Word Segmentation for Chinese Wikipedia Using N-Gram Mutual Information

In this paper, we propose an unsupervised segmentation approach, named "n-gram mutual information", or NGMI, which is used to segment Chinese documents into n-character words or phrases, using language statistics drawn from the Chinese Wikipedia corpus. The approach alleviates the tremendous effort that is required in preparing and maintaining the manually segmented Chinese text for training purposes, and manually maintaining ever expanding lexicons. Previously, mutual information was used to achieve automated segmentation into 2-character words. The NGMI approach extends the approach to handle longer n-character words. Experiments with heterogeneous documents from the Chinese Wikipedia collection show good results.

Zernike radial slope polynomials for wavefront reconstruction and refraction

Ophthalmic wavefront sensors typically measure wavefront slope, from which wavefront phase is reconstructed. We show that ophthalmic prescriptions (in power-vector format) can be obtained directly from slope measurements without wavefront reconstruction. This is achieved by fitting the measurement data with a new set of orthonormal basis functions called Zernike radial slope polynomials. Coefficients of this expansion can be used to specify the ophthalmic power vector using explicit formulas derived by a variety of methods. Zernike coefficients for wavefront error can be recovered from the coefficients of radial slope polynomials, thereby offering an alternative way to perform wavefront reconstruction.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Continuous infusion of ticarcillin-clavulanate for home treatment of serious infections : clinical efficacy, safety, pharmacokinetics and pharmacodynamics

Continuous infusion (CI) ticarcillin–clavulanate is a potential therapeutic improvement over conventional intermittent dosing because the major pharmacodynamic (PD) predictor of efficacy of β-lactams is the time that free drug levels exceed the MIC. This study incorporated a 6-year retrospective arm evaluating efficacy and safety of CI ticarcillin–clavulanate in the home treatment of serious infections and a prospective arm additionally evaluating pharmacokinetics (PK) and PD. In the prospective arm, steady-state serum ticarcillin and clavulanate levels and MIC testing of significant pathogens were performed. One hundred and twelve patients (median age, 56 years) were treated with a CI dose of 9.3–12.4 g/day and mean CI duration of 18.0 days. Infections treated included osteomyelitis (50 patients), septic arthritis (6), cellulitis (17), pulmonary infections (12), febrile neutropenia (7), vascular infections (7), intra-abdominal infections (2), and Gram-negative endocarditis (2); 91/112 (81%) of patients were cured, 14 (13%) had partial response and 7 (6%) failed therapy. Nine patients had PICC line complications and five patients had drug adverse events. Eighteen patients had prospective PK/PD assessment although only four patients had sufficient data for a full PK/PD evaluation (both serum steady-state drug levels and ticarcillin and clavulanate MICs from a bacteriological isolate), as this was difficult to obtain in home-based patients, particularly as serum clavulanate levels were found to deteriorate rapidly on storage. Three of four patients with matched PK/PD assessment had free drug levels exceeding the MIC of the pathogen. Home CI of ticarcillin–clavulanate is a safe, effective, convenient and practical therapy and is a therapeutic advance over traditional intermittent dosing when used in the home setting.

A functional screen identifies lateral transfer of beta-glucuronidase (gus) from bacteria to fungi

