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Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive tract. Clinical findings reveal that the five-year survival rate for mid-to late-stage ESCC patients is merely around 20 %, whereas those diagnosed at an early stage can achieve up to a 95 % survival rate. Consequently, early detection is paramount to improving ESCC patient survival. Protein markers are essential for diagnosing diseases, and the identification of new candidate proteins associated with ESCC through the protein-protein interaction (PPI) network is aimed for in this paper. The PPI network related to ESCC was constructed using protein data, comprising 2094 nodes and 19,660 edges. To assess the nodes' importance in the network, three metrics-degree centrality, betweenness centrality, and closeness centrality-were employed, leading to the identification of 81 key proteins. Subsequently, the biological significance of these proteins in the network was explored, combining biomedical knowledge from three perspectives: network, node, and cluster. The results demonstrated that 52 out of 81 key proteins were confirmed to be linked to ESCC. Among the remaining 29 unreported proteins, 18 displayed significant biological significance, indicating their potential as protein markers related to ESCC.

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Target antigens are crucial for developing chimeric antigen receptor (CAR)-T cells, but their application to ovarian cancers is limited. This study aimed to identify potential genes as CAR-T-cell antigen candidates for ovarian cancers. A differential gene expression analysis was performed on ovarian cancer samples from four datasets obtained from the GEO datasets. Functional annotation, pathway analysis, protein localization, and gene expression analysis were conducted using various datasets and tools. An oncogenicity analysis and network analysis were also performed. In total, 153 differentially expressed genes were identified in ovarian cancer samples, with 60 differentially expressed genes expressing plasma membrane proteins suitable for CAR-T-cell antigens. Among them, 21 plasma membrane proteins were predicted to be oncogenes in ovarian cancers, with nine proteins playing crucial roles in the network. Key genes identified in the oncogenic pathways of ovarian cancers included MUC1, CXCR4, EPCAM, RACGAP1, UBE2C, PRAME, SORT1, JUP, and CLDN3, suggesting them as recommended antigens for CAR-T-cell therapy for ovarian cancers. This study sheds light on potential targets for immunotherapy in ovarian cancers.

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Cryptosporidiosis is a worldwide zoonotic disease. Oxymatrine, an alkaloid extracted and isolated from the plant bitter ginseng, has been reported to have therapeutic effects on cryptosporidiosis. However, the underlying mechanism of its action remains unclear. In this study, we utilized network pharmacology and experimental validation to investigate the mechanism of oxymatrine in the treatment of cryptosporidiosis. First, the potential targets of drugs and diseases were predicted by TCMSP, Gene Cards, and other databases. Following the intersection of drug-disease targets, the DAVID database was used to implement the enrichment analysis of GO functions and KEGG pathways, and then the network diagram of "intersected target-KEGG" relationship was constructed. Autodock 4.2.6 software was used to carry out the molecular docking of core targets to drug components. Based on the establishment of a mouse model of cryptosporidiosis, the validity of the targets in the TNF/NF-κB signaling pathway was confirmed using Western blot analysis and Quantitative Rea-ltime-PCR. A total of 41 intersectional targets of oxymatrine and Cryptosporidium were generated from the results, and five core targets were screened out by network analysis, including RELA, AKT1, ESR1, TNF, and CASP3. The enrichment analysis showed that oxymatrine could regulate multiple gene targets, mediate TNF, Apoptpsis, IL-17, NF-κB and other signaling pathways. Molecular docking experiments revealed that oxymatrine was tightly bound to core targets with stable conformation. Furthermore, we found through animal experiments that oxymatrine could regulate the mRNA and protein expression of IL-6, NF-κB, and TNF-α in the intestinal tissues of post-infected mice through the TNF/NF-κB signaling pathway. Therefore, it can be concluded that oxymatrine can regulate the inflammatory factors TNF-α, NF-κB, and IL-6 through the TNF/NF-κB signaling pathway for the treatment of cryptosporidiosis. This prediction has also been validated by network pharmacology and animal experiments.

