Identification of microRNAs and messenger RNAs involved in human umbilical cord mesenchymal stem cell treatment of ischemic cerebral infarction using integrated bioinformatics analysis

In recent years,a large number of differentially expressed genes have been identified in human umbilical cord mesenchymal stem cell(hUMSC)transplants for the treatment of ischemic cerebral infarction.These genes are involved in various biochemical processes,but the role of microRNAs(miRNAs)in this process is still unclear.From the Gene Expression Omnibus(GEO)database,we downloaded two microarray datasets for GSE78731(messenger RNA(mRNA)profile)and GSE97532(miRNA profile).The differentially expressed genes screened were compared between the hUMSC group and the middle cerebral artery occlusion group.Gene ontology enrichment and pathway enrichment analyses were subsequently conducted using the online Database for Annotation,Visualization,and Integrated Discovery.Identified genes were applied to perform weighted gene co-suppression analyses,to establish a weighted co-expression network model.Furthermore,the protein-protein interaction network for differentially expressed genes from turquoise modules was built using Cytoscape(version 3.40)and the most highly correlated subnetwork was extracted from the protein-protein interaction network using the MCODE plugin.The predicted target genes for differentially expressed miRNAs were also identified using the online database starBase v3.0.A total of 3698 differentially expressed genes were identified.Gene ontology analysis demonstrated that differentially expressed genes that are related to hUMSC treatment of ischemic cerebral infarction are involved in endocytosis and inflammatory responses.We identified 12 differentially expressed miRNAs in middle cerebral artery occlusion rats after hUMSC treatment,and these differentially expressed miRNAs were mainly involved in signaling in inflammatory pathways,such as in the regulation of neutrophil migration.In conclusion,we have identified a number of differentially expressed genes and differentially expressed mRNAs,miRNA-mRNAs,and signaling pathways involved in the hUMSC treatment of ischemic cerebral infarction.Bioinformatics and interaction analyses can provide novel clues for further research into hUMSC treatment of ischemic cerebral infarction.

Molecular Cloning and Bioinformatics Analysis of sucC Gene of Vibrio alginolyticus Strain HY9901

[Objectives]To clone the sucC gene of Vibrio alginolyticus strain HY9901 and conduct the bioinformatics analysis.[Methods]Based on the sucC gene of V.alginolyticus strain HY9901,specific primers were designed to amplify the full length sequence by PCR and make further analysis.[Results]The theoretical molecular weight of SucC protein was about 41528.45 Da,and the full length was 1167 bp,encoding 388 amino acids.It has no signal peptide and transmembrane region,and has a variety of functional sites.It is predicted that it is mainly located in the cytoplasm,and the ubiquitin and lactate modification sites overlap,and it has high gene homology with Vibrio parahaemolyticus.Theα-helix,random coil and extended strand are the main secondary structures.The similarity between the constructed three-level structure model and the template is high.[Conclusions]This study reveals the structural characteristics and functional potential of SucC protein,and provides a theoretical basis for the study of drug resistance mechanism and prevention strategies.

Identification of differentially expressed genes regulated by methylation in colon cancer based on bioinformatics analysis

BACKGROUND DNA methylation, acknowledged as a key modification in the field of epigenetics, regulates gene expression at the transcriptional level. Aberrant methylation in DNA regulatory regions could upregulate oncogenes and downregulate tumor suppressor genes without changing the sequences.However, studies of methylation in the control of gene expression are still inadequate. In the present research, we performed bioinformatics analysis to clarify the function of methylation and supply candidate methylation-related biomarkers and drivers for colon cancer.AIM To identify and analyze methylation-regulated differentially expressed genes(MeDEGs) in colon cancer by bioinformatics analysis.METHODS We downloaded RNA expression profiles, Illumina Human Methylation 450 K BeadChip data, and clinical data of colon cancer from The Cancer Genome Atlas project. MeDEGs were identified by analyzing the gene expression and methylation levels using the edgeR and limma package in R software. Gene ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed in the DAVID database and KEGG Orthology-Based Annotation System 3.0, respectively. We then conducted Kaplan–Meier survival analysis to explore the relationship between methylation and expression and prognosis. Gene set enrichment analysis(GSEA) and investigation of protein-protein interactions(PPI) were performed to clarify the function of prognosis-related genes.RESULTS A total of 5 up-regulated and 81 down-regulated genes were identified asMeDEGs. GO and KEGG pathway analyses indicated that MeDEGs were enriched in multiple cancer-related terms. Furthermore, Kaplan–Meier survival analysis showed that the prognosis was negatively associated with the methylation status of glial cell-derived neurotrophic factor(GDNF) and reelin(RELN). In PPI networks, GDNF and RELN interact with neural cell adhesion molecule 1. Besides, GDNF can interact with GDNF family receptor alpha(GFRA1), GFRA2, GFRA3, and RET. RELN can interact with RAFAH1 B1,disabled homolog 1, very low-density lipoprotein receptor, lipoprotein receptorrelated protein 8, and NMDA 2 B. Based on GSEA, hypermethylation of GDNF and RELN were both significantly associated with pathways including "RNA degradation," "ribosome," "mismatch repair," "cell cycle" and "base excision repair."CONCLUSION Aberrant DNA methylation plays an important role in colon cancer progression.MeDEGs that are associated with the overall survival of patients may be potential targets in tumor diagnosis and treatment.

