Software Suite Research Articles

Rational Design of Non-Covalent Imprinted Polymers Based on the Combination of Molecular Dynamics Simulation and Quantum Mechanics Calculations.

Molecular imprinting is a promising approach for developing polymeric materials as artificial receptors. However, only a few types of molecularly imprinted polymers (MIPs) are commercially available, and most research on MIPS is still in the experimental phase. The significant limitation has been a challenge for screening imprinting systems, particularly for weak functional target molecules. Herein, a combined method of quantum mechanics (QM) computations and molecular dynamics (MD) simulations was employed to screen an appropriate 2,4-dichlorophenoxyacetic acid (2,4-D) imprinting system. QM calculations were performed using the Gaussian 09 software. MD simulations were conducted using the Gromacs2018.8 software suite. The QM computation results were consistent with those of the MD simulations. In the MD simulations, a realistic model of the 'actual' pre-polymerisation mixture was obtained by introducing numerous components in the simulations to thoroughly investigate all non-covalent interactions during imprinting. This study systematically examined MIP systems using computer simulations and established a theoretical prediction model for the affinity and selectivity of MIPs. The combined method of QM computations and MD simulations provides a robust foundation for the rational design of MIPs.

Identification of Novel PBP2B Protein Inhibitors against Streptococcus pneumoniae in Marine Natural Products using an In-Silico Approach

Background: The aim of this research is to identify marine natural compounds derived from green, red, and brown algae that might possibly inhibit the Penicillin-Binding Proteins (PBPs) protein, which is responsible for the development of antibiotic resistance in Streptococcus pneumoniae (mutated resistant 5204-PBP2B strain). We obtained this by using virtual screening and molecular docking. In AutoDock Vina and the Schrodinger suite software, we screened a library of marine natural chemicals and discovered four intriguing candidates that had strong binding affinities to the active region of the PBPs protein. Based on our findings, four naturally occurring marine chemicals show great promise as new inhibitors of S. pneumoniae 5204-PBP2B protein. These discoveries reveal important new information on the potential application of marine natural products as a source of new drugs to combat antibiotic resistance in Streptococcus pneumoniae and other bacterial infections. Methods: The 3318 compounds in the Comprehensive Marine Natural Products Database (CMNPD) derived from green algae (293 compounds), brown algae (1212 compounds) and red algae (1813 compounds) were taken into consideration for this study. Through virtual screening and molecular docking investigations, we found the optimum compounds for the Penicillin-Binding Proteins (PBPs) protein in Streptococcus pneumoniae. Utilizing AutoDock Vina and Schrodinger Suite software, the 5204-PBP2B protein selected for this investigation was examined. The structure and binding interaction have been displayed using PyMOL software. Results: Through virtual screening and molecular docking investigations for the 5204-PBP2B protein in Streptococcus pneumoniae, we were able to identify four marine natural products that are present in brown algae from the Comprehensive Marine Natural Products Database. Conclusion: The study has indicated that the main cause of bacterial resistance to antibiotics is 5204-PBP2B in S. pneumoniae. This study's methodology has been shown to be effective in identifying four strong inhibitors of the CMNPD. In this work, potent molecules from CMNPD compounds were screened using the 3D structure of mutated resistant 5204 strain, named 5204- PBP2B (PDB ID: 2WAE) of S. pneumoniae. Out of 3318 compounds that showed strong interactions with PBP2B, docking studies revealed that four of the compounds were inhibitory for the protein and could be used to treat PBP2B. These four marine products were selected as a result of our earlier research on Klebsiella pneumonia’s New Delhi metallo-β-lactamase-1 (NDM-1) protein. This study thus reveals the importance of marine natural products for improving the drug development process, as well as the ability of four marine products generated from brown algae to inhibit both the NDM-1 protein of Klebsiella pneumoniae and the 5204-PBP2B protein in Streptococcus pneumoniae. It is also possible to expand this approach by investigating how different receptor inhibitors interact in a lab setting. Potential inhibitors can be discovered by evaluating the biological activity of the drugs and applying virtual screening and molecular docking techniques.

