Molecular structure of Mg-Al, Mn-Al and Zn-Al halotrichites : an infrared spectroscopic study

Near infrared (NIR), X-ray diffraction (XRD) and infrared (IR) spectroscopy have been applied to halotrichites of the formula MgAl2(SO4)4∙22H2O, MnAl2(SO4)4∙22H2O and ZnAl2(SO4)4∙22H2O. Comparison of the halotrichites in different spectral regions has shown that the incorporation of a divalent transition metal into the halotrichite structure causes a shift in OH stretching band positions to lower wavenumbers. Therefore, an increase in hydrogen bonded water is observed for divalent cations with a larger molecular mass. XRD has confirmed the formation of halotrichite for all three samples and characteristic peaks of halotrichite have been identified at 18.5 and 24.5° 2θ, along with a group of six peaks between 5 and 15° 2θ. It has been observed that Mg-Al and Mn-Al halotrichite are very similar in structure, while Zn-Al showed several differences particularly in the NIR spectra. This work has shown that halotrichite structures can be synthesised and characterised by infrared and NIR spectroscopy.

Addressing sustainable living using a collaborative approach and multi-disciplinary techniques

In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Investigation into the introduction of clonal strains of Pseudomonas aeruginosa to the cystic fibrosis population by consumption of raw salad vegetables

Most salad vegetables are eaten fresh by consumers. However, raw vegetables may pose a risk of transmitting opportunistic bacteria to immunocompromised people, including cystic fibrosis (CF) patients. In particular, CF patients are vulnerable to chronic Pseudomonas aeruginosa lung infections and this organism is the primary cause of morbidity and mortality in this group. Clonal variants of P. aeruginosa have been identified as emerging threats to people afflicted with CF; however it has not yet been proven from where these clones originate or how they are transmitted. Due to the organisms‟ aquatic environmental niche, it was hypothesised that vegetables may be a source of these clones. To test this hypothesis, lettuce, tomatoes, mushrooms and bean sprout packages (n = 150) were analysed from a green grocer, supermarket and farmers‟ market within the Brisbane region, availability permitting. The internal and external surfaces of the vegetables were separately analysed for the presence of clonal strains of P. aeruginosa using washings and homogenisation techniques, respectively. This separation was in an attempt to establish which surface was contaminated, so that recommendations could be made to decrease or eliminate P. aeruginosa from these foods prior to consumption. Soil and water samples (n = 17) from local farms were also analysed for the presence of P. aeruginosa. Presumptive identification of isolates recovered from these environmental samples was made based on growth on Cetrimide agar at 42°C, presence of the cytochrome-oxidase enzyme and inability to ferment lactose. P. aeruginosa duplex real-time polymerase chain reaction assay (PAduplex) was performed on all bacterial isolates presumptively identified as P. aeruginosa. Enterobacterial repetitive intergenic consensus strain typing PCR (ERIC-PCR) was subsequently performed on confirmed bacterial isolates. Although 72 P. aeruginosa were isolated, none of these proved to be clonal strains. The significance of these findings is that vegetables may pose a risk of transmitting sporadic strains of P. aeruginosa to people afflicted with CF and possibly, other immunocompromised people.

Periodontal regeneration and mesenchymal stem cells

The ultimate goal of periodontal therapy is to regenerate periodontal supporting tissues, but this is hard to achieve as the results of periodontal techniques for regeneration are clinically unpredictable. Stem cells owing to their plasticity and proliferation potential provides a new paradigm for periodontal regeneration. Stem cells from mesenchyme can self renew and generate new dental tissues (including dentin and cementum), alveolar bone and periodontal ligament, and thus they have great potential in periodontal regeneration. This chapter presents an insight into mesenchymal stem cells and their potential use in periodontal regeneration. In this chapter the cellular and molecular biology in periodontal regeneration will be introduced, followed by a range of conventional surgical procedures for periodontal regeneration will be discussed. Mesenchymal stem cells applied in regenerated periodontal tissue and their biological characterizations in vitro will be also introduced. Lastly, the use of mesenchymal stem cell to repair periodontal tissues in large animal models will be also reviewed.

