A dynamic model of angiotensin II infusion experiments

Applications of control theory in studies of biological system dynamics have come to be called compartmental modelling. A second order, nonlinear, compartmental model is developed which describes the dynamics of the hormone angiotensin II (AII) and arterial blood pressure (BP) during AII infusion experiments. The model is partially identified using dose response data for constant infusion rates between 0.01 and 0.10 μg/kg/min over a period of several minutes. This study represents a first step in understanding the dynamics of regulation of arterial blood pressure by the renin-angiotensin system. All is a vasoconstrictor and is known to participate in the natural regulation of BP. AII is also believed to be an agent in the development of hypertension and atherosclerosis. The model is used to identify causal mechanisms which are consistent both with the established correlation between plasma AII concentration and arterial BP and with current physiological knowledge. The study demonstrates how a simple state variable model can be used to provide guidance concerning the design of future infusion experiments.     

A model for dispersion experiments

Summary A new model is proposed for the dispersion of animals and other organisms and its use is discussed for the analysis of the data from experiments on dispersion. The model is a generalisation of the random walk model, but because of its flexibility it should be much more widely applicable than the random walk model.The new model has been found to fit the results of many dispersion experiments and examples are given of its use with data for millipedes and Drosophila.     

A neural network model for texture discrimination

A model of texture discrimination in visual cortex was built using a feedforward network with lateral interactions among relatively realistic spiking neural elements. The elements have various membrane currents, equilibrium potentials and time constants, with action potentials and synapses. The model is derived from the modified programs of MacGregor (1987). Gabor-like filters are applied to overlapping regions in the original image; the neural network with lateral excitatory and inhibitory interactions then compares and adjusts the Gabor amplitudes in order to produce the actual texture discrimination. Finally, a combination layer selects and groups various representations in the output of the network to form the final transformed image material. We show that both texture segmentation and detection of texture boundaries can be represented in the firing activity of such a network for a wide variety of synthetic to natural images. Performance details depend most strongly on the global balance of strengths of the excitatory and inhibitory lateral interconnections. The spatial distribution of lateral connective strengths has relatively little effect. Detailed temporal firing activities of single elements in the lateral connected network were examined under various stimulus conditions. Results show (as in area 17 of cortex) that a single element's response to image features local to its receptive field can be altered by changes in the global context.     

Improving bioreactor cultivation conditions for sensitive cell lines by dynamic membrane aeration

Although the importance of animal cell culture for the industrial (large scale) production of pharmaceutical products is continuously increasing, the sensibility of the cells towards their cultivation environment is still a challenging issue. In comparison to microbial cultures, cell cultures which are not protected by a cell wall are much more sensitive to shear stress and foam formation. Reactor design as well as the selection of ‘robust’ cell lines is particularly important for these circumstances. Nevertheless, even ‘sensitive’ cell lines are selected for certain pharmaceutical processes due to various reasons. These sensitive cell lines have even higher requirements regarding their cultivation environment. Important characteristics for the corresponding reactor design are a high (volumetric) gas mass transfer coefficient, low volumetric power input, low shear stress, low susceptibility to bio-fouling, the ability to cultivate sticky cells and sufficient mixing properties. Membrane aeration has been a long-known possibility to meet some of these requirements, but has not often been applied in recent years. The reasons lie mainly in low gas mass transfer rates, a limited installable volume-specific membrane surface area, restrictions in scalability and problems with membrane fouling. The dynamic membrane aeration bioreactor aeration is a simple concept for bubble-free oxygen supply of such sensitive cultures. It overcomes limitations and draw-backs of previous systems. Consisting of an oscillating, centrally arranged rotor (stirrer) that is wrapped with silicone membrane tubing, it enables doubling the gas mass transfer at the same shear stress in the investigated cultivation scales of 12, 20, 100, and 200 L. Continuous cultivation at these scales allows the same product output as fed-batch cultivation does at tremendously larger reactor volumes. Apart from introducing this novel technology, the presentation comprises selected cultivation results obtained for blood coagulation factor VIII in continuous mode and a therapeutic monoclonal antibody in fed-batch mode in comparison to reference trials.     

Optimal operating policy of the ultrafiltration membrane bioreactor for enzymatic hydrolysis of cellulose

The dilution rate of an ultrafiltration membrane bioreactor in the enzymatic hydrolysis of cellulose was optimized using the kinetic model developed by Fan and Lee.(4) The sequence of optimal dilution rates was found to generally consist of an initial period of a minimal value (batch period), a subsequent period of maximum dilution rate, a period of a second batch, and a final period of a singular dilution rate. The effects of operating conditions, such as beta-glucosidase activity, operating time, maximum dilution rate, substrate feeding rate, and enzyme-to-substrate ratio on both the conversion yield and the sequence of optimal dilution rates were investigated. To evaluate the validity of kinetic model employed in this work, enzymatic hydrolysis was carried out using alpha-cellulose as a substrate in the ultrafiltration membrane bioreactor. The experimental data were well consistent with the simulation results. (c) 1993 John Wiley & Sons, Inc.     

