Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5′- and 3′-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.     

Modeling of conductivity in composites with random resistor networks

Composite polymeric electrolytes (CPE) are well known systems in which an improvement in electrical conductivity of the polymer is achieved by the addition of a non-conductive additive (ceramic powders and immiscible polymers). A new class of conductivity models based on the application of the multi-value random resistor networks to the studies of CPE was developed by the authors. The first stage of the simulation is based on the virtual composite sample generation and its transformation into a form of the three-dimensional resistor network. The sample generation can take into account variable material parameters such as average grain diameter, shell thickness as well as their statistical distribution and different dependencies of local shell conductivity on the distance from the grain surface. The second stage of the algorithm is the use of the modified iteration procedure based on Kirkpatrick approach leading to the direct current resistivity of the virtual sample. The presented results were obtained for the matrix size 100 unit × 100 unit × 100 unit (with assumption 1 unit = 1 μm). The dependency of conductivity on the grain filler concentration was studied for varying grain sizes, changing shell thickness as well as for different statistical distributions of these parameters. The obtained results of simulation are in general agreement with the experimental data.     

Detecting evoked potentials with SVD- and ICA-based statistical models.

In the functional diagnostics of human sensor systems, the analysis of stimulus responses embedded in an electroencephalogram (EEG), e.g. evoked potentials (EPs), is of high relevance for an objective electrophysiological assessment. The aim of this work is to detect weak EPs from highly contaminated signal traces. In principle this can be done using methods of spatiotemporal signal processing, which simultaneously increase the weak SNR (signal-to-noise ratio). However, methods based on any a priori knowledge of spatial or temporal properties as well as the propagation speed and direction are not applicable. Models with adjustable signal properties similar to real cortical activity are necessary for the development and evaluation of new methods of spatiotemporal signal processing. A model is needed which can be used in forward- and inverse-projection calculations. This study aims to develop a signal generator of the background EEG activity with embedded EPs of fully adjustable signal parameters. The study also compares the results of modeled signal analysis by known methods for signal decomposition, SVD (singular value decomposition) and ICA (independent component analysis).     

Evolution of the microstructure in the hot rolling process

A thermomechanical finite-element model of flat rolling is coupled with closed form equations describing the process of recrystallization and is applied to study hot rolling of low carbon steel strips. Formulae for the recrystallized grain diameters, developed by various authors, are considered. Calculated diameters of the grains are compared with the results of the measurements carried out after experimental hot rolling of the carbon steel samples. Evaluating the accuracy of the calculations, using each of the expressions for the diameter of the recrystallized austenite grains, indicates that the relation of Roberts is closest to the measurements.     

Interfacial activity of 4-alkylphenylamines and the rate of palladium(II) extraction

Interfacial tension isotherms were determined in hydrocarbon-water systems for 4-alkylphenylamines containing from 6 to 16 carbon atoms in their alkyl chains, and the surface excess isotherms were computed and interpreted using various adsorption isotherms. Palladium(II) was extracted with 4-alkylphenylamines from 3 M HCI solutions. The maximum extraction rate of palladium(II) is observed for 4-decyl- and 4-dodecylphenylamines which exhibit good interfacial activity. Compounds soluble in the aqueous phase (4-hexylphenylamine) or in toluene (4-hexadecylphenylamine) extract palladium(II) slower than 4-decyl- and 4-dodecyl- phenylamines.     

A labeling algorithm to recognize a line digraph and output its root graph

In this short note we present a very efficient, linear time algorithm for the recognition of line digraphs. The algorithm is based on a reformulation of the characterization of line digraphs proved by Harary and Norman.     

Solvent Screening for Solubility Enhancement of Theophylline in Neat,Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally studied binary systems, the one containing DMSO with water in unimolar proportions was found to be the most effective in theophylline dissolution. Likewise, for NADES, the addition of water (0.2 molar fraction) resulted in increased solubility compared to pure eutectics, with the highest solubilisation potential offered by the composition of choline chloride with glycerol. The ensemble of Statistica Automated Neural Networks (SANNs) developed using intermolecular interactions in pure systems has been found to be a very accurate model for solubility computations. This machine learning protocol was also applied as an extensive screening for potential solvents with higher solubility of theophylline. Such solvents were identified in all three subgroups, including neat solvents, binary mixtures and ternary NADES systems. Some methodological considerations of SANNs applications for future modelling were also provided. Although the developed protocol is focused exclusively on theophylline solubility, it also has general importance and can be used for the development of predictive models adequate for solvent screening of other compounds in a variety of systems. Formulation of such a model offers rational guidance for the selection of proper candidates as solubilisers in the designed solvents screening.     

The Role of TRPM2 in Endothelial Function and Dysfunction

The transient receptor potential (TRP) melastatin-like subfamily member 2 (TRPM2) is a non-selective calcium-permeable cation channel. It is expressed by many mammalian tissues, including bone marrow, spleen, lungs, heart, liver, neutrophils, and endothelial cells. The best-known mechanism of TRPM2 activation is related to the binding of ADP-ribose to the nudix-box sequence motif (NUDT9-H) in the C-terminal domain of the channel. In cells, the production of ADP-ribose is a result of increased oxidative stress. In the context of endothelial function, TRPM2-dependent calcium influx seems to be particularly interesting as it participates in the regulation of barrier function, cell death, cell migration, and angiogenesis. Any impairments of these functions may result in endothelial dysfunction observed in such conditions as atherosclerosis or hypertension. Thus, TRPM2 seems to be an attractive therapeutic target for the conditions connected with the increased production of reactive oxygen species. However, before the application of TRPM2 inhibitors will be possible, some issues need to be resolved. The main issues are the lack of specificity, poor membrane permeabilization, and low stability in in vivo conditions. The article aims to summarize the latest findings on a role of TRPM2 in endothelial cells. We also show some future perspectives for the application of TRPM2 inhibitors in cardiovascular system diseases.     

A multifactor study of catalyzed hydrolysis of solid NaBH4 on cobalt nanoparticles: Thermodynamics and kinetics

In the present work, hydrogen generation through hydrolysis of a NaBH_4(s)/catalyst_(s) solid mixture was realized for the first time as a solid/liquid compact hydrogen storage system using Co nanoparticles as a model catalyst. The performance of the system was analysed from both the thermodynamic and kinetic points of view and compared with the classical catalyzed hydrolysis of a NaBH₄ solution. The kinetic analysis of the NaBH_4(s)/catalyst_(s)/H₂O_(l) system shows that the reaction is first order with respect to the catalyst concentration, and the activation energy equal to 35 kJ mol_NaBH4⁻¹. Additionally, calorimetric measurements of the heat evolved during the hydrolysis of NaBH₄ solutions evidence the global process energy (−217 kJ mol_NaBH4⁻¹). Characterization of the cobalt nanoparticles before and after the hydrolysis associated with the calorimetric measurements suggests the “in situ” formation of a catalytically active Co_xB phase through “reduction” of an outer protective oxide layer that is regenerated at the end of reaction.