👤 Annuo 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, 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, 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

miR-375-3p/STX6 Exacerbates Atherosclerosis by Promoting Endothelial Cell Senescence via Activation of TGF-Beta Signals.

Ying Zhu, Zhirui Liu, Yiqi Wan +9 more · 2026 · Aging cell · Blackwell Publishing · added 2026-04-24
Atherosclerosis, a key pathological basis of cardio-cerebrovascular diseases, is closely associated with aging and endothelial cell senescence. The role of microRNAs (miRNAs) in regulating endothelial Show more
Atherosclerosis, a key pathological basis of cardio-cerebrovascular diseases, is closely associated with aging and endothelial cell senescence. The role of microRNAs (miRNAs) in regulating endothelial cell senescence and atherosclerosis remains incompletely understood. In this study, we discovered that miR-375-3p expression was significantly elevated in the serum of both aged and atherosclerotic mice. Overexpression of miR-375-3p induced endothelial cell senescence, evidenced by increased senescence-associated β-galactosidase (SA-β-gal) staining, upregulation of p15, IL6, and IL8, and inhibited cell colony formation. In vivo inhibition of miR-375-3p in ApoE Show less
📄 PDF DOI: 10.1111/acel.70326
APOE

Dysfunctional TRIM31 of POMC Neurons Provokes Hypothalamic Injury and Peripheral Metabolic Disorder under Long-Term Fine Particulate Matter Exposure.

Chenxu Ge, Jiamao Lin, Changsheng Yang +19 more · 2026 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Particulate matter ≤2.5 µm (PM
📄 PDF DOI: 10.1002/advs.202508458
MC4R

Sinomenine inhibits oxidative stress to attenuate Alzheimer's disease pathology via α7 nicotinic acetylcholine receptor.

Haojie Ni, Yiyi Xiong, Min Liu +14 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
The pathological mechanism of Alzheimer's disease (AD) is complex. The binding of Aβ to α7 nicotinic acetylcholine receptor (α7nAChR) contributes to neuronal damage. Sinomenine (SIN) is an alkaloid ex Show more
The pathological mechanism of Alzheimer's disease (AD) is complex. The binding of Aβ to α7 nicotinic acetylcholine receptor (α7nAChR) contributes to neuronal damage. Sinomenine (SIN) is an alkaloid extracted from the traditional Chinese medicine Qingfengteng (Sinomenium acutum). The anti-inflammatory, antioxidant, and immunomodulatory effects of SIN were confirmed to be closely associated with the α7nAChR. This study aimed to investigate whether α7nAChR serves as a pharmacological target of SIN against AD, and to evaluate the neuroprotective effects of SIN both in vivo and in vitro, focusing on the α7nAChR/Nrf2/Keap1 signaling pathway. In this study, the effects of SIN in both APP/PS1 transgenic mice and SH-SY5Y cells subjected to Aβ1-42-induced injury were assessed. The selective antagonist α-bungarotoxin ‌(α-BTX), the agonist nicotine (Nic) of α7nAChR, and α7nAChR siRNA were employed. The cognitive function, Aβ deposition, synaptic plasticity markers, the tau protein phosphorylation, mitochondrial membrane potential, oxidative stress and the α7nAChR/Nrf2/Keap1 signaling pathway were analyzed in vivo and/or in vitro. SIN significantly enhanced learning and memory abilities in APP/PS1 mice, reduced Aβ plaque deposition and synaptic dysfunction, and inhibited hyperphosphorylation of tau protein and oxidative stress in the brain. In Aβ1-42-induced neuronal injury model, SIN alleviated apoptosis, increased BDNF and ACh levels, inhibited mitochondrial damage, stabilized calcium homeostasis, and suppressed oxidative stress. Meanwhile, SIN disrupted Nrf2-Keap1 binding to promote the Nrf2/HO-1 signaling pathway. Nevertheless, SIN effects above were inhibited by α-BTX. The knockdown of α7nAChR in vitro significantly promoted Nrf2/HO-1 pathway and BDNF expression. SIN exerts neuroprotective effect in APP/PS1 transgenic mice and Aβ1-42-induced neuronal injury by inhibiting oxidative stress via α7nAChR/Nrf2/Keap1 pathway. This study provides evidence for α7nAChR as a new target and the clinical application potential of SIN in AD treatment. Show less
no PDF DOI: 10.1016/j.phymed.2026.157779
BDNF alzheimer's disease antioxidant inflammation neuroprotection oxidative stress pathology sinomenine

SAMHD1 drives immunosuppression in non-small cell lung cancer by promoting macrophage infiltration and restricting oncolytic adenovirus replication.

Shichuan Hu, Jian Xu, Zhiwu Wang +7 more · 2026 · Journal for immunotherapy of cancer · added 2026-04-24
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and the leading cause of cancer-related deaths. Immune checkpoint inhibitors (ICIs) of programmed death-1 (PD-1)/programmed de Show more
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and the leading cause of cancer-related deaths. Immune checkpoint inhibitors (ICIs) of programmed death-1 (PD-1)/programmed death ligand-1 signaling induce tumor regression in some patients with NSCLC, but most patients with NSCLC exhibit resistance to ICIs therapy. NSCLC shapes the potent tumor immunosuppressive microenvironment (TIME) that underlies tumor immune tolerance and acquired resistance. Therefore, elucidating the cellular and molecular mechanisms by which NSCLC establishes and sustains the TIME is essential for developing novel strategies to overcome immune resistance and enhance the clinical benefit of ICIs. The correlation between sterile alpha motif domain and histidine-aspartate domain-containing protein 1 (SAMHD1) expression and ICIs was analyzed via immunohistochemistry. Cell migration assay was performed to assess the effect of SAMHD1 on macrophage recruitment. Multicolor flow cytometry was performed to analyze the effect of SAMHD1 knockdown on the tumor microenvironment. SAMHD1 regulation of the dual specificity phosphatase 6-extracellular regulated protein kinases 1/2 (DUSP6-ERK1/2) pathway was verified by RNA sequencing and western blotting. Here, we identify the SAMHD1 as a potential therapeutic target and a major determinant of poor response to ICIs in patients with NSCLC. Tumors with high SAMHD1 expression show resistance to anti-PD-1 antibody (αPD-1) treatment, whereas tumors with low SAMHD1 expression are highly sensitive. SAMHD1-dependent resistance to αPD-1 is characterized by increased tumor-associated macrophages (TAMs) infiltration and reduced CD8+T cell numbers. Mechanistically, SAMHD1 regulates the expression of macrophage-associated chemokines by influencing the activation of the DUSP6-ERK1/2 pathway, which contributes to TAMs aggregation within NSCLC tumors to shape an immunosuppressive microenvironment. The HIV accessory protein viral protein-x (VPX) specifically degrades SAMHD1 to promote HIV replication. Similarly, the vpx-engineered oncolytic adenovirus (oAd-vpx) targets SAMDH1 degradation to enhance oncolytic adenovirus replication and weaken the hostile immune microenvironment shaped by TAMs, thereby triggering a CD8+T-cell-dependent antitumor immune response. The combination of oAd-vpx and αPD-1 inhibits tumor growth and enhances sensitivity to ICIs in both mouse and human NSCLC. This research identifies a key mechanism of SAMHD1-driven immunosuppression and highlights its important role in oncolytic adenovirus therapy. This study provides a theoretical basis for targeting SAMHD1 as a drug therapy strategy in patients with NSCLC. Show less
📄 PDF DOI: 10.1136/jitc-2025-013550
DUSP6

