998 resultados para Variability Modeling


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The effective dose delivered to the patient was determined, by modeling, for 257 types of examinations covering the different modalities of diagnostic and interventional radiology. The basic operational dosimetric quantities considered were obtained from the parameters of the examinations on the basis of dosimetric models. These models required a precise characterization of each examination. The operational dosimetric quantities were converted into doses to organs and effective doses using appropriate conversion factors. The determination of the collective effective dose to the Swiss population requires a number of corrections to account for the variability of several parameters: sensitivity of the detection system, age, gender, and build of the patient. The use of various dosimetric models is illustrated in this paper for a limited number of examination types covering the different radiological modalities, for which the established typical effective doses are given. With regard to individual doses, the study indicated that the average effective doses per type of examination can be classified into three levels: (a) the weakly irradiating examinations (less than 0.1 mSv), which represent 78% of the examinations and 4% of the collective dose, (b) the moderately irradiating examinations (between 0.1 mSv and 10 mSv), which represent 21% of the examinations and 72% of the collective dose, (c) the strongly irradiating examinations (more than 10 mSv), which represent 1% of the examinations and 24% of the collective dose.

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Cork is the bark of the cork oak tree (Quercus suber L), a renewable and biodegradable raw bioresource concentrated mainly in the Mediterranean region. Development of its potential uses as a biosorbent will require the investigation of its chemical composition; such information can be of help to understand its interactions with organic pollutants. The present study investigates the summative chemical composition of three bark layers (back, cork, and belly) of five Spanish cork samples and one cork sample from Portugal. Suberin was the main component in all the samples (21.1 to 53.1%), followed by lignin (14.8 to 31%), holocellulose (2.3 to 33.6%), extractives (7.3 to 20.4%), and ash (0.4 to 3.3%). The Kruskal-Wallis test was used to determine whether the variations in chemical composition with respect to the production area and bark layers were significant. The results indicate that, with respect to the bark layer, significant differences were found only for suberin and holocellulose contents: they were higher in the belly and cork than in the back. Based on the results presented, cork is a material with a lot of potential because of its heterogeneity in chemical composition

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Waveform-based tomographic imaging of crosshole georadar data is a powerful method to investigate the shallow subsurface because of its ability to provide images of electrical properties in near-surface environments with unprecedented spatial resolution. A critical issue with waveform inversion is the a priori unknown source signal. Indeed, the estimation of the source pulse is notoriously difficult but essential for the effective application of this method. Here, we explore the viability and robustness of a recently proposed deconvolution-based procedure to estimate the source pulse during waveform inversion of crosshole georadar data, where changes in wavelet shape with location as a result of varying near-field conditions and differences in antenna coupling may be significant. Specifically, we examine whether a single, average estimated source current function can adequately represent the pulses radiated at all transmitter locations during a crosshole georadar survey, or whether a separate source wavelet estimation should be performed for each transmitter gather. Tests with synthetic and field data indicate that remarkably good tomographic reconstructions can be obtained using a single estimated source pulse when moderate to strong variability exists in the true source signal with antenna location. Only in the case of very strong variability in the true source pulse are tomographic reconstructions clearly improved by estimating a different source wavelet for each transmitter location.

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The spatial variability of strongly weathered soils under sugarcane and soybean/wheat rotation was quantitatively assessed on 33 fields in two regions in São Paulo State, Brazil: Araras (15 fields with sugarcane) and Assis (11 fields with sugarcane and seven fields with soybean/wheat rotation). Statistical methods used were: nested analysis of variance (for 11 fields), semivariance analysis and analysis of variance within and between fields. Spatial levels from 50 m to several km were analyzed. Results are discussed with reference to a previously published study carried out in the surroundings of Passo Fundo (RS). Similar variability patterns were found for clay content, organic C content and cation exchange capacity. The fields studied are quite homogeneous with respect to these relatively stable soil characteristics. Spatial variability of other characteristics (resin extractable P, pH, base- and Al-saturation and also soil colour), varies with region and, or land use management. Soil management for sugarcane seems to have induced modifications to greater depths than for soybean/wheat rotation. Surface layers of soils under soybean/wheat present relatively little variation, apparently as a result of very intensive soil management. The major part of within-field variation occurs at short distances (< 50 m) in all study areas. Hence, little extra information would be gained by increasing sampling density from, say, 1/km² to 1/50 m². For many purposes, the soils in the study regions can be mapped with the same observation density, but residual variance will not be the same in all areas. Bulk sampling may help to reveal spatial patterns between 50 and 1.000 m.

