161 resultados para Host range analysis
Resumo:
We provide a unified framework for a range of linear transforms that can be used for the analysis of terahertz spectroscopic data, with particular emphasis on their application to the measurement of leaf water content. The use of linear transforms for filtering, regression, and classification is discussed. For illustration, a classification problem involving leaves at three stages of drought and a prediction problem involving simulated spectra are presented. Issues resulting from scaling the data set are discussed. Using Lagrange multipliers, we arrive at the transform that yields the maximum separation between the spectra and show that this optimal transform is equivalent to computing the Euclidean distance between the samples. The optimal linear transform is compared with the average for all the spectra as well as with the Karhunen–Loève transform to discriminate a wet leaf from a dry leaf. We show that taking several principal components into account is equivalent to defining new axes in which data are to be analyzed. The procedure shows that the coefficients of the Karhunen–Loève transform are well suited to the process of classification of spectra. This is in line with expectations, as these coefficients are built from the statistical properties of the data set analyzed.
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A radiometric analysis of the light coupled by optical fiber amplitude modulating extrinsic-type reflectance displacement sensors is presented. Uncut fiber sensors show the largest range but a smaller responsivity. Single cut fiber sensors exhibit an improvement in responsivity at the expense of range. A further increase in responsivity as well as a reduction in the operational range is obtained when the double cut sensor configuration is implemented. The double cut configuration is particularly suitable in applications where feedback action is applied to the moving reflector surface. © 2000 American Institute of Physics.
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Recent laboratory observations and advances in theoretical quantum chemistry allow a reappraisal of the fundamental mechanisms that determine the water vapour self-continuum absorption throughout the infrared and millimetre wave spectral regions. By starting from a framework that partitions bimolecular interactions between water molecules into free-pair states, true bound and quasi-bound dimers, we present a critical review of recent observations, continuum models and theoretical predictions. In the near-infrared bands of the water monomer, we propose that spectral features in recent laboratory-derived self-continuum can be well explained as being due to a combination of true bound and quasi-bound dimers, when the spectrum of quasi-bound dimers is approximated as being double the broadened spectrum of the water monomer. Such a representation can explain both the wavenumber variation and the temperature dependence. Recent observations of the self-continuum absorption in the windows between these near-infrared bands indicate that widely used continuum models can underestimate the true strength by around an order of magnitude. An existing far-wing model does not appear able to explain the discrepancy, and although a dimer explanation is possible, currently available observations do not allow a compelling case to be made. In the 8–12 micron window, recent observations indicate that the modern continuum models either do not properly represent the temperature dependence, the wavelength variation, or both. The temperature dependence is suggestive of a transition from the dominance of true bound dimers at lower temperatures to quasibound dimers at higher temperatures. In the mid- and far-infrared spectral region, recent theoretical calculations indicate that true bound dimers may explain at least between 20% and 40% of the observed self-continuum. The possibility that quasi-bound dimers could cause an additional contribution of the same size is discussed. Most recent theoretical considerations agree that water dimers are likely to be the dominant contributor to the self-continuum in the mm-wave spectral range.
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Automatic keyword or keyphrase extraction is concerned with assigning keyphrases to documents based on words from within the document. Previous studies have shown that in a significant number of cases author-supplied keywords are not appropriate for the document to which they are attached. This can either be because they represent what the author believes the paper is about not what it actually is, or because they include keyphrases which are more classificatory than explanatory e.g., “University of Poppleton” instead of “Knowledge Discovery in Databases”. Thus, there is a need for a system that can generate appropriate and diverse range of keyphrases that reflect the document. This paper proposes a solution that examines the synonyms of words and phrases in the document to find the underlying themes, and presents these as appropriate keyphrases. The primary method explores taking n-grams of the source document phrases, and examining the synonyms of these, while the secondary considers grouping outputs by their synonyms. The experiments undertaken show the primary method produces good results and that the secondary method produces both good results and potential for future work.
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We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues.
