The Potential Predictive Role of Tumour Necrosis Factor-α, Interleukin-1ß, and Monocyte Chemoattractant Protein-1 for COVID-19 Patients Survival.

Background: Tumour necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), and monocyte chemoattractant protein-1 (MCP-1) are early phase cytokines often encountered when the body is exposed to severe acute respiratory syndrome-associated-coronavirus-2. TNF-α, IL-1ß, and MCP-1 are pro-inflammatory cytokines critical in the defence response against systemic infection and injury. Therefore, TNF-α, IL-1ß, and MCP-1 are the most aggressive responses to viral infections in the acute phase, so they can be used to determine the survival of coronavirus disease 2019 (COVID-19) patients. Purpose: The study aimed to determine the levels of TNF-α, IL-1ß, and MCP-1 as predictors of survival for COVID-19 patients. Patients and Methods: A prospective cohort study was conducted on confirmed COVID-19 by a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) in 84 adults admitted to the hospital in Indonesia. TNF-α, IL-1ß, and MCP-1 level were measured from serum subjects using the enzyme-linked immunosorbent assay. Results: The results from logistic regression modelling of the survival status of COVID-19 patients based on TNF-α, IL-1ß, and MCP-1 levels were significant (p-value=0.024). The predictors of all cytokines had P Wald <0.05, so the three cytokines could be used simultaneously to predict the survival status of COVID-19 patients. MCP-1 has the most dominant risk relative value (2.76; 95% CI; 2.53-4.68) compared to TNF-α and IL-1ß in predicting patient survival. Conclusion: TNF-α, IL-1ß, and MCP-1 as markers of acute systemic inflammatory cytokines can be measured at the beginning of hospitalisation of COVID-19 patients for early diagnosis of disease severity so that healthcare professionals can determine clinical guidance needs for therapeutic programs.

Detection of Vascular Inflammation and Oxidative Stress by Cotinine in Smokers: Measured Through Interleukin-6 and Superoxide Dismutase.

Purpose: Smoking is a significant risk factor in developing cardiovascular disease pathogenesis through oxidative stress and inflammation mechanisms. This study used cotinine as a biomarker of nicotine exposure levels in the body, which was associated with levels of Interleukin-6 (IL-6) and Superoxide Dismutase (SOD) as markers of oxidative stress and vascular inflammation. The research aimed to analyze the effect of cotinine levels on the expression of IL-6 and SOD. Methods: This study used a cross-sectional design on 200 subjects, consisting 100 smokers and 100 non-smokers. Cotinine levels, IL-6 expression, and SOD were measured from the blood serum of each subject using the Enzyme-Linked Immunosorbent Assay (ELISA) method. Then the data were analyzed using Generalized Structured Component Analysis (GSCA). Results: There was a significant effect of cotinine levels on the reduction of SOD mediated by IL-6 (CR = 4.006). Cotinine levels also increased IL-6 mediated by SOD (CR = 4.292). The structural model shows that higher cotinine levels will increase IL-6 expression, and conversely, SOD expression will decrease. Conclusion: High cotinine levels cause an increase in the inflammatory process and oxidative stress in the vasculature of smokers, which is characterized by high IL-6 expression and low SOD expression.

Early Detection of Negative Smoking Impacts: Vascular Adaptation Deviation Based on Quantification of Circulated Endothelial Activation Markers.

