👤 Yinxia Xu

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Also published as: Ting-Xin Xu, Shuang Xu, Renyuan Xu, Cheng Xu, Xiao Xu, Jia-Chen Xu, Yanyong Xu, Shengjie Xu, Nong Xu, D-J Xu, Hongfa Xu, Shiyi Xu, Yunjian Xu, Maochang Xu, Lingyan Xu, Guoheng Xu, Zaibin Xu, Yuexuan Xu, Jinhe Xu, Yitong Xu, Yaping Xu, Miao Xu, Hongming Xu, Jiang Xu, Feng-Qin Xu, Zaihua Xu, Yaru Xu, Yuanzhong Xu, Qiuyu Xu, Mingcong Xu, Mai Xu, Biao Xu, Jingjun Xu, Shuwan Xu, Ya-Ru Xu, Zhilong Xu, Jun-Chao Xu, Shutao Xu, Jinyu Xu, TianBo Xu, Jie-Hua Xu, Peng Xu, Guo-Xing Xu, Yushan Xu, Yongsong Xu, Xin-Rong Xu, Bilin Xu, Xiang-Min Xu, Xiaolong Xu, Jinchao Xu, Han Xu, Xuting Xu, Yu Xu, Yingqianxi Xu, Yanyang Xu, Aili Xu, Weizhi Xu, Peidi Xu, Tongyang Xu, Tieshan Xu, Jianping Xu, Wen-Juan Xu, Bing Xu, Chengyun Xu, Xiaofeng Xu, Zhengang Xu, Guang-Hong Xu, Fangui Xu, Shan-Shan Xu, Song-Song Xu, Hailiang Xu, Quanzhong Xu, Mengqi Xu, Gezhi Xu, Dawei Xu, Linyan Xu, Meishu Xu, Yidan Xu, Tonghong Xu, Panpan Xu, Keli Xu, Xiufeng Xu, Hongwen Xu, Liang Xu, Hanyuan Xu, Zaoyi Xu, Fengqin Xu, Run-Xiang Xu, Xiaoyan Xu, Ruxiang Xu, Huiming Xu, Daqian Xu, Qin-Zhi Xu, Jiancheng Xu, Boming Xu, Zihao Xu, Jinghong Xu, Aimin Xu, Renfang Xu, Ran Xu, Di-Mei Xu, Xiang-liang Xu, Yana Xu, Richard H Xu, Yanchang Xu, Danyi Xu, Xiaocheng Xu, Lingli Xu, Chengqi Xu, Xiaoshuang Xu, H X Xu, Min Xu, Ya'nan Xu, Zhi Ping Xu, Zihe Xu, Hongle Xu, Xuan Xu, Jielin Xu, Yuping Xu, Limin Xu, Yinli Xu, Renshi Xu, Da Xu, C C Xu, Yongqing Xu, Heping Xu, Yiquan Xu, Weilan Xu, Jingjing Xu, Yangxian Xu, Yifan Xu, Congjian Xu, Binqiang Xu, Wentao Xu, Yuerong Xu, Jiaqi Xu, Shang-Fu Xu, Jiachi Xu, Yuejuan Xu, Zhi-Qing David Xu, Chao Xu, Yi-Xian Xu, Longfei Xu, Ziwei Xu, Mengyue Xu, Jingying Xu, Wenhui Xu, Zi-Xiang Xu, Caixia Xu, Chenjie Xu, Jiacheng Xu, Xiaoting Xu, Chunhui Xu, Chengxun Xu, Hengyi Xu, Songsong Xu, Lingyao Xu, Qingqiu Xu, Gangchun Xu, Yanjun Xu, Qiong Xu, Zifan Xu, Wenxuan Xu, Jiayunzhu Xu, Yifeng Xu, DongZhu Xu, Lingna Xu, Qianzhu Xu, Bocheng Xu, Qingjia Xu, Yanni Xu, Li-Yan Xu, Benhong Xu, Fang Xu, Geyang Xu, Xingsheng Xu, Anqi Xu, Zeao Xu, Mengsi Xu, Jun Xu, Qiuhong Xu, Ning'an Xu, Lian-Wei Xu, H F Xu, Hua Xu, Danping Xu, Xiaofang Xu, Shanshan Xu, Sheng-Qian Xu, Bingxin Xu, Ke Xu, Shiqing Xu, Cunshuan Xu, Guangwei Xu, Beibei Xu, Changwu Xu, Zhuangzhuang Xu, Chong-Feng Xu, Yunyi Xu, Yunxuan Xu, Zeya Xu, Jinshu Xu, Laizhi Xu, Xinyu Xu, Meiyu Xu, Bi-Yun Xu, Mingliang Xu, Bingfang Xu, Weixia Xu, Suling Xu, W W Xu, Lidan Xu, Chengkai Xu, Feng Xu, Yunhe Xu, Zesheng Xu, Song Xu, Li Xu, Yungen Xu, Yaobo Xu, Qinli Xu, Yi-Liang Xu, Tan Xu, Dong Xu, Ruiling Xu, Wanqi Xu, Ziyang Xu, Xiaohong Ruby Xu, Guangyu Xu, Xiao-Shan Xu, Wenxin Xu, Yongsheng Xu, Jingya Xu, Zhong-Hua Xu, Jiajie Xu, Dan Xu, Youjia Xu, Longsheng Xu, Mengjie Xu, Guo-Tong Xu, Ting Xu, Chunwei Xu, Tianmin Xu, Xianghong Xu, Nenggui Xu, Meixi Xu, Hongxia Xu, Rongying Xu, Guoliang Xu, Lisi Xu, Leisheng Xu, Xianli Xu, Yurui Xu, Yunfang Xu, Honglin Xu, Guo Xu, Shengyu Xu, Kelin Xu, Xiaoqin Xu, Zheng Xu, Junchang Xu, Jiaying Xu, Chunyu Xu, Zhen-Guo Xu, Beisi Xu, Haonan Xu, Tianyi Xu, Haiman Xu, Lili Xu, Yi Xu, Qihang Xu, Dongju Xu, Zihua Xu, Qikui Xu, Zhongwei Xu, Li-Jun Xu, Zhijie Xu, Hanchen Xu, Qi-Qi Xu, Yaqi Xu, Daohua Xu, Shaonian Xu, Xihui Xu, D Xu, Ziqi Xu, Tian-Ying Xu, Xiangbin Xu, Chen-Run Xu, Jianjuan Xu, Bin Xu, Zhanyu Xu, Lingjuan Xu, Wenjie Xu, Yu-Ming Xu, Shuwen Xu, Cian Xu, Qiulin Xu, Zeyu Xu, Jia Xu, Zengliang Xu, Yujie Xu, Yuting Xu, Jing-Yi Xu, Jiajia Xu, Xiqi Xu, Leiyu Xu, Shi-Na Xu, Ruonan Xu, Wenhuan Xu, Bai-Hui Xu, Jishu Xu, Xiangyu Xu, Lu-Lu Xu, Shiyun Xu, Huaxiang Xu, Lei Xu, Yuli Xu, Chan Xu, Tengfei Xu, Yong Xu, Xuejun Xu, Hang Xu, Junjie Xu, Jinjie Xu, Haoda Xu, Rui-Ming Xu, Yunxi Xu, Jinghua Xu, Ye Xu, Jiyi Xu, Jianyong Xu, Mei-Jun Xu, Yingzheng Xu, Kaiyue Xu, Yeqiu Xu, Songli Xu, Chenqi Xu, Cheng-Jian Xu, Qiaoshi Xu, Rongrong Xu, YanFeng Xu, Jin Xu, Huimian Xu, Zaikun Xu, Aixiao Xu, Yanfei Xu, Chunlin Xu, Dapeng Xu, Huiqiong Xu, Fengxia Xu, Yongmei Xu, Yubin Xu, Xiaojing Xu, Xiaoli Xu, Pu Xu, Wenming Xu, Wenjing Xu, Wenjuan Xu, Haijin Xu, Yawei Xu, Chuanrui Xu, Wenping Xu, Tongtong Xu, Zhigang Xu, Yinfeng Xu, Zi-Hua Xu, Jiean Xu, Ming Xu, Keshu Xu, Weili Xu, Guofeng Xu, Ai-Guo Xu, Xingyu Xu, Shujing Xu, Weiqun Xu, Wen-Hao Xu, Hong-wei Xu, Jianfeng Xu, Y Xu, Steven Jing-Liang Xu, Fangfang Xu, Xiao-Dan Xu, Keyun Xu, Yetao Xu, Qianhui Xu, Chaoqun Xu, Fenghuang Xu, Yuzhi Xu, Zelin Xu, Tengxiao Xu, Xueni Xu, Jing-Ying Xu, Yichi Xu, Ruifeng Xu, Kewei Xu, Jiapeng Xu, Fang-Fang Xu, Sifan Xu, Pengli Xu, Jiaqin Xu, Xiaotao Xu, Chunming Xu, X Xu, Gang Xu, Xinyin Xu, Wei Xu, Yuzhen Xu, Wancheng Xu, Qiming Xu, Hailey Xu, Xiaoming Xu, Yuanyuan Xu, Yimeng Xu, Shihao Xu, Zhipeng Xu, Minxuan Xu, Dilin Xu, Haowen Xu, Rui Xu, Jingzhou Xu, Qiongying Xu, Zhengshui Xu, Jinyi Xu, Q P Xu, Yongjian Xu, Qiushi Xu, Junfei Xu, Mengjun Xu, Hui Ming Xu, Xiaolei Xu, Yanzhe Xu, Qin Xu, Zichuan Xu, Xinyun Xu, Xiaoge Xu, Tianyu Xu, Lanjin Xu, Yigang Xu, Hongyan Xu, Guowang Xu, Jingjie Xu, Yangyang Xu, Yi-Huan Xu, Guanhua Xu, Hongrong Xu, Fen Xu, Jian Xu, Pin-Xian Xu, Tiantian Xu, Zhonghui Xu, Changfu Xu, Dong-Hui Xu, Yi-Ni Xu, Jialu Xu, Yuzhong Xu, Hongli Xu, Mingyuan Xu, Minghao Xu, Qinghua Xu, C F Xu, Yiting Xu, Jiahong Xu, Qian Xu, Haixiang Xu, Xizheng Xu, Kun Xu, Yunfei Xu, Xiaoyang Xu, Xiaojun Xu, Xinyuan Xu, Chen Xu, Guogang Xu, Jinguo Xu, Guiyun Xu, Lingyi Xu, Wenbin Xu, Chunjie Xu, Cheng-Bin Xu, Manman Xu, Dongke Xu, Jia-Mei Xu, Bing-E Xu, Lijiao Xu, You-Song Xu, Mengmeng Xu, Yu-Xin Xu, Jianwei Xu, Kuanfeng Xu, Chun Xu, Shiliyang Xu, Waner Xu, Zhiyao Xu, Gu-Feng Xu, Wenyuan Xu, J T Xu, Chaohua Xu, Haifeng Xu, Ling Xu, Lisha Xu, Huaisha Xu, Xiayun Xu, Qian-Fei Xu, Jinying Xu, Tengyun Xu, Chaoguang Xu, Fuyi Xu, Shihui Xu, Yingna Xu, Aishi Xu, Yanyan Xu, Bilian Xu, Qiuhui Xu, Jinsheng Xu, Qinwen Xu, Tianfeng Xu, Liyi Xu, Lihui Xu, Guanyi Xu, Wenyan Xu, Ru-xiang Xu, Zongzhen Xu, Nan Xu, Rui-Xia Xu, Jinxian Xu, Zhiting Xu, Jiaming Xu, Yi-Tong Xu, Shan-Rong Xu, Xiaojuan Xu, Guifa Xu, Xia-Jing Xu, Libin Xu, Dequan Xu, Guoxu Xu, Lubin Xu, Hong Xu, Cai Xu, Mengying Xu, Tian-Le Xu, J Xu, Weidong Xu, Chengbi Xu, Cong-jian Xu, Yibin Xu, Qianlan Xu, Tingting Xu, Caiqiu Xu, Hong-Yan Xu, Hanqian Xu, Xiao Le Xu, Bei Xu, Guanlan Xu, Jianxin Xu, Ming-Zhu Xu, Long Xu, Xiaopeng Xu, Yinjie Xu, Shufen Xu, Zhihua Xu, Ming-Jiang Xu, Di Xu, Qingwen Xu, Jiake Xu, Tingxuan Xu, Ping Xu, Peng-Ju Xu, Li-Zhi Xu, Shang-Rong Xu, Baoping Xu, Huan Xu, Wenwu Xu, Zhenyu Xu, Chong Xu, Sihua Xu, Anlong Xu, Lu Xu, Chen-Yang Xu, Xiaoyu Xu, Zhe Xu, Qiuyue Xu, Guangquan Xu, Peiyu Xu, Huihui Xu, Ding Xu, Yuchen Xu, Jianguo Xu, Lingyang Xu, Xuegong Xu, Jia-Yue Xu, Liping Xu, Yuling Xu, Yiyi Xu, Jianqiu Xu, Lichi Xu, Xiaojiang Xu, Xiao-Hui Xu, Mao Xu, Yuyang Xu, Zhaofa Xu, Qingchan Xu, Yanli Xu, Julie Xu, Minglan Xu, G Xu, Yali Xu, Miaomiao Xu, Yao Xu, Yanqi Xu, Tian Xu, Xiaojin Xu, Xiaowen Xu, Qing-Yang Xu, Lingxiang Xu, Jianguang Xu, Zhanchi Xu, Shiwen Xu, Haikun Xu, Hongbei Xu, Yixin Xu, Zhan Xu, Fangmin Xu, Xingshun Xu, Wenzhuo Xu, Fu Xu, Haimin Xu, Jiahui Xu, Shengtao Xu, Zhiwei Xu, Peiwei Xu, Daichao Xu, Wen-Hui Xu, Xingyan Xu, H Eric Xu, Zhi-Feng Xu, Mingming Xu, Hongtao Xu, Daiqi Xu, Keman Xu, Yinying Xu, Yuexin