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Background Chikungunya virus (CHIKV) infection poses a significant global health threat, necessitating a deeper understanding of its molecular mechanisms for effective management and treatment. This study aimed to understand the molecular and genetic mechanisms of CHIKV infection by analyzing microarray expression data. Methodology National Center for Biotechnology Information (NCBI) GEO2R with an adjusted p-value cut-off of <0.05 and |log2FC ≥ 1.5| was used to identify the differentially expressed genes involved in CHIKV infection using microarray data from the Gene Expression Omnibus (GEO) database, followed by enrichment analysis, protein-protein interaction (PPI) network construction, and, finally, hub gene identification. Results Analysis of the microarray dataset revealed 25 highly significant differentially expressed genes (DEGs), including 21 upregulated and four downregulated genes. PPI network analysis elucidated interactions among these DEGs, with hub genes such as ACTB and CTNNB1 exhibiting central roles. Enrichment analysis identified crucial pathways, including leukocyte transendothelial migration, regulation of actin cytoskeleton, and thyroid hormone signaling, implicating their involvement in CHIKV infection. Furthermore, the study highlights potential therapeutic targets such as ACTB and CTNNB1, which showed significant upregulation in infected cells. Conclusions These findings underscore the complex interplay between viral infection and host cellular processes, shedding light on novel avenues for diagnostic marker discovery and advancing antiviral strategies. In this study, we shed light on the molecular and genetic mechanisms of CHIKV infection and the potential role of ACTB and CTNNB1 genes.

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Ulcerative colitis (UC) is a chronic inflammatory disease that targets the colon and has seen an increasing prevalence worldwide. In our pursuit of new diagnostic and therapeutic approaches for UC, we undertook a sequencing of colons from UC mouse models. We focused on analyzing their differentially expressed genes (DEGs), enriching pathways, and constructing protein-protein interaction (PPI) and Competing Endogenous RNA (ceRNA) networks. Our analysis highlighted novel DEGs such as Tppp3, Saa3, Cemip, Pappa, and Nr1d1. These DEGs predominantly play roles in pathways like cytokine-mediated signaling, extracellular matrix organization, extracellular structure organization, and external encapsulating structure organization. This suggests that the UC pathogenesis is intricately linked to the interactions between immune and non-immune cells with the extracellular matrix (ECM). To corroborate our findings, we also verified certain DEGs through quantitative real-time PCR. Within the PPI network, nodes like Stat3, Il1b, Mmp3, and Lgals3 emerged as significant and were identified to be involved in the crucial cytokine-mediated signaling pathway, which is central to inflammation. Our ceRNA network analysis further brought to light the role of the Smad7 Long non-coding RNA (lncRNA). Key MicroRNA (miRNAs) in the ceRNA network were pinpointed as mmu-miR-17-5p, mmu-miR-93-5p, mmu-miR-20b-5p, mmu-miR-16-5p, and mmu-miR-106a-5p, while central mRNAs included Egln3, Plagl2, Sema7a, Arrdc3, and Stat3. These insights imply that ceRNA networks are influential in UC progression and could provide further clarity on its pathogenesis. In conclusion, this research deepens our understanding of UC pathogenesis and paves the way for potential new diagnostic and therapeutic methods. Nevertheless, to solidify our findings, additional experiments are essential to confirm the roles and molecular interplay of the identified DEGs in UC.

