The relationships among monocyte subsets,miRNAs and inflammatory cytokines in patients with acute myocardial infarction

Background

Acute myocardial infarction (AMI) causes irreversible myocardial damage and release of inflammatory mediators, including cytokines, chemokines and miRNAs. We aimed to investigate changes in the levels of cytokines (IL-6, TNF-α and IL-10), miRNAs profiles (miR-146 and miR-155) and distribution of different monocyte subsets (CD14++CD16-, CD14++CD16+, CD14+CD16++) in the acute and post-healing phases of AMI.

Transport mechanism of L-[14C]glutamate in cortical slices and synaptosomes of rabbits exposed to brain ischemia and reperfusion

Molecular and chemical neuropathology - Changes in the functioning of the glutamatergic system in rabbit brain were studied after partial brain ischemia and reperfusion. In vitro studies were...     

In vivo effect of prothymosin-alpha 1 on humoral and cell-mediated immune responses in the young rat.

There is a large body of evidence for the role of thymosin peptides in immunogenesis and immunity. In this paper we report on the influence of prothymosin alpha 1 (ProT-alpha 1), a hormone-like peptide derived from the calf thymus, on humoral and cellular immune reactions in the rat. Young adults received intraperitoneal injections of ProT-alpha 1 in the periods before and after immunization with cellular and soluble antigens. ProT-alpha-treatment produced a dose-dependent increase of both humoral and cell-mediated immune responses. The thymus weight increased but not that of spleen. Treatment of nonimmunized rats with this polypeptide significantly elevated the number of CD4+ and decreased the number of CD8+ cells in the peripheral blood. The results suggest a potent immunostimulatory activity of ProT-alpha 1 and imply direct action of this polypeptide on T lymphocytes.     

Decision trees based on automatic learning and their use in cardiology

Computerized information systems, especially decision support systems, have become an increasingly important role in medical applications, particularly in those where important decision must be made effectively and reliably. But the possibility of using computers in medical decision making is limited by many difficulties, including the complexity of conventional computer languages, methodologies and tools. Thus a conceptual simple decision making model with the possibility of automating learning should be used. In this paper we introduce a cardiological knowledge-based system based on the decision tree approach supporting the mitral valve prolapse determination. Prolapse is defined as the displacement of a bodily part from its normal position. The term mitral valve prolaps (PMV), therefore, implies that the mitral leaflets are displaced relative to some structure, generally taken to be the mitral annulus. The implications of the PMV are the following: disturbed normal laminar blood flow, turbulence of the blood flow, injury of the chordae tendinae, the possibility of thrombus's composition, bacterial endocarditis, and finally hemodynamic changes defined as mitral insufficiency and mitral regurgitation. Uncertainty persists about how it should be diagnosed and about its clinical importance. It is our deep belief that the echocardiography enables properly trained experts armed with proper criteria to evaluate PMV almost 100%. But unfortunately, there are some problems concerned with the use of echocardiography. In that manner we have decided to start a research project aimed at finding new criteria and enabling the general practitioner to evaluate PMV using conventional methods and to select potential patients from the general population. To empower one to perform needed activities we have developed a computer tool called ROSE (computeRised prOlaps Syndrom dEtermination) based on algorithms of automatic learning. This tool supports the definition of new criteria and the selection of potential PMV-patients.