Software Package Research Articles

Computational biomechanics for a standing human body: Modal analysis and simulation.

We develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues. A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much more faithful modeling method is to model the human body as it is, namely, as a continuum. We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation. The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal vibration modes are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Such a "walking mode" shows the in-phase and out-of-phase movements between the legs and arms on the left and right sides of a human body, implying that this walking motion is spontaneous, likely not requiring any directives from the brain. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LS-DYNA computer codes are also included for possible use by other researchers.

Virtual bracket removal: a comparative assessment of different software packages

BackgroundHigh precision intra-oral scans, coupled with advanced software, enable virtual bracket removal (VBR) from digital models. VBR allows the delivery of retainers and clear aligners promptly following debonding, thus reducing the patients' appointments and minimizing the likelihood of tooth movement. The objective of this study was to compare the enamel surface before bonding and after VBR using three different Computer-aided design (CAD) software and to compare their accuracy.MethodsMaxillary scans of 20 participants starting orthodontic treatment were selected for inclusion in the study, who exhibited mild to moderate crowding and required bonding of brackets on the labial surface of permanent maxillary teeth (from the maxillary left first molar to the maxillary right first molar). Two intra-oral scans were conducted on the same day, before bonding and immediately after bonding using CEREC Omnicam (Sirona Dental Systems, Bensheim, Germany). The virtual removal of the brackets from the post-bonding models was performed using OrthoAnalyzer (3Shape, Copenhagen, Denmark), Meshmixer (Autodesk, San Rafael, Calif, USA), and EasyRx (LLC, Atlanta, GA, USA) software. The models that underwent VBR were superimposed on the pre-bonding models by Medit Link App (Medit, Seoul, South Korea) using surface-based registration. The changes in the enamel surface following VBR using the three software packages were quantified using the Medit Link App.ResultsThere was a significant difference among the 3Shape, Meshmixer, and EasyRx software in tooth surface change following VBR. Specifically, EasyRx exhibited lower levels of accuracy compared to the other two VBR software programs (p<.001, p<.001). A significant difference in enamel surface change was observed between tooth segments across all software groups, in both incisors and molars, with VBR of the molars exhibiting the lowest level of accuracy (3Shape p=.002, Meshmixer p<.001, EasyRx p<.001). Regarding the direction of tooth surface changes following VBR, it was observed that all three groups exhibited a significant increase in the percentage of inadequate bracket removal across all teeth segments.Conclusions3Shape and Meshmixer manual VBR software were found to be more accurate than EasyRx automated software, however, the differences were minimal and clinically insignificant.

In silico-guided discovery and in vitro validation of novel sugar-tethered lysinated carbon nanotubes for targeted drug delivery of doxorubicin

