Identification of a novel prostate cancer susceptibility variant in the KLK3 gene transcript

Abstract Genome-wide association studies (GWAS) have identified more than 30 prostate cancer (PrCa) susceptibility loci. One of these (rs2735839) is located close to a plausible candidate susceptibility gene, KLK3, which encodes prostate-specific antigen (PSA). PSA is widely used as a biomarker for PrCa detection and disease monitoring. To refine the association between PrCa and variants in this region, we used genotyping data from a two-stage GWAS using samples from the UK and Australia, and the Cancer Genetic Markers of Susceptibility (CGEMS) study. Genotypes were imputed for 197 and 312 single nucleotide polymorphisms (SNPs) from HapMap2 and the 1000 Genome Project, respectively. The most significant association with PrCa was with a previously unidentified SNP, rs17632542 (combined P = 3.9 × 10−22). This association was confirmed by direct genotyping in three stages of the UK/Australian GWAS, involving 10,405 cases and 10,681 controls (combined P = 1.9 × 10−34). rs17632542 is also shown to be associated with PSA levels and it is a non-synonymous coding SNP (Ile179Thr) in KLK3. Using molecular dynamic simulation, we showed evidence that this variant has the potential to introduce alterations in the protein or affect RNA splicing. We propose that rs17632542 may directly influence PrCa risk.

Social identification dimensions as mediators of the effect of prototypicality on intergroup behaviours

Cameron (2004) proposed a three-dimensional model and measure of social identification consisting of cognitive centrality, in-group affect, and in-group ties. This approach has received growing theoretical and empirical support; however, little research has examined how these dimensions of social identification may relate differentially to intergroup outcome behaviors. The current research sought to address this question by examining the possible mediating role the dimensions of social identification on the relationship between prototypicality of group members and the intergroup outcome behaviors of in-group favoritism, out-group derogation, and collective self-esteem. The current study examined university students’ (N = 235) feelings towards students from their own and another local university. Structural equation modeling was used to identify the most appropriate and parsimonious models of these pathways. The results showed support for the utility of measuring social identification using a multidimensional approach with unique meditational pathways emerging for the distinct intergroup behaviors.

An improved method to detect damage using modal strain energy based damage index

This paper presents two novel concepts to enhance the accuracy of damage detection using the Modal Strain Energy based Damage Index (MSEDI) with the presence of noise in the mode shape data. Firstly, the paper presents a sequential curve fitting technique that reduces the effect of noise on the calculation process of the MSEDI, more effectively than the two commonly used curve fitting techniques; namely, polynomial and Fourier’s series. Secondly, a probability based Generalized Damage Localization Index (GDLI) is proposed as a viable improvement to the damage detection process. The study uses a validated ABAQUS finite-element model of a reinforced concrete beam to obtain mode shape data in the undamaged and damaged states. Noise is simulated by adding three levels of random noise (1%, 3%, and 5%) to the mode shape data. Results show that damage detection is enhanced with increased number of modes and samples used with the GDLI.

Identification of vitronectin as a novel insulin-like growth factor-II binding protein

We have previously reported the presence of a 70 kDa insulin-like growth factor (IGF)-II-specific binding protein in chicken serum using Western ligand blotting approaches. In order to ascertain the identity of this 70 kDa IGF-II binding species, the protein has been purified from chicken serum using a combination of ion-exchange and gel-permeation chromatography. Interestingly, amino acid sequencing of the purified protein revealed that it has the same N-terminal sequence as chicken vitronectin (VN). The protein has the ability to specifically bind IGF-II and not IGF-I as determined by ligand blotting, cross-linking and competitive binding assay approaches. In addition, the protein binds 125I-des(l-6)-IGF-II, suggesting that the interaction with IGF-II is different to those with other characterized IGF-binding proteins. Importantly, we have ascertained that both human and bovine VN also specifically bind IGF-II. These results are particularly relevant in the light of the recent report that the urokinase-type plasminogen activator receptor, a protein that also binds VN, has been shown to associate with the cation-independent mannose-6-phosphate/GF-II receptor and suggest a possible role for IGF-II in cell adhesion and invasion.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

