Dynamics of in vitro polymer degradation of polycaprolactone-based scaffolds : accelerated versus simulated physiological conditions

The increasing use of biodegradable devices in tissue engineering and regenerative medicine means it is essential to study and understand their degradation behaviour. Accelerated degradation systems aim to achieve similar degradation profiles within a shorter period of time, compared with standard conditions. However, these conditions only partially mimic the actual situation, and subsequent analyses and derived mechanisms must be treated with caution and should always be supported by actual long-term degradation data obtained under physiological conditions. Our studies revealed that polycaprolactone (PCL) and PCL-composite scaffolds degrade very differently under these different degradation conditions, whilst still undergoing hydrolysis. Molecular weight and mass loss results differ due to the different degradation pathways followed (surface degradation pathway for accelerated conditions and bulk degradation pathway for simulated physiological conditions). Crystallinity studies revealed similar patterns of recrystallization dynamics, and mechanical data indicated that the scaffolds retained their functional stability, in both instances, over the course of degradation. Ultimately, polymer degradation was shown to be chiefly governed by molecular weight, crystallinity susceptibility to hydrolysis and device architecture considerations whilst maintaining its thermodynamic equilibrium.

Market access of Papua New Guinea bananas (Musa spp.) with particular respect to banana fly (Bactrocera musae (Tryon)) (Diptera: Tephritidae)

International market access for fresh commodities is regulated by international accepted phytosanitary guidelines, the objectives of which are to reduce the biosecurity risk of plant pest and disease movement. Papua New Guinea (PNG) has identified banana as a potential export crop and to help meet international market access requirements, this thesis provides information for the development of a pest risk analysis (PRA) for PNG banana fruit. The PRA is a three step process which first identifies the pests associated with a particular commodity or pathway, then assesses the risk associated with those pests, and finally identifies risk management options for those pests if required. As the first step of the PRA process, I collated a definitive list on the organisms associated with the banana plant in PNG using formal literature, structured interviews with local experts, grey literature and unpublished file material held in PNG field research stations. I identified 112 organisms (invertebrates, vertebrate, pathogens and weeds) associated with banana in PNG, but only 14 of these were reported as commonly requiring management. For these 14 I present detailed information summaries on their known biology and pest impact. A major finding of the review was that of the 14 identified key pests, some research information occurs for 13. The single exception for which information was found to be lacking was Bactrocera musae (Tryon), the banana fly. The lack of information for this widely reported ‘major pest on PNG bananas’ would hinder the development of a PNG banana fruit PRA. For this reason the remainder of the thesis focused on this organism, particularly with respect to generation of information required by the PRA process. Utilising an existing, but previously unanalysed fruit fly trapping database for PNG, I carried out a Geographic Information System analysis of the distribution and abundance of banana in four major regions of PNG. This information is required for a PRA to determine if banana fruit grown in different parts of the country are at different risks from the fly. Results showed that the fly was widespread in all cropping regions and that temperature and rainfall were not significantly correlated with banana fly abundance. Abundance of the fly was significantly correlated (albeit weakly) with host availability. The same analysis was done with four other PNG pest fruit flies and their responses to the environmental factors differed to banana fly and each other. This implies that subsequent PRA analyses for other PNG fresh commodities will need to investigate the risk of each of these flies independently. To quantify the damage to banana fruit caused by banana fly in PNG, local surveys and one national survey of banana fruit infestation were carried out. Contrary to expectations, infestation was found to be very low, particularly in the widely grown commercial cultivar, Cavendish. Infestation of Cavendish fingers was only 0.41% in a structured, national survey of over 2 700 banana fingers. Follow up laboratory studies showed that fingers of Cavendish, and another commercial variety Lady-finger, are very poor hosts for B. musae, with very low host selection rates by female flies and very poor immature survival. An analysis of a recent (within last decade) incursion of B. musae into the Gazelle Peninsula of East New Britain Province, PNG, provided the final set of B. musae data. Surveys of the fly on the peninsular showed that establishment and spread of the fly in the novel environment was very rapid and thus the fly should be regarded as being of high biosecurity concern, at least in tropical areas. Supporting the earlier impact studies, however, banana fly has not become a significant banana fruit problem on the Gazelle, despite bananas being the primary starch staple of the region. The results of the research chapters are combined in the final Discussion in the form of a B. musae focused PRA for PNG banana fruit. Putting the thesis in a broader context, the Discussion also deals with the apparent discrepancy between high local abundance of banana fly and very low infestation rates. This discussion focuses on host utilisation patterns of specialist herbivores and suggests that local pest abundance, as determined by trapping or monitoring, need not be good surrogate for crop damage, despite this linkage being implicit in a number of international phytosanitary protocols.

