Production and characterization of polymeric nanoparticles, as colloidal dispersions, are processes that require time and technical skills to make the results accurate. Computational simulations in nanoscience have been used to help in these processes and provide agility and support to reach results: stability and quality in dispersions. Multi-Agent System for Polymeric Nanoparticles (MASPN) is an innovative and original simulation environment with features to demonstrate interactions of particles from physical-chemical parameters, ensuring Brownian motion of particles and attractive and repulsive behaviour. The MASPN environment has been designed and has been built according to the feature-driven development (FDD), as software methodology, and a multi-agent systems approach. In addition, we have used the eventdriven simulation package algs4, the JASON agent building environment, all integrated by Java language. This paper aims to present the relation of the algs4 package and the JASON tool, both integrated into the MASPN environment to generate Brownian motion with elastic and inelastic collisions. The MASPN environment as a simulation tool emerges as a result, including the following features: graphical interface; integrated physical-chemical parameters; Brownian motion; JASON and algs4 integration; and distribution charts (size, zeta potential, and pH).
To present a possible new alternative for wound treatment, this work evaluated the biological safety and therapeutic efficacy of graphene oxide (GO) and reduced graphene oxide (rGO) nanoparticles (NPs). First, the nanostructures were studied in silico and showed to be able to inhibit the production of some pro-inflammatory cytokines and stimulate the production of the anti-inflammatory cytokine IL-10, especially rGO. The results of the morphological and structural characterization of GO NPs synthesized from the Hummers method and reduced by ascorbic acid, were consistent with the literature, confirming their achievement. In the broth microdilution assay, GO and rGO showed antimicrobial activity against the clinical isolate of Streptococcus agalactiae (S. agalactiae) at a minimum inhibitory concentration (MIC) of 625 µg/mL for GO and 312.5 µg/mL for rGO. In addition, the nanostructure of rGO was able to inhibit, in subinhibitory concentration, the formation of S. agalactiae biofilm by up to 77% when compared to the positive control. Both NPs, in all tested concentrations, did not cause hemolysis, and alterations in coagulation in vitro assays. However, in the safety tests, it was evidenced that only the MIC of 312, µg/mL for rGO was biologically safe and presented anti-inflammatory and healing behavior in vitro. In general, the present work confirmed rGO's potential in the treatment of chronic wounds, since in silico showed anti-inflammatory behavior and in vitro showed therapeutic efficacy at low concentrations, prevented biofilm formation, and showed no significant toxic effects.
Resumo:Muitas anomalias e doenças genéticas podem ser descobertas através da análise da forma e das características morfológicas dos cromossomos. Para alcançar este objetivo, geralmente constrói-se o cariótipo, a partir de uma fotografia obtida através de um microscópio, através da organização e ordenação dos cromossomos de uma célula humana de acordo com o seu tamanho. Apesar dos grandes avanços nas técnicas de cultura celular, bandeamento, coleta e análise dos materiais para a elaboração do cariótipo, este processo ainda é bastante empregado de forma manual, pois a oferta de sistemas automáticos que auxiliem o trabalho dos geneticistas ainda é baixa. Através da automatização deste processo é possível agilizar condutas terapêuticas, obtendo resultados em um espaço de tempo menor. Desta forma, este trabalho propõe o desenvolvimento de uma ferramenta capaz de auxiliar o geneticista na elaboração do cariótipo humano através da automatização do processo de segmentação de metáfases e identificação dos cromossomos através de imagens obtidas de um microscópio.
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