94 resultados para RESPONSE DATA
Resumo:
Objectives: The use of triclosan within various environments has been linked to the development of multiple drug resistance (MDR) through the increased expression of efflux pumps such as AcrAB-ToIC. In this work, we investigate the effect of triclosan exposure in order to ascertain the response of two species to the presence of this widely used biocide. Methods: The transcriptomes of Salmonella enterica serovar Typhimurium SL1344 and Escherichia coli K-12 MG1655 after exposure to the MIC of triclosan (0.12 mg/L) were determined in microarray experiments. Phenotypic validation of the transcriptomic data included RT-PCR, ability to form a biofilm and motility assays. Results: Despite important differences in the triclosan-dependent transcriptomes of the two species, increased expression of efflux pump component genes was seen in both. Increased expression of soxS was observed in Salmonella Typhimurium, however, within E. coli, decreased expression was seen. Expression of fabBAGI in Salmonella Typhimurium was decreased, whereas in E. coli expression of fabABFH was increased. Increased expression of ompR and genes within this regulon (e.g. ompC, csgD and ssrA) was seen in the transcriptome of Salmonella Typhimurium. An unexpected response of E. coli was the differential expression of genes within operons involved in iron homeostasis; these included fhu, fep and ent. Conclusions: These data indicate that whilst a core response to triclosan exposure exists, the differential transcriptome of each species was different. This suggests that E. coli K-12 should not be considered the paradigm for the Enterobacteriaceae when exploring the effects of antimicrobial agents.
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This paper reports the findings from two large scale national on-line surveys carried out in 2009 and 2010, which explored the state of history teaching in English secondary schools. Large variation in provision was identified within comprehensive schools in response to national policy decisions and initiatives. Using the data from the surveys and school level data that is publicly available, this study examines situated factors, particularly the nature of the school intake, the numbers of pupils with special educational needs and the socio-economic status of the area surrounding the school, and the impact these have on the provision of history education. The findings show that there is a growing divide between those students that have access to the ‘powerful knowledge’, provided by subjects like history, and those that do not.
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The mesospheric response to the 2002 Antarctic Stratospheric Sudden Warming (SSW) is analysed using the Canadian Middle Atmosphere Model Data Assimilation System (CMAM-DAS), where it represents a vertical propagation of information from the observations into the data-free mesosphere. The CMAM-DAS simulates a cooling in the lowest part of the mesosphere which is accomplished by resolved motions, but which is extended to the mid- to upper mesosphere by the response of the model's non-orographic gravity-wave drag parameterization to the change in zonal winds. The basic mechanism is that elucidated by Holton consisting of a net eastward wave-drag anomaly in the mesosphere during the SSW, although in this case there is a net upwelling in the polar mesosphere. Since the zonal-mean mesospheric response is shown to be predictable, this demonstrates that variations in the mesospheric state can be slaved to the lower atmosphere through gravity-wave drag.
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As a consequence of land use change and the burning of fossil fuels, atmospheric concentrations of CO2 are increasing and altering the dynamics of the carbon cycle in forest ecosystems. In a number of studies using single tree species, fine root biomass has been shown to be strongly increased by elevated CO2. However, natural forests are often intimate mixtures of a number of co-occurring species. To investigate the interaction between tree mixture and elevated CO2, Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of single species and a three species polyculture in a free-air CO2 enrichment study (BangorFACE). The trees were exposed to ambient or elevated CO2 (580 µmol mol-1) for four years. Fine and coarse root biomass, together with fine root turnover and fine root morphological characteristics were measured. Fine root biomass, and morphology responded differentially to elevated CO2 at different soil depths in the three species when grown in monocultures. In polyculture, a greater response to elevated CO2 was observed in coarse roots to a depth of 20 cm, and fine root area index to a depth of 30 cm. Total fine root biomass was positively affected by elevated CO2 at the end of the experiment, but not by species diversity. Our data suggest that existing biogeochemical cycling models parameterised with data from species grown in monoculture may be underestimating the belowground response to global change.
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The nature of private commercial real estate markets presents difficulties for monitoring market performance. Assets are heterogeneous and spatially dispersed, trading is infrequent and there is no central marketplace in which prices and cash flows of properties can be easily observed. Appraisal based indices represent one response to these issues. However, these have been criticised on a number of grounds: that they may understate volatility, lag turning points and be affected by client influence issues. Thus, this paper reports econometrically derived transaction based indices of the UK commercial real estate market using Investment Property Databank (IPD) data, comparing them with published appraisal based indices. The method is similar to that presented by Fisher, Geltner, and Pollakowski (2007) and used by Massachusett, Institute of Technology (MIT) on National Council of Real Estate Investment Fiduciaries (NCREIF) data, although it employs value rather than equal weighting. The results show stronger growth from the transaction based indices in the run up to the peak in the UK market in 2007. They also show that returns from these series are more volatile and less autocorrelated than their appraisal based counterparts, but, surprisingly, differences in turning points were not found. The conclusion then debates the applications and limitations these series have as measures of market performance.
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Reduced flexibility of low carbon generation could pose new challenges for future energy systems. Both demand response and distributed storage may have a role to play in supporting future system balancing. This paper reviews how these technically different, but functionally similar approaches compare and compete with one another. Household survey data is used to test the effectiveness of price signals to deliver demand responses for appliances with a high degree of agency. The underlying unit of storage for different demand response options is discussed, with particular focus on the ability to enhance demand side flexibility in the residential sector. We conclude that a broad range of options, with different modes of storage, may need to be considered, if residential demand flexibility is to be maximised.
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Undeniably, anticipation plays a crucial role in cognition. By what means, to what extent, and what it achieves remain open questions. In a recent BBS target article, Clark (in press) depicts an integrative model of the brain that builds on hierarchical Bayesian models of neural processing (Rao and Ballard, 1999; Friston, 2005; Brown et al., 2011), and their most recent formulation using the free-energy principle borrowed from thermodynamics (Feldman and Friston, 2010; Friston, 2010; Friston et al., 2010). Hierarchical generative models of cognition, such as those described by Clark, presuppose the manipulation of representations and internal models of the world, in as much detail as is perceptually available. Perhaps surprisingly, Clark acknowledges the existence of a “virtual version of the sensory data” (p. 4), but with no reference to some of the historical debates that shaped cognitive science, related to the storage, manipulation, and retrieval of representations in a cognitive system (Shanahan, 1997), or accounting for the emergence of intentionality within such a system (Searle, 1980; Preston and Bishop, 2002). Instead of demonstrating how this Bayesian framework responds to these foundational questions, Clark describes the structure and the functional properties of an action-oriented, multi-level system that is meant to combine perception, learning, and experience (Niedenthal, 2007).
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In the heart, inflammatory cytokines including interleukin (IL) 1β are implicated in regulating adaptive and maladaptive changes, whereas IL33 negatively regulates cardiomyocyte hypertrophy and promotes cardioprotection. These agonists signal through a common co-receptor but, in cardiomyocytes, IL1β more potently activates mitogen-activated protein kinases and NFκB, pathways that regulate gene expression. We compared the effects of external application of IL1β and IL33 on the cardiomyocyte transcriptome. Neonatal rat cardiomyocytes were exposed to IL1β or IL33 (0.5, 1 or 2h). Transcriptomic profiles were determined using Affymetrix rat genome 230 2.0 microarrays and data were validated by quantitative PCR. IL1β induced significant changes in more RNAs than IL33 and, generally, to a greater degree. It also had a significantly greater effect in downregulating mRNAs and in regulating mRNAs associated with selected pathways. IL33 had a greater effect on a small, select group of specific transcripts. Thus, differences in intensity of intracellular signals can deliver qualitatively different responses. Quantitatively different responses in production of receptor agonists and transcription factors may contribute to qualitative differences at later times resulting in different phenotypic cellular responses.
