187 research outputs found

    Optimising self-directed funding for the long-term disabled: briefing document

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    People with long-term disabilities have become increasingly frustrated with the inadequate support services provided by the disability sector. In particular, people with long-term disabilities want to have support services which met their needs as well as greater choice and control in the decisions around them. Over the last five years the popularity of self-directed funding has increased significantly. In 2011/12 the Australian Government made a commitment to implement a National Disability Insurance Scheme (NDIS) as advised through an inquiry by the Productivity Commission to have full rollout country wide by 2018. Self-directed funding is used as a mechanism to promote self-determination and empowerment in people with long-term disabilities and to facilitate their living in the community independently. Self-directed funding can be provided by an individual package held by a provider, by an individual budget held by the person to spend through providers or by direct payments to spend on the open market. The implementation of self-directed funding models has been implemented in various forms over the past couple of decades, including the piloting of small scale programs and the introduction of larger scale programs by government bodies or departments in specific disability groups.  Self-directed funding models are strongly established in the UK, USA and Western Australia. The inclusion of infrastructure supports such as independent brokers, financial intermediaries and ongoing support for clients are beneficial features of established models, particularly for people with complex needs. Despite their popularity, there is a lack of evidence about the effectiveness of self-directed funding models in practice, and no evidence comparing different models.  No single model has been demonstrated to be superior to another, likely in part because the cultural and political context in which a scheme is introduced has a strong influence on its design, implementation and outcomes. Despite this, there are consistent indications that offering flexible and creative options within models is the best approach for ensuring people with more complex and potentially unmet needs, have an opportunity to take up self-directed funding successfully. There are limited studies of the feasibility and impact of self-directed funding for people in the compensable sector with catastrophic injuries. Qualitative studies using interviews or questionnaires reveal that, generally, people with long-term disabilities recognise that self-directed funding should be one option among the range of options for receiving necessary support services; however, there is variability in the stated willingness to take on self-directed funding themselves. A lack of awareness of what is involved in self-directed funding and how it can be managed has been reported. In addition, it has been suggested that not all people have the skills, education or experience to manage self-directed funding, hence training and information sessions that are understandable and comprehensive are likely to be necessary in order to encourage uptake.  This NTRI Forum aims to consider the factors which influence the uptake of self-directed funding by the long-term disabled. Two questions were identified for deliberation in a Stakeholder Dialogue: 1. What are the barriers and facilitators to optimal implementation and uptake of self- directed funding in Australia and New Zealand? 2. How can knowledge of barriers and facilitators be used to address these challenges

    ReCoDe: A Data Reduction and Compression Description for High Throughput Time-Resolved Electron Microscopy

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    Fast, direct electron detectors have significantly improved the spatio-temporal resolution of electron microscopy movies. Preserving both spatial and temporal resolution in extended observations, however, requires storing prohibitively large amounts of data. Here, we describe an efficient and flexible data reduction and compression scheme (ReCoDe) that retains both spatial and temporal resolution by preserving individual electron events. Running ReCoDe on a workstation we demonstrate on-the-fly reduction and compression of raw data streaming off a detector at 3 GB/s, for hours of uninterrupted data collection. The output was 100-fold smaller than the raw data and saved directly onto network-attached storage drives over a 10 GbE connection. We discuss calibration techniques that support electron detection and counting (e.g. estimate electron backscattering rates, false positive rates, and data compressibility), and novel data analysis methods enabled by ReCoDe (e.g. recalibration of data post acquisition, and accurate estimation of coincidence loss).Comment: 53 pages, 20 figure

    Dual pathogenicity island transfer by piggybacking lateral transduction

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    Lateral transduction (LT) is the process by which temperate phages mobilize large sections of bacterial genomes. Despite its importance, LT has only been observed during prophage induction. Here, we report that superantigen-carrying staphylococcal pathogenicity islands (SaPIs) employ a related but more versatile and complex mechanism of gene transfer to drive chromosomal hypermobility while self-transferring with additional virulence genes from the host. We found that after phage infection or prophage induction, activated SaPIs form concatamers in the bacterial chromosome by switching between parallel genomic tracks in replication bubbles. This dynamic life cycle enables SaPIbov1 to piggyback its LT of staphylococcal pathogenicity island vSaα, which encodes an array of genes involved in host-pathogen interactions, allowing both islands to be mobilized intact and transferred in a single infective particle. Our findings highlight previously unknown roles of pathogenicity islands in bacterial virulence and show that their evolutionary impact extends beyond the genes they carry

    Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.

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    Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. We develop a computational method, chromatin interaction neural network (ChINN), to predict chromatin interactions between open chromatin regions using only DNA sequences. ChINN predicts CTCF- and RNA polymerase II-associated and Hi-C chromatin interactions. ChINN shows good across-sample performances and captures various sequence features for chromatin interaction prediction. We apply ChINN to 6 chronic lymphocytic leukemia (CLL) patient samples and a published cohort of 84 CLL open chromatin samples. Our results demonstrate extensive heterogeneity in chromatin interactions among CLL patient samples

    Healthcare Worker Seroconversion in SARS Outbreak

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    Serum samples were obtained from healthcare workers 5 weeks after exposure to an outbreak of severe acute respiratory syndrome (SARS). A sensitive dot blot enzyme-linked immunosorbent assay, complemented by a specific neutralization test, shows that only persons in whom probable SARS was diagnosed had specific antibodies and suggests that subclinical SARS is not an important feature of the disease

    Conditional deletion of melanin-concentrating hormone receptor 1 from GABAergic neurons increases locomotor activity

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    Objective: Melanin-concentrating hormone (MCH) plays a key role in regulating energy balance. MCH acts via its receptor MCHR1, and MCHR1 deletion increases energy expenditure and locomotor activity, which is associated with a hyperdopaminergic state. Since MCHR1 expression is widespread, the neurons supporting the effects of MCH on energy expenditure are not clearly defined. There is a high density of MCHR1 neurons in the striatum, and these neurons are known to be GABAergic. We thus de
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