915 resultados para High-throughput assay method
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Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.
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IntraCavity Laser Absorption Spectroscopy (ICLAS) is a high-resolution, high sensitivity spectroscopic method capable of measuring line positions, linewidths, lineshapes, and absolute line intensities with a sensitivity that far exceeds that of a traditional multiple pass absorption cell or Fourier Transform spectrometer. From the fundamental knowledge obtained through these measurements, information about the underlying spectroscopy, dynamics, and kinetics of the species interrogated can be derived. The construction of an ICLA Spectrometer will be detailed, and the measurements utilizing ICLAS will be discussed, as well as the theory of operation and modifications of the experimental apparatus. Results include: i) Line intensities and collision-broadening coefficients of the A band of oxygen and previously unobserved, high J, rotational transitions of the A band, hot-band transitions, and transitions of isotopically substituted species. ii) High-resolution (0.013 cm-1) spectra of the second overtone of the OH stretch of trans-nitrous acid recorded between 10,230 and 10,350 cm-1. The spectra were analyzed to yield a complete set of rotational parameters and an absolute band intensity, and two groups of anharmonic perturbations were observed and analyzed. These findings are discussed in the context of the contribution of overtone-mediated processes to OH radical production in the lower atmosphere.
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Experimental and epidemiological studies demonstrate that fetal growth restriction and low birth weight enhance the risk of chronic diseases in adulthood. Derangements in tissue-specific epigenetic programming of fetal and placental tissues are a suggested mechanism of which DNA methylation is best understood. DNA methylation profiles in human tissue are mostly performed in DNA from white blood cells. The objective of this study was to assess DNA methylation profiles of IGF2 DMR and H19 in DNA derived from four tissues of the newborn. We obtained from 6 newborns DNA from fetal placental tissue (n = 5), umbilical cord CD34+ hematopoietic stem cells (HSC) and CD34- mononuclear cells (MNC) (n = 6), and umbilical cord Wharton jelly (n = 5). HCS were isolated using magnetic-activated cell separation. DNA methylation of the imprinted fetal growth genes IGF2 DMR and H19 was measured in all tissues using quantitative mass spectrometry. ANOVA testing showed tissue-specific differences in DNA methylation of IGF2 DMR (p value 0.002) and H19 (p value 0.001) mainly due to a higher methylation of IGF2 DMR in Wharton jelly (mean 0.65, sd 0.14) and a lower methylation of H19 in placental tissue (mean 0.25, sd 0.02) compared to other tissues. This study demonstrates the feasibility of the assessment of differential tissue specific DNA methylation. Although the results have to be confirmed in larger sample sizes, our approach gives opportunities to investigate epigenetic profiles as underlying mechanism of associations between pregnancy exposures and outcome, and disease risks in later life.
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The authors present a systolic design for a simple GA mechanism which provides high throughput and unidirectional pipelining by exploiting the inherent parallelism in the genetic operators. The design computes in O(N+G) time steps using O(N2) cells where N is the population size and G is the chromosome length. The area of the device is independent of the chromosome length and so can be easily scaled by replicating the arrays or by employing fine-grain migration. The array is generic in the sense that it does not rely on the fitness function and can be used as an accelerator for any GA application using uniform crossover between pairs of chromosomes. The design can also be used in hybrid systems as an add-on to complement existing designs and methods for fitness function acceleration and island-style population management
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The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.
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Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.
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We have designed a highly parallel design for a simple genetic algorithm using a pipeline of systolic arrays. The systolic design provides high throughput and unidirectional pipelining by exploiting the implicit parallelism in the genetic operators. The design is significant because, unlike other hardware genetic algorithms, it is independent of both the fitness function and the particular chromosome length used in a problem. We have designed and simulated a version of the mutation array using Xilinix FPGA tools to investigate the feasibility of hardware implementation. A simple 5-chromosome mutation array occupies 195 CLBs and is capable of performing more than one million mutations per second. I. Introduction Genetic algorithms (GAs) are established search and optimization techniques which have been applied to a range of engineering and applied problems with considerable success [1]. They operate by maintaining a population of trial solutions encoded, using a suitable encoding scheme.
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BACKGROUND: The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls. METHODS: We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set. RESULTS: Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set. CONCLUSIONS: For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.
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As a continuing effort to establish the structure-activity relationships (SARs) within the series of the angiotensin II antagonists (sartans), a pharmacophoric model was built by using novel TOPP 3D descriptors. Statistical values were satisfactory (PC4: r(2)=0.96, q(2) ((5) (random) (groups))=0.84; SDEP=0.26) and encouraged the synthesis and consequent biological evaluation of a series of new pyrrolidine derivatives. SAR together with a combined 3D quantitative SAR and high-throughput virtual screening showed that the newly synthesized 1-acyl-N-(biphenyl-4-ylmethyl)pyrrolidine-2-carboxamides may represent an interesting starting point for the design of new antihypertensive agents. In particular, biological tests performed on CHO-hAT(1) cells stably expressing the human AT(1) receptor showed that the length of the acyl chain is crucial for the receptor interaction and that the valeric chain is the optimal one.
