Bone Metabolism in Very Preterm Infants Receiving Total Parenteral Nutrition: do Intravenous Fat Emulsions Have an Impact?

ery preterm infants (<32 weeks' gestation) are at high risk for impaired skeletal development because of factors that limit the provision of extrauterine nutrients. Cumulative net deficiencies of calcium, phosphorus, docosahexaenoic acid (DHA), and arachidonic acid (ARA) are evident in these infants after prolonged administration of total parenteral nutrition (TPN). This is significant because minerals as well as metabolites of DHA and ARA are important modulators of bone cell differentiation, lengthening of bone, and bone matrix deposition. Furthermore, diets containing only precursors of DHA and ARA result in suboptimal skeletal growth. With the emergence of new intravenous lipid emulsions, it is important to understand the impact of fatty acids on bone metabolism in the third trimester in order to optimize the provision of TPN in very preterm infants. The purpose of this review is to evaluate current evidence regarding intravenous lipid emulsions and bone metabolism in very preterm infants receiving prolonged TPN and to identify areas of research needed.info:eu-repo/semantics/publishedVersio

Reprogramming human cells to naïve pluripotency: how close are we?

Pluripotent stem cells (PSCs) have the potential to revolutionize biomedical science; however, while it is simple to reproducibly obtain comparable, stable cell lines in mouse, those produced from human material typically show significant variability both within and between cell lines. This is likely due to differences in the cell identity of conventional mouse and human PSCs. It is hoped that recently identified conditions to reprogram human cells to a naïve-like state will produce better PSCs resulting in reproducible experimental outcomes and more consistent differentiation protocols. In this review we discuss the latest literature on the discovery of human naïve-like stem cells and examine how similar they are to both mouse naïve cells and the preimplantation human epiblast.L.E.B. is the recipient of a MRC PhD studentship and J.C.R.S. of a Wellcome Trust Senior Research Fellowship (WT101861)

Physicochemical and microbiological characteristics of Italian salami made of lamb and enriched with pequi (Caryocar brasiliense, Cambess)

The purpose of this study was to evaluate and compare the inclusion of different levels of pequi (Caryocar Brasiliense, Cambess) pulp in the processing of Italian salami made of lamb for the evaluation of their physicochemical and microbiological characteristics. Six formulations of Italian salamis were processed: no pequi pulp (control - treatment 1); 4% pequi pulp (treatment 2); 8% pequi pulp (treatment 3), 12% pequi pulp (Treatment 4), 16% pequi pulp (treatment 5) and 20% pequi pulp (treatment 6). During the maturation period, all Italian salamis made of lamb enriched with pequi presented similar behaviors; and acidity (pH) and water activity (aw) results showed stable end values. For protein, the Italian salami made of lamb without pequi pump presented a higher content. For one of the lowest contents of fat, treatment 3 showed the highest content of humidity. The contents of fat and ashes did not present any significant difference when comparing the Italian salami formulations. A color tending to dark, yellowish and reddish shades was observed in the Italian salamis made of lamb and enriched with pequi. All Italian salamis were microbiologically satisfactory, showing ideal sanitary conditions for consumption. Pequi is a typical fruit from the Brazilian cerrado region, with characteristic color, odor and flavor, and it is an option for inclusion in Italian salamis, but additional studies should be conducted to inspect the sensory acceptability of these products.Keywords: Cerrado fruit, fermented stuffed meat sausages, physicochemical parameters, microbiological parameters

Patients- and physicians- priorities for improvement: The case of rheumatic diseases

