Development and Analytical Validation of a Surface-Enhanced Raman Scattering Paper Lateral Flow Immunoassay for Detection of the Ubiquitin C‑Terminal Hydrolase-L1 Traumatic Brain Injury Biomarker
Paper lateral flow immunoassays combined with surface-enhanced Raman scattering (SERS) technology have gained increasing attention due to their high sensitivity characteristics resulting from the amplified SERS signals of the plasmon-enhanced optical probes. In contrast to conventional colorimetric...
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Veröffentlicht in: | ACS omega 2024-09, Vol.9 (36), p.37965-37972 |
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Sprache: | eng |
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Zusammenfassung: | Paper lateral flow immunoassays combined with surface-enhanced Raman scattering (SERS) technology have gained increasing attention due to their high sensitivity characteristics resulting from the amplified SERS signals of the plasmon-enhanced optical probes. In contrast to conventional colorimetric lateral flow strips, SERS paper lateral flow strips (SERS-PLFSs) are currently not commercially available for widespread use. Analytical validation is the key step for commercialization. In this work, we have developed a PLFS with a hierarchical SERS probe (gold–silver nanoparticle@Raman reporter@silica) for detection of the US Food and Drug Administration (FDA)-approved traumatic brain injury (TBI) protein biomarker, ubiquitin C-terminal hydrolase-L1 (UCH-L1), in blood plasma samples. Analytical validation has been performed on this SERS-PLFS in terms of the limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, selectivity, and stability. The SERS-PLFS exhibits a reportable range of 0.2–100 ng/mL with a LOD of 0.08 ng/mL toward measurement of UCH-L1 in blood plasma. The SERS-PLFS has been applied to clinical TBI samples. The test results were compared with those from enzyme-linked immunosorbent assay (ELISA), demonstrating a strong correlation between the two analytical methods. This study has important implications in the commercialization of SERS-PLFSs for rapid TBI detection in clinical practice. |
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ISSN: | 2470-1343 2470-1343 |
DOI: | 10.1021/acsomega.4c04685 |