Analysis of cell growth kinetics and substrate diffusion in a polymer scaffold.

The cultivation of cartilage cells (chondrocytes) in polymer scaffolds leads to implants that may potentially be used to repair damaged joint cartilage or for reconstructive surgery. For this technique to be medically applicable, the physical parameters that govern cell growth in a polymer scaffold must be understood. This understanding of cell behavior under in vitro conditions, where diffusion is the primary mode of transport of nutrients, may aid in the scale-up of the cartilage generation process. A mathematical model of chondrocyte generation and nutrient consumption is developed here to analyze the behavior of cell growth in a biodegradable polymer matrix for a series of different thickness polymers. Recent literature has implied that the diffusion of nutrients is a major factor that limits cell growth (Freed et al., 1994). In the present paper, a mathematical model is developed to directly relate the effects of increasing cell mass in the polymer matrix on the transport of nutrients. Reaction and diffusion of nutrients in the cell-polymer system are described using the fundamental species continuity equations and the volume averaging method. The volume averaging method is utilized to derive a single averaged nutrient continuity equation that includes the effective transport properties. This approach allows for the derivation of effective diffusion and rate coefficients as functions of the cell volume fraction. The cell volume fraction as a function of time is determined by solution of a material balance on cell mass. Growth functions including the Moser, a modified Contois, and an nth-order heterogeneous growth kinetic model are evaluated through a parameter analysis, and the results are compared to experimental data found in the literature. The results indicate that cellular functions in conjunction with mass transfer processes can account partially for the general trends in the cell growth behavior for various thickness polymers. The Contois growth function appeared to describe the data more accurately in terms of the lag period at early times and the long time limits. However, all kinetic growth functions required variations in the kinetic parameters to fully describe the effects of polymer thickness. This result implies that restricted diffusion of nutrients is not the sole factor limiting cell growth when the thickness of the polymer is changed. Therefore, further experimental data and model improvements are needed to accurately describe the cell growth process.     

Exclusion processes on a growing domain

A discrete model provides a useful framework for experimentalists to understand the interactions between growing tissues and other biological mechanisms. A cellular automata (CA) model with domain growth, cell motility and cell proliferation, based on cellular exclusion processes, is developed here. Average densities can be defined from the CA model and a continuum representation can be determined. The domain growth mechanism in the CA model gives rise to a Fokker-Planck equation in the corresponding continuum model, with a diffusive and a convective term. Deterministic continuum models derived from conservation laws do not include this diffusive term. The new diffusive term arises because of the stochasticity inherited from the CA mechanism for domain growth. We extend the models to multiple species and investigate the influence of the flux terms arising from the exclusion processes. The averaged CA agent densities are well approximated by the solution of nonlinear advection-diffusion equations, provided that the relative size of the proliferation processes to the diffusion processes is sufficiently small. This dual approach provides an understanding of the microscopic and macroscopic scales in a developmental process.     

Matrix notation for efficient development of first-principles models within PAT applications: integrated modeling of antibiotic production with Streptomyces coelicolor

A matrix notation coupled to macroscopic principles is introduced as a means to develop first- principles models in an efficient and structured way within PAT applications. The notation was evaluated for developing an integrated biological, chemical (pH modeling) and physical (gas-liquid exchange) model for describing antibiotic production with Streptomyces coelicolor in batch fermentations. The model provided statistically adequate fits to all the monitored macroscopic biological, chemical and physical data of the process, except the phosphate uptake dynamics. This phosphate discrepancy is hypothesized to result from the internal storage of phosphate as polyphosphate prior to the exponential growth phase. The antibiotic production was associated with the stationary phase and its kinetics was adequately described using a modified Luedeking-Piret equation. Further, the maintenance was best described by employing a combination of Pirt and Herbert models, a result that was supported by a model-based hypothesis testing. Overall the process knowledge currently incorporated in the model is believed to be useful both for process optimization purposes and for further testing of hypotheses aiming at improving the mechanistic understanding of antibiotic production with S. coelicolor. Last but not least, the matrix notation is believed to be a promising supporting tool for efficient development and communication of complex dynamic models within a PAT framework.     

Population based models of cortical drug response: insights from anaesthesia

A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia.     

Determination of cell membrane permeability in concentrated cell ensembles

The method of volume averaging is used to analyze the process of diffusion in concentrated cell ensembles in which significant resistance to mass transfer is caused by the cellular membrane. A general closure scheme is given that allows for direct theoretical prediction of effective diffusivities for any cellular geometry. Numerical results are presented for the classical parallelepiped arrangement used to model cellular systems, and these results are used in conjunction with experimental studies of concentrated cell ensembles to determine membrane permeabilities for solute diffusion in several cellular systems. Membrane permeabilities are compared with predictions from other models of diffusion in cellular systems.     

