An imbalance between RAGE/MR/HMGB1 and ATP1α3 is associated with inflammatory changes in rat brain harboring cerebral aneurysms prone to rupture

Slow G-Quadruplex Conformation Rearrangement and Accessibility Change Induced by Potassium in Human Telomeric Single-Stranded DNA

The guanine-rich telomeric repeats can form G-quadruplexes (G4s) that alter the accessibility of the single-stranded telomeric overhang. In this study, we investigated the effects of Na+ and K+ on G4 folding and accessibility through cation introduction and exchange. We combined differential scanning calorimetry (DSC), circular dichroism (CD), and single molecule Förster resonance energy transfer (smFRET) to monitor the stability, conformational dynamics, and complementary strand binding accessibility of G4 formed by single-stranded telomeric DNA. Our data showed that G4 formed through heating and slow cooling in K+ solution exhibited fewer conformational dynamics than G4 formed in Na+ solution, which is consistent with the higher thermal stability of G4 in K+. Monitoring cation exchange with real time smFRET at room temperature shows that Na+ and K+ can replace each other in G4. When encountering high K+ at room or body temperature, G4 undergoes a slow conformational rearrangement process which is mostly complete by 2 h. The slow conformational rearrangement ends with a stable G4 that is unable to be unfolded by a complementary strand. This study provides new insights into the accessibility of G4 forming sequences at different time points after introduction to a high K+ environment in cells, which may affect how the nascent telomeric overhang interacts with proteins and telomerase.

Increased serum levels of high-mobility group box 1 protein and the location characteristics in the patients of intracranial aneurysms

OBJECTIVE

Inflammation-related factors play a crucial role in intracranial aneurysms (IA) initiation, progression, and rupture. High mobility group box 1 (HMGB-1) serves as an alarm to drive the pathogenesis of the inflammatory disease. This study aimed to evaluate the role of HMGB-1 in IA and explore the correlation with other inflammatory-related factors.

METHODS

A total of twenty-eight adult male Japanese white rabbits were included in with elastase-induced aneurysms, n = 18) and the control group (normal rabbits, n = 10). To assess the expression of HMGB-1, both reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA) was performed on serum samples obtained from human subjects (10 patients with IA and 10 healthy donors) as well as from rabbits (aneurysm group and control group). Immunohistochemistry and immunofluorescence were employed to evaluate the expression levels of elastic fibers, HMGB-1, tumor necrosis factor-alpha (TNF-α), and triggering receptor expressed on myeloid cells-1 (TREM-1).

RESULTS

The expression of HMGB-1 was found to be significantly higher in the IA group compared to the control group, both at the mRNA and protein levels (P < 0.0001). Similar findings were observed in the rabbit aneurysm model group compared to the control group (P < 0.0001). HMGB-1 expression was observed to be more abundant in the inner wall of the aneurysm compared to the external wall, whereas in the control group, it was rarely scattered. Additionally, the localization patterns of TNF-α and TREM-1 exhibited similar characteristics to HMGB-1.

CONCLUSION

Our findings demonstrate that HMGB-1 is highly expressed in both IA patients and rabbit aneurysm models. Furthermore, the similar localization patterns of HMGB-1, TNF-α, and TREM-1 suggest their potential involvement in the inflammatory processes associated with IA. These results highlight the potential of HMGB-1 as a novel therapeutic target for IA.

An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine learning

Background

Immunogenic Cell Death (ICD) is a novel way to regulate cell death and can sufficiently activate adaptive immune responses. Its role in immunity is still emerging. However, the involvement of ICD in Intracranial Aneurysms (IA) remains unclear. This study aimed to identify biomarkers associated with ICDs and determine the relationship between them and the immune microenvironment during the onset and progression of IA

Methods

The IA gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in IA were identified and the effects of the ICD on immune microenvironment signatures were studied. Techniques like Lasso, Bayes, DT, FDA, GBM, NNET, RG, SVM, LR, and multivariate analysis were used to identify the ICD gene signatures in IA. A consensus clustering algorithm was used for conducting the unsupervised cluster analysis of the ICD patterns in IA. Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.

Results

The above techniques were used for establishing the ICD gene signatures of HMGB1, HMGN1, IL33, BCL2, HSPA4, PANX1, TLR9, CLEC7A, and NLRP3 that could easily distinguish IA from normal samples. The unsupervised cluster analysis helped in identifying three ICD gene patterns in different datasets. Gene enrichment analysis revealed that the IA samples showed many differences in pathways such as the cytokine-cytokine receptor interaction, regulation of actin cytoskeleton, chemokine signaling pathway, NOD-like receptor signaling pathway, viral protein interaction with the cytokines and cytokine receptors, and a few other signaling pathways compared to normal samples. In addition, the three ICD modification modes showed obvious differences in their immune microenvironment and the biological function pathways. Eight ICD-regulators were identified and showed meaningful associations with IA, suggesting they could severe as potential prognostic biomarkers.

Conclusions

A new gene signature for IA based on ICD features was created. This signature shows that the ICD pattern and the immune microenvironment are closely related to IA and provide a basis for optimizing risk monitoring, clinical decision-making, and developing novel treatment strategies for patients with IA.