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Background: Crohn's disease (CD) is a chronic idiopathic inflammatory bowel disease affecting the entire gastrointestinal tract from the mouth to the anus. These patients often experience a period of symptomatic relapse and remission. A 20 - 30% symptomatic recurrence rate is reported in the first year after surgery, with a 10% increase each subsequent year. Thus, surgery is done only to relieve symptoms and not for the complete cure of the disease. The determinants and the genetic factors of this disease recurrence are also not well-defined. Therefore, enhanced diagnostic efficiency and prognostic outcome are critical for confronting CD recurrence. Methods: We analysed ileal mucosa samples collected from neo-terminal ileum six months after surgery (M6=121 samples) from Crohn's disease dataset (GSE186582). The primary aim of this study is to identify the potential genes and critical pathways in post-operative recurrence of Crohn's disease. We combined the differential gene expression analysis with Recursive feature elimination (RFE), a machine learning approach to get five critical genes for the postoperative recurrence of Crohn's disease. The features (genes) selected by different methods were validated using five binary classifiers for recurrence and remission samples: Logistic Regression (LR), Decision tree classifier (DT), Support Vector Machine (SVM), Random Forest classifier (RF), and K-nearest neighbor (KNN) with 10-fold cross-validation. We also performed weighted gene co-expression network analysis (WGCNA) to select specific modules and feature genes associated with Crohn's disease postoperative recurrence, smoking, and biological sex. Combined with other biological interpretations, including Gene Ontology (GO) analysis, pathway enrichment, and protein-protein interaction (PPI) network analysis, our current study sheds light on the in-depth research of CD diagnosis and prognosis in postoperative recurrence. Results: PLOD2, ZNF165, BOK, CX3CR1, and ARMCX4, are the important genes identified from the machine learning approach. These genes are reported to be involved in the viral protein interaction with cytokine and cytokine receptors, lysine degradation, and apoptosis. They are also linked with various cellular and molecular functions such as Peptidyl-lysine hydroxylation, Central nervous system maturation, G protein-coupled chemoattractant receptor activity, BCL-2 homology (BH) domain binding, Gliogenesis and negative regulation of mitochondrial depolarization. WGCNA identified a gene co-expression module that was primarily involved in mitochondrial translational elongation, mitochondrial translational termination, mitochondrial translation, mitochondrial respiratory chain complex, mRNA splicing via spliceosome pathways, etc.; Both the analysis result emphasizes that the mitochondrial depolarization pathway is linked with CD recurrence leading to oxidative stress in promoting inflammation in CD patients. Conclusion: These key genes serve as the novel diagnostic biomarker for the postoperative recurrence of Crohn's disease. Thus, among other treatment options present until now, these biomarkers would provide success in both diagnosis and prognosis, aiming for a long-lasting remission to prevent further complications in CD.

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Introduction: Colibacillosis is a worldwide prevalent disease in poultry production linked to Escherichia coli strains that belong to the avian pathogenic E. coli (APEC) pathotype. While many virulence factors have been linked to APEC isolates, no single gene or set of genes has been found to be exclusively associated with the pathotype. Moreover, a comprehensive description of the biological processes linked to APEC pathogenicity is currently lacking. Methods: In this study, we compiled a dataset of 2015 high-quality avian E. coli genomes from pathogenic and commensal isolates, based on publications from 2000 to 2021. We then conducted a genome-wide association study (GWAS) and integrated candidate gene identification with available protein-protein interaction data to decipher the genetic network underlying the biological processes connected to APEC pathogenicity. Results: Our GWAS identified variations in gene content for 13 genes and SNPs in 3 different genes associated with APEC isolates, suggesting both gene-level and SNP-level variations contribute to APEC pathogenicity. Integrating protein-protein interaction data, we found that 15 of these genes clustered in the same genetic network, suggesting the pathogenicity of APEC might be due to the interplay of different regulated pathways. We also found novel candidate genes including an uncharacterized multi-pass membrane protein (yciC) and the outer membrane porin (ompD) as linked to APEC isolates. Discussion: Our findings suggest that convergent pathways related to nutrient uptake from host cells and defense from host immune system play a major role in APEC pathogenicity. In addition, the dataset curated in this study represents a comprehensive historical genomic collection of avian E. coli isolates and constitutes a valuable resource for their comparative genomics investigations.

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ETHNOPHARMACOLOGICAL RELEVANCE: The efficacy of the herbal formula Huosu-Yangwei (HSYW) in the treatment of advanced gastric cancer and chronic atrophic gastritis with precancerous lesions has been reported in clinical trials. However, the molecular mechanisms underlying its inhibition of gastric tumor are not well-understood. AIM OF THE STUDY: Combined with transcriptomics and systems network-based molecular mechanism to explore the potential circRNA-miRNA-mRNA network of HSYW in the treatment of gastric cancer. MATERIALS AND METHODS: Animal experiments were conducted to investigate the effect of HSYW on tumor growth in vivo. RNA sequencing (RNA-seq) was implemented to identify the differentially expressed (DE) genes. Predictive miRNA targets and mRNA were used to construct circRNA-miRNA-mRNA networks and protein-protein interaction (PPI) networks. Quantitative real-time PCR (qRT-PCR) was utilized to verify the accuracy of the proposed circRNA-miRNA-mRNA networks. Additionally, the differentially expressed target proteins between gastric cancer (GC) and normal patients were assessed using data from the TCGA (The Cancer Genome Atlas) and HPA (The Human Protein Atlas) databases. RESULTS: We demonstrate HSYW significantly inhibits tumor growth of N87 cell-bearing Balb/c mice. Transcriptomic analysis revealed the existence of 119 differentially expressed (DE) circRNAs and 200 DE mRNAs between HSYW-treated and model mice. By associating predicted circRNA-miRNA pairs and miRNA-mRNA pairs, we constructed a circRNA-miRNA-mRNA (CMM) network. Furthermore, a protein-protein interaction (PPI) network was developed using the differential expressed mRNAs. Consequently, the reconstructed core CMM network and qRT-PCR validation indicated that 4 circRNAs, 5 miRNAs and 6 mRNAs could potentially serve as biomarkers to assess the therapeutic effects of HSYW-treated N87-bearing Balb/c mice. The TCGA and HPA databases also demonstrated that mRNA KLF15 and PREX1 had substantial differences between gastric cancer (GC) and healthy controls. CONCLUSIONS: By combining the experimental and bioinformatics analysis, this study confirms that the circRNA_00240/hsa-miR-642a-5p/KLF15 and circRNA_07980/hsa-miR-766-3p/PREX1 pathways play critical roles in HSYW-treated gastric cancer.

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Cadmium (Cd) contamination is becoming a widespread environmental problem. However, the differential responsive mechanisms of Cd hyperaccumulator Solanum nigrum to low or high dose of Cd are not well documented. In this study, phenotypic and physiological analysis firstly suggested that the seedlings of S. nigrum showed slight leaf chlorosis symptoms under 25 µM Cd and severe inhibition on growth and photosynthesis under 100 µM Cd. Further proteomic analysis identified 105 differentially expressed proteins (DEPs) in the Cd-treated leaves. Under low dose of Cd stress, 47 DEPs are mainly involved in primary metabolic processes, while under high dose of Cd stress, 92 DEPs are mainly involved in photosynthesis, energy metabolism, production of phytochelatin and reactive oxygen species (ROS). Protein-protein interaction (PPI) network analysis of DEPs support above differential responses in the leaves of S. nigrum to low and high dose of Cd treatments. This work provides the differential responsive mechanisms in S. nigrum to low and high dose of Cd, and the theoretical foundation for the application of hyperaccumulating plants in the phytoremediation of Cd-contaminated soils.

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Mucormycosis or 'Black Fungus' has been known to target immunocompromised individuals even before the emergence of COVID-19. Nevertheless, the present circumstances provide the best opening for Covid Associated Mucormycosis (CAM), as the global pandemic is engulfing a large part of human population making them immunocompromised. This drastic increase in Mucormycosis infections has to be addressed as early as possible. There is a growing tendency of relying upon herbal drugs that have minimal side effects and does not compromise our immune system. Recently, the concept of network pharmacology has grabbed the attention of modern science, especially advanced medical sciences. This is a new discipline that can use computational power to systematically catalogue the molecular interactions between botanical formulations and the human body. In this study, Neem and Turmeric was considered as the target plants and an attempt was made to reveal various aspects through which phytocompounds derived from them may effectively manage CAM menace. We have taken a step-by-step approach for identifying the target proteins and ligands associated with Mucormycosis treatment. Functional network analysis and Molecular docking approaches were applied to validate our findings. Quercetin derived from both Neem and Turmeric was found to be one of the main phytocompounds working against Mucormycosis. Along with that, Caffeic acid, Curcumin, Kaempferol, Tetrahydrocurcumin and Myricetin also play a pivotal role in fighting against Black-Fungus. A thorough analysis of our result suggested a triple-front attack on the fungal pathogens and the approaches are necrosis inhibition, iron chelation and immuno-boosting.Communicated by Ramaswamy H. Sarma.

