Vascular smooth muscle cells (VSMCs) are the most abundant cell in vessels. Earlier experiments have found that VSMCs possess high plasticity. Vascular injury stimulates VSMCs to switch into a ...dedifferentiated type, also known as synthetic VSMCs, with a high migration and proliferation capacity for repairing vascular injury. In recent years, largely owing to rapid technological advances in single-cell sequencing and cell-lineage tracing techniques, multiple VSMCs phenotypes have been uncovered in vascular aging, atherosclerosis (AS), aortic aneurysm (AA), etc. These VSMCs all down-regulate contractile proteins such as α-SMA and calponin1, and obtain specific markers and similar cellular functions of osteoblast, fibroblast, macrophage, and mesenchymal cells. This highly plastic phenotype transformation is regulated by a complex network consisting of circulating plasma substances, transcription factors, growth factors, inflammatory factors, non-coding RNAs, integrin family, and Notch pathway. This review focuses on phenotypic characteristics, molecular profile and the functional role of VSMCs phenotype landscape; the molecular mechanism regulating VSMCs phenotype switching; and the contribution of VSMCs phenotype switching to vascular aging, AS, and AA. Video Abstract.
Link prediction is a fundamental problem in biological network analysis, personalized recommendation, network evolution modeling, etc. It aims at discovering links in the network that are unknown, ...missing, or will be formed in the future. Network representation learning-based link prediction approaches have drawn extensive attention, due to its high efficiency. The previous approaches use random or hyper parameters to select nodes from neighbors or communities when generating walk sequences. However, they do not fully consider the contribution of nodes to the embedded representation and hence impairing the affect the role of community structure in link prediction. To overcome this limitation and utilize community structure, we propose a betweenness centrality-based community adaptive network representation for link prediction method called CALP, which forms network representation by using betweenness centrality to measure the different contribution of community nodes and neighbor nodes for embedding and then applies it to link prediction. CALP first divides the network into communities. Then, it selects a node from the community nodes or neighbor nodes to join the walk sequence by the contribution of the node to embedding. Finally, it generates the corresponding network representation for link prediction. Experiments on realistic networks such as Cora, Citeseer, etc. show that the accuracy of CALP is much better than other approaches.
Aortic aneurysm (AA) and aortic dissection (AD) are prevalent severe cardiovascular diseases that result in catastrophic complications and unexpected deaths. Owing to the lack of clinically ...established and effective medications, the only treatment options are open surgical repair or endovascular therapy. Most researchers have focused on the development of innovative medications or therapeutic targets to slow the progression of AA/AD or lower the risk of malignant consequences. Recent studies have shown that the use of fluoroquinolones (FQs) may increase susceptibility to AA/AD to some extent, especially in patients with aortic dilatation and those at a high risk of AD. Therefore, it is crucial for doctors, particularly those in cardiovascular specialties, to recognize the dangers of FQs and adopt alternatives. In the present review, the main clinical observational studies on the correlation between FQs and AA/AD in recent years are summarized, with an emphasis on the relative physiopathological mechanism incorporating destruction of the extracellular matrix (ECM), phenotypic transformation of vascular smooth muscle cells, and local inflammation. Although additional data are required, it is anticipated that the rational use of FQs will become the standard of care for the treatment of aortic diseases.
Phenotypic switching in vascular smooth muscle cells (VSMCs) has been linked to aortic aneurysm, but the phenotypic landscape in aortic aneurysm is poorly understood. The present study aimed to ...analyse the phenotypic landscape, phenotypic differentiation trajectory, and potential functions of various VSMCs phenotypes in aortic aneurysm.
Single-cell sequencing data of 12 aortic aneurysm samples and 5 normal aorta samples (obtained from GSE166676 and GSE155468) were integrated by the R package Harmony. VSMCs were identified according to the expression levels of ACTA2 and MYH11. VSMCs clustering was determined by the R package 'Seurat'. Cell annotation was determined by the R package 'singleR' and background knowledge of VSMCs phenotypic switching. The secretion of collagen, proteinases, and chemokines by each VSMCs phenotype was assessed. Cell‒cell junctions and cell-matrix junctions were also scored by examining the expression of adhesion genes. Trajectory analysis was performed by the R package 'Monocle2'. qPCR was used to quantify VSMCs markers. RNA fluorescence in situ hybridization (RNA FISH) was performed to determine the spatial localization of vital VSMCs phenotypes in aortic aneurysms.
