Mesenchymal Stem Cells Promote Oligodendroglial Differentiation in Hippocampal Slice Cultures

We have previously shown that soluble factors derived from mesenchymal stem cells (MSCs) induce oligodendrogenic fate and differentiation in adult rat neural progenitors (NPCs) in vitro. Here, we investigated if this pro-oligodendrogenic effect is maintained after cells have been transplanted onto rat hippocampal slice cultures, a CNS-organotypic environment. We first tested whether NPCs, that were pre-differentiated in vitro by MSC-derived conditioned medium, would generate oligodendrocytes after transplantation. This approach resulted in the loss of grafted NPCs, suggesting that oligodendroglial pre-differentiated cells could not integrate in the tissue and therefore did not survive grafting. However, when NPCs together with MSCs were transplanted in situ into hippocampal slice cultures, the grafted NPCs survived and the majority of them differentiated into oligodendrocytes. In contrast to the prevalent oligodendroglial differentiation in case of the NPC/MSC co-transplantation, naive NPCs transplanted in the absence of MSCs differentiated predominantly into astrocytes. In summary, the pro-oligodendrogenic activity of MSCs was maintained only after co-transplantation into hippocampal slice cultures. Therefore, in the otherwise astrogenic milieu, MSCs established an oligodendrogenic niche for transplanted NPCs, and thus, co-transplantation of MSCs with NPCs might provide an attractive approach to re-myelinate the various regions of the diseased CNS. Copyright (C) 2009 S. Karger AG, Base

Streamlining Cross-Organizational Aircraft Development: Results from the AGILE Project

The research and innovation AGILE project developed the next generation of aircraft Multidisciplinary Design and Optimization processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. The high level objective is the reduction of the lead time of 40% with respect to the current state-of-the-art. 19 industry, research and academia partners from Europe, Canada and Russia developed solutions to cope with the challenges of collaborative design and optimization of complex products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization (MDO), a novel methodology, the so-called AGILE Paradigm, has been developed. Furthermore, the AGILE project has developed and released a set of open technologies enabling the implementation of the AGILE Paradigm approach. The collection of all the technologies constitutes AGILE Framework, which has been deployed for the design and the optimization of multiple aircraft configurations. This paper focuses on the application of the AGILE Paradigm on seven novel aircraft configurations, proving the achievement of the project’s objectives

Liver Fibrosis and Metabolic Alterations in Adults With alpha-1-antitrypsin Deficiency Caused by the Pi*ZZ Mutation

BACKGROUND & AIMS: Alpha-1 antitrypsin deficiency (AATD) is among the most common genetic disorders. Severe AATD is caused by a homozygous mutation in the SERPINA1 gene that encodes the Glu342Lys substitution (called the Pi*Z mutation, Pi*ZZ genotype). Pi*ZZ carriers may develop lung and liver diseases. Mutation- associated lung disorders have been well studied, but less is known about the effects in liver. We assessed the liver disease burden and associated features in adults with this form of AATD. METHODS: We collected data from 554 Pi*ZZ adults (403 in an exploratory cohort, 151 in a confirmatory cohort), in 9 European countries, with AATD who were homozygous for the Pi*Z mutation, and 234 adults without the Pi*Z mutation (controls), all without pre-existing liver disease. We collected data on demographic parameters, comorbidities, lung- and liver-related health, and blood samples for laboratory analysis. Liver fibrosis was assessed non-invasively via the serum tests Aspartate Aminotransferase to Platelet Ratio Index and HepaScore and via transient elastography. Liver steatosis was determined via transient elastography-based controlled attenuation parameter. We performed histologic analyses of livers from transgenic mice that overexpress the AATD-associated Pi*Z variant. RESULTS: Serum levels of liver enzymes were significantly higher in Pi*ZZ carriers vs controls. Based on non-invasive tests for liver fibrosis, significant fibrosis was suspected in 20%–36% of Pi*ZZ carriers, whereas signs of advanced fibrosis were 9- to 20-fold more common in Pi*ZZ carriers compared to non-carriers. Male sex; age older than 50 years; increased levels of alanine aminotransferase, aspartate aminotransferase, or g-glutamyl transferase; and low numbers of platelets were associated with higher liver fibrosis burden. We did not find evidence for a relationship between lung function and liver fibrosis. Controlled attenuation parameter 280 dB/m, suggesting severe steatosis, was detected in 39% of Pi*ZZ carriers vs 31% of controls. Carriers of Pi*ZZ had lower serum concentrations of triglyceride and low- and very-lowdensity lipoprotein cholesterol than controls, suggesting impaired hepatic secretion of lipid. Livers from Pi*Zoverexpressing mice had steatosis and down-regulation of genes involved in lipid secretion. CONCLUSIONS: In studies of AATD adults with the Pi*ZZ mutation, and of Pi*Z-overexpressing mice, we found evidence of liver steatosisinfo:eu-repo/semantics/publishedVersio

