Search

Tissues and organs provide the structural and biochemical landscapes upon which microbial pathogens and commensals function to regulate health and disease. While flat two-dimensional (2-D) monolayers composed of a single cell type have provided important insight into understanding host-pathogen interactions and infectious disease mechanisms, these reductionist models lack many essential features present in the native host microenvironment that are known to regulate infection, including three-dimensional (3-D) architecture, multicellular complexity, commensal microbiota, gas exchange and nutrient gradients, and physiologically relevant biomechanical forces (e.g., fluid shear, stretch, compression). A major challenge in tissue engineering for infectious disease research is recreating this dynamic 3-D microenvironment (biological, chemical, and physical/mechanical) to more accurately model the initiation and progression of host-pathogen interactions in the laboratory. Here we review selected 3-D models of human intestinal mucosa, which represent a major portal of entry for infectious pathogens and an important niche for commensal microbiota. We highlight seminal studies that have used these models to interrogate host-pathogen interactions and infectious disease mechanisms, and we present this literature in the appropriate historical context. Models discussed include 3-D organotypic cultures engineered in the rotating wall vessel (RWV) bioreactor, extracellular matrix (ECM)-embedded/organoid models, and organ-on-a-chip (OAC) models. Collectively, these technologies provide a more physiologically relevant and predictive framework for investigating infectious disease mechanisms and antimicrobial therapies at the intersection of the host, microbe, and their local microenvironments.

Pour travailler sur les dynamiques spatiales du tissu urbain implanté sur l’amphithéâtre antique de Tours, nous avons engagé une réflexion sur l’organisation des données mobilisées. Isolées, celles-ci permettent d’obtenir des renseignements significatifs mais ponctuels sur l’occupation du site. L’analyse spatiale doit donc porter sur une mise en commun de ces informations. La modélisation des données selon la méthode HBDS (Hypergraph Based Data Structure) apparaît comme une solution tout à fait efficace. Une déconstruction géographique des données historiques et archéologiques est alors nécessaire. Cette étape fondamentale permet en effet non seulement de rendre compte d’états successifs mais aussi des dynamiques spatiales.In order to understand the spatial dynamics of the urban fabric implanted on the site of the antique amphitheatre of Tours, it is necessary to analyse the data gathered. In isolation, this data allows for certain significant items of information to be collated concerning for example the occupation of the site, but this information is of a partial nature. Spatial analysis can only be based on the confrontation of different levels of data. Modelling data using the HBDS method (Hypergraph Based Data Structure) emerges as an efficient method. The geographical deconstruction of the historical and archaeological data is first necessary. This preliminary stage allows not only to account for succeeding states but also to understand spatial dynamics.

The first hours after a disaster happens are very chaotic and difficult but perhaps the most important for successfully fighting the consequences, saving human lives and reducing damages in private and public properties. Despite some advances, complete inventory of the information needed during the emergency response remains challenging. In the last years several nationally and internationally funded projects have concentrated on inventory of emergency response processes, structures for storing dynamic information and standards and services for accessing needed data sets. A good inventory would clarify many aspects of the information exchange such as data sets, models, representations; a good structuring would facilitate the fast access to a desired piece of information, as well as the automation of analysis of the information. Consequently the information can be used better in the decision-making process. This paper presents our work on models for dynamic data for different disasters and incidents in Europe. The Dutch data models are derived from a thorough study on emergency response procedure in the Netherlands. Two more models developed within the project HUMBOLDT reflect several cross border disaster management scenarios in Europe. These models are compared with the Geospatial Data Model of the Department of Homeland Security in USA. The paper draws conclusions about the type of geographical information needed to perform emergency response operations and the possibility to have a generic model to be used world-wide.

INDLEDNING: Siden 2000 Aarhus Workbench (aarhusgeo, 2008) er under konstant udvikling for at opfylde de forskningsmæssige behov for HydroGeophysics Group (HGG) ved Aarhus Universitet. Det giver dig mulighed for at håndtere, forarbejde, vendes og visualisere elektriske og elektromagnetisk (EM) data på en fælles GIS-platform. Geologiske data kan vises på GIS-kort og på tværs af sektioner for sammenligning med de geofysiske results.The grundlæggende idé i Aarhus Workbench var at udvikle en samlet og integreret software-platform til håndtering af en række forskellige datatyper. Den Workbench bruger en open source klient-server-database til at administrere data og indstillinger. Fordelene ved at bruge en databaser i forhold til fladt ASCII-kolonne-filer bør ikke undervurderes. For det første bruger-håndteres input / output er næsten elimineret, hvilket minimerer risikoen for menneskelige fejl. For det andet data gemmes i et nøje beskrevet og dokumenteret format, som er velegnet til både udveksling og opbevaring af data.The Workbench giver brugeren mulighed for at præsentere resultatet af inversioner som punkt temaer eller som farve Konturerne tematiske kort, som betyder resistivitet skiver , dybde til en dirigent osv. modeller kan også blive vist på strækninger, der er knyttet både til GIS og skærme af data og sende data. Det afsnit kan indeholde mange lag, der repræsenterer forskellige data types.Over årene HGG har udviklet stabil forarbejdning og inversion algoritmer til luftbårne og jordbaserede EM data. Den inversion er kendt som siderne Constrained inversion (LCI) for kvasi 2-D modellering og Rumlig Constrained inversion (SCI) for kvasi 3-D inversion. Den Workbench gennemfører et brugervenligt interface til disse algoritmer gør det muligt for ikke-geofysikere til at foretage inversion af komplicerede luftbårne datasæt uden at have indgående viden om, hvordan algoritmen rent faktisk virker. Lige så vigtigt er et omfattende system til evaluering af inversion resultater med afbildninger af resultater som resistivitet modeller, flyvning højde, hældning, rulning, residualer osv. INTRODUCTIONSince 2000 the Aarhus Workbench (aarhusgeo, 2008) is constantly developed to meet the research needs of the HydroGeophysics Group (HGG) at the University of Aarhus. It allows you to handle, process, invert and visualize electric and electromagnetic (EM) data on a common GIS platform. Geological data can be shown on the GIS map and on cross-sections for comparison with the geophysical results.The basic idea of the Aarhus Workbench was to develop a single and integrated software platform for handling a number of different data types. The Workbench uses an open-source client server database to manage data and settings. The benefits of using a databases compared to flat ASCII column files should not be underestimated. Firstly, user-handled input/output is nearly eliminated, thus minimizing the chance of human errors. Secondly, data are stored in a well described and documented format which is well suited for both exchange and storage of data.The Workbench allows the user to present the output of inversions as point themes or as color contoured thematic maps, such as mean resistivity slices, depth to a conductor etc. Models can also be shown on sections which are linked both to the GIS and to displays of data and forward data. The sections can contain numerous layers representing different data types.Over the years HGG has developed stable processing and inversion algorithms for airborne and ground-based EM data. The inversion is known as Laterally Constrained inversion (LCI) for quasi 2-D modeling and Spatial Constrained inversion (SCI) for quasi 3-D inversion. The Workbench implements a user friendly interface to these algorithms enabling non-geophysicists to carry out inversion of complicated airborne data sets without having in-depth knowledge about how the algorithm actually works. Just as important is an extensive system for evaluation of inversion results with plots of results like resistivity models, flight height, pitch, roll, residuals etc.