Discovery of Key Molecular Pathways of C1 Metabolism and Formaldehyde Detoxification in Maize through a Systematic Bioinformatics Literature Review

Computational systems biology approaches provide insights to understand complex molecular phenomena in living systems. Such understanding demands the need to systematically interrogate and review existing literature to refine and distil key molecular pathways. This paper explores a methodological process to identify key molecular pathways from systematic bioinformatics literature review. This process is used to identify molecular pathways for a ubiquitous molecular process in all plant biological systems: C1 metabolism and formaldehyde detoxification, specific to maize. The C1 metabolism is essential for all organisms to provide one-carbon units for methylation and other types of modifications, as well as for nucleic acid, amino acid, and other biomolecule syntheses. Formaldehyde is a toxic one-carbon molecule which is produced endogenously and found in the environment, and whose detoxification is an important part of C1 metabolism. This systematic review involves a five-part process: 1) framing of the research question;2) literature collection based on a parallel search strategy;3) relevant study selection based on search refinement;4) molecular pathway identification;and 5) integration of key molecular pathway mechanisms to yield a well-defined set molecular systems associated with a particular biochemical function. Findings from this systematic review produced three main molecular systems: a) methionine biosynthesis;b) the methylation cycle;and c) formaldehyde detoxification. Specific insights from the resulting molecular pathways indicate that normal C1 metabolism involves the transfer of a carbon group from serine through a folate-mediated pathway to methionine, and eventually the methylation of a biomolecule. In photosynthetic tissues, C1 metabolism often proceeds in reverse towards serine biosynthesis and formate oxidation. C1 metabolism, in maize, appears to be present in the developing embryo and endosperm indicating that these cells are vulnerable to perturbations in formaldehyde detoxification. These insights demonstrate the value of a systematic bioinformatics literature review process from a broad spectrum of domain literature to specific and relevant molecular pathways.

Targeted gene sequencing and bioinformatics analysis of patients with gallbladder neuroendocrine carcinoma:A case report

BACKGROUND Gallbladder neuroendocrine carcinoma(NEC)represents a subtype of gallbladder malignancies characterized by a low incidence,aggressive nature,and poor prognosis.Despite its clinical severity,the genetic alterations,mechanisms,and signaling pathways underlying gallbladder NEC remain unclear.CASE SUMMARY This case study presents a rare instance of primary gallbladder NEC in a 73-year-old female patient,who underwent a radical cholecystectomy with hepatic hilar lymphadenectomy and resection of liver segments IV-B and V.Targeted gene sequencing and bioinformatics analysis tools,including STRING,GeneMANIA,Metascape,TRRUST,Sangerbox,cBioPortal and GSCA,were used to analyze the biological functions and features of mutated genes in gallbladder NEC.Twelve mutations(APC,ARID2,IFNA6,KEAP1,RB1,SMAD4,TP53,BTK,GATA1,GNAS,and PRDM3)were identified,and the tumor mutation burden was determined to be 9.52 muts/Mb via targeted gene sequencing.A protein-protein interaction network showed significant interactions among the twelve mutated genes.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to assess mutation functions and pathways.The results revealed 40 tumor-related pathways.A key regulatory factor for gallbladder NEC-related genes was identified,and its biological functions and features were compared with those of gallbladder carcinoma.CONCLUSION Gallbladder NEC requires standardized treatment.Comparisons with other gallbladder carcinomas revealed clinical phenotypes,molecular alterations,functional characteristics,and enriched pathways.

