scholarly journals Mix & Match: Phenotypic coexistence as a key facilitator of solid tumour invasion

2019 ◽  
Author(s):  
Maximilian A. R. Strobl ◽  
Andrew L. Krause ◽  
Mehdi Damaghi ◽  
Robert Gillies ◽  
Alexander R. A. Anderson ◽  
...  
Keyword(s):  
Alternative Hypothesis ◽  
Cell Movement ◽  
Reaction Diffusion ◽  
Cell Types ◽  
The Body ◽  
Reaction Diffusion Equations ◽  
Species Competition ◽  
Invasion Process ◽  
Malignant Tumours ◽  
Reaction Diffusion Model

AbstractInvasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity an alternative hypothesis presents itself: Could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth, and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: i) a glycolytic phenotype which produces acid that kills stromal cells, and ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby-Gawlinski reaction-diffusion model to derive a system of five coupled reaction-diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: i) rapidly (matrix-degraders dominate), or ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated.

NEW DEVELOPMENTS IN AN ANATOMICAL FRAMEWORK FOR MODELING CARDIAC ISCHEMIA

2003 ◽  
Vol 13 (12) ◽  
pp. 3717-3722 ◽  
Author(s):  
NICOLAS SMITH ◽  
CAREY STEVENS ◽  
ANDREW PULLAN ◽  
PETER HUNTER ◽  
PETER MULQUINEY
Keyword(s):  
Sheet Material ◽  
Ionic Current ◽  
Reaction Diffusion ◽  
Wall Stress ◽  
Ventricular Myocardium ◽  
The Body ◽  
Reaction Diffusion Equations ◽  
Constitutive Law ◽  
Cardiac Contraction ◽  
Sheet Structure

A new, anatomically accurate, mathematical model of the right and left porcine ventricular myocardium is described based on measurements of the geometry and fibrous-sheet structure. Passive and active properties of the myocardium are calculated using an orthotropic constitutive law based on the fibrous-sheet structure and a biophysical cellular based model of cardiac contraction. Using Galerkin finite element techniques, the equations of finite deformation are solved to determine deformation and regional wall stress through the heart cycle. The mechanics model is coupled via myocardial wall stress, to a one-dimensional coronary blood flow model embedded in the myocardium. Bidomain electrical activation of the myocardium is also modeled, with ionic current based electrophysiological equations and reaction–diffusion equations based on orthotropic conductivity tensors referred to the fibrous-sheet material axes. Metabolic models are used to couple energy supply to contraction and excitation in the heart, and at the body surface, a framework for quantifying the effect of ischemic heart disease is developed.

scholarly journals A contraction-reaction-diffusion model for circular pattern formation in embryogenesis

2021 ◽  
Author(s):  
Tiankai Zhao ◽  
Yubing Sun ◽  
Xin Li ◽  
Mehdi Baghaee ◽  
Yuenan Wang ◽  
...  
Keyword(s):  
Pattern Formation ◽  
Cell Fate ◽  
Diffusion Model ◽  
Early Stage ◽  
Reaction Diffusion ◽  
Diffusion Models ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Reaction Diffusion Model ◽  
Stress Dependent

Reaction-diffusion models have been widely used to elucidate pattern formation in developmental biology. More recently, they have also been applied in modeling cell fate patterning that mimic early-stage human development events utilizing geometrically confined pluripotent stem cells. However, the traditional reaction-diffusion equations could not satisfactorily explain the concentric ring distributions of various cell types, as they do not yield circular patterns even for circular domains. In previous mathematical models that yield ring patterns, certain conditions that lack biophysical understandings had been considered in the reaction-diffusion models. Here we hypothesize that the circular patterns are the results of the coupling of the mechanobiological factors with the traditional reaction-diffusion model. We propose two types of coupling scenarios: tissue tension-dependent diffusion flux and traction stress-dependent activation of signaling molecules. By coupling reaction-diffusion equations with the elasticity equations, we demonstrate computationally that the contraction-reaction-diffusion model can naturally yield the circular patterns.

scholarly journals Correspondences between parameters in a reaction-diffusion model and connexin functions during zebrafish stripe formation

2021 ◽  
Author(s):  
Akiko Nakamasu
Keyword(s):  
Molecular Mechanisms ◽  
Reaction Diffusion ◽  
The Body ◽  
Pigment Cells ◽  
Turing Pattern ◽  
Reaction Diffusion Model ◽  
Spatial Periodicity ◽  
Pattern Formations ◽  
Mathematical Analyses ◽  
Spotted Pattern

