Network Analysis Research Articles

A new methodological quest to evaluate South Korean digital diplomacy in US government web domains

This study employs a novel methodological approach to evaluate the effectiveness of South Korea’s digital diplomacy within U.S. government web spaces. Given the United States’ experience with modern digital public diplomacy, its foreign policy has a significant impact on both Korea and Japan. We examine how key issues in the Korea-Japan territorial dispute are perceived and preserved on U.S. government web spaces, as well as their effects on the public. The study used web archives for data collection, as well as a composite analysis combining web impact studies and semantic network analysis. The analysis revealed that Japan’s digital public diplomacy is more prominent, primarily through online media operated by the U.S. Embassy in Japan. This suggests that Korea needs strategies similar to Japan’s, leveraging digital technology and media.

Differential miRNA Expression Patterns between TallyHo/JngJ Mice and Non-Diabetic SWR/J Mice

Abstract Type 2 diabetes mellitus (T2DM) increases the susceptibility of bone fragility. The underlying mechanisms have, however, remained largely unknown. MicroRNAs (miRNAs) are short single-stranded non-coding RNA molecules with utility as biomarkers due to their easy accessibility and stability in bodily fluids. Here, we aimed to use an unbiased approach to identify miRNAs dysregulated in a polygenic mouse model of T2DM. Genome-wide analysis of miRNAs in serum, bone marrow and bone from the polygenic TallyHo/JngJ (TH) mice, which recapitulate T2DM in humans, was performed. This analysis was compared to the recommended control SWR/J and a strain-matched non-diabetic control (TH-ND). When comparing TH mice with TH-ND using an adjusted P-value (FDR) cut-off of 0.2 to identify differentially expressed miRNAs, mmu-miR-466i-5p and mmu-miR-1195 were found to be up-regulated in both serum and in bone marrow. Dysregulated miRNAs were not found in bone tissue. When comparing TH-ND mice with SWR/J using the same FDR cut-off, mmu-miR-351-5p and mmu-miR-322-3p were upregulated in both bone marrow and serum, while mmu-miR-449a-5p and mmu-miR-6240 were downregulated in bone marrow and serum. Dysregulated miRNAs in bone marrow or cortical bone compared to serum between TH-ND mice and SWR/J were investigated for their cell-type enrichment to identify putative donor cells and their gene target networks. Gene target network analysis revealed genes involved in diabetes-related signaling pathways as well as in diabetic bone disease. Cell-type enrichment analysis identified hsa-miR-449a enriched in immune cells, hsa-miR-592 in hepatocytes and endothelial cells, while hsa-miR-424-3p, hsa-miR-1-3p and hsa-miR-196b-5p were enriched in mesenchymal stem cells and their derived tissues. In conclusion, our comparative miRNA profiling sheds light on differential expression patterns between SWR/J and both subgroups of TH. No differences were observed between TH and TH-ND suggesting the genetical background of SWR/J may be responsible for the change of dysregulated miRNA.

"Academic Influence and Industry Funding in Nerve Allograft Research: A Co-Authorship Network Analysis".

Clinical use of acellular nerve allografts is rapidly increasing despite limited high-quality, comparative evidence of superiority. Simultaneously, non-research payments to clinicians by the nerve allograft industry exceeds $14,000,000 over the last decade. In this study, the authors hypothesized that nerve allograft-related academic influence would correlate with industry funding. PubMed studies on nerve allografts in plastic and reconstructive surgery journals were reviewed. Using author lists from extracted studies, a co-authorship network was generated and degree centralities - quantitative measurements of influence within a network - were calculated. Open Payments data from the nerve allograft industry was summated for each author. Finally, Pearson correlation and linear regression were used to analyze the relationship between centrality and payments received. 185 studies were included, with 581 unique authors (nodes) and 2,406 co-authorships (ties) between them. Among authors with exceptional network influence (centrality >10, 75th percentile; n=113), 56 were clinicians with valid NPIs and therefore eligible for inclusion in the Open Payments database. 44 (79%) of these authors received at least one payment from the industry. Pearson correlation revealed a moderate (0.4<r<0.6) positive correlation between centrality and payments received (r=0.51, p<0.001). Linear regression demonstrated an estimated 16% increase in total pay per additional unit of centrality (p<0.001; 95% CI [8%, 25%]). There is a significant connection between academic influence and financial support from the nerve allograft industry. Such results warrant discussion concerning conflicts of interest in clinical research and best practices for mitigating potential bias related to commercially backed treatments.

