👤 Lulu 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, 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

Superior performance of chitosan microspheres loaded with hyperbranched polylysine for endotoxin adsorption: From molecular interactions to hemoperfusion applications.

Yuhui Feng, Ziyue Ling, Xianda Liu +4 more · 2026 · Carbohydrate polymers · Elsevier · added 2026-04-24
Sepsis triggered by lipopolysaccharide (LPS) is a life-threatening condition. Inspired by the specific capture mechanism of innate proteins like LBP and CD14, we develop oxidized chitosan microspheres Show more
Sepsis triggered by lipopolysaccharide (LPS) is a life-threatening condition. Inspired by the specific capture mechanism of innate proteins like LBP and CD14, we develop oxidized chitosan microspheres functionalized with hyperbranched polylysine (OCS-HBPL) as a sepsis detoxification agent. Isothermal titration calorimetry (ITC) reveals that HBPL-LPS binding is an enthalpy-driven process, distinct from the entropy-driven interaction of linear polylysine (LPL)-LPS. Validated by surface plasmon resonance (SPR), HBPL demonstrates superior affinity with a dissociation constant (K Show less
no PDF DOI: 10.1016/j.carbpol.2026.125269
LPL

The stem-derived bioactive fraction of Syringa oblata Lindl. Ameliorates insomnia via cAMP signaling-mediated regulation of neurotransmission, oxidative stress, and inflammation: A multi-omics study.

Wei Xiao, Shuting Zhai, Kuangyi Liu +6 more · 2026 · Fitoterapia · Elsevier · added 2026-04-24
This study aimed to elucidate the sedative-hypnotic effects of a stem-derived bioactive fraction from Syringa oblata Lindl. (ZDX) and to reveal its underlying mechanisms, thereby providing a theoretic Show more
This study aimed to elucidate the sedative-hypnotic effects of a stem-derived bioactive fraction from Syringa oblata Lindl. (ZDX) and to reveal its underlying mechanisms, thereby providing a theoretical and practical basis for the development of new sleep aid drugs. ZDX was prepared by optimizing the extraction and purification procedures. Using UPLC-Q-TOF-MS, the prototype compounds absorbed into the brain of insomnia mice were analyzed, and 15 bioactive compounds were identified or predicted, including Dihydrocubebin, (-)-Cubebin, Isoguamarol, and others. Its efficacy and mechanisms were investigated using network pharmacology, transcriptomics, metabolomics, and molecular docking, complemented by in vivo pharmacodynamic and molecular analyses. In an insomnia mouse model, ZDX significantly increased body weight, reduced sleep latency, and prolonged total sleep duration, while alleviating anxiety and depression-like behaviors and improving histopathological damage in the hippocampus and hypothalamus, showing significant sedative-hypnotic effects. Mechanistically, ZDX modulated key genes and proteins involved in the cAMP signaling pathway, enhanced superoxide dismutase activity, reduced malondialdehyde levels, decreased inflammatory cytokines (IL-6, IL-1β, and TNF-α), and restored neurotransmitter homeostasis in the brain. Collectively, ZDX exerts sedative-hypnotic effects, at least in part, by activating the cAMP/PKA-CREB-BDNF axis and coordinately regulating neurotransmission, oxidative stress, and inflammation. Show less
no PDF DOI: 10.1016/j.fitote.2026.107182
BDNF camp signaling inflammation insomnia multi-omics neurotransmission oxidative stress sedative-hypnotic effects

Association of plasma glial fibrillary acidic protein and APOE-ε4 with Alzheimer's disease.

Yalin Zhu, Guoyu Lan, Anqi Li +15 more · 2026 · Neurobiology of aging · Elsevier · added 2026-04-24
Both Apolipoprotein E-ε4 (APOE-ε4) and astrocytic activation, as measured by glial fibrillary acidic protein (GFAP), play critical roles in Alzheimer's disease (AD). However, the influence of astrocyt Show more
Both Apolipoprotein E-ε4 (APOE-ε4) and astrocytic activation, as measured by glial fibrillary acidic protein (GFAP), play critical roles in Alzheimer's disease (AD). However, the influence of astrocytic activation on the relationship between APOE-ε4 and AD pathologies remains unclear. This study investigates the interrelationships among astrocytic activation, APOE-ε4, and AD pathophysiology in 529 participants who underwent plasma biomarker measurements, APOE genotyping, and cognitive testing. Additionally, 277, 284, and 104 underwent structural magnetic resonance imaging (MRI), amyloid-β (Aβ) positron emission tomography (PET), and tau PET, respectively. The associations of plasma GFAP, APOE-ε4, and AD-related biomarkers, as well as whether plasma GFAP mediates APOE-ε4-related effects on AD, were investigated. Higher plasma GFAP and APOE-ε4 were independently associated with more severe Aβ and tau aggregation, as well as cognitive decline. Mediation analyses showed a significant indirect effect of APOE-ε4 on plasma p-tau biomarkers (21.1%-24.9%), Aβ PET (16.4%), and cognition (19.6%), while the indirect effect on tau PET was trend-level (29.1%, p Show less
no PDF DOI: 10.1016/j.neurobiolaging.2026.03.009
APOE

A cross-sectional study of the correlation between short-chain fatty acids, lipids, cytokines, and cognition, emotions in late pregnancy.