A 1 × 8 Optical Splitter Based on Polycarbonate Multicore Polymer Optical Fibers.

Visible light communication (VLC) is becoming more relevant due to the accelerated advancement of optical fibers. Polymer optical fiber (POF) technology appears to be a solution to the growing demand for improved transmission efficiency and high-speed data rates in the visible light range. However, the VLC system requires efficient splitters with low power losses to expand the optical energy capability and boost system performance. To solve this issue, we propose an effective 1 × 8 optical splitter based on multicore polycarbonate (PC) POF technology suitable for functioning in the green-light spectrum at a 530 nm wavelength. The new design is based on replacing 23 air-hole layers with PC layers over the fiber length, while each PC layer length is suitable for the light coupling of the operating wavelength, which allows us to set the right size of each PC layer between the closer PC cores. To achieve the best result, the key geometrical parameters were optimized through RSoft Photonics CAD suite software that utilized the beam propagation method (BPM) and analysis using MATLAB script codes for finding the tolerance ranges that can support device fabrication. The results show that after a light propagation of 2 mm, an equally green light at a 530 nm wavelength is divided into eight channels with very low power losses of 0.18 dB. Additionally, the splitter demonstrates a large bandwidth of 25 nm and stability with a tolerance range of ±8 nm around the operated wavelength, ensuring robust performance even under laser drift conditions. Furthermore, the splitter can function with 80% and above of the input signal power around the operated wavelength, indicating high efficiency. Therefore, the proposed device has a great potential to boost sensing detection applications, such as Raman spectroscopic and bioengineering applications, using the green light.

Software for Bioprinting.

The bioprinting of heterogeneous organs is a crucial issue. To reach the complexity of such organs, there is a need for highly specialized software that will meet all requirements such as accuracy, complexity, and others. The primary objective of this review is to consider various software tools that are used in bioprinting and to reveal their capabilities. The sub-objective was to consider different approaches for the model creation using these software tools. Related articles on this topic were analyzed. Software tools are classified based on control tools, general computer-aided design (CAD) tools, tools to convert medical data to CAD formats, and a few highly specialized research-project tools. Different geometry representations are considered, and their advantages and disadvantages are considered applicable to heterogeneous volume modeling and bioprinting. The primary factor for the analysis is suitability of the software for heterogeneous volume modeling and bioprinting or multimaterial three-dimensional printing due to the commonality of these technologies. A shortage of specialized suitable software tools is revealed. There is a need to develop a new application area such as computer science for bioprinting which can contribute significantly in future research work.

Design of Radial Flux PM Synchronous Motor for EV Applications

Abstract: High-performance electric propulsion systems are becoming increasingly important as the automotive industry rapidly shifts to electric cars (EVs). The electric motor is an essential part of these systems as it determines the power, efficiency, and overall performance of the vehicle.This project uses Altair Flux, a full-featured finite element analysis (FEA) software suite, to build and optimize a radial flux motor (RFM) with permanent magnet synchronous motor (pmsm) . The main goal is to increase the power density and efficiency of the electric propulsion system for electric cars by utilizing Altair Flux's simulation and analytical capabilities.

MuscleX: data analysis software for fiber diffraction patterns from muscle.

MuscleX is an integrated, open-source computer software suite for data reduction of X-ray fiber diffraction patterns from striated muscle and other fibrous systems. It is written in Python and runs on Linux, Microsoft Windows or macOS. Most modules can be run either from a graphical user interface or in a `headless mode' from the command line, suitable for incorporation into beamline control systems. Here, we provide an overview of the general structure of the MuscleX software package and describe the specific features of the individual modules as well as examples of applications.

