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From January 2020, coronavirus disease (COVID-19) originated in China has spread around the world. The disease is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The presence of myocarditis, cardiac arrest, and acute heart failure in COVID-19 patients suggests the existence of a relationship between SARS-CoV-2 infection and cardiac disease. The Notch signalling is a major regulator of cardiovascular function and it is also implicated in several biological processes mediating viral infections. In this report we discuss the possibility to target Notch signalling to prevent SARS-CoV-2 infection and interfere with the progression of COVID-19- associated heart and lungs disease.

Background Biomarkers can be used to detect the presence of endothelial and/or alveolar epithelial injuries in case of ARDS. Angiopoietin-2 (Ang-2), soluble intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion protein-1 (VCAM-1), P-selectin and E-selectin are biomarkers of endothelial injury, whereas the receptor for advanced glycation end-products (RAGE) reflects alveolar epithelial injury. The aims of this study were to evaluate whether the plasma concentration of the above-mentioned biomarkers was different 1) in survivors and non-survivors of COVID-19-related ARDS and 2) in COVID-19-related and classical ARDS. Methods This prospective study was performed in two COVID-19-dedicated Intensive Care Units (ICU) and one non-COVID-19 ICU at Ferrara University Hospital. A cohort of 31 mechanically ventilated patients with COVID-19 ARDS and a cohort of 11 patients with classical ARDS were enrolled. Ang-2, ICAM-1, VCAM-1, P-selectin, E-selectin and RAGE were determined with a bead-based multiplex immunoassay at three time points: inclusion in the study (T1), after 7 ± 2 days (T2) and 14 ± 2 days (T3). The primary outcome was to evaluate the plasma trend of the biomarker levels in survivors and non-survivors. The secondary outcome was to evaluate the differences in respiratory mechanics variables and gas exchanges between survivors and non-survivors. Furthermore, we compared the plasma levels of the biomarkers at T1 in patients with COVID-19-related ARDS and classical ARDS. Results In COVID-19-related ARDS, the plasma levels of Ang-2 and ICAM-1 at T1 were statistically higher in non-survivors than survivors, (p = 0.04 and p = 0.03, respectively), whereas those of P-selectin, E-selectin and RAGE did not differ. Ang-2 and ICAM-1 at T1 were predictors of mortality (AUROC 0.650 and 0.717, respectively). At T1, RAGE and P-selectin levels were higher in classical ARDS than in COVID-19-related ARDS. Ang-2, ICAM-1 and E-selectin were lower in classical ARDS than in COVID-19-related ARDS (all p < 0.001). Conclusions COVID-19 ARDS is characterized by an early pulmonary endothelial injury, as detected by Ang-2 and ICAM-1. COVID-19 ARDS and classical ARDS exhibited a different expression of biomarkers, suggesting different pathological pathways. Trial registration NCT04343053 , Date of registration: April 13, 2020

Atherosclerosis is a chronic autoimmune inflammatory disease that can cause coronary artery disease, stroke, peripheral artery disease, depending on which arteries are affected. At the beginning of atherosclerosis plasma lipoproteins accumulate in the sub-endothelial space. In response, monocytes migrate from the circulation through the endothelium into the intima where they differentiate into macrophages. These early events trigger a complex immune response that eventually involves many cellular subtypes of both innate and adaptive immunity. The Notch signaling pathway is an evolutionary conserved cell signaling system that mediates cell-to-cell communication. Recent studies have revealed that Notch modulate atherosclerosis by controlling macrophages polarization into M1 or M2 subtypes. Furthermore, it is known that Notch signaling controls differentiation and activity of T-helper and cytotoxic T-cells in inflammatory diseases. In this review, we will discuss the role of Notch in modulating immunity in the context of atherosclerosis and whether targeting Notch may represent a therapeutic strategy.

