Environmental vulnerability evolution in the Brazilian Amazon.

Decision making and environmental policies are mainly based on propensity level to impact in the area. The propensity level can be determined through artificial intelligence techniques included in geotechnological universe. Thus, this study aimed to determine the areas of greatest vulnerability to human activities, in Amazon biome, through MODIS images of Land use and land cover (LULC) from the 2001 and 2013. Remote sensing, Euclidean distance, Fuzzy logic, AHP method and analysis of net variations were applied to specialize the classes of vulnerability in the states belonging to the Amazon Biome. From the results, it can be seen that the class that most evolved in a positive net gain during the evaluated period was "very high" and the one that most reduced was "high", showing that there was a transition from "high" to "very high" risk areas. The states with the largest areas under "very high" risk class were Mato Grosso (101,100.10 km2) and Pará (81,010.30 km2). It is concluded that the application of remote sensing techniques allows the determination and assessment of the environmental vulnerability evolution. Mitigation measures urgently need to be implemented in the Amazon biome. The methodology can be extended to any other area of the planet.

Use of machine learning as a tool for determining fire management units in the brazilian atlantic forest.

Geoprocessing techniques are generally applied in natural disaster risk management due to their ability to integrate and visualize different sets of geographic data. The objective of this study was to evaluate the capacity of classification and regression tree (CART) to assess fire risk. MCD45A1 product of the burnt area, relative to a 16-year period (2000-2015) was used to obtain a fire occurrence map, from center points of the raster, using a kernel density approach. The resulting map was then used as a response variable for CART analysis with fire influence variables used as predictors. A total of 12 predictors were determined from several databases, including environmental, physical, and socioeconomic aspects. Rules generated by the regression process allowed to of define different risk levels, expressed in 35 management units, and used to produce a fire prediction map. Results of the regression process (r = 0.94 and r² = 0.88) demonstrate the capability of the CART algorithm in highlighting hierarchical relationships among predictors, while the model's easy interpretability provides a solid basis for decision making. This methodology can be expanded in other environmental risk analysis studies and applied to any area of the globe on a regional scale.

Genetic risk factors and COVID-19 severity in Brazil: results from BRACOVID study.

The coronavirus disease 2019 (COVID-19) pandemic has changed the paradigms for disease surveillance and rapid deployment of scientific-based evidence for understanding disease biology, susceptibility and treatment. We have organized a large-scale genome-wide association study (GWAS) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected individuals in Sao Paulo, Brazil, one of the most affected areas of the pandemic in the country, itself one of the most affected in the world. Here, we present the results of the initial analysis in the first 5233 participants of the BRACOVID study. We have conducted a GWAS for COVID-19 hospitalization enrolling 3533 cases (hospitalized COVID-19 participants) and 1700 controls (non-hospitalized COVID-19 participants). Models were adjusted by age, sex and the 4 first principal components. A meta-analysis was also conducted merging BRACOVID hospitalization data with the Human Genetic Initiative (HGI) Consortia results. BRACOVID results validated most loci previously identified in the HGI meta-analysis. In addition, no significant heterogeneity according to ancestral group within the Brazilian population was observed for the two most important COVID-19 severity associated loci: 3p21.31 and Chr21 near IFNAR2. Using only data provided by BRACOVID, a new genome-wide significant locus was identified on Chr1 near the genes DSTYK and RBBP5. The associated haplotype has also been previously associated with a number of blood cell related traits and might play a role in modulating the immune response in COVID-19 cases.

Gis and fuzzy logic applied to modelling forest fire risk.

Fire risk mapping is a basic planning and protection element. This study presents the application of fuzzy logic in a geographic information system (GIS) as an alternative multi-criteria analysis for determining the areas of highest risk of forest fire in natural forest remnants in the Brazil. In the decision-making process, a set of factors that are relevant to fire safety were identified in the study area. For each input variable chosen for the model, a pertinence function was defined that best described its influence on fire risk. Subsequently, the variables were combined for the presentation of the final fire risk map. Concluded in the study that an increased risk of fire occurs at the wildland - urban interface. A strong relationship was observed between the fire ignition points and proximity to roads and urban areas. The proposed model was efficient to integrate the variables and determine areas of greatest risk.

Using DNA Barcodes to Identify Road-Killed Animals in Two Atlantic Forest Nature Reserves, Brazil.

