👤 Serina Huang

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1004
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Also published as: Ai-Chun Huang, Ai-long Huang, Aijie Huang, Ailong Huang, Aimin Huang, Alden Y Huang, An-Fang Huang, Annie Huang, Aohuan Huang, Ariane Huang, Baihai Huang, Baisong Huang, Bao-Hua Huang, Bao-Yi Huang, Baoqin Huang, Baoying Huang, Benjamin J Huang, Benlin Huang, Bevan E Huang, Bi Huang, Biao Huang, Bin Huang, Binfang Huang, Bing Huang, Bingcang Huang, Bingkun Huang, Bizhi Huang, Bo Huang, Bo-Shih Huang, Bor-Ren Huang, Bowen Huang, Boyue Huang, C Y Huang, Caihong Huang, Caiyun Huang, Can Huang, Canhua Huang, Caoxin Huang, Cathelin Huang, Catherine Huang, Chang Ming Huang, Chang X Huang, Chang-Jen Huang, Changjiang Huang, Chao Huang, Chao Wei Huang, Chao-Wei Huang, Chao-Yuan Huang, Chaolin Huang, Chaoqun Huang, Chaowang Huang, Chaoyang Huang, Chen Huang, Chen-Na Huang, Chen-Ping Huang, Cheng Huang, Chengcheng Huang, Chengrui Huang, Chenshen Huang, Chenxiao Huang, Chi-Cheng Huang, Chi-Shuan Huang, Chia-Chang Huang, Chia-Wei Huang, Chieh-Cheng Huang, Chieh-Liang Huang, Chien-Hsun Huang, Chih-Chun Huang, Chih-Hsiang Huang, Chih-Jen Huang, Chih-Ting Huang, Chih-Yang Huang, Chin-Chang Huang, Chin-Chou Huang, Ching-Shan Huang, Ching-Shin Huang, Ching-Tang Huang, Ching-Wei Huang, Chiu-Ju Huang, Chiu-Jung Huang, Chiun-Sheng Huang, Chong Huang, Chongbiao Huang, Christine S Huang, Chuan Huang, Chuanbing Huang, Chuanhong Huang, Chuanjiang Huang, Chuanjun Huang, Chuansheng Huang, Chuiguo Huang, Chun Huang, Chun-Mei Huang, Chun-Yao Huang, Chun-Yin Huang, Chunfan Huang, Chung-Hsiung Huang, Chunhong Huang, Chunjian Huang, Chunkai Huang, Chunlan Huang, Chunling Huang, Chunshuai Huang, Chunxia Huang, Chunyao Huang, Chunyi Huang, Chunying Huang, Chunyu Huang, Chuxin Huang, Chuying Huang, Congcong Huang, Cuiyu Huang, Da Huang, Dajun Huang, Dan Huang, Dane Huang, Danqing Huang, Dantong Huang, David Huang, David J Huang, De Huang, De-Jun Huang, Dejia Huang, Dengjun Huang, Dianhua Huang, Dishu Huang, Dong Huang, Donglan Huang, Dongmei Huang, Dongni Huang, Dongqin Huang, Dongqing Huang, Dongsheng Huang, Dongyu Huang, Du-Juan Huang, Emily C Huang, Enhao Huang, Enping Huang, Eric Huang, Erya Huang, F Huang, Fan Huang, Fang Huang, Fang-Ling Huang, Fangling Huang, Fei Huang, Fei Wan Huang, Feiruo Huang, Feiteng Huang, Feizhou Huang, Feng Huang, Fengxian Huang, Fengyu Huang, Franklin W Huang, Fu-Chen Huang, Fu-Mei Huang, Fubiao Huang, Fude Huang, Fuhao Huang, Furong Huang, G Huang, Gairong Huang, Gang Huang, Gao-Zhong Huang, Gaoxingyu Huang, Ge Huang, Guang-Jian Huang, Guang-Yun Huang, Guangjian Huang, Guangming Huang, Guangqian Huang, Guangrui Huang, Guanhong Huang, Guanling Huang, Guanning Huang, Guanqun Huang, Guanrong Huang, Guicheng Huang, Guodong Huang, Guohong Huang, Guoping Huang, Guoqian Huang, Guowei Huang, Guoxing Huang, Guoying Huang, Guoyong Huang, Guoyuan Huang, H Huang, H S Huang, Hai Huang, Haigang Huang, Haihong Huang, Hailin Huang, Haimiao Huang, Haixin Huang, Haiyan Huang, Han-Chang Huang, Hanxia Huang, Hao Huang, Hao-Fei Huang, Haobo Huang, Haochu Huang, Haomin Huang, Haoyu Huang, Haoyue Huang, Haozhang Huang, Haozhong Huang, He Huang, Hefeng Huang, Heguang Huang, Helen Huang, Heming Huang, Hengbin Huang, Heqing Huang, Hete Huang, Hong Huang, Hongbiao Huang, Hongcan Huang, Hongda Huang, Hongfei Huang, Hongfeng Huang, Honghui Huang, Hongou Huang, Hongqiang Huang, Hongyan Huang, Hongyang Huang, Hongyi Huang, Hongying Huang, Hongyu Huang, Hongyun Huang, Hsi-Yuan Huang, Hsien-Da Huang, Hsing-Yen Huang, Hsu Chih Huang, Hsuan-Cheng Huang, Hsuan-Ying Huang, Hu Huang, Hua Huang, Huafei Huang, Huaju Huang, Huan Huang, Huanhuan Huang, Huanliang Huang, Huapin Huang, Huashan Huang, Huayun Huang, Hui Huang, Hui-Huang Huang, Hui-Kuang Huang, Hui-Yu Huang, Huibin Huang, Huifen Huang, Huiling Huang, Huimin Huang, Huina Huang, Huiqiao Huang, Huixian Huang, Huixin Huang, Huiyan Huang, Huiyu Huang, Huizhe Huang, Huizhen Huang, Hy Huang, I-Chieh Huang, J V Huang, Janice J Huang, Jasmin Huang, Jeffrey K Huang, Jia Huang, Jia-Jia Huang, Jiaan Huang, Jiahui Huang, Jiajin Huang, Jiajun Huang, Jian Huang, Jian-Dong Huang, Jiana Huang, Jianbiao Huang, Jianbing Huang, Jianfang Huang, Jianfeng Huang, Jiangfeng Huang, Jiangtao Huang, Jiangwei Huang, Jianhua Huang, Jianlu Huang, Jianmin Huang, Jianming Huang, Jiansheng Huang, Jianzhen Huang, Jiao-Qian Huang, Jiaoti Huang, Jiaotian Huang, Jiaqi Huang, Jiawen Huang, Jiaxing Huang, Jiayu Huang, Jiayue Huang, Jie Huang, Jie Qi Huang, Jiechun Huang, Jieli Huang, Jieling Huang, Jieping Huang, Jin Huang, Jin-Di Huang, Jin-Feng Huang, Jin-Hong Huang, Jin-Yan Huang, Jinbao Huang, Jinfang Huang, Jing Huang, Jing-Fei Huang, Jingang Huang, Jinghan Huang, Jingjing Huang, Jingkun Huang, Jinglong Huang, Jingtao Huang, Jingxian Huang, Jingyong Huang, Jingyuan Huang, Jingyue Huang, Jinhua Huang, Jinling Huang, Jinlu Huang, Jinshu Huang, Jinxing Huang, Jinyan Huang, Jinzhou Huang, Jiuhong Huang, Jiyu Huang, Ju Huang, Juan Huang, Jucun Huang, Jun Huang, Jun-Hua Huang, Jun-You Huang, Junhao Huang, Junhua Huang, Junjie Huang, Junming Huang, Junning Huang, Junqi Huang, Junwen Huang, Junyuan Huang, Junyun Huang, Juxiang Huang, K Huang, K N Huang, Kai Huang, Kaipeng Huang, Kang Huang, Kangbo Huang, Kate Huang, Katherine Huang, Ke Huang, Ke-Ke Huang, Ke-Pu Huang, Kevin Huang, Kevin Y Huang, Kuan-Chun Huang, Kui-Yuan Huang, Kuiyuan Huang, Kun Huang, Kuo-Hsiang Huang, Kuo-Hung Huang, L Huang, L-B Huang, Laiqiang Huang, Lan Huang, Lanlan Huang, Lei Huang, Leijuan Huang, Li Huang, Li-Hao Huang, Li-Jiang Huang, Li-Juan Huang, Li-Jun Huang, Li-Ping Huang, Li-Rung Huang, Li-Wei Huang, Li-Yun Huang, Lian Huang, Liang Huang, Liang-Yu Huang, Liangchong Huang, Lianggui Huang, Libin Huang, Lige Huang, Lihua Huang, Lijia Huang, Lijiang Huang, Lijuan Huang, Lijun Huang, Lili Huang, Limin Huang, Liming Huang, Lin Huang, Linchen Huang, Ling Huang, Ling-Chun Huang, Ling-Jin Huang, Lingling Huang, Lining Huang, Linjing Huang, Linsheng Huang, Linxue Huang, Linyuan Huang, Liping Huang, Liqiong Huang, Lixia Huang, Lixiang Huang, Lixuan Huang, Lixue Huang, Lizhen Huang, Longfei Huang, Lu Huang, Lu-Jie Huang, Lu-Qi Huang, Luanluan Huang, Luqi Huang, Luyang Huang, Luyao Huang, Lvzhen Huang, M C Huang, Man Huang, Manning Y Huang, Manyun Huang, Mao-Mao Huang, Mei Huang, Meihua Huang, Meina Huang, Meixiang Huang, Melissa Y Huang, Meng-Chuan Huang, Meng-Fan Huang, Meng-Na Huang, MengQian Huang, Menghao Huang, Mengjie Huang, Mengjun Huang, Mengnan Huang, Mengting Huang, Mengzhen Huang, Mia L Huang, Miao Huang, Min Huang, Ming-Lu Huang, Ming-Shyan Huang, Mingjian Huang, Mingjun Huang, Minglei Huang, Mingrui Huang, Mingwei Huang, Mingxuan Huang, Mingyu Huang, Mingyuan Huang, Minjun Huang, Minqi Huang, Minxuan Huang, Minyuan Huang, N Huang, Na Huang, Nian Huang, Nianyuan Huang, Ning-Na Huang, Ning-Ping Huang, Ninghao Huang, Nongyu Huang, Pan Huang, Pang-Shuo Huang, Paul L Huang, Pei Huang, Pei-Chi Huang, Pei-Ying Huang, Peiying Huang, Peng Huang, Peng-Fei Huang, Pengyu Huang, Piao-Piao Huang, Piaopiao Huang, Pin-Rui Huang, Ping Huang, Pingping Huang, Pintong Huang, Po-Hsun Huang, Po-Jung Huang, Poyao Huang, Qi Huang, Qi-Tao Huang, Qian Huang, Qiang Huang, Qianqian Huang, Qiaobing Huang, Qibin Huang, Qidi Huang, Qin Huang, Qing Huang, Qing-yong Huang, Qingjiang Huang, Qingke Huang, Qingling Huang, Qingqing Huang, Qingsong Huang, Qingxia Huang, Qingxing Huang, Qingyu Huang, Qingzhi Huang, Qinlou Huang, Qiong Huang, Qiubo Huang, Qiumin Huang, Qiuming Huang, Qiuru Huang, Qiuyin Huang, Qiuyue Huang, Qizhen Huang, Quanfang Huang, Qun Huang, R H Huang, R Stephanie Huang, Rae-Chi Huang, Ran Huang, Renbin Huang, Renhua Huang, Renli Huang, Richard Huang, Richard S P Huang, Riqing Huang, Ritai Huang, Robert J Huang, Rong Huang, Rong Stephanie Huang, Ronghua Huang, Ronghui Huang, Rongjie Huang, Rongrong Huang, Rongxiang Huang, Ru-Ting Huang, Ruby Yun-Ju Huang, Rui Huang, Ruihua Huang, Ruijin Huang, Ruina