Simulation of Brugada syndrome using cellular and three-dimensional whole-heart modeling approaches

Brugada syndrome (BS) is a genetic disease identified by an abnormal electrocardiogram ( ECG) ( mainly abnormal ECGs associated with right bundle branch block and ST-elevation in right precordial leads). BS can lead to increased risk of sudden cardiac death. Experimental studies on human ventricular myocardium with BS have been limited due to difficulties in obtaining data. Thus, the use of computer simulation is an important alternative. Most previous BS simulations were based on animal heart cell models. However, due to species differences, the use of human heart cell models, especially a model with three-dimensional whole-heart anatomical structure, is needed. In this study, we developed a model of the human ventricular action potential (AP) based on refining the ten Tusscher et al (2004 Am. J. Physiol. Heart Circ. Physiol. 286 H1573 - 89) model to incorporate newly available experimental data of some major ionic currents of human ventricular myocytes. These modified channels include the L-type calcium current (ICaL), fast sodium current (I-Na), transient outward potassium current (I-to), rapidly and slowly delayed rectifier potassium currents (I-Kr and I-Ks) and inward rectifier potassium current (I-Ki). Transmural heterogeneity of APs for epicardial, endocardial and mid-myocardial (M) cells was simulated by varying the maximum conductance of IKs and Ito. The modified AP models were then used to simulate the effects of BS on cellular AP and body surface potentials using a three-dimensional dynamic heart - torso model. Our main findings are as follows. (1) BS has little effect on the AP of endocardial or mid-myocardial cells, but has a large impact on the AP of epicardial cells. (2) A likely region of BS with abnormal cell AP is near the right ventricular outflow track, and the resulting ST-segment elevation is located in the median precordium area. These simulation results are consistent with experimental findings reported in the literature. The model can reproduce a variety of electrophysiological behaviors and provides a good basis for understanding the genesis of abnormal ECG under the condition of BS disease.

Using urea dilution to standardise cellular and non-cellular components of pleural and bronchoalveolar lavage (BAL) fluids in the cat

A technique to standardise the analysis of cellular and non-cellular components in epithelial lining fluid (ELF) collected during saline lavage of pulmonary and pleural cavities was developed using the urea dilution method. Bronchoalveolar lavage (BAL) and pleural lavage (PL) fluids were collected from 12 clinically healthy cats. Total and differential cell counts in BAL fluid were within normal ranges for the cat, while cell Counts in PL fluid were assumed to be normal based on clinical health during examination, auscultation and lactate dehydrogenase (LDH) activities being comparable with other species. The major clinical implication of this study was that nucleated cell counts within feline ELF could not be predicted from analysis of lavage fluid which suggests that calculation of the proportion of ELF in lavage fluid by the urea dilution method may be necessary to avoid misdiagnosis of health or disease in pulmonary or pleural cavities. (C) 2005 ESFM and AAFP. Published by Elsevier Ltd. All rights reserved.

Inorganic nanoparticles as carriers for efficient cellular delivery

Cellular delivery involving the transfer of various drugs and bio-active molecules (peptides, proteins and DNAs, etc.) through the cell membrane into cells has attracted increasing attention because of its importance in medicine and drug delivery. This topic has been extensively reviewed. The direct delivery of drugs and biomolecules, however, is generally inefficient and suffering from problems such as enzymic degradation of DNAs. Therefore, searching for efficient and safe transport vehicles (carriers) to delivery genes or drugs into cells has been challenging yet exciting area of research. In past decades, many carriers have been developed and investigated extensively which can be generally classified into four major groups: viral carriers, organic cationic compounds, recombinant protiens and inorganic nanoparticles. Many inorganic materials, such as calcium phosphate, gold, carbon materials, silicon oxide, iron oxide and layered double hydroxide (LDH), have been studied. Inorganic nanoparticles show low toxicity and promise for controlled delivery properties, thus presenting a new alternative to viral carriers and cationic carriers. Inorganic nanoparticles generally possess versatile properties suitable for cellular delivery, including wide availability, rich functionality, good biocompatibility, potential capability of targeted delivery (e.g. selectively destroying cancer cells but sparing normal tissues) and controlled release of carried drugs. This paper reviews the latest advances in inorganic nanoparticle applications as cellular delivery carriers and highlights some key issues in efficient cellular delivery using inorganic nanoparticles. Critical proper-ties of inorganic nanoparticles, surface functionalisation (modification), uptake of biomolecules, the driving forces for delivery, and release of biomolecules will be reviewed systematically. Selected examples of promising inorganic nanoparticle delivery systems, including gold, fullerences and carbon nanotubes, LDH and various oxide nanoparticles in particular their applications for gene delivery will be discussed. The fundamental understanding of properties of inorganic nanoparticles in relation to cellular delivery efficiency as the most paramount issue will be highlighted. (c) 2005 Elsevier Ltd. All rights reserved.

Recurrence interval statistics of cellular automaton seismicity models

The recurrence interval statistics for regional seismicity follows a universal distribution function, independent of the tectonic setting or average rate of activity (Corral, 2004). The universal function is a modified gamma distribution with power-law scaling of recurrence intervals shorter than the average rate of activity and exponential decay for larger intervals. We employ the method of Corral (2004) to examine the recurrence statistics of a range of cellular automaton earthquake models. The majority of models has an exponential distribution of recurrence intervals, the same as that of a Poisson process. One model, the Olami-Feder-Christensen automaton, has recurrence statistics consistent with regional seismicity for a certain range of the conservation parameter of that model. For conservation parameters in this range, the event size statistics are also consistent with regional seismicity. Models whose dynamics are dominated by characteristic earthquakes do not appear to display universality of recurrence statistics.

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

Combining influence maps and cellular automata for reactive game agents

Agents make up an important part of game worlds, ranging from the characters and monsters that live in the world to the armies that the player controls. Despite their importance, agents in current games rarely display an awareness of their environment or react appropriately, which severely detracts from the believability of the game. Some games have included agents with a basic awareness of other agents, but they are still unaware of important game events or environmental conditions. This paper presents an agent design we have developed, which combines cellular automata for environmental modeling with influence maps for agent decision-making. The agents were implemented into a 3D game environment we have developed, the EmerGEnT system, and tuned through three experiments. The result is simple, flexible game agents that are able to respond to natural phenomena (e.g. rain or fire), while pursuing a goal.