Gut-Brain Metabolic Remodeling Mediates the Neuroprotective Effects of Combined Shrimp and Corn Peptides in Scopolamine-Induced Cognitive Impairment.

Xiaomeng Xu, Ruowen Liu, Enhui Ma +2 more · 2026 · Foods (Basel, Switzerland) · MDPI · added 2026-04-24
(1) Background: Bioactive peptides from marine and plant sources show neuroprotective potential, yet how their combination ratios affect memory regulation via the gut-brain axis remains unclear. This Show more
(1) Background: Bioactive peptides from marine and plant sources show neuroprotective potential, yet how their combination ratios affect memory regulation via the gut-brain axis remains unclear. This study investigated the effects of different ratios of marine peptide QMDDQ (Glutamine-Methionine-Aspartate-Aspartate-Glutamine) and plant peptide AGLPM (Alanine-Glycine-Leucine-Proline-Methionine) on scopolamine-induced memory impairment in mice. (2) Methods: Cognitive function was assessed using the Morris water maze and novel object recognition tests. Nissl staining, microplate-based assays for acetylcholine (ACh) content and acetylcholinesterase (AChE) activity, Western blotting for neurotrophic factors, LC-MS/MS-based intestinal peptide profiling, and HPLC-based brain amino acid analysis were performed. (3) Results: The 1:1 ratio most effectively restored learning and memory, regulated hippocampal cholinergic function, mitigated neuronal damage, and elevated BDNF, NGF, and NTF-3 expression. In the gut, peptides were hydrolyzed into glutamate- and proline-rich fragments, which influenced brain amino acid balance by elevating glutamate and proline levels while reducing NH Show less
📄 PDF DOI: 10.3390/foods15050827
BDNF

4-MEC potentially triggers CAV1 via the BDNF-TrkB signaling pathway.

Wangping Zhang, Fangqi Cao, Ming Li +4 more · 2026 · Molecular and cellular neurosciences · Elsevier · added 2026-04-24
4-Methylethcathinone (4-MEC), a synthetic cathinone with psychostimulant properties, is increasingly abused as a "designer drug". However, its molecular mechanisms, particularly those related to neuro Show more
4-Methylethcathinone (4-MEC), a synthetic cathinone with psychostimulant properties, is increasingly abused as a "designer drug". However, its molecular mechanisms, particularly those related to neuroplasticity regulation, remain poorly understood. Caveolin-1 (CAV1) is a scaffolding protein of membrane lipid rafts and has been confirmed to organize multiple synaptic signaling proteins to regulate synaptic signaling and neuroplasticity. Herein, we investigated whether CAV1 modulates 4-MEC-induced alterations in the BDNF-TrkB signal pathway and neuroplasticity markers in human SH-SY5Y neuroblastoma cells and a mouse-conditioned place preference (CPP) model. Using qRT-PCR and Western blotting, we demonstrated that 4-MEC significantly upregulated CAV1 mRNA and protein levels, as well as components of the BDNF-TrkB signaling pathway and neuroplasticity markers (GAP43, MAP2, SYP). siRNA-mediated CAV1 knockdown abolished 4-MEC-induced increases in these proteins and neuroplasticity-related mRNAs, whereas CAV1 overexpression potentiated these effects. Additionally, molecular docking predicted potential binding sites between 4-MEC and CAV1. Meanwhile, protein docking also predicted the potential binding sites between CAV1 and TrkB, and co-immunoprecipitation confirmed their physical interactions in SH-SY5Y cells. In the mice exposed to 4-MEC in the CPP paradigm, we observed similar upregulation of CAV1, BDNF-TrkB signaling pathway components, and neuroplasticity markers in the brain. These findings identify CAV1 as a potential critical mediator of 4-MEC's neuroadaptive effects through the BDNF-TrkB signal pathway to regulate neuroplasticity. It suggests a possible novel molecular target for synthetic cathinone toxicity, with potential implications for forensic research. Show less
no PDF DOI: 10.1016/j.mcn.2026.104074
BDNF bdnf cav1 lipid rafts neuroplasticity psychostimulant signaling pathway synaptic signaling

Phytochemical profiling and molecular interactions of Parishins a and C as potent AChE inhibitors from red Gastrodia elata.

Ming Chen, Yuchi Zhang, Jingying Xu +7 more · 2026 · Biophysical chemistry · Elsevier · added 2026-04-24
Current in vitro enzyme inhibition assays often involve subjective data analysis based on the researcher's experience. In this study, we developed a multi-dimensional quantitative integration platform Show more
Current in vitro enzyme inhibition assays often involve subjective data analysis based on the researcher's experience. In this study, we developed a multi-dimensional quantitative integration platform (MDQIP) that uses a model to objectively calculate and rank compound activities, addressing the limitations of traditional "experience-driven" evaluations, accelerates the screening and evaluation of potential AChE inhibitors from Red Gastrodia elata, offering a more efficient approach to drug discovery. Ultrafiltration-LC screening identified parishin A as having the most stable binding, with binding degree and recovery rates of 98.85% and 99.39%, respectively. Molecular docking revealed that parishins A and C were the strongest AChE inhibitors, exhibiting stable binding through hydrogen bonds, π-alkyl, and π-π interactions. Molecular dynamics simulations confirmed the stability of these compounds, with binding energies of -82.65 ± 4.24 and - 80.69 ± 4.19 kcal/mol. Enzyme kinetics showed that parishins A and C are mixed-type inhibitors, with IC Show less
no PDF DOI: 10.1016/j.bpc.2026.107617
BACE1

Effects of GABAAR modulators CL218872 and MRK-016 on neural repair and synaptic plasticity in mice with Intracerebral hemorrhage.

