👤 Xiaomin Liu

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

Cholesterol metabolism: molecular mechanisms, biological functions, diseases, and therapeutic targets.

Daxin Cui, Xiaoqian Yu, Qiuyue Guan +4 more · 2025 · Molecular biomedicine · BioMed Central · added 2026-04-24
Cholesterol, an indispensable structural and signaling lipid, is fundamental to cellular membrane integrity, steroidogenesis, and developmental morphogen pathways. Its homeostasis hinges on the precis Show more
Cholesterol, an indispensable structural and signaling lipid, is fundamental to cellular membrane integrity, steroidogenesis, and developmental morphogen pathways. Its homeostasis hinges on the precise coordination of four interdependent metabolic modules: de novo biosynthesis, intestinal absorption, enzymatic conversion, and systemic clearance. This review delineates the molecular machinery governing these processes-from the Bloch/Kandutsch-Russell synthesis pathways and niemann-pick C1-like 1 (NPC1L1)-mediated cholesterol uptake to cholesterol 7α-hydroxylase (CYP7A1)-driven bile acid synthesis and HDL-dependent reverse transport. We further elucidate cholesterol's multifaceted roles in lipid raft assembly, Hedgehog signal transduction, and vitamin D/hormone production. Critically, dysregulation of cholesterol flux underpins pathogenesis in atherosclerosis, metabolic dysfunction-associated fatty liver disease (MAFLD), neurodegenerative disorders, and oncogenesis, with disrupted synthesis, efflux, or esterification cascades serving as key drivers. Emerging therapeutic strategies extend beyond conventional statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors to include transformative modalities: CRISPR-based in vivo gene editing (e.g., VERVE-101 targeting PCSK9), small interfering RNA (siRNA) therapeutics (inclisiran), and microbiota-directed interventions. Pioneering approaches against targets Such as angiopoietin-like 3 (ANGPTL3), lipoprotein(a) [Lp(a)], and asialoglycoprotein receptor 1 (ASGR1)-alongside repurposed natural agents (berberine, probiotics)-offer promise for mitigating residual cardiovascular risk and advancing precision cardiometabolic medicine. By integrating mechanistic insights with clinical advancements, this review underscores the transition from broad-spectrum therapies to personalized, multi-target regimens, offering a roadmap for mitigating cholesterol-related diseases in the era of genomic and metabolic medicine. Show less
📄 PDF DOI: 10.1186/s43556-025-00321-3
LPA

Case Report: A rare case of hepatoid carcinoma of the ovary with genomic profiling and long-term follow-up: diagnostic and therapeutic perspectives.

Yufang Zuo, Xuan Liu, Yajun Pang +7 more · 2025 · Frontiers in oncology · Frontiers · added 2026-04-24
Hepatoid carcinoma of the ovary (HCO) is a highly uncommon and aggressive neoplasm originating from the surface epithelial cells of the ovary, characterized by hepatocyte-like differentiation. To date Show more
Hepatoid carcinoma of the ovary (HCO) is a highly uncommon and aggressive neoplasm originating from the surface epithelial cells of the ovary, characterized by hepatocyte-like differentiation. To date, most information on HCO is derived from case reports, with fewer than 50 documented cases globally. In this case report, we present a detailed account of the diagnosis, treatment, and prognosis of a patient diagnosed as having bilateral HCO, which is even rarer. Targeted next-generation sequencing revealed somatic mutations in PIK3C3 and TP53, with no BRCA1/2 alterations, and a molecular profile consistent with microsatellite stability and low tumor mutational burden. We also review the current literature to situate our findings within the broader context of existing knowledge. Given the rarity of bilateral HCO, our objective is to contribute to the existing body of knowledge by providing a comprehensive description of its clinical features, molecular characteristics, and treatment strategies. This effort may enhance understanding of this rare malignancy and offer insights to improve patient outcomes in clinical practice. Show less
no PDF DOI: 10.3389/fonc.2025.1631424
PIK3C3

Genome-wide association studies identify genetic determinants of synucleinopathy biomarkers.

Emma N Somerville, Lang Liu, Michael Ta +4 more · 2025 · medRxiv : the preprint server for health sciences · added 2026-04-24
α-synucleinopathies are clinically and biologically heterogeneous disorders lacking reliable biomarkers to assist with early diagnosis, disease progression, patient stratification, and therapeutic tar Show more
α-synucleinopathies are clinically and biologically heterogeneous disorders lacking reliable biomarkers to assist with early diagnosis, disease progression, patient stratification, and therapeutic targeting. Genetic variation is known to impact biomarker levels, influencing their utility and interpretation in research and clinical settings. We aimed to identify common genetic modulators of biomarker levels implicated in α-synucleinopathy pathogenesis. Genome-wide association studies (GWASs) were conducted on 63 CSF, plasma, and urine biomarkers in 581 individuals from the Parkinson's Progression Markers Initiative (PPMI). Analyses were adjusted for age, sex, disease status, and principal components. PD- and DLB-risk loci associations were separately assessed for each GWAS. We confirm strong associations between urine bis(monoacylglycerol)phosphate (BMP) isoforms and the variants The present study reveals established and novel genetic modulators of potential α-synucleinopathy biomarkers, demonstrating that genetic background significantly shapes biomarker levels. These genetic influences should be accounted for when conducting biomarker-based research, clinical trials, or therapeutic development to ensure accurate interpretation and improve their translational relevance. Show less
📄 PDF DOI: 10.64898/2025.12.29.25343142
APOE

SIRT7 regulates T-cell antitumor immunity through modulation BCAA and fatty acid metabolism.

Zuojian Hu, Yingji Chen, Jielin Lei +11 more · 2025 · Cell death and differentiation · Nature · added 2026-04-24
SIRT7, one of the least studied members of the Sirtuins family, is an NAD
no PDF DOI: 10.1038/s41418-025-01490-y
BCKDK

Decoding the Therapeutic Effects of Acupuncture in Hemorrhagic Stroke Using Single-Cell RNA Sequencing.

Chen Ruan, Jia Du, Wentao Zhang +8 more · 2025 · CNS neuroscience & therapeutics · Wiley · added 2026-04-24
Acupuncture has been proposed as a therapeutic intervention for stroke recovery, yet the underlying molecular mechanisms remain poorly understood. In this study, we used a mouse model of hemorrhagic s Show more
Acupuncture has been proposed as a therapeutic intervention for stroke recovery, yet the underlying molecular mechanisms remain poorly understood. In this study, we used a mouse model of hemorrhagic stroke induced by autologous blood injection to investigate the effects of acupuncture on post-stroke recovery at the cellular and molecular levels, utilizing single-cell RNA sequencing. Our findings revealed that acupuncture modulates the gene expression of microglia, astrocytes, and oligodendrocytes, three major glial cell types, which may contribute to the improvement of stroke-induced phenotypes. Notably, we identified a potential role of the APOE-TREM2 signaling axis, with ligand-binding interactions enhancing microglia activation and promoting their neuroprotective functions. These findings also suggested that acupuncture may promote microglia-astrocyte interactions, leading to enhanced neuroinflammation resolution and tissue repair. Our study provided new insights into the cellular mechanisms underlying acupuncture's therapeutic effects in stroke recovery and highlighted the potential of targeting glial cell-mediated pathways, including APOE-TREM2, as a strategy for improving post-stroke rehabilitation. Show less
📄 PDF DOI: 10.1002/cns.70689
APOE

ApoB/ApoA-Ι is associated with major cardiovascular events and readmission risk of patients after percutaneous coronary intervention in one year.

Jie Zhang, Mengyu Liu, Ju Gao +4 more · 2025 · Scientific reports · Nature · added 2026-04-24
Percutaneous coronary intervention (PCI) is a practical and effective method for treating coronary heart disease (CHD). This study aims to explore the influencing factors of major cardiovascular event Show more
Percutaneous coronary intervention (PCI) is a practical and effective method for treating coronary heart disease (CHD). This study aims to explore the influencing factors of major cardiovascular events (MACEs) and hospital readmission risk within one year following PCI treatment. Additionally, it seeks to assess the clinical value of Apolipoprotein B/Apolipoprotein A-I (ApoB/ApoA-I) in predicting the risk of one-year MACEs and readmission post-PCI. A retrospective study included 1938 patients who underwent PCI treatment from January 2010 to December 2018 at Shandong Provincial Hospital affiliated with Shandong First Medical University. Patient demographics, medications, and biochemical indicators were recorded upon admission, with one-year follow-up post-operation. Univariate and multivariate Cox proportional hazards regression models were utilized to establish the relationship between ApoB/ApoA-I levels and MACEs/readmission. Predictive nomograms were constructed to forecast MACEs and readmission, with the accuracy of the nomograms assessed using the concordance index. Subgroup analyses were conducted to explore the occurrence of MACEs and readmission. We observed a correlation between ApoB/ApoA-I and other lipid indices, including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) (P < 0.001). Univariate and multivariate Cox regression analyses demonstrated that ApoB/ApoA-I is an independent risk factor for MACEs in post-PCI patients (P = 0.038). Within one year, the incidence of MACEs significantly increased in the high-level ApoB/ApoA-I group (ApoB/ApoA-I ratio ≥ 0.824) (P = 0.038), while the increase in readmission incidence within one year was not statistically significant. Furthermore, a nomogram predicting one-year MACEs was established (Concordance Index: 0.668). Subgroup analysis revealed that ApoB/ApoA-I was associated with the occurrence of both MACEs and readmission in male patients, those using CCB/ARB/ACEI, those without multivessel diseases, or those with LDL-C < 2.6 mmol/L. The ApoB/ApoA-I ratio serves as an independent risk factor for one-year MACEs in post-PCI patients and correlates closely with other blood lipid indicators. ApoB/ApoA-I demonstrates significant predictive value for the occurrence of MACEs within one year.Trial registration Chinese clinical trial registry: No.ChiCTR22000597-23. Show less
📄 PDF DOI: 10.1038/s41598-024-84092-x
APOB

Olverembatinib for 8p11 myeloproliferative syndrome with a positive BCR-FGFR1 fusion gene: a case report.

Man Wu, Lin Huang, Yibin Yao +4 more · 2025 · Annals of hematology · Springer · added 2026-04-24
8p11 myeloproliferative syndrome (EMS) is a rare aggressive hematologic malignancy with a poor prognosis that can rapidly develop into acute leukemia. It is characterized by the translocation of fibro Show more
8p11 myeloproliferative syndrome (EMS) is a rare aggressive hematologic malignancy with a poor prognosis that can rapidly develop into acute leukemia. It is characterized by the translocation of fibroblast growth factor receptor-1 (FGFR1), and there is still a lack of effective and reliable treatment methods at present. This report provides a new therapeutic strategy for EMS patients diagnosed with BCR-FGFR1 fusion. This report describes a case of EMS patient with a positive BCR-FGFR1 fusion gene, whose manifestations are similar to those of chronic myeloid leukemia (CML). After diagnosis by fluorescence in situ hybridization (FISH) and RNA sequencing (RNA-seq), olverembatinib, the third-generation tyrosinase inhibitor (TKI) developed in China, was used for treatment. After monotherapy and follow-up for more than one year, partial molecular response (PR) was achieved. During this period, hematologic remission and cytogenetic remission were achieved. The treatment safety of the entire process was excellent. In summary, olverembatinib provides more treatment options for rare diseases such as 8p11 myeloproliferative syndrome. Show less
📄 PDF DOI: 10.1007/s00277-025-06522-8
FGFR1

Pediatric diffuse low-grade glioma with oligodendroglioma-like features: A case report.

Pengwei Hou, Chengzhu Cai, Meiyan Liu +2 more · 2025 · Experimental and therapeutic medicine · added 2026-04-24
The present case report presents the diagnostic challenges of pediatric diffuse low-grade glioma (pDLGG) with oligodendroglioma-like features. The patient, an 11-year-old girl, presented with refracto Show more
The present case report presents the diagnostic challenges of pediatric diffuse low-grade glioma (pDLGG) with oligodendroglioma-like features. The patient, an 11-year-old girl, presented with refractory epilepsy and brain imaging did not provide a clear diagnosis. Intraoperatively, the tumor appeared gray-yellow to gray-red, with moderate texture and unclear borders, consistent with LGG. Postoperative pathology showed diffuse infiltrative growth of the tumor, with pleomorphic cell morphology and oligodendroglioma-like gliocyte proliferation. Staining was positive for markers such as glial fibrillary acidic protein and Olig-2. Genomic analysis revealed BRAF V600E, fibroblast growth factor receptor (FGFR)1 and FGFR4 mutations, but no IDH mutations or other related mutations. The final diagnosis was pDLGG with alterations in the MAPK pathway. The present case underscores the importance of molecular and histological features in the diagnosis of pDLGG, especially when clinical and imaging characteristics are atypical, as molecular diagnostics provide key insights for disease classification. Show less
📄 PDF DOI: 10.3892/etm.2025.12985
FGFR1

Co-Targeting Biomimetic Nanoparticles Alleviate Atherosclerosis by Inhibiting the Vicious Circle Between Inflammation and Lipids.

Chengxi Wu, Yaoyao Li, Yuting Liu +7 more · 2025 · International journal of nanomedicine · added 2026-04-24
In the microenvironment of atherosclerosis (AS), low-density lipoprotein (LDL) accumulates in injured endothelial areas and undergoes oxidation, thereby generating oxidized LDL (ox-LDL). The formation Show more
In the microenvironment of atherosclerosis (AS), low-density lipoprotein (LDL) accumulates in injured endothelial areas and undergoes oxidation, thereby generating oxidized LDL (ox-LDL). The formation of ox-LDL, in turn, not only amplifies endothelial cell (EC) dysfunction but also triggers macrophage polarization into the pro-inflammatory M1 phenotype. This cascade results in increased inflammatory cytokine secretion and exacerbated lipid accumulation. Therefore, a dual-targeting strategy aimed at both ECs and macrophages to inhibit the vicious circle between inflammation and lipids is a promising avenue for AS treatment. Simvastatin (SIM)-loaded nanomicelles (PLA-PEG/SIM) were prepared using the thin-film hydration method. Then, platelet membrane (PM) was coated the nanomicelles via sonication to obtain PM@PLA-PEG/SIM dual-targeting biomimetic nanoparticles. The morphological features of the nanoparticles were assessed by transmission electron microscopy (TEM). Cytotoxicity was evaluated using the CCK-8 assay and live/dead cell staining. Their targeting ability toward ECs and macrophages was assessed by flow cytometry and confocal laser scanning microscopy (CLSM). The biosafety, targeting ability, and therapeutic efficacy of PM@PLA-PEG/SIM against AS were further validated in ApoE PM@PLA-PEG/SIM effectively reduced the drug toxicity of SIM, exhibiting good biocompatibility. In vitro, cell experiment results showed that the nanoparticles inhibited foam cell formation, decreased interleukin-6 (IL-6) expression, and increased interleukin-4 (IL-4) and interleukin-10 (IL-10) expression by promoting macrophage repolarization. In vivo, results indicated that the formulation demonstrated excellent plaque-targeting ability. More importantly, the plaque area and lipid levels in the PM@PLA-PEG/SIM group were lowest, and plaques were most stable, showing its best therapeutic efficiency. PM@PLA-PEG/SIM alleviated progression of AS by co-targeting ECs and macrophages to inhibit the vicious cycle between inflammation and lipids. Our study provides a new strategy for the treatment of the disease by the co-targeting biomimetic nanoparticle. Show less
📄 PDF DOI: 10.2147/IJN.S558039
APOE

Regulation of partial endothelial-to-mesenchymal transition by circATXN1 in ischemic diseases.

Yue Li, Zhe Zheng, Yanze Li +14 more · 2025 · Nature communications · Nature · added 2026-04-24
Ischemic injury induces a partial mesenchymal shift in endothelial cells (ECs), contributing to impaired vascular regeneration. However, the molecular regulators of this transitional state remain poor Show more
Ischemic injury induces a partial mesenchymal shift in endothelial cells (ECs), contributing to impaired vascular regeneration. However, the molecular regulators of this transitional state remain poorly defined. To address this, we performed circular RNA profiling of endothelial cells under ischemic-like conditions and identified a marked upregulation of a circular RNA, named circATXN1. Functional studies revealed that circATXN1 knockdown modulates endothelial phenotype and vascular response after ischemia. Functional studies have shown that knockdown of circATXN1 can regulate the endothelial cell phenotype and vascular response after ischemia. Mechanistically, circATXN1 knockdown enhances the demethylase protein ALKBH5 to reduce the RNA methylation level of the key transcription factor SLUG, thereby stabilizing SLUG. In animal models, suppression of circATXN1 enhances angiogenesis and improves recovery following ischemic injury. Here, we show that circATXN1 regulates partial endothelial-to-mesenchymal transition (EndMT) and angiogenesis by controlling SLUG mRNA methylation dynamics, highlighting its potential as a therapeutic target in ischemic disease. Show less
no PDF DOI: 10.1038/s41467-025-61596-2
SNAI1

Potassium molybdate blocks APN-dependent coronavirus entry by degrading receptor via PIK3C3-mediated autophagy.

Yunhang Zhang, Na Zhang, Yue Zhang +11 more · 2025 · Journal of virology · added 2026-04-24
Swine enteric coronaviruses pose a significant challenge to the global pig industry, inflicting severe diarrhea and high mortality rates among piglets, and resulting in substantial economic losses. In Show more
Swine enteric coronaviruses pose a significant challenge to the global pig industry, inflicting severe diarrhea and high mortality rates among piglets, and resulting in substantial economic losses. In our clinical practice, we observed that the addition of potassium molybdate (PM) to the feed could dramatically reduce diarrhea and diarrhea-related mortality in piglets. However, the underlying mechanisms remain elusive and merit further investigation. In this study, we revealed that PM effectively inhibited the infection of both aminopeptidase N (APN)-dependent coronaviruses, transmissible gastroenteritis virus (TGEV), and porcine respiratory coronavirus (PRCV), both Show less
no PDF DOI: 10.1128/jvi.01449-24
PIK3C3

ENO1-related gene signature predicts prognosis and therapeutic response in diffuse large B-cell lymphoma.

Wenli Yan, Xiaoxi Liu, Beibei Gao +6 more · 2025 · Frontiers in immunology · Frontiers · added 2026-04-24
Alpha-enolase (ENO1), the enzyme catalyzing 2-phosphoglycerate conversion to phosphoenolpyruvate, is highly expressed in diffuse large B-cell lymphoma (DLBCL) and correlates with adverse clinical outc Show more
Alpha-enolase (ENO1), the enzyme catalyzing 2-phosphoglycerate conversion to phosphoenolpyruvate, is highly expressed in diffuse large B-cell lymphoma (DLBCL) and correlates with adverse clinical outcomes. Thus, understanding the relationship between ENO1-related gene (ERG) network and DLBCL is imperative. Here, we integrated multi-omics profiling (RIP-seq, RNA-seq, and protein interactome analysis) to identify ERGs and established a prognostic model by machine learning algorithms. We identified eleven hub genes (CHERP, SYNE2, INTS1, FAP, MMP9, LRP5, RBM8A, PRMT5, SLC25A6, PABPC4, PSTPIP2) using RNA sequencing, RNA immunoprecipitation sequencing, and protein interaction profiling. A prognostic model was constructed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression in the GSE10846 dataset and validated in two independent cohorts. DLBCL patients were stratified into high- and low-risk groups based on the model, and clinical characteristics were compared. The tumor immune microenvironment (TIME) was analyzed using CIBERSORT and xCell algorithms to explore correlations with the ERG score. Drug sensitivity assays in DLBCL cell lines were performed to validate the model's predictive capacity for chemotherapy response. Furthermore, the functional role of PABPC4, a key gene in the scoring system, was investigated through A prognostic model including 11 hub genes was established. Patients in the high-risk group exhibited worse clinical outcomes and an immunosuppressive TIME, characterized by altered expression of immune checkpoint-related proteins. This group demonstrated increased sensitivity to vincristine, etoposide, and oxaliplatin. Knockdown of PABPC4 significantly inhibited cell proliferation, reduced colony formation, and delayed tumor growth The ERG scoring system offers a robust and precise tool for predicting survival and guiding personalized treatment in DLBCL patients. Show less
no PDF DOI: 10.3389/fimmu.2025.1644020
PABPC4

Multi-organ transcriptomics provide insights into growth regulation in the Dongtingking crucian carp (Carassius auratus indigentiaus).

Dan Zeng, Yunsheng Zhang, Hu Xia +4 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
To investigate the key regulatory genes and pathways related to growth traits in the Dongtingking crucian carp (Carassius auratus indigentiaus), the transcriptomes of brain, intestine, and muscle tiss Show more
To investigate the key regulatory genes and pathways related to growth traits in the Dongtingking crucian carp (Carassius auratus indigentiaus), the transcriptomes of brain, intestine, and muscle tissues were sequenced at early juvenile stage using RNA-Seq from two groups with extreme growth rates (fast-growing and slow-growing). A total of 65, 184, and 130 differentially expressed genes (DEGs) were detected in the brain, intestine, and muscle, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted that the PPAR signaling pathway, Insulin/PI3K/Akt/mTOR/FoxO/AMPK pathway, and Protein digestion and absorption pathways are crucial for growth in this species. Based on the transcriptome data, 32 key DEGs were identified, mainly participating in processes such as cell proliferation and differentiation, growth, development, and metabolism. Prominent examples are cyclic AMP-responsive element-binding protein 5 (creb5b), forkhead box protein O1-A (foxo1a), transcription factor AP-1-like (jun), lipoprotein lipase-like (lpl), angiopoietin-like 4 (angptl4), and egl nine homolog 3-like (egln3). This study enhances the understanding of the genetic factors and regulatory mechanisms responsible for variations in growth rates and provides a valuable basis for further studies on the regulatory mechanisms of growth in C. auratus indigentiaus. Show less
no PDF DOI: 10.1016/j.cbd.2025.101538
ANGPTL4

Key oxidized lipid metabolites in pancreatic cancer tissue and metastasis based on metabolomics analysis.

Hezhi Wang, Qingyu Yang, Hongxia Xiang +7 more · 2025 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Pancreatic cancer (PC) represents a highly lethal malignancy characterized by diagnostic challenges owing to nonspecific early symptoms and insufficiently sensitive biomarkers. This investigation soug Show more
Pancreatic cancer (PC) represents a highly lethal malignancy characterized by diagnostic challenges owing to nonspecific early symptoms and insufficiently sensitive biomarkers. This investigation sought to identify novel PC biomarkers through lipidomic profiling, an emerging metabolomics methodology examining lipid pathways in disease pathogenesis. We established a humanized murine PC model. Small-molecule oxidized lipid metabolites in primary pancreatic tumors and hepatic metastases were quantitatively analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) integrated with a comprehensive metabolomics platform. Multivariate statistical approaches including principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were systematically applied. Analysis identified 64 differentially expressed oxidized lipids structurally classified as unsaturated fatty acid derivatives. Comparative assessment of metabolic profiles revealed a pronounced reduction in prostaglandins (PGE Our findings establish prostaglandins PGE Show less
no PDF DOI: 10.1016/j.bbrc.2025.152900
LPA

Orlistat Confers Neuroprotection in Traumatic Brain Injury by Modulating Microglial Lipid Metabolism.

Chenxuan Yu, Yu Ni, Yuxuan Xiong +9 more · 2025 · Cells · MDPI · added 2026-04-24
Traumatic brain injury (TBI) represents a major cause of mortality and disability worldwide, particularly affecting young adults and elderly populations. This study investigates the neuroprotective po Show more
Traumatic brain injury (TBI) represents a major cause of mortality and disability worldwide, particularly affecting young adults and elderly populations. This study investigates the neuroprotective potential of orlistat (ORL), a gastrointestinal lipase inhibitor, in a murine TBI model. Behavioral, histological, and molecular analyses demonstrated that ORL significantly attenuated TBI-induced neurological damage. Microglial depletion experiments revealed that ORL's neuroprotective effects were largely mediated through microglial modulation. In vitro and in vivo studies showed that ORL suppressed microglial activation, phagocytosis, and migration. Single-cell RNA sequencing identified upregulation of lipoprotein lipase (LPL) in a TBI-induced microglial subpopulation. Molecular docking predicted ORL-LPL binding, suggesting direct enzymatic inhibition. Transcriptomic and metabolomic analyses further revealed ORL's modulation of microglial metabolic pathways and inflammatory responses. Our findings position ORL as a promising repurposed therapeutic for TBI through its novel mechanism of targeting microglial LPL-mediated neuroinflammation. Show less
📄 PDF DOI: 10.3390/cells14181469
LPL

Macrophage marker gene-driven prognostic models for esophageal cancer: integrating multi-omics analysis and therapeutic strategies.

Zehan Li, Huazhen Wu, Chuzhong Wei +15 more · 2025 · 3 Biotech · Springer · added 2026-04-24
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORD Show more
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORDC1, and BCKDK). This signature effectively stratified patients into high- and low-risk groups with significantly different overall survival, achieving area under the curve (AUC) values greater than 0.7 for 1-, 2-, and 3-year survival prediction. A high-risk status correlated with an immunosuppressive tumor microenvironment, characterized by lower infiltration of B cells and CD8 + T cells, and was associated with reduced sensitivity to multiple chemotherapeutic agents, including Cisplatin and 5-Fluorouracil. Conversely, a low-risk status was linked to greater immune cell infiltration and higher predicted chemosensitivity. At the single-cell level, pseudotime analysis revealed that macrophage maturation significantly correlated with a decreasing risk score, suggesting that mature macrophages may contribute to a favorable prognosis. Furthermore, cell communication analysis identified high-risk macrophages as dominant drivers of a pro-tumorigenic microenvironment via signaling pathways, such as SPP1 and complement. In conclusion, this seven-gene signature is a robust prognostic biomarker that offers a new strategy for personalized risk assessment and treatment selection in ESCA. The online version contains supplementary material available at 10.1007/s13205-025-04452-w. Show less
no PDF DOI: 10.1007/s13205-025-04452-w
BCKDK

High-abundance serum glycoproteins as valuable resources for glycopeptide standards.

Jun Li, Didi Liu, Yingjie Zhang +3 more · 2025 · Carbohydrate polymers · Elsevier · added 2026-04-24
High-abundance serum proteins, mostly modified by N-glycans, are usually depleted from human sera to achieve in-depth analyses of serum proteome and sub-proteomes. In this study, we show that these hi Show more
High-abundance serum proteins, mostly modified by N-glycans, are usually depleted from human sera to achieve in-depth analyses of serum proteome and sub-proteomes. In this study, we show that these high-abundance glycoproteins (HAGPs) can be used as valuable standard glycopeptide resources, as long as the structural features of their glycans have been well defined at the glycosite-specific level. By directly analyzing intact glycopeptides enriched from serum, we identified 1322 unique glycopeptides at 48 N-glycosites from the top 12 HAGPs (19 subclasses). These HAGPs could be further classified into four major groups based on the structural features of their attached N-glycans. Immunoglobins including IGHG1/2/3/4, IGHA1/2 and IGHM were mostly modified by core fucosylated and bisected N-glycans with rarely sialic acids. Alpha-1-acid glycoproteins (ORM1/2) and haptoglobins (HP) were mainly modified by tri-and tetra-antennary (40 %) N-glycans with antenna-fucoses and sialic acids. Complement components C3 and C4A/B were highly modified by oligo-mannose glycans. The other HAGPs including SERPINA1, A2M, TF, FGB/G and APOB mainly contain bi-antennary complex glycans with the common core structure and (sialyl-) LacNAc branch structures. These HAGPs are easily detected by LC-MS analysis and therefore could be used as standard glycopeptides for glycoproteomic methodology studies as well as possible clinical utilities. Show less
no PDF DOI: 10.1016/j.carbpol.2024.122746
APOB

Modulation of β secretase and neuroinflammation by biomimetic nanodelivery system for Alzheimer's disease therapy.

Xiaolei Song, Chenchen Wang, Qin Ding +8 more · 2025 · Journal of controlled release : official journal of the Controlled Release Society · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disorder. The vicious circle between amyloid-β peptide (Aβ) overgeneration and microglial dysfunction is an important path Show more
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disorder. The vicious circle between amyloid-β peptide (Aβ) overgeneration and microglial dysfunction is an important pathological event that promotes AD progression. However, therapeutic strategies toward only Aβ or microglial modulation still have many problems. Herein, inspired by the Aβ transportation, an Aβ-derived peptide (CKLVFFAED) engineered biomimetic nanodelivery system (MK@PC-R NPs) is reported for realizing BBB penetration and reprogram neuron and microglia in AD lesion sites. This hollow mesoporous Prussian blue-based MK@PC-R NPs carrying curcumin and miRNA-124 can down-regulate β secretase expression, thereby inhibiting Aβ production and reducing Aβ-induced neurotoxicity. Meanwhile, MK@PC-R NPs with excellent antioxidant and anti-inflammatory properties could normalize the microglial phenotype and promote Aβ degradation, providing neuroprotection. As expected, after treatment with MK@PC-R NPs, the Aβ burdens, neuron damages, neuroinflammation, and memory deficits of transgenic AD mice (APP/PS1 mice) are significantly attenuated. Overall, this biomimetic nanodelivery system with anti-Aβ and anti-inflammatory properties provides a promising strategy for the multi-target therapy of early AD. Show less
no PDF DOI: 10.1016/j.jconrel.2024.12.060
BACE1

Mitochondrial proteins: Potential pathophysiological mechanisms of malignant progression in HCC.

Yicun Liu, Yawen Shao, Xudong Zhu +2 more · 2025 · PloS one · PLOS · added 2026-04-24
Based on the special role of mitochondria in tumour energy metabolism. We hope to explore the pathogenesis and potential therapeutic targets of Hepatocellular carcinoma by analysing the expression of Show more
Based on the special role of mitochondria in tumour energy metabolism. We hope to explore the pathogenesis and potential therapeutic targets of Hepatocellular carcinoma by analysing the expression of 1136 mitochondrial proteins in hepatocellular carcinoma and their mechanisms in the Human.MitoCarta3.0 database. The expression of 1136 mitochondrial proteins in HCC was analysed by the TCGA database. We selected the top eight mitochondrial proteins among the highly expressed mitochondrial proteins that had not been studied in HCC and were statistically (P < 0.05) significant, according to fold change. Protein expression was verified by real-time quantitative reverse transcription polymerase chain reaction in tumours and adjacent paracancerous tissues of 34 pairs of HCC patients. Further in HCC cells, the expression of FDPS, DNA2 and MYO19 was verified. Clinical correlations of FDPS, DNA2 and MYO19 were analysed by UALCAN and KM-plot databases. Immune correlation of FDPS, DNA2 and MYO19 was analysed by TIMER2.0 and Sangerbox3.0 online databases. Mitochondrial proteins were expressed on all 24 chromosomes. More than 2/3 of the mitochondria were 100-600 bp long, of which 204 were secondary transmembrane proteins. 1136 mitochondrial proteins, of which 202 are not included in the TCGA database. Of the 934 mitochondrial proteins included in the TCGA database, 706 were highly expressed and 228 were poorly expressed in HCC. Further validated by HCC tissues and cells, the study found that significantly high expression of FDPS, DNA2 and MYO19 was negatively correlated with the prognosis of HCC patients. The results of the immune correlation analysis showed that DNA2 and MYO19 may be involved in regulating the infiltration of immune cells. 934 out of 1136 mitochondrial proteins in the Human.MitoCarta3.0 database were differentially expressed in HCC, suggesting that mitochondrial proteins play an important biological role in the development of HCC. Further experimental validation and bioinformatics analyses showed that functional mitochondrial proteins are potential pathophysiological mechanisms for malignant progression of HCC. Mitochondrial proteins, in the future, have the potential to be valuable therapeutic targets for HCC. Show less
no PDF DOI: 10.1371/journal.pone.0329209
MYO19

The joint predictive roles of achievement task values and academic achievement on trajectories of school satisfaction among elementary school students: A latent transition analysis.

Meiru Deng, E Scott Huebner, Wang Liu +1 more · 2025 · The British journal of educational psychology · Blackwell Publishing · added 2026-04-24
Exploring how different profiles of academic task values (ATVs) and academic achievement (AA) influence students' school satisfaction should enrich understanding of how school satisfaction develops in Show more
Exploring how different profiles of academic task values (ATVs) and academic achievement (AA) influence students' school satisfaction should enrich understanding of how school satisfaction develops in specific academic situations. This study aimed to identify profiles of ATV (attainment value [AV], utility value [UV]) and AA, as well as heterogeneous trajectories of school satisfaction, and then examine the joint predictive effects of ATV and AA on the development of school satisfaction. A total of 3548 Chinese elementary school students (M Data were collected through self-reports of ATVs and school satisfaction, while AA data were collected from final examination scores at the end of each semester. Latent profile analysis (LPA) and latent class growth analysis revealed six profiles of ATV and AA (i.e., congruent subgroups: congruent-low, congruent-high, congruent-moderate and incongruent subgroups: high ATV-low AA, lower UV-moderate AA, low ATV-moderate AA); and four heterogeneous trajectories of school satisfaction (i.e., high-decreasing, low-stable, high-stable, low-increasing). Latent transition analysis (LTA) indicated that students with congruent levels of AA and ATV were more likely to transition into the optimal school satisfaction groups (high-stable and low-increasing groups), whereas students with greater gaps between AA and ATV were more likely to transition into the adverse groups (i.e., low-stable and high-decreasing groups). These findings highlight the need for educators to tailor interventions to distinct groups to optimize students' school satisfaction. Show less
no PDF DOI: 10.1111/bjep.70054
LPA

Establishment of an induced pluripotent stem cell line (HMUCPi001-A) from a hypertrophic cardiomyopathy patient carrying MYBPC3 c.3072C > A mutation.

Dongping Liu, Mingyu Yang, Shasha Fan +6 more · 2025 · Stem cell research · Elsevier · added 2026-04-24
Hypertrophic cardiomyopathy (HCM) is an inherited cardiovascular disorder characterized by left ventricular hypertrophy and an elevated risk of sudden cardiac death. Cardiac myosin binding protein C ( Show more
Hypertrophic cardiomyopathy (HCM) is an inherited cardiovascular disorder characterized by left ventricular hypertrophy and an elevated risk of sudden cardiac death. Cardiac myosin binding protein C (MYBPC3) is the most frequently mutated gene leading to HCM. In this study, peripheral blood mononuclear cells isolated from an HCM patient harboring a heterozygous MYBPC3 missense mutation (c.3072C > A; p.S1024R) were reprogrammed via Sendai virus vectors to generate a patient-specific induced pluripotent stem cell (iPSC) line. The iPSC line exhibits normal morphology and karyotype, alongside definitive hallmarks of pluripotency, including trilineage differentiation potential. Show less
no PDF DOI: 10.1016/j.scr.2025.103841
MYBPC3

C6orf223 promotes colorectal cancer growth and metastasis by facilitating PRMT5-MEP50 multiprotein complex assembling.

Yufeng Qiao, Zhenzhen Wu, Peng Wang +18 more · 2025 · The Journal of clinical investigation · added 2026-04-24
Protein arginine methyltransferase 5 (PRMT5) complexes with methylosome protein 50 (MEP50) play crucial roles in tumor progress. However, the regulatory mechanism of governing the PRMT5-MEP50 hetero-o Show more
Protein arginine methyltransferase 5 (PRMT5) complexes with methylosome protein 50 (MEP50) play crucial roles in tumor progress. However, the regulatory mechanism of governing the PRMT5-MEP50 hetero-octameric complex remains unclear. Here, we demonstrate that C6orf223, to our knowledge an uncharacterized protein, facilitates PRMT5-MEP50 multiprotein complex assembling, thereby promoting colorectal cancer (CRC) growth and metastasis. C6orf223 forms dimers through disulfide bonds, with its N-terminal arginine-enriched region binding to the C-terminal negatively charged groove of PRMT5, thus stabilizing PRMT5-MEP50 multiprotein and enhancing PRMT5 methyltransferase activity. Consequently, PRMT5-mediated H4R3me2s substantially decreases the expression of the tumor suppressor GATA5, leading to the upregulation of multiple oncogenic target genes including WWTR1, FGFR1, and CLU. Targeting C6orf223 using siRNAs encapsulated in ferritin protein shells effectively suppresses CRC tumor growth and metastasis. Collectively, our findings characterize the role of C6orf223 in facilitating PRMT5-MEP50 hetero-octameric complex assembling and suggest that C6orf223 could serve as a potential therapeutic target for CRC. Show less
📄 PDF DOI: 10.1172/JCI186052
FGFR1

Transcriptome analysis of postnatal mouse cardiac tissue growth and development.

Xiao-Cong Zhu, Sheng-Nan Wang, Lin Jiang +1 more · 2025 · Yi chuan = Hereditas · added 2026-04-24
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy h Show more
Postnatal cardiac function in mammals is closely associated with cardiomyocyte proliferation and hypertrophy. However, the molecular mechanisms regulating cardiomyocyte proliferation and hypertrophy have not yet been fully elucidated. Therefore, phenotypic measurements and transcriptomic sequencing were performed on myocardial tissues from 7-day-old (P7) and 3-month-old (3m) female C57BL/6 mice to investigate changes in cardiomyocytes during growth and development and to identify key genes regulating myocardial growth and development. In comparison to 7-day-old mice, 3-month-old mice exhibited a significant increase in heart weight ( Show less
no PDF DOI: 10.16288/j.yczz.24-328
HEY2

Accelerometer-measured intensity-specific physical activity, genetic susceptibility, and back pain risk: a UK biobank cohort study.

Yuanpeng Zhu, Di Liu, Xiangjie Yin +3 more · 2025 · The spine journal : official journal of the North American Spine Society · Elsevier · added 2026-04-24
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose Show more
Current clinical guidelines lack clear, quantitative recommendations on intensity-specific physical activity (PA) levels for preventing back pain. Moreover, accelerometer-based evidence regarding dose-response relationships and interactions between PA and genetic susceptibility remains limited. To determine the relationships between accelerometer-measured total and intensity-specific PA and incident back pain, and to assess potential effect modification by polygenic risk scores (PRS). Prospective, large-scale, population-based study using UK Biobank data. UK Biobank participants who wore wrist accelerometers for 7 days (N=71,601). Incident back pain, defined as the first recorded ICD-10 dorsalgia code (M54). Total PA, light PA (LPA), and moderate-to-vigorous PA (MVPA) were derived using validated machine-learning algorithms from raw accelerometer data. Dose-response relationships were modeled using restricted cubic splines within Cox proportional hazards models, with adjustment for and stratification by a polygenic risk score (PRS). Point estimates for the population attributable fraction (PAF) were then calculated. Body mass index (BMI) mediation was assessed. Over a median follow-up of 7.0 years, total PA and MVPA exhibited nonlinear inverse associations with incident back pain, independent of genetic risk, with thresholds at approximately 35 milli-g (total PA) and 60 min/day (MVPA). The adjusted PAF was 15.9% for low MVPA and 9.9% for low total PA. Associations were strongest for MVPA, followed by total PA; no significant association was observed for LPA. Within both PRS strata, risk declined monotonically across PA quartiles, with similar effect sizes and no PA × PRS interaction. Notably, participants with high PRS and high PA had lower risk than those with low PRS and low PA. BMI mediated 26.2% of the total PA association and 15.5% of the MVPA association. Accelerometer-measured MVPA robustly reduces back-pain risk, independent of genetic predisposition. Future guidelines should provide clear, intensity-specific recommendations and account for the observed nonlinear dose-response to optimize prevention. Show less
no PDF DOI: 10.1016/j.spinee.2025.10.021
LPA

Demoralization profiles and their association with active aging in Chinese older adults with disabilities: a latent profile analysis.