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The interaction between the gut microbiota and their mammalian host is known to have far-reaching consequences with respect to metabolism and health. We investigated the effects of eight days of oral antibiotic exposure (penicillin and streptomycin sulfate) on gut microbial composition and host metabolic phenotype in male Han-Wistar rats (n = 6) compared to matched controls. Early recolonization was assessed in a third group exposed to antibiotics for four days followed by four days recovery (n = 6). Fluorescence in situ hybridization analysis of the intestinal contents collected at eight days showed a significant reduction in all bacterial groups measured (control, 1010.7 cells/g feces; antibiotic-treated, 108.4). Bacterial suppression reduced the excretion of mammalian-microbial urinary cometabolites including hippurate, phenylpropionic acid, phenylacetylglycine and indoxyl-sulfate whereas taurine, glycine, citrate, 2-oxoglutarate, and fumarate excretion was elevated. While total bacterial counts remained notably lower in the recolonized animals (109.1 cells/g faeces) compared to the controls, two cage-dependent subgroups emerged with Lactobacillus/Enterococcus probe counts dominant in one subgroup. This dichotomous profile manifested in the metabolic phenotypes with subgroup differences in tricarboxylic acid cycle metabolites and indoxyl-sulfate excretion. Fecal short chain fatty acids were diminished in all treated animals. Antibiotic treatment induced a profound effect on the microbiome structure, which was reflected in the metabotype. Moreover, the recolonization process was sensitive to the microenvironment, which may impact on understanding downstream consequences of antibiotic consumption in human populations.
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Single-cell analysis is essential for understanding the processes of cell differentiation and metabolic specialisation in rare cell types. The amount of single proteins in single cells can be as low as one copy per cell and is for most proteins in the attomole range or below; usually considered as insufficient for proteomic analysis. The development of modern mass spectrometers possessing increased sensitivity and mass accuracy in combination with nano-LC-MS/MS now enables the analysis of single-cell contents. In Arabidopsis thaliana, we have successfully identified nine unique proteins in a single-cell sample and 56 proteins from a pool of 15 single-cell samples from glucosinolate-rich S-cells by nanoLC-MS/MS proteomic analysis, thus establishing the proof-of-concept for true single-cell proteomic analysis. Dehydrin (ERD14_ARATH), two myrosinases (BGL37_ARATH and BGL38_ARATH), annexin (ANXD1_ARATH), vegetative storage proteins (VSP1_ARATH and VSP2_ARATH) and four proteins belonging to the S-adenosyl-l-methionine cycle (METE_ARATH, SAHH1_ARATH, METK4_ARATH and METK1/3_ARATH) with associated adenosine kinase (ADK1_ARATH), were amongst the proteins identified in these single-S-cell samples. Comparison of the functional groups of proteins identified in S-cells with epidermal/cortical cells and whole tissue provided a unique insight into the metabolism of S-cells. We conclude that S-cells are metabolically active and contain the machinery for de novo biosynthesis of methionine, a precursor for the most abundant glucosinolate glucoraphanine in these cells. Moreover, since abundant TGG2 and TGG1 peptides were consistently found in single-S-cell samples, previously shown to have high amounts of glucosinolates, we suggest that both myrosinases and glucosinolates can be localised in the same cells, but in separate subcellular compartments. The complex membrane structure of S-cells was reflected by the presence of a number of proteins involved in membrane maintenance and cellular organisation.
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The ASTER Global Digital Elevation Model (GDEM) has made elevation data at 30 m spatial resolution freely available, enabling reinvestigation of morphometric relationships derived from limited field data using much larger sample sizes. These data are used to analyse a range of morphometric relationships derived for dunes (between dune height, spacing, and equivalent sand thickness) in the Namib Sand Sea, which was chosen because there are a number of extant studies that could be used for comparison with the results. The relative accuracy of GDEM for capturing dune height and shape was tested against multiple individual ASTER DEM scenes and against field surveys, highlighting the smoothing of the dune crest and resultant underestimation of dune height, and the omission of the smallest dunes, because of the 30 m sampling of ASTER DEM products. It is demonstrated that morphometric relationships derived from GDEM data are broadly comparable with relationships derived by previous methods, across a range of different dune types. The data confirm patterns of dune height, spacing and equivalent sand thickness mapped previously in the Namib Sand Sea, but add new detail to these patterns.
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European economic and political integration have been recognised as having implications for patterns of performance in national real estate and capital markets and have generated a wide body of research and commentary. In 1999, progress towards monetary integration within the European Union culminated in the introduction of a common currency and monetary policy. This paper investigates the effects of this ‘event’ on the behaviour of stock returns in European real estate companies. A range of statistical tests is applied to the performance of European property companies to test for changes in segmentation, co-movement and causality. The results suggest that, relative to the wider equity markets, the dispersion of performance is higher, correlations are lower, a common contemporaneous factor has much lower explanatory power whilst lead-lag relationships are stronger. Consequently, the evidence of transmission of monetary integration to real estate securities is less noticeable than to general securities. Less and slower integration is attributed to the relatively small size of the real estate securities market and the local and national nature of the majority of the companies’ portfolios.
