Design of cellular porous biomaterials for wall shear stress criterion

The microfluidic environment provided by implanted prostheses has a decisive influence on the viability, proliferation and differentiation of cells. In bone tissue engineering, for instance, experiments have confirmed that a certain level of wall shear stress (WSS) is more advantageous to osteoblastic differentiation. This paper proposes a level‐set‐based topology optimization method to regulate fluidic WSS distribution for design of cellular biomaterials. The topological boundary of fluid phase is represented by a level‐set model embedded in a higher‐dimensional scalar function. WSS is determined by the computational fluid dynamics analysis in the scale of cellular base cells. To achieve a uniform WSS distribution at the solid–fluid interface, the difference between local and target WSS is taken as the design criterion, which determines the speed of the boundary evolution in the level‐set model. The examples demonstrate the effectiveness of the presented method and exhibit a considerable potential in the design optimization and fabrication of new prosthetic cellular materials for bioengineering applications. Biotechnol. Bioeng. 2010;107:737–746. © 2010 Wiley Periodicals, Inc.     

Granules characteristics in the vertical profile of a full-scale upflow anaerobic sludge blanket reactor treating poultry slaughterhouse wastewater

The performance and the granules characteristics of a 450 m(3) -UASB reactor operating for 1228 days, treating poultry slaughterhouse wastewater with an average COD reduction of 85% was examined. Granules were sampled in three different positions along the vertical central line of the reactor, revealing variations in the concentration of volatile total solids. Although the reactor had been in operation for an extended period of time, granule sizes of 0.5-1.5 mm appeared to predominate. The hollow core was well defined for granules with sizes ranging from 2 to 3 mm in all the sampling ports. The granules exhibited no layered microbial distribution and were packed with different morphotype cells intertwined randomly throughout the cross-section. Methanogenic Archaea predominated in the granules taken from every sampling port along the reactor. The results indicated that the characterization of the granules is a useful tool for the adoption of operational strategies toward optimization of UASB reactors.     

Optimal temperature policy for immobilized enzyme packed bed reactor performing reversible Michaelis-Menten kinetics using the disjoint policy.

The optimal temperature policy that maximizes the time-averaged productivity of a continuous immobilized enzyme packed bed reactor is determined. This optimization study takes into consideration the enzyme thermal deactivation with substrate protection during the reactor operation. The general case of reversible Michaelis-Menten kinetics under constant reactor feed flow rate is assumed. The corresponding nonlinear optimization problem is solved using the calculus of variations by applying the disjoint policy. This policy reduces the optimization problem into a differential-algebraic system, DAE. This DAE system defines completely the optimal temperature-time profiles. These profiles depend on the kinetic parameters, feed substrate concentration, operating period, and the residence time and are characterized by increasing form with time. Also, general analytical expressions for the slopes of the temperature and residual enzyme activity profiles are derived. An efficient solution algorithm is developed to solve the DAE system, which results into a one-dimensional optimization problem with simple bounds on the initial feed temperature. The enzymatic isomerization of glucose into fructose is selected as a case study. The computed productivities are very close to that obtained by numerical nonlinear optimization with simpler problem to solve. Moreover, the computed conversion profiles are almost constant over 90% of the operating periods, thus producing a homogeneous product.     

Optimization of Operating Temperature for Continuous Immobilized Glucose Isomerase Reactor with Pseudo Linear Kinetics