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Climate is an important control on biomass burning, but the sensitivity of fire to changes in temperature and moisture balance has not been quantified. We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.
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The interannual variability of the stratospheric polar vortex during winter in both hemispheres is observed to correlate strongly with the phase of the quasi-biennial oscillation (QBO) in tropical stratospheric winds. It follows that the lack of a spontaneously generated QBO in most atmospheric general circulation models (AGCMs) adversely affects the nature of polar variability in such models. This study examines QBO–vortex coupling in an AGCM in which a QBO is spontaneously induced by resolved and parameterized waves. The QBO–vortex coupling in the AGCM compares favorably to that seen in reanalysis data [from the 40-yr ECMWF Re-Analysis (ERA-40)], provided that careful attention is given to the definition of QBO phase. A phase angle representation of the QBO is employed that is based on the two leading empirical orthogonal functions of equatorial zonal wind vertical profiles. This yields a QBO phase that serves as a proxy for the vertical structure of equatorial winds over the whole depth of the stratosphere and thus provides a means of subsampling the data to select QBO phases with similar vertical profiles of equatorial zonal wind. Using this subsampling, it is found that the QBO phase that induces the strongest polar vortex response in early winter differs from that which induces the strongest late-winter vortex response. This is true in both hemispheres and for both the AGCM and ERA-40. It follows that the strength and timing of QBO influence on the vortex may be affected by the partial seasonal synchronization of QBO phase transitions that occurs both in observations and in the model. This provides a mechanism by which changes in the strength of QBO–vortex correlations may exhibit variability on decadal time scales. In the model, such behavior occurs in the absence of external forcings or interannual variations in sea surface temperatures.
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Abstract Objective: Studies have started to question whether a specific component or combinations of metabolic syndrome (MetS) components may be more important in relation to cardiovascular disease risk. Our aim was to examine the impact of the presence of raised fasting glucose as a MetS component on postprandial lipaemia. Methods: Men classified with the MetS underwent a sequential test meal investigation, in which blood samples were taken at regular intervals after a test breakfast (t=0 min) and lunch (t=330 min). Lipids, glucose and insulin were measured in the fasting and postprandial samples. Results: MetS subjects with 3 or 4 components were subdivided into those without (n=34) and with (n=23) fasting hyperglycaemia (≥ 5.6 mmol/l), irrespective of the combination of components. Fasting lipids and insulin were similar in the two groups, with glucose significantly higher in the men with glucose as a MetS component (P<0.001). Following the test meals, there was a higher maximum concentration (maxC), area under the curve (AUC) and incremental AUC (P≤0.016) for the postprandial triacylglycerol (TAG) response in men with fasting hyperglycaemia. Greater glucose AUC (P<0.001) and insulin maxC (P=0.010) was also observed in these individuals after the test meals. Multivariate regression analysis revealed fasting glucose to be an important predictor of the postprandial TAG and glucose response. Conclusion: Our data analysis has revealed a greater impairment of postprandial TAG than glucose response in MetS subjects with raised fasting glucose. The worsening of postprandial lipaemic control may contribute to the greater CVD risk reported in individuals with MetS component combinations which include hyperglycaemia.
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We discuss the modeling of dielectric responses of electromagnetically excited networks which are composed of a mixture of capacitors and resistors. Such networks can be employed as lumped-parameter circuits to model the response of composite materials containing conductive and insulating grains. The dynamics of the excited network systems are studied using a state space model derived from a randomized incidence matrix. Time and frequency domain responses from synthetic data sets generated from state space models are analyzed for the purpose of estimating the fraction of capacitors in the network. Good results were obtained by using either the time-domain response to a pulse excitation or impedance data at selected frequencies. A chemometric framework based on a Successive Projections Algorithm (SPA) enables the construction of multiple linear regression (MLR) models which can efficiently determine the ratio of conductive to insulating components in composite material samples. The proposed method avoids restrictions commonly associated with Archie’s law, the application of percolation theory or Kohlrausch-Williams-Watts models and is applicable to experimental results generated by either time domain transient spectrometers or continuous-wave instruments. Furthermore, it is quite generic and applicable to tomography, acoustics as well as other spectroscopies such as nuclear magnetic resonance, electron paramagnetic resonance and, therefore, should be of general interest across the dielectrics community.
