👤 Xiangbin Zhang

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
3874
Articles
2387
Name variants
Also published as: A-Mei Zhang, Ai Zhang, Ai-Min Zhang, Aiguo Zhang, Aihua Zhang, Aijun Zhang, Aileen Zhang, Ailin Zhang, Aimei Zhang, Aimin Zhang, Aixiang Zhang, Alaina Zhang, Alex R Zhang, Amy L Zhang, An Zhang, An-Qi Zhang, Anan Zhang, Andrew Zhang, Ang Zhang, Anli Zhang, Anqi Zhang, Anwei Zhang, Anying Zhang, Ao Zhang, Bangke Zhang, Bangzhou Zhang, Bao Long Zhang, Bao-Fu Zhang, Bao-Rong Zhang, Baohu Zhang, Baojing Zhang, Baojun Zhang, Baoren Zhang, Baorong Zhang, Baotong Zhang, Bei B Zhang, Bei Zhang, Bei-Bei Zhang, Beiyu Zhang, Ben Zhang, Benjian Zhang, Benyou Zhang, Bi-Tian Zhang, Biao Zhang, Bicheng Zhang, Bikui Zhang, Bin Zhang, Binbin Zhang, Bing Zhang, Bing-Qi Zhang, Bingbing Zhang, Bingkun Zhang, Bingqiang Zhang, Bingxue Zhang, Bingye Zhang, Bixia Zhang, Bo Zhang, Bo-Fei Zhang, Bo-Heng Zhang, Bo-Ya Zhang, Bochuan Zhang, Bofang Zhang, Bohao Zhang, Bohong Zhang, Bohua Zhang, Bojian Zhang, Bolin Zhang, Boping Zhang, Boqing Zhang, Bosheng Zhang, Bowei Zhang, Bowen Zhang, Boxi Zhang, Boxiang Zhang, Boya Zhang, Boyan Zhang, C D Zhang, C H Zhang, C Zhang, Cai Zhang, Cai-Ling Zhang, Caihong Zhang, Caiping Zhang, Caiqing Zhang, Caishi Zhang, Caiyi Zhang, Caiying Zhang, Caiyu Zhang, Can Zhang, Cathy C Zhang, Chan-na Zhang, Chang Zhang, Chang-Hua Zhang, Changhua Zhang, Changhui Zhang, Changjiang Zhang, Changjing Zhang, Changlin Zhang, Changlong Zhang, Changquan Zhang, Changteng Zhang, Changwang Zhang, Channa Zhang, Chao Zhang, Chao-Hua Zhang, Chao-Sheng Zhang, Chao-Yang Zhang, ChaoDong Zhang, Chaobao Zhang, Chaoke Zhang, Chaoqiang Zhang, Chaoyang Zhang, Chaoyue Zhang, Chen Zhang, Chen-Qi Zhang, Chen-Ran Zhang, Chen-Song Zhang, Chen-Xi Zhang, Chen-Yan Zhang, Chen-Yang Zhang, Chenan Zhang, Chenfei Zhang, Cheng Cheng Zhang, Cheng Zhang, Cheng-Lin Zhang, Cheng-Wei Zhang, Chengbo Zhang, Chengcheng Zhang, Chengfei Zhang, Chenggang Zhang, Chengkai Zhang, Chenglong Zhang, Chengnan Zhang, Chengrui Zhang, Chengsheng Zhang, Chengshi Zhang, Chenguang Zhang, Chengwu Zhang, Chengxiang Zhang, Chengxiong Zhang, Chengyu Zhang, Chenhong Zhang, Chenhui Zhang, Chenjie Zhang, Chenlin Zhang, Chenlu Zhang, Chenmin Zhang, Chenming Zhang, Chenrui Zhang, Chenshuang Zhang, Chenxi Zhang, Chenyan Zhang, Chenyang Zhang, Chenyi Zhang, Chenzi Zhang, Chi Zhang, Chong Zhang, Chong-Hui Zhang, Chongguo Zhang, Chonghe Zhang, Chris Zhiyi Zhang, Chu-Yue Zhang, Chuan Zhang, Chuanfu Zhang, Chuankuan Zhang, Chuankuo Zhang, Chuanmao Zhang, Chuantao Zhang, Chuanxin Zhang, Chuanyong Zhang, Chuchu Zhang, Chumeng Zhang, Chun Zhang, Chun-Lan Zhang, Chun-Mei Zhang, Chun-Qing Zhang, Chungu Zhang, Chunguang Zhang, Chunhai Zhang, Chunhong Zhang, Chunhua Zhang, Chunjun Zhang, Chunli Zhang, Chunling Zhang, Chunqing Zhang, Chunxia Zhang, Chunxiang Zhang, Chunxiao Zhang, Chunyan Zhang, Chunying Zhang, Churen Zhang, Chuting Zhang, Chuyue Zhang, Ci Zhang, Claire Y Zhang, Claire Zhang, Clarence K Zhang, Cong Zhang, Congen Zhang, Cuihua Zhang, Cuijuan Zhang, Cuilin Zhang, Cuiping Zhang, Cuiyu Zhang, Cun Zhang, Da Zhang, Da-Qi Zhang, Da-Wei Zhang, Dachuan Zhang, Dadong Zhang, Daguo Zhang, Dai Zhang, Dalong Zhang, Daming Zhang, Dan Zhang, Dan-Dan Zhang, DanDan Zhang, Danfeng Zhang, Danhua Zhang, Danning Zhang, Danyan Zhang, Danyang Zhang, Daolai Zhang, Daoyong Zhang, Dapeng Zhang, David Y Zhang, David Zhang, Dawei Zhang, Daxin Zhang, Dayi Zhang, De-Jun Zhang, Dekai Zhang, Delai Zhang, Deng-Feng Zhang, Dengke Zhang, Deqiang Zhang, Detao Zhang, Deyi Zhang, Deyin Zhang, Di Zhang, Dian Ming Zhang, Dianbo Zhang, Dianzheng Zhang, Ding Zhang, Dingdong Zhang, Dinghu Zhang, Dingkai Zhang, Dingyi Zhang, Dingyu Zhang, Dong Zhang, Dong-Hui Zhang, Dong-Mei Zhang, Dong-Wei Zhang, Dong-Ying Zhang, Dong-cui Zhang, Dong-juan Zhang, Dong-qiang Zhang, Dongdong Zhang, Dongfeng Zhang, Donghua Zhang, Donghui Zhang, Dongjian Zhang, Dongjie Zhang, Donglei Zhang, Dongmei Zhang, Dongsheng Zhang, Dongxin Zhang, Dongyan Zhang, Dongyang Zhang, Dongying Zhang, Donna D Zhang, Donna Zhang, Duo Zhang, Duoduo Zhang, Duowen Zhang, En Zhang, Enhui Zhang, Enming Zhang, Erchen Zhang, F P Zhang, F Zhang, Fa Zhang, Famin Zhang, Fan Zhang, Fang Zhang, Fanghong Zhang, Fangmei Zhang, Fangting Zhang, Fangyuan Zhang, Fei Zhang, Fei-Ran Zhang, Feifei Zhang, Feixue Zhang, Fen Zhang, Feng Zhang, Fengqing Zhang, Fengshi Zhang, Fengshuo Zhang, Fengwei Zhang, Fengxi Zhang, Fengxia Zhang, Fengxu Zhang, Fomin Zhang, Fred Zhang, Fu-Ping Zhang, Fubo Zhang, Fugui Zhang, Fuhan Zhang, Fujun Zhang, Fukang Zhang, Fuming Zhang, Fuqiang Zhang, Fuquan Zhang, Furen Zhang, Fushun Zhang, Fuxing Zhang, Fuyang Zhang, Fuyuan Zhang, G Zhang, G-Y Zhang, Gan Zhang, Gang Zhang, Ganlin Zhang, Gaoxin Zhang, Gary Zhang, Ge Zhang, Geng Zhang, Genglin Zhang, Genxi Zhang, Geyang Zhang, Gong Zhang, Gu Zhang, Guan-Yan Zhang, Guang Zhang, Guang-Qiong Zhang, Guang-Xian Zhang, Guang-Ya Zhang, Guanghui Zhang, Guangji Zhang, Guanglei Zhang, Guangliang Zhang, Guangping Zhang, Guangqiong Zhang, Guangxian Zhang, Guangxin Zhang, Guangye Zhang, Guangyong Zhang, Guangyuan Zhang, Guanqun Zhang, Gui-Ping Zhang, Guicheng Zhang, Guihua Zhang, Guijie Zhang, Guili Zhang, Guiliang Zhang, Guilin Zhang, Guimin Zhang, Guiping Zhang, Guisen Zhang, Guixia Zhang, Guixiang Zhang, Gumuyang Zhang, Guo-Fang Zhang, Guo-Fu Zhang, Guo-Guo Zhang, Guo-Liang Zhang, Guo-Wei Zhang, Guo-Xiong Zhang, Guoan Zhang, Guochao Zhang, Guodong Zhang, Guofang Zhang, Guofeng Zhang, Guofu Zhang, Guoguo Zhang, Guohua Zhang, Guohui Zhang, Guojun Zhang, Guoli Zhang, Guoliang Zhang, Guolong Zhang, Guomin Zhang, Guoming Zhang, Guoping Zhang, Guoqiang Zhang, Guoqing Zhang, Guorui Zhang, Guosen Zhang, Guowei Zhang, Guoxin Zhang, Guoying Zhang, Guozhi Zhang, H D Zhang, H F Zhang, H L Zhang, H P Zhang, H W Zhang, H X Zhang, H Y Zhang, H Zhang, H-F Zhang, Hai Zhang, Hai-Bo Zhang, Hai-Feng Zhang, Hai-Gang Zhang, Hai-Han Zhang, Hai-Liang Zhang, Hai-Man Zhang, Hai-Ying Zhang, Haibei Zhang, Haibing Zhang, Haibo Zhang, Haicheng Zhang, Haifeng Zhang, Haihong Zhang, Haihua Zhang, Haijiao Zhang, Haijun Zhang, Haikuo Zhang, Hailei Zhang, Hailian Zhang, Hailiang Zhang, Hailin Zhang, Hailing Zhang, Hailong Zhang, Hailou Zhang, Haiming Zhang, Hainan Zhang, Haipeng Zhang, Haisan Zhang, Haisen Zhang, Haitao Zhang, Haiwang Zhang, Haiwei Zhang, Haixia Zhang, Haiyan Zhang, Haiyang Zhang, Haiying Zhang, Haiyue Zhang, Han Zhang, Hanchao Zhang, Hang Zhang, Hanqi Zhang, Hanrui Zhang, Hansi Zhang, Hanting Zhang, Hanwang Zhang, Hanwen Zhang, Hanxu Zhang, Hanyin Zhang, Hanyu Zhang, Hao Zhang, Hao-Chen Zhang, Hao-Yu Zhang, Haohao Zhang, Haojian Zhang, Haojie Zhang, Haojun Zhang, Haokun Zhang, Haolin Zhang, Haomin Zhang, Haonan Zhang, Haopeng Zhang, Haoran Zhang, Haotian Zhang, Haowen Zhang, Haoxing Zhang, Haoyu Zhang, Haoyuan Zhang, Haoyue Zhang, Haozheng Zhang, He Zhang, Hefang Zhang, Hejun Zhang, Heng Zhang, Hengming Zhang, Hengrui Zhang, Hengyuan Zhang, Heping Zhang, Hong Zhang, Hong-Jie Zhang, Hong-Sheng Zhang, Hong-Xing Zhang, Hong-Yu Zhang, Hong-Zhen Zhang, Hongbin Zhang, Hongbing Zhang, Hongcai Zhang, Hongfeng Zhang, Hongfu Zhang, Honghe Zhang, Honghong Zhang, Honghua Zhang, Hongjia Zhang, Hongjie Zhang, Hongjin Zhang, Hongju Zhang, Hongjuan Zhang, Honglei Zhang, Hongliang Zhang, Hongmei Zhang, Hongmin Zhang, Hongquan Zhang, Hongrong Zhang, Hongrui Zhang, Hongsen Zhang, Hongtao Zhang, Hongting Zhang, Hongwu Zhang, Hongxia Zhang, Hongxin Zhang, Hongxing Zhang, Hongya Zhang, Hongyan Zhang, Hongyang Zhang, Hongyi Zhang, Hongying Zhang, Hongyou Zhang, Hongyuan Zhang, Hongyun Zhang, Hongzhong Zhang, Hongzhou Zhang, Houbin Zhang, Hu Zhang, Hua Zhang, Hua-Min Zhang, Hua-Xiong Zhang, Huabing Zhang, Huafeng Zhang, Huaiyong Zhang, Huajia Zhang, Huan Zhang, Huan-Tian Zhang, Huanmin Zhang, Huanqing Zhang, Huanxia Zhang, Huanyu Zhang, Huaqi Zhang, Huaqiu Zhang, Huawei Zhang, Huawen Zhang, Huayang Zhang, Huayong Zhang, Huayu Zhang, Hugang Zhang, Huhan Zhang, Hui Hua Zhang, Hui Z Zhang, Hui Zhang, Hui-Jun Zhang, Hui-Wen Zhang, Huibing Zhang, Huifang Zhang, Huihui Zhang, Huijie Zhang, Huijun Zhang, Huili Zhang, Huilin Zhang, Huimao Zhang, Huimin Zhang, Huiming Zhang, Huiping Zhang, Huiqing Zhang, Huiru Zhang, Huiting Zhang, Huixin Zhang, Huiying Zhang, Huiyu Zhang, Huiyuan Zhang, Huize Zhang, Huizhen Zhang, Igor Ying Zhang, J B Zhang, J R Zhang, J Y Zhang, J Zhang, J-Y Zhang, Jamie Zhang, Jason Z Zhang, Jennifer Y Zhang, Jerry Z Zhang, Ji Yao Zhang, Ji Zhang, Ji-Yuan Zhang, Jia Zhang, Jia-Bao Zhang, Jia-Si Zhang, Jia-Su Zhang, Jia-Xuan Zhang, Jiabi Zhang, Jiachao