👤 Didi Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, 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

Decreased adipokine CTRP4 in CAD patients: CTRP4 attenuates atherosclerosis via inhibition of RAGE and TLR4.

Xinyi Shu, Feifei Li, Jiawei Chen +15 more · 2026 · Clinical and translational medicine · Wiley · added 2026-04-24
C1q/TNF-related proteins (CTRPs) belong to the adipokine family. Here, we aimed to assess the relation of CTRP4 levels in serum and perivascular adipose tissue (PVAT) with coronary artery disease (CAD Show more
C1q/TNF-related proteins (CTRPs) belong to the adipokine family. Here, we aimed to assess the relation of CTRP4 levels in serum and perivascular adipose tissue (PVAT) with coronary artery disease (CAD), and investigate the effect of CTRP4 on atherosclerosis and the underlying mechanisms. CTRP4 levels were examined in serum and epicardial adipose tissue (a major PVAT) from patients with CAD. Atherosclerotic lesions were analysed in CTRP4 CTRP4 levels were lower in serum and epicardial adipose tissue of patients with CAD compared to non-CAD controls. CTRP4 knockout promoted atherosclerosis in ApoE Decreased CTRP4 levels in serum and epicardial adipose tissue are associated with CAD in patients. CTRP4 deficiency promotes the development of atherosclerosis in ApoE Show less
📄 PDF DOI: 10.1002/ctm2.70624
APOE

Pitolisant Inhibits Alcohol Drinking and Improves Withdrawal Negative Affect Through Lateral Habenula Histaminergic Signaling in Mice.

Yan Zhao, Yixin Fu, Tianhao Liu +11 more · 2026 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Alcohol use disorder (AUD) is a chronic condition marked by compulsive drinking and withdrawal-related negative affect. Histamine (HA) signaling, particularly via the histamine H3 receptor (H3R), may Show more
Alcohol use disorder (AUD) is a chronic condition marked by compulsive drinking and withdrawal-related negative affect. Histamine (HA) signaling, particularly via the histamine H3 receptor (H3R), may modulate alcohol-related behaviors. We investigated the effects of pitolisant, an FDA-approved H3R antagonist, on ethanol (EtOH)-related behaviors in mice. Adult male C57BL/6J mice underwent acute or chronic (2 or > 8 weeks) intermittent alcohol exposure. Pitolisant pretreatment was administered, and then pharmacological behavior, histologic, and molecular assays were conducted. Pitolisant administration reduced acute EtOH-induced locomotor activation, conditioned place preference, and sedative effects, and also curtailed EtOH intake. It alleviated anxiety and depression-like behavior during 24-h withdrawal (Post-EtOH). Mechanistically, the Post-EtOH condition was featured by complicated brain cFos expression mapping, including elevated cFos, [HA] and [glutamine]/[glutamate] ratio in the lateral habenula (LHb). However, systemic pitolisant treatment significantly increased [norepinephrine]/[normetanephrine] ratio, and restored the diminished phosphorylated CREB and BDNF levels in the LHb. Intra-LHb H2R antagonist cimetidine infusion partly blocked the pitolisant therapeutic effect on alcohol-related behavior. These findings highlight the HAergic system as a critical regulator of alcohol-related behaviors. The LHb HA signaling and norepinephrine neurotransmission might underlie pitolisant's potential novel therapeutic strategy for AUD. Show less
📄 PDF DOI: 10.1002/cns.70732
BDNF

Narciclasine Alleviates Endothelial Inflammation and Atherosclerosis Initiation by Inhibiting Histone Lactylation-Mediated NF-κB Activation.

Ziqian Wang, Zhengbin Zhang, Ran Xin +8 more · 2026 · Inflammation · Springer · added 2026-04-24
Glycolysis-derived lactate serves as a substrate for lysine lactylation, an epigenetic modification playing critical transcriptional regulatory roles in inflammatory diseases. Endothelial inflammation Show more
Glycolysis-derived lactate serves as a substrate for lysine lactylation, an epigenetic modification playing critical transcriptional regulatory roles in inflammatory diseases. Endothelial inflammation, characterized by upregulated glycolysis, initiates atherosclerosis, yet the contribution of histone lactylation remains undefined. Although narciclasine exhibits anti-inflammatory and antioxidant properties, its impact on endothelial inflammation in atherosclerosis is unknown. Connectivity Map (CMap) analysis predicted narciclasine as an inhibitor of oscillatory shear stress and TNF-α-induced endothelial inflammation. In vitro, treatment of human umbilical vein endothelial cells (HUVECs) with 20 nM narciclasine significantly suppressed ox-LDL-induced expression of VCAM1, ICAM1, SELE, and CCL2, reduced reactive oxygen species (ROS) production, and inhibited monocyte adhesion and migration. In vivo, administration of narciclasine (0.02 mg/kg) attenuated carotid artery endothelial inflammation and macrophage infiltration, consequently reducing early atherogenesis in partial carotid ligation model in ApoE Show less
📄 PDF DOI: 10.1007/s10753-025-02446-7
APOE

