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.

Identification and Validation of SLC9A2 as A Potential Tumor Suppressor in Colorectal Cancer:Integrating Bioinformatics Analysis with Experimental Confirmation

Objective To uncover the mechanisms underlying the development of colorectal cancer(CRC),we applied bioinformatic analyses to identify key genes and experimentally validated their possible roles in CRC onset and progression.Methods We performed Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis on differentially expressed genes(DEGs),constructed a protein-protein interaction(PPI)network to find the top 10 hub genes,and analyzed their expression in colon adenocarcinoma(COAD)and rectum adenocarcinoma(READ).We also studied the correlation between these genes and immune cell infiltration and prognosis and validated the expression of SLC9A2 in CRC tissues and cell lines using qRT-PCR and Western blotting.Functional experiments were conducted in vitro to investigate the effects of SLC9A2 on tumor growth and metastasis.Results We found 130 DEGs,with 45 up-regulated and 85 down-regulated in CRC.GO analysis indicated that these DEGs were primarily enriched in functions related to the regulation of cellular pH,zymogen granules,and transmembrane transporter activity.KEGG pathway analysis revealed that the DEGs played pivotal roles in pancreatic secretion,rheumatoid arthritis,and the IL-17 signaling pathway.We identified 10 hub genes:CXCL1,SLC26A3,CXCL2,MMP7,MMP1,SLC9A2,SLC4A4,CLCA1,CLCA4,and ZG16.GO enrichment analysis showed that these hub genes were predominantly involved in the positive regulation of transcription.Gene expression analysis revealed that CXCL1,CXCL2,MMP1,and MMP7 were highly expressed in CRC,whereas CLCA1,CLCA4,SLC4A4,SLC9A2,SLC26A3,and ZG16 were expressed at lower levels.Survival analysis revealed that 5 key genes were significantly associated with the prognosis of CRC.Both mRNA and protein expression levels of SLC9A2 were markedly reduced in CRC tissues and cell lines.Importantly,SLC9A2 overexpression in SW480 cells led to a notable inhibition of cell proliferation,migration,and invasion.Western blotting analysis revealed that the expression levels of phosphorylated ERK(p-ERK)and phosphorylated JNK(p-JNK)proteins were significantly increased,whereas there were no significant changes in the expression levels of ERK and JNK following SLC9A2 overexpression.Correlation analysis indicated a potential link between SLC9A2 expression and the MAPK signaling pathway.Conclusion Our study suggests that SLC9A2 acts as a tumor suppressor through the MAPK pathway and could be a potential target for CRC diagnosis and therapy.

Molecular Cloning and Bioinformatics Analysis of msrA Gene from Vibrio alginolyticus Strain HY9901

[Objectives]This study was conducted to understand the structure and function of MsrA protein.[Methods]With Vibrio alginolyticus HY9901 as the object of study,primers were designed to amplify the full-length gene of msrA,and its bioinformatics analysis was carried out.[Results]The full length of msrA gene was 639 bp,encoding 212 amino acids,and its theoretical molecular weight was about 23729.60 Da.The protein had a stable structure,and it was hydrophobic overall.The structure of signal peptides at the N terminal of the amino acid sequence was predicted,and it was found that there was no signal peptide cleavage site and no transmembrane region.The amino acid sequence of MsrA contained multiple signal binding sites.Protein subcellular localization showed that MsrA protein was most likely located in the cytoplasm.Homology analysis showed that MsrA of V.alginolyticus had high homology with other Vibrio species,and the highest homology with V.alginolyticus.In the prediction of functional domains,MsrA had the function of methionine sulfoxide reduction.In secondary structure prediction,MsrA contained random coils at a proportion of 46.70%,which was the highest.The similarity between the tertiary structure model of MsrA and template Q87SW6.1.A was 89.15%.PTM analysis showed that MsrA protein had many PTM modification sites such as phosphorylation and glycosylation sites.[Conclusions]This study provides some reference value for further study on the role of MsrA in bacterial antioxidant stress.