Zhang, Jiachen Zhang, Jiacheng Zhang, Jiahai Zhang, Jiahao Zhang, Jiahe Zhang, Jiajia Zhang, Jiajing Zhang, Jiaming Zhang, Jian Zhang, Jian-Guo Zhang, Jian-Ping Zhang, Jian-Xu Zhang, Jianan Zhang, Jianbin Zhang, Jianbo Zhang, Jianchao Zhang, Jianduan Zhang, Jianeng Zhang, Jianfa Zhang, Jiang Zhang, Jiangang Zhang, Jianghong Zhang, Jianglin Zhang, Jiangmei Zhang, Jiangtao Zhang, Jianguang Zhang, Jianguo Zhang, Jiangyan Zhang, Jianhai Zhang, Jianhong Zhang, Jianhua Zhang, Jianhui Zhang, Jianing Zhang, Jianjun Zhang, Jiankang Zhang, Jiankun Zhang, Jianliang Zhang, Jianling Zhang, Jianmei Zhang, Jianmin Zhang, Jianming Zhang, Jiannan Zhang, Jianping Zhang, Jianqiong Zhang, Jianshe Zhang, Jianting Zhang, Jianwei Zhang, Jianwen Zhang, Jianwu Zhang, Jianxia Zhang, Jianxiang Zhang, Jianxin Zhang, Jianying Zhang, Jianyong Zhang, Jianzhao Zhang, Jiao Zhang, Jiaqi Zhang, Jiasheng Zhang, Jiawei Zhang, Jiawen Zhang, Jiaxin Zhang, Jiaxing Zhang, Jiayan Zhang, Jiayi Zhang, Jiayin Zhang, Jiaying Zhang, Jiayu Zhang, Jiayuan Zhang, Jibin Zhang, Jicai Zhang, Jie Zhang, Jiecheng Zhang, Jiehao Zhang, Jiejie Zhang, Jieming Zhang, Jieping Zhang, Jieqiong Zhang, Jieying Zhang, Jifa Zhang, Jifeng Zhang, Jihang Zhang, Jimei Zhang, Jiming Zhang, Jimmy Zhang, Jin Zhang, Jin-Ge Zhang, Jin-Jing Zhang, Jin-Man Zhang, Jin-Ru Zhang, Jin-Rui Zhang, Jin-Yu Zhang, Jinbiao Zhang, Jinfan Zhang, Jinfang Zhang, Jinfeng Zhang, Jing Jing Zhang, Jing Zhang, Jing-Bo Zhang, Jing-Chang Zhang, Jing-Fa Zhang, Jing-Lve Zhang, Jing-Nan Zhang, Jing-Qiu Zhang, Jing-Zhan Zhang, JingZi Zhang, Jingchuan Zhang, Jingchun Zhang, Jingdan Zhang, Jingdong Zhang, Jingfa Zhang, Jinghui Zhang, Jingjing Zhang, Jinglan Zhang, Jingli Zhang, Jingliang Zhang, Jinglu Zhang, Jingmei Zhang, Jingmian Zhang, Jingning Zhang, Jingping Zhang, Jingqi Zhang, Jingrong Zhang, Jingru Zhang, Jingshuang Zhang, Jingsong Zhang, Jingtian Zhang, Jingting Zhang, Jingwei Zhang, Jingwen Zhang, Jingxi Zhang, Jingxiao Zhang, Jingxuan Zhang, Jingxue Zhang, Jingyao Zhang, Jingyi Zhang, Jingying Zhang, Jingyu Zhang, Jingyuan Zhang, Jingyue Zhang, Jingzhe Zhang, Jinhua Zhang, Jinhui Zhang, Jinjin Zhang, Jinjing Zhang, Jinliang Zhang, Jinlong Zhang, Jinming Zhang, Jinquan Zhang, Jinrui Zhang, Jinsong Zhang, Jinsu Zhang, Jintao Zhang, Jinwei Zhang, Jinxiu Zhang, Jinyi Zhang, Jinying Zhang, Jinyu Zhang, Jinze Zhang, Jinzhou Zhang, Jiqiang Zhang, Jiquan Zhang, Jishou Zhang, Jishui Zhang, Jitai Zhang, Jiuchun Zhang, Jiupan Zhang, Jiuwei Zhang, Jiuxuan Zhang, Jixia Zhang, Jixing Zhang, Jiyang Zhang, Joe Z Zhang, John H Zhang, John Z H Zhang, Joshua Zhang, Joyce Zhang, Juan Zhang, Juan-Juan Zhang, Jue Zhang, Juliang Zhang, Jun Zhang, Jun-Feng Zhang, Jun-Jie Zhang, Jun-Xiao Zhang, Jun-Xiu Zhang, Jun-ying Zhang, June Zhang, Junfeng Zhang, Junhan Zhang, Junhang Zhang, Junhua Zhang, Junhui Zhang, Junjie Zhang, Junjing Zhang, Junkai Zhang, Junli Zhang, Junling Zhang, Junlong Zhang, Junmei Zhang, Junmin Zhang, Junpei Zhang, Junpeng Zhang, Junping Zhang, Junqing Zhang, Junran Zhang, Junru Zhang, Junsheng Zhang, Juntai Zhang, Junwei Zhang, Junxia Zhang, Junxiao Zhang, Junxing Zhang, Junxiu Zhang, Junyan Zhang, Junyi Zhang, Junying Zhang, Junyu Zhang, Junzhi Zhang, Juqing Zhang, K Y Zhang, K Zhang, Kai Zhang, Kai-Jie Zhang, Kai-Qiang Zhang, Kaichuang Zhang, Kaige Zhang, Kaihua Zhang, Kaihui Zhang, Kailin Zhang, Kailing Zhang, Kaiming Zhang, Kainan Zhang, Kaitai Zhang, Kaituo Zhang, Kaiwen Zhang, Kaiyi Zhang, Kan Zhang, Kang Zhang, Kang-Ling Zhang, Kangjun Zhang, Kangning Zhang, Karen Zhang, Ke Zhang, Ke-Wen Zhang, Ke-lan Zhang, Kefen Zhang, Kejia Zhang, Kejian Zhang, Kejin Zhang, Kejun Zhang, Keke Zhang, Keshan Zhang, Kewen Zhang, Keyi Zhang, Keyong Zhang, Keyu Zhang, Kezhong Zhang, Kongyong Zhang, Kui Zhang, Kui-ming Zhang, Kun Zhang, Kunning Zhang, Kunshan Zhang, Kunyi Zhang, Kuo Zhang, L F Zhang, L Zhang, L-S Zhang, Laihong Zhang, Lan Zhang, Lanfang Zhang, Lanju Zhang, Lanjun Zhang, Lanlan Zhang, Lantian Zhang, Lanyue Zhang, Le Zhang, Le-Le Zhang, Lechi Zhang, Lei Zhang, Lei-Lei Zhang, Lei-Sheng Zhang, Leilei Zhang, Leili Zhang, Leitao Zhang, Leiying Zhang, Lele Zhang, Leli Zhang, Leo H Zhang, Li Zhang, Li-Fen Zhang, Li-Jie Zhang, Li-Ke Zhang, Li-ping Zhang, Lian Zhang, Lian-Lian Zhang, Lianbo Zhang, Lianfeng Zhang, Liang Zhang, Liang-Rong Zhang, Liangdong Zhang, Liangliang Zhang, Liangming Zhang, Lianjun Zhang, Lianmei Zhang, Lianqin Zhang, Lianxin Zhang, Libo Zhang, Lichao Zhang, Lichen Zhang, Licheng Zhang, Lichuan Zhang, Licui Zhang, Lida Zhang, Lie Zhang, Lifan Zhang, Lifang Zhang, Liguo Zhang, Lihong Zhang, Lihua Zhang, Lijian Zhang, Lijiao Zhang, Lijie Zhang, Lijuan Zhang, Lijun Zhang, Lilei Zhang, Lili Zhang, Limei Zhang, Limin Zhang, Liming Zhang, Lin Zhang, Lin-Jie Zhang, Lina Zhang, Linan Zhang, Linbo Zhang, Linda S Zhang, Ling Xia Zhang, Ling Zhang, Ling-Yu Zhang, Lingjie Zhang, Lingli Zhang, Lingling Zhang, Lingna Zhang, Lingqiang Zhang, Lingxiao Zhang, Lingyan Zhang, Lingyu Zhang, Lining Zhang, Linjing Zhang, Linli Zhang, Linlin Zhang, Lintao Zhang, Linyou Zhang, Linyuan Zhang, Liping Zhang, Liqian Zhang, Lirong Zhang, Lishuang Zhang, Litao Zhang, Liu Zhang, Liuming Zhang, Liuwei Zhang, Liwei Zhang, Liwen Zhang, Lixia Zhang, Lixing Zhang, Liyan Zhang, Liyi Zhang, Liyin Zhang, Liying Zhang, Liyu Zhang, Liyuan Zhang, Liyun Zhang, Lizhi Zhang, Long Zhang, Longlong Zhang, Longxin Zhang, Longzhen Zhang, Lu Zhang, Lu-Pei Zhang, Lu-Yang Zhang, Luanluan Zhang, Lucia Zhang, Lufei Zhang, Lukuan Zhang, Lulu Zhang, Lun Zhang, Lunan Zhang, Luning Zhang, Luo Zhang, Luo-Meng Zhang, Luoping Zhang, Lupei Zhang, Lusha Zhang, Luwen Zhang, Luyao Zhang, Luyun Zhang, Luzheng Zhang, Lv-Lang Zhang, M H Zhang, M J Zhang, M M Zhang, M Q Zhang, M X Zhang, M Zhang, Man Zhang, Manjin Zhang, Mao Zhang, Maomao Zhang, Mei Zhang, Mei-Fang Zhang, Mei-Ling Zhang, Mei-Qing Zhang, Mei-Ya Zhang, Mei-Zhen Zhang, MeiLu Zhang, Meidi Zhang, Meijia Zhang, Meiling Zhang, Meimei Zhang, Meishan Zhang, Meiwei Zhang, Meixia Zhang, Meixian Zhang, Meiyu Zhang, Melissa C Zhang, Melody Zhang, Meng Zhang, Meng-Jie Zhang, Meng-Wen Zhang, Meng-Ying Zhang, Mengdi Zhang, Mengguo Zhang, Menghao Zhang, Menghuan Zhang, Menghui Zhang, Mengjia Zhang, Mengjie Zhang, Mengliang Zhang, Menglu Zhang, Mengmeng Zhang, Mengmin Zhang, Mengna Zhang, Mengnan Zhang, Mengni Zhang, Mengqi Zhang, Mengqiu Zhang, Mengren Zhang, Mengshi Zhang, Mengxi Zhang, Mengxian Zhang, Mengxue Zhang, Mengying Zhang, Mengyuan Zhang, Mengyue Zhang, Mengzhao Zhang, Mengzhen Zhang, Mi Zhang, Mianzhi Zhang, Miao Zhang, Miao-Miao Zhang, Miaomiao Zhang, Miaoran Zhang, Michael Zhang, Min Zhang, Minfang Zhang, Ming Zhang, Ming-Jun Zhang, Ming-Liang Zhang, Ming-Ming Zhang, Ming-Rong Zhang, Ming-Yu Zhang, Ming-Zhu Zhang, Mingai Zhang, Mingchang Zhang, Mingdi Zhang, Mingfa Zhang, Mingfeng Zhang, Minghang Zhang, Minghao Zhang, Minghui Zhang, Mingjie Zhang, Mingjiong Zhang, Mingjun Zhang, Mingming Zhang, Mingqi Zhang, Mingtong Zhang, Mingxiang Zhang, Mingxiu Zhang, Mingxuan Zhang, Mingxue Zhang, Mingyang A Zhang, Mingyang Zhang, Mingyao Zhang, Mingyi Zhang, Mingying Zhang, Mingyu Zhang, Mingyuan Zhang, Mingyue Zhang, Mingzhao Zhang, Mingzhen Zhang, Minhong Zhang, Minying Zhang, Minyue Zhang, Minzhi Zhang, Minzhu Zhang, Mo Zhang, Mo-Ruo Zhang, Mu Zhang, Muqing Zhang, Muxin Zhang, Muzi Zhang, N Zhang, Na Zhang, Naijin Zhang, Naiqi Zhang, Naisheng Zhang, Naixia Zhang, Nan Yang Zhang, Nan Zhang, Nan-Nan Zhang, Nana Zhang, Nannan Zhang, Nasha Zhang, Ni Zhang, Niankai Zhang, Nianxiang Zhang, Nieke Zhang, Ning Zhang, Ning-Ping Zhang, Ninghan Zhang, Ningkun Zhang, Ningning Zhang, Ningzhen Zhang, Ningzhi Zhang, Nisi Zhang, Nong Zhang, Nu Zhang, P Zhang, Pan Zhang, Pan-Pan Zhang, Panpan Zhang, Pei Zhang, Pei-Weng Zhang, Pei-Zhuo Zhang, PeiFeng Zhang, Peichun Zhang, Peijing Zhang, Peijun Zhang, Peilin Zhang, Peiqin Zhang, Peiwen Zhang, Peiyi Zhang, Peizhen Zhang, Peng Zhang, Peng-Cheng Zhang, Peng-Fei Zhang, Pengbo Zhang, Pengcheng Zhang, Pengfei Zhang, Pengpeng Zhang, Pengwei Zhang, Pengyuan Zhang, Pili Zhang, Ping Zhang, Ping-Fan Zhang, Pingchuan Zhang, Pinggen Zhang, Pingmei Zhang, Pu-Hong Zhang, Pumin Zhang, Q L Zhang, Q Y Zhang, Q Zhang, Q-D Zhang, Qi Zhang, Qi-Ai Zhang, Qi-Lei Zhang, Qi-Min Zhang, QiYue Zhang, Qian Jun Zhang, Qian ZHANG, Qian-Qian Zhang, Qian-Wen Zhang, Qiang Zhang, Qiang-Sheng Zhang, Qiangsheng Zhang, Qiangyan Zhang, Qianhui Zhang, Qianjun Zhang, Qiannan Zhang, Qianqian Zhang, Qianru Zhang, Qiao-Xia Zhang, Qiaofang Zhang, Qiaojun Zhang, Qiaoxuan Zhang, Qifan Zhang, Qiguo Zhang, Qihao Zhang, Qihong Zhang, Qilong Zhang, Qilu Zhang, Qimin