Patterns of physical activity and SARS-CoV-2 severe pneumonia: A case-control study.

BACKGROUND: Regular physical activity is associated with a low risk of severe community-acquired infections. However, the hypothesis that a physical inactivity pattern is associated with a higher risk for severe COVID-19 has not been completely proven, especially with severe pneumonia. OBJECTIVE: The goal of this study was to confirm the link between physical activity patterns and severe SARS-CoV-2 pneumonia. DESIGN: Case-control study. METHODS: This study involved 307 patients who developed SARS-CoV-2 severe pneumonia and were hospitalized in an intensive care unit. Age- and sex-matched controls (307) were selected from the same population: patients with mild to moderate forms of COVID-19 who were not hospitalized. Physical activity patterns were assessed using the short version of the International Physical Activity Questionnaire. RESULTS: The mean physical activity levels were lower in the SARS-CoV-2 severe pneumonia group as compared to the control group: 1576±2939 vs 2438±2999, metabolic equivalent of task (MET-min/week), p<0.001. A high or moderate physical activity level was more common in the control group, and a low physical activity level was more observed in the case group (p<0.001). Obesity was also associated with severe SARS-CoV-2 pneumonia (p<0.001). Multivariable analysis showed that a low physical activity level was associated with a higher risk for severe SARS-CoV-2 pneumonia, independent of nutritional status (CI 3.7; 2.24-5.99), p<0.001). CONCLUSION: A higher and moderate level of physical activity is linked to a lower risk of SARS-CoV-2 severe pneumonia.

Morphological, cellular, and molecular basis of brain infection in COVID-19 patients.

Although increasing evidence confirms neuropsychiatric manifestations associated mainly with severe COVID-19 infection, long-term neuropsychiatric dysfunction (recently characterized as part of "long COVID-19" syndrome) has been frequently observed after mild infection. We show the spectrum of cerebral impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, ranging from long-term alterations in mildly infected individuals (orbitofrontal cortical atrophy, neurocognitive impairment, excessive fatigue and anxiety symptoms) to severe acute damage confirmed in brain tissue samples extracted from the orbitofrontal region (via endonasal transethmoidal access) from individuals who died of COVID-19. In an independent cohort of 26 individuals who died of COVID-19, we used histopathological signs of brain damage as a guide for possible SARS-CoV-2 brain infection and found that among the 5 individuals who exhibited those signs, all of them had genetic material of the virus in the brain. Brain tissue samples from these five patients also exhibited foci of SARS-CoV-2 infection and replication, particularly in astrocytes. Supporting the hypothesis of astrocyte infection, neural stem cell-derived human astrocytes in vitro are susceptible to SARS-CoV-2 infection through a noncanonical mechanism that involves spike-NRP1 interaction. SARS-CoV-2-infected astrocytes manifested changes in energy metabolism and in key proteins and metabolites used to fuel neurons, as well as in the biogenesis of neurotransmitters. Moreover, human astrocyte infection elicits a secretory phenotype that reduces neuronal viability. Our data support the model in which SARS-CoV-2 reaches the brain, infects astrocytes, and consequently, leads to neuronal death or dysfunction. These deregulated processes could contribute to the structural and functional alterations seen in the brains of COVID-19 patients.

Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic

The current scenario of a global pandemic caused by the virus SARS-CoV-2 (COVID19), highlights the importance of water studies in sewage systems. In Brazil, about 35 million Brazilians still do not have treated water and more than 100 million do not have basic sanitation. These people, already exposed to a range of diseases, are among the most vulnerable to COVID-19. According to studies, places that have poor sanitation allow the proliferation of the coronavirus, been observed a greater number of infected people being found in these regions. This social problem is strongly related to the lack of effective management of water resources, since they are the sources for the population's water supply and the recipients of effluents stemming from sanitation services (household effluents, urban drainage and solid waste). In this context, studies are needed to develop technologies and methodologies to improve the management of water resources. The application of tools such as artificial intelligence and hydrometeorological models are emerging as a promising alternative to meet the world's needs in water resources planning, assessment of environmental impacts on a region's hydrology, risk prediction and mitigation. The main model of this type, WRF-Hydro Weather Research and Forecasting Model), represents the state of the art regarding water resources, as well as being the object of study of small and medium-sized river basins that tend to have less water availability. hydrometeorological data and analysis. Thus, this article aims to analyze the feasibility of a web tool for greater software usability and computational cost use, making it possible to use the WRF-Hydro model integrated with Artificial Intelligence tools for short and medium term, optimizing the time of simulations with reduced computational cost, so that it is able to monitor and generate a predictive analysis of water bodies in the MATOPIBA region (Maranhão-Tocantins-Piauí-Bahia), constituting an instrument for water resources management. The results obtained show that the WRF-Hydro model proves to be an efficient computational tool in hydrometeorological simulation, with great potential for operational, research and technological development purposes, being considered viable to implement the web tool for analysis and management of water resources and consequently, assist in monitoring and mitigating the number of cases related to the current COVID-19 pandemic. This research are in development and represents a preliminary results with future perspectives.