Optimization of polymer electrolyte membrane fuel cell flow channels using a genetic algorithm

NASA Astrophysics Data System (ADS)

Catlin, Glenn; Advani, Suresh G.; Prasad, Ajay K.

The design of the flow channels in PEM fuel cells directly impacts the transport of reactant gases to the electrodes and affects cell performance. This paper presents results from a study to optimize the geometry of the flow channels in a PEM fuel cell. The optimization process implements a genetic algorithm to rapidly converge on the channel geometry that provides the highest net power output from the cell. In addition, this work implements a method for the automatic generation of parameterized channel domains that are evaluated for performance using a commercial computational fluid dynamics package from ANSYS. The software package includes GAMBIT as the solid modeling and meshing software, the solver FLUENT, and a PEMFC Add-on Module capable of modeling the relevant physical and electrochemical mechanisms that describe PEM fuel cell operation. The result of the optimization process is a set of optimal channel geometry values for the single-serpentine channel configuration. The performance of the optimal geometry is contrasted with a sub-optimal one by comparing contour plots of current density, oxygen and hydrogen concentration. In addition, the role of convective bypass in bringing fresh reactant to the catalyst layer is examined in detail. The convergence to the optimal geometry is confirmed by a bracketing study which compares the performance of the best individual to those of its neighbors with adjacent parameter values.

Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Mao, Lei; Jackson, Lisa

2016-10-01

In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

Modeling and optimization of proton-conducting solid oxide electrolysis cell: Conversion of CO2 into value-added products

NASA Astrophysics Data System (ADS)

Namwong, Lawit; Authayanun, Suthida; Saebea, Dang; Patcharavorachot, Yaneeporn; Arpornwichanop, Amornchai

2016-11-01

Proton-conducting solid oxide electrolysis cells (SOEC-H+) are a promising technology that can utilize carbon dioxide to produce syngas. In this work, a detailed electrochemical model was developed to predict the behavior of SOEC-H+ and to prove the assumption that the syngas is produced through a reversible water gas-shift (RWGS) reaction. The simulation results obtained from the model, which took into account all of the cell voltage losses (i.e., ohmic, activation, and concentration losses), were validated using experimental data to evaluate the unknown parameters. The developed model was employed to examine the structural and operational parameters. It is found that the cathode-supported SOEC-H+ is the best configuration because it requires the lowest cell potential. SOEC-H+ operated favorably at high temperatures and low pressures. Furthermore, the simulation results revealed that the optimal S/C molar ratio for syngas production, which can be used for methanol synthesis, is approximately 3.9 (at a constant temperature and pressure). The SOEC-H+ was optimized using a response surface methodology, which was used to determine the optimal operating conditions to minimize the cell potential and maximize the carbon dioxide flow rate.

Analysis and optimization of solid oxide fuel cell-based auxiliary power units using a generic zero-dimensional fuel cell model

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.

Verification of immune response optimality through cybernetic modeling.

PubMed

Batt, B C; Kompala, D S

1990-02-09

An immune response cascade that is T cell independent begins with the stimulation of virgin lymphocytes by antigen to differentiate into large lymphocytes. These immune cells can either replicate themselves or differentiate into plasma cells or memory cells. Plasma cells produce antibody at a specific rate up to two orders of magnitude greater than large lymphocytes. However, plasma cells have short life-spans and cannot replicate. Memory cells produce only surface antibody, but in the event of a subsequent infection by the same antigen, memory cells revert rapidly to large lymphocytes. Immunologic memory is maintained throughout the organism's lifetime. Many immunologists believe that the optimal response strategy calls for large lymphocytes to replicate first, then differentiate into plasma cells and when the antigen has been nearly eliminated, they form memory cells. A mathematical model incorporating the concept of cybernetics has been developed to study the optimality of the immune response. Derived from the matching law of microeconomics, cybernetic variables control the allocation of large lymphocytes to maximize the instantaneous antibody production rate at any time during the response in order to most efficiently inactivate the antigen. A mouse is selected as the model organism and bacteria as the replicating antigen. In addition to verifying the optimal switching strategy, results showing how the immune response is affected by antigen growth rate, initial antigen concentration, and the number of antibodies required to eliminate an antigen are included.

Application of CFD in Bioprocessing: Separation of mammalian cells using disc stack centrifuge during production of biotherapeutics.

PubMed

Shekhawat, Lalita Kanwar; Sarkar, Jayati; Gupta, Rachit; Hadpe, Sandeep; Rathore, Anurag S

2018-02-10

Centrifugation continues to be one of the most commonly used unit operations for achieving efficient harvest of the product from the mammalian cell culture broth during production of therapeutic monoclonal antibodies (mAbs). Since the mammalian cells are known to be shear sensitive, optimal performance of the centrifuge requires a balance between productivity and shear. In this study, Computational Fluid Dynamics (CFD) has been successfully used as a tool to facilitate efficient optimization. Multiphase Eulerian-Eulerian model coupled with Gidaspow drag model along with Eulerian-Eulerian k-ε mixture turbulence model have been used to quantify the complex hydrodynamics of the centrifuge and thus evaluate the turbulent stresses generated by the centrifugal forces. An empirical model has been developed by statistical analysis of experimentally observed cell lysis data as a function of turbulent stresses. An operating window that offers the optimal balance between high productivity, high separation efficiency, and low cell damage has been identified by use of CFD modeling. Copyright © 2017 Elsevier B.V. All rights reserved.

A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

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.

Layout optimization of DRAM cells using rigorous simulation model for NTD

NASA Astrophysics Data System (ADS)

Jeon, Jinhyuck; Kim, Shinyoung; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Kuechler, Bernd; Zimmermann, Rainer; Muelders, Thomas; Klostermann, Ulrich; Schmoeller, Thomas; Do, Mun-hoe; Choi, Jung-Hoe

2014-03-01

DRAM chip space is mainly determined by the size of the memory cell array patterns which consist of periodic memory cell features and edges of the periodic array. Resolution Enhancement Techniques (RET) are used to optimize the periodic pattern process performance. Computational Lithography such as source mask optimization (SMO) to find the optimal off axis illumination and optical proximity correction (OPC) combined with model based SRAF placement are applied to print patterns on target. For 20nm Memory Cell optimization we see challenges that demand additional tool competence for layout optimization. The first challenge is a memory core pattern of brick-wall type with a k1 of 0.28, so it allows only two spectral beams to interfere. We will show how to analytically derive the only valid geometrically limited source. Another consequence of two-beam interference limitation is a "super stable" core pattern, with the advantage of high depth of focus (DoF) but also low sensitivity to proximity corrections or changes of contact aspect ratio. This makes an array edge correction very difficult. The edge can be the most critical pattern since it forms the transition from the very stable regime of periodic patterns to non-periodic periphery, so it combines the most critical pitch and highest susceptibility to defocus. Above challenge makes the layout correction to a complex optimization task demanding a layout optimization that finds a solution with optimal process stability taking into account DoF, exposure dose latitude (EL), mask error enhancement factor (MEEF) and mask manufacturability constraints. This can only be achieved by simultaneously considering all criteria while placing and sizing SRAFs and main mask features. The second challenge is the use of a negative tone development (NTD) type resist, which has a strong resist effect and is difficult to characterize experimentally due to negative resist profile taper angles that perturb CD at bottom characterization by scanning electron microscope (SEM) measurements. High resist impact and difficult model data acquisition demand for a simulation model that hat is capable of extrapolating reliably beyond its calibration dataset. We use rigorous simulation models to provide that predictive performance. We have discussed the need of a rigorous mask optimization process for DRAM contact cell layout yielding mask layouts that are optimal in process performance, mask manufacturability and accuracy. In this paper, we have shown the step by step process from analytical illumination source derivation, a NTD and application tailored model calibration to layout optimization such as OPC and SRAF placement. Finally the work has been verified with simulation and experimental results on wafer.

Design and optimization of membrane-type acoustic metamaterials

NASA Astrophysics Data System (ADS)

Blevins, Matthew Grant

One of the most common problems in noise control is the attenuation of low frequency noise. Typical solutions require barriers with high density and/or thickness. Membrane-type acoustic metamaterials are a novel type of engineered material capable of high low-frequency transmission loss despite their small thickness and light weight. These materials are ideally suited to applications with strict size and weight limitations such as aircraft, automobiles, and buildings. The transmission loss profile can be manipulated by changing the micro-level substructure, stacking multiple unit cells, or by creating multi-celled arrays. To date, analysis has focused primarily on experimental studies in plane-wave tubes and numerical modeling using finite element methods. These methods are inefficient when used for applications that require iterative changes to the structure of the material. To facilitate design and optimization of membrane-type acoustic metamaterials, computationally efficient dynamic models based on the impedance-mobility approach are proposed. Models of a single unit cell in a waveguide and in a baffle, a double layer of unit cells in a waveguide, and an array of unit cells in a baffle are studied. The accuracy of the models and the validity of assumptions used are verified using a finite element method. The remarkable computational efficiency of the impedance-mobility models compared to finite element methods enables implementation in design tools based on a graphical user interface and in optimization schemes. Genetic algorithms are used to optimize the unit cell design for a variety of noise reduction goals, including maximizing transmission loss for broadband, narrow-band, and tonal noise sources. The tools for design and optimization created in this work will enable rapid implementation of membrane-type acoustic metamaterials to solve real-world noise control problems.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

A new epidemic modeling approach: Multi-regions discrete-time model with travel-blocking vicinity optimal control strategy.

PubMed

Zakary, Omar; Rachik, Mostafa; Elmouki, Ilias

2017-08-01

First, we devise in this paper, a multi-regions discrete-time model which describes the spatial-temporal spread of an epidemic which starts from one region and enters to regions which are connected with their neighbors by any kind of anthropological movement. We suppose homogeneous Susceptible-Infected-Removed (SIR) populations, and we consider in our simulations, a grid of colored cells, which represents the whole domain affected by the epidemic while each cell can represent a sub-domain or region. Second, in order to minimize the number of infected individuals in one region, we propose an optimal control approach based on a travel-blocking vicinity strategy which aims to control only one cell by restricting movements of infected people coming from all neighboring cells. Thus, we show the influence of the optimal control approach on the controlled cell. We should also note that the cellular modeling approach we propose here, can also describes infection dynamics of regions which are not necessarily attached one to an other, even if no empty space can be viewed between cells. The theoretical method we follow for the characterization of the travel-locking optimal controls, is based on a discrete version of Pontryagin's maximum principle while the numerical approach applied to the multi-points boundary value problems we obtain here, is based on discrete progressive-regressive iterative schemes. We illustrate our modeling and control approaches by giving an example of 100 regions.

Modeling and Control of a Delayed Hepatitis B Virus Model with Incubation Period and Combination Treatment.

PubMed

Sun, Deshun; Liu, Fei

2018-06-01

In this paper, a hepatitis B virus (HBV) model with an incubation period and delayed state and control variables is firstly proposed. Furthermore, the combination treatment is adopted to have a longer-lasting effect than mono-therapy. The equilibrium points and basic reproduction number are calculated, and then the local stability is analyzed on this model. We then present optimal control strategies based on the Pontryagin's minimum principle with an objective function not only to reduce the levels of exposed cells, infected cells and free viruses nearly to zero at the end of therapy, but also to minimize the drug side-effect and the cost of treatment. What's more, we develop a numerical simulation algorithm for solving our HBV model based on the combination of forward and backward difference approximations. The state dynamics of uninfected cells, exposed cells, infected cells, free viruses, CTL and ALT are simulated with or without optimal control, which show that HBV is reduced nearly to zero based on the time-varying optimal control strategies whereas the disease would break out without control. At last, by the simulations, we prove that strategy A is the best among the three kinds of strategies we adopt and further comparisons have been done between model (1) and model (2).

Modeling Filamentous Cyanobacteria Reveals the Advantages of Long and Fast Trichomes for Optimizing Light Exposure

PubMed Central

Tamulonis, Carlos; Postma, Marten; Kaandorp, Jaap

2011-01-01

Cyanobacteria form a very large and diverse phylum of prokaryotes that perform oxygenic photosynthesis. Many species of cyanobacteria live colonially in long trichomes of hundreds to thousands of cells. Of the filamentous species, many are also motile, gliding along their long axis, and display photomovement, by which a trichome modulates its gliding according to the incident light. The latter has been found to play an important role in guiding the trichomes to optimal lighting conditions, which can either inhibit the cells if the incident light is too weak, or damage the cells if too strong. We have developed a computational model for gliding filamentous photophobic cyanobacteria that allows us to perform simulations on the scale of a Petri dish using over 105 individual trichomes. Using the model, we quantify the effectiveness of one commonly observed photomovement strategy—photophobic responses—in distributing large populations of trichomes optimally over a light field. The model predicts that the typical observed length and gliding speeds of filamentous cyanobacteria are optimal for the photophobic strategy. Therefore, our results suggest that not just photomovement but also the trichome shape itself improves the ability of the cyanobacteria to optimize their light exposure. PMID:21789215

Systematic optimization of fed-batch simultaneous saccharification and fermentation at high-solid loading based on enzymatic hydrolysis and dynamic metabolic modeling of Saccharomyces cerevisiae.

PubMed

Unrean, Pornkamol; Khajeeram, Sutamat; Laoteng, Kobkul

2016-03-01

An integrative simultaneous saccharification and fermentation (SSF) modeling is a useful guiding tool for rapid process optimization to meet the techno-economic requirement of industrial-scale lignocellulosic ethanol production. In this work, we have developed the SSF model composing of a metabolic network of a Saccharomyces cerevisiae cell associated with fermentation kinetics and enzyme hydrolysis model to quantitatively capture dynamic responses of yeast cell growth and fermentation during SSF. By using model-based design of feeding profiles for substrate and yeast cell in the fed-batch SSF process, an efficient ethanol production with high titer of up to 65 g/L and high yield of 85 % of theoretical yield was accomplished. The ethanol titer and productivity was increased by 47 and 41 %, correspondingly, in optimized fed-batch SSF as compared to batch process. The developed integrative SSF model is, therefore, considered as a promising approach for systematic design of economical and sustainable SSF bioprocessing of lignocellulose.

Optimal design and operation of solid oxide fuel cell systems for small-scale stationary applications

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.

Validation of in vitro assays in three-dimensional human dermal constructs.

PubMed

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.

Active model-based balancing strategy for self-reconfigurable batteries

NASA Astrophysics Data System (ADS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2016-08-01

This paper describes a novel balancing strategy for self-reconfigurable batteries where the discharge and charge rates of each cell can be controlled. While much effort has been focused on improving the hardware architecture of self-reconfigurable batteries, energy equalization algorithms have not been systematically optimized in terms of maximizing the efficiency of the balancing system. Our approach includes aspects of such optimization theory. We develop a balancing strategy for optimal control of the discharge rate of battery cells. We first formulate the cell balancing as a nonlinear optimal control problem, which is modeled afterward as a network program. Using dynamic programming techniques and MATLAB's vectorization feature, we solve the optimal control problem by generating the optimal battery operation policy for a given drive cycle. The simulation results show that the proposed strategy efficiently balances the cells over the life of the battery, an obvious advantage that is absent in the other conventional approaches. Our algorithm is shown to be robust when tested against different influencing parameters varying over wide spectrum on different drive cycles. Furthermore, due to the little computation time and the proved low sensitivity to the inaccurate power predictions, our strategy can be integrated in a real-time system.

Rhombicuboctahedron unit cell based scaffolds for bone regeneration: geometry optimization with a mechanobiology - driven algorithm.

PubMed

Boccaccio, Antonio; Fiorentino, Michele; Uva, Antonio E; Laghetti, Luca N; Monno, Giuseppe

2018-02-01

In a context more and more oriented towards customized medical solutions, we propose a mechanobiology-driven algorithm to determine the optimal geometry of scaffolds for bone regeneration that is the most suited to specific boundary and loading conditions. In spite of the huge number of articles investigating different unit cells for porous biomaterials, no studies are reported in the literature that optimize the geometric parameters of such unit cells based on mechanobiological criteria. Parametric finite element models of scaffolds with rhombicuboctahedron unit cell were developed and incorporated into an optimization algorithm that combines them with a computational mechanobiological model. The algorithm perturbs iteratively the geometry of the unit cell until the best scaffold geometry is identified, i.e. the geometry that allows to maximize the formation of bone. Performances of scaffolds with rhombicuboctahedron unit cell were compared with those of other scaffolds with hexahedron unit cells. We found that scaffolds with rhombicuboctahedron unit cell are particularly suited for supporting medium-low loads, while, for higher loads, scaffolds with hexahedron unit cells are preferable. The proposed algorithm can guide the orthopaedic/surgeon in the choice of the best scaffold to be implanted in a patient-specific anatomic region. Copyright © 2017 Elsevier B.V. All rights reserved.

Solid oxide fuel cell simulation and design optimization with numerical adjoint techniques

NASA Astrophysics Data System (ADS)

Elliott, Louie C.

This dissertation reports on the application of numerical optimization techniques as applied to fuel cell simulation and design. Due to the "multi-physics" inherent in a fuel cell, which results in a highly coupled and non-linear behavior, an experimental program to analyze and improve the performance of fuel cells is extremely difficult. This program applies new optimization techniques with computational methods from the field of aerospace engineering to the fuel cell design problem. After an overview of fuel cell history, importance, and classification, a mathematical model of solid oxide fuel cells (SOFC) is presented. The governing equations are discretized and solved with computational fluid dynamics (CFD) techniques including unstructured meshes, non-linear solution methods, numerical derivatives with complex variables, and sensitivity analysis with adjoint methods. Following the validation of the fuel cell model in 2-D and 3-D, the results of the sensitivity analysis are presented. The sensitivity derivative for a cost function with respect to a design variable is found with three increasingly sophisticated techniques: finite difference, direct differentiation, and adjoint. A design cycle is performed using a simple optimization method to improve the value of the implemented cost function. The results from this program could improve fuel cell performance and lessen the world's dependence on fossil fuels.

Modeling and optimal designs for dislocation and radiation tolerant single and multijunction solar cells

NASA Astrophysics Data System (ADS)

Mehrotra, A.; Alemu, A.; Freundlich, A.

2011-02-01

Crystalline defects (e.g. dislocations or grain boundaries) as well as electron and proton induced defects cause reduction of minority carrier diffusion length which in turn results in degradation of efficiency of solar cells. Hetro-epitaxial or metamorphic III-V devices with low dislocation density have high BOL efficiencies but electron-proton radiation causes degradation in EOL efficiencies. By optimizing the device design (emitter-base thickness, doping) we can obtain highly dislocated metamorphic devices that are radiation resistant. Here we have modeled III-V single and multi junction solar cells using drift and diffusion equations considering experimental III-V material parameters, dislocation density, 1 Mev equivalent electron radiation doses, thicknesses and doping concentration. Thinner device thickness leads to increment in EOL efficiency of high dislocation density solar cells. By optimizing device design we can obtain nearly same EOL efficiencies from high dislocation solar cells than from defect free III-V multijunction solar cells. As example defect free GaAs solar cell after optimization gives 11.2% EOL efficiency (under typical 5x1015cm-2 1 MeV electron fluence) while a GaAs solar cell with high dislocation density (108 cm-2) after optimization gives 10.6% EOL efficiency. The approach provides an additional degree of freedom in the design of high efficiency space cells and could in turn be used to relax the need for thick defect filtering buffer in metamorphic devices.

Clonal analysis of synovial fluid stem cells to characterize and identify stable mesenchymal stromal cell/mesenchymal progenitor cell phenotypes in a porcine model: a cell source with enhanced commitment to the chondrogenic lineage.

PubMed

Ando, Wataru; Kutcher, Josh J; Krawetz, Roman; Sen, Arindom; Nakamura, Norimasa; Frank, Cyril B; Hart, David A

2014-06-01

Previous studies have demonstrated that porcine synovial membrane stem cells can adhere to a cartilage defect in vivo through the use of a tissue-engineered construct approach. To optimize this model, we wanted to compare effectiveness of tissue sources to determine whether porcine synovial fluid, synovial membrane, bone marrow and skin sources replicate our understanding of synovial fluid mesenchymal stromal cells or mesenchymal progenitor cells from humans both at the population level and the single-cell level. Synovial fluid clones were subsequently isolated and characterized to identify cells with a highly characterized optimal phenotype. The chondrogenic, osteogenic and adipogenic potentials were assessed in vitro for skin, bone marrow, adipose, synovial fluid and synovial membrane-derived stem cells. Synovial fluid cells then underwent limiting dilution analysis to isolate single clonal populations. These clonal populations were assessed for proliferative and differentiation potential by use of standardized protocols. Porcine-derived cells demonstrated the same relationship between cell sources as that demonstrated previously for humans, suggesting that the pig may be an ideal preclinical animal model. Synovial fluid cells demonstrated the highest chondrogenic potential that was further characterized, demonstrating the existence of a unique clonal phenotype with enhanced chondrogenic potential. Porcine stem cells demonstrate characteristics similar to those in human-derived mesenchymal stromal cells from the same sources. Synovial fluid-derived stem cells contain an inherent phenotype that may be optimal for cartilage repair. This must be more fully investigated for future use in the in vivo tissue-engineered construct approach in this physiologically relevant preclinical porcine model. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

The Isolation and Characterization of Human Prostate Cancer Stem Cells

DTIC Science & Technology

2012-02-01

established cell lines and primary patient samples) with human prostate fibroblasts hold promise as models of tumor initiation/cancer stem cell activity...We continue to optimize and validate our in vitro model of prostate cancer initiation to facilitate cancer stem cell discovery as well as drug targeting.

Evaluation of automated cell disruptor methods for oomycetous and ascomycetous model organisms

USDA-ARS?s Scientific Manuscript database

Two automated cell disruptor-based methods for RNA extraction; disruption of thawed cells submerged in TRIzol Reagent (method QP), and direct disruption of frozen cells on dry ice (method CP), were optimized for a model oomycete, Phytophthora capsici, and compared with grinding in a mortar and pestl...

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

DOE PAGES

De Pillis, L. G.; Radunskaya, A.

2001-01-01

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Pillis, L. G.; Radunskaya, A.

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Cell transmission model of dynamic assignment for urban rail transit networks.

PubMed

Xu, Guangming; Zhao, Shuo; Shi, Feng; Zhang, Feilian

2017-01-01

For urban rail transit network, the space-time flow distribution can play an important role in evaluating and optimizing the space-time resource allocation. For obtaining the space-time flow distribution without the restriction of schedules, a dynamic assignment problem is proposed based on the concept of continuous transmission. To solve the dynamic assignment problem, the cell transmission model is built for urban rail transit networks. The priority principle, queuing process, capacity constraints and congestion effects are considered in the cell transmission mechanism. Then an efficient method is designed to solve the shortest path for an urban rail network, which decreases the computing cost for solving the cell transmission model. The instantaneous dynamic user optimal state can be reached with the method of successive average. Many evaluation indexes of passenger flow can be generated, to provide effective support for the optimization of train schedules and the capacity evaluation for urban rail transit network. Finally, the model and its potential application are demonstrated via two numerical experiments using a small-scale network and the Beijing Metro network.

Theoretical analysis of improved efficiency of silicon-wafer solar cells with textured nanotriangular grating structure

NASA Astrophysics Data System (ADS)

Zhang, Yaoju; Zheng, Jun; Zhao, Xuesong; Ruan, Xiukai; Cui, Guihua; Zhu, Haiyong; Dai, Yuxing

2018-03-01

A practical model of crystalline silicon-wafer solar cells is proposed in order to enhance the light absorption and improve the conversion efficiency of silicon solar cells. In the model, the front surface of the silicon photovoltaic film is designed to be a textured-triangular-grating (TTG) structure, and the ITO contact film and the antireflection coating (ARC) of glass are coated on the TTG surface of silicon solar cells. The optical absorption spectrum of solar cells are simulated by applying the finite difference time domain method. Electrical parameters of the solar cells are calculated using two models with and without carrier loss. The effect of structure parameters on the performance of the TTG cell is discussed in detail. It is found that the thickness (tg) of the ARC, period (p) of grating, and base angle (θ) of triangle have a crucial influence on the conversion efficiency. The optimal structure of the TTG cell is designed. The TTG solar cell can produce higher efficiency in a wide range of solar incident angle and the average efficiency of the optimal TTG cell over 7:30-16:30 time of day is 8% higher than that of the optimal plane solar cell. In addition, the study shows that the bulk recombination of carriers has an influence on the conversion efficiency of the cell, the conversion efficiency of the actual solar cell with carrier recombination is reduced by 20.0% of the ideal cell without carrier recombination.

Dendritic Immunotherapy Improvement for an Optimal Control Murine Model

PubMed Central

Chimal-Eguía, J. C.; Castillo-Montiel, E.

2017-01-01

Therapeutic protocols in immunotherapy are usually proposed following the intuition and experience of the therapist. In order to deduce such protocols mathematical modeling, optimal control and simulations are used instead of the therapist's experience. Clinical efficacy of dendritic cell (DC) vaccines to cancer treatment is still unclear, since dendritic cells face several obstacles in the host environment, such as immunosuppression and poor transference to the lymph nodes reducing the vaccine effect. In view of that, we have created a mathematical murine model to measure the effects of dendritic cell injections admitting such obstacles. In addition, the model considers a therapy given by bolus injections of small duration as opposed to a continual dose. Doses timing defines the therapeutic protocols, which in turn are improved to minimize the tumor mass by an optimal control algorithm. We intend to supplement therapist's experience and intuition in the protocol's implementation. Experimental results made on mice infected with melanoma with and without therapy agree with the model. It is shown that the dendritic cells' percentage that manages to reach the lymph nodes has a crucial impact on the therapy outcome. This suggests that efforts in finding better methods to deliver DC vaccines should be pursued. PMID:28912828

Exosome delivered anticancer drugs across the blood-brain barrier for brain cancer therapy in Danio rerio.

PubMed

Yang, Tianzhi; Martin, Paige; Fogarty, Brittany; Brown, Alison; Schurman, Kayla; Phipps, Roger; Yin, Viravuth P; Lockman, Paul; Bai, Shuhua

2015-06-01

The blood-brain barrier (BBB) essentially restricts therapeutic drugs from entering into the brain. This study tests the hypothesis that brain endothelial cell derived exosomes can deliver anticancer drug across the BBB for the treatment of brain cancer in a zebrafish (Danio rerio) model. Four types of exosomes were isolated from brain cell culture media and characterized by particle size, morphology, total protein, and transmembrane protein markers. Transport mechanism, cell uptake, and cytotoxicity of optimized exosome delivery system were tested. Brain distribution of exosome delivered anticancer drugs was evaluated using transgenic zebrafish TG (fli1: GFP) embryos and efficacies of optimized formations were examined in a xenotransplanted zebrafish model of brain cancer model. Four exosomes in 30-100 diameters showed different morphologies and exosomes derived from brain endothelial cells expressed more CD63 tetraspanins transmembrane proteins. Optimized exosomes increased the uptake of fluorescent marker via receptor mediated endocytosis and cytotoxicity of anticancer drugs in cancer cells. Images of the zebrafish showed exosome delivered anticancer drugs crossed the BBB and entered into the brain. In the brain cancer model, exosome delivered anticancer drugs significantly decreased fluorescent intensity of xenotransplanted cancer cells and tumor growth marker. Brain endothelial cell derived exosomes could be potentially used as a carrier for brain delivery of anticancer drug for the treatment of brain cancer.

Modeling and optimization of a typical fuel cell-heat engine hybrid system and its parametric design criteria

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.

Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

NASA Astrophysics Data System (ADS)

Ajdari, Ali; Ghate, Archis; Kim, Minsun

2018-04-01

Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

Optimized Delivery System Achieves Enhanced Endomyocardial Stem Cell Retention

PubMed Central

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

Optimizing radiotherapy protocols using computer automata to model tumour cell death as a function of oxygen diffusion processes.

PubMed

Paul-Gilloteaux, Perrine; Potiron, Vincent; Delpon, Grégory; Supiot, Stéphane; Chiavassa, Sophie; Paris, François; Costes, Sylvain V

2017-05-23

The concept of hypofractionation is gaining momentum in radiation oncology centres, enabled by recent advances in radiotherapy apparatus. The gain of efficacy of this innovative treatment must be defined. We present a computer model based on translational murine data for in silico testing and optimization of various radiotherapy protocols with respect to tumour resistance and the microenvironment heterogeneity. This model combines automata approaches with image processing algorithms to simulate the cellular response of tumours exposed to ionizing radiation, modelling the alteration of oxygen permeabilization in blood vessels against repeated doses, and introducing mitotic catastrophe (as opposed to arbitrary delayed cell-death) as a means of modelling radiation-induced cell death. Published data describing cell death in vitro as well as tumour oxygenation in vivo are used to inform parameters. Our model is validated by comparing simulations to in vivo data obtained from the radiation treatment of mice transplanted with human prostate tumours. We then predict the efficacy of untested hypofractionation protocols, hypothesizing that tumour control can be optimized by adjusting daily radiation dosage as a function of the degree of hypoxia in the tumour environment. Further biological refinement of this tool will permit the rapid development of more sophisticated strategies for radiotherapy.

Groundwater management under uncertainty using a stochastic multi-cell model

NASA Astrophysics Data System (ADS)

Joodavi, Ata; Zare, Mohammad; Ziaei, Ali Naghi; Ferré, Ty P. A.

2017-08-01

The optimization of spatially complex groundwater management models over long time horizons requires the use of computationally efficient groundwater flow models. This paper presents a new stochastic multi-cell lumped-parameter aquifer model that explicitly considers uncertainty in groundwater recharge. To achieve this, the multi-cell model is combined with the constrained-state formulation method. In this method, the lower and upper bounds of groundwater heads are incorporated into the mass balance equation using indicator functions. This provides expressions for the means, variances and covariances of the groundwater heads, which can be included in the constraint set in an optimization model. This method was used to formulate two separate stochastic models: (i) groundwater flow in a two-cell aquifer model with normal and non-normal distributions of groundwater recharge; and (ii) groundwater management in a multiple cell aquifer in which the differences between groundwater abstractions and water demands are minimized. The comparison between the results obtained from the proposed modeling technique with those from Monte Carlo simulation demonstrates the capability of the proposed models to approximate the means, variances and covariances. Significantly, considering covariances between the heads of adjacent cells allows a more accurate estimate of the variances of the groundwater heads. Moreover, this modeling technique requires no discretization of state variables, thus offering an efficient alternative to computationally demanding methods.

A Peptide Filtering Relation Quantifies MHC Class I Peptide Optimization

PubMed Central

Goldstein, Leonard D.; Howarth, Mark; Cardelli, Luca; Emmott, Stephen; Elliott, Tim; Werner, Joern M.

2011-01-01

Major Histocompatibility Complex (MHC) class I molecules enable cytotoxic T lymphocytes to destroy virus-infected or cancerous cells, thereby preventing disease progression. MHC class I molecules provide a snapshot of the contents of a cell by binding to protein fragments arising from intracellular protein turnover and presenting these fragments at the cell surface. Competing fragments (peptides) are selected for cell-surface presentation on the basis of their ability to form a stable complex with MHC class I, by a process known as peptide optimization. A better understanding of the optimization process is important for our understanding of immunodominance, the predominance of some T lymphocyte specificities over others, which can determine the efficacy of an immune response, the danger of immune evasion, and the success of vaccination strategies. In this paper we present a dynamical systems model of peptide optimization by MHC class I. We incorporate the chaperone molecule tapasin, which has been shown to enhance peptide optimization to different extents for different MHC class I alleles. Using a combination of published and novel experimental data to parameterize the model, we arrive at a relation of peptide filtering, which quantifies peptide optimization as a function of peptide supply and peptide unbinding rates. From this relation, we find that tapasin enhances peptide unbinding to improve peptide optimization without significantly delaying the transit of MHC to the cell surface, and differences in peptide optimization across MHC class I alleles can be explained by allele-specific differences in peptide binding. Importantly, our filtering relation may be used to dynamically predict the cell surface abundance of any number of competing peptides by MHC class I alleles, providing a quantitative basis to investigate viral infection or disease at the cellular level. We exemplify this by simulating optimization of the distribution of peptides derived from Human Immunodeficiency Virus Gag-Pol polyprotein. PMID:22022238

Two-Step Production of Phenylpyruvic Acid from L-Phenylalanine by Growing and Resting Cells of Engineered Escherichia coli: Process Optimization and Kinetics Modeling.

PubMed

Hou, Ying; Hossain, Gazi Sakir; Li, Jianghua; Shin, Hyun-Dong; Liu, Long; Du, Guocheng; Chen, Jian

2016-01-01

Phenylpyruvic acid (PPA) is widely used in the pharmaceutical, food, and chemical industries. Here, a two-step bioconversion process, involving growing and resting cells, was established to produce PPA from l-phenylalanine using the engineered Escherichia coli constructed previously. First, the biotransformation conditions for growing cells were optimized (l-phenylalanine concentration 20.0 g·L-1, temperature 35°C) and a two-stage temperature control strategy (keep 20°C for 12 h and increase the temperature to 35°C until the end of biotransformation) was performed. The biotransformation conditions for resting cells were then optimized in 3-L bioreactor and the optimized conditions were as follows: agitation speed 500 rpm, aeration rate 1.5 vvm, and l-phenylalanine concentration 30 g·L-1. The total maximal production (mass conversion rate) reached 29.8 ± 2.1 g·L-1 (99.3%) and 75.1 ± 2.5 g·L-1 (93.9%) in the flask and 3-L bioreactor, respectively. Finally, a kinetic model was established, and it was revealed that the substrate and product inhibition were the main limiting factors for resting cell biotransformation.

Processing of Cells' Trajectories Data for Blood Flow Simulation Model*

NASA Astrophysics Data System (ADS)

Slavík, Martin; Kovalčíková, Kristína; Bachratý, Hynek; Bachratá, Katarína; Smiešková, Monika

2018-06-01

Simulations of the red blood cells (RBCs) flow as a movement of elastic objects in a fluid, are developed to optimize microfluidic devices used for a blood sample analysis for diagnostic purposes in the medicine. Tracking cell behaviour during simulation helps to improve the model and adjust its parameters. For the optimization of the microfluidic devices, it is also necessary to analyse cell trajectories as well as likelihood and frequency of their occurrence in a particular device area, especially in the parts, where they can affect circulating tumour cells capture. In this article, we propose and verify several ways of processing and analysing the typology and trajectory stability in simulations with single or with a large number of red blood cells (RBCs) in devices with different topologies containing cylindrical obstacles.

Modelling and optimization of environmental conditions for kefiran production by Lactobacillus kefiranofaciens.

PubMed

Cheirsilp, B; Shimizu, H; Shioya, S

2001-12-01

A mathematical model for kefiran production by Lactobacillus kefiranofaciens was established, in which the effects of pH, substrate and product on cell growth, exopolysaccharide formation and substrate assimilation were considered. The model gave a good representation both of the formation of exopolysaccharides (which are not only attached to cells but also released into the medium) and of the time courses of the production of galactose and glucose in the medium (which are produced and consumed by the cells). Since pH and both lactose and lactic acid concentrations differently affected production and growth activity, the model included the effects of pH and the concentrations of lactose and lactic acid. Based on the mathematical model, an optimal pH profile for the maximum production of kefiran in batch culture was obtained. In this study, a simplified optimization method was developed, in which the optimal pH profile was determined at a particular final fermentation time. This was based on the principle that, at a certain time, switching from the maximum specific growth rate to the critical one (which yields the maximum specific production rate) results in maximum production. Maximum kefiran production was obtained, which was 20% higher than that obtained in the constant-pH control fermentation. A genetic algorithm (GA) was also applied to obtain the optimal pH profile; and it was found that practically the same solution was obtained using the GA.

Culture in embryonic kidney serum and xeno-free media as renal cell carcinoma and renal cell carcinoma cancer stem cells research model.

PubMed

Krawczyk, Krzysztof M; Matak, Damian; Szymanski, Lukasz; Szczylik, Cezary; Porta, Camillo; Czarnecka, Anna M

2018-04-01

The use of fetal bovine serum hinders obtaining reproducible experimental results and should also be removed in hormone and growth factor studies. In particular hormones found in FBS act globally on cancer cell physiology and influence transcriptome and metabolome. The aim of our study was to develop a renal carcinoma serum free culture model optimized for (embryonal) renal cells in order to select the best study model for downstream auto-, para- or endocrine research. Secondary aim was to verify renal carcinoma stem cell culture for this application. In the study, we have cultured renal cell carcinoma primary tumour cell line (786-0) as well as human kidney cancer stem cells in standard 2D monolayer cultures in Roswell Park Memorial Institute Medium or Dulbecco's Modified Eagle's Medium and Complete Human Kidney Cancer Stem Cell Medium, respectively. Serum-free, animal-component free Human Embryonic Kidney 293 media were tested. Our results revealed that xeno-free embryonal renal cells optimized culture media provide a useful tool in RCC cancer biology research and at the same time enable effective growth of RCC. We propose bio-mimic RCC cell culture model with specific serum-free and xeno-free medium that promote RCC cell viability.

Aurora B kinase inhibition in mitosis: strategies for optimising the use of aurora kinase inhibitors such as AT9283.

PubMed

Curry, Jayne; Angove, Hayley; Fazal, Lynsey; Lyons, John; Reule, Matthias; Thompson, Neil; Wallis, Nicola

2009-06-15

Aurora kinases play a key role in regulating mitotic division and are attractive oncology targets. AT9283, a multi-targeted kinase inhibitor with potent activity against Aurora A and B kinases, inhibited growth and survival of multiple solid tumor cell lines and was efficacious in mouse xenograft models. AT9283-treatment resulted in endoreduplication and ablation of serine-10 histone H3 phosphorylation in both cells and tumor samples, confirming that in these models it acts as an Aurora B kinase inhibitor. In vitro studies demonstrated that exposure to AT9283 for one complete cell cycle committed an entire population of p53 checkpoint-compromised cells (HCT116) to multinucleation and death whereas treatment of p53 checkpoint-competent cells (HMEC, A549) for a similar length of time led to a reversible arrest of cells with 4N DNA. Further studies in synchronized cell populations suggested that exposure to AT9283 during mitosis was critical for optimal cytotoxicity. We therefore investigated ways in which these properties might be exploited to optimize the efficacy and therapeutic index of Aurora kinase inhibitors for p53 checkpoint compromised tumors in vivo. Combining Aurora B kinase inhibition with paclitaxel, which arrests cells in mitosis, in a xenograft model resulted in promising efficacy without additional toxicity. These findings have implications for optimizing the efficacy of Aurora kinase inhibitors in clinical practice.

Static capacity model for sealed nickel cadmium cells

NASA Astrophysics Data System (ADS)

Lomaniec, Jacob

1989-04-01

A model was developed for calculating the capacity of nickel cadmium rechargeable sealed cells. The model applies only to the following operating conditions for a cell of capacity C ampere-hours: Temperature of 20 + or - 5 C; charging for 16 hr, at 0.1 C amp; discharging at 0.2 C amp until the terminal voltage falls to 1.0 V. The study considers the dimensional and quantitative relationships among the cell's chemical and mechanical components, and the application of these relationships to optimizing cell design in terms of energy density and electrical performance. The model comprises several components, representing the several stages of the manufacturing process: assembling the electrodes and separator in a cylindrical can; production of porous, sintered nickel plaque on a perforated steel substrate; impregnating the plaque with active material; oxidation of the sintered nickel during impregnation; insertion and concentration of the electrolyte solution. Results from the model were compared with those obtained from cells manufactured during a long period. Good agreement was obtained. The models were used in the plant, to define the operating parameters of various production stages and contributed to a general improvement in product quality. The models were also applied to the optimization of new cell designs, and reduction of development costs by the elimination of much experimental work.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Regional Delivery of Chimeric Antigen Receptor-Engineered T Cells Effectively Targets HER2+ Breast Cancer Metastasis to the Brain.

PubMed

Priceman, Saul J; Tilakawardane, Dileshni; Jeang, Brook; Aguilar, Brenda; Murad, John P; Park, Anthony K; Chang, Wen-Chung; Ostberg, Julie R; Neman, Josh; Jandial, Rahul; Portnow, Jana; Forman, Stephen J; Brown, Christine E

2018-01-01

Purpose: Metastasis to the brain from breast cancer remains a significant clinical challenge, and may be targeted with CAR-based immunotherapy. CAR design optimization for solid tumors is crucial due to the absence of truly restricted antigen expression and potential safety concerns with "on-target off-tumor" activity. Here, we have optimized HER2-CAR T cells for the treatment of breast to brain metastases, and determined optimal second-generation CAR design and route of administration for xenograft mouse models of breast metastatic brain tumors, including multifocal and leptomeningeal disease. Experimental Design: HER2-CAR constructs containing either CD28 or 4-1BB intracellular costimulatory signaling domains were compared for functional activity in vitro by measuring cytokine production, T-cell proliferation, and tumor killing capacity. We also evaluated HER2-CAR T cells delivered by intravenous, local intratumoral, or regional intraventricular routes of administration using in vivo human xenograft models of breast cancer that have metastasized to the brain. Results: Here, we have shown that HER2-CARs containing the 4-1BB costimulatory domain confer improved tumor targeting with reduced T-cell exhaustion phenotype and enhanced proliferative capacity compared with HER2-CARs containing the CD28 costimulatory domain. Local intracranial delivery of HER2-CARs showed potent in vivo antitumor activity in orthotopic xenograft models. Importantly, we demonstrated robust antitumor efficacy following regional intraventricular delivery of HER2-CAR T cells for the treatment of multifocal brain metastases and leptomeningeal disease. Conclusions: Our study shows the importance of CAR design in defining an optimized CAR T cell, and highlights intraventricular delivery of HER2-CAR T cells for treating multifocal brain metastases. Clin Cancer Res; 24(1); 95-105. ©2017 AACR . ©2017 American Association for Cancer Research.

Modeling of defect-tolerant thin multi-junction solar cells for space application

NASA Astrophysics Data System (ADS)

Mehrotra, A.; Alemu, A.; Freundlich, A.

2012-02-01

Using drift-diffusion model and considering experimental III-V material parameters, AM0 efficiencies of lattice-matched multijunction solar cells have been calculated and the effects of dislocations and radiation damage have been analyzed. Ultrathin multi-junction devices perform better in presence of dislocations or/and radiation harsh environment compared to conventional thick multijunction devices. Our results show that device design optimization of Ga0.51In0.49P/GaAs multijunction devices leads to an improvement in EOL efficiency from 4.8%, for the conventional thick device design, to 12.7%, for the EOL optimized thin devices. In addition, an optimized defect free lattice matched Ga0.51In0.49P/GaAs solar cell under 1016cm-2 1Mev equivalent electron fluence is shown to give an EOL efficiency of 12.7%; while a Ga0.51In0.49P/GaAs solar cell with 108 cm-2 dislocation density under 1016cm-2 electron fluence gives an EOL efficiency of 12.3%. The results suggest that by optimizing the device design, we can obtain nearly the same EOL efficiencies for high dislocation metamorphic solar cells and defect filtered metamorphic multijunction solar cells. The findings relax the need for thick or graded buffer used for defect filtering in metamorphic devices. It is found that device design optimization allows highly dislocated devices to be nearly as efficient as defect free devices for space applications.

A new model for simulating microbial cyanide production and optimizing the medium parameters for recovering precious metals from waste printed circuit boards.

PubMed

Yuan, Zhihui; Ruan, Jujun; Li, Yaying; Qiu, Rongliang

2018-04-10

Bioleaching is a green recycling technology for recovering precious metals from waste printed circuit boards (WPCBs). However, this technology requires increasing cyanide production to obtain desirable recovery efficiency. Luria-Bertani medium (LB medium, containing tryptone 10 g/L, yeast extract 5 g/L, NaCl 10 g/L) was commonly used in bioleaching of precious metal. In this study, results showed that LB medium did not produce highest yield of cyanide. Under optimal culture conditions (25 °C, pH 7.5), the maximum cyanide yield of the optimized medium (containing tryptone 6 g/L and yeast extract 5 g/L) was 1.5 times as high as that of LB medium. In addition, kinetics and relationship of cell growth and cyanide production was studied. Data of cell growth fitted logistics model well. Allometric model was demonstrated effective in describing relationship between cell growth and cyanide production. By inserting logistics equation into allometric equation, we got a novel hybrid equation containing five parameters. Kinetic data for cyanide production were well fitted to the new model. Model parameters reflected both cell growth and cyanide production process. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimal flow conditions of a tracheobronchial model to reengineer lung structures

NASA Astrophysics Data System (ADS)

Casarin, Stefano; Aletti, Federico; Baselli, Giuseppe; Garbey, Marc

2017-04-01

The high demand for lung transplants cannot be matched by an adequate number of lungs from donors. Since fully ex-novo lungs are far from being feasible, tissue engineering is actively considering implantation of engineered lungs where the devitalized structure of a donor is used as scaffold to be repopulated by stem cells of the receiving patient. A decellularized donated lung is treated inside a bioreactor where transport through the tracheobronchial tree (TBT) will allow for both deposition of stem cells and nourishment for their subsequent growth, thus developing new lung tissue. The key concern is to set optimally the boundary conditions to utilize in the bioreactor. We propose a predictive model of slow liquid ventilation, which combines a one-dimensional (1-D) mathematical model of the TBT and a solute deposition model strongly dependent on fluid velocity across the tree. With it, we were able to track and drive the concentration of a generic solute across the airways, looking for its optimal distribution. This was given by properly adjusting the pumps' regime serving the bioreactor. A feedback system, created by coupling the two models, allowed us to derive the optimal pattern. The TBT model can be easily invertible, thus yielding a straightforward flow/pressure law at the inlet to optimize the efficiency of the bioreactor.

Size and shape effects on diffusion and absorption of colloidal particles near a partially absorbing sphere: implications for uptake of nanoparticles in animal cells.

PubMed

Shi, Wendong; Wang, Jizeng; Fan, Xiaojun; Gao, Huajian

2008-12-01

A mechanics model describing how a cell membrane with diffusive mobile receptors wraps around a ligand-coated cylindrical or spherical particle has been recently developed to model the role of particle size in receptor-mediated endocytosis. The results show that particles in the size range of tens to hundreds of nanometers can enter cells even in the absence of clathrin or caveolin coats. Here we report further progress on modeling the effects of size and shape in diffusion, interaction, and absorption of finite-sized colloidal particles near a partially absorbing sphere. Our analysis indicates that, from the diffusion and interaction point of view, there exists an optimal hydrodynamic size of particles, typically in the nanometer regime, for the maximum rate of particle absorption. Such optimal size arises as a result of balance between the diffusion constant of the particles and the interaction energy between the particles and the absorbing sphere relative to the thermal energy. Particles with a smaller hydrodynamic radius have larger diffusion constant but weaker interaction with the sphere while larger particles have smaller diffusion constant but stronger interaction with the sphere. Since the hydrodynamic radius is also determined by the particle shape, an optimal hydrodynamic radius implies an optimal size as well as an optimal aspect ratio for a nonspherical particle. These results show broad agreement with experimental observations and may have general implications on interaction between nanoparticles and animal cells.

Size and shape effects on diffusion and absorption of colloidal particles near a partially absorbing sphere: Implications for uptake of nanoparticles in animal cells

NASA Astrophysics Data System (ADS)

Shi, Wendong; Wang, Jizeng; Fan, Xiaojun; Gao, Huajian

2008-12-01

A mechanics model describing how a cell membrane with diffusive mobile receptors wraps around a ligand-coated cylindrical or spherical particle has been recently developed to model the role of particle size in receptor-mediated endocytosis. The results show that particles in the size range of tens to hundreds of nanometers can enter cells even in the absence of clathrin or caveolin coats. Here we report further progress on modeling the effects of size and shape in diffusion, interaction, and absorption of finite-sized colloidal particles near a partially absorbing sphere. Our analysis indicates that, from the diffusion and interaction point of view, there exists an optimal hydrodynamic size of particles, typically in the nanometer regime, for the maximum rate of particle absorption. Such optimal size arises as a result of balance between the diffusion constant of the particles and the interaction energy between the particles and the absorbing sphere relative to the thermal energy. Particles with a smaller hydrodynamic radius have larger diffusion constant but weaker interaction with the sphere while larger particles have smaller diffusion constant but stronger interaction with the sphere. Since the hydrodynamic radius is also determined by the particle shape, an optimal hydrodynamic radius implies an optimal size as well as an optimal aspect ratio for a nonspherical particle. These results show broad agreement with experimental observations and may have general implications on interaction between nanoparticles and animal cells.

Stochastic modelling of slow-progressing tumors: Analysis and applications to the cell interplay and control of low grade gliomas

NASA Astrophysics Data System (ADS)

Rodríguez, Clara Rojas; Fernández Calvo, Gabriel; Ramis-Conde, Ignacio; Belmonte-Beitia, Juan

2017-08-01

Tumor-normal cell interplay defines the course of a neoplastic malignancy. The outcome of this dual relation is the ultimate prevailing of one of the cells and the death or retreat of the other. In this paper we study the mathematical principles that underlay one important scenario: that of slow-progressing cancers. For this, we develop, within a stochastic framework, a mathematical model to account for tumor-normal cell interaction in such a clinically relevant situation and derive a number of deterministic approximations from the stochastic model. We consider in detail the existence and uniqueness of the solutions of the deterministic model and study the stability analysis. We then focus our model to the specific case of low grade gliomas, where we introduce an optimal control problem for different objective functionals under the administration of chemotherapy. We derive the conditions for which singular and bang-bang control exist and calculate the optimal control and states.

Optimization of life support systems and their systems reliability

NASA Technical Reports Server (NTRS)

Fan, L. T.; Hwang, C. L.; Erickson, L. E.

1971-01-01

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

Modeling, simulation and optimization of a no-chamber solid oxide fuel cell operated with a flat-flame burner

NASA Astrophysics Data System (ADS)

Vogler, Marcel; Horiuchi, Michio; Bessler, Wolfgang G.

A detailed computational model of a direct-flame solid oxide fuel cell (DFFC) is presented. The DFFC is based on a fuel-rich methane-air flame stabilized on a flat-flame burner and coupled to a solid oxide fuel cell (SOFC). The model consists of an elementary kinetic description of the premixed methane-air flame, a stagnation-point flow description of the coupled heat and mass transport within the gas phase, an elementary kinetic description of the electrochemistry, as well as heat, mass and charge transport within the SOFC. Simulated current-voltage characteristics show excellent agreement with experimental data published earlier (Kronemayer et al., 2007 [10]). The model-based analysis of loss processes reveals that ohmic resistance in the current collection wires dominates polarization losses, while electronic loss currents in the mixed conducting electrolyte have only little influence on the polarized cell. The model was used to propose an optimized cell design. Based on this analysis, power densities of above 200 mW cm -2 can be expected.

Optimal control of fuel overpressure in a polymer electrolyte membrane fuel cell with hydrogen transfer leak during load change

NASA Astrophysics Data System (ADS)

Ebadighajari, Alireza; DeVaal, Jake; Golnaraghi, Farid

2017-02-01

Formation of membrane pinholes is a common defect in fuel cells, inflicting more cost and making less durable cells. This work focuses on mitigating this issue, and offers a continuous online treatment instead of attempting to dynamically model the hydrogen transfer leak rate. This is achieved by controlling the differential pressure between the anode and cathode compartments at the inlet side of the fuel cell stack, known as the fuel overpressure. The model predictive control approach is used to attain the objectives in a Ballard 9-cell Mk1100 polymer electrolyte membrane fuel cell (PEMFC) with inclusion of hydrogen transfer leak. Furthermore, the pneumatic modeling technique is used to model the entire anode side of a fuel cell station. The hydrogen transfer leak is embedded in the model in a novel way, and is considered as a disturbance during the controller design. Experimental results for different sizes of hydrogen transfer leaks are provided to show the benefits of fuel overpressure control system in alleviating the effects of membrane pinholes, which in turn increases membrane longevity, and reduces hydrogen emissions in the eventual presence of transfer leaks. Moreover, the model predictive controller provides an optimal control input while satisfying the problem constraints.

Unconventional bearing capacity analysis and optimization of multicell box girders.

PubMed

Tepic, Jovan; Doroslovacki, Rade; Djelosevic, Mirko

2014-01-01

This study deals with unconventional bearing capacity analysis and the procedure of optimizing a two-cell box girder. The generalized model which enables the local stress-strain analysis of multicell girders was developed based on the principle of cross-sectional decomposition. The applied methodology is verified using the experimental data (Djelosevic et al., 2012) for traditionally formed box girders. The qualitative and quantitative evaluation of results obtained for the two-cell box girder is realized based on comparative analysis using the finite element method (FEM) and the ANSYS v12 software. The deflection function obtained by analytical and numerical methods was found consistent provided that the maximum deviation does not exceed 4%. Multicell box girders are rationally designed support structures characterized by much lower susceptibility of their cross-sectional elements to buckling and higher specific capacity than traditionally formed box girders. The developed local stress model is applied for optimizing the cross section of a two-cell box carrier. The author points to the advantages of implementing the model of local stresses in the optimization process and concludes that the technological reserve of bearing capacity amounts to 20% at the same girder weight and constant load conditions.

Two-Step Production of Phenylpyruvic Acid from L-Phenylalanine by Growing and Resting Cells of Engineered Escherichia coli: Process Optimization and Kinetics Modeling

PubMed Central

Hou, Ying; Hossain, Gazi Sakir; Li, Jianghua; Shin, Hyun-dong; Liu, Long; Du, Guocheng; Chen, Jian

2016-01-01

Phenylpyruvic acid (PPA) is widely used in the pharmaceutical, food, and chemical industries. Here, a two-step bioconversion process, involving growing and resting cells, was established to produce PPA from l-phenylalanine using the engineered Escherichia coli constructed previously. First, the biotransformation conditions for growing cells were optimized (l-phenylalanine concentration 20.0 g·L−1, temperature 35°C) and a two-stage temperature control strategy (keep 20°C for 12 h and increase the temperature to 35°C until the end of biotransformation) was performed. The biotransformation conditions for resting cells were then optimized in 3-L bioreactor and the optimized conditions were as follows: agitation speed 500 rpm, aeration rate 1.5 vvm, and l-phenylalanine concentration 30 g·L−1. The total maximal production (mass conversion rate) reached 29.8 ± 2.1 g·L−1 (99.3%) and 75.1 ± 2.5 g·L−1 (93.9%) in the flask and 3-L bioreactor, respectively. Finally, a kinetic model was established, and it was revealed that the substrate and product inhibition were the main limiting factors for resting cell biotransformation. PMID:27851793

A Computational Approach for Model Update of an LS-DYNA Energy Absorbing Cell

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Jackson, Karen E.; Kellas, Sotiris

2008-01-01

NASA and its contractors are working on structural concepts for absorbing impact energy of aerospace vehicles. Recently, concepts in the form of multi-cell honeycomb-like structures designed to crush under load have been investigated for both space and aeronautics applications. Efforts to understand these concepts are progressing from tests of individual cells to tests of systems with hundreds of cells. Because of fabrication irregularities, geometry irregularities, and material properties uncertainties, the problem of reconciling analytical models, in particular LS-DYNA models, with experimental data is a challenge. A first look at the correlation results between single cell load/deflection data with LS-DYNA predictions showed problems which prompted additional work in this area. This paper describes a computational approach that uses analysis of variance, deterministic sampling techniques, response surface modeling, and genetic optimization to reconcile test with analysis results. Analysis of variance provides a screening technique for selection of critical parameters used when reconciling test with analysis. In this study, complete ignorance of the parameter distribution is assumed and, therefore, the value of any parameter within the range that is computed using the optimization procedure is considered to be equally likely. Mean values from tests are matched against LS-DYNA solutions by minimizing the square error using a genetic optimization. The paper presents the computational methodology along with results obtained using this approach.

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

PubMed

Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

2017-01-01

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Development of transferrin targeted NCL-240 micelles and their evaluation using in-vitro 3D cancer cell culture (spheroid) models

NASA Astrophysics Data System (ADS)

Nagelli, Srikar Goud

The main objective of this project was to develop targeted micellar delivery systems of a novel cytotoxic drug (NCL-240; a second generation DM-PIT-1 analog) and to evaluate their efficacy using optimized 3D cell culture spheroid models. Spheroids were optimized for several cancer cell lines using a range of techniques such as non-adhesive liquid overlay method, hanging drop method, and co-culturing. Transferrin (Tf)-conjugated NCL-240 micelles were prepared with varying Tf amounts and their cytotoxicities were evaluated using the optimized spheroid models. The uptake and penetration of the formulations were also studied using confocal microscopy. The results indicated that the concentration of NCL-240 micelles required to achieve the same cytotoxicity was relatively higher in spheroids compared to the monolayers. Also, In NCI-ADR-RES, Tf-targeted NCL-240 micelles were shown to have a significant increase in cytotoxicity compared to untargeted NCL-240 micelles. Even the penetration and uptake studies indicated that targeting improves the uptake and penetration of formulations. However, in U87-MG spheroids, there was a significant difference in cell viability among micelles compared to free drug but no significant benefit due to targeting was observed. The same formulations penetrated lesser in U87-MG spheroids compared to NCI-ADR-RES spheroids. This study thereby emphasizes the importance of drug screening in spheroid models as the penetration dynamics are varying from cell line to cell line because of the 3D structure.

Optimization of the antireflection coating of thin epitaxial crystalline silicon solar cells

DOE PAGES

Selj, Josefine K.; Young, David; Grover, Sachit

2015-08-28

In this study we use an effective weighting function to include the internal quantum efficiency (IQE) and the effective thickness, Te, of the active cell layer in the optical modeling of the antireflection coating (ARC) of very thin crystalline silicon solar cells. The spectrum transmitted through the ARC is hence optimized for efficient use in the given cell structure and the solar cell performance can be improved. For a 2-μm thick crystalline silicon heterojunction solar cell the optimal thickness of the Indium Tin Oxide (ITO) ARC is reduced by ~8 nm when IQE data and effective thickness are taken intomore » account compared to the standard ARC optimization, using the AM1.5 spectrum only. The reduced ARC thickness will shift the reflectance minima towards shorter wavelengths and hence better match the absorption of very thin cells, where the short wavelength range of the spectrum is relatively more important than the long, weakly absorbed wavelengths. For this cell, we find that the optimal thickness of the ITO starts at 63 nm for very thin (1 μm) active Si layer and then increase with increasing T e until it saturates at 71 nm for T e > 30 μm.« less

Magnetic manipulation device for the optimization of cell processing conditions.

PubMed

Ito, Hiroshi; Kato, Ryuji; Ino, Kosuke; Honda, Hiroyuki

2010-02-01

Variability in human cell phenotypes make it's advancements in optimized cell processing necessary for personalized cell therapy. Here we propose a strategy of palm-top sized device to assist physically manipulating cells for optimizing cell preparations. For the design of such a device, we combined two conventional approaches: multi-well plate formatting and magnetic cell handling using magnetite cationic liposomes (MCLs). From our previous works, we showed the labeling applications of MCL on adhesive cells for various tissue engineering approaches. To feasibly transfer cells in multi-well plate, we here evaluated the magnetic response of MCL-labeled suspension type cells. The cell handling performance of Jurkat cells proved to be faster and more robust compared to MACS (Magnetic Cell Sorting) bead methods. To further confirm our strategy, prototype palm-top sized device "magnetic manipulation device (MMD)" was designed. In the device, the actual cell transportation efficacy of Jurkat cells was satisfying. Moreover, as a model of the most distributed clinical cell processing, primary peripheral blood mononuclear cells (PBMCs) from different volunteers were evaluated. By MMD, individual PBMCs indicated to have optimum Interleukin-2 (IL-2) concentrations for the expansion. Such huge differences of individual cells indicated that MMD, our proposing efficient and self-contained support tool, could assist the feasible and cost-effective optimization of cell processing in clinical facilities. Copyright (c) 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image

PubMed Central

Wang, Xin; Sommer, Friedrich T.; Hirsch, Judith A.

2014-01-01

Summary It is widely assumed that mosaics of retinal ganglion cells establish the optimal representation of visual space. However, relay cells in the visual thalamus often receive convergent input from several retinal afferents and, in cat, outnumber ganglion cells. To explore how the thalamus transforms the retinal image, we built a model of the retinothalamic circuit using experimental data and simple wiring rules. The model shows how the thalamus might form a resampled map of visual space with the potential to facilitate detection of stimulus position in the presence of sensor noise. Bayesian decoding conducted with the model provides support for this scenario. Despite its benefits, however, resampling introduces image blur, thus impairing edge perception. Whole-cell recordings obtained in vivo suggest that this problem is mitigated by arrangements of excitation and inhibition within the receptive field that effectively boost contrast borders, much like strategies used in digital image processing. PMID:24559681

Optimization of bead milling parameters for the cell disruption of microalgae: process modeling and application to Porphyridium cruentum and Nannochloropsis oculata.

PubMed

Montalescot, V; Rinaldi, T; Touchard, R; Jubeau, S; Frappart, M; Jaouen, P; Bourseau, P; Marchal, L

2015-11-01

A study of cell disruption by bead milling for two microalgae, Nannochloropsis oculata and Porphyridium cruentum, was performed. Strains robustness was quantified by high-pressure disruption assays. The hydrodynamics in the bead mill grinding chamber was studied by Residence Time Distribution modeling. Operating parameters effects were analyzed and modeled in terms of stress intensities and stress number. RTD corresponded to a 2 CSTR in series model. First order kinetics cell disruption was modeled in consequence. Continuous bead milling was efficient for both strains disruption. SI-SN modeling was successfully adapted to microalgae. As predicted by high pressure assays, N. oculata was more resistant than P. cruentum. The critical stress intensity was twice more important for N. oculata than for P. cruentum. SI-SN modeling allows the determination of operating parameters minimizing energy consumption and gives a scalable approach to develop and optimize microalgal disruption by bead milling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimal control of a repowered vehicle: Plug-in fuel cell against plug-in hybrid electric powertrain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tribioli, L., E-mail: laura.tribioli@unicusano.it; Cozzolino, R.; Barbieri, M.

2015-03-10

This paper describes two different powertrain configurations for the repowering of a conventional vehicle, equipped with an internal combustion engine (ICE). A model of a mid-sized ICE-vehicle is realized and then modified to model both a parallel plug-in hybrid electric powertrain and a proton electrolyte membrane (PEM) fuel cell (FC) hybrid powertrain. The vehicle behavior under the application of an optimal control algorithm for the energy management is analyzed for the different scenarios and results are compared.

Metabolic regulation and maximal reaction optimization in the central metabolism of a yeast cell

NASA Astrophysics Data System (ADS)

Kasbawati, Gunawan, A. Y.; Hertadi, R.; Sidarto, K. A.

2015-03-01

Regulation of fluxes in a metabolic system aims to enhance the production rates of biotechnologically important compounds. Regulation is held via modification the cellular activities of a metabolic system. In this study, we present a metabolic analysis of ethanol fermentation process of a yeast cell in terms of continuous culture scheme. The metabolic regulation is based on the kinetic formulation in combination with metabolic control analysis to indicate the key enzymes which can be modified to enhance ethanol production. The model is used to calculate the intracellular fluxes in the central metabolism of the yeast cell. Optimal control is then applied to the kinetic model to find the optimal regulation for the fermentation system. The sensitivity results show that there are external and internal control parameters which are adjusted in enhancing ethanol production. As an external control parameter, glucose supply should be chosen in appropriate way such that the optimal ethanol production can be achieved. For the internal control parameter, we find three enzymes as regulation targets namely acetaldehyde dehydrogenase, pyruvate decarboxylase, and alcohol dehydrogenase which reside in the acetaldehyde branch. Among the three enzymes, however, only acetaldehyde dehydrogenase has a significant effect to obtain optimal ethanol production efficiently.

Optimized shielding for space radiation protection

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Cucinotta, F. A.; Kim, M. H.; Schimmerling, W.

2001-01-01

Future deep space mission and International Space Station exposures will be dominated by the high-charge and -energy (HZE) ions of the Galactic Cosmic Rays (GCR). A few mammalian systems have been extensively tested over a broad range of ion types and energies. For example, C3H10T1/2 cells, V79 cells, and Harderian gland tumors have been described by various track-structure dependent response models. The attenuation of GCR induced biological effects depends strongly on the biological endpoint, response model used, and material composition. Optimization of space shielding is then driven by the nature of the response model and the transmission characteristics of the given material.