Novel approach for forest road maintenance using smartphone sensor data and deep learning methods

ABSTRACT High costs primarily pose challenges to forest management in planning and executing the repair of forest roads. With budget limitations and inadequate oversight, it has become critically essential to monitor the state of these roads. Monitoring the condition of forest roads has become imperative, driven by budget constraints and a lack of effective supervision. While smartphones have proven effective in detecting road defects on public roads, their application on forest roads is hindered by the absence of suitable indices and software infrastructure. Addressing this gap, this research focuses on the development of the Forest Road Pavement Condition Index (FRPCI) to facilitate smartphone-based monitoring. We collected and compared data from 4 kilometers of forest roads, employing two traditional harvesting methods alongside smartphone sensor data. Utilizing deep learning methods, including Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and CNN-LSTM, we processed the collected data. Signal processing using GPS data, coupled with wavelet transformation, demonstrated promising results with an accuracy and recall exceeding 80%. The proposed system functions as a distributed information system, transitioning data from organizational mode to field mode. It measures damage, assesses forest road conditions, and leverages image processing and GPS technologies. This monitoring system technology offers capabilities for preparing, storing, updating, maintaining, and analyzing diverse information. Importantly, adopting this method can significantly reduce operating costs, making forest road monitoring for maintenance purposes more feasible.

Tooth Anatomy Inspector: A comprehensive assessment of an extended reality (XR) application designed for teaching and learning of root canal anatomy by students.

To develop and evaluate a suitable software application for mobile devices designed for teaching root canal anatomy to undergraduate students in an informative and engaging manner. Extracted human teeth were scanned by μCT and digitized by converting into STL files. An extended reality (XR) application illustrating the root canal anatomy of the scanned teeth was developed. Prior to deployment, undergraduate dental students were voluntarily asked about their expectations regarding an educational application on tooth anatomy. After a testing phase of the application on a mobile device and within a virtual reality environment, a subsequent evaluation was conducted to assess their overall experience in relation to their initial expectations. Data were analysed using Kolmogorov-Smirnov test and Mann-Whitney U test. The level of significance was set to .05 (p = .05). The application was able to meet the expectations of the students in all categories (p < .466-.731). Furthermore, it was evaluated as user-friendly (98.2%) and highly motivating for the purpose of learning more on root canal anatomy (100%). Given the overwhelmingly positive reception from undergraduate dental students, the application emerges to be a promising supplementary teaching method for the endodontic curriculum.

Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.

Mortality is an economically important trait usually handled as a discrete outcome from hatch time until selection in most broiler breeder programs. However, in other species, it has been shown that not only does the genetic component change over time, but also there are maternal genetic effects to be considered when mortality is recorded early in life. This study aimed to investigate alternative trait definitions of mortality with varying models and effects. Three years' worth of data were provided by Cobb-Vantress, Inc. and included 2 mortality traits. The first trait was binary, whether the bird died or not (OM), and the second trait was a categorical weekly mortality trait. After data cleaning, 6wk of data for the 2 given mortality traits were used to develop 5 additional trait definitions. The definitions were broiler mortality (BM), early and late mortality (EM & LM), and 2 traits with repeated records as cumulative or binary (CM and RM, respectively). Variance components were estimated using linear and threshold models to investigate whether either model had a benefit. Genomic breeding values were predicted using the BLUP90 software suite, and linear regression validation (LR) was used to compare trait definitions and models. Heritability estimates ranged from 0.01 (0.00) to 0.16 (0.01) under linear and 0.04 (0.01) to 0.21 (0.01) under threshold models, indicating genetic variability within the population across these trait definitions. The genetic correlation between EM and LM ranged from 0.48 to 0.81 across the different lines, indicating they have divergent genetic backgrounds and should be considered different traits. The LR accuracies showed that EM and LM used together in a 2-trait model have comparable accuracies to that of OM while giving a more precise picture of mortality. When including the maternal effect, the direct heritability considerably decreased for EM, indicating that the maternal effect plays an important role in early mortality. Therefore, a suitable approach would be a model with EM and LM while considering the maternal effect for EM. Single nucleotide polymorphism effects were estimated, and no individual SNP explained more than 1% of the additive genetic variance. Additionally, the SNP with the largest effect size and variance were inconsistent across trait definitions. Chicken mortality can be defined in different ways, and reviewing these definitions and models may benefit poultry breeding programs.

