👤 Zijing J Liu

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3182
Articles
1983
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Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaowei Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, Yajuan Liu, Yaling Liu, Yalu Liu, Yan Liu, Yan-Li Liu, Yanan Liu, Yanchao Liu, Yanchen Liu, Yandong Liu, Yanfei Liu, Yanfen Liu, Yanfeng Liu, Yang Liu, Yange Liu, Yangfan Liu, Yangfan P Liu, Yangjun Liu, Yangkai Liu, Yangruiyu Liu, Yangyang Liu, Yanhong Liu, Yanhua Liu, Yanhui Liu, Yanjie Liu, Yanju Liu, Yanjun Liu, Yankuo Liu, Yanli Liu, Yanliang Liu, Yanling Liu, Yanman Liu, Yanmin Liu, Yanping Liu, Yanqing Liu, Yanqiu Liu, Yanquan Liu, Yanru Liu, Yansheng Liu, Yansong Liu, Yanting Liu, Yanwu Liu, Yanxiao Liu, Yanyan Liu, Yanyao Liu, Yanying Liu, Yanyun Liu, Yao Liu, Yao-Hui Liu, Yaobo Liu, Yaoquan Liu, Yaou Liu, Yaowen Liu, Yaoyao Liu, Yaozhong Liu, Yaping Liu, Yaqiong Liu, Yarong Liu, Yaru Liu, Yating Liu, Yaxin Liu, Ye Liu, Ye-Dan Liu, Yehai Liu, Yen-Chen Liu, Yen-Chun Liu, Yen-Nien Liu, Yeqing Liu, Yi Liu, Yi-Chang Liu, Yi-Chien Liu, Yi-Han Liu, Yi-Hung Liu, Yi-Jia Liu, Yi-Ling Liu, Yi-Meng Liu, Yi-Ming Liu, Yi-Yun Liu, Yi-Zhang Liu, YiRan Liu, Yibin Liu, Yibing Liu, Yicun Liu, Yidan Liu, Yidong Liu, Yifan Liu, Yifu Liu, Yihao Liu, Yiheng Liu, Yihui Liu, Yijing Liu, Yilei Liu, Yili Liu, Yilin Liu, Yimei Liu, Yiming Liu, Yin Liu, Yin-Ping Liu, Yinchu Liu, Yinfang Liu, Ying Liu, Ying Poi Liu, Yingchun Liu, Yinghua Liu, Yinghuan Liu, Yinghui Liu, Yingjun Liu, Yingli Liu, Yingwei Liu, Yingxia Liu, Yingyan Liu, Yingyi Liu, Yingying Liu, Yingzi Liu, Yinhe Liu, Yinhui Liu, Yining Liu, Yinjiang Liu, Yinping Liu, Yinuo Liu, Yiping Liu, Yiqing Liu, Yitian Liu, Yiting Liu, Yitong Liu, Yiwei Liu, Yiwen Liu, Yixiang Liu, Yixiao Liu, Yixuan Liu, Yiyang Liu, Yiyi Liu, Yiyuan Liu, Yiyun Liu, Yizhi Liu, Yizhuo Liu, Yong Liu, Yong Mei Liu, Yong-Chao Liu, Yong-Hong Liu, Yong-Jian Liu, Yong-Jun Liu, Yong-Tai Liu, Yong-da Liu, Yongchao Liu, Yonggang Liu, Yonggao Liu, Yonghong Liu, Yonghua Liu, Yongjian Liu, Yongjie Liu, Yongjun Liu, Yongli Liu, Yongmei Liu, Yongming Liu, 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, 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

GraphBAN-based identification of active ingredients and key gene targets in compound Chinese herbal medicines for polycystic ovary syndrome.

Shiyang Wei, Ting Qin, Ying Li +4 more · 2026 · Naunyn-Schmiedeberg's archives of pharmacology · Springer · added 2026-04-24
While active ingredients from compound Chinese herbal medicines (CCHMs) have demonstrated potential in alleviating symptoms of polycystic ovary syndrome (PCOS), their mechanisms of action remain insuf Show more
While active ingredients from compound Chinese herbal medicines (CCHMs) have demonstrated potential in alleviating symptoms of polycystic ovary syndrome (PCOS), their mechanisms of action remain insufficiently understood. This study aimed to identify key active ingredients and gene targets in Xiaochaihu Decoction, Sijunzi Decoction, and Shensiwei that contribute to their efficacy against PCOS. Transcriptomic data of PCOS were obtained from public databases. Information on gut microbiota metabolite-related targets and active ingredients of CCHMs was retrieved from relevant databases. Key gene targets and active ingredients were identified using Graph-based Bioactive Network Analysis (GraphBAN) and toxicological assessments. Molecular docking and dynamic simulations were conducted to validate interactions. Functional enrichment and regulatory network analysis were performed. LCT, FADS1, and CYP11A1 were identified as key genes associated with α-β T cell activation, immune receptor signaling, and adaptive immune responses. LCT and FADS1 were targeted by linolenic acid, while CYP11A1 was regulated by mandenol, EIC, and linolenic acid. Three microRNAs (hsa-miR-320a-3p, hsa-miR-4487, hsa-miR-6090) co-regulated these genes. Molecular docking and dynamics simulations confirmed stable binding between key genes and active ingredients, with binding energies < -5.0 kcal/mol. The findings indicate that CCHMs exert therapeutic effects on PCOS by multi-target regulation of key genes involved in androgen synthesis, metabolic regulation, and immune-inflammatory activation. The observed strong binding affinities provide a structural basis for these interactions. This study identified three key genes and three core active ingredients in CCHMs for PCOS treatment, laying a theoretical foundation for developing multi-target therapeutics. Show less
📄 PDF DOI: 10.1007/s00210-025-04970-7
FADS1

Replacing sedentary behaviour with physical activity and all-cause mortality in older adults: two-cohort study in China and the UK.

Huan Huang, Zhaojun Chen, Jiong Liu +4 more · 2026 · Journal of epidemiology and community health · added 2026-04-24
Older adults typically have higher sedentary behaviour (SB) and lower physical activity (PA) than younger adults. Studies on replacing SB with PA in relation to all-cause mortality in racially diverse Show more
Older adults typically have higher sedentary behaviour (SB) and lower physical activity (PA) than younger adults. Studies on replacing SB with PA in relation to all-cause mortality in racially diverse older adults remain limited. This study included 122 966 older adults from the China Kadoorie Biobank (CKB) and 207 212 older adults from the UK Biobank (UKB). SB and PA were assessed using baseline questionnaires, with PA classified as light (LPA), moderate (MPA) or vigorous (VPA) based on metabolic equivalents. Cox proportional hazards models and isotemporal substitution models were used to examine the associations between replacing SB with different PA intensities and all-cause mortality. Longer SB (per 30 min/day increase) was associated with a higher risk of all-cause mortality in both cohorts (CKB: HR 1.013, 95% CI 1.010 to 1.017; UKB: HR 1.012, 95% CI 1.009 to 1.015). PA of any intensity was associated with a reduced risk of all-cause mortality. In the CKB, replacing 30 min/day of SB with an equivalent duration of PA showed comparable protective associations (LPA: HR 0.963, 95% CI 0.958 to 0.968; MPA: HR 0.967, 95% CI 0.961 to 0.972; VPA: HR 0.965, 95% CI 0.960 to 0.971). In the UKB, replacing 30 min/day of SB with VPA was associated with the largest reduction in mortality risk (HR: 0.950, 95% CI 0.931 to 0.970). Replacing SB with PA of any intensity was associated with reduced all-cause mortality risk in older adults, with variations across populations. These findings highlight the need for population-specific PA recommendations to promote healthy ageing. Show less
no PDF DOI: 10.1136/jech-2025-225695
LPA

DPP-4 inhibitors for preventing post-stroke cognitive impairment in diabetic patients with acute ischemic stroke: a retrospective cohort study.

