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Plasmonic Biosensors for Health Monitoring: Inflammation Biomarker Detection

生物传感器 纳米技术 表面等离子共振 降钙素原 生物标志物 材料科学 计算机科学 医学 纳米颗粒 化学 免疫学 败血症 生物化学
作者
Muhammad Amirul Islam,Jean‐François Masson
出处
期刊:ACS Sensors [American Chemical Society]
卷期号:10 (2): 577-601 被引量:54
标识
DOI:10.1021/acssensors.4c03562
摘要

Surface plasmon resonance (SPR) and localized SPR (LSPR) biosensors have emerged as viable technologies in the clinical detection of biomarkers for a wide array of health conditions. The success of SPR biosensors lies in their ability to monitor in real-time label-free biomarkers in complex biofluids. Recent breakthroughs in nanotechnology and surface chemistry have significantly improved this feature, notably from the incorporation of advanced nanomaterials including gold nanoparticles, graphene, and carbon nanotubes providing better SPR sensor performance in terms of detection limits, stability, and specificity. Recent progress in microfluidic integration has enabled SPR biosensors to detect multiple biomarkers simultaneously in complex biological samples. Taken together, these advances are closing the gap for their use in clinical diagnostics and point-of-care (POC) applications. While broadly applicable, the latest advancements in plasmonic biosensing are overviewed using inflammation biomarkers C-reactive protein (CRP), interleukins (ILs), tumor necrosis factor-α (TNF-α), procalcitonin (PCT), ferritin, and fibrinogen for a series of conditions, including cardiovascular diseases, autoimmune disorders, infections, and sepsis, as a key example of plasmonic biosensors for clinical applications. We highlight developments in sensor design, nanomaterial integration, surface functionalization, and multiplexing and provide a look forward to clinical applications by assessing the current limitations and exploring future directions for translating SPR biosensors for diagnostics and health monitoring. By enhancement of diagnostic accuracy, reproducibility, and accessibility, particularly in POC settings, SPR biosensors have the potential to significantly contribute to personalized healthcare and bring real-time, high-precision diagnostics to the forefront of clinical practice.
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