Interrogation of related clinical pan-azole-resistant Aspergillus fumigatus strains: G138C, Y431C, and G434C single nucleotide polymorphisms in cyp51A, upregulation of cyp51A, and integration and activation of transposon Atf1 in the cyp51A promoter.

Multiple Aspergillus fumigatus isolates from a patient with two aspergillomas complicating chronic pulmonary aspergillosis were pan-azole resistant. Microsatellite typing was identical for all isolates despite major phenotypic and some growth rate differences. Three different cyp51A mutations were found (G138C, Y431C, and G434C), of which the first two were demonstrated by heterologous expression in a hypersusceptible Saccharomyces cerevisiae strain to be at least partly responsible for elevated MICs. cyp51A and cyp51B gene duplication was excluded, but increased expression of cyp51A was demonstrated in three isolates selected for additional study (7-to 13-fold increases). In the isolate with the greatest cyp51A expression, an Aft1 transposon was found inserted 370 bp upstream of the start codon of the cyp51A gene, an integration location never previously demonstrated in Aspergillus. Two transcription start sites were identified at 49 and 136 bp upstream of the start codon. The role of the Aft1 transposon, if any, in modulating cyp51A expression remains to be established. Increased mRNA expression of the transporters AfuMDR1 and AfuMDR4 also was demonstrated in some isolates, which could contribute to azole resistance or simply represent a stress response. The diversity of confirmed and possible azole resistance mechanisms demonstrated in a single series of isogenic isolates is remarkable, indicating the ability of A. fumigatus to adapt in the clinical setting.

Man Made Black Holes and Big Bangs: Diffusion and Integration of Scientific Information into Everyday Thinking

Drawing on Social Representations Theory, this study investigates focalisation and anchoring during the diffusion of information concerning the Large Hadron Collider (LHC), the particle accelerator at the European Organisation for Nuclear Research (CERN). We hypothesised that people focus on striking elements of the message, abandoning others, that the nature of the initial information affects diffusion of information, and that information is anchored in prior attitudes toward CERN and science. A serial reproduction experiment with two generations and four chains of reproduction diffusing controversial versus descriptive information about the LHC shows a reduction of information through generations, the persistence of terminology regarding the controversy and a decrease of other elements for participants exposed to polemical information. Concerning anchoring, positive attitudes toward CERN and science increase the use of expert terminology unrelated to the controversy. This research highlights the relevance of a social representational approach in the public understanding of science.

Synergy Sources, Target Autonomy and Integration in Acquisitions

Determining the appropriate level of integration is crucial to realizing value from acquisitions. Most prior research assumes that higher integration implies the removal of autonomy from target managers, which in turn undermines the functioning of the target firm if it entails unfamiliar elements for the acquirer. Using a survey of 86 acquisitions to obtain the richness of detail necessary to distinguish integration from autonomy, the authors argue and find that integration and autonomy are not the opposite ends of a single continuum. Certain conditions (e.g., when complementarity rather than similarity is the primary source of synergy) lead to high levels of both integration and autonomy. In addition, similarity negatively moderates the relationship between complementarity and autonomy when the target offers both synergy sources. In contrast, similarity does not moderate the link between complementarity and integration. The authors' findings advance scholarly understanding about the drivers of implementation strategy and in particular the different implementation strategies acquiring managers deploy when they attempt to leverage complementarities, similarities, or both.

Transforming scientific information with everyday thinking: A social representations perspective