In this work, the optimal operating temperature for the enzymatic isomerization of glucose to fructose using a continuous immobilized glucose isomerase packed bed reactor is studied. This optimization problem describing the performance of such reactor is based on reversible pseudo linear kinetics and is expressed in terms of a recycle ratio. The thermal deactivation of the enzyme as well as the substrate protection during the reactor operation is considered. The formulation of the problem is expressed in terms of maximization of the productivity of fructose. This constrained nonlinear optimization problem is solved using the disjoint policy of the calculus of variations. Accordingly, this method of solution transforms the nonlinear optimization problem into a system of two coupled nonlinear ordinary differential equations (ODEs) of the initial value type, one equation for the operating temperature profile and the other one for the enzyme activity. The ODE for the operating temperature profile is dependent on the recycle ratio, operating time period, and the reactor residence time as well as the kinetics of the reaction and enzyme deactivation. The optimal initial operating temperature is selected by solving the ODEs system by maximizing the fructose productivity. This results into an unconstrained one‐dimensional optimization problem with simple bounds on the operating temperature. Depending on the limits of the recycle ratio, which represents either a plug flow or a mixed flow reactor, it is found that the optimal temperature of operation is characterized by an increasing temperature profile. For higher residence time and low operating periods the residual enzyme activity in the mixed flow reactor is higher than that for the plug flow reactor, which in turn allows the mixed flow reactor to operate at lower temperature than that of the plug flow reactor. At long operating times and short residence time, the operating temperature profiles are almost the same for both reactors. This could be attributed to the effect of substrate protection on the enzyme stability, which is almost the same for both reactors. Improvement in the fructose productivity for both types of reactors is achieved when compared to the constant optimum temperature of operation. The improvement in the fructose productivity for the plug flow reactor is significant in comparison with the mixed flow reactor.     

Computational study of Wolff's law with trabecular architecture in the human proximal femur using topology optimization

In the field of bone adaptation, it is believed that the morphology of bone is affected by its mechanical loads, and bone has self-optimizing capability; this phenomenon is well known as Wolff's law of the transformation of bone. In this paper, we simulated trabecular bone adaptation in the human proximal femur using topology optimization and quantitatively investigated the validity of Wolff's law. Topology optimization iteratively distributes material in a design domain producing optimal layout or configuration, and it has been widely and successfully used in many engineering fields. We used a two-dimensional micro-FE model with 50 microm pixel resolution to represent the full trabecular architecture in the proximal femur, and performed topology optimization to study the trabecular morphological changes under three loading cases in daily activities. The simulation results were compared to the actual trabecular architecture in previous experimental studies. We discovered that there are strong similarities in trabecular patterns between the computational results and observed data in the literature. The results showed that the strain energy distribution of the trabecular architecture became more uniform during the optimization; from the viewpoint of structural topology optimization, this bone morphology may be considered as an optimal structure. We also showed that the non-orthogonal intersections were constructed to support daily activity loadings in the sense of optimization, as opposed to Wolff's drawing.     

Theoretical and computational studies of the glucose signaling pathways in yeast using global gene expression data

We have combined DNA microarray experiments with novel computational methods as a means of defining the topology of a biological signal transduction pathway. By DNA microarray techniques, we previously acquired data on expression over time of all genes in the yeast Saccharomyces following addition of glucose to wild-type cells and to cells mutated in one or more components of the Ras signaling network. In addition, we examined the time course of expression following activation of components of the Ras signaling network in the absence of glucose addition. In this current study, we have applied a novel theoretical and computational framework to these data to identify the network topology of the glucose signaling pathway in yeast and the role of Ras components in that network. The computational approach involves clustering genes by expression pattern, postulating a signaling network topology superstructure that includes all possible component interconnections and then evaluating the feasibility of the superstructure interconnections by optimization methods using Mixed Integer Linear Programming techniques. This approach is the first rigorous mathematical framework for addressing the biological network topology issue, and the novel formulation features the introduction of discrete variables for the connectivity and logical expressions that connect the experimental observations to the network structure. This analysis yields a topology for the glucose signaling pathway that is consistent with, and an extension of, known biological interactions in glucose signaling.     

Modeling and static optimization of the ethanol production in a cascade reactor. II. Static optimization

In Part I(1) of this research a complex model was obtained for describing the ethanol fermentation in a cascade reactor. This complexity is due to both the nonlinearity and the large scale representation. Based on techniques of partitioning and relaxation, a decentralized successive approximation method is developed for static optimization. The influence of the way of fermentation during continuous culture in multistage fermentors is studied in the case of a double inhibition of cell growth and product formation by both substrate and final product. The optimal number of reactors is discussed with respect to the strength of the ethanol inhibition, while the interest of head feeding or distributed feeding is evaluated in relation to the strength of substrate inhibition.     

Development of anaerobic filters for treatment of high strength agro-industrial wastewaters

The suitability and advantages of anaerobic filters for the treatment of various agro-industrial wastewaters are discussed. Recent developments in reactor design and typical operating parameters and performance data are given for reactors operated in the up- and downflow mode. The distribution of the most important process parameters throughout the reactor height is discussed and methods for process optimization are presented.     

From network structure to network reorganization: implications for adult neurogenesis

Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells.     

Flow analysis for determination of paraoxon with use of immobilized acetylcholinesterase reactor and new type of chemiluminescent reaction

A highly sensitive flow analysis method for determination of acetylcholinesterase (AChE) inhibitors like organophosphorous pesticides using a new chemiluminescent reaction was developed and optimized. This method is fast, sensitive, and cheap, because it requires only one enzyme and its substrate. The system incorporates a reactor with immobilized AChE on controlled pore glass (CPG) and a chemiluminometric detector. Variations in enzyme activity due to inhibition are measured from the changes of concentrations of thiocholine produced when the substrate (acetylthiocholine chloride) is pumped before and after the passage of the solution containing the pesticide through the immobilized AChE reactor. Thiocholine is determined by a new chemiluminescent reaction with luminol in the presence of potassium ferricyanide. The percentage inhibition of enzyme activity is correlated to the pesticide concentration. The inhibited enzyme is reactivated by 10 mM pyridine-2-aldoxime methiodide (2-PAM). The experimental conditions were first optimized for activity determination of the effect of pH, flow rates, and Tris concentrations. For the measurement of AChE inhibition, the appropriate concentration of the substrate is selected such that the rate of noninhibited reaction can be considered unchanged and could be used as a reference. For optimization of experimental conditions for inhibition, several parameters of the system are studied and discussed: flow rate, enzyme-pesticide contact time, luminol concentration, ferricyanide concentration, 2-PAM concentration, and configuration of the FIA manifold. Paraoxon, an organophosphorous pesticide was tested. For an inhibition time of 10 min the calibration graph is linear from 0.1 to 1 ppm paraoxon with a relative standard deviation (n = 5) of 4.6% at 0.5 ppm. For an inhibition time of 30 min the calibration graph is linear from 25 to 250 ppb paraoxon.     

Ethanol production in horizontal bioreactor

Summary The rate of continuous alcohol fermentation by a mixture of free and immobilized yeast cells was found to be higher in a horizontal flow channel reactor than in a vertical column reactor under the same operational conditions. This higher fermentation rate in the horizontal reactor was attributed to accumulation of yeast cells in the reactor by free sedimentation and incomplete mixing in the direction of liquid flow. It was estimated that most of the ethanol in the horizontal bioreactor was produced by free cells in suspended or settled states. The relatively low ethanol production by the immobilized yeast cells on the ethanol production was considered due to higher product inhibition of fermentation rate within the support.     

Three-dimensional topology optimization model to simulate the external shapes of bone

Elucidation of the mechanism by which the shape of bones is formed is essential for understanding vertebrate development. Bones support the body of vertebrates by withstanding external loads, such as those imposed by gravity and muscle tension. Many studies have reported that bone formation varies in response to external loads. An increased external load induces bone synthesis, whereas a decreased external load induces bone resorption. This relationship led to the hypothesis that bone shape adapts to external load. In fact, by simulating this relationship through topology optimization, the internal trabecular structure of bones can be successfully reproduced, thereby facilitating the study of bone diseases. In contrast, there have been few attempts to simulate the external structure of bones, which determines vertebrate morphology. However, the external shape of bones may be reproduced through topology optimization because cells of the same type form both the internal and external structures of bones. Here, we constructed a three-dimensional topology optimization model to attempt the reproduction of the external shape of teleost vertebrae. In teleosts, the internal structure of the vertebral bodies is invariable, exhibiting an hourglass shape, whereas the lateral structure supporting the internal structure differs among species. Based on the anatomical observations, we applied different external loads to the hourglass-shaped part. The simulations produced a variety of three-dimensional structures, some of which exhibited several structural features similar to those of actual teleost vertebrae. In addition, by adjusting the geometric parameters, such as the width of the hourglass shape, we reproduced the variation in the teleost vertebrae shapes. These results suggest that a simulation using topology optimization can successfully reproduce the external shapes of teleost vertebrae. By applying our topology optimization model to various bones of vertebrates, we can understand how the external shape of bones adapts to external loads.     