Neural network architecture of a mammalian brain

Connectomics research is making rapid advances, although models revealing general principles of connectional architecture are far from complete. Our analysis of 106 published connection reports indicates that the adult rat brain interregional connectome has about 76,940 of a possible 623,310 axonal connections between its 790 gray matter regions mapped in a reference atlas, equating to a network density of 12.3%. We examined the sexually dimorphic network using multiresolution consensus clustering that generated a nested hierarchy of interconnected modules/subsystems with three first-order modules and 157 terminal modules in females. Top-down hierarchy analysis suggests a mirror-image primary module pair in the central nervous system's rostral sector (forebrain-midbrain) associated with behavior control, and a single primary module in the intermediate sector (rhombicbrain) associated with behavior execution; the implications of these results are considered in relation to brain development and evolution. Bottom-up hierarchy analysis reveals known and unfamiliar modules suggesting strong experimentally testable hypotheses. Global network analyses indicate that all hubs are in the rostral module pair, a rich club extends through all three primary modules, and the network exhibits small-world attributes. Simulated lesions of all regions individually enabled ranking their impact on global network organization, and the visual path from the retina was used as a specific example, including the effects of cyclic connection weight changes from the endogenous circadian rhythm generator, suprachiasmatic nucleus. This study elucidates principles of interregional neuronal network architecture for a mammalian brain and suggests a strategy for modeling dynamic structural connectivity.

Differential immunological responses in lamb rumen and colon to alfalfa hay and wheat straw in a concentrate-rich diet: insights into microbe-host interactions.

The impact of a concentrate-rich (CR) diet on the gut microbiome and epithelium homeostasis is well documented. However, it has not been systematically studied whether and how host-microbial interaction contributes to the immune homeostasis in the rumen and colon of lambs fed alfalfa hay and wheat straw, alone or combined, in a CR diet. In all, 63 lambs (initial body weight, 16.69 ± 1.50 kg) were randomly allotted to three dietary groups, each consisting of three pens with seven lambs per pen. Over 14 weeks, the lambs were fed diets as follows: 60% concentrate supplemented with either 40% wheat straw (WG), 20% alfalfa hay combined with 20% wheat straw (MG), or 40% alfalfa hay (AG). The present findings showed that lambs in the AG group had greater (P < 0.05) IgG and lower (P = 0.067) tumor necrosis factor-alpha concentrations relative to those in the MG and WG groups. The 16S rRNA analysis highlighted that various bacterial phyla and genera in the rumen and colon preferentially degrade fiber and starch derived from alfalfa hay and wheat straw. The weighted gene co-expression network analysis revealed that the bacterial genera from the Firmicutes are broadly associated with genes involved in various signaling pathways, underscoring the potential role of Firmicutes as key drivers of host-microbial interactions under the present feeding conditions. These findings shed light on the fact that the rumen and colon immune homeostasis is distinctively influenced by diets of alfalfa hay, wheat straw, or their combination in a CR diet. Further studies should examine the prolonged effects of replacing wheat straw with alfalfa hay in a concentrate-rich diet formulated to provide equivalent neutral detergent fiber levels. This could reveal how various forage fibers influence host-microbial interactions and gut health.IMPORTANCEIn contemporary feedlots, a growing trend is to feed animals a concentrate-rich (CR) diet that could disrupt the synchronized interplay between microbes and host metabolism, leading to altered metabolic functions. Wheat straw and alfalfa hay have different levels of protein and neutral detergent fiber, each with varying rates of digestion. It is unclear how including alfalfa hay and wheat straw, alone or combined in a CR diet, influences the host-microbial consortia and immune homeostasis. Herein, we showed that rumen and colon showed differential immune responses to the alfalfa hay, wheat straw, or both. Bacterial genera preferentially degrade fiber and starch derived from alfalfa hay, wheat straw, or both. Bacterial genera from Firmicutes phylum play a pivotal role in driving the host-microbial interactions, as indicated by their extensive association with genes across various signaling pathways.