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

Predictive lipidaemic and clinical factors for PVR formation after RRD surgery in nondiabetic patients.

Yan Jiang, Tian Niu, Guo-Hui Lan +2 more · 2026 · International journal of ophthalmology · added 2026-04-24
To investigate the potential impact of lipidaemic and clinical factors on the development of proliferative vitreoretinopathy (PVR) following uncomplicated primary rhegmatogenous retinal detachment (RR Show more
To investigate the potential impact of lipidaemic and clinical factors on the development of proliferative vitreoretinopathy (PVR) following uncomplicated primary rhegmatogenous retinal detachment (RRD) surgery in nondiabetic individuals. This was a retrospective, single-center, case-control study of consecutive patients who underwent primary RRD surgery. The study group comprised 145 patients who developed PVR within 3y of follow-up, while the control group comprised 161 patients with RRD who did not develop PVR. Cox regression analysis was utilized to identify independent associations between various risk markers and the occurrence of PVR. The mean age of patients was 52.31y (SD=13.29), and 54.25% ( Apart from macular involvement and smoking, the lipidaemic factors ApoA1 and ApoE are risk factors of PVR after primary RRD surgery. Show less
no PDF DOI: 10.18240/ijo.2026.04.12
APOE

Lower Plasma Serotonin is Associated with Higher Amyloid Burden, Hippocampal Atrophy, and Cognitive decline in Alzheimer's Disease: A 24-Month Longitudinal Study.

Yingbo Han, Li Liu, Li Chang +6 more · 2026 · Journal of molecular neuroscience : MN · Springer · added 2026-04-24
This study investigated longitudinal plasma serotonin dynamics across the Alzheimer's disease (AD) continuum (cognitively normal [CN], mild cognitive impairment [MCI], and AD) to determine whether bas Show more
This study investigated longitudinal plasma serotonin dynamics across the Alzheimer's disease (AD) continuum (cognitively normal [CN], mild cognitive impairment [MCI], and AD) to determine whether baseline serotonin and its 24-month change are associated with CSF amyloid-β (Aβ42), tau biomarkers, amyloid PET burden, structural brain integrity, and cognitive decline. Data from 959 ADNI participants (CN = 306, MCI = 421, AD = 232) with baseline and 24-month follow-up were analyzed. Measures included plasma serotonin, CSF biomarkers (Aβ42, total tau, p-tau181), florbetapir PET, MRI (hippocampal volume, cortical thickness), and cognitive tests (MMSE, ADAS-Cog 11, CDR-SB). Group differences were tested using ANOVA or Kruskal-Wallis, and associations were examined via partial correlations and mixed-effects models adjusted for age, sex, education, and APOE ε4, with FDR correction. The results revealed that baseline plasma serotonin levels showed a stepwise decline across the clinical continuum (CN > MCI > AD; p ≤ 0.05), consistent with progressive serotonergic dysregulation. In AD participants, higher baseline serotonin was significantly associated with less amyloid pathology and preserved brain structure, including higher CSF Aβ42 (β = 0.28, FDR p = 0.01), lower florbetapir PET SUVR (β = -0.31, FDR p = 0.02), and larger hippocampal volume (β = 0.33, FDR p = 0.02). Higher serotonin was also linked to better cognitive performance (MMSE: β = 0.22, FDR p = 0.02; ADAS-Cog 11: β = -0.24, FDR p = 0.02). Longitudinally, decreases in serotonin over 24 months in AD were associated with worsening amyloid burden (ΔPET SUVR: β = -0.29, FDR p = 0.02) and accelerated hippocampal atrophy (β = 0.32, FDR p = 0.01). Baseline serotonin predicted smaller 24-month declines in CSF Aβ42 (β = 0.28, FDR p = 0.01) and reduced hippocampal volume loss (β = 0.31, FDR p = 0.01). In CN and MCI groups, associations between serotonin and AD biomarkers or cognitive outcomes were not significant after FDR correction. On the whole, lower plasma serotonin levels are linked to amyloid pathology, hippocampal neurodegeneration, and cognitive decline in AD, supporting serotonin's potential as a stage-specific biomarker and mechanistic contributor to disease progression. Integrative longitudinal studies are needed to clarify causality and evaluate serotonergic pathways as therapeutic targets. Show less
📄 PDF DOI: 10.1007/s12031-026-02497-x
APOE