Hongran Fu, Jianfang Liu, Jie Wu +1 more · 2026 · American journal of translational research · added 2026-04-24
To evaluate the preventive effect of dipeptidyl peptidase-4 inhibitors (DPP-4i) on post-stroke cognitive impairment (PSCI) in patients with type 2 diabetes mellitus (T2DM) and concurrent acute ischemi Show more
To evaluate the preventive effect of dipeptidyl peptidase-4 inhibitors (DPP-4i) on post-stroke cognitive impairment (PSCI) in patients with type 2 diabetes mellitus (T2DM) and concurrent acute ischemic stroke (AIS). A retrospective cohort study was conducted on 236 patients with T2DM+AIS recruited from April 2021 to October 2024. Patients were grouped based on DPP-4i use: an observation group (107 cases) with DPP-4i therapy and a control group (129 cases) without. Patients' baseline demographics, clinical features, laboratory indices, and follow-up data were extracted from the electronic medical record system. The primary outcome measure was the incidence of PSCI, defined as a Montreal Cognitive Assessment Scale (MoCA) score <26 at six months after AIS. Secondary outcomes included inflammatory cytokines, oxidative stress markers, neuroprotective factors (BDNF), glycemic metabolism indicators, and life quality [Barthel Index (BI), Functional Independence Measure (FIM), and Instrumental Activities of Daily Living (IADL)]. At 6 months after AIS, the incidence of PSCI was significantly lower in the observation group than in the control group (P<0.05). Furthermore, inflammatory and oxidative stress marker levels were decreased whereas BDNF level was significantly elevated in the observation group compared to the control group (all P<0.05). According to the quality-of-life assessment, patients receiving DPP-4i had higher BI, FIM, and IADL scores (P<0.05), along with a lower all-cause readmission rate (P<0.05). Subgroup analysis indicated that different DPP-4i types (e.g., sitagliptin, saxagliptin) had consistent cognitive protective effects (P>0.05). DPP-4i can lower PSCI risk in T2DM+AIS patients. Its mechanism involves multi-dimensional effects like anti-inflammation, anti-oxidation, insulin sensitivity enhancement, and neuroprotection. Show less
no PDF DOI: 10.62347/PLKN4994
BDNF cognitive impairment diabetes dpd-4 inhibitors ischemic stroke post-stroke cognitive impairment stroke type 2 diabetes

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

Fear of progression and association factors in stroke patients: a latent profile analysis.

Yunyun Liu, Xiangrui Li, Ting Zhao +9 more · 2026 · Frontiers in psychology · Frontiers · added 2026-04-24
Fear of progression (FoP) is a prevalent psychological issue among stroke patients. Previous studies failing to distinguish characteristics of patient groups with varying FoP levels. Latent profile an Show more
Fear of progression (FoP) is a prevalent psychological issue among stroke patients. Previous studies failing to distinguish characteristics of patient groups with varying FoP levels. Latent profile analysis (LPA) classifies individuals into distinct subgroups via continuous FoP indicators, boosting classification accuracy by accounting for variable uncertainty. Given FoP's heterogeneity, investigating FoP profiles and their influencing factors in stroke patients is clinically significant for personalized psychological care and improved patient quality of life. A total of 366 stroke patients were selected as study subjects through convenience sampling, and a cross-sectional survey was conducted. FoP was assessed using the Fear of Progression Questionnaire-Short Form (FoP-Q-SF, 2 dimensions, 12 items). Independent variables included demographic characteristics, clinical indicators, the Recurrence Risk Perception Scale for Stroke patients (RRPSS), and the Medical Coping Modes Questionnaire (MCMQ). LPA was performed on the FoP-Q-SF items to identify subgroups. The R3STEP method was used to analyze influencing factors of subgroup membership, and the BCH method was applied to compare differences in distal outcomes across subgroups. Statistical significance was set at The study sample had a mean age of 63.93 ± 10.58 years, with 70.5% males and 65.0% first-ever stroke patients. Two latent profiles were identified: Low-FoP Adaptive Type (C1, 48.6%) and High-FoP Sustained Type (C2, 51.4%). The R3STEP showed that age 18-59 years (OR = 0.476, 95%CI = 0.245-0.924, This study revealed significant heterogeneity in FoP among stroke patients. Age, hypertension comorbidity, excessive recurrence risk perception, MCMQ-confrontation, and MCMQ-avoidance were associated with high FoP. Healthcare providers should prioritize identifying high-risk individuals and develop tailored interventions to reduce FoP and improve rehabilitation outcomes. Show less
📄 PDF DOI: 10.3389/fpsyg.2026.1741344
LPA

Unraveling the shared genetic architecture of osteoarthritis and metabolic traits through multi-omics insights.

Binzhi Liao, Yumeng Mu, Mengliang Luo +8 more · 2026 · Osteoarthritis and cartilage · Elsevier · added 2026-04-24
Osteoarthritis (OA) often coexists with metabolic traits (MTs), causing significant disability. Our study aims to uncover the shared genetic mechanisms between OA and MTs, revealing novel OA-MT relate Show more
Osteoarthritis (OA) often coexists with metabolic traits (MTs), causing significant disability. Our study aims to uncover the shared genetic mechanisms between OA and MTs, revealing novel OA-MT related genes, proteins and pathways. We first explored the clinical associations between OA and MTs based on UK Biobank data. Using GWAS statistics for 9 OA subtypes and 51 MTs, we identified both global and regional genetic correlations. Multi-trait GWAS helped revealed credible genes and relevant pathways through various methods. Protein-level analyses were also conducted to identify key proteins. We developed polygenic scores (PGS), machine learning models and drug repurposing strategies were explored to translate these findings into clinical applications. We identified 152 trait pairs with significant associations and 709 local regions linked to OA-MT. Key SNVs like rs13135092 (SLC39A8) and rs34811474 (ANAPC4) were associated with multiple OA-MT pairs. Lipid and glucose metabolism emerged as central pathways, with tissue-specific enrichment analyses revealing key gene clusters in hepatocytes, arteries, and brain regions. Protein-level analyses identified 205 protein subgroups. PGS integrating MTs outperformed model based solely on OA, improving AUC by 17.5%. Causal gene-based models showed strong diagnostic accuracy (average AUC = 0.875 in external cohorts). Drug prediction highlighted fenofibrate as a promising treatment among 71 candidates. This study provides new insights into the genetic links between OA and MTs. We identified genes, proteins, and pathways related to comorbidities, revealing shared mechanisms, highlighting the potential of integrating metabolic factors to improve OA prediction, diagnosis, and treatment. Show less
no PDF DOI: 10.1016/j.joca.2025.10.010
ANAPC4

Lecanemab treatment for mild alzheimer's disease with high risk of cerebral hemorrhage: a case report.

