{"title":"Correlation Between Fecal Microbiota and Corticosteroid Responsiveness in Primary Immune Thrombocytopenia: an Exploratory Study (Adv. Sci. 22/2025)","authors":"Feng-Qi Liu, Zhuo-Yu An, Li-Juan Cui, Meng-Yu Xiao, Ye-Jun Wu, Wei Li, Bang-Shuo Zhang, Li Yu, Jia Feng, Zhuo-Gang Liu, Ru Feng, Zhong-Xing Jiang, Rui-Bin Huang, Hong-Mei Jing, Jin-Hai Ren, Xiao-Yu Zhu, Yun-Feng Cheng, Yu-Hua Li, He-Bing Zhou, Da Gao, Yi Liu, Fan Yu, Xin Wang, Jian-Lin Qiao, Dai-Hong Hu, Lu-Lu Wang, Meng-Tong Zang, Qi Chen, Qing-Yuan Qu, Jian-Ying Zhou, Meng-Lin Li, Yu-Xiu Chen, Qiu-Sha Huang, Hai-Xia Fu, Yue-Ying Li, Qian-Fei Wang, Xiao-Jun Huang, Xiao-hui Zhang, the Cooperative ITP Working Group","doi":"10.1002/advs.202570168","DOIUrl":null,"url":null,"abstract":"<p><b>Immune Thrombocytopenia</b></p><p>Immune thrombocytopenia (ITP) is characterized by splenic platelet destruction and dysfunctional megakaryocyte maturation. Emerging research demonstrates that machine learning frameworks analyzing gut microbiome profiles and clinical parameters can reliably forecast treatment responses to corticosteroids through microbiota-immune axis modulation. This predictive modeling approach enables personalized therapeutic strategies in ITP care, advancing precision hematology through computational biomarker integration. More details can be found in article number 2410417 by Xiao-hui Zhang and co-worders.\n\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":"12 22","pages":""},"PeriodicalIF":14.3000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/advs.202570168","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/advs.202570168","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Immune Thrombocytopenia
Immune thrombocytopenia (ITP) is characterized by splenic platelet destruction and dysfunctional megakaryocyte maturation. Emerging research demonstrates that machine learning frameworks analyzing gut microbiome profiles and clinical parameters can reliably forecast treatment responses to corticosteroids through microbiota-immune axis modulation. This predictive modeling approach enables personalized therapeutic strategies in ITP care, advancing precision hematology through computational biomarker integration. More details can be found in article number 2410417 by Xiao-hui Zhang and co-worders.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.