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.     

Resveratrol Affects Insulin Signaling in Type 2 Diabetic Goto-Kakizaki Rats

Resveratrol is a biologically active diphenolic compound exerting multiple beneficial effects in the organism, including anti-diabetic properties. This action is, however, not fully elucidated. In the present study, we examined effects of resveratrol on some parameters related to insulin signaling, and also on diabetes-associated dysregulation in Goto-Kakizaki (GK) rats with congenital type 2 diabetes. Resveratrol was given at the dose of 20 mg/kg b.w. for 10 weeks. It was shown that the expression and phosphorylation levels of insulin receptor in the skeletal muscle of GK rats were significantly decreased, compared with control animals. However, these changes were totally prevented by resveratrol. Liver expression of the insulin receptor was also reduced, but in this case, resveratrol was ineffective. Resveratrol was also demonstrated to significantly influence parameters of insulin binding (dissociation constant and binding capacity) in the skeletal muscle and liver. Moreover, it was shown that the expression levels of proteins related to intracellular glucose transport (GLUT4 and TUG) in adipose tissue of GK rats were significantly decreased. However, treatment with resveratrol completely abolished these changes. Resveratrol was found to induce normalization of TUG expression in the skeletal muscle. Blood levels of insulin and GIP were elevated, whereas proinsulin and GLP-1 diminished in GK rats. However, concentrations of these hormones were not affected by resveratrol. These results indicate that resveratrol partially ameliorates diabetes-associated dysregulation in GK rats. The most relevant finding covers the normalization of the insulin receptor expression in the skeletal muscle and also GLUT4 and TUG in adipose tissue.     

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient''s disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [¹⁸F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.     

Catalytic graphene formation in coal tar pitch- derived carbon structure in the presence of SiO2 nanoparticles

A simple and effective way to manufacture graphene from a coal tar pitch (CTP) is demonstrated. Silica (SiO₂) nanoparticles were used to modify the CTP as carbon precursor. A silica nanofiller introduced into the CTP matrix underwent carboreduction during heat treatment to 2000 °C, resulting in the formation of silicon carbide. Surfaces of SiC grains were sites for graphene formation. The influence of SiO₂ on the structure and microstructure of CTP- based carbon matrix, after annealing up to 2800 °C, was studied. Carbon samples were analyzed using X- ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and Raman Spectroscopy. Crystallite sizes (L_a, L_c) and interplanar distance (d₀₀₂) were determined. The presence of SiO₂ in CTP carbon precursor favored the crystallites’ growth in the ‘a′ crystallographic graphite direction, and inhibited their growth on the ‘c′ axis. The crystallites composing of graphene layers, were characterized by an elongated dimension in the ‘a′ axis direction. Above 2000 °C silicon carbide decomposed, followed by the sublimation of silicon from the carbon matrix.     

Hydroxyl Group Separation Distances in Anti-Freeze Compounds and Their Effects on Ice Nucleation

Since the discovery of biological antifreeze glycoproteins (AFGPs), which can inhibit ice nucleation, there has been considerable interest in understanding their mechanisms and mimicking them in synthetic polymers. In this study, we used molecular dynamics simulations of modified polyvinyl alcohol (PVA) compounds to show that the hydroxyl (OH) group distance is a key factor in whether certain compounds promote or inhibit ice nucleation. A hydroxyl distance smaller than ~2.8 Å but greater than ~7.1 Å in modified PVA (MPVA) compounds was associated with the promotion of ice nucleation, while a hydroxyl group separation distance of approximately ~5.0 Å was correlated with a delay in ice nucleation, owing to changes in the energy of the system. Thus, these results may help explain some of the mechanisms of current known anti-freeze compounds and may have implications for designing new anti-freeze compounds in the future.