Stochastic simulation of structured skin cell population dynamics

The epidermis is the outmost skin tissue. It operates as a first defense system to process inflammatory signals and responds by producing inflammatory mediators that promote the recruitment of immune cells. Various skin diseases such as atopic dermatitis occur as a result of the defect of proper skin barrier function and successive impaired inflammatory responses. The onset of such a skin disease links to the disturbed epidermal homeostasis regulated by appropriate self-renewal and differentiation of epidermal stem cells. The theory of physiologically structured population models provides a versatile framework to formulate mathematical models which describe the growth dynamics of a cell population such as the epidermis. In this paper, we develop an algorithm to implement stochastic simulation for a class of physiologically structured population models. We demonstrate that the developed algorithm is applicable to several cell population models and typical age-structured population models. On the basis of the developed algorithm, we investigate stochastic dynamics of skin cell populations and spread of inflammation. It is revealed that demographic stochasticity can bring considerable impact on the outcome of inflammation spread at the tissue level.     

The cell graphs of cancer

We report a novel, proof-of-concept, computational method that models a type of brain cancer (glioma) only by using the topological properties of its cells in the tissue image. From low-magnification (80x) tissue images of 384 x 384 pixels, we construct the graphs of the cells based on the locations of the cells within the images. We generate such cell graphs of 1000-3000 cells (nodes) with 2000-10,000 links, each of which is calculated as a decaying exponential function of the Euclidean distance between every pair of cells in accordance with the Waxman model. At the cellular level, we compute the graph metrics of the cell graphs, including the degree, clustering coefficient, eccentricity and closeness for each cell. Working with a total of 285 tissue samples surgically removed from 12 different patients, we demonstrate that the self-organizing clusters of cancerous cells exhibit distinctive graph metrics that distinguish them from the healthy cells and the unhealthy inflamed cells at the cellular level with an accuracy of at least 85%. At the tissue level, we accomplish correct tissue classifications of cancerous, healthy and non-neoplastic inflamed tissue samples with an accuracy of 100% by requiring correct classification for the majority of the cells within the tissue sample.     

The cellular basis of cell sorting kinetics

Cell sorting is a dynamical cooperative phenomenon that is fundamental for tissue morphogenesis and tissue homeostasis. According to Steinberg's differential adhesion hypothesis, the structure of sorted cell aggregates is determined by physical characteristics of the respective tissues, the tissue surface tensions. Steinberg postulated that tissue surface tensions result from quantitative differences in intercellular adhesion. Several experiments in cell cultures as well as in developing organisms support this hypothesis.The question of how tissue surface tension might result from differential adhesion was addressed in some theoretical models. These models describe the cellular interdependence structure once the temporal evolution has stabilized. In general, these models are capable of reproducing sorted patterns. However, the model dynamics at the cellular scale are defined implicitly and are not well-justified. The precise mechanism describing how differential adhesion generates the observed sorting kinetics at the tissue level is still unclear.It is necessary to formulate the concepts of cell level kinetics explicitly. Only then it is possible to understand the temporal development at the cellular and tissue scales. Here we argue that individual cell mobility is reduced the more the cells stick to their neighbors. We translate this assumption into a precise mathematical model which belongs to the class of stochastic interacting particle systems. Analyzing this model, we are able to predict the emergent sorting behavior at the population level. We describe qualitatively the geometry of cell segregation depending on the intercellular adhesion parameters. Furthermore, we derive a functional relationship between intercellular adhesion and surface tension and highlight the role of cell mobility in the process of sorting. We show that the interaction between the cells and the boundary of a confining vessel has a major impact on the sorting geometry.     

Three dimensional tissue and organ models in vitro: their application in basic and practical research

Good and reliable three dimensional biomodel in vitro should mimic the in vivo structure and function of investigated tissue or organ. This can be achieved through the interaction of various cell types and the environment (extracellular matrix, as well as spatial cell contacts). While designing such a model it is necessary to find best nutritive and adhesive factors, to allow access to components of optimal matrix and to enable cell contacts in three dimensions. The response and function of such models reminds physiological function of tissue of origin. Over several years there has been an increasing number of experiments and publications reporting research involving spatial cell models. This model and its structural and molecular analysis clearly showed, that in comparison with conventional cultures, mainly monocultures grown as monolayers, spatial cultures resemble the in vivo situation with regard to cell shape and biological behaviour. Spatial arrangement of cells and the environment can direct tissue differentiation. Interesting example of the importance of the environment for the latter, is the finding that the ectopic implantation of embryonic cells transforms them into malignant tissue while the same cells located in the uterus undergo normal embryogenesis. The present review describes several three-dimensional models in vitro and their application in basic and practical studies. It is especially interesting and important in the light of developments of tissue modeling to obtain in vitro substitutes of damaged or impaired tissues and organs. Other demands come from animal protectionists who suggest replacement of experimental animals with cultures and tissue models in bio-, pharmacological, and toxicological assays. In response, European Union legislation introduces increasing restrictions on animal experiments. At last, researchers seek in vitro models which would enable avoiding discrepancies between in vitro and in vivo results.     

High-resolution finite element models with tissue strength asymmetry accurately predict failure of trabecular bone

The ability to predict trabecular failure using microstructure-based computational models would greatly facilitate study of trabecular structure–function relations, multiaxial strength, and tissue remodeling. We hypothesized that high-resolution finite element models of trabecular bone that include cortical-like strength asymmetry at the tissue level, could predict apparent level failure of trabecular bone for multiple loading modes. A bilinear constitutive model with asymmetric tissue yield strains in tension and compression was applied to simulate failure in high-resolution finite element models of seven bovine tibial specimens. Tissue modulus was reduced by 95% when tissue principal strains exceeded the tissue yield strains. Linear models were first calibrated for effective tissue modulus against specimen-specific experimental measures of apparent modulus, producing effective tissue moduli of (mean±S.D.) 18.7±3.4 GPa. Next, a parameter study was performed on a single specimen to estimate the tissue level tensile and compressive yield strains. These values, 0.60% strain in tension and 1.01% strain in compression, were then used in non-linear analyses of all seven specimens to predict failure for apparent tensile, compressive, and shear loading. When compared to apparent yield properties previously measured for the same type of bone, the model predictions of both the stresses and strains at failure were not statistically different for any loading case (p>0.15). Use of symmetric tissue strengths could not match the experimental data. These findings establish that, once effective tissue modulus is calibrated and uniform but asymmetric tissue failure strains are used, the resulting models can capture the apparent strength behavior to an outstanding level of accuracy. As such, these computational models have reached a level of fidelity that qualifies them as surrogates for destructive mechanical testing of real specimens.     

Coupled analysis of in vitro and histology tissue samples to quantify structure-function relationship

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models.     

VirtualLeaf: an open-source framework for cell-based modeling of plant tissue growth and development

Plant organs, including leaves and roots, develop by means of a multilevel cross talk between gene regulation, patterned cell division and cell expansion, and tissue mechanics. The multilevel regulatory mechanisms complicate classic molecular genetics or functional genomics approaches to biological development, because these methodologies implicitly assume a direct relation between genes and traits at the level of the whole plant or organ. Instead, understanding gene function requires insight into the roles of gene products in regulatory networks, the conditions of gene expression, etc. This interplay is impossible to understand intuitively. Mathematical and computer modeling allows researchers to design new hypotheses and produce experimentally testable insights. However, the required mathematics and programming experience makes modeling poorly accessible to experimental biologists. Problem-solving environments provide biologically intuitive in silico objects ("cells", "regulation networks") required for setting up a simulation and present those to the user in terms of familiar, biological terminology. Here, we introduce the cell-based computer modeling framework VirtualLeaf for plant tissue morphogenesis. The current version defines a set of biologically intuitive C++ objects, including cells, cell walls, and diffusing and reacting chemicals, that provide useful abstractions for building biological simulations of developmental processes. We present a step-by-step introduction to building models with VirtualLeaf, providing basic example models of leaf venation and meristem development. VirtualLeaf-based models provide a means for plant researchers to analyze the function of developmental genes in the context of the biophysics of growth and patterning. VirtualLeaf is an ongoing open-source software project (http://virtualleaf.googlecode.com) that runs on Windows, Mac, and Linux.     

