فصلنامه مهندسی پزشکی زیستی
سال پنجم شماره 3 (پاییز 1390)

In this paper, two models are introduced based on cellular automata and the game theory to study behavior, growth, development and morphology of cancerous cells by assuming nutrition supplies, extracellular matrix, and immune cells. A two-dimensional cellular automaton combine with game theory is considered as the structure of model. The cellular automata modeling framework can be an efficient approach to a number of biological problems; and game theory aims to help us to understand situations in which decision-makers interact such as competitive activity. In the first model, we consider different oxygen supplies to study the growth and invasion of cancerous cell. The results of our simulation are validated by the results of other articles. The results show that the number of cancerous cells is easily changed by changing amount of oxygen supplies, but invasive distance of tumor cells is not easily affected by this factor. Furthermore the results of this model are not linear, that could show the improvement of the model. In addition, this model has the ability of producing metastasis, as it is shown. In the second model, the interaction between immune cells and cancerous cells are considered. Two-dimensional cellular automata and game theory are used for this purpose. In this model the behavior of cellular automata is determined by the game theory. The rules of cellular automata are determined by game theory table, so each element of the system could make a decision separately.

In recent years, nanoparticles have attracted considerable attention due to their special optical, chemical, and electrical properties. Developments of nanoparticles synthesis methods for producing materials with precise size and morphology have been considered recently. Among these methods, biosynthesis has a special position for its high compatibility with environment. The use of microorganism in nanotechnology is one of the important aspects of this issue. In this survey we have used Escherichia coli 35218 to Cadmium Sulfide nanoparticles synthesis. First, appropriate time of cadmium ions addition and their maximum concentrations were determined that they don􀂶t inhibit bacterial growth. Then we studied intra and extracellular biosynthesis. According to this survey, this strain wasn't able to produce cadmium sulfide nanoparticles intracellulary but also these nanoparticles were extracellulary synthesized in the medium supplemented with L-cysteine. Formation of CdS nanoparticles, their morphologies and fluorescence properties were determined with WDX, SEM and fluorescence microscopy.

Using microwave irradiation in microwave-assisted synthesis method is a new approach employed to decrease synthesis time and to form more homogenous structures of biphasic calcium phosphate bioceramics. In this research, the microwave assisted synthesis and characterization of biphasic calcium phosphate nanopowders have been studied. The phase transformation, chemical components, morphology and particle size were characterized by X-Ray Diffraction (XRD) analysis, Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). The results showed that the use of microwave led to improve crystallinity and the crystallite size increases from 16 nm to 27 nm. Also the amount of hydroxyapatite phase in biphasic calcium phosphate changed in the range of 5% to 17%. The prepared sample was put in Simulated Body Fluid (SBF).The pH of the solution was decreased in the present of beta-tricalcium phosphate showed its biodegradable behavior. Also the nucleation and growth of hydroxyapatite particles on TCP produced by microwave -assisted synthesis method changed to be rod like in SBF solution.

One of main the issues in achieving to a successful FES control is using an as much as possible accurate model of the under electrical stimulation system so that it can adequately indicate the system behavior. Classical computational models that are commonly used for this purpose have a reductionism nature; so they cannot consider the interaction existed in biological systems. Considering these restrictions, recently behavioral black box models are mostly used. These models focus on input/output dynamic, which is certainly the necessary modeling information for control design; thus the system is dealt with as a whole, which has hidden the interactions between components inside. Such a model has notbeen presented for elbow angle movement so far. Therefore in this study, we have been to present and verify a black box model of elbow joint movement in the transverse plane, forreaching movement control in people with C5/C6 SCI using dynamic neural networks, including time-delayed feedforward and recurrent networks. Extreme flexibility of time-delayed feedforward architectures was obtainedin a 2 layer structure including 5 hidden neurons and using 1.25s of history of input with performance indexes of 89.89% & 4.85% for cross correlation coefficient and normalized mean square error respectively. The best recurrent network with NARX architecture and equal history of input & output was also occurred in a 2 layer structure having 12 neurons in the hidden layer and using 0.1s of history, with performance indexes of 89.89% & 4.85% for cross correlation coefficient and normalized mean square error respectively. Comparison between best results of training using feedforward and recurrent networks, clearly illustrates both qualitative and quantitative excellency of the latter one in identification of the under-study system.

Reliable gradation of neonatal brain development is important for clinical investigation of neurological disorders. A prerequisite for such quantification of development is knowledge about an appropriate temporal resolvability. For this purpose, we investigated the evolution of macroscopic morphological features of the neonatal brain to estimate, for the first time, the required temporal interval in the early weeks after birth. In a first step, we constructed two neonatal templates for the age ranges of 39-40 and 41- 42 weeks' gestational age using T1-weighted MR images. We compared the spatial variation of anatomical landmarks and the average and the maximal length of spatial deformation in 25 subjects normalized to the two templates along x, y and z directions. MANOVA confirmed the significant difference between spatial variations of the above macroscopic features in the two age ranges. Furthermore, quantitative analysis of feature scattering yielded the same result even in features for which the null hypothesis was not rejected by MANOVA. We conclude that minimal temporal interval of two weeks is required for acute macroscopic morphological studies of the developing brain in the early weeks after birth.

During the last decade, functional neuromuscular stimulation (FNS) has been proposed as a potential technique for restoring motor function in paralyzed limbs. A major challenge to restoring a desired functional limb movement through the use of intramuscular stimulation is the development of a robust control strategy for determining the stimulation patterns. A major impediment to stimulating the paralyzed limbs and determining the stimulation pattern has been the highly non-linear, time-varying properties of electrically stimulated muscle, muscle fatigue, large latency and time constant which limit the utility of pre-specified stimulation pattern and open-loop FES control system. In this paper we present a robust strategy for multi-joint control through intramuscular stimulation in which the system parameters are adapted online and the controller requires no offline training phase. The method is based on the combination of sliding mode control with fuzzy logic and neural control. Extensive experiments on three rats are provided to demonstrate the robustness, stability, and tracking accuracy of the proposed method. The results show that the proposed strategy can provide accurate tracking control with fast convergence.

Selection of muscle activation pattern to reach a specific goal by considering the complexities of neuromuscular system and the way it overcomes these complications, is of researchers􀂶interest in motor control. One proposed solutionfor resolving thesecomplexities is the concept of simple module (synergies) that the combination of them leads to more complex activities. In the present work, the existence and arrangement of synergies in the lumbar spine are proved. For this purpose, a model with 18-muscles in level L4-L5 is utilized in the static condition. In order to obtaina muscular and stability synergies, muscle activation, which are obtained by exerting moments in 2D and 3D spaces and angular stiffness to the model,are used. The results show that six muscular synergies suffice to be able to reach any point in the moment space. Also, three stability synergies can reconstruct a part of joint angular stiffness space. In addition, the obtained muscular synergies are robust against changes in the amplitude of exerted moment. In this study, it is shown that one can generates any task involves producing determined moment and angular stiffness in the joint, by combining muscular and stability synergies together.