ContextMultiwalled carbon nanotubes (MWCNTs) functionalized with lysine via 1,3-dipolar cycloaddition and conjugated to galactose or mannose are potential nanocarriers that can effectively bind to the lectin receptor in MDA-MB-231 or MCF-7 breast cancer cells. In this work, a method based on molecular dynamics (MD) simulation was used to predict the interaction of these functionalized MWCNTs with doxorubicin and obtain structural evidence that allows a better understanding of the drug loading and release process. The MD simulations showed that while doxorubicin only interacted with pristine MWCNTs through π-π stacking interactions, functionalized MWCNTs were also able to establish hydrogen bonds, suggesting that the functionalized groups improve doxorubicin loading. Moreover, the elevated adsorption levels observed for functionalized nanotubes further support this enhancement in loading efficiency. MD simulations also shed light on the intratumoral pH-specific release of doxorubicin from functionalized MWCNTs, which is induced by protonation of the daunosamine moiety. The simulations show that this change in protonation leads to a lower absorption of doxorubicin to the MWCNTs. The MD studies were then experimentally validated, where functionalized MWCNTs showed improved dispersion in aqueous medium compared to pristine MWCNTs and, in agreement with the computational predictions, increased drug loading capacity. Doxorubicin-loaded functionalized MWCNTs demonstrated specific release of doxorubicin in tumor microenvironment (pH = 5.0) with negligible release in the physiological pH (pH = 7.4). Furthermore, doxorubicin-free MWNCT nanoformulations exhibited insignificant cytotoxicity. The experimental studies yielded nearly identical results to the MD studies, underlining the usefulness of the method. Our functionalized MWCNTs represent promising non-toxic nanoplatforms with enhanced aqueous dispersibility and the potential for conjugation with ligands for targeted delivery of anti-cancer drugs to breast cancer cells.MethodsThe computational model of a pristine carbon nanotube was created with the buildCstruct 1.2 Python script. The lysinated functionalized groups were added with PyMOL and VMD. The carbon nanotubes and doxorubicin molecules were parameterized using the general AMBER force field, and RESP charges were determined using Gaussian 09. Molecular dynamics simulations were carried out with the AMBER 20 software package. Adsorption levels were calculated using the water-shell function of cpptraj. Cytotoxicity was evaluated via a MTT assay using MDA-MB-231 and MCF-7 breast cancer cells. Drug uptake of doxorubicin and doxorubicin-loaded MWCNTs was measured by fluorescence microscopy.

An investigation of stress analysis via finite element methods on compacted snow runways

Compacted snow runways for heavy wheeled aircraft are challenging in polar regions and possible extraterrestrial infrastructure constructions. A finite element method was successfully employed to simulate a wheel landing on layered snow using the ABAQUS software package based on the Phoenix runway in Antarctica. First, the method was validated with theoretical results of several layered systems. Thereafter, basic parameters of snow were chosen with reference to the Phoenix runway's pavement. Stress distributions under landing gear were calculated for the C17, A319, B757 and Il-76 aircraft. Furthermore, the effect of subgrades on stress distributions were discussed. This study explores current knowledge on snow pavements and provides technical support for the design and construction of compacted snow runways.

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

MolSym: A Python package for handling symmetry in molecular quantum chemistry.

A consideration of the point group symmetry of molecules is often advantageous from a computational efficiency standpoint and sometimes necessary for the correct treatment of chemical physics problems. Many modern electronic structure software packages include a treatment of symmetry, but these are sometimes incomplete or unusable outside of that program's environment. Therefore, we have developed the MolSym package for handling molecular symmetry and its associated functionalities to provide a platform for including symmetry in the implementation and development of other methods. Features include point group detection, molecule symmetrization, arbitrary generation of symmetry element sets and character tables, and symmetry adapted linear combinations of real spherical harmonic basis functions, Cartesian displacement coordinates, and internal coordinates. We present some of the advantages of using molecular symmetry as achieved by MolSym, particularly with respect to Hartree-Fock theory, and the reduction of finite difference displacements in gradient/Hessian computations. This package is designed to be easily integrated into other software development efforts and may be extended to further symmetry applications.

Conventional PCR-based versus next-generation sequencing-based approach for T-cell receptor γ gene clonality assessment in mature T-cell lymphomas: A phase 3 diagnostic accuracy study