Construction of Defined Human Engineered Cardiac Tissues to Study Mechanisms of Cardiac Cell Therapy

Human cardiac tissue engineering can fundamentally impact therapeutic discovery through the development of new species-specific screening systems that replicate the biofidelity of three-dimensional native human myocardium, while also enabling a controlled level of biological complexity, and allowing non-destructive longitudinal monitoring of tissue contractile function. Initially, human engineered cardiac tissues (hECT) were created using the entire cell population obtained from directed differentiation of human pluripotent stem cells, which typically yielded less than 50% cardiomyocytes. However, to create reliable predictive models of human myocardium, and to elucidate mechanisms of heterocellular interaction, it is essential to accurately control the biological composition in engineered tissues. To address this limitation, we utilize live cell sorting for the cardiac surface marker SIRPα and the fibroblast marker CD90 to create tissues containing a 3:1 ratio of these cell types, respectively, that are then mixed together and added to a collagen-based matrix solution. Resulting hECTs are, thus, completely defined in both their cellular and extracellular matrix composition.Here we describe the construction of defined hECTs as a model system to understand mechanisms of cell-cell interactions in cell therapies, using an example of human bone marrow-derived mesenchymal stem cells (hMSC) that are currently being used in human clinical trials. The defined tissue composition is imperative to understand how the hMSCs may be interacting with the endogenous cardiac cell types to enhance tissue function. A bioreactor system is also described that simultaneously cultures six hECTs in parallel, permitting more efficient use of the cells after sorting.     

Effects of low testosterone levels and of adrenal androgens on growth of prostate tumor models in nude mice

Two transplantable, androgen dependent prostate tumor models of human origin, PC-82 and PC-EW, were used to study the effect of low androgen levels and adrenal androgens on prostate tumor cell proliferation. Tumor load of the PC-82 and PC-EW tumors could be maintained constant when plasma testosterone levels were 0.8 and 0.9 nmol/l, respectively, corresponding with an intratissue 5-dihydrotestosterone level of 3–4 pmol/g tissue. This critical androgen level for prostate tumor growth stimulation amounted to 2–3 times the castration level and proved to be similar for both tumor models. Relatively high levels of androstenedione resulted in physiological levels of plasma testosterone causing androgen concentrations in PC-82 tumor tissue exceeding the critical level for tumor growth. These results indicate that submaximal suppression of androgens can stop tumor growth in these prostate tumor models.     

Selected contribution: a three-dimensional model for assessment of in vitro toxicity in balaena mysticetus renal tissue.

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.     

Modeling radiation dose and effects from internal emitters in nuclear medicine: from the whole body to individual cells.

In nuclear medicine, proper application of radiation protection principles depends on balancing the potential risks of exposure to ionizing radiation against its possible benefits. Average doses to organs, in diagnostic or therapeutic applications, are not always representative of the doses received at the tissue or cellular level. Therefore, understanding of the relationship between the overall biological effect and absorbed dose delivered by the radiopharmaceutical may require study of doses at the organ, tissue, or cell level. In this paper, we review current models for radiation dose assessment, with consideration of the different models and assumptions employed for study at all levels of investigation.     

Potential advantages of acute kidney injury management by mesenchymal stem cells

Mesenchymal stem cells are currently considered as a promising tool for therapeutic application in acute kidney injury (AKI) management. AKI is characterized by acute tubular injury with rapid loss of renal function. After AKI, inflammation, oxidative stress and excessive deposition of extracellular matrix are the molecular events that ultimately cause the end-stage renal disease. Despite numerous improvement of supportive therapy, the mortality and morbidity among patients remain high. Therefore, exploring novel therapeutic options to treat AKI is mandatory. Numerous evidence in animal models has demonstrated the capability of mesenchymal stem cells (MSCs) to restore kidney function after induced kidney injury. After infusion, MSCs engraft in the injured tissue and release soluble factors and microvesicles that promote cell survival and tissue repairing. Indeed, the main mechanism of action of MSCs in tissue regeneration is the paracrine/endocrine secretion of bioactive molecules. MSCs can be isolated from several tissues, including bone marrow, adipose tissue, and blood cord; pre-treatment procedures to improve MSCs homing and their paracrine function have been also described. This review will focus on the application of cell therapy in AKI and it will summarize preclinical studies in animal models and clinical trials currently ongoing about the use of mesenchymal stem cells after AKI.     

Endothelial development taking shape

Blood vessel development is a vital process during embryonic development, during tissue growth, regeneration and disease processes in the adult. In the past decade researchers have begun to unravel basic molecular mechanisms that regulate the formation of vascular lumen, sprouting angiogenesis, fusion of vessels, and pruning of the vascular plexus. The understanding of the biology of these angiogenic processes is increasingly driven through studies on vascular development at the cellular resolution. Single cell analysis in vivo, advanced genetic tools and the widespread use of powerful animal models combined with improved imaging possibilities are delivering new insights into endothelial cell form, function and behavior angiogenesis. Moreover, the combination of in silico modeling and experimentation including dynamic imaging promotes insights into higher level cooperative behavior leading to functional patterning of vascular networks. Here we summarize recent concepts and advances in the field of vascular development, focusing in detail on the endothelial cell.     