Transcriptomic and bioinformatics analysis of the mechanism by which erythropoietin promotes recovery from traumatic brain injury in mice

Recent studies have found that erythropoietin promotes the recovery of neurological function after traumatic brain injury.However,the precise mechanism of action remains unclea r.In this study,we induced moderate traumatic brain injury in mice by intrape ritoneal injection of erythro poietin for 3 consecutive days.RNA sequencing detected a total of 4065 differentially expressed RNAs,including 1059 mRNAs,92 microRNAs,799 long non-coding RNAs,and 2115circular RNAs.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses revealed that the coding and non-coding RNAs that were differentially expressed after traumatic brain injury and treatment with erythropoietin play roles in the axon guidance pathway,Wnt pathway,and MAPK pathway.Constructing competing endogenous RNA networks showed that regulatory relationship between the differentially expressed non-coding RNAs and mRNAs.Because the axon guidance pathway was repeatedly enriched,the expression of Wnt5a and Ephb6,key factors in the axonal guidance pathway,was assessed.Ephb6 expression decreased and Wnt5a expression increased after traumatic brain injury,and these effects were reversed by treatment with erythro poietin.These findings suggest that erythro poietin can promote recove ry of nerve function after traumatic brain injury through the axon guidance pathway.

Bioinformatics analyses of differentially expressed genes associated with spinal cord injury:a microarray-based analysis in a mouse model

Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury,which may affect the microenvironment of the damaged site.Microarray analysis provides a new opportunity for investigating diagnosis,treatment,and prognosis of spinal cord injury.However,differentially expressed genes are not consistent among studies,and many key genes and signaling pathways have not yet been accurately studied.GSE5296 was retrieved from the Gene Expression Omnibus DataSet.Differentially expressed genes were obtained using R/Bioconductor software(expression changed at least two-fold;P < 0.05).Database for Annotation,Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors.The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease.In total,this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5,4,and 24 hours,and 3,7,and 28 days after spinal cord injury.The number of downregulated genes was smaller than the number of upregulated genes at each time point.Database for Annotation,Visualization and Integrated Discovery analysis found that many inflammation-related pathways were upregulated in injured spinal cord.Additionally,expression levels of these inflammation-related genes were maintained for at least 28 days.Moreover,399 regulation modes and 77 nodes were shown in the protein-protein interaction network of upregulated differentially expressed genes.Among the 10 upregulated differentially expressed genes with the highest degrees of distribution,six genes were transcription factors.Among these transcription factors,ATF3 showed the greatest change.ATF3 was upregulated within 30 minutes,and its expression levels remained high at28 days after spinal cord injury.These key genes screened by bioinformatics tools can be used as biological markers to diagnose diseases and provide a reference for identifying therapeutic targets.

Computational and bioinformatics tools for understanding disease mechanisms

Computational methods have significantly transformed biomedical research,offering a comprehensive exploration of disease mechanisms and molecular protein functions.This article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease states.The utilization of protein/gene interaction and genetic variation databases,coupled with pathway analysis can facilitate the identification of potential drug targets.By bridging the gap between molecular-level information and disease understanding,this review contributes insights into the impactful utilization of computational methods,paving the way for targeted interventions and therapeutic advancements in biomedical research.