Lateral gene transfer (LGT) from prokaryotes to microbial eukaryotes is usually detected by chance through genome-sequencing projects. Here, we explore a different, hypothesis-driven approach. We show that the fitness advantage associated with the transferred gene, typically invoked only in retrospect, can be used to design a functional screen capable of identifying postulated LGT cases. We hypothesized that beta-glucuronidase (gus) genes may be prone to LGT from bacteria to fungi (thought to lack gus) because this would enable fungi to utilize glucuronides in vertebrate urine as a carbon source. Using an enrichment procedure based on a glucose-releasing glucuronide analog (cellobiouronic acid), we isolated two gus(+) ascomycete fungi from soils (Penicillium canescens and Scopulariopsis sp.). A phylogenetic analysis suggested that their gus genes, as well as the gus genes identified in genomic sequences of the ascomycetes Aspergillus nidulans and Gibberella zeae, had been introgressed laterally from high-GC gram(+) bacteria. Two such bacteria (Arthrobacter spp.), isolated together with the gus(+) fungi, appeared to be the descendants of a bacterial donor organism from which gus had been transferred to fungi. This scenario was independently supported by similar substrate affinities of the encoded beta-glucuronidases, the absence of introns from fungal gus genes, and the similarity between the signal peptide-encoding 5' extensions of some fungal gus genes and the Arthrobacter sequences upstream of gus. Differences in the sequences of the fungal 5' extensions suggested at least two separate introgression events after the divergence of the two main Euascomycete classes. We suggest that deposition of glucuronides on soils as a result of the colonization of land by vertebrates may have favored LGT of gus from bacteria to fungi in soils.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

The development of Lactococcus lactis as an antimicrobial agent

Non-pathogenic lactic acid bacteria are economically important Gram-positive bacteria used extensively in the food industry. Due to their “generally regarded as safe” status, certain species from the genera Lactobacillus and Lactococcus are also considered desirable as candidates for the production and secretion of recombinant proteins, particular those with therapeutic applications. The hypothesis examined by this thesis is that Lactococcus lactis can be modified to be an effective antimicrobial agent. Therefore, the aims of this thesis were to investigate the optimisation of the expression, secretion and/or activities of potential heterologous antimicrobial proteins by the model lactic acid bacterium, Lactococcus lactis subsp. cremoris MG1363. L. lactis strains were engineered to express and secrete the recombinant CyuC surface protein from Lactobacillus reuteri BR11, and a fusion protein consisting of CyuC and lysostaphin using the Sep promoter and secretion signal. CyuC has been characterised as a cystine-binding protein, but has also been demonstrated to have fibronectin binding activity. Lysostaphin is a bacteriolytic enzyme with specific activity against the Gram-positive pathogen, Staphylococcus aureus. These modified L. lactis strains were then investigated to see if they had the ability to inhibit the adhesion of S. aureus to host extracellular matrix (ECM) proteins. It was observed that the cell extracts of the L. lactis strain with the vector only (pGhost9:ISS1) was able to inhibit the adhesion of S. aureus to fibronectin, whilst the cell extracts of the L. lactis strain expressing lysostaphin was able to inhibit adhesion to keratin. Finally, this thesis has identified specific lactococcal genes that affect the secretion of lysostaphin through the use of random transposon mutagenesis. Ten mutants with higher lysostaphin activity contained insertions in four different genes encoding: (i) an uncharacterised putative transmembrane protein (llmg_0609), (ii) an enzyme catalysing the first step in peptidoglycan biosynthesis (murA2), (iii) a homolog of the oxidative defence regulator (trmA), and (iv) an uncharacterised putative enzyme involved in ubiquinone biosynthesis (llmg_2148). The higher lysostaphin activity observed in these mutants was found to be due to higher amounts of lysostaphin being secreted. The findings of this thesis contribute to the development of this organism as an antimicrobial agent and also to our understanding of L. lactis genetics.

In vivo performance of melimine as an antimicrobial coating for contact lenses in models of CLARE and CLPU

