Types Of Clusters Research Articles

Role of anoikis-related gene RAC3 in prognosis, immune microenvironment, and contribution to malignant behavior in vitro and in vivo of bladder urothelial carcinoma

BackgroundAnoikis disrupts the normal apoptotic process in cells, leading to abnormal proliferation and migration, thereby promoting tumor formation and development. However, the role of anoikis in bladder urothelial carcinoma (BLCA) still requires further exploration.MethodsAnoikis-related genes (ARGs) were retrieved from the GeneCards and Harmonizome databases to distinguish various subtypes of BLCA and develop a predictive model for BLCA. The immune microenvironment and enrichment pathways between various subtypes were also analyzed using consensus clustering. Potential medications were screened by utilizing drug sensitivity analysis. In vitro and vivo, the character of the independent prognostic gene in BLCA was confirmed through cell studies and mouse xenograft models.ResultsOne hundred thirty differentially expressed genes (DEGs) were identified, and nine of them were chosen to construct predictive models that can accurately forecast the prognosis of BLCA patients. K = 2 was correctly identified as the optimal clustering type for BLCA, showing prominent differences in survival rates between the two subgroups. The immune-related functional studies manifested that the two subtypes’ immune cell expressions differed. It was verified that RAC3 is an independent prognostic gene for BLCA. RAC3 shows high expression levels in BLCA, as indicated by its consistent mRNA and protein levels across different gene expressions. The functional verification results of RAC3 in BLCA showed that silencing RAC3 can significantly inhibit BLCA cell proliferation, colony formation, and migration. RAC3 knockdown inhibited the growth and migration of BLCA in vivo. SB505124 exhibited a significant inhibitory effect on the proliferation of BLCA cells.ConclusionBased on the predictive model developed in this study, BLCA patients’ prognoses can be accurately predicted. SB505124 could become an important drug in the treatment of BLCA patients. RAC3 is essential in prognosis, immune microenvironment, and malignant behavior of BLCA in vitro and in vivo. It will also offer the potential for personalized treatment for BLCA patients and generate new research avenues for clinical investigators.

Spatial Distribution Characteristics and Driving Factors of 777 Traditional Villages in Yunnan Province: A Study Based on GWR Model and Geodetector

Traditional villages (TVs) are clusters for the conservation of farming civilization heritage with multiple values. Studying their spatial distribution and driving mechanisms is conducive to formulating conservation and development strategies. In this study, 777 TVs in Yunnan Province were examined. Spatial analysis methods such as the nearest neighbor index (NNI), kernel density estimation (KDE), and Moran’s I were used to investigate their spatial distribution patterns. Twelve driving factors were selected from natural, spatial, social, and cultural aspects. The driving mechanisms affecting the distribution of TVs were explored by employing the geographically weighted regression (GWR) model and Geodetector combined with mathematical and statistical methods to systematically study the spatial autocorrelation and heterogeneity of TVs in Yunnan. The results of this study indicate that: (1) The 777 TVs in Yunnan Province are evidently clustered in the overall distribution, presenting a contiguous and concentrated distribution pattern of “3 high-density areas + multiple medium-density belts”. However, the distribution of TVs is unbalanced. The spatial distribution is significantly positively correlated globally, and there exist three types of clustering in local areas. (2) The spatial layout of TVs in Yunnan Province is jointly influenced by multiple factors, with obvious spatial heterogeneity. Regional cultural factors are the key ones. TVs tend to be distributed in areas with medium–high elevation, flat slops, sunny slopes, moderate precipitation and temperatures, and a certain distance from water sources and roads. A large number of TVs are distributed in areas with a high proportion of ethnic minorities. (3) The main factors affecting the distribution of national-level TVs in Yunnan are intangible cultural heritage, cultural relic protection units, followed by factors such as transportation, slope, and elevation. The interaction between intangible cultural heritage (X11) and cultural relic protection units (X12) reveals the strongest interactive driving force. This study reveals the diverse characteristics of the spatial distribution of national-level TVs in Yunnan and their influencing mechanisms, which can provide a scientific decision-making basis for the future protection and development of TVs in Yunnan and guide the sustainable development of TV cultural heritage clusters.