Green Development of Chinese Agriculture from the Perspective of Bidirectional Correlation

China’s agricultural green development exhibits spatial imbalances. To promote the coordinated green development of agriculture across various regions, this paper explores the evolution of spatial association networks and driving factors of agricultural green development from a bidirectional correlation perspective, using social network analysis and spatial econometric methods. This research indicates that China’s agricultural green efficiency has steadily improved, with a complex multi-threaded network structure. Although the spatial interaction and spillover effects of the overall network structure have increased, they remain relatively weak. The individual network structure shows significant regional imbalances. The spatial association network of agricultural green efficiency forms four major blocks, with sparse connections within the blocks but close connections between blocks, demonstrating strong spillover effects. Regarding the driving factors, the proportion of the primary industry, labor level, and R&amp;D investment have significant spatial impacts, while the spatial impacts of human capital level, degree of openness, economic development level, and new quality productivity level are not significant. Therefore, we believe that it is necessary to establish the concept of coordinated green development in agriculture, fully leverage regional associations and spillover effects, and formulate differentiated policies to improve agricultural green efficiency.

Minimal invasive extracorporeal circulation: A bibliometric network analysis of the global scientific output.

Minimal Invasive Extracorporeal Circulation (MiECC) has recently emerged as a more 'physiologic' alternative to conventional extracorporeal circulation. However, its adoption is still limited due to lack of robust scientific evidence and ongoing debate about its potential benefits. This bibliometric analysis aims to analyze the scientific articles on MiECC and identify current research domains and existing gaps to be addressed in future studies. Pertinent articles were retrieved from the Web of Science (WOS) database. The search string included 'minimal invasive extracorporeal circulation' and its synonyms. The VOSviewer (version 1.6.17) software was used to conduct comprehensive analyses. Semantic and research networks, bibliographic coupling and journal analysis were performed. Of the 1777 articles identified in WOS, 292 were retrieved. The trend in publications increased from 1991 to date. Most articles focused on transfusion requirements, acute kidney injury, inflammatory markers and cytokines, inflammation and delirium, though the impact of intraoperative optimal fluid and hemodynamic management as far as the occurrence of postoperative complications were poorly addressed. The semantic network analysis found inter-connections between the terms "cardiopulmonary bypass", "inflammatory response", and "cardiac surgery". Perfusion contributed the highest number of published documents. The most extensive research partnerships were between Germany, Greece, Italy, and England. Notwithstanding the scientific community's growing interest in MiECC, crucial topics (i.e., the best anesthetic management and intraoperative need for inotropes, vasopressors and fluids) still require more comprehensive exploration. This investigation may prove to be a useful tool for clinicians, scientists, and students concerning global publication output and for the use of MiECC in cardiac surgery.

Characteristics of Semiconducting Minerals Affects Microbial Communities in Purple Soils

Purple soil is rich in semiconducting minerals, but the impact of these minerals on soil properties and associated microbiome assemblages has received little attention. To better understand the influence of semiconducting minerals in soils, samples were collected from 4 soil classifications, including purple soil, siltstone, farmland, and new formed soil. Goethite was the main semiconducting mineral in purple soil followed by rutile and birnessite, while for siltstone, rutile was the major semiconducting mineral. Proteobacteria (77.77–98.56%) was the most prevalent phylum among all samples, with the second most abundant phylum being Cyanobacteria (purple soil and farmland) and Firmicutes (siltstone and new formed soil). According to the average path length in network analysis, purple soil showed higher species segregation, which suggested purple soil was potentially more susceptible to external interference than the other types. The relationship between microbes may be synergistic due to the positive links between microbial phyla. Rutile affected microbial composition to the greatest extent, accounting for 13.66% of the total variation in microbial assembly, while goethite (r= –0.0947) and birnessite (r = 0.0215) content were also associated with changes in microbial composition. These results demonstrated that semiconducting minerals affected the structure and potential energy utilization of soil microbial communities.

