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Background: Systemic lupus erythematosus (SLE) is an autoimmune disease defined by the production of autoantibodies and involves multiple organs and systems. Although there are reports on SLE, data on its pathogenesis is limited. Methods: Using R language software, we constructed a competing endogenous RNA (ceRNA) network. We then utilized the Search Tool for Recurring Instances of Neighbouring Genes (STRING) and cytoHubba databases to generate a protein-protein interaction (PPI) network, which led to the identification of hub genes. The top two hub genes with the highest Maximal Clique Centrality (MCC) score in the PPI network were further validated via quantitative real-time polymerase chain reaction (qRT-PCR) using in-house clinical samples. Also, weighted gene co-expression network analysis (WGCNA) with genes from the Gene Expression Omnibus Series (GSE)121239 dataset identified hub modules that were associated with clinical indicators. In addition, the genes contained in key modules as obtained by WGCNA were enriched and analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. The top hub gene, X-linked apoptosis inhibitory protein-associated factor (XAF1), was then identified by intersection of the PPI and WGCNA outcomes, and a pan-cancer analysis of this hub gene was subsequently performed. Results: We comprehensively profiled the expression of Circular RNAs (circRNAs), MicroRNAs (miRNAs), and messenger RNAs (mRNAs) in SLE. We identified a hub gene, XAF1, based on evidence from the ceRNA network, WGCNA key module genes, and PPI network analyses. Moreover, qRT-PCR analysis demonstrated that the expression of XAF1 was significantly upregulated in SLE. Through the pan-cancer analysis, we demonstrated the common molecular roles of XAF1 in the pathogenesis of SLE and tumors, especially cutaneous melanoma. Conclusions: XAF1 is a key molecular biomarker in SLE. The pan-cancer analysis in this study provided shared genomic characteristics in SLE and cancers, especially for skin cutaneous melanoma (SKCM).
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Introduction: Pseudomonas aeruginosa is a common clinical opportunistic pathogen. Antibiotic resistance of P. aeruginosa is frequent, and it affects the clinical curative effect and leads to recurrent infections, disease progression, and difficult treatment, especially in cystic fibrosis patients. The drug-resistance mechanism of P. aeruginosa is complex, and biofilms play an important role. Given the widespread antibiotic resistance of P. aeruginosa, the discovery of a drug that can prevent or eradicate biofilm formation is imperative. Daphnetin (DAP), a coumarin derivative, is a safe, non-toxic, natural compound with antibacterial and anti-biofilm properties. Herein, this study highlights the bacterial motility effects, antibacterial effect, pyocyanin production, and anti-biofilm potential of DAP against P. aeruginosa. Methods: In this study, the minimal inhibitory concentration of DAP against P. aeruginosa was determined using the microdilution method. The antibiofilm activity of DAP against P. aeruginosa was determined using crystal violet staining, colony-forming unit enumeration, and scanning electron microscopy. The effect of DAP on P. aeruginosa motility was detected using the swimming, swarming, and twitching agar plates to measure the diameter of the concentric area. Results: We found that DAP at concentrations of 0.445-1.781 mg/mL and 0.89-1.781 mg/mL can effectively inhibit biofilm formation and eradicate the formed biofilm of P. aeruginosa, respectively. DAP reduced pyocyanin production and inhibited bacterial motility of P. aeruginosa. Discussion: In conclusion, our results support the conclusion that DAP can effectively eradicate formed biofilm and inhibit biofilm formation, bacterial motility, and pyocyanin production of P. aeruginosa and may represent a natural anti-biofilm therapeutic agent.
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Pseudomonas aeruginosa , Piocianina , Humanos , Umbeliferonas/farmacologia , Antibacterianos/farmacologiaRESUMO
BACKGROUND: Circular RNAs (circRNAs) are a class of endogenous noncoding RNAs that are more abundant, specific, and highly organized than linear RNAs. Increasing evidence supports that circRNAs may serve as diagnostic biomarkers in many diseases, but their potential as biomarkers in systemic lupus erythematosus (SLE) remains unclear. OBJECTIVE: We investigated the critical circRNAs involved in SLE progression and explored their potential application as biomarkers in SLE. METHOD: RNA sequencing was conducted on peripheral blood mononuclear cells (PBMCs) from 4 SLE patients and 4 healthy volunteers. CircRNA profile data were analyzed to identify differentially expressed circRNAs and visualized via R software. After screening, qPCR analysis of target circRNA expression was performed using PBMCs from 31 SLE patients and 35 healthy volunteers. Correlations between circRNA expression levels and the SLEDAI score were assessed via Spearman correlation analysis. Finally, the performance of circRNAs as biomarkers in SLE was examined by receiver operating characteristic curve analysis. RESULTS: The result identified six differentially expressed circRNAs between SLE patients and healthy controls: hsa_circ_0006689, hsa_circ_0070562, hsa_circ_0006117, hsa_circ_0007683, hsa_circ_0042519, and hsa_circ_0008647. The validation analysis showed differing relative expression levels of hsa_circ_0007683, hsa_circ_0042519, hsa_circ_0008647, and hsa_circ_0006689 between SLE patients and healthy volunteers (P < 0.05), and hsa_circ_0006689 expression in PBMCs correlated with the SLEDAI score (P < 0.05). Furthermore, addition of hsa_circ_0006689 expression increased the sensitivities of anti-dsDNA antibody and anti-Sm antibody levels for SLE diagnosis (from 29.03 to 61.30% and 32.26-71.00%, respectively). CONCLUSION: Our results suggest hsa_circ_0006689 may be a useful circRNA biomarker for SLE diagnosis and prognosis.