Where are the mental health nurses?

In the 2007 national census, 7.1 million Australians answered yes to having a mental illness in their lifetime (ABS, 2013). This is a significant number of people, all of whom deserve specialist care from appropriately trained and qualified nurses

Particle size segregation in granular flow in silos

Segregation and layering of alumina in storage silos are investigated, with a view to predicting output quality versus time, given known variations in input quality on emplacement. A variety of experiments were conducted, existing relevant publications were reviewed, and the basis for an algorithm for predicting the effect of withdrawing from a central flowing region, in combination with variations in quality due to geometric, layering and segregation effects, is described in this report

Microglia-derived TNFα induces apoptosis in neural precursor cells via transcriptional activation of the Bcl-2 family member Puma

Neuroinflammation is a common feature of acute neurological conditions such as stroke and spinal cord injury, as well as neurodegenerative conditions such as Parkinson’s disease, Alzheimer’s disease, and amyotrophic lateral sclerosis. Previous studies have demonstrated that acute neuroinflammation can adversely affect the survival of neural precursor cells (NPCs) and thereby limit the capacity for regeneration and repair. However, the mechanisms by which neuroinflammatory processes induce NPC death remain unclear. Microglia are key mediators of neuroinflammation and when activated to induce a pro-inflammatory state produce a number of factors that could affect NPC survival. Importantly, in the present study we demonstrate that tumor necrosis factor α (TNFα) produced by lipopolysaccharide-activated microglia is necessary and sufficient to trigger apoptosis in mouse NPCs in vitro. Furthermore, we demonstrate that microglia-derived TNFα induces NPC apoptosis via a mitochondrial pathway regulated by the Bcl-2 family protein Bax. BH3-only proteins are known to play a key role in regulating Bax activation and we demonstrate that microglia-derived TNFα induces the expression of the BH3-only family member Puma in NPCs via an NF-jB-dependent mechanism. Specifically, we show that NF-jB is activated in NPCs treated with conditioned media from activated microglia and that Puma induction and NPC apoptosis is blocked by the NF-jB inhibitor BAY-117082. Importantly, we have determined that NPC apoptosis induced by activated microglia-derived TNFα is attenuated in Puma-deficient NPCs, indicating that Puma induction is required for NPC death. Consistent with this, we demonstrate that Puma-deficient NPCs exhibit an B13-fold increase in survival as compared with wild-type NPCs following transplantation into the inflammatory environment of the injured spinal cord in vivo. In summary, we have identified a key signaling pathway that regulates neuroinflammation induced apoptosis in NPCs in vitro and in vivo that could be targeted to promote regeneration and repair in diverse neurological conditions

Framework for better living with HIV in England

Duration: April 2007 - May 2009 Sigma Research was funded by Terrence Higgins Trust to co-ordinate the development of a framework to address the health, social care, support and information needs of people with diagnosed HIV in England. It has now been published as the Framework for better living with HIV in England. The over-arching goal of the framework is that all people with diagnosed HIV in England "are enabled to have the maximum level of health, well-being, quality of life and social integration". In its explanation of how this should occur the document presents a road map for social care, support and information provision to people with diagnosed HIV in England. By establishing and communicating aims and objectives, the framework should build consensus and provide a means to establish how interventions could be prioritised and coordinated. The key drivers for the framework were clearly articulated ethical principles, agreed by all those who sign up to it, and an inclusive social development / health promotion approach. Sigma Research worked on the framework with a range of other organisations who sent representatives to a Framework Development Group (see below for membership). The framework is evidence-based and seeks to: Promote and protect the rights and well-being of all people with HIV in England. Maximise the capacity of individuals and groups of people with HIV to care for, advocate and represent themselves effectively. Improve and protect access to appropriate information, social support, social care and clinical services. Minimise social, economic, governmental and judicial change detrimental to the health and well being of people with HIV. Alongside the development of the framework, Sigma Research undertook a national needs assessment among people with diagnosed HIV across the UK called What do you need?. These two projects informed and supported each other. Framework Development Group included: African HV Policy Network Black Health Agency George House Trust NAM NAT (National AIDS Trust) Positively Women Terrence Higgins Trus

