فصلنامه مهندسی پزشکی زیستی
سال یازدهم شماره 1 (بهار 1396)

In this paper, a new method is proposed for slowing down avascular tumor growth. Our method is established on an agent based avascular tumor growth model (ABM). The model is based on biological assumptions with regard to the immune system interactions. The model parameters are fitted in compatability with cancer biology using in vivo expremental data. The immune cells recruitment, which usually occur after that tumor cells are identified, are also considered in ABM model. The results show that the proposed model not only is able to simulate the tumor growth graphically, but also the in vivo tumor growth quantitatively and qualitatively. Besides, the model proposes a new idea for slowing down the tumor growth considering two types of prolaiferative tumor cells, i.e. the tumor will grow slowly if the division probability of the proliferative tumor cells depends on the microenvironmental conditions. The proposed idea has been validated using an in silico simulation.

Pedaling is one of the common physical activities for muscles strengthening. Pedaling performance is affected by various factors. The purpose of this study is investigating the effect of pedaling rate and resistance moment against pedaling in the feasible pedaling places (kinematics view) on the muscles activity and ankle, knee and hip joints forces. For this purpose, the biomechanical model of human movement system presented in AnyBody software, is used. The mechanical power of pedaling is deemed to constant (200 w). The Pedaling rate of 40, 60, 80, 100 and 120 rpm and the resistance moment of 0, 5, 10, 15 and 20 Nm, are considered in the pedaling feasible places. Results indicate that although the range of pedaling feasible places is proper by the kinematics view, however changing the pedaling rate and the applied resistance moment, all of the pedaling places from this range cannot be proper due to the excessive muscles activity (more than 0.95). In the pedaling rate of 80, 100 and 120 rpm by applying the resistance moment of 0 and 5 Nm, approximately all of the feasible places are suitable (muscles activity are less than 0.95). By increasing the pedaling rate in a constant resistance moment, the large part and reversely, by increasing the resistance moment in a constant pedaling rate, the small part of feasible range are appropriate. Joints forces increase with decreasing the pedaling rate and increasing the applied resistance moment.

Predicting AD based on Brain network analysis has been the subject of much investigation. Here, we aim to identify the changes in brain in patients that conversion from (Mild Cognitive Impariment) MCI to AD (MCI-C) and non conversion from MCI to AD (MCI-NC), to provide an algorithm for classification of these patients by using a graph theoretical approach. In this algorithm we proposed Discriminant Correlation Analysis (DCA), feature level fusion for multimodal biometric recognition method were applied to the original feature sets. An accuracy of 86/167% was achieved for predicting AD using the DCA and the support vector machine classifier. We also performed a hub node analysis and found the number of hubs in progressive AD patients. Indeed, this is the first neuroimaging study that integrates rs-fMRI with sMRI for detecting conversion from MCI to AD. The proposed classification method highlights the potential of using both resting state fMRI and MRI data for identification of the early stage of AD.

Cancer is one of the most important causes of mortality in human society; therefore, scientists are always looking for new ways to cope with the disease. Understanding more about the dynamics of cancerous tumors in body can help researches. Therefore, making simple models for tumor growth is important. Various models have been proposed for the dynamics of cancer cell growth in the body. In some models, the interaction of different types of cells in the cancerous system is mentioned. The cells in the cancerous system include tumor, healthy, and the immune system cells. Generally, the previous models based on these three cell populations couldn’t simulate chaotic behaviors, while the biology of cancer has confirmed chaos in the system. In this paper, a model of three variables is presented and it’s shown that for some values ​​of parameters the system can simulate chaotic behaviors. Model parameters are defined based on biological relationships, each of which plays a particular role in the dynamics of the system. To analyze the role of the parameters, a specific interval is assigned to each parameter, and by plotting the bifurcation diagram, behavioral changes of the system is observed. The results show that some of the parameters have less role in the system's behavior, and by adjusting some of them, free tumor system can be provided. Also, by setting other parameters, the system can lead to a malignant tumor. The parameters of the immune system equation have the least effect on the system’s dynamics. Regarding this finding, it can be said that applying a therapeutic approach that changes the parameters of the immune system will play a minor role in treatment. While applying therapies that change the parameters of healthy cells has the greatest effect on treatment.

