Platelet-Leucocyte Aggregates as Novel Biomarkers in Cardiovascular Diseases

Red ginseng extract inhibits lipopolysaccharide-induced platelet-leukocyte aggregates in mice

Background

Platelet-leukocyte aggregates (PLAs) play important roles in cardiovascular disease and sepsis. Red ginseng extract (RGE) has been well-studied for its antiplatelet and anti-inflammatory activities. However, the potential inhibitory effects of RGE on PLA have not been investigated.

Methods

Six-week-old ICR mice were given oral gavage of RGE for 7 days, followed by an intraperitoneal injection of 15 mg/kg of lipopolysaccharide. Mice were euthanized 24 h later, and blood samples were collected for further analysis. Flow cytometry was utilized to sort populations of PLAs and platelet-neutrophil aggregates (PNAs). By using confocal microscopy, PNAs were validated. Morphological changes in platelets and leukocytes were visualized with scanning electron microscopy. Expressions of tissue factor (TF) and platelet factor 4 (PF4) were investigated using enzyme-linked immunosorbent assay.

Results

Populations of activated platelets, PLAs and PNAs, were significantly increased with LPS-induction. Treatment with 200 and 400 mg/kg of RGE decreased platelet activation. Moreover, the populations of PLAs and PNAs were reduced. PNAs were visible in the blood of septic mice, and this was attenuated by treatment with 400 mg/kg of RGE. Morphologically, sepsisinduced platelet activation and fibrin formation in the blood. This was reduced with RGE treatment. Sepsis-induced increase in the plasma levels of TF and PF4 was also reduced with RGE treatment.

Conclusion

This study shows that RGE is a potential therapeutic that reduces the activation of platelets and targets PLA and PNA formation. Detailed inhibitory mechanisms of RGE should be studied.

Redefining vascular repair: revealing cellular responses on PEUU-gelatin electrospun vascular grafts for endothelialization and immune responses on in vitro models

Tissue-engineered vascular grafts (TEVGs) poised for regenerative applications are central to effective vascular repair, with their efficacy being significantly influenced by scaffold architecture and the strategic distribution of bioactive molecules either embedded within the scaffold or elicited from responsive tissues. Despite substantial advancements over recent decades, a thorough understanding of the critical cellular dynamics for clinical success remains to be fully elucidated. Graft failure, often ascribed to thrombogenesis, intimal hyperplasia, or calcification, is predominantly linked to improperly modulated inflammatory reactions. The orchestrated behavior of repopulating cells is crucial for both initial endothelialization and the subsequent differentiation of vascular wall stem cells into functional phenotypes. This necessitates the TEVG to provide an optimal milieu wherein immune cells can promote early angiogenesis and cell recruitment, all while averting persistent inflammation. In this study, we present an innovative TEVG designed to enhance cellular responses by integrating a physicochemical gradient through a multilayered structure utilizing synthetic (poly (ester urethane urea), PEUU) and natural polymers (Gelatin B), thereby modulating inflammatory reactions. The luminal surface is functionalized with a four-arm polyethylene glycol (P4A) to mitigate thrombogenesis, while the incorporation of adhesive peptides (RGD/SV) fosters the adhesion and maturation of functional endothelial cells. The resultant multilayered TEVG, with a diameter of 3.0 cm and a length of 11 cm, exhibits differential porosity along its layers and mechanical properties commensurate with those of native porcine carotid arteries. Analyses indicate high biocompatibility and low thrombogenicity while enabling luminal endothelialization and functional phenotypic behavior, thus limiting inflammation in in-vitro models. The vascular wall demonstrated low immunogenicity with an initial acute inflammatory phase, transitioning towards a pro-regenerative M2 macrophage-predominant phase. These findings underscore the potential of the designed TEVG in inducing favorable immunomodulatory and pro-regenerative environments, thus holding promise for future clinical applications in vascular tissue engineering.

