296 research outputs found
Effective models of employment-based training
Evolving models of employment-based training (EBT) are responding to skill shortages and the need to develop technical skills at a level higher than a certificate III—the benchmark qualification level considered by many as the minimum for ensuring sustainable job outcomes (Stanwick 2004). This research explored a variety of current employment-based training models and proposed five enhancements for higher-level qualifications. These changes concentrate on maintaining a balance of learning experiences between educational institutions and the workplace. The project was based around case studies in process manufacturing and child care. Thirty-three individuals, representing employers, employees/apprentices, vocational education and training (VET) providers, industry bodies and training package developers were interviewed. The issues and views expressed by those interviewed from both industries were consistent with what was found in the literature review. Current models of employment-based training can usefully be grouped as: two forms of 'fast-tracking' options in a formal apprenticeship model, especially at certificate III level, to address immediate skills shortages. These are accelerated progression models (shorter durations linked to a truly competency-based approach) and intensive up-front training, followed by work-based learning to ensure immediate productivity of the learner in the workplace higher-level VET qualifications gained either through an apprenticeship or by undertaking a vocational course the design of new skill sets/qualifications at various levels of the Australian Qualifications Framework (AQF) alternative provisions for young people. Although these models continue to make a significant contribution to the skilling of the Australian workforce, their full potential is limited by certain persistent issues. These include inconsistent regulatory arrangements, non-compliance by employers and registered training organisations, poor audit processes, variations in the interpretation and practice of competency-based training, and wages and awards. These various factors mean poor completion rates and losses for individuals, employers, governments and other stakeholders. Recent changes in policy direction are attempting to address some of these issues and simultaneously increase interest and growth in the uptake of employment-based training. Any new models of employment-based training should address existing problems, as well as take into account the emerging needs of industry for skilled labour. The design of the models must also address an ageing workforce and allow flexible entry points for all age groups. Furthermore, future employment-based training models also need to keep pace with how work is organised in an environment characterised by increased competition, outsourcing, casualisation and an emphasis on specialisation and innovation. What is becoming apparent is the need for a compendium of models, rather than a 'one size fits all' approach
Hyperpolarized (3)He magnetic resonance imaging-derived pulmonary pressure-volume curves
We aimed to evaluate the potential for the use of hyperpolarized helium-3 magnetic resonance imaging (MRI) apparent diffusion coefficient (ADC) surrogates of alveolar size, together with literature-based morphological parameters in a theoretical model of lung mechanics to simulate noninvasive transpulmonary pressure-volume curves. Fourteen ex-smokers with chronic obstructive pulmonary disease (COPD) (n = 8 stage II, n = 6 stage III/IV COPD) and five age-matched never-smokers, provided written, informed consent and were evaluated at baseline and 26 + or - 2 mo later (n = 15 subjects) using plethysmography, spirometry, and (3)He MRI at 3.0 T. Total lung capacity, residual volume, and literature-based morphological parameters were used with alveolar volumes derived from (3)He ADC to simulate noninvasive pressure-volume curves. The resultant anterior-posterior transpulmonary pressure gradient was significantly decreased for stage II COPD (P \u3c 0.01) and stage III COPD subjects (P \u3c 0.001) compared with healthy volunteers. Both COPD subgroups showed increased alveolar radius compared with healthy subjects (P \u3c 0.01, stage II COPD; P \u3c 0.001, stage III COPD). In addition, surface area and surface tension were significantly increased in stage III COPD compared with healthy volunteers (P \u3c 0.01). These results suggest that (3)He MRI provides a potential noninvasive approach to evaluate lung mechanics regionally and further supports the use of ADC values as a regional noninvasive probe of pulmonary microstructure and compliance
Targeted pruning of a neuron's dendritic tree via femtosecond laser dendrotomy
Neurons are classified according to action potential firing in response to current injection. While such firing patterns are shaped by the composition and distribution of ion channels, modelling studies suggest that the geometry of dendritic branches also influences temporal firing patterns. Verifying this link is crucial to understanding how neurons transform their inputs to output but has so far been technically challenging. Here, we investigate branching-dependent firing by pruning the dendritic tree of pyramidal neurons. We use a focused ultrafast laser to achieve highly localized and minimally invasive cutting of dendrites, thus keeping the rest of the dendritic tree intact and the neuron functional. We verify successful dendrotomy via two-photon uncaging of neurotransmitters before and after dendrotomy at sites around the cut region and via biocytin staining. Our results show that significantly altering the dendritic arborisation, such as by severing the apical trunk, enhances excitability in layer V cortical pyramidal neurons as predicted by simulations. This method may be applied to the analysis of specific relationships between dendritic structure and neuronal function. The capacity to dynamically manipulate dendritic topology or isolate inputs from various dendritic domains can provide a fresh perspective on the roles they play in shaping neuronal outpu