Huang, Ruiyan Huang, Ruizhen Huang, Runyue Huang, Ruo-Hui Huang, S Huang, S Y Huang, S Z Huang, Saisai Huang, San-Yuan Huang, See-Chang Huang, Sen Huang, Shan Huang, Shang-Ming Huang, Shanhe Huang, Shanshan Huang, Shaojun Huang, Shaoxin Huang, Shaoze Huang, Shau Ku Huang, Shau-Ku Huang, Shenan Huang, Sheng-He Huang, Shengfeng Huang, Shengjie Huang, Shengnan Huang, Shengyan Huang, Shengyun Huang, Shi-Feng Huang, Shi-Shi Huang, Shi-Ying Huang, Shiang-Suo Huang, Shichao Huang, Shih-Chiang Huang, Shih-Wei Huang, Shih-Yi Huang, Shihao Huang, Shijing Huang, Shilu Huang, Shixia Huang, Shiya Huang, Shiying Huang, Shiyun Huang, Shoucheng Huang, Shu Huang, Shu-Pang Huang, Shu-Pin Huang, Shu-Qiong Huang, Shu-Wei Huang, Shu-Yi Huang, Shu-ying Huang, Shuai Huang, Shuang Huang, Shungen Huang, Shuo Huang, Shushu Huang, Shutong Huang, Shuwen Huang, Si-Yang Huang, Sidong Huang, Sihua Huang, Sijia Huang, Sinchun Huang, Sisi Huang, Sixiu Huang, Song Bin Huang, Song-Mei Huang, Songmei Huang, Songming Huang, Songqian Huang, Steven Huang, Steven Kuan-Hua Huang, Suli Huang, Sung-Ying Huang, Susan M Huang, Suwen Huang, Taiqi Huang, Tang-Hsiu Huang, Tao Huang, Te-Hsuan Huang, Tengda Huang, Tengfei Huang, Tian Hao Huang, Tianhao Huang, Tianpu Huang, Tiantian Huang, Tieqiu Huang, Tim H Huang, Ting Huang, Tinghua Huang, Tingping Huang, Tingqin Huang, Tingting Huang, Tingxuan Huang, Tingyun Huang, Tong Huang, Tongsheng Huang, Tongtong Huang, Tony T Huang, Tse-Shun Huang, Tseng-Yu Huang, Tsung-Wei Huang, Tzu-Rung Huang, Wan-Ping Huang, Way-Ren Huang, Wei Huang, Wei-Chi Huang, Weibin Huang, Weicheng Huang, Weifeng Huang, Weihua Huang, Weijun Huang, Weiqi Huang, Weisu Huang, Weiwei Huang, Weixue Huang, Weizhen Huang, Wen Huang, Wen-yu Huang, Wenbin Huang, Wenda Huang, Wenfang Huang, Wenfeng Huang, Wenhua Huang, Wenji Huang, Wenjie Huang, Wenjun Huang, Wenqiao Huang, Wenqing Huang, Wenqiong Huang, Wenshan Huang, Wentao Huang, Wenxin Huang, Wenya Huang, Wenying Huang, Wunan Huang, Wuqing Huang, X F Huang, X Huang, Xi Huang, Xian-sheng HUANG, Xiang Huang, Xianghua Huang, Xianglong Huang, Xiangming Huang, Xianping Huang, Xianqing Huang, Xiansheng Huang, Xianwei Huang, Xianxi Huang, Xianxian Huang, Xianying Huang, Xianzhang Huang, Xiao Huang, Xiao-Fang Huang, Xiao-Fei Huang, Xiao-Ming Huang, Xiao-Song Huang, Xiao-Yan Huang, Xiao-Yong Huang, Xiao-Yu Huang, XiaoFang Huang, Xiaochun Huang, Xiaofei Huang, Xiaofeng Huang, Xiaohong Huang, Xiaohua Huang, Xiaojie Huang, Xiaojing Huang, Xiaojuan Huang, Xiaolan Huang, Xiaoli Huang, Xiaolin Huang, Xiaoman Huang, Xiaomin Huang, Xiaoqing Huang, Xiaoshuai Huang, Xiaowen Huang, Xiaowu Huang, Xiaoxia Huang, Xiaoyan Huang, Xiaoying Huang, Xiaoyu Huang, Xiaoyuan Huang, Xiaoyun Huang, Xiaozhun Huang, Xiayang Huang, Xichang Huang, Xie-Lin Huang, Xin Huang, Xin-Di Huang, Xinen Huang, Xinfeng Huang, Xingguo Huang, Xingming Huang, Xingqin Huang, Xingru Huang, Xingxu Huang, Xingya Huang, Xingzhen Huang, Xinwen Huang, Xinyi Huang, Xinying Huang, Xinyue Huang, Xinzhu Huang, Xiongfeng Huang, Xionggao Huang, Xiuju Huang, Xiuyun Huang, Xiuzhen Huang, Xiwen Huang, Xu Huang, Xu-Feng Huang, Xuan Huang, Xuanzhang Huang, Xucong Huang, Xudong Huang, Xue-Ying Huang, Xue-shuang Huang, Xuehong Huang, Xuejie Huang, Xuejing Huang, Xuejun Huang, Xuemei Huang, Xueming Huang, Xueqi Huang, Xuewei Huang, Xuezhe Huang, Xuhui Huang, Xuliang Huang, Xun Huang, Xuxiong Huang, Y Huang, Y Joyce Huang, Y S Huang, Ya-Chih Huang, Ya-Dong Huang, Ya-Fang Huang, Ya-Ru Huang, Yabo Huang, Yadong Huang, Yafang Huang, Yajiao Huang, Yajuan Huang, Yali Huang, Yamei Huang, Yan Huang, Yan-Lin Huang, Yan-Qing Huang, Yan-Ting Huang, Yang Huang, Yang Zhong Huang, Yangqing Huang, Yangyang Huang, Yanhao Huang, Yani Huang, Yanjun Huang, Yanlong Huang, Yanna Huang, Yanping Huang, Yanqin Huang, Yanqing Huang, Yanqun Huang, Yanru Huang, Yanshan Huang, Yansheng Huang, Yanxia Huang, Yanyan Huang, Yanyao Huang, Yao Huang, Yao-Kuang Huang, Yaowei Huang, Yatian Huang, Yating Huang, Ye Huang, Yechao Huang, Yen-Chu Huang, Yen-Ning Huang, Yen-Tsung Huang, Yeqing Huang, Yewei Huang, Yi Huang, Yi-Chun Huang, Yi-Jan Huang, Yi-Jia Huang, Yi-Wen Huang, Yi-ping Huang, Yichao Huang, Yichuan Huang, Yicong Huang, Yifan Huang, Yihao Huang, Yiheng Huang, Yihong Huang, Yikeng Huang, Yilin Huang, Yin Huang, Yin-Tsen Huang, Ying Huang, Ying-Hsuan Huang, Ying-Jung Huang, Ying-Zhi Huang, Yinghua Huang, Yingying Huang, Yingzhen Huang, Yingzhi Huang, Yiping Huang, Yiquan Huang, Yishan Huang, Yiwei Huang, Yixian Huang, Yizhou Huang, Yong Huang, Yong-Fu Huang, Yongbiao Huang, Yongcan Huang, Yongjie Huang, Yongqi Huang, Yongsheng Huang, Yongtong Huang, Yongye Huang, Yongyi Huang, Yongzhen Huang, Youheng Huang, Youyang Huang, Yu Huang, Yu-Ching Huang, Yu-Chu Huang, Yu-Chuen Huang, Yu-Chyi Huang, Yu-Fang Huang, Yu-Han Huang, Yu-Jie Huang, Yu-Lei Huang, Yu-Ren Huang, Yu-Shu Huang, Yu-Ting Huang, Yuan Huang, Yuan-Lan Huang, Yuan-Li Huang, Yuan-Lu Huang, Yuancheng Huang, Yuanpeng Huang, Yuanshuai Huang, Yuanyu Huang, Yuanyuan Huang, Yue Huang, Yue-Hua Huang, Yuedi Huang, Yueh-Hsiang Huang, Yuehong Huang, Yuejun Huang, Yueye Huang, Yuezhen Huang, Yufang Huang, Yufen Huang, Yuguang Huang, Yuh-Chin T Huang, Yuhong Huang, Yuhua Huang, Yuhui Huang, Yujia Huang, Yujie Huang, Yulin Huang, Yumei Huang, Yumeng Huang, Yun Huang, Yun-Juan Huang, Yunchao Huang, Yung-Hsin Huang, Yung-Yu Huang, Yunmao Huang, Yunpeng Huang, Yunru Huang, Yunyan Huang, Yuping Huang, Yuqi Huang, Yuqiang Huang, Yuqiong Huang, Yusi Huang, Yutang Huang, Yuting Huang, Yutong Huang, Yuxian Huang, Yuxin Huang, Yuxuan Huang, Yuyang Huang, Yuying Huang, Z Huang, Z Z Huang, Z-Y Huang, Zebin Huang, Zebo Huang, Zehua Huang, Zeling Huang, Zengwen Huang, Zhang Huang, Zhao Huang, Zhaoxia Huang, Zhe Huang, Zhen Huang, Zhenfei Huang, Zheng Huang, Zheng-Xiang Huang, Zhengwei Huang, Zhengxian Huang, Zhengxiang Huang, Zhengyang Huang, Zhenlin Huang, Zhenrui Huang, Zhenyao Huang, Zhenyi Huang, Zhi Huang, Zhi-Ming Huang, Zhi-Qiang Huang, Zhi-Xin Huang, Zhi-xiang Huang, Zhican Huang, Zhicong Huang, Zhifang Huang, Zhifeng Huang, Zhigang Huang, Zhihong Huang, Zhilin Huang, Zhilong Huang, Zhipeng Huang, Zhiping Huang, Zhiqi Huang, Zhiqiang Huang, Zhiqin Huang, Zhiqing Huang, Zhitong Huang, Zhiwei Huang, Zhixiang Huang, Zhiying Huang, Zhiyong Huang, Zhiyu Huang, Zhongbin Huang, Zhongcheng Huang, Zhongfeng Huang, Zhonglu Huang, Zhouyang Huang, Zi-Xin Huang, Zi-Ye Huang, Zicheng Huang, Zichong Huang, Zihan Huang, Zihao Huang, Ziheng Huang, Ziling Huang, Zini Huang, Zirui Huang, Zizhan Huang, Zongjian Huang, Zongliang Huang, Zunnan Huang, Zuotian Huang, Zuxian Huang, Zuyi Huang
articles
Yu-Wei Luo, Hongyu Ji, Ai-long Huang +1 more · 2024 · Autophagy · Taylor & Francis · added 2026-04-24
The CGAS (cyclic GMP-AMP synthase)-STING1 (stimulator of interferon response cGAMP interactor 1) pathway is an important innate immune pathway that induces proinflammatory cytokine production followin Show more
The CGAS (cyclic GMP-AMP synthase)-STING1 (stimulator of interferon response cGAMP interactor 1) pathway is an important innate immune pathway that induces proinflammatory cytokine production following stimulation with dsDNA > 45 bp. We recently identified a class of ~ 20-40 bp small cytosolic dsDNA (scDNA) that blocks CGAS-STING1 activation. In this punctum, we discuss the mechanism underlying the inhibition of CGAS-STING1 activation via scDNA. scDNA binds to CGAS but cannot activate its enzymatic activity. It competes with dsDNA > 45 bp for binding with CGAS to inhibit CGAS-STING1 activation. Moreover, scDNA activates macroautophagy/autophagy and induces the autophagic degradation of STING1 and long dsDNA. Autophagy then increases scDNA levels, driving a feedback loop that accelerates the degradation of STING1 and long cytosolic dsDNA. These findings reveal that mutual communication between scDNA and autophagy inhibits CGAS-STING1 activation following stimulation with dsDNA > 45 bp. Show less
no PDF DOI: 10.1080/15548627.2023.2285612
PIK3C3
