Investigating the population structure of Queensland invasive Streptococcus pneumoniae isolates in children: Using a modified multi-locus variable number of tandem repeat analysis and a novel minimum SNPs capsular typing method

This research investigated the use of DNA fingerprinting to characterise the bacteria Streptococcus pneumoniae or pneumococcus, and hence gain insight into the development of new vaccines or antibiotics. Different bacterial DNA fingerprinting methods were studied, and a novel method was developed and validated, which characterises different cell coatings that pneumococci produce. This method was used to study the epidemiology of pneumococci in Queensland before and after the introduction of the current pneumococcal vaccine. This study demonstrated that pneumococcal disease is highly prevalent in children under four years, that the bacteria can `switch' its cell coating to evade the vaccine, and that some DNA fingerprinting methods are more discriminatory than others. This has an impact on understanding which strains are more prone to cause invasive disease. Evidence of the excellent research findings have been published in high impact internationally refereed journals.

Variable Size Population NSGA-II: VPNSGA-II

Multi-objective optimization is an active field of research with broad applicability in aeronautics. This report details a variant of the original NSGA-II software aimed to improve the performances of such a widely used Genetic Algorithm in finding the optimal Pareto-front of a Multi-Objective optimization problem for the use of UAV and aircraft design and optimsaiton. Original NSGA-II works on a population of predetermined constant size and its computational cost to evaluate one generation is O(mn^2 ), being m the number of objective functions and n the population size. The basic idea encouraging this work is that of reduce the computational cost of the NSGA-II algorithm by making it work on a population of variable size, in order to obtain better convergence towards the Pareto-front in less time. In this work some test functions will be tested with both original NSGA-II and VPNSGA-II algorithms; each test will be timed in order to get a measure of the computational cost of each trial and the results will be compared.

Estimation of parameters for macroparasite population evolution using approximate Bayesian computation

We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra-binomial variation in terms of a zero-one immunity variable, which has a short-lived presence in the host.

Models of collective cell spreading with variable cell aspect ratio : a motivation for degenerate diffusion models

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multi-scale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (pme). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the pme to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

Analysis of higher-order aberrations in a large clinical population

Purpose: To use a large wavefront database of a clinical population to investigate relationships between refractions and higher order aberrations and between aberrations of right and left eyes. Methods: Third and fourth-order aberration coefficients and higher-order root-mean-squared aberrations (HO RMS), scaled to a pupil size of 4.5 mm diameter, were analysed in a population of about 24,000 patients from Carl Zeiss Vision's European wavefront database. Correlations were determined between the aberrations and the variables of refraction, near addition and cylinder. Results: Most aberration coefficients were significantly dependent upon these variables, but the proportions of aberrations that could be explained by these factors were less than 2% except for spherical aberration (12%), horizontal coma (9%) and HO RMS (7%). Near addition was the major contributor for horizontal coma (8.5% out of 9.5%) and spherical equivalent was the major contributor for spherical aberration (7.7% out of 11.6%). Interocular correlations were highly significant for all aberration coefficients, varying between 0.16 and 0.81. Anisometropia was a variable of significance for three aberrations (vertical coma, secondary astigmatism and tetrafoil), but little importance can be placed on this because of the small proportions of aberrations that can be explained by refraction (all less than 1.0 %). Conclusions: Most third- and fourth-order aberration coefficients were significantly dependent upon spherical equivalent, near addition and cylinder, but only horizontal coma (9%) and spherical aberration (12%) showed dependencies of greater than 2%. Interocular correlations were highly significant for all aberration coefficients, but anisometropia had little influence on aberration coefficients.

An envirogenomic signature is associated with risk of IBD-related surgery in a population-based Crohn’s Disease cohort

BACKGROUND AND AIMS: Crohn's disease (CD) is an inflammatory bowel disease (IBD) caused by a combination of genetic, clinical, and environmental factors. Identification of CD patients at high risk of requiring surgery may assist clinicians to decide on a top-down or step-up treatment approach. METHODS: We conducted a retrospective case-control analysis of a population-based cohort of 503 CD patients. A regression-based data reduction approach was used to systematically analyse 63 genomic, clinical and environmental factors for association with IBD-related surgery as the primary outcome variable. RESULTS: A multi-factor model was identified that yielded the highest predictive accuracy for need for surgery. The factors included in the model were the NOD2 genotype (OR = 1.607, P = 2.3 × 10(-5)), having ever had perianal disease (OR = 2.847, P = 4 × 10(-6)), being post-diagnosis smokers (OR = 6.312, P = 7.4 × 10(-3)), being an ex-smoker at diagnosis (OR = 2.405, P = 1.1 × 10(-3)) and age (OR = 1.012, P = 4.4 × 10(-3)). Diagnostic testing for this multi-factor model produced an area under the curve of 0.681 (P = 1 × 10(-4)) and an odds ratio of 3.169, (95 % CI P = 1 × 10(-4)) which was higher than any factor considered independently. CONCLUSIONS: The results of this study require validation in other populations but represent a step forward in the development of more accurate prognostic tests for clinicians to prescribe the most optimal treatment approach for complicated CD patients.

