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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.

Rice black-streaked dwarf virus (RBSDV) causes maize rough dwarf disease (MRDD), which is a viral disease that significantly affects maize yields worldwide. Plants tolerate stress through transcriptional reprogramming at the alternative splicing (AS), transcriptional, and fusion gene (FG) levels. However, it is unclear whether and how AS and FG interfere with transcriptional reprogramming in MRDD. In this study, we performed global profiling of AS and FG on maize response to RBSDV and compared it with transcriptional changes. There are approximately 1.43 to 2.25 AS events per gene in maize infected with RBSDV. GRMZM2G438622 was only detected in four AS modes (A3SS, A5SS, RI, and SE), whereas GRMZM2G059392 showed downregulated expression and four AS events. A total of 106 and 176 FGs were detected at two time points, respectively, including six differentially expressed genes and five differentially spliced genes. The gene GRMZM2G076798 was the only FG that occurred at two time points and was involved in two FG events. Among these, 104 GOs were enriched, indicating that nodulin-, disease resistance-, and chloroplastic-related genes respond to RBSDV stress in maize. These results provide new insights into the mechanisms underlying post-transcriptional and transcriptional regulation of maize response to RBSDV stress.

Epididymitis is a commonly diagnosed disease associated with male infertility. However, little is known about the molecules that are involved in its development. This study was to identify critical genes associated with lipopolysaccharide-induced epididymitis and analyze the molecular mechanism of epididymitis through RNA sequencing. Experimental epididymitis models were generated by administering male Sprague-Dawley rats' lipopolysaccharide. A total of 1378 differentially expressed genes, including 531 upregulated and 847 downregulated genes, were identified in the epididymitis model rats compared with those in sham-operated rats by RNA sequencing. Functional enrichment analyses suggested that the upregulated genes were markedly enriched in inflammation-related biological processes, as well as in the tumor necrosis factor (TNF) signaling pathway, cytokine-cytokine receptor interactions, complement and coagulation cascades, and in the chemokine signaling pathway. Four downregulated genes (collagen type XXVIII alpha 1 chain [Col28α1], cyclin-dependent kinase-like 1 [Cdkl1], phosphoserine phosphatase [Psph], and fatty acid desaturase 2 [Fads2]) and ten upregulated genes (CCAAT/enhancer-binding protein beta [Cebpβ], C-X-C motif chemokine receptor 2 [Cxcr2], interleukin 11 [Il11], C-C motif chemokine ligand 20 [Ccl20], nuclear factor-kappa-B inhibitor alpha [Nfkbiα], claudin 4 [Cldn4], matrix metallopeptidase 9 [Mmp9], heat shock 70 kDa protein 8 [Hspa8], intercellular cell adhesion molecule-1 [Icam1], and Jun) were successfully confirmed by real-time polymerase chain reaction. Western blot demonstrated that CDKL1 was decreased, while MMP9 and NFKBIA were increased in the experimental model group compared with those in the sham-operated group. Our study sheds new light on the understanding of the early response of the epididymis during bacterial epididymitis.

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 mRNA 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.

The development and progression of colorectal cancer (CRC) are known to be affected by the interplay between tumor and immune cells. However, the impact of CRC cells on the systemic immunity has yet to be elucidated. We aimed to comprehensively evaluate the circulating immune subsets and transcriptional profiles of CRC patients. In contrast to healthy controls (HCs), CRC patients had a lower percentage of B and T lymphocytes, T helper (Th) cells, non-classical monocytes, dendritic cells, and a higher proportion of polymorphonuclear myeloid-derived suppressor cells, as well as a reduced expression of CD69 on NK cells. Therefore, CRC patients exhibit a more evident systemic immune suppression than HCs. A diagnostic model integrating seven immune subsets was constructed to distinguish CRC patients from HCs with an AUC of 1.000. Moreover, NR3C2, CAMK4, and TRAT1 were identified as candidate genes regulating the number of Th cells in CRC patients. The altered composition of circulating immune cells in CRC could complement the regional immune status of the tumor microenvironment and contribute to the discovery of immune-related biomarkers for the diagnosis of CRC.

Accumulating evidences disclose that COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a marked effect on acute myocardial infarction (AMI). Nevertheless, the underlying pathophysiology correlation between the AMI and COVID-19 remains vague. Bioinformatics analyses of the altered transcriptional profiling of peripheral blood mononuclear cells (PBMCs) in patients with AMI and COVID-19 were implemented, including identification of differentially expressed genes and common genes between AMI and COVID-19, protein-protein interactions, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, TF-genes and miRNA coregulatory networks, to explore their biological functions and potential roles in the pathogenesis of COVID-19-related AMI. Our bioinformatic analyses of gene expression profiling of PBMCs in patients with AMI and COVID-19 provide us with a unique view regarding underlying pathophysiology correlation between the two vital diseases.

