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Traditionally, rock engravings were studied through their visual characteristics. They have been analyzed with comparative and interpretative methodologies of iconography and iconology. However, there has been a recent shift towards identifying production processes, allowing reconstruction of operational characteristics through various methods. Nevertheless, the studies of the technological aspects typically focus on the operational and the mechanical, often omitting the visuality of the outcome. In the current paper, we are using ArchCUT3-D software for computational analysis of 3-D data acquired from various rock engravings located in Timna Park, southern Israel. We show how micro-morphological evidence, extracted from the engraved lines, can decode technical trends and variabilities in a technique's particular implementation. Then, we conduct a focused examination of one group of engraved figures in order to establish a link between execution techniques and visual considerations. Based on our results and the following discussion, we suggest the term Techné to indicate the choice of technique that goes beyond the instrumental or purely operative perspectives. We highlight the intentional choice, which designs the visual rhetoric of the engraved marks and suggests cultural concepts that contrived the procedural processes. [ABSTRACT FROM AUTHOR]

Interleukin-37 is a cytokine with potent immunosuppressive properties that has been shown to have potential to treat autoimmune and chronic inflammatory diseases, as well as certain types of cancer. IL-37 is a 19 kDa protein which interacts with proteins in receptor-dependent and receptor-independent pathways. The expression of the IL-37 protein cloned into the pET-28a vector was optimized in Rosetta 2(DE3) after comparing its expression with Rosetta-gami 2(DE3) and Rosetta 2(DE3) pLysS, which was then used for the large-scale production of IL-37. IMAC purification of IL-37 yielded > 97% pure 0.9 mg/mL protein from auto-induced fermentation. The IC50 value of IL-37 was < 1 µM, which was similar to that of doxorubicin, and proliferation of > 80% of all cancer cells was inhibited by 100 µg/mL of IL-37 protein. IL-37 may be a promising theragnostic target for cancer due to its comparable IC50 value with that of doxorubicin. [ABSTRACT FROM AUTHOR]

Background: The emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, notably Omicron and Delta, necessitates a detailed analysis of the amino acid substitutions occurring within the spike (S) protein. The substitutions mentioned above are crucial in regulating the interactions between the virus and its host receptor angiotensin-converting enzyme 2 (ACE2), in addition to impacting the effectiveness of monoclonal antibodies (mAbs) used in therapy. Methods: In this paper, we employed computational mutational analysis using PremPS to predict the stability scores of the S protein. Our analysis highlighted several key mutations, including G181V and A222V, which exhibited significant alterations in stability, particularly within the N-terminal domain (NTD), and were notably prevalent in the Omicron variant. To further elucidate the impact of these mutations, we conducted docking simulations employing HADDOCK 2.4 to assess the binding affinity between the Omicron receptor-binding domain (RBD) and ACE2. Results: Our outcomes emerged that the Omicron RBD has a stronger attraction to ACE2, driven by mutations such as Q493R, Q498R, S477N, T478K, G496S and L452R, which significantly influenced the RBD-ACE2 complex dynamics. Additionally, we ascertained the potential for immune evasion by these mutations through docking simulations with mAbs. Our findings identified specific interactions between mutations like L452R, E484Q/A and Q493R with mAbs, suggesting their potential to evade immune recognition. Conclusions: In summary, our paper provides insight into the complex connection between the fluctuation of the SARS-CoV-2 S protein, receptor binding dynamics, and immunotherapeutic efficacy. These insights are essential for guiding the development of novel therapeutics and informing public health strategies aimed at combating the ongoing COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

In this study, the dispersion and explosion of liquid hydrogen (LH 2) in leakage accidents are investigated using the Flame Accelerator Simulator (FLACS) code. The study focus was a liquid hydrogen research facility in Gimhae, South Korea. Simulations were conducted under various conditions by varying the mass flow rates (0.61 and 0.3 kg/s), directions (lateral in areas with minimal structures, lateral towards a tube trailer truck, and downward), and durations (90 and 180 s) of leakage. The results indicated that higher leakage mass flow rates produce a larger flammable cloud volume (FCV), resulting in higher maximum overpressures than that caused by lower flow rates. Downward leakage generally resulted in a larger FCV and higher overpressure than lateral leakage. The explosion characteristics were also influenced by geometry of LH 2 facility, including the presence of structures in the leakage path. Contrastingly, leakage duration had a minimal effect on the maximum overpressure because an increased duration causes a greater dilution of hydrogen, only slightly expanding the FCV. According to the overpressure–impulse diagram, higher leakage flow rates cause severe health risks, approaching thresholds for lung rupture and 100% fatality. Contrary to the minor damages caused by lower leakage flow rates. High flow rates, particularly with downward leaks, can cause significant structural damage in brick buildings, potentially leading to partial demolition. • Higher leakage mass flow rates result in larger flammable cloud volumes and increased maximum overpressures. • Downward hydrogen leaks lead to larger flammable clouds and higher overpressures than lateral leaks. • Facility geometry and structures significantly affect explosion overpressure magnitude and distribution. • Leakage duration has a minimal effect on maximum overpressure due to hydrogen dilution during leakage. [ABSTRACT FROM AUTHOR]

ABSTRACT Cystitis glandularis (CG), known as a pre‐gradual lesion in the bladder, is the pathological changes in the vesical mucosa characterized by inflammatory invasion and chronic obstruction. Clinically, effective treatment against CG is prescribed only when using drug therapy. Fucoidan, the naturally extractive polysaccharide, is well‐reported bioactive compound with anti‐inflammatory and immunoregulatory properties. In this research, an emerging computational approach was applied to explicate anti‐CG actions and pharmacological targets exhibited by fucoidan in detail. Current network pharmacology data showed that 16 intersection genes of fucoidan and CG were identified, whereas all 6 core targets, including interleukin‐6 (IL‐6), tumor necrosis factor (TNF), interleukin‐1B (IL‐1B), matrix metalloproteinase‐9 (MMP‐9), interleukin‐10 (IL‐10), matrix metalloproteinase‐2 (MMP‐2), biological processes, and signaling pathways of fucoidan against CG were characterized, respectively. As revealed in the underlying mechanism, the anti‐CG actions achieved by fucoidan were chiefly implicated in the reduction of inflammatory reactions and enhancement of immunoregulation. Taken together, these network bioinformatics findings may be used to reveal anti‐CG effects and the pharmacological mechanism of fucoidan before further experimental validation. Furthermore, those core genes identified may be therapeutic targets for research and development of fucoidan‐anti‐CG. [ABSTRACT FROM AUTHOR]