Embedding of Genes Using Cancer Gene Expression Data: Biological Relevance and Potential Application on Biomarker Discovery
Artificial neural networks (ANNs) have been utilized for classification and prediction task with remarkable accuracy. However, its implications for unsupervised data mining using molecular data is under-explored. We found that embedding can extract biologically relevant information from The Cancer Genome Atlas (TCGA) gene expression dataset by learning a vector representation through gene co-occurrence. Ground truth relationship, such as cancer types of the input sample and semantic meaning of genes, were showed to retain in the resulting entity matrices. We also demonstrated the interpretability and usage of these matrices in shortlisting candidates from a long gene list as in the case of immunotherapy response. 73 related genes are singled out while the relatedness of 55 genes with immune checkpoint proteins (PD-1, PD-L1, and CTLA-4) are supported by literature. 16 novel genes (ACAP1, C11orf45, CD79B, CFP, CLIC2, CMPK2, CXCR2P1, CYTIP, FER, MCTO1, MMP25, RASGEF1B, SLFN12, TBC1D10C, TRAF3IP3, TTC39B) related to immune checkpoint proteins were identified. Thus, this method is feasible to mine big volume of biological data, and embedding would be a valuable tool to discover novel knowledge from omics data. The resulting embedding matrices mined from TCGA gene expression data are interactively explorable online (http://bit.ly/tcga-embedding-cancer) and could serve as an informative reference for gene relatedness in the context of cancer and is readily applicable to biomarker discovery of any molecular targeted therapy
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Tropical cyclone projections: changing climate threats for Pacific island defense installations
Potential changing climate threats in the tropical and subtropical North Pacific Ocean were assessed, using coupled ocean-atmosphere and atmosphere-only general circulation models, to explore their response to projected increasing greenhouse gas emissions. Tropical cyclone occurrence, described by frequency and intensity, near islands housing major U.S. defense installations was the primary focus. Four island regions-Guam and Kwajalein Atoll in the tropical northwestern Pacific, Okinawa in the subtropical northwestern Pacific, and Oahu in the tropical north-central Pacific-were considered, as they provide unique climate and geographical characteristics that either enhance or reduce the tropical cyclone risk. Guam experiences the most frequent and severe tropical cyclones, which often originate as weak systems close to the equator near Kwajalein and sometimes track far enough north to affect Okinawa, whereas intense storms are the least frequent around Oahu. From assessments of models that simulate well the tropical Pacific climate, it was determined that, with a projected warming climate, the number of tropical cyclones is likely to decrease for Guam and Kwajalein but remain about the same near Okinawa and Oahu; however, the maximum intensity of the strongest storms may increase in most regions. The likelihood of fewer but stronger storms will necessitate new localized assessments of the risk and vulnerabilities to tropical cyclones in the North Pacific
Autoregulation of the Escherichia coli melR promoter: repression involves four molecules of MelR
The Escherichia coli MelR protein is a transcription activator that autoregulates its own promoter by repressing transcription initiation. Optimal repression requires MelR binding to a site that overlaps the melR transcription start point and to upstream sites. In this work, we have investigated the different determinants needed for optimal repression and their spatial requirements. We show that repression requires a complex involving four DNA-bound MelR molecules, and that the global CRP regulator plays little or no role
Melioidosis in Birds and Burkholderia pseudomallei Dispersal, Australia
To the Editor: Melioidosis is an emerging infectious disease of humans and animals caused by the gram-negative bacterium Burkholderia pseudomallei, which inhabits soil and surface water in the disease-endemic regions of Southeast Asia and northern Australia (1). The aim of this study was to assess the potential for birds to spread B. pseudomallei. Birds are known carriers of various human pathogens, including influenza viruses, West Nile virus, Campylobacter jejuni, and antimicrobial drug–resistant Escherichia coli (2)
Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity
BACKGROUND: It is important to quantify the dose response for a drug in phase 2a clinical trials so the optimal doses can then be selected for subsequent late phase trials. In a phase 2a clinical trial of new lead drug being developed for the treatment of rheumatoid arthritis (RA), a U-shaped dose response curve was observed. In the light of this result further research was undertaken to design an efficient phase 2a proof of concept (PoC) trial for a follow-on compound using the lessons learnt from the lead compound.
