ObjectiveTo conduct a bioinformatics analysis of gene expression profiles in frontal lobe of patients with Parkinson disease (PD), in order to explore the potential mechanism related to depression in PD.MethodsAll the bioinformatics data before March 20th 2019 were acquired from Gene Expression Omnibus (GEO) database, using " Parkinson disease” as the key word. The species was limited to human (Homo sapiens), and the detective method was limited to expression profiling by array. ImgGEO (Integrative Gene Expression Meta-Analysis from GEO database), DAVID (the Database for Annotation, Visualization and Integrated Discovery), STRING and Cytoscape 3.6.1 software were utilized for data analysis.ResultsTotally, 45 samples (24 PD cases and 21 healthy controls) were obtained from 2 datasets. We identified 236 differentially expressed genes (DEGs) in the post-mortem frontal lobe between PD cases and healthy controls, in which 146 genes were up-regulated and 90 genes were down-regulated. Based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis, the DEGs were mainly enriched in the structures of postsynaptic membrane, cell membrane component, postsynaptic membrane dense area, and myelin sheath, and were involved in the occurrence of PD, depression, and other diseases. These genes were involved in the biological processes of dopaminergic, glutamate-nergic, GABA-nergic synapses, and some other synapses, as well as several signaling pathways (e.g. mitogen- activated protein kinase signal pathway, p53 signal pathway, and Wnt signal pathway), which were associated with PD and depression pathogenesis. Besides, we found that NFKBIA, NRXN1, and RPL35A were the Hub proteins.ConclusionsGene expression in frontal lobe of patients with PD is associated with the pathogenesis of PD. This study provides a theoretical basis for understanding the mechanism of PD occurrence and progression, as well as the potential mechanism of depression in PD.
Objective To explore the pathogenesis of acute respiratory disease syndrome (ARDS) by bioinformatics analysis of neutrophil gene expression profile in order to find new therapeutic targets. Methods The gene expression chips include ARDS patients and healthy volunteers were screened from the Gene Expression Omnibus (GEO) database. The differentially expressed genes were carried out through GEO2R, OmicsBean, STRING, and Cytoscape, then enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathways was conducted to investigate the biological processes involved in ARDS via DAVID website. Results Bioinformatics analysis showed 86 differential genes achieved through the GEO2R website. Eighty-one genes were included in the STRING website for protein interaction analysis. The results of the interaction were further analyzed by Cytoscape software to obtain 11 hub genes: AHSP, ALAS2, CD177, CLEC4D, EPB42, GPR84, HBD, HVCN1, KLF1, SLC4A1, and STOM. GO analysis showed that the differential gene was enriched in the cellular component, especially the integrity of the plasma membrane. KEGG analysis showed that multiple pathways especially the cytokine receptor pathway involved in the pathogenesis of ARDS. Conclusions A variety of genes and pathways have been involved in the pathogenesis of ARDS. Eleven hub genes are screened, which may be involved in the pathogenesis of ARDS and can be used in subsequent studies.
Circular RNA are one kind of non-coding RNA, charactered by covalently closed rings. They can influence biological functions such as cell transduction and protein synthesis. They are associated with pathogenesis of many diseases and become a novel family of biomarkers. Now we try to introduce the origin, structure, function of circular RNA and the involved research methodology. Furthermore, we primarily discuss their application in the tuberculosis research.
ObjectiveA competing endogenous RNA (ceRNA) regulatory network associated with long non-coding RNA (lncRNA) specific for lung adenocarcinoma (LUAD) was constructed based on bioinformatics methods, and the functional mechanism of actinfilament-associated protein 1-antisense RNA1 (AFAP1-AS1) in LUAD was analyzed, in order to provide a new direction for the study of LUAD therapeutic targets. MethodsThe gene chip of LUAD was downloaded from the Gene Expression Omnibus (GEO), and lncRNA and mRNA with differential expression between LUAD and normal tissues were screened using GEO2R online software, and their target genes were predicted by online databases to construct ceRNA networks and perform enrichment analysis. In cell experiments, AFAP1-AS1 was genetically knocked down and siRNA was constructed and transfected into LUAD cells A549 by cell transfection. CCK8, transwell, scratch assay and flow cytometry were used to detect the ability of cells to proliferate, invade, migrate and apoptosis. ResultsA total of 6 differentially expressed lncRNA and 494 differentially expressed mRNA were identified in the microarray of LUAD. The ceRNA network involved a total of 6 lncRNA, 22 miRNA, and 55 mRNA. Enrichment analysis revealed that mRNA was associated with cancer-related pathways. In cell assays, knockdown of AFAP1-AS1 inhibited cell proliferation, invasion, and migration, and AFAP1-AS1 promoted apoptosis. ConclusionIn this study, we construct a lncRNA-mediated ceRNA network, which may help to further investigate the mechanism of action of LUAD. In addition, through cellular experiments, AFAP1-AS1 is found to have potential as a therapeutic target for LUAD.
