941 resultados para INDIRECT QUANTIFICATION


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OBJECTIVES To investigate and correct the temperature dependence of postmortem MR quantification used for soft tissue characterization and differentiation in thoraco-abdominal organs. MATERIAL AND METHODS Thirty-five postmortem short axis cardiac 3-T MR examinations were quantified using a quantification sequence. Liver, spleen, left ventricular myocardium, pectoralis muscle and subcutaneous fat were analysed in cardiac short axis images to obtain mean T1, T2 and PD tissue values. The core body temperature was measured using a rectally inserted thermometer. The tissue-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. RESULTS In a 3D plot comprising the combined data of T1, T2 and PD, different organs/tissues could be well differentiated from each other. The quantitative values were influenced by the temperature. T1 in particular exhibited strong temperature dependence. The correction of quantitative values to a temperature of 37 °C resulted in better tissue discrimination. CONCLUSION Postmortem MR quantification is feasible for soft tissue discrimination and characterization of thoraco-abdominal organs. This provides a base for computer-aided diagnosis and detection of tissue lesions. The temperature dependence of the T1 values challenges postmortem MR quantification. Equations to correct for the temperature dependence are provided. KEY POINTS • Postmortem MR quantification is feasible for soft tissue discrimination and characterization • Temperature dependence of the T1 values challenges the MR quantification approach • The results provide the basis for computer-aided postmortem MRI diagnosis • Diagnostic criteria may also be applied for living patients.

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With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

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BACKGROUND Flavobacterium psychrophilum is the agent of Bacterial Cold Water Disease and Rainbow Trout Fry Syndrome, two diseases leading to high mortality. Pathogen detection is mainly carried out using cultures and more rapid and sensitive methods are needed. RESULTS We describe a qPCR technique based on the single copy gene β' DNA-dependent RNA polymerase (rpoC). Its detection limit was 20 gene copies and the quantification limit 103 gene copies per reaction. Tests on spiked spleens with known concentrations of F. psychrophilum (106 to 101 cells per reaction) showed no cross-reactions between the spleen tissue and the primers and probe. Screening of water samples and spleens from symptomless and infected fishes indicated that the pathogen was already present before the outbreaks, but F. psychrophilum was only quantifiable in spleens from diseased fishes. CONCLUSIONS This qPCR can be used as a highly sensitive and specific method to detect F. psychrophilum in different sample types without the need for culturing. qPCR allows a reliable detection and quantification of F. psychrophilum in samples with low pathogen densities. Quantitative data on F. psychrophilum abundance could be useful to investigate risk factors linked to infections and also as early warning system prior to potential devastating outbreak.

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Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

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The aim of the present study was to analyze if and how career adaptability reduces different types of insecurity. More specifically, we argue in a theoretical model at the intersection of career and organizational research that perceived internal and external marketability serve as connecting variables in the link between career adaptability and job and career insecurity. We tested our assumptions by means of multiple indirect effects path analyses across two measurement points (6 month timespan) with data from 142 university researchers working in the STEM fields. The results showed that career adaptability was positively related to perceived internal and external marketability, which both subsequently were negatively associated with job and career insecurity. We draw theoretical implications for career research in intra- and extraorganizational settings and discuss practical implications for fostering secure employment.

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Supervisor support, peer support and transfer motivation have been identified as important predictors for training transfer. Transfer motivation is supposed to mediate the support–training transfer relationship. Especially after team training interventions that include all team members (i.e., intact-team training), individual perception of these factors might be shared among team members. However, an integration of the team level in the training transfer process is rare, yet still needed. Analyzing 194 employees from 34 teams in the context of intact-team training interventions, we found similar relationships and processes at both levels of analysis: Social support enhances transfer motivation at the individual and team levels. Furthermore, motivation to transfer increases training transfer and serves as a connecting mechanism in the social support–training transfer link. The results underline the importance of (1) considering multiple levels in theories and research about the training transfer process and (2) ensuring the practice of individual-directed support and a shared, supportive climate within teams.

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The twenty-first century has seen a further dramatic increase in the use of quantitative knowledge for governing social life after its explosion in the 1980s. Indicators and rankings play an increasing role in the way governmental and non-governmental organizations distribute attention, make decisions, and allocate scarce resources. Quantitative knowledge promises to be more objective and straightforward as well as more transparent and open for public debate than qualitative knowledge, thus producing more democratic decision-making. However, we know little about the social processes through which this knowledge is constituted nor its effects. Understanding how such numeric knowledge is produced and used is increasingly important as proliferating technologies of quantification alter modes of knowing in subtle and often unrecognized ways. This book explores the implications of the global multiplication of indicators as a specific technology of numeric knowledge production used in governance. Combination of insights from anthropology of law, history of science, science and technology studies, sociology of quantification, economics and geography will appeal to those who are uncomfortable with the separation between 'theoretical' and 'empirical' approaches and with the current weakness of critique that address the main trends shaping the relations between capitalism, markets, law and democracy Theoretical discussion of the nature and historical formation of quantification will appeal to those who ask questions such as, 'What is new or different about our contemporary reliance on quantitative knowledge?' Groundbreaking empirical case studies uncover the social work and politics that often go into the making of indicators and explore the far-reaching effects and impacts of these numerical representations in specific settings

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The effects of tetrahydrocannabinol (THC) and endogenous cannabinoids (endocannabinoids, ECs) are both mediated by activation of the cannabinoid receptors CB1 and CB2. Exogenous activation of these receptors by THC could therefore alter EC levels. We tested this hypothesis in healthy volunteers (n = 25) who received a large intravenous dose of THC (0.10 mg/kg). Effects on the EC system were quantified by serial measurements of plasma ECs after THC administration. Eleven blood samples were drawn during the first 5 h after THC administration and two more samples after 24 and 48 h. THC, its metabolites THC-OH (biologically active) and THC-COOH (non-active), and the ECs anandamide and 2-arachidonoylglycerol (2-AG) were quantified by liquid chromatography-mass spectrometry. EC-plasma levels showed a biphasic response after THC injection reaching maximal values at 30 min. Anandamide increased slightly from 0.58 ± 0.21 ng/ml at baseline to 0.64 ± 0.24 ng/ml (p < 0.05) and 2-AG from 7.60 ± 4.30 ng/ml to 9.50 ± 5.90 ng/ml (p < 0.05). After reaching maximal concentrations, EC plasma levels decreased markedly to a nadir of 300 min after THC administration (to 0.32 ± 0.15 ng/ml for anandamide and to 5.50 ± 3.01 ng/ml for 2-AG, p < 0.05). EC plasma concentrations returned to near baseline levels until 48 h after the experiment. THC (0.76 ± 0.16 ng/ml) and THC-OH (0.36 ± 0.17 ng/ml) were still measurable at 24 h and remained detectible until 48 h after THC administration. Although the underlying mechanism is not clear, high doses of intravenous THC appear to influence endogenous cannabinoid concentrations and presumably EC-signalling.

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Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.