Qi Tian, Mengqi Liu, Fuxin Zhong +2 more · 2026 · BMC neurology · BioMed Central · added 2026-04-24
Lecanemab has been approved for the treatment of mild cognitive impairment due to Alzheimer's disease (AD) and mild AD dementia based on the efficacy in slowing cognitive decline and preliminary safet Show more
Lecanemab has been approved for the treatment of mild cognitive impairment due to Alzheimer's disease (AD) and mild AD dementia based on the efficacy in slowing cognitive decline and preliminary safety data from the phase Ⅲ Clarity AD trial. However, this trial excluded patients with high risk of cerebral hemorrhage, such as individuals with intracranial aneurysms or > 4 microhemorrhages. A 70-year-old male with mild AD, intracranial aneurysm, microhemorrhages, and APOE ε3/ε4 genotype received lecanemab after multidisciplinary evaluation and informed consent. Over six months of intensive monitoring, cognitive function stabilized with no deterioration, daily activities were preserved, microhemorrhages remained stable (with one new small lesion noted at 3 months), and no aneurysm rupture or severe adverse events (including amyloid-related imaging abnormalities) occurred. This case suggests that, despite hemorrhage risks, lecanemab may have a manageable risk-benefit profile in selected real-world AD patients under intensive monitoring and multidisciplinary care, with its application beyond clinical trial criteria requiring more nuanced and individualized consideration. Show less
📄 PDF DOI: 10.1186/s12883-025-04581-y
APOE

RT-ICI therapy induces a distal immunometabolic axis that shapes systemic macrophage polarization and enhances local T cell immunity.

Yizhi Ge, Haitao Liu, Jiayi Shen +4 more · 2026 · Cell communication and signaling : CCS · BioMed Central · added 2026-04-24
Colorectal cancer (CRC) liver metastases remain refractory to immunotherapy due to a profoundly immunosuppressive tumor microenvironment. Here, we conducted a prospective clinical study enrolling 18 p Show more
Colorectal cancer (CRC) liver metastases remain refractory to immunotherapy due to a profoundly immunosuppressive tumor microenvironment. Here, we conducted a prospective clinical study enrolling 18 patients with microsatellite-stable CRC liver metastases treated with high-dose radiotherapy (RT) followed by anti–PD-1 immune checkpoint inhibitors (RT–ICI). Integrative analysis of single-cell RNA-sequencing, spatial transcriptomics, and peripheral immune profiling revealed that RT–ICI therapy reprograms both tumor-intrinsic and immune compartments. RT triggered the emergence of an APOA2⁺ tumor cell state characterized by enhanced lipid metabolic activity and transient elevation of circulating HDL. This metabolic reprogramming, in turn, promoted systemic activation of CETP⁺ M2-like macrophages, a population marked by high LXR/RXR transcriptional activity and enriched expression of immunosuppressive and lipid-processing genes. Despite their expansion, CETP⁺ macrophages localized preferentially to non-irradiated tumor regions, suggesting a distal immunometabolic effect driven by HDL-mediated signaling. Concurrently, combination therapy expanded GZMB⁺ effector T cells and induced a novel population of inflammatory–toxic T cells (IT_T), which exhibited high cytotoxicity and spatial co-localization with CXCL10⁺ macrophages. Ligand–receptor analysis and pseudotime modeling revealed that irradiated tumor cells acted as “in situ vaccines” by enhancing MHC–TCR interactions and promoting T cell differentiation along non-exhausted cytotoxic lineages. Together, these findings reveal a dual mechanism by which RT–ICI therapy enhances local anti-tumor immunity while modulating systemic lipid metabolism and macrophage polarization, offering insights for combinatorial immunotherapy design in immunologically “cold” tumors. The online version contains supplementary material available at 10.1186/s12964-026-02689-3. Show less
📄 PDF DOI: 10.1186/s12964-026-02689-3
CETP

IGF2BP3/m6A-mediated intron retention isoform of DUSP6 promotes cisplatin resistance in nasopharyngeal carcinoma by inhibiting pyroptosis.

Xiaochen Li, XiaoMei Sun, Qingyu Gu +2 more · 2026 · BMC cancer · BioMed Central · added 2026-04-24
Nasopharyngeal carcinoma (NPC) is a complicated pathological cancer, which has a close association with pyroptosis and abnormal alternative splicing (AS). However, the molecular changes and functions Show more
Nasopharyngeal carcinoma (NPC) is a complicated pathological cancer, which has a close association with pyroptosis and abnormal alternative splicing (AS). However, the molecular changes and functions of AS-mediated pyroptosis in cisplatin-resistant NPC cells remain poorly understood. The expression patterns of different splicing isomers of dual-specificity phosphatase 6 (DUSP6) were evaluated by semi-quantitative PCR. The effects of DUSP6 knockdown on cisplatin sensitivity and pyroptosis in NPC were examined by CCK-8 assay, immunofluorescence and ELISA. The occurrence mechanism of DUSP6 AS was explored by RNA pull down, mass spectrometry and MeRIP-PCR. DUSP6 underwent AS, among which the intron retention isoform DUSp6-IR1 increased in expression dependent on the dose and time of cisplatin. Knockdown of DUSP6-IR1 significantly suppressed viability and cisplatin resistance and promoted apoptosis of C666-1 cells upon cisplatin treatment. In vivo, sh-DUSP6-IR1 reduced the weight and volume of tumors. While DUSP6-IR1 knockdown in C666-1 cells enhanced pyroptosis (evidenced by elevated LDH release, Gasdermin D (GSDMD)/NOD-like receptor thermal protein domain associated protein 3 (NLRP3) expression, and IL-18/IL-1β levels, along with reduced cell viability), these effects were reversed by a pyroptosis inhibitor. The m6A reader protein insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) enhanced the splicing generation of the DUSP6-IR1 isoform through its KH3-4 domains, thereby suppressing pyroptosis in NPC cells and ultimately conferring cisplatin resistance. These findings revealed a promising novel direction to investigate cisplatin resistance and suggested potential therapeutic target for overcoming chemotherapy resistance in NPC. The online version contains supplementary material available at 10.1186/s12885-025-15337-9. Show less
📄 PDF DOI: 10.1186/s12885-025-15337-9
DUSP6

Exosome Cargo Molecules and NLRP3/BDNF: Clinical and Preclinical Evidence for Acupuncture-Mediated Spinal Cord Injury Recovery.