Network analysis of Tourette syndrome and attention-deficit/hyperactivity disorder symptoms in children and adolescents

BackgroundWhile Tourette syndrome (TS) and attention-deficit/hyperactivity disorder (ADHD) often co-occur, the nature of the relationship between their symptoms is not well understood. Network analysis of psychopathology allow for detailed examinations of symptom interactions, providing an effective approach to explore the patterns of comorbidity between TS and ADHD symptoms.MethodsThis study included 3,958 participants (male/female = 3,004/954, age mean ± SD = 8.60 ± 2.25 years). We collected data on TS symptoms using the Motor Tic, Obsessions and Compulsions, Vocal Tic Evaluation Survey (MOVES), and ADHD symptoms using the Swanson, Nolan, and Pelham Rating Scale-IV (SNAP-IV). Network analysis was employed to construct a combined network of TS and ADHD symptoms at the symptom level. We utilized the expected influence (EI) and bridge EI metrics to explore the core and bridge symptoms within the network.ResultsThe network structure demonstrated a moderate number of non-zero connections between TS and ADHD symptoms, constituting 23.06% of all potential connections. Core symptoms in the comorbidity network included “Often has difficulty sustaining attention in tasks or play activities,” “Certain bad words or thoughts keep going through my mind,” and “Words come out that I can’t stop or control.” Bridging symptoms identified were “Words come out that I can’t stop or control,” “I do certain things like jumping or clapping over and over,” “I can’t control all my movements,” and “Often talks excessively.”ConclusionThe core and bridging symptoms identified in this study serve as potential therapeutic targets for the treatment of TS and ADHD comorbidity in clinical children and adolescents.

Assessing the causal effect of inflammation-related genes on myocarditis: A Mendelian randomization study.

Prior evidence has shown a significant link between inflammation and the development of myocarditis. This study aimed to investigate the causal relationship between inflammation-related genes (IRGs) and myocarditis. In this study, the causal relationship between 167 IRGs and myocarditis were investigated using datasets from the Gene Set Enrichment Analysis and Integrative Epidemiology Unit open genome-wide association study (IEU OpenGWAS) databases. The GWAS data (finn-b-I9 MYOCARD) contained single nucleotide polymorphisms (SNPs) data from 117755 myocarditis samples (16379455 SNPs, 829 cases vs. 116926 controls). Five algorithms [MR-Egger, weighted median, inverse variance weighted (IVW), simple mode, and weighted mode regression] were employed for the MR analysis, with IVW as the primary method, and sensitivity analysis was conducted. Subcellular localization and protein-protein interaction (PPI) network analyses were performed for selected biomarkers. Results were verified in ebi-a-GCST90018882 (24180570 SNPs, 633 cases vs. 427278 controls) and finn-b-I9 MYOCARD EXNONE (16380466 SNPs, 829 cases vs. 217963 controls) to enhance reliability. IRF7 and ADORA2B were shown to be two exposure factors after screening. Univariable MR (UVMR) analysis revealed that IRF7 was a risk factor for myocarditis [IVW: odd ratio (OR)=1.041, 95% confidence interval (CI)=1.018-1.955, P=0.039], while ADORA2B was a protective factors for myocarditis (IVW: OR=0.799, 95% CI=0.640-0.997, P=0.047). Sensitivity analysis confirmed the robustness of these findings. Multivariable MR (MVMR) analysis further demonstrated a direct causal role of ADORA2B in preventing myocarditis. Subcellular localization analysis indicated predominant cytoplasmic expression and limited mitochondrial expression for both genes. The results of PPI analysis showed that 20 genes were predicted to be associated with IRF7 function, such as response to type I interferon, pattern recognition receptor signalling pathway, and toll-like receptor signalling pathway. The results in finn-b-I9 MYOCARD EXNONE were consistent with MR analysis. The findings indicated there was a causal connection between IRGs (IRF7 and ADORA2B) and myocarditis, which offered a crucial point of reference and guidance for future studies and myocarditis treatment.

The analysis of P2P networks with malicious peers and repairable breakdown based on Geo/Geo/1+1 queue

The incredible growth of Peer-to-Peer (P2P) networks has brought with it some complex challenges, such as trust issues and high bandwidth consumption. To address these challenges, this paper analyzes the “free-riding” behavior, system energy consumption, and the benefits of requesting and service peers in the network. A Geo/Geo/1+1 queuing model is built with malicious peers which includes several strategies such as repairable breakdown, synchronized multiple working vacations, differentiated service, and waiting threshold. The matrix-geometric solution method is used to obtain steady-state distribution and performance measures. By conducting numerical experiments and analyzing the impact of each parameter, it is possible to optimize the system's performance and reduce energy consumption. With careful adjustments to parameter values, significant cost savings of requesting peers and energy conservation can be achieved. The resulting analysis provides a comprehensive understanding of the behavior of P2P networks, and the strategies proposed in the study can be used to optimize the performance of P2P networks.

