👤 Jianxin Liu

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, 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

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

The E3 ligases Itch and WWP2 regulate autoimmune neuroinflammation by controlling T

Mei Zhao, Chao Zhang, Xin Zhang +3 more · 2026 · Nature communications · Nature · added 2026-04-24
Multiple sclerosis (MS) is a neurodegenerative autoimmune disease primarily mediated by T helper 17 (T
no PDF DOI: 10.1038/s41467-025-67665-w
WWP2

Effects of

Xitian Wang, Chunhua Zhang, Xiaocong Liu +5 more · 2026 · Journal of Alzheimer's disease : JAD · SAGE Publications · added 2026-04-24
BackgroundMild cognitive impairment (MCI) confers an increased risk of Alzheimer's disease (AD). The apolipoprotein E (
no PDF DOI: 10.1177/13872877261435429
APOE

Association of uric acid-to-HDL cholesterol ratio and coronary atherosclerotic heart disease in patients with and without CKD.

Chang-Hao Sun, Xin-Yu Zhu, Zhi-Long Wang +5 more · 2026 · BMC cardiovascular disorders · BioMed Central · added 2026-04-24
The ratio of uric acid to high-density lipoprotein cholesterol (UHR) is a novel comprehensive indicator related to dyslipidemia. However, the association between UHR and coronary artery disease (CAD) Show more
The ratio of uric acid to high-density lipoprotein cholesterol (UHR) is a novel comprehensive indicator related to dyslipidemia. However, the association between UHR and coronary artery disease (CAD) risk in patients with chronic kidney disease (CKD) remains unclear. After matching based on age and gender propensity scores, 2124 subjects were included and divided into the CKD group (708 cases) and the non-CKD group (1416 cases). The predictive performance of UHR for CAD was evaluated by the area under the curve (AUC), and the independent association between UHR and the risk of CAD onset was analyzed using a multivariate logistic regression model. The correlation and dose-response relationship between the ratio of uric acid to high-density lipoprotein cholesterol (UHR) and the risk of CAD were analyzed using LOESS fitting and restricted cubic spline (RCS) analysis. After matching, the multiple lipid-related indices (Triglycerides (TG), Remnant Cholesterol (RC), Atherogenic Index (AI), Atherogenic Index of Plasma (AIP), Triglyceride Glucose Index (TyG), Lipoprotein Composite Index (LCI), Triglyceride to High-Density Lipoprotein Cholesterol Ratio (TG/HDL-C), Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio (TC/HDL-C), Low-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio (LDL-C/HDL-C), UHR) in the CKD group were significantly higher than those in the non-CKD group. The AUC analysis showed that HDL-C, AIP, TG/HDL-C, and UHR had strong predictive performance in the overall cohort and the non-CKD group, while in the CKD group, HDL-C, AI, and TC/HDL-C are better predictive indicators. After adjusting for all confounding factors, multivariate regression analysis revealed that HDL-C, apolipoprotein A-1 (APOA-1), and the APOA-1/APOB ratio were independent protective factors for CAD in the entire cohort. Among them, the protective effect of HDL-C was the most stable (overall population aOR = 0.26, 95% CI: 0.17-0.39, p < 0.001), and it was significantly in both the CKD (aOR = 0.18, 95% CI: 0.09-0.40, p < 0.001) and non-CKD subgroups (aOR = 0.31, 95% CI: 0.18-0.52, p < 0.001). In CKD, UHR is significantly correlated with CAD (aOR = 6.23, 95% CI: 1.89-20.60, p = 0.003), and the association was more significant in the non-CKD group (aOR = 15.15, 95% CI: 4.20-54.72, p < 0.001). CKD status significantly modified the association between UHR and CAD (P for interaction = 0.015). LOESS fitting suggested that UHR was positively correlated with the probability of CAD occurrence (the correlation was more significant at low UHR, and it slowed down when UHR > 0.5, r = 0.2, p < 0.001), and negatively correlated with eGFR (r = -0.38, p < 0.001). RCS analysis confirmed a significant nonlinear association between UHR and CAD (overall P < 0.001, nonlinear P = 0.002), and the risk of CAD increased when UHR was > 0.41 in CKD patients. UHR is an independent risk factor for coronary heart disease, with higher adjusted OR values and more significant independent risk effects in non-CKD populations. Show less
no PDF DOI: 10.1186/s12872-026-05838-1
APOB

Multi-omics Analysis Reveals Comprehensive Aberrant Protein and Phosphorylation Characteristics in Breast Cancer and Paired Metastatic Lymph Nodes.

Linhui Zhai, Cui-Cui Liu, Lei Zhao +14 more · 2026 · Protein & cell · Oxford University Press · added 2026-04-24
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune s Show more
Breast cancer is the most frequently diagnosed cancer, with metastasis accounting for the majority of cancer-related deaths. The mechanisms of early-stage breast cancer metastasis to regional immune sites like lymph nodes remain elusive. Here, we performed an in-depth proteomic and phosphoproteomic analysis of a substantial series of breast cancer samples, alongside genomic and transcriptomic evaluations. This cohort encompasses 195 specimens: 65 primary breast tumors, their corresponding normal tissues, and metastatic axillary lymph nodes. We offer an overview of the molecular alterations at the transcriptomic, proteomic, and phosphoproteomic levels during lymph node metastasis. Notably, the findings indicate that regional lymph node metastasis is primarily influenced by proteomic and phosphoproteomic alterations, rather than genomic or transcriptomic changes. We found the ANGPTL4 and HMGB1 could serve as the biomarker of lymph node metastasis. Data analysis and cell experiments involving silencing of the alternative splicing factor HNRNPU demonstrated that alternative splicing plays a significant role in modulating protein expression, phosphorylation profiles and cell proliferation. The key phosphorylation sites, including MARCKSL1-S104 and FKBP15-S320, as well as the upstream kinase PRKCB, were identified as playing crucial roles in breast cancer lymph node metastasis. Targeted intervention of the kinase PRKCB resulted in effectively suppressing the proliferation and metastasis of breast cancer tumor cells. Immune profiling analysis and experimental validation of breast cancer cell cocultured with CD8+ T cell reveals correlations between phosphorylation of MARCKSL1-S104 and FKBP15-S320 with immune checkpoint PD-L1 expression, and their impact on tumor cell apoptosis, suggesting a potential mechanism of immune evasion in metastasis. This study systematically characterizes the molecular landscape and features of primary breast tumors and their matched metastatic lymph nodes. These insights enhance our understanding of early-stage breast cancer metastasis and may pave the way for improved diagnostic tools and targeted therapeutic strategies. Show less
no PDF DOI: 10.1093/procel/pwag002
ANGPTL4