Background: Deficient interferon responses have been proposed as one of the relevant mechanisms prompting severe manifestations of COVID-19. Objective: To evaluate the interferon (IFN)-α levels in a cohort of COVID-19 patients in relation to severity, evolution of the clinical manifestations and immune/inflammatory profile. Methods: This is prospective study recruiting consecutive hospitalized patients with respiratory failure associated with SARS-COV-2 infection and matched controls. After enrollment, patients were assessed every 7 ± 2 days for additional 2 consecutive visits, for a total of 21 days. The severity of the clinical condition was ranked based on the level of respiratory support required. At each time-point blood samples were obtained to assess immune cells and mediators by multiplex immunoassay. Results: Fifty-four COVD-19 and 11 control patients matched for severity were enrolled. At recruitment, lower levels of blood IFN-α were found in COVID-19 patients compared to controls (3.8-fold difference, p < 0.01). Improvements in COVID-19 severity were paralleled by a significant increase of blood IFN-α levels. A significant increase in blood IFN-α was found over the study period in survivors (70% of the study population). A similar trend was found for blood IFN-β with IFN-β levels below the threshold of detectability in a substantial proportion of subjects. Significantly higher values of blood lymphocytes and lower levels of IL-10 were found at each time point in patients who survived compared to patients who died. In patients who clinically improved and survived during the study, we found an inverse association between IL-10 and IFN-α levels. Conclusion: The study identifies a blood immune profile defined by deficient IFN-α levels associated with increased IL-10 expression in patients progressing to severe/life threatening COVID-19 conditions, suggesting the involvement of immunological pathways that could be target of pharmacological intervention. Clinical Trial Registration: ClinicalTrials.gov identifier NCT04343053.

Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These procedures are associated with high post-intervention mortality, then the corresponding risk assessment is relevant from a clinical standpoint. This study compares the traditional Cox Proportional Hazard (CPH) against Machine Learning (ML) based methods, such as Deep Learning Survival (DeepSurv) and Random Survival Forest (RSF), to identify variables able to estimate the risk of death one year after the intervention, in patients undergoing either to SAVR or TAVI. We found that with all three approaches the combination of six variables, named albumin, age, BMI, glucose, hypertension, and clonal hemopoiesis of indeterminate potential (CHIP), allows for predicting mortality with a c-index of approximately 80 % . Importantly, we found that the ML models have a better prediction capability, making them as effective for statistical analysis in medicine as most state-of-the-art approaches, with the additional advantage that they may expose non-linear relationships. This study aims to improve the early identification of patients at higher risk of death, who could then benefit from a more appropriate therapeutic intervention.

Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by the presence of clones of mutated blood cells without overt blood diseases. In the last few years, it has emerged that CHIP is associated with atherosclerosis and coronary calcification and that it is an independent determinant of cardiovascular mortality. Recently, CHIP has been found to occur frequently in patients with calcific aortic valve disease (CAVD) and it is associated with a poor prognosis after valve replacement. We assessed the frequency of CHIP by DNA sequencing in the blood cells of 168 CAVD patients undergoing surgical aortic valve replacement or transcatheter aortic valve implantation and investigated the effect of CHIP on 12 months survival. To investigate the pathological process of CAVD in CHIP carriers, we compared by RNA-Seq the aortic valve transcriptome of patients with or without CHIP and non-calcific controls. Transcriptomics data were validated by immunohistochemistry on formalin-embedded aortic valve samples. We confirm that CHIP is common in CAVD patients and that its presence is associated with higher mortality following valve replacement. Additionally, we show, for the first time, that CHIP is often accompanied by a broad cellular and humoral immune response in the explanted aortic valve. Our results suggest that an excessive inflammatory response in CHIP patients may be related to the onset and/or progression of CAVD and point to B cells as possible new effectors of CHIP-induced inflammation.

Human bone marrow-derived mesenchymal stem cells (hBMSCs) and their derivative enhanced green fluorescent protein (eGFP)-hBMSCs were employed to evaluate an innovative hybrid scaffold composed of granular hydroxylapatite and collagen hemostat (Coll/HA). The cellular morphology/cytoskeleton organization and cell viability were investigated by immunohistochemistry (IHC) and AlamarBlue metabolic assay, respectively. The expression of osteopontin and osteocalcin proteins was analyzed by IHC and ELISA, whereas osteogenic genes were investigated by quantitative PCR (Q-PCR). Cell morphology of eGFP-hBMSCs was indistinguishable from that of parental hBMSCs. The cytoskeleton architecture of hBMSCs grown on the scaffold appeared to be well organized, whereas its integrity remained uninfluenced by the scaffold during the time course. Metabolic activity measured in hBMSCs grown on a biomaterial was increased during the experiments, up to day 21 ( p < 0.05). The biomaterial induced the matrix mineralization in hBMSCs. The scaffold favored the expression of osteogenic proteins, such as osteocalcin and osteopontin. In hBMSC cultures, the scaffold induced up-regulation in specific genes that are involved in ossification process (BMP2/3, SPP1, SMAD3, and SP7), whereas they showed an up-regulation of MMP9 and MMP10, which play a central role during the skeletal development. hBMSCs were induced to chondrogenic differentiation through up-regulation of COL2A1 gene. Our experiments suggest that the innovative scaffold tested herein provides a good microenvironment for hBMSC adhesion, viability, and osteoinduction. hBMSCs are an excellent in vitro cellular model to assay scaffolds, which can be employed for bone repair and bone tissue engineering.

