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Relevance. The study aimed to increase the effectiveness of comprehensive diagnosis and treatment of patients with TMD using an intraoral occlusal appliance.Materials and methods. All patients of the main group underwent a digital comprehensive functional examination, including TMJ magnetic resonance imaging, kinesiography, joint vibration analysis, surface myography and electrical stimulation of the masticatory muscles, followed by a bite registration of the optimal mandible position. According to the bite recorder, the models were mounted in the articulator and the intraoral occlusal appliance was fabricated. This occlusal appliance used the first-class lever principle, which acts on the condyle using a force applied to the mesial part of the canine and rests on the distal part of the upper second molar. After the diagnosis and treatment stage using an occlusal appliance, a digital comprehensive functional examinatio n was performed again.Results. Analysis of the digital comprehensive diagnosis data evidenced the restoration of the lower jaw movement, the elimination of intra-articular disorder and the normalization of the dentition functioning as a whole, using TENS appliance and an improved intraoral occlusal appliance (Patent # 273 0995, 26.08.2020) in patients with TMD.Conclusion. Treatment of patients with TMD using an intraoral occlusal appliance, which eliminates condyle compression and dislocation of the articular disc, allows restoring the lower jaw movement and the functioning of the dentition as a whole. Kinesiography at all stages of the prosthodontic treatment allows objectively monitoring the restoration of the mandibular movement pathways, taking into account time inte rvals.

Differential methylation (DM) is actively recruited in different types of fundamental and translational studies. Currently, microarray- and NGS-based approaches for methylation analysis are the most widely used with multiple statistical models designed to extract differential methylation signatures. The benchmarking of DM models is challenging due to the absence of gold standard data. In this study, we analyze an extensive number of publicly available NGS and microarray datasets with divergent and widely utilized statistical models and apply the recently suggested and validated rank-statistic-based approach Hobotnica to evaluate the quality of their results. Overall, microarray-based methods demonstrate more robust and convergent results, while NGS-based models are highly dissimilar. Tests on the simulated NGS data tend to overestimate the quality of the DM methods and therefore are recommended for use with caution. Evaluation of the top 10 DMC and top 100 DMC in addition to the not-subset signature also shows more stable results for microarray data. Summing up, given the observed heterogeneity in NGS methylation data, the evaluation of newly generated methylation signatures is a crucial step in DM analysis. The Hobotnica metric is coordinated with previously developed quality metrics and provides a robust, sensitive, and informative estimation of methods’ performance and DM signatures’ quality in the absence of gold standard data solving a long-existing problem in DM analysis.

The impact of mechanochemical activation and methods of addition of non-hydrolyzing salts of NaCl, NH4Cl, NH4Br и MgCl2∙(either dry powder or solution) on the reaction rate and yield of hydrogen production upon magnesium hydride oxidation by water was investigated. It was established that addition of halides increases the hydrogen yield from 22% to 99% (of theoretical value) while the rate of hydrogen production has increased from ∼220 to 1700 mL/min g (MgH2). The addition of dry salts during the mechanochemical treatment of the hydride always results in much higher reaction rate compared to the use of the same salt solutions. It was observed that activation by NH4Cl and MgCl2 results in bell-shaped change in the hydrogen release rate. Of all evaluated halide salt activators, the greatest overall yield (∼99%) was achieved in the presence of 0.17 M NaCl solution. The reaction rate at these conditions was rather slow; it took up to 4 h to complete the oxidation. The highest rate of oxidation, when 94% of theoretical yield was achieved in 3 min, was observed in the presence of 0.85 M NH4Br.

The investigation proposes the application of an ontological semantic approach to describing workflow control patterns, research workflow step patterns, and the meaning of the workflows in terms of domain knowledge. The approach can provide wide opportunities for semantic refinement, reuse, and composition of workflows. Automatic reasoning allows verifying those compositions and implementations and provides machine-actionable workflow manipulation and problem-solving using workflows. The described approach can take into account the implementation of workflows in different workflow management systems, the organization of workflows collections in data infrastructures and the search for them, the semantic approach to the selection of workflows and resources in the research domain, the creation of research step patterns and their implementation reusing fragments of existing workflows, the possibility of automation of problemsolving based on the reuse of workflows. The application of the approach to CWFR conceptions is proposed.

