ABSTRACT
Magnesium alloy is an excellent material for biodegradable cerebrovascular stents. However, the rapid degradation rate of magnesium alloy will make stent unstable. To improve the biocompatibility of magnesium alloy, in this study, biodegradable sodium alginate and carboxymethyl chitosan (SA/CMCS) was used to coat onto hydrothermally treated the surface of magnesium alloy by a dipping coating method. The results show that the SA/CMCS coating facilitates the growth, proliferation, and migration of endothelial cells and promotes neovascularization. Moreover, the SA/CMCS coating suppresses macrophage activation while promoting their transformation into M2 type macrophages. Overall, the SA/CMCS coating demonstrates positive effects on the safety and biocompatibility of magnesium alloy after implantation, and provide a promising therapy for the treatment of intracranial atherosclerotic stenosis in the future.
ABSTRACT
BACKGROUND: Autophagy plays an important role in the progression of carotid atherosclerosis (CAS). This study aimed to identify hub autophagy-related genes (ATGs) associated with CAS. METHODS: GSE43292 and GSE28829 datasets of early and advanced CAS plaques were enrolled from the Gene Expression Omnibus (GEO) database. A comprehensive analysis of differentially expressed ATGs (DE-ATGs) was conducted. Functional enrichment assay was used to explore biological functions of DE-ATGs. The hub ATGs were identified by protein-protein interaction (PPI) network. Immunohistochemistry (IHC) and Real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to validate hub ATGs at the protein level and mRNA level. Correlation analysis of hub ATGs with immune cells was also conducted. In addition, a competitive endogenous RNA (ceRNA) network was constructed, and diagnostic value of hub ATGs was evaluated. RESULTS: A total of 19 DE-ATGs were identified in early and advanced CAS plaques. Functional enrichment analysis of DE-ATGs suggested that they were closely correlated to autophagy, apoptosis, and lipid regulation. Moreover, 5 hub ATGs, including TNFSF10, ITGA6, CTSD, CCL2, and CASP1, were identified and further verified by IHC. The area under the curve (AUC) values of the 5 hub ATGs were 0.818, 0.732, 0.792, 0.814, and 0.812, respectively. Competing endogenous RNA (ceRNA) networks targeting the hub ATGs were also constructed. In addition, the 5 hub ATGs were found to be closely associated with immune cell infiltration in CAS. CONCLUSION: In this study, we identified 5 hub ATGs including CASP1, CCL2, CTSD, ITGA6 and TNFSF10, which could serve as candidate diagnostic biomarkers and therapeutic targets.
Subject(s)
Carotid Artery Diseases , Transcriptome , Humans , Transcriptome/genetics , Carotid Artery Diseases/genetics , Autophagy/genetics , Apoptosis , BiomarkersABSTRACT
Background: Intracranial aneurysm (IA) is an uncommon but severe subtype of cerebrovascular disease, with high mortality after aneurysm rupture. Current risk assessments are mainly based on clinical and imaging data. This study aimed to develop a molecular assay tool for optimizing the IA risk monitoring system. Methods: Peripheral blood gene expression datasets obtained from the Gene Expression Omnibus were integrated into a discovery cohort. Weighted gene co-expression network analysis (WGCNA) and machine learning integrative approaches were utilized to construct a risk signature. QRT-PCR assay was performed to validate the model in an in-house cohort. Immunopathological features were estimated using bioinformatics methods. Results: A four-gene machine learning-derived gene signature (MLDGS) was constructed for identifying patients with IA rupture. The AUC of MLDGS was 1.00 and 0.88 in discovery and validation cohorts, respectively. Calibration curve and decision curve analysis also confirmed the good performance of the MLDGS model. MLDGS was remarkably correlated with the circulating immunopathologic landscape. Higher MLDGS scores may represent higher abundance of innate immune cells, lower abundance of adaptive immune cells, and worse vascular stability. Conclusions: The MLDGS provides a promising molecular assay panel for identifying patients with adverse immunopathological features and high risk of aneurysm rupture, contributing to advances in IA precision medicine.
ABSTRACT
Objective: To evaluate the safety and efficacy of the SeparGate™ balloon-guiding catheter (BGC) for blocking flow and delivering devices in neurointerventional surgery. Method: This prospective multicenter single-arm trial enrolled patients who received BGC adjuvant therapy to provide temporary blood flow arrest of the supra-aortic arch arteries and their branch vessels in interventional therapy. The primary endpoint was immediate procedural success rate in flow arrest, device delivery, and withdrawal. The efficacy endpoints were intraoperative product performance, including rigidity, smoothness, fracture resistance of the catheter wall, catheter push performance, compatibility and radiopaque display, integrity, adhesion thrombus after withdrawal and balloon rupture. The safety endpoints were adverse and serious adverse events associated with the test device and serious adverse events resulting in death or serious health deterioration. Result: A total of 129 patients were included; of them, 128 were analyzed in the full analysis set (FAS) and per protocol set (PPS). Immediate procedural success was achieved in 97.7% of patients with FAS and PPS. The lower bound of the 95% confidence interval was 94.6%, higher than the preset efficacy margin of 94%. Device-related adverse events occurred in 2 (1.6%) cases. One was mild adverse event of vasospasm, which resolved spontaneously. The other was serious adverse event of dissection aggravation, which was treated with stenting angioplasty. No device defects were observed. Conclusion: In neurointerventional surgery, the SeparGate™ BGC can be used to temporarily block the flow of the supra-aortic arch arteries and their branch vessels and guide the interventional device to the target vascular position.
ABSTRACT
Immune inflammation plays an essential role in the formation and rupture of intracranial aneurysm (IA). However, the current limited knowledge of alterations in the immune microenvironment of IA has hampered the mastery of pathological mechanisms and technological advances, such as molecular diagnostic and coated stent-based molecular therapy. In this study, seven IA datasets were enrolled from the GEO database to decode the immune microenvironment and relevant biometric alterations. The ssGSEA algorithm was employed for immune infiltration assessment. IAs displayed abundant immune cell infiltration, activated immune-related pathways, and high expression of immune-related genes. Several immunosuppression cells and genes were also coordinately upregulated in IAs. Five immune-related hub genes, including CXCL10, IL6, IL10, STAT1, and VEGFA, were identified from the protein-protein interaction network and further detected at the protein level. CeRNA networks and latent drugs targeting the hub genes were predicted for targeted therapy reference. Two gene modules recognized via WCGNA were functionally associated with contractile smooth muscle loss and extracellular matrix metabolism, respectively. In blood datasets, a pathological feature-derived gene signature (PFDGS) for IA diagnosis and rupture risk prediction was established using machine learning. Patients with high PFDGS scores may possess adverse biological alterations and present with a high risk of morbidity or IA rupture, requiring more vigilance or prompt intervention. Overall, we systematically unveiled an "immuno-thermal" microenvironment characterized by co-enhanced immune activation and immunosuppression in IA, which provides a novel insight into molecular pathology. The PFDGS is a promising signature for optimizing risk surveillance and clinical decision-making in IA patients.
