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Aims Chemoattractants and their cognate receptors are essential for leucocyte recruitment during atherogenesis, and atherosclerotic plaques preferentially occur at predilection sites of the arterial wall with disturbed flow (d-flow). In profiling the endothelial expression of atypical chemoattractant receptors (ACKRs), we found that Ackr5 (CCRL2) was up-regulated in an endothelial subpopulation by atherosclerotic stimulation. We therefore investigated the role of CCRL2 and its ligand chemerin in atherosclerosis and the underlying mechanism. Methods and results By analysing scRNA-seq data of the left carotid artery under d-flow and scRNA-seq datasets GSE131776 of ApoE−/− mice from the Gene Expression Omnibus database, we found that CCRL2 was up-regulated in one subpopulation of endothelial cells in response to d-flow stimulation and atherosclerosis. Using CCRL2−/−ApoE−/− mice, we showed that CCRL2 deficiency protected against plaque formation primarily in the d-flow areas of the aortic arch in ApoE−/− mice fed high-fat diet. Disturbed flow induced the expression of vascular endothelial CCRL2, recruiting chemerin, which caused leucocyte adhesion to the endothelium. Surprisingly, instead of binding to monocytic CMKLR1, chemerin was found to activate β2 integrin, enhancing ERK1/2 phosphorylation and monocyte adhesion. Moreover, chemerin was found to have protein disulfide isomerase-like enzymatic activity, which was responsible for the interaction of chemerin with β2 integrin, as identified by a Di-E-GSSG assay and a proximity ligation assay. For clinical relevance, relatively high serum levels of chemerin were found in patients with acute atherothrombotic stroke compared to healthy individuals. Conclusions Our findings indicate that d-flow-induced CCRL2 promotes atherosclerotic plaque formation via a novel CCRL2-chemerin-β2 integrin axis, providing potential targets for the prevention or therapeutic intervention of atherosclerosis. [ABSTRACT FROM AUTHOR]

Carotid plaque neovascularization is one of the major factors for the classification of vulnerable plaque, but the axial force effects of the pulsatile blood flow on the plaque with neovessel and intraplaque hemorrhage was unclear. Together with the severity of stenosis, the fibrous cap thickness, large lipid core, and the neovascularization followed by intraplaque hemorrhage (IPH) have been regarded as high-risk features of plaque rupture. In this work, the effects of these factors were evaluated on the progression and rupture of the carotid atherosclerotic plaques. Five geometries of carotid artery plaque were developed based on contrast-enhanced ultrasound (CEUS) images, which contain two types of neovessel and IPH, and geometry without neovessel and IPH. A one-way fluid-structure interaction model was applied to compute the maximum principal stress and strain in the plaque. For that hyper-elastic and non-linear material, Yeoh 3rd Order strain energy density function was used for components of the plaque. The simulation results indicated that the maximum principal stress of plaque in the carotid artery was higher when the degree of the luminal stenosis increased and the thickness of the fibrous cap decreased. The neovessels within the plaque could introduce a 2.5% increments of deformation in the plaque under the pulsatile blood flow pressure. The IPH also contributed to the increased risk of plaque rupture that a gain of stress was 8.983, 14.526, and 34.47 kPa for the plaque with 50, 65, and 75%, respectively, when comparing stress in the plaque with IPH distributed at the middle to the shoulder of the plaque. In conclusion, neovascularization in the plaque could reduce the stability of the plaque by increasing the stress within the plaque. Also, the risk of plaque rupture increased when large luminal stenosis, thin fibrous cap, and IPH were observed. [ABSTRACT FROM AUTHOR]

