Performance evaluation of ImmunoCAP® ISAC 112: a multi-site study.

BACKGROUND: After the re-introduction of ImmunoCAP® ISAC sIgE 112 on the market, we undertook a study to evaluate the performance of this multiplex-based immunoassay for IgE measurements to allergen components. METHODS: The study was carried out at 22 European and one South African site. Microarrays from different batches, eight specific IgE (sIgE) positive, three sIgE negative serum samples and a calibration sample were sent to participating laboratories where assays were performed according to the manufacturer's instructions. RESULTS: For both the negative and positive samples results were consistent between sites, with a very low frequency of false positive results (0.014%). A similar pattern of results for each of the samples was observed across the 23 sites. Homogeneity analysis of all measurements for each sample were well clustered, indicating good reproducibility; unsupervised hierarchical clustering and classification via random forests, showed clustering of identical samples independent of the assay site. Analysis of raw continuous data confirmed the good accuracy across the study sites; averaged standardized, site-specific ISU-E values fell close to the center of the distribution of measurements from all sites. After outlier filtering, variability across the whole study was estimated at 25.5%, with values of 22%, 27.1% and 22.4% for the 'Low', 'Moderate to High' and 'Very High' concentration categories, respectively. CONCLUSIONS: The study shows a robust performance of the ImmunoCAP® ISAC 112 immunoassay at different sites. Essentially the same results were obtained irrespective of assay site, laboratory-specific conditions and instruments, operator, or the use of microarrays from different batches.

Pollen food syndrome amongst children with seasonal allergic rhinitis attending allergy clinic.

BACKGROUND: There is limited information regarding the onset and sensitization patterns of pollen food syndrome (PFS) in children. The aim was to explore this within children referred to a specialist allergy clinic at a London Tertiary Hospital. METHODS: A total of 54 patients with seasonal allergic rhinitis (SAR) were enrolled in equal numbers in three age groups; 0-5, 6-10, 11-15 years. Families completed a questionnaire on rhinitis, food symptoms and quality of life. Children underwent skin prick testing (SPT) to fresh fruits, nuts and a blood test for microarray analysis. RESULTS: Clinical diagnosis of PFS was made in 26/54 (48%), increasing with age (group 1 = 3 (17%), group 2 = 9 (50%), group 3 = 14 (78%) (p = 0.03)). Microarray demonstrates children aged 2.8 years sensitized to pan-allergens and 4.5 years symptomatic to pan-allergens. Peach, cherry, carrot and strawberry SPT had the highest sensitivity and NPV at 100%. The sensitivity of PR10 molecules on microarray was 92%, PPV 62% and NPV 87%. Microarray confirmed 69% of allergens on clinical history compared to 61% by SPT. Microarray and SPT had a 19% false-negative rate. The quality-of-life data showed moderate impact across all domains, and patients with PFS were significantly more likely to have increased anxiety over time spent preparing food (p = 0.029). CONCLUSIONS: We demonstrate that SAR occurs in children from 1.4 years and PFS from 4.5 years with a changing pattern of pan-allergen sensitization. Microarray and SPT have moderate concordance in confirming allergens. PFS impacts negatively on quality of life and should be assessed in all paediatric allergy patients.

An analysis toolbox to explore mesenchymal migration heterogeneity reveals adaptive switching between distinct modes.

Mesenchymal (lamellipodial) migration is heterogeneous, although whether this reflects progressive variability or discrete, 'switchable' migration modalities, remains unclear. We present an analytical toolbox, based on quantitative single-cell imaging data, to interrogate this heterogeneity. Integrating supervised behavioral classification with multivariate analyses of cell motion, membrane dynamics, cell-matrix adhesion status and F-actin organization, this toolbox here enables the detection and characterization of two quantitatively distinct mesenchymal migration modes, termed 'Continuous' and 'Discontinuous'. Quantitative mode comparisons reveal differences in cell motion, spatiotemporal coordination of membrane protrusion/retraction, and how cells within each mode reorganize with changed cell speed. These modes thus represent distinctive migratory strategies. Additional analyses illuminate the macromolecular- and cellular-scale effects of molecular targeting (fibronectin, talin, ROCK), including 'adaptive switching' between Continuous (favored at high adhesion/full contraction) and Discontinuous (low adhesion/inhibited contraction) modes. Overall, this analytical toolbox now facilitates the exploration of both spontaneous and adaptive heterogeneity in mesenchymal migration.

Disentangling Membrane Dynamics and Cell Migration; Differential Influences of F-actin and Cell-Matrix Adhesions.

Cell migration is heavily interconnected with plasma membrane protrusion and retraction (collectively termed "membrane dynamics"). This makes it difficult to distinguish regulatory mechanisms that differentially influence migration and membrane dynamics. Yet such distinctions may be valuable given evidence that cancer cell invasion in 3D may be better predicted by 2D membrane dynamics than by 2D cell migration, implying a degree of functional independence between these processes. Here, we applied multi-scale single cell imaging and a systematic statistical approach to disentangle regulatory associations underlying either migration or membrane dynamics. This revealed preferential correlations between membrane dynamics and F-actin features, contrasting with an enrichment of links between cell migration and adhesion complex properties. These correlative linkages were often non-linear and therefore context-dependent, strengthening or weakening with spontaneous heterogeneity in cell behavior. More broadly, we observed that slow moving cells tend to increase in area, while fast moving cells tend to shrink, and that the size of dynamic membrane domains is independent of cell area. Overall, we define macromolecular features preferentially associated with either cell migration or membrane dynamics, enabling more specific interrogation and targeting of these processes in future.

RipleyGUI: software for analyzing spatial patterns in 3D cell distributions.

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers.

Spatial Point Pattern Analysis of Neurons Using Ripley's K-Function in 3D.

The aim of this paper is to apply a non-parametric statistical tool, Ripley's K-function, to analyze the 3-dimensional distribution of pyramidal neurons. Ripley's K-function is a widely used tool in spatial point pattern analysis. There are several approaches in 2D domains in which this function is executed and analyzed. Drawing consistent inferences on the underlying 3D point pattern distributions in various applications is of great importance as the acquisition of 3D biological data now poses lesser of a challenge due to technological progress. As of now, most of the applications of Ripley's K-function in 3D domains do not focus on the phenomenon of edge correction, which is discussed thoroughly in this paper. The main goal is to extend the theoretical and practical utilization of Ripley's K-function and corresponding tests based on bootstrap resampling from 2D to 3D domains.