OBJECTIVES: To compare the health priorities elected by patients with rheumatic diseases and by their attending rheumatologists. PATIENTS AND METHODS: We undertook a cross-sectional study among patients and rheumatologists in Portuguese rheumatology outpatient clinics. 75% of all Portuguese Rheumatology Departments agreed to participate. Rheumatologists from non-participating hospital departments were asked to collaborate through their private practices. All patients were eligible for inclusion except if they were under 18 years of age or had a mental disorder that would affect their participation. Data were collected through dedicated questionnaires. Patients were asked to indicate 3 priorities for improvement out of 12 health domains (Arthritis Impact Measurement Scale 2) regarding their rheumatic disease. Rheumatologists were asked similar questions focused around rheumatoid arthritis (RA) and osteoarthritis (OA). RESULTS: 1,868 patients and 56 rheumatologists entered the study. The most commonly selected priorities by patients with rheumatic diseases were: "Rheumatic pain" (70%), "Walking and bending" (45%), and "Hand and Finger Function" (40%). The main priority for improvement among patients with RA was "Rheumatic Pain" (69%), while rheumatologists more commonly elected "Work" (55%) as their main priority for these patients. Among patients with OA, "Rheumatic Pain" was the first priority for both patients and doctors (elected by 75%, and 55% of respondents, respectively). CONCLUSIONS: Our study showed discordance between the priorities for improvement elected by patients and by their respective physicians. This was more pronounced in RA than in OA. Studying and addressing such differences may support physicians and institutions to better achieve the prime goal of incorporating and responding to patients' needs and preferences

Mapping of Alternative Oilseeds from the Brazilian Caatinga and Assessment of Catalytic Pathways toward Biofuels Production

Biofuels are increasingly important renewable resources in the world's energy matrix that have challenged the scientific community as well as small and large farmers to develop alternatives to fossil fuels in order to achieve the aims of energy transition. In particular, Brazil's proven competitiveness in agribusiness together with its rich biodiversity put the country in a key position in the biofuels market. The semiarid Caatinga of northeastern Brazil, an exclusive biome rich in many oilseed species suitable for potential energy purposes, is of particular interest in this field. Nowadays, soybeans are the main feedstock used for the production of biodiesel, but, due to the increasing demand for biofuels, the search for alternative sources of oil from tropical flora with high productivity is crucial. Under this premise, this systematic review focuses on mapping Caatinga's vegetable oil crops that could be used as alternative raw materials for biofuels' production in Brazil, in addition to traditional soybeans and sugarcane. To gain more detailed insight into these matrices, their main properties, including oil content, fatty acid profile and physicochemical properties, are discussed. Moreover, an overview is provided of processes to synthesize different types of biofuels, particularly biodiesel and aviation biokerosene, including the routes employing homogeneous, enzymatic and mainly heterogeneous catalysts. Finally, future prospects and challenges for renewable biofuels and the Caatinga biome are addressed

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

Ferromagnetic resonance studies in granular Co-SiO2 thin films

Properties of thin granular Co-SiO2 films have been studied by means of ferromagnetic resonance (FMR). The obtained FMR results are discussed using sample magnetization, electrical conductivity, and transmission electron microscopy analysis. Co and SiO2 were sequentially deposited for the sample preparation. The general behavior of the applied field for resonance could be described using effective out-of-plane anisotropies. A dipolar interaction model developed for magnetic heterostructures was applied to the interpretation of these anisotropies. The anisotropy terms caused by the magnetic particle shapes and by the film shape can explain the results for two metallic films close to percolation, in which the film shape is the preponderant contribution. In the case of an insulating sample, the consideration of an additional anisotropy term seems to be necessary to explain the results.99

The elastic constants of MgSiO3 perovskite at pressures and temperatures of the Earth's mantle

The temperature anomalies in the Earth's mantle associated with thermal convection1 can be inferred from seismic tomography, provided that the elastic properties of mantle minerals are known as a function of temperature at mantle pressures. At present, however, such information is difficult to obtain directly through laboratory experiments. We have therefore taken advantage of recent advances in computer technology, and have performed finite-temperature ab initio molecular dynamics simulations of the elastic properties of MgSiO3 perovskite, the major mineral of the lower mantle, at relevant thermodynamic conditions. When combined with the results from tomographic images of the mantle, our results indicate that the lower mantle is either significantly anelastic or compositionally heterogeneous on large scales. We found the temperature contrast between the coldest and hottest regions of the mantle, at a given depth, to be about 800K at 1000 km, 1500K at 2000 km, and possibly over 2000K at the core-mantle boundary.Comment: Published in: Nature 411, 934-937 (2001