Potential health and dietary consequences of food insecurity among Australian adults residing in urbanised disadvantaged areas

Purpose: Food insecurity is the limited/uncertain availability or ability to acquire nutritionally-adequate, culturally-relevant and safe foods. Adults suffering from food insecurity are at risk of inadequate nutrient intakes or, paradoxically, overweight/obesity and the development of chronic disease. Despite the global financial crisis and rising costs of living, few studies have investigated the potential dietary and health consequences of food insecurity among the Australian population. This study examined whether food insecurity was associated with health behaviours and dietary intakes among adults residing in socioeconomically-disadvantaged urbanised areas. Methods: In this cross-sectional study, a random sample of residents (n = 1000) were selected from the most disadvantaged suburbs of Brisbane city (response rate 51%). Data were collected by postal questionnaire which ascertained information on socio-demographic information, household food security, height, weight, frequency of healthcare utilisation, presence of chronic disease and intakes of fruit, vegetables and take-away. Data were analysed using logistic regression. Results/Findings: The prevalence of food insecurity was 25%. Those reporting food insecurity were two-to-three times more likely to have seen a general practitioner or been hospitalised within the previous 6 months. Furthermore, food insecurity was associated with a three-to-six-fold increase in the likelihood of experiencing depression. Food insecurity was associated with higher intakes of some take-away foods, however was not significantly associated with weight status or intakes of fruits or vegetables among this disadvantaged sample. Conclusion: Food insecurity has potential adverse health consequences that may result in significant health burdens among the population, and this may be concentrated in socioeconomically-disadvantaged suburbs.

Coal seam gas waters - their geochemical signature and potential environmental implications

Coal Seam Gas (CSG) is a form of natural gas (mainly methane) sorbed in underground coal beds. To mine this gas, wells are drilled directly into an underground coal seam and groundwater (CSG water) is pumped out to the surface. This lowers the downhole piezometric pressure and enables gas desporption from the coal matrix. In the United States, this gas has been extracted commercially since the 1980s. The economic success of US CSG projects has inspired exploration and development in Australia and New Zealand. In Australia, Queensland’s Bowen and Surat basins have been the subject of increased CSG development over the last decade. CSG growth in other Australian basins has not matured to the same level but exploration and development are taking place at an accelerated pace in the Sydney Basin (Illawarra and the Hunter Valley, NSW) and in the Gunnedah Basin. Similarly, CSG exploration in New Zealand has focused in the Waikato region (Maramarua and Huntly), in the West Coast region (Buller, Reefton, and Greymouth), and in Southland (Kaitangata, Mataura, and Ohai). Figure 1 shows a Shcoeller diagram with CSG samples from selected basins in Australia, New Zealand, and the USA. CSG water from all of these basins exhibit the same geochemical signature – low calcium, low magnesium, high bicarbonate, low sulphate and, sometimes, high chloride. This water quality is a direct result of specific biological and geological processes that have taken part in the formation of CSG. In general, these processes include the weathering of rocks (carbonates, dolomite, and halite), cation exchange with clays (responsible for enhanced sodium and depleted calcium and magnesium), and biogenic processes (accounting for the presence of high bicarbonate concentrations). The salinity of CSG waters tends to be brackish (TDS < 30000 mg/l) with a fairly neutral pH. These particular characteristics need to be taken into consideration when assessing water management and disposal alternatives. Environmental issues associated with CSG water disposal have been prominent in developed basins such as the Powder River Basin (PRB) in the United States. When disposed on the land or used for irrigation, water having a high dissolved salts content may reduce water availability to crops thus affecting crop yield. In addition, the high sodium, low calcium and low magnesium concentrations increase the potential to disperse soils and significantly reduce the water infiltration rate. Therefore, CSG waters need to be properly characterised, treated, and disposed to safeguard the environment without compromising other natural resources.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

A new technique for optimal allocation and sizing of capacitors and setting of LTC

An iterative based strategy is proposed for finding the optimal rating and location of fixed and switched capacitors in distribution networks. The substation Load Tap Changer tap is also set during this procedure. A Modified Discrete Particle Swarm Optimization is employed in the proposed strategy. The objective function is composed of the distribution line loss cost and the capacitors investment cost. The line loss is calculated using estimation of the load duration curve to multiple levels. The constraints are the bus voltage and the feeder current which should be maintained within their standard range. For validation of the proposed method, two case studies are tested. The first case study is the semi-urban 37-bus distribution system which is connected at bus 2 of the Roy Billinton Test System which is located in the secondary side of a 33/11 kV distribution substation. The second case is a 33 kV distribution network based on the modification of the 18-bus IEEE distribution system. The results are compared with prior publications to illustrate the accuracy of the proposed strategy.

Non-invasive identification of proteoglycans and chondrocyte differentiation state by Raman microspectroscopy

Proteoglycans (PGs) are crucial extracellular matrix (ECM) components that are present in all tissues and organs. Pathological remodeling of these macromolecules can lead to severe diseases such as osteoarthritis or rheumatoid arthritis. To date, PG-associated ECM alterations are routinely diagnosed by invasive analytical methods. Here, we employed Raman microspectroscopy, a laser-based, marker-free and non-destructive technique that allows the generation of spectra with peaks originating from molecular vibrations within a sample, to identify specific Raman bands that can be assigned to PGs within human and porcine cartilage samples and chondrocytes. Based on the non-invasively acquired Raman spectra, we further revealed that a prolonged in vitro culture leads to phenotypic alterations of chondrocytes, resulting in a decreased PG synthesis rate and loss of lipid contents. Our results are the first to demonstrate the applicability of Raman microspectroscopy as an analytical and potential diagnostic tool for non-invasive cell and tissue state monitoring of cartilage in biomedical research. ((c) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Psychosocial experience of cancer : surpassing mere survival and recognising the potential for posttraumatic growth as well as distress.