Cellular Modelling of Secondary Radial Growth in Conifer Trees: Application to Pinus Radiata (D. Don)

The radial growth of conifer trees proceeds from the dynamics of a merismatic tissue called vascular cambium or cambium. Cambium is a thin layer of active proliferating cells. The purpose of this paper was to model the main characteristics of cambial activity and its consecutive radial growth. Cell growth is under the control of the auxin hormone indole-3-acetic. The model is composed of a discrete part, which accounts for cellular proliferation, and a continuous part involving the transport of auxin. Cambium is modeled in a two-dimensional cross-section by a cellular automaton that describes the set of all its constitutive cells. Proliferation is defined as growth and division of cambial cells under neighbouring constraints, which can eliminate some cells from the cambium. The cell-growth rate is determined from auxin concentration, calculated with the continuous model. We studied the integration of each elementary cambial cell activity into the global coherent movement of macroscopic morphogenesis. Cases of normal and abnormal growth of Pinus radiata (D. Don) are modelled. Abnormal growth includes deformed trees where gravity influences auxin transport, producing heterogeneous radial growth. Cross-sectional microscopic views are also provided to validate the model's hypothesis and results.     

Capturing microscopic features of bone remodeling into a macroscopic model based on biological rationales of bone adaptation

To understand Wolff’s law, bone adaptation by remodeling at the cellular and tissue levels has been discussed extensively through experimental and simulation studies. For the clinical application of a bone remodeling simulation, it is significant to establish a macroscopic model that incorporates clarified microscopic mechanisms. In this study, we proposed novel macroscopic models based on the microscopic mechanism of osteocytic mechanosensing, in which the flow of fluid in the lacuno-canalicular porosity generated by fluid pressure gradients plays an important role, and theoretically evaluated the proposed models, taking biological rationales of bone adaptation into account. The proposed models were categorized into two groups according to whether the remodeling equilibrium state was defined globally or locally, i.e., the global or local uniformity models. Each remodeling stimulus in the proposed models was quantitatively evaluated through image-based finite element analyses of a swine cancellous bone, according to two introduced criteria associated with the trabecular volume and orientation at remodeling equilibrium based on biological rationales. The evaluation suggested that nonuniformity of the mean stress gradient in the local uniformity model, one of the proposed stimuli, has high validity. Furthermore, the adaptive potential of each stimulus was discussed based on spatial distribution of a remodeling stimulus on the trabecular surface. The theoretical consideration of a remodeling stimulus based on biological rationales of bone adaptation would contribute to the establishment of a clinically applicable and reliable simulation model of bone remodeling.     

A reaction-diffusion model to predict the influence of neo-matrix on the subsequent development of tissue-engineered cartilage

Extracellular matrix (ECM) in chondrocytes-seeded agarose aggregates to form islands of matrix. These islands need to coalesce to develop functional cartilage. Hence, macroscopic properties are determined by transport and aggregation of macromolecules at the microscale, which varies temporally and spatially. This study evaluates the importance of the mutual interaction between matrix components and matrix development. Fluorescence recovery after photobleaching measurements demonstrates that diffusivity depends on the presence and density of ECM. A reaction-diffusion model describing synthesis, transport and immobilisation of ECM predicts steep gradients in ECM around chondrocytes, resembling histology. Steric hindrance of diffusion by ECM is essential for the formation of these gradients. Finally, microscopic ECM concentration is linked with macroscopic mechanical properties. Construct softening is predicted when temporal and spatial variations in diffusivity are considered. In conclusion, non-constant diffusion renders significant effects on both the microscopic ECM development and the macroscopic mechanical properties of developing tissue-engineered cartilage.     

Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure

Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved. We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity. We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.     

