Case-control study of apoE gene polymorphism in young CHD patients and controls in the Serbian population

Apolipoprotein E displays polymorphism with three common alleles, e2, e3, and e4. The aim of this research was to determine apoE gene polymorphism in a group of healthy patients and a group of patients with CHD, and to reveal the relation between anthropometric and biochemical parameters and the apoE genotype. In CHD group significantly higher values of blood pressure, waist circumference, BMI and fat %, triglycerides, insulin (HOMA IR) and CRP were found. A statistically significant higher presence of the e3e4 genotype and e4 allele was detected in the CHD group. Statistically significant differences between waist circumference, BMI, insulin and HOMA IR were found between subjects with e3e3 and e3e4 genotypes

Aplication of nonlinear methods in analysis of EEG theta rhythm changes during auditory short-term memory formation in human.

Kratkoročna auditivna memorija (KAM) predstavlja kratkotrajno zadržavanje auditivno primljenih informacija u memoriji. Kratkoročna memorija, iako zaseban sistem, nije u potpunosti nezavisna od dugoročne memorija. Memorija se ne nalazi na jednom području u mozgu, već obuhvata široko - distribuiranu mrežu koja se sastoji, uglavnom, od mreža koje formiraju prefrontalni, temporalni i parijetalni regioni i njihove interakcije sa subkortikalnim regijama limbičkog sistema. Prethodna istraživanja promena EEG-a tokom formiranja KAM naglašavaju značaj aktivnosti teta ritma. Postoje brojna istraživanja EEG pokazatelja (korelata) formiranja KAM kod ljudi. Međutim, skoro da nema studija koje su primenjivale nelinearne metode za kvantifikaciju promena kompleksnosti EEG signala u procesu formiranja KAM. U ovoj studiji primenjene su nelinearne metode – fraktalna dimenzija (FD), fraktalna dimenzija u okviru pokretnog prozora (prozorska fraktalna dimenzija – pFD) i entropija uzorka (SampEn) – za kvantifikaciju promena EEG signala tokom procesa formiranja KAM. Analiziran je period zadržavanja stimulusa u kratkoročnoj memoriji (eng. „retention period“– retencija) u klasičnoj Sternbergovoj paradigmi za tri nivoa memorijskog opterećenja (MO) – tri, pet i sedam stimulusa. Rezultati primene nelinearnih metoda su upoređeni sa linearnim metodama – spektralna snaga, koherenca i analiza izvora EEG signala (analiza dipola). Primenom nelinearnih metoda utvrđeno je da pri formiranju KAM za stimuluse sa značenjem (reči) dolazi do promene kompleksnosti EEG signala u posteriornim regionima korteksa a anteriornim tokom formiranja KAM za stimuluse bez značenja (nereči). Primena FD i SampEn omogućila je detekciju promena stepena MO. Po prvi put je pokazano da sa povećanjem MO dolazi do linearnog povećanja ili smanjenja vrednosti FD i SampEn EEG signala. pFD analizom utvrđeno je da tokom formiranja KAM za reči dolazi do maksimuma kompleksnosti EEG signala u intervalu od 600-800 ms perioda retencije. Pri formiranju KAM za nereči maksimum kompleksnosti se javlja ranije u odnosu na reči, u intervalu od 200-600ms sa cikličnim ponavljanjem porasta i smanjenja kompleksnosti do kraja perioda retencije...Short-term auditory memory (STAM) is a short-term retention of auditory received information in memory. Short-term memory, although a separate system, is not entirely independent of long-term memory. Memory is not located in one area of the brain, but also includes a wide - distributed network consisting mainly of networks that form the frontal, temporal and parietal regions and their interaction with subcortical regions of the limbic system. Previous studies of changes in the EEG during the formation of STAM emphasize the importance of theta rhytm activities. There are numerous studies of EEG correlates of STAM forming in humans. However, there are almost no studies that have applied non-linear method for quantification of changes in the complexity of the EEG signal during formation of STAM. In this study, we applied the non-linear methods – fractal dimension (FD), fractal dimension with moving window (wFD), and sample entropy (SampEn) – to quantify the changes in the EEG signal complexity during formation of STAM. We analyzed the period of retention in the classic Sternberg’s paradigm for three levels of memory load (ML) - three, five, and seven stimuli. Results of nonlinear methods were compared with linear methods - spectral power, coherence and analysis of the sources of EEG signals (analysis of the dipoles). During formation of the STAM for stimuli with meaning (words) there is a change in the complexity of EEG signal in the posterior regions of the cortex, and the anterior during the formation of the STAM for the stimuli without meaning (nonwords). Application of FD and SampEn has enabled the detection of changes in the level of ML. For the first time it is shown that with increasing ML comes a linear increase (decrease), respectively, in the value of the FD and SampEn. Window fractal analysis showed that during the formation of STAM for words, there is a maximum of complexity in the range of 600-800 ms during retention period. In forming STAM for nonwords, maximum of complexity occurs earlier than for words, in the range of 200-600ms with cyclic repetition of the complexity increase and decrease towards the end of the retention period..

