Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies

An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)’s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak

A major genetic locus in <i>Trypanosoma brucei</i> is a determinant of host pathology

The progression and variation of pathology during infections can be due to components from both host or pathogen, and/or the interaction between them. The influence of host genetic variation on disease pathology during infections with trypanosomes has been well studied in recent years, but the role of parasite genetic variation has not been extensively studied. We have shown that there is parasite strain-specific variation in the level of splenomegaly and hepatomegaly in infected mice and used a forward genetic approach to identify the parasite loci that determine this variation. This approach allowed us to dissect and identify the parasite loci that determine the complex phenotypes induced by infection. Using the available trypanosome genetic map, a major quantitative trait locus (QTL) was identified on T. brucei chromosome 3 (LOD = 7.2) that accounted for approximately two thirds of the variance observed in each of two correlated phenotypes, splenomegaly and hepatomegaly, in the infected mice (named &lt;i&gt;TbOrg1&lt;/i&gt;). In addition, a second locus was identified that contributed to splenomegaly, hepatomegaly and reticulocytosis (&lt;i&gt;TbOrg2&lt;/i&gt;). This is the first use of quantitative trait locus mapping in a diploid protozoan and shows that there are trypanosome genes that directly contribute to the progression of pathology during infections and, therefore, that parasite genetic variation can be a critical factor in disease outcome. The identification of parasite loci is a first step towards identifying the genes that are responsible for these important traits and shows the power of genetic analysis as a tool for dissecting complex quantitative phenotypic traits

An outbreak of suspected cutaneous leishmaniasis in Ghana: lessons learnt and preparation for future outbreaks

Human cutaneous leishmaniasis (CL) has previously been reported in West Africa, but more recently, sporadic reports of CL have increased. Leishmania major has been identified from Mauritania, Senegal, Mali, and Burkina Faso. Three zymodemes (MON-26, MON-117, and MON-74, the most frequent) have been found. The geographic range of leishmaniasis is limited by the sand fly vector, its feeding preferences, and its capacity to support internal development of specific species of Leishmania. The risk of acquiring CL has been reported to increase considerably with human activity and epidemics of CL have been associated with deforestation, road construction, wars, or other activities where humans intrude the habitat of the vector. In the Ho Municipality in the Volta Region of Ghana, a localised outbreak of skin ulcers, possibly CL, was noted in 2003 without any such documented activity. This outbreak was consistent with CL as evidenced using various methods including parasite identification, albeit, in a small number of patients with ulcers

Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic

Epidemics can spread across large regions becoming pandemics by flowing along transportation and social networks. Two network attributes, transitivity (when a node is connected to two other nodes that are also directly connected between them) and centrality (the number and intensity of connections with the other nodes in the network), are widely associated with the dynamics of transmission of pathogens. Here we investigate how network centrality and transitivity influence vulnerability to diseases of human populations by examining one of the most devastating pandemic in human history, the fourteenth century plague pandemic called Black Death. We found that, after controlling for the city spatial location and the disease arrival time, cities with higher values of both centrality and transitivity were more severely affected by the plague. A simulation study indicates that this association was due to central cities with high transitivity undergo more exogenous re-infections. Our study provides an easy method to identify hotspots in epidemic networks. Focusing our effort in those vulnerable nodes may save time and resources by improving our ability of controlling deadly epidemics

Residential mobility during pregnancy in the north of England

<p>Abstract</p> <p>Background</p> <p>Many epidemiological studies assign exposure to an individual's residence at a single time point, such as birth or death. This approach makes no allowance for migration and may result in exposure error, leading to reduced study power and biased risk estimates. Pregnancy outcomes are less susceptible to this bias, however data from North American populations indicate that pregnant women are a highly mobile group. We assessed mobility in pregnant women in the north of England using data from the Northern Congenital Abnormality Survey (NorCAS).</p> <p>Methods</p> <p>Data were extracted from NorCAS for 1985 to 2003. Eligible cases had a gestational age at delivery of ≥ 24 weeks (a viable delivery) (n = 11 559). We assessed mobility between booking appointment (average gestational age 13 weeks) and delivery for pregnancies where the address at booking appointment and delivery were known. The impacts on mobility of maternal age and area-level socio-economic indicators were explored using standard descriptive statistics. A sensitivity analysis and a small validation exercise were undertaken to assess the impact of missing data on the estimate of mobility.</p> <p>Results</p> <p>Out of 7 919 eligible cases for whom addresses at booking and delivery were known, 705 (8.9% (95% CI 8.3 - 9.5)) moved between booking and delivery; the mean and median moving distance was 9.7 and 1.4 km respectively. Movers were significantly younger (25.4 versus 27.3 years, p < 0.01) and lived in more deprived areas (index of multiple deprivation score 38.3 versus 33.7, p < 0.01) than non movers.</p> <p>Conclusion</p> <p>Mobility in the north of England (9%) is considerably lower than that reported in North America and the only other study from the UK (23%). Consistent with other studies, mobility was related to maternal age and socio-economic status, and the majority of moves were over a relatively short distance. Although this population appears relatively stable, the mobility we have observed may still introduce misclassification or error into an exposure assessment relying solely on postcode at delivery, and migration should still therefore be considered a potential source of bias in future studies.</p