Background: Clonality assessment is currently the major molecular analysis utilized to support the diagnosis of suspicious lymphoid malignancies. Clonal rearrangements of the V-J segments of T-cell receptor G chain locus (TCRγ or TRG) have been observed in almost all types of T neoplasms, such as T-cell-related non-Hodgkin lymphomas and leukemias. At present, the gold standard for clonality evaluation is multiplex polymerase chain reaction (PCR), plus subsequent capillary electrophoresis/heteroduplex analyses, and/or Sanger sequencing. This approach overcomes the problem with the conventional Southern blot hybridization and is more efficient, simple, fast, and reproducible. In the recent years, the new next-generation sequencing (NGS) technologies provided alternative techniques for the analysis of antigen receptors genes, which presented several advantages, such as increased efficiency, specificity (SP), sensitivity (ST), resolution, and objectivity of the results, leading to a better classification, stratification, and monitoring of lymphoid malignancies. Nonetheless, these technologies are still far from being the new gold standard since further studies are warranted to prove their utility. The present study aimed to assess the diagnostic accuracy of these two methods by comparing a commercial NGS-based assay for the evaluation of TRG locus with the gold standard PCR-based one, to fulfill the requirements of a phase 3 diagnostic accuracy study. Methods: We assessed the TRG gene rearrangements in 72 cases using the conventional and highly-validated PCR-based assay proposed by EuroClonality consortium, an alternative commercial PCR-based assay, namely, IdentiClone® TCR Gamma Gene Rearrangement Assay 2.0, and a commercial NGS-based assay, that is, Invivoscribe LymphoTrack® Dx MiSeq® (both by Invivoscribe Technologies Inc., San Diego, CA, USA), to determine the diagnostic accuracy of the latter, and compare them with reference diagnoses made based on observation of clinical manifestations, cytohistological, and immunohistochemical analyses. Statistical values were calculated using the Oxford CATmaker software package. Results: Using standardized criteria of interpretation, the obtained results showed a diagnostic accuracy of 90.3% (correspondence in 65 out of 72 cases) of the test under investigation, with a ST of 86%, a SP of 95%, a positive predicting value of 94%, and a negative predicting value of 88%, demonstrating that Invivoscribe LymphoTrack® Dx MiSeq® assay had high efficiency and reliability in detecting clonal TRG gene rearrangements in T-cell non-Hodgkin lymphomas. Conclusions: This diagnostic accuracy study yielded comparable results using a validated PCR-based approach and a new NGS-based one. Subsequent studies and cost-effectiveness evaluation are needed to put the NGS-based clonality assessment into routine diagnostic practice.

Examining the ability of big data analytics to investigate financial reporting quality: a comprehensive bibliometric analysis

Purpose This study aims to examine the ability of big data analytics (BDA) to investigate financial reporting quality (FRQ), identify the knowledge base and conceptual structure of this research field and explore BDA techniques used over time. Design/methodology/approach This study uses a comprehensive bibliometric analysis approach (performance analysis and science mapping) using software packages, including Biblioshiny and VOSviewer. Multiple analyses are conducted, including authors, sources, keywords, co-citations, thematic evolution and trend topic analysis. Findings This study reveals that the intellectual structure of using BDA in investigating FRQ encompasses three clusters. These clusters include applying data mining to detect financial reporting fraud (FRF), using machine learning (ML) to examine FRQ and detecting earnings management as a measure of FRQ. Additionally, the results demonstrate that ML and DM algorithms are the most effective techniques for investigating FRQ by providing various prediction and detection models of FRF and EM. Moreover, BDA offers text mining techniques to detect managerial fraud in narrative reports. The findings indicate that artificial intelligence, deep learning and ML are currently trending methods and are expected to continue in the coming years. Originality/value To the best of the authors’ knowledge, this study is the first to provide a comprehensive analysis of the current state of the use of BDA in investigating FRQ.

Программный комплекс для дифференциальной оценки риска здоровью населения от воздействия шума железнодорожного и автомобильного транспорта

Objective: in the modern world, the number of vehicles on the roads is growing exponentially, and the infrastructure either remains unchanged or is changing, but it is not happening as fast as we would like [1]. Long-term effects of noise exposure, such as disorders of the cardiovascular system (high blood pressure, myocardial infarction, coronary heart disease, etc.), the nervous system (sleep disorder, cognitive impairment, vegetative vascular dystonia), diseases of the ear and mastoid process (conductive and sensorineural hearing loss), depression and other mental disorders [2, 3, 4], are more related to indicators that sum up the noise exposure over a long time. Both when conducting tests by accredited specialists and when choosing housing for buyers, you have to rely on an analytical or practical way to assess the noise pollution of a room. In order to provide a person with a simple and objective way to assess noise pollution, a software package has been developed that allows assessing the impact of noise pollution from transport on public health. Methods: quantitative risk assessment was carried out in accordance with the methodological recommendations of MP 2.1.10.0059-12 “Assessment of public health risk from exposure to traffic noise”. Results: in order to automate calculations, unify the evaluation of results and reduce time costs, the authors propose a software package for differential assessment of public health risks from exposure to rail and road transport. The end product is a user-friendly, cross-platform application for operational risk assessment in the field for employees of test centers who measure noise from known sources of automobile, railway or combined traf fic flows. Practical importance: convenience and optimization of risk processing by noise measurements by employees of noise measurement laboratories using the application.