Yongliang Wang, Jian Zhang, Jinsheng Liu +3 more · 2026 · International journal of general medicine · added 2026-04-24
Validate the clinical utility of exosome cargo (miRNAs/proteins) and NLRP3/BDNF as key regulatory molecules for acupuncture-mediated spinal cord injury (SCI) recovery. From the establishment of the da Show more
Validate the clinical utility of exosome cargo (miRNAs/proteins) and NLRP3/BDNF as key regulatory molecules for acupuncture-mediated spinal cord injury (SCI) recovery. From the establishment of the database to May 2025, a literature search was conducted on PubMed, and Embase, using keywords ["exosome cargo" or "exosome"], ["acupuncture" or "acupuncture and moxibustion" or "electroacupuncture" or "EA"], ["spinal cord injury" or "SCI"], ["immune regulation"], ["inflammatory reaction"], ["neuroregeneration" or "nerve"]. Including peer-reviewed studies on human/animal models, articles that do not meet the requirements are excluded. Preclinically, MSC-exosomal miR-145-5p suppressed TLR4/NF-κB signaling, reducing spinal IL-1β by 47% in SD rats. Schwann cell-exosomal MFG-E8 activated SOCS3/STAT3, increasing M2 macrophage CD206 by 63% and raising rat BBB scores by 3.8 points; Treg-exosomal miR-2861 upregulated tight junction proteins (occludin/ZO-1) to repair the blood-spinal cord barrier. Acupuncture (EA at GV14/GV4) upregulated spinal BDNF by 72% and NGF by 58% via Wnt/β-catenin, while EA at GV6/GV9 downregulated NLRP3 by 42-58% and TNF-α by 35-47%. Clinically, EA at EX-B2 increased ASIA scores by 3.2±1.1 points (Guo et al). Besides, 5x/week EA improved ASIA vs 3x/week (+6.4 points). EA+exercise reduced MAS by 1.6-2.9 points, with outcomes correlated to peripheral NLRP3 reduction, BDNF elevation, and MBI/WISCIII increases. Exosome cargo (miR-145-5p/MFG-E8) and NLRP3/BDNF are key regulatory molecules underlying acupuncture-mediated SCI recovery. However, limitations (small RCT samples, heterogeneous acupuncture protocols, unstandardized exosome isolation) hinder translation. Future work should focus on standardized biomarker detection, exosome engineering, and large-scale clinical trials. Show less
📄 PDF DOI: 10.2147/IJGM.S595567
BDNF

[Influences of aged male parents on learning ability of offspring in SD rats and intervention effect of Wuzi Yanzong Pills based on miR-34a-5p/SIRT1 signaling pathway].

Zi-Hao Liu, Min Xiao, Xiao-Cui Jiang +4 more · 2026 · Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica · added 2026-04-24
This study aims to investigate the effects of aged male parents on the learning ability of offspring and the intervention effect of Wuzi Yanzong Pills based on the microRNA-34a-5p(miR-34a-5p)/silent i Show more
This study aims to investigate the effects of aged male parents on the learning ability of offspring and the intervention effect of Wuzi Yanzong Pills based on the microRNA-34a-5p(miR-34a-5p)/silent information regulator 1(SIRT1) signaling pathway. Thirty-two SD male rats of 15 months old were randomized into aged model, model+high-dose(8 g·kg~(-1)) Wuzi Yanzong Pills, model+low-dose(2 g·kg~(-1)) Wuzi Yanzong Pills, and model+vitamin C(100 mg·kg~(-1)) groups(n=8). In addition, 8 SD male rats of 3 months old were selected as the control group. Rats in treatment groups were fed the diets containing different doses of Wuzi Yanzong Pills or vitamin C, and the control and model groups received a regular diet for 12 weeks. After 5 days of co-caging with 3-month-old female mice, the fertilization rate was recorded. An automated sperm analyzer was used to examine the sperm motility and count, and the testicular spermatogenesis was assessed by hematoxylin-eosin staining. The senescence cells in the testicular tissue was detected by β-galactosidase staining, and miR-34a-5p expression was quantified via qPCR. The litter size was counted, and the body mass and body length were measured on days 1 and 30 to assess offspring development. For the offspring of 30 days old, their learning ability was examined via Morris water maze, and Nissl staining was employed to count hippocampal neurons. The miR-34a-5p expression in the hippocampal tissue of the offspring was determined by qPCR, and the protein levels of brain-derived neurotrophic factor(BDNF) and SIRT1 were determined by Western blot. Compared with the control group, the model group exhibited reductions in fertility rate, litter size, and sperm motility and count, as well as impaired testicular spermatogenesis(P<0.01). In addition, the model group showed increased senescence cells in testicular and epididymal tissue, accompanied by elevated miR-34a-5p expression in sperms. The 30-day-old offspring showed slow growth, reduced hippocampal neurons, up-regulated miR-34a-5p expression, and down-regulated protein levels of SIRT1 and BDNF in the hippocampus(P<0.01), along with impaired learning and memory performance(P<0.01). Compared with the model group, both high-dose Wuzi Yanzong Pills and vitamin C improved the fertilization rate, litter size, sperm motility, sperm count, and testicular spermatogenesis(P<0.05). The 30-day-old offspring in the two groups showed accelerated growth and development, increased hippocampal neurons, and elevated BDNF protein level in the hippocampus(P<0.05), along with enhanced learning and memory capabilities(P<0.05). Compared with the vitamin C group, the high-dose Wuzi Yanzong Pills group exhibited accelerated offspring growth(P<0.05), increases in fertilization rate and litter size(P<0.05), and improved learning and memory abilities(P<0.05). These findings indicate that Wuzi Yanzong Pills can improve testicular spermatogenesis and sperm quality in aged rats, thereby enhancing offspring's learning and memory performance. Specifically, Wuzi Yanzong Pills regulate miR-34a-5p expression to delay spermatogenic cell senescence in the testicular tissue and improve the offspring's cognitive function by miR-34a-5p mediated intergenerational transmission. Show less
no PDF DOI: 10.19540/j.cnki.cjcmm.20250916.801
BDNF intervention learning ability microrna mir-34a-5p rats signaling pathway sirt1

Agrin as a Stable Biomarker for Muscle Strength Decline in Elderly Sarcopenic Patients Associated with Neuromuscular Junction Dysfunction.

Jihai Chen, Nuo Cheng, Ye Liu +4 more · 2026 · Rejuvenation research · SAGE Publications · added 2026-04-24
Agrin-mediated neuromuscular junction (NMJ) morphological alterations is one of the main pathogeneses of sarcopenia. The aim of this study was to observe the changes in serum agrin in patients with di Show more
Agrin-mediated neuromuscular junction (NMJ) morphological alterations is one of the main pathogeneses of sarcopenia. The aim of this study was to observe the changes in serum agrin in patients with different degrees of sarcopenia and the alterations in Agrin receptors in human skeletal muscle with age. A total of 236 elderly subjects were enrolled and categorized into nonsarcopenia, possible sarcopenia, sarcopenia, and severe sarcopenia groups. Serum levels of the C-terminal Agrin fragment were quantified using an Enzyme-Linked Immunosorbent Assay (ELISA) kit. In addition, in a distinct and smaller exploratory subgroup ( Show less
no PDF DOI: 10.1177/15491684251410100
RAPSN

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

Associations between physical activity parameters and multidimensional trajectories of muscle health in middle-aged and older adults: a group-based multi-trajectory modeling study.

