ABSTRACT
Gold nanoclusters (AuNCs) possess weak intrinsic fluorescence, limiting their sensitivity in biosensing applications. This study addresses these limitations by developing a spatially confined dual-emission nanoprobe composed of silicon nanoparticles (SiNPs) and AuNCs. This amplified and stabilized fluorescence mechanism overcomes the limitations associated with using AuNCs alone, achieving superior sensitivity in the sensing platform. The nanoprobe was successfully employed for ratiometric detection of bleomycin (BLM) in serum samples, operating at an excitation wavelength of 365 nm, with emission wavelengths at 480 nm and 580 nm. The analytical performance of the system is distinguished by a linear detection range of 0-3.5 µM, an impressive limit of detection (LOD) of 35.27 nM, and exceptional recoveries ranging from 96.80 to 105.9%. This innovative approach significantly enhances the applicability and reliability of AuNC-based biosensing in complex biological media, highlighting its superior analytical capabilities.
Subject(s)
Biosensing Techniques , Gold , Limit of Detection , Metal Nanoparticles , Silicon , Gold/chemistry , Silicon/chemistry , Biosensing Techniques/methods , Metal Nanoparticles/chemistry , Nanoparticles/chemistry , Fluorescent Dyes/chemistry , Spectrometry, Fluorescence/methods , HumansABSTRACT
Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.
