Gut-Skin Axis: Unravelling the Link Between Gut Microbiome and Chronic Kidney Disease-Related Skin Lesions.

It is well known that skin lesions are among the most common complications of chronic kidney disease (CKD), which significantly impact the patient's quality of life. Research has demonstrated that gut and skin lesions are closely interconnected and affect each other. This interaction is referred to as the "gut-skin axis" and the intestinal microbiota plays a critical role in this interaction. Changes in gut microbiota composition and function are associated with the development of skin diseases, which are part of the "gut-skin axis". Presently, preliminary results have been demonstrated in basic and clinical research on CKD skin lesions. With further research, the "gut-skin axis" theory can provide new ideas for treating CKD skin lesions and may become a potential treatment target.

CD163 as a Potential Biomarker-associated Immune Inflammation in Diabetes Mellitus: A Systematic Review and Bioinformatics Analysis.

BACKGROUND: Several studies have identified CD163 as a potential mediator of diabetes mellitus through an immune-inflammation. Further study is necessary to identify its specific mechanism. OBJECTIVES: In this study, we aimed to investigate CD163 as a potential biomarker associated with immune inflammation in diabetes mellitus through a systematic review and bioinformatics analysis. METHODS: We searched PubMed, Web of Science, the Cochrane Library, and Embase databases with a time limit of September 2, 2022. Furthermore, we conducted a systematic search and review based on PRISMA guidelines. Additionally, diabetic gene expression microarray datasets GSE29221, GSE30528, GSE30529, and GSE20966 were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo) for bioinformatics analysis. The PROSPERO number for this study is CRD420222347160. RESULTS: Following the inclusion and exclusion criteria, seven articles included 1607 patients, comprising 912 diabetic patients and 695 non-diabetic patients. This systematic review found significantly higher levels of CD163 in diabetic patients compared to non-diabetic patients. People with diabetes had higher levels of CRP expression compared to the control group. Similarly, two of the three papers that used TNF- α as an outcome indicator showed higher expression levels in diabetic patients. Furthermore, IL-6 expression levels were higher in diabetic patients than in the control group. A total of 62 samples were analyzed by bioinformatics (33 case controls and 29 experimental groups), and 85 differential genes were identified containing CD163. According to the immune cell correlation analysis, CD163 was associated with macrophage M2, γδ T lymphocytes, macrophage M1, and other immune cells. Furthermore, to evaluate the diagnostic performance of CD163, we validated it using the GSE20966 dataset. In the validation set, CD163 showed high diagnostic accuracy. CONCLUSION: This study suggests CD163 participates in the inflammatory immune response associated with diabetes mellitus and its complications by involving several immune cells. Furthermore, the results suggest CD163 may be a potential biomarker reflecting immune inflammation in diabetic mellitus.

Identification of Novel Hub Genes Associated with Inflammation and Autophagy in Astragaloside Membranaceus ameliorates Lupus Nephritis by Bioinformatics Analysis and Molecular Dynamics Simulation.

BACKGROUND: Lupus nephritis is an autoimmune disease, and its pathogenesis involves inflammation and autophagy disorders. Studies have demonstrated that Astragalus membranaceus can effectively suppress the progression of LN, but the underlying therapeutic target is still unclear. OBJECTION: This study aimed to investigate the therapeutic target whereby AM ameliorates LN. METHOD: We downloaded AM and LN-related chips from the TCMSP and GEO databases, respectively. We selected the two compound targets for the subsequent analysis via WGCNA, and constructed protein interaction networks of compound targets and determined the core targets. GO, KEGG analyses were conducted on compound targets to identify enriched functional and genomic pathways. The core genes were further validated in clinical and external datasets. Molecular docking of AS with the core targets was performed using the AutoDock software, and molecular dynamics simulation was conducted for the optimal core protein ligand obtained by molecular docking by Gromacs 2020.6 software. RESULT: We obtained 10 core targets, namely IL-1ß, EGF, CCND1, CASP3, STAT1, PTGS2, PPARγ, AR, CXCL10, and KDR, from the 24 compound targets identified. The results of the GO enrichment analysis mainly included cell growth regulation. The results of the KEGG enrichment analysis showed that 7 out of 23 valid targets were significantly enriched in the mitogen-activated protein kinase pathway (p < 0.01). Combined with the clinical datasets, we found that IL-1ß, EGF, CCND1, CASP3, STAT1, PTGS2, and PPARγ have high diagnostic values for LN. In the validation dataset, all the core targets were significantly differentially expressed, except for EGF deletion. The molecular docking and molecular dynamics simulation results showed that AM and IL- 1ß, CASP3, STAT1, and PPARγ all had binding energies < -5 kJ·mol-1 and good binding properties. CONCLUSION: IL-1ß, CASP3, STAT1, and PPARγ could be potential biomarkers and therapeutic targets in AM ameliorates LN.