Morphologic and genomic characterisation of the koala Chlamydia pneumoniae strain

Chlamydia pneumoniae is a common human and animal pathogen associated with a wide range of upper and lower respiratory tract infections. In more recent years there has been increasing evidence to suggest a link between C. pneumoniae and chronic diseases in humans, including atherosclerosis, stroke and Alzheimer’s disease. C. pneumoniae human strains show little genetic variation, indicating that the human-derived strain originated from a common ancestor in the recent past. Despite extensive information on the genetics and morphology processes of the human strain, knowledge concerning many other hosts (including marsupials, amphibians, reptiles and equines) remains virtually unexplored. The koala (Phascolarctos cinereus) is a native Australian marsupial under threat due to habitat loss, predation and disease. Koalas are very susceptible to chlamydial infections, most commonly affecting the conjunctiva, urogenital tract and/or respiratory tract. To address this gap in the literature, the present study (i) provides a detailed description of the morphologic and genomic architecture of the C. pneumoniae koala (and human) strain, and shows that the koala strain is microscopically, developmentally and genetically distinct from the C. pneumoniae human strain, and (ii) examines the genetic relationship of geographically diverse C. pneumoniae isolates from human, marsupial, amphibian, reptilian and equine hosts, and identifies two distinct lineages that have arisen from animal-to-human cross species transmissions. Chapter One of this thesis explores the scientific problem and aims of this study, while Chapter Two provides a detailed literature review of the background in this field of work. Chapter Three, the first results chapter, describes the morphology and developmental stages of C. pneumoniae koala isolate LPCoLN, as revealed by fluorescence and transmission electron microscopy. The profile of this isolate, when cultured in HEp-2 human epithelial cells, was quite different to the human AR39 isolate. Koala LPCoLN inclusions were larger; the elementary bodies did not have the characteristic pear-shaped appearance, and the developmental cycle was completed within a shorter period of time (as confirmed by quantitative real-time PCR). These in vitro findings might reflect biological differences between koala LPCoLN and human AR39 in vivo. Chapter Four describes the complete genome sequence of the koala respiratory pathogen, C. pneumoniae LPCoLN. This is the first animal isolate of C. pneumoniae to be fully-sequenced. The genome sequence provides new insights into genomic ‘plasticity’ (organisation), evolution and biology of koala LPCoLN, relative to four complete C. pneumoniae human genomes (AR39, CWL029, J138 and TW183). Koala LPCoLN contains a plasmid that is not shared with any of the human isolates, there is evidence of gene loss in nucleotide salvage pathways, and there are 10 hot spot genomic regions of variation that were previously not identified in the C. pneumoniae human genomes. Sequence (partial-length) from a second, independent, wild koala isolate (EBB) at several gene loci confirmed that the koala LPCoLN isolate was representative of a koala C. pneumoniae strain. The combined sequence data provides evidence that the C. pneumoniae animal (koala LPCoLN) genome is ancestral to the C. pneumoniae human genomes and that human infections may have originated from zoonotic infections. Chapter Five examines key genome components of the five C. pneumoniae genomes in more detail. This analysis reveals genomic features that are shared by and/or contribute to the broad ecological adaptability and evolution of C. pneumoniae. This analysis resulted in the identification of 65 gene sequences for further analysis of intraspecific variation, and revealed some interesting differences, including fragmentation, truncation and gene decay (loss of redundant ancestral traits). This study provides valuable insights into metabolic diversity, adaptation and evolution of C. pneumoniae. Chapter Six utilises a subset of 23 target genes identified from the previous genomic comparisons and makes a significant contribution to our understanding of genetic variability among C. pneumoniae human (11) and animal (6 amphibian, 5 reptilian, 1 equine and 7 marsupial hosts) isolates. It has been shown that the animal isolates are genetically diverse, unlike the human isolates that are virtually clonal. More convincing evidence that C. pneumoniae originated in animals and recently (in the last few hundred thousand years) crossed host species to infect humans is provided in this study. It is proposed that two animal-to-human cross species events have occurred in the context of the results, one evident by the nearly clonal human genotype circulating in the world today, and the other by a more animal-like genotype apparent in Indigenous Australians. Taken together, these data indicate that the C. pneumoniae koala LPCoLN isolate has morphologic and genomic characteristics that are distinct from the human isolates. These differences may affect the survival and activity of the C. pneumoniae koala pathogen in its natural host, in vivo. This study, by utilising the genetic diversity of C. pneumoniae, identified new genetic markers for distinguishing human and animal isolates. However, not all C. pneumoniae isolates were genetically diverse; in fact, several isolates were highly conserved, if not identical in sequence (i.e. Australian marsupials) emphasising that at some stage in the evolution of this pathogen, there has been an adaptation/s to a particular host, providing some stability in the genome. The outcomes of this study by experimental and bioinformatic approaches have significantly enhanced our knowledge of the biology of this pathogen and will advance opportunities for the investigation of novel vaccine targets, antimicrobial therapy, or blocking of pathogenic pathways.

