ObjectiveTo screen for the differentially expressed genes in steroid-induced osteonecrosis of the femoral head (ONFH) by gene microarray. MethodsThe femoral head tissue of ONFH was harvested from 3 patients with steroid-induced ONFH, aged 25, 31, and 38 years, respectively. Normal tissue was harvested from a 26-year-old male remains contributor. HE staining of the specimens was performed for observing the histology manifestation; the total RNA was extracted for measuring the purity; cDNA probe was synthesized by reverse transcription, and then were hybridized as the cDNA microarray for scanning of fluorescent signals and differentially expressed genes in the tissues. ResultsHE staining of normal tissue showed complete unit composed of lamellar bone, continuous and complete lamellar bone with a concentric arrangement around blood vessels, and normal bone cells in the trabecular bone lacuna. In ONFH tissue, adipose tissue increased in the medullary cavity, with increased fat cells filling in the medullary cavity and extruding capillary, and with decreased bone cells in the bone trabecula, which had deeply-stained nuclear chromatin, pyknotic or cracking nucleus, and even bone cells disappeared in the part of the bone lacuna, and trabecular bone became thin, sparse, interrupt, reduced area in visual field/unit. Total RNA extraction electrophoretogram displayed clear bands of 28S and 18S, and the brightness ratio of the 28S:18S was 2:1, indicating good total RNA quality. And 44 genes were differentially expressed, and there were 28 up-regulated genes and 16 down-regulated genes, including cell/organism defense genes, cell structure/motility genes, cell division genes, cell signaling/cell communication genes, cell metabolism genes, gene/protein expression genes, and unclassified genes. ConclusionThe analysis of the gene expression profile of steroid-induced ONFH can provide evidence for the pathogenesis of ONFH.
ObjectiveTo study microRNA (miRNA) involved in the regulation of sinus cell differentiation by comparing sinus node, atrial myocardium, and ventricular myocardium specific miRNA expression profile differences in Kunming mice. MethodsA total of 180 Kunming mice, aged 60-90 days and weighing 35-45 g, were selected without gender differences after the method of anatomical localization for sinus node had been confirmed by preliminary experiments in another 10 Kunming mice. All the sinus node, atrial myocardium, and ventricular myocardium tissue from 180 mice were dissected and frozen by liquid nitrogen. The structure of tissue was observed by HE staining. Total RNA were extracted and quality-controlled before hybridize with miRNA chip. The chips with miRNA were used to screen specific miRNAs; and correlation analysis of gene function was done. ResultsThe area of mice sinus node located at juncture of the superior vena cava and the right atrium junction with crista as its longitudinal axis, ranged 2.0 mm×1.5 mm×1.0 mm. HE staining showed the sinus cells were less, with no stripes, lightly stained cytoplasm, large and round nucleus, and there were much fibrous connective tissue around cells with a visible sinus node artery. The miRNA microarray results showed that compared with atrial myocardium and ventricular myocardium, there were 39 differentially expressed miRNAs in sinus node, including 12 up-regulated miRNAs and 27 down-regulated miRNAs. Based on the regulatory networks of differential miRNA and target gene, the regulatory miRNA was obtained. ConclusionThe differentially expressed miRNA in mice sinus node possibly may be involved in the regulation of sinus cell differentiation.
ObjectiveTo investigate key differentially expressed genes (DEGs) in peripheral blood of idiopathic epilepsy patients, as well as their biological functions, cellular localization, involved signaling pathways, through bioinformatics analysis. So to provide new insights for the pathogenesis and prevention of idiopathic epilepsy.MethodsFirstly, we screened and downloaded microarray data including 6 peripheral blood samples of drug-naive patients with idiopathic epilepsy, 8 peripheral blood samples of responders of idiopathic epilepsy treated with Valproate (VPA), and 10 peripheral blood samples of non-responders of idiopathic epilepsy treated with VPA from Gene Expression Omnibus (GEO) data series GSE143272, which Public in January 2020. Secondly, we identified DEGs via the limma package and others in R software. Then we had gotten 74 DEGs, and subsequently conducted gene ontology and pathway enrichment analysis, PPI network analysis and hub gene analysis, using multiple methods containing DAVID, STRING, and Cytohubba in Cytoscape.ResultsWe had identified significant hub DEGs, including TREML3P, KCNJ15, ORM1, RNA28S5, ELANE, RETN, ARG1, LCN2, SLPI, HP, PGLYRP1, BPI, DEFA4, TCN1, MPO, MMP9, CTSG, CXCL8, RNASE3, RNASE2, S100A12, DEFA1B, DEFA1, DEFA3, CEACAM8, MS4A3, PTGS2, PI3, CCL3. The biological processes involved in these DEGs include immune response, inflammatory response, chemotaxis, etc. While, the molecular function is focused on peroxidase activity, chemokine activity, etc. Moreover, KEGG pathway enrichment analysis shows that DEGs were mainly involved in cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, chemokine signaling pathway and so on.ConclusionThese important key DEGs may be involved in the onset and development of idiopathic epilepsy through a variety of signaling pathways and complex mechanisms.
Objective To screen the differentially expressed genes and pathways involved in rosacea using bioinformatics analysis. Methods The GSE65914 gene chipset was collected from the Gene Expression Omnibus (up to July 12th, 2021). It was searched according to the keyword “rosacea”. The data was analyzed by GEO2R platform. The common differential genes of three subtypes of rosacea were screened out. The online DAVID analysis tool was used to perform the gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Protein-protein interaction networks of differentially expressed genes were made by String and Cytoscape. The key modules and genes were screened by Mcode and Cytohubba. Results A total of 957 common differential genes were identified, including 533 up-regulated genes and 424 down-regulated genes. GO enrichment analysis showed that these genes were mainly involved in immune response, inflammatory response, intercellular signal transduction, positive regulation of T cell proliferation, chemokine signaling pathways, cell surface receptor signaling pathways, cellular response to interferon-γ, and other biological processes. KEGG pathway enrichment analysis mainly included cytokine-cytokine receptor interaction, rheumatoid arthritis, chemokine signaling pathway, PPAR signaling pathway, Toll-like receptor signaling pathway, nuclear transcription factor-κB signaling pathway, tumor necrosis factor signaling pathway and other signaling pathways. Cytohubba analysis revealed 10 key genes, including PTPRC, MMP9, CCR5, IL1B, TLR2, STAT1, CXCR4, CXCL10, CCL5 and VCAM1. Conclusion The key genes and related pathways may play an important role in the pathogenesis of rosacea.