Zhang, Qin Zhang, Qing Zhang, Qing-Hui Zhang, Qing-Zhu Zhang, Qingchao Zhang, Qingcheng Zhang, Qingchuan Zhang, Qingfeng Zhang, Qinghong Zhang, Qinghua Zhang, Qingjiong Zhang, Qingjun Zhang, Qingling Zhang, Qingna Zhang, Qingqing Zhang, Qingquan Zhang, Qingrun Zhang, Qingshuang Zhang, Qingtian Zhang, Qingxiu Zhang, Qingxue Zhang, Qingyu Zhang, Qingyue Zhang, Qingyun Zhang, Qinjun Zhang, Qiong Zhang, Qishu Zhang, Qiu Zhang, Qiuting Zhang, Qiuxia Zhang, Qiuyang Zhang, Qiuyue Zhang, Qiwei Zhang, Qiyong Zhang, Quan Zhang, Quan-bin Zhang, Quanfu Zhang, Quanqi Zhang, Quanquan Zhang, Qun Zhang, Qun-Feng Zhang, Qunchen Zhang, Qunfeng Zhang, Qunyuan Zhang, R Zhang, Ran Zhang, Ranran Zhang, Ren Zhang, Renbo Zhang, Renhe Zhang, Renliang Zhang, Renshuai Zhang, Rey M Zhang, Richard Zhang, Rong Zhang, Rong-Kai Zhang, Rongcai Zhang, Rongchao Zhang, Rongguang Zhang, Rongrong Zhang, Rongxin Zhang, Rongxu Zhang, Rongying Zhang, Rongyu Zhang, Ru Zhang, Rugang Zhang, Rui Long Zhang, Rui Xue Zhang, Rui Yan Zhang, Rui Zhang, Rui-Nan Zhang, Rui-Ning Zhang, Rui-fang Zhang, Ruihao Zhang, Ruihong Zhang, Ruikun Zhang, Ruilin Zhang, Ruiling Zhang, Ruimin Zhang, Ruiqi Zhang, Ruiqian Zhang, Ruisan Zhang, Ruixia Zhang, Ruixin Zhang, Ruixue Zhang, Ruiyan Zhang, Ruiyang Zhang, Ruiying Zhang, Ruizhe Zhang, Ruizhi Zhang, Ruizhong Zhang, Rulin Zhang, Run Zhang, Runcheng Zhang, Runxiang Zhang, Runyun Zhang, Runze Zhang, Ruo-Xin Zhang, Ruohan Zhang, Ruoshi Zhang, Ruotian Zhang, Ruoxuan Zhang, Ruoying Zhang, Rusi Zhang, Ruth Zhang, Ruxiang Zhang, Ruxuan Zhang, Ruyi Zhang, S Y Zhang, S Z Zhang, S Zhang, Sai Zhang, Saidan Zhang, Saifei Zhang, Sainan Zhang, Sanbao Zhang, Sen Zhang, Sha Zhang, Shan Zhang, Shan-Shan Zhang, Shanchun Zhang, Shang Zhang, Shangxiong Zhang, Shanhong Zhang, Shanshan Zhang, Shanxiang Zhang, Shao Kang Zhang, Shao Zhang, Shao-Qi Zhang, Shaochuan Zhang, Shaochun Zhang, Shaofei Zhang, Shaofeng Zhang, Shaohua Zhang, Shaojun Zhang, Shaoyang Zhang, Shaozhao Zhang, Shaozhen Zhang, Shasha Zhang, Shen Zhang, Sheng Zhang, Sheng-Dao Zhang, Sheng-Hong Zhang, Sheng-Qiang Zhang, Sheng-Xiao Zhang, Shengchi Zhang, Shengding Zhang, Shengkun Zhang, Shenglai Zhang, Shenglan Zhang, Shenglei Zhang, Shengli Zhang, Shengming Zhang, Shengnan Zhang, Shengye Zhang, Shenqi Zhang, Shenqian Zhang, Shi Zhang, Shi-Han Zhang, Shi-Jie Zhang, Shi-Meng Zhang, Shi-Qian Zhang, Shi-Yao Zhang, ShiSong Zhang, Shichao Zhang, Shihan Zhang, Shijun Zhang, Shikai Zhang, Shilei Zhang, Shimao Zhang, Shining Zhang, Shiping Zhang, Shiqi Zhang, Shiquan Zhang, Shiti Zhang, Shitian Zhang, Shiwen Zhang, Shiwu Zhang, Shiyao Zhang, Shiyi Zhang, Shiyu Zhang, Shiyun Zhang, Shou-Mei Zhang, Shou-Peng Zhang, Shouyue Zhang, Shu Zhang, Shu-Dong Zhang, Shu-Fan Zhang, Shu-Fang Zhang, Shu-Min Zhang, Shu-Ming Zhang, Shu-Yang Zhang, Shu-Zhen Zhang, Shuai Zhang, Shuai-Nan Zhang, Shuaishuai Zhang, Shuang Zhang, Shuangjie Zhang, Shuanglu Zhang, Shuangxin Zhang, Shubing Zhang, Shuchen Zhang, Shucong Zhang, Shuer Zhang, Shuge Zhang, Shuhong Zhang, Shuijun Zhang, Shujun Zhang, Shuli Zhang, Shulong Zhang, Shun Zhang, Shun-Bo Zhang, Shunfen Zhang, Shunming Zhang, Shuo Zhang, Shupeng Zhang, Shuran Zhang, Shurui Zhang, Shushan Zhang, Shuwan Zhang, Shuwei Zhang, Shuxia Zhang, Shuya Zhang, Shuyan Zhang, Shuyang Zhang, Shuye Zhang, Shuyi Zhang, Shuyuan Zhang, Si Zhang, Si-Zhong Zhang, Sibin Zhang, Sifan Zhang, Sihe Zhang, Simeng Zhang, Simin Zhang, Siqi Zhang, Sisi Zhang, Sixue Zhang, Siyuan Zhang, Siyue Zhang, Sizhong Zhang, Song Zhang, Song-Yang Zhang, Songlin Zhang, Songying Zhang, Sophia L Zhang, Stanley Weihua Zhang, Stephen X Zhang, Su Zhang, Sujiang Zhang, Sulin Zhang, Sumei Zhang, Suming Zhang, Suping Zhang, Susie Zhang, Suya Zhang, Suyang Zhang, Suzhen Zhang, T Zhang, Tangjuan Zhang, Tao Zhang, Tao-Lan Zhang, Taojun Zhang, Taoyuan Zhang, Teng Zhang, Tengfang Zhang, Terry Jianguo Zhang, Ti Zhang, Tian Zhang, Tian-Guang Zhang, Tian-Yu Zhang, Tiane Zhang, Tianfeng Zhang, Tianliang Zhang, Tianlong Zhang, Tianpeng Zhang, Tianshu Zhang, Tiantian Zhang, Tianxi Zhang, Tianxiao Zhang, Tianxin Zhang, Tianyang Zhang, Tianye Zhang, Tianyi Zhang, Tianyu Zhang, Tie-mei Zhang, Tiefeng Zhang, Tiehua Zhang, Tiejun Zhang, Ting Ting Zhang, Ting Zhang, Ting-Ting Zhang, Tinghu Zhang, Tingting Zhang, Tingxue Zhang, Tingying Zhang, Tong Xuan Zhang, Tong Zhang, Tong-Cun Zhang, Tongcun Zhang, Tongfu Zhang, Tonghan Zhang, Tonghua Zhang, Tonghui Zhang, Tongran Zhang, Tongshuo Zhang, Tongtong Zhang, Tongwu Zhang, Tongxin Zhang, Tongxue Zhang, Tuo Zhang, Vita Zhang, W G Zhang, W X Zhang, W Zhang, Wancong Zhang, Wang-Dong Zhang, Wangang Zhang, Wangping Zhang, Wanjiang Zhang, Wanjun Zhang, Wannian Zhang, Wanqi Zhang, Wanting Zhang, Wanying Zhang, Wanyu Zhang, Wei Zhang, Wei-Jia Zhang, Wei-Na Zhang, Wei-Yi Zhang, Weibo Zhang, Weichen Zhang, Weifeng Zhang, Weiguo Zhang, Weihua Zhang, Weijian Zhang, Weikang Zhang, Weili Zhang, Weilin Zhang, Weiling Zhang, Weilong Zhang, Weimin Zhang, Weina Zhang, Weipeng Zhang, Weiping J Zhang, Weiqin Zhang, Weisen Zhang, Weiwei Zhang, Weixia Zhang, Weiyi Zhang, Weiyu Zhang, Weizheng Zhang, Weizhou Zhang, Wen Jun Zhang, Wen Zhang, Wen-Hong Zhang, Wen-Jie Zhang, Wen-Jing Zhang, Wen-Xin Zhang, Wen-Xuan Zhang, Wenbin Zhang, Wenbo Zhang, Wenchao Zhang, Wencheng Zhang, Wencong Zhang, Wendi Zhang, Wenguang Zhang, Wenhao Zhang, Wenhong Zhang, Wenhua Zhang, Wenhui Zhang, Wenji Zhang, Wenjia Zhang, Wenjing Zhang, Wenjuan Zhang, Wenjun Zhang, Wenkai Zhang, Wenkui Zhang, Wenli Zhang, Wenlong Zhang, Wenlu Zhang, Wenming Zhang, Wenqian Zhang, Wenru Zhang, Wentao Zhang, Wenting Zhang, Wenwen Zhang, Wenxi Zhang, Wenxiang Zhang, Wenxin Zhang, Wenxue Zhang, Wenya Zhang, Wenyang Zhang, Wenyi Zhang, Wenyuan Zhang, Wenzhong Zhang, Wuhu Zhang, X N Zhang, X X Zhang, X Y Zhang, X Zhang, X-T Zhang, X-Y Zhang, Xi Zhang, Xi'an Zhang, Xi-Feng Zhang, XiHe Zhang, Xia Zhang, Xian Zhang, Xian-Bo Zhang, Xian-Li Zhang, Xian-Man Zhang, Xiang Yang Zhang, Xiang Zhang, Xiangfei Zhang, Xianglian Zhang, Xiangsong Zhang, Xiangwu Zhang, Xiangyang Zhang, Xiangyu Zhang, Xiangzheng Zhang, Xianhong Zhang, Xianhua Zhang, Xianjing Zhang, Xianpeng Zhang, Xianxian Zhang, Xiao Bin Zhang, Xiao Min Zhang, Xiao Yu Cindy Zhang, Xiao Zhang, Xiao-Chang Zhang, Xiao-Cheng Zhang, Xiao-Chong Zhang, Xiao-Feng Zhang, Xiao-Hong Zhang, Xiao-Hua Zhang, Xiao-Jun Zhang, Xiao-Lei Zhang, Xiao-Lin Zhang, Xiao-Ling Zhang, Xiao-Meng Zhang, Xiao-Ming Zhang, Xiao-Qi Zhang, Xiao-Qian Zhang, Xiao-Shuo Zhang, Xiao-Wei Zhang, Xiao-Xuan Zhang, Xiao-Yong Zhang, Xiao-Yu Zhang, Xiao-bo Zhang, Xiao-yan Zhang, XiaoLin Zhang, XiaoPing Zhang, XiaoYi Zhang, Xiaobao Zhang, Xiaobiao Zhang, Xiaobo Zhang, Xiaochang Zhang, Xiaochen Zhang, Xiaochun Zhang, Xiaocong Zhang, Xiaocui Zhang, Xiaodan Zhang, Xiaodong Zhang, Xiaofan Zhang, Xiaofang Zhang, Xiaofei Zhang, Xiaofeng Zhang, Xiaogang Zhang, Xiaohan Zhang, Xiaohong Zhang, Xiaohui Zhang, Xiaojia Zhang, Xiaojian Zhang, Xiaojie Zhang, Xiaojin Zhang, Xiaojing Zhang, Xiaojun Zhang, Xiaokui Zhang, Xiaolan Zhang, Xiaolei Zhang, Xiaoli Zhang, Xiaoling Zhang, Xiaolong Zhang, Xiaomei Zhang, Xiaomeng Zhang, Xiaomin Zhang, Xiaoming Zhang, Xiaoning Zhang, Xiaonyun Zhang, Xiaopei Zhang, Xiaopo Zhang, Xiaoqi Zhang, Xiaoqing Zhang, Xiaorong Zhang, Xiaosheng Zhang, Xiaotian Michelle Zhang, Xiaotian Zhang, Xiaotong Zhang, Xiaotun Zhang, Xiaowan Zhang, Xiaowei Zhang, Xiaoxi Zhang, Xiaoxia Zhang, Xiaoxian Zhang, Xiaoxiao Zhang, Xiaoxin Zhang, Xiaoxue Zhang, Xiaoyan Zhang, Xiaoying Zhang, Xiaoyu Zhang, Xiaoyuan Zhang, Xiaoyue Zhang, Xiaoyun Zhang, Xiaozhe Zhang, Xiayin Zhang, Xibo Zhang, Xieyi Zhang, Xijiang Zhang, Xilin Zhang, Xiling Zhang, Ximei Zhang, Xin Zhang, Xin-Hui Zhang, Xin-Xin Zhang, Xin-Yan Zhang, Xin-Ye Zhang, Xin-Yuan Zhang, Xinan Zhang, Xinbao Zhang, Xinbo Zhang, Xincheng Zhang, Xindang Zhang, Xindong Zhang, Xinfeng Zhang, Xinfu Zhang, Xing Yu Zhang, Xing Zhang, Xingan Zhang, Xingang Zhang, Xingcai Zhang, Xingen Zhang, Xinglai Zhang, Xingong Zhang, Xingwei Zhang, Xingxing Zhang, Xingxu Zhang, Xingyi Zhang, Xingyu Zhang, Xingyuan Zhang, Xinhai Zhang, Xinhan Zhang, Xinhe Zhang, Xinheng Zhang, Xinhong Zhang, Xinhua Zhang, Xinjiang Zhang, Xinjing Zhang, Xinjun Zhang, Xinke Zhang, Xinlei Zhang, Xinlian Zhang, Xinlin Zhang, Xinling Zhang, Xinlong Zhang, Xinlu Zhang, Xinmin Zhang, Xinping Zhang, Xinqiao Zhang, Xinquan Zhang, Xinran Zhang, Xinrui Zhang, Xinruo Zhang, Xintao Zhang, Xinwei Zhang, Xinwu Zhang, Xinxin Zhang, Xinyao Zhang, Xinye Zhang, Xinyi Zhang, Xinyu Zhang, Xinyue Zhang, Xiong Zhang, Xiongjun Zhang, Xiongze Zhang, Xipeng Zhang, Xiping Zhang, Xiu Qi Zhang, Xiu-Juan