961 resultados para MADDEN-JULIAN OSCILLATION
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Germline mutations in BRCA1 predispose carriers to a high incidence of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through critical roles in DNA repair, cell cycle arrest and transcriptional control. A major question has been why BRCA1 loss or mutation leads to tumors mainly in estrogen-regulated tissues, given that BRCA1 has essential functions in all cell types. Here we report that estrogen and estrogen metabolites can cause DNA double strand breaks (DSB) in estrogen receptor-α negative breast cells and that BRCA1 is required to repair these DSBs to prevent metabolite-induced genomic instability. We found that BRCA1 also regulates estrogen metabolism and metabolite-mediated DNA damage by repressing the transcription of estrogen-metabolising enzymes, such as CYP1A1, in breast cells. Lastly, we used a knock-in human cell model with a heterozygous BRCA1 pathogenic mutation to show how BRCA1 haploinsufficiency affects these processes. Our findings provide pivotal new insights into why BRCA1 mutation drives the formation of tumours in estrogen-regulated tissues, despite the general role of BRCA1 in DNA repair in all cell types.
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In medical negligence litigation expert evidence has long played a dominant role. The trend towards the use of concurrent expert evidence is now well underway. However, for the lawyers and the doctors involved, the pathway is not yet familiar. Disputes have frequently arisen in the context of pre-hearing expert conclaves, given the adversarial nature of litigation and perhaps fuelled by fears of a less transparent process at this increasingly important stage. This article explains the concurrent expert evidence framework and examines areas of common dispute both in the conclaves and at trial, with a view to providing assistance to legal practitioners working in this area and the medical practitioners called upon to provide expert evidence in such litigation.
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This research identifies the commuting mode choice behaviour of 3537 adults living in different types of transit oriented development (TOD) in Brisbane by disentangling the effects of their “evil twin” transit adjacent developments (TADs), and by also controlling for residential self-selection, travel attitudes and preferences, and socio-demographic effects. A TwoStep cluster analysis was conducted to identify the natural groupings of respondents’ living environment based on six built environment indicators. The analysis resulted in five types of neighbourhoods: urban TODs, activity centre TODs, potential TODs, TADs, and traditional suburbs. HABITAT survey data were used to derive the commute mode choice behaviour of people living in these neighbourhoods. In addition, statements reflecting both respondents’ travel attitudes and living preferences were also collected as part of the survey. Factor analyses were conducted based on these statements and these derived factors were then used to control for residential self-selection. Four binary logistic regression models were estimated, one for each of the travel modes used (e.g. public transport, active transport, less sustainable transport such as the car/taxi, and other), to differentiate between the commuting behaviour of people living in the five types of neighbourhoods. The findings verify that urban TODs enhance the use of public transport and reduce car usage. No significant difference was found in the commuting behaviour between respondents living in traditional suburbs and TADs. The results confirm the hypothesis that TADs are the “evil twin” of TODs. The data indicates that TADs and the mode choices of residents in these neighbourhoods is a missed transport policy opportunity. Further policy efforts are required for a successive transition of TADs into TODs in order to realise the full benefits of these. TOD policy should also be integrated with context specific TOD design principles.
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Disconnector switch operation in GIS generates VFT voltages in the system. It is important, for insulation co-ordination purposes, to obtain accurate VFT V-t data for typical gap geometries found in GIS. This paper presents experimentally obtained VFT V-t data for a 180/1 lOmm co-axial gap. The VFT has a time to first peak of 35 ns and a oscillation frequency of 13,6 MHz. Due to the location of the voltage divider in a compartment adjacent to the gap, a correction factor of 1.1 is used to relate the measured breakdown voltage to that in the gap. Positive polarity VFT V-t data is presented for 1, 2, 3 and 4 bar absolute and negative polarity VFT data for 3 and 4 bar absolute. Two methods of generating the VFT's are used. The first is to power up the test transformer at power frequency. The second is to generate a switching impulse by discharging a capacitor into the primary of the test transformer.