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The quality of semi-detailed (scale 1:100.000) soil maps and the utility of a taxonomically based legend were assessed by studying 33 apparently homogeneous fields with strongly weathered soils in two regions in São Paulo State: Araras and Assis. An independent data set of 395 auger sites was used to determine purity of soil mapping units and analysis of variance within and between mapping units and soil classification units. Twenty three soil profiles were studied in detail. The studied soil maps have a high purity for some legend criteria, such as B horizon type (> 90%) and soil texture class (> 80%). The purity for the "trophic character" (eutrophic, dystrophic, allic) was only 55% in Assis. It was 88% in Araras, where many soil units had been mapped as associations. In both regions, the base status of clay-textured soils was generally better than suggested by the maps. Analysis of variance showed that mapping was successful for "durable" soil characteristics such as clay content (> 80% of variance explained) and cation exchange capacity (≥ 50% of variance explained) of 0-20 and 60-80 cm layers. For soil characteristics that are easily modified by management, such as base saturation of the 0-20 cm layer, the maps had explained very little (< 15%) of the total variance in the study areas. Intermediate results were obtained for base saturation of the 60-80 cm layer (56% in Assis; 42% in Araras). Variance explained by taxonomic groupings that formed the basis for the legend of the soil maps was similar to, often even smaller than, variance explained by mapping units. The conclusion is that map boundaries have been very carefully located, but descriptions of mapping units could be improved. In future mappings, this could possibly be done at low cost by (a) bulk sampling to remove short range variation and enhance visualization of spatial patterns at distances > 100 m; (b) taking advantage of correlations between easily measured soil characteristics and chemical soil properties and, (c) unbending the link between legend criteria and a taxonomic system. The maps are well suited to obtain an impression of land suitability for high-input farming. Additional field work and data on former land use/management are necessary for the evaluation of chemical properties of surface horizons.

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Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

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Although all brain cells bear in principle a comparable potential in terms of energetics, in reality they exhibit different metabolic profiles. The specific biochemical characteristics explaining such disparities and their relative importance are largely unknown. Using a modeling approach, we show that modifying the kinetic parameters of pyruvate dehydrogenase and mitochondrial NADH shuttling within a realistic interval can yield a striking switch in lactate flux direction. In this context, cells having essentially an oxidative profile exhibit pronounced extracellular lactate uptake and consumption. However, they can be turned into cells with prominent aerobic glycolysis by selectively reducing the aforementioned parameters. In the case of primarily oxidative cells, we also examined the role of glycolysis and lactate transport in providing pyruvate to mitochondria in order to sustain oxidative phosphorylation. The results show that changes in lactate transport capacity and extracellular lactate concentration within the range described experimentally can sustain enhanced oxidative metabolism upon activation. Such a demonstration provides key elements to understand why certain brain cell types constitutively adopt a particular metabolic profile and how specific features can be altered under different physiological and pathological conditions in order to face evolving energy demands.

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PURPOSE: To assess tobacco, alcohol, cannabis and benzodiazepine use in methadone maintenance treatment (MMT) as potential sources of variability in methadone pharmacokinetics. METHODS: Trough plasma (R)- and (S)-methadone concentrations were measured on 77 Australian and 74 Swiss MMT patients with no additional medications other than benzodiazepines. Simple and multiple regression analyses were performed for the primary metric, plasma methadone concentration/dose. RESULTS: Cannabis and methadone dose were significantly associated with lower 24-h plasma (R)- and (S)-methadone concentrations/dose. The models containing these variables explained 14-16% and 17-25% of the variation in (R)- and (S)-methadone concentration/dose, respectively. Analysis of 61 patients using only CYP3A4 metabolised benzodiazepines showed this class to be associated with higher (R)-concentration/dose, which is consistent with a potential competitive inhibition of CYP3A4. CONCLUSION: Cannabis use and higher methadone doses in MMT could in part be a response to-or a cause of-more rapid methadone clearance. The effects of cannabis and benzodiazepines should be controlled for in future studies on methadone pharmacokinetics in MMT.