Purpose: One strategy to minimize bacteria-associated adverse responses such as microbial keratitis, contact lens–induced acute red eye (CLARE), and contact lens induced peripheral ulcers (CLPUs) that occur with contact lens wear is the development of an antimicrobial or antiadhesive contact lens. Cationic peptides represent a novel approach for the development of antimicrobial lenses.---------- Methods: A novel cationic peptide, melimine, was covalently incorporated into silicone hydrogel lenses. Confirmation tests to determine the presence of peptide and anti-microbial activity were performed. Cationic lenses were then tested for their ability to prevent CLPU in the Staphylococcus aureus rabbit model and CLARE in the Pseudomonas aeruginosa guinea pig model. ---------- Results: In the rabbit model of CLPU, melimine-coated lenses resulted in significant reductions in ocular symptom scores and in the extent of corneal infiltration (P < 0.05). Evaluation of the performance of melimine lenses in the CLARE model showed significant improvement in all ocular response parameters measured, including the percentage of eyes with corneal infiltrates, compared with those observed in the eyes fitted with the control lens (P ≤ 0.05). ---------- Conclusions: Cationic coating of contact lenses with the peptide melimine may represent a novel method of prevention of bacterial growth on contact lenses and consequently result in reduction of the incidence and severity of adverse responses due to Gram-positive and -negative bacteria during lens wear.

Predictive factors of contact lens case contamination

PURPOSE: To examine the relationship between contact lens (CL) case contamination and various potential predictive factors. METHODS: 74 subjects were fitted with lotrafilcon B (CIBA Vision) CLs on a daily wear basis for 1 month. Subjects were randomly assigned one of two polyhexamethylene biguanide (PHMB) preserved disinfecting solutions with the corresponding regular lens case. Clinical evaluations were conducted at lens delivery and after 1 month, when cases were collected for microbial culture. A CL care non-compliance score was determined through administration of a questionnaire and the volume of solution used was calculated for each subject. Data was examined using backward stepwise binary logistic regression. RESULTS: 68% of cases were contaminated. 35% were moderately or heavily contaminated and 36% contained gram-negative bacteria. Case contamination was significantly associated with subjective dryness symptoms (OR 4.22, CI 1.37–13.01) (P<0.05). There was no association between contamination and subject age, ethnicity, gender, average wearing time, amount of solution used, non-compliance score, CL power and subjective redness (P>0.05). The effect of lens care system on case contamination approached significance (P=0.07). Failure to rinse the case with disinfecting solution following CL insertion (OR 2.51, CI 0.52–12.09) and not air drying the case (OR 2.31, CI 0.39–13.35) were positively correlated with contamination; however, did not reach statistical significance. CONCLUSIONS: Our results suggest that case contamination may influence subjective comfort. It is difficult to predict the development of case contamination from a variety of clinical factors. The efficacy of CL solutions, bacterial resistance to disinfection and biofilm formation are likely to play a role. Further evaluation of these factors will improve our understanding of the development of case contamination and its clinical impact.

Renal bioenergetics during early gram-negative mammalian sepsis and angiotensin II infusion

Purpose: To measure renal adenosine triphosphate (ATP) (bioenergetics) during hypotensive sepsis with or without angiotensin II (Ang II) infusion. Methods: In anaesthetised sheep implanted with a renal artery flow probe and a magnetic resonance coil around one kidney, we induced hypotensive sepsis with intravenous Escherichia coli injection. We measured mean arterial pressure (MAP), heart rate, renal blood flow RBF and renal ATP levels using magnetic resonance spectroscopy. After 2 h of sepsis, we randomly assigned sheep to receive an infusion of Ang II or vehicle intravenously and studied the effect of treatment on the same variables. Results: After E. coli administration, the experimental animals developed hypotensive sepsis (MAP from 92 ± 9 at baseline to 58 ± 4 mmHg at 4 h). Initially, RBF increased, then, after 4 h, it decreased below control levels (from 175 ± 28 at baseline to 138 ± 27 mL/min). Despite decreased RBF and hypotension, renal ATP was unchanged (total ATP to inorganic phosphate ratio from 0.69 ± 0.02 to 0.70 ± 0.02). Ang II infusion restored MAP but caused significant renal vasoconstriction. However, it induced no changes in renal ATP (total ATP to inorganic phosphate ratio from 0.79 ± 0.03 to 0.80 ± 0.02). Conclusions:During early hypotensive experimental Gram-negative sepsis, there was no evidence of renal bioenergetic failure despite decreased RBF. In this setting, the addition of a powerful renal vasoconstrictor does not lead to deterioration in renal bioenergetics.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Molecular characterisation of environmental enterococci derived from water samples and assessment of associated public health hazards