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

Vibrio alginolyticus is a zoonotic bacterium.A pair of specific primers was designed using the sodB gene sequence of Vibrio alginolyticus HY9901 in order to amplify the full length of the gene by PCR.The results indicated that the total length of the sodB gene was 585 bp and that it could encode 194 amino acids.The predicted amino acid sequence derivation indicated that the molecular weight of the protein was approximately 21.56 kDa,with an isoelectric point of 4.95.Upon prediction of the N-terminal signal peptide structure of the protein,no significant signal peptide cleavage site was observed,indicating that the protein lacked both a signal peptide and a transmembrane region.The amino acid sequence contained an N-glycosylation site,a casein kinase II phosphorylation site,a microsomal C-terminal target signal site,and a manganese and iron superoxide dismutase signal site.The probability of intracytoplasmic localization of the SodB protein was 56.5%,which was analyzed according to the subcellular localization of the protein.The amino acid sequence of the sodB gene of V.alginolyticus exhibited 98%-100%homology to other Vibrio species,clustering into the same subfamily with V.parahaem,indicating a relatively close relationship between them.In the prediction of protein structure,the proportions ofα-helix,random coil,β-sheet,and extended strand were 48.45%,30.41%,5.67%,and 15.46%,respectively.The similarity to template 1dt0.1.A reached 71.58%.A PTM site analysis revealed the presence of phosphorylation,glycosylation,ubiquitination,sumoylation,acetylation,and methylation modification sites,as well as the absence of lactylation modification sites.

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

[Objectives]This study was conducted to explore the biological functions of cyaA gene of Vibrio alginolyticus.[Methods]With DNA of V.alginolyticus HY 9901 as a template,primers were designed according to the sequence of cyaA gene,and the cyaA gene was amplified by PCR.Bioinformatics analysis was performed.[Results]The cyaA gene of V.alginolyticus HY9901 was 2529 bp in size,and encoded 842 amino acids.The molecular structure of CyaA protein was C_(4358)H_(6745)N_(1171)O_(1286)S_(35).Its theoretical molecular weight was 97.24167 kDa and the theoretical pI value was 5.56.It had no signal peptide and transmembrane domain.CyaA protein had three N-terminal glycosylation sites,one cAMP and cGMP-dependent protein kinase phosphorylation site,nine protein kinase C phosphorylation sites,nine casein kinase II phosphorylation sites,one tyrosine kinase phosphorylation site,seven N-terminal myristoylation sites,one pentenyl binding site and ten microbody C-terminal localization signal sites.Subcellular localization prediction showed that CyaA protein was mainly located in the nucleus and cytoplasm.Through multi-sequence alignment and phylogenetic tree construction,it was concluded that V.alginolyticus had high CyaA homology with other Vibrio species.cyaA of V.alginolyticus was clustered with Vibrio fluminensis and Vibrio marinisedimini,and they were closely related.The secondary structure of CyaA protein consisted ofα-helixes(43.11%),random coils(38.00%)and extended strands(14.49%).In protein network interaction,it was found that the proteins adjacent to CyaA protein were Crp-2,CpdA,Crr,PtsG-2,ANP67209.1,Crp-1,PykF,Pyk,RelA and Ndk.[Conclusions]This study provides a new idea for formulating strategies for the prevention and control of vibriosis.

