H1-antihistamines for chronic spontaneous urticaria: An abridged Cochrane Systematic Review

Background Chronic spontaneous urticaria is characterized by recurrent itchy wheals. First-line management is with H1-antihistamines. Objective We sought to conduct a Cochrane Review of H1-antihistamines in the treatment of chronic spontaneous urticaria. Methods A systematic search of major databases for randomized controlled trials was conducted. Results We included 73 studies with 9759 participants; 34 studies provided outcome data for 23 comparisons. Compared with placebo, cetirizine 10 mg daily in the short and intermediate term (RR 2.72; 95% confidence interval [CI] 1.51-4.91) led to complete suppression of urticaria. Levocetirizine 20 mg daily was effective for short-term use (RR 20.87; 95% CI 1.37-317.60) as was 5 mg for intermediate-term use (RR 52.88; 95% CI 3.31-843.81). Desloratadine 20 mg was effective for the short term (RR 15.97; 95% CI 1.04-245.04) as was 5 mg in the intermediate term (RR 37.00; 95% CI 2.31-593.70). There was no evidence to suggest difference in adverse event rates between treatments. Limitations Some methodological limitations were observed. Few studies for each comparison reported outcome data that could be incorporated in meta-analyses. Conclusions At standard doses, several antihistamines are effective and safe in complete suppression of chronic spontaneous urticaria. Research on long-term treatment using standardized outcome measures and quality of life scores is needed

A Framework for 4-D Biomedical Image Processing, Visualization and Analysis

Today, studies on biological systems are often realized acquiring, processing and analyzing 3D-time lapse images. Different structures of the organism can be simultaneously observed by acquiring multi-channel image datasets. In this paper we present a software framework that aims at providing support for managing these kinds of multidimensional images, designing and validating new image processing algorithms, and analyzing processed images through different visualization techniques. We present a real scenario where the framework has been used for the detection and segmentation of biological cell membranes and nuclei imaged from live zebrafish embryos

CELLS SHAPE RECONSTRUCTION FROM 3-D+TIME LSM IMAGES OF EARLY ZEBRAFISH EMBRYOGENESIS

We design a chain of image processing methods to automatically reconstruct the shape of membranes and nuclei from time lapse Multi Photon Laser Scanning Microscopy images, taken throughout early animal embryogenesis. This strategy is a prerequisite for an integrated understanding of morphogenetic processes during organogenesis. In order to produce high contrast images, the embryo is labelled through the expression of fluorescent proteins, the eGFP (enhanced Green Fluorescent Protein) and the mcherry (Red Fluorescent Protein), addressed to membranes and nuclei. The two channels are acquired separately but simultaneously. The noise intrinsically related to the images is removed using the geodesic mean curvature flow, an edge-preserving filtering method which has been proven to be the best suitable for this kind of data. Cells are recognized and located either applying the so-called advection-diffusion equations or the generalized 3D Hough transform on nuclei images. The segmentation of cellular structures is then achieved using variational level set techniques