Endothelial dysfunction characterizes every aspect of the so-called cardiovascular continuum, a series of events ranging from hypertension to the development of atherosclerosis and, finally, to coronary heart disease, thrombus formation, myocardial infarction, and heart failure. Endothelial dysfunction is the main prognostic factor for the progression of vascular disorders, which responds to drug intervention and lifestyle changes. Virtually all of the drugs used to prevent cardiovascular disorders, such as long-used and new antilipidemic agents and inhibitors of angiotensin enzyme (ACEi), exert an important effect on the endothelium. Endothelial dysfunction is a central feature of coronavirus disease -19 (COVID-19), and it is now clear that life-risk complications of the disease are prompted by alterations of the endothelium induced by viral infection. As a consequence, the progression of COVID-19 is worse in the subjects in whom endothelial dysfunction is already present, such as elderly, diabetic, obese, and hypertensive patients. Importantly, circulating biomarkers of endothelial activation and injury predict the severity and mortality of the disease and can be used to evaluate the efficacy of treatments. The purpose of this review is to provide updates on endothelial function by discussing its clinical relevance in the cardiovascular continuum, the latest insights from molecular and cellular biology, and their implications for clinical practice, with a focus on new actors, such as the Notch signaling and emerging therapies for cardiovascular disease.

The ATTAC-Co is a single-center, prospective study including 54 patients admitted to hospital for moderate-severe respiratory failure and positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. TABLE 1 Baseline characteristics Controls (n = 11) Cases (n = 54) P1 Survivors (n = 38) Nonsurvivors (n = 16) P2 Age, years 70 [66-80] 65 [57-73] .244 62.5 [55-71] 72.5 [65-78] .003 Male sex, no. (%) 8 (73) 40 (74) .999 28 (74) 12 (75) .602 BMI, kg/m2 24.3 [21.7-27.0] 26.4 [24.2-30.2] .169 26 [24-29.4] 28.5 [26.1-31] .218 Comorbidities, no. (%) Hypertension 5 (45) 30 (55) .741 20 (53) 4 (25) .078 Dyslipidemia 5 (45) 11 (20) .120 7 (18) 4 (25) .713 Former smoker 4 (36) 16 (30) .725 9 (24) 7 (44) .194 Diabetes 3 (27) 7 (13) .353 5 (13) 2 (13) .999 Prior MI 0 (0) 3 (6) .999 1 (3) 2 (12) .206 Prior coronary revascularization 0 (0) 3 (6) .999 1 (3) 2 (12) .206 Prior CVA 1 (9) 2 (4) .432 2 (5) 0 (0) .491 Peripheral artery disease 2 (18) 8 (15) .673 3 (8) 5 (31) .041 Chronic kidney disease 4 (36) 13 (24) .400 5 (13) 8 (50) .004 Home medical therapy, no. (%) Aspirin 1 (9) 5 (9) .999 2 (5) 3 (19) .147 ACE inhibitors 4 (36) 21 (39) .999 13 (34) 8 (50) .362 Beta-blockers 2 (18) 12 (22) .999 6 (16) 6 (37) .148 Calcium channel blockers 1 (9) 9 (17) .999 4 (10) 5 (31) .105 Statins 2 (18) 9 (17) .999 4 (10) 5 (31) .105 Respiratory parameters at inclusion P/F ratio 140 [80-220] 131 [79-210] .354 161 [90-229] 107 [76-131] .097 PaO2, mmHg 87 [60-120] 85 [65-119] .423 