Analysis of the expression activity of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. The nature of sRNA calls for bioinformatical approaches, adapted for the specific structure of the data. Despite a number of approaches proposed, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This article is dedicated to identifying the optimal pipeline configurations for each step of sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. For categorical factors and two groups of biosamples, we suggest approaches for the most crucial stages of sRNA analysis pipeline such as: (1) trimming with the lower length bound = 15 and the upper length bound = Readlength−40%Adapterlength; (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

Reinforcement learning is a type of machine learning algorithm. These algorithms interact with the model of the environment in which the robotic system is supposed to be used, and make it possible to obtain relatively simple approximations of effective sets of system actions to achieve the set goal. The use of reinforcement learning will allow training the model on server hardware, and in the final system use already trained neural networks, the complexity of calculating the response of which directly depends on their topology. In the presented work, a statistical calculation of a prototype of a robotic manipulator for bench research of reinforcement learning systems has been carried out. The choice of design features and materials has been substantiated; the main units and design features have been considered. The studies were carried out in the SolidWorks Simulation software. A prototype of a robotic manipulator with a sufficiently high safety margin was obtained. It is concluded that the main stress concentrator is the junction of the eyelet and the platform, however, the maximum stress value was 38.804 kgf/sm2, which is insignificant. In this case, the maximum resulting movement will be concentrated in the upper part of the eyelet, and will shift depending on the position of the manipulator arm. The maximum recorded displacement is 0.073 mm, which is negligible

One of the most important ways of improving the speed of complex task solving is employing a multiprocessor computational system. This paper describes the experience of software development for research management and solving educational problems using parallel computing technologies. The authors describe approaches to computation parallelization using a multiprocessor system with shared memory within a task of finding a numerical root of a system of linear equations with a tridiagonal coefficient matrix that appears when solving a boundary problem for a partial differential equation of parabolic type, the heat equation. Additionally, the approaches to parallelization implementation of the tridiagonal matrix method for the heat equation in the two-dimensional case within a numerical root-finding algorithm using the alternating-direction implicit method for a multiprocessor system with shared memory are described. A finite-difference method of variable directions is used to find a numerical root of a heat equation in the two-dimensional case. Sequential and parallel algorithms (two-sided Thomas algorithm and multithread horizontal block Thomas algorithm) that fit an execution on computational systems with shared memory have been used to implement a tridiagonal matrix method. Two parallel computation organization technologies for computational systems with shared memory have been used for computation parallelization: one based on OpenMP technology and one using .NET framework facilities. The parallelization process and load balance serving have been performed by means of the environment in the first case as manual operation of threads parallelization process is allowed in the latter one. As an assessment of the described approach performance, the calculation time for sequential and parallel algorithms is given depending on the task’s size and the number of threads used. Comparison of the considered parallelization algorithms and implementation technologies is performed based on the analysis of the resulting acceleration. This paper shows that total computation time is several times smaller and calculation acceleration is several times bigger when using Thread instead of OpenMP. An application has been developed that allows obtaining a visual result of modelling of process of temperature propagation in the study area using parallel calculation technologies in real time.