Cette thèse examine la circulation et l'intégration des informations scientifiques dans la pensée quotidienne d'après la théorie des représentations sociales (TRS). En tant qu'alternative aux approches traditionnelles de la communication de la science, les transformations survenant entre le discours scientifique et le discours de sens commun sont considérées comme adaptatives. Deux études sur la circulation des informations dans les media (études 1 et 2) montrent des variations dans les thèmes de discours exposés aux profanes, et parmi les discours de ceux-ci, en fonction de différentes sources. Ensuite, le processus d'ancrage dans le positionnement préalable envers la science est étudié, pour l'explication qu'il fournit de la réception et de la transmission d'informations scientifiques dans le sens commun. Les effets d'ancrage dans les attitudes et croyances préexistants sont reportés dans différents contextes de circulation des informations scientifiques (études 3 à 7), incluant des études de type corrélationnel, experimental et de terrain. Globalement, cette thèse procure des arguments en faveur de la pertinence de la TRS pour la recherche sur la communication de la science, et suggère des développements théoriques et méthodologiques pour ces deux domaines de recherche. Drawing on the social representations theory (SRT), this thesis examines the circulation and integration of scientific information into everyday thinking. As an alternative to the traditional approaches of science communication, it considers transformations between scientific and common-sense discourses as adaptive. Two studies, focused on the spreading of information into the media (Studies 1 and 2), show variations in the themes of discourses introduced to laypersons and in the themes among laypersons' discourses, according to different sources. Anchoring in prior positioning toward science is then studied for the explanation it provides on the reception and transmission of scientific information into common sense. Anchoring effects in prior attitudes and beliefs are reported in different contexts of circulation of scientific information (Studies 3 to 7) by using results from correlational, field, and experimental studies. Overall, this thesis provides arguments for the relevance of SRT in science communication research and suggests theoretical and methodological developments for both domains of research.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Stochasticity and bistability in horizontal transfer control of a genomic island in Pseudomonas.

Genomic islands (GEI) comprise a recently recognized large family of potentially mobile DNA elements and play an important role in the rapid differentiation and adaptation of bacteria. Most importantly, GEIs have been implicated in the acquisition of virulence factors, antibiotic resistances or toxic compound metabolism. Despite detailed information on coding capacities of GEIs, little is known about the regulatory decisions in individual cells controlling GEI transfer. Here, we show how self-transfer of ICEclc, a GEI in Pseudomonas knackmussii B13 is controlled by a series of stochastic processes, the result of which is that only a few percent of cells in a population will excise ICEclc and launch transfer. Stochastic processes have been implicated before in producing bistable phenotypic transitions, such as sporulation and competence development, but never before in horizontal gene transfer (HGT). Bistability is instigated during stationary phase at the level of expression of an activator protein InrR that lays encoded on ICEclc, and then faithfully propagated to a bistable expression of the IntB13 integrase, the enzyme responsible for excision and integration of the ICEclc. Our results demonstrate how GEI of a very widespread family are likely to control their transfer rates. Furthermore, they help to explain why HGT is typically confined to few members within a population of cells. The finding that, despite apparent stochasticity, HGT rates can be modulated by external environmental conditions provides an explanation as to why selective conditions can promote DNA exchange.

Geophysical Investigations for Hydrogeological Characterization at the Kappelen Test Site (Switzerland)

Vertical electric soundings, 2D resistivity imaging and several logging measurements were performed at Kappelen test site to identify the various geolelectric facies that allowed determining the tabular and horizontal structure of the aquifer. The surface-based geoelectric methods allowed for a reliable characterization of the overall structure and the geometry of the aquifer, while geophysical logging methods allowed for inferring detailed hydrogeophysical characteristics, such as the electrical resistivity, total porosity, global and matrix density and hydraulic conductivity. The synoptic interpretation and integration of this broad and diverse database allows for constraining the key hydrological characteristics and hence forms the basis for the detailed hydraulic modelling of flow and transport process.

NOTCH1 can initiate NF-κB activation via cytosolic interactions with components of the T cell Signalosome.