Analytical Description of the Electric Field inside a High Voltage Glass Insulator

Research presented in this paper analyzes the accuracy and applicability of analytical expressions to describe the electric field of a high-voltage glass insulator. The metal cap and the metal pin of the glass insulator are represented by coaxial cylindrical electrodes. The insulating materials between them are modeled as coaxial hollow cylinders. Analytical expressions for the electric field in these insulating materials are derived. Using these expressions, the spatial distribution of the electric field in the insulating materials was determined. Suitable software, based on the finite element method (FEM), was used to determine the spatial distribution of the electric field in dielectrics in the same space. Both analyses were performed under quasi-static conditions, and the results of the analytical expressions were compared with the FEM results. Discrepancies between the results of the two mentioned analyses were observed. The reasons for the observed discrepancies and the applicability of the presented analytical expressions are commented on.

On the detection of population heterogeneity in causation between two variables: Finite mixture modeling of data collected from twin pairs.

Causal inference is inherently complex, often dependent on key assumptions that are sometimes overlooked. One such assumption is the potential for unidirectional or bidirectional causality, while another is population homogeneity, which suggests that the causal direction between two variables remains consistent across the study sample. Discerning these processes requires meticulous data collection through an appropriate research design and the use of suitable software to define and fit alternative models. In psychiatry, the co-occurrence of different disorders is common and can stem from various origins. A patient diagnosed with two disorders might have one recognized as primary and the other as secondary, suggesting the existence of two types of comorbidity within the population. For example, in some individuals, depression might lead to substance use, while in others, substance use could lead to depression. Identifying the primary disorder is crucial for developing effective treatment plans. This article explores the use of finite mixture models to depict within-sample heterogeneity. We begin with the Direction of Causation (DoC) model for twin data and extend it to a mixture distribution model. This extension allows for the calculation of the likelihood of each individual's data for the two alternate causal directions. Given twin data, there are four possible pairwise combinations of causal direction. Through simulations, we investigate the Direction of Causation Twin Mixture (mixCLPM) model's potential to detect and model heterogeneity due to varying causal directions.

Формирование цифровой модели угольного месторождения в горно-геологической информационной системе МАЙНФРЭЙМ

Digitalization of enterprise management using Russian software is the main trend in the development of the country's mining sector. Sharp fluctuations in demand and prices in the mineral markets, as well as the development of technical tools for mechanization and automation of technological processes along with a systematic increase in their cost affect the financial performance of mining companies. This determines the need for a rapid adoption of technical, technological and organizational decisions, which, along with the requirements of the company's owners and regulators to obtain prompt, reliable and the most complete information about the production process explains the urgent need for the prompt introduction of digital control systems for mining operations. In the article the authors describe an algorithm to design a digital model of the mining and geological system, including a digital geological model of the deposit, digital models of mine workings and the surface topography, based on the experience of creating three-dimensional digital models of complex-structured coal deposits. The basic software suite for designing a digital management system for mining operations is the MINEFRAME mining and geological information system developed at the Mining Institute of the Kola Scientific Center of the Russian Academy of Sciences. MINEFRAME allows to perform a full range of tasks aimed at creation of a digital 3D model of the mining and geological system for a coal deposit with the possibility to account for the complex bedding in the modelling. High accuracy and correctness of the input geological sampling data is achieved by means of tools to check for errors in the tables of borehole collar coordinates, inclinometry and sampling. The wireframe modelling methods implemented in MINEFRAME provide the possibility to create wireframe models of seams with high detail in the fracture zones.

Fulvenallenyl Radical (C7H5·)-Mediated Gas-Phase Synthesis of Bicyclic Aromatic C10H8 Isomers: Can Fulvenallenyl Efficiently React with Closed-Shell Hydrocarbons?