Optimized Shielding for Space Radiation Protection

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Cucinotta, F. A.; Kim, M.-H. Y.; Schimmerling, W.

2000-01-01

Abstract. Future deep space mission and International Space Station exposures will be dominated by the high-charge and -energy (HZE) ions of the Galactic Cosmic Rays (GCR). A few mammalian systems have been extensively tested over a broad range of ion types and energies. For example, C3H10T1/2 cells, V79 cells, and Harderian gland tumors have been described by various track-structure dependent response models. The attenuation of GCR induced biological effects depends strongly on the biological endpoint, response model used, and material composition. Optimization of space shielding is then driven by the nature of the response model and the transmission characteristics of the given material.

Optimal robust control strategy of a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Wu, Xiaojuan; Gao, Danhui

2018-01-01

Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.

Optimization of Dosing for EGFR-Mutant Non–Small Cell Lung Cancer with Evolutionary Cancer Modeling

PubMed Central

Chmielecki, Juliann; Foo, Jasmine; Oxnard, Geoffrey R.; Hutchinson, Katherine; Ohashi, Kadoaki; Somwar, Romel; Wang, Lu; Amato, Katherine R.; Arcila, Maria; Sos, Martin L.; Socci, Nicholas D.; Viale, Agnes; de Stanchina, Elisa; Ginsberg, Michelle S.; Thomas, Roman K.; Kris, Mark G.; Inoue, Akira; Ladanyi, Marc; Miller, Vincent A.; Michor, Franziska; Pao, William

2012-01-01

Non–small cell lung cancers (NSCLCs) that harbor mutations within the epidermal growth factor receptor (EGFR) gene are sensitive to the tyrosine kinase inhibitors (TKIs) gefitinib and erlotinib. Unfortunately, all patients treated with these drugs will acquire resistance, most commonly as a result of a secondary mutation within EGFR (T790M). Because both drugs were developed to target wild-type EGFR, we hypothesized that current dosing schedules were not optimized for mutant EGFR or to prevent resistance. To investigate this further, we developed isogenic TKI-sensitive and TKI-resistant pairs of cell lines that mimic the behavior of human tumors. We determined that the drug-sensitive and drug-resistant EGFR-mutant cells exhibited differential growth kinetics, with the drug-resistant cells showing slower growth. We incorporated these data into evolutionary mathematical cancer models with constraints derived from clinical data sets. This modeling predicted alternative therapeutic strategies that could prolong the clinical benefit of TKIs against EGFR-mutant NSCLCs by delaying the development of resistance. PMID:21734175

Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2016-01-01

Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

Optimization of a new flow design for solid oxide cells using computational fluid dynamics modelling

NASA Astrophysics Data System (ADS)

Duhn, Jakob Dragsbæk; Jensen, Anker Degn; Wedel, Stig; Wix, Christian

2016-12-01

Design of a gas distributor to distribute gas flow into parallel channels for Solid Oxide Cells (SOC) is optimized, with respect to flow distribution, using Computational Fluid Dynamics (CFD) modelling. The CFD model is based on a 3d geometric model and the optimized structural parameters include the width of the channels in the gas distributor and the area in front of the parallel channels. The flow of the optimized design is found to have a flow uniformity index value of 0.978. The effects of deviations from the assumptions used in the modelling (isothermal and non-reacting flow) are evaluated and it is found that a temperature gradient along the parallel channels does not affect the flow uniformity, whereas a temperature difference between the channels does. The impact of the flow distribution on the maximum obtainable conversion during operation is also investigated and the obtainable overall conversion is found to be directly proportional to the flow uniformity. Finally the effect of manufacturing errors is investigated. The design is shown to be robust towards deviations from design dimensions of at least ±0.1 mm which is well within obtainable tolerances.

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.

Subzero water permeability parameters and optimal freezing rates for sperm cells of the southern platyfish, Xiphophorus maculatus.

PubMed

Pinisetty, D; Huang, C; Dong, Q; Tiersch, T R; Devireddy, R V

2005-06-01

This study reports the subzero water transport characteristics (and empirically determined optimal rates for freezing) of sperm cells of live-bearing fishes of the genus Xiphophorus, specifically those of the southern platyfish Xiphophorus maculatus. These fishes are valuable models for biomedical research and are commercially raised as ornamental fish for use in aquariums. Water transport during freezing of X. maculatus sperm cell suspensions was obtained using a shape-independent differential scanning calorimeter technique in the presence of extracellular ice at a cooling rate of 20 degrees C/min in three different media: (1) Hanks' balanced salt solution (HBSS) without cryoprotective agents (CPAs); (2) HBSS with 14% (v/v) glycerol, and (3) HBSS with 10% (v/v) dimethyl sulfoxide (DMSO). The sperm cell was modeled as a cylinder with a length of 52.35 microm and a diameter of 0.66 microm with an osmotically inactive cell volume (Vb) of 0.6 V0, where V0 is the isotonic or initial cell volume. This translates to a surface area, SA to initial water volume, WV ratio of 15.15 microm(-1). By fitting a model of water transport to the experimentally determined volumetric shrinkage data, the best fit membrane permeability parameters (reference membrane permeability to water at 0 degrees C, Lpg or Lpg [cpa] and the activation energy, E(Lp) or E(Lp) [cpa]) were found to range from: Lpg or Lpg [cpa] = 0.0053-0.0093 microm/minatm; E(Lp) or E(Lp) [cpa] = 9.79-29.00 kcal/mol. By incorporating these membrane permeability parameters in a recently developed generic optimal cooling rate equation (optimal cooling rate, [Formula: see text] where the units of B(opt) are degrees C/min, E(Lp) or E(Lp) [cpa] are kcal/mol, L(pg) or L(pg) [cpa] are microm/minatm and SA/WV are microm(-1)), we determined the optimal rates of freezing X. maculatus sperm cells to be 28 degrees C/min (in HBSS), 47 degrees C/min (in HBSS+14% glycerol) and 36 degrees C/min (in HBSS+10% DMSO). Preliminary empirical experiments suggest that the optimal rate of freezing X. maculatus sperm in the presence of 14% glycerol to be approximately 25 degrees C/min. Possible reasons for the observed discrepancy between the theoretically predicted and experimentally determined optimal rates of freezing X. maculatus sperm cells are discussed.

Optimization and comprehensive characterization of a faithful tissue culture model of the benign and malignant human prostate.

PubMed

Maund, Sophia Lisette; Nolley, Rosalie; Peehl, Donna Mae

2014-02-01

Few preclinical models accurately depict normal human prostate tissue or primary prostate cancer (PCa). In vitro systems typically lack complex cellular interactions among structured prostatic epithelia and a stromal microenvironment, and genetic and molecular fidelity are concerns in both in vitro and in vivo models. 'Tissue slice cultures' (TSCs) provide realistic preclinical models of diverse tissues and organs, but have not been fully developed or widely utilized for prostate studies. Problems encountered include degeneration of differentiated secretory cells, basal cell hyperplasia, and poor survival of PCa. Here, we optimized, characterized, and applied a TSC model of primary human PCa and benign prostate tissue that overcomes many deficiencies of current in vitro models. Tissue cores from fresh prostatectomy specimens were precision-cut at 300 μm and incubated in a rotary culture apparatus. The ability of varied culture conditions to faithfully maintain benign and cancer cell and tissue structure and function over time was evaluated by immunohistological and biochemical assays. After optimization of the culture system, molecular and cellular responses to androgen ablation and to piperlongumine (PL), purported to specifically reduce androgen signaling in PCa, were investigated. Optimized culture conditions successfully maintained the structural and functional fidelity of both benign and PCa TSCs for 5 days. TSCs exhibited androgen dependence, appropriately undergoing ductal degeneration, reduced proliferation, and decreased prostate-specific antigen expression upon androgen ablation. Further, TSCs revealed cancer-specific reduction of androgen receptor and increased apoptosis upon treatment with PL, validating data from cell lines. We demonstrate a TSC model that authentically recapitulates the structural, cellular, and genetic characteristics of the benign and malignant human prostate, androgen dependence of the native tissue, and cancer-specific response to a potentially new therapeutic for PCa. The work described herein provides a basis for advancing the experimental utility of the TSC model.

Pharmacokinetic-Pharmacodynamic Modeling of the Anti-Tumor Effect of Sunitinib Combined with Dopamine in the Human Non-Small Cell Lung Cancer Xenograft.

PubMed

Hao, Fangran; Wang, Siyuan; Zhu, Xiao; Xue, Junsheng; Li, Jingyun; Wang, Lijie; Li, Jian; Lu, Wei; Zhou, Tianyan

2017-02-01

To investigate the anti-tumor effect of sunitinib in combination with dopamine in the treatment of nu/nu nude mice bearing non-small cell lung cancer (NSCLC) A549 cells and to develop the combination PK/PD model. Further, simulations were conducted to optimize the administration regimens. A PK/PD model was developed based on our preclinical experiment to explore the relationship between plasma concentration and drug effect quantitatively. Further, the model was evaluated and validated. By fixing the parameters obtained from the PK/PD model, simulations were built to predict the tumor suppression under various regimens. The synergistic effect was observed between sunitinib and dopamine in the study, which was confirmed by the effect constant (GAMA, estimated as 2.49). The enhanced potency of dopamine on sunitinib was exerted by on/off effect in the PK/PD model. The optimal dose regimen was selected as sunitinib (120 mg/kg, q3d) in combination with dopamine (2 mg/kg, q3d) based on the simulation study. The synergistic effect of sunitinib and dopamine was demonstrated by the preclinical experiment and confirmed by the developed PK/PD model. In addition, the regimens were optimized by means of modeling as well as simulation, which may be conducive to clinical study.

Fuzzy control based engine sizing optimization for a fuel cell/battery hybrid mini-bus

NASA Astrophysics Data System (ADS)

Kim, Minjin; Sohn, Young-Jun; Lee, Won-Yong; Kim, Chang-Soo

The fuel cell/battery hybrid vehicle has been focused for the alternative engine of the existing internal-combustion engine due to the following advantages of the fuel cell and the battery. Firstly, the fuel cell is highly efficient and eco-friendly. Secondly, the battery has the fast response for the changeable power demand. However, the competitive efficiency of the hybrid fuel cell vehicle is necessary to successfully alternate the conventional vehicles with the fuel cell hybrid vehicle. The most relevant factor which affects the overall efficiency of the hybrid fuel cell vehicle is the relative engine sizing between the fuel cell and the battery. Therefore the design method to optimize the engine sizing of the fuel cell hybrid vehicle has been proposed. The target system is the fuel cell/battery hybrid mini-bus and its power distribution is controlled based on the fuzzy logic. The optimal engine sizes are determined based on the simulator developed in this paper. The simulator includes the several models for the fuel cell, the battery, and the major balance of plants. After the engine sizing, the system efficiency and the stability of the power distribution are verified based on the well-known driving schedule. Consequently, the optimally designed mini-bus shows good performance.

Adaptive non-linear control for cancer therapy through a Fokker-Planck observer.

PubMed

Shakeri, Ehsan; Latif-Shabgahi, Gholamreza; Esmaeili Abharian, Amir

2018-04-01

In recent years, many efforts have been made to present optimal strategies for cancer therapy through the mathematical modelling of tumour-cell population dynamics and optimal control theory. In many cases, therapy effect is included in the drift term of the stochastic Gompertz model. By fitting the model with empirical data, the parameters of therapy function are estimated. The reported research works have not presented any algorithm to determine the optimal parameters of therapy function. In this study, a logarithmic therapy function is entered in the drift term of the Gompertz model. Using the proposed control algorithm, the therapy function parameters are predicted and adaptively adjusted. To control the growth of tumour-cell population, its moments must be manipulated. This study employs the probability density function (PDF) control approach because of its ability to control all the process moments. A Fokker-Planck-based non-linear stochastic observer will be used to determine the PDF of the process. A cost function based on the difference between a predefined desired PDF and PDF of tumour-cell population is defined. Using the proposed algorithm, the therapy function parameters are adjusted in such a manner that the cost function is minimised. The existence of an optimal therapy function is also proved. The numerical results are finally given to demonstrate the effectiveness of the proposed method.

Reversals and collisions optimize protein exchange in bacterial swarms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy

Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as amechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthusmore » optimizes the connection rate between cells and maximizes the spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that predesigned motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.« less

Optimization of fuel-cell tram operation based on two dimension dynamic programming

NASA Astrophysics Data System (ADS)

Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu

2018-02-01

This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.

Simulation study of GaAsP/Si tandem cells including the impact of threading dislocations on the luminescent coupling between the cells

NASA Astrophysics Data System (ADS)

Onno, Arthur; Harder, Nils-Peter; Oberbeck, Lars; Liu, Huiyun

2016-03-01

A model, derived from the detailed balance model from Shockley and Queisser, has been adapted to monolithically grown GaAsP/Si tandem dual junction solar cells. In this architecture, due to the difference of lattice parameters between the silicon bottom cell - acting as the substrate - and the GaAsP top cell, threading dislocations (TDs) arise at the IIIV/ Si interface and propagate in the top cell. These TDs act as non-radiative recombination centers, degrading the performances of the tandem cell. Our model takes into account the impact of TDs by integrating the NTT model developed by Yamaguchi et. al.. Two surface geometries have been investigated: flat and ideally textured. Finally the model considers the luminescent coupling (LC) between the cells due to reemitted photons from the top cell cascading to the bottom cell. Without dislocations, LC allows a greater flexibility in the cell design by rebalancing the currents between the two cells when the top cell presents a higher short-circuit current. However we show that, as the TD density (TDD) increases, nonradiative recombinations take over radiative recombinations in the top cell and the LC is quenched. As a result, nonoptimized tandem cells with higher short-circuit current in the top cell experience a very fast degradation of efficiency for TDDs over 104cm-2. On the other hand optimized cells with matching currents only experience a small efficiency drop for TDDs up to 105cm-2. High TDD cells therefore need to be current-matched for optimal performances as the flexibility due to LC is lost.

Determination of optimal parameters for dual-layer cathode of polymer electrolyte fuel cell using computational intelligence-aided design.

PubMed

Chen, Yi; Huang, Weina; Peng, Bei

2014-01-01

Because of the demands for sustainable and renewable energy, fuel cells have become increasingly popular, particularly the polymer electrolyte fuel cell (PEFC). Among the various components, the cathode plays a key role in the operation of a PEFC. In this study, a quantitative dual-layer cathode model was proposed for determining the optimal parameters that minimize the over-potential difference η and improve the efficiency using a newly developed bat swarm algorithm with a variable population embedded in the computational intelligence-aided design. The simulation results were in agreement with previously reported results, suggesting that the proposed technique has potential applications for automating and optimizing the design of PEFCs.

The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

NASA Astrophysics Data System (ADS)

Guan, Yujuan; Zhang, Liquan

2006-10-01

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Predicting the optimal geometry of microneedles and their array for dermal vaccination using a computational model.

PubMed

Römgens, Anne M; Bader, Dan L; Bouwstra, Joke A; Oomens, Cees W J

2016-11-01

Microneedle arrays have been developed to deliver a range of biomolecules including vaccines into the skin. These microneedles have been designed with a wide range of geometries and arrangements within an array. However, little is known about the effect of the geometry on the potency of the induced immune response. The aim of this study was to develop a computational model to predict the optimal design of the microneedles and their arrangement within an array. The three-dimensional finite element model described the diffusion and kinetics in the skin following antigen delivery with a microneedle array. The results revealed an optimum distance between microneedles based on the number of activated antigen presenting cells, which was assumed to be related to the induced immune response. This optimum depends on the delivered dose. In addition, the microneedle length affects the number of cells that will be involved in either the epidermis or dermis. By contrast, the radius at the base of the microneedle and release rate only minimally influenced the number of cells that were activated. The model revealed the importance of various geometric parameters to enhance the induced immune response. The model can be developed further to determine the optimal design of an array by adjusting its various parameters to a specific situation.

WE-H-BRA-03: Development of a Model to Include the Evolution of Resistant Tumor Subpopulations Into the Treatment Optimization Process for Schedules Involving Targeted Agents in Chemoradiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grassberger, C; Paganetti, H

Purpose: To develop a model that includes the process of resistance development into the treatment optimization process for schedules that include targeted therapies. Further, to validate the approach using clinical data and to apply the model to assess the optimal induction period with targeted agents before curative treatment with chemo-radiation in stage III lung cancer. Methods: Growth of the tumor and its subpopulations is modeled by Gompertzian growth dynamics, resistance induction as a stochastic process. Chemotherapy induced cell kill is modeled by log-cell kill dynamics, targeted agents similarly but restricted to the sensitive population. Radiation induced cell kill is assumedmore » to follow the linear-quadratic model. The validation patient data consist of a cohort of lung cancer patients treated with tyrosine kinase inhibitors that had longitudinal imaging data available. Results: The resistance induction model was successfully validated using clinical trial data from 49 patients treated with targeted agents. The observed recurrence kinetics, with tumors progressing from 1.4–63 months, result in tumor growth equaling a median volume doubling time of 92 days [34–248] and a median fraction of pre-existing resistance of 0.035 [0–0.22], in agreement with previous clinical studies. The model revealed widely varying optimal time points for the use of curative therapy, reaching from ∼1m to >6m depending on the patient’s growth rate and amount of pre-existing resistance. This demonstrates the importance of patient-specific treatment schedules when targeted agents are incorporated into the treatment. Conclusion: We developed a model including evolutionary dynamics of resistant sub-populations with traditional chemotherapy and radiation cell kill models. Fitting to clinical data yielded patient specific growth rates and resistant fraction in agreement with previous studies. Further application of the model demonstrated how proper timing of chemo-radiation could minimize the probability of resistance, increasing tumor control significantly.« less

An application of PSO algorithm for multi-criteria geometry optimization of printed low-pass filters based on conductive periodic structures

NASA Astrophysics Data System (ADS)

Steckiewicz, Adam; Butrylo, Boguslaw

2017-08-01

In this paper we discussed the results of a multi-criteria optimization scheme as well as numerical calculations of periodic conductive structures with selected geometry. Thin printed structures embedded on a flexible dielectric substrate may be applied as simple, cheap, passive low-pass filters with an adjustable cutoff frequency in low (up to 1 MHz) radio frequency range. The analysis of an electromagnetic phenomena in presented structures was realized on the basis of a three-dimensional numerical model of three proposed geometries of periodic elements. The finite element method (FEM) was used to obtain a solution of an electromagnetic harmonic field. Equivalent lumped electrical parameters of printed cells obtained in such manner determine the shape of an amplitude transmission characteristic of a low-pass filter. A nonlinear influence of a printed cell geometry on equivalent parameters of cells electric model, makes it difficult to find the desired optimal solution. Therefore an optimization problem of optimal cell geometry estimation with regard to an approximation of the determined amplitude transmission characteristic with an adjusted cutoff frequency, was obtained by the particle swarm optimization (PSO) algorithm. A dynamically suitable inertia factor was also introduced into the algorithm to improve a convergence to a global extremity of a multimodal objective function. Numerical results as well as PSO simulation results were characterized in terms of approximation accuracy of predefined amplitude characteristics in a pass-band, stop-band and cutoff frequency. Three geometries of varying degrees of complexity were considered and their use in signal processing systems was evaluated.

Modeling and Predicting the Electrical Conductivity of Composite Cathode for Solid Oxide Fuel Cell by Using Support Vector Regression

NASA Astrophysics Data System (ADS)

Tang, J. L.; Cai, C. Z.; Xiao, T. T.; Huang, S. J.

2012-07-01

The electrical conductivity of solid oxide fuel cell (SOFC) cathode is one of the most important indices affecting the efficiency of SOFC. In order to improve the performance of fuel cell system, it is advantageous to have accurate model with which one can predict the electrical conductivity. In this paper, a model utilizing support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter optimization was established to modeling and predicting the electrical conductivity of Ba0.5Sr0.5Co0.8Fe0.2 O3-δ-xSm0.5Sr0.5CoO3-δ (BSCF-xSSC) composite cathode under two influence factors, including operating temperature (T) and SSC content (x) in BSCF-xSSC composite cathode. The leave-one-out cross validation (LOOCV) test result by SVR strongly supports that the generalization ability of SVR model is high enough. The absolute percentage error (APE) of 27 samples does not exceed 0.05%. The mean absolute percentage error (MAPE) of all 30 samples is only 0.09% and the correlation coefficient (R2) as high as 0.999. This investigation suggests that the hybrid PSO-SVR approach may be not only a promising and practical methodology to simulate the properties of fuel cell system, but also a powerful tool to be used for optimal designing or controlling the operating process of a SOFC system.

Application of response surface methodology to maximize the productivity of scalable automated human embryonic stem cell manufacture.

PubMed

Ratcliffe, Elizabeth; Hourd, Paul; Guijarro-Leach, Juan; Rayment, Erin; Williams, David J; Thomas, Robert J

2013-01-01

Commercial regenerative medicine will require large quantities of clinical-specification human cells. The cost and quality of manufacture is notoriously difficult to control due to highly complex processes with poorly defined tolerances. As a step to overcome this, we aimed to demonstrate the use of 'quality-by-design' tools to define the operating space for economic passage of a scalable human embryonic stem cell production method with minimal cell loss. Design of experiments response surface methodology was applied to generate empirical models to predict optimal operating conditions for a unit of manufacture of a previously developed automatable and scalable human embryonic stem cell production method. Two models were defined to predict cell yield and cell recovery rate postpassage, in terms of the predictor variables of media volume, cell seeding density, media exchange and length of passage. Predicted operating conditions for maximized productivity were successfully validated. Such 'quality-by-design' type approaches to process design and optimization will be essential to reduce the risk of product failure and patient harm, and to build regulatory confidence in cell therapy manufacturing processes.

Magnetic resonance imaging of water content across the Nafion membrane in an operational PEM fuel cell.

PubMed

Zhang, Ziheng; Martin, Jonathan; Wu, Jinfeng; Wang, Haijiang; Promislow, Keith; Balcom, Bruce J

2008-08-01

Water management is critical to optimize the operation of polymer electrolyte membrane fuel cells. At present, numerical models are employed to guide water management in such fuel cells. Accurate measurements of water content variation in polymer electrolyte membrane fuel cells are required to validate these models and to optimize fuel cell behavior. We report a direct water content measurement across the Nafion membrane in an operational polymer electrolyte membrane fuel cell, employing double half k-space spin echo single point imaging techniques. The MRI measurements with T2 mapping were undertaken with a parallel plate resonator to avoid the effects of RF screening. The parallel plate resonator employs the electrodes inherent to the fuel cell to create a resonant circuit at RF frequencies for MR excitation and detection, while still operating as a conventional fuel cell at DC. Three stages of fuel cell operation were investigated: activation, operation and dehydration. Each profile was acquired in 6 min, with 6 microm nominal resolution and a SNR of better than 15.

Mammalian cell culture process for monoclonal antibody production: nonlinear modelling and parameter estimation.

PubMed

Selişteanu, Dan; Șendrescu, Dorin; Georgeanu, Vlad; Roman, Monica

2015-01-01

Monoclonal antibodies (mAbs) are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO) algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies.

Mammalian Cell Culture Process for Monoclonal Antibody Production: Nonlinear Modelling and Parameter Estimation

PubMed Central

Selişteanu, Dan; Șendrescu, Dorin; Georgeanu, Vlad

2015-01-01

Monoclonal antibodies (mAbs) are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO) algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies. PMID:25685797

Optimization of the temporal pattern of applied dose for a single fraction of radiation: Implications for radiation therapy

NASA Astrophysics Data System (ADS)

Altman, Michael B.

The increasing prevalence of intensity modulated radiation therapy (IMRT) as a treatment modality has led to a renewed interest in the potential for interaction between prolonged treatment time, as frequently associated with IMRT, and the underlying radiobiology of the irradiated tissue. A particularly relevant aspect of radiobiology is cell repair capacity, which influences cell survival, and thus directly relates to the ability to control tumors and spare normal tissues. For a single fraction of radiation, the linear quadratic (LQ) model is commonly used to relate the radiation dose to the fraction of cells surviving. The LQ model implies a dependence on two time-related factors which correlate to radiobiological effects: the duration of radiation application, and the functional form of how the dose is applied over that time (the "temporal pattern of applied dose"). Although the former has been well studied, the latter has not. Thus, the goal of this research is to investigate the impact of the temporal pattern of applied dose on the survival of human cells and to explore how the manipulation of this temporal dose pattern may be incorporated into an IMRT-based radiation therapy treatment planning scheme. The hypothesis is that the temporal pattern of applied dose in a single fraction of radiation can be optimized to maximize or minimize cell kill. Furthermore, techniques which utilize this effect could have clinical ramifications. In situations where increased cell kill is desirable, such as tumor control, or limiting the degree of cell kill is important, such as the sparing of normal tissue, temporal sequences of dose which maximize or minimize cell kill (temporally "optimized" sequences) may provide greater benefit than current clinically used radiation patterns. In the first part of this work, an LQ-based modeling analysis of effects of the temporal pattern of dose on cell kill is performed. Through this, patterns are identified for maximizing cell kill for a given radiation pattern by concentrating the highest doses in the middle of a fraction (a "Triangle" pattern), or minimizing cell kill by placing the highest doses near the beginning and end (a "V-shaped" pattern). The conditions under which temporal optimization effects are most acute are also identified: irradiation of low alpha/beta tissues, long fraction durations, and high doses/fx. An in vitro study is then performed which verifies that the temporal effects and trends predicted by the modeling study are clearly manifested in human cells. Following this a phantom which could allow similar in vitro radiobiological experiments in a 3-dimensional clinically-based environment is designed, created, and dosimetrically assessed using TLDs, film, and biological assay-based techniques. The phantom is found to be a useful and versatile tool for such experiments. A scheme for utilizing the phantom in a clinical treatment environment is then developed. This includes a demonstration of prototype methods for optimizing the temporal pattern of applied dose in clinical IMRT plans to manipulate tissue-dependent effects. Looking toward future experimental validation of such plans using the phantom, an analysis of the suitability of biological assays for use in phantom-based in vitro experiments is performed. Finally, a discussion is provided about the steps necessary to integrate temporal optimization into in vivo experiments and ultimately into a clinical radiation therapy environment. If temporal optimization is ultimately shown to have impact in vivo, the successful implementation of the methods developed in this study could enhance the efficacy and care of thousands of patients receiving radiotherapy.

Bacterial growth laws reflect the evolutionary importance of energy efficiency.

PubMed

Maitra, Arijit; Dill, Ken A

2015-01-13

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

Regenerative Fuel Cells for Space Power and Energy Conversion (NaBH4/H2O2 Fuel Cell Development)

NASA Technical Reports Server (NTRS)

Valdez, Thomas I.; Miley, George H.; Luo, Nie; Burton, Rodney; Mather, Joseph; Hawkins, Glenn; Byrd, Ethan; Gu, Lifeng; Shrestha, Prajakti Joshi

2006-01-01

A viewgraph presentation describing hydrogen peroxide and sodium borohydride development is shown. The topics include: 1) Motivation; 2) The Sodium Borohydride Fuel Cell; 3) Fuel Cell Comparisons; 4) MEA Optimization; 5) 500-Watt Stack Testing; 6) System Modeling: Fuel Cell Power Source for Lunar Rovers; and 7) Conclusions

Optimized depletion of chimeric antigen receptor T cells in murine xenograft models of human acute myeloid leukemia

PubMed Central

Kenderian, Saad S.; Shen, Feng; Ruella, Marco; Shestova, Olga; Kozlowski, Miroslaw; Li, Yong; Schrank-Hacker, April; Morrissette, Jennifer J. D.; Carroll, Martin; June, Carl H.; Grupp, Stephan A.; Gill, Saar

2017-01-01

We and others previously reported potent antileukemia efficacy of CD123-redirected chimeric antigen receptor (CAR) T cells in preclinical human acute myeloid leukemia (AML) models at the cost of severe hematologic toxicity. This observation raises concern for potential myeloablation in patients with AML treated with CD123-redirected CAR T cells and mandates novel approaches for toxicity mitigation. We hypothesized that CAR T-cell depletion with optimal timing after AML eradication would preserve leukemia remission and allow subsequent hematopoietic stem cell transplantation. To test this hypothesis, we compared 3 CAR T-cell termination strategies: (1) transiently active anti-CD123 messenger RNA–electroporated CART (RNA-CART123); (2) T-cell ablation with alemtuzumab after treatment with lentivirally transduced anti–CD123-4-1BB-CD3ζ T cells (CART123); and (3) T-cell ablation with rituximab after treatment with CD20-coexpressing CART123 (CART123-CD20). All approaches led to rapid leukemia elimination in murine xenograft models of human AML. Subsequent antibody-mediated depletion of CART123 or CART123-CD20 did not impair leukemia remission. Time-course studies demonstrated that durable leukemia remission required CAR T-cell persistence for 4 weeks prior to ablation. Upon CAR T-cell termination, we further demonstrated successful hematopoietic engraftment with a normal human donor to model allogeneic stem cell rescue. Results from these studies will facilitate development of T-cell depletion strategies to augment the feasibility of CAR T-cell therapy for patients with AML. PMID:28246194

Design and Optimization of Copper Indium Gallium Selenide Thin Film Solar Cells

DTIC Science & Technology

2015-09-01

determined by the intensity of the illumination that the solar cell is exposed to. The diffusion lengths L can be further defined by n n nL D τ...absorbers with graded Ga concentrations. (3) Back Contact Model Models for back contact silicon solar cells have been created with results that closely...Radiation. New York, NY: Academic Press, 2012. [12] B. Richards, “Enhancing the performance of silicon solar cells via the application of passive

Comparative modeling of InP solar cell structures

NASA Technical Reports Server (NTRS)

Jain, R. K.; Weinberg, I.; Flood, D. J.

1991-01-01

The comparative modeling of p(+)n and n(+)p indium phosphide solar cell structures is studied using a numerical program PC-1D. The optimal design study has predicted that the p(+)n structure offers improved cell efficiencies as compared to n(+)p structure, due to higher open-circuit voltage. The various cell material and process parameters to achieve the maximum cell efficiencies are reported. The effect of some of the cell parameters on InP cell I-V characteristics was studied. The available radiation resistance data on n(+)p and p(+)p InP solar cells are also critically discussed.

Electrochemical model based charge optimization for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Pramanik, Sourav; Anwar, Sohel

2016-05-01

In this paper, we propose the design of a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model that is aimed at improved performance. A performance index that aims at minimizing the charging effort along with a minimum deviation from the rated maximum thresholds for cell temperature and charging current has been defined. The method proposed in this paper aims at achieving a faster charging rate while maintaining safe limits for various battery parameters. Safe operation of the battery is achieved by including the battery bulk temperature as a control component in the performance index which is of critical importance for electric vehicles. Another important aspect of the performance objective proposed here is the efficiency of the algorithm that would allow higher charging rates without compromising the internal electrochemical kinetics of the battery which would prevent abusive conditions, thereby improving the long term durability. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal algorithm as opposed to the conventional equivalent circuit models. To solve the optimization problem, Pontryagins principle has been used which is very effective for constrained optimization problems with both state and input constraints. Simulation results show that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium ion cell while maintaining the temperature constraint when compared with the standard constant current charging. The designed method also maintains the internal states within limits that can avoid abusive operating conditions.

Optimal experimental design for parameter estimation of a cell signaling model.

PubMed

Bandara, Samuel; Schlöder, Johannes P; Eils, Roland; Bock, Hans Georg; Meyer, Tobias

2009-11-01

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

Ensemble engineering and statistical modeling for parameter calibration towards optimal design of microbial fuel cells

NASA Astrophysics Data System (ADS)

Sun, Hongyue; Luo, Shuai; Jin, Ran; He, Zhen

2017-07-01

Mathematical modeling is an important tool to investigate the performance of microbial fuel cell (MFC) towards its optimized design. To overcome the shortcoming of traditional MFC models, an ensemble model is developed through integrating both engineering model and statistical analytics for the extrapolation scenarios in this study. Such an ensemble model can reduce laboring effort in parameter calibration and require fewer measurement data to achieve comparable accuracy to traditional statistical model under both the normal and extreme operation regions. Based on different weight between current generation and organic removal efficiency, the ensemble model can give recommended input factor settings to achieve the best current generation and organic removal efficiency. The model predicts a set of optimal design factors for the present tubular MFCs including the anode flow rate of 3.47 mL min-1, organic concentration of 0.71 g L-1, and catholyte pumping flow rate of 14.74 mL min-1 to achieve the peak current at 39.2 mA. To maintain 100% organic removal efficiency, the anode flow rate and organic concentration should be controlled lower than 1.04 mL min-1 and 0.22 g L-1, respectively. The developed ensemble model can be potentially modified to model other types of MFCs or bioelectrochemical systems.

SU-F-19A-08: Optimal Time Release Schedule of In-Situ Drug Release During Permanent Prostate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cormack, R; Ngwa, W; Makrigiorgos, G

Purpose: Permanent prostate brachytherapy spacers can be used to deliver sustained doses of radiosentitizing drug directly to the target, in order to enhance the radiation effect. Implantable nanoplatforms for chemo-radiation therapy (INCeRTs) have a maximum drug capacity and can be engineered to control the drug release schedule. The optimal schedule for sensitization during continuous low dose rate irradiation is unknown. This work studies the optimal release schedule of drug for both traditional sensitizers, and those that work by suppressing DNA repair processes. Methods: Six brachytherapy treatment plans were used to model the anatomy, implant geometry and calculate the spatial distributionmore » of radiation dose and drug concentrations for a range of drug diffusion parameters. Three state partial differential equations (cells healthy, damaged or dead) modeled the effect of continuous radiation (radiosensitivities α,β) and cellular repair (time tr) on a cell population. Radiosensitization was modeled as concentration dependent change in α,β or tr which with variable duration under the constraint of fixed total drug release. Average cell kill was used to measure effectiveness. Sensitization by means of both enhanced damage and reduced repair were studied. Results: Optimal release duration is dependent on the concentration of radiosensitizer compared to the saturation concentration (csat) above which additional sensitization does not occur. Long duration drug release when enhancing α or β maximizes cell death when drug concentrations are generally over csat. Short term release is optimal for concentrations below saturation. Sensitization by suppressing repair has a similar though less distinct trend that is more affected by the radiation dose distribution. Conclusion: Models of sustained local radiosensitization show potential to increase the effectiveness of radiation in permanent prostate brachytherapy. INCeRTs with high drug capacity produce the greatest benefit with drug release over weeks. If in-vivo drug concentrations are not able to approach saturation concentration, durations of days is optimal. DOD 1R21CA16977501; A. David Mazzone Awards Program 2012PD164.« less

Determination of Optimal Parameters for Dual-Layer Cathode of Polymer Electrolyte Fuel Cell Using Computational Intelligence-Aided Design

PubMed Central

Chen, Yi; Huang, Weina; Peng, Bei

2014-01-01

Because of the demands for sustainable and renewable energy, fuel cells have become increasingly popular, particularly the polymer electrolyte fuel cell (PEFC). Among the various components, the cathode plays a key role in the operation of a PEFC. In this study, a quantitative dual-layer cathode model was proposed for determining the optimal parameters that minimize the over-potential difference and improve the efficiency using a newly developed bat swarm algorithm with a variable population embedded in the computational intelligence-aided design. The simulation results were in agreement with previously reported results, suggesting that the proposed technique has potential applications for automating and optimizing the design of PEFCs. PMID:25490761

Genome-scale biological models for industrial microbial systems.

PubMed

Xu, Nan; Ye, Chao; Liu, Liming

2018-04-01

The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

Reliability prediction of large fuel cell stack based on structure stress analysis

NASA Astrophysics Data System (ADS)

Liu, L. F.; Liu, B.; Wu, C. W.

2017-09-01

The aim of this paper is to improve the reliability of Proton Electrolyte Membrane Fuel Cell (PEMFC) stack by designing the clamping force and the thickness difference between the membrane electrode assembly (MEA) and the gasket. The stack reliability is directly determined by the component reliability, which is affected by the material property and contact stress. The component contact stress is a random variable because it is usually affected by many uncertain factors in the production and clamping process. We have investigated the influences of parameter variation coefficient on the probability distribution of contact stress using the equivalent stiffness model and the first-order second moment method. The optimal contact stress to make the component stay in the highest level reliability is obtained by the stress-strength interference model. To obtain the optimal contact stress between the contact components, the optimal thickness of the component and the stack clamping force are optimally designed. Finally, a detailed description is given how to design the MEA and gasket dimensions to obtain the highest stack reliability. This work can provide a valuable guidance in the design of stack structure for a high reliability of fuel cell stack.

Modeling and optimization of an enhanced battery thermal management system in electric vehicles

NASA Astrophysics Data System (ADS)

Li, Mao; Liu, Yuanzhi; Wang, Xiaobang; Zhang, Jie

2018-06-01

This paper models and optimizes an air-based battery thermal management system (BTMS) in a battery module with 36 battery lithium-ion cells. A design of experiments is performed to study the effects of three key parameters (i.e., mass flow rate of cooling air, heat flux from the battery cell to the cooling air, and passage spacing size) on the battery thermal performance. Three metrics are used to evaluate the BTMS thermal performance, including (i) the maximum temperature in the battery module, (ii) the temperature uniformity in the battery module, and (iii) the pressure drop. It is found that (i) increasing the total mass flow rate may result in a more non-uniform distribution of the passage mass flow rate among passages, and (ii) a large passage spacing size may worsen the temperature uniformity on the battery walls. Optimization is also performed to optimize the passage spacing size. Results show that the maximum temperature difference of the cooling air in passages is reduced from 23.9 to 2.1 K by 91.2%, and the maximum temperature difference among the battery cells is reduced from 25.7 to 6.4 K by 75.1%.

Modeling of steady-state convective cooling of cylindrical Li-ion cells

NASA Astrophysics Data System (ADS)

Shah, K.; Drake, S. J.; Wetz, D. A.; Ostanek, J. K.; Miller, S. P.; Heinzel, J. M.; Jain, A.

2014-07-01

While Lithium-ion batteries have the potential to serve as an excellent means of energy storage, they suffer from several operational safety concerns. Temperature excursion beyond a specified limit for a Lithium-ion battery triggers a sequence of decomposition and release, which can preclude thermal runaway events and catastrophic failure. To optimize liquid or air-based convective cooling approaches, it is important to accurately model the thermal response of Lithium-ion cells to convective cooling, particularly in high-rate discharge applications where significant heat generation is expected. This paper presents closed-form analytical solutions for the steady-state temperature profile in a convectively cooled cylindrical Lithium-ion cell. These models account for the strongly anisotropic thermal conductivity of cylindrical Lithium-ion batteries due to the spirally wound electrode assembly. Model results are in excellent agreement with experimentally measured temperature rise in a thermal test cell. Results indicate that improvements in radial thermal conductivity and axial convective heat transfer coefficient may result in significant peak temperature reduction. Battery sizing optimization using the analytical model is discussed, indicating the dependence of thermal performance of the cell on its size and aspect ratio. Results presented in this paper may aid in accurate thermal design and thermal management of Lithium-ion batteries.

HOMER: The Micropower Optimization Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2004-03-01

HOMER, the micropower optimization model, helps users to design micropower systems for off-grid and grid-connected power applications. HOMER models micropower systems with one or more power sources including wind turbines, photovoltaics, biomass power, hydropower, cogeneration, diesel engines, cogeneration, batteries, fuel cells, and electrolyzers. Users can explore a range of design questions such as which technologies are most effective, what size should components be, how project economics are affected by changes in loads or costs, and is the renewable resource adequate.

Reduction of wafer-edge overlay errors using advanced correction models, optimized for minimal metrology requirements

NASA Astrophysics Data System (ADS)

Kim, Min-Suk; Won, Hwa-Yeon; Jeong, Jong-Mun; Böcker, Paul; Vergaij-Huizer, Lydia; Kupers, Michiel; Jovanović, Milenko; Sochal, Inez; Ryan, Kevin; Sun, Kyu-Tae; Lim, Young-Wan; Byun, Jin-Moo; Kim, Gwang-Gon; Suh, Jung-Joon

2016-03-01

In order to optimize yield in DRAM semiconductor manufacturing for 2x nodes and beyond, the (processing induced) overlay fingerprint towards the edge of the wafer needs to be reduced. Traditionally, this is achieved by acquiring denser overlay metrology at the edge of the wafer, to feed field-by-field corrections. Although field-by-field corrections can be effective in reducing localized overlay errors, the requirement for dense metrology to determine the corrections can become a limiting factor due to a significant increase of metrology time and cost. In this study, a more cost-effective solution has been found in extending the regular correction model with an edge-specific component. This new overlay correction model can be driven by an optimized, sparser sampling especially at the wafer edge area, and also allows for a reduction of noise propagation. Lithography correction potential has been maximized, with significantly less metrology needs. Evaluations have been performed, demonstrating the benefit of edge models in terms of on-product overlay performance, as well as cell based overlay performance based on metrology-to-cell matching improvements. Performance can be increased compared to POR modeling and sampling, which can contribute to (overlay based) yield improvement. Based on advanced modeling including edge components, metrology requirements have been optimized, enabling integrated metrology which drives down overall metrology fab footprint and lithography cycle time.

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation.

PubMed

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-03-04

Two mathematical models were developed for studying the effect of main fermentation temperature ( T MF ), immobilized cell mass ( M IC ) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model.

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation

PubMed Central

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-01-01

Two mathematical models were developed for studying the effect of main fermentation temperature (T MF), immobilized cell mass (M IC) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model. PMID:26019512

Simulation and optimization of silicon-on-sapphire pressure sensor

NASA Astrophysics Data System (ADS)

Kulesh, N. A.; Kudyukov, E. V.; Balymov, K. G.; Beloyshov, A. A.

2017-09-01

In this paper, finite element analysis software COMSOL Multiphysics was used to simulate the performance of silicon-on-sapphire piezoresistive pressure sensor, aiming to elaborate a flexible model suitable for further optimization and customization of the currently produced pressure sensors. The base model was built around the cylindrical pressure cell made of titanium alloy having a circular diaphragm with monocrystalline sapphire layer attached. The monocrystalline piezoresistive elements were placed on top of the double-layer diaphragm and electrically connected to form the Wheatstone bridge. Verification of the model and parametric study included three main areas: geometrical parameters of the cell, position of the elements on the diaphragm, and operation at elevated temperature. Optimization of the cell geometry included variation of bossed titanium diaphragm parameters as well as rounding-off radiuses near the edges of the diaphragm. Influence of the temperature was considered separately for thermal expansion of the mechanical components and for the changes of electrical and piezoresistive properties of the piezoresistive elements. In conclusion, the simulation results were compared to the experimental data obtained for three different constructions of the commercial pressure sensors produced by SPA of Automatics named after Academician N.A. Semikhatov.

Biokinetic model-based multi-objective optimization of Dunaliella tertiolecta cultivation using elitist non-dominated sorting genetic algorithm with inheritance.

PubMed

Sinha, Snehal K; Kumar, Mithilesh; Guria, Chandan; Kumar, Anup; Banerjee, Chiranjib

2017-10-01

Algal model based multi-objective optimization using elitist non-dominated sorting genetic algorithm with inheritance was carried out for batch cultivation of Dunaliella tertiolecta using NPK-fertilizer. Optimization problems involving two- and three-objective functions were solved simultaneously. The objective functions are: maximization of algae-biomass and lipid productivity with minimization of cultivation time and cost. Time variant light intensity and temperature including NPK-fertilizer, NaCl and NaHCO 3 loadings are the important decision variables. Algal model involving Monod/Andrews adsorption kinetics and Droop model with internal nutrient cell quota was used for optimization studies. Sets of non-dominated (equally good) Pareto optimal solutions were obtained for the problems studied. It was observed that time variant optimal light intensity and temperature trajectories, including optimum NPK fertilizer, NaCl and NaHCO 3 concentration has significant influence to improve biomass and lipid productivity under minimum cultivation time and cost. Proposed optimization studies may be helpful to implement the control strategy in scale-up operation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling and process optimization of electrospinning of chitosan-collagen nanofiber by response surface methodology

NASA Astrophysics Data System (ADS)

Amiri, Nafise; Moradi, Ali; Abolghasem Sajjadi Tabasi, Sayyed; Movaffagh, Jebrail

2018-04-01

Chitosan-collagen composite nanofiber is of a great interest to researchers in biomedical fields. Since the electrospinning is the most popular method for nanofiber production, having a comprehensive knowledge of the electrospinning process is beneficial. Modeling techniques are precious tools for managing variables in the electrospinning process, prior to the more time- consuming and expensive experimental techniques. In this study, a central composite design of response surface methodology (RSM) was employed to develop a statistical model as well as to define the optimum condition for fabrication of chitosan-collagen nanofiber with minimum diameter. The individual and the interaction effects of applied voltage (10–25 kV), flow rate (0.5–1.5 mL h‑1), and needle to collector distance (15–25 cm) on the fiber diameter were investigated. ATR- FTIR and cell study were done to evaluate the optimized nanofibers. According to the RSM, a two-factor interaction (2FI) model was the most suitable model. The high regression coefficient value (R 2 ≥ 0.9666) of the fitted regression model and insignificant lack of fit (P = 0.0715) indicated that the model was highly adequate in predicting chitosan-collagen nanofiber diameter. The optimization process showed that the chitosan-collagen nanofiber diameter of 156.05 nm could be obtained in 9 kV, 0.2 ml h‑1, and 25 cm which was confirmed by experiment (155.92 ± 18.95 nm). The ATR-FTIR and cell study confirmed the structure and biocompatibility of the optimized membrane. The represented model could assist researchers in fabricating chitosan-collagen electrospun scaffolds with a predictable fiber diameter, and optimized chitosan-collagen nanofibrous mat could be a potential candidate for wound healing and tissue engineering.

Optimization of the formation of embedded multicellular spheroids of MCF-7 cells: How to reliably produce a biomimetic 3D model.

PubMed

Zhang, Wenli; Li, Caibin; Baguley, Bruce C; Zhou, Fang; Zhou, Weisai; Shaw, John P; Wang, Zhen; Wu, Zimei; Liu, Jianping

2016-12-15

To obtain a multicellular MCF-7 spheroid model to mimic the three-dimensional (3D) of tumors, the microwell liquid overlay (A) and hanging-drop/agar (B) methods were first compared for their technical parameters. Then a method for embedding spheroids within collagen was optimized. For method A, centrifugation assisted cells form irregular aggregates but not spheroids. For method B, an extended sedimentation period of over 24 h for cell suspensions and increased viscosity of the culture medium using methylcellulose were necessary to harvest a dense and regular cell spheroid. When the number was less than 5000 cells/drop, embedded spheroids showed no tight cores and higher viability than the unembedded. However, above 5000 cells/drop, cellular viability of embedded spheroids was not significantly different from unembedded spheroids and cells invading through the collagen were in a sun-burst pattern with tight cores. Propidium Iodide staining indicated that spheroids had necrotic cores. The doxorubicin cytotoxicity demonstrated that spheroids were less susceptible to DOX than their monolayer cells. A reliable and reproducible method for embedding spheroids using the hanging-drop/agarose method within collagen is described herein. The cell culture model can be used to guide experimental manipulation of 3D cell cultures and to evaluate anticancer drug efficacy. Copyright © 2016 Elsevier Inc. All rights reserved.

Cell-microenvironment interactions and architectures in microvascular systems

PubMed Central

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.

PubMed

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.

Generation of improved humanized mouse models for human infectious diseases

PubMed Central

Brehm, Michael A.; Wiles, Michael V.; Greiner, Dale L.; Shultz, Leonard D.

2014-01-01

The study of human-specific infectious agents has been hindered by the lack of optimal small animal models. More recently development of novel strains of immunodeficient mice has begun to provide the opportunity to utilize small animal models for the study of many human-specific infectious agents. The introduction of a targeted mutation in the IL2 receptor common gamma chain gene (IL2rgnull) in mice already deficient in T and B cells led to a breakthrough in the ability to engraft hematopoietic stem cells, as well as functional human lymphoid cells and tissues, effectively creating human immune systems in immunodeficient mice. These humanized mice are becoming increasingly important as pre-clinical models for the study of human immunodeficiency virus-1 (HIV-1) and other human-specific infectious agents. However, there remain a number of opportunities to further improve humanized mouse models for the study of human-specific infectious agents. This is being done by the implementation of innovative technologies, which collectively will accelerate the development of new models of genetically modified mice, including; i) modifications of the host to reduce innate immunity, which impedes human cell engraftment; ii) genetic modification to provide human-specific growth factors and cytokines required for optimal human cell growth and function; iii) and new cell and tissue engraftment protocols. The development of “next generation” humanized mouse models continues to provide exciting opportunities for the establishment of robust small animal models to study the pathogenesis of human-specific infectious agents, as well as for testing the efficacy of therapeutic agents and experimental vaccines. PMID:24607601

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

CD8+ T Cells Orchestrate pDC-XCR1+ Dendritic Cell Spatial and Functional Cooperativity to Optimize Priming.

PubMed

Brewitz, Anna; Eickhoff, Sarah; Dähling, Sabrina; Quast, Thomas; Bedoui, Sammy; Kroczek, Richard A; Kurts, Christian; Garbi, Natalio; Barchet, Winfried; Iannacone, Matteo; Klauschen, Frederick; Kolanus, Waldemar; Kaisho, Tsuneyasu; Colonna, Marco; Germain, Ronald N; Kastenmüller, Wolfgang

2017-02-21

Adaptive cellular immunity is initiated by antigen-specific interactions between T lymphocytes and dendritic cells (DCs). Plasmacytoid DCs (pDCs) support antiviral immunity by linking innate and adaptive immune responses. Here we examined pDC spatiotemporal dynamics during viral infection to uncover when, where, and how they exert their functions. We found that pDCs accumulated at sites of CD8 + T cell antigen-driven activation in a CCR5-dependent fashion. Furthermore, activated CD8 + T cells orchestrated the local recruitment of lymph node-resident XCR1 chemokine receptor-expressing DCs via secretion of the XCL1 chemokine. Functionally, this CD8 + T cell-mediated reorganization of the local DC network allowed for the interaction and cooperation of pDCs and XCR1 + DCs, thereby optimizing XCR1 + DC maturation and cross-presentation. These data support a model in which CD8 + T cells upon activation create their own optimal priming microenvironment by recruiting additional DC subsets to the site of initial antigen recognition. Published by Elsevier Inc.

Immunization Route Dictates Cross-Priming Efficiency and Impacts the Optimal Timing of Adjuvant Delivery

PubMed Central

Bouvier, Isabelle; Jusforgues-Saklani, Hélène; Lim, Annick; Lemaître, Fabrice; Lemercier, Brigitte; Auriau, Charlotte; Nicola, Marie-Anne; Leroy, Sandrine; Law, Helen K.; Bandeira, Antonio; Moon, James J.; Bousso, Philippe; Albert, Matthew L.

2011-01-01

Delivery of cell-associated antigen represents an important strategy for vaccination. While many experimental models have been developed in order to define the critical parameters for efficient cross-priming, few have utilized quantitative methods that permit the study of the endogenous repertoire. Comparing different strategies of immunization, we report that local delivery of cell-associated antigen results in delayed T cell cross-priming due to the increased time required for antigen capture and presentation. In comparison, delivery of disseminated antigen resulted in rapid T cell priming. Surprisingly, local injection of cell-associated antigen, while slower, resulted in the differentiation of a more robust, polyfunctional, effector response. We also evaluated the combination of cell-associated antigen with poly I:C delivery and observed an immunization route-specific effect regarding the optimal timing of innate immune stimulation. These studies highlight the importance of considering the timing and persistence of antigen presentation, and suggest that intradermal injection with delayed adjuvant delivery is the optimal strategy for achieving CD8+ T cell cross-priming. PMID:22566860

Systematic design of 3D auxetic lattice materials with programmable Poisson's ratio for finite strains

NASA Astrophysics Data System (ADS)

Wang, Fengwen

2018-05-01

This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.

Revisiting Bevacizumab + Cytotoxics Scheduling Using Mathematical Modeling: Proof of Concept Study in Experimental Non-Small Cell Lung Carcinoma.

PubMed

Imbs, Diane-Charlotte; El Cheikh, Raouf; Boyer, Arnaud; Ciccolini, Joseph; Mascaux, Céline; Lacarelle, Bruno; Barlesi, Fabrice; Barbolosi, Dominique; Benzekry, Sébastien

2018-01-01

Concomitant administration of bevacizumab and pemetrexed-cisplatin is a common treatment for advanced nonsquamous non-small cell lung cancer (NSCLC). Vascular normalization following bevacizumab administration may transiently enhance drug delivery, suggesting improved efficacy with sequential administration. To investigate optimal scheduling, we conducted a study in NSCLC-bearing mice. First, experiments demonstrated improved efficacy when using sequential vs. concomitant scheduling of bevacizumab and chemotherapy. Combining this data with a mathematical model of tumor growth under therapy accounting for the normalization effect, we predicted an optimal delay of 2.8 days between bevacizumab and chemotherapy. This prediction was confirmed experimentally, with reduced tumor growth of 38% as compared to concomitant scheduling, and prolonged survival (74 vs. 70 days). Alternate sequencing of 8 days failed in achieving a similar increase in efficacy, thus emphasizing the utility of modeling support to identify optimal scheduling. The model could also be a useful tool in the clinic to personally tailor regimen sequences. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Optimization of the structural configuration of ICBA/P3HT photovoltaic cells

NASA Astrophysics Data System (ADS)

Nemnes, G. A.; Iftimie, Sorina; Palici, Alexandra; Nicolaev, Adela; Mitran, T. L.; Radu, A.; Antohe, S.

2017-12-01

We investigate a possible route for optimization of organic P3HT:ICBA photovoltaic cells. In order to ensure a more efficient charge separation and collection at the electrodes, two- and three-layer structures are produced, where additional P3HT and ICBA single layers are placed adjacent to the mixed layer. The J-V characteristics are modeled using Monte-Carlo simulations in a flexible computational framework, reproducing the typical morphologies of the active layers. We discuss the implications of the structural modifications, in particular the enhancement of the open circuit voltage. Qualitative features of the theoretical simulations are validated by experiment. The proposed fabrication technique of using solvents with different boiling points for successive deposition of the individual layers may constitute an accessible route for producing optimized solar cell structures.

nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data.

PubMed

Zhang, Changsheng; Cai, Hongmin; Huang, Jingying; Song, Yan

2016-09-17

Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genomic heterogeneity at the single-cell level, thereby providing important evolutionary information about cancer cells. In contrast to traditional bulk sequencing, single-cell sequencing requires the amplification of the whole genome of a single cell to accumulate enough samples for sequencing. However, the amplification process inevitably introduces amplification bias, resulting in an over-dispersing portion of the sequencing data. Recent study has manifested that the over-dispersed portion of the single-cell sequencing data could be well modelled by negative binomial distributions. We developed a read-depth based method, nbCNV to detect the copy number variants (CNVs). The nbCNV method uses two constraints-sparsity and smoothness to fit the CNV patterns under the assumption that the read signals are negatively binomially distributed. The problem of CNV detection was formulated as a quadratic optimization problem, and was solved by an efficient numerical solution based on the classical alternating direction minimization method. Extensive experiments to compare nbCNV with existing benchmark models were conducted on both simulated data and empirical single-cell sequencing data. The results of those experiments demonstrate that nbCNV achieves superior performance and high robustness for the detection of CNVs in single-cell sequencing data.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

Radiobiological description of the LET dependence of the cell survival of oxic and anoxic cells irradiated by carbon ions.

PubMed

Antonovic, L; Brahme, A; Furusawa, Y; Toma-Dasu, I

2013-01-01

Light-ion radiation therapy against hypoxic tumors is highly curative due to reduced dependence on the presence of oxygen in the tumor at elevated linear energy transfer (LET) towards the Bragg peak. Clinical ion beams using spread-out Bragg peak (SOBP) are characterized by a wide spectrum of LET values. Accurate treatment optimization requires a method that can account for influence of the variation in response for a broad range of tumor hypoxia, absorbed doses and LETs. This paper presents a parameterization of the Repairable Conditionally-Repairable (RCR) cell survival model that can describe the survival of oxic and hypoxic cells over a wide range of LET values, and investigates the relationship between hypoxic radiation resistance and LET. The biological response model was tested by fitting cell survival data under oxic and anoxic conditions for V79 cells irradiated with LETs within the range of 30-500 keV/µm. The model provides good agreement with experimental cell survival data for the range of LET investigated, confirming the robustness of the parameterization method. This new version of the RCR model is suitable for describing the biological response of mixed populations of oxic and hypoxic cells and at the same time taking into account the distribution of doses and LETs in the incident beam and its variation with depth in tissue. The model offers a versatile tool for the selection of LET and dose required in the optimization of the therapeutic effect, without severely affecting normal tissue in realistic tumors presenting highly heterogeneous oxic and hypoxic regions.

Resource Allocation Algorithms for the Next Generation Cellular Networks

NASA Astrophysics Data System (ADS)

Amzallag, David; Raz, Danny

This chapter describes recent results addressing resource allocation problems in the context of current and future cellular technologies. We present models that capture several fundamental aspects of planning and operating these networks, and develop new approximation algorithms providing provable good solutions for the corresponding optimization problems. We mainly focus on two families of problems: cell planning and cell selection. Cell planning deals with choosing a network of base stations that can provide the required coverage of the service area with respect to the traffic requirements, available capacities, interference, and the desired QoS. Cell selection is the process of determining the cell(s) that provide service to each mobile station. Optimizing these processes is an important step towards maximizing the utilization of current and future cellular networks.

Solid-state proton conductors

NASA Astrophysics Data System (ADS)

Jewulski, J. R.; Osif, T. L.; Remick, R. J.

1990-12-01

The purpose of this program was to survey the field of solid-state proton conductors (SSPC), identify conductors that could be used to develop solid-state fuel cells suitable for use with coal derived fuel gases, and begin the experimental research required for the development of these fuel cells. This document covers the following topics: the history of developments and current status of the SSPC, including a review of proton conducting electrolyte structures, the current status of the medium temperature SSPC development, electrodes for moderate temperature (SSPC) fuel cell, basic material and measurement techniques applicable for SSPC development, modeling, and optimization studies. Correlation and optimization studies are described which include correlation studies on proton conduction and oxide cathode optimization for the SSPC fuel cell. Experiments with the SSPC fuel cells are presented which include the fabrication of the electrolyte disks, apparatus for conducting measurements, the strontium-cerium based electrolyte, the barium-cerium based electrolyte with solid foil electrodes, the barium-cerium based electrolyte with porous electrodes, and conduction mechanisms.

Selective arylsulfonamide inhibitors of ADAM-17: hit optimization and activity in ovarian cancer cell models.

PubMed

Nuti, Elisa; Casalini, Francesca; Santamaria, Salvatore; Fabbi, Marina; Carbotti, Grazia; Ferrini, Silvano; Marinelli, Luciana; La Pietra, Valeria; Novellino, Ettore; Camodeca, Caterina; Orlandini, Elisabetta; Nencetti, Susanna; Rossello, Armando

2013-10-24

Activated leukocyte cell adhesion molecule (ALCAM) is expressed at the surface of epithelial ovarian cancer (EOC) cells and is released in a soluble form (sALCAM) by ADAM-17-mediated shedding. This process is relevant to EOC cell motility and invasiveness, which is reduced by inhibitors of ADAM-17. In addition, ADAM-17 plays a key role in EGFR signaling and thus may represent a useful target in anticancer therapy. Herein we report our hit optimization effort to identify potent and selective ADAM-17 inhibitors, starting with previously identified inhibitor 1. A new series of secondary sulfonamido-based hydroxamates was designed and synthesized. The biological activity of the newly synthesized compounds was tested in vitro on isolated enzymes and human EOC cell lines. The optimization process led to compound 21, which showed an IC50 of 1.9 nM on ADAM-17 with greatly increased selectivity. This compound maintained good inhibitory properties on sALCAM shedding in several in vitro assays.

Comprehensive model of microalgae photosynthesis rate as a function of culture conditions in photobioreactors.

PubMed

Costache, T A; Acién Fernández, F Gabriel; Morales, M M; Fernández-Sevilla, J M; Stamatin, I; Molina, E

2013-09-01

In this paper, the influence of culture conditions (irradiance, temperature, pH, and dissolved oxygen) on the photosynthesis rate of Scenedesmus almeriensis cultures is analyzed. Short-run experiments were performed to study cell response to variations in culture conditions, which take place in changing environments such as outdoor photobioreactors. Experiments were performed by subjecting diluted samples of cells to different levels of irradiance, temperature, pH, and dissolved oxygen concentration. Results demonstrate the existence of photoinhibition phenomena at irradiances higher than 1,000 μE/m(2) s; in addition to reduced photosynthesis rates at inadequate temperatures or pH-the optimal values being 35 °C and 8, respectively. Moreover, photosynthesis rate reduction at dissolved oxygen concentrations above 20 mg/l is demonstrated. Data have been used to develop an integrated model based on considering the simultaneous influence of irradiance, temperature, pH, and dissolved oxygen. The model fits the experimental results in the range of culture conditions tested, and it was validated using data obtained by the simultaneous variation of two of the modified variables. Furthermore, the model fits experimental results obtained from an outdoor culture of S. almeriensis performed in an open raceway reactor. Results demonstrate that photosynthetic efficiency is modified as a function of culture conditions, and can be used to determine the proximity of culture conditions to optimal values. Optimal conditions found (T = 35 °C, pH = 8, dissolved oxygen concentration <20 mg/l) allows to maximize the use of light by the cells. The developed model is a powerful tool for the optimal design and management of microalgae-based processes, especially outdoors, where the cultures are subject to daily culture condition variations.

Modeling and predictions of biphasic mechanosensitive cell migration altered by cell-intrinsic properties and matrix confinement.

PubMed

Pathak, Amit

2018-04-12

Motile cells sense the stiffness of their extracellular matrix (ECM) through adhesions and respond by modulating the generated forces, which in turn lead to varying mechanosensitive migration phenotypes. Through modeling and experiments, cell migration speed is known to vary with matrix stiffness in a biphasic manner, with optimal motility at an intermediate stiffness. Here, we present a two-dimensional cell model defined by nodes and elements, integrated with subcellular modeling components corresponding to mechanotransductive adhesion formation, force generation, protrusions and node displacement. On 2D matrices, our calculations reproduce the classic biphasic dependence of migration speed on matrix stiffness and predict that cell types with higher force-generating ability do not slow down on very stiff matrices, thus disabling the biphasic response. We also predict that cell types defined by lower number of total receptors require stiffer matrices for optimal motility, which also limits the biphasic response. For a cell type with robust biphasic migration on 2D surface, simulations in channel-like confined environments of varying width and height predict faster migration in more confined matrices. Simulations performed in shallower channels predict that the biphasic mechanosensitive cell migration response is more robust on 2D micro-patterns as compared to the channel-like 3D confinement. Thus, variations in the dimensionality of matrix confinement alters the way migratory cells sense and respond to the matrix stiffness. Our calculations reveal new phenotypes of stiffness- and topography-sensitive cell migration that critically depend on both cell-intrinsic and matrix properties. These predictions may inform our understanding of various mechanosensitive modes of cell motility that could enable tumor invasion through topographically heterogeneous microenvironments. © 2018 IOP Publishing Ltd.

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation.

PubMed

Chisholm, Rebecca H; Lorenzi, Tommaso; Clairambault, Jean

2016-11-01

Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

Photonic crystal enhanced silicon cell based thermophotovoltaic systems

DOE PAGES

Yeng, Yi Xiang; Chan, Walker R.; Rinnerbauer, Veronika; ...

2015-01-30

We report the design, optimization, and experimental results of large area commercial silicon solar cell based thermophotovoltaic (TPV) energy conversion systems. Using global non-linear optimization tools, we demonstrate theoretically a maximum radiative heat-to-electricity efficiency of 6.4% and a corresponding output electrical power density of 0.39 W cm⁻² at temperature T = 1660 K when implementing both the optimized two-dimensional (2D) tantalum photonic crystal (PhC) selective emitter, and the optimized 1D tantalum pentoxide – silicon dioxide PhC cold-side selective filter. In addition, we have developed an experimental large area TPV test setup that enables accurate measurement of radiative heat-to-electricity efficiency formore » any emitter-filter-TPV cell combination of interest. In fact, the experimental results match extremely well with predictions of our numerical models. Our experimental setup achieved a maximum output electrical power density of 0.10W cm⁻² and radiative heat-to-electricity efficiency of 1.18% at T = 1380 K using commercial wafer size back-contacted silicon solar cells.« less

Optimization of the lithium/thionyl chloride battery

NASA Technical Reports Server (NTRS)

White, Ralph E.

