu, Zhenjiang Liu, Zhenjiao Liu, Zhenjie Liu, Zhenkui Liu, Zhenlei Liu, Zhenmi Liu, Zhenming Liu, Zhenna Liu, Zhenqian Liu, Zhenqiu Liu, Zhenwei Liu, Zhenxing Liu, Zhenxiu Liu, Zhenzhen Liu, Zhenzhu Liu, Zhi Liu, Zhi Y Liu, Zhi-Fen Liu, Zhi-Guo Liu, Zhi-Jie Liu, Zhi-Kai Liu, Zhi-Ping Liu, Zhi-Ren Liu, Zhi-Wen Liu, Zhi-Ying Liu, Zhicheng Liu, Zhifang Liu, Zhigang Liu, Zhiguo Liu, Zhihan Liu, Zhihao Liu, Zhihong Liu, Zhihua Liu, Zhihui Liu, Zhijia Liu, Zhijie Liu, Zhikui Liu, Zhili Liu, Zhiming Liu, Zhipeng Liu, Zhiping Liu, Zhiqian Liu, Zhiqiang Liu, Zhiru Liu, Zhirui Liu, Zhishuo Liu, Zhitao Liu, Zhiteng Liu, Zhiwei Liu, Zhixiang Liu, Zhixue Liu, Zhiyan Liu, Zhiying Liu, Zhiyong Liu, Zhiyuan Liu, Zhong Liu, Zhong Wu Liu, Zhong-Hua Liu, Zhong-Min Liu, Zhong-Qiu Liu, Zhong-Wu Liu, Zhong-Ying Liu, Zhongchun Liu, Zhongguo Liu, Zhonghua Liu, Zhongjian Liu, Zhongjuan Liu, Zhongmin Liu, Zhongqi Liu, Zhongqiu Liu, Zhongwei Liu, Zhongyu Liu, Zhongyue Liu, Zhongzhong Liu, Zhou Liu, Zhou-di Liu, Zhu Liu, Zhuangjun Liu, Zhuanhua Liu, Zhuo Liu, Zhuoyuan Liu, Zi Hao Liu, Zi-Hao Liu, Zi-Lun Liu, Zi-Ye Liu, Zi-wen Liu, Zichuan Liu, Zihang Liu, Zihao Liu, Zihe Liu, Ziheng Liu, Zijia Liu, Zijian Liu, Zijing J Liu, Zimeng Liu, Ziqian Liu, Ziqin Liu, Ziteng Liu, Zitian Liu, Ziwei Liu, Zixi Liu, Zixuan Liu, Ziyang Liu, Ziying Liu, Ziyou Liu, Ziyuan Liu, Ziyue Liu, Zong-Chao Liu, Zong-Yuan Liu, Zonghua Liu, Zongjun Liu, Zongtao Liu, Zongxiang Liu, Zu-Guo Liu, Zuguo Liu, Zuohua Liu, Zuojin Liu, Zuolu Liu, Zuyi Liu, Zuyun Liu
articles

Derazantinib Inhibits the Planktonic Growth and Biofilm Formation of

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

Hypoxia Affects Mitochondrial Stress and Facilitates Tumor Metastasis of Colorectal Cancer Through Slug SUMOylation.

Jin-Bao Wang, Shi-Lin Ding, Xiao-Song Liu +3 more · 2025 · Current molecular medicine · Bentham Science · added 2026-04-24
Colorectal cancer (CRC) is a malignant tumor. Slug has been found to display a key role in diversified cancers, but its relevant regulatory mechanisms in CRC development are not fully explored. Hence, Show more
Colorectal cancer (CRC) is a malignant tumor. Slug has been found to display a key role in diversified cancers, but its relevant regulatory mechanisms in CRC development are not fully explored. Hence, exploring the function and regulatory mechanisms of Slug is critical for the treatment of CRC. Protein expressions of Slug, N-cadherin, E-cadherin, Snail, HIF-1α, SUMO- 1, Drp1, Opa1, Mfn1/2, PGC-1α, NRF1, and TFAM were measured through western blot. To evaluate the protein expression of Slug and SUMO-1, an immunofluorescence assay was used. Cell migration ability was tested through transwell assay. The SUMOylation of Slug was examined through CO-IP assay. Slug displayed higher expression and facilitated tumor metastasis in CRC. In addition, hypoxia treatment was discovered to upregulate HIF-1α, Slug, and SUMO-1 levels, as well as induce Slug SUMOylation. Slug SUMOylation markedly affected mitochondrial biosynthesis, fusion, and mitogen-related protein expression levels to trigger mitochondrial stress. Additionally, the induced mitochondrial stress by hypoxia could be rescued by Slug inhibition and TAK-981 treatment. Our study expounded that hypoxia affects mitochondrial stress and facilitates tumor metastasis of CRC through Slug SUMOylation. Show less
no PDF DOI: 10.2174/0115665240271525231112121008
SNAI1

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

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

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

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

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

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

RNA-seq shows Angiopoietin-like 4 promotes hepatocellular carcinoma progression by inducing M2 polarization of tumor-associated macrophages.

Guanghua Cui, Wei Liu, Xiaoke Sun +8 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
Hepatocellular carcinoma (HCC) represents a particularly aggressive form of cancer, characterized by its rapid progression and a complex interplay with the surrounding immune cellular environment. The Show more
Hepatocellular carcinoma (HCC) represents a particularly aggressive form of cancer, characterized by its rapid progression and a complex interplay with the surrounding immune cellular environment. The primary objective of this study was to comprehensively investigate the role of ANGPTL4 in the context of HCC, utilizing RNA sequencing (RNA-seq) techniques to explore its impact on the M2 polarization of tumor-associated macrophages (TAM) and to uncover potential mechanisms driving HCC progression. To achieve this, we performed a transcriptome analysis of HCC cell lines, alongside cells obtained after co-culturing these lines with macrophages. By comparing gene expression profiles between the experimental groups exposed to ANGPTL4 and control groups, we aimed to identify specific molecular pathways associated with ANGPTL4's function. In addition to gene expression analysis, we employed flow cytometry to assess the polarization status of TAM. Furthermore, we utilized immunohistochemistry to evaluate the distribution of macrophages within HCC tissues and to quantify the expression levels of M2 macrophage markers. The results derived from RNA-seq analysis were particularly revealing; treatment with ANGPTL4 led to a significant upregulation of genes linked to M2 polarization, notably including CD206 and Arg1. In subsequent experimental observations, it became evident that ANGPTL4 not only facilitated the M2 polarization of macrophages but also enhanced the proliferation and migratory capacity of HCC cells through the upregulation of these same cytokines. Show less
no PDF DOI: 10.1016/j.ijbiomac.2024.138523
ANGPTL4

Heme and lithospermic acid synergistically inhibit aggregation of human islet amyloid polypeptide: A novel hIAPP inhibitor for the potential therapy of type 2 diabetes.

Bin Xiao, Junhao Xiao, Xiaoying Xiao +5 more · 2025 · Journal of inorganic biochemistry · Elsevier · added 2026-04-24
Amyloid deposition of human islet amyloid polypeptide (hIAPP) is closely linked to the pathogenesis and progression of type 2 diabetes mellitus (T2DM). Developing effective inhibitors to suppress hIAP Show more
Amyloid deposition of human islet amyloid polypeptide (hIAPP) is closely linked to the pathogenesis and progression of type 2 diabetes mellitus (T2DM). Developing effective inhibitors to suppress hIAPP aggregation holds significant therapeutic potential for the prevention and treatment of T2DM. Recent researches indicate that both heme and lithospermic acid (LPA) can inhibit hIAPP aggregation. However, heme is prone to induce protein damage under oxidative stress, while LPA exhibits limited inhibitory efficacy despite its antioxidant properties. To overcome these limitations, we aimed to develop a dual-component inhibitor comprising heme and LPA. thioflavin T (ThT) fluorescence, transmission electron microscopy (TEM), circular dichroism (CD) and gel electrophoresis were combined to observe the inhibitory efficacy of heme-LPA co-formulation on hIAPP aggregation. The results demonstrate that LPA and heme can synergistically inhibit hIAPP aggregation. The inhibitory effect of heme-LPA co-formulation on hIAPP aggregation is significantly stronger than that of either component alone. The heme-LPA not only prevents the complete conversion of hIAPP into β-sheet fibrillar structures but also maintains its active monomeric conformation for extended periods. Furthermore, peroxidase activity assays revealed that the presence of LPA significantly reduces the peroxidase activity of heme in a concentration-dependent manner and attenuates peptide nitration damage under H₂O₂-NO₂ Show less
no PDF DOI: 10.1016/j.jinorgbio.2025.113087
LPA

Clinical Relationship Between Serum ApoB, HER2, and Myocardial Ischemia Risk in Breast Cancer Patients.