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

Nrf2 deficiency in myeloid cells accelerates atherosclerosis by promoting the inflammatory response and impairing efferocytosis.

Xiaoge Xu, Cuijie Liu, Jinshan Bo +6 more · 2026 · Journal of advanced research · Elsevier · added 2026-04-24
Atherosclerotic lesions are the fundamental pathologies of cardiovascular diseases. The exact role of the nuclear factor erythroid 2-related factor 2 (NRF2) in macrophages in atherosclerosis remains u Show more
Atherosclerotic lesions are the fundamental pathologies of cardiovascular diseases. The exact role of the nuclear factor erythroid 2-related factor 2 (NRF2) in macrophages in atherosclerosis remains uncertain. This study aimed to investigate the role of NRF2 in myeloid cells in the development of atherosclerosis. Single-cell RNA sequencing databases were used to explore the expression levels of NRF2 in human and murine atherosclerosis. Plaque areas, necrotic core size, instability index, and efferocytosis in aortic lesions were investigated in myeloid cell-specific Nrf2-knockout mice on an ApoE-deficient background (Nrf2(M)-KO; ApoE NRF2 expression was upregulated in the macrophages of human and murine atherosclerotic arteries compared with their corresponding controls. Nrf2(M)-KO; ApoE Myeloid-specific deletion of Nrf2 promotes inflammation and inhibits macrophage efferocytosis, thereby leading to the aggravation of atherosclerosis. NRF2 activation in macrophages could be a valuable strategy for preventing and treating atherosclerosis. Show less
no PDF DOI: 10.1016/j.jare.2026.01.005
APOE

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

KCC2 Dysfunction Mediated by Microglial BDNF/TrkB Signaling Exacerbates Early Post-Stroke Seizure Susceptibility.

Jing Zhou, Benjamin H Wang, Jiangning Yu +9 more · 2026 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Post-stroke seizures are a common and debilitating complication with limited therapeutic options, underscoring the need to identify novel molecular targets. Disruption of chloride homeostasis via impa Show more
Post-stroke seizures are a common and debilitating complication with limited therapeutic options, underscoring the need to identify novel molecular targets. Disruption of chloride homeostasis via impaired potassium chloride cotransporter 2 (KCC2) activity is a key driver of neuronal hyperexcitability. While microglia are a predominant source of brain-derived neurotrophic factor (BDNF) in the acute phase after brain injury, the role of microglial BDNF and its signaling in KCC2 dysregulation and early post-stroke seizure susceptibility remain poorly defined. Using a middle cerebral artery occlusion-reperfusion (MCAO-R) mouse model and oxygen-glucose deprivation/reoxygenation (OGD/R) in hippocampal neurons, we assessed KCC2 function, neuronal excitability, and seizure susceptibility. Pharmacological tools, including the microglial inhibitor minocycline, the TrkB antagonist K252a, the loop diuretic furosemide (FUR), repurposed here as a KCC2-stabilizing agent, and the KCC2 activator CLP290, were employed. Techniques included immunofluorescence, Western blotting, patch-clamp electrophysiology, electroencephalography (EEG), and behavioral seizure assessment. MCAO-R and OGD/R significantly reduced membrane KCC2 expression, leading to a depolarizing shift in the GABA equilibrium potentials (E Our findings identify microglia-derived BDNF/TrkB signaling as a critical upstream pathway mediating KCC2 dysfunction in early post-stroke seizure. Targeting this axis by inhibiting microglial activation, blocking TrkB, or directly enhancing KCC2 function with activators like CLP290 represents a promising therapeutic strategy for stroke-related epilepsy. Show less
📄 PDF DOI: 10.1002/cns.70795
BDNF

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

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

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

A latent profile analysis of health characteristics in relation to sleep among female sex workers in entertainment venues in Wuhan, China.