1987-01-01

The progress which has been made in modeling the lithium/thionyl chloride cell over the past year and proposed research for the coming year are discussed. A one-dimensional mathematical model for a lithium/thionyl chloride cell has been developed and used to investigate methods of improving cell performance. During the course of the work a problem was detected with the banded solver being used. It was replaced with one more reliable. Future work may take one of two directions. The one-dimensional model could be augmented to include additional features and to investigate in more detail the cell temperature behavior, or a simplified two-dimensional model for the spirally wound design of this battery could be developed to investigate the heat flow within the cell.

Modeling spatial distribution of oxygen in 3d culture of islet beta-cells.

PubMed

McReynolds, John; Wen, Yu; Li, Xiaofei; Guan, Jianjun; Jin, Sha

2017-01-01

Three-dimensional (3D) scaffold culture of pancreatic β-cell has been proven to be able to better mimic physiological conditions in the body. However, one critical issue with culturing pancreatic β-cells is that β-cells consume large amounts of oxygen, and hence insufficient oxygen supply in the culture leads to loss of β-cell mass and functions. This becomes more significant when cells are cultured in a 3D scaffold. In this study, in order to understand the effect of oxygen tension inside a cell-laden collagen culture on β-cell proliferation, a culture model with encapsulation of an oxygen-generator was established. The oxygen-generator was made by embedding hydrogen peroxide into nontoxic polydimethylsiloxane to avoid the toxicity of a chemical reaction in the β-cell culture. To examine the effectiveness of the oxygenation enabled 3D culture, the spatial-temporal distribution of oxygen tension inside a scaffold was evaluated by a mathematical modeling approach. Our simulation results indicated that an oxygenation-aided 3D culture would augment the oxygen supply required for the β-cells. Furthermore, we identified that cell seeding density and the capacity of the oxygenator are two critical parameters in the optimization of the culture. Notably, cell-laden scaffold cultures with an in situ oxygen supply significantly improved the β-cells' biological function. These β-cells possess high insulin secretion capacity. The results obtained in this work would provide valuable information for optimizing and encouraging functional β-cell cultures. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:221-228, 2017. © 2016 American Institute of Chemical Engineers.

Optimized efficiency in InP nanowire solar cells with accurate 1D analysis

NASA Astrophysics Data System (ADS)

Chen, Yang; Kivisaari, Pyry; Pistol, Mats-Erik; Anttu, Nicklas

2018-01-01

Semiconductor nanowire arrays are a promising candidate for next generation solar cells due to enhanced absorption and reduced material consumption. However, to optimize their performance, time consuming three-dimensional (3D) opto-electronics modeling is usually performed. Here, we develop an accurate one-dimensional (1D) modeling method for the analysis. The 1D modeling is about 400 times faster than 3D modeling and allows direct application of concepts from planar pn-junctions on the analysis of nanowire solar cells. We show that the superposition principle can break down in InP nanowires due to strong surface recombination in the depletion region, giving rise to an IV-behavior similar to that with low shunt resistance. Importantly, we find that the open-circuit voltage of nanowire solar cells is typically limited by contact leakage. Therefore, to increase the efficiency, we have investigated the effect of high-bandgap GaP carrier-selective contact segments at the top and bottom of the InP nanowire and we find that GaP contact segments improve the solar cell efficiency. Next, we discuss the merit of p-i-n and p-n junction concepts in nanowire solar cells. With GaP carrier selective top and bottom contact segments in the InP nanowire array, we find that a p-n junction design is superior to a p-i-n junction design. We predict a best efficiency of 25% for a surface recombination velocity of 4500 cm s-1, corresponding to a non-radiative lifetime of 1 ns in p-n junction cells. The developed 1D model can be used for general modeling of axial p-n and p-i-n junctions in semiconductor nanowires. This includes also LED applications and we expect faster progress in device modeling using our method.

Optimized efficiency in InP nanowire solar cells with accurate 1D analysis.

PubMed

Chen, Yang; Kivisaari, Pyry; Pistol, Mats-Erik; Anttu, Nicklas

2018-01-26

Semiconductor nanowire arrays are a promising candidate for next generation solar cells due to enhanced absorption and reduced material consumption. However, to optimize their performance, time consuming three-dimensional (3D) opto-electronics modeling is usually performed. Here, we develop an accurate one-dimensional (1D) modeling method for the analysis. The 1D modeling is about 400 times faster than 3D modeling and allows direct application of concepts from planar pn-junctions on the analysis of nanowire solar cells. We show that the superposition principle can break down in InP nanowires due to strong surface recombination in the depletion region, giving rise to an IV-behavior similar to that with low shunt resistance. Importantly, we find that the open-circuit voltage of nanowire solar cells is typically limited by contact leakage. Therefore, to increase the efficiency, we have investigated the effect of high-bandgap GaP carrier-selective contact segments at the top and bottom of the InP nanowire and we find that GaP contact segments improve the solar cell efficiency. Next, we discuss the merit of p-i-n and p-n junction concepts in nanowire solar cells. With GaP carrier selective top and bottom contact segments in the InP nanowire array, we find that a p-n junction design is superior to a p-i-n junction design. We predict a best efficiency of 25% for a surface recombination velocity of 4500 cm s -1 , corresponding to a non-radiative lifetime of 1 ns in p-n junction cells. The developed 1D model can be used for general modeling of axial p-n and p-i-n junctions in semiconductor nanowires. This includes also LED applications and we expect faster progress in device modeling using our method.

Optimizing heat shock protein expression induced by prostate cancer laser therapy through predictive computational models

NASA Astrophysics Data System (ADS)

Rylander, Marissa N.; Feng, Yusheng; Zhang, Yongjie; Bass, Jon; Stafford, Roger J.; Hazle, John D.; Diller, Kenneth R.

2006-07-01

Thermal therapy efficacy can be diminished due to heat shock protein (HSP) induction in regions of a tumor where temperatures are insufficient to coagulate proteins. HSP expression enhances tumor cell viability and imparts resistance to chemotherapy and radiation treatments, which are generally employed in conjunction with hyperthermia. Therefore, an understanding of the thermally induced HSP expression within the targeted tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of the overall tissue response. A treatment planning computational model capable of predicting the temperature, HSP27 and HSP70 expression, and damage fraction distributions associated with laser heating in healthy prostate tissue and tumors is presented. Measured thermally induced HSP27 and HSP70 expression kinetics and injury data for normal and cancerous prostate cells and prostate tumors are employed to create the first HSP expression predictive model and formulate an Arrhenius damage model. The correlation coefficients between measured and model predicted temperature, HSP27, and HSP70 were 0.98, 0.99, and 0.99, respectively, confirming the accuracy of the model. Utilization of the treatment planning model in the design of prostate cancer thermal therapies can enable optimization of the treatment outcome by controlling HSP expression and injury.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeong, J; Deasy, J O

Purpose: Concurrent chemo-radiation therapy (CCRT) has become a more common cancer treatment option with a better tumor control rate for several tumor sites, including head and neck and lung cancer. In this work, possible optimal chemotherapy schedules were investigated by implementing chemotherapy cell-kill into a tumor response model of RT. Methods: The chemotherapy effect has been added into a published model (Jeong et al., PMB (2013) 58:4897), in which the tumor response to RT can be simulated with the effects of hypoxia and proliferation. Based on the two-compartment pharmacokinetic model, the temporal concentration of chemotherapy agent was estimated. Log cell-killmore » was assumed and the cell-kill constant was estimated from the observed increase in local control due to concurrent chemotherapy. For a simplified two cycle CCRT regime, several different starting times and intervals were simulated with conventional RT regime (2Gy/fx, 5fx/wk). The effectiveness of CCRT was evaluated in terms of reduction in radiation dose required for 50% of control to find the optimal chemotherapy schedule. Results: Assuming the typical slope of dose response curve (γ50=2), the observed 10% increase in local control rate was evaluated to be equivalent to an extra RT dose of about 4 Gy, from which the cell-kill rate of chemotherapy was derived to be about 0.35. Best response was obtained when chemotherapy was started at about 3 weeks after RT began. As the interval between two cycles decreases, the efficacy of chemotherapy increases with broader range of optimal starting times. Conclusion: The effect of chemotherapy has been implemented into the resource-conservation tumor response model to investigate CCRT. The results suggest that the concurrent chemotherapy might be more effective when delayed for about 3 weeks, due to lower tumor burden and a larger fraction of proliferating cells after reoxygenation.« less

A carbon dioxide stripping model for mammalian cell culture in manufacturing scale bioreactors.

PubMed

Xing, Zizhuo; Lewis, Amanda M; Borys, Michael C; Li, Zheng Jian

2017-06-01

Control of carbon dioxide within the optimum range is important in mammalian bioprocesses at the manufacturing scale in order to ensure robust cell growth, high protein yields, and consistent quality attributes. The majority of bioprocess development work is done in laboratory bioreactors, in which carbon dioxide levels are more easily controlled. Some challenges in carbon dioxide control can present themselves when cell culture processes are scaled up, because carbon dioxide accumulation is a common feature due to longer gas-residence time of mammalian cell culture in large scale bioreactors. A carbon dioxide stripping model can be used to better understand and optimize parameters that are critical to cell culture processes at the manufacturing scale. The prevailing carbon dioxide stripping models in literature depend on mass transfer coefficients and were applicable to cell culture processes with low cell density or at stationary/cell death phase. However, it was reported that gas bubbles are saturated with carbon dioxide before leaving the culture, which makes carbon dioxide stripping no longer depend on a mass transfer coefficient in the new generation cell culture processes characterized by longer exponential growth phase, higher peak viable cell densities, and higher specific production rate. Here, we present a new carbon dioxide stripping model for manufacturing scale bioreactors, which is independent of carbon dioxide mass transfer coefficient, but takes into account the gas-residence time and gas CO 2 saturation time. The model was verified by CHO cell culture processes with different peak viable cell densities (7 to 12 × 10 6  cells mL -1 ) for two products in 5,000-L and 25,000-L bioreactors. The model was also applied to a next generation cell culture process to optimize cell culture conditions and reduce carbon dioxide levels at manufacturing scale. The model provides a useful tool to understand and better control cell culture carbon dioxide profiles for process development, scale up, and characterization. Biotechnol. Bioeng. 2017;114: 1184-1194. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity

PubMed Central

Anchang, Benedict; Davis, Kara L.; Fienberg, Harris G.; Bendall, Sean C.; Karacosta, Loukia G.; Tibshirani, Robert; Nolan, Garry P.; Plevritis, Sylvia K.

2018-01-01

An individual malignant tumor is composed of a heterogeneous collection of single cells with distinct molecular and phenotypic features, a phenomenon termed intratumoral heterogeneity. Intratumoral heterogeneity poses challenges for cancer treatment, motivating the need for combination therapies. Single-cell technologies are now available to guide effective drug combinations by accounting for intratumoral heterogeneity through the analysis of the signaling perturbations of an individual tumor sample screened by a drug panel. In particular, Mass Cytometry Time-of-Flight (CyTOF) is a high-throughput single-cell technology that enables the simultaneous measurements of multiple (>40) intracellular and surface markers at the level of single cells for hundreds of thousands of cells in a sample. We developed a computational framework, entitled Drug Nested Effects Models (DRUG-NEM), to analyze CyTOF single-drug perturbation data for the purpose of individualizing drug combinations. DRUG-NEM optimizes drug combinations by choosing the minimum number of drugs that produce the maximal desired intracellular effects based on nested effects modeling. We demonstrate the performance of DRUG-NEM using single-cell drug perturbation data from tumor cell lines and primary leukemia samples. PMID:29654148

Assessing the Mechanisms of MDS and Its Transformation to Leukemia in a Novel Humanized Mouse

DTIC Science & Technology

2016-05-01

achievements N/A References N/A References: 1. Rongvaux, A., et al., Development and function of human innate immune cells in a...in cancer survivors. MDS is inherently difficult to study. MDS stem cells cannot be grown in culture and in vivo models are thus the gold standard...However, MDS stem cells are diseased and fail to efficiently engraft in current immunodeficient mouse models. We have optimized engraftment of

Deformation simulation of cells seeded on a collagen-GAG scaffold in a flow perfusion bioreactor using a sequential 3D CFD-elastostatics model.

PubMed

Jungreuthmayer, C; Jaasma, M J; Al-Munajjed, A A; Zanghellini, J; Kelly, D J; O'Brien, F J

2009-05-01

Tissue-engineered bone shows promise in meeting the huge demand for bone grafts caused by up to 4 million bone replacement procedures per year, worldwide. State-of-the-art bone tissue engineering strategies use flow perfusion bioreactors to apply biophysical stimuli to cells seeded on scaffolds and to grow tissue suitable for implantation into the patient's body. The aim of this study was to quantify the deformation of cells seeded on a collagen-GAG scaffold which was perfused by culture medium inside a flow perfusion bioreactor. Using a microCT scan of an unseeded collagen-GAG scaffold, a sequential 3D CFD-deformation model was developed. The wall shear stress and the hydrostatic wall pressure acting on the cells were computed through the use of a CFD simulation and fed into a linear elastostatics model in order to calculate the deformation of the cells. The model used numerically seeded cells of two common morphologies where cells are either attached flatly on the scaffold wall or bridging two struts of the scaffold. Our study showed that the displacement of the cells is primarily determined by the cell morphology. Although cells of both attachment profiles were subjected to the same mechanical load, cells bridging two struts experienced a deformation up to 500 times higher than cells only attached to one strut. As the scaffold's pore size determines both the mechanical load and the type of attachment, the design of an optimal scaffold must take into account the interplay of these two features and requires a design process that optimizes both parameters at the same time.

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling.

PubMed

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.

A Comprehensively Curated Genome-Scale Two-Cell Model for the Heterocystous Cyanobacterium Anabaena sp. PCC 71201[CC-BY

PubMed Central

Steuer, Ralf

2017-01-01

Anabaena sp. PCC 7120 is a nitrogen-fixing filamentous cyanobacterium. Under nitrogen-limiting conditions, a fraction of the vegetative cells in each filament terminally differentiate to nongrowing heterocysts. Heterocysts are metabolically and structurally specialized to enable O2-sensitive nitrogen fixation. The functionality of the filament, as an association of vegetative cells and heterocysts, is postulated to depend on metabolic exchange of electrons, carbon, and fixed nitrogen. In this study, we compile and evaluate a comprehensive curated stoichiometric model of this two-cell system, with the objective function based on the growth of the filament under diazotrophic conditions. The predicted growth rate under nitrogen-replete and -deplete conditions, as well as the effect of external carbon and nitrogen sources, was thereafter verified. Furthermore, the model was utilized to comprehensively evaluate the optimality of putative metabolic exchange reactions between heterocysts and vegetative cells. The model suggested that optimal growth requires at least four exchange metabolites. Several combinations of exchange metabolites resulted in predicted growth rates that are higher than growth rates achieved by only considering exchange of metabolites previously suggested in the literature. The curated model of the metabolic network of Anabaena sp. PCC 7120 enhances our ability to understand the metabolic organization of multicellular cyanobacteria and provides a platform for further study and engineering of their metabolism. PMID:27899536

Mycobacteria Modify Their Cell Size Control under Sub-Optimal Carbon Sources

PubMed Central

Priestman, Miles; Thomas, Philipp; Robertson, Brian D.; Shahrezaei, Vahid

2017-01-01

The decision to divide is the most important one that any cell must make. Recent single cell studies suggest that most bacteria follow an “adder” model of cell size control, incorporating a fixed amount of cell wall material before dividing. Mycobacteria, including the causative agent of tuberculosis Mycobacterium tuberculosis, are known to divide asymmetrically resulting in heterogeneity in growth rate, doubling time, and other growth characteristics in daughter cells. The interplay between asymmetric cell division and adder size control has not been extensively investigated. Moreover, the impact of changes in the environment on growth rate and cell size control have not been addressed for mycobacteria. Here, we utilize time-lapse microscopy coupled with microfluidics to track live Mycobacterium smegmatis cells as they grow and divide over multiple generations, under a variety of growth conditions. We demonstrate that, under optimal conditions, M. smegmatis cells robustly follow the adder principle, with constant added length per generation independent of birth size, growth rate, and inherited pole age. However, the nature of the carbon source induces deviations from the adder model in a manner that is dependent on pole age. Understanding how mycobacteria maintain cell size homoeostasis may provide crucial targets for the development of drugs for the treatment of tuberculosis, which remains a leading cause of global mortality. PMID:28748182

Modelling and fabrication of high-efficiency silicon solar cells

NASA Astrophysics Data System (ADS)

Rohatgi, A.; Smith, A. W.; Salami, J.

1991-10-01

This report covers the research conducted on modelling and development of high efficiency silicon solar cells during the period May 1989 to August 1990. First, considerable effort was devoted toward developing a ray tracing program for the photovoltaic community to quantify and optimize surface texturing for solar cells. Second, attempts were made to develop a hydrodynamic model for device simulation. Such a model is somewhat slower than drift-diffusion type models like PC-1D, but it can account for more physical phenomena in the device, such as hot carrier effects, temperature gradients, thermal diffusion, and lattice heat flow. In addition, Fermi-Dirac statistics have been incorporated into the model to deal with heavy doping effects more accurately. The third and final component of the research includes development of silicon cell fabrication capabilities and fabrication of high efficiency silicon cells.

On the MTD paradigm and optimal control for multi-drug cancer chemotherapy.

PubMed

Ledzewicz, Urszula; Schättler, Heinz; Gahrooi, Mostafa Reisi; Dehkordi, Siamak Mahmoudian

2013-06-01

In standard chemotherapy protocols, drugs are given at maximum tolerated doses (MTD) with rest periods in between. In this paper, we briey discuss the rationale behind this therapy approach and, using as example multidrug cancer chemotherapy with a cytotoxic and cytostatic agent, show that these types of protocols are optimal in the sense of minimizing a weighted average of the number of tumor cells (taken both at the end of therapy and at intermediate times) and the total dose given if it is assumed that the tumor consists of a homogeneous population of chemotherapeutically sensitive cells. A 2-compartment linear model is used to model the pharmacokinetic equations for the drugs.

Mathematical Modeling and Optimization Studies on Development of Fuel Cells for Multifarious Applications

DTIC Science & Technology

2010-05-12

multicomponent steady-state model for liquid -feed solid polymer electrolyte DBFCs. These fuel cells use sodium borohydride (NaBH4) in alkaline media...layers, diffusion layers and the polymer electrolyte membrane for a liquid feed DBFC. Diffusion of reactants within and between the pores is accounted...projected for futuristic portable applications. In this project we developed a three- dimensional, multicomponent steady-state model for liquid -feed solid

Quantifying the importance of pMHC valency, total pMHC dose and frequency on nanoparticle therapeutic efficacy.

PubMed

Sugarman, Jordan; Tsai, Sue; Santamaria, Pere; Khadra, Anmar

2013-05-01

Nanoparticles (NPs) coated with β-cell-specific peptide major histocompatibility complex (pMHC) class I molecules can effectively restore normoglycemia in spontaneously diabetic nonobese diabetic mice. They do so by expanding pools of cognate memory autoreactive regulatory CD8+ T cells that arise from naive low-avidity T-cell precursors to therapeutic levels. Here we develop our previously constructed mathematical model to explore the effects of compound design parameters (NP dose and pMHC valency) on therapeutic efficacy with the underlying hypothesis that the functional correlates of the therapeutic response (expansion of autoregulatory T cells and deletion of autoantigen-loaded antigen-presenting cells by these T cells) are biphasic. We show, using bifurcation analysis, that the model exhibits a 'resonance'-like behavior for a given range of NP dose in which bistability between the healthy state (possessing zero level of effector T-cell population) and autoimmune state (possessing elevated level of the same population) disappears. A heterogeneous population of model mice subjected to several treatment protocols under these new conditions is conducted to quantify both the average percentage of autoregulatory T cells in responsive and nonresponsive model mice, and the average valency-dependent minimal optimal dose needed for effective therapy. Our results reveal that a moderate increase (≥1.6-fold) in the NP-dependent expansion rate of autoregulatory T-cell population leads to a significant increase in the efficacy and the area corresponding to the effective treatment regimen, provided that NP dose ≥8 μg. We expect the model developed here to generalize to other autoimmune diseases and serve as a computational tool to understand and optimize pMHC-NP-based therapies.

Simulation of the Mars Surface Solar Spectra for Optimized Performance of Triple-Junction Solar Cells

NASA Technical Reports Server (NTRS)

Edmondson, Kenneth M.; Joslin, David E.; Fetzer, Chris M.; King, RIchard R.; Karam, Nasser H.; Mardesich, Nick; Stella, Paul M.; Rapp, Donald; Mueller, Robert

2007-01-01

The unparalleled success of the Mars Exploration Rovers (MER) powered by GaInP/GaAs/Ge triple-junction solar cells has demonstrated a lifetime for the rovers that exceeded the baseline mission duration by more than a factor of five. This provides confidence in future longer-term solar powered missions on the surface of Mars. However, the solar cells used on the rovers are not optimized for the Mars surface solar spectrum, which is attenuated at shorter wavelengths due to scattering by the dusty atmosphere. The difference between the Mars surface spectrum and the AM0 spectrum increases with solar zenith angle and optical depth. The recent results of a program between JPL and Spectrolab to optimize GaInP/GaAs/Ge solar cells for Mars are presented. Initial characterization focuses on the solar spectrum at 60-degrees zenith angle at an optical depth of 0.5. The 60-degree spectrum is reduced to 1/6 of the AM0 intensity and is further reduced in the blue portion of the spectrum. JPL has modeled the Mars surface solar spectra, modified an X-25 solar simulator, and completed testing of Mars-optimized solar cells previously developed by Spectrolab with the modified X-25 solar simulator. Spectrolab has focused on the optimization of the higher efficiency Ultra Triple-Junction (UTJ) solar cell for Mars. The attenuated blue portion of the spectrum requires the modification of the top sub-cell in the GaInP/GaAs/Ge solar cell for improved current balancing in the triple-junction cell. Initial characterization confirms the predicted increase in power and current matched operation for the Mars surface 60-degree zenith angle solar spectrum.

Optimization of Glioblastoma Mouse Orthotopic Xenograft Models for Translational Research.

PubMed

Irtenkauf, Susan M; Sobiechowski, Susan; Hasselbach, Laura A; Nelson, Kevin K; Transou, Andrea D; Carlton, Enoch T; Mikkelsen, Tom; deCarvalho, Ana C

2017-08-01

Glioblastoma is an aggressive primary brain tumor predominantly localized to the cerebral cortex. We developed a panel of patient-derived mouse orthotopic xenografts (PDOX) for preclinical drug studies by implanting cancer stem cells (CSC) cultured from fresh surgical specimens intracranially into 8-wk-old female athymic nude mice. Here we optimize the glioblastoma PDOX model by assessing the effect of implantation location on tumor growth, survival, and histologic characteristics. To trace the distribution of intracranial injections, toluidine blue dye was injected at 4 locations with defined mediolateral, anterioposterior, and dorsoventral coordinates within the cerebral cortex. Glioblastoma CSC from 4 patients and a glioblastoma nonstem-cell line were then implanted by using the same coordinates for evaluation of tumor location, growth rate, and morphologic and histologic features. Dye injections into one of the defined locations resulted in dye dissemination throughout the ventricles, whereas tumor cell implantation at the same location resulted in a much higher percentage of small multifocal ventricular tumors than did the other 3 locations tested. Ventricular tumors were associated with a lower tumor growth rate, as measured by in vivo bioluminescence imaging, and decreased survival in 4 of 5 cell lines. In addition, tissue oxygenation, vasculature, and the expression of astrocytic markers were altered in ventricular tumors compared with nonventricular tumors. Based on this information, we identified an optimal implantation location that avoided the ventricles and favored cortical tumor growth. To assess the effects of stress from oral drug administration, mice that underwent daily gavage were compared with stress-positive and -negative control groups. Oral gavage procedures did not significantly affect the survival of the implanted mice or physiologic measurements of stress. Our findings document the importance of optimization of the implantation site for preclinical mouse models of glioblastoma.

Optimization of Glioblastoma Mouse Orthotopic Xenograft Models for Translational Research

PubMed Central

Irtenkauf, Susan M; Sobiechowski, Susan; Hasselbach, Laura A; Nelson, Kevin K; Transou, Andrea D; Carlton, Enoch T; Mikkelsen, Tom; deCarvalho, Ana C

2017-01-01

Glioblastoma is an aggressive primary brain tumor predominantly localized to the cerebral cortex. We developed a panel of patient-derived mouse orthotopic xenografts (PDOX) for preclinical drug studies by implanting cancer stem cells (CSC) cultured from fresh surgical specimens intracranially into 8-wk-old female athymic nude mice. Here we optimize the glioblastoma PDOX model by assessing the effect of implantation location on tumor growth, survival, and histologic characteristics. To trace the distribution of intracranial injections, toluidine blue dye was injected at 4 locations with defined mediolateral, anterioposterior, and dorsoventral coordinates within the cerebral cortex. Glioblastoma CSC from 4 patients and a glioblastoma nonstem-cell line were then implanted by using the same coordinates for evaluation of tumor location, growth rate, and morphologic and histologic features. Dye injections into one of the defined locations resulted in dye dissemination throughout the ventricles, whereas tumor cell implantation at the same location resulted in a much higher percentage of small multifocal ventricular tumors than did the other 3 locations tested. Ventricular tumors were associated with a lower tumor growth rate, as measured by in vivo bioluminescence imaging, and decreased survival in 4 of 5 cell lines. In addition, tissue oxygenation, vasculature, and the expression of astrocytic markers were altered in ventricular tumors compared with nonventricular tumors. Based on this information, we identified an optimal implantation location that avoided the ventricles and favored cortical tumor growth. To assess the effects of stress from oral drug administration, mice that underwent daily gavage were compared with stress-positive and ‑negative control groups. Oral gavage procedures did not significantly affect the survival of the implanted mice or physiologic measurements of stress. Our findings document the importance of optimization of the implantation site for preclinical mouse models of glioblastoma. PMID:28830577

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

PubMed

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.

Dynamic modeling, experimental evaluation, optimal design and control of integrated fuel cell system and hybrid energy systems for building demands

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.

Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane

NASA Technical Reports Server (NTRS)

Conners, Timothy R.

1992-01-01

Results are presented from the evaluation of the performance seeking control (PSC) optimization algorithm developed by Smith et al. (1990) for F-15 aircraft, which optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. Comparisons are presented between the load cell measurements, PSC onboard model thrust calculations, and posttest state variable model computations. Actual performance improvements using the PSC algorithm are presented for its various modes. The results of using PSC algorithm are compared with similar test case results using the HIDEC algorithm.

Oxygen supply for CHO cells immobilized on a packed-bed of Fibra-Cel disks.

PubMed

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.

Multi-phase models for water and thermal management of proton exchange membrane fuel cell: A review

NASA Astrophysics Data System (ADS)

Zhang, Guobin; Jiao, Kui

2018-07-01

The 3D (three-dimensional) multi-phase CFD (computational fluid dynamics) model is widely utilized in optimizing water and thermal management of PEM (proton exchange membrane) fuel cell. However, a satisfactory 3D multi-phase CFD model which is able to simulate the detailed gas and liquid two-phase flow in channels and reflect its effect on performance precisely is still not developed due to the coupling difficulties and computation amount. Meanwhile, the agglomerate model of CL (catalyst layer) should also be added in 3D CFD model so as to better reflect the concentration loss and optimize CL structure in macroscopic scale. Besides, the effect of thermal management is perhaps underestimated in current 3D multi-phase CFD simulations due to the lack of coolant channel in computation domain and constant temperature boundary condition. Therefore, the 3D CFD simulations in cell and stack levels with convection boundary condition are suggested to simulate the water and thermal management more accurately. Nevertheless, with the rapid development of PEM fuel cell, current 3D CFD simulations are far from practical demand, especially at high current density and low to zero humidity and for the novel designs developed recently, such as: metal foam flow field, 3D fine mesh flow field, anode circulation etc.

Optimization of micro-fabricated porous membranes for intestinal epithelial cell culture and in vitro modeling of the human intestinal barrier

NASA Astrophysics Data System (ADS)

Nair Gourikutty Sajay, Bhuvanendran; Yin, Chiam Su; Ramadan, Qasem

2017-12-01

In vitro modeling of organs could provide a controlled platform for studying physiological events and has great potential in the field of pharmaceutical development. Here, we describe the characterization of in vitro modeling of the human intestinal barrier mimicked using silicon porous membranes as a substrate. To mimic an intestinal in vivo setup as closely as possible, a porous substrate is required in a dynamic environment for the cells to grow rather than a static setup with an impermeable surface such as a petri dish. In this study, we focus on the detailed characterization of Caco-2 cells cultured on a silicon membrane with different pore sizes as well as the effect of dynamic fluid flow on the model. The porous silicon membrane together with continuous perfusion of liquid applying shear stress on the cells enhances the differentiation of polarized cells by providing access to the both their basal and apical surfaces. Membranes with pore sizes of 0.5-3 µm were used and a shear stress of ~0.03 dyne cm-2 was created by applying a low flow rate of 20 nl s-1. By providing these optimized conditions, cells were able to differentiate with columnar morphology, which developed microvilli structures on their apical side and tight junctions between adjacent cells like those in a healthy human intestinal barrier. In this setup, it is possible to study the important cellular functions of the intestine such as transport, absorption and secretion, and thus this model has great potential in drug screening.

Will stem cell therapies be safe and effective for treating spinal cord injuries?

PubMed Central

Thomas, Katharine E.; Moon, Lawrence D. F.

2017-01-01

Introduction A large number of different cells including embryonic and adult stem cells have been transplanted into animal models of spinal cord injury, and in many cases these procedures have resulted in modest sensorimotor benefits. In October 2010 the world’s first clinical trial using human embryonic stem cells began, using stem cells converted into oligodendrocyte precursor cells. Sources of data In this review we examine some of the publically-available pre-clinical evidence that some of these cell types improve outcome in animal models of spinal cord injury. Much evidence is not available for public scrutiny, however, being private commercial property of various stem cell companies. Areas of agreement Transplantation of many different types of stem and progenitor cell enhances spontaneous recovery of function when transplanted acutely after spinal cord injury in animal models. Areas of disagreement The common mechanism(s) whereby the generic procedure of cellular transplantation enhances recovery of function are not well understood, although a range of possibilities are usually cited (including preservation of tissue, remyelination, axon sprouting, glial cell replacement). Only in exceptional cases has it been shown that functional recovery depends causally on the survival and differentiation of the transplanted cells. There is no agreement about the optimal cell type for transplantation: candidate stem cells have not yet been compared with each other or with other cell types (e.g., autologous Schwann cells) in a single study. Areas timely for developing research Transplantation of cells into animals with a long lifespan is important to determine whether or not tumours will eventually form. It will also be important to determine whether long-term survival of cells is required for functional recovery, and if so, how many are optimal. PMID:21586446

A Substance Exchanger-Based Bioreactor Culture of Pig Discs for Studying the Immature Nucleus Pulposus.

PubMed

Li, Pei; Gan, Yibo; Wang, Haoming; Xu, Yuan; Song, Lei; Wang, Liyuan; Ouyang, Bin; Zhou, Qiang

2017-11-01

Various research models have been developed to study the biology of disc cells. Recently, the adult disc nucleus pulposus (NP) has been well studied. However, the immature NP is underinvestigated due to a lack of a suitable model. This study aimed to establish an organ culture of immature porcine disc by optimizing culture conditions and using a self-developed substance exchanger-based bioreactor. Immature porcine discs were first cultured in the bioreactor for 7 days at various levels of glucose (low, medium, high), osmolarity (hypo-, iso-, hyper-) and serum (5, 10, 20%) to determine the respective optimal level. The porcine discs were then cultured under the optimized conditions in the novel bioreactor, and were compared with fresh discs at day 14. For high-glucose, iso-osmolarity, or 10% serum, cell viability, the gene expression profile (for anabolic genes and catabolic genes), and glycosaminoglycan (GAG) and hydroxyproline (HYP) contents were more favorable than for other levels of glucose, osmolarity, and serum. When the immature discs were cultured under the optimized conditions using the novel bioreactor for 14 days, the viability of the immature NP was maintained based on histology, cell viability, GAG and HYP contents, and matrix molecule expression. In conclusion, the viability of the immature NP in organ culture could be maintained under the optimized culture conditions (high-glucose, iso-osmolarity, and 10% serum) in the substance exchanger-based bioreactor. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Population Pharmacokinetics and Optimal Sampling Strategy for Model-Based Precision Dosing of Melphalan in Patients Undergoing Hematopoietic Stem Cell Transplantation.

PubMed

Mizuno, Kana; Dong, Min; Fukuda, Tsuyoshi; Chandra, Sharat; Mehta, Parinda A; McConnell, Scott; Anaissie, Elias J; Vinks, Alexander A

2018-05-01

High-dose melphalan is an important component of conditioning regimens for patients undergoing hematopoietic stem cell transplantation. The current dosing strategy based on body surface area results in a high incidence of oral mucositis and gastrointestinal and liver toxicity. Pharmacokinetically guided dosing will individualize exposure and help minimize overexposure-related toxicity. The purpose of this study was to develop a population pharmacokinetic model and optimal sampling strategy. A population pharmacokinetic model was developed with NONMEM using 98 observations collected from 15 adult patients given the standard dose of 140 or 200 mg/m 2 by intravenous infusion. The determinant-optimal sampling strategy was explored with PopED software. Individual area under the curve estimates were generated by Bayesian estimation using full and the proposed sparse sampling data. The predictive performance of the optimal sampling strategy was evaluated based on bias and precision estimates. The feasibility of the optimal sampling strategy was tested using pharmacokinetic data from five pediatric patients. A two-compartment model best described the data. The final model included body weight and creatinine clearance as predictors of clearance. The determinant-optimal sampling strategies (and windows) were identified at 0.08 (0.08-0.19), 0.61 (0.33-0.90), 2.0 (1.3-2.7), and 4.0 (3.6-4.0) h post-infusion. An excellent correlation was observed between area under the curve estimates obtained with the full and the proposed four-sample strategy (R 2  = 0.98; p < 0.01) with a mean bias of -2.2% and precision of 9.4%. A similar relationship was observed in children (R 2  = 0.99; p < 0.01). The developed pharmacokinetic model-based sparse sampling strategy promises to achieve the target area under the curve as part of precision dosing.

A comparison of GaAs and Si hybrid solar power systems

NASA Technical Reports Server (NTRS)

Heinbockel, J. H.; Roberts, A. S., Jr.

1977-01-01

Five different hybrid solar power systems using silicon solar cells to produce thermal and electric power are modeled and compared with a hybrid system using a GaAs cell. Among the indices determined are capital cost per unit electric power plus mechanical power, annual cost per unit electric energy, and annual cost per unit electric plus mechanical work. Current costs are taken to be $35,000/sq m for GaAs cells with an efficiency of 15% and $1000/sq m for Si cells with an efficiency of 10%. It is shown that hybrid systems can be competitive with existing methods of practical energy conversion. Limiting values for annual costs of Si and GaAs cells are calculated to be 10.3 cents/kWh and 6.8 cents/kWh, respectively. Results for both systems indicate that for a given flow rate there is an optimal operating condition for minimum cost photovoltaic output. For Si cell costs of $50/sq m optimal performance can be achieved at concentrations of about 10; for GaAs cells costing 1000/sq m, optimal performance can be obtained at concentrations of around 100. High concentration hybrid systems offer a distinct cost advantage over flat systems.

Reliability evaluation of high-performance, low-power FinFET standard cells based on mixed RBB/FBB technique

NASA Astrophysics Data System (ADS)

Wang, Tian; Cui, Xiaoxin; Ni, Yewen; Liao, Kai; Liao, Nan; Yu, Dunshan; Cui, Xiaole

2017-04-01

With shrinking transistor feature size, the fin-type field-effect transistor (FinFET) has become the most promising option in low-power circuit design due to its superior capability to suppress leakage. To support the VLSI digital system flow based on logic synthesis, we have designed an optimized high-performance low-power FinFET standard cell library based on employing the mixed FBB/RBB technique in the existing stacked structure of each cell. This paper presents the reliability evaluation of the optimized cells under process and operating environment variations based on Monte Carlo analysis. The variations are modelled with Gaussian distribution of the device parameters and 10000 sweeps are conducted in the simulation to obtain the statistical properties of the worst-case delay and input-dependent leakage for each cell. For comparison, a set of non-optimal cells that adopt the same topology without employing the mixed biasing technique is also generated. Experimental results show that the optimized cells achieve standard deviation reduction of 39.1% and 30.7% at most in worst-case delay and input-dependent leakage respectively while the normalized deviation shrinking in worst-case delay and input-dependent leakage can be up to 98.37% and 24.13%, respectively, which demonstrates that our optimized cells are less sensitive to variability and exhibit more reliability. Project supported by the National Natural Science Foundation of China (No. 61306040), the State Key Development Program for Basic Research of China (No. 2015CB057201), the Beijing Natural Science Foundation (No. 4152020), and Natural Science Foundation of Guangdong Province, China (No. 2015A030313147).

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

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.

Bifurcation-based approach reveals synergism and optimal combinatorial perturbation.

PubMed

Liu, Yanwei; Li, Shanshan; Liu, Zengrong; Wang, Ruiqi

2016-06-01

Cells accomplish the process of fate decisions and form terminal lineages through a series of binary choices in which cells switch stable states from one branch to another as the interacting strengths of regulatory factors continuously vary. Various combinatorial effects may occur because almost all regulatory processes are managed in a combinatorial fashion. Combinatorial regulation is crucial for cell fate decisions because it may effectively integrate many different signaling pathways to meet the higher regulation demand during cell development. However, whether the contribution of combinatorial regulation to the state transition is better than that of a single one and if so, what the optimal combination strategy is, seem to be significant issue from the point of view of both biology and mathematics. Using the approaches of combinatorial perturbations and bifurcation analysis, we provide a general framework for the quantitative analysis of synergism in molecular networks. Different from the known methods, the bifurcation-based approach depends only on stable state responses to stimuli because the state transition induced by combinatorial perturbations occurs between stable states. More importantly, an optimal combinatorial perturbation strategy can be determined by investigating the relationship between the bifurcation curve of a synergistic perturbation pair and the level set of a specific objective function. The approach is applied to two models, i.e., a theoretical multistable decision model and a biologically realistic CREB model, to show its validity, although the approach holds for a general class of biological systems.

Design of high-efficiency, radiation-hard, GaInP/GaAs solar cells

NASA Technical Reports Server (NTRS)

Kurtz, Sarah R.; Bertness, K. A.; Kibbler, A. E.; Kramer, C.; Olson, J. M.

1994-01-01

In recently years, Ga(0.5)In((0.5)P/GaAs cells have drawn increased attention both because of their high efficiencies and because they are well suited for space applications. They can be grown and processed as two-junction devices with roughly twice the voltage and half the current of GaAs cells. They have low temperature coefficients, and have good potential for radiation hardness. We have previously reported the effects of electron irradiation on test cells which were not optimally designed for space. From those results we estimated that an optimally designed cell could achieve 20 percent after irradiation with 10(exp 15) cm(exp -2) 1 MeV electrons. Modeling studies predicted that slightly higher efficiencies may be achievable. Record efficiencies for EOL performance of other types of cells are significantly lower. Even the best Si and InP cells have BOL efficiencies lower than the EOL efficiency we report here. Good GaAs cells have an EOL efficiency of 16 percent. The InP/Ga(0.5)In(0.5)As two-junction, two-terminal device has a BOL efficiency as high as 22.2 percent, but radiation results for these cells were limited. In this study we use the previous modeling and irradiation results to design a set of Ga(0.5)In(0.5)P/GaAs cells that will demonstrate the importance of the design parameters and result in high-efficiency devices. We report record AMO efficiencies: a BOL efficiency of 25.7 percent for a device optimized for BOL performance and two of different designs with EOL efficiencies of 19.6 percent (at 10(exp 15) cm(exp -2) 1MeV electrons). We vary the bottom-cell base doping and the top-cell thickness to show the effects of these two important design parameters. We get an unexpected result indicating that the dopant added to the bottom-cell base also increases the degradation of the top cell.

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex

PubMed Central

Coppola, David; White, Leonard E.; Wolf, Fred

2015-01-01

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1’s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models. PMID:26575467

Curcumin-loaded chitosan-cholesterol micelles: evaluation in monolayers and 3D cancer spheroid model.

PubMed

Muddineti, Omkara Swami; Kumari, Preeti; Ray, Eupa; Ghosh, Balaram; Biswas, Swati

2017-06-02

To improve the bioavailability and anticancer potential of curcumin by using a cholesterol-conjugated chitosan micelle. Methods & methods: Cholesterol was conjugated to chitosan (15 kDa) to form self-assembled micelles, which loaded curcumin. Physicochemical characterization and formulation optimization of the drug-loaded micelles (curcumin-loaded chitosan-cholesterol micelles [C-CCM]) were performed. In vitro cellular uptake and viability of C-CCM were investigated in melanoma and breast cancer cell lines. The antitumor efficacy was evaluated in 3D lung cancer spheroid model. The optimized C-CCM had size of approximately 162 nm with loading efficiency of approximately 36%. C-CCM was taken up efficiently by the cells, and it reduced cancer cell viability significantly compared with free curcumin. C-CCM enhanced the antitumor efficacy in spheroids, suggesting that C-CCM could be used as an effective chemotherapy in cancer.

Investigating the Functional Role of Prostate-Specific Membrane Antigen and its Enzymatic Activity in Prostate Cancer Metastasis

DTIC Science & Technology

2008-02-01

fluorescent probes for live cell imaging . PSMA distribution of cells grown on different extracellular matrices will be characterized to provide guidance...PCa migration, using in vitro cell model systems and live - cell imaging methods, we characterized the role of PSMA in cell motility and adhesion. Using...Generated fluorescently conjugated anti-PSMA antibodies for live cell imaging . 2. Optimized the siRNA-PSMA transfection and achieved an approximately

Metformin Preconditioning of Human induced Pluripotent Stem Cell-derived Neural Stem Cells Promotes Their Engraftment and Improves Post-Stroke Regeneration and Recovery.

PubMed

Ould-Brahim, Fares; Sarma, Sailendra Nath; Syal, Charvi; Lu, Kevin Jiaqi; Seegobin, Matthew; Carter, Anthony; Jeffers, Matthew S; Doré, Carole; Stanford, William; Corbett, Dale; Wang, Jing

2018-06-12

While transplantation of hiPSC-derived neural stem cells (hiPSC-NSCs) shows therapeutic potential in animal stroke models, major concerns for translating hiPSC therapy to the clinic are efficacy and safety. Therefore, there is a demand to develop an optimal strategy to enhance the engraftment and regenerative capacity of transplanted hiPSC-NSCs in order to produce fully differentiated neural cells to replace lost brain tissues. Metformin, an FDA approved drug, is an optimal neuroregenerative agent that not only promotes NSC proliferation but also drives NSC towards differentiation. In this regard, we hypothesize that preconditioning of hiPSC-NSCs with metformin before transplantation into the stroke-damaged brain will improve engraftment and regenerative capabilities of hiPSC-NSCs, ultimately enhancing functional recovery. Here we show that pretreatment of hiPSC-NSCs with metformin enhances the proliferation and differentiation of hiPSC-NSCs in culture. Furthermore, metformin-preconditioned hiPSC-NSCs show increased engraftment 1-week post-transplant in a rat endothelin-1 focal ischemic stroke model. In addition, metformin preconditioned cell grafts exhibit increased survival compared to naïve cell grafts at 7-week post-transplant. Analysis of the grafts demonstrates that metformin preconditioning enhances the differentiation of hiPSC-NSCs. As an outcome, rats receiving metformin preconditioned cells display accelerated gross motor recovery and reduced infarct volume. These studies represent a vital step forward in the optimization of hiPSC-NSC based transplantation to promote post-stroke recovery.

An Improved Model for Nucleation-Limited Ice Formation in Living Cells during Freezing

PubMed Central

Zhao, Gang; He, Xiaoming

2014-01-01

Ice formation in living cells is a lethal event during freezing and its characterization is important to the development of optimal protocols for not only cryopreservation but also cryotherapy applications. Although the model for probability of ice formation (PIF) in cells developed by Toner et al. has been widely used to predict nucleation-limited intracellular ice formation (IIF), our data of freezing Hela cells suggest that this model could give misleading prediction of PIF when the maximum PIF in cells during freezing is less than 1 (PIF ranges from 0 to 1). We introduce a new model to overcome this problem by incorporating a critical cell volume to modify the Toner's original model. We further reveal that this critical cell volume is dependent on the mechanisms of ice nucleation in cells during freezing, i.e., surface-catalyzed nucleation (SCN) and volume-catalyzed nucleation (VCN). Taken together, the improved PIF model may be valuable for better understanding of the mechanisms of ice nucleation in cells during freezing and more accurate prediction of PIF for cryopreservation and cryotherapy applications. PMID:24852166

Flow cells for bioanalytical and bioprocess applications with optimized dynamic response and flow characteristics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lancaster, V.R.; Modlin, D.N.

1994-12-31

In this study, the authors present a method for design and characterization of flow cells developed for minimum flow volume and optimal dynamic response with a given central observation area. The dynamic response of a circular shaped dual ported flow cell was compared to that obtained from a flow cell whose optimized shape was determined using this method. In the optimized flow cell design, the flow rate at the nominal operating pressure increased by 50% whereas the flow cell volume was reduced by 70%. In addition, the dynamic response of the new flow cell was found to be 200% fastermore » than the circular flow cell. The fluid dynamic analysis included simple graphical techniques utilizing free stream vorticity functions and Hagen-Poiseuille relationships. The flow cell dynamic response was measured using a fluorescence detection system. The fluoresce in emission from a 400{micro}m spot located at the exit port was measured as a function of time after switching the input to the flow cell between fluorescent and non-fluorescent solutions. Analysis of results revealed the system could be reasonably characterized as a first order dynamic system. Although some evidence of second order behavior was also observed, it is reasonable to assume that a first order model will provide adequate predictive capability for many real world applications. Given a set of flow cell requirements, the methods presented in this study can be used to design and characterize flow cells with lower reagent consumption and reduced purging times. These improvements can be readily translated into reduced process times and/or lower usage of high cost reagents.« less

Optimization of enhanced bioelectrical reactor with electricity from microbial fuel cells for groundwater nitrate removal.

PubMed

Liu, Ye; Zhang, Baogang; Tian, Caixing; Feng, Chuanping; Wang, Zhijun; Cheng, Ming; Hu, Weiwu

2016-01-01

Factors influencing the performance of a continual-flow bioelectrical reactor (BER) intensified by microbial fuel cells for groundwater nitrate removal, including nitrate load, carbon source and hydraulic retention time (HRT), were investigated and optimized by response surface methodology (RSM). With the target of maximum nitrate removal and minimum intermediates accumulation, nitrate load (for nitrogen) of 60.70 mg/L, chemical oxygen demand (COD) of 849.55 mg/L and HRT of 3.92 h for the BER were performed. COD was the dominant factor influencing performance of the system. Experimental results indicated the undistorted simulation and reliable optimized values. These demonstrate that RSM is an effective method to evaluate and optimize the nitrate-reducing performance of the present system and can guide mathematical models development to further promote its practical applications.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Dynamic optimal control of homeostasis: an integrative system approach for modeling of the central nitrogen metabolism in Saccharomyces cerevisiae.

PubMed

van Riel, N A; Giuseppin, M L; Verrips, C T

2000-01-01

The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the source of the cellular amino acids and proteins, including flavors and potentially valuable biomolecules; therefore, it is also of industrial interest. In the DOMC approach the cell is regarded as an optimally controlled system. Given the metabolic genotype, the cell faces a control problem to maintain an optimal flux distribution in a changing environment. The regulation is based on strategies and balances feedback control of homeostasis and feedforward regulation for adaptation. The DOMC approach is an integrative, holistic approach, not based on mechanistic descriptions and (therefore) not biased by the variation present in biochemical and molecular biological data. It is an effective tool to structure the rapidly increasing amount of data on the function of genes and pathways. The DOMC model is used successfully to predict the responses of pulses of ammonia and glutamine to nitrogen-limited continuous cultures of a wild-type strain and a glutamine synthetase-negative mutant. The simulation results are validated with experimental data.

MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design

NASA Astrophysics Data System (ADS)

Torrents, A.; Azgin, K.; Godfrey, S. W.; Topalli, E. S.; Akin, T.; Valdevit, L.

2010-12-01

This paper presents the design, optimization and manufacturing of a novel micro-fabricated load cell based on a double-ended tuning fork. The device geometry and operating voltages are optimized for maximum force resolution and range, subject to a number of manufacturing and electromechanical constraints. All optimizations are enabled by analytical modeling (verified by selected finite elements analyses) coupled with an efficient C++ code based on the particle swarm optimization algorithm. This assessment indicates that force resolutions of ~0.5-10 nN are feasible in vacuum (~1-50 mTorr), with force ranges as large as 1 N. Importantly, the optimal design for vacuum operation is independent of the desired range, ensuring versatility. Experimental verifications on a sub-optimal device fabricated using silicon-on-glass technology demonstrate a resolution of ~23 nN at a vacuum level of ~50 mTorr. The device demonstrated in this article will be integrated in a hybrid micro-mechanical test frame for unprecedented combinations of force resolution and range, displacement resolution and range, optical (or SEM) access to the sample, versatility and cost.

Optimization and control of perfusion cultures using a viable cell probe and cell specific perfusion rates.

PubMed

Dowd, Jason E; Jubb, Anthea; Kwok, K Ezra; Piret, James M

2003-05-01

Consistent perfusion culture production requires reliable cell retention and control of feed rates. An on-line cell probe based on capacitance was used to assay viable biomass concentrations. A constant cell specific perfusion rate controlled medium feed rates with a bioreactor cell concentration of approximately 5 x 10(6) cells mL(-1). Perfusion feeding was automatically adjusted based on the cell concentration signal from the on-line biomass sensor. Cell specific perfusion rates were varied over a range of 0.05 to 0.4 nL cell(-1) day(-1). Pseudo-steady-state bioreactor indices (concentrations, cellular rates and yields) were correlated to cell specific perfusion rates investigated to maximize recombinant protein production from a Chinese hamster ovary cell line. The tissue-type plasminogen activator concentration was maximized ( approximately 40 mg L(-1)) at 0.2 nL cell(-1) day(-1). The volumetric protein productivity ( approximately 60 mg L(-1) day(-1) was maximized above 0.3 nL cell(-1) day(-1). The use of cell specific perfusion rates provided a straightforward basis for controlling, modeling and optimizing perfusion cultures.

Optimization of culture medium for novel cell-associated tannase production from Bacillus massiliensis using response surface methodology.

PubMed

Belur, Prasanna D; Goud, Rakesh; Goudar, Dinesh C

2012-02-01

Naturally immobilized tannase (tannin acyl hydrolase, E.C. 3.1.1.20) has many advantages, as it avoids the expensive and laborious operation of isolation, purification, and immobilization, plus it is highly stable in adverse pH and temperature. However, in the case of cell-associated enzymes, since the enzyme is associated with the biomass, separation of the pure biomass is necessary. However, tannic acid, a known inducer of tannase, forms insoluble complexes with media proteins, making it difficult to separate pure biomass. Therefore, this study optimizes the production of cell-associated tannase using a "protein-tannin complex" free media. An exploratory study was first conducted in shake-flasks to select the inducer, carbon source, and nitrogen sources. As a result it was found that gallic acid induces tannase synthesis, a tryptose broth gives higher biomass, and lactose supplementation is beneficial. The medium was then optimized using response surface methodology based on the full factorial central composite design in a 3 l bioreactor. A 2(3) factorial design augmented by 7 axial points (alpha = 1.682) and 2 replicates at the center point was implemented in 17 experiments. A mathematical model was also developed to show the effect of each medium component and their interactions on the production of cell-associated tannase. The validity of the proposed model was verified, and the optimized medium was shown to produce maximum cell-associated tannase activity of 9.65 U/l, which is 93.8% higher than the activity in the basal medium, after 12 h at pH 5.0, 30 degrees C. The optimum medium consists of 38 g/l lactose, 50 g/l tryptose, and 2.8 g/l gallic acid.

Analysis Balance Parameter of Optimal Ramp metering

NASA Astrophysics Data System (ADS)

Li, Y.; Duan, N.; Yang, X.

2018-05-01

Ramp metering is a motorway control method to avoid onset congestion through limiting the access of ramp inflows into the main road of the motorway. The optimization model of ramp metering is developed based upon cell transmission model (CTM). With the piecewise linear structure of CTM, the corresponding motorway traffic optimization problem can be formulated as a linear programming (LP) problem. It is known that LP problem can be solved by established solution algorithms such as SIMPLEX or interior-point methods for the global optimal solution. The commercial software (CPLEX) is adopted in this study to solve the LP problem within reasonable computational time. The concept is illustrated through a case study of the United Kingdom M25 Motorway. The optimal solution provides useful insights and guidances on how to manage motorway traffic in order to maximize the corresponding efficiency.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugano, Yasutaka; Mizuta, Masahiro; Takao, Seishin

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of themore » tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.« less

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

PubMed

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Studies of mineralization in tissue culture: optimal conditions for cartilage calcification

NASA Technical Reports Server (NTRS)

Boskey, A. L.; Stiner, D.; Doty, S. B.; Binderman, I.; Leboy, P.

1992-01-01

The optimal conditions for obtaining a calcified cartilage matrix approximating that which exists in situ were established in a differentiating chick limb bud mesenchymal cell culture system. Using cells from stage 21-24 embryos in a micro-mass culture, at an optimal density of 0.5 million cells/20 microliters spot, the deposition of small crystals of hydroxyapatite on a collagenous matrix and matrix vesicles was detected by day 21 using X-ray diffraction, FT-IR microscopy, and electron microscopy. Optimal media, containing 1.1 mM Ca, 4 mM P, 25 micrograms/ml vitamin C, 0.3 mg/ml glutamine, no Hepes buffer, and 10% fetal bovine serum, produced matrix resembling the calcifying cartilage matrix of fetal chick long bones. Interestingly, higher concentrations of fetal bovine serum had an inhibitory effect on calcification. The cartilage phenotype was confirmed based on the cellular expression of cartilage collagen and proteoglycan mRNAs, the presence of type II and type X collagen, and cartilage type proteoglycan at the light microscopic level, and the presence of chondrocytes and matrix vesicles at the EM level. The system is proposed as a model for evaluating the events in cell mediated cartilage calcification.

A Finite Element Study of Micropipette Aspiration of Single Cells: Effect of Compressibility

PubMed Central

Jafari Bidhendi, Amirhossein; Korhonen, Rami K.

2012-01-01

Micropipette aspiration (MA) technique has been widely used to measure the viscoelastic properties of different cell types. Cells experience nonlinear large deformations during the aspiration procedure. Neo-Hookean viscohyperelastic (NHVH) incompressible and compressible models were used to simulate the creep behavior of cells in MA, particularly accounting for the effect of compressibility, bulk relaxation, and hardening phenomena under large strain. In order to find optimal material parameters, the models were fitted to the experimental data available for mesenchymal stem cells. Finally, through Neo-Hookean porohyperelastic (NHPH) material model for the cell, the influence of fluid flow on the aspiration length of the cell was studied. Based on the results, we suggest that the compressibility and bulk relaxation/fluid flow play a significant role in the deformation behavior of single cells and should be taken into account in the analysis of the mechanics of cells. PMID:22400045

Surgery on spinal epidural metastases (SEM) in renal cell carcinoma: a plea for a new paradigm.

PubMed

Bakker, Nicolaas A; Coppes, Maarten H; Vergeer, Rob A; Kuijlen, Jos M A; Groen, Rob J M

2014-09-01

Prediction models for outcome of decompressive surgical resection of spinal epidural metastases (SEM) have in common that they have been developed for all types of SEM, irrespective of the type of primary tumor. It is our experience in clinical practice, however, that these models often fail to accurately predict outcome in the individual patient. To investigate whether decision making could be optimized by applying tumor-specific prediction models. For the proof of concept, we analyzed patients with SEM from renal cell carcinoma that we have operated on. Retrospective chart analysis 2006 to 2012. Twenty-one consecutive patients with symptomatic SEM of renal cell carcinoma. Predictive factors for survival. Next to established predictive factors for survival, we analyzed the predictive value of the Motzer criteria in these patients. The Motzer criteria comprise a specific and validated risk model for survival in patients with renal cell carcinoma. After multivariable analysis, only Motzer intermediate (hazard ratio [HR] 17.4, 95% confidence interval [CI] 1.82-166, p=.01) and high risk (HR 39.3, 95% CI 3.10-499, p=.005) turned out to be significantly associated with survival in patients with renal cell carcinoma that we have operated on. In this study, we have demonstrated that decision making could have been optimized by implementing the Motzer criteria next to established prediction models. We, therefore, suggest that in future, in patients with SEM from renal cell carcinoma, the Motzer criteria are also taken into account. Copyright © 2014 Elsevier Inc. All rights reserved.

An intracellular analysis of the visual responses of neurones in cat visual cortex.

PubMed Central

Douglas, R J; Martin, K A; Whitteridge, D

1991-01-01

1. Extracellular and intracellular recordings were made from neurones in the visual cortex of the cat in order to compare the subthreshold membrane potentials, reflecting the input to the neurone, with the output from the neurone seen as action potentials. 2. Moving bars and edges, generated under computer control, were used to stimulate the neurones. The membrane potential was digitized and averaged for a number of trials after stripping the action potentials. Comparison of extracellular and intracellular discharge patterns indicated that the intracellular impalement did not alter the neurones' properties. Input resistance of the neurone altered little during stable intracellular recordings (30 min-2 h 50 min). 3. Intracellular recordings showed two distinct patterns of membrane potential changes during optimal visual stimulation. The patterns corresponded closely to the division of S-type (simple) and C-type (complex) receptive fields. Simple cells had a complex pattern of membrane potential fluctuations, involving depolarizations alternating with hyperpolarizations. Complex cells had a simple single sustained plateau of depolarization that was often followed but not preceded by a hyperpolarization. In both simple and complex cells the depolarizations led to action potential discharges. The hyperpolarizations were associated with inhibition of action potential discharge. 4. Stimulating simple cells with non-optimal directions of motion produced little or no hyperpolarization of the membrane in most cases, despite a lack of action potential output. Directional complex cells always produced a single plateau of depolarization leading to action potential discharge in both the optimal and non-optimal directions of motion. The directionality could not be predicted on the basis of the position of the hyperpolarizing inhibitory potentials found in the optimal direction. 5. Stimulation of simple cells with non-optimal orientations occasionally produced slight hyperpolarizations and inhibition of action potential discharge. Complex cells, which had broader orientation tuning than simple cells, could show marked hyperpolarization for non-optimal orientations, but this was not generally the case. 6. The data do not support models of directionality and orientation that rely solely on strong inhibitory mechanisms to produce stimulus selectivity. PMID:1804981

Comparative study of four immortalized human brain capillary endothelial cell lines, hCMEC/D3, hBMEC, TY10, and BB19, and optimization of culture conditions, for an in vitro blood–brain barrier model for drug permeability studies

PubMed Central

2013-01-01

Background Reliable human in vitro blood–brain barrier (BBB) models suitable for high-throughput screening are urgently needed in early drug discovery and development for assessing the ability of promising bioactive compounds to overcome the BBB. To establish an improved human in vitro BBB model, we compared four currently available and well characterized immortalized human brain capillary endothelial cell lines, hCMEC/D3, hBMEC, TY10, and BB19, with respect to barrier tightness and paracellular permeability. Co-culture systems using immortalized human astrocytes (SVG-A cell line) and immortalized human pericytes (HBPCT cell line) were designed with the aim of positively influencing barrier tightness. Methods Tight junction (TJ) formation was assessed by transendothelial electrical resistance (TEER) measurements using a conventional epithelial voltohmmeter (EVOM) and an automated CellZscope system which records TEER and cell layer capacitance (CCL) in real-time. Paracellular permeability was assessed using two fluorescent marker compounds with low BBB penetration (sodium fluorescein (Na-F) and lucifer yellow (LY)). Conditions were optimized for each endothelial cell line by screening a series of 24-well tissue culture inserts from different providers. For hBMEC cells, further optimization was carried out by varying coating material, coating procedure, cell seeding density, and growth media composition. Biochemical characterization of cell type-specific transmembrane adherens junction protein VE-cadherin and of TJ proteins ZO-1 and claudin-5 were carried out for each endothelial cell line. In addition, immunostaining for ZO-1 in hBMEC cell line was performed. Results The four cell lines all expressed the endothelial cell type-specific adherens junction protein VE-cadherin. The TJ protein ZO-1 was expressed in hCMEC/D3 and in hBMEC cells. ZO-1 expression could be confirmed in hBMEC cells by immunocytochemical staining. Claudin-5 expression was detected in hCMEC/D3, TY10, and at a very low level in hBMEC cells. Highest TEER values and lowest paracellular permeability for Na-F and LY were obtained with mono-cultures of hBMEC cell line when cultivated on 24-well tissue culture inserts from Greiner Bio-one® (transparent PET membrane, 3.0 μm pore size). In co-culture models with SVG-A and HBPCT cells, no increase of TEER could be observed, suggesting that none of the investigated endothelial cell lines responded positively to stimuli from immortalized astrocytic or pericytic cells. Conclusions Under the conditions examined in our experiments, hBMEC proved to be the most suitable human cell line for an in vitro BBB model concerning barrier tightness in a 24-well mono-culture system intended for higher throughput. This BBB model is being validated with several compounds (known to cross or not to cross the BBB), and will potentially be selected for the assessment of BBB permeation of bioactive natural products. PMID:24262108

Comparative study of four immortalized human brain capillary endothelial cell lines, hCMEC/D3, hBMEC, TY10, and BB19, and optimization of culture conditions, for an in vitro blood-brain barrier model for drug permeability studies.

PubMed

Eigenmann, Daniela E; Xue, Gongda; Kim, Kwang S; Moses, Ashlee V; Hamburger, Matthias; Oufir, Mouhssin

2013-11-22

Reliable human in vitro blood-brain barrier (BBB) models suitable for high-throughput screening are urgently needed in early drug discovery and development for assessing the ability of promising bioactive compounds to overcome the BBB. To establish an improved human in vitro BBB model, we compared four currently available and well characterized immortalized human brain capillary endothelial cell lines, hCMEC/D3, hBMEC, TY10, and BB19, with respect to barrier tightness and paracellular permeability. Co-culture systems using immortalized human astrocytes (SVG-A cell line) and immortalized human pericytes (HBPCT cell line) were designed with the aim of positively influencing barrier tightness. Tight junction (TJ) formation was assessed by transendothelial electrical resistance (TEER) measurements using a conventional epithelial voltohmmeter (EVOM) and an automated CellZscope system which records TEER and cell layer capacitance (CCL) in real-time.Paracellular permeability was assessed using two fluorescent marker compounds with low BBB penetration (sodium fluorescein (Na-F) and lucifer yellow (LY)). Conditions were optimized for each endothelial cell line by screening a series of 24-well tissue culture inserts from different providers. For hBMEC cells, further optimization was carried out by varying coating material, coating procedure, cell seeding density, and growth media composition. Biochemical characterization of cell type-specific transmembrane adherens junction protein VE-cadherin and of TJ proteins ZO-1 and claudin-5 were carried out for each endothelial cell line. In addition, immunostaining for ZO-1 in hBMEC cell line was performed. The four cell lines all expressed the endothelial cell type-specific adherens junction protein VE-cadherin. The TJ protein ZO-1 was expressed in hCMEC/D3 and in hBMEC cells. ZO-1 expression could be confirmed in hBMEC cells by immunocytochemical staining. Claudin-5 expression was detected in hCMEC/D3, TY10, and at a very low level in hBMEC cells. Highest TEER values and lowest paracellular permeability for Na-F and LY were obtained with mono-cultures of hBMEC cell line when cultivated on 24-well tissue culture inserts from Greiner Bio-one® (transparent PET membrane, 3.0 μm pore size). In co-culture models with SVG-A and HBPCT cells, no increase of TEER could be observed, suggesting that none of the investigated endothelial cell lines responded positively to stimuli from immortalized astrocytic or pericytic cells. Under the conditions examined in our experiments, hBMEC proved to be the most suitable human cell line for an in vitro BBB model concerning barrier tightness in a 24-well mono-culture system intended for higher throughput. This BBB model is being validated with several compounds (known to cross or not to cross the BBB), and will potentially be selected for the assessment of BBB permeation of bioactive natural products.

