999 resultados para distance dependence
Resumo:
Until recently, the low-abundance (LA) range of the serum proteome was an unexplored reservoir of diagnostic information. Today it is increasingly appreciated that a diagnostic goldmine of LA biomarkers resides in the blood stream in complexed association with more abundant higher molecular weight carrier proteins such as albumin and immunoglobulins. As we now look to the possibility of harvesting these LA biomarkers more efficiently through engineered nano-scale particles, mathematical approaches are needed in order to reveal the mechanisms by which blood carrier proteins act as molecular 'mops' for LA diagnostic cargo, and the functional relationships between bound LA biomarker concentrations and other variables of interest such as biomarker intravasation and clearance rates and protein half-lives in the bloodstream. Here we show, by simple mathematical modeling, how the relative abundance of large carrier proteins and their longer half-lives in the bloodstream work together to amplify the total blood concentration of these tiny biomarkers. The analysis further suggests that alterations in the production of biomarkers lead to gradual rather than immediate changes in biomarker levels in the blood circulation. The model analysis also points to the characteristics of artificial nano-particles that would render them more efficient harvesters of tumor biomarkers in the circulation, opening up possibilities for the early detection of curable disease, rather than simply better detection of advanced disease.
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Using a multiple plasma deposition-annealing (MDA) technique, we have fabricated an Au nanoisland-based thin film nanoresistor with a very low temperature coefficient of electrical resistivity in a cryogenic-to-room temperature range of 10 to 300 K. The nanoislanded gold film was deposited on a SiO2/Si wafer (500 nm SiO2 thickness) between two 300 nm thick Au electrodes which were separated by 100 m. A sophisticated selection of the thickness of the nanoislanded gold film, the annealing temperature, as well as the number of deposition/annealing cycles resulted in the fabrication of a nanoresistor with a temperature coefficient of electrical resistivity of 2.1 × 10-3 K-1 and the resistivity deviation not exceeding 2% in a cryogenic-to-room temperature range. We have found that the constant resistivity regime of the nanoisland-based thin film nanoresistor corresponds to a minimized nanoisland activation energy (approximately 0.3 meV). This energy can be minimized by reducing the nearest neighbor distance and increasing the size of the Au nanoislands in the optimized nanoresistor structure. It is shown that the constant resistivity nanoresistor operates in the regime where the thermally activated electron tunneling is compensated by the negative temperature dependence of the metallic-type conductivity of nanoislands. Our results are relevant to the development of commercially viable methods of nanoresistor production for various nanoelectronics-based devices. The proposed MDA technique also provides the opportunity to fabricate large arrays of metallic nanoparticles with controllable size, shapes and inter-nanoparticle gaps.
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The possibility to control the electric resistivity-temperature dependence of the nanosized resistive components made using hierarchical multilevel arrays of self-assembled gold nanoparticles prepared by multiple deposition/annealing is demonstrated. It is experimentally shown that the hierarchical three-level patterns, where the nanoparticles of sizes ranging from several nanometers to several tens of nanometer play a competitive roles in the electric conductivity, demonstrate sharp changes in the activation energy. These patterns can be used for the precise tuning of the resistivity-temperature behavior of nanoelectronic components.
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Aims The functional BDNF single nucleotide polymorphism (SNP) rs6265 has been associated with many disorders including schizophrenia and alcohol dependence. However, studies have been inconsistent, reporting both positive and negative associations. Comorbid alcohol dependence has a high prevalence in schizophrenia so we investigated the role of rs6265 in alcohol dependence in Australian populations of schizophrenia and alcohol dependent patients. Methods Two BDNF SNPs rs6265 and a nearby SNP rs7103411 were genotyped in a total of 848 individuals. These included a schizophrenia group (n = 157) and a second schizophrenia replication group (n = 235), an alcohol dependent group (n = 231) that had no schizophrenia diagnosis and a group of healthy controls (n = 225). Results Allelic association between rs7103411 and comorbid alcohol dependence was identified (P = 0.044) in the primary schizophrenia sample. In the replication study, we were able to detect allelic associations between both BDNF SNPs and comorbid alcohol dependence (rs6265, P = 0.006; rs7103411, P = 0.014). Moreover, we detected association between both SNPs and risk-taking behaviour after drinking (rs6265, P = 0.005; rs7103411, P = 0.009) and we detected strong association between both SNPs and alcohol dependence in males (rs6265, P = 0.009; rs7103411, P = 0.013) while females showed association with multiple behavioural measures reflecting repetitive alcohol consumption. Haplotype analysis revealed the rs6265-rs7103411 A/C haplotype is associated with comorbid alcohol dependence (P = 0.002). When these SNPs were tested in the non-schizophrenia alcohol dependent group we were unable to detect association. Conclusion We conclude that these BDNF SNPs play a role in development of comorbid alcohol dependence in schizophrenia while our data does not indicate that they play a role in alcohol dependent patients who do not have schizophrenia.
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Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.
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We examine enterprise social network usage data obtained from a community of store managers in a leading Australian retail organization, over a period of fifteen months. Our interest in examining this data is in spatial preferences by the network users, that is, to ascertain who is communicating with whom and where. We offer several contrasting theoretical perspectives for spatial preference patterns and examine these against data collected from over 12,000 messages exchanged between 530 managers in 897 stores. Our findings show that interactions can generally be characterized by individual preferences for local communication but also that two different user communities exist – locals and globals. We develop empirical profiles for these social network user communities and outline implications for theories on spatial influences on communication behaviours on enterprise social networks.
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This thesis involved research into the barriers and enablers that existed for a cohort of mature-aged education support students engaging with blended learning through distance education. The findings that emerged from this research indicated that a flexible model of blended learning is possible in this context. The findings shed light on the experiences of novice technology users' participation in blended learning. The study highlighted the significance of factors such as isolation, technology, communication, connectivity, prior learning, and the growth of self-efficacy that influenced learner engagement.
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Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.
Resumo:
Many techniques in information retrieval produce counts from a sample, and it is common to analyse these counts as proportions of the whole - term frequencies are a familiar example. Proportions carry only relative information and are not free to vary independently of one another: for the proportion of one term to increase, one or more others must decrease. These constraints are hallmarks of compositional data. While there has long been discussion in other fields of how such data should be analysed, to our knowledge, Compositional Data Analysis (CoDA) has not been considered in IR. In this work we explore compositional data in IR through the lens of distance measures, and demonstrate that common measures, naïve to compositions, have some undesirable properties which can be avoided with composition-aware measures. As a practical example, these measures are shown to improve clustering. Copyright 2014 ACM.
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Background: The existence of an ecstasy dependence syndrome is controversial. We examined whether the acute after-effects of ecstasy use (i.e., the “come-down”) falsely lead to the identification of ecstasy withdrawal and the subsequent diagnosis of ecstasy dependence. Methods: The Structured Clinical Interview for DSM-IV-TR Disorders: Research Version (SCID-RV) was administered to 214 Australian ecstasy users. Ecstasy withdrawal was operationalized in three contrasting ways: (i) as per DSM-IV criteria; (ii) as the expected after effects of ecstasy (a regular come-down); or (iii) as a substantially greater or longer come-down than on first use (intense come-down). These definitions were validated against frequency of ecstasy use, readiness to change and ability to resist the urge to use ecstasy. Confirmatory factor analyses were used to see how they aligned with the overall dependence syndrome. Results: Come-down symptoms increased the prevalence of withdrawal from 1% (DSM-IV criterion) to 11% (intense come-downs) and 75% (regular come-downs). Past year ecstasy dependence remained at 31% when including the DSM-IV withdrawal criteria and was 32% with intense come-downs, but increased to 45% with regular come-downs. Intense come-downs were associated with lower ability to resist ecstasy use and loaded positively on the dependence syndrome. Regular come-downs did not load positively on the ecstasy dependence syndrome and were not related to other indices of dependence. Conclusion: The acute after-effects of ecstasy should be excluded when assessing ecstasy withdrawal as they can lead to a false diagnosis of ecstasy dependence. Worsening of the ecstasy come-down may be a marker for dependence.