Xingqin Huang, Linglin Jiang, Ting Li +1 more · 2024 · International journal of laboratory hematology · Blackwell Publishing · added 2026-04-24
no PDF DOI: 10.1111/ijlh.14230
RGS17
Yonggang Wang, Zhihao Li, Xiaolong Xu +3 more · 2024 · Scientific reports · Nature · added 2026-04-24
The aim of this study is to screen key target genes of osteoarthritis associated with aging and to preliminarily explore the associated immune infiltration cells and potential drugs. Differentially ex Show more
The aim of this study is to screen key target genes of osteoarthritis associated with aging and to preliminarily explore the associated immune infiltration cells and potential drugs. Differentially expressed senescence-related genes (DESRGs) selected from Cellular senescence-related genes (SRGs) and differentially expressed genes (DEGs) were analyzed using Gene Ontology enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein-protein interaction networks. Hub genes in DESRGs were selected based on degree, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. CIBERSORTx and ssGSEA algorithms were then used to assess immune cell infiltration and to analyse the correlation between key DESRGs and immune infiltration. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed. Combined with the DEGs and SRGs, we screened 19 DESRGs for further study. Five diagnostic genes were ultimately identified: CDKN1A, VEGFA, MCL1, SNAI1 and MYC. ROC analysis showed that the area under the curve (AUC). Correlation analysis showed that the five hub genes were closely associated with neutrophil, plasmacytoid dendritic cell, activated CD4 T-cell and type 2 T-helper cell infiltration in the development of Osteoarthritis (OA). Finally, we found that drugs such as lithium chloride, acetaminophen, curcumin, celecoxib and resveratrol could be targeted for the treatment of senescence-related OA. The results of this study indicate that CDKN1A, VEGFA, MCL1, SNAI1, and MYC are key biomarkers that can be used to predict and prevent early aging-related OA. Lithium chloride, acetaminophen, curcumin, celecoxib, and resveratrol can be used for personalized treatment of aging-related OA. Show less
no PDF DOI: 10.1038/s41598-024-83268-9
SNAI1
Fan Yang, Xiaoyun Zhang, Jiaan Huang +5 more · 2024 · Scientific reports · Nature · added 2026-04-24
The present study was undertaken to investigate the therapeutic effect and underlying mechanisms of lumbrokinase (LK) on diabetic kidney disease (DKD). Kidney tissue samples from DKD patients and norm Show more
The present study was undertaken to investigate the therapeutic effect and underlying mechanisms of lumbrokinase (LK) on diabetic kidney disease (DKD). Kidney tissue samples from DKD patients and normal controls were collected from hospitals. The type 2 diabetic nephropathy model was induced in db/db mice. The mice were then randomly divided into a model group (DM group) and an LK group. db/m mice were used as the control group (Con group). After 12 weeks of treatment with LK (234 KU/kg/day), biochemical parameters were tested, and pathological changes in the kidney were observed under a light microscope. The epithelial-to-mesenchymal transition (EMT), mRNA m6A methylation proteins, and activated TGF-β1/Smad pathway components were assessed by western blot or immunofluorescence in DKD patients, model mice, and high glucose-stimulated HK-2 cells. We found that the m6A eraser METTL3 was expressed at low levels in DKD patients, model mice, and high glucose-stimulated HK-2 cells. METTL3 overexpression reversed the high glucose-induced activation of the TGF-β1/Smad pathway and EMT through snail in vitro. However, LK can restore the expression of the m6A-modifying enzyme METTL3 in vivo and in vitro, suppressed EMT, and alleviated renal interstitial fibrosis by downregulating snail. Overall, LK ameliorated renal fibrosis through the regulation of Snail via m6A RNA METTL3. Show less
no PDF DOI: 10.1038/s41598-024-80168-w
SNAI1
Xilin Zhao, Songping Wang, Xuelan He +2 more · 2024 · Food & function · Royal Society of Chemistry · added 2026-04-24
Our previous studies have demonstrated that ubiquitin-specific peptidase 22 (USP22) has the capacity to accelerate renal epithelial-to-mesenchymal transition (EMT) and promote the pathological progres Show more
Our previous studies have demonstrated that ubiquitin-specific peptidase 22 (USP22) has the capacity to accelerate renal epithelial-to-mesenchymal transition (EMT) and promote the pathological progression of diabetic tubulointerstitial fibrosis (TIF) by regulating the ubiquitination of Snail1, an EMT transcription factor. Quercetin is a type of flavonol compound widely found in fruits and vegetables that has anti-inflammatory, antioxidant and anti-fibrosis effects. However, whether quercetin promotes the degradation of Snail1 and regulates the pathological progression of TIF by inhibiting USP22 requires further investigation. In this study, we found that quercetin significantly inhibited the expression of USP22 and Snail1 in high glucose (HG)-induced renal tubular epithelial cells (TECs), and reversed the expression of EMT-related proteins and inhibited the overproduction of fibronectin (FN) and Collage Type IV (Collagen IV) induced by high glucose. Additionally, quercetin blocked the deubiquitination of Snail1 mediated by USP22. Further study found that quercetin inhibited the interaction between USP22 and Snail1, thereby reducing the stability of Snail1. Furthermore, quercetin also reduced the protein levels of USP22 and Snail1 in the kidney tissue of diabetic mice and ameliorated renal function, delayed EMT and TIF. In conclusion, quercetin regulates the USP22-Snail1 signal pathway to inhibit the occurrence of EMT both Show less
no PDF DOI: 10.1039/d4fo03564j
SNAI1
Hong-Xun Ruan, Xiao-Ning Qin, Wei Huang +1 more · 2024 · Discover oncology · Springer · added 2026-04-24
Colorectal cancer (CRC) is a prevalent malignancy with high morbidity and mortality rates. Previous studies have demonstrated that interleukin (IL)-22 is involved in CRC progression; however, the exac Show more
Colorectal cancer (CRC) is a prevalent malignancy with high morbidity and mortality rates. Previous studies have demonstrated that interleukin (IL)-22 is involved in CRC progression; however, the exact mechanism remains unclear. This study aimed to investigate the effects of IL-22 on CRC cell proliferation and metastasis. IL-22 levels in the serum and tissues of CRC patients were measured using enzyme-linked immunosorbent assay (ELISA). Cell counting kit-8 (CCK-8) assay was used to detect the viability of CRC (HCT116) cells treated with different IL-22 concentrations. Colony formation, Transwell invasion, and scratch assays were employed to assess the effects of IL-22 on cell proliferation, invasion, and migration. Western blotting was performed to measure the expression levels of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), p-PI3K, p-AKT, E-cadherin, matrix metalloproteinase (MMP)-2, MMP-9, SNAI1, and TWIST1 in HCT116 cells treated with IL-22 or a PI3K inhibitor. ELISA results showed that the expression of IL-22 was significantly increased in the serum and tissues of CRC patients compared to controls. IL-22 treatment increased cell viability and colony formation in a concentration-dependent manner and enhanced cell invasion and migration. Western blotting analysis revealed that IL-22 stimulation upregulated p-PI3K and p-AKT expression, while total PI3K and AKT levels remained unchanged. Additionally, IL-22 also decreased E-cadherin expression and increased the expression of MMP-2, MMP-9, SNAI1, and TWIST1. IL-22 activates the PI3K-AKT pathway and promotes HCT116 cell proliferation and metastasis. Targeting the regulation of the PI3K/AKT pathway may be a potential therapeutic strategy for CRC. Show less
no PDF DOI: 10.1007/s12672-024-01169-9
SNAI1

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Z Ke, Z Huang, R He +4 more · 2024 · Nan fang yi ke da xue xue bao = Journal of Southern Medical University · added 2026-04-24
