97 research outputs found
Predicting the sensitivity and specificity of published real-time PCR assays
<p>Abstract</p> <p>Background</p> <p>In recent years real-time PCR has become a leading technique for nucleic acid detection and quantification. These assays have the potential to greatly enhance efficiency in the clinical laboratory. Choice of primer and probe sequences is critical for accurate diagnosis in the clinic, yet current primer/probe signature design strategies are limited, and signature evaluation methods are lacking.</p> <p>Methods</p> <p>We assessed the quality of a signature by predicting the number of true positive, false positive and false negative hits against all available public sequence data. We found real-time PCR signatures described in recent literature and used a BLAST search based approach to collect all hits to the primer-probe combinations that should be amplified by real-time PCR chemistry. We then compared our hits with the sequences in the NCBI taxonomy tree that the signature was designed to detect.</p> <p>Results</p> <p>We found that many published signatures have high specificity (almost no false positives) but low sensitivity (high false negative rate). Where high sensitivity is needed, we offer a revised methodology for signature design which may designate that multiple signatures are required to detect all sequenced strains. We use this methodology to produce new signatures that are predicted to have higher sensitivity and specificity.</p> <p>Conclusion</p> <p>We show that current methods for real-time PCR assay design have unacceptably low sensitivities for most clinical applications. Additionally, as new sequence data becomes available, old assays must be reassessed and redesigned. A standard protocol for both generating and assessing the quality of these assays is therefore of great value. Real-time PCR has the capacity to greatly improve clinical diagnostics. The improved assay design and evaluation methods presented herein will expedite adoption of this technique in the clinical lab.</p
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SPUF - a simple polyurethane foam mass loss and response model.
A Simple PolyUrethane Foam (SPUF) mass loss and response model has been developed to predict the behavior of unconfined, rigid, closed-cell, polyurethane foam-filled systems exposed to fire-like heat fluxes. The model, developed for the B61 and W80-0/1 fireset foam, is based on a simple two-step mass loss mechanism using distributed reaction rates. The initial reaction step assumes that the foam degrades into a primary gas and a reactive solid. The reactive solid subsequently degrades into a secondary gas. The SPUF decomposition model was implemented into the finite element (FE) heat conduction codes COYOTE [1] and CALORE [2], which support chemical kinetics and dynamic enclosure radiation using 'element death.' A discretization bias correction model was parameterized using elements with characteristic lengths ranging from 1-mm to 1-cm. Bias corrected solutions using the SPUF response model with large elements gave essentially the same results as grid independent solutions using 100-{micro}m elements. The SPUF discretization bias correction model can be used with 2D regular quadrilateral elements, 2D paved quadrilateral elements, 2D triangular elements, 3D regular hexahedral elements, 3D paved hexahedral elements, and 3D tetrahedron elements. Various effects to efficiently recalculate view factors were studied -- the element aspect ratio, the element death criterion, and a 'zombie' criterion. Most of the solutions using irregular, large elements were in agreement with the 100-{micro}m grid-independent solutions. The discretization bias correction model did not perform as well when the element aspect ratio exceeded 5:1 and the heated surface was on the shorter side of the element. For validation, SPUF predictions using various sizes and types of elements were compared to component-scale experiments of foam cylinders that were heated with lamps. The SPUF predictions of the decomposition front locations were compared to the front locations determined from real-time X-rays. SPUF predictions of the 19 radiant heat experiments were also compared to a more complex chemistry model (CPUF) predictions made with 1-mm elements. The SPUF predictions of the front locations were closer to the measured front locations than the CPUF predictions, reflecting the more accurate SPUF prediction of mass loss. Furthermore, the computational time for the SPUF predictions was an order of magnitude less than for the CPUF predictions
Practically Useful: What the Rosetta Protein Modeling Suite Can Do for You
The objective of this review is to enable researchers to use the software package ROSETTA for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with ROSETTA. For each of these six tasks, we provide a tutorial that illustrates a basic ROSETTA protocol. The ROSETTA method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 A ˚. More impressively, there are several cases in which ROSETTA has been used to predict structures with atomic level accuracy better than 2.5 A ˚. In addition to de novo structure prediction, ROSETTA also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. ROSETTA has been used to accurately design a novel protein structure, predict the structure of protein-protein complexes, design altered specificity protein-protein and protein-DNA interactions, and stabilize proteins and protein complexes. Most recently, ROSETTA has been used to solve the X-ray crystallographic phase problem. ROSETTA is a unified software package for protein structure prediction and functional design. It has been used to predic
Interleukin-4 Alters Early Phagosome Phenotype by Modulating Class I PI3K Dependent Lipid Remodeling and Protein Recruitment
Phagocytosis is a complex process that involves membranelipid remodeling and the attraction and retention of key effector proteins. Phagosome phenotype depends on the type of receptor engaged and can be influenced by extracellular signals. Interleukin 4 (IL-4) is a cytokine that induces the alternative activation of macrophages (MΦs) upon prolonged exposure, triggering a different cell phenotype that has an altered phagocytic capacity. In contrast, the direct effects of IL-4 during phagocytosis remain unknown. Here, we investigate the impact of short-term IL-4 exposure (1 hour) during phagocytosis of IgG-opsonized yeast particles by MΦs. By time-lapse confocal microscopy of GFP-tagged lipid-sensing probes, we show that IL-4 increases the negative charge of the phagosomal membrane by prolonging the presence of the negatively charged second messenger PI(3,4,5)P3. Biochemical assays reveal an enhanced PI3K/Akt activity upon phagocytosis in the presence of IL-4. Blocking the specific class I PI3K after the onset of phagocytosis completely abrogates the IL-4-induced changes in lipid remodeling and concomitant membrane charge. Finally, we show that IL-4 direct signaling leads to a significantly prolonged retention profile of the signaling molecules Rac1 and Rab5 to the phagosomal membrane in a PI3K-dependent manner. This protracted early phagosome phenotype suggests an altered maturation, which is supported by the delayed phagosome acidification measured in the presence of IL-4. Our findings reveal that molecular differences in IL-4 levels, in the extracellular microenvironment, influence the coordination of lipid remodeling and protein recruitment, which determine phagosome phenotype and, eventually, fate. Endosomal and phagosomal membranes provide topological constraints to signaling molecules. Therefore, changes in the phagosome phenotype modulated by extracellular factors may represent an additional mechanism that regulates the outcome of phagocytosis and could have significant impact on the net biochemical output of a cell
Financial Leverage and Corporate Taxation: Evidence from German Corporate Tax Return Data
Extent of pre-translational regulation for the control of nucleocytoplasmic protein localization
The Petrochemistry of Jake_M: A Martian Mugearite
“Jake_M,” the first rock analyzed by the Alpha Particle X-ray Spectrometer instrument on the
Curiosity rover, differs substantially in chemical composition from other known martian igneous
rocks: It is alkaline (>15% normative nepheline) and relatively fractionated. Jake_M is
compositionally similar to terrestrial mugearites, a rock type typically found at ocean islands and
continental rifts. By analogy with these comparable terrestrial rocks, Jake_M could have been
produced by extensive fractional crystallization of a primary alkaline or transitional magma at
elevated pressure, with or without elevated water contents. The discovery of Jake_M suggests that
alkaline magmas may be more abundant on Mars than on Earth and that Curiosity could encounter
even more fractionated alkaline rocks (for example, phonolites and trachytes)
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