Enterococci are versatile Gram-positive bacteria that can survive under extreme conditions. Most enterococci are non-virulent and found in the gastrointestinal tract of humans and animals. Other strains are opportunistic pathogens that contribute to a large number of nosocomial infections globally. Epidemiological studies demonstrated a direct relationship between the density of enterococci in surface waters and the risk of swimmer-associated gastroenteritis. The distribution of infectious enterococcal strains from the hospital environment or other sources to environmental water bodies through sewage discharge or other means, could increase the prevalence of these strains in the human population. Environmental water quality studies may benefit from focusing on a subset of Enterococcus spp. that are consistently associated with sources of faecal pollution such as domestic sewage, rather than testing for the entire genus. E. faecalis and E. faecium are potentially good focal species for such studies, as they have been consistently identified as the dominant Enterococcus spp. in human faeces and sewage. On the other hand enterococcal infections are predominantly caused by E. faecalis and E. faecium. The characterisation of E. faecalis and E. faecium is important in studying their population structures, particularly in environmental samples. In developing and implementing rapid, robust molecular genotyping techniques, it is possible to more accurately establish the relationship between human and environmental enterococci. Of particular importance, is to determine the distribution of high risk enterococcal clonal complexes, such as E. faecium clonal complex 17 and E. faecalis clonal complexes 2 and 9 in recreational waters. These clonal complexes are recognized as particularly pathogenic enterococcal genotypes that cause severe disease in humans globally. The Pimpama-Coomera watershed is located in South East Queensland, Australia and was investigated in this study mainly because it is used intensively for agriculture and recreational purposes and has a strong anthropogenic impact. The primary aim of this study was to develop novel, universally applicable, robust, rapid and cost effective genotyping methods which are likely to yield more definitive results for the routine monitoring of E. faecalis and E. faecium, particularly in environmental water sources. To fullfill this aim, new genotyping methods were developed based on the interrogation of highly informative single nucleotide polymorphisms (SNPs) located in housekeeping genes of both E. faecalis and E. faecium. SNP genotyping was successfully applied in field investigations of the Coomera watershed, South-East Queensland, Australia. E. faecalis and E. faecium isolates were grouped into 29 and 23 SNP profiles respectively. This study showed the high longitudinal diversity of E. faecalis and E. faecium over a period of two years, and both human-related and human-specific SNP profiles were identified. Furthermore, 4.25% of E. faecium strains isolated from water was found to correspond to the important clonal complex-17 (CC17). Strains that belong to CC17 cause the majority of hospital outbreaks and clinical infections globally. Of the six sampling sites of the Coomera River, Paradise Point had the highest number of human-related and human-specific E. faecalis and E. faecium SNP profiles. The secondary aim of this study was to determine the antibiotic-resistance profiles and virulence traits associated with environmental E. faecalis and E. faecium isolates compared to human pathogenic E. faecalis and E. faecium isolates. This was performed to predict the potential health risks associated with coming into contact with these strains in the Coomera watershed. In general, clinical isolates were found to be more resistant to all the antibiotics tested compared to water isolates and they harbored more virulence traits. Multi-drug resistance was more prevalent in clinical isolates (71.18% of E. faecalis and 70.3 % of E. faecium) compared to water isolates (only 5.66 % E. faecium). However, tetracycline, gentamicin, ciprofloxacin and ampicillin resistance was observed in water isolates. The virulence gene esp was the most prevalent virulence determinant observed in clinical isolates (67.79% of E. faecalis and 70.37 % of E. faecium), and this gene has been described as a human-specific marker used for microbial source tracking (MST). The presence of esp in water isolates (16.36% of E. faecalis and 19.14% of E. faecium) could be indicative of human faecal contamination in these waterways. Finally, in order to compare overall gene expression between environmental and clinical strains of E. faecalis, a comparative gene hybridization study was performed. The results of this investigation clearly demonstrated the up-regulation of genes associated with pathogenicity in E. faecalis isolated from water. The expression study was performed at physiological temperatures relative to ambient temperatures. The up-regulation of virulence genes demonstrates that environmental strains of E. faecalis can pose an increased health risk which can lead to serious disease, particularly if these strains belong to the virulent CC17 group. The genotyping techniques developed in this study not only provide a rapid, robust and highly discriminatory tool to characterize E. faecalis and E. faecium, but also enables the efficient identification of virulent enterococci that are distributed in environmental water sources.