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Background: Bromodomains are a structurally conserved epigenetic reader domain that bind to acetylated lysine residues in both histone and non-histone proteins. Bromodomain-containing proteins (BRD proteins) often function as scaffolding proteins in the assembly of multi-protein complexes to regulate diverse biological processes. BRD proteins have been classified based on biological and functional similarity, however the functions of many BRD proteins remains unknown. PPI network analysis is useful for revealing organizational roles, identifying functional clusters, and predicting function for BRD proteins. Results: We used available data to construct protein-protein interaction networks (PPINs) to study the properties of the human bromodomain protein family. The network properties of the BRD PPIN establishes that the BRD proteins serve as hub proteins that are enriched near the global center to form an inter-connected PPIN. We identified dense subgraphs formed by BRD proteins and find that different BRD proteins share topological similarity and functional associations. We explored the functional relationships through clustering and Hallmark pathway gene set enrichment analysis and identify potential biological roles for different BRD proteins. Conclusion: In our network analysis we confirmed that BRD proteins are conserved central nodes in the human PPI network and function as scaffolds to form distinctive functional clusters. Overall, this study provides detailed insight into the predictive functions of BRD proteins in the context of functional complexes and biological pathways.

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BACKGROUND: Neuropathic pain is a common chronic pain, characterized by spontaneous pain and mechanical allodynia. The incidence of neuropathic pain is on the rise due to infections, higher rates of diabetes and stroke, and increased use of chemotherapy drugs in cancer patients. At present, due to its pathophysiological process and molecular mechanism remaining unclear, there is a lack of effective treatment and prevention methods in clinical practice. Now, we use bioinformatics technology to integrate and filter hub genes that may be related to the pathogenesis of neuropathic pain, and explore their possible molecular mechanism by functional annotation and pathway enrichment analysis. METHODS: The expression profiles of GSE24982, GSE2884, GSE2636 and GSE30691 were downloaded from the Gene Expression Omnibus（GEO）database, and these datasets include 93 neuropathic pain Rattus norvegicus and 59 shame controls. After the four datasets were all standardized by quantiles, the differentially expressed genes (DEGs) between NPP Rattus norvegicus and the shame controls were finally identified by the robust rank aggregation (RRA) analysis method. In order to reveal the possible underlying biological function of DEGs, the Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis of DEGs were performed. In addition, a Protein-protein Interaction (PPI) network was also established. At the end of our study, a high throughput sequencing dataset GSE117526 was used to corroborate our calculation results. RESULTS: Through RRA analysis of the above four datasets GSE24982, GSE2884, GSE2636, and GSE30691, we finally obtained 231 DEGs, including 183 up-regulated genes and 47 down-regulated genes. Arranging 231 DEGs in descending order according to |log2 fold change (FC)|, we found that the top 20 key genes include 14 up-regulated genes and 6 down-regulated genes. The most down-regulated hub gene abnormal expressed in NPP was Egf17 (P-value = 0.008), Camk2n2 (P-value = 0.002), and Lep (P-value = 0.02), and the most up-regulated hub gene abnormal expressed in NPP was Nefm (P-value = 1.08E-06), Prx (P-value = 2.68E-07), and Stip1 (P-value = 4.40E-07). In GO functional annotation analysis results, regulation of ion transmembrane transport (GO:0034765; P-value = 1.45E-09) was the most remarkable enriched for biological process, synaptic membrane (GO:0097060; P-value = 2.95E-08) was the most significantly enriched for cellular component, channel activity (GO:0015267; P-value = 2.44E-06) was the most prominent enriched for molecular function. In KEGG pathway enrichment analysis results, the top three notable enrichment pathways were Neuroactive ligand-receptor interaction (rno04080; P-value = 3.46E-08), Calcium signaling pathway (rno04020; P-value = 5.37E-05), and Osteoclast differentiation (rno04380; P-value = 0.000459927). Cav1 and Lep appeared in the top 20 genes in both RRA analysis and PPI analysis, while Nefm appeared in RRA analysis and datasets GSE117526 validation analysis, so we finally identified these three genes as hub genes. CONCLUSIONS: Our research identified the hub genes and signal pathways of neuropathic pain, enriched the pathophysiological mechanism of neuropathic pain to some extent, and provided a possible basis for the targeted therapy of neuropathic pain.