Model-based strategy for cell culture seed train layout verified at lab scale.

PubMed

Kern, Simon; Platas-Barradas, Oscar; Pörtner, Ralf; Frahm, Björn

2016-08-01

Cell culture seed trains-the generation of a sufficient viable cell number for the inoculation of the production scale bioreactor, starting from incubator scale-are time- and cost-intensive. Accordingly, a seed train offers potential for optimization regarding its layout and the corresponding proceedings. A tool has been developed to determine the optimal points in time for cell passaging from one scale into the next and it has been applied to two different cell lines at lab scale, AGE1.HN AAT and CHO-K1. For evaluation, experimental seed train realization has been evaluated in comparison to its layout. In case of the AGE1.HN AAT cell line, the results have also been compared to the formerly manually designed seed train. The tool provides the same seed train layout based on the data of only two batches.

Cellular recovery from exposure to sub-optimal concentrations of AB toxins that inhibit protein synthesis.

PubMed

Cherubin, Patrick; Quiñones, Beatriz; Teter, Ken

2018-02-06

Ricin, Shiga toxin, exotoxin A, and diphtheria toxin are AB-type protein toxins that act within the host cytosol and kill the host cell through pathways involving the inhibition of protein synthesis. It is thought that a single molecule of cytosolic toxin is sufficient to kill the host cell. Intoxication is therefore viewed as an irreversible process. Using flow cytometry and a fluorescent reporter system to monitor protein synthesis, we show a single molecule of cytosolic toxin is not sufficient for complete inhibition of protein synthesis or cell death. Furthermore, cells can recover from intoxication: cells with a partial loss of protein synthesis will, upon removal of the toxin, increase the level of protein production and survive the toxin challenge. Thus, in contrast to the prevailing model, ongoing toxin delivery to the cytosol appears to be required for the death of cells exposed to sub-optimal toxin concentrations.

Second generation codon optimized minicircle (CoMiC) for nonviral reprogramming of human adult fibroblasts.

PubMed

Diecke, Sebastian; Lisowski, Leszek; Kooreman, Nigel G; Wu, Joseph C

2014-01-01

The ability to induce pluripotency in somatic cells is one of the most important scientific achievements in the fields of stem cell research and regenerative medicine. This technique allows researchers to obtain pluripotent stem cells without the controversial use of embryos, providing a novel and powerful tool for disease modeling and drug screening approaches. However, using viruses for the delivery of reprogramming genes and transcription factors may result in integration into the host genome and cause random mutations within the target cell, thus limiting the use of these cells for downstream applications. To overcome this limitation, various non-integrating techniques, including Sendai virus, mRNA, minicircle, and plasmid-based methods, have recently been developed. Utilizing a newly developed codon optimized 4-in-1 minicircle (CoMiC), we were able to reprogram human adult fibroblasts using chemically defined media and without the need for feeder cells.

Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production.

PubMed

Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens

2009-11-01

In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.

Optimal policies of non-cross-resistant chemotherapy on Goldie and Coldman's cancer model.

PubMed

Chen, Jeng-Huei; Kuo, Ya-Hui; Luh, Hsing Paul

2013-10-01

Mathematical models can be used to study the chemotherapy on tumor cells. Especially, in 1979, Goldie and Coldman proposed the first mathematical model to relate the drug sensitivity of tumors to their mutation rates. Many scientists have since referred to this pioneering work because of its simplicity and elegance. Its original idea has also been extended and further investigated in massive follow-up studies of cancer modeling and optimal treatment. Goldie and Coldman, together with Guaduskas, later used their model to explain why an alternating non-cross-resistant chemotherapy is optimal with a simulation approach. Subsequently in 1983, Goldie and Coldman proposed an extended stochastic based model and provided a rigorous mathematical proof to their earlier simulation work when the extended model is approximated by its quasi-approximation. However, Goldie and Coldman's analytic study of optimal treatments majorly focused on a process with symmetrical parameter settings, and presented few theoretical results for asymmetrical settings. In this paper, we recast and restate Goldie, Coldman, and Guaduskas' model as a multi-stage optimization problem. Under an asymmetrical assumption, the conditions under which a treatment policy can be optimal are derived. The proposed framework enables us to consider some optimal policies on the model analytically. In addition, Goldie, Coldman and Guaduskas' work with symmetrical settings can be treated as a special case of our framework. Based on the derived conditions, this study provides an alternative proof to Goldie and Coldman's work. In addition to the theoretical derivation, numerical results are included to justify the correctness of our work. Copyright © 2013 Elsevier Inc. All rights reserved.

Modeling of a VMJ PV array under Gaussian high intensity laser power beam condition

NASA Astrophysics Data System (ADS)

Eom, Jeongsook; Kim, Gunzung; Park, Yongwan

2018-02-01

The high intensity laser power beaming (HILPB) system is one of the most promising systems in the long-rang wireless power transfer field. The vertical multi-junction photovoltaic (VMJ PV) array converts the HILPB into electricity to power the load or charges a battery. The output power of a VMJ PV array depends mainly on irradiance values of each VMJ PV cells. For simulating an entire VMJ PV array, the irradiance profile of the Gaussian HILPB and the irradiance level of the VMJ PV cell are mathematically modeled first. The VMJ PV array is modeled as a network with dimension m*n, where m represents the number of VMJ PV cells in a column, and n represents the number of VMJ PV cells in a row. In order to validate the results obtained in modeling and simulation, a laboratory setup was developed using 55 VMJ PV array. By using the output power model of VMJ PV array, we can establish an optimal power transmission path by the receiver based on the received signal strength. When the laser beam from multiple transmitters aimed at a VMJ PV array at the same time, the received power is the sum of all energy at a VMJ PV array. The transmitter sends its power characteristics as optically coded laser pulses and powers as HILPB. Using the attenuated power model and output power model of VMJ PV array, the receiver can estimate the maximum receivable powers from the transmitters and select optimal transmitters.

Multiscale modelling of Flow-Induced Blood Cell Damage

NASA Astrophysics Data System (ADS)

Liu, Yaling; Sohrabi, Salman

2017-11-01

We study red blood cell (RBC) damage and hemolysis at cellular level. Under high shear rates, pores form on RBC membranes through which hemoglobin (Hb) leaks out and increases free Hb content of plasma leading to hemolysis. By coupling lattice Boltzmann and spring connected network models through immersed boundary method, we estimate hemolysis of a single RBC under various shear rates. The developed cellular damage model can be used as a predictive tool for hydrodynamic and hematologic design optimization of blood-wetting medical devices.

Trophic Strategies of Unicellular Plankton.

PubMed

Chakraborty, Subhendu; Nielsen, Lasse Tor; Andersen, Ken H

2017-04-01

Unicellular plankton employ trophic strategies ranging from pure photoautotrophs over mixotrophy to obligate heterotrophs (phagotrophs), with cell sizes from 10 -8 to 1 μg C. A full understanding of how trophic strategy and cell size depend on resource environment and predation is lacking. To this end, we develop and calibrate a trait-based model for unicellular planktonic organisms characterized by four traits: cell size and investments in phototrophy, nutrient uptake, and phagotrophy. We use the model to predict how optimal trophic strategies depend on cell size under various environmental conditions, including seasonal succession. We identify two mixotrophic strategies: generalist mixotrophs investing in all three investment traits and obligate mixotrophs investing only in phototrophy and phagotrophy. We formulate two conjectures: (1) most cells are limited by organic carbon; however, small unicellulars are colimited by organic carbon and nutrients, and only large photoautotrophs and smaller mixotrophs are nutrient limited; (2) trophic strategy is bottom-up selected by the environment, while optimal size is top-down selected by predation. The focus on cell size and trophic strategies facilitates general insights into the strategies of a broad class of organisms in the size range from micrometers to millimeters that dominate the primary and secondary production of the world's oceans.

Mathematical modeling of cell adhesion in shear flow: application to targeted drug delivery in inflammation and cancer metastasis.

PubMed

Jadhav, Sameer; Eggleton, Charles D; Konstantopoulos, Konstantinos

2007-01-01

Cell adhesion plays a pivotal role in diverse biological processes that occur in the dynamic setting of the vasculature, including inflammation and cancer metastasis. Although complex, the naturally occurring processes that have evolved to allow for cell adhesion in the vasculature can be exploited to direct drug carriers to targeted cells and tissues. Fluid (blood) flow influences cell adhesion at the mesoscale by affecting the mechanical response of cell membrane, the intercellular contact area and collisional frequency, and at the nanoscale level by modulating the kinetics and mechanics of receptor-ligand interactions. Consequently, elucidating the molecular and biophysical nature of cell adhesion requires a multidisciplinary approach involving the synthesis of fundamentals from hydrodynamic flow, molecular kinetics and cell mechanics with biochemistry/molecular cell biology. To date, significant advances have been made in the identification and characterization of the critical cell adhesion molecules involved in inflammatory disorders, and, to a lesser degree, in cancer metastasis. Experimental work at the nanoscale level to determine the lifetime, interaction distance and strain responses of adhesion receptor-ligand bonds has been spurred by the advent of atomic force microscopy and biomolecular force probes, although our current knowledge in this area is far from complete. Micropipette aspiration assays along with theoretical frameworks have provided vital information on cell mechanics. Progress in each of the aforementioned research areas is key to the development of mathematical models of cell adhesion that incorporate the appropriate biological, kinetic and mechanical parameters that would lead to reliable qualitative and quantitative predictions. These multiscale mathematical models can be employed to predict optimal drug carrier-cell binding through isolated parameter studies and engineering optimization schemes, which will be essential for developing effective drug carriers for delivery of therapeutic agents to afflicted sites of the host.

Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.

PubMed

Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted

2017-01-01

Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.

Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies

PubMed Central

Abel zur Wiesch, Pia; Cohen, Ted

2017-01-01

Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood. PMID:28060813

Hybrid optimal scheduling for intermittent androgen suppression of prostate cancer

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; di Bernardo, Mario; Bruchovsky, Nicholas; Aihara, Kazuyuki

2010-12-01

We propose a method for achieving an optimal protocol of intermittent androgen suppression for the treatment of prostate cancer. Since the model that reproduces the dynamical behavior of the surrogate tumor marker, prostate specific antigen, is piecewise linear, we can obtain an analytical solution for the model. Based on this, we derive conditions for either stopping or delaying recurrent disease. The solution also provides a design principle for the most favorable schedule of treatment that minimizes the rate of expansion of the malignant cell population.

Modeling to Optimize Terminal Stem Cell Differentiation

PubMed Central

Gallicano, G. Ian

2013-01-01

Embryonic stem cell (ESC), iPCs, and adult stem cells (ASCs) all are among the most promising potential treatments for heart failure, spinal cord injury, neurodegenerative diseases, and diabetes. However, considerable uncertainty in the production of ESC-derived terminally differentiated cell types has limited the efficiency of their development. To address this uncertainty, we and other investigators have begun to employ a comprehensive statistical model of ESC differentiation for determining the role of intracellular pathways (e.g., STAT3) in ESC differentiation and determination of germ layer fate. The approach discussed here applies the Baysian statistical model to cell/developmental biology combining traditional flow cytometry methodology and specific morphological observations with advanced statistical and probabilistic modeling and experimental design. The final result of this study is a unique tool and model that enhances the understanding of how and when specific cell fates are determined during differentiation. This model provides a guideline for increasing the production efficiency of therapeutically viable ESCs/iPSCs/ASC derived neurons or any other cell type and will eventually lead to advances in stem cell therapy. PMID:24278782

Measuring optical properties of a blood vessel model using optical coherence tomography

NASA Astrophysics Data System (ADS)

Levitz, David; Hinds, Monica T.; Tran, Noi; Vartanian, Keri; Hanson, Stephen R.; Jacques, Steven L.

2006-02-01

In this paper we develop the concept of a tissue-engineered optical phantom that uses engineered tissue as a phantom for calibration and optimization of biomedical optics instrumentation. With this method, the effects of biological processes on measured signals can be studied in a well controlled manner. To demonstrate this concept, we attempted to investigate how the cellular remodeling of a collagen matrix affected the optical properties extracted from optical coherence tomography (OCT) images of the samples. Tissue-engineered optical phantoms of the vascular system were created by seeding smooth muscle cells in a collagen matrix. Four different optical properties were evaluated by fitting the OCT signal to 2 different models: the sample reflectivity ρ and attenuation parameter μ were extracted from the single scattering model, and the scattering coefficient μ s and root-mean-square scattering angle θ rms were extracted from the extended Huygens-Fresnel model. We found that while contraction of the smooth muscle cells was clearly evident macroscopically, on the microscopic scale very few cells were actually embedded in the collagen. Consequently, no significant difference between the cellular and acellular samples in either set of measured optical properties was observed. We believe that further optimization of our tissue-engineering methods is needed in order to make the histology and biochemistry of the cellular samples sufficiently different from the acellular samples on the microscopic level. Once these methods are optimized, we can better verify whether the optical properties of the cellular and acellular collagen samples differ.

The establishment of insulin resistance model in FL83B and L6 cell

NASA Astrophysics Data System (ADS)

Liu, Lanlan; Han, Jizhong; Li, Haoran; Liu, Mengmeng; Zeng, Bin

2017-10-01

The insulin resistance models of mouse liver epithelial and rat myoblasts cells were induced by three kinds of inducers: dexamethasone, high insulin and high glucose. The purpose is to select the optimal insulin resistance model, to provide a simple and reliable TR cell model for the study of the pathogenesis of TR and the improvement of TR drugs and functional foods. The MTT method is used for toxicity screening of three compounds, selecting security and suitable concentration. We performed a Glucose oxidase peroxidase (GOD-POD) method involving FL83B and L6 cell with dexamethasone, high insulin and high glucose-induced insulin resistance. Results suggested that FL83B cells with dexamethasone-induced (0.25uM) were established insulin resistance and L6 cells with high-glucose (30mM) and dexamethasone-induced (0.25uM) were established insulin resistance.

Computer modeling of a two-junction, monolithic cascade solar cell

NASA Technical Reports Server (NTRS)

Lamorte, M. F.; Abbott, D.

1979-01-01

The theory and design criteria for monolithic, two-junction cascade solar cells are described. The departure from the conventional solar cell analytical method and the reasons for using the integral form of the continuity equations are briefly discussed. The results of design optimization are presented. The energy conversion efficiency that is predicted for the optimized structure is greater than 30% at 300 K, AMO and one sun. The analytical method predicts device performance characteristics as a function of temperature. The range is restricted to 300 to 600 K. While the analysis is capable of determining most of the physical processes occurring in each of the individual layers, only the more significant device performance characteristics are presented.

Initiation of primary cell culture from amphioxus Branchiostoma belcheri tsingtauense

NASA Astrophysics Data System (ADS)

Wang, Changliu; Zhang, Shicui; Su, Feng; Wang, Lei; Li, Hongyan

2009-02-01

Amphioxus, a cephalochordate, is an important model fish for studies in evolution and comparative biology. A successful cell culture from amphioxus tissues in vitro would help understanding some basic issues. To determine the optimal culture conditions for proliferation of amphioxus cells, primary cultures were initiated from buccal cirri, tail, gill, gut and metapleural fold of amphioxus Branchiostoma belcheri tsingtauense. The media tested were L-15, F-12, M 199, MEM, DMEM, PRMI 1640 and LDF, each was supplemented with 20% fetal bovine serum. The optimal conditions include tail tissue cultured in L-15 or F-12 with supplement of 20% FBS and 1.5% NaCl at about 25°C.

A modeling of the structure and favorable H-docking sites and defects for the high-pressure silica polymorph stishovite

NASA Astrophysics Data System (ADS)

Gibbs, G. V.; Cox, D. F.; Ross, N. L.

Employing first-principles methods, the docking sites for H were determined and H, Al, and vacancy defects were modeled with an infinite periodic array of super unit cells each consisting of 27 contiguous symmetry nonequivalent unit cells of the crystal structure of stishovite. A geometry optimization of the super-cell structure reproduces the observed bulk structure within the experimental error when P1 translational symmetry was assumed and an array of infinite extent was generated. A mapping of the valence electrons for the structure displays mushroom-shaped isosurfaces on the O atom, one on each side of the plane of the OSi3 triangle in the nonbonded region. An H atom, placed in a cell near the center of the super cell, was found to dock upon geometry optimization at a distance of 1.69 Å from the O atom with the OH vector oriented nearly perpendicular to the plane of the triangle such that the OH vector makes a angle of 91° with respect to [001]. However, an optimization of a super cell with an Al atom replacing Si and an H atom placed nearby in a centrally located cell resulted in an OH distance of 1.02 Å with the OH vector oriented perpendicular to [001] as observed in infrared studies. The geometry-optimized position of the H atom was found to be in close agreement with that (0.44, 0.12, 0.0) determined in an earlier study of the theoretical electron density distribution. The docking of the H atom at this site was found to be 330 kJ mol-1 more stable than a docking of the atom just off the shared OO edge of the octahedra as determined for rutile. A geometry optimization of a super cell with a missing Si generated a vacant octahedra that is 20% larger than that of the SiO6 octahedra. The valence electron density distribution displayed by the two-coordinate O atoms that coordinate the vacant octahedral site is very similar to those displayed by the bent SiOSi angles in coesite. The internal distortions induced by the defect were found to diminish rather rapidly with distance, with the structure annealing to that observed in the bulk crystal to within about three coordination spheres.

Basic features of boron isotope separation by SILARC method in the two-step iterative static model

NASA Astrophysics Data System (ADS)

Lyakhov, K. A.; Lee, H. J.

2013-05-01

In this paper we develop a new static model for boron isotope separation by the laser assisted retardation of condensation method (SILARC) on the basis of model proposed by Jeff Eerkens. Our model is thought to be adequate to so-called two-step iterative scheme for isotope separation. This rather simple model helps to understand combined action on boron separation by SILARC method of all important parameters and relations between them. These parameters include carrier gas, molar fraction of BCl3 molecules in carrier gas, laser pulse intensity, gas pulse duration, gas pressure and temperature in reservoir and irradiation cells, optimal irradiation cell and skimmer chamber volumes, and optimal nozzle throughput. A method for finding optimal values of these parameters based on some objective function global minimum search was suggested. It turns out that minimum of this objective function is directly related to the minimum of total energy consumed, and total setup volume. Relations between nozzle throat area, IC volume, laser intensity, number of nozzles, number of vacuum pumps, and required isotope production rate were derived. Two types of industrial scale irradiation cells are compared. The first one has one large throughput slit nozzle, while the second one has numerous small nozzles arranged in parallel arrays for better overlap with laser beam. It is shown that the last one outperforms the former one significantly. It is argued that NO2 is the best carrier gas for boron isotope separation from the point of view of energy efficiency and Ar from the point of view of setup compactness.

Maximizing neotissue growth kinetics in a perfusion bioreactor: An in silico strategy using model reduction and Bayesian optimization.

PubMed

Mehrian, Mohammad; Guyot, Yann; Papantoniou, Ioannis; Olofsson, Simon; Sonnaert, Maarten; Misener, Ruth; Geris, Liesbet

2018-03-01

In regenerative medicine, computer models describing bioreactor processes can assist in designing optimal process conditions leading to robust and economically viable products. In this study, we started from a (3D) mechanistic model describing the growth of neotissue, comprised of cells, and extracellular matrix, in a perfusion bioreactor set-up influenced by the scaffold geometry, flow-induced shear stress, and a number of metabolic factors. Subsequently, we applied model reduction by reformulating the problem from a set of partial differential equations into a set of ordinary differential equations. Comparing the reduced model results to the mechanistic model results and to dedicated experimental results assesses the reduction step quality. The obtained homogenized model is 10 5 fold faster than the 3D version, allowing the application of rigorous optimization techniques. Bayesian optimization was applied to find the medium refreshment regime in terms of frequency and percentage of medium replaced that would maximize neotissue growth kinetics during 21 days of culture. The simulation results indicated that maximum neotissue growth will occur for a high frequency and medium replacement percentage, a finding that is corroborated by reports in the literature. This study demonstrates an in silico strategy for bioprocess optimization paying particular attention to the reduction of the associated computational cost. © 2017 Wiley Periodicals, Inc.

Differentiation and Characterization of Dopaminergic Neurons From Baboon Induced Pluripotent Stem Cells.

PubMed

Grow, Douglas A; Simmons, DeNard V; Gomez, Jorge A; Wanat, Matthew J; McCarrey, John R; Paladini, Carlos A; Navara, Christopher S

2016-09-01

: The progressive death of dopamine producing neurons in the substantia nigra pars compacta is the principal cause of symptoms of Parkinson's disease (PD). Stem cells have potential therapeutic use in replacing these cells and restoring function. To facilitate development of this approach, we sought to establish a preclinical model based on a large nonhuman primate for testing the efficacy and safety of stem cell-based transplantation. To this end, we differentiated baboon fibroblast-derived induced pluripotent stem cells (biPSCs) into dopaminergic neurons with the application of specific morphogens and growth factors. We confirmed that biPSC-derived dopaminergic neurons resemble those found in the human midbrain based on cell type-specific expression of dopamine markers TH and GIRK2. Using the reverse transcriptase quantitative polymerase chain reaction, we also showed that biPSC-derived dopaminergic neurons express PAX6, FOXA2, LMX1A, NURR1, and TH genes characteristic of this cell type in vivo. We used perforated patch-clamp electrophysiology to demonstrate that biPSC-derived dopaminergic neurons fired spontaneous rhythmic action potentials and high-frequency action potentials with spike frequency adaption upon injection of depolarizing current. Finally, we showed that biPSC-derived neurons released catecholamines in response to electrical stimulation. These results demonstrate the utility of the baboon model for testing and optimizing the efficacy and safety of stem cell-based therapeutic approaches for the treatment of PD. Functional dopamine neurons were produced from baboon induced pluripotent stem cells, and their properties were compared to baboon midbrain cells in vivo. The baboon has advantages as a clinically relevant model in which to optimize the efficacy and safety of stem cell-based therapies for neurodegenerative diseases, such as Parkinson's disease. Baboons possess crucial neuroanatomical and immunological similarities to humans, and baboon pluripotent stem cells can be differentiated into functional neurons that mimic those in the human brain, thus laying the foundation for the utility of the baboon model for evaluating stem cell therapies. ©AlphaMed Press.

Energy-efficient growth of phage Q Beta in Escherichia coli.

PubMed

Kim, Hwijin; Yin, John

2004-10-20

The role of natural selection in the optimal design of organisms is controversial. Optimal forms, functions, or behaviors of organisms have long been claimed without knowledge of how genotype contributes to phenotype, delineation of design constraints, or reference to alternative designs. Moreover, arguments for optimal designs have been often based on models that were difficult, if not impossible, to test. Here, we begin to address these issues by developing and probing a kinetic model for the intracellular growth of bacteriophage Q beta in Escherichia coli. The model accounts for the energetic costs of all template-dependent polymerization reactions, in ATP equivalents, including RNA-dependent RNA elongation by the phage replicase and synthesis of all phage proteins by the translation machinery of the E. coli host cell. We found that translation dominated phage growth, requiring 85% of the total energy expenditure. Only 10% of the total energy was applied to activities other than the direct synthesis of progeny phage components, reflecting primarily the cost of making the negative-strand RNA template that is needed for replication of phage genomic RNA. Further, we defined an energy efficiency of phage growth and showed its direct relationship to the yield of phage progeny. Finally, we performed a sensitivity analysis and found that the growth of wild-type phage was optimized for progeny yield or energy efficiency, suggesting that phage Q beta has evolved to optimally utilize the finite resources of its host cells.

Highly Adaptable Triple-Negative Breast Cancer Cells as a Functional Model for Testing Anticancer Agents

PubMed Central

Singh, Balraj; Shamsnia, Anna; Raythatha, Milan R.; Milligan, Ryan D.; Cady, Amanda M.; Madan, Simran; Lucci, Anthony

2014-01-01

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance. PMID:25279830

Highly adaptable triple-negative breast cancer cells as a functional model for testing anticancer agents.

PubMed

Singh, Balraj; Shamsnia, Anna; Raythatha, Milan R; Milligan, Ryan D; Cady, Amanda M; Madan, Simran; Lucci, Anthony

2014-01-01

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance.

Numerical modelling of high efficiency InAs/GaAs intermediate band solar cell

NASA Astrophysics Data System (ADS)

Imran, Ali; Jiang, Jianliang; Eric, Debora; Yousaf, Muhammad

2018-01-01

Quantum Dots (QDs) intermediate band solar cells (IBSC) are the most attractive candidates for the next generation of photovoltaic applications. In this paper, theoretical model of InAs/GaAs device has been proposed, where we have calculated the effect of variation in the thickness of intrinsic and IB layer on the efficiency of the solar cell using detailed balance theory. IB energies has been optimized for different IB layers thickness. Maximum efficiency 46.6% is calculated for IB material under maximum optical concentration.

Development and design of experiments optimization of a high temperature proton exchange membrane fuel cell auxiliary power unit with onboard fuel processor

NASA Astrophysics Data System (ADS)

Karstedt, Jörg; Ogrzewalla, Jürgen; Severin, Christopher; Pischinger, Stefan

In this work, the concept development, system layout, component simulation and the overall DOE system optimization of a HT-PEM fuel cell APU with a net electric power output of 4.5 kW and an onboard methane fuel processor are presented. A highly integrated system layout has been developed that enables fast startup within 7.5 min, a closed system water balance and high fuel processor efficiencies of up to 85% due to the recuperation of the anode offgas burner heat. The integration of the system battery into the load management enhances the transient electric performance and the maximum electric power output of the APU system. Simulation models of the carbon monoxide influence on HT-PEM cell voltage, the concentration and temperature profiles within the autothermal reformer (ATR) and the CO conversion rates within the watergas shift stages (WGSs) have been developed. They enable the optimization of the CO concentration in the anode gas of the fuel cell in order to achieve maximum system efficiencies and an optimized dimensioning of the ATR and WGS reactors. Furthermore a DOE optimization of the global system parameters cathode stoichiometry, anode stoichiometry, air/fuel ratio and steam/carbon ratio of the fuel processing system has been performed in order to achieve maximum system efficiencies for all system operating points under given boundary conditions.

Experimental characterization of recurrent ovarian immature teratoma cells after optimal surgery.

PubMed

Tanaka, Tetsuji; Toujima, Saori; Utsunomiya, Tomoko; Yukawa, Kazunori; Umesaki, Naohiko

2008-07-01

Minimal optimal surgery without chemotherapy is often performed for patients with ovarian immature teratoma, which frequently occurs in young women who hope for future pregnancies. If tumors recur after the operation, anticancer drug chemotherapy is often administered, although few studies have highlighted differences between the recurrent and the primary tumor cells. Therefore, we have established experimental animal models of recurrent ovarian immature teratoma cells after optimal surgery and characterized the anticancer drug sensitivity and antigenicity of the recurrent tumors. Surgically-excised tumor cells of a grade II ovarian immature teratoma were cultured in vitro and transplanted into nude mice to establish stable cell lines. Differential drug sensitivity and antigenicity of the tumor cells were compared between the primary and the nude mouse tumors. Nude mouse tumor cells showed a normal 46XX karyotype. Cultured primary cells showed a remarkably high sensitivity to paclitaxel, docetaxel, adriamycin and pirarubicin, compared to peritoneal cancer cells obtained from a patient with ovarian adenocarcinomatous peritonitis. The drug sensitivity of teratoma cells to 5-fluorouracil, bleomycin or peplomycin was also significantly higher. However, there was no significant difference in sensitivity to platinum drugs between the primary teratoma and the peritoneal adenocarcinoma cells. As for nude mouse tumor cells, sensitivity to 12 anticancer drugs was significantly lower than that of the primary tumor cells, while there was little difference in sensitivity to carboplatin or peplomycin between the primary and nude mouse tumor cells. Flow cytometry showed that the expression of smooth muscle actin (SMA) significantly decreased in nude mouse tumor cells when compared to cultured primary cells. In conclusion, ovarian immature teratomas with normal karyotypes have a malignant potential to recur after minimal surgery. During nude mouse transplantation, SMA-overexpressing cells appeared to be selectively excluded and nude mouse tumor cells were less sensitive to the majority of anticancer drugs than the primary tumor cells. These results indicate that after optimal surgery for ovarian immature teratoma, recurrent cells can be more resistant to anticancer drugs than the primary tumors. Therefore, it is likely that adjuvant chemotherapy lowers the risk of ovarian immature teratomas recurring after optimal surgery. BEP and PBV regimens are frequently given to teratoma patients. However, paclitaxel/carboplatin or docetaxel/carboplatin, which are the most effective chemotherapy treatments for epithelial ovarian cancer patients, are considered to be an alternative regimen, especially in the prevention of reproductive toxicity.

Effect of Transplanting Various Concentrations of a Composite of Human Umbilical Cord Blood-Derived Mesenchymal Stem Cells and Hyaluronic Acid Hydrogel on Articular Cartilage Repair in a Rabbit Model

PubMed Central

Ha, Chul-Won; Kim, Jin-A; Rhim, Ji-Heon; Park, Yong-Geun; Chung, Jun Young; Lee, Han-Jun

2016-01-01

Background Mesenchymal stem cells (MSCs) are known to have therapeutic potential for cartilage repair. However, the optimal concentration of MSCs for cartilage repair remains unclear. Therefore, we aimed to explore the feasibility of cartilage repair by human umbilical cord blood-derived MSCs (hUCB-MSCs) and to determine the optimal concentrations of the MSCs in a rabbit model. Methods Osteochondral defects were created in the trochlear groove of femur in 55 rabbits. Four experimental groups (11 rabbits/group) were treated by transplanting the composite of hUCB-MSCs and HA with various MSCs concentrations (0.1, 0.5, 1.0, and 1.5 x 107 cells/ml). One control group was left untreated. At 4, 8, and 16 weeks post-transplantation, the degree of cartilage repair was evaluated grossly and histologically. Findings Overall, transplanting hUCB-MSCs and HA hydrogel resulted in cartilage repair tissue with better quality than the control without transplantation (P = 0.015 in 0.1, P = 0.004 in 0.5, P = 0.004 in 1.0, P = 0.132 in 1.5 x 107 cells/ml). Interestingly, high cell concentration of hUCB-MSCs (1.5×107 cells/ml) was inferior to low cell concentrations (0.1, 0.5, and 1.0 x 107 cells/ml) in cartilage repair (P = 0.394,P = 0.041, P = 0.699, respectively). The 0.5 x 107 cells/ml group showed the highest cartilage repair score at 4, 8 and 16 weeks post transplantation, and followed by 0.1x107 cells/ml group or 1.0 x 107 cell/ml group. Conclusions The results of this study suggest that transplantation of the composite of hUCB-MSCs and HA is beneficial for cartilage repair. In addition, this study shows that optimal MSC concentration needs to be determined for better cartilage repair. PMID:27824874

Effect of Transplanting Various Concentrations of a Composite of Human Umbilical Cord Blood-Derived Mesenchymal Stem Cells and Hyaluronic Acid Hydrogel on Articular Cartilage Repair in a Rabbit Model.

PubMed

Park, Yong-Beom; Ha, Chul-Won; Kim, Jin-A; Rhim, Ji-Heon; Park, Yong-Geun; Chung, Jun Young; Lee, Han-Jun

2016-01-01

Mesenchymal stem cells (MSCs) are known to have therapeutic potential for cartilage repair. However, the optimal concentration of MSCs for cartilage repair remains unclear. Therefore, we aimed to explore the feasibility of cartilage repair by human umbilical cord blood-derived MSCs (hUCB-MSCs) and to determine the optimal concentrations of the MSCs in a rabbit model. Osteochondral defects were created in the trochlear groove of femur in 55 rabbits. Four experimental groups (11 rabbits/group) were treated by transplanting the composite of hUCB-MSCs and HA with various MSCs concentrations (0.1, 0.5, 1.0, and 1.5 x 107 cells/ml). One control group was left untreated. At 4, 8, and 16 weeks post-transplantation, the degree of cartilage repair was evaluated grossly and histologically. Overall, transplanting hUCB-MSCs and HA hydrogel resulted in cartilage repair tissue with better quality than the control without transplantation (P = 0.015 in 0.1, P = 0.004 in 0.5, P = 0.004 in 1.0, P = 0.132 in 1.5 x 107 cells/ml). Interestingly, high cell concentration of hUCB-MSCs (1.5×107 cells/ml) was inferior to low cell concentrations (0.1, 0.5, and 1.0 x 107 cells/ml) in cartilage repair (P = 0.394,P = 0.041, P = 0.699, respectively). The 0.5 x 107 cells/ml group showed the highest cartilage repair score at 4, 8 and 16 weeks post transplantation, and followed by 0.1x107 cells/ml group or 1.0 x 107 cell/ml group. The results of this study suggest that transplantation of the composite of hUCB-MSCs and HA is beneficial for cartilage repair. In addition, this study shows that optimal MSC concentration needs to be determined for better cartilage repair.

Generation of functional cardiomyocytes from rat embryonic and induced pluripotent stem cells using feeder-free expansion and differentiation in suspension culture.

PubMed

Dahlmann, Julia; Awad, George; Dolny, Carsten; Weinert, Sönke; Richter, Karin; Fischer, Klaus-Dieter; Munsch, Thomas; Leßmann, Volkmar; Volleth, Marianne; Zenker, Martin; Chen, Yaoyao; Merkl, Claudia; Schnieke, Angelika; Baraki, Hassina; Kutschka, Ingo; Kensah, George

2018-01-01

The possibility to generate cardiomyocytes from pluripotent stem cells in vitro has enormous significance for basic research, disease modeling, drug development and heart repair. The concept of heart muscle reconstruction has been studied and optimized in the rat model using rat primary cardiovascular cells or xenogeneic pluripotent stem cell derived-cardiomyocytes for years. However, the lack of rat pluripotent stem cells (rPSCs) and their cardiovascular derivatives prevented the establishment of an authentic clinically relevant syngeneic or allogeneic rat heart regeneration model. In this study, we comparatively explored the potential of recently available rat embryonic stem cells (rESCs) and induced pluripotent stem cells (riPSCs) as a source for cardiomyocytes (CMs). We developed feeder cell-free culture conditions facilitating the expansion of undifferentiated rPSCs and initiated cardiac differentiation by embryoid body (EB)-formation in agarose microwell arrays, which substituted the robust but labor-intensive hanging drop (HD) method. Ascorbic acid was identified as an efficient enhancer of cardiac differentiation in both rPSC types by significantly increasing the number of beating EBs (3.6 ± 1.6-fold for rESCs and 17.6 ± 3.2-fold for riPSCs). These optimizations resulted in a differentiation efficiency of up to 20% cTnTpos rPSC-derived CMs. CMs showed spontaneous contractions, expressed cardiac markers and had typical morphological features. Electrophysiology of riPSC-CMs revealed different cardiac subtypes and physiological responses to cardio-active drugs. In conclusion, we describe rPSCs as a robust source of CMs, which is a prerequisite for detailed preclinical studies of myocardial reconstruction in a physiologically and immunologically relevant small animal model.

Exciton delocalization incorporated drift-diffusion model for bulk-heterojunction organic solar cells

NASA Astrophysics Data System (ADS)

Wang, Zi Shuai; Sha, Wei E. I.; Choy, Wallace C. H.

2016-12-01

Modeling the charge-generation process is highly important to understand device physics and optimize power conversion efficiency of bulk-heterojunction organic solar cells (OSCs). Free carriers are generated by both ultrafast exciton delocalization and slow exciton diffusion and dissociation at the heterojunction interface. In this work, we developed a systematic numerical simulation to describe the charge-generation process by a modified drift-diffusion model. The transport, recombination, and collection of free carriers are incorporated to fully capture the device response. The theoretical results match well with the state-of-the-art high-performance organic solar cells. It is demonstrated that the increase of exciton delocalization ratio reduces the energy loss in the exciton diffusion-dissociation process, and thus, significantly improves the device efficiency, especially for the short-circuit current. By changing the exciton delocalization ratio, OSC performances are comprehensively investigated under the conditions of short-circuit and open-circuit. Particularly, bulk recombination dependent fill factor saturation is unveiled and understood. As a fundamental electrical analysis of the delocalization mechanism, our work is important to understand and optimize the high-performance OSCs.

Numerical Simulation and Performance Optimization of a Magnetophoretic Bio-separation chip

NASA Astrophysics Data System (ADS)

Golozar, Matin; Darabi, Jeff; Molki, Majid

Separation of micro/nanoparticles is important in biomedicine and biotechnology. This research presents the modeling and optimization of a magnetophoretic bio-separation chip for the isolation of biomaterials, such as circulating tumor cells (CTCs) from the peripheral blood. The chip consists of a continuous flow through microfluidic channels that contains locally engineered magnetic field gradients. The high gradient magnetic field produced by the magnets is spatially non-uniform and gives rise to an attractive force on magnetic particles that move through the flow channel. The computational model takes into account the magnetic and fluidic forces as well as the effect of the volume fraction of particles on the continuous phase. The model is used to investigate the effect of two-way particle-fluid coupling on both the capture efficiency and the flow pattern in the separation chip. The results show that the microfluidic device has the capability of separating CTCs from their native environment. Additionally, a parametric study is performed to investigate the effects of the channel height, substrate thickness, magnetic bead size, bioparticle size, and the number of beads per cell on the cell separation performance.

Dynamic cellular manufacturing system considering machine failure and workload balance

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Labeling of stem cells with monocrystalline iron oxide for tracking and localization by magnetic resonance imaging

PubMed Central

Calzi, Sergio Li; Kent, David L.; Chang, Kyung-Hee; Padgett, Kyle R.; Afzal, Aqeela; Chandra, Saurav B.; Caballero, Sergio; English, Denis; Garlington, Wendy; Hiscott, Paul S.; Sheridan, Carl M.; Grant, Maria B.; Forder, John R.

2013-01-01

Precise localization of exogenously delivered stem cells is critical to our understanding of their reparative response. Our current inability to determine the exact location of small numbers of cells may hinder optimal development of these cells for clinical use. We describe a method using magnetic resonance imaging to track and localize small numbers of stem cells following transplantation. Endothelial progenitor cells (EPC) were labeled with monocrystalline iron oxide nanoparticles (MIONs) which neither adversely altered their viability nor their ability to migrate in vitro and allowed successful detection of limited numbers of these cells in muscle. MION-labeled stem cells were also injected into the vitreous cavity of mice undergoing the model of choroidal neovascularization, laser rupture of Bruch’s membrane. Migration of the MION-labeled cells from the injection site towards the laser burns was visualized by MRI. In conclusion, MION labeling of EPC provides a non-invasive means to define the location of small numbers of these cells. Localization of these cells following injection is critical to their optimization for therapy. PMID:19345699

Dynamics of Receptor-Mediated Nanoparticle Internalization into Endothelial Cells

PubMed Central

Gonzalez-Rodriguez, David; Barakat, Abdul I.

2015-01-01

Nanoparticles offer a promising medical tool for targeted drug delivery, for example to treat inflamed endothelial cells during the development of atherosclerosis. To inform the design of such therapeutic strategies, we develop a computational model of nanoparticle internalization into endothelial cells, where internalization is driven by receptor-ligand binding and limited by the deformation of the cell membrane and cytoplasm. We specifically consider the case of nanoparticles targeted against ICAM-1 receptors, of relevance for treating atherosclerosis. The model computes the kinetics of the internalization process, the dynamics of binding, and the distribution of stresses exerted between the nanoparticle and the cell membrane. The model predicts the existence of an optimal nanoparticle size for fastest internalization, consistent with experimental observations, as well as the role of bond characteristics, local cell mechanical properties, and external forces in the nanoparticle internalization process. PMID:25901833

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espinoza, I; Peschke, P; Karger, C

Purpose: In radiotherapy, it is important to predict the response of tumour to irradiation prior to the treatment. Mathematical modelling of tumour control probability (TCP) based on the dose distribution, medical imaging and other biological information may help to improve this prediction and to optimize the treatment plan. The aim of this work is to develop an image based 3D multiscale radiobiological model, which describes the growth and the response to radiotherapy of hypoxic tumors. Methods: The computer model is based on voxels, containing tumour, normal (including capillary) and dead cells. Killing of tumour cells due to irradiation is calculatedmore » by the Linear Quadratic Model (extended for hypoxia), and the proliferation and resorption of cells are modelled by exponential laws. The initial shape of the tumours is taken from CT images and the initial vascular and cell density information from PET and/or MR images. Including the fractionation regime and the physical dose distribution of the radiation treatment, the model simulates the spatial-temporal evolution of the tumor. Additionally, the dose distribution may be biologically optimized. Results: The model describes the appearance of hypoxia during tumour growth and the reoxygenation processes during radiotherapy. Among other parameters, the TCP is calculated for different dose distributions. The results are in accordance with published results. Conclusion: The simulation model may contribute to the understanding of the influence of biological parameters on tumor response during treatment, and specifically on TCP. It may be used to implement dose-painting approaches. Experimental and clinical validation is needed. This study is supported by a grant from the Ministry of Education of Chile, Programa Mece Educacion Superior (2)« less

Optimizing homeostatic cell renewal in hierarchical tissues

PubMed Central

Fider, Nicole A.

2018-01-01

In order to maintain homeostasis, mature cells removed from the top compartment of hierarchical tissues have to be replenished by means of differentiation and self-renewal events happening in the more primitive compartments. As each cell division is associated with a risk of mutation, cell division patterns have to be optimized, in order to minimize or delay the risk of malignancy generation. Here we study this optimization problem, focusing on the role of division tree length, that is, the number of layers of cells activated in response to the loss of terminally differentiated cells, which is related to the balance between differentiation and self-renewal events in the compartments. Using both analytical methods and stochastic simulations in a metapopulation-style model, we find that shorter division trees are advantageous if the objective is to minimize the total number of one-hit mutants in the cell population. Longer division trees on the other hand minimize the accumulation of two-hit mutants, which is a more likely evolutionary goal given the key role played by tumor suppressor genes in cancer initiation. While division tree length is the most important property determining mutant accumulation, we also find that increasing the size of primitive compartments helps to delay two-hit mutant generation. PMID:29447149

Light transfer in agar immobilized microalgae cell cultures

NASA Astrophysics Data System (ADS)

Kandilian, Razmig; Jesus, Bruno; Legrand, Jack; Pilon, Laurent; Pruvost, Jérémy

2017-09-01

This paper experimentally and theoretically investigates light transfer in agar-immobilized cell cultures. Certain biotechnological applications such as production of metabolites secreted by photosynthetic microorganisms require cells to be immobilized in biopolymers to minimize contamination and to facilitate metabolite recovery. In such applications, light absorption by cells is one of the most important parameters affecting cell growth or metabolite productivity. Modeling light transfer therein can aid design and optimize immobilized-cell reactors. In this study, Parachlorella kessleri cells with areal biomass concentrations ranging from 0.36 to 16.9 g/m2 were immobilized in 2.6 mm thick agar gels. The average absorption and scattering cross-sections as well as the scattering phase function of P. kessleri cells were measured. Then, the absorption and transport scattering coefficients of the agar gel were determined using an inverse method based on the modified two-flux approximation. The forward model was used to predict the normal-hemispherical transmittance and reflectance of the immobilized-cell films accounting for absorption and scattering by both microalgae and the agar gel. Good agreement was found between the measured and predicted normal-hemispherical transmittance and reflectance provided absorption and scattering by agar were taken into account. Moreover, good agreement was found between experimentally measured and predicted mean rate of photon absorption. Finally, optimal areal biomass concentration was determined to achieve complete absorption of the incident radiation.

A toxicity cost function approach to optimal CPA equilibration in tissues.

PubMed

Benson, James D; Higgins, Adam Z; Desai, Kunjan; Eroglu, Ali

2018-02-01

There is growing need for cryopreserved tissue samples that can be used in transplantation and regenerative medicine. While a number of specific tissue types have been successfully cryopreserved, this success is not general, and there is not a uniform approach to cryopreservation of arbitrary tissues. Additionally, while there are a number of long-established approaches towards optimizing cryoprotocols in single cell suspensions, and even plated cell monolayers, computational approaches in tissue cryopreservation have classically been limited to explanatory models. Here we develop a numerical approach to adapt cell-based CPA equilibration damage models for use in a classical tissue mass transport model. To implement this with real-world parameters, we measured CPA diffusivity in three human-sourced tissue types, skin, fibroid and myometrium, yielding propylene glycol diffusivities of 0.6 × 10 -6  cm 2 /s, 1.2 × 10 -6  cm 2 /s and 1.3 × 10 -6  cm 2 /s, respectively. Based on these results, we numerically predict and compare optimal multistep equilibration protocols that minimize the cell-based cumulative toxicity cost function and the damage due to excessive osmotic gradients at the tissue boundary. Our numerical results show that there are fundamental differences between protocols designed to minimize total CPA exposure time in tissues and protocols designed to minimize accumulated CPA toxicity, and that "one size fits all" stepwise approaches are predicted to be more toxic and take considerably longer than needed. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal integration strategies for a syngas fuelled SOFC and gas turbine hybrid

NASA Astrophysics Data System (ADS)

Zhao, Yingru; Sadhukhan, Jhuma; Lanzini, Andrea; Brandon, Nigel; Shah, Nilay

This article aims to develop a thermodynamic modelling and optimization framework for a thorough understanding of the optimal integration of fuel cell, gas turbine and other components in an ambient pressure SOFC-GT hybrid power plant. This method is based on the coupling of a syngas-fed SOFC model and an associated irreversible GT model, with an optimization algorithm developed using MATLAB to efficiently explore the range of possible operating conditions. Energy and entropy balance analysis has been carried out for the entire system to observe the irreversibility distribution within the plant and the contribution of different components. Based on the methodology developed, a comprehensive parametric analysis has been performed to explore the optimum system behavior, and predict the sensitivity of system performance to the variations in major design and operating parameters. The current density, operating temperature, fuel utilization and temperature gradient of the fuel cell, as well as the isentropic efficiencies and temperature ratio of the gas turbine cycle, together with three parameters related to the heat transfer between subsystems are all set to be controllable variables. Other factors affecting the hybrid efficiency have been further simulated and analysed. The model developed is able to predict the performance characteristics of a wide range of hybrid systems potentially sizing from 2000 to 2500 W m -2 with efficiencies varying between 50% and 60%. The analysis enables us to identify the system design tradeoffs, and therefore to determine better integration strategies for advanced SOFC-GT systems.

Kinetic modeling of multi-feed simultaneous saccharification and co-fermentation of pretreated birch to ethanol.

PubMed

Wang, Ruifei; Koppram, Rakesh; Olsson, Lisbeth; Franzén, Carl Johan

2014-11-01

Fed-batch simultaneous saccharification and fermentation (SSF) is a feasible option for bioethanol production from lignocellulosic raw materials at high substrate concentrations. In this work, a segregated kinetic model was developed for simulation of fed-batch simultaneous saccharification and co-fermentation (SSCF) of steam-pretreated birch, using substrate, enzymes and cell feeds. The model takes into account the dynamics of the cellulase-cellulose system and the cell population during SSCF, and the effects of pre-cultivation of yeast cells on fermentation performance. The model was cross-validated against experiments using different feed schemes. It could predict fermentation performance and explain observed differences between measured total yeast cells and dividing cells very well. The reproducibility of the experiments and the cell viability were significantly better in fed-batch than in batch SSCF at 15% and 20% total WIS contents. The model can be used for simulation of fed-batch SSCF and optimization of feed profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Enhanced cell disruption strategy in the release of recombinant hepatitis B surface antigen from Pichia pastoris using response surface methodology

PubMed Central

2012-01-01

Background Cell disruption strategies by high pressure homogenizer for the release of recombinant Hepatitis B surface antigen (HBsAg) from Pichia pastoris expression cells were optimized using response surface methodology (RSM) based on the central composite design (CCD). The factors studied include number of passes, biomass concentration and pulse pressure. Polynomial models were used to correlate the above mentioned factors to project the cell disruption capability and specific protein release of HBsAg from P. pastoris cells. Results The proposed cell disruption strategy consisted of a number of passes set at 20 times, biomass concentration of 7.70 g/L of dry cell weight (DCW) and pulse pressure at 1,029 bar. The optimized cell disruption strategy was shown to increase cell disruption efficiency by 2-fold and 4-fold for specific protein release of HBsAg when compared to glass bead method yielding 75.68% cell disruption rate (CDR) and HBsAg concentration of 29.20 mg/L respectively. Conclusions The model equation generated from RSM on cell disruption of P. pastoris was found adequate to determine the significant factors and its interactions among the process variables and the optimum conditions in releasing HBsAg when validated against a glass bead cell disruption method. The findings from the study can open up a promising strategy for better recovery of HBsAg recombinant protein during downstream processing. PMID:23039947

Radiation Damage to Nervous System: Designing Optimal Models for Realistic Neuron Morphology in Hippocampus

NASA Astrophysics Data System (ADS)

Batmunkh, Munkhbaatar; Bugay, Alexander; Bayarchimeg, Lkhagvaa; Lkhagva, Oidov

2018-02-01

The present study is focused on the development of optimal models of neuron morphology for Monte Carlo microdosimetry simulations of initial radiation-induced events of heavy charged particles in the specific types of cells of the hippocampus, which is the most radiation-sensitive structure of the central nervous system. The neuron geometry and particles track structures were simulated by the Geant4/Geant4-DNA Monte Carlo toolkits. The calculations were made for beams of protons and heavy ions with different energies and doses corresponding to real fluxes of galactic cosmic rays. A simple compartmental model and a complex model with realistic morphology extracted from experimental data were constructed and compared. We estimated the distribution of the energy deposition events and the production of reactive chemical species within the developed models of CA3/CA1 pyramidal neurons and DG granule cells of the rat hippocampus under exposure to different particles with the same dose. Similar distributions of the energy deposition events and concentration of some oxidative radical species were obtained in both the simplified and realistic neuron models.

Synthesis and Process Optimization of Electrospun PEEK-Sulfonated Nanofibers by Response Surface Methodology

PubMed Central

Boaretti, Carlo; Roso, Martina; Lorenzetti, Alessandra; Modesti, Michele

2015-01-01

In this study electrospun nanofibers of partially sulfonated polyether ether ketone have been produced as a preliminary step for a possible development of composite proton exchange membranes for fuel cells. Response surface methodology has been employed for the modelling and optimization of the electrospinning process, using a Box-Behnken design. The investigation, based on a second order polynomial model, has been focused on the analysis of the effect of both process (voltage, tip-to-collector distance, flow rate) and material (sulfonation degree) variables on the mean fiber diameter. The final model has been verified by a series of statistical tests on the residuals and validated by a comparison procedure of samples at different sulfonation degrees, realized according to optimized conditions, for the production of homogeneous thin nanofibers. PMID:28793427

Synthesis and Process Optimization of Electrospun PEEK-Sulfonated Nanofibers by Response Surface Methodology.

PubMed

Boaretti, Carlo; Roso, Martina; Lorenzetti, Alessandra; Modesti, Michele

2015-07-07

In this study electrospun nanofibers of partially sulfonated polyether ether ketone have been produced as a preliminary step for a possible development of composite proton exchange membranes for fuel cells. Response surface methodology has been employed for the modelling and optimization of the electrospinning process, using a Box-Behnken design. The investigation, based on a second order polynomial model, has been focused on the analysis of the effect of both process (voltage, tip-to-collector distance, flow rate) and material (sulfonation degree) variables on the mean fiber diameter. The final model has been verified by a series of statistical tests on the residuals and validated by a comparison procedure of samples at different sulfonation degrees, realized according to optimized conditions, for the production of homogeneous thin nanofibers.

Diffused junction p(+)-n solar cells in bulk GaAs. II - Device characterization and modelling

NASA Technical Reports Server (NTRS)

Keeney, R.; Sundaram, L. M. G.; Rode, H.; Bhat, I.; Ghandhi, S. K.; Borrego, J. M.

1984-01-01

The photovoltaic characteristics of p(+)-n junction solar cells fabricated on bulk GaAs by an open tube diffusion technique are presented in detail. Quantum efficiency measurements were analyzed and compared to computer simulations of the cell structure in order to determine material parameters such as diffusion length, surface recombination velocity and junction depth. From the results obtained it is projected that proper optimization of the cell parameters can increase the efficiency of the cells to close to 20 percent.

Advanced Thermophotovoltaic Cells Modeling, Optimized for Use in Radioisotope Thermoelectric Generators (RTGs) for Mars and Deep Space Missions

DTIC Science & Technology

2004-06-01

PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Thermophotovoltaic cells are a good candidate for use in high efficiency radioiso- tope...ongoing in this field since the 1950’s, but the exotic materials necessary for high efficiency cells has only been recently available. Here, several...This cell was able to operate at 24% efficiency which is very high for a silicon cell [Ref. 6]. The inverted pyramids labeled in the figure are

Testing the sensitivity of pumpage to increases in surficial aquifer system heads in the Cypress Creek well-field area, West-Central Florida : an optimization technique

USGS Publications Warehouse

Yobbi, Dann K.

2002-01-01

Tampa Bay depends on ground water for most of the water supply. Numerous wetlands and lakes in Pasco County have been impacted by the high demand for ground water. Central Pasco County, particularly the area within the Cypress Creek well field, has been greatly affected. Probable causes for the decline in surface-water levels are well-field pumpage and a decade-long drought. Efforts are underway to increase surface-water levels by developing alternative sources of water supply, thus reducing the quantity of well-field pumpage. Numerical ground-water flow simulations coupled with an optimization routine were used in a series of simulations to test the sensitivity of optimal pumpage to desired increases in surficial aquifer system heads in the Cypress Creek well field. The ground-water system was simulated using the central northern Tampa Bay ground-water flow model. Pumping solutions for 1987 equilibrium conditions and for a transient 6-month timeframe were determined for five test cases, each reflecting a range of desired target recovery heads at different head control sites in the surficial aquifer system. Results are presented in the form of curves relating average head recovery to total optimal pumpage. Pumping solutions are sensitive to the location of head control sites formulated in the optimization problem and as expected, total optimal pumpage decreased when desired target head increased. The distribution of optimal pumpage for individual production wells also was significantly affected by the location of head control sites. A pumping advantage was gained for test-case formulations where hydraulic heads were maximized in cells near the production wells, in cells within the steady-state pumping center cone of depression, and in cells within the area of the well field where confining-unit leakance is the highest. More water was pumped and the ratio of head recovery per unit decrease in optimal pumpage was more than double for test cases where hydraulic heads are maximized in cells located at or near the production wells. Additionally, the ratio of head recovery per unit decrease in pumpage was about three times more for the area where confining-unit leakance is the highest than for other leakance zone areas of the well field. For many head control sites, optimal heads corresponding to optimal pumpage deviated from the desired target recovery heads. Overall, pumping solutions were constrained by the limiting recovery values, initial head conditions, and by upper boundary conditions of the ground-water flow model.

Optimization protocol for the extraction of 6-gingerol and 6-shogaol from Zingiber officinale var. rubrum Theilade and improving antioxidant and anticancer activity using response surface methodology.

PubMed

Ghasemzadeh, Ali; Jaafar, Hawa Z E; Rahmat, Asmah

2015-07-30

Analysis and extraction of plant matrices are important processes for the development, modernization, and quality control of herbal formulations. Response surface methodology is a collection of statistical and mathematical techniques that are used to optimize the range of variables in various experimental processes to reduce the number of experimental runs, cost , and time, compared to other methods. Response surface methodology was applied for optimizing reflux extraction conditions for achieving high 6-gingerol and 6-shogaol contents, and high antioxidant activity in Zingiber officinale var. rubrum Theilade . The two-factor central composite design was employed to determine the effects of two independent variables, namely extraction temperature (X1: 50-80 °C) and time (X2: 2-4 h), on the properties of the extracts. The 6-gingerol and 6-shogaol contents were measured using ultra-performance liquid chromatography. The antioxidant activity of the rhizome extracts was determined by means of the 1,1-diphenyl-2-picrylhydrazyl assay. Anticancer activity of optimized extracts against HeLa cancer cell lines was measured using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Increasing the extraction temperature and time induced significant response of the variables. The optimum extraction condition for all responses was at 76.9 °C for 3.4 h. Under the optimum condition, the corresponding predicted response values for 6-gingerol, 6-shogaol, and the antioxidant activity were 2.89 mg/g DW, 1.85 mg/g DW, and 84.3%, respectively. 6-gingerol and 6-shogaol were extracted under optimized condition to check the viability of the models. The values were 2.92 and 1.88 mg/g DW, and 84.0% for 6-gingerol, 6-shogaol, and the antioxidant activity respectively. The experimental values agreed with those predicted, thus indicating suitability of the models employed and the success of RSM in optimizing the extraction condition. With optimizing of reflux extraction anticancer activity of extracts against HeLa cancer cells enhanced about 16.8%. The half inhibition concentration (IC50) value of optimized and unoptimized extract was found at concentration of 20.9 and 38.4 μg/mL respectively. Optimized extract showed more distinct anticancer activities against HeLa cancer cells in a concentration of 40 μg/mL (P < 0.01) without toxicity to normal cells. The results indicated that the pharmaceutical quality of ginger could be improved significantly by optimizing of extraction process using response surface methodology.

Universal entrainment mechanism controls contact times with motile cells

NASA Astrophysics Data System (ADS)

Mathijssen, Arnold J. T. M.; Jeanneret, Raphaël; Polin, Marco

2018-03-01

Contact between particles and motile cells underpins a wide variety of biological processes, from nutrient capture and ligand binding to grazing, viral infection, and cell-cell communication. The window of opportunity for these interactions depends on the basic mechanism determining contact time, which is currently unknown. By combining experiments on three different species—Chlamydomonas reinhardtii, Tetraselmis subcordiforms, and Oxyrrhis marina—with simulations and analytical modeling, we show that the fundamental physical process regulating proximity to a swimming microorganism is hydrodynamic particle entrainment. The resulting distribution of contact times is derived within the framework of Taylor dispersion as a competition between advection by the cell surface and microparticle diffusion, and predicts the existence of an optimal tracer size that is also observed experimentally. Spatial organization of flagella, swimming speed, and swimmer and tracer size influence entrainment features and provide tradeoffs that may be tuned to optimize the estimated probabilities for microbial interactions like predation and infection.

Process change evaluation framework for allogeneic cell therapies: impact on drug development and commercialization.

PubMed

Hassan, Sally; Huang, Hsini; Warren, Kim; Mahdavi, Behzad; Smith, David; Jong, Simcha; Farid, Suzanne S

2016-04-01

Some allogeneic cell therapies requiring a high dose of cells for large indication groups demand a change in cell expansion technology, from planar units to microcarriers in single-use bioreactors for the market phase. The aim was to model the optimal timing for making this change. A development lifecycle cash flow framework was created to examine the implications of process changes to microcarrier cultures at different stages of a cell therapy's lifecycle. The analysis performed under assumptions used in the framework predicted that making this switch earlier in development is optimal from a total expected out-of-pocket cost perspective. From a risk-adjusted net present value view, switching at Phase I is economically competitive but a post-approval switch can offer the highest risk-adjusted net present value as the cost of switching is offset by initial market penetration with planar technologies. The framework can facilitate early decision-making during process development.

Defining an optimal surface chemistry for pluripotent stem cell culture in 2D and 3D

NASA Astrophysics Data System (ADS)

Zonca, Michael R., Jr.

Surface chemistry is critical for growing pluripotent stem cells in an undifferentiated state. There is great potential to engineer the surface chemistry at the nanoscale level to regulate stem cell adhesion. However, the challenge is to identify the optimal surface chemistry of the substrata for ES cell attachment and maintenance. Using a high-throughput polymerization and screening platform, a chemically defined, synthetic polymer grafted coating that supports strong attachment and high expansion capacity of pluripotent stem cells has been discovered using mouse embryonic stem (ES) cells as a model system. This optimal substrate, N-[3-(Dimethylamino)propyl] methacrylamide (DMAPMA) that is grafted on 2D synthetic poly(ether sulfone) (PES) membrane, sustains the self-renewal of ES cells (up to 7 passages). DMAPMA supports cell attachment of ES cells through integrin beta1 in a RGD-independent manner and is similar to another recently reported polymer surface. Next, DMAPMA has been able to be transferred to 3D by grafting to synthetic, polymeric, PES fibrous matrices through both photo-induced and plasma-induced polymerization. These 3D modified fibers exhibited higher cell proliferation and greater expression of pluripotency markers of mouse ES cells than 2D PES membranes. Our results indicated that desirable surfaces in 2D can be scaled to 3D and that both surface chemistry and structural dimension strongly influence the growth and differentiation of pluripotent stem cells. Lastly, the feasibility of incorporating DMAPMA into a widely used natural polymer, alginate, has been tested. Novel adhesive alginate hydrogels have been successfully synthesized by either direct polymerization of DMAPMA and methacrylic acid blended with alginate, or photo-induced DMAPMA polymerization on alginate nanofibrous hydrogels. In particular, DMAPMA-coated alginate hydrogels support strong ES cell attachment, exhibiting a concentration dependency of DMAPMA. This research provides a new avenue for stem cell culture and maintenance using an optimal organic-based chemistry.

Patient-derived multicellular tumor spheroids towards optimized treatment for patients with hepatocellular carcinoma.

PubMed

Song, Yeonhwa; Kim, Jin-Sun; Kim, Se-Hyuk; Park, Yoon Kyung; Yu, Eunsil; Kim, Ki-Hun; Seo, Eul-Ju; Oh, Heung-Bum; Lee, Han Chu; Kim, Kang Mo; Seo, Haeng Ran

2018-05-25

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and has poor prognosis. Specially, patients with HCC usually have poor tolerance of systemic chemotherapy, because HCCs develop from chronically damaged tissue that contains considerable inflammation, fibrosis, and cirrhosis. Since HCC exhibits highly heterogeneous molecular characteristics, a proper in vitro system is required for the study of HCC pathogenesis. To this end, we have established two new hepatitis B virus (HBV) DNA-secreting HCC cell lines from infected patients. Based on these two new HCC cell lines, we have developed chemosensitivity assays for patient-derived multicellular tumor spheroids (MCTSs) in order to select optimized anti-cancer drugs to provide more informative data for clinical drug application. To monitor the effect of the interaction of cancer cells and stromal cells in MCTS, we used a 3D co-culture model with patient-derived HCC cells and stromal cells from human hepatic stellate cells, human fibroblasts, and human umbilical vein endothelial cells to facilitate screening for optimized cancer therapy. To validate our system, we performed a comparison of chemosensitivity of the three culture systems, which are monolayer culture system, tumor spheroids, and MCTSs of patient-derived cells, to sorafenib, 5-fluorouracil, and cisplatin, as these compounds are typically standard therapy for advanced HCC in South Korea. In summary, these findings suggest that the MCTS culture system is the best methodology for screening for optimized treatment for each patients with HCC, because tumor spheroids not only mirror the 3D cellular context of the tumors but also exhibit therapeutically relevant pathophysiological gradients and heterogeneity of in vivo tumors.

Simulation-assisted design of microfluidic sample traps for optimal trapping and culture of non-adherent single cells, tissues, and spheroids.

PubMed

Rousset, Nassim; Monet, Frédéric; Gervais, Thomas

2017-03-21

This work focuses on modelling design and operation of "microfluidic sample traps" (MSTs). MSTs regroup a widely used class of microdevices that incorporate wells, recesses or chambers adjacent to a channel to individually trap, culture and/or release submicroliter 3D tissue samples ranging from simple cell aggregates and spheroids, to ex vivo tissue samples and other submillimetre-scale tissue models. Numerous MST designs employing various trapping mechanisms have been proposed in the literature, spurring the development of 3D tissue models for drug discovery and personalized medicine. Yet, there lacks a general framework to optimize trapping stability, trapping time, shear stress, and sample metabolism. Herein, the effects of hydrodynamics and diffusion-reaction on tissue viability and device operation are investigated using analytical and finite element methods with systematic parametric sweeps over independent design variables chosen to correspond to the four design degrees of freedom. Combining different results, we show that, for a spherical tissue of diameter d < 500 μm, the simplest, closest to optimal trap shape is a cube of dimensions w equal to twice the tissue diameter: w = 2d. Furthermore, to sustain tissues without perfusion, available medium volume per trap needs to be 100× the tissue volume to ensure optimal metabolism for at least 24 hours.

Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

PubMed

Dühring, Sybille; Ewald, Jan; Germerodt, Sebastian; Kaleta, Christoph; Dandekar, Thomas; Schuster, Stefan

2017-07-01

The release of fungal cells following macrophage phagocytosis, called non-lytic expulsion, is reported for several fungal pathogens. On one hand, non-lytic expulsion may benefit the fungus in escaping the microbicidal environment of the phagosome. On the other hand, the macrophage could profit in terms of avoiding its own lysis and being able to undergo proliferation. To analyse the causes of non-lytic expulsion and the relevance of macrophage proliferation in the macrophage- Candida albicans interaction, we employ Evolutionary Game Theory and dynamic optimization in a sequential manner. We establish a game-theoretical model describing the different strategies of the two players after phagocytosis. Depending on the parameter values, we find four different Nash equilibria and determine the influence of the systems state of the host upon the game. As our Nash equilibria are a direct consequence of the model parameterization, we can depict several biological scenarios. A parameter region, where the host response is robust against the fungal infection, is determined. We further apply dynamic optimization to analyse whether macrophage mitosis is relevant in the host-pathogen interaction of macrophages and C. albicans For this, we study the population dynamics of the macrophage- C. albicans interactions and the corresponding optimal controls for the macrophages, indicating the best macrophage strategy of switching from proliferation to attacking fungal cells. © 2017 The Author(s).

Supraphysiologic control over HIV-1 replication mediated by CD8 T cells expressing a re-engineered CD4-based chimeric antigen receptor

PubMed Central

Richardson, Max W.; Ellebrecht, Christoph T.; Glover, Joshua A.; Secreto, Anthony J.; Kulikovskaya, Irina; Yi, Yanjie; Wang, Jianbin; Dufendach, Keith A.; Holmes, Michael C.; Collman, Ronald G.

2017-01-01

HIV is adept at avoiding naturally generated T cell responses; therefore, there is a need to develop HIV-specific T cells with greater potency for use in HIV cure strategies. Starting with a CD4-based chimeric antigen receptor (CAR) that was previously used without toxicity in clinical trials, we optimized the vector backbone, promoter, HIV targeting moiety, and transmembrane and signaling domains to determine which components augmented the ability of T cells to control HIV replication. This re-engineered CAR was at least 50-fold more potent in vitro at controlling HIV replication than the original CD4 CAR, or a TCR-based approach, and substantially better than broadly neutralizing antibody-based CARs. A humanized mouse model of HIV infection demonstrated that T cells expressing optimized CARs were superior at expanding in response to antigen, protecting CD4 T cells from infection, and reducing viral loads compared to T cells expressing the original, clinical trial CAR. Moreover, in a humanized mouse model of HIV treatment, CD4 CAR T cells containing the 4-1BB costimulatory domain controlled HIV spread after ART removal better than analogous CAR T cells containing the CD28 costimulatory domain. Together, these data indicate that potent HIV-specific T cells can be generated using improved CAR design and that CAR T cells could be important components of an HIV cure strategy. PMID:29023549

Designing Experiments to Discriminate Families of Logic Models.

PubMed

Videla, Santiago; Konokotina, Irina; Alexopoulos, Leonidas G; Saez-Rodriguez, Julio; Schaub, Torsten; Siegel, Anne; Guziolowski, Carito

2015-01-01

Logic models of signaling pathways are a promising way of building effective in silico functional models of a cell, in particular of signaling pathways. The automated learning of Boolean logic models describing signaling pathways can be achieved by training to phosphoproteomics data, which is particularly useful if it is measured upon different combinations of perturbations in a high-throughput fashion. However, in practice, the number and type of allowed perturbations are not exhaustive. Moreover, experimental data are unavoidably subjected to noise. As a result, the learning process results in a family of feasible logical networks rather than in a single model. This family is composed of logic models implementing different internal wirings for the system and therefore the predictions of experiments from this family may present a significant level of variability, and hence uncertainty. In this paper, we introduce a method based on Answer Set Programming to propose an optimal experimental design that aims to narrow down the variability (in terms of input-output behaviors) within families of logical models learned from experimental data. We study how the fitness with respect to the data can be improved after an optimal selection of signaling perturbations and how we learn optimal logic models with minimal number of experiments. The methods are applied on signaling pathways in human liver cells and phosphoproteomics experimental data. Using 25% of the experiments, we obtained logical models with fitness scores (mean square error) 15% close to the ones obtained using all experiments, illustrating the impact that our approach can have on the design of experiments for efficient model calibration.

Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs.

PubMed

Abou-El-Enein, Mohamed; Römhild, Andy; Kaiser, Daniel; Beier, Carola; Bauer, Gerhard; Volk, Hans-Dieter; Reinke, Petra

2013-03-01

Advanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities. The "Clean-Room Technology Assessment Technique" (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system. CTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost. CTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions. Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Geometric modeling of space-optimal unit-cell-based tissue engineering scaffolds

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Lu, Lichun; Yaszemski, Michael J.; Robb, Richard A.

2005-04-01

Tissue engineering involves regenerating damaged or malfunctioning organs using cells, biomolecules, and synthetic or natural scaffolds. Based on their intended roles, scaffolds can be injected as space-fillers or be preformed and implanted to provide mechanical support. Preformed scaffolds are biomimetic "trellis-like" structures which, on implantation and integration, act as tissue/organ surrogates. Customized, computer controlled, and reproducible preformed scaffolds can be fabricated using Computer Aided Design (CAD) techniques and rapid prototyping devices. A curved, monolithic construct with minimal surface area constitutes an efficient substrate geometry that promotes cell attachment, migration and proliferation. However, current CAD approaches do not provide such a biomorphic construct. We address this critical issue by presenting one of the very first physical realizations of minimal surfaces towards the construction of efficient unit-cell based tissue engineering scaffolds. Mask programmability, and optimal packing density of triply periodic minimal surfaces are used to construct the optimal pore geometry. Budgeted polygonization, and progressive minimal surface refinement facilitate the machinability of these surfaces. The efficient stress distributions, as deduced from the Finite Element simulations, favor the use of these scaffolds for orthopedic applications.

Effect of Shock Waves Generated by Pulsed Electric Discharges in Water on Yeast Cells and Virus Particles

NASA Astrophysics Data System (ADS)

Girdyuk, A. E.; Gorshkov, A. N.; Egorov, V. V.; Kolikov, V. A.; Snetov, V. N.; Shneerson, G. A.

2018-02-01

The aim of this study is to determine the optimal parameters of the electric pulses and shock waves generated by them for the soft destruction of the virus and yeast envelopes with no changes in the structure of antigenic surface albumin and in the cell morphology in order to use them to produce antivirus vaccines and in biotechnology. The pulse electric discharges in water have been studied for different values of amplitude, pulse duration and the rate of the rise in the current. A mathematical model has been developed to estimate the optimal parameters of pulsed electric charges and shock waves for the complete destruction of the yeast cell envelopes and virus particles at a minimum of pulses.

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

NASA Astrophysics Data System (ADS)

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2012-12-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.

Cell wall modifications of two Arabidopsis thaliana ecotypes, Col and Sha, in response to sub-optimal growth conditions: An integrative study.

PubMed

Duruflé, Harold; Hervé, Vincent; Ranocha, Philippe; Balliau, Thierry; Zivy, Michel; Chourré, Josiane; San Clemente, Hélène; Burlat, Vincent; Albenne, Cécile; Déjean, Sébastien; Jamet, Elisabeth; Dunand, Christophe

2017-10-01

With the global temperature change, plant adaptations are predicted, but little is known about the molecular mechanisms underlying them. Arabidopsis thaliana is a model plant adapted to various environmental conditions, in particular able to develop along an altitudinal gradient. Two ecotypes, Columbia (Col) growing at low altitude, and Shahdara (Sha) growing at 3400m, have been studied at optimal and sub-optimal growth temperature (22°C vs 15°C). Macro- and micro-phenotyping, cell wall monosaccharides analyses, cell wall proteomics, and transcriptomics have been performed in order to accomplish an integrative analysis. The analysis has been focused on cell walls (CWs) which are assumed to play roles in response to environmental changes. At 15°C, both ecotypes presented characteristic morphological traits of low temperature growth acclimation such as reduced rosette diameter, increased number of leaves, modifications of their CW composition and cuticle reinforcement. Altogether, the integrative analysis has allowed identifying several candidate genes/proteins possibly involved in the cell wall modifications observed during the temperature acclimation response. Copyright © 2017 Elsevier B.V. All rights reserved.

Interplay between intrinsic noise and the stochasticity of the cell cycle in bacterial colonies.

PubMed

Canela-Xandri, Oriol; Sagués, Francesc; Buceta, Javier

2010-06-02

Herein we report on the effects that different stochastic contributions induce in bacterial colonies in terms of protein concentration and production. In particular, we consider for what we believe to be the first time cell-to-cell diversity due to the unavoidable randomness of the cell-cycle duration and its interplay with other noise sources. To that end, we model a recent experimental setup that implements a protein dilution protocol by means of division events to characterize the gene regulatory function at the single cell level. This approach allows us to investigate the effect of different stochastic terms upon the total randomness experimentally reported for the gene regulatory function. In addition, we show that the interplay between intrinsic fluctuations and the stochasticity of the cell-cycle duration leads to different constructive roles. On the one hand, we show that there is an optimal value of protein concentration (alternatively an optimal value of the cell cycle phase) such that the noise in protein concentration attains a minimum. On the other hand, we reveal that there is an optimal value of the stochasticity of the cell cycle duration such that the coherence of the protein production with respect to the colony average production is maximized. The latter can be considered as a novel example of the recently reported phenomenon of diversity induced resonance. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Cancer Modeling: From Optimal Cell Renewal to Immunotherapy

NASA Astrophysics Data System (ADS)

Alvarado Alvarado, Cesar Leonardo

Cancer is a disease caused by mutations in normal cells. According to the National Cancer Institute, in 2016, an estimated 1.6 million people were diagnosed and approximately 0.5 million people died from the disease in the United States. There are many factors that shape cancer at the cellular and organismal level, including genetic, immunological, and environmental components. In this thesis, we show how mathematical modeling can be used to provide insight into some of the key mechanisms underlying cancer dynamics. First, we use mathematical modeling to investigate optimal homeostatic cell renewal in tissues such as the small intestine with an emphasis on division patterns and tissue architecture. We find that the division patterns that delay the accumulation of mutations are strictly associated with the population sizes of the tissue. In particular, patterns with long chains of differentiation delay the time to observe a second-hit mutant, which is important given that for many cancers two mutations are enough to initiate a tumor. We also investigated homeostatic cell renewal under a selective pressure and find that hierarchically organized tissues act as suppressors of selection; we find that an architecture with a small number of stem cells and larger pools of transit amplifying cells and mature differentiated cells, together with long chains of differentiation, form a robust evolutionary strategy to delay the time to observe a second-hit mutant when mutations acquire a fitness advantage or disadvantage. We also formulate a model of the immune response to cancer in the presence of costimulatory and inhibitory signals. We demonstrate that the coordination of such signals is crucial to initiate an effective immune response, and while immunotherapy has become a promising cancer treatment over the past decade, these results offer some explanations for why it can fail.

Optimization of Residual Stresses in MMC's through Process Parameter Control and the use of Heterogeneous Compensating/Compliant Interfacial Layers. OPTCOMP2 User's Guide

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Salzar, Robert S.

1996-01-01

A user's guide for the computer program OPTCOMP2 is presented in this report. This program provides a capability to optimize the fabrication or service-induced residual stresses in unidirectional metal matrix composites subjected to combined thermomechanical axisymmetric loading by altering the processing history, as well as through the microstructural design of interfacial fiber coatings. The user specifies the initial architecture of the composite and the load history, with the constituent materials being elastic, plastic, viscoplastic, or as defined by the 'user-defined' constitutive model, in addition to the objective function and constraints, through a user-friendly data input interface. The optimization procedure is based on an efficient solution methodology for the inelastic response of a fiber/interface layer(s)/matrix concentric cylinder model where the interface layers can be either homogeneous or heterogeneous. The response of heterogeneous layers is modeled using Aboudi's three-dimensional method of cells micromechanics model. The commercial optimization package DOT is used for the nonlinear optimization problem. The solution methodology for the arbitrarily layered cylinder is based on the local-global stiffness matrix formulation and Mendelson's iterative technique of successive elastic solutions developed for elastoplastic boundary-value problems. The optimization algorithm employed in DOT is based on the method of feasible directions.

Thermodynamic efficiency limits of classical and bifacial multi-junction tandem solar cells: An analytical approach

NASA Astrophysics Data System (ADS)

Alam, Muhammad Ashraful; Khan, M. Ryyan

2016-10-01

Bifacial tandem cells promise to reduce three fundamental losses (i.e., above-bandgap, below bandgap, and the uncollected light between panels) inherent in classical single junction photovoltaic (PV) systems. The successive filtering of light through the bandgap cascade and the requirement of current continuity make optimization of tandem cells difficult and accessible only to numerical solution through computer modeling. The challenge is even more complicated for bifacial design. In this paper, we use an elegantly simple analytical approach to show that the essential physics of optimization is intuitively obvious, and deeply insightful results can be obtained with a few lines of algebra. This powerful approach reproduces, as special cases, all of the known results of conventional and bifacial tandem cells and highlights the asymptotic efficiency gain of these technologies.

A variable structure fuzzy neural network model of squamous dysplasia and esophageal squamous cell carcinoma based on a global chaotic optimization algorithm.

PubMed

Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Malekzadeh, Reza

2013-02-07

Identification of squamous dysplasia and esophageal squamous cell carcinoma (ESCC) is of great importance in prevention of cancer incidence. Computer aided algorithms can be very useful for identification of people with higher risks of squamous dysplasia, and ESCC. Such method can limit the clinical screenings to people with higher risks. Different regression methods have been used to predict ESCC and dysplasia. In this paper, a Fuzzy Neural Network (FNN) model is selected for ESCC and dysplasia prediction. The inputs to the classifier are the risk factors. Since the relation between risk factors in the tumor system has a complex nonlinear behavior, in comparison to most of ordinary data, the cost function of its model can have more local optimums. Thus the need for global optimization methods is more highlighted. The proposed method in this paper is a Chaotic Optimization Algorithm (COA) proceeding by the common Error Back Propagation (EBP) local method. Since the model has many parameters, we use a strategy to reduce the dependency among parameters caused by the chaotic series generator. This dependency was not considered in the previous COA methods. The algorithm is compared with logistic regression model as the latest successful methods of ESCC and dysplasia prediction. The results represent a more precise prediction with less mean and variance of error. Copyright © 2012 Elsevier Ltd. All rights reserved.

Design of optimal hyperthermia protocols for prostate cancer by controlling HSP expression through computer modeling (Invited Paper)

NASA Astrophysics Data System (ADS)

Rylander, Marissa N.; Feng, Yusheng; Diller, Kenneth; Bass, J.

2005-04-01

Heat shock proteins (HSP) are critical components of a complex defense mechanism essential for preserving cell survival under adverse environmental conditions. It is inevitable that hyperthermia will enhance tumor tissue viability, due to HSP expression in regions where temperatures are insufficient to coagulate proteins, and would likely increase the probability of cancer recurrence. Although hyperthermia therapy is commonly used in conjunction with radiotherapy, chemotherapy, and gene therapy to increase therapeutic effectiveness, the efficacy of these therapies can be substantially hindered due to HSP expression when hyperthermia is applied prior to these procedures. Therefore, in planning hyperthermia protocols, prediction of the HSP response of the tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of overall tissue response. In this paper, we present a highly accurate, adaptive, finite element tumor model capable of predicting the HSP expression distribution and tissue damage region based on measured cellular data when hyperthermia protocols are specified. Cubic spline representations of HSP27 and HSP70, and Arrhenius damage models were integrated into the finite element model to enable prediction of the HSP expression and damage distribution in the tissue following laser heating. Application of the model can enable optimized treatment planning by controlling of the tissue response to therapy based on accurate prediction of the HSP expression and cell damage distribution.

Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

NASA Astrophysics Data System (ADS)

Rothenberger, Michael J.

This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input-output measurements, and is the approach used in this dissertation. Research in the literature studies optimal current input shaping for high-order electrochemical battery models and focuses on offline laboratory cycling. While this body of research highlights improvements in identifiability through optimal input shaping, each optimal input is a function of nominal parameters, which creates a tautology. The parameter values must be known a priori to determine the optimal input for maximizing estimation speed and accuracy. The system identification literature presents multiple studies containing methods that avoid the challenges of this tautology, but these methods are absent from the battery parameter estimation domain. The gaps in the above literature are addressed in this dissertation through the following five novel and unique contributions. First, this dissertation optimizes the parameter identifiability of a thermal battery model, which Sergio Mendoza experimentally validates through a close collaboration with this dissertation's author. Second, this dissertation extends input-shaping optimization to a linear and nonlinear equivalent-circuit battery model and illustrates the substantial improvements in Fisher identifiability for a periodic optimal signal when compared against automotive benchmark cycles. Third, this dissertation presents an experimental validation study of the simulation work in the previous contribution. The estimation study shows that the automotive benchmark cycles either converge slower than the optimized cycle, or not at all for certain parameters. Fourth, this dissertation examines how automotive battery packs with additional power electronic components that dynamically route current to individual cells/modules can be used for parameter identifiability optimization. While the user and vehicle supervisory controller dictate the current demand for these packs, the optimized internal allocation of current still improves identifiability. Finally, this dissertation presents a robust Bayesian sequential input shaping optimization study to maximize the conditional Fisher information of the battery model parameters without prior knowledge of the nominal parameter set. This iterative algorithm only requires knowledge of the prior parameter distributions to converge to the optimal input trajectory.

Sensing in tissue bioreactors

NASA Astrophysics Data System (ADS)

Rolfe, P.

2006-03-01

Specialized sensing and measurement instruments are under development to aid the controlled culture of cells in bioreactors for the fabrication of biological tissues. Precisely defined physical and chemical conditions are needed for the correct culture of the many cell-tissue types now being studied, including chondrocytes (cartilage), vascular endothelial cells and smooth muscle cells (blood vessels), fibroblasts, hepatocytes (liver) and receptor neurones. Cell and tissue culture processes are dynamic and therefore, optimal control requires monitoring of the key process variables. Chemical and physical sensing is approached in this paper with the aim of enabling automatic optimal control, based on classical cell growth models, to be achieved. Non-invasive sensing is performed via the bioreactor wall, invasive sensing with probes placed inside the cell culture chamber and indirect monitoring using analysis within a shunt or a sampling chamber. Electroanalytical and photonics-based systems are described. Chemical sensing for gases, ions, metabolites, certain hormones and proteins, is under development. Spectroscopic analysis of the culture medium is used for measurement of glucose and for proteins that are markers of cell biosynthetic behaviour. Optical interrogation of cells and tissues is also investigated for structural analysis based on scatter.

Efficiency of timing delays and electrode positions in optimization of biventricular pacing: a simulation study.

PubMed

Miri, Raz; Graf, Iulia M; Dössel, Olaf

2009-11-01

Electrode positions and timing delays influence the efficacy of biventricular pacing (BVP). Accordingly, this study focuses on BVP optimization, using a detailed 3-D electrophysiological model of the human heart, which is adapted to patient-specific anatomy and pathophysiology. The research is effectuated on ten heart models with left bundle branch block and myocardial infarction derived from magnetic resonance and computed tomography data. Cardiac electrical activity is simulated with the ten Tusscher cell model and adaptive cellular automaton at physiological and pathological conduction levels. The optimization methods are based on a comparison between the electrical response of the healthy and diseased heart models, measured in terms of root mean square error (E(RMS)) of the excitation front and the QRS duration error (E(QRS)). Intra- and intermethod associations of the pacing electrodes and timing delays variables were analyzed with statistical methods, i.e., t -test for dependent data, one-way analysis of variance for electrode pairs, and Pearson model for equivalent parameters from the two optimization methods. The results indicate that lateral the left ventricle and the upper or middle septal area are frequently (60% of cases) the optimal positions of the left and right electrodes, respectively. Statistical analysis proves that the two optimization methods are in good agreement. In conclusion, a noninvasive preoperative BVP optimization strategy based on computer simulations can be used to identify the most beneficial patient-specific electrode configuration and timing delays.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

PubMed

Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

A Functional High-Throughput Assay of Myelination in Vitro

DTIC Science & Technology

2014-07-01

iPS cells derived from human astrocytes. These cell lines will serve as an excellent source of human cells from which our model systems may be...image the 3D rat dorsal root ganglion ( DRG ) cultures with sufficiently low background as to detect electrically-evoked depolarization events, as...stimulation and recording system specifically for this purpose. Further, we found that the limitations inherent in optimizing speed and FOV may

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

NASA Astrophysics Data System (ADS)

Sanaye, Sepehr; Katebi, Arash

2014-02-01

Energy, exergy, economic and environmental (4E) analysis and optimization of a hybrid solid oxide fuel cell and micro gas turbine (SOFC-MGT) system for use as combined generation of heat and power (CHP) is investigated in this paper. The hybrid system is modeled and performance related results are validated using available data in literature. Then a multi-objective optimization approach based on genetic algorithm is incorporated. Eight system design parameters are selected for the optimization procedure. System exergy efficiency and total cost rate (including capital or investment cost, operational cost and penalty cost of environmental emissions) are the two objectives. The effects of fuel unit cost, capital investment and system power output on optimum design parameters are also investigated. It is observed that the most sensitive and important design parameter in the hybrid system is fuel cell current density which has a significant effect on the balance between system cost and efficiency. The selected design point from the Pareto distribution of optimization results indicates a total system exergy efficiency of 60.7%, with estimated electrical energy cost 0.057 kW-1 h-1, and payback period of about 6.3 years for the investment.

Design and optimization of reverse-transcription quantitative PCR experiments.

PubMed

Tichopad, Ales; Kitchen, Rob; Riedmaier, Irmgard; Becker, Christiane; Ståhlberg, Anders; Kubista, Mikael

2009-10-01

Quantitative PCR (qPCR) is a valuable technique for accurately and reliably profiling and quantifying gene expression. Typically, samples obtained from the organism of study have to be processed via several preparative steps before qPCR. We estimated the errors of sample withdrawal and extraction, reverse transcription (RT), and qPCR that are introduced into measurements of mRNA concentrations. We performed hierarchically arranged experiments with 3 animals, 3 samples, 3 RT reactions, and 3 qPCRs and quantified the expression of several genes in solid tissue, blood, cell culture, and single cells. A nested ANOVA design was used to model the experiments, and relative and absolute errors were calculated with this model for each processing level in the hierarchical design. We found that intersubject differences became easily confounded by sample heterogeneity for single cells and solid tissue. In cell cultures and blood, the noise from the RT and qPCR steps contributed substantially to the overall error because the sampling noise was less pronounced. We recommend the use of sample replicates preferentially to any other replicates when working with solid tissue, cell cultures, and single cells, and we recommend the use of RT replicates when working with blood. We show how an optimal sampling plan can be calculated for a limited budget. .

Effective cancer laser-therapy design through the integration of nanotechnology and computational treatment planning models

NASA Astrophysics Data System (ADS)

Fisher, Jessica W.; Rylander, Marissa Nichole

2008-02-01

Laser therapies can provide a minimally invasive treatment alternative to surgical resection of tumors. However, the effectiveness of these therapies is limited due to nonspecific heating of target tissue which often leads to healthy tissue injury and extended treatment durations. These therapies can be further compromised due to heat shock protein (HSP) induction in tumor regions where non-lethal temperature elevation occurs, thereby imparting enhanced tumor cell viability and resistance to subsequent chemotherapy and radiation treatments. Introducing multi-walled nanotubes (MWNT) into target tissue prior to laser irradiation increases heating selectivity permitting more precise thermal energy delivery to the tumor region and enhances thermal deposition thereby increasing tumor injury and reducing HSP expression induction. This study investigated the impact of MWNT inclusion in untreated and laser irradiated monolayer cell culture and cell phantom model. Cell viability remained high for all samples with MWNT inclusion and cells integrated into alginate phantoms, demonstrating the non-toxic nature of both MWNTs and alginate phantom models. Following, laser irradiation samples with MWNT inclusion exhibited dramatic temperature elevations and decreased cell viability compared to samples without MWNT. In the cell monolayer studies, laser irradiation of samples with MWNT inclusion experienced up-regulated HSP27, 70 and 90 expression as compared to laser only or untreated samples due to greater temperature increases albeit below the threshold for cell death. Further tuning of laser parameters will permit effective cell killing and down-regulation of HSP. Due to optimal tuning of laser parameters and inclusion of MWNT in phantom models, extensive temperature elevations and cell death occurred, demonstrating MWNT-mediated laser therapy as a viable therapy option when parameters are optimized. In conclusion, MWNT-mediated laser therapies show great promise for effective tumor destruction, but require determination of appropriate MWNT characteristics and laser parameters for maximum tumor destruction.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

Perfluorocarbon Particle Size Influences Magnetic Resonance Signal and Immunological Properties of Dendritic Cells

PubMed Central

Waiczies, Helmar; Lepore, Stefano; Janitzek, Nicole; Hagen, Ulrike; Seifert, Frank; Ittermann, Bernd; Purfürst, Bettina; Pezzutto, Antonio; Paul, Friedemann; Niendorf, Thoralf; Waiczies, Sonia

2011-01-01

The development of cellular tracking by fluorine (19F) magnetic resonance imaging (MRI) has introduced a number of advantages for following immune cell therapies in vivo. These include improved signal selectivity and a possibility to correlate cells labeled with fluorine-rich particles with conventional anatomic proton (1H) imaging. While the optimization of the cellular labeling method is clearly important, the impact of labeling on cellular dynamics should be kept in mind. We show by 19F MR spectroscopy (MRS) that the efficiency in labeling cells of the murine immune system (dendritic cells) by perfluoro-15-crown-5-ether (PFCE) particles increases with increasing particle size (560>365>245>130 nm). Dendritic cells (DC) are professional antigen presenting cells and with respect to impact of PFCE particles on DC function, we observed that markers of maturation for these cells (CD80, CD86) were also significantly elevated following labeling with larger PFCE particles (560 nm). When labeled with these larger particles that also gave an optimal signal in MRS, DC presented whole antigen more robustly to CD8+ T cells than control cells. Our data suggest that increasing particle size is one important feature for optimizing cell labeling by PFCE particles, but may also present possible pitfalls such as alteration of the immunological status of these cells. Therefore depending on the clinical scenario in which the 19F-labeled cellular vaccines will be applied (cancer, autoimmune disease, transplantation), it will be interesting to monitor the fate of these cells in vivo in the relevant preclinical mouse models. PMID:21811551

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

Development of Multivariable Models to Predict and Benchmark Transfusion in Elective Surgery Supporting Patient Blood Management.

PubMed

Hayn, Dieter; Kreiner, Karl; Ebner, Hubert; Kastner, Peter; Breznik, Nada; Rzepka, Angelika; Hofmann, Axel; Gombotz, Hans; Schreier, Günter

2017-06-14

Blood transfusion is a highly prevalent procedure in hospitalized patients and in some clinical scenarios it has lifesaving potential. However, in most cases transfusion is administered to hemodynamically stable patients with no benefit, but increased odds of adverse patient outcomes and substantial direct and indirect cost. Therefore, the concept of Patient Blood Management has increasingly gained importance to pre-empt and reduce transfusion and to identify the optimal transfusion volume for an individual patient when transfusion is indicated. It was our aim to describe, how predictive modeling and machine learning tools applied on pre-operative data can be used to predict the amount of red blood cells to be transfused during surgery and to prospectively optimize blood ordering schedules. In addition, the data derived from the predictive models should be used to benchmark different hospitals concerning their blood transfusion patterns. 6,530 case records obtained for elective surgeries from 16 centers taking part in two studies conducted in 2004-2005 and 2009-2010 were analyzed. Transfused red blood cell volume was predicted using random forests. Separate models were trained for overall data, for each center and for each of the two studies. Important characteristics of different models were compared with one another. Our results indicate that predictive modeling applied prior surgery can predict the transfused volume of red blood cells more accurately (correlation coefficient cc = 0.61) than state of the art algorithms (cc = 0.39). We found significantly different patterns of feature importance a) in different hospitals and b) between study 1 and study 2. We conclude that predictive modeling can be used to benchmark the importance of different features on the models derived with data from different hospitals. This might help to optimize crucial processes in a specific hospital, even in other scenarios beyond Patient Blood Management.

Study on Topology Optimization Design, Manufacturability, and Performance Evaluation of Ti-6Al-4V Porous Structures Fabricated by Selective Laser Melting (SLM)

PubMed Central

Xu, Yangli; Zhang, Dongyun; Zhou, Yan; Wang, Weidong; Cao, Xuanyang

2017-01-01

The combination of topology optimization (TOP) and selective laser melting (SLM) provides the possibility of fabricating the complex, lightweight and high performance geometries overcoming the traditional manufacturing “bottleneck”. This paper evaluates the biomechanical properties of porous structures with porosity from 40% to 80% and unit cell size from 2 to 8 mm, which are designed by TOP and manufactured by SLM. During manufacturability exploration, three typical structures including spiral structure, arched bridge structure and structures with thin walls and small holes are abstracted and investigated, analyzing their manufacturing limits and forming reason. The property tests show that dynamic elastic modulus and compressive strength of porous structures decreases with increases of porosity (constant unit cell size) or unit cell size (constant porosity). Based on the Gibson-Ashby model, three failure models are proposed to describe their compressive behavior, and the structural parameter λ is used to evaluate the stability of the porous structure. Finally, a numerical model for the correlation between porous structural parameters (unit cell size and porosity) and elastic modulus is established, which provides a theoretical reference for matching the elastic modulus of human bones from different age, gender and skeletal sites during innovative medical implant design and manufacturing. PMID:28880229

Study on Topology Optimization Design, Manufacturability, and Performance Evaluation of Ti-6Al-4V Porous Structures Fabricated by Selective Laser Melting (SLM).

PubMed

Xu, Yangli; Zhang, Dongyun; Zhou, Yan; Wang, Weidong; Cao, Xuanyang

2017-09-07

The combination of topology optimization (TOP) and selective laser melting (SLM) provides the possibility of fabricating the complex, lightweight and high performance geometries overcoming the traditional manufacturing "bottleneck". This paper evaluates the biomechanical properties of porous structures with porosity from 40% to 80% and unit cell size from 2 to 8 mm, which are designed by TOP and manufactured by SLM. During manufacturability exploration, three typical structures including spiral structure, arched bridge structure and structures with thin walls and small holes are abstracted and investigated, analyzing their manufacturing limits and forming reason. The property tests show that dynamic elastic modulus and compressive strength of porous structures decreases with increases of porosity (constant unit cell size) or unit cell size (constant porosity). Based on the Gibson-Ashby model, three failure models are proposed to describe their compressive behavior, and the structural parameter λ is used to evaluate the stability of the porous structure. Finally, a numerical model for the correlation between porous structural parameters (unit cell size and porosity) and elastic modulus is established, which provides a theoretical reference for matching the elastic modulus of human bones from different age, gender and skeletal sites during innovative medical implant design and manufacturing.

3D geometrical characterization and modelling of solid oxide cells electrodes microstructure by image analysis

NASA Astrophysics Data System (ADS)

Moussaoui, H.; Debayle, J.; Gavet, Y.; Delette, G.; Hubert, M.; Cloetens, P.; Laurencin, J.

2017-03-01

A strong correlation exists between the performance of Solid Oxide Cells (SOCs), working either in fuel cell or electrolysis mode, and their electrodes microstructure. However, the basic relationships between the three-dimensional characteristics of the microstructure and the electrode properties are not still precisely understood. Thus, several studies have been recently proposed in an attempt to improve the knowledge of such relations, which are essential before optimizing the microstructure, and hence, designing more efficient SOC electrodes. In that frame, an original model has been adapted to generate virtual 3D microstructures of typical SOCs electrodes. Both the oxygen electrode, which is made of porous LSCF, and the hydrogen electrodes, made of porous Ni-YSZ, have been studied. In this work, the synthetic microstructures are generated by the so-called 3D Gaussian `Random Field model'. The morphological representativeness of the virtual porous media have been validated on real 3D electrode microstructures of a commercial cell, obtained by X-ray nano-tomography at the European Synchrotron Radiation Facility (ESRF). This validation step includes the comparison of the morphological parameters like the phase covariance function and granulometry as well as the physical parameters like the `apparent tortuosity'. Finally, this validated tool will be used, in forthcoming studies, to identify the optimal microstructure of SOCs.

A rigorous multiple independent binding site model for determining cell-based equilibrium dissociation constants.

PubMed

Drake, Andrew W; Klakamp, Scott L

2007-01-10

A new 4-parameter nonlinear equation based on the standard multiple independent binding site model (MIBS) is presented for fitting cell-based ligand titration data in order to calculate the ligand/cell receptor equilibrium dissociation constant and the number of receptors/cell. The most commonly used linear (Scatchard Plot) or nonlinear 2-parameter model (a single binding site model found in commercial programs like Prism(R)) used for analysis of ligand/receptor binding data assumes only the K(D) influences the shape of the titration curve. We demonstrate using simulated data sets that, depending upon the cell surface receptor expression level, the number of cells titrated, and the magnitude of the K(D) being measured, this assumption of always being under K(D)-controlled conditions can be erroneous and can lead to unreliable estimates for the binding parameters. We also compare and contrast the fitting of simulated data sets to the commonly used cell-based binding equation versus our more rigorous 4-parameter nonlinear MIBS model. It is shown through these simulations that the new 4-parameter MIBS model, when used for cell-based titrations under optimal conditions, yields highly accurate estimates of all binding parameters and hence should be the preferred model to fit cell-based experimental nonlinear titration data.

Optimal Battery Charging for Damage Mitigation

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2003-01-01

Our control philosophy is to charge the NiH2 cell in such a way that the damage incurred during the charging period is minimized, thus extending its cycle life. This requires nonlinear dynamic model of NiH2 cell and a damage rate model. We must do this first. This control philosophy is generally considered damage mitigating control or life-extending control. This presentation covers how NiH2 cells function, electrode behavior, an essentialized model, damage mechanisms for NiH2 batteries, battery continuum damage modeling, and battery life models. The presentation includes graphs and a chart illustrating how charging a NiH2 battery with different voltages and currents affects damages the battery and affects its life. The presentation concludes with diagrams of control system architectures for tracking battery recharging.

An Illumination- and Temperature-Dependent Analytical Model for Copper Indium Gallium Diselenide (CIGS) Solar Cells

DOE PAGES

Sun, Xingshu; Silverman, Timothy; Garris, Rebekah; ...

2016-07-18

In this study, we present a physics-based analytical model for copper indium gallium diselenide (CIGS) solar cells that describes the illumination- and temperature-dependent current-voltage (I-V) characteristics and accounts for the statistical shunt variation of each cell. The model is derived by solving the drift-diffusion transport equation so that its parameters are physical and, therefore, can be obtained from independent characterization experiments. The model is validated against CIGS I-V characteristics as a function of temperature and illumination intensity. This physics-based model can be integrated into a large-scale simulation framework to optimize the performance of solar modules, as well as predict themore » long-term output yields of photovoltaic farms under different environmental conditions.« less

Portfolio Optimization of Nanomaterial Use in Clean Energy Technologies.

PubMed

Moore, Elizabeth A; Babbitt, Callie W; Gaustad, Gabrielle; Moore, Sean T

2018-04-03

While engineered nanomaterials (ENMs) are increasingly incorporated in diverse applications, risks of ENM adoption remain difficult to predict and mitigate proactively. Current decision-making tools do not adequately account for ENM uncertainties including varying functional forms, unique environmental behavior, economic costs, unknown supply and demand, and upstream emissions. The complexity of the ENM system necessitates a novel approach: in this study, the adaptation of an investment portfolio optimization model is demonstrated for optimization of ENM use in renewable energy technologies. Where a traditional investment portfolio optimization model maximizes return on investment through optimal selection of stock, ENM portfolio optimization maximizes the performance of energy technology systems by optimizing selective use of ENMs. Cumulative impacts of multiple ENM material portfolios are evaluated in two case studies: organic photovoltaic cells (OPVs) for renewable energy and lithium-ion batteries (LIBs) for electric vehicles. Results indicate ENM adoption is dependent on overall performance and variance of the material, resource use, environmental impact, and economic trade-offs. From a sustainability perspective, improved clean energy applications can help extend product lifespans, reduce fossil energy consumption, and substitute ENMs for scarce incumbent materials.

Optimal control for Malaria disease through vaccination

NASA Astrophysics Data System (ADS)

Munzir, Said; Nasir, Muhammad; Ramli, Marwan

2018-01-01

Malaria is a disease caused by an amoeba (single-celled animal) type of plasmodium where anopheles mosquito serves as the carrier. This study examines the optimal control problem of malaria disease spread based on Aron and May (1982) SIR type models and seeks the optimal solution by minimizing the prevention of the spreading of malaria by vaccine. The aim is to investigate optimal control strategies on preventing the spread of malaria by vaccination. The problem in this research is solved using analytical approach. The analytical method uses the Pontryagin Minimum Principle with the symbolic help of MATLAB software to obtain optimal control result and to analyse the spread of malaria with vaccination control.

Optimal Battery Charging, Part 1: Minimizing Time-to-Charge, Energy Loss, and Temperature Rise for OCV-Resistance Battery Model

DTIC Science & Technology

2015-02-18

vi½k ¼ 0 (17) l½k ¼ vH½k vs ½k (18) s½kþ 1 ¼ vH½k vl½kþ 1 (19) From (17) we have i½k ¼ chl½kþ 1 2R0D k ¼ 0;1;…k1 1 (20) From (18), we...resistance R0 in model I. The batteries are Samsung EB575152 (four cells), Samsung EB504465 (four cells), Samsung AB463651 (two cells), Nokia BP-4L (four cells...commercial batteries. Make Model Cell# R0 (mU) R1 (mU) C1 (F) a Cbatt (Ah) Samsung EB575152 1 253 106 4581 0.997934 1.1875 Samsung EB575152 2 209 94 5203

Single-cell-based computer simulation of the oxygen-dependent tumour response to irradiation

NASA Astrophysics Data System (ADS)

Harting, Christine; Peschke, Peter; Borkenstein, Klaus; Karger, Christian P.

2007-08-01

Optimization of treatment plans in radiotherapy requires the knowledge of tumour control probability (TCP) and normal tissue complication probability (NTCP). Mathematical models may help to obtain quantitative estimates of TCP and NTCP. A single-cell-based computer simulation model is presented, which simulates tumour growth and radiation response on the basis of the response of the constituting cells. The model contains oxic, hypoxic and necrotic tumour cells as well as capillary cells which are considered as sources of a radial oxygen profile. Survival of tumour cells is calculated by the linear quadratic model including the modified response due to the local oxygen concentration. The model additionally includes cell proliferation, hypoxia-induced angiogenesis, apoptosis and resorption of inactivated tumour cells. By selecting different degrees of angiogenesis, the model allows the simulation of oxic as well as hypoxic tumours having distinctly different oxygen distributions. The simulation model showed that poorly oxygenated tumours exhibit an increased radiation tolerance. Inter-tumoural variation of radiosensitivity flattens the dose response curve. This effect is enhanced by proliferation between fractions. Intra-tumoural radiosensitivity variation does not play a significant role. The model may contribute to the mechanistic understanding of the influence of biological tumour parameters on TCP. It can in principle be validated in radiation experiments with experimental tumours.

Immortalized endothelial cell lines for in vitro blood-brain barrier models: A systematic review.

PubMed

Rahman, Nurul Adhwa; Rasil, Alifah Nur'ain Haji Mat; Meyding-Lamade, Uta; Craemer, Eva Maria; Diah, Suwarni; Tuah, Ani Afiqah; Muharram, Siti Hanna

2016-07-01

Endothelial cells play the most important role in construction of the blood-brain barrier. Many studies have opted to use commercially available, easily transfected or immortalized endothelial cell lines as in vitro blood-brain barrier models. Numerous endothelial cell lines are available, but we do not currently have strong evidence for which cell lines are optimal for establishment of such models. This review aimed to investigate the application of immortalized endothelial cell lines as in vitro blood-brain barrier models. The databases used for this review were PubMed, OVID MEDLINE, ProQuest, ScienceDirect, and SpringerLink. A narrative systematic review was conducted and identified 155 studies. As a result, 36 immortalized endothelial cell lines of human, mouse, rat, porcine and bovine origins were found for the establishment of in vitro blood-brain barrier and brain endothelium models. This review provides a summary of immortalized endothelial cell lines as a guideline for future studies and improvements in the establishment of in vitro blood-brain barrier models. It is important to establish a good and reproducible model that has the potential for multiple applications, in particular a model of such a complex compartment such as the blood-brain barrier. Copyright © 2016 Elsevier B.V. All rights reserved.

Bayesian Integration of Information in Hippocampal Place Cells

PubMed Central

Madl, Tamas; Franklin, Stan; Chen, Ke; Montaldi, Daniela; Trappl, Robert

2014-01-01

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We compare the predictions of our model with physiological data from rats. Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters. PMID:24603429

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.

PubMed

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders' preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning.

PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

PubMed Central

Liu, Yaolin; Peng, Jinjin; Jiao, Limin; Liu, Yanfang

2016-01-01

Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases the economic benefits of land-use activities, and reduces the ecological risk of land-use planning. Most land-use optimization models allocate land-use using cell-level operations that fragment land-use patches. These models do not cooperate well with land-use planning knowledge, leading to irrational land-use patterns. This study focuses on building a heuristic land-use allocation model (PSOLA) using particle swarm optimization. The model allocates land-use with patch-level operations to avoid fragmentation. The patch-level operations include a patch-edge operator, a patch-size operator, and a patch-compactness operator that constrain the size and shape of land-use patches. The model is also integrated with knowledge-informed rules to provide auxiliary knowledge of land-use planning during optimization. The knowledge-informed rules consist of suitability, accessibility, land use policy, and stakeholders’ preference. To validate the PSOLA model, a case study was performed in Gaoqiao Town in Zhejiang Province, China. The results demonstrate that the PSOLA model outperforms a basic PSO (Particle Swarm Optimization) in the terms of the social, economic, ecological, and overall benefits by 3.60%, 7.10%, 1.53% and 4.06%, respectively, which confirms the effectiveness of our improvements. Furthermore, the model has an open architecture, enabling its extension as a generic tool to support decision making in land-use planning. PMID:27322619

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose

PubMed Central

Lever, Melissa; Lim, Hong-Sheng; Kruger, Philipp; Nguyen, John; Trendel, Nicola; Abu-Shah, Enas; Maini, Philip Kumar; van der Merwe, Philip Anton

2016-01-01

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose–response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways. PMID:27702900

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose.

PubMed

Lever, Melissa; Lim, Hong-Sheng; Kruger, Philipp; Nguyen, John; Trendel, Nicola; Abu-Shah, Enas; Maini, Philip Kumar; van der Merwe, Philip Anton; Dushek, Omer

2016-10-25

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways.

Inactivation disinfection property of Moringa Oleifera seed extract: optimization and kinetic studies

NASA Astrophysics Data System (ADS)

Idris, M. A.; Jami, M. S.; Hammed, A. M.

2017-05-01

This paper presents the statistical optimization study of disinfection inactivation parameters of defatted Moringa oleifera seed extract on Pseudomonas aeruginosa bacterial cells. Three level factorial design was used to estimate the optimum range and the kinetics of the inactivation process was also carried. The inactivation process involved comparing different disinfection models of Chicks-Watson, Collins-Selleck and Homs models. The results from analysis of variance (ANOVA) of the statistical optimization process revealed that only contact time was significant. The optimum disinfection range of the seed extract was 125 mg/L, 30 minutes and 120rpm agitation. At the optimum dose, the inactivation kinetics followed the Collin-Selleck model with coefficient of determination (R2) of 0.6320. This study is the first of its kind in determining the inactivation kinetics of pseudomonas aeruginosa using the defatted seed extract.

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.

Modeling and Optimization of Commercial Buildings and Stationary Fuel Cell Systems (Presentation)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ainscough, C.; McLarty, D.; Sullivan, R.

2013-10-01

This presentation describes the Distributed Generation Building Energy Assessment Tool (DG-BEAT) developed by the National Renewable Energy Laboratory and the University of California Irvine. DG-BEAT is designed to allow stakeholders to assess the economics of installing stationary fuel cell systems in a variety of building types in the United States.

Efficient SRAM yield optimization with mixture surrogate modeling

NASA Astrophysics Data System (ADS)

Zhongjian, Jiang; Zuochang, Ye; Yan, Wang

2016-12-01

Largely repeated cells such as SRAM cells usually require extremely low failure-rate to ensure a moderate chi yield. Though fast Monte Carlo methods such as importance sampling and its variants can be used for yield estimation, they are still very expensive if one needs to perform optimization based on such estimations. Typically the process of yield calculation requires a lot of SPICE simulation. The circuit SPICE simulation analysis accounted for the largest proportion of time in the process yield calculation. In the paper, a new method is proposed to address this issue. The key idea is to establish an efficient mixture surrogate model. The surrogate model is based on the design variables and process variables. This model construction method is based on the SPICE simulation to get a certain amount of sample points, these points are trained for mixture surrogate model by the lasso algorithm. Experimental results show that the proposed model is able to calculate accurate yield successfully and it brings significant speed ups to the calculation of failure rate. Based on the model, we made a further accelerated algorithm to further enhance the speed of the yield calculation. It is suitable for high-dimensional process variables and multi-performance applications.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

PubMed

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

A Motor-Gradient and Clustering Model of the Centripetal Motility of MTOCs in Meiosis I of Mouse Oocytes

PubMed Central

2016-01-01

Asters nucleated by Microtubule (MT) organizing centers (MTOCs) converge on chromosomes during spindle assembly in mouse oocytes undergoing meiosis I. Time-lapse imaging suggests that this centripetal motion is driven by a biased ‘search-and-capture’ mechanism. Here, we develop a model of a random walk in a drift field to test the nature of the bias and the spatio-temporal dynamics of the search process. The model is used to optimize the spatial field of drift in simulations, by comparison to experimental motility statistics. In a second step, this optimized gradient is used to determine the location of immobilized dynein motors and MT polymerization parameters, since these are hypothesized to generate the gradient of forces needed to move MTOCs. We compare these scenarios to self-organized mechanisms by which asters have been hypothesized to find the cell-center- MT pushing at the cell-boundary and clustering motor complexes. By minimizing the error between simulation outputs and experiments, we find a model of “pulling” by a gradient of dynein motors alone can drive the centripetal motility. Interestingly, models of passive MT based “pushing” at the cortex, clustering by cross-linking motors and MT-dynamic instability gradients alone, by themselves do not result in the observed motility. The model predicts the sensitivity of the results to motor density and stall force, but not MTs per aster. A hybrid model combining a chromatin-centered immobilized dynein gradient, diffusible minus-end directed clustering motors and pushing at the cell cortex, is required to comprehensively explain the available data. The model makes experimentally testable predictions of a spatial bias and self-organized mechanisms by which MT asters can find the center of a large cell. PMID:27706163

A Motor-Gradient and Clustering Model of the Centripetal Motility of MTOCs in Meiosis I of Mouse Oocytes.

PubMed

Khetan, Neha; Athale, Chaitanya A

2016-10-01

Asters nucleated by Microtubule (MT) organizing centers (MTOCs) converge on chromosomes during spindle assembly in mouse oocytes undergoing meiosis I. Time-lapse imaging suggests that this centripetal motion is driven by a biased 'search-and-capture' mechanism. Here, we develop a model of a random walk in a drift field to test the nature of the bias and the spatio-temporal dynamics of the search process. The model is used to optimize the spatial field of drift in simulations, by comparison to experimental motility statistics. In a second step, this optimized gradient is used to determine the location of immobilized dynein motors and MT polymerization parameters, since these are hypothesized to generate the gradient of forces needed to move MTOCs. We compare these scenarios to self-organized mechanisms by which asters have been hypothesized to find the cell-center- MT pushing at the cell-boundary and clustering motor complexes. By minimizing the error between simulation outputs and experiments, we find a model of "pulling" by a gradient of dynein motors alone can drive the centripetal motility. Interestingly, models of passive MT based "pushing" at the cortex, clustering by cross-linking motors and MT-dynamic instability gradients alone, by themselves do not result in the observed motility. The model predicts the sensitivity of the results to motor density and stall force, but not MTs per aster. A hybrid model combining a chromatin-centered immobilized dynein gradient, diffusible minus-end directed clustering motors and pushing at the cell cortex, is required to comprehensively explain the available data. The model makes experimentally testable predictions of a spatial bias and self-organized mechanisms by which MT asters can find the center of a large cell.

Insolation-oriented model of photovoltaic module using Matlab/Simulink

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, Huan-Liang

2010-07-15

This paper presents a novel model of photovoltaic (PV) module which is implemented and analyzed using Matlab/Simulink software package. Taking the effect of sunlight irradiance on the cell temperature, the proposed model takes ambient temperature as reference input and uses the solar insolation as a unique varying parameter. The cell temperature is then explicitly affected by the sunlight intensity. The output current and power characteristics are simulated and analyzed using the proposed PV model. The model verification has been confirmed through an experimental measurement. The impact of solar irradiation on cell temperature makes the output characteristic more practical. In addition,more » the insolation-oriented PV model enables the dynamics of PV power system to be analyzed and optimized more easily by applying the environmental parameters of ambient temperature and solar irradiance. (author)« less

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-01

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation.

PubMed

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-14

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

Current Technologies Based on the Knowledge of the Stem Cells Microenvironments.

PubMed

Mawad, Damia; Figtree, Gemma; Gentile, Carmine

2017-01-01

The stem cell microenvironment or niche plays a critical role in the regulation of survival, differentiation and behavior of stem cells and their progenies. Recapitulating each aspect of the stem cell niche is therefore essential for their optimal use in in vitro studies and in vivo as future therapeutics in humans. Engineering of optimal conditions for three-dimensional stem cell culture includes multiple transient and dynamic physiological stimuli, such as blood flow and tissue stiffness. Bioprinting and microfluidics technologies, including organs-on-a-chip, are among the most recent approaches utilized to replicate the three-dimensional stem cell niche for human tissue fabrication that allow the integration of multiple levels of tissue complexity, including blood flow. This chapter focuses on the physico-chemical and genetic cues utilized to engineer the stem cell niche and provides an overview on how both bioprinting and microfluidics technologies are improving our knowledge in this field for both disease modeling and tissue regeneration, including drug discovery and toxicity high-throughput assays and stem cell-based therapies in humans.

A kinetic investigation of interacting, stimulated T cells identifies conditions for rapid functional enhancement, minimal phenotype differentiation, and improved adoptive cell transfer tumor eradication.

PubMed

Zhou, Jing; Bethune, Michael T; Malkova, Natalia; Sutherland, Alexander M; Comin-Anduix, Begonya; Su, Yapeng; Baltimore, David; Ribas, Antoni; Heath, James R

2018-01-01

For adoptive cell transfer (ACT) immunotherapy of tumor-reactive T cells, an effective therapeutic outcome depends upon cell dose, cell expansion in vivo through a minimally differentiated phenotype, long term persistence, and strong cytolytic effector function. An incomplete understanding of the biological coupling between T cell expansion, differentiation, and response to stimulation hinders the co-optimization of these factors. We report on a biophysical investigation of how the short-term kinetics of T cell functional activation, through molecular stimulation and cell-cell interactions, competes with phenotype differentiation. T cells receive molecular stimulation for a few minutes to a few hours in bulk culture. Following this priming period, the cells are then analyzed at the transcriptional level, or isolated as single cells, with continuing molecular stimulation, within microchambers for analysis via 11-plex secreted protein assays. We resolve a rapid feedback mechanism, promoted by T cell-T cell contact interactions, which strongly amplifies T cell functional performance while yielding only minimal phenotype differentiation. When tested in mouse models of ACT, optimally primed T cells lead to complete tumor eradication. A similar kinetic process is identified in CD8+ and CD4+ T cells collected from a patient with metastatic melanoma.

Autonomous Bacterial Localization and Gene Expression Based on Nearby Cell Receptor Density

DTIC Science & Technology

2013-01-22

synthesis of novel products (Kwok, 2010). In such cases, cell populations are aligned for optimal production . While Nature’s biosynthetic toolbox is vast...less commonly examined but equally innovative strategy envisions a repro- grammed cell itself or small collections of cells as the end products of...to surfaces. In Figure 2B, we depict the level of NF binding and AI-2 production as a function of coated avidin. We used a mathematical model for E

Optimization of IL13Rα2-Targeted Chimeric Antigen Receptor T Cells for Improved Anti-tumor Efficacy against Glioblastoma.

PubMed

Brown, Christine E; Aguilar, Brenda; Starr, Renate; Yang, Xin; Chang, Wen-Chung; Weng, Lihong; Chang, Brenda; Sarkissian, Aniee; Brito, Alfonso; Sanchez, James F; Ostberg, Julie R; D'Apuzzo, Massimo; Badie, Behnam; Barish, Michael E; Forman, Stephen J

2018-01-03

T cell immunotherapy is emerging as a powerful strategy to treat cancer and may improve outcomes for patients with glioblastoma (GBM). We have developed a chimeric antigen receptor (CAR) T cell immunotherapy targeting IL-13 receptor α2 (IL13Rα2) for the treatment of GBM. Here, we describe the optimization of IL13Rα2-targeted CAR T cells, including the design of a 4-1BB (CD137) co-stimulatory CAR (IL13BBζ) and a manufacturing platform using enriched central memory T cells. Utilizing orthotopic human GBM models with patient-derived tumor sphere lines in NSG mice, we found that IL13BBζ-CAR T cells improved anti-tumor activity and T cell persistence as compared to first-generation IL13ζ-CAR CD8 + T cells that had shown evidence for bioactivity in patients. Investigating the impact of corticosteroids, given their frequent use in the clinical management of GBM, we demonstrate that low-dose dexamethasone does not diminish CAR T cell anti-tumor activity in vivo. Furthermore, we found that local intracranial delivery of CAR T cells elicits superior anti-tumor efficacy as compared to intravenous administration, with intraventricular infusions exhibiting possible benefit over intracranial tumor infusions in a multifocal disease model. Overall, these findings help define parameters for the clinical translation of CAR T cell therapy for the treatment of brain tumors. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Enhancement of photovoltaic cell performance using periodic triangular gratings

NASA Astrophysics Data System (ADS)

Bordatchev, Evgueni; Tauhiduzzaman, Mohammed; Dey, Rajat

2014-01-01

The solar energy industry strives to produce more efficient and yet cost effective solar panels each consisting of an array of photovoltaic (PV) cells. The goal of this study was to enhance the performance of PV cells through increasing the cells' optical efficiency defined as a percentage of surface incident light that reaches the PV material. This was achieved through the reduction of waveguide decoupling loss and Fresnel reflection losses by integrating specific nonimaging micro-optical structures on the top surface of existing PV cells. Due to this integration, optical efficiency and performance were increased through the enhancement of light trapping, light guiding, and in-coupling functionalities. Periodic triangular gratings (PTGs) were designed, nonsequentially modeled, optimized, and fabricated in polydimethylsiloxane as proposed micro-optical structures. Then the performance of PV cells with and without integrated PTGs was evaluated and compared. Initial optical simulation results show that an original PV cell (without PTG) exhibits an average optical efficiency of 32.7% over a range of incident light angles between 15 and 90 deg. Integration of the PTG allows the capture of incoming sunlight by total internal reflection (TIR), whence it is reflected back onto the PV cell for multiple consecutive chances for absorption and PV conversion. Geometry of the PTG was optimized with respect to an angle of light incidence of {15, 30, 45, 60, 75, 90} deg. Optical efficiency of the geometrically optimized PTGs was then analyzed under the same set of incident light angles and a maximum optical efficiency of 54.1% was observed for a PV cell with integrated PTG optimized at 90 deg. This is a 53.3% relative improvement in optical performance when compared to an original PV cell. Functional PTG prototypes were then fabricated with optical surface quality (below 10 nm Ra) and integrated with PV cells demonstrating an increase in maximum power by 1.08 mW/cm (7.6% improvement in PV performance) and in short circuit current by 2.39 mA/cm (6.4% improvement).

Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor.

PubMed

Loomba, Varun; Huber, Gregor; von Lieres, Eric

2018-01-01

Flat-panel photo-bioreactors (PBRs) are customarily applied for investigating growth of microalgae. Optimal design and operation of such reactors is still a challenge due to complex non-linear combinations of various impact factors, particularly hydrodynamics, light irradiation, and cell metabolism. A detailed analysis of single-cell light reception can lead to novel insights into the complex interactions of light exposure and algae movement in the reactor. The combined impacts of hydrodynamics and light irradiation on algae cultivation in a flat-panel PBR were studied by tracing the light exposure of individual cells over time. Hydrodynamics and turbulent mixing in this air-sparged bioreactor were simulated using the Eulerian approach for the liquid phase and a slip model for the gas phase velocity profiles. The liquid velocity was then used for tracing single cells and their light exposure, using light intensity profiles obtained from solving the radiative transfer equation at different wavelengths. The residence times of algae cells in defined dark and light zones of the PBR were statistically analyzed for different algal concentrations and sparging rates. The results indicate poor mixing caused by the reactor design which can be only partially improved by increased sparging rates. The results provide important information for optimizing algal biomass productivity by improving bioreactor design and operation and can further be utilized for an in-depth analysis of algal growth by using advanced models of cell metabolism.

Modeling OPC complexity for design for manufacturability

NASA Astrophysics Data System (ADS)

Gupta, Puneet; Kahng, Andrew B.; Muddu, Swamy; Nakagawa, Sam; Park, Chul-Hong

2005-11-01

Increasing design complexity in sub-90nm designs results in increased mask complexity and cost. Resolution enhancement techniques (RET) such as assist feature addition, phase shifting (attenuated PSM) and aggressive optical proximity correction (OPC) help in preserving feature fidelity in silicon but increase mask complexity and cost. Data volume increase with rise in mask complexity is becoming prohibitive for manufacturing. Mask cost is determined by mask write time and mask inspection time, which are directly related to the complexity of features printed on the mask. Aggressive RET increase complexity by adding assist features and by modifying existing features. Passing design intent to OPC has been identified as a solution for reducing mask complexity and cost in several recent works. The goal of design-aware OPC is to relax OPC tolerances of layout features to minimize mask cost, without sacrificing parametric yield. To convey optimal OPC tolerances for manufacturing, design optimization should drive OPC tolerance optimization using models of mask cost for devices and wires. Design optimization should be aware of impact of OPC correction levels on mask cost and performance of the design. This work introduces mask cost characterization (MCC) that quantifies OPC complexity, measured in terms of fracture count of the mask, for different OPC tolerances. MCC with different OPC tolerances is a critical step in linking design and manufacturing. In this paper, we present a MCC methodology that provides models of fracture count of standard cells and wire patterns for use in design optimization. MCC cannot be performed by designers as they do not have access to foundry OPC recipes and RET tools. To build a fracture count model, we perform OPC and fracturing on a limited set of standard cells and wire configurations with all tolerance combinations. Separately, we identify the characteristics of the layout that impact fracture count. Based on the fracture count (FC) data from OPC and mask data preparation runs, we build models of FC as function of OPC tolerances and layout parameters.

Copy number variants calling for single cell sequencing data by multi-constrained optimization.

PubMed

Xu, Bo; Cai, Hongmin; Zhang, Changsheng; Yang, Xi; Han, Guoqiang

2016-08-01

Variations in DNA copy number carry important information on genome evolution and regulation of DNA replication in cancer cells. The rapid development of single-cell sequencing technology allows one to explore gene expression heterogeneity among single-cells, thus providing important cancer cell evolution information. Single-cell DNA/RNA sequencing data usually have low genome coverage, which requires an extra step of amplification to accumulate enough samples. However, such amplification will introduce large bias and makes bioinformatics analysis challenging. Accurately modeling the distribution of sequencing data and effectively suppressing the bias influence is the key to success variations analysis. Recent advances demonstrate the technical noises by amplification are more likely to follow negative binomial distribution, a special case of Poisson distribution. Thus, we tackle the problem CNV detection by formulating it into a quadratic optimization problem involving two constraints, in which the underling signals are corrupted by Poisson distributed noises. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signals from single-cell sequencing data are anticipated to fit the CNVs patterns more accurately. An efficient numerical solution based on the classical alternating direction minimization method (ADMM) is tailored to solve the proposed model. We demonstrate the advantages of the proposed method using both synthetic and empirical single-cell sequencing data. Our experimental results demonstrate that the proposed method achieves excellent performance and high promise of success with single-cell sequencing data. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Kinetic models in industrial biotechnology - Improving cell factory performance.

PubMed

Almquist, Joachim; Cvijovic, Marija; Hatzimanikatis, Vassily; Nielsen, Jens; Jirstrand, Mats

2014-07-01

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

A kinetic investigation of interacting, stimulated T cells identifies conditions for rapid functional enhancement, minimal phenotype differentiation, and improved adoptive cell transfer tumor eradication

PubMed Central

Zhou, Jing; Bethune, Michael T.; Malkova, Natalia; Sutherland, Alexander M.; Comin-Anduix, Begonya; Su, Yapeng; Baltimore, David; Ribas, Antoni

2018-01-01

For adoptive cell transfer (ACT) immunotherapy of tumor-reactive T cells, an effective therapeutic outcome depends upon cell dose, cell expansion in vivo through a minimally differentiated phenotype, long term persistence, and strong cytolytic effector function. An incomplete understanding of the biological coupling between T cell expansion, differentiation, and response to stimulation hinders the co-optimization of these factors. We report on a biophysical investigation of how the short-term kinetics of T cell functional activation, through molecular stimulation and cell-cell interactions, competes with phenotype differentiation. T cells receive molecular stimulation for a few minutes to a few hours in bulk culture. Following this priming period, the cells are then analyzed at the transcriptional level, or isolated as single cells, with continuing molecular stimulation, within microchambers for analysis via 11-plex secreted protein assays. We resolve a rapid feedback mechanism, promoted by T cell—T cell contact interactions, which strongly amplifies T cell functional performance while yielding only minimal phenotype differentiation. When tested in mouse models of ACT, optimally primed T cells lead to complete tumor eradication. A similar kinetic process is identified in CD8+ and CD4+ T cells collected from a patient with metastatic melanoma. PMID:29360859

Microfluidic cell disruption system employing a magnetically actuated diaphragm.

PubMed

Huh, Yun Suk; Choi, Jong Hyun; Huh, Kyoung Ae Kim; Kim, Kyoung Ae; Park, Tae Jung; Hong, Yeon Ki; Kim, Do Hyun; Hong, Won Hi; Lee, Sang Yup

2007-12-01

A microfluidic cell lysis chip equipped with a micromixer and SPE unit was developed and used for quantitative analysis of intracellular proteins. This miniaturized sample preparation system can be employed for any purpose where cell disruption is needed to obtain intracellular constituents for the subsequent analysis. This system comprises a magnetically actuated micromixer to disrupt cells, a hydrophobic valve to manipulate the cell lysate, and a packed porous polymerized monolith chamber for SPE and filtering debris from the cell lysate. Using recombinant Escherichia coli expressing intracellular enhanced green fluorescent protein (EGFP) and lipase as model bacteria, we optimized the cell disruption condition with respect to the lysis buffer composition, mixing time, and the frequency of the diaphragm in the micromixer, which was magnetically actuated by an external magnetic stirrer in the micromixer chamber. The lysed sample prepared under the optimal condition was purified by the packed SPE in the microfluidic chip. At a frequency of 1.96 Hz, the final cell lysis efficiency and relative fluorescence intensity of EGFP after the cell disruption process were greater than 90 and 94%, respectively. Thus, this microfluidic cell disruption chip can be used for the efficient lysis of cells for further analysis of intracellular contents in many applications.

In vitro reconstruction of branched tubular structures from lung epithelial cells in high cell concentration gradient environment.

