910 resultados para Automated quantification
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The European Prospective Investigation into Cancer and nutrition (EPIC) is a long-term, multi-centric prospective study in Europe investigating the relationships between cancer and nutrition. This study has served as a basis for a number of Genome-Wide Association Studies (GWAS) and other types of genetic analyses. Over a period of 5 years, 52,256 EPIC DNA samples have been extracted using an automated DNA extraction platform. Here we have evaluated the pre-analytical factors affecting DNA yield, including anthropometric, epidemiological and technical factors such as center of subject recruitment, age, gender, body-mass index, disease case or control status, tobacco consumption, number of aliquots of buffy coat used for DNA extraction, extraction machine or procedure, DNA quantification method, degree of haemolysis and variations in the timing of sample processing. We show that the largest significant variations in DNA yield were observed with degree of haemolysis and with center of subject recruitment. Age, gender, body-mass index, cancer case or control status and tobacco consumption also significantly impacted DNA yield. Feedback from laboratories which have analyzed DNA with different SNP genotyping technologies demonstrate that the vast majority of samples (approximately 88%) performed adequately in different types of assays. To our knowledge this study is the largest to date to evaluate the sources of pre-analytical variations in DNA extracted from peripheral leucocytes. The results provide a strong evidence-based rationale for standardized recommendations on blood collection and processing protocols for large-scale genetic studies.
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Advances in clinical virology for detecting respiratory viruses have been focused on nucleic acids amplification techniques, which have converted in the reference method for the diagnosis of acute respiratory infections of viral aetiology. Improvements of current commercial molecular assays to reduce hands-on-time rely on two strategies, a stepwise automation (semi-automation) and the complete automation of the whole procedure. Contributions to the former strategy have been the use of automated nucleic acids extractors, multiplex PCR, real-time PCR and/or DNA arrays for detection of amplicons. Commercial fully-automated molecular systems are now available for the detection of respiratory viruses. Some of them could convert in point-of-care methods substituting antigen tests for detection of respiratory syncytial virus and influenza A and B viruses. This article describes laboratory methods for detection of respiratory viruses. A cost-effective and rational diagnostic algorithm is proposed, considering technical aspects of the available assays, infrastructure possibilities of each laboratory and clinic-epidemiologic factors of the infection.
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Because of the emergence of dried blood spots (DBS) as an attractive alternative to conventional venous plasma sampling in many pharmaceutical companies and clinical laboratories, different analytical approaches have been developed to enable automated handling of DBS samples without any pretreatment. Associated with selective and sensitive MS-MS detection, these procedures give good results in the rapid identification and quantification of drugs (generally less than 3 min total run time), which is desirable because of the high throughput requirements of analytical laboratories. The objective of this review is to describe the analytical concepts of current direct DBS techniques and to present their advantages and disadvantages, with particular focus on automation capacity and commercial availability. Finally, an overview of the different biomedical applications in which these concepts could be of major interest will be presented.
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The hepatitis C virus (HCV) can be detected in blood and other bodily fluids, such as saliva, semen and gastric juices. The aim of this study was to compare the HCV viral loads in the serum and saliva of infected patients. Twenty-nine patients with detectable HCV RNA in their serum and saliva were included in this study. The HCV viral loads were determined through quantitative real-time polymerase chain reactions. The median viral RNA levels were 5.78 log10 copies in the serum and 3.32 log10 copies in the saliva. We observed that the salivary HCV viral load was significantly lower than the viral load in the serum. Further studies are required to understand the role of saliva in the diagnosis, management and potential transmission of HCV.
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Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.
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Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.
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The accuracy of the MicroScan WalkAway, BD Phoenix, and Vitek-2 systems for susceptibility testing of quinolones and aminoglycosides against 68 enterobacteria containing qnrB, qnrS, and/or aac(6 ')-Ib-cr was evaluated using reference microdilution. Overall, one very major error (0.09%), 6 major errors (0.52%), and 45 minor errors (3.89%) were noted.
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INTRODUCTION: Rivaroxaban (RXA) is licensed for prophylaxis of venous thromboembolism after major orthopaedic surgery of the lower limbs. Currently, no test to quantify RXA in plasma has been validated in an inter-laboratory setting. Our study had three aims: to assess i) the feasibility of RXA quantification with a commercial anti-FXa assay, ii) its accuracy and precision in an inter-laboratory setting, and iii) the influence of 10mg of RXA on routine coagulation tests. METHODS: The same chromogenic anti-FXa assay (Hyphen BioMed) was used in all participating laboratories. RXA calibrators and sets of blinded probes (aim ii.) were prepared in vitro by spiking normal plasma. The precise RXA content was assessed by high-pressure liquid chromatography-tandem mass spectrometry. For ex-vivo studies (aim iii), plasma samples from 20 healthy volunteers taken before and 2 - 3hours after ingestion of 10mg of RXA were analyzed by participating laboratories. RESULTS: RXA can be assayed chromogenically. Among the participating laboratories, the mean accuracy and the mean coefficient of variation for precision of RXA quantification were 7.0% and 8.8%, respectively. Mean RXA concentration was 114±43μg/L .RXA significantly altered prothrombin time, activated partial thromboplastin time, factor analysis for intrinsic and extrinsic factors. Determinations of thrombin time, fibrinogen, FXIII and D-Dimer levels were not affected. CONCLUSIONS: RXA plasma levels can be quantified accurately and precisely by a chromogenic anti-FXa assay on different coagulometers in different laboratories. Ingestion of 10mg RXA results in significant alterations of both PT- and aPTT-based coagulation assays.
