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The emergence of Covid-19 started in China and has rapidly spread across the globe, notably in Italy and more recently to Brazil. This is a very worrying situation for the affected countries. This Brief Communication aims to describe and correlate the number of confirmed cases and deaths of Covid-19 in Brazil and Italy. This is a descriptive and retrospective study that used data collated on the World Health Organization (WHO) online platform between 21 January and 19 April 2020. After analyzing the data, it was observed that the number of confirmed cases and deaths in Brazil is lower than that in Italy. There are certain factors in Brazil which see it in a lower risk position than Italy; however, despite the current slow spread of the virus, the situation in Brazil is difficult to predict.

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Social isolation is extremely important to minimize the effects of a pandemic. Latin American countries have similar socioeconomic characteristics and health system infrastructures. These countries face difficulties in dealing with the COVID-19 pandemic, and some of them have very high death rates. The government stringency index (GSI) of 12 Latin American countries was gathered from the Oxford COVID-19 Government Response Tracker project. The GSI is calculated by considering nine social distancing and isolation measures. Population data from the United Nations Population Fund and number-of-deaths data were collected from the dashboard of the WHO. We performed an analysis of the data collected from March through December 2020 using a mixed linear model. Peru, Brazil, Chile, Bolivia, Colombia, Argentina, and Ecuador had the highest death rates, with an increasing trend over time. Suriname, Venezuela, Uruguay, Paraguay, and Guyana had the lowest death rates, and these rates remained steady. The GSI in most countries followed the same pattern during the months analyzed. In other words, high indices at the beginning of the pandemic and lower indices in the latter months, whereas the number of deaths increased during the entire period. Almost no country kept its GSI high for a long time, especially from October to December. Time and GSI, as well as their interaction, were highly significant. As their interaction increases, the death rate decreases. In conclusion, a greater GSI at the start of the COVID-19 pandemic was associated with a decrease in the number of deaths over time in Latin American countries.

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Diabetes associated with post-menopause is related to a worse condition of kidney disease. Taking into consideration that this disorder may be regulated by estrogenic mediators, we evaluated the renal protective effect of isoflavone. We investigated the role of the PPARγ in the pathogenesis of the disease. For this study, we used diabetic female rats in a postmenopausal model through ovariectomy. The animals were treated with isoflavone or 17β-estradiol. A dosage was administered to bring on blood glycemia, and through immunohistochemistry, we evaluated the immunoreactivity of PPARγ in the endometrium and renal tissue. We analyzed the immunoreactivity of renal injury molecule KIM-1 and the collagen and glycogen densities in the kidney. Through bioinformatics analysis, we observed PPARγ and COL1A1 gene expression under the influence of different glucose doses. In particular, we observed that isoflavone and 17β-estradiol regulate blood glycemia. Renal injury was inhibited by isoflavone, observed by a reduction in KIM-1, along with glycogen accumulation. These benefits of isoflavone may be associated with PPARγ overexpression in the kidneys and endometrium of diabetic ovariectomized rats.