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The Eating Disorder Risk Composite (EDRC) comprises the Drive for Thinness, Bulimia, and Body Dissatisfaction subscales of the Eating Disorder Inventory, Third Edition (EDI-3, Garner, 2004). Past research conducted with Latina college women (LCW) has found older versions of the EDRC subscales to be reliable, but the EDI-3's EDRC factor structure has yet to be studied among LCW. The present study investigated the pattern of responses to and the factor structure of the EDRC in LCW. It was hypothesized that eating pathology would be present and that a factor analysiswould find some discrepancies between the original factor structure of the EDRC and the factor structure from LCW. Analyses of data on a 6-point Likert scale indicate that drive for thinness and body dissatisfaction are far more prevalent than is bulimic symptomology in LCW. Principal Axis Factoring with promax rotation was used to extract three factors very similar to the original EDRC. Some discrepancies in the item loadings were observed, most notably that half of the items from the original Body Dissatisfaction subscale did not load together on one factor. Overall, the EDRC appears to be a goodmeasurement of eating- and body-related phenomena among LCW. Implications, limitations, and future directions are discussed.
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The Trans-Pacific Partnership is a sweeping trade agreement, spanning the Pacific Rim, and covering an array of topics, including intellectual property. There has been much analysis of the recently leaked intellectual property chapter of the Trans-Pacific Partnership by WikiLeaks. Julian Assange, WikiLeaks’ Editor-in-Chief, observed “The selective secrecy surrounding the TPP negotiations, which has let in a few cashed-up megacorps but excluded everyone else, reveals a telling fear of public scrutiny. By publishing this text we allow the public to engage in issues that will have such a fundamental impact on their lives.” Critical attention has focused upon the lack of transparency surrounding the agreement, copyright law and the digital economy; patent law, pharmaceutical drugs, and data protection; and the criminal procedures and penalties for trade secrets. The topic of trade mark law and related rights, such as internet domain names and geographical indications, deserves greater analysis.
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Twitter and other social networking sites play an ever more present role in the spread of current events. The dynamics of information dissemination through digital network structures are still relatively unexplored, however. At what time an issue is taken up by whom? Who forwards a message when to whom else? What role do individual communication participants, existing digital communities or the technical foundations of each network platform play in the spread of news? In this chapter we discuss, using the example of a video on a current sociopolitical issue in Australia that was shared on Twitter, a number of new methods for the dynamic visualisation and analysis of communication processes. Our method combines temporal and spatial analytical approaches and provides new insights into the spread of news in digital networks. [Social media dienen immer häufger als Disseminationsmechanismen für Medieninhalte. Auf Twitter ermöglicht besonders die Retweet-Funktion den schnellen und weitläufgen Transfer von Nachrichten. In diesem Beitrag etablieren neue methodische Ansätze zur Erfassung, Visualisierung und Analyse von Retweet-Ketten. Insbesondere heben wir hervor, wie bestehende Netzwerkanalysemethoden ergänzt werden können, um den Ablauf der Weiterleitung sowohl temporal als auch spatial zu erfassen. Unsere Fallstudie demonstriert die verbreitung des videoclips einer am 9. Oktober 2012 spontan gehaltenen Wutrede der australischen Premierministerin Julia Gillard, in der sie Oppositionsführer Tony Abbott als Frauenhasser brandmarkte. Durch die Erfassung von Hintergrunddaten zu den jeweiligen NutzerInnen, die sich an der Weiterleitung des Videoclips beteiligten, erstellen wir ein detailliertes Bild des Disseminationsablaufs im vorliegenden Fall. So lassen sich die wichtigsten AkteurInnen und der Ablauf der Weiterleitung darstellen und analysieren. Daraus entstehen Einblicke in die allgemeinen verbreitungsmuster von Nachrichten auf Twitter].
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Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10-8) and three variants reported as suggestive (P<5×10-7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10-9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10-9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10-8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma. © 2012 Ramasamy et al.
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As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.