Dongxue Liu, Yihan Pan, Hairong Wang +1 more · 2026 · Journal of exercise science and fitness · Elsevier · added 2026-04-24
This study used a group-based multi-trajectory model (GBMTM) to identify distinct muscle health trajectories and examine their associations with physical activity (PA) in middle-aged and older adults. Show more
This study used a group-based multi-trajectory model (GBMTM) to identify distinct muscle health trajectories and examine their associations with physical activity (PA) in middle-aged and older adults. Data were obtained from 2818 middle-aged and older adults (aged ≥40 years) in the China Health and Retirement Longitudinal Study (2011-2015). Muscle health was assessed using muscle mass (appendicular skeletal muscle mass index), muscle strength (handgrip strength), and physical performance (5-time chair stand test). PA was assessed using the International Physical Activity Questionnaire Short Form. A GBMTM was applied to jointly identify longitudinal trajectories of muscle mass, muscle strength, and physical performance, and to evaluate their associations with PA. In this study, four muscle health trajectories were identified: low-function declining, moderate-function declining, moderate-function stable, and high-function stable group. Engaging in ≥150 min/wk of light PA (LPA), moderate PA (MPA), or vigorous PA (VPA) was associated with the moderate-function stable group (LPA: aOR = 3.44, 95% CI: 1.94 - 6.11; MPA: aOR = 2.83, 95% CI: 1.67 - 4.96; VPA: aOR = 2.88, 95% CI: 1.61 - 5.13) and the high-function stable group (LPA: aOR = 5.20, 95% CI: 2.44 - 11.19; MPA: aOR = 4.10, 95% CI: 1.92 - 8.73; VPA: aOR = 3.42, 95% CI: 1.55 - 8.55). In older adults aged ≥70 years, associations persisted for MPA and VPA. Distinct muscle health trajectories highlight individualized muscle aging and inform personalized PA guidance. Regular PA ≥150 min/wk across intensities was associated with more favorable longitudinal muscle health. Show less
📄 PDF DOI: 10.1016/j.jesf.2026.200462
LPA

TrkB promotes the neuronal secretion of soluble Siglec-2 (CD22) to mitigate microglial activation and alleviate depression-like behaviors in male mice.

Xin Shi, Shi-Zhong Cai, Jin-Long Chai +5 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Microglia-neuron contacts have been shown to regulate neural network activity through the formation and elimination of synapses. The pathogenesis of major depressive disorder is accompanied by a decli Show more
Microglia-neuron contacts have been shown to regulate neural network activity through the formation and elimination of synapses. The pathogenesis of major depressive disorder is accompanied by a decline in brain-derived neurotrophic factor (BDNF) signaling, associated with increased microglia activity that disrupts cognitive function. The actions of both typical and rapid-acting antidepressant drugs, which have been shown to increase BDNF signaling through the tropomyosin receptor kinase B (TrkB) receptor, decrease microglia activation and the levels of pro-inflammatory cytokines. Examining the link between BDNF signaling and the microglial pro-inflammatory response, we demonstrate that TrkB signaling elicits the neuronal secretion of CD22 (Siglec-2), a sialic acid-binding immunoglobulin-type lectin, to inhibit microglial activation and alleviate depression-like symptoms. In a male chronic mild stress (CMS) mouse model of depression decreased expression of the postsynaptic scaffolding protein PSD-95 and Gαi1/3 were found to compromise TrkB signaling leading to reduced CD22 levels in hippocampal tissue. Restoration of TrkB-Gαi1/3-Akt signaling with dSyn3, a peptidomimetic compound targeting the PDZ3 domain of PSD-95, enhanced CD22 expression to inhibit microglial activation, promote dendritic spine formation and rapidly mitigate depression-like symptoms. Furthermore, hippocampal overexpression of CD22 in neurons was sufficient to reduce microglial activation and depressive-like behaviors in male CMS mice. S-ketamine, a rapid-acting antidepressant, increased CD22 expression to mitigate depression-like symptoms. While neuronal knockdown of CD22 in the hippocampus did not significantly impair the rapid (within 4 h) antidepressant effects typically observed with S-ketamine or dSyn3 administration, strikingly, knockdown of CD22 attenuated the long-acting (within 3 days) antidepressant effects of S-ketamine or dSyn3, as evidenced by sustained immobility in the TST (tail suspension test) and FST (forced swim test), and a lack of improvement in sucrose preference. In contrast, a single dose of fluoxetine failed to increase CD22 expression or inhibit microglia activity. These results suggest that rapidly-acting anti-depressant drugs enhance TrkB-induced neuronal expression and secretion of CD22 to promote the homeostatic state of microglia required for antidepressant actions. In male depression mice, dSyn3 facilitates BDNF-induced TrkB-PSD-95-Gαi1/3 complex formation to increase Akt-mTOR activation as well as synaptic and spine density in the hippocampus. TrkB signaling increases CD22 expression and secretion from neurons blocking microglial activation in the hippocampal region of male CMS mice. Show less
📄 PDF DOI: 10.1038/s41380-026-03575-7
BDNF

Effect and mechanism of compound Nujia honey paste on chronic unpredictable mild stress (CUMS) depression rats based on network pharmacology analysis.

Shaowei Fu, Mahinur Bakri, Xueying Lu +3 more · 2026 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Compound Nujia honey paste (Nujia), a classic formulation from Traditional Uyghur Medicine, has been historically used for depression treatment and is listed in the Catalog of Ancient Classical Famous Show more
Compound Nujia honey paste (Nujia), a classic formulation from Traditional Uyghur Medicine, has been historically used for depression treatment and is listed in the Catalog of Ancient Classical Famous Formulas issued by the National Administration of Traditional Chinese Medicine and the National Medical Products Administration. Clarifying its pharmacodynamic material basis is essential for understanding its efficacy, yet this remains incompletely characterized. This study aimed to systematically elucidate Nujia's antidepressant efficacy and mechanisms by combining chemical analysis, computational prediction, and experimental validation in a CUMS rat model, providing a comprehensive approach to understanding its action. This study employed LC/MS to analyze the chemical constituents and blood-absorbed compounds of Nujia. This was combined with network pharmacology and molecular docking to predict and verify its potential antidepressant targets and signaling pathways. Using behavioral tests, ELISA, histopathology, Western blot, and qRT-PCR in a CUMS rat model, the research thoroughly evaluated Nujia's therapeutic effects and mechanisms, fostering trust in the findings. In this study, LC/MS analysis identified 124 chemical constituents from Nujia, and further analysis determined 26 blood-absorbed compounds (including 10 prototype compounds). Network pharmacology analysis revealed that its potential antidepressant effects are closely associated with core targets such as AKT1 and TNF, a prediction subsequently verified by molecular docking results. In the CUMS-induced rat model of depression, intervention with Nujia significantly ameliorated depression-like behaviors in the animals and alleviated neuropathological damage in the hippocampus and prefrontal cortex. Mechanistic investigations revealed that Nujia upregulated the levels of monoamine neurotransmitters (5-HT, DA, NE) and neurotrophic factors (BDNF, NGF) in serum, while downregulating the expression of pro-inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-18). Further molecular experiments confirmed that Nujia likely mitigates neuroinflammation by inhibiting the TNF-α/NF-κB signaling pathway, and inhibits neuronal apoptosis by activating the PI3K/AKT signaling pathway and its downstream anti-apoptotic proteins. Furthermore, Nujia significantly upregulated the expression of key synaptic plasticity proteins (SYP, GAP43, and PSD95) in hippocampal tissue, thereby enhancing synaptic structure and function. These findings underscore the complex, multi-target mechanisms underlying Nujia's antidepressant effects, encouraging further exploration of its therapeutic potential. This study systematically elucidates that Nujia achieves its antidepressant therapeutic effects by mediating multi-pathway synergistic actions, including but not limited to the TNF-α/NF-κB and PI3K/AKT signaling pathways, to ameliorate neuroinflammation, attenuate apoptosis, and enhance synaptic plasticity. Show less
no PDF DOI: 10.1016/j.jep.2026.121518
BDNF chronic unpredictable mild stress cums depression network pharmacology pharmacology stress traditional chinese medicine

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

TRIM47 Promotes Atherosclerosis by Activating NF-κB Signaling via IκBα Ubiquitination.

