Matrix metalloproteinases are associated with severity of disease among COVID-19 patients: A possible pharmacological target.

COVID-19 is a devastating disease and imbalanced matrix metalloproteinase (MMP) activity may contribute to its pathophysiology. This exploratory study examined whether increased circulating concentrations of MMP-2 and MMP-9, and their endogenous inhibitors, the tissue inhibitors of MMP (TIMP)-1, TIMP-2, TIMP-3 and TIMP-4 are persistently found in patients 2 weeks after their recovery from severe or critical COVID-19 as compared with those in healthy controls. Subjects who had severe (n = 26) or critical (n = 25) PCR-confirmed COVID-19 and healthy controls (n = 21) had blood samples drawn 2 weeks after recovery and serum MMP-2, MMP-9, TIMP-1, TIMP-2, TIMP-3 and TIMP-4 were determined using two Human Luminex® Discovery Assays.

Genomic epidemiology of SARS-CoV-2 in large university hospital cohort: the UnCoVER-Brazil project.

This work aimed to study the role of different SARS-CoV-2 lineages in the epidemiology of multiple waves of the COVID-19 pandemic in Ribeirão Preto (São Paulo state), with comparison within Brazil and globally. Viral genomic sequencing was combined with clinical and sociodemographic information of 2,379 subjects at a large Brazilian hospital. On the whole 2,395 complete SARS-CoV-2 genomes were obtained from April 2020 to January 2022.

Modelling the adsorption on oxidized carbon nanotubes using a statistical mechanics approach.

Carbon nanotubes have several applications including the removal of pollutants via adsorption. Many studies were carried out in order to evaluate how the functionalization of these materials improves the efficiency of the process. However, a better understanding of the mechanisms involved in adsorption on nanotubes is still needed.

Adsorbate-adsorbent potential energy function from second virial coefficient data: a non-linear Hopfield Neural Network approach.

The Hopfield Neural Network has been successfully applied to solve ill-posed inverse problems in different fields of chemistry and physics. In this work, the non-linear approach for this method will be applied to retrieve the empirical parameters of potential energy function, [Formula: see text], between adsorbate and adsorbent from experimental data. Since the adsorption data is related to the second virial coefficient and therefore to [Formula: see text] through an integral equation, the Hopfield Neural Network will be used to find the best parameters which fits the experimental data.

Partial radial distribution functions for a two-component glassy solid, GeSe[Formula: see text], from scattering experimental data using an artificial intelligence framework.

The Hopfield neural network has been applied successfully to solve ill-posed inverse problems in simple monoatomic liquids structure using scattering experimental data to retrieve the radial distribution function, g(r), and direct correlation function, C(r). In this work, the method was extended to a more complex system: a two-component glassy solid, GeSe. To acquire results with correct peak intensities and behavior for large values of r, it was necessary to carry out the calculations a few times by adjusting the initial conditions to solve a set of coupled equations.

Long-Term Symptoms among COVID-19 Survivors in Prospective Cohort Study, Brazil.

We conducted a prospective cohort study in a population with diverse ethnic backgrounds from Brazil to assess clinically meaningful symptoms after surviving coronavirus disease. For most of the 175 patients in the study, clinically meaningful symptoms, including fatigue, dyspnea, cough, headache, and muscle weakness, persisted for >120 days after disease onset.

Flammability limits of hydrated and anhydrous ethanol at reduced pressures in aeronautical applications.

There is interest in finding the flammability limits of ethanol at reduced pressures for the future use of this biofuel in aeronautical applications taking into account typical commercial aviation altitude (<40,000 ft). The lower and upper flammability limits (LFL and UFL, respectively) for hydrated ethanol and anhydrous ethanol (92.6% and 99.

Flammability limits: a review with emphasis on ethanol for aeronautical applications and description of the experimental procedure.

The lower and upper flammability limits of a fuel are key tools for predicting fire, assessing the possibility of explosion, and designing protection systems. Knowledge about the risks involved with the explosion of both gaseous and vaporized liquid fuel mixtures with air is very important to guarantee safety in industrial, domestic, and aeronautical applications. Currently, most countries use various standard experimental tests, which lead to different experimental values for these limits.