Weiwei Xiang, Hua Ke, Xiaojia Song +10 more · 2026 · BMC women's health · BioMed Central · added 2026-04-24
This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This stu Show more
This study aims to examine the health characteristics of female sex workers (FSWs) in entertainment venues and to investigate the relationship between these characteristics and sleep quality. This study employed a cross-sectional design and was conducted from January to April 2024 in Wuhan, China. Participants were FSWs recruited through snowball sampling from entertainment venues, including hotels, restaurants, nightclubs, karaoke bars and dance halls. Data were collected via structured questionnaires covering sociodemographic information, work experience, psychological stress, health status, sleep quality and circadian rhythms. Latent profile analysis (LPA) was employed to identify health characteristic profiles among FSWs, and multivariate logistic regression was used to examine the associations between these profiles and sleep quality. Among the 1,036 FSWs surveyed, 45.1% had poor sleep quality. LPA classified FSWs’ health characteristics into three profiles: the high overall functioning group, the lower physical–emotional functioning group and the lower psychosocial functioning group. Multivariate logistic regression analysis showed that FSWs in the lower physical–emotional functioning group had higher odds of poor sleep quality (OR = 2.184) compared with those in the high overall functioning group. FSWs in the lower psychosocial functioning group had substantially higher odds of poor sleep quality (OR = 7.755) than that in the high overall functioning group. FSWs demonstrate substantial heterogeneity in health characteristics and exhibit lower overall sleep quality compared with the general population. Psychological and physiological factors are major influencing factors for their sleep quality, suggesting the importance of prioritising mental and physical health in this population. Show less
📄 PDF DOI: 10.1186/s12905-026-04346-w
LPA

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

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

MicroRNA-96 inhibition retarded the progression of atherosclerotic plaques via FOXO1/CYP7A1 mediated cholesterol-bile acid metabolism pathway.

Li Wang, Yiting Liu, Jin Zhang +5 more · 2026 · Expert opinion on therapeutic targets · Taylor & Francis · added 2026-04-24
Conversion of cholesterol into bile acids is a central pathway for cholesterol disposal, which was mainly controlled by cholesterol 7alpha-hydroxylase (Cyp7a1). In present study, we aimed to investiga Show more
Conversion of cholesterol into bile acids is a central pathway for cholesterol disposal, which was mainly controlled by cholesterol 7alpha-hydroxylase (Cyp7a1). In present study, we aimed to investigate the effect and the potential underlying mechanism of microRNA-96 (miR-96) on atherosclerosis development. The anti-atherosclerosis effects of a miR-96 inhibitor (miR-96i) were evaluated using ApoE KO mice fed a high-fat diet, which was treated with miR-96i for 8 weeks. The regulatory mechanism was revealed and validated by RNA-seq transcriptomics, quantitative PCR and western blotting analyses in hepatic cells. The authors identified that miR-96i significantly decreased serum cholesterol and bile acid levels and attenuated arterial plaque in mice. We further revealed that miR-96 regulated Cyp7a1 via a FOXO1-involved indirect pathway, in which miR-96 directly modulated FOXO1 in a posttranscriptional manner. A coordinated regulatory effect of miR-96 and miR-185 on FOXO1 was also observed. The full spectrum of mechanisms underlying the antiatherosclerotic activity beside miR-96-FOXO1-CYP7A1 axis remains to be elucidated. This study provides convincing evidence for the pivotal role of miR-96 in FOXO1 modulation and CYP7A1-involved cholesterol-bile acid metabolism, suggesting that miR-96 is a novel therapeutic target for the discovery and development of drugs against ACVD. Show less
no PDF DOI: 10.1080/14728222.2026.2620602
APOE

Potential profile and influencing factors of feedback-seeking behavior among nursing interns during the early stages of internships: a multicenter cross-sectional study.