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BACKGROUND: Protein-energy malnutrition is highly prevalent in aged populations. Associated clinical, economic, and social burden is important. A valid screening method that would be robust and precise, but also easy, simple, and rapid to apply, is essential for adequate therapeutic management. OBJECTIVES: To compare the interobserver variability of 2 methods measuring food intake: semiquantitative visual estimations made by nurses versus calorie measurements performed by dieticians on the basis of standardized color digital photographs of servings before and after consumption. DESIGN: Observational monocentric pilot study. SETTING/PARTICIPANTS: A geriatric ward. The meals were randomly chosen from the meal tray. The choice was anonymous with respect to the patients who consumed them. MEASUREMENTS: The test method consisted of the estimation of calorie consumption by dieticians on the basis of standardized color digital photographs of servings before and after consumption. The reference method was based on direct visual estimations of the meals by nurses. Food intake was expressed in the form of a percentage of the serving consumed and calorie intake was then calculated by a dietician based on these percentages. The methods were applied with no previous training of the observers. Analysis of variance was performed to compare their interobserver variability. RESULTS: Of 15 meals consumed and initially examined, 6 were assessed with each method. Servings not consumed at all (0% consumption) or entirely consumed by the patient (100% consumption) were not included in the analysis so as to avoid systematic error. The digital photography method showed higher interobserver variability in calorie intake estimations. The difference between the compared methods was statistically significant (P < .03). CONCLUSIONS: Calorie intake measures for geriatric patients are more concordant when estimated in a semiquantitative way. Digital photography for food intake estimation without previous specific training of dieticians should not be considered as a reference method in geriatric settings, as it shows no advantages in terms of interobserver variability.

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BACKGROUND: Hyperoxaluria is a major risk factor for kidney stone formation. Although urinary oxalate measurement is part of all basic stone risk assessment, there is no standardized method for this measurement. METHODS: Urine samples from 24-h urine collection covering a broad range of oxalate concentrations were aliquoted and sent, in duplicates, to six blinded international laboratories for oxalate, sodium and creatinine measurement. In a second set of experiments, ten pairs of native urine and urine spiked with 10 mg/L of oxalate were sent for oxalate measurement. Three laboratories used a commercially available oxalate oxidase kit, two laboratories used a high-performance liquid chromatography (HPLC)-based method and one laboratory used both methods. RESULTS: Intra-laboratory reliability for oxalate measurement expressed as intraclass correlation coefficient (ICC) varied between 0.808 [95% confidence interval (CI): 0.427-0.948] and 0.998 (95% CI: 0.994-1.000), with lower values for HPLC-based methods. Acidification of urine samples prior to analysis led to significantly higher oxalate concentrations. ICC for inter-laboratory reliability varied between 0.745 (95% CI: 0.468-0.890) and 0.986 (95% CI: 0.967-0.995). Recovery of the 10 mg/L oxalate-spiked samples varied between 8.7 ± 2.3 and 10.7 ± 0.5 mg/L. Overall, HPLC-based methods showed more variability compared to the oxalate oxidase kit-based methods. CONCLUSIONS: Significant variability was noted in the quantification of urinary oxalate concentration by different laboratories, which may partially explain the differences of hyperoxaluria prevalence reported in the literature. Our data stress the need for a standardization of the method of oxalate measurement.

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This paper describes the application of the Soil and Water Assessment Tool (SWAT) model to the Maquoketa River watershed, located in northeast Iowa. The inputs to the model were obtained from the Environmental Protection Agency’s geographic information/database system called Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). Climatic data from six weather stations located in and around the watershed, and measured streamflow data from a U.S. Geological Survey gage station at the watershed outlet were used in the sensitivity analysis of SWAT model parameters as well as its calibration and validation for watershed hydrology and streamflow. A sensitivity analysis was performed using an influence coefficient method to evaluate surface runoff and base flow variations in response to changes in model input hydrologic parameters. The curve number, evaporation compensation factor, and soil available water capacity were found to be the most sensitive parameters among eight selected parameters when applying SWAT to the Maquoketa River watershed. Model calibration, facilitated by the sensitivity analysis, was performed for the period 1988 through 1993, and validation was performed for 1982 through 1987. The model performance was evaluated by well-established statistical methods and was found to explain at least 86% and 69% of the variability in the measured stream flow data for the calibration and validation periods, respectively. This initial hydrologic modeling analysis will facilitate future applications of SWAT to the Maquoketa River watershed for various watershed analysis, including water quality.

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Based on conclusions drawn from general climatic impact assessment in mountain regions, the review synthesizes results relevant to the European Alps published mainly from 1994 onward in the fields of population genetics, ecophysiology, phenology, phytogeography, modeling, paleoecology and vegetation dynamics. Other important factors of global change interacting synergistically with climatic factors are also mentioned, such as atmospheric CO2 concentration, eutrophication, ozone or changes in land-use. Topics addressed are general species distribution and populations (persistence, acclimation, genetic variability, dispersal, fragmentation, plant/animal interaction, species richness, conservation), potential response of vegetation (ecotonal shift - area, physiography - changes in the composition, structural changes), phenology, growth and productivity, and landscape. In conclusion, the European Alps appear to have a natural inertia and thus to tolerate an increase of 1-2 K of mean air temperature as far as plant species and ecosystems are concerned in general. However, the impact of land-use is very likely to negate this buffer in many areas. For a change of the order of 3 K or more, profound changes may be expected.

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Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.