Xu, Yuanwei Xu, Jinfeng Xu, Xuanqi Xu, L Xu, Chunyan Xu, Hanting Xu, Chaoyu Xu, Shendong Xu, Tiancheng Xu, Guangsen Xu, Chentong Xu, Yaozeng Xu, Banglao Xu, Tao Xu, Danyan Xu, Ren-He Xu, Haiyan Xu, Jian-Guang Xu, Yu-Fen Xu, Youzhi Xu, Enwei Xu, Hui Xu, F F Xu, Zejun Xu, Ningda Xu, Li-Wei Xu, N Y Xu, Xiaoya Xu, Ren Xu, Ze-Jun Xu, Yanan Xu, Jiapei Xu, Peigang Xu, Tianxiang Xu, Haiqi Xu, Qing-Wen Xu, Junnv Xu, Tian-Rui Xu, Wanfu Xu, Wang-Hong Xu, Maotian Xu, Suoyu Xu, Mingli Xu, Qingqing Xu, Liwen Xu, Zhenming Xu, Jingyi Xu, Yihua Xu, Dong-Juan Xu, Mu Xu, Meifeng Xu, Dongmei Xu, Li-Ling Xu, Jianliang Xu, Pengfei Xu, Xinjie Xu, Changlin Xu, Shuai Xu, Yingli Xu, Fang-Yuan Xu, Ying Xu, Guo-Liang Xu, Zhiqiang Xu, Xirui Xu, Haiying Xu, Wen Xu, Wenwen Xu, Xiaoyin Xu, Mengping Xu, Jing-Yu Xu, Chunlan Xu, Danfeng Xu, Yuan Xu, Wenchun Xu, Zekuan Xu, Nuo Xu, Shuxiang Xu, Min Jie Xu, Penghui Xu, Zixuan Xu, Bingqi Xu, Hongen Xu, Zongli Xu, Tianli Xu, Bo Xu, Qingyuan Xu, Zhaojun Xu, Shuhua Xu, Min-Xuan Xu, Xu Xu, Runhao Xu, M Xu, Xiongfei Xu, Zhaoyao Xu, Yayun Xu, Yingju Xu, Guang-Qing Xu, Kaixiang Xu, Lingling Xu, Jiyu Xu, Anton Xu, Jason Xu, Donghang Xu, Xiaowu Xu, Fengzhe Xu, Xia Xu, Xiangshan Xu, Wan-Ting Xu, Fengyan Xu, Qingheng Xu, Changlu Xu, Huaiyuan Xu, Jinsong Xu, Dongchen Xu, Rang Xu, Peng-Yuan Xu, Jinyuan Xu, Weihong Xu, Wanxue Xu, Xinyi Xu, Jie Xu, Junfeng Xu, Danning Xu, Haiming Xu, Sutong Xu, Shan Xu, Meng Xu, Yueyue Xu, Jixuan Xu, Hongjian Xu, Zhidong Xu, Jinjin Xu, Xiaobo Xu, Hongmei Xu, Shu-Xian Xu, Chuang Xu, Shuaili Xu, Yun Xu, Zhixian Xu, Yue Xu, George X Xu, Man Xu, Jiaai Xu, Zeqing Xu, Baijie Xu, Zheng-Fan Xu, Bojie Xu, Mengru Xu, H Y Xu, Yinhe Xu, Linna Xu, Liqun Xu, Zhi-Zhen Xu, Xiaohui Xu, Xingmeng Xu, Pan Xu, Pengjie Xu, Kai Xu, Kexin Xu, Xiaolin Xu, Cun Xu, Yuxiang Xu, Tong Xu, Jingyu Xu, Li-Li Xu, Yancheng Xu, Chunxiao Xu, Yan Xu, Huajun Xu, Hongjiang Xu, Shuiyang Xu, Kaihao Xu, Suo-Wen Xu, Heng Xu, Zebang Xu, Hongbo Xu, Chenhao Xu, Fanghua Xu, Yaowen Xu, Jing Xu, Qianqian Xu, Andrew Z Xu, Flora Mengyang Xu, Yuanzhi Xu, Leilei Xu, Leyuan Xu, M-Y Xu, Hongzhi Xu, Zongren Xu, Xinyue Xu, Qingxia Xu, Cineng Xu, Xiao-Hua Xu, Nannan Xu, Guoshuai Xu, Mingzhu Xu, X S Xu, Guang Xu, Zhiyang Xu, Song-Hui Xu, Wang-Dong Xu, De-Xiang Xu, Yi Ran Xu, Shengen Xu, Jianzhong Xu, F Xu, Dexiang Xu, Rui-Hua Xu, Tongxin Xu, Wanting Xu, Bingqian Xu, Yang Xu, Jiaqian Xu, Yu-Ping Xu, Zhanqiong Xu, Haixia Xu, Hao Xu, HuiTing Xu, Hanfei Xu, Shu-Zhen Xu, Zhong Xu, Xun Xu, Xiaolu Xu, S Xu, Ning Xu, Guangyan Xu, Chengye Xu, Xizhan Xu, Ya-Peng Xu, Jianming Xu, Wenhao Xu, Minghong Xu, Mingqian Xu, Yaqin Xu, Chang-Qing Xu, Weiyong Xu, Huixuan Xu, Jialin Xu, Fei Xu, Z Xu, Pao Xu, Youping Xu, Keke Xu, Shunjiang Xu, Feilai Xu, Jia-Li Xu, Yucheng Xu, Qi Xu, Jinhua Xu, Chunli Xu, Zhiliang Xu, Jinxin Xu, Bingqing Xu, Lianjun Xu, Weihai Xu, Lifen Xu, Wenqi Xu, Zheng-Hong Xu, Lin Xu, Zuojun Xu, Yanquan Xu, Mingjie Xu, Hui-Lian Xu, Yanwu Xu, Dongjun Xu, Maodou Xu, Cong Xu, Rong Xu, Haoyang Xu, Shanhai Xu, Haoyu Xu, Yinglin Xu, Wenqing Xu, Jiali Xu, Changliu Xu, Xiaoke Xu, Feng-Xia Xu, Carrie Xu, Yuheng Xu, Shimeng Xu, Wanwan Xu, Weiming Xu, Gui-Ping Xu, Zhenzhou Xu, Yangbin Xu, Aohong Xu, Wenlong Xu, Jia-Xin Xu, Luyi Xu, Manyi Xu, Changde Xu, De Xu, Xinxuan Xu, Gaosi Xu, Baofeng Xu, Chang Xu, Wanhai Xu, Qing Xu, Zuyuan Xu, Pingwen Xu, Feng-Yuan Xu, Aoling Xu, Erping Xu, Shaoqi Xu, Zhicheng Xu, Lun-Shan Xu, Shiyao Sherrie Xu, Jianing Xu, Boqing Xu, Janfeng Xu, Yin Xu, Weijie Xu, Yu-Peng Xu, Ya-Nan Xu, Gaoyuan Xu, Iris M J Xu, Zhi Xu, Xiaomeng Xu, Mengyi Xu, Meifang Xu, Houxi Xu, Yuanfeng Xu, Shuqia Xu, Da-Peng Xu, Hong-tao Xu, Yaling Xu, Mei Xu, Xiaojiao Xu, Zhiru Xu, Weide Xu, Dandan Xu, W Xu, Shun Xu, Jianhua Xu, Tongda Xu, Lijun Xu, Cynthia M Xu, Yechun Xu, Xiao-Lin Xu, Ziye Xu, Xiaohan Xu, Guozheng Xu, Rongbin Xu, Nathan Xu, Wangdong Xu, Kailian Xu, Yongfeng Xu, Zhunan Xu, Jiawei Xu, Ruohong Xu, Yuhan Xu, Shanqi Xu, Shoujia Xu, T Xu, Weifeng Xu, Qiuyun Xu, Hu Xu, Yanming Xu, Hongwei Xu, Ziyu Xu, Kaishou Xu, Jian Hua Xu, Xin Xu, Liu Xu, Zetan Xu, Leiting Xu, Yong-Nan Xu, Houguo Xu, Zhizhen Xu, Ya-lin Xu, Xiang Xu, Suowen Xu, Xuejin Xu, Yiming Xu, Shude Xu, Genxing Xu, Yun-Teng Xu, Yanling Xu, Yuanhong Xu, Lijuan Xu, Xingzhi Xu, Guanghao Xu, Qiu-Han Xu, Siqun Xu, Wen-Xiong Xu, Qianghua Xu, Shuangbing Xu, Wenjun Xu, Jiangang Xu, Yangliu Xu, Jinjian Xu, W M Xu, Shanqiang Xu, Zefeng Xu
articles
Junfeng Zhang, Hongwei Tian, Can Li +15 more · 2022 · Molecular immunology · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.molimm.2021.11.006
IL27
Jialing Wang, Xiaodan Liu, Haixia Wang +10 more · 2022 · Cells · MDPI · added 2026-04-24
The histone demethylase JMJD1C is associated with human platelet counts. The JMJD1C knockout in zebrafish and mice leads to the ablation of megakaryocyte-erythroid lineage anemia. However, the specifi Show more
The histone demethylase JMJD1C is associated with human platelet counts. The JMJD1C knockout in zebrafish and mice leads to the ablation of megakaryocyte-erythroid lineage anemia. However, the specific expression, function, and mechanism of JMJD1C in megakaryopoiesis remain unknown. Here, we used cell line models, cord blood cells, and thrombocytopenia samples, to detect the JMJD1C expression. ShRNA of JMJD1C and a specific peptide agonist of JMJD1C, SAH-JZ3, were used to explore the JMJD1C function in the cell line models. The actin ratio in megakaryopoiesis for the JMJDC modulation was also measured. Mass spectrometry was used to identify the JMJD1C-interacting proteins. We first show the JMJD1C expression difference in the PMA-induced cell line models, the thrombopoietin (TPO)-induced megakaryocyte differentiation of the cord blood cells, and also the thrombocytopenia patients, compared to the normal controls. The ShRNA of JMJD1C and SAH-JZ3 showed different effects, which were consistent with the expression of JMJD1C in the cell line models. The effort to find the underlying mechanism of JMJD1C in megakaryopoiesis, led to the discovery that SAH-JZ3 decreases F-actin in K562 cells and increases F-actin in MEG-01 cells. We further performed mass spectrometry to identify the potential JMJD1C-interacting proteins and found that the important Ran GTPase interacts with JMJD1C. To sum up, JMJD1C probably regulates megakaryopoiesis by influencing the actin network. Show less
📄 PDF DOI: 10.3390/cells11223660
JMJD1C
Junchang Xu, Zijian Yan, Guihua Wu +3 more · 2022 · Journal of musculoskeletal & neuronal interactions · added 2026-04-24
The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs). GSE32317 and GSE55457 gene expression d Show more
The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs). GSE32317 and GSE55457 gene expression data were downloaded from the GEO database, and DEGs were discovered using R software to obtain overlapping DEGs. The interaction between overlapping DEGs was further analyzed by establishing the protein-protein interaction (PPI) network. Finally, GO and KEGG were used for enrichment analysis. 924 overlapping DEGs between postmenopausal women and men with osteoarthritis (OA) were identified, including 674 up-regulated genes and 249 down-regulated ones. And 10 hub genes were identified in the PPI network, including BMP4, KDM6A, JMJD1C, NFATC1, PRKX, SRF, ZFX, LAMTOR5, UFD1L and AMBN. The findings of the functional enrichment analysis suggested that these genes were predominantly expressed in MAPK signaling pathway as well as the Thyroid hormone signaling pathway, indicating that those two pathways may be involved in onset and disease progression of OA in postmenopausal patients. BMP4, KDM6A, JMJD1C, PRKX, ZFX and LAMTOR5 are expected to play crucial roles in disease development in postmenopausal patients and may be ideal targets or prognostic markers for the treatment of OA. Show less