The impact of phenotypic switching on glioblastoma growth and invasion

The brain tumour glioblastoma is characterised by diffuse and infiltrative growth into surrounding brain tissue. At the macroscopic level, the progression speed of a glioblastoma tumour is determined by two key factors: the cell proliferation rate and the cell migration speed. At the microscopic level, however, proliferation and migration appear to be mutually exclusive phenotypes, as indicated by recent in vivo imaging data. Here, we develop a mathematical model to analyse how the phenotypic switching between proliferative and migratory states of individual cells affects the macroscopic growth of the tumour. For this, we propose an individual-based stochastic model in which glioblastoma cells are either in a proliferative state, where they are stationary and divide, or in motile state in which they are subject to random motion. From the model we derive a continuum approximation in the form of two coupled reaction-diffusion equations, which exhibit travelling wave solutions whose speed of invasion depends on the model parameters. We propose a simple analytical method to predict progression rate from the cell-specific parameters and demonstrate that optimal glioblastoma growth depends on a non-trivial trade-off between the phenotypic switching rates. By linking cellular properties to an in vivo outcome, the model should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.     

A microscopic model of enzyme kinetics.

Many in vivo enzymatic processes, such as those of the tissue factor pathway of blood coagulation, occur in environments with facilitated substrate delivery or enzymes bound to cellular or lipid surfaces, which are quite different from the ideal fluid environment for which the Michaelis-Menten equation was derived. To describe the kinetics of such reactions, we propose a microscopic model that focuses on the kinetics of a single-enzyme molecule. This model provides the foundation for macroscopic models of the system kinetics of reactions occurring in both ideal and nonideal environments. For ideal reaction systems, the corresponding macroscopic models thus derived are consistent with the Michaelis-Menten equation. It is shown that the apparent Km is in fact a function of the mechanism of substrate delivery and should be interpreted as the substrate level at which the enzyme vacancy time equals the residence time of ES-complexes; it is suggested that our microscopic model parameters characterize more accurately an enzyme and its catalytic efficiency than does the classical Km. This model can also be incorporated into computer simulations of more complex reactions as an alternative to explicit analytical formulation of a macroscopic model.     

Elastic Properties of Polymer Networks

Many fundamental questions for the understanding of polymer melts and networks are more suitably addressed by current computer simulations than by experiments. The reason is that simulations have simultaneous access to the microscopic structure and the macroscopic behavior of well-defined model systems. The coarse-grained models used often bear little relation to actual chemical species. This is justified by the experimentally established universality of polymer dynamics and no limitation for the test and development of theories which are directed at these universal aspects. The difficulties already encountered on this level will be illustrated for entanglements between polymers which dominate the dynamic in dense systems.For practical purposes it would, of coarse, be desirable to predict the characteristic length and time scales of experimental systems from the chemical structure of the polymer chains. Due to the extremely long relaxation times it is impossible to achieve this in brute-force simulations of truely microscopic models. Systematic coarse-graining combined with a better theoretical understanding seem to offer a practical alternative.Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1007/s0089460020293     

A systematic concept in bioprocess analysis and design

A systematic concept in bioprocess analysis and design is presented according to an integrating strategy as basis for a biotechnological methodology. A comparison illustrates analogies and significant differences between chemical and biological processes. The study of the interactions between environments and organisms includes influences of physical transport phenomena and also enzyme and metabolic regulations. In both cases the macroscopic principle with a formalkinetic approach is recommended for quantification purposes. The determination of the characteristic-time-regime with characteristic rate constants makesit possible to simplify mathematical modeling using the concepts of the rate-determining-step and quasistationarity. Finally, guidelines are summarized for the use of unstructured and structured kinetic models.     

From Microscopic to Macroscopic Descriptions of Cell Migration on Growing Domains

Cell migration and growth are essential components of the development of multicellular organisms. The role of various cues in directing cell migration is widespread, in particular, the role of signals in the environment in the control of cell motility and directional guidance. In many cases, especially in developmental biology, growth of the domain also plays a large role in the distribution of cells and, in some cases, cell or signal distribution may actually drive domain growth. There is an almost ubiquitous use of partial differential equations (PDEs) for modelling the time evolution of cellular density and environmental cues. In the last 20 years, a lot of attention has been devoted to connecting macroscopic PDEs with more detailed microscopic models of cellular motility, including models of directional sensing and signal transduction pathways. However, domain growth is largely omitted in the literature. In this paper, individual-based models describing cell movement and domain growth are studied, and correspondence with a macroscopic-level PDE describing the evolution of cell density is demonstrated. The individual-based models are formulated in terms of random walkers on a lattice. Domain growth provides an extra mathematical challenge by making the lattice size variable over time. A reaction–diffusion master equation formalism is generalised to the case of growing lattices and used in the derivation of the macroscopic PDEs.     