Zhang, Xiu-Li Zhang, Xiu-Peng Zhang, Xiujie Zhang, Xiujun Zhang, Xiulan Zhang, Xiuming Zhang, Xiupeng Zhang, Xiuping Zhang, Xiuqin Zhang, Xiuqing Zhang, Xiuse Zhang, Xiushan Zhang, Xiuwen Zhang, Xiuxing Zhang, Xiuxiu Zhang, Xiuyin Zhang, Xiuyue Zhang, Xiuyun Zhang, Xiuzhen Zhang, Xixi Zhang, Xixun Zhang, Xiyu Zhang, Xu Dong Zhang, Xu Zhang, Xu-Chao Zhang, Xu-Jun Zhang, Xu-Mei Zhang, Xuan Zhang, Xudan Zhang, Xudong Zhang, Xue Zhang, Xue-Ping Zhang, Xue-Qin Zhang, Xue-Qing Zhang, XueWu Zhang, Xuebao Zhang, Xuebin Zhang, Xuefei Zhang, Xueguang Zhang, Xuehai Zhang, Xuehong Zhang, Xuehui Zhang, Xuejiao Zhang, Xuejun C Zhang, Xueli Zhang, Xuelian Zhang, Xuelong Zhang, Xueluo Zhang, Xuemei Zhang, Xuemin Zhang, Xueming Zhang, Xuening Zhang, Xueping Zhang, Xueqia Zhang, Xueqian Zhang, Xueqin Zhang, Xueting Zhang, Xuewei Zhang, Xuewen Zhang, Xuexi Zhang, Xueya Zhang, Xueyan Zhang, Xueyi Zhang, Xueying Zhang, Xuezhi Zhang, Xufang Zhang, Xuhao Zhang, Xujun Zhang, Xunming Zhang, Xuting Zhang, Xutong Zhang, Xuxiang Zhang, Y H Zhang, Y L Zhang, Y Y Zhang, Y Zhang, Y-H Zhang, Ya Zhang, Ya-Juan Zhang, Ya-Li Zhang, Ya-Long Zhang, Ya-Meng Zhang, Yachen Zhang, Yadi Zhang, Yadong Zhang, Yafang Zhang, Yafei Zhang, Yafeng Zhang, Yaguang Zhang, Yahua Zhang, Yajie Zhang, Yajing Zhang, Yajun Zhang, Yakun Zhang, Yalan Zhang, Yali Zhang, Yaling Zhang, Yameng Zhang, Yamin Zhang, Yaming Zhang, Yan Zhang, Yan-Chun Zhang, Yan-Ling Zhang, Yan-Min Zhang, Yan-Qing Zhang, Yanan Zhang, Yanbin Zhang, Yanbing Zhang, Yanchao Zhang, Yandong Zhang, Yanfei Zhang, Yanfen Zhang, Yanfeng Zhang, Yang Zhang, Yang-Yang Zhang, Yangfan Zhang, Yanghui Zhang, Yangqianwen Zhang, Yangyang Zhang, Yangyu Zhang, Yanhong Zhang, Yanhua Zhang, Yani Zhang, Yanjiao Zhang, Yanju Zhang, Yanjun Zhang, Yanli Zhang, Yanlin Zhang, Yanling Zhang, Yanman Zhang, Yanmin Zhang, Yanming Zhang, Yanna Zhang, Yannan Zhang, Yanping Zhang, Yanqiao Zhang, Yanquan Zhang, Yanru Zhang, Yanting Zhang, Yanxia Zhang, Yanxiang Zhang, Yanyan Zhang, Yanyi Zhang, Yanyu Zhang, Yao Zhang, Yao-Hua Zhang, Yaodong Zhang, Yaoxin Zhang, Yaoyang Zhang, Yaoyao Zhang, Yaozhengtai Zhang, Yaping Zhang, Yaqi Zhang, Yaru Zhang, Yashuo Zhang, Yating Zhang, Yawei Zhang, Yaxin Zhang, Yaxuan Zhang, Yayong Zhang, Yazhuo Zhang, Ye Zhang, Yefan Zhang, Yeqian Zhang, Yerui Zhang, Yeting Zhang, Yexiang Zhang, Yi J Zhang, Yi Ping Zhang, Yi Zhang, Yi-Chi Zhang, Yi-Feng Zhang, Yi-Ge Zhang, Yi-Hang Zhang, Yi-Hua Zhang, Yi-Min Zhang, Yi-Ming Zhang, Yi-Qi Zhang, Yi-Wei Zhang, Yi-Wen Zhang, Yi-Xuan Zhang, Yi-Yue Zhang, Yi-yi Zhang, YiJie Zhang, YiPei Zhang, Yibin Zhang, Yibo Zhang, Yichen Zhang, Yichi Zhang, Yidan Zhang, Yidong Zhang, Yifan Zhang, Yifang Zhang, Yige Zhang, Yiguo Zhang, Yihan Zhang, Yihang Zhang, Yihao Zhang, Yiheng Zhang, Yihong Zhang, Yihui Zhang, Yijing Zhang, Yikai Zhang, Yikun Zhang, Yili Zhang, Yiliang Zhang, Yilin Zhang, Yimei Zhang, Yimeng Zhang, Yimin Zhang, Yiming Zhang, Yin Jiang Zhang, Yin Zhang, Yin-Hong Zhang, Yina Zhang, Yinci Zhang, Ying E Zhang, Ying Zhang, Ying-Jun Zhang, Ying-Lin Zhang, Ying-Qian Zhang, Yingang Zhang, Yingchao Zhang, Yinghui Zhang, Yingjie Zhang, Yingli Zhang, Yingmei Zhang, Yingna Zhang, Yingnan Zhang, Yingqi Zhang, Yingqian Zhang, Yingyi Zhang, Yingying Zhang, Yingze Zhang, Yingzi Zhang, Yinhao Zhang, Yinjiang Zhang, Yintang Zhang, Yinzhi Zhang, Yinzhuang Zhang, Yipeng Zhang, Yiping Zhang, Yiqian Zhang, Yiqing Zhang, Yiren Zhang, Yirong Zhang, Yitian Zhang, Yiting Zhang, Yiwan Zhang, Yiwei Zhang, Yiwen Zhang, Yixia Zhang, Yixin Zhang, Yiyao Zhang, Yiyi Zhang, Yiyuan Zhang, Yizhe Zhang, Yizhi Zhang, Yong Zhang, Yong-Guo Zhang, Yong-Liang Zhang, Yong-hong Zhang, Yongbao Zhang, Yongchang Zhang, Yongchao Zhang, Yongci Zhang, Yongfa Zhang, Yongfang Zhang, Yongfeng Zhang, Yonggang Zhang, Yonggen Zhang, Yongguang Zhang, Yongguo Zhang, Yongheng Zhang, Yonghong Zhang, Yonghui Zhang, Yongjie Zhang, Yongjiu Zhang, Yongjuan Zhang, Yonglian Zhang, Yongliang Zhang, Yonglong Zhang, Yongpeng Zhang, Yongping Zhang, Yongqiang Zhang, Yongsheng Zhang, Yongwei Zhang, Yongxiang Zhang, Yongxing Zhang, Yongyan Zhang, Yongyun Zhang, You-Zhi Zhang, Youjin Zhang, Youmin Zhang, Youti Zhang, Youwen Zhang, Youyi Zhang, Youying Zhang, Youzhong Zhang, Yu Chen Zhang, Yu Zhang, Yu-Bo Zhang, Yu-Chi Zhang, Yu-Fei Zhang, Yu-Hui Zhang, Yu-Jie Zhang, Yu-Jing Zhang, Yu-Qi Zhang, Yu-Qiu Zhang, Yu-Yu Zhang, Yu-Zhe Zhang, YuHang Zhang, YuHong Zhang, Yuan Zhang, Yuan-Wei Zhang, Yuan-Yuan Zhang, Yuanchao Zhang, Yuanhao Zhang, Yuanhui Zhang, Yuanping Zhang, Yuanqiang Zhang, Yuanqing Zhang, Yuansheng Zhang, Yuanxi Zhang, Yuanxiang Zhang, Yuanyi Zhang, Yuanyuan Zhang, Yuanzhen Zhang, Yuanzhuang Zhang, Yubin Zhang, Yucai Zhang, Yuchao Zhang, Yuchen Zhang, Yuchi Zhang, Yue Zhang, Yue-Bo Zhang, Yue-Ming Zhang, Yuebin Zhang, Yuebo Zhang, Yuehong Zhang, Yuehua Zhang, Yuejuan Zhang, Yuemei Zhang, Yueqi Zhang, Yueru Zhang, Yuetong Zhang, Yufang Zhang, Yufeng Zhang, Yuhan Zhang, Yuhao Zhang, Yuheng Zhang, Yuhua Zhang, Yuhui Zhang, Yujia Zhang, Yujiao Zhang, Yujie Zhang, Yujin Zhang, Yujing Zhang, Yujuan Zhang, Yuke Zhang, Yukun Zhang, Yulin Zhang, Yuling Zhang, Yulong Zhang, Yumei Zhang, Yumeng Zhang, Yumin Zhang, Yun Zhang, Yun-Feng Zhang, Yun-Lin Zhang, Yun-Mei Zhang, Yun-Sheng Zhang, Yun-Xiang Zhang, Yunfan Zhang, Yunfei Zhang, Yunfeng Zhang, Yunhai Zhang, Yunhang Zhang, Yunhe Zhang, Yunhui Zhang, Yuning Zhang, Yunjia Zhang, Yunli Zhang, Yunmei Zhang, Yunpeng Zhang, Yunqi Zhang, Yunqiang Zhang, Yunqing Zhang, Yunsheng Zhang, Yunxia Zhang, Yupei Zhang, Yupeng Zhang, Yuping Zhang, Yuqi Zhang, Yuqing Zhang, Yurou Zhang, Yuru Zhang, Yusen Zhang, Yushan Zhang, Yutian Zhang, Yuting Zhang, Yutong Zhang, Yuwei Zhang, Yuxi Zhang, Yuxia Zhang, Yuxin Zhang, Yuxuan Zhang, Yuyan Zhang, Yuyanan Zhang, Yuyang Zhang, Yuying Zhang, Yuyu Zhang, Yuyuan Zhang, Yuzhe Zhang, Yuzhi Zhang, Yuzhou Zhang, Yuzhu Zhang, Yvonne Zhang, Z Zhang, Z-K Zhang, Zai-Rong Zhang, Zaifeng Zhang, Zaijun Zhang, Zaiqi Zhang, Zebang Zhang, Zekun Zhang, Zemin Zhang, Zeming Zhang, Zeng Zhang, Zengdi Zhang, Zengfu Zhang, Zenglei Zhang, Zengli Zhang, Zengqiang Zhang, Zengrong Zhang, Zengtie Zhang, Zepeng Zhang, Zewei Zhang, Zewen Zhang, Zeyan Zhang, Zeyuan Zhang, Zhan-Xiong Zhang, Zhangjin Zhang, Zhanhao Zhang, Zhanjie Zhang, Zhanjun Zhang, Zhanming Zhang, Zhanyi Zhang, Zhao Zhang, Zhao-Huan Zhang, Zhao-Ming Zhang, Zhaobo Zhang, Zhaocong Zhang, Zhaofeng Zhang, Zhaohua Zhang, Zhaohuai Zhang, Zhaohuan Zhang, Zhaohui Zhang, Zhaomin Zhang, Zhaoping Zhang, Zhaoqi Zhang, Zhaotian Zhang, Zhaoxue Zhang, Zhe Zhang, Zhehua Zhang, Zhemei Zhang, Zhen Zhang, Zhen-Dong Zhang, Zhen-Jie Zhang, Zhen-Shan Zhang, Zhen-Tao Zhang, Zhen-lin Zhang, Zhenfeng Zhang, Zheng Zhang, Zhengbin Zhang, Zhengfen Zhang, Zhenglang Zhang, Zhengliang Zhang, Zhengxiang Zhang, Zhengxing Zhang, Zhengyu Zhang, Zhengyun Zhang, Zhenhao Zhang, Zhenhua Zhang, Zhenlin Zhang, Zhenqiang Zhang, Zhentao Zhang, Zhenyang Zhang, Zhenyu Zhang, Zhenzhen Zhang, Zhenzhu Zhang, Zhewei Zhang, Zhewen Zhang, Zheyuan Zhang, Zhezhe Zhang, Zhi Zhang, Zhi-Chang Zhang, Zhi-Jie Zhang, Zhi-Jun Zhang, Zhi-Peng Zhang, Zhi-Qing Zhang, Zhi-Shuai Zhang, Zhi-Shuo Zhang, Zhi-Xin Zhang, Zhibo Zhang, Zhicheng Zhang, Zhicong Zhang, Zhifei Zhang, Zhigang Zhang, Zhiguo Zhang, Zhihan Zhang, Zhihao Zhang, Zhihong Zhang, Zhihua Zhang, Zhihui Zhang, Zhijian Zhang, Zhijiao Zhang, Zhijing Zhang, Zhijun Zhang, Zhikun Zhang, Zhimin Zhang, Zhiming Zhang, Zhiping Zhang, Zhiqian Zhang, Zhiqiang Zhang, Zhiqiao Zhang, Zhiru Zhang, Zhishang Zhang, Zhishuai Zhang, Zhiwang Zhang, Zhiwen Zhang, Zhixia Zhang, Zhixin Zhang, Zhiyan Zhang, Zhiyao Zhang, Zhiye Zhang, Zhiyi Zhang, Zhiyong Zhang, Zhiyu Zhang, Zhiyuan Zhang, Zhiyun Zhang, Zhizhong Zhang, Zhong Zhang, Zhong-Bai Zhang, Zhong-Yi Zhang, Zhong-Yin Zhang, Zhong-Yuan Zhang, Zhongheng Zhang, Zhongjie Zhang, Zhonglin Zhang, Zhongqi Zhang, Zhongwei Zhang, Zhongxin Zhang, Zhongxu Zhang, Zhongyang Zhang, Zhongyi Zhang, Zhou Zhang, Zhu Zhang, Zhu-Qin Zhang, Zhuang Zhang, Zhuo Zhang, Zhuo-Ya Zhang, Zhuohua Zhang, Zhuojun Zhang, Zhuorong Zhang, Zhuoya Zhang, Zhuqin Zhang, Zhuqing Zhang, Zhuzhen Zhang, Zi-Feng Zhang, Zi-Jian Zhang, Zian Zhang, Zicheng Zhang, Ziding Zhang, Ziguo Zhang, Zihan Zhang, Ziheng Zhang, Zijian Zhang, Zijiao Zhang, Zijing Zhang, Zikai Zhang, Zilong Zhang, Zilu Zhang, Ziping Zhang, Ziqi Zhang, Zishuo Zhang, Zixiong Zhang, Zixu Zhang, Zixuan Zhang, Ziyang Zhang, Ziyi Zhang, Ziyin Zhang, Ziyu Zhang, Ziyue Zhang, Zizhen Zhang, Zongping Zhang, Zongquan Zhang, Zongwang Zhang, Zongxiang Zhang, Zu-Xuan Zhang, Zufa Zhang, Zuoyi Zhang
articles

