Gering, Kevin L
2013-08-27
A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware periodically samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics of the electrochemical cell. The computing system also develops a mechanistic level model of the electrochemical cell to determine performance fade characteristics of the electrochemical cell and analyzing the mechanistic level model to estimate performance fade characteristics over aging of a similar electrochemical cell. The mechanistic level model uses first constant-current pulses applied to the electrochemical cell at a first aging period and at three or more current values bracketing a first exchange current density. The mechanistic level model also is based on second constant-current pulses applied to the electrochemical cell at a second aging period and at three or more current values bracketing the second exchange current density.
GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.
Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru
2006-03-23
Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.
cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology
Johnson, Graham T.; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.
2014-01-01
cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10−7–10−8m) between molecular and cellular biology. cellPACK’s modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is currently available as open source code, with tools for validation of models and with recipes and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators, and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org. PMID:25437435
Development of a Solid-Oxide Fuel Cell/Gas Turbine Hybrid System Model for Aerospace Applications
NASA Technical Reports Server (NTRS)
Freeh, Joshua E.; Pratt, Joseph W.; Brouwer, Jacob
2004-01-01
Recent interest in fuel cell-gas turbine hybrid applications for the aerospace industry has led to the need for accurate computer simulation models to aid in system design and performance evaluation. To meet this requirement, solid oxide fuel cell (SOFC) and fuel processor models have been developed and incorporated into the Numerical Propulsion Systems Simulation (NPSS) software package. The SOFC and reformer models solve systems of equations governing steady-state performance using common theoretical and semi-empirical terms. An example hybrid configuration is presented that demonstrates the new capability as well as the interaction with pre-existing gas turbine and heat exchanger models. Finally, a comparison of calculated SOFC performance with experimental data is presented to demonstrate model validity. Keywords: Solid Oxide Fuel Cell, Reformer, System Model, Aerospace, Hybrid System, NPSS
Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, Ying; Smith, Kandler; Wood, Eric
Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model,more » which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.« less
The Future of Cell Biology: Emerging Model Organisms.
Goldstein, Bob; King, Nicole
2016-11-01
Most current research in cell biology uses just a handful of model systems including yeast, Arabidopsis, Drosophila, Caenorhabditis elegans, zebrafish, mouse, and cultured mammalian cells. And for good reason - for many biological questions, the best system for the question is likely to be found among these models. However, in some cases, and particularly as the questions that engage scientists broaden, the best system for a question may be a little-studied organism. Modern research tools are facilitating a renaissance for unusual and interesting organisms as emerging model systems. As a result, we predict that an ever-expanding breadth of model systems may be a hallmark of future cell biology. Copyright © 2016 Elsevier Ltd. All rights reserved.
Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques
Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger
2011-01-01
Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345
Systems Modelling and the Development of Coherent Understanding of Cell Biology
ERIC Educational Resources Information Center
Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.
2008-01-01
This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…
Engineering model system study for a regenerative fuel cell: Study report
NASA Technical Reports Server (NTRS)
Chang, B. J.; Schubert, F. H.; Kovach, A. J.; Wynveen, R. A.
1984-01-01
Key design issues of the regenerative fuel cell system concept were studied and a design definition of an alkaline electrolyte based engineering model system or low Earth orbit missions was completed. Definition of key design issues for a regenerative fuel cell system include gaseous reactant storage, shared heat exchangers and high pressure pumps. A power flow diagram for the 75 kW initial space station and the impact of different regenerative fuel cell modular sizes on the total 5 year to orbit weight and volume are determined. System characteristics, an isometric drawing, component sizes and mass and energy balances are determined for the 10 kW engineering model system. An open loop regenerative fuel cell concept is considered for integration of the energy storage system with the life support system of the space station. Technical problems and their solutions, pacing technologies and required developments and demonstrations for the regenerative fuel cell system are defined.
Optimization of cell seeding in a 2D bio-scaffold system using computational models.
Ho, Nicholas; Chua, Matthew; Chui, Chee-Kong
2017-05-01
The cell expansion process is a crucial part of generating cells on a large-scale level in a bioreactor system. Hence, it is important to set operating conditions (e.g. initial cell seeding distribution, culture medium flow rate) to an optimal level. Often, the initial cell seeding distribution factor is neglected and/or overlooked in the design of a bioreactor using conventional seeding distribution methods. This paper proposes a novel seeding distribution method that aims to maximize cell growth and minimize production time/cost. The proposed method utilizes two computational models; the first model represents cell growth patterns whereas the second model determines optimal initial cell seeding positions for adherent cell expansions. Cell growth simulation from the first model demonstrates that the model can be a representation of various cell types with known probabilities. The second model involves a combination of combinatorial optimization, Monte Carlo and concepts of the first model, and is used to design a multi-layer 2D bio-scaffold system that increases cell production efficiency in bioreactor applications. Simulation results have shown that the recommended input configurations obtained from the proposed optimization method are the most optimal configurations. The results have also illustrated the effectiveness of the proposed optimization method. The potential of the proposed seeding distribution method as a useful tool to optimize the cell expansion process in modern bioreactor system applications is highlighted. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Theoretical Solid Oxide Fuel Cell Model for System Controls and Stability Design
NASA Technical Reports Server (NTRS)
Kopasakis, George; Brinson, Thomas; Credle, Sydni; Xu, Ming
2006-01-01
As the aviation industry moves towards higher efficiency electrical power generation, all electric aircraft, or zero emissions and more quiet aircraft, fuel cells are sought as the technology that can deliver on these high expectations. The Hybrid Solid Oxide Fuel Cell system combines the fuel cell with a microturbine to obtain up to 70 percent cycle efficiency, and then distributes the electrical power to the loads via a power distribution system. The challenge is to understand the dynamics of this complex multi-discipline system, and design distributed controls that take the system through its operating conditions in a stable and safe manner while maintaining the system performance. This particular system is a power generation and distribution system and the fuel cell and microturbine model fidelity should be compatible with the dynamics of the power distribution system in order to allow proper stability and distributed controls design. A novel modeling approach is proposed for the fuel cell that will allow the fuel cell and the power system to be integrated and designed for stability, distributed controls, and other interface specifications. This investigation shows that for the fuel cell, the voltage characteristic should be modeled, but in addition, conservation equation dynamics, ion diffusion, charge transfer kinetics, and the electron flow inherent impedance should also be included.
Hunsberger, Joshua G; Efthymiou, Anastasia G; Malik, Nasir; Behl, Mamta; Mead, Ivy L; Zeng, Xianmin; Simeonov, Anton; Rao, Mahendra
2015-08-15
There is great need to develop more predictive drug discovery tools to identify new therapies to treat diseases of the central nervous system (CNS). Current nonpluripotent stem cell-based models often utilize non-CNS immortalized cell lines and do not enable the development of personalized models of disease. In this review, we discuss why in vitro models are necessary for translational research and outline the unique advantages of induced pluripotent stem cell (iPSC)-based models over those of current systems. We suggest that iPSC-based models can be patient specific and isogenic lines can be differentiated into many neural cell types for detailed comparisons. iPSC-derived cells can be combined to form small organoids, or large panels of lines can be developed that enable new forms of analysis. iPSC and embryonic stem cell-derived cells can be readily engineered to develop reporters for lineage studies or mechanism of action experiments further extending the utility of iPSC-based systems. We conclude by describing novel technologies that include strategies for the development of diversity panels, novel genomic engineering tools, new three-dimensional organoid systems, and modified high-content screens that may bring toxicology into the 21st century. The strategic integration of these technologies with the advantages of iPSC-derived cell technology, we believe, will be a paradigm shift for toxicology and drug discovery efforts.
NASA Astrophysics Data System (ADS)
Braun, Robert Joseph
The advent of maturing fuel cell technologies presents an opportunity to achieve significant improvements in energy conversion efficiencies at many scales; thereby, simultaneously extending our finite resources and reducing "harmful" energy-related emissions to levels well below that of near-future regulatory standards. However, before realization of the advantages of fuel cells can take place, systems-level design issues regarding their application must be addressed. Using modeling and simulation, the present work offers optimal system design and operation strategies for stationary solid oxide fuel cell systems applied to single-family detached dwellings. A one-dimensional, steady-state finite-difference model of a solid oxide fuel cell (SOFC) is generated and verified against other mathematical SOFC models in the literature. Fuel cell system balance-of-plant components and costs are also modeled and used to provide an estimate of system capital and life cycle costs. The models are used to evaluate optimal cell-stack power output, the impact of cell operating and design parameters, fuel type, thermal energy recovery, system process design, and operating strategy on overall system energetic and economic performance. Optimal cell design voltage, fuel utilization, and operating temperature parameters are found using minimization of the life cycle costs. System design evaluations reveal that hydrogen-fueled SOFC systems demonstrate lower system efficiencies than methane-fueled systems. The use of recycled cell exhaust gases in process design in the stack periphery are found to produce the highest system electric and cogeneration efficiencies while achieving the lowest capital costs. Annual simulations reveal that efficiencies of 45% electric (LHV basis), 85% cogenerative, and simple economic paybacks of 5--8 years are feasible for 1--2 kW SOFC systems in residential-scale applications. Design guidelines that offer additional suggestions related to fuel cell-stack sizing and operating strategy (base-load or load-following and cogeneration or electric-only) are also presented.
NASA Astrophysics Data System (ADS)
Meiler, M.; Andre, D.; Schmid, O.; Hofer, E. P.
Intelligent energy management is a cost-effective key path to realize efficient automotive drive trains [R. O'Hayre, S.W. Cha, W. Colella, F.B. Prinz. Fuel Cell Fundamentals, John Wiley & Sons, Hoboken, 2006]. To develop operating strategy in fuel cell drive trains, precise and computational efficient models of all system components, especially the fuel cell stack, are needed. Should these models further be used in diagnostic or control applications, then some major requirements must be fulfilled. First, the model must predict the mean fuel cell voltage very precisely in all possible operating conditions, even during transients. The model output should be as smooth as possible to support best efficient optimization strategies of the complete system. At least, the model must be computational efficient. For most applications, a difference between real fuel cell voltage and model output of less than 10 mV and 1000 calculations per second will be sufficient. In general, empirical models based on system identification offer a better accuracy and consume less calculation resources than detailed models derived from theoretical considerations [J. Larminie, A. Dicks. Fuel Cell Systems Explained, John Wiley & Sons, West Sussex, 2003]. In this contribution, the dynamic behaviour of the mean cell voltage of a polymer-electrolyte-membrane fuel cell (PEMFC) stack due to variations in humidity of cell's reactant gases is investigated. The validity of the overall model structure, a so-called general Hammerstein model (or Uryson model), was introduced recently in [M. Meiler, O. Schmid, M. Schudy, E.P. Hofer. Dynamic fuel cell stack model for real-time simulation based on system identification, J. Power Sources 176 (2007) 523-528]. Fuel cell mean voltage is calculated as the sum of a stationary and a dynamic voltage component. The stationary component of cell voltage is represented by a lookup-table and the dynamic voltage by a parallel placed, nonlinear transfer function. A suitable experimental setup to apply fast variations of gas humidity is introduced and is used to investigate a 10 cell PEMFC stack under various operation conditions. Using methods like stepwise multiple-regression a good mathematical description with reduced free parameters is achieved.
Simulations of Living Cell Origins Using a Cellular Automata Model
NASA Astrophysics Data System (ADS)
Ishida, Takeshi
2014-04-01
Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.
Simulations of living cell origins using a cellular automata model.
Ishida, Takeshi
2014-04-01
Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.
NASA Astrophysics Data System (ADS)
Cordoba-Arenas, Andrea; Onori, Simona; Rizzoni, Giorgio
2015-04-01
A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of its battery systems. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of battery systems. The field of battery aging modeling and prognosis has seen progress with respect to model-based and data-driven approaches to describe the aging of battery cells. However, in real world applications cells are interconnected and aging propagates. The propagation of aging from one cell to others exhibits itself in a reduced battery system life. This paper proposes a control-oriented battery pack model that describes the propagation of aging and its effect on the life span of battery systems. The modeling approach is such that it is able to predict pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models of the electrical and thermal dynamics, and dynamic models of cell aging. The system-level state-of-health (SOH) is assessed based on knowledge of individual cells SOH, pack electrical topology and voltage equalization approach.
Exergy analysis of a solid oxide fuel cell micropowerplant
NASA Astrophysics Data System (ADS)
Hotz, Nico; Senn, Stephan M.; Poulikakos, Dimos
In this paper, an analytical model of a micro solid oxide fuel cell (SOFC) system fed by butane is introduced and analyzed in order to optimize its exergetic efficiency. The micro SOFC system is equipped with a partial oxidation (POX) reformer, a vaporizer, two pre-heaters, and a post-combustor. A one-dimensional (1D) polarization model of the SOFC is used to examine the effects of concentration overpotentials, activation overpotentials, and ohmic resistances on cell performance. This 1D polarization model is extended in this study to a two-dimensional (2D) fuel cell model considering convective mass and heat transport along the fuel cell channel and from the fuel cell to the environment. The influence of significant operational parameters on the exergetic efficiency of the micro SOFC system is discussed. The present study shows the importance of an exergy analysis of the fuel cell as part of an entire thermodynamic system (transportable micropowerplant) generating electric power.
A Theoretical Solid Oxide Fuel Cell Model for Systems Controls and Stability Design
NASA Technical Reports Server (NTRS)
Kopasakis, George; Brinson, Thomas; Credle, Sydni
2008-01-01
As the aviation industry moves toward higher efficiency electrical power generation, all electric aircraft, or zero emissions and more quiet aircraft, fuel cells are sought as the technology that can deliver on these high expectations. The hybrid solid oxide fuel cell system combines the fuel cell with a micro-turbine to obtain up to 70% cycle efficiency, and then distributes the electrical power to the loads via a power distribution system. The challenge is to understand the dynamics of this complex multidiscipline system and the design distributed controls that take the system through its operating conditions in a stable and safe manner while maintaining the system performance. This particular system is a power generation and a distribution system, and the fuel cell and micro-turbine model fidelity should be compatible with the dynamics of the power distribution system in order to allow proper stability and distributed controls design. The novelty in this paper is that, first, the case is made why a high fidelity fuel cell mode is needed for systems control and stability designs. Second, a novel modeling approach is proposed for the fuel cell that will allow the fuel cell and the power system to be integrated and designed for stability, distributed controls, and other interface specifications. This investigation shows that for the fuel cell, the voltage characteristic should be modeled but in addition, conservation equation dynamics, ion diffusion, charge transfer kinetics, and the electron flow inherent impedance should also be included.
Fostering synergy between cell biology and systems biology.
Eddy, James A; Funk, Cory C; Price, Nathan D
2015-08-01
In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Simulation of a 250 kW diesel fuel processor/PEM fuel cell system
NASA Astrophysics Data System (ADS)
Amphlett, J. C.; Mann, R. F.; Peppley, B. A.; Roberge, P. R.; Rodrigues, A.; Salvador, J. P.
Polymer-electrolyte membrane (PEM) fuel cell systems offer a potential power source for utility and mobile applications. Practical fuel cell systems use fuel processors for the production of hydrogen-rich gas. Liquid fuels, such as diesel or other related fuels, are attractive options as feeds to a fuel processor. The generation of hydrogen gas for fuel cells, in most cases, becomes the crucial design issue with respect to weight and volume in these applications. Furthermore, these systems will require a gas clean-up system to insure that the fuel quality meets the demands of the cell anode. The endothermic nature of the reformer will have a significant affect on the overall system efficiency. The gas clean-up system may also significantly effect the overall heat balance. To optimize the performance of this integrated system, therefore, waste heat must be used effectively. Previously, we have concentrated on catalytic methanol-steam reforming. A model of a methanol steam reformer has been previously developed and has been used as the basis for a new, higher temperature model for liquid hydrocarbon fuels. Similarly, our fuel cell evaluation program previously led to the development of a steady-state electrochemical fuel cell model (SSEM). The hydrocarbon fuel processor model and the SSEM have now been incorporated in the development of a process simulation of a 250 kW diesel-fueled reformer/fuel cell system using a process simulator. The performance of this system has been investigated for a variety of operating conditions and a preliminary assessment of thermal integration issues has been carried out. This study demonstrates the application of a process simulation model as a design analysis tool for the development of a 250 kW fuel cell system.
System level modeling and component level control of fuel cells
NASA Astrophysics Data System (ADS)
Xue, Xingjian
This dissertation investigates the fuel cell systems and the related technologies in three aspects: (1) system-level dynamic modeling of both PEM fuel cell (PEMFC) and solid oxide fuel cell (SOFC); (2) condition monitoring scheme development of PEM fuel cell system using model-based statistical method; and (3) strategy and algorithm development of precision control with potential application in energy systems. The dissertation first presents a system level dynamic modeling strategy for PEM fuel cells. It is well known that water plays a critical role in PEM fuel cell operations. It makes the membrane function appropriately and improves the durability. The low temperature operating conditions, however, impose modeling difficulties in characterizing the liquid-vapor two phase change phenomenon, which becomes even more complex under dynamic operating conditions. This dissertation proposes an innovative method to characterize this phenomenon, and builds a comprehensive model for PEM fuel cell at the system level. The model features the complete characterization of multi-physics dynamic coupling effects with the inclusion of dynamic phase change. The model is validated using Ballard stack experimental result from open literature. The system behavior and the internal coupling effects are also investigated using this model under various operating conditions. Anode-supported tubular SOFC is also investigated in the dissertation. While the Nernst potential plays a central role in characterizing the electrochemical performance, the traditional Nernst equation may lead to incorrect analysis results under dynamic operating conditions due to the current reverse flow phenomenon. This dissertation presents a systematic study in this regard to incorporate a modified Nernst potential expression and the heat/mass transfer into the analysis. The model is used to investigate the limitations and optimal results of various operating conditions; it can also be utilized to perform the optimal design of tubular SOFC. With the system-level dynamic model as a basis, a framework for the robust, online monitoring of PEM fuel cell is developed in the dissertation. The monitoring scheme employs the Hotelling T2 based statistical scheme to handle the measurement noise and system uncertainties and identifies the fault conditions through a series of self-checking and conformal testing. A statistical sampling strategy is also utilized to improve the computation efficiency. Fuel/gas flow control is the fundamental operation for fuel cell energy systems. In the final part of the dissertation, a high-precision and robust tracking control scheme using piezoelectric actuator circuit with direct hysteresis compensation is developed. The key characteristic of the developed control algorithm includes the nonlinear continuous control action with the adaptive boundary layer strategy.
Thermal System Modeling for Lunar and Martian Surface Regenerative Fuel Cell Systems
NASA Technical Reports Server (NTRS)
Gilligan, Ryan Patrick; Smith, Phillip James; Jakupca, Ian Joseph; Bennett, William Raymond; Guzik, Monica Christine; Fincannon, Homer J.
2017-01-01
The Advanced Exploration Systems (AES) Advanced Modular Power Systems (AMPS) Project is investigating different power systems for various lunar and Martian mission concepts. The AMPS Fuel Cell (FC) team has created two system-level models to evaluate the performance of regenerative fuel cell (RFC) systems employing different fuel cell chemistries. Proton Exchange Membrane fuel cells PEMFCs contain a polymer electrolyte membrane that separates the hydrogen and oxygen cavities and conducts hydrogen cations (protons) across the cell. Solid Oxide fuel cells (SOFCs) operate at high temperatures, using a zirconia-based solid ceramic electrolyte to conduct oxygen anions across the cell. The purpose of the modeling effort is to down select one fuel cell chemistry for a more detailed design effort. Figures of merit include the system mass, volume, round trip efficiency, and electrolyzer charge power required. PEMFCs operate at around 60 degrees Celsius versus SOFCs which operate at temperatures greater than 700 degrees Celsius. Due to the drastically different operating temperatures of the two chemistries the thermal control systems (TCS) differ. The PEM TCS is less complex and is characterized by a single pump cooling loop that uses deionized water coolant and rejects heat generated by the system to the environment via a radiator. The solid oxide TCS has its own unique challenges including the requirement to reject high quality heat and to condense the steam produced in the reaction. This paper discusses the modeling of thermal control systems for an extraterrestrial RFC that utilizes either a PEM or solid oxide fuel cell.
Roeder, Ingo; Herberg, Maria; Horn, Matthias
2009-04-01
Previously, we have modeled hematopoietic stem cell organization by a stochastic, single cell-based approach. Applications to different experimental systems demonstrated that this model consistently explains a broad variety of in vivo and in vitro data. A major advantage of the agent-based model (ABM) is the representation of heterogeneity within the hematopoietic stem cell population. However, this advantage comes at the price of time-consuming simulations if the systems become large. One example in this respect is the modeling of disease and treatment dynamics in patients with chronic myeloid leukemia (CML), where the realistic number of individual cells to be considered exceeds 10(6). To overcome this deficiency, without losing the representation of the inherent heterogeneity of the stem cell population, we here propose to approximate the ABM by a system of partial differential equations (PDEs). The major benefit of such an approach is its independence from the size of the system. Although this mean field approach includes a number of simplifying assumptions compared to the ABM, it retains the key structure of the model including the "age"-structure of stem cells. We show that the PDE model qualitatively and quantitatively reproduces the results of the agent-based approach.
Gering, Kevin L.
2013-01-01
A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics. The computing system also analyzes the cell information of the electrochemical cell with a Butler-Volmer (BV) expression modified to determine exchange current density of the electrochemical cell by including kinetic performance information related to pulse-time dependence, electrode surface availability, or a combination thereof. A set of sigmoid-based expressions may be included with the modified-BV expression to determine kinetic performance as a function of pulse time. The determined exchange current density may be used with the modified-BV expression, with or without the sigmoid expressions, to analyze other characteristics of the electrochemical cell. Model parameters can be defined in terms of cell aging, making the overall kinetics model amenable to predictive estimates of cell kinetic performance along the aging timeline.
Description and modelling of the solar-hydrogen-biogas-fuel cell system in GlashusEtt
NASA Astrophysics Data System (ADS)
Hedström, L.; Wallmark, C.; Alvfors, P.; Rissanen, M.; Stridh, B.; Ekman, J.
The need to reduce pollutant emissions and utilise the world's available energy resources more efficiently has led to increased attention towards e.g. fuel cells, but also to other alternative energy solutions. In order to further understand and evaluate the prerequisites for sustainable and energy-saving systems, ABB and Fortum have equipped an environmental information centre, located in Hammarby Sjöstad, Stockholm, Sweden, with an alternative energy system. The system is being used to demonstrate and evaluate how a system based on fuel cells and solar cells can function as a complement to existing electricity and heat production. The stationary energy system is situated on the top level of a three-floor glass building and is open to the public. The alternative energy system consists of a fuel cell system, a photovoltaic (PV) cell array, an electrolyser, hydrogen storage tanks, a biogas burner, dc/ac inverters, heat exchangers and an accumulator tank. The fuel cell system includes a reformer and a polymer electrolyte fuel cell (PEFC) with a maximum rated electrical output of 4 kW el and a maximum thermal output of 6.5 kW th. The fuel cell stack can be operated with reformed biogas, or directly using hydrogen produced by the electrolyser. The cell stack in the electrolyser consists of proton exchange membrane (PEM) cells. To evaluate different automatic control strategies for the system, a simplified dynamic model has been developed in MATLAB Simulink. The model based on measurement data taken from the actual system. The evaluation is based on demand curves, investment costs, electricity prices and irradiation. Evaluation criteria included in the model are electrical and total efficiencies as well as economic parameters.
NASA Astrophysics Data System (ADS)
Nguyen, Gia Luong Huu
Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage. In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack. The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.
Development of a model system to analyze chondrogenic differentiation of mesenchymal stem cells
Ruedel, Anke; Hofmeister, Simone; Bosserhoff, Anja-Katrin
2013-01-01
High-density cell culture is widely used for the analysis of cartilage development of human mesenchymal stem cells (HMSCs) in vitro. Several cell culture systems, as micromass, pellet culture and alginate culture, are applied by groups in the field to induce chondrogenic differentiation of HMSCs. A draw back of all model systems is the high amount of cells necessary for the experiments. Further, handling of large experimental approaches is difficult due to culturing e.g. in 15 ml tubes. Therefore, we aimed to develop a new model system based on “hanging drop” cultures using 10 to 100 fold less cells. Here, we demonstrate that differentiation of chondrogenic cells was induced as previously shown in other model systems. Real time RT-PCR analysis demonstrated that Collagen type II and MIA/CD-RAP were upregulated during culturing whereas for induction of hypertrophic markers like Collagen type X and AP-2 epsilon treatment with TGF beta was needed. To further test the system, siRNA against Sox9 was used and effects on chondrogenic gene expression were evaluated. In summary, the hanging drop culture system was determined to be a promising tool for in vitro chondrogenic studies. PMID:24294400
Cell illustrator 4.0: a computational platform for systems biology.
Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru
2011-01-01
Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.
Cell Illustrator 4.0: a computational platform for systems biology.
Nagasaki, Masao; Saito, Ayumu; Jeong, Euna; Li, Chen; Kojima, Kaname; Ikeda, Emi; Miyano, Satoru
2010-01-01
Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.
Deep Reinforcement Learning of Cell Movement in the Early Stage of C. elegans Embryogenesis.
Wang, Zi; Wang, Dali; Li, Chengcheng; Xu, Yichi; Li, Husheng; Bao, Zhirong
2018-04-25
Cell movement in the early phase of C. elegans development is regulated by a highly complex process in which a set of rules and connections are formulated at distinct scales. Previous efforts have demonstrated that agent-based, multi-scale modeling systems can integrate physical and biological rules and provide new avenues to study developmental systems. However, the application of these systems to model cell movement is still challenging and requires a comprehensive understanding of regulatory networks at the right scales. Recent developments in deep learning and reinforcement learning provide an unprecedented opportunity to explore cell movement using 3D time-lapse microscopy images. We present a deep reinforcement learning approach within an agent-based modeling system to characterize cell movement in the embryonic development of C. elegans. Our modeling system captures the complexity of cell movement patterns in the embryo and overcomes the local optimization problem encountered by traditional rule-based, agent-based modeling that uses greedy algorithms. We tested our model with two real developmental processes: the anterior movement of the Cpaaa cell via intercalation and the rearrangement of the superficial left-right asymmetry. In the first case, the model results suggested that Cpaaa's intercalation is an active directional cell movement caused by the continuous effects from a longer distance (farther than the length of two adjacent cells), as opposed to a passive movement caused by neighbor cell movements. In the second case, a leader-follower mechanism well explained the collective cell movement pattern in the asymmetry rearrangement. These results showed that our approach to introduce deep reinforcement learning into agent-based modeling can test regulatory mechanisms by exploring cell migration paths in a reverse engineering perspective. This model opens new doors to explore the large datasets generated by live imaging. Source code is available at https://github.com/zwang84/drl4cellmovement. dwang7@utk.edu, baoz@mskcc.org. Supplementary data are available at Bioinformatics online.
Newgreen, Donald F; Dufour, Sylvie; Howard, Marthe J; Landman, Kerry A
2013-10-01
We review morphogenesis of the enteric nervous system from migratory neural crest cells, and defects of this process such as Hirschsprung disease, centering on cell motility and assembly, and cell adhesion and extracellular matrix molecules, along with cell proliferation and growth factors. We then review continuum and agent-based (cellular automata) models with rules of cell movement and logistical proliferation. Both movement and proliferation at the individual cell level are modeled with stochastic components from which stereotyped outcomes emerge at the population level. These models reproduced the wave-like colonization of the intestine by enteric neural crest cells, and several new properties emerged, such as colonization by frontal expansion, which were later confirmed biologically. These models predict a surprising level of clonal heterogeneity both in terms of number and distribution of daughter cells. Biologically, migrating cells form stable chains made up of unstable cells, but this is not seen in the initial model. We outline additional rules for cell differentiation into neurons, axon extension, cell-axon and cell-cell adhesions, chemotaxis and repulsion which can reproduce chain migration. After the migration stage, the cells re-arrange as a network of ganglia. Changes in cell adhesion molecules parallel this, and we describe additional rules based on Steinberg's Differential Adhesion Hypothesis, reflecting changing levels of adhesion in neural crest cells and neurons. This was able to reproduce enteric ganglionation in a model. Mouse mutants with disturbances of enteric nervous system morphogenesis are discussed, and these suggest future refinement of the models. The modeling suggests a relatively simple set of cell behavioral rules could account for complex patterns of morphogenesis. The model has allowed the proposal that Hirschsprung disease is mostly an enteric neural crest cell proliferation defect, not a defect of cell migration. In addition, the model suggests an explanations for zonal and skip segment variants of Hirschsprung disease, and also gives a novel stochastic explanation for the observed discordancy of Hirschsprung disease in identical twins. © 2013 Elsevier Inc. All rights reserved.
Systems Analysis Initiated for All-Electric Aircraft Propulsion
NASA Technical Reports Server (NTRS)
Kohout, Lisa L.
2003-01-01
A multidisciplinary effort is underway at the NASA Glenn Research Center to develop concepts for revolutionary, nontraditional fuel cell power and propulsion systems for aircraft applications. There is a growing interest in the use of fuel cells as a power source for electric propulsion as well as an auxiliary power unit to substantially reduce or eliminate environmentally harmful emissions. A systems analysis effort was initiated to assess potential concepts in an effort to identify those configurations with the highest payoff potential. Among the technologies under consideration are advanced proton exchange membrane (PEM) and solid oxide fuel cells, alternative fuels and fuel processing, and fuel storage. Prior to this effort, the majority of fuel cell analysis done at Glenn was done for space applications. Because of this, a new suite of models was developed. These models include the hydrogen-air PEM fuel cell; internal reforming solid oxide fuel cell; balance-of-plant components (compressor, humidifier, separator, and heat exchangers); compressed gas, cryogenic, and liquid fuel storage tanks; and gas turbine/generator models for hybrid system applications. Initial mass, volume, and performance estimates of a variety of PEM systems operating on hydrogen and reformate have been completed for a baseline general aviation aircraft. Solid oxide/turbine hybrid systems are being analyzed. In conjunction with the analysis efforts, a joint effort has been initiated with Glenn s Computer Services Division to integrate fuel cell stack and component models with the visualization environment that supports the GRUVE lab, Glenn s virtual reality facility. The objective of this work is to provide an environment to assist engineers in the integration of fuel cell propulsion systems into aircraft and provide a better understanding of the interaction between system components and the resulting effect on the overall design and performance of the aircraft. Initially, three-dimensional computer-aided design (CAD) models of representative PEM fuel cell stack and components were developed and integrated into the virtual reality environment along with an Excel-based model used to calculate fuel cell electrical performance on the basis of cell dimensions (see the figure). CAD models of a representative general aviation aircraft were also developed and added to the environment. With the use of special headgear, users will be able to virtually manipulate the fuel cell s physical characteristics and its placement within the aircraft while receiving information on the resultant fuel cell output power and performance. As the systems analysis effort progresses, we will add more component models to the GRUVE environment to help us more fully understand the effect of various system configurations on the aircraft.
UML as a cell and biochemistry modeling language.
Webb, Ken; White, Tony
2005-06-01
The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top-down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.
Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations
NASA Astrophysics Data System (ADS)
Ellis, Michael; Dobrovolny, Hana
2014-03-01
One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.
Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions
NASA Astrophysics Data System (ADS)
Oprisan, Sorinel Adrian; Oprisan, Ana
2005-03-01
Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.
Chaos in an Eulerian Based Model of Sickle Cell Blood Flow
NASA Astrophysics Data System (ADS)
Apori, Akwasi; Harris, Wesley
2001-11-01
A novel Eulerian model describing the manifestation of sickle cell blood flow in the capillaries has been formulated to study the apparently chaotic onset of sickle cell crises. This Eulerian model was based on extending previous models of sickle cell blood flow which were limited due to their Lagrangian formulation. Oxygen concentration, red blood cell velocity, cell stiffness, and plasma viscosity were modeled as system state variables. The governing equations of the system were expressed in canonical form. The non-linear coupling of velocity-viscosity and viscosity- stiffness proved to be the origin of chaos in the system. The system was solved with respect to a control parameter representing the unique rheology of the sickle cell erythrocytes. Results of chaos tests proved positive for various ranges of the control parameter. The results included con-tinuous patterns found in the Poincare section, spectral broadening of the Fourier power spectrum, and positive Lyapunov exponent values. The onset of chaos predicted by this sickle cell flow model as the control parameter was varied appeared to coincide with the change from a healthy state to a crisis state in a sickle cell patient. This finding that sickle cell crises may be caused from the well understood change of a solution from a steady state to chaotic could point to new ways in preventing and treating crises and should be validated in clinical trials.
Genome Editing of Erythroid Cell Culture Model Systems.
Yik, Jinfen J; Crossley, Merlin; Quinlan, Kate G R
2018-01-01
Genome editing to introduce specific mutations or to knock out genes in model cell systems has become an efficient platform for research in the fields of molecular biology, genetics, and cell biology. With recent rapid improvements in genome editing techniques, bench-top manipulation of the genome in cell culture has become progressively easier. The application of this knowledge to erythroid cell culture systems now allows the rapid analysis of the downstream effects of virtually any engineered gene disruption or modification in cell systems. Here, we describe a CRISPR/Cas9-based approach to making genomic modifications in erythroid lineage cells which we have successfully used in both murine (MEL) and human (K562) erythroleukaemia immortalized cell lines.
500 Watt Solar AMTEC Power System for Small Spacecraft.
1995-03-01
Thermal Modeling of High Efficiency AMTEC Cells ," Proceedings of the 24th National Heat Transfer Conference. Journal Article 12. SPACE...power flow calculation is the power required by the AMTEC cells which is the cell output power over the cell efficiency . The system model also...Converter ( AMTEC ) cell , called the multi-tube cell , integrated with an individual Thermal Energy Storage (TES) unit. The
NASA Astrophysics Data System (ADS)
Göll, S.; Samsun, R. C.; Peters, R.
Fuel-cell-based auxiliary power units can help to reduce fuel consumption and emissions in transportation. For this application, the combination of solid oxide fuel cells (SOFCs) with upstream fuel processing by autothermal reforming (ATR) is seen as a highly favorable configuration. Notwithstanding the necessity to improve each single component, an optimized architecture of the fuel cell system as a whole must be achieved. To enable model-based analyses, a system-level approach is proposed in which the fuel cell system is modeled as a multi-stage thermo-chemical process using the "flowsheeting" environment PRO/II™. Therein, the SOFC stack and the ATR are characterized entirely by corresponding thermodynamic processes together with global performance parameters. The developed model is then used to achieve an optimal system layout by comparing different system architectures. A system with anode and cathode off-gas recycling was identified to have the highest electric system efficiency. Taking this system as a basis, the potential for further performance enhancement was evaluated by varying four parameters characterizing different system components. Using methods from the design and analysis of experiments, the effects of these parameters and of their interactions were quantified, leading to an overall optimized system with encouraging performance data.
A System for Modelling Cell–Cell Interactions during Plant Morphogenesis
Dupuy, Lionel; Mackenzie, Jonathan; Rudge, Tim; Haseloff, Jim
2008-01-01
Background and aims During the development of multicellular organisms, cells are capable of interacting with each other through a range of biological and physical mechanisms. A description of these networks of cell–cell interactions is essential for an understanding of how cellular activity is co-ordinated in regionalized functional entities such as tissues or organs. The difficulty of experimenting on living tissues has been a major limitation to describing such systems, and computer modelling appears particularly helpful to characterize the behaviour of multicellular systems. The experimental difficulties inherent to the multitude of parallel interactions that underlie cellular morphogenesis have led to the need for computer models. Methods A new generic model of plant cellular morphogenesis is described that expresses interactions amongst cellular entities explicitly: the plant is described as a multi-scale structure, and interactions between distinct entities is established through a topological neighbourhood. Tissues are represented as 2D biphasic systems where the cell wall responds to turgor pressure through a viscous yielding of the cell wall. Key Results This principle was used in the development of the CellModeller software, a generic tool dedicated to the analysis and modelling of plant morphogenesis. The system was applied to three contrasting study cases illustrating genetic, hormonal and mechanical factors involved in plant morphogenesis. Conclusions Plant morphogenesis is fundamentally a cellular process and the CellModeller software, through its underlying generic model, provides an advanced research tool to analyse coupled physical and biological morphogenetic mechanisms. PMID:17921524
NASA Astrophysics Data System (ADS)
Zhao, Yingru; Chen, Jincan
A theoretical modeling approach is presented, which describes the behavior of a typical fuel cell-heat engine hybrid system in steady-state operating condition based on an existing solid oxide fuel cell model, to provide useful fundamental design characteristics as well as potential critical problems. The different sources of irreversible losses, such as the electrochemical reaction, electric resistances, finite-rate heat transfer between the fuel cell and the heat engine, and heat-leak from the fuel cell to the environment are specified and investigated. Energy and entropy analyses are used to indicate the multi-irreversible losses and to assess the work potentials of the hybrid system. Expressions for the power output and efficiency of the hybrid system are derived and the performance characteristics of the system are presented and discussed in detail. The effects of the design parameters and operating conditions on the system performance are studied numerically. It is found that there exist certain optimum criteria for some important parameters. The results obtained here may provide a theoretical basis for both the optimal design and operation of real fuel cell-heat engine hybrid systems. This new approach can be easily extended to other fuel cell hybrid systems to develop irreversible models suitable for the investigation and optimization of similar energy conversion settings and electrochemistry systems.
Walsh, James C; Angstmann, Christopher N; Duggin, Iain G; Curmi, Paul M G
2015-01-01
Oscillations of the Min protein system are involved in the correct midcell placement of the divisome during Escherichia coli cell division. Based on molecular interactions of the Min system, we formulated a mathematical model that reproduces Min patterning during cell growth and division. Specifically, the increase in the residence time of MinD attached to the membrane as its own concentration increases, is accounted for by dimerisation of membrane-bound MinD and its interaction with MinE. Simulation of this system generates unparalleled correlation between the waveshape of experimental and theoretical MinD distributions, suggesting that the dominant interactions of the physical system have been successfully incorporated into the model. For cells where MinD is fully-labelled with GFP, the model reproduces the stationary localization of MinD-GFP for short cells, followed by oscillations from pole to pole in larger cells, and the transition to the symmetric distribution during cell filamentation. Cells containing a secondary, GFP-labelled MinD display a contrasting pattern. The model is able to account for these differences, including temporary midcell localization just prior to division, by increasing the rate constant controlling MinD ATPase and heterotetramer dissociation. For both experimental conditions, the model can explain how cell division results in an equal distribution of MinD and MinE in the two daughter cells, and accounts for the temperature dependence of the period of Min oscillations. Thus, we show that while other interactions may be present, they are not needed to reproduce the main characteristics of the Min system in vivo.
Gardner, Shea Nicole
2007-10-23
A method and system for tailoring treatment regimens to individual patients with diseased cells exhibiting evolution of resistance to such treatments. A mathematical model is provided which models rates of population change of proliferating and quiescent diseased cells using cell kinetics and evolution of resistance of the diseased cells, and pharmacokinetic and pharmacodynamic models. Cell kinetic parameters are obtained from an individual patient and applied to the mathematical model to solve for a plurality of treatment regimens, each having a quantitative efficacy value associated therewith. A treatment regimen may then be selected from the plurlaity of treatment options based on the efficacy value.
Architecture and inherent robustness of a bacterial cell-cycle control system.
Shen, Xiling; Collier, Justine; Dill, David; Shapiro, Lucy; Horowitz, Mark; McAdams, Harley H
2008-08-12
A closed-loop control system drives progression of the coupled stalked and swarmer cell cycles of the bacterium Caulobacter crescentus in a near-mechanical step-like fashion. The cell-cycle control has a cyclical genetic circuit composed of four regulatory proteins with tight coupling to processive chromosome replication and cell division subsystems. We report a hybrid simulation of the coupled cell-cycle control system, including asymmetric cell division and responses to external starvation signals, that replicates mRNA and protein concentration patterns and is consistent with observed mutant phenotypes. An asynchronous sequential digital circuit model equivalent to the validated simulation model was created. Formal model-checking analysis of the digital circuit showed that the cell-cycle control is robust to intrinsic stochastic variations in reaction rates and nutrient supply, and that it reliably stops and restarts to accommodate nutrient starvation. Model checking also showed that mechanisms involving methylation-state changes in regulatory promoter regions during DNA replication increase the robustness of the cell-cycle control. The hybrid cell-cycle simulation implementation is inherently extensible and provides a promising approach for development of whole-cell behavioral models that can replicate the observed functionality of the cell and its responses to changing environmental conditions.
NASA Astrophysics Data System (ADS)
Xu, Shengzhi; Chu, Ian; Zhao, Gengshen; Wang, Qingzhang
2008-03-01
When proceed photovoltaic power system design, engineer needs prepared model of PV cells to evaluate system response, capability performance, and stability, the DC model is not enough, but an accuracy AC model plays a big role. This paper talks first about the AC model of PV cells, and DC model is also introduced in simple. There is a PV controller example explaining the steps to do system simulation in this paper. Two equivalent circuit models are implemented with mixed-signal language verilog-a, one hardware language easy to use and having good speed and high accuracy. Both of two models include solar cell arrays, one buck switched mode DC-DC converter, and the maximum power point tracking algorithm. The difference between them is that Solar cell in one of two models is with ac small signal parameter, another is without. The simulation result is given in comparison. This paper's work shows that ac parameter plays large role in switch-mode PV power system, especially when the switch frequency is higher than 100kHz.
A multi-scale model for correlation in B cell VDJ usage of zebrafish
NASA Astrophysics Data System (ADS)
Pan, Keyao; Deem, Michael W.
2011-10-01
The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.
Multiway modeling and analysis in stem cell systems biology
2008-01-01
Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate. Conclusion Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models. PMID:18625054
3D molecular models of whole HIV-1 virions generated with cellPACK
Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.
2014-01-01
As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262
Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.
Getto, Philipp; Marciniak-Czochra, Anna
2015-01-01
Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.
Thermal Design for Extra-Terrestrial Regenerative Fuel Cell System
NASA Technical Reports Server (NTRS)
Gilligan, R.; Guzik, M.; Jakupca, I.; Bennett, W.; Smith, P.; Fincannon, J.
2017-01-01
The Advanced Exploration Systems (AES) Advanced Modular Power Systems (AMPS) Project is investigating different power systems for various lunar and Martian mission concepts. The AMPS Fuel Cell (FC) team has created two system-level models to evaluate the performance of regenerative fuel cell (RFC) systems employing different fuel cell chemistries. Proton Exchange Membrane fuel cells PEMFCs contain a polymer electrolyte membrane that separates the hydrogen and oxygen cavities and conducts hydrogen cations (protons) across the cell. Solid Oxide fuel cells (SOFCs) operate at high temperatures, using a zirconia-based solid ceramic electrolyte to conduct oxygen anions across the cell. The purpose of the modeling effort is to down select one fuel cell chemistry for a more detailed design effort. Figures of merit include the system mass, volume, round trip efficiency, and electrolyzer charge power required. PEMFCs operate at around 60 C versus SOFCs which operate at temperatures greater than 700 C. Due to the drastically different operating temperatures of the two chemistries the thermal control systems (TCS) differ. The PEM TCS is less complex and is characterized by a single pump cooling loop that uses deionized water coolant and rejects heat generated by the system to the environment via a radiator. The solid oxide TCS has its own unique challenges including the requirement to reject high quality heat and to condense the steam produced in the reaction. This paper discusses the modeling of thermal control systems for an extraterrestrial RFC that utilizes either a PEM or solid oxide fuel cell.
Galle, J; Hoffmann, M; Aust, G
2009-01-01
Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
JaeHwa Koh; DuckJoo Yoon; Chang H. Oh
2010-07-01
An electrolyzer model for the analysis of a hydrogen-production system using a solid oxide electrolysis cell (SOEC) has been developed, and the effects for principal parameters have been estimated by sensitivity studies based on the developed model. The main parameters considered are current density, area specific resistance, temperature, pressure, and molar fraction and flow rates in the inlet and outlet. Finally, a simple model for a high-temperature hydrogen-production system using the solid oxide electrolysis cell integrated with very high temperature reactors is estimated.
A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology
Sung, Myong-Hee
2013-01-01
Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701
Local and systemic tumor immune dynamics
NASA Astrophysics Data System (ADS)
Enderling, Heiko
Tumor-associated antigens, stress proteins, and danger-associated molecular patterns are endogenous immune adjuvants that can both initiate and continually stimulate an immune response against a tumor. In retaliation, tumors can hijack intrinsic immune regulatory programs that are intended to prevent autoimmune disease, thereby facilitating continued growth despite the activated antitumor immune response. In metastatic disease, this ongoing tumor-immune battle occurs at each site. Adding an additional layer of complexity, T cells activated at one tumor site can cycle through the blood circulation system and extravasate in a different anatomic location to surveil a distant metastasis. We propose a mathematical modeling framework that incorporates the trafficking of activated T cells between metastatic sites. We extend an ordinary differential equation model of tumor-immune system interactions to multiple metastatic sites. Immune cells are activated in response to tumor burden and tumor cell death, and are recruited from tumor sites elsewhere in the body. A model of T cell trafficking throughout the circulatory system can inform the tumor-immune interaction model about the systemic distribution and arrival of T cells at specific tumor sites. Model simulations suggest that metastases not only contribute to immune surveillance, but also that this contribution varies between metastatic sites. Such information may ultimately help harness the synergy of focal therapy with the immune system to control metastatic disease.
Freezing Transition Studies Through Constrained Cell Model Simulation
NASA Astrophysics Data System (ADS)
Nayhouse, Michael; Kwon, Joseph Sang-Il; Heng, Vincent R.; Amlani, Ankur M.; Orkoulas, G.
2014-10-01
In the present work, a simulation method based on cell models is used to deduce the fluid-solid transition of a system of particles that interact via a pair potential, , which is of the form with . The simulations are implemented under constant-pressure conditions on a generalized version of the constrained cell model. The constrained cell model is constructed by dividing the volume into Wigner-Seitz cells and confining each particle in a single cell. This model is a special case of a more general cell model which is formed by introducing an additional field variable that controls the number of particles per cell and, thus, the relative stability of the solid against the fluid phase. High field values force configurations with one particle per cell and thus favor the solid phase. Fluid-solid coexistence on the isotherm that corresponds to a reduced temperature of 2 is determined from constant-pressure simulations of the generalized cell model using tempering and histogram reweighting techniques. The entire fluid-solid phase boundary is determined through a thermodynamic integration technique based on histogram reweighting, using the previous coexistence point as a reference point. The vapor-liquid phase diagram is obtained from constant-pressure simulations of the unconstrained system using tempering and histogram reweighting. The phase diagram of the system is found to contain a stable critical point and a triple point. The phase diagram of the corresponding constrained cell model is also found to contain both a stable critical point and a triple point.
Fuzzy Petri nets to model vision system decisions within a flexible manufacturing system
NASA Astrophysics Data System (ADS)
Hanna, Moheb M.; Buck, A. A.; Smith, R.
1994-10-01
The paper presents a Petri net approach to modelling, monitoring and control of the behavior of an FMS cell. The FMS cell described comprises a pick and place robot, vision system, CNC-milling machine and 3 conveyors. The work illustrates how the block diagrams in a hierarchical structure can be used to describe events at different levels of abstraction. It focuses on Fuzzy Petri nets (Fuzzy logic with Petri nets) including an artificial neural network (Fuzzy Neural Petri nets) to model and control vision system decisions and robot sequences within an FMS cell. This methodology can be used as a graphical modelling tool to monitor and control the imprecise, vague and uncertain situations, and determine the quality of the output product of an FMS cell.
Multidisciplinary approaches to understanding collective cell migration in developmental biology.
Schumacher, Linus J; Kulesa, Paul M; McLennan, Rebecca; Baker, Ruth E; Maini, Philip K
2016-06-01
Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell-cell interactions, cell-environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions. © 2016 The Authors.
A flexible and qualitatively stable model for cell cycle dynamics including DNA damage effects.
Jeffries, Clark D; Johnson, Charles R; Zhou, Tong; Simpson, Dennis A; Kaufmann, William K
2012-01-01
This paper includes a conceptual framework for cell cycle modeling into which the experimenter can map observed data and evaluate mechanisms of cell cycle control. The basic model exhibits qualitative stability, meaning that regardless of magnitudes of system parameters its instances are guaranteed to be stable in the sense that all feasible trajectories converge to a certain trajectory. Qualitative stability can also be described by the signs of real parts of eigenvalues of the system matrix. On the biological side, the resulting model can be tuned to approximate experimental data pertaining to human fibroblast cell lines treated with ionizing radiation, with or without disabled DNA damage checkpoints. Together these properties validate a fundamental, first order systems view of cell dynamics. Classification Codes: 15A68.
Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells
Sen, Partho; Kemppainen, Esko; Orešič, Matej
2018-01-01
Human peripheral blood mononuclear cells (PBMCs) are the key drivers of the immune responses. These cells undergo activation, proliferation and differentiation into various subsets. During these processes they initiate metabolic reprogramming, which is coordinated by specific gene and protein activities. PBMCs as a model system have been widely used to study metabolic and autoimmune diseases. Herein we review various omics and systems-based approaches such as transcriptomics, epigenomics, proteomics, and metabolomics as applied to PBMCs, particularly T helper subsets, that unveiled disease markers and the underlying mechanisms. We also discuss and emphasize several aspects of T cell metabolic modeling in healthy and disease states using genome-scale metabolic models. PMID:29376056
Morabito, Caterina; Steimberg, Nathalie; Mazzoleni, Giovanna; Guarnieri, Simone; Fanò-Illic, Giorgio; Mariggiò, Maria A
2015-01-01
We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions.
Mazzoleni, Giovanna; Fanò-Illic, Giorgio; Mariggiò, Maria A.
2015-01-01
We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions. PMID:25654124
A hybrid model of cell cycle in mammals.
Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck
2016-02-01
Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication.
A systems model for immune cell interactions unravels the mechanism of inflammation in human skin.
Valeyev, Najl V; Hundhausen, Christian; Umezawa, Yoshinori; Kotov, Nikolay V; Williams, Gareth; Clop, Alex; Ainali, Crysanthi; Ouzounis, Christos; Tsoka, Sophia; Nestle, Frank O
2010-12-02
Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes.
Abroudi, Ali; Samarasinghe, Sandhya; Kulasiri, Don
2017-09-21
Not many models of mammalian cell cycle system exist due to its complexity. Some models are too complex and hard to understand, while some others are too simple and not comprehensive enough. Moreover, some essential aspects, such as the response of G1-S and G2-M checkpoints to DNA damage as well as the growth factor signalling, have not been investigated from a systems point of view in current mammalian cell cycle models. To address these issues, we bring a holistic perspective to cell cycle by mathematically modelling it as a complex system consisting of important sub-systems that interact with each other. This retains the functionality of the system and provides a clearer interpretation to the processes within it while reducing the complexity in comprehending these processes. To achieve this, we first update a published ODE mathematical model of cell cycle with current knowledge. Then the part of the mathematical model relevant to each sub-system is shown separately in conjunction with a diagram of the sub-system as part of this representation. The model sub-systems are Growth Factor, DNA damage, G1-S, and G2-M checkpoint signalling. To further simplify the model and better explore the function of sub-systems, they are further divided into modules. Here we also add important new modules of: chk-related rapid cell cycle arrest, p53 modules expanded to seamlessly integrate with the rapid arrest module, Tyrosine phosphatase modules that activate Cyc_Cdk complexes and play a crucial role in rapid and delay arrest at both G1-S and G2-M, Tyrosine Kinase module that is important for inactivating nuclear transport of CycB_cdk1 through Wee1 to resist M phase entry, Plk1-Related module that is crucial in activating Tyrosine phosphatases and inactivating Tyrosine kinase, and APC-Related module to show steps in CycB degradation. This multi-level systems approach incorporating all known aspects of cell cycle allowed us to (i) study, through dynamic simulation of an ODE model, comprehensive details of cell cycle dynamics under normal and DNA damage conditions revealing the role and value of the added new modules and elements, (ii) assess, through a global sensitivity analysis, the most influential sub-systems, modules and parameters on system response, such as G1-S and G2-M transitions, and (iii) probe deeply into the relationship between DNA damage and cell cycle progression and test the biological evidence that G1-S is relatively inefficient in arresting damaged cells compared to G2-M checkpoint. To perform sensitivity analysis, Self-Organizing Map with Correlation Coefficient Analysis (SOMCCA) is developed which shows that Growth Factor and G1-S Checkpoint sub-systems and 13 parameters in the modules within them are crucial for G1-S and G2-M transitions. To study the relative efficiency of DNA damage checkpoints, a Checkpoint Efficiency Evaluator (CEE) is developed based on perturbation studies and statistical Type II error. Accordingly, cell cycle is about 96% efficient in arresting damaged cells with G2-M checkpoint being more efficient than G1-S. Further, both checkpoint systems are near perfect (98.6%) in passing healthy cells. Thus this study has shown the efficacy of the proposed systems approach to gain a better understanding of different aspects of mammalian cell cycle system separately and as an integrated system that will also be useful in investigating targeted therapy in future cancer treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.
Statistical Modeling of Single Target Cell Encapsulation
Moon, SangJun; Ceyhan, Elvan; Gurkan, Umut Atakan; Demirci, Utkan
2011-01-01
High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems. PMID:21814548
Nichols, Joan E; Niles, Jean A; Vega, Stephanie P; Argueta, Lissenya B; Eastaway, Adriene; Cortiella, Joaquin
2014-09-01
Respiratory tract specific cell populations, or tissue engineered in vitro grown human lung, have the potential to be used as research tools to mimic physiology, toxicology, pathology, as well as infectious diseases responses of cells or tissues. Studies related to respiratory tract pathogenesis or drug toxicity testing in the past made use of basic systems where single cell populations were exposed to test agents followed by evaluations of simple cellular responses. Although these simple single-cell-type systems provided good basic information related to cellular responses, much more can be learned from cells grown in fabricated microenvironments which mimic in vivo conditions in specialized microfabricated chambers or by human tissue engineered three-dimensional (3D) models which allow for more natural interactions between cells. Recent advances in microengineering technology, microfluidics, and tissue engineering have provided a new approach to the development of 2D and 3D cell culture models which enable production of more robust human in vitro respiratory tract models. Complex models containing multiple cell phenotypes also provide a more reasonable approximation of what occurs in vivo without the confounding elements in the dynamic in vivo environment. The goal of engineering good 3D human models is the formation of physiologically functional respiratory tissue surrogates which can be used as pathogenesis models or in the case of 2D screening systems for drug therapy evaluation as well as human toxicity testing. We hope that this manuscript will serve as a guide for development of future respiratory tract model systems as well as a review of conventional models. © 2014 by the Society for Experimental Biology and Medicine.
Thoma, Eva C; Heckel, Tobias; Keller, David; Giroud, Nicolas; Leonard, Brian; Christensen, Klaus; Roth, Adrian; Bertinetti-Lapatki, Cristina; Graf, Martin; Patsch, Christoph
2016-10-25
Due to their broad differentiation potential, pluripotent stem cells (PSCs) offer a promising approach for generating relevant cellular models for various applications. While human PSC-based cellular models are already advanced, similar systems for non-human primates (NHPs) are still lacking. However, as NHPs are the most appropriate animals for evaluating the safety of many novel pharmaceuticals, the availability of in vitro systems would be extremely useful to bridge the gap between cellular and animal models. Here, we present a NHP in vitro endothelial cell system using induced pluripotent stem cells (IPSCs) from Cynomolgus monkey (Macaca fascicularis). Based on an adapted protocol for human IPSCs, we directly differentiated macaque IPSCs into endothelial cells under chemically defined conditions. The resulting endothelial cells can be enriched using immuno-magnetic cell sorting and display endothelial marker expression and function. RNA sequencing revealed that the differentiation process closely resembled vasculogenesis. Moreover, we showed that endothelial cells derived from macaque and human IPSCs are highly similar with respect to gene expression patterns and key endothelial functions, such as inflammatory responses. These data demonstrate the power of IPSC differentiation technology to generate defined cell types for use as translational in vitro models to compare cell type-specific responses across species.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomas, Dennis G.; Smith, Jordan N.; Thrall, Brian D.
The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles ion dosimetry on cellular toxicology. We developed ISD3, an extension ofmore » our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is modular, and can be adapted by application of any empirical model of dissolution, alternative approaches to calculating sedimentation rates, and cellular uptake or treatment of boundary conditions. We apply the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. The results demonstrate utility and accuracy of the ISD3 framework for dosimetry in these systems. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media has effects both on the initial rate of dissolution and the resulting near-steady state ion concentration in solution.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.