Xiaoming Qin, Jiachen Luo, Yiqian Yuan +5 more · 2026 · Drug development research · Wiley · added 2026-04-24
Atherosclerosis, a major contributor to cardiovascular diseases, is characterized by chronic inflammation in arterial walls. The role of NF-κB signaling in this process is well-established, but the up Show more
Atherosclerosis, a major contributor to cardiovascular diseases, is characterized by chronic inflammation in arterial walls. The role of NF-κB signaling in this process is well-established, but the upstream regulators remain incompletely understood. This study explored the role of TRIM47, an E3 ubiquitin ligase, in promoting atherosclerosis through NF-κB activation. In vitro studies used human umbilical vein endothelial cells (EC) treated with oxidized low-density lipoprotein (ox-LDL). TRIM47 expression was modulated using siRNA knockdown and overexpression plasmids. Inflammation markers, cell viability, and NF-κB activation were assessed. In vivo studies utilized ApoE-/- mice fed a high-fat diet and treated with adenovirus-mediated TRIM47 knockdown. ox-LDL treatment increased TRIM47 expression in EC, alongside elevated inflammatory markers, and reduced cell viability. TRIM47 overexpression exacerbated ox-LDL-induced inflammation, while knockdown attenuated these effects. Mechanistically, TRIM47 directly interacted with IκBα, promoting its ubiquitination and degradation, leading to enhanced NF-κB activation. In ApoE-/- mice, TRIM47 knockdown significantly reduced atherosclerotic plaque formation and lesion size. This study identified TRIM47 as a novel regulator of atherosclerosis progression through IκBα ubiquitination and NF-κB activation. TRIM47 knockdown attenuated vascular inflammation and atherosclerotic plaque formation. The findings suggested that TRIM47 might be a potential therapeutic target for the treatment of atherosclerosis and related cardiovascular diseases. Show less
no PDF DOI: 10.1002/ddr.70264
APOE

Stevia rebaudiana Bertoni root polysaccharide ameliorate high-fat-diet-induced atherosclerosis in ApoE-knock out mice: potential role of inflammation regulation.

Chunyan Liu, Guangdong Hu, Haoyu Zhang +5 more · 2026 · Natural product research · Taylor & Francis · added 2026-04-24
Atherosclerosis (AS) is a prevalent typical chronic inflammation disease characterised by lipid deposition, immune cell infiltration and inflammatory response in the arterial intima. The long-term tre Show more
Atherosclerosis (AS) is a prevalent typical chronic inflammation disease characterised by lipid deposition, immune cell infiltration and inflammatory response in the arterial intima. The long-term treatments of the existing drugs suffered safety concerns. Show less
no PDF DOI: 10.1080/14786419.2026.2613756
APOE

Obesity Boosts the Tumor Delivery and Anticancer Effects of Liposomal Doxorubicin by an Apolipoprotein E-Mediated Mechanism.

Shiyi Xu, Nana Bie, Haojie Liu +7 more · 2026 · Molecular pharmaceutics · ACS Publications · added 2026-04-24
The protein corona formed upon systemic administration critically modulates the pharmacokinetics, biodistribution, and therapeutic efficacy of the nanomedicines. While emerging evidence links obesity Show more
The protein corona formed upon systemic administration critically modulates the pharmacokinetics, biodistribution, and therapeutic efficacy of the nanomedicines. While emerging evidence links obesity to heightened chemosensitivity, the underlying nanobio-interfacial mechanisms remain poorly understood. Herein, we demonstrate that pegylated liposomal doxorubicin (PLD) exhibits significantly enhanced antitumor and antimetastatic efficacy in obese breast tumor-bearing mice compared to normal controls. Mechanistic investigations reveal that obesity confers PLD with prolonged systemic circulation and improved tumor accumulation. Notably, preincubation of PLD with plasma from obese mice reduces macrophage uptake while promoting internalization by breast cancer cells compared to that from normal mice. Genetic ablation of apolipoprotein E (ApoE) in obese mice abolishes obesity-associated improvements in PLD blood circulation, tumor accumulation, and uptake by cancer cells. Conversely, supplementation with recombinant ApoE restores these effects in ApoE-deficient mice and potentiates PLD's antitumor efficacy. Collectively, our findings demonstrate obesity-induced ApoE as a pivotal regulator of the protein corona that actively enhances tumor-targeted delivery of PLD, which offers a rational strategy for engineering protein-corona-mediated tumor-targeted nanomedicines. Show less
no PDF DOI: 10.1021/acs.molpharmaceut.5c00794
APOE

Endogenous GIP signaling is indispensable for DPP-4 inhibitor-mediated metabolic control in mice.

Saki Kubota-Okamoto, Sodai Kubota, Hiromi Tsuchida +15 more · 2026 · Journal of diabetes investigation · Blackwell Publishing · added 2026-04-24
Dipeptidyl peptidase-4 (DPP-4) inhibitors enhance circulating levels of biologically intact incretins, yet the relative contribution of glucose-dependent insulinotropic polypeptide (GIP) to their meta Show more
Dipeptidyl peptidase-4 (DPP-4) inhibitors enhance circulating levels of biologically intact incretins, yet the relative contribution of glucose-dependent insulinotropic polypeptide (GIP) to their metabolic effects remains incompletely understood. While glucagon-like peptide-1 (GLP-1) has long been emphasized in incretin biology, emerging evidence suggests important physiological roles for GIP. This study investigated whether endogenous GIP signaling is indispensable for the glucose-lowering and anti-obesity effects of DPP-4 inhibition. Male Gipr DPP-4 inhibition significantly improved glucose tolerance and attenuated body-weight gain in HFD-fed Gipr Endogenous GIP signaling is essential for both glucose-lowering and anti-obesity actions of DPP-4 inhibitors in mice. GLP-1 elevation alone is insufficient to compensate for GIP receptor deficiency. These findings refined the mechanistic understanding of DPP-4 inhibitors, highlighted the physiological importance of GIP, and suggested context-dependent metabolic actions of incretins. Show less
📄 PDF DOI: 10.1111/jdi.70252
GIPR

Clinical characteristics and APOE variant spectrum in Chinese patients with lipoprotein glomerulopathy.

Mengshi Li, Yang Li, Lei Jiang +7 more · 2026 · Chinese medical journal · added 2026-04-24
📄 PDF DOI: 10.1097/CM9.0000000000003978
APOE

Prognostic prediction and immune correlation analysis of anoikis- and epithelial-mesenchymal transition-related genes in lung adenocarcinoma.

