Escherichia coli O157 infection on Scottish cattle farms: dynamics and control

In this study, we parametrize a stochastic individual-based model of the transmission dynamics of Escherichia coli O157 infection among Scottish cattle farms and use the model to predict the impacts of both targeted and non-targeted interventions. We first generate distributions of model parameter estimates using Markov chain Monte Carlo methods. Despite considerable uncertainty in parameter values, each set of parameter values within the 95th percentile range implies a fairly similar impact of interventions. Interventions that reduce the transmission coefficient and/or increase the recovery rate of infected farms (e.g. via vaccination and biosecurity) are much more effective in reducing the level of infection than reducing cattle movement rates, which improves effectiveness only when the overall control effort is small. Targeted interventions based on farm-level risk factors are more efficient than non-targeted interventions. Herd size is a major determinant of risk of infection, and our simulations confirmed that targeting interventions at farms with the largest herds is almost as effective as targeting based on overall risk. However, because of the striking characteristic that the infection force depends weakly on the number of infected farms, no interventions that are less than 100 per cent effective can eradicate E. coli O157 infection from Scottish cattle farms, implying that eliminating the disease is impractical.     

Rational spatio-temporal strategies for controlling a Chagas disease vector in urban environments

The rational design of interventions is critical to controlling communicable diseases, especially in urban environments. In the case of the Chagas disease vector Triatoma infestans, successful control is stymied by the return of the insect after the effectiveness of the insecticide wanes. Here, we adapt a genetic algorithm, originally developed for the travelling salesman problem, to improve the spatio-temporal design of insecticide campaigns against T. infestans, in a complex urban environment. We find a strategy that reduces the expected instances of vector return 34-fold compared with the current strategy of sequential insecticide application to spatially contiguous communities. The relative success of alternative control strategies depends upon the duration of the effectiveness of the insecticide, and it shows chaotic fluctuations in response to unforeseen delays in a control campaign. We use simplified models to analyse the outcomes of qualitatively different spatio-temporal strategies. Our results provide a detailed procedure to improve control efforts for an urban Chagas disease vector, as well as general guidelines for improving the design of interventions against other disease agents in complex environments.     

Directional reversals enable Myxococcus xanthus cells to produce collective one-dimensional streams during fruiting-body formation

The formation of a collectively moving group benefits individuals within a population in a variety of ways. The surface-dwelling bacterium Myxococcus xanthus forms dynamic collective groups both to feed on prey and to aggregate during times of starvation. The latter behaviour, termed fruiting-body formation, involves a complex, coordinated series of density changes that ultimately lead to three-dimensional aggregates comprising hundreds of thousands of cells and spores. How a loose, two-dimensional sheet of motile cells produces a fixed aggregate has remained a mystery as current models of aggregation are either inconsistent with experimental data or ultimately predict unstable structures that do not remain fixed in space. Here, we use high-resolution microscopy and computer vision software to spatio-temporally track the motion of thousands of individuals during the initial stages of fruiting-body formation. We find that cells undergo a phase transition from exploratory flocking, in which unstable cell groups move rapidly and coherently over long distances, to a reversal-mediated localization into one-dimensional growing streams that are inherently stable in space. These observations identify a new phase of active collective behaviour and answer a long-standing open question in Myxococcus development by describing how motile cell groups can remain statistically fixed in a spatial location.     

Transient dynamic phenotypes as criteria for model discrimination: fold-change detection in Rhodobacter sphaeroides chemotaxis

The chemotaxis pathway of the bacterium Rhodobacter sphaeroides shares many similarities with that of Escherichia coli. It exhibits robust adaptation and has several homologues of the latter''s chemotaxis proteins. Recent theoretical results have correctly predicted that the E. coli output behaviour is unchanged under scaling of its ligand input signal; this property is known as fold-change detection (FCD). In the light of recent experimental results suggesting that R. sphaeroides may also show FCD, we present theoretical assumptions on the R. sphaeroides chemosensory dynamics that can be shown to yield FCD behaviour. Furthermore, it is shown that these assumptions make FCD a property of this system that is robust to structural and parametric variations in the chemotaxis pathway, in agreement with experimental results. We construct and examine models of the full chemotaxis pathway that satisfy these assumptions and reproduce experimental time-series data from earlier studies. We then propose experiments in which models satisfying our theoretical assumptions predict robust FCD behaviour where earlier models do not. In this way, we illustrate how transient dynamic phenotypes such as FCD can be used for the purposes of discriminating between models that reproduce the same experimental time-series data.     