Juan Zhou, Wenxiang Li, Yuan Zhang +9 more · 2026 · Journal of affective disorders · Elsevier · added 2026-04-24
Pregnant women have a high incidence of perinatal mood and anxiety disorders (PMADs). To explore the influence factor on perinatal psychology, we analysed the SCFAs, lipids, cognition, emotion, and cy Show more
Pregnant women have a high incidence of perinatal mood and anxiety disorders (PMADs). To explore the influence factor on perinatal psychology, we analysed the SCFAs, lipids, cognition, emotion, and cytokines in the late pregnant women. The mood, cognition, SCFAs of the non-pregnant group were compared to those in the late pregnancy. The differences in SCFAs, lipids, cognition, and cytokines between the high-risk and low-risk groups for affective disorders among women in the late pregnancy were analysed, and the risk factors were sought. Compared with the non-pregnant group, the pregnant group scored lower on the SDMT (P < 0.001), DST (P = 0.035), VRT (P = 0.001), and VFT (P < 0.001), and took longer on the TMTA (P = 0.004). Acetate (P = 0.001) and butyrate (P = 0.002) were higher, while propionate (P < 0.001) and isobutyrate (P = 0.001) were lower in the pregnant group than in the non-pregnant group. Among the pregnant women, CRP was higher in the high-risk group for mood disorders than in the low-risk group (P = 0.048). Meanwhile, HDL was positively associated with DST (P = 0.000), VRT (P = 0.015), and VFT (P < 0.001). Longer TMTA completion times were associated with reduced propionate (P = 0.072) and LPa (P = 0.022). Longer TMTB completion time was associated with lower life satisfaction (P = 0.037), as well as decreased cholesterol (P = 0.026). Pregnant women experience changes in cognition and SCFAs. CRP is a sensitive indicator for monitoring affective disorder. Regulation of SCFAs and lipids may be beneficial for cognition and affect. Show less
no PDF DOI: 10.1016/j.jad.2025.120432
LPA

Latent Profile Analysis of Depressive Symptoms and Their Associated Factors Among Older Adults in Chinese Nursing Homes: Identification of Three Distinct Symptom Profiles.

Jianlei Liu, Yaling Cui, Hongyu Wang +2 more · 2026 · Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · Blackwell Publishing · added 2026-04-24
With global population aging, the number of older adults in Chinese nursing homes is rising rapidly, and depression is the most prevalent mental health problem in this population. Most previous studie Show more
With global population aging, the number of older adults in Chinese nursing homes is rising rapidly, and depression is the most prevalent mental health problem in this population. Most previous studies assessed depression via total scale scores, ignoring individual heterogeneity of depressive symptoms. This study aimed to identify distinct depressive symptom profiles and their associated factors in this population. Data were derived from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), with 353 valid nursing home older adults included. Depressive symptoms, anxiety and functional status were assessed using the CESD-10, GAD-7 and IADL scales. Latent profile analysis (LPA), univariate tests and multinomial logistic regression were performed, with supplementary effect size and sensitivity analyses to verify result robustness. Three distinct depressive symptom profiles were identified: low level (39%, n = 135), medium level (52%, n = 187) and high level (9%, n = 31). Town residence and anxiety were risk factors for moderate depression, while good self-rated health, regular exercise and social activity participation were protective factors. Good self-rated health protected against severe depression, while occasional television/radio viewing and anxiety were risk factors. Anxiety was the only independent correlate of high-level versus medium-level depression (OR = 1.322, p < 0.001). Supplementary analyses confirmed the robustness of core findings. The CESD-10, as a screening tool, has limited diagnostic efficacy for clinical depression, and the cross-sectional design cannot confirm causal relationships. Depressive symptoms in Chinese nursing home older adults show significant heterogeneity with three distinct latent profiles. Early screening and targeted stratified interventions should be implemented for this population to improve quality of life and promote healthy aging. Show less
no PDF DOI: 10.1111/psyg.70166
LPA

Novel associations of VPS13C with phenotype and conversion of idiopathic REM sleep behavior disorder.

Yanfei Ding, Xinyi Zhou, Aonan Zhao +8 more · 2026 · NPJ Parkinson's disease · Nature · added 2026-04-24
While VPS13C is a recessively inherited Parkinson's disease (PD) gene, its potential dominant effects in idiopathic Rapid-eye movement (REM) sleep behavior disorder (iRBD) remain unexplored. The relat Show more
While VPS13C is a recessively inherited Parkinson's disease (PD) gene, its potential dominant effects in idiopathic Rapid-eye movement (REM) sleep behavior disorder (iRBD) remain unexplored. The relation between its monogenic form and the onset of PD suggested that subtype specificity may need to be considered. We examined the presence of likely pathogenic VPS13C variants in 150 iRBD and 180 α-synucleinopathy patients (iRBD-first and movement disorder-first). VPS13C variants were significantly enriched in iRBD patients, and ten iRBD risk variants have been identified. iRBD risk VPS13C variant carriers demonstrated more severe RBD symptoms and greater autonomic dysfunction, correlating with REM sleep EEG and autonomic network activity abnormalities. Notably, enrichment was specific to the iRBD-first α-synucleinopathy subtype, and iRBD risk VPS13C variant carriers showed accelerated progression to overt α-synucleinopathy. These results suggest that VPS13C not only contributes to iRBD susceptibility but also serves as a marker for the iRBD-first α-synucleinopathy and faster disease conversion. Show less
no PDF DOI: 10.1038/s41531-026-01352-5
VPS13C

The association between short video addiction and emotion dysregulation among college students: a latent profile analysis and its influencing factors.

