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Construction and Evaluation of a Self-Calibrating Multiresponse and Multifunctional Graphene Biosensor
Recently, many studies have been focused on the development of graphene-based biosensors. However, they rely on one type of signal and need to be calibrated by other techniques. In this study, a nonenzymatic graphene-based biosensor has been designed and constructed. Its ability to detect glucose an...
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Published in: | Langmuir 2019-08, Vol.35 (32), p.10461-10474 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Recently, many studies have been focused on the development of graphene-based biosensors. However, they rely on one type of signal and need to be calibrated by other techniques. In this study, a nonenzymatic graphene-based biosensor has been designed and constructed. Its ability to detect glucose and Escherichia coli by three different types of signals has been investigated. For its preparation, dopamine-functionalized polyethylene glycol and 2,5-thiophenediylbisboronic acid were conjugated onto the surface of graphene sheets by nitrene [2 + 1] cycloaddition and condensation reactions, respectively. Multivalent interactions between boronic acid segments and biosystems consequently increased the quantifiable fluorescence emission and UV absorption of dopamine segments. Additionally, changing the electrochemical behavior of the functionalized graphene sheets was possible and resulted in a measurable output signal. Conjugation of mannose onto the surface of the biosensor improved its magnitude of signals and specificity for sensing E. coli in a complex medium. The efficiency and accuracy of each signal was monitored by others, which resulted in a real-time self-calibrating biosensor. Taking advantage of the versatility of the three different indicators, including florescence, UV, and electrochemistry, the functionalized graphene sheets have been used as self-regulating biosensors to detect a variety of biosystems with a high accuracy and specificity in a short time. |
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ISSN: | 0743-7463 1520-5827 |
DOI: | 10.1021/acs.langmuir.9b00915 |