To investigate the role of high-mobility group AT-hook 2 (HMGA2) in osteogenic differentiation of adipose-derived mesenchymal stem cells (ADSCs) and the effect of Bioinformatics studies using the GEO Show more
To investigate the role of high-mobility group AT-hook 2 (HMGA2) in osteogenic differentiation of adipose-derived mesenchymal stem cells (ADSCs) and the effect of Bioinformatics studies using the GEO database and Rstudio software identified HMGA2 as a key factor in adipogenic-osteogenic differentiation balance of ADSCs. The protein-protein interaction network of HMGA2 in osteogenic differentiation was mapped using String and visualized with Cytoscape to predict the downstream targets of HMGA2. Primary mouse ADSCs (mADSCs) were transfected with GEO database analysis showed that HMGA2 is a crucial regulator of osteogenic differentiation in ADSCs, and Show less
no PDF DOI: 10.12122/j.issn.1673-4254.2024.07.02
SNAI1
Yen-Nien Liu, Wei-Yu Chen, Hsiu-Lien Yeh +9 more · 2024 · Science signaling · Science · added 2026-04-24
Neuroendocrine prostate cancer (PCa) (NEPC), an aggressive subtype that is associated with poor prognosis, may arise after androgen deprivation therapy (ADT). We investigated the molecular mechanisms Show more
Neuroendocrine prostate cancer (PCa) (NEPC), an aggressive subtype that is associated with poor prognosis, may arise after androgen deprivation therapy (ADT). We investigated the molecular mechanisms by which ADT induces neuroendocrine differentiation in advanced PCa. We found that transmembrane protein 1 (MCTP1), which has putative Ca Show less
no PDF DOI: 10.1126/scisignal.adc9142
SNAI1
Mei Li, Litao Zhang, Tangming Guan +11 more · 2024 · Cancer letters · Elsevier · added 2026-04-24
Triple-negative breast cancer (TNBC) is a highly lethal malignancy with limited therapy options. Aberrant metabolism, a key hallmark of human cancers, plays a crucial role in tumor progression, therap Show more
Triple-negative breast cancer (TNBC) is a highly lethal malignancy with limited therapy options. Aberrant metabolism, a key hallmark of human cancers, plays a crucial role in tumor progression, therapeutic responses and TNBC-related death. However, the underlying mechanisms are not fully understood. In this study, we delineate a previously unrecognized role of aberrant glucose metabolism in regulating the turnover of Snail1, which is a key transcriptional factor of epithelial-mesenchymal transition (EMT) and critically contributes to the acquisition of stemness, metastasis and chemo-resistance. Mechanistically, we demonstrate that AMP-activated protein kinase (AMPK), when activated in response to glucose deprivation, directly phosphorylates Snail1 at Ser11. Such a phosphorylation modification of Snail1 facilitates its recruitment of the E3 ligase FBXO11 and promotes its degradation, thereby suppressing stemness, metastasis and increasing cellular sensitivity to chemotherapies in vitro and in vivo. Clinically, histological analyses reveal a negative correlation between p-AMPKα and Snail1 in TNBC specimens. Taken together, our findings establish a novel mechanism and functional significance of AMPK in linking glucose status to Snail1-dependent malignancies and underscore the potential of AMPK agonists as a promising therapeutic strategy in the management of TNBC. Show less
no PDF DOI: 10.1016/j.canlet.2024.216987
SNAI1
Jinlong Wang, Qiuying Gu, Yuexi Liu +5 more · 2024 · Experimental cell research · Elsevier · added 2026-04-24
Widespread metastasis is the primary reason for the high mortality associated with ovarian cancer (OC), and effective targeted therapy for tumor aggressiveness is still insufficient in clinical practi Show more
Widespread metastasis is the primary reason for the high mortality associated with ovarian cancer (OC), and effective targeted therapy for tumor aggressiveness is still insufficient in clinical practice. Therefore, it is urgent to find new targets to improve prognosis of patients. PDE4A is a cyclic nucleotide phosphodiesterase that plays a crucial role in the occurrence and development in various malignancies. Our study firstly reported the function of PDE4A in OC. Expression of PDE4A was validated through bioinformatics analysis, RT-qPCR, Western blot, and immunohistochemistry. Additionally, its impact on cell growth and motility was assessed via in vitro and in vivo experiments. PDE4A was downregulated in OC tissues compared with normal tissues and low PDE4A expression was correlated with poor clinical outcomes in OC patients. The knockdown of PDE4A significantly promoted the proliferation, migration and invasion of OC cells while overexpression of PDE4A resulted in the opposite effect. Furthermore, smaller and fewer tumor metastatic foci were observed in mice bearing PDE4A-overexpressing OVCAR3 cells. Mechanistically, downregulation of PDE4A expression can induce epithelial-mesenchymal transition (EMT) and nuclear translocation of Snail, which suggests that PDE4A plays a pivotal role in suppressing OC progression. Notably, Rolipram, the PDE4 inhibitor, mirrored the effects observed with PDE4A deletion. In summary, the downregulation of PDE4A appears to facilitate OC progression by modulating the Snail/EMT pathway, underscoring the potential of PDE4A as a therapeutic target against ovarian cancer metastasis. Show less
no PDF DOI: 10.1016/j.yexcr.2024.114100
SNAI1
Yewei Huang, Gan Luo, Kesong Peng +13 more · 2024 · The Journal of cell biology · added 2026-04-24
The transcription factor TFEB is a major regulator of lysosomal biogenesis and autophagy. There is growing evidence that posttranslational modifications play a crucial role in regulating TFEB activity Show more
The transcription factor TFEB is a major regulator of lysosomal biogenesis and autophagy. There is growing evidence that posttranslational modifications play a crucial role in regulating TFEB activity. Here, we show that lactate molecules can covalently modify TFEB, leading to its lactylation and stabilization. Mechanically, lactylation at K91 prevents TFEB from interacting with E3 ubiquitin ligase WWP2, thereby inhibiting TFEB ubiquitination and proteasome degradation, resulting in increased TFEB activity and autophagy flux. Using a specific antibody against lactylated K91, enhanced TFEB lactylation was observed in clinical human pancreatic cancer samples. Our results suggest that lactylation is a novel mode of TFEB regulation and that lactylation of TFEB may be associated with high levels of autophagy in rapidly proliferating cells, such as cancer cells. Show less
no PDF DOI: 10.1083/jcb.202308099
WWP2
Chenxiao Huang, Tao Jiang, Wen Pan +5 more · 2024 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · Wiley · added 2026-04-24
Arboviruses, transmitted by medical arthropods, pose a serious health threat worldwide. During viral infection, Post Translational Modifications (PTMs) are present on both host and viral proteins, reg Show more
Arboviruses, transmitted by medical arthropods, pose a serious health threat worldwide. During viral infection, Post Translational Modifications (PTMs) are present on both host and viral proteins, regulating multiple processes of the viral lifecycle. In this study, a mammalian E3 ubiquitin ligase WWP2 (WW domain containing E3 ubiquitin ligase 2) is identified, which interacts with the NS1 protein of Zika virus (ZIKV) and mediates K63 and K48 ubiquitination of Lys 265 and Lys 284, respectively. WWP2-mediated NS1 ubiquitination leads to NS1 degradation via the ubiquitin-proteasome pathway, thereby inhibiting ZIKV infection in mammalian hosts. Simultaneously, it is found Su(dx), a protein highly homologous to host WWP2 in mosquitoes, is capable of ubiquitinating NS1 in mosquito cells. Unexpectedly, ubiquitination of NS1 in mosquitoes does not lead to NS1 degradation; instead, it promotes viral infection in mosquitoes. Correspondingly, the NS1 K265R mutant virus is less infectious to mosquitoes than the wild-type (WT) virus. The above results suggest that the ubiquitination of the NS1 protein confers different adaptations of ZIKV to hosts and vectors, and more importantly, this explains why NS1 K265-type strains have become predominantly endemic in nature. This study highlights the potential application in antiviral drug and vaccine development by targeting viral proteins' PTMs. Show less
