991 resultados para Rydelius, Andreas, 1671-1738.
Comparison of causality analysis on simultaneously measured fMRI and NIRS signals during motor tasks
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Breast cancer is a common disease in both developing and developed countries with early identification and treatment improving prognosis and survival. Heparan sulfate proteoglycans (HSPGs) are key components of the extracellular matrix (ECM) that mediate cell adhesion, motility, proliferation, invasion and cell signalling. Members of the syndecan family of HSPGs have been identified to be involved in breast cancer progression through their varied interactions with a number of growth factors, ligands and receptors. Specifically, high expression levels of syndecan-1 (SDC1) have been demonstrated in more invasive breast tumours while elevated syndecan-4 (SDC4) levels have been identified to correspond with improved prognosis. With genetic changes in the syndecans and their association with breast cancers plausible, we examined two single nucleotide polymorphisms in SDC1 (rs1131351) and SDC4 (rs67068737) within an Australian Caucasian breast cancer case/control population. No association was found with SDC4 and breast cancer in our population. However, a significant association between SDC1 and breast cancer was identified in both our case/control population and in a replication cohort. When both populations were combined for analysis, this association became more significant (genotype, p = 0.0003; allele, p = 0.0001). This data suggests an increased risk of developing breast cancer associated with the presence of the C allele of the SDC1 rs1131351 single nucleotide polymorphism (SNP) and may provide a marker toward early breast cancer detection.
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Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.
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Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows implementation onboard an Autonomous Underwater Vehicle for improving navigation and obstacle avoidance performance.
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Ovarian cancer is the most common cause of gynaecological cancer death, with an overall 5-year relative survival of 43%. Impaired physical wellbeing and overall quality of life (QoL) represent major concerns for women during and following ovarian cancer treatment, predict survival and are amenable to change through interventions. Exercise, now considered an important part of overall management of a number of cancers, improves short-term outcomes (e.g., function, fatigue, QoL) during chemotherapy...
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Objective Women treated for endometrial cancer currently commonly attend clinic-based follow-up examinations for up to five years. This is based on little evidence and alternative models need to be investigated. This study aimed to identify currently available symptom checklists, determine the comprehensiveness of identified checklists, and generate an updated list of symptoms potentially associated with a recurrence of endometrial cancer for future testing within a prospective study. Methods/materials We conducted a systematic review of the literature extracting; routine follow-up schedules; proportion of patients with symptomatic or asymptomatic recurrence; symptoms of recurrence; prevalence of these symptoms at recurrence. Results Overall, three previous checklists, and 12 retrospective studies were identified meeting the selection criteria. The average rate of recurrence across the studies was 13% (range 3%-19%). The proportion of patients identified with a symptomatic recurrence varied widely (overall average 67%;range 41% to 91%). The most commonly reported symptoms were vaginal bleeding (25%), pain [not further described] (16%) and abdominal pain and/or discomfort and swelling (15%) which combined, represented 56% of the total reported symptoms. The three previous checklists listed 14 and this review identified an additional 24 symptoms (e.g. vaginal discharge, leg pain, constipation, headache and self-detected mass) not previously identified. Conclusion The newly developed symptom checklist expands previous ones, by an additional 24 symptoms. It will be used in a prospective cohort study to assess whether it is sensitive and specific enough to identify recurrence compared to current standard follow-up examinations.
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Human half-lives of PentaBDE congeners have been estimated from the decline in serum concentrations measured over a 6-12 month period for a population of exchange students moving from North America to Australia. Australian serum PBDE concentrations are typically between 5 -10 times lower than in North America and we can therefore hypothesize that if the biological half-life is sufficiently short we would observe a decline in serum concentration with length of residence in Australia. Thirty students were recruited over a period of 3 years from whom serum were archived every 2 months during their stay in Australia. Australian residents (n=22) were also sampled longitudinally to estimate general population background levels. All serum samples were analyzed by gas chromatography high resolution mass spectrometry. Key findings confirmed that BDE-47 concentrations in the Australians (median 2.3;
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Drawing upon an action learning perspective, we hypothesized that a leader’s learning of project leadership skills would be related to facilitative leadership, team reflexivity, and team performance. Secondly, we proposed that new and experienced leaders would differ in the amount they learn from their current and recent experience as project managers, and in the strength of the relationship between their self-reported learning, facilitative leadership, and team reflexivity. We conducted a 1-year longitudinal study of 50 R&D teams, led by 25 new and 25 experienced leaders, with 313 team members and 22 project customers, collecting both quantitative and qualitative data. We found evidence of a significant impact of the leader’s learning on subsequent facilitative leadership and team performance 8 and 12 months later, suggesting a lag between learning leadership skills and translating these skills into leadership behavior. The findings contribute to an understanding of how leaders consolidate their learned experience into facilitative leadership behavior.
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Background The Lymphoedema Evaluation in Gynecological cancer Study (LEGS) was a longitudinal, observational, cohort study prospectively evaluating the incidence and risk factors of lower-limb lymphedema after treatment for gynecological cancer. Here we describe the study protocol and characteristics of the sample. Methods Women with a newly diagnosed gynecological cancer between June 1, 2008 and February 28, 2011, aged 18 years or older, and treated at one of six hospitals in Queensland, Australia, were eligible. Lymphedema was assessed by circumference measurements, bioimpedance spectroscopy, and self-reported swelling. LEGS incorporated a cohort of patients requiring surgery for benign gynecological conditions for comparison purposes. Data were collected prior to surgery and at regular intervals thereafter up to 2-years post-diagnosis. Results 546 women participated (408 cancer, 138 benign), with a 24-month retention rate of 78%. Clinical and treatment characteristics of participants were similar to the Queensland gynecological cancer population, except for a higher proportion of early-stage cervical cancers recruited to LEGS compared with Queensland proportions (89% versus 55%, respectively). Discussion Few imbalances were observed between participants with complete and incomplete follow-up data. The prospective design and collection of objective and patient-reported outcome data will allow comprehensive assessment of incidence and risk factors of lower-limb lymphedema.
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Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.
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Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
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Exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse health outcomes. Concentrations of urinary PAH metabolites (OH-PAHs) provide an integrated measure of human exposure to PAHs but measurement of urinary OH-PAHs has not been done in Australia and rarely in Vietnam, where air pollution is of concern. In this study, we assessed exposure to PAHs in 16 participants living in Brisbane, Australia and Hanoi, Vietnam, with 4 participants travelling between the two cities during the monitoring period. A total of 312 first morning urine samples were collected over 10 weeks and were analysed for nine OH-PAHs. Concentrations of the urinary OH-PAHs were 2–10 times higher in participants from Hanoi than those from Brisbane. For example, the median concentrations of 1-hydroxypyrene were 292 pg/mL in Hanoi, compared to 64 pg/mL in Brisbane. For participants travelling from Brisbane to Hanoi and back, differences in exposure to PAHs in these two cities resulted in corresponding changes of urinary OH-PAH concentrations, demonstrating that the more polluted environment in Hanoi was likely the source for higher PAH exposure there.