👤 Jingyue Zhang

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

Effect of cholesterol on distribution, cell uptake, and protein corona of lipid microspheres at sites of cardiovascular inflammatory injury.

Lingyan Li, Xingjie Wu, Qianqian Guo +9 more · 2025 · Journal of pharmaceutical analysis · Elsevier · added 2026-04-24
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, over Show more
Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma (PPAR-γ) expression in vascular endothelial cells and estrogen receptor alpha (ERα) protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation Show less
📄 PDF DOI: 10.1016/j.jpha.2024.101182
APOA5

Polystyrene/polylactic acid microplastics impair transzonal projections and oocyte maturation via gut microbiota-mediated lipoprotein lipase inhibition.

Jiacheng Zhang, Hangqi Hu, Yutian Zhu +11 more · 2025 · Journal of hazardous materials · Elsevier · added 2026-04-24
This study focuses on the impacts of polystyrene/polylactic acid microplastics (PS/PLA-MPs) on ovarian reserve and oocyte maturation in female mice, along with the underlying mechanisms. 1 μm PS-MPs a Show more
This study focuses on the impacts of polystyrene/polylactic acid microplastics (PS/PLA-MPs) on ovarian reserve and oocyte maturation in female mice, along with the underlying mechanisms. 1 μm PS-MPs and PLA-MPs were prepared, with PLA-MPs having a rougher surface and broader size distribution. In vitro, PLA-MPs showed higher cytotoxicity to granulosa cells compared to PS-MPs. In vivo, MPs exposure disrupted the estrous cycle, and damaged ovarian reserve. Granulosa cell apoptosis and cytokine activation led to transzonal projection retraction, oocyte oxidative stress, meiotic abnormalities, and reduced oocyte retrieval and polar body extrusion rate, thus reducing litter size. PS-MPs induced more severe intestinal and ovarian impairment. Analysis of feces 16S rRNA, serum metabolomics, and ovarian RNA sequencing revealed that lipoprotein lipase (LPL) was suppressed by both MPs, linking gut microbiota, lipid metabolism, and ovarian injury. Fecal microbiota transplantation as a rescue strategy in MPs exposed mice upregulated LPL, alleviating ovarian reserve decline. In PLA-MPs exposed mice, ovarian reserve related indicators partially recovered after a two-week exposure cessation. These results clarify the similarities and differences in how PS-MPs and PLA-MPs impair ovarian function via gut-ovary axis and lipid metabolism dysregulation. Show less
no PDF DOI: 10.1016/j.jhazmat.2025.139475
LPL

Copper metabolism-related biomarkers and therapeutic targets for diabetic nephropathy.

Qiaofang Yan, Yuanyuan Du, Fei Huang +9 more · 2025 · PeerJ · added 2026-04-24
Diabetic nephropathy (DN) is the most intractable complication of diabetes. Despite decades of research, accurate diagnostic markers and effective therapeutic drugs are still elusive. Abnormal copper Show more
Diabetic nephropathy (DN) is the most intractable complication of diabetes. Despite decades of research, accurate diagnostic markers and effective therapeutic drugs are still elusive. Abnormal copper metabolism is also implicated in diabetes and its complications. This study aims to identify copper metabolism-related biomarkers and potential drugs for DN. DN datasets and copper metabolism-related genes (CMGs) were obtained from Gene Expression Omnibus (GEO) and GeneCards. Differentially expressed CMGs (DE-CMGs) were identified using the limma package and the Venn algorithm. Functional enrichment analysis and protein-protein interaction (PPI) network were performed to identify candidate hub genes. The single gene with an area under the receiver operating characteristic (ROC) curve > 0.7 was identified as a potential diagnostic biomarker of DN. Finally, these biomarkers were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. These validated hub genes were used to construct a combined prediction model, confirmed by additional GSE30528 and GSE30529 datasets. The correlation analysis between the expression level of the hub genes and the estimated glomerular filtration rate (eGFR) was carried out. Additionally, immune cell infiltration and potential target drugs were investigated for these biomarkers. Five hub genes associated with copper metabolism, namely CD36, CCL2, CASP3, LPL, and APOC3, were identified as biomarkers for the early diagnosis of DN. Utilizing multiple biomarkers enhanced diagnostic accuracy and specificity. CD36, CCL2, and CASP3 correlated negatively with eGFR levels, while LPL and APOC3 correlated positively. Additionally, these hub genes were significantly linked to various immune cell types, including macrophages M1 and M2, T cells, gamma delta resting dendritic cells, neutrophils, and NK cells. Furthermore, 15 agents targeting these biomarkers were retrieved from the DrugBank database. Our study identified key genes possibly related to copper metabolism in the pathological mechanism of DN that could serve as novel targets for the diagnosis and therapy of DN. Show less
📄 PDF DOI: 10.7717/peerj.20468
APOC3

Multi-Angle Bioactivity Cartography for Computational Screening and Mechanistic Analysis of AChE Inhibitors From Yellow Gastrodia elata.

Ruijun Sun, Yuchi Zhang, Jingying Xu +7 more · 2025 · Archiv der Pharmazie · Wiley · added 2026-04-24
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-se Show more
Acetylcholinesterase (AChE) inhibitors are crucial for the symptomatic management of Alzheimer's disease (AD), with natural products-particularly botanical sources like Yellow Gastrodia elata (YGE)-serving as promising reservoirs of such inhibitors. Nevertheless, comprehensive screening and mechanistic characterization of their inhibitory potential remain limited. This study sought to identify potent AChE inhibitors from YGE, investigate their mechanisms of action, and assess their therapeutic prospects for AD. Methodologically, an integrated approach was employed, combining ultrafiltration-liquid chromatography (UF-LC) for rapid inhibitor screening, molecular docking and dynamics simulations for mechanistic insight, two-stage high-speed countercurrent chromatography for compound isolation, enzyme kinetics to delineate inhibition modalities, and network pharmacology to uncover relevant AD-related targets. The findings identified seven active constituents with notable AChE inhibition, among which parishins A and G were obtained at high purity (98.26% and 97.26%, respectively) and exhibited mixed-type inhibition with low IC Show less
no PDF DOI: 10.1002/ardp.70174
BACE1

RPL22L1 fosters malignant features of cervical cancer via the modulation of DUSP6-ERK axis.