Constitutive modelling in computational geomechanics – 61st Rankine lecture, British Geotechnical Association, 2023

Constitutive models are an essential part of computational modelling in geotechnics; they are at the heart of almost all theoretical predictions of geotechnical structures. How the stress-strain (and perhaps time) response of soil (and rock) is represented in these mathematical models is usually the key to successful prediction of the behaviour of geotechnical structures. However, the important details of these models, particularly the idealisations that are made, may be poorly or incompletely understood, or ignored, sometimes at significant cost to the unwary analyst. Indeed, the capabilities and the shortcomings of these models, especially the more advanced models, are not always easy to ascertain. In some cases, determination of the values of the input parameters is not straightforward. Consequently, it may be difficult to determine which model to select for a particular task. This paper explores some of the more important developments in the constitutive modelling of soils and addresses some of these issues of potential concern. The need for such models and the various attributes and capabilities that the commonly used models possess is reviewed. Also discussed is the issue of matching a particular model to the geotechnical problem at hand, which model attributes are required and why. The intention is to place emphasis on the physical basis of these models, rather than explore their mathematical complexity in detail. Some of the constitutive models encoded in the software packages used routinely in geotechnical practice are reviewed, and discussion is also provided on their specific limitations. Examples of practical applications, involving the solution of boundary and initial value problems, are described to illustrate both the advantages and some of the limitations of both commonly used and highly advanced constitutive models.

Revolutionizing consumer insights: the impact of fMRI in neuromarketing research

This study performs a comprehensive bibliometric (performance analysis) and thematic content analysis of global research in "neuromarketing or consumer neuroscience" and "functional magnetic resonance imaging or fMRI." Utilizing the PRISMA framework and R package software, we analyzed thirty-six Scopus-indexed articles. The USA and California Institute of Technology emerged as leading contributors, with Rangel, A., and Reimann, M., as notable authors. Prominent themes include 'advertising,' 'product,' 'price,' and 'brand', with the “Journal of Consumer Psychology” and “Journal of Neuroscience” being key publications. The most cited article is "Marketing actions can modulate neural representations of experienced pleasantness," with 620 citations. In addition, fMRI has been used to study consumer behavior (impulsiveness, reward, emotion, decision-making, and memory) toward marketing stimuli such as price (WTP), advertising (celebrity endorsement, MSV), product (packaging design), and brand (Halal logo, label, and personality). This study provides an invaluable literature review matrix and detailed insights into the current trends in global neuromarketing research utilizing fMRI. This study highlights the significant impact of fMRI in both academic and commercial realms, offering new insights for targeted marketing and consumer behavior research. It provides valuable guidance for developing more effective advertising strategies, understanding consumer decision-making processes, enhancing business performance, and collaborating academically.