Tingting Chen, Hongxia He, Fei Huang +3 more · 2026 · PloS one · PLOS · added 2026-04-24
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor Show more
Intracerebral hemorrhage (ICH) is a devastating condition characterized by rapid onset, high rates of disability and mortality, and prolonged recovery. Dysregulated γ-aminobutyric acid type A receptor (GABAAR) signaling contributes to ICH-induced neurotoxicity, presenting a promising therapeutic target. To assess the neurorestorative effects of the GABAAR α1-selective partial positive allosteric modulator (PAM) CL218872 and the α5-selective negative allosteric modulator (NAM) MRK-016 on synaptic plasticity and neural repair following ICH. An ICH mouse model was constructed using collagenase IV, and ICH mice were administered the GABAAR modulators CL218872 or MRK-016. Differences in inflammation and neurological deficit score were compared between different groups of mice. Morphologic and functional changes in mouse neuronal cells were next determined by Nissl and Golgi-Cox staining. Synaptic structural changes in ICH mice were visualized by transmission electron microscopy, and changes in synaptic plasticity-related molecules were quantified to assess the effects of GABAAR modulators on synapses in ICH mice. Treatment with CL218872 resulted in a reduction in hemorrhage and improved neurobehavioral outcomes in ICH mice. Additionally, CL218872 mitigated inflammation by downregulating phospho-p65, IL-6 and TNF-α expression. Histological analysis revealed an increase in neuronal density, preservation of cell morphology, and enhanced synaptic connectivity following CL218872 treatment. Furthermore, synaptic structure was restored, and there was an upregulation of brain-derived neurotrophic factor (BDNF), growth-associated protein-43 (GAP-43), postsynaptic density protein 95 (PSD-95), and synaptophysin in ICH mice. However, treatment with MRK-016 yielded the opposite result. The GABAAR α1-selective PAM CL218872 exerts neuroprotective and neurorestorative effects in ICH, suggesting its therapeutic potential for ICH management. Show less
📄 PDF DOI: 10.1371/journal.pone.0345025
BDNF

Identification of Blood Pressure-Associated Metabolites by Integrating Metabolomic and Genetic Analysis.

Yuanjiao Liu, Chunxiao Cheng, Xiong-Fei Pan +3 more · 2026 · MedComm · Wiley · added 2026-04-24
This study aimed to identify blood pressure-associated metabolites and explore their underlying pathways using multiomics data from 1188 Chinese participants. Serum metabolite levels were profiled usi Show more
This study aimed to identify blood pressure-associated metabolites and explore their underlying pathways using multiomics data from 1188 Chinese participants. Serum metabolite levels were profiled using untargeted and widely targeted metabolomic technologies. The associations of metabolites as well as ratios with blood pressure were assessed using generalized linear models (GLM). Targeted metabolomics was used to replicate a subset of metabolites. Genome-wide association studies (GWAS) were performed on all metabolites identified. Potential causality was examined using two-sample Mendelian randomization (MR) analyses, with partial validation against GWAS results from an independent cohort. This study identified 10 blood pressure-associated metabolites supported by GLM and MR analyses. Cortisol demonstrated the strongest association with blood pressure, with l-glutamic acid and its ratios identified as key drivers. Multiomics integration revealed that a genetic variant near the omega-3 metabolism genes ( Show less
📄 PDF DOI: 10.1002/mco2.70718
FADS1

Integrated transcriptomic, proteomic, and metabolomic analyses reveal molecular mechanisms underlying clutch length differences in goose ovaries.

Hechuan Wang, Yunuo Liu, Ke Jiang +6 more · 2026 · Poultry science · Elsevier · added 2026-04-24
Clutch length is a key determinant of reproductive efficiency in geese and strongly positively correlates with egg production. We recorded daily egg production in 280 individually housed Zi geese, cal Show more
Clutch length is a key determinant of reproductive efficiency in geese and strongly positively correlates with egg production. We recorded daily egg production in 280 individually housed Zi geese, calculated clutch-related indices, and selected 12 geese to form long-clutch (LC) and short-clutch (SC) groups for ovarian transcriptomic, proteomic, and metabolomic analyses. The results showed that egg number, large clutch length, large clutch number, average clutch length, and average clutch number were significantly higher in LC than in SC groups (P < 0.0001). Transcriptomic analysis identified 885 differentially expressed genes enriched in oocyte development and ovarian steroidogenesis, with APOB, PLA2G4C, MMP2, MMP9, and NOBOX as key genes; proteomic analysis identified 437 differentially abundant proteins enriched in arachidonic acid metabolism and mitophagy, with CXCL12, RARB, and MAD2L1 as key proteins; and metabolomic analysis identified 35 differentially abundant metabolites enriched in glycolysis/gluconeogenesis, with lactic acid, guanidinoacetic acid, and 3-hydroxybutyrylcarnitine as key metabolites. Integration of multi-omics datasets highlighted a lactate-associated cross-omics signature supported by YWHAZ at the protein level and by the lactate transporter SLC16A3. Collectively, these findings deepen our understanding of the molecular basis underlying clutch-length variation in goose ovaries and highlight candidate genes, proteins, and metabolites for future functional validation. Show less
📄 PDF DOI: 10.1016/j.psj.2026.106731
APOB

Paeonol alleviates atherosclerosis by inhibiting CD8

Yulong Yang, Ting Zhang, Lishun Dong +4 more · 2026 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Moutan Cortex, a traditional Chinese medicine, has been used to treat cardiovascular diseases. Paeonol (Pae), a key bioactive compound, is responsible for its anti-atherosclerotic effects. Although CD Show more
Moutan Cortex, a traditional Chinese medicine, has been used to treat cardiovascular diseases. Paeonol (Pae), a key bioactive compound, is responsible for its anti-atherosclerotic effects. Although CD8 We investigated whether Pae inhibits atherosclerosis by targeting the spleen tyrosine kinase (SYK)/nuclear factor of activated T-cells c1 (NFATc1) pathway, thereby reducing CD8 High-fat diet-fed apolipoprotein E-deficient (ApoE Pae attenuated plaque formation and T-cell activation in ApoE SYK in CD8 Show less
no PDF DOI: 10.1016/j.jep.2026.121462
APOE

GSTM2 as the molecular linking of depression-driven colon cancer progression and chemoresistance: Reversal by Sinisan.