Dongmei Zhang, Meiqi Zhao, Ping Jiang +13 more · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
Cervical cancer remains one of the leading causes of cancer-related deaths among women globally, and there is still a need to research molecular targets that can be used for prognosis assessment and p Show more
Cervical cancer remains one of the leading causes of cancer-related deaths among women globally, and there is still a need to research molecular targets that can be used for prognosis assessment and personalized molecular therapies. Here, we investigate the role of potential molecular target ribosomal L22-like 1 (RPL22L1) on cervical cancer, identify its potential mechanisms, and explore its related applications in prognosis and molecular therapies. Multiple cervical cancer cohorts online, tissue microarrays and clinical tissue specimens were analyzed for the association between RPL22L1 expression and patient outcomes. Functional and molecular biology studies of cell and mice models were used to clarify the effects and potential mechanisms of RPL22L1 on cervical cancer. RPL22L1 is highly expressed in both cervical adenocarcinoma and squamous cell carcinoma, and its expression is significantly associated with histology grade, clinical stage, recurrence, vascular space involvement, tumor sizes and poor prognosis. In vitro and in vivo experiment revealed that RPL22L1 overexpression significantly promoted cervical cancer cell proliferation, migration, invasion, tumorigenicity and Sorafenib resistance, which were attenuated by RPL22L1 knockdown. Mechanistically, RPL22L1 competitively binds to ERK phosphatase DUSP6, leading to excessive activation of ERK. The combined application of ERK inhibitors can effectively inhibit RPL22L1 overexpressing cervical cancer cells both in vivo and in vitro. RPL22L1 promotes malignant biological behavior of cervical cancer cells by competitively binding with DUSP6, thereby activating the ERK pathway. The combined use of Sorafenib and an ERK inhibitor is a potentially effective molecular targeted therapy for RPL22L1-high cervical cancer. Show less
📄 PDF DOI: 10.1186/s12967-025-06249-0
DUSP6

Association of Vitiligo With Autoimmune Disorders: A Bidirectional Two-Sample and Summary-Based Mendelian Randomization Study.

Jiangfeng Huang, Ling Jiang, Yibo Hu +7 more · 2025 · Journal of cosmetic dermatology · Blackwell Publishing · added 2026-04-24
The existence of a definite direct causal relationship between vitiligo and diverse autoimmune disorders remains unknown due to the influence of confounding factors and potential reverse causality. Me Show more
The existence of a definite direct causal relationship between vitiligo and diverse autoimmune disorders remains unknown due to the influence of confounding factors and potential reverse causality. Mendelian randomization (MR) is a technique employed to explore causal connections between two phenotypes. In our research, bidirectional two-sample MR analyses were utilized to evaluate the causal connections between vitiligo and multiple autoimmune diseases (systemic lupus erythematosus, Graves' disease, inflammatory bowel disease, alopecia areata [AA], type 1 diabetes mellitus [T1MD], and rheumatoid arthritis [RA]). Furthermore, we utilized summary-based Mendelian randomization (SMR) analysis to search for common susceptibility loci between two diseases that reciprocally elevate each other's risk. Finally, colocalization analyses were used to validate the robustness of the selected genes. There was an indication of potential causation between RA and vitiligo (IVW OR = 1.19; 95% CI = 1.05-1.13; p = 0.008). Furthermore, evident causal connections exist between vitiligo and AA (IVW OR = 1.14; 95% CI = 1.04-1.26; p = 0.008), T1MD (IVW OR = 1.14; 95% CI = 1.06-1.23; p < 0.001), and RA (IVW OR = 1.08; 95% CI = 1.03-1.13; p < 0.001). In SMR analyses and colocalization analyses, we identified three shared genes associated with both vitiligo and RA, including: FCRL3, FADS1, and FADS2. Our findings demonstrated that vitiligo and RA mutually act as risk factors for each other. Additionally, vitiligo had significant causal relationships with AA and type 1 diabetes. Show less
📄 PDF DOI: 10.1111/jocd.70211
FADS1

Effect of different Lys/Met ratios in a low-protein diet on the meat quality of Tibetan sheep: A transcriptomics- and metabolomics-based analysis.

Fengshuo Zhang, Zhenling Wu, Quyangangmao Su +5 more · 2025 · Food research international (Ottawa, Ont.) · Elsevier · added 2026-04-24
This study integrated the the effects of dietary Lys/Met ratio in a low protein diet on the meat quality in Tibetan sheep. A total of 90 weaned Tibetan sheep, 2 months old with initial weight of 15.37 Show more
This study integrated the the effects of dietary Lys/Met ratio in a low protein diet on the meat quality in Tibetan sheep. A total of 90 weaned Tibetan sheep, 2 months old with initial weight of 15.37 ± 0.92 kg were randomly divided into 3 treatments, which were supplemented with Lys/Met ratio at 3 (LP-H), 2 (LP-M), and 1 (LP-L) in the basal diet (10 % crude protein), respectively. After slaughter (150 days of age), the growth performances and meat quality of longissimus dorsi muscle were evaluated. The LP-L group showed significantly higher final body weight compared to the LP-M group (P < 0.05). Serum albumin and total protein levels were significantly higher in the LP-L group than in the LP-H group (P < 0.05). Furthermore, meat from the LP-L group had significantly higher protein, calcium, and vitamin E content compared to the LP-M group (P < 0.05). Transcriptomic analysis revealed 3,479 differentially expressed genes enriched in pathways related to muscle growth, energy metabolism, and signaling transduction. Metabolomic analysis identified 771 differential metabolites, significantly enriched in ABC transporters, beta-alanine metabolism, and taste transduction pathways. Integrated analysis highlighted the upregulation of the ABCD4 gene and L-valine metabolite in the LP-L group, contributing to improved phenotypic traits. These findings provide molecular insights into the regulatory mechanisms underlying the effects of dietary Lys/Met ratios on Tibetan sheep meat quality and offer a basis for developing nutritional strategies to enhance premium meat production. Show less
no PDF DOI: 10.1016/j.foodres.2025.115893
LPL

Systemic inflammation modulates lipoprotein(a)-associated coronary stenosis in the chronic coronary syndromes.

