Abdominal aortic aneurysm (AAA) is a chronic dilated disease of the aorta that is characterized by chronic inflammation. Curcumin (Cur) is previously showed to attenuate AAA by inhibiting inflammatory response in ApoE −/− mice. Since Cur has the limitations of aqueous solubility and instability. Here, we focus on the role of curcumin nicotinate (CurTn), a Cur derivative is derived from Cur and nicotinate. An in vitro model of AAA was established by treating vascular smooth muscle cells (VSMCs) with II (Ang-II). Gene and protein expressions were examined by quantitative real-time PCR (qPCR) or western blotting. Cell migration and pyroptosis were determined by transwell assay and flow cytometry. The interaction between plasmacytoma variant translocation 1 (PVT1), miR-26a and krüppel-like factor 4 (KLF4) was predicted by online prediction tool and confirmed by luciferase reporter assay. CurTn reduced Ang-II-induced AAA-associated proteins, inflammatory cytokine expressions, and attenuated pyroptosis in VSMCs. PVT1 overexpression suppressed the inhibitory effect of CurTn on AngII-induced pyroptosis and inflammatory in VSMCs by sponging miR-26a. miR-26a directly targeted KLF4 and suppressed its expression, which eventually led to the deactivation of the PI3K/AKT signaling pathway. Besides, the regulatory effect of CurTn on pyroptosis of VSMCs induced by Ang-II was reversed through the PVT1/miR-26a/KLF4 pathway. In short, CurTn suppressed VSMCs pyroptosis and inflammation though mediation PVT1/miR-26a/KLF4 axis by regulating the PI3K/AKT signaling pathway, CurTn might consider as a potential therapeutic target in the treatment of AAA.

Background: Deep vein thrombosis (DVT) is a prevalent peripheral vascular disease. The intricate and multifaceted nature of the associated mechanisms hinders a comprehensive understanding of disease-relevant targets. This study aimed to identify and examine the most distinctive genes linked to DVT.Methods: In this study, the bulk RNA sequencing (bulk RNA-seq) analysis was conducted on whole blood samples from 11 DVT patients and six control groups. Topology analysis was performed using seven protein-protein interaction (PPI) network algorithms. The combination of weighted correlation network analysis (WGCNA) and clinical prediction models was employed to validate hub DEGs. Furthermore, single-cell RNA sequencing (scRNA-seq) was performed on peripheral blood samples from 3 DVT patients and three control groups to probe the cellular localization of target genes. Based on the same methodology as the internal test set, 12 DVT patients and six control groups were collected to construct an external test set and validated using machine learning (ML) algorithms and immunofluorescence (IF). Concurrently, the examination of the pathways in disparate cell populations was conducted on the basis of the CellChat pathway.Results: A total of 193 DEGs were identified in the internal test set. Additionally, a total of eight highly characteristic genes (including TLR1, TLR7, TLR8, CXCR4, DDX58, TNFSF10, FCGR1A and CD36) were identified by the PPI network algorithm. In accordance with the WGCNA model, the aforementioned genes were all situated within the blue core module, exhibiting a correlation coefficient of 0.84. The model demonstrated notable disparities in TLR8 (P = 0.018, AUC = 0.847), CXCR4 (P = 0.00088, AUC = 1.000), TNFSF10 (P = 0.00075, AUC = 0.958), and FCGR1A (P = 0.00022, AUC = 0.986). Furthermore, scRNA-seq demonstrated that B cells, T cells and monocytes play an active role in DVT. In the external validation set, CXCR4 was validated as a potential target by the ML algorithm and IF. In the context of the CellChat pathway, it indicated that MIF - (CD74 + CXCR4) plays a potential role.Conclusion: The findings of this study indicate that CXCR4 may serve as a potential genetic marker for DVT, with MIF - (CD74 + CXCR4) potentially implicated in the regulatory mechanisms underlying DVT.