NRBF2 homodimerization by its coiled-coil domain strengthens association with the PtdIns3K complex mediated by the MIT domain to promote autophagy.

Na Li, Xiaohua Li, Xianxiu Qiu +7 more · 2026 · Autophagy · Taylor & Francis · added 2026-04-24
The mammalian class III phosphatidylinositol-3-kinase complex (PtdIns3K) forms two biochemically and functionally distinct subcomplexes including the ATG14-containing complex I (PtdIns3K-C1) and the U Show more
The mammalian class III phosphatidylinositol-3-kinase complex (PtdIns3K) forms two biochemically and functionally distinct subcomplexes including the ATG14-containing complex I (PtdIns3K-C1) and the UVRAG-containing complex II (PtdIns3K-C2). Both subcomplexes adopt a V-shaped architecture with a BECN1-ATG14 or UVRAG adaptor arm and a PIK3R4/VPS15-PIK3C3/VPS34 catalytic arm. NRBF2 is a pro-autophagic modulator that specifically associates with PtdIns3K-C1 to enhance its kinase activity and promotes macroautophagy/autophagy. How NRBF2 exerts such a positive effect is not fully understood. Here we report that NRBF2 binds to PIK3R4/VPS15 with moderate affinity through a conserved site on its N-terminal MIT domain. The NRBF2-PIK3R4/VPS15 interaction is incompatible with the UVRAG-containing PtdIns3K-C2 because the C2 domain of UVRAG outcompetes NRBF2 for PIK3R4/VPS15 binding. Our crystal structure of the NRBF2 coiled-coil (CC) domain reveals a symmetric homodimer with multiple hydrophobic pairings at the CC interface, which is in distinct contrast to the asymmetric dimer observed in the yeast ortholog Atg38. Mutations in the CC domain that rendered NRBF2 monomeric led to weakened binding to PIK3R4/VPS15 and only partial rescue of autophagy deficiency in Show less
no PDF DOI: 10.1080/15548627.2025.2580438
PIK3C3

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

Phase 1 dose-escalation trial of sub-endometrial injection of human embryonic stem cells-derived immunity-and-matrix-regulatory cells to promote endometrial angiogenesis in refractory intrauterine adhesion.

Qiang Li, Zhiqi Liao, Xinyao Hu +26 more · 2026 · Molecular therapy : the journal of the American Society of Gene Therapy · Elsevier · added 2026-04-24
Clinical application of mesenchymal stem cells for endometrial repair has been hampered by variability in cell quality, large-scale production, and uncertainty regarding the optimal delivery route. In Show more
Clinical application of mesenchymal stem cells for endometrial repair has been hampered by variability in cell quality, large-scale production, and uncertainty regarding the optimal delivery route. In this study, we investigated the therapeutic potential of clinical-grade human embryonic stem cell-derived immunity-and-matrix-regulatory cells (IMRCs) for treating refractory moderate-to-severe intrauterine adhesion (IUA). In a rabbit IUA model, sub-endometrial injection of IMRCs significantly reduced fibrosis and enhanced endometrial angiogenesis, outperforming uterine perfusion. Transcriptomic analysis revealed distinct pro-angiogenic gene expression profiles between the two delivery routes. In vitro, IMRCs co-cultured with endometrial stromal cells (ESCs) markedly enhanced angiogenic potential compared to either cell type alone. Protein array analysis of the co-culture supernatant showed elevated levels of angiogenic factors, with functional assays confirming that inhibition of ANGPTL4, a non-canonical pro-angiogenic mediator, impaired angiogenesis. In a first-in-human, single-center, phase 1 dose-escalation trial involving 18 patients with refractory IUA, high-dose sub-endometrial IMRC injection promoted angiogenesis, reduced uterine scarring, and improved pregnancy outcomes, with no safety concerns observed over 3 years of follow-up. These findings highlight the translational promise of IMRCs as a novel therapeutic strategy for endometrial regeneration in severe IUA. Show less
📄 PDF DOI: 10.1016/j.ymthe.2025.09.035
ANGPTL4

Causal Relationship Between Neurotrophins and Normal Pressure Hydrocephalus: Insights From a Bidirectional Two-Sample Mendelian Randomization Study.