Liver Phenotypes of European Adults Heterozygous or Homozygous for Pi∗Z Variant of AAT (Pi∗MZ vs Pi∗ZZ genotype) and Noncarriers

Homozygosity for the Pi∗Z variant of the gene that encodes the alpha-1 antitrypsin peptide (AAT), called the Pi∗ZZ genotype, causes a liver and lung disease called alpha-1 antitrypsin deficiency. Heterozygosity (the Pi∗MZ genotype) is a risk factor for cirrhosis in individuals with liver disease. Up to 4% of Europeans have the Pi∗MZ genotype; we compared features of adults with and without Pi∗MZ genotype among persons without preexisting liver disease.info:eu-repo/semantics/publishedVersio

Extraction of tabular information from PDF documents : a graph-based approach

Eine strukturierte Repräsentation von dem Inhalt von Dokumenten ist die Basis für viele Systeme, ob es sich nun um eine automatisierte Verarbeitung von Dokumenten mithilfe von intelligenten Workflows oder generell um Datenabfragen im World Wide Web handelt. Jedoch ist eine Vielzahl an Dokumenten in unstrukturierten Formaten abgespeichert. Ein weitverbreitetes Beispiel eines solchen Formates ist das Portable Document Format (PDF). Daher liegt ein großes, unerschlossenes Potential in der Ableitung von strukturierter Information aus unstrukturierten Dateiformaten. Große Anteile von wichtiger Information sind hierbei in Tabellen hinterlegt, da diese eine sehr dichte Repräsentation von Inhalten darstellen. Durch eine nicht greifbare Anzahl an verschiedenen Gestaltungen ist die Erkennung von tabellarischen Strukturen eine schwierige Aufgabe. Heutzutage basieren die meisten dafür angewendeten Systeme auf neuronalen Netzen, welche große Trainingssets voraussetzten und ebenfalls Schwierigkeiten hinsichtlich Daten zeigen, welche darin nicht präsent sind. In dieser Arbeit wird ein System entwickelt, welches den Zweck erfüllt, Tabellen aus PDFs sowohl zu erkennen als auch zu extrahieren und dabei über die verschiedensten Gestaltungen zu generalisieren. Dieses Ziel bezieht sich direkt auf die Forschungsfrage, nämlich inwieweit die Leistung von auf Graphen und auf unüberwachtes Lernen basierender Ansätze im Gegensatz zu neuronalen Netzen für Tabellenerkennungen vergleichbar ist. In dieser Arbeit werden textuelle Elemente dabei direkt aus PDF Dokumenten extrahiert. Darauffolgend wird ein Sichtbarkeitsgraph erstellt, welcher die Beziehungen zwischen diesen Elementen darstellt. Auf diesen Graph wird anschließend ein Clustering Algorithmus angewendet, welcher die Seiten eines Dokuments in logische Segmente unterteilt. Aus den resultierenden Segmenten werden Tabellen mithilfe von multimodalen Attributen klassifiziert. Eine Evaluation der Ergebnisse gibt Aufschluss darüber, dass das entwickelte System eine gute Erkennung auf verschiedene und auch nicht im Trainingsprozess eingeschlossene Formate bietet, ganz egal in welcher Form Tabellen visuell kommuniziert sind. Dies wurde ohne speziellen Parameteradaptionen erreicht, wobei solche unterstützt werden und dementsprechend zu besseren Ergebnissen für bestimmte Tabellenformate führen können.A structured content representation is the foundation for several systems, be it for an automated processing of documents when considering intelligent workflows or for general queries in the World Wide Web. However, vast amounts of information are stored in unstructured formats. A wide-spread example of such a format is the Portable Document Format (PDF). Therefore, a lot of unlocked potential lies in the derivation of structural characteristics from unstructured file formats. Important information in documents is often stored in tables, which provide a quite dense representation of content. However, detecting tables is a difficult task because of an infeasible amount of possible different visual or structural representations. Nowadays, most state-of-the-art systems for this task use Neural Networks which need a high amount of training data and have difficulties with handling out-of-the-box data. In this work, a system is developed with the aim of detecting and extracting tables from PDFs under a generalization over all kinds of layouts. This goal is directly related to the research question, namely how graph-based and unsupervised approaches compare to recently developed Neural Networks for table recognition. In this work, textual content is extracted directly from PDF documents. Then, a Visibility Graph from the extracted layout elements is created, indicating their relationships. On this graph, a clustering procedure is employed which segments a page into logical groups. From the resulting segments, tables are then classified using multimodal features. The evaluation shows that the developed system performs well on different and unseen layouts, irrespective of the visual representations of tables. This can be achieved without specific parameter tweaks, even though these can lead to even better performances on known table layouts and the system provides a possibility for such adaptions.11