To investigate characteristics of intra- and extracranial arterial culprit plaques between patients with single infarct and multiple-infarcts by a head-neck combined high resolution magnetic resonance vessel wall imaging (HR-MRVWI). Forty-three patients with recent ischemic stroke due to large artery atherosclerosis were enrolled. The head-neck combined HR-MRVWI was performed in all patients both pre- and post-contrast administration. Based on diffusion weighted imaging findings, patients were divided into single-infarction and multiple-infarction groups. For patients with anterior circulation ischemic stroke, they were also divided into perforating artery infarction (PAI) and non-PAI groups. Patient demographics, number and location of culprit plaques, artery stenosis percentage, intraplaque hemorrhage, and plaque enhancement were evaluated and compared between single-infarction and multiple-infarction groups, as well as between PAI and non-PAI groups. A total of 83 culprit plaques were identified. The artery stenosis degree was more severe and plaque enhancement more prominent in multiple-infarction group than in single-infarction group. Patients with multiple infarcts also had more culprit plaques per patient than those with single infarct, which contributed to the occurrence of multiple infarcts. For comparison of PAI and non-PAI groups, a higher artery stenosis percentage was observed in non-PAI group, and patients with non-PAI had more culprit plaques per patient, which contributed to a variety of infarct manifestations. A higher stenosis grade and higher number of culprit plaques seem to be associated with a higher number of cerebral infarcts in patients with large artery atherosclerosis. [ABSTRACT FROM AUTHOR]

• As far as we know, we are the first to assess the carotid plaque occurrence using a machine learning method. • High accuracy is achieved in carotid plaque prediction, even when data are missing. • The underlying causal reasoning for the machine decisions is explainable, enabling subclinical interventions.The proposed method is a promising tool for large-scale screening of stroke. The identification of carotid plaque, one of the most crucial tasks in stroke screening, is of great significance in the assessment of subclinical atherosclerosis and preventing the onset of stroke. However, traditional ultrasound examination is not prevalent or cost-effective for asymptomatic people, particularly low-income individuals in rural areas. Thus, it is necessary to develop an accurate and explainable model for early identification of the risk of plaque prevalence that can help in the primary prevention of stroke. We developed an ensemble learning method to predict the occurrence of carotid plaques. A dataset comprising 1440 subjects (50% with plaques and 50% without plaques) and ten-fold cross-validation were utilized to evaluate the model performance. Four machine learning methods (extreme gradient boosting (XGBoost), gradient boosting decision tree, random forest, and support vector machine) were evaluated. Subsequently, the interpretability of the XGBoost model, which provided the best performance, was analyzed from three aspects: feature importance, feature effect on prediction model, and feature effect on prediction decision for a specific subject. The XGBoost algorithm provided the best performance (sensitivity: 0.8678, specificity: 0.8592, accuracy: 0.8632, F1 score: 0.8621, area under the curve: 0.8635) in carotid plaque prediction and also had excellent performance under missing data circumstances. Further, interpretability analysis showed that the decisions of the XGBoost model were highly congruent with clinical knowledge. The model results are superior to those of state-of-the-art methods. Thus, it is a promising carotid plaque prediction tool that could be used in the primary prevention of stroke. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the clinical performance of a newly developed three-dimensional (3D) intra- and extracranial arterial vessel wall joint imaging technique at 3T using T1-weighted 3D variable-flip-angle turbo spin-echo sequence with improved cerebrospinal fluid suppression in patients with cerebrovascular disease.Materials and Methods: 122 consecutive patients (mean age 45.96 ± 12.16 years) with clinically confirmed cerebrovascular symptoms were imaged using a 3D intra- and extracranial arterial vessel wall joint imaging sequence with and without contrast enhancement on a 3 T MR system. The number of plaques and culprit plaques were evaluated. The image quality score, percent stenosis, remodeling ratio, and plaque burden were measured and compared between intracranial and carotid arterial plaques, and between non-culprit and culprit plaques.Results: Except for 23 patients, there were 322 plaques (111 culprit plaques) detected in 96 patients with large artery atherosclerosis. Of the plaques, 278 (96 culprit plaques) and 44 (15 culprit plaques) plaques were identified in intracranial and extracranial arteries, respectively. Image quality did not differ significantly between pre- and post-contrast vessel wall magnetic resonance images. There were also no significant differences in the percent stenosis, remodeling ratio, and plaque burden between intracranial and carotid arteries, and between non-culprit and culprit plaques. The enhancement rate of culprit plaques was significantly higher than that of non-culprit plaques.Conclusions: The described joint imaging is a promising vessel wall magnetic resonance imaging method for comprehensive diagnosis of cerebrovascular symptoms and investigation of etiology. The imaging technique is a potentially valuable means to optimize treatment. [ABSTRACT FROM AUTHOR]