Jiarui Chen
Wuhan University
45 Papers
37 Citations
Jiarui Chen is an academic researcher from Wuhan University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 3, co-authored 3 publications.
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Papers
Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis
Jichong Zhu,Qing Lu,Tuo Liang,JieJiang,Hao Li,Chenxing Zhou,Shaofeng Wu,Tianyou Chen,Jiarui Chen,Guobing Deng,Yuanlin Yao,Shian Liao,Chao Jie Yu,Shengsheng Huang,Xuhua Sun,Liyi Chen,Wenkang Chen,Zhen Ye,Hao Guo,Wuhua Chen,Binguang Fan,Xiang Tao,Xinli Zhan,Chong Liu +23 more
TL;DR: Wang et al. as discussed by the authors used machine learning (ML) methods to construct diagnostic models based on blood routine examination, liver function test, and kidney function test of patients with ankylosing spondylitis.
Baicalein suppresses the proliferation of acute T-lymphoblastic leukemia Jurkat cells by inhibiting the Wnt/β-catenin signaling.
TL;DR: It is proved that baicalein might be a potential choice for the treatment of T-ALL by demonstrating that it could down-regulated the mRNA and protein levels of β-catenin and its widely accepted downstream targets in dose-dependent manners.
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Transfer of microRNA-22-3p by M2 macrophage-derived extracellular vesicles facilitates the development of ankylosing spondylitis through the PER2-mediated Wnt/β-catenin axis
TL;DR: In this article , extracellular vesicle (EV)-packaged microRNA-22-3p from M2 macrophages in the osteogenic differentiation of mesenchymal stem cells (MSCs) in ankylosing spondylitis (AS).
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Baicalein suppresses the proliferation of acute T-lymphoblastic
Xiangyu Meng,Sheng-cai Liu,Li He,Jiarui Chen,Xiao-Ping Liu,Shangqin Liu +5 more
- 01 Jan 2016
TL;DR: In this article, the authors used Jurkat cells as an in vitro model of T-ALL and showed that baicalein could inhibit the proliferation of Jurkat cell both in dose-and time-dependent manners.
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MMP9 and STAT1 are biomarkers of the change in immune infiltration after anti-tuberculosis therapy, and the immune status can identify patients with spinal tuberculosis.
Chenxing Zhou,Tuo Liang,Jie Jiang,Jiarui Chen,Tianyou Chen,Shengsheng Huang,Liyi Chen,Xuhua Sun,Wenkang Chen,Jichong Zhu,Shaofeng Wu,Binguang Fan,Chong Liu,Xinli Zhan +13 more
TL;DR: In this article , the authors investigated the possible pathogenesis of STB and developed a clinical diagnostic model for STB based on immune cell infiltration using GO enrichment analysis and KEGG pathway analysis.
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