Lu Shen, Wenqing Zhai, Ping Jiang +6 more · 2025 · American journal of preventive cardiology · Elsevier · added 2026-04-24
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether syst Show more
Recent researches highlight the interdependence of lipoprotein(a) [Lp(a)] and Lp(a)-associated cardiovascular risk with the background inflammatory burden. This study aimed to investigate whether systemic inflammation modulates Lp(a)-associated coronary stenosis in chronic coronary syndromes (CCS). A total of 1513 participants undergoing angiography at a tertiary cardiology center in China were included in our retrospective, cross-sectional study. Participants were categorized into normal, mild, and severe groups based on the Gensini Scores, which quantitatively assess stenosis severity. Multinomial logistic models were calculated according to accompanying systemic inflammation concentration. Participants with elevated Lp(a) levels had a high coronary stenosis risk: fully adjusted model odds ratios (ORs) [95% confidence intervals (CIs)] for the mild vs. normal and severe vs. normal groups were 1.47 (1.11-1.96) and 1.68 (1.21-2.33). Notably, the strongest Lp(a)-coronary stenosis associations after multi-variable adjustment persisted only in low inflammation concentration [systemic inflammation response index (SIRI) < 0.64)] [mild vs. normal, OR 2.03, 95% CI 1.17-3.54, Elevated Lp(a) correlates with coronary stenosis only in low inflammation concentration. Considering systemic inflammation in personalized Lp(a)-lowering therapies is more conducive for CCS managements. Show less
📄 PDF DOI: 10.1016/j.ajpc.2025.101324
LPA

A Novel IgG-IgM Autoantibody Panel Enhances Detection of Early-stage Lung Adenocarcinoma from Benign Nodules.

Rongrong Luo, Xiying Li, Ruyun Gao +13 more · 2025 · Genomics, proteomics & bioinformatics · Oxford University Press · added 2026-04-24
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for det Show more
Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. In this study, we investigated novel IgG and IgM autoantibodies for detecting early-stage lung adenocarcinoma (Early-LUAD) by employing a multi-step approach, including Human Proteome Microarray (HuProtTM) discovery, focused microarray verification, and ELISA validation, on 1246 individuals consisting of 634 patients with Early-LUAD (stage 0-I), 280 patients with benign lung disease (BLD), and 332 normal healthy controls (NHCs). HuProtTM selected 417 IgG/IgM candidates, and focused microarray further verified 55 significantly elevated IgG/IgM autoantibodies targeting 32 tumor-associated antigens in Early-LUAD compared to BLD/NHC/BLD+NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and a specificity of 77.0% or 80.0% for distinguishing Early-LUAD from BLD or NHC in ELISA validation. Positive predictive values for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9-20 mm, and > 20 mm significantly increased from 47.27%, 52.00%, and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13%, and 87.88% (10-autoantibody panel combined with LDCT), respectively. The combined risk score (CRS), based on the 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified the risk for Early-LUAD. Individuals with 10 ≤ CRS ≤ 25 and CRS > 25 indicated a higher risk of Early-LUAD compared to the reference (CRS < 10), with adjusted odds ratios of 5.28 [95% confidence interval (CI): 3.18-8.76] and 9.05 (95% CI: 5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules. Show less
no PDF DOI: 10.1093/gpbjnl/qzae085
WWP2

[Latent classes and their associated factors of sleep quality among police officers in Inner Mongolia Autonomous Region in 2021].

Yifei Dou, Ying Li, Meng Zhang · 2025 · Wei sheng yan jiu = Journal of hygiene research · added 2026-04-24
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 p Show more
To explore the latent classes and their associated factors of sleep quality among police officers, and to analyze the potential heterogeneity in sleep quality within this population. A total of 1162 police officers were selected using cluster random sampling in the Inner Mongolia Autonomous Region between September and December 2021. Participants completed a basic information questionnaire and the Pittsburgh sleep quality index(PSQI). Latent profile analysis(LPA) was employed to examine heterogeneity in sleep quality, and multinomial Logistic regression was used to identify associated factors of the latent profiles. The mean age of participants was(43.08±8.98) years. The sample comprised 920 males(79.2%) and 242 females(20.8%), 987(84.9%) were married and 175(15.1%) were single, 644(55.4%) had a high school education or below, and 518(44.6%) had college education or above. By department, 607(52.2%) worked in grassroots police stations, 200(17.2%) were criminal police, and 355(30.6%) served in other units. Significant heterogeneity in sleep quality was identified, revealing four distinct latent classes: good sleep group(n=821, 70.6%), moderate sleep group(n=46, 4.0%), sleep-disordered group(n=249, 21.4%), and medication-assisted sleep group(n=46, 4.0%). Using the good sleepers as the reference group, multinomial Logistic regression indicated that older age was a significant risk factor for belonging to the medication-assisted sleep group(OR=1.348, 95%CI 1.078-1.822). Higher education level was a protective factor against membership in the moderate sleep group(OR=4.101, 95%CI 1.304-12.893). Serving as a grassroots police station officer or criminal police officer was a significant risk factor for membership in both the moderate sleep group(OR = 3.329, 95%CI 1.338-8.284; OR=4.188, 95%CI 1.415-12.396) and sleep-disordered group(OR=1.701, 95%CI 1.196-2.420; OR=1.587, 95%CI 1.073-2.533). Sleep quality among police officers demonstrates significant heterogeneity. Age, police department assignment, and educational level are key associated factors of distinct latent classes of sleep quality. Show less
no PDF DOI: 10.19813/j.cnki.weishengyanjiu.2025.05.015
LPA

METTL3 promotes peritoneal metastasis of colorectal cancer through regulating m6A modification of NRXN3 mRNA.

Tian-Hao Lan, Wei Li, Xin Wang +12 more · 2025 · iScience · Elsevier · added 2026-04-24
Colorectal cancer (CRC) is a prevalent digestive system malignancy accompanied by peritoneal metastasis occurring in 7% of cases. Methyltransferase-like 3 (METTL3) promoted the progression of CRC wher Show more
Colorectal cancer (CRC) is a prevalent digestive system malignancy accompanied by peritoneal metastasis occurring in 7% of cases. Methyltransferase-like 3 (METTL3) promoted the progression of CRC whereas its function in peritoneal metastasis was incompletely understood. Here, we found that METTL3 was upregulated in peritoneal metastasis tissues of CRC patients compared with CRC tissues. By sequencing the mRNA of above tissues, we discovered that METTL3-mediated N6-methyladenosine (m6A) modification regulated the downstream target Show less
no PDF DOI: 10.1016/j.isci.2025.113165
NRXN3

Myocardial dysfunction caused by MyBPC3 P459fs mutation in hypertrophic cardiomyopathy: evidence from multi-omics approaches and super-resolution imaging.