Na Li, Keying Chen, Bin Nie +14 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Depression has emerged as a concerning factor in colon cancer progression and treatment, yet its underlying mechanisms and therapeutic targets remain poorly defined. This study aimed to elucidate how Show more
Depression has emerged as a concerning factor in colon cancer progression and treatment, yet its underlying mechanisms and therapeutic targets remain poorly defined. This study aimed to elucidate how depression affects colon cancer progression and chemotherapeutic response, and to explore potential molecular targets and therapeutic interventions involving the traditional Chinese medicine formula Sinisan (SNS) and its bioactive component Quercetin. A mouse model combining depression and colon cancer was established to evaluate behavioral alterations, tumor progression, and pathological features. RNA sequencing was performed to screen the differentially expressed genes. The effects of corticosterone (CORT) on proliferation, colony formation, migration, and GSTM2 expression were examined in HCT116 cells, followed by functional validation through GSTM2 overexpression and inhibition assays. Molecular docking, molecular dynamics simulations, and surface plasmon resonance (SPR) were used to validate the binding of Quercetin to GSTM2. The therapeutic efficacy of SNS and Quercetin was assessed with respect to depressive symptoms, serum BDNF levels, NLRP3 inflammasome activity, and the potency of 5-fluorouracil (5-FU) chemotherapy. Mice with depression and colon cancer exhibited aggravated depressive behaviors and accelerated tumor progression. RNA-sequencing and network pharmacology analyses identified GSTM2 as a promising candidate target in colon cancer treatment, which was markedly down-regulated in the DP-CC group. CORT enhanced proliferation, colony formation, and migration of HCT116 cells while simultaneously suppressing GSTM2 expression. Conversely, GSTM2 levels negatively correlated with cell proliferation, colony formation, and chemoresistance in HCT116 cells. Treatment with SNS alleviated depressive symptoms, elevated serum BDNF, reduced NLRP3 inflammasome activity, and potentiated the efficacy of 5-FU chemotherapy. Quercetin, a bioactive component of SNS, bound to GSTM2 through hydrogen-bond and van-der-Waals interactions, up-regulated GSTM2 expression, and mitigated CORT-induced proliferation, colony formation, and chemoresistance. Our findings suggest that depression promotes colon-cancer progression by down-regulating GSTM2, whereas SNS restores GSTM2 expression and enhances chemotherapeutic response. Show less
no PDF DOI: 10.1016/j.phymed.2026.158113
BDNF cancer progression chemoresistance chemotherapy colon cancer depression gst

Bidirectional association between immune-mediated diseases and major depressive disorder: evidence from cohort, genome-wide pleiotropic, and experimental studies.

Xiaohua Chen, Huan Liu, Yurong Liu +16 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospect Show more
Although immune-mediated diseases (IMDs) and major depressive disorder (MDD) commonly co-occur, the bidirectional relationship between them remains to be fully elucidated. Using data from the prospective UK Biobank cohort, we evaluated the bidirectional associations by time-varying Cox proportional hazards regression models and assessed shared genetic architecture using genome-wide association study summary statistics. Additionally, we employed collagen-induced arthritis (CIA) and chronic social defeat stress (CSDS) mouse models to investigate the relationship between rheumatoid arthritis (RA) and depression. Over 5,226,841 person-years of follow-up, 23,534 incident MDD cases were identified. The presence of any IMD was associated with higher MDD risk (hazard ratio [HR]: 1.95; 95% CI: 1.89-2.01). Conversely, 59,742 incident cases of IMD were documented. MDD was associated with increased IMD risk (HR: 1.47; 95% CI: 1.40-1.54). We observed significant global genetic correlations between IMDs and MDD (r Show less
📄 PDF DOI: 10.1038/s41380-026-03459-w
BDNF

DPP4-regulated endothelial cell ferroptosis modulates atherosclerosis progression by ferritinophagy.

Lanzhuoying Zheng, Ke Liang, Yuanyuan Peng +9 more · 2026 · Journal of molecular and cellular cardiology · Elsevier · added 2026-04-24
Atherosclerosis (AS), the primary pathophysiological foundation of coronary artery disease (CAD), initiates through endothelial dysfunction that facilitates lipid deposition and plaque formation. Emer Show more
Atherosclerosis (AS), the primary pathophysiological foundation of coronary artery disease (CAD), initiates through endothelial dysfunction that facilitates lipid deposition and plaque formation. Emerging evidence implicates dipeptidyl peptidase IV (DPP4) in vascular pathologies, yet its mechanistic role in AS-associated endothelial ferroptosis remains undefined. Multidisciplinary approaches were employed: 1) Bioinformatic analysis of public databases identified DPP4-ferroptosis-AS associations; 2) Clinical samples measured plasma DPP4 levels across CAD severity strata; 3) Atherogenic progression was compared between DPP4 Clinical samples analysis revealed a significant increase in plasma DPP4 levels in patients with severe coronary artery stenosis, with DPP4 enrichment observed at plaque. Animal studies demonstrated that DPP4 deficiency attenuated progression of AS and ferroptosis in murine models. Cellular experiments revealed ox-LDL upregulated DPP4 expression, concomitant with increased ferroptosis susceptibility and endothelial dysfunction. DPP4 inhibition preserved endothelial viability by blocking lipid peroxide accumulation. Mechanistically, mouse proteomics revealed that ferroptosis and autophagy pathways were associated with DPP4 in AS. DPP4 destabilized FTH1 via NCOA4-mediated ferritinophagy, proven by concordant rescue effects of chloroquine (autophagy inhibition) and saxagliptin (DPP4 inhibition) on FTH1 preservation. This study establishes endothelial DPP4 as a regulator of ferritinophagy-driven ferroptosis, inducing endothelial dysfunction in AS. Our findings propose targeting the DPP4-NCOA4-FTH1 axis as a promising strategy to preserve endothelial viability and halt early AS progression, with translational implications for repurposing DPP4 inhibitors in cardiovascular therapeutics. Show less
no PDF DOI: 10.1016/j.yjmcc.2026.01.006
APOE

Brusatol derivative ameliorates rheumatoid arthritis and atherosclerosis with associated suppression of mitochondrial fission.