Fathers’ Parenting Stress and Participation Based on Perfectionism

This study aims to identify the cluster distribution of perfectionism among fathers by categorizing them according to their perfectionism type and analyzing the differences between different fathers' parenting stress and involvement. The study targeted 321 pairs of parents with infants aged 4 and 5 years old. Data was collected by distributing questionnaires via mobile device. The collected data was tested for reliability and correlation using reliability analysis and inferential correlation analysis. After that, a K-means cluster analysis was conducted to categorize the perfectionism types of fathers. From there, an analysis of the covariance was conducted to test the differences between parenting stress and involvement according to the categorized cluster types. As a result, Korean fathers were categorized into perfectionist, non-perfectionist, and eclectic perfectionist groups according to the characteristics of each cluster type. The results showed that fathers with high levels of perfectionism were more sensitive to parenting stress, while non-perfectionist fathers experienced lower parenting stress and were more involved in parenting. These findings may have implications for modern society's emphasis on the role of fathers when it comes to co-parenting.

An Accurate Construction Method of E-commerce User Profile Based on Artificial Intelligence Algorithm and Big Data Analysis

User’s basic attributes, behavior characteristics, value attributes, social attributes, interest attributes, psychological attributes, and other factors will lead to poor user experience, information overload, interference, and other negative effects. In order to develop more accurate marketing strategies, optimize user experience, and improve the conversion rate and user satisfaction of e-commerce platforms, an accurate construction method of e-commerce user profile based on artificial intelligence algorithm and big data analysis is proposed. Based on big data analysis technology, the basic attributes, behavior characteristics, value attributes, social attributes, interest attributes, and psychological attributes of e-commerce users are collected and integrated from multiple dimensions. The improved sequential pattern mining algorithm (PBWL) is applied to mine the frequent sequential pattern in the e-commerce user behavior, and to reveal the user’s behavior habit. The comprehensive attribute representation of e-commerce users is obtained by combining the LINE network model and the convolutional neural network. The firefly K-means clustering algorithm is used to cluster the e-commerce users, group the users based on the similarity of user attribute information, create different types of user clusters, and achieve the accurate construction of an e-commerce user profile. The experimental results show that this method can build an accurate e-commerce user profile and provide strong support for personalized recommendation and precision marketing of e-commerce platforms. This method can dig deeply into the behavior habits of e-commerce users and accurately reflect their interest preferences and consumption characteristics. This method can quickly and stably cluster e-commerce users, and the clustering effect of user profiles is optimal. This method can also divide the data into meaningful groups according to the user’s consumption behavior, and reveal the characteristics and values of different groups.

Data-driven insights: Unravelling traffic dynamics with k-means clustering and vehicle type differentiation

Data-driven insights: Unravelling traffic dynamics with k-means clustering and vehicle type differentiation

Optimizing Si─O Conjugation to Enhance Interfacial Kinetics for Low-Temperature Rechargeable Lithium-Ion Batteries.

With the growing demand for high-voltage and wide-temperature range applications of lithium-ion batteries (LIBs), the requirements for electrolytes have become increasingly stringent. While fluorination engineering has enhanced the performance of traditional solvent systems, it has also raised concerns regarding cost, environmental hazards, and low reduction stability. Through strategic molecular bond design, a novel class of low-temperature (LT) solvents-siloxanes-is identified, meeting the demands of LT and high-voltage applications in LIBs. The d-p conjugation of the Si─O bond enhances voltage resistance and weakens the Li+-solvent interactions. By modulating the number of Si─O conjugated bonds, the type of anion clusters in the solvation structure can be controlled, ultimately leading to the formation of a LiF and Si─O-rich interfacial layer and facilitating rapid Li+ conduction. Consequently, the graphite||NCM811 pouch cell (2.3 Ah, 4.45 V) with a siloxane-based electrolyte retains 75.1% of room temperature capacity (RTC) at -50°C. The rapid interface kinetics allow a superior reversible charging capacity retention of 67.6% at -40°C, with good cycle stability at -20°C. This study provides new insights into solvent design to fortify LIB performance in harsh conditions.

Methicillin-Resistant S. aureus Carrying the PVL and Toxic Shock Syndrome Toxin in Healthy Dogs in Algeria.