Distinct brain-wide presynaptic networks underlie the functional identity of individual cortical neurons.

Neuronal connections provide the scaffolding for neuronal function. Revealing the connectivity of functionally identified individual neurons is necessary to understand how activity patterns emerge and support behavior. Yet, the brain-wide presynaptic wiring rules that lay the foundation for the functional selectivity of individual neurons remain largely unexplored. Cortical neurons, even in primary sensory cortex, are heterogeneous in their selectivity, not only to sensory stimuli but also to multiple aspects of behavior. Here, to investigate presynaptic connectivity rules underlying the selectivity of pyramidal neurons to behavioral state 1-12 in primary somatosensory cortex (S1), we used two-photon calcium imaging, neuropharmacology, single-cell based monosynaptic input tracing, and optogenetics. We show that behavioral state-dependent neuronal activity patterns are stable over time. These are minimally affected by neuromodulatory inputs and are instead driven by glutamatergic inputs. Analysis of brain-wide presynaptic networks of individual neurons with distinct behavioral state-dependent activity profiles revealed characteristic patterns of anatomical input. While both behavioral state-related and unrelated neurons had a similar pattern of local inputs within S1, their long-range glutamatergic inputs differed. Individual cortical neurons, irrespective of their functional properties, received converging inputs from the main S1-projecting areas. Yet, neurons that tracked behavioral state received a smaller proportion of motor cortical inputs and a larger proportion of thalamic inputs. Optogenetic suppression of thalamic inputs reduced behavioral state-dependent activity in S1, but this activity was not externally driven. Our results revealed distinct long-range glutamatergic inputs as a substrate for preconfigured network dynamics associated with behavioral state.

Evaluating influence of weather on Ascochyta blight severity in chickpea using correlation network, regression and principal component analysis

Aim: Weather parameters play a critical role in the survival and propagation of the causal pathogen Ascochyta rabiei. In the absence of vertical host resistance, the present study was designed to explore the weather-disease interrelationship for effective disease management. Methodology: Field experiments were conducted with three chickpea cultivars and three sowing times for two years. The relationship between the percent severity index (PSI) at weekly interval and observed weather data was explored using multivariate statistical techniques. Results: The correlation networks revealed that temperature and relative humidity parameters were negatively and positively associated with the blight PSI, respectively. Humid thermal ratio (HTR) significantly correlated with PSI among all three chickpea cultivars. The linear regression of PSI with weather variables exhibited a significant negative slope (β) with all thermal variables whereas a strong positive β was displayed with relative humidity and HTR. The Best subset multiple regression models further affirmed that PSI in three chickpea cultivars can be strongly predicted with models constituted with temperature, humidity and HTR. Principal component analysis showed that PC1 and PC2 explained 88.2% variability with weather variables affecting the PSI. The clustering of thermal and humidity condition parameters around the first two PCs explained their pivotal role in disease severity progress. Interpretation: The multivariate analysis revealed that air temperature, relative humidity and HTR had significant influence on periodic Ascochyta blight severity in chickpea crop. Present exploration will be vital in developing more targeted disease prediction and management strategies to secure chickpea production. Key words: Ascochyta blight, Best subset regression, Chickpea, Correlation network, Weather variables

Informal participation in digital planning: How can third parties use social media to shift power relations in planning?

In recent years, social media has become an influential tool for engaging various participants and facilitating inclusivity in digital planning. While many studies highlight local governments' use of social media for formal participation, limited research assesses its impact on power dynamics in informal participation. This study aims to fill the gap by identifying key features of social media that facilitate informal participation and applying Castells' four forms of network power to understand power dynamics among civil society, journalism, citizens, and governments in planning processes. It also develops a novel mixed-methods approach that combines social media scraping, social network analysis (SNA), semi-structured interviews, and field observation. This approach is applied to investigate the Enning Road regeneration project in Guangzhou as a case study. Analyzing data from China's Weibo, the study reveals network disputes across three dimensions: graph, community, and network statistics. Hyperlink-Induced Topic Search (HITS) and community detection results suggest that civil society and journalism have substantial networked power as they strategically utilize social media to promote collaboration, mobilize citizens, and foster communities. They also excise network-making power by switching online and offline networks, thereby transmitting online debate to a wide range of audiences and compelling local governments to shift planning priorities from demolitions to preservation.