Metabolic and ecological study of environmental pentose utilizing bacteria (E-PUB)

Lignocellulosic materials, such as sugar cane bagasse, a waste product of the sugarcane processing industry, agricultural residues and herbaceous crops, may serve as an abundant and comparatively cheap feedstock for largescale industrial fermentation, resulting in the production of marketable end-products. However, the complex structure of lignocellulosic materials, the presence of various hexose and pentose sugars in the hemicellulose component, and the presence of various compounds that inhibit the organisms selected for the fermentation process, all constitute barriers that add to the production costs and make full scale industrial production economically less feasible. The work presented in this thesis was conducted in order to screen microorganisms for ability to utilize pentose sugars derived from the sugar mill industrial waste. A large number of individual bacterial strains were investigated from hemi-cellulose rich material collected at the Proserpine and Maryborough sugar mills, notably soil samples from the mill sites. The research conducted to isolation of six pentose-capable Gram-positive organisms from the actinomycetes group by using pentose as a sole carbon source in the cultivation process. The isolates were identified as Corynebacterium glutamicum, Actinomyces odontolyticus, Nocardia elegans, and Propionibacterium freudenreichii all of which were isolated from the hemicellulose-enriched soil. Pentose degrading microbes are very rare in the environment, so this was a significant discovery. Previous research indicated that microbes could degrade pentose after genetic modification but the microbes discovered in this research were able to naturally utilize pentose. Six isolates, identified as four different genera, were investigated for their ability to utilize single sugars as substrates (glucose, xylose, arabinose or ribose), and also dual sugars as substrates (a hexose plus a pentose). The results demonstrated that C. glutamicum, A. odontolyticus, N. elegans, and P. freudenreichii were pentose-capable (able to grow using xylose or other pentose sugar), and also showed diauxie growth characteristics during the dual-sugar (glucose, in combination with xylose, arabinose or ribose) carbon source tests. In addition, it was shown that the isolates displayed very small differences in growth rates when grown on dual sugars as compared to single sugars, whether pentose or hexose in nature. The anabolic characteristics of C. glutamicum, A. odontolyticus, N. elegans and P. freudenreichii were subsequently investigated by qualitative analysis of their end-products, using high performance liquid chromatography (HPLC). All of the organisms produced arginine and cysteine after utilization of the pentose substrates alone. In addition, P. freudenreichii produced alanine and glycine. The end-product profile arising from culture with dual carbon sources was also tested. Interestingly, this time the product was different. All of them produced the amino acid glycine, when grown on a combination substrate-mix of glucose with xylose, and also glucose with arabinose. Only N. elegans was able to break down ribose, either singly or in combination with glucose, and the end-product of metabolism of the glucose plus ribose substrate combination was glutamic acid. The ecological analysis of microbial abundance in sugar mill waste was performed using denaturing gradient gel electrophoresis (DGGE) and also the metagenomic microarray PhyloChip method. Eleven solid samples and seven liquid samples were investigated. A very complex bacterial ecosystem was demonstrated in the seven liquid samples after testing with the PhyloChip method. It was also shown that bagasse leachate was the most different, compared to all of the other samples, by virtue of its richness in variety of taxa and the complexity of its bacterial community. The bacterial community in solid samples from Proserpine, Mackay and Maryborough sugar mills showed huge diversity. The information found from 16S rDNA sequencing results was that the bacterial genera Brevibacillus, Rhodospirillaceae, Bacillus, Vibrio and Pseudomonas were present in greatest abundance. In addition, Corynebacterium was also found in the soil samples. The metagenomic studies of the sugar mill samples demonstrate two important outcomes: firstly that the bagasse leachate, as potentially the most pentose-rich sample tested, had the most complex and diverse bacterial community; and secondly that the pentose-capable isolates that were initially discovered at the beginning of this study, were not amongst the most abundant taxonomic groups discovered in the sugar mill samples, and in fact were, as suspected, very rare. As a bioprospecting exercise, therefore, the study has discovered organisms that are naturally present, but in very small numbers, in the appropriate natural environment. This has implications for the industrial application of E-PUB, in that a seeding process using a starter culture will be necessary for industrial purposes, rather than simply assuming that natural fermentation might occur.