Abstract Different diffusivities among interacting substances actualize the potential instability of a system. When these elicited instabilities manifested as forms of spatial periodicity, they are called Turing patterns. Simulations using general reaction-diffusion (RD) models have demonstrated that pigment patterns on the body trunk of growing fish follow a Turing pattern. Laser ablation experiments performed on zebrafish revealed apparent interactions among pigment cells, which allowed for a three-components RD model to be derived. However, the underlying molecular mechanisms responsible for Turing pattern formation in this system had been remained unknown. A zebrafish mutant with a spotted pattern was found to have a defect in Connexin41.8 (Cx41.8) which, together with Cx39.4, exists in pigment cells and controls pattern formations. Here, molecular-level evidence derived from connexin analyses was linked to the interactions among pigment cells described in previous RD modeling. Channels on pigment cells were generalized as “gates,” and the effects of respective gates were deduced. The model used partial differential equations (PDEs) to enable numerical and mathematical analyses of characteristics observed in the experiments. Furthermore, the improved PDE model included nonlinear reaction terms, enabled the consideration of the behavior of components.

HyAlx, an aristaless-related gene, is involved in tentacle formation in hydra

Development ◽  
2000 ◽  
Vol 127 (22) ◽  
pp. 4743-4752 ◽  
Author(s):  
K.M. Smith ◽  
L. Gee ◽  
H.R. Bode
Keyword(s):  
Expression Patterns ◽  
Reaction Diffusion ◽  
The Body ◽  
Related Gene ◽  
Axial Patterning ◽  
Bud Formation ◽  
Isolation And Characterization ◽  
Reaction Diffusion Model ◽  
Head Regeneration

Developmental gradients are known to play important roles in axial patterning in hydra. Current efforts are directed toward elucidating the molecular basis of these gradients. We report the isolation and characterization of HyAlx, an aristaless-related gene in hydra. The expression patterns of the gene in adult hydra, as well as during bud formation, head regeneration and the formation of ectopic head structures along the body column, indicate the gene plays a role in the specification of tissue for tentacle formation. The use of RNAi provides more direct evidence for this conclusion. The different patterns of HyAlx expression during head regeneration and bud formation also provide support for a recent version of a reaction-diffusion model for axial patterning in hydra.

Effects of Catastrophic Anemia in an Intra-Host Model of Malaria

2014 ◽  
Vol 24 (07) ◽  
pp. 1450105
Author(s):  
Eddy Takoutsing ◽  
Samuel Bowong ◽  
David Yemele ◽  
Jurgen Kurths
Keyword(s):  
Blood Cells ◽  
Malaria Parasite ◽  
Reaction Diffusion ◽  
The Body ◽  
Reaction Diffusion Equations ◽  
Reproduction Rate ◽  
Spatiotemporal Model ◽  
Cell Reproduction ◽  
Temporal Model ◽  
The Impact

In this paper, we develop a mathematical model to assess the strength of the effects of catastrophic anemia level on the dynamical transmission of malaria parasite within the body of a host. We first consider a temporal model. The important mathematical features of the model are thoroughly investigated. We found that the model exhibits forward bifurcation. We also consider a spatiotemporal model using reaction–diffusion equations. The model is numerically analyzed to assess the impact of anemia on the dynamical transmission of malaria parasite within the body of a host. Through numerical simulation, we found that malaria can lead to a catastrophic anemia level even if the parasite is nonpersistent within the body of a host. Numerical results also suggest that to reduce or control the anemia level, the strategy should be to accelerate innate cell reproduction rate or should have the ability to clean parasitized red blood cells (PRBCs) with a high mortality rate.

scholarly journals A COMPUTATIONAL ANALYSIS OF BONE FORMATION IN THE CRANIAL VAULT USING A COUPLED REACTION–DIFFUSION-STRAIN MODEL

2017 ◽  
Vol 17 (04) ◽  
pp. 1750073 ◽  
Author(s):  
CHANYOUNG LEE ◽  
JOAN T. RICHTSMEIER ◽  
REUBEN H. KRAFT
Keyword(s):  
Bone Formation ◽  
Mechanical Strain ◽  
Mathematical Formulation ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Cranial Vault ◽  
Model Parameters ◽  
Computational Domain ◽  
Reaction Diffusion Model

Bones of the murine cranial vault are formed by differentiation of mesenchymal cells into osteoblasts, a process that is primarily understood to be controlled by a cascade of reactions between extracellular molecules and cells. We assume that the process can be modeled using Turing's reaction–diffusion equations, a mathematical model describing the pattern formation controlled by two interacting molecules (activator and inhibitor). In addition to the processes modeled by reaction–diffusion equations, we hypothesize that mechanical stimuli of the cells due to growth of the underlying brain contribute significantly to the process of cell differentiation in cranial vault development. Structural analysis of the surface of the brain was conducted to explore the effects of the mechanical strain on bone formation. We propose a mechanobiological model for the formation of cranial vault bones by coupling the reaction-–diffusion model with structural mechanics. The mathematical formulation was solved using the finite volume method. The computational domain and model parameters are determined using a large collection of experimental data that provide precise three-dimensional (3D) measures of murine cranial geometry and cranial vault bone formation for specific embryonic time points. The results of this study suggest that mechanical strain contributes information to specific aspects of bone formation. Our mechanobiological model predicts some key features of cranial vault bone formation that were verified by experimental observations including the relative location of ossification centers of individual vault bones, the pattern of cranial vault bone growth over time, and the position of cranial vault sutures.