Perianal disease combined with NOD2 genotype predicts need for IBD-related surgery in Crohn’s Disease patients from a population-based cohort

Background: Patients with Crohn’s disease (CD) often require surgery at some stage of disease course. Prediction of CD outcome is influenced by clinical, environmental, serological, and genetic factors (eg, NOD2). Being able to identify CD patients at high risk of surgical intervention should assist clinicians to decide whether or not to prescribe early aggressive treatment with immunomodulators. Methods: We performed a retrospective analysis of selected clinical (age at diagnosis, perianal disease, active smoking) and genetic (NOD2 genotype) data obtained for a population-based CD cohort from the Canterbury Inflammatory Bowel Disease study. Logistic regression was used to identify predictors of complicated outcome in these CD patients (ie, need for inflammatory bowel disease-related surgery). Results: Perianal disease and the NOD2 genotype were the only independent factors associated with the need for surgery in this patient group (odds ratio=2.84 and 1.60, respectively). By combining the associated NOD2 genotype with perianal disease we generated a single “clinicogenetic” variable. This was strongly associated with increased risk of surgery (odds ratio=3.84, P=0.00, confidence interval, 2.28-6.46) and offered moderate predictive accuracy (positive predictive value=0.62). Approximately 1/3 of surgical outcomes in this population are attributable to the NOD2+PA variable (attributable risk=0.32). Conclusions: Knowledge of perianal disease and NOD2 genotype in patients presenting with CD may offer clinicians some decision-making utility for early diagnosis of complicated CD progression and initiating intensive treatment to avoid surgical intervention. Future studies should investigate combination effects of other genetic, clinical, and environmental factors when attempting to identify predictors of complicated CD outcomes.

Novel NOD2 haplotype strengthens the association between TLR4 Asp299gly and Crohnʼs disease in an Australian population

Background:: The first major Crohn's disease (CD) susceptibility gene, NOD2, implicates the innate intestinal immune system and other pattern recognition receptors in the pathogenesis of this chronic, debilitating disorder. These include the Toll‐like receptors, specifically TLR4 and TLR5. A variant in the TLR4 gene (A299G) has demonstrated variable association with CD. We aimed to investigate the relationship between TLR4 A299G and TLR5 N392ST, and an Australian inflammatory bowel disease cohort, and to explore the strength of association between TLR4 A299G and CD using global meta‐analysis. Methods:: Cases (CD = 619, ulcerative colitis = 300) and controls (n = 360) were genotyped for TLR4 A299G, TLR5 N392ST, and the 4 major NOD2 mutations. Data were interrogated for case‐control analysis prior to and after stratification by NOD2 genotype. Genotype–phenotype relationships were also sought. Meta‐analysis was conducted via RevMan. Results:: The TLR4 A299G variant allele showed a significant association with CD compared to controls (P = 0.04) and a novel NOD2 haplotype was identified which strengthened this (P = 0.003). Furthermore, we identified that TLR4 A299G was associated with CD limited to the colon (P = 0.02). In the presence of the novel NOD2 haplotype, TLR4 A299G was more strongly associated with colonic disease (P < 0.001) and nonstricturing disease (P = 0.009). A meta‐analysis of 11 CD cohorts identified a 1.5‐fold increase in risk for the variant TLR4 A299G allele (P < 0.00001). Conclusions:: TLR 4 A299G appears to be a significant risk factor for CD, in particular colonic, nonstricturing disease. Furthermore, we identified a novel NOD2 haplotype that strengthens the relationship between TLR4 A299G and these phenotypes.

Population variation in biomonitoring data for persistent organic pollutants (POPs) : an examination of multiple population-based datasets for application to Australian pooled biomonitoring data

Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

Decline in perfluorooctane sulfonate and perfluorooctanoate serum concentrations in an Australian population from 2002 to 2011

Some perfluoroalkyl and polyfluoroalkyl substances (PFASs) have become widespread pollutants detected in human and wildlife samples worldwide. The main objective of this study was to assess temporal trends of PFAS concentrations in human blood in Australia over the last decade (2002–2011), taking into consideration age and sex trends. Pooled human sera from 2002/03 (n=26); 2008/09 (n=24) and 2010/11 (n=24) from South East Queensland, Australia were obtained from de-identified surplus pathology samples and compared with samples collected previously from 2006/07 (n=84). A total of 9775 samples in 158 pools were available for assessment of PFASs. Stratification criteria included sex and age: <16 years (2002/03 only); 0–4 (2006/07, 2008/09, 2010/11); 5–15 (2006/07, 2008/09, 2010/11); 16–30; 31–45; 46–60; and >60 years (all collection periods). Sera were analyzed using on-line solid-phase extraction coupled to high-performance liquid chromatography-isotope dilution-tandem mass spectrometry. Perfluorooctane sulfonate (PFOS) was detected in the highest concentrations ranging from 5.3–19.2 ng/ml (2008/09) to 4.4–17.4 ng/ml (2010/11). Perfluorooctanoate (PFOA) was detected in the next highest concentration ranging from 2.8–7.3 ng/ml (2008/09) to 3.1–6.5 ng/ml (2010/11). All other measured PFASs were detected at concentrations <1 ng/ml with the exception of perfluorohexane sulfonate which ranged from 1.2–5.7 ng/ml (08/09) and 1.4–5.4 ng/ml (10/11). The mean concentrations of both PFOS and PFOA in the 2010/11 period compared to 2002/03 were lower for all adult age groups by 56%. For 5-15 year olds, the decrease was 66% (PFOS) and 63% (PFOA) from 2002/03 to 2010/11. For 0-4 year olds the decrease from 2006/07 (when data were first available for this age group) was 50% (PFOS) and 22% (PFOA). This study provides strong evidence for decreasing serum PFOS and PFOA concentrations in an Australian population from 2002 through 2011. Age trends were variable and concentrations were higher in males than females. Global use has been in decline since around 2002 and hence primary exposure levels are expected to be decreasing. Further biomonitoring will allow assessment of PFAS exposures to confirm trends in exposure as primary and eventually secondary sources are depleted.

A Model to Estimate the Population Contributing to the Wastewater Using Samples Collected on Census Day

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.