Yupeng Wu, Yuzhu Zhang, Qirui Zheng +5 more · 2025 · Frontiers in cardiovascular medicine · Frontiers · added 2026-04-24
Mutations in the sarcomere protein, particularly in cardiac myosin binding protein C gene ( We used multi-omics approaches and super-resolution imaging to explore the effects of MyBPC3 P459fs mutation Show more
Mutations in the sarcomere protein, particularly in cardiac myosin binding protein C gene ( We used multi-omics approaches and super-resolution imaging to explore the effects of MyBPC3 P459fs mutation on humans and cells. HCM patients carrying MyBPC3 P459fs mutation (MyBPC3-P459fs HCMs) and healthy controls (HCs) were evaluated for myocardial function using both conventional and advanced echocardiography. In parallel, H9C2 myocardial cells infected with either MyBPC3 P459fs mutation (P459fs cells) or its wild type (WT cells) were investigated for myocardial fiber formation and the potential pathways behind this using super-resolution imaging and metabolomics and proteomics. First, conventional and advanced echocardiography showed that MyBPC3-P459fs HCMs exhibited left ventricular diastolic and systolic dysfunction. Subsequently, super-resolution imaging indicated that P459fs cells formed fewer and shorter myocardial fibers in the cytoplasm compared to WT cells. Moreover, our metabolomic and proteomic data suggested several key components of mitochondrial membrane integrity, myocardial remodeling, myocardial energy metabolism, oxidative stress, inflammation, and actin binding capacity were significantly altered in response to P459fs mutation. This investigation indicated myocardial dysfunction and myocardial fiber disarray in clinical HCMs with MyBPC3 P459fs mutation and added potential pathways underlying this. These findings provided a link between the observed structural and functional disorders in MyBPC3 P459fs mutation and its onset of HCM pathogenesis and might have a significant translational contribution to effective treatment in HCM patients with MyBPC3 P459fs mutation. Show less
📄 PDF DOI: 10.3389/fcvm.2025.1529921
MYBPC3

Interleukin-27 is a multitarget regulator of fibroblast remodeling in thyroid-associated ophthalmopathy.

Pengbo Zhang, Xiaofang Wang, Nanji Lu +3 more · 2025 · iScience · Elsevier · added 2026-04-24
Thyroid-associated ophthalmopathy (TAO) is characterized by inflammation and tissue remodeling, including fibrosis and adipogenesis. Here, we identify interleukin-27 (IL-27) as a negative feedback imm Show more
Thyroid-associated ophthalmopathy (TAO) is characterized by inflammation and tissue remodeling, including fibrosis and adipogenesis. Here, we identify interleukin-27 (IL-27) as a negative feedback immunomodulator in TAO. Serum IL-27α levels were significantly elevated in patients with TAO compared with healthy and inflammatory disease controls. In orbital fibroblasts (OFs), exogenous IL-27 suppressed IL-1β-induced proinflammatory cytokines and reduced hypoxia-induced NLRP3 inflammasome activation. IL-27 also attenuated TGF-β-driven fibrosis via p38 MAPK signaling in CD90 Show less
📄 PDF DOI: 10.1016/j.isci.2025.113982
IL27

Safety and efficacy of inclisiran in treating hypercholesterolemia: A systemic review and meta-analysis.

Zhiling Cheng, Meiling Gao, Yang Liu +4 more · 2025 · Nutrition, metabolism, and cardiovascular diseases : NMCD · Elsevier · added 2026-04-24
To evaluate the efficacy and safety of inclisiran in the treatment of hypercholesterolemia. Randomized controlled trials comparing inclisiran with a placebo were searched until April 2024. Overall, 8 Show more
To evaluate the efficacy and safety of inclisiran in the treatment of hypercholesterolemia. Randomized controlled trials comparing inclisiran with a placebo were searched until April 2024. Overall, 8 studies involving 4947 patients were included. Inclisiran reduced low-density lipoprotein cholesterol (mean difference [MD]: -46.95 %; 95 % confidence interval [CI]: -53.26 to -40.46; P < 0.05), proprotein convertase subtilisin/kexin type 9 (MD: -70.80 %; 95 % CI: -76.52 to -65.08; P < 0.05), serum total cholesterol (MD: -29.47 %; 95 % CI: -32.56 to -26.39; P < 0.05), non-high-density lipoprotein cholesterol (MD: -40.46 %; 95 % CI: -45.24 to -35.68; P < 0.05), apolipoprotein B (MD: -36.77 %; 95 % CI: -40.94 to -32.61; P < 0.05), and lipoprotein(a) (MD: -20.04 %; 95 % CI: -24.2 to -15.87; P < 0.05) levels but increased high-density lipoprotein cholesterol level (MD: 6.09 %; 95 % CI: 3.63 to 8.55; P < 0.05). The incidences of adverse events, serious adverse events, headache, nasopharyngitis, and muscular adverse reactions were not significantly different between the inclisiran and placebo groups. Inclisiran reduced the incidence of cardiovascular adverse reactions (odds ratio [OR] = 0.79; 95 % CI: 0.65 to 0.96; P = 0.02) and increased the incidence of injection-site reactions (OR = 4.79; 95 % CI: 2.18 to 10.52; P < 0.05). Inclisiran is effective in treating hypercholesterolemia and has a good safety profile. Show less
no PDF DOI: 10.1016/j.numecd.2024.10.017
APOB

Genetic association of lipids characteristics and lipid lowering drug target genes with sepsis.