Shuhe Wang, Zhongguo Liu · 2026 · Frontiers in psychology · Frontiers · added 2026-04-24
This study aimed to use latent profile analysis (LPA) to identify heterogeneous configurational patterns of short video addiction and emotion dysregulation among college students, and to systematicall Show more
This study aimed to use latent profile analysis (LPA) to identify heterogeneous configurational patterns of short video addiction and emotion dysregulation among college students, and to systematically examine the predictive effects of cognitive reappraisal, emotional loneliness, and sociodemographic factors on latent profile membership. A cross-sectional survey design was employed. From April to July 2025, full-time undergraduate students were recruited from multiple universities in Shandong Province using a combination of convenience sampling and snowball sampling. Participants completed online questionnaires including the Short Video Addiction Scale, the Emotion Dysregulation Inventory (EDI), the Cognitive Reappraisal Scale, and the Emotional Loneliness Scale. A total of 1,168 valid questionnaires were obtained. LPA identified four optimal profiles: Profile 1 ("low short video addiction-low emotion dysregulation"), Profile 2 ("medium to lower short video addiction-medium to lower emotion dysregulation"), Profile 3 ("medium to upper short video addiction-medium to upper emotion dysregulation"), and Profile 4 ("high short video addiction-high emotion dysregulation"). Multivariable logistic regression analyses indicated that, with Profile 4 as the reference category, cognitive reappraisal significantly increased the likelihood of membership in lower-risk profiles, whereas emotional loneliness significantly decreased the likelihood of membership in lower-risk profiles. Among sociodemographic factors, being female and having an urban background significantly increased the likelihood of membership in Profile 1 (vs. Profile 4); being a non-only child and having no part-time work experience significantly predicted membership in Profile 3. Marked heterogeneity exists among college students in the measured dimensions of short-form video addiction and emotion dysregulation, and the two constructs exhibit highly concordant co-variation. The findings provide empirical support for developing risk-stratified and precision-oriented mental health intervention strategies. Show less
📄 PDF DOI: 10.3389/fpsyg.2026.1789207
LPA

Ptch2 Deficiency Triggers Lipoma Formation and Adipogenic Transcriptome Reprogramming in Nile tilapia (

Changle Zhao, Xiang Liu, Xi Peng +5 more · 2026 · Animals : an open access journal from MDPI · MDPI · added 2026-04-24
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, usi Show more
The Hedgehog (Hh) signaling pathway is a key regulator of adipogenesis and lipid metabolism. However, the specific role of its receptor, Patched2 (Ptch2), in these processes remains unclear. Here, using a CRISPR/Cas9-mediated Show less
📄 PDF DOI: 10.3390/ani16030405
LPL

CD80

Yin Wang, Pan Li, Wenming Li +10 more · 2026 · Cell communication and signaling : CCS · BioMed Central · added 2026-04-24
Tc17 cells (IL-17 The percentage of Tc17 cells, monocytes and IL-1β Higher populations of Tc17 cells, IL-1β The present results show that suppressing IL-1β expression by preventing CD80 [Figure: see t Show more
Tc17 cells (IL-17 The percentage of Tc17 cells, monocytes and IL-1β Higher populations of Tc17 cells, IL-1β The present results show that suppressing IL-1β expression by preventing CD80 [Figure: see text] The online version contains supplementary material available at 10.1186/s12964-026-02785-4. Show less
📄 PDF DOI: 10.1186/s12964-026-02785-4
APOE

Fusobacterium nucleatum exacerbates atherosclerosis progression via ceRNA network-mediated epigenetic reprogramming.

Keyi Zhang, Lin Liu, Peiyao Wu +3 more · 2026 · Genomics · Elsevier · added 2026-04-24
Fusobacterium nucleatum (F. nucleatum), a key periodontal pathogen, is increasingly detected in atherosclerotic plaques, yet its epigenetic regulatory mechanisms in atherosclerosis remain enigmatic. T Show more
Fusobacterium nucleatum (F. nucleatum), a key periodontal pathogen, is increasingly detected in atherosclerotic plaques, yet its epigenetic regulatory mechanisms in atherosclerosis remain enigmatic. This study investigates how F. nucleatum reshapes the non-coding RNA landscape to drive atherosclerosis progression. Periodontal infection with F. nucleatum significantly increased atherosclerotic lesion area (p < 0.001) and necrotic core ratio, while reducing collagen content (p < 0.05) in ApoE Show less
no PDF DOI: 10.1016/j.ygeno.2025.111186
APOE

BCAAs and related metabolic enzymes: partners in crime driving tumor development.

Binfan He, Lingxi Li, Ye Liu +3 more · 2026 · Frontiers in cell and developmental biology · Frontiers · added 2026-04-24
Metabolic reprogramming of Branched-chain amino acids (BCAAs)-leucine, isoleucine, and valine-has emerged as a constitutive feature of cancer, extending far beyond their canonical roles in protein syn Show more
Metabolic reprogramming of Branched-chain amino acids (BCAAs)-leucine, isoleucine, and valine-has emerged as a constitutive feature of cancer, extending far beyond their canonical roles in protein synthesis and energy provision. In malignancy, these essential amino acids function as pivotal signaling mediators and epigenetic modulators, thereby propelling tumor progression, facilitating immune evasion, and conferring resistance to therapeutic agents. This review delineates how cancer cells subvert branched-chain amino acid metabolism to fuel anabolic processes, activate oncogenic signaling cascades including mTOR and PI3K/AKT, and remodel the tumor microenvironment. A framework is presented to categorize the differential reliance of various cancers on key catabolic enzymes-BCAT1, BCAT2 and BCKDK-underscoring their therapeutic vulnerability. The paradoxical role of BCAAs in modulating anti-tumor immunity is examined alongside the potential of dietary modulation and the development of pharmacological inhibitors targeting this pathway. Concluding perspectives highlight the trajectory for translating these insights into precision oncology, advocating for biomarker-guided and context-specific therapeutic strategies. Show less
📄 PDF DOI: 10.3389/fcell.2026.1748587
BCKDK

Interplay of accelerated biological aging, lifestyle factors, and genetic susceptibility in cognitive function: a community study.