Background: PhenoMetaboDiff is a novel R package for computational analysis and visualization of data generated by Biolog Phenotype Mammalian Microarrays (PM-Ms). These arrays measure the energy production of mammalian cells in different metabolic environments, assess the metabolic activity of cells exposed to various drugs or energy sources, and compare the metabolic profiles of cells from individuals affected by specific disorders versus healthy controls. Methods: PhenoMetaboDiff has several modules that facilitate statistical analysis by sample comparisons using non-parametric Mann–Whitney U-test, the integration of the OPM package (an R package for analysing OmniLog® phenotype microarray data) for robust file conversion, and calculation of slope and area under the curve (AUC). In addition, the built-in visualization allows specific wells to be visualized in selected pathways for a particular time slice. Results: Compared to the standard OPM package, the features developed in PhenoMetaboDiff assess metabolic profiles by employing statistical tests and visualize the dynamic nature of the energy production in several conditions. Examples of how this package can be used are demonstrated for several rare disease conditions. The incorporation of a graphical user interface expands the utility of this program to both expert and novice users of R. Conclusions: PhenoMetaboDiff makes the deployment of the cutting-edge Biolog system available to any researcher. [ABSTRACT FROM AUTHOR]

The operation of vertical axis wind turbines (VAWTs) to generate low-carbon electricity is growing in popularity. Their advantages over the widely used horizontal axis wind turbine (HAWT) include their low tip speed, which reduces noise, and their cost-effective installation and maintenance. A Farrah turbine equipped with 12 blades was designed to enhance performance and was recently the subject of experimental investigation. However, little research has been focused on turbine configurations with more than three blades. The objective of this study is to employ numerical methods to analyse the performance of the Farrah wind turbine and to validate the findings in comparison with experimental results. The investigated blade pitch angles included both positive and negative angles of 7, 15, 20 and 40 degrees. The k-ω SST model with the sliding mesh technique was used to perform simulations of a 14.4 million element unstructured mesh. Comparable trends of power output results in the experimental investigation were obtained and the assumptions of mechanical losses discussed. Wake recovery was determined at an approximate distance of nine times the turbine diameter. Two large complex quasi-symmetric vortical structures were observed between positive and negative blade pitch angles, located in the near wake region of the turbine and remaining present throughout its rotation. It is demonstrated that a number of recognised vortical structures are transferred towards the wake region, further contributing to its formation. Additional notable vortical formations are examined, along with a recirculation zone located in the turbine's core, which is described to exhibit quasi-symmetric behaviour between positive and negative rotations. [ABSTRACT FROM AUTHOR]

L‐aspartate‐alpha‐decarboxylase (ADC) catalyzes the decarboxylation of L‐aspartate to produce β‐alanine, which is the decisive step in the biosynthesis of β‐alanine. However, the low catalytic stability and efficiency of ADC limit its industrial applications. In this study, a variant of ADC from Bacillus subtilis were used as a starting point for engineering. After constructing a random mutagenesis library by error‐prone PCR, followed by high‐throughput screening,four substitutions (S7 N, K63 N, A99T, and K113R) were identified. By screening saturation mutagenesis libraries on these positions and computational analysis, two recombined variants N3(S7 N/K63 N/I88 M/A99E/K113R/I126*) and Y1(S7Y/K63 N/I88 M/A99E/K113R/I126*) with improved performance were obtained. Compared to the wild type, the catalytic efficiency and catalytic stability of the best two variants were enhanced up to 95 %(variant N3) and up to 89 %(variant Y1), respectively. In addition, Y1 exhibited 3.37 times improved half‐life and 2‐fold improved total turnover number. Hydrophilicity analysis and molecular dynamics (MD) simulation revealed that the increased hydrophilicity and steric hindrance of key amino acid residues would affect the catalytic activity and stability. The improved catalytic performance of the variants could be attributed to their enhanced binding capacity to the substrate within the active pocket and the alleviation of mechanism‐based inactivation. [ABSTRACT FROM AUTHOR]

AbstractAmidst an explosion in anti-LGBTQIA+ legislation and hate crimes in the United States, this study examines public discourses around legislation that suppress LGBTQIA+ rights. We conducted a computer-assisted content analysis of 25,711 posts on Twitter (now called X) collected during the time when bans on youths’ access to gender-affirming care were beginning to proliferate across the country. We identified five topics: education, legislation, medical, Disney dispute, anti-LGBTQIA+ attacks, and assessed the sentiments and toxicity levels of each topic. Findings reveal a fractured virtual public sphere in which discussions about LGBTQIA+ rights are contentious and toxic. We found that education was the most salient topic—whether children should be taught about sexual orientation and gender identity in schools—and tweets on this topic were also the most toxic. Overwhelmingly, the tone of the tweets was negative, although this varied by the topic of the tweets. We discuss the implications of our findings for a healthy online public sphere. [ABSTRACT FROM AUTHOR]