To understand the reactivity of resonantly stabilized radicals, often found in relevant concentrations in gaseous environments, it is important to determine their main reaction pathways. Here, it is investigated whether the fulvenallenyl radical (C7H5·) reacts preferentially with closed-shell molecules or radicals. Electronic structure calculations on the C10H9 potential energy surface accessed by the reactions of C7H5· with methylacetylene (CH3CCH) and allene (H2CCCH2) were combined with RRKM-ME calculations of temperature- and pressure-dependent rate constants using the automated EStokTP software suite and kinetic modeling to assess the reactivity of C7H5· with closed-shell unsaturated hydrocarbons. Experimentally, the reactions were attempted in a chemical microreactor heated to 998 ± 10 K by preparing fulvenallenyl radicals via pyrolysis of trichloromethylbenzene (C7H5Cl3) and seeding the radicals in methylacetylene or allene carrier gas, with product identification by means of photoionization mass spectrometry. The measured photoionization efficiency curve of m/z = 128 was assigned to a linear combination of the reference curves of two C10H8 isomers, azulene (minor) and naphthalene (major), presumably resulting from the C7H5· plus C3H4 reactions. However, the calculations demonstrated that these reactions are too slow, and kinetic modeling of processes in the reactor allowed us to conclude that the observation of naphthalene and azulene is due to the C7H5· plus C3H3· reaction, where propargyl is produced by direct hydrogen atom abstraction by chlorine (Cl) atoms from allene or methylacetylene and Cl stem from the pyrolysis of C7H5Cl3. Modeling results under the copyrolysis conditions of toluene and methylacetylene in high-temperature shock tube experiments confirmed the prevalence of the fulvenallenyl reaction with propargyl over its reactions with C3H4 even when the concentrations of allene and methylacetylene largely exceed that of propargyl. Overall, the reactions of fulvenallenyl with both allene and methylacetylene were found to be noncompetitive in the formation of naphthalene and azulene thus attesting the inefficiency of the fulvenallenyl radical reactions with the prototype closed-shell hydrocarbon species. In the meantime, the new reaction pathways revealed, including H-assisted isomerizations between C10H8 isomers and decomposition reactions of various C10H9 isomers, emerge as relevant and are recommended for inclusion in combustion kinetic models for naphthalene formation.

P-322 Development of a CD138-based histopathological scoring system to diagnose chronic endometritis