Tianpei Ma, Xin Chen, Qingwen Zhao +19 more · 2026 · The journals of gerontology. Series A, Biological sciences and medical sciences · Oxford University Press · added 2026-04-24
Cognitive impairment is a significant health concern in aging populations, but the interplay between biological aging, lifestyle factors, and genetic susceptibility remains unclear. This study examine Show more
Cognitive impairment is a significant health concern in aging populations, but the interplay between biological aging, lifestyle factors, and genetic susceptibility remains unclear. This study examined whether accelerated biological aging is associated with cognitive impairment, whether lifestyle modifies this association, and how genetic background influences these relationships in Chinese older adults. In this cross-sectional study (2022-2023), 7033 participants from southwestern China were included. Accelerated biological aging was calculated as the residual difference between biological age (based on 10 biomarkers) and chronological age. Lifestyle was assessed via a composite index (smoking, alcohol, physical activity, diet, sleep). Cognitive function was measured using the Chinese Mini-Mental State Examination (C-MMSE), and genetic risk was evaluated through polygenic scores and APOE ε4 status. Linear and logistic regression models assessed associations between accelerated aging and cognition. Accelerated biological aging was associated with lower MMSE scores ( β = -0.243, 95% CI: -0.354, -0.133) and higher cognitive impairment prevalence (OR = 1.098, 95% CI: 1.040, 1.158). An unhealthy lifestyle exacerbated cognitive impairment in biologically older individuals (RERI = 0.25). Those with both accelerated aging and unhealthy lifestyle had the lowest MMSE scores ( β = -1.424, 95% CI: -1.846, -1.003) and highest odds of cognitive impairment (OR = 1.467, 95% CI: 1.194, 1.803). These effects were consistent across all genetic background subgroups. Accelerated aging was associated with lower cognitive function, especially in individuals with unhealthy lifestyles, regardless of genetic susceptibility. This highlights lifestyle modification as a potential intervention target for aging-related cognitive impairment. Show less
no PDF DOI: 10.1093/gerona/glaf277
APOE

Tirzepatide improves angiogenesis after diabetic hindlimb ischemia through Akt/eNOS and ERK1/2 pathways.

Jing Li, Chengsi Li, Chengyingjie Yang +5 more · 2026 · Peptides · Elsevier · added 2026-04-24
Critical limb ischemia (CLI) represents a severe vascular complication of type 2 diabetes, primarily driven by impaired angiogenic capacity, and frequently results in limb amputation or mortality. Her Show more
Critical limb ischemia (CLI) represents a severe vascular complication of type 2 diabetes, primarily driven by impaired angiogenic capacity, and frequently results in limb amputation or mortality. Here, we investigated the therapeutic potential of tirzepatide in promoting perfusion recovery in diabetic hindlimb ischemia and delineated the underlying molecular mechanisms. Human umbilical vein endothelial cells (HUVECs) exposed to high glucose were employed to evaluate tirzepatide's effects on endothelial proliferation, migration, and tube formation, alongside the activation of Akt, endothelial nitric oxide synthase (eNOS), and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling, assessed by western blotting. Knockdown of GLP-1R or GIPR abrogated the pro-angiogenic effects of tirzepatide, while pharmacological inhibition of the Akt/eNOS or ERK1/2 pathways attenuated endothelial responses. In vivo, tirzepatide treatment significantly enhanced perfusion recovery and increased capillary density in the ischemic limbs of diabetic mice, corroborating its angiogenic effects. Collectively, these findings demonstrate that tirzepatide facilitates angiogenesis and accelerates ischemic limb revascularization through dual GLP-1R/GIPR activation and subsequent engagement of Akt/eNOS and ERK1/2 signaling pathways, highlighting its potential as a therapeutic strategy for diabetic CLI. Show less
no PDF DOI: 10.1016/j.peptides.2026.171489
GIPR

Identifying the causal relationship between gut microbiota and chronic sinusitis and the mediating effects of inflammatory cytokines: Insights from a Mendelian randomization study and mediation analysis.

Yiting Liu, Cuida Meng, Qingjia Sun +3 more · 2026 · Microbial pathogenesis · Elsevier · added 2026-04-24
The causal links between gut microbiota, inflammatory cytokines, and chronic rhinosinusitis are unclear. A Mendelian randomization study used data from the MiBioGen consortium (211 microbiota taxa, n  Show more
The causal links between gut microbiota, inflammatory cytokines, and chronic rhinosinusitis are unclear. A Mendelian randomization study used data from the MiBioGen consortium (211 microbiota taxa, n = 18,340), genome-wide association studies of 91 inflammatory cytokines, and chronic rhinosinusitis data from the FinnGen consortium. Five microbiota taxa were causally linked to chronic rhinosinusitis. The genera Ruminococcaceae NK4A214 group and Victivallis were risk factors, while Lachnospiraceae NC2004 group, Ruminococcus2, and Subdoligranulum were protective. Elevated levels of axin-1, C-X-C motif chemokine 10, interleukin-18 receptor 1, interleukin-1-alpha, and vascular endothelial growth factor A increased risk, whereas C-C motif chemokine 19, CD40L receptor, and Fractalkine were protective. The Ruminococcaceae NK4A214 group id.11358 increased risk through reduced Fractalkine and elevated vascular endothelial growth factor A levels. The study supports a causal link between Ruminococcaceae NK4A214 group id.11358 and chronic rhinosinusitis, mediated by Fractalkine and vascular endothelial growth factor A levels. Show less
no PDF DOI: 10.1016/j.micpath.2025.108254
AXIN1

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

Inflammation-induced impairment of synaptic plasticity accelerates atherosclerosis co-depression disease: insights from bioinformatics analysis and transcriptomics.

