[Experimental studies of biodegradable ureteral stent prototype].

Degradable ureteral stent not requiring redo procedure for removal is an important issue in modern urology. This device could solve the problem of «forgotten stent» often leading to long-term complications. The authors describe the prototype of biodegradable ureteral stent based on poly(L-lactide-co-ε-caprolactone) and present the first results of its testing.

Tunable high-order harmonic generation in GeSbTe nano-films.

High-order harmonic generation (HHG) in solids opens new frontiers in ultrafast spectroscopy of carrier and field dynamics in condensed matter, picometer resolution structural lattice characterization and designing compact platforms for attosecond pulse sources. Nanoscale structuring of solid surfaces provides a powerful tool for controlling the spatial characteristics and efficiency of the harmonic emission. Here we study HHG in a prototypical phase-change material GeSbTe (GST).

Crystal structure of KMnPOF with short- and long-range order inside the layered magnetic system.

Potassium manganese fluoride phosphate, KMnPOF, has been obtained through mild hydrothermal synthesis and characterized by scanning electron microscopy, microprobe analysis and X-ray diffraction. The compound possesses an orthorhombic symmetry and chiral space group 222 with = 4.7884(2), = 9.

Dynamics of the content of reactive oxygen species and the state of the glutathione system in the oral cavity during subchronic intoxication wuth the fungicide thiram and its antioxidant correction.

Thiram is a dithiocarbamate derivative, which is used as a fungicide for seed dressing and spraying during the vegetation period of plants, and also as an active vulcanization accelerator in the production of rubber-based rubber products. In this study the content of reactive oxygen species (ROS) and the state of the glutathione system have been investigated in the oral fluid and gum tissues of adult male Wistar rats treated with thiram for 28 days during its administration with food at a dose of 1/50 LD50. Thiram induced formation of ROS in the oral cavity; this was accompanied by an imbalance in the ratio of reduced and oxidized forms of glutathione due to a decrease in glutathione and an increase in its oxidized form as compared to the control.

The carbon footprint of predicting CO storage capacity in metal-organic frameworks within neural networks.

While artificial intelligence drives remarkable progress in natural sciences, its broader societal implications are mostly disregarded. In this study, we evaluate environmental impacts of deep learning in materials science through extensive benchmarking. In particular, a set of diverse neural networks is trained for a given supervised learning task to assess greenhouse gas (GHG) emissions during training and inference phases.

Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design.

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from the variation of building units─metal centers and organic linkers─in almost infinite chemical space. Such variation substantially complicates the experimental design and promotes the use of computational methods.

Thermodynamic Properties and DFT Study on Highly Frustrated CrBO: Coexistence of Spin-Singlets with Long-Range Magnetic Order.

The triangle-based magnetic subsystem of borates with the mineral norbergite structure MBO (M = Fe, Cr, V) makes these compounds unique to investigate rare quantum ground states influenced by strong magnetic frustration. In this work, we investigated the thermal and magnetic properties of CrBO to find that despite very large negative Weiss temperature Θ = -160.7 K, it orders only at = 4.

Accurate, interpretable predictions of materials properties within transformer language models.

Property prediction accuracy has long been a key parameter of machine learning in materials informatics. Accordingly, advanced models showing state-of-the-art performance turn into highly parameterized black boxes missing interpretability. Here, we present an elegant way to make their reasoning transparent.

The Role of Chromatin Assembly Factors in Induced Mutagenesis at Low Levels of DNA Damage.

The problem of low-dose irradiation has been discussed in the scientific literature for several decades, but it is impossible to come to a generally accepted conclusion about the presence of any specific features of low-dose irradiation in contrast to acute irradiation. We were interested in the effect of low doses of UV radiation on the physiological processes, including repair processes in cells of the yeast , in contrast to high doses of radiation. Cells utilize excision repair and DNA damage tolerance pathways without significant delay of the cell cycle to address low levels of DNA damage (such as spontaneous base lesions).

MR-guided non-invasive typing of brain gliomas using machine learning.

Unlabelled: Gliomas are the most common neuroepithelial brain tumors. The modern classification of tumors of central nervous system and treatment approaches are based on tissue and molecular features of a particular neoplasm. Today, histological and molecular genetic typing of tumors can only be carried out through invasive procedures.

A universal similarity based approach for predictive uncertainty quantification in materials science.

Immense effort has been exerted in the materials informatics community towards enhancing the accuracy of machine learning (ML) models; however, the uncertainty quantification (UQ) of state-of-the-art algorithms also demands further development. Most prominent UQ methods are model-specific or are related to the ensembles of models; therefore, there is a need to develop a universal technique that can be readily applied to a single model from a diverse set of ML algorithms. In this study, we suggest a new UQ measure known as the Δ-metric to address this issue.

Noninvasive Glioma Grading with Deep Learning: A Pilot Study.

Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue types and prognosis. They could be graded with four levels according to the 2007 WHO classification. The emergence of non-invasive histological and molecular diagnostics for nervous system neoplasms can revolutionize the efficacy and safety of medical care and radically reduce healthcare costs.

Parametrization of Nonbonded Force Field Terms for Metal-Organic Frameworks Using Machine Learning Approach.

The enormous structural and chemical diversity of metal-organic frameworks (MOFs) forces researchers to actively use simulation techniques as often as experiments. MOFs are widely known for their outstanding adsorption properties, so a precise description of the host-guest interactions is essential for high-throughput screening aimed at ranking the most promising candidates. However, highly accurate ab initio calculations cannot be routinely applied to model thousands of structures due to the demanding computational costs.