This study identifies and characterizes a second polymorph (Poly‐II) of quinoline‐4‐carbaldoxime (HQ), isolated from an acetone‐acetonitrile mixture. Poly‐II was compared to the previously known Poly‐I using PXRD, DSC, IR, and Raman spectroscopy. Poly‐I forms a 1D supramolecular assembly, whereas Poly‐II exhibits a 2D assembly with additional hydrogen bonds. Hirshfeld surface analysis reveals the presence of different non‐covalent interactions in Poly‐I and Poly‐II, and atom‐in‐molecule (AIM) analysis identifies their strength. AIM analysis, along with Espinosa's relation, was used to calculate the strength of O─H···N and C─H···N interactions in Poly‐I and Poly‐II. The values are −30.0 and −6.17 kJ/mol for Poly‐I, whereas the values for Poly‐II are −36.18 and −3.66 kJ/mol. The plane wave periodic DFT calculations determined the lattice energies of Poly‐I and Poly‐II to be −1.52 and −1.53 eV, respectively, indicating that both polymorphs have comparable stability. The crystal parameters of Poly‐I and Poly‐II obtained from theoretical simulations and the experiment are comparable, indicating the similar stability of Poly‐I and Poly‐II. Computational simulations confirmed experimental data, showing both polymorphs have similar stability and melting points despite different unit cell volumes. [ABSTRACT FROM AUTHOR]

Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across languages but clearly different when remediating legacy and new media. Trust in legacy media is correlated with higher proportion of shared links from legacy media and reversely related to the proportion of shared links from new media sources. Considering the volume and timing of the remediated content, we conclude that legacy media retains its agenda setting power. New media linked content tends to cover migration in association to subjects such as Islam or terrorism and to express strong critical opinions against migrants/refugees. The language used is more toxic than in legacy media linked content. The tweets remediating legacy media articles covered topics like domestic or European politics, causes of refugee arrivals and procedures to give them protection. Thus, legacy and new media remediated content differs in both tone and function: toxicity is low and factuality high for content linking to legacy media, with the reverse being true for new media remediations. [ABSTRACT FROM AUTHOR]

The assumption that ownership has an effect on the diversity of news is based on the forms of control that ownership allows and the market conditions in which ownership is exercised. In this study, we perform a large-scale analysis of the Swedish newspaper market, surveying 130 newspapers and parliamentary speeches over a period of six years (2014–2019), to substantiate to what extent market and for-profit ownership forms impact political viewpoint diversity. Our analysis shows that newspapers with market leadership and chain ownership offer more political viewpoint diversity than number two and single-owned papers. In contrast, the ownership forms surveyed here (private, foundation, and publicly traded ownerships) display little effect on newspapers' internal diversity. We also find that a greater number of papers in a local market does not imply more external diversity in that market. The analysis thus offers some nuance to the notion that ownership form and market pluralism are prerequisites for viewpoint diversity, highlighting instead the importance of scale effects for pluralistic media systems. [ABSTRACT FROM AUTHOR]

Purpose of Review: This review paper provides step-by-step instructions on the fundamental process, from handling fastq datasets to illustrating plots and drawing trajectories. Recent Findings: The number of studies using single-cell RNA-seq (scRNA-seq) is increasing. scRNA-seq revealed the heterogeneity or diversity of the cellular populations. scRNA-seq also provides insight into the interactions between different cell types. User-friendly scRNA-seq packages for ligand-receptor interactions and trajectory analyses are available. In skeletal biology, osteoclast differentiation, fracture healing, ectopic ossification, human bone development, and the bone marrow niche have been examined using scRNA-seq. scRNA-seq data analysis tools are still being developed, even at the fundamental step of dataset integration. However, updating the latest information is difficult for many researchers. Investigators and reviewers must share their knowledge of in silico scRNA-seq for better biological interpretation. Summary: This review article aims to provide a useful guide for complex analytical processes in single-cell RNA-seq data analysis. [ABSTRACT FROM AUTHOR]

Background: Gliomas are neoplasms of the central nervous system that originate in glial cells. The genetic characteristics of this type of neoplasm are the loss of function of tumor suppressor genes such as TP53 and somatic mutations in genes such as IDH1/2. Additionally, in clinical cases, de novo single nucleotide polymorphisms (SNP) are reported, of which their pathogenicity and their effects on the function and stability of the protein are known. Methodology: Non-synonymous SNPs were analyzed for their structural and functional effect on proteins using a set of bioinformatics tools such as SIFT, PolyPhen-2, PhD-SNP, I-Mutant 3.0, MUpro, and mutation3D. A structural comparison between normal and mutated residues for disease-associated coding SNPs was performed using TM-aling and the SWISS MODEL. Results: A total of 13 SNPs were obtained for the TP53 gene, 1 SNP for IDH1, and 1 for IDH2, which would be functionally detrimental and associated with disease. Additionally, these changes compromise the structure and function of the protein; the A161S SNP for TP53 that has not been reported in any databases was classified as detrimental. Conclusions: All non-synonymous SNPs reported for TP53 were in the region of the deoxyribonucleic acid (DNA) binding domain and had a great impact on the function and stability of the protein. In addition, the two polymorphisms detected in IDH1 and IDH2 genes compromise the structure and activity of the protein. Both genes are related to the development of high-grade gliomas. All the data obtained in this study must be validated through experimental approaches. [ABSTRACT FROM AUTHOR]

Artificial material properties assignment is usually adopted in the computational modelling of laser powder bed fusion (LPBF) process to obtain better agreement between the simulated and experimental results. In this context, various mathematical models are used in the literature to calculate the thermal conductivity of the powder bed in the continuous domain computational analysis of the LPBF process for metallic materials like Ti6Al4V, irrespective of the impact they have on the melt pool thermo-hydrodynamics and solidification parameters. In this study, a comparison of two different powder bed thermal conductivity models—linear and power law, was conducted. Computational analyses were conducted using each of the two models for powder bed thermal conductivity, and the melt pool dimensions, temperature field and solidification parameters were calculated and compared. It was seen that the power law model resulted in slightly larger melt pool dimensions with higher temperatures and solidification parameters, compared to the linear model for the powder bed thermal conductivity. The present study shows that the arbitrary assignment of material properties during computational analysis of LPBF process may lead to widely different results. [ABSTRACT FROM AUTHOR]

Understanding the changes in arterial wall viscoelasticity during the progression of vascular disease is crucial. Nonetheless, there has been a lack of comprehensive investigation into the assessment of viscoelastic parameters and their impact on radial wall motion. To address this gap, we analyzed the radius waveform by solving the viscoelastic constitutive equations of the standard linear model (SLM) based on a thin-wall tube assumption. Additionally, a finite element method (FEM) was applied to simulate radial wall motion for thicker walls. The analytic solution showed that a well-balanced SLM model with the time constant ( τ ε ) values smaller than 0.05 s could effectively simulate the dynamic response of radial wall motion in a human carotid artery. FEM result showed that increasing wall thickness led to a decrease in the amplitude of the radius waveform, while its effect on phase lag was marginal. To evaluate the clinical relevance of arterial wall viscoelasticity, the viscoelastic parameters of the SLM were estimated from the pressure and diameter waveforms of each patient using an optimization technique. The 105 patients were categorized according to their cardiovascular disease risk status, and statistical comparisons were made for viscoelastic parameters across the different groups. The results revealed that the high-risk group exhibited significantly higher wall elasticity than the low-risk group (p < 0.03), while the intermediate-risk group demonstrated higher wall viscosity than the low-risk group (p < 0.01). Therefore, arterial wall elasticity holds potential as a significant indicator for distinguishing between low-risk and high-risk groups, whereas viscosity shows promise as a significant indicator for distinguishing between low-risk and intermediate-risk groups. [ABSTRACT FROM AUTHOR]

The present investigation employed information mining and knowledge learning processes to showcase their efficacy in comprehending the viscoelastic properties of nanocomposites comprising vapor-grown carbon nanofiber and vinyl ester. The study relied solely on the data obtained from an experimental analysis. This study involves an investigation into the utilization of enhanced distance strategy in conjunction with the data-space clustering techniques possibilistic C-means and fuzzy possibilistic C-means. This study employs clustering methodologies to discern patterns of behaviour in the viscoelastic properties of polymer nano-composites. Principal component analysis is utilized as a dimensionality reduction technique to facilitate this analysis. By employing these methodologies, it was feasible to categories the nanocomposite specimens based on diverse attributes and partition the vapour-grown carbon nanofiber and vinyl ester specimens into distinct clusters. This paper emphasizes the significance and utility of data mining methodologies within the realm of materials informatics. [ABSTRACT FROM AUTHOR]

Legal Literacies for Text Data Mining - Cross-Border (“LLTDM-X”) is a National Endowment for the Humanities Level 1 Advancement Grant project addressing legal and ethical issues faced by U.S. digital humanities (DH) practitioners whose text data mining (TDM) research and practice intersects with foreign-held or - licensed content, or involves international cooperations.LLTDM-X is a collaboration between the University of California Berkeley Library and Internet Archive, and builds upon the previous NEH-sponsored institute, Building Legal Literacies for Text Data Mining (Building LLTDM). That institute provided guidance and strategies to DH TDM researchers on navigating legal literacies for text data mining (including copyright, contracts, privacy, and ethics) within a U.S. context.A common challenge highlighted during Building LLTDM was the fact that TDM practitioners encounter numerous and complex legal problems in cross-border TDM research. These occur when: (i) the materials practitioners want to mine are housed in a foreign jurisdiction, or are otherwise subject to foreign database licensing or laws; (ii) the human subjects they are studying or who created the underlying content reside in another country; or, (iii) the colleagues with whom they are collaborating reside abroad, yielding uncertainty about which country’s laws, agreements, and policies apply.We designed LLTDM-X to identify and better understand the cross-border issues that DH TDM practitioners face, with the aim of using these issues to inform prospective research and education. We also hoped that LLTDM-X would yield preliminary guidance to benefit researchers in the meantime, as instructional materials are being developed. In early 2023, we hosted a series of three online round tables with U.S.-based cross-border TDM practitioners (“Practitioners”), and law and ethics experts (“Experts”) practicing in six countries. The round table conversations were structured to illustrate the empirical issues that researchers face, and also for the Practitioners to benefit from guidance on legal and ethical challenges. Upon the completion of the round tables, the LLTDM-X project team created a robust and hypothetical case study that (i) reflects the observed cross-border LLTDM issues and (ii) contains analysis to facilitate the development of future instructional materials.

The purpose of this research is to explore the biomechanical consequences of maternal injuries on fetal movements. Additionally, the research aims to comprehend the relationship between these injuries and fetal movement within the amniotic sac and to understand the extent to which the amniotic fluid can provide protection during severe injuries. The focus is on the potential impact these injuries could have on surgical procedures and preventative strategies. Using advanced computational simulations, the study investigates how various maternal injuries can influence the behavior of amniotic fluid and the subsequent stress exerted on fetal development. The findings suggest that maternal injuries can induce stress, primarily affecting the posterior regions of the fetus and the umbilical cord, depending on the boundary and initial conditions. This stress is associated with fetal displacement within the amniotic sac. While the amniotic fluid provides a certain level of protection, its limitations become apparent during severe injuries. These insights have implications for the field of surgery, particularly fetal procedures. They underscore the need for improved protective measures and the development of personalized obstetric and neonatal care strategies. Moreover, the study highlights the potential of computational simulations in aiding surgeons. These simulations can provide a more accurate understanding of the critical areas to focus on during surgical procedures, thereby enhancing the precision and safety of these operations.

Abstract The utility of spatial omics in leveraging cellular interactions in normal and diseased states for precision medicine is hampered by a lack of strategies for matching disease states with spatial heterogeneity-guided cellular annotations. Here we use a spatial context-dependent approach that matches spatial pattern detection to cell annotation. Using this approach in existing datasets from ulcerative colitis patient colonic biopsies, we identified architectural complexities and associated difficult-to-detect rare cell types in ulcerative colitis germinal-center B cell follicles. Our approach deepens our understanding of health and disease pathogenesis, illustrates a strategy for automating nested architecture detection for highly multiplexed spatial biology data, and informs precision diagnosis and therapeutic strategies.

Our study delves into the dynamics of a convective Magneto-Hydrodynamic Bioconvective Nanofluid model (MHD-BCNFM) flowing over a convectively heated stretched sheet. To accomplish this, we utilize the distinctive capabilities of the Supervised Stochastic Approach for Computational Analysis (SSACA). By integrating similarity transformations, we convert the partial differential equations (PDEs) governing the system into coupled ordinary differential equations (ODEs). We generate the dataset for our approach using the Adam numerical technique specifically tailored for the (MHD-BCNFM). Achieving this involves systematic modulation of parameters such as λ, bioconvection Péclet number Pe, Bioconvection constant σ, Brownian motion parameter Nb, and thermophoresis parameter Nt. ''Moreover, we utilize a reference dataset to compute numerical values of various physical quantities in the (MHD-BCNFM) employing SSACA-based Artificial Intelligence methods. The effectiveness of our devised SSACA approach is demonstrated by a negligible mean squared error, ranging from approximately 10−8 to 10−10. Histograms exhibit a maximum error range of 10−5, closely aligning with optimal correlation/regression measures. Outstanding performance metrics in terms of Mean Squared Error (MSE) are attained at levels such as l 9.93E−12, 1.07E−11, 6.28E−10, 1.43E−11, 2.09E−09, 3.65E−11, 2.97E−11, and 2.80E−13 against 320, 430, 209, 85, 356, 295, 66, and 136 epochs. A comparative study between the proposed and reference datasets underscores the authenticity and precision of SSACA, supported by error analyses ranging from E-05 to E-09 across all scenarios.

MicroRNAs (miRNAs) are molecules that influence messenger RNA (mRNA) expression levels by binding to the 3′ untranslated region (3′ UTR) of target genes. Host miRNAs can influence flavivirus replication, either by inducing changes in the host transcriptome or by directly binding to viral genomes. The 3′ UTR of the flavivirus genome is a conserved region crucial for viral replication. Cells might exploit this well-preserved region by generating miRNAs that interact with it, ultimately impacting viral replication. Despite significant efforts to identify miRNAs capable of arresting viral replication, the potential of all these miRNAs to interact with the flavivirus 3′ UTR is still poorly characterised. In this context, bioinformatic tools have been proposed as a fundamental part of accelerating the discovery of interactions between miRNAs and the 3′ UTR of viral genomes. In this study, we performed a computational analysis to reveal potential miRNAs from human and mosquito species that bind to the 3′ UTR of flaviviruses. In humans, miR-6842 and miR-661 were found, while in mosquitoes, miR-9-C, miR-2945-5p, miR-11924, miR-282-5p, and miR-79 were identified. These findings open new avenues for studying these miRNAs as antivirals against flavivirus infections. [ABSTRACT FROM AUTHOR]

Radical S‐adenosyl‐L‐methionine (SAM) enzymes couple the reductive cleavage of SAM to radical‐mediated transformations that have proven to be quite broad in scope. DesII is one such enzyme from the biosynthetic pathway of TDP‐desosamine where it catalyzes a radical‐mediated deamination. Previous studies have suggested that this reaction proceeds via direct elimination of ammonia from an α‐hydroxyalkyl radical or its conjugate base (i.e., a ketyl radical) rather than 1,2‐migration of the amino group to form a carbinolamine radical intermediate. However, without a crystal structure, the active site features responsible for this chemistry have remained largely unknown. The crystallographic studies described herein help to fill this gap by providing a structural description of the DesII active site. Computational analyses based on the solved crystal structure are consistent with direct elimination and indicate that an active site glutamate residue likely serves as a general base to promote deprotonation of the α‐hydroxyalkyl radical intermediate and elimination of the ammonia group. [ABSTRACT FROM AUTHOR]

Potent radiolabelled compounds eligible for therapy of prostate cancer need to be developed. Hence, we developed two candidate therapeutic agents bearing the iodine-131 (131I) radionuclide, namely, [131I]-xanthine (3,7-dihydropurine-2,6-dione) and [131I]-hypoxanthine (1,9-dihydro-6H-purin-6-one). The radiolabelled compounds were subjected to a cellular uptake study, which was accomplished by incubating [131I]-xanthine and [131I]-hypoxanthine with the human prostate cancer cell line (LNCaP) for 5, 15, 30, 60, and 90 min. Results showed that the accumulation of both [131I]-xanthine and [131I]-hypoxanthine in prostate cancer cells was significantly higher than the control group (131I). [131I]-xanthine rapidly accumulated in prostate cancer cells, with the highest percentage of cellular uptake of 2.73% ± 0.40% observed at 30 min of incubation. By contrast, [131I]-hypoxanthine exhibited more efficient accumulation in prostate cancer cells, especially at 60 and 90 min of incubation, with cellular uptake values of 11.5% ± 3.14% and 11.9% ± 1.83%, respectively. Furthermore, the computational analysis showed that radioiodinated xanthine and hypoxanthine provide potential binding affinities and interaction on both androgen and prostate-specific membrane antigen receptors. Overall, this study indicates that [131I]-xanthine and [131I]-hypoxanthine can be potentially developed as therapeutic agents for prostate cancer. [ABSTRACT FROM AUTHOR]

