Obeagu Emmanuel Ifeanyi, Okoroiwu G I A, Ubosi N I, Obeagu Getrude U, Onohuean Hope, Muhammad Tukur, Adias Teddy C
Department of Medical Laboratory Science, Kampala International University.
Department of Public Health Science, Faculty of Health Sciences, National Open University of Nigeria, Jabi, Abuja.
Ann Med Surg (Lond). 2024 Jul 17;86(10):5859-5876. doi: 10.1097/MS9.0000000000002383. eCollection 2024 Oct.
The ongoing battle against malaria has seen significant advancements in diagnostic methodologies, particularly through the discovery and application of novel biomarkers. Traditional diagnostic techniques, such as microscopy and rapid diagnostic tests, have their limitations in terms of sensitivity, specificity, and the ability to detect low-level infections. Recent breakthroughs in biomarker research promise to overcome these challenges, providing more accurate, rapid, and non-invasive detection methods. These advancements are critical in enhancing early detection, guiding effective treatment, and ultimately reducing the global malaria burden. Innovative approaches in biomarker detection are leveraging cutting-edge technologies like next-generation sequencing, proteomics, and metabolomics. These techniques have led to the identification of new biomarkers that can be detected in blood, saliva, or urine, offering less invasive and more scalable options for widespread screening. For instance, the discovery of specific volatile organic compounds in the breath of infected individuals presents a revolutionary non-invasive diagnostic tool. Additionally, the integration of machine learning algorithms with biomarker data is enhancing the precision and predictive power of malaria diagnostics, making it possible to distinguish between different stages of infection and identify drug-resistant strains. Looking ahead, the future of malaria detection lies in the continued exploration of multi-biomarker panels and the development of portable, point-of-care diagnostic devices. The incorporation of smartphone-based technologies and wearable biosensors promises to bring real-time monitoring and remote diagnostics to even the most resource-limited settings.
在抗击疟疾的持续斗争中,诊断方法取得了重大进展,特别是通过新型生物标志物的发现和应用。传统的诊断技术,如显微镜检查和快速诊断测试,在灵敏度、特异性以及检测低水平感染的能力方面存在局限性。生物标志物研究的最新突破有望克服这些挑战,提供更准确、快速且非侵入性的检测方法。这些进展对于加强早期检测、指导有效治疗并最终减轻全球疟疾负担至关重要。生物标志物检测的创新方法正在利用下一代测序、蛋白质组学和代谢组学等前沿技术。这些技术已导致发现了可在血液、唾液或尿液中检测到的新生物标志物,为广泛筛查提供了侵入性较小且更具可扩展性的选择。例如,在受感染个体呼出的气体中发现特定的挥发性有机化合物,提供了一种革命性的非侵入性诊断工具。此外,将机器学习算法与生物标志物数据相结合,正在提高疟疾诊断的精度和预测能力,从而能够区分感染的不同阶段并识别耐药菌株。展望未来,疟疾检测的未来在于持续探索多生物标志物组合以及开发便携式即时诊断设备。基于智能手机的技术和可穿戴生物传感器的纳入有望为即使是资源最有限的环境带来实时监测和远程诊断。