Background: The role of epicardial fat (eFat)-derived extracellular vesicles (EVs) in the pathogenesis of atrial fibrillation (AF) has never been studied. We tested the hypothesis that eFat-EVs transmit proinflammatory, profibrotic, and proarrhythmic molecules that induce atrial myopathy and fibrillation. Methods: We collected eFat specimens from patients with (n=32) and without AF (n=30) during elective heart surgery. eFat samples were grown as organ cultures, and the culture medium was collected every two days. We then isolated and purified eFat-EVs from the culture medium, and analyzed the EV number, size, morphology, specific markers, encapsulated cytokines, proteome, and miRNAs. Next, we evaluated the biological effects of unpurified and purified EVs on atrial mesenchymal stromal cells (MSCs) and endothelial cells (ECs) in vitro. To establish a causal association between eFat-EVs and vulnerability to AF, we modeled AF in vitro using induced pluripotent stem cell-derived cardiomyocytes (iCMs). Results: Microscopic examination revealed excessive inflammation, fibrosis, and apoptosis in fresh and cultured eFat tissues. Cultured explants from patients with AF secreted more EVs and harbored greater amounts of proinflammatory and profibrotic cytokines, as well as profibrotic miRNA, than those without AF. The proteomic analysis confirmed the distinctive profile of purified eFat-EVs from patients with AF. In vitro, purified and unpurified eFat-EVs from patients with AF had a greater effect on proliferation and migration of human MSCs and ECs, compared to eFat-EVs from patients without AF. Finally, while eFat-EVs from patients with and without AF shortened the action potential duration of iCMs, only eFat-EVs from patients with AF induced sustained reentry (rotor) in iCMs. Conclusions: We show, for the first time, a distinctive proinflammatory, profibrotic, and proarrhythmic signature of eFat-EVs from patients with AF. Our findings uncover another pathway by which eFat promotes the development of atrial myopathy and fibrillation.

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Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in COVID-19 detection with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. In summary, we show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.

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Non-alcoholic fatty liver disease (NAFLD) comprises a spectrum of progressive liver pathologies, ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. A liver biopsy is currently required to stratify high-risk patients, and predicting the degree of liver inflammation and fibrosis using non-invasive tests remains challenging. Here, we sought to develop a novel, cost-effective screening tool for NAFLD based on thermal imaging. We used a commercially available and non-invasive thermal camera and developed a new image processing algorithm to automatically predict disease status in a small animal model of fatty liver disease. To induce liver steatosis and inflammation, we fed C57/black female mice (8 weeks old) a methionine-choline deficient diet (MCD diet) for 6 weeks. We evaluated structural and functional liver changes by serial ultrasound studies, histopathological analysis, blood tests for liver enzymes and lipids, and measured liver inflammatory cell infiltration by flow cytometry. We developed an image processing algorithm that measures relative spatial thermal variation across the skin covering the liver. Thermal parameters including temperature variance, homogeneity levels and other textural features were fed as input to a t-SNE dimensionality reduction algorithm followed by k-means clustering. During weeks 3,4, and 5 of the experiment, our algorithm demonstrated a 100% detection rate and classified all mice correctly according to their disease status. Direct thermal imaging of the liver confirmed the presence of changes in surface thermography in diseased livers. We conclude that non-invasive thermal imaging combined with advanced image processing and machine learning-based analysis successfully correlates surface thermography with liver steatosis and inflammation in mice. Future development of this screening tool may improve our ability to study, diagnose and treat liver disease.

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Inflammation and fibrosis limit the reparative properties of human mesenchymal stromal cells (hMSCs). We hypothesized that disrupting the toll-like receptor 4 (TLR4) gene would switch hMSCs toward a reparative phenotype and improve the outcome of cell therapy for infarct repair. We developed and optimized an improved electroporation protocol for CRISPR-Cas9 gene editing. This protocol achieved a 68% success rate when applied to isolated hMSCs from the heart and epicardial fat of patients with ischemic heart disease. While cell editing lowered TLR4 expression in hMSCs, it did not affect classical markers of hMSCs, proliferation, and migration rate. Protein mass spectrometry analysis revealed that edited cells secreted fewer proteins involved in inflammation. Analysis of biological processes revealed that TLR4 editing reduced processes linked to inflammation and extracellular organization. Furthermore, edited cells expressed less NF-ƙB and secreted lower amounts of extracellular vesicles and pro-inflammatory and pro-fibrotic cytokines than unedited hMSCs. Cell therapy with both edited and unedited hMSCs improved survival, left ventricular remodeling, and cardiac function after myocardial infarction (MI) in mice. Postmortem histologic analysis revealed clusters of edited cells that survived in the scar tissue 28 days after MI. Morphometric analysis showed that implantation of edited cells increased the area of myocardial islands in the scar tissue, reduced the occurrence of transmural scar, increased scar thickness, and decreased expansion index. We show, for the first time, that CRISPR-Cas9-based disruption of the TLR4-gene reduces pro-inflammatory polarization of hMSCs and improves infarct healing and remodeling in mice. Our results provide a new approach to improving the outcomes of cell therapy for cardiovascular diseases.

Background Coronavirus disease 2019 (COVID-19) is associated with microvascular dysfunction. Non-invasive thermal imaging can hypothetically detect changes in perfusion, inflammation and vascular injury. We sought to develop a new point-of-care, non-contact thermal imaging tool to detect COVID-19 by microvascular dysfunction, based on image processing algorithms and machine learning analysis. Materials and methods We captured thermal images of the back of 101 individuals, with (n=62) and without (n=39) COVID-19, using a portable thermal camera that connects directly to smartphones. We developed new image processing algorithms that automatically extract multiple texture and shape features of the thermal images (Figure 1A). We then evaluated the ability of our thermal features to detect COVID-19 and systemic changes of heat distribution associated with microvascular disease. We also assessed correlations between thermal imaging to conventional biomarkers and chest X-ray (CXR). Results Our novel image processing algorithms achieved up to 92% sensitivity in detecting COVID-19 with an area under the curve of 0.85 (95% CI: 0.78, 0.93; p<0.01). Systemic alterations in blood flow associated with vascular disease were observed across the entire back. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression, including blood oxygen saturation, C- reactive protein, and D-dimer. The thermal imaging findings were not correlated with the results of CXR. Conclusions We show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources. Moreover, thermal imaging might detect micro-angiopathies and endothelial dysfunction in patients with COVID-19 and could possibly improve risk stratification of infected individuals (Figure 1B). Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): 1. The Israel Innovation Authority2. The Nicholas and Elizabeth Slezak Super Center for Cardiac Research and Biomedical Engineering at Tel Aviv University Figure 1. A. Representative steps of our thermal image processing algorithms. B. A schematic illustration of the research design and potential impact.