Impact of rise and fall phases of shear on platelet activation and aggregation using microfluidics

Blood flow disorders are often the result of the non-physiological narrowing of blood arteries caused by atherosclerosis and thrombus. The blood then proceeds through rising-peak-decreasing phases as it passes through the narrow area. Although abnormally high shear is known to activate platelets, the shear process that platelets undergo in small arteries is complex. Thus, understanding how each shear phase affects platelet activation can be used to improve antiplatelet therapy and decrease the risk of side effects like bleeding. Blood samples were sheared (68.8 ms,5200 s-1) in vitro by the microfluidic technique, and platelet activation levels (P-selectin and integrin αIIbβ3) and von Willebrand factor (vWF) binding to platelets were analyzed by flow cytometry. Post-stenosis platelet aggregation was dynamically detected using microfluidic technology. We studied TXA2, P2Y12-ADP, and integrin αIIbβ3-fibrinogen receptor pathways by adding antiplatelet drugs, such as acetylsalicylic acid (ASA, an active ingredient of aspirin that inhibits platelet metabolism), ticagrelor (hinders platelet activation), and tirofiban (blocks integrin αIIbβ3 receptor) in vitro, respectively, to determine platelet activation function mediated by transient non-physiological high shear rates. We demonstrated that platelets can be activated under transient pathological high shear rates. The shear rise and fall phases influenced shear-induced platelet activation by regulating the binding of vWF to platelets. The degree of platelet activation and aggregation increased with multiple shear rise and fall phases. ASA did not inhibit shear-mediated platelet activation, but ticagrelor and tirofiban effectively inhibited shear-mediated platelet activation. Our data demonstrated that the shear rise and fall phases play an important role in shear-mediated platelet activation and promote platelet activation and aggregation in a vWF-dependent manner. Blocking integrin αIIbβ3 receptor and hindering P2Y12-ADP were beneficial to reducing shear-mediated platelet activation.

A novel and cost-effective method for high-throughput 3D culturing and rhythmic assessment of hiPSC-derived cardiomyocytes using retroreflective Janus microparticles

BACKGROUND

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) gain attention as a potent cell source in regenerative medicine and drug discovery. With the necessity of the demands for experimental models to create a more physiologically relevant model of the heart in vitro we herein investigate a 3D culturing platform and a method for assessing rhythm in hiPSC-CMs.

METHODS

The 3D cell culture PAMCELL™ plate is designed to enable cells to attach exclusively to adhesive patterned areas. These cell adhesive zones, named as micro-patterned pads, feature micron silica beads that are surface-modified with the well-known arginyl-glycyl-aspartic acid (RGD) peptide. RGD binding to the surface of hiPSC-CMs facilitates cell-cell attachment and the formation of uniform-size spheroids, which is controlled by the diameter of the micro-patterned pads. The assessment and evaluation of 3D hiPSC-CMs beating pattern are carried out using reflective properties of retroreflective Janus micro-particle (RJP). These RJPs are modified with an antibody targeting the gap junction protein found on the surface of hiPSC-CM spheroids. The signal assessment system comprises a camera attached to an optical microscope and a white light source.

RESULTS

The 3D PAMCELL™ R100 culture plate efficiently generate approximately 350 uniform-sized hiPSC-CM spheroids in each well of a 96-well plate and supported a 20-day culture. Analysis of genes and protein expression levels reveal that iPSC-CM spheroids grown on PAMCELL™ R100 retain cardiac stem cell characteristics and functions, outperforming traditional 2D culture platform. Additionally, the RJPs enable monitoring and evaluation of in vitro beating properties of cardiomyocytes without using complex monitoring setup. The system demonstrates its capability to identify alteration in the rhythmic activity of cardiac cells when exposed to ion channel blockers, nifedipine and E4031.

CONCLUSIONS

The integration of the 3D culture method and RJPs in this study establishes a platform for evaluating the rhythmic properties of 3D hiPSC-CMs. This approach holds significant potential for identifying arrhythmias or other cardiac abnormalities, ultimately contributing to the development of more effective therapies for heart diseases.

Changing Face of Inflammatory Activation in Complex Coronary Artery Disease during the COVID-19 Pandemic

INTRODUCTION

The COVID-19 pandemic has changed the immunological status of the population, indicating increased activation. The aim of the study was to compare the degree of inflammatory activation in patients admitted for surgical revascularization in the period before and during the COVID-19 pandemic.

MATERIALS AND METHODS

This retrospective analysis included an analysis of inflammatory activation assessed on the basis of whole blood counts in 533 patients (435 (82%) male and 98 (18%) female) with a median age of 66 (61-71) years who underwent surgical revascularization, including 343 and 190 patients operated on in 2018 and 2022, respectively.