Objective To study the expression of 4 circular RNA (circRNA) in peripheral blood mononuclear cells (PBMC) of patients with epilepsy and to predict its function by bioinformatics, so as to provide basis for exploring the pathogenesis of epilepsy. Methods From May 2020 to May 2021, 22 epilepsy patients were treated in the Department of Neurology of the First Affiliated Hospital of Baotou Medical College of Inner Mongolia University of Science and Technology, and 22 control group were selected. There were 13 males and 8 females in the epilepsy group, with an average age of (36.41±8.39)years. There were 11 males and 11 females in the control group, with an average age of (34.41±8.68) years. The expression levels of circRNA EFCAB2, C14orf159, PARG and TMEM39 in PBMC were detected by real-time fluorescence quantitative PCR, and their functions were predicted by bioinformatics. Results Compared with the control group, the relative expression of EFCAB2 and C14orf159 in PBMC of epileptic patients was 1.42±0.06 (t=29.41) and 1.31±0.03 (t=25.27), PARG and TMEM39 were not detected in peripheral blood PBMC. Bioinformatics analysis showed that three mirnas obtained by EFCAB2 were miR-6873-3p, miR-6739-3p and miR-7110-3p. Three mirnas were obtained by C14orf159: miR-1180-3p, miR-6501-3p, and miR-3622b-5p. The seizure-related genes were predicted by TargetScan database. EFCAB2: miR-6873-3p met the requirements of 11 downstream genes. A total of 7 downstream genes of miR-6739-3p met the requirements.A total of 14 downstream genes were eligible for miR-7110-3p and a total of 9 downstream genes were eligible for miR-6501-3p. A total of 14 downstream genes were eligible for miR-3622B-5p.miR-1180-3p has a total of 1 downstream genes that meet the requirements. Conclusions Studies have shown that two circrnas, EFCAB2 and C14orf159, may be important biological markers of epilepsy. Through bioinformatics analysis, these two circrnas may act as "molecular sponges" to regulate epilepsy. EFCAB2 has the potential to act as a "molecular sponge" for miR-6873-3p and miR-7110-3p, and it was found that miR-6873-3p and miR-7110-3 share a common downstream target gene MAP1B-which plays a role in epilepsy by regulating voltage-gated sodium channels. C14orf159 can act as a molecular sponge for miR-6501-3p to regulate the expression of CCL3 and play a role in epilepsy.
ObjectiveThe role of ferroptosis-related genes in the occurrence and development of lung injury caused by sepsis was investigated by bioinformatics methods, and the closely related genes were predicted. MethodsThe Dataset GSE154653 was downloaded from the gene expression database (GEO), and a total of 8 cases of microarray gene set were included in normal group and lipopolysaccharide (LPS)-induced sepsis lung tissue. The differential expression genes (DEGs) were screened out under conditions of |log2 FC|>1 and P.adj<0.05. Meanwhile, the selected DEGs were combined with the driver and suppressor genes of ferroptosis downloaded from the ferroptosis database (FerrDb) to obtain the differential genes associated with ferroptosis in sepsis (Fe-DEGs). These Fe-DEGs were further analyzed using R language, DAVID, and STRING online tools to identify GO-KEGG functions and pathways, and the construction of PPI network. Results The Bioinformatics approach screened out 3533 DEGs and intersected 53 key genes related to ferroptosis. The further biological process (BP) of GO enrichment analysis mainly involves the positive regulation of transcription, the positive regulation of RNA polymerase II promoter transcription, the cytokine mediated signaling pathway, and the positive regulation of angiogenesis. The molecular function (MF) mainly involves the same protein binding, transcriptional activation activity and REDOX enzyme activity. The pathways are enriched in iron death, HIF-1 signaling pathway and AGE-RAGE signaling pathway. Five key Fe-DEGs genes were screened by constructing PPI network, including CYBB, LCN2, HMOX1, TIMP1 and CDKN1A. Conclusion CYBB、LCN2、HMOX1、TIMP1 and CDKNIA genes may be key genes involved in ferroptosis of lung tissue caused by sepsis.