Fractal analysis of behaviour in a wild primate: behavioural complexity in health and disease

Parasitism and other stressors are ubiquitous in nature but their effects on animal behaviour can be difficult to identify. We investigated the effects of nematode parasitism and other indicators of physiological impairment on the sequential complexity of foraging and locomotion behaviour among wild Japanese macaques (Macaca fuscata yakui). We observed all sexually mature individuals (n = 28) in one macaque study group between October 2007 and August 2008, and collected two faecal samples/month/individual (n = 362) for parasitological examination. We used detrended fluctuation analysis (DFA) to investigate long-range autocorrelation in separate, binary sequences of foraging (n = 459) and locomotion (n = 446) behaviour collected via focal sampling. All behavioural sequences exhibited long-range autocorrelation, and linear mixed-effects models suggest that increasing infection with the nodular worm Oesophagostomum aculeatum, clinically impaired health, reproductive activity, ageing and low dominance status were associated with reductions in the complexity of locomotion, and to a lesser extent foraging, behaviour. Furthermore, the sequential complexity of behaviour increased with environmental complexity. We argue that a reduction in complexity in animal behaviour characterizes individuals in impaired or ‘stressed’ states, and may have consequences if animals cannot cope with heterogeneity in their natural habitats.     

Edge-based compartmental modelling for infectious disease spread

The primary tool for predicting infectious disease spread and intervention effectiveness is the mass action susceptible–infected–recovered model of Kermack & McKendrick. Its usefulness derives largely from its conceptual and mathematical simplicity; however, it incorrectly assumes that all individuals have the same contact rate and partnerships are fleeting. In this study, we introduce edge-based compartmental modelling, a technique eliminating these assumptions. We derive simple ordinary differential equation models capturing social heterogeneity (heterogeneous contact rates) while explicitly considering the impact of partnership duration. We introduce a graphical interpretation allowing for easy derivation and communication of the model and focus on applying the technique under different assumptions about how contact rates are distributed and how long partnerships last.     

Dynamic behaviour of 304 stainless steel during high Z deformation

The deformation behaviour of 304 stainless steel was investigated over a range of strain rates spanning those from typical laboratory conditions through to those more commonly experienced in industry. This study examines the effect of the Zener-Hollomon (Z) parameter on the shape of the deformation flow curves. At Z values typical of laboratory experiments the flow curves display a behaviour indicative of dynamic recrystallization (DRX). A clear peak can be seen in the curve, but as the Z value increases (increasing strain rate/decreasing temperature) the shape of the curve changes to a ‘flat-top’ behaviour which has traditionally been used to indicate that no DRX is occurring and that dynamic recovery (DRV) is the only softening mechanism operating. Examination of the corresponding work hardening curves (θ = δσ/δ?) and deformation microstructures suggests that some level of dynamic recrystallization has occurred. The results suggest that at the higher strain rates the main mechanism for DRX is only the formation from prior austenite grain boundary bulges and that subsequent layers of DRX grains are very difficult to form. The overall deformation textures were also found to be independent of the strain rate.     

Remote automated multi-generational growth and observation of an animal in low Earth orbit

The ultimate survival of humanity is dependent upon colonization of other planetary bodies. Key challenges to such habitation are (patho)physiologic changes induced by known, and unknown, factors associated with long-duration and distance space exploration. However, we currently lack biological models for detecting and studying these changes. Here, we use a remote automated culture system to successfully grow an animal in low Earth orbit for six months. Our observations, over 12 generations, demonstrate that the multi-cellular soil worm Caenorhabditis elegans develops from egg to adulthood and produces progeny with identical timings in space as on the Earth. Additionally, these animals display normal rates of movement when fully fed, comparable declines in movement when starved, and appropriate growth arrest upon starvation and recovery upon re-feeding. These observations establish C. elegans as a biological model that can be used to detect changes in animal growth, development, reproduction and behaviour in response to environmental conditions during long-duration spaceflight. This experimental system is ready to be incorporated on future, unmanned interplanetary missions and could be used to study cost-effectively the effects of such missions on these biological processes and the efficacy of new life support systems and radiation shielding technologies.     

Experimental evolution gone wild

Because of their large population sizes and rapid cell division rates, marine microbes have, or can generate, ample variation to fuel evolution over a few weeks or months, and subsequently have the potential to evolve in response to global change. Here we measure evolution in the marine diatom Skeletonema marinoi evolved in a natural plankton community in CO₂-enriched mesocosms deployed in situ. Mesocosm enclosures are typically used to study how the species composition and biogeochemistry of marine communities respond to environmental shifts, but have not been used for experimental evolution to date. Using this approach, we detect a large evolutionary response to CO₂ enrichment in a focal marine diatom, where population growth rate increased by 1.3-fold in high CO₂-evolved lineages. This study opens an exciting new possibility of carrying out in situ evolution experiments to understand how marine microbial communities evolve in response to environmental change.     

