Network Analysis Research Articles

Design and Evaluation of Steganographic Channels in Fifth-Generation New Radio

Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat.

Metrics of physiological network topology are novel biomarkers to capture functional disability and health.

Physiological networks are highly complex, integrating connections among multiple organ systems and their dynamic changes underlying human aging. It is unknown whether individual-level network could serve as robust biomarkers for health and aging. We used personalized network analysis to construct single sample network and examine the associations between network properties and functional disability in the Rugao Longevity and Aging Study (RuLAS), the China Health and Retirement Longitudinal Study (CHARLS), the Chinese Longitudinal Healthy Longevity Survey (CLHLS), and the National Health and Nutrition Examination Survey (NHANES). We observed impairments in interconnected physiological systems among long-lived adults in RuLAS. Single sample network analysis was applied to reflect the co-occurrence of these multi-system impairments at the individual level. The ADL-disabled individuals' networks exhibited notably increased connectivity among various biomarkers. Significant associations were found between network topology and functional disability across RuLAS, CHARLS, CLHLS and NHANES. Additionally, network topology served as novel biomarkers to capture risks of incident ADL disability in CHARLS. Furthermore, these metrics of physiological network topology predicted mortality across four cohorts. Sensitivity analysis demonstrated that prediction performance of network topology remained robust, regardless of the chosen biomarkers and parameters. These findings showed that metrics of network topology were sensitive and robust biomarkers to capture risks of functional disability and mortality, highlighting the role of single sample physiological networks as novel biomarker for health and aging.

DMI fungicide resistance in Zymoseptoria tritici is unlinked to geographical origin and genetic background: a case study in Europe.

The hemibiotrophic fungus Zymoseptoria tritici causing Septoria tritici blotch (STB), is a devastating foliar pathogen of wheat worldwide. A common group of fungicides used to control STB are the demethylation inhibitors (DMIs). DMI fungicides restrict fungal growth by inhibiting the sterol 14-α-demethylase, a protein encoded by CYP51 gene and essential for maintaining fungal cell permeability. However, the adaptation of Z. tritici populations in response to intensive and prolonged DMI usage has resulted in a gradual shift towards reduced sensitivity to this group of fungicides. In this study, 311 isolates were collected pre-treatment from nine wheat-growing regions in Europe in 2019. These isolates were analysed by high-throughput amplicon-based sequencing of nine housekeeping genes and the CYP51 gene. Analyses based on housekeeping genes and the CYP51 gene revealed a lack of population structure in Z. tritici samples irrespective of geographical origin. Minimum spanning network (MSN) analysis showed clustering of multilocus genotypes (MLGs) based on CYP51 haplotypes, indicating an effect of selection due to DMI fungicide use. The majority of the haplotypes identified in this study have been reported previously. The diversity and frequencies of mutations varied across regions. Using a high-throughput amplicon-sequencing approach, we found several mutations in the CYP51 gene combined in different haplotypes that are likely to cause fungicide resistance. These mutations occurred irrespective of genetic background or geographical origin. Overall, these results contribute to the development of effective and sustainable risk monitoring for DMI fungicide resistance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Comparative analysis of resettled refugees’ social networks: A mixed-method approach with visualisation tools

ABSTRACT Despite a growing interest in Social Network Analysis (SNA) within migration studies, refugees’ networks are still overlooked. Employing a mixed-method SNA (MMSNA), incorporating Hogan et al.’s participant-aided sociogram and Gephi, this article compares the networks of refugees resettled in England through the Vulnerable Persons Resettlement Scheme (VPRS) and Community Sponsorship (CS). Findings suggest that CS facilitates the development of wider, more diversified and more interconnected social networks compared to VPRS. The study highlights the role of individual and contextual factors in shaping networks while also underscoring the benefits of MMSNA, including visualisation tools, in advancing our understanding of refugees’ social networks.