Yulong Zhao, Qiang Luo, Peng Ren +7 more · 2026 · Cell & bioscience · BioMed Central · added 2026-04-24
Atherosclerosis (AS) serves as the pathological foundation for numerous cardiovascular and cerebrovascular diseases and is highly comorbid with depression. The mechanisms underlying this co-morbidity Show more
Atherosclerosis (AS) serves as the pathological foundation for numerous cardiovascular and cerebrovascular diseases and is highly comorbid with depression. The mechanisms underlying this co-morbidity are exceptionally complex, posing significant challenges to effective clinical treatment. Consequently, our study aims to explore the potential biomarkers and mechanisms involved in developing atherosclerosis co-depression disease. We performed differential expression analysis, protein-protein interaction analysis, Gene Ontology (GO) function enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on co-differentiated genes using AS and depression-related datasets from the GEO database. Potential biomarkers were identified through ROC curve analysis. To evaluate the effectiveness of the model, we established an animal model of AS comorbid with depressive disorder and performed a series of assessments, including the sugar-water preference test, open field test, tail suspension test, lipid profile analysis, and pathological examination of aortic sections. Additionally, RNA sequencing analysis of brain tissue, Golgi staining, and detection of synaptic function-related proteins were performed in AS comorbid depressed mice. Finally, in vitro cellular experiments were conducted to further validate the molecular targets and underlying mechanisms. We identified 968 differentially expressed genes associated with AS and 472 differentially expressed genes associated with depression, with 30 genes co-differentially expressed. Protein-protein interaction (PPI) analysis revealed that CCR5, CCR2, NPY, and OPRM1 were strongly associated with AS co-depression, while ROC analysis indicated that Shank2, MDGA2, and S100B were diagnostic markers for AS with depression. Differentially expressed genes were closely associated with the chemokine signaling pathway, neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, and taste transduction. Animal studies demonstrated that ApoE Our study identified seven candidate AS co-depression biomarkers and verified that inflammation-induced damage to synaptic plastic rows is an important mechanism of AS co-depression, providing new insights into the diagnosis and treatment of AS co-depression disorders. Show less
📄 PDF DOI: 10.1186/s13578-026-01535-w
APOE

Normalization strategies for protein quantification in plasma astrocyte-derived extracellular vesicles: a clinical applicability study.

Kun Li, Mian-Mian Chen, Shu-Xian Xu +1 more · 2026 · BMC psychiatry · BioMed Central · added 2026-04-24
Astrocyte-derived extracellular vesicles (ADEVs) have emerged as a novel research tool in the field of central nervous system disorders. However, significant differences in yield and purity exist amon Show more
Astrocyte-derived extracellular vesicles (ADEVs) have emerged as a novel research tool in the field of central nervous system disorders. However, significant differences in yield and purity exist among extracellular vesicles (EVs) isolated by different methods, leading to considerable heterogeneity in clinical study outcomes. Therefore, establishing appropriate normalization strategies to enhance comparability across results is a key prerequisite for their clinical translation. This study included 15 patients with major depressive disorder (MDD) and 15 healthy controls (HCs). ADEVs were isolated from plasma using ultracentrifugation combined with immunoaffinity capture. Subsequently, the levels of brain-derived neurotrophic factor (BDNF), five EV biomarkers (CD9, CD63, CD81, Alix, and TSG101), and particle counts in ADEVs were quantified. In addition, plasma lipoprotein levels were measured. Our results demonstrated a lack of significant correlation between particle counts and the levels of five EV biomarkers in plasma ADEVs, whereas strong correlations were observed among the five biomarkers themselves. Normalization of BDNF levels to CD81 or CD9 revealed a significant decrease in the MDD group, whereas normalization to EV particle counts or other EV biomarkers did not show such differences. Notably, plasma levels of apolipoprotein B (APOB), low-density lipoprotein (LDL), and total cholesterol (TC) significantly interfered with the measurement of particle counts. In summary, under conventional EV isolation and detection conditions, our findings support the use of EV biomarker levels rather than particle counts as a normalization method for quantifying target proteins of ADEVs in plasma. [Image: see text] The online version contains supplementary material available at 10.1186/s12888-026-07796-6. Show less
📄 PDF DOI: 10.1186/s12888-026-07796-6
BDNF

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

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

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

Knowledge, Attitudes, and Practices of Lower Limb Arteriosclerosis Obliterans among Patients: A Latent Profile Analysis.

