Louise Dyson

Age‐Related Changes in Speed and Mechanism of Adult Skeletal Muscle Stem Cell Migration

Skeletal muscle undergoes a progressive age‐related loss in mass and function. Preservation of muscle mass depends in part on satellite cells, the resident stem cells of skeletal muscle. Reduced satellite cell function may contribute to the age‐associated decrease in muscle mass. Here, we focused on characterizing the effect of age on satellite cell migration. We report that aged satellite cells migrate at less than half the speed of young cells. In addition, aged cells show abnormal membrane extension and retraction characteristics required for amoeboid‐based cell migration. Aged satellite cells displayed low levels of integrin expression. By deploying a mathematical model approach to investigate mechanism of migration, we have found that young satellite cells move in a random “memoryless” manner, whereas old cells demonstrate superdiffusive tendencies. Most importantly, we show that nitric oxide, a key regulator of cell migration, reversed the loss in migration speed and reinstated the unbiased mechanism of movement in aged satellite cells. Finally, we found that although hepatocyte growth factor increased the rate of aged satellite cell movement, it did not restore the memoryless migration characteristics displayed in young cells. Our study shows that satellite cell migration, a key component of skeletal muscle regeneration, is compromised during aging. However, we propose clinically approved drugs could be used to overcome these detrimental changes. STEM CELLS2012;30:1182–1195

Noise-induced bistable states and their mean switching time in foraging colonies.

We investigate a type of bistability occurring in population systems where noise not only causes transitions between stable states, but also constructs the states themselves. We focus on the experimentally well-studied system of ants choosing between two food sources to illustrate the essential points, but the ideas are more general. The mean time for switching between the two bistable states of the system is calculated. This suggests a procedure for estimating, in a real system, the critical population size above which bistability ceases to occur.

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination ‘as a public health problem’ when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models’ predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020.

Measuring and modelling the effects of systematic non-adherence to mass drug administration

Highlights • We review models of systematic non-adherence and propose a new model for the effect.• We use two simplified models to explore the effects of systematic non-adherence.• We find that systematicness has a significant impact on the campaign outcome.• The number of rounds attended can be analysed to find the level of systematicness.• In published data the correlation between treatment rounds is between 0.281and 0.535.

The importance of volume exclusion in modelling cellular migration

The modelling of collective migration has traditionally been undertaken in a continuous framework, with little reference to the individual-level mechanisms that give rise to such a concerted movement. One factor whose importance is now coming to light is that the individuals themselves occupy space in the domain, thus obstructing others from moving past them (volume exclusion). In this work, we systematically derive continuous descriptions of cellular migration with volume exclusion for a wide range of individual-based mechanisms and in one, two and three dimensions. We also consider subpopulations of migrating individuals, which may have different characteristics, such as differing sizes and speeds of migration. We demonstrate that volume exclusion is of particular importance when biased movement is included, and thus conclude that volume exclusion may have its greatest effect when considering directed migratory mechanisms such as chemotaxis.

Modelling Acidosis and the Cell Cycle in Multicellular Tumour Spheroids

A partial differential equation model is developed to understand the effect that nutrient and acidosis have on the distribution of proliferating and quiescent cells and dead cell material (necrotic and apoptotic) within a multicellular tumour spheroid. The rates of cell quiescence and necrosis depend upon the local nutrient and acid concentrations and quiescent cells are assumed to consume less nutrient and produce less acid than proliferating cells. Analysis of the differences in nutrient consumption and acid production by quiescent and proliferating cells shows low nutrient levels do not necessarily lead to increased acid concentration via anaerobic metabolism. Rather, it is the balance between proliferating and quiescent cells within the tumour which is important; decreased nutrient levels lead to more quiescent cells, which produce less acid than proliferating cells. We examine this effect via a sensitivity analysis which also includes a quantification of the effect that nutrient and acid concentrations have on the rates of cell quiescence and necrosis.

Staged Models for Interdisciplinary Research

Modellers of complex biological or social systems are often faced with an invidious choice: to use simple models with few mechanisms that can be fully analysed, or to construct complicated models that include all the features which are thought relevant. The former ensures rigour, the latter relevance. We discuss a method that combines these two approaches, beginning with a complex model and then modelling the complicated model with simpler models. The resulting “chain” of models ensures some rigour and relevance. We illustrate this process on a complex model of voting intentions, constructing a reduced model which agrees well with the predictions of the full model. Experiments with variations of the simpler model yield additional insights which are hidden by the complexity of the full model. This approach facilitated collaboration between social scientists and physicists—the complex model was specified based on the social science literature, and the simpler model constrained to agree (in core aspects) with the complicated model.

Onset of collective motion in locusts is captured by a minimal model

We present a minimal model to describe the onset of collective motion seen when a population of locusts are placed in an annular arena. At low densities motion is disordered, while at high densities locusts march in a common direction, which may reverse during the experiment. The data are well captured by an individual-based model, in which demographic noise leads to the observed density-dependent effects. By fitting the model parameters to equation-free coefficients, we give a quantitative comparison, showing time series, stationary distributions, and the mean switching times between states.

Targeted Treatment of Yaws With Household Contact Tracing: How Much Do We Miss?

Abstract Yaws is a disabling bacterial infection found primarily in warm and humid tropical areas. The World Health Organization strategy mandates an initial round of total community treatment (TCT) with single-dose azithromycin followed either by further TCT or active case-finding and treatment of cases and their contacts (the Morges strategy). We sought to investigate the effectiveness of the Morges strategy. We employed a stochastic household model to study the transmission of infection using data collected from a pre-TCT survey conducted in the Solomon Islands. We used this model to assess the proportion of asymptomatic infections that occurred in households without active cases. This analysis indicated that targeted treatment of cases and their household contacts would miss a large fraction of asymptomatic infections (65%–100%). This fraction was actually higher at lower prevalences. Even assuming that all active cases and their households were successfully treated, our analysis demonstrated that at all prevalences present in the data set, up to 90% of (active and asymptomatic) infections would not be treated under household-based contact tracing. Mapping was undertaken as part of the study “Epidemiology of Yaws in the Solomon Islands and the Impact of a Trachoma Control Programme,” in September–October 2013.

Diagnosing risk factors alongside mass drug administration using serial diagnostic tests—which test first?

Abstract Background When tests are used in series to determine individual risk factors and infection status in a mass drug administration (MDA), the diagnostics, test order and subsequent treatment decisions (the testing algorithm) affect population-level treatment coverage and cost, but there is no existing framework for evaluating which algorithm optimizes any given outcome. Methods We present a mathematical tool (with spreadsheet implementation) to analyse the effect of test ordering, illustrated using treatment for onchocerciasis in an area where high-burden Loa loa co-infections present a known risk factor. Results The prevalence of the infection and risk factor have a non-linear impact on the optimal ordering of tests. Testing for the MDA infection first always leaves more infected people untreated but fewer people with the risk factor being misclassified. The cost of the treatment given to infected individuals with the risk factor does not affect which algorithm is more cost effective. Conclusions For a given test and treat algorithm and its costs, the correct strategy depends on the expected prevalence. In most cases, when the apparent prevalence of the target infection is greater than the apparent prevalence of the risk factor, it is cheaper to do the risk factor test first, and vice versa.