Digital clocks: simple Boolean models can quantitatively describe circadian systems

The gene networks that comprise the circadian clock modulate biological function across a range of scales, from gene expression to performance and adaptive behaviour. The clock functions by generating endogenous rhythms that can be entrained to the external 24-h day–night cycle, enabling organisms to optimally time biochemical processes relative to dawn and dusk. In recent years, computational models based on differential equations have become useful tools for dissecting and quantifying the complex regulatory relationships underlying the clock''s oscillatory dynamics. However, optimizing the large parameter sets characteristic of these models places intense demands on both computational and experimental resources, limiting the scope of in silico studies. Here, we develop an approach based on Boolean logic that dramatically reduces the parametrization, making the state and parameter spaces finite and tractable. We introduce efficient methods for fitting Boolean models to molecular data, successfully demonstrating their application to synthetic time courses generated by a number of established clock models, as well as experimental expression levels measured using luciferase imaging. Our results indicate that despite their relative simplicity, logic models can (i) simulate circadian oscillations with the correct, experimentally observed phase relationships among genes and (ii) flexibly entrain to light stimuli, reproducing the complex responses to variations in daylength generated by more detailed differential equation formulations. Our work also demonstrates that logic models have sufficient predictive power to identify optimal regulatory structures from experimental data. By presenting the first Boolean models of circadian circuits together with general techniques for their optimization, we hope to establish a new framework for the systematic modelling of more complex clocks, as well as other circuits with different qualitative dynamics. In particular, we anticipate that the ability of logic models to provide a computationally efficient representation of system behaviour could greatly facilitate the reverse-engineering of large-scale biochemical networks.     

Insights into mucosal innate responses to Escherichia coli O157 : H7 colonization of cattle by mathematical modelling of excretion dynamics

Mathematical model-based statistical inference applied to within-host dynamics of infectious diseases can help dissect complex interactions between hosts and microbes. This work has applied advances in model-based inference to understand colonization of cattle by enterohaemorrhagic Escherichia coli O157 : H7 at the terminal rectum. A mathematical model was developed based on niche replication and transition rates at this site. A nested-model comparison, applied to excretion curves from 25 calves, was used to reduce complexity while maintaining integrity. We conclude that, 5–9 days post inoculation, the innate immune response negates bacterial replication on the epithelium and either reduces attachment to or increases detachment from the epithelium of the terminal rectum. Thus, we provide a broadly applicable model that gives novel insights into bacterial replication rates in vivo and the timing and impact of host responses.     

Cerebrospinal fluid dynamics in the human cranial subarachnoid space: an overlooked mediator of cerebral disease. II. In vitro arachnoid outflow model

The arachnoid membrane (AM) and granulations (AGs) are important in cerebrospinal fluid (CSF) homeostasis, regulating intracranial pressure in health and disease. We offer a functional perspective of the human AM''s transport mechanism to clarify the role of AM in the movement of CSF and metabolites. Using cultures of human AG cells and a specialized perfusion system, we have shown that this in vitro model mimics the in vivo characteristics of unidirectional fluid transport and we present the first report of serum-free permeability values (92.5 µl min⁻¹ mm Hg⁻¹ cm⁻²), which in turn are in agreement with the CSF outflow rates derived from a dynamic, in vivo magnetic resonance imaging-based computational model of the subarachnoid cranial space (130.9 µl min⁻¹ mm Hg⁻¹ cm⁻²). Lucifer yellow permeability experiments have verified the maintenance of tight junctions by the arachnoidal cells with a peak occurring around 21 days post-seeding, which is when all perfusion experiments were conducted. Addition of ruthenium red to the perfusate, and subsequent analysis of its distribution post-perfusion, has verified the passage of perfusate via both paracellular and transcellular mechanisms with intracellular vacuoles of approximately 1 µm in diameter being the predominant transport mechanism. The comparison of the computational and in vitro models is the first report to measure human CSF dynamics functionally and structurally, enabling the development of innovative approaches to modify CSF outflow and will change concepts and management of neurodegenerative diseases resulting from CSF stagnation.     

Re-conceptualising the reckless driving behaviour of young drivers

Reckless driving is a major contributing factor to road morbidity and mortality. While further research into the nature and impact of reckless driving, particularly among young people, is urgently needed, the measurement of reckless driving behaviour also requires increased attention. Three major shortcomings apparent in established measures of driver behaviour are that they do not target the full range of reckless driving behaviours, they measure characteristics other than driving behaviours, and/or they fail to categorise and label reckless driver behaviour based on characteristics of the behaviours themselves. To combat these shortcomings, this paper reports the development and preliminary validation of a new measure of reckless driving behaviour for young drivers. Exploratory factor analysis of self-reported driving data revealed four, conceptually distinct categories of reckless driving behaviour: those that increase crash-risk due to (a) distractions or deficits in perception, attention or reaction time (labelled “distracted”), (b) driving under the influence of drugs or alcohol (labelled “substance-use”), (c) placing the vehicle in an unsafe environment beyond its design expectations (labelled “extreme”), and (d) speed and positioning of the vehicle relative to other vehicles and objects (labelled “positioning”). Confirmatory factor analysis of data collected from a separate, community sample confirmed this four-factor structure. Multiple regression analyses found differences in the demographic and psychological variables related to these four factors, suggesting that interventions in one reckless driving domain may not be helpful in others.     

Insights into the dissolution mechanisms of detergent agglomerates: An approach to assess dissolution heterogeneity

In this work, the dissolution mechanisms of detergent agglomerates with different binders were investigated in aqueous solution. The dissolution processes of detergent agglomerates were online monitored by using in situ UV–VIS spectrophotometer and electric conductivity probe. Dissolution profiles were correlated by Weibull model to evaluate the time-dependent dissolution rate coefficient and to classify the type of dissolution rate function k_t(t). The Kullback-Leibler information distance d_K-L was proposed to assess the degree of dissolution heterogeneity. The results indicate that the sodium linear alkylbenzene sulfonates (NaLAS) and sodium carbonates (Na₂CO₃) in detergent agglomerates have different dissolution behaviors, and their dissolution rates are influenced by the type and content of binders. Moreover, detergent agglomerates using semi-solid NaLAS paste or liquid linear alkylbenzene sulfonic acid (HLAS) as binders in granulation processes follow different dissolution mechanisms in water.     

Rebound behaviour of spheres for plastic impacts

This paper presents a study on the rebound behaviour of spheres impacted normally against a target wall using finite element methods. The emphasis is on the prediction of the coefficient of restitution and the effects of material properties and impact velocities on the rebound behaviour of the sphere. Finite deformation during plastic impact is addressed. The finite element results show that, for impacts of small plastic deformation, the coefficient of restitution is mainly dependent on the ratio of the impact velocity V_i to the yield velocity V_y which is consistent with those predicted by the theory of impact mechanics; while for impacts of finite-plastic-deformation it is also dependent on the ratio of the representative Young's Modulus E^* to the yield stress Y. The FEA results suggest that for impacts of finite-plastic-deformation the coefficient of restitution can be approximated to be proportional to [(V_i/V_y)/(E^*/Y)]^−1/2.     

Mechanistic analysis of the search behaviour of Caenorhabditis elegans

A central question in movement research is how animals use information and movement to promote encounter success. Current random search theory identifies reorientation patterns as key to the compromise between optimizing encounters for both nearby and faraway targets, but how the balance between intrinsic motor programmes and previous environmental experience determines the occurrence of these reorientation behaviours remains unknown. We used high-resolution tracking and imaging data to describe the complete motor behaviour of Caenorhabditis elegans when placed in a novel environment (one in which food is absent). Movement in C. elegans is structured around different reorientation behaviours, and we measured how these contributed to changing search strategies as worms became familiar with their new environment. This behavioural transition shows that different reorientation behaviours are governed by two processes: (i) an environmentally informed ‘extrinsic’ strategy that is influenced by recent experience and that controls for area-restricted search behaviour, and (ii) a time-independent, ‘intrinsic’ strategy that reduces spatial oversampling and improves random encounter success. Our results show how movement strategies arise from a balance between intrinsic and extrinsic mechanisms, that search behaviour in C. elegans is initially determined by expectations developed from previous environmental experiences, and which reorientation behaviours are modified as information is acquired from new environments.     