Low shear stress promotes atherosclerosis by inducing endothelial ferroptosis via the P53/xCT pathway.

Jia-Wei Hu, Ya-Peng Chen, Ai-Qun Chen +8 more · 2026 · Experimental cell research · Elsevier · added 2026-04-24
Atherosclerotic lesions commonly develop in curved or bifurcated arteries, where blood flow exhibits characteristics of low shear stress (LSS). Subjected to LSS continually, endothelial cells (ECs) ad Show more
Atherosclerotic lesions commonly develop in curved or bifurcated arteries, where blood flow exhibits characteristics of low shear stress (LSS). Subjected to LSS continually, endothelial cells (ECs) adopt a pro-atherosclerotic phenotype. Ferroptosis is a recently identified form of controlled cell demise prompted by iron-dependent buildup of cellular reactive oxygen species (ROS), which has been associated with diverse cardiovascular diseases, particularly atherosclerosis (AS). P53 is a broadly acting tumor suppressor that can be activated by diverse stimuli and mediates multiple biological outcomes, including cell cycle arrest, DNA repair, apoptosis, and ferroptosis. However, it remains unknown whether LSS promotes the development of AS by inducing P53-dependent ferroptosis in endothelial cells. In our experiments, we induced LSS by partial ligation of the right common carotid artery in high-fat diet-fed (HFD) male ApoE Our findings demonstrated that LSS induced endothelial ferroptosis, which in turn accelerated AS development both in vivo and in vitro. This effect was partially counteracted by both the ferroptosis inhibitor Fer-1 and endothelium-specific glutathione peroxidase 4 (GPX4) overexpression in ApoE Our experiments suggested that LSS promotes atherosclerosis by inducing endothelial ferroptosis through the P53/xCT signaling pathway. Show less
no PDF DOI: 10.1016/j.yexcr.2026.114901
APOE

Panax ginseng-Polygonum cuspidatum is beneficial for alleviating atherosclerosis in ApoE-/- mice by modulating the composition of gut microbiota and related metabolites.

Ya Wang, Jinyi Fu, Jingyi Zhan +7 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Atherosclerosis (AS) is a central pathological driver underlying most cardiovascular diseases. Gut microbiota and related metabolites participate in regulating atherosclerosis. Fifty C57BL/6J ApoE Ath Show more
Atherosclerosis (AS) is a central pathological driver underlying most cardiovascular diseases. Gut microbiota and related metabolites participate in regulating atherosclerosis. Fifty C57BL/6J ApoE Atherosclerotic plaques accumulated in the aorta and aortic sinus after HFD, while statin and high-dose GP alleviated this burden. TC, TG, LDL-C, MCP-1, MCP-3 and IL-2 showed significant increase after HFD, while statin and GP decreased LDL-C, MCP-1 and MCP-3. The goblet cells, ZO-1 and Occludin decreased after HFD, while statin and GP increased them, indicating that the intestinal barrier integrity was improved. Additionally, the composition of gut microbiota was modulated by GP. Some candidate taxa were identified, such as This study suggests that GP is beneficial for alleviating atherosclerosis in HFD-induced ApoE Show less
📄 PDF DOI: 10.3389/fcvm.2026.1773819
APOE

Novel Protective Role for Gut Microbiota-derived Metabolite PAGln in Doxorubicin-induced Cardiotoxicity.

Jie Huang, Xingyuan Hou, Ni Zhou +7 more · 2026 · Cardiovascular drugs and therapy · Springer · added 2026-04-24
Doxorubicin (Dox) is a classic anthracycline chemotherapy drug with cause cumulative and dose-dependent cardiotoxicity. This study aimed to investigate the potential role and molecular mechanism of ph Show more
Doxorubicin (Dox) is a classic anthracycline chemotherapy drug with cause cumulative and dose-dependent cardiotoxicity. This study aimed to investigate the potential role and molecular mechanism of phenylacetylglutamine (PAGln), a novel gut microbiota metabolite, in Dox-induced cardiotoxicity (DIC). DIC models were established in vivo and in vitro, and a series of experiments were performed to verify the cardioprotective effect of PAGln. RNA sequencing (RNA-seq) was employed to explore the mechanism of PAGln in DIC. Subsequently, the differentially expressed genes (DEGs) were subjected to comprehensive analysis using diverse public databases, and RT-PCR was used to confirm the expression levels of the candidate genes. Finally, molecular docking techniques were used for validation. PAGln effectively prevented both in vivo and in vitro Dox-induced myocardial injury and cell apoptosis. RNA-seq results showed that 40 genes were up-regulated and 54 down-regulated in the Dox group compared to the Con group, displaying opposite changes in the Dox + PAGln group. Enrichment analysis highlighted several mechanisms by which PAGln alleviated Dox-induced cardiotoxicity, including the lipid metabolic process, calcium-mediated signaling, positive regulation of store-operated calcium channel activity, and hypertrophic cardiomyopathy. In vitro and in vivo experiments confirmed that PAGln treatment could reverse the changes in the expression levels of Klb, Ece2, Nmnat2, Casq1, Pak1, and Apob in Dox. Molecular docking results showed that these genes had good binding activity with PAGln. PAGln shows potential in alleviating Dox-induced cardiotoxicity, with Ece2 identified as key regulatory molecules related to endothelial dysfunction. Show less
📄 PDF DOI: 10.1007/s10557-024-07665-y
APOB

Human umbilical cord mesenchymal stem cells therapy for Alzheimer's disease: a systematic review and meta-analysis of mouse models.

Chunyan Si, Liang Ma, Wei Ding +5 more · 2026 · Frontiers in neurology · Frontiers · added 2026-04-24
Given the limitations of current treatments for Alzheimer's disease (AD), this study aims to comprehensively evaluate the therapeutic efficacy of human umbilical cord mesenchymal stem cells (hUCMSCs) Show more
Given the limitations of current treatments for Alzheimer's disease (AD), this study aims to comprehensively evaluate the therapeutic efficacy of human umbilical cord mesenchymal stem cells (hUCMSCs) in AD mouse models through a systematic review and meta-analysis. Additionally, we explore the impact of transplantation dose and route on treatment outcomes to identify the optimal window for clinical application. In accordance with the PRISMA guidelines, we systematically searched four major databases to identify randomized controlled trials involving hUCMSCs in AD mouse models. We used the standardized mean difference (SMD) to synthesize effect sizes and performed subgroup analyses based on pre-defined transplantation routes and doses. A total of 13 studies were included in the analysis. The meta-analysis revealed that hUCMSCs transplantation significantly improved spatial learning and memory in AD model mice, with a marked reduction in escape latency (SMD = -2.55; 95% CI: -3.34 to -1.75; Human umbilical cord mesenchymal stem cells can improve behavioral and pathological outcomes in AD mouse models via multiple mechanisms of action. The intravenous route using medium to high doses emerges as a critical factor for achieving optimal effects, providing important evidence and informing future experimental design and clinical translational research. Show less
📄 PDF DOI: 10.3389/fneur.2026.1783757
BDNF

Latent profiles and network analysis of adolescent depression and cognitive impairment.