Tao Xu, Qiang Gan, Handong Wang +2 more · 2026 · Brain and behavior · Wiley · added 2026-04-24
Researchers have postulated a link between higher levels of brain-derived neurotrophic factor (BDNF) and more favorable outcomes in patients with normal pressure hydrocephalus (NPH). However, there is Show more
Researchers have postulated a link between higher levels of brain-derived neurotrophic factor (BDNF) and more favorable outcomes in patients with normal pressure hydrocephalus (NPH). However, there is no clear evidence regarding the causal association between neurotrophins and NPH. To delve deeper into this potential connection, scientists employed a rigorous method known as bidirectional Mendelian randomization (MR). This technique was utilized to explore the causal impact of various neurotrophins-such as BDNF, nerve growth factor (NGF), neurotrophin-3 (NT-3), NT-4, ciliary neurotrophic factor (CNTF), and glial cell line-derived neurotrophic factor (GDNF)-on the development or progression of NPH. To investigate the causal relationship between five neurotrophin subtypes and NPH, we designed a two-sample Mendelian randomization (MR) study using comprehensive genome-wide association study (GWAS) data. Our primary approach involved the inverse-variance weighted (IVW) method. We also conducted reverse causality analysis to ensure robustness. Furthermore, we implemented complementary methods like the weighted median (WM), weighted mode, and MR-Egger to strengthen our findings. Sensitivity analyses, including MR-Egger, MR-PRESSO, leave-one-out, and Cochran's Q tests, were employed to validate results, explore heterogeneity and pleiotropy, and pinpoint potential biases. MR analysis of genetic prediction showed no statistical association of neurotrophins on NPH. However, a reverse analysis indicated a causal association between NPH and two neurotrophins: CNTF and GDNF. Specifically, individuals with NPH had a lower risk of CNTF (odds ratio: 0.7963, with a 95% confidence interval of 0.6537 to 0.9701, p = 0.0237) and a slightly reduced risk of GDNF (odds ratio: 0.9576, with a 95% confidence interval of 0.9226 to 0.9940, p = 0.0230). MR-Egger regression showed that pleiotropy did not affect the analysis. In addition, MR-PRESSO detected no outliers, and a leave-one-out analysis verified the robustness of the results. NPH was negatively and causally associated with CNTF and GDNF. Additional research is crucial to uncover the underlying mechanisms and devise strategies, including nutritional guidelines, to prevent NPH. Show less
no PDF DOI: 10.1002/brb3.71309
BDNF bdnf causal relationship hydrocephalus mendelian randomization neurotrophic factor neurotrophins normal pressure hydrocephalus

A shear-responsive nanosystem engineered from fucoidan targets endothelial for atherosclerosis therapy.

Ruyue Liu, Xuli Ruan, Mengran Guo +14 more · 2026 · Biomaterials · Elsevier · added 2026-04-24
Hemodynamic abnormalities within atherosclerotic plaque regions, particularly localized high shear stress and endothelial dysfunction, present novel targets for intervention by drug delivery systems. Show more
Hemodynamic abnormalities within atherosclerotic plaque regions, particularly localized high shear stress and endothelial dysfunction, present novel targets for intervention by drug delivery systems. In this study, we designed a polysaccharide-based carrier (HF-AF) from fucoidan, featuring a dynamic supramolecular structure. A dynamic supramolecular network was established within this carrier via dynamic supramolecular interactions between hydroxypropyl-β-cyclodextrin and adamantane-methylamine. The anti-inflammatory compound tilianin, formulated into nanocrystals (Til NCs), was then encapsulated to create a shear-responsive nanosystem (HF-AF@Til NCs). The system's primary therapeutic strategy is its response to pathological hemodynamic forces: upon encountering high shear stress at a stenosis, the supramolecular network undergoes dissociation, triggering a mechanically-gated release of the encapsulated Til NCs. This shear-triggered function is complemented by the natural P-selectin affinity of the fucoidan backbone, which facilitates the anchoring of the nanocarrier at the inflamed lesion site. This sophisticated "anchor-and-release" mechanism enables superior drug accumulation precisely at plaque sites. In ApoE Show less
no PDF DOI: 10.1016/j.biomaterials.2025.123931
APOE

Associations between plasma ANGPTL4 levels and the risk of 24 cancers: a prospective cohort study.

Xi Cheng, Shuzhen Zhao, Mingyi Du +4 more · 2026 · Cytokine · Elsevier · added 2026-04-24
Angiopoietin-like 4 (ANGPTL4) is a hepatokine involved in metabolism and inflammation and has been implicated in oncogenesis, yet its relationship with cancer risk in humans remains unclear. We analyz Show more
Angiopoietin-like 4 (ANGPTL4) is a hepatokine involved in metabolism and inflammation and has been implicated in oncogenesis, yet its relationship with cancer risk in humans remains unclear. We analyzed 35,716 cancer-free UK Biobank participants with baseline plasma ANGPTL4. Multivariable Cox models and restricted cubic splines assessed associations with 24 site-specific incident cancers; bidirectional two-sample Mendelian randomization (MR) evaluated causality. During a median follow-up of 12.5 years, 9304 incident cancer cases occurred. Compared with the lowest quartile (Q1), the higher quartiles (Q2, Q3, and Q4) of ANGPTL4 levels were significantly associated with the risks of ten cancers, including cancers of the bladder, breast, cervix uteri, colorectum/anus, esophagus, kidney, liver, mesothelial/soft tissues, multiple myeloma, and ovary (hazard ratios ranging from 1.02 to 3.98). Risks generally increased across ANGPTL4 quartiles, and spline analyses supported approximately linear dose-response patterns. Adding ANGPTL4 to an age-sex model improved discrimination across several sites (ΔC-index 0-0.071), with statistical significance observed only for breast cancer. Associations were directionally consistent but heterogeneous by age, sex, and BMI. Forward MR provided no evidence that genetically proxied ANGPTL4 causally increases cancer risk. In reverse MR, genetic liability to liver cancer showed a nominal positive association with circulating ANGPTL4, suggesting ANGPTL4 may be elevated as part of tumor-related biology. Higher circulating ANGPTL4 is associated with increased risk of multiple cancers, with sex-and tissue-specific heterogeneity. Although MR does not support a universal causal role, ANGPTL4 remains a promising pan-cancer biomarker for risk stratification and early prevention. Show less
no PDF DOI: 10.1016/j.cyto.2025.157089
ANGPTL4

Endoplasmic reticulum stress mediates oxidative stress-driven endothelial impairment and atherogenesis induced by sodium perfluorononenoxybenzene sulfonate exposure.