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

AIM To identify multiple micro RNAs(mi RNAs) for predicting the prognosis of gastric cancer(GC) patients by bioinformatics analysis.METHODS The original microarray dataset GSE93415,which included 20 GC and 20 tumor adjacent normal gastric mucosal tissues,was downloaded from the Gene Expression Omnibus database and used for screening differentially expressed mi RNAs(DEMs).The cutoff criteria were P < 0.05 and fold change > 2.0.In addition,we acquired the mi RNA expression profiles and clinical information of 361 GC patients from The Cancer Genome Atlas database to assess the prognostic role of the DEMs.The target genes of mi RNAs were predicted using Target Scan,mi RDB,mi RWalk,and DIANA,and then the common target genes were selected for functional enrichment analysis.RESULTS A total of 110 DEMs including 19 up-regulated and 91 down-regulated mi RNAs were identified between 20 pairs of GC and tumor adjacent normal tissues,and the Kaplan-Meier survival analysis found that a threemi RNA signature(mi R-145-3 p,mi R-125 b-5 p,and mi R-99 a-5 p) had an obvious correlation with the survival of GC patients.Furthermore,univariate and multivariate Cox regression analyses indicated that the three-mi RNA signature could be a significant prognostic marker in GC patients.The common target genes of the three mi RNAs are added up to 108 and used for Gene Functional Enrichment analysis.Biological Process and Molecular Function analyses showed that the target genes are involved in cell recognition,gene silencing and nucleic acid binding,transcription factor activity,and transmembrane receptor activity.Cellular Component analysis revealed that the genes are portion of nucleus,chromatin silencing complex,and TORC1/2 complex.Biological Pathway analysis indicated that the genes participate in several cancer-related pathways,such as the focal adhesion,PI3 K,and m TOR signaling pathways.CONCLUSION This study justified that a three-mi RNA signature could play a role in predicting the survival of GC patients.

Acupuncture as a bioinformatics science and a proposal for the recognition of a new law of nature “Law of therapeutic neuromodulation”

Brain, an organ similar to a computer, is the ultimate director of the body1. This means that organs, tissues and cells are under its control and that these parts of the body do not control what happen to them. If the brain is functioning properly, we have health;and if it works wrongly a disease will show. Acting on the brain by neuromodulation, by means of acupuncture, homeopathy or even allopathic drugs can produce a therapeutic response. The purpose of this paper is to recognize this effect and propose a new Law of Cure which explains how several complementary and alternative medicine (CAM) systems work. In this theory, acupuncture works by stimulating peripheral sensory receptors and transmitting information to the brain which in turn will trigger a curative response to the affected organ. In this sense, acupuncture is an informatics system for a biological system, and therefore it could be considered part of the bioinformatics sciences, in the same idea that the brain is a living computer which has inputs and outputs and controls all process inside the body. In this paper we present the basis for this theory.

Gene Cloning and Bioinformatics Analysis of phoR Gene from Vibrio alginolyticus HY9901

PhoR is a histidine kinase in a two-component regulatory system that regulates phosphorus metabolic pathways and undertakes the key mission of information transmission in pathogenic bacteria.The full-length phoR gene was successfully cloned from the Vibrio alginolyticus HY9901 strain.A comprehensive analysis of the cloned gene was conducted using bioinformatics.Sequence analysis revealed that the total length of the phoR gene(GenBank accession No.:KJ958404.1)is 1299 bp,with the coding region containing a total of 432 amino acid residues.The phylogenetic tree of PhoR revealed that it belongs to the same subclade as V.diabolicus.The SMART program was employed for the purpose of functional domain prediction,which revealed that PhoR possesses three major functional domains:PAS(amino acids 98-166),HisKA(amino acids 205-272),and HATPase_c(amino acids 317-429).

Cloning and Bioinformatics Analysis of hcp Gene in Aeromonas hydrophila

[Objectives]To explore the function of hcp gene in Aeromonas hydrophila.[Methods]A pair of specific primers was designed referring to the hcp gene sequence of A.hydrophila.The hcp gene was amplified by PCR,and performed bioinformatics analysis.[Results]The hcp gene had a total length of 1650 bp and encoded 549 amino acids.The theoretical molecular weight of the protein predicted was about 59476.44 kDa.After predicting the N-terminal signal peptide structure of the amino acid sequence,neither obvious signal peptide cleavage site nor signal peptide was found,and the protein had no transmembrane region.The amino acid sequence had a N-glycosylation site,4 protein kinase C phosphorylation sites,7 casein kinase II phosphorylation sites,9 N-myristoylation sites,4 isoprene binding sites,10 microbody C-terminal target signal sites,and an ATP/GTP binding site motif A(P-ring).The amino acid sequence of hcp gene of A.hydrophila was performed homology analysis with other Aeromonas strains,and it showed higher homology with A.veronii.In the secondary structure,theα-helix,β-sheet,random coil and extended strand accounted for 45.36%,6.01%,37.52%and 11.11%,respectively.The tertiary structure model consisted of 18α-helix and 22β-sheet.Analysis of protein-protein network interaction demonstrated that the proteins interacting with Hcp protein were AHA_3407,nrfA,nirB-1,nirB-2 and AHA_1112.[Conclusions]Through the bioinformatics prediction results,the basic information of hcp gene of A.hydrophila is preliminarily understood,and the possible function of this protein is predicted,in order to provide guidance for subsequent vaccine research.

Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis

BACKGROUND According to study,anoikis-related genes(ARGs)have been demonstrated to play a significant impact in cirrhosis,a major disease threatening human health worldwide.AIM To investigate the relationship between ARGs and cirrhosis development to provide insights into the clinical treatment of cirrhosis.METHODS RNA-sequencing data related to cirrhosis were obtained from the Gene Expression Omnibus database.Differentially expressed genes(DEGs)between cirrhotic and normal tissues were intersected with ARGs to derive differentially expressed ARGs(DEARGs).The DEARGs were filtered using the least absolute shrinkage and selection operator,support vector machine recursive feature elimination,and random forest algorithms to identify biomarkers for cirrhosis.These biomarkers were used to create a nomogram for predicting the prognosis of cirrhosis.The proportions of diverse immune cell subsets in cirrhotic vs normal tissues were compared using the CIBERSORT computational method.In addition,the linkage between immune cells and biomarkers was assessed,and a regulatory network of mRNA,miRNA,and transcription factors was constructed relying on the biomarkers.RESULTS The comparison of cirrhotic and normal tissue samples led to the identification of 635 DEGs.Subsequent intersection of the DEGs with ARGs produced a set of 26 DEARGs.Subsequently,three DEARGs,namely,ACTG1,STAT1,and CCR7,were identified as biomarkers using three machine-learning algorithms.The proportions of M1 and M2 macrophages,resting CD4 memory T cells,resting mast cells,and plasma cells significantly differed between cirrhotic and normal tissue samples.The proportions of M1 and M2 macrophages,resting CD4 memory T cells,and resting mast cells were significantly correlated with the expression of the three biomarkers.The mRNA–miRNA–TF network showed that ACTG1,CCR7,and STAT1 were regulated by 28,42,and 35 miRNAs,respectively.Moreover,AR,MAX,EP300,and FOXA1 were found to regulate four miRNAs related to the biomarkers.CONCLUSION This study revealed ACTG1,STAT1,and CCR7 as biomarkers of cirrhosis,providing a reference for developing novel diagnostic and therapeutic strategies for cirrhosis.

Molecular Cloning of clpX Gene from Vibrio alginolyticus HY9901 and Its Bioinformatics Analysis

According to the clpX gene sequence of Vibrio alginolyticus HY9901,a pair of specific primers were designed,and the full length was cloned by PCR and subjected to bioinformatics analysis.The results showed that the clpX gene was 1281 bp in length and encoded 426 amino acids.Its molecular structure formula was C 3842 H 6405 N 1281 O 1598 S 260,with a theoretical protein molecular weight of approximately 1044473.4 kDa and a theoretical pI value of 5.04.The clpX gene was predominantly situated within the cytoplasm,exhibiting unstable and hydrophilic protein characteristics.It possessed a signal peptide cleavage site,lacked a transmembrane region,and was not associated with any KEGG metabolic pathway.Additionally,it possessed 2 glycine phosphorylation sites,a CAMP-dependent protein kinase phosphorylation site,a C-terminal amidation modification site,6 protein kinase C phosphorylation sites,7 microbody C-terminal target signal sites,and an ATP/GTP site.The clpX phylogenetic tree was constructed using the MEGA 5.0 software via the neighbor-joining method.The results demonstrated that the clpX of V.alginolyticus exhibited up to 100%affinity with the clpX of Vibrio spp.The single subunit 3D structure model of the ClpX protein was obtained using the SWISS-MODEL program.A structural and functional analysis of the protein revealed the presence of three distinct ClpX structural and functional domains.In the prediction of secondary structure,the proportions ofα-helix,random coil,β-sheet and extended strand were 40.38%,37.09%,5.40%and 17.14%,respectively.The analysis of the ClpX protein through the STRING database revealed that the proteins interacting with the ClpX protein were Tig,Atpd,Hflb,Msrb-2,Rpod,Clpp,Clpa,Lon-1,Hfq,and ANP63951.1.A computational analysis of the ClpX protein identified a number of post-translational modification sites,including phosphorylation,acetylation,ubiquitination,glycosylation,methylation,S-palmitoylation,and lactylation.The significance of this study is to analyze the function of the clpX gene and establish a robust foundation for subsequent investigations into the mechanism of the clpX gene in Vibrio alginolyticus.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