Wüstenameisen (Cataglyphis fortis) orientieren sich mittels Wegintegration sowie, in visuell abwechslungsreichem Gelände, anhand von Landmarken. In der vorliegenden Arbeit wurden in Verhaltensexperimenten die Orientierungsmechanismen von C. fortis im Kontext dreidimensionaler Routen untersucht. 1. Wüstenameisen sind in der Lage, Steigungen und Gefälle eines dreidimensionalen Laufs mit den korrespondierenden Grunddistanzen in ihren Heimvektor zu integrieren. Hierdurch bleibt eine zweidimensionale Wegintegration selbst in hügeligem Gelände akkurat. 2. Entlang bekannter Routen werden Eigenschaften eines Aufstiegs wie Winkel und Länge gespeichert. Wenn Auf- und Abstiege nur auf dem Hinweg zu einer Futterquelle auftreten, werden sie trotzdem auch auf dem Rückweg akzeptiert. 3. Erfolgreiche Aufstiege führen zu einer neu erlernten, generellen Akzeptanz von Rampen, selbst wenn ihr Auftreten inkongruent mit dem aktuell erlernten Lauf ist. 4. Haben Wüstenameisen im Test die Wahl zwischen einem Auf- bzw. Abstieg und einem horizontalen Kanal, entscheiden sie sich häufiger für die Rampen und legen auf ihnen größere Distanzen zurück, wenn auch das vorherige Training geneigte Streckenabschnitte besaß. Dies gilt auch, wenn die Kombination eines Auf- und Abstiegs im Training einen horizontalen Vektor zur Folge hatte. Die Reihenfolge von Auf- und Abstiegen wird jedoch nicht gespeichert, ebenso wenig die Distanz einer Rampe von Nest und Futterstelle. 5. Erzwungene vertikale Ablenkungen im Lauf einer Ameise werden nicht kompensiert. Der Heimvektor besitzt demnach keine vertikale Komponente, sondern funktioniert auf Basis der Korrektur geneigter Wegstrecken zu ihren entsprechenden Grunddistanzen. Cataglyphis fortis verfügt demnach nicht über eine tatsächlich dreidimensionale Repräsentation ihrer Routen. Stattdessen ermöglicht ihr wahrscheinlich das Zusammenspiel einer Reihe einfacherer Navigationsmechanismen eine genaue Orientierung auch in hügeligem Terrain., Desert ants (Cataglyphis fortis) orientate by means of path integration, and the use of landmarks, if available. In this thesis, behavioural experiments were conducted to elucidate C. fortis’ orientation mechanisms in the context of three-dimensional routes. 1 Along a three-dimensional route, desert ants are able to incorporate the ground distances of slopes into their home vector. Thus, two-dimensional path integration remains accurate also in hilly terrain. 2 Along familiar routes, ants store and recall a slope’s properties such as inclination and length. Even if ascents and descents only occur on the outbound trip, they are also accepted on the homebound run nevertheless. 3 Successful ascents result in a newly learnt, general acceptance of ramps, even if their occurrence is incongruent with a currently learnt route. 4 Given that desert ants can choose between a horizontal continuation of a channel and a ramp, they decide more often to walk on ramps if earlier training included sloped path segments, and continue to walk on them for greater distances. This is also the case if a combination of an ascent and descent results in a horizontal home vector during training. Neither their sequence nor the distance of a ramp from nest and feeder is stored and subsequently recalled. 5 Forced vertical detours in an ant’s run are not compensated for. The home vector consequently possesses no vertical component, and instead is functional due to the correction of sloped path segments to their respective ground distances. In summary, three-dimensional orientation in C. fortis is carried out by the combination of several mechanisms, namely (1) a global vector that corresponds to a plane projection of a route in the horizontal plane; (2) behavioural rules that are generally learnt; and (3) the storing and recollection of specific information along familiar routes.