Optimal covalent immobilization of glucose oxidase-containing liposomes for highly stable biocatalyst in bioreactor

The glucose oxidase-containing liposomes (GOL) were prepared by entrapping glucose oxidase (GO) in the liposomes composed of phosphatidylcholine (PC), dimyristoyl L-alpha-phosphatidylethanolamine (DMPE), and cholesterol (Chol) and then covalently immobilized in the glutaraldehyde-activated chitosan gel beads. The immobilized GOL gel beads (IGOL) were characterized to obtain a highly stable biocatalyst applicable to bioreactor. At first, the glutaraldehyde concentration used in the gel beads activation as well as the immobilizing temperature and time were optimized to enhance the immobilization yield of the GOL to the highest extent. The liposome membrane composition and liposome size were then optimized to obtain the greatest possible immobilization yield of the GOL, the highest possible activity efficiency of the IGOL, and the lowest possible leakage of the entrapped GO during the GOL immobilization. As a result, the optimal immobilization conditions were found to be as follows: the liposome composition, PC/DMPE/Chol = 65/5/30 (molar percentage); the liposome size, 100 nm; the glutaraldehyde concentration, 2% (w/v); the immobilizing temperature, 4 degrees C; and the immobilizing time, 10 h. Furthermore, the optimal IGOL prepared were characterized by its rapidly increasing effective GO activity to the externally added substrate (glucose) with increasing temperature from 20 to 40 degrees C, and also by its high stability at 40 degrees C against not only the thermal denaturation in a long-term (7 days) incubation but also the bubbling stress in a bubble column. Finally, compared to the conventionally immobilized glucose oxidase (IGO), the higher operational stability of the optimal IGOL was verified by using it either repeatedly (4 times) or for a long time (7 days) to catalyze the glucose oxidation in a small-scale airlift bioreactor.     

Optimal foot shape for a passive dynamic biped

Passive walking dynamics describe the motion of a biped that is able to "walk" down a shallow slope without any actuation or control. Instead, the walker relies on gravitational and inertial effects to propel itself forward, exhibiting a gait quite similar to that of humans. These purely passive models depend on potential energy to overcome the energy lost when the foot impacts the ground. Previous research has demonstrated that energy loss at heel-strike can vary widely for a given speed, depending on the nature of the collision. The point of foot contact with the ground (relative to the hip) can have a significant effect: semi-circular (round) feet soften the impact, resulting in much smaller losses than point-foot walkers. Collisional losses are also lower if a single impulse is broken up into a series of smaller impulses that gradually redirect the velocity of the center of mass rather than a single abrupt impulse. Using this principle, a model was created where foot-strike occurs over two impulses, "heel-strike" and "toe-strike," representative of the initial impact of the heel and the following impact as the ball of the foot strikes the ground. Having two collisions with the flat-foot model did improve efficiency over the point-foot model. Representation of the flat-foot walker as a rimless wheel helped to explain the optimal flat-foot shape, driven by symmetry of the virtual spoke angles. The optimal long period foot shape of the simple passive walking model was not very representative of the human foot shape, although a reasonably anthropometric foot shape was predicted by the short period solution.     

Simple generic model for dynamic experiments with Saccharomyces cerevisiae in continuous culture: decoupling between anabolism and catabolism

The dynamic behavior of a continuous culture of Saccharomyces cerevisiae subjected to a sudden increase in the dilution rate has been successfully modelled for anaerobic growth on glucose, and for aerobic growth on acetate, on ethanol, and on glucose. The catabolism responded by an immediate jump whereas biosynthesis did not. Thus catabolism was in excess to anabolism. The model considers the decoupling between biosynthesis and catabolism, both types of reactions being modelled by first-order kinetic expressions evolving towards maximal values. Yield parameters and maximal reaction rates were identified in steady state continuous cultures or during batch experiments. Only the time constant of biosynthesis regeneration, tauX, and the time constant of catabolic capacity regeneration, taucat, had to be identified during transient experiments. In most experiments tauX was around 3 h, and taucat varied between 2 and 2.5 h for the different metabolisms investigated.     

Optimal avian migration: A dynamic model of fuel stores and site use

Birds migrating between widely separated wintering and breeding grounds may choose among a number of potential stopover sites by using different itineraries. Our aim is to predict the optimal migration schedule in terms of (1) rates of fuel deposition, (2) departure fuel loads and (3) stopover site use, when only a handful of such sites are available. We assume that reproductive success depends on the date and fuel load at arrival on the breeding grounds. On migration, the birds face a trade-off between gaining fuel and avoiding predation. To allow the optimal decision at any given moment to depend on the fuel load and the location of the bird, as well as on unpredictability in conditions, we employed stochastic dynamic programming. This technique assumes that the birds know the probability distribution of conditions in all sites, but not the particular realization they will encounter. We examined the consequences of varying aspects of the model, like (1) the shape of the relationship between arrival date and fitness, (2) the presence of stochasticity in fuel deposition rates and wind conditions, and (3) the nature of predation (i.e. whether predation risk depends on the fuel load of the birds or their feeding intensity). Optimal fuel deposition rates are predicted to be constant if there are either only predation risks of maintaining stores or only risks of acquiring fuel stores. If only fuel acquisition is risky, fuel deposition rates can be below maximum, especially if there also is an intermediate best arrival time at the breeding ground. The fuel deposition rate at a site then depends not just on the site's quality but on the qualities of all visited sites. In contrast, rates of fuel deposition are not constant if both the acquisition and the maintenance of fuel stores carry risk. Optimal departure fuel loads are just enough to reach the next site if the environment is deterministic and are simply set by the energetic cost of covering the distance. As with time-minimizing models, more fuel than necessary to reach a site is only deposited under very restricted circumstances. Such overloads are more likely to be deposited if either fuel gains or expenditure are stochastic. The size of overloads is then determined by the variance in fuel gain at the target site and the worst possible conditions during flight. Site use is modified by differences in predation risk between sites and differences in fuel deposition rates. An expression derived to predict site use under time minimization provides a good approximation in state-dependent models. In some cases, the possibility of starvation may influence optimal decisions, even when the probability of starvation under the optimal policy is low. This effect of starvation has also been found in other contexts. This revised version was published online in July 2006 with corrections to the Cover Date.