The purpose of this research is to explore the biomechanical consequences of maternal injuries on fetal movements. Additionally, the research aims to comprehend the relationship between these injuries and fetal movement within the amniotic sac and to understand the extent to which the amniotic fluid can provide protection during severe injuries. The focus is on the potential impact these injuries could have on surgical procedures and preventative strategies. Using advanced computational simulations, the study investigates how various maternal injuries can influence the behavior of amniotic fluid and the subsequent stress exerted on fetal development. The findings suggest that maternal injuries can induce stress, primarily affecting the posterior regions of the fetus and the umbilical cord, depending on the boundary and initial conditions. This stress is associated with fetal displacement within the amniotic sac. While the amniotic fluid provides a certain level of protection, its limitations become apparent during severe injuries. These insights have implications for the field of surgery, particularly fetal procedures. They underscore the need for improved protective measures and the development of personalized obstetric and neonatal care strategies. Moreover, the study highlights the potential of computational simulations in aiding surgeons. These simulations can provide a more accurate understanding of the critical areas to focus on during surgical procedures, thereby enhancing the precision and safety of these operations. [ABSTRACT FROM AUTHOR]

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Purpose: Intracerebral hemorrhage is the deadliest form of stroke. This study aimed to enhance the prediction of 30-day mortality in intracerebral hemorrhage patients by integrating computational parameters. Methods: This study retrospectively analyzed 435 patients with spontaneous intracerebral hemorrhage (ICH). Utilizing the acquired computed tomography (CT) images, we extracted the contour and visual representation of ICH. For the extracted contour, the analysis encompassed factors including compactness, fractal dimension, Fourier factor, and circle factor. For the images depicting ICH, we calculated various factors related to density distribution including mean, coefficient of variance, skewness and kurtosis, as well as texture parameters, such as energy, entropy, contrast and homogeneity. To assess the impact of surgical treatment on 30-day mortality, logistic regression analysis was used. Results: A total of 126 patients (29.09%) died within 30 days. A total of 62 (14.25%) patients underwent surgical treatment. Multivariate logistic regression analysis revealed that surgical treatment was independently associated with a lower risk of 30-day mortality (odds ratio, OR 0.226, 95% confidence interval, CI 0.049–0.85; p = 0.039). Based on the moderated analysis, we found that the volume of ICH (OR 0.905, 95% CI 0.902–0.908; p < 0.001) and ICH energy (OR 1.389, 95%CI 0.884–0.988; p = 0.010) had positive moderating effect on such associations while the presence of intraventricular blood had negative moderating effect (OR 1.154, 95% CI 1.034–1.628; p = 0.010). Conclusion: Patients exhibiting a higher volume and energy of ICH might benefit from surgical treatment; however, this efficacy was found to be diminished in cases involving the presence of intraventricular blood. [ABSTRACT FROM AUTHOR]

The utility of spatial omics in leveraging cellular interactions in normal and diseased states for precision medicine is hampered by a lack of strategies for matching disease states with spatial heterogeneity-guided cellular annotations. Here we use a spatial context-dependent approach that matches spatial pattern detection to cell annotation. Using this approach in existing datasets from ulcerative colitis patient colonic biopsies, we identified architectural complexities and associated difficult-to-detect rare cell types in ulcerative colitis germinal-center B cell follicles. Our approach deepens our understanding of health and disease pathogenesis, illustrates a strategy for automating nested architecture detection for highly multiplexed spatial biology data, and informs precision diagnosis and therapeutic strategies. [ABSTRACT FROM AUTHOR]

AbstractIn this study, a multi-objective version of the recently proposed cheetah optimizer called multi-objective cheetah optimizer (MOCO) has been proposed. MOCO draws inspiration from the targeted hunting strategy employed by cheetahs, which involves a sequence of actions: searching for prey, patiently waiting for the right moment to attack, swiftly launching the attack, and then retreating from the prey and returning to their habitat. MOCO is the result of modification and enhancement from its single-objective counterpart, utilizing a Pareto dominance-based approach. This adaptation allows MOCO to efficiently handle multiple objectives, explores and exploits promising areas in the optimization landscape, and identifies non-dominated solutions, offering valuable tradeoff choices for decision-makers. To demonstrate its practical applications, the MOCO method has been employed to address five intricate structural design problems. These problems involve a pair of competing objectives: the minimization of structural weight and the reduction of maximum nodal displacement. To gauge the efficacy and efficiency of the proposed algorithm, a comparative analysis is conducted against three alternative state-of-the-art multi-objective algorithms. Furthermore, a rigorous evaluation is carried out utilizing hypervolume testing. The findings reveal that the MOCO algorithm surpasses the performance of the other algorithms, underscored by its capacity to uncover a diverse array of non-dominated solutions. To delve deeper into the experimental results, statistical analysis employing Friedman’s rank test is employed. The solutions generated and the convergence patterns exhibited by the MOCO approach underscore its exceptional proficiency in resolving intricate design problems. [ABSTRACT FROM AUTHOR]

Anatomic patellar components for total knee arthroplasty (TKA) have demonstrated favorable in vivo kinematics. A novel failure mechanism in TKA patients with an anatomic patellar component was observed prompting an investigation to identify patient- and implant-related factors associated with suboptimal performance. A retrospective evaluation was performed comparing 100 TKA patients with an anatomic patellar component to 100 gender-, age-, and body mass index–matched patients with a medialized dome component. All surgeries were performed with the same posterior-stabilized TKA system with minimum of 1-year follow-up. Several radiographic parameters were assessed. A separate computational evaluation was performed using finite-element analysis, comparing bone strain energy density through the patella bone remnant. Patients with an anatomic patellar component had significantly higher rates of anterior knee pain (18 versus 2%, P <.001), chronic effusions (18 versus 2%, P <.001), and superior patellar pole fragmentation (36 versus 13%, P <.001) compared to those with a dome component. Radiographically, the anatomic group demonstrated more lateral patellar subluxation (2.3 versus 1.1 mm, P <.001) and lateral tilt (5.4 versus 4.0 mm, P =.013). Furthermore, there were more revisions in the anatomic group (7 versus 3, P =.331). On computational evaluation, all simulations demonstrated increased bone strain energy density at the superior patellar pole with the anatomic patella. Resection thickness <13 mm resulted in over 2-fold higher strain energy density, and negative resection angle of 7° resulted in 6-fold higher superior pole strain energy. Patients with an anatomic patellar component showed higher rates of anterior knee pain, chronic effusion, and superior pole fragmentation compared to patients with a dome patella, with higher superior patellar pole strain energy confirmed on computational evaluation. Avoiding higher resection angles and excessive patellar resection may improve the performance and survivorship of the anatomic patella. [ABSTRACT FROM AUTHOR]