The publication of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) introduced the notion that a life-threatening illness can be a stressor and catalyst for Posttraumatic Stress Disorder (PTSD). Since then a solid body of research has been established investigating the post-diagnosis experience of cancer. These studies have identified a number of short and long-term life changes resulting from a diagnosis of cancer and associated treatments. In this chapter, we discuss the psychosocial response to the cancer experience and the potential for cancer-related distress. Cancer can represent a life-threatening diagnosis that may be associated with aggressive treatments and result in physical and psychological changes. The potential for future trauma through the lasting effects of the disease and treatment, and the possibility of recurrence, can be a source of continued psychological distress. In addition to the documented adverse repercussions of cancer, we also outline the recent shift that has occurred in the psycho-oncology literature regarding positive life change or posttraumatic growth that is commonly reported after a diagnosis of cancer. Adopting a salutogenic framework acknowledges that the cancer experience is a dynamic psychosocial process with both negative and positive repercussions. Next, we describe the situational and individual factors that are associated with posttraumatic growth and the types of positive life change that are prevalent in this context. Finally, we discuss the implications of this research in a therapeutic context and the directions of future posttraumatic growth research with cancer survivors. This chapter will present both quantitative and qualitative research that indicates the potential for personal growth from adversity rather than just mere survival and return to pre-diagnosis functioning. It is important to emphasise however, that the presence of growth and prevalence of resilience does not negate the extremely distressing nature of a cancer diagnosis for the patient and their families and the suffering that can accompany treatment regimes. Indeed, it will be explained that for growth to occur, the experience must be one that quite literally shatters previously held schemas in order to act as a catalyst for change.

Lysosomal secretion of Flightless I upon injury has the potential to alter inflammation

Intracellular Flightless I (Flii), a gelsolin family member, has been found to have roles modulating actin regulation, transcriptional regulation and inflammation. In vivo Flii can regulate wound healing responses. We have recently shown that a pool of Flii is secreted by fibroblasts and macrophages, cells typically found in wounds, and its secretion can be upregulated upon wounding. We show that secreted Flii can bind to the bacterial cell wall component lipopolysaccharide and has the potential to regulate inflammation. We now show that secreted Flii is present in both acute and chronic wound fluid.

Use of focus group technique to investigate infection control practice

Use of focus groups as a technique of inquiry is gaining attention in the area of health-care research. This paper will report on the technique of focus group interviewing to investigate the role of the infection control practitioner. Infection control is examined as a specialty area of health-care practice that has received little research attention to date. Additionally, it is an area of practice that is expanding in response to social, economic and microbiological forces. The focus group technique in this study helped a group of infection control practitioners from urban, regional and rural areas throughout Queensland identify and categorise their daily work activities. The outcomes of this process were then analysed to identify the growth in breadth and complexity of the role of the infection control practitioner in the contemporary health-care environment. Findings indicate that the role of the infection control practitioner in Australia has undergone changes consistent with and reflecting changing models of health-care delivery.

Intraurban rail access : Policy implications of five revealed perspectives from a Q-sorting exercise in three Australian cities

This project advances current understanding of intra-urban rail passengers and their travel experiences in order to help rail industry leaders tailor policy approaches to fit specific, relevant segments of their target population. Using a Q sorting technique and cluster analysis, our preliminary research identified five perspectives occurring in a small sample of rail passengers, who varied in their frequency and location of rail travel as well as certain socio-demographic characteristics. Revealed perspectives (named to capture the gist of their content) included: ‘Rail Travel is About the Destination, Not the Journey’; ‘Despite Challenges, Public Transport is Still the Best Option’; ‘Rail Travel is Fine’; ‘Rail Travel? So Far, So Good’; and ‘Bad Taste for Rail Travel’. This paper discusses each of the perspectives in detail, and considers them in terms of tailored policy implications. An overarching finding from this study is that improving railway travel ‘access’ requires attention to physical, psychological, financial, and social facets of accessibility. For example, designing waiting areas to be more socially functional and comfortable has the potential to increase ridership by addressing social forms of access, decreasing perceived wait times, and making time at the station feel like time well spent. Even at this preliminary stage, the Q sorting technique promises to provide a valuable, holistic albeit fine-grained analysis of passenger attitudes and experiences that will assist industry efforts to increase ridership.

The potential for ethanol production from sugarcane in Australia

The Australian sugar industry processes approximately 35 million tonnes of sugarcane per year from 400 000 hectares of land. Sugar remains the principal revenue stream from sugarcane in Australia with less than 60 ML/y of fuel ethanol produced from final molasses at present. Modelling has been undertaken to estimate the potential ethanol production from the Australian sugar industry for integrated facilities producing both sugar and ethanol from the entire sugarcane resource. Although research aimed at developing commercial processes is ongoing, the use of a proportion of the bagasse and trash for ethanol production, in addition to juice and molasses fermentation, would allow significant increases in the scale of ethanol production from sugarcane in Australia, increasing total industry revenues while maintaining energy self sufficiency.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.