Boxiang Zhang, Zeming Liu, Qing Li +4 more · 2026 · Environmental research · Elsevier · added 2026-04-24
Sodium perfluorononenoxybenzene sulfonate (OBS), a substitute for perfluorooctane sulfonate (PFOS), has been frequently detected in the environment and human blood. Although OBS exposure has been iden Show more
Sodium perfluorononenoxybenzene sulfonate (OBS), a substitute for perfluorooctane sulfonate (PFOS), has been frequently detected in the environment and human blood. Although OBS exposure has been identified as a novel risk factor for atherosclerosis associated with endothelial dysfunction, the underlying molecular mechanisms remain unclear. In this study, in vitro experiments using human umbilical vein endothelial cells (HUVECs) demonstrated that OBS exposure induced oxidative stress, activated the PERK-eIF2α-ATF4 axis of endoplasmic reticulum stress (ERS) and triggered NF-κB signaling. Pharmacological inhibition with N-acetylcysteine (NAC, an antioxidant), 4-phenylbutyric acid (4-PBA, an ERS inhibitor), and BAY 11-7082 (an inhibitor for NF-κB signaling pathway) revealed a sequential pathogenic cascade, in which oxidative stress acts upstream to initiate ERS and compromise endothelial barrier function, leading to NF-κB activation, which drives inflammatory responses, monocyte adhesion, and impaired endothelial migration. Consistent with these findings, in vivo experiments in ApoE Show less
no PDF DOI: 10.1016/j.envres.2026.124344
APOE

USP18 ameliorates atherosclerosis through inhibiting the activation of TAK1.

Song Li, Wenyi Li, Piaopiao Long +10 more · 2026 · International immunopharmacology · Elsevier · added 2026-04-24
Atherosclerosis is a chronic inflammatory condition marked by the deposition of lipids within the arterial wall and the infiltration of inflammatory cells, culminating in the development of atheroscle Show more
Atherosclerosis is a chronic inflammatory condition marked by the deposition of lipids within the arterial wall and the infiltration of inflammatory cells, culminating in the development of atherosclerotic plaques. Ubiquitin-specific protease 18, USP18, a specific deubiquitinating enzyme, has been demonstrated to exert protective effects on the cardiovascular system. Pathological studies were performed utilizing human coronary arteries obtained from the Forensic Medical Examination Center of Guizhou Medical University, in conjunction with the aorta from experimental ApoE knockout mice. The ApoE knockout mice underwent intervention with adenovirus carrying USP18-RNAi and a control adenovirus containing hU6-MCS-CMV-EGFP, after which pathological analyses were conducted. In vitro, THP-1 cells, induced with phorbol ester, were subjected to treatment with si-USP18 or si-NC, followed by exposure to oxidized low-density lipoprotein. The expression levels of USP18 and proteins associated with the TAK1/NF-κB signaling pathway, as well as the interaction between USP18 and TAK1, were assessed using Western blotting, RT-PCR, and immunofluorescence techniques.The interaction between USP18 and TAK1 was confirmed using molecular docking techniques, co-immunoprecipitation assays, and immunofluorescence analysis. The purpose of this study is to explore the role of USP18 on atherosclerosis and the underlying mechanism. The expression of USP18 is elevated in early-stage human coronary atherosclerotic plaques but decreases in advanced lesions. Treatment of macrophages derived from THP-1 cells and bone marrow-derived macrophages (BMDMs) with lipopolysaccharide (LPS) results in reduced USP18 expression. In ApoE USP18 modulates TAK1 to suppress the activation of the NF-κB signaling pathway in macrophages, consequently exerting an anti-atherosclerotic effect and offering a potential therapeutic strategy for atherosclerosis treatment. Show less
no PDF DOI: 10.1016/j.intimp.2026.116516
APOE

Efficacy of personalized acupuncture combined with accelerated deep transcranial magnetic stimulation in mild cognitive impairment: A randomized controlled trial.

Jing Xia, Xinhe Wu, Zitao Wang +9 more · 2026 · Integrative medicine research · Elsevier · added 2026-04-24
This study evaluated the efficacy of combining personalized acupuncture with accelerated deep transcranial magnetic stimulation (adTMS) for mild cognitive impairment (MCI). In this randomized, double- Show more
This study evaluated the efficacy of combining personalized acupuncture with accelerated deep transcranial magnetic stimulation (adTMS) for mild cognitive impairment (MCI). In this randomized, double-blind, controlled trial, 120 MCI patients were assigned to a Combined group (personalized acupuncture + active adTMS), a Single Stimulation group (active adTMS + sham acupuncture), or a Placebo group (sham TMS + sham acupuncture). The primary outcome was the change in Montreal Cognitive Assessment (MoCA) score at 12 weeks. Secondary outcomes included P300 latency, magnetic resonance spectroscopy (MRS) NAA/Cr ratio, serum brain-derived neurotrophic factor (BDNF), C-reactive protein (CRP), interleukin-6 (IL-6), and the Modified Barthel Index (MBI). The Combined group showed a significantly greater improvement in MoCA scores (3.2 ± 1.3 points) compared to the Single Stimulation (1.9 ± 1.2 points; mean difference 1.3, 95 % CI 0.4 to 2.2) and Placebo groups (1.1 ± 1.0 points; mean difference 2.1, 95 % CI 1.2 to 3.0). The Combined group also demonstrated greater reductions in P300 latency and increases in NAA/Cr ratio and serum BDNF levels than the other groups. The combination of personalized acupuncture and adTMS significantly improves cognitive function in MCI patients, supported by positive changes in electrophysiological and metabolic markers. This integrative approach represents a promising non-pharmacological strategy for MCI.Trial registration: International Traditional Medicine Clinical Trials Registry (ITMCTR2025000652). Show less
📄 PDF DOI: 10.1016/j.imr.2026.101289
BDNF

Ginsenoside Rg3 Mitigates LPS-Induced Injury in Human Bronchial Epithelial Cells by Restoring Autophagic Flux and Inhibiting the TLR4/NF-κB-Mediated Inflammatory Response.