Nonlinear Impurity Modes in Homogeneous and Periodic Media

We analyze the existence and stability of nonlinear localized waves described by the Kronig-Penney model with a nonlinear impurity. We study the properties of such waves in a homogeneous medium, and then analyze new effects introduced by periodicity of the medium parameters. In particular, we demonstrate the existence of a novel type of stable nonlinear band-gap localized states, and also reveal an important physical mechanism of the oscillatory wave instabilities associated with the band-gap wave resonances.Comment: 11 pages, 3 figures; To be published in: Proceedings of the NATO Advanced Research Workshop "Nonlinearity and Disorder: Theory and Applications" (Tashkent, 2-6 Oct, 2000) Editors: P.L. Christiansen and F.K. Abdullaev (Kluwer, 2001

SNP-PHAGE – High throughput SNP discovery pipeline

BACKGROUND: Single nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable. RESULTS: We developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis) and GenBank (-dbSNP) submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at . CONCLUSION: SNP-PHAGE provides a bioinformatics solution for high throughput SNP discovery, identification of common haplotypes within an amplicon, and GenBank (dbSNP) submissions. SNP selection and visualization are aided through a user-friendly web interface. This tool is useful for analyzing sequence tagged sites (STSs) of genomic sequences, and this software can serve as a starting point for groups interested in developing SNP markers

Application of machine learning in SNP discovery

<p>Abstract</p> <p>Background</p> <p>Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given species. Polymorphism detection software PolyBayes and PolyPhred give high false positive SNP predictions even with stringent parameter values. We developed a machine learning (ML) method to augment PolyBayes to improve its prediction accuracy. ML methods have also been successfully applied to other bioinformatics problems in predicting genes, promoters, transcription factor binding sites and protein structures.</p> <p>Results</p> <p>The ML program C4.5 was applied to a set of features in order to build a SNP classifier from training data based on human expert decisions (True/False). The training data were 27,275 candidate SNP generated by sequencing 1973 STS (sequence tag sites) (12 Mb) in both directions from 6 diverse homozygous soybean cultivars and PolyBayes analysis. Test data of 18,390 candidate SNP were generated similarly from 1359 additional STS (8 Mb). SNP from both sets were classified by experts. After training the ML classifier, it agreed with the experts on 97.3% of test data compared with 7.8% agreement between PolyBayes and experts. The PolyBayes positive predictive values (PPV) (i.e., fraction of candidate SNP being real) were 7.8% for all predictions and 16.7% for those with 100% posterior probability of being real. Using ML improved the PPV to 84.8%, a 5- to 10-fold increase. While both ML and PolyBayes produced a similar number of true positives, the ML program generated only 249 false positives as compared to 16,955 for PolyBayes. The complexity of the soybean genome may have contributed to high false SNP predictions by PolyBayes and hence results may differ for other genomes.</p> <p>Conclusion</p> <p>A machine learning (ML) method was developed as a supplementary feature to the polymorphism detection software for improving prediction accuracies. The results from this study indicate that a trained ML classifier can significantly reduce human intervention and in this case achieved a 5–10 fold enhanced productivity. The optimized feature set and ML framework can also be applied to all polymorphism discovery software. ML support software is written in Perl and can be easily integrated into an existing SNP discovery pipeline.</p

Reviews

Reviews of International and comparative industrial relations, Tatau Tatau - one big union altogether, Remedy for present evils: a history of the New Zealand Public Service Association from 1890, Sexual harassment in the workplace, Employee selection, Legislating for workplace hazards in New Zealand: overseas experience and our present and future needs, People and enterprises - human behaviour in New Zealand organisations and From school to unemployment? The labour market for young peopl

Stimulated emission of polarization-entangled photons

Entangled photon pairs -- discrete light quanta that exhibit non-classical correlations -- play a crucial role in quantum information science (for example in demonstrations of quantum non-locality and quantum cryptography). At the macroscopic optical field level non-classical correlations can also be important, as in the case of squeezed light, entangled light beams and teleportation of continuous quantum variables. Here we use stimulated parametric down-conversion to study entangled states of light that bridge the gap between discrete and macroscopic optical quantum correlations. We demonstrate experimentally the onset of laser-like action for entangled photons. This entanglement structure holds great promise in quantum information science where there is a strong demand for entangled states of increasing complexity.Comment: 5 pages, 4 figures, RevTeX