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Harnessing Small-Molecule Analyte Detection in Complex Media: Combining Molecularly Imprinted Polymers, Electrolytic Transistors, and Machine Learning

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Autor(es):
Lelis, Gabrielle Coelho ; Fonseca, Wilson Tiago ; de Lima, Alessandro Henrique ; Okazaki, Anderson Kenji ; Figueiredo, Eduardo Costa ; Riul Jr, Antonio ; Schleder, Gabriel Ravanhani ; Samori, Paolo ; de Oliveira, Rafael Furlan
Número total de Autores: 9
Tipo de documento: Artigo Científico
Fonte: ACS APPLIED MATERIALS & INTERFACES; v. N/A, p. 11-pg., 2023-12-22.
Resumo

Small-molecule analyte detection is key for improving quality of life, particularly in health monitoring through the early detection of diseases. However, detecting specific markers in complex multicomponent media using devices compatible with point-of-care (PoC) technologies is still a major challenge. Here, we introduce a novel approach that combines molecularly imprinted polymers (MIPs), electrolyte-gated transistors (EGTs) based on 2D materials, and machine learning (ML) to detect hippuric acid (HA) in artificial urine, being a critical marker for toluene intoxication, parasitic infections, and kidney and bowel inflammation. Reduced graphene oxide (rGO) was used as the sensory material and molecularly imprinted polymer (MIP) as supramolecular receptors. Employing supervised ML techniques based on symbolic regression and compressive sensing enabled us to comprehensively analyze the EGT transfer curves, eliminating the need for arbitrary signal selection and allowing a multivariate analysis during HA detection. The resulting device displayed simultaneously low operating voltages (<0.5 V), rapid response times (<= 10 s), operation across a wide range of HA concentrations (from 0.05 to 200 nmol L-1), and a low limit of detection (LoD) of 39 pmol L-1. Thanks to the ML multivariate analysis, we achieved a 2.5-fold increase in the device sensitivity (1.007 mu A/nmol L-1) with respect to the human data analysis (0.388 mu A/nmol L-1). Our method represents a major advance in PoC technologies, by enabling the accurate determination of small-molecule markers in complex media via the combination of ML analysis, supramolecular analyte recognition, and electrolytic transistors. (AU)

Processo FAPESP: 23/03501-2 - Avaliação da Operação e Estabilidade de Transistores Eletrolíticos de Óxido de Grafeno Reduzido em Condições Fisiológicas Artificiais visando Biossensoriamento
Beneficiário:Gabrielle Coelho Lelis
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
Processo FAPESP: 21/06238-5 - Materiais 2D funcionalizados processados em solução: desenvolvimento de sensores e biossensores elétricos prototipáveis
Beneficiário:Rafael Furlan de Oliveira
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
Processo FAPESP: 19/14949-9 - EMU: infraestrutura multiusuário dedicada à nanofabricação e caracterização de nanodispositivos no LNNano / CNPEM
Beneficiário:Edson Roberto Leite
Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários