2020

Paper-Based Platform with an In Situ Molecularly Imprinted Polymer for β-Amyloid.

ACS omega Pereira MV, Marques AC, Oliveira D, Martins R, Moreira FTC, Sales MGF, Fortunato E
阅读原文 PDF DOI PubMed

组成图示

示意图生成中

传感器类型

检测对象

检测原理

检测灵敏度

效应效果

传感器的构成

中文摘要

英文摘要

Alzheimer's disease (AD) is one of the most common forms of dementia affecting millions of people worldwide. Currently, an easy and effective form of diagnosis is missing, which significantly hinders a possible improvement of the patient's quality of life. In this context, biosensors emerge as a future solution, opening the doors for preventive medicine and allowing the premature diagnosis of numerous pathologies. This work presents a pioneering biosensor that combines a bottom-up design approach using paper as a platform for the electrochemical recognition of peptide amyloid β-42 (Aβ-42), a biomarker for AD present in blood, associated with visible differences in the brain tissue and responsible for the formation of senile plaques. The sensor layer relies on a molecularly imprinted polymer as a biorecognition element, created on the carbon ink electrode's surface by electropolymerizing a mixture of the target analyte (Aβ-42) and a monomer (O-phenylenediamine) at neutral pH 7.2. Next, the template molecule was removed from the polymeric network by enzymatic and acidic treatments. The vacant sites so obtained preserved the shape of the imprinted protein and were able to rebind the target analyte. Morphological and chemical analyses were performed in order to control the surface modification of the materials. The analytical performance of the biosensor was evaluated by an electroanalytical technique, namely, square wave voltammetry. For this purpose, the analytical response of the biosensor was tested with standard solutions ranging from 0.1 ng/mL to 1 μg/mL of Aβ-42. The linear response of the biosensor went down to 0.1 ng/mL. Overall, the developed biosensor offered numerous benefits, such as simplicity, low cost, reproducibility, fast response, and repeatability less than 10%. All together, these features may have a strong impact in the early detection of AD.

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