Polarity in Mammalian Epithelial Morphogenesis

Cell polarity is fundamental for the architecture and function of epithelial tissues. Epithelial polarization requires the intervention of several fundamental cell processes, whose integration in space and time is only starting to be elucidated. To understand what governs the building of epithelial tissues during development, it is essential to consider the polarization process in the context of the whole tissue. To this end, the development of three-dimensional organotypic cell culture models has brought new insights into the mechanisms underlying the establishment and maintenance of higher-order epithelial tissue architecture, and in the dynamic remodeling of cell polarity that often occurs during development of epithelial organs. Here we discuss some important aspects of mammalian epithelial morphogenesis, from the establishment of cell polarity to epithelial tissue generation.     

Systems biology in drug discovery

The hope of the rapid translation of 'genes to drugs' has foundered on the reality that disease biology is complex, and that drug development must be driven by insights into biological responses. Systems biology aims to describe and to understand the operation of complex biological systems and ultimately to develop predictive models of human disease. Although meaningful molecular level models of human cell and tissue function are a distant goal, systems biology efforts are already influencing drug discovery. Large-scale gene, protein and metabolite measurements ('omics') dramatically accelerate hypothesis generation and testing in disease models. Computer simulations integrating knowledge of organ and system-level responses help prioritize targets and design clinical trials. Automation of complex primary human cell-based assay systems designed to capture emergent properties can now integrate a broad range of disease-relevant human biology into the drug discovery process, informing target and compound validation, lead optimization, and clinical indication selection. These systems biology approaches promise to improve decision making in pharmaceutical development.     

Action Potential Duration Heterogeneity of Cardiac Tissue Can Be Evaluated from Cell Properties Using Gaussian Green's Function Approach

Action potential duration (APD) heterogeneity of cardiac tissue is one of the most important factors underlying initiation of deadly cardiac arrhythmias. In many cases such heterogeneity can be measured at tissue level only, while it originates from differences between the individual cardiac cells. The extent of heterogeneity at tissue and single cell level can differ substantially and in many cases it is important to know the relation between them. Here we study effects from cell coupling on APD heterogeneity in cardiac tissue in numerical simulations using the ionic TP06 model for human cardiac tissue. We show that the effect of cell coupling on APD heterogeneity can be described mathematically using a Gaussian Green''s function approach. This relates the problem of electrotonic interactions to a wide range of classical problems in physics, chemistry and biology, for which robust methods exist. We show that, both for determining effects of tissue heterogeneity from cell heterogeneity (forward problem) as well as for determining cell properties from tissue level measurements (inverse problem), this approach is promising. We illustrate the solution of the forward and inverse problem on several examples of 1D and 2D systems.     

Emerging models and paradigms for stem cell ageing

Ageing is accompanied by a progressive decline in stem cell function, resulting in less effective tissue homeostasis and repair. Here we discuss emerging invertebrate models that provide insights into molecular pathways of age-related stem cell dysfunction in mammals, and we present various paradigms of how stem cell functionality changes with age, including impaired self-renewal and aberrant differentiation potential.     

Tumor necrosis factor-alpha-induced insulin resistance in adipocytes

Recent studies examining the link between insulin resistance and the development of obesity and noninsulin-dependent diabetes mellitus are consistent with the involvement of tumor necrosis factor-alpha (TNF-alpha) as a central mediator. In insulin resistant obese mouse models, neutralization of TNF-alpha in circulation has been demonstrated to restore insulin-mediated glucose uptake. Adipose tissue has been shown to be a site for synthesis of TNF-alpha, with the degree of adiposity directly correlated with the level of synthesis. Studies conducted on obese human patients have demonstrated a correlation between levels of TNF-alpha, the extent of obesity, as well as the level of hyperinsulinemia observed. Mechanistic studies in cell culture have suggested that TNF-alpha functions to render cells insulin resistant through regulation of the synthesis of the insulin responsive glucose transporter as well as through interference with insulin signaling. This review will address these issues and additionally introduce the reader to the molecular aspects of TNF-alpha, its receptors as well as TNF-alpha-initiated signaling cascades, that are necessary to understand the function of this cytokine in the regulation of adipose tissue metabolism.