BACKGROUND Circular RNAs(circRNAs)are involved in the pathogenesis of many diseases through competing endogenous RNA(ceRNA)regulatory mechanisms.AIM To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis(UC).METHODS We obtained gene expression profiles of circRNAs,miRNAs,and mRNAs in UC from the Gene Expression Omnibus dataset.The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions.Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs.We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram,whose efficacy was tested with the C-index,receiver operating characteristic curve(ROC),and decision curve analysis(DCA).RESULTS A circRNA-miRNA-mRNA regulatory network was obtained,containing 12 circRNAs,three miRNAs,and 38 mRNAs.Two optimal prognostic-related differentially expressed circRNAs,hsa_circ_0085323 and hsa_circ_0036906,were included to construct a predictive nomogram.The model showed good discrimination,with a C-index of 1(>0.9,high accuracy).ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.CONCLUSION This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC.The circRNa-miRNA-mRNA network in UC could be more clinically significant.

Effects of OGFOD1 in bladder cancer progression and its prognostic significance:Insights from bioinformatics analysis

Background:Previous studies have established the role of 2-oxoglutarate and Fe(II)-dependent oxygenase domain–containing protein 1(OGFOD1)in oncogenesis.The objective of this investigation was to discern the diagnostic and prognostic relevance of OGFOD1 within the context of bladder cancer(BLCA)using bioinformatics methodologies.Methods:We collected RNA sequencing data from The Cancer Genome Atlas database and verified it using the GSE13507 dataset.Immunohistochemical analysis was based on data from the human protein atlas,and the protein-protein interaction network was constructed using the STRING database.Bioinformatics analysis was performed using the R application,analyzing the correlation between clinical characteristics and OGFOD1 expression,exploring the potential mechanisms of OGFOD1 in BLCA through Kyoto Encyclopedia of Genes and Genomes analysis,and evaluating the diagnostic and prognostic value of OGFOD1 expression in BLCA through receiver operating characteristic curve analysis,Kaplan-Meier analysis,and multivariate Cox analysis.Furthermore,a BLCA prognostic nomogram was constructed.Results:We report higher expression levels of OGFOD1 in BLCA specimens compared with those in noncancerous tissues;this can be used to predict the outcome of the disease.Further,results suggest that OGFOD1 is implicated in the activation of the peroxisome proliferator-activated receptor signaling cascade,potentially interacting with other genes linked to expression in promoting the onset and progression of BLCA.Conclusions:OGFOD1 is a promising candidate as a prognostic indicator in BLCA.

To analyze the differentially expressed genes in chronic rejection after renal transplantation by bioinformatics

Objective: To use bioinformatics technology to analyse differentially expressed genes in chronic rejection after renal transplantation, we can screen out potential pathogenic targets associated with the development of this disease, providing a theoretical basis for finding new therapeutic targets. Methods: Gene microarray data were downloaded from the Gene Expression Profiling Integrated Database (GEO) and cross-calculated to identify differentially expressed genes (DEGs). Analysis of differentially expressed genes (DEGs) with gene ontology (GO) is a method used to study the differences in gene expression under different conditions as well as their functions and interrelationships, while Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis is a tool used to explore the functions and pathways of genes in specific biological processes. By calculating the distribution of immune cell infiltration, the result of immune infiltration in the rejection group can be analysed as a trait in Weighted Gene Co-Expression Network Analysis (WGCNA) for genes associated with rejection. Then, protein-protein interaction networks (PPI) were constructed using the STRING database and Cytoscape software to identify hub gene markers. Results: A total of 60 integrated DEGs were obtained from 3 datasets (GSE7392, GSE181757, GSE222889). By GO and KEGG analysis, the GEDs were mainly concentrated in the regulation of immune response, defence response, regulation of immune system processes, and stimulation response. The pathways were mainly enriched in antigen processing and presentation, EBV infection, graft-versus-host, allograft rejection, and natural killer cell-mediated cytotoxicity. After further screening using WGCNA and PPI networks, HLA-A, HLA-B, HLA-F, and TYROBP were identified as hub genes (Hub genes). The data GSE21374 with clinical information was selected to construct the diagnostic efficacy and risk prediction model plots of the four hub genes, and the results concluded that all four Hub genes had good diagnostic value (area under the curve in the range of 0.794-0.819). From the inference, it can be concluded that the four genes, HLA-A, HLA-B, HLA-F and TYROBP, may have an important role in the development and progression of chronic rejection after renal transplantation. Conclusion: DEGs play an important role in the study of the pathogenesis of chronic rejection after renal transplantation, and can provide theoretical support for further research on the pathogenesis of chronic rejection after renal transplantation and the discovery of new therapeutic targets through enrichment analysis and pivotal gene screening, as well as inferential analyses of related diagnostic efficacy and disease risk prediction.