The U.S. Department of Energy (DOE) has developed a vehicle framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE’s Technical Targets using four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework model for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be easily estimated. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. Additionally, this design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the framework model and compare it to the DOE Technical Targets. These models will be explained and exercised with existing hydrogen storage materials.« less
The use of experimental design to find the operating maximum power point of PEM fuel cells
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crăciunescu, Aurelian; Pătularu, Laurenţiu; Ciumbulea, Gloria
2015-03-10
Proton Exchange Membrane (PEM) Fuel Cells are difficult to model due to their complex nonlinear nature. In this paper, the development of a PEM Fuel Cells mathematical model based on the Design of Experiment methodology is described. The Design of Experiment provides a very efficient methodology to obtain a mathematical model for the studied multivariable system with only a few experiments. The obtained results can be used for optimization and control of the PEM Fuel Cells systems.
Cell-microenvironment interactions and architectures in microvascular systems
Bersini, Simone; Yazdi, Iman K.; Talò, Giuseppe; Shin, Su Ryon; Moretti, Matteo; Khademhosseini, Ali
2016-01-01
In the past decade, significant advances have been made in the design and optimization of novel biomaterials and microfabrication techniques to generate vascularized tissues. Novel microfluidic systems have facilitated the development and optimization of in vitro models for exploring the complex pathophysiological phenomena that occur inside a microvascular environment. To date, most of these models have focused on engineering of increasingly complex systems, rather than analyzing the molecular and cellular mechanisms that drive microvascular network morphogenesis and remodeling. In fact, mutual interactions among endothelial cells (ECs), supporting mural cells and organ-specific cells, as well as between ECs and the extracellular matrix, are key driving forces for vascularization. This review focuses on the integration of materials science, microengineering and vascular biology for the development of in vitro microvascular systems. Various approaches currently being applied to study cell-cell/cell-matrix interactions, as well as biochemical/biophysical cues promoting vascularization and their impact on microvascular network formation, will be identified and discussed. Finally, this review will explore in vitro applications of microvascular systems, in vivo integration of transplanted vascularized tissues, and the important challenges for vascularization and controlling the microcirculatory system within the engineered tissues, especially for microfabrication approaches. It is likely that existing models and more complex models will further our understanding of the key elements of vascular network growth, stabilization and remodeling to translate basic research principles into functional, vascularized tissue constructs for regenerative medicine applications, drug screening and disease models. PMID:27417066
Cell-microenvironment interactions and architectures in microvascular systems.
Bersini, Simone; Yazdi, Iman K; Talò, Giuseppe; Shin, Su Ryon; Moretti, Matteo; Khademhosseini, Ali
2016-11-01
In the past decade, significant advances have been made in the design and optimization of novel biomaterials and microfabrication techniques to generate vascularized tissues. Novel microfluidic systems have facilitated the development and optimization of in vitro models for exploring the complex pathophysiological phenomena that occur inside a microvascular environment. To date, most of these models have focused on engineering of increasingly complex systems, rather than analyzing the molecular and cellular mechanisms that drive microvascular network morphogenesis and remodeling. In fact, mutual interactions among endothelial cells (ECs), supporting mural cells and organ-specific cells, as well as between ECs and the extracellular matrix, are key driving forces for vascularization. This review focuses on the integration of materials science, microengineering and vascular biology for the development of in vitro microvascular systems. Various approaches currently being applied to study cell-cell/cell-matrix interactions, as well as biochemical/biophysical cues promoting vascularization and their impact on microvascular network formation, will be identified and discussed. Finally, this review will explore in vitro applications of microvascular systems, in vivo integration of transplanted vascularized tissues, and the important challenges for vascularization and controlling the microcirculatory system within the engineered tissues, especially for microfabrication approaches. It is likely that existing models and more complex models will further our understanding of the key elements of vascular network growth, stabilization and remodeling to translate basic research principles into functional, vascularized tissue constructs for regenerative medicine applications, drug screening and disease models. Copyright © 2016 Elsevier Inc. All rights reserved.
Modeling and control of hybrid wind/photovoltaic/fuel cell distributed generation systems
NASA Astrophysics Data System (ADS)
Wang, Caisheng
Due to ever increasing energy consumption, rising public awareness of environmental protection, and steady progress in power deregulation, alternative (i.e., renewable and fuel cell based) distributed generation (DG) systems have attracted increased interest. Wind and photovoltaic (PV) power generation are two of the most promising renewable energy technologies. Fuel cell (FC) systems also show great potential in DG applications of the future due to their fast technology development and many merits they have, such as high efficiency, zero or low emission (of pollutant gases) and flexible modular structure. The modeling and control of a hybrid wind/PV/FC DG system is addressed in this dissertation. Different energy sources in the system are integrated through an AC bus. Dynamic models for the main system components, namely, wind energy conversion system (WECS), PV energy conversion system (PVECS), fuel cell, electrolyzer, power electronic interfacing circuits, battery, hydrogen storage tank, gas compressor and gas pressure regulator, are developed. Two types of fuel cells have been modeled in this dissertation: proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC). Power control of a grid-connected FC system as well as load mitigation control of a stand-alone FC system are investigated. The pitch angle control for WECS, the maximum power point tracking (MPPT) control for PVECS, and the control for electrolyzer and power electronic devices, are also addressed in the dissertation. Based on the dynamic component models, a simulation model for the proposed hybrid energy system has been developed using MATLAB/Simulink. The overall power management strategy for coordinating the power flows among the different energy sources is presented in the dissertation. Simulation studies have been carried out to verify the system performance under different scenarios using a practical load profile and real weather data. The results show that the overall power management strategy is effective and the power flows among the different energy sources and the load demand is balanced successfully. The DG's impacts on the existing power system are also investigated in this dissertation. Analytical methods for finding optimal sites to deploy DG sources in power systems are presented and verified with simulation studies.
NASA Astrophysics Data System (ADS)
Leucht, Florian; Bessler, Wolfgang G.; Kallo, Josef; Friedrich, K. Andreas; Müller-Steinhagen, H.
A sustainable future power supply requires high fuel-to-electricity conversion efficiencies even in small-scale power plants. A promising technology to reach this goal is a hybrid power plant in which a gas turbine (GT) is coupled with a solid oxide fuel cell (SOFC). This paper presents a dynamic model of a pressurized SOFC system consisting of the fuel cell stack with combustion zone and balance-of-plant components such as desulphurization, humidification, reformer, ejector and heat exchangers. The model includes thermal coupling between the different components. A number of control loops for fuel and air flows as well as power management are integrated in order to keep the system within the desired operation window. Models and controls are implemented in a MATLAB/SIMULINK environment. Different hybrid cycles proposed earlier are discussed and a preferred cycle is developed. Simulation results show the prospects of the developed modeling and control system.
Spectrophotovoltaic orbital power generation
NASA Technical Reports Server (NTRS)
Knowles, G.; Carroll, J.
1983-01-01
A subscale model of a photovoltaic power system employing spectral splitting and 1000:1 concentration was fabricated and tested. The 10-in. aperture model demonstrated 15.5% efficiency with 86% of the energy produced by a GaAs solar cell and 14% of the energy produced by an Si cell. The calculated efficiency of the system using the same solar cells, but having perfect optics, would be approximately 20%. The model design, component measurements, test results, and mathematical model are presented.
Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo
2017-01-31
Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.
DOE Office of Scientific and Technical Information (OSTI.GOV)
University of California, Berkeley; Wei, Max; Lipman, Timothy
2014-06-23
A total cost of ownership model is described for low temperature proton exchange membrane stationary fuel cell systems for combined heat and power (CHP) applications from 1-250kW and backup power applications from 1-50kW. System designs and functional specifications for these two applications were developed across the range of system power levels. Bottom-up cost estimates were made for balance of plant costs, and detailed direct cost estimates for key fuel cell stack components were derived using design-for-manufacturing-and-assembly techniques. The development of high throughput, automated processes achieving high yield are projected to reduce the cost for fuel cell stacks to the $300/kWmore » level at an annual production volume of 100 MW. Several promising combinations of building types and geographical location in the U.S. were identified for installation of fuel cell CHP systems based on the LBNL modelling tool DER CAM. Life-cycle modelling and externality assessment were done for hotels and hospitals. Reduced electricity demand charges, heating credits and carbon credits can reduce the effective cost of electricity ($/kWhe) by 26-44percent in locations such as Minneapolis, where high carbon intensity electricity from the grid is displaces by a fuel cell system operating on reformate fuel. This project extends the scope of existing cost studies to include externalities and ancillary financial benefits and thus provides a more comprehensive picture of fuel cell system benefits, consistent with a policy and incentive environment that increasingly values these ancillary benefits. The project provides a critical, new modelling capacity and should aid a broad range of policy makers in assessing the integrated costs and benefits of fuel cell systems versus other distributed generation technologies.« less
Population-expression models of immune response
NASA Astrophysics Data System (ADS)
Stromberg, Sean P.; Antia, Rustom; Nemenman, Ilya
2013-06-01
The immune response to a pathogen has two basic features. The first is the expansion of a few pathogen-specific cells to form a population large enough to control the pathogen. The second is the process of differentiation of cells from an initial naive phenotype to an effector phenotype which controls the pathogen, and subsequently to a memory phenotype that is maintained and responsible for long-term protection. The expansion and the differentiation have been considered largely independently. Changes in cell populations are typically described using ecologically based ordinary differential equation models. In contrast, differentiation of single cells is studied within systems biology and is frequently modeled by considering changes in gene and protein expression in individual cells. Recent advances in experimental systems biology make available for the first time data to allow the coupling of population and high dimensional expression data of immune cells during infections. Here we describe and develop population-expression models which integrate these two processes into systems biology on the multicellular level. When translated into mathematical equations, these models result in non-conservative, non-local advection-diffusion equations. We describe situations where the population-expression approach can make correct inference from data while previous modeling approaches based on common simplifying assumptions would fail. We also explore how model reduction techniques can be used to build population-expression models, minimizing the complexity of the model while keeping the essential features of the system. While we consider problems in immunology in this paper, we expect population-expression models to be more broadly applicable.
Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.
2012-01-01
In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894
Comparing ESC and iPSC-Based Models for Human Genetic Disorders.
Halevy, Tomer; Urbach, Achia
2014-10-24
Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.
Development of a human adaptive immune system in cord blood cell-transplanted mice.
Traggiai, Elisabetta; Chicha, Laurie; Mazzucchelli, Luca; Bronz, Lucio; Piffaretti, Jean-Claude; Lanzavecchia, Antonio; Manz, Markus G
2004-04-02
Because ethical restrictions limit in vivo studies of the human hemato-lymphoid system, substitute human to small animal xenotransplantation models have been employed. Existing models, however, sustain only limited development and maintenance of human lymphoid cells and rarely produce immune responses. Here we show that intrahepatic injection of CD34+ human cord blood cells into conditioned newborn Rag2-/-gammac-/- mice leads to de novo development of B, T, and dendritic cells; formation of structured primary and secondary lymphoid organs; and production of functional immune responses. This provides a valuable model to study development and function of the human adaptive immune system in vivo.
Thomas, Dennis G; Smith, Jordan N; Thrall, Brian D; Baer, Donald R; Jolley, Hadley; Munusamy, Prabhakaran; Kodali, Vamsi; Demokritou, Philip; Cohen, Joel; Teeguarden, Justin G
2018-01-25
The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles and ion dosimetry on cellular toxicology. We developed ISD3, an extension of our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. We applied the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media affects the initial rate of dissolution and the resulting near-steady state ion concentration in solution for the systems we have studied. By combining experiments and modeling, we were able to quantify the influence of proteins on silver particle solubility, determine the relative amounts of silver ions and particles in exposed cells, and demonstrate the influence of particle size changes resulting from dissolution on particle delivery to cells in culture. ISD3 is modular and can be adapted to new applications by replacing descriptions of dissolution, sedimentation and boundary conditions with those appropriate for particles other than silver.
Evaluation of a load cell model for dynamic calibration of the rotor systems research aircraft
NASA Technical Reports Server (NTRS)
Duval, R. W.; Bahrami, H.; Wellman, B.
1985-01-01
The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission system from the fuselage. An analytical model of the relationship between applied rotor loads and the resulting load cell measurements is derived by applying a force-and-moment balance to the isolated rotor/transmission system. The model is then used to estimate the applied loads from measured load cell data, as obtained from a ground-based shake test. Using nominal design values for the parameters, the estimation errors, for the case of lateral forcing, were shown to be on the order of the sensor measurement noise in all but the roll axis. An unmodeled external load appears to be the source of the error in this axis.
Quantum entanglement in photoactive prebiotic systems.
Tamulis, Arvydas; Grigalavicius, Mantas
2014-06-01
This paper contains the review of quantum entanglement investigations in living systems, and in the quantum mechanically modelled photoactive prebiotic kernel systems. We define our modelled self-assembled supramolecular photoactive centres, composed of one or more sensitizer molecules, precursors of fatty acids and a number of water molecules, as a photoactive prebiotic kernel systems. We propose that life first emerged in the form of such minimal photoactive prebiotic kernel systems and later in the process of evolution these photoactive prebiotic kernel systems would have produced fatty acids and covered themselves with fatty acid envelopes to become the minimal cells of the Fatty Acid World. Specifically, we model self-assembling of photoactive prebiotic systems with observed quantum entanglement phenomena. We address the idea that quantum entanglement was important in the first stages of origins of life and evolution of the biospheres because simultaneously excite two prebiotic kernels in the system by appearance of two additional quantum entangled excited states, leading to faster growth and self-replication of minimal living cells. The quantum mechanically modelled possibility of synthesizing artificial self-reproducing quantum entangled prebiotic kernel systems and minimal cells also impacts the possibility of the most probable path of emergence of protocells on the Earth or elsewhere. We also examine the quantum entangled logic gates discovered in the modelled systems composed of two prebiotic kernels. Such logic gates may have application in the destruction of cancer cells or becoming building blocks of new forms of artificial cells including magnetically active ones.
The Dynamics of HPV Infection and Cervical Cancer Cells.
Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan
2016-01-01
The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.
Wienecke, Sarah; Ishwarbhai, Alka; Tsipa, Argyro; Aw, Rochelle; Kylilis, Nicolas; Bell, David J.; McClymont, David W.; Jensen, Kirsten; Biedendieck, Rebekka
2018-01-01
Native cell-free transcription–translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription–translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription–translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications. PMID:29666238
An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...
Three-dimensional Myoblast Aggregates--Effects of Modeled Microgravity
NASA Technical Reports Server (NTRS)
Byerly, Diane; Sognier, M. A.; Marquette, M. L.
2006-01-01
The overall objective of these studies is to elucidate the molecular and cellular alterations that contribute to muscle atrophy in astronauts caused by exposure to microgravity conditions in space. To accomplish this, a three-dimensional model test system was developed using mouse myoblast cells (C2C12). Myoblast cells were grown as three-dimensional aggregates (without scaffolding or other solid support structures) in both modeled microgravity (Rotary Cell Culture System, Synthecon, Inc.) and at unit gravity in coated Petri dishes. Evaluation of H&E stained thin sections of the aggregates revealed the absence of any necrosis. Confocal microscopy evaluations of cells stained with the Live/Dead assay (Molecular Probes) confirmed that viable cells were present throughout the aggregates with an average of only three dead cells observed per aggregate. Preliminary results from gene array analysis (Affymetrix chip U74Av2) showed that approximately 14% of the genes were down regulated (decreased more than 3 fold) and 4% were upregulated in cells exposed to modeled microgravity for 12 hours compared to unit gravity controls. Additional studies using fluorescent phallacidin revealed a decrease in F-actin in the cells exposed to modeled microgravity compared to unit gravity. Myoblast cells grown as aggregates in modeled microgravity exhibited spontaneous differentiation into syncitia while no differentiation was seen in the unit gravity controls. These studies show that 1)the model test system developed is suitable for assessing cellular and molecular alterations in myoblasts; 2) gene expression alterations occur rapidly (within 12 hours) following exposure to modeled microgravity; and 3) modeled microgravity conditions stimulated myoblast cell differentiation. Achieving a greater understanding of the molecular alterations leading to muscle atrophy will eventually enable the development of cell-based countermeasures, which may be valuable for treatment of muscle diseases on Earth and future space explorations.
Correa de Sampaio, Pedro; Auslaender, David; Krubasik, Davia; Failla, Antonio Virgilio; Skepper, Jeremy N.; Murphy, Gillian; English, William R.
2012-01-01
Angiogenesis, the formation of new blood vessels, is an essential process for tumour progression and is an area of significant therapeutic interest. Different in vitro systems and more complex in vivo systems have been described for the study of tumour angiogenesis. However, there are few human 3D in vitro systems described to date which mimic the cellular heterogeneity and complexity of angiogenesis within the tumour microenvironment. In this study we describe the Minitumour model – a 3 dimensional human spheroid-based system consisting of endothelial cells and fibroblasts in co-culture with the breast cancer cell line MDA-MB-231, for the study of tumour angiogenesis in vitro. After implantation in collagen-I gels, Minitumour spheroids form quantifiable endothelial capillary-like structures. The endothelial cell pre-capillary sprouts are supported by the fibroblasts, which act as mural cells, and their growth is increased by the presence of cancer cells. Characterisation of the Minitumour model using small molecule inhibitors and inhibitory antibodies show that endothelial sprout formation is dependent on growth factors and cytokines known to be important for tumour angiogenesis. The model also shows a response to anti-angiogenic agents similar to previously described in vivo data. We demonstrate that independent manipulation of the different cell types is possible, using common molecular techniques, before incorporation into the model. This aspect of Minitumour spheroid analysis makes this model ideal for high content studies of gene function in individual cell types, allowing for the dissection of their roles in cell-cell interactions. Finally, using this technique, we were able to show the requirement of the metalloproteinase MT1-MMP in endothelial cells and fibroblasts, but not cancer cells, for sprouting angiogenesis. PMID:22363483
An open-access microfluidic model for lung-specific functional studies at an air-liquid interface.
Nalayanda, Divya D; Puleo, Christopher; Fulton, William B; Sharpe, Leilani M; Wang, Tza-Huei; Abdullah, Fizan
2009-10-01
In an effort to improve the physiologic relevance of existing in vitro models for alveolar cells, we present a microfluidic platform which provides an air-interface in a dynamic system combining microfluidic and suspended membrane culture systems. Such a system provides the ability to manipulate multiple parameters on a single platform along with ease in cell seeding and manipulation. The current study presents a comparison of the efficacy of the hybrid system with conventional platforms using assays analyzing the maintenance of function and integrity of A549 alveolar epithelial cell monolayer cultures. The hybrid system incorporates bio-mimetic nourishment on the basal side of the epithelial cells along with an open system on the apical side of the cells exposed to air allowing for easy access for assays.
NASA Astrophysics Data System (ADS)
Zhou, Lingfei; Chapuis, Yves-Andre; Blonde, Jean-Philippe; Bervillier, Herve; Fukuta, Yamato; Fujita, Hiroyuki
2004-07-01
In this paper, the authors proposed to study a model and a control strategy of a two-dimensional conveyance system based on the principles of the Autonomous Decentralized Microsystems (ADM). The microconveyance system is based on distributed cooperative MEMS actuators which can produce a force field onto the surface of the device to grip and move a micro-object. The modeling approach proposed here is based on a simple model of a microconveyance system which is represented by a 5 x 5 matrix of cells. Each cell is consisted of a microactuator, a microsensor, and a microprocessor to provide actuation, autonomy and decentralized intelligence to the cell. Thus, each cell is able to identify a micro-object crossing on it and to decide by oneself the appropriate control strategy to convey the micro-object to its destination target. The control strategy could be established through five simple decision rules that the cell itself has to respect at each calculate cycle time. Simulation and FPGA implementation results are given in the end of the paper in order to validate model and control approach of the microconveyance system.
A tidal wave of signals: calcium and ROS at the forefront of rapid systemic signaling.
Gilroy, Simon; Suzuki, Nobuhiro; Miller, Gad; Choi, Won-Gyu; Toyota, Masatsugu; Devireddy, Amith R; Mittler, Ron
2014-10-01
Systemic signaling pathways enable multicellular organisms to prepare all of their tissues and cells to an upcoming challenge that may initially only be sensed by a few local cells. They are activated in plants in response to different stimuli including mechanical injury, pathogen infection, and abiotic stresses. Key to the mobilization of systemic signals in higher plants are cell-to-cell communication events that have thus far been mostly unstudied. The recent identification of systemically propagating calcium (Ca(2+)) and reactive oxygen species (ROS) waves in plants has unraveled a new and exciting cell-to-cell communication pathway that, together with electric signals, could provide a working model demonstrating how plant cells transmit long-distance signals via cell-to-cell communication mechanisms. Here, we summarize recent findings on the ROS and Ca(2+) waves and outline a possible model for their integration. Copyright © 2014 Elsevier Ltd. All rights reserved.
Role of Microenvironment in Glioma Invasion: What We Learned from In Vitro Models
Manini, Ivana; Caponnetto, Federica; Bartolini, Anna; Ius, Tamara; Mariuzzi, Laura; Di Loreto, Carla; Cesselli, Daniela
2018-01-01
The invasion properties of glioblastoma hamper a radical surgery and are responsible for its recurrence. Understanding the invasion mechanisms is thus critical to devise new therapeutic strategies. Therefore, the creation of in vitro models that enable these mechanisms to be studied represents a crucial step. Since in vitro models represent an over-simplification of the in vivo system, in these years it has been attempted to increase the level of complexity of in vitro assays to create models that could better mimic the behaviour of the cells in vivo. These levels of complexity involved: 1. The dimension of the system, moving from two-dimensional to three-dimensional models; 2. The use of microfluidic systems; 3. The use of mixed cultures of tumour cells and cells of the tumour micro-environment in order to mimic the complex cross-talk between tumour cells and their micro-environment; 4. And the source of cells used in an attempt to move from commercial lines to patient-based models. In this review, we will summarize the evidence obtained exploring these different levels of complexity and highlighting advantages and limitations of each system used. PMID:29300332
Multiscale modeling of mucosal immune responses
2015-01-01
Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787
Multiscale modeling of mucosal immune responses.
Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep
2015-01-01
Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.
A discrete model of Drosophila eggshell patterning reveals cell-autonomous and juxtacrine effects.
Fauré, Adrien; Vreede, Barbara M I; Sucena, Elio; Chaouiya, Claudine
2014-03-01
The Drosophila eggshell constitutes a remarkable system for the study of epithelial patterning, both experimentally and through computational modeling. Dorsal eggshell appendages arise from specific regions in the anterior follicular epithelium that covers the oocyte: two groups of cells expressing broad (roof cells) bordered by rhomboid expressing cells (floor cells). Despite the large number of genes known to participate in defining these domains and the important modeling efforts put into this developmental system, key patterning events still lack a proper mechanistic understanding and/or genetic basis, and the literature appears to conflict on some crucial points. We tackle these issues with an original, discrete framework that considers single-cell models that are integrated to construct epithelial models. We first build a phenomenological model that reproduces wild type follicular epithelial patterns, confirming EGF and BMP signaling input as sufficient to establish the major features of this patterning system within the anterior domain. Importantly, this simple model predicts an instructive juxtacrine signal linking the roof and floor domains. To explore this prediction, we define a mechanistic model that integrates the combined effects of cellular genetic networks, cell communication and network adjustment through developmental events. Moreover, we focus on the anterior competence region, and postulate that early BMP signaling participates with early EGF signaling in its specification. This model accurately simulates wild type pattern formation and is able to reproduce, with unprecedented level of precision and completeness, various published gain-of-function and loss-of-function experiments, including perturbations of the BMP pathway previously seen as conflicting results. The result is a coherent model built upon rules that may be generalized to other epithelia and developmental systems.
Three-dimensional hydrogel cell culture systems for modeling neural tissue
NASA Astrophysics Data System (ADS)
Frampton, John
Two-dimensional (2-D) neural cell culture systems have served as physiological models for understanding the cellular and molecular events that underlie responses to physical and chemical stimuli, control sensory and motor function, and lead to the development of neurological diseases. However, the development of three-dimensional (3-D) cell culture systems will be essential for the advancement of experimental research in a variety of fields including tissue engineering, chemical transport and delivery, cell growth, and cell-cell communication. In 3-D cell culture, cells are provided with an environment similar to tissue, in which they are surrounded on all sides by other cells, structural molecules and adhesion ligands. Cells grown in 3-D culture systems display morphologies and functions more similar to those observed in vivo, and can be cultured in such a way as to recapitulate the structural organization and biological properties of tissue. This thesis describes a hydrogel-based culture system, capable of supporting the growth and function of several neural cell types in 3-D. Alginate hydrogels were characterized in terms of their biomechanical and biochemical properties and were functionalized by covalent attachment of whole proteins and peptide epitopes. Methods were developed for rapid cross-linking of alginate hydrogels, thus permitting the incorporation of cells into 3-D scaffolds without adversely affecting cell viability or function. A variety of neural cell types were tested including astrocytes, microglia, and neurons. Cells remained viable and functional for longer than two weeks in culture and displayed process outgrowth in 3-D. Cell constructs were created that varied in cell density, type and organization, providing experimental flexibility for studying cell interactions and behavior. In one set of experiments, 3-D glial-endothelial cell co-cultures were used to model blood-brain barrier (BBB) structure and function. This co-culture system was designed for use as a tool to predict the transport and processing that occurs prior to drug uptake in the central nervous system (CNS), and to predict BBB permeability. Electrochemical techniques and immunohistochemistry were used to validate this model and provide detailed information about cellular organization and function. Electrochemical impedance spectroscopy (EIS) provided evidence that endothelial cells cultured in the presence of astrocytes formed tight junctions capable of occluding the flow of electrical current. In a second series of experiments, a microglia-astrocyte co-culture system was developed to assess the effects of glial cells on electrode impedance recorded from neural prosthetic devices in vitro. Impedance measurements were compared with confocal images to determine the effects of glial cell density and cell type on electrode performance. The results indicate that EIS data can be used to model components of the reactive cell responses in brain tissue, and that impedance measurements recorded in vitro can be compared to measurements recorded in vivo. Taken together, these results demonstrate that alginate hydrogels can be used for the creation of 3-D neural cell scaffolds, and that such cell scaffolds can be used to model a variety of three-dimensional neural tissues in vitro, that cannot be studied in 2-D cultures.
Oxygen supply for CHO cells immobilized on a packed-bed of Fibra-Cel disks.
Meuwly, F; Loviat, F; Ruffieux, P-A; Bernard, A R; Kadouri, A; von Stockar, U
2006-03-05
Packed-bed bioreactors (PBR) have proven to be efficient systems to culture mammalian cells at very high cell density in perfusion mode, thus leading to very high volumetric productivity. However, the immobilized cells must be continuously supplied with all nutrients in sufficient quantities to remain viable and productive over the full duration of the perfusion culture. Among all nutrients, oxygen is the most critical since it is present at very low concentration due to its low solubility in cell culture medium. This work presents the development of a model for oxygenation in a packed-bed bioreactor system. The experimental system used to develop the model was a packed-bed of Fibra-Cel disk carriers used to cultivate Chinese Hamster Ovary cells at high density ( approximately 6.1 x 10(7) cell/mL) in perfusion mode. With the help of this model, it was possible to identify if a PBR system is operated in optimal or sub-optimal conditions. Using the model, two options were proposed, which could improve the performance of the basal system by about twofold, that is, by increasing the density of immobilized cells per carrier volume from 6.1 x 10(7) to 1.2 x 10(8) cell/mL, or by increasing the packed-bed height from 0.2 to 0.4 m. Both strategies would be rather simple to test and implement in the packed-bed bioreactor system used for this study. As a result, it would be possible to achieve a substantial improvement of about twofold higher productivity as compared with the basal conditions.
NASA Astrophysics Data System (ADS)
Eftimie, Raluca
2015-03-01
One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).
A hybrid agent-based approach for modeling microbiological systems.
Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing
2008-11-21
Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.
Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lewis, Daniel D.; Department of Biomedical Engineering, University of California Davis, Davis, CA; Villarreal, Fernando D.
As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with amore » special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.« less
Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems
Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng
2014-01-01
As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems. PMID:25538941
Synthetic biology outside the cell: linking computational tools to cell-free systems.
Lewis, Daniel D; Villarreal, Fernando D; Wu, Fan; Tan, Cheemeng
2014-01-01
As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.
Bibi, Siham; Zhang, Yanyan; Hugonin, Caroline; Mangean, Mallorie Depond; He, Liang; Wedeh, Ghaith; Launay, Jean-Marie; Van Rijn, Sjoerd; Würdinger, Thomas; Louache, Fawzia; Arock, Michel
2016-01-01
Systemic mastocytosis are rare neoplasms characterized by accumulation of mast cells in at least one internal organ. The majority of systemic mastocytosis patients carry KIT D816V mutation, which activates constitutively the KIT receptor. Patient with advanced forms of systemic mastocytosis, such as aggressive systemic mastocytosis or mast cell leukemia, are poorly treated to date. Unfortunately, the lack of in vivo models reflecting KIT D816V+ advanced disease hampers pathophysiological studies and preclinical development of new therapies for such patients. Here, we describe a new in vivo model of KIT D816V+ advanced systemic mastocytosis developed by transplantation of the human ROSAKIT D816V-Gluc mast cell line in NOD-SCID IL-2R g−/− mice, using Gaussia princeps luciferase as a reporter. Intravenous injection of ROSAKIT D816V-Gluc cells led, in 4 weeks, to engraftment in all injected primary recipient mice. Engrafted cells were found at high levels in bone marrow, and at lower levels in spleen, liver and peripheral blood. Disease progression was easily monitored by repeated quantification of Gaussia princeps luciferase activity in peripheral blood. This quantification evidenced a linear relationship between the number of cells injected and the neoplastic mast cell burden in mice. Interestingly, the secondary transplantation of ROSAKIT D816V-Gluc cells increased their engraftment capability. To conclude, this new in vivo model mimics at the best the features of human KIT D816V+ advanced systemic mastocytosis. In addition, it is a unique and convenient tool to study the kinetics of the disease and the potential in vivo activity of new drugs targeting neoplastic mast cells. PMID:27783996
Bibi, Siham; Zhang, Yanyan; Hugonin, Caroline; Mangean, Mallorie Depond; He, Liang; Wedeh, Ghaith; Launay, Jean-Marie; Van Rijn, Sjoerd; Würdinger, Thomas; Louache, Fawzia; Arock, Michel
2016-12-13
Systemic mastocytosis are rare neoplasms characterized by accumulation of mast cells in at least one internal organ. The majority of systemic mastocytosis patients carry KIT D816V mutation, which activates constitutively the KIT receptor. Patient with advanced forms of systemic mastocytosis, such as aggressive systemic mastocytosis or mast cell leukemia, are poorly treated to date. Unfortunately, the lack of in vivo models reflecting KIT D816V+ advanced disease hampers pathophysiological studies and preclinical development of new therapies for such patients. Here, we describe a new in vivo model of KIT D816V+ advanced systemic mastocytosis developed by transplantation of the human ROSAKIT D816V-Gluc mast cell line in NOD-SCID IL-2R γ-/- mice, using Gaussia princeps luciferase as a reporter. Intravenous injection of ROSAKIT D816V-Gluc cells led, in 4 weeks, to engraftment in all injected primary recipient mice. Engrafted cells were found at high levels in bone marrow, and at lower levels in spleen, liver and peripheral blood. Disease progression was easily monitored by repeated quantification of Gaussia princeps luciferase activity in peripheral blood. This quantification evidenced a linear relationship between the number of cells injected and the neoplastic mast cell burden in mice. Interestingly, the secondary transplantation of ROSAKIT D816V-Gluc cells increased their engraftment capability. To conclude, this new in vivo model mimics at the best the features of human KIT D816V+ advanced systemic mastocytosis. In addition, it is a unique and convenient tool to study the kinetics of the disease and the potential in vivo activity of new drugs targeting neoplastic mast cells.
Running and rotating: modelling the dynamics of migrating cell clusters
NASA Astrophysics Data System (ADS)
Copenhagen, Katherine; Gov, Nir; Gopinathan, Ajay
Collective motion of cells is a common occurrence in many biological systems, including tissue development and repair, and tumor formation. Recent experiments have shown cells form clusters in a chemical gradient, which display three different phases of motion: translational, rotational, and random. We present a model for cell clusters based loosely on other models seen in the literature that involves a Vicsek-like alignment as well as physical collisions and adhesions between cells. With this model we show that a mechanism for driving rotational motion in this kind of system is an increased motility of rim cells. Further, we examine the details of the relationship between rim and core cells, and find that the phases of the cluster as a whole are correlated with the creation and annihilation of topological defects in the tangential component of the velocity field.
Magrofuoco, Enrico; Elvassore, Nicola; Doyle, Francis J
2012-01-01
Three-dimensional (3D) cell cultures in bioreactors are becoming relevant as models for biological and physiological in vitro studies. In such systems, mathematical models can assist the experiment design that links the macroscopic properties to single-cell responses. We investigated the relationship between biochemical stimuli and cell response within a 3D cell culture in scaffold with heterogeneous porosity. Specifically, we studied the effect of insulin on the local glucose metabolism as a function of 3D pore size distribution. The multiscale mathematical model combines the mass transport within a 3D scaffold and a signaling pathways model. It considers the scaffold heterogeneity, and it describes spatiotemporal concentration of metabolites, biochemical stimuli, and cell density. The signaling model was integrated into this model, linking the local insulin concentration at cell membrane to the glucose uptake rate through glucose transporter type 4 (GLUT4) translocation from the cytosol to the cell membrane. The integrated model determines the cell response heterogeneities in a single channel, hence the biological response distribution in a 3D system. It also provides macroscopic outcomes to evaluate the feasibility of an experimental measurement of the system response. From our analysis, it became apparent that the flow rate is the most important operative variable, and that an optimum value ensures a fast and detectable cell response. This model on insulin-dependent glucose consumption rate offers insight into the cell metabolism physiology, which is a fundamental requirement for the study metabolic disorder such as Type 2 diabetes mellitus, in which the physiological insulin-dependent glucose metabolism is impaired. Copyright © 2012 American Institute of Chemical Engineers (AIChE).
Computer modeling describes gravity-related adaptation in cell cultures.
Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny
2009-12-16
Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.
Katsuoka, Yuichi; Ohta, Hiroki; Fujimoto, Eisuke; Izuhara, Luna; Yokote, Shinya; Kurihara, Sho; Yamanaka, Shuichiro; Tajiri, Susumu; Chikaraish, Tatsuya; Okano, Hirotaka J; Yokoo, Takashi
2016-04-01
Mesenchymal stem cell therapy in renal failure is rarely used because of low rates of cell engraftment after systemic delivery. Repeated intra-arterial cell administration may improve results; however, no current delivery method permits repeated intra-arterial infusions in a rat model. In this study, we developed an intra-arterial delivery system for repeated stem cell infusion via the aorta, catheterizing the left femoral artery to the suprarenal aorta under fluoroscopic guidance in rats with adenosine-induced renal failure. First, we compared our intra-arterial catheter system (C group, n = 3) with tail vein injection (V group, n = 3) for engraftment efficacy, using mesenchymal stem cells from luciferase transgenic rats. Rats were infused with the cells and euthanized the following day; we performed cell-tracking experiments using a bioluminescence imaging system to assess the distribution of the infused cells. Second, we assessed the safety of the system over a 30-day period in a second group of six rats receiving infusions every 7 days. Cells infused through our delivery system efficiently engrafted into the kidney, compared with peripheral venous infusion. In five of the six rats in the safety study, the delivery system remained patent for at least 9 days (range, 9-24 days). Complications became evident only after 10 days. Our intra-arterial catheter system was effective in delivering cells to the kidney and permitted repeated injection of cells.
Space power systems technology
NASA Technical Reports Server (NTRS)
Coulman, George A.
1994-01-01
Reported here is a series of studies which examine several potential catalysts and electrodes for some fuel cell systems, some materials for space applications, and mathematical modeling and performance predictions for some solid oxide fuel cells and electrolyzers. The fuel cell systems have a potential for terrestrial applications in addition to solar energy conversion in space applications. Catalysts and electrodes for phosphoric acid fuel cell systems and for polymer electrolyte membrane (PEM) fuel cell and electrolyzer systems were examined.
Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems
NASA Astrophysics Data System (ADS)
Wang, Rongrong; Qi, Liang; Xie, Xiaofeng; Ding, Qingqing; Li, Chunwen; Ma, ChenChi M.
The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system.
Cell cycle dynamics in a response/signalling feedback system with a gap.
Gong, Xue; Buckalew, Richard; Young, Todd; Boczko, Erik
2014-01-01
We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.
Ultrathin Ceramic Membranes as Scaffolds for Functional Cell Coculture Models on a Biomimetic Scale
Jud, Corinne; Ahmed, Sher; Müller, Loretta; Kinnear, Calum; Vanhecke, Dimitri; Umehara, Yuki; Frey, Sabine; Liley, Martha; Angeloni, Silvia; Petri-Fink, Alke; Rothen-Rutishauser, Barbara
2015-01-01
Abstract Epithelial tissue serves as an interface between biological compartments. Many in vitro epithelial cell models have been developed as an alternative to animal experiments to answer a range of research questions. These in vitro models are grown on permeable two-chamber systems; however, commercially available, polymer-based cell culture inserts are around 10 μm thick. Since the basement membrane found in biological systems is usually less than 1 μm thick, the 10-fold thickness of cell culture inserts is a major limitation in the establishment of realistic models. In this work, an alternative insert, accommodating an ultrathin ceramic membrane with a thickness of only 500 nm (i.e., the Silicon nitride Microporous Permeable Insert [SIMPLI]-well), was produced and used to refine an established human alveolar barrier coculture model by both replacing the conventional inserts with the SIMPLI-well and completing it with endothelial cells. The structural–functional relationship of the model was evaluated, including the translocation of gold nanoparticles across the barrier, revealing a higher translocation if compared to corresponding polyethylene terephthalate (PET) membranes. This study demonstrates the power of the SIMPLI-well system as a scaffold for epithelial tissue cell models on a truly biomimetic scale, allowing construction of more functionally accurate models of human biological barriers. PMID:26713225
Computational modeling of epidermal cell fate determination systems.
Ryu, Kook Hui; Zheng, Xiaohua; Huang, Ling; Schiefelbein, John
2013-02-01
Cell fate decisions are of primary importance for plant development. Their simple 'either-or' outcome and dynamic nature has attracted the attention of computational modelers. Recent efforts have focused on modeling the determination of several epidermal cell types in the root and shoot of Arabidopsis where many molecular components have been defined. Results of integrated modeling and molecular biology experimentation in these systems have highlighted the importance of competitive positive and negative factors and interconnected feedback loops in generating flexible yet robust mechanisms for establishing distinct gene expression programs in neighboring cells. These models have proven useful in judging hypotheses and guiding future research. Copyright © 2012 Elsevier Ltd. All rights reserved.
An adaptive state of charge estimation approach for lithium-ion series-connected battery system
NASA Astrophysics Data System (ADS)
Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael
2018-07-01
Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.
Synapse fits neuron: joint reduction by model inversion.
van der Scheer, H T; Doelman, A
2017-08-01
In this paper, we introduce a novel simplification method for dealing with physical systems that can be thought to consist of two subsystems connected in series, such as a neuron and a synapse. The aim of our method is to help find a simple, yet convincing model of the full cascade-connected system, assuming that a satisfactory model of one of the subsystems, e.g., the neuron, is already given. Our method allows us to validate a candidate model of the full cascade against data at a finer scale. In our main example, we apply our method to part of the squid's giant fiber system. We first postulate a simple, hypothetical model of cell-to-cell signaling based on the squid's escape response. Then, given a FitzHugh-type neuron model, we derive the verifiable model of the squid giant synapse that this hypothesis implies. We show that the derived synapse model accurately reproduces synaptic recordings, hence lending support to the postulated, simple model of cell-to-cell signaling, which thus, in turn, can be used as a basic building block for network models.
NASA Astrophysics Data System (ADS)
Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir
2016-09-01
We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.
NASA Astrophysics Data System (ADS)
Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir
We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.
Zebrafish hair cell mechanics and physiology through the lens of noise-induced hair cell death
NASA Astrophysics Data System (ADS)
Coffin, Allison B.; Xu, Jie; Uribe, Phillip M.
2018-05-01
Hair cells are exquisitely sensitive to auditory stimuli, but also to damage from a variety of sources including noise trauma and ototoxic drugs. Mammals cannot regenerate cochlear hair cells, while non-mammalian vertebrates exhibit robust regenerative capacity. Our research group uses the lateral line system of larval zebrafish to explore the mechanisms underlying hair cell damage, identify protective therapies, and determine molecular drivers of innate regeneration. The lateral line system contains externally located sensory organs called neuromasts, each composed of ˜8-20 hair cells. Lateral line hair cells are homologous to vertebrate inner ear hair cells and share similar susceptibility to ototoxic damage. In the last decade, the lateral line has emerged as a powerful model system for understanding hair cell death mechanisms and for identifying novel protective compounds. Here we demonstrate that the lateral line is a tractable model for noise-induced hair cell death. We have developed a novel noise damage system capable of inducing over 50% loss of lateral line hair cells, with hair cell death occurring in a dose- and time-dependent manner. Cell death is greatest 72 hours post-exposure. However, early signs of hair cell damage, including changes in membrane integrity and reduced mechanotransduction, are apparent within hours of noise exposure. These features, early signs of damage followed by delayed hair cell death, are consistent with mammalian data, suggesting that noise acts similarly on zebrafish and mammalian hair cells. In our future work we will use our new model system to investigate noise damage events in real time, and to develop protective therapies for future translational research.
NASA Astrophysics Data System (ADS)
Various papers on photovoltaics are presented. The general topics considered include: amorphous materials and cells; amorphous silicon-based solar cells and modules; amorphous silicon-based materials and processes; amorphous materials characterization; amorphous silicon; high-efficiency single crystal solar cells; multijunction and heterojunction cells; high-efficiency III-V cells; modeling and characterization of high-efficiency cells; LIPS flight experience; space mission requirements and technology; advanced space solar cell technology; space environmental effects and modeling; space solar cell and array technology; terrestrial systems and array technology; terrestrial utility and stand-alone applications and testing; terrestrial concentrator and storage technology; terrestrial stand-alone systems applications; terrestrial systems test and evaluation; terrestrial flatplate and concentrator technology; use of polycrystalline materials; polycrystalline II-VI compound solar cells; analysis of and fabrication procedures for compound solar cells.
Dynamic self-organisation of haematopoiesis and (a)symmetric cell division.
Måløy, Marthe; Måløy, Frode; Jakobsen, Per; Olav Brandsdal, Bjørn
2017-02-07
A model of haematopoiesis that links self-organisation with symmetric and asymmetric cell division is presented in this paper. It is assumed that all cell divisions are completely random events, and that the daughter cells resulting from symmetric and asymmetric stem cell divisions are, in general, phenotypically identical, and still, the haematopoietic system has the flexibility to self-renew, produce mature cells by differentiation, and regenerate undifferentiated and differentiated cells when necessary, due to self-organisation. As far as we know, no previous model implements symmetric and asymmetric division as the result of self-organisation. The model presented in this paper is inspired by experiments on the Drosophila germline stem cell, which imply that under normal conditions, the stem cells typically divide asymmetrically, whereas during regeneration, the rate of symmetric division increases. Moreover, the model can reproduce several of the results from experiments on female Safari cats. In particular, the model can explain why significant fluctuation in the phenotypes of haematopoietic cells was observed in some cats, when the haematopoietic system had reached normal population level after regeneration. To our knowledge, no previous model of haematopoiesis in Safari cats has captured this phenomenon. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Mechano-logical model of C. elegans germ line suggests feedback on the cell cycle
Atwell, Kathryn; Qin, Zhao; Gavaghan, David; Kugler, Hillel; Hubbard, E. Jane Albert; Osborne, James M.
2015-01-01
The Caenorhabditis elegans germ line is an outstanding model system in which to study the control of cell division and differentiation. Although many of the molecules that regulate germ cell proliferation and fate decisions have been identified, how these signals interact with cellular dynamics and physical forces within the gonad remains poorly understood. We therefore developed a dynamic, 3D in silico model of the C. elegans germ line, incorporating both the mechanical interactions between cells and the decision-making processes within cells. Our model successfully reproduces key features of the germ line during development and adulthood, including a reasonable ovulation rate, correct sperm count, and appropriate organization of the germ line into stably maintained zones. The model highlights a previously overlooked way in which germ cell pressure may influence gonadogenesis, and also predicts that adult germ cells might be subject to mechanical feedback on the cell cycle akin to contact inhibition. We provide experimental data consistent with the latter hypothesis. Finally, we present cell trajectories and ancestry recorded over the course of a simulation. The novel approaches and software described here link mechanics and cellular decision-making, and are applicable to modeling other developmental and stem cell systems. PMID:26428008
Use of the HepaRG Cell Line to Assess Potential Human Hepatotoxicity of ToxCast™ Chemicals
The HepaRG cell line is a promising model system for predicting human hepatotoxicity in part because of the greater capacity to metabolize chemicals than other cell models. We hypothesized that this cell line would be a relevant model for toxicity testing of industrial chemicals....
New tools for the analysis of glial cell biology in Drosophila.
Awasaki, Takeshi; Lee, Tzumin
2011-09-01
Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.
Alzheimer’s in 3D culture: Challenges and perspectives
D'Avanzo, Carla; Aronson, Jenna; Kim, Young Hye; Choi, Se Hoon; Tanzi, Rudolph E.; Kim, Doo Yeon
2015-01-01
Summary Alzheimer’s disease (AD) is the most common cause of dementia, and there is currently no cure. The “β-amyloid cascade hypothesis” of AD is the basis of current understanding of AD pathogenesis and drug discovery. However, no AD models have fully validated this hypothesis. We recently developed a human stem cell culture model of AD by cultivating genetically modified human neural stem cells in a three-dimensional (3D) cell culture system. These cells were able to recapitulate key events of AD pathology including β-amyloid plaques and neurofibrillary tangles. In this review, we will discuss the progress and current limitations of AD mouse models and human stem cell models as well as explore the breakthroughs of 3D cell culture systems. We will also share our perspective on the potential of dish models of neurodegenerative diseases for studying pathogenic cascades and therapeutic drug discovery. PMID:26252541
Longitudinal growth of skeletal myotubes in vitro in a new horizontal mechanical cell stimulator
NASA Technical Reports Server (NTRS)
Vandenburgh, Herman H.; Karlisch, Patricia
1989-01-01
A tissue-culture model system for growing skeletal-muscle cells under more dynamic conditions than found in normal tissue-culture environments is described. A computerized device presented allows mechanical stimulation of the cell's substratum by 300 to 400 pct in length in the horizontal plane. Cell growth rates and skeletal-muscle organogenesis are stimulated in this in vitro system. It is noted that longitudinal myotube growth observed is accompanied by increased rates of cell proliferation and myoblast fusion. Prestretching the collagen-coated substratum before cell plating is shown to lead to increased cell proliferation, myotube orientation, and longitudinal myotube growth. The effects of substratum stretching on myogenesis in the model system are also assessed and attributed to alterations in the cell's extracellular matrix.
Langerhans Cells Maintain Local Tissue Tolerance in a Model of Systemic Autoimmune Disease1
King, Jennifer K.; Philips, Rachael L.; Eriksson, Anna U.; Kim, Peter J.; Halder, Ramesh C.; Lee, Delphine J.; Singh, Ram Raj
2015-01-01
Systemic autoimmune diseases such as lupus affect multiple organs, usually in a diverse fashion where only certain organs are affected in individual patients. It is unclear whether the ‘local’ immune cells play a role in regulating tissue specificity in relation to disease heterogeneity in systemic autoimmune diseases. Here, we used skin as a model to determine the role of tissue-resident dendritic cells in local and systemic involvement within a systemic lupus disease model. Skin-resident dendritic cells, namely Langerhans cells (LC), have been implicated in regulating tolerance or autoimmunity using elegant transgenic models, however, their role in local versus systemic immune regulation is unknown. We demonstrate that while lymphocytes from skin-draining lymph nodes of autoimmune-prone MRL/MpJ-Faslpr/lpr mice react spontaneously to a physiological skin self-Ag desmoglein-3, epicutaneous applications of desmoglein-3 induced tolerance that is dependent on LCs. Inducible ablation of LCs in adult, preclinical MRL/MpJ-Faslpr/lpr and MRL/MpJ-Fas+/+ mice resulted in increased autoantibodies against skin Ags and markedly accelerated lupus dermatitis with increased local macrophage infiltration, but had no effect on systemic autoantibodies such as anti-dsDNA Abs or disease in other organs such as kidneys, lung, and liver. Furthermore, skin-draining lymph nodes of LC-ablated MRL/MpJ-Faslpr/lpr mice had significantly fewer CD4+ T-cells producing anti-inflammatory cytokine IL-10 than LC-intact controls. These results indicate that a skin-resident dendritic cell population regulates local tolerance in systemic lupus and emphasize the importance of the local immune milieu in preventing tissue-specific autoimmunity yet have no effect on systemic autoimmunity. PMID:26071559
Microfluidic Devices for Drug Delivery Systems and Drug Screening
Kompella, Uday B.; Damiati, Safa A.
2018-01-01
Microfluidic devices present unique advantages for the development of efficient drug carrier particles, cell-free protein synthesis systems, and rapid techniques for direct drug screening. Compared to bulk methods, by efficiently controlling the geometries of the fabricated chip and the flow rates of multiphase fluids, microfluidic technology enables the generation of highly stable, uniform, monodispersed particles with higher encapsulation efficiency. Since the existing preclinical models are inefficient drug screens for predicting clinical outcomes, microfluidic platforms might offer a more rapid and cost-effective alternative. Compared to 2D cell culture systems and in vivo animal models, microfluidic 3D platforms mimic the in vivo cell systems in a simple, inexpensive manner, which allows high throughput and multiplexed drug screening at the cell, organ, and whole-body levels. In this review, the generation of appropriate drug or gene carriers including different particle types using different configurations of microfluidic devices is highlighted. Additionally, this paper discusses the emergence of fabricated microfluidic cell-free protein synthesis systems for potential use at point of care as well as cell-, organ-, and human-on-a-chip models as smart, sensitive, and reproducible platforms, allowing the investigation of the effects of drugs under conditions imitating the biological system. PMID:29462948
Toward the reconstitution of synthetic cell motility
Siton-Mendelson, Orit; Bernheim-Groswasser, Anne
2016-01-01
ABSTRACT Cellular motility is a fundamental process essential for embryonic development, wound healing, immune responses, and tissues development. Cells are mostly moving by crawling on external, or inside, substrates which can differ in their surface composition, geometry, and dimensionality. Cells can adopt different migration phenotypes, e.g., bleb-based and protrusion-based, depending on myosin contractility, surface adhesion, and cell confinement. In the few past decades, research on cell motility has focused on uncovering the major molecular players and their order of events. Despite major progresses, our ability to infer on the collective behavior from the molecular properties remains a major challenge, especially because cell migration integrates numerous chemical and mechanical processes that are coupled via feedbacks that span over large range of time and length scales. For this reason, reconstituted model systems were developed. These systems allow for full control of the molecular constituents and various system parameters, thereby providing insight into their individual roles and functions. In this review we describe the various reconstituted model systems that were developed in the past decades. Because of the multiple steps involved in cell motility and the complexity of the overall process, most of the model systems focus on very specific aspects of the individual steps of cell motility. Here we describe the main advancement in cell motility reconstitution and discuss the main challenges toward the realization of a synthetic motile cell. PMID:27019160
Rehm, Markus; Prehn, Jochen H M
2013-06-01
Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.
Culture Models for Studying Thyroid Biology and Disorders
Toda, Shuji; Aoki, Shigehisa; Uchihashi, Kazuyoshi; Matsunobu, Aki; Yamamoto, Mihoko; Ootani, Akifumi; Yamasaki, Fumio; Koike, Eisuke; Sugihara, Hajime
2011-01-01
The thyroid is composed of thyroid follicles supported by extracellular matrix, capillary network, and stromal cell types such as fibroblasts. The follicles consist of thyrocytes and C cells. In this microenvironment, thyrocytes are highly integrated in their specific structural and functional polarization, but monolayer and floating cultures cannot allow thyrocytes to organize the follicles with such polarity. In contrast, three-dimensional (3-D) collagen gel culture enables thyrocytes to form 3-D follicles with normal polarity. However, these systems never reconstruct the follicles consisting of both thyrocytes and C cells. Thyroid tissue-organotypic culture retains 3-D follicles with both thyrocytes and C cells. To create more appropriate experimental models, we here characterize four culture systems above and then introduce the models for studying thyroid biology and disorders. Finally, we propose a new approach to the cell type-specific culture systems on the basis of in vivo microenvironments of various cell types. PMID:22363871
A microfluidic co-culture system to monitor tumor-stromal interactions on a chip
Menon, Nishanth V.; Cao, Bin; Lim, Mayasari; Kang, Yuejun
2014-01-01
The living cells are arranged in a complex natural environment wherein they interact with extracellular matrix and other neighboring cells. Cell-cell interactions, especially those between distinct phenotypes, have attracted particular interest due to the significant physiological relevance they can reveal for both fundamental and applied biomedical research. To study cell-cell interactions, it is necessary to develop co-culture systems, where different cell types can be cultured within the same confined space. Although the current advancement in lab-on-a-chip technology has allowed the creation of in vitro models to mimic the complexity of in vivo environment, it is still rather challenging to create such co-culture systems for easy control of different colonies of cells. In this paper, we have demonstrated a straightforward method for the development of an on-chip co-culture system. It involves a series of steps to selectively change the surface property for discriminative cell seeding and to induce cellular interaction in a co-culture region. Bone marrow stromal cells (HS5) and a liver tumor cell line (HuH7) have been used to demonstrate this co-culture model. The cell migration and cellular interaction have been analyzed using microscopy and biochemical assays. This co-culture system could be used as a disease model to obtain biological insight of pathological progression, as well as a tool to evaluate the efficacy of different drugs for pharmaceutical studies. PMID:25553194
Mina, Petros; di Bernardo, Mario; Savery, Nigel J.; Tsaneva-Atanasova, Krasimira
2013-01-01
Population-level measurements of phenotypic behaviour in biological systems may not necessarily reflect individual cell behaviour. To assess qualitative changes in the behaviour of a single cell, when alone and when part of a community, we developed an agent-based model describing the metabolic states of a population of quorum-coupled cells. The modelling is motivated by published experimental work of a synthetic genetic regulatory network (GRN) used in Escherichia coli cells that exhibit oscillatory behaviour across the population. To decipher the mechanisms underlying oscillations in the system, we investigate the behaviour of the model via numerical simulation and bifurcation analysis. In particular, we study the effect of an increase in population size as well as the spatio-temporal behaviour of the model. Our results demonstrate that oscillations are possible only in the presence of a high concentration of the coupling chemical and are due to a time scale separation in key regulatory components of the system. The model suggests that the population establishes oscillatory behaviour as the system's preferred stable state. This is achieved via an effective increase in coupling across the population. We conclude that population effects in GRN design need to be taken into consideration and be part of the design process. This is important in planning intervention strategies or designing specific cell behaviours. PMID:23135248
Mina, Petros; di Bernardo, Mario; Savery, Nigel J; Tsaneva-Atanasova, Krasimira
2013-01-06
Population-level measurements of phenotypic behaviour in biological systems may not necessarily reflect individual cell behaviour. To assess qualitative changes in the behaviour of a single cell, when alone and when part of a community, we developed an agent-based model describing the metabolic states of a population of quorum-coupled cells. The modelling is motivated by published experimental work of a synthetic genetic regulatory network (GRN) used in Escherichia coli cells that exhibit oscillatory behaviour across the population. To decipher the mechanisms underlying oscillations in the system, we investigate the behaviour of the model via numerical simulation and bifurcation analysis. In particular, we study the effect of an increase in population size as well as the spatio-temporal behaviour of the model. Our results demonstrate that oscillations are possible only in the presence of a high concentration of the coupling chemical and are due to a time scale separation in key regulatory components of the system. The model suggests that the population establishes oscillatory behaviour as the system's preferred stable state. This is achieved via an effective increase in coupling across the population. We conclude that population effects in GRN design need to be taken into consideration and be part of the design process. This is important in planning intervention strategies or designing specific cell behaviours.