Copyright of Comparative Literature / Primerjalna Književnost is the property of Slovenian Comparative Literature Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The dynamics of plant-herbivore interactions are essential for understanding ecosystem stability and resilience. This article investigated the effects of incorporating a harvesting effect on the dynamics of a discrete-time plant-herbivore system. An analysis was performed to determine the existence and stability of fixed points. In addition, studies have shown that the system experienced transcritical, period-doubling, and Neimark-Sacker bifurcations. Moreover, we provided numerical simulations to substantiate our theoretical results. Our research indicated that harvesting in excessive amounts may have negative effects on the populations of both plants and herbivores. However, when harvesting was done at moderate levels, it promoted the coexistence and stability of both populations. The findings of our analysis provided a deep understanding of the intricate dynamics of ecological systems and underscored the need to use sustainable harvesting methods for the management and preservation of ecosystems. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industrial applications in domains such as warm rolling, crystal development, thermal extrusion and optical fiber illustration are seeing a significant increase. These applications specifically focus on addressing the challenge of a cylinder in motion inside a fluid environment. Elevated temperatures may affect the viscosity and thermal conductivity of fluids. Understanding the relationship between temperature and the properties of fluids is crucial. In light of these presumptions, the primary goal of this study is to examine, under transverse magnetic field, shape factor, velocity, thermal slip conditions and viscous dissipation, how temperature-dependent fluid properties could enhance the heat transfer efficiency and performance evolution of ternary hybrid nanofluid. In order to study flow fluctuations, the impact of nanoparticle addition and improvements in heat transfer, a variable Prandtl number is also included. The use of similarity variables converts the controlling flow model from partial differential equations (PDEs) to ordinary differential equations (ODEs). Mathematica’s shooting strategy solves ODEs using the fourth-order Runge–Kutta (RK-IV) method. Numerical calculations were done after setting parameters to acquire the desired results. Analytical data are provided in tables and graphs for convenient usage. The results showed that the velocity profile increases as the values of ϕ3, Pr, M, Re and S grow, and decreases when the values of θr decrease. Re, Pr and S lower the temperature profile, whereas ϕ3, θr and Ec raise it. The skin friction profile steepens as ϕ3, S, Re and M increase relative to the stretched cylinder, and flattens as θr and ω decrease. The Nusselt number profile rises as θr, Pr, S and Re decrease with ϕ3, Ec and δ. When the Prandtl number goes from 3.0 to 6.2 in a ternary hybrid nanofluid with brick-shaped nanoparticles, the Nusselt number goes up by around 55.7%. [ABSTRACT FROM AUTHOR]

Introduction: Capsicum species are known in food and trado-medicinal uses for maladies management due their rich content of phytochemicals, but with little work done on in silico bioprospection of its volatilome. Objectives: This study targeted chemometric profiling, virtual bioprospection of potential lead metabolites in 2 Capsicum annuum L. fruit variants' (green and red) to identify lead gyrase B inhibitors (GBIs) and provide new mechanistic insights. Methods: Metabolites were profiled using Gas Chromatography-Mass Spectrometry (GC-MS), and quantitative phytochemical assays. Extracts antioxidant (DPPH, ABTS, FRAP) and antibacterial (susceptibility testing) activities were also determined. In silico [docking, pharmacokinetics, DFT] analyses were used to identify and predict chemical features of potential lead GBIs key to extracts molecular mechanism of action. Results: Mass spectral analysis identified hydrocarbons, fatty acid and other derivatives. Quantitative phytochemical analysis showed flavonoids, cardiac glycosides and alkaloids. The green C. annuum extract had better antioxidative action, while extracts of both green and red variant showed similar antimicrobial profiles against resistant bacterial pathogens. In silico highest docking scores were observed for [1-Ethyloctyl) cyclohexane (-6.6 kcal/mol)] and dibutyl phthalate (-6.4 kcal/mol). All lead GBIs had desirable pharmacokinetics in line with the Lipinski rule of 5, and chemical reactivity properties. Conclusion: In silico and in vitro methods combination provided robust metabolomic profiling. The identified lead C. annuum-based natural GBIs contribute to the bioactivity profile and molecular mechanism of action of fractions. The study provided a first-hand report on natural GBIs derivable from Capsicum fruits which could be exploited in formulations for non-food and pharmaceutical applications. [ABSTRACT FROM AUTHOR]

Cistus ladanifer L. is an aromatic and resinous perennial shrub commonly used in Moroccan folk medicine against a range of illnesses including skin problems, diabetes, diarrhea, and inflammation. The current investigation aims to determine the bioactive compounds of C. ladanifer essential oil (CL-Eo) extracted by microwave-assisted hydrodistillation and their biological properties using in vitro and molecular docking approaches. The GC-MS analysis identified linderol (17.76%), gamma-terpinene (17.55%), and borneol (13.78%) as main bioactive compounds. CL-Eo significantly inhibited α-amylase (IC50 = 0.41 ± 0.009 mg/mL), α-glucosidase (IC50 = 0.49 ± 0.002 mg/mL) and lipase (IC50 = 0.45 ± 0.004 mg/mL) enzymes. Moreover, CL-Eo showed significant hemoglobin glycation as well as antioxidant capacity as indicated by DPPH, ABTS, Frap and beta-carotene tests. The antimicrobial evaluation used disc-diffusion and microdilution tests in vitro. The results showed that CL-Eo had significant antibacterial activity, particularly against P. mirabilis (17.16 ± 1.04 mm), and moderate effects against L. innocua (13.48 ± 1.65 mm) and E. coli (12.47 ± 0.61 mm). In addition, it demonstrated potent antifungal activity against C. albicans (18.01 ± 0.91 mm) and C. tropicalis (16.45 ± 0.32 mm). The MIC and MBC tests provided confirmation that CL-Eo exhibited potent growth inhibition. The MIC ranged from 0.25 to 8.0% v/v and the MBC or MFC ranged from 0.25 to 16.0% v/v Eo. The tolerance level ratio showed bactericidal and fungicidal effects against tested microbial strains in varying degrees. According to these data, CL-Eo might be suggested as a promising candidate for drug development, specifically for combating candidiasis and diabetes. [ABSTRACT FROM AUTHOR]

