Back Cover: Integrating Aggregate Materials and Machine Learning Algorithms: Advancing Detection of Pathogen-Derived Extracellular Vesicles

IF 13.9 Q1 CHEMISTRY, MULTIDISCIPLINARY
Lihan Lai, Yun Su, Cong Hu, Zehong Peng, Wei Xue, Liang Dong, Tony Y. Hu
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引用次数: 0

Abstract

This review highlights cutting-edge strategies for enhancing the detection of pathogen-derived extracellular vesicles, including novel aggregate materials and machine learning approaches. Pathogen-derived vesicles are pivotal in host-pathogen interactions and possess significant diagnostic promise, as their unique cargo offers a rich repository of potential biomarkers. Enhancing vesicle detection may ultimately pave the way for transformative clinical applications (e70018).

封底:整合聚合材料和机器学习算法:推进病原体来源的细胞外囊泡的检测
本文综述了加强病原体来源的细胞外囊泡检测的前沿策略,包括新型聚集体材料和机器学习方法。病原体来源的囊泡在宿主-病原体相互作用中起着关键作用,并且具有重要的诊断前景,因为它们独特的货物提供了丰富的潜在生物标志物库。增强囊泡检测可能最终为变革性临床应用铺平道路(e70018)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
17.40
自引率
0.00%
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0
审稿时长
7 weeks
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