Yeyan Lei, Dongmei Li, Shuang Bai +3 more · 2025 · Cancer reports (Hoboken, N.J.) · Wiley · added 2026-04-24
The risk factors and clinical prediction of cardiovascular comorbidities in patients with breast cancer have not been fully clarified. This retrospective case-control study was designed to investigate Show more
The risk factors and clinical prediction of cardiovascular comorbidities in patients with breast cancer have not been fully clarified. This retrospective case-control study was designed to investigate the factors affecting myocardial ischemia occurrence in breast cancer patients. A total of 194 cases (144 breast cancer and 50 benign breast tumor patients) were included. Univariate and multivariable Cox regression found that ApoB, age, and HER2 were significant factors responsible for the myocardial ischemia occurrence in breast cancer patients. By comparing the significance of ApoB in breast cancer patients versus benign breast tumor patients, it was observed that ApoB and HER2 were crucial predictors of myocardial ischemia in breast cancer patients compared to those with benign breast tumors. These factors were utilized to construct the clinical prediction model, achieving a combined area under the curve (AUC) of 0.583. The decision curve analysis (DCA) indicated that the model-predicted population, within a threshold ranging from 0.35 to 0.70, would experience a therapeutically clinical net benefit. Kaplan-Meier plot indicated that ApoB We demonstrated that ApoB and HER2 were potential factors in predicting the myocardial ischemia occurrence in breast cancer patients. This study will help provide clinical evidence for the early prediction of cardiovascular comorbidities in breast cancer patients. Show less
📄 PDF DOI: 10.1002/cnr2.70075
APOB

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

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

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

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

Targeting VSMCs to suppress macrophage-like phenotype switching that restrains atherogenesis by immunosuppressive oligodeoxynucleotide (A151) functionalized selenium nanoparticles.

Jingru Wang, Bo Yao, Yutian Zhang +13 more · 2025 · Journal of nanobiotechnology · BioMed Central · added 2026-04-24
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strat Show more
Macrophage-like phenotype switching of vascular smooth muscle cells (VSMCs) is a crucial mechanism driving atherogenesis. Inhibition of a phenotype switch to macrophage-like cells is a promising strategy to prevent atherosclerosis (AS), and targeted nanotherapeutics represent one approach for implementing this strategy. To this end, we designed immunosuppressive oligodeoxynucleotide A151 functionalized selenium nanoparticles with a spearhead LacNAc (LN-A151-SeNPs) that target macrophage-like VSMCs. Nano characterization showed that the uniformity and stability of nanoparticles were optimized by modification with LacNAc and A151, resulting in an average diameter of 88.90 ± 1.45 nm, Zeta potentials of -21.1 ± 1.5 mV, a A151:Se molar ratio of 1:60 and mass ratio of 1.68:1. The effects of LN-A151-SeNPs on inhibiting VSMCs phenotype switching and attenuation of AS were investigated using [Image: see text] The online version contains supplementary material available at 10.1186/s12951-025-03925-7. Show less
📄 PDF DOI: 10.1186/s12951-025-03925-7
APOE

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

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

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

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

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

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

[Calcified chondroid mesenchymal neoplasm of the hand: report of a case].

H X Yang, L H Gong, J Liu +2 more · 2025 · Zhonghua bing li xue za zhi = Chinese journal of pathology · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112151-20241128-00794
FGFR1

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

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

Case Report: Quantitative multimodal imaging for surgical planning in isolated pulmonary artery sling.