METHODS: The planned analysis for the Phase 2a trial for GSK123456 was a Bayesian Emax model which assumes the dose-response relationship follows a monotonic sigmoid "S" shaped curve. This model was found to be suboptimal to model the U-shaped dose response observed in the data from this trial and alternatives approaches were needed to be considered for the next compound for which a Normal dynamic linear model (NDLM) is proposed. This paper compares the statistical properties of the Bayesian Emax model and NDLM model and both models are evaluated using simulation in the context of adaptive Phase 2a PoC design under a variety of assumed dose response curves: linear, Emax model, U-shaped model, and flat response.
RESULTS: It is shown that the NDLM method is flexible and can handle a wide variety of dose-responses, including monotonic and non-monotonic relationships. In comparison to the NDLM model the Emax model excelled with higher probability of selecting ED90 and smaller average sample size, when the true dose response followed Emax like curve. In addition, the type I error, probability of incorrectly concluding a drug may work when it does not, is inflated with the Bayesian NDLM model in all scenarios which would represent a development risk to pharmaceutical company. The bias, which is the difference between the estimated effect from the Emax and NDLM models and the simulated value, is comparable if the true dose response follows a placebo like curve, an Emax like curve, or log linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve.
CONCLUSIONS: In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response
Dapagliflozin Versus Placebo on Left Ventricular Remodeling in Patients With Diabetes and Heart Failure:The REFORM Trial
OBJECTIVE To determine the effects of dapagliflozin in patients with heart failure (HF) and type 2 diabetes mellitus (T2DM) on left ventricular (LV) remodeling using cardiac MRI.
RESEARCH DESIGN AND METHODS We randomized 56 patients with T2DM and HF with LV systolic dysfunction to dapagliflozin 10 mg daily or placebo for 1 year, on top of usual therapy. The primary end point was difference in LV end-systolic volume (LVESV) using cardiac MRI. Key secondary end points included other measures of LV remodeling and clinical and biochemical parameters.
RESULTS In our cohort, dapagliflozin had no effect on LVESV or any other parameter of LV remodeling. However, it reduced diastolic blood pressure and loop diuretic requirements while increasing hemoglobin, hematocrit, and ketone bodies. There was a trend toward lower weight.
CONCLUSIONS We were unable to determine with certainty whether dapagliflozin in patients with T2DM and HF had any effect on LV remodeling. Whether the benefits of dapagliflozin in HF are due to remodeling or other mechanisms remains unknown
Chemical Genetics Reveals an RGS/G-Protein Role in the Action of a Compound
We report here on a chemical genetic screen designed to address the mechanism of action of a small molecule. Small molecules that were active in models of urinary incontinence were tested on the nematode Caenorhabditis elegans, and the resulting phenotypes were used as readouts in a genetic screen to identify possible molecular targets. The mutations giving resistance to compound were found to affect members of the RGS protein/G-protein complex. Studies in mammalian systems confirmed that the small molecules inhibit muscarinic G-protein coupled receptor (GPCR) signaling involving G-αq (G-protein alpha subunit). Our studies suggest that the small molecules act at the level of the RGS/G-αq signaling complex, and define new mutations in both RGS and G-αq, including a unique hypo-adapation allele of G-αq. These findings suggest that therapeutics targeted to downstream components of GPCR signaling may be effective for treatment of diseases involving inappropriate receptor activation
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