Yu Wang, Haiyue Zhang, Yuanyuan Zhan +4 more · 2025 · PloS one · PLOS · added 2026-04-24
Sepsis is a severe systemic infection that can result in organ dysfunction and mortality. Dyslipidemia emerges as a key player in the intricate web of sepsis pathogenesis. Yet, the causal relationship Show more
Sepsis is a severe systemic infection that can result in organ dysfunction and mortality. Dyslipidemia emerges as a key player in the intricate web of sepsis pathogenesis. Yet, the causal relationship between blood lipid profiles and sepsis risk remains uncertain. This study aims to investigate the association between genetically predicted lipid traits, drug targets, and sepsis. The UK Biobank's Genome-wide association studies (GWAS) produced data on lipid and apolipoprotein characteristics. Four independent GWAS datasets were used to generate the sepsis statistics. The study utilized the two-sample Mendelian randomization (MR) approach, which incorporates multivariable (MVMR) models, to assess the correlations between sepsis risk and lipid-related parameters. To gain further insight, expression quantitative trait loci (eQTL) data were used to investigate the significant drug targets for lipid-lowering. Increasing ApoA-1 levels was associated with a diminished risk of sepsis (under 75) (OR 0.927, 95% CI 0.861-0.999; p = 0.047). This inverse correlation persevered even after performing multivariable MR. Elevated levels of HDL-C were associated with a decreased risk of sepsis (under 75) (OR 0.897, 95% CI 0.838-0.960; P = 0.002) and incidence of sepsis (OR 0.883, 95% CI 0.820-0.951; P = 0.001), which was consistent across sensitivity analyses. Furthermore, a decrease in total cholesterol exhibited a causal effect on sepsis in multivariable MR (OR 0.779, 95% CI 0.642-0.944; P = 0.01). The genetic variants related to lowering LDL-C, located near the HMGCR and LDLR genes, were predicted to elevate the risk of sepsis. Moreover, genetic mimicry near the ANGPTL3 and LPL gene suggested that reducing the activity of ANGPTL3 and LPL (mimicking antisense anti-ANGPTL3 and LPL agents) was forecasted to decrease sepsis risk. Genetically inferred elevated ApoA-1, total cholesterol, and HDL-C manifest a protective effect against sepsis. Within the 9 lipid-lowering drug targets investigated ANGPTL3 and LPL exhibit potential as candidate drug targets for sepsis. Show less
📄 PDF DOI: 10.1371/journal.pone.0331023
LPL

White matter hyperintensity segmentation of multiple sclerosis and neuromyelitis optical spectrum disorders using 2.5D FrC-ResUnet.

Li Zhang, Kai Niu, Yinglu Sun +9 more · 2025 · Quantitative imaging in medicine and surgery · added 2026-04-24
Assessing white matter hyperintensity (WMH) is essential for the diagnosis, treatment, and prognosis of multiple sclerosis (MS) and neuromyelitis optical spectrum disorder (NMOSD). MS and NMOSD presen Show more
Assessing white matter hyperintensity (WMH) is essential for the diagnosis, treatment, and prognosis of multiple sclerosis (MS) and neuromyelitis optical spectrum disorder (NMOSD). MS and NMOSD present dispersed small lesions alongside larger aggregated lesions that are irregularly shaped, posing challenges for the automatic segmentation of WMH on magnetic resonance images. Furthermore, research on NMOSD brain WMH segmentation is limited due to the rare nature of the disease. This study aims to propose a deep learning method for MS and NMOSD brain WMH segmentation. In this study, we propose a 2.5D Fourier Convolutional ResUnet (FrC-ResUnet). It utilizes a spectral encoder to extract global information, enabling accurate segmentation of scattered lesions. Additionally, the model incorporates the selective features module (SFM) and the convolutional block attention module (CBAM) to enhance lesion-background differentiation and outline the lesions distinctly. We evaluated our approach on the MS public and local datasets of MS and NMOSD. Compared to U-Net, ResUNet, FC-DenseNet, AttentionUNet, lesion prediction algorithm (LPA) and Sequence Adaptive Multimodal SEGmentation (SAMSEG), the 2.5D FrC-ResUnet achieved the highest Dice similarity coefficient (DSC) on three different datasets, with values of 0.710, 0.667, and 0.822, respectively. The 2.5D FrC-ResUnet demonstrates accurate and robust segmentation of NMOSD brain WMH. Meanwhile, the model excels in segmenting MS brain WMH, particularly when confronted with irregularly shaped and dispersed lesions. Show less
📄 PDF DOI: 10.21037/qims-24-2384
LPA

METTL3-dependent DLG2 inhibits the malignant progression of cervical cancer by inactivating the Hippo/YAP signaling.

Mei Pu, Xia Xiao, Shasha Lv +6 more · 2025 · Hereditas · BioMed Central · added 2026-04-24
Discs large homolog 2 (DLG2) has been implicated in cancer development, yet its role in cervical cancer remains unclear. This study aims to explore the regulatory mechanism of DLG2 in cervical cancer Show more
Discs large homolog 2 (DLG2) has been implicated in cancer development, yet its role in cervical cancer remains unclear. This study aims to explore the regulatory mechanism of DLG2 in cervical cancer and its clinical implications. Quantitative reverse transcription polymerase chain reaction and western blotting assays were employed to detect RNA and protein expression, respectively. Colony formation assay, 5-Ethynyl-2'-deoxyuridine assay, flow cytometry, and transwell assays were conducted for cell functional analysis. A xenograft mouse model assay was performed to analyze tumor tumorigenesis in vivo. m6A RNA immunoprecipitation assay was used to analyze the association of METTL3 and DLG2. DLG2 was underexpressed in cervical cancer tissues and cells. Elevating DLG2 levels significantly suppressed cervical cancer cell proliferation, migration, and invasion, while promoting apoptosis. Additionally, DLG2 overexpression led to the deactivation of the Hippo/YAP signaling pathway. In vivo, DLG2 overexpression was shown to reduce tumor formation. We also discovered that METTL3 destabilized DLG2 mRNA through an m6A-dependent mechanism. Moreover, lowering DLG2 expression mitigated the effects of METTL3 silencing on cervical cancer cell malignancy. DLG2 acted as a tumor suppressor in cervical cancer by inhibiting the Hippo/YAP signaling pathway. The METTL3-dependent regulation of DLG2 mRNA stability could be a critical factor in cervical cancer progression. Show less
📄 PDF DOI: 10.1186/s41065-025-00365-z
DLG2

Improving variant interpretation and diagnosis in Koolen-de Vries syndrome through a curated genotype-phenotype repository.