Investigation of risk signatures associated with anoikis in thyroid cancer through integrated transcriptome and Mendelian randomization analysis

BackgroundAnoikis is intricately associated with the malignant progression of cancer. Thyroid cancer (THCA) is the most common endocrine tumor, metastasis is closely related to treatment response and prognosis of THCA. Hence, it is imperative to comprehensively identify predictive prognostic genes and novel molecular targets for effective THCA therapy.MethodsDifferential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to mine differentially expressed anoikis-related (DE-ARGs). Then, the prognostic genes were identified and a risk signature was constructed for THCA using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) method. Furthermore, the associations between risk signature and immune infiltration, immunotherapy, as well as potential mechanisms of action were determined using multiple R packages and Wilcoxon test. Finally, Mendelian randomized (MR) analysis was conducted to investigate the causal relationship between the prognostic genes and THCA.ResultsIn total, six prognostic genes (LRRC75A, METTL7B, ADRA1B, TPD52L1, TNFRSF10C, and CXCL8) related to anoikis were identified, and the corresponding risk signature were constructed to assess the survival time of THCA patients. Immunocorrelation analysis demonstrated the anoikis-relevant risk signature could be used to evaluate immunotherapy effects in THCA patients, and the infiltration of immune cells was correlated with the degree of risk in THCA patients. According to two-sample MR analysis, there was the significant causal relationship between CXCL8 and THCA (odds ratio [OR] > 1 & p< 0.05), and the increase of its gene expression would lead to an increased risk of THCA. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the upregulated expression patterns of these prognostic genes in THCA tissues.ConclusionIn conclusion, we constructed the risk signature related to anoikis for THCA, which might have important clinical significance for improving the quality of life and treatment effect of THCA patients.

Peer Interaction Dynamics and Second Language Learning Trajectories During Study Abroad: A Longitudinal Investigation Using Dynamic Computational Social Network Analysis

AbstractUsing computational Social Network Analysis (SNA), this longitudinal study investigates the development of the interaction network and its influence on the second language (L2) gains of a complete cohort of 41 U.S. sojourners enrolled in a 3‐month intensive study‐abroad Arabic program in Jordan. Unlike extant research, our study focuses on students’ interactions with alma mater classmates, reconstructing their complete network, tracing the impact of individual students’ positions in the social graph using centrality metrics, and incorporating a developmental perspective with three measurement points. Objective proficiency gains were influenced by predeparture proficiency (negatively), multilingualism, perceived integration of the peer learner group (negatively), and the number of fellow learners speaking to the student. Analyses reveal relatively stable same‐gender cliques, but with changes in the patterns and strength of interaction. We also discuss interesting divergent trajectories of centrality metrics, L2 use, and progress; predictors of self‐perceived progress across skills; and the interplay of context and gender.

Exploring tourist perceptions of calligraphic landscapes: Insights from social media text analysis

Calligraphic landscapes, as distinctive cultural symbols and landscapes with Chinese characteristics, are widely used in urban design, placemaking, and tourism promotion. In cultural heritage tourism, tourists’ perceptions of the symbolic meanings of landscapes significantly influence their travel experiences. This study primarily utilizes social media text analysis to explore the perceptual characteristics and symbolic meanings of calligraphic landscapes in different touristic contexts. Using Python tools, user-generated content was extracted from the Xiaohongshu app and analyzed with ROST CM6, VOSviewer, and NVivo 20 to conduct systematic quantitative and qualitative analyses, including content analysis, semantic network analysis, and co-occurrence clustering. The findings indicate that cultural exchanges on social media significantly enhance public perception of the symbolic meanings of touristic spaces. As online check-in behavior becomes increasingly popular, calligraphic landscapes have gained new esthetic-symbolic meanings among young tourists, becoming part of fashion culture and reflecting the digitalization of a sense of place. In addition, user-generated content reveals that tourists’ perceptions of calligraphic landscapes are intricately linked to place recognition, cultural symbolism, calligraphic appreciation, heritage value, and esthetic experiences. As a significant cultural symbol, calligraphic landscapes are frequently encountered during travel, with their symbolic meanings varying according to the surrounding environment, thereby influencing tourists’ preferences in diverse settings. Furthermore, this study proposes several innovative strategies for designing calligraphic landscapes. This research not only validates the feasibility of web text analysis for exploring the symbolic meanings of cultural landscapes but also enhances theoretical perspectives on how symbolic landscapes shape tourists’ psychological and behavioral responses.