Background/Objectives: Staphylococcus aureus and Staphylococcus pseudintermedius are major opportunistic pathogens in both humans and dogs. In pets, the dissemination of methicillin-resistant isolates (MRSA or MRSP) is problematic for the treatment of animals and is a public health issue due to their zoonotic potential. MRSA and MRSP may also harbor virulent genes that increase their dangerousness. This study aimed to assess the prevalence of (MR)SA and (MR)SP in healthy dogs and their owners in Algeria. Methods: Swabs were collected from various body sites of healthy dogs (n = 88) and from the nose of their owners (n = 38). Antimicrobial susceptibility testing was performed by antibiograms according to the disc diffusion method, and clonality was assessed using Pulsed-Field Gel Electrophoresis (PFGE). All methicillin-resistant isolates were short-read whole-genome sequenced using the Illumina technology. Results: 26 S. aureus and 17 S. pseudintermedius isolates were respectively collected from 13 dogs (13/88, 14.8%). No MRSP isolate was detected, while MRSA was found in six dogs (6.8%). Isolates belonged to ST1 (n = 3), ST 80 (n = 1), and ST 22 (n = 2, including the single-locus variant ST7118). All MRSA displayed the immune evasion cluster (IEC) type E. The ST80 isolate presented the Panton-Valentine toxin, and the ST22/ST7118 isolates carried the tst gene coding for the toxic shock syndrome toxin. Conclusions: The epidemiology of MRSA in healthy Algerian dogs mirrors the one in Algerian people. This poses a zoonotic and public health concern due to the virulence and resistance genes displayed by these isolates. Our results indicate the need for developing One Health strategies to avoid a large-scale dissemination of MRSA in Algerian dogs.

Кластерне управління проєктами: підходи, виклики та перспективи

The article examines cluster project management as a modern innovative approach to organizing and coordinating projects. It establishes that cluster management is based on the consolidation of interrelated projects into clusters for the joint use of resources, enhancing the efficiency of innovative potential utilization, and stimulating innovation. Cluster management allows for resource optimization, improved communication, the development of synergy between projects, and decision-making flexibility. The article analyzes the main types of clusters, including geographical, sectoral, vertical, and horizontal, and their impact on the success of project management and the productivity of individual projects. It also discusses the key advantages of cluster management, including resource optimization, improved coordination among participants, increased overall productivity, and flexibility. The study reveals that the cluster approach helps reduce costs, avoid duplication of efforts, promotes rapid market response, and allows organizations to effectively adapt to market challenges. In addition to the advantages, the article highlights the challenges organizations face when applying the cluster approach. These include the need to adapt to external changes, competition among cluster participants, and intellectual property protection, which can pose a threat to innovation. A new approach to cluster project management is proposed, which integrates vertical and horizontal clusters with modern digital technologies, such as monitoring and management tools. This approach enhances the effectiveness, resilience, and innovativeness of projects in the context of globalization and digitalization. The article also explores successful examples of clusters, such as the Silicon Valley technology cluster and the California wine cluster, which illustrate the benefits of collaboration within a cluster system. The article emphasizes the importance of flexibility and continuous updating of management methodologies to ensure the success of clusters in today's competitive environment.

Machine Learning in Genomics: Applications in Whole Genome Sequencing, Whole Exome Sequencing, Single-Cell Genomics, and Spatial Transcriptomics

The application of machine learning (ML) to genomics has transformed the process of analyzing and interpreting large-scale, complex datasets, leading to important breakthroughs in our knowledge of biological systems. This review provides a comprehensive overview of ML applications in key genomic areas: Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), single-cell genomics, and spatial transcriptomics. In WGS and WES, ML techniques are employed for variant calling, genome-wide association studies, rare variant analysis, and the prediction of pathogenicity. In single-cell genomics, ML facilitates clustering, trajectory inference, and cell type identification, while in spatial transcriptomics, it aids in deciphering spatial patterns of gene expression and tissue heterogeneity. This review further explores the application of ML in related omics fields, including proteomics, transcriptomics, metagenomics, epigenomics, and microbiome research. These applications encompass protein structure prediction, functional annotation, microbial community profiling, and the analysis of epigenetic modifications. We address the challenges caused by high dimensionality, variability in the data, and the requirement for interpretable machine learning models when dealing with genomic data. Emerging technologies like explainable AI and federated learning are highlighted for their potential to address these challenges. Additionally, the review addresses ethical considerations, data privacy issues, and the necessity for standardized protocols in ML applications. This comprehensive examination underscores the transformative impact of ML in genomics and highlights its potential to drive future innovations in personalized medicine and biological research.

