COVID-19: Direct and Indirect Mechanisms of Statins

The virus responsible for the current COVID-19 pandemic is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): a new virus with high infectivity and moderate mortality. The major clinical manifestation of COVID-19 is interstitial pneumonia, which may progress to acute respiratory distress syndrome (ARDS). However, the disease causes a potent systemic hyperin-flammatory response, i.e., a cytokine storm or macrophage activation syndrome (MAS), which is associated with thrombotic complications. The complexity of the disease requires appropriate intensive treatment. One of promising treatment is statin administration, these being 3-hydroxy-3-methylglutaryl-CoA reductase inhibitors that exert pleiotropic anti-inflammatory effects. Recent studies indicate that statin therapy is associated with decreased mortality in COVID-19, which may be caused by direct and indirect mechanisms. According to literature data, statins can limit SARS-CoV-2 cell entry and replication by inhibiting the main protease (Mpro) and RNA-dependent RNA polymerase (RdRp). The cytokine storm can be ameliorated by lowering serum IL-6 levels; this can be achieved by inhibiting Toll-like receptor 4 (TLR4) and modulating macrophage activity. Statins can also reduce the complications of COVID-19, such as thrombosis and pulmonary fibrosis, by reducing serum PAI-1 levels, attenuating TGF-β and VEGF in lung tissue, and improving endothelial function. Despite these benefits, statin therapy may have side effects that should be considered, such as elevated creatinine kinase (CK), liver enzyme and serum glucose levels, which are already elevated in severe COVID-19 infection. The present study analyzes the latest findings regarding the benefits and limitations of statin therapy in patients with COVID-19.     

The Antipsychotic D2AAK1 as a Memory Enhancer for Treatment of Mental and Neurodegenerative Diseases

The treatment of memory impairments associated with the central nervous system diseases remains an unmet medical need with social and economic implications. Here we show, that a multi-target ligand of aminergic G protein-coupled receptors with antipsychotic activity in vivo (D2AAK1) stimulates neuron growth and survival and promotes neuron integrity. We focused on the multilevel evaluation of the D2AAK1-related effects on neurons in terms of behavioral, cellular, molecular, and biochemical features in vivo and in vitro, such as memory-related responses, locomotor activity, tissue sections analysis, metabolic activity, proliferation level, neurons morphology, and proteins level involved in intracellular signaling pathways. In silico studies indicate that activation of calcium/calmodulin-dependent protein kinase I (CaMKI) may underline some of the observed activities of the compound. Furthermore, the compound increases hippocampal neuron proliferation via the activation of neurotrophic factors and cooperating signals responsible for cell growth and proliferation. D2AAK1 improves memory and learning processes in mice after both acute and chronic administration. D2AAK1 also causes an increase in the number of hippocampal pyramidal neurons after chronic administration. Because of its neuroprotective properties and pro-cognitive activity in behavioral studies D2AAK1 has the potential for the treatment of memory disturbances in neurodegenerative and mental diseases.     

β-Hydroxy-β-Methylbutyrate (HMB) Supplementation Prevents Bone Loss during Pregnancy—Novel Evidence from a Spiny Mouse (Acomys cahirinus) Model

The aim of this study was to determine the effects of ß-hydroxy-ß-methylbutyrate (HMB) supplementation during pregnancy on postpartum bone tissue quality by assessing changes in trabecular and compact bone as well as in hyaline and epiphyseal cartilage. The experiment was carried out on adult 6-month-old female spiny mice (Acomys cahirinus) divided into three groups: pregnant control (PregCont), pregnant HMB-treated (supplemented with 0.02 g/kg b.w of HMB during the second trimester of pregnancy, PregHMB), and non-pregnant females (NonPreg). Cross-sectional area and cortical index of the femoral mid-shaft, stiffness, and Young modulus were significantly greater in the PregHMB group. Whole-bone mineral density was similar in all groups, and HMB supplementation increased trabecular number. Growth plate cartilage was the thinnest, while the articular cartilage was the thickest in the PregHMB group. HMB supplementation increased the content of proteoglycans in the articular cartilage and the percentage of immature collagen content in metaphyseal trabeculae and compact bone. In summary, dietary HMB supplementation during the second trimester of pregnancy intensifies bone metabolic processes and prevents bone loss during pregnancy.     

Homogenization of metallic fiber-reinforced composites under stochastic ageing

The main aim of this paper is to present an application of the generalized stochastic perturbation technique to model stochastic ageing processes of the metallic fibre-reinforced periodic composite materials in terms of their effective properties. Those ageing processes are modelled here as two-parametric time series having Gaussian random initial values and time rate, both defined uniquely by their expectations and standard deviations. Computational homogenization procedure is discrete and based on the Finite Element Method program MCCEFF as well as the computer algebra system MAPLE, where the Response Function Method and the stochastic analysis are entirely implemented. This numerical strategy is used to analyze probabilistic moments of the effective elastic tensor of the few metal matrix composites as well as to simulate stochastic ageing of two representative composites - MoSio₂-SiC and Ti-SiC. The approach proposed and results of computations may be further applied in the reliability analysis of metallic or the other composites.     

Artificial neural network model of molten carbonate fuel cells: Validation on experimental data

This article shows the teaching processes of artificial neural networks that are used to model the molten carbonate fuel cell (MCFC). Researchers model MCFCs to address a variety of issues across a range of complexities, from simply gauging the effect of temperature through to a complete model with 14 input parameters. The architecture of the model is a triple layer network with one hidden layer containing three neurons. The activation function used for the hidden layer was a hyperbolic tangent, with the last layer being based on linear function. We produced various network configurations, mostly networks containing one hidden layer. Models map the work of a real fuel cell with an average error in the range of 2.4% to 4.6%. The model we created guided the optimization of the thermal‐flow and construction parameters of the MCFC. Commercially available software was used to build the model and optimize the operating parameters. The selected objective functions were the efficiency of electricity production and the power density obtained from the cell's surface. The results obtained serve as pointers for possible changes in fuel cell operation and could lead to some structural changes being made.     