Road mortality is the leading source of biodiversity loss in the world, especially due to fragmentation of natural habitats and loss of wildlife. The survey of the main species victims of roadkill is of fundamental importance for the better understanding of the problem, being necessary, for this, the correct species identification. The aim of this study was to verify if DNA barcodes can be applied to identify road-killed samples that often cannot be determined morphologically. For this purpose, 222 vertebrate samples were collected in a stretch of the BR-101 highway that crosses two Discovery Coast Atlantic Forest Natural Reserves, the Sooretama Biological Reserve and the Vale Natural Reserve, in Espírito Santo, Brazil. The mitochondrial COI gene was amplified, sequenced and confronted with the BOLD database. It was possible to identify 62.16% of samples, totaling 62 different species, including Pyrrhura cruentata, Chaetomys subspinosus, Puma yagouaroundi and Leopardus wiedii considered Vulnerable in the National Official List of Species of Endangered Wildlife. The most commonly identified animals were a bat (Molossus molossus), an opossum (Didelphis aurita) and a frog (Trachycephalus mesophaeus) species. Only one reptile was identified using the technique, probably due to lack of reference sequences in BOLD. These data may contribute to a better understanding of the impact of roads on species biodiversity loss and to introduce the DNA barcode technique to road ecology scenarios.

Bioclimatic distribution and prevalence maps for Fasciola hepatica in Espírito Santo State, Brazil.

BACKGROUND: Fasciolosis affects different ruminant species and leads to great economic losses for cattle farmers worldwide. Thus, the current study aimed to evaluate bovine fasciolosis prevalence in the state of Espírito Santo, Brazil, using slaughter maps provided by slaughterhouses and verifying the origin of cattle. METHODS: A map was created based on analysis of epidemiological data. The ArcGIS/ArcINFO 10.1 software was employed in order to elaborate updated bioclimatic maps that displayed the fasciolosis prevalence within the state - per city- between 2009 and 2011. RESULTS: According to the bioclimatic map it was clear that 52.24% of the state's total area comprise regions considered favorable for the development and survival of Fasciola hepatica. According to the data provided by slaughterhouses, the parasite was more frequent in the cities of Atílio Vivácqua, Itapemirim and Anchieta with respective prevalence of 28.41, 25.50 and 24.95%. Although the northern portion of the state is also favorable for the disease maintenance (reaching rates above 90%), several cities presented prevalence of only 0.99 and 1.94% respectively. These findings indicate that climatic and environmental factors only cannot be considered preponderant to fasciolosis occurrence. Regarding the slaughterhouse located in Anchieta city, the higher prevalence was registered in the cities of Jerônimo Monteiro, Alegre and Cachoeiro de Itapemirim, with mean prevalence of 1.21, 1.07 and 2.09% respectively. CONCLUSION: Although the present findings suggest a pattern for the prevalence of fasciolosis, records of the cities for the occurrence of the disease usually do not reflect the true origin of animals.

Bioclimatic distribution and prevalence maps for Fasciola hepatica in Espírito Santo State, Brazil

Fasciolosis affects different ruminant species and leads to great economic losses for cattle farmers worldwide. Thus, the current study aimed to evaluate bovine fasciolosis prevalence in the state of Espírito Santo, Brazil, using slaughter maps provided by slaughterhouses and verifying the origin of cattle. : A map was created based on analysis of epidemiological data. The ArcGIS/ArcINFO 10.1 software was employed in order to elaborate updated bioclimatic maps that displayed the fasciolosis prevalence within the state – per city– between 2009 and 2011.

Bioclimatic distribution and prevalence maps for Fasciola hepatica in Espírito Santo State, Brazil

Fasciolosis affects different ruminant species and leads to great economic losses for cattle farmers worldwide. Thus, the current study aimed to evaluate bovine fasciolosis prevalence in the state of Espírito Santo, Brazil, using slaughter maps provided by slaughterhouses and verifying the origin of cattle. : A map was created based on analysis of epidemiological data. The ArcGIS/ArcINFO 10.1 software was employed in order to elaborate updated bioclimatic maps that displayed the fasciolosis prevalence within the state – per city– between 2009 and 2011.

Procedimentos híbridos cardiovasculares / Cardiovascular hybrid procedures

Nos últimos anos, abservam-se mudanças de paradigmas no tratamento das doenças cardiovasculares no Brasil e no mundo. O aumento da prevalência de pacientes com cardiopatias complexas resulta em siuações clínicas nas quais a conjugação de esforços entre o cardiologista clínico, o cirurgião cardíaco o cardiologista intervencionista e outras especialidades é necessária para solucionar problemas e alcançar melhores resultados...