Increased sporulation underpins adaptation of Clostridium difficile strain 630 to a biologically–relevant faecal environment, with implications for pathogenicity

Abstract Clostridium difficile virulence is driven primarily by the processes of toxinogenesis and sporulation, however many in vitro experimental systems for studying C. difficile physiology have arguably limited relevance to the human colonic environment. We therefore created a more physiologically–relevant model of the colonic milieu to study gut pathogen biology, incorporating human faecal water (FW) into growth media and assessing the physiological effects of this on C. difficile strain 630. We identified a novel set of C. difficile–derived metabolites in culture supernatants, including hexanoyl– and pentanoyl–amino acid derivatives by LC-MSn. Growth of C. difficile strain 630 in FW media resulted in increased cell length without altering growth rate and RNA sequencing identified 889 transcripts as differentially expressed (p < 0.001). Significantly, up to 300–fold increases in the expression of sporulation–associated genes were observed in FW media–grown cells, along with reductions in motility and toxin genes’ expression. Moreover, the expression of classical stress–response genes did not change, showing that C. difficile is well–adapted to this faecal milieu. Using our novel approach we have shown that interaction with FW causes fundamental changes in C. difficile biology that will lead to increased disease transmissibility

Clostridium difficile infection.

Infection of the colon with the Gram-positive bacterium Clostridium difficile is potentially life threatening, especially in elderly people and in patients who have dysbiosis of the gut microbiota following antimicrobial drug exposure. C. difficile is the leading cause of health-care-associated infective diarrhoea. The life cycle of C. difficile is influenced by antimicrobial agents, the host immune system, and the host microbiota and its associated metabolites. The primary mediators of inflammation in C. difficile infection (CDI) are large clostridial toxins, toxin A (TcdA) and toxin B (TcdB), and, in some bacterial strains, the binary toxin CDT. The toxins trigger a complex cascade of host cellular responses to cause diarrhoea, inflammation and tissue necrosis - the major symptoms of CDI. The factors responsible for the epidemic of some C. difficile strains are poorly understood. Recurrent infections are common and can be debilitating. Toxin detection for diagnosis is important for accurate epidemiological study, and for optimal management and prevention strategies. Infections are commonly treated with specific antimicrobial agents, but faecal microbiota transplants have shown promise for recurrent infections. Future biotherapies for C. difficile infections are likely to involve defined combinations of key gut microbiota

INTEGRATING AND MANAGING BIM IN GIS, SOFTWARE REVIEW

International audienc

Automatic Reconstruction of 3D Building Models from Terrestrial Laser Scanner Data

With modern 3D laser scanners we can acquire a large amount of 3D data in only a few minutes. This technology results in a growing number of applications ranging from the digitalization of historical artifacts to facial authentication. The modeling process demands a lot of time and work (Tim Volodine, 2007). In comparison with the other two stages, the acquisition and the registration, the degree of automation of the modeling stage is almost zero. In this paper, we propose a new surface reconstruction technique for buildings to process the data obtained by a 3D laser scanner. These data are called a point cloud which is a collection of points sampled from the surface of a 3D object. Such a point cloud can consist of millions of points. In order to work more efficiently, we worked with simplified models which contain less points and so less details than a point cloud obtained in situ. The goal of this study was to facilitate the modeling process of a building starting from 3D laser scanner data. In order to do this, we wrote two scripts for Rhinoceros 5.0 based on intelligent algorithms. The first script finds the exterior outline of a building. With a minimum of human interaction, there is a thin box drawn around the surface of a wall. This box is able to rotate 360° around an axis in a corner of the wall in search for the points of other walls. In this way we can eliminate noise points. These are unwanted or irrelevant points. If there is an angled roof, the box can also turn around the edge of the wall and the roof. With the different positions of the box we can calculate the exterior outline. The second script draws the interior outline in a surface of a building. By interior outline we mean the outline of the openings like windows or doors. This script is based on the distances between the points and vector characteristics. Two consecutive points with a relative big distance will form the outline of an opening. Once those points are found, the interior outline can be drawn. The designed scripts are able to ensure for simple point clouds: the elimination of almost all noise points and the reconstruction of a CAD model

Developing Optimal Paths for Evacuating Risky Construction Sites

International audienc

Optimal construction site layout based on risk spatial variability

International audienc

UTILIZING MOBILE SENSING TO INVESTIGATE THE EFFECTS OF URBAN SPACE ON USERS BEHAVIOR

International audienc

Indoor guided evacuation: TIN for graph generation and crowd evacuation

International audienc

Hazards, Vulnerability and Interactions at Construction Sites: spatial risk mapping

International audienceConstruction sites contain several supporting facilities that are required to perform construction activities. These facilities may be exposed to several hazards. This may lead to adverse consequences for the whole construction process, which in turn lead to fatal accidents that have a major impact on worker and employee productivity, project completion time, project quality and project budget. This paper proposes a framework to visualize spatial variability of a construction site's risk, generated by natural or technological hazard, through using hazard and vulnerability interaction matrices, between potential sources and potential surrounding targets. The proposed framework depends on using analytical hierarchy process (AHP), the potential global impact of facilities obtained from the interaction matrices, and the capabilities of GIS to generate results in the mapping form. The methodology is implemented in a real case project. The results show the capability of framework to visualize construction site risks due to natural or technological hazard, and also identify the most at risk position within a construction site

UAV PHOTOGRAMMETRY IMPLEMENTATION TO ENHANCE LAND SURVEYING, COMPARISONS AND POSSIBILITIES

The use of Unmanned Aerial Vehicles (UAVs) for surveying is now widespread and operational for several applications – quarry monitoring, archeological site surveys, forest management and 3D modeling for buildings, for instance. UAV is increasingly used by land surveyors especially for those kinds of projects. It is still ambiguous whether UAV can be applicable for smaller sites and property division. Therefore, the objective of this research is to extract a vectorized plan utilizing a UAV for a small site and investigate the possibility of an official land surveyor exploiting and certificating it. To do that, two plans were created, one using a UAV and another utilizing classical land surveyor instruments (Total Station). A comparison was conducted between the two plans to evaluate the accuracy of the UAV technique compared to the classical one. Moreover, other parameters were also considered such as execution time and the surface covered. The main problems associated with using a UAV are the level of precision and the visualization of the whole area. The results indicated that the precision is quite satisfactory with a maximum error of 1.0&thinsp;cm on ground control points, and 4&thinsp;cm for the rest of the model. On the other hand, the results showed that it is not possible to represent the whole area of interest utilizing a UAV, due to vegetation