RESULTS

The compared groups were matched by propensity score matching analysis, obtaining 190 patients in each group. Significantly higher values of preoperative monocyte count (p = 0.015), monocyte-to-lymphocyte ratio (p = 0.004) and systemic inflammatory response index (p = 0.022) were found in the during-COVID subgroup. The perioperative and 12-month mortality rates were comparable, with 1% (n = 4) in 2018 vs. 1% (n = 2) in 2022 (p = 0.911), and 5.6 % (n = 11 patients) vs. 7% (n = 13 patients) (p = 0.413), in the pre-COVID and during-COVID subgroups, respectively.

CONCLUSIONS

Simple whole blood analysis in patients with complex coronary artery disease performed before and during the COVID-19 pandemic indicates excessive inflammatory activation. However, the immune variation did not interfere with one-year mortality rate after surgical revascularization.

Weibull Regression and Machine Learning Survival Models: Methodology, Comparison, and Application to Biomedical Data Related to Cardiac Surgery

In this article, we propose a comparative study between two models that can be used by researchers for the analysis of survival data: (i) the Weibull regression model and (ii) the random survival forest (RSF) model. The models are compared considering the error rate, the performance of the model through the Harrell C-index, and the identification of the relevant variables for survival prediction. A statistical analysis of a data set from the Heart Institute of the University of São Paulo, Brazil, has been carried out. In the study, the length of stay of patients undergoing cardiac surgery, within the operating room, was used as the response variable. The obtained results show that the RSF model has less error rate for the training and testing data sets, at 23.55% and 20.31%, respectively, than the Weibull model, which has an error rate of 23.82%. Regarding the Harrell C-index, we obtain the values 0.76, 0.79, and 0.76, for the RSF and Weibull models, respectively. After the selection procedure, the Weibull model contains variables associated with the type of protocol and type of patient being statistically significant at 5%. The RSF model chooses age, type of patient, and type of protocol as relevant variables for prediction. We employ the randomForestSRC package of the R software to perform our data analysis and computational experiments. The proposal that we present has many applications in biology and medicine, which are discussed in the conclusions of this work.

Early Prediction in Classification of Cardiovascular Diseases with Machine Learning, Neuro-Fuzzy and Statistical Methods

Timely and accurate detection of cardiovascular diseases (CVDs) is critically important to minimize the risk of a myocardial infarction. Relations between factors of CVDs are complex, ill-defined and nonlinear, justifying the use of artificial intelligence tools. These tools aid in predicting and classifying CVDs. In this article, we propose a methodology using machine learning (ML) approaches to predict, classify and improve the diagnostic accuracy of CVDs, including support vector regression (SVR), multivariate adaptive regression splines, the M5Tree model and neural networks for the training process. Moreover, adaptive neuro-fuzzy and statistical approaches, nearest neighbor/naive Bayes classifiers and adaptive neuro-fuzzy inference system (ANFIS) are used to predict seventeen CVD risk factors. Mixed-data transformation and classification methods are employed for categorical and continuous variables predicting CVD risk. We compare our hybrid models and existing ML techniques on a CVD real dataset collected from a hospital. A sensitivity analysis is performed to determine the influence and exhibit the essential variables with regard to CVDs, such as the patient's age, cholesterol level and glucose level. Our results report that the proposed methodology outperformed well known statistical and ML approaches, showing their versatility and utility in CVD classification. Our investigation indicates that the prediction accuracy of ANFIS for the training process is 96.56%, followed by SVR with 91.95% prediction accuracy. Our study includes a comprehensive comparison of results obtained for the mentioned methods.

Serum copper concentration reflect inflammatory activation in the complex coronary artery disease - A pilot study

INTRODUCTION

Coronary artery disease possess inflammatory background related to enzymatic processes with trace elements involvements as co-factors. The aim of the study was to compare serum, urine and salivary copper, magnesium, calcium and zinc levels with inflammatory indices obtained from the whole blood count in patients with complex coronary artery disease.