A total of 7150 VSMCs were categorize into 6 phenotypes: contractile VSMCs, fibroblast-like VSMCs, T-cell-like VSMCs, adipocyte-like VSMCs, macrophage-like VSMCs, and mesenchymal-like VSMCs. The proportions of T-cell-like VSMCs, adipocyte-like VSMCs, macrophage-like VSMCs, and mesenchymal-like VSMCs were significantly increased in aortic aneurysm. Fibroblast-like VSMCs secreted abundant amounts of collagens. T-cell-like VSMCs and macrophage-like VSMCs were characterized by high chemokine levels and proinflammatory effects. Adipocyte-like VSMCs and mesenchymal-like VSMCs were associated with high proteinase levels. RNA FISH validated the presence of T-cell-like VSMCs and macrophage-like VSMCs in the tunica media and the presence of mesenchymal-like VSMCs in the tunica media and tunica adventitia.
A variety of VSMCs phenotypes are involved in the formation of aortic aneurysm. T-cell-like VSMCs, macrophage-like VSMCs, and mesenchymal-like VSMCs play pivotal roles in this process. Video Abstract.
Network representation learning is proposed to make it easier to perform complex inference processes on large-scale networks. It aims to represent each node in the network as a low-dimensional ...potential representation while preserving the structure and inherent features of the network. Most existing learning methods do not consider the comprehensive structure or the rich semantics of between nodes, which lead to incomplete embeddings. We attempt to find a way to learn network representation while keeping the network structure and relations between nodes to address this issue. In this paper, we propose a Community Aware and Relational Attention (CARA) method to enhance network representation learning. In CARA, community aware random walks capture both the community and local context from a global perspective to enhance the structure embedding. And we design a two-layer attention mechanism to model the semantic relationships between nodes, which can learn different text embedding for different neighbors. Then, these two embeddings are combined together to obtain the node representation. Experiments on four real-world networks show that CARA has better performance than other methods in link prediction and node classification.
The link prediction can be used to seek missing or future links in the network, so it has become a hot research topic. The network generally contains two types of information: the topological ...structure of network formed by the connection between nodes, and the attribute information of nodes. However, the existing topology-based link prediction algorithms consider little attribute information. In this paper, a novel algorithm called Network Embedding with Attribute Deep Fusion for Link Prediction (NEADF-LP) is proposed. We get the embedded vectors with topological structure and attribute information by structure encoder and attribute encoder respectively, and fuse two vectors deeply. Compared with mainstream baselines on CiteSeer and Cora datasets, the results show that the deep fusion of topological structure and attribute information improve the accuracy of link prediction effectively.
This paper applies two methods to analyze the ecological sensitivity in Huixian wetland, (Guangxi province, China). The one method (the ecological unit method) is that the Huixian wetland reserve is ...divided into several ecological units according to different geographic condition and agricultural structure; the main factors of ecological sensitivity are selected; Delphi and Analytical Hierarchy Process (AHP) are applied to determine evaluation factors and the weight of each factor; at last, Index Accumulation Method (IAM) is adopted to evaluate the ecological sensitivity. The other method (the GIS method) is that using ecological sensitivity indexes and GIS spatial analysis module, makes a comprehensive evaluation of the ecological sensitivity in Huixian wetland. The results of the ecological sensitivity analysis show that the most sensible zone lies in the centre of the wetland reserve, which can be set to the core protection area. The high sensibility zone is around the core protection area, which can be set to the buffer zone or experimental zone. The lowest sensibility zone is located in the east of the wetland reserve, which can be set to the demonstration area. The compared results of the two different methods show that the first method, the ecological unit method, can be used in case of comparative shortage of existing data. The ecological sensibility distribution is relatively explicit. The second method, the GIS method, can be used in case of the abundant Remote Sensing (RS) and geographic information systems (GIS) data. The analytical results are meticulous and objective. The ecological sensibility distribution is relatively implicit.
The Finkel‐Biskis‐Jinkins Osteosarcoma (c‐Fos; encoded by FOS) plays an important role in several cardiovascular diseases, including atherosclerosis and stroke. However, the relationship between FOS ...and venous thromboembolism (VTE) remains unknown. We identified differentially expressed genes in Gene Expression Omnibus dataset, GSE48000, comprising VTE patients and healthy individuals, and analysed them using CIBERSORT and weighted co‐expression network analysis (WGCNA). FOS and CD46 expressions were significantly downregulated (FOS p = 2.26E‐05, CD64 p = 8.83E‐05) and strongly linked to neutrophil activity in VTE. We used GSE19151 and performed PCR to confirm that FOS and CD46 had diagnostic potential for VTE; however, only FOS showed differential expression by PCR and ELISA in whole blood samples. Moreover, we found that hsa‐miR‐144 which regulates FOS expression was significantly upregulated in VTE. Furthermore, FOS expression was significantly downregulated in neutrophils of VTE patients (p = 0.03). RNA sequencing performed on whole blood samples of VTE patients showed that FOS exerted its effects in VTE via the leptin‐mediated adipokine signalling pathway. Our results suggest that FOS and related genes or proteins can outperform traditional clinical markers and may be used as diagnostic biomarkers for VTE.
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