Toxoplasmose gestacional: uma revisão da literatura

Background and Objectives. Toxoplasmosis is an infectious disease caused by the parasite Toxoplasma gondiie has high vertical transmission rates, reaching 65% in the third trimester of pregnancy. The main focus was to review the diagnosis and management of gestational toxoplasmosis, highlighting the importance of screening during pregnancy with serology request early during the prenatal period. Content. The main ways of getting gestational toxoplasmosis are the ingestion of undercooked meat and unwashed vegetables and also the direct or indirect contact with oocysts present in the feces of cats. The diagnosis of gestational toxoplasmosis is done through research of specific antibodies of the IgG and IgM against Toxoplasma gondii in serum samples and tracking is required during the prenatal period. Nevertheless, this disease is highly prevalent in Brazil, with 60,000 new cases a year and is considered a serious public health problem. Treatment varies according to the gestational period and is based on the spiramycin administration, may or may not be switched sulfadiazine, pyrimethamine and folinic acid, aiming to reduce the consequences for the newborn. Conclusion: Thus, it is understood that for the diagnosis of acute infections serological screening is the most appropriate treatment and, once detected seroconversion in pregnant women should be immediately initiated therapy with spiramycin. Key-words: Toxoplasma. Congenital toxoplasmosis. Communicable Diseases. Infection Diseases transmission vertical. Prenatal Care.Justificativa e objetivos. A toxoplasmose é uma doença infecciosa causada pelo parasita Toxoplasma gondiie apresenta elevadas taxas de transmissão vertical, podendo chegar a 65% no terceiro trimestre de gestação. O foco principal foi revisar o diagnóstico e manejo da toxoplasmose gestacional, destacando a importância do rastreio na gestação com solicitação de sorologias precocemente durante o pré-natal. Conteúdo. As principais formas de contrair a toxoplasmose gestacional são a ingestão de carnes mal cozidas e verduras mal lavadas e, ainda, o contato direto ou indireto com oocistos presentes nas fezes de gatos. O diagnóstico da toxoplasmose gestacional é feito através da pesquisa de anticorpos específicos das classes IgG e IgM contra Toxoplasma gondii em amostras de soro e o rastreamento é obrigatório durante o pré-natal. Apesar disso, essa doença apresenta alta prevalência no Brasil, com 60 mil novos casos ao ano, sendo considerado um grave problema de saúde pública. O tratamento varia de acordo com o período gestacional e baseia-se na administração de espiramicina, podendo ou não ser alternado sulfadiazina, pirimetamina e ácido fólinico, tendo como objetivo diminuir as sequelas para o recém nascido. Conclusão: Assim, entende se que para o diagnóstico das infecções agudas a triagem sorológica é amais indicada e para tratamento, uma vez detectada a soroconversão na grávida, deve ser imediatamente iniciada terapêutica com espiramicina. Descritores: Toxoplasma. Toxoplasmose congênita. Doenças transmissíveis. Transmissão vertical de doença infecciosa. Cuidado pré-natal

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Meninas High-Tech

Inequality and discrimination according to gender have been debated for decades, gender equality is among the Millennium Development Goals, proposed by the UN. Numerous barriers are still faced in the academic and work world, with regard to the participation of women in science and technology. The Girls High-Tech project was created in line with the “Digital Girls” program, proposed by the Brazilian Computer Society, working within the scope of the IFRS Happy Campus and schools located in the region. The main objective of the project is to promote reflections and actions on female participation in the area of Information Technology (IT), seeking to encourage the performance of girls in this area and problematizing gender inequalities

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%