ОСОБЛИВОСТІ ВИКОРИСТАННЯ СУЧАСНИХ ІНФОРМАЦІЙНОКОМУНІКАЦІЙНИХ ТЕХНОЛОГІЙ У ВИЩІЙ МАТЕМАТИЧНІЙ ОСВІТІ

The article discusses the relevance of using information and communication technologies (ICT) in higher mathematical education within the context of the contemporary educational environment characterized by rapid technological changes. It is noted that effective utilization of ICT, such as electronic journals, multimedia technologies, testing systems, and computer mathematics systems, contributes to the improvement of the teaching and learning process. Emphasis is placed on the necessity of reviewing and modifying teaching methodologies for mathematical disciplines to integrate innovative solutions. Furthermore, the use of information and communication technologies in higher mathematical education is deemed highly relevant due to the rapid development of the modern technological environment and the needs of the contemporary job market. The implementation of electronic journals, multimedia technologies, testing systems, and computer mathematics not only enhances the efficiency of teaching mathematical disciplines but also helps create a solid foundation for the future professional success of students. Electronic journals serve not only as convenient tools for administrative processes but also as platforms for active interaction among students, teachers, and administration, fostering the development of academic community and stimulating discussions and collaboration. Multimedia technologies, such as video lessons, interactive exercises, and simulations, provide students with opportunities to better grasp material and understand complex concepts, opening up new possibilities for personalized learning and adaptation to various learning styles. Testing systems, particularly those based on interactive platforms, enable instructors to effectively monitor students' knowledge and track their progress, as well as provide opportunities for personalized learning through automatic adaptation of task complexity Computer mathematics systems, including software packages for numerical and symbolic computations, become an integral part of modern mathematical education, empowering students to efficiently solve complex mathematical problems and explore new concepts, thus stimulating their creative potential and innovative approach to problem-solving. Together with educational platforms and distance learning systems, these tools contribute to the modernization and optimization of the educational process, leading to the improvement of the quality of higher mathematical education and the preparation of qualified professionals for the contemporary world.

Advancements in multi-wavelength data analysis: The ThreeML framework for high-energy astronomy

The Multi-Mission Maximum Likelihood framework (ThreeML) is a Python-based software package designed for multi-wavelength data analysis in high-energy astronomy. Integrating X-ray and gamma-ray data from various instruments, along with measurements at lower wavelengths, is essential for unlocking the full potential of observational data. However, the lack of standardization and unique challenges posed by each instrument often complicate the process of combining data from multiple sources. ThreeML addresses these challenges with its flexible, plugin-based structure, allowing for the seamless inclusion of data from diverse observatories in their native formats. Leveraging astromodels, a versatile modeling framework, ThreeML enables separate handling of source modeling and data access from likelihood optimization, facilitating a flexible combination of both aspects. Moreover, in addition to frequentist maximum likelihood analysis, ThreeML supports Bayesian analysis through posterior distribution sampling.

A DFT investigation on halide double perovskites X2ScTlI6 (X= Rb, Cs) for thermoelectric and optoelectronic applications

The present study conducted by first-principles calculations to explore the physical properties of Rb2ScTlI6 and Cs2ScTlI6 double perovskite compound utilizing the FP-LAPW method within the framework of DFT, as implemented in the WIEN2K software package. The electronic and optical characteristics of double perovskite materials were assessed utilizing the TB-mBJ functional, while the structural properties were analyzed employing the GGA-PBE approximation. Electronic properties demonstrated the semiconducting nature of the materials. Optical properties including the dielectric function, absorption coefficient, and reflectivity were computed, affirming the suitability of the compound for device applications across various spectral regions (infrared, visible, and ultraviolet). Additionally, this research delves into the thermoelectric properties, examining factors such as the ratio of thermal to electrical conductivity, a key metric known as the figure of merit, and the Seebeck coefficient. The study reveals that ZT exhibits higher values at lower temperatures but declines as temperature increases. ZT calculations demonstrate minute variations within 200–800 K and computed parameter values are quite favorable for thermoelectric applications of these materials in the future. Notably, this research contributes novelty by investigating the thermoelectric properties of Rb2ScTlI6 and Cs2ScTlI6 double perovskite, encompassing electrical conductivity, Seebeck coefficient, and the figure of merit.

A benchmarked comparison of software packages for time-lapse image processing of monolayer bacterial population dynamics.

