Background: Rupture of intracranial aneurysms (IA) is associated with high rates of mortality around the world. Use of intestinal probiotics can regulate the pathophysiology of aneurysms, but the details of the mechanism involved have been unclear. Material/Methods: The GEO2R analysis website was used to detect the DEGs between IAs, AAAs, samples after supplementation with probiotics, and normal samples. The online tool DAVID provides functional classification and annotation analyses of associated genes, including GO and KEGG pathway. PPI of these DEGs was analyzed based on the STRING database, followed by analysis using Cytoscape software. Results: We found 170 intersecting DEGs (contained in GSE75240 and more than 2 of the 4 aneurysms datasets), 5 intersecting DEGs (contained in all datasets) and 1 intersecting DEG (contained in GSE75240 and all IAs datasets). GO analysis results suggested that the DEGs primarily participate in signal transduction, cell adhesion, immune response, response to drug, extracellular matrix organization, cell-cell signaling, and inflammatory response in the BP terms, and the KEGG pathways are mainly enriched in focal adhesion, cytokine-cytokine receptor interaction, ECM-receptor interaction, amoebiasis, chemokine signaling pathway, proteoglycans, and PI3K-Akt signaling pathway in cancer pathways. Through PPI network analysis, we confirmed 2 candidates for further study: CAV1 and MYH11. These downregulated DEGs are associated with the formation of aneurysms, and the change of these DEGs is the opposite in probiotics-treated animals. Conclusions: Our study suggests that MYH11 and CAV1 are potential target genes for prevention of aneurysms. Further experiments are needed to verify these findings.
Purpose To explore factors affecting the prognosis of choroidal anterior artery aneurysm (AChAA) and provide a reference for improving the postoperative outcome.
Methods The clinical data of 86 patients with AChAA who underwent treatment by a single surgeon were collected and analyzed retrospectively. Univariate analysis and multivariate logistic regression analysis were conducted to examine 12 factors that possibly affected outcome.
Results The five factors that affected the patient outcomes were times of subarachnoid hemorrhage (SAH), characteristics of SAH on computed tomography (CT), Hunt-Hess grade, aneurysm size, and presence or absence of postoperative complications. Characteristics of SAH on CT (odds ratio [OR]: 3.727; p = 0.000; 95% confidence interval [CI], 1.850–7.508), aneurysm size (OR: 6.335; p = 0.000; 95% CI, 2.564–15.647), and presence or absence of postoperative complications (OR: 4.141; p = 0.000; 95% CI, 1.995–8.599) were independent risk factors influencing the prognosis. In addition, the incidence of postoperative ischemia (caused by anterior choroidal artery syndrome) is related to the aneurysm emitting part and presence or absence of intraoperative rupture.
Conclusions The analysis of characteristics of SAH on CT, aneurysm size, and presence or absence of postoperative complications can roughly determine the outcome of patients with AChAAs.
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