Hailin Huang, Jia Geng, Yang Long +11 more · 2025 · Molecular genetics and genomics : MGG · Springer · added 2026-04-24
Neurodevelopmental disorders (NDDs) exhibit complex genotype-phenotype associations that frequently result in inconclusive variant interpretations, contributing to suboptimal diagnostic yields (~ 40%) Show more
Neurodevelopmental disorders (NDDs) exhibit complex genotype-phenotype associations that frequently result in inconclusive variant interpretations, contributing to suboptimal diagnostic yields (~ 40%). Koolen-de Vries syndrome (KdVS), an autosomal dominant NDD caused by KANSL1 haploinsufficiency, exemplifies this diagnostic challenge with its multisystem manifestations and lack of systematic genotype-phenotype associations. To address this gap, we constructed a comprehensive KdVS genotype-phenotype repository by systematically integrating all molecularly confirmed cases from global literature. Comprehensive phenotypic analysis revealed that core KdVS features include developmental delay/intellectual disability, characteristic craniofacial dysmorphism, hypotonia, and multisystem abnormalities. Phenotypic association analysis identified 249 significant correlations, demonstrating that KdVS clinical manifestations are highly interconnected rather than representing isolated features, such as the association between strabismus and hydrocephalus (OR = 14.26). Application of this repository to screen a Chinese rare disease cohort identified 53 KANSL1 variants. Among these, one de novo nonsense variant (NM₀₀₁₁₉₃₄₆₆.2: c.902T > G, p.Leu301Ter) was classified as pathogenic in a Chinese boy with classic KdVS features. The remaining 52 variants were categorized as variants of uncertain significance (VUS), approximately half of which were absent from gnomAD databases. Each VUS was comprehensively annotated with detailed clinical profiles to facilitate phenotype-driven reinterpretation. In conclusion, this study establishes KdVS as a highly interconnected multisystem disorder and demonstrates that deep phenotypic association analysis enhanced genetic diagnosis. This disease-specific repository approach provides a scalable framework for improving molecular diagnostics across rare NDDs. Show less
no PDF DOI: 10.1007/s00438-025-02322-x
KANSL1

Hesperetin-Enhanced Metformin to Alleviate Cognitive Impairment via Gut-Brain Axis in Type 2 Diabetes Rats.

Danyang Zhang, Xiaoshi He, Yinbo Wang +8 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Diabetes constitutes a risk factor for cognitive impairment, whereas insulin resistance serves as the shared pathogenesis underlying both diabetes and cognitive decline. The use of metformin for treat Show more
Diabetes constitutes a risk factor for cognitive impairment, whereas insulin resistance serves as the shared pathogenesis underlying both diabetes and cognitive decline. The use of metformin for treating cognitive impairment remains controversial. The present study found that hesperetin, a flavanone derived from citrus peel, enhanced metformin's efficacy in reducing blood sugar levels, improving insulin sensitivity, and ameliorating cognitive impairment in diabetic rats. Additionally, it reduced the required dosage of metformin to one-third of its conventional dose. Transcriptome analysis and 16S rRNA sequencing revealed that the activation of insulin and cyclic-adenosine monophosphate response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) pathways benefited from the regulation of gut microbiota and the promotion of short-chain fatty acid (SCFA) producers such as Show less
📄 PDF DOI: 10.3390/ijms26051923
BACE1

Ferroptosis-related hub genes and immune cell dynamics as diagnostic biomarkers in age-related macular degeneration.

Jinquan Chen, Zhao Long, Dandan Shi +2 more · 2025 · European journal of medical research · BioMed Central · added 2026-04-24
Age-related Macular Degeneration (AMD) is widely acknowledged as a principal cause of vision loss in the elderly. Currently, the therapeutic interventions available in clinical practice fail to achiev Show more
Age-related Macular Degeneration (AMD) is widely acknowledged as a principal cause of vision loss in the elderly. Currently, the therapeutic interventions available in clinical practice fail to achieve satisfactory outcomes. Therefore, it is imperative that we approach the progress of AMD from novel perspectives in order to explore new therapeutic strategies. We obtained transcriptomic data from the macular and the peripheral retina from patients with AMD and a control group from the Gene Expression Omnibus (GEO) database. Through Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we identified differentially expressed genes (DEGs) that were significantly enriched in functions associated with ferroptosis. Subsequent application of machine learning techniques enabled the identification of key hub genes, whose diagnostic potential was further validated. Additionally, the expression of these hub genes was corroborated in both animal and cellular models. Finally, we performed a functional enrichment analysis of these hub genes. In the macula of patients with AMD, 452 DEGs were identified, while in the peripheral retina, 222 DEGs were discovered. Within the macula, 19 genes were associated with ferroptosis, compared to 3 in the peripheral retina. Consequently, the macular was selected as the primary focus of the study. Subsequent screening of these 19 genes using LASSO regression, Support Vector Machine (SVM), and Random Forest algorithms identified four hub genes: FADS1, TFAP2A, AKR1C3, and TTPA. Consequently, we utilized cigarette smoke extract (CSE) to either stimulate retinal pigment epithelial (RPE) cells in vitro or administer it via intravitreal injection, thereby establishing in vitro and in vivo models of AMD. Results from RT-PCR and Western blot analyses revealed an upregulation of FADS1, AKR1C3, and TTPA, while TFAP2A exhibited decreased expression. Finally, we investigated the infiltration of immune cells within the macular and performed a functional enrichment analysis of the hub genes. We identified four key ferroptosis-related genes (FRGs)-FADS1, AKR1C3, TFAP2A, and TTPA-that possess diagnostic relevance for AMD and correlate with immune cell infiltration. Moreover, significant changes in both mRNA and protein expression levels of these genes have been observed in in vitro experiments and mice models. Show less
📄 PDF DOI: 10.1186/s40001-025-03044-x
FADS1

The Clinical Value of Apolipoprotein C3 Combined with FAR and RWT in Heart Failure with Preserved Ejection Fraction.