Novel clustering-based pruning algorithms

Pattern Analysis and Applications - One of the crucial problems of designing a classifier ensemble is the proper choice of the base classifier line-up. Basically, such an ensemble is formed on the...     

Optical vortices generation using the Wollaston prism

A new setup of interferometers is proposed in which the set of specific optical markers--optical vortices--could be generated. The classical Mach-Zender two-beam interferometer has been modernized using the Wollaston prism. In this setup, the optical vortices could be obtained for a wide range of both beam parameters. The numerical analysis and experiments confirm our theoretical predictions.     

Temperature influence on six layers samaria doped ceria matrix impregnated by lithium/potassium electrolyte for Molten Carbonate Fuel Cells

Fuel cells operating at elevated temperatures are suitable for medium and large scale applications, thus they have good prospects for commercialization. Molten Carbonate Fuel Cells (MCFCs) appear among the most promising in this respect. MCFC has a number of advantages over other high temperature fuel cells: (i) high energy efficiency and high electromotive force, (ii) nickel instead of platinium as a catalyst, (iii) electrolyte thickness of about 1 mm is much more easier to manufacture, (iv) it can be used as a CO₂ separator due to its ability to capture carbon dioxide from the cathode side.LiAlO₂ is a very effective support for molten carbonates, but it is very expensive as there are few manufacturers. In a single conducting electrolyte, the cathode inlet needs to contain an adequate ratio of CO₂ to O₂, (2:1), this results in low oxygen partial pressure at the cathode inlet (taking into account that oxygen is being delivered in air at an initial molar fraction of 21%). The low pressure of oxygen results in a relatively low Nernst voltage and feeds through into lower MCFC performance. By using a dual conducting electrolyte, a more favorable ratio between carbon dioxide and oxygen (CO₂:O₂<2) can be obtained, achieving higher maximum voltages which in turn translate into higher efficiency.Excellent performance was obtained for the Sm_0.2·Ce_0.8·O_1.9– carbonate composite and nanocomposite electrolytes prepared using eutectic carbonates with a mixture of Li₂·CO₃/Na₂·CO₃. High temperature membranes based on dual carbonate and oxide electrolytes have been shown to selectively separate CO₂ above 600 °C.In this paper, the testing results of a composite electrolyte layer based on Samaria Doper Ceria and Lithium/Potassium carbonates for its electrochemical performance as a matrix for MCFC are presented. The voltage–current density curves were collected in a range of temperatures: 500–800 °C.The idea is to use a dual conductive composite electrolyte as a matrix for Molten Carbonate Fuel Cells. This results in an improvement in the performance of the MCFC, by, in particular, increasing ionic conductivity through additional O⁼ conduction.     

Rotifer Diversity in the Acidic Pyrite Mine Pit Lakes in the Sudety Mountains (Poland)

The diversity of rotifers was studied in three artificial water bodies (Azure Lake, Yellow Lake, and Purple Lake), which were once pyrite mines. The physicochemical parameters and the zooplankton composition of the water were determined. Azure Lake had a pH of 3.4–6.9, conductivity values of 165–194 µS cm^??1, and low concentrations of sulphate, calcium, magnesium, copper, and iron, while the other lakes had a pH of 2.6–2.9, a conductivity of 1636–3400 µS cm^??1, and high concentrations of sulphate (up to 2863 mg dm^??3), Cu (up to 2650 µg dm^??3), and Fe (up to 178.3 mg dm^??3). The rotifer community in the lakes comprised 27 taxa (15 in Azure Lake, 13 in Purple Lake and 14 in Yellow Lake). We also found two species that are rarely observed in Poland (Aspelta cincinator and Elosa spinifera), and three species commonly found in acidic water (E. worallii, Cephalodella delicata, and C. hoodi). The types of rotifers in Azure Lake differed from those in the other two lakes. The Shannon–Weaver biodiversity index (H′) was the highest in Purple Lake (H′?=?1.255) and lowest in Azure Lake (H′?=?0.455). The effect of some of the physicochemical parameters on rotifer diversity is discussed.     

Manufacturing of γ-LiAlO2 matrix for molten carbonate fuel cell by high-energy milling

Molten carbonate fuel cells (MCFCs) are promising high temperature power generating devices. However, unlike solid oxide fuel cells (SOFCs) they utilize a liquid electrolyte which must be immobilized in a porous matrix.In this paper, a slurry composition for lithium aluminate (γ-LiAlO₂) matrix was developed and green matrices were subsequently formed by the tape casting method. In order to achieve the desired structure of the matrix (pore size, porosity) γ-LiAlO₂ powder was milled in a planetary ball mill for 18 h with a solvent, dispersant and defoamer. After this step, other ingredients were added, including a binder and plasticizer to obtain optimal rheology of the slurry. Cell tests confirmed optimal performance of the matrix compared to the third party reference γ-LiAlO₂ matrices. Burned out matrix was characterized by scanning electron microscopy (SEM) and laser diffraction in order to determine the γ-LiAlO₂ powder particle size and morphology. The results show that high-energy milling enabled a fine pore structure and high specific surface area of the matrix to be obtained in a relatively short time, compared to conventional fabrication routes. The matrix structure obtained within this study is suitable for high performance operation of MCFC.