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Background. Meta-analyses show that cognitive behaviour therapy for psychosis (CBT-P) improves distressing positive symptoms. However, it is a complex intervention involving a range of techniques. No previous study has assessed the delivery of the different elements of treatment and their effect on outcome. Our aim was to assess the differential effect of type of treatment delivered on the effectiveness of CBT-P, using novel statistical methodology. Method. The Psychological Prevention of Relapse in Psychosis (PRP) trial was a multi-centre randomized controlled trial (RCT) that compared CBT-P with treatment as usual (TAU). Therapy was manualized, and detailed evaluations of therapy delivery and client engagement were made. Follow-up assessments were made at 12 and 24 months. In a planned analysis, we applied principal stratification (involving structural equation modelling with finite mixtures) to estimate intention-to-treat (ITT) effects for subgroups of participants, defined by qualitative and quantitative differences in receipt of therapy, while maintaining the constraints of randomization. Results. Consistent delivery of full therapy, including specific cognitive and behavioural techniques, was associated with clinically and statistically significant increases in months in remission, and decreases in psychotic and affective symptoms. Delivery of partial therapy involving engagement and assessment was not effective. Conclusions. Our analyses suggest that CBT-P is of significant benefit on multiple outcomes to patients able to engage in the full range of therapy procedures. The novel statistical methods illustrated in this report have general application to the evaluation of heterogeneity in the effects of treatment.
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A semiochemical based push-pull strategy for control of oilseed rape pests is being developed at Rothamsted Research. This strategy uses insect and plant derived semiochemicals to manipulate pests and their natural enemies. An important element within this strategy is an understanding of the importance of non-host plant cues for pest insects and how such signals could be used to manipulate their behaviour. Previous studies using a range of non-host plants have shown that, for the pollen beetle Meligethes aeneus (Coleoptera: Nitidulidae), the essential oil of lavender, Lavandula angustifolia (Lamiaceae), was the most repellent. The aim of this study was to identify the active components in L. angustifolia oil, and to investigate the behaviour of M. aeneus to these chemicals, to establish the most effective use of repellent stimuli to disrupt colonisation of oilseed rape crops. Coupled gas chromatography-electroantennography (GC-EAG) and gas chromatography-mass spectrometry (GC-MS) resulted in the identification of seven active compounds which were tested for behavioural activity using a 4-way olfactometer. Repellent responses were observed with (±)-linalool and (±)-linalyl acetate. The use of these chemicals within a push-pull pest control strategy is discussed.
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The adsorption of carbon monoxide on the Pt{110} surface at coverages of 0.5 ML and 1.0 ML was investigated using quantitative low-energy electron diffraction (LEED IV) and density-functional theory (DFT). At 0.5 ML CO lifts the reconstruction of the clean surface but does not form an ordered overlayer. At the saturation coverage, 1.0 ML, a well-ordered p(2×1) superstructure with glide line symmetry is formed. It was confirmed that the CO molecules adsorb on top of the Pt atoms in the top-most substrate layer with the molecular axes tilted by ±22° with respect to the surface normal in alternating directions away from the close packed rows of Pt atoms. This is accompanied by significant lateral shifts of 0.55 Å away from the atop sites in the same direction as the tilt. The top-most substrate layer relaxes inwards by −4% with respect to the bulk-terminated atom positions, while the consecutive layers only show minor relaxations. Despite the lack of long-range order in the 0.5 ML CO layer it was possible to determine key structural parameters by LEED IV using only the intensities of the integer-order spots. At this coverage CO also adsorbs on atop sites with the molecular axis closer to the surface normal (b10°). The average substrate relaxations in each layer are similar for both coverages and consistent with DFT calculations performed for a variety of ordered structures with coverages of 1.0 ML and 0.5 ML.
