Multiprofessional team in the elaboration of media contents on Covid-19

Em junho de 2020, a Situation Room/UnB e parceiros implementaram um projeto de vigilância comunitária participativa cuja ferramenta principal é a aplicação móvel Guardiões da Saúde. A equipe de comunicação do projeto buscou aumentar a cobertura da aplicação, manter os usuários engajados, oferecer informações confiáveis sobre a COVID-19, garantir uma boa experiência de uso e mostrar a importância da vigilância participativa através do sentimento de responsabilidade social da comunidade acadêmica. Este relato apresenta o papel dessa equipe multiprofissional de extensionistas na orientação da comunidade sobre o controle da epidemia e no enfrentamento à infodemia e notícias falsas. Os produtos da equipe pertencem a três categorias: “Postagens Informativas”, “Retorno ao Usuário” e “Pertencimento à Comunidade”. No período analisado, a maior parte do conteúdo publicado pertence à última categoria. A experiência destaca a importância da colaboração interprofissional, enfatizando a integração dos saberes, para o sucesso da comunicação com os usuários.Since June, 2020, the Situation Room/UnB and partners have been conducting a project on participatory communitary surveillance which has as its main tool a mobile application entitled “Guardiões da Saúde”. The project’s communication team seeks to increase and maintain user engagement in the application; provide reliable information on COVID-19; ensure a good user experience and express the importance of participatory surveillance through the feeling of social responsibility. This report presents the role of a multiprofessional team of university extension students on orienting the community regarding the control of the epidemics and facing infodemia and false news. The team’s products belong to three categories: “Informative Posts”, “Return to the User” and “Belonging to the Community”. On the analyzed data, most of the content published by the team belongs to the latter category. The experience highlights the importance of interprofessional collaboration, emphasizing knowledge integration to succeed communicating with users

Development and validation of a HPLC analytical assay method for efavirenz tablets: a medicine for HIV infections

O efavirenz é um inibidor não análogo de nucleosídeo da transcriptase reversa, utilizado no tratamento da infecção por HIV. Um método simples, por cromatografia líquida de alta eficiência, foi desenvolvido e validado para quantificação do efavirenz em comprimidos. O desenvolvimento do método levou em consideração as características físico-químicas do efavirenz. O método foi validado seguindo os parâmetros da USP 29. A análise foi realizada por meio de detector ultravioleta, utilizando um comprimento de onda de 252 nm, com coluna de fase reversa (C18, 250 mm x 3.9 mm, 10 μm) e fase móvel isocrática contendo acetonitrila/água/ácido ortofosfórico (70: 30: 0.1). Os critérios usados para validação foram: seletividade, linearidade, precisão, exatidão, robustez e limites de detecção e quantificação do método. Foi utilizado método estatístico em todas as etapas do processo de validação. Os resultados obtidos mostraram que o método é uma alternativa para quantificação do efavirenz em comprimidos, tornando viável seu uso na rotina industrial e laboratórios analíticos.Efavirenz is a reverse transcriptase non analog nucleoside inhibitor used to treat HIV infections. A simple assay method by high performance liquid chromatography was developed and validated for efavirenz tablets. The physical chemical characteristics of efavirenz were investigated to developing the method. The method was validated observing the parameters described in USP 29. Analyses were performed by an ultraviolet detector at a 252 nm wavelength, on a reverse-phase column (C18, 250 mm x 3.9 mm, 10 μm), using an isocratic mobile phase containing acetonitrile/water/orthophosphoric acid (70:30:0.1). The validation parameters used were: selectivity, linearity, precision, accuracy, robustness, detection and quantification limits, and all resulting data were treated by a statistical method. The results obtained confirmed an alternative assay method for efavirenz tablets adequate for routine industrial use

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post—the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. / Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. / Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. / Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. / Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. / Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. / Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America

Cashew gum (Anacardium occidentale) as a potential source for the production of tocopherol-loaded nanoparticles: formulation, release profile and cytotoxicity

Every year, more than thirty thousand tons of Cashew gum (Anacardium occidentale, family: Anacardiaceae) are produced in Brazil; however, only a small amount is used for different applications in foodstuff and in pharmaceutical industries. As a raw material for the production of drug delivery systems, cashew gum is still regarded as an innovative compound worth to be exploited. In this work, cashew gum was extracted from the crude exudate of cashew tree employing four methodologies resulting in a light brown powder in different yields (40.61% to 58.40%). The total ashes (0.34% to 1.05%) and moisture (12.90% to 14.81%) were also dependent on the purification approach. FTIR spectra showed the typical bands of purified cashew gum samples, confirming their suitability for the development of a pharmaceutical product. Cashew gum nanoparticles were produced by nanoprecipitation resulting in particles of low polydispersity (<0.2) and an average size depending on the percentage of the oil. The zeta potential of nanoparticles was found to be below 20 mV, which promotes electrostatic stability. Encapsulation efficiencies were above 99.9%, while loading capacity increased with the increase of the percentage of the oil content of particles. The release of the oil from the nanoparticles followed the KorsmeyerPeppas kinetics model, while particles did not show any signs of toxicity when tested in three distinct cell lines (LLC-MK2, HepG2, and THP-1). Our study highlights the potential added value of using a protein-, lignans-, and nucleic acids-enriched resin obtained from crude extract as a new raw material for the production of drug delivery systems.This research received funding from the Coordenação Aperfeiçoamento de Pessoal de Nivel Superior (CAPES), Fundação de Ámparo à Pesquisa do Estado de Sergipe (FAPITEC) (PROCESSO: 88887.159533/2017-00 extração, encapsulação e caracterização de bioativos para o interesse biotecnologico) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq 301964/2019-0 Chamada 06/2019, and Chamada CNPq nº 01/2019), from Portuguese Foundation for Science and Technology (FCT/MEC) through national funds, and co-financed by FEDER, under the Partnership Agreement PT2020 for the project UIDB/04469/2020.info:eu-repo/semantics/publishedVersio