Variable species densities are induced by volume exclusion interactions upon domain growth.

In this work we study the effect of domain growth on spatial correlations in agent populations containing multiple species. This is important as heterogenous cell populations are ubiquitous during the embryonic development of many species. We have previously shown that the long term behaviour of an agent population depends on the way in which domain growth is implemented. We extend this work to show that, depending on the way in which domain growth is implemented, different species dominate in multispecies simulations. Continuum approximations of the lattice-based model that ignore spatial correlations cannot capture this behaviour, while those that explicitly account for spatial correlations can. The results presented here show that the precise mechanism of domain growth can determine the long term behaviour of multispecies populations, and in certain circumstances, establish spatially varying species densities

Using approximate Bayesian computation to quantify cell-cell adhesion parameters in a cell migratory process

In this work we implement approximate Bayesian computational methods to improve the design of a wound-healing assay used to quantify cell-cell interactions. This is important as cell-cell interactions, such as adhesion and repulsion, have been shown to play a role in cell migration. Initially, we demonstrate with a model of an unrealistic experiment that we are able to identify model parameters that describe agent motility and adhesion, given we choose appropriate summary statistics for our model data. Following this, we replace our model of an unrealistic experiment with a model representative of a practically realisable experiment. We demonstrate that, given the current (and commonly used) experimental set-up, our model parameters cannot be accurately identified using approximate Bayesian computation methods. We compare new experimental designs through simulation, and show more accurate identification of model parameters is possible by expanding the size of the domain upon which the experiment is performed, as opposed to increasing the number of experimental replicates. The results presented in this work therefore describe time and cost-saving alterations for a commonly performed experiment for identifying cell motility parameters. Moreover, this work will be of interest to those concerned with performing experiments that allow for the accurate identification of parameters governing cell migratory processes, especially cell migratory processes in which cell-cell adhesion or repulsion are known to play a significant role

The effect of domain growth on spatial correlations

Mathematical models describing cell movement and proliferation are important tools in developmental biology research. In this work we present methods to include the effects of domain growth on the evolution of spatial correlations between agent locations in a continuum approximation of a one-dimensional lattice-based model of cell motility and proliferation. This is important as the inclusion of spatial correlations in continuum models of cell motility and proliferation without domain growth has previously been shown to be essential for their accuracy in certain scenarios. We include the effect of spatial correlations by deriving a system of ordinary differential equations that describe the expected evolution of individual and pair density functions for agents on a growing domain. We then demonstrate how to simplify this system of ordinary differential equations by using an appropriate approximation. This simplification allows domain growth to be included in models describing the evolution of spatial correlations between agents in a tractable manner

Variable species densities are induced by volume exclusion interactions upon domain growth.

In this work we study the effect of domain growth on spatial correlations in agent populations containing multiple species. This is important as heterogenous cell populations are ubiquitous during the embryonic development of many species. We have previously shown that the long term behaviour of an agent population depends on the way in which domain growth is implemented. We extend this work to show that, depending on the way in which domain growth is implemented, different species dominate in multispecies simulations. Continuum approximations of the lattice-based model that ignore spatial correlations cannot capture this behaviour, while those that explicitly account for spatial correlations can. The results presented here show that the precise mechanism of domain growth can determine the long term behaviour of multispecies populations, and in certain circumstances, establish spatially varying species densities

How domain growth is implemented determines the long-term behavior of a cell population through its effect on spatial correlations

Domain growth plays an important role in many biological systems, and so the inclusion of domain growth in models of these biological systems is important to understanding how these systems function. In this work we present methods to include the effects of domain growth on the evolution of spatial correlations in a continuum approximation of a lattice-based model of cell motility and proliferation. We show that, depending on the way in which domain growth is implemented, different steady-state densities are predicted for an agent population. Furthermore, we demonstrate that the way in which domain growth is implemented can result in the evolution of the agent density depending on the size of the domain. Continuum approximations that ignore spatial correlations cannot capture these behaviors, while those that account for spatial correlations do. These results will be of interest to researchers in developmental biology, as they suggest that the nature of domain growth can determine the characteristics of cell populations

Increased uptake and new therapies are needed to avert rising hepatitis C-related end stage liver disease in England: modelling the predicted impact of treatment under different scenarios.

BACKGROUND & AIMS: Hepatitis C (HCV) related disease in England is predicted to rise, and it is unclear whether treatment at current levels will be able to avert this. The aim of this study was to estimate the number of people with chronic HCV infection in England that are treated and assess the impact and costs of increasing treatment uptake. METHODS: Numbers treated were estimated using national data sources for pegylated interferon supplied, dispensed, or purchased from 2006 to 2011. A back-calculation approach was used to project disease burden over the next 30 years and determine outcomes under various scenarios of treatment uptake. RESULTS: 5000 patients were estimated to have been treated in 2011 and 28,000 in total from 2006 to 2011; approximately 3.1% and 17% respectively of estimated chronic infections. Without treatment, incident cases of decompensated cirrhosis and hepatocellular carcinoma were predicted to increase until 2035 and reach 2290 cases per year. Treatment at current levels should reduce incidence by 600 cases per year, with a peak around 2030. Large increases in treatment are needed to halt the rise; and with more effective treatment the best case scenario predicts incidence of around 500 cases in 2030, although treatment uptake must still be increased considerably to achieve this. CONCLUSIONS: If the infected population is left untreated, the number of patients with severe HCV-related disease will continue to increase and represent a substantial future burden on healthcare resources. This can be mitigated by increasing treatment uptake, which will have the greatest impact if implemented quickly

Molecular profiling of multiplexed gene markers to assess viability of ex vivo human colon explant cultures

© Janice E. Drew et al. 2015; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. Acknowledgments The authors would like to thank the patients who kindly donated tissue samples, Sally Chalmers of the Tayside Tissue Bank for her help with collecting of the tissue donor samples, Emma Moss for advice on human colon dissection and explant culture, and Claus Dieter Mayer, Biomathematics and Statistics Scotland, for advice on statistical analysis. This work was supported by the Scottish Government (GT403), Scottish Universities Life Science Alliance, and TENOVUS Scotland.Peer reviewedPublisher PD

Tree water uptake enhances nitrogen acquisition in a fertilized boreal forest - but not under nitrogen-poor conditions

Understanding how plant water uptake interacts with acquisition of soil nitrogen (N) and other nutrients is fundamental for predicting plant responses to a changing environment, but it is an area where models disagree. We present a novel isotopic labelling approach which reveals spatial patterns of water and N uptake, and their interaction, by trees. The stable isotopes N-15 and H-2 were applied to a small area of the forest floor in stands with high and low soil N availability. Uptake by surrounding trees was measured. The sensitivity of N acquisition to water uptake was quantified by statistical modelling. Trees in the high-N stand acquired twice as much N-15 as in the low-N stand and around half of their N uptake was dependent on water uptake (H-2 enrichment). By contrast, in the low-N stand there was no positive effect of water uptake on N uptake. We conclude that tree N acquisition was only marginally dependent on water flux toward the root surface under low-N conditions whereas under high-N conditions, the water-associated N uptake was substantial. The results suggest a fundamental shift in N acquisition strategy under high-N conditions

Vitamin D levels and risk of type 1 diabetes:A Mendelian randomization study

[This corrects the article DOI: 10.1371/journal.pmed.1003536.]