Chuqin Xiong, Shuge Wang, Peiran Guo +6 more · 2026 · Frontiers in medicine · Frontiers · added 2026-04-24
Nursing interns often face maladjustment during the early stages of clinical practice, which not only directly affects their physical and mental health as well as work efficiency but also significantl Show more
Nursing interns often face maladjustment during the early stages of clinical practice, which not only directly affects their physical and mental health as well as work efficiency but also significantly inhibits their proactive feedback-seeking behavior (FSB). As an active self-regulation strategy, FSB can enhance interns' work initiative and promote role transition. However, existing research has yet to thoroughly investigate the potential heterogeneity and categorical characteristics of FSB within this population, and the role of psychological resources such as career adaptability in shaping these patterns requires further investigation. To investigate the status of FSB in early-stage nursing interns, identify latent subgroups via latent profile analysis (LPA), and analyze associated factors, thereby providing evidence for targeted clinical educational interventions. Multicenter cross-sectional research. This study employed a multistage stratified cluster sampling to survey 1,308 early-stage nursing interns from nine universities in Hubei, China, between June and September 2024. Data were collected using a demographic questionnaire, Feedback-Seeking Behavior Scale, and Career Adapt-Abilities Scale. LPA was employed to delineate FSB profiles and multivariate logistic regression analysis to examine the associated predictors. A total of 1,370 questionnaires were distributed, with 1,308 valid responses, yielding an effective response rate of 95.47%. The mean score on the feedback-seeking behavior scale was 5.06 ± 1.08. LPA identified three distinct feedback-seeking profiles: low (20.87%), moderate (38.3%), and high (40.83%). Education level, student cadre experience, internship hospital type, and career adaptability were significant predictors of profile membership ( FSB among early-stage nursing interns exhibited heterogeneity. Nursing educators and managers should implement tiered interventions: for the low and moderate feedback-seeking groups, career guidance and feedback awareness cultivation should be strengthened; for the high feedback-seeking group, peer modeling should be encouraged. This strategy can enhance proactive FSB, supports role transition and professional identity, and promotes long-term nursing workforce stability. Show less
📄 PDF DOI: 10.3389/fmed.2026.1664329
LPA

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

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

The OIP5 Antisense RNA 1/miR-30b-5p/RASA1 Axis Regulates Endothelial Senescence and Atherosclerosis Progression via Epigenetic Regulation.

Li Xiao, Xuejiao Men, Ping Liu +1 more · 2026 · Journal of biochemical and molecular toxicology · Wiley · added 2026-04-24
Atherosclerosis is a major cause of cardiovascular diseases, and endothelial cells (ECs) senescence plays a key role in its initiation and progression. This study investigates the function and epigene Show more
Atherosclerosis is a major cause of cardiovascular diseases, and endothelial cells (ECs) senescence plays a key role in its initiation and progression. This study investigates the function and epigenetic regulatory mechanisms of long non-coding RNA (lncRNA) OIP5 antisense RNA 1 (OIP5-AS1) in oxidized low-density lipoprotein (Ox-LDL)-induced senescence and atherosclerosis in human aortic endothelial cells (HAECs). The experiments show that Ox-LDL stimulation upregulates the expression of OIP5-AS1 and RASA1 while inhibiting miR-30b-5p. Silencing OIP5-AS1 significantly suppresses the expression of senescence-associated secretory phenotype (SASP) factors, alleviates HAECs senescence, and enhances proliferation, migration, and angiogenesis. Methylation-specific primers (MSP) and bisulfite-specific primers (BSP) analyses reveal that Ox-LDL stimulation activates OIP5-AS1 expression by reducing the DNA methylation level in its promoter region and altering histone modifications (increased H3K27ac and decreased H3K9me3). Luciferase assays show that OIP5-AS1 acts as a competing endogenous RNA (ceRNA) by binding to miR-30b-5p and upregulating RASA1. Animal experiments further confirm that the knockdown of OIP5-AS1 alleviates atherosclerosis in ApoE Show less
no PDF DOI: 10.1002/jbt.70714
APOE

Identifying Family Resilience Profiles in Chinese ASD Families: Associations With Social Support, Posttraumatic Growth and Family Stressors.

Ling-Rong Xiao, Si-Jin Liu, Jun-Ru Li +6 more · 2026 · Child: care, health and development · Blackwell Publishing · added 2026-04-24
Families with children diagnosed with autism spectrum disorder (ASD) often encounter significant challenges, manifesting in elevated stress levels and compromised physical and mental well-being. This Show more
Families with children diagnosed with autism spectrum disorder (ASD) often encounter significant challenges, manifesting in elevated stress levels and compromised physical and mental well-being. This study employed Latent Profile Analysis (LPA) to comprehensively examine family resilience attributes among 328 Chinese parents of children with ASD. Drawing on Walsh's family resilience framework and the Double ABCX stress-adaptation model, the research examined how protective factors (social support, posttraumatic growth) and risk factors (family stressors) distinctively characterize resilience profiles and predict profile membership, alongside sociodemographic correlates. Through rigorous statistical analysis, the following three distinct family resilience profiles emerged: adversity (32.31%; characterized by low resilience), ordinary (46.65%; demonstrating moderate resilience) and growth (21.03%; exhibiting high resilience). Critically, the findings revealed that higher family income, perceived social support and posttraumatic growth were associated with higher family resilience, while family stressors were associated with lower family resilience. These insights underscore the importance of developing targeted, personalized intervention strategies that can effectively enhance familial coping mechanisms and psychological adaptation for families navigating the complex challenges of ASD. Show less
no PDF DOI: 10.1111/cch.70222
LPA

A microglial LCN2-MC4R signaling axis drives silica-induced neuronal damage via C1q release.

