345 resultados para Multiple routes


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Background Single nucleotide polymorphisms (SNPs) rs429358 (ε4) and rs7412 (ε2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently. Methods We genotyped 12 740 subjects hitherto not studied for their APOE status, imputed raw genotype data from 8739 subjects from five independent genome wide association studies datasets using the most recent high-resolution reference panels, and extracted genotype data for 8265 subjects from previous candidate gene assessments. Results Despite sufficient power to detect associations at genome-wide significance thresholds across a range of ORs, our analyses did not support a role of rs429358 or rs7412 on MS susceptibility. This included meta-analyses of the combined data across 13 913 MS cases and 15 831 controls (OR=0.95, p=0.259, and OR 1.07, p=0.0569, for rs429358 and rs7412, respectively). Conclusion Given the large sample size of our analyses, it is unlikely that the two APOE missense SNPs studied here exert any relevant effects on MS susceptibility.

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Human leucocyte antigen (HLA)-DRB1*1501 and other class II alleles influence susceptibility to multiple sclerosis (MS), but their contribution if any to the clinical course of MS remains uncertain. Here, we have investigated DRB1 alleles in a large sample of 1230 Australian MS cases, with some enrichment for subjects with primary progressive (PPMS) disease (n = 246) and 1210 healthy controls. Using logistic regression, we found that DRB1*1501 was strongly associated with risk (P = 7 x 10-45), as expected, and after adjusting for DRB1*1501, a predisposing effect was also observed for DRB1*03 (P = 5 x 10-7). Individuals homozygous for either DRB1*15 or DRB1*03 were considerably more at risk of MS than heterozygotes and non-carriers. Both the DRB1*04 and the DRB1*01/DRB1*15 genotype combination, respectively, protected against PPMS in comparison to subjects with relapsing disease. Together, these data provide further evidence of heterogeneity at the DRB1 locus and confirm the importance of HLA variants in the phenotypic expression of MS.

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The study described in this article aimed to identify issues relating to incontinence and assess the impact of referral to a continence adviser on the lives of people with multiple sclerosis (MS). The study design used an in-depth, two-phase anonymous mail survey within a general community as nominated by the participants. Fifty-six people participated in phase 1 and eleven people completed phase 2. The results indicated that incontinence is a problem for the vast majority of participants — people with MS. One-third of the eligible participants took up the option of a consultation, assessment and treatment from a continence nurse. Reasons for not taking up the visit from the continence nurse included ‘managing OK’, ‘didn’t think it would help’, ‘embarrassed’ and ‘too busy’. Increasing awareness of urinary incontinence in the community is important and education needs to focus on at-risk groups in presenting the range of options available to assist people experiencing incontinence.

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Rationale Developing models to efficiently explore the mechanisms by which stress can mediate reinstatement of drug-seeking behavior is crucial to the development of new pharmacotherapies for alcohol use disorders. Objectives We examined the effects of multiple reinstatement sessions using the pharmacological stressor, yohimbine, in ethanol- and sucrose-seeking rats in order to develop a more efficient model of stress-induced reinstatement. Methods Long–Evans rats were trained to self-administer 10% ethanol with a sucrose-fading procedure, 20% ethanol without a sucrose-fading procedure, or 5% sucrose in 30-min operant self-administration sessions, followed by extinction training. After reaching extinction criteria, the animals were tested once per week with yohimbine vehicle and yohimbine (2 mg/kg), respectively, 30 min prior to the reinstatement sessions or blood collection. Levels of reinstatement and plasma corticosterone (CORT) were determined each week for four consecutive weeks. Results Yohimbine induced reinstatement of ethanol- and sucrose-seeking in each of the 4 weeks. Interestingly, the magnitude of the reinstatement decreased for the 10% ethanol group after the first reinstatement session but remained stable for the 20% ethanol group trained without sucrose. Plasma CORT levels in response to injection of both vehicle and yohimbine were significantly higher in the ethanol-trained animals compared to sucrose controls. Conclusions The stable reinstatement in the 20% ethanol group supports the use of this training procedure in studies using within-subject designs with multiple yohimbine reinstatement test sessions. Additionally, these results indicate that the hormonal response to stressors can be altered following extinction from self-administration of relatively modest amounts of ethanol.

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Extrapulmonary small cell and small cell neuroendocrine tumors of unknown primary site are, in general, aggressive neoplasms with a short median survival. Like small cell lung cancer (SCLC), they often are responsive to chemotherapy and radiotherapy. Small cell lung cancer and well differentiated neuroendocrine carcinomas of the gastrointestinal tract and pancreas tend to express somatostatin receptors. These tumors may be localized in patients by scintigraphic imaging using radiolabeled somatostatin analogues. A patient with an anaplastic neuroendocrine small cell tumor arising on a background of multiple endocrine neoplasia type 1 syndrome is reported. The patient had a known large pancreatic gastrinoma and previously treated parathyroid adenopathy. At presentation, there was small cell cancer throughout the liver and skeleton. Imaging with a radiolabeled somatostatin analogue, 111In- pentetreotide (Mallinckrodt Medical B. V., Petten, Holland), revealed all sites of disease detected by routine biochemical and radiologic methods. After six cycles of chemotherapy with doxorubicin, cyclophosphamide, and etoposide, there was almost complete clearance of the metastatic disease. 111In-pentetreotide scintigraphy revealed uptake consistent with small areas of residual disease in the liver, the abdomen (in mesenteric lymph nodes), and posterior thorax (in a rib). The primary gastrinoma present before the onset of the anaplastic small cell cancer showed no evidence of response to the treatment. The patient remained well for 1 year and then relapsed with brain, lung, liver, and skeletal metastases. Despite an initial response to salvage radiotherapy and chemotherapy with carboplatin and dacarbazine, the patient died 6 months later.