Effect of CT electron density identification on Monte Carlo simulations of radiotherapeutic treatments

Introduction: The accurate identification of tissue electron densities is of great importance for Monte Carlo (MC) dose calculations. When converting patient CT data into a voxelised format suitable for MC simulations, however, it is common to simplify the assignment of electron densities so that the complex tissues existing in the human body are categorized into a few basic types. This study examines the effects that the assignment of tissue types and the calculation of densities can have on the results of MC simulations, for the particular case of a Siemen’s Sensation 4 CT scanner located in a radiotherapy centre where QA measurements are routinely made using 11 tissue types (plus air). Methods: DOSXYZnrc phantoms are generated from CT data, using the CTCREATE user code, with the relationship between Hounsfield units (HU) and density determined via linear interpolation between a series of specified points on the ‘CT-density ramp’ (see Figure 1(a)). Tissue types are assigned according to HU ranges. Each voxel in the DOSXYZnrc phantom therefore has an electron density (electrons/cm3) defined by the product of the mass density (from the HU conversion) and the intrinsic electron density (electrons /gram) (from the material assignment), in that voxel. In this study, we consider the problems of density conversion and material identification separately: the CT-density ramp is simplified by decreasing the number of points which define it from 12 down to 8, 3 and 2; and the material-type-assignment is varied by defining the materials which comprise our test phantom (a Supertech head) as two tissues and bone, two plastics and bone, water only and (as an extreme case) lead only. The effect of these parameters on radiological thickness maps derived from simulated portal images is investigated. Results & Discussion: Increasing the degree of simplification of the CT-density ramp results in an increasing effect on the resulting radiological thickness calculated for the Supertech head phantom. For instance, defining the CT-density ramp using 8 points, instead of 12, results in a maximum radiological thickness change of 0.2 cm, whereas defining the CT-density ramp using only 2 points results in a maximum radiological thickness change of 11.2 cm. Changing the definition of the materials comprising the phantom between water and plastic and tissue results in millimetre-scale changes to the resulting radiological thickness. When the entire phantom is defined as lead, this alteration changes the calculated radiological thickness by a maximum of 9.7 cm. Evidently, the simplification of the CT-density ramp has a greater effect on the resulting radiological thickness map than does the alteration of the assignment of tissue types. Conclusions: It is possible to alter the definitions of the tissue types comprising the phantom (or patient) without substantially altering the results of simulated portal images. However, these images are very sensitive to the accurate identification of the HU-density relationship. When converting data from a patient’s CT into a MC simulation phantom, therefore, all possible care should be taken to accurately reproduce the conversion between HU and mass density, for the specific CT scanner used. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital (RBWH), Brisbane, Australia. The authors are grateful to the staff of the RBWH, especially Darren Cassidy, for assistance in obtaining the phantom CT data used in this study. The authors also wish to thank Cathy Hargrave, of QUT, for assistance in formatting the CT data, using the Pinnacle TPS. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.