miR-21 is a 22-nucleotide long microRNA that matches target mRNAs in a complementary base pairing fashion and regulates gene expression by repressing or degrading target mRNAs. miR-21 is involved in various cardiomyopathies, including heart failure, dilated cardiomyopathy, myocardial infarction, and diabetic cardiomyopathy. Expression levels of miR-21 notably change in both heart and circulation and provide cardiac protection after heart injury. In the meantime, miR-21 also tightly links to cardiac dysfunctions such as cardiac hypertrophy and fibrosis. This review focuses on the miR-21 expression pattern and its functions in diseased-heart and further discusses the feasibility of miR-21 as a biomarker and therapeutic target in cardiomyopathies.

In obesity, several epigenetic modifications, including histones remodeling, DNA methylation, and microRNAs, could accumulate and determine increased expression of inflammatory molecules, the adipokines, that in turn might induce or accelerate the onset and development of cardiovascular and metabolic disorders. In order to better clarify the potential epigenetic mechanisms underlying the modulation of the inflammatory response by adipokines, the DNA methylation profile in peripheral leukocytes of the promoter region of IL-6 and NF-kB genes and plasma miRNA-21 levels were evaluated in 356 healthy subjects, using quantitative pyrosequencing-based analysis, and correlated with plasma adiponectin levels, body fat content and the primary pro-inflammatory markers. In addition, correlation analysis of DNA methylation profiles and miRNA-21 plasma levels with intima-media thickness (IMT), a surrogate marker for early atherosclerosis, left ventricular mass (LVM), left ventricular ejection fraction (LVEF), and cardiac performance index (MPI) was also performed to evaluate any potential clinical implication in terms of cardiovascular outcome. Results achieved confirmed the role of epigenetics in the obesity-related cardiovascular complications and firstly supported the potential role of plasma miRNA-21 and IL-6 and NF-kB DNA methylation changes in nucleated blood cells as potential biomarkers for predicting cardiovascular risk in obesity. Furthermore, our results, showing a role of adiponectin in preventing epigenetic modification induced by increased adipose tissue content in obese subjects, provide new evidence of an additional mechanism underlying the anti-inflammatory properties and the cardiovascular benefits of adiponectin. The exact mechanisms underlying the obesity-related epigenetic modifications found in the blood cells and whether similar epigenetic changes reflect adipose and myocardial tissue modifications need to be further investigated in future experiments.

Background: Sodium-glucose co-transporters inhibitors showed many beneficial effects at the cardiovascular level. Several mechanisms of action have been identified. However, no data are reported on their capability to act via epigenetic mechanisms. Therefore, this study aimed to investigate the ability of SGLT2 inhibitors to induce protective effects at the cardiovascular level by acting on DNA methylation. Methods: To better clarify this issue, the effects of empagliflozin on hyperglycemia-induced epigenetic modifications were evaluated in human ventricular cardiac myoblasts AC16 exposed to hyperglycemia for 7 days. Therefore, effects of EMPA on DNA methylation of NF-κB, SOD2, and IL-6 genes in AC16 exposed to high glucose were analyzed by pyrosequencing-based methylation analysis. Modifications of gene expression and DNA methylation of NF-κB and SOD2 were confirmed in response to a transient SGLT2 gene silencing in the same cellular model. Moreover, chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR) was performed to evaluate the occupancy of TET2 across the investigated regions of NF-κB and SOD2 promoters. Results: Seven days of high glucose treatment induced a significant demethylation in the promoter regions of NF-kB and SOD2 with a consequently high level in mRNA expression of both genes. The observed DNA demethylation was mediated by increased TET2 expression and binding to the CpGs island in promoter regions of analyzed genes. Indeed, empagliflozin prevented the HG-induced demethylation changes by reducing TET2 binding to the investigated promoter region and counteracts the altered gene expression. The transient SGLT2 gene silencing prevents the DNA demethylation observed in promoter regions, thus suggesting a role of SGLT2 as a potential target of the anti-inflammatory and anti-oxidant effect of empagliflozin in cardiomyocytes. Conclusions: In conclusion, our results demonstrated that empagliflozin, mainly acting on SGLT2, prevented DNA methylation changes induced by high glucose and provided evidence of a new mechanism by which SGLT2i can exert cardio-beneficial effects.

BackgroundmiRNA-21 is a micro-RNA widely studied for its implications in several biological functions, including apoptosis, inflammation, fibrosis, and metabolism. Interestingly, miRNA-21 is a crucial regulator of developing cardiac diseases, but its role is controversial, and it is necessary to clarify its function in pathophysiological events of diabetic cardiomyopathy. In the present study we clarified the protective role of miRNA-21 at cardiac level and evaluated the involvement of miRNA-21 in high glucose induced-acute and chronic cardiac damage. MethodsHuman ventricular cardiac myoblasts AC16, treated and not with miR-21 inhibitor, were exposed to high glucose (33 mM) for 2 and 7 days, and the expression of fibrosis, inflammation, apoptosis, oxidative stress markers were assessed using western blotting. Further, cardiac energetic metabolism was evaluated by measuring both the expression of glucose transporters and regulators of lipids using western blotting analysis and key mitochondrial function parameters (oxygen consumption rate and proton production rate) using Seahorse technology.ResultsShort-term high glucose treatment induced a significant increase in miR-21 expression (p<0.05) that was associated with an increase in hydrogen ion flux and energy potential dissipation without any change in energy production or increase in the expression of genes involved in cellular damage. The reduction of miR-21 expression levels (p<0.05), observed after long-term (7 days) high glucose treatment, induced the activation of inflammation, apoptosis pathways and compromises mitochondrial function as demonstrated by the incapacity to answer energy demand and the impairment of physiological mitochondrial function (p<0.05).ConclusionIn human cardiomyocytes, the abundance of miR-21 takes part in the first defense mechanism against cardiac insult and its cardioprotective effect depends on the time of exposure to the injury. Moreover, miRNA-21regulates mitochondrial respiration and the ability of cells to select the most appropriate substrate for ATP production in a given environment.

In this dissertation, we discuss multi-level image thresholding techniques based on information theoretic entropies. In order to apply the correlation information of neighboring pixels of an image to obtain better segmentation results, we propose several multi-level thresholding models by using Gray-Level & Local-Average histogram (GLLA) and Gray-Level & Local-Variance histogram (GLLV). Firstly, a RGB color image thresholding model based on GLLA histogram and Tsallis-Havrda-Charvát entropy is discussed. We validate the multi-level thresholding criterion function by using mathematical induction. For each component image, we assign the mean value from each thresholded class to obtain three segmented component images independently. Then we obtain the segmented color image by combining the three segmented component images. Secondly, we use the GLLV histogram to propose three novel entropic multilevel thresholding models based on Shannon entropy, Rényi entropy and Tsallis-Havrda-Charvát entropy respectively. Then we apply these models on the three components of a RGB color image to complete the RGB color image segmentation. An entropic thresholding model is mostly about searching for the optimal threshold values by maximizing or minimizing a criterion function. We apply particle swarm optimization (PSO) algorithm to search the optimal threshold values vi for all the models. We conduct the experiments extensively on The Berkeley Segmentation Dataset and Benchmark (BSDS300) and calculate the average four performance indices (Probability Rand Index, P RI, Global Consistency Error, GCE, Variation of Information, V OI and Boundary Displacement Error, BDE) to show the effectiveness and reasonability of the proposed models. vii TABLE OF CONTENTS