Multiple signal amplification and selective recognition reactions-assisted homogeneous binary visual aptasensor of tuberculosis interferon γ in clinical samples

同种类的 二进制数 信号(编程语言) 模式识别(心理学) 人工智能 计算机科学 数学 组合数学 算术 程序设计语言
作者
Piaopiao Chen,Mei Li,Peng Wu,Tangyuheng Liu,Jin Huang,Binwu Ying
出处
期刊:Sensors and Actuators B-chemical [Elsevier]
卷期号:376: 132997-132997 被引量:1
标识
DOI:10.1016/j.snb.2022.132997
摘要

Interferon- γ (IFN- γ ) analysis is critical for tuberculosis (TB) diagnosis. However, the existing conventional immunoassay methods are less sensitive and laborious. We describe cadmium telluride quantum dots (CdTe QDs) and calcein-based binary visual and fluorescence homogeneous aptamer sensing strategy for IFN- γ analysis. This strategy integrates enzyme-free catalytic hairpin assembly (CHA) amplification, selective recognition properties of QDs and calcein for Ag + and C-Ag + -C structures, and ink-jet printing technology for making test strips. Using QDs- and calcein-based fluorescence modes, respectively, IFN- γ with limits of detection (LODs) as low as 0.3 ag/mL and 0.25 ag/mL were obtained at optimum conditions. Color and distance reading modes enabled the analysis of 100 ag/mL IFN- γ with naked eyes. Quantitative findings of IFN- γ analysis in 51 clinical plasma samples using dual fluorescence modes were in line with those obtained by enzyme-linked immunosorbent assay (ELISA), sputum culture, polymerase chain reaction (PCR), Xpert MTB/rifampin (RIF) and computed tomography (CT). Additionally, findings from IFN- γ analysis in 12 clinical samples obtained using QDs- and calcein-based distance reading strips were highly consistent with those of ELISA. Therefore, our analytical system may provide an additional and more sensitive tool for early diagnosis of TB. • A homogeneous fluorescence and binary visualization strategy for the analysis of tuberculosis IFN- γ was developed. • The developed simple, rapid, low cost and homogeneous visual sensor was present high sensitivity and selectivity. • This system has been successfully used in fluorescence and test strips analysis of tuberculosis IFN- γ in 51 clinical samples.
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