Bioinformatics Analysis of the Association between Ewing’s Sarcoma and Tuberculosis Comorbidity

Objective To screen and analyze the differentially expressed genes of Ewing’s sarcoma (ES) and Tuberculosis (TB) by bioinformatics. Methods GEO gene chip public database in NCBI was used for data retrieval, and chip data GSE17674 and GSE57736 were selected as analysis objects. The R language limma toolkit was used to screen DEmRNAs, and the data were standardized, and the common differentially expressed genes were screened by Venn diagram. The GO function and KEGG pathway enrichment of common differentially expressed genes were analyzed by using the R cluster Profiler package. String database was selected for PPI analysis, and the results were imported into Cytoscape software to obtain PPI interaction map, core module and Hub gene. Import Hub gene into BioGPS database. Results: A total of 3 Hub genes were screened, namely CD3D, LCK, KLRB1;The genes were imported into BioGPS database to obtain the specific genes. Conclusion The selected differential genes and related signaling pathways are helpful to understand the molecular mechanism of ES and TB, and can provide the basis for early diagnosis of ES complicated with TB. It also provides new ideas for clinical treatment and diagnosis.

Bioinformatics Analysis of the Biological Properties of Ewing Sarcoma

Purpose: Bioinformatics-based approach to screen and analyze differentially expressed genes associated with the biological characteristics of Ewing sarcoma. Means: The GSE17674 dataset was selected for analysis, obtained by data retrieval based on the GEO public database. The R language limma toolkit was used to screen DEmRNAs. After the data were normalized, the Metascape online analysis software and the R language clusterProfiler package were used to analyze the GO function and KEGG pathway enrichment of DEmRNAs lines, respectively. The string database was selected for PPI analysis, and the results were imported into Cytoscape software to derive the core modules and predicted core genes. The genes selected above were analyzed for tissue localization specificity. Results: Through the analysis of GSE17674, differentially expressed genes were screened out, and GO and KEGG analyses were performed on the differentially expressed genes. The GO functional enrichment analysis was mainly enriched in the process of muscle system, muscle contraction, myocyte development, contractile fibers, myogenic fibers, myofibers, myofibrillar segments, actin binding, structural composition of muscle, and actin filament binding. KEGG pathway analysis showed that the core pathways associated with the development of ES were the core genes for myocardial contraction, congestive cardiomyopathy, and hypertrophic cardiomyopathy. Five Hub genes were obtained based on Cytoscape prediction. Tissue localization specificity analysis of Hub genes was performed, and a total of 2 Hub genes with tissue specificity were screened;MYH6 was specifically expressed in cardiac cells and MYL1 was specifically expressed in skeletal muscle cells. Conclusions: The differential genes screened will help to understand the molecular mechanisms underlying the highly invasive and metastasis-prone biological characteristics of ES, as well as provide new ideas for clinical drug-targeted treatment of ES.

Bioinformatics Analysis of the Relationship between Dilated Cardiomyopathy and Chronic Heart Failure

Objective: To screen and analyze the differentially expressed genes between dilated cardiomyopathy (DCM) and chronic heart failure (CHF) based on bioinformatics methods. Methods: The Gene Expression Omnibus (GEO) database was used for data retrieval, and the chip data GSE3585 was downloaded, which was the original data of DCM and normal control group. At the same time, the chip data GSE76701 was downloaded, which was the original data of CHF and control group. Differentially expressed mRNAs (DEmRNAs) were screened by R language limma package, the data were standardized, and the common differentially expressed genes were screened. GO function and KEGG pathway enrichment analysis were performed on the common differentially expressed genes. String11.0 online tool was used for data analysis to obtain differentially expressed genes, and the results were imported into Cytoscape 3.9.1 software. The results were imported into Cytoscape 3.9.1 software, and the common expression gene module was obtained by MOCDE algorithm. Nine Hub genes were obtained by 10 algorithms such as MCC. Results: A total of 248 differentially expressed genes were screened. GO analysis showed that differentially expressed genes were mainly concentrated in 9 different physiological and pathological processes. KEGG analysis showed that the main signaling pathways involved in differentially expressed genes were 2, and 9 key differentially expressed genes were predicted: NPPB, NPPA, MYH6, FRZB, ASPN, SFRP4, RPS4Y1, DDX3Y. Conclusion: This study preliminarily explored the molecular mechanism of DCM and CHF, and obtained the common differentially expressed genes of the two diseases. Further experimental studies are needed to verify the correlation between gene expression and clinicopathological features. Provide new ideas for clinical drug treatment research.

