The aim of this study was to check if serum interleukin-18 (IL-18) predicts 2-year cardiovascular mortality in patients at various stages of chronic kidney disease (CKD) and history of acute myocardial infarction (AMI) within the previous year. Diabetes mellitus was one of the key factors of exclusion. It was found that an increase in serum concentration of IL-18 above the cut-off point (1584.5 pg/mL) was characterized by 20.63-fold higher risk of cardiovascular deaths among studied patients. IL-18 serum concentration was found to be superior to the well-known cardiovascular risk parameters, like high sensitivity C-reactive protein (hsCRP), carotid intima media thickness (CIMT), glomerular filtration rate, albumins, ferritin, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in prognosis of cardiovascular mortality. The best predictive for IL-18 were 4 variables, such as CIMT, NT-proBNP, albumins and hsCRP, as they predicted its concentration at 89.5%. Concluding, IL-18 seems to be important indicator and predictor of cardiovascular death in two-year follow-up among non-diabetic patients suffering from CKD, with history of AMI in the previous year. The importance of IL-18 in the process of atherosclerotic plaque formation has been confirmed by systems analysis based on a formal model expressed in the language of Petri nets theory.
Systems biology approach to investigate biological phenomena seems to be very promising because it is capable to capture one of the fundamental properties of living organisms, i.e. their inherent complexity. It allows for analysis biological entities as complex systems of interacting objects. The first and necessary step of such an analysis is building a precise model of the studied biological system. This model is expressed in the language of some branch of mathematics, as for example, differential equations. During the last two decades the theory of Petri nets has appeared to be very well suited for building models of biological systems. The structure of these nets reflects the structure of interacting biological molecules and processes. Moreover, on one hand, Petri nets have intuitive graphical representation being very helpful in understanding the structure of the system and on the other hand, there is a lot of mathematical methods and software tools supporting an analysis of the properties of the nets. In this paper a Petri net based model of the hemojuvelin-hepcidin axis involved in the maintenance of the human body iron homeostasis is presented. The analysis based mainly on T-invariants of the model properties has been made and some biological conclusions have been drawn.
Full-size ATP-binding cassette (ABC) transporters belonging to the ABCG subfamily are unique for plants and fungi. There is growing evidence that certain of these proteins play a role in plant defense or signaling systems. As yet, a complete set of full-size ABCG protein genes has been inventoried and classified in only two plants: Arabidopsis thaliana and Oryza sativa. Recently, a domain-based clustering analysis has predicted the presence of at least 12 genes encoding such proteins in the Lotus japonicus genome. Here, we identify and classify 19 genes coding full-size ABCG proteins in Medicago truncatula, a model legume plant. We have found that the majority of these genes are expressed in roots and flowers whereas only a few are expressed in leaves. Expression of several has been induced upon pathogenic infection in both roots and leaves. ABCG messenger RNAs have been detected in root nodules forming during symbiosis of legume plants and nitrogen-fixing bacteria. The data presented provide a scaffold for further studies of the physiological function of Medicago ABCG transporters and their possible role in modulating plant-microorganism interactions.
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