Does quality of life among breast cancer survivors one year after diagnosis differ depending on urban and non-urban residence? A comparative study

Background: This study examined the quality of life (QOL), measured by the Functional Assessment of Cancer Therapy (FACT) questionnaire, among urban (n=277) and non-urban (n=323) breast cancer survivors and women from the general population (n=1140) in Queensland, Australia. ---------- Methods: Population-based samples of breast cancer survivors aged <75 years who were 12 months post-diagnosis and similarly-aged women from the general population were recruited between 2002 and 2007. ---------- Results: Age-adjusted QOL among urban and non-urban breast cancer survivors was similar, although QOL related to breast cancer concerns was the weakest domain and was lower among non-urban survivors than their urban counterparts (36.8 versus 40.4, P<0.01). Irrespective of residence, breast cancer survivors, on average, reported comparable scores on most QOL scales as their general population peers, although physical well-being was significantly lower among non-urban survivors (versus the general population, P<0.01). Overall, around 20%-33% of survivors experienced lower QOL than peers without the disease. The odds of reporting QOL below normative levels were increased more than two-fold for those who experienced complications following surgery, reported upper-body problems, had higher perceived stress levels and/or a poor perception of handling stress (P<0.01 for all). ---------- Conclusions: Results can be used to identify subgroups of women at risk of low QOL and to inform components of tailored recovery interventions to optimize QOL for these women following cancer treatment.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Crosstalk between developmental and tumour-specific signalling pathways : kallikrein-related serine peptidases and nodal in prostrate cancer