Time-lapse microscopy provides a detailed window into the world of bacterial behavior. However, the vast amount of data produced by these techniques is difficult to analyze manually. We have analyzed four software tools designed to process such data and compared their performance, using populations of commonly studied bacterial species as our test subjects. Our findings offer a roadmap to scientists, helping them choose the right tool for their research. This comparison bridges a gap between microbiology and computational analysis, streamlining research efforts.

Structures of Epstein-Barr virus and Kaposi's sarcoma-associated herpesvirus virions reveal species-specific tegument and envelope features.

Discovered in 1964, Epstein-Barr virus (EBV) is the first identified human oncogenic virus and the founding member of the gammaherpesvirus subfamily. In 1994, another cancer-causing virus was discovered in lesions of AIDS patients and later named Kaposi's sarcoma-associated herpesvirus (KSHV), the second human gammaherpesvirus. Despite the historical importance of EBV and KSHV, technical difficulties with isolating large quantities of these viruses and the pleiomorphic nature of their envelope and tegument layers have limited structural characterization of their virions. In this study, we employed the latest technologies in cryogenic electron microscopy (cryoEM) and tomography (cryoET) supplemented with an artificial intelligence-powered data processing software package to reconstruct 3D structures of the EBV and KSHV virions. We uncovered unique properties of the envelope glycoproteins and tegument layers of both EBV and KSHV. Comparison of these features with their non-tumorigenic counterparts provides insights into their relevance during infection.

Molecular self-assembled helix peptide nanotubes based on some amino acid molecules and their dipeptides: molecular modeling studies.

The paper considers the features of the structure and dipole moments of several amino acids and their dipeptides which play an important role in the formation of the peptide nanotubes based on them. The influence of the features of their chirality (left L and right D) and the alpha-helix conformations of amino acids are taken into account. In particular, amino acids with aromatic rings, such as phenylalanine (Phe/F), and branched-chain amino acids (BCAAs)-leucine (Leu/L) and isoleucine (Ile/I)-as well as corresponding dipeptides (diphenylalanine (FF), dileucine (LL), and diisoleucine (II)) are considered. The main features and properties of these dipeptide structures and peptide nanotubes (PNTs), based on them, are investigated using computational molecular modeling and quantum-chemical semi-empirical calculations. Their polar, piezoelectric, and photoelectronic properties and features are studied in detail. The results of calculations of dipole moments and polarization, as well as piezoelectric coefficients and band gap width, for different types of helical peptide nanotubes are presented. The calculated values of the chirality indices of various nanotubes are given, depending on the chirality of the initial dipeptides-the results obtained are consistent with the law of changes in the type of chirality as the hierarchy of molecular structures becomes more complex. The influence of water molecules in the internal cavity of nanotubes on their physical properties is estimated. A comparison of the results of these calculations by various computational methods with the available experimental data is presented and discussed. The main tool for molecular modeling of all studied nanostructures in this work was the HyperChem 8.01 software package. The main approach used here is the Hartree-Fock (HF) self-consistent field (SCF) with various quantum-chemical semi-empirical methods (AM1, PM3, RM1) in the restricted Hartree-Fock (RHF) and in the unrestricted Hartree-Fock (UHF) approximations. Optimization of molecular systems and the search for their optimal geometry is carried out in this work using the Polak-Ribeire algorithm (conjugate gradient method), which determines the optimized geometry at the point of their minimum total energy. For such optimized structures, dipole moments D and electronic energy levels (such as EHOMO and ELUMO), as well as the band gap Eg = ELUMO - EHOMO, were then calculated. For each optimized molecular structure, the volume was calculated using the QSAR program implemented also in the HyperChem software package.

