Biosensing for rapid detection of MDR, XDR and PDR bacteria.

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2025-02-01 Epub Date: 2024-12-31 DOI:10.1016/j.cca.2024.120121
Samad Rastmanesh, Ilghar Zeinaly, Vahid Alivirdiloo, Ahmad Mobed, Mohammad Darvishi
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Abstract

The emergence of multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) bacteria poses a significant threat to global public health, complicating the management of infectious diseases and increasing morbidity and mortality rates. Rapid and sensitive detection of these resistant pathogens is crucial for effective treatment and infection control. This manuscript provides a comprehensive overview of various biosensor technologies developed for the rapid identification and quantification of MDR and XDR bacteria. We discuss the principles of operation, sensitivity, specificity, and practical applications of different biosensing platforms, including electrochemical, optical, and piezoelectric sensors. Additionally, we explore recent advancements in nanomaterials and microfluidics that enhance biosensor performance and enable point-of-care testing. The manuscript also addresses the challenges faced in the implementation of these technologies in clinical settings, such as regulatory hurdles and the need for standardization. A systematic literature review was conducted to identify relevant studies. Databases utilized include PubMed and Scopus, covering the time frame from 2015 to 2024. The literature screening criteria focused on the inclusion of only clinically validated studies to ensure the reliability and applicability of the findings. By highlighting the potential of biosensors to revolutionize the detection of drug-resistant bacteria, this work aims to inform researchers, clinicians, and policymakers about the critical role of innovative diagnostic tools in combating antibiotic resistance and improving patient outcomes.

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用于MDR、XDR和PDR细菌快速检测的生物传感技术。
耐多药(MDR)、广泛耐药(XDR)和耐潘德药(PDR)细菌的出现对全球公共卫生构成了重大威胁,使传染病的管理复杂化,并增加了发病率和死亡率。快速灵敏地检测这些耐药病原体对于有效治疗和感染控制至关重要。本手稿全面概述了为快速识别和定量 MDR 和 XDR 细菌而开发的各种生物传感器技术。我们讨论了不同生物传感平台(包括电化学、光学和压电传感器)的工作原理、灵敏度、特异性和实际应用。此外,我们还探讨了纳米材料和微流控技术的最新进展,这些技术提高了生物传感器的性能,实现了床旁检测。稿件还探讨了在临床环境中应用这些技术所面临的挑战,如监管障碍和标准化需求。为确定相关研究,我们进行了系统的文献综述。使用的数据库包括 PubMed 和 Scopus,时间跨度为 2015 年至 2024 年。文献筛选标准侧重于只纳入经过临床验证的研究,以确保研究结果的可靠性和适用性。通过强调生物传感器在彻底改变耐药细菌检测方面的潜力,本研究旨在让研究人员、临床医生和政策制定者了解创新诊断工具在抗击抗生素耐药性和改善患者预后方面的关键作用。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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