209 resultados para exact methods
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Purpose: To evaluate the diagnostic value and image quality of CT with filtered back projection (FBP) compared with adaptive statistical iterative reconstructed images (ASIR) in body stuffers with ingested cocaine-filled packets.Methods and Materials: Twenty-nine body stuffers (mean age 31.9 years, 3 women) suspected for ingestion of cocaine-filled packets underwent routine-dose 64-row multidetector CT with FBP (120kV, pitch 1.375, 100-300 mA and automatic tube current modulation (auto mA), rotation time 0.7sec, collimation 2.5mm), secondarily reconstructed with 30 % and 60 % ASIR. In 13 (44.83%) out of the body stuffers cocaine-filled packets were detected, confirmed by exact analysis of the faecal content including verification of the number (range 1-25). Three radiologists independently and blindly evaluated anonymous CT examinations (29 FBP-CT and 68 ASIR-CT) for the presence and number of cocaine-filled packets indicating observers' confidence, and graded them for diagnostic quality, image noise, and sharpness. Sensitivity, specificity, area under the receiver operating curve (ROC) Az and interobserver agreement between the 3 radiologists for FBP-CT and ASIR-CT were calculated.Results: The increase of the percentage of ASIR significantly diminished the objective image noise (p<0.001). Overall sensitivity and specificity for the detection of the cocaine-filled packets were 87.72% and 76.15%, respectively. The difference of ROC area Az between the different reconstruction techniques was significant (p= 0.0101), that is 0.938 for FBP-CT, 0.916 for 30 % ASIR-CT, and 0.894 for 60 % ASIR-CT.Conclusion: Despite the evident image noise reduction obtained by ASIR, the diagnostic value for detecting cocaine-filled packets decreases, depending on the applied ASIR percentage.
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The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).
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The generation of an antigen-specific T-lymphocyte response is a complex multi-step process. Upon T-cell receptor-mediated recognition of antigen presented by activated dendritic cells, naive T-lymphocytes enter a program of proliferation and differentiation, during the course of which they acquire effector functions and may ultimately become memory T-cells. A major goal of modern immunology is to precisely identify and characterize effector and memory T-cell subpopulations that may be most efficient in disease protection. Sensitive methods are required to address these questions in exceedingly low numbers of antigen-specific lymphocytes recovered from clinical samples, and not manipulated in vitro. We have developed new techniques to dissect immune responses against viral or tumor antigens. These allow the isolation of various subsets of antigen-specific T-cells (with major histocompatibility complex [MHC]-peptide multimers and five-color FACS sorting) and the monitoring of gene expression in individual cells (by five-cell reverse transcription-polymerase chain reaction [RT-PCR]). We can also follow their proliferative life history by flow-fluorescence in situ hybridization (FISH) analysis of average telomere length. Recently, using these tools, we have identified subpopulations of CD8+ T-lymphocytes with distinct proliferative history and partial effector-like properties. Our data suggest that these subsets descend from recently activated T-cells and are committed to become differentiated effector T-lymphocytes.
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Non-structural protein 2 (NS2) plays an important role in hepatitis C virus (HCV) assembly, but neither the exact contribution of this protein to the assembly process nor its complete structure are known. In this study we used a combination of genetic, biochemical and structural methods to decipher the role of NS2 in infectious virus particle formation. A large panel of NS2 mutations targeting the N-terminal membrane binding region was generated. They were selected based on a membrane topology model that we established by determining the NMR structures of N-terminal NS2 transmembrane segments. Mutants affected in virion assembly, but not RNA replication, were selected for pseudoreversion in cell culture. Rescue mutations restoring virus assembly to various degrees emerged in E2, p7, NS3 and NS2 itself arguing for an interaction between these proteins. To confirm this assumption we developed a fully functional JFH1 genome expressing an N-terminally tagged NS2 demonstrating efficient pull-down of NS2 with p7, E2 and NS3 and, to a lower extent, NS5A. Several of the mutations blocking virus assembly disrupted some of these interactions that were restored to various degrees by those pseudoreversions that also restored assembly. Immunofluorescence analyses revealed a time-dependent NS2 colocalization with E2 at sites close to lipid droplets (LDs) together with NS3 and NS5A. Importantly, NS2 of a mutant defective in assembly abrogates NS2 colocalization around LDs with E2 and NS3, which is restored by a pseudoreversion in p7, whereas NS5A is recruited to LDs in an NS2-independent manner. In conclusion, our results suggest that NS2 orchestrates HCV particle formation by participation in multiple protein-protein interactions required for their recruitment to assembly sites in close proximity of LDs.