Jakubikova, Jana; Cholujova, Danka; Hideshima, Teru; Gronesova, Paulina; Soltysova, Andrea; Harada, Takeshi; Joo, Jungnam; Kong, Sun-Young; Szalat, Raphael E.; Richardson, Paul G.; Munshi, Nikhil C.; Dorfman, David M.; Anderson, Kenneth C.
2016-01-01
Specific niches within the tumor bone marrow (BM) microenvironment afford a sanctuary for multiple myeloma (MM) clones due to stromal cell-tumor cell interactions, which confer survival advantage and drug resistance. Defining the sequelae of tumor cell interactions within the MM niches on an individualized basis may provide the rationale for personalized therapies. To mimic the MM niche, we here describe a new 3D co-culture ex-vivo model in which primary MM patient BM cells are co-cultured with mesenchymal stem cells (MSC) in a hydrogel 3D system. In the 3D model, MSC with conserved phenotype (CD73+CD90+CD105+) formed compact clusters with active fibrous connections, and retained lineage differentiation capacity. Extracellular matrix molecules, integrins, and niche related molecules including N-cadherin and CXCL12 are expressed in 3D MSC model. Furthermore, activation of osteogenesis (MMP13, SPP1, ADAMTS4, and MGP genes) and osteoblastogenic differentiation was confirmed in 3D MSC model. Co-culture of patient-derived BM mononuclear cells with either autologous or allogeneic MSC in 3D model increased proliferation of MM cells, CXCR4 expression, and SP cells. We carried out immune profiling to show that distribution of immune cell subsets was similar in 3D and 2D MSC model systems. Importantly, resistance to novel agents (IMiDs, bortezomib, carfilzomib) and conventional agents (doxorubicin, dexamethasone, melphalan) was observed in 3D MSC system, reflective of clinical resistance. This 3D MSC model may therefore allow for studies of MM pathogenesis and drug resistance within the BM niche. Importantly, ongoing prospective trials are evaluating its utility to inform personalized targeted and immune therapy in MM. PMID:27764795
A two-scale model for correlation between B cell VDJ usage in zebrafish
NASA Astrophysics Data System (ADS)
Pan, Keyao; Deem, Michael
2011-03-01
The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.
Modeling of indirect carbon fuel cell systems with steam and dry gasification
NASA Astrophysics Data System (ADS)
Ong, Katherine M.; Ghoniem, Ahmed F.
2016-05-01
An indirect carbon fuel cell (ICFC) system that couples coal gasification to a solid oxide fuel cell (SOFC) is a promising candidate for high efficiency stationary power. This study couples an equilibrium gasifier model to a detailed 1D MEA model to study the theoretical performance of an ICFC system run on steam or carbon dioxide. Results show that the fuel cell in the ICFC system is capable of power densities greater than 1.0 W cm-2 with H2O recycle, and power densities ranging from 0.2 to 0.4 W cm-2 with CO2 recycle. This result indicates that the ICFC system performs better with steam than with CO2 gasification as a result of the faster electro-oxidation kinetics of H2 relative to CO. The ICFC system is then shown to reach higher current densities and efficiencies than a thermally decoupled gasifier + fuel cell (G + FC) system because it does not include combustion losses associated with autothermal gasification. 55-60% efficiency is predicted for the ICFC system coupled to a bottoming cycle, making this technology competitive with other state-of-the-art stationary power candidates.
A Novel Three-Dimensional Immune Oncology Model for High-Throughput Testing of Tumoricidal Activity.
Sherman, Hilary; Gitschier, Hannah J; Rossi, Ann E
2018-01-01
The latest advancements in oncology research are focused on autologous immune cell therapy. However, the effectiveness of this type of immunotherapy for cancer remediation is not equivalent for all patients or cancer types. This suggests the need for better preclinical screening models that more closely recapitulate in vivo tumor biology. The established method for investigating tumoricidal activity of immunotherapies has been study of two-dimensional (2D) monolayer cultures of immortalized cancer cell lines or primary tumor cells in standard tissue culture vessels. Indeed, a proven means to examine immune cell migration and invasion are 2D chemotaxis assays in permeabilized supports or Boyden chambers. Nevertheless, the more in vivo -like three-dimensional (3D) multicellular tumor spheroids are quickly becoming the favored model to examine immune cell invasion and tumor cell cytotoxicity. Accordingly, we have developed a 3D immune oncology model by combining 96-well permeable support systems and 96-well low-attachment microplates. The use of the permeable support system enables assessment of immune cell migration, which was tested in this study as chemotactic response of natural killer NK-92MI cells to human stromal-cell derived factor-1 (SDF-1α). Immune invasion was assessed by measuring NK-92MI infiltration into lung carcinoma A549 cell spheroids that were formed in low-attachment microplates. The novel pairing of the permeable support system with low-attachment microplates permitted simultaneous investigation of immune cell homing, immune invasion of tumor spheroids, and spheroid cytotoxicity. In effect, the system represents a more comprehensive and in vivo -like immune oncology model that can be utilized for high-throughput study of tumoricidal activity.
Centeno, Eduarda G Z; Cimarosti, Helena; Bithell, Angela
2018-05-22
Neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS), affect millions of people every year and so far, there are no therapeutic cures available. Even though animal and histological models have been of great aid in understanding disease mechanisms and identifying possible therapeutic strategies, in order to find disease-modifying solutions there is still a critical need for systems that can provide more predictive and physiologically relevant results. One possible avenue is the development of patient-derived models, e.g. by reprogramming patient somatic cells into human induced pluripotent stem cells (hiPSCs), which can then be differentiated into any cell type for modelling. These systems contain key genetic information from the donors, and therefore have enormous potential as tools in the investigation of pathological mechanisms underlying disease phenotype, and progression, as well as in drug testing platforms. hiPSCs have been widely cultured in 2D systems, but in order to mimic human brain complexity, 3D models have been proposed as a more advanced alternative. This review will focus on the use of patient-derived hiPSCs to model AD, PD, HD and ALS. In brief, we will cover the available stem cells, types of 2D and 3D culture systems, existing models for neurodegenerative diseases, obstacles to model these diseases in vitro, and current perspectives in the field.
Muscle Stem Cells: A Model System for Adult Stem Cell Biology.
Cornelison, Ddw; Perdiguero, Eusebio
2017-01-01
Skeletal muscle stem cells, originally termed satellite cells for their position adjacent to differentiated muscle fibers, are absolutely required for the process of skeletal muscle repair and regeneration. In the last decade, satellite cells have become one of the most studied adult stem cell systems and have emerged as a standard model not only in the field of stem cell-driven tissue regeneration but also in stem cell dysfunction and aging. Here, we provide background in the field and discuss recent advances in our understanding of muscle stem cell function and dysfunction, particularly in the case of aging, and the potential involvement of muscle stem cells in genetic diseases such as the muscular dystrophies.
Phosphoric acid fuel cell power plant system performance model and computer program
NASA Technical Reports Server (NTRS)
Alkasab, K. A.; Lu, C. Y.
1984-01-01
A FORTRAN computer program was developed for analyzing the performance of phosphoric acid fuel cell power plant systems. Energy mass and electrochemical analysis in the reformer, the shaft converters, the heat exchangers, and the fuel cell stack were combined to develop a mathematical model for the power plant for both atmospheric and pressurized conditions, and for several commercial fuels.
Reciprocating air flow for Li-ion battery thermal management to improve temperature uniformity
NASA Astrophysics Data System (ADS)
Mahamud, Rajib; Park, Chanwoo
The thermal management of traction battery systems for electrical-drive vehicles directly affects vehicle dynamic performance, long-term durability and cost of the battery systems. In this paper, a new battery thermal management method using a reciprocating air flow for cylindrical Li-ion (LiMn 2O 4/C) cells was numerically analyzed using (i) a two-dimensional computational fluid dynamics (CFD) model and (ii) a lumped-capacitance thermal model for battery cells and a flow network model. The battery heat generation was approximated by uniform volumetric joule and reversible (entropic) losses. The results of the CFD model were validated with the experimental results of in-line tube-bank systems which approximates the battery cell arrangement considered for this study. The numerical results showed that the reciprocating flow can reduce the cell temperature difference of the battery system by about 4 °C (72% reduction) and the maximum cell temperature by 1.5 °C for a reciprocation period of τ = 120 s as compared with the uni-directional flow case (τ = ∞). Such temperature improvement attributes to the heat redistribution and disturbance of the boundary layers on the formed on the cells due to the periodic flow reversal.
Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.; ...
2018-04-07
The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brooks, Kriston P.; Sprik, Samuel J.; Tamburello, David A.
The U.S. Department of Energy (DOE) developed a vehicle Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to Technical Targets established by DOE for four drive cycles/profiles. Chemical hydrogen storage models have been developed for the Framework for both exothermic and endothermic materials. Despite the utility of such models, they require that material researchers input system design specifications that cannot be estimated easily. To address this challenge, a design tool has been developed that allows researchers to directlymore » enter kinetic and thermodynamic chemical hydrogen storage material properties into a simple sizing module that then estimates system parameters required to run the storage system model. Additionally, the design tool can be used as a standalone executable file to estimate the storage system mass and volume outside of the Framework model. Here, these models will be explained and exercised with the representative hydrogen storage materials exothermic ammonia borane (NH 3BH 3) and endothermic alane (AlH 3).« less
Preparation of a Three-Dimensional Full Thickness Skin Equivalent.
Reuter, Christian; Walles, Heike; Groeber, Florian
2017-01-01
In vitro test systems are a promising alternative to animal models. Due to the use of human cells in a three-dimensional arrangement that allows cell-cell or cell-matrix interactions these models may be more predictive for the human situation compared to animal models or two-dimensional cell culture systems. Especially for dermatological research, skin models such as epidermal or full-thickness skin equivalents (FTSE) are used for different applications. Although epidermal models provide highly standardized conditions for risk assessment, FTSE facilitate a cellular crosstalk between the dermal and epidermal layer and thus can be used as more complex models for the investigation of processes such as wound healing, skin development, or infectious diseases. In this chapter, we describe the generation and culture of an FTSE, based on a collagen type I matrix and provide troubleshooting tips for commonly encountered technical problems.
The Impact of Prophage on the Equilibria and Stability of Phage and Host
NASA Astrophysics Data System (ADS)
Yu, Pei; Nadeem, Alina; Wahl, Lindi M.
2017-06-01
In this paper, we present a bacteriophage model that includes prophage, that is, phage genomes that are incorporated into the host cell genome. The general model is described by an 18-dimensional system of ordinary differential equations. This study focuses on asymptotic behaviour of the model, and thus the system is reduced to a simple six-dimensional model, involving uninfected host cells, infected host cells and phage. We use dynamical system theory to explore the dynamic behaviour of the model, studying in particular the impact of prophage on the equilibria and stability of phage and host. We employ bifurcation and stability theory, centre manifold and normal form theory to show that the system has multiple equilibrium solutions which undergo a series of bifurcations, finally leading to oscillating motions. Numerical simulations are presented to illustrate and confirm the analytical predictions. The results of this study indicate that in some parameter regimes, the host cell population may drive the phage to extinction through diversification, that is, if multiple types of host emerge; this prediction holds even if the phage population is likewise diverse. This parameter regime is restricted, however, if infecting phage are able to recombine with prophage sequences in the host cell genome.
NASA Technical Reports Server (NTRS)
Duval, R. W.; Bahrami, M.
1985-01-01
The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.
Cellular Models: HD Patient-Derived Pluripotent Stem Cells.
Geater, Charlene; Hernandez, Sarah; Thompson, Leslie; Mattis, Virginia B
2018-01-01
Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by expanded polyglutamine (polyQ)-encoding repeats in the Huntingtin (HTT) gene. Traditionally, HD cellular models consisted of either patient cells not affected by disease or rodent neurons expressing expanded polyQ repeats in HTT. As these models can be limited in their disease manifestation or proper genetic context, respectively, human HD pluripotent stem cells (PSCs) are currently under investigation as a way to model disease in patient-derived neurons and other neural cell types. This chapter reviews embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) models of disease, including published differentiation paradigms for neurons and their associated phenotypes, as well as current challenges to the field such as validation of the PSCs and PSC-derived cells. Highlighted are potential future technical advances to HD PSC modeling, including transdifferentiation, complex in vitro multiorgan/system reconstruction, and personalized medicine. Using a human HD patient model of the central nervous system, hopefully one day researchers can tease out the consequences of mutant HTT (mHTT) expression on specific cell types within the brain in order to identify and test novel therapies for disease.
Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates
Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda
2012-01-01
One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039
Crypt dynamics and colorectal cancer: advances in mathematical modelling.
van Leeuwen, I M M; Byrne, H M; Jensen, O E; King, J R
2006-06-01
Mathematical modelling forms a key component of systems biology, offering insights that complement and stimulate experimental studies. In this review, we illustrate the role of theoretical models in elucidating the mechanisms involved in normal intestinal crypt dynamics and colorectal cancer. We discuss a range of modelling approaches, including models that describe cell proliferation, migration, differentiation, crypt fission, genetic instability, APC inactivation and tumour heterogeneity. We focus on the model assumptions, limitations and applications, rather than on the technical details. We also present a new stochastic model for stem-cell dynamics, which predicts that, on average, APC inactivation occurs more quickly in the stem-cell pool in the absence of symmetric cell division. This suggests that natural niche succession may protect stem cells against malignant transformation in the gut. Finally, we explain how we aim to gain further understanding of the crypt system and of colorectal carcinogenesis with the aid of multiscale models that cover all levels of organization from the molecular to the whole organ.
PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.
Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold
2016-01-21
The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multiscale modeling of sickle anemia blood blow by Dissipative Partice Dynamics
NASA Astrophysics Data System (ADS)
Lei, Huan; Caswell, Bruce; Karniadakis, George
2011-11-01
A multi-scale model for sickle red blood cell is developed based on Dissipative Particle Dynamics (DPD). Different cell morphologies (sickle, granular, elongated shapes) typically observed in in vitro and in vivo are constructed and the deviations from the biconcave shape is quantified by the Asphericity and Elliptical shape factors. The rheology of sickle blood is studied in both shear and pipe flow systems. The flow resistance obtained from both systems exhibits a larger value than the healthy blood flow due to the abnormal cell properties. However, the vaso-occulusion phenomenon, reported in a recent microfluid experiment, is not observed in the pipe flow system unless the adhesive interactions between sickle blood cells and endothelium properly introduced into the model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burger, D.E.
1979-11-01
The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less
Chen, Qihong; Long, Rong; Quan, Shuhai
2014-01-01
This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206
Use of Drosophila S2 Cells as a Model for Studying Ehrlichia chaffeensis Infections▿
Luce-Fedrow, Alison; Von Ohlen, Tonia; Boyle, Daniel; Ganta, Roman R.; Chapes, Stephen K.
2008-01-01
Ehrlichia chaffeensis is an obligate intracellular bacterium and the causative agent of human monocytic ehrlichiosis. Although this pathogen grows in several mammalian cell lines, no general model for eukaryotic cellular requirements for bacteria replication has yet been proposed. We found that Drosophila S2 cells are permissive for the growth of E. chaffeensis. We saw morulae (aggregates of bacteria) by microscopy, detected the E. chaffeensis 16S rRNA gene by reverse transcriptase PCR, and used immunocytochemistry to detect E. chaffeensis in S2 and mammalian cells. Bacteria grown in S2 cells reinfected mammalian macrophages. S2 cells were made nonpermissive for E. chaffeensis through incubation with lipopolysaccharide. Our results demonstrate that S2 cells are an appropriate system for studying the pathogenesis of E. chaffeensis. The use of a Drosophila system has the potential to serve as a model system for studying Ehrlichia due to its completed genome, ease of genetic manipulation, and the availability of mutants. PMID:18245255
Engineered in vitro disease models.
Benam, Kambez H; Dauth, Stephanie; Hassell, Bryan; Herland, Anna; Jain, Abhishek; Jang, Kyung-Jin; Karalis, Katia; Kim, Hyun Jung; MacQueen, Luke; Mahmoodian, Roza; Musah, Samira; Torisawa, Yu-suke; van der Meer, Andries D; Villenave, Remi; Yadid, Moran; Parker, Kevin K; Ingber, Donald E
2015-01-01
The ultimate goal of most biomedical research is to gain greater insight into mechanisms of human disease or to develop new and improved therapies or diagnostics. Although great advances have been made in terms of developing disease models in animals, such as transgenic mice, many of these models fail to faithfully recapitulate the human condition. In addition, it is difficult to identify critical cellular and molecular contributors to disease or to vary them independently in whole-animal models. This challenge has attracted the interest of engineers, who have begun to collaborate with biologists to leverage recent advances in tissue engineering and microfabrication to develop novel in vitro models of disease. As these models are synthetic systems, specific molecular factors and individual cell types, including parenchymal cells, vascular cells, and immune cells, can be varied independently while simultaneously measuring system-level responses in real time. In this article, we provide some examples of these efforts, including engineered models of diseases of the heart, lung, intestine, liver, kidney, cartilage, skin and vascular, endocrine, musculoskeletal, and nervous systems, as well as models of infectious diseases and cancer. We also describe how engineered in vitro models can be combined with human inducible pluripotent stem cells to enable new insights into a broad variety of disease mechanisms, as well as provide a test bed for screening new therapies.
Monteagudo, Ángel; Santos, José
2015-01-01
Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.
A simplified solar cell array modelling program
NASA Technical Reports Server (NTRS)
Hughes, R. D.
1982-01-01
As part of the energy conversion/self sufficiency efforts of DSN engineering, it was necessary to have a simplified computer model of a solar photovoltaic (PV) system. This article describes the analysis and simplifications employed in the development of a PV cell array computer model. The analysis of the incident solar radiation, steady state cell temperature and the current-voltage characteristics of a cell array are discussed. A sample cell array was modelled and the results are presented.
Mast, Fred D.; Ratushny, Alexander V.
2014-01-01
Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336
Novel approaches to models of Alzheimer's disease pathology for drug screening and development.
Shaughnessy, Laura; Chamblin, Beth; McMahon, Lori; Nair, Ayyappan; Thomas, Mary Beth; Wakefield, John; Koentgen, Frank; Ramabhadran, Ram
2004-01-01
Development of therapeutics for Alzheimer's disease (AD) requires appropriate cell culture models that reflect the errant biochemical pathways and animal models that reflect the pathological hallmarks of the disease as well as the clinical manifestations. In the past two decades AD research has benefited significantly from the use of genetically engineered cell lines expressing components of the amyloid-generating pathway, as well as from the study of transgenic mice that develop the pathological hallmarks of the disease, mainly neuritic plaques. The choice of certain cell types and the choice of mouse as the model organism have been mandated by the feasibility of introduction and expression of foreign genes into these model systems. We describe a universal and efficient gene-delivery system, using lentiviral vectors, that permits the development of relevant cell biological systems using neuronal cells, including primary neurons and animal models in mammalian species best suited for the study of AD. In addition, lentiviral gene delivery provides avenues for creation of novel models by direct and prolonged expression of genes in the brain in any vertebrate animal. TranzVector is a lentiviral vector optimized for efficiency and safety that delivers genes to cells in culture, in tissue explants, and in live animals regardless of the dividing or differentiated status of the cells. Genes can also be delivered efficiently to fertilized single-cell-stage embryos of a wide range of mammalian species, broadening the range of the model organism (from rats to nonhuman primates) for the study of disease mechanism as well as for development of therapeutics. Copyright 2004 Humana Press Inc.
Miming the cancer-immune system competition by kinetic Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Bianca, Carlo; Lemarchand, Annie
2016-10-01
In order to mimic the interactions between cancer and the immune system at cell scale, we propose a minimal model of cell interactions that is similar to a chemical mechanism including autocatalytic steps. The cells are supposed to bear a quantity called activity that may increase during the interactions. The fluctuations of cell activity are controlled by a so-called thermostat. We develop a kinetic Monte Carlo algorithm to simulate the cell interactions and thermalization of cell activity. The model is able to reproduce the well-known behavior of tumors treated by immunotherapy: the first apparent elimination of the tumor by the immune system is followed by a long equilibrium period and the final escape of cancer from immunosurveillance.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hendricks, T.J.; Borkowski, C.A.; Huang, C.
1998-01-01
AMTEC (Alkali Metal Thermal-to-Electric Conversion) cell development has received increased attention and funding in the space power community because of several desirable performance characteristics compared to current radioisotope thermoelectric generation and solar photovoltaic (PV) power generation. AMTEC cell development is critically dependent upon the ability to predict thermal, fluid dynamic and electrical performance of an AMTEC cell which has many complex thermal, fluid dynamic and electrical processes and interactions occurring simultaneously. Development of predictive capability is critical to understanding the complex processes and interactions within the AMTEC cell, and thereby creating the ability to design high-performance, cost-effective AMTEC cells. Amore » flexible, sophisticated thermal/fluid/electrical model of an operating AMTEC cell has been developed using the SINDA/FLUINT analysis software. This model can accurately simulate AMTEC cell performance at any hot side and cold side temperature combination desired, for any voltage and current conditions, and for a broad range of cell design parameters involving the cell dimensions, current collector and electrode design, electrode performance parameters, and cell wall and thermal shield emissivity. The model simulates the thermal radiation network within the AMTEC cell using RadCAD thermal radiation analysis; hot side, cold side and cell wall conductive and radiative coupling; BASE (Beta Alumina Solid Electrode) tube electrochemistry, including electrode over-potentials; the fluid dynamics of the low-pressure sodium vapor flow to the condenser and liquid sodium flow in the wick; sodium condensation at the condenser; and high-temperature sodium evaporation in the wick. The model predicts the temperature profiles within the AMTEC cell walls, the BASE tube temperature profiles, the sodium temperature profile in the artery return, temperature profiles in the evaporator, thermal energy flows throughout the AMTEC cell, all sodium pressure drops from hot BASE tubes to the condenser, the current, voltage, and power output from the cell, and the cell efficiency. This AMTEC cell model is so powerful and flexible that it is used in radioisotope AMTEC power system design, solar AMTEC power system design, and combustion-driven power system design on several projects at Advanced Modular Power Systems, Inc. (AMPS). The model has been successfully validated against actual cell experimental data and its performance predictions agree very well with experimental data on PX-5B cells and other test cells at AMPS. {copyright} {ital 1998 American Institute of Physics.}« less
Snyder, Jessica; Son, Ae Rin; Hamid, Qudus; Wu, Honglu; Sun, Wei
2016-01-13
Bottom-up tissue engineering requires methodological progress of biofabrication to capture key design facets of anatomical arrangements across micro, meso and macro-scales. The diffusive mass transfer properties necessary to elicit stability and functionality require hetero-typic contact, cell-to-cell signaling and uniform nutrient diffusion. Bioprinting techniques successfully build mathematically defined porous architecture to diminish resistance to mass transfer. Current limitations of bioprinted cell assemblies include poor micro-scale formability of cell-laden soft gels and asymmetrical macro-scale diffusion through 3D volumes. The objective of this work is to engineer a synchronized multi-material bioprinter (SMMB) system which improves the resolution and expands the capability of existing bioprinting systems by packaging multiple cell types in heterotypic arrays prior to deposition. This unit cell approach to arranging multiple cell-laden solutions is integrated with a motion system to print heterogeneous filaments as tissue engineered scaffolds and nanoliter droplets. The set of SMMB process parameters control the geometric arrangement of the combined flow's internal features and constituent material's volume fractions. SMMB printed hepatocyte-endothelial laden 200 nl droplets are cultured in a rotary cell culture system (RCCS) to study the effect of microgravity on an in vitro model of the human hepatic lobule. RCCS conditioning for 48 h increased hepatocyte cytoplasm diameter 2 μm, increased metabolic rate, and decreased drug half-life. SMMB hetero-cellular models present a 10-fold increase in metabolic rate, compared to SMMB mono-culture models. Improved bioprinting resolution due to process control of cell-laden matrix packaging as well as nanoliter droplet printing capability identify SMMB as a viable technique to improve in vitro model efficacy.
Asymptotic behaviors of a cell-to-cell HIV-1 infection model perturbed by white noise
NASA Astrophysics Data System (ADS)
Liu, Qun
2017-02-01
In this paper, we analyze a mathematical model of cell-to-cell HIV-1 infection to CD4+ T cells perturbed by stochastic perturbations. First of all, we investigate that there exists a unique global positive solution of the system for any positive initial value. Then by using Lyapunov analysis methods, we study the asymptotic property of this solution. Moreover, we discuss whether there is a stationary distribution for this system and if it owns the ergodic property. Numerical simulations are presented to illustrate the theoretical results.
Usuludin, Suaidah Binte Mohamed; Cao, Xue; Lim, Mayasari
2012-05-01
We have developed a hematopoietic co-culture system using the hollow fiber bioreactor (HFBR) as a potential in vitro bone marrow model for evaluating leukemia. Supporting stroma using HS-5 cells was established in HFBR system and the current bioprocess configuration yielded an average glucose consumption of 640 mg/day and an average protein concentration of 6.40 mg/mL in the extracapillary space over 28 days. Co-culture with erythroleukemia K562 cells was used as a model for myelo-leukemic cell proliferation and differentiation. Two distinct localizations of K562 cells (loosely adhered and adherent cells) were identified and characterized after 2 weeks. The HFBR co-culture resulted in greater leukemic cell expansion (3,130 fold vs. 43 fold) compared to a standard tissue culture polystyrene (TCP) culture. Majority of expanded cells (68%) in HFBR culture were the adherent population, highlighting the importance of cell-cell contact for myelo-leukemic proliferation. Differentiation tendencies in TCP favored maturation toward monocyte and erythrocyte lineages but maintained a pool of myeloid progenitors. In contrast, HFBR co-culture exhibited greater lineage diversity, stimulating monocytic and megakaryocytic differentiation while inhibiting erythroid maturation. With the extensive stromal expansion capacity on hollow fiber surfaces, the HFBR system is able to achieve high cell densities and 3D cell-cell contacts mimicking the bone marrow microenvironment. The proposed in vitro system represents a dynamic and highly scalable 3D co-culture platform for the study of cell-stroma dependent hematopoietic/leukemic cell functions and ex vivo expansion. Copyright © 2011 Wiley Periodicals, Inc.
Raasch, Martin; Fritsche, Enrico; Kurtz, Andreas; Bauer, Michael; Mosig, Alexander S
2018-06-14
Complex cell culture models such as microphysiological models (MPS) mimicking human liver functionality in vitro are in the spotlight as alternative to conventional cell culture and animal models. Promising techniques like microfluidic cell culture or micropatterning by 3D bioprinting are gaining increasing importance for the development of MPS to address the needs for more predictivity and cost efficiency. In this context, human induced pluripotent stem cells (hiPSCs) offer new perspectives for the development of advanced liver-on-chip systems by recreating an in vivo like microenvironment that supports the reliable differentiation of hiPSCs to hepatocyte-like cells (HLC). In this review we will summarize current protocols of HLC generation and highlight recently established MPS suitable to resemble physiological hepatocyte function in vitro. In addition, we are discussing potential applications of liver MPS for disease modeling related to systemic or direct liver infections and the use of MPS in testing of new drug candidates. Copyright © 2018. Published by Elsevier B.V.
Brain Aggregates: An Effective In Vitro Cell Culture System Modeling Neurodegenerative Diseases.
Ahn, Misol; Kalume, Franck; Pitstick, Rose; Oehler, Abby; Carlson, George; DeArmond, Stephen J
2016-03-01
Drug discovery for neurodegenerative diseases is particularly challenging because of the discrepancies in drug effects between in vitro and in vivo studies. These discrepancies occur in part because current cell culture systems used for drug screening have many limitations. First, few cell culture systems accurately model human aging or neurodegenerative diseases. Second, drug efficacy may differ between dividing and stationary cells, the latter resembling nondividing neurons in the CNS. Brain aggregates (BrnAggs) derived from embryonic day 15 gestation mouse embryos may represent neuropathogenic processes in prion disease and reflect in vivo drug efficacy. Here, we report a new method for the production of BrnAggs suitable for drug screening and suggest that BrnAggs can model additional neurological diseases such as tauopathies. We also report a functional assay with BrnAggs by measuring electrophysiological activities. Our data suggest that BrnAggs could serve as an effective in vitro cell culture system for drug discovery for neurodegenerative diseases. © 2016 American Association of Neuropathologists, Inc. All rights reserved.
A mathematical model of antibody-dependent cellular cytotoxicity (ADCC).
Hoffman, F; Gavaghan, D; Osborne, J; Barrett, I P; You, T; Ghadially, H; Sainson, R; Wilkinson, R W; Byrne, H M
2018-01-07
Immunotherapies exploit the immune system to target and kill cancer cells, while sparing healthy tissue. Antibody therapies, an important class of immunotherapies, involve the binding to specific antigens on the surface of the tumour cells of antibodies that activate natural killer (NK) cells to kill the tumour cells. Preclinical assessment of molecules that may cause antibody-dependent cellular cytotoxicity (ADCC) involves co-culturing cancer cells, NK cells and antibody in vitro for several hours and measuring subsequent levels of tumour cell lysis. Here we develop a mathematical model of such an in vitro ADCC assay, formulated as a system of time-dependent ordinary differential equations and in which NK cells kill cancer cells at a rate which depends on the amount of antibody bound to each cancer cell. Numerical simulations generated using experimentally-based parameter estimates reveal that the system evolves on two timescales: a fast timescale on which antibodies bind to receptors on the surface of the tumour cells, and NK cells form complexes with the cancer cells, and a longer time-scale on which the NK cells kill the cancer cells. We construct approximate model solutions on each timescale, and show that they are in good agreement with numerical simulations of the full system. Our results show how the processes involved in ADCC change as the initial concentration of antibody and NK-cancer cell ratio are varied. We use these results to explain what information about the tumour cell kill rate can be extracted from the cytotoxicity assays. Copyright © 2017 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Domanskyi, Sergii; Schilling, Joshua E.; Privman, Vladimir, E-mail: privman@clarkson.edu
We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model wemore » describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of “stiff” equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.« less
NASA Astrophysics Data System (ADS)
Xia, Quan; Wang, Zili; Ren, Yi; Sun, Bo; Yang, Dezhen; Feng, Qiang
2018-05-01
With the rapid development of lithium-ion battery technology in the electric vehicle (EV) industry, the lifetime of the battery cell increases substantially; however, the reliability of the battery pack is still inadequate. Because of the complexity of the battery pack, a reliability design method for a lithium-ion battery pack considering the thermal disequilibrium is proposed in this paper based on cell redundancy. Based on this method, a three-dimensional electric-thermal-flow-coupled model, a stochastic degradation model of cells under field dynamic conditions and a multi-state system reliability model of a battery pack are established. The relationships between the multi-physics coupling model, the degradation model and the system reliability model are first constructed to analyze the reliability of the battery pack and followed by analysis examples with different redundancy strategies. By comparing the reliability of battery packs of different redundant cell numbers and configurations, several conclusions for the redundancy strategy are obtained. More notably, the reliability does not monotonically increase with the number of redundant cells for the thermal disequilibrium effects. In this work, the reliability of a 6 × 5 parallel-series configuration is the optimal system structure. In addition, the effect of the cell arrangement and cooling conditions are investigated.
Kim, Michelle; Hosmane, Nina N.; Bullen, C. Korin; Capoferri, Adam; Yang, Hung-Chih; Siliciano, Janet D.; Siliciano, Robert F.
2015-01-01
A mechanistic understanding of HIV-1 latency depends upon a model system that recapitulates the in vivo condition of latently infected, resting CD4+ T lymphocytes. Latency appears to be established after activated CD4+ T cells, the principal targets of HIV-1 infection, become productively infected and survive long enough to return to a resting memory state in which viral expression is inhibited by changes in the cellular environment. This protocol describes an ex vivo primary cell system that is generated under conditions that reflect the in vivo establishment of latency. Creation of these latency model cells takes 12 weeks and, once established, the cells can be maintained and used for several months. The resulting cell population contains both uninfected and latently infected cells. This primary cell model can be used to perform drug screens, study CTL responses to HIV-1, compare viral alleles, or to expand the ex vivo lifespan of cells from HIV-1 infected individuals for extended study. PMID:25375990
NASA Astrophysics Data System (ADS)
Wendel, Christopher H.; Gao, Zhan; Barnett, Scott A.; Braun, Robert J.
2015-06-01
Electrical energy storage is expected to be a critical component of the future world energy system, performing load-leveling operations to enable increased penetration of renewable and distributed generation. Reversible solid oxide cells, operating sequentially between power-producing fuel cell mode and fuel-producing electrolysis mode, have the capability to provide highly efficient, scalable electricity storage. However, challenges ranging from cell performance and durability to system integration must be addressed before widespread adoption. One central challenge of the system design is establishing effective thermal management in the two distinct operating modes. This work leverages an operating strategy to use carbonaceous reactant species and operate at intermediate stack temperature (650 °C) to promote exothermic fuel-synthesis reactions that thermally self-sustain the electrolysis process. We present performance of a doped lanthanum-gallate (LSGM) electrolyte solid oxide cell that shows high efficiency in both operating modes at 650 °C. A physically based electrochemical model is calibrated to represent the cell performance and used to simulate roundtrip operation for conditions unique to these reversible systems. Design decisions related to system operation are evaluated using the cell model including current density, fuel and oxidant reactant compositions, and flow configuration. The analysis reveals tradeoffs between electrical efficiency, thermal management, energy density, and durability.
NASA Astrophysics Data System (ADS)
Mao, Lei; Jackson, Lisa; Jackson, Tom
2017-09-01
This paper investigates the polymer electrolyte membrane (PEM) fuel cell internal behaviour variation at different operating condition, with characterization test data taken at predefined inspection times, and uses the determined internal behaviour evolution to predict the future PEM fuel cell performance. For this purpose, a PEM fuel cell behaviour model is used, which can be related to various fuel cell losses. By matching the model to the collected polarization curves from the PEM fuel cell system, the variation of fuel cell internal behaviour can be obtained through the determined model parameters. From the results, the source of PEM fuel cell degradation during its lifetime at different conditions can be better understood. Moreover, with determined fuel cell internal behaviour, the future fuel cell performance can be obtained by predicting the future model parameters. By comparing with prognostic results using adaptive neuro fuzzy inference system (ANFIS), the proposed prognostic analysis can provide better predictions for PEM fuel cell performance at dynamic condition, and with the understanding of variation in PEM fuel cell internal behaviour, mitigation strategies can be designed to extend the fuel cell performance.
Mast, Fred D; Ratushny, Alexander V; Aitchison, John D
2014-09-15
Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.
Evaluation of Nanoparticle Uptake in Co-culture Cancer Models
Costa, Elisabete C.; Gaspar, Vítor M.; Marques, João G.; Coutinho, Paula; Correia, Ilídio J.
2013-01-01
Co-culture models are currently bridging the gap between classical cultures and in vivo animal models. Exploring this novel approach unlocks the possibility to mimic the tumor microenvironment in vitro, through the establishment of cancer-stroma synergistic interactions. Notably, these organotypic models offer a perfect platform for the development and pre-clinical evaluation of candidate nanocarriers loaded with anti-tumoral drugs in a high throughput screening mode, with lower costs and absence of ethical issues. However, this evaluation was until now limited to co-culture systems established with precise cell ratios, not addressing the natural cell heterogeneity commonly found in different tumors. Therefore, herein the multifunctional nanocarriers efficiency was characterized in various fibroblast-MCF-7 co-culture systems containing different cell ratios, in order to unravel key design parameters that influence nanocarrier performance and the therapeutic outcome. The successful establishment of the co-culture models was confirmed by the tissue-like distribution of the different cells in culture. Nanoparticles incubation in the various co-culture systems reveals that these nanocarriers possess targeting specificity for cancer cells, indicating their suitability for being used in this illness therapy. Additionally, by using different co-culture ratios, different nanoparticle uptake profiles were obtained. These findings are of crucial importance for the future design and optimization of new drug delivery systems, since their real targeting capacity must be addressed in heterogenous cell populations, such as those found in tumors. PMID:23922909
NASA Astrophysics Data System (ADS)
Wilson, Jolaine M.; Krigsfeld, Gabriel S.; Sanzari, Jenine K.; Wagner, Erika B.; Mick, Rosemarie; Kennedy, Ann R.
2012-01-01
Animal models are frequently used to assist in the determination of the long- and short-term effects of space flight. The space environment, including microgravity, can impact many physiological and immunological system parameters. It has been found that ground based models of microgravity produce changes in white blood cell counts, which negatively affects immunologic function. As part of the Center of Acute Radiation Research (CARR), we compared the acute effects on white blood cell parameters induced by the more traditionally used animal model of hindlimb unloading (HU) with a recently developed reduced weightbearing analog known as partial weight suspension (PWS). Female ICR mice were either hindlimb unloaded or placed in the PWS system at 16% quadrupedal weightbearing for 4 h, 1, 2, 7 or 10 days, at which point complete blood counts were obtained. Control animals (jacketed and non-jacketed) were exposed to identical conditions without reduced weightbearing. Results indicate that significant changes in total white blood cell (WBC), neutrophil, lymphocyte, monocyte and eosinophil counts were observed within the first 2 days of exposure to each system. These differences in blood cell counts normalized by day 7 in both systems. The results of these studies indicate that there are some statistically significant changes observed in the blood cell counts for animals exposed to both the PWS and HU simulated microgravity systems.
Hanging drop: an in vitro air toxic exposure model using human lung cells in 2D and 3D structures.
Liu, Faye F; Peng, Cheng; Escher, Beate I; Fantino, Emmanuelle; Giles, Cindy; Were, Stephen; Duffy, Lesley; Ng, Jack C
2013-10-15
Using benzene as a candidate air toxicant and A549 cells as an in vitro cell model, we have developed and validated a hanging drop (HD) air exposure system that mimics an air liquid interface exposure to the lung for periods of 1h to over 20 days. Dose response curves were highly reproducible for 2D cultures but more variable for 3D cultures. By comparing the HD exposure method with other classically used air exposure systems, we found that the HD exposure method is more sensitive, more reliable and cheaper to run than medium diffusion methods and the CULTEX(®) system. The concentration causing 50% of reduction of cell viability (EC50) for benzene, toluene, p-xylene, m-xylene and o-xylene to A549 cells for 1h exposure in the HD system were similar to previous in vitro static air exposure. Not only cell viability could be assessed but also sub lethal biological endpoints such as DNA damage and interleukin expressions. An advantage of the HD exposure system is that bioavailability and cell concentrations can be derived from published physicochemical properties using a four compartment mass balance model. The modelled cellular effect concentrations EC50cell for 1h exposure were very similar for benzene, toluene and three xylenes and ranged from 5 to 15 mmol/kgdry weight, which corresponds to the intracellular concentration of narcotic chemicals in many aquatic species, confirming the high sensitivity of this exposure method. Copyright © 2013 Elsevier B.V. All rights reserved.
Zhou, Haiying; Purdie, Jennifer; Wang, Tongtong; Ouyang, Anli
2010-01-01
The number of therapeutic proteins produced by cell culture in the pharmaceutical industry continues to increase. During the early stages of manufacturing process development, hundreds of clones and various cell culture conditions are evaluated to develop a robust process to identify and select cell lines with high productivity. It is highly desirable to establish a high throughput system to accelerate process development and reduce cost. Multiwell plates and shake flasks are widely used in the industry as the scale down model for large-scale bioreactors. However, one of the limitations of these two systems is the inability to measure and control pH in a high throughput manner. As pH is an important process parameter for cell culture, this could limit the applications of these scale down model vessels. An economical, rapid, and robust pH measurement method was developed at Eli Lilly and Company by employing SNARF-4F 5-(-and 6)-carboxylic acid. The method demonstrated the ability to measure the pH values of cell culture samples in a high throughput manner. Based upon the chemical equilibrium of CO(2), HCO(3)(-), and the buffer system, i.e., HEPES, we established a mathematical model to regulate pH in multiwell plates and shake flasks. The model calculates the required %CO(2) from the incubator and the amount of sodium bicarbonate to be added to adjust pH to a preset value. The model was validated by experimental data, and pH was accurately regulated by this method. The feasibility of studying the pH effect on cell culture in 96-well plates and shake flasks was also demonstrated in this study. This work shed light on mini-bioreactor scale down model construction and paved the way for cell culture process development to improve productivity or product quality using high throughput systems. Copyright 2009 American Institute of Chemical Engineers
MCF-10A-NeoST: A New Cell System for Studying Cell-ECM and Cell-Cell Interactions in Breast Cancer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zantek, Nicole Dodge; Walker-Daniels, Jennifer; Stewart, Jane
2001-08-22
There is a continuing need for genetically matched cell systems to model cellular behaviors that are frequently observed in aggressive breast cancers. We report here the isolation and initial characterization of a spontaneously arising variant of MCF-10A cells, NeoST, which provides a new model to study cell adhesion and signal transduction in breast cancer. NeoST cells recapitulate important biological and biochemical features of metastatic breast cancer, including anchorage-independent growth, invasiveness in threedimensional reconstituted membranes, loss of E-cadherin expression, and increased tyrosine kinase activity. A comprehensive analysis of tyrosine kinase expression revealed overexpression or functional activation of the Axl, FAK, andmore » EphA2 tyrosine kinases in transformed MCF-10A cells. MCF-10A and these new derivatives provide a genetically matched model to study defects in cell adhesion and signaling that are relevant to cellular behaviors that often typify aggressive breast cancer cells.« less
simBio: a Java package for the development of detailed cell models.
Sarai, Nobuaki; Matsuoka, Satoshi; Noma, Akinori
2006-01-01
Quantitative dynamic computer models, which integrate a variety of molecular functions into a cell model, provide a powerful tool to create and test working hypotheses. We have developed a new modeling tool, the simBio package (freely available from ), which can be used for constructing cell models, such as cardiac cells (the Kyoto model from Matsuoka et al., 2003, 2004 a, b, the LRd model from Faber and Rudy, 2000, and the Noble 98 model from Noble et al., 1998), epithelial cells (Strieter et al., 1990) and pancreatic beta cells (Magnus and Keizer, 1998). The simBio package is written in Java, uses XML and can solve ordinary differential equations. In an attempt to mimic biological functional structures, a cell model is, in simBio, composed of independent functional modules called Reactors, such as ion channels and the sarcoplasmic reticulum, and dynamic variables called Nodes, such as ion concentrations. The interactions between Reactors and Nodes are described by the graph theory and the resulting graph represents a blueprint of an intricate cellular system. Reactors are prepared in a hierarchical order, in analogy to the biological classification. Each Reactor can be composed or improved independently, and can easily be reused for different models. This way of building models, through the combination of various modules, is enabled through the use of object-oriented programming concepts. Thus, simBio is a straightforward system for the creation of a variety of cell models on a common database of functional modules.
A Systems Model of Parkinson's Disease Using Biochemical Systems Theory.
Sasidharakurup, Hemalatha; Melethadathil, Nidheesh; Nair, Bipin; Diwakar, Shyam
2017-08-01
Parkinson's disease (PD), a neurodegenerative disorder, affects millions of people and has gained attention because of its clinical roles affecting behaviors related to motor and nonmotor symptoms. Although studies on PD from various aspects are becoming popular, few rely on predictive systems modeling approaches. Using Biochemical Systems Theory (BST), this article attempts to model and characterize dopaminergic cell death and understand pathophysiology of progression of PD. PD pathways were modeled using stochastic differential equations incorporating law of mass action, and initial concentrations for the modeled proteins were obtained from literature. Simulations suggest that dopamine levels were reduced significantly due to an increase in dopaminergic quinones and 3,4-dihydroxyphenylacetaldehyde (DOPAL) relating to imbalances compared to control during PD progression. Associating to clinically observed PD-related cell death, simulations show abnormal parkin and reactive oxygen species levels with an increase in neurofibrillary tangles. While relating molecular mechanistic roles, the BST modeling helps predicting dopaminergic cell death processes involved in the progression of PD and provides a predictive understanding of neuronal dysfunction for translational neuroscience.
Direct 3D cell-printing of human skin with functional transwell system.
Kim, Byoung Soo; Lee, Jung-Seob; Gao, Ge; Cho, Dong-Woo
2017-06-06
Three-dimensional (3D) cell-printing has been emerging as a promising technology with which to build up human skin models by enabling rapid and versatile design. Despite the technological advances, challenges remain in the development of fully functional models that recapitulate complexities in the native tissue. Moreover, although several approaches have been explored for the development of biomimetic human skin models, the present skin models based on multistep fabrication methods using polydimethylsiloxane chips and commercial transwell inserts could be tackled by leveraging 3D cell-printing technology. In this paper, we present a new 3D cell-printing strategy for engineering a 3D human skin model with a functional transwell system in a single-step process. A hybrid 3D cell-printing system was developed, allowing for the use of extrusion and inkjet modules at the same time. We began by revealing the significance of each module in engineering human skin models; by using the extrusion-dispensing module, we engineered a collagen-based construct with polycaprolactone (PCL) mesh that prevented the contraction of collagen during tissue maturation; the inkjet-based dispensing module was used to uniformly distribute keratinocytes. Taking these features together, we engineered a human skin model with a functional transwell system; the transwell system and fibroblast-populated dermis were consecutively fabricated by using the extrusion modules. Following this process, keratinocytes were uniformly distributed onto the engineered dermis by the inkjet module. Our transwell system indicates a supportive 3D construct composed of PCL, enabling the maturation of a skin model without the aid of commercial transwell inserts. This skin model revealed favorable biological characteristics that included a stabilized fibroblast-stretched dermis and stratified epidermis layers after 14 days. It was also observed that a 50 times reduction in cost was achieved and 10 times less medium was used than in a conventional culture. Collectively, because this single-step process opens up chances for versatile designs, we envision that our cell-printing strategy could provide an attractive platform in engineering various human skin models.
Sundaram, Meera V.; Buechner, Matthew
2016-01-01
The excretory system of the nematode Caenorhabditis elegans is a superb model of tubular organogenesis involving a minimum of cells. The system consists of just three unicellular tubes (canal, duct, and pore), a secretory gland, and two associated neurons. Just as in more complex organs, cells of the excretory system must first adopt specific identities and then coordinate diverse processes to form tubes of appropriate topology, shape, connectivity, and physiological function. The unicellular topology of excretory tubes, their varied and sometimes complex shapes, and the dynamic reprogramming of cell identity and remodeling of tube connectivity that occur during larval development are particularly fascinating features of this organ. The physiological roles of the excretory system in osmoregulation and other aspects of the animal’s life cycle are only beginning to be explored. The cellular mechanisms and molecular pathways used to build and shape excretory tubes appear similar to those used in both unicellular and multicellular tubes in more complex organs, such as the vertebrate vascular system and kidney, making this simple organ system a useful model for understanding disease processes. PMID:27183565
Horii, Takuro; Tamura, Daiki; Morita, Sumiyo; Kimura, Mika; Hatada, Izuho
2013-09-30
Genome manipulation of human induced pluripotent stem (iPS) cells is essential to achieve their full potential as tools for regenerative medicine. To date, however, gene targeting in human pluripotent stem cells (hPSCs) has proven to be extremely difficult. Recently, an efficient genome manipulation technology using the RNA-guided DNase Cas9, the clustered regularly interspaced short palindromic repeats (CRISPR) system, has been developed. Here we report the efficient generation of an iPS cell model for immunodeficiency, centromeric region instability, facial anomalies syndrome (ICF) syndrome using the CRISPR system. We obtained iPS cells with mutations in both alleles of DNA methyltransferase 3B (DNMT3B) in 63% of transfected clones. Our data suggest that the CRISPR system is highly efficient and useful for genome engineering of human iPS cells.
Computer support for physiological cell modelling using an ontology on cell physiology.
Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda
2006-01-01
The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.
Sipahi, Rifat; Zupanc, Günther K H
2018-05-14
Neural stem and progenitor cells isolated from the central nervous system form, under specific culture conditions, clonal cell clusters known as neurospheres. The neurosphere assay has proven to be a powerful in vitro system to study the behavior of such cells and the development of their progeny. However, the theory of neurosphere growth has remained poorly understood. To overcome this limitation, we have, in the present paper, developed a cellular automata model, with which we examined the effects of proliferative potential, contact inhibition, cell death, and clearance of dead cells on growth rate, final size, and composition of neurospheres. Simulations based on this model indicated that the proliferative potential of the founder cell and its progenitors has a major influence on neurosphere size. On the other hand, contact inhibition of proliferation limits the final size, and reduces the growth rate, of neurospheres. The effect of this inhibition is particularly dramatic when a stem cell becomes encapsulated by differentiated or other non-proliferating cells, thereby suppressing any further mitotic division - despite the existing proliferative potential of the stem cell. Conversely, clearance of dead cells through phagocytosis is predicted to accelerate growth by reducing contact inhibition. A surprising prediction derived from our model is that cell death, while resulting in a decrease in growth rate and final size of neurospheres, increases the degree of differentiation of neurosphere cells. It is likely that the cellular automata model developed as part of the present investigation is applicable to the study of tissue growth in a wide range of systems. Copyright © 2018 Elsevier Ltd. All rights reserved.
Untangling cell tracks: Quantifying cell migration by time lapse image data analysis.
Svensson, Carl-Magnus; Medyukhina, Anna; Belyaev, Ivan; Al-Zaben, Naim; Figge, Marc Thilo
2018-03-01
Automated microscopy has given researchers access to great amounts of live cell imaging data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks from such data using a plethora of segmentation and tracking algorithms, but further analysis is normally required to draw biologically relevant conclusions. Such relevant conclusions may be whether the migration is directed or not, whether the population has homogeneous or heterogeneous migration patterns. This review focuses on the analysis of cell migration data that are extracted from time lapse images. We discuss a range of measures and models used to analyze cell tracks independent of the biological system or the way the tracks were obtained. For single-cell migration, we focus on measures and models giving examples of biological systems where they have been applied, for example, migration of bacteria, fibroblasts, and immune cells. For collective migration, we describe the model systems wound healing, neural crest migration, and Drosophila gastrulation and discuss methods for cell migration within these systems. We also discuss the role of the extracellular matrix and subsequent differences between track analysis in vitro and in vivo. Besides methods and measures, we are putting special focus on the need for openly available data and code, as well as a lack of common vocabulary in cell track analysis. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.
Dynamical crossover in a stochastic model of cell fate decision
NASA Astrophysics Data System (ADS)
Yamaguchi, Hiroki; Kawaguchi, Kyogo; Sagawa, Takahiro
2017-07-01
We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e., proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multicellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.
Cotter, Christopher R.; Schüttler, Heinz-Bernd; Igoshin, Oleg A.; Shimkets, Lawrence J.
2017-01-01
Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell–cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues. PMID:28533367
Examples of Mathematical Modeling
Johnston, Matthew D.; Edwards, Carina M.; Bodmer, Walter F.; Maini, Philip K.; Chapman, S. Jonathan
2008-01-01
Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis. We use the cell population model by Johnston et al.5 to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt. We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters. PMID:17873520
Liverani, Chiara; La Manna, Federico; Groenewoud, Arwin; Mercatali, Laura; Van Der Pluijm, Gabri; Pieri, Federica; Cavaliere, Davide; De Vita, Alessandro; Spadazzi, Chiara; Miserocchi, Giacomo; Bongiovanni, Alberto; Recine, Federica; Riva, Nada; Amadori, Dino; Tasciotti, Ennio; Snaar-Jagalska, Ewa; Ibrahim, Toni
2017-02-15
Patient-derived specimens are an invaluable resource to investigate tumor biology. However, in vivo studies on primary cultures are often limited by the small amount of material available, while conventional in vitro systems might alter the features and behavior that characterize cancer cells. We present our data obtained on primary dedifferentiated liposarcoma cells cultured in a 3D scaffold-based system and injected into a zebrafish model. Primary cells were characterized in vitro for their morphological features, sensitivity to drugs and biomarker expression, and in vivo for their engraftment and invasiveness abilities. The 3D culture showed a higher enrichment in cancer cells than the standard monolayer culture and a better preservation of liposarcoma-associated markers. We also successfully grafted primary cells into zebrafish, showing their local migratory and invasive abilities. Our work provides proof of concept of the ability of 3D cultures to maintain the original phenotype of ex vivo cells, and highlights the potential of the zebrafish model to provide a versatile in vivo system for studies with limited biological material. Such models could be used in translational research studies for biomolecular analyses, drug screenings and tumor aggressiveness assays. © 2016. Published by The Company of Biologists Ltd.
Lee, Se Jeong; Kang, Won Young; Yoon, Yeup; Jin, Ju Youn; Song, Hye Jin; Her, Jung Hyun; Kang, Sang Mi; Hwang, Yu Kyeong; Kang, Kyeong Jin; Joo, Kyeung Min; Nam, Do-Hyun
2015-12-24
Glioblastoma multiforme (GBM) is characterized by extensive local invasion, which is in contrast with extremely rare systemic metastasis of GBM. Molecular mechanisms inhibiting systemic metastasis of GBM would be a novel therapeutic candidate for GBM in the brain. Patient-derived GBM cells were primarily cultured from surgical samples of GBM patients and were inoculated into the brains of immune deficient BALB/c-nude or NOD-SCID IL2Rgamma(null) (NSG) mice. Human NK cells were isolated from peripheral blood mononucleated cells and expanded in vitro. Patient-derived GBM cells in the brains of NSG mice unexpectedly induced spontaneous lung metastasis although no metastasis was detected in BALB/c-nude mice. Based on the difference of the innate immunity between two mouse strains, NK cell activities of orthotopic GBM xenograft models based on BALB/c-nude mice were inhibited. NK cell inactivation induced spontaneous lung metastasis of GBM cells, which indicated that NK cells inhibit the systemic metastasis. In vitro cytotoxic activities of human NK cells against GBM cells indicated that cytotoxic activity of NK cells against GBM cells prevents systemic metastasis of GBM and that NK cells could be effective cell therapeutics against GBM. Accordingly, NK cells transplanted into orthotopic GBM xenograft models intravenously or intratumorally induced apoptosis of GBM cells in the brain and showed significant therapeutic effects. Our results suggest that innate NK immunity is responsible for rare systemic metastasis of GBM and that sufficient supplementation of NK cells could be a promising immunotherapeutic strategy for GBM in the brain.
Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.
Watanabe, Leandro; Myers, Chris J
2016-08-19
The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime.
Modeling integrated photovoltaic–electrochemical devices using steady-state equivalent circuits
Winkler, Mark T.; Cox, Casandra R.; Nocera, Daniel G.; Buonassisi, Tonio
2013-01-01
We describe a framework for efficiently coupling the power output of a series-connected string of single-band-gap solar cells to an electrochemical process that produces storable fuels. We identify the fundamental efficiency limitations that arise from using solar cells with a single band gap, an arrangement that describes the use of currently economic solar cell technologies such as Si or CdTe. Steady-state equivalent circuit analysis permits modeling of practical systems. For the water-splitting reaction, modeling defines parameters that enable a solar-to-fuels efficiency exceeding 18% using laboratory GaAs cells and 16% using all earth-abundant components, including commercial Si solar cells and Co- or Ni-based oxygen evolving catalysts. Circuit analysis also provides a predictive tool: given the performance of the separate photovoltaic and electrochemical systems, the behavior of the coupled photovoltaic–electrochemical system can be anticipated. This predictive utility is demonstrated in the case of water oxidation at the surface of a Si solar cell, using a Co–borate catalyst.
Peroxisystem: harnessing systems cell biology to study peroxisomes.
Schuldiner, Maya; Zalckvar, Einat
2015-04-01
In recent years, high-throughput experimentation with quantitative analysis and modelling of cells, recently dubbed systems cell biology, has been harnessed to study the organisation and dynamics of simple biological systems. Here, we suggest that the peroxisome, a fascinating dynamic organelle, can be used as a good candidate for studying a complete biological system. We discuss several aspects of peroxisomes that can be studied using high-throughput systematic approaches and be integrated into a predictive model. Such approaches can be used in the future to study and understand how a more complex biological system, like a cell and maybe even ultimately a whole organism, works. © 2015 Société Française des Microscopies and Société de Biologie Cellulaire de France. Published by John Wiley & Sons Ltd.
A Brain Unfixed: Unlimited Neurogenesis and Regeneration of the Adult Planarian Nervous System
Brown, David D. R.; Pearson, Bret J.
2017-01-01
Powerful genetic tools in classical laboratory models have been fundamental to our understanding of how stem cells give rise to complex neural tissues during embryonic development. In contrast, adult neurogenesis in our model systems, if present, is typically constrained to one or a few zones of the adult brain to produce a limited subset of neurons leading to the dogma that the brain is primarily fixed post-development. The freshwater planarian (flatworm) is an invertebrate model system that challenges this dogma. The planarian possesses a brain containing several thousand neurons with very high rates of cell turnover (homeostasis), which can also be fully regenerated de novo from injury in just 7 days. Both homeostasis and regeneration depend on the activity of a large population of adult stem cells, called neoblasts, throughout the planarian body. Thus, much effort has been put forth to understand how the flatworm can continually give rise to the diversity of cell types found in the adult brain. Here we focus on work using single-cell genomics and functional analyses to unravel the cellular hierarchies from stem cell to neuron. In addition, we will review what is known about how planarians utilize developmental signaling to maintain proper tissue patterning, homeostasis, and cell-type diversity in their brains. Together, planarians are a powerful emerging model system to study the dynamics of adult neurogenesis and regeneration. PMID:28588444
Ryu, Do-Yeal; Rahman, Md Saidur; Pang, Myung-Geol
2017-09-06
Bisphenol-A (BPA) is a ubiquitous endocrine-disrupting chemical. Recently, many issues have arisen surrounding the disease pathogenesis of BPA. Therefore, several studies have been conducted to investigate the proteomic biomarkers of BPA that are associated with disease processes. However, studies on identifying highly sensitive biological cell model systems in determining BPA health risk are lacking. Here, we determined suitable cell model systems and potential biomarkers for predicting BPA-mediated disease using the bioinformatics tool Pathway Studio. We compiled known BPA-mediated diseases in humans, which were categorized into five major types. Subsequently, we investigated the differentially expressed proteins following BPA exposure in several cell types, and analyzed the efficacy of altered proteins to investigate their associations with BPA-mediated diseases. Our results demonstrated that colon cancer cells (SW480), mammary gland, and Sertoli cells were highly sensitive biological model systems, because of the efficacy of predicting the majority of BPA-mediated diseases. We selected glucose-6-phosphate dehydrogenase (G6PD), cytochrome b-c1 complex subunit 1 (UQCRC1), and voltage-dependent anion-selective channel protein 2 (VDAC2) as highly sensitive biomarkers to predict BPA-mediated diseases. Furthermore, we summarized proteomic studies in spermatozoa following BPA exposure, which have recently been considered as another suitable cell type for predicting BPA-mediated diseases.
Ryu, Do-Yeal
2017-01-01
Bisphenol-A (BPA) is a ubiquitous endocrine-disrupting chemical. Recently, many issues have arisen surrounding the disease pathogenesis of BPA. Therefore, several studies have been conducted to investigate the proteomic biomarkers of BPA that are associated with disease processes. However, studies on identifying highly sensitive biological cell model systems in determining BPA health risk are lacking. Here, we determined suitable cell model systems and potential biomarkers for predicting BPA-mediated disease using the bioinformatics tool Pathway Studio. We compiled known BPA-mediated diseases in humans, which were categorized into five major types. Subsequently, we investigated the differentially expressed proteins following BPA exposure in several cell types, and analyzed the efficacy of altered proteins to investigate their associations with BPA-mediated diseases. Our results demonstrated that colon cancer cells (SW480), mammary gland, and Sertoli cells were highly sensitive biological model systems, because of the efficacy of predicting the majority of BPA-mediated diseases. We selected glucose-6-phosphate dehydrogenase (G6PD), cytochrome b-c1 complex subunit 1 (UQCRC1), and voltage-dependent anion-selective channel protein 2 (VDAC2) as highly sensitive biomarkers to predict BPA-mediated diseases. Furthermore, we summarized proteomic studies in spermatozoa following BPA exposure, which have recently been considered as another suitable cell type for predicting BPA-mediated diseases. PMID:28878155
Systematic reconstruction of TRANSPATH data into Cell System Markup Language
Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru
2008-01-01
Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683
Systematic reconstruction of TRANSPATH data into cell system markup language.
Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru
2008-06-23
Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.
Modeling Ebola Virus Genome Replication and Transcription with Minigenome Systems.
Cressey, Tessa; Brauburger, Kristina; Mühlberger, Elke
2017-01-01
In this chapter, we describe the minigenome system for Ebola virus (EBOV), which reconstitutes EBOV polymerase activity in cells and can be used to model viral genome replication and transcription. This protocol comprises all steps including cell culture, plasmid preparation, transfection, and luciferase reporter assay readout.
Miao, Xin; Koch, Gilbert; Ait-Oudhia, Sihem; Straubinger, Robert M.; Jusko, William J.
2016-01-01
Combinations of gemcitabine and trabectedin exert modest synergistic cytotoxic effects on two pancreatic cancer cell lines. Here, systems pharmacodynamic (PD) models that integrate cellular response data and extend a prototype model framework were developed to characterize dynamic changes in cell cycle phases of cancer cell subpopulations in response to gemcitabine and trabectedin as single agents and in combination. Extensive experimental data were obtained for two pancreatic cancer cell lines (MiaPaCa-2 and BxPC-3), including cell proliferation rates over 0–120 h of drug exposure, and the fraction of cells in different cell cycle phases or apoptosis. Cell cycle analysis demonstrated that gemcitabine induced cell cycle arrest in S phase, and trabectedin induced transient cell cycle arrest in S phase that progressed to G2/M phase. Over time, cells in the control group accumulated in G0/G1 phase. Systems cell cycle models were developed based on observed mechanisms and were used to characterize both cell proliferation and cell numbers in the sub G1, G0/G1, S, and G2/M phases in the control and drug-treated groups. The proposed mathematical models captured well both single and joint effects of gemcitabine and trabectedin. Interaction parameters were applied to quantify unexplainable drug-drug interaction effects on cell cycle arrest in S phase and in inducing apoptosis. The developed models were able to identify and quantify the different underlying interactions between gemcitabine and trabectedin, and captured well our large datasets in the dimensions of time, drug concentrations, and cellular subpopulations. PMID:27895579
NASA Astrophysics Data System (ADS)
Nguyen, H. T.; Le, M. V.; Nguyen, T. A.; Nguyen, T. A. N.
2017-06-01
The solid oxide fuel cell is one of the promising technologies for future energy demand. Solid oxide fuel cell operated in the single-chamber mode exhibits several advantages over conventional single oxide fuel cell due to the simplified, compact, sealing-free cell structure. There are some studies on simulating the behavior of this type of fuel cell but they mainly focus on the 2D model. In the present study, a three-dimensional numerical model of a single chamber solid oxide fuel cell (SOFC) is reported and solved using COMSOL Multiphysics software. Experiments of a planar button solid oxide fuel cell were used to verify the simulation results. The system is fed by methane and oxygen and operated at 700°C. The cathode is LSCF6482, the anode is GDC-Ni, the electrolyte is LDM and the operating pressure is 1 atm. There was a good agreement between the cell temperature and current voltage estimated from the model and measured from the experiment. The results indicate that the model is applicable for the single chamber solid oxide fuel cell and it can provide a basic for the design, scale up of single chamber solid oxide fuel cell system.
Markham, Deborah C; Simpson, Matthew J; Baker, Ruth E
2015-04-01
In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insufficient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.
Unitized Regenerative Fuel Cell System Gas Dryer/Humidifier Analytical Model Development
NASA Technical Reports Server (NTRS)
Burke, Kenneth A.; Jakupca, Ian
2004-01-01
A lightweight Unitized Regenerative Fuel Cell (URFC) Energy Storage System concept is being developed at the NASA Glenn Research Center (GRC). This Unitized Regenerative Fuel Cell System (URFCS) is unique in that it uses Regenerative Gas Dryers/Humidifiers (RGD/H) that are mounted on the surface of the gas storage tanks that act as the radiators for thermal control of the Unitized Regenerative Fuel Cell System (URFCS). As the gas storage tanks cool down during URFCS charging the RGD/H dry the hydrogen and oxygen gases produced by electrolysis. As the gas storage tanks heat up during URFCS discharging, the RGD/H humidify the hydrogen and oxygen gases used by the fuel cell. An analytical model was developed to simulate the URFCS RGD/H. The model is in the form of a Microsoft (registered trademark of Microsoft Corporation) Excel worksheet that allows the investigation of the RGD/H performance. Finite Element Analysis (FEA) modeling of the RGD/H and the gas storage tank wall was also done to analyze spatial temperature distribution within the RGD/H and the localized tank wall. Test results obtained from the testing of the RGD/H in a thermal vacuum environment were used to corroborate the analyses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Webb, Carol F., E-mail: carol-webb@omrf.org; Immunobiology and Cancer Research, Oklahoma Medical Research Foundation, Oklahoma City, OK; Department of Microbiology and Immunology, University of Oklahoma Health Sciences Center, Oklahoma City, OK
Despite exciting new possibilities for regenerative therapy posed by the ability to induce pluripotent stem cells, recapitulation of three-dimensional kidneys for repair or replacement has not been possible. ARID3a-deficient mouse tissues generated multipotent, developmentally plastic cells. Therefore, we assessed the adult mouse ARID3a−/− kidney cell line, KKPS5, which expresses renal progenitor surface markers as an alternative cell source for modeling kidney development. Remarkably, these cells spontaneously developed into multicellular nephron-like structures in vitro, and engrafted into immunocompromised medaka mesonephros, where they formed mouse nephron structures. These data implicate KKPS5 cells as a new model system for studying kidney development. - Highlights:more » • An ARID3a-deficient mouse kidney cell line expresses multiple progenitor markers. • This cell line spontaneously forms multiple nephron-like structures in vitro. • This cell line formed mouse kidney structures in immunocompromised medaka fish kidneys. • Our data identify a novel model system for studying kidney development.« less
Generation of iPS-derived model cells for analyses of hair shaft differentiation.
Kido, Takumi; Horigome, Tomoatsu; Uda, Minori; Adachi, Naoki; Hirai, Yohei
2017-09-01
Biological evaluation of hair growth/differentiation activity in vitro has been a formidable challenge, primarily due to the lack of relevant model cell systems. To solve this problem, we generated a stable model cell line in which successive differentiation via epidermal progenitors to hair components is easily inducible and traceable. Mouse induced pluripotent stem (iPS) cell-derived cells were selected to stably express a tetracycline (Tet)-inducible bone morphogenic protein-4 (BMP4) expression cassette and a luciferase reporter driven by a hair-specific keratin 31 gene (krt31) promoter (Tet-BMP4-KRT31-Luc iPS). While Tet- BMP4-KRT31-Luc iPS cells could be maintained as stable iPS cells, the cells differentiated to produce luciferase luminescence in the presence of all-trans retinoic acid (RA) and doxycycline (Dox), and addition of a hair differentiation factor significantly increased luciferase fluorescence. Thus, this cell line may provide a reliable cell-based screening system to evaluate drug candidates for hair differentiation activity.
Investigation of Tumor Cell Behaviors on a Vascular Microenvironment-Mimicking Microfluidic Chip
Huang, Rong; Zheng, Wenfu; Liu, Wenwen; Zhang, Wei; Long, Yunze; Jiang, Xingyu
2015-01-01
The extravasation of tumor cells is a key event in tumor metastasis. However, the mechanism underlying tumor cell extravasation remains unknown, mainly hindered by obstacles from the lack of complexity of biological tissues in conventional cell culture, and the costliness and ethical issues of in vivo experiments. Thus, a cheap, time and labor saving, and most of all, vascular microenvironment-mimicking research model is desirable. Herein, we report a microfluidic chip-based tumor extravasation research model which is capable of simultaneously simulating both mechanical and biochemical microenvironments of human vascular systems and analyzing their synergistic effects on the tumor extravasation. Under different mechanical conditions of the vascular system, the tumor cells (HeLa cells) had the highest viability and adhesion activity in the microenvironment of the capillary. The integrity of endothelial cells (ECs) monolayer was destroyed by tumor necrosis factor-α (TNF-α) in a hemodynamic background, which facilitated the tumor cell adhesion, this situation was recovered by the administration of platinum nanoparticles (Pt-NPs). This model bridges the gap between cell culture and animal experiments and is a promising platform for studying tumor behaviors in the vascular system. PMID:26631692
Modeling mechanical inhomogeneities in small populations of proliferating monolayers and spheroids.
Lejeune, Emma; Linder, Christian
2018-06-01
Understanding the mechanical behavior of multicellular monolayers and spheroids is fundamental to tissue culture, organism development, and the early stages of tumor growth. Proliferating cells in monolayers and spheroids experience mechanical forces as they grow and divide and local inhomogeneities in the mechanical microenvironment can cause individual cells within the multicellular system to grow and divide at different rates. This differential growth, combined with cell division and reorganization, leads to residual stress. Multiple different modeling approaches have been taken to understand and predict the residual stresses that arise in growing multicellular systems, particularly tumor spheroids. Here, we show that by using a mechanically robust agent-based model constructed with the peridynamic framework, we gain a better understanding of residual stresses in multicellular systems as they grow from a single cell. In particular, we focus on small populations of cells (1-100 s) where population behavior is highly stochastic and prior investigation has been limited. We compare the average strain energy density of cells in monolayers and spheroids using different growth and division rules and find that, on average, cells in spheroids have a higher strain energy density than cells in monolayers. We also find that cells in the interior of a growing spheroid are, on average, in compression. Finally, we demonstrate the importance of accounting for stochastic fluctuations in the mechanical environment, particularly when the cellular response to mechanical cues is nonlinear. The results presented here serve as a starting point for both further investigation with agent-based models, and for the incorporation of major findings from agent-based models into continuum scale models when explicit representation of individual cells is not computationally feasible.
A web-server of cell type discrimination system.
Wang, Anyou; Zhong, Yan; Wang, Yanhua; He, Qianchuan
2014-01-01
Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells.
A Web-Server of Cell Type Discrimination System
Zhong, Yan
2014-01-01
Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and somatic cells (SCs). Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells. PMID:24578634
Study of muscle cell dedifferentiation after skeletal muscle injury of mice with a Cre-Lox system.
Mu, Xiaodong; Peng, Hairong; Pan, Haiying; Huard, Johnny; Li, Yong
2011-02-03
Dedifferentiation of muscle cells in the tissue of mammals has yet to be observed. One of the challenges facing the study of skeletal muscle cell dedifferentiation is the availability of a reliable model that can confidentially distinguish differentiated cell populations of myotubes and non-fused mononuclear cells, including stem cells that can coexist within the population of cells being studied. In the current study, we created a Cre/Lox-β-galactosidase system, which can specifically tag differentiated multinuclear myotubes and myotube-generated mononuclear cells based on the activation of the marker gene, β-galactosidase. By using this system in an adult mouse model, we found that β-galactosidase positive mononuclear cells were generated from β-galactosidase positive multinuclear myofibers upon muscle injury. We also demonstrated that these mononuclear cells can develop into a variety of different muscle cell lineages, i.e., myoblasts, satellite cells, and muscle derived stem cells. These novel findings demonstrated, for the first time, that cellular dedifferentiation of skeletal muscle cells actually occurs in mammalian skeletal muscle following traumatic injury in vivo.
Modeling and Optimization of Renewable and Hybrid Fuel Cell Systems for Space Power and Propulsion
2010-11-14
For that the project achieved: the optimization of SOFC and PEMFC internal structure and external shape under a volume constraint; an initial set of...subcomponent models for regenerative, renewable fuel cell system (RFC); the integration of PEMFC into RFC systems were developed; power electronic...with the same objectives and goals but using a PEMFC regenerative system instead. This research group studied and published on the optimization and
NASA Astrophysics Data System (ADS)
Pachauri, Rupendra Kumar; Chauhan, Yogesh K.
2017-02-01
This paper is a novel attempt to combine two important aspects of fuel cell (FC). First, it presents investigations on FC technology and its applications. A description of FC operating principles is followed by the comparative analysis of the present FC technologies together with the issues concerning various fuels. Second, this paper also proposes a model for the simulation and performances evaluation of a proton exchange membrane fuel cell (PEMFC) generation system. Furthermore, a MATLAB/Simulink-based dynamic model of PEMFC is developed and parameters of FC are so adjusted to emulate a commercially available PEMFC. The system results are obtained for the PEMFC-driven adjusted speed induction motor drive (ASIMD) system, normally used in electric vehicles and analysis is carried out for different operating conditions of FC and ASIMD system. The obtained results prove the validation of system concept and modelling.
Chen, Yi-Dao; Huang, Shiang-Fu; Wang, Hung-Ming
2015-01-01
To precisely and faithfully perform cell-based drug chemosensitivity assays, a well-defined and biologically relevant culture condition is required. For the former, a perfusion microbioreactor system capable of providing a stable culture condition was adopted. For the latter, however, little is known about the impact of culture models on the physiology and chemosensitivity assay results of primary oral cavity cancer cells. To address the issues, experiments were performed. Results showed that minor environmental pH change could significantly affect the metabolic activity of cells, demonstrating the importance of stable culture condition for such assays. Moreover, the culture models could also significantly influence the metabolic activity and proliferation of cells. Furthermore, the choice of culture models might lead to different outcomes of chemosensitivity assays. Compared with the similar test based on tumor-level assays, the spheroid model could overestimate the drug resistance of cells to cisplatin, whereas the 2D and 3D culture models might overestimate the chemosensitivity of cells to such anticancer drug. In this study, the 3D culture models with same cell density as that in tumor samples showed comparable chemosensitivity assay results as the tumor-level assays. Overall, this study has provided some fundamental information for establishing a precise and faithful drug chemosensitivity assay. PMID:25654105
Evolving cell models for systems and synthetic biology.
Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio
2010-03-01
This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.
Tissue-engineered microenvironment systems for modeling human vasculature.
Tourovskaia, Anna; Fauver, Mark; Kramer, Gregory; Simonson, Sara; Neumann, Thomas
2014-09-01
The high attrition rate of drug candidates late in the development process has led to an increasing demand for test assays that predict clinical outcome better than conventional 2D cell culture systems and animal models. Government agencies, the military, and the pharmaceutical industry have started initiatives for the development of novel in-vitro systems that recapitulate functional units of human tissues and organs. There is growing evidence that 3D cell arrangement, co-culture of different cell types, and physico-chemical cues lead to improved predictive power. A key element of all tissue microenvironments is the vasculature. Beyond transporting blood the microvasculature assumes important organ-specific functions. It is also involved in pathologic conditions, such as inflammation, tumor growth, metastasis, and degenerative diseases. To provide a tool for modeling this important feature of human tissue microenvironments, we developed a microfluidic chip for creating tissue-engineered microenvironment systems (TEMS) composed of tubular cell structures. Our chip design encompasses a small chamber that is filled with an extracellular matrix (ECM) surrounding one or more tubular channels. Endothelial cells (ECs) seeded into the channels adhere to the ECM walls and grow into perfusable tubular tissue structures that are fluidically connected to upstream and downstream fluid channels in the chip. Using these chips we created models of angiogenesis, the blood-brain barrier (BBB), and tumor-cell extravasation. Our angiogenesis model recapitulates true angiogenesis, in which sprouting occurs from a "parent" vessel in response to a gradient of growth factors. Our BBB model is composed of a microvessel generated from brain-specific ECs within an ECM populated with astrocytes and pericytes. Our tumor-cell extravasation model can be utilized to visualize and measure tumor-cell migration through vessel walls into the surrounding matrix. The described technology can be used to create TEMS that recapitulate structural, functional, and physico-chemical elements of vascularized human tissue microenvironments in vitro. © 2014 by the Society for Experimental Biology and Medicine.
Sun, Jianxin; Moore, Lee; Xue, Wei; Kim, James; Zborowski, Maciej; Chalmers, Jeffrey J
2018-05-01
Magnetic separation of cells has been, and continues to be, widely used in a variety of applications, ranging from healthcare diagnostics to detection of food contamination. Typically, these technologies require cells labeled with antibody magnetic particle conjugate and a high magnetic energy gradient created in the flow containing the labeled cells (i.e., a column packed with magnetically inducible material), or dense packing of magnetic particles next to the flow cell. Such designs, while creating high magnetic energy gradients, are not amenable to easy, highly detailed, mathematic characterization. Our laboratories have been characterizing and developing analysis and separation technology that can be used on intrinsically magnetic cells or spores which are typically orders of magnitude weaker than typically immunomagnetically labeled cells. One such separation system is magnetic deposition microscopy (MDM) which not only separates cells, but deposits them in specific locations on slides for further microscopic analysis. In this study, the MDM system has been further characterized, using finite element and computational fluid mechanics software, and separation performance predicted, using a model which combines: 1) the distribution of the intrinsic magnetophoretic mobility of the cells (spores); 2) the fluid flow within the separation device; and 3) accurate maps of the values of the magnetic field (max 2.27 T), and magnetic energy gradient (max of 4.41 T 2 /mm) within the system. Guided by this model, experimental studies indicated that greater than 95% of the intrinsically magnetic Bacillus spores can be separated with the MDM system. Further, this model allows analysis of cell trajectories which can assist in the design of higher throughput systems. © 2018 Wiley Periodicals, Inc.
Matsiaka, Oleksii M; Penington, Catherine J; Baker, Ruth E; Simpson, Matthew J
2018-04-01
Scratch assays are routinely used to study the collective spreading of cell populations. In general, the rate at which a population of cells spreads is driven by the combined effects of cell migration and proliferation. To examine the effects of cell migration separately from the effects of cell proliferation, scratch assays are often performed after treating the cells with a drug that inhibits proliferation. Mitomycin-C is a drug that is commonly used to suppress cell proliferation in this context. However, in addition to suppressing cell proliferation, mitomycin-C also causes cells to change size during the experiment, as each cell in the population approximately doubles in size as a result of treatment. Therefore, to describe a scratch assay that incorporates the effects of cell-to-cell crowding, cell-to-cell adhesion, and dynamic changes in cell size, we present a new stochastic model that incorporates these mechanisms. Our agent-based stochastic model takes the form of a system of Langevin equations that is the system of stochastic differential equations governing the evolution of the population of agents. We incorporate a time-dependent interaction force that is used to mimic the dynamic increase in size of the agents. To provide a mathematical description of the average behaviour of the stochastic model we present continuum limit descriptions using both a standard mean-field approximation and a more sophisticated moment dynamics approximation that accounts for the density of agents and density of pairs of agents in the stochastic model. Comparing the accuracy of the two continuum descriptions for a typical scratch assay geometry shows that the incorporation of agent growth in the system is associated with a decrease in accuracy of the standard mean-field description. In contrast, the moment dynamics description provides a more accurate prediction of the evolution of the scratch assay when the increase in size of individual agents is included in the model.
Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.
Bosl, William J
2007-02-15
Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.
Barrio, Rafael A.; Romero-Arias, José Roberto; Noguez, Marco A.; Azpeitia, Eugenio; Ortiz-Gutiérrez, Elizabeth; Hernández-Hernández, Valeria; Cortes-Poza, Yuriria; Álvarez-Buylla, Elena R.
2013-01-01
A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. PMID:23658505
Mort, Richard Lester; Ford, Matthew Jonathan; Sakaue-Sawano, Asako; Lindstrom, Nils Olof; Casadio, Angela; Douglas, Adam Thomas; Keighren, Margaret Anne; Hohenstein, Peter; Miyawaki, Atsushi; Jackson, Ian James
2014-01-01
Markers of cell cycle stage allow estimation of cell cycle dynamics in cell culture and during embryonic development. The Fucci system incorporates genetically encoded probes that highlight G1 and S/G2/M phases of the cell cycle allowing live imaging. However the available mouse models that incorporate Fucci are beset by problems with transgene inactivation, varying expression level, lack of conditional potential and/or the need to maintain separate transgenes-there is no transgenic mouse model that solves all these problems. To address these shortfalls we re-engineered the Fucci system to create 2 bicistronic Fucci variants incorporating both probes fused using the Thosea asigna virus 2A (T2A) self cleaving peptide. We characterize these variants in stable 3T3 cell lines. One of the variants (termed Fucci2a) faithfully recapitulated the nuclear localization and cell cycle stage specific florescence of the original Fucci system. We go on to develop a conditional mouse allele (R26Fucci2aR) carefully designed for high, inducible, ubiquitous expression allowing investigation of cell cycle status in single cell lineages within the developing embryo. We demonstrate the utility of R26Fucci2aR for live imaging by using high resolution confocal microscopy of ex vivo lung, kidney and neural crest development. Using our 3T3 system we describe and validate a method to estimate cell cycle times from relatively short time-lapse sequences that we then apply to our neural crest data. The Fucci2a system and the R26Fucci2aR mouse model are compelling new tools for the investigation of cell cycle dynamics in cell culture and during mouse embryonic development.
Integration of systems biology with organs-on-chips to humanize therapeutic development
NASA Astrophysics Data System (ADS)
Edington, Collin D.; Cirit, Murat; Chen, Wen Li Kelly; Clark, Amanda M.; Wells, Alan; Trumper, David L.; Griffith, Linda G.
2017-02-01
"Mice are not little people" - a refrain becoming louder as the gaps between animal models and human disease become more apparent. At the same time, three emerging approaches are headed toward integration: powerful systems biology analysis of cell-cell and intracellular signaling networks in patient-derived samples; 3D tissue engineered models of human organ systems, often made from stem cells; and micro-fluidic and meso-fluidic devices that enable living systems to be sustained, perturbed and analyzed for weeks in culture. Integration of these rapidly moving fields has the potential to revolutionize development of therapeutics for complex, chronic diseases, including those that have weak genetic bases and substantial contributions from gene-environment interactions. Technical challenges in modeling complex diseases with "organs on chips" approaches include the need for relatively large tissue masses and organ-organ cross talk to capture systemic effects, such that current microfluidic formats often fail to capture the required scale and complexity for interconnected systems. These constraints drive development of new strategies for designing in vitro models, including perfusing organ models, as well as "mesofluidic" pumping and circulation in platforms connecting several organ systems, to achieve the appropriate physiological relevance.
Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J
2016-12-01
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.
Ball, David A.
2016-01-01
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally. PMID:27935947
Koenig, Geraldine; Ozcelik, Hayriye; Haesler, Lisa; Cihova, Martina; Ciftci, Sait; Dupret-Bories, Agnes; Debry, Christian; Stelzle, Martin; Lavalle, Philippe; Vrana, Nihal Engin
2016-03-01
Porous titanium implants are widely used in dental, orthopaedic and otorhinolaryngology fields to improve implant integration to host tissue. A possible step further to improve the integration with the host is the incorporation of autologous cells in porous titanium structures via cell-laden hydrogels. Fast gelling hydrogels have advantageous properties for in situ applications such as localisation of specific cells and growth factors at a target area without dispersion. The ability to control the cell types in different regions of an implant is important in applications where the target tissue (i) has structural heterogeneity (multiple cell types with a defined spatial configuration with respect to each other); (ii) has physical property gradients essential for its function (such as in the case of osteochondral tissue transition). Due to their near immediate gelation, such gels can also be used for site-specific modification of porous titanium structures, particularly for implants which would face different tissues at different locations. Herein, we describe a step by step design of a model system: the model cell-laden gel-containing porous titanium implants in the form of titanium microbead/hydrogel (maleimide-dextran or maleimide-PVA based) microhybrids. These systems enable the determination of the effect of titanium presence on gel properties and encapsulated cell behaviour as a miniaturized version of full-scale implants, providing a system compatible with conventional analysis methods. We used a fibroblast/vascular endothelial cell co-cultures as our model system and by utilising single microbeads we have quantified the effect of gel microenvironment (degradability, presence of RGD peptides within gel formulation) on cell behaviour and the effect of the titanium presence on cell behaviour and gel formation. Titanium presence slightly changed gel properties without hindering gel formation or affecting cell viability. Cells showed a preference to move towards the titanium beads and fibroblast proliferation was significantly higher in hybrids compared to gel only controls. The MMP (Matrix Metalloproteinase)-sensitive hydrogels induced sprouting by cells in co-culture configuration which was quantified by fluorescence microscopy, confocal microscopy and qRT-PCR (Quantitative Reverse transcription polymerase chain reaction). When the microhybrid up-scaled to 3D thick structures, cellular localisation in specific areas of the 3D titanium structures was achieved, without decreasing overall cell proliferation compared to titanium only scaffolds. Microhybrids of titanium and hydrogels are useful models for deciding the necessary modifications of metallic implants and they can be used as a modelling system for the study of tissue/titanium implant interactions. This article demonstrates a method to apply cell-laden hydrogels to porous titanium implants and a model of titanium/hydrogel interaction at micro-level using titanium microbeads. The feasibility of site-specific modification of titanium implants with cell-laden microgels has been demonstrated. Use of titanium microbeads in combination with hydrogels with conventional analysis techniques as described in the article can facilitate the characterisation of surface modification of titanium in a relevant model system. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Lymphocyte-based model systems for allergy research: a historic overview.
Neunkirchner, Alina; Schmetterer, Klaus G; Pickl, Winfried F
2014-01-01
During the last decades, a multitude of studies applying distinct in vitro and in vivo model systems have contributed greatly to our better understanding of the initiation and regulation of inflammatory processes leading to allergic diseases. Over the years, it has become evident that among lymphocytes, not only IgE-producing B cells and allergy-orchestrating CD4(+) helper cells but also cytotoxic CD8(+) T cells, γδ-T cells and innate lymphoid cells, as well as regulatory lymphocytes, might critically shape the immune response towards usually innocuous allergens. In this review, we provide a historic overview of pioneering work leading to the establishment of important lymphocyte-based model systems for allergy research. Moreover, we contrast the original findings with our currently more refined knowledge to appreciate the actual validity of the respective models and to reassess the conclusions obtained from them. Conflicting studies and interpretations are identified and discussed. The tables are intended to provide an easy overview of the field not only for scientists newly entering the field but also for the broader readership interested in updating their knowledge. Along those lines, herein we discuss in vitro and in vivo approaches to the investigation of lymphocyte effector cell activation, polarization and regulation, and describe depletion and adoptive transfer models along with gene knockout and transgenic (tg) methodologies. In addition, novel attempts to establish humanized T cell antigen receptor tg mouse models for allergy research are described and discussed. © 2014 S. Karger AG, Basel.
Continuum-level modelling of cellular adhesion and matrix production in aggregates.
Geris, Liesbet; Ashbourn, Joanna M A; Clarke, Tim
2011-05-01
Key regulators in tissue-engineering processes such as cell culture and cellular organisation are the cell-cell and cell-matrix interactions. As mathematical models are increasingly applied to investigate biological phenomena in the biomedical field, it is important, for some applications, that these models incorporate an adequate description of cell adhesion. This study describes the development of a continuum model that represents a cell-in-gel culture system used in bone-tissue engineering, namely that of a cell aggregate embedded in a hydrogel. Cell adhesion is modelled through the use of non-local (integral) terms in the partial differential equations. The simulation results demonstrate that the effects of cell-cell and cell-matrix adhesion are particularly important for the survival and growth of the cell population and the production of extracellular matrix by the cells, concurring with experimental observations in the literature.
Kelwick, Richard; Webb, Alexander J; MacDonald, James T; Freemont, Paul S
2016-11-01
Cell-free transcription-translation systems were originally applied towards in vitro protein production. More recently, synthetic biology is enabling these systems to be used within a systematic design context for prototyping DNA regulatory elements, genetic logic circuits and biosynthetic pathways. The Gram-positive soil bacterium, Bacillus subtilis, is an established model organism of industrial importance. To this end, we developed several B. subtilis-based cell-free systems. Our improved B. subtilis WB800N-based system was capable of producing 0.8µM GFP, which gave a ~72x fold-improvement when compared with a B. subtilis 168 cell-free system. Our improved system was applied towards the prototyping of a B. subtilis promoter library in which we engineered several promoters, derived from the wild-type P grac (σA) promoter, that display a range of comparable in vitro and in vivo transcriptional activities. Additionally, we demonstrate the cell-free characterisation of an inducible expression system, and the activity of a model enzyme - renilla luciferase. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Molluscan cells in culture: primary cell cultures and cell lines
Yoshino, T. P.; Bickham, U.; Bayne, C. J.
2013-01-01
In vitro cell culture systems from molluscs have significantly contributed to our basic understanding of complex physiological processes occurring within or between tissue-specific cells, yielding information unattainable using intact animal models. In vitro cultures of neuronal cells from gastropods show how simplified cell models can inform our understanding of complex networks in intact organisms. Primary cell cultures from marine and freshwater bivalve and gastropod species are used as biomonitors for environmental contaminants, as models for gene transfer technologies, and for studies of innate immunity and neoplastic disease. Despite efforts to isolate proliferative cell lines from molluscs, the snail Biomphalaria glabrata Say, 1818 embryonic (Bge) cell line is the only existing cell line originating from any molluscan species. Taking an organ systems approach, this review summarizes efforts to establish molluscan cell cultures and describes the varied applications of primary cell cultures in research. Because of the unique status of the Bge cell line, an account is presented of the establishment of this cell line, and of how these cells have contributed to our understanding of snail host-parasite interactions. Finally, we detail the difficulties commonly encountered in efforts to establish cell lines from molluscs and discuss how these difficulties might be overcome. PMID:24198436
Yarmolyuk, Yaroslav R; Vesper, Benjamin J; Paradise, William A; Elseth, Kim M; Tarjan, Gabor; Haines, G Kenneth; Radosevich, James A
2011-02-01
The free radical nitric oxide (NO) is over-expressed in many tumors, including head and neck squamous cell carcinomas (HNSCC); however, the role NO plays in tumor pathophysiology is still not well understood. We, herein, report the development of an in vitro model system which can be used to probe the role of NO in the carcinogenesis of HNSCC. Five HNSCC cell lines were adapted to a high NO (HNO) environment by gradually introducing increasing concentrations of DETA-NONOate, a nitrogen-based NO donor, to cell media. The adaptation process was carried out until a sufficiently high enough donor concentration was reached which enabled the HNO cells to survive and grow, but which was lethal to the original, unadapted ("parent") cells. The adapted HNO cells exhibited analogous morphology to the parent cells, but grew better than their corresponding parent cells in normal media, on soft agar, and in the presence of hydrogen peroxide, an oxygen-based free radical donor. These results indicate that the HNO cell lines are unique and possess biologically different properties than the parent cell lines from which they originated. The HNO/parent cell lines developed herein may be used as a model system to better understand the role NO plays in HNSCC carcinogenesis.
Propulsion System Models for Rotorcraft Conceptual Design
NASA Technical Reports Server (NTRS)
Johnson, Wayne
2014-01-01
The conceptual design code NDARC (NASA Design and Analysis of Rotorcraft) was initially implemented to model conventional rotorcraft propulsion systems, consisting of turboshaft engines burning jet fuel, connected to one or more rotors through a mechanical transmission. The NDARC propulsion system representation has been extended to cover additional propulsion concepts, including electric motors and generators, rotor reaction drive, turbojet and turbofan engines, fuel cells and solar cells, batteries, and fuel (energy) used without weight change. The paper describes these propulsion system components, the architecture of their implementation in NDARC, and the form of the models for performance and weight. Requirements are defined for improved performance and weight models of the new propulsion system components. With these new propulsion models, NDARC can be used to develop environmentally-friendly rotorcraft designs.
Mathematical modeling of solid cancer growth with angiogenesis
2012-01-01
Background Cancer arises when within a single cell multiple malfunctions of control systems occur, which are, broadly, the system that promote cell growth and the system that protect against erratic growth. Additional systems within the cell must be corrupted so that a cancer cell, to form a mass of any real size, produces substances that promote the growth of new blood vessels. Multiple mutations are required before a normal cell can become a cancer cell by corruption of multiple growth-promoting systems. Methods We develop a simple mathematical model to describe the solid cancer growth dynamics inducing angiogenesis in the absence of cancer controlling mechanisms. Results The initial conditions supplied to the dynamical system consist of a perturbation in form of pulse: The origin of cancer cells from normal cells of an organ of human body. Thresholds of interacting parameters were obtained from the steady states analysis. The existence of two equilibrium points determine the strong dependency of dynamical trajectories on the initial conditions. The thresholds can be used to control cancer. Conclusions Cancer can be settled in an organ if the following combination matches: better fitness of cancer cells, decrease in the efficiency of the repairing systems, increase in the capacity of sprouting from existing vascularization, and higher capacity of mounting up new vascularization. However, we show that cancer is rarely induced in organs (or tissues) displaying an efficient (numerically and functionally) reparative or regenerative mechanism. PMID:22300422
Mathematical modeling based on ordinary differential equations: A promising approach to vaccinology
Bonin, Carla Rezende Barbosa; Fernandes, Guilherme Cortes; dos Santos, Rodrigo Weber; Lobosco, Marcelo
2017-01-01
ABSTRACT New contributions that aim to accelerate the development or to improve the efficacy and safety of vaccines arise from many different areas of research and technology. One of these areas is computational science, which traditionally participates in the initial steps, such as the pre-screening of active substances that have the potential to become a vaccine antigen. In this work, we present another promising way to use computational science in vaccinology: mathematical and computational models of important cell and protein dynamics of the immune system. A system of Ordinary Differential Equations represents different immune system populations, such as B cells and T cells, antigen presenting cells and antibodies. In this way, it is possible to simulate, in silico, the immune response to vaccines under development or under study. Distinct scenarios can be simulated by varying parameters of the mathematical model. As a proof of concept, we developed a model of the immune response to vaccination against the yellow fever. Our simulations have shown consistent results when compared with experimental data available in the literature. The model is generic enough to represent the action of other diseases or vaccines in the human immune system, such as dengue and Zika virus. PMID:28027002
Mathematical modeling based on ordinary differential equations: A promising approach to vaccinology.
Bonin, Carla Rezende Barbosa; Fernandes, Guilherme Cortes; Dos Santos, Rodrigo Weber; Lobosco, Marcelo
2017-02-01
New contributions that aim to accelerate the development or to improve the efficacy and safety of vaccines arise from many different areas of research and technology. One of these areas is computational science, which traditionally participates in the initial steps, such as the pre-screening of active substances that have the potential to become a vaccine antigen. In this work, we present another promising way to use computational science in vaccinology: mathematical and computational models of important cell and protein dynamics of the immune system. A system of Ordinary Differential Equations represents different immune system populations, such as B cells and T cells, antigen presenting cells and antibodies. In this way, it is possible to simulate, in silico, the immune response to vaccines under development or under study. Distinct scenarios can be simulated by varying parameters of the mathematical model. As a proof of concept, we developed a model of the immune response to vaccination against the yellow fever. Our simulations have shown consistent results when compared with experimental data available in the literature. The model is generic enough to represent the action of other diseases or vaccines in the human immune system, such as dengue and Zika virus.
Petri, Robert Michael; Hackel, Alexander; Hahnel, Katrin; Dumitru, Claudia Alexandra; Bruderek, Kirsten; Flohe, Stefanie B; Paschen, Annette; Lang, Stephan; Brandau, Sven
2017-09-12
The interaction of mesenchymal stromal cells (MSCs) with natural killer (NK) cells is traditionally thought of as a static inhibitory model, whereby resting MSCs inhibit NK cell effector function. Here, we use a dynamic in vitro system of poly(I:C) stimulation to model the interaction of NK cells and tissue-resident MSCs in the context of infection or tissue injury. The experiments suggest a time-dependent system of regulation and feedback, where, at early time points, activated MSCs secrete type I interferon to enhance NK cell effector function, while at later time points TGF-β and IL-6 limit NK cell effector function and terminate inflammatory responses by induction of a regulatory senescent-like NK cell phenotype. Importantly, feedback of these regulatory NK cells to MSCs promotes survival, proliferation, and pro-angiogenic properties. Our data provide additional insight into the interaction of stromal cells and innate immune cells and suggest a model of time-dependent MSC polarization and licensing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
A Simple Protein Synthesis Model for the PURE System Operation.
Mavelli, Fabio; Marangoni, Roberto; Stano, Pasquale
2015-06-01
The encapsulation of transcription-translation (TX-TL) cell-free machinery inside lipid vesicles (liposomes) is a key element in synthetic cell technology. The PURE system is a TX-TL kit composed of well-characterized parts, whose concentrations are fine tunable, which works according to a modular architecture. For these reasons, the PURE system perfectly fulfils the requirements of synthetic biology and is widely used for constructing synthetic cells. In this work, we present a simplified mathematical model to simulate the PURE system operations. Based on Michaelis-Menten kinetics and differential equations, the model describes protein synthesis dynamics by using 9 chemical species, 6 reactions and 16 kinetic parameters. The model correctly predicts the time course for messenger RNA and protein production and allows quantitative predictions. By means of this model, it is possible to foresee how the PURE system species affect the mechanism of proteins synthesis and therefore help in understanding scenarios where the concentration of the PURE system components has been modified purposely or as a result of stochastic fluctuations (for example after random encapsulation inside vesicles). The model also makes the determination of response coefficients for all species involved in the TX-TL mechanism possible and allows for scrutiny on how chemical energy is consumed by the three PURE system modules (transcription, translation and aminoacylation).
Empirical membrane lifetime model for heavy duty fuel cell systems
NASA Astrophysics Data System (ADS)
Macauley, Natalia; Watson, Mark; Lauritzen, Michael; Knights, Shanna; Wang, G. Gary; Kjeang, Erik
2016-12-01
Heavy duty fuel cells used in transportation system applications such as transit buses expose the fuel cell membranes to conditions that can lead to lifetime-limiting membrane failure via combined chemical and mechanical degradation. Highly durable membranes and reliable predictive models are therefore needed in order to achieve the ultimate heavy duty fuel cell lifetime target of 25,000 h. In the present work, an empirical membrane lifetime model was developed based on laboratory data from a suite of accelerated membrane durability tests. The model considers the effects of cell voltage, temperature, oxygen concentration, humidity cycling, humidity level, and platinum in the membrane using inverse power law and exponential relationships within the framework of a general log-linear Weibull life-stress statistical distribution. The obtained model is capable of extrapolating the membrane lifetime from accelerated test conditions to use level conditions during field operation. Based on typical conditions for the Whistler, British Columbia fuel cell transit bus fleet, the model predicts a stack lifetime of 17,500 h and a membrane leak initiation time of 9200 h. Validation performed with the aid of a field operated stack confirmed the initial goal of the model to predict membrane lifetime within 20% of the actual operating time.
Morrison, Jennifer A; Pike, Laura A; Lund, Greg; Zhou, Qiong; Kessler, Brittelle E; Bauerle, Kevin T; Sams, Sharon B; Haugen, Bryan R; Schweppe, Rebecca E
2015-06-01
Thyroid cancer incidence has been increasing over time, and it is estimated that ∼1950 advanced thyroid cancer patients will die of their disease in 2015. To combat this disease, an enhanced understanding of thyroid cancer development and progression as well as the development of efficacious, targeted therapies are needed. In vitro and in vivo studies utilizing thyroid cancer cell lines and animal models are critically important to these research efforts. In this report, we detail our studies with a panel of authenticated human anaplastic and papillary thyroid cancer (ATC and PTC) cell lines engineered to express firefly luciferase in two in vivo murine cancer models-an orthotopic thyroid cancer model as well as an intracardiac injection metastasis model. In these models, primary tumor growth in the orthotopic model and the establishment and growth of metastases in the intracardiac injection model are followed in vivo using an IVIS imaging system. In the orthotopic model, the ATC cell lines 8505C and T238 and the PTC cell lines K1/GLAG-66 and BCPAP had take rates >90 % with final tumor volumes ranging 84-214 mm(3) over 4-5 weeks. In the intracardiac model, metastasis establishment was successful in the ATC cell lines HTh74, HTh7, 8505C, THJ-16T, and Cal62 with take rates ≥70 %. Only one of the PTC cell lines tested (BCPAP) was successful in the intracardiac model with a take rate of 30 %. These data will be beneficial to inform the choice of cell line and model system for the design of future thyroid cancer studies.
In Vitro Microfluidic Models for Neurodegenerative Disorders.
Osaki, Tatsuya; Shin, Yoojin; Sivathanu, Vivek; Campisi, Marco; Kamm, Roger D
2018-01-01
Microfluidic devices enable novel means of emulating neurodegenerative disease pathophysiology in vitro. These organ-on-a-chip systems can potentially reduce animal testing and substitute (or augment) simple 2D culture systems. Reconstituting critical features of neurodegenerative diseases in a biomimetic system using microfluidics can thereby accelerate drug discovery and improve our understanding of the mechanisms of several currently incurable diseases. This review describes latest advances in modeling neurodegenerative diseases in the central nervous system and the peripheral nervous system. First, this study summarizes fundamental advantages of microfluidic devices in the creation of compartmentalized cell culture microenvironments for the co-culture of neurons, glial cells, endothelial cells, and skeletal muscle cells and in their recapitulation of spatiotemporal chemical gradients and mechanical microenvironments. Then, this reviews neurodegenerative-disease-on-a-chip models focusing on Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Finally, this study discusses about current drawbacks of these models and strategies that may overcome them. These organ-on-chip technologies can be useful to be the first line of testing line in drug development and toxicology studies, which can contribute significantly to minimize the phase of animal testing steps. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Direct methanol fuel cells: A database-driven design procedure
NASA Astrophysics Data System (ADS)
Flipsen, S. F. J.; Spitas, C.
2011-10-01
To test the feasibility of DMFC systems in preliminary stages of the design process the design engineer can make use of heuristic models identifying the opportunity of DMFC systems in a specific application. In general these models are to generic and have a low accuracy. To improve the accuracy a second-order model is proposed in this paper. The second-order model consists of an evolutionary algorithm written in Mathematica, which selects a component-set satisfying the fuel-cell systems' performance requirements, places the components in 3D space and optimizes for volume. The results are presented as a 3D draft proposal together with a feasibility metric. To test the algorithm the design of DMFC system applied in the MP3 player is evaluated. The results show that volume and costs are an issue for the feasibility of the fuel-cell power-system applied in the MP3 player. The generated designs and the algorithm are evaluated and recommendations are given.
Modeling human disease using organotypic cultures.
Schweiger, Pawel J; Jensen, Kim B
2016-12-01
Reliable disease models are needed in order to improve quality of healthcare. This includes gaining better understanding of disease mechanisms, developing new therapeutic interventions and personalizing treatment. Up-to-date, the majority of our knowledge about disease states comes from in vivo animal models and in vitro cell culture systems. However, it has been exceedingly difficult to model disease at the tissue level. Since recently, the gap between cell line studies and in vivo modeling has been narrowing thanks to progress in biomaterials and stem cell research. Development of reliable 3D culture systems has enabled a rapid expansion of sophisticated in vitro models. Here we focus on some of the latest advances and future perspectives in 3D organoids for human disease modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.
Adamo, Federica; Farina, Marco; Thekkedath, Usha R; Grattoni, Alessandro; Sesana, Raffaella
2018-06-01
Cell transplantation in bioengineered scaffolds and encapsulation systems has shown great promise in regenerative medicine. Depending on the site of implantation, type of cells and their expected function, these systems are designed to provide cells with a physiological-like environment while providing mechanical support and promoting long-term viability and function of the graft. A minimally invasive 3D printed system termed neovascularized implantable cell homing and encapsulation (NICHE) was developed in polylactic acid for subcutaneous transplantation of endocrine cells, including pancreatic islets. The suitability of the NICHE for long term in vivo deployment is investigated by assessing mechanical behavior of both fresh devices under simulated subcutaneous conditions and NICHE retrieved from subcutaneous implantation in pigs. Both experimental and numerical studies were performed with a focus on validating the constitutive material model used in the numerical analysis for accuracy and reliability. Notably, homogeneous isotropic constitutive material model calibrated by means of uniaxial testing well suited experimental results. The results highlight the long term durability for in vivo applications and the potential applicability of the model to predict the mechanical behavior of similar devices in various physiological settings. Copyright © 2018 Elsevier Ltd. All rights reserved.
Laboratory models for central nervous system tumor stem cell research.
Khan, Imad Saeed; Ehtesham, Moneeb
2015-01-01
Central nervous system (CNS) tumors are complex organ systems comprising of a neoplastic component with associated vasculature, inflammatory cells, and reactive cellular and extracellular components. Research has identified a subset of cells in CNS tumors that portray defining properties of neural stem cells, namely, that of self-renewal and multi-potency. Growing evidence suggests that these tumor stem cells (TSC) play an important role in the maintenance and growth of the tumor. Furthermore, these cells have also been shown to be refractory to conventional therapy and may be crucial for tumor recurrence and metastasis. Current investigations are focusing on isolating these TSC from CNS tumors to investigate their unique biological processes. This understanding will help identify and develop more effective and comprehensive treatment strategies. This chapter provides an overview of some of the most commonly used laboratory models for CNSTSC research.
NASA Astrophysics Data System (ADS)
Radisavljevic, Verica
2011-10-01
In this paper we first show that the linear models of proton exchange membrane (polymer electrolyte membrane, PEM) and solid oxide (SO) fuel cells, commonly used in power and energy literature, are not controllable. The source of uncontrollability is the equation for pressure of the water vapor that is only affected by the fuel cell current, which in fact is a disturbance in this system and cannot be controlled by the given model inputs: inlet molar flow rates of hydrogen and oxygen. Being uncontrollable these models are not good candidates for studying control of dynamic processes in PEM and SO fuel cells. However, due to their simplicity, they can be used in hybrid configurations with other energy producing devices such as photovoltaic (solar) cells, wind turbine, micro gas turbine, battery (ultra capacitor) to demonstrate some other phenomena, but not for control purposes unless the hybrid models formed in such hybrid configurations are controllable. Testing controllability of such hybrid models is mandatory. Secondly, we introduce some algebraic constraints that follow from the model dynamics and the Nernst open-loop fuel cell voltage formula. These constraints must be satisfied in simulation of considered fuel cell modes, for example, via MATLAB/Simulink or any other computer software package.
de Oliveira, Vivian L.; Keijsers, Romy R. M. C.; van de Kerkhof, Peter C. M.; Seyger, Marieke M. B.; Fasse, Esther; Svensson, Lars; Latta, Markus; Norsgaard, Hanne; Labuda, Tord; Hupkens, Pieter; van Erp, Piet E. J.; Joosten, Irma; Koenen, Hans J. P. M.
2012-01-01
Humanized mouse models offer a challenging possibility to study human cell function in vivo. In the huPBL-SCID-huSkin allograft model human skin is transplanted onto immunodeficient mice and allowed to heal. Thereafter allogeneic human peripheral blood mononuclear cells are infused intra peritoneally to induce T cell mediated inflammation and microvessel destruction of the human skin. This model has great potential for in vivo study of human immune cells in (skin) inflammatory processes and for preclinical screening of systemically administered immunomodulating agents. Here we studied the inflammatory skin response of human keratinocytes and human T cells and the concomitant systemic human T cell response. As new findings in the inflamed human skin of the huPBL-SCID-huSkin model we here identified: 1. Parameters of dermal pathology that enable precise quantification of the local skin inflammatory response exemplified by acanthosis, increased expression of human β-defensin-2, Elafin, K16, Ki67 and reduced expression of K10 by microscopy and immunohistochemistry. 2. Induction of human cytokines and chemokines using quantitative real-time PCR. 3. Influx of inflammation associated IL-17A-producing human CD4+ and CD8+ T cells as well as immunoregulatory CD4+Foxp3+ cells using immunohistochemistry and -fluorescence, suggesting that active immune regulation is taking place locally in the inflamed skin. 4. Systemic responses that revealed activated and proliferating human CD4+ and CD8+ T cells that acquired homing marker expression of CD62L and CLA. Finally, we demonstrated the value of the newly identified parameters by showing significant changes upon systemic treatment with the T cell inhibitory agents cyclosporine-A and rapamycin. In summary, here we equipped the huPBL-SCID-huSkin humanized mouse model with relevant tools not only to quantify the inflammatory dermal response, but also to monitor the peripheral immune status. This combined approach will gain our understanding of the dermal immunopathology in humans and benefit the development of novel therapeutics for controlling inflammatory skin diseases. PMID:23094018
Mathematical modeling the radiation effects on humoral immunity
NASA Astrophysics Data System (ADS)
Smirnova, O.
One of the biological processes affecting the carcinogenesis is a response of humoral immune system to an antigen of malignant cells. Humoral immunity involves the production of protein molecules, antibodies, which can specifically bind to a certain antigen. This body system is radiosensitive. Therefore when simulating the radiation carcinogenesis, it is important to take into account the radiation effects on humoral immunity. To this end, a model of humoral immune response in irradiated mammals is developed. It is based on conventional theories and experimental facts. The model represents a system of nonlinear differential equations whose variables are the concentrations of antigen-sensitive immuno-competent cells carrying surface receptors and their bone-marrow precursor cells, as well as the concentrations of antibody-producing cells, antibodies, and an antigen. The dose of acute exposure and the dose rate of chronic exposure are the variable parameters in our approach. The model quantitatively reproduces the dynamics of the humoral immune response to the T-independent antigen (capsular antigen of Pasteurella pestis) in nonirradiated mammals (CBA mice). The model simulates the processes of the damage and recovery of the system of humoral immunity after acute exposure and predicts an adaptation of this system to low-level long-term chronic irradiation. These results give evidence that the developed model, after the appropriate identification, can be incorporated into a model of radiation carcinogenesis in humans. Together with a model of cellular immunity, such joined model will give capability to estimate the risk of radiation carcinogenesis for cosmonauts and astronauts on long space missions such as a voyage to Mars or a lunar colony.
Basel, Matthew T; Balivada, Sivasai; Wang, Hongwang; Shrestha, Tej B; Seo, Gwi Moon; Pyle, Marla; Abayaweera, Gayani; Dani, Raj; Koper, Olga B; Tamura, Masaaki; Chikan, Viktor; Bossmann, Stefan H; Troyer, Deryl L
2012-01-01
Using magnetic nanoparticles to absorb alternating magnetic field energy as a method of generating localized hyperthermia has been shown to be a potential cancer treatment. This report demonstrates a system that uses tumor homing cells to actively carry iron/iron oxide nanoparticles into tumor tissue for alternating magnetic field treatment. Paramagnetic iron/ iron oxide nanoparticles were synthesized and loaded into RAW264.7 cells (mouse monocyte/ macrophage-like cells), which have been shown to be tumor homing cells. A murine model of disseminated peritoneal pancreatic cancer was then generated by intraperitoneal injection of Pan02 cells. After tumor development, monocyte/macrophage-like cells loaded with iron/ iron oxide nanoparticles were injected intraperitoneally and allowed to migrate into the tumor. Three days after injection, mice were exposed to an alternating magnetic field for 20 minutes to cause the cell-delivered nanoparticles to generate heat. This treatment regimen was repeated three times. A survival study demonstrated that this system can significantly increase survival in a murine pancreatic cancer model, with an average post-tumor insertion life expectancy increase of 31%. This system has the potential to become a useful method for specifically and actively delivering nanoparticles for local hyperthermia treatment of cancer.
Tensegrity I. Cell structure and hierarchical systems biology
NASA Technical Reports Server (NTRS)
Ingber, Donald E.
2003-01-01
In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.
DOE Office of Scientific and Technical Information (OSTI.GOV)
King, D.L.
1995-11-01
The objective of this work was to develop improved performance model for modules and systems for for all operating conditions for use in module specifications, system and BOS component design, and system rating or monitoring. The approach taken was to identify and quantify the influence of dominant factors of solar irradiance, cell temperature, angle-of-incidence; and solar spectrum; use outdoor test procedures to separate the effects of electrical, thermal, and optical performance; use fundamental cell characteristics to improve analysis; and combine factors in simple model using the common variables.
NASA Astrophysics Data System (ADS)
Rǎdulescu, I. R.; Cândea, D.; Kaslik, E.
2017-01-01
In this paper, a delay differential equations (DDEs) model of leukemia is introduced and its dynamical properties are investigated in comparison with the modified fractional-order system where the Caputo's derivative is used. The model takes into account three types of division that a stem-like cell can undergo and cell competition between healthy and leukemia cell populations. The action of the immune system on the leukemic cell populations is also considered. The stability properties of the equilibrium points are established through numerical results and the differences between the two types of approaches are discussed. Medical conclusions are drawn in view of the obtained numerical simulations.
NASA Astrophysics Data System (ADS)
Han, Kyungreem; Kang, Hyuk; Choi, M. Y.; Kim, Jinwoong; Lee, Myung-Shik
2012-10-01
A theoretical approach to the glucose-insulin regulatory system is presented. By means of integrated mathematical modeling and extensive numerical simulations, we probe the cell-level dynamics of the membrane potential, intracellular Ca2+ concentration, and insulin secretion in pancreatic β-cells, together with the whole-body level glucose-insulin dynamics in the liver, brain, muscle, and adipose tissues. In particular, the three oscillatory modes of insulin secretion are reproduced successfully. Such comprehensive mathematical modeling may provide a theoretical basis for the simultaneous assessment of the β-cell function and insulin resistance in clinical examination.