no PDF DOI: 10.1002/advs.202408024
WWP2
Tao Huang, Qi You, Dengjun Huang +9 more · 2024 · Cell communication and signaling : CCS · BioMed Central · added 2026-04-24
Increasing evidence has indicated that long non-coding RNAs (lncRNAs) have been proven to regulate esophageal cancer progression. The lncRNA protein disulfide isomerase family A member 3 pseudogene 1 Show more
Increasing evidence has indicated that long non-coding RNAs (lncRNAs) have been proven to regulate esophageal cancer progression. The lncRNA protein disulfide isomerase family A member 3 pseudogene 1 (PDIA3P1) has been shown to promote cancer stem cell properties; however, its mechanism of action remains unclear. In this study, we investigated the regulation of esophageal cancer stem cell properties by the interaction of PDIA3P1 with proteins. The GEPIA2 and Gene Expression Omnibus databases were used to analyze gene expression. PDIA3P1 expression in human esophageal squamous cell carcinoma (ESCC) tissues and cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Loss-of-function experiments were performed to determine the effects of PDIA3P1 on ESCC cell proliferation, migration, and invasion. The sphere formation assay, number of side population cells, and CD271 + /CD44 + cells were detected by flow cytometry to identify the cancer stem cell properties. RNA immunoprecipitation (RIP), RNA pull-down, co-immunoprecipitation (co-IP), dual luciferase reporter, and cleavage under targets and tagmentation (CUT&Tag) assays were performed to elucidate the underlying molecular mechanisms. PDIA3P1 expression was upregulated in ESCC cell lines and tissues. Functionally, higher PDIA3P1 expression promoted cell proliferation, invasion, and metastasis and inhibited apoptosis in esophageal cancer. Importantly, PDIA3P1 promoted cancer stem cell properties in ESCC. Mechanistically, PDIA3P1 interacted with and stabilized octamer-binding transcription factor 4 (OCT4) by eliminating its ubiquitination by the ubiquitinating enzyme WW domain-containing protein 2 (WWP2). Moreover, as a transcription factor, OCT4 bound to the PDIA3P1 promoter and promoted its transcription. Our research revealed a novel mechanism by which a positive feedback loop exists between PDIA3P1 and OCT4. It also demonstrated that the PDIA3P1-WWP2-OCT4 loop is beneficial for promoting the cancer stem cell properties of ESCC. Owing to this regulatory relationship, the PDIA3P1-WWP2-OCT4-positive feedback loop might be used in the diagnosis and prognosis, as well as in the development of novel therapeutics for esophageal cancer. Show less
no PDF DOI: 10.1186/s12964-024-01475-3
WWP2
Jin Li, Jiayu Zhu, Olivia Gray +10 more · 2024 · The Journal of cell biology · added 2026-04-24
Vascular homeostasis and pathophysiology are tightly regulated by mechanical forces generated by hemodynamics. Vascular disorders such as atherosclerotic diseases largely occur at curvatures and bifur Show more
Vascular homeostasis and pathophysiology are tightly regulated by mechanical forces generated by hemodynamics. Vascular disorders such as atherosclerotic diseases largely occur at curvatures and bifurcations where disturbed blood flow activates endothelial cells while unidirectional flow at the straight part of vessels promotes endothelial health. Integrated analysis of the endothelial transcriptome, the 3D epigenome, and human genetics systematically identified the SNP-enriched cistrome in vascular endothelium subjected to well-defined atherosclerosis-prone disturbed flow or atherosclerosis-protective unidirectional flow. Our results characterized the endothelial typical- and super-enhancers and underscored the critical regulatory role of flow-sensitive endothelial super-enhancers. CRISPR interference and activation validated the function of a previously unrecognized unidirectional flow-induced super-enhancer that upregulates antioxidant genes NQO1, CYB5B, and WWP2, and a disturbed flow-induced super-enhancer in endothelium which drives prothrombotic genes EDN1 and HIVEP in vascular endothelium. Our results employing multiomics identify the cis-regulatory architecture of the flow-sensitive endothelial epigenome related to atherosclerosis and highlight the regulatory role of super-enhancers in mechanotransduction mechanisms. Show less
no PDF DOI: 10.1083/jcb.202211125
WWP2
Lu Huang, Xin Deng, Xiangqiong Yang +5 more · 2023 · Frontiers in endocrinology · Frontiers · added 2026-04-24
Melanocortin-3 and -4 receptors (MC3R and MC4R), G protein-coupled receptors, play vital roles in the regulation of energy homeostasis. To understand the functions of The full-length cDNAs of RCC In c Show more
Melanocortin-3 and -4 receptors (MC3R and MC4R), G protein-coupled receptors, play vital roles in the regulation of energy homeostasis. To understand the functions of The full-length cDNAs of RCC In conclusion, these results will assist in the further investigation of the molecular mechanisms in which MC3R and MC4R were involved in the regulation of energy homeostasis in fish. Show less
📄 PDF DOI: 10.3389/fendo.2023.1310000
MC4R
Yingyun Gong, Qinyi Wu, Shushu Huang +9 more · 2023 · Advanced biology · Wiley · added 2026-04-24
Mutations in MC4R are the most common genetic cause of obesity. In the reported Chinese morbid obesity cohort, 10 out of 59 harbor six MC4R variants, including Y35C, T53I, V103I, R165W, G233S, and C27 Show more
Mutations in MC4R are the most common genetic cause of obesity. In the reported Chinese morbid obesity cohort, 10 out of 59 harbor six MC4R variants, including Y35C, T53I, V103I, R165W, G233S, and C277X, among which V103I has a relatively high frequency, while other five variants are rare in the population. The prevalence of MC4R carriers in Chinese morbid obese patients (body mass index ≥ 45 kg m Show less
no PDF DOI: 10.1002/adbi.202300007
MC4R
Hongli Li, Yuanzhong Xu, Yanyan Jiang +9 more · 2023 · Nature communications · Nature · added 2026-04-24
The melanocortin action is well perceived for its ability to regulate body weight bidirectionally with its gain of function reducing body weight and loss of function promoting obesity. However, this n Show more
The melanocortin action is well perceived for its ability to regulate body weight bidirectionally with its gain of function reducing body weight and loss of function promoting obesity. However, this notion cannot explain the difficulty in identifying effective therapeutics toward treating general obesity via activation of the melanocortin action. Here, we provide evidence that altered melanocortin action is only able to cause one-directional obesity development. We demonstrate that chronic inhibition of arcuate neurons expressing proopiomelanocortin (POMC) or paraventricular hypothalamic neurons expressing melanocortin receptor 4 (MC4R) causes massive obesity. However, chronic activation of these neuronal populations failed to reduce body weight. Furthermore, gain of function of the melanocortin action through overexpression of MC4R, POMC or its derived peptides had little effect on obesity prevention or reversal. These results reveal a bias of the melanocortin action towards protection of weight loss and provide a neural basis behind the well-known, but mechanistically ill-defined, predisposition to obesity development. Show less
📄 PDF DOI: 10.1038/s41467-023-37912-z
MC4R
Hao Wu, Xin Ke, Wei Huang +7 more · 2023 · The Journal of investigative dermatology · Elsevier · added 2026-04-24
Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease with multiple environmental and genetic factors involved in its etiology. Although lots of genetic loci associated with AD have Show more
Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease with multiple environmental and genetic factors involved in its etiology. Although lots of genetic loci associated with AD have been reported by GWASs, only a small part of phenotypic variations can be explained. To identify additional susceptibility genes on AD, we conducted a large-scale transcriptome-wide association study using a joint-tissue imputation approach in ∼840,000 European individuals combined with six precomputed gene expression weights of four AD-relevant tissues, including skin fibroblast, lymphocyte, and whole blood. The Mendelian randomization causal inference analysis was performed to estimate the causal effect of transcriptome-wide association study‒identified genes. We identified 51 genes significantly associated with AD after Bonferroni corrections, and 19 genes showed putatively causal associations such as an established gene FLG (P = 3.98 × 10 Show less
no PDF DOI: 10.1016/j.jid.2022.09.006
ADCY3
Chih-Jie Shen, Ren-Hao Chan, Bo-Wen Lin +4 more · 2023 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.85855
ANGPTL4
X Zhao, H S Huang, S R Shi · 2023 · Molekuliarnaia biologiia · added 2026-04-24
Angiopoietin-like protein 4 (ANGPTL4) is considered to be one of the important circulating mediators linking intestinal microorganisms and host lipid metabolism. The objective of this study was to ass Show more
Angiopoietin-like protein 4 (ANGPTL4) is considered to be one of the important circulating mediators linking intestinal microorganisms and host lipid metabolism. The objective of this study was to assess the effects of peroxisome proliferator-activated receptor у (PPARγ) on modulating ANGPTL4 synthesis in Caco-2 cells exposed to Clostridium butyricum. The viability of Caco-2 cells and the expression of PPARγ and ANGPTL4 in Caco-2 cells were detected after the Caco-2 cells were co-cultured with C. butyricum at the concentration of 1 x 10⁽⁶⁾, 1 x 10⁽⁷⁾ and 1 x 10⁽⁸⁾ CFU/mL. The results showed that cell viability was enhanced by C. butyricum. Besides, PPARγ and ANGPTL4 expression and secretion in Caco-2 cells was significantly increased by 1 x 10⁽⁷⁾ and 1 x 10⁽⁸⁾ CFU/mL of C. butyricum. Furthermore, the effects of PPARγ on modulating ANGPTL4 synthesis in Caco-2 cells regulated by 1 x 10⁽⁸⁾ CFU/mL of C. butyricum was also be expounded in PPARγ activation/inhibition model based on Caco-2 cells and via ChIP technique. It was found that C. butyricum promoted the binding of PPARγ to the PPAR binding site (chr19: 8362157-8362357, located upstream of the transcriptional start site of angptl4) of the angptl4 gene in Caco-2 cells. However, the PPARγ was not the only way for C. butyricum to stimulate ANGPTL4 production. Taken together, PPARγ played a role in the regulation of ANGPTL4 synthesis by C. butyricum in Caco-2 cells. Show less
no PDF DOI: 10.31857/S0026898423030217
ANGPTL4
Fangfang Xu, Lijun Shen, Yongguang Yang +5 more · 2023 · Diabetes, metabolic syndrome and obesity : targets and therapy · added 2026-04-24
ANGPTL3, 4 and 8 have been reported to be involved in the regulation of lipid and glucose metabolism. The aim of this study was to investigate the expression of ANGPTL3, 4, 8 in hypertensive patients Show more
ANGPTL3, 4 and 8 have been reported to be involved in the regulation of lipid and glucose metabolism. The aim of this study was to investigate the expression of ANGPTL3, 4, 8 in hypertensive patients with or without overweight/obesity, T2D, and hyperlipidemia, and the possible association between their expression and the status of the aforementioned comorbidities. Plasma levels of ANGPTL3, 4, and 8 in 87 hospitalized patients with hypertension were measured using ELISA kits. Associations between circulating ANGPTLs levels and the most common additional cardiovascular risk factors were assessed using multivariate linear regression analyses. Pearson's correlation analysis was used to examine the association between ANGPTLs and clinical parameters. In the context of hypertension, (1) although not statistically significant, circulating ANGPTL3 levels were higher in the overweight/obese group than in the normal weight group; (2) circulating levels of ANGPTL3 and ANGPTL8 were significantly lower in patients with T2D than in non-diabetic patients; (3) circulating ANGPTL3 levels were significantly higher in the hyperlipidemic group than in the non-hyperlipidemic group. ANGPTL3 was associated with T2D and hyperlipidemia status, whereas ANGPTL8 was independently associated with T2D status. In addition, circulating ANGPTL3 levels were positively correlated with TC, TG, LDL-C, HCY, and ANGPTL8, and circulating ANGPTL4 levels were positively correlated with UACR and BNP. Changes in circulating ANGPTL3 and ANGPTL8 levels have been observed in hypertensive patients with the most common additional cardiovascular risk factors, suggesting a role in the common comorbidities of hypertension and cardiovascular disease. Hypertensive patients with overweight/obesity or hyperlipidemia may benefit from therapies targeting ANGPTL3. Show less
📄 PDF DOI: 10.2147/DMSO.S411483
ANGPTL4
Saisai Huang, Zhuoya Zhang, Yiyuan Cui +3 more · 2023 · Clinical rheumatology · Springer · added 2026-04-24
Disturbed lipid metabolism was observed in systemic lupus erythematosus (SLE) patients. This study aimed to evaluate the relationships between dyslipidemia and visceral organ involvement, disease seve Show more
Disturbed lipid metabolism was observed in systemic lupus erythematosus (SLE) patients. This study aimed to evaluate the relationships between dyslipidemia and visceral organ involvement, disease severity, inflammatory factors, and drug intake in SLE patients. Inpatients with SLE (n = 105) and healthy controls (HC) (n = 75) were recruited in this study. Clinical and laboratory data were collected from patient records. The concentrations of tumor necrosis factor receptors superfamily member1A (TNFRSF1A), member1B (TNFRSF1B) and adipokine angiopoietin-like 4 (ANGPTL4) in plasma were measured by ELISA. Compared to HC, serum levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and apolipoprotein B (ApoB) were significantly increased, while high-density lipoprotein (HDL) and apolipoprotein A1 (ApoA1) were decreased in SLE patients. Patients with higher disease activity and renal damage suffered from more severe dyslipidemia. Renal functional parameters were closely correlated with serum lipid levels. Inflammatory factors were associated with dyslipidemia. The levels of TNFRSF1A and TNFRSF1B were obviously increased and associated with kidney involvement in SLE patients. Patients with high-dose glucocorticoid intake showed more severe dyslipidemia. Attention should be paid to the dyslipidemia of SLE. Dyslipidemia is associated with inflammation and organ involvement in SLE. These findings might provide a new strategy for the treatment of SLE. Key Points • Serum levels of TG, TC, LDL, and ApoB were significantly increased, while HDL and ApoA1 were decreased in SLE patients. • Patients with higher disease activity and renal damage suffered from more severe dyslipidemia. Renal functional parameters and inflammatory factors were closely correlated with serum lipid levels. • Patients with high-dose glucocorticoid intake showed more severe dyslipidemia. • These findings might provide a new strategy for the treatment of SLE. Show less
📄 PDF DOI: 10.1007/s10067-023-06539-2
ANGPTL4
Wenhui Qiu, Luyang Huang, YueQiang Li +2 more · 2023 · Current pharmaceutical design · Bentham Science · added 2026-04-24
Angiopoietin-like protein 4 (Angptl4) is a glycoprotein that is involved in regulating lipid metabolism, which has been indicated as a link between hypertriglyceridemia and albuminuria in glomerulonep Show more