Ruicong Ma, Jiaqing Liu, Siwen Yang +8 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Brusatol (BRU), a major bioactive quassinoid isolated from Brucea javanica, has shown potential in the treatment of inflammatory diseases. As mitochondrial dysfunction has been implicated in chronic i Show more
Brusatol (BRU), a major bioactive quassinoid isolated from Brucea javanica, has shown potential in the treatment of inflammatory diseases. As mitochondrial dysfunction has been implicated in chronic inflammatory disorders, modulation of mitochondrial homeostasis may offer a potential approach for the treatment of rheumatoid arthritis (RA) and atherosclerosis (AS). To develop a novel BRU derivative through rational modification at the C11‑hydroxyl group and to compare the therapeutic effects of BRU and its derivative BRUD in experimental models of RA and AS, with particular focus on mitochondrial regulation and Drp1-associated signaling. This study combined in vivo and in vitro experiments to evaluate the pharmacological effects of BRU and BRUD and investigate the underlying mechanisms. The chemical constituents of BRU and BRUD were confirmed by HPLC and NMR spectroscopy ( In vivo studies demonstrated that both compounds ameliorated joint damage in CIA rats and reduced atherosclerotic lesion burden in ApoE These findings suggest that BRUD exhibits improved activity compared with BRU in RA and AS models, with protective effects associated with modulation of mitochondrial dysfunction, supporting its further evaluation as a lead compound. Show less
no PDF DOI: 10.1016/j.phymed.2026.158171
APOE

Cerebral FURIN deficiency impairs astrocytic lipophagy through ITGAV maturation.

Xiao-Yong Xie, Lu Wang, Shi-Qi Xie +14 more · 2026 · Autophagy · Taylor & Francis · added 2026-04-24
FURIN cleaves a subset of proproteins into functional mature fragments. Evidence suggests that FURIN is involved in brain development and the associated diseases, whereas the potential mechanisms rema Show more
FURIN cleaves a subset of proproteins into functional mature fragments. Evidence suggests that FURIN is involved in brain development and the associated diseases, whereas the potential mechanisms remain incompletely understood. Here, we report that cerebral FURIN-deficient mice exhibit cognitive decline and neurodegeneration. Lipid droplets (LDs) that are preferentially accumulated in astrocytes correlate with an increase of the LD markers PLIN2 and PLIN3, and conversely a decreased level of autophagic proteins including ATG5, BECN1 and MAP1LC3/LC3 as well as LAMP1. Accordingly, silencing of Show less
no PDF DOI: 10.1080/15548627.2025.2601039
BACE1

In vivo epigenome editing reduces circulating lipids and attenuates atherosclerosis in mice.

Wei Wang, Yingjie Zhang, Lin Chen +10 more · 2026 · Journal of genetics and genomics = Yi chuan xue bao · Elsevier · added 2026-04-24
Atherosclerotic cardiovascular disease remains the leading cause of global mortality, with hypercholesterolemia serving as a critical driver of atherogenesis. Although current lipid-lowering therapies Show more
Atherosclerotic cardiovascular disease remains the leading cause of global mortality, with hypercholesterolemia serving as a critical driver of atherogenesis. Although current lipid-lowering therapies substantially improve circulating lipid profiles, strategies that provide more durable, safe, and efficient control of lipid metabolism are still needed. Epigenome editing offers a promising approach for long-lasting repression of disease-modifying genes without altering the underlying DNA sequence. Here, we develop CRISPRoff platforms delivered by adeno-associated virus or lipid nanoparticle to epigenetically silence hepatic Hmgcr or Pcsk9 in vivo. In both C57BL/6J wild-type and ApoE Show less
no PDF DOI: 10.1016/j.jgg.2026.04.004
APOE

Targeting CPS1 attenuates lung cancer metastasis by regulating EMT through an epigenetic mechanism.

Yi Ding, Yuying Tian, Mengjuan Li +14 more · 2026 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.123679
CPS1

Multiscale Mechanisms of Exercise-Induced Neuroplasticity: From Molecular Pathways to Network Dynamics and Behavioral Adaptation.

Xue Wang, Jun Zhang, Xiaoyu Wang +7 more · 2026 · Brain sciences · MDPI · added 2026-04-24
Exercise as a non-pharmacological measure is important to increase the brain plasticity hence improving cognitive performance as well as mental health. This narrative review describes in depth the hie Show more
Exercise as a non-pharmacological measure is important to increase the brain plasticity hence improving cognitive performance as well as mental health. This narrative review describes in depth the hierarchical multiscale processes of neuroplasticity to exercise, including the presence of neurotrophic factor regulation, cellular metabolic adaptations and neurotransmitter remodeling, up to the structure and functional reorganization of brain networks as seen through neuroimaging, and concluding with adaptive cognitive and behavioral outcomes. We further investigate the role of personal variations in genetic time and social environments in moderating the neuroplasticity of exercise. Furthermore, the review identifies the importance of combining multimodal visualization methods with computational models in generating accurate workout prescriptions and their potential of translation into clinical and educational practice. Lastly, the research problems and "grand challenges" are addressed, with a focus on the importance of exercise as a pleiotropic behavior-intervention and its general implications to the area of promoting brain health. Show less
📄 PDF DOI: 10.3390/brainsci16030294
BDNF

Dapagliflozin Attenuates Atherosclerosis Under Chronic Stress by Maintaining AKT/FoxO1 Pathway Through Downregulation of REDD1.

Jianyi Li, Luyao Zhang, Jiapei Xu +7 more · 2026 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
Chronic stress is associated with inflammatory activation and oxidative stress responses leading to endothelial dysfunction, which promotes the development of atherosclerosis (AS). SGLT2 inhibitors, s Show more
Chronic stress is associated with inflammatory activation and oxidative stress responses leading to endothelial dysfunction, which promotes the development of atherosclerosis (AS). SGLT2 inhibitors, such as Dapagliflozin (DAPA), exhibit a protective effect against cardiovascular diseases. However, the effects and mechanisms of DAPA on chronic stress-induced AS are largely unknown. The aim of this study was to determine whether DAPA confers a protective effect against chronic stress-induced AS and to elucidate its further molecular mechanisms. The combined high-fat diet-fed and chronic unpredictable mild stress in ApoE-/- mice and lipopolysaccharides- and corticosterone-induced human umbilical vein endothelial cells (HUVECs) were employed to evaluate the antiatherosclerotic effect of DAPA under chronic stress in vivo and in vitro. Histological staining, western blot analysis, siRNA transfection, reactive oxygen species (ROS) staining, and apoptosis assessment were used to investigate the potential mechanisms of DAPA against AS under chronic stress. The results indicate that DAPA significantly improved plaque size and increased plaque stability in the aorta under chronic stress and reduced inflammation and oxidative stress and inhibited apoptosis in the aorta and HUVECs. Chronic stress upregulated regulated in development and DNA damage response 1 (REDD1) expression, which exacerbated cellular inflammation, oxidative stress, and apoptosis levels, leading to endothelial dysfunction. In contrast, DAPA downregulated REDD1 expression and activated the AKT/FoxO1 pathway. In addition, p53 was a transcriptional regulator of REDD1 under chronic stress. More importantly, p53 agonists prevented DAPA from downregulating REDD1 and inhibited AKT/FoxO1 activation, thereby exacerbating chronic stress-induced endothelial dysfunction. These results suggest that DAPA effectively attenuates chronic stress-induced endothelial dysfunction and AS by downregulating REDD1 to activate the AKT/FoxO1 pathway. Show less
no PDF DOI: 10.1096/fj.202502868R
APOE

The effect of ionizable lipids on the cellular uptake of lipid bilayer coated mesoporous silica nanoparticles in the liver.

