Quantitative Assessment of Fungal Biomarkers in Clinical Samples via an Interface-Modulated Optical Fiber Biosensor

© 2024 Wiley‐VCH GmbH.

Bibliographische Detailangaben
Veröffentlicht in:Advanced materials (Deerfield Beach, Fla.). - 1998. - 36(2024), 21 vom: 27. Mai, Seite e2312985
1. Verfasser: Chen, Pengwei (VerfasserIn)
Weitere Verfasser: Wu, Haotian, Zhao, Yajing, Zhong, Lv, Zhang, Yujiao, Zhan, Xundi, Xiao, Aoxiang, Huang, Yunyun, Zhang, Hong, Guan, Bai-Ou
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Advanced materials (Deerfield Beach, Fla.)
Schlagworte:Journal Article clinical samples interface modulation optical fiber biosensor point‐of‐care testing quantitative assessment Biomarkers
Beschreibung
Zusammenfassung:© 2024 Wiley‐VCH GmbH.
Invasive fungal infections pose a significant public health threat. The lack of precise and timely diagnosis is a primary factor contributing to the significant increase in patient mortality rates. Here, an interface-modulated biosensor utilizing an optical fiber for quantitative analysis of fungal biomarkers at the early stage of point-of-care testing (POCT), is reported. By integrating surface refractive index (RI) modulation and plasmon enhancement, the sensor to achieve high sensitivity in a directional response to the target analytes, is successfully optimized. As a result, a compact fiber-optic sensor with rapid response time, cost-effectiveness, exceptional sensitivity, stability, and specificity, is developed. This sensor can successfully identify the biomarkers of specific pathogens from blood or other tissue specimens in animal models. It quantifies clinical blood samples with precision and effectively discriminates between negative and positive cases, thereby providing timely alerts to potential patients. It significantly reduces the detection time of fungal infection to only 30 min. Additionally, this approach exhibits remarkable stability and achieves a limit of detection (LOD) three orders of magnitude lower than existing methods. It overcomes the limitations of existing detection methods, including a high rate of misdiagnosis, prolonged detection time, elevated costs, and the requirement for stringent laboratory conditions
Beschreibung:Date Completed 24.05.2024
Date Revised 24.05.2024
published: Print-Electronic
Citation Status MEDLINE
ISSN:1521-4095
DOI:10.1002/adma.202312985