Abstract Study question Does a standardized histopathological classification system lead to a robust interobserver agreement to diagnose chronic endometritis (CE) and can an accurate computation algorithm be developed? Summary answer The proposed scoring system has a particularly good to excellent interobserver agreement among pathologists. A machine-learning algorithm outperformed pathologists in the clinically most relevant 2-tier-system. What is known already Plasma cell (PC) presence in the stromal endometrium has been proposed as a marker for CE, yet no standardized classification system that considers the amount or distribution of PCs exists. Also, interobserver agreement has been insufficiently reported in the previous publications on the topic. Without a robust histopathological score, the potential clinical impact of CE on ART treatment outcomes cannot be investigated. This issue is strongly reflected in the heterogeneity of the current diagnostic and therapeutic approaches, specifically for patients experiencing repeated implantation failure (RIF) or recurrent pregnancy loss (RPL). Study design, size, duration A 5-tier classification system based on CD138-positive PCs (Roche B-A38/automated Ventana system) was established: class0 (no PCs), classIPC (isolated PCs), class1 (³1 cluster of 5-19 PCs/0.25mm2), class2 (³1 cluster of 20-49 PCs/0.25mm2), class3 (³1 cluster of 50 or more PCs/0.25mm2). A test set of 78 endometrial biopsies (collected over two years) was selected by a certified pathologist who sorted &amp;gt;1000 biopsies to ensure the full spectrum of PC counts/distribution was accounted for. Participants/materials, setting, methods The 3DHistech-platform digitized the slides (pixel size 0.2738x0.2738mm) and a scoring session was set up in the Pathomation software suite. Six pathologists scored independently after training. Overall agreement was expressed by Fleiss’ Kappa values. Pairwise interobserver agreement was calculated using Cohen’s Kappa statistics. A supervised machine-learning algorithm was developed in QuPath(V0.4.2) and considered a seventh observer in the interobserver agreement calculations. Main results and the role of chance The CD138-based semiquantitative scoring system showed particularly good to excellent interobserver agreement among all observers. Overall agreement values were 0.722 for the 5-tier system and 0.858 for the 2-tier system (0+IPC versus 1 + 2+3, which was considered the clinically most relevant classification, i.e. CE absent versus diagnosed). Pairwise interobserver agreement was 0.871-0.951. Intra-class correlations varied from 0.727 to 0.839 in the 5-tier system and 0.893 to 0.965 in the 2-tier system. All findings were statistically significant (p &amp;lt; 0.001). The supervised machine-learning algorithm was able to compete with human pathologist observers and outperformed them in the 2-tier system. The proposed classification system provides a framework for assessing the presence and severity of endometrial PC infiltration and can guide further research. Limitations, reasons for caution Inconsistent staining intensity, non-specific epithelial staining and background interference are common problems that might limit interlaboratory use of the algorithm. Furthermore, the algorithm has not yet been associated to patient/clinical parameters. Accurate analysis of an endometrial biopsy might still be insufficient to provide a formal diagnosis of CE. Wider implications of the findings To unravel the association between PCs in endometrial biopsies (as a proxy for the diagnosis of CE) and the reproductive outcomes following ART, a standardized methodology is of crucial importance for future studies. Higher accuracy, efficieny and automation are advantages when using computer-aided diagnostics for CE. Trial registration number BUN 143202042810

Hybrid Control System for a Vertically Guided Bomb During Self-guidance in Turbulent Conditions

The article presents a mathematical model and an algorithm for hybrid control of a bomb aimed at a moving ground target. The guided bomb flight control system subject to the study combines a conventional PD controller and a quasi-sliding mode (QSM) controller. The target trajectory was determined based on the kinematic relations of the mutual motion of the bomb and the ground target using the proportional approach method. The main aim of the article is to analyse the impact of atmospheric turbulence on the flight of a guided bomb, and then to determine its impact on homing parameters, such as homing time and accuracy of hitting a ground target. The numerical studies covered three types of controllers: conventional PID, quasi-sliding and hybrid. The effectiveness of the proposed control system was analysed without and during random atmospheric turbulence. The article examines the hybrid system’s properties for controlling guided bombs. Numerical studies were performed using the Matlab/Simulink software suite. The article presents selected results of this computer simulation.

The Influence of Atmospheric Conditions on a Glider’s Lift Forces

The article presents the methodology and results of a simulation study on the air flow around a glider, focusing on the issue of changing the lift force and drag force in changing atmospheric conditions. The experiment was based on simulations in the SolidWorks Flow Simulation 2022 software suite. The model for simulation research was developed at the Faculty of Technical Sciences of the University of Warmia and Mazury in Olsztyn (Poland).

Experimental and Numerical Determination of the Aerodynamic Characteristics of a Cruise Missile Model

A model of a cruise missile was tested in symmetrical air flow in a low-speed wind tunnel of the Military University of Technology (Warsaw, Poland). A virtual model of the missile was developed, and the geometry of the computational domain was built in the CAD environment of the ANSYS computational software suite. The domain was discretised in the ANSYS Meshing application, creating a hybrid computational mesh. Boundary conditions were determined in the ANSYS Fluent application, and physical (turbulent compressible flow) and numerical models were selected. Calculations were performed for three different turbulence models – Spalart-Almaras, realizable k-ε, and SST k-ω – and the results were compared to find the model providing the best convergence with in-tunnel measurements.