JMJD1C
Daoxin Qi, Jialing Wang, Yao Zhao +7 more · 2022 · Leukemia & lymphoma · Taylor & Francis · added 2026-04-24
no PDF DOI: 10.1080/10428194.2022.2068004
JMJD1C
Xiaowen Xu, Xinying Bi, Jing Wang +4 more · 2022 · Journal of molecular medicine (Berlin, Germany) · Springer · added 2026-04-24
Developmental dysplasia of the hip (DDH) is a common anomaly leading to adult osteoarthritis. Environmental and genetic factors contribute to DDH, but its exact genetic mechanism is unclear. In this s Show more
Developmental dysplasia of the hip (DDH) is a common anomaly leading to adult osteoarthritis. Environmental and genetic factors contribute to DDH, but its exact genetic mechanism is unclear. In this study, we used whole exome sequencing to identify the causative gene of a DDH pedigree. A rare missense variant in KANSL1 (c.C767T; p.S256F) was identified as the pathogenic cause of DDH. Subsequent mutation screening showed another missense variant in 1 of 200 sporadic patients. Kansl1-mutated mice showed reduced chondrocytes in the acetabulum and a decrease in the cartilage matrix, which may be DDH phenotype-related abnormalities. Furthermore, functional studies showed that cell proliferation was delayed and Mmp13 expression was abnormally upregulated in chondrocytes differentiated from Kansl1 mutant mouse embryonic stem cells. In conclusion, our findings suggest that KANSL1 is a novel pathogenic gene for DDH. The identification of KANSL1 variants has great diagnostic value for identifying individuals with DDH. KEY MESSAGES: Developmental dysplasia of the hip (DDH) is a common anomaly causing adult osteoarthritis. Environmental and genetic factors contribute to DDH, but its exact genetic mechanism is unclear. Using high-throughput whole exome sequencing, we found a novel variant in KANSL1 that was co-inherited by all severely affected individuals diagnosed with DDH from a three-generation family. Further analysis revealed that a Kansl1 variant in mice reduced the number of chondrocytes and decreased cartilage matrix, and mouse embryonic stem differentiation assay showed cartilage defects. These findings indicate a direct association between KANSL1 and hip development, expanding the pathogenic gene spectrum in DDH and providing insight into potential new targets for diagnosing and treating hip dysplasia. Show less
no PDF DOI: 10.1007/s00109-022-02220-4
KANSL1
Ting Li, Dingyi Lu, Chengcheng Yao +25 more · 2022 · Nature communications · Nature · added 2026-04-24
no PDF DOI: 10.1038/s41467-022-29129-3
KANSL1
Ting Li, Dingyi Lu, Chengcheng Yao +25 more · 2022 · Nature communications · Nature · added 2026-04-24
Koolen-de Vries syndrome (KdVS) is a rare disorder caused by haploinsufficiency of KAT8 regulatory NSL complex subunit 1 (KANSL1), which is characterized by intellectual disability, heart failure, hyp Show more
Koolen-de Vries syndrome (KdVS) is a rare disorder caused by haploinsufficiency of KAT8 regulatory NSL complex subunit 1 (KANSL1), which is characterized by intellectual disability, heart failure, hypotonia, and congenital malformations. To date, no effective treatment has been found for KdVS, largely due to its unknown pathogenesis. Using siRNA screening, we identified KANSL1 as an essential gene for autophagy. Mechanistic study shows that KANSL1 modulates autophagosome-lysosome fusion for cargo degradation via transcriptional regulation of autophagosomal gene, STX17. Kansl1 Show less
📄 PDF DOI: 10.1038/s41467-022-28613-0
KANSL1
Yuen Tan, Qingchuan Chen, Siwei Pan +4 more · 2022 · BMC cancer · BioMed Central · added 2026-04-24
The Lauren classification of gastric tumors strongly correlates with prognosis. The purpose of this study was to explore the specific molecular mechanism of Lauren classification of gastric cancer and Show more
The Lauren classification of gastric tumors strongly correlates with prognosis. The purpose of this study was to explore the specific molecular mechanism of Lauren classification of gastric cancer and provide a possible theoretical basis for the treatment of gastric cancer. We standardized the gene expression data of five Gene Expression Omnibus gastric cancer databases and constructed a Weighted Co-expression Network Analysis (WGCNA) model based on clinicopathological information. The overall survival (OS) and disease-free survival (DFS) curves were extracted from the Cancer Genome Atlas (TCGA) and GSE62254 databases. Western blotting was used to measure protein expression in cells and tissues. Scratch and transwell experiments were used to test the migration ability of tumor cells. Immunohistochemistry was used to measure tissue protein expression in clinical tissue samples to correlate to survival data. The WGCNA model demonstrated that blue cyan was highly correlated with the Lauren classification of the tumor (r = 0.24, P = 7 × 10 LMOD1 is an oncogene associated with diffuse gastric cancer and can affect the occurrence and development of EMT by regulating the FAK-Akt/mTOR pathway. LMOD1 can therefore promote peritoneal metastasis of gastric cancer cells and can be used as a novel therapeutic target for gastric cancer. Show less
📄 PDF DOI: 10.1186/s12885-022-09541-0
LMOD1
Zhihao Chen, Ying Huai, Gaoyang Chen +18 more · 2022 · International journal of biological sciences · added 2026-04-24
Senile osteoporosis is one of the major health problems in an aging society. Decreased bone formation due to osteoblast dysfunction may be one of the causes of aging-related bone loss. With increasing Show more
Senile osteoporosis is one of the major health problems in an aging society. Decreased bone formation due to osteoblast dysfunction may be one of the causes of aging-related bone loss. With increasing evidence suggesting that multiple microRNAs (miRNAs) play important roles in osteoblast function, the relationship between miRNAs and senile osteoporosis has become a popular research topic. Previously, we confirmed that mechanoresponsive miR-138-5p negatively regulated bone anabolic action. In this study, the miR-138-5p level was found to be negatively correlated with BMD and osteogenic markers in bone specimens of senile osteoporotic patients by bioinformatic analysis and experimental verification. Furthermore, high miR-138-5p levels aggravated the decrease of aged osteoblast differentiation Show less
📄 PDF DOI: 10.7150/ijbs.71411
MACF1
Xuekui Liu, Huihui Xu, Ying Liu +4 more · 2022 · Diabetology & metabolic syndrome · BioMed Central · added 2026-04-24
Body mass index was intimately associated with islet function, which was affected by various confounding factors. Among all methods of statistical analysis, Mendelian randomization best ruled out bias Show more
