899 resultados para Fit quantification


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Using diffusion tensor tractography, we quantified the microstructural changes in the association, projection, and commissural compact white matter pathways of the human brain over the lifespan in a cohort of healthy right-handed children and adults aged 6-68 years. In both males and females, the diffusion tensor radial diffusivity of the bilateral arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, corticospinal, somatosensory tracts, and the corpus callosum followed a U-curve with advancing age; fractional anisotropy in the same pathways followed an inverted U-curve. Our study provides useful baseline data for the interpretation of data collected from patients.

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We enlarge the notion of institutional fit using theoretical approaches from New Institutionalism, including rational choice and strategic action, political ecology and constructivist approaches. These approaches are combined with ecological approaches (system and evolutionary ecology) focusing on feedback loops and change. We offer results drawn from a comparison of fit and misfit cases of institutional change in pastoral commons in four African floodplain contexts (Zambia, Cameroon, Tanzania (two cases). Cases of precolonial fit and misfit in the postcolonial past, as well as a case of institutional fit in the postcolonial phase, highlight important features, specifically, flexible institutions, leadership, and mutual economic benefit under specific relations of bargaining power of actors. We argue that only by combining otherwise conflicting approaches can we come to understand why institutional fit develops into misfit and back again. Key Words: African floodplains; governance; institutional change; institutional fit; New Institutionalism; pastoral commons

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The objective of this study was to determine if area measurements of pleural fluid on computed tomography (CT) reflect the actual pleural fluid volume (PEvol) as measured at autopsy, to establish a formula to estimate the volume of pleural effusion (PEest), and to test the accuracy and observer reliability of PEest.132 human cadavers, with pleural effusion were divided into phase 1 (n = 32) and phase 2 (n = 100). In phase 1, PEvol was compared to area measurements on axial (axA), sagittal (sagA), and coronal (corA) CT images. Linear regression analysis was used to create a formula to calculate PEest. In phase 2, intra-class correlation (ICC) was used to assess inter-reader reliability and determine the agreement between PEest and PEvol. PEvol correlated to a higher degree to axA (r s mean = 0.738; p < 0.001) than to sagA (r s mean = 0.679, p < 0.001) and corA (r s mean = 0.709; p < 0.001). PEest can be established with the following formula: axA × 0.1 = PEest. Mean difference between PEest and PEvol was less than 40 mL (ICC = 0.837-0.874; p < 0.001). Inter-reader reliability was higher between two experienced readers (ICC = 0.984-0.987; p < 0.001) than between an inexperienced reader and both experienced readers (ICC = 0.660-0.698; p < 0.001). Pleural effusions may be quantified in a rapid, reliable, and reasonably accurate fashion using single area measurements on CT.

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Rice has the predilection to take up arsenic in the form of methylated arsenic (o-As) and inorganic arsenic species (i-As). Plants defend themselves using i-As efflux systems and the production of phytochelatins (PCs) to complex i-As. Our study focused on the identification and quantification of phytochelatins by HPLC-ICP-MS/ESI-MS, relating them to the several variables linked to As exposure. GSH, 11 PCs, and As–PC complexes from the roots of six rice cultivars (Italica Carolina, Dom Sofid, 9524, Kitrana 508, YRL-1, and Lemont) exposed to low and high levels of i-As were compared with total, i-As, and o-As in roots, shoots, and grains. Only Dom Sofid, Kitrana 508, and 9524 were found to produce higher levels of PCs even when exposed to low levels of As. PCs were only correlated to i-As in the roots (r=0.884, P <0.001). However, significant negative correlations to As transfer factors (TF) roots–grains (r= –0.739, P <0.05) and shoots–grains (r= –0.541, P <0.05), suggested that these peptides help in trapping i-As but not o-As in the roots, reducing grains’ i-As. Italica Carolina reduced i-As in grains after high exposure, where some specific PCs had a special role in this reduction. In Lemont, exposure to elevated levels of i-As did not result in higher i-As levels in the grains and there were no significant increases in PCs or thiols. Finally, the high production of PCs in Kitrana 508 and Dom Sofid in response to high As treatment did not relate to a reduction of i-As in grains, suggesting that other mechanisms such as As–PC release and transport seems to be important in determining grain As in these cultivars.

