166 resultados para medically supervised injectable maintenance clinic


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Background Injury is the leading cause of adolescent death and injury around the road is a common source of adolescent injuries. Skills for Preventing Injury in Youth (SPIY) is a comprehensive program developed in Australia for early adolescents (term-long curriculum, including looking out for friends, first-aid training coupled with teacher school-connectedness professional development). Jessors’ Protection-Risk Framework guided the program approach focusing on building protective relationships. Method A randomized controlled trial with 35 schools was undertaken. Students completed surveys at baseline, six-months post-intervention and twelve-months post intervention. There were 1686 students (56% female) who completed the twelve-month survey, including the Extended-Adolescent Injury Checklist whereby students self-report on medically-treated injuries over the previous three-months (only road-related items are reported in this study; cycling, motorcycle riding, pedestrian, and riding as a passenger). Randomly selected SPIY classes also participated in focus groups and reported on perceptions of SPIY and injury risk behavior. Results As a check of randomization baseline differences of the variables were examined, with no significant differences between intervention and control groups. At the 12-month follow-up, there were fewer medically-treated injuries among the intervention students compared with the control group, particularly associated with being a passenger. The process evaluation revealed students perceived change in injury risk and risk behaviors. Conclusions While data analyses are continuing, the results indicate that the program seeking to encourage adolescents to look out for their friends, build connections to school and provide first aid skills training goes some way to reducing self-reported medically-treated injuries around the road.

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Next-generation sequencing techniques have revolutionized over the last decade providing researchers with low cost, high-throughput alternatives compared to the traditional Sanger sequencing methods. These sequencing techniques have rapidly evolved from first-generation to fourth-generation with very broad applications such as unravelling the complexity of the genome, in terms of genetic variations, and having a high impact on the biological field. In this review, we discuss the transition of sequencing from the second-generation to the third- and fourth-generations, and describe some of their novel biological applications. With the advancement in technology, the earlier challenges of minimal size of the instrument, flexibility of throughput, ease of data analysis and short run times are being addressed. However, the need for prospective analysis and effectiveness to test whether the knowledge of any given new variants identified has an effect on clinical outcome may need improvement.

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Mutations within BRCA1 predispose carriers to a high risk of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through the assembly of multiple protein complexes involved in DNA repair, cell-cycle arrest, and transcriptional regulation. Here, we report the identification of a DNA damage-induced BRCA1 protein complex containing BCLAF1 and other key components of the mRNA-splicing machinery. In response to DNA damage, this complex regulates pre-mRNA splicing of a number of genes involved in DNA damage signaling and repair, thereby promoting the stability of these transcripts/proteins. Further, we show that abrogation of this complex results in sensitivity to DNA damage, defective DNA repair, and genomic instability. Interestingly, mutations in a number of proteins found within this complex have been identified in numerous cancer types. These data suggest that regulation of splicing by the BRCA1-mRNA splicing complex plays an important role in the cellular response to DNA damage.

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There are limited community-based data on the burden of influenza and influenza-like illnesses during pregnancy to inform disease surveillance and control. We aimed to determine the incidence of medically-attended respiratory illnesses (MARI) in pregnant women and the proportion of women who are tested for respiratory pathogens at these visits. We conducted a nested retrospective cohort study of a non-random sample of women aged ≥18 years who had a live birth in maternity units in Brisbane, Queensland, from March 2012 to October 2014. The primary outcomes were self-reported doctor visits for MARI and laboratory investigations for respiratory pathogens. Descriptive analyses were performed. Among 1202 participants, 222 (18.5%, 95%CI 16.3%-20.7%) self-reported MARI during their pregnancy. Of those with an MARI, 20.3% (45/222) self-reported a laboratory test was performed. We were able to confirm with health service providers that 46.7% (21/45) of tests were undertaken, responses from providers were not received for the remainder. Whilst one in five women in this population reported a MARI in pregnancy, only 3.7% (45/1202) reported a clinical specimen had been arranged at the consultation and the ability to validate that self-report was problematic. As the focus on maternal immunisation increases, ascertainment of the aetiological agent causing MARI in this population will be required and efficient and reliable methods for obtaining those data at the community level need to be established.

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In the coming decades the design, construction and maintenance of roads will face a range of new issues and as such will require a number of new approaches. In particular, road authorities will be required to consider and respond to a range of issues related to climate change, and associated extreme weather events, such as the extensive flooding in January 2011 in Queensland, Australia Figure 1). Coupled with diminishing access to road construction supplies (such as aggregate), water scarcity, and the potential for increases in oil and electricity prices, this range of challenges bear little resemblance to those previously faced. In Australia, state and federal authorities face further pressures given the variety of needs resulting from the country's geographical and population diversity, expansive road networks, road freight requirements and relatively small population base.

