Table 3_Recent progress in tuberculosis diagnosis: insights into blood-based biomarkers and emerging technologies.docx

Tuberculosis (TB) remains a global health challenge, with timely and accurate diagnosis being critical for effective disease management and control. Recent advancements in the field of TB diagnostics have focused on the identification and utilization of blood-based biomarkers, offering a non-invasive, rapid, and scalable approach to disease detection. This review provides a comprehensive overview of the latest progress in blood-based biomarkers for TB, highlighting their potential to revolutionize diagnostic strategies. Furthermore, we explore emerging technologies such as NGS, PET-CT, Xpert and line probe assays, which have enhanced the sensitivity, specificity, and accessibility of biomarker-based diagnostics. The integration of artificial intelligence (AI) and machine learning (ML) in biomarker analysis is also examined, showcasing its potential to improve diagnostic accuracy and predictive capabilities. This review underscores the need for multidisciplinary collaboration and continued innovation to translate these promising technologies into practical, point-of-care solutions. By addressing these challenges, blood-based biomarkers and emerging technologies hold the potential to significantly improve TB diagnosis, ultimately contributing to global efforts to eradicate this devastating disease.

结核病（Tuberculosis, TB）仍是一项全球性公共卫生挑战，及时且精准的诊断对于疾病的有效管控与防控至关重要。结核病诊断领域的最新进展聚焦于血液生物标志物的识别与应用，为疾病检测提供了一种非侵入式、快速且可规模化推广的检测路径。本综述全面梳理了结核病血液生物标志物领域的最新研究进展，着重阐述了其革新诊断策略的巨大潜力。此外，本综述还探讨了下一代测序（NGS）、正电子发射计算机断层显像（PET-CT）、Xpert检测系统以及线性探针检测（line probe assays）等新兴技术，这些技术提升了基于生物标志物的诊断方法的灵敏度、特异性与可及性。人工智能（AI）与机器学习（ML）在生物标志物分析中的整合应用也得到了探讨，展现了其提升诊断准确性与预测能力的潜力。本综述强调了多学科协作与持续创新的必要性，以将这些极具前景的技术转化为实用的床旁检测解决方案。通过应对这些挑战，血液生物标志物与新兴技术有望大幅提升结核病诊断水平，最终为全球根除这一毁灭性疾病的努力作出贡献。