Use of Mouse Carotid Artery Ligation Model of Intimal Thickening to Probe Vascular smooth muscle cell (VSMC) Remodelling and Function in Atherosclerosis
Abstract
The thickening of the intima is a critical underlying component of atherosclerosis. Consequently, robust and reproducible animal models of intimal thickening are essential for a greater understanding of the mechanisms underlying the process of intimal thickening and to evaluate new approaches for the reduction of intimal thickening and thereby atherosclerosis. The ligation of the carotid artery in the mouse causes the thickening of the intimal layer of the artery. This model is relatively simple and is reproducible and therefore is a preferred and well-established model of intimal thickening. Here, we detail a protocol for carotid artery ligation in the mouse and methods for histological examination and quantification of intimal thickening.Key wordsMouseCarotid arteryIntimal thickening
Proliferation
Migration
... The mice were housed in a room maintained at 22°C with a 12-h light/dark cycle, and provided with ad libitum access to food and water. The carotid artery procedure was performed as described in previous studies (Williams et al., 2022). Briefly, the mice were anesthetized with an intraperitoneal injection of 100 mg/kg ketamine-HCl and 10 mg/kg xylazine-HCl. ...
Background: Neointimal hyperplasia (NH) is a crucial pathophysiological feature in vascular transplant and in-stent restenosis. Excessive proliferation and migration of vascular smooth muscle cells (VSMCs) play important roles in neointimal hyperplasia. This study aims to explore the potentialities and mechanism of sulfasalazine (SSZ) in the prevention of restenosis.
Methods: Sulfasalazine was encapsulated in nanoparticles made of poly (lactic-co-glycolic acid) (PLGA). In vivo, carotid ligation injury was induced in mice to induce Neointimal hyperplasia, with or without sulfasalazine containing nanoparticles (NP-SSZ) treatment. After 4 weeks, the arteries were collected for histology, immunofluorescence, Western blotting (WB) and qRT-PCR. In vitro, vascular smooth muscle cells were treated with TNF-α to induce cell proliferation and migration, followed by SSZ or vehicle treatment. WB was performed to further explore its mechanism.
Results: The ratio of intima to media thickness (I/M) was increased after ligation injury on day 28, while the ratio was significantly reduced in the NP-SSZ treatment group. The dual positive nuclei of Ki-67 and α-SMA were 47.83% ± 9.15%, whereas only 29.83% ± 5.98% in the NP-SSZ-treated group (p < 0.05). Both MMP-2 and MMP-9 were decreased in the NP-SSZ treatment group (p < 0.05, p < 0.05, respectively) compared to the control group. The levels of the targeted inflammatory genes (TNF-α, VCAM-1, ICAM-1, MCP-1) were lower in the NP-SSZ treatment group compared with the control group. In vitro, the proliferating cell nuclear antigen (PCNA) expression was significantly decreased in the SSZ treatment group. The cell viability of VSMCs was markedly increased in the TNF-α treatment group, whereas sulfasalazine treatment inhibited this effect. LC3 II and P62 protein expression were higher in the SSZ group than in the vehicle group both in vitro and in vivo. The phosphorylation of NF-kB (p-NF-kB) and the phosphorylation of mTOR (p-mTOR) were decreased in the TNF-α+ SSZ group, whereas the P62 and LC3 II expression levels were increased. However, the expression level of p-mTOR, P62, and LC3 II was reversed after co-treatment with the agonist of mTOR MHY1485, whereas the p-NF-kB expression level was unchanged.
Conclusion: sulfasalazine inhibited vascular smooth muscle cells proliferation and migration in vitro and Neointimal hyperplasia in vivo through NF-kB/mTOR-mediated autophagy.
The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce “weighted-nearest neighbor” analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.
Atherosclerosis is a major cause of human cardiovascular disease, which is the leading cause of mortality around the world. Various physiological and pathological processes are involved, including chronic inflammation, dysregulation of lipid metabolism, development of an environment characterized by oxidative stress and improper immune responses. Accordingly, the expansion of novel targets for the treatment of atherosclerosis is necessary. In this study, we focus on the role of foam cells in the development of atherosclerosis. The specific therapeutic goals associated with each stage in the formation of foam cells and the development of atherosclerosis will be considered. Processing and metabolism of cholesterol in the macrophage is one of the main steps in foam cell formation. Cholesterol processing involves lipid uptake, cholesterol esterification and cholesterol efflux, which ultimately leads to cholesterol equilibrium in the macrophage. Recently, many preclinical studies have appeared concerning the role of non-encoding RNAs in the formation of atherosclerotic lesions. Non-encoding RNAs, especially microRNAs, are considered regulators of lipid metabolism by affecting the expression of genes involved in the uptake (e.g., CD36 and LOX1) esterification (ACAT1) and efflux (ABCA1, ABCG1) of cholesterol. They are also able to regulate inflammatory pathways, produce cytokines and mediate foam cell apoptosis. We have reviewed important preclinical evidence of their therapeutic targeting in atherosclerosis, with a special focus on foam cell formation.
Advanced optical methods combined with various probes pave the way toward molecular imaging within living cells. However, major challenges are associated with the need to enhance the imaging resolution even further to the subcellular level for the imaging of larger tissues, as well as for in vivo studies. High scattering and absorption of opaque tissues limit the penetration of light into deep tissues and thus the optical imaging depth. Tissue optical clearing technique provides an innovative way to perform deep-tissue imaging. Recently, various optical clearing methods have been developed, which provide tissue clearing based on similar physical principles via different chemical approaches. Here, we introduce the mechanisms of the current clearing methods from fundamental physical and chemical perspectives, including the main physical principle, refractive index matching via various chemical approaches, such as dissociation of collagen, delipidation, decalcification, dehydration, and hyperhydration, to reduce scattering, as well as decolorization to reduce absorption.