Junyi Tu, Runpu Ma, Wei Jiang +5 more · 2026 · Journal of materials chemistry. B · Royal Society of Chemistry · added 2026-04-24
Conventional nanocarriers are readily cleared by macrophages in the liver, with only a minimal fraction reaching hepatocytes. This limitation has been effectively overcome in clinically approved lipid Show more
Conventional nanocarriers are readily cleared by macrophages in the liver, with only a minimal fraction reaching hepatocytes. This limitation has been effectively overcome in clinically approved lipid nanoparticles (LNPs) through the incorporation of ionizable lipids. Inspired by this property, we explored whether incorporating ionizable lipids into the lipid bilayer membrane of mesoporous silica nanoparticles (silicasomes) could similarly enhance their hepatic cellular uptake. We developed ionizable silicasomes (I-silicasomes) and systematically compared them with ionizable liposomes (I-liposomes), as well as their conventional counterparts (C-silicasomes and C-liposomes). Surprisingly, I-silicasomes did not enhance hepatocyte uptake Show less
no PDF DOI: 10.1039/d5tb02579f
APOE

Relationship between amyloid burden, cholinergic integrity, and cognitive function.

Li-Hua Lee, Chia-Ju Chou, Yao-Chia Shih +4 more · 2026 · Journal of Alzheimer's disease : JAD · SAGE Publications · added 2026-04-24
BackgroundAmyloid accumulation and degeneration of the cholinergic white matter pathways are key factors in early Alzheimer's disease pathogenesis and progression. However, the relationship between th Show more
BackgroundAmyloid accumulation and degeneration of the cholinergic white matter pathways are key factors in early Alzheimer's disease pathogenesis and progression. However, the relationship between them remains unclear.ObjectiveTo investigate the association between amyloid accumulation, the integrity of cholinergic white matter pathways, and cognitive performance.MethodsThis cross-sectional study recruited 109 individuals, including 37 controls with normal cognition and 72 patients with early Alzheimer's disease. All participants underwent neuropsychological testing: the Mini-Mental Status Examination (MMSE), Clinical Dementia Rating scale with sum of box (CDR-SB), and verbal fluency tests. Cholinergic white matter integrity and amyloid burden were assessed through diffusion tensor imaging study (DTI) and amyloid positron emission tomography (PET). Stepwise linear regression analyses were performed. Partial correlations between amyloid burden and cholinergic integrity were also evaluated according to apolipoprotein E4 ( Show less
no PDF DOI: 10.1177/13872877251406620
APOE

IL-33-Driven Macrophage Reprogramming as a Potential Immunometabolic Strategy for Herpes Simplex Keratitis.

Yun He, Yaoyao Liu, Junwen Ouyang +6 more · 2026 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph19020285
LPL

Rejuvenation of THY1

Haoxin Zhai, Zexin Wang, Shaoyi Wang +10 more · 2026 · Journal of advanced research · Elsevier · added 2026-04-24
Intervertebral disc degeneration (IVDD), a major cause of low back pain, is primarily characterized by compromised regeneration ability of nucleus pulposus-derived stem cells (NPSCs) owing to their se Show more
Intervertebral disc degeneration (IVDD), a major cause of low back pain, is primarily characterized by compromised regeneration ability of nucleus pulposus-derived stem cells (NPSCs) owing to their senescence. The role of NPSCs as major regenerative cells in IVDD is garnering attention. However, the drivers and mechanisms of NPSCs reactivation and regeneration are poorly understood, limiting the development of targeted therapies. The fibroblast growth factor (FGF) family has shown increasing promise in tissue regeneration; however, the key factors involved in IVDD remain unclear. To elucidate the regenerative driver of NPSCs and the underlying anti-senescence mechanism to provide a potential therapeutic strategy. Single cell RNA sequencing (scRNA-seq) and bulk RNA sequencing were performed to identify the key NPSCs clusters and regenerative drivers in IVDD. Clinical IVDD samples were collected to determine the alterations in the NPSCs subset proportion and the expression of regeneration factors. Further, NPSCs senescence and in vivo models were utilized to investigate the specific mechanisms and therapeutic effects. Thy-1 membrane glycoprotein (THY1) Our findings elucidate the pivotal roles of THY1 Show less
no PDF DOI: 10.1016/j.jare.2026.03.008
FGFR1

Associations of physical activity intensity with the non-high-density lipoprotein to high-density lipoprotein cholesterol ratio and mortality in middle-aged and older adults: New evidence from China.

Fangyu Zhao, Xuemin Peng, Yongbin Zhuang +4 more · 2026 · Experimental gerontology · Elsevier · added 2026-04-24
The non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a comprehensive lipid index reflecting the balance between atherogenic and anti-atherogenic lipopro Show more
The non-high-density lipoprotein to high-density lipoprotein cholesterol ratio (NHHR) has emerged as a comprehensive lipid index reflecting the balance between atherogenic and anti-atherogenic lipoproteins. However, evidence on how different intensities and durations of physical activity (PA) influence NHHR remains scarce, particularly in aging populations. Data were obtained from China Health and Retirement Longitudinal Study. PA was self-reported and categorized as high- (HPA), moderate- (MPA), or low-intensity (LPA). Multivariable linear regression models assessed associations between PA and NHHR, with subgroup, sensitivity, and dose-response analyses further exploring robustness. Cox regression and mediation analyses examined the associations of PA and NHHR with 10-year all-cause mortality. Higher levels of total, moderate-, and high-intensity PA were significantly associated with lower NHHR. The results were generally consistent with a graded pattern, with lower NHHR observed at higher activity durations, particularly for moderate-to-vigorous activity. Exploratory mediation analyses suggested that NHHR may partially account for the inverse association between PA and mortality. This study adds large-scale, population-based evidence on the associations between different PA intensities and NHHR. Regular moderate-to-vigorous PA is associated with more favorable lipid profiles and lower mortality risk. These findings highlight NHHR as a valuable biomarker linking physical activity to cardiometabolic health and longevity in middle-aged and older adults. Show less
no PDF DOI: 10.1016/j.exger.2026.113098
LPA

Heterogeneity of Academic Stress Profiles and Depression-Anxiety Symptom Networks in Left-Behind Children: A Latent Profile and Simulated Intervention Network Analysis.