Feasibility of culturing C2C12 mouse myoblasts on glass microcarriers in a continuous stirred tank bioreactor

Commercial culturing of mammalian cell lines is increasing in importance as more biological products unique to mammals are being produced in genetically altered mammalian cells. Most mammalian cells are anchorage dependent, so they must be cultured on a support matrix. This limitation, along with the requirement of a low shear environment, severely effects the scale-up of bench-scale culture systems. The need to culture mammalian cells on a support matrix limits the increase in cell population to a factor of 10-20 before growth virtually stops due to contact inhibition. Commercial culturing systems for anchorage dependent cells are batch processes because of the combination of contact inhibition and support matrix requirements. Development of a continuous bioreactor system could allow both unlimited scale-up and continuous cell-mass production. To design a continuous reactor, a mathematical model to predict the reactor performance should be developed. This paper addresses the development of a mathematical model for predicting continuous bioreactor performance. It was found that anchorage dependent C2C12 mouse myoblast cells, a continuous cell line, followed Monod kinetics for glucose consumption and cell mass production in batch flask experiments, with w_max = 0.040 hr^у and K_m = 2.5 mM. Furthermore, it was found that these parameters could be used to predict the glucose consumption in a continuous bioreactor operated with constant feed of seeded microcarriers operated at two different residence times. The success of this model implies the possibility of developing a continuous cell harvesting and reinoculation system using a microcarrier bioreactor to produce cell mass.     

Modeling the partial nitrification in sequencing batch reactor for biomass adapted to high ammonia concentrations

Partial nitrification has proven to be an economic way for treatment of industrial N-rich effluent, reducing oxygen and external COD requirements during nitrification/denitrification process. One of the key issues of this system is the intermediate nitrite accumulation stability. This work presents a control strategy and a modeling tool for maintaining nitrite build-up. Partial nitrification process has been carried out in a sequencing batch reactor at 30 degrees C, maintaining strong changing ammonia concentration in the reactor (sequencing feed). Stable nitrite accumulation has been obtained with the help of an on-line oxygen uptake rate (OUR)-based control system, with removal rate of 2 kg NH4 (+)-N x m(-3)/day and 90%-95% of conversion of ammonium into nitrite. A mathematical model, identified through the occurring biological reactions, is proposed to optimize the process (preventing nitrate production). Most of the kinetic parameters have been estimated from specific respirometric tests on biomass and validated on pilot-scale experiments of one-cycle duration. Comparison of dynamic data at different pH confirms that NH3 and NO2- should be considered as the true substrate of nitritation and nitratation, respectively. The proposed model represents major features: the inhibition of ammonia-oxidizing bacteria by its substrate (NH3) and product (HNO2), the inhibition of nitrite-oxidizing bacteria by free ammonia (NH3), the INFluence of pH. It appears that the model correctly describes the short-term dynamics of nitrogenous compounds in SBR, when both ammonia oxidizers and nitrite oxidizers are present and active in the reactor. The model proposed represents a useful tool for process design and optimization.     

Mapping of oxygen tension and cell distribution in a hollow-fiber bioreactor using magnetic resonance imaging

We mapped the distribution of dissolved oxygen and mammalian cells in a hollow-fiber bioreactor (HFBR) using (19)F NMR T(1) relaxation time imaging measurements on an infused perfluorocarbon probe molecule and diffusion-weighted (1)H NMR imaging of water. This study shows how cell density influences dissolved oxygen concentration in the reactor and demonstrates that NMR can play an important role in defining the biochemical engineering parameters required for optimization of HFBR design and operation. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 56-61, 1997.     

