Sadegh Marzban | Univsersity of Szeged (original) (raw)
Papers by Sadegh Marzban
Cancer research, Mar 22, 2024
Lenia, a cellular automata framework used in artificial life, provides a natural setting to desig... more Lenia, a cellular automata framework used in artificial life, provides a natural setting to design, implement, and analyze mathematical models of cancer progression and treatment. Lenia's suitability as a cancer model is derived from the strong parallels between artificial life and cancer evolution: morphogenesis, homeostasis, motility, reproduction, growth, stimuli response, evolvability, and adaptation. Historically, agent-based models of cancer progression have been constructed with rules that govern birth, death and migration based on local availability for space, with attempts to map local rules to emergent global growth dynamics. Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining an interaction kernel governing density-dependent growth dynamics. First, we show Lenia can recapitulate a range of cancer model classifications including local or global, deterministic or stochastic, non-spatial or spatial, single or multi-population, and off or on-lattice. Lenia is subsequently used to develop data-informed models of 1) single-population growth dynamics, 2) multi-population cell-cell competition models, and 3) cell migration or chemotaxis.
Journal of Electrical Bioimpedance, 2018
Computational dosimetry has become the main tool for estimating induced electric fields within br... more Computational dosimetry has become the main tool for estimating induced electric fields within brain tissues in transcranial direct current stimulation (tDCS) which is recently attracting the attention of researches for motor function disturbances such as Parkinson’s disease. This paper investigates the effect of including or excluding the very thin meninges in computing tDCS electric fields using CST software. For this purpose, two models of the brain with and without meninges were used to induce electric field with two DC current electrodes (2 mA) in regions of the model referring to M1 and Prefrontal Cortex (FP2) similar to tDCS. Considering meninges, the results have shown differences in the induced field showing that there might be problems with conventional models in which meninges are not taken into account.
This PhD thesis presents three new mathematical models aimed at advancing the current understandi... more This PhD thesis presents three new mathematical models aimed at advancing the current understanding of viral dynamics and cancer. The models are implemented in the HAL system and are applied to address current significant questions in the field. The first model, described in Chapter 3, is focused on the evolution of sensitive and resistant tumor cells and considers Darwinian selection, Lamarckian induction, and microvesicle transfer as mechanisms for resistance. The model is compared to an agent-based model and provides insight into the impact of microvesicles on the spread of cancer cells. Chapter 4 presents a hybrid partial differential equation - agent-based (PDE-ABM) model to describe the spatiotemporal viral dynamics in a cell population. The virus concentration is modeled as a continuous variable, while changes in the states of cells are represented by a stochastic agent-based model. The two subsystems are intertwined and the model is applied to predict SARS-CoV-2 and influenz...
World Academy of Science, Engineering and Technology, International Journal of Medical and Health Sciences, 2017
Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the ... more Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the treatment. Due to chemotherapeutic agents, resistance can emerge by Darwinian evolution. Besides this, acquired drug resistance may arise via changes in gene expression. A recent discovery in cancer research uncovered a third possibility, indicating that this phenotype conversion can occur through the transfer of microvesicles from resistant to sensitive cells, a mechanism resembling the spread of an infectious agent. We present a model describing the evolution of sensitive and resistant tumour cells considering Darwinian selection, Lamarckian induction and microvesicle transfer. We identify three threshold parameters which determine the existence and stability of the three possible equilibria. Using a simple Dulac function, we give a complete description of the dynamics of the model depending on the three threshold parameters. We demonstrate the possible effects of increasing drug conce...
Paxlovid is a promising, orally bioavailable novel drug for SARS--CoV--2 with excellent safety pr... more Paxlovid is a promising, orally bioavailable novel drug for SARS--CoV--2 with excellent safety profiles. Our main goal here is to explore the pharmacometric features of this new antiviral. To provide a detailed assessment of Paxlovid, we propose a hybrid multiscale mathematical approach. We demonstrate that the results of the present \textit{in silico} evaluation match the clinical expectations remarkably well: on the one hand, our computations successfully replicate the outcome of an actual \textit{in vitro} experiment; on the other hand we verify both the sufficiency and the necessity of Paxlovid's two main components (nirmatrelvir and ritonavir) for a simplified \textit{in vivo} case. Moreover, in the simulated context of our computational framework we visualize the importance of early interventions, and identify the time window where a unit--length delay causes the highest level of tissue damage. Finally, the results' sensitivity to the diffusion coefficient of the virus is explored in details.