MATERIAL AND METHOD

Fifty-two (42(81 %) males, 10 (19 %) females) consecutive patients (mean (SD) age 68 (9) years with symptomatic complex coronary artery disease were enrolled into prospective single center study in 2021. Serum, saliva and urine samples were collected at the day of admission for trace elements concentration (copper, zinc, magnesium, calcium) and compared with inflammatory indexes obtained from preoperative and perioperative period.

RESULTS

Multivariable regression analysis revealed relation between the copper serum concentration and neutrophil to lymphocyte ratio (NLR) and systemic inflammatory index (SII).

CONCLUSION

Serum copper concentration interplay with preoperative inflammatory activation in complex coronary disease measured by NLR and SII. The copper serum concentration possesses the strongest relation to preoperative inflammatory activation in patients reffered for off-pump coronary artery bypass grafting.

Correction: Pluta et al. Platelet–Leucocyte Aggregates as Novel Biomarkers in Cardiovascular Diseases. Biology 2022, 11, 224

The authors would like to make the following correction to the published paper [...]

Bioinformatics and System Biological Approaches for the Identification of Genetic Risk Factors in the Progression of Cardiovascular Disease

Background

Cardiovascular disease (CVD) is the combination of coronary heart disease, myocardial infarction, rheumatic heart disease, and peripheral vascular disease of the heart and blood vessels. It is one of the leading deadly diseases that causes one-third of the deaths yearly in the globe. Additionally, the risk factors associated with it make the situation more complex for cardiovascular patients, which lead them towards mortality, but the genetic association between CVD and its risk factors is not clearly explored in the global literature. We addressed this issue and explored the linkage between CVD and its risk factors.

Methods

We developed an analytical approach to reveal the risk factors and their linkages with CVD. We used GEO microarray datasets for the CVD and other risk factors in this study. We performed several analyses including gene expression analysis, diseasome analysis, protein-protein interaction (PPI) analysis, and pathway analysis for discovering the relationship between CVD and its risk factors. We also examined the validation of our study using gold benchmark databases OMIM, dbGAP, and DisGeNET.

Results

We observed that the number of 32, 17, 53, 70, and 89 differentially expressed genes (DEGs) is overlapped between CVD and its risk factors of hypertension (HTN), type 2 diabetes (T2D), hypercholesterolemia (HCL), obesity, and aging, respectively. We identified 10 major hub proteins (FPR2, TNF, CXCL8, CXCL1, IL1B, VEGFA, CYBB, PTGS2, ITGAX, and CCR5), 12 significant functional pathways, and 11 gene ontological pathways that are associated with CVD. We also found the connection of CVD with its risk factors in the gold benchmark databases. Our experimental outcomes indicate a strong association of CVD with its risk factors of HTN, T2D, HCL, obesity, and aging.

Conclusions

Our computational approach explored the genetic association of CVD with its risk factors by identifying the significant DEGs, hub proteins, and signaling and ontological pathways. The outcomes of this study may be further used in the lab-based analysis for developing the effective treatment strategies of CVD.

Platelets at the Crossroads of Pro-Inflammatory and Resolution Pathways during Inflammation

Platelets are among the most abundant cells in the mammalian circulation. Classical platelet functions in hemostasis and wound healing have been intensively explored and are generally accepted. During the past decades, the research focus broadened towards their participation in immune-modulatory events, including pro-inflammatory and, more recently, inflammatory resolution processes. Platelets are equipped with a variety of abilities enabling active participation in immunological processes. Toll-like receptors mediate the recognition of pathogens, while the release of granule contents and microvesicles promotes direct pathogen defense and an interaction with leukocytes. Platelets communicate and physically interact with neutrophils, monocytes and a subset of lymphocytes via soluble mediators and surface adhesion receptors. This interaction promotes leukocyte recruitment, migration and extravasation, as well as the initiation of effector functions, such as the release of extracellular traps by neutrophils. Platelet-derived prostaglandin E2, C-type lectin-like receptor 2 and transforming growth factor β modulate inflammatory resolution processes by promoting the synthesis of pro-resolving mediators while reducing pro-inflammatory ones. Furthermore, platelets promote the differentiation of CD4⁺ T cells in T helper and regulatory T cells, which affects macrophage polarization. These abilities make platelets key players in inflammatory diseases such as pneumonia and the acute respiratory distress syndrome, including the pandemic coronavirus disease 2019. This review focuses on recent findings in platelet-mediated immunity during acute inflammation.