Rewilding and the risk of creating new, unwanted ecological interactions

Through a global and interdisciplinary lens, this book discusses, analyzes and summarizes the novel conservation approach of rewilding. The volume introduces key rewilding definitions and initiatives, highlighting their similarities and differences. It reviews matches and mismatches between the current state of ecological knowledge and the stated aims of rewilding projects, and discusses the role of human action in rewilding initiatives. Collating current scholarship, the book also considers the merits and dangers of rewilding approaches, as well as the economic and socio-political realities of using rewilding as a conservation tool. Its interdisciplinary nature will appeal to a broad range of readers, from primary ecologists and conservation biologists to land managers, policy makers and conservation practitioners in NGOs and government departments. Written for a scientifically literate readership of academics, researchers, students, and managers, the book also acts as a key resource for advanced undergraduate and graduate courses

Finding and tracing human MSC in 3D microenvironments with the photoconvertible proteinDendra2

Mesenchymal Stem/Stromal Cells (MSC) are a promising cell type for cell-based therapies - from tissue regeneration to treatment of autoimmune diseases - due to their capacity to migrate to damaged tissues, to differentiate in different lineages and to their immunomodulatory and paracrine properties. Here, a simple and reliable imaging technique was developed to study MSC dynamical behavior in natural and bioengineered 3D matrices. Human MSC were transfected to express a fluorescent photoswitchable protein, Dendra2, which was used to highlight and follow the same group of cells for more than seven days, even if removed from the microscope to the incubator. This strategy provided reliable tracking in 3D microenvironments with different properties, including the hydrogels Matrigel and alginate as well as chitosan porous scaffolds. Comparison of cells mobility within matrices with tuned physicochemical properties revealed that MSC embedded in Matrigel migrated 64% more with 5.2 mg protein/mL than with 9.6 mg/mL and that MSC embedded in RGD-alginate migrated 51% faster with 1% polymer concentration than in 2% RGD-alginate. This platform thus provides a straightforward approach to characterize MSC dynamics in 3D and has applications in the field of stem cell biology and for the development of biomaterials for tissue regeneration

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

Camouflaging in a Complex Environment—Octopuses Use Specific Features of Their Surroundings for Background Matching

Living under intense predation pressure, octopuses evolved an effective and impressive camouflaging ability that exploits features of their surroundings to enable them to “blend in.” To achieve such background matching, an animal may use general resemblance and reproduce characteristics of its entire surroundings, or it may imitate a specific object in its immediate environment. Using image analysis algorithms, we examined correlations between octopuses and their backgrounds. Field experiments show that when camouflaging, Octopus cyanea and O. vulgaris base their body patterns on selected features of nearby objects rather than attempting to match a large field of view. Such an approach enables the octopus to camouflage in partly occluded environments and to solve the problem of differences in appearance as a function of the viewing inclination of the observer

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

Possible bite-induced abscess and osteomyelitis in Lufengosaurus (Dinosauria: sauropodomorph) from the Lower Jurassic of the Yimen Basin, China

We report an osseous abnormality on a specimen of the sauropod dinosaur Lufengosaurus huenei from the Fengjiahe Formation in Yuxi Basin, China. A gross pathological defect occurs on the right third rib, which was subjected to micro-computed tomographic imaging as an aid in diagnosis. The analysis of pathological characteristics and the shape of the abnormality is incompatible with impact or healed trauma, such as a common rib fracture, and instead suggests focal penetration of the rib, possibly due to a failed predator attack. The identification of characteristics based on gross morphology and internal micro-morphology presented by the specimen, suggests an abscess with osteomyelitis as the most parsimonious explanation. Osteomyelitis is a severe infection originating in the bone marrow, usually resulting from the introduction of pyogenic (pus-producing) bacteria into the bone. Micro-tomographic imaging of the lesion suggests a degree of healing and bone remodelling following post-traumatic wound infection with evidence of sclerotic bone formation at the site of pathological focus, indicating that L. huenei survived the initial trauma. However, as osteomyelitis can express through widespread systemic effects, including a lowering of immune response and overall condition, this disease may have been a contributing factor to the eventual death of the individual

Dietary availability patterns of the brazilian macro-regions

<p>Abstract</p> <p>Introduction</p> <p>Epidemiological studies have raised concerns about the role of dietary patterns on the risk of chronic diseases and also in the formulation of better informed nutrition policies.</p> <p>Objective</p> <p>The development of a dietary availability patterns according to geographic regions in Brazil.</p> <p>Methodology</p> <p>The 2002-2003 Brazilian Household Budget Survey was conducted in 48,470 households. Dietary availability patterns were identified by Principal Component Analysis using as a unit of analysis the survey's Primary Sampling Units (PSUs) and purchased amounts for 21 food groups. Each of the extracted dietary availability patterns was regressed on socioeconomics categories.</p> <p>Results</p> <p>There were no differences in dietary availability patterns between urban and rural areas. In all regions, a rice and beans pattern was identified. This pattern explained 15% to 28% of the variance dependent on the region of the country. In South, Southeast and Midwest regions, a mixed pattern including at least 10 food groups explaining 8% to 16% of the variance. In the North region (Amazon forest included) the first pattern was based on fish and nuts and then it was designed as regional pattern. In multiple linear regression the rice and beans pattern was associated with the presence of adolescents in the households, except for North region, whereas the presence of adolescents was associated with the Regional pattern. A mixed patterns were associated with a higher income and education (p < 0.05), except in the South region.</p> <p>Conclusion</p> <p>The rice and beans and regional dietary availability patterns, both considered healthy eating patterns are still important in the country. Brazil has taken many actions to improve nutrition as part of their public health policies, the data of the Household Budget Survey could help to recognize the different food choices in the large regions of the country.</p