Reliability of two behavioral tools to assess pain in preterm neonates

CONTEXT: One of the main difficulties in adequately treating the pain of neonatal patients is the scarcity of validated pain evaluation methods for this population. OBJECTIVE: To analyze the reliability of two behavioral pain scales in neonates. TYPE OF STUDY: Cross-sectional. SETTING: University hospital neonatal intensive care unit. PARTICIPANTS: 22 preterm neonates were studied, with gestational age of 34 ± 2 weeks, birth weight of 1804 ± 584 g, 68% female, 30 ± 12 hours of life, and 30% intubated. PROCEDURES: Two neonatologists (A and B) observed the patients at the bedside and on video films for 10 minutes. The Neonatal Facial Coding System and the Clinical Scoring System were scored at 1, 5, and 10 minutes. The final score was the median of the three values for each observer and scale. A and B were blinded to each other. Video assessments were made three months after bedside evaluations. MAIN MEASUREMENTS: End scores were compared between the observers using the intraclass correlation coefficient and bias analysis (paired t test and signal test). RESULTS: For the Neonatal Facial Coding System, at the bedside and on video, A and B showed a significant correlation of scores (intraclass correlation score: 0.62), without bias between them (t test and signal test: p > 0.05). For the Clinical Scoring System bedside assessment, A and B showed correlation of scores (intraclass correlation score: 0.55), but bias was also detected between them: A scored on average two points higher than B (paired t test and signal test: p 0,05). Para a Escala de Conforto Clínico à beira do leito, os escores obtidos por A e B mostraram uma correlação significante (0,55), foi detectado: o escore obtido por A foi, em média, dois pontos superior ao de B (teste t e do sinal: p < 0,05). Para a mesma escala aplicada em vídeo, os escores obtidos por A e B não mostraram correlação (0,25) e detectou-se viés (teste t e do sinal: p < 0,05). CONCLUSÃO: Os resultados reforçam a confiabilidade do Sistema de Codificação da Atividade Facial Neonatal aplicado à beira do leito para a avaliação da dor no recém-nascido pré-termo.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de MedicinaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Neonatal DivisionUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Department of EpidemiologyUNIFESP, EPM, Neonatal DivisionUNIFESP, EPM, Department of EpidemiologySciEL

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

Produção orgânica de rabanete em plantio direto sobre cobertura morta e viva.

O objetivo deste trabalho foi avaliar o uso de plantas espontâneas e cobertura viva de amendoim forrageiro(Arachis pintoi), associado à aplicação de composto orgânico na produção orgânica do rabanete em plantio direto. O experimento foi instalado na Universidade Federal do Acre, em Rio Branco-AC, de 15/06 a 14/07/2007. O delineamento experimental utilizado foi em blocos casualizados com parcelas subdivididas 4x3, em quatro repetições. As parcelas corresponderam ao sistema de plantio direto com cobertura viva de amendoim forrageiro, cobertura viva de planta espontânea, cobertura morta de planta espontânea e sistema de plantio em canteiro com solo descoberto. As subparcelas foram compostas pelas doses de composto orgânico de 5, 10 e 15 t ha-1 (base seca). O plantio direto na palha de plantas espontâneas teve desempenho semelhante ao preparo convencional do solo, ambos superiores ao plantio sobre as coberturas vivas. A produtividade do rabanete cv. Cometo, não foi afetada pelas doses crescentes de composto orgânico, podendo aplicar-se apenas 5 t ha-1, enquanto em preparo convencional do solo, o aumento da produtividade ultrapassa o plantio direto na palha apenas na dose maior de composto (15 t ha-1)

A tetravalent dengue nanoparticle stimulates antibody production in mice

<p>Abstract</p> <p>Background</p> <p>Dengue is a major public health problem worldwide, especially in the tropical and subtropical regions of the world. Infection with a single <it>Dengue virus </it>(DENV) serotype causes a mild, self-limiting febrile illness called dengue fever. However, a subset of patients experiencing secondary infection with a different serotype progresses to the severe form of the disease, dengue hemorrhagic fever/dengue shock syndrome. Currently, there are no licensed vaccines or antiviral drugs to prevent or treat dengue infections. Biodegradable nanoparticles coated with proteins represent a promising method for in vivo delivery of vaccines.</p> <p>Findings</p> <p>Here, we used a murine model to evaluate the IgG production after administration of inactivated DENV corresponding to all four serotypes adsorbed to bovine serum albumin nanoparticles. This formulation induced a production of anti-DENV IgG antibodies (p < 0.001). However, plaque reduction neutralization assays with the four DENV serotypes revealed that these antibodies have no neutralizing activity in the dilutions tested.</p> <p>Conclusions</p> <p>Our results show that while the nanoparticle system induces humoral responses against DENV, further investigation with different DENV antigens will be required to improve immunogenicity, epitope specicity, and functional activity to make this platform a viable option for DENV vaccines.</p

Similar Genetic Mechanisms Underlie the Parallel Evolution of Floral Phenotypes

The repeated origin of similar phenotypes is invaluable for studying the underlying genetics of adaptive traits; molecular evidence, however, is lacking for most examples of such similarity. The floral morphology of neotropical Malpighiaceae is distinctive and highly conserved, especially with regard to symmetry, and is thought to result from specialization on oil-bee pollinators. We recently demonstrated that CYCLOIDEA2–like genes (CYC2A and CYC2B) are associated with the development of the stereotypical floral zygomorphy that is critical to this plant–pollinator mutualism. Here, we build on this developmental framework to characterize floral symmetry in three clades of Malpighiaceae that have independently lost their oil bee association and experienced parallel shifts in their floral morphology, especially in regard to symmetry. We show that in each case these species exhibit a loss of CYC2B function, and a strikingly similar shift in the expression of CYC2A that is coincident with their shift in floral symmetry. These results indicate that similar floral phenotypes in this large angiosperm clade have evolved via parallel genetic changes from an otherwise highly conserved developmental program