In recent years, in the oil production industry there is a tendency of mass use of stationary multiphase metering units for determining oil, water, and associated gas flow rates in the recoverable well production. Automated group metering units, allowing to cover the whole group of wells in rotation metering mode, became widespread. The necessity of equipping wells with individual or group measuring devices is dictated, first of all, by the economic tasks of improving oil recovery factor and production optimization. In these conditions, the task of periodic verification of stationary measuring devices in the field with the help of mobile standards-measuring devices of higher accuracy class becomes urgent. The standard’s mobility and the need to work in the field with fluids of different composition significantly complicates the task of creating such a device. The practicality and economy of the created units first of all depends on a choice of a measuring method determining the design of the unit. This article analyzes the existing types of equipment for measuring oil, gas, and water consumption at the oil production wells. Showing the main advantages and disadvantages of each of them, this paper proves the necessity of using complex solutions based on different physical principles to improve the accuracy of measurements. The authors have proposed a combined scheme of a mobile standard of the 2nd category with a dynamic method for measuring the phase rates at the core. The unit performs a multi-stage partial separation of the input multiphase flow into liquid and gas phases and determines the fractions of water and oil in the liquid stream using a hydrostatic-type mixture composition analyzer. In addition, this article indicates the ways of increasing the accuracy of the measuring installation.

Учет межзвездного поглощения - необходимый этап в процессе параметризации звезд по многоцветной фотометрии. Мы анализируем опубликованные законы межзвездного поглощения и обсуждаем возможность оценки величины межзвездного поглощения для фотометрических полос современных больших обзоров. Taking into account interstellar extinction is the necessary procedure in the process of parameterization of stars from multicolor photometry. We analyze published interstellar extinction laws and discuss the possibility of assessing the interstellar extinction in photometric bands of modern large surveys.

Currently, most large enterprises are actively using industrial robots and other automated solutions. This allows a significant increase in productivity and quality of work performed. This article gave a brief overview of modern industrial robots, their operating principle, basic components and systems. A reinforcement learning algorithm was developed and tested. The task of constructing a learning algorithm with reinforcement was divided into two stages: modeling the environment and description and optimization of the cost function. Since industrial robotic systems operate in the real world, the environment model should reflect basic physical laws. Therefore, the pyBullet library of the physical environment was chosen as the physical environment for testing. After modeling the manipulator in the selected physical medium, it was given the trivial task of touching a given object with the capture of the manipulator. An artificial neural network was used as an agent interacting with the environment. The inputs were the coordinates of the object and the existing angles of rotation of the articulated joints of the robot. Outputs - angle of rotation of joints at this step. This network was trained using the back propagation method, Adam modification. The system was trained for about 12 hours. Success is achieved in 95% of cases when testing the stability of the system (random position of the cylinder). In future, it is planned to test the obtained models on bench samples

New non-crystallizable low-dispersity star-shaped polydimethylsiloxanes (PDMS) containing stereoregular cis-tetra(organo)(dimethylsiloxy)cyclotetrasiloxanes containing methyl-, tolyl- and phenyl-substituents at silicon atoms and the mixture of four stereoisomers of tetra[phenyl(dimethylsiloxy)]cyclotetrasiloxane as the cores were synthesized. Their thermal and viscous properties were studied. All synthesized compounds were characterized by a complex of physicochemical analysis methods: nuclear magnetic resonance (NMR), FT-IR spectroscopy, gel permeation chromatography (GPC), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), viscometry in solution, rheometry, and Langmuir trough study.

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = \(Read\ length - 40\% Adapter\ length\); (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system still lacking a cure. Treatment typically focuses on slowing the progression and managing MS symptoms. Single-cell transcriptomics allows the investigation of the immune system—the key player in MS onset and development—in great detail increasing our understanding of MS mechanisms and stimulating the discovery of the targets for potential therapies. Still, de novo drug development takes decades; however, this can be reduced by drug repositioning. A promising approach is to select potential drugs based on activated or inhibited genes and pathways. In this study, we explored the public single-cell RNA data from an experiment with six patients on single-cell RNA peripheral blood mononuclear cells (PBMC) and cerebrospinal fluid cells (CSF) of patients with MS and idiopathic intracranial hypertension. We demonstrate that AIM2 inflammasome, SMAD2/3 signaling, and complement activation pathways are activated in MS in different CSF and PBMC immune cells. Using genes from top-activated pathways, we detected several promising small molecules to reverse MS immune cells’ transcriptomic signatures, including AG14361, FGIN-1-27, CA-074, ARP 101, Flunisolide, and JAK3 Inhibitor VI. Among these molecules, we also detected an FDA-approved MS drug Mitoxantrone, supporting the reliability of our approach.