Kuiliang Li, Lei Ren, Rui Lang +7 more · 2026 · Stress and health : journal of the International Society for the Investigation of Stress · Wiley · added 2026-04-24
Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the het Show more
Compared with non-left-behind children (NLBC), left-behind children (LBC) face a higher risk of academic stress, depression, and anxiety symptoms due to separation from their parents; however, the heterogeneity of academic stress profiles and their relationships with the symptom network remain insufficiently explored. To address this gap, a cross-sectional survey of 10,524 Chinese children compared LBC (n = 2487) and NLBC. Latent profile analysis (LPA) was first conducted to identify academic stress subgroups among LBC. Subsequently, depression-anxiety symptom networks were estimated using Ising and Gaussian graphical models (GGM), with edge weights derived from regularised logistic regression (Ising) and partial correlation (GGM). Simulated interventions were further evaluated via the NodeIdentifyR algorithm (NIRA). Overall, compared to NLBC, LBC exhibited higher levels of academic stress, depression, and anxiety (ps < 0.001, Cliff's δ = 0.076; Cohen's d = 0.067). LPA revealed three academic stress subgroups: moderate (31.44%), high (9.17%), and low (59.39%). The severity of depression and anxiety symptoms increased with the level of academic stress. The high stress subgroup displayed a sparse network with stronger edges (e.g., A1 'Sudden Fear'-A4 'Physical Symptoms', edge weight = 2.10) compared to moderate- and low-academic stress subgroups. Core nodes with the strongest expected influence were A8 ('Decision Hesitation', moderate subgroup), A2 ('Worry', high subgroup), and D1/D6 ('Sadness' and 'Failure', low subgroup). Simulated interventions indicated that alleviating A8 'Decision Hesitation' or A2 'Worry' most effectively reduced symptom risk (16.66%-30.76%), whereas D8 'Motor' and A7 'Early Departure' were associated with maximal symptom aggravation. Taken together, by integrating LPA-derived academic stress profiles with symptom network analysis, this study reveals distinct symptom associations across subgroups. In the high stress subgroup, symptom A2 ('Worry') is a core intervention target; in the low stress subgroup, A7 ('Early Departure') holds preventive potential. These findings underscore subgroup-specific interventions tailored to individual stress profiles. Show less
no PDF DOI: 10.1002/smi.70172
LPA

Rs12516 A allele elevates the risk of colorectal cancer via functional CeRNA network of BDNF-AS, miR-4704-5p and BRCA1.

Daxu Liu, Zhijun Fan, Teng Zhang +5 more · 2026 · BMC cancer · BioMed Central · added 2026-04-24
DNA double-strand break repair has emerged as a vital pathway to repair DNA damage seriously related to the risk of colorectal cancer (CRC). To explore valid susceptible biomarkers of CRC via investig Show more
DNA double-strand break repair has emerged as a vital pathway to repair DNA damage seriously related to the risk of colorectal cancer (CRC). To explore valid susceptible biomarkers of CRC via investigating the association of single nucleotide polymorphisms in DSBR genes with CRC risk, seven polymorphisms located in 3'-untranslated regions of DSBR genes including RAD51 rs11852786, RAD51B rs963917, BRCA1 rs12516 and rs8176318, BRCA2 rs15869, XRCC4 rs2035990 and XRCC5 rs2440 were detected and analyzed in a CRC case-control study (cases (202) and also controls (202)). The PolymiRTs and miRSNP database were used to predict the microRNAs that can bind to 3'UTR SNPs. Since long non-coding RNA as a miRNA "sponge" played the role of competing endogenous RNA, DAVID database was used to find the lncRNAs that can bind to the candidate miRNA seed sequences. BRCA1 rs12516 minor A allele was found to be linked with a higher risk of CRC than its major G allele (OR = 2.716, 95%CI: 1.394-5.292, P = 0.003). The stratified analyses demonstrated rs12516 AA genotype with a more elevated risk of CRC in male (OR = 3.089, 95% CI:1.315 ~ 7.255) or age > 50 population (OR = 3.318, 95%CI:1.571 ~ 7.006) than its GG genotype. BRCA1 rs12516 A allele created a novel miR-4704-5p binding target, and there was a negative correlation between miR-4704-5p and BRCA1 expression (r =-0.7199, P = 0.0440). Based on the theory of ceRNA network, it was predicted that lncRNA BDNF-AS can competitively bind to miR-4704-5p, whose expression was exhibited to be negatively correlated with BDNF-AS (r=-0.3481, P = 0.0375). On the contrary, BDNF-AS expression showed a positive correlation with BRCA1 mRNA level in colorectal tissue carrying rs12516 of A allele (adjacent tissue: r = 0.7269, P = 0.0411; cancer tissue: r = 0.7134, P = 0.0469). ROC curve showed both BDNF-AS (AUC = 0.651, P = 0.0277) and miR-4704-5p (AUC = 0.7215, P = 0.0012) can distinguish CRC tissues from their adjacent tissues. BRCA1 rs12516 is characterized as a potential biomarker associated with CRC risk, via a possible functional ceRNA network of BDNF-AS, miR-4704-5p and BRCA1. The interaction of a lower expression of BDNF-AS, a higher expression of miR-4704-5p and rs12516 A allele could together increase the risk of colorectal cancer. Show less
📄 PDF DOI: 10.1186/s12885-025-14692-x
BDNF

Ultra-low-input rG4-seq reveals the RNA G-quadruplex regulome in gene expression and genome integrity.