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.

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.

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.

A Bioinformatics Analysis of FAM3A to Identify its Potential Role as a Biomarker in Liver Hepatocellular Cancer

Liver hepatocellular cancer(LIHC)is positioned as the third cancer with the highest mortalities worldwide,and high mortalities are associated with late diagnosis and recurrence.This study advances bioinformatics analysis of FAM3A expression in LIHC to evaluate its potential as a prognostic,diagnostic and therapeutic biomarker.Bioinformatics tools such as UALCAN,GEPIA2,KM plotter,TIMER2 and cBioPortal are employed to conduct analysis.Initially,the expression analysis revealed up-regulation of FAM3A in LIHC based on various variables.Further,the study observed that FAM3A methylation regulates expression as variation in methylation level of FAM3A was assessed in LIHC.Moreover,this over-expression of FAM3A results in poor overall survival(OS)in LIHC patients.All of these proposed that FAM3A has a role in the progression and development of LIHC.While examined association of FAM3A expression and infiltration level of CD8+T cells in LIHC patients using TIMER2 revealed that FAM3A has a positive correlation with purity in LIHC that highlights the molecular landscape.Analysis of genetic alteration revealed minute role of FAM3A in LIHC still provides valuable insight.Overall,our findings reveal that FAM3A has potential as diagnostic,therapeutic and prognostic biomarkers in LIHC.

Identification of Prognosis-Related Genes and Key Target Genes for Pancreatic Cancer: A Bioinformatics Analysis

Objective: The mortality and morbidity rates associated with pancreatic cancer (PaCa) are extremely high. Various studies have demonstrated that pancreatic cancer will be the fourth cancer-related death by 2030, raising more concern for scholars to find effective methods to prevent and treat in order to improve the pancreatic cancer outcome. Using bioinformatic analysis, this study aims to pinpoint key genes that could impact PaCa patients’ prognosis and could be used as therapeutic targets. Methods: The TCGA and GEO datasets were integratively analyzed to identify prognosis-related differentially expressed genes. Next, the STRING database was used to develop PPI networks, and the MCODE and CytoNCA Cytoscape in Cytoscape were used to screen for critical genes. Through CytoNCA, three kinds of topology analysis were considered (degree, betweenness, and eigenvector). Essential genes were confirmed as potential target treatment through Go function and pathways enrichment analysis, a developed predictive risk model based on multivariate analysis, and the establishment of nomograms using the clinical information. Results: Overall, the GSE183795 and TCGA datasets associated 1311 and 2244 genes with pancreatic cancer prognosis, respectively. We identified 132 genes that were present in both datasets. The PPI network analysis using, the centrality analysis approach with the CytoNCA plug-in, showed that CDK2, PLK1, CCNB1, and TOP2A ranked in the top 5% across all three metrics. The independent analysis of a risk model revealed that the four key genes had a Hazard Ratio (HR) > 1. The monogram showed the predictive risk model and individual patient survival predictions were accurate. The results indicate that the effect of the selected vital genes was significant and that they could be used as biomarkers to predict a patient’s outcome and as possible target therapy in patients with pancreatic cancer. GO function and pathway analysis demonstrated that crucial genes might affect the P53 signaling pathway and FoxO signaling pathway, through which Meiotic nuclear division and cell cycle may have a significant function in essential genes affecting the outcome of patients who have pancreatic cancer. Conclusions: This study suggests that CDK2, CCNB1, PLK1 and TOP2A are four key genes that have a significant influence on PaCa migration and proliferation. CDK2, CCNB1, PLK1, and TOP2A can be used as potential PaCa prognostic biomarkers and therapeutic targets. However, experimental validation is necessary to confirm these predictions. Our study comes into contributions to the development of personalized target therapy for pancreatic cancer patients.

