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Micromachines
Article . 2022
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Molecular Recognition and Quantification of HER-3, HER-4 and HRG-α in Whole Blood and Tissue Samples Using Stochastic Sensors

Authors: Raluca-Ioana Stefan-van Staden; Damaris-Cristina Gheorghe;

Molecular Recognition and Quantification of HER-3, HER-4 and HRG-α in Whole Blood and Tissue Samples Using Stochastic Sensors

Abstract

Human epidermal growth factor receptor-3, human epidermal growth factor-receptor-4, and heregulin-α are some of the biomarkers related to gastric cancer currently being used for early detection, personalized treatment, and evaluation of the efficiency of the treatment. Two stochastic sensors based on graphene decorated with TiO2 and/or Au modified with maltodextrin were proposed for the screening of two types of whole blood and tissue samples for the simultaneous recognition and analysis of the three biomarkers. The sensitivity of the two sensors showed high values, whereas the limits of determination were of fg mL−1 magnitude order. Thus, the proposed screening method can perform the quantitative analysis of both of the biomarkers of interest in whole blood and tissue samples, with recoveries higher than 96.00% and relative standard deviations lower than 1.00%.

Keywords

stochastic sensors, human epidermal growth factor-receptor-4, TJ1-1570, heregulin-α, Mechanical engineering and machinery, human epidermal growth factor receptor-3, stochastic sensors; human epidermal growth factor receptor-3; human epidermal growth factor-receptor-4; heregulin-α, Article

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold
Related to Research communities
Cancer Research