Dawn Walker

Agent-based computational modeling of wounded epithelial cell monolayers

Computational modeling of biological systems, or in silico biology, is an emerging tool for understanding structure and order in biological tissues. Computational models of the behavior of epithelial cells in monolayer cell culture have been developed and used to predict the healing characteristics of scratch wounds made to urothelial cell cultures maintained in low- and physiological [Ca/sup 2+/] environments. Both computational models and in vitro experiments demonstrated that in low exogenous [Ca/sup 2+/], the closure of 500-/spl mu/m scratch wounds was achieved primarily by cell migration into the denuded area. The wound healing rate in low (0.09 mM) [Ca/sup 2+/] was approximately twice as rapid as in physiological (2 mM) [Ca/sup 2+/]. Computational modeling predicted that in cell cultures that are actively proliferating, no increase in the fraction of cells in the S-phase would be expected, and this conclusion was supported experimentally in vitro by bromodeoxyuridine incorporation assay. We have demonstrated that a simple rule-based model of cell behavior, incorporating rules relating to contact inhibition of proliferation and migration, is sufficient to qualitatively predict the calcium-dependent pattern of wound closure observed in vitro. Differences between the in vitro and in silico models suggest a role for wound-induced signaling events in urothelial cell cultures.

The application of multiscale modelling to the process of development and prevention of stenosis in a stented coronary artery

The inherent complexity of biomedical systems is well recognized; they are multiscale, multiscience systems, bridging a wide range of temporal and spatial scales. While the importance of multiscale modelling in this context is increasingly recognized, there is little underpinning literature on the methodology and generic description of the process. The COAST (complex autonoma simulation technique) project aims to address this by developing a multiscale, multiscience framework, coined complex autonoma (CxA), based on a hierarchical aggregation of coupled cellular automata (CA) and agent-based models (ABMs). The key tenet of COAST is that a multiscale system can be decomposed into N single-scale CA or ABMs that mutually interact across the scales. Decomposition is facilitated by building a scale separation map on which each single-scale system is represented according to its spatial and temporal characteristics. Processes having well-separated scales are thus easily identified as the components of the multiscale model. This paper focuses on methodology, introduces the concept of the CxA and demonstrates its use in the generation of a multiscale model of the physical and biological processes implicated in a challenging and clinically relevant problem, namely coronary artery in-stent restenosis.

A study of the morphological parameters of cervical squamous epithelium

Electrical impedance spectroscopy is a technique that has been investigated as a potential method for the diagnosis of epithelial carcinomas. Finite element modelling can provide an insight into the patterns of current flow in normal and pathological epithelium and hence aid in the process of probe design optimization. In order to develop a finite element model of the structure of normal and precancerous cervical squamous epithelium, it was first necessary to obtain the mean values and ranges of a number of morphological tissue parameters. The most important parameters in discriminating normal from neoplastic tissue were identified as being cell size and shape distribution, nuclear-to-cytoplasmic volume ratio and volume of extracellular space. A survey of the literature revealed an absence of reliable quantitative data for these parameters. We therefore present the results of our own basic image analysis on normal and pathological tissue sections, which we hope will be of use to other workers wishing to model cervical squamous epithelium, or other similar tissue structures.

A Complex Automata approach for in-stent restenosis: two-dimensional multiscale modelling and simulations

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale system involving a large number of biological and physical processes. We describe a Complex Automata model for in-stent restenosis, coupling bulk flow, drug diffusion, and smooth muscle cell models, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. Preliminary results show that the model can reproduce growth trends observed in experimental studies and facilitate testing of hypotheses concerning the interaction of key factors.

Modelling of epithelial tissue impedance measured using three different designs of probe

Impedance measurement is a promising technique for detecting pre-malignant changes in epithelial tissue. This paper considers how the design of the impedance probe affects the ability to discriminate between tissue types. To do this, finite element models of the electrical properties of squamous and glandular columnar epithelia have been used. The glandular tissue model is described here for the first time. Glandular mucosa is found in many regions of the gastrointestinal tract, such as the stomach and intestine, and has a large effective surface area. Firstly, the electrical properties of a small section of gland, with epithelial cells and supportive tissue, are determined. These properties are then used to build up a three-dimensional model of a whole section of mucosa containing many thousands of glands. Measurements using different types of impedance probe were simulated by applying different boundary conditions to the models. Transepithelial impedance, and tetrapolar measurement with a probe placed on the tissue surface have been modelled. In the latter case, the impedance can be affected by conductive fluid, such as mucus, on the tissue surface. This effect has been investigated, and a new design of probe, which uses a guard electrode to counteract this potential source of variability, is proposed.

Modelled current distribution in cervical squamous tissue.