Tissue engineering is a promising approach for developing viable alternative for current treatments of cardiovascular diseases such as autologous vessel and synthetic bypass graft transplantation. One of the major challenges in development of an applicable tissue engineered vessel is proper design of scaffold. Scaffolds are served to mimic the natural in vivo environment of cells where they interact and behave according to the mechanical cues obtained from the surrounding extracellular matrix. In recent studies alginate hydrogels containing silk fibroin protein have shown sufficient biological capability for vascular cells attachment, spreading, growth and metabolic activity. The purpose of this study was to evaluate the mechanical properties of mentioned hydrogels as scaffolds for vascular tissue engineering.  Elastic modulus of linear region, yield strain and stress and compliance of three types of Alginate based hydrogel with different synthesis procedures were obtained via uniaxial tensile test of dogbone shaped specimens and thick-wall cylinders stress-strain equations. Results were compared to find the optimal formulation and synthesis process for mimicing mechanical properties of native tissue. Results of this study shows that while the proposed formulation of alginate/fibroin hydrogel lacks required mechanical stiffness, flexibility and strength; hybrid dual-network hydrogels of alginate/fibroin/polyacrylamide with a two-steps synthesis process and cross-linked by Fe3+ and Ca2+ cations promote suitable mechanical properties to be used as vascular tissue engineering scaffolds. Adding polyacrylamide to alginate-firoin hydrogels increased its elastisity modulus from 46 kPa to 480 kPa with a two step gelation process which makes it more similar to arteries wall tissue mechanically.

Nowadays, with technological advancements and increasing computing power, the use of mathematical models to describe the functioning of the brain in normal and abnormal manners, especially the study of the formation causes and methods of controlling and treating some nervous system diseases, such as epilepsy, have become widespread and many models have been developed to simulate patterns appearing in the brain signals of these patients. One of the most commonly used types of modeling is neural mass models such as the Jansen-Rit model that those can simulate some of the essential brain patterns and rhythms that appear in the brain recorded signals. Therefore, in this paper, we have tried to provide a complete dynamical analysis of the Jansen-Rit model. To analyze this model, first, the equations of the model have been changed so that the output of the model be one of the system states variables. Then, the new equations have been nondimensionalized by defining a biological parameter (proportion of inhibition to excitation in neural populations of the model). In the following, the bifurcation diagram of the dimensionless model has been plotted with respect to nondimensional input and inhibition to excitation proportion parameters (codimension-two bifurcation) and the dynamical behavior of the system, such as bifurcations, periods and frequency of the limit cycles and time responses, have been investigated. Further, we have discussed two significant behaviors in this model, spike-and-wave discharges (SWDs) and alpha rhythms. In the present paper, we have been shown how these models can describe complex disease such as epilepsy and have been mentioned dynamical mechanism underlying transition from a normal state (background activity) to an abnormal situation (epileptic seizures). The innovations of this study one can be the definition of the new meaningful and significant biological parameter in the dimensionless model that all dynamical analysis are based on it. Also, some bifurcations and, consequently, some of the behaviors observed in the model are for the first time reported. Moreover, this new parameter contains two primary model parameters and then the effect of three parameters simultaneously in the system behavior has been investigated.

The brain stimulation and its widespread use is one of the most important subjects in studies of neurophysiology. In brain electrical stimulation methods, following the surgery and electrode implantation, electrodes send electrical impulses to the specific targets in the brain. The use of this stimulation method is provided therapeutic benefits for treatment chronic pain, essential tremor, Parkinson’s disease, major depression, and neurological movement disorder syndrome (dystonia). One area in which advancements have been recently made is in controlling the movement and navigation of animals in a specific pathway. It is important to identify brain targets in order to stimulate appropriate brain regions for all the applications listed above. An animal navigation system based on brain electrical stimulation is used to develop new behavioral models for the aim of creating a platform for interacting with the animal nervous system in the spatial learning task. In the context of animal navigation the electrical stimulation has been used either as creating virtual sensation for movement guidance or virtual reward for movement motivation. In this paper, different approaches and techniques of brain electrical stimulation for this application has been reviewed.