Identification of hub genes associated with Helicobacter pylori infection and type 2 diabetes mellitus:A pilot bioinformatics study

BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.

Non-alcoholic fatty liver disease and Atherosclerosis at a crossroad:The overlap of a theory of change and bioinformatics

Atherosclerosis(ATH)and non-alcoholic fatty liver disease(NAFLD)are medical conditions that straddle a communal epidemiology,underlying mechanism and a clinical syndrome that has protean manifestations,touching every organ in the body.These twin partners,ATH and NAFLD,are seemingly straightforward and relatively simple topics when considered alone,but their interdependence calls for more thought.The study of the mutual relationship of NAFLD and ATH should involve big data analytics approaches,given that they encompass a constellation of diseases and are related to several recognized risk factors and health determinants and calls to an explicit theory of change,to justify intervention.Research studies on the“association between aortic stiffness and liver steatosis in morbidly obese patients”,published recently,sparsely hypothesize new mechanisms of disease,claiming the“long shadow of NAFLD”as a risk factor,if not as a causative factor of arterial stiffness and ATH.This statement is probably overreaching the argument and harmful for the scientific credence of this area of medicine.Despite the verification that NAFLD and cardiovascular disease are strongly interrelated,current evidence is that NAFLD may be a useful indicator for flagging early arteriosclerosis,and not a likely causative factor.Greater sustainable contribution by precision medicine tools,by validated bioinformatics approaches,is needed for substantiating conjectures,assumptions and inferences related to the management of big data and addressed to intervention for behavioral changes within an explicit theory of change.

Hub genes and key pathways of traumatic brain injury: bioinformatics analysis and in vivo validation

The exact mechanisms associated with secondary brain damage following traumatic brain injury(TBI)remain unclear;therefore,identifying the critical molecular mechanisms involved in TBI is essential.The m RNA expression microarray GSE2871 was downloaded from the Gene Expression Omnibus(GEO)repository.GSE2871 comprises a total of 31 cerebral cortex samples,including two post-TBI time points.The microarray features eight control and seven TBI samples,from 4 hours post-TBI,and eight control and eight TBI samples from 24 hours post-TBI.In this bioinformatics-based study,109 and 66 differentially expressed genes(DEGs)were identified in a Sprague-Dawley(SD)rat TBI model,4 and 24 hours post-TBI,respectively.Functional enrichment analysis showed that the identified DEGs were significantly enriched in several terms,such as positive regulation of nuclear factor-κB transcription factor activity,mitogen-activated protein kinase signaling pathway,negative regulation of apoptotic process,and tumor necrosis factor signaling pathway.Moreover,the hub genes with high connectivity degrees were primarily related to inflammatory mediators.To validate the top five hub genes,a rat model of TBI was established using the weight-drop method,and real-time quantitative polymerase chain reaction analysis of the cerebral cortex was performed.The results showed that compared with control rats,Tnf-α,c-Myc,Spp1,Cxcl10,Ptprc,Egf,Mmp9,and Lcn2 were upregulated,and Fn1 was downregulated in TBI rats.Among these hub genes,Fn1,c-Myc,and Ptprc may represent novel biomarkers or therapeutic targets for TBI.These identified pathways and key genes may provide insights into the molecular mechanisms of TBI and provide potential treatment targets for patients with TBI.This study was approved by the Experimental Animal Ethics Committee of the First Affiliated Hospital of Nanchang University,China(approval No.003)in January 2016.