Tianjia Liu, Xueting Dong, Yuling Liang +6 more · 2026 · Translational cancer research · added 2026-04-24
Anoikis resistance and epithelial-mesenchymal transition (EMT) are crucial factors in tumor invasiveness and metastasis in lung adenocarcinoma (LUAD). Identifying anoikis-EMT-related genes could be be Show more
Anoikis resistance and epithelial-mesenchymal transition (EMT) are crucial factors in tumor invasiveness and metastasis in lung adenocarcinoma (LUAD). Identifying anoikis-EMT-related genes could be beneficial for predicting prognosis and immunotherapeutic efficacy in patients with LUAD. This study aims to establish and validate a novel prognostic signature based on anoikis-EMT-related genes for LUAD and to identify the potential biomarkers encapsulated within it. Anoikis-related genes and EMT-related genes were retrieved from the GeneCards and dbEMT 2.0 databases. Univariate Cox regression analysis and principal component analysis (PCA) were conducted to define anoikis and EMT levels. Gene expression and clinical information of patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Univariate Cox regression and multivariate Cox regression analyses were conducted to construct a risk score model. Immune correlation and drug sensitivity analyses were performed to investigate the association of the risk score with the immune profile and antitumor treatment. Three essential genes in the model were examined for messenger RNA (mRNA) expression by reverse transcription-polymerase chain reaction (RT-PCR) and for protein levels via the Human Protein Atlas (HPA) database. LUAD patients demonstrating low Anoikis Potential Index (API) combined with high EMT Potential Index (EPI) exhibited the poorest overall survival (OS). We further constructed a nine-gene prognostic risk model that combines anoikis and EMT. High-risk patients demonstrated significantly shorter survival duration. The clinical-prognostic nomogram accurately predicted outcomes at 1, 3, and 5 years. In addition, patients in low-risk group demonstrated superior immune responses to treatment and were more sensitive to commonly used chemotherapy drugs. Our validation studies confirmed upregulated expression of ANGPTL4, SLC2A1, and BIRC5 in LUAD, observed at both transcriptional and translational levels. The anoikis-EMT-based risk model effectively forecasts both OS and immunotherapy response in LUAD patients, accelerating the identification of groundbreaking molecular biomarkers and prospective molecular targets. Show less
📄 PDF DOI: 10.21037/tcr-2025-aw-2282
ANGPTL4

Cardiometabolic indicators of cognitive impairment in the Cameron County Hispanic Cohort.

Fadi I Musfee, Seema Agarwal, Vahed Maroufy +4 more · 2026 · Journal of Alzheimer's disease : JAD · SAGE Publications · added 2026-04-24
BackgroundCognitive impairment (CI) and its related risk factors (e.g., diabetes and stroke) are highly prevalent among Hispanic/Latinos (H/L); however, prior research in H/L focused on aging individu Show more
BackgroundCognitive impairment (CI) and its related risk factors (e.g., diabetes and stroke) are highly prevalent among Hispanic/Latinos (H/L); however, prior research in H/L focused on aging individuals (≥65 years old).ObjectiveTo comprehensively assess the associations between a wide-range of cardiometabolic health indicators and CI using a prospective study design in a younger cohort of H/L (majority <65 years old) from the Cameron County Hispanic Cohort (CCHC).MethodsWe identified a total of 1240 CCHC subjects with complete Mini-Mental Status Exam (MMSE) data at study baseline and at 5-year follow-up. The outcome (i.e., CI) was based on MMSE scores of less than 24. We conducted univariate associations for multiple cardiometabolic indicators with CI; and mixed logistic regression models to estimate odds ratios for the associations between cardiometabolic indicators and CI adjusted for age, education, prior stroke, and Show less
no PDF DOI: 10.1177/13872877251408098
APOE

Altered Amyloid-β42 and BACE-1 Proteins in Plasma Astrocyte-Derived Exosomes in Hypertensive Patients With Cerebral Microbleeds.

Xiaoxiao Liu, Yuanyuan Liu, Ran Yao +6 more · 2026 · American journal of hypertension · Oxford University Press · added 2026-04-24
Cerebral microbleeds (CMBs) have been found to promote Alzheimer's disease (AD) progression. Hypertension (HTN) is one of the major etiological factors for CMBs and an important risk factor for AD. Ho Show more
Cerebral microbleeds (CMBs) have been found to promote Alzheimer's disease (AD) progression. Hypertension (HTN) is one of the major etiological factors for CMBs and an important risk factor for AD. However, the association between HTN-related CMBs and AD pathology remains undetermined. This study aims to identify the relationship between HTN-related CMBs and amyloid-β 42 (Aβ42) and β-site amyloid precursor protein cleaving enzyme 1 (BACE-1) levels in plasma astrocyte-derived exosomes (ADEs). In total, 88 HTN participants including 30 with deep/infratentorial (D/I) CMBs, 30 with mixed CMBs, and 28 without CMBs were analyzed. Susceptibility-weighted imaging was performed to assess the location, presence, and number of CMBs. ELISA kits for BACE-1 and Aβ42 were employed to evaluate the levels of astrocyte-derived exosomal proteins. The results indicated that plasma ADE levels of Aβ42 were reduced in the HTN + D/I CMBs and HTN + Mixed CMBs groups relative to the HTN-CMBs group. Furthermore, the plasma ADE levels of Aβ42 were significantly associated with CMBs in patients with HTN. However, no significant differences were found in the plasma ADE levels of BACE-1 among the HTN + D/I CMBs, HTN + Mixed CMBs, and HTN-CMBs groups. The study revealed that reduced plasma ADE levels of Aβ42 were significantly associated with CMBs in HTN patients. This finding suggests a potential link between HTN-related CMBs and AD-related amyloid-β pathology, offering novel insights into the mechanisms by which HTN-related CMBs promote AD progression. Show less
no PDF DOI: 10.1093/ajh/hpaf158
BACE1

The KANSL1-ARL17A fusion gene generates oncogenic chKANSARL and F-circKA RNAs that synergistically drive lung cancer progression via a novel F-circKA/miR-6860/chKANSARL axis.

Xinchao Guan, Tao Liu, Sili Chen +4 more · 2026 · The Journal of biological chemistry · Elsevier · added 2026-04-24
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to c Show more
Fusion genes are pivotal drivers of tumorigenesis, often generating oncogenic chimeric RNAs and fusion circular RNAs. However, the mechanisms by which these transcripts synergistically contribute to cancer progression remain poorly understood. Here, we identified a lung cancer-specific chimeric RNA KANSL1-ARL17A (chKANSARL) and its circular variant fusion circular RNA KANSL1-ARL17 A (F-circKA), both derived from the fusion gene KANSARL. Functional assays revealed that overexpression of either chKANSARL or F-circKA significantly enhanced lung cancer cell proliferation, migration, and invasion, while their knockdown suppressed these malignant phenotypes. In vivo experiments demonstrated that chKANSARL overexpression accelerated tumor growth in immunodeficient mice. Notably, coexpression experiments uncovered a synergistic regulatory interaction between F-circKA and chKANSARL, amplifying oncogenic effects. Mechanistically, miRNA sequencing and dual-luciferase assays revealed that F-circKA acts as a molecular sponge for miR-6860, thereby derepressing chKANSARL expression. Rescue experiments further validated this regulatory axis, wherein miR-6860 inhibition reversed the tumor-suppressive effects of F-circKA knockdown. Collectively, our study identifies and characterizes a novel F-circKA/miR-6860/chKANSARL regulatory axis, revealing how dual transcriptional outputs from the KANSARL fusion gene can synergistically drive lung cancer progression. These findings highlight a previously unrecognized layer of cooperative regulation between linear and circular fusion RNAs in oncogenesis and provide a new framework for understanding fusion gene-mediated tumorigenesis. Show less
📄 PDF DOI: 10.1016/j.jbc.2026.111170
KANSL1

APM⁺ macrophages associated with plaque vulnerability via MIF-CD74 signaling: a multi-omics study.