Modeling the Soft Geometry of Biological Membranes
NASA Astrophysics Data System (ADS)
Daly, K.
This dissertation presents work done applying the techniques of physics to biological systems. The difference in length scales of the thickness of the phospolipid bilayer and overall size of a biological cell allows bilayer to be modeled elastically as a thin sheet. The Helfrich free energy is extended applied to models representing various biological systems, in order to find quasi-equilibrium states as well as transitions between states. Morphologies are approximated as axially sym-metric. Stable morphologies are de-termined analytically and through the use of computer simulation. The simple morphologies examined analytically give a model for the pearling transition seen in growing biological cells. An analytic model of celluar bulging in gram-negative bacteria predicts a critical pore radius for bulging of 20 nanometers. This model is extended to the membrane dynamics of human red blood cells, predicting three morphologic phases which are seen in vivo. A computer simulation was developed to study more complex morphologies with models representing different bilayer compositions. Single and multi-component bilayer models reproduce morphologies previously predicted by Seifert. A mean field model representing the intrinsic curvature of proteins coupling to membrane curvature is used to explore the stability of the particular morphology of rod outer segment cells. The process of pore formation and expansion in cell-cell fusion is not well understood. Simulation of the pore created in cell-cell fusion led to the finding of a minimal pore radius required for pore expansion, suggesting pores formed in nature are formed with a minimum size.
The Use of the Humanized Mouse Model in Gene Therapy and Immunotherapy for HIV and Cancer
Carrillo, Mayra A.; Zhen, Anjie; Kitchen, Scott G.
2018-01-01
HIV and cancer remain prevailing sources of morbidity and mortality worldwide. There are current efforts to discover novel therapeutic strategies for the treatment or cure of these diseases. Humanized mouse models provide the investigative tool to study the interaction between HIV or cancer and the human immune system in vivo. These humanized models consist of immunodeficient mice transplanted with human cells, tissues, or hematopoietic stem cells that result in reconstitution with a nearly full human immune system. In this review, we discuss preclinical studies evaluating therapeutic approaches in stem cell-based gene therapy and T cell-based immunotherapies for HIV and cancer using a humanized mouse model and some recent advances in using checkpoint inhibitors to improve antiviral or antitumor responses. PMID:29755454
NASA Technical Reports Server (NTRS)
Walker, Raymond J.; Ogino, Tatsuki
1988-01-01
A time-dependent three-dimensional MHD model was used to investigate the magnetospheric configuration as a function of the interplanetary magnetic field direction when it was in the y-z plane in geocentric solar magnetospheric coordinates. The model results show large global convection cells, tail lobe cells, high-latitude polarcap cells, and low latitude cells. The field-aligned currents generated in the model magnetosphere and the model convection system are compared with observations from low-altitude polar orbiting satellites.
Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism.
Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti
2014-01-01
Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.
Heuts, Frank; Nagy, Noemi
2017-01-01
Recent developments in mouse models that harbor part of a human immune system have proved extremely valuable to study the in vivo immune response to human specific pathogens such as Epstein-Barr virus. Over the last decades, advances in immunodeficient mouse strains that can be used as recipients for human immune cells have greatly enhanced the use of these models. Here, we describe the generation of mice with reconstituted human immune system (HIS mice) using immunocompromised mice transplanted with human CD34 + hematopoietic stem cells. We will also describe how such mice, in which human immune cells are generated de novo, can be used to study EBV infection.
Mechanically induced alterations in cultured skeletal muscle growth
NASA Technical Reports Server (NTRS)
Vandenburgh, H. H.; Hatfaludy, S.; Karlisch, P.; Shansky, J.
1991-01-01
Model systems are available for mechanically stimulating cultured skeletal muscle cells by passive tensile forces which simulate those found in vivo. When applied to embryonic muscle cells in vitro these forces induce tissue organogenesis, metabolic adaptations, and muscle cell growth. The mechanical stimulation of muscle cell growth correlates with stretch-induced increases in the efflux of prostaglandins PGE2 and PGF2(alpha) in a time and frequency dependent manner. These prostaglandins act as mechanical 'second messengers' regulating skeletal muscle protein turnover rates. Since they also effect bone remodelling in response to tissue loading and unloading, secreted prostaglandins may serve as paracrine growth factors, coordinating the growth rates of muscle and bone in response to external mechanical forces. Cell culture model systems will supplement other models in understanding mechanical transduction processes at the molecular level.
Modeling and simulation of an unmanned ground vehicle power system
NASA Astrophysics Data System (ADS)
Broderick, John; Hartner, Jack; Tilbury, Dawn M.; Atkins, Ella M.
2014-06-01
Long-duration missions challenge ground robot systems with respect to energy storage and efficient conversion to power on demand. Ground robot systems can contain multiple power sources such as fuel cell, battery and/or ultra-capacitor. This paper presents a hybrid systems framework for collectively modeling the dynamics and switching between these different power components. The hybrid system allows modeling power source on/off switching and different regimes of operation, together with continuous parameters such as state of charge, temperature, and power output. We apply this modeling framework to a fuel cell/battery power system applicable to unmanned ground vehicles such as Packbot or TALON. A simulation comparison of different control strategies is presented. These strategies are compared based on maximizing energy efficiency and meeting thermal constraints.
[Advance in study of vascular endothelial cell and smooth muscle cell co-culture system].
Li, Yujie; Yang, Qing; Weng, Xiaogang; Chen, Ying; Ruan, Congxiao; Li, Dan; Zhu, Xiaoxing
2012-02-01
The interactions between endothelial cells (EC) and smooth muscle cells (SMC) contribute to vascular physiological functions and also cause the occurrence and development of different kinds of diseases. Currently, EC-SMC co-culture model is the best way to study the interactions between the two kinds of cells. This article summarizes existing EC-SMC co-culture models and their effects on the structure and functions of the two kinds of cells. Microscopically speaking, it provides a basis for in-depth studies on their interactions as well as a reference for the establishment of in vitro EC-SMC co-culture system that is closer to organic physiology or pathology state.
Dynamics of cancerous tissue correlates with invasiveness
NASA Astrophysics Data System (ADS)
West, Ann-Katrine Vransø; Wullkopf, Lena; Christensen, Amalie; Leijnse, Natascha; Tarp, Jens Magelund; Mathiesen, Joachim; Erler, Janine Terra; Oddershede, Lene Broeng
2017-03-01
Two of the classical hallmarks of cancer are uncontrolled cell division and tissue invasion, which turn the disease into a systemic, life-threatening condition. Although both processes are studied, a clear correlation between cell division and motility of cancer cells has not been described previously. Here, we experimentally characterize the dynamics of invasive and non-invasive breast cancer tissues using human and murine model systems. The intrinsic tissue velocities, as well as the divergence and vorticity around a dividing cell correlate strongly with the invasive potential of the tissue, thus showing a distinct correlation between tissue dynamics and aggressiveness. We formulate a model which treats the tissue as a visco-elastic continuum. This model provides a valid reproduction of the cancerous tissue dynamics, thus, biological signaling is not needed to explain the observed tissue dynamics. The model returns the characteristic force exerted by an invading cell and reveals a strong correlation between force and invasiveness of breast cancer cells, thus pinpointing the importance of mechanics for cancer invasion.
A discrete cell model with adaptive signalling for aggregation of Dictyostelium discoideum.
Dallon, J C; Othmer, H G
1997-01-01
Dictyostelium discoideum (Dd) is a widely studied model system from which fundamental insights into cell movement, chemotaxis, aggregation and pattern formation can be gained. In this system aggregation results from the chemotactic response by dispersed amoebae to a travelling wave of the chemoattractant cAMP. We have developed a model in which the cells are treated as discrete points in a continuum field of the chemoattractant, and transduction of the extracellular cAMP signal into the intracellular signal is based on the G protein model developed by Tang & Othmer. The model reproduces a number of experimental observations and gives further insight into the aggregation process. We investigate different rules for cell movement the factors that influence stream formation the effect on aggregation of noise in the choice of the direction of movement and when spiral waves of chemoattractant and cell density are likely to occur. Our results give new insight into the origin of spiral waves and suggest that streaming is due to a finite amplitude instability. PMID:9134569
Modelling of robotic work cells using agent based-approach
NASA Astrophysics Data System (ADS)
Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.
2016-08-01
In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.
Estrada, Marta F; Rebelo, Sofia P; Davies, Emma J; Pinto, Marta T; Pereira, Hugo; Santo, Vítor E; Smalley, Matthew J; Barry, Simon T; Gualda, Emilio J; Alves, Paula M; Anderson, Elizabeth; Brito, Catarina
2016-02-01
3D cell tumour models are generated mainly in non-scalable culture systems, using bioactive scaffolds. Many of these models fail to reflect the complex tumour microenvironment and do not allow long-term monitoring of tumour progression. To overcome these limitations, we have combined alginate microencapsulation with agitation-based culture systems, to recapitulate and monitor key aspects of the tumour microenvironment and disease progression. Aggregates of MCF-7 breast cancer cells were microencapsulated in alginate, either alone or in combination with human fibroblasts, then cultured for 15 days. In co-cultures, the fibroblasts arranged themselves around the tumour aggregates creating distinct epithelial and stromal compartments. The presence of fibroblasts resulted in secretion of pro-inflammatory cytokines and deposition of collagen in the stromal compartment. Tumour cells established cell-cell contacts and polarised around small lumina in the interior of the aggregates. Over the culture period, there was a reduction in oestrogen receptor and membranous E-cadherin alongside loss of cell polarity, increased collective cell migration and enhanced angiogenic potential in co-cultures. These phenotypic alterations, typical of advanced stages of cancer, were not observed in the mono-cultures of MCF-7 cells. The proposed model system constitutes a new tool to study tumour-stroma crosstalk, disease progression and drug resistance mechanisms. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
NASA Astrophysics Data System (ADS)
Ristow, Alan H.
2008-10-01
Electricity generated from photovoltaics (PV) promises to satisfy the world's ever-growing thirst for energy without significant pollution and greenhouse gas emissions. At present, however, PV is several times too expensive to compete economically with conventional sources of electricity delivered via the power grid. To ensure long-term success, must achieve cost parity with electricity generated by conventional sources of electricity. This requires detailed understanding of the relationship between technology and economics as it pertains to PV devices and systems. The research tasks of this thesis focus on developing and using four types of models in concert to develop a complete picture of how solar cell technology and design choices affect the quantity and cost of energy produced by PV systems. It is shown in this thesis that high-efficiency solar cells can leverage balance-of-systems (BOS) costs to gain an economic advantage over solar cells with low efficiencies. This advantage is quantified and dubbed the "efficiency premium." Solar cell device models are linked to models of manufacturing cost and PV system performance to estimate both PV system cost and performance. These, in turn, are linked to a model of levelized electricity cost to estimate the per-kilowatt-hour cost of electricity produced by the PV system. A numerical PV module manufacturing cost model is developed to facilitate this analysis. The models and methods developed in this thesis are used to propose a roadmap to high-efficiency multicrystalline-silicon PV modules that achieve cost parity with electricity from the grid. The impact of PV system failures on the cost of electricity is also investigated; from this, a methodology is proposed for improving the reliability of PV inverters.
Examining a scaled dynamical system of telomere shortening
NASA Astrophysics Data System (ADS)
Cyrenne, Benoit M.; Gooding, Robert J.
2015-02-01
A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced model that incorporates stem cells as progenitors of new cells, imposes the Hayflick limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected via the introduction of scaled populations, rate constants and time. The application of this model to available leukocyte baboon data is discussed.
In Vitro Model of Tumor Cell Extravasation
Jeon, Jessie S.; Zervantonakis, Ioannis K.; Chung, Seok; Kamm, Roger D.; Charest, Joseph L.
2013-01-01
Tumor cells that disseminate from the primary tumor and survive the vascular system can eventually extravasate across the endothelium to metastasize at a secondary site. In this study, we developed a microfluidic system to mimic tumor cell extravasation where cancer cells can transmigrate across an endothelial monolayer into a hydrogel that models the extracellular space. The experimental protocol is optimized to ensure the formation of an intact endothelium prior to the introduction of tumor cells and also to observe tumor cell extravasation by having a suitable tumor seeding density. Extravasation is observed for 38.8% of the tumor cells in contact with the endothelium within 1 day after their introduction. Permeability of the EC monolayer as measured by the diffusion of fluorescently-labeled dextran across the monolayer increased 3.8 fold 24 hours after introducing tumor cells, suggesting that the presence of tumor cells increases endothelial permeability. The percent of tumor cells extravasated remained nearly constant from1 to 3 days after tumor seeding, indicating extravasation in our system generally occurs within the first 24 hours of tumor cell contact with the endothelium. PMID:23437268
Ma, Liang; Barker, Jeremy; Zhou, Changchun; Li, Wei; Zhang, Jing; Lin, Biaoyang; Foltz, Gregory; Küblbeck, Jenni; Honkakoski, Paavo
2013-01-01
A three-dimensional micro-scale perfusion-based two-chamber (3D-μPTC) tissue model system was developed to test the cytotoxicity of anticancer drugs in conjunction with liver metabolism. Liver cells with different cytochrome P450 (CYP) subtypes and glioblastoma multiforme (GBM) brain cancer cells were cultured in two separate chambers connected in tandem. Both chambers contained a 3D tissue engineering scaffold fabricated with biodegradable poly(lactic acid) (PLA) using a solvent-free approach. We used this model system to test the cytotoxicity of anticancer drugs, including temozolomide (TMZ) and ifosfamide (IFO). With the liver cells, TMZ showed a much lower toxicity to GBM cells under both 2D and 3D cell culture conditions. Comparing 2D, GBM cells cultured in 3D had much high viability under TMZ treatment. IFO was used to test the CYP-related metabolic effects. Cells with different expression levels of CYP3A4 differed dramatically in their ability to activate IFO, which led to strong metabolism-dependent cytotoxicity to GBM cells. These results demonstrate that our 3D-μPTC system could provide a more physiologically realistic in vitro environment than the current 2D monolayers for testing metabolism-dependent toxicity of anticancer drugs. It could therefore be used as an important platform for better prediction of drug dosing and schedule towards personalized medicine. PMID:22429982
Calibration of the head direction network: a role for symmetric angular head velocity cells.
Stratton, Peter; Wyeth, Gordon; Wiles, Janet
2010-06-01
Continuous attractor networks require calibration. Computational models of the head direction (HD) system of the rat usually assume that the connections that maintain HD neuron activity are pre-wired and static. Ongoing activity in these models relies on precise continuous attractor dynamics. It is currently unknown how such connections could be so precisely wired, and how accurate calibration is maintained in the face of ongoing noise and perturbation. Our adaptive attractor model of the HD system that uses symmetric angular head velocity (AHV) cells as a training signal shows that the HD system can learn to support stable firing patterns from poorly-performing, unstable starting conditions. The proposed calibration mechanism suggests a requirement for symmetric AHV cells, the existence of which has previously been unexplained, and predicts that symmetric and asymmetric AHV cells should be distinctly different (in morphology, synaptic targets and/or methods of action on postsynaptic HD cells) due to their distinctly different functions.
A Computational Framework for Bioimaging Simulation.
Watabe, Masaki; Arjunan, Satya N V; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi
2015-01-01
Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units.
NASA Astrophysics Data System (ADS)
Liu, Xiangdong; Li, Qingze; Pan, Jianxin
2018-06-01
Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.
Mathematical modeling and numerical simulation of the mitotic spindle orientation system.
Ibrahim, Bashar
2018-05-21
The mitotic spindle orientation and position is crucial for the fidelity of chromosome segregation during asymmetric cell division to generate daughter cells with different sizes or fates. This mechanism is best understood in the budding yeast Saccharomyces cerevisiae, named the spindle position checkpoint (SPOC). The SPOC inhibits cells from exiting mitosis until the mitotic spindle is properly oriented along the mother-daughter polarity axis. Despite many experimental studies, the mechanisms underlying SPOC regulation remains elusive and unexplored theoretically. Here, a minimal mathematical is developed to describe SPOC activation and silencing having autocatalytic feedback-loop. Numerical simulations of the nonlinear ordinary differential equations (ODEs) model accurately reproduce the phenotype of SPOC mechanism. Bifurcation analysis of the nonlinear ODEs reveals the orientation dependency on spindle pole bodies, and how this dependence is altered by parameter values. These results provide for systems understanding on the molecular organization of spindle orientation system via mathematical modeling. The presented mathematical model is easy to understand and, within the above mentioned context, can be used as a base for further development of quantitative models in asymmetric cell-division. Copyright © 2018. Published by Elsevier Inc.
Correlated receptor transport processes buffer single-cell heterogeneity
Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland
2017-01-01
Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754
Microphysiological models of the developing nervous system (SOT workshop session overview)
Recent advances using human stem cells and other cells that can be ushered through differentiation and developmental maturation offer an unprecedented opportunity to develop predictive systems for toxicological assessment. The use of human cells is an advantage because there is n...
Dynamics of an HIV-1 infection model with cell mediated immunity
NASA Astrophysics Data System (ADS)
Yu, Pei; Huang, Jianing; Jiang, Jiao
2014-10-01
In this paper, we study the dynamics of an improved mathematical model on HIV-1 virus with cell mediated immunity. This new 5-dimensional model is based on the combination of a basic 3-dimensional HIV-1 model and a 4-dimensional immunity response model, which more realistically describes dynamics between the uninfected cells, infected cells, virus, the CTL response cells and CTL effector cells. Our 5-dimensional model may be reduced to the 4-dimensional model by applying a quasi-steady state assumption on the variable of virus. However, it is shown in this paper that virus is necessary to be involved in the modeling, and that a quasi-steady state assumption should be applied carefully, which may miss some important dynamical behavior of the system. Detailed bifurcation analysis is given to show that the system has three equilibrium solutions, namely the infection-free equilibrium, the infectious equilibrium without CTL, and the infectious equilibrium with CTL, and a series of bifurcations including two transcritical bifurcations and one or two possible Hopf bifurcations occur from these three equilibria as the basic reproduction number is varied. The mathematical methods applied in this paper include characteristic equations, Routh-Hurwitz condition, fluctuation lemma, Lyapunov function and computation of normal forms. Numerical simulation is also presented to demonstrate the applicability of the theoretical predictions.
Modeling Local Interactions during the Motion of Cyanobacteria
Galante, Amanda; Wisen, Susanne; Bhaya, Devaki; Levy, Doron
2012-01-01
Synechocystis sp., a common unicellular freshwater cyanobacterium, has been used as a model organism to study phototaxis, an ability to move in the direction of a light source. This microorganism displays a number of additional characteristics such as delayed motion, surface dependence, and a quasi-random motion, where cells move in a seemingly disordered fashion instead of in the direction of the light source, a global force on the system. These unexplained motions are thought to be modulated by local interactions between cells such as intercellular communication. In this paper, we consider only local interactions of these phototactic cells in order to mathematically model this quasi-random motion. We analyze an experimental data set to illustrate the presence of quasi-random motion and then derive a stochastic dynamic particle system modeling interacting phototactic cells. The simulations of our model are consistent with experimentally observed phototactic motion. PMID:22713858
Space-time dynamics of Stem Cell Niches: a unified approach for Plants.
Pérez, Maria Del Carmen; López, Alejandro; Padilla, Pablo
2013-06-01
Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.
Space-time dynamics of stem cell niches: a unified approach for plants.
Pérez, Maria del Carmen; López, Alejandro; Padilla, Pablo
2013-04-02
Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.
Nayhouse, Michael; Kwon, Joseph Sang-Il; Orkoulas, G
2012-05-28
In simulation studies of fluid-solid transitions, the solid phase is usually modeled as a constrained system in which each particle is confined to move in a single Wigner-Seitz cell. The constrained cell model has been used in the determination of fluid-solid coexistence via thermodynamic integration and other techniques. In the present work, the phase diagram of such a constrained system of Lennard-Jones particles is determined from constant-pressure simulations. The pressure-density isotherms exhibit inflection points which are interpreted as the mechanical stability limit of the solid phase. The phase diagram of the constrained system contains a critical and a triple point. The temperature and pressure at the critical and the triple point are both higher than those of the unconstrained system due to the reduction in the entropy caused by the single occupancy constraint.
Analysis and Test of a Proton Exchange Membrane Fuel Cell Power System for Space Power Applications
NASA Technical Reports Server (NTRS)
Vasquez, Arturo; Varanauski, Donald; Clark, Robert, Jr.
2000-01-01
An effort is underway to develop a prototype Proton Exchange Membrane (PEM) Fuel Cell breadboard system for fuhlre space applications. This prototype will be used to develop a comprehensive design basis for a space-rated PEM fuel cell powerplant. The prototype system includes reactant pressure regulators, ejector-based reactant pumps, a 4-kW fuel cell stack and cooling system, and a passive, membranebased oxygen / water separator. A computer model is being developed concurrently to analytically predict fluid flow in the oxidant reactant system. Fuel cells have historically played an important role in human-rated spacecraft. The Gemini and Apollo spacecraft used fuel cells for vehicle electrical power. The Space Shuttle currently uses three Alkaline Fuel Cell Powerplants (AFCP) to generate all of the vehicle's 15-20kW electrical power. Engineers at the Johnson Space Center have leveraged off the development effort ongoing in the commercial arena to develop PEM fuel cel ls for terrestrial uses. The prototype design originated from efforts to develop a PEM fuel cell replacement for the current Space Shuttle AFCP' s. In order to improve on the life and an already excellent hi storical record of reliability and safety, three subsystems were focused on. These were the fuel cell stack itself, the reactant circulation devices, and reactant / product water separator. PEM fuel cell stack performance is already demonstrating the potential for greater than four times the useful life of the current Shuttle's AFCP. Reactant pumping for product water removal has historically been accomplished with mechanical pumps. Ejectors offer an effective means of reactant pumping as well as the potential for weight reduction, control simplification, and long life. Centrifugal water separation is used on the current AFCP. A passive, membrane-based water separator offers compatibility with the micro-gravity environment of space, and the potential for control simplification, elimination of moving parts in an oxygen environment, and long life. The prototype system has been assembled from components that have previously been tested and evaluated at the component level. Preliminary data obtained from tests performed with the prototype system, as well as other published data, has been used to validate the analytical component models. These components have been incorporated into an integrated oxidant fluid system model. Results obtained from both the performance tests and the analytical model are presented.
Chen, Jiao; Weihs, Daphne; Vermolen, Fred J
2018-04-01
Cell migration, known as an orchestrated movement of cells, is crucially important for wound healing, tumor growth, immune response as well as other biomedical processes. This paper presents a cell-based model to describe cell migration in non-isotropic fibrin networks around pancreatic tumor islets. This migration is determined by the mechanical strain energy density as well as cytokines-driven chemotaxis. Cell displacement is modeled by solving a large system of ordinary stochastic differential equations where the stochastic parts result from random walk. The stochastic differential equations are solved by the use of the classical Euler-Maruyama method. In this paper, the influence of anisotropic stromal extracellular matrix in pancreatic tumor islets on T-lymphocytes migration in different immune systems is investigated. As a result, tumor peripheral stromal extracellular matrix impedes the immune response of T-lymphocytes through changing direction of their migration.
Guo, Ling; Luo, Shi; Du, Zhengwu; Zhou, Meiling; Li, Peiwen; Fu, Yao; Sun, Xun; Huang, Yuan; Zhang, Zhirong
2017-10-12
Mesangial cells-mediated glomerulonephritis is a frequent cause of end-stage renal disease. Here, we show that celastrol is effective in treating both reversible and irreversible mesangioproliferative glomerulonephritis in rat models, but find that its off-target distributions cause severe systemic toxicity. We thus target celastrol to mesangial cells using albumin nanoparticles. Celastrol-albumin nanoparticles crosses fenestrated endothelium and accumulates in mesangial cells, alleviating proteinuria, inflammation, glomerular hypercellularity, and excessive extracellular matrix deposition in rat anti-Thy1.1 nephritis models. Celastrol-albumin nanoparticles presents lower drug accumulation than free celastrol in off-target organs and tissues, thereby minimizing celastrol-related systemic toxicity. Celastrol-albumin nanoparticles thus represents a promising treatment option for mesangioproliferative glomerulonephritis and similar glomerular diseases.Mesangial cell-mediated glomerulonephritis is a frequent cause of kidney disease. Here the authors show that celastrol loaded in albumin nanoparticles efficiently targets mesangial cells, and is effective in rat models.
NASA Astrophysics Data System (ADS)
Duan, J.; Lu, X.; He, G.
2017-01-01
In this work, a co-culture system with liver cancer cell line HepG2 and normal cell line L02 is used to investigate the selective effect on cancer and normal cells by plasma activated medium (PAM), which is closer to the real environment where cancer cells develop. Besides, the co-culture system is a better model to study the selective effect than the widely used separate culture systems, where the cancer cell line and normal cell line are cultured independently. By using the co-culture system, it is found that there is an optimum dose of PAM to induce significant cancer cell apoptosis while keeping minimum damage to normal cells.
Pieczywek, Piotr M; Zdunek, Artur
2017-10-18
A hybrid model based on a mass-spring system methodology coupled with the discrete element method (DEM) was implemented to simulate the deformation of cellular structures in 3D. Models of individual cells were constructed using the particles which cover the surfaces of cell walls and are interconnected in a triangle mesh network by viscoelastic springs. The spatial arrangement of the cells required to construct a virtual tissue was obtained using Poisson-disc sampling and Voronoi tessellation in 3D space. Three structural features were included in the model: viscoelastic material of cell walls, linearly elastic interior of the cells (simulating compressible liquid) and a gas phase in the intercellular spaces. The response of the models to an external load was demonstrated during quasi-static compression simulations. The sensitivity of the model was investigated at fixed compression parameters with variable tissue porosity, cell size and cell wall properties, such as thickness and Young's modulus, and a stiffness of the cell interior that simulated turgor pressure. The extent of the agreement between the simulation results and other models published is discussed. The model demonstrated the significant influence of tissue structure on micromechanical properties and allowed for the interpretation of the compression test results with respect to changes occurring in the structure of the virtual tissue. During compression virtual structures composed of smaller cells produced higher reaction forces and therefore they were stiffer than structures with large cells. The increase in the number of intercellular spaces (porosity) resulted in a decrease in reaction forces. The numerical model was capable of simulating the quasi-static compression experiment and reproducing the strain stiffening observed in experiment. Stress accumulation at the edges of the cell walls where three cells meet suggests that cell-to-cell debonding and crack propagation through the contact edge of neighboring cells is one of the most prevalent ways for tissue to rupture.
An oscillating dynamic model of collective cells in a monolayer
NASA Astrophysics Data System (ADS)
Lin, Shao-Zhen; Xue, Shi-Lei; Li, Bo; Feng, Xi-Qiao
2018-03-01
Periodic oscillations of collective cells occur in the morphogenesis and organogenesis of various tissues and organs. In this paper, an oscillating cytodynamic model is presented by integrating the chemomechanical interplay between the RhoA effector signaling pathway and cell deformation. We show that both an isolated cell and a cell aggregate can undergo spontaneous oscillations as a result of Hopf bifurcation, upon which the system evolves into a limit cycle of chemomechanical oscillations. The dynamic characteristics are tailored by the mechanical properties of cells (e.g., elasticity, contractility, and intercellular tension) and the chemical reactions involved in the RhoA effector signaling pathway. External forces are found to modulate the oscillation intensity of collective cells in the monolayer and to polarize their oscillations along the direction of external tension. The proposed cytodynamic model can recapitulate the prominent features of cell oscillations observed in a variety of experiments, including both isolated cells (e.g., spreading mouse embryonic fibroblasts, migrating amoeboid cells, and suspending 3T3 fibroblasts) and multicellular systems (e.g., Drosophila embryogenesis and oogenesis).
Radiogenic cell transformation and carcinogenesis
NASA Technical Reports Server (NTRS)
Yang, T. C.; Georgy, K. A.; Mei, M.; Durante, M.; Craise, L. M.
1995-01-01
Radiation carcinogenesis is one of the major biological effects considered important in the risk assessment for space travel. Various biological model systems, including both cultured cells and animals, have been found useful for studying the carcinogenic effects of space radiations, which consist of energetic electrons, protons and heavy ions. The development of techniques for studying neoplastic cell transformation in culture has made it possible to examine the cellular and molecular mechanisms of radiation carcinogenesis. Cultured cell systems are thus complementary to animal models. Many investigators have determined the oncogenic effects of ionizing and nonionizing radiation in cultured mammalian cells. One of the cell systems used most often for radiation transformation studies is mouse embryonic cells (C3H10T1/2), which are easy to culture and give good quantitative dose-response curves. Relative biological effectiveness (RBE) for heavy ions with various energies and linear energy transfer (LET) have been obtained with this cell system. Similar RBE and LET relationship was observed by investigators for other cell systems. In addition to RBE measurements, fundamental questions on repair of sub- and potential oncogenic lesions, direct and indirect effect, primary target and lesion, the importance of cell-cell interaction and the role of oncogenes and tumor suppressor genes in radiogenic carcinogenesis have been studied, and interesting results have been found. Recently several human epithelial cell systems have been developed, and ionizing radiation have been shown to transform these cells. Oncogenic transformation of these cells, however, requires a long expression time and/or multiple radiation exposures. Limited experimental data indicate high-LET heavy ions can be more effective than low-LET radiation in inducing cell transformation. Cytogenetic and molecular analyses can be performed with cloned transformants to provide insights into basic genetic mechanism(s) of radiogenic transformation of human epithelial cells.
Validation of a model for investigating red cell mass changes during weightlessness
NASA Technical Reports Server (NTRS)
Leonard, J. I.
1976-01-01
The model, both the conceptual model and simulation model, provided a convenient framework on which to demonstrate the commonality between such diverse stresses as descent from altitude, red cell infusions, bed rest, and weightlessness. The results suggest that all of these stresses induce an increased blood hematocrit leading to tissue hyperoxia and eventual inhibition of the erythyocyte producing circuit until the hyperoxic condition is relieved. The erythropoietic system was acting, in these situations, as if it were an hematocrit sensor and regulator. In these terms the decreases in red cell mass during Skylab may be explained in terms of normal feedback regulation of the erythropoietic system in the face of sustained decreases in plasma colume.
Mast cell heterogeneity underlies different manifestations of food allergy in mice
Benedé, Sara
2018-01-01
Food can trigger a diverse array of symptoms in food allergic individuals from isolated local symptoms affecting skin or gut to multi-system severe reactions (systemic anaphylaxis). Although we know that gastrointestinal and systemic manifestations of food allergy are mediated by tissue mast cells (MCs), it is not clear why allergen exposure by the oral route can result in such distinct clinical manifestations. Our aim was to assess the contribution of mast cell subsets to different manifestations of food allergy. We used two common models of IgE-mediated food allergy, one resulting in systemic anaphylaxis and the other resulting in acute gastrointestinal symptoms, to study the immune basis of allergic reactions. We used responders and non-responders in each model system, as well as naïve controls to identify the association of mast cell activation with clinical reactivity rather than sensitization. Systemic anaphylaxis was uniquely associated with activation of connective tissue mast cells (identified by release of mouse mast cell protease (MMCP) -7 into the serum) and release of histamine, while activation of mucosal mast cells (identified by release of MMCP-1 in the serum) did not correlate with symptoms. Gastrointestinal manifestations of food allergy were associated with an increase of MMCP-1-expressing mast cells in the intestine, and evidence of both mucosal and connective tissue mast cell activation. The data presented in this paper demonstrates that mast cell heterogeneity is an important contributor to manifestations of food allergy, and identifies the connective tissue mast cell subset as key in the development of severe systemic anaphylaxis. PMID:29370173
Caenorhabditis elegans in regenerative medicine: a simple model for a complex discipline.
Aitlhadj, Layla; Stürzenbaum, Stephen R
2014-06-01
Stem cell research is a major focus of regenerative medicine, which amalgamates diverse disciplines ranging from developmental cell biology to chemical and genetic therapy. Although embryonic stem cells have provided the foundation of stem cell therapy, they offer an in vitro study system that might not provide the best insight into mechanisms and behaviour of cells within living organisms. Caenorhabditis elegans is a well defined model organism with highly conserved cell development and signalling processes that specify cell fate. Its genetic amenability coupled with its chemical screening applicability make the nematode well suited as an in vivo system in which regenerative therapy and stem cell processes can be explored. Here, we describe some of the major advances in stem cell research from the worm's perspective. Copyright © 2014 Elsevier Ltd. All rights reserved.
An Off-Lattice Hybrid Discrete-Continuum Model of Tumor Growth and Invasion
Jeon, Junhwan; Quaranta, Vito; Cummings, Peter T.
2010-01-01
Abstract We have developed an off-lattice hybrid discrete-continuum (OLHDC) model of tumor growth and invasion. The continuum part of the OLHDC model describes microenvironmental components such as matrix-degrading enzymes, nutrients or oxygen, and extracellular matrix (ECM) concentrations, whereas the discrete portion represents individual cell behavior such as cell cycle, cell-cell, and cell-ECM interactions and cell motility by the often-used persistent random walk, which can be depicted by the Langevin equation. Using this framework of the OLHDC model, we develop a phenomenologically realistic and bio/physically relevant model that encompasses the experimentally observed superdiffusive behavior (at short times) of mammalian cells. When systemic simulations based on the OLHDC model are performed, tumor growth and its morphology are found to be strongly affected by cell-cell adhesion and haptotaxis. There is a combination of the strength of cell-cell adhesion and haptotaxis in which fingerlike shapes, characteristic of invasive tumor, are observed. PMID:20074513
Feasibility of solid oxide fuel cell dynamic hydrogen coproduction to meet building demand
NASA Astrophysics Data System (ADS)
Shaffer, Brendan; Brouwer, Jacob
2014-02-01
A dynamic internal reforming-solid oxide fuel cell system model is developed and used to simulate the coproduction of electricity and hydrogen while meeting the measured dynamic load of a typical southern California commercial building. The simulated direct internal reforming-solid oxide fuel cell (DIR-SOFC) system is controlled to become an electrical load following device that well follows the measured building load data (3-s resolution). The feasibility of the DIR-SOFC system to meet the dynamic building demand while co-producing hydrogen is demonstrated. The resulting thermal responses of the system to the electrical load dynamics as well as those dynamics associated with the filling of a hydrogen collection tank are investigated. The DIR-SOFC system model also allows for resolution of the fuel cell species and temperature distributions during these dynamics since thermal gradients are a concern for DIR-SOFC.
Feinerman, Ofer; Jentsch, Garrit; Tkach, Karen E; Coward, Jesse W; Hathorn, Matthew M; Sneddon, Michael W; Emonet, Thierry; Smith, Kendall A; Altan-Bonnet, Grégoire
2010-01-01
Understanding how the immune system decides between tolerance and activation by antigens requires addressing cytokine regulation as a highly dynamic process. We quantified the dynamics of interleukin-2 (IL-2) signaling in a population of T cells during an immune response by combining in silico modeling and single-cell measurements in vitro. We demonstrate that IL-2 receptor expression levels vary widely among T cells creating a large variability in the ability of the individual cells to consume, produce and participate in IL-2 signaling within the population. Our model reveals that at the population level, these heterogeneous cells are engaged in a tug-of-war for IL-2 between regulatory (Treg) and effector (Teff) T cells, whereby access to IL-2 can either increase the survival of Teff cells or the suppressive capacity of Treg cells. This tug-of-war is the mechanism enforcing, at the systems level, a core function of Treg cells, namely the specific suppression of survival signals for weakly activated Teff cells but not for strongly activated cells. Our integrated model yields quantitative, experimentally validated predictions for the manipulation of Treg suppression. PMID:21119631
Leoni, M; Sens, P
2015-02-01
We study a generic model for the polarization and motility of self-propelled soft objects, biological cells, or biomimetic systems, interacting with a viscous substrate. The active forces generated by the cell on the substrate are modeled by means of oscillating force multipoles at the cell-substrate interface. Symmetry breaking and cell polarization for a range of cell sizes naturally "emerge" from long range mechanical interactions between oscillating units, mediated both by the intracellular medium and the substrate. However, the harnessing of cell polarization for motility requires substrate-mediated interactions. Motility can be optimized by adapting the oscillation frequency to the relaxation time of the system or when the substrate and cell viscosities match. Cellular noise can destroy mechanical coordination between force-generating elements within the cell, resulting in sudden changes of polarization. The persistence of the cell's motion is found to depend on the cell size and the substrate viscosity. Within such a model, chemotactic guidance of cell motion is obtained by directionally modulating the persistence of motion, rather than by modulating the instantaneous cell velocity, in a way that resembles the run and tumble chemotaxis of bacteria.
Phase equilibrium modeling for high temperature metallization on GaAs solar cells
NASA Technical Reports Server (NTRS)
Chung, M. A.; Davison, J. E.; Smith, S. R.
1991-01-01
Recent trends in performance specifications and functional requirements have brought about the need for high temperature metallization technology to be developed for survivable DOD space systems and to enhance solar cell reliability. The temperature constitution phase diagrams of selected binary and ternary systems were reviewed to determine the temperature and type of phase transformation present in the alloy systems. Of paramount interest are the liquid-solid and solid-solid transformations. Data are being utilized to aid in the selection of electrical contact materials to gallium arsenide solar cells. Published data on the phase diagrams for binary systems is readily available. However, information for ternary systems is limited. A computer model is being developed which will enable the phase equilibrium predictions for ternary systems where experimental data is lacking.
Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems
The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, ...
Power Management for Fuel Cell and Battery Hybrid Unmanned Aerial Vehicle Applications
NASA Astrophysics Data System (ADS)
Stein, Jared Robert
As electric powered unmanned aerial vehicles enter a new age of commercial viability, market opportunities in the small UAV sector are expanding. Extending UAV flight time through a combination of fuel cell and battery technologies enhance the scope of potential applications. A brief survey of UAV history provides context and examples of modern day UAVs powered by fuel cells are given. Conventional hybrid power system management employs DC-to-DC converters to control the power split between battery and fuel cell. In this study, a transistor replaces the DC-to-DC converter which lowers weight and cost. Simulation models of a lithium ion battery and a proton exchange membrane fuel cell are developed and integrated into a UAV power system model. Flight simulations demonstrate the operation of the transistor-based power management scheme and quantify the amount of hydrogen consumed by a 5.5 kg fixed wing UAV during a six hour flight. Battery power assists the fuel cell during high throttle periods but may also augment fuel cell power during cruise flight. Simulations demonstrate a 60 liter reduction in hydrogen consumption when battery power assists the fuel cell during cruise flight. Over the full duration of the flight, averaged efficiency of the power system exceeds 98%. For scenarios where inflight battery recharge is desirable, a constant current battery charger is integrated into the UAV power system. Simulation of inflight battery recharge is performed. Design of UAV hybrid power systems must consider power system weight against potential flight time. Data from the flight simulations are used to identify a simple formula that predicts flight time as a function of energy stored onboard the modeled UAV. A small selection of commercially available batteries, fuel cells, and compressed air storage tanks are listed to characterize the weight of possible systems. The formula is then used in conjunction with the weight data to generate a graph of power system weight versus potential flight times. Combinations of the listed batteries, fuel cells, and storage tanks are plotted on the graph to evaluate various hybrid power system configurations.
Gering, Kevin L.
2013-06-18
A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware periodically samples charge characteristics of the electrochemical cell. The computing system periodically determines cell information from the charge characteristics of the electrochemical cell. The computing system also periodically adds a first degradation characteristic from the cell information to a first sigmoid expression, periodically adds a second degradation characteristic from the cell information to a second sigmoid expression and combines the first sigmoid expression and the second sigmoid expression to develop or augment a multiple sigmoid model (MSM) of the electrochemical cell. The MSM may be used to estimate a capacity loss of the electrochemical cell at a desired point in time and analyze other characteristics of the electrochemical cell. The first and second degradation characteristics may be loss of active host sites and loss of free lithium for Li-ion cells.
Bales, Jerad; Fulford, Janice M.; Swain, Eric D.
1997-01-01
A study was conducted to review selected features of the Natural System Model, version 4.3 . The Natural System Model is a regional-scale model that uses recent climatic data and estimates of historic vegetation and topography to simulate pre-canal-drainage hydrologic response in south Florida. Equations used to represent the hydrologic system and the numerical solution of these equations in the model were documented and reviewed. Convergence testing was performed using 1965 input data, and selected other aspects of the model were evaluated.Some conclusions from the evaluation of the Natural System Model include the following observations . Simulations were generally insensitive to the temporal resolution used in the model. However, reduction of the computational cell size from 2-mile by 2-mile to 2/3-mile by 2/3-mile resulted in a decrease in spatial mean ponding depths for October of 0.35 foot for a 3-hour time step.Review of the computer code indicated that there is no limit on the amount of water that can be transferred from the river system to the overland flow system, on the amount of seepage from the river to the ground-water system, on evaporation from the river system, or on evapotranspiration from the overland-flow system . Oscillations of 0.2 foot or less in simulated river stage were identified and attributed to a volume limiting function which is applied in solution of the overland-flow equations. The computation of the resistance coefficient is not consistent with the computation of overland-flow velocity. Ground-water boundary conditions do not always ensure a no-flow condition at the boundary. These inconsistencies had varying degrees of effects on model simulations, and it is likely that simulations longer than 1 year are needed to fully identify effects. However, inconsistencies in model formulations should not be ignored, even if the effects of such errors on model results appear to be small or have not been clearly defined.The Natural System Model can be a very useful tool for estimating pre-drainage hydrologic response in south Florida. The model includes all of the important physical processes needed to simulate a water balance. With a few exceptions, these hydrologic processes are represented in a reasonable manner using empirical, semiempirical, and mechanistic relations . The data sets that have been assembled to represent physical features, and hydrologic and meteorological conditions are quite extensive in their scope.Some suggestions for model application were made. Simulation results from the Natural System Model need to be interpreted on a regional basis, rather than cell by cell. The available evidence suggests that simulated water levels should be interpreted with about a plus or minus 1 foot uncertainty. It is probably not appropriate to use the Natural System Model to estimate pre-drainage discharges (as opposed to hydroperiods and water levels) at a particular location or across a set of adjacent computational cells. All simulated results for computational cells within about 10 miles of the model boundaries have a higher degree of uncertainty than results for the interior of the model domain. It is most appropriate to interpret the Natural System Model simulation results in connection with other available information. Stronger linkages between hydrologic inputs to the Everglades and the ecological response of the system would enhance restoration efforts .
Mendes, Bárbara; Marques, Cláudia; Carvalho, Isabel; Costa, Paulo; Martins, Susana; Ferreira, Domingos; Sarmento, Bruno
2015-07-25
The blood-brain barrier plays an important role in protecting the brain from injury and diseases, but also restrains the delivery of potential therapeutic drugs for the treatment of brain illnesses, such as tumors. Glioma is most common cancer type of central nervous system in adults and the most lethal in children. The treatment is normally poor and ineffective. To better understand the ability of drug delivery systems to permeate this barrier, a blood-brain barrier model using human brain endothelial cells and a glioma cell line is herein proposed. The consistent trans-endothelial electrical values, immunofluorescence and scanning electronic microscopy showed a confluent endothelial cell monolayer with high restrictiveness. Upon inclusion of glioma cell line, the trans-endothelial electrical resistance decreased, with consequent increase of apparent permeability of fluorescein isothiocyanate dextran used as model drug, revealing a reduction of the barrier robustness. In addition, it was demonstrated a cell shape modification in the co-culture, with loss of tight junctions. The microenvironment of co-cultured model presented significant increase of of CCL2/MCP-1 and IL-6 production, correlating with the modulation of permeation. The results encourage the use of the proposed in vitro model as a screening tool when performing drugs permeability for the treatment of disorders among the central nervous system. Copyright © 2015 Elsevier B.V. All rights reserved.
Subia, Bano; Dey, Tuli; Sharma, Shaily; Kundu, Subhas C
2015-02-04
To avoid the indiscriminating action of anticancer drugs, the cancer cell specific targeting of drug molecule becomes a preferred choice for the treatment. The successful screening of the drug molecules in 2D culture system requires further validation. The failure of target specific drug in animal model raises the issue of creating a platform in between the in vitro (2D) and in vivo animal testing. The metastatic breast cancer cells migrate and settle at different sites such as bone tissue. This work evaluates the in vitro 3D model of the breast cancer and bone cells to understand the cellular interactions in the presence of a targeted anticancer drug delivery system. The silk fibroin based cytocompatible 3D scaffold is used as in vitro 3D distribution model. Human breast adenocarcinoma and osteoblast like cells are cocultured to evaluate the efficiency of doxorubicin loaded folic acid conjugated silk fibroin nanoparticle as drug delivery system. Decreasing population of the cancer cells, which lower the levels of vascular endothelial growth factors, glucose consumption, and lactate production are observed in the drug treated coculture constructs. The drug treated constructs do not show any major impact on bone mineralization. The diminished expression of osteogenic markers such as osteocalcein and alkaline phosphatase are recorded. The result indicates that this type of silk based 3D in vitro coculture model may be utilized as a bridge between the traditional 2D and animal model system to evaluate the new drug molecule (s) or to reassay the known drug molecules or to develop target specific drug in cancer research.
Stochastic models for regulatory networks of the genetic toggle switch.
Tian, Tianhai; Burrage, Kevin
2006-05-30
Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.
Stochastic models for regulatory networks of the genetic toggle switch
Tian, Tianhai; Burrage, Kevin
2006-01-01
Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385
NASA Astrophysics Data System (ADS)
Nanaeda, Kimihiro; Mueller, Fabian; Brouwer, Jacob; Samuelsen, Scott
Operating strategies of solid oxide fuel cell (SOFC) combined heat and power (CHP) systems are developed and evaluated from a utility, and end-user perspective using a fully integrated SOFC-CHP system dynamic model that resolves the physical states, thermal integration and overall efficiency of the system. The model can be modified for any SOFC-CHP system, but the present analysis is applied to a hotel in southern California based on measured electric and heating loads. Analysis indicates that combined heat and power systems can be operated to benefit both the end-users and the utility, providing more efficient electric generation as well as grid ancillary services, namely dispatchable urban power. Design and operating strategies considered in the paper include optimal sizing of the fuel cell, thermal energy storage to dispatch heat, and operating the fuel cell to provide flexible grid power. Analysis results indicate that with a 13.1% average increase in price-of-electricity (POE), the system can provide the grid with a 50% operating range of dispatchable urban power at an overall thermal efficiency of 80%. This grid-support operating mode increases the operational flexibility of the SOFC-CHP system, which may make the technology an important utility asset for accommodating the increased penetration of intermittent renewable power.
A phase field approach for multicellular aggregate fusion in biofabrication.
Yang, Xiaofeng; Sun, Yi; Wang, Qi
2013-07-01
We present a modeling and computational approach to study fusion of multicellular aggregates during tissue and organ fabrication, which forms the foundation for the scaffold-less biofabrication of tissues and organs known as bioprinting. It is known as the phase field method, where multicellular aggregates are modeled as mixtures of multiphase complex fluids whose phase mixing or separation is governed by interphase force interactions, mimicking the cell-cell interaction in the multicellular aggregates, and intermediate range interaction mediated by the surrounding hydrogel. The material transport in the mixture is dictated by hydrodynamics as well as forces due to the interphase interactions. In a multicellular aggregate system with fixed number of cells and fixed amount of the hydrogel medium, the effect of cell differentiation, proliferation, and death are neglected in the current model, which can be readily included in the model, and the interaction between different components is dictated by the interaction energy between cell and cell as well as between cell and medium particles, respectively. The modeling approach is applicable to transient simulations of fusion of cellular aggregate systems at the time and length scale appropriate to biofabrication. Numerical experiments are presented to demonstrate fusion and cell sorting during tissue and organ maturation processes in biofabrication.
Modeling for Visual Feature Extraction Using Spiking Neural Networks
NASA Astrophysics Data System (ADS)
Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya
This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.
Inverse approaches with lithologic information for a regional groundwater system in southwest Kansas
Tsou, Ming‐shu; Perkins, S.P.; Zhan, X.; Whittemore, Donald O.; Zheng, Lingyun
2006-01-01
Two practical approaches incorporating lithologic information for groundwater modeling calibration are presented to estimate distributed, cell-based hydraulic conductivity. The first approach is to estimate optimal hydraulic conductivities for geological materials by incorporating thickness distribution of materials into inverse modeling. In the second approach, residuals for the groundwater model solution are minimized according to a globalized Newton method with the aid of a Geographic Information System (GIS) to calculate a cell-wise distribution of hydraulic conductivity. Both approaches honor geologic data and were effective in characterizing the heterogeneity of a regional groundwater modeling system in southwest Kansas. ?? 2005 Elsevier Ltd All rights reserved.
Time-lapse microscopy and image processing for stem cell research: modeling cell migration
NASA Astrophysics Data System (ADS)
Gustavsson, Tomas; Althoff, Karin; Degerman, Johan; Olsson, Torsten; Thoreson, Ann-Catrin; Thorlin, Thorleif; Eriksson, Peter
2003-05-01
This paper presents hardware and software procedures for automated cell tracking and migration modeling. A time-lapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.
Clarke, Kirsty E; Tams, Daniel M; Henderson, Andrew P; Roger, Mathilde F; Whiting, Andrew; Przyborski, Stefan A
2017-06-01
The inability of neurites to grow and restore neural connections is common to many neurological disorders, including trauma to the central nervous system and neurodegenerative diseases. Therefore, there is need for a robust and reproducible model of neurite outgrowth, to provide a tool to study the molecular mechanisms that underpin the process of neurite inhibition and to screen molecules that may be able to overcome such inhibition. In this study a novel in vitro pluripotent stem cell based model of human neuritogenesis was developed. This was achieved by incorporating additional technologies, notably a stable synthetic inducer of neural differentiation, and the application of three-dimensional (3D) cell culture techniques. We have evaluated the use of photostable, synthetic retinoid molecules to promote neural differentiation and found that 0.01 μM EC23 was the optimal concentration to promote differentiation and neurite outgrowth from human pluripotent stem cells within our model. We have also developed a methodology to enable quick and accurate quantification of neurite outgrowth derived from such a model. Furthermore, we have obtained significant neurite outgrowth within a 3D culture system enhancing the level of neuritogenesis observed and providing a more physiological microenvironment to investigate the molecular mechanisms that underpin neurite outgrowth and inhibition within the nervous system. We have demonstrated a potential application of our model in co-culture with glioma cells, to recapitulate aspects of the process of neurite inhibition that may also occur in the injured spinal cord. We propose that such a system that can be utilised to investigate the molecular mechanisms that underpin neurite inhibition mediated via glial and neuron interactions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Frascoli, Federico; Flood, Emelie; Kim, Peter S
2017-06-01
We present a three-dimensional model simulating the dynamics of an anti-cancer T-cell response against a small, avascular, early-stage tumour. Interactions at the tumour site are accounted for using an agent-based model (ABM), while immune cell dynamics in the lymph node are modelled as a system of delay differential equations (DDEs). We combine these separate approaches into a two-compartment hybrid ABM-DDE system to capture the T-cell response against the tumour. In the ABM at the tumour site, movement of tumour cells is modelled using effective physical forces with a specific focus on cell-to-cell adhesion properties and varying levels of tumour cell motility, thus taking into account the ability of cancer cells to spread and form clusters. We consider the effectiveness of the immune response over a range of parameters pertaining to tumour cell motility, cell-to-cell adhesion strength and growth rate. We also investigate the dependence of outcomes on the distribution of tumour cells. Low tumour cell motility is generally a good indicator for successful tumour eradication before relapse, while high motility leads, almost invariably, to relapse and tumour escape. In general, the effect of cell-to-cell adhesion on prognosis is dependent on the level of tumour cell motility, with an often unpredictable cross influence between adhesion and motility, which can lead to counterintuitive effects. In terms of overall tumour shape and structure, the spatial distribution of cancer cells in clusters of various sizes has shown to be strongly related to the likelihood of extinction. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
Stem Cell Models: A Guide to Understand and Mitigate Aging?
Brunauer, Regina; Alavez, Silvestre; Kennedy, Brian K
2017-01-01
Aging is studied either on a systemic level using life span and health span of animal models, or on the cellular level using replicative life span of yeast or mammalian cells. While useful in identifying general and conserved pathways of aging, both approaches provide only limited information about cell-type specific causes and mechanisms of aging. Stem cells are the regenerative units of multicellular life, and stem cell aging might be a major cause for organismal aging. Using the examples of hematopoietic stem cell aging and human pluripotent stem cell models, we propose that stem cell models of aging are valuable for studying tissue-specific causes and mechanisms of aging and can provide unique insights into the mammalian aging process that may be inaccessible in simple model organisms. © 2016 S. Karger AG, Basel.
NASA Astrophysics Data System (ADS)
Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus
2014-12-01
An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.
2011-01-01
ABSTRACT Title of Document: MODELING OF WATER-BREATHING PROPULSION SYSTEMS UTILIZING THE ALUMINUM-SEAWATER REACTION AND SOLID...Hybrid Aluminum Combustor (HAC): a novel underwater power system based on the exothermic reaction of aluminum with seawater. The system is modeled ...using a NASA-developed framework called Numerical Propulsion System Simulation (NPSS) by assembling thermodynamic models developed for each component
Spin glass model for dynamics of cell reprogramming
NASA Astrophysics Data System (ADS)
Pusuluri, Sai Teja; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.
2015-03-01
Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming.
Dynamic model of a micro-tubular solid oxide fuel cell stack including an integrated cooling system
NASA Astrophysics Data System (ADS)
Hering, Martin; Brouwer, Jacob; Winkler, Wolfgang
2017-02-01
A novel dynamic micro-tubular solid oxide fuel cell (MT-SOFC) and stack model including an integrated cooling system is developed using a quasi three-dimensional, spatially resolved, transient thermodynamic, physical and electrochemical model that accounts for the complex geometrical relations between the cells and cooling-tubes. The modeling approach includes a simplified tubular geometry and stack design including an integrated cooling structure, detailed pressure drop and gas property calculations, the electrical and physical constraints of the stack design that determine the current, as well as control strategies for the temperature. Moreover, an advanced heat transfer balance with detailed radiative heat transfer between the cells and the integrated cooling-tubes, convective heat transfer between the gas flows and the surrounding structures and conductive heat transfer between the solid structures inside of the stack, is included. The detailed model can be used as a design basis for the novel MT-SOFC stack assembly including an integrated cooling system, as well as for the development of a dynamic system control strategy. The evaluated best-case design achieves very high electrical efficiency between around 75 and 55% in the entire power density range between 50 and 550 mW /cm2 due to the novel stack design comprising an integrated cooling structure.
Modeling the hydrodynamic and electrochemical efficiency of semi-solid flow batteries
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brunini, VE; Chiang, YM; Carter, WC
2012-05-01
A mathematical model of flow cell operation incorporating hydrodynamic and electrochemical effects in three dimensions is developed. The model and resulting simulations apply to recently demonstrated high energy-density semi-solid flow cells. In particular, state of charge gradients that develop during low flow rate operation and their effects on the spatial non-uniformity of current density within flow cells are quantified. A one-dimensional scaling model is also developed and compared to the full three-dimensional simulation. The models are used to demonstrate the impact of the choice of electrochemical couple on flow cell performance. For semi-solid flow electrodes, which can use solid activemore » materials with a wide variety of voltage-capacity responses, we find that cell efficiency is maximized for electrochemical couples that have a relatively flat voltage vs. capacity curve, operated under slow flow conditions. For example, in flow electrodes limited by macroscopic charge transport, an LiFePO4-based system requires one-third the polarization to reach the same cycling rate as an LiCoO2-based system, all else being equal. Our conclusions are generally applicable to high energy density flow battery systems, in which flow rates can be comparatively low for a given required power. (C) 2012 Elsevier Ltd. All rights reserved.« less
Dynamic Properties of Electrotonic Coupling between Cells of Early Xenopus Embryos
DiCaprio, R. A.; French, A. S.; Sanders, E. J.
