A biosensor for S100B detection based on PSS-MA-GoldMag-LFIA in early clinical diagnosis of brain damage

S100B is an essential biomarker in the early diagnosis and treatment monitoring of brain injury. However, the traditional clinical diagnostic assay for S100B detection requires a complex operation or large equipment, which limits its application for rapid point-of-care tests (POCT). This study aimed to establish a lateral-flow immunoassay (LFIA) strip test system for S100B determination. PSS-MA-GoldMag nanoparticles were conjugated with anti-S100B antibodies as probes. Using this antibody-nanoparticle composite, an LFIA system based on magnetic quantification was established for S100B detection. For the evaluation of the performance of this LFIA system in clinical practice, 216 clinical samples were assayed using the LFIA test system and a commercial ECLI kit. Using the LFIA system, reliable results could be obtained in 30 min with a detection limit of 0.05 ng mL(-1). The coefficient of variation (CV) was <13.8% and <14.03% for intra- and inter-assay precision, respectively. The recoveries were between 95.1 and 107.3%. The relative deviation of the interference experiments was <10%. In the analysis of clinical samples, the result indicated that the sera level of S100B in the detection group did not correlate with gender (p = 0.564 > 0.05) or age (p = 0.083 > 0.05). There is a good correlation between the novel method and the Elecsys (R), with a determination coefficient of R-2 0.9566, p > 0.05. The Bland-Altman analysis between the two ways shows that the 95% confidence bands between the two methods in measuring S100B were -0.27 ng mL(-1) to +0.29 ng mL(-1) with a mean difference of +0.006 ng mL(-1). These results indicated that the novel LFIA system could be a simple, rapid, convenient, and accurate method for S100B determination.

Automated summary

This study successfully established a lateral-flow immunoassay test system for S100B detection, which achieved simple, rapid, and accurate testing through magnetic quantification. Reliable results were obtained in the analysis of clinical samples.