The rapid development of high-throughput chromatin conformation capture (Hi-C) technology provides rich genomic interaction data between chromosomal loci for chromatin structure analysis. However, existing methods for identifying topologically associated domains (TADs) based on Hi-C data suffer from low accuracy and sensitivity to parameters. In this context, a TAD identification method based on spatial density clustering was designed and implemented in this paper. The method preprocessed the raw Hi-C data to obtain normalized Hi-C contact matrix data. Then, it computed the distance matrix between loci, generated a reachability graph based on the core distance and reachability distance of loci, and extracted clustering clusters. Finally, it extracted TAD boundaries based on clustering results. This method could identify TAD structures with higher coherence, and TAD boundaries were enriched with more ChIP-seq factors. Experimental results demonstrate that our method has advantages such as higher accuracy and practical significance in TAD identification.
Evidence-based medicine is the methodology of modern clinical research and plays an important role in guiding clinical practice. It has become an integral part of medical education. In the digital age, evidence-based medicine has evolved to incorporate innovative research models that utilize multimodal clinical big data and artificial intelligence methods. These advancements aim to address the challenges posed by diverse research questions, data methods, and evidence sources. However, the current teaching content in medical schools often fails to keep pace with the rapidly evolving disciplines, impeding students' comprehensive understanding of the discipline's knowledge system, cutting-edge theories, and development directions. In this regard, this article takes the opportunity of graduate curriculum reform to incorporate real-world data research, artificial intelligence, and bioinformatics into the existing evidence-based medicine curriculum, and explores the reform of evidence-based medicine teaching in the information age. The aim is to enable students to truly understand the role and value of evidence-based medicine in the development of medicine, while possessing a solid theoretical foundation, a broad international perspective, and a keen research sense, in order to cultivate talents for the development of the evidence-based medicine discipline.
ObjectiveTo bioinformatically analyze the gene chip data of chondrocytes from osteoarthritis patients from the Gene Expression Omnibus (GEO) database, and explore the molecular mechanisms of osteoarthritis.MethodsWe searched the GEO database (up to April 23rd, 2021) for data of chondrocytes and gene expression profiling in human knee osteoarthritis via the key words of “osteoarthritis OR cartilage OR chondrocyte*”. Then, we selected the samples by our inclusion criteria. The data were normalized before analysis. After differentially expressed genes were identified, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Search Tool for the Retrival of Interacting Genes/Proteinsm, R language, Perl language, Cytoscape software, and DAVID database were used to perform differentially expressed gene analysis, functional annotation, and enrichment analysis.ResultsThe differentially expressed genes were mostly enriched in cell components and some extracellular regions, which participated in cell division, mitosis, cell proliferation and inflammatory response mainly via the regulation of protein kinase activity. The differentially expressed genes were mainly involved in the cell proliferation signaling pathway, mitogen-activated protein kinase signaling pathway, oocyte meiosis, cell cycle and so on.ConclusionsMultiple signaling pathways are involved in the changes of chondrocytes in human knee osteoarthritis, mainly about cell cycle and protein metabolism genes/pathways. Inflammatory factors and cytokines may be the most important links in the pathogenesis of osteoarthritis.
ObjectiveTo investigate the expression of Yes-associated protein (YAP) screened by bioinformatics in rats with myocardial-ischemia reperfusion injury and establish the base for further research. MethodsThe difference of gene spectrum of rats with myocardial-ischemia reperfusion injury was analyzed by bioinformatics technique. The related signaling pathways and key genes were screened by KOBAS2.0 and KEGG. Eighteen Sprague Dawley rats were randomly divided into three groups: normal group (n=6), sham operation group (n=6) and myocardial-ischemia reperfusion injury group (n=6). The expression of target gene was detected by immunochemistry, quantitive reverse transcription polymerase chain reaction and western blotting. ResultsA total of 345 differentially expressed genes were found by bioinformatics, among which 181 were up-regulated and 164 were down-regulated. The differential genes were mainly enriched in Wnt, HIPPO, MAPK, Jak-STAT and other signaling pathways. We focused on HIPPO pathway and found that the expression of YAP increased significantly in myocardial-ischemia reperfusion injury group, compared with the normal group and sham operation group (P＜0.05). ConclusionsThe expression of YAP of HIPPO signal pathway is increased in rats with myocardial-ischemia reperfusion injury.