Hyperlipidemia or dyslipidemia is a major risk factor for atherosclerotic diseases. Experimental animals play an important role in elucidating the molecular mechanisms of the pathophysiology of hyperlipidemia as well as in drug development. Rabbits are one of the most suitable models to study human hyperlipidemia because many features of the lipoprotein metabolism of rabbits are similar to those of humans such as LDL-rich lipoproteins in plasma, apolipoprotein B mRNA editing, and cholesteryl ester transfer protein. Currently, three types of rabbit models are commonly used for studying hyperlipidemia: (1) diet-induced hyperlipidemic rabbits, (2) spontaneous hyperlipidemic rabbits, and (3) gene-manipulated rabbits (transgenic and knockout rabbits). In this review, we give an overview of the features of hyperlipidemic rabbits and discuss the usefulness of rabbits for the development of anti-atherogenic drugs.
Despite exciting advances in structural intravascular imaging [intravascular ultrasound (IVUS) and optical coherence tomography (OCT)] that have enabled partial assessment of atheroma burden and high-risk features associated with acute coronary syndromes, structural-based imaging modalities alone do not comprehensively phenotype the complex pathobiology of atherosclerosis. Near-infrared fluorescence (NIRF) is an emerging molecular intravascular imaging modality that allows for in vivo visualization of pathobiological and cellular processes at atheroma plaque level, including inflammation, oxidative stress, and abnormal endothelial permeability. Established intravascular NIRF imaging targets include macrophages, cathepsin protease activity, oxidized low-density lipoprotein and abnormal endothelial permeability. Structural and molecular intravascular imaging provide complementary information about plaque microstructure and biology. For this reason, integrated hybrid catheters that combine NIRF-IVUS or NIRF-OCT have been developed to allow co-registration of morphological and molecular processes with a single pullback, as performed for standalone IVUS or OCT. NIRF imaging is approaching application in clinical practice. This will be accelerated by the use of FDA-approved indocyanine green (ICG), which illuminates lipid- and macrophage-rich zones of permeable atheroma. The ability to comprehensively phenotype coronary pathobiology in patients will enable a deeper understanding of plaque pathobiology, improve local and patient-based risk prediction, and usher in a new era of personalized therapy.
Transgenic rabbits have contributed to the progress of biomedical science as human disease models because of their unique features, such as the lipid metabolism system similar to humans and medium body size that facilitates handling and experimental manipulation. In fact, many useful transgenic rabbits have been generated and used in research fields such as lipid metabolism and atherosclerosis, cardiac failure, immunology, and oncogenesis. However, there have been long-term problems, namely that the transgenic efficiency when using pronuclear microinjection is low compared with transgenic mice and production of knockout rabbits is impossible owing to the lack of embryonic stem cells for gene targeting in rabbits. Despite these limitations, the emergence of novel genome editing technology has changed the production of genetically modified animals including the rabbit. We are finally able to produce both transgenic and knockout rabbit models to analyze gain- and loss-of-functions of specific genes. It is expected that the use of genetically modified rabbits will extend to various research fields. In this review, we describe the unique features of rabbits as laboratory animals, the current status of their development and use, and future perspectives of transgenic rabbit models for human diseases.
BACKGROUND
The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).
METHODS
The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year’s worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year’s edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.
RESULTS
Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
CONCLUSIONS
The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
In single-cell RNA sequencing (scRNA-seq), doublets form when two cells are encapsulated into one reaction volume. The existence of doublets, which appear to be—but are not—real cells, is a key confounder in scRNA-seq data analysis. Computational methods have been developed to detect doublets in scRNA-seq data; however, the scRNA-seq field lacks a comprehensive benchmarking of these methods, making it difficult for researchers to choose an appropriate method for specific analyses. We conducted a systematic benchmark study of nine cutting-edge computational doublet-detection methods. Our study included 16 real datasets, which contained experimentally annotated doublets, and 112 realistic synthetic datasets. We compared doublet-detection methods regarding detection accuracy under various experimental settings, impacts on downstream analyses, and computational efficiencies. Our results show that existing methods exhibited diverse performance and distinct advantages in different aspects. Overall, the DoubletFinder method has the best detection accuracy, and the cxds method has the highest computational efficiency. A record of this paper’s transparent peer review process is included in the Supplemental Information.
Due to the complexity and limited availability of human brain tissues, for decades, pathologists have sought to maximize information gained from individual samples, based on which (patho)physiological processes could be inferred. Recently, new understandings of chemical and physical properties of biological tissues and multiple chemical profiling have given rise to the development of scalable tissue clearing methods allowing superior optical clearing of across-the-scale samples. In the past decade, tissue clearing techniques, molecular labeling methods, advanced laser scanning microscopes, and data visualization and analysis have become commonplace. Combined, they have made 3D visualization of brain tissues with unprecedented resolution and depth widely accessible. To facilitate further advancements and applications, here we provide a critical appraisal of these techniques. We propose a classification system of current tissue clearing and expansion methods that allows users to judge the applicability of individual ones to their questions, followed by a review of the current progress in molecular labeling, optical imaging, and data processing to demonstrate the whole 3D imaging pipeline based on tissue clearing and downstream techniques for visualizing the brain. We also raise the path forward of tissue-clearing-based imaging technology, that is, integrating with state-of-the-art techniques, such as multiplexing protein imaging, in situ signal amplification, RNA detection and sequencing, super-resolution imaging techniques, multiomics studies, and deep learning, for drawing the complete atlas of the human brain and building a 3D pathology platform for central nervous system disorders.