Body mass index was intimately associated with islet function, which was affected by various confounding factors. Among all methods of statistical analysis, Mendelian randomization best ruled out bias to find the causal relationship. In the present study, we explored the relationship between 13 East Asian body mass index-related genes reported previously and islet function using the Mendelian randomization method. A total of 2892 participants residing in northern China were enrolled. Anthropological information, such as sex, age, drinking status, smoking status, weight, height and blood pressure, was recorded for all participants. Fasting glucose and insulin were detected, and the insulin sensitivity index was calculated. 13 single nucleotide polymorphismss in East Asian body mass index -related genes were analysed with the ABI7900HT system. Five genetic locus mutations, CDKAL1, MAP2K5, BDNF, FTO and SEC16B, were found to be associated with body mass index and were used to estimate the genetic risk score. We found that the genetic risk score was negatively associated with the insulin sensitivity index. Even after adjusted of confounding factors, the relationship showed statistical significance. A subsequent interaction effect analysis suggested that the negative relationship between the genetic risk score and insulin sensitivity index no longer existed in the nondrinking population, and smokers had a stronger negative relationship than nonsmokers. We found a negative causal relationship between body mass index-related genetic locus mutations and insulin resistance, which might be increased by acquired lifestyle factors, such as drinking and smoking status. Show less
📄 PDF DOI: 10.1186/s13098-022-00828-7
MAP2K5
Chunhua Liu, Wei Zhang, Guozheng Xu +5 more · 2022 · FASEB journal : official publication of the Federation of American Societies for Experimental Biology · added 2026-04-24
The risk of high-grade gliomas is lower in young females, however, its incidence enhances after menopause, suggesting potential protective roles of female sex hormones. Hormone oscillations after meno Show more
The risk of high-grade gliomas is lower in young females, however, its incidence enhances after menopause, suggesting potential protective roles of female sex hormones. Hormone oscillations after menopause have received attention as a possible risk factor. Little is known about risk factors for adult gliomas. We examined the association of the aging brain after menopause, determining the risk of gliomas with proteomics and the MALDI-MSI experiment. Menopause caused low neurotransmitter levels such as GABA and ACH, high inflammatory factor levels like il-1β, and increased lipid metabolism-related levels like triglycerides in the brain. Upregulated and downregulated proteins after menopause were correlated with differentially expressed glioma genes, such as ACTA2, CAMK2D, FNBPIL, ARL1, HEBP1, CAST, CLIC1, LPCAT4, MAST3, and DOCK9. Furthermore, differential gene expression analysis of monocytes showed that the downregulated gene LPCAT4 could be used as a marker to prevent menopausal gliomas in women. Our findings regarding the association of menopause with the risk of gliomas are consistent with several extensive cohort studies. In view of the available evidence, postmenopausal status is likely to represent a significant risk factor for gliomas. Show less
no PDF DOI: 10.1096/fj.202200427RR
MAST3
Yu Jiang, Travis J Meyers, Adaeze A Emeka +94 more · 2022 · HGG advances · Elsevier · added 2026-04-24
Yu Jiang, Travis J Meyers, Adaeze A Emeka, Lauren Folgosa Cooley, Phillip R Cooper, Nicola Lancki, Irene Helenowski, Linda Kachuri, Daniel W Lin, Janet L Stanford, Lisa F Newcomb, Suzanne Kolb, Antonio Finelli, Neil E Fleshner, Maria Komisarenko, James A Eastham, Behfar Ehdaie, Nicole Benfante, Christopher J Logothetis, Justin R Gregg, Cherie A Perez, Sergio Garza, Jeri Kim, Leonard S Marks, Merdie Delfin, Danielle Barsa, Danny Vesprini, Laurence H Klotz, Andrew Loblaw, Alexandre Mamedov, S Larry Goldenberg, Celestia S Higano, Maria Spillane, Eugenia Wu, H Ballentine Carter, Christian P Pavlovich, Mufaddal Mamawala, Tricia Landis, Peter R Carroll, June M Chan, Matthew R Cooperberg, Janet E Cowan, Todd M Morgan, Javed Siddiqui, Rabia Martin, Eric A Klein, Karen Brittain, Paige Gotwald, Daniel A Barocas, Jeremiah R Dallmer, Jennifer B Gordetsky, Pam Steele, Shilajit D Kundu, Jazmine Stockdale, Monique J Roobol, Lionne D F Venderbos, Martin G Sanda, Rebecca Arnold, Dattatraya Patil, Christopher P Evans, Marc A Dall'Era, Anjali Vij, Anthony J Costello, Ken Chow, Niall M Corcoran, Soroush Rais-Bahrami, Courtney Phares, Douglas S Scherr, Thomas Flynn, R Jeffrey Karnes, Michael Koch, Courtney Rose Dhondt, Joel B Nelson, Dawn McBride, Michael S Cookson, Kelly L Stratton, Stephen Farriester, Erin Hemken, Walter M Stadler, Tuula Pera, Deimante Banionyte, Fernando J Bianco, Isabel H Lopez, Stacy Loeb, Samir S Taneja, Nataliya Byrne, Christopher L Amling, Ann Martinez, Luc Boileau, Franklin D Gaylis, Jacqueline Petkewicz, Nicholas Kirwen, Brian T Helfand, Jianfeng Xu, Denise M Scholtens, William J Catalona, John S Witte Show less
Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prosta Show more
Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion ( Show less
📄 PDF DOI: 10.1016/j.xhgg.2021.100070
MAST3
Xiwen Guan, Shuanping Zhao, Weixuan Xiang +5 more · 2022 · Biology · MDPI · added 2026-04-24
Dabieshan cattle are a typical breed of southern Chinese cattle that have the characteristics of muscularity, excellent meat quality and tolerance to temperature and humidity. Based on 148 whole-genom Show more
Dabieshan cattle are a typical breed of southern Chinese cattle that have the characteristics of muscularity, excellent meat quality and tolerance to temperature and humidity. Based on 148 whole-genome data, our analysis disclosed the ancestry components of Dabieshan cattle with Chinese indicine (0.857) and East Asian taurine (0.139). The Dabieshan genome demonstrated a higher genomic diversity compared with the other eight populations, supported by the observed nucleotide diversity, linkage disequilibrium decay and runs of homozygosity. The candidate genes were detected by a selective sweep, which might relate to the fertility ( Show less
📄 PDF DOI: 10.3390/biology11091327
MLLT10
Yunqiang He, Qi Fu, Min Sun +11 more · 2022 · Clinical and translational medicine · Wiley · added 2026-04-24
Acetylcholine (ACh) and norepinephrine (NE) are representative neurotransmitters of parasympathetic and sympathetic nerves, respectively, that antagonize each other to coregulate internal body functio Show more
Acetylcholine (ACh) and norepinephrine (NE) are representative neurotransmitters of parasympathetic and sympathetic nerves, respectively, that antagonize each other to coregulate internal body functions. This also includes the control of different kinds of hormone secretion from pancreatic islets. However, the molecular mechanisms have not been fully elucidated, and whether innervation in islets is abnormal in diabetes mellitus also remains unclear. Immunofluorescence colocalization and islet perfusion were performed and the results demonstrated that ACh/NE and their receptors were highly expressed in islet and rapidly regulated different hormones secretion. Phosphorylation is considered an important posttranslational modification in islet innervation and it was identified by quantitative proteomic and phosphoproteomic analyses in this study. The phosphorylated islet proteins were found involved in many biological and pathological processes, such as synaptic signalling transduction, calcium channel opening and insulin signalling pathway. Then, the kinases were predicted by motif analysis and further screened and verified by kinase-specific siRNAs in different islet cell lines (αTC1-6, Min6 and TGP52). After functional verification, Ksr2 and Pkacb were considered the key kinases of ACh and NE in insulin secretion, and Cadps, Mlxipl and Pdcd4 were the substrates of these kinases measured by immunofluorescence co-staining. Then, the decreased expression of receptors, kinases and substrates of ACh and NE were found in diabetic mice and the aberrant rhythm in insulin secretion could be improved by combined interventions on key receptors (M3 (pilocarpine) or α2a (guanfacine)) and kinases (Ksr2 or Pkacb). Abnormal innervation was closely associated with the degree of islet dysfunction in diabetic mice and the aberrant rhythm in insulin secretion could be ameliorated significantly after intervention with key receptors and kinases in the early stage of diabetes mellitus, which may provide a promising therapeutic strategy for diabetes mellitus in the future. Show less
📄 PDF DOI: 10.1002/ctm2.890
MLXIPL

A Novel

Y Peng, J Xu, Y Wang +7 more · 2022 · Balkan journal of medical genetics : BJMG · added 2026-04-24
Cardiomyopathies are a heterogeneous group of diseases predominantly affecting the heart muscle and often lead to progressive heart failure-related disability or cardiovascular death. Hypertrophic car Show more
Cardiomyopathies are a heterogeneous group of diseases predominantly affecting the heart muscle and often lead to progressive heart failure-related disability or cardiovascular death. Hypertrophic cardiomyopathy (HCM) is a cardiac muscle disorder mostly caused by the mutations in genes encoding cardiac sarcomere. Germ-line mutations in Show less
📄 PDF DOI: 10.2478/bjmg-2022-0002
MYBPC3
Cheng Shen, Lei Xu, Xiaoning Sun +2 more · 2022 · Annals of translational medicine · added 2026-04-24
Multiple genes have been associated with familial dilated cardiomyopathy (DCM). However, the role of genetic factors in sporadic DCM (SDCM) remains unclear. Therefore, we studied the genetic variation Show more
Multiple genes have been associated with familial dilated cardiomyopathy (DCM). However, the role of genetic factors in sporadic DCM (SDCM) remains unclear. Therefore, we studied the genetic variations in Chinese patients with SDCM. Sixty-six unrelated Chinese patients (mean age 49.1±17.0 years; 71% male) diagnosed with SDCM were enrolled. The clinical history and genomic DNA of the cohort were collected and examined. The exons of 24 genes closely associated with familial DCM ( Eighty-five nonsynonymous variants were detected in 17 genes. The variants and their occurrence frequencies in the patients were compared against population data from the 1000 Genomes and NHLBI (National Heart, Lung, and Blood Institute) Go Exome Sequencing Project. Forty-nine nonsynonymous variants had occurrence frequencies that were significantly higher in the study patients than in the general population, indicating that they have the potential to increase the risk of DCM. The risk variants were distributed in 40 (61%) patients, among whom 25 carried a single variant, while the remaining patients carried multiple (2 to 4) variants. Risk variants occurred more frequently in We found that genetic variants with potential risk for DCM were commonly present in SDCM patients, indicating that genetic factors contribute to the pathogenesis, and (probably) the onset, of DCM in these patients. Show less
📄 PDF DOI: 10.21037/atm-21-6774
MYBPC3
Yu Zhang, Yuming Zhu, Mo Zhang +9 more · 2022 · European heart journal. Quality of care & clinical outcomes · Oxford University Press · added 2026-04-24
In the clinical practice, the right ventricular (RV) manifestations have received less attention in hypertrophic cardiomyopathy (HCM). This paper aimed to evaluate the risk prediction value and geneti Show more
In the clinical practice, the right ventricular (RV) manifestations have received less attention in hypertrophic cardiomyopathy (HCM). This paper aimed to evaluate the risk prediction value and genetic characteristics of RV involvement in HCM patients. A total of 893 patients with HCM were recruited. RV hypertrophy, RV obstruction, and RV late gadolinium enhancement were evaluated by echocardiography and/or cardiac magnetic resonance. Patients with any of the above structural abnormalities were identified as having RV involvement. All patients were followed with a median follow-up time of 3.0 years. The primary endpoint was cardiovascular death; the secondary endpoints were all-cause death and heart failure (HF)-related death. Survival analyses were conducted to evaluate the associations between RV involvement and the endpoints. Genetic testing was performed on 669 patients. RV involvement was recognized in 114 of 893 patients (12.8%). Survival analyses demonstrated that RV involvement was an independent risk factor for cardiovascular death (P = 0.002), all-cause death (P = 0.011), and HF-related death (P = 0.004). These outcome results were then confirmed by a sensitivity analysis. Genetic testing revealed a higher frequency of genotype-positive in patients with RV involvement (57.0% vs. 31.0%, P < 0.001), and the P/LP variants of MYBPC3 were more frequently identified in patients with RV involvement (30.4% vs. 12.0%, P < 0.001). Logistic analyses indicated the independent correlation between RV involvement and these genetic factors. RV involvement was an independent risk factor for cardiovascular death, all-cause death and HF-related death in HCM patients. Genetic factors might contribute to RV involvement in HCM. Show less
no PDF DOI: 10.1093/ehjqcco/qcac008
MYBPC3
Ge Chen, Ge Wang, Weidong Xu +2 more · 2022 · Frontiers in nutrition · Frontiers · added 2026-04-24
Chlorantraniliprole is a diamide insecticide widely used in agriculture. Chlorantraniliprole has been previously found to increase the accumulation of triglycerides (fats) in adipocytes, however, the Show more
Chlorantraniliprole is a diamide insecticide widely used in agriculture. Chlorantraniliprole has been previously found to increase the accumulation of triglycerides (fats) in adipocytes, however, the underlying molecular mechanism is unknown. The present study aimed to explore the molecular mechanisms of chlorantraniliprole-induced fat accumulation in 3T3-L1 adipocytes. We measured the triglyceride content in chlorantraniliprole-treated 3T3-L1 adipocytes, and collected cell samples treated with chlorantraniliprole for 24 h and without any treatment for RNA sequencing. Compared with the control group, the content of triglyceride in the treatment group of chlorantraniliprole was significantly increased. The results of RNA sequencing (RNA-seq) showed that 284 differentially expressed genes (DEGs) were identified after treatment with chlorantraniliprole, involving 39 functional groups of gene ontology (GO) and 213 KEGG pathways. Moreover, these DEGs were significantly enriched in several key genes that regulate adipocyte differentiation and lipogenesis including In general, these results suggest that chlorantraniliprole-induced lipogenesis is attributed to a whole-gene transcriptome response, which promotes further understanding of the potential mechanism of chlorantraniliprole-induced adipogenesis. Show less