Xiang Xu, Yuanze Li, Siqi Xiang +3 more · 2026 · Human genomics · BioMed Central · added 2026-04-24
Atherosclerosis (AS) is a chronic vascular disease and the principal cause leading to ischemic cardiomyopathy (ICM). It involves complex metabolic dysregulation beyond the resolution of single-omics. Show more
Atherosclerosis (AS) is a chronic vascular disease and the principal cause leading to ischemic cardiomyopathy (ICM). It involves complex metabolic dysregulation beyond the resolution of single-omics. Emerging evidence implicates arginine-proline metabolism (APM) in driving inflammation and impairing efferocytosis, yet the cellular basis of plaque instability remains elusive. We employed a five-stage analytical framework. First, metabolomic profiling revealed shared pathways between AS and ICM. Second, single-cell RNA sequencing identified APM-enriched macrophage subtypes in both diseases. Pseudotime analysis, Scissor algorithm, and cell-cell communication analyses linked these subtypes to APM signaling, stroke prognosis, and key ligand-receptor interactions. Third, cNMF and unsupervised clustering defined APM-related gene signatures in macrophages, validated by survival analysis. Fourth, spatial transcriptomics confirmed their spatial distribution and colocalization within unstable plaques. Finally, key biomarkers were validated in atherosclerotic lesions using ApoE Metabolomic profiling revealed APM as a shared dysregulated pathway in AS and ICM. We identified a macrophage subset (SPP1⁺ macrophages and mono-macrophages), termed APM_high macrophages, enriched in the fibrous cap and characterized by elevated collagenase activity, heightened inflammation, and disrupted cholesterol homeostasis. Spatial and cell-cell communication analyses revealed strong interactions with dendritic cells via the MIF-(CD74 + CXCR4) axis, potentially contributing to plaque destabilization. Transcriptomic clustering uncovered a high-APM plaque subtype associated with worse ischemic outcomes. Six diagnostic biomarkers were identified through machine learning and validated across multiple cohorts and in ApoE In summary, our study decodes the metabolic basis of inflammation shared between AS and ICM, suggesting an APM_high macrophage-centered regulatory axis across multiple omics layers. This work advances our understanding of the cardio-metabolic axis and suggests new avenues for targeted therapy. Show less
📄 PDF DOI: 10.1186/s40246-025-00869-9
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

Genome-wide association study identified genomic regions and putative candidate genes affecting different backfat layers in Landrace pigs.

Z Meng, Y Liu, W Yang +4 more · 2026 · Animal : an international journal of animal bioscience · Elsevier · added 2026-04-24
Backfat thickness, a key selection trait in pig-breeding programmes, has traditionally been measured as a homogeneous layer. However, backfat is anatomically structured into three distinct layers, and Show more
Backfat thickness, a key selection trait in pig-breeding programmes, has traditionally been measured as a homogeneous layer. However, backfat is anatomically structured into three distinct layers, and each layer likely contributes differently to carcass quality. In addition, previous studies have shown that the deposition of the third layer of backfat is phenotypically correlated with intramuscular fat (IMF). Therefore, targeted selection for specific backfat layers, particularly the third layer, represents a potential strategy to increase IMF content while maintaining a high lean meat percentage. However, the genetic architecture of these distinct porcine backfat layers remains poorly understood. The aim of this study was to estimate the genetic parameters and identify key candidate genes underlying the three backfat layers. We collected B-mode ultrasound images from 561 Landrace pigs to measure individual layer thickness, followed by DNA extraction, genotyping, genetic parameter estimation, and a genome-wide association study (GWAS). Our measurements showed that the first layer of backfat (FBF) is the thickest, followed by the second (SBF) and the third (TBF) layers. Genetic parameter estimation yielded heritability estimates of 0.37, 0.42, 0.38, 0.34, 0.32, 0.24, and 0.21 for total backfat (BF), FBF, FBF/BF, SBF, SBF/BF, TBF, and TBF/BF, respectively. Through integrated analysis of GWAS, Bayesian fine-mapping, and gene annotation, we identified 15 non-redundant candidate genes associated with different backfat layers. These included two genes (SOAT1 and ACBD6) shared by BF and SBF, LPL for BF and FBF, and CAND1 for TBF and TBF/BF. Additionally, SERPINA12 and SERPINA6 were associated with BF; PRKAG1 and PRDM16 with FBF; EPRS1 and SLC39A10 with FBF/BF; PTGES and CRAT with SBF; and ACLY, CAVIN1, and PDZRN3 with SBF/BF. Our results indicate that each layer is governed by a distinct set of genes, which advances our understanding of the genetic basis of backfat layers in pigs. Show less
no PDF DOI: 10.1016/j.animal.2026.101764
LPL

Dingxin Recipe III resolves atherosclerotic inflammation via revitalizing Regulatory T cell lineage fidelity associated with fatty acid oxidation metabolic reprogramming.

Xiao Li, Yuanyu Tu, Yao Jin +14 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Atherosclerosis is fundamentally a pathology of unresolved inflammation perpetuated by the collapse of Regulatory T cell (Treg)-mediated tolerance. Emerging evidence indicates that Treg functional int Show more
Atherosclerosis is fundamentally a pathology of unresolved inflammation perpetuated by the collapse of Regulatory T cell (Treg)-mediated tolerance. Emerging evidence indicates that Treg functional integrity is intrinsically dictated by mitochondrial fatty acid oxidation (FAO), a metabolic checkpoint often compromised under systemic metabolic stress. Current lipid-lowering therapies, such as statins, often fall short in correcting this maladaptive immunometabolic defect and may introduce collateral metabolic perturbations. This study aimed to elucidate the immunometabolic therapeutic mechanism of Dingxin Recipe III (DXR III) in ameliorating atherosclerosis. We employed an integrated systems pharmacology strategy-combining serum pharmacochemistry, multi-omics profiling, and extensive high-dimensional flow cytometry-to elucidate the therapeutic mechanism of DXR III, a traditional Chinese herbal formula in an in vivo study. ApoE DXR III treatment effectively attenuating atherosclerotic progression. Serum pharmacochemistry identified 254 prototypical absorbed constituents, including Tanshinone I (a potential Peroxisome Proliferator-Activated Receptor Gamma agonist), as bioactive candidates. Multi-omics analysis revealed that DXR III modulated the metabolic environment, coinciding with restored FAO flux. This shift was associated with a favorable metabolic niche characterized by increased FAO substrates, which correlated with the rescue of Treg differentiation and phenotypic stability. Specifically, DXR III facilitated the redistribution of Tregs from the spleen to plaque sites and significantly inhibited their trans-differentiation into Th1-like or Th17-like phenotypes. Conversely, Simvastatin treatment, despite lowering lipids, resulted in peripheral Th17 accumulation and failed to alleviate hyperglycemia. In contrast, DXR III maintained Th17 homeostasis-abolishing the pathogenic non-classical Th17 subset-and exerted dual-regulatory effects on both lipid and glucose metabolism. DXR III ameliorates atherosclerosis, a process closely associated with the modulation of the FAO metabolic checkpoint to correct the immune imbalance driving plaque progression. By rescuing the Treg differentiation, functional integrity, and phenotypic fidelity while avoiding the immunological trade-offs associated with Th1/Th17, DXR III represents a promising candidate for comprehensive cardiovascular protection. Show less
no PDF DOI: 10.1016/j.phymed.2026.158044
APOE