90 [68-126] 75 [65-101] .287 PaCO2, mmHg 42 [25-55] 41 [26-52] .357 39 [35-51] 48 [35-62] .165 pH 7.4 [7.4-7.5] 7.5 [7.4-7.5] .854 7.5 [7.4-7.5] 7.4 [7.3-7.5] .083 Laboratory data at inclusion WBC (u × 103/L) 12.1 [9.6-15.1] 9.1 [5-15] .121 9.1 [6.5-12.7] 9.1 [7.3-11.8] .788 Lymphocytes (u × 103/L) 0.86 [0.71-1.75] 0.80 [0.52-1.06] .217 0.83 [0.52-1.11] 0.72 [0.56-0.90] .404 Hemoglobin, g/dL 12.1 [11.4-13.7] 10.7 [9.6-12.3] .071 11 [9.6-12.3] 10.5 [9.7-12.1] .968 Creatinine clearance, mg/dL 87.2 [45.6-108.6] 88.1 [74.1-106.2] .391 96 [80.5-109.5] 75.8 [60-91.2] .024 Platelets (u × 103/L) 253.5 [162-277] 293 [245-382] .072 311 [264-396] 247 [174-326] .036 Fibrinogen, mg/dL 464 [452-802] 708 [576-823] .275 705 [576-823] 765 [584-842] .356 D-dimer, mg/L FEU 0.85 [0.70-1.7] 2.3 [1.2-4.2] .064 1.85 [1.15-3.95] 2.8 [1.8-4.3] .173 C-reactive protein, mg/dL 5.7 [3.4-10.3] 12.2 [5.4-20.5] .087 9.9 [2.7-15.6] 16.6 [12.5-29.1] .004 HS troponin I, ng/L 9 [3-18] 15.5 [8-52] .001 9.5 [8-24] 34 [15.5-96.5] .002 IL-6, pg/mL 7.8 [1.1, 32.7] 37.7 [9.7, 146.0] .014 35.0 [7.1, 148.5] 41.5 [22.9, 127.8] .543 TNF-α, pg/mL 11.3 [7.9, 33.6] 32.5 [21.8, 54.6] .041 31.82 [21.5, 53.8] 42.6 [27.4, 58.8] .343 Biomarkers at inclusion Soluble endoglin, pg/mL 1045.2 [696.6, 1443.3] 1131.9 [523.3, 1488.0] .944 921.3 [432.6, 1435.3] 1408.9 [884.6, 1902.0] .023 Endothelin-1, pg/mL 5.8 [5.8, 14.9] 7.2 [2.8, 9.8] .384 5.8 [2.8, 8.5] 8.5 [5.4, 11.1] .143 sE-selectin, ng/mL 17.8 [16.6, 38.2] 23.6 [18.9, 35.8] .441 23.0 [18.0, 39.4] 24.0 [22.4, 30.4] .437 sVCAM-1, ng/mL 750.8 [643.2, 966.1] 1087.9 [835.4, 1614.4] .010 986.38 [789.6, 1392.7] 1574.3 [1331.0, 1947.7] .003 Thrombomodulin, ng/mL 5.8 [4.5, 7.3] 8.6 [5.7, 13.9] .031 8.3 [5.5, 11.6] 12.6 [7.1, 17.6] .153 vWF, μg/mL 41.3 [17.9, 57.7] 43.0 [27.1, 84.6] .146 44.5 [27.4, 78.4] 38.8 [26.8, 86.0] .999 Note. Abbreviations: ACE, angiotensin converting enzyme; BMI, body mass index; COPD, chronic obstructive disease; CVA, cerebrovascular accident; FEU, fibrinogen equivalent unit; HS, high sensitivity; MI, myocardial infarction; WBC, white blood cells. Endothelin-1 binds to its receptors exerting a potent vasoconstrictor High levels of circulating endothelin-1 are associated with the impairment of vascular tone regulation sE-selectin Expressed on the membrane of activated endothelial cells, and promotes adhesion of leukocytes Circulating E-selectin reflects endothelial activation or damage sVCAM-1 Expressed on the membrane of activated endothelial cells, and promotes adhesion of leukocytes Circulating sVCAM-1 reflects endothelial activation or damage Soluble thrombomodulin Expressed on the membrane endothelial cells, plays a role as a protein C cofactor and possess anticoagulant activity Released from injured endothelial cells is a marker of endothelial cell damage von Willebrand factor (vWF) Expressed in the endothelial cells, and mediates platelets adhesion to the endothelium vWF is released when endothelial cells are damaged and reflects a prothrombotic status [IMAGE OMITTED.