Xintong Ma, Wei Li, Yuanyuan Liu +8 more · 2026 · BMC psychiatry · BioMed Central · added 2026-04-24
Adolescence is a critical period for rapid emotional and cognitive development. Depression and cognitive impairment frequently co-occur in this population, yet their comorbidity patterns and symptom-l Show more
Adolescence is a critical period for rapid emotional and cognitive development. Depression and cognitive impairment frequently co-occur in this population, yet their comorbidity patterns and symptom-level interactions remain insufficiently explored. A total of 2,244 students (mean age = 16.8 ± 0.84 years; 1,218 males, 1,026 females) from a high school in Heilongjiang Province, China, were recruited. Depressive symptoms and cognitive impairment were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D) and the Perceived Deficits Questionnaire–Depression (PDQ-D). Latent profile analysis (LPA) was applied to identify subgroups, followed by network analysis to examine central symptoms (expected influence, EI), bridge symptoms (bridge expected influence, BEI), and network differences (NCT). The optimal LPA model identified three comorbidity subgroups: low, moderate, and high. NCT revealed significant differences in network structure and global strength between the low–moderate (S = 1.514, Adolescent Depression and Cognitive Impairment can be classified into low, moderate, and high comorbidity subgroups. Somatic symptoms emerged as the central symptom, while prospective memory impairment and interpersonal problems were identified as key bridge symptoms, suggesting potential intervention targets for early screening and stratified treatment. Not applicable. The online version contains supplementary material available at 10.1186/s12888-026-07946-w. Show less
📄 PDF DOI: 10.1186/s12888-026-07946-w
LPA

Association between vaginal microbiota in early pregnancy and gestational diabetes mellitus: a nested case-control study.

Xiang Hong, Mengjie Zhao, Furong Tan +5 more · 2026 · BMC microbiology · BioMed Central · added 2026-04-24
To investigate the association between vaginal microbiota structure in early pregnancy and gestational diabetes mellitus (GDM) and to characterize microbial signatures for early screening for GDM. The Show more
To investigate the association between vaginal microbiota structure in early pregnancy and gestational diabetes mellitus (GDM) and to characterize microbial signatures for early screening for GDM. The present study was a nested case-control study recruiting pregnant women from the Nanjing Gulou Maternal-Child Health Center, China. Vaginal swabs were collected before 20 weeks of gestation for 16S rRNA sequencing. Following 1:3 propensity score matching, 45 GDM cases and 135 controls were enrolled. The final analysis included 42 GDM cases and 121 controls. A random forest model was used to explore the genera of vaginal differential microbiota associated with GDM. Based on these findings, latent profile analysis (LPA) was conducted to explore potential types of vaginal microbiota, and logistic regression was used to analyze the association between vaginal microbiota types and GDM. The GDM group exhibited elevated alpha diversity (Chao1 index, The composition and structure of vaginal microbiota in early pregnancy are different in the two groups. The vaginal microbiota in early pregnancy, which is characterized by co-dominated by The online version contains supplementary material available at 10.1186/s12866-026-04910-2. Show less
📄 PDF DOI: 10.1186/s12866-026-04910-2
LPA

Cathelicidin LL-37-ApoB-100 interaction promotes LDL clearance and attenuates cholesterol accumulation in the liver.

Yaqun Fang, Zhiye Zhang, Qiqi Cao +10 more · 2026 · Science China. Life sciences · Springer · added 2026-04-24
Dysregulation of low-density lipoprotein (LDL) cholesterol is strongly correlated with the risk of metabolic dysfunction-associated steatotic liver disease. Endogenous molecules targeting LDL clearanc Show more
Dysregulation of low-density lipoprotein (LDL) cholesterol is strongly correlated with the risk of metabolic dysfunction-associated steatotic liver disease. Endogenous molecules targeting LDL clearance play crucial roles in the progression of liver steatosis. Human cathelicidin LL-37 can form complexes with lipoproteins, but whether these complexes regulate lipoprotein-driven cholesterol metabolism is not clear. Here, we find that cathelicidin LL-37 binds to LDL via apolipoprotein (Apo)B-100 domains, enhancing the solubility of ApoB-100 and inhibiting the modifications and aggregation of LDL. LL-37-LDL interaction promotes LDL uptake through LDL receptor (LDLR) both in hepatocytes and macrophages. This interaction also promotes LDL cholesterol clearance by facilitating cholesterol excretion and cholesterol efflux. In Apoe Show less
📄 PDF DOI: 10.1007/s11427-025-3006-2
APOB

Advances in Understanding Neuron-Microglia Interactions During Sciatic Nerve Injury and Regeneration.

Wei Zhang, Mei Liu, Ronghua Wu · 2026 · Current neuropharmacology · Bentham Science · added 2026-04-24
The repair mechanisms following sciatic nerve injury involve complex signaling interactions between neurons and microglia. Recent studies have demonstrated that neurons activate microglia by releasing Show more
The repair mechanisms following sciatic nerve injury involve complex signaling interactions between neurons and microglia. Recent studies have demonstrated that neurons activate microglia by releasing chemokines, glutamate, and neurotrophic factors. In turn, microglia regulate neuronal survival and regeneration via phagocytosis, phenotypic switching, and secretion of growth factors. However, the spatiotemporal diversity of signaling pathways, metabolic regulation of the microenvironment, and barriers to clinical application remain inadequately addressed. This review provides a comprehensive analysis of morphological and functional changes in neuronal cell bodies and of the activation and regulatory mechanisms of microglia after sciatic nerve injury. It highlights the dynamic interaction network encompassing the ATP-P2X7 signaling pathway, the CX3CL1- CX3CR1 pathway, the CCL2-CCR2 chemokine axis, the BDNF-TrkB pathway, and inflammatory mediators, offering novel insights into precision therapeutic strategies targeting neuron-glial interactions. Show less
no PDF DOI: 10.2174/011570159X435745251229091943
BDNF metabolic regulation microenvironment neuron-microglia interactions neurotrophic factors regeneration sciatic nerve injury signaling pathways

Dementia risk prediction in individuals with prediabetes or diabetes: A novel multi-protein score with biological pathway analysis.

Yuanyuan Zhang, Yu Huang, Junyu Xue +8 more · 2026 · General psychiatry · Wiley · added 2026-04-24
Individuals with prediabetes or diabetes face elevated dementia risk, yet robust prediction tools and mechanistic insights remain limited. This study aimed to develop and validate a protein-based risk Show more
Individuals with prediabetes or diabetes face elevated dementia risk, yet robust prediction tools and mechanistic insights remain limited. This study aimed to develop and validate a protein-based risk score for dementia prediction in this high-risk population while elucidating underlying biological pathways and therapeutic targets. Utilising data from 10 433 UK Biobank participants with prediabetes or diabetes and proteomic profiling (2911 plasma proteins measured), we developed a dementia protein risk score in a training set ( In the training set, 23 out of 2911 proteins were selected. In the testing set, compared with the basic model (age and sex, C-index: 0.78; 95% confidence interval [CI] 0.74-0.82), the dementia protein risk score (C-index: 0.84; 95% CI 0.81-0.88) significantly improved the performance in predicting incident dementia (C-index increase: 0.06; 95% CI 0.02-0.12), while cardiovascular risk factors, ageing and dementia incidence risk factors (C-index: 0.80; 95% CI 0.76-0.83) and apolipoprotein E (APOE; age and sex included, C-index: 0.81; 95% CI 0.77-0.85) had no significant improvement. Six key proteins (glial fibrillary acidic protein [GFAP], neurofilament light polypeptide [NEFL], Brevican core protein [BCAN], protein MENT [MENT], APOE and growth/differentiation factor 15 [GDF15]) captured the most predictive power. Pathway analyses implicated extracellular matrix remodelling and cholesterol metabolism, whereas Mendelian randomisation identified causal roles for APOE, haematopoietic prostaglandin D synthase (HPGDS), BAG family molecular chaperone regulator 3 (BAG3) and GDF15. Nine proteins were prioritised as druggable targets, including HPGDS, with existing Food and Drug Administration-approved drugs. This study establishes a highly accurate protein-based risk score for dementia prediction (including 6-23 proteins) in individuals with prediabetes or diabetes, uncovering actionable biological pathways and therapeutic targets. The findings enable precision risk stratification and accelerate translational opportunities for dementia prevention in this population. Show less
📄 PDF DOI: 10.1002/gps3.70010
APOE

Covalent Bond Locking in Semiconducting Oligomers Boosts Ultrabright NIR-II Luminescence for Deep Brain Theranostics.

Xiliang Li, Haohong Gan, Chi Zhang +14 more · 2026 · Angewandte Chemie (International ed. in English) · Wiley · added 2026-04-24
Near-infrared (NIR)-II fluorescence imaging at 1000-1700 nm is widely used for deep-tissue visualisation and disease theranostics in the brain, with NIR-II theranostics greatly improving imaging resol Show more
Near-infrared (NIR)-II fluorescence imaging at 1000-1700 nm is widely used for deep-tissue visualisation and disease theranostics in the brain, with NIR-II theranostics greatly improving imaging resolution, imaging depth, and therapeutic efficacy. However, the extreme lack of molecular design in NIR-II fluorophores has slowed the discovery of bright candidates and restricted their efficacious application in brain theranostics. Here, we develop a covalent bond locking (CBL) strategy that enables the feasible design of bright NIR-II fluorophores by effectively restricting the twisted intramolecular charge transfer state. These spirofluorophores incorporate terminally spiro-donor groups, which leads to a higher molar extinction coefficient and improved quantum yield than non-spirofluorophores do. With bright and stable NIR-II fluorescence advantages, we demonstrate that CBL nanoparticles (NPs) of spirofluorophores achieve multiscale high-resolution NIR-II angiography via one-photon fluorescence and two-photon fluorescence bioimaging simultaneously. With apolipoprotein E (ApoE) modification, CBL@ApoE NPs achieve enhanced blood-brain barrier permeability, facilitating superior brain glioma theranostics. This work proposes a CBL strategy to engineer highly bright NIR-II fluorescent fluorophores, providing a reliable nanoplatform for deep brain theranostics that can be effectively delivered across biological barriers to target brain tumors. Show less
no PDF DOI: 10.1002/anie.7337664
APOE

The association between APOE 𝜀4 carrierships and the detection of amyloid positivity using an Alzheimer's disease proteomic blood test in asymptomatic Down syndrome.

Lubnaa Badriyyah Abdullah, Fan Zhang, Melissa Petersen +24 more · 2026 · Alzheimer's & dementia : the journal of the Alzheimer's Association · Wiley · added 2026-04-24
This study evaluates plasma-based proteomic profiles for predicting amyloid positivity in adults with Down syndrome (DS) and examines the impact of apolipoprotein E ε4 (APOE ε4) on test performance. C Show more
This study evaluates plasma-based proteomic profiles for predicting amyloid positivity in adults with Down syndrome (DS) and examines the impact of apolipoprotein E ε4 (APOE ε4) on test performance. Cross-sectional data from 290 adults with DS were analyzed using single molecule array (SIMOA) technology to measure plasma amyloid beta (Aβ)42, Aβ40, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), tau phosphorylated at threonine 181, and total tau. Amyloid burden was quantified using Pittsburgh Compound B and (18)F-florbetapir Aβ positron emission tomography. Support vector machine analyses were conducted with biomarkers as predictors and age, sex, and APOE ε4 carrier status as covariates. Age, GFAP, and NfL contributed the most to the model performance. The proteomic profile achieved an area under the curve (AUC) of 96% in models with and without APOE ε4. These findings suggest that plasma proteomic biomarkers can effectively identify amyloid positivity in adults with DS and may support clinical triage, monitoring, and selection for clinical trials, independent of APOE ε4 status. Show less
📄 PDF DOI: 10.1002/alz.71338
APOE

Chicoric acid enhanced brain cholesterol efflux and reduced Aβ pathology via LXR-ABCA1 signaling in Alzheimer's models.