T cell stimulation requires the input and integration of external signals. Signaling through the T cell receptor (TCR) is known to induce formation of the membrane-tethered CBM complex, comprising CARMA1, BCL10, and MALT1, which is required for TCR-mediated NF-κB activation. TCR signaling has been shown to activate NOTCH proteins, transmembrane receptors also implicated in NF-κB activation. However, the link between TCR-mediated NOTCH signaling and early events leading to induction of NF-κB activity remains unclear. In this report, we demonstrate a novel cytosolic function for NOTCH1 and show that it is essential to CBM complex formation. Using a model of skin allograft rejection, we show in vivo that NOTCH1 acts in the same functional pathway as PKCθ, a T cell-specific kinase important for CBM assembly and classical NF-κB activation. We further demonstrate in vitro NOTCH1 associates physically with PKCθ and CARMA1 in the cytosol. Unexpectedly, when NOTCH1 expression was abrogated using RNAi approaches, interactions between CARMA1, BCL10, and MALT1 were lost. This failure in CBM assembly reduced inhibitor of kappa B alpha phosphorylation and diminished NF-κB-DNA binding. Finally, using a luciferase gene reporter assay, we show the intracellular domain of NOTCH1 can initiate robust NF-κB activity in stimulated T cells, even when NOTCH1 is excluded from the nucleus through modifications that restrict it to the cytoplasm or hold it tethered to the membrane. Collectively, these observations provide evidence that NOTCH1 may facilitate early events during T cell activation by nucleating the CBM complex and initiating NF-κB signaling.

Human muscular fetal cells: a potential cell source for muscular therapies.

Myoblast transfer therapy has been extensively studied for a wide range of clinical applications, such as tissue engineering for muscular loss, cardiac surgery or Duchenne Muscular Dystrophy treatment. However, this approach has been hindered by numerous limitations, including early myoblast death after injection and specific immune response after transplantation with allogenic cells. Different cell sources have been analyzed to overcome some of these limitations. The object of our study was to investigate the growth potential, characterization and integration in vivo of human primary fetal skeletal muscle cells. These data together show the potential for the creation of a cell bank to be used as a cell source for muscle cell therapy and tissue engineering. For this purpose, we developed primary muscular cell cultures from biopsies of human male thigh muscle from a 16-week-old fetus and from donors of 13 and 30 years old. We show that fetal myogenic cells can be successfully isolated and expanded in vitro from human fetal muscle biopsies, and that fetal cells have higher growth capacities when compared to young and adult cells. We confirm lineage specificity by comparing fetal muscle cells to fetal skin and bone cells in vitro by immunohistochemistry with desmin and 5.1 H11 antibodies. For the feasibility of the cell bank, we ensured that fetal muscle cells retained intrinsic characteristics after 5 years cryopreservation. Finally, human fetal muscle cells marked with PKH26 were injected in normal C57BL/6 mice and were found to be present up to 4 days. In conclusion we estimate that a human fetal skeletal muscle cell bank can be created for potential muscle cell therapy and tissue engineering.

The role of the radiotherapy technologist in gamma knife radiosurgery within a multidisciplinary team: the Lausanne experience

Objective: Integration of the radiotherapy technologist "know-how" in the Gamma Knife treatment processMaterials and Methods: Gamma Knife (GK) treatments started in July 2010 at the GK Center in C.H.U.V. with the Leksell Gamma KnifeR Perfexion?(Elekta AB, Sweden). The multidisciplinary GK team involves neurosurgeons, radio-oncologists, physicists, neuroradiologists, nurses and technologists, aiming at a full integration for optimal patient management.Results: Between July and December 2010, 60 patients have been treated. Required stereotactic imaging involves IRM, CT scan (and angiography for AVM). All the steps in the treatment process (Leksell coordinate frame fixation, imaging, planning, treatment) are supervised by the members of the multidisciplinary team. In our experience, radiotherapy technologist (RTT) have acquired an important role in the multidisciplinary team communication and integration. Specifically, the RTT are responsible of: supervision of the image acquisition, performing the Gamma Knife unit control tests, patient setup, and patient surveillance during treatment.Conclusion: RTT have a fundamental role in the communication within the team, between the team and the patient and also to assure the patient security. Our experience shows that it is possible and required to involve RTT in all steps of the GK treatment process, to guarantee the best GK treatment possible.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

The GENCODE pseudogene resource.

BACKGROUND: Pseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data. RESULTS: As part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection. CONCLUSIONS: At one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.