Machine-learning-assisted waveguide scattering microscopy for the immunological detection of bovine brucellosis: A proof concept

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dc.contributor.authorFonsaca J.E.S.
dc.contributor.authorTeixeira W.S.R.
dc.contributor.authorTieppo B.
dc.contributor.authorRaitz C.
dc.contributor.authorRehan M.
dc.contributor.authorGerosa R.M.
dc.contributor.authorMegid J.
dc.contributor.authorAppolinario C.M.
dc.contributor.authorSalles M.O.
dc.contributor.authorSaito L.A.M.
dc.contributor.authorVale D.L.
dc.contributor.authorGrasseschi D.
dc.contributor.authorde Matos C.J.S.
dc.date.accessioned2025-04-01T06:17:41Z
dc.date.available2025-04-01T06:17:41Z
dc.date.issued2025
dc.description.abstract© 2025 Elsevier B.V.Photonic biosensors based on optical waveguides are at the forefront of biosensing technology, offering exceptional sensitivity and robustness. This study presents a proof-of-concept for detecting Brucella abortus antibodies in bovine serum using He-Ne laser-excited integrated optical waveguides. The antigen-antibody interactions in positive samples resulted in agglutination, forming scattering spots on the light-coupled waveguide, while no such spots were observed in negative samples. These spots were imaged over time using a microscope-coupled camera, generating 718 images that were processed to create a dataset for an artificial neural network (ANN). The ANN accurately distinguished between positive and negative samples, achieving 98.6 % accuracy, 98.7 % precision, and 98.7 % recall, with only a 1.4 % loss. This method detected bacterial antibodies in real animal samples within 20 min, using just 100 µL of reagents without requiring prior waveguide surface modification for antigen immobilization. Combining light scattering-based sensing protocols in photonic waveguides with machine learning tools offers a promising pathway for revolutionizing infectious disease diagnostics.
dc.description.volume432
dc.identifier.doi10.1016/j.snb.2025.137458
dc.identifier.issnNone
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/40327
dc.relation.ispartofSensors and Actuators B: Chemical
dc.rightsAcesso Restrito
dc.subject.otherlanguageArtificial neural network
dc.subject.otherlanguageImage processing
dc.subject.otherlanguageLight scattering
dc.subject.otherlanguagePhotonics biosensor
dc.subject.otherlanguageSilicon nitride waveguide
dc.titleMachine-learning-assisted waveguide scattering microscopy for the immunological detection of bovine brucellosis: A proof concept
dc.typeArtigo
local.scopus.citations0
local.scopus.eid2-s2.0-85218638975
local.scopus.subjectImages processing
local.scopus.subjectImmunological detection
local.scopus.subjectMachine-learning
local.scopus.subjectNegative samples
local.scopus.subjectNeural-networks
local.scopus.subjectOptical-
local.scopus.subjectPhotonic biosensor
local.scopus.subjectScattering microscopies
local.scopus.subjectSilicon nitride waveguides
local.scopus.subjectWaveguide scattering
local.scopus.updated2025-04-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85218638975&origin=inward
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