PubMed

Hagiwara, Masaya; Peng, Fei; Ho, Chih-Ming

2015-01-27

We have succeeded in developing hollow branching structure in vitro commonly observed in lung airway using primary lung airway epithelial cells. Cell concentration gradient is the key factor that determines production of the branching cellular structures, as optimization of this component removes the need for heterotypic culture. The higher cell concentration leads to the more production of morphogens and increases the growth rate of cells. However, homogeneous high cell concentration does not make a branching structure. Branching requires sufficient space in which cells can grow from a high concentration toward a low concentration. Simulation performed using a reaction-diffusion model revealed that long-range inhibition prevents cells from branching when they are homogeneously spread in culture environments, while short-range activation from neighboring cells leads to positive feedback. Thus, a high cell concentration gradient is required to make branching structures. Spatial distributions of morphogens, such as BMP-4, play important roles in the pattern formation. This simple yet robust system provides an optimal platform for the further study and understanding of branching mechanisms in the lung airway, and will facilitate chemical and genetic studies of lung morphogenesis programs.

Numerical algebraic geometry for model selection and its application to the life sciences

PubMed Central

Gross, Elizabeth; Davis, Brent; Ho, Kenneth L.; Bates, Daniel J.

2016-01-01

Researchers working with mathematical models are often confronted by the related problems of parameter estimation, model validation and model selection. These are all optimization problems, well known to be challenging due to nonlinearity, non-convexity and multiple local optima. Furthermore, the challenges are compounded when only partial data are available. Here, we consider polynomial models (e.g. mass-action chemical reaction networks at steady state) and describe a framework for their analysis based on optimization using numerical algebraic geometry. Specifically, we use probability-one polynomial homotopy continuation methods to compute all critical points of the objective function, then filter to recover the global optima. Our approach exploits the geometrical structures relating models and data, and we demonstrate its utility on examples from cell signalling, synthetic biology and epidemiology. PMID:27733697

Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

NASA Astrophysics Data System (ADS)

Sieniutycz, Stanislaw

2010-03-01

We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

NASA Astrophysics Data System (ADS)

Kumar, S.; Singh, A.; Dhar, A.

2017-08-01

The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.

Temperature and pH Conditions That Prevail during Fermentation of Sausages Are Optimal for Production of the Antilisterial Bacteriocin Sakacin K

PubMed Central

Leroy, Frédéric; de Vuyst, Luc

1999-01-01

Sakacin K is an antilisterial bacteriocin produced by Lactobacillus sake CTC 494, a strain isolated from Spanish dry fermented sausages. The biokinetics of cell growth and bacteriocin production of L. sake CTC 494 in vitro during laboratory fermentations were investigated by making use of MRS broth. The data obtained from the fermentations was used to set up a predictive model to describe the influence of the physical factors temperature and pH on microbial behavior. The model was validated successfully for all components. However, the specific bacteriocin production rate seemed to have an upper limit. Both cell growth and bacteriocin activity were very much influenced by changes in temperature and pH. The production of biomass was closely related to bacteriocin activity, indicating primary metabolite kinetics, but was not the only factor of importance. Acidity dramatically influenced both the production and the inactivation of sakacin K; the optimal pH for cell growth did not correspond to the pH for maximal sakacin K activity. Furthermore, cells grew well at 35°C but no bacteriocin production could be detected at this temperature. L. sake CTC 494 shows special promise for implementation as a novel bacteriocin-producing sausage starter culture with antilisterial properties, considering the fact that the temperature and acidity conditions that prevail during the fermentation process of dry fermented sausages are optimal for the production of sakacin K. PMID:10049850

Use of Adipose Derived Stem Cells to Treat Large Bone Defects. Addendum

DTIC Science & Technology

2009-07-01

optimal delivery . We have also completed characterization of our segmental defect model, including analysis of vascular ingrowth during defect healing...cells seeded in 1.2% Keltone alginate at a density of 12-15x106cells/ml were loaded on 24-well transwell insert membranes [6]. Once hydrogel discs...process from tissue culture plates and hydrogels does not alter the surface phenotype. Gene expression of surface markers and proteins associated with

Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, J.

2017-12-01

Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

Effect of Grain Boundaries on the Performance of Thin-Film-Based Polycrystalline Silicon Solar Cells: A Numerical Modeling

NASA Astrophysics Data System (ADS)

Chhetri, Nikita; Chatterjee, Somenath

2018-01-01

Solar cells/photovoltaic, a renewable energy source, is appraised to be the most effective alternative to the conventional electrical energy generator. A cost-effective alternative of crystalline wafer-based solar cell is thin-film polycrystalline-based solar cell. This paper reports the numerical analysis of dependency of the solar cell parameters (i.e., efficiency, fill factor, open-circuit voltage and short-circuit current density) on grain size for thin-film-based polycrystalline silicon (Si) solar cells. A minority carrier lifetime model is proposed to do a correlation between the grains, grain boundaries and lifetime for thin-film-based polycrystalline Si solar cells in MATLAB environment. As observed, the increment in the grain size diameter results in increase in minority carrier lifetime in polycrystalline Si thin film. A non-equivalent series resistance double-diode model is used to find the dark as well as light (AM1.5) current-voltage (I-V) characteristics for thin-film-based polycrystalline Si solar cells. To optimize the effectiveness of the proposed model, a successive approximation method is used and the corresponding fitting parameters are obtained. The model is validated with the experimentally obtained results reported elsewhere. The experimentally reported solar cell parameters can be found using the proposed model described here.

CFD modeling of catheter-based Chemofilter device for filtering chemotherapy drugs from venous flow

NASA Astrophysics Data System (ADS)

Maani, Nazanin; Yee, Daryl; Nosonovsky, Michael; Greer, Julia; Hetts, Steven; Rayz, Vitaliy

2017-11-01

Purpose: Intra-arterial chemotherapy, a procedure where drugs are injected into arteries supplying a tumor, may cause systemic toxicity. The Chemofilter device, deployed in a vein downstream of the tumor, can chemically filter the excessive drugs from the circulation. In our study, CFD modeling of blood flow through the Chemofilter is used to optimize its hemodynamic performance. Methods:The Chemofilter consists of a porous membrane attached to a stent-like frame of the RX Accunet distal protection filters used for capturing blood clots. The membrane is formed by a lattice of symmetric micro-cells. This design provides a large surface area for the drug binding, and allows blood cells to pass through the lattice. A two-scale modeling approach is used, where the flow through individual micro-cells is simulated to determine the lattice permeability and then the entire device is modeled as a porous membrane. Results: The simulations detected regions of flow stagnation and recirculation caused by the membrane and its supporting frame. The effect of the membrane's leading angle on the velocity and pressure fields was determined. The device optimization will help the efficacy of drug absorption, while the risk of blood clotting reduces. NIH NCI R01CA194533.

Sponge-supported cultures of primary head and neck tumors for an optimized preclinical model.

PubMed

Dohmen, Amy J C; Sanders, Joyce; Canisius, Sander; Jordanova, Ekaterina S; Aalbersberg, Else A; van den Brekel, Michiel W M; Neefjes, Jacques; Zuur, Charlotte L

2018-05-18

Treatment of advanced head and neck cancer is associated with low survival, high toxicity and a widely divergent individual response. The sponge-gel-supported histoculture model was previously developed to serve as a preclinical model for predicting individual treatment responses. We aimed to optimize the sponge-gel-supported histoculture model and provide more insight in cell specific behaviour by evaluating the tumor and its microenvironment using immunohistochemistry. We collected fresh tumor biopsies from 72 untreated patients and cultured them for 7 days. Biopsies from 57 patients (79%) were successfully cultured and 1451 tumor fragments (95.4%) were evaluated. Fragments were scored for percentage of tumor, tumor viability and proliferation, EGF-receptor expression and presence of T-cells and macrophages. Median tumor percentage increased from 53% at day 0 to 80% at day 7. Viability and proliferation decreased after 7 days, from 90% to 30% and from 30% to 10%, respectively. Addition of EGF, folic acid and hydrocortisone can lead to improved viability and proliferation, however this was not systematically observed. No patient subgroup could be identified with higher culture success rates. Immune cells were still present at day 7, illustrating that the tumor microenvironment is sustained. EGF supplementation did not increase viability and proliferation in patients overexpressing EGF-Receptor.

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Analytical optimal controls for the state constrained addition and removal of cryoprotective agents

PubMed Central

Chicone, Carmen C.; Critser, John K.

2014-01-01

Cryobiology is a field with enormous scientific, financial and even cultural impact. Successful cryopreservation of cells and tissues depends on the equilibration of these materials with high concentrations of permeating chemicals (CPAs) such as glycerol or 1,2 propylene glycol. Because cells and tissues are exposed to highly anisosmotic conditions, the resulting gradients cause large volume fluctuations that have been shown to damage cells and tissues. On the other hand, there is evidence that toxicity to these high levels of chemicals is time dependent, and therefore it is ideal to minimize exposure time as well. Because solute and solvent flux is governed by a system of ordinary differential equations, CPA addition and removal from cells is an ideal context for the application of optimal control theory. Recently, we presented a mathematical synthesis of the optimal controls for the ODE system commonly used in cryobiology in the absence of state constraints and showed that controls defined by this synthesis were optimal. Here we define the appropriate model, analytically extend the previous theory to one encompassing state constraints, and as an example apply this to the critical and clinically important cell type of human oocytes, where current methodologies are either difficult to implement or have very limited success rates. We show that an enormous increase in equilibration efficiency can be achieved under the new protocols when compared to classic protocols, potentially allowing a greatly increased survival rate for human oocytes, and pointing to a direction for the cryopreservation of many other cell types. PMID:22527943

Modeling and experimental methods to predict oxygen distribution in bone defects following cell transplantation.

PubMed

Heylman, Christopher M; Santoso, Sharon; Krebs, Melissa D; Saidel, Gerald M; Alsberg, Eben; Muschler, George F

2014-04-01

We have developed a mathematical model that allows simulation of oxygen distribution in a bone defect as a tool to explore the likely effects of local changes in cell concentration, defect size or geometry, local oxygen delivery with oxygen-generating biomaterials (OGBs), and changes in the rate of oxygen consumption by cells within a defect. Experimental data for the oxygen release rate from an OGB and the oxygen consumption rate of a transplanted cell population are incorporated into the model. With these data, model simulations allow prediction of spatiotemporal oxygen concentration within a given defect and the sensitivity of oxygen tension to changes in critical variables. This information may help to minimize the number of experiments in animal models that determine the optimal combinations of cells, scaffolds, and OGBs in the design of current and future bone regeneration strategies. Bone marrow-derived nucleated cell data suggest that oxygen consumption is dependent on oxygen concentration. OGB oxygen release is shown to be a time-dependent function that must be measured for accurate simulation. Simulations quantify the dependency of oxygen gradients in an avascular defect on cell concentration, cell oxygen consumption rate, OGB oxygen generation rate, and OGB geometry.

Transient stimulation expands superior antitumor T cells for adoptive therapy.

PubMed

Kagoya, Yuki; Nakatsugawa, Munehide; Ochi, Toshiki; Cen, Yuchen; Guo, Tingxi; Anczurowski, Mark; Saso, Kayoko; Butler, Marcus O; Hirano, Naoto

2017-01-26

Adoptive cell therapy is a potentially curative therapeutic approach for patients with cancer. In this treatment modality, antitumor T cells are exponentially expanded in vitro prior to infusion. Importantly, the results of recent clinical trials suggest that the quality of expanded T cells critically affects their therapeutic efficacy. Although anti-CD3 mAb-based stimulation is widely used to expand T cells in vitro, a protocol to generate T cell grafts for optimal adoptive therapy has yet to be established. In this study, we investigated the differences between T cell stimulation mediated by anti-CD3/CD28 mAb-coated beads and cell-based artificial antigen-presenting cells (aAPCs) expressing CD3/CD28 counter-receptors. We found that transient stimulation with cell-based aAPCs, but not prolonged stimulation with beads, resulted in the superior expansion of CD8 + T cells. Transiently stimulated CD8 + T cells maintained a stem cell-like memory phenotype and were capable of secreting multiple cytokines significantly more efficiently than chronically stimulated T cells. Importantly, the chimeric antigen receptor-engineered antitumor CD8 + T cells expanded via transient stimulation demonstrated superior persistence and antitumor responses in adoptive immunotherapy mouse models. These results suggest that restrained stimulation is critical for generating T cell grafts for optimal adoptive immunotherapy for cancer.

Simultaneous saccharification and bioethanol production from corn cobs: Process optimization and kinetic studies.

PubMed

Sewsynker-Sukai, Yeshona; Gueguim Kana, E B

2018-08-01

This study investigates the simultaneous saccharification and fermentation (SSF) process for bioethanol production from corn cobs with prehydrolysis (PSSF) and without prehydrolysis (OSSF). Two response surface models were developed with high coefficients of determination (>0.90). Process optimization gave high bioethanol concentrations and bioethanol conversions for the PSSF (36.92 ± 1.34 g/L and 62.36 ± 2.27%) and OSSF (35.04 ± 0.170 g/L and 58.13 ± 0.283%) models respectively. Additionally, the logistic and modified Gompertz models were used to study the kinetics of microbial cell growth and ethanol formation under microaerophilic and anaerobic conditions. Cell growth in the OSSF microaerophilic process gave the highest maximum specific growth rate (µ max ) of 0.274 h -1 . The PSSF microaerophilic bioprocess gave the highest potential maximum bioethanol concentration (P m ) (42.24 g/L). This study demonstrated that microaerophilic rather than anaerobic culture conditions enhanced cell growth and bioethanol production, and that additional prehydrolysis steps do not significantly impact on the bioethanol concentration and conversion in SSF process. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synthesis of MSnO{sub 3} (M = Ba, Sr) nanoparticles by reverse micelle method and particle size distribution analysis by whole powder pattern modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, Jahangeer; Blakely, Colin K.; Bruno, Shaun R.

2012-09-15

Highlights: ► BaSnO{sub 3} and SrSnO{sub 3} nanoparticles synthesized using the reverse micelle method. ► Particle size and size distribution studied by whole powder pattern modeling. ► Nanoparticles are of optimal size for investigation in dye-sensitized solar cells. -- Abstract: Light-to-electricity conversion efficiency in dye-sensitized solar cells critically depends not only on the dye molecule, semiconducting material and redox shuttle selection but also on the particle size and particle size distribution of the semiconducting photoanode. In this study, nanocrystalline BaSnO{sub 3} and SrSnO{sub 3} particles have been synthesized using the microemulsion method. Particle size distribution was studied by whole powdermore » pattern modeling which confirmed narrow particle size distribution with an average size of 18.4 ± 8.3 nm for SrSnO{sub 3} and 15.8 ± 4.2 nm for BaSnO{sub 3}. These values are in close agreement with results of transmission electron microscopy. The prepared materials have optimal microstructure for successive investigation in dye-sensitized solar cells.« less

Development of an in vitro skin sensitization test using human cell lines; human Cell Line Activation Test (h-CLAT). II. An inter-laboratory study of the h-CLAT.

PubMed

Sakaguchi, H; Ashikaga, T; Miyazawa, M; Yoshida, Y; Ito, Y; Yoneyama, K; Hirota, M; Itagaki, H; Toyoda, H; Suzuki, H

2006-08-01

Recent regulatory changes have placed a major emphasis on in vitro safety testing and alternative models. In regard to skin sensitization tests, dendritic cells (DCs) derived from human peripheral blood have been considered in the development of new in vitro alternatives. Human cell lines have been also reported recently. In our previous study, we suggested that measuring CD86 and/or CD54 expression on THP-1 cells (human monocytic leukemia cell line) could be used as an in vitro skin sensitization method. An inter-laboratory study among two laboratories was undertaken in Japan in order to further develop an in vitro skin sensitization model. In the present study, we used two human cell lines: THP-1 and U-937 (human histiocytic lymphoma cell line). First we optimized our test protocol (refer to the related paper entitled "optimization of the h-CLAT protocol" within this journal) and then we did an inter-laboratory validation with nine chemicals using the optimized protocol. We measured the expression of CD86 and CD54 on the above cells using flow cytometry after a 24h and 48h exposure to six known allergens (e.g., DNCB, pPD, NiSO(4)) and three non-allergens (e.g., SLS, tween 80). For the sample test concentration, four doses (0.1x, 0.5x, 1x, and 2x of the 50% inhibitory concentration (IC(50))) were evaluated. IC(50) was calculated using MTT assay. We found that allergens/non-allergens were better predicted using THP-1 cells compared to U-937 cells following a 24 h and a 48 h exposure. We also found that the 24h treatment time tended to have a better accuracy than the 48 h treatment time for THP-1 cells. Expression of CD86 and CD54 were good predictive markers for THP-1 cells, but for U-937 cells, expression of CD86 was a better predictor than CD54, at the 24h and the 48 h treatment time. The accuracy also improved when both markers (CD86 and CD54) were used as compared with a single marker for THP-1 cells. Both laboratories gave a good prediction of allergen/non-allergen, especially using THP-1 cells. These results suggest that our method, human Cell Line Activation Test (h-CLAT), using human cell lines THP-1 and U-937, but especially THP-1 cells at 24h treatment, may be a useful in vitro skin sensitization model to predict various contact allergens.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koizumi, Yoshiki; Nakajim, Syo; Ohash, Hirofumi

Cell culture study combing a mathematical model and computer simulation quantifies the anti-hepatitis C virus drug efficacy at any concentrations and any combinations in preclinical settings, and can obtain rich basic evidences for selecting optimal treatments prior to costly clinical trials.

Tumour-on-a-chip provides an optical window into nanoparticle tissue transport

NASA Astrophysics Data System (ADS)

Albanese, Alexandre; Lam, Alan K.; Sykes, Edward A.; Rocheleau, Jonathan V.; Chan, Warren C. W.

2013-10-01

Nanomaterials are used for numerous biomedical applications, but the selection of optimal properties for maximum delivery remains challenging. Thus, there is a significant interest in elucidating the nano-bio interactions underlying tissue accumulation. To date, researchers have relied on cell culture or animal models to study nano-bio interactions. However, cell cultures lack the complexity of biological tissues and animal models are prohibitively slow and expensive. Here we report a tumour-on-a-chip system where incorporation of tumour-like spheroids into a microfluidic channel permits real-time analysis of nanoparticle (NP) accumulation at physiological flow conditions. We show that penetration of NPs into the tissue is limited by their diameter and that retention can be improved by receptor targeting. NP transport is predominantly diffusion-limited with convection improving accumulation mostly at the tissue perimeter. A murine tumour model confirms these findings and demonstrates that the tumour-on-a-chip can be useful for screening optimal NP designs prior to in vivo studies.

Kinetics of biochemical sensing by single cells and populations of cells

NASA Astrophysics Data System (ADS)

Saakian, David B.

2017-10-01

We investigate the collective stationary sensing using N communicative cells, which involves surface receptors, diffusive signaling molecules, and cell-cell communication messengers. We restrict the scenarios to the signal-to-noise ratios (SNRs) for both strong communication and extrinsic noise only. We modified a previous model [Bialek and Setayeshgar, Proc. Natl. Acad. Sci. USA 102, 10040 (2005), 10.1073/pnas.0504321102] to eliminate the singularities in the fluctuation correlations by considering a uniform receptor distribution over the surface of each cell with a finite radius a . The modified model enables a simple and rigorous mathematical treatment of the collective sensing phenomenon. We then derive the scaling of the SNR for both juxtacrine and autocrine cases in all dimensions. For the optimal locations of the cells in the autocrine case, we find identical scaling for both two and three dimensions.

On the micro-indentation of plant cells in a tissue context

NASA Astrophysics Data System (ADS)

Mosca, Gabriella; Sapala, Aleksandra; Strauss, Soeren; Routier-Kierzkowska, Anne-Lise; Smith, Richard S.

2017-02-01

The effect of geometry on cell stiffness measured with micro-indentation techniques has been explored in single cells, however it is unclear if results on single cells can be readily transferred to indentation experiments performed on a tissue in vivo. Here we explored this question by using simulation models of osmotic treatments and micro-indentation experiments on 3D multicellular tissues with the finite element method. We found that the cellular context does affect measured cell stiffness, and that several cells of context in each direction are required for optimal results. We applied the model to micro-indentation data obtained with cellular force microscopy on the sepal of A. thaliana, and found that differences in measured stiffness could be explained by cellular geometry, and do not necessarily indicate differences in cell wall material properties or turgor pressure.

PD-1 or PD-L1 Blockade Restores Antitumor Efficacy Following SSX2 Epitope-Modified DNA Vaccine Immunization.

PubMed

Rekoske, Brian T; Smith, Heath A; Olson, Brian M; Maricque, Brett B; McNeel, Douglas G

2015-08-01

DNA vaccines have demonstrated antitumor efficacy in multiple preclinical models, but low immunogenicity has been observed in several human clinical trials. This has led to many approaches seeking to improve the immunogenicity of DNA vaccines. We previously reported that a DNA vaccine encoding the cancer-testis antigen SSX2, modified to encode altered epitopes with increased MHC class I affinity, elicited a greater frequency of cytolytic, multifunctional CD8(+) T cells in non-tumor-bearing mice. We sought to test whether this optimized vaccine resulted in increased antitumor activity in mice bearing an HLA-A2-expressing tumor engineered to express SSX2. We found that immunization of tumor-bearing mice with the optimized vaccine elicited a surprisingly inferior antitumor effect relative to the native vaccine. Both native and optimized vaccines led to increased expression of PD-L1 on tumor cells, but antigen-specific CD8(+) T cells from mice immunized with the optimized construct expressed higher PD-1. Splenocytes from immunized animals induced PD-L1 expression on tumor cells in vitro. Antitumor activity of the optimized vaccine could be increased when combined with antibodies blocking PD-1 or PD-L1, or by targeting a tumor line not expressing PD-L1. These findings suggest that vaccines aimed at eliciting effector CD8(+) T cells, and DNA vaccines in particular, might best be combined with PD-1 pathway inhibitors in clinical trials. This strategy may be particularly advantageous for vaccines targeting prostate cancer, a disease for which antitumor vaccines have demonstrated clinical benefit and yet PD-1 pathway inhibitors alone have shown little efficacy to date. ©2015 American Association for Cancer Research.

Computational analysis of integrated biosensing and shear flow in a microfluidic vascular model

NASA Astrophysics Data System (ADS)

Wong, Jeremy F.; Young, Edmond W. K.; Simmons, Craig A.

2017-11-01

Fluid flow and flow-induced shear stress are critical components of the vascular microenvironment commonly studied using microfluidic cell culture models. Microfluidic vascular models mimicking the physiological microenvironment also offer great potential for incorporating on-chip biomolecular detection. In spite of this potential, however, there are few examples of such functionality. Detection of biomolecules released by cells under flow-induced shear stress is a significant challenge due to severe sample dilution caused by the fluid flow used to generate the shear stress, frequently to the extent where the analyte is no longer detectable. In this work, we developed a computational model of a vascular microfluidic cell culture model that integrates physiological shear flow and on-chip monitoring of cell-secreted factors. Applicable to multilayer device configurations, the computational model was applied to a bilayer configuration, which has been used in numerous cell culture applications including vascular models. Guidelines were established that allow cells to be subjected to a wide range of physiological shear stress while ensuring optimal rapid transport of analyte to the biosensor surface and minimized biosensor response times. These guidelines therefore enable the development of microfluidic vascular models that integrate cell-secreted factor detection while addressing flow constraints imposed by physiological shear stress. Ultimately, this work will result in the addition of valuable functionality to microfluidic cell culture models that further fulfill their potential as labs-on-chips.

Transient stimulation expands superior antitumor T cells for adoptive therapy

PubMed Central

Kagoya, Yuki; Nakatsugawa, Munehide; Ochi, Toshiki; Guo, Tingxi; Anczurowski, Mark; Saso, Kayoko; Butler, Marcus O.

2017-01-01

Adoptive cell therapy is a potentially curative therapeutic approach for patients with cancer. In this treatment modality, antitumor T cells are exponentially expanded in vitro prior to infusion. Importantly, the results of recent clinical trials suggest that the quality of expanded T cells critically affects their therapeutic efficacy. Although anti-CD3 mAb-based stimulation is widely used to expand T cells in vitro, a protocol to generate T cell grafts for optimal adoptive therapy has yet to be established. In this study, we investigated the differences between T cell stimulation mediated by anti–CD3/CD28 mAb–coated beads and cell-based artificial antigen-presenting cells (aAPCs) expressing CD3/CD28 counter-receptors. We found that transient stimulation with cell-based aAPCs, but not prolonged stimulation with beads, resulted in the superior expansion of CD8+ T cells. Transiently stimulated CD8+ T cells maintained a stem cell–like memory phenotype and were capable of secreting multiple cytokines significantly more efficiently than chronically stimulated T cells. Importantly, the chimeric antigen receptor–engineered antitumor CD8+ T cells expanded via transient stimulation demonstrated superior persistence and antitumor responses in adoptive immunotherapy mouse models. These results suggest that restrained stimulation is critical for generating T cell grafts for optimal adoptive immunotherapy for cancer. PMID:28138559

Inverse approaches with lithologic information for a regional groundwater system in southwest Kansas

USGS Publications Warehouse

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.

Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features

PubMed Central

Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T.

2016-01-01

Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer’s disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may be useful for monitoring disease progression over time or evaluating therapeutic interventions. PMID:27445790

The role of backward cell migration in two-hit mutants' production in the stem cell niche.

PubMed

Bollas, Audrey; Shahriyari, Leili

2017-01-01

It has been discovered that there are two stem cell groups in the intestinal crypts: central stem cells (CeSCs), which are at the very bottom of the crypt, and border stem cells (BSCs), which are located between CeSCs and transit amplifying cells (TAs). Moreover, backward cell migration from BSCs to CeSCs has been observed. Recently, a bi-compartmental stochastic model, which includes CeSCs and BSCs, has been developed to investigate the probability of two-hit mutant production in the stem cell niche. In this project, we improve this stochastic model by adding the probability of backward cell migration to the model. The model suggests that the probability of two-hit mutant production increases when the frequency of backward cell migration increases. Furthermore, a small non-zero probability of backward cell migration leads to the largest range of optimal values for the frequency of symmetric divisions and the portion of divisions at each stem cell compartment in terms of delaying 2-hit mutant production. Moreover, the probability of two-hit mutant production is more sensitive to the probability of symmetric divisions than to the rate of backward cell migrations. The highest probability of two-hit mutant production corresponds to the case when all stem cell's divisions are asymmetric.

Modeling the Performance Limitations and Prospects of Perovskite/Si Tandem Solar Cells under Realistic Operating Conditions

PubMed Central

2017-01-01

Perovskite/Si tandem solar cells have the potential to considerably out-perform conventional solar cells. Under standard test conditions, perovskite/Si tandem solar cells already outperform the Si single junction. Under realistic conditions, however, as we show, tandem solar cells made from current record cells are hardly more efficient than the Si cell alone. We model the performance of realistic perovskite/Si tandem solar cells under real-world climate conditions, by incorporating parasitic cell resistances, nonradiative recombination, and optical losses into the detailed-balance limit. We show quantitatively that when optimizing these parameters in the perovskite top cell, perovskite/Si tandem solar cells could reach efficiencies above 38% under realistic conditions, even while leaving the Si cell untouched. Despite the rapid efficiency increase of perovskite solar cells, our results emphasize the need for further material development, careful device design, and light management strategies, all necessary for highly efficient perovskite/Si tandem solar cells. PMID:28920081

Modeling the Performance Limitations and Prospects of Perovskite/Si Tandem Solar Cells under Realistic Operating Conditions.

PubMed

Futscher, Moritz H; Ehrler, Bruno

2017-09-08

Perovskite/Si tandem solar cells have the potential to considerably out-perform conventional solar cells. Under standard test conditions, perovskite/Si tandem solar cells already outperform the Si single junction. Under realistic conditions, however, as we show, tandem solar cells made from current record cells are hardly more efficient than the Si cell alone. We model the performance of realistic perovskite/Si tandem solar cells under real-world climate conditions, by incorporating parasitic cell resistances, nonradiative recombination, and optical losses into the detailed-balance limit. We show quantitatively that when optimizing these parameters in the perovskite top cell, perovskite/Si tandem solar cells could reach efficiencies above 38% under realistic conditions, even while leaving the Si cell untouched. Despite the rapid efficiency increase of perovskite solar cells, our results emphasize the need for further material development, careful device design, and light management strategies, all necessary for highly efficient perovskite/Si tandem solar cells.

Surface-engineered substrates for improved human pluripotent stem cell culture under fully defined conditions.

PubMed

Saha, Krishanu; Mei, Ying; Reisterer, Colin M; Pyzocha, Neena Kenton; Yang, Jing; Muffat, Julien; Davies, Martyn C; Alexander, Morgan R; Langer, Robert; Anderson, Daniel G; Jaenisch, Rudolf

2011-11-15

The current gold standard for the culture of human pluripotent stem cells requires the use of a feeder layer of cells. Here, we develop a spatially defined culture system based on UV/ozone radiation modification of typical cell culture plastics to define a favorable surface environment for human pluripotent stem cell culture. Chemical and geometrical optimization of the surfaces enables control of early cell aggregation from fully dissociated cells, as predicted from a numerical model of cell migration, and results in significant increases in cell growth of undifferentiated cells. These chemically defined xeno-free substrates generate more than three times the number of cells than feeder-containing substrates per surface area. Further, reprogramming and typical gene-targeting protocols can be readily performed on these engineered surfaces. These substrates provide an attractive cell culture platform for the production of clinically relevant factor-free reprogrammed cells from patient tissue samples and facilitate the definition of standardized scale-up friendly methods for disease modeling and cell therapeutic applications.

Modelling breast cancer requires identification and correction of a critical cell lineage-dependent transduction bias

DOE PAGES

Hines, William C.; Yaswen, Paul; Bissell, Mina J.

2015-04-21

When trying to explore the biology and etiology of human cancers, clinically relevant human culture models are essential. Current breast tumour models, such as those from oncogenically transformed primary breast cells, produce predominantly basal-like properties, whereas the more common phenotype expressed by the vast majority of breast tumours are luminal. Reasons for this puzzling, yet important phenomenon, are not understood. We show here that luminal epithelial cells are significantly more resistant to viral transduction than their myoepithelial counterparts. Here, we suggest that this is a significant barrier to generating luminal cell lines and experimental tumours in vivo and to accuratemore » interpretation of results. We show that the resistance is due to lower affinity of luminal cells for virus attachment, which can be overcome by pretreating cells—or virus—with neuraminidase. We present an analytical method for quantifying transductional differences between cell types and an optimized protocol for transducing unsorted primary human breast cells in context.« less

Biomimicry of quorum sensing using bacterial lifecycle model.

PubMed

Niu, Ben; Wang, Hong; Duan, Qiqi; Li, Li

2013-01-01

Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems.

Biomimicry of quorum sensing using bacterial lifecycle model

PubMed Central

2013-01-01

Background Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. Results In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Conclusions Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms, which can be used for solving the real-world problems. PMID:23815296

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren, Emily L.; Deceglie, Michael G.; Stradins, Paul

Three-terminal (3T) tandem cells fabricated by combining an interdigitated back contact (IBC) Si device with a wider bandgap top cell have the potential to provide a robust operating mechanism to efficiently capture the solar spectrum without the need to current match sub-cells or fabricate complicated metal interconnects between cells. Here we develop a two dimensional device physics model to study the behavior of IBC Si solar cells operated in a 3T configuration. We investigate how different cell designs impact device performance and discuss the analysis protocol used to understand and optimize power produced from a single junction, 3T device.

Secreted HSP Vaccine for Malaria Prophylaxis

DTIC Science & Technology

2014-10-01

AWARD NUMBER: W81XWH-13-2-0098 TITLE: Secreted HSP Vaccine for Malaria Prophylaxis PRINCIPAL INVESTIGATOR: Dr. Eckhard R. Podack...model. 15. SUBJECT TERMS Malaria , Plasmodium Falciparum, circumsporozoite protein, apical membrane antigen-1, vaccine , heat shock proteins, gp96...approach to stimulate cytotoxic T cells against malaria antigens and investigate the optimal vaccination route to target these T cells to the liver. To

Optimization and critical evaluation of decellularization strategies to develop renal extracellular matrix scaffolds as biological templates for organ engineering and transplantation.

PubMed

Caralt, M; Uzarski, J S; Iacob, S; Obergfell, K P; Berg, N; Bijonowski, B M; Kiefer, K M; Ward, H H; Wandinger-Ness, A; Miller, W M; Zhang, Z J; Abecassis, M M; Wertheim, J A

2015-01-01

The ability to generate patient-specific cells through induced pluripotent stem cell (iPSC) technology has encouraged development of three-dimensional extracellular matrix (ECM) scaffolds as bioactive substrates for cell differentiation with the long-range goal of bioengineering organs for transplantation. Perfusion decellularization uses the vasculature to remove resident cells, leaving an intact ECM template wherein new cells grow; however, a rigorous evaluative framework assessing ECM structural and biochemical quality is lacking. To address this, we developed histologic scoring systems to quantify fundamental characteristics of decellularized rodent kidneys: ECM structure (tubules, vessels, glomeruli) and cell removal. We also assessed growth factor retention--indicating matrix biofunctionality. These scoring systems evaluated three strategies developed to decellularize kidneys (1% Triton X-100, 1% Triton X-100/0.1% sodium dodecyl sulfate (SDS) and 0.02% Trypsin-0.05% EGTA/1% Triton X-100). Triton and Triton/SDS preserved renal microarchitecture and retained matrix-bound basic fibroblast growth factor and vascular endothelial growth factor. Trypsin caused structural deterioration and growth factor loss. Triton/SDS-decellularized scaffolds maintained 3 h of leak-free blood flow in a rodent transplantation model and supported repopulation with human iPSC-derived endothelial cells and tubular epithelial cells ex vivo. Taken together, we identify an optimal Triton/SDS-based decellularization strategy that produces a biomatrix that may ultimately serve as a rodent model for kidney bioengineering. © Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.

Chronic behavior evaluation of a micro-machined neural implant with optimized design based on an experimentally derived model.

PubMed

Andrei, Alexandru; Welkenhuysen, Marleen; Ameye, Lieveke; Nuttin, Bart; Eberle, Wolfgang

2011-01-01

Understanding the mechanical interactions between implants and the surrounding tissue is known to have an important role for improving the bio-compatibility of such devices. Using a recently developed model, a particular micro-machined neural implant design aiming the reduction of insertion forces dependence on the insertion speed was optimized. Implantations with 10 and 100 μm/s insertion speeds showed excellent agreement with the predicted behavior. Lesion size, gliosis (GFAP), inflammation (ED1) and neuronal cells density (NeuN) was evaluated after 6 week of chronic implantation showing no insertion speed dependence.

Joint CPT and N resonance in compact atomic time standards

NASA Astrophysics Data System (ADS)

Crescimanno, Michael; Hohensee, Michael; Xiao, Yanhong; Phillips, David; Walsworth, Ron

2008-05-01

Currently development efforts towards small, low power atomic time standards use current-modulated VCSELs to generate phase-coherent optical sidebands that interrogate the hyperfine structure of alkali atoms such as rubidium. We describe and use a modified four-level quantum optics model to study the optimal operating regime of the joint CPT- and N-resonance clock. Resonant and non-resonant light shifts as well as modulation comb detuning effects play a key role in determining the optimal operating point of such clocks. We further show that our model is in good agreement with experimental tests performed using Rb-87 vapor cells.

Model-Based Analysis for Qualitative Data: An Application in Drosophila Germline Stem Cell Regulation

PubMed Central

Pargett, Michael; Rundell, Ann E.; Buzzard, Gregery T.; Umulis, David M.

2014-01-01

Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques. This is the case for stem cell regulation mechanisms explored in the Drosophila germarium through fluorescent immunohistochemistry. To enable better integration of biological data with modeling in this and similar situations, we have developed a general parameter estimation process to quantitatively optimize models with qualitative data. The process employs a modified version of the Optimal Scaling method from social and behavioral sciences, and multi-objective optimization to evaluate the trade-off between fitting different datasets (e.g. wild type vs. mutant). Using only published imaging data in the germarium, we first evaluated support for a published intracellular regulatory network by considering alternative connections of the same regulatory players. Simply screening networks against wild type data identified hundreds of feasible alternatives. Of these, five parsimonious variants were found and compared by multi-objective analysis including mutant data and dynamic constraints. With these data, the current model is supported over the alternatives, but support for a biochemically observed feedback element is weak (i.e. these data do not measure the feedback effect well). When also comparing new hypothetical models, the available data do not discriminate. To begin addressing the limitations in data, we performed a model-based experiment design and provide recommendations for experiments to refine model parameters and discriminate increasingly complex hypotheses. PMID:24626201

Convex reformulation of biologically-based multi-criteria intensity-modulated radiation therapy optimization including fractionation effects

NASA Astrophysics Data System (ADS)

Hoffmann, Aswin L.; den Hertog, Dick; Siem, Alex Y. D.; Kaanders, Johannes H. A. M.; Huizenga, Henk

2008-11-01

Finding fluence maps for intensity-modulated radiation therapy (IMRT) can be formulated as a multi-criteria optimization problem for which Pareto optimal treatment plans exist. To account for the dose-per-fraction effect of fractionated IMRT, it is desirable to exploit radiobiological treatment plan evaluation criteria based on the linear-quadratic (LQ) cell survival model as a means to balance the radiation benefits and risks in terms of biologic response. Unfortunately, the LQ-model-based radiobiological criteria are nonconvex functions, which make the optimization problem hard to solve. We apply the framework proposed by Romeijn et al (2004 Phys. Med. Biol. 49 1991-2013) to find transformations of LQ-model-based radiobiological functions and establish conditions under which transformed functions result in equivalent convex criteria that do not change the set of Pareto optimal treatment plans. The functions analysed are: the LQ-Poisson-based model for tumour control probability (TCP) with and without inter-patient heterogeneity in radiation sensitivity, the LQ-Poisson-based relative seriality s-model for normal tissue complication probability (NTCP), the equivalent uniform dose (EUD) under the LQ-Poisson model and the fractionation-corrected Probit-based model for NTCP according to Lyman, Kutcher and Burman. These functions differ from those analysed before in that they cannot be decomposed into elementary EUD or generalized-EUD functions. In addition, we show that applying increasing and concave transformations to the convexified functions is beneficial for the piecewise approximation of the Pareto efficient frontier.

Design and formulation of functional pluripotent stem cell-derived cardiac microtissues

PubMed Central

Thavandiran, Nimalan; Dubois, Nicole; Mikryukov, Alexander; Massé, Stéphane; Beca, Bogdan; Simmons, Craig A.; Deshpande, Vikram S.; McGarry, J. Patrick; Chen, Christopher S.; Nanthakumar, Kumaraswamy; Keller, Gordon M.; Radisic, Milica; Zandstra, Peter W.

2013-01-01

Access to robust and information-rich human cardiac tissue models would accelerate drug-based strategies for treating heart disease. Despite significant effort, the generation of high-fidelity adult-like human cardiac tissue analogs remains challenging. We used computational modeling of tissue contraction and assembly mechanics in conjunction with microfabricated constraints to guide the design of aligned and functional 3D human pluripotent stem cell (hPSC)-derived cardiac microtissues that we term cardiac microwires (CMWs). Miniaturization of the platform circumvented the need for tissue vascularization and enabled higher-throughput image-based analysis of CMW drug responsiveness. CMW tissue properties could be tuned using electromechanical stimuli and cell composition. Specifically, controlling self-assembly of 3D tissues in aligned collagen, and pacing with point stimulation electrodes, were found to promote cardiac maturation-associated gene expression and in vivo-like electrical signal propagation. Furthermore, screening a range of hPSC-derived cardiac cell ratios identified that 75% NKX2 Homeobox 5 (NKX2-5)+ cardiomyocytes and 25% Cluster of Differentiation 90 OR (CD90)+ nonmyocytes optimized tissue remodeling dynamics and yielded enhanced structural and functional properties. Finally, we demonstrate the utility of the optimized platform in a tachycardic model of arrhythmogenesis, an aspect of cardiac electrophysiology not previously recapitulated in 3D in vitro hPSC-derived cardiac microtissue models. The design criteria identified with our CMW platform should accelerate the development of predictive in vitro assays of human heart tissue function. PMID:24255110

The role of backward cell migration in two-hit mutants’ production in the stem cell niche

PubMed Central

Bollas, Audrey

2017-01-01

It has been discovered that there are two stem cell groups in the intestinal crypts: central stem cells (CeSCs), which are at the very bottom of the crypt, and border stem cells (BSCs), which are located between CeSCs and transit amplifying cells (TAs). Moreover, backward cell migration from BSCs to CeSCs has been observed. Recently, a bi-compartmental stochastic model, which includes CeSCs and BSCs, has been developed to investigate the probability of two-hit mutant production in the stem cell niche. In this project, we improve this stochastic model by adding the probability of backward cell migration to the model. The model suggests that the probability of two-hit mutant production increases when the frequency of backward cell migration increases. Furthermore, a small non-zero probability of backward cell migration leads to the largest range of optimal values for the frequency of symmetric divisions and the portion of divisions at each stem cell compartment in terms of delaying 2-hit mutant production. Moreover, the probability of two-hit mutant production is more sensitive to the probability of symmetric divisions than to the rate of backward cell migrations. The highest probability of two-hit mutant production corresponds to the case when all stem cell’s divisions are asymmetric. PMID:28931019

Cardiomyocytes from late embryos and neonates do optimal work and striate best on substrates with tissue-level elasticity: metrics and mathematics.

PubMed

Majkut, Stephanie F; Discher, Dennis E

2012-11-01

In this review, we discuss recent studies on the mechanosensitive morphology and function of cardiomyocytes derived from embryos and neonates. For early cardiomyocytes cultured on substrates of various stiffnesses, contractile function as measured by force production, work output and calcium handling is optimized when the culture substrate stiffness mimics that of the tissue from which the cells were obtained. This optimal contractile function corresponds to changes in sarcomeric protein conformation and organization that promote contractile ability. In light of current models for myofibillogenesis, a recent mathematical model of striation and alignment on elastic substrates helps to illuminate how substrate stiffness modulates early myofibril formation and organization. During embryonic heart formation and maturation, cardiac tissue mechanics change dynamically. Experiments and models highlighted here have important implications for understanding cardiomyocyte differentiation and function in development and perhaps in regeneration processes.

Heading-vector navigation based on head-direction cells and path integration.

PubMed

Kubie, John L; Fenton, André A

2009-05-01

Insect navigation is guided by heading vectors that are computed by path integration. Mammalian navigation models, on the other hand, are typically based on map-like place representations provided by hippocampal place cells. Such models compute optimal routes as a continuous series of locations that connect the current location to a goal. We propose a "heading-vector" model in which head-direction cells or their derivatives serve both as key elements in constructing the optimal route and as the straight-line guidance during route execution. The model is based on a memory structure termed the "shortcut matrix," which is constructed during the initial exploration of an environment when a set of shortcut vectors between sequential pairs of visited waypoint locations is stored. A mechanism is proposed for calculating and storing these vectors that relies on a hypothesized cell type termed an "accumulating head-direction cell." Following exploration, shortcut vectors connecting all pairs of waypoint locations are computed by vector arithmetic and stored in the shortcut matrix. On re-entry, when local view or place representations query the shortcut matrix with a current waypoint and goal, a shortcut trajectory is retrieved. Since the trajectory direction is in head-direction compass coordinates, navigation is accomplished by tracking the firing of head-direction cells that are tuned to the heading angle. Section 1 of the manuscript describes the properties of accumulating head-direction cells. It then shows how accumulating head-direction cells can store local vectors and perform vector arithmetic to perform path-integration-based homing. Section 2 describes the construction and use of the shortcut matrix for computing direct paths between any pair of locations that have been registered in the shortcut matrix. In the discussion, we analyze the advantages of heading-based navigation over map-based navigation. Finally, we survey behavioral evidence that nonhippocampal, heading-based navigation is used in small mammals and humans. Copyright 2008 Wiley-Liss, Inc.

Population PKPD modeling of BACE1 inhibitor-induced reduction in Aβ levels in vivo and correlation to in vitro potency in primary cortical neurons from mouse and guinea pig.

PubMed

Janson, Juliette; Eketjäll, Susanna; Tunblad, Karin; Jeppsson, Fredrik; Von Berg, Stefan; Niva, Camilla; Radesäter, Ann-Cathrin; Fälting, Johanna; Visser, Sandra A G

2014-03-01

The aims were to quantify the in vivo time-course between the oral dose, the plasma and brain exposure and the inhibitory effect on Amyloid β (Aβ) in brain and cerebrospinal fluid, and to establish the correlation between in vitro and in vivo potency of novel β-secretase (BACE1) inhibitors. BACE1-mediated inhibition of Aβ was quantified in in vivo dose- and/or time-response studies and in vitro in SH-SY5Y cells, N2A cells, and primary cortical neurons (PCN). An indirect response model with inhibition on Aβ production rate was used to estimate unbound in vivo IC 50 in a population pharmacokinetic-pharmacodynamic modeling approach. Estimated in vivo inhibitory potencies varied between 1 and 1,000 nM. The turnover half-life of Aβ40 in brain was predicted to be 0.5 h in mouse and 1 h in guinea pig. An excellent correlation between PCN and in vivo potency was observed. Moreover, a strong correlation in potency was found between human SH-SY5Y cells and mouse PCN, being 4.5-fold larger in SH-SY5Y cells. The strong in vivo-in vitro correlation increased the confidence in using human cell lines for screening and optimization of BACE1 inhibitors. This can optimize the design and reduce the number of preclinical in vivo effect studies.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of the failure constraints in the deterministic and reliability based optimization of the ITPS panel. It was shown that using adaptive sampling, the number of designs required to find the optimum were reduced drastically, while improving the accuracy. System reliability of ITPS was estimated using Monte Carlo Simulation (MCS) based method. Separable Monte Carlo method was employed that allowed separable sampling of the random variables to predict the probability of failure accurately. The reliability analysis considered uncertainties in the geometry, material properties, loading conditions of the panel and error in finite element modeling. These uncertainties further increased the computational cost of MCS techniques which was also reduced by employing surrogate models. In order to estimate the error in the probability of failure estimate, bootstrapping method was applied. This research work thus demonstrates optimization of the ITPS composite panel with multiple failure modes and large number of uncertainties using adaptive sampling techniques.

The relevance of human stem cell-derived organoid models for epithelial translational medicine

PubMed Central

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

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design

PubMed Central

Adesina, Simeon K.; Wight, Scott A.; Akala, Emmanuel O.

2015-01-01

Purpose Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize crosslinked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Methods Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Results and Conclusion Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the crosslinking agent and stabilizer indicate the important factors for minimizing particle size. PMID:24059281

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design.

PubMed

Adesina, Simeon K; Wight, Scott A; Akala, Emmanuel O

2014-11-01

Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize cross-linked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the cross-linking agent and stabilizer indicate the important factors for minimizing particle size.

Incorporating Resilience into Transportation Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Connelly, Elizabeth; Melaina, Marc

To aid decision making for developing transportation infrastructure, the National Renewable Energy Laboratory has developed the Scenario Evaluation, Regionalization and Analysis (SERA) model. The SERA model is a geospatially and temporally oriented model that has been applied to determine optimal production and delivery scenarios for hydrogen, given resource availability and technology cost and performance, for use in fuel cell vehicles. In addition, the SERA model has been applied to plug-in electric vehicles.

Mathematical modeling of vesicle drug delivery systems 2: targeted vesicle interactions with cells, tumors, and the body.

PubMed

Ying, Chong T; Wang, Juntian; Lamm, Robert J; Kamei, Daniel T

2013-02-01

Vesicles have been studied for several years in their ability to deliver drugs. Mathematical models have much potential in reducing time and resources required to engineer optimal vesicles, and this review article summarizes these models that aid in understanding the ability of targeted vesicles to bind and internalize into cancer cells, diffuse into tumors, and distribute in the body. With regard to binding and internalization, radiolabeling and surface plasmon resonance experiments can be performed to determine optimal vesicle size and the number and type of ligands conjugated. Binding and internalization properties are also inputs into a mathematical model of vesicle diffusion into tumor spheroids, which highlights the importance of the vesicle diffusion coefficient and the binding affinity of the targeting ligand. Biodistribution of vesicles in the body, along with their half-life, can be predicted with compartmental models for pharmacokinetics that include the effect of targeting ligands, and these predictions can be used in conjunction with in vivo models to aid in the design of drug carriers. Mathematical models can prove to be very useful in drug carrier design, and our hope is that this review will encourage more investigators to combine modeling with quantitative experimentation in the field of vesicle-based drug delivery.

Establishment of an immortalized mouse dermal papilla cell strain with optimized culture strategy.

PubMed

Guo, Haiying; Xing, Yizhan; Zhang, Yiming; He, Long; Deng, Fang; Ma, Xiaogen; Li, Yuhong

2018-01-01

Dermal papilla (DP) plays important roles in hair follicle regeneration. Long-term culture of mouse DP cells can provide enough cells for research and application of DP cells. We optimized the culture strategy for DP cells from three dimensions: stepwise dissection, collagen I coating, and optimized culture medium. Based on the optimized culture strategy, we immortalized primary DP cells with SV40 large T antigen, and established several immortalized DP cell strains. By comparing molecular expression and morphologic characteristics with primary DP cells, we found one cell strain named iDP6 was similar with primary DP cells. Further identifications illustrate that iDP6 expresses FGF7 and α-SMA, and has activity of alkaline phosphatase. During the process of characterization of immortalized DP cell strains, we also found that cells in DP were heterogeneous. We successfully optimized culture strategy for DP cells, and established an immortalized DP cell strain suitable for research and application of DP cells.

Establishment of an immortalized mouse dermal papilla cell strain with optimized culture strategy

PubMed Central

Zhang, Yiming; He, Long; Deng, Fang; Ma, Xiaogen

2018-01-01

Dermal papilla (DP) plays important roles in hair follicle regeneration. Long-term culture of mouse DP cells can provide enough cells for research and application of DP cells. We optimized the culture strategy for DP cells from three dimensions: stepwise dissection, collagen I coating, and optimized culture medium. Based on the optimized culture strategy, we immortalized primary DP cells with SV40 large T antigen, and established several immortalized DP cell strains. By comparing molecular expression and morphologic characteristics with primary DP cells, we found one cell strain named iDP6 was similar with primary DP cells. Further identifications illustrate that iDP6 expresses FGF7 and α-SMA, and has activity of alkaline phosphatase. During the process of characterization of immortalized DP cell strains, we also found that cells in DP were heterogeneous. We successfully optimized culture strategy for DP cells, and established an immortalized DP cell strain suitable for research and application of DP cells. PMID:29383288

Optimizing Culture Medium Composition to Improve Oligodendrocyte Progenitor Cell Yields In Vitro from Subventricular Zone-Derived Neural Progenitor Cell Neurospheres

PubMed Central

Franco, Paula G.; Pasquini, Juana M.; Silvestroff, Lucas

2015-01-01

Neural Stem and Progenitor Cells (NSC/NPC) are gathering tangible recognition for their uses in cell therapy and cell replacement therapies for human disease, as well as a model system to continue research on overall neural developmental processes in vitro. The Subventricular Zone is one of the largest NSC/NPC niches in the developing mammalian Central Nervous System, and persists through to adulthood. Oligodendrocyte progenitor cell (OPC) enriched cultures are usefull tools for in vitro studies as well as for cell replacement therapies for treating demyelination diseases. We used Subventricular Zone-derived NSC/NPC primary cultures from newborn mice and compared the effects of different growth factor combinations on cell proliferation and OPC yield. The Platelet Derived Growth Factor-AA and BB homodimers had a positive and significant impact on OPC generation. Furthermore, heparin addition to the culture media contributed to further increase overall culture yields. The OPC generated by this protocol were able to mature into Myelin Basic Protein-expressing cells and to interact with neurons in an in vitro co-culture system. As a whole, we describe an optimized in vitro method for increasing OPC. PMID:25837625

Estimated Costs for Delivery of HIV Antiretroviral Therapy to Individuals with CD4+ T-Cell Counts >350 cells/uL in Rural Uganda

PubMed Central

Jain, Vivek; Chang, Wei; Byonanebye, Dathan M.; Owaraganise, Asiphas; Twinomuhwezi, Ellon; Amanyire, Gideon; Black, Douglas; Marseille, Elliot; Kamya, Moses R.; Havlir, Diane V.; Kahn, James G.

2015-01-01

Background Evidence favoring earlier HIV ART initiation at high CD4+ T-cell counts (CD4>350/uL) has grown, and guidelines now recommend earlier HIV treatment. However, the cost of providing ART to individuals with CD4>350 in Sub-Saharan Africa has not been well estimated. This remains a major barrier to optimal global cost projections for accelerating the scale-up of ART. Our objective was to compute costs of ART delivery to high CD4+count individuals in a typical rural Ugandan health center-based HIV clinic, and use these data to construct scenarios of efficient ART scale-up. Methods Within a clinical study evaluating streamlined ART delivery to 197 individuals with CD4+ cell counts >350 cells/uL (EARLI Study: NCT01479634) in Mbarara, Uganda, we performed a micro-costing analysis of administrative records, ART prices, and time-and-motion analysis of staff work patterns. We computed observed per-person-per-year (ppy) costs, and constructed models estimating costs under several increasingly efficient ART scale-up scenarios using local salaries, lowest drug prices, optimized patient loads, and inclusion of viral load (VL) testing. Findings Among 197 individuals enrolled in the EARLI Study, median pre-ART CD4+ cell count was 569/uL (IQR 451–716). Observed ART delivery cost was $628 ppy at steady state. Models using local salaries and only core laboratory tests estimated costs of $529/$445 ppy (+/-VL testing, respectively). Models with lower salaries, lowest ART prices, and optimized healthcare worker schedules reduced costs by $100–200 ppy. Costs in a maximally efficient scale-up model were $320/$236 ppy (+/- VL testing). This included $39 for personnel, $106 for ART, $130/$46 for laboratory tests, and $46 for administrative/other costs. A key limitation of this study is its derivation and extrapolation of costs from one large rural treatment program of high CD4+ count individuals. Conclusions In a Ugandan HIV clinic, ART delivery costs—including VL testing—for individuals with CD4>350 were similar to estimates from high-efficiency programs. In higher efficiency scale-up models, costs were substantially lower. These favorable costs may be achieved because high CD4+ count patients are often asymptomatic, facilitating more efficient streamlined ART delivery. Our work provides a framework for calculating costs of efficient ART scale-up models using accessible data from specific programs and regions. PMID:26632823

Estimated Costs for Delivery of HIV Antiretroviral Therapy to Individuals with CD4+ T-Cell Counts >350 cells/uL in Rural Uganda.

PubMed

Jain, Vivek; Chang, Wei; Byonanebye, Dathan M; Owaraganise, Asiphas; Twinomuhwezi, Ellon; Amanyire, Gideon; Black, Douglas; Marseille, Elliot; Kamya, Moses R; Havlir, Diane V; Kahn, James G

2015-01-01

Evidence favoring earlier HIV ART initiation at high CD4+ T-cell counts (CD4>350/uL) has grown, and guidelines now recommend earlier HIV treatment. However, the cost of providing ART to individuals with CD4>350 in Sub-Saharan Africa has not been well estimated. This remains a major barrier to optimal global cost projections for accelerating the scale-up of ART. Our objective was to compute costs of ART delivery to high CD4+count individuals in a typical rural Ugandan health center-based HIV clinic, and use these data to construct scenarios of efficient ART scale-up. Within a clinical study evaluating streamlined ART delivery to 197 individuals with CD4+ cell counts >350 cells/uL (EARLI Study: NCT01479634) in Mbarara, Uganda, we performed a micro-costing analysis of administrative records, ART prices, and time-and-motion analysis of staff work patterns. We computed observed per-person-per-year (ppy) costs, and constructed models estimating costs under several increasingly efficient ART scale-up scenarios using local salaries, lowest drug prices, optimized patient loads, and inclusion of viral load (VL) testing. Among 197 individuals enrolled in the EARLI Study, median pre-ART CD4+ cell count was 569/uL (IQR 451-716). Observed ART delivery cost was $628 ppy at steady state. Models using local salaries and only core laboratory tests estimated costs of $529/$445 ppy (+/-VL testing, respectively). Models with lower salaries, lowest ART prices, and optimized healthcare worker schedules reduced costs by $100-200 ppy. Costs in a maximally efficient scale-up model were $320/$236 ppy (+/- VL testing). This included $39 for personnel, $106 for ART, $130/$46 for laboratory tests, and $46 for administrative/other costs. A key limitation of this study is its derivation and extrapolation of costs from one large rural treatment program of high CD4+ count individuals. In a Ugandan HIV clinic, ART delivery costs--including VL testing--for individuals with CD4>350 were similar to estimates from high-efficiency programs. In higher efficiency scale-up models, costs were substantially lower. These favorable costs may be achieved because high CD4+ count patients are often asymptomatic, facilitating more efficient streamlined ART delivery. Our work provides a framework for calculating costs of efficient ART scale-up models using accessible data from specific programs and regions.

Advanced interface modelling of n-Si/HNO3 doped graphene solar cells to identify pathways to high efficiency

NASA Astrophysics Data System (ADS)

Zhao, Jing; Ma, Fa-Jun; Ding, Ke; Zhang, Hao; Jie, Jiansheng; Ho-Baillie, Anita; Bremner, Stephen P.

2018-03-01

In graphene/silicon solar cells, it is crucial to understand the transport mechanism of the graphene/silicon interface to further improve power conversion efficiency. Until now, the transport mechanism has been predominantly simplified as an ideal Schottky junction. However, such an ideal Schottky contact is never realised experimentally. According to literature, doped graphene shows the properties of a semiconductor, therefore, it is physically more accurate to model graphene/silicon junction as a Heterojunction. In this work, HNO3-doped graphene/silicon solar cells were fabricated with the power conversion efficiency of 9.45%. Extensive characterization and first-principles calculations were carried out to establish an advanced technology computer-aided design (TCAD) model, where p-doped graphene forms a straddling heterojunction with the n-type silicon. In comparison with the simple Schottky junction models, our TCAD model paves the way for thorough investigation on the sensitivity of solar cell performance to graphene properties like electron affinity. According to the TCAD heterojunction model, the cell performance can be improved up to 22.5% after optimizations of the antireflection coatings and the rear structure, highlighting the great potentials for fabricating high efficiency graphene/silicon solar cells and other optoelectronic devices.

Engineering an in vitro air-blood barrier by 3D bioprinting

PubMed Central

Horváth, Lenke; Umehara, Yuki; Jud, Corinne; Blank, Fabian; Petri-Fink, Alke; Rothen-Rutishauser, Barbara

2015-01-01

Intensive efforts in recent years to develop and commercialize in vitro alternatives in the field of risk assessment have yielded new promising two- and three dimensional (3D) cell culture models. Nevertheless, a realistic 3D in vitro alveolar model is not available yet. Here we report on the biofabrication of the human air-blood tissue barrier analogue composed of an endothelial cell, basement membrane and epithelial cell layer by using a bioprinting technology. In contrary to the manual method, we demonstrate that this technique enables automatized and reproducible creation of thinner and more homogeneous cell layers, which is required for an optimal air-blood tissue barrier. This bioprinting platform will offer an excellent tool to engineer an advanced 3D lung model for high-throughput screening for safety assessment and drug efficacy testing. PMID:25609567

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Daniel L.; Debeb, Bisrat G.; Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, Texas

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. Anmore » independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.« less

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Computational design optimization for microfluidic magnetophoresis

PubMed Central

Plouffe, Brian D.; Lewis, Laura H.; Murthy, Shashi K.

2011-01-01

Current macro- and microfluidic approaches for the isolation of mammalian cells are limited in both efficiency and purity. In order to design a robust platform for the enumeration of a target cell population, high collection efficiencies are required. Additionally, the ability to isolate pure populations with minimal biological perturbation and efficient off-chip recovery will enable subcellular analyses of these cells for applications in personalized medicine. Here, a rational design approach for a simple and efficient device that isolates target cell populations via magnetic tagging is presented. In this work, two magnetophoretic microfluidic device designs are described, with optimized dimensions and operating conditions determined from a force balance equation that considers two dominant and opposing driving forces exerted on a magnetic-particle-tagged cell, namely, magnetic and viscous drag. Quantitative design criteria for an electromagnetic field displacement-based approach are presented, wherein target cells labeled with commercial magnetic microparticles flowing in a central sample stream are shifted laterally into a collection stream. Furthermore, the final device design is constrained to fit on standard rectangular glass coverslip (60 (L)×24 (W)×0.15 (H) mm3) to accommodate small sample volume and point-of-care design considerations. The anticipated performance of the device is examined via a parametric analysis of several key variables within the model. It is observed that minimal currents (<500 mA) are required to generate magnetic fields sufficient to separate cells from the sample streams flowing at rate as high as 7 ml∕h, comparable to the performance of current state-of-the-art magnet-activated cell sorting systems currently used in clinical settings. Experimental validation of the presented model illustrates that a device designed according to the derived rational optimization can effectively isolate (∼100%) a magnetic-particle-tagged cell population from a homogeneous suspension even in a low abundance. Overall, this design analysis provides a rational basis to select the operating conditions, including chamber and wire geometry, flow rates, and applied currents, for a magnetic-microfluidic cell separation device. PMID:21526007

Modelling and Optimization of Polycaprolactone Ultrafine-Fibres Electrospinning Process Using Response Surface Methodology

PubMed Central

Ruys, Andrew J.

2018-01-01

Electrospun fibres have gained broad interest in biomedical applications, including tissue engineering scaffolds, due to their potential in mimicking extracellular matrix and producing structures favourable for cell and tissue growth. The development of scaffolds often involves multivariate production parameters and multiple output characteristics to define product quality. In this study on electrospinning of polycaprolactone (PCL), response surface methodology (RSM) was applied to investigate the determining parameters and find optimal settings to achieve the desired properties of fibrous scaffold for acetabular labrum implant. The results showed that solution concentration influenced fibre diameter, while elastic modulus was determined by solution concentration, flow rate, temperature, collector rotation speed, and interaction between concentration and temperature. Relationships between these variables and outputs were modelled, followed by an optimization procedure. Using the optimized setting (solution concentration of 10% w/v, flow rate of 4.5 mL/h, temperature of 45 °C, and collector rotation speed of 1500 RPM), a target elastic modulus of 25 MPa could be achieved at a minimum possible fibre diameter (1.39 ± 0.20 µm). This work demonstrated that multivariate factors of production parameters and multiple responses can be investigated, modelled, and optimized using RSM. PMID:29562614

Concerning the electrosynthesis of hydrogen peroxide and peroxodisulfates. Section 2: Optimization of electrolysis cells using an electrolyzer for peroxodisulfuric acid as an example

NASA Technical Reports Server (NTRS)

Schleiff, M.; Thiele, W.; Matschiner, H.

1986-01-01

The model is presented of an electrolyzer for peroxodisulfuric acid, and it is analyzed mathematically. Its application for engineering and economic optimization is investigated in detail. The mathematical analysis leads to conclusions concerning the change in position of the optimum with respect to the various target functions due to changes of the individual design-caused and economic parameters.

Polarization of cells and soft objects driven by mechanical interactions: consequences for migration and chemotaxis.

PubMed

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.

Development of CAR T cells designed to improve antitumor efficacy and safety

PubMed Central

Jaspers, Janneke E.; Brentjens, Renier J.

2017-01-01

Chimeric antigen receptor (CAR) T cell therapy has shown promising efficacy against hematologic malignancies. Antitumor activity of CAR T cells, however, needs to be improved to increase therapeutic efficacy in both hematologic and solid cancers. Limitations to overcome are ‘on-target, off-tumor’ toxicity, antigen escape, short CAR T cell persistence, little expansion, trafficking to the tumor and inhibition of T cell activity by an inhibitory tumor microenvironment. Here we will discuss how optimizing the design of CAR T cells through genetic engineering addresses these limitations and improves the antitumor efficacy of CAR T cell therapy in pre-clinical models. PMID:28342824

Development of CAR T cells designed to improve antitumor efficacy and safety.

PubMed

Jaspers, Janneke E; Brentjens, Renier J

2017-10-01

Chimeric antigen receptor (CAR) T cell therapy has shown promising efficacy against hematologic malignancies. Antitumor activity of CAR T cells, however, needs to be improved to increase therapeutic efficacy in both hematologic and solid cancers. Limitations to overcome are 'on-target, off-tumor' toxicity, antigen escape, short CAR T cell persistence, little expansion, trafficking to the tumor and inhibition of T cell activity by an inhibitory tumor microenvironment. Here we will discuss how optimizing the design of CAR T cells through genetic engineering addresses these limitations and improves the antitumor efficacy of CAR T cell therapy in pre-clinical models. Published by Elsevier Inc.