A topology optimization based model of bone adaptation

A novel topology optimization model based on homogenization methods was developed for predicting bone density distribution and anisotropy, assuming the bone structure to be a self-optimizing biological material which maximizes its own structural stiffness. The feasibility and efficiency of this method were tested on a 2D model for a proximal femur under single and multiple loading conditions. The main aim was to compute homogenized optimal designs using an optimal laminated microstructure. The computational results showed that high bone density levels are distributed along the diaphysis and form arching struts within the femoral head. The pattern of bone density distribution and the anisotropic bone behavior predicted by the model in the multiple load case were both in good agreement with the structural architecture and bone density distribution occurring in natural femora. This approach provides a novel means of understanding the remodeling processes involved in fracture repair and the treatment of bone diseases.     

A topology optimization based model of bone adaptation

A novel topology optimization model based on homogenization methods was developed for predicting bone density distribution and anisotropy, assuming the bone structure to be a self-optimizing biological material which maximizes its own structural stiffness. The feasibility and efficiency of this method were tested on a 2D model for a proximal femur under single and multiple loading conditions. The main aim was to compute homogenized optimal designs using an optimal laminated microstructure. The computational results showed that high bone density levels are distributed along the diaphysis and form arching struts within the femoral head. The pattern of bone density distribution and the anisotropic bone behavior predicted by the model in the multiple load case were both in good agreement with the structural architecture and bone density distribution occurring in natural femora. This approach provides a novel means of understanding the remodeling processes involved in fracture repair and the treatment of bone diseases.     

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity.     

Enzyme reactor design under thermal inactivation

Temperature is a very relevant variable for any bioprocess. Temperature optimization of bioreactor operation is a key aspect for process economics. This is especially true for enzyme-catalyzed processes, because enzymes are complex, unstable catalysts whose technological potential relies on their operational stability. Enzyme reactor design is presented with a special emphasis on the effect of thermal inactivation. Enzyme thermal inactivation is a very complex process from a mechanistic point of view. However, for the purpose of enzyme reactor design, it has been oversimplified frequently, considering one-stage first-order kinetics of inactivation and data gathered under nonreactive conditions that poorly represent the actual conditions within the reactor. More complex mechanisms are frequent, especially in the case of immobilized enzymes, and most important is the effect of catalytic modulators (substrates and products) on enzyme stability under operation conditions. This review focuses primarily on reactor design and operation under modulated thermal inactivation. It also presents a scheme for bioreactor temperature optimization, based on validated temperature-explicit functions for all the kinetic and inactivation parameters involved. More conventional enzyme reactor design is presented merely as a background for the purpose of highlighting the need for a deeper insight into enzyme inactivation for proper bioreactor design.     

Modeling, simulation, and optimization of bacterial leaching reactors

Bacterial leaching represents an unusual problem in biochemical engineering, because the substrate for bacterial growth is not supplied directly, but is a product of another reaction, the leaching of mineral particles. In addition, leaching is a heterogeneous reaction dependent on the particle-size distribution in the feed and on the kinetics of particle shrinkage. In this study, these effects are incorporated in the material balance for each mineral by the number balance. Examination of the number balance gives rise to a novel analysis of the competing technologies for leaching. The model is completed by the addition of material balances for the ferrous and ferric ions, the dissolved oxygen, and for each bacterial species to the number balance for each mineral present in the feed. The model is compared with pilot plant data for three different ores. It is shown that the model is in excellent agreement with the data. The performance of a bacterial leaching reactor is explored using the model, and the washout and sensitivity criteria are determined. It is shown that there are three washout conditions, in which the leaching conversion drops to zero. The washout conditions are dependent on the growth rate of the bacteria, on the rate of dissolution of the mineral, and on the rate of mass transfer of oxygen to the reactor. The critical washout condition is that arising from the rate of mineral dissolution. The optimization of a plant in which continuous tank reactors are configured in series is addressed. This analysis shows that the primary reactor should be between 1.5 and 2 times the size of each of the secondary reactors in a series combination.