The Impact of Vocabulary Clustering on Facilitating Vocabulary Development Among Saudi EFL Learners

The current study sought to investigate how organizing new vocabulary through semantic, ‎thematic, or unrelated sets could affect the learning process among Saudi EFL learners. The ‎majority of EFL teachers and materials writers seem to introduce and cluster new words according to a ‎particular type of semantic relationship (e.g., vegetables, body organs, car parts, or house parts) or a thematical relationship (e.g., a hotel room reservation, visiting a doctor's clinic, going to the post office, or at the train station). ‎Participants in the current research were 149 EFL students from the Preparatory Year Program (PYP) at Al-Imam Mohammad Ibn Saud Islamic University (IMISIU), Riyadh, Saudi Arabia. The design of this study was a pretest-treatment and posttest-delayed post-test. Two ‎types of clustering of new vocabulary were explored: semantically related sets and semantically ‎unrelated sets, which were constructed to identify how organizing new vocabulary could affect ‎the learning process among Saudi EFL learners. The findings of the study showed that both semantically ‎related (SR) and semantically unrelated (SU) sets ‎ seemed to help in learning new words. Nonetheless, ‎those new words behaved differently one week after the treatment. Moreover, the SR group scored significantly better on both delayed tests than ‎their ‎counterparts. Furthermore, the study's outcomes failed to indicate any interfering effect of ‎teaching and studying semantically relevant terms simultaneously in an actual classroom setting.‎ This study concluded with recommendations for teaching and learning programs to ‎develop ‎students' conceptual understanding of organizing new vocabulary that affects the learning ‎process among Saudi EFL learner’s context.‎

Molecular Characterization of Multidrug-Resistant and Hypervirulent New Delhi Metallo-Beta-Lactamase Klebsiella pneumoniae in Lazio, Italy: A Five-Year Retrospective Study.

Antimicrobial resistance represents a challenge to public health systems because of the array of resistance and virulence mechanisms that lead to treatment failure and increased mortality rates. Although for years the main driver of carbapenem resistance in Italy has been the Klebsiella pneumoniae KPC carbapenemase, recent years have seen an increase in VIM and NDM metallo-beta-lactamases (MBLs). We conducted a five-year survey of New Delhi Metallo-beta-Lactamase (NDM)-producing Klebsiella pneumoniae (NDM-Kpn) clinical isolates from the Lazio region, Italy; the study aimed to elucidate the molecular mechanisms underpinning their resistant and virulent phenotype. Antimicrobial susceptibility was evaluated by automated systems and broth microdilution. In silico analysis of acquired resistance and virulence genes was performed using whole-genome sequencing (WGS), molecular typing through MLST, and core genome multi-locus sequence typing (cgMLST). A total of 126 clinical NDM-Kpn isolates were collected from 19 distinct hospitals in the Lazio region. Molecular analysis highlighted the existence of NDM-1 (108/126) and NDM-5 (18/126) variants, 18 Sequence Types (STs), and 15 Cluster Types (CTs). Notably, 31/126 isolates displayed a virulence score of 4, carrying ybt, ICEKp, iuc, and rmp genes. This study identified a variety of NDM-Kpn STs, mainly carrying the blaNDM-1 gene, with a significant number linked to high-risk clones. Of these isolates, 24.6% showed high-level resistance and virulence, emphasizing the risk of the spread of strains that combine multi-drug-resistance (MDR) and virulence. Proactive surveillance and international collaborations are needed to prevent the spread of high-risk clones, as well as further research into new antimicrobial agents to fight antibiotic resistance.

Identifying the pattern of shallow groundwater hydrochemistry and its driving factors in a typical estuarine delta of Poyang Lake watershed, China: Insights into water quality assessment

Study regionA typical estuarine delta of Gan−Xiu River within Poyang Lake watershed, situated in the north of Jiangxi Province, China Study focusAlthough groundwater is considered as a crucial water resource for social development and public health, it presents significant challenges in preventing the deterioration of groundwater quality in the seasonal floodplain regions. Hence, this study focuses on the spatiotemporal variations of ionic concentrations of shallow groundwater in an estuarine delta of Gan-Xiu River in Poyang Lake watershed, which is greatly complicated by complex hydrological regimes and intensive anthropogenic activities such as cropland fertilizer. The potential factors controlling the ionic concentrations were identified using self-organizing map clustering and Piper diagram approaches. Moreover, the overall water quality of shallow groundwater was assessed according to the ionic compositions. New hydrological insights for the region(1) Shallow groundwater chemistry was influenced by weathering silicate and carbonate from ionic and Gibbs plots, which is highly associated with the distribution of the carbonate rock fissure-karst aquifer in the study region. (2) The contribution of groundwater to river water varied from 53.2 % to 71.5 % via isotopic analysis, suggesting that groundwater dominate the component of river water. (3) Most samples from cluster types are suitable for drinking and irrigation use except for sites from Cluster 6, which were characterized by the higher concentrations of Cl−, NO3− and SO42−.

XMM-SERVS X-ray extended Galaxy Cluster (XVXGC) catalog

Context. To explain the well-known tension between cosmological parameter constraints obtained from the primary cosmic microwave background (CMB) and those drawn from X-ray-selected galaxy cluster samples identified with early data, we propose a possible explanation for the incompleteness of detected clusters being higher than estimated. Specifically, we suggest that certain types of galaxy groups or clusters may have been overlooked in previous works. Aims. We aim to search for galaxy groups and clusters with especially extended surface brightness distributions by creating a new X-ray-selected catalog of extended galaxy clusters from the XMM-Spitzer Extragalactic Representative Volume Survey (XMM-SERVS) data, based on a dedicated source detection and characterization algorithm optimized for extended sources. Methods. Our state-of-the-art algorithm is composed of wavelet filtering, source detection, and characterization. We carried out a visual inspection of the optical image, and spatial distribution of galaxies within the same redshift layer to confirm the existence of clusters and estimated the cluster redshift with the spectroscopic and photometric redshifts of galaxies. The growth curve analysis was used to characterize the detections. Results. We present a catalog of extended X-ray galaxy clusters detected from the XMM-SERVS data. The XMM-SERVS X-ray eXtended Galaxy Cluster (XVXGC) catalog features 141 cluster candidates. Specifically, there are 53 clusters previously identified as clusters with intracluster medium (ICM) emission (class 3); 40 that were previously known as optical or infrared (IR) clusters, but detected as X-ray clusters for the first time (class 2); and 48 identified as clusters for the first time (class 1). Compared with the class 3 sample, the “class 1 + class 2” sample is systematically fainter and exhibits a flatter surface brightness profile. Specifically, the median flux in [0.5–2.0] keV band for “class 1 + class 2” and class 3 sample is 1.288 × 10−14 erg/s/cm2 and 1.887 × 10−14 erg/s/cm2, respectively. The median values of β (i.e., the slope of the cluster surface brightness profile) are 0.506 and 0.573 for the “class 1 + class 2” and class 3 samples, respectively. The entire sample is available at the CDS.

Clustering Universities According to Performance Indicators and Determination of Organizational Culture Types in Clusters

This study aims to reveal the organizational culture types of state universities in Kazakhstan, to define the dominant organizational culture type and to interpret the organizational culture types in terms of performance indicators. In order to achieve this goal, statistical data collected from 29 state universities were classified using hierarchical cluster analysis and Ward’s Technique. In this context, firstly, the concept of organizational culture and its effects on organizational performance were explained in the light of literature information, then cluster analysis was conducted on universities in terms of institutional size and performance. In addition, since a data-oriented approach was preferred in this study, universities were classified based on objective data instead of predetermined criteria. Finally, SPSS 22.0 program and Organizational Culture Assessment Tool were used to analyze the validity of the obtained data and the relationships between the variables, and as a result, the organizational culture types of universities were revealed, the dominant organizational culture type among them was determined and suggestions were given based on empirical findings in the study. It is expected that the results of this study will bring different perspectives on the effect of organizational culture on performance indicators in state universities in Kazakhstan.

Microscopic Remaining Oil Classification Method and Utilization Based on Kinetic Mechanism

In reality, the remaining oil in the ultra-high water cut period is highly dispersed, so a thorough investigation is required to understand the microscopic remaining oil. This will directly influence the technological direction and allow for countermeasures such as enhanced oil recovery (EOR). Therefore, this study aims to investigate the state, classification method and utilization mechanism of the microscopic remaining oil in the late period of the ultra-high water cut. To achieve this, the classification of microscopic remaining oil based on mechanical mechanism was developed using displacement CT scan and micro-scale flow simulation methods. Three carefully selected mechanical characterization parameters were used: oil–water connectivity, oil–mass specific surface and oil–water area ratio. These give five types of microscopic remaining oil, which are as follows: A (capillary and viscous oil cluster type), B (capillary and viscous oil drop type), C (viscous oil film type), D (capillary force control throat type), and E (viscous control blind end type). The state of the microscopic remaining oil in classified oil reservoirs was defined after high-expansion water erosion. Based on micro-flow simulation and analysis of different forces during the displacement process, the main microscopic remaining oil recognized is in class-I, class-II and class-III reservoirs. Within the Eastern sandstone oilfields in China, the ultra-high water-cut stage is a good indicator that the class-I oil layer is dominated by capillary and viscous oil drop types distributed in large connected holes. The class-II oil layer has capillary and viscous force-controlled clusters distributed in small and medium pores with high connectivity. In the case of the class-III oil layer, it enjoys the support of capillary force control throats that are mainly distributed in small holes with high connectivity. Integrating mechanisms of different types of micro-remaining oil indicates that, enhancing utilization conditions requires increasing pressure gradient and shear force while reducing capillary resistance. An effective way to improve the remaining oil utilization is to increase the pressure gradient and change the flow direction during the water-drive development process. Hence, this forms a theoretical basis and a guide for the potential exploitation of remaining oil. Likewise, it provides a strategy for optimizing enhanced oil recovery in the ultra-high water-cut stage of mid-high permeability oil reservoirs worldwide.

Politics of International Oil Companies (IOCs): Understanding PETRONAS Carigali Nile Ltd Exit From South Sudanese Oilfields

The study has examined the politics of the International Oil Companies (IOCs), the case study of PETRONAS Carigali Nile Ltd. It does this by appraising the legal violations of PETRONAS Carigali Nile Ltd exit and farming out from South Sudanese oilfields. The study explains the politics of IOCs and particularly, PETRONAS Carigali Nile Ltd as dependent variable and independent variables such as legal violations of Petronas Carigali Nile Ltd, types of residual liabilities and responsibility of these liabilities.The study was subjected to stringent empirical literature review and the gaps in the literature were filled through fieldwork. During fieldwork, the methodology of research tools and instruments such as questionnaires and interview guides/schedules were deployed with target of 52 respondents. Persuasive and cluster type of sampling amongst the senior staff of Ministry of Petroleum (MOP), Nile Petroleum Corporation (NILEPET), Dar Petroleum Operating Company (DPOC), Sudd Petroleum Operating Company (SPOC) and Greater Pioneer Operating Company (GPOC) were applied. The study findings indicate that PETRONAS Carigali Nile Ltd has politicized and violated sections 12, 22, 23, 24, 41 & 42 of the Petroleum Act 2012. Various types of liabilities such as cost recovery audits, environmental audit, petroleum taxes, surface rentals, and cash calls should be taken care off by Petronas Carigali Nile Ltd or by a company that farms into its shares. While the study concludes that PETRONAS Carigali Nile Ltd exit and farming out has been politicized and violated the laws of the Republic of South Sudan, the study recommends that the Ministry of Petroleum should be held responsible for all the legal violations Petronas Carigali Nile Ltd have committed in South Sudan without any action. Whether Savannah Energy Ltd farms into Petronas Carigali Nile Ltd shares or not after the PETRONAS has exited, consequences should be rolled out for such violations so that no any other IOC can do it again in the near future in this volatile oil and gas industry.

Short and medium range order in the rapidly solidified metallic liquid Ta: Atomic packing, connection modes, and pressure effect

In this study, molecular dynamics (MD) simulations were utilized to explore the Short and Medium-Range Order (MRO) in the rapidly solidified metallic liquid tantalum (Ta). Radial distribution function (RDF) and Voronoi tessellation analysis (VTA) techniques were employed to thoroughly explore the effect of pressure on the connectivity and structural properties at the Short-Range Order (SRO) and MRO levels. Our findings indicate that, at a quenching rate of 1013 K s-1, glassy states are achieved at or below 20 GPa, while crystalline phases emerge at 25 GPa. VTA analysis indicates a significant alteration in the local structure of glassy Ta with increasing pressure. Specifically, the fraction of icosahedral-like clusters decreases while the fraction of crystal-like clusters rises notably.Furthermore, we highlight that icosahedral-like clusters strongly tend to form 3-atom connection mode, while crystal-like clusters prefer 2-atom and 4-atom connection modes. Notably, icosahedral-like clusters are identified as the primary contributors to the emergence of the left sub-peak in the second peak of the RDF. In contrast, all cluster types contribute to the appearance of the right sub-peak.

