932 resultados para Research data
Resumo:
Dual-energy X-ray absorptiometry (DXA) is a widely used method for measuring bone mineral in the growing skeleton. Because scan analysis in children offers a number of challenges, we compared DXA results using six analysis methods at the total proximal femur (PF) and five methods at the femoral neck (FN), In total we assessed 50 scans (25 boys, 25 girls) from two separate studies for cross-sectional differences in bone area, bone mineral content (BMC), and areal bone mineral density (aBMD) and for percentage change over the short term (8 months) and long term (7 years). At the proximal femur for the short-term longitudinal analysis, there was an approximate 3.5% greater change in bone area and BMC when the global region of interest (ROI) was allowed to increase in size between years as compared with when the global ROI was held constant. Trend analysis showed a significant (p < 0.05) difference between scan analysis methods for bone area and BMC across 7 years. At the femoral neck, cross-sectional analysis using a narrower (from default) ROI, without change in location, resulted in a 12.9 and 12.6% smaller bone area and BMC, respectively (both p < 0.001), Changes in FN area and BMC over 8 months were significantly greater (2.3 %, p < 0.05) using a narrower FN rather than the default ROI, Similarly, the 7-year longitudinal data revealed that differences between scan analysis methods were greatest when the narrower FN ROI was maintained across all years (p < 0.001), For aBMD there were no significant differences in group means between analysis methods at either the PF or FN, Our findings show the need to standardize the analysis of proximal femur DXA scans in growing children.
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OBJECTIVE: To describe variation in all cause and selected cause-specific mortality rates across Australia. METHODS: Mortality and population data for 1997 were obtained from the Australian Bureau of Statistics. All cause and selected cause-specific mortality rates were calculated and directly standardised to the 1997 Australian population in 5-year age groups. Selected major causes of death included cancer, coronary artery disease, cerebrovascular disease, diabetes, accidents and suicide. Rates are reported by statistical division, and State and Territory. RESULTS: All cause age-standardised mortality was 6.98 per 1000 in 1997 and this varied 2-fold from a low in the statistical division of Pilbara, Western Australia (5.78, 95% confidence interval 5.06-6.56), to a high in Northern Territory-excluding Darwin (11.30, 10.67-11.98). Similar mortality variation (all p<0.0001) exists for cancer (1.01-2.23 per 1000) and coronary artery disease (0.99-2.23 per 1000), the two biggest killers. Larger variation (all p<0.0001) exists for cerebrovascular disease (0.7-11.8 per 10,000), diabetes (0.7-6.9 per 10,000), accidents (1.7-7.2 per 10,000) and suicide (0.6-3.8 per 10,000). Less marked variation was observed when analysed by State and Territory. but Northern Territory consistently has the highest age-standardised mortality rates. CONCLUSIONS: Analysed by statistical division, substantial mortality gradients exist across Australia, suggesting an inequitable distribution of the determinants of health. Further research is required to better understand this heterogeneity.
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This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.
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We present a method of estimating HIV incidence rates in epidemic situations from data on age-specific prevalence and changes in the overall prevalence over time. The method is applied to women attending antenatal clinics in Hlabisa, a rural district of KwaZulu/Natal, South Africa, where transmission of HIV is overwhelmingly through heterosexual contact. A model which gives age-specific prevalence rates in the presence of a progressing epidemic is fitted to prevalence data for 1998 using maximum likelihood methods and used to derive the age-specific incidence. Error estimates are obtained using a Monte Carlo procedure. Although the method is quite general some simplifying assumptions are made concerning the form of the risk function and sensitivity analyses are performed to explore the importance of these assumptions. The analysis shows that in 1998 the annual incidence of infection per susceptible woman increased from 5.4 per cent (3.3-8.5 per cent; here and elsewhere ranges give 95 per cent confidence limits) at age 15 years to 24.5 per cent (20.6-29.1 per cent) at age 22 years and declined to 1.3 per cent (0.5-2.9 per cent) at age 50 years; standardized to a uniform age distribution, the overall incidence per susceptible woman aged 15 to 59 was 11.4 per cent (10.0-13.1 per cent); per women in the population it was 8.4 per cent (7.3-9.5 per cent). Standardized to the age distribution of the female population the average incidence per woman was 9.6 per cent (8.4-11.0 per cent); standardized to the age distribution of women attending antenatal clinics, it was 11.3 per cent (9.8-13.3 per cent). The estimated incidence depends on the values used for the epidemic growth rate and the AIDS related mortality. To ensure that, for this population, errors in these two parameters change the age specific estimates of the annual incidence by less than the standard deviation of the estimates of the age specific incidence, the AIDS related mortality should be known to within +/-50 per cent and the epidemic growth rate to within +/-25 per cent, both of which conditions are met. In the absence of cohort studies to measure the incidence of HIV infection directly, useful estimates of the age-specific incidence can be obtained from cross-sectional, age-specific prevalence data and repeat cross-sectional data on the overall prevalence of HIV infection. Several assumptions were made because of the lack of data but sensitivity analyses show that they are unlikely to affect the overall estimates significantly. These estimates are important in assessing the magnitude of the public health problem, for designing vaccine trials and for evaluating the impact of interventions. Copyright (C) 2001 John Wiley & Sons, Ltd.
