Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Cells respond to various biochemical and physical cues during wound–healing and tumour progression. In vitro assays used to study these processes are typically conducted in one particular geometry and it is unclear how the assay geometry affects the capacity of cell populations to spread, or whether the relevant mechanisms, such as cell motility and cell proliferation, are somehow sensitive to the geometry of the assay. In this work we use a circular barrier assay to characterise the spreading of cell populations in two different geometries. Assay 1 describes a tumour–like geometry where a cell population spreads outwards into an open space. Assay 2 describes a wound–like geometry where a cell population spreads inwards to close a void. We use a combination of discrete and continuum mathematical models and automated image processing methods to obtain independent estimates of the effective cell diffusivity, D, and the effective cell proliferation rate, λ. Using our parameterised mathematical model we confirm that our estimates of D and λ accurately predict the time–evolution of the location of the leading edge and the cell density profiles for both assay 1 and assay 2. Our work suggests that the effective cell diffusivity is up to 50% lower for assay 2 compared to assay 1, whereas the effective cell proliferation rate is up to 30% lower for assay 2 compared to assay 1.

Ship roll damping control

The technical feasibility of roll motion control devices has been amply demonstrated for over 100 years. Performance, however, can still fall short of expectations because of difficulties associated with control system designs, which have proven to be far from trivial due to fundamental performance limitations and large variations of the spectral characteristics of wave-induced roll motion. This tutorial paper presents an account of the development of various ship roll motion control systems together with the challenges associated with their design. It discusses the assessment of performance and the applicability of different mathematical models, and it surveys the control methods that have been implemented and validated with full scale experiments. The paper also presents an outlook on what are believed to be potential areas of research within this topic.

An overview of the marine systems simulator (MSS) : a Simulink toolbox for marine control systems

The Marine Systems Simulator (MSS) is an environment which provides the necessary resources for rapid implementation of mathematical models of marine systems with focus on control system design. The simulator targets models¡Xand provides examples ready to simulate¡Xof different floating structures and its systems performing various operations. The platform adopted for the development of MSS is Matlab/Simulink. This allows a modular simulator structure, and the possibility of distributed development. Openness and modularity of software components have been the prioritized design principles, which enables a systematic reuse of knowledge and results in efficient tools for research and education. This paper provides an overview of the structure of the MSS, its features, current accessability, and plans for future development.

Development of an inter-vehicle communications & positioning platform for transport safety applications

This project is a breakthrough in developing new scientific approaches for the design, development and evaluation of inter-vehicle communications, networking and positioning systems as part of Cooperative Intelligent Transportation Systems ensuring the safety of both roads and rail networks. This research focused on the elicitation, specification, analysis and validation of requirements for Vehicle-to-Vehicle communications and networking, and Vehicle-to-Vehicle positioning, which are accomplished with the research platform developed for this study. A number of mathematical models for communications, networking and positioning were developed from which simulations and field experiments were conducted to evaluate the overall performance of the platform. The outcomes of this research significantly contribute to improving the performance of the communications and positioning components of Cooperative Intelligent Transportation Systems.

Benthic metabolism as an indicator of stream ecosystem health

We tested direct and indirect measures of benthic metabolism as indicators of stream ecosystem health across a known agricultural land-use disturbance gradient in southeast Queensland, Australia. Gross primary production (GPP) and respiration (R24) in benthic chambers in cobble and sediment habitats, algal biomass (as chlorophyll a) from cobbles and sediment cores, algal biomass accrual on artificial substrates and stable carbon isotope ratios of aquatic plants and benthic sediments were measured at 53 stream sites, ranging from undisturbed subtropical rainforest to catchments where improved pasture and intensive cropping are major land-uses. Rates of benthic GPP and R24 varied by more than two orders of magnitude across the study gradient. Generalised linear regression modelling explained 80% or more of the variation in these two indicators when sediment and cobble substrate dominated sites were considered separately, and both catchment and reach scale descriptors of the disturbance gradient were important in explaining this variation. Model fits were poor for net daily benthic metabolism (NDM) and production to respiration ratio (P/R). Algal biomass accrual on artificial substrate and stable carbon isotope ratios of aquatic plants and benthic sediment were the best of the indirect indicators, with regression model R2 values of 50% or greater. Model fits were poor for algal biomass on natural substrates for cobble sites and all sites. None of these indirect measures of benthic metabolism was a good surrogate for measured GPP. Direct measures of benthic metabolism, GPP and R24, and several indirect measures were good indicators of stream ecosystem health and are recommended in assessing process-related responses to riparian and catchment land use change and the success of ecosystem rehabilitation actions.