Qingyu Zhang, Zongliang Yu · 2025 · International journal of general medicine · added 2026-04-24
Heart failure with preserved ejection fraction (HFpEF) is becoming increasingly prevalent, yet clinical practice lacks specific biomarkers, early diagnostic tools, and reliable risk assessment methods Show more
Heart failure with preserved ejection fraction (HFpEF) is becoming increasingly prevalent, yet clinical practice lacks specific biomarkers, early diagnostic tools, and reliable risk assessment methods. Given the growing burden of HFpEF, identifying novel diagnostic markers is crucial. This study investigates the diagnostic potential of apolipoprotein C3 (ApoC3) in HFpEF and its correlation with ventricular structure. We analyzed data from HFpEF patients admitted to the Kunshan Branch of Gusu College of Nanjing Medical University and the First People's Hospital of Kunshan (March-December 2023). Controls included HFrEF+HFmrEF patients and healthy individuals. Enzyme-linked immunosorbent assay (ELISA) was used to detect the concentration of ApoC3 in all collected cases. The receiver operating characteristic (ROC) curve was plotted to evaluate the diagnostic performance of ApoC3 alone and combined with the fibrinogen-to-albumin ratio (FAR) in plasma, and the relative wall thickness (RWT) in echocardiography for HFpEF. After exclusions, 80 HFpEF patients (39 male, 41 female), 41 HFrEF+HFmrEF patients (27 male, 14 female), and 79 healthy controls (53 male, 26 female) were included. ApoC3 levels were significantly higher in HFpEF (63136.03±12,113.07 ng/mL) than in HFrEF+HFmrEF (55580.84±13,685.35 ng/mL) and controls (53090.31±5893.25 ng/mL, P<0.001). ROC analysis demonstrated that ApoC3 alone (AUC=0.836) and the combined index (ApoC3+FAR+RWT, AUC=0.891) effectively distinguished HFpEF. Both also aided in differentiating HFpEF from HFrEF+HFmrEF (AUC=0.702 vs 0.823). ApoC3 is a promising biomarker for HFpEF diagnosis, and the combined index (ApoC3+FAR+RWT) enhances diagnostic accuracy. These findings may improve early detection and clinical management of HFpEF. Show less
📄 PDF DOI: 10.2147/IJGM.S532542
APOC3

Unveiling circulating targets in pancreatic cancer: Insights from proteogenomic evidence and clinical cohorts.

Haokang Feng, Zhixue Chen, Jianang Li +13 more · 2025 · iScience · Elsevier · added 2026-04-24
Pancreatic cancer (PC), characterized by the absence of effective biomarkers and therapies, remains highly fatal. Data regarding the correlations between PC risk and individual plasma proteome known f Show more
Pancreatic cancer (PC), characterized by the absence of effective biomarkers and therapies, remains highly fatal. Data regarding the correlations between PC risk and individual plasma proteome known for minimally invasive biomarkers are scarce. Here, we analyzed 1,345 human plasma proteins using proteome-wide association studies, identifying 78 proteins significantly associated with PC risk. Of these, four proteins (ROR1, FN1, APOA5, and ABO) showed the most substantial causal link to PC, confirmed through Mendelian randomization and colocalization analyses. Data from two clinical cohorts further demonstrated that FN1 and ABO were notably overexpressed in both blood and tumor samples from PC patients, compared to healthy controls or para-tumor tissues. Additionally, elevated FN1 and ABO levels correlated with shorter median survival in patients. Multiple drugs targeting FN1 or ROR1 are available or in clinical trials. These findings suggest that plasma protein FN1 associated with PC holds potential as both prognostic biomarkers and therapeutic targets. Show less
📄 PDF DOI: 10.1016/j.isci.2024.111693
APOA5

Current status of career adaptability among Chinese cardiovascular specialist nurses: a latent profile analysis.

Yanling Du, Chao Wu, Ziyue Gai +6 more · 2025 · BMC nursing · BioMed Central · added 2026-04-24
This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, Show more
This study aimed to explore the career adaptability status of cardiovascular specialist nurses (CSNs) through latent profile analysis (LPA), identify distinct subgroups and their demographic features, and determine factors influencing different adaptability categories. CSNs play a vital role in treating and rehabilitating patients with cardiovascular conditions. However, the existing literature offers limited insights into the career adaptability of CSNs in China. A multicenter, cross-sectional survey involving 659 Chinese CSNs was conducted. LPA was utilized to classify career adaptability profiles based on responses to the Career Adaptation Abilities Scale Short Form (CAAS-SF). Influencing factors were assessed using the Conditions of Work Effectiveness Questionnaire-II (CWEQ-II) and the General Self-Efficacy Scale (GSES). Differences among identified profiles were analyzed through ANOVA, chi-square tests, and multinomial logistic regression to explore relevant socio-demographic characteristics and influencing variables. A four-profile model provided the best fit, identifying groups labeled as “high adaptability” (Class 4, These findings provide evidence to assist nursing administrators in developing training programs to enhance CSNs’ career adaptability. The variables identified as associated with profile membership may enable more tailored training strategies. Show less
📄 PDF DOI: 10.1186/s12912-025-03887-z
LPA

Integrated single-cell RNA-seq and bulk RNA-seq analysis to investigate key adipogenesis genes in adipose-derived stem cells.

Tongtong Zhang, Zhongming Cai, Haoran Li +3 more · 2025 · PloS one · PLOS · added 2026-04-24
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-s Show more
Adipogenic differentiation of adipose-derived stem cells (ADSCs) is fundamental to both adipose tissue homeostasis and clinical applications, particularly fat grafting. However, the global and stage-specific transcriptional regulatory networks underlying ADSC adipogenesis remain incompletely elucidated. In this study, we integrated bulk and single-cell RNA-seq datasets across multiple time points of ADSC adipogenesis to identify core regulators of differentiation and maturation. A total of 41 genes were consistently upregulated during early differentiation, among which eight hub genes (FABP4, FASN, FABP5, ADIPOQ, PLIN1, LPL, CIDEC, and ACSL1) formed a tightly connected protein-protein interaction (PPI) module associated with lipid metabolism, lipid droplet formation, and adipocyte maturation. Further integration of differentially expressed lncRNAs and miRNAs led to the construction of a ceRNA network involving 7 mRNAs, 9 miRNAs, and 4 lncRNAs, comprising 34 predicted lncRNA-miRNA-mRNA regulatory axes. To identify temporal transcriptional regulators, we defined five genes (TTC14, MBNL2, UBR3, ABCD2, and SORT1) as early-stage inducers of adipogenesis, and four genes (UQCR11, NDUFB4, S100A10, and PRDX3) as late-stage regulators involved in maintaining the mature phenotype. These stage-specific regulators showed distinct temporal expression patterns and were validated by qPCR. GeneMANIA network analysis further revealed that early-stage regulators were enriched in lipid transport and lipase activity regulation, while late-stage regulators were associated with mitochondrial electron transport and energy metabolism. These findings highlight the stage-dependent transcriptional landscape of ADSC adipogenesis and provide candidate regulatory targets for modulating adipocyte differentiation and stability. Show less
📄 PDF DOI: 10.1371/journal.pone.0335152
LPL

Integration of gut microbiome and lipid metabolism reveals the anti-cancer effects of pentadecanoic acid on bladder cancer.

