Título:	Microfluidic Electronic Tongue Made with Nanostructured Films of Proteins from Renewable Sources to Detect H5N1 Antibodiesfrom Avian Influenza Virus.
Autor:	COATRINI-SOARES, A. SOARES, J. C. POPOLIN-NETO, M. SOARES, G. O. N. MELLO, S. S. de SANCHES, E. A. PAULOVICH, F. V. MATTOSO, L. H. C.
Afiliación:	FEDERAL UNIVERSITY OF AMAZONAS, 69067-005 MANAUS, AMAZONAS UNIVERSITY OF SÃO PAULO (USP) FEDERAL INSTITUTE OF SÃO PAULO (IFSP), 14804-296 ARARAQUARA, SÃO PAULO, BRAZIL UNIVERSITY OF SÃO PAULO (USP) HARVARD MEDICAL SCHOOL, BOSTON, MASSACHUSETTS MA02114, UNITED STATES FEDERAL UNIVERSITY OF SÃO CARLOS (UFSCAR), 13565-905 SÃO CARLOS, SÃO PAULO, BRAZIL EINDHOVEN UNIVERSITY OF TECHNOLOGY (TU/E), 5600 MB EINDHOVEN, THE NETHERLANDS LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA.
Año:	2026
Referencia:	ACS Applied Nano Materials, v. 9, 2026,
Páginas:	6581−6590
Descripción:	Avianinfluenzaviruses,particularlytheH5N1subtype,representa majorglobal threatduetotheirhightransmissibilityandmortalityrates.Rapid, low-cost, andreliabledetection is essential for controllingviral spread inboth avian and human populations. This work presents amicrofluidic electronic tongue composed of interdigitated electrodes functionalized with one-layer, nanostructuredfilms fromrenewable sources zein, jacalin, concanavalinA, and sericin-modifiedgoldnanoparticles(AuNP-SER)forthedetectionofanti-H5N1 antibodies. Electrical impedance spectroscopywas employed tomonitor the interactionbetweenantibodiesandmoleculararchitectures,supportedbycontact angle and polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS)analyses toelucidatethedetectionmechanism.Thesensorsexhibitedhighsensitivityandselectivity,withlimitsof detectionrangingfrom0.42to0.56ng/mLandnofalsepositiveswhentestedagainstcommonaviandiseaseantibodies.Information visualizationtechniquesdemonstratedstrongdiscriminationamonganalytes,withsilhouettecoefficientsupto0.81fortheelectronic tongue.Usingthemultidimensionalcalibrationspace(MCS)approachwithdecision-treemodels,thesystemachieved78%accuracy inmulticlassclassificationof10antibodyconcentrationsand98.6%accuracyindistinguishingpositivefromnegativesamples.The MCSrevealedthat the2154Hz frequencyfromtheAuNP-SERunitwas influential inbothscenarios.Theseresultsconfirmthe potential of theelectronic tongueproposedasa robust, interpretable, and low-costdiagnostic tool forH5N1-relateddiseases in veterinaryandclinical contexts.
Palabras clave:	Impedance spectroscopy H5N1 Machine learning
DOI:	https://doi.org/10.1021/acsanm.6c00138 A
Tipo de Material:	Artigo de periódico
Acceso:	openAccess
Aparece en las colecciones:	Artigo em periódico indexado (CNPDIA)