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Genome maintenance (GM) is an essential defense system against aging and cancer, as both are characterized by increased genome instability. Here, we compared the copy number variation and mutation rate of 518 GM-associated genes in the naked mole rat (NMR), mouse, and human genomes. GM genes appeared to be strongly conserved, with copy number variation in only four genes. Interestingly, we found NMR to have a higher copy number of CEBPG, a regulator of DNA repair, and TINF2, a protector of telomere integrity. NMR, as well as human, was also found to have a lower rate of germline nucleotide substitution than the mouse. Together, the data suggest that the long-lived NMR, as well as human, has more robust GM than mouse and identifies new targets for the analysis of the exceptional longevity of the NMR.

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Background Formalised predialysis care has been shown to extend the wellness of individuals with advanced chronic kidney disease, slow disease progression and increase the uptake of home dialysis. Predialysis care, incorporating multidisciplinary input is also vital in delaying the onset of end-stage kidney disease and reducing hospital admissions; thereby decreasing financial demands on health budgets. Predialysis care should include comprehensive information provision and predialysis education. This empowers patients to choose self-care strategies and therapies.

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Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

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Background: Smoking cessation interventions delivered by dental practitioners can be as effective as those delivered by general medical practitioners. However, concern that addressing smoking may cause offence to their patients is a reason cited by dental practitioners for not regularly addressing patient smoking behaviours, despite believing they should play a role in smoking cessation. This study aimed to elicit the smoking behaviour and smoking cessation preferences of dental patients to determine if these concerns accurately reflect patient attitudes. Methods: We surveyed 726 adult dental patients attending the University of Queensland’s School of Dentistry Dental Clinics, Brisbane Dental Hospital, and four private dental practices in South East Queensland. Results: Most (80%) current daily smokers had tried to quit smoking. Smokers and non-smokers both agreed that dentists should screen for smoking behaviour and are qualified to offer smoking cessation advice (99% and 96% respectively). Almost all participants (96%) said they would be comfortable with their dentist asking about their smoking and that if their smoking was affecting their oral health their dentist should advise them to quit. Conclusions: Patients are receptive to dental practitioners inquiring about smoking behaviour and offering advice on quitting. Smoking patients showed considerable motivation and interest in quitting smoking, particularly in the context of health problems related to smoking being identified. These results should encourage dentists to raise the issue with their patients.

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Circulating tumor cells (CTCs) are the seeds for cancer metastases development, which is responsible for >90% of cancer-related deaths. Accurate quantification of CTCs in human fluids could be an invaluable tool for understanding cancer prognosis, delivering personalized medicine to prevent metastasis and finding cancer therapy effectiveness. Although CTCs were first discovered more than 200 years ago, until now it has been a nightmare for clinical practitioners to capture and diagnose CTCs in clinical settings. Our society needs rapid, sensitive, and reliable assays to identify the CTCs from blood in order to help save millions of lives. Due to the phenotypic EMT transition, CTCs are undetected for more than one-third of metastatic breast cancer patients in clinics. To tackle the above challenges, the first volume in “Circulating Tumor Cells (CTCs): Detection Methods, Health Impact and Emerging Clinical Challenges discusses recent developments of different technologies, which have the capability to target and elucidate the phenotype heterogenity of CTCS. It contains seven chapters written by world leaders in this area, covering basic science to possible device design which can have beneficial applications in society. This book is unique in its design and content, providing an in-depth analysis to elucidate biological mechanisms of cancer disease progression, CTC detection challenges, possible health effects and the latest research on evolving technologies which have the capability to tackle the above challenges. It describes the broad range of coverage on understanding CTCs biology from early predictors of the metastatic spread of cancer, new promising technology for CTC separation and detection in clinical environment and monitoring therapy efficacy via finding the heterogeneous nature of CTCs. (Imprint: Nova Biomedical)

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Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

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A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

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While dehydration is common in older patients and is associated with poor outcomes, it has been infrequently studied in the hospital setting. Thus, the aim of this study was to identify potential barriers and enablers to the maintenance of adequate hydration in older patients in an acute hospital environment. An observational study, involving patients aged 60 years and older admitted to an acute care hospital in Queensland, Australia, was undertaken. Forty-four patients were observed during mealtimes, and chart and room audits were performed to identify hydration management strategies, weight records and the presence or absence of fluid balance charts. Results revealed a number of system and practice-related barriers including patient difficulties with opening fluid containers and low levels of documentation of hydration management strategies. Addressing these issues is an important first step towards improving the management of hydration in medically ill older hospital patients.

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Introduction: Major Depressive Disorder (MDD) has high prevalence among adolescents and young adults. Evidence of any effective treatments is limited. Exercise as an effective treatment for adults has some support but studies in younger populations are lacking. Therefore the aim of this study was to investigate the feasibility and preliminary efficacy of brief motivational interviewing (MI) plus 12-weeks exercise training as a treatment for MDD in youth...

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Objectives To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. Patients and Methods Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. Results In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. Conclusion These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.