Development and application of a predictive model of freshwater fish assemblage composition to evaluate river health in eastern Australia

Multivariate predictive models are widely used tools for assessment of aquatic ecosystem health and models have been successfully developed for the prediction and assessment of aquatic macroinvertebrates, diatoms, local stream habitat features and fish. We evaluated the ability of a modelling method based on the River InVertebrate Prediction and Classification System (RIVPACS) to accurately predict freshwater fish assemblage composition and assess aquatic ecosystem health in rivers and streams of south-eastern Queensland, Australia. The predictive model was developed, validated and tested in a region of comparatively high environmental variability due to the unpredictable nature of rainfall and river discharge. The model was concluded to provide sufficiently accurate and precise predictions of species composition and was sensitive enough to distinguish test sites impacted by several common types of human disturbance (particularly impacts associated with catchment land use and associated local riparian, in-stream habitat and water quality degradation). The total number of fish species available for prediction was low in comparison to similar applications of multivariate predictive models based on other indicator groups, yet the accuracy and precision of our model was comparable to outcomes from such studies. In addition, our model developed for sites sampled on one occasion and in one season only (winter), was able to accurately predict fish assemblage composition at sites sampled during other seasons and years, provided that they were not subject to unusually extreme environmental conditions (e.g. extended periods of low flow that restricted fish movement or resulted in habitat desiccation and local fish extinctions).

Assessing the role of spatial correlations during collective cell spreading

Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher’s equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations.

A control theoretic paradigm for cell signaling networks : a simple complexity for a sensitive robustness

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

Effective diffusivity and evaporative cooling in convective drying of food material

This article presents mathematical models to simulate coupled heat and mass transfer during convective drying of food materials using three different effective diffusivities: shrinkage dependent, temperature dependent and average of those two. Engineering simulation software COMSOL Multiphysics was utilized to simulate the model in 2D and 3D. The simulation results were compared with experimental data. It is found that the temperature dependent effective diffusivity model predicts the moisture content more accurately at the initial stage of the drying, whereas, the shrinkage dependent effective diffusivity model is better for the final stage of the drying. The model with shrinkage dependent effective diffusivity shows evaporative cooling phenomena at the initial stage of drying. This phenomenon was investigated and explained. Three dimensional temperature and moisture profiles show that even when the surface is dry, inside of the sample may still contain large amount of moisture. Therefore, drying process should be carefully dealt with otherwise microbial spoilage may start from the centre of the ‘dried’ food. A parametric investigation has been conducted after the validation of the model.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision.

Evaluation of the potential impact of the global economic crisis on HIV epidemics in Southeast Asia