no PDF DOI: 10.3389/fnut.2022.1091477
NR1H3
Qing-Bing Zhou, Yao Chen, Yan Zhang +6 more · 2022 · Journal of inflammation research · added 2026-04-24
To investigate if a traditional Chinese medicine formulation, called "Yiqihuoxue" (YQHX), could improve diabetic atherosclerosis (DA) and explore potential mechanisms based on DNA methylation. Apolipo Show more
To investigate if a traditional Chinese medicine formulation, called "Yiqihuoxue" (YQHX), could improve diabetic atherosclerosis (DA) and explore potential mechanisms based on DNA methylation. Apolipoprotein E-knockout mice were administered streptozotocin (50 mg/d, i.p.) for 5 days and fed a high-fat diet for 16 weeks. Mice were divided randomly into DA model, rosiglitazone, as well as low-, medium-, and high-dose YQHX groups. Ten healthy C57BL/6J mice were the control group. Serum levels of fasting insulin, blood glucose, homeostasis model-insulin resistance index (HOMA-IR), serum lipids, and inflammatory factors were analyzed after the final treatment. Aorta tissues were collected for staining (hematoxylin and eosin, and Oil red O). Genomic DNA was extracted for methyl-capture sequencing (MC-seq). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) databases were used to analyze differentially methylated genes. Pyrosequencing was used to verify MC-seq data. Low-dose and high-dose YQHX could reduce the HOMA-IR ( YQHX decoction had positive treatment effects against DA, because it could regulate aberrant hypomethylation of DNA. Show less
no PDF DOI: 10.2147/JIR.S335374
NR1H3
Jing Yue, Kai Su, Guangxin Zhang +3 more · 2022 · Inflammation · Springer · added 2026-04-24
Dihydrotanshinone (DIH) is an extract of Salvia miltiorrhiza Bunge. It has been reported that DIH could regulate NF-κB signaling pathway. The aim of this study was to investigate whether DIH could pro Show more
Dihydrotanshinone (DIH) is an extract of Salvia miltiorrhiza Bunge. It has been reported that DIH could regulate NF-κB signaling pathway. The aim of this study was to investigate whether DIH could protect mice from lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice. In this study, sixty mice were randomly divided into five groups, one group as blank control group, the second group as LPS control group, and the last three groups were pre-injected with different doses of DIH and then inhaled LPS for experimental comparison. After 12 h of LPS treatment, the wet-dry ratio, histopathlogical changes, and myeloperoxidase (MPO) activity of lungs were measured. In addition, ELISA kits were used to measure the levels of TNF-α and IL-1β inflammatory cytokines in bronchoalveolar lavage fluids (BALF), and western blot analysis was used to measure the activity of NF-κB signaling pathway. The results demonstrated that DIH could effectively reduce pulmonary edema, MPO activity, and improve the lung histopathlogical changes. Furthermore, DIH suppressed the levels of inflammatory cytokines in BALF, such as TNF-α and IL-1β. In addition, DIH could also downregulate the activity of NF-κB signaling pathway. We also found that DIH dose-dependently increased the expression of LXRα. In addition, DIH could inhibit LPS-induced IL-8 production and NF-κB activation in A549 cells. And the inhibitory effects were reversed by LXRα inhibitor geranylgeranyl pyrophosphate (GGPP). Therefore, we speculate that DIH regulates LPS-induced ALI in mice by increasing LXRα expression, which subsequently inhibiting NF-κB signaling pathway. Show less
no PDF DOI: 10.1007/s10753-021-01539-3
NR1H3
Xuechen Zhu, Gaoxingyu Huang, Chao Zeng +12 more · 2022 · Science (New York, N.Y.) · Science · added 2026-04-24
INTRODUCTION The nuclear pore complex (NPC) resides on the nuclear envelope (NE) and mediates nucleocytoplasmic cargo transport. As one of the largest cellular machineries, a vertebrate NPC consists o Show more
INTRODUCTION The nuclear pore complex (NPC) resides on the nuclear envelope (NE) and mediates nucleocytoplasmic cargo transport. As one of the largest cellular machineries, a vertebrate NPC consists of cytoplasmic filaments, a cytoplasmic ring (CR), an inner ring, a nuclear ring, a nuclear basket, and a luminal ring. Each NPC has eight repeating subunits. Structure determination of NPC is a prerequisite for understanding its functional mechanism. In the past two decades, integrative modeling, which combines x-ray structures of individual nucleoporins and subcomplexes with cryo-electron tomography reconstructions, has played a crucial role in advancing our knowledge about the NPC. The CR has been a major focus of structural investigation. The CR subunit of human NPC was reconstructed by cryo-electron tomography through subtomogram averaging to an overall resolution of ~20 Å, with local resolution up to ~15 Å. Each CR subunit comprises two Y-shaped multicomponent complexes known as the inner and outer Y complexes. Eight inner and eight outer Y complexes assemble in a head-to-tail fashion to form the proximal and distal rings, respectively, constituting the CR scaffold. To achieve higher resolution of the CR, we used single-particle cryo-electron microscopy (cryo-EM) to image the intact NPC from the NE of Show less
no PDF DOI: 10.1126/science.abl8280
NUP160
Jing Wang, Sami Ullah Khan, Pan Cao +17 more · 2022 · Life (Basel, Switzerland) · MDPI · added 2026-04-24
As a member of the PIKs family, PIK3C3 participates in autophagy and plays a central role in liver function. Several studies demonstrated that the complete suppression of PIK3C3 in mammals can cause h Show more
As a member of the PIKs family, PIK3C3 participates in autophagy and plays a central role in liver function. Several studies demonstrated that the complete suppression of PIK3C3 in mammals can cause hepatomegaly and hepatosteatosis. However, the function of PIK3C3 overexpression on the liver and other organs is still unknown. In this study, we successfully generated PIK3C3 transgenic pigs through somatic cell nuclear transfer (SCNT) by designing a specific vector for the overexpression of PIK3C3. Plasmid identification was performed through enzyme digestion and transfected into the fetal fibroblasts derived from Show less
no PDF DOI: 10.3390/life12050630
PIK3C3
Haifeng Zhang, Houyi Sun, Wei Zhang +2 more · 2022 · Journal of inflammation research · added 2026-04-24
Osteoarthritis (OA) is a degenerative joint disease that acts as a major cause of early disability in the old population. However, the molecular mechanisms of autophagy in osteoclasts involved in OA r Show more
