Rationale:: Monocyte infiltration into the subintimal space and its intracellular lipid accumulation are the most prominent features of atherosclerosis. To understand the pathophysiology of atherosclerotic disease, we need to understand the characteristics of lipid-laden foamy macrophages in the subintimal space during atherosclerosis. Objective:: We sought to examine the transcriptomic profiles of foamy and nonfoamy macrophages isolated from atherosclerotic intima. Methods and Results:: Single-cell RNA sequencing analysis of CD45 ⁺ leukocytes from murine atherosclerotic aorta revealed that there are macrophage subpopulations with distinct differentially expressed genes involved in various functional pathways. To specifically characterize the intimal foamy macrophages of plaque, we developed a lipid staining–based flow cytometric method for analyzing the lipid-laden foam cells of atherosclerotic aortas. We used the fluorescent lipid probe BODIPY493/503 and assessed side-scattered light as an indication of cellular granularity. BODIPY ^hi SSC ^hi foamy macrophages were found residing in intima and expressing CD11c. Foamy macrophage accumulation determined by flow cytometry was positively correlated with the severity of atherosclerosis. Bulk RNA sequencing analysis showed that compared with nonfoamy macrophages, foamy macrophages expressed few inflammatory genes but many lipid-processing genes. Intimal nonfoamy macrophages formed the major population expressing IL (interleukin)-1β and many other inflammatory transcripts in atherosclerotic aorta. Conclusions:: RNA sequencing analysis of intimal macrophages from atherosclerotic aorta revealed that lipid-loaded plaque macrophages are not likely the plaque macrophages that drive lesional inflammation.

On 31 December 2019 an outbreak of COVID-19 in Wuhan, China, was reported. The outbreak spread rapidly to other Chinese cities and multiple countries. This study described the spatio-temporal pattern and measured the spatial association of the early stages of the COVID-19 epidemic in mainland China from 16 January-06 February 2020. This study explored the spatial epidemic dynamics of COVID-19 in mainland China. Moran's I spatial statistic with various definitions of neighbours was used to conduct a test to determine whether a spatial association of the COVID-19 infections existed. The spatial spread of the COVID-19 pandemic in China was observed. The results showed that most of the models, except medical-care-based connection models, indicated a significant spatial association of COVID-19 infections from around 22 January 2020. Spatial analysis is of great help in understanding the spread of infectious diseases, and spatial association was the key to the spatial spread during the early stages of the COVID-19 pandemic in mainland China.