The effects of various factors on the efficacy of lithotripsy treatment of urolithiasis

Introduction. Currently, single- and multifactorial criteria are employed to evaluate the quality of urolithiasis treatment utilizing lithotripsy. Among the most utilized single factors that influence the efficacy of urolithiasis therapy are the stone-free rate (SFR), the duration of lithotripsy, the level of intra- and post-operative complications, and hospital stay following lithotripsy. A more promising approach is the integrated indicator of the efficacy of urolithiasis management using the lithotripter, which considers all the aforementioned factors. It is an urgent task to determine the extent to which alterations in individual variables impact the value of an integrated assessment of the efficacy of laser lithotripsy-based urolithiasis intervention.Objective. To study the dependence of the integral efficiency indicator on the magnitude of influencing factors in the treatment of urolithiasis using transurethral thulium lithotripsy.Materials &amp; methods. We used the method of mathematical modeling of the integral criterion for urolithiasis treatment efficacy using the Scilab v.6.02 software package to determine the extent to which individual factors influence the overall effectiveness of laser thulium lithotripsy.Results. Graphical dependences of the index of urolithiasis treatment efficacy for lithotripsy on the complication rate (at different values of surgery time and dependence of urolithiasis treatment efficacy on SFR at different values of complication rate, surgery time and hospital stay) were obtained. A software system for determining the integral index of urolithiasis treatment efficiency for lithotripsy was developed.Conclusion. The resulting dependencies of the index of urolithiasis treatment efficacy for lithotripsy can be used to evaluate the impact of the complication grade and the SFR on the value of the efficacy index and to devise measures to enhance it. The software developed for the calculation of this index allows to obtain the required value at different input influencing parameters.

Genome scans reveal signals of selection associated with pollution in fish populations of Basilichthys microlepidotus, an endemic species of Chile

The Maipo River catchment is one of Chile’s most polluted basins. In recent decades, discharges of untreated sewage and organic matter have caused eutrophication and water quality degradation. We employed the indigenous silverfish species Basilichthys microlepidotus as a model organism to investigate the process of adaptation and selection on genes influenced by pollution. Using variation at single nucleotide polymorphisms (SNPs), we determined the temporal stability of the population structure patterns previously identified in this species by varying SNPs. We also examined local adaptation to pollution-selected genes. Using the genotypes of 7684 loci in 180 individuals, we identified 429 and 700 loci that may be undergoing selection. We detected these loci using the FSTHET and ARLEQUIN outlier detection software, respectively. Both software packages simultaneously identified a total of 250 loci. B. microlepidotus' population structure did not change over time at contaminated or unpolluted sites. In addition, our analysis found: (i) selection of genes associated with pollution, consistent with observations in other organisms; (ii) identification of candidate genes that are functionally linked to the same biological processes, molecular functions and/or cellular components that previously showed differential expression in the same populations; and (iii) a candidate gene with differential expression and a non-synonymous substitution.

Integrated miRNA Profiling of Extracellular Vesicles from Uterine Aspirates, Malignant Ascites and Primary-Cultured Ascites Cells for Ovarian Cancer Screening.

Extracellular vesicles (EVs) are of growing interest in the context of screening for highly informative cancer markers. We have previously shown that uterine aspirate EVs (UA EVs) are a promising source of ovarian cancer (OC) diagnostic markers. In this study, we first conducted an integrative analysis of EV-miRNA profiles from UA, malignant ascitic fluid (AF), and a conditioned medium of cultured ascites cells (ACs). Using three software packages, we identified 79 differentially expressed miRNAs (DE-miRNAs) in UA EVs from OC patients and healthy individuals. To narrow down this panel and select miRNAs most involved in OC pathogenesis, we aligned these molecules with the DE-miRNA sets obtained by comparing the EV-miRNA profiles from OC-related biofluids with the same control. We found that 76% of the DE-miRNAs from the identified panel are similarly altered (differentially co-expressed) in AF EVs, as are 58% in AC EVs. Interestingly, the set of miRNAs differentially co-expressed in AF and AC EVs strongly overlaps (40 out of 44 miRNAs). Finally, the application of more rigorous criteria for DE assessment, combined with the selection of miRNAs that are differentially co-expressed in all biofluids, resulted in the identification of a panel of 29 miRNAs for ovarian cancer screening.