Tie-Gang Meng, Wei Yue, Chao Li +14 more · 2026 · Nucleic acids research · Oxford University Press · added 2026-04-24
RNA G-quadruplexes (rG4s), formed through guanine self-recognition into stacked tetrads, serve as critical regulators of gene expression, yet their comprehensive mapping and dynamic regulation in phys Show more
RNA G-quadruplexes (rG4s), formed through guanine self-recognition into stacked tetrads, serve as critical regulators of gene expression, yet their comprehensive mapping and dynamic regulation in physiological contexts remain technically challenging. Here, we develop Ultra-low-input rG4-seq (ULI-rG4-seq), enabling precise rG4 detection enabling precise rG4 detection with ∼140 bp resolution in samples as small as 100 oocytes, and reveal notable enrichment of rG4s near crucial regulatory regions, particularly transcription start sites and end sites. This technological advance, combined with Trim-away or oocyte-specific knockout of DHX36 (also known as G4R1 or RHAU), an rG4-specific helicase, reveals acute and chronic loss of DHX36 leads to opposing effects on rG4 levels. This observation extends beyond the traditional view of helicases as unwinding enzymes and suggests sophisticated cellular mechanisms maintaining RNA structural homeostasis. Through integrated analysis of rG4 landscapes and DHX36-binding profiles, we demonstrate coordination between cytoplasmic rG4 regulation and nuclear gene expression, revealing how RNA structure dynamics orchestrate RNA stability and translation, thereby influencing transcriptional elongation, genome stability, and alternative splicing. Finally, we show that deletion of DHX36 resulted in decreased oocyte quality, premature ovarian failure and complete female infertility due to transcriptional defects and genome instability related to R-loop accumulation. These technological and conceptual advances not only deepen our understanding of RNA-based regulation but also open new therapeutic possibilities for diseases involving RNA structure. Show less
📄 PDF DOI: 10.1093/nar/gkag040
DHX36

Retinal vascular phenotyping for early detection of coronary artery disease: quantitative assessment and diagnostic modelling.

Zhenyan Wu, Xue Jiang, Yu Xin +3 more · 2026 · BMJ open · added 2026-04-24
To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-in Show more
To investigate the association between quantitative retinal vascular parameters and coronary artery disease (CAD) and to evaluate the efficacy of a retinal phenotype-based diagnostic model as a non-invasive tool for early CAD screening. A retrospective cross-sectional study. A single-centre study conducted at the Cardiovascular Center of Beijing Tongren Hospital, Capital Medical University, China, between January and October 2024. 417 patients with suspected angina undergoing their first coronary angiography (CAG) were enrolled. Inclusion criteria were age >18 years and high-quality fundus photography within 24 hours pre-CAG. Major exclusions were prior coronary interventions, severe systemic/valvular heart diseases and ocular conditions impairing retinal vascular visualisation. The primary outcome was the association between quantitative retinal vascular parameters and the presence of CAD (defined as ≥50% stenosis). Secondary outcomes included the diagnostic performance area under the receiver operating characteristic curve (AUROC) of three predictive models: one based on quantitative retinal vascular parameters alone, one based on traditional risk factors and a combined model integrating both retinal and clinical variables. This study enrolled 417 patients undergoing initial CAG. Compared with non-CAD controls (n=190), patients with CAD (n=227) had higher prevalence of hypertension, dyslipidaemia and diabetes, along with elevated levels of fasting blood glucose, lipoprotein(a) (Lp(a)), triglyceride (TG) and glycated haemoglobin (HbA1c) (all p<0.05). Quantitative fundus analysis revealed that multiple retinal vascular parameters were independently associated with CAD after multivariable adjustment, including fractal dimension (FD), vessel density (VD) and specific zonal measures of vessel diameter and tortuosity (all p<0.05). Multivariable logistic regression incorporating both fundus and clinical variables identified the following independent predictors of CAD: a decrease in FD (OR=0.26, 95% CI 0.16 to 0.41, p<0.01), reduced optic disc long-to-short axis ratio (OR=0.04, 95% CI 0.004 to 0.46, p=0.01) and optic disc-to-macula distance (OR=0.91, 95% CI 0.86 to 0.97, p<0.01), male sex, dyslipidaemia and elevated levels of Lp(a), TG, low-density lipoprotein cholesterol and HbA1c (all p<0.05). The final diagnostic model achieved an AUROC of 0.802 (95% CI 0.76 to 0.845), with a sensitivity of 0.797 and a specificity of 0.679 at the optimal cut-off. Internal validation via bootstrap resampling (1000 iterations) confirmed the robustness of the identified predictors. Our findings, derived from an artificial intelligence-based fully automated quantitative retinal vascular parameters measurement method, revealed that multiple quantitative fundus parameters-including FD, VD and other morphological parameters were significantly associated with CAD risk. The CAD diagnostic model we developed demonstrates strong performance and high interpretability, making it suitable for early CAD screening and diagnosis. Show less
📄 PDF DOI: 10.1136/bmjopen-2025-106135
LPA

Exploring the Hypoglycemic Activity and Mechanism of Polyphenols From Highland Barley Through Lactobacillus acidophilus Fermentation.

Mengyao Zhu, Xu Guo, Yingying Chen +6 more · 2026 · Journal of food science · Blackwell Publishing · added 2026-04-24
The polyphenols in grains are highly active, but some polyphenols in highland barley are in a bound form and have extremely low bioavailability. Fermentation by lactic acid bacteria (LAB) is capable o Show more
The polyphenols in grains are highly active, but some polyphenols in highland barley are in a bound form and have extremely low bioavailability. Fermentation by lactic acid bacteria (LAB) is capable of altering the functionality of foods. This research investigated the effects of fermentation with different LAB, such as Lactobacillus acidophilus (LAC), Lactobacillus casei (LCA), Lactobacillus rhamnosus (LRH), Lactobacillus plantarum (LPL), and Lactobacillus bulgaricus (LBU), on the hypoglycemic activity and mechanism of polyphenols in highland barley. The hypoglycemic activity of the fermentation products was measured by in vitro antioxidant, enzyme activity, and glucose consumption experiments. Untargeted metabolomic analysis used UHPLC-Q Exactive HF-X/MS to reveal distinct metabolic profiles among the fermented groups. Molecular docking and western blot experiments were conducted to elucidate the mechanism underlying the hypoglycemic effect of fermentation products. Polyphenolic antioxidant activity in highland barley and its inhibitory activities against α-glucosidase and α-amylase were increased after LAC fermentation. Furthermore, the fermented extracts improved glucose consumption in HepG2 cells. The content determination and metabolomic analysis showed that fermented highland barley polyphenols were increased, and 113 differential phenolic metabolites were identified and annotated, among which 44 exhibited a significant upregulation compared with raw highland barley polyphenols. At the molecular level, the polyphenol extract upregulated PI3K and phosphorylated Akt expression in HepG2 cells. Overall, the results indicate that fermentation by LAC biotransformed highland barley polyphenols into smaller molecules with improved hypoglycemic activities, thereby enhancing their bioavailability. Show less
no PDF DOI: 10.1111/1750-3841.71061
LPL