1974-01-01
Frequency response functions were measured between the cells of Xenopus laevis embryos during the first two cleavage stages. Linear systems theory was then used to produce electronic models which account for the electrical behavior of the systems. Coupling between the cells may be explained by models which have simple resistive elements joining each cell to its neighbors. The vitelline, or fertilization, membrane which surrounds the embryos has no detectable resistance to the passage of electric current. The electrical properties of the four-cell embryo can only be explained by the existence of individual junctions linking each pair of cells. This arrangement suggests that electrotonic coupling is important in the development of the embryos, at least until the four-cell stage. ImagesFIGURE 5FIGURE 14FIGURE 15 PMID:19431351
Optimal Charging of Nickel-Hydrogen Batteries for Life Extension
NASA Technical Reports Server (NTRS)
Hartley, Tom T.; Lorenzo, Carl F.
2002-01-01
We are exploring the possibility of extending the cycle life of battery systems by using a charging profile that minimizes cell damage. Only nickel-hydrogen cells are discussed at this time, but applications to lithium-ion cells are being considered. The process first requires the development of a fractional calculus based nonlinear dynamic model of the specific cells being used. The parameters of this model are determined from the cell transient responses. To extend cell cycle life, an instantaneous damage rate model is developed. The model is based on cycle life data and is highly dependent on cell voltage. Once both the cell dynamic model and the instantaneous damage rate model have been determined, the charging profile for a specific cell is determined by numerical optimization. Results concerning the percentage life extension for different charging strategies are presented. The overall procedure is readily adaptable to real-time implementations where the charging profile can maintain its minimum damage nature as the specific cell ages.
Multiscale modeling of the dynamics of multicellular systems
NASA Astrophysics Data System (ADS)
Kosztin, Ioan
2011-03-01
Describing the biomechanical properties of cellular systems, regarded as complex highly viscoelastic materials, is a difficult problem of great conceptual and practical value. Here we present a novel approach, referred to as the Cellular Particle Dynamics (CPD) method, for: (i) quantitatively relating biomechanical properties at the cell level to those at the multicellular and tissue level, and (ii) describing and predicting the time evolution of multicellular systems that undergo biomechanical relaxations. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. Cell and multicellular level biomechanical properties (e.g., viscosity, surface tension and shear modulus) are determined through the combined use of experiments and theory of continuum viscoelastic media. The same biomechanical properties are also ``measured'' computationally by employing the CPD method, the results being expressed in terms of CPD parameters. Once these parameters have been calibrated experimentally, the formalism provides a systematic framework to predict the time evolution of complex multicellular systems during shape-changing biomechanical transformations. By design, the CPD method is rather flexible and most suitable for multiscale modeling of multicellular system. The spatial level of detail of the system can be easily tuned by changing the number of CPs in a cell. Thus, CPD can be used equally well to describe both cell level processes (e.g., the adhesion of two cells) and tissue level processes (e.g., the formation of 3D constructs of millions of cells through bioprinting). Work supported by NSF [FIBR-0526854 and PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.
Seet, Christopher S; He, Chongbin; Bethune, Michael T; Li, Suwen; Chick, Brent; Gschweng, Eric H; Zhu, Yuhua; Kim, Kenneth; Kohn, Donald B; Baltimore, David; Crooks, Gay M; Montel-Hagen, Amélie
2017-05-01
Studies of human T cell development require robust model systems that recapitulate the full span of thymopoiesis, from hematopoietic stem and progenitor cells (HSPCs) through to mature T cells. Existing in vitro models induce T cell commitment from human HSPCs; however, differentiation into mature CD3 + TCR-αβ + single-positive CD8 + or CD4 + cells is limited. We describe here a serum-free, artificial thymic organoid (ATO) system that supports efficient and reproducible in vitro differentiation and positive selection of conventional human T cells from all sources of HSPCs. ATO-derived T cells exhibited mature naive phenotypes, a diverse T cell receptor (TCR) repertoire and TCR-dependent function. ATOs initiated with TCR-engineered HSPCs produced T cells with antigen-specific cytotoxicity and near-complete lack of endogenous TCR Vβ expression, consistent with allelic exclusion of Vβ-encoding loci. ATOs provide a robust tool for studying human T cell differentiation and for the future development of stem-cell-based engineered T cell therapies.
Computational modeling of the cell-autonomous mammalian circadian oscillator.
Podkolodnaya, Olga A; Tverdokhleb, Natalya N; Podkolodnyy, Nikolay L
2017-02-24
This review summarizes various mathematical models of cell-autonomous mammalian circadian clock. We present the basics necessary for understanding of the cell-autonomous mammalian circadian oscillator, modern experimental data essential for its reconstruction and some special problems related to the validation of mathematical circadian oscillator models. This work compares existing mathematical models of circadian oscillator and the results of the computational studies of the oscillating systems. Finally, we discuss applications of the mathematical models of mammalian circadian oscillator for solving specific problems in circadian rhythm biology.
Rinkenauer, Alexandra C; Press, Adrian T; Raasch, Martin; Pietsch, Christian; Schweizer, Simon; Schwörer, Simon; Rudolph, Karl L; Mosig, Alexander; Bauer, Michael; Traeger, Anja; Schubert, Ulrich S
2015-10-28
Polymer-based nanoparticles are promising drug delivery systems allowing the development of new drug and treatment strategies with reduced side effects. However, it remains a challenge to screen for new and effective nanoparticle-based systems in vitro. Important factors influencing the behavior of nanoparticles in vivo cannot be simulated in screening assays in vitro, which still represent the main tools in academic research and pharmaceutical industry. These systems have serious drawbacks in the development of nanoparticle-based drug delivery systems, since they do not consider the highly complex processes influencing nanoparticle clearance, distribution, and uptake in vivo. In particular, the transfer of in vitro nanoparticle performance to in vivo models often fails, demonstrating the urgent need for novel in vitro tools that can imitate aspects of the in vivo situation more accurate. Dynamic cell culture, where cells are cultured and incubated in the presence of shear stress has the potential to bridge this gap by mimicking key-features of organs and vessels. Our approach implements and compares a chip-based dynamic cell culture model to the common static cell culture and mouse model to assess its capability to predict the in vivo success more accurately, by using a well-defined poly((methyl methacrylate)-co-(methacrylic acid)) and poly((methyl methacrylate)-co-(2-dimethylamino ethylmethacrylate)) based nanoparticle library. After characterization in static and dynamic in vitro cell culture we were able to show that physiological conditions such as cell-cell communication of co-cultured endothelial cells and macrophages as well as mechanotransductive signaling through shear stress significantly alter cellular nanoparticle uptake. In addition, it could be demonstrated by using dynamic cell cultures that the in vivo situation is simulated more accurately and thereby can be applied as a novel system to investigate the performance of nanoparticle systems in vivo more reliable. Copyright © 2015. Published by Elsevier B.V.
Single cell model for simultaneous drug delivery and efflux.
Yi, C; Saidel, G M; Gratzl, M
1999-01-01
Multidrug resistance (MDR) of some cancer cells is a major challenge for chemotherapy of systemic cancers to overcome. To experimentally uncover the cellular mechanisms leading to MDR, it is necessary to quantitatively assess both drug influx into, and efflux from, the cells exposed to drug treatment. By using a novel molecular microdelivery system to enforce continuous and adjustable drug influx into single cells by controlled diffusion through a gel plug in a micropipet tip, drug resistance studies can now be performed on the single cell level. Our dynamic model of this scheme incorporates drug delivery, diffusive mixing, and accumulation inside the cytoplasm, and efflux by both passive and active membrane transport. Model simulations using available experimental information on these processes can assist in the design of MDR related experiments on single cancer cells which are expected to lead to a quantitative evaluation of mechanisms. Simulations indicate that drug resistance of a cancer cell can be quantified better by its dynamic response than by steady-state analysis.
Fas ligand promotes an inducible TLR-dependent model of cutaneous lupus-like inflammation.
Mande, Purvi; Zirak, Bahar; Ko, Wei-Che; Taravati, Keyon; Bride, Karen L; Brodeur, Tia Y; Deng, April; Dresser, Karen; Jiang, Zhaozhao; Ettinger, Rachel; Fitzgerald, Katherine A; Rosenblum, Michael D; Harris, John E; Marshak-Rothstein, Ann
2018-06-11
Toll-like receptors TLR7 and TLR9 are both implicated in the activation of autoreactive B cells and other cell types associated with systemic lupus erythematosus (SLE) pathogenesis. However, Tlr9-/- autoimmune-prone strains paradoxically develop more severe disease. We have now leveraged the negative regulatory role of TLR9 to develop an inducible rapid-onset murine model of systemic autoimmunity that depends on T cell detection of a membrane-bound OVA fusion protein expressed by MHC class II+ cells, expression of TLR7, expression of the type I IFN receptor, and loss of expression of TLR9. These mice are distinguished by a high frequency of OVA-specific Tbet+, IFN-γ+, and FasL-expressing Th1 cells as well as autoantibody-producing B cells. Unexpectedly, contrary to what occurs in most models of SLE, they also developed skin lesions that are very similar to those of human cutaneous lupus erythematosus (CLE) as far as clinical appearance, histological changes, and gene expression. FasL was a key effector mechanism in the skin, as the transfer of FasL-deficient DO11gld T cells completely failed to elicit overt skin lesions. FasL was also upregulated in human CLE biopsies. Overall, our model provides a relevant system for exploring the pathophysiology of CLE as well as the negative regulatory role of TLR9.
Mouse Models for Studying Oral Cancer: Impact in the Era of Cancer Immunotherapy.
Luo, J J; Young, C D; Zhou, H M; Wang, X J
2018-04-01
Model systems for oral cancer research have progressed from tumor epithelial cell cultures to in vivo systems that mimic oral cancer genetics, pathological characteristics, and tumor-stroma interactions of oral cancer patients. In the era of cancer immunotherapy, it is imperative to use model systems to test oral cancer prevention and therapeutic interventions in the presence of an immune system and to discover mechanisms of stromal contributions to oral cancer carcinogenesis. Here, we review in vivo mouse model systems commonly used for studying oral cancer and discuss the impact these models are having in advancing basic mechanisms, chemoprevention, and therapeutic intervention of oral cancer while highlighting recent discoveries concerning the role of immune cells in oral cancer. Improvements to in vivo model systems that highly recapitulate human oral cancer hold the key to identifying features of oral cancer initiation, progression, and invasion as well as molecular and cellular targets for prevention, therapeutic response, and immunotherapy development.
ERIC Educational Resources Information Center
National Academy of Sciences - National Research Council, Washington, DC. Inst. of Lab. Animal Resources.
This volume contains the prepared papers and discussions of a National Academy of Sciences - National Research Council Symposium on the Future of Animals, Cells, Models, and Systems in Research, Development, Education, and Testing. The purpose of the symposium was to examine the past, present, and future contributions of animals to human health…
Entropy-based separation of yeast cells using a microfluidic system of conjoined spheres
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Kai-Jian; Qin, S.-J., E-mail: shuijie.qin@gmail.com; Bai, Zhong-Chen
2013-11-21
A physical model is derived to create a biological cell separator that is based on controlling the entropy in a microfluidic system having conjoined spherical structures. A one-dimensional simplified model of this three-dimensional problem in terms of the corresponding effects of entropy on the Brownian motion of particles is presented. This dynamic mechanism is based on the Langevin equation from statistical thermodynamics and takes advantage of the characteristics of the Fokker-Planck equation. This mechanism can be applied to manipulate biological particles inside a microfluidic system with identical, conjoined, spherical compartments. This theoretical analysis is verified by performing a rapid andmore » a simple technique for separating yeast cells in these conjoined, spherical microfluidic structures. The experimental results basically match with our theoretical model and we further analyze the parameters which can be used to control this separation mechanism. Both numerical simulations and experimental results show that the motion of the particles depends on the geometrical boundary conditions of the microfluidic system and the initial concentration of the diffusing material. This theoretical model can be implemented in future biophysics devices for the optimized design of passive cell sorters.« less
Physiologically relevant organs on chips
Yum, Kyungsuk; Hong, Soon Gweon; Lee, Luke P.
2015-01-01
Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or organs on chips, that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue–tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. PMID:24357624
Basel, Matthew T; Balivada, Sivasai; Wang, Hongwang; Shrestha, Tej B; Seo, Gwi Moon; Pyle, Marla; Abayaweera, Gayani; Dani, Raj; Koper, Olga B; Tamura, Masaaki; Chikan, Viktor; Bossmann, Stefan H; Troyer, Deryl L
2012-01-01
Using magnetic nanoparticles to absorb alternating magnetic field energy as a method of generating localized hyperthermia has been shown to be a potential cancer treatment. This report demonstrates a system that uses tumor homing cells to actively carry iron/iron oxide nanoparticles into tumor tissue for alternating magnetic field treatment. Paramagnetic iron/ iron oxide nanoparticles were synthesized and loaded into RAW264.7 cells (mouse monocyte/ macrophage-like cells), which have been shown to be tumor homing cells. A murine model of disseminated peritoneal pancreatic cancer was then generated by intraperitoneal injection of Pan02 cells. After tumor development, monocyte/macrophage-like cells loaded with iron/ iron oxide nanoparticles were injected intraperitoneally and allowed to migrate into the tumor. Three days after injection, mice were exposed to an alternating magnetic field for 20 minutes to cause the cell-delivered nanoparticles to generate heat. This treatment regimen was repeated three times. A survival study demonstrated that this system can significantly increase survival in a murine pancreatic cancer model, with an average post-tumor insertion life expectancy increase of 31%. This system has the potential to become a useful method for specifically and actively delivering nanoparticles for local hyperthermia treatment of cancer. PMID:22287840
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lorenzi, Tommaso; Chisholm, Rebecca H.; Lorz, Alexander
We formulate an individual-based model and a population model of phenotypic evolution, under cytotoxic drugs, in a cancer cell population structured by the expression levels of survival-potential and proliferation-potential. We apply these models to a recently studied experimental system. Our results suggest that mechanisms based on fundamental laws of biology can reversibly push an actively-proliferating, and drug-sensitive, cell population to transition into a weakly-proliferative and drug-tolerant state, which will eventually facilitate the emergence of more potent, proliferating and drug-tolerant cells.
ERIC Educational Resources Information Center
Na, Shin-Young; Cao, Yi; Toben, Catherine; Nitschke, Lars; Stadelmann, Christine; Gold, Ralf; Schimpl, Anneliese; Hunig, Thomas
2008-01-01
In multiple sclerosis, CD8 T-cells are thought play a key pathogenetic role, but mechanistic evidence from rodent models is limited. Here, we have tested the encephalitogenic potential of CD8 T-cells specific for the model antigen ovalbumin (OVA) sequestered in oligodendrocytes as a cytosolic molecule. We show that in these "ODC-OVA" mice, the…
Optimized Delivery System Achieves Enhanced Endomyocardial Stem Cell Retention
Behfar, Atta; Latere, Jean-Pierre; Bartunek, Jozef; Homsy, Christian; Daro, Dorothee; Crespo-Diaz, Ruben J.; Stalboerger, Paul G.; Steenwinckel, Valerie; Seron, Aymeric; Redfield, Margaret M.; Terzic, Andre
2014-01-01
Background Regenerative cell-based therapies are associated with limited myocardial retention of delivered stem cells. The objective of this study is to develop an endocardial delivery system for enhanced cell retention. Methods and Results Stem cell retention was simulated in silico using one and three-dimensional models of tissue distortion and compliance associated with delivery. Needle designs, predicted to be optimal, were accordingly engineered using nitinol – a nickel and titanium alloy displaying shape memory and super-elasticity. Biocompatibility was tested with human mesenchymal stem cells. Experimental validation was performed with species-matched cells directly delivered into Langendorff-perfused porcine hearts or administered percutaneously into the endocardium of infarcted pigs. Cell retention was quantified by flow cytometry and real time quantitative polymerase chain reaction methodology. Models, computing optimal distribution of distortion calibrated to favor tissue compliance, predicted that a 75°-curved needle featuring small-to-large graded side holes would ensure the highest cell retention profile. In isolated hearts, the nitinol curved needle catheter (C-Cath) design ensured 3-fold superior stem cell retention compared to a standard needle. In the setting of chronic infarction, percutaneous delivery of stem cells with C-Cath yielded a 37.7±7.1% versus 10.0±2.8% retention achieved with a traditional needle, without impact on biocompatibility or safety. Conclusions Modeling guided development of a nitinol-based curved needle delivery system with incremental side holes achieved enhanced myocardial stem cell retention. PMID:24326777
NASA Astrophysics Data System (ADS)
Wendel, C. H.; Kazempoor, P.; Braun, R. J.
2015-02-01
Electrical energy storage (EES) is an important component of the future electric grid. Given that no other widely available technology meets all the EES requirements, reversible (or regenerative) solid oxide cells (ReSOCs) working in both fuel cell (power producing) and electrolysis (fuel producing) modes are envisioned as a technology capable of providing highly efficient and cost-effective EES. However, there are still many challenges and questions from cell materials development to system level operation of ReSOCs that should be addressed before widespread application. This paper presents a novel system based on ReSOCs that employ a thermal management strategy of promoting exothermic methanation within the ReSOC cell-stack to provide thermal energy for the endothermic steam/CO2 electrolysis reactions during charging mode (fuel producing). This approach also serves to enhance the energy density of the stored gases. Modeling and parametric analysis of an energy storage concept is performed using a physically based ReSOC stack model coupled with thermodynamic system component models. Results indicate that roundtrip efficiencies greater than 70% can be achieved at intermediate stack temperature (680 °C) and elevated stack pressure (20 bar). The optimal operating condition arises from a tradeoff between stack efficiency and auxiliary power requirements from balance of plant hardware.
Gkigkitzis, Ioannis
2013-01-01
The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.
Evaluation of Differentiated Human Bronchial Epithelial Cell Culture Systems for Asthma Research
Stewart, Ceri E.; Torr, Elizabeth E.; Mohd Jamili, Nur H.; Bosquillon, Cynthia; Sayers, Ian
2012-01-01
The aim of the current study was to evaluate primary (human bronchial epithelial cells, HBEC) and non-primary (Calu-3, BEAS-2B, BEAS-2B R1) bronchial epithelial cell culture systems as air-liquid interface- (ALI-) differentiated models for asthma research. Ability to differentiate into goblet (MUC5AC+) and ciliated (β-Tubulin IV+) cells was evaluated by confocal imaging and qPCR. Expression of tight junction/adhesion proteins (ZO-1, E-Cadherin) and development of transepithelial electrical resistance (TEER) were assessed. Primary cells showed localised MUC5AC, β-Tubulin IV, ZO-1, and E-Cadherin and developed TEER with, however, a large degree of inter- and intradonor variation. Calu-3 cells developed a more reproducible TEER and a phenotype similar to primary cells although with diffuse β-Tubulin IV staining. BEAS-2B cells did not differentiate or develop tight junctions. These data highlight the challenges in working with primary cell models and the need for careful characterisation and selection of systems to answer specific research questions. PMID:22287976
Microengineering methods for cell-based microarrays and high-throughput drug-screening applications.
Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan
2011-09-01
Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.
Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications
Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan
2011-01-01
Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell based drug-screening models, which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell based drug screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds a great potential to provide repeatable 3D cell based constructs with high temporal, spatial control and versatility. PMID:21725152
Bilsland, Alan E.; Stevenson, Katrina; Liu, Yu; Hoare, Stacey; Cairney, Claire J.; Roffey, Jon; Keith, W. Nicol
2014-01-01
Cancer cells depend on transcription of telomerase reverse transcriptase (TERT). Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3′-oxime (BIO) predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several aspects of TERT regulation including previously unknown mechanisms. An extrapolation suggests that a dominant stimulatory system may programme TERT for transcriptional stability. PMID:24550717
Interacting damage models mapped onto ising and percolation models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Toussaint, Renaud; Pride, Steven R.
The authors introduce a class of damage models on regular lattices with isotropic interactions between the broken cells of the lattice. Quasistatic fiber bundles are an example. The interactions are assumed to be weak, in the sense that the stress perturbation from a broken cell is much smaller than the mean stress in the system. The system starts intact with a surface-energy threshold required to break any cell sampled from an uncorrelated quenched-disorder distribution. The evolution of this heterogeneous system is ruled by Griffith's principle which states that a cell breaks when the release in potential (elastic) energy in themore » system exceeds the surface-energy barrier necessary to break the cell. By direct integration over all possible realizations of the quenched disorder, they obtain the probability distribution of each damage configuration at any level of the imposed external deformation. They demonstrate an isomorphism between the distributions so obtained and standard generalized Ising models, in which the coupling constants and effective temperature in the Ising model are functions of the nature of the quenched-disorder distribution and the extent of accumulated damage. In particular, they show that damage models with global load sharing are isomorphic to standard percolation theory, that damage models with local load sharing rule are isomorphic to the standard ising model, and draw consequences thereof for the universality class and behavior of the autocorrelation length of the breakdown transitions corresponding to these models. they also treat damage models having more general power-law interactions, and classify the breakdown process as a function of the power-law interaction exponent. Last, they also show that the probability distribution over configurations is a maximum of Shannon's entropy under some specific constraints related to the energetic balance of the fracture process, which firmly relates this type of quenched-disorder based damage model to standard statistical mechanics.« less
2013-01-01
Background The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach. Results A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-β. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The results demonstrate how this framework can be used to integrate mathematical models of the immune response from several published sources and describe qualitative predictions of global immune system response arising from the integrated, hybrid model. In addition, we show how the model can be expanded to include novel biological findings. Case studies were carried out to simulate TB infection, tumor rejection, response to a blood borne pathogen and the consequences of accounting for regulatory T-cells. Conclusions The final result of this work is a postulated and increasingly comprehensive representation of the mammalian immune system, based on physiological knowledge and susceptible to further experimental testing and validation. We believe that the integrated nature of FIRM has the potential to simulate a range of responses under a variety of conditions, from modeling of immune responses after tuberculosis (TB) infection to tumor formation in tissues. FIRM also has the flexibility to be expanded to include both complex and novel immunological response features as our knowledge of the immune system advances. PMID:24074340
Shirani, Sahar; Hellweger, Ferdi L
2017-08-01
Molecular observations reveal substantial biogeographic patterns of cyanobacteria within systems of connected lakes. An important question is the relative role of environmental selection and neutral processes in the biogeography of these systems. Here, we quantify the effect of genetic drift and dispersal limitation by simulating individual cyanobacteria cells using an agent-based model (ABM). In the model, cells grow (divide), die, and migrate between lakes. Each cell has a full genome that is subject to neutral mutation (i.e., the growth rate is independent of the genome). The model is verified by simulating simplified lake systems, for which theoretical solutions are available. Then, it is used to simulate the biogeography of the cyanobacterium Microcystis aeruginosa in a number of real systems, including the Great Lakes, Klamath River, Yahara River, and Chattahoochee River. Model output is analyzed using standard bioinformatics tools (BLAST, MAFFT). The emergent patterns of nucleotide divergence between lakes are dynamic, including gradual increases due to accumulation of mutations and abrupt changes due to population takeovers by migrant cells (coalescence events). The model predicted nucleotide divergence is heterogeneous within systems, and for weakly connected lakes, it can be substantial. For example, Lakes Superior and Michigan are predicted to have an average genomic nucleotide divergence of 8200 bp or 0.14%. The divergence between more strongly connected lakes is much lower. Our results provide a quantitative baseline for future biogeography studies. They show that dispersal limitation can be an important factor in microbe biogeography, which is contrary to the common belief, and could affect how a system responds to environmental change.
Power conversion and control methods for renewable energy sources
NASA Astrophysics Data System (ADS)
Yu, Dachuan
2005-07-01
In recent years, there has been an increase in the use of renewable energy due to the growing concern over the pollution caused by fossil-fuel-based energy. Renewable energy sources, such as photovoltaic (PV) and fuel cell, can be used to enhance the safety, reliability, sustainability, and transmission efficiency of a power system. This dissertation focuses on the power conversion and control for two major renewable-energy sources: PV and fuel cell. Firstly, a current-based, maximum power-point tracking (MPPT) algorithm is proposed for PV energy. An economical converter system using the above scheme for converting the output from PV panels into 60 Hz AC voltage is developed and built. Secondly, a novel circuit model for the Proton Exchange Membrane (PEM) fuel-cell stack that is useful in the design and analysis of fuel-cell-based power systems is proposed. This Pspice-based model uses elements available in the Pspice library with some modifications to represent both the static and dynamic responses of a PEM fuel-cell module. The accuracy of the model is verified by comparing the simulation and experimental results. Thirdly, a DSP-controlled three-phase induction-motor drive using constant voltage over frequency is built and can be used in a fuel-cell automobile. A hydrogen sensor is used in the drive to both sound an alarm and shut down the inverter trigger pulses through the DSP. Finally, a hybrid power system consisting of PV panels and fuel cell is proposed and built. In the proposed system, PV panels can supply most of the power when the sunlight is available, and the excess power required by the load is supplied by a fuel cell. Load sharing between a fuel cell (FC) and the PV panel is investigated by both simulation and experiments.
Metzger, Marco; Bareiss, Petra M; Nikolov, Ivan; Skutella, Thomas; Just, Lothar
2007-01-01
Three-dimensional intestinal cultures offer new possibilities for the examination of growth potential, analysis of time specific gene expression, and spatial cellular arrangement of enteric nervous system in an organotypical environment. We present an easy to produce in vitro model of the enteric nervous system for analysis and manipulation of cellular differentiation processes. Slice cultures of murine fetal colon were cultured on membrane inserts for up to 2 weeks without loss of autonomous contractility. After slice preparation, cultured tissue reorganized within the first days in vitro. Afterward, the culture possessed more than 35 cell layers, including high prismatic epithelial cells, smooth muscle cells, glial cells, and neurons analyzed by immunohistochemistry. The contraction frequency of intestinal slice culture could be modulated by the neurotransmitter serotonin and the sodium channel blocker tetrodotoxin. Coculture experiments with cultured neurospheres isolated from enhanced green fluorescent protein (eGFP) transgenic mice demonstrated that differentiating eGFP-positive neurons were integrated into the intestinal tissue culture. This slice culture model of enteric nervous system proved to be useful for studying cell-cell interactions, cellular signaling, and cell differentiation processes in a three-dimensional cell arrangement.
Modeling collective cell migration in geometric confinement
NASA Astrophysics Data System (ADS)
Tarle, Victoria; Gauquelin, Estelle; Vedula, S. R. K.; D'Alessandro, Joseph; Lim, C. T.; Ladoux, Benoit; Gov, Nir S.
2017-06-01
Monolayer expansion has generated great interest as a model system to study collective cell migration. During such an expansion the culture front often develops ‘fingers’, which we have recently modeled using a proposed feedback between the curvature of the monolayer’s leading edge and the outward motility of the edge cells. We show that this model is able to explain the puzzling observed increase of collective cellular migration speed of a monolayer expanding into thin stripes, as well as describe the behavior within different confining geometries that were recently observed in experiments. These comparisons give support to the model and emphasize the role played by the edge cells and the edge shape during collective cell motion.
Modeling collective cell migration in geometric confinement.
Tarle, Victoria; Gauquelin, Estelle; Vedula, S R K; D'Alessandro, Joseph; Lim, C T; Ladoux, Benoit; Gov, Nir S
2017-05-03
Monolayer expansion has generated great interest as a model system to study collective cell migration. During such an expansion the culture front often develops 'fingers', which we have recently modeled using a proposed feedback between the curvature of the monolayer's leading edge and the outward motility of the edge cells. We show that this model is able to explain the puzzling observed increase of collective cellular migration speed of a monolayer expanding into thin stripes, as well as describe the behavior within different confining geometries that were recently observed in experiments. These comparisons give support to the model and emphasize the role played by the edge cells and the edge shape during collective cell motion.
NASA Astrophysics Data System (ADS)
Rainarli, E.; E Dewi, K.
2017-04-01
The research conducted by Fister & Panetta shown an optimal control model of bone marrow cells against Cell Cycle Specific chemotherapy drugs. The model used was a bilinear system model. Fister & Panetta research has proved existence, uniqueness, and characteristics of optimal control (the chemotherapy effect). However, by using this model, the amount of bone marrow at the final time could achieve less than 50 percent from the amount of bone marrow before given treatment. This could harm patients because the lack of bone marrow cells made the number of leukocytes declining and patients will experience leukemia. This research would examine the optimal control of a bilinear system that applied to fixed final state. It will be used to determine the length of optimal time in administering chemotherapy and kept bone marrow cells on the allowed level at the same time. Before simulation conducted, this paper shows that the system could be controlled by using a theory of Lie Algebra. Afterward, it shows the characteristics of optimal control. Based on the simulation, it indicates that strong chemotherapy drug given in a short time frame is the most optimal condition to keep bone marrow cells spine on the allowed level but still could put playing an effective treatment. It gives preference of the weight of treatment for keeping bone marrow cells. The result of chemotherapy’s effect (u) is not able to reach the maximum value. On the other words, it needs to make adjustments of medicine’s dosage to satisfy the final treatment condition e.g. the number of bone marrow cells should be at the allowed level.
Encapsulated Optically Responsive Cell Systems: Toward Smart Implants in Biomedicine.
Boss, Christophe; Bouche, Nicolas; De Marchi, Umberto
2018-04-01
Managing increasingly prevalent chronic diseases will require close continuous monitoring of patients. Cell-based biosensors may be used for implantable diagnostic systems to monitor health status. Cells are indeed natural sensors in the body. Functional cellular systems can be maintained in the body for long-term implantation using cell encapsulation technology. By taking advantage of recent progress in miniaturized optoelectronic systems, the genetic engineering of optically responsive cells may be combined with cell encapsulation to generate smart implantable cell-based sensing systems. In biomedical research, cell-based biosensors may be used to study cell signaling, therapeutic effects, and dosing of bioactive molecules in preclinical models. Today, a wide variety of genetically encoded fluorescent sensors have been developed for real-time imaging of living cells. Here, recent developments in genetically encoded sensors, cell encapsulation, and ultrasmall optical systems are highlighted. The integration of these components in a new generation of biosensors is creating innovative smart in vivo cell-based systems, bringing novel perspectives for biomedical research and ultimately allowing unique health monitoring applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ucciferri, Nadia; Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa; Sbrana, Tommaso
2014-12-17
Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting differentmore » cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.« less
Seet, Christopher S.; He, Chongbin; Bethune, Michael T.; Li, Suwen; Chick, Brent; Gschweng, Eric H.; Zhu, Yuhua; Kim, Kenneth; Kohn, Donald B.; Baltimore, David; Crooks, Gay M.; Montel-Hagen, Amélie
2017-01-01
Studies of human T cell development require robust model systems that recapitulate the full span of thymopoiesis, from hematopoietic stem and progenitor cells (HSPCs) through to mature T cells. Existing in vitro models induce T cell commitment from human HSPCs; however, differentiation into mature CD3+TCRab+ single positive (SP) CD8+ or CD4+ cells is limited. We describe here a serum-free, artificial thymic organoid (ATO) system that supports highly efficient and reproducible in vitro differentiation and positive selection of conventional human T cells from all sources of HSPCs. ATO-derived T cells exhibited mature naïve phenotypes, a diverse TCR repertoire, and TCR-dependent function. ATOs initiated with TCR-engineered HSPCs produced T cells with antigen specific cytotoxicity and near complete lack of endogenous TCR Vβ expression, consistent with allelic exclusion of Vβ loci. ATOs provide a robust tool for studying human T cell development and stem cell based approaches to engineered T cell therapies. PMID:28369043
A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology
2011-01-01
Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191
Predicting lymph node output efficiency using systems biology
Gong, Chang; Mattila, Joshua T.; Miller, Mark; Flynn, JoAnne L.; Linderman, Jennifer J.; Kirschner, D.
2013-01-01
Dendritic cells (DCs) capture pathogens and foreign antigen (Ag) in peripheral tissues and migrate to secondary lymphoid tissues, such as lymph nodes (LNs), where they present processed Ag as MHC-bound peptide (pMHC) to naïve T cells. Interactions between DCs and T cells result, over periods of hours, in activation, clonal expansion and differentiation of antigen-specific T cells, leading to primed cells that can now participate in immune responses. Two-photon microscopy (2PM) has been widely adopted to analyze lymphocyte dynamics and can serve as a powerful in vivo assay for cell trafficking and activation over short length and time scales. Linking biological phenomena between vastly different spatiotemporal scales can be achieved using a systems biology approach. We developed a 3D agent-based cellular model of a LN that allows for the simultaneous in silico simulation of T cell trafficking, activation and production of effector cells under different antigen (Ag) conditions. The model anatomy is based on in situ analysis of LN sections (from primates and mice) and cell dynamics based on quantitative measurements from 2PM imaging of mice. Our simulations make three important predictions. First, T cell encounters by DCs and T cell receptor (TCR) repertoire scanning are more efficient in a 3D model compared with 2D, suggesting that a 3D model is needed to analyze LN function. Second, LNs are able to produce primed CD4+T cells at the same efficiency over broad ranges of cognate frequencies (from 10−5 to 10−2). Third, reducing the time that naïve T cells are required to bind DCs before becoming activated will increase the rate at which effector cells are produced. This 3D model provides a robust platform to study how T cell trafficking and activation dynamics relate to the efficiency of T cell priming and clonal expansion. We envision that this systems biology approach will provide novel insights for guiding vaccine development and understanding immune responses to infection. PMID:23816876
Lewis, Natasha S; Lewis, Emily EL; Mullin, Margaret; Wheadon, Helen; Dalby, Matthew J; Berry, Catherine C
2017-01-01
Multicellular spheroids are an established system for three-dimensional cell culture. Spheroids are typically generated using hanging drop or non-adherent culture; however, an emerging technique is to use magnetic levitation. Herein, mesenchymal stem cell spheroids were generated using magnetic nanoparticles and subsequently cultured within a type I collagen gel, with a view towards developing a bone marrow niche environment. Cells were loaded with magnetic nanoparticles, and suspended beneath an external magnet, inducing self-assembly of multicellular spheroids. Cells in spheroids were viable and compared to corresponding monolayer controls, maintained stem cell phenotype and were quiescent. Interestingly, core spheroid necrosis was not observed, even with increasing spheroid size, in contrast to other commonly used spheroid systems. This mesenchymal stem cell spheroid culture presents a potential platform for modelling in vitro bone marrow stem cell niches, elucidating interactions between cells, as well as a useful model for drug delivery studies. PMID:28616152
Real-time visualization of early metastasis events in Danio rerio
NASA Astrophysics Data System (ADS)
Tanner, Kandice
Metastasis, the process by which cancer cells travel from a primary tumor to establish lesions in distant organs, is the cause of most cancer-related deaths. One critical process during metastasis is the transit of cells from a primary tumor and through the vasculature or lymphatic systems to a distant site prior to metastatic colonization. However, visualization of cellular behavior in the vasculature is difficult in most model systems, where final cell destination is not known beforehand. Here, we used bone- and brain-tropic subclones of MDA-MB-231 breast adenocarcinoma cells (231BO and 231BR, respectively) injected into the circulation of embryonic zebrafish as a model xenograft system of metastasis. The zebrafish vasculature contains vessels on the scale of human capillaries. Real-time intravital imaging revealed metastatic spread to be an inefficient process, with less than 20% of cells passing through a given organ remaining there following 14 h of imaging. Additionally, there was no significant difference in the organ-specific residence time or migration speed of single 231BO and 231BR cells in the organ vasculature. Instead, cell capture was dependent on vessel topography and the function of integrin β1. Interestingly, a fraction of cells extravasated from the vasculature and survived in a perivascular position in the head and caudal venous plexus for up to two weeks. In conclusion, use of the zebrafish vasculature as a model capillary bed has revealed critical steps in early metastasis that are difficult to capture in other systems.
NASA Astrophysics Data System (ADS)
Lambrou, George I.; Chatziioannou, Aristotelis; Vlahopoulos, Spiros; Moschovi, Maria; Chrousos, George P.
Biological systems are dynamic and possess properties that depend on two key elements: initial conditions and the response of the system over time. Conceptualizing this on tumor models will influence conclusions drawn with regard to disease initiation and progression. Alterations in initial conditions dynamically reshape the properties of proliferating tumor cells. The present work aims to test the hypothesis of Wolfrom et al., that proliferation shows evidence for deterministic chaos in a manner such that subtle differences in the initial conditions give rise to non-linear response behavior of the system. Their hypothesis, tested on adherent Fao rat hepatoma cells, provides evidence that these cells manifest aperiodic oscillations in their proliferation rate. We have tested this hypothesis with some modifications to the proposed experimental setup. We have used the acute lymphoblastic leukemia cell line CCRF-CEM, as it provides an excellent substrate for modeling proliferation dynamics. Measurements were taken at time points varying from 24h to 48h, extending the assayed populations beyond that of previous published reports that dealt with the complex dynamic behavior of animal cell populations. We conducted flow cytometry studies to examine the apoptotic and necrotic rate of the system, as well as DNA content changes of the cells over time. The cells exhibited a proliferation rate of nonlinear nature, as this rate presented oscillatory behavior. The obtained data have been fit in known models of growth, such as logistic and Gompertzian growth.
Spatial self-organization in hybrid models of multicellular adhesion
NASA Astrophysics Data System (ADS)
Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard
2016-10-01
Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.
NASA Astrophysics Data System (ADS)
Gallas, Michelle R.; Gallas, Marcia R.; Gallas, Jason A. C.
2014-10-01
We study complex oscillations generated by the de Pillis-Radunskaya model of cancer growth, a model including interactions between tumor cells, healthy cells, and activated immune system cells. We report a wide-ranging systematic numerical classification of the oscillatory states and of their relative abundance. The dynamical states of the cell populations are characterized here by two independent and complementary types of stability diagrams: Lyapunov and isospike diagrams. The model is found to display stability phases organized regularly in old and new ways: Apart from the familiar spirals of stability, it displays exceptionally long zig-zag networks and intermixed cascades of two- and three-doubling flanked stability islands previously detected only in feedback systems with delay. In addition, we also characterize the interplay between continuous spike-adding and spike-doubling mechanisms responsible for the unbounded complexification of periodic wave patterns. This article is dedicated to Prof. Hans Jürgen Herrmann on the occasion of his 60th birthday.
Gutierrez, Jahir M; Lewis, Nathan E
2015-07-01
Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Artificial cell mimics as simplified models for the study of cell biology.
Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval
2017-07-01
Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.
Thermofluid Modeling of Fuel Cells
NASA Astrophysics Data System (ADS)
Young, John B.
2007-01-01
Fuel cells offer the prospect of silent electrical power generation at high efficiency with near-zero pollutant emission. Many materials and fabrication problems have now been solved and attention has shifted toward system modeling, including the fluid flows that supply the cells with hydrogen and oxygen. This review describes the current thermofluid modeling capabilities for proton exchange membrane fuel cells (PEMFCs) and solid oxide fuel cells (SOFCs), the most promising candidates for commercial exploitation. Topics covered include basic operating principles and stack design, convective-diffusive flow in porous solids, special modeling issues for PEMFCs and SOFCs, and the use of computational fluid dynamics (CFD) methods.
Three-dimensional cell culture models for investigating human viruses.
He, Bing; Chen, Guomin; Zeng, Yi
2016-10-01
Three-dimensional (3D) culture models are physiologically relevant, as they provide reproducible results, experimental flexibility and can be adapted for high-throughput experiments. Moreover, these models bridge the gap between traditional two-dimensional (2D) monolayer cultures and animal models. 3D culture systems have significantly advanced basic cell science and tissue engineering, especially in the fields of cell biology and physiology, stem cell research, regenerative medicine, cancer research, drug discovery, and gene and protein expression studies. In addition, 3D models can provide unique insight into bacteriology, virology, parasitology and host-pathogen interactions. This review summarizes and analyzes recent progress in human virological research with 3D cell culture models. We discuss viral growth, replication, proliferation, infection, virus-host interactions and antiviral drugs in 3D culture models.
A spatial model of the efficiency of T cell search in the influenza-infected lung.
Levin, Drew; Forrest, Stephanie; Banerjee, Soumya; Clay, Candice; Cannon, Judy; Moses, Melanie; Koster, Frederick
2016-06-07
Emerging strains of influenza, such as avian H5N1 and 2009 pandemic H1N1, are more virulent than seasonal H1N1 influenza, yet the underlying mechanisms for these differences are not well understood. Subtle differences in how a given strain interacts with the immune system are likely a key factor in determining virulence. One aspect of the interaction is the ability of T cells to locate the foci of the infection in time to prevent uncontrolled expansion. Here, we develop an agent based spatial model to focus on T cell migration from lymph nodes through the vascular system to sites of infection. We use our model to investigate whether different strains of influenza modulate this process. We calibrate the model using viral and chemokine secretion rates we measure in vitro together with values taken from literature. The spatial nature of the model reveals unique challenges for T cell recruitment that are not apparent in standard differential equation models. In this model comparing three influenza viruses, plaque expansion is governed primarily by the replication rate of the virus strain, and the efficiency of the T cell search-and-kill is limited by the density of infected epithelial cells in each plaque. Thus for each virus there is a different threshold of T cell search time above which recruited T cells are unable to control further expansion. Future models could use this relationship to more accurately predict control of the infection. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cellular Manufacturing System with Dynamic Lot Size Material Handling
NASA Astrophysics Data System (ADS)
Khannan, M. S. A.; Maruf, A.; Wangsaputra, R.; Sutrisno, S.; Wibawa, T.
2016-02-01
Material Handling take as important role in Cellular Manufacturing System (CMS) design. In several study at CMS design material handling was assumed per pieces or with constant lot size. In real industrial practice, lot size may change during rolling period to cope with demand changes. This study develops CMS Model with Dynamic Lot Size Material Handling. Integer Linear Programming is used to solve the problem. Objective function of this model is minimizing total expected cost consisting machinery depreciation cost, operating costs, inter-cell material handling cost, intra-cell material handling cost, machine relocation costs, setup costs, and production planning cost. This model determines optimum cell formation and optimum lot size. Numerical examples are elaborated in the paper to ilustrate the characterictic of the model.
Toxicity of Nanoparticles and an Overview of Current Experimental Models.
Bahadar, Haji; Maqbool, Faheem; Niaz, Kamal; Abdollahi, Mohammad
2016-01-01
Nanotechnology is a rapidly growing field having potential applications in many areas. Nanoparticles (NPs) have been studied for cell toxicity, immunotoxicity, and genotoxicity. Tetrazolium-based assays such as MTT, MTS, and WST-1 are used to determine cell viability. Cell inflammatory response induced by NPs is checked by measuring inflammatory biomarkers, such as IL-8, IL-6, and tumor necrosis factor, using ELISA. Lactate dehydrogenase (LDH) assay is used for cell membrane integrity. Different types of cell cultures, including cancer cell lines have been employed as in vitro toxicity models. It has been generally agreed that NPs interfere with either assay materials or with detection systems. So far, toxicity data generated by employing such models are conflicting and inconsistent. Therefore, on the basis of available experimental models, it may be difficult to judge and list some of the more valuable NPs as more toxic to biological systems and vice versa. Considering the potential applications of NPs in many fields and the growing apprehensions of FDA about the toxic potential of nanoproducts, it is the need of the hour to look for new internationally agreed free of bias toxicological models by focusing more on in vivo studies.
Voronoi cell patterns: Theoretical model and applications
NASA Astrophysics Data System (ADS)
González, Diego Luis; Einstein, T. L.
2011-11-01
We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.
Innovation in stem cell advocacy: you only get what you can measure.
Jakimo, Alan L; Fernandez, Alan C
2011-11-01
We propose that stem cell advocacy must engage in self-analysis to determine how to be maximally effective. For this analysis, eight advocacy elements can be measured: agitation, legislation, regulation, litigation, policy development, collaboration, education and innovation. For several of these elements, we show that stem cell advocates, particularly advocates for human embryonic stem cell research, have been matched by their opponents. This demonstrates the need for combining innovation and collaboration with advocacy-oriented education. To pursue innovative and collaborative education, we propose a 'bench-to-public knowledge' model and present some preliminary observations made with this model for different stem cell types. We also propose development of a semantic web information system to be operated within Internet Cloud/Apps/Social Media. We call this system the 'Stem Cell Information Technology Accelerator Platform'. Toward its construction, we propose formation of a working group to conceive semantic web ontology for stem cell science and its clinical translation into medicine. This ontology would function as a map of the relationships between and among the various informational components comprising discourse on stem cell research and its clinical translation, and would allow various stakeholders to contribute to evolving models of that science and translation. These models could, in turn, support an innovative and collaborative approach to education in furtherance of stem cell advocacy.
A quantitative framework to evaluate modeling of cortical development by neural stem cells
Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.
2014-01-01
Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955
Performance of a Fuel-Cell-Powered, Small Electric Airplane Assessed
NASA Technical Reports Server (NTRS)
Berton, Jeffrey J.
2004-01-01
Rapidly emerging fuel-cell-power technologies may be used to launch a new revolution of electric propulsion systems for light aircraft. Future small electric airplanes using fuel cell technologies hold the promise of high reliability, low maintenance, low noise, and - with the exception of water vapor - zero emissions. An analytical feasibility and performance assessment was conducted by NASA Glenn Research Center's Airbreathing Systems Analysis Office of a fuel-cell-powered, propeller-driven, small electric airplane based on a model of the MCR-01 two-place kitplane (Dyn'Aero, Darois, France). This assessment was conducted in parallel with an ongoing effort by the Advanced Technology Products Corporation and the Foundation for Advancing Science and Technology Education. Their project - partially funded by a NASA grant - is to design, build, and fly the first manned, continuously propelled, nongliding electric airplane. In our study, an analytical performance model of a proton exchange membrane (PEM) fuel cell propulsion system was developed and applied to a notional, two-place light airplane modeled after the MCR-01 kitplane. The PEM fuel cell stack was fed pure hydrogen fuel and humidified ambient air via a small automotive centrifugal supercharger. The fuel cell performance models were based on chemical reaction analyses calibrated with published data from the fledgling U.S. automotive fuel cell industry. Electric propeller motors, rated at two shaft power levels in separate assessments, were used to directly drive a two-bladed, variable-pitch propeller. Fuel sources considered were compressed hydrogen gas and cryogenic liquid hydrogen. Both of these fuel sources provided pure, contaminant-free hydrogen for the PEM cells.
Surface tension and modeling of cellular intercalation during zebrafish gastrulation.
Calmelet, Colette; Sepich, Diane
2010-04-01
In this paper we discuss a model of zebrafish embryo notochord development based on the effect of surface tension of cells at the boundaries. We study the process of interaction of mesodermal cells at the boundaries due to adhesion and cortical tension, resulting in cellular intercalation. From in vivo experiments, we obtain cell outlines of time-lapse images of cell movements during zebrafish embryo development. Using Cellular Potts Model, we calculate the total surface energy of the system of cells at different time intervals at cell contacts. We analyze the variations of total energy depending on nature of cell contacts. We demonstrate that our model can be viable by calculating the total surface energy value for experimentally observed configurations of cells and showing that in our model these configurations correspond to a decrease in total energy values in both two and three dimensions.
Sohrabi, Salman; Liu, Yaling
2018-03-01
Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the bubble dynamic and cell mechanical damage during the printing process.
NASA Astrophysics Data System (ADS)
Sohrabi, Salman; Liu, Yaling
2018-03-01
Pseudopotential lattice Boltzmann methods (LBMs) can simulate a phase transition in high-density ratio multiphase flow systems. If coupled with thermal LBMs through equation of state, they can be used to study instantaneous phase transition phenomena with a high-temperature gradient where only one set of formulations in an LBM system can handle liquid, vapor, phase transition, and heat transport. However, at lower temperatures an unrealistic spurious current at the interface introduces instability and limits its application in real flow system. In this study, we proposed new modifications to the LBM system to minimize a spurious current which enables us to study nucleation dynamic at room temperature. To demonstrate the capabilities of this approach, the thermal ejection process is modeled as one example of a complex flow system. In an inkjet printer, a thermal pulse instantly heats up the liquid in a microfluidic chamber and nucleates bubble vapor providing the pressure pulse necessary to eject droplets at high speed. Our modified method can present a more realistic model of the explosive vaporization process since it can also capture a high-temperature/density gradient at nucleation region. Thermal inkjet technology has been successfully applied for printing cells, but cells are susceptible to mechanical damage or death as they squeeze out of the nozzle head. To study cell deformation, a spring network model, representing cells, is connected to the LBM through the immersed boundary method. Looking into strain and stress distribution of a cell membrane at its most deformed state, it is found that a high stretching rate effectively increases the rupture tension. In other words, membrane deformation energy is released through creation of multiple smaller nanopores rather than big pores. Overall, concurrently simulating multiphase flow, phase transition, heat transfer, and cell deformation in one unified LB platform, we are able to provide a better insight into the bubble dynamic and cell mechanical damage during the printing process.
Schmutzer, Michael; Aszodi, Attila
2017-04-01
The loss and degradation of articular cartilage tissue matrix play central roles in the process of osteoarthritis (OA). New models for evaluating cartilage repair/regeneration are thus of great value for transferring various culture systems into clinically relevant situations. The repair process can be better monitored in ex vivo systems than in in vitro cell cultures. I have therefore established an ex vivo defect model prepared from bovine femoral condyles for evaluating cartilage repair by the implantation of cells cultured in various ways, e.g., monolayer-cultured cells or suspension or pellet cultures of articular bovine chondrocytes representing different cell compactions with variable densities of chondrocytes. I report that the integrin subunit α10 was significantly upregulated in suspension-cultured bovine chondrocytes at passage P2 compared with monolayer-cultured cells at P1 (p = 0.0083) and P2 (p < 0.05). Suspension-cultured cells did not promote cartilage repair when compared with implanted monolayer-cultured chondrocytes and pellets: 24.0 ± 0.66% for suspension cells, 46.4 ± 2.9% for monolayer cells, and 127.64 ± 0.90% for pellets (p < 0.0001) of the original defect volume (percentage of defect). Additional cultivation with chondrogenesis-promoting growth factors TGF-β1 and BMP-2 revealed an enhancing effect on cartilage repair in all settings. The advantage and innovation of this system over in vitro differentiation (e.g., micromass, pellet) assays is the possibility of examining and evaluating cartilage regeneration in an environment in which implanted cells are embedded within native surrounding tissue at the defect site. Such ex vivo explants might serve as a better model system to mimic clinical situations. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya
2013-01-01
Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.
Denker, Elsa; Jiang, Di
2012-05-01
Biological tubes are a prevalent structural design across living organisms. They provide essential functions during the development and adult life of an organism. Increasing progress has been made recently in delineating the cellular and molecular mechanisms underlying tubulogenesis. This review aims to introduce ascidian notochord morphogenesis as an interesting model system to study the cell biology of tube formation, to a wider cell and developmental biology community. We present fundamental morphological and cellular events involved in notochord morphogenesis, compare and contrast them with other more established tubulogenesis model systems, and point out some unique features, including bipolarity of the notochord cells, and using cell shape changes and cell rearrangement to connect lumens. We highlight some initial findings in the molecular mechanisms of notochord morphogenesis. Based on these findings, we present intriguing problems and put forth hypotheses that can be addressed in future studies. Copyright © 2012 Elsevier Ltd. All rights reserved.
3D modeling of cancer stem cell niche
He, Jun; Xiong, Li; Li, Qinglong; Lin, Liangwu; Miao, Xiongying; Yan, Shichao; Hong, Zhangyong; Yang, Leping; Wen, Yu; Deng, Xiyun
2018-01-01
Cancer stem cells reside in a distinct microenvironment called niche. The reciprocal interactions between cancer stem cells and niche contribute to the maintenance and enrichment of cancer stem cells. In order to simulate the interactions between cancer stem cells and niche, three-dimensional models have been developed. These in vitro culture systems recapitulate the spatial dimension, cellular heterogeneity, and the molecular networks of the tumor microenvironment and show great promise in elucidating the pathophysiology of cancer stem cells and designing more clinically relavant treatment modalites. PMID:29416698
Zhang, Yanli; Sastre, Danuta; Wang, Feng
2018-01-01
Induced pluripotent stem cells hold tremendous potential for biological and therapeutic applications. The development of efficient technologies for targeted genome alteration of stem cells in disease models is a prerequisite for utilizing stem cells to their full potential. The revolutionary technology for genome editing known as the clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 9 (Cas9) system is recently recognized as a powerful tool for editing DNA at specific loci. The ease of use of the CRISPR-Cas9 technology will allow us to improve our understanding of genomic variation in disease processes via cellular and animal models. More recently, this system was modified to repress (CRISPR interference, CRISPRi) or activate (CRISPR activation, CRISPRa) gene expression without alterations in the DNA, which amplified the scope of applications of CRISPR systems for stem cell biology. Here, we highlight latest advances of CRISPR-associated applications in human pluripotent stem cells. The challenges and future prospects of CRISPR-based systems for human research are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tan, Ji Wei; Israf, Daud Ahmad; Harith, Hanis Haze
tHGA, a geranyl acetophenone compound originally isolated from a local shrub called Melicope ptelefolia, has been previously reported to prevent ovalbumin-induced allergic airway inflammation in a murine model of allergic asthma by targeting cysteinyl leukotriene synthesis. Mast cells are immune effector cells involved in the pathogenesis of allergic diseases including asthma by releasing cysteinyl leukotrienes. The anti-asthmatic properties of tHGA could be attributed to its inhibitory effect on mast cell degranulation. As mast cell degranulation is an important event in allergic responses, this study aimed to investigate the anti-allergic effects of tHGA in cellular and animal models of IgE-mediated mastmore » cell degranulation. For in vitro model of IgE-mediated mast cell degranulation, DNP-IgE-sensitized RBL-2H3 cells were pre-treated with tHGA before challenged with DNP-BSA to induce degranulation. For IgE-mediated passive systemic anaphylaxis, Sprague Dawley rats were sensitized by intraperitoneal injection of DNP-IgE before challenged with DNP-BSA. Both in vitro and in vivo models showed that tHGA significantly inhibited the release of preformed mediators (β-hexosaminidase and histamine) as well as de novo mediators (interleukin-4, tumour necrosis factor-α, prostaglandin D{sub 2} and leukotriene C{sub 4}). Pre-treatment of tHGA also prevented IgE-challenged RBL-2H3 cells and peritoneal mast cells from undergoing morphological changes associated with mast cell degranulation. These findings indicate that tHGA possesses potent anti-allergic activity via attenuation of IgE-mediated mast cell degranulation and inhibition of IgE-mediated passive systemic anaphylaxis. Thus, tHGA may have the potential to be developed as a mast cell stabilizer for the treatment of allergic diseases in the future. - Highlights: • The in vitro and in vivo mast cell stabilizing effects of tHGA were examined. • tHGA counteracts the plasma membrane deformation in degranulating mast cells. • tHGA attenuates preformed and de novo mediators released by degranulating mast cells. • tHGA prevents in vivo mast cell activation and passive systemic anaphylaxis in rats. • tHGA could be a potential mast cell stabilizer for the treatment of allergic diseases.« less
A Computational Framework for Bioimaging Simulation
Watabe, Masaki; Arjunan, Satya N. V.; Fukushima, Seiya; Iwamoto, Kazunari; Kozuka, Jun; Matsuoka, Satomi; Shindo, Yuki; Ueda, Masahiro; Takahashi, Koichi
2015-01-01
Using bioimaging technology, biologists have attempted to identify and document analytical interpretations that underlie biological phenomena in biological cells. Theoretical biology aims at distilling those interpretations into knowledge in the mathematical form of biochemical reaction networks and understanding how higher level functions emerge from the combined action of biomolecules. However, there still remain formidable challenges in bridging the gap between bioimaging and mathematical modeling. Generally, measurements using fluorescence microscopy systems are influenced by systematic effects that arise from stochastic nature of biological cells, the imaging apparatus, and optical physics. Such systematic effects are always present in all bioimaging systems and hinder quantitative comparison between the cell model and bioimages. Computational tools for such a comparison are still unavailable. Thus, in this work, we present a computational framework for handling the parameters of the cell models and the optical physics governing bioimaging systems. Simulation using this framework can generate digital images of cell simulation results after accounting for the systematic effects. We then demonstrate that such a framework enables comparison at the level of photon-counting units. PMID:26147508
Non-Invasive Cell-Based Therapy for Traumatic Optic Neuropathy
2013-10-01
Morgans, Sergey Girman, Raymond Lund and Shaomei Wang Retinal Morphological and Functional Changes in an Animal Model of Retinitis Pigmentosa . Vis...model was created. 2. Rat MSC and M-Sch were reliable produced for experiments. 3. Systemic administration of MSC significantly preserved retinal ...TON also promote retinal ganglion cell survival. From the first year study, we have shown that systemic administration of MSC can significantly
Distributed delays in a hybrid model of tumor-immune system interplay.