Downregulation of ferroptosis-related ATF3 alleviates lupus nephritis progression

BackgroundThe role of ferroptosis in lupus nephritis (LN) is unclear. This study aimed to explore the effects of ferroptosis-related genes in LN through bioinformatics prediction and experimental validation. MethodsSample data were collected from the GEO dataset and divided into glomeruli and tubulointerstitium. We collected 382 ferroptosis-related genes. The intersection of ferroptosis-related genes with glomeruli and tubulointerstitium data, respectively, was performed. Machine learning methods (including unsupervised cluster typing and random forests) were operated to identify ferroptosis subtyping and ferroptosis important genes in LN. Immune infiltration and functional analysis were performed. The expression of ferroptosis important gene ATF3 was validated in vivo and in vitro. Results6 ferroptosis important genes common to glomeruli and tubulointerstitium were screened, including ATF3, CD44, CYBB, JUN, NCF2, and NNMT. ATF3 decreased in the LN group compared to the Control. Silencing ATF3 mitigated LPS/erastin-induced ferroptosis. Functional analysis showed that ATF3 was markedly enriched in the interferon-gamma-mediated signaling pathway, ECM-receptor interaction, and cell adhesion. In glomeruli, T cells regulatory (Tregs) infiltration decreased and Macrophages M1 levels increased with elevated ATF3 expression. Levels of immune cell infiltration were altered in different ferroptosis subtypes of LN glomeruli and tubulointerstitium. ConclusionsFerroptosis-related ATF3 levels decreased in LN. Inhibition of ATF3 might alleviate LN development by affecting the macrophage M1 and Treg cell infiltration. These implied that ATF3 might be a potential target for developing LN therapeutic strategies.

Atomic-level design of biomimetic iron-sulfur clusters for biocatalysis.

Designing biomimetic materials with high activity and customized biological functions by mimicking the central structure of biomolecules has become an important avenue for the development of medical materials. As an essential electron carrier, the iron-sulfur (Fe-S) clusters have the advantages of simple structure and high electron transport capacity. To rationally design and accurately construct functional materials, it is crucial to clarify the electronic structure and conformational relationships of Fe-S clusters. However, due to the complex catalytic mechanism and synthetic process in vitro, it is hard to reveal the structure-activity relationship of Fe-S clusters accurately. This review introduces the main structural types of Fe-S clusters and their catalytic mechanisms first. Then, several typical structural design strategies of biomimetic Fe-S clusters are systematically introduced. Furthermore, the development of Fe-S clusters in the biocatalytic field is enumerated, including tumor treatment, antibacterial, virus inhibition and plant photoprotection. Finally, the problems and development directions of Fe-S clusters are summarized. This review aims to guide people to accurately understand and regulate the electronic structure of Fe-S at the atomic level, which is of great significance for designing biomimetic materials with specific functions and expanding their applications in biocatalysis.

Spatial characteristics of health outcomes and geographical detection of its influencing factors in Beijing.

Social determinants of health (SDOH) broadly influence health levels. Research on health and its influencing factors can help improve health status. There is limited research on the spatial stratified heterogeneity of health status and the interactions between the factors influencing it. This study aimed to analyze the spatial characteristics of health outcomes in Beijing and identify its influencing factors. Based on the Healthy Beijing Initiative (2020-2030), we constructed health outcomes and five dimensions of the SDOH evaluation system. Our study measured the health outcomes and SDOH based on the latest data from 16 districts in Beijing in 2020-2022. We explored the spatial characteristics of health outcomes through descriptive and spatial autocorrelation analyses. Moreover, the Geographical Detector (GeoDetector) technique has been used to reveal the effect of SDOH and its interactions on health outcomes. A significant spatial stratified heterogeneity of health outcomes was observed, with the health outcomes mainly exhibiting two clustering types (high-high and low-low) with positive autocorrelation. The results of the geodetector showed that social and economic factors (q = 0.85), healthy lifestyle (q = 0.68) and health service (q = 0.53) could mainly explain the heterogeneity of health outcomes. Social and economic factors, healthy lifestyle and healthy environment gradually became the main influential factor in health outcomes over time. Furthermore, the interaction of any two factors on health outcomes was found to be more pronounced than the impact of a single factor. There existed obvious spatial stratified heterogeneity of health outcomes in Beijing, which could be primarily explained by social and economic factors, and healthy lifestyle and health service.