The identification of therapeutic targets in metastatic melanoma

Metastatic melanoma, a cancer historically refractory to chemotherapeutic strategies, has a poor prognosis and accounts for the majority of skin cancer related mortality. Although the recent approval of two new drugs combating this disease, Ipilimumab and Vemurafenib (PLX4032), has demonstrated for the first time in decades an improvement in overall survival; the clinical efficacy of these drugs has been marred by severe adverse immune reactions and acquired drug resistance in patients, respectively. Thus, understanding the etiology of metastatic melanoma will contribute to the improvement of current therapeutic strategies while leading to the development of novel drug approaches. In order to identify recurrently mutated genes of therapeutic relevance in metastatic melanoma, a panel of stage III local lymph node melanomas were extensively characterised using high-throughput genomic technologies. This led to the identification of mutations in TFG in 5% of melanomas from a candidate gene sequencing approach using SNP array analysis, 24% of melanomas with mutations in MAP3K5 or MAP3K9 though unbiased whole-exome sequencing strategies, and inactivating mutations in NF1 in BRAF/NRAS wild type tumours though pathway analysis. Lastly, this thesis describes the development of a melanoma specific mutation panel that can rapidly identify clinically relevant mutation profiles that could guide effective treatment strategies through a personalised therapeutic approach. These findings are discussed in respect to a number of important issues raised by this study including the current limitation of next-generation sequencing technology, the difficulty in identifying ‘driver’ mutations critical to the development of melanoma due to high carcinogenic exposure by UV radiation, and the ultimate application of mutation screening in a personalised therapeutic setting. In summary, a number novel genes involved in metastatic melanoma have been identified that may have relevance for current therapeutic strategies in treating this disease.

The spatial distribution of rodent damage in Australian macadamia (Macadamia integrifolia) orchards

The Black Rat (Rattus rattus), a global pest within the macadamia production industry, causes up to 30% crop damage in Australian orchards. During early stages of production in Australia, research demonstrated the importance of non crop adjacent habitats as significant in affecting the patterns of crop damage seen throughout orchards. Where once rodent damage was limited to the outside edges of orchard blocks, growers are now reporting finding crop damage throughout entire orchards. This study therefore aims to explore the spatial patterns of rodent distribution and damage now occurring in Australian macadamia orchards. We show that rodent damage and rodent distribution in these newer production regions differ from that shown in previous Australian research. Previous Australian research has shown damage patterns which were associated with the edges of orchard blocks however this study demonstrates a more widespread damage distribution. In the current study there is no relationship between rodent damage and the orchard edge. Arboreal rodent nests were identified within these newer orchard systems, suggesting rodents are residing within the tree component of the orchard system and not dependent on adjacent non-crop habitat for shelter. Results from this study confirm that rodents have modified their nesting and foraging behaviour in newer orchards systems in Australia. We suggest that this is a response of increased and prolonged availability of macadamia nuts in newer production regions enabling populations to be maintained throughout the year. Management strategies will require modification if control is to be achieved.

A database for person re-identification in multi-camera surveillance networks

Person re-identification involves recognising individuals in different locations across a network of cameras and is a challenging task due to a large number of varying factors such as pose (both subject and camera) and ambient lighting conditions. Existing databases do not adequately capture these variations, making evaluations of proposed techniques difficult. In this paper, we present a new challenging multi-camera surveillance database designed for the task of person re-identification. This database consists of 150 unscripted sequences of subjects travelling in a building environment though up to eight camera views, appearing from various angles and in varying illumination conditions. A flexible XML-based evaluation protocol is provided to allow a highly configurable evaluation setup, enabling a variety of scenarios relating to pose and lighting conditions to be evaluated. A baseline person re-identification system consisting of colour, height and texture models is demonstrated on this database.

When non-significance may be significant : lessons learned from a study of the development, implementation and evaluation of a fleet risk assessment tool

This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

Leucocytes, cytokines and satellite cells : what role do they play in muscle damage and regeneration following eccentric exercise?