Integrated cytokine and metabolic analysis of pathological responses to parasite exposure in rodents
Resumo:
Parasitic infections cause a myriad of responses in their mammalian hosts, on immune as well as on metabolic level. A multiplex panel of cytokines and metabolites derived from four parasite-rodent models, namely, Plasmodium berghei-mouse, Trypanosoma brucei brucei-mouse, Schistosoma mansoni-mouse, and Fasciola hepatica-rat were statistically coanalyzed. 1H NMR spectroscopy and multivariate statistical analysis were used to characterize the urine and plasma metabolite profiles in infected and noninfected animals. Each parasite generated a unique metabolic signature in the host. Plasma cytokine concentrations were obtained using the ‘Meso Scale Discovery’ multi cytokine assay platform. Multivariate data integration methods were subsequently used to elucidate the component of the metabolic signature which is associated with inflammation and to determine specific metabolic correlates with parasite-induced changes in plasma cytokine levels. For example, the relative levels of acetyl glycoproteins extracted from the plasma metabolite profile in the P. berghei-infected mice were statistically correlated with IFN-γ, whereas the same cytokine was anticorrelated with glucose levels. Both the metabolic and the cytokine data showed a similar spatial distribution in principal component analysis scores plots constructed for the combined murine data, with samples from all infected animals clustering according to the parasite species and whereby the protozoan infections (P. berghei and T. b. brucei) grouped separately from the helminth infection (S. mansoni). For S. mansoni, the main infection-responsive cytokines were IL-4 and IL-5, which covaried with lactate, choline, and D-3-hydroxybutyrate. This study demonstrates that the inherently differential immune response to single and multicellular parasites not only manifests in the cytokine expression, but also consequently imprints on the metabolic signature, and calls for in-depth analysis to further explore direct links between immune features and biochemical pathways.
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Although the Unified Huntington's Disease Rating Scale (UHDRS) is widely used in the assessment of Huntington disease (HD), the ability of individual items to discriminate individual differences in motor or behavioral manifestations has not been extensively studied in HD gene expansion carriers without a motor-defined clinical diagnosis (ie, prodromal-HD or prHD). To elucidate the relationship between scores on individual motor and behavioral UHDRS items and total score for each subscale, a nonparametric item response analysis was performed on retrospective data from 2 multicenter longitudinal studies. Motor and behavioral assessments were supplied for 737 prHD individuals with data from 2114 visits (PREDICT-HD) and 686 HD individuals with data from 1482 visits (REGISTRY). Option characteristic curves were generated for UHDRS subscale items in relation to their subscale score. In prHD, overall severity of motor signs was low, and participants had scores of 2 or above on very few items. In HD, motor items that assessed ocular pursuit, saccade initiation, finger tapping, tandem walking, and to a lesser extent, saccade velocity, dysarthria, tongue protrusion, pronation/supination, Luria, bradykinesia, choreas, gait, and balance on the retropulsion test were found to discriminate individual differences across a broad range of motor severity. In prHD, depressed mood, anxiety, and irritable behavior demonstrated good discriminative properties. In HD, depressed mood demonstrated a good relationship with the overall behavioral score. These data suggest that at least some UHDRS items appear to have utility across a broad range of severity, although many items demonstrate problematic features.
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Background: Medication errors are common in primary care and are associated with considerable risk of patient harm. We tested whether a pharmacist-led, information technology-based intervention was more effective than simple feedback in reducing the number of patients at risk of measures related to hazardous prescribing and inadequate blood-test monitoring of medicines 6 months after the intervention. Methods: In this pragmatic, cluster randomised trial general practices in the UK were stratified by research site and list size, and randomly assigned by a web-based randomisation service in block sizes of two or four to one of two groups. The practices were allocated to either computer-generated simple feedback for at-risk patients (control) or a pharmacist-led information technology intervention (PINCER), composed of feedback, educational outreach, and dedicated support. The allocation was masked to general practices, patients, pharmacists, researchers, and statisticians. Primary outcomes were the proportions of patients at 6 months after the intervention who had had any of three clinically important errors: non-selective non-steroidal anti-inflammatory drugs (NSAIDs) prescribed to those with a history of peptic ulcer without co-prescription of a proton-pump inhibitor; β blockers prescribed to those with a history of asthma; long-term prescription of angiotensin converting enzyme (ACE) inhibitor or loop diuretics to those 75 years or older without assessment of urea and electrolytes in the preceding 15 months. The cost per error avoided was estimated by incremental cost-eff ectiveness analysis. This study is registered with Controlled-Trials.com, number ISRCTN21785299. Findings: 72 general practices with a combined list size of 480 942 patients were randomised. At 6 months’ follow-up, patients in the PINCER group were significantly less likely to have been prescribed a non-selective NSAID if they had a history of peptic ulcer without gastroprotection (OR 0∙58, 95% CI 0∙38–0∙89); a β blocker if they had asthma (0∙73, 0∙58–0∙91); or an ACE inhibitor or loop diuretic without appropriate monitoring (0∙51, 0∙34–0∙78). PINCER has a 95% probability of being cost eff ective if the decision-maker’s ceiling willingness to pay reaches £75 per error avoided at 6 months. Interpretation: The PINCER intervention is an effective method for reducing a range of medication errors in general practices with computerised clinical records. Funding: Patient Safety Research Portfolio, Department of Health, England.