Osteoarthritis (OA) is a degenerative joint disease that acts as a major cause of early disability in the old population. However, the molecular mechanisms of autophagy in osteoclasts involved in OA remain unclear. The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) repository. The NCBI GEO2R and ScanGEO analysis tool were used to identify differentially expressed genes (DEGs). The protein-protein interaction (PPI) network was predicted by the STRING website and visualized with Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed to enrich GO terms and signaling pathways using Metascape database. To predict LC3-interacting region (LIR) motif among these DEGs, the iLIR database was selected to assess specific short linear sequences. To obtain potential upstream miRNA targets of these DEGs, the mRNA-miRNA interaction networks were predicted by miRWalk database. The knee OA model was performed in mice, and autophagy related mRNAs of osteoclasts were identified. Experimental specimens were further verified with histopathological staining. Our results reveal that the role of autophagy in osteoclasts could be a regulatory mechanism in OA and that these autophagy-related genes might be targets for the intervention of OA disease. Show less
no PDF DOI: 10.2147/JIR.S354824
PIK3C3
Lijia Yang, Ying Chen, Liang Xu +13 more · 2022 · Molecular plant · Elsevier · added 2026-04-24
Plants have evolved a sophisticated set of mechanisms to adapt to drought stress. Transcription factors play crucial roles in plant responses to various environmental stimuli by modulating the express Show more
Plants have evolved a sophisticated set of mechanisms to adapt to drought stress. Transcription factors play crucial roles in plant responses to various environmental stimuli by modulating the expression of numerous stress-responsive genes. However, how the crosstalk between different transcription factor families orchestrates initiation of the key transcriptional network and the role of posttranscriptional modification of transcription factors, especially in cellular localization/trafficking in response to stress in rice, remain still largely unknown. In this study, we isolated an Osmybr57 mutant that displays a drought-sensitive phenotype through a genetic screen for drought stress sensitivity. We found that OsMYBR57, an MYB-related protein, directly regulates the expression of several key drought-related OsbZIPs in response to drought treatment. Further studies revealed that OsMYBR57 interacts with a homeodomain transcription factor, OsHB22, which also plays a positive role in drought signaling. We further demonstrate that OsFTIP6 interacts with OsHB22 and promotes the nucleocytoplasmic translocation of OsHB22 into the nucleus, where OsHB22 cooperates with OsMYBR57 to regulate the expression of drought-responsive genes. Our findings have revealed a mechanistic framework underlying the OsFTIP6-OsHB22-OsMYBR57 module-mediated regulation of drought response in rice. The OsFTIP6-mediated OsHB22 nucleocytoplasmic shuttling and OsMYBR57-OsHB22 regulation of OsbZIP transcription ensure precise control of expression of OsLEA3 and Rab21, and thereby regulate the response to water deficiency in rice. Show less
no PDF DOI: 10.1016/j.molp.2022.06.003
RAB21
Lu-Jie Huang, Qiao-Xia Zhang, Robert K Valenzuela +3 more · 2022 · Biochemistry and biophysics reports · Elsevier · added 2026-04-24
Hypertension is a leading risk factor of cardiovascular disease and mortality in the population worldwide. Recently, hundreds of genomic loci were reported for hypertension by GWAS, however, the most Show more
Hypertension is a leading risk factor of cardiovascular disease and mortality in the population worldwide. Recently, hundreds of genomic loci were reported for hypertension by GWAS, however, the most SNPs are located in intergenic regions of genome, where a functional cause is difficult to determine. In the current study, a TWAS of hypertension was conducted using 452,264 individuals including 84,640 patients. KEGG and GO enrichment analyses were performed for the hypertension-related genes identified via TWAS. PPI network analysis based on the STRING database was also performed to detect TWAS-identified genes in hypertension. We have identified 18,420 genes from the GWAS summary data, and of those 1010 non-overlapping genes expression were significantly associated with hypertension after FDR correction (PFDR <0.05) in four tissues (left heart ventricle, aorta, whole blood, and peripheral blood). The KEGG and GO terms were mostly related to autoimmune mechanisms, and the autoimmune-related pathways have also been enriched using GO analysis for PPI genes. We further performed Mendelian randomization analysis, and the results supported a significant association between autoimmunity and hypertension. Moreover, 15 novel hypertension-susceptible genes were identified in all tissues, and five of the genes ( Show less
no PDF DOI: 10.1016/j.bbrep.2022.101387
RBM6
Caitlin R Davies, Tianyu Guo, Edwina Burke +18 more · 2022 · Frontiers in oncology · Frontiers · added 2026-04-24
Docetaxel improves overall survival (OS) in castration-resistant prostate cancer (PCa) (CRPC) and metastatic hormone-sensitive PCa (mHSPC). However, not all patients respond due to inherent and/or acq Show more
Docetaxel improves overall survival (OS) in castration-resistant prostate cancer (PCa) (CRPC) and metastatic hormone-sensitive PCa (mHSPC). However, not all patients respond due to inherent and/or acquired resistance. There remains an unmet clinical need for a robust predictive test to stratify patients for treatment. Liquid biopsy of circulating tumour cell (CTCs) is minimally invasive, can provide real-time information of the heterogeneous tumour and therefore may be a potentially ideal docetaxel response prediction biomarker. In this study we investigate the potential of using CTCs and their gene expression to predict post-docetaxel tumour response, OS and progression free survival (PFS). Peripheral blood was sampled from 18 mCRPC and 43 mHSPC patients, pre-docetaxel treatment, for CTC investigation. CTCs were isolated using the epitope independent Parsortix Detection of CTCs pre-docetaxel was associated with poor patient outcome post-docetaxel treatment. Combining total-CTC number with PSA and ALP predicted lack of partial response (PR) with an AUC of 0.90, p= 0.037 in mCRPC. A significantly shorter median OS was seen in mCRPC patients with positive CTC-score (12.80 vs. 37.33 months, HR= 5.08, p= 0.0005), ≥3 total-CTCs/7.5mL (12.80 vs. 37.33 months, HR= 3.84, p= 0.0053), ≥1 epithelial-CTCs/7.5mL (14.30 vs. 37.33 months, HR= 3.89, p= 0.0041) or epithelial to mesenchymal transitioning (EMTing)-CTCs/7.5mL (11.32 vs. 32.37 months, HR= 6.73, p= 0.0001). Significantly shorter PFS was observed in patients with ≥2 epithelial-CTCs/7.5mL (7.52 vs. 18.83 months, HR= 3.93, p= 0.0058). mHSPC patients with ≥5 CTCs/7.5mL had significantly shorter median OS (24.57 vs undefined months, HR= 4.14, p= 0.0097). In mHSPC patients, expression of While it is clear that CTC numbers and gene expression were prognostic for PCa post-docetaxel treatment, and CTC subtype analysis may have additional value, their potential predictive value for docetaxel chemotherapy response needs to be further investigated in large patient cohorts. Show less
no PDF DOI: 10.3389/fonc.2022.1060864
SNAI1
Yanping Liang, Junjie Cen, Yong Huang +11 more · 2022 · Molecular cancer · BioMed Central · added 2026-04-24
Recent studies have identified that circular RNAs (circRNAs) have an important role in cancer via their well-recognized sponge effect on miRNAs, which regulates a large variety of cancer-related genes Show more