Prostate cancer is an important male health issue. The strategies used to diagnose and treat prostate cancer underscore the cell and molecular interactions that promote disease progression. Prostate cancer is histologically defined by increasingly undifferentiated tumour cells and therapeutically targeted by androgen ablation. Even as the normal glandular architecture of the adult prostate is lost, prostate cancer cells remain dependent on the androgen receptor (AR) for growth and survival. This project focused on androgen-regulated gene expression, altered cellular differentiation, and the nexus between these two concepts. The AR controls prostate development, homeostasis and cancer progression by regulating the expression of downstream genes. Kallikrein-related serine peptidases are prominent transcriptional targets of AR in the adult prostate. Kallikrein 3 (KLK3), which is commonly referred to as prostate-specific antigen, is the current serum biomarker for prostate cancer. Other kallikreins are potential adjunct biomarkers. As secreted proteases, kallikreins act through enzyme cascades that may modulate the prostate cancer microenvironment. Both as a panel of biomarkers and cascade of proteases, the roles of kallikreins are interconnected. Yet the expression and regulation of different kallikreins in prostate cancer has not been compared. In this study, a spectrum of prostate cell lines was used to evaluate the expression profile of all 15 members of the kallikrein family. A cluster of genes was co-ordinately expressed in androgenresponsive cell lines. This group of kallikreins included KLK2, 3, 4 and 15, which are located adjacent to one another at the centromeric end of the kallikrein locus. KLK14 was also of interest, because it was ubiquitously expressed among the prostate cell lines. Immunohistochemistry showed that these 5 kallikreins are co-expressed in benign and malignant prostate tissue. The androgen-regulated expression of KLK2 and KLK3 is well-characterised, but has not been compared with other kallikreins. Therefore, KLK2, 3, 4, 14 and 15 expression were all measured in time course and dose response experiments with androgens, AR-antagonist treatments, hormone deprivation experiments and cells transfected with AR siRNA. Collectively, these experiments demonstrated that prostatic kallikreins are specifically and directly regulated by the AR. The data also revealed that kallikrein genes are differentially regulated by androgens; KLK2 and KLK3 were strongly up-regulated, KLK4 and KLK15 were modestly up-regulated, and KLK14 was repressed. Notably, KLK14 is located at the telomeric end of the kallikrein locus, far away from the centromeric cluster of kallikreins that are stimulated by androgens. These results show that the expression of KLK2, 3, 4, 14 and 15 is maintained in prostate cancer, but that these genes exhibit different responses to androgens. This makes the kallikrein locus an ideal model to investigate AR signalling. The increasingly dedifferentiated phenotype of aggressive prostate cancer cells is accompanied by the re-expression of signalling molecules that are usually expressed during embryogenesis and foetal tissue development. The Wnt pathway is one developmental cascade that is reactivated in prostate cancer. The canonical Wnt cascade regulates the intracellular levels of β-catenin, a potent transcriptional co-activator of T-cell factor (TCF) transcription factors. Notably, β-catenin can also bind to the AR and synergistically stimulate androgen-mediated gene expression. This is at the expense of typical Wnt/TCF target genes, because the AR:β-catenin and TCF:β-catenin interactions are mutually exclusive. The effect of β-catenin on kallikrein expression was examined to further investigate the role of β-catenin in prostate cancer. Stable knockdown of β-catenin in LNCaP prostate cancer cells attenuated the androgen-regulated expression of KLK2, 3, 4 and 15, but not KLK14. To test whether KLK14 is instead a TCF:β-catenin target gene, the endogenous levels of β-catenin were increased by inhibiting its degradation. Although KLK14 expression was up-regulated by these treatments, siRNA knockdown of β-catenin demonstrated that this effect was independent of β-catenin. These results show that β-catenin is required for maximal expression of KLK2, 3, 4 and 15, but not KLK14. Developmental cells and tumour cells express a similar repertoire of signalling molecules, which means that these different cell types are responsive to one another. Previous reports have shown that stem cells and foetal tissues can reprogram aggressive cancer cells to less aggressive phenotypes by restoring the balance to developmental signalling pathways that are highly dysregulated in cancer. To investigate this phenomenon in prostate cancer, DU145 and PC-3 prostate cancer cells were cultured on matrices pre-conditioned with human embryonic stem cells (hESCs). Soft agar assays showed that prostate cancer cells exposed to hESC conditioned matrices had reduced clonogenicity compared with cells harvested from control matrices. A recent study demonstrated that this effect was partially due to hESC-derived Lefty, an antagonist of Nodal. A member of the transforming growth factor β (TGFβ) superfamily, Nodal regulates embryogenesis and is re-expressed in cancer. The role of Nodal in prostate cancer has not previously been reported. Therefore, the expression and function of the Nodal signalling pathway in prostate cancer was investigated. Western blots confirmed that Nodal is expressed in DU145 and PC-3 cells. Immunohistochemistry revealed greater expression of Nodal in malignant versus benign glands. Notably, the Nodal inhibitor, Lefty, was not expressed at the mRNA level in any prostate cell lines tested. The Nodal signalling pathway is functionally active in prostate cancer cells. Recombinant Nodal treatments triggered downstream phosphorylation of Smad2 in DU145 and LNCaP cells, and stably-transfected Nodal increased the clonogencity of LNCaP cells. Nodal was also found to modulate AR signalling. Nodal reduced the activity of an androgen-regulated KLK3 promoter construct in luciferase assays and attenuated the endogenous expression of AR target genes including prostatic kallikreins. These results demonstrate that Nodal is a novel example of a developmental signalling molecule that is reexpressed in prostate cancer and may have a functional role in prostate cancer progression. In summary, this project clarifies the role of androgens and changing cellular differentiation in prostate cancer by characterising the expression and function of the downstream genes encoding kallikrein-related serine proteases and Nodal. Furthermore, this study emphasises the similarities between prostate cancer and early development, and the crosstalk between developmental signalling pathways and the AR axis. The outcomes of this project also affirm the utility of the kallikrein locus as a model system to monitor tumour progression and the phenotype of prostate cancer cells.