The impact of fatigue caused by sprint running on the median power frequency of the hamstring muscle group

Hamstring strain injuries (HSI) are the predominant non-contact injury in many sports. Intermittent running has been shown to result in preferential reductions in eccentric hamstring strength, which increase the risk of sustaining a HSI. The eccentric specific nature of this decline in hamstring function implicates central mechanisms, as peripheral fatigue mechanisms tend to impact upon both concentric and eccentric contractions modes. However, neural function of the hamstrings, such as the median power frequency (MPF) of the surface electromyography signal has yet to be examined in the fatigued hamstring following intermittent sprint running. AIM: To determine the impact of fatigue induced by intermittent sprinting on the MPF of the medial and lateral hamstring muscles. METHODS: Fifteen recreationally active males completed 18 × 20m overground sprints. Maximal strength (concentric and eccentric knee flexor and concentric knee extensor) was determined isokinetically at the velocities of ±180.s-1 and ±60.s- while hamstring muscle activation was assessed using surface electromyography, before and 15 minutes after the running protocol. RESULTS: Overground intermittent running caused a significant reduction in eccentric knee flexor strength (27.2 Nm; 95% CI = 11.2 to 43.3; p=0.0001) but not concentric strength (9.3 Nm; 95% CI = -6.7 to 25.3; P=0.6361). Following the overground running, MPF of the lateral hamstrings showed a significant decline eccentrically (0.86; 95% CI = 0.59 to 1.54; P=0.038) and concentrically (0.76; 95%CI = 0.66 to 0.83; P=0.039). Similar declines in MPF were also noted in the medial hamstrings eccentrically (1.54; 95% CI = 0.59 to 7.9; P=0.005) and concentrically (1.18; 95% CI = 0.44 to 6.8; P=0.040). CONCLUSION: Whilst sprint running induced fatigue led to a eccentric specific reduction in knee flexor torque, MPF was suppressed across both contraction modes. This would indicate that factors associated with the decline in MPF do not appear to explain the contraction mode-specific loss of strength after intermittent sprints. This would implicate other central mechanisms, such as declines in voluntary activation, in explaining the eccentric specific decline in strength seen following sprint running.

Kallikrein 14 is down-regulated by androgen receptor signalling and harbours genetic variation that is associated with prostate tumour aggressiveness

Kallikrein 14 (KLK14) has been proposed as a useful prognostic marker in prostate cancer, with expression reported to be associated with tumour characteristics such as higher stage and Gleason score. KLK14 tumour expression has also shown the potential to predict prostate cancer patients at risk of disease recurrence after radical prostatectomy. The KLKs are a remarkably hormone-responsive family of genes, although detailed studies of androgen regulation of KLK14 in prostate cancer have not been undertaken to date. Using in vitro studies, we have demonstrated that unlike many other prostatic KLK genes that are strictly androgen responsive, KLK14 is more broadly expressed and inversely androgen regulated in prostate cancer cells. Given these results and evidence that KLK14 may play a role in prostate cancer prognosis, we also investigated whether common genetic variants in the KLK14 locus are associated with risk and/or aggressiveness of prostate cancer in approximately 1200 prostate cancer cases and 1300 male controls. Of 41 single nucleotide polymorphisms assessed, three were associated with higher Gleason score (≥7): rs17728459 and rs4802765, both located upstream of KLK14, and rs35287116, which encodes a p.Gln33Arg substitution in the KLK14 signal peptide region. Our findings provide further support for KLK14 as a marker of prognosis in prostate cancer.

Refugees : the Millenium Development Goals' overlooked priority group

The Millennium Development Goals (MDGs) apply to the world’s 43 million refugees and forcibly displaced. While States have an obligation to meet minimum human rights levels for all persons including 'non-citizens', UNHCR must ensure countries adopting MDG targets report on the progress of their refugee populations. If we are to make significant change within the MDG time-frame, the health and human rights needs of refugees and the displaced must be urgently integrated into the development policy agendas of sovereign States, and be at the fore of the international community’s attention.

Global genetic diversity and geographical and host-species distribution of beak and feather disease virus isolates

Psittacine beak and feather disease (PBFD) has a broad host range and is widespread in wild and captive psittacine populations in Asia, Africa, the Americas, Europe and Australasia. Beak and feather disease circovirus (BFDV) is the causative agent. BFDV has an ~2 kb single stranded circular DNA genome encoding just two proteins (Rep and CP). In this study we provide support for demarcation of BFDV strains by phylogenetic analysis of 65 complete genomes from databases and 22 new BFDV sequences isolated from infected psittacines in South Africa. We propose 94% genome-wide sequence identity as a strain demarcation threshold, with isolates sharing > 94% identity belonging to the same strain, and strain subtypes sharing> 98% identity. Currently, BFDV diversity falls within 14 strains, with five highly divergent isolates from budgerigars probably representing a new species of circovirus with three strains (budgerigar circovirus; BCV-A, -B and -C). The geographical distribution of BFDV and BCV strains is strongly linked to the international trade in exotic birds; strains with more than one host are generally located in the same geographical area. Lastly, we examined BFDV and BCV sequences for evidence of recombination, and determined that recombination had occurred in most BFDV and BCV strains. We established that there were two globally significant recombination hotspots in the viral genome: the first is along the entire intergenic region and the second is in the C-terminal portion of the CP ORF. The implications of our results for the taxonomy and classification of circoviruses are discussed. © 2011 SGM.