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Carbon isotope ratio of androgens in urine specimens is routinely determined to exclude an abuse of testosterone or testosterone prohormones by athletes. Increasing application of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) in the last years for target and systematic investigations on samples has resulted in the demand for rapid sample throughput as well as high selectivity in the extraction process particularly in the case of conspicuous samples. For that purpose, we present herein the complimentary use of an SPE-based assay and an HPLC fractionation method as a two-stage strategy for the isolation of testosterone metabolites and endogenous reference compounds prior to GC/C/IRMS analyses. Assays validation demonstrated acceptable performance in terms of intermediate precision (range: 0.1-0.4 per thousand) and Bland-Altman analyses revealed no significant bias (0.2 per thousand). For further validation of this two-stage analyses strategy, all the specimens (n=124) collected during a major sport event were processed.
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Painful neuromas may follow traumatic nerve injury. We carried out a double-blind controlled trial in which patients with a painful neuroma of the lower limb (n = 20) were randomly assigned to treatment by resection of the neuroma and translocation of the proximal nerve stump into either muscle tissue or an adjacent subcutaneous vein. Translocation into a vein led to reduced intensity of pain as assessed by visual analogue scale (5.8 (SD 2.7) vs 3.8 (SD 2.4); p < 0.01), and improved sensory, affective and evaluative dimensions of pain as assessed by the McGill pain score (33 (SD 18) vs 14 (SD 12); p < 0.01). This was associated with an increased level of activity (p < 0.01) and improved function (p < 0.01). Transposition of the nerve stump into an adjacent vein should be preferred to relocation into muscle.
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This book gives a general view of sequence analysis, the statistical study of successions of states or events. It includes innovative contributions on life course studies, transitions into and out of employment, contemporaneous and historical careers, and political trajectories. The approach presented in this book is now central to the life-course perspective and the study of social processes more generally. This volume promotes the dialogue between approaches to sequence analysis that developed separately, within traditions contrasted in space and disciplines. It includes the latest developments in sequential concepts, coding, atypical datasets and time patterns, optimal matching and alternative algorithms, survey optimization, and visualization. Field studies include original sequential material related to parenting in 19th-century Belgium, higher education and work in Finland and Italy, family formation before and after German reunification, French Jews persecuted in occupied France, long-term trends in electoral participation, and regime democratization. Overall the book reassesses the classical uses of sequences and it promotes new ways of collecting, formatting, representing and processing them. The introduction provides basic sequential concepts and tools, as well as a history of the method. Chapters are presented in a way that is both accessible to the beginner and informative to the expert.
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OBJECTIVE: Postmortem investigations are becoming more and more sophisticated. CT and MRI are already being used in pathology and forensic medicine. In this context, the impact of postmortem angiography increases because of the rapid evaluation of organ-specific vascular patterns, vascular alteration under pathologic and physiologic conditions, and tissue changes induced by artificial and unnatural causes. CONCLUSION: In this article, the advantages and disadvantages of former and current techniques and contrast agents are reviewed.