Lulu Wu, Ziqing Qi, Yue Zhang +5 more · 2025 · Frontiers in public health · Frontiers · added 2026-04-24
To identify latent profiles of demoralization among older adults with disabilities, analyze their influencing factors, and examine their associations with active aging. From February to July 2025, a c Show more
To identify latent profiles of demoralization among older adults with disabilities, analyze their influencing factors, and examine their associations with active aging. From February to July 2025, a convenience sample of 411 older adults with disabilities was recruited from a tertiary hospital in Anhui Province, China. Data were collected using a general information questionnaire, the Chinese version of the Demoralization Scale, and the Active Aging Scale. Latent profile analysis (LPA) was performed based on demoralization subscale scores. Univariate and multinominal analyses were employed to investigate the influencing factors, and the Kruskal-Wallis The prevalence of demoralization syndrome was 49.1%. LPA identified three distinct profiles: the Well-Adapted Group (53.3%), the Disheartened-Helpless Group (23.8%), and the Fully Demoralized Group (22.9%). The Kruskal-Wallis Nearly half of the older adults with disabilities experienced demoralization, with heterogeneous subgroups identified. The active aging status of demoralized subgroups requires urgent attention. These findings suggest the need for targeted interventions tailored to the characteristics of each profile to improve mental health and promote active aging in this population. Show less
📄 PDF DOI: 10.3389/fpubh.2025.1715566
LPA

Dual-Mode Method for the Sensitive Detection of β-Secretase (BACE1) Based on Surface-Enhanced Raman Scattering and Dark-Field Microscopy.

Xiaowan Zhang, Xiaolei Song, Chenchen Wang +4 more · 2025 · Analytical chemistry · ACS Publications · added 2026-04-24
β-Secretase (BACE1), a key enzyme to producing neurotoxic β-amyloid, is a potential biomarker of Alzheimer's disease (AD). Developing a sensitive and efficient detection method for BACE1 activity is s Show more
β-Secretase (BACE1), a key enzyme to producing neurotoxic β-amyloid, is a potential biomarker of Alzheimer's disease (AD). Developing a sensitive and efficient detection method for BACE1 activity is significant for AD progression evaluation. Due to the poor cleavage efficiency and acidic working conditions of BACE1, developing probes with high stability and strong signals is challenging for its detection. This work proposed a dual-mode BACE1 detection method based on surface-enhanced Raman scattering and dark-field microscopy. 4-Mercaptobenzoic acid (4-MBA), as the internal Raman reporter of Au@Ag nanoparticles (NPs), shows stable and enhanced Raman signals in an acidic environment. The plasmonic Au Show less
no PDF DOI: 10.1021/acs.analchem.5c02512
BACE1

GPR45 modulates Gα

Yu Xun, Yiao Jiang, Baijie Xu +7 more · 2025 · Science (New York, N.Y.) · Science · added 2026-04-24
The melanocortin system centrally regulates energy homeostasis, with key components such as melanocortin-4 receptor (MC4R) and adenylyl cyclase 3 (ADCY3) in neuronal primary cilia. Mutations in
📄 PDF DOI: 10.1126/science.adp3989
ADCY3

FGF22 Secreted by Hair Papilla Cells Regulates Hair Follicle Stem Cell Proliferation and Differentiation.

Yu Luo, Tong Xiao, Binpeng Xi +5 more · 2025 · Biomolecules · MDPI · added 2026-04-24
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine res Show more
Hair follicle stem cells (HFSCs) are resident stem cells within hair follicles (HFs) that possess self-renewal and differentiation capacities, serving as a critical model for regenerative medicine research. Their dynamic interaction with dermal papilla cells (DPCs) plays a decisive role in HF development and cycling. Show less
📄 PDF DOI: 10.3390/biom15111560
FGFR1

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

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

Association between 24-hour movement behaviors and depressive symptoms among urban older adults in china: a compositional isotemporal substitution analysis.

Hu Ji, Glenn Roswal, Jing Min Liu +2 more · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
To examine the association between 24-hour movement behaviors and depressive symptoms in older adults using compositional data analysis, and to investigate the dose-response characteristics of time re Show more
To examine the association between 24-hour movement behaviors and depressive symptoms in older adults using compositional data analysis, and to investigate the dose-response characteristics of time reallocations between movement behaviors in relation to depressive symptoms. A cross-sectional study was conducted among 1093 urban-dwelling older adults aged 60 years and above in selected communities of Jinan City, Shandong Province, China, between April 2024 and September 2024. The Chinese version of the International Physical Activity Questionnaire-Long Form (IPAQ-LF) was used to estimate time spent in moderate to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), sedentary behavior (SB), and sleep (SLP) across a typical 24-hour day. The Chinese version of the Patient Health Questionnaire Depression Scale-9 item (PHQ-9) was applied to assess depressive symptoms. Compositional isotemporal substitution models were employed to explore the associations between time reallocations among 24-hour movement behaviors and depressive symptoms, accounting for the co-dependent nature of time-use data. (1) The geometric means of time spent in MVPA, LPA, SB, and SLP were 25.33 minutes, 141.26 minutes, 738.10 minutes, and 455.15 minutes, respectively. Variation matrix analysis revealed the highest log-ratio variance between MVPA and SB (0.168), and the lowest between SLP and SB (0.031). (2) The prevalence of screening-positive depressive symptoms was 16.29% among Chinese urban older adults. (3) Results from compositional linear regression models showed that time allocated to MVPA, LPA, and SLP (relative to the remaining movement behaviors) was negatively associated with depressive symptoms, while time spent in SB was positively associated. (4) Dose-response analysis further indicated that: (a) MVPA substitutions with other movement behaviors exhibited nonlinear and markedly asymmetric effects on depressive symptoms; (b) replacing MVPA with LPA, SB, or SLP resulted in increasingly larger changes in predicted scores as substitution duration increased, whereas the reverse substitution (MVPA for other movement behaviors) produced progressively smaller changes; and (c) substitutions between SB and LPA displayed linear and symmetrical effects. The findings provide evidence of an association between 24-hour movement behaviors and depressive symptoms in Chinese urban-dwelling older adults and reinforce the importance of achieving a balance between different types of movement behaviors over a 24-hour period for mental health. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1706591
LPA