Daiyue Li, Yu Zhang, Ruonan Wang +6 more · 2026 · Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · Elsevier · added 2026-04-24
Alzheimer's disease (AD) is one of the most pressing public health challenges in an aging world. However, effective therapeutic strategies are still lacking. Imbalance in lipid homeostasis is a key dr Show more
Alzheimer's disease (AD) is one of the most pressing public health challenges in an aging world. However, effective therapeutic strategies are still lacking. Imbalance in lipid homeostasis is a key driver of AD. Given the established link between dysregulated lipid metabolism and amyloid-beta (Aβ) aggregation, we investigated whether chicoric acid (CA), a dietary polyphenol with reported lipid-modulating properties, could mitigate Aβ pathology by modulating lipid metabolism in 5xFAD transgenic mice. In the brain, we found that CA upregulated the expression of liver X receptor Beta (LXR-β) and ATP-binding cassette transporter A1 (ABCA1) in 5xFAD mice. Through this pathway, it promoted apolipoprotein E (ApoE) lipidation and enhanced the expression of Aβ-clearance proteins (IDE and LRP1). Notably, in the periphery, CA reshaped the gut microbiota in 5xFAD mice, which reduced serum neurotoxic bile acid levels and preserved the integrity of the peripheral Aβ clearance system. Together, our study first demonstrated that CA globally regulated lipid homeostasis to alleviate Aβ pathology by coordinating cerebral cholesterol efflux with peripheral bile acid metabolism. The findings facilitated exploring active compounds from traditional Chinese medicine that may reduce Aβ deposition by targeting lipid metabolism pathways. Show less
📄 PDF DOI: 10.1016/j.neurot.2026.e00899
APOE

Multi-stage transcriptomic analysis of mouse embryonic lethality induced by homozygous knockout of the

Ya-Xin Deng, Bao-Jun Ding, Hong-Chun Li +4 more · 2026 · Yi chuan = Hereditas · added 2026-04-24
The
no PDF DOI: 10.16288/j.yczz.25-190
APOA4

Dynamic evaluation of blood marker changes induced by acute binge drinking in healthy individuals: a randomized controlled trial.

Jiaomei Li, Kaixin Pan, Yuxuan Zhang +8 more · 2026 · Scientific reports · Nature · added 2026-04-24
Acute alcohol consumption is known to exert widespread physiological effects, yet the immediate impacts on metabolic biomarkers remain incompletely understood. The present randomized controlled trial Show more
Acute alcohol consumption is known to exert widespread physiological effects, yet the immediate impacts on metabolic biomarkers remain incompletely understood. The present randomized controlled trial was conducted to investigate the acute effects of a single episode of alcohol ingestion on various biomarkers in healthy individuals. A total of 45 male participants were recruited and randomized into an alcohol group (n = 40) and a control group (n = 5) at an 8:1 ratio. Volunteers in the alcohol group ingested 40% Absolut vodka within 15 min. Blood pressure, heart rate, and blood oxygen saturation were measured at 0 h, 1 h, 3 h, 5 h, 12 h, and 24 h. Venous blood samples were drawn at 0 h, 1 h, 5 h, 12 h, and 24 h after alcohol intake. Our results showed that levels of liver function markers, including α-fucosidase (AFU), albumin (ALB), and alkaline phosphatase (ALP), were significantly increased in the alcohol group compared to the control group. The 24-h area under curve (AUC) of AFU, ALB, and ALP were significantly higher in the alcohol group. The liver fibrosis maker collagen type Ⅳ (Ⅳ-C) tended to be higher at 1 h and 12 h in the alcohol group compared to the control group. Lipid levels, including triglycerides (TG), apolipoprotein A1 (APOA1), and the APOA1/APOB, were significantly elevated after alcohol ingestion, particularly at 5 h and 12 h. The 24 h-AUC of TG, APOA1, and APOA1/APOB were higher in the alcohol group than in the control group. Additionally, cardiac function indicators, including heart rate, systolic blood pressure (SBP), and diastolic blood pressure (DBP), were significantly elevated in the alcohol group. SBP and DBP remained higher 24 h after alcohol ingestion compared to the control group. This study demonstrated that even a single episode of binge drinking could induce significant alterations of biomarkers related to liver function, cardiac function, and lipid profiles. These findings provided valuable insights into the short-term impact of alcohol on health and highlighted the importance of further research to explore the long-term implications of repeated acute alcohol exposure. Given the very small control group, these results should be interpreted as preliminary and confirmed in larger, more balanced randomized trials. The online version contains supplementary material available at 10.1038/s41598-026-40028-1. Show less
📄 PDF DOI: 10.1038/s41598-026-40028-1
APOB

Interpretable machine-learning prediction of PSEN1 missense variant pathogenicity based on multi-omics enrichment in six core Alzheimer's disease genes.

Dehao Yang, Shiyue Wang, Yangguang Lu +8 more · 2026 · Alzheimer's research & therapy · BioMed Central · added 2026-04-24
The clinical interpretation of Alzheimer's disease (AD) is frequently complicated by the prevalence of missense variants designated as being of uncertain significance within associated genes. Conventi Show more
The clinical interpretation of Alzheimer's disease (AD) is frequently complicated by the prevalence of missense variants designated as being of uncertain significance within associated genes. Conventional computational prediction tools often overlook disease-specific pathophysiological contexts and lack pertinence and interpretability. Therefore, the present study aimed to develop a novel, interpretable framework for predicting the pathogenicity of AD missense variants by integrating transcriptomic and proteomic data enrichment patterns with machine learning methods. A cross-sectional variant-level analysis was performed using publicly available databases. Missense variants in APOE, APP, PSEN1, PSEN2, SORL1, and TREM2 reported in AD patients were retrieved from Alzforum and compared with missense variants from individuals without neurological diseases, as cataloged in the gnomAD v2.1.1 non-neuro subset. Variants were annotated with tissue-specific expression, secondary structure, relative solvent accessibility, and other functional features using tools like AlphaFold. Enrichment of specific features was assessed with Fisher's exact tests with Bonferroni correction for multiple comparisons. Given that PSEN1 showed the strongest enrichment signals, six machine-learning algorithms were trained on PSEN1 variants to distinguish AD-associated variants from gnomAD variants, using a 10 × 5 nested cross-validation scheme. External validation was conducted using PSEN1 missense variants from ClinVar annotated as pathogenic/likely pathogenic or benign/likely benign. Model performance was compared with SIFT and PolyPhen-2, and interpretability was evaluated by feature ablation and SHapley Additive exPlanations analyses. AD-associated variants exhibited statistically significant enrichment within some transcriptomic or proteomic features, with PSEN1 contributing significantly to the enrichment observed across these features. Random forest and gradient boosting models achieved high performance in the internal training dataset and maintained high recall in the external validation dataset, outperforming SIFT and approaching the performance of PolyPhen-2. Relative solvent accessibility was the most discriminative individual feature, while regional and topological features provided complementary discriminative power. This integrative, multi-omics framework links disease-specific enrichment patterns with interpretable gene-level machine learning for AD missense variants. The results highlight the importance of expression level, structural context, etc. for PSEN1 variant pathogenicity and may help prioritize variants for functional studies. Further validation in additional genes and independent cohorts is warranted prior to any clinical application. Show less
📄 PDF DOI: 10.1186/s13195-025-01950-0
APOE

Integrating six-stage cascade focused strategy to reveal the potential mechanisms and effective components of Ershiwei Roudoukou pills in anti-atherosclerosis.

Hongbin Zhang, Li Qiao, Fan Yang +5 more · 2026 · Phytomedicine : international journal of phytotherapy and phytopharmacology · Elsevier · added 2026-04-24
Elucidating effective components and mechanisms of traditional Chinese medicine (TCM) formulas remains a critical challenge for modernization. ErShiWei RouDouKou Pills (ESWRDK), a Tibetan formula with Show more
Elucidating effective components and mechanisms of traditional Chinese medicine (TCM) formulas remains a critical challenge for modernization. ErShiWei RouDouKou Pills (ESWRDK), a Tibetan formula with cardiovascular potential, lacks systematic exploration of its anti-atherosclerotic (AS) material basis and mechanisms. A novel six-stage cascade focused strategy integrating three-dimensional filtering mode, qualitative characterization, multi-component quantification, anti-AS efficacy, multi-lipidomics and bioactive compounds evaluation was proposed, advancing TCM research by holistic and multi-layered approach. UHPLC-MS combined with mass defect-ion intensity filtering (MD-ITF), DPIs, Nl and FBMN employed for profiling. Nine characteristic components were quantitated. A 12-week high-fat diet was fed to ApoE Firstly, the MD-ITF method and structural classification was established for complicated matrix. Secondly, 426 chemical components including 74 low-abundance were characterized. Thirdly, 9 characteristic components were quantified, and content distribution were profiled. Fourthly, ESWRDK reduced lipids, inflammation, and aortic plaques in AS mice. Fifthly, a total of 38, 23 and 48 differential biomarkers were identified predominantly linked to glycerophospholipids (GP) metabolism. WB confirmed ESWRDK downregulated hepatic PLA2, upregulated p-AMPK/AMPK and PPAR-α, and suppressed SREBP-1, orchestrating and mitigating lipid dysregulation. Finally, dehydrodiisoeugenol and agarotetrol bound PLA2, formed stable 1:1 static quenchingand inhibited PLA2 activity in vitro. A novel six-stage cascade-focused strategy was successfully established to elucidate ESWRDK's anti-AS mechanisms, offering feasible paradigm for advancing modernization of TCM. Show less
no PDF DOI: 10.1016/j.phymed.2026.158052
APOE

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

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

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

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

Psychedelics and the Extracellular Matrix: Rewiring Neuroplasticity and Metaplasticity for Next-Generation Psychiatric Therapies.

Jin Zhang, Cong Lin, Xinyou Lv +2 more · 2026 · Biological psychiatry · Elsevier · added 2026-04-24
Classic psychedelics, such as psilocybin, lysergic acid diethylamide (LSD), and N,N-dimethyltryptamine (DMT), have emerged as potent modulators of neuroplasticity and metaplasticity in the adult brain Show more
Classic psychedelics, such as psilocybin, lysergic acid diethylamide (LSD), and N,N-dimethyltryptamine (DMT), have emerged as potent modulators of neuroplasticity and metaplasticity in the adult brain, offering novel therapeutic strategies for neuropsychiatric disorders. Recent findings reveal that beyond their transient psychotropic effects, these compounds activate serotonin 5-HT Show less
no PDF DOI: 10.1016/j.biopsych.2026.02.011
BDNF metaplasticity neuroplasticity neuropsychiatric disorders neuroscience psychedelics psychiatric therapies serotonin

The heterogeneous treatment effects of statins on dementia: a target trial emulation with causal machine learning using integrated genetic and real-world data.

Yongjie Lai, Qoua L Her, Yue Zhang +8 more · 2026 · Alzheimer's & dementia : the journal of the Alzheimer's Association · Wiley · added 2026-04-24
Given the complexity of dementia, the inconsistent evidence on statins and dementia highlights the need for robust methods to assess heterogeneous treatment effects (HTEs). We emulated a target trial Show more
Given the complexity of dementia, the inconsistent evidence on statins and dementia highlights the need for robust methods to assess heterogeneous treatment effects (HTEs). We emulated a target trial using UK Biobank comparing statin initiators and non-initiators aged ≥55 years. Marginal structural models were fitted to estimate 5-year adjusted risk difference (aRD). We used iterative causal forest, a causal machine learning subgrouping algorithm, to identify subgroups with HTEs. Among 18,366 participants, the overall aRD for all-cause dementia was -1.0‰ (95% CI: -4.2‰ to 2.3‰). We identified subgroups by polygenic risk score for Alzheimer's disease (AD) excluding apolipoprotein E (APOE) genotype ("non-APOE PRS"). Participants with high non-APOE PRS showed cognitive benefit (all-cause dementia: aRD -5.9‰, 95% CI: -8.1‰ to 1.2‰; AD: aRD -5.0‰, 95% CI: -8.2‰ to -0.2‰). Participants with high non-APOE PRS may benefit from statins, suggesting genetic susceptibility beyond APOE could modify statins' cognitive effects. Show less
📄 PDF DOI: 10.1002/alz.71178
APOE

Serum lipoprotein(a) and risk of contrast-induced nephropathy in patients with type 2 diabetes mellitus.

Yesheng Ling, Yang Chen, Xianguan Yu +1 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
To assess the predictive value of serum lipoprotein(a) [Lp(a)] for contrast-induced nephropathy in patients with type 2 diabetes mellitus (T2DM). Consecutive T2DM patients who underwent coronary angio Show more
To assess the predictive value of serum lipoprotein(a) [Lp(a)] for contrast-induced nephropathy in patients with type 2 diabetes mellitus (T2DM). Consecutive T2DM patients who underwent coronary angiography (CAG) or percutaneous coronary intervention (PCI) between January 2019 and December 2021 were enrolled. Baseline Lp(a) was measured before the operation. CIN was defined as an increase in serum creatinine of more than 25% or 44 μmol within 72 h of contrast administration. The relationship between Lp(a) and CIN risk was analyzed. A total of 928 T2DM patients were included. CIN developed in 11.1% (103/928) of patients. The Lp(a) level was significantly higher in patients with CIN than in non-CIN patients (311.12 ± 278.66 vs. 254.19 ± 274.56 mg/L, A higher serum Lp(a) level indicates an increased risk of CIN in T2DM patients undergoing CAG or PCI and can serve as an independent predictor of CIN in this population. This study's findings will aid in the clinical prevention and treatment of contrast agent-induced kidney disease. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1733119
LPA

Categories and Influencing factors of critical care nurses' compassion fatigue: A latent profiel analysis.

Jian Zhang, Xilin Yu, Lili Wei +3 more · 2026 · Nursing ethics · SAGE Publications · added 2026-04-24
PurposeThis study aims to explore the latent classes of compassion fatigue among intensive care unit (ICU) nurses and identify the factors that influence their compassion fatigue.MethodsBetween Novemb Show more
PurposeThis study aims to explore the latent classes of compassion fatigue among intensive care unit (ICU) nurses and identify the factors that influence their compassion fatigue.MethodsBetween November 2024 and February 2025, 1029 ICU nurses were selected as study participants using convenience sampling. Data were gathered through general demographic questionnaires, the Chinese version of the Short Scale of Compassion Fatigue (CFSS), the Occupational Stress Scale, the Perceived Social Support Scale, as well as the Professional Identity Scale. A latent profile analysis (LPA) was conducted based on the three dimensions of the CFSS as observed indicators. Additionally, factors influencing outcomes were analyzed using both univariate and multivariate logistic regression methods.Ethical considerationsThis study was approved by the Institutional Review Board of the Affiliated Hospital of Qingdao University.ResultsA total of 1029 valid questionnaires were obtained, resulting in an effective response rate of 93.46%. The average score on the ICU Nurse Compassion Fatigue Scale was 60.00 ± 27.36 points. Three distinct profiles were identified: low compassion fatigue-low secondary trauma type (33.04%), moderate compassion fatigue-overall fluctuation type (48.30%), and high compassion fatigue-high burnout type (18.66%). Multivariate logistic regression analysis revealed that health status, sleep quality, highest education level, occupational stress, professional identity, and social support significantly influence the potential compassion fatigue profiles among critical care nurses ( Show less
no PDF DOI: 10.1177/09697330261426430
LPA

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

Associations of non-traditional lipid parameters with high-risk plaques characterized by optical coherence tomography in acute myocardial infarction culprit lesions.

Mengyao Cheng, Erkun Xing, Minmin Wang +2 more · 2026 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
The objective of this research was to investigate the association between non-traditional lipid parameters and optical coherence tomography (OCT)-characterized high-risk plaques in patients with acute Show more
The objective of this research was to investigate the association between non-traditional lipid parameters and optical coherence tomography (OCT)-characterized high-risk plaques in patients with acute myocardial infarction (AMI). This retrospective study included 249 first-episode AMI patients admitted to the First Affiliated Hospital of Lanzhou University between January 2022 and December 2024. All patients underwent OCT-guided assessment of culprit lesions before revascularization. High-risk plaques were defined by more than two of the following features: lipid arc ≥90 °, fibrous cap thickness <65 μm, or plaque rupture/thrombus. Lesions with fewer than two of these criteria were classified as non-high-risk plaques. Clinical and laboratory data were collected, and a comprehensive lipid profile was calculated, including traditional indicators [e.g., non-HDL cholesterol (non-HDL-C)] and non-traditional ratios [e.g., apolipoprotein B/A1 ratio (ApoB/A1)]. Spearman correlation was used to assess relationships between lipid parameters and high-risk plaques. After excluding collinear variables, logistic regression, restricted cubic spline (RCS), and subgroup analyses were performed. Model discrimination and clinical value were evaluated using receiver operating characteristic (ROC) curves, the DeLong test, integrated discrimination improvement (IDI), net reclassification index (NRI), and decision curve analysis (DCA). Among 249 AMI patients, 137 (55.0%) exhibited OCT-characterized high-risk plaques. These patients were more often male (89.8%) and presented with STEMI (84.7%). They had elevated levels of myoglobin, LDL-C, non-HDL-C, ApoB, ApoB/A1, remnant lipoprotein cholesterol (RLP-C), non-HDL-C/HDL-C ratio (NHHR), and TC/HDL-C (all Both the non-traditional ApoB/A1 ratio and the traditional lipid marker non-HDL-C were independently and linearly associated with OCT-characterized high-risk plaques in AMI. Their combined assessment enhanced the identification of high-risk plaques morphology. Show less
📄 PDF DOI: 10.3389/fcvm.2026.1698482
APOB

BDNF and NLRP3 signaling differentially regulate formation and retrieval of nitrous oxide (N

Huarong Shen, Yatong Shi, Jiancheng Xu +7 more · 2026 · International immunopharmacology · Elsevier · added 2026-04-24
The formation and retrieval of reward memories within the hippocampus are critical mechanisms underlying the development of substance use disorder. Nitrous oxide (N
no PDF DOI: 10.1016/j.intimp.2026.116327
BDNF bdnf hippocampus nitrous oxide nlrp3 substance use disorder

The association between sedentary behavior, internet addiction, and body composition among Chinese college students: A cross-sectional study.

Rong Chen, Qixin Xiao, Gesang Pingcuo +3 more · 2026 · Acta psychologica · Elsevier · added 2026-04-24
Previous research has suggested that high levels of internet use are associated with lower levels of physical activity. However, recent studies have yielded mixed findings. First, we aim to explore th Show more
Previous research has suggested that high levels of internet use are associated with lower levels of physical activity. However, recent studies have yielded mixed findings. First, we aim to explore the prevalence of internet addiction and sedentary behavior among college students. Second, we examine the relationship between sedentary behavior and body composition. Additionally, we employ latent profile analysis (LPA) to identify subgroups of internet addiction profiles and to explore the associations between these latent profiles and sedentary behavior. This cross-sectional study examined the relationship between sedentary behavior, internet addiction, and body composition among 369 Chinese college students. Sedentary behavior was assessed via self-reported sitting time, internet addiction was measured using a standardized questionnaire, and body composition was evaluated with the InBody 120 device. LPA, an individual-centered method, was used to identify homogeneous subgroups of internet addiction. 42.3 % of students exhibited internet addiction and 72.6 % reported ≥6 h of daily sitting. LPA revealed two distinct profiles of internet addiction-"Regular" (57.2 %) and "Internet addiction" (42.8 %)-highlighting its heterogeneous nature. The findings suggest that age (p = 0.296), gender (p = 0.304), and sedentary time (p = 0.954) may not be the primary factors contributing to these profiles. Policymakers and campus health programs should tailor interventions to distinct internet addiction subgroups. Further research is needed to examine psychological, behavioral, and social contributors, as well as long-term effects. Show less
no PDF DOI: 10.1016/j.actpsy.2025.106027
LPA

Protective Effect of Red Yeast Rice on Immune Checkpoint Inhibitors-Related Atherosclerotic Progression Through Inhibiting Macrophage Inflammatory Response and T Lymphocytes Infiltration.

Jian'an Pan, Hui Zhang, Xiaozhen He +6 more · 2026 · Phytotherapy research : PTR · Wiley · added 2026-04-24
Immune checkpoint inhibitors (ICIs) have prolonged cancer survival but exacerbated atherosclerotic cardiovascular disease (ASCVD). This research aims to interrogate the underlying mechanism of ICIs-re Show more
Immune checkpoint inhibitors (ICIs) have prolonged cancer survival but exacerbated atherosclerotic cardiovascular disease (ASCVD). This research aims to interrogate the underlying mechanism of ICIs-related atherosclerotic progression and the potential protective effect of Red Yeast Rice (RYR) on it. A tumor-bearing atherosclerotic (TB-AS) mouse model was established by subcutaneously injecting MC38 cells in male ApoE Show less
no PDF DOI: 10.1002/ptr.70261
APOE

BDNF genetic variants modulate the impact of childhood trauma on symptom dimensions in first-episode schizophrenia.

Junjiao Ping, Yong Wu, Jiali Luo +3 more · 2026 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Gene-environment interactions play a critical role in shaping phenotypic heterogeneity in complex psychiatric disorders. Brain-derived neurotrophic factor (BDNF) is a key genetic regulator of stress-s Show more
Gene-environment interactions play a critical role in shaping phenotypic heterogeneity in complex psychiatric disorders. Brain-derived neurotrophic factor (BDNF) is a key genetic regulator of stress-sensitive neuroplasticity. Yet, how We conducted a case-control study including 93 patients with first-episode schizophrenia (SZ) and 64 healthy controls. Childhood trauma exposure was assessed using the Childhood Trauma Questionnaire (CTQ), and symptom dimensions were evaluated with the Positive and Negative Syndrome Scale (PANSS). Three Patients with SZ exhibited significantly higher CTQ scores across all trauma subtypes compared with controls (all These findings demonstrate that Show less
📄 PDF DOI: 10.3389/fpsyt.2026.1790184
BDNF

Altered Microglia-Neuron Crosstalk and Regional Heterogeneity in Alzheimer's Disease Revealed by Single-Nucleus RNA Sequencing.

Zhenqi Yang, Mingzhao Zhang, Weijia Zhi +4 more · 2026 · International journal of molecular sciences · MDPI · added 2026-04-24
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by irreversible cognitive decline and synaptic dysfunction and represents the most prevalent etiology of dementia, ac Show more
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by irreversible cognitive decline and synaptic dysfunction and represents the most prevalent etiology of dementia, accounting for an estimated 60-70% of all clinically diagnosed cases worldwide. The growing focus on microglia-neuron interactions in AD research highlights their diverse, region-specific responses, which are driven by the functional and pathological heterogeneity across different brain regions. Therefore, investigating the interactions between microglia and neurons is of crucial importance. To explore the regional heterogeneity of microglia-neuron crosstalk in AD, we integrated human single-nucleus RNA sequencing data from the prefrontal cortex (PFC), hippocampus (HPC), and occipital lobe (OL) provided by the ssREAD database. Our study delineated four microglial subtypes and uncovered a pseudotime trajectory activation trajectory leading to the disease-associated microglia (DAM) phenotype. The transition along this trajectory is driven and stabilized by a key molecular switch: the coordinated downregulation of inhibitory factors (e.g., LINGO1) and upregulation of immune-effector and antigen-presentation programs, which collectively establish the pro-inflammatory DAM state. Furthermore, we observed that each brain region displayed unique microglia-neuron communication patterns in response to AD pathology. The PFC and OL engage a THY1-ITGAX/ITGB2 signaling axis; the HPC predominantly utilizes the PTPRM pathway. Notably, THY1 dysregulation strongly correlates with pathology in the PFC, HPC, and OL, suggesting that microglia-neuron crosstalk in AD possesses both heterogeneity and commonality. The main contribution of this study is the systematic characterization of region-specific microglia-neuron interactions and the identification of THY1 as a potential mediator that may be targeted therapeutically to modulate microglial function in affected brain regions. Show less
📄 PDF DOI: 10.3390/ijms27031492
LINGO1

Restoring mitochondria-endoplasmic reticulum-synapse axis: a proteomic dissection of Rhein's multi-pathway antidepressant mechanism.

Ziyu Ge, Yang Yang, Pei Chen +12 more · 2026 · Biochemical pharmacology · Elsevier · added 2026-04-24
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive Show more
Depression is a heterogeneous psychiatric disorder with limited treatment efficacy, as 30-50% of patients exhibit inadequate responses to conventional monoaminergic antidepressants. Rhein, a bioactive anthraquinone derived from Rheum palmatum, exhibits rapid and sustained antidepressant effects in both acute and chronic social defeat stress (CSDS) mouse models. Using quantitative proteomics on prefrontal cortex (PFC) samples from control, CSDS, Rhein-treated, and imipramine-treated cohorts, we identified differentially expressed proteins that revealed Rhein's multi-target regulatory profile. Functional enrichment and clustering analyses indicated that Rhein predominantly restores dysregulated pathways related to lipid metabolism, ribosomal translation, mitochondrial and endoplasmic reticulum (ER) function, and synaptic plasticity, forming a coherent mechanistic axis underlying its therapeutic effects. Comparative analysis with imipramine-treated mice further highlighted Rhein's distinct capacity to modulate organelle homeostasis and synaptic remodeling with greater breadth. Parallel reaction monitoring (PRM) and Western Blotting validated key proteins involved in mitochondrial functions (BNIP1, PISD, MRPL42, MRPS30, LRBA, IGHM), ER homeostasis (ACBD5, APOA4, RPL14), and synaptic plasticity (HDAC1, FAM3C, SSU72). These molecular findings suggest that Rhein exerts its antidepressant effects by restoring the functional integrity of mitochondria and the ER, thereby reprogramming synaptic plasticity. We inferred that this organelle-centered regulation further reinforces its potent modulation through multiple mechanisms and signaling pathways of synaptic plasticity, enabling Rhein to exert antidepressant effects through a coordinated, multi-layered mechanism. Collectively, our findings provide a systems-level mechanistic framework for Rhein's antidepressant efficacy and support its potential as a multi-pathway natural therapeutic, particularly for metabolic subtypes of depression. Show less
no PDF DOI: 10.1016/j.bcp.2025.117548
APOA4