Background: Abdominal aortic aneurysm (AAA) is a potentially life-threatening vascular abnormality, that, if ruptured, is almost universally fatal without repair, and is associated with up to 50% mortality even if repaired in hospital. To date, there is no drug therapy that has clinically proven benefit to reduce or prevent expansion of AAA. The aim of this study was to investigate whether Daxx could affect AAA through inhibiting the PI3K/AKT/ID2 signaling pathway mediated by transforming growth factor β-1 (TGFβ1). Methods: The AAA model was constructed by injecting angiotensin Ⅱ (Ang-Ⅱ) into rats, and the Daxx lentivirus vector was constructed. Hematoxylin and eosin (HE) staining was used to detect the wall thickness of the abdominal aorta in rats. The gene and protein expressions in abdominal aortic tissues were detected utilizing western blot, immunohistochemistry (IHC) and fluorescence quantitative real-time polymerase chain reaction (qRT-PCR). Finally, the concentration of TGF-β1 in abdominal aortic tissue was determined by ELISA. Results: The abdominal aortic wall thickness was decreased in the Daxx expression group (by HE staining), and Daxx overexpression markedly reduced the protein expression levels of MMP2 and MMP9. Proteins related to the PI3K/AKT/ID2 signaling pathway were highly enhanced in the aneurysm wall of rats, but were reduced following Daxx addition. Moreover, Daxx reduced the damage to elastin (by IHC), and the expression levels of α-SMA and SM22α were up-regulated by Daxx (by qRT-PCR). The concentration of TGF-β1 was correlated with the activation of the PI3K/AKT/ID2 signaling pathway (by ELISA), whereas AKT overexpression weakened the inhibitory effect of Daxx. Conclusion: Daxx ameliorated several mechanisms that contributed to expansion of AAA suppressing the tissue concentration of TGF-β1, thereby inhibiting the activation of the PI3K/AKT/ID2 signaling pathway. This evidence might form the basis to develop a therapeutic target for AAA.

Background: This study aimed to analyze the effect of proximal neck angulation on the biomechanical indices of abdominal aortic aneurysms (AAA) and to investigate its impact on the risk of AAA rupture. Methods: CT angiography (CTA) data of patients with AAA from January 2015 to January 2022 were collected. Patients were divided into three groups based on the angle of the proximal neck: Group A (∠β ≤ 30°), Group B (30°<∠β ≤ 60°), and Group C (∠β > 60°). Biomechanical indices related to the rupture risk of AAA were analyzed using computational fluid dynamics modeling (CFD-Post) based on the collected data. Results: Group A showed slight turbulence in the AAA lumen with a mixed laminar flow pattern. Group B had a regular low-speed eddy line characterized by cross-flow dominated by lumen blood flow and turbulence. In Group C, a few turbulent lines appeared at the proximal neck, accompanied by eddy currents in the lumen expansion area following the AAA shape. Significant differences were found in peak wall stress, shear stress, and the maximum blood flow velocity impact among the three groups. The maximum blood flow velocity at the angle of the proximal neck impact indicated the influence of the proximal neck angle on the blood flow state in the lumen. Conclusion: As the angle of the proximal neck increased, it caused stronger eddy currents and turbulent blood flow due to a high-speed area near the neck. The region with the largest diameter in the abdominal aortic aneurysm was prone to the highest stress, indicating a higher risk of rupture. The corner of the proximal neck experienced the greatest shear stress, potentially leading to endothelial injury and further enlargement of the aneurysm.

Deep vein thrombosis (DVT) is a complex thrombotic disorder with multiple environmental and genetic determinants. Nevertheless, the intricacies of DVT regu

Deep vein thrombosis (DVT) is a prevalent peripheral vascular disease that is frequently accompanied by significant complications. However, the complexity and diversity of its pathogenesis have resulted in a lack of in-depth understanding of relevant regulatory targets. The objective of this study was to identify the highly distinctive genes associated with DVT, and to investigate their intricacies. In this study, a comprehensive transcriptomic analysis was conducted on blood samples from 4 DVT patients and 6 healthy subjects from an internal test set, employing established standard procedures. Differential (diff) circular RNAs (circRNAs), diff microRNAs (miRNAs) and diff messenger RNAs (mRNAs) associated with DVT were identified to construct a competing endogenous RNA (ceRNA) network model, and node mRNAs were identified in an external validation set (n = 14). Furthermore, a topological analysis was conducted by using 7 protein–protein interaction (PPI) network algorithms. Concurrently, AlphaFold 2 was employed for three-dimensional prediction and assessment of the molecular structure. The comparative toxicology genomics database (CTD) was employed to assess the interconnectivity between these genes. Subsequently, single-cell RNA sequencing (scRNA-seq) was conducted on blood samples from 3 DVT patients and 3 healthy subjects, following the standard protocol, to ascertain the cellular localization of gene expression and the role of core pathways. A whole-transcriptome analysis identified a total of 406 diff circRNAs, 29 diff miRNAs and 154 diff mRNAs. Concurrently, a total of 6 circRNAs, 5 miRNAs and 16 mRNAs were incorporated into the ceRNA network models (a total of 6 node mRNAs were identified differentially). A total of 5 hub genes (including JAK2, CD36, TNFSF13B, TLR7 and PARP9) were identified by 7 PPI network algorithms. The structure and function of the above genes are adequately described by the AlphaFold 2 and CTD interference scores. A total of 7 cell types were identified by scRNA-seq, and there were obvious differences in the localization of genes and the role of core pathways in different cells. JAK2, CD36, TNFSF13B, TLR7 and PARP9 were identified as potential regulatory target genes for the pathophysiological process of DVT. Additionally, hsa_circ_0095124/hsa-miR-3074-5p/TNFSF13B is a potential regulatory pathway for DVT.