ScholarWorks@성균관대학교

초록

Rapid and accurate differential diagnosis of infections, sepsis, and septic shock is essential for preventing unnecessary antibiotic overuse and improving the chance of patient survival. To address this, a 3D gold nanogranule decorated gold-silver alloy nanopillar (AuNG@Au-AgNP) based surface-enhanced Raman scattering (SERS) biosensor is developed, capable of quantitatively profiling immune-related soluble proteins (interleukin three receptor, alpha chain: CD123, programmed cell death ligand 1: PD-L1, human leukocyte antigen-DR isotype: HLA-DR, and chitotriosidase: ChiT) in serum samples. The 3D bimetallic nanoarchitecture, fabricated using anodized aluminum oxide (AAO), features a uniform structure with densely packed nanogaps on the heads of Au-Ag alloy nanopillars, enabling fast, simple, and replicable production. The proposed biosensor achieves accurate results even with low detection limits (4-6 fM) and high signal consistency (relative standard deviation (RSD) = 1.79%) within a one-step multi-analytes identification chip with a directly loadable chamber. To enhance the diagnostic performance, a support vector machine (SVM) based machine learning algorithm is utilized, achieving 95.0% accuracy and 95.8% precision in classifying healthy controls, infections with and without sepsis, and septic shock. This advanced 3D plasmonic bimetallic alloy nanoarchitecture-based SERS biosensor demonstrates clinical usefulness for sepsis diagnosis and severity assessment, providing timely and personalized treatment.

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