Antibody cross-linking and target elution protocols used for immunoprecipitation significantly modulate signal-to noise ratio in downstream 2D-PAGE analysis

<p>Abstract</p> <p>Background</p> <p>Immunoprecipitation and subsequent 2D-PAGE/mass spectrometry are powerful tools to study post-translational protein modifications. Often disregarded in this workflow is the impact of the chemical cross-linker upon antibody affinity, as well as incomplete elution of primary target protein in buffers commonly used in 2D-PAGE. This may impede detection of non-abundant protein isoforms.</p> <p>Results</p> <p>Here we have compared cross-linking of antibodies to Dynabeads^®Protein A by using DMP or BS³, as well as the efficiency of various target elution buffers prior to 2D-PAGE separation. BS³cross-linking generally resulted in less non-specific binding than DMP, whereas DMP cross-linking gave overall higher yield of target protein. Regardless of the cross-linker used, incomplete elution of target protein was observed with conventional glycine- or urea-based buffers. Conversely, complete elution was obtained with 2% hot SDS and subsequent dilution in urea buffer containing 4% CHAPS, to 0.2% final SDS yielded perfectly focused gels suitable for mass spectrometry analysis.</p> <p>Conclusion</p> <p>Careful choice of Ig cross-linker as well as efficient elution of target protein in SDS prior to downstream 2D-PAGE may be key factors to analyze low-abundance proteins enriched by magnetic bead immunoprecipitation.</p

Comparison of genetic association strategies in the presence of rare alleles

In the quest for the missing heritability of most complex diseases, rare variants have received increased attention. Advances in large-scale sequencing have led to a shift from the common disease/common variant hypothesis to the common disease/rare variant hypothesis or have at least reopened the debate about the relevance and importance of rare variants for gene discoveries. The investigation of modeling and testing approaches to identify significant disease/rare variant associations is in full motion. New methods to better deal with parameter estimation instabilities, convergence problems, or multiple testing corrections in the presence of rare variants or effect modifiers of rare variants are in their infancy. Using a recently developed semiparametric strategy to detect causal variants, we investigate the performance of the model-based multifactor dimensionality reduction (MB-MDR) technique in terms of power and family-wise error rate (FWER) control in the presence of rare variants, using population-based and family-based data (FAM-MDR). We compare family-based results obtained from MB-MDR analyses to screening findings from a quantitative trait Pedigree-based association test (PBAT). Population-based data were further examined using penalized regression models. We restrict attention to all available single-nucleotide polymorphisms on chromosome 4 and consider Q1 as the outcome of interest. The considered family-based methods identified marker C4S4935 in the VEGFC gene with estimated power not exceeding 0.35 (FAM-MDR), when FWER was kept under control. The considered population-based methods gave rise to highly inflated FWERs (up to 90% for PBAT screening)

Molecular targets for therapy in systemic sclerosis

Despite significant advances have been made in the recent years regarding organ-specific therapies, there is no approved 'disease-modifying' antifibrotic drug for systemic sclerosis (SSc) available to date. Although non-selective immunosuppressive agents are routinely used to treat patients with SSc, large well-controlled studies are lacking for almost all immunosuppressive agents and further evidence is required for long-term beneficial effects of these drugs. Considering these facts about immunosuppressive agents in SSc and also considering the high mortality of SSc, other therapeutic strategies are urgently needed. Recently an important role of the 5-hydroxytryptamine (5-HT: serotonin) pathway in fibrosis was reported. In this review, we discuss the role of 5-HT in fibrosis and therapeutic potential of this molecule. Besides 5-HT, there are a number of promising targets that have been extensively characterized in recent years. For many of these molecular targets, modifiers are readily available for clinical studies, and often these modifiers are used already in clinical use for other diseases. Results from these studies will show, in how far the promising preclinical results for novel antifibrotic strategies can be translated to clinical practice

Multiple publications: The main reason for the retraction of papers in computer science

This paper intends to review the reasons for the retraction over the last decade. The paper particularly aims at reviewing these reasons with reference to computer science field to assist authors in comprehending the style of writing. To do that, a total of thirty-six retracted papers found on the Web of Science within Jan 2007 through July 2017 are explored. Given the retraction notices which are based on ten common reasons, this paper classifies the two main categories, namely random and nonrandom retraction. Retraction due to the duplication of publications scored the highest proportion of all other reasons reviewed