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In recent years, the phenomenon of microbial resistance has become increasingly serious. The generation of reactive oxygen species (ROS) during the bactericidal process of antibiotics has attracted great interest, but little research has been done on the generation of ROS in the early stage of antibiotic action. We confirmed the rapid production of ROS by flow cytometry and transmission electron microscopy (TEM). GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis indicated that the oxidative phosphorylation pathway is the key pathway of ROS production. Protein-protein interaction (PPI) network results indicate that sdhC/D are key genes in the oxidative phosphorylation pathway. The overexpression of sdhC/D resulted in a lower survival rate than the control strain after antibiotic treatments, which might be due to excess ROS induced by sdhC/D overexpression. The production of superoxide anion in the overexpress strain was significantly higher than that in the control strain, which further verified the importance of sdhC/D in the ROS release of bacteria. Current results showed that bacteria produce large amounts of ROS in the early stage of gentamicin and ampicillin action, and the regulation patterns of genes in the key pathway were consistent. sdhC/D are key genes in the early ROS release process of bacteria. Our study provides a basis for the search of ROS-related enhancers of antimicrobial action.

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Deletion of brain-derived neurotrophic factor (BDNF) and upregulation of indoleamine 2,3-dioxygenase 1 (IDO1) are associated with depression severity in animals. The neurotransmitter hypothesis of depression at the transcriptomic level can be tested using BDNF- and IDO1-knockout mouse models and RNA-seq. In this study, BDNF+/-, IDO1-/-, and chronic ultra-mild stress (CUMS)-induced depression mouse models and controls were developed, and the differentially expressed genes were analyzed. Furthermore, the ceRNA package was used to search the lncRNA2Target database for potential lncRNAs. Finally, a protein-protein interaction (PPI) network was constructed using STRINGdb. By comparing the control and CUMS model groups, it was found that pathway enrichment analysis and ceRNA network analysis revealed that most differentially expressed genes (DEGs) were associated with protection of vulnerable neuronal circuits. In addition, we found the enriched pathways were associated with nervous system development and synapse organization when comparing the control and BDNF+/-model groups. When replicating the neurotransmitter disruption features of clinical patients, such comparisons revealed the considerable differences between CUMS and knockdown BDNF models, and the BDNF+/-model may be superior to the classic CUMS model. The data obtained in the present study implicated the potential DEGs and their enriched pathway in three mouse models related to depression and the regulation of the ceRNA network-mediated gene in the progression of depression. Together, our findings may be crucial for uncovering the mechanisms underlying the neurotransmitter hypothesis of depression in animals.

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BACKGROUND: The aim of this study was to mine cartilage damage and regeneration-related biomarkers and identify the gene regulatory networks of cartilage damage. METHODS: A gene expression data set (GSE129147) containing damaged and control samples collected from the knee of the same patients was employed. R package limma was used to identify differentially expressed genes (DEGs), and clusterProfiler was performed for the GO and KEGG functional enrichment analysis. Cytoscape plug-ins of CytoHubba and MCODE were applied to investigate protein-protein interaction (PPI) network, modules, and hub genes. RESULTS: We identified 422 DEGs that were involved in skeletal system development, bone development, ossification, mesenchyme development, mesenchymal cell differentiation, connective tissue development, osteoblast differentiation, and extracellular matrix. We dug out 30 hub genes, identified three PPI modules, and constructed a miRNA regulatory network for DEGs. The miRNAs of the DEGs were predicted by miRNet, and the miRNA-mRNA network displayed some important miRNAs such as miR-335-5p, miR-92a-3p, and miR-98-5p. CONCLUSIONS: Collectively, these results have the potential to clarify the mechanism of cartilage damage and to assist us in discovering the damage and repair-related biomarkers.