A search for a DFT functional for actinide compounds.

Actinide chemistry often lies beyond the applicability domain of the majority of modern theoretical tools due to high computational costs, relativistic effects, or just the absence of actinide data for semiempirical method fitting. On the other hand, radioactivity pushes the usage of computational methods instead of experimental ones. Here, we would like to present a novel relPBE functional as an actinide-fitted version of the PBE0 functional.

Size Doesn't Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules.

The use of machine learning in chemistry has become a common practice. At the same time, despite the success of modern machine learning methods, the lack of data limits their use. Using a transfer learning methodology can help solve this problem.

Visualization of the Anisotropy of the Velocity Dispersion and Characteristics of the Multi-Velocity Continuum in the Regions of Multi-Stream Flows of Gas-Dust Media with Polydisperse Dust.

Collisionless media devoid of intrinsic stresses, for example, a dispersed phase in a multiphase medium, have a much wider variety of space-time structures and features formed in them than collisional media, for example, a carrier, gas, or liquid phase. This is a consequence of the fact that evolution in such media occurs in phase space, i.e.

Genetic Analysis of the Hsm3 Protein Function in Yeast NuB4 Complex.

In the nuclear compartment of yeast, NuB4 core complex consists of three proteins, Hat1, Hat2, and Hif1, and interacts with a number of other factors. In particular, it was shown that NuB4 complex physically interacts with Hsm3p. Early we demonstrated that the gene participates in the control of replicative and reparative spontaneous mutagenesis, and that mutants increase the frequency of mutations induced by different mutagens.

Polarization Dependent Excitation and High Harmonic Generation from Intense Mid-IR Laser Pulses in ZnO.

The generation of high order harmonics from femtosecond mid-IR laser pulses in ZnO has shown great potential to reveal new insight into the ultrafast electron dynamics on a few femtosecond timescale. In this work we report on the experimental investigation of photoluminescence and high-order harmonic generation (HHG) in a ZnO single crystal and polycrystalline thin film irradiated with intense femtosecond mid-IR laser pulses. The ellipticity dependence of the HHG process is experimentally studied up to the 17th harmonic order for various driving laser wavelengths in the spectral range 3-4 µm.

Participation of the HIM1 gene of yeast Saccharomyces cerevisiae in the error-free branch of post-replicative repair and role Polη in him1-dependent mutagenesis.

In eukaryotes, DNA damage tolerance (DDT) is determined by two repair pathways, homologous repair recombination (HRR) and a pathway controlled by the RAD6-epistatic group of genes. Monoubiquitylation of PCNA mediates an error-prone pathway, whereas polyubiquitylation stimulates an error-free pathway. The error-free pathway involves components of recombination repair; however, the factors that act in this pathway remain largely unknown.

Simple Automatized Tool for Exchange-Correlation Functional Fitting.

Density functional theory is, perhaps, the most popular and convenient tool in computational chemistry. DFT methods allow solving different chemical tasks with a good balance of accuracy and computational time. Dozens of existing functionals cover a majority of possible systems, and the development of new ones is still ongoing.

Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability.

Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chemical structure representation. The classical approach of rigorous feature engineering in ML typically improves the performance of the predictive model, but at the same time, it narrows down the scope of applicability and decreases the physical interpretability of predicted results. In this study, we present graph convolutional neural networks (GCNNs) as an architecture that allows for successfully predicting the properties of compounds from diverse domains of chemical space, using a minimal set of meaningful descriptors.

Aroma Molecules as Dynamic Volatile Surfactants: Functionality beyond the Scent.

Understanding of nonequilibrium processes at dynamic interfaces is indispensable for advancing design and fabrication of solid-state and soft materials. The research presented here unveils specific interfacial behavior of aroma molecules and justifies their usage as multifunctional volatile surfactants. As nonconventional volatile amphiphiles, we study commercially available poorly water-soluble compounds from the classes of synthetic and essential flavor oils.

Three-Component GaHal-Promoted Reactions of Substituted Methylidenemalonates and Donor-Acceptor Cyclopropanes with Propargyl Halides: Cascade Diastereoselective Construction of Five-Membered Lactones.

A new cascade three-component process for high trans,trans-diastereoselective assembly of five-membered (1-halovinyl)lactones has been developed. The process is based on reactions of substituted methylidenemalonates and cyclopropanedicarboxylates with 3-haloprop-1-ynes in the presence of GaHal and involves the intermediate in situ generation of 1,2-zwitterionic gallium complexes with [Ga(L)][GaX] composition. Chloro, bromo, and iodo derivatives can be obtained successfully.

Influence of electro-osmosis on physicochemical parameters and microstructure of clay soils.

The change in properties and structure of clay soils due to electro-osmosis was studied. These alterations were exemplified by mantle loam and kaolin. It is shown that electro-osmotic treatment of the soils on the open scheme resulted in the transformations in their moisture content, total and dry density, salinity, pH, and the parameters of their particles.

Determination of Hyperfine Coupling Constants of Fluorinated Diphenylacetylene Radical Anions by Magnetic Field-Affected Reaction Yield Spectroscopy.

Magnetic field-affected reaction yield (MARY) spectroscopy is a spin chemistry technique for detecting short-lived radical ions. Having sensitivity to transient species with lifetimes as short as nanoseconds, MARY spectroscopy usually does not provide detailed information on their magnetic resonance parameters, except for simple systems with equivalent magnetic nuclei. In this work, the radical anions of two fluorinated diphenylacetylene derivatives with nonequivalent magnetic nuclei and unknown hyperfine coupling constants ( A) were investigated by MARY spectroscopy.