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This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.

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Background The expansion of cell colonies is driven by a delicate balance of several mechanisms including cell motility, cell-to-cell adhesion and cell proliferation. New approaches that can be used to independently identify and quantify the role of each mechanism will help us understand how each mechanism contributes to the expansion process. Standard mathematical modelling approaches to describe such cell colony expansion typically neglect cell-to-cell adhesion, despite the fact that cell-to-cell adhesion is thought to play an important role. Results We use a combined experimental and mathematical modelling approach to determine the cell diffusivity, D, cell-to-cell adhesion strength, q, and cell proliferation rate, ?, in an expanding colony of MM127 melanoma cells. Using a circular barrier assay, we extract several types of experimental data and use a mathematical model to independently estimate D, q and ?. In our first set of experiments, we suppress cell proliferation and analyse three different types of data to estimate D and q. We find that standard types of data, such as the area enclosed by the leading edge of the expanding colony and more detailed cell density profiles throughout the expanding colony, does not provide sufficient information to uniquely identify D and q. We find that additional data relating to the degree of cell-to-cell clustering is required to provide independent estimates of q, and in turn D. In our second set of experiments, where proliferation is not suppressed, we use data describing temporal changes in cell density to determine the cell proliferation rate. In summary, we find that our experiments are best described using the range D = 161 - 243 ?m2 hour-1, q = 0.3 - 0.5 (low to moderate strength) and ? = 0.0305 - 0.0398 hour-1, and with these parameters we can accurately predict the temporal variations in the spatial extent and cell density profile throughout the expanding melanoma cell colony. Conclusions Our systematic approach to identify the cell diffusivity, cell-to-cell adhesion strength and cell proliferation rate highlights the importance of integrating multiple types of data to accurately quantify the factors influencing the spatial expansion of melanoma cell colonies.

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Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

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This thesis investigates condition monitoring (CM) of diesel engines using acoustic emission (AE) techniques. The AE signals recorded from a small size diesel engine are mixtures of multiple sources from multiple cylinders. Thus, it is difficult to interpret the information conveyed in the signals for CM purposes. This thesis develops a series of practical signal processing techniques to overcome this problem. Various experimental studies conducted to assess the CM capabilities of AE analysis for diesel engines. A series of modified signal processing techniques were proposed. These techniques showed promising results of capability for CM of multiple cylinders diesel engine using multiple AE sensors.

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OBJECTIVE To compare different reliability coefficients (exact agreement, and variations of the kappa (generalised, Cohen's and Prevalence Adjusted and Biased Adjusted (PABAK))) for four physiotherapists conducting visual assessments of scapulae. DESIGN Inter-therapist reliability study. SETTING Research laboratory. PARTICIPANTS 30 individuals with no history of neck or shoulder pain were recruited with no obvious significant postural abnormalities. MAIN OUTCOME MEASURES Ratings of scapular posture were recorded in multiple biomechanical planes under four test conditions (at rest, and while under three isometric conditions) by four physiotherapists. RESULTS The magnitude of discrepancy between the two therapist pairs was 0.04 to 0.76 for Cohen's kappa, and 0.00 to 0.86 for PABAK. In comparison, the generalised kappa provided a score between the two paired kappa coefficients. The difference between mean generalised kappa coefficients and mean Cohen's kappa (0.02) and between mean generalised kappa and PABAK (0.02) were negligible, but the magnitude of difference between the generalised kappa and paired kappa within each plane and condition was substantial; 0.02 to 0.57 for Cohen's kappa and 0.02 to 0.63 for PABAK, respectively. CONCLUSIONS Calculating coefficients for therapist pairs alone may result in inconsistent findings. In contrast, the generalised kappa provided a coefficient close to the mean of the paired kappa coefficients. These findings support an assertion that generalised kappa may lead to a better representation of reliability between three or more raters and that reliability studies only calculating agreement between two raters should be interpreted with caution. However, generalised kappa may mask more extreme cases of agreement (or disagreement) that paired comparisons may reveal.

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A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

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Welcome to the Teacher evidence matrix. This matrix is designed for highly qualified discipline experts to evaluate their teaching in a systematic manner. The primary purpose of the Teacher evidence matrix is to provide a tool that an academic staff member at university can annually review their teaching. The annual review will result in you being ready for performance, planning and review; promotion; awards; or employment application. This tool is designed for individual use and will lead to an action plan for implementation.

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This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

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A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.