Nitric Oxide/Glucose Transporter Type 4 Pathway Mediates Cardioprotection against Ischemia/Reperfusion Injury under Hyperglycemic and Diabetic Conditions in Rats

Introduction: The comorbidities of ischemic heart disease (IHD) and diabetes mellitus (DM) compromise the protection of the diabetic heart from ischemia/reperfusion (I/R) injury. We hypothesized that manipulation of reperfusion injury salvage kinase (RISK) and survivor activating factor enhancement (SAFE) pathways might protect the diabetic heart, and intervention of these pathways could be a new avenue for potentially protecting the diabetic heart. Methods: All hearts were subjected to 30-min ischemia and 30-min reperfusion. During reperfusion, hearts were exposed to molecules proven to protect the heart from I/R injury. The hemodynamic data were collected using suitable software. The infarct size, troponin T levels, and protein levels in hearts were evaluated. Results: Both cyclosporine-A and nitric oxide donor (SNAP) infusion at reperfusion protected 4-week diabetic hearts from I/R injury. However, 6-week diabetic hearts were protected only by SNAP, but not cyclosporin-A. These treatments significantly (p < 0.05) improved cardiac hemodynamics and decreased infarct size. Conclusions: The administration of SNAP to diabetic hearts protected both 4- and 6-week diabetic hearts; however, cyclosporine-A protected only the 4-week diabetic hearts. The eNOS/GLUT-4 pathway executed the SNAP-mediated cardioprotection.

Circular RNA hsa_circ_0002268 (PHACTR1) Is Specific to Gestational Diabetes Mellitus in a Polish Pregnant Population.

Gestational diabetes mellitus (GDM) is an intolerance of carbohydrate of any degree, which appears for the first time or is diagnosed during pregnancy. The objective of this study is to assess the differences in circular RNA (circRNA) in a Polish pregnant population with and without GDM. A total of 62 pregnant women, 34 with GDM and 28 controls, were enrolled in the study. Total RNAs were extracted from plasma and reverse transcription to complementary DNA (cDNA) was performed. A panel covering 271 amplicons, targeting both linear and circular as well as negative control gene transcripts, was used. Next-generation sequencing was used to evaluate the circRNA quantity. Data analysis was performed using the Coverage Analysis plugin in the Torrent Suite Software (Torrent Suite 5.12.3). A two-step normalization was performed by dividing each transcript read count by the total number of reads generated for the sample, followed by dividing the quantity of each transcript by β-actin gene expression. Both circular and linear forms of RNAs were independently evaluated. A total of 57 transcripts were dysregulated between pregnant women with GDM and controls. Most of the targets (n = 25) were downregulated (cut-off ratio below 0.5), and one target showed a trend toward strong upregulation (ratio 1.45). A total of 39 targets were positively correlated with fasting plasma glucose (FPG), but none of the tested targets were correlated with insulin, CRP or HOMA-IR levels. Among the pregnant women with gestational diabetes, the relative quantity of hsa_circ_0002268 (PHACTR1) was approximately 120% higher than among healthy pregnant women: 0.046 [0.022-0.096] vs. 0.021 [0.007-0.047], respectively, (p = 0.0029). Elevated levels of hsa_circ_0002268 (PHACTR1) might be specific to the Polish population of pregnant women with GDM, making it useful as a potential molecular biomarker in the management of GDM in Poland.

Revisiting calculation of tilt angles for double-tilt sample holders in transmission electron microscopes.

We revisited the formula related to the overall tilt angle of a specimen using a side-entry double-tilt sample holder in a transmission electron microscope. Initially, we examined existing formulas in the literature for calculating the overall tilt angle. Subsequently, a new formula was derived, proven to better account for the actions of the double-tilt holder, thereby providing improved accuracy in the calculation. This newly derived formula has been implemented in the Landyne software suite. Furthermore, we demonstrated the accuracy of the new formula through examples. RESEARCH HIGHLIGHTS: A new formula has been derived to calculate overall tilt angles for side-entry double-tilt holders in TEM.