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Institute
Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagnostic test sensitivity of COVID-19 is limited due to irregularities in specimen handling. We propose a deep learning framework that identifies COVID-19 from medical images as an auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography images to train the convolutional neural network, which achieves a performance similar to that of experts and provides high scores for multiple statistical indices (F1 scores > 96.72% (0.9307, 0.9890) and specificity >99.33% (0.9792, 1.0000)). Heatmaps are used to visualize the salient features extracted by the neural network. The neural network-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, resulting in high accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.
Highlights
• This current review covers studies that have identified long non-coding RNAs in aortic aneurysm development and progression.
• We separately discuss transcripts and mechanisms of importance to thoracic as well as abdominal aortic aneurysms.
• Functional data on lncRNAs being identified are highlighted.
• Some have been studied in human as well as experimental models of the disease pathology.
Abstract
Aortic aneurysm (AA) is a complex and dangerous vascular disease, featuring progressive and irreversible vessel dilatation. AA is typically detected either by screening, or identified incidentally through imaging studies. To date, no effective pharmacological therapies have been identified for clinical AA management, and either endovascular repair or open surgery remains the only option capable of preventing aneurysm rupture. In recent years, multiple research groups have endeavored to both identify noncoding RNAs and to clarify their function in vascular diseases, including aneurysmal pathologies. Notably, the molecular roles of noncoding RNAs in AA development appear to vary significantly between thoracic aortic aneurysms (TAAs) and abdominal aortic aneurysms (AAAs). Some microRNAs (miRNA - a non-coding RNA subspecies) appear to contribute to AA pathophysiology, with some showing major potential for use as biomarkers or as therapeutic targets. Studies of long noncoding RNAs (lncRNAs) are more limited, and their specific contributions to disease development and progression largely remain unexplored. This review aims to summarize and discuss the most current data on lncRNAs and their mediation of AA pathophysiology.
Long non-coding RNAs (lncRNAs) orchestrate various biological processes and regulate the development of cardiovascular diseases. Their potential therapeutic benefit to tackle disease progression has recently been extensively explored. Our study investigates the role of lncRNA Nudix Hydrolase 6 (NUDT6) and its antisense target fibroblast growth factor 2 (FGF2) in two vascular pathologies: abdominal aortic aneurysms (AAA) and carotid artery disease. Using tissue samples from both diseases, we detected a substantial increase of NUDT6, whereas FGF2 was downregulated. Targeting Nudt6 in vivo with antisense oligonucleotides in three murine and one porcine animal model of carotid artery disease and AAA limited disease progression. Restoration of FGF2 upon Nudt6 knockdown improved vessel wall morphology and fibrous cap stability. Overexpression of NUDT6 in vitro impaired smooth muscle cell (SMC) migration, while limiting their proliferation and augmenting apoptosis. By employing RNA pulldown followed by mass spectrometry as well as RNA immunoprecipitation, we identified Cysteine and Glycine Rich Protein 1 (CSRP1) as another direct NUDT6 interaction partner, regulating cell motility and SMC differentiation. Overall, the present study identifies NUDT6 as a well-conserved antisense transcript of FGF2. NUDT6 silencing triggers SMC survival and migration and could serve as a novel RNA-based therapeutic strategy in vascular diseases.
An abdominal aortic aneurysm (AAA) is a pathological widening of the aortic wall characterized by loss of smooth muscle cells (SMCs), extracellular matrix degradation, and local inflammation. This condition is often asymptomatic until rupture occurs, leading to high morbidity and mortality rates. Diagnosis is mostly accidental and the only currently available treatment option remains surgical intervention. Circular RNAs (circRNAs) represent a novel class of regulatory non-coding RNAs that originate from backsplicing. Their highly stable loop structure, combined with a remarkable enrichment in body fluids, make circRNAs promising disease biomarkers. We investigated the contribution of circRNAs to AAA pathogenesis and their potential application to improve AAA diagnostics. Gene expression analysis revealed the presence of deregulated circular transcripts stemming from AAA-relevant gene loci. Among these, the circRNA to the Ataxia Telangiectasia Mutated gene (cATM) was upregulated in human AAA specimens, in AAA-derived SMCs, and serum samples collected from aneurysm patients. In primary aortic SMCs, cATM increased upon angiotensin II and doxorubicin stimulation, while its silencing triggered apoptosis. Higher cATM levels made AAA-derived SMCs less vulnerable to oxidative stress, compared with control SMCs. These data suggest that cATM contributes to elicit an adaptive oxidative-stress response in SMCs and provides a reliable AAA disease signature.