The electrical properties of cervical squamous epithelium have been modelled in the frequency range 100 Hz to 10 MHz. The hierarchical modelling process comprises a cellular level stage, which includes detailed models of cells typical of different depths within the epithelium and a tissue model, which utilizes electrical properties obtained from the cellular models. The fit between the modelled and measured impedance spectra and the distribution of current with depth depends on the macroscopic model structure. Both the properties of the basement membrane and the presence of a surface mucus layer are shown to have a significant effect. The best fit with measured data is obtained when a 10 microm thick, high-conductivity surface layer is included in the tissue model.

Functional expression of purinergic P2 receptors and transient receptor potential channels by the human urothelium

In addition to its role as a physical barrier, the urothelium is considered to play an active role in mechanosensation. A key mechanism is the release of transient mediators that activate purinergic P2 receptors and transient receptor potential (TRP) channels to effect changes in intracellular Ca²⁺. Despite the implied importance of these receptors and channels in urothelial tissue homeostasis and dysfunctional bladder disease, little is known about their functional expression by the human urothelium. To evaluate the expression and function of P2X and P2Y receptors and TRP channels, the human ureter and bladder were used to separate urothelial and stromal tissues for RNA isolation and cell culture. RT-PCR using stringently designed primer sets was used to establish which P2 and TRP species were expressed at the transcript level, and selective agonists/antagonists were used to confirm functional expression by monitoring changes in intracellular Ca²⁺ and in a scratch repair assay. The results confirmed the functional expression of P2Y₄ receptors and excluded nonexpressed receptors/channels (P2X₁, P2X₃, P2X₆, P2Y₆, P2Y₁₁, TRPV5, and TRPM8), while a dearth of specific agonists confounded the functional validation of expressed P2X₂, P2X₄, P2Y₁, P2Y₂, TRPV2, TRPV3, TRPV6 and TRPM7 receptors/channels. Although a conventional response was elicited in control stromal-derived cells, the urothelial cell response to well-characterized TRPV1 and TRPV4 agonists/antagonists revealed unexpected anomalies. In addition, agonists that invoked an increase in intracellular Ca²⁺ promoted urothelial scratch repair, presumably through the release of ATP. The study raises important questions about the ligand selectivity of receptor/channel targets expressed by the urothelium. These pathways are important in urothelial tissue homeostasis, and this opens the possibility of selective drug targeting.

Modelling the electrical properties of bladder tissue?quantifying impedance changes due to inflammation and oedema

Electrical impedance spectroscopy has been developed as a potential method for the diagnosis of carcinoma in epithelial tissues. An understanding of the influence of structural changes in the tissue on the properties measured using this technique is essential for interpreting measured data and optimization of probe design. In contrast to other tissue types, carcinoma in situ of the bladder gives rise to an increase in electrical impedance over the kHz-MHz frequency range in comparison to normal tissue. Finite element models of the urothelium and the underlying superficial lamina propria have been constructed and solved in order to ascertain the influence of structural changes associated with malignancy, oedema and inflammation on the measured electrical properties of the tissue. Sensitivity analysis of results from a composite tissue model suggests that the increase in lymphocyte density in the lamina propria associated with an inflammatory response to the infiltration of urine into the tissue may explain these unusual electrical properties.

Electrical bioimpedance readings increase with higher pressure applied to the measuring probe

Electrical bioimpedance spectroscopy (EBIS) is a technique that uses a probe to calculate the transfer impedance from tissues. This transfer impedance can give information about the normal or pathological condition of the tissue. To take readings, pressure has to be applied to the probe in order to get a good contact between the electrodes and the tissue. We have been using EBIS to investigate the early diagnosis of dysplasia and cancer in the human cervix, oesophagus and bladder. We have found that, with increasing pressure (range used here was approximately 1 kPa to approximately 50 kPa), the resistivity readings increase in a consistent way up to 80%. In this paper, we show how this is a case in three different tissue types (oesophageal, gastric and vesical samples). These increases can be higher than those associated with the pathological changes that we are investigating (non-inflamed columnar tissue, for instance, shows values 50% higher than dysplastic columnar tissue). Finite-element modelling was also used to investigate the effect of volume reduction in the connective tissue or stroma. This simulation suggests no strong correlation between reduction of this structure and increase in resistivity. We hypothesize therefore that these changes may be mainly associated with the squeezing of water from the extracellular space. Finally, as pressure is difficult to control by hand, we raise the issue of the necessity of considering this variable when making EIS measurements.

Development and validation of computational models of cellular interaction

In this paper we take the view that computational models of biological systems should satisfy two conditions – they should be able to predict function at a systems biology level, and robust techniques of validation against biological models must be available. A modelling paradigm for developing a predictive computational model of cellular interaction is described, and methods of providing robust validation against biological models are explored, followed by a consideration of software issues.