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INTRODUCTION: Obsessive-Compulsive Disorder (OCD) is one of the complex neuropsychiatric conditions. This disorder disables individuals in many different aspects of their personal and social life. Interactome analysis may provide a better understanding of this disorder's molecular origin and its underlying mechanisms. METHODS: In this study, the OCD-associated genes were extracted from the literature. The criterion for gene selection was to choose genes with at least one significant report. Furthermore, by applying Cytoscape and its plugins, protein-protein interaction network, and gene ontology of the 31 candidate genes related to OCD from genetic association studies is examined. The cross-validation method was used for network centrality assessment. RESULTS: A scale-free network, including 1940 nodes and 3269 edges for 31 genes, was constructed. According to the network centrality evaluation, ESR1, TNFα, DRD2, DRD4, HTR1B, HTR2A, and CDH2 showed the highest values and can be considered hub-bottlenecks elements. It is also confirmed by the number of 123 cross-validation tests that the frequency of these essential genes remains unaltered against the initial seed genes' changes with the accuracy of 0.962. Besides, enrichment analysis identified four highlighted biological processes related to the 31 candidate genes. The top biological processes are determined as dopamine transport, learning, memory, and monoamine transport. CONCLUSION: Among 31 initial genes, 7 were introduced as crucial elements for onset and development in OCD and can be suggested for further investigations. Furthermore, the complex molecular origin of OCD requires high-throughput screening for diagnosis and treatment goals. The findings are a possible valuable source to establish molecular-based diagnostic tools for OCD.

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Huosu Yangwei (HSYW) Formula is a traditioanl Chinese herbal medicine that has been extensively used to treat chronic atrophic gastritis, precancerous lesions of gastric cancer and advanced gastric cancer. However, the effective compounds of HSYW and its related anti-tumor mechanisms are not completely understood. In the current study, 160 ingredients of HSYW were identified and 64 effective compounds were screened by the ADMET evaluation. Furthermore, 64 effective compounds and 2579 potential targets were mapped based on public databases. Animal experiments demonstrated that HSYW significantly inhibited tumor growth in vivo. Transcriptional profiles revealed that 81 mRNAs were differentially expressed in HSYW-treated N87-bearing Balb/c mice. Network pharmacology and PPI network showed that 12 core genes acted as potential markers to evaluate the curative effects of HSYW. Bioinformatics and qRT-PCR results suggested that HSYW might regulate the mRNA expression of DNAJB4, CALD, AKR1C1, CST1, CASP1, PREX1, SOCS3 and PRDM1 against tumor growth in N87-bearing Balb/c mice.

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BACKGROUND: Ionizing radiation, especially heavy ion (HI) beams, has been widely used in biology and medicine. However, the mechanism of membrane damage by such radiation remains primarily uncharacterized. PURPOSE: Transcriptomic profiles of Escherichia coli (E. coli) treated with HI illustrated the response mechanisms of the membrane, mainly ABC transporters, related genes regulated by antibiotics treatment through enrichment analyses of GO and KEGG. The networks of protein-protein interactions indicated that LsrB was the crucial one among the ABC transporters specially regulated by HI through the calculation of plugins MCODE and cytoHubba of Cytoscape. Finally, the expression pattern, GO/KEGG enrichment terms, and the interaction between nine LuxS/AI-2 quorum sensing system members were investigated. CONCLUSIONS: Above all, results suggested that HI might perform membrane damage through regulated material transport, inhibited LuxS/AI-2 system, finally impeded biofilm formation. This work provides further evidence for the role of ABC transporters, especially LsrB, in membrane damage of E. coli to HI. It will provide new strategies for improving the precise application of HI.

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Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in China. Sinisan (SNS) is a traditional Chinese medicine formula that has been widely used in treating chronic liver diseases, including NAFLD. However, its underlying biological mechanisms are still unclear. In this study, we employed a network pharmacology approach consisting of overlapped terms- (genes or pathway terms-) based analysis, protein-protein interaction (PPI) network-based analysis, and PPI clusters identification. Unlike the previous network pharmacology study, we used the shortest path length-based network proximity algorithm to evaluate the efficacy of SNS against NAFLD. And we also used random walk with restart (RWR) algorithm and Community Cluster (Glay) algorithm to identify important targets and clusters. The screening results showed that the mean shortest path length between genes of SNS and NAFLD was significantly smaller than degree-matched random ones. Six PPI clusters were identified and ten hub targets were obtained, including STAT3, CTNNB1, MAPK1, MAPK3, AGT, NQO1, TOP2A, FDFT1, ALDH4A1, and KCNH2. The experimental study indicated that SNS reduced hyperlipidemia, liver steatosis, and inflammation. Most importantly, JAK2/STAT3 signal was inhibited by SNS treatment and was recognized as the most important signal considering the network pharmacology part. This study provides a systems perspective to study the relationship between Chinese medicines and diseases and helps to discover potential mechanisms by which SNS ameliorates NAFLD.