Ya-Ting Chen, Jing Sui, Yu Yang +16 more · 2025 · BMC medicine · BioMed Central · added 2026-04-24
Pentadecanoic acid (PEA), an odd-chain fatty acid derived from diet by the gut microbiome, has garnered increasing attention for its systemic health-promoting properties. Its potential role in bladder Show more
Pentadecanoic acid (PEA), an odd-chain fatty acid derived from diet by the gut microbiome, has garnered increasing attention for its systemic health-promoting properties. Its potential role in bladder cancer (BC) occurrence and invasion, however, remains unclear. Large-scale cohorts' analyses were performed to assess the association between dietary PEA and BC occurrence and invasion. In vitro and in vivo experiments, including EJ and T24 BC cell assays and a BBN-induced mouse model, were conducted to experimentally assess the impact of PEA on BC. Serum proteomics, gut microbiome, and targeted fecal lipidomics analyses were employed to explore the underlying mechanisms. Dietary PEA was negatively associated with BC occurrence and invasion in cohort analyses. PEA suppressed EJ and T24 BC cell migration, invasion, and proliferation, while inhibiting BC development in a BBN-induced mouse model. In vivo serum proteomics identified differentially expressed lipid-related proteins (e.g., Apoe and Apob) following PEA treatment, implicating its modulation of lipid metabolism pathways. Considering the essential role of the gut-bladder axis, the gut microbiome analysis exhibited that PEA markedly altered bacteria (e.g., g_Alistipes) and fungi (e.g., o_Erysiphales, g_Teberdinia, and g_Gibberella), with concomitant lipid metabolism changes. Furthermore, targeted fecal lipidomics demonstrated the shifts in key lipids, such as phosphatidylethanolamines (PE) involved in essential lipid clusters, suggesting regulation by gut microbiome linked to BC development. Collectively, our findings demonstrate that PEA mitigates BC by reshaping the gut microbiome and modulating lipid metabolism, providing new insights into its molecular and therapeutic potential. Show less
📄 PDF DOI: 10.1186/s12916-025-04554-5
APOB

Canine genome-wide association study identifies

Natalie J Wallis, Alyce McClellan, Alexander Mörseburg +29 more · 2025 · Science (New York, N.Y.) · Science · added 2026-04-24
Obesity is a heritable disease, but its genetic basis is incompletely understood. Canine population history facilitates trait mapping. We performed a canine genome-wide association study for body cond Show more
Obesity is a heritable disease, but its genetic basis is incompletely understood. Canine population history facilitates trait mapping. We performed a canine genome-wide association study for body condition score-a measure of obesity-in 241 Labrador retrievers. Using a cross-species approach, we showed that canine obesity genes are also associated with rare and common forms of obesity in humans. The lead canine association was within the gene DENN domain containing 1B ( Show less
📄 PDF DOI: 10.1126/science.ads2145
MC4R

Preliminary exploration of potential biomarkers for heart failure and bipolar disorder: an exploratory study based on bioinformatics.

Wei Zhang, Na Li · 2025 · Frontiers in psychiatry · Frontiers · added 2026-04-24
Individuals with bipolar disorder (BD) exhibit a significantly increased risk of cardiovascular disease, yet the specific mechanisms linking heart failure (HF) and BD remain poorly understood. This st Show more
Individuals with bipolar disorder (BD) exhibit a significantly increased risk of cardiovascular disease, yet the specific mechanisms linking heart failure (HF) and BD remain poorly understood. This study aimed to identify common potential diagnostic biomarkers associated with both conditions. Differentially expressed genes (DEGs) were analyzed separately in HF (GSE57338) and BD (GSE5389) datasets. Key module genes for each condition were identified through co-expression network analysis and intersected with DEGs to pinpoint candidate genes. Subsequently, a protein-protein interaction (PPI) network, receiver operating characteristic (ROC) analysis, and expression validation were employed to identify potential diagnostic biomarkers. Gene set enrichment analysis (GSEA) and drug predictions were also conducted. Clinical validation of biomarker expression was performed via quantitative polymerase chain reaction (qPCR). A total of 44 candidate genes were identified as being associated with both HF and BD. Six potential diagnostic biomarkers ( This study preliminarily explored the common molecular mechanisms between HF and BD, and identified 6 potential biomarkers for early detection, providing a solid theoretical basis for future research on HF and BD. Show less
📄 PDF DOI: 10.3389/fpsyt.2025.1627105
EXT1

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

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

NSUN2/ALYREF-medicated m5C-modified circRNA505 regulates the proliferation, differentiation, and glycolysis of antler chondrocytes via the miRNA-127/p53 axis and LDHA.

Haibo Yao, Mengmeng Song, Huan Zhang +5 more · 2025 · International journal of biological macromolecules · Elsevier · added 2026-04-24
The deer antler is a fully regenerable and the fastest-growing osseous organ. Circular RNA (circRNA), a novel member of the non-coding RNA family, has significant research potential and crucial roles Show more
The deer antler is a fully regenerable and the fastest-growing osseous organ. Circular RNA (circRNA), a novel member of the non-coding RNA family, has significant research potential and crucial roles in biological processes. This study aims to explore the impact and mechanisms of circRNA505 on antler chondrocytes. Functional experiments demonstrated that m5C-modified circRNA505 inhibits antler chondrocyte proliferation, enhances osteogenic differentiation, and facilitates cellular glycolysis. Mechanistically, dual luciferase and AGO2-RIP assays revealed a direct binding relationship between circRNA505, miR-127, and p53. Rescue assays further showed that circRNA505 affects cell proliferation and differentiation through the miR-127/p53 axis. Meanwhile, RNA Antisense Purification (RAP) screening and analysis of related proteins binding to circRNA505 demonstrated that circRNA505 binds to LDHA and increases the level of LDHA phosphorylation through FGFR1 to promote cellular glycolysis by FISH-IF, RIP, and Western blot experiments. Additionally, Me-RIP assays confirmed the m5C methylation modification of circRNA505. NSUN2 mediates the m5C modification of circRNA505, affecting its stability, while the m5C reader ALYREF promotes the nuclear export of circRNA505 in an ALYREF-dependent manner. This study provides new insights into the regulatory mechanisms underlying rapid antler development. Show less
no PDF DOI: 10.1016/j.ijbiomac.2025.142527
FGFR1

Effects of Acorns on Subcutaneous Fat Deposition in Yuxi Black Pigs by Transcriptomic Analysis.

Zhe Sun, Dongyang Liu, Siyuan An +3 more · 2025 · Metabolites · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/metabo15020071
LPL