Genome-Wide Identification of the bHLH Gene Family in Callerya speciosa Reveals Its Potential Role in the Regulation of Isoflavonoid Biosynthesis

Callerya speciosa (Champ. ex Benth.) Schot is a significant leguminous plant valued for its edible tuberous roots, which are a plentiful source of isoflavonoids. Basic helix–loop–helix (bHLH) transcription factors (TFs) have been reported to regulate secondary metabolism in plants, especially flavonoid biosynthesis. However, the bHLH genes in C. speciosa have not yet been reported, and their regulatory role in isoflavonoid biosynthesis remains unexplored. Here, 146 CsbHLH genes were identified in the C. speciosa genome, classifying them into 23 subfamilies based on the gene structures and phylogenetic relationships. All the CsbHLH proteins contained both motifs 1 and 2, whereas motif 8 was only distributed in subgroup III (d + e). Collinearity analysis demonstrated that fragmental replications are the primary driver of CsbHLH evolution, with the majority of duplicated CsbHLH gene pairs experiencing selective pressure. Nine candidate CsbHLH genes were found to play a potential role in regulating isoflavonoid biosynthesis through a combination of gene-to-metabolite correlation analysis and weighted gene co-expression network analysis (WGCNA). Additionally, the cis-regulatory elements and response to MeJA of these nine genes were characterized and confirmed through quantitative real-time PCR (qRT-PCR) analysis. Among them, three CsbHLHs (CsbHLH9, CsbHLH89, and CsbHLH95) were selected for further investigation. Yeast two-hybrid (Y2H), dual-luciferase (LUC) assays, bimolecular fluorescence complementation (BiFC) assays, and transient transformation demonstrated that CsbHLH9 acted as a transcriptional activator through its interaction with CsMYB36 and binding to the promoters of isoflavonoid biosynthesis genes in a MeJA-induced manner, such as CsIFR2, CsI3′H2, and CsCHS4, to promote isoflavonoid (calycosin, calycosin-7-o-glucoside, and formononetin) accumulation. Our results establish a basis for the functional analysis of bHLH genes and investigations into the molecular mechanisms underlying isoflavonoid biosynthesis in C. speciosa.

Yigu decoction regulates plasma miRNA in postmenopausal osteoporosis patients: a randomized controlled trial

BackgroundPostmenopausal osteoporosis (PMOP) is a serious condition that affects elderly individuals. Our previous study revealed that Yigu decoction (YGD) effectively improved bone mineral density (BMD) in elderly individuals, but the mechanism underlying this effect remains unclear. In this study, we investigated the relationships among YGD, microRNAs (miRNAs), and bone metabolism by assessing the effects of YGD on the miRNA levels in patient plasma to provide a scientific basis for treating PMOP with YGD.MethodsIn this clinical trial, 60 patients were randomly assigned to the YGD group or the control group (ratio of 1:1) and treated for 3 months. The primary outcome measure was BMD, and the secondary outcome measures included plasma miRNA levels, visual analogue scale (VAS) scores, alkaline phosphatase (ALP) levels, anti-tartrate acid phosphatase (TRACP-5b) levels and traditional Chinese medicine (TCM) syndrome scores. We assessed the regulatory roles of miRNAs in PMOP patients by analysing publicly available data from the Gene Expression Omnibus (GEO) database. Bioinformatics methods were also used to explore the mechanism by which YGD regulates miRNAs that are involved in bone metabolism.ResultsCompared with those before treatment, the BMD, ALP levels, TRACP-5b levels, TCM syndrome scores and VAS scores improved in both groups after 3 months of treatment (P < 0.05). A total of 82 miRNAs differed between the groups. After analysing data from the GEO database, we confirmed that miR-133a-3p is the key molecule that mediates the effects of YGD intervention on PMOP. GO analysis of key genes suggested that gene enrichment was more pronounced in response to hormones, cellular response to growth factor stimulation, and positive regulation of physiological and metabolic processes. KEGG analysis revealed that these genes were enriched mainly in the PI3K-Akt, FOXO, and JAK-STAT pathways and other pathways. The results of the protein‒protein interaction (PPI) network analysis revealed that epidermal growth factor receptor (EGFR), Insulin-like growth factor 1 (IGF-1), Caveolin-1 (Cav-1) and others were core proteins.ConclusionThis study demonstrated that YGD is beneficial in the treatment of PMOP, ameliorating clinical symptoms and bone turnover indices. Moreover, the inhibition of miR-133a-3p expression may be the key mechanisms by which YGD regulates bone metabolism in the treatment of PMOP, although YGD regulates bone metabolism in a multitarget and multipathway manner.