Exercise-induced muscle damage is an important topic in exercise physiology. However several aspects of our understanding of how muscles respond to highly stressful exercise remain unclear In the first section of this review we address the evidence that exercise can cause muscle damage and inflammation in otherwise healthy human skeletal muscles. We approach this concept by comparing changes in muscle function (i.e., the force-generating capacity) with the degree of leucocyte accumulation in muscle following exercise. In the second section, we explore the cytokine response to 'muscle-damaging exercise', primarily eccentric exercise. We review the evidence for the notion that the degree of muscle damage is related to the magnitude of the cytokine response. In the third and final section, we look at the satellite cell response to a single bout of eccentric exercise, as well as the role of the cyclooxygenase enzymes (COX1 and 2). In summary, we propose that muscle damage as evaluated by changes in muscle function is related to leucocyte accumulation in the exercised muscles. 'Extreme' exercise protocols, encompassing unaccustomed maximal eccentric exercise across a large range of motion, generally inflict severe muscle damage, inflammation and prolonged recovery (> 1 week). By contrast, exercise resembling regular athletic training (resistance exercise and downhill running) typically causes mild muscle damage (myofibrillar disruptions) and full recovery normally occurs within a few days. Large variation in individual responses to a given exercise should, however be expected. The link between cytokine and satellite cell responses and exercise-induced muscle damage is not so clear The systemic cytokine response may be linked more closely to the metabolic demands of exercise rather than muscle damage. With the exception of IL-6, the sources of systemic cytokines following exercise remain unclear The satellite cell response to severe muscle damage is related to regeneration, whereas the biological significance of satellite cell proliferation after mild damage or non-damaging exercise remains uncertain. The COX enzymes regulate satellite cell activity, as demonstrated in animal models; however the roles of the COX enzymes in human skeletal muscle need further investigation. We suggest using the term 'muscle damage' with care. Comparisons between studies and individuals must consider changes in and recovery of muscle force-generating capacity.

Identification of bone morphogenetic proteins 2 and 4 in commercial demineralized freeze-dried bone allograft preparations : pilot study

BACKGROUND: Demineralized freeze-dried bone allografts (DFDBAs) have been proposed as a useful adjunct in periodontal therapy to induce periodontal regeneration through the induction of new bone formation. The presence of bone morphogenetic proteins (BMPs) within the demineralized matrix has been proposed as a possible mechanism through which DFDBA may exert its biologic effect. However, in recent years, the predictability of results using DFDBA has been variable and has led to its use being questioned. One reason for the variability in tissue response may be attributed to differences in the processing of DFDBA, which may lead to loss of activity of any bioactive substances within the DFDBA matrix. Therefore, the purpose of this investigation was to determine whether there are detectable levels of bone morphogenetic proteins in commercial DFDBA preparations. METHODS: A single preparation of DFDBA was obtained from three commercial sources. Each preparation was studied in triplicate. Proteins within the DFDBA samples were first extracted with 4M guanidinium HCI for seven days at 40 degrees celsius and the residue was further extracted with 4M guanidinium HCL/EDTA for seven days at 40 degrees celsius. Two anti-human BMP-2 and -4 antibodies were used for the detection of the presence of BMP's in the extracts. RESULTS: Neither BMP-2 nor BMP-4 was detected in any of the extracts. When recombinant human BMP-2 and -4 were added throughout the extraction process of DFDBA extraction, not only were intact proteins detected but smaller molecular weight fragments were also noted in the extract. CONCLUSIONS: These results indicate that all of the DFDBA samples tested had no detectable amounts of BMP-2 and -4. In addition, an unknown substance present in the DFDBA may be responsible for degradation of whatever BMPs might be present.

Accident risk identification and its impact analyses for strategic construction safety management

The study presented in this paper reviewed 9,358 accidents which occurred in the U.S. construction industry between 2002 and 2011, in order to understand the relationships between the risk factors and injury severity (e.g. fatalities, hospitalized injuries, or non-hospitalized injuries) and to develop a strategic prevention plan to reduce the likelihood of fatalities where an accident is unavoidable. The study specifically aims to: (1) verify the relationships among risk factors, accident types, and injury severity, (2) determine significant risk factors associated with each accident type that are highly correlated to injury severity, and (3) analyze the impact of the identified key factors on accident and fatality occurrence. The analysis results explained that safety managers’ roles are critical to reducing human-related risks—particularly misjudgement of hazardous situations—through safety training and education, appropriate use of safety devices and proper safety inspection. However, for environment-related factors, the dominant risk factors were different depending on the different accident types. The outcomes of this study will assist safety managers to understand the nature of construction accidents and plan for strategic risk mitigation by prioritizing high frequency risk factors to effectively control accident occurrence and manage the likelihood of fatal injuries on construction sites.