Recent studies have identified that circular RNAs (circRNAs) have an important role in cancer via their well-recognized sponge effect on miRNAs, which regulates a large variety of cancer-related genes. However, only a few circRNAs have been well-studied in renal cell carcinoma (RCC) and their regulatory function remains largely elusive. Bioinformatics approaches were used to characterize the differentially expressed circRNAs in our own circRNA-sequencing dataset, as well as two public circRNA microarray datasets. CircNTNG1 (hsa_circ₀₀₀₂₂₈₆₎ was identified as a potential tumor-suppressing circRNA. Transwell assay and CCK-8 assay were used to assess phenotypic changes. RNA pull-down, luciferase reporter assays and FISH experiment were used to confirm the interactions among circNTNG1, miR-19b-3p, and HOXA5 mRNA. GSEA was performed to explore the downstream pathway regulated by HOXA5. Immunoblotting, chromatin immunoprecipitation, and methylated DNA immunoprecipitation were used to study the mechanism of HOXA5. In all three circRNA datasets, circNTNG1, which was frequently deleted in RCC, showed significantly low expression in the tumor group. The basic properties of circNTNG1 were characterized, and phenotype studies also demonstrated the inhibitory effect of circNTNG1 on RCC cell aggressiveness. Clinically, circNTNG1 expression was associated with RCC stage and Fuhrman grade, and it also served as an independent predictive factor for both OS and RFS of RCC patients. Next, the sponge effect of circNTNG1 on miR-19b-3p and the inhibition of HOXA5 by miR-19b-3p were validated. GSEA analysis indicated that HOXA5 could inactivate the epithelial-mesenchymal transition (EMT) process, and this inactivation was mediated by HOXA5-induced SNAI2 (Slug) downregulation. Finally, it was confirmed that the Slug downregulation was caused by HOXA5, along with the DNA methyltransferase DNMT3A, binding to its promoter region and increasing the methylation level. Based on the experimental data, in RCC, circNTNG1/miR-19b-3p/HOXA5 axis can regulate the epigenetic silencing of Slug, thus interfering EMT and metastasis of RCC. Together, our findings provide potential biomarkers and novel therapeutic targets for future study in RCC. Show less
no PDF DOI: 10.1186/s12943-022-01694-7
SNAI1
Wei Xu, Linna Chen, Jiheng Liu +8 more · 2022 · Cell death & disease · Nature · added 2026-04-24
Lung adenocarcinoma (LUAD) is one of the main causes of cancer-related mortality, with a strong tendency to metastasize early. Transforming growth factor-β (TGF-β) signaling is a powerful regulator to Show more
Lung adenocarcinoma (LUAD) is one of the main causes of cancer-related mortality, with a strong tendency to metastasize early. Transforming growth factor-β (TGF-β) signaling is a powerful regulator to promote metastasis of LUAD. Here, we screened long non-coding RNAs (lncRNAs) responsive to TGF-β and highly expressed in LUAD cells, and finally obtained our master molecular LINC00152. We proved that the TGF-β promoted transcription of LINC00152 through the classical TGF-β/SMAD3 signaling pathway and maintained its stability through the RNA-binding protein HuR. Moreover, LINC00152 increased ZEB1, SNAI1 and SNAI2 expression via increasing the interactions of HuR and these transcription factors, ultimately promoting epithelial-mesenchymal transition of LUAD cell and enhancing LUAD metastasis in vivo. These data provided evidence that LINC00152 induced by TGF-β promotes metastasis depending HuR in lung adenocarcinoma. Designing targeting LINC00152 and HuR inhibitors may therefore be an effective therapeutic strategy for LUAD treatment. Show less
no PDF DOI: 10.1038/s41419-022-05164-2
SNAI1
Rong Li, Runze Shang, Shunle Li +7 more · 2022 · Environmental toxicology · Wiley · added 2026-04-24
Lysyl-oxidase-like 3 (LOXL3) was reported to be essential in epithelial-mesenchymal transition (EMT) of cancers. However, the role of LOXL3 in hepatocellular carcinoma (HCC) remained unclear. In this Show more
Lysyl-oxidase-like 3 (LOXL3) was reported to be essential in epithelial-mesenchymal transition (EMT) of cancers. However, the role of LOXL3 in hepatocellular carcinoma (HCC) remained unclear. In this study, we explored clinical significance, biological functions, and regulatory mechanisms of LOXL3 in HCC. Our study found that LOXL3 expression was markedly associated with the tumor size and clinical stage of HCC, and it was highly expressed in tumor tissues of metastatic HCC patients. High expression of LOXL3 predicted a poor prognosis of HCC. TGF-β1 treatment elevated LOXL3 protein expression and cell invasion, and reduced cell apoptosis in HCC cell lines (SMMC-7721 and Huh-7), while downregulation of LOXL3 reversed the promotive effects of TGF-β1 treatment on LOXL3 protein expression and cell invasion, and the inhibitory effect on cell apoptosis. Mechanistically, LOXL3 interacted with snail family transcriptional repressor 1 (Snail1) through STRING database and RIP assay, and Snail1 bound to ubiquitin-specific peptidase 4 (USP4) promoter by JASPAR database, luciferase reporter gene and Co-IP assays. Overexpression of USP4 reversed the inhibitory effect of LOXL3 silence on EMT in HCC cells through deubiquitinating and stabilizing the expression of Snail1. Moreover, LOXL3-promoted HCC EMT through Wnt/β-catenin/Snail1 signaling pathway. In vivo study revealed that silence of LOXL3-inhibited HCC tumor growth. In conclusion, LOXL3 silence inhibited HCC invasion and EMT through Snail1/USP4-mediated circulation loop and Wnt/β-catenin signaling pathway. Show less
no PDF DOI: 10.1002/tox.23617
SNAI1
Juanfen Mo, Zhenzhen Gao, Li Zheng +5 more · 2022 · Cell death discovery · Nature · added 2026-04-24
Metabolic remodeling is the fundamental molecular feature of malignant tumors. Cancer cells require sufficient energy supplies supporting their high proliferative rate. MTHFD2, a mitochondrial one-car Show more
Metabolic remodeling is the fundamental molecular feature of malignant tumors. Cancer cells require sufficient energy supplies supporting their high proliferative rate. MTHFD2, a mitochondrial one-carbon metabolic enzyme, is dysregulated in several malignancies and may serve as a promising therapeutic candidate in cancer treatment. Here, our data confirmed that MTHFD2 gene and protein was upregulated in the cancerous tissues of LUAD patients and was correlated with a poor survival in LUAD. MTHFD2 was involved in lung cancer cell proliferation, migration, and apoptosis by mediating its downstream molecules, such as DNA helicases (MCM4 and MCM7), as well as ZEB1, Vimentin and SNAI1, which contributed to tumor cell growth and epithelial-to-mesenchymal transition (EMT) process. Moreover, we identified that miRNA-99a-3p appeared to be an upstream mediator directly regulating MTHFD2 and MCM4 expression. Moreover, specific inhibition of MTHFD2 functions by siRNA or a chemical compound, improved anti-tumor sensitivities induced by pemetrexed in LUAD. Taken together, our study revealed the underlying molecular mechanisms of MTHFD2 in regulating cell proliferation and identified a novel therapeutic strategy improving the treatment efficacies in LUAD. Show less
no PDF DOI: 10.1038/s41420-022-01098-y
SNAI1