scholarly journals Analysis of dynamic morphogen scale invariance

2009 ◽  
Vol 6 (41) ◽  
pp. 1179-1191 ◽  
Author(s):  
David M. Umulis
Keyword(s):  
Scale Invariance ◽  
Reaction Diffusion ◽  
Cell Types ◽  
Transport Processes ◽  
Reaction Diffusion Equations ◽  
Local Concentration ◽  
Flux Dynamic ◽  
Multipotent Cells ◽  
Total Input ◽  
Distinct Cell

During the development of some tissues, fields of multipotent cells differentiate into distinct cell types in response to the local concentration of a signalling factor called a morphogen. Typically, individual organisms within a population differ in size, but their body plans appear to be scaled versions of a common template. Similarly, closely related species may differ by three or more orders of magnitude in size, yet common structures between species scale to have similar proportions. In standard reaction–diffusion equations, the morphogen range has a length scale that depends on a balance between kinetic and transport processes and not on the length or size of the field of cells being patterned. However, as shown here for a class of morphogen-patterning systems, a number of conditions lead to scale invariance of the morphogen distribution at equilibrium and during the transient approach to equilibrium. Equilibrium scale invariance requires conservation of the total binding site number and total input flux. Dynamic scale invariance additionally requires sufficient binding to slow the diffusion of ligand. The equations derived herein can be extended to the study of other perturbations to gain further insight into the processes regulating the robustness and scaling of morphogen-mediated pattern formation.

Dynamics Analysis in a Gierer–Meinhardt Reaction–Diffusion Model with Homogeneous Neumann Boundary Condition

2019 ◽  
Vol 29 (09) ◽  
pp. 1930025 ◽  
Author(s):  
Xiang-Ping Yan ◽  
Ya-Jun Ding ◽  
Cun-Hua Zhang
Keyword(s):  
Boundary Condition ◽  
Hopf Bifurcation ◽  
Neumann Boundary Condition ◽  
Neumann Boundary ◽  
Reaction Diffusion ◽  
Turing Instability ◽  
Reaction Diffusion Equations ◽  
Positive Equilibrium ◽  
Reaction Diffusion Model ◽  
Homogeneous Neumann Boundary Condition

A reaction–diffusion Gierer–Meinhardt system with homogeneous Neumann boundary condition on one-dimensional bounded spatial domain is considered in the present article. Local asymptotic stability, Turing instability and existence of Hopf bifurcation of the constant positive equilibrium are explored by analyzing in detail the associated eigenvalue problem. Moreover, properties of spatially homogeneous Hopf bifurcation are carried out by employing the normal form method and the center manifold technique for reaction–diffusion equations. Finally, numerical simulations are also provided in order to check the obtained theoretical conclusions.

scholarly journals Correspondences between parameters in a reaction-diffusion model and connexin functions during zebrafish stripe formation

2021 ◽  
Author(s):  
Akiko Nakamasu
Keyword(s):  
Molecular Mechanisms ◽  
Reaction Diffusion ◽  
The Body ◽  
Pigment Cells ◽  
Turing Pattern ◽  
Reaction Diffusion Model ◽  
Spatial Periodicity ◽  
Pattern Formations ◽  
Mathematical Analyses ◽  
Spotted Pattern

Abstract Different diffusivities among interacting substances actualize the potential instability of a system. When these elicited instabilities manifested as forms of spatial periodicity, they are called Turing patterns. Simulations using general reaction-diffusion (RD) models have demonstrated that pigment patterns on the body trunk of growing fish follow a Turing pattern. Laser ablation experiments performed on zebrafish revealed apparent interactions among pigment cells, which allowed for a three-components RD model to be derived. However, the underlying molecular mechanisms responsible for Turing pattern formation in this system had been remained unknown. A zebrafish mutant with a spotted pattern was found to have a defect in Connexin41.8 (Cx41.8) which, together with Cx39.4, exists in pigment cells and controls pattern formations. Here, molecular-level evidence derived from connexin analyses was linked to the interactions among pigment cells described in previous RD modeling. Channels on pigment cells were generalized as “gates,” and the effects of respective gates were deduced. The model used partial differential equations (PDEs) to enable numerical and mathematical analyses of characteristics observed in the experiments. Furthermore, the improved PDE model included nonlinear reaction terms, enabled the consideration of the behavior of components.

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