Calculations of electrostatic energies in proteins. The energetics of ionized groups in bovine pancreatic trypsin inhibitor

The importance of including different energy contributions in calculations of electrostatic energies in proteins is examined by calculating the intrinsic pKa values of the acidic groups of bovine pancreatic trypsin inhibitor. It appears that such calculations provide a powerful and revealing test; the relevant solvation energies of the ionized acids are of the order of -70 kcal/mol (1 cal = 4.184 J), and microscopic calculations that do not attempt to simulate the complete protein dielectric effect (including the surrounding solvent) can underestimate the solvation energy by as much as 50 kcal/mol. Reproducing correctly, by the same set of parameters, the solvation energies of ionized acids in different sites of a protein cannot be accomplished by including only part of the key energy contributions. The problems associated with macroscopic calculations are also considered and illustrated by the specific case of bovine pancreatic trypsin inhibitor. A promising approach is shown to be provided by a refinement of the previously developed Protein Dipoles Langevin Dipoles model. This model seems to represent consistently the microscopic dielectric of the protein and the surrounding water molecules. The model overcomes the problems associated with the macroscopic models (by treating explicitly the solvent molecules) and avoids the convergence problems associated with all-atom solvent models (by treating the average solvent polarization rather than averaging the actual polarization energy). This paper describes in detail the actual implementation of the model and examines its performance in evaluating intrinsic pKa values. Preliminary microscopic considerations of charge-charge interactions are presented.     

Mesoscopic Model of Actin-Based Propulsion

Two theoretical models dominate current understanding of actin-based propulsion: microscopic polymerization ratchet model predicts that growing and writhing actin filaments generate forces and movements, while macroscopic elastic propulsion model suggests that deformation and stress of growing actin gel are responsible for the propulsion. We examine both experimentally and computationally the 2D movement of ellipsoidal beads propelled by actin tails and show that neither of the two models can explain the observed bistability of the orientation of the beads. To explain the data, we develop a 2D hybrid mesoscopic model by reconciling these two models such that individual actin filaments undergoing nucleation, elongation, attachment, detachment and capping are embedded into the boundary of a node-spring viscoelastic network representing the macroscopic actin gel. Stochastic simulations of this ‘in silico’ actin network show that the combined effects of the macroscopic elastic deformation and microscopic ratchets can explain the observed bistable orientation of the actin-propelled ellipsoidal beads. To test the theory further, we analyze observed distribution of the curvatures of the trajectories and show that the hybrid model''s predictions fit the data. Finally, we demonstrate that the model can explain both concave-up and concave-down force-velocity relations for growing actin networks depending on the characteristic time scale and network recoil. To summarize, we propose that both microscopic polymerization ratchets and macroscopic stresses of the deformable actin network are responsible for the force and movement generation.     

Complex growth dynamics in batch cultures: experiments and cybernetic models

The cybernetic framework developed by Ramkrishna and co-workers is shown to encompass the regulation of nutrient transport processes as well as the effect of nutrient transport on the biotic phase. A structured model which accounts for both an abiotic or environmental phase and a biotic or cellular phase is proposed to describe bacterial growth on lactose as the limiting carbon and energy source. In the presence of lactose, competing uptake mechanisms are proposed. At low lactose concentrations, an energy-requiring transport process is the preferred uptake mechanism. The coupling between cellular energetics and nutrient uptake results in an interesting intermittent growth phenomenon. As the concentration of lactose increases, a nonenergetic transport process is preferred and cellular growth ceases to be intermittent. Model simulations are compared with previously reported experimental results and exhibit good agreement over the entire range of initial lactose concentrations.     

M5 mesoscopic and macroscopic models for mesenchymal motion

In this paper mesoscopic (individual based) and macroscopic (population based) models for mesenchymal motion of cells in fibre networks are developed. Mesenchymal motion is a form of cellular movement that occurs in three-dimensions through tissues formed from fibre networks, for example the invasion of tumor metastases through collagen networks. The movement of cells is guided by the directionality of the network and in addition, the network is degraded by proteases. The main results of this paper are derivations of mesoscopic and macroscopic models for mesenchymal motion in a timely varying network tissue. The mesoscopic model is based on a transport equation for correlated random walk and the macroscopic model has the form of a drift-diffusion equation where the mean drift velocity is given by the mean orientation of the tissue and the diffusion tensor is given by the variance-covariance matrix of the tissue orientations. The transport equation as well as the drift-diffusion limit are coupled to a differential equation that describes the tissue changes explicitly, where we distinguish the cases of directed and undirected tissues. As a result the drift velocity and the diffusion tensor are timely varying. We discuss relations to existing models and possible applications.Dedicated to K.P. Hadeler, a great scientist, teacher, and friend.