An efficient network clustering approach using graph-boosting and nonnegative matrix factorization

Network clustering is a critical task in data analysis, aimed at uncovering the underlying structure and patterns within complex networks. Traditional clustering methods often struggle with large-scale and noisy data, leading to suboptimal results. Also, the efficiency of positive samples in network clustering depends on the carefully constructed data augmentation, and the pre-training process of the model deals with large-scale data. To address these issues, in this paper, we introduce an efficient network clustering approach that leverages Graph-Boosting and Nonnegative Matrix Factorization to enhance clustering performance (GBNMF). Our algorithm addresses the limitations of traditional clustering techniques by incorporating the strengths of graph-boosting, which iteratively improves the quality of clusters, and Nonnegative Matrix Factorization (NMF), which effectively captures latent structures within the data. We validate our algorithm through extensive experiments on various benchmark network datasets, demonstrating significant improvements in clustering accuracy and robustness. The proposed algorithm not only achieves superior clustering results but also exhibits remarkable computational efficiency, making it a valuable tool for large-scale network analysis applications.

Deciphering Internal Regulatory Patterns within the p53 Core Tetramer: Insights from Community Network Analysis.

Gene therapy is one of the most effective strategies for cancer treatment. The p53 protein, commonly known as the "guardian of the genome", plays a critical role in gene activation and tumor suppression. Tetramerization of the p53 core domain is an essential allosteric process that supports its suppression functions. This letter presents a framework to analyze the structure, function, and dynamic connectivity of the p53 tetramer, using community network analysis based on all-atom molecular dynamics simulations. The communities within the p53 monomer exhibit distinct functional roles, while interactions between molecules establish a symmetrical network structure. We identified direct evidence of single, double, and multiple pathway regulations within the p53 tetramer and crucial residue pairs involved in these connections. Our study provides a comprehensive framework to understand the community network of the p53 tetramer, offering new insights into the stable formation of the p53 core tetramer.

Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines.

The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this study was to investigate the influence of matrix stiffness on PDAC progression by analyzing the proteome of PDAC-derived extracellular vesicles (EVs). PDAC cell lines (mPDAC and KPC) were grown on synthetic supports with a stiffness close to non-tumor (NT) or tumor tissue (T), and the protein expression levels in cell-derived EVs were analyzed by a quantitative MSE label-free mass spectrometry approach. Our analysis figured out 15 differentially expressed proteins (DEPs) in mPDAC-EVs and 20 DEPs in KPC-EVs in response to matrix rigidification. Up-regulated proteins participate to the processes of metabolism, matrix remodeling, and immune response, altogether hallmarks of PDAC progression. A multimodal network analysis revealed that the majority of DEPs are strongly related to pancreatic cancer. Interestingly, among DEPs, 11 related genes (ACTB/ANXA7/C3/IGSF8/LAMC1/LGALS3/PCD6IP/SFN/TPM3/VARS/YWHAZ) for mPDAC-EVs and 9 (ACTB/ALDH2/GAPDH/HNRNPA2B/ITGA2/NEXN/PKM/RPN1/S100A6) for KPC-EVs were significantly overexpressed in tumor tissues according to gene expression profiling interaction analysis (GEPIA). Concerning the potential clinical relevance of these data, the cluster of ACTB, ITGA2, GAPDH and PKM genes displayed an adverse effect (p<0.05) on the overall survival of PDAC patients.

NR0B2 Is a Key Factor for Gastric Diseases: A GEO Database Analysis Combined with Drug-Target Mendelian Randomization.

