ACE-inhibition induces a cardioprotective transcriptional response in the metabolic syndrome heart
Cardiovascular disease associated with metabolic syndrome has a high prevalence, but the mechanistic basis of metabolic cardiomyopathy remains poorly understood. We characterised the cardiac transcriptome in a murine metabolic syndrome (MetS) model (LDLR−/−; ob/ob, DKO) relative to the healthy, control heart (C57BL/6, WT) and the transcriptional changes induced by ACE-inhibition in those hearts. RNA-Seq, differential gene expression and transcription factor analysis identified 288 genes differentially expressed between DKO and WT hearts implicating 72 pathways. Hallmarks of metabolic cardiomyopathy were increased activity in integrin-linked kinase signalling, Rho signalling, dendritic cell maturation, production of nitric oxide and reactive oxygen species in macrophages, atherosclerosis, LXR-RXR signalling, cardiac hypertrophy, and acute phase response pathways. ACE-inhibition had a limited effect on gene expression in WT (55 genes, 23 pathways), and a prominent effect in DKO hearts (1143 genes, 104 pathways). In DKO hearts, ACE-I appears to counteract some of the MetS-specific pathways, while also activating cardioprotective mechanisms. We conclude that MetS and control murine hearts have unique transcriptional profiles and exhibit a partially specific transcriptional response to ACE-inhibition.
The mass application of mobile cardiographs already leads to both explosive quantitative growth of the number of patients available for ECG study, registered daily outside the hospital (Big DATA in cardiology), and to the emergence of new qualitative opportunities for the study of long-term oscillatory processes (weeks, months, years) of the dynamics of the individual state of the Cardiovascular system of any patient.
The article demonstrates that new opportunities of long - term continuous monitoring of the Cardiov ascular system state of patients ' mass allow to reveal the regularities (DATA MINING) of Cardiovascular system dynamics, leading to the hypothesis of the existence of an adequate Cardiovascular system model as a distributed nonlinearself - oscillating system of the FPU recurrence model class . The presence of a meaningful mathematical model of Cardiovascular system within the framework of the FPU auto – recurrence , as a refinement of the traditional model of studying black box, further allows us to offer new computational methods for ECG analysis and prediction of Cardiovascular system dynamics for a refined diagnosis and evaluation of the effectiveness of the treatment.
According to the results of epidemiological studies of prevalence of erectile dysfunction in the Russian Federation, the search for the determinants of risk of its development was performed. It was found that the leading risk factors for the development of erectile dysfunction, in descending order of statistical significance, include the amount of accumulation of points according to the IPSS score, arterial hypertension, LIPSS quality of life index, age, diabetes, and overweight and obesity.
This paper drew extensively on the research under the Basic Research Program at the National Research University Higher School of Economics. The authors appreciate having been able to use the results of the research done together with Shishkin S., Director of the Center for Health Policy of HSE. The authors are grateful for valuable peer review comments provided by Dorota Nowak, Owen Smith and Somil Nagpal. This paper was produced under the overall guidance of Daniel Cotlear, Enis Baris and Andras Horvai.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The Handbook of CO₂ in Power Systems' objective is to include the state-of-the-art developments that occurred in power systems taking CO₂ emission into account. The book includes power systems operation modeling with CO₂ emissions considerations, CO₂ market mechanism modeling, CO₂ regulation policy modeling, carbon price forecasting, and carbon capture modeling. For each of the subjects, at least one article authored by a world specialist on the specific domain is included.