Arabidopsis R2R3-MYB transcription factor AtMYB60 functions as a transcriptional repressor of anthocyanin biosynthesis in lettuce (Lactuca sativa)

The MYB transcription factors play important roles in the regulation of many secondary metabolites at the transcriptional level. We evaluated the possible roles of the Arabidopsis R2R3-MYB transcription factors in flavonoid biosynthesis because they are induced by UV-B irradiation but their associated phenotypes are largely unexplored. We isolated their genes by RACE-PCR, and performed transgenic approach and metabolite analyses in lettuce (Lactuca sativa). We found that one member of this protein family, AtMYB60, inhibits anthocyanin biosynthesis in the lettuce plant. Wild-type lettuce normally accumulates anthocyanin, predominantly cyanidin and traces of delphinidin, and develops a red pigmentation. However, the production and accumulation of anthocyanin pigments in AtMYB60-overexpressing lettuce was inhibited. Using RT-PCR analysis, we also identified the complete absence or reduction of dihydroflavonol 4-reductase (DFR) transcripts in AtMYB60- overexpressing lettuce (AtMYB60-117 and AtMYB60-112 lines). The correlation between the overexpression of AtMYB60 and the inhibition of anthocyanin accumulation suggests that the transcription factorAtMYB60 controls anthocyanin biosynthesis in the lettuce leaf. Clarification of the roles of the AtMYB60 transcription factor will facilitate further studies and provide genetic tools to better understand the regulation in plants of the genes controlled by the MYB-type transcription factors. Furthermore, the characterization of AtMYB60 has implications for the development of new varieties of lettuce and other commercially important plants with metabolic engineering approaches

Diurnal Variation in Urodynamics of Rat

In humans, the storage and voiding functions of the urinary bladder have a characteristic diurnal variation, with increased voiding during the day and urine storage during the night. However, in animal models, the daily functional differences in urodynamics have not been well-studied. The goal of this study was to identify key urodynamic parameters that vary between day and night. Rats were chronically instrumented with an intravesical catheter, and bladder pressure, voided volumes, and micturition frequency were measured by continuous filling cystometry during the light (inactive) or dark (active) phases of the circadian cycle. Cage activity was recorded by video during the experiment. We hypothesized that nocturnal rats entrained to a standard 12:12 light:dark cycle would show greater ambulatory activity and more frequent, smaller volume micturitions in the dark compared to the light. Rats studied during the light phase had a bladder capacity of 1.44±0.21 mL and voided every 8.2±1.2 min. Ambulatory activity was lower in the light phase, and rats slept during the recording period, awakening only to urinate. In contrast, rats studied during the dark were more active, had a lower bladder capacities (0.65±0.18 mL), and urinated more often (every 3.7±0.9 min). Average bladder pressures were not significantly different between the light and dark (13.40±2.49 and 12.19±2.85 mmHg, respectively). These results identify a day-night difference in bladder capacity and micturition frequency in chronically-instrumented nocturnal rodents that is phase-locked to the normal circadian locomotor activity rhythm of the animal. Furthermore, since it has generally been assumed that the daily hormonal regulation of renal function is a major driver of the circadian rhythm in urination, and few studies have addressed the involvement of the lower urinary tract, these results establish the bladder itself as a target for circadian regulation

The influenza pandemic preparedness planning tool InfluSim

BACKGROUND: Planning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality. RESULTS: InfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers. CONCLUSION: InfluSim is an online available software which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability

Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses