Adenosine Signaling in Mast Cells and Allergic Diseases

Adenosine is a nucleoside involved in the pathogenesis of allergic diseases. Its effects are mediated through its binding to G protein-coupled receptors: A1, A2a, A2b and A3. The receptors differ in the type of G protein they recruit, in the effect on adenylyl cyclase (AC) activity and the downstream signaling pathway triggered. Adenosine can produce both an enhancement and an inhibition of mast cell degranulation, indicating that adenosine effects on these receptors is controversial and remains to be clarified. Depending on the study model, A1, A2b, and A3 receptors have shown anti- or pro-inflammatory activity. However, most studies reported an anti-inflammatory activity of A2a receptor. The precise knowledge of the adenosine mechanism of action may allow to develop more efficient therapies for allergic diseases by using selective agonist and antagonist against specific receptor subtypes.     

EVALUATION OF A METHOD FOR MEASURING MIXING TIME USING NUMERICAL SIMULATION AND EXPERIMENTAL DATA

A method for measuring mixing performance in large-scale vessels is investigated. The method is evaluated experimentally in a pilotscale reactor and by using a model based on the three-dimensional calculation of the flow field. The method is based on injection of a tracer and measuring the concentration with several detectors at different locations. The mixing performance is measured as the decay rate of the difference between the concentration at the detectors and the final concentration.

The model predicts a strong dependence on injection point. The assumption of a first-order decay rate of the concentration deviation is more appropriate for some injection points.     

Visual Inspection of Multivariate Graphs

Most graph visualization techniques focus on the structure of graphs and do not offer support for dealing with node attributes and edge labels. To enable users to detect relations and patterns in terms of data associated with nodes and edges, we present a technique where this data plays a more central role. Nodes and edges are clustered based on associated data. Via direct manipulation users can interactively inspect and query the graph. Questions that can be answered include, “which edge types are activated by specific node attributes?” and, “how and from where can I reach specific types of nodes?” To validate our approach we contrast it with current practice. We also provide several examples where our method was used to study transition graphs that model real‐world systems.     

Introduction of lysine residues on the light chain constant domain improves the labelling properties of a recombinant Fab fragment

Europium chelates provide a non-radioactive alternative forsensitive labelling of antibodies for diagnostic immunoassays.Lysine residues at antibody surfaces are ready targets for labellingby an isothiocyanate derivative of the europium chelate (Eu³⁺).Here the labelling efficiency of a recombinant anti-human -fetoprotein(hAFP) Fab fragment has been improved by increasing its lysinecontent by protein engineering. Molecular modelling was usedto identify three light chain constant domain surface arginineresidues, R154, R187 and R210, which were mutated to lysineresidues. The mutations did not influence the affinity of thelysine-enriched Fab fragment and its labelling efficiency wasfound to be 40% higher than that of the wildtype Fab fragmentWith low degree of labelling, the affinities of the two Fabfragments were identical and comparable with that of the originalmonoclonal anti-hAFP IgG. With a higher degree of labellingthe affinities of both Fab fragments decreased more than thatof the intact IgG since more lysine residues are available forlabelling in the additional heavy chain constant domains ofthe larger molecule. Electrostatic adsorption and covalent immobilizationof the Fab fragments were characterized by BIAcore^TM and thelysine-enriched Fab fragment was found to be more efficientlyimmobilized to an activated carboxymethyl surface.     

Flexible Linked Axes for multivariate data visualization

Multivariate data visualization is a classic topic, for which many solutions have been proposed, each with its own strengths and weaknesses. In standard solutions the structure of the visualization is fixed, we explore how to give the user more freedom to define visualizations. Our new approach is based on the usage of Flexible Linked Axes: The user is enabled to define a visualization by drawing and linking axes on a canvas. Each axis has an associated attribute and range, which can be adapted. Links between pairs of axes are used to show data in either scatter plot- or Parallel Coordinates Plot-style. Flexible Linked Axes enable users to define a wide variety of different visualizations. These include standard methods, such as scatter plot matrices, radar charts, and PCPs [11]; less well known approaches, such as Hyperboxes [1], TimeWheels [17], and many-to-many relational parallel coordinate displays [14]; and also custom visualizations, consisting of combinations of scatter plots and PCPs. Furthermore, our method allows users to define composite visualizations that automatically support brushing and linking. We have discussed our approach with ten prospective users, who found the concept easy to understand and highly promising.     

Computing multiscale curve and surface skeletons of genus 0 shapes using a global importance measure

We present a practical algorithm for computing robust, multiscale curve and surface skeletons of 3D objects. Based on a model which follows an advection principle, we assign to each point on the skeleton a part of the object surface, called the collapse. The size of the collapse is used as a uniform importance measure for the curve and surface skeleton, so that both can be simplified by imposing a single threshold on this intuitive measure. The simplified skeletons are connected by default, without special precautions, due to the monotonicity of the importance measure. The skeletons possess additional desirable properties: They are centered, robust to noise, hierarchical, and provide a natural skeleton-to-boundary mapping. We present a voxel-based algorithm that is straightforward to implement and simple to use. We illustrate our method on several realistic 3D objects.     

Screening of serum samples from Wegener's granulomatosis patients using antibody microarrays

Wegener's Granulomatosis (WG) is an idiopathic granulomatosis autoimmune vasculitis that primarily affects small vessels and is associated with glomerulonephritis and pulmonary granulomatous vasculitis. Anti‐neutrophil cytoplasmic auto‐antibodies (cANCA) against proteinase‐3 are used to identify WG, but ANCA titers are not present in some patients with the localized disease. The objective of this study was to develop an antibody array to help identify protein expression patterns in serum from patients with WG as compared to normals. The arrays were tested for limits of detection, background, and cross reactivity using standard proteins. The arrays were hybridized with either normal patient serum (n = 30) or with serum samples from a population of WG patients (n = 26) that were age and sex matched. Data analysis and curve fitting of the standard dilution series calculated r² values and determined a sensitivity of <50 pg/mL for the majority of proteins. A total of 24 proteins were assessed. Several statistically significant increases (p<0.05) were seen in the expression of: angiotensin converting enzyme‐I, IFN‐γ, IL‐8, s‐ICAM‐1 and s‐VCAM in WG patients as compared to controls. Utilizing the antibody microarray technology has led to the identification of potential biomarkers of vascular injury in the serum of WG patients.     

Views on visualization

The field of visualization is maturing. Many problems have been solved and new directions are sought. In order to make good choices, an understanding of the purpose and meaning of visualization is needed. In this paper, visualization is considered from multiple points of view. First, a technological viewpoint is adopted, where the value of visualization is measured based on effectiveness and efficiency. An economic model of visualization is presented and benefits and costs are established. Next, consequences and limitations of visualization are discussed (including the use of alternative methods, high initial costs, subjectiveness, and the role of interaction). Example uses of the model for the judgment of existing classes of methods are given to understand why they are or are not used in practice. However, such an economic view is too restrictive. Alternative views on visualization are presented and discussed: visualization as an art, visualization as design and, finally, visualization as a scientific discipline.