Avaliação do papel de nanopartículas de prata e de ouro no sensoriamento de toxinas urêmicas por meio de técnicas de espectroscopia ótica e aplicação do modelo pix2pix no ensaio de migração celular

Abstract

This work proposes a colorimetric sensor based on metallic nanoparticles for quantification of protein-bound uremic toxins (PBUTs), as well as the application of the pix2pix model in the improvement of the cell migration assay. In chronic kidney disease (CKD), the kidneys partially or completely lose their ability to remove uremic toxins (UTs) from the bloodstream, which would normally be excreted through the urine, resulting in a higher concentration of these compounds in the blood. This condition is called uremia and is strongly associated with several deleterious effects in the body, among them cardiovascular disease (CVD), the leading cause of death in patients affected by the disease. Cell migration can also be affected by uremia. In order to understand and evaluate these effects, it is necessary to monitor and quantify the concentrations of TUs in biological media, as well as to evaluate the capacity of cell adhesion and migration. Experiments of production, characterization and photoconversion of nanoparticles were performed, which allowed the observation that the ratio of localized surface plasmon resonance (LSPR) and the average size of the quasi-spherical NPs produced under the tested conditions did not corroborate with some articles found in the literature. The average size of the silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) near the first 20 min of pulsed laser ablation in liquid (PLAL) diminished although the LSPR redshifted, which was followed by the increase of the solution temperature. Based on these assays, a AgNPs sensor capable of detecting uremic and normal concentrations of PBUTs, such as indoxyl sulfate (IS) and p-cresyl sulfate (PCS) was developed using optical spectroscopy techniques. The sensor response to interferents such as urea and creatinine was also evaluated and was shown to be reduced when compared to the sensor response to PBUTs, being within the control error even after exposure to hydrogen peroxide (H2O2). To improve the cell migration assay, the pix2pix model was applied, a neural network capable of reducing human bias in the analysis of the experiment, which automated the analysis process, and proved efficient in minimizing or eliminating the bias of manual analysis.