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Aim Determining how ecological processes vary across space is a major focus in ecology. Current methods that investigate such effects remain constrained by important limiting assumptions. Here we provide an extension to geographically weighted regression in which local regression and spatial weighting are used in combination. This method can be used to investigate non-stationarity and spatial-scale effects using any regression technique that can accommodate uneven weighting of observations, including machine learning. Innovation We extend the use of spatial weights to generalized linear models and boosted regression trees by using simulated data for which the results are known, and compare these local approaches with existing alternatives such as geographically weighted regression (GWR). The spatial weighting procedure (1) explained up to 80% deviance in simulated species richness, (2) optimized the normal distribution of model residuals when applied to generalized linear models versus GWR, and (3) detected nonlinear relationships and interactions between response variables and their predictors when applied to boosted regression trees. Predictor ranking changed with spatial scale, highlighting the scales at which different species–environment relationships need to be considered. Main conclusions GWR is useful for investigating spatially varying species–environment relationships. However, the use of local weights implemented in alternative modelling techniques can help detect nonlinear relationships and high-order interactions that were previously unassessed. Therefore, this method not only informs us how location and scale influence our perception of patterns and processes, it also offers a way to deal with different ecological interpretations that can emerge as different areas of spatial influence are considered during model fitting.
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Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.
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Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency.
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The main genetic determinant of soluble interleukin 6 receptor (sIL-6R) levels is the missense variant rs2228145 that maps to the cleavage site of IL-6R. For each Ala allele, sIL-6R serum levels increase by ∼20 ng ml -1 and asthma risk by 1.09-fold. However, this variant does not explain the total heritability for sIL-6R levels. Additional independent variants in IL6R may therefore contribute to variation in sIL-6R levels and influence asthma risk. We imputed 471 variants in IL6R and tested these for association with sIL-6R serum levels in 360 individuals. An intronic variant (rs12083537) was associated with sIL-6R levels independently of rs4129267 (P=0.0005), a proxy single-nucleotide polymorphism for rs2228145. A significant and consistent association for rs12083537 was observed in a replication panel of 354 individuals (P=0.033). Each rs12083537:A allele increased sIL-6R serum levels by 2.4 ng ml -1. Analysis of mRNA levels in two cohorts did not identify significant associations between rs12083537 and IL6R transcription levels. On the other hand, results from 16 705 asthmatics and 30 809 controls showed that the rs12083537:A allele increased asthma risk by 1.04-fold (P=0.0419). Genetic risk scores based on IL6R regulatory variants may prove useful in explaining variation in clinical response to tocilizumab, an anti-IL-6R monoclonal antibody.
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We aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying the disease. We did a genome-wide association study (GWAS) in 2669 physician-diagnosed asthmatics and 4528 controls from Australia. Seven loci were prioritised for replication after combining our results with those from the GABRIEL consortium (n=26 475), and these were tested in an additional 25 358 independent samples from four in-silico cohorts. Quantitative multi-marker scores of genetic load were constructed on the basis of results from the GABRIEL study and tested for association with asthma in our Australian GWAS dataset. Two loci were confirmed to associate with asthma risk in the replication cohorts and reached genome-wide significance in the combined analysis of all available studies (n=57 800): rs4129267 (OR 1·09, combined p= 2·4×10-8) in the interleukin-6 receptor (IL6R) gene and rs7130588 (OR 1·09, p=1·8×10-8) on chromosome 11q13.5 near the leucine-rich repeat containing 32 gene (LRRC32, also known as GARP). The 11q13.5 locus was significantly associated with atopic status among asthmatics (OR 1·33, p=7×10-4), suggesting that it is a risk factor for allergic but not non-allergic asthma. Multi-marker association results are consistent with a highly polygenic contribution to asthma risk, including loci with weak effects that might be shared with other immune-related diseases, such as NDFIP1, HLA-B, LPP, and BACH2. The IL6R association further supports the hypothesis that cytokine signalling dysregulation affects asthma risk, and raises the possibility that an IL6R antagonist (tocilizumab) may be effective to treat the disease, perhaps in a genotype-dependent manner. Results for the 11q13.5 locus suggest that it directly increases the risk of allergic sensitisation which, in turn, increases the risk of subsequent development of asthma. Larger or more functionally focused studies are needed to characterise the many loci with modest effects that remain to be identified for asthma. National Health and Medical Research Council of Australia. A full list of funding sources is provided in the webappendix. © 2011 Elsevier Ltd.