Aggregation by depletion attraction in cultures of bacteria producing exopolysaccharide

In bacteria, the production of exopolysaccharides—polysaccharides secreted by the cells into their growth medium—is integral to the formation of aggregates and biofilms. These exopolysaccharides often form part of a matrix that holds the cells together. Investigating the bacterium Sinorhizobium meliloti, we found that a mutant that overproduces the exopolysaccharide succinoglycan showed enhanced aggregation, resulting in phase separation of the cultures. However, the aggregates did not appear to be covered in polysaccharides. Succinoglycan purified from cultures was applied to different concentrations of cells, and observation of the phase behaviour showed that the limiting polymer concentration for aggregation and phase separation to occur decreased with increasing cell concentration, suggesting a ‘crowding mechanism’ was occurring. We suggest that, as found in colloidal dispersions, the presence of a non-adsorbing polymer in the form of the exopolysaccharide succinoglycan drives aggregation of S. meliloti by depletion attraction. This force leads to self-organization of the bacteria into small clusters of laterally aligned cells, and, furthermore, leads to aggregates clustering into biofilm-like structures on a surface.     

Dissecting the determinants of malaria chronicity: why within-host models struggle to reproduce infection dynamics

The duration of infection is fundamental to the epidemiological behaviour of any infectious disease, but remains one of the most poorly understood aspects of malaria. In endemic areas, the malaria parasite Plasmodium falciparum can cause both acute, severe infections and asymptomatic, chronic infections through its interaction with the host immune system. Frequent superinfection and massive parasite genetic diversity make it extremely difficult to accurately measure the distribution of infection lengths, complicating the estimation of basic epidemiological parameters and the prediction of the impact of interventions. Mathematical models have qualitatively reproduced parasite dynamics early during infection, but reproducing long-lived chronic infections remains much more challenging. Here, we construct a model of infection dynamics to examine the consequences of common biological assumptions for the generation of chronicity and the impact of co-infection. We find that although a combination of host and parasite heterogeneities are capable of generating chronic infections, they do so only under restricted parameter choices. Furthermore, under biologically plausible assumptions, co-infection of parasite genotypes can alter the course of infection of both the resident and co-infecting strain in complex non-intuitive ways. We outline the most important puzzles for within-host models of malaria arising from our analysis, and their implications for malaria epidemiology and control.     

Estimating Bounds on Collisional Relaxation Rates of Spin-Polarized 87Rb Atoms at Ultracold Temperatures

We present quantum scattering calculations for the collisional relaxation rate coefficient of spin-polarized ⁸⁷Rb(f = 2,m = 2) atoms, which determines the loss rate of cold Rb atoms from a magnetic trap. Unlike the lighter alkali atoms, spin-polarized ⁸⁷Rb atoms can undergo dipolar relaxation due to both the normal spin-spin dipole interaction and a second-order spin-orbit interaction with distant electronic states of the dimer. We present ab initio calculations for the second-order spin-orbit terms for both Rb₂ and Cs₂. The corrections lead to a reduction in the relaxation rate for ⁸⁷Rb. Our primary concern is to analyze the sensitivity of the ⁸⁷Rb trap loss to the uncertainties in the ground state molecular potentials. Since the scattering length for the a³Σ⁺_u state is already known, the major uncertainties are associated with the X¹Σ⁺_g potential. After testing the effect of systematically modifying the short-range form of the molecular potentials over a reasonable range, and introducing our best estimate of the second-order spin-orbit interaction, we estimate that in the low temperature limit the rate coefficient for loss of Rb atoms from the f = 2,m = 2 state is between 0.4 × 10⁻¹⁵ cm³/s and 2.4 × 10⁻¹⁵ cm³/s (where this number counts two atoms lost per collision). In a pure condensate the rate coefficient would be reduced by 1/2.     

A novel in vivo method for quantifying the interfacial biochemical bond strength of bone implants

Quantifying the in vivo interfacial biochemical bond strength of bone implants is a biological challenge. We have developed a new and novel in vivo method to identify an interfacial biochemical bond in bone implants and to measure its bonding strength. This method, named biochemical bond measurement (BBM), involves a combination of the implant devices to measure true interfacial bond strength and surface property controls, and thus enables the contributions of mechanical interlocking and biochemical bonding to be distinguished from the measured strength values. We applied the BBM method to a rabbit model, and observed great differences in bone integration between the oxygen (control group) and magnesium (test group) plasma immersion ion-implanted titanium implants (0.046 versus 0.086 MPa, n=10, p=0.005). The biochemical bond in the test implants resulted in superior interfacial behaviour of the implants to bone: (i) close contact to approximately 2 μm thin amorphous interfacial tissue, (ii) pronounced mineralization of the interfacial tissue, (iii) rapid bone healing in contact, and (iv) strong integration to bone. The BBM method can be applied to in vivo experimental models not only to validate the presence of a biochemical bond at the bone–implant interface but also to measure the relative quantity of biochemical bond strength. The present study may provide new avenues for better understanding the role of a biochemical bond involved in the integration of bone implants.