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There is large uncertainty about the magnitude of warming and how rainfall patterns will change in response to any given scenario of future changes in atmospheric composition and land use. The models used for future climate projections were developed and calibrated using climate observations from the past 40 years. The geologic record of environmental responses to climate changes provides a unique opportunity to test model performance outside this limited climate range. Evaluation of model simulations against palaeodata shows that models reproduce the direction and large-scale patterns of past changes in climate, but tend to underestimate the magnitude of regional changes. As part of the effort to reduce model-related uncertainty and produce more reliable estimates of twenty-first century climate, the Palaeoclimate Modelling Intercomparison Project is systematically applying palaeoevaluation techniques to simulations of the past run with the models used to make future projections. This evaluation will provide assessments of model performance, including whether a model is sufficiently sensitive to changes in atmospheric composition, as well as providing estimates of the strength of biosphere and other feedbacks that could amplify the model response to these changes and modify the characteristics of climate variability.
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(ABR) is of fundamental importance to the investiga- tion of the auditory system behavior, though its in- terpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analyzing the ABR, clinicians are often interested in the identi- fication of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave la- tency) is a practical tool for the diagnosis of disorders affecting the auditory system. In this context, the aim of this research is to compare ABR manual/visual analysis provided by different examiners. Methods: The ABR data were collected from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). A total of 160 data samples were analyzed and a pair- wise comparison between four distinct examiners was executed. We carried out a statistical study aiming to identify significant differences between assessments provided by the examiners. For this, we used Linear Regression in conjunction with Bootstrap, as a me- thod for evaluating the relation between the responses given by the examiners. Results: The analysis sug- gests agreement among examiners however reveals differences between assessments of the variability of the waves. We quantified the magnitude of the ob- tained wave latency differences and 18% of the inves- tigated waves presented substantial differences (large and moderate) and of these 3.79% were considered not acceptable for the clinical practice. Conclusions: Our results characterize the variability of the manual analysis of ABR data and the necessity of establishing unified standards and protocols for the analysis of these data. These results may also contribute to the validation and development of automatic systems that are employed in the early diagnosis of hearing loss.
Resumo:
Abstract Background: The analysis of the Auditory Brainstem Response (ABR) is of fundamental importance to the investigation of the auditory system behaviour, though its interpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analysing the ABR, clinicians are often interested in the identification of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave latency) is a practical tool for the diagnosis of disorders affecting the auditory system. Significant differences in inter-examiner results may lead to completely distinct clinical interpretations of the state of the auditory system. In this context, the aim of this research was to evaluate the inter-examiner agreement and variability in the manual classification of ABR. Methods: A total of 160 ABR data samples were collected, for four different stimulus intensity (80dBHL, 60dBHL, 40dBHL and 20dBHL), from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). Four examiners with expertise in the manual classification of ABR components participated in the study. The Bland-Altman statistical method was employed for the assessment of inter-examiner agreement and variability. The mean, standard deviation and error for the bias, which is the difference between examiners’ annotations, were estimated for each pair of examiners. Scatter plots and histograms were employed for data visualization and analysis. Results: In most comparisons the differences between examiner’s annotations were below 0.1 ms, which is clinically acceptable. In four cases, it was found a large error and standard deviation (>0.1 ms) that indicate the presence of outliers and thus, discrepancies between examiners. Conclusions: Our results quantify the inter-examiner agreement and variability of the manual analysis of ABR data, and they also allows for the determination of different patterns of manual ABR analysis.