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OBJECTIVE: To assess total free-living energy expenditure (EE) in Gambian farmers with two independent methods, and to determine the most realistic free-living EE and physical activity in order to establish energy requirements for rural populations in developing countries. DESIGN: In this cross-sectional study two methods were applied at the same time. SETTING: Three rural villages and Dunn Nutrition Centre Keneba, MRC, The Gambia. SUBJECTS: Eight healthy, male subjects were recruited from three rural Gambian villages in the sub-Sahelian area (age: 25 +/- 4y; weight: 61.2 +/- 10.1 kg; height: 169.5 +/- 6.5 cm, body mass index: 21.2 +/- 2.5 kg/m2). INTERVENTION: We assessed free-living EE with two inconspicuous and independent methods: the first one used doubly labeled water (DLW) (2H2 18O) over a period of 12 days, whereas the second one was based on continuous heart rate (HR) measurements on two to three days using individual regression lines (HR vs EE) established by indirect calorimetry in a respiration chamber. Isotopic dilution of deuterium (2H2O) was also used to assess total body water and hence fat-free mass (FFM). RESULTS: EE assessed by DLW was found to be 3880 +/- 994 kcal/day (16.2 +/- 4.2 MJ/day). Expressed per unit body weight the EE averaged 64.2 +/- 9.3 kcal/kg/d (269 +/- 38 kJ/kg/d). These results were consistent with the EE results assessed by HR: 3847 +/- 605 kcal/d (16.1 +/- 2.5 MJ/d) or 63.4 +/- 8.2 kcal/kg/d (265 +/- 34kJ/kg/d). Physical activity index, expressed as a multiple of basal metabolic rate (BMR), averaged 2.40 +/- 0.41 (DLW) or 2.40 +/- 0.28 (HR). CONCLUSIONS: These findings suggest an extremely high level of physical activity in Gambian men during intense agricultural work (wet season). This contrasts with the relative food shortage, previously reported during the harvesting period. We conclude that the assessment of EE during the agricultural season in non-industrialized countries needs further investigations in order to obtain information on the energy requirement of these populations. For this purpose the use of the DLW and HR methods have been shown to be useful and complementary.
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This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.
Exact asymptotics and limit theorems for supremum of stationary chi-processes over a random interval
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When requesting a blood level measurement in the context of "Therapeutic drug monitoring" (TDM), numerous aspects have to be considered in the pre-analytical and analytical area, as in the integration of associated clinical data. This review presents therapeutic classes for which a clinical benefit of TDM is established or suggested, at least in some settings. For each class of drugs, the main pharmacokinetic, pre-analytical, analytical and clinical aspects are evaluated in the scope of such a monitoring. Each step of the TDM process is important and none should be neglected. Additional clinical trials are however warranted to better establish the exact conditions of use for such a monitoring.
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Objectives: The aim of this study was to assess the concomitant perioperative procedures, the causes of nasolacrimal duct obstruction, the success rate, and the complications associated with endonasal dacryocystorhinostomy (ENDCR).Methods: In this single-center retrospective study, 98 patients underwent 104 ENDCRs between January 1994 and February 2006. There were 78 patients with 84 nasolacrimal duct obstructions who were included in this study.Results: The overall functional success rate with improvement in symptoms was 94.9% for primary surgery (59 of 84 obstructions) and 63.6% for salvage surgery after failure of primary surgery performed in another hospital (25 of 84 obstructions). The mean follow-up time was 36.8 +/- 17.11 months. Primary surgery showed better results, with a complete success rate of 93.2%, than did salvage surgery, with a success rate of only 68%. Persistent symptoms, despite an open rhinostomy, were found in 1.7% of patients with primary surgery and in 12% of those with salvage surgery. Failure of ENDCR was observed in 3.4% of patients after primary surgery and in 20% after salvage surgery. We encountered only minimal perioperative complications, and these were essentially related to lacrimal intubation.Conclusions: Because of the possibility of treating concomitant sinonasal disorders, the cosmetic advantages, and the excellent results, ENDCR represents the procedure of choice for treating nasolacrimal duct obstructions. The main challenge lies in the exact preoperative assessment, as well as postoperative evaluation in case of failure.
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Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.