Research on Weighted Network Model Construction and Layout Structure of New Energy Vehicle Charging Station

(1) Background: Spatial layout is the key to the construction and development of new energy vehicle charging stations; (2) Methods: A network analysis method is used to build the new energy vehicle charging station network, design network indicators, analyze the structural characteristics of new energy vehicle charging stations based on the local nodes and the overall structure of the network, and identify the key nodes and important parts of the network; (3) Results: Taking the new energy vehicle charging station in Jinan City of Shandong Province as an example, the empirical analysis is carried out. The empirical results show that the new energy vehicle charging station network constructed in this paper and the network indicators designed can effectively describe the layout of new energy vehicle charging stations, identifying key stations and important parts of the network; (4) Conclusions: This provides a theoretical basis for further improving the utilization rate of charging stations and the reasonable planning of new energy vehicle charging stations. It provides an idea and method for the research on the layout of charging stations for new energy vehicles.

A Unified Canon? Latin American Graduate Training in Comparative Politics

ABSTRACT In Latin American comparative politics, a tension exists between North Americanization and parochialism. While certain academic scholarship is published in Scopus-indexed journals that engage with “mainstream” Global North literature, other works are found in non-indexed outlets, focusing solely on their home countries and fostering parochial scientific communities. To assess this tension in graduate program curricula, we compiled an original dataset of comparative politics readings from 21 universities across nine Latin American countries. Our network analysis reveals a centralized structure influenced by mainstream readings, challenging the expectation of parochialism. In addition to the mainstream content, universities tend to incorporate readings from regional journals to facilitate cross-case comparisons. However, these materials are inconsistently shared, resulting in fragmentation of content from Latin American sources. Our findings contribute to and challenge the North Americanization versus parochialism debate, showing that future scholars receive similar mainstream training but encounter diverse regional materials during their PhD studies.

Identifying the genetic association between severe autoimmune type 2 diabetes and the risk of focal epilepsy

BackgroundObservational studies suggested a bidirectional relationship between severe autoimmune type 2 diabetes and focal epilepsy. However, it remains debated whether and in which direction a causal association exists. This genetics-based study aimed to explore the relationships of severe autoimmune type 2 diabetes (T2DM) and focal epilepsy outcomes with two sample Mendelian randomization (TSMR) method.MethodsGenetic instruments were obtained from large-scale genome-wide meta-analysis of severe autoimmune T2DM (Ncase = 452, Ncontrol = 2,744), and focal epilepsy (Ncase = 929, Ncontrol = 212,532) of European ancestry. A series of analyses were performed to select eligible genetic instruments robustly associated with each of the traits using summary-level statistics. Inverse variance weighted was used for primary analysis, with alternative 11 MR methods. A scatter plot was utilized to illustrate the association between single nucleotide polymorphism (SNP) effects on the exposure and SNP effects on the outcome. The Wald ratio for individual SNPs and their cumulative effects was depicted using a forest plot. And diagnostics and sensitivity analyses were used to evaluate if the causal estimates are robust to violations of MR underlying assumptions, including pleiotropy, heterogeneity assessment, and leave-one-out analysis. Then the results were validated using CURATED database of DisGeNET platform.ResultsFor forward analysis, genetic predisposition to severe autoimmune T2DM was associated with an increased risk of focal epilepsy (Inverse variance weighted (IVW) method: OR = 1.11, 95% CI = 1.03-1.18, p = 0.012). For reverse analysis, there was no enough instrument variables of focal epilepsy on severe autoimmune T2DM. Further, the interrelation between severe autoimmune T2DM and focal epilepsy was demonstrated via variant-disease association network analysis using the instrument SNPs.DiscussionThis MR study supports a causal link between severe autoimmune T2DM and focal epilepsy. More effort should be made to screen seizure in severe autoimmune T2DM, unravel its clinical implications, and explore its role as a putative modifiable risk factor.

Exploring and comparing central mental health problems between rural primary and secondary school teachers—insight from a large sample symptom network analysis

Exploring and comparing central mental health problems between rural primary and secondary school teachers—insight from a large sample symptom network analysis

Variation in the intestinal bacterial community composition under different water temperature culture conditions in largemouth bass (Micropterus salmoides)