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Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

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In this study, the development of a new sensitive method for the analysis of alpha-dicarbonyls glyoxal (G) and methylglyoxal (MG) in environmental ice and snow is presented. Stir bar sorptive extraction with in situ derivatization and liquid desorption (SBSE-LD) was used for sample extraction, enrichment, and derivatization. Measurements were carried out using high-performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). As part of the method development, SBSE-LD parameters such as extraction time, derivatization reagent, desorption time and solvent, and the effect of NaCl addition on the SBSE efficiency as well as measurement parameters of HPLC-ESI-MS/MS were evaluated. Calibration was performed in the range of 1–60 ng/mL using spiked ultrapure water samples, thus incorporating the complete SBSE and derivatization process. 4-Fluorobenzaldehyde was applied as internal standard. Inter-batch precision was <12 % RSD. Recoveries were determined by means of spiked snow samples and were 78.9 ± 5.6 % for G and 82.7 ± 7.5 % for MG, respectively. Instrumental detection limits of 0.242 and 0.213 ng/mL for G and MG were achieved using the multiple reaction monitoring mode. Relative detection limits referred to a sample volume of 15 mL were 0.016 ng/mL for G and 0.014 ng/mL for MG. The optimized method was applied for the analysis of snow samples from Mount Hohenpeissenberg (close to the Meteorological Observatory Hohenpeissenberg, Germany) and samples from an ice core from Upper Grenzgletscher (Monte Rosa massif, Switzerland). Resulting concentrations were 0.085–16.3 ng/mL for G and 0.126–3.6 ng/mL for MG. Concentrations of G and MG in snow were 1–2 orders of magnitude higher than in ice core samples. The described method represents a simple, green, and sensitive analytical approach to measure G and MG in aqueous environmental samples.

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Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

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An HPLC-DAD method for the quantitative analysis of Δ(9)-tetrahydrocannabinol (THC), Δ(9)-tetrahydrocannabinolic acid-A (THCA-A), cannabidiol (CBD), and cannabinol (CBN) in confiscated cannabis products has been developed, fully validated and applied to analyse seized cannabis products. For determination of the THC content of plant material, this method combines quantitation of THCA-A, which is the inactive precursor of THC, and free THC. Plant material was dried, homogenized and extracted with methanol by ultrasonication. Chromatographic separation was achieved with a Waters Alliance 2695 HPLC equipped with a Merck LiChrospher 60 RP-Select B (5μm) precolumn and a Merck LiChroCart 125-4 LiChrospher 60 RP-Select B (5μm) analytical column. Analytes were detected and quantified using a Waters 2996 photo diode array detector. This method has been accepted by the public authorities of Switzerland (Bundesamt für Gesundheit, Federal Office of Public Health), and has been used to analyse 9092 samples since 2000. Since no thermal decarboxylation of THCA-A occurs, the method is highly reproducible for different cannabis materials. Two calibration ranges are used, a lower one for THC, CBN and CBD, and a higher one for THCA-A, due to its dominant presence in fresh plant material. As provider of the Swiss proficiency test, the robustness of this method has been tested over several years, and homogeneity tests even in the low calibration range (1%) show high precision (RSD≤4.3%, except CBD) and accuracy (bias≤4.1%, except CBN).

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Leptospirosis is a global zoonotic disease. Pathogenic Leptospira species, the causative agent of leptospirosis, colonize the renal tubules of chronically infected maintenance hosts such as dogs, rats and cattle. Maintenance hosts typically remain clinically asymptomatic and shed leptospires into the environment via urine. In contrast, accidental hosts such as humans can suffer severe acute forms of the disease. Infection results from direct contact with infected urine or indirectly, through contaminated water sources. In this study, a quantitative real-time PCR specific for lipL32 was designed to detect the urinary shedding of leptospires from dogs. The sensitivity and specificity of the assay was evaluated using both a panel of pathogenic Leptospira species and clinical microbial isolates, and samples of urine collected from experimentally infected rats and non-infected controls. The lower limit of detection was approximately 3 genome equivalents per reaction. The assay was applied to canine urine samples collected from local dog sanctuaries and the University Veterinary Hospital (UVH) at University College Dublin. Of 525 canine urine samples assayed, 37 were positive, indicating a prevalence of urinary shedding of leptospires of 7.05%. These results highlight the need to provide effective canine vaccination strategies and raise public health awareness.