Machine Learning-Assisted Pattern Recognition of Amyloid Beta Aggregates with Fluorescent Conjugated Polymers and Graphite Oxide Electrostatic Complexes
Hao Wang, Mingqi Chen, Yimin Sun, Lian Xu, Fei Li, Jinsong Han
Abstract
Five fluorescent positively charged poly(para-aryleneethynylene) (P1–P5) were designed to construct electrostatic complexes C1–C5 with negatively charged graphene oxide (GO). The fluorescence of conjugated polymers was quenched by the quencher GO. Three electrostatic complexes were enough to distinguish between 12 proteins with 100% accuracy. Furthermore, using these sensor arrays, we could identify the levels of Aβ40 and Aβ42 aggregates (monomers, oligomers, and fibrils) via employing machine learning algorithms, making it an attractive strategy for early diagnosis of Alzheimer’s disease.
Topics & Concepts
ChemistryConjugated systemFluorescenceGraphenePolymerOxideMonomerGraphite oxideAmyloid betaElectrostaticsGraphiteNanotechnologyPhotochemistryCombinatorial chemistryOrganic chemistryPeptideBiochemistryPhysical chemistryQuantum mechanicsMaterials sciencePhysicsLuminescence and Fluorescent MaterialsMolecular Sensors and Ion DetectionConducting polymers and applications