Abstract Aims This study aimed to investigate the impact of temperature on the intestinal microbiota of largemouth bass using 16S rRNA gene amplicon sequencing, focusing on the under-explored role of abiotic factors in shaping the gut microbial community. Methods and Results Five water temperature groups (20.0 ± 0.2 °C, 25.0 ± 0.2 °C, 28.0 ± 0.2 °C, 31.0 ± 0.2 °C, and 35.0 ± 0.2 °C) were established, each with three replicates. Significant variations in intestinal bacterial community composition were observed across these conditions. Elevated temperatures (31.0 ± 0.2 °C and 35.0 ± 0.2 °C) led to an increase in opportunistic pathogens such as OTU180 Vibrio and OTU2015 Vogesella (P < 0.05). Species correlation network analysis showed a shift towards more positive relationships among intestinal microbes at higher temperatures (P < 0.05). Ecological process analysis highlighted a greater role of ecological drift in microbial community structure at 31.0 ± 0.2 °C and 35.0 ± 0.2 °C (P < 0.05). Conclusions The study suggests that higher temperatures may predispose largemouth bass to opportunistic pathogens by altering their intestinal microbiota. Effective water temperature management is crucial for largemouth bass aquaculture to mitigate pathogen risks and maintain a balanced intestinal microbiota. This research provides critical insights into the temperature-microbiota relationship and offers practical recommendations for aquaculture practices.

Gritty Philadelphia: Orientation to local ideology as a predictor of sound change

Abstract Local orientation has been shown to influence speakers’ participation in local dialect norms and ongoing sound changes since the beginning of modern sociolinguistics (e.g., Labov, 1963). I argue here that local orientation is best understood as an orientation to the ideological imagined place, rather than to the actual physical hometown itself. Analysis of the effect of orientation to the imagined Philadelphia shows that speakers’ personal orientation impacts their adoption of an ongoing change. This change is best understood when orientation is considered alongside a major structural influence on young speakers—secondary school attendance—using a bipartite network analysis. The sound change under investigation, a change in the conditioning of a split in /æ/, is highly abstract and complex, making it an unlikely candidate for overt or intentional identity work. Nevertheless, a regression analysis finds strong effects of both structural influences and personal orientation on speakers’ advancement in this abstract change.

Network analysis of childhood maltreatment and internet addiction in adolescents with major depressive disorder.

Childhood maltreatment (CM) is closely linked to internet addiction (IA), especially in adolescents with Major Depressive Disorder (MDD). Previous studies have shown that adolescents who experience CM are more likely to develop IA and other psychological problems. This study aims to explore the complex relationship between CM and IA through network analysis, particularly identifying the core symptoms and bridge symptoms to better understand the development of IA in these adolescents. A cross-sectional study was conducted in seven hospitals in Anhui Province, China, involving 332 adolescents diagnosed with MDD using DSM-5 criteria. The Childhood Trauma Questionnaire - Short Form (CTQ-SF) and the Internet Addiction Test (IAT) were used to assess CM and IA symptoms, respectively. Gender-based network analysis was also performed. Network analysis constructed a CM-IA network and identified core and bridge symptoms. "Depress/moody/nervous being offline", "Request an extension for longer time", "Sleep loss due to late-night logins", and "emotional abuse" emerged as central symptoms within the CM-IA network. Additionally, "emotional abuse", "sexual abuse", and "complaints about online time" were identified as key bridge symptoms linking CM and IA. These symptoms demonstrated significant connectivity, underscoring their critical role in linking CM and IA. The findings highlight the complex relationship between CM and IA in adolescents with MDD. Specific symptoms, such as emotional abuse and online-related symptoms, play important roles in understanding and intervening in adolescent IA. Future interventions should target these core and bridge symptoms for more effective prevention and treatment.

Psychological Responses to Home-Working Practices: A Network Analysis of Relationships with Health Behaviour and Wellbeing

Working at home, rather than in the workplace, has been suggested to affect office-based workers’ health and wellbeing. This exploratory, cross-sectional study sought to identify discrete psychological responses to home-working practices and investigate their relationship with engagement in health-related behaviours and wellbeing. A sample of 491 home-workers completed a survey assessing ten psychological responses to home-working (e.g., the ability to ‘switch off’ from work), ten health behaviour indices (e.g., sleep trouble), and seven wellbeing indices. Network Analysis modelled relationships between these variables. Results showed four clusters of psychological responses to home-working practices (representing ‘home-working independence’, ‘home-work transition’, ‘daily work pressure’, and ‘work-day forecasting’). Variables within these clusters linked to health behaviour and wellbeing: perceptions of workload manageability, ability to switch off from work, homeworking autonomy, and planning and organising a home-working day had cascading influences on indicators of health, health behaviours, and wellbeing. The findings point to a complex system of potential health and wellbeing consequences of working from home. Further evidence is needed to establish truly causal relationships; nonetheless, our findings call for the development of public health initiatives and organisational policies to support the adoption of home-working practices to benefit the health and wellbeing of home-workers.