Subject. The state of the stomatognathic system in patients who used removable implant-retained overdentures for a period more than 4 years was analyzed by evaluating the bioelectrical activity of temporal and masticatory muscles. Objectives ― to analyze the influence of long-term usage of removable implant-retained overdentures on the dynamic parameters of the stomatognathic system by evaluating the bioelectrical activity of temporal and masticatory muscles. Methods. Clinical studies of bioelectrical activity and symmetry of the temporal and masticatory muscles using surface electromyography were carried out. Electromyography was carried out in five probes: physiological rest, occlusion, natural swallowing, clench and clench on rolls. Results. It was revealed that in a state of physiological rest and occlusion, the absolute electromyography indicators were elevated. During natural swallowing, the bioelectric activity of the muscles in patients who used removable implant-retained overdentures was characterized as reduced. During clenching and clenching on rolls, the indicators were at the level of the lower limit of the norm. It was also found that the symmetry of the temporal and masticatory muscles was below the normal level. Conclusions. The obtained data is a sign of the modified dynamic state of the stomatognathic system in patients who used removable implant-retained overdentures. In addition to changes of the bioelectric activity of the muscles, a significant violation of the symmetry of the muscles has been revealed.

Longitudinal next-generation sequencing of cancer patient samples has enhanced our understanding of the evolution and progression of various cancers. As a result, and due to our increasing knowledge of heterogeneity, such sampling is becoming increasingly common in research and clinical trial sample collections. Traditionally, the evolutionary analysis of these cohorts involves the use of an aligner followed by subsequent stringent downstream analyses. However, this can lead to large levels of information loss due to the vast mutational landscape that characterizes tumor samples. Here, we propose an alignment-free approach for sequence comparison—a well-established approach in a range of biological applications including typical phylogenetic classification. Such methods could be used to compare information collated in raw sequence files to allow an unsupervised assessment of the evolutionary trajectory of patient genomic profiles. In order to highlight this utility in cancer research we have applied our alignment-free approach using a previously established metric, Jensen–Shannon divergence, and a metric novel to this area, Hellinger distance, to two longitudinal cancer patient cohorts in glioma and clear cell renal cell carcinoma using our software, NUQA. We hypothesize that this approach has the potential to reveal novel information about the heterogeneity and evolutionary trajectory of spatiotemporal tumor samples, potentially revealing early events in tumorigenesis and the origins of metastases and recurrences. Key words: alignment-free, Hellinger distance, exome-seq, evolution, phylogenetics, longitudinal.

Long noncoding RNAs (lncRNAs) have emerged as key coordinators of biological and cellular processes. Characterizing lncRNA expression across cells and tissues is key to understanding their role in determining phenotypes, including human diseases. We present here FC-R2, a comprehensive expression atlas across a broadly defined human transcriptome, inclusive of over 109,000 coding and noncoding genes, as described in the FANTOM CAGE-Associated Transcriptome (FANTOM-CAT) study. This atlas greatly extends the gene annotation used in the originalrecount2resource. We demonstrate the utility of the FC-R2 atlas by reproducing key findings from published large studies and by generating new results across normal and diseased human samples. In particular, we (a) identify tissue-specific transcription profiles for distinct classes of coding and noncoding genes, (b) perform differential expression analysis across thirteen cancer types, identifying novel noncoding genes potentially involved in tumor pathogenesis and progression, and (c) confirm the prognostic value for several enhancer lncRNAs expression in cancer. Our resource is instrumental for the systematic molecular characterization of lncRNA by the FANTOM6 Consortium. In conclusion, comprised of over 70,000 samples, the FC-R2 atlas will empower other researchers to investigate functions and biological roles of both known coding genes and novel lncRNAs.