Elucidating the interplay of ferroptosis-related genes in keloid formation:Insights from bioinformatics analysis

Background:Keloids are benign skin tumors characterized by fibroblast proliferation,tumor-like biological behavior,and excessive deposition of extracellular matrix in wounded skin.Ferroptosis,a type of programmed cell death,is critical in tumor pathogenesis.We aimed to investigate the role of ferroptosis in keloid formation.Methods:We downloaded public high-throughput sequencing raw count data(GSE92566),containing three normal skin and four keloid samples,from the Gene Expression Omnibus database.Ferroptosis-related genes were obtained from the Ferroptosis database website.The ferroptosis-related differentially expressed genes(FRDEGs)were obtained by merging differentially expressed genes with ferroptosis-related genes.The FRDEGs were then used for Gene Ontology,Kyoto Encyclopedia of Genes and Genomes,Gene Set Enrichment Analysis,proteinprotein interaction(PPI)network,and microRNA(miRNA)-mRNA network analysis.Finally,real-time quantitative polymerase chain reaction(RT-qPCR)was performed to validate our findings.Results:We found 25 FRDEGs,including 8 up-regulated and 17 down-regulated genes.Pathway enrichment analysis revealed that the Hippo and transforming growth factorβsignaling pathways were significantly upregulated in keloids.In contrast,regulation of the peroxisome proliferator-activated receptor signaling pathway,glutathione metabolism,and unsaturated fatty acid metabolic process were down-regulated.PPI and FRDEGs hub networks were constructed using the STRING database and Cytoscape software.Ten hub genes were identified,including PLA2G6,RARRES2,SNCA,CYP4F8,CDKN2A,ALOX12,FABP4,ALOX12B,NEDD4,and NEDD4L.We constructed a miRNA-mRNA network,which predicted hsa-mir-155-5p,hsa-let-7b-5p,hsa-mir-124-3p,hsa-mir-145-5p,hsa-mir-328-3p,hsa-mir-24-3p,and hsa-mir-10b-5p as the most connected miRNAs regulating ferroptosis in keloids.Finally,we verified the expression levels of the hub genes by RT-qPCR,which confirmed that ALOX12,ALOX12B,and CYP4F8 expression were reduced in keloids.Conclusions:This study provides novel information on ferroptosis-mediated keloid pathogenesis,underscoring the importance of further research in this area to unlock new therapeutic avenues for keloid treatment.

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.

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.

Bioinformatics analysis of ferroptosis in spinal cord injury

Ferroptosis plays a key role in aggravating the progression of spinal cord injury(SCI),but the specific mechanism remains unknown.In this study,we constructed a rat model of T10 SCI using a modified Allen method.We identified 48,44,and 27 ferroptosis genes that were differentially expressed at 1,3,and 7 days after SCI induction.Compared with the sham group and other SCI subgroups,the subgroup at 1 day after SCI showed increased expression of the ferroptosis marker acyl-CoA synthetase long-chain family member 4 and the oxidative stress marker malondialdehyde in the injured spinal cord while glutathione in the injured spinal cord was lower.These findings with our bioinformatics results suggested that 1 day after SCI was the important period of ferroptosis progression.Bioinformatics analysis identified the following top ten hub ferroptosis genes in the subgroup at 1 day after SCI:STAT3,JUN,TLR4,ATF3,HMOX1,MAPK1,MAPK9,PTGS2,VEGFA,and RELA.Real-time polymerase chain reaction on rat spinal cord tissue confirmed that STAT3,JUN,TLR4,ATF3,HMOX1,PTGS2,and RELA mRNA levels were up-regulated and VEGFA,MAPK1 and MAPK9 mRNA levels were down-regulated.Ten potential compounds were predicted using the DSigDB database as potential drugs or molecules targeting ferroptosis to repair SCI.We also constructed a ferroptosis-related mRNA-miRNA-lncRNA network in SCI that included 66 lncRNAs,10 miRNAs,and 12 genes.Our results help further the understanding of the mechanism underlying ferroptosis in SCI.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).