Xinjun Liu, Qiqi Wang, Tingting Qiu +4 more · 2026 · Annals of vascular surgery · Elsevier · added 2026-04-24
This study aimed to assess the knowledge, attitudes, and practices (KAP) of patients with lower limb arteriosclerosis obliterans (ASO) toward their disease. This cross-sectional study was conducted at Show more
This study aimed to assess the knowledge, attitudes, and practices (KAP) of patients with lower limb arteriosclerosis obliterans (ASO) toward their disease. This cross-sectional study was conducted at 3 tertiary hospitals in Chengdu between August 2023 and January 2024 and included patients with lower limb ASO. Data were collected using an interviewer-administered questionnaire that captured demographic information and KAP scores. A latent profile analysis (LPA) was used to identify the KAP patterns among participants. A total of 515 nonproblematic questionnaires were collected, yielding an effective response rate of 95.72%. Among the respondents, 395 (76.85%) were male, with a disease course of 15.96 ± 17.55 months. The knowledge, attitude, and practice scores were 5.27 ± 4.69 (possible range: 0-22), 17.65 ± 2.86 (possible range: 5-25), and 107.63 ± 17.15 (possible range: 33-165), respectively. LPA identified 4 participant profiles: Profile 1 (high attitude, low practice), Profile 2 (low attitude, high practice), Profile 3 (low attitude, low practice), and Profile 4 (high attitude, high practice). Significant differences were found among profiles in residence (P = 0.028), medical insurance (P = 0.043), self-efficacy (P < 0.001), and patient activation (P < 0.001). Patients with lower limb ASO demonstrated inadequate knowledge but moderate levels of attitude and practice. Residence, medical insurance, self-efficacy, and patient activation may affect the KAP patterns of the patients. These findings suggest that tailored interventions targeting distinct patient profiles, while considering broader social determinants of health, may be critical to improving self-management and outcomes. Show less
no PDF DOI: 10.1016/j.avsg.2025.10.022
LPA

Probucol attenuates bone loss in APP/PS1 mice and ameliorates Aβ42-induced osteoblast dysfunction by regulating AKT/FOXO3a signaling pathway.

Dong Liu, Hongyan Yang, Xiangqian Feng +13 more · 2026 · Experimental gerontology · Elsevier · added 2026-04-24
Alzheimer's disease (AD) and osteoporosis are common age-related degenerative diseases. Emerging evidence suggests that amyloid-β (Aβ) deposition may contribute to the pathogenesis of both conditions. Show more
Alzheimer's disease (AD) and osteoporosis are common age-related degenerative diseases. Emerging evidence suggests that amyloid-β (Aβ) deposition may contribute to the pathogenesis of both conditions. This study investigated whether probucol could alleviate AD-associated bone loss and Aβ42-induced osteoblast dysfunction, and further explored the underlying mechanisms. Female mice were divided into four groups (n = 5 per group): C57BL/6 wild-type (WT), WT treated with probucol (WT + PBC), APP/PS1 transgenic (AD) mice, and AD treated with probucol (AD+PBC). Bone mineral density (BMD) was assessed by micro-CT. Levels of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α) along with bone metabolism markers including fibroblast growth factor 23 (FGF23), sclerostin, and brain-derived neurotrophic factor (BDNF) in bone and brain tissues were measured by ELISA. FOXO3a was knocked down in the bone marrow of APP/PS1 mice via stereotactic injection of lentiviral vectors. Expression of APP and FOXO3a in bone tissue was evaluated using RT-qPCR and Western blotting (WB). Mitochondrial damage in osteoblasts and neuronal cells was assessed by transmission electron microscopy (TEM). In vitro study, osteoblast differentiation and mineralization deficits were evaluated using Alizarin Red staining. WB was used to measure the expression of AKT, FOXO3a, autophagy and apoptosis related proteins. Probucol attenuated bone loss and mitochondrial damage in both APP/PS1 and FOXO3a-knockdown APP/PS1 mice, and improved cognitive impairment and neuronal ultrastructure in APP/PS1 mice. Furthermore, probucol attenuated Aβ42-induced osteoblast differentiation and mineralization via the AKT/FOXO3a signaling pathway in vitro. These findings demonstrate that probucol ameliorates AD-associated bone loss and Aβ42-induced osteoblast impairments by regulating AKT/FOXO3a signaling pathway. Show less
no PDF DOI: 10.1016/j.exger.2026.113034
BDNF alzheimer's disease amyloid bone loss osteoblast osteoporosis pathogenesis signaling pathway

Levosimendan inhibits HIV-1 infection in myeloid cells in the RIOK1-dependent manner.

Jinshan He, Jie Ma, Youngmin Park +10 more · 2026 · bioRxiv : the preprint server for biology · added 2026-04-24
Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, includ Show more
Despite of the highly potent antiretroviral therapies, HIV-1 establishes persistent infection and causes chronic inflammation in AIDS patients. Beyond CD4+ T cells, HIV-1 infects myeloid cells, including circulating monocytes and tissue-resident macrophages, and integrates with host genomes to form stable viral reservoirs. To achieve a functional HIV cure, latency-promoting agents (LPAs) have been developed for the "block-and-lock" strategy to reinforce deep HIV-1 latency and permanently silence proviruses. However, most LPAs have been tested mainly in CD4 Show less
no PDF DOI: 10.64898/2026.04.08.717218
LPA

Cerebrospinal fluid proteomic signatures reveal

Zhiyuan Ning, Jeff Y L Lam, Zonghua Li +10 more · 2026 · Research square · added 2026-04-24
Cerebrospinal fluid (CSF) proteomics offers insights into molecular changes in aging and Alzheimer's disease (AD). Key AD biomarkers, in particular amyloid-β (Aβ) and tau, in CSF are strongly associat Show more
Cerebrospinal fluid (CSF) proteomics offers insights into molecular changes in aging and Alzheimer's disease (AD). Key AD biomarkers, in particular amyloid-β (Aβ) and tau, in CSF are strongly associated with Show less
📄 PDF DOI: 10.21203/rs.3.rs-8605807/v1
APOE

Posterior communicating artery variation is linked to compromised cerebral hemodynamics in middle-aged and older adults.