Small Heterodimer Partner (SHP; NR0B2) is an orphan receptor that acts as a transcriptional regulator, controlling various metabolic processes, and is a potential therapeutic target for cancer. Examining the correlation between the expression of NR0B2 and the risk of gastric diseases could open a new path for treatment and drug development. The Gene Expression Omnibus (GEO) database was utilized to explore NR0B2 gene expression profiles in gastric diseases. Co-expressed genes were identified through Weighted Correlation Network Analysis (WGCNA), and GO enrichment was performed to identify potential pathways. The Xcell method was employed to analyze immune infiltration relationships. To determine the potential causal relationship between NR0B2 expression and gastric diseases, we identified six single-nucleotide polymorphisms (SNPs) as a proxy for NR0B2 expression located within 100 kilobases of NR0B2 and which are associated with triglyceride homeostasis and performed drug-target Mendelian randomization (MR). Bioinformatics analysis revealed that NR0B2 expression levels were reduced in gastric cancer and increased in gastritis. GO analysis and Gene Set Enrichment Analysis (GSEA) showed that NR0B2 is widely involved in oxidation-related processes. Immune infiltration analyses found that NR0B2 was associated with Treg. Prognostic analyses showed that a low expression of NR0B2 is a risk factor for the poor prognoses of gastric cancer. MR analyses revealed that NR0B2 expression is associated with a risk of gastric diseases (NR0B2 vs. gastric cancer, p = 0.006, OR: 0.073, 95%CI: 0.011-0.478; NR0B2 vs. gastric ulcer, p = 0.03, OR: 0.991, 95%CI: 0.984-0.999; NR0B2 vs. other gastritis, p = 0.006, OR:3.82, 95%CI: 1.468-9.942). Our study confirms the causal relationship between the expression of NR0B2 and the risk of gastric diseases, and highlights its role in the progression of gastric cancer. The present study opens new avenues for exploring the potential of drugs that either activate or inhibit the NR0B2 receptor in the treatment of gastric diseases.

Emotion regulation and psychopathology: Investigating differential associations between emotion regulation skills and psychological symptoms using a network approach.

Emotion regulation plays an important role in the development and maintenance of psychopathology. However, the question whether specific ER skills are related to specific psychological symptoms has rarely been studied, but has important implications for targeted interventions. This analysis aims to explore potential differential associations between various ER skills and psychological symptoms using a network analysis approach. Routine data from a transdiagnostic clinical sample of 716 patients (460 females, 256 males) from an outpatient clinic for psychotherapy were analysed. Nine ER skills were assessed with the Emotion Regulation Skills Questionnaire, and nine symptom dimension scores were obtained using the Brief Symptom Inventory. A regularized partial correlation network models including ER skills and individual symptom domains were calculated. Bridge expected influence was calculated to estimate the strength of association of each ER skill with psychological symptoms. Only the following ER skills were most strongly related to psychological symptoms (bridge expected influence): Tolerance, Confrontation and Modification. All other ER skills were indirectly connected to symptom severity through these four skills. The strongest direct edges between ER skills and symptoms were Modification-Depression, Confrontation-Obsession-Compulsion and Tolerance-Interpersonal Sensitivity, which were significantly stronger than the vast majority of other associations between ER skills and psychological symptoms. These exploratory findings provide valuable targets for future studies to investigate specific associations between ER skills and psychological symptoms which could help to improve outcome monitoring and efficacy of interventions targeting ER.

Identification of transcription factors associated with leaf senescence in tobacco

Leaf senescence represents the final stage of leaf development, involving transcription factors (TFs)-mediated genetic reprogramming events. The timing of crop leaf senescence has a major influence on the yield and quality of crop in agricultural production. As important regulator of plant growth, the significance of TFs in the regulation of leaf senescence have been highlighted in various plant species by recent advances in genetics. However, studies on underlying molecular mechanisms are still not adequately explained. In this study, for analyzing the regulation of TFs on senescence of tobacco leaves, we combined gene differential expression analysis with weighted gene co-expression network analysis (WGCNA) to analyze the time-series gene expression profiles in senescing tobacco leaf. Among 3517 TF genes expressed in tobacco leaves, we identified 21, 35, and 183 TFs that were associated with early, middle, and late stages of tobacco leaf senescence, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation results reveal that these senescence response TFs are correlated with several biological pathways such as plant hormone signal transduction, ubiquitin mediated proteolysis and MAPK signaling pathway, indicating the roles of TFs in regulating leaf senescence. Our results provide implications for future studies of the potential regulatory mechanisms of TFs involved in senescence of tobacco leaves.