Objective: The mechanisms underlying the chronic rhinosinusitis with nasal polyps (CRSwNP) remained unclear. This study aimed to identify differentially expressed genes (DEGs) in nasal polyps from CRSwNP patients compared to healthy controls and explore key genes and pathways associated with CRSwNP pathophysiology and prognosis. Methods: Three datasets were obtained from the Gene Expression Omnibus database and the intersecting DEGs were identified in CRSwNP patients. Gene Ontology (GO) and protein-protein interaction (PPI) network analysis were applied to investigate the function of DEGs. Nasal specimens from 90 CRSwNP and 45 controls were further collected and qRT-PCR was applied to verify the mRNA expression of hub genes, and moreover, their association with tissue eosinophilia and clinical characteristics in CRSwNP were analyzed. Results: Sixty-eight co-DEGs including 8 upregulated and 60 downregulated genes were identified and GO analyses identified the terms including positive regulation of ERK1 and ERK2 cascade, transforming growth factor beta receptor signaling pathway. PPI networks identified hub genes including EGF, ERBB4, AZGP1, CRISP3 and PIP which were validated to be significantly down-regulated in CRSwNP and showed well diagnostic prediction quality. In addition, lower mRNA expressions level of EGF and AZGP1 in eosinophilic CRSwNP compared with non-eosinophilic CRSwNP were found. Aberrant low expressions of EGF and AZGP1 protein in CRSwNP were identified, and there was good consistency between their mRNA expression level and protein relative expression level. Furthermore, the expressions of EGF and AZGP1 mRNA were significantly correlated with clinical severity parameters. Conclusion: Integrated analysis revealed 68 co-DEGs between nasal polyps and controls and identified hub genes, of which EGF and AZGP1 expression was significantly downregulated in eosinophilic CRSwNP and correlated with disease severity. Downregulation of EGF and AZGP1 may contribute to epithelial barrier dysfunction and type 2 inflammation in CRSwNP, suggesting them as potential diagnostic biomarkers and therapeutic targets. Keywords: chronic rhinosinusitis with nasal polyps, bioinformatics analysis, differentially expressed genes, EGF, AZGP1

Background Oxidative stress (OS) plays a major role in the progress of hypoxic‐ischemic brain damage (HIBD). This study aimed to investigate OS‐related genes and their underlying molecular mechanisms in neonatal HIBD. Methods Microarray data sets were acquired from the Gene Expression Omnibus (GEO) database to screen the differentially expressed genes (DEGs) between control samples and HIBD samples. OS‐related genes were drawn from GeneCards and OS‐DEGs in HIBD were obtained by intersecting with the DEGs. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were conducted to determine the underlying mechanisms and functions of OS‐DEGs in HIBD. Moreover, the hub genes were screened using the protein−protein interaction network and identified in the GSE144456 data set. CIBERSORT was then performed to evaluate the expression of immunocytes in each sample and perform a correlation analysis of the optimal OS‐DEGs and immunocytes. Finally, quantitative reverse transcription polymerase chain reaction (RT‐qPCR) and immunohistochemistry were performed to validate the expression levels of the optimal OS‐DEGs. Results In total, 93 OS‐DEGs were identified. GO, KEGG, and GSEA enrichment analyses indicated that these genes were predominantly enriched in OS and inflammation. Four OS‐related biomarker genes (Jun, Fos, Tlr2, and Atf3) were identified and verified. CIBERSORT analysis revealed the dysregulation of six types of immune cells in the HIBD group. Moreover, 47 drugs that might target four OS‐related biomarker genes were screened. Eventually, RT‐qPCR and immunohistochemistry results for rat samples further validated the expression levels of Fos, Tlr2, and Atf3. Conclusions Fos, Tlr2 and Atf3 are potential OS‐related biomarkers of HIBD progression. The mechanisms of OS are associated with those of neonatal HIBD. This research was the first to explore the underlying oxidative stress (OS)‐related genes in hypoxic‐ischemic brain damage (HIBD) and their correlation with immunocytes infiltration. Three potential OS‐related marker genes (Fos, Tlr2, and Atf3) associated with HIBD were identified using bioinformatics analysis and experimentally validated in rat samples.

Improved insight into the molecular mechanisms of triple negative breast cancer (TNBC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify key genes which may affect the prognosis of TNBC patients by bioinformatic analysis. In our study, the RNA sequencing (RNA-seq) expression data of 116 breast cancer lacking ER, PR, and HER2 expression and 113 normal tissues were downloaded from The Cancer Genome Atlas (TCGA). We screened out 147 differentially co-expressed genes in TNBC compared to non-cancerous tissue samples by using weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were constructed, revealing that 147 genes were mainly enriched in nuclear division, chromosomal region, ATPase activity, and cell cycle signaling. After using Cytoscape software for protein-protein interaction (PPI) network analysis and LASSO feature selection, a total of fifteen key genes were identified. Among them, BUB1 and CENPF were significantly correlated with the overall survival rate (OS) difference of TNBC patients (p value < 0.05). In addition, BUB1, CCNA2, and PACC1 showed significant poor disease-free survival (DFS) in TNBC patients (p value < 0.05), and may serve as candidate biomarkers in TNBC diagnosis. Thus, our results collectively suggest that BUB1, CCNA2, and PACC1 genes could play important roles in the progression of TNBC and provide attractive therapeutic targets.

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 at 28 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.