Xingyu Tao, Lingjiao Liu, Xiaoke Gu +5 more · 2026 · Journal of inflammation research · added 2026-04-24
To elucidate the molecular mechanism by which ginsenoside Rg3 (G-Rg3) protects human bronchial epithelial (HBE) cells against lipopolysaccharide (LPS)-induced injury, focusing on its regulation of aut Show more
To elucidate the molecular mechanism by which ginsenoside Rg3 (G-Rg3) protects human bronchial epithelial (HBE) cells against lipopolysaccharide (LPS)-induced injury, focusing on its regulation of autophagic flux and the TLR4/NF-κB-mediated inflammatory pathway. HBE cells were treated with LPS (1-100 ng/mL) to induce autophagy dysregulation and inflammation. G-Rg3 (2-16 μM) was administered to evaluate its protective effects. Western blotting was used to detect autophagy-related proteins (ATG4B, ATG7, PIK3C3, LC3B, p62) and TLR4/NF-κB signaling molecules; ELISA quantified proinflammatory cytokines (TNF-α, IL-1β, IL-2, IL-6, IL-8); PI staining and flow cytometry analyzed cell death and apoptosis. LPS dose-dependently upregulated the expression of autophagy-related proteins (ATG4B, ATG7, PIK3C3, p62, LC3B-II), with accumulated p62 and LC3B-II indicating impaired clearance of autophagic substrates. Additionally, G-Rg3 inhibited LPS-induced TLR4/NF-κB activation, suppressed proinflammatory cytokine secretion, and attenuated HBE cell apoptosis/necrosis. G-Rg3 mitigates LPS-induced HBE cell injury by dual mechanisms: restoring impaired autophagic flux and inhibiting the TLR4/NF-κB inflammatory cascade. These findings identify G-Rg3 as a promising therapeutic agent targeting the crosstalk between autophagy and inflammation in respiratory diseases such as COPD and acute lung injury. Show less
no PDF DOI: 10.2147/JIR.S555053
PIK3C3

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

Genetic insights into radiomic and proteomic changes under β1-blockers treatment in hypertensive heart disease and hypertrophic cardiomyopathy.

Zhe Chen, Yifan Tang, Shuang Li +6 more · 2026 · BMC medicine · BioMed Central · added 2026-04-24
Hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) are characterized by left ventricular hypertrophy and diastolic dysfunction. Despite overlapping remodeling features, their disti Show more
Hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) are characterized by left ventricular hypertrophy and diastolic dysfunction. Despite overlapping remodeling features, their distinct mechanisms and therapeutic responses remain unclear. This study integrated genetic, imaging, and proteomic data to identify key mediators underlying β1-adrenergic receptor blockers (β1-blockers)-related therapeutic heterogeneity between HHD and HCM. Genetic instruments for β1-blockers were derived from two genome-wide association studies and integrated with cardiac magnetic resonance radiomic traits and plasma proteomic data from the UK Biobank, along with disease outcomes from FinnGen. A refined two-stage network Mendelian randomization framework with pleiotropy-robust estimators identified mediators of treatment response. To further elucidate their biological and clinical significance, additional analyses were performed, including drug-target profiling, molecular docking, adverse events (AEs) assessment, and drug prediction. We identified three types of imaging features and ten mediator proteins that contributed to therapeutic responses in HHD and HCM. These mediators were categorized as either mediating (aligned with therapeutic outcomes) or suppressing (opposing therapeutic outcomes). Left ventricular regional radial strain acted as a suppressing factor in HHD but a mediating factor in HCM, whereas end-diastolic and end-systolic volumes consistently showed suppressing effects in both. Regional myocardial wall thickness also exerted a suppressing role in HCM. Among protein mediators, APOE, CGREF1, ITGA5, LSP1, NOS3, and NPPB were linked to HHD, whereas DUSP13, ITGA11, NID1, and SERPINA4 were related to HCM. Specifically, APOE, ITGA5, NOS3, NPPB, DUSP13, and ITGA11 acted as mediating factors, while CGREF1, LSP1, NID1, and SERPINA4 served as suppressing ones. These findings remained robust after pleiotropy adjustment and other genetic analyses. Molecular docking revealed interactions between ADRB1, the β1-blockers target, and downstream proteins, while drug prediction identified eight potential compounds linked to these mediators. Additionally, AE analyses indicated that some targets, such as DUSP13, could both mitigate and aggravate common AEs while contributing to cardiac therapy. This integrative multi-omics analysis revealed distinct imaging and proteomic mechanisms of genetically proxied β1-blockers in HHD and HCM, providing genetic evidence for differential therapeutic responses and highlighting molecular targets for precision cardiovascular therapy. Show less
📄 PDF DOI: 10.1186/s12916-026-04691-5
APOE

Site-Specific Blockade of LPA-TRPV1 Interaction at K710 Residue Influences on Myocardial Ischemia/Reperfusion Injury in Ex Vivo Mouse Hearts.