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

The Functional Renormalization Group and O(4) scaling

The critical behavior of the chiral quark-meson model is studied within the Functional Renormalization Group (FRG). We derive the flow equation for the scale dependent thermodynamic potential at finite temperature and density in the presence of a symmetry-breaking external field. Within this scheme, the critical scaling behavior of the order parameter, its transverse and longitudinal susceptibilities as well as the correlation lengths near the chiral phase transition are computed. We focus on the scaling properties of these observables at non-vanishing external field when approaching the critical point from the symmetric as well as from the broken phase. We confront our numerical results with the Widom-Griffiths form of the magnetic equation of state, obtained by a systematic epsilon-expansion of the scaling function. Our results for the critical exponents are consistent with those recently computed within Lattice Monte-Carlo studies of the O(4) spin system.Comment: 14 pages, 11 figure

Aplication of nonlinear methods in analysis of EEG theta rhythm changes during auditory short-term memory formation in human.

Kratkoročna auditivna memorija (KAM) predstavlja kratkotrajno zadržavanje auditivno primljenih informacija u memoriji. Kratkoročna memorija, iako zaseban sistem, nije u potpunosti nezavisna od dugoročne memorija. Memorija se ne nalazi na jednom području u mozgu, već obuhvata široko - distribuiranu mrežu koja se sastoji, uglavnom, od mreža koje formiraju prefrontalni, temporalni i parijetalni regioni i njihove interakcije sa subkortikalnim regijama limbičkog sistema. Prethodna istraživanja promena EEG-a tokom formiranja KAM naglašavaju značaj aktivnosti teta ritma. Postoje brojna istraživanja EEG pokazatelja (korelata) formiranja KAM kod ljudi. Međutim, skoro da nema studija koje su primenjivale nelinearne metode za kvantifikaciju promena kompleksnosti EEG signala u procesu formiranja KAM. U ovoj studiji primenjene su nelinearne metode – fraktalna dimenzija (FD), fraktalna dimenzija u okviru pokretnog prozora (prozorska fraktalna dimenzija – pFD) i entropija uzorka (SampEn) – za kvantifikaciju promena EEG signala tokom procesa formiranja KAM. Analiziran je period zadržavanja stimulusa u kratkoročnoj memoriji (eng. „retention period“– retencija) u klasičnoj Sternbergovoj paradigmi za tri nivoa memorijskog opterećenja (MO) – tri, pet i sedam stimulusa. Rezultati primene nelinearnih metoda su upoređeni sa linearnim metodama – spektralna snaga, koherenca i analiza izvora EEG signala (analiza dipola). Primenom nelinearnih metoda utvrđeno je da pri formiranju KAM za stimuluse sa značenjem (reči) dolazi do promene kompleksnosti EEG signala u posteriornim regionima korteksa a anteriornim tokom formiranja KAM za stimuluse bez značenja (nereči). Primena FD i SampEn omogućila je detekciju promena stepena MO. Po prvi put je pokazano da sa povećanjem MO dolazi do linearnog povećanja ili smanjenja vrednosti FD i SampEn EEG signala. pFD analizom utvrđeno je da tokom formiranja KAM za reči dolazi do maksimuma kompleksnosti EEG signala u intervalu od 600-800 ms perioda retencije. Pri formiranju KAM za nereči maksimum kompleksnosti se javlja ranije u odnosu na reči, u intervalu od 200-600ms sa cikličnim ponavljanjem porasta i smanjenja kompleksnosti do kraja perioda retencije...Short-term auditory memory (STAM) is a short-term retention of auditory received information in memory. Short-term memory, although a separate system, is not entirely independent of long-term memory. Memory is not located in one area of the brain, but also includes a wide - distributed network consisting mainly of networks that form the frontal, temporal and parietal regions and their interaction with subcortical regions of the limbic system. Previous studies of changes in the EEG during the formation of STAM emphasize the importance of theta rhytm activities. There are numerous studies of EEG correlates of STAM forming in humans. However, there are almost no studies that have applied non-linear method for quantification of changes in the complexity of the EEG signal during formation of STAM. In this study, we applied the non-linear methods – fractal dimension (FD), fractal dimension with moving window (wFD), and sample entropy (SampEn) – to quantify the changes in the EEG signal complexity during formation of STAM. We analyzed the period of retention in the classic Sternberg’s paradigm for three levels of memory load (ML) - three, five, and seven stimuli. Results of nonlinear methods were compared with linear methods - spectral power, coherence and analysis of the sources of EEG signals (analysis of the dipoles). During formation of the STAM for stimuli with meaning (words) there is a change in the complexity of EEG signal in the posterior regions of the cortex, and the anterior during the formation of the STAM for the stimuli without meaning (nonwords). Application of FD and SampEn has enabled the detection of changes in the level of ML. For the first time it is shown that with increasing ML comes a linear increase (decrease), respectively, in the value of the FD and SampEn. Window fractal analysis showed that during the formation of STAM for words, there is a maximum of complexity in the range of 600-800 ms during retention period. In forming STAM for nonwords, maximum of complexity occurs earlier than for words, in the range of 200-600ms with cyclic repetition of the complexity increase and decrease towards the end of the retention period..