Francis E Cambronero, Panpan Zhang, W Hudson Robb +8 more · 2026 · Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · SAGE Publications · added 2026-04-24
We investigate whether common circle of Willis (CoW) variants relate to cerebral blood flow (CBF) characteristics among aging adults. Vanderbilt Memory and Aging Project participants free of clinical Show more
We investigate whether common circle of Willis (CoW) variants relate to cerebral blood flow (CBF) characteristics among aging adults. Vanderbilt Memory and Aging Project participants free of clinical stroke ( Show less
📄 PDF DOI: 10.1177/0271678X261424053
APOE

Proposed Role of Circadian Clock Genes in Pathogenesis of HCC: Molecular Subtyping and Characterization.

Zhikui Lu, Yi Zhou, Jian Luo +2 more · 2026 · Biomedicines · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/biomedicines14030645
AXIN1

Fujian Tablets promote corticospinal tract remodeling and improve motor function in MCAO rats by regulating BDNF shearing enzyme-mediated proBDNF/mBDNF balance.

Shang Gao, Rui Su, Jie Gao +7 more · 2026 · Journal of ethnopharmacology · Elsevier · added 2026-04-24
Fujian Tablets (FJT), a traditional Chinese medicinal (TCM) preparation, has been clinically used in the rehabilitation of neurological disorders related to ischemic brain injury in the context of TCM Show more
Fujian Tablets (FJT), a traditional Chinese medicinal (TCM) preparation, has been clinically used in the rehabilitation of neurological disorders related to ischemic brain injury in the context of TCM theory. However, its molecular mechanism underlying the promotion of post-ischemic stroke motor function recovery, especially via regulating corticospinal tract (CST) remodeling-a key structure for motor control-remains unelucidated. This study aimed to investigate the effect of FJT on CST remodeling in the denervated hemisphere and motor function recovery in middle cerebral artery occlusion (MCAO) rats, and to explore its potential mechanism by focusing on the balance between precursor brain-derived neurotrophic factor (proBDNF) and mature BDNF (mBDNF), which is tightly regulated by BDNF-cleaving enzymes (Pcsk1 and Furin). The MCAO rat model was established using the intraluminal filament method. Model rats were randomly divided into four groups: MCAO model group, FJT low-dose group, FJT medium-dose group, and FJT high-dose group. Motor function was evaluated by Catwalk gait analysis (assessing average speed, step length, and standing time). CST remodeling and conduction efficiency were determined via biotinylated dextran amine (BDA) neural tracing and motor evoked potential (MEP) detection, respectively. The mRNA and protein expressions of BDNF, cleaving enzymes (Pcsk1, Furin), and related receptors (TrkB, p75NTR, Sortilin) in brain tissues were measured using quantitative real-time polymerase chain reaction (RT-qPCR) and Western blot. BDNF silencing experiment was performed to verify the role of BDNF in FJT-induced effects. Additionally, in vitro neuronal culture was used to observe the effects of FJT, exogenous mBDNF, and Pcsk1/Furin inhibitors on neuronal growth. Compared with the MCAO model group, medium-dose FJT exhibited the most significant therapeutic effects. Specifically, FJT notably improved gait parameters increasing average speed from 20.77 mm/s (MCAO) to 25.71 mm/s (FJT) and step length by approximately 21.14 %. Furthermore, FJT enhanced MEP conduction efficiency and promoted CST remodeling, characterized by a 5.26 % increase in BDA-positive nerve fibers and elevated growth-associated protein 43 (GAP43) expression in the denervated hemisphere. At the molecular level, FJT upregulated the mRNA and protein expressions of Pcsk1 and Furin, increased the levels of BDNF and its functional receptor TrkB, and downregulated the expressions of proBDNF-preferring receptors p75NTR and Sortilin, ultimately shifting the proBDNF/mBDNF ratio toward mBDNF dominance. BDNF silencing significantly attenuated these improvements, reversing FJT-induced motor recovery and CST remodeling. In vitro, FJT-promoted neuronal growth was mimicked by exogenous mBDNF but reversed by Pcsk1/Furin inhibitors. Compared with the MCAO model group, medium-dose FJT exhibited the most significant therapeutic effects. Specifically, FJT notably improved gait parameters, increasing the average speed from 20.77 mm/s (MCAO) to 25.71 mm/s (FJT) and step length by approximately 21.14 %. Furthermore, FJT enhanced MEP conduction efficiency and promoted CST remodeling, characterized by a 5.26% increase in BDA-positive nerve fibers and elevated Growth-Associated Protein 43 (GAP43) expression in the denervated hemisphere. At the molecular level, FJT upregulated the mRNA and protein expressions of Pcsk1 and Furin, increased the levels of BDNF and its functional receptor TrkB, and downregulated the expressions of proBDNF-preferring receptors p75NTR and Sortilin, ultimately shifting the proBDNF/mBDNF ratio toward mBDNF dominance. BDNF silencing significantly attenuated these improvements, reversing FJT-induced motor recovery and CST remodeling. In vitro, FJT-promoted neuronal growth was mimicked by exogenous mBDNF but reversed by Pcsk1/Furin inhibitors. Show less
no PDF DOI: 10.1016/j.jep.2026.121235
BDNF bdnf corticospinal tract ischemic brain injury motor function neurological disorders stroke recovery traditional chinese medicine

Yin-Yang 1/Neural Precursor Cell-Expressed Developmentally Downregulated 4-Like Axis Suppresses Mer Tyrosine Kinase-Mediated Macrophage Efferocytosis to Exacerbate Atherosclerosis Via Triggering Pyroptosis.