Muge Qile, Zhaofei Luo, Chao Wu +7 more · 2026 · Anesthesia and analgesia · added 2026-04-24
Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators rel Show more
Myocardial ischemia/reperfusion (I/R) injury commonly occurs in patients undergoing cardiac or noncardiac surgeries, increasing perioperative mortality risk. Although numerous endogenous mediators released during I/R contribute to myocardial damage, their mechanisms require further elucidation. We investigated whether lysophosphatidic acid (LPA), a bioactive phospholipid, mediates myocardial I/R injury by interacting with cardiac transient receptor potential vanilloid 1 (TRPV1). A TRPV1K710N knock-in mouse model was generated by CRISPR/Cas9, introducing a point mutation at K710, the known LPA-binding site on TRPV1. Langendorff perfused isolated hearts from TRPV1K710N and wild-type (WT) mice underwent global I/R injury with or without exogenous LPA (10 μM). Myocardial infarct size, coronary effluent LDH levels, and mitochondrial ultrastructure/function were assessed. Additionally, H9c2 cardiomyocytes were transfected with a pCMV6-entry plasmid carrying TRPV1-K710N or TRPV1-WT for mitochondrial calcium influx and cell viability assays. The V1-Cal peptide (1μM), targeting the K710 region, was applied ex vivo and in vitro to block LPA-TRPV1 interaction. TRPV1K710N hearts exhibited resistance to global I/R injury versus WT hearts, with reduced infarct size (28.3 ± 2.4% vs 39.9 ±2.3%, respectively, P= 0006), lower LDH levels, and attenuated mitochondrial damage. Exogenous LPA exacerbated I/R injury in WT hearts, increasing infarct size (63.7 ± 1.2% vs vehicle: 38.4 ± 2.4%; P <.0001), LDH release, and mitochondrial damage. TRPV1K710N hearts were resistant to LPA-induced injury, with no significant increase in infarct size after LPA treatment. Exogenous LPA induced pronounced swelling in mitochondria isolated from WT hearts, while mitochondria from TRPV1K710N hearts showed resistance to LPA challenge. In H9c2 cells, LPA significantly decreased viability in rTRPV1-WT cells and elevated mitochondrial calcium influx relative to rTRPV1-K710N cells. V1-Cal peptide attenuated LPA-mediated myocardial injury in WT hearts and reduced mitochondrial calcium overload in H9c2 cells. Blockade of the TRPV1 K710 site by K710N mutation or V1-Cal peptide mitigates LPA-mediated myocardial injury and mitochondrial damage/dysfunction in isolated mouse hearts. Targeting the cardiac LPA-TRPV1 interaction represents a promising therapeutic strategy against perioperative myocardial injury. Show less
no PDF DOI: 10.1213/ANE.0000000000007907
LPA

Simulated closed-loop magnetic stimulation promotes function recovery and axonal regeneration in spinal cord injury.

Lechi Zhang, Zhihang Xiao, Chunya Xia +6 more · 2026 · Communications biology · Nature · added 2026-04-24
Spinal cord injury (SCI) represents significant central nervous system trauma and has consistently been a focal point of research in the domain of neural regeneration and repair. Currently, there is n Show more
Spinal cord injury (SCI) represents significant central nervous system trauma and has consistently been a focal point of research in the domain of neural regeneration and repair. Currently, there is no effective treatment available. Various modalities of magnetic stimulation have emerged for recovery from spinal cord injuries; however, the underlying mechanisms remain unclear, significantly hindering the application of magnetic stimulation technologies in treating such injuries. This study aims to elucidate these relevant mechanisms by establishing a simulated closed-loop magnetic stimulation system. In this study, we established a right hemisection model at T8 in mice and administered continuous simulated closed-loop magnetic stimulation targeting the left motor cortex and right L5 nerve root over six weeks. We subsequently utilized a spinal cord dorsal hemisection model to examine regeneration of the corticospinal tract (CST). Motor-evoked potential assessments and calcium imaging techniques were employed to explore neural circuit repair. Additionally, we integrated transcriptomics, proteomics, and metabolomics approaches to investigate related mechanisms. The findings indicate that simulated closed-loop magnetic stimulation effectively restores motor function in the hind limbs, promotes the regeneration of corticospinal tracts in mice with spinal cord injuries, and facilitates the reconstruction of sensorimotor circuits and functions within the spinal cord. Simulated closed-loop magnetic stimulation significantly enhances axonal regeneration of the CST following SCI. This effect may be mediated through the activation of the AMPK-CREB-BDNF signaling pathway, which promotes neurotrophic factor secretion and subsequently induces nerve axon regeneration. This study suggests that simulated closed-loop magnetic stimulation represents a promising therapeutic approach for the treatment for impaired gait following SCI. Show less
no PDF DOI: 10.1038/s42003-026-09848-9
BDNF axonal regeneration central nervous system function recovery magnetic stimulation neural regeneration spinal cord injury trauma

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

Late-life methionine restriction attenuates neuroinflammation in Alzheimer's disease mice via FGF21 activation in a metabolism-independent manner.

Yuyu Zhang, Yiju Li, Qianxu Wang +4 more · 2026 · Alzheimer's & dementia : the journal of the Alzheimer's Association · Wiley · added 2026-04-24
Aging worsens Alzheimer's disease (AD) peripheral metabolism and central pathology, yet few interventions are effective when started late. Methionine restriction (MR) induces the hepatokine FGF21 and Show more
Aging worsens Alzheimer's disease (AD) peripheral metabolism and central pathology, yet few interventions are effective when started late. Methionine restriction (MR) induces the hepatokine FGF21 and may protect brain function, but its efficacy and mechanisms when started late are unclear. Fourteen-month-old male APP/PS1 mice received 17 weeks of MR (0.17% methionine); behavioral, histological, and molecular assays were performed and hippocampal FGFR1 was knocked down by adeno-associated virus. Late-life MR improved peripheral glucose/lipid profiles, reduced Aβ deposition, preserved synaptic markers, and suppressed neuroinflammation. MR-induced hepatic FGF21 and brain FGFR1-AMPKα signaling to inhibit NFκB; hippocampal FGFR1 knockdown abolished MR's neuroprotective effects while leaving peripheral metabolic changes intact. Even when initiated in late life, MR robustly reduces AD pathology via the hepatic FGF21-brain FGFR1 axis, independent of peripheral metabolic changes. These preclinical findings position MR and FGF21-FGFR1 axis as actionable late-life intervention targets with potential for clinical translation. Show less
📄 PDF DOI: 10.1002/alz.71287
FGFR1

Metformin improves the impairment of cognitive function caused by total abdominal irradiation via the miR-34a-5p/BDNF/CREB axis.