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The production of sufficient quantities of protein is an essential prelude to a structure determination, but for many viral and human proteins this cannot be achieved using prokaryotic expression systems. Groups in the Structural Proteomics In Europe ( SPINE) consortium have developed and implemented high- throughput ( HTP) methodologies for cloning, expression screening and protein production in eukaryotic systems. Studies focused on three systems: yeast ( Pichia pastoris and Saccharomyces cerevisiae), baculovirusinfected insect cells and transient expression in mammalian cells. Suitable vectors for HTP cloning are described and results from their use in expression screening and protein-production pipelines are reported. Strategies for coexpression, selenomethionine labelling ( in all three eukaryotic systems) and control of glycosylation ( for secreted proteins in mammalian cells) are assessed.
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Cashew (Anacardium occidentale L.) is the most economically important tropical nut crop in the world, and yet there are no sequence tagged site (STS) markers available for its study. Here we use an automated, high-throughput system to isolate cashew microsatellites from a non-enriched genomic library blotted onto membranes at high density for screening. Sixty-five sequences contained a microsatellite array, of which 21 proved polymorphic among a closely related seed garden population of 49 genotypes. Twelve markers were suitable for multiplex analysis. Of these, 10 amplified in all three related tropical tree species tested: Anacardium microcarpum, Anacardium pumilum and Anacardium nanum.
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The expression of proteins using recombinant baculoviruses is a mature and widely used technology. However, some aspects of the technology continue to detract from high throughput use and the basis of the final observed expression level is poorly understood. Here, we describe the design and use of a set of vectors developed around a unified cloning strategy that allow parallel expression of target proteins in the baculovirus system as N-terminal or C-terminal fusions. Using several protein kinases as tests we found that amino-terminal fusion to maltose binding protein rescued expression of the poorly expressed human kinase Cot but had only a marginal effect on expression of a well-expressed kinase IKK-2. In addition, MBP fusion proteins were found to be secreted from the expressing cell. Use of a carboxyl-terminal GFP tagging vector showed that fluorescence measurement paralleled expression level and was a convenient readout in the context of insect cell expression, an observation that was further supported with additional non-kinase targets. The expression of the target proteins using the same vectors in vitro showed that differences in expression level were wholly dependent on the environment of the expressing cell and an investigation of the time course of expression showed it could affect substantially the observed expression level for poorly but not well-expressed proteins. Our vector suite approach shows that rapid expression survey can be achieved within the baculovirus system and in addition, goes some way to identifying the underlying basis of the expression level obtained. (c) 2006 Elsevier Inc. All rights reserved.
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A number of strategies are emerging for the high throughput (HTP) expression of recombinant proteins to enable structural and functional study. Here we describe a workable HTP strategy based on parallel protein expression in E. coli and insect cells. Using this system we provide comparative expression data for five proteins derived from the Autographa californica polyhedrosis virus genome that vary in amino acid composition and in molecular weight. Although the proteins are part of a set of factors known to be required for viral late gene expression, the precise function of three of the five, late expression factors (lefs) 6, 7 and 10, is unknown. Rapid expression and characterisation has allowed the determination of their ability to bind DNA and shown a cellular location consistent with their properties. Our data point to the utility of a parallel expression strategy to rapidly obtain workable protein expression levels from many open reading frames (ORFs).
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Recombinant baculoviruses have established themselves as a favoured technology for the high-level expression of recombinant proteins. The construction of recombinant viruses, however, is a time consuming step that restricts consideration of the technology for high throughput developments. Here we use a targeted gene knockout technology to inactivate an essential viral gene that lies adjacent to the locus used for recombination. Viral DNA prepared from the knockout fails to initiate an infection unless rescued by recombination with a baculovirus transfer vector. Modified viral DNA allows 100% recombinant virus formation, obviates the need for further virus purification and offers an efficient means of mass parallel recombinant formation.
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Matrix-assisted laser desorption/ionization (MALDI) is a key technique in mass spectrometry (MS)-based proteomics. MALDI MS is extremely sensitive, easy-to-apply, and relatively tolerant to contaminants. Its high-speed data acquisition and large-scale, off-line sample preparation has made it once again the focus for high-throughput proteomic analyses. These and other unique properties of MALDI offer new possibilities in applications such as rapid molecular profiling and imaging by MS. Proteomics and its employment in Systems Biology and other areas that require sensitive and high-throughput bioanalytical techniques greatly depend on these methodologies. This chapter provides a basic introduction to the MALDI methodology and its general application in proteomic research. It describes the basic MALDI sample preparation steps and two easy-to-follow examples for protein identification including extensive notes on these topics with practical tips that are often not available in the Subheadings 2 and 3 of research articles.