Mathematical model for the analysis of structure and optimal operational parameters of a solid oxide fuel cell generator

NASA Astrophysics Data System (ADS)

Coralli, Alberto; Villela de Miranda, Hugo; Espiúca Monteiro, Carlos Felipe; Resende da Silva, José Francisco; Valadão de Miranda, Paulo Emílio

2014-12-01

Solid oxide fuel cells are globally recognized as a very promising technology in the area of highly efficient electricity generation with a low environmental impact. This technology can be advantageously implemented in many situations in Brazil and it is well suited to the use of ethanol as a primary energy source, an important feature given the highly developed Brazilian ethanol industry. In this perspective, a simplified mathematical model is developed for a fuel cell and its balance of plant, in order to identify the optimal system structure and the most convenient values for the operational parameters, with the aim of maximizing the global electric efficiency. In this way it is discovered the best operational configuration for the desired application, which is the distributed generation in the concession area of the electricity distribution company Elektro. The data regarding this configuration are required for the continuation of the research project, i.e. the development of a prototype, a cost analysis of the developed system and a detailed perspective of the market opportunities in Brazil.

From Genes to Ecosystems in Microbiology: Modeling Approaches and the Importance of Individuality

PubMed Central

Kreft, Jan-Ulrich; Plugge, Caroline M.; Prats, Clara; Leveau, Johan H. J.; Zhang, Weiwen; Hellweger, Ferdi L.

2017-01-01

Models are important tools in microbial ecology. They can be used to advance understanding by helping to interpret observations and test hypotheses, and to predict the effects of ecosystem management actions or a different climate. Over the past decades, biological knowledge and ecosystem observations have advanced to the molecular and in particular gene level. However, microbial ecology models have changed less and a current challenge is to make them utilize the knowledge and observations at the genetic level. We review published models that explicitly consider genes and make predictions at the population or ecosystem level. The models can be grouped into three general approaches, i.e., metabolic flux, gene-centric and agent-based. We describe and contrast these approaches by applying them to a hypothetical ecosystem and discuss their strengths and weaknesses. An important distinguishing feature is how variation between individual cells (individuality) is handled. In microbial ecosystems, individual heterogeneity is generated by a number of mechanisms including stochastic interactions of molecules (e.g., gene expression), stochastic and deterministic cell division asymmetry, small-scale environmental heterogeneity, and differential transport in a heterogeneous environment. This heterogeneity can then be amplified and transferred to other cell properties by several mechanisms, including nutrient uptake, metabolism and growth, cell cycle asynchronicity and the effects of age and damage. For example, stochastic gene expression may lead to heterogeneity in nutrient uptake enzyme levels, which in turn results in heterogeneity in intracellular nutrient levels. Individuality can have important ecological consequences, including division of labor, bet hedging, aging and sub-optimality. Understanding the importance of individuality and the mechanism(s) underlying it for the specific microbial system and question investigated is essential for selecting the optimal modeling strategy. PMID:29230200

Student Collaboration in a Series of Integrated Experiments to Study Enzyme Reactor Modeling with Immobilized Cell-Based Invertase

ERIC Educational Resources Information Center

Taipa, M. A^ngela; Azevedo, Ana M.; Grilo, Anto´nio L.; Couto, Pedro T.; Ferreira, Filipe A. G.; Fortuna, Ana R. M.; Pinto, Ine^s F.; Santos, Rafael M.; Santos, Susana B.

2015-01-01

An integrative laboratory study addressing fundamentals of enzyme catalysis and their application to reactors operation and modeling is presented. Invertase, a ß-fructofuranosidase that catalyses the hydrolysis of sucrose, is used as the model enzyme at optimal conditions (pH 4.5 and 45 °C). The experimental work involves 3 h of laboratory time…

Collaborative modelling: the future of computational neuroscience?

PubMed

Davison, Andrew P

2012-01-01

Given the complexity of biological neural circuits and of their component cells and synapses, building and simulating robust, well-validated, detailed models increasingly surpasses the resources of an individual researcher or small research group. In this article, I will briefly review possible solutions to this problem, argue for open, collaborative modelling as the optimal solution for advancing neuroscience knowledge, and identify potential bottlenecks and possible solutions.

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.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis.

PubMed

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A; Soni, Nipunjot; Mandal, Raju K; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y; Govender, Thavendran; Kruger, Hendrik G; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD 600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD 600 nm ): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis

PubMed Central

Haque, Shafiul; Khan, Saif; Wahid, Mohd; Dar, Sajad A.; Soni, Nipunjot; Mandal, Raju K.; Singh, Vineeta; Tiwari, Dileep; Lohani, Mohtashim; Areeshi, Mohammed Y.; Govender, Thavendran; Kruger, Hendrik G.; Jawed, Arshad

2016-01-01

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600 nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties. PMID:27920762

Dynamical observation on biological progression of VX2 liver tumors to identify the optimal time for intervention in animal models.

PubMed

Wang, Zhenguang; Yang, Guangjie; Nie, Pei; Fu, Junhua; Wang, Xufu; Liu, Dan

2013-01-01

Based on practice guideline of "management of hepatocellular carcinoma (HCC): update" published by American Association for the Study of Liver Diseases (AASLD) and "Barcelona Clinic Liver Cancer staging system (BCLC)," this study investigated how to enroll the optimal VX2 liver tumor model for HCC researches by dynamically observing the biological progression of the tumor. Thirty-two healthy New Zealand white rabbits were implanted VX2 liver tumor by cell suspension method (n=24) and tissue fragment method (n=8). All the rabbits underwent CT scans on day 7, 14, 21 and 28 after implantation to observe the size of the tumors, the time when metastases and ascites occurred and the survival time. Appropriate intervention times were estimated corresponding to different clinical HCC stages by using tumor diameter-time curve. The VX2 liver tumors grew rapidly within 28 days after implantation. And the tumors in the cell suspension group grew faster than those of the tissue fragment group. The appropriate intervention time corresponding to very early stage, early stage and intermediate stage were <11 days, 11-16.9 days and >16.9 days, respectively in the cell suspension group, and <19.9 days, 19.9-25.5 days and >25.5 days, respectively in the tissue fragment group. Preclinical animal research needs to improve on different levels to yield best predictions for human patients. Researchers should seek for an individualized proposal to select optimal VX2 liver tumor models for their experiments. This approach may lead to a more accurate determination of therapeutic outcomes.

SU-D-BRB-06: Treating Glioblastoma Multiforme (GBM) as a Chronic Disease: Implication of Temporal-Spatial Dose Fractionation Optimization Including Cancer Stem Cell Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, V; Nguyen, D; Pajonk, F

Purpose: To explore the feasibility of improving GBM treatment outcome with temporal-spatial dose optimization of an ordinary differential equation (ODE) that models the differentiation and distinct radiosensitivity between cancer stem cells (CSC) and differentiated cancer cells (DCC). Methods: The ODE was formulated into a non-convex optimization problem with the objective to minimize remaining total cancer cells 500 days from the onset of radiotherapy when the total cancer cell number was 3.5×10{sup 7}, while maintaining normal tissue biological effective dose (BED) of 100Gy resulted from standard prescription of 2Gyx30. Assuming spatially separated CSC and DCC, optimization was also performed to exploremore » the potential benefit from dose-painting the two compartments. Dose escalation to a sub-cell-population in the GTV was also examined assuming that a 2 cm margin around the GTV allows sufficient dose drop-off to 100Gy BED. The recurrence time was determined as the time at which the total cancer cell number regrows to 10{sup 9} cells. Results: The recurrence time with variable fractional doses administered once per week, bi-week and month for one year were found to be 615, 593 and 570 days, superior to the standard-prescription recurrence time of 418 days. The optimal dose-fraction size progression for both uniform and dose-painting to the tumor is low and relatively constant in the beginning and gradually increases to more aggressive fractions at end of the treatment course. Dose escalation to BED of 200Gy to the whole tumor alongside with protracted weekly treatment was found to further delay recurrence to 733 days. Dose-painting of 200 and 500Gy BED to CSC on a year-long weekly schedule further extended recurrence to 736 and 1076 days, respectively. Conclusion: GBM treatment outcome can possibly be improved with a chronic treatment approach. Further dose escalation to the entire tumor or CSC targeted killing is needed to achieve total tumor control. This work is supported by the NSF Graduate Research Fellowship (DGE-1144087)« less

Optimizing lighting, thermal performance, and energy production of building facades by using automated blinds and PV cells

NASA Astrophysics Data System (ADS)

Alzoubi, Hussain Hendi

Energy consumption in buildings has recently become a major concern for environmental designers. Within this field, daylighting and solar energy design are attractive strategies for saving energy. This study seeks the integrity and the optimality of building envelopes' performance. It focuses on the transparent parts of building facades, specifically, the windows and their shading devices. It suggests a new automated method of utilizing solar energy while keeping optimal solutions for indoor daylighting. The method utilizes a statistical approach to produce mathematical equations based on physical experimentation. A full-scale mock-up representing an actual office was built. Heat gain and lighting levels were measured empirically and correlated with blind angles. Computational methods were used to estimate the power production from photovoltaic cells. Mathematical formulas were derived from the results of the experiments; these formulas were utilized to construct curves as well as mathematical equations for the purpose of optimization. The mathematical equations resulting from the optimization process were coded using Java programming language to enable future users to deal with generic locations of buildings with a broader context of various climatic conditions. For the purpose of optimization by automation under different climatic conditions, a blind control system was developed based on the findings of this study. This system calibrates the blind angles instantaneously based upon the sun position, the indoor daylight, and the power production from the photovoltaic cells. The functions of this system guarantee full control of the projected solar energy on buildings' facades for indoor lighting and heat gain. In winter, the system automatically blows heat into the space, whereas it expels heat from the space during the summer season. The study showed that the optimality of building facades' performance is achievable for integrated thermal, energy, and lighting models in buildings. There are blind angles that produce maximum energy from the photovoltaic cells while keeping indoor light within the acceptable limits that prevent undesired heat gain in summer.

A new strategy of glucose supply in a microbial fermentation model

NASA Astrophysics Data System (ADS)

Kasbawati, Gunawan, A. Y.; Sidarto, K. A.; Hertadi, R.

2015-09-01

Strategy of glucose supply to achieve an optimal productivity of ethanol production of a yeast cell is one of the main features in a microbial fermentation process. Beside a known continuous glucose supply, in this study we consider a new supply strategy so called the on-off supply. An optimal control theory is applied to the fermentation system to find the optimal rate of glucose supply and time of supply. The optimization problem is solved numerically using Differential Evolutionary algorithm. We find two alternative solutions that we can choose to get the similar result: either long period process with low supply or short period process with high glucose supply.

Polymer coating on a micropillar chip for robust attachment of PuraMatrix peptide hydrogel for 3D hepatic cell culture.

PubMed

Roth, Alexander David; Lama, Pratap; Dunn, Stephen; Hong, Stephen; Lee, Moo-Yeal

2018-09-01

For better mimicking tissues in vivo and developing predictive cell models for high-throughput screening (HTS) of potential drug candidates, three-dimensional (3D) cell cultures have been performed in various hydrogels. In this study, we have investigated several polymer coating materials to robustly attach PuraMatrix peptide hydrogel on a micropillar chip for 3D culture of Hep3B human hepatic cells, which can be used as a tool for high-throughput assessment of compound hepatotoxicity. Among several amphiphilic polymers with maleic anhydride groups tested, 0.01% (w/v) poly(maleic anhydride-alt-1-octadecene) (PMA-OD) provided superior coating properties with no PuraMatrix spot detachment from the micropillar chip and no air bubble entrapment in a complementary microwell chip. To maintain Hep3B cell viability in PuraMatrix gel on the chip, gelation conditions were optimized in the presence of additional salts, at different seeding densities, and for growth medium washes. As a result, salts in growth media were sufficient for gelation, and relatively high cell seeding at 6 million cells/mL and two media washes for pH neutralization were required. With optimized 3D cell culture conditions, controlled gene expression and compound toxicity assessment were successfully demonstrated by using recombinant adenoviruses carrying genes for green and red fluorescent proteins as well as six model compounds. Overall, PuraMatrix hydrogel on the chip was suitable for 3D cell encapsulation, gene expression, and rapid toxicity assessment. Published by Elsevier B.V.

Structure-Guided Design and Optimization of Dipeptidyl Inhibitors of Norovirus 3CL Protease. Structure–Activity Relationships and Biochemical, X-ray Crystallographic, Cell-Based, and In Vivo Studies

DOE PAGES

Galasiti Kankanamalage, Anushka C.; Kim, Yunjeong; Weerawarna, Pathum M.; ...

2015-04-09

Norovirus infection constitutes the primary cause of acute viral gastroenteritis. There are currently no vaccines or norovirus-specific antiviral therapeutics available for the management of norovirus infection. Norovirus 3C-like protease is essential for viral replication, consequently, inhibition of this enzyme is a fruitful avenue of investigation that may lead to the emergence of antinorovirus therapeutics. We describe herein the optimization of dipeptidyl inhibitors of norovirus 3C-like protease using iterative SAR, X-ray crystallographic, and enzyme and cell-based studies. We also demonstrate herein in vivo efficacy of an inhibitor using the murine model of norovirus infection.

Electrospun Collagen/Silk Tissue Engineering Scaffolds: Fiber Fabrication, Post-Treatment Optimization, and Application in Neural Differentiation of Stem Cells

NASA Astrophysics Data System (ADS)

Zhu, Bofan

Biocompatible scaffolds mimicking the locally aligned fibrous structure of native extracellular matrix (ECM) are in high demand in tissue engineering. In this thesis research, unidirectionally aligned fibers were generated via a home-built electrospinning system. Collagen type I, as a major ECM component, was chosen in this study due to its support of cell proliferation and promotion of neuroectodermal commitment in stem cell differentiation. Synthetic dragline silk proteins, as biopolymers with remarkable tensile strength and superior elasticity, were also used as a model material. Good alignment, controllable fiber size and morphology, as well as a desirable deposition density of fibers were achieved via the optimization of solution and electrospinning parameters. The incorporation of silk proteins into collagen was found to significantly enhance mechanical properties and stability of electrospun fibers. Glutaraldehyde (GA) vapor post-treatment was demonstrated as a simple and effective way to tune the properties of collagen/silk fibers without changing their chemical composition. With 6-12 hours GA treatment, electrospun collagen/silk fibers were not only biocompatible, but could also effectively induce the polarization and neural commitment of stem cells, which were optimized on collagen rich fibers due to the unique combination of biochemical and biophysical cues imposed to cells. Taken together, electrospun collagen rich composite fibers are mechanically strong, stable and provide excellent cell adhesion. The unidirectionally aligned fibers can accelerate neural differentiation of stem cells, representing a promising therapy for neural tissue degenerative diseases and nerve injuries.

Multifactorial Experimental Design to Optimize the Anti-Inflammatory and Proangiogenic Potential of Mesenchymal Stem Cell Spheroids.

PubMed

Murphy, Kaitlin C; Whitehead, Jacklyn; Falahee, Patrick C; Zhou, Dejie; Simon, Scott I; Leach, J Kent

2017-06-01

Mesenchymal stem cell therapies promote wound healing by manipulating the local environment to enhance the function of host cells. Aggregation of mesenchymal stem cells (MSCs) into three-dimensional spheroids increases cell survival and augments their anti-inflammatory and proangiogenic potential, yet there is no consensus on the preferred conditions for maximizing spheroid function in this application. The objective of this study was to optimize conditions for forming MSC spheroids that simultaneously enhance their anti-inflammatory and proangiogenic nature. We applied a design of experiments (DOE) approach to determine the interaction between three input variables (number of cells per spheroid, oxygen tension, and inflammatory stimulus) on MSC spheroids by quantifying secretion of prostaglandin E 2 (PGE 2 ) and vascular endothelial growth factor (VEGF), two potent molecules in the MSC secretome. DOE results revealed that MSC spheroids formed with 40,000 cells per spheroid in 1% oxygen with an inflammatory stimulus (Spheroid 1) would exhibit enhanced PGE 2 and VEGF production versus those formed with 10,000 cells per spheroid in 21% oxygen with no inflammatory stimulus (Spheroid 2). Compared to Spheroid 2, Spheroid 1 produced fivefold more PGE 2 and fourfold more VEGF, providing the opportunity to simultaneously upregulate the secretion of these factors from the same spheroid. The spheroids induced macrophage polarization, sprout formation with endothelial cells, and keratinocyte migration in a human skin equivalent model-demonstrating efficacy on three key cell types that are dysfunctional in chronic non-healing wounds. We conclude that DOE-based analysis effectively identifies optimal culture conditions to enhance the anti-inflammatory and proangiogenic potential of MSC spheroids. Stem Cells 2017;35:1493-1504. © 2017 AlphaMed Press.

Modeling and Optimization of Sub-Wavelength Grating Nanostructures on Cu(In,Ga)Se2 Solar Cell

NASA Astrophysics Data System (ADS)

Kuo, Shou-Yi; Hsieh, Ming-Yang; Lai, Fang-I.; Liao, Yu-Kuang; Kao, Ming-Hsuan; Kuo, Hao-Chung

2012-10-01

In this study, an optical simulation of Cu(In,Ga)Se2 (CIGS) solar cells by the rigorous coupled-wave analysis (RCWA) method is carried out to investigate the effects of surface morphology on the light absorption and power conversion efficiencies. Various sub-wavelength grating (SWG) nanostructures of periodic ZnO:Al (AZO) on CIGS solar cells were discussed in detail. SWG nanostructures were used as efficient antireflection layers. From the simulation results, AZO structures with nipple arrays effectively suppress the Fresnel reflection compared with nanorod- and cone-shaped AZO structures. The optimized reflectance decreased from 8.44 to 3.02% and the efficiency increased from 14.92 to 16.11% accordingly. The remarkable enhancement in light harvesting is attributed to the gradient refractive index profile between the AZO nanostructures and air.

Multiple Lytic Origins of Replication Are Required for Optimal Gammaherpesvirus Fitness In Vitro and In Vivo.

PubMed

Sattler, Christine; Steer, Beatrix; Adler, Heiko

2016-03-01

An unresolved question in herpesvirus biology is why some herpesviruses contain more than one lytic origin of replication (oriLyt). Using murine gammaherpesvirus 68 (MHV-68) as model virus containing two oriLyts, we demonstrate that loss of either of the two oriLyts was well tolerated in some situations but not in others both in vitro and in vivo. This was related to the cell type, the organ or the route of inoculation. Depending on the cell type, different cellular proteins, for example Hexim1 and Rbbp4, were found to be associated with oriLyt DNA. Overexpression or downregulation of these proteins differentially affected the growth of mutants lacking either the left or the right oriLyt. Thus, multiple oriLyts are required to ensure optimal fitness in different cell types and tissues.

Optimally achieving milk bulk tank somatic cell count thresholds.

PubMed

Troendle, Jason A; Tauer, Loren W; Gröhn, Yrjo T

2017-01-01

High somatic cell count in milk leads to reduced shelf life in fluid milk and lower processed yields in manufactured dairy products. As a result, farmers are often penalized for high bulk tank somatic cell count or paid a premium for low bulk tank somatic cell count. Many countries also require all milk from a farm to be lower than a specified regulated somatic cell count. Thus, farms often cull cows that have high somatic cell count to meet somatic cell count thresholds. Rather than naïvely cull the highest somatic cell count cows, a mathematical programming model was developed that determines the cows to be culled from the herd by maximizing the net present value of the herd, subject to meeting any specified bulk tank somatic cell count level. The model was applied to test-day cows on 2 New York State dairy farms. Results showed that the net present value of the herd was increased by using the model to meet the somatic cell count restriction compared with naïvely culling the highest somatic cell count cows. Implementation of the model would be straightforward in dairy management decision software. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espinoza, I., E-mail: iespinoza@fis.puc.cl; Peschke, P.; Karger, C. P.

2015-01-15

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii)more » hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was found to be significantly more important for reoxygenation than angiogenesis or decreased oxygen consumption due to an increased fraction of dead cells. In the studied HNSSC-case, the TCD{sub 50} values (dose at 50% TCP) decreased from 71.0 Gy under hypoxic to 53.6 Gy under the oxic condition. Conclusions: The results obtained with the developed multiscale model are in accordance with expectations based on radiobiological principles and clinical experience. As the model is voxel-based, radiological imaging methods may help to provide the required 3D-characterization of the tumor prior to irradiation. For clinical application, the model has to be further validated with experimental and clinical data. If this is achieved, the model may be used to optimize fractionation schedules and dose distributions for the treatment of hypoxic tumors.« less

Thermal Modeling and Management of Solid Oxide Fuel Cells Operating with Internally Reformed Methane

NASA Astrophysics Data System (ADS)

Wu, Yiyang; Shi, Yixiang; Cai, Ningsheng; Ni, Meng

2018-06-01

A detailed three-dimensional mechanistic model of a large-scale solid oxide fuel cell (SOFC) unit running on partially pre-reformed methane is developed. The model considers the coupling effects of chemical and electrochemical reactions, mass transport, momentum and heat transfer in the SOFC unit. After model validation, parametric simulations are conducted to investigate how the methane pre-reforming ratio affects the transport and electrochemistry of the SOFC unit. It is found that the methane steam reforming reaction has a "smoothing effect", which can achieve more uniform distributions of gas compositions, current density and temperature among the cell plane. In the case of 1500 W/m2 power density output, adding 20% methane absorbs 50% of internal heat production inside the cell, reduces the maximum temperature difference inside the cell from 70 K to 22 K and reduces the cathode air supply by 75%, compared to the condition of completely pre-reforming of methane. Under specific operating conditions, the pre-reforming ratio of methane has an optimal range for obtaining a good temperature distribution and good cell performance.

Cell-cycle research with synchronous cultures: an evaluation

NASA Technical Reports Server (NTRS)

Helmstetter, C. E.; Thornton, M.; Grover, N. B.

2001-01-01

The baby-machine system, which produces new-born Escherichia coli cells from cultures immobilized on a membrane, was developed many years ago in an attempt to attain optimal synchrony with minimal disturbance of steady-state growth. In the present article, we put forward a model to describe the behaviour of cells produced by this method, and provide quantitative evaluation of the parameters involved, at each of four different growth rates. Considering the high level of selection achievable with this technique and the natural dispersion in interdivision times, we believe that the output of the baby machine is probably close to optimal in terms of both quality and persistence of synchrony. We show that considerable information on events in the cell cycle can be obtained from populations with age distributions very much broader than those achieved with the baby machine and differing only modestly from steady state. The data presented here, together with the long and fruitful history of findings employing the baby-machine technique, suggest that minimisation of stress on cells is the single most important factor for successful cell-cycle analysis.

°Enhancing High Temperature Anode Performance with 2° Anchoring Phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, Robert A.; Sofie, Stephen W.; Amendola, Roberta

2015-10-01

Project accomplishments included developing and optimizing strength testing of aluminum titanate (ALT)-doped Ni-YSZ materials and identified the dopant levels that optimized mechanical strength and enhanced electrochemical performance. We also optimized our ability to fabricate electrolyte supported button cells with anodes consisting of powders provided by Fuel Cell Energy. In several instances, those anodes were infiltrated with ALT and tested with hydrogen for 30 hours at 800°C at an applied potential of 0.4 V. Our research activities were focused in three areas: 1) mechanical strength testing on as prepared and reducced nickel-YSZ structures that were either free of a dopant ormore » prepared by mechanically mixing in ALT at various weight percents (up to 10 wt%); 2) 24-hour electrochemical testing of electroylte supported cells having anodes made from Ni/YSZ and Ni/YSZ/ALT anodes with specific attention focused on modeling degradation rates; and 3) operando EIS and optical testing of both in-house fabricated devices as well as membrane electrode assemblies that were acquired from commercial vendors.« less

Theory of optimal information transmission in E. coli chemotaxis pathway

NASA Astrophysics Data System (ADS)

Micali, Gabriele; Endres, Robert G.

Bacteria live in complex microenvironments where they need to make critical decisions fast and reliably. These decisions are inherently affected by noise at all levels of the signaling pathway, and cells are often modeled as an input-output device that transmits extracellular stimuli (input) to internal proteins (channel), which determine the final behavior (output). Increasing the amount of transmitted information between input and output allows cells to better infer extracellular stimuli and respond accordingly. However, in contrast to electronic devices, the separation into input, channel, and output is not always clear in biological systems. Output might feed back into the input, and the channel, made by proteins, normally interacts with the input. Furthermore, a biological channel is affected by mutations and can change under evolutionary pressure. Here, we present a novel approach to maximize information transmission: given cell-external and internal noise, we analytically identify both input distributions and input-output relations that optimally transmit information. Using E. coli chemotaxis as an example, we conclude that its pathway is compatible with an optimal information transmission device despite the ultrasensitive rotary motors.

Design optimization of electric vehicle battery cooling plates for thermal performance

NASA Astrophysics Data System (ADS)

Jarrett, Anthony; Kim, Il Yong

The performance of high-energy battery cells utilized in electric vehicles (EVs) is greatly improved by adequate temperature control. An efficient thermal management system is also desirable to avoid diverting excessive power from the primary vehicle functions. In a battery cell stack, cooling can be provided by including cooling plates: thin metal fabrications which include one or more internal channels through which a coolant is pumped. Heat is conducted from the battery cells into the cooling plate, and transported away by the coolant. The operating characteristics of the cooling plate are determined in part by the geometry of the channel; its route, width, length, etc. In this study, a serpentine-channel cooling plate is modeled parametrically and its characteristics assessed using computational fluid dynamics (CFD). Objective functions of pressure drop, average temperature, and temperature uniformity are defined and numerical optimization is carried out by allowing the channel width and position to vary. The optimization results indicate that a single design can satisfy both pressure and average temperature objectives, but at the expense of temperature uniformity.

Optimal design of solid oxide fuel cell, ammonia-water single effect absorption cycle and Rankine steam cycle hybrid system

NASA Astrophysics Data System (ADS)

Mehrpooya, Mehdi; Dehghani, Hossein; Ali Moosavian, S. M.

2016-02-01

A combined system containing solid oxide fuel cell-gas turbine power plant, Rankine steam cycle and ammonia-water absorption refrigeration system is introduced and analyzed. In this process, power, heat and cooling are produced. Energy and exergy analyses along with the economic factors are used to distinguish optimum operating point of the system. The developed electrochemical model of the fuel cell is validated with experimental results. Thermodynamic package and main parameters of the absorption refrigeration system are validated. The power output of the system is 500 kW. An optimization problem is defined in order to finding the optimal operating point. Decision variables are current density, temperature of the exhaust gases from the boiler, steam turbine pressure (high and medium), generator temperature and consumed cooling water. Results indicate that electrical efficiency of the combined system is 62.4% (LHV). Produced refrigeration (at -10 °C) and heat recovery are 101 kW and 22.1 kW respectively. Investment cost for the combined system (without absorption cycle) is about 2917 kW-1.

Optimized feline vitrectomy technique for therapeutic stem cell delivery to the inner retina

PubMed Central

Jayaram, Hari; Becker, Silke; Eastlake, Karen; Jones, Megan F; Charteris, David G; Limb, G Astrid

2014-01-01

Objective To describe an optimized surgical technique for feline vitrectomy which reduces bleeding and aids posterior gel clearance in order to facilitate stem cell delivery to the inner retina using cellular scaffolds. Procedures Three-port pars plana vitrectomies were performed in six-specific pathogen-free domestic cats using an optimized surgical technique to improve access and minimize severe intraoperative bleeding. Results The surgical procedure was successfully completed in all six animals. Lens sparing vitrectomy resulted in peripheral lens touch in one of three animals but without cataract formation. Transient bleeding from sclerotomies, which was readily controlled, was seen in two of the six animals. No cases of vitreous hemorrhage, severe postoperative inflammation, retinal detachment, or endophthalmitis were observed during postoperative follow-up. Conclusions Three-port pars plana vitrectomy can be performed successfully in the cat in a safe and controlled manner when the appropriate precautions are taken to minimize the risk of developing intraoperative hemorrhage. This technique may facilitate the use of feline models of inner retinal degeneration for the development of stem cell transplantation techniques using cellular scaffolds. PMID:24661435

Study on Pyroelectric Harvesters with Various Geometry

PubMed Central

Siao, An-Shen; Chao, Ching-Kong; Hsiao, Chun-Ching

2015-01-01

Pyroelectric harvesters convert time-dependent temperature variations into electric current. The appropriate geometry of the pyroelectric cells, coupled with the optimal period of temperature fluctuations, is key to driving the optimal load resistance, which enhances the performance of pyroelectric harvesters. The induced charge increases when the thickness of the pyroelectric cells decreases. Moreover, the induced charge is extremely reduced for the thinner pyroelectric cell when not used for the optimal period. The maximum harvested power is achieved when a 100 μm-thick PZT (Lead zirconate titanate) cell is used to drive the optimal load resistance of about 40 MΩ. Moreover, the harvested power is greatly reduced when the working resistance diverges even slightly from the optimal load resistance. The stored voltage generated from the 75 μm-thick PZT cell is less than that from the 400 μm-thick PZT cell for a period longer than 64 s. Although the thinner PZT cell is advantageous in that it enhances the efficiency of the pyroelectric harvester, the much thinner 75 μm-thick PZT cell and the divergence from the optimal period further diminish the performance of the pyroelectric cell. Therefore, the designers of pyroelectric harvesters need to consider the coupling effect between the geometry of the pyroelectric cells and the optimal period of temperature fluctuations to drive the optimal load resistance. PMID:26270666

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU

PubMed Central

Xia, Yong; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations. PMID:26581957

Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU.

PubMed

Xia, Yong; Wang, Kuanquan; Zhang, Henggui

2015-01-01

Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation) and the other is the diffusion term of the monodomain model (partial differential equation). Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.

Tumor-targeted T cells modified to secrete IL-12 eradicate systemic tumors without need for prior conditioning

PubMed Central

Pegram, Hollie J.; Lee, James C.; Hayman, Erik G.; Imperato, Gavin H.; Tedder, Thomas F.; Sadelain, Michel

2012-01-01

Adoptive cell therapy with tumor-targeted T cells is a promising approach to cancer therapy. Enhanced clinical outcome using this approach requires conditioning regimens with total body irradiation, lymphodepleting chemotherapy, and/or additional cytokine support. However, the need for prior conditioning precludes optimal application of this approach to a significant number of cancer patients intolerant to these regimens. Herein, we present preclinical studies demonstrating that treatment with CD19-specific, chimeric antigen receptor (CAR)–modified T cells that are further modified to constitutively secrete IL-12 are able to safely eradicate established disease in the absence of prior conditioning. We demonstrate in a novel syngeneic tumor model that tumor elimination requires both CD4+ and CD8+ T-cell subsets, autocrine IL-12 stimulation, and subsequent IFNγ secretion by the CAR+ T cells. Importantly, IL-12–secreting, tumor-targeted T cells acquire intrinsic resistance to T regulatory cell–mediated inhibition. Based on these preclinical data, we anticipate that adoptive therapy using CAR-targeted T cells modified to secrete IL-12 will obviate or reduce the need for potentially hazardous conditioning regimens to achieve optimal antitumor responses in cancer patients. PMID:22354001

An assessment of the effects of cell size on AGNPS modeling of watershed runoff

USGS Publications Warehouse

Wu, S.-S.; Usery, E.L.; Finn, M.P.; Bosch, D.D.

2008-01-01

This study investigates the changes in simulated watershed runoff from the Agricultural NonPoint Source (AGNPS) pollution model as a function of model input cell size resolution for eight different cell sizes (30 m, 60 m, 120 m, 210 m, 240 m, 480 m, 960 m, and 1920 m) for the Little River Watershed (Georgia, USA). Overland cell runoff (area-weighted cell runoff), total runoff volume, clustering statistics, and hot spot patterns were examined for the different cell sizes and trends identified. Total runoff volumes decreased with increasing cell size. Using data sets of 210-m cell size or smaller in conjunction with a representative watershed boundary allows one to model the runoff volumes within 0.2 percent accuracy. The runoff clustering statistics decrease with increasing cell size; a cell size of 960 m or smaller is necessary to indicate significant high-runoff clustering. Runoff hot spot areas have a decreasing trend with increasing cell size; a cell size of 240 m or smaller is required to detect important hot spots. Conclusions regarding cell size effects on runoff estimation cannot be applied to local watershed areas due to the inconsistent changes of runoff volume with cell size; but, optimal cells sizes for clustering and hot spot analyses are applicable to local watershed areas due to the consistent trends.

Dielectric spectroscopy platform to measure MCF10A epithelial cell aggregation as a model for spheroidal cell cluster analysis.

PubMed

Heileman, K L; Tabrizian, M

2017-05-02

3-Dimensional cell cultures are more representative of the native environment than traditional cell cultures on flat substrates. As a result, 3-dimensional cell cultures have emerged as a very valuable model environment to study tumorigenesis, organogenesis and tissue regeneration. Many of these models encompass the formation of cell aggregates, which mimic the architecture of tumor and organ tissue. Dielectric impedance spectroscopy is a non-invasive, label free and real time technique, overcoming the drawbacks of established techniques to monitor cell aggregates. Here we introduce a platform to monitor cell aggregation in a 3-dimensional extracellular matrix using dielectric spectroscopy. The MCF10A breast epithelial cell line serves as a model for cell aggregation. The platform maintains sterile conditions during the multi-day assay while allowing continuous dielectric spectroscopy measurements. The platform geometry optimizes dielectric measurements by concentrating cells within the electrode sensing region. The cells show a characteristic dielectric response to aggregation which corroborates with finite element analysis computer simulations. By fitting the experimental dielectric spectra to the Cole-Cole equation, we demonstrated that the dispersion intensity Δε and the characteristic frequency f c are related to cell aggregate growth. In addition, microscopy can be performed directly on the platform providing information about cell position, density and morphology. This platform could yield many applications for studying the electrophysiological activity of cell aggregates.

State-of-charge inconsistency estimation of lithium-ion battery pack using mean-difference model and extended Kalman filter

NASA Astrophysics Data System (ADS)

Zheng, Yuejiu; Gao, Wenkai; Ouyang, Minggao; Lu, Languang; Zhou, Long; Han, Xuebing

2018-04-01

State-of-charge (SOC) inconsistency impacts the power, durability and safety of the battery pack. Therefore, it is necessary to measure the SOC inconsistency of the battery pack with good accuracy. We explore a novel method for modeling and estimating the SOC inconsistency of lithium-ion (Li-ion) battery pack with low computation effort. In this method, a second-order RC model is selected as the cell mean model (CMM) to represent the overall performance of the battery pack. A hypothetical Rint model is employed as the cell difference model (CDM) to evaluate the SOC difference. The parameters of mean-difference model (MDM) are identified with particle swarm optimization (PSO). Subsequently, the mean SOC and the cell SOC differences are estimated by using extended Kalman filter (EKF). Finally, we conduct an experiment on a small Li-ion battery pack with twelve cells connected in series. The results show that the evaluated SOC difference is capable of tracking the changing of actual value after a quick convergence.

Model-based approach for design verification and co-optimization of catastrophic and parametric-related defects due to systematic manufacturing variations

NASA Astrophysics Data System (ADS)

Perry, Dan; Nakamoto, Mark; Verghese, Nishath; Hurat, Philippe; Rouse, Rich

2007-03-01

Model-based hotspot detection and silicon-aware parametric analysis help designers optimize their chips for yield, area and performance without the high cost of applying foundries' recommended design rules. This set of DFM/ recommended rules is primarily litho-driven, but cannot guarantee a manufacturable design without imposing overly restrictive design requirements. This rule-based methodology of making design decisions based on idealized polygons that no longer represent what is on silicon needs to be replaced. Using model-based simulation of the lithography, OPC, RET and etch effects, followed by electrical evaluation of the resulting shapes, leads to a more realistic and accurate analysis. This analysis can be used to evaluate intelligent design trade-offs and identify potential failures due to systematic manufacturing defects during the design phase. The successful DFM design methodology consists of three parts: 1. Achieve a more aggressive layout through limited usage of litho-related recommended design rules. A 10% to 15% area reduction is achieved by using more aggressive design rules. DFM/recommended design rules are used only if there is no impact on cell size. 2. Identify and fix hotspots using a model-based layout printability checker. Model-based litho and etch simulation are done at the cell level to identify hotspots. Violations of recommended rules may cause additional hotspots, which are then fixed. The resulting design is ready for step 3. 3. Improve timing accuracy with a process-aware parametric analysis tool for transistors and interconnect. Contours of diffusion, poly and metal layers are used for parametric analysis. In this paper, we show the results of this physical and electrical DFM methodology at Qualcomm. We describe how Qualcomm was able to develop more aggressive cell designs that yielded a 10% to 15% area reduction using this methodology. Model-based shape simulation was employed during library development to validate architecture choices and to optimize cell layout. At the physical verification stage, the shape simulator was run at full-chip level to identify and fix residual hotspots on interconnect layers, on poly or metal 1 due to interaction between adjacent cells, or on metal 1 due to interaction between routing (via and via cover) and cell geometry. To determine an appropriate electrical DFM solution, Qualcomm developed an experiment to examine various electrical effects. After reporting the silicon results of this experiment, which showed sizeable delay variations due to lithography-related systematic effects, we also explain how contours of diffusion, poly and metal can be used for silicon-aware parametric analysis of transistors and interconnect at the cell-, block- and chip-level.

Toxicity testing of four silver nanoparticle-coated dental castings in 3-D LO2 cell cultures.

PubMed

Zhao, Yi-Ying; Chu, Qiang; Shi, Xu-Er; Zheng, Xiao-Dong; Shen, Xiao-Ting; Zhang, Yan-Zhen

To address the controversial issue of the toxicity of dental alloys and silver nanoparticles in medical applications, an in vivo-like LO2 3-D model was constructed within polyvinylidene fluoride hollow fiber materials to mimic the microenvironment of liver tissue. The use of microscopy methods and the measurement of liver-specific functions optimized the model for best cell performances and also proved the superiority of the 3-D LO2 model when compared with the traditional monolayer model. Toxicity tests were conducted using the newly constructed model, finding that four dental castings coated with silver nanoparticles were toxic to human hepatocytes after cell viability assays. In general, the toxicity of both the castings and the coated silver nanoparticles aggravated as time increased, yet the nanoparticles attenuated the general toxicity by preventing metal ion release, especially at high concentrations.

Optimization of gene delivery methods in Xenopus laevis kidney (A6) and Chinese hamster ovary (CHO) cell lines for heterologous expression of Xenopus inner ear genes

PubMed Central

Ramirez-Gordillo, Daniel; Trujillo-Provencio, Casilda; Knight, V. Bleu; Serrano, Elba E.

2014-01-01

The Xenopus inner ear provides a useful model for studies of hearing and balance because it shares features with the mammalian inner ear, and because amphibians are capable of regenerating damaged mechanosensory hair cells. The structure and function of many proteins necessary for inner ear function have yet to be elucidated and require methods for analysis. To this end, we seek to characterize Xenopus inner ear genes outside of the animal model through heterologous expression in cell lines. As part of this effort, we aimed to optimize physical (electroporation), chemical (lipid-mediated; Lipofectamine™ 2000, Metafectene® Pro), and biological (viral-mediated; BacMam virus Cellular Lights™ Tubulin-RFP) gene delivery methods in amphibian (Xenopus; A6) cells and mammalian (Chinese hamster ovary (CHO)) cells. We successfully introduced the commercially available pEGFP-N3, pmCherry-N1, pEYFP-Tubulin, and Cellular Lights™ Tubulin-RFP fluorescent constructs to cells and evaluated their transfection or transduction efficiencies using the three gene delivery methods. In addition, we analyzed the transfection efficiency of a novel construct synthesized in our laboratory by cloning the Xenopus inner ear calcium-activated potassium channel β1 subunit, then subcloning the subunit into the pmCherry-N1 vector. Every gene delivery method was significantly more effective in CHO cells. Although results for the A6 cell line were not statistically significant, both cell lines illustrate a trend towards more efficient gene delivery using viral-mediated methods; however the cost of viral transduction is also much higher. Our findings demonstrate the need to improve gene delivery methods for amphibian cells and underscore the necessity for a greater understanding of amphibian cell biology. PMID:21959846

The stability of colorectal cancer mathematical models

NASA Astrophysics Data System (ADS)

Khairudin, Nur Izzati; Abdullah, Farah Aini

2013-04-01

Colorectal cancer is one of the most common types of cancer. To better understand about the kinetics of cancer growth, mathematical models are used to provide insight into the progression of this natural process which enables physicians and oncologists to determine optimal radiation and chemotherapy schedules and develop a prognosis, both of which are indispensable for treating cancer. This thesis investigates the stability of colorectal cancer mathematical models. We found that continuous saturating feedback is the best available model of colorectal cancer growth. We also performed stability analysis. The result shows that cancer progress in sequence of genetic mutations or epigenetic which lead to a very large number of cells population until become unbounded. The cell population growth initiate and its saturating feedback is overcome when mutation changes causing the net per-capita growth rate of stem or transit cells exceed critical threshold.

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

PubMed

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Toward “optimal” integration of terrestrial biosphere models

DOE PAGES

Schwalm, Christopher R.; Huntzinger, Deborah N.; Fisher, Joshua B.; ...

2015-06-10

Multimodel ensembles (MME) are commonplace in Earth system modeling. Here we perform MME integration using a 10-member ensemble of terrestrial biosphere models (TBMs) from the Multiscale synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We contrast optimal (skill based for present-day carbon cycling) versus naive (one model-one vote) integration. MsTMIP optimal and naive mean land sink strength estimates (-1.16 versus -1.15 Pg C per annum respectively) are statistically indistinguishable. This holds also for grid cell values and extends to gross uptake, biomass, and net ecosystem productivity. TBM skill is similarly indistinguishable. The added complexity of skill-based integration does not materially changemore » MME values. This suggests that carbon metabolism has predictability limits and/or that all models and references are misspecified. Finally, resolving this issue requires addressing specific uncertainty types (initial conditions, structure, and references) and a change in model development paradigms currently dominant in the TBM community.« less

Cell-free protein synthesis in micro compartments: building a minimal cell from biobricks.

PubMed

Jia, Haiyang; Heymann, Michael; Bernhard, Frank; Schwille, Petra; Kai, Lei

2017-10-25

The construction of a minimal cell that exhibits the essential characteristics of life is a great challenge in the field of synthetic biology. Assembling a minimal cell requires multidisciplinary expertise from physics, chemistry and biology. Scientists from different backgrounds tend to define the essence of 'life' differently and have thus proposed different artificial cell models possessing one or several essential features of living cells. Using the tools and methods of molecular biology, the bottom-up engineering of a minimal cell appears in reach. However, several challenges still remain. In particular, the integration of individual sub-systems that is required to achieve a self-reproducing cell model presents a complex optimization challenge. For example, multiple self-organisation and self-assembly processes have to be carefully tuned. We review advances and developments of new methods and techniques, for cell-free protein synthesis as well as micro-fabrication, for their potential to resolve challenges and to accelerate the development of minimal cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Emerging In Vitro Liver Technologies for Drug Metabolism and Inter-Organ Interactions

PubMed Central

Bale, Shyam Sundhar; Moore, Laura

2016-01-01

In vitro liver models provide essential information for evaluating drug metabolism, metabolite formation, and hepatotoxicity. Interfacing liver models with other organ models could provide insights into the desirable as well as unintended systemic side effects of therapeutic agents and their metabolites. Such information is invaluable for drug screening processes particularly in the context of secondary organ toxicity. While interfacing of liver models with other organ models has been achieved, platforms that effectively provide human-relevant precise information are needed. In this concise review, we discuss the current state-of-the-art of liver-based multiorgan cell culture platforms primarily from a drug and metabolite perspective, and highlight the importance of media-to-cell ratio in interfacing liver models with other organ models. In addition, we briefly discuss issues related to development of optimal liver models that include recent advances in hepatic cell lines, stem cells, and challenges associated with primary hepatocyte-based liver models. Liver-based multiorgan models that achieve physiologically relevant coupling of different organ models can have a broad impact in evaluating drug efficacy and toxicity, as well as mechanistic investigation of human-relevant disease conditions. PMID:27049038

Evolving cell models for systems and synthetic biology.

PubMed

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.

A stepwise approach for the reproducible optimization of PAMO expression in Escherichia coli for whole-cell biocatalysis

PubMed Central

2012-01-01

Background Baeyer-Villiger monooxygenases (BVMOs) represent a group of enzymes of considerable biotechnological relevance as illustrated by their growing use as biocatalyst in a variety of synthetic applications. However, due to their increased use the reproducible expression of BVMOs and other biotechnologically relevant enzymes has become a pressing matter while knowledge about the factors governing their reproducible expression is scattered. Results Here, we have used phenylacetone monooxygenase (PAMO) from Thermobifida fusca, a prototype Type I BVMO, as a model enzyme to develop a stepwise strategy to optimize the biotransformation performance of recombinant E. coli expressing PAMO in 96-well microtiter plates in a reproducible fashion. Using this system, the best expression conditions of PAMO were investigated first, including different host strains, temperature as well as time and induction period for PAMO expression. This optimized system was used next to improve biotransformation conditions, the PAMO-catalyzed conversion of phenylacetone, by evaluating the best electron donor, substrate concentration, and the temperature and length of biotransformation. Combining all optimized parameters resulted in a more than four-fold enhancement of the biocatalytic performance and, importantly, this was highly reproducible as indicated by the relative standard deviation of 1% for non-washed cells and 3% for washed cells. Furthermore, the optimized procedure was successfully adapted for activity-based mutant screening. Conclusions Our optimized procedure, which provides a comprehensive overview of the key factors influencing the reproducible expression and performance of a biocatalyst, is expected to form a rational basis for the optimization of miniaturized biotransformations and for the design of novel activity-based screening procedures suitable for BVMOs and other NAD(P)H-dependent enzymes as well. PMID:22720747

Proton exchange membrane fuel cell model for aging predictions: Simulated equivalent active surface area loss and comparisons with durability tests

NASA Astrophysics Data System (ADS)

Robin, C.; Gérard, M.; Quinaud, M.; d'Arbigny, J.; Bultel, Y.

2016-09-01

The prediction of Proton Exchange Membrane Fuel Cell (PEMFC) lifetime is one of the major challenges to optimize both material properties and dynamic control of the fuel cell system. In this study, by a multiscale modeling approach, a mechanistic catalyst dissolution model is coupled to a dynamic PEMFC cell model to predict the performance loss of the PEMFC. Results are compared to two 2000-h experimental aging tests. More precisely, an original approach is introduced to estimate the loss of an equivalent active surface area during an aging test. Indeed, when the computed Electrochemical Catalyst Surface Area profile is fitted on the experimental measures from Cyclic Voltammetry, the computed performance loss of the PEMFC is underestimated. To be able to predict the performance loss measured by polarization curves during the aging test, an equivalent active surface area is obtained by a model inversion. This methodology enables to successfully find back the experimental cell voltage decay during time. The model parameters are fitted from the polarization curves so that they include the global degradation. Moreover, the model captures the aging heterogeneities along the surface of the cell observed experimentally. Finally, a second 2000-h durability test in dynamic operating conditions validates the approach.

Rejuvenating Strategies for Stem Cell-based Therapies in Aging

PubMed Central

Neves, Joana; Sousa-Victor, Pedro; Jasper, Heinrich

2017-01-01

SUMMARY Recent advances in our understanding of tissue regeneration and the development of efficient approaches to induce and differentiate pluripotent stem cells for cell replacement therapies promise exciting avenues for treating degenerative age-related diseases. However, clinical studies and insights from model organisms have identified major roadblocks that normal aging processes impose on tissue regeneration. These new insights suggest that specific targeting of environmental niche components, including growth factors, ECM and immune cells, and intrinsic stem cell properties that are affected by aging will be critical for development of new strategies to improve stem cell function and optimize tissue repair processes. PMID:28157498

Algorithms for optimization of the transport system in living and artificial cells.

PubMed

Melkikh, A V; Sutormina, M I

2011-06-01

An optimization of the transport system in a cell has been considered from the viewpoint of the operations research. Algorithms for an optimization of the transport system of a cell in terms of both the efficiency and a weak sensitivity of a cell to environmental changes have been proposed. The switching of various systems of transport is considered as the mechanism of weak sensitivity of a cell to changes in environment. The use of the algorithms for an optimization of a cardiac cell has been considered by way of example. We received theoretically for a cell of a cardiac muscle that at the increase of potassium concentration in the environment switching of transport systems for this ion takes place. This conclusion qualitatively coincides with experiments. The problem of synthesizing an optimal system in an artificial cell has been stated.

Pattern formations and optimal packing.

PubMed

Mityushev, Vladimir

2016-04-01

Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary value problems. We demonstrate an intimate connection between pattern formations and optimal random packing on the plane. The main study is based on the following two points. First, the diffusive flux in reaction-diffusion systems is approximated by piecewise linear functions in the framework of structural approximations. This leads to a discrete network approximation of the considered continuous problem. Second, the discrete energy minimization yields optimal random packing of the domains (disks) in the representative cell. Therefore, the general problem of pattern formations based on the reaction-diffusion equations is reduced to the geometric problem of random packing. It is demonstrated that all random packings can be divided onto classes associated with classes of isomorphic graphs obtained from the Delaunay triangulation. The unique optimal solution is constructed in each class of the random packings. If the number of disks per representative cell is finite, the number of classes of isomorphic graphs, hence, the number of optimal packings is also finite. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving Embryonic Stem Cell Expansion through the Combination of Perfusion and Bioprocess Model Design

PubMed Central

Yeo, David; Kiparissides, Alexandros; Cha, Jae Min; Aguilar-Gallardo, Cristobal; Polak, Julia M.; Tsiridis, Elefterios; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

Background High proliferative and differentiation capacity renders embryonic stem cells (ESCs) a promising cell source for tissue engineering and cell-based therapies. Harnessing their potential, however, requires well-designed, efficient and reproducible expansion and differentiation protocols as well as avoiding hazardous by-products, such as teratoma formation. Traditional, standard culture methodologies are fragmented and limited in their fed-batch feeding strategies that afford a sub-optimal environment for cellular metabolism. Herein, we investigate the impact of metabolic stress as a result of inefficient feeding utilizing a novel perfusion bioreactor and a mathematical model to achieve bioprocess improvement. Methodology/Principal Findings To characterize nutritional requirements, the expansion of undifferentiated murine ESCs (mESCs) encapsulated in hydrogels was performed in batch and perfusion cultures using bioreactors. Despite sufficient nutrient and growth factor provision, the accumulation of inhibitory metabolites resulted in the unscheduled differentiation of mESCs and a decline in their cell numbers in the batch cultures. In contrast, perfusion cultures maintained metabolite concentration below toxic levels, resulting in the robust expansion (>16-fold) of high quality ‘naïve’ mESCs within 4 days. A multi-scale mathematical model describing population segregated growth kinetics, metabolism and the expression of selected pluripotency (‘stemness’) genes was implemented to maximize information from available experimental data. A global sensitivity analysis (GSA) was employed that identified significant (6/29) model parameters and enabled model validation. Predicting the preferential propagation of undifferentiated ESCs in perfusion culture conditions demonstrates synchrony between theory and experiment. Conclusions/Significance The limitations of batch culture highlight the importance of cellular metabolism in maintaining pluripotency, which necessitates the design of suitable ESC bioprocesses. We propose a novel investigational framework that integrates a novel perfusion culture platform (controlled metabolic conditions) with mathematical modeling (information maximization) to enhance ESC bioprocess productivity and facilitate bioprocess optimization. PMID:24339957

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium tuberculosis Drug Discovery

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Hobrath, Judith V.; White, E. Lucile; Reynolds, Robert C

2013-01-01

Purpose Tuberculosis treatments need to be shorter and overcome drug resistance. Our previous large scale phenotypic high-throughput screening against Mycobacterium tuberculosis (Mtb) has identified 737 active compounds and thousands that are inactive. We have used this data for building computational models as an approach to minimize the number of compounds tested. Methods A cheminformatics clustering approach followed by Bayesian machine learning models (based on publicly available Mtb screening data) was used to illustrate that application of these models for screening set selections can enrich the hit rate. Results In order to explore chemical diversity around active cluster scaffolds of the dose-response hits obtained from our previous Mtb screens a set of 1924 commercially available molecules have been selected and evaluated for antitubercular activity and cytotoxicity using Vero, THP-1 and HepG2 cell lines with 4.3%, 4.2% and 2.7% hit rates, respectively. We demonstrate that models incorporating antitubercular and cytotoxicity data in Vero cells can significantly enrich the selection of non-toxic actives compared to random selection. Across all cell lines, the Molecular Libraries Small Molecule Repository (MLSMR) and cytotoxicity model identified ~10% of the hits in the top 1% screened (>10 fold enrichment). We also showed that seven out of nine Mtb active compounds from different academic published studies and eight out of eleven Mtb active compounds from a pharmaceutical screen (GSK) would have been identified by these Bayesian models. Conclusion Combining clustering and Bayesian models represents a useful strategy for compound prioritization and hit-to lead optimization of antitubercular agents. PMID:24132686

Optimization of lipids' ultrasonic extraction and production from Chlorella sp. using response-surface methodology.

PubMed

Hadrich, Bilel; Akremi, Ismahen; Dammak, Mouna; Barkallah, Mohamed; Fendri, Imen; Abdelkafi, Slim

2018-04-17

Three steps are very important in order to produce microalgal lipids: (1) controlling microalgae cultivation via experimental and modeling investigations, (2) optimizing culture conditions to maximize lipids production and to determine the fatty acid profile the most appropriate for biodiesel synthesis, and (3) optimizing the extraction of the lipids accumulated in the microalgal cells. Firstly, three kinetics models, namely logistic, logistic-with-lag and modified Gompertz, were tested to fit the experimental kinetics of the Chlorella sp. microalga culture established on standard conditions. Secondly, the response-surface methodology was used for two optimizations in this study. The first optimization was established for lipids production from Chlorella sp. culture under different culture conditions. In fact, different levels of nitrate concentrations, salinities and light intensities were applied to the culture medium in order to study their influences on lipids production and determine their fatty acid profile. The second optimization was concerned with the lipids extraction factors: ultrasonic's time and temperature, and chloroform-methanol solvent ratio. All models (logistic, logistic-with-lag and modified Gompertz) applied for the experimental kinetics of Chlorella sp. show a very interesting fitting quality. The logistic model was chosen to describe the Chlorella sp. kinetics, since it yielded the most important statistical criteria: coefficient of determination of the order of 94.36%; adjusted coefficient of determination equal to 93.79% and root mean square error reaching 3.685 cells · ml - 1 . Nitrate concentration and the two interactions involving the light intensity (Nitrate concentration × light intensity, and salinities × light intensity) showed a very significant influence on lipids production in the first optimization (p < 0.05). Yet, only the quadratic term of chloroform-methanol solvent ratio showed a significant influence on lipids extraction relative to the second step of optimization (p < 0.05). The two most abundant fatty acid methyl esters (≈72%) derived from the Chlorella sp. microalga cultured in the determined optimal conditions are: palmitic acid (C16:0) and oleic acid (C18:1) with the corresponding yields of 51.69% and 20.55% of total fatty acids, respectively. Only the nitrate deficiency and the high intensity of light can influence the microalgal lipids production. The corresponding fatty acid methyl esters composition is very suitable for biodiesel production. Lipids extraction is efficient only over long periods of time when using a solvent with a 2/1 chloroform/methanol ratio.

Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised?

PubMed

André, Silvère; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-03-01

In recent years, as a result of the process analytical technology initiative of the US Food and Drug Administration, many different works have been carried out on direct and in situ monitoring of critical parameters for mammalian cell cultures by Raman spectroscopy and multivariate regression techniques. However, despite interesting results, it cannot be said that the proposed monitoring strategies, which will reduce errors of the regression models and thus confidence limits of the predictions, are really optimized. Hence, the aim of this article is to optimize some critical steps of spectroscopic acquisition and data treatment in order to reach a higher level of accuracy and robustness of bioprocess monitoring. In this way, we propose first an original strategy to assess the most suited Raman acquisition time for the processes involved. In a second part, we demonstrate the importance of the interbatch variability on the accuracy of the predictive models with a particular focus on the optical probes adjustment. Finally, we propose a methodology for the optimization of the spectral variables selection in order to decrease prediction errors of multivariate regressions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:308-316, 2017. © 2017 American Institute of Chemical Engineers.

Model-based optimization of G-CSF treatment during cytotoxic chemotherapy.

PubMed

Schirm, Sibylle; Engel, Christoph; Loibl, Sibylle; Loeffler, Markus; Scholz, Markus

2018-02-01

Although G-CSF is widely used to prevent or ameliorate leukopenia during cytotoxic chemotherapies, its optimal use is still under debate and depends on many therapy parameters such as dosing and timing of cytotoxic drugs and G-CSF, G-CSF pharmaceuticals used and individual risk factors of patients. We integrate available biological knowledge and clinical data regarding cell kinetics of bone marrow granulopoiesis, the cytotoxic effects of chemotherapy and pharmacokinetics and pharmacodynamics of G-CSF applications (filgrastim or pegfilgrastim) into a comprehensive model. The model explains leukocyte time courses of more than 70 therapy scenarios comprising 10 different cytotoxic drugs. It is applied to develop optimized G-CSF schedules for a variety of clinical scenarios. Clinical trial results showed validity of model predictions regarding alternative G-CSF schedules. We propose modifications of G-CSF treatment for the chemotherapies 'BEACOPP escalated' (Hodgkin's disease), 'ETC' (breast cancer), and risk-adapted schedules for 'CHOP-14' (aggressive non-Hodgkin's lymphoma in elderly patients). We conclude that we established a model of human granulopoiesis under chemotherapy which allows predictions of yet untested G-CSF schedules, comparisons between them, and optimization of filgrastim and pegfilgrastim treatment. As a general rule of thumb, G-CSF treatment should not be started too early and patients could profit from filgrastim treatment continued until the end of the chemotherapy cycle.

A sigmoidal model for biosorption of heavy metal cations from aqueous media.

PubMed

Özen, Rümeysa; Sayar, Nihat Alpagu; Durmaz-Sam, Selcen; Sayar, Ahmet Alp

2015-07-01

A novel multi-input single output (MISO) black-box sigmoid model is developed to simulate the biosorption of heavy metal cations by the fission yeast from aqueous medium. Validation and verification of the model is done through statistical chi-squared hypothesis tests and the model is evaluated by uncertainty and sensitivity analyses. The simulated results are in agreement with the data of the studied system in which Schizosaccharomyces pombe biosorbs Ni(II) cations at various process conditions. Experimental data is obtained originally for this work using dead cells of an adapted variant of S. Pombe and represented by Freundlich isotherms. A process optimization scheme is proposed using the present model to build a novel application of a cost-merit objective function which would be useful to predict optimal operation conditions. Copyright © 2015. Published by Elsevier Inc.

Mathematical modeling in chronobiology.

PubMed

Bordyugov, G; Westermark, P O; Korenčič, A; Bernard, S; Herzel, H

2013-01-01

Circadian clocks are autonomous oscillators entrained by external Zeitgebers such as light-dark and temperature cycles. On the cellular level, rhythms are generated by negative transcriptional feedback loops. In mammals, the suprachiasmatic nucleus (SCN) in the anterior part of the hypothalamus plays the role of the central circadian pacemaker. Coupling between individual neurons in the SCN leads to precise self-sustained oscillations even in the absence of external signals. These neuronal rhythms orchestrate the phasing of circadian oscillations in peripheral organs. Altogether, the mammalian circadian system can be regarded as a network of coupled oscillators. In order to understand the dynamic complexity of these rhythms, mathematical models successfully complement experimental investigations. Here we discuss basic ideas of modeling on three different levels (1) rhythm generation in single cells by delayed negative feedbacks, (2) synchronization of cells via external stimuli or cell-cell coupling, and (3) optimization of chronotherapy.

Optimizing neuronal differentiation from induced pluripotent stem cells to model ASD

PubMed Central

Kim, Dae-Sung; Ross, P. Joel; Zaslavsky, Kirill; Ellis, James

2014-01-01

Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder characterized by deficits in social communication, and restricted and repetitive patterns of behavior. Despite its high prevalence, discovery of pathophysiological mechanisms underlying ASD has lagged due to a lack of appropriate model systems. Recent advances in induced pluripotent stem cell (iPSC) technology and neural differentiation techniques allow for detailed functional analyses of neurons generated from living individuals with ASD. Refinement of cortical neuron differentiation methods from iPSCs will enable mechanistic studies of specific neuronal subpopulations that may be preferentially impaired in ASD. In this review, we summarize recent accomplishments in differentiation of cortical neurons from human pluripotent stems cells and efforts to establish in vitro model systems to study ASD using personalized neurons. PMID:24782713

Rapamycin and CHIR99021 Coordinate Robust Cardiomyocyte Differentiation From Human Pluripotent Stem Cells Via Reducing p53-Dependent Apoptosis.

PubMed

Qiu, Xiao-Xu; Liu, Yang; Zhang, Yi-Fan; Guan, Ya-Na; Jia, Qian-Qian; Wang, Chen; Liang, He; Li, Yong-Qin; Yang, Huang-Tian; Qin, Yong-Wen; Huang, Shuang; Zhao, Xian-Xian; Jing, Qing

2017-10-02

Cardiomyocytes differentiated from human pluripotent stem cells can serve as an unexhausted source for a cellular cardiac disease model. Although small molecule-mediated cardiomyocyte differentiation methods have been established, the differentiation efficiency is relatively unsatisfactory in multiple lines due to line-to-line variation. Additionally, hurdles including line-specific low expression of endogenous growth factors and the high apoptotic tendency of human pluripotent stem cells also need to be overcome to establish robust and efficient cardiomyocyte differentiation. We used the H9-human cardiac troponin T-eGFP reporter cell line to screen for small molecules that promote cardiac differentiation in a monolayer-based and growth factor-free differentiation model. We found that collaterally treating human pluripotent stem cells with rapamycin and CHIR99021 during the initial stage was essential for efficient and reliable cardiomyocyte differentiation. Moreover, this method maintained consistency in efficiency across different human embryonic stem cell and human induced pluripotent stem cell lines without specifically optimizing multiple parameters (the efficiency in H7, H9, and UQ1 human induced pluripotent stem cells is 98.3%, 93.3%, and 90.6%, respectively). This combination also increased the yield of cardiomyocytes (1:24) and at the same time reduced medium consumption by about 50% when compared with the previous protocols. Further analysis indicated that inhibition of the mammalian target of rapamycin allows efficient cardiomyocyte differentiation through overcoming p53-dependent apoptosis of human pluripotent stem cells during high-density monolayer culture via blunting p53 translation and mitochondrial reactive oxygen species production. We have demonstrated that mammalian target of rapamycin exerts a stage-specific and multifaceted regulation over cardiac differentiation and provides an optimized approach for generating large numbers of functional cardiomyocytes for disease modeling and in vitro drug screening. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

The Influence of Soft Layer Electrokinetics on Electroporation of Gram-positive Bacteria

NASA Astrophysics Data System (ADS)

Dingari, Naga Neehar; Moran, Jeffrey L.; Garcia, Paulo A.; Buie, Cullen R.

2016-11-01

Bacterial electroporation involves subjecting cells to intense ( 10 kV/cm) electric pulses, to open pores on the cell membrane for intracellular delivery of exogenous molecules. Its high efficiency in genetic transformation makes it an attractive tool for synthetic biology. While mammalian cell electroporation has received extensive theoretical and experimental investigation, bacterial electroporation has received markedly less attention. In this work, we develop a theoretical model of electroporation for gram-positive bacteria, taking into account the effect of the bacterial cell envelope on the cell's response to an electroporation pulse. We model the influence of the cell wall charge on the electrokinetic transport (and hence the pore properties) around the bacterial cell envelope using the Poisson-Nernst-Planck equations. Further, we account for the influence of the cell wall's mechanical elasticity on the pore radius evolution during electroporation, which is typically neglected in mammalian cell electroporation. This yields valuable information about favorable conditions for pore formation and will enable designing optimal platforms for bacteria electroporation.