Tianhe Ye, Cong Liu · 2025 · Frontiers in pediatrics · Frontiers · added 2026-04-24
Pulmonary artery sling (PAS) is a rare congenital vascular anomaly in which the left pulmonary artery (LPA) originates from the right pulmonary artery (RPA), forming a ring around the tracheobronchial Show more
Pulmonary artery sling (PAS) is a rare congenital vascular anomaly in which the left pulmonary artery (LPA) originates from the right pulmonary artery (RPA), forming a ring around the tracheobronchial tree. Due to non-specific respiratory symptoms, it is frequently misdiagnosed, leading to significant delays in diagnosis. This report emphasizes the crucial role of quantitative multimodal imaging in establishing a definitive diagnosis, stratifying risk, and guiding optimal surgical planning. A 4-year-and-7-month-old boy presented with a 4-year history of recurrent cough and wheezing that was refractory to standard medical therapy. Echocardiography revealed a dilated main pulmonary artery (MPA) measuring 1.9 cm ( This case of isolated PAS underscores the indispensable role of a multimodal imaging strategy. While echocardiography can provide initial clues, quantitative CTA is paramount for definitive anatomical classification, precise stenosis quantification, and comprehensive preoperative planning. Early consideration of PAS in children presenting with refractory respiratory symptoms, coupled with advanced imaging, can prevent misdiagnosis and optimize outcomes. Show less
📄 PDF DOI: 10.3389/fped.2025.1689213
LPA

Genetic Crosstalk Between Type 1 Diabetes and Sjögren's Syndrome: A Systematic Exploration of Risk Genes and Common Pathways.

Aamir Fahira, Kai Zhuang, Xuemin Jian +5 more · 2025 · Journal of cellular and molecular medicine · Blackwell Publishing · added 2026-04-24
Sjögren's Syndrome (SS) and Type 1 Diabetes (T1D) are autoimmune disorders that can co-occur in patients, leading to complex clinical presentations. Despite observational evidence of their co-occurren Show more
Sjögren's Syndrome (SS) and Type 1 Diabetes (T1D) are autoimmune disorders that can co-occur in patients, leading to complex clinical presentations. Despite observational evidence of their co-occurrence, the underlying genetic mechanisms remain poorly understood. To investigate the shared genetic factors and pathways between SS and T1D, we conducted a comprehensive analysis using multiomic approaches. Conditional and conjunctional false discovery rate analyses were performed to identify genetic polygenicity and overlap between the two diseases. Functional annotation and pathway analysis identified SNPs with regulatory potential. Furthermore, Mendelian Randomization (MR) analyses were employed to investigate causal associations between gene expression and disease risk. Single-cell differential gene expression analysis was also employed to validate the associations of risk genes with T1D and SS. Our analysis identified 36 shared loci, revealing common genetic enrichment between SS and T1D. Functional annotation and pathway analysis revealed 52 credible genes involved in cysteine-related processes, apoptotic signalling and immune responses. MR analyses revealed that AC007283.5 was positively linked with both SS and T1D, while PLEKHM1 and CRHR1-T1 were negatively associated. Additionally, CERS2 was positively associated with SS, DEF6 was positively associated with T1D, and KANSL1-AS1 was negatively associated with T1D, indicating the presence of complex regulatory mechanisms. Moreover, Single-cell differential gene expression analysis confirmed the dysregulation of risk genes in SS and T1D. This study identified shared genetic factors and pathways underlying SS and T1D, highlighting cysteine-related processes and apoptotic signalling. The findings underscore the complex interplay of autoimmunity and the need for targeted treatments addressing their common mechanisms. Show less
📄 PDF DOI: 10.1111/jcmm.70930
KANSL1

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

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

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

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

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

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

3D printing combined with thermally induced phase separation for engineering hierarchical osteogenic PLA scaffolds.

Xinyi Yun, Ziyue Li, Zi Yan +13 more · 2025 · Materials today. Bio · Elsevier · added 2026-04-24
Accelerated population aging and rising incidence of bone defects have intensified the need for advanced bone regeneration strategies. While tissue-engineered scaffolds fabricated via 3D printing offe Show more
Accelerated population aging and rising incidence of bone defects have intensified the need for advanced bone regeneration strategies. While tissue-engineered scaffolds fabricated via 3D printing offer promising alternatives to conventional grafts, most techniques fail to replicate the multi-scale fibrous architecture of native bone extracellular matrix, limiting their biofunctionality. To address this, we developed a hybrid manufacturing strategy integrating low-temperature thermally induced phase separation with extrusion-based 3D printing of polylactic acid (PLA) scaffolds. By optimizing solvent ratios (THF: DMF = 3:1) and freezing temperatures (-196 °C-4 °C), we produced scaffolds with tunable micro-nano fibrous surfaces and macroporous structures. Key findings revealed that scaffolds processed at -196 °C (PLA-196) exhibited the highest porosity (pore size: 6.01 ± 2.06 μm), superior hydrophilicity, and enhanced compressive modulus. These scaffolds significantly promoted BMSC adhesion, proliferation, and osteogenic differentiation via activation of Show less
📄 PDF DOI: 10.1016/j.mtbio.2025.102621
MACF1