Angiopoietin-like protein 4 (Angptl4) is a glycoprotein that is involved in regulating lipid metabolism, which has been indicated as a link between hypertriglyceridemia and albuminuria in glomerulonephropathy. Deregulated lipid metabolism is increasingly recognized as an important risk factor of glomerulonephropathy. This study aimed to investigate the Angptl4 expression in renal tissue and podocyte under hyperlipidemia conditions and explore the potential molecular mechanisms. The role of Angptl4 in hyperlipidemia-induced glomerular disease and the detailed underlying mechanisms are unclear. This study sought new insights into this issue. We measured Angptl4 levels in the plasma and urine from patients with hyperlipidemia and healthy people. Rats were fed a high fat diet (HFD) to induce dyslipidemia model and the human podocytes were stimulated by palmitic acid as in vivo and in vitro experiments. The podocytes injury and the Angptl4 level in renal tissues were evaluated. Furthermore, the mechanism of Angptl4 on podocytes injury was investigated. The urinary Angptl4 level was gradually upregulated in both patients with hyperlipidaemia and high fat-diet-induced rats. HFD rats showed increased 24 h urinary protein and glomerular tuft area at week 12. The levels of nephrin and WT-1 were down-regulated, but the Angptl4 levels were markedly upregulated on the glomerular of rats on HFD. In the human podocytes, lipid accumulation accompanied by increases of Angptl4, but the expression of nephrin, WT-1, p-AMPKα and p-ACC was decreased after palmitic acid treatment. However, this injury effect was mediated by the aminoimidazole-4-carboxamide-1β-D-ribofuranoside (AICAR), activator of the low energy sensor AMPK/ACC signaling. This study was the first of its kind to show that podocyte damage induced by dyslipidemia could be associated with upregulated Angptl4 and that patients with hyperlipidemia might have relatively high urinary Angptl4 expression. The dysregulation of Angptl4 in the podocytes under hyperlipidemia is possibly carried out through AMPK/ACC signaling pathway. Show less
no PDF DOI: 10.2174/1381612829666221219123937
ANGPTL4
Xiaoying Gu, Siyuan Wang, Wanying Zhang +15 more · 2023 · EBioMedicine · Elsevier · added 2026-04-24
As a debilitating condition that can impact a whole spectrum of people and involve multi-organ systems, long COVID has aroused the most attention than ever. However, mechanisms of long COVID are not c Show more
As a debilitating condition that can impact a whole spectrum of people and involve multi-organ systems, long COVID has aroused the most attention than ever. However, mechanisms of long COVID are not clearly understood, and underlying biomarkers that can affect the long-term consequences of COVID-19 are paramount to be identified. Participants for the current study were from a cohort study of COVID-19 survivors discharged from hospital between Jan 7, and May 29, 2020. We profiled the proteomic of plasma samples from hospitalised COVID-19 survivors at 6-month, 1-year, and 2-year after symptom onset and age and sex matched healthy controls. Fold-change of >2 or <0.5, and false-discovery rate adjusted P value of 0.05 were used to filter differentially expressed proteins (DEPs). In-genuity pathway analysis was performed to explore the down-stream effects in the dataset of significantly up- or down-regulated proteins. Proteins were integrated with long-term consequences of COVID-19 survivors to explore potential biomarkers of long COVID. The proteomic of 709 plasma samples from 181 COVID-19 survivors and 181 matched healthy controls was profiled. In both COVID-19 and control group, 114 (63%) were male. The results indicated four major recovery modes of biological processes. Pathways related to cell-matrix interactions and cytoskeletal remodeling and hypertrophic cardiomyopathy and dilated cardiomyopathy pathways recovered relatively earlier which was before 1-year after infection. Majority of immune response pathways, complement and coagulation cascade, and cholesterol metabolism returned to similar status of matched healthy controls later but before 2-year after infection. Fc receptor signaling pathway still did not return to status similar to healthy controls at 2-year follow-up. Pathways related to neuron generation and differentiation showed persistent suppression across 2-year after infection. Among 98 DEPs from the above pathways, evidence was found for association of 11 proteins with lung function recovery, with the associations consistent at two consecutive or all three follow-ups. These proteins were mainly enriched in complement and coagulation (COMP, PLG, SERPINE1, SRGN, COL1A1, FLNA, and APOE) and hypertrophic/dilated cardiomyopathy (TPM2, TPM1, and AGT) pathways. Two DEPs (APOA4 and LRP1) involved in both neuron and cholesterol pathways showed associations with smell disorder. The study findings provided molecular insights into potential mechanism of long COVID, and put forward biomarkers for more precise intervention to reduce burden of long COVID. National Natural Science Foundation of China; Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences; Clinical Research Operating Fund of Central High Level Hospitals; the Talent Program of the Chinese Academy of Medical Science; Training Program of the Big Science Strategy Plan; Ministry of Science and Technology of the People's Republic of China; New Cornerstone Science Foundation; Peking Union Medical College Education Foundation; Research Funds from Health@InnoHK Program. Show less
📄 PDF DOI: 10.1016/j.ebiom.2023.104851
APOA4
Lu Shi, Jingkang Wang, Changhao He +14 more · 2023 · BMC complementary medicine and therapies · BioMed Central · added 2026-04-24
Mulberry (Morus alba L.) leaf, as a medicinal and food homologous traditional Chinese medicine, has a clear therapeutic effect on type 2 diabetes mellitus (T2DM), yet its underlying mechanisms have no Show more
Mulberry (Morus alba L.) leaf, as a medicinal and food homologous traditional Chinese medicine, has a clear therapeutic effect on type 2 diabetes mellitus (T2DM), yet its underlying mechanisms have not been totally clarified. The study aimed to explore the mechanism of mulberry leaf in the treatment of T2DM through tandem mass tag (TMT)-based quantitative proteomics analysis of skeletal muscle. The anti-diabetic activity of mulberry leaf extract (MLE) was evaluated by using streptozotocin-induced diabetic rats at a dose of 4.0 g crude drug /kg p.o. daily for 8 weeks. Fasting blood glucose, body weight, food and water intake were monitored at specific intervals, and oral glucose tolerance test and insulin tolerance test were conducted at the 7th and 8th week respectively. At the end of the experiment, levels of glycated hemoglobin A1c, insulin, free fat acid, leptin, adiponectin, total cholesterol, triglyceride, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol were assessed and the pathological changes of rat skeletal muscle were observed by HE staining. TMT-based quantitative proteomic analysis of skeletal muscle and bioinformatics analysis were performed and differentially expressed proteins (DEPs) were validated by western blot. The interactions between the components of MLE and DEPs were further assessed using molecular docking. After 8 weeks of MLE intervention, the clinical indications of T2DM such as body weight, food and water intake of rats were improved to a certain extent, while insulin sensitivity was increased and glycemic control was improved. Serum lipid profiles were significantly reduced, and the skeletal muscle fiber gap and atrophy were alleviated. Proteomic analysis of skeletal muscle showed that MLE treatment reversed 19 DEPs in T2DM rats, regulated cholesterol metabolism, fat digestion and absorption, vitamin digestion and absorption and ferroptosis signaling pathways. Key differential proteins Apolipoprotein A-1 (ApoA1) and ApoA4 were successfully validated by western blot and exhibited strong binding activity to the MLE's ingredients. This study first provided skeletal muscle proteomic changes in T2DM rats before and after MLE treatment, which may help us understand the molecular mechanisms, and provide a foundation for developing potential therapeutic targets of anti-T2DM of MLE. Show less