NOS1AP is associated with increased severity of PTSD and depression in untreated combat veterans

Background Post traumatic stress disorder (PTSD) and depressive disorder are over represented in combat veterans. Veterans with both disorders have an increased risk of suicide. The nitric oxide synthase 1 adaptor protein (NOS1AP) gene, which modulates stress-evoked N-methyl-D-aspartate (NMDA) activity, was investigated in combat veterans. Methods A comprehensive genetic analysis of NOS1AP and its association with PTSD was investigated in Vietnam combat veterans with PTSD (n=121) and a group of healthy control individuals (n=237). PTSD patients were assessed for symptom severity and level of depression using the Mississippi Scale for Combat-Related PTSD and the Beck Depression Inventory-II (BDI). Results The G allele of NOS1AP SNP rs386231 was significantly associated with PTSD (p = 0.002). Analysis of variance revealed significant differences in BDI-II and Mississippi scores between genotypes for rs386231 with the GG genotype associated with increased severity of depression (p = 0.002 F = 6.839) and higher Mississippi Scale for Combat-Related PTSD scores (p = 0.033). Haplotype analysis revealed that the C/G haplotype (rs451275/rs386231) was significantly associated with PTSD (p = 0.001). Limitations The sample sizes in our study were not sufficient to detect SNP associations with very small effects. In addition the study was limited by its cross sectional design. Conclusions This is the first study reporting that a variant of the NOS1AP gene is associated with PTSD. Our data also suggest that a genetic variant in NOS1AP may increase the susceptibility to severe depression in patients with PTSD and increased risk for suicide.

Media education, collaboration and industry : a case study of what a group of year 10 and 11 students value in a community of practice

This case study incorporated an analysis of a group of young people as media producers and placed young people’s perspectives of their media education learning at the core of the analysis. Communities of practice social learning theory provided an effective conceptual framework for investigating the nature of the participants’ involvement in a secondary school and creative industry partnership. The analysis of the data in this study indicated that the participants valued their learning by imagining, actively participating and belonging to a media education community of practice. By enabling young people to work directly with creative industries this school and industry partnership provided students with what they saw as valuable first-hand experience of professional expertise, that contributed to students’ understanding of their own and others’ identities.

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.

Adaptive sizing of populations and number of islands in distributed genetic algorithms

Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

Dynamic optimization of migration topology in internet-based distributed genetic algorithms

Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

Innovative Products Focus Group Report 2012. Brisbane: QUT

This report presents the results of Phase 3 of the Innovative Road Products Project: National Focus Groups. The groups developed solutions to address the most important obstacles constraining the adoption of innovative products in Australian road construction projects. The Innovative Products Survey, the major Project deliverable in 2011, and the largest innovation survey ever undertaken in the Australian road consutrction industry, results in the identification of key obstacles constraining the adoption of innovative products on road projects.

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.

Student or scholar? Transforming identities through a research writing group

This article explores the role a writing group played in influencing the scholarly identities of a group of doctoral students by fostering their writing expertise. While the interest in writing groups usually centres on their potential to support doctoral students to publish, few studies have been conducted and written by the students themselves. Using a situated learning perspective on identity, we explore the connection that emerged between our perceptions of ourselves as developing expertise as scholarly writers and the function of the writing group as a dynamic space for transforming our identities. Findings show that our writing group served as a flexible and interactive Community of Practice (CoP) that shaped critical and durable shifts in identity amongst members.

Genetic polymorphisms in the human tissue kallikrein (KLK) locus and their implication in various malignant and non-malignant diseases

The Kallikrein (KLK) gene locus encodes a family of serine proteases and is the largest contiguous cluster of protease-encoding genes attributed an evolutionary age of 330 million years. The KLK locus has been implicated as a high susceptibility risk loci in numerous cancer studies through the last decade. The KLK3 gene already has established clinical relevance as a biomarker in prostate cancer prognosis through its encoded protein, prostate-specific antigen. Data mined through genome-wide association studies (GWAS) and next-generation sequencing point to many important candidate single nucleotide polymorphisms (SNPs) in KLK3 and other KLK genes. SNPs in the KLK locus have been found to be associated with several diseases including cancer, hypertension, cardiovascular disease and atopic dermatitis. Moreover, introducing a model incorporating SNPs to improve the efficiency of prostate-specific antigen in detecting malignant states of prostate cancer has been recently suggested. Establishing the functional relevance of these newly-discovered SNPs, and their interactions with each other, through in silico investigations followed by experimental validation, can accelerate the discovery of diagnostic and prognostic biomarkers. In this review, we discuss the various genetic association studies on the KLK loci identified either through candidate gene association studies or at the GWAS and post-GWAS front to aid researchers in streamlining their search for the most significant, relevant and therapeutically promising candidate KLK gene and/or SNP for future investigations.

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10−8). More than 70 prostate cancer susceptibility loci, explaining ~30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.

Slithering snakes, angry men and out-group members : what and whom are we evolved to fear?

The preparedness theory of classical conditioning proposed by Seligman (1970, 1971) has been applied extensively over the past 40 years to explain the nature and "source" of human fear and phobias. In this review we examine the formative studies that tested the four defining characteristics of prepared learning with animal fear-relevant stimuli (typically snakes and spiders) and consider claims that fear of social stimuli, such as angry faces, or faces of racial out-group members, may also be acquired utilising the same preferential learning mechanism. Exposition of critical differences between fear learning to animal and social stimuli suggests that a single account cannot adequately explain fear learning with animal and social stimuli. We demonstrate that fear conditioned to social stimuli is less robust than fear conditioned to animal stimuli as it is susceptible to cognitive influence and propose that it may instead reflect on negative stereotypes and social norms. Thus, a theoretical model that can accommodate the influence of both biological and cultural factors is likely to have broader utility in the explanation of fear and avoidance responses than accounts based on a single mechanism.