Exploring the evolution and collaboration in two-sided matching: a comprehensive bibliometric and topic modeling analysis

PurposeThis study aims to provide a comprehensive analysis of two-sided matching (TSM) research, an interdisciplinary field that integrates both theoretical and practical perspectives. By examining 756 research articles from the Web of Science database, this paper seeks to identify key trends, collaboration patterns and emerging research topics within the TSM domain.Design/methodology/approachThe research utilizes bibliometric analysis combined with a structural topic model to analyze TSM-related articles published between January 1, 2000, and September 30, 2022. The study identifies leading subfields, journals, countries/regions and institutions based on publication volume, total citations and average citations per article. Interaction and collaboration patterns among these entities are examined through co-occurrence and coupling networks. Additionally, five major research topics are identified and explored using topic modeling and co-word networks. This hybrid knowledge mining approach better reveals the inherent structural changes in topic clusters. Topic distribution and network analysis are beneficial in capturing the attention allocation of different entities to knowledge.FindingsThe analysis reveals five prominent research topics in TSM: communication resource allocation, stable matching research, computing task assignment, TSM decision-making and market matching mechanism design. These topics represent the main directions of TSM research. The study also uncovers a shift in research focus from theoretical aspects to practical applications. Furthermore, the distribution of knowledge and interaction patterns among key entities align with the identified research trends.Originality/valueThis study offers a novel and detailed overview of TSM research highlighting significant trends and collaboration patterns within the field. By integrating bibliometric methods with structural topic modeling the study provides unique insights into the evolution of TSM research making it a valuable resource for both academic and professional communities.

Suspicious Financial Activity in the Context of In-Game Asset Exchange Marketplace

In this study, we investigated the expanding problem of suspicious activity when using online in-game asset trading platforms. The decentralized structures and anonymity offered by these platforms provide a basis for suspicious actions, creating a threat to the virtual economy. By evaluating 18,157 rows of anonymized transaction data from 38 unique sellers with the help of the interquartile range approach and network analysis, we were able to identify suspicious activities. The results highlight suspicious online activities of individual transactions. This research contributes by identifying new, concerning trends and unraveling complex networks by analyzing in-game asset transaction data. It also assists in informing experts and lawmakers about new suspicious activities.

Transcriptomics Revealed Differentially Expressed Transcription Factors and MicroRNAs in Human Diabetic Foot Ulcers

Non-healing diabetic foot ulcers (DFUs) not only significantly increase morbidity and mortality but also cost a lot and drain healthcare resources. Persistent inflammation, decreased angiogenesis, and altered extracellular matrix remodeling contribute to delayed healing or non-healing. Recent studies suggest an increasing trend of DFUs in diabetes patients, and non-healing DFYs increase the incidence of amputation. Despite the current treatment with offloading, dressing, antibiotics use, and oxygen therapy, the risk of amputation persists. Thus, there is a need to understand the molecular and cellular factors regulating healing in DFUs. The ongoing research based on proteomics and transcriptomics has predicted multiple potential targets, but there is no definitive therapy to enhance healing in chronic DFUs. Increased or decreased expression of various proteins encoded by genes, whose expression transcriptionally and post-transcriptionally is regulated by transcription factors (TFs) and microRNAs (miRs), regulates DFU healing. For this study, RNA sequencing was conducted on 20 DFU samples of ulcer tissue and non-ulcerated nearby healthy tissues. The IPA analysis revealed various activated and inhibited transcription factors and microRNAs. Further network analysis revealed interactions between the TFs and miRs and the molecular targets of these TFs and miRs. The analysis revealed 30 differentially expressed transcription factors (21 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and seven miRs, including mir-486, mir-324, mir-23, mir-186, mir-210, mir-199, and mir-338 in upstream regulators (p < 0.05), while causal network analysis (p < 0.05) revealed 28 differentially expressed TFs (19 activated and 9 inhibited), two translational regulators (RPSA and EIF4G2), and five miRs including mir-155, mir-486, mir-324, mir-210, and mir-1225. The protein–protein interaction analysis revealed the interaction of various novel proteins with the proteins involved in regulating DFU pathogenesis and healing. The results of this study highlight many activated and inhibited novel TFs and miRs not reported in the literature so far, as well as the targeted molecules. Since proteins are the functional units during biological processes, alteration of gene expression may result in different proteoforms and protein species, making the wound microenvironment a complex protein interaction (proteome complexity). Thus, investigating the effects of these TFs and miRs on protein expression using proteomics and combining these results with transcriptomics will help advance research on DFU healing and delineate potential therapeutic strategies.