Caravagna, Giulio; Graudenzi, Alex; d'Onofrio, Alberto
2013-02-01
A tumor is kinetically characterized by the presence of multiple spatio-temporal scales in which its cells interplay with, for instance, endothelial cells or Immune system effectors, exchanging various chemical signals. By its nature, tumor growth is an ideal object of hybrid modeling where discrete stochastic processes model low-numbers entities, and mean-field equations model abundant chemical signals. Thus, we follow this approach to model tumor cells, effector cells and Interleukin-2, in order to capture the Immune surveillance effect. We here present a hybrid model with a generic delay kernel accounting that, due to many complex phenomena such as chemical transportation and cellular differentiation, the tumor-induced recruitment of effectors exhibits a lag period. This model is a Stochastic Hybrid Automata and its semantics is a Piecewise Deterministic Markov process where a two-dimensional stochastic process is interlinked to a multi-dimensional mean-field system. We instantiate the model with two well-known weak and strong delay kernels and perform simulations by using an algorithm to generate trajectories of this process. Via simulations and parametric sensitivity analysis techniques we (i) relate tumor mass growth with the two kernels, we (ii) measure the strength of the Immune surveillance in terms of probability distribution of the eradication times, and (iii) we prove, in the oscillatory regime, the existence of a stochastic bifurcation resulting in delay-induced tumor eradication.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arsenin, V. V.; Terekhin, P. N.
2010-08-15
The Kruskal-Oberman kinetic model is used to determine the conditions for the convective stability of a plasma in a system of coupled axisymmetric adiabatic open cells in which the magnetic field curvature has opposite signs. For a combination of a nonparaxial simple mirror cell and a semicusp, the boundaries of the interval of values of the flux coordinate where the plasma can be stable are determined, as well as the range in which the ratio of the pressures in the component cells should lie. Numerical simulations were carried out for different particle distributions over the pitch angle.
Chemical Ototoxicity of the Fish Inner Ear and Lateral Line.
Coffin, Allison B; Ramcharitar, John
2016-01-01
Hair cell-driven mechanosensory systems are crucial for successful execution of a number of behaviors in fishes, and have emerged as good models for exploring questions relevant to human hearing. This review focuses on ototoxic effects in the inner ear and lateral line system of fishes. We specifically examine studies where chemical ototoxins such as aminoglycoside antibiotics have been employed as tools to disable the lateral line. Lateral line ablation results in alterations to feeding behavior and orientation to water current in a variety of species. However, neither behavior is abolished in the presence of additional sensory cues, supporting the hypothesis that many fish behaviors are driven by multisensory integration. Within biomedical research, the larval zebrafish lateral line has become an important model system for understanding signaling mechanisms that contribute to hair cell death and for developing novel pharmacological therapies that protect hair cells from ototoxic damage. Furthermore, given that fishes robustly regenerate damaged hair cells, ototoxin studies in fishes have broadened our understanding of the molecular and genetic events in an innately regenerative system, offering potential targets for mammalian hair cell regeneration. Collectively, studies of fish mechanosensory systems have yielded insight into fish behavior and in mechanisms of hair cell death, protection, and regeneration.
The fuel cell model of abiogenesis: a new approach to origin-of-life simulations.
Barge, Laura M; Kee, Terence P; Doloboff, Ivria J; Hampton, Joshua M P; Ismail, Mohammed; Pourkashanian, Mohamed; Zeytounian, John; Baum, Marc M; Moss, John A; Lin, Chung-Kuang; Kidd, Richard D; Kanik, Isik
2014-03-01
In this paper, we discuss how prebiotic geo-electrochemical systems can be modeled as a fuel cell and how laboratory simulations of the origin of life in general can benefit from this systems-led approach. As a specific example, the components of what we have termed the "prebiotic fuel cell" (PFC) that operates at a putative Hadean hydrothermal vent are detailed, and we used electrochemical analysis techniques and proton exchange membrane (PEM) fuel cell components to test the properties of this PFC and other geo-electrochemical systems, the results of which are reported here. The modular nature of fuel cells makes them ideal for creating geo-electrochemical reactors with which to simulate hydrothermal systems on wet rocky planets and characterize the energetic properties of the seafloor/hydrothermal interface. That electrochemical techniques should be applied to simulating the origin of life follows from the recognition of the fuel cell-like properties of prebiotic chemical systems and the earliest metabolisms. Conducting this type of laboratory simulation of the emergence of bioenergetics will not only be informative in the context of the origin of life on Earth but may help in understanding whether life might emerge in similar environments on other worlds.
Systems Modeling in Developmental Toxicity
An individual starts off as a single cell, the progeny of which form complex structures that are themselves integrated into progressively larger systems. Developmental biology is concerned with how this cellular complexity and patterning arises through orchestration of cell divi...
A model for the kinetics of homotypic cellular aggregation under static conditions
NASA Technical Reports Server (NTRS)
Neelamegham, S.; Munn, L. L.; Zygourakis, K.; McIntire, L. V. (Principal Investigator)
1997-01-01
We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells.
Cell-Free Optogenetic Gene Expression System.
Jayaraman, Premkumar; Yeoh, Jing Wui; Jayaraman, Sudhaghar; Teh, Ai Ying; Zhang, Jingyun; Poh, Chueh Loo
2018-04-20
Optogenetic tools provide a new and efficient way to dynamically program gene expression with unmatched spatiotemporal precision. To date, their vast potential remains untapped in the field of cell-free synthetic biology, largely due to the lack of simple and efficient light-switchable systems. Here, to bridge the gap between cell-free systems and optogenetics, we studied our previously engineered one component-based blue light-inducible Escherichia coli promoter in a cell-free environment through experimental characterization and mathematical modeling. We achieved >10-fold dynamic expression and demonstrated rapid and reversible activation of the target gene to generate oscillatory response. The deterministic model developed was able to recapitulate the system behavior and helped to provide quantitative insights to optimize dynamic response. This in vitro optogenetic approach could be a powerful new high-throughput screening technology for rapid prototyping of complex biological networks in both space and time without the need for chemical induction.
Dynamical analysis of uterine cell electrical activity model.
Rihana, S; Santos, J; Mondie, S; Marque, C
2006-01-01
The uterus is a physiological system consisting of a large number of interacting smooth muscle cells. The uterine excitability changes remarkably with time, generally quiescent during pregnancy, the uterus exhibits forceful synchronized contractions at term leading to fetus expulsion. These changes characterize thus a dynamical system susceptible of being studied through formal mathematical tools. Multiple physiological factors are involved in the regulation process of this complex system. Our aim is to relate the physiological factors to the uterine cell dynamic behaviors. Taking into account a previous work presented, in which the electrical activity of a uterine cell is described by a set of ordinary differential equations, we analyze the impact of physiological parameters on the response of the model, and identify the main subsystems generating the complex uterine electrical activity, with respect to physiological data.
Cardiac tissue engineering using perfusion bioreactor systems
Radisic, Milica; Marsano, Anna; Maidhof, Robert; Wang, Yadong; Vunjak-Novakovic, Gordana
2009-01-01
This protocol describes tissue engineering of synchronously contractile cardiac constructs by culturing cardiac cell populations on porous scaffolds (in some cases with an array of channels) and bioreactors with perfusion of culture medium (in some cases supplemented with an oxygen carrier). The overall approach is ‘biomimetic’ in nature as it tends to provide in vivo-like oxygen supply to cultured cells and thereby overcome inherent limitations of diffusional transport in conventional culture systems. In order to mimic the capillary network, cells are cultured on channeled elastomer scaffolds that are perfused with culture medium that can contain oxygen carriers. The overall protocol takes 2–4 weeks, including assembly of the perfusion systems, preparation of scaffolds, cell seeding and cultivation, and on-line and end-point assessment methods. This model is well suited for a wide range of cardiac tissue engineering applications, including the use of human stem cells, and high-fidelity models for biological research. PMID:18388955
Criteria for robustness of heteroclinic cycles in neural microcircuits
2011-01-01
We introduce a test for robustness of heteroclinic cycles that appear in neural microcircuits modeled as coupled dynamical cells. Robust heteroclinic cycles (RHCs) can appear as robust attractors in Lotka-Volterra-type winnerless competition (WLC) models as well as in more general coupled and/or symmetric systems. It has been previously suggested that RHCs may be relevant to a range of neural activities, from encoding and binding to spatio-temporal sequence generation. The robustness or otherwise of such cycles depends both on the coupling structure and the internal structure of the neurons. We verify that robust heteroclinic cycles can appear in systems of three identical cells, but only if we require perturbations to preserve some invariant subspaces for the individual cells. On the other hand, heteroclinic attractors can appear robustly in systems of four or more identical cells for some symmetric coupling patterns, without restriction on the internal dynamics of the cells. PMID:22656192
Problems in hard and soft matter: From brain folds and Levy localization to active elasticity
NASA Astrophysics Data System (ADS)
Mayett, David
This thesis presents a study of condensed matter systems at different length scales. The first part presents a study of elastic instabilities in biological systems ranging from the cerebral cortex in the brain to the lining of the intestines. Such instabilities lead to a zoo of morphologies ranging from primary folds to villi and crypts to secondary folds and are brought about by growth, mechanical stresses, or a combination of the two. We propose a novel model for the description of primary folds in the cerebral cortex. Motivated by the spatial structure of the cortex, we model its elasticity as a smectic liquid crystal. With this novel description we show that vertical pulling forces via axonal tension from the brain underlying white matter can lead to buckling, which initiates the primary folds. Moreover, we are able to obtain a reasonable estimate of the critical wavelength and strain for buckling. We also model the formation of secondary folds in the cortex to obtain a more comprehensive theory. We continue this study of elastic instabilities due to growth by studying a more general system comprised of two coupled elastic membranes, one of which undergoes growth and one that does not. We employ an active formulation of growth and compare it to the one due to Rodriguez (Rodriguez). We show that different morphologies corresponding to different systems, such as the cerebral cortex and the lining of the intestines, can be obtained from our model by choosing different active stress functional forms to begin to classify the zoo of morphologies observed in seemingly different biological systems. In the second part of this thesis, to work towards a more microscopic view of biological tissues such as the brain tissue, which is composed of neurons, glial cells, and progenitor cells, we model an experiment (Theveneau) studying the dynamic interaction between neural crest cells and placodal cells in which the placodal cells run away from the neural crest cells following contact between the two. Our modeling contributes towards generalizing the rules governing the interplay between different cell types, particularly during collective cell migration. In the final part of this thesis, we move to an even smaller length scale. Our main motivations come from a series of experiments on the localization of light and the application of tight-binding models to the electronic transport properties of DNA sequences. To this end, we study the statistical properties of the conductance distribution and Lyapunov exponents in the Anderson tight-binding model with Levy-type disorder.
Games network and application to PAs system.
Chettaoui, C; Delaplace, F; Manceny, M; Malo, M
2007-02-01
In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Xiao-xi; Liu, Chang; University of Chinese Academy of Sciences, 19A Yuquanlu, Beijing 100049
2013-08-15
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and often forms metastases, which are the most important prognostic factors. For further elucidation of the mechanism underlying the progression and metastasis of HCC, a culture system mimicking the in vivo tumor microenvironment is needed. In this study, we investigated the metastatic ability of HCC cells cultured within alginate gel (ALG) beads. In the culture system, HCC cells formed spheroids by proliferation and maintained in nuclear abnormalities. The gene and protein expression of metastasis-related molecules was increased in ALG beads, compared with the traditional adhesion culture. Furthermore, several gene expressionmore » levels in ALG bead culture system were even closer to liver cancer tissues. More importantly, in vitro invasion assay showed that the invasion cells derived from ALG beads was 7.8-fold higher than adhesion cells. Our results indicated that the in vitro three-dimensional (3D) model based on ALG beads increased metastatic ability compared with adhesion culture, even partly mimicked the in vivo tumor tissues. Moreover, due to the controllable preparation conditions, steady characteristics and production at large-scale, the 3D ALG bead model would become an important tool used in the high-throughput screening of anti-metastasis drugs and the metastatic mechanism research. -- Highlights: •We established a 3D metastasis model mimicking the metastatic ability in vivo. •The invasion ability of cells derived from our model was increased significantly. •The model is easy to reproduce, convenient to handle, and amenable for large-scale.« less
Simultaneously Coupled Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, C.; Santhanagopalan, S.; Sprague, M. A.
2016-07-28
Understanding the combined electrochemical-thermal and mechanical response of a system has a variety of applications, for example, structural failure from electrochemical fatigue and the potential induced changes of material properties. For lithium-ion batteries, there is an added concern over the safety of the system in the event of mechanical failure of the cell components. In this work, we present a generic multi-scale simultaneously coupled mechanical-electrochemical-thermal model to examine the interaction between mechanical failure and electrochemical-thermal responses. We treat the battery cell as a homogeneous material while locally we explicitly solve for the mechanical response of individual components using a homogenizationmore » model and the electrochemical-thermal responses using an electrochemical model for the battery. A benchmark problem is established to demonstrate the proposed modeling framework. The model shows the capability to capture the gradual evolution of cell electrochemical-thermal responses, and predicts the variation of those responses under different short-circuit conditions.« less
Simultaneously Coupled Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Chao; Santhanagopalan, Shriram; Sprague, Michael A.
2016-08-01
Understanding the combined electrochemical-thermal and mechanical response of a system has a variety of applications, for example, structural failure from electrochemical fatigue and the potential induced changes of material properties. For lithium-ion batteries, there is an added concern over the safety of the system in the event of mechanical failure of the cell components. In this work, we present a generic multi-scale simultaneously coupled mechanical-electrochemical-thermal model to examine the interaction between mechanical failure and electrochemical-thermal responses. We treat the battery cell as a homogeneous material while locally we explicitly solve for the mechanical response of individual components using a homogenizationmore » model and the electrochemical-thermal responses using an electrochemical model for the battery. A benchmark problem is established to demonstrate the proposed modeling framework. The model shows the capability to capture the gradual evolution of cell electrochemical-thermal responses, and predicts the variation of those responses under different short-circuit conditions.« less
Thermal modelling of Li-ion polymer battery for electric vehicle drive cycles
NASA Astrophysics Data System (ADS)
Chacko, Salvio; Chung, Yongmann M.
2012-09-01
Time-dependent, thermal behaviour of a lithium-ion (Li-ion) polymer cell has been modelled for electric vehicle (EV) drive cycles with a view to developing an effective battery thermal management system. The fully coupled, three-dimensional transient electro-thermal model has been implemented based on a finite volume method. To support the numerical study, a high energy density Li-ion polymer pouch cell was tested in a climatic chamber for electric load cycles consisting of various charge and discharge rates, and a good agreement was found between the model predictions and the experimental data. The cell-level thermal behaviour under stressful conditions such as high power draw and high ambient temperature was predicted with the model. A significant temperature increase was observed in the stressful condition, corresponding to a repeated acceleration and deceleration, indicating that an effective battery thermal management system would be required to maintain the optimal cell performance and also to achieve a full battery lifesapn.
Clustered carbohydrates as a target for natural killer cells: a model system.
Kovalenko, Elena I; Abakushina, Elena; Telford, William; Kapoor, Veena; Korchagina, Elena; Khaidukov, Sergei; Molotkovskaya, Irina; Sapozhnikov, Alexander; Vlaskin, Pavel; Bovin, Nicolai
2007-03-01
Membrane-associated oligosaccharides are known to take part in interactions between natural killer (NK) cells and their targets and modulate NK cell activity. A model system was therefore developed using synthetic glycoconjugates as tools to modify the carbohydrate pattern on NK target cell surfaces. NK cells were then assessed for function in response to synthetic glycoconjugates, using both cytolysis-associated caspase 6 activation measured by flow cytometry and IFN-gamma production. Lipophilic neoglycoconjugates were synthesized to provide their easy incorporation into the target cell membranes and to make carbohydrate residues available for cell-cell interactions. While incorporation was successful based on fluorescence monitoring, glycoconjugate incorporation did not evoke artifactual changes in surface antigen expression, and had no negative effect on cell viability. Glycoconjugates contained Le(x), sulfated Le(x), and Le(y) sharing the common structure motif trisaccharide Le(x) were revealed to enhance cytotoxicity mediated specifically by CD16 +CD56+NK cells. The glycoconjugate effects were dependent on saccharide presentation in a polymeric form. Only polymeric, or clustered, but not monomeric glycoconjugates resulted in alteration of cytotoxicity in our system, suggesting that appropriate presentation is critical for carbohydrate recognition and subsequent biological effects.
Mattern, Kai; Beißner, Nicole; Reichl, Stephan; Dietzel, Andreas
2018-05-01
Conventional safety and efficacy test models, such as animal experiments or static in vitro cell culture models, can often not reliably predict the most promising drug candidates. Therefore, a novel microfluidic cell culture platform, called Dynamic Micro Tissue Engineering System (DynaMiTES), was designed to allow online analysis of drugs permeating through barrier forming tissues under dynamic conditions combined with monitoring of the transepithelial electrical resistance (TEER) by electrodes optimized for homogeneous current distribution. A variety of pre-cultivated cell culture inserts can be integrated and exposed to well controlled dynamic micro flow conditions, resulting in a tightly regulated exposure of the cells to tested drugs, drug formulations and shear forces. With these qualities, the new system can provide more relevant information compared to static measurements. As a first in vitro model, a three-dimensional hemicornea construct consisting of human keratocytes (HCK-Ca) and epithelial cells (HCE-T) was successfully tested in the DynaMiTES. Thereby, we were able to demonstrate the functionality and cell compatibility of this new organ on chip test platform. The modular design of the DynaMiTES allows fast adaptation suitable for the investigation of drug permeation through other important cellular barriers. Copyright © 2017. Published by Elsevier B.V.
Piaseczny, Matthew M; Pio, Graciella M; Chu, Jenny E; Xia, Ying; Nguyen, Kim; Goodale, David; Allan, Alison
2016-06-13
Breast cancer preferentially metastasizes to the lymph node, bone, lung, brain and liver in breast cancer patients. Previous research efforts have focused on identifying factors inherent to breast cancer cells that are responsible for this observed metastatic pattern (termed organ tropism), however much less is known about factors present within specific organs that contribute to this process. This is in part because of a lack of in vitro model systems that accurately recapitulate the organ microenvironment. To address this, an ex vivo model system has been established that allows for the study of soluble factors present within different organ microenvironments. This model consists of generating conditioned media from organs (lymph node, bone, lung, and brain) isolated from normal athymic nude mice. The model system has been validated by demonstrating that different breast cancer cell lines display cell-line specific and organ-specific malignant behavior in response to organ-conditioned media that corresponds to their in vivo metastatic potential. This model system can be used to identify and evaluate specific organ-derived soluble factors that may play a role in the metastatic behavior of breast and other types of cancer cells, including influences on growth, migration, stem-like behavior, and gene expression, as well as the identification of potential new therapeutic targets for cancer. This is the first ex vivo model system that can be used to study organ-specific metastatic behavior in detail and evaluate the role of specific organ-derived soluble factors in driving the process of cancer metastasis.
McCann, Conor J.; Cooper, Julie E.; Natarajan, Dipa; Jevans, Benjamin; Burnett, Laura E.; Burns, Alan J.; Thapar, Nikhil
2017-01-01
Enteric nervous system neuropathy causes a wide range of severe gut motility disorders. Cell replacement of lost neurons using enteric neural stem cells (ENSC) is a possible therapy for these life-limiting disorders. Here we show rescue of gut motility after ENSC transplantation in a mouse model of human enteric neuropathy, the neuronal nitric oxide synthase (nNOS−/−) deficient mouse model, which displays slow transit in the colon. We further show that transplantation of ENSC into the colon rescues impaired colonic motility with formation of extensive networks of transplanted cells, including the development of nNOS+ neurons and subsequent restoration of nitrergic responses. Moreover, post-transplantation non-cell-autonomous mechanisms restore the numbers of interstitial cells of Cajal that are reduced in the nNOS−/− colon. These results provide the first direct evidence that ENSC transplantation can modulate the enteric neuromuscular syncytium to restore function, at the organ level, in a dysmotile gastrointestinal disease model. PMID:28671186
An Energy Model of Place Cell Network in Three Dimensional Space.
Wang, Yihong; Xu, Xuying; Wang, Rubin
2018-01-01
Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.
The relevance of human stem cell-derived organoid models for epithelial translational medicine
Hynds, Robert E.; Giangreco, Adam
2014-01-01
Epithelial organ remodeling is a major contributing factor to worldwide death and disease, costing healthcare systems billions of dollars every year. Despite this, most fundamental epithelial organ research fails to produce new therapies and mortality rates for epithelial organ diseases remain unacceptably high. In large part, this failure in translating basic epithelial research into clinical therapy is due to a lack of relevance in existing preclinical models. To correct this, new models are required that improve preclinical target identification, pharmacological lead validation, and compound optimization. In this review, we discuss the relevance of human stem cell-derived, three-dimensional organoid models for addressing each of these challenges. We highlight the advantages of stem cell-derived organoid models over existing culture systems, discuss recent advances in epithelial tissue-specific organoids, and present a paradigm for using organoid models in human translational medicine. PMID:23203919
Thermal modeling of the lithium/polymer battery
NASA Astrophysics Data System (ADS)
Pals, C. R.
1994-10-01
Research in the area of advanced batteries for electric-vehicle applications has increased steadily since the 1990 zero-emission-vehicle mandate of the California Air Resources Board. Due to their design flexibility and potentially high energy and power densities, lithium/polymer batteries are an emerging technology for electric-vehicle applications. Thermal modeling of lithium/polymer batteries is particularly important because the transport properties of the system depend exponentially on temperature. Two models have been presented for assessment of the thermal behavior of lithium/polymer batteries. The one-cell model predicts the cell potential, the concentration profiles, and the heat-generation rate during discharge. The cell-stack model predicts temperature profiles and heat transfer limitations of the battery. Due to the variation of ionic conductivity and salt diffusion coefficient with temperature, the performance of the lithium/polymer battery is greatly affected by temperature. Because of this variation, it is important to optimize the cell operating temperature and design a thermal management system for the battery. Since the thermal conductivity of the polymer electrolyte is very low, heat is not easily conducted in the direction perpendicular to cell layers. Temperature profiles in the cells are not as significant as expected because heat-generation rates in warmer areas of the cell stack are lower than heat-generation rates in cooler areas of the stack. This nonuniform heat-generation rate flattens the temperature profile. Temperature profiles as calculated by this model are not as steep as those calculated by previous models that assume a uniform heat-generation rate.
In vitro cell and tissue models for studying host-microbe interactions: a review.
Bermudez-Brito, Miriam; Plaza-Díaz, Julio; Fontana, Luis; Muñoz-Quezada, Sergio; Gil, Angel
2013-01-01
Ideally, cell models should resemble the in vivo conditions; however, in most in vitro experimental models, epithelial cells are cultivated as monolayers, in which the establishment of functional epithelial features is not achieved. To overcome this problem, co-culture experiments with probiotics, dendritic cells and intestinal epithelial cells and three-dimensional models attempt to reconcile the complex and dynamic interactions that exist in vivo between the intestinal epithelium and bacteria on the luminal side and between the epithelium and the underlying immune system on the basolateral side. Additional models include tissue explants, bioreactors and organoids. The present review details the in vitro models used to study host-microbe interactions and explores the new tools that may help in understanding the molecular mechanisms of these interactions.
Chiang, Michael; Hallman, Sam; Cinquin, Amanda; de Mochel, Nabora Reyes; Paz, Adrian; Kawauchi, Shimako; Calof, Anne L; Cho, Ken W; Fowlkes, Charless C; Cinquin, Olivier
2015-11-25
Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge. Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels. High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.
Modern Perspectives on Numerical Modeling of Cardiac Pacemaker Cell
Maltsev, Victor A.; Yaniv, Yael; Maltsev, Anna V.; Stern, Michael D.; Lakatta, Edward G.
2015-01-01
Cardiac pacemaking is a complex phenomenon that is still not completely understood. Together with experimental studies, numerical modeling has been traditionally used to acquire mechanistic insights in this research area. This review summarizes the present state of numerical modeling of the cardiac pacemaker, including approaches to resolve present paradoxes and controversies. Specifically we discuss the requirement for realistic modeling to consider symmetrical importance of both intracellular and cell membrane processes (within a recent “coupled-clock” theory). Promising future developments of the complex pacemaker system models include the introduction of local calcium control, mitochondria function, and biochemical regulation of protein phosphorylation and cAMP production. Modern numerical and theoretical methods such as multi-parameter sensitivity analyses within extended populations of models and bifurcation analyses are also important for the definition of the most realistic parameters that describe a robust, yet simultaneously flexible operation of the coupled-clock pacemaker cell system. The systems approach to exploring cardiac pacemaker function will guide development of new therapies, such as biological pacemakers for treating insufficient cardiac pacemaker function that becomes especially prevalent with advancing age. PMID:24748434
Design considerations for a 10-kW integrated hydrogen-oxygen regenerative fuel cell system
NASA Technical Reports Server (NTRS)
Hoberecht, M. A.; Miller, T. B.; Rieker, L. L.; Gonzalez-Sanabria, O. D.
1984-01-01
Integration of an alkaline fuel cell subsystem with an alkaline electrolysis subsystem to form a regenerative fuel cell (RFC) system for low earth orbit (LEO) applications characterized by relatively high overall round trip electrical efficiency, long life, and high reliability is possible with present state of the art technology. A hypothetical 10 kW system computer modeled and studied based on data from ongoing contractual efforts in both the alkaline fuel cell and alkaline water electrolysis areas. The alkaline fuel cell technology is under development utilizing advanced cell components and standard Shuttle Orbiter system hardware. The alkaline electrolysis technology uses a static water vapor feed technique and scaled up cell hardware is developed. The computer aided study of the performance, operating, and design parameters of the hypothetical system is addressed.
Persistent neural activity in head direction cells
NASA Technical Reports Server (NTRS)
Taube, Jeffrey S.; Bassett, Joshua P.; Oman, C. M. (Principal Investigator)
2003-01-01
Many neurons throughout the rat limbic system discharge in relation to the animal's directional heading with respect to its environment. These so-called head direction (HD) cells exhibit characteristics of persistent neural activity. This article summarizes where HD cells are found, their major properties, and some of the important experiments that have been conducted to elucidate how this signal is generated. The number of HD and angular head velocity cells was estimated for several brain areas involved in the generation of the HD signal, including the postsubiculum, anterior dorsal thalamus, lateral mammillary nuclei and dorsal tegmental nucleus. The HD cell signal has many features in common with what is known about how neural integration is accomplished in the oculomotor system. The nature of the HD cell signal makes it an attractive candidate for using neural network models to elucidate the signal's underlying mechanisms. The conditions that any network model must satisfy in order to accurately represent how the nervous system generates this signal are highlighted and areas where key information is missing are discussed.
Computational modeling of single-cell mechanics and cytoskeletal mechanobiology.
Rajagopal, Vijay; Holmes, William R; Lee, Peter Vee Sin
2018-03-01
Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state-of-the-art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed-forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.
Decentralized solar photovoltaic energy systems
NASA Astrophysics Data System (ADS)
Krupka, M. C.
1980-09-01
Emphasis was placed upon the selection and use of a model residential photovoltaic system to develop and quantify the necessary data. The model consists of a reference home located in Phoenix, AZ utilizing a unique solar cell array roof shingle combination. Silicon solar cells, rated at 13.5 percent efficiency at 28 C and 100 mW/sq cm insolation are used to generate 10 kW (peak). An all electric home is considered with lead acid battery storage, DC AC inversion and utility backup. The reference home is compared to others in regions of different insolation. It is suggested that solar cell materials production and fabrication may have the major environmental impact when comparing all facets of photovoltaic system usage. Fabrication of the various types of solar cell systems involves the need, handling, and transportation of many toxic and hazardous chemicals with attendant health and safety impacts. Increases in production of such materials as lead, antimony, sulfuric acid, copper, plastics, cadmium and gallium will be required should large scale usage of photovoltaic systems be implemented.
Influence of cell shape, inhomogeneities and diffusion barriers in cell polarization models
NASA Astrophysics Data System (ADS)
Giese, Wolfgang; Eigel, Martin; Westerheide, Sebastian; Engwer, Christian; Klipp, Edda
2015-12-01
In silico experiments bear the potential for further understanding of biological transport processes by allowing a systematic modification of any spatial property and providing immediate simulation results. Cell polarization and spatial reorganization of membrane proteins are fundamental for cell division, chemotaxis and morphogenesis. We chose the yeast Saccharomyces cerevisiae as an exemplary model system which entails the shuttling of small Rho GTPases such as Cdc42 and Rho, between an active membrane-bound form and an inactive cytosolic form. We used partial differential equations to describe the membrane-cytosol shuttling of proteins. In this study, a consistent extension of a class of 1D reaction-diffusion systems into higher space dimensions is suggested. The membrane is modeled as a thin layer to allow for lateral diffusion and the cytosol is modeled as an enclosed volume. Two well-known polarization mechanisms were considered. One shows the classical Turing-instability patterns, the other exhibits wave-pinning dynamics. For both models, we investigated how cell shape and diffusion barriers like septin structures or bud scars influence the formation of signaling molecule clusters and subsequent polarization. An extensive set of in silico experiments with different modeling hypotheses illustrated the dependence of cell polarization models on local membrane curvature, cell size and inhomogeneities on the membrane and in the cytosol. In particular, the results of our computer simulations suggested that for both mechanisms, local diffusion barriers on the membrane facilitate Rho GTPase aggregation, while diffusion barriers in the cytosol and cell protrusions limit spontaneous molecule aggregations of active Rho GTPase locally.
Label Structured Cell Proliferation Models
2010-06-16
and (, + ) are the cell proliferation and death rates , respectively, relative to the moving label coordinate system + . Daughter...proliferation and death rates relative to this new coordinate system. While not common in the biological sciences, it is altogether common in the physical
"A Cellular Encounter": Constructing the Cell as a Whole System Using Illustrative Models
ERIC Educational Resources Information Center
Cohen, Joel I.
2014-01-01
A standard part of biology curricula is a project-based assessment of cell structure and function. However, these are often individual assignments that promote little problem-solving or group learning and avoid the subject of organelle chemical interactions. I evaluate a model-based cell project designed to foster group and individual guided…
NASA Technical Reports Server (NTRS)
Evans, H. H.; DeMarini, D. M.
1999-01-01
Ionizing radiation was the first mutagen discovered and was used to develop the first mutagenicity assay. In the ensuing 70+ years, ionizing radiation became a fundamental tool in understanding mutagenesis and is still a subject of intensive research. Frederick de Serres et al. developed and used the Neurospora crassa ad-3 system initially to explore the mutagenic effects of ionizing radiation. Using this system, de Serres et al. demonstrated the dependence of the frequency and spectra of mutations induced by ionizing radiation on the dose, dose rate, radiation quality, repair capabilities of the cells, and the target gene employed. This work in Neurospora predicted the subsequent observations of the mutagenic effects of ionizing radiation in mammalian cells. Modeled originally on the mouse specific-locus system developed by William L. Russell, the N. crassa ad-3 system developed by de Serres has itself served as a model for interpreting the results in subsequent systems in mammalian cells. This review describes the primary findings on the nature of ionizing radiation-induced mutagenesis in the N. crassa ad-3 system and the parallel observations made years later in mammalian cells.
A Worldwide Competition to Compare the Speed and Chemotactic Accuracy of Neutrophil-Like Cells
Wong, Elisabeth; Hamza, Bashar; Bae, Albert; Martel, Joseph; Kataria, Rama; Keizer-Gunnink, Ineke; Kortholt, Arjan; Van Haastert, Peter J. M.; Charras, Guillaume; Janetopoulos, Christopher; Irimia, Daniel
2016-01-01
Chemotaxis is the ability to migrate towards the source of chemical gradients. It underlies the ability of neutrophils and other immune cells to hone in on their targets and defend against invading pathogens. Given the importance of neutrophil migration to health and disease, it is crucial to understand the basic mechanisms controlling chemotaxis so that strategies can be developed to modulate cell migration in clinical settings. Because of the complexity of human genetics, Dictyostelium and HL60 cells have long served as models system for studying chemotaxis. Since many of our current insights into chemotaxis have been gained from these two model systems, we decided to compare them side by side in a set of winner-take-all races, the Dicty World Races. These worldwide competitions challenge researchers to genetically engineer and pharmacologically enhance the model systems to compete in microfluidic racecourses. These races bring together technological innovations in genetic engineering and precision measurement of cell motility. Fourteen teams participated in the inaugural Dicty World Race 2014 and contributed cell lines, which they tuned for enhanced speed and chemotactic accuracy. The race enabled large-scale analyses of chemotaxis in complex environments and revealed an intriguing balance of speed and accuracy of the model cell lines. The successes of the first race validated the concept of using fun-spirited competition to gain insights into the complex mechanisms controlling chemotaxis, while the challenges of the first race will guide further technological development and planning of future events. PMID:27332963
Nardini, John T; Chapnick, Douglas A; Liu, Xuedong; Bortz, David M
2016-07-07
The in vitro migration of keratinocyte cell sheets displays behavioral and biochemical similarities to the in vivo wound healing response of keratinocytes in animal model systems. In both cases, ligand-dependent Epidermal Growth Factor Receptor (EGFR) activation is sufficient to elicit collective cell migration into the wound. Previous mathematical modeling studies of in vitro wound healing assays assume that physical connections between cells have a hindering effect on cell migration, but biological literature suggests a more complicated story. By combining mathematical modeling and experimental observations of collectively migrating sheets of keratinocytes, we investigate the role of cell-cell adhesion during in vitro keratinocyte wound healing assays. We develop and compare two nonlinear diffusion models of the wound healing process in which cell-cell adhesion either hinders or promotes migration. Both models can accurately fit the leading edge propagation of cell sheets during wound healing when using a time-dependent rate of cell-cell adhesion strength. The model that assumes a positive role of cell-cell adhesion on migration, however, is robust to changes in the leading edge definition and yields a qualitatively accurate density profile. Using RNAi for the critical adherens junction protein, α-catenin, we demonstrate that cell sheets with wild type cell-cell adhesion expression maintain migration into the wound longer than cell sheets with decreased cell-cell adhesion expression, which fails to exhibit collective migration. Our modeling and experimental data thus suggest that cell-cell adhesion promotes sustained migration as cells pull neighboring cells into the wound during wound healing. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cellular automata with object-oriented features for parallel molecular network modeling.
Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan
2005-06-01
Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.
Simulation system of arrhythmia using ActiveX control.
Takeuchi, Akihiro; Hirose, Minoru; Hamada, Atsushi; Ikeda, Noriaki
2005-07-01
A simulation system for arrhythmias has been developed using Windows-based software technology, ActiveX control. The cardiac module consists of six cells, the sinus, atrium, AV node, ventricle, and ectopic foci. The physiological properties of the cells, the automaticity and conduction delay, were modelled, respectively, by the phase response curve and the excitability recovery curve. Cell functions were implemented in the ActiveX control and incorporated into the cardiac module. The system draws the ECG sequence as a ladder diagram in real time. The system interactively shows diverse arrhythmias for various user settings of the cell function and bidirectional conduction between the cells. Users are able to experiment virtually by setting up a so-called electrophysiological stimulation. This system is useful for learning and for teaching the interaction between the cells and arrhythmias.
Warner, Kathrin; Crispatzu, Giuliano; Al-Ghaili, Nabil; Weit, Nicole; Florou, Vaia; You, M James; Newrzela, Sebastian; Herling, Marco
2013-12-01
Mature T-cell lymphomas/leukemias (MTCL) have been understudied lymphoid neoplasms that currently receive growing attention. Our historically rudimentary molecular understanding and dissatisfactory interventional success in this complex and for the most part poor-prognostic group of tumors is only slightly improving. A major limiting aspect in further progress in these rare neoplasms is the lack of suitable model systems that would substantially facilitate pathogenic studies and pre-clinical drug evaluations. Such representations of MTCL have thus far not been systematically appraised. We therefore provide an overview on existing models and point out their particular advantages and limitations in the context of the specific scientific questions. After addressing issues of species-specific differences and classifications, we summarize data on MTCL cell lines of human as well as murine origin, on murine strain predispositions to MTCL, on available models of genetically engineered mice, and on transplant systems. From an in-silico meta-analysis of available primary data of gene expression profiles on human MTCL we cross-reference genes reported to transform T-cells in mice and reflect on their general vs entity-restricted relevance and on target-promoter influences. Overall, we identify the urgent need for new models of higher fidelity to human MTCL with respect to their increasingly recognized diversity and to predictions of drug response. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Rezvanpanah, Elham; Ghaffarian Anbaran, S. Reza
2017-11-01
This study establishes a model and simulation scheme to describe the effect of crystallinity as one of the most effective parameters on cell growth phenomena in a solid batch foaming process. The governing model of cell growth dynamics, based on the well-known ‘Cell model’, is attained in details. To include the effect of crystallinity in the model, the properties of the polymer/gas mixtures (i.e. solubility, diffusivity, surface tension and viscosity) are estimated by modifying relations to consider the effect of crystallinity. A finite element-finite difference (FEFD) method is employed to solve the highly nonlinear and coupled equations of cell growth dynamics. The proposed simulation is able to evaluate all properties of the system at the given process condition and uses them to calculate the cell size, pressure and gas concentration gradient with time. A high-density polyethylene/nitrogen (HDPE/N2) system is used herein as a case study. Comparing the simulation results with the others works and experimental results verify the accuracy of the simulation scheme. The cell growth is a complicated combination of several phenomena. This study attempted to reach a better understanding of cell growth trend, driving and retarding forces and the effect of crystallinity on them.
Power-Law Modeling of Cancer Cell Fates Driven by Signaling Data to Reveal Drug Effects
Zhang, Fan; Wu, Min; Kwoh, Chee Keong; Zheng, Jie
2016-01-01
Extracellular signals are captured and transmitted by signaling proteins inside a cell. An important type of cellular responses to the signals is the cell fate decision, e.g., apoptosis. However, the underlying mechanisms of cell fate regulation are still unclear, thus comprehensive and detailed kinetic models are not yet available. Alternatively, data-driven models are promising to bridge signaling data with the phenotypic measurements of cell fates. The traditional linear model for data-driven modeling of signaling pathways has its limitations because it assumes that the a cell fate is proportional to the activities of signaling proteins, which is unlikely in the complex biological systems. Therefore, we propose a power-law model to relate the activities of all the measured signaling proteins to the probabilities of cell fates. In our experiments, we compared our nonlinear power-law model with the linear model on three cancer datasets with phosphoproteomics and cell fate measurements, which demonstrated that the nonlinear model has superior performance on cell fates prediction. By in silico simulation of virtual protein knock-down, the proposed model is able to reveal drug effects which can complement traditional approaches such as binding affinity analysis. Moreover, our model is able to capture cell line specific information to distinguish one cell line from another in cell fate prediction. Our results show that the power-law data-driven model is able to perform better in cell fate prediction and provide more insights into the signaling pathways for cancer cell fates than the linear model. PMID:27764199
The mathematical cell model reconstructed from interference microscopy data
NASA Astrophysics Data System (ADS)
Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.
2017-09-01
The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.
The CD8 T cell in multiple sclerosis: suppressor cell or mediator of neuropathology?
Johnson, Aaron J; Suidan, Georgette L; McDole, Jeremiah; Pirko, Istvan
2007-01-01
Multiple sclerosis (MS) is the most common human demyelinating disease of the central nervous system. It is universally accepted that the immune system plays a major role in the pathogenesis of MS. For decades, CD4 T cells have been considered the predominant mediator of neuropathology in MS. This perception was largely due to the similarity between MS and CD4 T-cell-driven experimental allergic encephalomyelitis, the most commonly studied murine model of MS. Over the last decade, several new observations in MS research imply an emerging role for CD8 T cells in neuropathogenesis. In certain experimental autoimmune encephalomyelitis (EAE) models, CD8 T cells are considered suppressors of pathology, whereas in other EAE models, neuropathology can be exacerbated by adoptive transfer of CD8 T cells. Studies using the Theiler's murine encephalomyelitis virus (TMEV) model have demonstrated preservation of motor function and axonal integrity in animals deficient in CD8 T cells or their effector molecules. CD8 T cells have also been demonstrated to be important regulators of blood-brain barrier permeability. There is also an emerging role for CD8 T cells in human MS. Human genetic studies reveal an important role for HLA class I molecules in MS susceptibility. In addition, neuropathologic studies demonstrate that CD8 T cells are the most numerous inflammatory infiltrate in MS lesions at all stages of lesion development. CD8 T cells are also capable of damaging neurons and axons in vitro. In this chapter, we discuss the neuropathologic, genetic, and experimental evidence for a critical role of CD8 T cells in the pathogenesis of MS and its most frequently studied animal models. We also highlight important new avenues for future research.
Stem cell transplantation as a dynamical system: are clinical outcomes deterministic?
Toor, Amir A; Kobulnicky, Jared D; Salman, Salman; Roberts, Catherine H; Jameson-Lee, Max; Meier, Jeremy; Scalora, Allison; Sheth, Nihar; Koparde, Vishal; Serrano, Myrna; Buck, Gregory A; Clark, William B; McCarty, John M; Chung, Harold M; Manjili, Masoud H; Sabo, Roy T; Neale, Michael C
2014-01-01
Outcomes in stem cell transplantation (SCT) are modeled using probability theory. However, the clinical course following SCT appears to demonstrate many characteristics of dynamical systems, especially when outcomes are considered in the context of immune reconstitution. Dynamical systems tend to evolve over time according to mathematically determined rules. Characteristically, the future states of the system are predicated on the states preceding them, and there is sensitivity to initial conditions. In SCT, the interaction between donor T cells and the recipient may be considered as such a system in which, graft source, conditioning, and early immunosuppression profoundly influence immune reconstitution over time. This eventually determines clinical outcomes, either the emergence of tolerance or the development of graft versus host disease. In this paper, parallels between SCT and dynamical systems are explored and a conceptual framework for developing mathematical models to understand disparate transplant outcomes is proposed.
Stem Cell Transplantation as a Dynamical System: Are Clinical Outcomes Deterministic?
Toor, Amir A.; Kobulnicky, Jared D.; Salman, Salman; Roberts, Catherine H.; Jameson-Lee, Max; Meier, Jeremy; Scalora, Allison; Sheth, Nihar; Koparde, Vishal; Serrano, Myrna; Buck, Gregory A.; Clark, William B.; McCarty, John M.; Chung, Harold M.; Manjili, Masoud H.; Sabo, Roy T.; Neale, Michael C.
2014-01-01
Outcomes in stem cell transplantation (SCT) are modeled using probability theory. However, the clinical course following SCT appears to demonstrate many characteristics of dynamical systems, especially when outcomes are considered in the context of immune reconstitution. Dynamical systems tend to evolve over time according to mathematically determined rules. Characteristically, the future states of the system are predicated on the states preceding them, and there is sensitivity to initial conditions. In SCT, the interaction between donor T cells and the recipient may be considered as such a system in which, graft source, conditioning, and early immunosuppression profoundly influence immune reconstitution over time. This eventually determines clinical outcomes, either the emergence of tolerance or the development of graft versus host disease. In this paper, parallels between SCT and dynamical systems are explored and a conceptual framework for developing mathematical models to understand disparate transplant outcomes is proposed. PMID:25520720
Hardware simulation of fuel cell/gas turbine hybrids
NASA Astrophysics Data System (ADS)
Smith, Thomas Paul
Hybrid solid oxide fuel cell/gas turbine (SOFC/GT) systems offer high efficiency power generation, but face numerous integration and operability challenges. This dissertation addresses the application of hardware-in-the-loop simulation (HILS) to explore the performance of a solid oxide fuel cell stack and gas turbine when combined into a hybrid system. Specifically, this project entailed developing and demonstrating a methodology for coupling a numerical SOFC subsystem model with a gas turbine that has been modified with supplemental process flow and control paths to mimic a hybrid system. This HILS approach was implemented with the U.S. Department of Energy Hybrid Performance Project (HyPer) located at the National Energy Technology Laboratory. By utilizing HILS the facility provides a cost effective and capable platform for characterizing the response of hybrid systems to dynamic variations in operating conditions. HILS of a hybrid system was accomplished by first interfacing a numerical model with operating gas turbine hardware. The real-time SOFC stack model responds to operating turbine flow conditions in order to predict the level of thermal effluent from the SOFC stack. This simulated level of heating then dynamically sets the turbine's "firing" rate to reflect the stack output heat rate. Second, a high-speed computer system with data acquisition capabilities was integrated with the existing controls and sensors of the turbine facility. In the future, this will allow for the utilization of high-fidelity fuel cell models that infer cell performance parameters while still computing the simulation in real-time. Once the integration of the numeric and the hardware simulation components was completed, HILS experiments were conducted to evaluate hybrid system performance. The testing identified non-intuitive transient responses arising from the large thermal capacitance of the stack that are inherent to hybrid systems. Furthermore, the tests demonstrated the capabilities of HILS as a research tool for investigating the dynamic behavior of SOFC/GT hybrid power generation systems.
Development of advanced fuel cell system, phase 2
NASA Technical Reports Server (NTRS)
Handley, L. M.; Meyer, A. P.; Bell, W. F.
1973-01-01
A multiple task research and development program was performed to improve the weight, life, and performance characteristics of hydrogen-oxygen alkaline fuel cells for advanced power systems. Development and characterization of a very stable gold alloy catalyst was continued from Phase I of the program. A polymer material for fabrication of cell structural components was identified and its long term compatibility with the fuel cell environment was demonstrated in cell tests. Full scale partial cell stacks, with advanced design closed cycle evaporative coolers, were tested. The characteristics demonstrated in these tests verified the feasibility of developing the engineering model system concept into an advanced lightweight long life powerplant.
Cheeseman, Bevan L.; Zhang, Dongcheng; Binder, Benjamin J.; Newgreen, Donald F.; Landman, Kerry A.
2014-01-01
Cell lineage tracing is a powerful tool for understanding how proliferation and differentiation of individual cells contribute to population behaviour. In the developing enteric nervous system (ENS), enteric neural crest (ENC) cells move and undergo massive population expansion by cell division within self-growing mesenchymal tissue. We show that single ENC cells labelled to follow clonality in the intestine reveal extraordinary and unpredictable variation in number and position of descendant cells, even though ENS development is highly predictable at the population level. We use an agent-based model to simulate ENC colonization and obtain agent lineage tracing data, which we analyse using econometric data analysis tools. In all realizations, a small proportion of identical initial agents accounts for a substantial proportion of the total final agent population. We term these individuals superstars. Their existence is consistent across individual realizations and is robust to changes in model parameters. This inequality of outcome is amplified at elevated proliferation rate. The experiments and model suggest that stochastic competition for resources is an important concept when understanding biological processes which feature high levels of cell proliferation. The results have implications for cell-fate processes in the ENS. PMID:24501272
Zuśka-Prot, Monika; Maślanka, Tomasz
2017-04-01
To achieve a better understanding of mechanisms underlying the anti-asthmatic action of inhaled and systemic glucocorticoids (GCs) and to provide more data regarding the risk of a negative effect of inhaled GCs on CD4 + T cells, a study was conducted on the effect of ciclesonide and methylprednisolone on CD4 + effector (Teff), regulatory (Treg) and resting (Trest) T cells within respiratory and extra-respiratory tissues in a mouse model of allergic asthma. The study indicated that one, and possibly a key mechanism, underlying the anti-asthmatic action of inhaled and systemic GCs is the prevention of the activation and clonal expansion of CD4 + Teff cells in the mediastinal lymph nodes (MLNs), which consequently prevents infiltration of the lungs with CD4 + Teff cells. The beneficial effects of GCs in asthma treatment were not mediated through increased recruitment of Treg cells into the MLNs and lungs and/or local generation of Treg cells. The results demonstrated that inhaled and systemic GCs induced comparable depletion of normal CD4 + Teff, Trest and Treg cells in the MLNs, head and neck lymph nodes and peripheral blood. Furthermore, inhaled, but not systemic GC therapy, led to the loss of these cells in the lungs. Thus, the study suggests that inhaled GC therapy may not be safer at all than systemic one with respect to the adverse effect on CD4 + T cells present within and outside the respiratory tract. Moreover, administration of inhaled GCs can produce negative effects on lung-residing CD4 + T cells. Copyright © 2017 Elsevier B.V. All rights reserved.
Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.
Schaff, James C; Gao, Fei; Li, Ye; Novak, Igor L; Slepchenko, Boris M
2016-12-01
Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.
Repair of Nerve Cell Membrane Damage by Calcium-Dependent, Membrane-Binding Proteins (Revised)
2012-09-01
protein, in model systems can promote a stable repair of broken membranes that could preserve cell viability. Preliminary data obtained using a novel...multilamellar liposomes prepared from bovine brain Folch Fraction I lipids (Sigma-Aldrich) and ion exchange chromatography on Poros Q medium using a Pharmacia...FPLC system [5]. Strategy for establishing the membrane leakage model The strategy employed in these studies was to encapsulate
Bouet, G; Cruel, M; Laurent, C; Vico, L; Malaval, L; Marchat, D
2015-05-15
An engineered three dimensional (3D) in vitro cell culture system was designed with the goal of inducing and controlling in vitro osteogenesis in a reproducible manner under conditions more similar to the in vivo bone microenvironment than traditional two-dimensional (2D) models. This bioreactor allows efficient mechanical loading and perfusion of an original cubic calcium phosphate bioceramic of highly controlled composition and structure. This bioceramic comprises an internal portion containing homogeneously interconnected macropores surrounded by a dense layer, which minimises fluid flow bypass around the scaffold. This dense and flat layer permits the application of a homogeneous loading on the bioceramic while also enhancing its mechanical strength. Numerical modelling of constraints shows that the system provides direct mechanical stimulation of cells within the scaffold. Experimental results establish that under perfusion at a steady flow of 2 µL/min, corresponding to 3 ≤ Medium velocity ≤ 23 µm/s, mouse calvarial cells grow and differentiate as osteoblasts in a reproducible manner, and lay down a mineralised matrix. Moreover, cells respond to mechanical loading by increasing C-fos expression, which demonstrates the effective mechanical stimulation of the culture within the scaffold. In summary, we provide a "proof-of-concept" for osteoblastic cell culture in a controlled 3D culture system under perfusion and mechanical loading. This model will be a tool to analyse bone cell functions in vivo, and will provide a bench testing system for the clinical assessment of bioactive bone-targeting molecules under load.
Reliability models applicable to space telescope solar array assembly system
NASA Technical Reports Server (NTRS)
Patil, S. A.
1986-01-01
A complex system may consist of a number of subsystems with several components in series, parallel, or combination of both series and parallel. In order to predict how well the system will perform, it is necessary to know the reliabilities of the subsystems and the reliability of the whole system. The objective of the present study is to develop mathematical models of the reliability which are applicable to complex systems. The models are determined by assuming k failures out of n components in a subsystem. By taking k = 1 and k = n, these models reduce to parallel and series models; hence, the models can be specialized to parallel, series combination systems. The models are developed by assuming the failure rates of the components as functions of time and as such, can be applied to processes with or without aging effects. The reliability models are further specialized to Space Telescope Solar Arrray (STSA) System. The STSA consists of 20 identical solar panel assemblies (SPA's). The reliabilities of the SPA's are determined by the reliabilities of solar cell strings, interconnects, and diodes. The estimates of the reliability of the system for one to five years are calculated by using the reliability estimates of solar cells and interconnects given n ESA documents. Aging effects in relation to breaks in interconnects are discussed.
Physiologically relevant organs on chips.
Yum, Kyungsuk; Hong, Soon Gweon; Healy, Kevin E; Lee, Luke P
2014-01-01
Recent advances in integrating microengineering and tissue engineering have generated promising microengineered physiological models for experimental medicine and pharmaceutical research. Here we review the recent development of microengineered physiological systems, or also known as "ogans-on-chips", that reconstitute the physiologically critical features of specific human tissues and organs and their interactions. This technology uses microengineering approaches to construct organ-specific microenvironments, reconstituting tissue structures, tissue-tissue interactions and interfaces, and dynamic mechanical and biochemical stimuli found in specific organs, to direct cells to assemble into functional tissues. We first discuss microengineering approaches to reproduce the key elements of physiologically important, dynamic mechanical microenvironments, biochemical microenvironments, and microarchitectures of specific tissues and organs in microfluidic cell culture systems. This is followed by examples of microengineered individual organ models that incorporate the key elements of physiological microenvironments into single microfluidic cell culture systems to reproduce organ-level functions. Finally, microengineered multiple organ systems that simulate multiple organ interactions to better represent human physiology, including human responses to drugs, is covered in this review. This emerging organs-on-chips technology has the potential to become an alternative to 2D and 3D cell culture and animal models for experimental medicine, human disease modeling, drug development, and toxicology. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bauer, Thomas R; Adler, Rima L; Hickstein, Dennis D
2009-01-01
Genetic mutations involving the cellular components of the hematopoietic system--red blood cells, white blood cells, and platelets--manifest clinically as anemia, infection, and bleeding. Although gene targeting has recapitulated many of these diseases in mice, these murine homologues are limited as translational models by their small size and brief life span as well as the fact that mutations induced by gene targeting do not always faithfully reflect the clinical manifestations of such mutations in humans. Many of these limitations can be overcome by identifying large animals with genetic diseases of the hematopoietic system corresponding to their human disease counterparts. In this article, we describe human diseases of the cellular components of the hematopoietic system that have counterparts in large animal species, in most cases carrying mutations in the same gene (CD18 in leukocyte adhesion deficiency) or genes in interacting proteins (DNA cross-link repair 1C protein and protein kinase, DNA-activated catalytic polypeptide in radiation-sensitive severe combined immunodeficiency). Furthermore, we describe the potential of these animal models to serve as disease-specific preclinical models for testing the efficacy and safety of clinical interventions such as hematopoietic stem cell transplantation or gene therapy before their use in humans with the corresponding disease.
COMPARISON OF MEDIUM CONCENTRATION VS. ACTUAL TISSUE DOSE IN IN VITRO NEUROTOXICANT MODELS.
In vitro methods have long been used to model the effects of toxicants on the nervous system. Generally, it is assumed that concentrations of toxicant present in the medium surrounding cells in in vitro models are an adequate biomarker of cell or tissue levels. However, this assu...
Flocking Transition in Confluent Tissues
NASA Astrophysics Data System (ADS)
Paoluzzi, Matteo; Giavazzi, Fabio; Macchi, Marta; Scita, Giorgio; Cerbino, Roberto; Manning, Lisa; Marchetti, Cristina
The emerging of collective migration in biological tissues plays a pivotal role in embryonic morphogenesis, wound healing and cancer invasion. While many aspects of single cell movements are well established, the mechanisms leading to coherent displacements of cohesive cell groups are still poorly understood. Some of us recently proposed a Self-Propelled Voronoi (SPV) model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers and exhibits a liquid-solid transition as a function of cell shape and cell motility. We now examine the role of cell polarization on collective cell dynamics by introducing an orientation mechanism that aligns cell polarization with local cell motility. The model predicts a density-independent flocking transition tuned by the strength of the aligning interaction, with both solid and liquid flocking states existing in different regions of parameter space. MP and MCM were supported by the Simons Foundation Targeted Grant in the Mathematical Modeling of Living Systems Number: 342354 and by the Syracuse Soft Matter Program.
Validation of in vitro assays in three-dimensional human dermal constructs.
Idrees, Ayesha; Chiono, Valeria; Ciardelli, Gianluca; Shah, Siegfried; Viebahn, Richard; Zhang, Xiang; Salber, Jochen
2018-05-01
Three-dimensional cell culture systems are urgently needed for cytocompatibility testing of biomaterials. This work aimed at the development of three-dimensional in vitro dermal skin models and their optimization for cytocompatibility evaluation. Initially "murine in vitro dermal construct" based on L929 cells was generated, leading to the development of "human in vitro dermal construct" consisting of normal human dermal fibroblasts in rat tail tendon collagen type I. To assess the viability of the cells, different assays CellTiter-Blue ® , RealTime-Glo ™ MT, and CellTiter-Glo ® (Promega) were evaluated to optimize the best-suited assay to the respective cell type and three-dimensional system. Z-stack imaging (Live/Dead and Phalloidin/DAPI-Promokine) was performed to visualize normal human dermal fibroblasts inside matrix revealing filopodia-like morphology and a uniform distribution of normal human dermal fibroblasts in matrix. CellTiter-Glo was found to be the optimal cell viability assay among those analyzed. CellTiter-Blue reagent affected the cell morphology of normal human dermal fibroblasts (unlike L929), suggesting an interference with cell biological activity, resulting in less reliable viability data. On the other hand, RealTime-Glo provided a linear signal only with a very low cell density, which made this assay unsuitable for this system. CellTiter-Glo adapted to three-dimensional dermal construct by optimizing the "shaking time" to enhance the reagent penetration and maximum adenosine triphosphate release, indicating 2.4 times higher viability value by shaking for 60 min than for 5 min. In addition, viability results showed that cells were viable inside the matrix. This model would be further advanced with more layers of skin to make a full thickness model.