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Background and Purpose - Unaccustomed strenuous physical exertion can trigger myocardial infarction, but little is known about the mechanisms precipitating subarachnoid hemorrhage (SAH). Methods - We identified all cases of first-ever SAH among the combined populations (2.8 million) of 4 urban centers in Australia and New Zealand. Information on the type, time, and intensity of exposures in the 26 hours before the onset of SAH was ascertained by structured interviews. We used the case-crossover technique to assess the risk of SAH associated with transient exposures of moderate to extreme physical exertion, heavy cigarette smoking, and binge alcohol consumption. Results - We registered 432 first-ever cases of SAH (62% women; mean age, 56.5 years). A definite time of onset of SAH was established for 393 patients (91%), and information on the levels of physical activity in the preceding 26 hours was obtained in 338 ( 78%). Of these patients, 19% engaged in moderate to extreme exertion (greater than or equal to5 metabolic equivalents) in the 2 hours before SAH, which was associated with a tripling in the risk of SAH (odds ratio [OR], 2.7; 95% CI, 1.6 to 4.6). There was no evidence of any association between heavy cigarette smoking or binge drinking and risk of SAH in the subsequent 2 hours ( OR, 1.1; 95% CI, 0.4 to 3.7; and OR, 0.41; 95% CI, -infinity to 5.3). Habitual exercise did not appear to alter the risk of SAH associated with moderate to extreme exertion. Conclusions - Moderate to extreme physical exertion tripled the risk of SAH, but there was no association between transient heavy smoking or binge drinking and risk of SAH. These data suggest that heavy physical activity may trigger SAH.
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There is a widely held paradigm that mangroves are critical for sustaining production in coastal fisheries through their role as important nursery areas for fisheries species. This paradigm frequently forms the basis for important management decisions on habitat conservation and restoration of mangroves and other coastal wetlands. This paper reviews the current status of the paradigm and synthesises the information on the processes underlying these potential links. In the past, the paradigm has been supported by studies identifying correlations between the areal and linear extent of mangroves and fisheries catch. This paper goes beyond the correlative approach to develop a new framework on which future evaluations can be based. First, the review identifies what type of marine animals are using mangroves and at what life stages. These species can be categorised as estuarine residents, marine-estuarine species and marine stragglers. The marine-estuarine category includes many commercial species that use mangrove habitats as nurseries. The second stage is to determine why these species are using mangroves as nurseries. The three main proposals are that mangroves provide a refuge from predators, high levels of nutrients and shelter from physical disturbances. The recognition of the important attributes of mangrove nurseries then allows an evaluation of how changes in mangroves will affect the associated fauna. Surprisingly few studies have addressed this question. Consequently, it is difficult to predict how changes in any of these mangrove attributes would affect the faunal communities within them and, ultimately, influence the fisheries associated with them. From the information available, it seems likely that reductions in mangrove habitat complexity would reduce the biodiversity and abundance of the associated fauna, and these changes have the potential to cause cascading effects at higher trophic levels with possible consequences for fisheries. Finally, there is a discussion of the data that are currently available on mangrove distribution and fisheries catch, the limitations of these data and how best to use the data to understand mangrove-fisheries links and, ultimately, to optimise habitat and fisheries management. Examples are drawn from two relatively data-rich regions, Moreton Bay (Australia) and Western Peninsular Malaysia, to illustrate the data needs and research requirements for investigating the mangrove-fisheries paradigm. Having reliable and accurate data at appropriate spatial and temporal scales is crucial for mangrove-fisheries investigations. Recommendations are made for improvements to data collection methods that would meet these important criteria. This review provides a framework on which to base future investigations of mangrove-fisheries links, based on an understanding of the underlying processes and the need for rigorous data collection. Without this information, the understanding of the relationship between mangroves and fisheries will remain limited. Future investigations of mangrove-fisheries links must take this into account in order to have a good ecological basis and to provide better information and understanding to both fisheries and conservation managers.
Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI
Resumo:
Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.
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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.
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Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.
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Mycosis fungoides (MF) and Sezary syndrome (SS), the major forms of cutaneous T-cell lymphoma, have unique characteristics that distinguish them from other types of non-Hodgkin`s lymphomas. Clinical trials in MF/SS have suffered from a lack of standardization in evaluation, staging, assessment, end points, and response criteria. Recently defined criteria for the diagnosis of early MF, guidelines for initial evaluation, and revised staging and classification criteria for MF and SS now offer the potential for uniform staging of patients enrolled in clinical trials for MF/SS. This article presents consensus recommendations for the general conduct of clinical trials of patients with MF/SS as well as methods for standardized assessment of potential disease manifestations in skin, lymph nodes, blood, and visceral organs, and definition of end points and response criteria. These guidelines should facilitate collaboration among investigators and collation of data from sponsor-generated or investigator-initiated clinical trials involving patients with MF or SS. J Clin Oncol 29:2598-2607. (C) 2011 by American Society of Clinical Oncology
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Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.
