Identification of the sharks of the genus Etmopterus Rafinesque, 1810 (Elasmobranchii: Etmopteridae) from the upper slope of southern Brazil, with comparison between the species E. bigelowi Shirai & Tachikawa, 1993 and E. pusillus Lowe, 1839

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Single-Step EUS-Guided Endoscopic Treatment for Sterile Pancreatic Collections: A Single-Center Experience

Background and Aims: Endoscopic ultrasound (EUS) is useful for the treatment of sterile pancreatic fluid collections (PFC), either by means of transmural drainage or by complete aspiration. The aim of this study was to evaluate the efficacy and safety of single-step EUS-guided endoscopic approaches for treatment of sterile PFC. Patients and Methods: During a 3-year period, 77 consecutive patients with symptomatic, persistent sterile PFC were evaluated and treated with the linear EUS. We excluded patients with grossly purulent collections, chronic pseudocyst and those whose cytology diagnostic was neoplastic cyst of pancreas. 44 patients received a single 10-Fr plastic straight stent under EUS or fluoroscopic control (group I) and 33 of these underwent a single-step complete aspiration with a 19-gauge needle (group II). Results: The mean size of the sterile PFC was 48 mm in group I and 28 mm in group II (p < 0.001). Overall, endoscopic treatment was successful in 70 (90.9%) patients. The mean volume aspirated was 25 (18-65) ml. The total number of procedures was 50 in group I and 41 punctures in group II. After a mean follow-up of 64 +/- 15.6 weeks there were 6 complications 13.6%): 2 recurrences (referred to surgery), 2 developing abscesses (submitted a new EUS-guided endoscopic drainage with success), 1 perforation that died (2.2%), and 1 case of bleeding (sent to surgery) in group I. In group II there were only 6 (18.1%) recurrences (submitted a new EUS-guided aspiration). None of the patients undergoing single-step aspiration developed infections, perforation or hemorrhage. Conclusion: The recurrence of pancreatic pseudocysts after endoscopic treatment was similar, either by means of plastic stents or by complete single-step aspiration. Copyright (C) 2009 S. Karger AG, Basel

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.