Jianyu Wang, Juan Guo, Li Guo +5 more · 2026 · Molecular neurobiology · Springer · added 2026-04-24
The gastrointestinal system is of particular importance in radiation biodosimetry because of its constant cell renewal and sensitivity to radiation-induced injury. It has been reported that total abdo Show more
The gastrointestinal system is of particular importance in radiation biodosimetry because of its constant cell renewal and sensitivity to radiation-induced injury. It has been reported that total abdominal irradiation causes distant cognitive defects in a mouse model. In this study, we demonstrated that metformin alleviated the cognitive dysfunction caused by total abdominal irradiation. No neuropathological changes were observed in hippocampal tissues in control, irradiated, and irradiated plus metformin-treated groups. However, we found that metformin treatment improved the expression of brain-derived neurotrophic factor and the phosphorylation level of cAMP response element-binding in the hippocampus from irradiated mice. Furthermore, our results revealed that metformin treatment reduced the expression of miR-34a-5p, which targets the brain-derived neurotrophic factor mRNA, in the small intestine, peripheral blood, and hippocampus. More importantly, injection of miR-34a-5p agomir inhibited the enhancement effects of metformin on the cognitive defects induced by total abdominal irradiation, as well as the enhanced expression of BNDF and the phosphorylation level of cAMP response element-binding in the hippocampus. Thus, our results provide alternative strategies for the treatment of total abdominal irradiation-induced distant cognitive impairment using metformin and further confirmed that miR-34a-5p is a potential drug target to reduce the cognitive defects caused by total abdominal irradiation. Show less
📄 PDF DOI: 10.1007/s12035-026-05696-0
BDNF

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

Metabolomics Identified Caloric Restriction-associated Glycerophospholipid Alterations in ApoE-/- Mice.

Zi-Yu Wei, He-Ping Wang, Song Tang +10 more · 2026 · Genomics, proteomics & bioinformatics · Oxford University Press · added 2026-04-24
Caloric restriction (CR) improves metabolic health and reduces the risk of aging-related vascular diseases. However, the systematic metabolic reprogramming associated with CR remains unclear. To addre Show more
Caloric restriction (CR) improves metabolic health and reduces the risk of aging-related vascular diseases. However, the systematic metabolic reprogramming associated with CR remains unclear. To address this, we performed multi-tissue metabolomic profiling (liver, heart, and serum) in apolipoprotein E-deficient (ApoE-/-) mice subjected to CR. Metabolomic analyses of the multiple tissues revealed that glycerophospholipid metabolism pathway was consistently modulated by CR. To explore its relevance in vascular diseases, we performed serum metabolomic profiling in an abdominal aortic aneurysm (AAA) model induced by angiotensin Ⅱ (AngⅡ) infusion in ApoE-/- mice. The level of lysophosphatidylethanolamine (LPE) (16:0/0:0), a metabolite in the glycerophospholipid metabolism pathway, was elevated during AAA progression and significantly reduced by CR intervention, suggesting its potential as a vascular disease risk factor. Notably, glycerophospholipid metabolism and LPE (16:0) were significantly associated with vascular diseases and aging-related indicators in human multi-omics data, including public transcriptomic and lipidomic, and our serum multi-omics profiling of 76 healthy aged individuals. Collectively, our findings establish glycerophospholipid metabolism and LPE (16:0) as systemic signatures of CR with diagnostic potential. They highlight a crucial link between systemic metabolism and vascular remodeling and remodeling-associated vascular diseases, while also functioning as indicators of systemic aging. Show less
no PDF DOI: 10.1093/gpbjnl/qzag030
APOE

Impact of hypertension on associations of all-cause mortality with admission lipoprotein (a) in acute decompensated heart failure.

Ashen L Vidanage, Tianyu Xu, Zihao Chen +9 more · 2026 · International journal of cardiology. Cardiovascular risk and prevention · Elsevier · added 2026-04-24
Serum lipoprotein(a) [Lp(a)] is recognized as an independent risk factor for cardiovascular disease. However, whether hypertension modifies the association between Lp(a) and adverse outcomes in acute Show more
Serum lipoprotein(a) [Lp(a)] is recognized as an independent risk factor for cardiovascular disease. However, whether hypertension modifies the association between Lp(a) and adverse outcomes in acute decompensated heart failure (ADHF) remains unclear. We investigated how hypertension status influences the relationship between Lp(a) and all-cause mortality in ADHF. We conducted a single-center retrospective observational study including 2610 patients hospitalized with ADHF. We normalized the distribution of Lp(a) by a logarithmic transformation and assessed the risk of all-cause mortality with Lp(a), using Cox regression with adjustment for potential confounders. Among 2610 patients (39.0% women; mean age, 68.8 years), 1606 (61.5%) had hypertension. Over 4.1 years (median), 1287 deaths occurred. In all patients, log-transformed Lp(a) was significantly associated with mortality (adjusted HR 1.21; 95% CI, 1.05-1.39; Increased admission Lp(a) levels were associated with a higher risk of all-cause mortality in ADHF patients with hypertension. Further studies are needed to explore the mechanistic links among Lp(a), hypertension and ADHF. Show less
📄 PDF DOI: 10.1016/j.ijcrp.2026.200594
LPA

Advances in plasma biomarkers for the diagnosis of Alzheimer's disease.