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Cancer/testis Antigens (CTAs) are immunogenic proteins with a restricted expression pattern in normal tissues and aberrant expression in different types of tumors being considered promising candidates for immunotherapy. We used the alignment between EST sequences and the human genome sequence to identify novel CT genes. By examining the EST tissue composition of known CT clusters we defined parameters for the selection of 1184 EST clusters corresponding to putative CT genes. The expression pattern of 70 CT gene candidates was evaluated by RT-PCR in 21 normal tissues, 17 tumor cell lines and 160 primary tumors. We were able to identify 4 CT genes expressed in different types of tumors. The presence of antibodies against the protein encoded by 1 of these 4 CT genes (FAM46D) was exclusively detected in plasma samples from cancer patients. Due to its restricted expression pattern and immunogenicity FAM46D represents a novel target for cancer immunotherapy. (c) 2009 Elsevier Inc. All rights reserved.
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Study Design: Data mining of single nucleotide polymorphisms (SNPs) in gene pathways related to spinal cord injury (SCI). Objectives: To identify gene polymorphisms putatively implicated with neuronal damage evolution pathways, potentially useful to SCI study. Setting: Departments of Psychiatry and Orthopedics, Faculdade de Medicina, Universidade de Sao Paulo, Brazil. Methods: Genes involved with processes related to SCI, such as apoptosis, inflammatory response, axonogenesis, peripheral nervous system development and axon ensheathment, were determined by evaluating the `Biological Process` annotation of Gene Ontology (GO). Each gene of these pathways was mapped using MapViewer, and gene coordinates were used to identify their polymorphisms in the SNP database. As a proof of concept, the frequency of subset of SNPs, located in four genes (ALOX12, APOE, BDNF and NINJ1) was evaluated in the DNA of a group of 28 SCI patients and 38 individuals with no SC lesions. Results: We could identify a total of 95 276 SNPs in a set of 588 genes associated with the selected GO terms, including 3912 nucleotide alterations located in coding regions of genes. The five non-synonymous SNPs genotyped in our small group of patients, showed a significant frequency, reinforcing their potential use for the investigation of SCI evolution. Conclusion: Despite the importance of SNPs in many aspects of gene expression and protein activity, these gene alterations have not been explored in SCI research. Here we describe a set of potentially useful SNPs, some of which could underlie the genetic mechanisms involved in the post trauma spinal cord damage.
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The mortality and morbidity caused by alcohol, tobacco and illicit drug misuse represents a significant public health burden (Ezzati et al., 2002). A key part of the public health response is the collection of epidemiological and social science data to define at-risk populations to identify opportunities for intervention and to evaluate the effectiveness of policies in preventing or treating drug misuse and drug-related harm. The systematic use of epidemiological and social science research methods to study illicit drug use is barely 40 years old in the United States and United Kingdom, which have pioneered this approach. Because of the sensitive nature of epidemiological research on illicit drug use a unique set of ethical challenges need to be explicitly addressed by the field. Although ethics guidelines have been proposed (Council for International Organizations of Medical Sciences, 1991), scholarship on the ethics of epidemiology is scant, and consensus on core values not yet achieved (Coughlin, 2000).
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P>The determination of normal parameters is an important procedure in the evaluation of the stomatognathic system. We used the surface electromyography standardization protocol described by Ferrario et al. (J Oral Rehabil. 2000;27:33-40, 2006;33:341) to determine reference values of the electromyographic standardized indices for the assessment of muscular symmetry (left and right side, percentage overlapping coefficient, POC), potential lateral displacing components (unbalanced contractile activities of contralateral masseter and temporalis muscles, TC), relative activity (most prevalent pair of masticatory muscles, ATTIV) and total activity (integrated areas of the electromyographic potentials over time, IMPACT) in healthy Brazilian young adults, and the relevant data reproducibility. Electromyography of the right and left masseter and temporalis muscles was performed during maximum teeth clenching in 20 healthy subjects (10 women and 10 men, mean age 23 years, s.d. 3), free from periodontal problems, temporomandibular disorders, oro-facial myofunctional disorder, and with full permanent dentition (28 teeth at least). Data reproducibility was computed for 75% of the sample. The values obtained were POC Temporal (88 center dot 11 +/- 1 center dot 45%), POC masseter (87 center dot 11 +/- 1 center dot 60%), TC (8 center dot 79 +/- 1 center dot 20%), ATTIV (-0 center dot 33 +/- 9 center dot 65%) and IMPACT (110 center dot 40 +/- 23 center dot 69 mu V/mu V center dot s %). There were no statistical differences between test and retest values (P > 0 center dot 05). The Technical Errors of Measurement (TEM) for 50% of subjects assessed during the same session were 1 center dot 5, 1 center dot 39, 1 center dot 06, 3 center dot 83 and 10 center dot 04. For 25% of the subjects assessed after a 6-month interval, the TEM were 0 center dot 80, 1 center dot 03, 0 center dot 73, 12 center dot 70 and 19 center dot 10. For all indices, there was good reproducibility. These electromyographic indices could be used in the assessment of patients with stomatognathic dysfunction.