Economic conditions around the world are likely to deteriorate in the short to medium term. The potential impact of this crisis on the spread of HIV is not clear. Government revenues and aid flows from international donors may face constraints, possibly leading to reductions in funding for HIV programs. Economic conditions (leading to increases in unemployment, for example) may also have an indirect impact on HIV epidemics by affecting the behaviour of individual people. Some behavioural changes may influence the rate of HIV transmission. This report presents findings from a study that investigates the potential impact of the economic crisis on HIV epidemics through the use of mathematical modelling. The potential epidemiological impacts of changes in the economy are explored for two distinctly characterised HIV epidemics: (i) a well-defined, established, and generalised HIV epidemic (specifically Cambodia, where incidence is declining); (ii) an HIV epidemic in its early expansion phase (specifically Papua New Guinea, where incidence has not yet peaked). Country-specific data are used for both settings and the models calibrated to accurately reflect the unique HIV epidemics in each population in terms of both incidence and prevalence. Models calibrated to describe the past and present epidemics are then used to forecast epidemic trajectories over the next few years under assumptions that behavioural or program conditions may change due to economic conditions. It should be noted that there are very limited solid data on how HIV/AIDS program funds may decrease or how social determinants related to HIV risk may change due to the economic crisis. Potential changes in key relevant factors were explored, along with sensitivity ranges around these assumptions, based on extensive discussions with in-country and international experts and stakeholders. As with all mathematical models, assumptions should be reviewed critically and results interpreted cautiously.

The management of venereal disease in New South Wales, 1871 to 1916

Practical techniques to manage the dangers associated with sexually transmitted diseases have varied considerably both cross culturally and historically. Adopting a Foucauldian perspective, this article examines sociohistorical aspects of the governance of venereal disease in New South Wales between 1871 and 1916. Public debates and official documents are analysed to identify strategic shifts in practices associated with venereal disease management , especially in relation to prostitution. Particular attention is paid to the development of contagious disease legislation and its role in the regulation of venereal disease . It is argued that during the period in question, two distinct governmental regimes of disease control can be identified. In the first, medical policing managed venereal disease through the mobilisation of repressive controls, requiring the isolation and detention of polluting bodies. In the second, liberal governance adopted pedagogic practices to train populations perceived as either healthy or unhealthy. It is further argued that as liberal strategies of governance came to dominate the management of venereal disease , the association of prostitution with venereal disease began to weaken. Instead, authorities became increasingly concerned with populations whose behaviour was not traditionally linked with venereal disease , such as the young and the sexually inexperienced.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Initial burden of disease estimates for South Africa, 2000

BACKGROUND This paper describes the first national burden of disease study for South Africa. The main focus is the burden due to premature mortality, i.e. years of life lost (YLLs). In addition, estimates of the burden contributed by morbidity, i.e. the years lived with disability (YLDs), are obtained to calculate disability-adjusted life years (DALYs); and the impact of AIDS on premature mortality in the year 2010 is assessed. METHOD Owing to the rapid mortality transition and the lack of timely data, a modelling approach has been adopted. The total mortality for the year 2000 is estimated using a demographic and AIDS model. The non-AIDS cause-of-death profile is estimated using three sources of data: Statistics South Africa, the National Department of Home Affairs, and the National Injury Mortality Surveillance System. A ratio method is used to estimate the YLDs from the YLL estimates. RESULTS The top single cause of mortality burden was HIV/AIDS followed by homicide, tuberculosis, road traffic accidents and diarrhoea. HIV/AIDS accounted for 38% of total YLLs, which is proportionately higher for females (47%) than for males (33%). Pre-transitional diseases, usually associated with poverty and underdevelopment, accounted for 25%, non-communicable diseases 21% and injuries 16% of YLLs. The DALY estimates highlight the fact that mortality alone underestimates the burden of disease, especially with regard to unintentional injuries, respiratory disease, and nervous system, mental and sense organ disorders. The impact of HIV/AIDS is expected to more than double the burden of premature mortality by the year 2010. CONCLUSION This study has drawn together data from a range of sources to develop coherent estimates of premature mortality by cause. South Africa is experiencing a quadruple burden of disease comprising the pre-transitional diseases, the emerging chronic diseases, injuries, and HIV/AIDS. Unless interventions that reduce morbidity and delay morbidity become widely available, the burden due to HIV/AIDS can be expected to grow very rapidly in the next few years. An improved base of information is needed to assess the morbidity impact more accurately.