INTRODUCTION: Smoking can cause vascular damage in the form of an inflammatory reaction characterized by endothelial activation. Endothelial activation forms a pathological adaptation pattern so that it can induce the atherogenesis process. Several markers, such as E-selectin, platelet-derived micro particles (PMPs) and hematopoietic stem cell (HSC) can identify the activation of endothelial in circulating blood. Therefore, the deviation of vascular adaptation due to smoking can be detected early through the feedback mechanism between E-selectin, PMPs, and HSC. PURPOSE: This study aims to analyze the initial picture of the negative impact of smoking on vascular adaptation by measuring E-selectin, PMPs, and HSC in the peripheral blood circulation. Participant criteria and methods: Peripheral blood samples (5 mL) were taken from each participant, both the smoking group (n = 30) and the non-smoker group (n = 31) to obtain peripheral blood mononuclear cells (PBMNC). PBMNC was isolated using ficoll-based gradient centrifugation. The flow cytometry assay method used to measure the E-selectin, PMPs and hematopoietic stem cells. RESULTS: The mean of circulating E-selectin in smokers was higher than that of non-smokers. On the other hand, the average number of PMPs and HSCs in smokers was lower than non-smokers. CONCLUSION: Smoking increases the risk of accelerated vascular block formation, as indicated by an increase in the amount of circulating E-selectin. The increase in E-selectin in the blood vessels mediates the increased adhesion of PMPs in the vascular area so that the number of circulating PMPs in smokers decreases. The decrease in circulating PMPs decreases the signal of vascular repair, which is characterized by a decline in the number of HSCs.

Differences in senescence of late Endothelial Progenitor Cells in non-smokers and smokers.

INTRODUCTION: Endothelial Progenitor Cells (EPCs) are part of hematopoietic stem cells that differentiate into endothelial cells during their blood vessels' maturation process. The role of EPCs is widely known to contribute to repair of the vascular wall when endothelial dysfunction occurs. However, various risk factors for cardiovascular disease (CVD) influence EPC performance, leading to endothelial dysfunction. One EPC dysfunction is decreased amount of EPC mobilization to the injured tissue. EPC dysfunction reduces the angiogenetic function of EPCs. The vital maturation process that the EPCs must pass is the late phase. The dysfunction of late EPCs is known as senescence. This study aimed to identify and compare senescence of late EPCs, through CD62E and CD41 markers, in non-smokers and smokers as a risk factor for CVD. METHODS: EPC collection was from peripheral mononuclear cells (PBMCs) in non-smokers (n=30) and smokers (n=31). The EPCs were then marked by CD62E/CD41 and senescence ß-galactosidase assay using FACS. Identification of senescence cells was based on fluorescence with DAPI. RESULTS: Positive percentage of late EPCs in non-smokers was not significantly different from that in smokers (p=0.014). The number of senescent late EPCs in smokers was higher than in non-smokers (p<0.0001). CONCLUSIONS: Endothelial progenitor cells that experienced senescence in the smokers showed EPC dysfunction, which resulted in decreased cell angiogenic function. Further research is needed to explain the mechanism of re-endothelialization failure in EPC dysfunction due to smoking.

Expression of Hypoxia-Inducible Factor-1α (HIF1A) and Lp-PLA2 in Low, Intermediate, and High Cardiovascular Disease Risk Population.

BACKGROUND: The pathomechanism of CVD is a complex and multifactorial process. The primary mechanism of CVD is atherosclerosis. Inflammation in atherogenesis raises the risk of hypoxia, which will activate hypoxia-inducible factor-1α (HIF1A). Also, together with lipoprotein-associated phospholipase A2 (Lp-PLA2), an inflammatory mediator for atherogenesis. PURPOSE: This study aims to measure the hypoxia-inducible factor-1α (HIF1A) expression and its correlation to Lp-PLA2 expression at low-risk, intermediate, and high-risk CVD populations. PATIENTS AND METHODS: The study used a correlational analysis method with a total sampling technique in 160 individuals in the risk population. The atherosclerosis risk group was analyzed using the Framingham Risk Score and categorized into low, intermediate, and high-risk groups. Venous blood samples taken from respondents were measured using the ELISA method with Lp-PLA2 and HIF-1α as parameters. Data were analyzed using normality test, homogeneity test, one-way ANOVA, post hoc-Tukey HSD, and Pearson correlation. RESULTS: The concentration of HIF1A had a very strong correlation with Lp-PLA2 expression, both in the low-risk group (r = 0.512), intermediate (r = 0.512), and high (r = 0.715) (P <0.05). However, the concentrations of Lp-PLA2 did not match the FRS. CONCLUSION: HIF1A expression increased with increasing risk, while Lp-PLA2 expression decreased with increasing risk of atherosclerosis based on the FRS category. There is a significant correlation between HIF1A expression and Lp-PLA2 expression based on FRS.