999 resultados para Enrichment methods
Resumo:
Proteomics has come a long way from the initial qualitative analysis of proteins present in a given sample at a given time ("cataloguing") to large-scale characterization of proteomes, their interactions and dynamic behavior. Originally enabled by breakthroughs in protein separation and visualization (by two-dimensional gels) and protein identification (by mass spectrometry), the discipline now encompasses a large body of protein and peptide separation, labeling, detection and sequencing tools supported by computational data processing. The decisive mass spectrometric developments and most recent instrumentation news are briefly mentioned accompanied by a short review of gel and chromatographic techniques for protein/peptide separation, depletion and enrichment. Special emphasis is placed on quantification techniques: gel-based, and label-free techniques are briefly discussed whereas stable-isotope coding and internal peptide standards are extensively reviewed. Another special chapter is dedicated to software and computing tools for proteomic data processing and validation. A short assessment of the status quo and recommendations for future developments round up this journey through quantitative proteomics.
Resumo:
Highway noise is one of the most pressing of the surface characteristics issues facing the concrete paving industry. This is particularly true in urban areas, where not only is there a higher population density near major thoroughfares, but also a greater volume of commuter traffic (Sandberg and Ejsmont 2002; van Keulen 2004). To help address this issue, the National Concrete Pavement Technology Center (CP Tech Center) at Iowa State University (ISU), Federal Highway Administration (FHWA), American Concrete Pavement Association (ACPA), and other organizations have partnered to conduct a multi-part, seven-year Concrete Pavement Surface Characteristics Project. This document contains the results of Part 1, Task 2, of the ISU-FHWA project, addressing the noise issue by evaluating conventional and innovative concrete pavement noise reduction methods. The first objective of this task was to determine what if any concrete surface textures currently constructed in the United States or Europe were considered quiet, had long-term friction characteristics, could be consistently built, and were cost effective. Any specifications of such concrete textures would be included in this report. The second objective was to determine whether any promising new concrete pavement surfaces to control tire-pavement noise and friction were in the development stage and, if so, what further research was necessary. The final objective was to identify measurement techniques used in the evaluation.
Resumo:
Integrative review (IR) has an international reputation in nursing research and evidence-based practice. This IR aimed at identifying and analyzing the concepts and methods recommended to undertaking IR in nursing. Nine information resources,including electronic databases and grey literature were searched. Seventeen studies were included. The results indicate that: primary studies were mostly from USA; it is possible to have several research questions or hypotheses and include primary studies in the review from different theoretical and methodological approaches; it is a type of review that can go beyond the analysis and synthesis of findings from primary studies allowing exploiting other research dimensions, and that presents potentialities for the development of new theories and new problems for research. Conclusion: IR is understood as a very complex type of review and it is expected to be developed using standardized and systematic methods to ensure the required rigor of scientific research and therefore the legitimacy of the established evidence.
Resumo:
Identification of post-translational modifications of proteins in biological samples often requires access to preanalytical purification and concentration methods. In the purification step high or low molecular weight substances can be removed by size exclusion filters, and high abundant proteins can be removed, or low abundant proteins can be enriched, by specific capturing tools. In this paper is described the experience and results obtained with a recently emerged and easy-to-use affinity purification kit for enrichment of the low amounts of EPO found in urine and plasma specimens. The kit can be used as a pre-step in the EPO doping control procedure, as an alternative to the commonly used ultrafiltration, for detecting aberrantly glycosylated isoforms. The commercially available affinity purification kit contains small disposable anti-EPO monolith columns (6 ?L volume, Ø7 mm, length 0.15 mm) together with all required buffers. A 24-channel vacuum manifold was used for simultaneous processing of samples. The column concentrated EPO from 20 mL urine down to 55 ?L eluate with a concentration factor of 240 times, while roughly 99.7% of non-relevant urine proteins were removed. The recoveries of Neorecormon (epoetin beta), and the EPO analogues Aranesp and Mircera applied to buffer were high, 76%, 67% and 57%, respectively. The recovery of endogenous EPO from human urine was 65%. High recoveries were also obtained when purifying human, mouse and equine EPO from serum, and human EPO from cerebrospinal fluid. Evaluation with the accredited EPO doping control method based on isoelectric focusing (IEF) showed that the affinity purification procedure did not change the isoform distribution for rhEPO, Aranesp, Mircera or endogenous EPO. The kit should be particularly useful for applications in which it is essential to avoid carry-over effects, a problem commonly encountered with conventional particle-based affinity columns. The encouraging results with EPO propose that similar affinity monoliths, with the appropriate antibodies, should constitute useful tools for general applications in sample preparation, not only for doping control of EPO and other hormones such as growth hormone and insulin but also for the study of post-translational modifications of other low abundance proteins in biological and clinical research, and for sample preparation prior to in vitro diagnostics.
Resumo:
Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays
Resumo:
Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.
Resumo:
Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.
Resumo:
This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.
Resumo:
The paper contrasts empirically the results of alternative methods for estimating thevalue and the depreciation of mineral resources. The historical data of Mexico andVenezuela, covering the period 1920s-1980s, is used to contrast the results of severalmethods. These are the present value, the net price method, the user cost method andthe imputed income method. The paper establishes that the net price and the user costare not competing methods as such, but alternative adjustments to different scenariosof closed and open economies. The results prove that the biases of the methods, ascommonly described in the theoretical literature, only hold under the most restrictedscenario of constant rents over time. It is argued that the difference between what isexpected to happen and what actually did happen is for the most part due to a missingvariable, namely technological change. This is an important caveat to therecommendations made based on these models.
Resumo:
Consider the problem of testing k hypotheses simultaneously. In this paper,we discuss finite and large sample theory of stepdown methods that providecontrol of the familywise error rate (FWE). In order to improve upon theBonferroni method or Holm's (1979) stepdown method, Westfall and Young(1993) make eective use of resampling to construct stepdown methods thatimplicitly estimate the dependence structure of the test statistics. However,their methods depend on an assumption called subset pivotality. The goalof this paper is to construct general stepdown methods that do not requiresuch an assumption. In order to accomplish this, we take a close look atwhat makes stepdown procedures work, and a key component is a monotonicityrequirement of critical values. By imposing such monotonicity on estimatedcritical values (which is not an assumption on the model but an assumptionon the method), it is demonstrated that the problem of constructing a validmultiple test procedure which controls the FWE can be reduced to the problemof contructing a single test which controls the usual probability of a Type 1error. This reduction allows us to draw upon an enormous resamplingliterature as a general means of test contruction.