Nanotechnology versus stem cell engineering: in vitro comparison of neurite inductive potentials.
Morano, Michela; Wrobel, Sandra; Fregnan, Federica; Ziv-Polat, Ofra; Shahar, Abraham; Ratzka, Andreas; Grothe, Claudia; Geuna, Stefano; Haastert-Talini, Kirsten
2014-01-01
Innovative nerve conduits for peripheral nerve reconstruction are needed in order to specifically support peripheral nerve regeneration (PNR) whenever nerve autotransplantation is not an option. Specific support of PNR could be achieved by neurotrophic factor delivery within the nerve conduits via nanotechnology or stem cell engineering and transplantation. Here, we comparatively investigated the bioactivity of selected neurotrophic factors conjugated to iron oxide nanoparticles (np-NTFs) and of bone marrow-derived stem cells genetically engineered to overexpress those neurotrophic factors (NTF-BMSCs). The neurite outgrowth inductive activity was monitored in culture systems of adult and neonatal rat sensory dorsal root ganglion neurons as well as in the cell line from rat pheochromocytoma (PC-12) cell sympathetic culture model system. We demonstrate that np-NTFs reliably support numeric neurite outgrowth in all utilized culture models. In some aspects, especially with regard to their long-term bioactivity, np-NTFs are even superior to free NTFs. Engineered NTF-BMSCs proved to be less effective in induction of sensory neurite outgrowth but demonstrated an increased bioactivity in the PC-12 cell culture system. In contrast, primary nontransfected BMSCs were as effective as np-NTFs in sensory neurite induction and demonstrated an impairment of neuronal differentiation in the PC-12 cell system. Our results evidence that nanotechnology as used in our setup is superior over stem cell engineering when it comes to in vitro models for PNR. Furthermore, np-NTFs can easily be suspended in regenerative hydrogel matrix and could be delivered that way to nerve conduits for future in vivo studies and medical application.
Combined dendritic cell cryotherapy of tumor induces systemic antimetastatic immunity.
Machlenkin, Arthur; Goldberger, Ofir; Tirosh, Boaz; Paz, Adrian; Volovitz, Ilan; Bar-Haim, Erez; Lee, Sung-Hyung; Vadai, Ezra; Tzehoval, Esther; Eisenbach, Lea
2005-07-01
Cryotherapy of localized prostate, renal, and hepatic primary tumors and metastases is considered a minimally invasive treatment demonstrating a low complication rate in comparison with conventional surgery. The main drawback of cryotherapy is that it has no systemic effect on distant metastases. We investigated whether intratumoral injections of dendritic cells following cryotherapy of local tumors (cryoimmunotherapy) provides an improved approach to cancer treatment, combining local tumor destruction and systemic anticancer immunity. The 3LL murine Lewis lung carcinoma clone D122 and the ovalbumin-transfected B16 melanoma clone MO5 served as models for spontaneous metastasis. The antimetastatic effect of cryoimmunotherapy was assessed in the lung carcinoma model by monitoring mouse survival, lung weight, and induction of tumor-specific CTLs. The mechanism of cryoimmunotherapy was elucidated in the melanoma model using adoptive transfer of T cell receptor transgenic OT-I CTLs into the tumor-bearing mice, and analysis of Th1/Th2 responses by intracellular cytokine staining in CD4 and CD8 cells. Cryoimmunotherapy caused robust and tumor-specific CTL responses, increased Th1 responses, significantly prolonged survival and dramatically reduced lung metastasis. Although intratumor administration of dendritic cells alone increased the proliferation rate of CD8 cells, only cryoimmunotherapy resulted in the generation of effector memory cells. Furthermore, cryoimmunotherapyprotected mice that had survived primary MO5 tumors from rechallenge with parental tumors. These results present cryoimmunotherapy as a novel approach for systemic treatment of cancer. We envisage that cryotherapy of tumors combined with subsequent in situ immunotherapy by autologous unmodified immature dendritic cells can be applied in practice.
Circuit transients due to negative bias arcs-II. [on solar cell power systems in low earth orbit
NASA Technical Reports Server (NTRS)
Metz, R. N.
1986-01-01
Two new models of negative-bias arcing on a solar cell power system in Low Earth Orbit are presented. One is an extended, analytical model and the other is a non-linear, numerical model. The models are based on an earlier analytical model in which the interactions between solar cell interconnects and the space plasma as well as the parameters of the power circuit are approximated linearly. Transient voltages due to arcs struck at the negative thermal of the solar panel are calculated in the time domain. The new models treat, respectively, further linear effects within the solar panel load circuit and non-linear effects associated with the plasma interactions. Results of computer calculations with the models show common-mode voltage transients of the electrically floating solar panel struck by an arc comparable to the early model but load transients that differ substantially from the early model. In particular, load transients of the non-linear model can be more than twice as great as those of the early model and more than twenty times as great as the extended, linear model.
Modeled Microgravity Inhibits Apoptosis in Peripheral Blood Lymphocytes
NASA Technical Reports Server (NTRS)
Risin, Diana; Pellis, Neal R.
2000-01-01
Microgravity interferes with numerous lymphocyte functions (expression of cell surface molecules, locomotion, polyclonal and antigen-specific activation, and the protein kinase C activity in signal transduction). The latter suggests that gravity may also affect programmed cell death (PCD) in lymphocyte populations. To test this hypothesis, we investigated spontaneous, activation- and radiation-induced PCD in peripheral blood mononuclear cells (PBMC) exposed to modeled microgravity using a rotating cell culture system. The results showed significant inhibition of radiation- and activation-induced apoptosis in modeled microgravity and provide insights into the potential mechanisms of this phenomenon.
Anelone, Anet J N; Spurgeon, Sarah K
2016-01-01
Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.
An non-uniformity voltage model for proton exchange membrane fuel cell
NASA Astrophysics Data System (ADS)
Li, Kelei; Li, Yankun; Liu, Jiawei; Guo, Ai
2017-01-01
The fuel cell used in transportation has environmental protection, high efficiency and no line traction power system which can greatly reduce line construction investment. That makes it a huge potential. The voltage uniformity is one of the most important factors affecting the operation life of proton exchange membrane fuel cell (PEMFC). On the basis of principle and classical model of the PEMFC, single cell voltage is calculated and the location coefficients are introduced so as to establish a non-uniformity voltage model. These coefficients are estimated with the experimental datum at stack current 50 A. The model is validated respectively with datum at 60 A and 100 A. The results show that the model reflects the basic characteristics of voltage non-uniformity and provides the beneficial reference for fuel cell control and single cell voltage detection.
Towards a visual modeling approach to designing microelectromechanical system transducers
NASA Astrophysics Data System (ADS)
Dewey, Allen; Srinivasan, Vijay; Icoz, Evrim
1999-12-01
In this paper, we address initial design capture and system conceptualization of microelectromechanical system transducers based on visual modeling and design. Visual modeling frames the task of generating hardware description language (analog and digital) component models in a manner similar to the task of generating software programming language applications. A structured topological design strategy is employed, whereby microelectromechanical foundry cell libraries are utilized to facilitate the design process of exploring candidate cells (topologies), varying key aspects of the transduction for each topology, and determining which topology best satisfies design requirements. Coupled-energy microelectromechanical system characterizations at a circuit level of abstraction are presented that are based on branch constitutive relations and an overall system of simultaneous differential and algebraic equations. The resulting design methodology is called visual integrated-microelectromechanical VHDL-AMS interactive design (VHDL-AMS is visual hardware design language for analog and mixed signal).
NASA Astrophysics Data System (ADS)
Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.
1997-02-01
In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.
Micro-tubular flame-assisted fuel cells for micro-combined heat and power systems
NASA Astrophysics Data System (ADS)
Milcarek, Ryan J.; Wang, Kang; Falkenstein-Smith, Ryan L.; Ahn, Jeongmin
2016-02-01
Currently the role of fuel cells in future power generation is being examined, tested and discussed. However, implementing systems is more difficult because of sealing challenges, slow start-up and complex thermal management and fuel processing. A novel furnace system with a flame-assisted fuel cell is proposed that combines the thermal management and fuel processing systems by utilizing fuel-rich combustion. In addition, the flame-assisted fuel cell furnace is a micro-combined heat and power system, which can produce electricity for homes or businesses, providing resilience during power disruption while still providing heat. A micro-tubular solid oxide fuel cell achieves a significant performance of 430 mW cm-2 operating in a model fuel-rich exhaust stream.
Biocellion: accelerating computer simulation of multicellular biological system models
Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya
2014-01-01
Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572
Kuijk, Ewart W.; Rasmussen, Shauna; Blokzijl, Francis; Huch, Meritxell; Gehart, Helmuth; Toonen, Pim; Begthel, Harry; Clevers, Hans; Geurts, Aron M.; Cuppen, Edwin
2016-01-01
The rat is an important model for liver regeneration. However, there is no in vitro culture system that can capture the massive proliferation that can be observed after partial hepatectomy in rats. We here describe the generation of rat liver stem cell lines. Rat liver stem cells, which grow as cystic organoids, were characterized by high expression of the stem cell marker Lgr5, by the expression of liver progenitor and duct markers, and by low expression of hepatocyte markers, oval cell markers, and stellate cell markers. Prolonged cultures of rat liver organoids depended on high levels of WNT-signalling and the inhibition of BMP-signaling. Upon transplantation of clonal lines to a Fah−/− Il2rg−/− rat model of liver failure, the rat liver stem cells engrafted into the host liver where they differentiated into areas with FAH and Albumin positive hepatocytes. Rat liver stem cell lines hold potential as consistent reliable cell sources for pharmacological, toxicological or metabolic studies. In addition, rat liver stem cell lines may contribute to the development of regenerative medicine in liver disease. To our knowledge, the here described liver stem cell lines represent the first organoid culture system in the rat. PMID:26915950
NASA Technical Reports Server (NTRS)
Parker, Peter A. (Inventor)
2003-01-01
A single vector calibration system is provided which facilitates the calibration of multi-axis load cells, including wind tunnel force balances. The single vector system provides the capability to calibrate a multi-axis load cell using a single directional load, for example loading solely in the gravitational direction. The system manipulates the load cell in three-dimensional space, while keeping the uni-directional calibration load aligned. The use of a single vector calibration load reduces the set-up time for the multi-axis load combinations needed to generate a complete calibration mathematical model. The system also reduces load application inaccuracies caused by the conventional requirement to generate multiple force vectors. The simplicity of the system reduces calibration time and cost, while simultaneously increasing calibration accuracy.
Low, Karen; Wong, Lauren Y; Maldonado, Maricela; Manjunath, Chetas; Horner, Christopher B; Perez, Mark; Myung, Nosang V; Nam, Jin
2017-05-09
Monitoring pluripotent stem cell behaviors (self-renewal and differentiation to specific lineages/phenotypes) is critical for a fundamental understanding of stem cell biology and their translational applications. In this study, a multi-modal stem cell monitoring system was developed to quantitatively characterize physico-electrochemical changes of the cells in real time, in relation to cellular activities during self-renewal or lineage-specific differentiation, in a non-destructive, label-free manner. The system was validated by measuring physical (mass) and electrochemical (impedance) changes in human induced pluripotent stem cells undergoing self-renewal, or subjected to mesendodermal or ectodermal differentiation, and correlating them to morphological (size, shape) and biochemical changes (gene/protein expression). An equivalent circuit model was used to further dissect the electrochemical (resistive and capacitive) contributions of distinctive cellular features. Overall, the combination of the physico-electrochemical measurements and electrical circuit modeling collectively offers a means to longitudinally quantify the states of stem cell self-renewal and differentiation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Thermal and optical performance of encapsulation systems for flat-plate photovoltaic modules
NASA Technical Reports Server (NTRS)
Minning, C. P.; Coakley, J. F.; Perrygo, C. M.; Garcia, A., III; Cuddihy, E. F.
1981-01-01
The electrical power output from a photovoltaic module is strongly influenced by the thermal and optical characteristics of the module encapsulation system. Described are the methodology and computer model for performing fast and accurate thermal and optical evaluations of different encapsulation systems. The computer model is used to evaluate cell temperature, solar energy transmittance through the encapsulation system, and electric power output for operation in a terrestrial environment. Extensive results are presented for both superstrate-module and substrate-module design schemes which include different types of silicon cell materials, pottants, and antireflection coatings.
Modeling and simulation of a direct ethanol fuel cell: An overview
NASA Astrophysics Data System (ADS)
Abdullah, S.; Kamarudin, S. K.; Hasran, U. A.; Masdar, M. S.; Daud, W. R. W.
2014-09-01
The commercialization of Direct Ethanol Fuel Cells (DEFCs) is still hindered because of economic and technical reasons. Fundamental scientific research is required to more completely understanding the complex electrochemical behavior and engineering technology of DEFCs. To use the DEFC system in real-world applications, fast, reliable, and cost-effective methods are needed to explore this complex phenomenon and to predict the performance of different system designs. Thus, modeling and simulation play an important role in examining the DEFC system as well as in designing an optimized DEFC system. The current DEFC literature shows that modeling studies on DEFCs are still in their early stages and are not able to describe the DEFC system as a whole. Potential DEFC applications and their current status are also presented.
NASA Astrophysics Data System (ADS)
De Domenico, Manlio
2018-03-01
Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.
Siggers, Keri A; Lesser, Cammie F
2008-07-17
Microbial pathogens utilize complex secretion systems to deliver proteins into host cells. These effector proteins target and usurp host cell processes to promote infection and cause disease. While secretion systems are conserved, each pathogen delivers its own unique set of effectors. The identification and characterization of these effector proteins has been difficult, often limited by the lack of detectable signal sequences and functional redundancy. Model systems including yeast, worms, flies, and fish are being used to circumvent these issues. This technical review details the versatility and utility of yeast Saccharomyces cerevisiae as a system to identify and characterize bacterial effectors.
Modeling cell adhesion and proliferation: a cellular-automata based approach.
Vivas, J; Garzón-Alvarado, D; Cerrolaza, M
Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.
Sun, Jie; Li, Qiu-Fen; Tian, Dai-Zhi; Jiang, Shao-Bo; Wu, Xian-De; Qiu, Shun-An; Ren, Xiao-Gang; Li, Yu-Bing
2014-09-01
To investigate the effects of Bushen Huoxue Fang (BSHX) on the apoptosis of epithelial cells in the prostatic ductal system of rats with benign prostatic hyperplasia (BPH) and its possible action mechanism. One hundred 3- month-old male Wistar rats were randomly divided into four groups of equal number (control, castrated, BPH model, and BSHX). BPH models were made by subcutaneous injection of testosterone following castration; the rats in the BSHX group were treated intragastrically with BSHX at 2.34 g/ml after modeling, while those in the other two groups with equal volume of saline, all for 37 days. On the 38th day, all the rats were sacrificed and their prostates harvested for detection of the distribution of TGF-beta1 and alpha-actin and the count of positive cells in the prostatic ductal system by immunohistochemical staining. The apoptosis rate of epithelial cells in the prostatic ductal system was determined by TUNEL assay. The expression of TGF-beta1 was significantly increased in the rats of the BSHX group as compared with the BPH models in both the proximal prostatic duct ([15.28 +/- 4.30]% vs [36.42 +/- 8.10]%, P < 0.01) and the distal prostatic duct ([4.42 +/- 2.07]% vs [8.71 +/- 2.28 ]%, P < 0.05), while the expression of alpha-actin in the proximal duct was remarkably higher in the BSHX-treated rats than in the models ([28.14 +/- 7.43]% vs [18.28 +/- 4.07]%, P < 0.01), but lower than in the control animals ([33.57 +/- 6.85]%, P < 0.05). Compared with the control group, the BPH models and BSHX-treated rats both exhibited markedly decreased apoptosis of epithelial cells in the proximal prostatic duct ([39.42 +/- 9.20]% vs [3.86 +/- 1.34]%, P < 0.01, and [31.14 +/- 5.64]%, P < 0.01) and distal prostatic duct ([17.60 +/- 4.86]% vs [3.07 +/- 1.14]%, P < 0.01, and [12.37 +/- 2.25]%, P < 0.05). The apoptosis rate of epithelial cells in the prostatic ductal system was significantly higher in the BSHX-treated rats than in the BPH models (P < 0.01). By upregulating the expression of TGF-beta, BSHX can suppress the reduction of smooth muscle cells in the proximal prostatic duct, promote the apoptosis of prostatic epithelial cells, and thus effectively inhibit benign prostatic hyperplasia.
Perfusion Stirred-Tank Bioreactors for 3D Differentiation of Human Neural Stem Cells.
Simão, Daniel; Arez, Francisca; Terasso, Ana P; Pinto, Catarina; Sousa, Marcos F Q; Brito, Catarina; Alves, Paula M
2016-01-01
Therapeutic breakthroughs in neurological disorders have been hampered by the lack of accurate central nervous system (CNS) models. The development of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of new therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmental, anatomic, and physiological) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity, etc.). Recapitulation of CNS phenotypic and functional features in vitro requires the implementation of advanced culture strategies, such as 3D culture systems, which enable to mimic the in vivo structural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. The development of robust and scalable processes for the 3D differentiation of hNSC can improve the accuracy of early stage development in preclinical research. In this context, the use of software-controlled stirred-tank bioreactors (STB) provides an efficient technological platform for hNSC aggregation and differentiation. This system enables to monitor and control important physicochemical parameters for hNSC culture, such as dissolved oxygen. Importantly, the adoption of a perfusion operation mode allows a stable flow of nutrients and differentiation/neurotrophic factors, while clearing the toxic by-products. This contributes to a setting closer to the physiological, by mimicking the in vivo microenvironment. In this chapter, we address the technical requirements and procedures for the implementation of 3D differentiation strategies of hNSC, by operating STB under perfusion mode for long-term cultures. This strategy is suitable for the generation of human 3D neural in vitro models, which can be used to feed high-throughput screening platforms, contributing to expand the available in vitro tools for drug screening and toxicological studies.
Establishment and quantitative imaging of a 3D lung organotypic model of mammary tumor outgrowth.
Martin, Michelle D; Fingleton, Barbara; Lynch, Conor C; Wells, Sam; McIntyre, J Oliver; Piston, David W; Matrisian, Lynn M
2008-01-01
The lung is the second most common site of metastatic spread in breast cancer and experimental evidence has been provided in many systems for the importance of an organ-specific microenvironment in the development of metastasis. To better understand the interaction between tumor and host cells in this important secondary site, we have developed a 3D in vitro organotypic model of breast tumor metastatic growth in the lung. In our model, cells isolated from mouse lungs are placed in a collagen sponge to serve as a scaffold and co-cultured with a green fluorescent protein-labeled polyoma virus middle T antigen (PyVT) mammary tumor cell line. Analysis of the co-culture system was performed using flow cytometry to determine the relative constitution of the co-cultures over time. This analysis determined that the cultures consisted of viable lung and breast cancer cells over a 5-day period. Confocal microscopy was then used to perform live cell imaging of the co-cultures over time. Our studies determined that host lung cells influence the ability of tumor cells to grow, as the presence of lung parenchyma positively affected the proliferation of the mammary tumor cells in culture. In summary, we have developed a novel in vitro model of breast tumor cells in a common metastatic site that can be used to study tumor/host interactions in an important microenvironment.
Human immune system mouse models of Ebola virus infection.
Spengler, Jessica R; Prescott, Joseph; Feldmann, Heinz; Spiropoulou, Christina F
2017-08-01
Human immune system (HIS) mice, immunodeficient mice engrafted with human cells (with or without donor-matched tissue), offer a unique opportunity to study pathogens that cause disease predominantly or exclusively in humans. Several HIS mouse models have recently been used to study Ebola virus (EBOV) infection and disease. The results of these studies are encouraging and support further development and use of these models in Ebola research. HIS mice provide a small animal model to study EBOV isolates, investigate early viral interactions with human immune cells, screen vaccines and therapeutics that modulate the immune system, and investigate sequelae in survivors. Here we review existing models, discuss their use in pathogenesis studies and therapeutic screening, and highlight considerations for study design and analysis. Finally, we point out caveats to current models, and recommend future efforts for modeling EBOV infection in HIS mice. Published by Elsevier B.V.
Chen, Ying; Zhou, Wenda; Roh, Terrence; Estes, Mary K; Kaplan, David L
2017-01-01
There is a need for functional in vitro 3D human intestine systems that can bridge the gap between conventional cell culture studies and human trials. The successful engineering in vitro of human intestinal tissues relies on the use of the appropriate cell sources, biomimetic scaffolds, and 3D culture conditions to support vital organ functions. We previously established a compartmentalized scaffold consisting of a hollow space within a porous bulk matrix, in which a functional and physiologically relevant intestinal epithelium system was generated using intestinal cell lines. In this study, we adopt the 3D scaffold system for the cultivation of stem cell-derived human small intestinal enteriods (HIEs) to engineer an in vitro 3D model of a nonstransformed human small intestinal epithelium. Characterization of tissue properties revealed a mature HIE-derived epithelium displaying four major terminally differentiated epithelial cell types (enterocytes, Goblet cells, Paneth cells, enteroendocrine cells), with tight junction formation, microvilli polarization, digestive enzyme secretion, and low oxygen tension in the lumen. Moreover, the tissue model demonstrates significant antibacterial responses to E. coli infection, as evidenced by the significant upregulation of genes involved in the innate immune response. Importantly, many of these genes are activated in human patients with inflammatory bowel disease (IBD), implicating the potential application of the 3D stem-cell derived epithelium for the in vitro study of host-microbe-pathogen interplay and IBD pathogenesis.
Fibroblasts Influence Survival and Therapeutic Response in a 3D Co-Culture Model
Majety, Meher; Pradel, Leon P.; Gies, Manuela; Ries, Carola H.
2015-01-01
In recent years, evidence has indicated that the tumor microenvironment (TME) plays a significant role in tumor progression. Fibroblasts represent an abundant cell population in the TME and produce several growth factors and cytokines. Fibroblasts generate a suitable niche for tumor cell survival and metastasis under the influence of interactions between fibroblasts and tumor cells. Investigating these interactions requires suitable experimental systems to understand the cross-talk involved. Most in vitro experimental systems use 2D cell culture and trans-well assays to study these interactions even though these paradigms poorly represent the tumor, in which direct cell-cell contacts in 3D spaces naturally occur. Investigating these interactions in vivo is of limited value due to problems regarding the challenges caused by the species-specificity of many molecules. Thus, it is essential to use in vitro models in which human fibroblasts are co-cultured with tumor cells to understand their interactions. Here, we developed a 3D co-culture model that enables direct cell-cell contacts between pancreatic, breast and or lung tumor cells and human fibroblasts/ or tumor-associated fibroblasts (TAFs). We found that co-culturing with fibroblasts/TAFs increases the proliferation in of several types of cancer cells. We also observed that co-culture induces differential expression of soluble factors in a cancer type-specific manner. Treatment with blocking antibodies against selected factors or their receptors resulted in the inhibition of cancer cell proliferation in the co-cultures. Using our co-culture model, we further revealed that TAFs can influence the response to therapeutic agents in vitro. We suggest that this model can be reliably used as a tool to investigate the interactions between a tumor and the TME. PMID:26053043
Cell differentiation modeled via a coupled two-switch regulatory network
NASA Astrophysics Data System (ADS)
Schittler, D.; Hasenauer, J.; Allgöwer, F.; Waldherr, S.
2010-12-01
Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.
Modelling the effect of GRP78 on anti-oestrogen sensitivity and resistance in breast cancer
Parmar, Jignesh H.; Cook, Katherine L.; Shajahan-Haq, Ayesha N.; Clarke, Pamela A. G.; Tavassoly, Iman; Clarke, Robert; Tyson, John J.; Baumann, William T.
2013-01-01
Understanding the origins of resistance to anti-oestrogen drugs is of critical importance to many breast cancer patients. Recent experiments show that knockdown of GRP78, a key gene in the unfolded protein response (UPR), can re-sensitize resistant cells to anti-oestrogens, and overexpression of GRP78 in sensitive cells can cause them to become resistant. These results appear to arise from the operation and interaction of three cellular systems: the UPR, autophagy and apoptosis. To determine whether our current mechanistic understanding of these systems is sufficient to explain the experimental results, we built a mathematical model of the three systems and their interactions. We show that the model is capable of reproducing previously published experimental results and some new data gathered specifically for this paper. The model provides us with a tool to better understand the interactions that bring about anti-oestrogen resistance and the effects of GRP78 on both sensitive and resistant breast cancer cells. PMID:24511377
Modeling our understanding of the His-Purkinje system.
Vigmond, Edward J; Stuyvers, Bruno D
2016-01-01
The His-Purkinje System (HPS) is responsible for the rapid electric conduction in the ventricles. It relays electrical impulses from the atrioventricular node to the muscle cells and, thus, coordinates the contraction of ventricles in order to ensure proper cardiac pump function. The HPS has been implicated in the genesis of ventricular tachycardia and fibrillation as a source of ectopic beats, as well as forming distinct portions of reentry circuitry. Despite its importance, it remains much less well characterized, structurally and functionally, than the myocardium. Notably, important differences exist with regard to cell structure and electrophysiology, including ion channels, intracellular calcium handling, and gap junctions. Very few computational models address the HPS, and the majority of organ level modeling studies omit it. This review will provide an overview of our current knowledge of structure and function (including electrophysiology) of the HPS. We will review the most recent advances in modeling of the system from the single cell to the organ level, with considerations for relevant interspecies distinctions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Analysis of electric and thermal behaviour of lithium-ion cells in realistic driving cycles
NASA Astrophysics Data System (ADS)
Tourani, Abbas; White, Peter; Ivey, Paul
2014-12-01
A substantial part of electric vehicles (EVs) powertrain is the battery cell. The cells are usually connected in series, and failure of a single cell can deactivate an entire module in the battery pack. Hence, understanding the cell behaviour helps to predict and improve the battery performance and leads to design a cost effective thermal management system for the battery pack. A first principle thermo electrochemical model is applied to study the cell behaviour. The model is in good agreement with the experimental results and can predict the heat generation and the temperature distribution across the cell for different operating conditions. The operating temperature effect on the cell performance is studied and the operating temperature for the best performance is verified. In addition, EV cells are examined in a realistic driving cycle from the Artemis class. The study findings lead to the proposal of some crucial recommendation to design cost effective thermal management systems for the battery pack.
Slack, RJ; Hall, DA
2012-01-01
BACKGROUND AND PURPOSE The operational model provides a key conceptual framework for the analysis of pharmacological data. However, this model does not include constitutive receptor activity, a frequent phenomenon in modern pharmacology, particularly in recombinant systems. Here, we developed extensions of the operational model which include constitutive activity and applied them to effects of agonists at the chemokine receptor CCR4. EXPERIMENTAL APPROACH The effects of agonists of CCR4 on [35S]GTPγS binding to recombinant cell membranes and on the filamentous (F-) actin content of human CD4+ CCR4+ T cells were determined. The basal [35S]GTPγS binding was changed by varying the GDP concentration whilst the basal F-actin contents of the higher expressing T cell populations were elevated, suggesting constitutive activity of CCR4. Both sets of data were analysed using the mathematical models. RESULTS The affinity of CCL17 (also known as TARC) derived from analysis of the T cell data (pKa= 9.61 ± 0.17) was consistent with radioligand binding experiments (9.50 ± 0.11) while that from the [35S]GTPγS binding experiments was lower (8.27 ± 0.09). Its intrinsic efficacy differed between the two systems (110 in T cells vs. 11). CONCLUSIONS AND IMPLICATIONS The presence of constitutive receptor activity allows the absolute intrinsic efficacy of agonists to be determined without a contribution from the signal transduction system. Intrinsic efficacy estimated in this way is consistent with Furchgott's definition of this property. CCL17 may have a higher intrinsic efficacy at CCR4 in human T cells than that expressed recombinantly in CHO cells. PMID:22335621
NASA Astrophysics Data System (ADS)
Beeri, Ofer; Rotem, Oded; Hazan, Eden; Katz, Eugene A.; Braun, Avi; Gelbstein, Yaniv
2015-09-01
An experimental demonstration of the combined photovoltaic (PV) and thermoelectric conversion of concentrated sunlight (with concentration factor, X, up to ˜300) into electricity is presented. The hybrid system is based on a multi-junction PV cell and a thermoelectric generator (TEG). The latter increases the electric power of the system and dissipates some of the excessive heat. For X ≤ 200, the system's maximal efficiency, ˜32%, was mostly due to the contribution from the PV cell. With increasing X and system temperature, the PV cell's efficiency decreased while that of the TEG increased. Accordingly, the direct electrical contribution of the TEG started to dominate in the total system power, reaching ˜20% at X ≈ 290. Using a simple steady state finite element modeling, the cooling effect of the TEG on the hybrid system's efficiency was proved to be even more significant than its direct electrical contribution for high solar concentrations. As a result, the total efficiency contribution of the TEG reached ˜40% at X ≈ 200. This suggests a new system optimization concept that takes into account the PV cell's temperature dependence and the trade-off between the direct electrical generation and cooling capabilities of the TEG. It is shown that the hybrid system has a real potential to exceed 50% total efficiency by using more advanced PV cells and TE materials.
Programmatic access to logical models in the Cell Collective modeling environment via a REST API.
Kowal, Bryan M; Schreier, Travis R; Dauer, Joseph T; Helikar, Tomáš
2016-01-01
Cell Collective (www.cellcollective.org) is a web-based interactive environment for constructing, simulating and analyzing logical models of biological systems. Herein, we present a Web service to access models, annotations, and simulation data in the Cell Collective platform through the Representational State Transfer (REST) Application Programming Interface (API). The REST API provides a convenient method for obtaining Cell Collective data through almost any programming language. To ensure easy processing of the retrieved data, the request output from the API is available in a standard JSON format. The Cell Collective REST API is freely available at http://thecellcollective.org/tccapi. All public models in Cell Collective are available through the REST API. For users interested in creating and accessing their own models through the REST API first need to create an account in Cell Collective (http://thecellcollective.org). thelikar2@unl.edu. Technical user documentation: https://goo.gl/U52GWo. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Mycoplasma pneumoniae, an Underutilized Model for Bacterial Cell Biology
2014-01-01
In recent decades, bacterial cell biology has seen great advances, and numerous model systems have been developed to study a wide variety of cellular processes, including cell division, motility, assembly of macromolecular structures, and biogenesis of cell polarity. Considerable attention has been given to these model organisms, which include Escherichia coli, Bacillus subtilis, Caulobacter crescentus, and Myxococcus xanthus. Studies of these processes in the pathogenic bacterium Mycoplasma pneumoniae and its close relatives have also been carried out on a smaller scale, but this work is often overlooked, in part due to this organism's reputation as minimalistic and simple. In this minireview, I discuss recent work on the role of the M. pneumoniae attachment organelle (AO), a structure required for adherence to host cells, in these processes. The AO is constructed from proteins that generally lack homology to those found in other organisms, and this construction occurs in coordination with cell cycle events. The proteins of the M. pneumoniae AO share compositional features with proteins with related roles in model organisms. Once constructed, the AO becomes activated for its role in a form of gliding motility whose underlying mechanism appears to be distinct from that of other gliding bacteria, including Mycoplasma mobile. Together with the FtsZ cytoskeletal protein, motility participates in the cell division process. My intention is to bring this deceptively complex organism into alignment with the better-known model systems. PMID:25157081
Microphysiological modeling of the reproductive tract: a fertile endeavor.
Eddie, Sharon L; Kim, J Julie; Woodruff, Teresa K; Burdette, Joanna E
2014-09-01
Preclinical toxicity testing in animal models is a cornerstone of the drug development process, yet it is often unable to predict adverse effects and tolerability issues in human subjects. Species-specific responses to investigational drugs have led researchers to utilize human tissues and cells to better estimate human toxicity. Unfortunately, human cell-derived models are imperfect because toxicity is assessed in isolation, removed from the normal physiologic microenvironment. Microphysiological modeling often referred to as 'organ-on-a-chip' or 'human-on-a-chip' places human tissue into a microfluidic system that mimics the complexity of human in vivo physiology, thereby allowing for toxicity testing on several cell types, tissues, and organs within a more biologically relevant environment. Here we describe important concepts when developing a repro-on-a-chip model. The development of female and male reproductive microfluidic systems is critical to sex-based in vitro toxicity and drug testing. This review addresses the biological and physiological aspects of the male and female reproductive systems in vivo and what should be considered when designing a microphysiological human-on-a-chip model. Additionally, interactions between the reproductive tract and other systems are explored, focusing on the impact of factors and hormones produced by the reproductive tract and disease pathophysiology. © 2014 by the Society for Experimental Biology and Medicine.
An experimental approach to identify dynamical models of transcriptional regulation in living cells
NASA Astrophysics Data System (ADS)
Fiore, G.; Menolascina, F.; di Bernardo, M.; di Bernardo, D.
2013-06-01
We describe an innovative experimental approach, and a proof of principle investigation, for the application of System Identification techniques to derive quantitative dynamical models of transcriptional regulation in living cells. Specifically, we constructed an experimental platform for System Identification based on a microfluidic device, a time-lapse microscope, and a set of automated syringes all controlled by a computer. The platform allows delivering a time-varying concentration of any molecule of interest to the cells trapped in the microfluidics device (input) and real-time monitoring of a fluorescent reporter protein (output) at a high sampling rate. We tested this platform on the GAL1 promoter in the yeast Saccharomyces cerevisiae driving expression of a green fluorescent protein (Gfp) fused to the GAL1 gene. We demonstrated that the System Identification platform enables accurate measurements of the input (sugars concentrations in the medium) and output (Gfp fluorescence intensity) signals, thus making it possible to apply System Identification techniques to obtain a quantitative dynamical model of the promoter. We explored and compared linear and nonlinear model structures in order to select the most appropriate to derive a quantitative model of the promoter dynamics. Our platform can be used to quickly obtain quantitative models of eukaryotic promoters, currently a complex and time-consuming process.
Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling.
Klanchui, Amornpan; Raethong, Nachon; Prommeenate, Peerada; Vongsangnak, Wanwipa; Meechai, Asawin
Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production.
NASA Astrophysics Data System (ADS)
Bao, Cheng; Cai, Ningsheng; Croiset, Eric
2011-10-01
Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.
Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.
Kurhekar, Manish; Deshpande, Umesh
2016-01-01
Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.
NASA Astrophysics Data System (ADS)
Le Floch, Francois; Harris, Wesley L.
2009-11-01
A novel methodology has been developed to address sickle cell disease, based on highly descriptive mathematical models for blood flow in the capillaries. Our investigations focus on the coupling between oxygen delivery and red blood cell dynamics, which is crucial to understanding sickle cell crises and is unique to this blood disease. The main part of our work is an extensive study of blood dynamics through simulations of red cells deforming within the capillary vessels, and relies on the use of a large mathematical system of equations describing oxygen transfer, blood plasma dynamics and red cell membrane mechanics. This model is expected to lead to the development of new research strategies for sickle cell disease. Our simulation model could be used not only to assess current researched remedies, but also to spur innovative research initiatives, based on our study of the physical properties coupled in sickle cell disease.
Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Khasanov, A A; Musaeva, Sh N; Saatov, T S
2012-04-01
The article deals with the results of computational experiments in research of dynamics of proliferation of cells of thyroid gland follicle in normal condition and in the case of malignant neoplasm. The model studies demonstrated that the chronic increase of parameter of proliferation of cells of thyroid gland follicle results in abnormal behavior of numbers of cell cenosis of thyroid gland follicle. The stationary state interrupts, the auto-oscillations occur with transition to irregular oscillations with unpredictable cell proliferation and further to the "black hole" effect. It is demonstrated that the present medical biologic experimental data and theory propositions concerning the structural functional organization of thyroid gland on cell level permit to develop mathematical models for quantitative analysis of numbers of cell cenosis of thyroid gland follicle in normal conditions. The technique of modeling of regulative mechanisms of living systems and equations of cell cenosis regulations was used
Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain
2017-07-01
If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.
Dani, Sergio U; Espindola, Rachel
2002-06-30
We developed a model system for testing gene vectors, based on the growth of murine tumors on the chorioallantoic membrane (CAM) of embryonic chickens. The ability of selected murine cells to grow on the CAM was rated according to the following criteria: i) formation of tumor masses; ii) metastasis formation; iii) reproducibility; iv) yield, indicated as the number of embryos surviving to assessment time with visible tumors on the CAM; v) maintainability of the cell, both in the original host and the embryonic chick, or 'shuttle maintainability'; vi) detection by the naked eye, and vii) cost/benefit relation. The murine melanoma cell lineage, B16F10, which efficiently forms distinct, pigmented tumor masses and metastases on the CAM, performed better in this model than the murine B61 cell line. In vitro transduction of B16F10 cells with a recombinant adenovirus carrying a construct of the E. coli LacZ gene followed by inoculation onto the CAM resulted in beta-galactosidase expression in the tumor mass growing on the CAM. This model is potentially applicable to preclinical evaluation of gene vectors, especially for gene therapy of cancer.
System Design, Implementation, and Evaluation of the Optical Broadband Correlator
1994-09-20
shear-mode TeO2 , Model No. N45075-6-20, manufactured by Newport Electro- Optic Systems with a length of 75 pjs, acoustic direction 1110], optical...optical aperture (or useful length) TOA of our cells are shown in Table 3. The Bragg cells are shear-mode TeO2 , Model No. N45075-6-20, manufactured by...focusing or integrating (Fourier transform) lens is a laser diode glass doublet Model 06LAI013/076, from Melles Griot. Its focal length is 145 nun at 830
NASA Astrophysics Data System (ADS)
Lapin, Alexei; Klann, Michael; Reuss, Matthias
Agent-based models are rigorous tools for simulating the interactions of individual entities, such as organisms or molecules within cells and assessing their effects on the dynamic behavior of the system as a whole. In context with bioprocess and biosystems engineering there are several interesting and important applications. This contribution aims at introducing this strategy with the aid of two examples characterized by striking distinctions in the scale of the individual entities and the mode of their interactions. In the first example a structured-segregated model is applied to travel along the lifelines of single cells in the environment of a three-dimensional turbulent field of a stirred bioreactor. The modeling approach is based on an Euler-Lagrange formulation of the system. The strategy permits one to account for the heterogeneity present in real reactors in both the fluid and cellular phases, respectively. The individual response of the cells to local variations in the extracellular concentrations is pictured by a dynamically structured model of the key reactions of the central metabolism. The approach permits analysis of the lifelines of individual cells in space and time.
Ghatreh-Samani, Mahdi; Esmaeili, Nafiseh; Soleimani, Masoud; Asadi-Samani, Majid; Ghatreh-Samani, Keihan; Shirzad, Hedayatolah
2016-01-01
Iron overload in β-thalassemia major occurs mainly due to blood transfusion, an essential treatment for β-thalassemia major patients, which results in oxidative stress. It has been thought that oxidative stress causes elevation of immune system senescent cells. Under this condition, cells normally enhance in aging, which is referred to as premature immunosenescence. Because there is no animal model for immunosenescence, most knowledge on the immunosenescence pattern is based on induction of immunosenescence. In this review, we describe iron overload and oxidative stress in β-thalassemia major patients and how they make these patients a suitable human model for immunosenescence. We also consider oxidative stress in some kinds of chronic virus infections, which induce changes in the immune system similar to β-thalassemia major. In conclusion, a therapeutic approach used to improve the immune system in such chronic virus diseases, may change the immunosenescence state and make life conditions better for β-thalassemia major patients.
Ghatreh-Samani, Mahdi; Esmaeili, Nafiseh; Soleimani, Masoud; Asadi-Samani, Majid; Ghatreh-Samani, Keihan
2016-01-01
Iron overload in β-thalassemia major occurs mainly due to blood transfusion, an essential treatment for β-thalassemia major patients, which results in oxidative stress. It has been thought that oxidative stress causes elevation of immune system senescent cells. Under this condition, cells normally enhance in aging, which is referred to as premature immunosenescence. Because there is no animal model for immunosenescence, most knowledge on the immunosenescence pattern is based on induction of immunosenescence. In this review, we describe iron overload and oxidative stress in β-thalassemia major patients and how they make these patients a suitable human model for immunosenescence. We also consider oxidative stress in some kinds of chronic virus infections, which induce changes in the immune system similar to β-thalassemia major. In conclusion, a therapeutic approach used to improve the immune system in such chronic virus diseases, may change the immunosenescence state and make life conditions better for β-thalassemia major patients. PMID:27095931
Chudasama, Vaishali L.; Ovacik, Meric A.; Abernethy, Darrell R.
2015-01-01
Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. PMID:26163548
User Guide and Documentation for Five MODFLOW Ground-Water Modeling Utility Programs
Banta, Edward R.; Paschke, Suzanne S.; Litke, David W.
2008-01-01
This report documents five utility programs designed for use in conjunction with ground-water flow models developed with the U.S. Geological Survey's MODFLOW ground-water modeling program. One program extracts calculated flow values from one model for use as input to another model. The other four programs extract model input or output arrays from one model and make them available in a form that can be used to generate an ArcGIS raster data set. The resulting raster data sets may be useful for visual display of the data or for further geographic data processing. The utility program GRID2GRIDFLOW reads a MODFLOW binary output file of cell-by-cell flow terms for one (source) model grid and converts the flow values to input flow values for a different (target) model grid. The spatial and temporal discretization of the two models may differ. The four other utilities extract selected 2-dimensional data arrays in MODFLOW input and output files and write them to text files that can be imported into an ArcGIS geographic information system raster format. These four utilities require that the model cells be square and aligned with the projected coordinate system in which the model grid is defined. The four raster-conversion utilities are * CBC2RASTER, which extracts selected stress-package flow data from a MODFLOW binary output file of cell-by-cell flows; * DIS2RASTER, which extracts cell-elevation data from a MODFLOW Discretization file; * MFBIN2RASTER, which extracts array data from a MODFLOW binary output file of head or drawdown; and * MULT2RASTER, which extracts array data from a MODFLOW Multiplier file.
Singh, Aman P; Maass, Katie F; Betts, Alison M; Wittrup, K Dane; Kulkarni, Chethana; King, Lindsay E; Khot, Antari; Shah, Dhaval K
2016-07-01
A mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.
A single-cell spiking model for the origin of grid-cell patterns
Kempter, Richard
2017-01-01
Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity. PMID:28968386
Modeling human diseases with induced pluripotent stem cells: from 2D to 3D and beyond.
Liu, Chun; Oikonomopoulos, Angelos; Sayed, Nazish; Wu, Joseph C
2018-03-08
The advent of human induced pluripotent stem cells (iPSCs) presents unprecedented opportunities to model human diseases. Differentiated cells derived from iPSCs in two-dimensional (2D) monolayers have proven to be a relatively simple tool for exploring disease pathogenesis and underlying mechanisms. In this Spotlight article, we discuss the progress and limitations of the current 2D iPSC disease-modeling platform, as well as recent advancements in the development of human iPSC models that mimic in vivo tissues and organs at the three-dimensional (3D) level. Recent bioengineering approaches have begun to combine different 3D organoid types into a single '4D multi-organ system'. We summarize the advantages of this approach and speculate on the future role of 4D multi-organ systems in human disease modeling. © 2018. Published by The Company of Biologists Ltd.
Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential
Kaneko, Kunihiko
2011-01-01
The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296
Gravity Research on Plants: Use of Single-Cell Experimental Models
Chebli, Youssef; Geitmann, Anja
2011-01-01
Future space missions and implementation of permanent bases on Moon and Mars will greatly depend on the availability of ambient air and sustainable food supply. Therefore, understanding the effects of altered gravity conditions on plant metabolism and growth is vital for space missions and extra-terrestrial human existence. In this mini-review we summarize how plant cells are thought to perceive changes in magnitude and orientation of the gravity vector. The particular advantages of several single-celled model systems for gravity research are explored and an overview over recent advancements and potential use of these systems is provided. PMID:22639598
Guo, Xiufang; Das, Mainak; Rumsey, John; Gonzalez, Mercedes; Stancescu, Maria; Hickman, James
2010-12-01
To date, the coculture of motoneurons (MNs) and skeletal muscle in a defined in vitro system has only been described in one study and that was between rat MNs and rat skeletal muscle. No in vitro studies have demonstrated human MN to rat muscle synapse formation, although numerous studies have attempted to implant human stem cells into rat models to determine if they could be of therapeutic use in disease or spinal injury models, although with little evidence of neuromuscular junction (NMJ) formation. In this report, MNs differentiated from human spinal cord stem cells, together with rat skeletal myotubes, were used to build a coculture system to demonstrate that NMJ formation between human MNs and rat skeletal muscles is possible. The culture was characterized by morphology, immunocytochemistry, and electrophysiology, while NMJ formation was demonstrated by immunocytochemistry and videography. This defined system provides a highly controlled reproducible model for studying the formation, regulation, maintenance, and repair of NMJs. The in vitro coculture system developed here will be an important model system to study NMJ development, the physiological and functional mechanism of synaptic transmission, and NMJ- or synapse-related disorders such as amyotrophic lateral sclerosis, as well as for drug screening and therapy design.
Efremova, Liudmila; Schildknecht, Stefan; Adam, Martina; Pape, Regina; Gutbier, Simon; Hanf, Benjamin; Bürkle, Alexander; Leist, Marcel
2015-01-01
Background and Purpose Few neuropharmacological model systems use human neurons. Moreover, available test systems rarely reflect functional roles of co-cultured glial cells. There is no human in vitro counterpart of the widely used 1-methyl-4-phenyl-tetrahydropyridine (MPTP) mouse model of Parkinson's disease Experimental Approach We generated such a model by growing an intricate network of human dopaminergic neurons on a dense layer of astrocytes. In these co-cultures, MPTP was metabolized to 1-methyl-4-phenyl-pyridinium (MPP+) by the glial cells, and the toxic metabolite was taken up through the dopamine transporter into neurons. Cell viability was measured biochemically and by quantitative neurite imaging, siRNA techniques were also used. Key Results We initially characterized the activation of PARP. As in mouse models, MPTP exposure induced (poly-ADP-ribose) synthesis and neurodegeneration was blocked by PARP inhibitors. Several different putative neuroprotectants were then compared in mono-cultures and co-cultures. Rho kinase inhibitors worked in both models; CEP1347, ascorbic acid or a caspase inhibitor protected mono-cultures from MPP+ toxicity, but did not protect co-cultures, when used alone or in combination. Application of GSSG prevented degeneration in co-cultures, but not in mono-cultures. The surprisingly different pharmacological profiles of the models suggest that the presence of glial cells, and the in situ generation of the toxic metabolite MPP+ within the layered cultures played an important role in neuroprotection. Conclusions and Implications Our new model system is a closer model of human brain tissue than conventional cultures. Its use for screening of candidate neuroprotectants may increase the predictiveness of a test battery. PMID:25989025
Tetsuka, Kazuhiro; Ohbuchi, Masato; Tabata, Kenji
2017-09-01
Tissue engineering technology has provided many useful culture models. This article reviews the merits of this technology in a hepatocyte culture system and describes the applications of the sandwich-cultured hepatocyte model in drug discovery. In addition, we also review recent investigations of the utility of the 3-dimensional bioprinted human liver tissue model and spheroid model. Finally, we present the future direction and developmental challenges of a hepatocyte culture model for the successful establishment of a microphysiological system, represented as an organ-on-a-chip and even as a human-on-a-chip. A merit of advanced culture models is their potential use for detecting hepatotoxicity through repeated exposure to chemicals as they allow long-term culture while maintaining hepatocyte functionality. As a future direction, such advanced hepatocyte culture systems can be connected to other tissue models for evaluating tissue-to-tissue interaction beyond cell-to-cell interaction. This combination of culture models could represent parts of the human body in a microphysiological system. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Nagasaka, Yuriko; Tanaka, Shinpei; Nehira, Tatsuo; Amimoto, Tomoko
2017-09-27
It is well known that oil droplets in or on water exhibit spontaneous movement induced by surfactants, and this self-propulsion is regarded as an important factor in droplet-based models for a living cell. We report here an oil-droplet system spontaneously producing amino acid-based surfactants, which are then utilized for the droplets' self-propulsion. Thus this system is an active system capable of producing the fuel for the propulsion by itself, which can be used as a conceptual model for cell metabolism.
Nagai, Takayuki; Ikegami, Yasuhiro; Mizumachi, Hideyuki; Shirakigawa, Nana; Ijima, Hiroyuki
2017-10-01
Two-dimensional monolayer culture is the most popular cell culture method. However, the cells may not respond as they do in vivo because the culture conditions are different from in vivo conditions. However, hydrogel-embedding culture, which cultures cells in a biocompatible culture substrate, can produce in vivo-like cell responses, but in situ evaluation of cells in a gel is difficult. In this study, we realized an in vivo-like environment in vitro to produce cell responses similar to those in vivo and established an in situ evaluation system for hydrogel-embedded cell responses. The extracellular matrix (ECM)-modeled gel consisted of collagen and heparin (Hep-col) to mimic an in vivo-like environment. The Hep-col gel could immobilize growth factors, which is important for ECM functions. Neural stem/progenitor cells cultured in the Hep-col gel grew and differentiated more actively than in collagen, indicating an in vivo-like environment in the Hep-col gel. Second, a thin-layered gel culture system was developed to realize in situ evaluation of the gel-embedded cells. Cells in a 200-μm-thick gel could be evaluated clearly by a phase-contrast microscope and immunofluorescence staining through reduced optical and diffusional effects. Finally, we found that the neural cells cultured in this system had synaptic connections and neuronal action potentials by immunofluorescence staining and Ca 2+ imaging. In conclusion, this culture method may be a valuable evaluation system for neurotoxicity testing. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
Glial cell migration in the eye disc.
Silies, Marion; Yuva, Yeliz; Engelen, Daniel; Aho, Annukka; Stork, Tobias; Klämbt, Christian
2007-11-28
Any complex nervous system is made out of two major cell types, neurons and glial cells. A hallmark of glial cells is their pronounced ability to migrate. En route to their final destinations, glial cells are generally guided by neuronal signals. Here we show that in the developing visual system of Drosophila glial cell migration is largely controlled by glial-glial interactions and occurs independently of axonal contact. Differentiation into wrapping glia is initiated close to the morphogenetic furrow. Using single cell labeling experiments we identified six distinct glial cell types in the eye disc. The migratory glial population is separated from the wrapping glial cells by the so-called carpet cells, extraordinary large glial cells, each covering a surface area of approximately 10,000 epithelial cells. Subsequent cell ablation experiments demonstrate that the carpet glia regulates glial migration in the eye disc epithelium and suggest a new model underlying glial migration and differentiation in the developing visual system.
NASA Astrophysics Data System (ADS)
Joos, Stella; Weißhar, Björn; Bessler, Wolfgang G.
2017-04-01
Standard photovoltaic battery systems based on AC or DC architectures require power electronics and controllers, including inverters, MPP tracker, and battery charger. Here we investigate an alternative system design based on the parallel connection of a photovoltaic module with battery cells without any intermediate voltage conversion. This approach, for which we use the term passive hybridization, is based on matching the solar cell's and battery cell's respective current/voltage behavior. A battery with flat discharge characteristics can allow to pin the solar cell to its maximum power point (MPP) independently of the external power consumption. At the same time, upon battery full charge, voltage increase will drive the solar cell towards zero current and therefore self-prevent battery overcharge. We present a modeling and simulation analysis of passively hybridizing a 5 kWp PV system with a 5 kWh LFP/graphite lithium-ion battery. Dynamic simulations with 1-min time resolution are carried out for three exemplary summer and winter days using historic weather data and a synthetic single-family household consumer profile. The results demonstrate the feasibility of the system. The passive hybrid allows for high self-sufficiencies of 84.6% in summer and 25.3% in winter, which are only slightly lower than those of a standard system.
NASA Astrophysics Data System (ADS)
Bernadowski, Timothy Adam, Jr.
Carbon dioxide in the Martian atmosphere can be converted to oxygen during high temperature electrolysis for use in life-support and fuel systems on manned missions to the red planet. During electrolysis of carbon dioxide to produce oxygen, carbon can deposit on the electrolysis cell resulting in lower efficiency and possibly cell damage. This would be detrimental, especially when the oxygen product is used as the key element of a space life support system. In this thesis, a theoretical model was developed to predict hazardous carbon deposition conditions under various operating conditions within the Martian atmosphere. The model can be used as a guide to determine the ideal operating conditions of the high-temperature oxygen production system. A parallel experimental investigation is underway to evaluate the accuracy of the theoretical model. The experimental design, cell fabrication, and some preliminary results as well as future work recommendations are also presented in this thesis.
Molecular Mechanisms of Radiation-Induced Genomic Instability in Human Cells
DOE Office of Scientific and Technical Information (OSTI.GOV)
Howard L. Liber; Jeffrey L. Schwartz
2005-10-31
There are many different model systems that have been used to study chromosome instability. What is clear from all these studies is that conclusions concerning chromosome instability depend greatly on the model system and instability endpoint that is studied. The model system for our studies was the human B-lymphoblastoid cell line TK6. TK6 was isolated from a spontaneously immortalized lymphoblast culture. Thus there was no outside genetic manipulation used to immortalize them. TK6 is a relatively stable p53-normal immortal cell line (37). It shows low gene and chromosome mutation frequencies (19;28;31). Our general approach to studying instability in TK6 cellsmore » has been to isolate individual clones and analyze gene and chromosome mutation frequencies in each. This approach maximizes the possibility of detecting low frequency events that might be selected against in mass cultures.« less
Interdisciplinary Team Science in Cell Biology.
Horwitz, Rick
2016-11-01
The cell is complex. With its multitude of components, spatial-temporal character, and gene expression diversity, it is challenging to comprehend the cell as an integrated system and to develop models that predict its behaviors. I suggest an approach to address this issue, involving system level data analysis, large scale team science, and philanthropy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Software Engineering Tools for Scientific Models
NASA Technical Reports Server (NTRS)
Abrams, Marc; Saboo, Pallabi; Sonsini, Mike
2013-01-01
Software tools were constructed to address issues the NASA Fortran development community faces, and they were tested on real models currently in use at NASA. These proof-of-concept tools address the High-End Computing Program and the Modeling, Analysis, and Prediction Program. Two examples are the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) atmospheric model in Cell Fortran on the Cell Broadband Engine, and the Goddard Institute for Space Studies (GISS) coupled atmosphere- ocean model called ModelE, written in fixed format Fortran.
Andersen, Morten; Sajid, Zamra; Pedersen, Rasmus K; Gudmand-Hoeyer, Johanne; Ellervik, Christina; Skov, Vibe; Kjær, Lasse; Pallisgaard, Niels; Kruse, Torben A; Thomassen, Mads; Troelsen, Jesper; Hasselbalch, Hans Carl; Ottesen, Johnny T
2017-01-01
The chronic Philadelphia-negative myeloproliferative neoplasms (MPNs) are acquired stem cell neoplasms which ultimately may transform to acute myelogenous leukemia. Most recently, chronic inflammation has been described as an important factor for the development and progression of MPNs in the biological continuum from early cancer stage to the advanced myelofibrosis stage, the MPNs being described as "A Human Inflammation Model for Cancer Development". This novel concept has been built upon clinical, experimental, genomic, immunological and not least epidemiological studies. Only a few studies have described the development of MPNs by mathematical models, and none have addressed the role of inflammation for clonal evolution and disease progression. Herein, we aim at using mathematical modelling to substantiate the concept of chronic inflammation as an important trigger and driver of MPNs.The basics of the model describe the proliferation from stem cells to mature cells including mutations of healthy stem cells to become malignant stem cells. We include a simple inflammatory coupling coping with cell death and affecting the basic model beneath. First, we describe the system without feedbacks or regulatory interactions. Next, we introduce inflammatory feedback into the system. Finally, we include other feedbacks and regulatory interactions forming the inflammatory-MPN model. Using mathematical modeling, we add further proof to the concept that chronic inflammation may be both a trigger of clonal evolution and an important driving force for MPN disease progression. Our findings support intervention at the earliest stage of cancer development to target the malignant clone and dampen concomitant inflammation.