2017 24th National and 2nd International Iranian Conference on Biomedical Engineering (ICBME), 2017
Parkinson's disease (PD) is a neurodegenerative disorder that mainly affects the motor areas ... more Parkinson's disease (PD) is a neurodegenerative disorder that mainly affects the motor areas of patients, although cognitive disorders are common among them, too. Various invasive and non-invasive neuromodulations have been proposed for treatment of the symptoms of PD, in which tDCS is one of the emerging methods. In this study, six right-handed patients with PD in drug-off condition were stimulated with 2mA tDCS in left primary motor cortex (Ml) for 20 minutes. Two new tasks were performed by the participants thrice pre and post stimulation to limit the effects of learning or anxiety. The trajectory signals of their hand movements were recorded using a graphical tablet. To investigate the effects of tDCS on the performance of hand movement in the participants, various features were extracted from the signals. Wilcoxon signed-rank test was applied to statistically evaluate them. The results showed that the time, velocity, acceleration and Approximate Entropy (ApE n) of participa...
Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the ... more Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the treatment. Due to chemotherapeutic agents, resistance can emerge by Darwinian evolution. Besides this, acquired drug resistance may arise via changes in gene expression. A recent discovery in cancer research uncovered a third possibility, indicating that this phenotype conversion can occur through the transfer of microvesicles from resistant to sensitive cells, a mechanism resembling the spread of an infectious agent. We present a model describing the evolution of sensitive and resistant tumour cells considering Darwinian selection, Lamarckian induction and microvesicle transfer. We identify three threshold parameters which determine the existence and stability of the three possible equilibria. Using a simple Dulac function, we give a complete description of the dynamics of the model depending on the three threshold parameters. We demonstrate the possible effects of increasing drug conce...
We propose a hybrid partial differential equation – agent-based (PDE–ABM) model to describe the s... more We propose a hybrid partial differential equation – agent-based (PDE–ABM) model to describe the spatio-temporal viral dynamics in a cell population. The virus concentration is considered as a continuous variable and virus movement is modelled by diffusion, while changes in the states of cells (i.e. healthy, infected, dead) are represented by a stochastic agent-based model. The two subsystems are intertwined: the probability of an agent getting infected in the ABM depends on the local viral concentration, and the source term of viral production in the PDE is determined by the cells that are infected.We develop a computational tool that allows us to study the hybrid system and the generated spatial patterns in detail. We systematically compare the outputs with a classical ODE system of viral dynamics, and find that the ODE model is a good approximation only if the diffusion coefficient is large.We demonstrate that the model is able to predict SARS–CoV–2 infection dynamics, and replica...
Cancer research, Mar 22, 2024
Lenia, a cellular automata framework used in artificial life, provides a natural setting to desig... more Lenia, a cellular automata framework used in artificial life, provides a natural setting to design, implement, and analyze mathematical models of cancer progression and treatment. Lenia's suitability as a cancer model is derived from the strong parallels between artificial life and cancer evolution: morphogenesis, homeostasis, motility, reproduction, growth, stimuli response, evolvability, and adaptation. Historically, agent-based models of cancer progression have been constructed with rules that govern birth, death and migration based on local availability for space, with attempts to map local rules to emergent global growth dynamics. Lenia provides a flexible framework for considering a spectrum of local (cell-scale) to global (tumor-scale) dynamics by defining an interaction kernel governing density-dependent growth dynamics. First, we show Lenia can recapitulate a range of cancer model classifications including local or global, deterministic or stochastic, non-spatial or spatial, single or multi-population, and off or on-lattice. Lenia is subsequently used to develop data-informed models of 1) single-population growth dynamics, 2) multi-population cell-cell competition models, and 3) cell migration or chemotaxis.
Journal of Electrical Bioimpedance, 2018
Computational dosimetry has become the main tool for estimating induced electric fields within br... more Computational dosimetry has become the main tool for estimating induced electric fields within brain tissues in transcranial direct current stimulation (tDCS) which is recently attracting the attention of researches for motor function disturbances such as Parkinson’s disease. This paper investigates the effect of including or excluding the very thin meninges in computing tDCS electric fields using CST software. For this purpose, two models of the brain with and without meninges were used to induce electric field with two DC current electrodes (2 mA) in regions of the model referring to M1 and Prefrontal Cortex (FP2) similar to tDCS. Considering meninges, the results have shown differences in the induced field showing that there might be problems with conventional models in which meninges are not taken into account.
This PhD thesis presents three new mathematical models aimed at advancing the current understandi... more This PhD thesis presents three new mathematical models aimed at advancing the current understanding of viral dynamics and cancer. The models are implemented in the HAL system and are applied to address current significant questions in the field. The first model, described in Chapter 3, is focused on the evolution of sensitive and resistant tumor cells and considers Darwinian selection, Lamarckian induction, and microvesicle transfer as mechanisms for resistance. The model is compared to an agent-based model and provides insight into the impact of microvesicles on the spread of cancer cells. Chapter 4 presents a hybrid partial differential equation - agent-based (PDE-ABM) model to describe the spatiotemporal viral dynamics in a cell population. The virus concentration is modeled as a continuous variable, while changes in the states of cells are represented by a stochastic agent-based model. The two subsystems are intertwined and the model is applied to predict SARS-CoV-2 and influenz...
World Academy of Science, Engineering and Technology, International Journal of Medical and Health Sciences, 2017
Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the ... more Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the treatment. Due to chemotherapeutic agents, resistance can emerge by Darwinian evolution. Besides this, acquired drug resistance may arise via changes in gene expression. A recent discovery in cancer research uncovered a third possibility, indicating that this phenotype conversion can occur through the transfer of microvesicles from resistant to sensitive cells, a mechanism resembling the spread of an infectious agent. We present a model describing the evolution of sensitive and resistant tumour cells considering Darwinian selection, Lamarckian induction and microvesicle transfer. We identify three threshold parameters which determine the existence and stability of the three possible equilibria. Using a simple Dulac function, we give a complete description of the dynamics of the model depending on the three threshold parameters. We demonstrate the possible effects of increasing drug conce...
Paxlovid is a promising, orally bioavailable novel drug for SARS--CoV--2 with excellent safety pr... more Paxlovid is a promising, orally bioavailable novel drug for SARS--CoV--2 with excellent safety profiles. Our main goal here is to explore the pharmacometric features of this new antiviral. To provide a detailed assessment of Paxlovid, we propose a hybrid multiscale mathematical approach. We demonstrate that the results of the present \textit{in silico} evaluation match the clinical expectations remarkably well: on the one hand, our computations successfully replicate the outcome of an actual \textit{in vitro} experiment; on the other hand we verify both the sufficiency and the necessity of Paxlovid's two main components (nirmatrelvir and ritonavir) for a simplified \textit{in vivo} case. Moreover, in the simulated context of our computational framework we visualize the importance of early interventions, and identify the time window where a unit--length delay causes the highest level of tissue damage. Finally, the results' sensitivity to the diffusion coefficient of the virus is explored in details.
2017 24th National and 2nd International Iranian Conference on Biomedical Engineering (ICBME), 2017
Parkinson's disease (PD) is a neurodegenerative disorder that mainly affects the motor areas ... more Parkinson's disease (PD) is a neurodegenerative disorder that mainly affects the motor areas of patients, although cognitive disorders are common among them, too. Various invasive and non-invasive neuromodulations have been proposed for treatment of the symptoms of PD, in which tDCS is one of the emerging methods. In this study, six right-handed patients with PD in drug-off condition were stimulated with 2mA tDCS in left primary motor cortex (Ml) for 20 minutes. Two new tasks were performed by the participants thrice pre and post stimulation to limit the effects of learning or anxiety. The trajectory signals of their hand movements were recorded using a graphical tablet. To investigate the effects of tDCS on the performance of hand movement in the participants, various features were extracted from the signals. Wilcoxon signed-rank test was applied to statistically evaluate them. The results showed that the time, velocity, acceleration and Approximate Entropy (ApE n) of participa...
Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the ... more Development of resistance to chemotherapy in cancer patients strongly effects the outcome of the treatment. Due to chemotherapeutic agents, resistance can emerge by Darwinian evolution. Besides this, acquired drug resistance may arise via changes in gene expression. A recent discovery in cancer research uncovered a third possibility, indicating that this phenotype conversion can occur through the transfer of microvesicles from resistant to sensitive cells, a mechanism resembling the spread of an infectious agent. We present a model describing the evolution of sensitive and resistant tumour cells considering Darwinian selection, Lamarckian induction and microvesicle transfer. We identify three threshold parameters which determine the existence and stability of the three possible equilibria. Using a simple Dulac function, we give a complete description of the dynamics of the model depending on the three threshold parameters. We demonstrate the possible effects of increasing drug conce...
We propose a hybrid partial differential equation – agent-based (PDE–ABM) model to describe the s... more We propose a hybrid partial differential equation – agent-based (PDE–ABM) model to describe the spatio-temporal viral dynamics in a cell population. The virus concentration is considered as a continuous variable and virus movement is modelled by diffusion, while changes in the states of cells (i.e. healthy, infected, dead) are represented by a stochastic agent-based model. The two subsystems are intertwined: the probability of an agent getting infected in the ABM depends on the local viral concentration, and the source term of viral production in the PDE is determined by the cells that are infected.We develop a computational tool that allows us to study the hybrid system and the generated spatial patterns in detail. We systematically compare the outputs with a classical ODE system of viral dynamics, and find that the ODE model is a good approximation only if the diffusion coefficient is large.We demonstrate that the model is able to predict SARS–CoV–2 infection dynamics, and replica...