Hong Wu, Ling Liu, Lianlin Zeng · 2026 · Brain research · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory impairment and deficits in other cognitive domains, ultimately leading to loss of independence in activitie Show more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory impairment and deficits in other cognitive domains, ultimately leading to loss of independence in activities of daily living. As AD becomes an increasingly prevalent global health burden, the demand for early diagnosis of AD in clinical practice is growing. Due to factors such as accessibility, invasiveness, and testing costs, blood-based biomarkers (BBMs) are generally more favored by patients and more feasible compared to lumbar puncture or neuroimaging. Blood-based biomarkers may represent a breakthrough area for AD diagnosis. This review summarizes the AD biomarkers that have been widely studied to date, aiming to provide a comprehensive understanding of these markers to advance early diagnosis and offer valuable insights for clinical practice. First, we summarize the currently discovered biomarkers that can be used for AD diagnosis. It is noted that only a few highly promising biomarkers have been practically applied in the clinical auxiliary diagnosis of AD (including APOE genotyping for assessing genetic risk; Aβ42/Aβ40, P-tau181/Aβ42, and p-tau217 for differentiating AD; NfL for monitoring AD progression). It should be noted that current AD biomarkers are only applicable for clinical auxiliary diagnosis and cannot completely replace classic assessment scales for independent diagnosis. Additionally, we summarize the clinical advantages and potential challenges of these biomarkers, as well as the differences in their applicability to different populations. We emphasize that extensive clinical cohort studies are still needed in the future to further clarify the specificity of blood biomarkers and develop more suitable laboratory testing methods for clinical use to meet the clinical demand for high-sensitivity and high-specificity AD biomarker detection. Show less
no PDF DOI: 10.1016/j.brainres.2025.150138
APOE

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

Macrophage-mediated CXCL2 regulation of EPC homing promotes the progression of atherosclerosis.

Jingting Mai, Runlu Sun, Wenhao Liu +4 more · 2026 · Cytokine · Elsevier · added 2026-04-24
Atherosclerosis is a chronic inflammatory disease driven by pathological angiogenesis and plaque instability. Herein, we investigated the role of macrophage-derived CXCL2 in mediating endothelial prog Show more
Atherosclerosis is a chronic inflammatory disease driven by pathological angiogenesis and plaque instability. Herein, we investigated the role of macrophage-derived CXCL2 in mediating endothelial progenitor cell (EPC) homing during atherosclerosis progression. Using ApoE-/- mice on a high-fat diet and in vitro co-culture models, we found that infused EPCs exacerbated plaque burden, neovascularization, and matrix degradation. Macrophages were essential for EPC recruitment to plaques. Ox-LDL-stimulated macrophages enhanced EPC angiogenic functions, with transcriptome sequencing identifying CXCL2 as a key upregulated mediator. Functional experiments confirmed CXCL2's critical role. In vivo silencing of CXCL2 attenuated EPC homing, reduced plaque size and lipid accumulation, decreased neovascularization, and stabilized the plaque matrix. Our findings demonstrate that macrophages promote pathological angiogenesis and plaque progression via CXCL2, suggesting that targeting this chemokine could be a novel therapeutic strategy for stabilizing atherosclerotic plaques. Show less
no PDF DOI: 10.1016/j.cyto.2026.157114
APOE

UFM1 suppresses VSMCs phenotypic switching and attenuates atherosclerosis by inhibiting AKT phosphorylation.

Qianru Zhang, Mirenuer Aikebaier, Yefan Hu +5 more · 2026 · Biochemical pharmacology · Elsevier · added 2026-04-24
Atherosclerosis is a chronic and progressive inflammatory disease that can lead to adverse cardiovascular and cerebrovascular events. Phenotypic switching of vascular smooth muscle cells (VSMCs) plays Show more
Atherosclerosis is a chronic and progressive inflammatory disease that can lead to adverse cardiovascular and cerebrovascular events. Phenotypic switching of vascular smooth muscle cells (VSMCs) plays a pivotal role in its development and progression, but the upstream regulatory mechanisms remain incompletely defined. Here, we identify ubiquitin-fold modifier 1 (UFM1), a ubiquitin-like protein, as a critical regulator of VSMCs plasticity and atherogenesis. In VSMCs stimulated with oxidized low-density lipoprotein (ox-LDL), UFM1 overexpression markedly attenuated phenotypic switching, restoring contractile features and suppressing synthetic activation, accompanied by reduced proliferation and migration. In contrast, UFM1 knockdown further exacerbated these phenotypic alterations. In ApoE Show less
no PDF DOI: 10.1016/j.bcp.2026.117957
APOE

Construction of a survival model for predicting biochemical recurrence of prostate cancer based on propionate metabolism-related genes.

Baosai Lu, Yalin Niu, Xi Liu +2 more · 2026 · Translational andrology and urology · added 2026-04-24
About 20-40% of prostate cancer (PCa) develop biochemical recurrence (BCR) after surgery, and propionate metabolism may contribute to tumor progression. BCR remains a major clinical challenge in PCa, Show more
About 20-40% of prostate cancer (PCa) develop biochemical recurrence (BCR) after surgery, and propionate metabolism may contribute to tumor progression. BCR remains a major clinical challenge in PCa, as current tools based on histopathology and prostate-specific antigen (PSA) fail to capture the molecular heterogeneity driving the disease. While metabolic reprogramming is known to facilitate post-treatment adaptation, the specific role of propionate metabolism in this context remains largely unexplored. Therefore, this study aimed to systematically investigate propionate metabolism-related genes (PMRGs) to develop a novel prognostic model for the improved early prediction of recurrence. In this study, The Cancer Genome Atlas-Prostate Adenocarcinoma (TCGA-PRAD), GSE70770 and 412 PMRGs were employed. Differentially expressed genes (DEGs) in PCa and control and DEGs2 in BCR and no BCR samples obtained by differential analysis were intersected with PMRGs to get candidate genes. After Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, biomarkers were identified to construct risk models. Biomarkers including In this study, PMRGs were regarded as biomarkers in PCa for risk model construction, which suggest that propionate metabolism represents a biologically relevant axis in PCa recurrence and may offer a novel framework for biomarker-driven risk assessment. Show less
📄 PDF DOI: 10.21037/tau-2025-aw-811
LPL