Xia Li, Zihao Xie, Hangbing Cao +10 more · 2026 · Journal of neuroinflammation · BioMed Central · added 2026-04-24
Silica exposure precipitates irreversible lung injury; however, its long-term neurological sequelae—and the microglial mechanisms underlying these effects—remain poorly understood. Here, we demonstrat Show more
Silica exposure precipitates irreversible lung injury; however, its long-term neurological sequelae—and the microglial mechanisms underlying these effects—remain poorly understood. Here, we demonstrate that inhaled crystalline silica induces persistent hippocampal inflammation, anxiety- and depression-like behaviors, and neuronal loss in mice. Bulk RNA sequencing, immunophenotyping, and pharmacological depletion studies revealed that microglia are the primary source of complement C1q in silica-exposed brains. Mechanistically, silica-induced lipocalin-2 (LCN2) engages the melanocortin-4 receptor (MC4R) on microglia, activating a cAMP/PKA/NF-κB cascade that transcriptionally upregulates C1q. Pharmacological blockade of MC4R (using PF) abolished C1q overproduction, normalized brain-derived neurotrophic factor levels, and restored both synaptic integrity and behavioral performance. Our findings establish the LCN2–MC4R–C1q axis as a critical microglial pathway in silica-related neurotoxicity and identify MC4R antagonism as a promising, readily translatable intervention for occupational neuroinflammation. The online version contains supplementary material available at 10.1186/s12974-026-03695-5. Show less
📄 PDF DOI: 10.1186/s12974-026-03695-5
MC4R

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

[Research progress in signaling pathways involved in traditional Chinese medicine treatment of attention deficit hyperactivity disorder].

Xi-Yu Zhao, Zhen-Qi Wu, Tian-Yu Zhang +4 more · 2026 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
Attention deficit hyperactivity disorder(ADHD), a common neurodevelopmental disorder in children, is characterized by inattention, hyperactivity, and impulsivity. Epidemiological surveys show that the Show more
Attention deficit hyperactivity disorder(ADHD), a common neurodevelopmental disorder in children, is characterized by inattention, hyperactivity, and impulsivity. Epidemiological surveys show that the prevalence of ADHD in children is gradually increasing worldwide, and it is the most common childhood mental disorder in China. Because of the complex clinical symptoms, multiple co-morbidities, and unknown etiology, ADHD has far-reaching negative impacts on individuals, families, and the society. Behavioral interventions, as a pillar in the management of ADHD, play a targeted role in improving children's social functioning, with significant benefits supported by evidence. However, they are constrained by uneven resources, poor compliance, and insufficient continuity, Western medicine has multiple adverse effects and unclear long-term effects in the treatment of ADHD despite the definite efficacy. Accordingly, there is an urgent need to find safe and effective therapies suitable for children. With a holistic view and treatment based on syndrome differentiation, traditional Chinese medicine(TCM) has significant advantages in treating ADHD via multiple targets, which involves dopamine(DA), norepinephrine(NE), 5-hydroxytryptamine(5-HT), cyclic adenosine monophosphate(cAMP), brain-derived neurotrophic factor(BDNF) and other signaling pathways. Through these pathways, TCM can treat ADHD through the regulation of neurotransmitters, enhancement of prefrontal and striatal functions, enhancement of neuronal protection, attenuation of neuroinflammation, and reduction of neuronal apoptosis. However, a systematic study remains to be conducted. This paper summarizes the signaling pathways related to the treatment of ADHD by TCM in the past two decades, aiming to provide reference for delving into the mechanism and exploring effective TCM prescriptions for ADHD in children and to give full play to the advantages of the efficacy and characteristics of TCM. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20251010.203
BDNF attention deficit hyperactivity disorder child mental disorder epidemiology neurodevelopmental disorder neuroscience signaling pathways traditional chinese medicine

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

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