Qiang Liu, Zaihua Cheng, Tao Wu +2 more · 2026 · Journal of the American Heart Association · added 2026-04-24
Atherosclerosis is considered as a major contributor for cardiovascular disease with high morbidity and mortality globally. However, the cross-talk between efferocytosis and inflammation in atheroscle Show more
Atherosclerosis is considered as a major contributor for cardiovascular disease with high morbidity and mortality globally. However, the cross-talk between efferocytosis and inflammation in atherosclerosis remains elusive. ApoE (apolipoprotein E) YY1 and NEDD4L were upregulated, but MerTK was downregulated in the arteries of ApoE Our findings demonstrated that YY1 positively regulated NEDD4L to modulate MerTK-mediated efferocytosis and activate NLRP3-mediated inflammation and pyroptosis, thus exacerbating atherosclerosis. Show less
📄 PDF DOI: 10.1161/JAHA.124.039855
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

Single-cell and transcriptomic profiling reveal stemness-driven immune evasion in obstructive sleep apnea (OSA) associated lung cancer.

Yu-Wei Liu, Chi-Jen Wu, Kai-Fu Chang +16 more · 2026 · Journal of Cancer · added 2026-04-24
Obstructive sleep apnea (OSA) is characterized by recurrent intermittent hypoxia (IH) and has been increasingly associated with lung cancer incidence and mortality. However, how IH-related biological Show more
Obstructive sleep apnea (OSA) is characterized by recurrent intermittent hypoxia (IH) and has been increasingly associated with lung cancer incidence and mortality. However, how IH-related biological programs relate to immune remodeling, stemness-associated phenotypes, and therapeutic resistance in lung cancer remains incompletely understood. We integrated single-cell RNA sequencing data from IH-exposed murine lung tissues (GSE301350) with bulk transcriptomic datasets from TCGA-LUAD and GSE31210 to examine hypoxia-associated cellular and transcriptional patterns. Stemness was quantified using CytoTRACE and transcriptome-based stemness scoring, and its associations with immune infiltration, immune checkpoint expression, TIDE scores, predicted drug sensitivity, and immunotherapy response were evaluated. A stemness-based prognostic model was constructed using LASSO Cox regression and validated in independent cohorts. Single-cell analysis revealed marked immune remodeling under intermittent hypoxia (IH), including expansion of effector T cells, and monocytes/macrophages, populations alongside reduced B cells and dendritic cells. In human LUAD cohorts, stemness-high tumors were associated with mitochondrial and metabolic stress-related transcriptional programs, and increased expression of immune checkpoint genes (PD-1, PD-L1, CTLA4, LAG3). Elevated stemness scores correlated with higher TIDE scores, poorer overall survival, and reduced predicted responsiveness to immunotherapy. LASSO modeling identified a six-gene stemness signature (EIF5A, MELTF, SEMA3C, CPS1, TCN1, SELENOK), that consistently stratified patients into high- and low-risk groups across TCGA and GSE31210 cohorts. Multivariate Cox regression confirmed the risk score as an independent prognostic factor. Drug sensitivity analyses further suggested that stemness-high tumors may exhibit increased susceptibility to selected kinase inhibitors (Dasatinib, A-770041) and metabolic modulators (Phenformin, Salubrinal). OSA-associated IH is linked to stemness-associated transcriptional plasticity, immune suppression, and adverse clinical outcomes in lung cancer. The identified stemness-based gene signature provides a robust prognostic biomarker and highlights potential therapeutic vulnerabilities, supporting integrative strategies that combine stemness and immune -targeted approaches with immunotherapy in OSA-associated lung cancer. Show less
📄 PDF DOI: 10.7150/jca.126708
CPS1

Cross-Platform and cross-species lipidomic profiling identifies promising biomarkers for adolescent major depressive disorder.

Yao Gao, Tao Dong, Ancha Baranova +9 more · 2026 · Molecular psychiatry · Nature · added 2026-04-24
Major depressive disorder (MDD) in adolescents is a critical public health concern, yet objective diagnostic biomarkers remain lacking. We conducted an integrative lipidomics study across human cohort Show more
Major depressive disorder (MDD) in adolescents is a critical public health concern, yet objective diagnostic biomarkers remain lacking. We conducted an integrative lipidomics study across human cohorts and a chronic unpredictable mild stress (CUMS) rat model. Targeted UPLC-MS/MS profiling was applied to a training cohort (95 MDD, 40 controls), and untargeted UPLC-HRMS profiling to an independent cohort (56 MDD, 37 controls). Candidate biomarkers were identified using univariate tests, partial least squares discriminant analysis, and three feature-selection methods (Boruta, LASSO, RFE), with predictive performance evaluated by cross-validation and external replication. Translational relevance was examined in CUMS rats through behavioral assays and lipidomic profiling of serum and brain tissues. Pathway enrichment and regression models explored metabolic context and clinical associations. In the training cohort, we found that 244 lipids were significantly altered, highlighting altered glycerophospholipid, glycerolipid, and sphingolipid metabolism. A 29-lipid panel achieved 90.4% cross-validation accuracy, while a reduced 7-lipid subset reached 94.8%. In the validation cohort, an 8-lipid panel achieved 71.2% accuracy, and a minimal 2-lipid set-LPA(18:2) and SPH(d16:1)-reached 72.1%. Cross-species analysis confirmed consistent downregulation of SPH(d16:1) in serum of both humans and rats, and of LPC(0:0/16:0) specifically in the rat prefrontal cortex. Regression analyses linked sex, age, and anxiety severity to lipid alterations. This cross-platform, cross-species study identifies reproducible lipid signatures of adolescent MDD, highlights SPH(d16:1) and LPC(0:0/16:0) as translational biomarkers, and implicates glycerophospholipid metabolism in MDD pathophysiology, providing a foundation for biomarker-guided diagnostics and therapeutics. Show less
📄 PDF DOI: 10.1038/s41380-026-03486-7
LPA