The molecular mechanisms utilised by mesenchymal stem cells in migration to acute myocardial infarction

Heart damage caused by acute myocardial infarction (AMI) is a leading cause of death and disability in Australia. Novel therapies are still required for the treatment of this condition due to the poor reparative ability of the heart. As such, cellular therapies that assist in the recovery of heart muscle are of great current interest. Culture expanded mesenchymal stem cells (MSC) represent a stem and progenitor cell population that has been shown to promote tissue recovery in pre-clinical studies of AMI. For MSC-based therapies in the clinic, an intravenous route of administration would ideally be used due to the low cost, ease of delivery and relative safety. The study of MSC migration is therefore clinically relevant for a minimally invasive cell therapy to promote regeneration of damaged tissue. C57BL/6, UBI-GFP-BL/6 and CD44-/-/GFP+/+ mice were utilised to investigate mMSC migration. To assist in murine models of MSC migration, a novel method was used for the isolation of murine MSC (mMSC). These mMSC were then expanded in culture and putative mMSC were positive for Sca-1, CD90.2, and CD44 and were negative for CD45 and CD11b. Furthermore, mMSC from C57BL/6 and UBI-GFP-BL/6 mice were shown to differentiate into cells of the mesodermal lineage. Cells from CD44-/-/GFP+/+ mice were positive for Sca-1 and CD90.2, and negative for CD44, CD45 and CD11b however, these cells were unable to differentiate into adipocytes and chondrocytes and express lineage specific genes, PLIN and ACAN. Analysis of mMSC chemokine receptor (CR) expression showed that although mMSC do express chemokine receptors, (including those specific for chemokines released after AMI), these were low or undetectable by mRNA. However, protein expression could be detected, which was predominantly cytoplasmic. It was further shown that in both healthy (unperturbed) and inflamed tissues, mMSC had very little specific migration and engraftment after intravenous injection. To determine if poor mMSC migration was due to the inability of mMSC to respond to chemotactic stimuli, chemokine expression in bone marrow, skin injury and hearts (healthy and after AMI) was analysed at various time points by quantitative real-time PCR (qRT PCR). Many chemokines were up-regulated after skin biopsy and AMI, but the highest acute levels were found for CXCL12 and CCL7. Due to their high expression in infarcted hearts, the chemokines CXCL12 and CCL7 were tested for their effect on mMSC migration. Despite CR expression at both protein and mRNA levels, migration in response to CXCL12 and CCL7 was low in mMSC cultured on Nunclon plastic. A novel tissue culture plastic technology (UpCellTM) was then used that allowed gentle non-enzymatic dissociation of mMSC, thus preserving surface expression of the CRs. Despite this the in vitro data indicated that CXCL12 fails to induce significant migration ability of mMSC, while CCL7 induces significant, but low-level migration. We speculated this may be because of low levels of surface expression of chemokine receptors. In a strategy to increase cell surface expression of mMSC chemokine receptors and enhance their in vitro and in vivo migration capacity, mMSC were pre-treated with pro-inflammatory cytokines. Increased levels of both mRNA and surface protein expression were found for CRs by pre-treating mMSC with pro-inflammatory cytokines including TNF-á, IFN-ã, IL-1á and IL-6. Furthermore, the chemotactic response of mMSC to CXCL12 and CCL7 was significantly higher with these pretreated cells. Finally, the effectiveness of this type of cell manipulation was demonstrated in vivo, where mMSC pre-treated with TNF-á and IFN-ã showed significantly increased migration in skin injury and AMI models. Therefore this thesis has demonstrated, using in vitro and in vivo models, the potential for prior manipulation of MSC as a possible means for increasing the utility of intravenously delivery for MSC-based cellular therapies.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Ghrelin axis genes, peptides and receptors : recent findings and future challenges

The ghrelin axis consists of the gene products of the ghrelin gene (GHRL), and their receptors, including the classical ghrelin receptor GHSR. While it is well-known that the ghrelin gene encodes the 28 amino acid ghrelin peptide hormone, it is now also clear that the locus encodes a range of other bioactive molecules, including novel peptides and non-coding RNAs. For many of these molecules, the physiological functions and cognate receptor(s) remain to be determined. Emerging research techniques, including proteogenomics, are likely to reveal further ghrelin axis-derived molecules. Studies of the role of ghrelin axis genes, peptides and receptors, therefore, promises to be a fruitful area of basic and clinical research in years to come.

Molecular dynamics study of dynamic buckling properties of nanowires with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the deformation properties of Cu nanowires with different single defects under dynamic compression have been studied. The mechanical behaviours of the perfect nanowire are first studied, and the critical stress decreases with the increase of the nanowire’s length, which is well agreed with the modified Euler theory. We then consider the effects to the buckling phenomenon resulted from different defects. It is found that obvious decrease of the critical stress is resulted from different defects, and the largest decrease is found in nanowire with the surface vertical defect. Surface defects are found exerting larger influence than internal defects. The buckling duration is found shortened due to different defects except the nanowire with surface horizon defect, which is also found possessing the largest deflection. Different deflections are also observed for different defected nanowires. It is find that due to surface defects, only deflection in one direction is happened, but for internal defects, more complex deflection circumstances are observed.