The use of real-time cell analyzer technology in drug discovery: defining optimal cell culture conditions and assay reproducibility with different adherent cellular models.

PubMed

Atienzar, Franck A; Tilmant, Karen; Gerets, Helga H; Toussaint, Gaelle; Speeckaert, Sebastien; Hanon, Etienne; Depelchin, Olympe; Dhalluin, Stephane

2011-07-01

The use of impedance-based label-free technology applied to drug discovery is nowadays receiving more and more attention. Indeed, such a simple and noninvasive assay that interferes minimally with cell morphology and function allows one to perform kinetic measurements and to obtain information on proliferation, migration, cytotoxicity, and receptor-mediated signaling. The objective of the study was to further assess the usefulness of a real-time cell analyzer (RTCA) platform based on impedance in the context of quality control and data reproducibility. The data indicate that this technology is useful to determine the best coating and cellular density conditions for different adherent cellular models including hepatocytes, cardiomyocytes, fibroblasts, and hybrid neuroblastoma/neuronal cells. Based on 31 independent experiments, the reproducibility of cell index data generated from HepG2 cells exposed to DMSO and to Triton X-100 was satisfactory, with a coefficient of variation close to 10%. Cell index data were also well reproduced when cardiomyocytes and fibroblasts were exposed to 21 compounds three times (correlation >0.91, p < 0.0001). The data also show that a cell index decrease is not always associated with cytotoxicity effects and that there are some confounding factors that can affect the analysis. Finally, another drawback is that the correlation analysis between cellular impedance measurements and classical toxicity endpoints has been performed on a limited number of compounds. Overall, despite some limitations, the RTCA technology appears to be a powerful and reliable tool in drug discovery because of the reasonable throughput, rapid and efficient performance, technical optimization, and cell quality control.

Validation of a Candida albicans delayed-type hypersensitivity (DTH) model in female juvenile rats for use in immunotoxicity assessments.

PubMed

Collinge, Mark; Thorn, Mitchell; Peachee, Vanessa; White, Kimber

2013-01-01

Establishing an in vivo cell-mediated immunity (CMI) assay, such as the delayed-type hypersensitivity (DTH) assay, has been identified as an important gap and recommended to receive highest priority for new model development in several workshops on developmental immunotoxicity. A Candida albicans DTH model has recently been developed that has the advantage over other DTH models, which use alternative sensitizing antigens, in that antigen-specific antibodies, which may interfere with the assay, are not produced. In addition, the in vivo C. albicans DTH model was demonstrated to be more sensitive in detecting immunosuppression than DTH models using keyhole limpet hemocyanin (KLH) or sheep red blood cells as antigens, as well as some ex vivo CMI assays. While KLH and sheep red blood cells are non-physiological immunogens, C. albicans is an important human pathogen. The present studies were conducted in order to optimize and validate the C. albicans DTH model for use in developmental immunotoxicity studies using juvenile rats. Three known immunosuppressive compounds with different mechanisms of action were tested in this model, cyclosprorin A (CsA), cyclophosphamide (CPS), and dexamethasone (DEX). Animals were sensitized with formalin-fixed C. albicans on postnatal day (PND) 28 and challenged with chitosan on PND 38. Drug was administered beginning on PND 23 and continued until PND 37. Exposure to each of the three immunotoxicants resulted in statistically significant decreases in the DTH response to C. albicans-derived chitosan. Decreases in footpad swelling were observed at ≥10 mg CsA/kg/day, ≥5 mg CPS/kg/day, and ≥0.03 mg DEX/kg/day. These results demonstrate that the C. albicans DTH model, optimized for use in juvenile rats, can be used to identify immunotoxic compounds, and fills the need for a sensitive in vivo CMI model for assessments of developmental immunotoxicity. Abbreviations Ab, antibody APC, antigen presenting cell BSA, bovine serum albumin C. albicans, Candida albicans CI, challenge interval CMI, cell-mediated immunity CO, challenge only CPS, cyclophosphamide CsA, cyclosporin A CTL, cytotoxic T lymphocyte DEX, dexamethasone DIT, developmental immunotoxicity DTH, delayed-type hypersensitivity ip, intraperitoneal KLH, keyhole limpet hemocyanin MLR, mixed lymphocyte reaction OVA, ovalbumin PBS, phosphate-buffered saline PND, postnatal day sc, subcutaneous SEM, standard error of the mean SRBC, sheep red blood cells.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Hyperglycaemia attenuates in vivo reprogramming of pancreatic exocrine cells to beta cells in mice

PubMed Central

Cavelti-Weder, Claudia; Li, Weida; Zumsteg, Adrian; Stemann-Andersen, Marianne; Zhang, Yuemei; Yamada, Takatsugu; Wang, Max; Lu, Jiaqi; Jermendy, Agnes; Bee, Yong Mong; Bonner-Weir, Susan; Weir, Gordon C.; Zhou, Qiao

2016-01-01

Aims/hypothesis Reprogramming of pancreatic exocrine to insulin-producing cells by viral delivery of the genes encoding transcription factors neurogenin-3 (Ngn3), pancreas/duodenum homeobox protein 1 (Pdx1) and MafA is an efficient method for reversing diabetes in murine models. The variables that modulate reprogramming success are currently ill-defined. Methods Here, we assess the impact of glycaemia on in vivo reprogramming in a mouse model of streptozotocin-induced beta cell ablation, using subsequent islet transplantation or insulin pellet implantation for creation of groups with differing levels of glycaemia before viral delivery of transcription factors. Results We observed that hyperglycaemia significantly impaired reprogramming of exocrine to insulin-producing cells in their quantity, differentiation status and function. With hyperglycaemia, the reprogramming of acinar towards beta cells was less complete. Moreover, inflammatory tissue changes within the exocrine pancreas including macrophage accumulation were found, which may represent the tissue’s response to clear the pancreas from insufficiently reprogrammed cells. Conclusions/interpretation Our findings shed light on normoglycaemia as a prerequisite for optimal reprogramming success in a diabetes model, which might be important in other tissue engineering approaches and disease models, potentially facilitating their translational applications. PMID:26693711

Hyperglycaemia attenuates in vivo reprogramming of pancreatic exocrine cells to beta cells in mice.

PubMed

Cavelti-Weder, Claudia; Li, Weida; Zumsteg, Adrian; Stemann-Andersen, Marianne; Zhang, Yuemei; Yamada, Takatsugu; Wang, Max; Lu, Jiaqi; Jermendy, Agnes; Bee, Yong Mong; Bonner-Weir, Susan; Weir, Gordon C; Zhou, Qiao

2016-03-01

Reprogramming of pancreatic exocrine to insulin-producing cells by viral delivery of the genes encoding transcription factors neurogenin-3 (Ngn3), pancreas/duodenum homeobox protein 1 (Pdx1) and MafA is an efficient method for reversing diabetes in murine models. The variables that modulate reprogramming success are currently ill-defined. Here, we assess the impact of glycaemia on in vivo reprogramming in a mouse model of streptozotocin-induced beta cell ablation, using subsequent islet transplantation or insulin pellet implantation for creation of groups with differing levels of glycaemia before viral delivery of transcription factors. We observed that hyperglycaemia significantly impaired reprogramming of exocrine to insulin-producing cells in their quantity, differentiation status and function. With hyperglycaemia, the reprogramming of acinar towards beta cells was less complete. Moreover, inflammatory tissue changes within the exocrine pancreas including macrophage accumulation were found, which may represent the tissue's response to clear the pancreas from insufficiently reprogrammed cells. Our findings shed light on normoglycaemia as a prerequisite for optimal reprogramming success in a diabetes model, which might be important in other tissue engineering approaches and disease models, potentially facilitating their translational applications.

The Bi-Directional Prediction of Carbon Fiber Production Using a Combination of Improved Particle Swarm Optimization and Support Vector Machine.

PubMed

Xiao, Chuncai; Hao, Kuangrong; Ding, Yongsheng

2014-12-30

This paper creates a bi-directional prediction model to predict the performance of carbon fiber and the productive parameters based on a support vector machine (SVM) and improved particle swarm optimization (IPSO) algorithm (SVM-IPSO). In the SVM, it is crucial to select the parameters that have an important impact on the performance of prediction. The IPSO is proposed to optimize them, and then the SVM-IPSO model is applied to the bi-directional prediction of carbon fiber production. The predictive accuracy of SVM is mainly dependent on its parameters, and IPSO is thus exploited to seek the optimal parameters for SVM in order to improve its prediction capability. Inspired by a cell communication mechanism, we propose IPSO by incorporating information of the global best solution into the search strategy to improve exploitation, and we employ IPSO to establish the bi-directional prediction model: in the direction of the forward prediction, we consider productive parameters as input and property indexes as output; in the direction of the backward prediction, we consider property indexes as input and productive parameters as output, and in this case, the model becomes a scheme design for novel style carbon fibers. The results from a set of the experimental data show that the proposed model can outperform the radial basis function neural network (RNN), the basic particle swarm optimization (PSO) method and the hybrid approach of genetic algorithm and improved particle swarm optimization (GA-IPSO) method in most of the experiments. In other words, simulation results demonstrate the effectiveness and advantages of the SVM-IPSO model in dealing with the problem of forecasting.

Organizing principles underlying microorganism's growth-robustness trade-off.

PubMed

Bolli, Alessandro; Salvador, Armindo

2014-10-01

Growth Robustness Reciprocity (GRR) is an intriguing microbial manifestation: the impairment of microorganism's growth enhances their ability to resist acute stresses, and vice-versa. This is caused by regulatory interactions that determine higher expression of protection mechanisms in response to low growth rates. But because such regulatory mechanisms are species-specific, GRR must result from convergent evolution. Why does natural selection favor such an outcome? We used mathematical models of optimal cellular resource allocation to identify the general principles underlying GRR. Non-linear optimization allowed to predict allocation patterns of biosynthetic resources (ribosomes devoted to the synthesis of each cell component) that maximize growth. These models predict the down-regulation of stress defenses under high substrate availabilities and low stress levels. Under these conditions, stress tolerance ensues from growth-related damage dilution: the higher the substrate availability, the fastest the dilution of damaged proteins by newly synthesized proteins, the lower the accumulation of damaged components into the cell. In turn, under low substrate availability growth is too slow for effective damage dilution, and the expression of the defenses up to some optimal level then increases growth. As a consequence, slow-growing cells are pre-adapted to withstand acute stresses. Therefore, the observed negative correlation between growth and stress tolerance can be explained as a consequence of optimal resource allocation for maximal growth. We acknowledge fellowship SFRH/BPD/90065/2012 and grants PEst-C/SAU/LA0001/2013-2014 and FCOMP-01-0124-FEDER-020978 financed by FEDER through the "Programa Operacional Factores de Competitividade, COMPETE" and by national funds through "FCT, Fundação para a Ciência e a Tecnologia" (project PTDC/QUI-BIQ/119657/2010). Copyright © 2014. Published by Elsevier Inc.

A Study of the Optimal Model of the Flotation Kinetics of Copper Slag from Copper Mine BOR

NASA Astrophysics Data System (ADS)

Stanojlović, Rodoljub D.; Sokolović, Jovica M.

2014-10-01

In this study the effect of mixtures of copper slag and flotation tailings from copper mine Bor, Serbia on the flotation results of copper recovery and flotation kinetics parameters in a batch flotation cell has been investigated. By simultaneous adding old flotation tailings in the ball mill at the rate of 9%, it is possible to increase copper recovery for about 20%. These results are compared with obtained copper recovery of pure copper slag. The results of batch flotation test were fitted by MatLab software for modeling the first-order flotation kinetics in order to determine kinetics parameters and define an optimal model of the flotation kinetics. Six kinetic models are tested on the batch flotation copper recovery against flotation time. All models showed good correlation, however the modified Kelsall model provided the best fit.

Model-based analysis of Arabidopsis leaf epidermal cells reveals distinct division and expansion patterns for pavement and guard cells.

PubMed

Asl, Leila Kheibarshekan; Dhondt, Stijn; Boudolf, Véronique; Beemster, Gerrit T S; Beeckman, Tom; Inzé, Dirk; Govaerts, Willy; De Veylder, Lieven

2011-08-01

To efficiently capture sunlight for photosynthesis, leaves typically develop into a flat and thin structure. This development is driven by cell division and expansion, but the individual contribution of these processes is currently unknown, mainly because of the experimental difficulties to disentangle them in a developing organ, due to their tight interconnection. To circumvent this problem, we built a mathematic model that describes the possible division patterns and expansion rates for individual epidermal cells. This model was used to fit experimental data on cell numbers and sizes obtained over time intervals of 1 d throughout the development of the first leaf pair of Arabidopsis (Arabidopsis thaliana). The parameters were obtained by a derivative-free optimization method that minimizes the differences between the predicted and experimentally observed cell size distributions. The model allowed us to calculate probabilities for a cell to divide into guard or pavement cells, the maximum size at which it can divide, and its average cell division and expansion rates at each point during the leaf developmental process. Surprisingly, average cell cycle duration remained constant throughout leaf development, whereas no evidence for a maximum cell size threshold for cell division of pavement cells was found. Furthermore, the model predicted that neighboring cells of different sizes within the epidermis expand at distinctly different relative rates, which could be verified by direct observations. We conclude that cell division seems to occur independently from the status of cell expansion, whereas the cell cycle might act as a timer rather than as a size-regulated machinery.

Model-Based Analysis of Arabidopsis Leaf Epidermal Cells Reveals Distinct Division and Expansion Patterns for Pavement and Guard Cells1[W][OA

PubMed Central

Asl, Leila Kheibarshekan; Dhondt, Stijn; Boudolf, Véronique; Beemster, Gerrit T.S.; Beeckman, Tom; Inzé, Dirk; Govaerts, Willy; De Veylder, Lieven

2011-01-01

To efficiently capture sunlight for photosynthesis, leaves typically develop into a flat and thin structure. This development is driven by cell division and expansion, but the individual contribution of these processes is currently unknown, mainly because of the experimental difficulties to disentangle them in a developing organ, due to their tight interconnection. To circumvent this problem, we built a mathematic model that describes the possible division patterns and expansion rates for individual epidermal cells. This model was used to fit experimental data on cell numbers and sizes obtained over time intervals of 1 d throughout the development of the first leaf pair of Arabidopsis (Arabidopsis thaliana). The parameters were obtained by a derivative-free optimization method that minimizes the differences between the predicted and experimentally observed cell size distributions. The model allowed us to calculate probabilities for a cell to divide into guard or pavement cells, the maximum size at which it can divide, and its average cell division and expansion rates at each point during the leaf developmental process. Surprisingly, average cell cycle duration remained constant throughout leaf development, whereas no evidence for a maximum cell size threshold for cell division of pavement cells was found. Furthermore, the model predicted that neighboring cells of different sizes within the epidermis expand at distinctly different relative rates, which could be verified by direct observations. We conclude that cell division seems to occur independently from the status of cell expansion, whereas the cell cycle might act as a timer rather than as a size-regulated machinery. PMID:21693673

Thermally coupled moving boundary model for charge-discharge of LiFePO4/C cells

NASA Astrophysics Data System (ADS)

Khandelwal, Ashish; Hariharan, Krishnan S.; Gambhire, Priya; Kolake, Subramanya Mayya; Yeo, Taejung; Doo, Seokgwang

2015-04-01

Optimal thermal management is a key requirement in commercial utilization of lithium ion battery comprising of phase change electrodes. In order to facilitate design of battery packs, thermal management systems and fast charging profiles, a thermally coupled electrochemical model that takes into account the phase change phenomenon is required. In the present work, an electrochemical thermal model is proposed which includes the biphasic nature of phase change electrodes, such as lithium iron phosphate (LFP), via a generalized moving boundary model. The contribution of phase change to the heat released during the cell operation is modeled using an equivalent enthalpy approach. The heat released due to phase transformation is analyzed in comparison with other sources of heat such as reversible, irreversible and ohmic. Detailed study of the thermal behavior of the individual cell components with changing ambient temperature, rate of operation and heat transfer coefficient is carried out. Analysis of heat generation in the various regimes is used to develop cell design and operating guidelines. Further, different charging protocols are analyzed and a model based methodology is suggested to design an efficient quick charging protocol.

Assessment, design and control strategy development of a fuel cell hybrid electric vehicle for CSU's EcoCAR

NASA Astrophysics Data System (ADS)

Fox, Matthew D.

Advanced automotive technology assessment and powertrain design are increasingly performed through modeling, simulation, and optimization. But technology assessments usually target many competing criteria making any individual optimization challenging and arbitrary. Further, independent design simulations and optimizations take considerable time to execute, and design constraints and objectives change throughout the design process. Changes in design considerations usually require re-processing of simulations and more time. In this thesis, these challenges are confronted through CSU's participation in the EcoCAR2 hybrid vehicle design competition. The complexity of the competition's design objectives leveraged development of a decision support system tool to aid in multi-criteria decision making across technologies and to perform powertrain optimization. To make the decision support system interactive, and bypass the problem of long simulation times, a new approach was taken. The result of this research is CSU's architecture selection and component sizing, which optimizes a composite objective function representing the competition score. The selected architecture is an electric vehicle with an onboard range extending hydrogen fuel cell system. The vehicle has a 145kW traction motor, 18.9kWh of lithium ion battery, a 15kW fuel cell system, and 5kg of hydrogen storage capacity. Finally, a control strategy was developed that improves the vehicles performance throughout the driving range under variable driving conditions. In conclusion, the design process used in this research is reviewed and evaluated against other common design methodologies. I conclude, through the highlighted case studies, that the approach is more comprehensive than other popular design methodologies and is likely to lead to a higher quality product. The upfront modeling work and decision support system formulation will pay off in superior and timely knowledge transfer and more informed design decisions. The hypothesis is supported by the three case studies examined in this thesis.

Modeling and simulation of anion-exchange membrane chromatography for purification of Sf9 insect cell-derived virus-like particles.

PubMed

Ladd Effio, Christopher; Hahn, Tobias; Seiler, Julia; Oelmeier, Stefan A; Asen, Iris; Silberer, Christine; Villain, Louis; Hubbuch, Jürgen

2016-01-15

Recombinant protein-based virus-like particles (VLPs) are steadily gaining in importance as innovative vaccines against cancer and infectious diseases. Multiple VLPs are currently evaluated in clinical phases requiring a straightforward and rational process design. To date, there is no generic platform process available for the purification of VLPs. In order to accelerate and simplify VLP downstream processing, there is a demand for novel development approaches, technologies, and purification tools. Membrane adsorbers have been identified as promising stationary phases for the processing of bionanoparticles due to their large pore sizes. In this work, we present the potential of two strategies for designing VLP processes following the basic tenet of 'quality by design': High-throughput experimentation and process modeling of an anion-exchange membrane capture step. Automated membrane screenings allowed the identification of optimal VLP binding conditions yielding a dynamic binding capacity of 5.7 mg/mL for human B19 parvovirus-like particles derived from Spodoptera frugiperda Sf9 insect cells. A mechanistic approach was implemented for radial ion-exchange membrane chromatography using the lumped-rate model and stoichiometric displacement model for the in silico optimization of a VLP capture step. For the first time, process modeling enabled the in silico design of a selective, robust and scalable process with minimal experimental effort for a complex VLP feedstock. The optimized anion-exchange membrane chromatography process resulted in a protein purity of 81.5%, a DNA clearance of 99.2%, and a VLP recovery of 59%. Copyright © 2015 Elsevier B.V. All rights reserved.

Intraoperative Detection of Cell Injury and Cell Death with an 800 nm Near-Infrared Fluorescent Annexin V Derivative

PubMed Central

Ohnishi, Shunsuke; Vanderheyden, Jean-Luc; Tanaka, Eiichi; Patel, Bhavesh; De Grand, Alec; Laurence, Rita G.; Yamashita, Kenichiro; Frangioni, John V.

2008-01-01

The intraoperative detection of cell injury and cell death is fundamental to human surgeries such as organ transplantation and resection. Because of low autofluorescence background and relatively high tissue penetration, invisible light in the 800 nm region provides sensitive detection of disease pathology without changing the appearance of the surgical field. In order to provide surgeons with real-time intraoperative detection of cell injury and death after ischemia/reperfusion (I/R), we have developed a bioactive derivative of human annexin V (annexin800), which fluoresces at 800 nm. Total fluorescence yield, as a function of bioactivity, was optimized in vitro, and final performance was assessed in vivo. In liver, intestine and heart animal models of I/R, an optimal signal to background ratio was obtained 30 min after intravenous injection of annexin800, and histology confirmed concordance between planar reflectance images and actual deep tissue injury. In summary, annexin800 permits sensitive, real-time detection of cell injury and cell death after I/R in the intraoperative setting, and can be used during a variety of surgeries for rapid assessment of tissue and organ status. PMID:16869796

Status of nickel-hydrogen cell technology

NASA Technical Reports Server (NTRS)

Warnock, D. R.

1980-01-01

Nickel hydrogen cell technology has been developed which solves the problems of thermal management, oxygen management, electrolyte management, and electrical and mechanical design peculiar to this new type of battery. This technology was weight optimized for low orbit operation using computer modeling programs but is near optimum for other orbits. Cells ranging in capacity up to about 70 ampere-hours can be made from components of a single standard size and are available from two manufacturers. The knowledge gained is now being applied to the development of two extensions to the basic design: a second set of larger standard components that will cover the capacity range up to 150 ampere-hours; and the development of multicell common pressure vessel modules to reduce volume, cost and weight. A manufacturing technology program is planned to optimize the producibility of the cell design and reduce cost. The most important areas for further improvement are life and reliability which are governed by electrode and separator technology.

Bispecific small molecule-antibody conjugate targeting prostate cancer.

PubMed

Kim, Chan Hyuk; Axup, Jun Y; Lawson, Brian R; Yun, Hwayoung; Tardif, Virginie; Choi, Sei Hyun; Zhou, Quan; Dubrovska, Anna; Biroc, Sandra L; Marsden, Robin; Pinstaff, Jason; Smider, Vaughn V; Schultz, Peter G

2013-10-29

Bispecific antibodies, which simultaneously target CD3 on T cells and tumor-associated antigens to recruit cytotoxic T cells to cancer cells, are a promising new approach to the treatment of hormone-refractory prostate cancer. Here we report a site-specific, semisynthetic method for the production of bispecific antibody-like therapeutics in which a derivative of the prostate-specific membrane antigen-binding small molecule DUPA was selectively conjugated to a mutant αCD3 Fab containing the unnatural amino acid, p-acetylphenylalanine, at a defined site. Homogeneous conjugates were generated in excellent yields and had good solubility. The efficacy of the conjugate was optimized by modifying the linker structure, relative binding orientation, and stoichiometry of the ligand. The optimized conjugate showed potent and selective in vitro activity (EC50 ~ 100 pM), good serum half-life, and potent in vivo activity in prophylactic and treatment xenograft mouse models. This semisynthetic approach is likely to be applicable to the generation of additional bispecific agents using drug-like ligands selective for other cell-surface receptors.

Study of series-connected polymer tandem solar cells based on a highly efficient donor material of PTB7-Th

NASA Astrophysics Data System (ADS)

Zang, Yue; Gao, Xiumin; Xin, Qing; Lin, Jun; Zhao, Jufeng

2017-06-01

A highly efficient donor polymer, PTB7-Th, combined with acceptor fullerene PC71BM was introduced as the subcell in the series-connected tandem devices to achieve high-performance polymer tandem solar cells. Design of the device architecture was investigated using modeling and simulation methods to identify the optimal structure and to predict performance of the tandem cells. To address the challenge of current matching between the constituent subcells, the effect of active layer thickness, different device structure, and use of ultrathin Ag film were analyzed. It was found that the distribution of optical intensity in the tandem structure can be optimized through the optical spacer effect of interfacial layers and micro-cavity effect derived from the embedded ultrathin Ag film. Our results indicate that the efficient light utilization with appropriate subcells can allow achievement of power conversion efficiency of 12%, which can be 25% higher than that of a single cell of PTB7-Th.

Formulation and Optimization of Polymeric Nanoparticles for Intranasal Delivery of Lorazepam Using Box-Behnken Design: In Vitro and In Vivo Evaluation

PubMed Central

Sharma, Deepak; Maheshwari, Dipika; Rana, Ravish; Bhatia, Shanu; Singh, Manisha; Gabrani, Reema; Sharma, Sanjeev K.; Ali, Javed; Sharma, Rakesh Kumar; Dang, Shweta

2014-01-01

The aim of the present study was to optimize lorazepam loaded PLGA nanoparticles (Lzp-PLGA-NPs) by investigating the effect of process variables on the response using Box-Behnken design. Effect of four independent factors, that is, polymer, surfactant, drug, and aqueous/organic ratio, was studied on two dependent responses, that is, z-average and % drug entrapment. Lzp-PLGA-NPs were successfully developed by nanoprecipitation method using PLGA as polymer, poloxamer as surfactant and acetone as organic phase. NPs were characterized for particle size, zeta potential, % drug entrapment, drug release behavior, TEM, and cell viability. Lzp-PLGA-NPs were characterized for drug polymer interaction using FTIR. The developed NPs showed nearly spherical shape with z-average 167–318 d·nm, PDI below 0.441, and −18.4 mV zeta potential with maximum % drug entrapment of 90.1%. In vitro drug release behavior followed Korsmeyer-Peppas model and showed initial burst release of 21.7 ± 1.3% with prolonged drug release of 69.5 ± 0.8% from optimized NPs up to 24 h. In vitro drug release data was found in agreement with ex vivo permeation data through sheep nasal mucosa. In vitro cell viability study on Vero cell line confirmed the safety of optimized NPs. Optimized Lzp-PLGA-NPs were radiolabelled with Technitium-99m for scintigraphy imaging and biodistribution studies in Sprague-Dawley rats to establish nose-to-brain pathway. PMID:25126544

Numerical simulation of proton exchange membrane fuel cells at high operating temperature

NASA Astrophysics Data System (ADS)

Peng, Jie; Lee, Seung Jae

A three-dimensional, single-phase, non-isothermal numerical model for proton exchange membrane (PEM) fuel cell at high operating temperature (T ≥ 393 K) was developed and implemented into a computational fluid dynamic (CFD) code. The model accounts for convective and diffusive transport and allows predicting the concentration of species. The heat generated from electrochemical reactions, entropic heat and ohmic heat arising from the electrolyte ionic resistance were considered. The heat transport model was coupled with the electrochemical and mass transport models. The product water was assumed to be vaporous and treated as ideal gas. Water transportation across the membrane was ignored because of its low water electro-osmosis drag force in the polymer polybenzimidazole (PBI) membrane. The results show that the thermal effects strongly affect the fuel cell performance. The current density increases with the increasing of operating temperature. In addition, numerical prediction reveals that the width and distribution of gas channel and current collector land area are key optimization parameters for the cell performance improvement.

A model for predicting field-directed particle transport in the magnetofection process.

PubMed

Furlani, Edward P; Xue, Xiaozheng

2012-05-01

To analyze the magnetofection process in which magnetic carrier particles with surface-bound gene vectors are attracted to target cells for transfection using an external magnetic field and to obtain a fundamental understanding of the impact of key factors such as particle size and field strength on the gene delivery process. A numerical model is used to study the field-directed transport of the carrier particle-gene vector complex to target cells in a conventional multiwell culture plate system. The model predicts the transport dynamics and the distribution of particle accumulation at the target cells. The impact of several factors that strongly influence gene vector delivery is assessed including the properties of the carrier particles, the strength of the field source, and its extent and proximity relative to the target cells. The study demonstrates that modeling can be used to predict and optimize gene vector delivery in the magnetofection process for novel and conventional in vitro systems.

Reversal of blindness in animal models of leber congenital amaurosis using optimized AAV2-mediated gene transfer.

PubMed

Bennicelli, Jeannette; Wright, John Fraser; Komaromy, Andras; Jacobs, Jonathan B; Hauck, Bernd; Zelenaia, Olga; Mingozzi, Federico; Hui, Daniel; Chung, Daniel; Rex, Tonia S; Wei, Zhangyong; Qu, Guang; Zhou, Shangzhen; Zeiss, Caroline; Arruda, Valder R; Acland, Gregory M; Dell'Osso, Lou F; High, Katherine A; Maguire, Albert M; Bennett, Jean

2008-03-01

We evaluated the safety and efficacy of an optimized adeno-associated virus (AAV; AAV2.RPE65) in animal models of the RPE65 form of Leber congenital amaurosis (LCA). Protein expression was optimized by addition of a modified Kozak sequence at the translational start site of hRPE65. Modifications in AAV production and delivery included use of a long stuffer sequence to prevent reverse packaging from the AAV inverted-terminal repeats, and co-injection with a surfactant. The latter allows consistent and predictable delivery of a given dose of vector. We observed improved electroretinograms (ERGs) and visual acuity in Rpe65 mutant mice. This has not been reported previously using AAV2 vectors. Subretinal delivery of 8.25 x 10(10) vector genomes in affected dogs was well tolerated both locally and systemically, and treated animals showed improved visual behavior and pupillary responses, and reduced nystagmus within 2 weeks of injection. ERG responses confirmed the reversal of visual deficit. Immunohistochemistry confirmed transduction of retinal pigment epithelium cells and there was minimal toxicity to the retina as judged by histopathologic analysis. The data demonstrate that AAV2.RPE65 delivers the RPE65 transgene efficiently and quickly to the appropriate target cells in vivo in animal models. This vector holds great promise for treatment of LCA due to RPE65 mutations.

Reversal of Blindness in Animal Models of Leber Congenital Amaurosis Using Optimized AAV2-mediated Gene Transfer

PubMed Central

Bennicelli, Jeannette; Wright, John Fraser; Komaromy, Andras; Jacobs, Jonathan B; Hauck, Bernd; Zelenaia, Olga; Mingozzi, Federico; Hui, Daniel; Chung, Daniel; Rex, Tonia S; Wei, Zhangyong; Qu, Guang; Zhou, Shangzhen; Zeiss, Caroline; Arruda, Valder R; Acland, Gregory M; Dell’Osso, Lou F; High, Katherine A; Maguire, Albert M; Bennett, Jean

2010-01-01

We evaluated the safety and efficacy of an optimized adeno-associated virus (AAV; AAV2.RPE65) in animal models of the RPE65 form of Leber congenital amaurosis (LCA). Protein expression was optimized by addition of a modified Kozak sequence at the translational start site of hRPE65. Modifications in AAV production and delivery included use of a long stuffer sequence to prevent reverse packaging from the AAV inverted-terminal repeats, and co-injection with a surfactant. The latter allows consistent and predictable delivery of a given dose of vector. We observed improved electroretinograms (ERGs) and visual acuity in Rpe65 mutant mice. This has not been reported previously using AAV2 vectors. Subretinal delivery of 8.25 × 1010 vector genomes in affected dogs was well tolerated both locally and systemically, and treated animals showed improved visual behavior and pupillary responses, and reduced nystagmus within 2 weeks of injection. ERG responses confirmed the reversal of visual deficit. Immunohistochemistry confirmed transduction of retinal pigment epithelium cells and there was minimal toxicity to the retina as judged by histopathologic analysis. The data demonstrate that AAV2.RPE65 delivers the RPE65 transgene efficiently and quickly to the appropriate target cells in vivo in animal models. This vector holds great promise for treatment of LCA due to RPE65 mutations. PMID:18209734

Tetraspanin CD37 contributes to the initiation of cellular immunity by promoting dendritic cell migration.

PubMed

Gartlan, Kate H; Wee, Janet L; Demaria, Maria C; Nastovska, Roza; Chang, Tsz Man; Jones, Eleanor L; Apostolopoulos, Vasso; Pietersz, Geoffrey A; Hickey, Michael J; van Spriel, Annemiek B; Wright, Mark D

2013-05-01

Previous studies on the role of the tetraspanin CD37 in cellular immunity appear contradictory. In vitro approaches indicate a negative regulatory role, whereas in vivo studies suggest that CD37 is necessary for optimal cellular responses. To resolve this discrepancy, we studied the adaptive cellular immune responses of CD37(-/-) mice to intradermal challenge with either tumors or model antigens and found that CD37 is essential for optimal cell-mediated immunity. We provide evidence that an increased susceptibility to tumors observed in CD37(-/-) mice coincides with a striking failure to induce antigen-specific IFN-γ-secreting T cells. We also show that CD37 ablation impairs several aspects of DC function including: in vivo migration from skin to draining lymph nodes; chemo-tactic migration; integrin-mediated adhesion under flow; the ability to spread and form actin protrusions and in vivo priming of adoptively transferred naïve T cells. In addition, multiphoton microscopy-based assessment of dermal DC migration demonstrated a reduced rate of migration and increased randomness of DC migration in CD37(-/-) mice. Together, these studies are consistent with a model in which the cellular defect that underlies poor cellular immune induction in CD37(-/-) mice is impaired DC migration. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design and Modelling of a Microfluidic Electro-Lysis Device with Controlling Plates

NASA Technical Reports Server (NTRS)

Jenkins, A.; Chen, C. P.; Spearing, S.; Monaco, L. A.; Steele, A.; Flores, G.

2006-01-01

Many Lab-on-Chip applications require sample pre-treatment systems. Using electric fields to perform cell-lysis in bio-MEMS systems has provided a powerful tool which can be integrated into Lab-on-a-Chip platforms. The major design considerations for electro-lysis devices include optimal geometry and placement of micro-electrodes, cell concentration, flow rates, optimal electric field (e.g. pulsed DC vs. AC), etc. To avoid electrolysis of the flowing solution at the exposed electrode surfaces, magnitudes and the applied voltages and duration of the DC pulse, or the AC frequency of the AC, have to be optimized for a given configuration. Using simulation tools for calculation of electric fields has proved very useful, for exploring alternative configurations and operating conditions for achieving electro cell-lysis. To alleviate the problem associated with low electric fields within the microfluidics channel and the high voltage demand on the contact electrode strips, two "control plates" are added to the microfluidics configuration. The principle of placing the two controlling plate-electrodes is based on the electric fields generated by a combined insulator/dielectric (gladwater) media. Surface charges are established at the insulator/dielectric interface. This paper discusses the effects of this interface charge on the modification of the electric field of the flowing liquid/cell solution.

Design and Modelling of a Microfluidic Electro-Lysis Device with Controlling Plates

NASA Astrophysics Data System (ADS)

Jenkins, A.; Chen, C. P.; Spearing, S.; Monaco, L. A.; Steele, A.; Flores, G.

2006-04-01

Many Lab-on-Chip applications require sample pre-treatment systems. Using electric fields to perform cell lysis in bio-MEMS systems has provided a powerful tool which can be integrated into Lab-on-a- Chip platforms. The major design considerations for electro-lysis devices include optimal geometry and placement of micro-electrodes, cell concentration, flow rates, optimal electric field (e.g. pulsed DC vs. AC), etc. To avoid electrolysis of the flowing solution at the exposed electrode surfaces, magnitudes and the applied voltages and duration of the DC pulse, or the AC frequency of the AC, have to be optimized for a given configuration. Using simulation tools for calculation of electric fields has proved very useful, for exploring alternative configurations and operating conditions for achieving electro cell-lysis. To alleviate the problem associated with low electric fields within the microfluidics channel and the high voltage demand on the contact electrode strips, two ''control plates'' are added to the microfluidics configuration. The principle of placing the two controlling plate-electrodes is based on the electric fields generated by a combined insulator/dielectric (glass/water) media. Surface charges are established at the insulator/dielectric interface. This paper discusses the effects of this interface charge on the modification of the electric field of the flowing liquid/cell solution.

Network simulation-based optimization of centrifugo-pneumatic blood plasma separation

PubMed Central

Zehnle, S.; Zengerle, R.; von Stetten, F.; Paust, N.

2017-01-01

Automated and robust separation of 14 μl of plasma from 40 μl of whole blood at a purity of 99.81% ± 0.11% within 43 s is demonstrated for the hematocrit range of 20%–60% in a centrifugal microfluidic polymer disk. At high rotational frequency, red blood cells (RBCs) within whole blood are concentrated in a radial outer RBC collection chamber. Simultaneously, plasma is concentrated in a radial inner pneumatic chamber, where a defined air volume is enclosed and compressed. Subsequent reduction of the rotational frequency to not lower than 25 Hz enables rapid transfer of supernatant plasma into a plasma collection chamber, with highly suppressed resuspension of red blood cells. Disk design and the rotational protocol are optimized to make the process fast, robust, and insusceptible for undesired cell resuspension. Numerical network simulation with lumped model elements is used to predict and optimize the fluidic characteristics. Lysis of the remaining red blood cells in the purified plasma, followed by measurement of the hemoglobin concentration, was used to determine plasma purity. Due to the pneumatic actuation, no surface treatment of the fluidic cartridge or any additional external means are required, offering the possibility for low-cost mass fabrication technologies, such as injection molding or thermoforming. PMID:28798850

Precision cancer immunotherapy: optimizing dendritic cell-based strategies to induce tumor antigen-specific T-cell responses against individual patient tumors.

PubMed

Osada, Takuya; Nagaoka, Koji; Takahara, Masashi; Yang, Xiao Yi; Liu, Cong-Xiao; Guo, Hongtao; Roy Choudhury, Kingshuk; Hobeika, Amy; Hartman, Zachary; Morse, Michael A; Lyerly, H Kim

2015-05-01

Most dendritic cell (DC)-based vaccines have loaded the DC with defined antigens, but loading with autologos tumor-derived antigens would generate DCs that activate personalized tumor-specific T-cell responses. We hypothesized that DC matured with an optimized combination of reagents and loaded with tumor-derived antigens using a clinically feasible electroporation strategy would induce potent antitumor immunity. We first studied the effects on DC maturation and antigen presentation of the addition of picibanil (OK432) to a combination of zoledronic acid, tumor necrosis factor-α, and prostaglandin E2. Using DC matured with the optimized combination, we tested 2 clinically feasible sources of autologous antigen for electroloading, total tumor mRNA or total tumor lysate, to determine which stimulated more potent antigen-specific T cells in vitro and activated more potent antitumor immunity in vivo. The combination of tumor necrosis factor-α/prostaglandin E2/zoledronic acid/OK432 generated DC with high expression of maturation markers and antigen-specific T-cell stimulatory function in vitro. Mature DC electroloaded with tumor-derived mRNA [mRNA electroporated dendritic cell (EPDC)] induced greater expansion of antigen-specific T cells in vitro than DC electroloaded with tumor lysate (lysate EPDC). In a therapeutic model of MC38-carcinoembryonic antigen colon cancer-bearing mice, vaccination with mRNA EPDC induced the most efficient anti-carcinoembryonic antigen cellular immune response, which significantly suppressed tumor growth. In conclusion, mature DC electroloaded with tumor-derived mRNA are a potent cancer vaccine, especially useful when specific tumor antigens for vaccination have not been identified, allowing autologous tumor, and if unavailable, allogeneic cell lines to be used as an unbiased source of antigen. Our data support clinical testing of this strategy.

Fighting Cancer with Mathematics and Viruses.

PubMed

Santiago, Daniel N; Heidbuechel, Johannes P W; Kandell, Wendy M; Walker, Rachel; Djeu, Julie; Engeland, Christine E; Abate-Daga, Daniel; Enderling, Heiko

2017-08-23

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments.

Fighting Cancer with Mathematics and Viruses

PubMed Central

Santiago, Daniel N.; Heidbuechel, Johannes P. W.; Kandell, Wendy M.; Walker, Rachel; Djeu, Julie; Abate-Daga, Daniel; Enderling, Heiko

2017-01-01

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments. PMID:28832539

Nonlinear data-driven identification of polymer electrolyte membrane fuel cells for diagnostic purposes: A Volterra series approach

NASA Astrophysics Data System (ADS)

Ritzberger, D.; Jakubek, S.

2017-09-01

In this work, a data-driven identification method, based on polynomial nonlinear autoregressive models with exogenous inputs (NARX) and the Volterra series, is proposed to describe the dynamic and nonlinear voltage and current characteristics of polymer electrolyte membrane fuel cells (PEMFCs). The structure selection and parameter estimation of the NARX model is performed on broad-band voltage/current data. By transforming the time-domain NARX model into a Volterra series representation using the harmonic probing algorithm, a frequency-domain description of the linear and nonlinear dynamics is obtained. With the Volterra kernels corresponding to different operating conditions, information from existing diagnostic tools in the frequency domain such as electrochemical impedance spectroscopy (EIS) and total harmonic distortion analysis (THDA) are effectively combined. Additionally, the time-domain NARX model can be utilized for fault detection by evaluating the difference between measured and simulated output. To increase the fault detectability, an optimization problem is introduced which maximizes this output residual to obtain proper excitation frequencies. As a possible extension it is shown, that by optimizing the periodic signal shape itself that the fault detectability is further increased.

Continuous piecewise-linear, reduced-order electrochemical model for lithium-ion batteries in real-time applications

NASA Astrophysics Data System (ADS)

Farag, Mohammed; Fleckenstein, Matthias; Habibi, Saeid

2017-02-01

Model-order reduction and minimization of the CPU run-time while maintaining the model accuracy are critical requirements for real-time implementation of lithium-ion electrochemical battery models. In this paper, an isothermal, continuous, piecewise-linear, electrode-average model is developed by using an optimal knot placement technique. The proposed model reduces the univariate nonlinear function of the electrode's open circuit potential dependence on the state of charge to continuous piecewise regions. The parameterization experiments were chosen to provide a trade-off between extensive experimental characterization techniques and purely identifying all parameters using optimization techniques. The model is then parameterized in each continuous, piecewise-linear, region. Applying the proposed technique cuts down the CPU run-time by around 20%, compared to the reduced-order, electrode-average model. Finally, the model validation against real-time driving profiles (FTP-72, WLTP) demonstrates the ability of the model to predict the cell voltage accurately with less than 2% error.

Is Human-induced Pluripotent Stem Cell the Best Optimal?

PubMed

Wang, Feng; Kong, Jie; Cui, Yi-Yao; Liu, Peng; Wen, Jian-Yan

2018-04-05

Since the advent of induced pluripotent stem cell (iPSC) technology a decade ago, enormous progress has been made in stem cell biology and regenerative medicine. Human iPSCs have been widely used for disease modeling, drug discovery, and cell therapy development. In this review, we discuss the progress in applications of iPSC technology that are particularly relevant to drug discovery and regenerative medicine, and consider the remaining challenges and the emerging opportunities in the field. Articles in this review were searched from PubMed database from January 2014 to December 2017. Original articles about iPSCs and cardiovascular diseases were included and analyzed. iPSC holds great promises for human disease modeling, drug discovery, and stem cell-based therapy, and this potential is only beginning to be realized. However, several important issues remain to be addressed. The recent availability of human cardiomyocytes derived from iPSCs opens new opportunities to build in vitro models of cardiac disease, screening for new drugs and patient-specific cardiac therapy.

A reliability design method for a lithium-ion battery pack considering the thermal disequilibrium in electric vehicles

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.

Enhanced reaction kinetics in biological cells

NASA Astrophysics Data System (ADS)

Loverdo, C.; Bénichou, O.; Moreau, M.; Voituriez, R.

2008-02-01

The cell cytoskeleton is a striking example of an `active' medium driven out-of-equilibrium by ATP hydrolysis. Such activity has been shown to have a spectacular impact on the mechanical and rheological properties of the cellular medium, as well as on its transport properties: a generic tracer particle freely diffuses as in a standard equilibrium medium, but also intermittently binds with random interaction times to motor proteins, which perform active ballistic excursions along cytoskeletal filaments. Here, we propose an analytical model of transport-limited reactions in active media, and show quantitatively how active transport can enhance reactivity for large enough tracers such as vesicles. We derive analytically the average interaction time with motor proteins that optimizes the reaction rate, and reveal remarkable universal features of the optimal configuration. We discuss why active transport may be beneficial in various biological examples: cell cytoskeleton, membranes and lamellipodia, and tubular structures such as axons.

Multiple Lytic Origins of Replication Are Required for Optimal Gammaherpesvirus Fitness In Vitro and In Vivo

PubMed Central

Sattler, Christine; Steer, Beatrix; Adler, Heiko

2016-01-01

An unresolved question in herpesvirus biology is why some herpesviruses contain more than one lytic origin of replication (oriLyt). Using murine gammaherpesvirus 68 (MHV-68) as model virus containing two oriLyts, we demonstrate that loss of either of the two oriLyts was well tolerated in some situations but not in others both in vitro and in vivo. This was related to the cell type, the organ or the route of inoculation. Depending on the cell type, different cellular proteins, for example Hexim1 and Rbbp4, were found to be associated with oriLyt DNA. Overexpression or downregulation of these proteins differentially affected the growth of mutants lacking either the left or the right oriLyt. Thus, multiple oriLyts are required to ensure optimal fitness in different cell types and tissues. PMID:27007137

Engineering plant metabolism into microbes: from systems biology to synthetic biology.

PubMed

Xu, Peng; Bhan, Namita; Koffas, Mattheos A G

2013-04-01

Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

Regenerative fuel cell systems for mid- to high-orbit satellites

NASA Technical Reports Server (NTRS)

Taenaka, R. K.; Adler, E.; Stofel, E. J.; Clark, K. B.

1987-01-01

An assessment of the present and projected capabilities of selected hydrogen-oxygen and hydrogen-halogen fuel cell and electrolyzer combinations for energy storage systems (ESS) in configurations useful for spacecraft missions operating in the 10- to 50-kW range for many years in midaltitude to geosynchronous orbits has recently been completed. Results of the study indicate that regenerative fuel cell ESS are feasible for the intended application. A computer model was used to provide tradeoff analyses for optimizing the various ESS fuel cell concepts. When appropriately configured to be compatible with the mission needs of the selected model spacecraft, the specific energy for these ESS are intermediate between that presently available for nickel-hydrogen batteries and that expected for the newly emerging sodium-sulfur technology.

A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy.

PubMed

Tao, Youshan; Guo, Qian; Aihara, Kazuyuki

2014-10-01

Hormonal therapy with androgen suppression is a common treatment for advanced prostate tumors. The emergence of androgen-independent cells, however, leads to a tumor relapse under a condition of long-term androgen deprivation. Clinical trials suggest that intermittent androgen suppression (IAS) with alternating on- and off-treatment periods can delay the relapse when compared with continuous androgen suppression (CAS). In this paper, we propose a mathematical model for prostate tumor growth under IAS therapy. The model elucidates initial hormone sensitivity, an eventual relapse of a tumor under CAS therapy, and a delay of a relapse under IAS therapy, which are due to the coexistence of androgen-dependent cells, androgen-independent cells resulting from reversible changes by adaptation, and androgen-independent cells resulting from irreversible changes by genetic mutations. The model is formulated as a free boundary problem of partial differential equations that describe the evolution of populations of the abovementioned three types of cells during on-treatment periods and off-treatment periods. Moreover, the model can be transformed into a piecewise linear ordinary differential equation model by introducing three new volume variables, and the study of the resulting model may help to devise optimal IAS schedules.

Codon Optimization of the Human Papillomavirus E7 Oncogene Induces a CD8+ T Cell Response to a Cryptic Epitope Not Harbored by Wild-Type E7

PubMed Central

Lorenz, Felix K. M.; Wilde, Susanne; Voigt, Katrin; Kieback, Elisa; Mosetter, Barbara; Schendel, Dolores J.; Uckert, Wolfgang

2015-01-01

Codon optimization of nucleotide sequences is a widely used method to achieve high levels of transgene expression for basic and clinical research. Until now, immunological side effects have not been described. To trigger T cell responses against human papillomavirus, we incubated T cells with dendritic cells that were pulsed with RNA encoding the codon-optimized E7 oncogene. All T cell receptors isolated from responding T cell clones recognized target cells expressing the codon-optimized E7 gene but not the wild type E7 sequence. Epitope mapping revealed recognition of a cryptic epitope from the +3 alternative reading frame of codon-optimized E7, which is not encoded by the wild type E7 sequence. The introduction of a stop codon into the +3 alternative reading frame protected the transgene product from recognition by T cell receptor gene-modified T cells. This is the first experimental study demonstrating that codon optimization can render a transgene artificially immunogenic through generation of a dominant cryptic epitope. This finding may be of great importance for the clinical field of gene therapy to avoid rejection of gene-corrected cells and for the design of DNA- and RNA-based vaccines, where codon optimization may artificially add a strong immunogenic component to the vaccine. PMID:25799237

Design, Modeling, Fabrication & Characterization of Industrial Si Solar Cells

NASA Astrophysics Data System (ADS)

Chowdhury, Ahrar Ahmed

Photovoltaic is a viable solution towards meeting the energy demand in an ecofriendly environment. To ensure the mass access in photovoltaic electricity, cost effective approach needs to be adapted. This thesis aims towards substrate independent fabrication process in order to achieve high efficiency cost effective industrial Silicon (Si) solar cells. Most cost-effective structures, such as, Al-BSF (Aluminum Back Surface Field), FSF (Front Surface Field) and bifacial cells are investigated in detail to exploit the efficiency potentials. First off, we introduced two-dimensional simulation model to design and modeling of most commonly used Si solar cells in today's PV arena. Best modelled results of high efficiency Al-BSF, FSF and bifacial cells are 20.50%, 22% and 21.68% respectively. Special attentions are given on the metallization design on all the structures in order to reduce the Ag cost. Furthermore, detail design and modeling were performed on FSF and bifacial cells. The FSF cells has potentials to gain 0.42%abs efficiency by combining the emitter design and front surface passivation. The prospects of bifacial cells can be revealed with the optimization of gridline widths and gridline numbers. Since, bifacial cells have metallization on both sides, a double fold cost saving is possible via innovative metallization design. Following modeling an effort is undertaken to reach the modelled result in fabrication the process. We proposed substrate independent fabrication process aiming towards establishing simultaneous processing sequences for both monofacial and bifacial cells. Subsequently, for the contact formation cost effective screen-printed technology is utilized throughout this thesis. The best Al-BSF cell attained efficiency ˜19.40%. Detail characterization was carried out to find a roadmap of achieving >20.50% efficiency Al-BSF cell. Since, n-type cell is free from Light Induced degradation (LID), recently there is a growing interest on FSF cell. Our best fabricated result of FSF cell achieved ˜18.40% efficiency. Characterizations on such cells provide that, cell performance can be further improved by utilizing high lifetime base wafer. We showed a step by step improvement on the device parameters to achieve ˜22% efficiency FSF cell. Finally, bifacial cells were fabricated with 13.32% front and 9.65% rear efficiency. The efficiency limitation is due to the quality of base wafer. Detail resistance breakdown was conducted on these cells to analyze parasitic resistance losses. It was found that base and gridline resistances dominated the FF loss. However, very low contact resistance of 20 mO-cm 2 at front side and 2 mO-cm2 at the rear side was observed by utilizing same Ag paste for front and rear contact formation. This might provide a pathway towards the search of an optimized Ag paste to attain high efficiency screen-printed bifacial cell. Detail investigations needs to be carried out to unveil the property of this Ag paste. In future work, more focus will be given on the metallization design to incorporate further reduction in Ag cost. Al2O3 passivation layer will be incorporated as a means to attain ˜23% screen-printed bifacial cell.

3-compartment talaporfin sodium pharmacokinetic model by optimization using fluorescence measurement data from canine skin to estimate the concentration in interstitial space

NASA Astrophysics Data System (ADS)

Uno, Yuko; Ogawa, Emiyu; Aiyoshi, Eitaro; Arai, Tsunenori

2018-02-01

We constructed the 3-compartment talaporfin sodium pharmacokinetic model for canine by an optimization using the fluorescence measurement data from canine skin to estimate the concentration in the interstitial space. It is difficult to construct the 3-compartment model consisted of plasma, interstitial space, and cell because there is a lack of the dynamic information. Therefore, we proposed the methodology to construct the 3-compartment model using the measured talaporfin sodium skin fluorescence change considering originated tissue part by a histological observation. In a canine animal experiment, the talaporfin sodium concentration time history in plasma was measured by a spectrophotometer with a prepared calibration curve. The time history of talaporfin sodium Q-band fluorescence on left femoral skin of a beagle dog excited by talaporfin sodium Soret-band of 409 nm was measured in vivo by our previously constructed measurement system. The measured skin fluorescence was classified to its source, that is, specific ratio of plasma, interstitial space, and cell. We represented differential rate equations of the talaporfin sodium concentration in plasma, interstitial space, cell. The specific ratios and a converting constant to obtain absolute value of skin concentration were arranged. Minimizing the squared error of the difference between the measured fluorescence data and calculated concentration by the conjugate gradient method in MATLAB, the rate constants in the 3-compartment model were determined. The accuracy of the fitting operation was confirmed with determination coefficient of 0.98. We could construct the 3-compartment pharmacokinetic model for canine using the measured talaporfin sodium fluorescence change from canine skin.

Fundamental research in the area of high temperature fuel cells in Russia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dyomin, A.K.

1996-04-01

Research in the area of molten carbonate and solid oxide fuel cells has been conducted in Russia since the late 60`s. Institute of High Temperature Electrochemistry is the lead organisation in this area. Research in the area of materials used in fuel cells has allowed us to identify compositions of electrolytes, electrodes, current paths and transmitting, sealing and structural materials appropriate for long-term fuel cell applications. Studies of electrode processes resulted in better understanding of basic patterns of electrode reactions and in the development of a foundation for electrode structure optimization. We have developed methods to increase electrode activity levelsmore » that allowed us to reach current density levels of up to 1 amper/cm{sup 2}. Development of mathematical models of processes in high temperature fuel cells has allowed us to optimize their structure. The results of fundamental studies have been tested on laboratory mockups. MCFC mockups with up to 100 W capacity and SOFC mockups with up to 1 kW capacity have been manufactured and tested at IHTE. There are three SOFC structural options: tube, plate and modular.« less

Optimized Assembly of a Multifunctional RNA-Protein Nanostructure in a Cell-Free Gene Expression System.

PubMed

Schwarz-Schilling, Matthaeus; Dupin, Aurore; Chizzolini, Fabio; Krishnan, Swati; Mansy, Sheref S; Simmel, Friedrich C

2018-04-11

Molecular complexes composed of RNA molecules and proteins are promising multifunctional nanostructures for a wide variety of applications in biological cells or in artificial cellular systems. In this study, we systematically address some of the challenges associated with the expression and assembly of such hybrid structures using cell-free gene expression systems. As a model structure, we investigated a pRNA-derived RNA scaffold functionalized with four distinct aptamers, three of which bind to proteins, streptavidin and two fluorescent proteins, while one binds the small molecule dye malachite green (MG). Using MG fluorescence and Förster resonance energy transfer (FRET) between the RNA-scaffolded proteins, we assess critical assembly parameters such as chemical stability, binding efficiency, and also resource sharing effects within the reaction compartment. We then optimize simultaneous expression and coassembly of the RNA-protein nanostructure within a single-compartment cell-free gene expression system. We demonstrate expression and assembly of the multicomponent nanostructures inside of emulsion droplets and their aptamer-mediated localization onto streptavidin-coated substrates, plus the successful assembly of the hybrid structures inside of bacterial cells.

Immune suppression with supraoptimal doses of antigen in contact sensitivity. I. Demonstration of suppressor cells and their sensitivity to cyclophosphamide.

PubMed

Sy, M S; Miller, S D; Claman, H N

1977-07-01

Immunologic suppression was induced in a mouse model of contact sensitization to DNFB by using supraoptimal doses of antigen. In these studies, in vivo measurement of ear swelling as an indication of immunologic responsiveness correlated well with measurement of in vitro antigen-induced cell proliferation. This unresponsiveness was specific, since supraoptimal doses of DNFB did not interfere with the development of contact sensitivity to another contactant, oxazolone. The decrease in responsiveness is a form of active suppression, as lymphoid cells from supraoptimally sensitized donors transferred suppression to normal recipients. Furthermore, pretreatment with cyclophosphamide (Cy) reversed the suppression seen in supraoptimally sensitized animals but had no effect on the optimal sensitization regimen. These results indicate that supraoptimal doses of contactants can activate suppressor cells and that precursors of these cells are sensitive to Cy. Such suppressors regenerate within 7 to 14 days after Cy treatment. The ability of Cy pretreatment to affect supraoptimal sensitization without affecting optimal sensitization confirms other reports indicating that the observed results of Cy treatment depend critically upon the dose of antigen used.

Disease modeling and drug screening for neurological diseases using human induced pluripotent stem cells.

PubMed

Xu, Xiao-hong; Zhong, Zhong

2013-06-01

With the general decline of pharmaceutical research productivity, there are concerns that many components of the drug discovery process need to be redesigned and optimized. For example, the human immortalized cell lines or animal primary cells commonly used in traditional drug screening may not faithfully recapitulate the pathological mechanisms of human diseases, leading to biases in assays, targets, or compounds that do not effectively address disease mechanisms. Recent advances in stem cell research, especially in the development of induced pluripotent stem cell (iPSC) technology, provide a new paradigm for drug screening by permitting the use of human cells with the same genetic makeup as the patients without the typical quantity constraints associated with patient primary cells. In this article, we will review the progress made to date on cellular disease models using human stem cells, with a focus on patient-specific iPSCs for neurological diseases. We will discuss the key challenges and the factors that associated with the success of using stem cell models for drug discovery through examples from monogenic diseases, diseases with various known genetic components, and complex diseases caused by a combination of genetic, environmental and other factors.

Photothermal Therapy Generates a Thermal Window of Immunogenic Cell Death in Neuroblastoma.

PubMed

Sweeney, Elizabeth E; Cano-Mejia, Juliana; Fernandes, Rohan

2018-04-17

A thermal "window" of immunogenic cell death (ICD) elicited by nanoparticle-based photothermal therapy (PTT) in an animal model of neuroblastoma is described. In studies using Prussian blue nanoparticles to administer photothermal therapy (PBNP-PTT) to established localized tumors in the neuroblastoma model, it is observed that PBNP-PTT conforms to the "more is better" paradigm, wherein higher doses of PBNP-PTT generates higher cell/local heating and thereby more cell death, and consequently improved animal survival. However, in vitro analysis of the biochemical correlates of ICD (ATP, high-motility group box 1, and calreticulin) elicited by PBNP-PTT demonstrates that PBNP-PTT triggers a thermal window of ICD. ICD markers are highly expressed within an optimal temperature (thermal dose) window of PBNP-PTT (63.3-66.4 °C) as compared with higher (83.0-83.5 °C) and lower PBNP-PTT (50.7-52.7 °C) temperatures, which both yield lower expression. Subsequent vaccination studies in the neuroblastoma model confirm the in vitro findings, wherein PBNP-PTT administered within the optimal temperature window results in long-term survival (33.3% at 100 d) compared with PBNP-PTT administered within the higher (0%) and lower (20%) temperature ranges, and controls (0%). The findings demonstrate a tunable immune response to heat generated by PBNP-PTT, which should be critically engaged in the administration of PTT for maximizing its therapeutic benefits. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigation of metabolic objectives in cultured hepatocytes.

PubMed

Uygun, Korkut; Matthew, Howard W T; Huang, Yinlun

2007-06-15

Using optimization based methods to predict fluxes in metabolic flux balance models has been a successful approach for some microorganisms, enabling construction of in silico models and even inference of some regulatory motifs. However, this success has not been translated to mammalian cells. The lack of knowledge about metabolic objectives in mammalian cells is a major obstacle that prevents utilization of various metabolic engineering tools and methods for tissue engineering and biomedical purposes. In this work, we investigate and identify possible metabolic objectives for hepatocytes cultured in vitro. To achieve this goal, we present a special data-mining procedure for identifying metabolic objective functions in mammalian cells. This multi-level optimization based algorithm enables identifying the major fluxes in the metabolic objective from MFA data in the absence of information about critical active constraints of the system. Further, once the objective is determined, active flux constraints can also be identified and analyzed. This information can be potentially used in a predictive manner to improve cell culture results or clinical metabolic outcomes. As a result of the application of this method, it was found that in vitro cultured hepatocytes maximize oxygen uptake, coupling of urea and TCA cycles, and synthesis of serine and urea. Selection of these fluxes as the metabolic objective enables accurate prediction of the flux distribution in the system given a limited amount of flux data; thus presenting a workable in silico model for cultured hepatocytes. It is observed that an overall homeostasis picture is also emergent in the findings.

Modeling Huntington׳s disease with patient-derived neurons.

PubMed

Mattis, Virginia B; Svendsen, Clive N

2017-02-01

Huntington׳s Disease (HD) is a fatal neurodegenerative disorder caused by expanded polyglutamine repeats in the Huntingtin (HTT) gene. While the gene was identified over two decades ago, it remains poorly understood why mutant HTT (mtHTT) is initially toxic to striatal medium spiny neurons (MSNs). Models of HD using non-neuronal human patient cells and rodents exhibit some characteristic HD phenotypes. While these current models have contributed to the field, they are limited in disease manifestation and may vary in their response to treatments. As such, human HD patient MSNs for disease modeling could greatly expand the current understanding of HD and facilitate the search for a successful treatment. It is now possible to use pluripotent stem cells, which can generate any tissue type in the body, to study and potentially treat HD. This review covers disease modeling in vitro and, via chimeric animal generation, in vivo using human HD patient MSNs differentiated from embryonic stem cells or induced pluripotent stem cells. This includes an overview of the differentiation of pluripotent cells into MSNs, the established phenotypes found in cell-based models and transplantation studies using these cells. This review not only outlines the advancements in the rapidly progressing field of HD modeling using neurons derived from human pluripotent cells, but also it highlights several remaining controversial issues such as the 'ideal' series of pluripotent lines, the optimal cell types to use and the study of a primarily adult-onset disease in a developmental model. This article is part of a Special Issue entitled SI: Exploiting human neurons. Copyright © 2015 Elsevier B.V. All rights reserved.

Stochastic models for tumoral growth

NASA Astrophysics Data System (ADS)

Escudero, Carlos

2006-02-01

Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are reported in this paper in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantage of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. An analysis of these models allows us to quantitatively estimate the response of the tumor to an unfavorable perturbation during growth.

Human MAIT-cell responses to Escherichia coli: activation, cytokine production, proliferation, and cytotoxicity.

PubMed

Dias, Joana; Sobkowiak, Michał J; Sandberg, Johan K; Leeansyah, Edwin

2016-07-01

Mucosa-associated invariant T cells are a large and relatively recently described innate-like antimicrobial T-cell subset in humans. These cells recognize riboflavin metabolites from a range of microbes presented by evolutionarily conserved major histocompatibility complex, class I-related molecules. Given the innate-like characteristics of mucosa-associated invariant T cells and the novel type of antigens they recognize, new methodology must be developed and existing methods refined to allow comprehensive studies of their role in human immune defense against microbial infection. In this study, we established protocols to examine a range of mucosa-associated invariant T-cell functions as they respond to antigen produced by Escherichia coli These improved and dose- and time-optimized experimental protocols allow detailed studies of MR1-dependent mucosa-associated invariant T-cell responses to Escherichia coli pulsed antigen-presenting cells, as assessed by expression of activation markers and cytokines, by proliferation, and by induction of apoptosis and death in major histocompatibility complex, class I-related-expressing target cells. The novel and optimized protocols establish a framework of methods and open new possibilities to study mucosa-associated invariant T-cell immunobiology, using Escherichia coli as a model antigen. Furthermore, we propose that these robust experimental systems can also be adapted to study mucosa-associated invariant T-cell responses to other microbes and types of antigen-presenting cells. © The Author(s).

Beam-energy-spread minimization using cell-timing optimization

NASA Astrophysics Data System (ADS)

Rose, C. R.; Ekdahl, C.; Schulze, M.

2012-04-01

Beam energy spread, and related beam motion, increase the difficulty in tuning for multipulse radiographic experiments at the dual-axis radiographic hydrodynamic test facility’s axis-II linear induction accelerator (LIA). In this article, we describe an optimization method to reduce the energy spread by adjusting the timing of the cell voltages (both unloaded and loaded), either advancing or retarding, such that the injector voltage and summed cell voltages in the LIA result in a flatter energy profile. We developed a nonlinear optimization routine which accepts as inputs the 74 cell-voltage, injector voltage, and beam current waveforms. It optimizes cell timing per user-selected groups of cells and outputs timing adjustments, one for each of the selected groups. To verify the theory, we acquired and present data for both unloaded and loaded cell-timing optimizations. For the unloaded cells, the preoptimization baseline energy spread was reduced by 34% and 31% for two shots as compared to baseline. For the loaded-cell case, the measured energy spread was reduced by 49% compared to baseline.