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In high hyperdiploid acute lymphoblastic leukemia (ALL), the concurrence of specific trisomies confers a more favorable outcome than hyperdiploidy alone. Interphase fluorescence in situ hybridization (FISH) complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in nondividing cells. To overcome the limits of manual I-FISH, we developed an automated four-color I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10, and 17. Parameters established for nucleus selection and signal detection were evaluated. Cutoff values were determined. Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 patient samples were compared with those obtained with CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed also by I-FISH, and I-FISH revealed numerous additional abnormal clones in all patients, ranging from < or =1% to 31.6% of cells analyzed. We conclude that four-color automated I-FISH permits the identification of concurrent aneuploidies of potential prognostic significance. Large numbers of cells can be analyzed rapidly. The large number of nuclei scored revealed a high level of chromosome variability both at diagnosis and relapse, the prognostic significance of which is of considerable clinical interest and merits further evaluation.
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A fully-automated 3D image analysis method is proposed to segment lung nodules in HRCT. A specific gray-level mathematical morphology operator, the SMDC-connection cost, acting in the 3D space of the thorax volume is defined in order to discriminate lung nodules from other dense (vascular) structures. Applied to clinical data concerning patients with pulmonary carcinoma, the proposed method detects isolated, juxtavascular and peripheral nodules with sizes ranging from 2 to 20 mm diameter. The segmentation accuracy was objectively evaluated on real and simulated nodules. The method showed a sensitivity and a specificity ranging from 85% to 97% and from 90% to 98%, respectively.
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Quantitative analyses of abscisic acid in the elongating zone of a single maize root (Zea mays L. cv LG 11) were performed by gas chromatography-mass spectrometry using negative chemical ion ionization. Data showed that the more abscisic acid, the slower the growth, but a large dispersion of individual values was observed. We assume that abscisic acid is perhaps not correlated only to the growth rate.
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Histology is the gold standard for diagnosing acute rejection and hepatitis C recurrence after liver transplantation. However, differential diagnosis between the two can be difficult. We evaluated the role of C4d staining and quantification of hepatitis C virus (HCV) RNA levels in liver tissue. This was a retrospective study of 98 liver biopsy samples divided into four groups by histological diagnosis: acute rejection in patients undergoing liver transplant for hepatitis C (RejHCV+), HCV recurrence in patients undergoing liver transplant for hepatitis C (HCVTx+), acute rejection in patients undergoing liver transplant for reasons other than hepatitis C and chronic hepatitis C not transplanted (HCVTx-). All samples were submitted for immunohistochemical staining for C4d and HCV RNA quantification. Immunoexpression of C4d was observed in the portal vessels and was highest in the HCVTx- group. There was no difference in C4d expression between the RejHCV+ and HCVTx+ groups. However, tissue HCV RNA levels were higher in the HCVTx+ group samples than in the RejHCV+ group samples. Additionally, there was a significant correlation between tissue and serum levels of HCV RNA. The quantification of HCV RNA in liver tissue might prove to be an efficient diagnostic test for the recurrence of HCV infection.
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Purpose: To develop and evaluate a practical method for the quantification of signal-to-noise ratio (SNR) on coronary MR angiograms (MRA) acquired with parallel imaging.Materials and Methods: To quantify the spatially varying noise due to parallel imaging reconstruction, a new method has been implemented incorporating image data acquisition followed by a fast noise scan during which radio-frequency pulses, cardiac triggering and navigator gating are disabled. The performance of this method was evaluated in a phantom study where SNR measurements were compared with those of a reference standard (multiple repetitions). Subsequently, SNR of myocardium and posterior skeletal muscle was determined on in vivo human coronary MRA.Results: In a phantom, the SNR measured using the proposed method deviated less than 10.1% from the reference method for small geometry factors (<= 2). In vivo, the noise scan for a 10 min coronary MRA acquisition was acquired in 30 s. Higher signal and lower SNR, due to spatially varying noise, were found in myocardium compared with posterior skeletal muscle.Conclusion: SNR quantification based on a fast noise scan is a validated and easy-to-use method when applied to three-dimensional coronary MRA obtained with parallel imaging as long as the geometry factor remains low.
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RATIONALE: The aim of the work was to develop and validate a method for the quantification of vitamin D metabolites in serum using ultra-high-pressure liquid chromatography coupled to mass spectrometry (LC/MS), and to validate a high-resolution mass spectrometry (LC/HRMS) approach against a tandem mass spectrometry (LC/MS/MS) approach using a large clinical sample set. METHODS: A fast, accurate and reliable method for the quantification of the vitamin D metabolites, 25-hydroxyvitamin D2 (25OH-D2) and 25-hydroxyvitamin D3 (25OH-D3), in human serum was developed and validated. The C3 epimer of 25OH-D3 (3-epi-25OH-D3) was also separated from 25OH-D3. The samples were rapidly prepared via a protein precipitation step followed by solid-phase extraction (SPE) using an HLB μelution plate. Quantification was performed using both LC/MS/MS and LC/HRMS systems. RESULTS: Recovery, matrix effect, inter- and intra-day reproducibility were assessed. Lower limits of quantification (LLOQs) were determined for both 25OH-D2 and 25OH-D3 for the LC/MS/MS approach (6.2 and 3.4 µg/L, respectively) and the LC/HRMS approach (2.1 and 1.7 µg/L, respectively). A Passing & Bablok fit was determined between both approaches for 25OH-D3 on 662 clinical samples (1.11 + 1.06x). It was also shown that results can be affected by the inclusion of the isomer 3-epi-25OH-D3. CONCLUSIONS: Quantification of the relevant vitamin D metabolites was successfully developed and validated here. It was shown that LC/HRMS is an accurate, powerful and easy to use approach for quantification within clinical laboratories. Finally, the results here suggest that it is important to separate 3-epi-25OH-D3 from 25OH-D3. Copyright © 2012 John Wiley & Sons, Ltd.