Joint angle variability and co-variation in a reaching with a rod task

The problem at the heart of motor control is how the myriad units of the neuromotor system are coordinated to perform goal-directed movements. Although for long these numerous degrees of freedom (DOFs) were considered redundant, recent views emphasize more that the DOFs should be considered abundant, allowing flexible performance. We studied how variability in arm joints was employed to stabilize the displaced end-effector in tool use to examine how the neuromotor system flexibly exploits DOFs in the upper extremity. Participants made pointing movements with the index finger and with the index finger extended by rods of 10, 20, and 30 cm. Using the uncontrolled manifold (UCM) method, the total joint angle variance was decomposed into two parts, the joint angle variance that did not affect the position of the end-effector (VUCM) and the variance that results in a deviation of the position of the end-effector from its mean (VORT). Analyses showed that some angles depended on length of the rod in use. For all rod lengths, VUCM was larger than VORT, and this did not differ over rod lengths, demonstrating that the arm was organized into a synergy. Finally, the variation in the joint angles in the arm as well as the degree of co-variation between these angles did not differ for the rod’s tip and the hand. We concluded that synergies are formed in the arm during reaching with an extended end-effector and those synergies stabilize different parts of the arm+rod system equally

“Excellence R Us”: university research and the fetishisation of excellence

The rhetoric of “excellence” is pervasive across the academy. It is used to refer to research outputs as well as researchers, theory and education, individuals and organisations, from art history to zoology. But does “excellence” actually mean anything? Does this pervasive narrative of “excellence” do any good? Drawing on a range of sources we interrogate “excellence” as a concept and find that it has no intrinsic meaning in academia. Rather it functions as a linguistic interchange mechanism. To investigate whether this linguistic function is useful we examine how the rhetoric of excellence combines with narratives of scarcity and competition to show that the hypercompetition that arises from the performance of “excellence” is completely at odds with the qualities of good research. We trace the roots of issues in reproducibility, fraud, and homophily to this rhetoric. But we also show that this rhetoric is an internal, and not primarily an external, imposition. We conclude by proposing an alternative rhetoric based on soundness and capacity-building. In the final analysis, it turns out that that “excellence” is not excellent. Used in its current unqualified form it is a pernicious and dangerous rhetoric that undermines the very foundations of good research and scholarship

A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection

BACKGROUND: Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. Here, depending on the technique used, violation of model assumptions may result in increased type I error, power loss, or biased parameter estimates. Remedial measures for violated underlying conditions or assumptions include data transformation or selecting a more relaxed modeling or testing strategy. Model-Based Multifactor Dimensionality Reduction (MB-MDR) for epistasis detection relies on association testing between a trait and a factor consisting of multilocus genotype information. For quantitative traits, the framework is essentially Analysis of Variance (ANOVA) that decomposes the variability in the trait amongst the different factors. In this study, we assess through simulations, the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect 2-locus epistasis signals in the absence of main effects. METHODOLOGY: Our simulation study focuses on pure epistasis models with varying degrees of genetic influence on a quantitative trait. Conditional on a multilocus genotype, we consider quantitative trait distributions that are normal, chi-square or Student’s t with constant or non-constant phenotypic variances. All data are analyzed with MB-MDR using the built-in Student’s t-test for association, as well as a novel MB-MDR implementation based on Welch’s t-test. Traits are either left untransformed or are transformed into new traits via logarithmic, standardization or rank-based transformations, prior to MB-MDR modeling. RESULTS: Our simulation results show that MB-MDR controls type I error and false positive rates irrespective of the association test considered. Empirically-based MB-MDR power estimates for MB-MDR with Welch’s t-tests are generally lower than those for MB-MDR with Student’s t-tests. Trait transformations involving ranks tend to lead to increased power compared to the other considered data transformations. CONCLUSIONS: When performing MB-MDR screening for gene-gene interactions with quantitative traits, we recommend to first rank-transform traits to normality and then to apply MB-MDR modeling with Student’s t-tests as internal tests for association