📄 PDF DOI: 10.1186/s12906-023-04140-3
APOA4
Yue Wang, Longfei Dai, Ran Huang +2 more · 2023 · Frontiers in oncology · Frontiers · added 2026-04-24
Cellular senescence occurs throughout life and can play beneficial roles in a variety of physiological processes, including embryonic development, tissue repair, and tumor suppression. However, the re Show more
Cellular senescence occurs throughout life and can play beneficial roles in a variety of physiological processes, including embryonic development, tissue repair, and tumor suppression. However, the relationship between cellular senescence-related genes (CSRGs) and immunotherapy in esophageal carcinoma (ECa) remains poorly defined. The data set used in the analysis was retrieved from TCGA (Research Resource Identifier (RRID): SCR₀₀₃₁₉₃₎, GEO (RRID: SCR₀₀₅₀₁₂₎, and CellAge databases. Data processing, statistical analysis, and diagram formation were conducted in R software (RRID: SCR₀₀₁₉₀₅₎ and GraphPad Prism (RRID: SCR₀₀₂₇₉₈₎. Based on CSRGs, we used the TCGA database to construct a prognostic signature for ECa and then validated it in the GEO database. The predictive efficiency of the signature was evaluated using receiver operating characteristic (ROC) curves, Cox regression analysis, nomogram, and calibration curves. According to the median risk score derived from CSRGs, patients with ECa were divided into high- and low-risk groups. Immune infiltration and immunotherapy were also analyzed between the two risk groups. Finally, the hub genes of the differences between the two risk groups were identified by the STRING (RRID: SCR₀₀₅₂₂₃₎ database and Cytoscape (RRID: SCR₀₀₃₀₃₂₎ software. A six-gene risk signature (DEK, RUNX1, SMARCA4, SREBF1, TERT, and TOP1) was constructed in the TCGA database. Patients in the high-risk group had a worse overall survival (OS) was disclosed by survival analysis. As expected, the signature presented equally prognostic significance in the GSE53624 cohort. Next, the Area Under ROC Curve (AUC=0.854) and multivariate Cox regression analysis (HR=3.381, 2.073-5.514, Our study reveals comprehensive clues that a novel signature based on CSRGs may provide reliable prognosis prediction and insight into new therapy for patients with ECa. Show less
📄 PDF DOI: 10.3389/fonc.2023.1203351
APOA4
Jun Ji, Xiaoyu Zhao, Jiajun Huang +5 more · 2023 · Experimental biology and medicine (Maywood, N.J.) · SAGE Publications · added 2026-04-24
Diabetic peripheral arterial atherosclerosis is one of the important characteristics of diabetic foot syndrome. Apolipoprotein (Apo A-IV) participates in various physiological processes, and animal st Show more
Diabetic peripheral arterial atherosclerosis is one of the important characteristics of diabetic foot syndrome. Apolipoprotein (Apo A-IV) participates in various physiological processes, and animal studies have shown that it has roles of anti-atherosclerosis, prevention of platelet aggregation and thrombosis. Apo A-IV glycosylation is closely related to the occurrence and development of diabetic peripheral atherosclerosis. This study aimed to explore the mechanism of diabetic peripheral arterial lesions caused by glycosylated Apo A-IV. Type 2 diabetes mellitus (T2DM) and T2DM with diabetic foot patients (T2DM-F; Show less
no PDF DOI: 10.1177/15353702221147562
APOA4
Xiao-Huan Liu, Yupeng Zhang, Liao Chang +8 more · 2023 · Molecular and cellular endocrinology · Elsevier · added 2026-04-24
Apolipoprotein A-IV (ApoA-IV) plays a role in satiation and serum lipid transport. In diet-induced obesity (DIO) C57BL/6J mice, ApoA-IV deficiency induced in ApoA-IV-/-knock-out (KO mice) resulted in Show more
Apolipoprotein A-IV (ApoA-IV) plays a role in satiation and serum lipid transport. In diet-induced obesity (DIO) C57BL/6J mice, ApoA-IV deficiency induced in ApoA-IV-/-knock-out (KO mice) resulted in increased bodyweight, insulin resistance (IR) and plasma free fatty acid (FFA), which was partially reversed by stable ApoA-IV-green fluorescent protein (KO-A4-GFP) transfection in KO mice. DIO KO mice exhibited increased M1 macrophages in epididymal white adipose tissue (eWAT) as well as in the blood. Based on RNA-sequencing analyses, cytokine-cytokine receptor interactions, T cell and B cell receptors, and especially IL-17 and TNF-α, were up-regulated in eWAT of DIO ApoA-IV KO compared with WT mice. Supplemented ApoA-IV suppressed lipopolysaccharide (LPS)-induced IKK and JNK phosphorylation in Raw264.7 macrophage cell culture assays. When the culture medium was supplemented to 3T3-L1 adipocytes they exhibited an increased sensitivity to insulin. ApoA-IV protects against obesity-associated metabolic inflammation mainly through suppression in M1 macrophages of eWAT, IL17-IKK and IL17-JNK activity. Show less
no PDF DOI: 10.1016/j.mce.2022.111813
APOA4
Chih-Yi Ho, Jia-In Lee, Shu-Pin Huang +2 more · 2023 · Nutrients · MDPI · added 2026-04-24
The purpose of this study was to investigate genetic factors associated with metabolic syndrome (MetS) by conducting a large-scale genome-wide association study (GWAS) in Taiwan, addressing the limite Show more
The purpose of this study was to investigate genetic factors associated with metabolic syndrome (MetS) by conducting a large-scale genome-wide association study (GWAS) in Taiwan, addressing the limited data on Asian populations compared to Western populations. Using data from the Taiwan Biobank, comprehensive clinical and genetic information from 107,230 Taiwanese individuals was analyzed. Genotyping data from the TWB1.0 and TWB2.0 chips, including over 650,000 single nucleotide polymorphisms (SNPs), were utilized. Genotype imputation using the 1000 Genomes Project was performed, resulting in more than 9 million SNPs. MetS was defined based on a modified version of the Adult Treatment Panel III criteria. Among all participants (mean age: 50 years), 23% met the MetS definition. GWAS analysis identified 549 SNPs significantly associated with MetS, collectively mapping to 10 genomic risk loci. Notable risk loci included rs1004558, rs3812316, rs326, rs4486200, rs2954038, rs10830963, rs662799, rs62033400, rs183130, and rs34342646. Gene-set analysis revealed 22 associated genes: Show less
📄 PDF DOI: 10.3390/nu16010077
APOA5
Jiayu Wu, Qiaoming Fan, Qi He +7 more · 2023 · Medicine · added 2026-04-24
Myocardial infarction (MI) is a major cause of death and disability worldwide, but current treatments are limited by their invasiveness, side effects, and lack of efficacy. Novel drug targets for MI p Show more
Myocardial infarction (MI) is a major cause of death and disability worldwide, but current treatments are limited by their invasiveness, side effects, and lack of efficacy. Novel drug targets for MI prevention are urgently needed. In this study, we used Mendelian randomization to identify potential therapeutic targets for MI using plasma protein quantitative trait loci as exposure variables and MI as the outcome variable. We further validated our findings using reverse causation analysis, Bayesian co-localization analysis, and external datasets. We also constructed a protein-protein interaction network to explore the relationships between the identified proteins and known MI targets. Our analysis revealed 2 proteins, LPA and APOA5, as potential drug targets for MI, with causal effects on MI risk confirmed by multiple lines of evidence. LPA and APOA5 are involved in lipid metabolism and interact with target proteins of current MI medications. We also found 4 other proteins, IL1RN, FN1, NT5C, and SEMA3C, that may have potential as drug targets but require further confirmation. Our study demonstrates the utility of Mendelian randomization and protein quantitative trait loci in discovering novel drug targets for complex diseases such as MI. It provides insights into the underlying mechanisms of MI pathology and treatment. Show less
📄 PDF DOI: 10.1097/MD.0000000000036284
APOA5