Hypoxia-induced epigenetic modifications are associated with cardiac tissue fibrosis and the development of a myofibroblast-like phenotype

Ischemia caused by coronary artery disease and myocardial infarction leads to aberrant ventricular remodeling and cardiac fibrosis. This occurs partly through accumulation of gene expression changes in resident fibroblasts, resulting in an overactive fibrotic phenotype. Long-term adaptation to a hypoxic insult is likely to require significant modification of chromatin structure in order to maintain the fibrotic phenotype. Epigenetic changes may play an important role in modulating hypoxia-induced fibrosis within the heart. Therefore, the aim of the study was to investigate the potential pro-fibrotic impact of hypoxia on cardiac fibroblasts and determine whether alterations in DNA methylation could play a role in this process. This study found that within human cardiac tissue, the degree of hypoxia was associated with increased expression of collagen 1 and alpha-smooth muscle actin (ASMA). In addition, human cardiac fibroblast cells exposed to prolonged 1% hypoxia resulted in a pro-fibrotic state. These hypoxia-induced pro-fibrotic changes were associated with global DNA hypermethylation and increased expression of the DNA methyltransferase (DNMT) enzymes DNMT1 and DNMT3B. Expression of these methylating enzymes was shown to be regulated by hypoxia-inducible factor (HIF)-1α. Using siRNA to block DNMT3B expression significantly reduced collagen 1 and ASMA expression. In addition, application of the DNMT inhibitor 5-aza-2'-deoxycytidine suppressed the pro-fibrotic effects of TGFβ. Epigenetic modifications and changes in the epigenetic machinery identified in cardiac fibroblasts during prolonged hypoxia may contribute to the pro-fibrotic nature of the ischemic milieu. Targeting up-regulated expression of DNMTs in ischemic heart disease may prove to be a valuable therapeutic approach.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

Work Extraction and Energy Storage in the Dicke Model

We study work extraction from the Dicke model achieved using simple unitary cyclic transformations keeping into account both a non optimal unitary protocol, and the energetic cost of creating the initial state. By analyzing the role of entanglement, we find that highly entangled states can be inefficient for energy storage when considering the energetic cost of creating the state. Such surprising result holds notwithstanding the fact that the criticality of the model at hand can sensibly improve the extraction of work. While showing the advantages of using a many-body system for work extraction, our results demonstrate that entanglement is not necessarily advantageous for energy storage purposes, when non optimal processes are considered. Our work shows the importance of better understanding the complex interconnections between non-equilibrium thermodynamics of quantum systems and correlations among their subparts.