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Low-cost bacterial nanocellulose-based interdigitated biosensor to detect the p53 cancer biomarker.
Bondancia, Thalita J; Soares, Andrey Coatrini; Popolin-Neto, Mário; Gomes, Nathalia O; Raymundo-Pereira, Paulo A; Barud, Hernane S; Machado, Sergio A S; Ribeiro, Sidney J L; Melendez, Matias E; Carvalho, André L; Reis, Rui M; Paulovich, Fernando V; Oliveira, Osvaldo N.
Afiliação
  • Bondancia TJ; São Carlos Institute of Physics, University of São Paulo (USP), São Carlos, 13566-590, São Paulo, Brazil; Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970 São Carlos, SP, Brazil.
  • Soares AC; Nanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, 13560-970 São Carlos, SP, Brazil.
  • Popolin-Neto M; Federal Institute of São Paulo (IFSP), 14804-296 Araraquara, Brazil; Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), 13566-590 São Carlos, Brazil.
  • Gomes NO; São Carlos Institute of Chemistry, University of São Paulo (USP), São Carlos, 13566-590, São Paulo, Brazil.
  • Raymundo-Pereira PA; São Carlos Institute of Physics, University of São Paulo (USP), São Carlos, 13566-590, São Paulo, Brazil.
  • Barud HS; Biopolymers and Biomaterials Laboratory (BIOPOLMAT), University of Araraquara (UNIARA), 14801-340 Araraquara, São Paulo, Brazil.
  • Machado SAS; São Carlos Institute of Chemistry, University of São Paulo (USP), São Carlos, 13566-590, São Paulo, Brazil.
  • Ribeiro SJL; Institute of Chemistry, São Paulo State University (UNESP), 14800-060 Araraquara, São Paulo, Brazil.
  • Melendez ME; Barretos Cancer Hospital, Molecular Oncology Research Center, Barretos, 14784-400, São Paulo, Brazil; Molecular Carcinogenesis Program, Research Center, National Cancer Institute (INCA), 20231-050 Rio de Janeiro, Brazil.
  • Carvalho AL; Barretos Cancer Hospital, Molecular Oncology Research Center, Barretos, 14784-400, São Paulo, Brazil.
  • Reis RM; Barretos Cancer Hospital, Molecular Oncology Research Center, Barretos, 14784-400, São Paulo, Brazil; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057 Braga, Portugal.
  • Paulovich FV; Institute of Mathematics and Computer Sciences (ICMC), University of São Paulo (USP), 13566-590 São Carlos, Brazil; Faculty of Computer Science (FCS), Dalhousie University (DAL), B3H 4R2, Nova Scotia, Canada.
  • Oliveira ON; São Carlos Institute of Physics, University of São Paulo (USP), São Carlos, 13566-590, São Paulo, Brazil. Electronic address: chu@ifsc.usp.br.
Biomater Adv ; 134: 112676, 2022 Mar.
Article em En | MEDLINE | ID: mdl-35599099
Low-cost sensors to detect cancer biomarkers with high sensitivity and selectivity are essential for early diagnosis. Herein, an immunosensor was developed to detect the cancer biomarker p53 antigen in MCF7 lysates using electrical impedance spectroscopy. Interdigitated electrodes were screen printed on bacterial nanocellulose substrates, then coated with a matrix of layer-by-layer films of chitosan and chondroitin sulfate onto which a layer of anti-p53 antibodies was adsorbed. The immunosensing performance was optimized with a 3-bilayer matrix, with detection of p53 in MCF7 cell lysates at concentrations between 0.01 and 1000 Ucell. mL-1, and detection limit of 0.16 Ucell mL-1. The effective buildup of the immunosensor on bacterial nanocellulose was confirmed with polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS) and surface energy analysis. In spite of the high sensitivity, full selectivity with distinction of the p53-containing cell lysates and possible interferents required treating the data with a supervised machine learning approach based on decision trees. This allowed the creation of a multidimensional calibration space with 11 dimensions (frequencies used to generate decision tree rules), with which the classification of the p53-containing samples can be explained.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Neoplasias Tipo de estudo: Health_economic_evaluation / Screening_studies Idioma: En Revista: Biomater Adv Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Neoplasias Tipo de estudo: Health_economic_evaluation / Screening_studies Idioma: En Revista: Biomater Adv Ano de publicação: 2022 Tipo de documento: Article