Cardiac Depression in Pigs after Multiple Trauma - Characterization of Posttraumatic Structural and Functional Alterations

Abstract The purpose of this study was to define the relationship between cardiac depression and morphological and immunological alterations in cardiac tissue after multiple trauma. However, the mechanistic basis of depressed cardiac function after trauma is still elusive. In a porcine polytrauma model including blunt chest trauma, liver laceration, femur fracture and haemorrhage serial trans-thoracic echocardiography was performed and correlated with cellular cardiac injury as well as with the occurrence of extracellular histones in serum. Postmortem analysis of heart tissue was performed 72 h after trauma. Ejection fraction and shortening fraction of the left ventricle were significantly impaired between 4 and 27 h after trauma. H-FABP, troponin I and extracellular histones were elevated early after trauma and returned to baseline after 24 and 48 h, respectively. Furthermore, increased nitrotyrosine and Il-1β generation and apoptosis were identified in cardiac tissue after trauma. Main structural findings revealed alteration of connexin 43 (Cx43) and co-translocation of Cx43 and zonula occludens 1 to the cytosol, reduction of α-actinin and increase of desmin in cardiomyocytes after trauma. The cellular and subcellular events demonstrated in this report may for the first time explain molecular mechanisms associated with cardiac dysfunction after multiple trauma

ALV: Automatisches Lesen und Verstehen Abschlussbericht

Project ALV conducted research in Document Analysis. The main goal of ALV was developing a phototypical system for analyzing printed documents, i.e. a system comprising all phases of analysis starting with scanning the document image up to representing its contents. This extensive approach has been highly important for ALV. Different research areas are integrated in order to perform Document Analysis: Computer Vision, Optical Character Recognition (OCR) -better-to-say Text Recognition, Pattern Recognition and Analysis, and Natural Language Processing. The resulting research prototype has been developed and tested within the domain of singlesided, printed business letters. Following research topics have been handled: Structural recognition - certain properties of the segmentation of non-homogeneously laid out documents have been examined, and respective techniques developed. Logical Labelling - a method has been adapted doing a classification purely based upon geometric features, which were acquired automatically. OCR - commercial systems as well as alternative approaches to text recognition have been analyzed and examined and a voting algorithm has been developed and implemented for integration of several text recognizers. Contentual analysis - well-known techniques have been investigated as far as they were appropriate for being incorporated into a recognition-based-system. Particularly, the following three techniques have been tested: (1) from Information Retrieval some statistically-based methods for indexing and classification of text have been adapted; (2) in order to extract certain information typical for a respective message-type, expectation-driven techniques have been used and have been refined for robust behaviour; (3) for recognition of the recipient's address on a letter, parsing techniques originating from Natural Language Processing have been adapted. Besides those tasks dealing with analysis phases, two further topics were the development of a lexicon satisfying requirements from both text recognition and analysis and the investigation of standards for document representation which in part influenced the prototype's design. (orig.)Das Projekt ALV beschaeftigte sich mit Forschungen im Bereich der Dokumentanalyse. Zentrales Ziel des Projektes war die Entwicklung eines prototypischen Systems zur Analyse gedruckter Dokumente, welches alle Bearbeitungsphasen beginnend mit der Bildverarbeitung bis hin zur inhaltlichen Analyse abdeckt. Somit war der integrative Aspekt des Projektes von besonderer Wichtigkeit: Die verschiedenen Forschungsgebiete der Bildverarbeitung, der Texterkennung, der Sprachanalyse und der Musterverarbeitung wurden fuer die Anwendung der Dokumentanalyse in einem Systemprototypen zusammengefuehrt. Dieser Forschungsprototyp wurde fuer die Domaene gedruckter, einseitiger Geschaeftsbriefe entwickelt und getestet. Schwerpunktmaessig wurden dabei die folgenden Forschungsbereiche bearbeitet. In der Strukturerkennung wurden die Besonderheiten der Segmentierung inhomogen strukturierter Dokumente am Beispiel von Geschaeftsbriefen untersucht und entsprechende Verfahren dafuer entwickelt. Fuer die Strukturanalyse wurde eine Methode erforscht, welche ein vorliegendes Dokument aufgrund rein geometrischer Kriterien gemaess vorgegebener, erlernter Muster klassifiziert. Im Bereich der Texterkennung wurden zu kommerziellen Systemen alternative Verfahren analysiert und getestet und zusaetzlich ein Verfahren zur Integration der Erkennungsergebnisse verschiedener Texterkenner entwickelt. Im Bereich der inhaltlichen Analyse wurden bekannte Verfahren hinsichtlich ihrer Verwendbarkeit in einem erkennungsbasierten System untersucht. Dabei wurden insbesondere die folgenden drei Techniken beruecksichtigt: Im Bereich des Information Retrieval entwickelte Methoden der Indexierung wurden zur statistischen Klassifikation von Texten weiterentwickelt: zur Extraktion textklassen-spezifischer Informationen wurden erwartungsgesteuerte Verfahren eingesetzt und robust gestaltet; zur identifikation von Adressaten wurden Techniken aus der Sprachverarbeitung adaptiert und zur Adressenerkennung verwendet. Neben diesen analyse-orientierten Forschungen wurde zum einen ein Lexikon entwickelt, welches den Erfordernissen sowohl der Texterkennung als auch der Textanalyse gerecht wird; zum anderen wurden bestehende Standards der Dokumentrepraesentation evaluiert und daraus gewonnene Erkenntnisse im Prototypen verwendet. (orig.)Available from TIB Hannover: F94B1067+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Forschung und Technologie (BMFT), Bonn (Germany)DEGerman

Document analysis at DFKI. Pt. 1 Image analysis and text recognition

Document analysis is responsible for an essential progress in office automation. This paper is part of an overview about the combined research efforts in document analysis at the DFKI. Common to all document analysis projects is the global of providing a high level electronic representation of documents in terms of iconic, structural, textual, and semantic information. These symbolic document descriptions enable an 'intelligent' access to a document database. Currently there are three ongoing document analysis projects a DFKI: INCA, OMEGA, and PASCAL2000/PASCAL+. Though the projects pursue different goals in different application domains, they all share the same problems which have to be resolved with similar techniques. For that reason the activities in these projects are bundled to avoid redundant work. At DFKI we have divided the problem of document analysis into two main tasks, text recognition and text analysis, which themselves are divided into a set of subtasks. In a series of three research reports the work of the document analysis and office automation department at DFKI is presented. The first report discusses the problem of text recognition, the second that of text analysis. In a third report we describe our concept for a specialized document analysis knowledge representation language. The report in hand describes the activities dealing with the text recognition task. Text recognition covers the phase starting with capturing a document image up to identifying the written words. This comprises the following subtasks: Preprocessing the pictorial information, segmenting into blocks, lines, words, and characters, classifying characters, and identifying the input words. For each subtask several competing solution algorithms, called specialists or knowledge sources, may exist. To efficiently control and organize these specialists an intelligent situation-based planning component is necessary, which is also described in this report. It should be mentioned that the planning component is also responsible to control the overall document analysis system instead of the text recognition phase only. (orig.)SIGLEAvailable from TIB Hannover: RR 1812(95-02) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman

GFI1 is required for RUNX1/ETO positive acute myeloid leukemia

Contains fulltext : 196389.pdf (publisher's version ) (Open Access