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

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

Repeated Intrathecal Stem Cells Optimize Neuroplasticity and Motor Function in Moderate-to-Severe Cerebral Palsy of Rats.

Yi Xu, Ting-Ting Peng, Shiya Huang +10 more · 2025 · Stem cells international · added 2026-04-24
Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) ameliorate motor deficits in cerebral palsy (CP), but the effect of injection frequency remains unclear. Moreover, most studies have focu Show more
Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) ameliorate motor deficits in cerebral palsy (CP), but the effect of injection frequency remains unclear. Moreover, most studies have focused on mild CP models (unilateral carotid artery occlusion [UCAO] model). This study explored the effect and mechanism of hUC-MSCs in a rat model of moderate-to-severe CP (bilateral carotid artery occlusion [BCAO] model). On postnatal Day 4 (P4), Wistar rat pups underwent BCAO induction. Subsequently, they received either a single intrathecal injection of hUC-MSCs on P21 or repeated injections on P21, P28, P35, and P42. Motor performance was assessed using the rotarod and front-limb suspension tests, while neuronal regeneration and inflammation were evaluated via biomarkers including neuronal nuclear antigen (NeuN), ionized calcium-binding adapter molecule-1 (Iba-1), glial fibrillary acidic protein (GFAP), myelin basic protein (MBP), and brain-derived neurotrophic factor (BDNF). P18 model screening confirmed that the BCAO model resulted in more severe brain damage and motor impairment than the UCAO model. After injection of lentivirally transfected hUC-MSCs, it was found that hUC-MSCs could nest in the damaged area and survive for at least 3 days. Administration of hUC-MSCs following BCAO modeling led to notable improvements in both behavioral performance and histological outcomes. Furthermore, repeated injections offered greater therapeutic benefits compared to single injection. It indicated that the efficacy of repeated injections of hUC-MSCs in the treatment of moderate-to-severe CP was superior to that of single injection. Its mechanism was related to the improvement of damaged myelin structure, reduced immunoinflammatory responses, and increased neurotrophic support. Show less
📄 PDF DOI: 10.1155/sci/4337435
BDNF

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

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

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

Oncometabolite D-2HG drives tumor metastasis and protumoral macrophage polarization by targeting FTO/m

Siyue Zhang, Ning Zhang, Tong Wan +10 more · 2025 · Journal of experimental & clinical cancer research : CR · BioMed Central · added 2026-04-24
D-2-hydroxyglutarate (D-2HG), an oncometabolite derived from the tricarboxylic acid cycle. Previous studies have reported the diverse effects of D-2HG in pathophysiological processes, yet its role in Show more
D-2-hydroxyglutarate (D-2HG), an oncometabolite derived from the tricarboxylic acid cycle. Previous studies have reported the diverse effects of D-2HG in pathophysiological processes, yet its role in breast cancer remains largely unexplored. We applied an advanced biosensor approach to detect the D-2HG levels in breast cancer samples. We then investigated the biological functions of D-2HG through multiple in vitro and in vivo assays. A joint MeRIP-seq and RNA-seq strategy was used to identify the target genes regulated by D-2HG-mediated N6-methyladenosine (m We found that D-2HG accumulated in triple-negative breast cancer (TNBC), exerting oncogenic effects both in vitro and in vivo by promoting TNBC cell growth and metastasis. Mechanistically, D-2HG enhanced global m Our study unveils a previously unrecognized role for D-2HG-mediated RNA modification in TNBC progression and targeting the D-2HG/FTO/m Show less
📄 PDF DOI: 10.1186/s13046-025-03282-1
ANGPTL4

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

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

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

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