The grasses are one of the most diverse plant families on Earth. However, their classification and evolutionary history are obscured by their pollen stenopalynous (similar) morphology. A combination of high‐resolution imaging of pollen surface ornamentation and computational analysis has previously been proposed as a promising tool to classify grass taxonomic boundaries. In this study, we test this hypothesis by studying Poaceae pollen across the phylogeny from plants collected in northern South America and also from published literature across the globe. We assessed if morphotypes that we establish using descriptive terminology are supported by computational analysis, if they vary along six (a)biotic variables and vary across the phylogeny. Based on this analysis, we constructed a reference framework for pollen surface ornamentation morphotypes. Our results showed that there is a wide variation of grass pollen surface ornamentation. We identified nine new and confirmed six known morphotypes, establishing a data set for 223 species (243 individual plant specimens) that represent 11 subfamilies. Computational analysis showed that our morphotypes are well‐supported by two quantitative features of pollen sculptural elements (size and density). The specific data set and mapping of the phylogeny confirmed that pollen morphological sculpture is unrelated to (a)biotic variables and is diverse across the phylogeny. [ABSTRACT FROM AUTHOR]

Our study delves into the dynamics of a convective Magneto-Hydrodynamic Bioconvective Nanofluid model (MHD-BCNFM) flowing over a convectively heated stretched sheet. To accomplish this, we utilize the distinctive capabilities of the Supervised Stochastic Approach for Computational Analysis (SSACA). By integrating similarity transformations, we convert the partial differential equations (PDEs) governing the system into coupled ordinary differential equations (ODEs). We generate the dataset for our approach using the Adam numerical technique specifically tailored for the (MHD-BCNFM). Achieving this involves systematic modulation of parameters such as λ , bioconvection Péclet number P e , Bioconvection constant σ , Brownian motion parameter N b , and thermophoresis parameter N t. "Moreover, we utilize a reference dataset to compute numerical values of various physical quantities in the (MHD-BCNFM) employing SSACA-based Artificial Intelligence methods. The effectiveness of our devised SSACA approach is demonstrated by a negligible mean squared error, ranging from approximately 10−8 to 10−10. Histograms exhibit a maximum error range of 10−5, closely aligning with optimal correlation/regression measures. Outstanding performance metrics in terms of Mean Squared Error (MSE) are attained at levels such as l 9.93E−12, 1.07E−11, 6.28E−10, 1.43E−11, 2.09E−09, 3.65E−11, 2.97E−11, and 2.80E−13 against 320, 430, 209, 85, 356, 295, 66, and 136 epochs. A comparative study between the proposed and reference datasets underscores the authenticity and precision of SSACA, supported by error analyses ranging from E-05 to E-09 across all scenarios. [ABSTRACT FROM AUTHOR]

The dynamics of plant-herbivore interactions are essential for understanding ecosystem stability and resilience. This article investigated the effects of incorporating a harvesting effect on the dynamics of a discrete-time plant-herbivore system. An analysis was performed to determine the existence and stability of fixed points. In addition, studies have shown that the system experienced transcritical, period-doubling, and Neimark-Sacker bifurcations. Moreover, we provided numerical simulations to substantiate our theoretical results. Our research indicated that harvesting in excessive amounts may have negative effects on the populations of both plants and herbivores. However, when harvesting was done at moderate levels, it promoted the coexistence and stability of both populations. The findings of our analysis provided a deep understanding of the intricate dynamics of ecological systems and underscored the need to use sustainable harvesting methods for the management and preservation of ecosystems.

This article is a commentary on "Are The Beatles Different? A Computerized Psychological Analysis of Their Music," by North and Krause (2023), in which they analyze features extracted from the Spotify API and ultimately claim that The Beatles' music is statistically "innovative" compared to other music. In this commentary, I explore potential methodological issues with some of their analyses. Chiefly, I show that applying their analysis to other artists results in similar results in most cases. I conclude that The Beatles' innovativeness, whether real or imaginary, cannot be statistically determined from Spotify's acoustically derived features.

Abstract Alzheimer’s disease (AD) prevalence is twice as high in non-Hispanic Blacks (NHBs) as in non-Hispanic Whites (NHWs). The objective of this study was to determine whether aberrant methylation at imprint control regions (ICRs) is associated with AD. Differentially methylated regions (DMRs) were bioinformatically identified from whole-genome bisulfite sequenced DNA derived from brain tissue of 9 AD (5 NHBs and 4 NHWs) and 8 controls (4 NHBs and 4 NHWs). We identified DMRs located within 120 regions defined as candidate ICRs in the human imprintome ( https://genome.ucsc.edu/s/imprintome/hg38.AD.Brain_track ). Eighty-one ICRs were differentially methylated in NHB-AD, and 27 ICRs were differentially methylated in NHW-AD, with two regions common to both populations that are proximal to the inflammasome gene, NLRP1, and a known imprinted gene, MEST/MESTIT1. These findings indicate that early developmental alterations in DNA methylation of regions regulating genomic imprinting may contribute to AD risk and that this epigenetic risk differs between NHBs and NHWs.