Persistent infection of arenaviruses : molecular mechanisms and pathogenesis

Arenaviruses are enveloped negative single strand RNA viruses that include a number of important human pathogens. The most prevalent human pathogen among the arenaviruses is the Old World arenavirus Lassa virus (LASV) which is endemic in West Africa from Senegal to Cameroon. LASV is the etiologic agent of a severe viral hemorrhagic fever named Lassa fever whose mortality rate can reach 30% in hospitalized patients. One of the hallmarks of fatal arenavirus infection in humans is the absence of an effective innate and adaptive immune response. In nature, arenaviruses are carried by rodents which represent the natural reservoirs as well as the vectors for transmission. In their natural rodent reservoir, arenaviruses have the ability to establish persistent infection without any overt signs and symptoms of pathology. We believe that the modulation of the host cell's innate immunity by arenaviruses is a key determinant for persistence in the natural host and for the pathogenesis in man. In this thesis, we studied the interaction of arenaviruses with two main branches of the host's innate anti-viral defense, the type I interferon (IFN) system and virus-induced mitochondrial apoptosis. The arenavirus nucleoprotein (NP) is responsible for the anti-IFN activity of arenaviruses. Specifically, NP blocks the activation and the nuclear translocation of the transcription factor interferon regulatory factor 3 (IRF3) which leads to type I IFN production. LASV and the prototypic arenavirus lymphocytic choriomeningitis virus (LCMV) NPs contain a 3'-5'exoribonuclease domain in the C terminal part that has been linked to the anti-IFN activity of NP. In the first project, we sought to identify cellular component(s) of the type I IFN induction pathway targeted by the viral NP. Our study revealed that LCMV NP prevents the activation of IRF3 by blocking phosphorylation of the transcription factor. We found that LCMV NP specifically targets the IRF-activating kinase IKKs, and this specific binding is conserved within the Arenaviridae. We could also demonstrate that LCMV NP associates with the kinase domain of IKKs involving NP's C-terminal region. Lastly, we showed that the binding of LCMV NP inhibits the kinase activity of IKKs. This study allowed the discovery of a new cellular interacting partner of arenavirus NP. This newly described association may play a role in the anti-IFN activity of arenaviruses but potentially also in other aspects of arenavirus infection. For the second project, we investigated the ability of arenaviruses to avoid and/or suppress mitochondrial apoptosis. As persistent viruses, arenaviruses evolved a "hit and stay" survival strategy where the apoptosis of the host cell would be deleterious. We found that LCMV does not induce mitochondrial apoptosis at any time during infection. Specifically, no caspase activity, no cytochrome c release from the mitochondria as well as no cleavage of poly (ADP-ribose) polymerase (PARP) were detected during LCMV infection. Interestingly, we found that virus-induced mitochondrial apoptosis remains fully functional in LCMV infected cells, while the induction of type IIFN is blocked. Since both type IIFN production and virus- induced mitochondrial apoptosis critically depend on the pattern recognition receptor (PRR) RIG-I, we examined the role of RIG-I in apoptosis in LCMV infected cells. Notably, virus- induced mitochondrial apoptosis in LCMV infected cells was found to be independent of RIG- I and MDA5, but still depended on MAVS. Our study uncovered a novel mechanism by which arenaviruses alter the host cell's pro-apoptotic signaling pathway. This might represent a strategy arenaviruses developed to maintain this branch of the innate anti-viral defense in absence of type I IFN response. Taken together, these results allow a better understanding of the interaction of arenaviruses with the host cell's innate immunity, contributing to our knowledge about pathogenic properties of these important viruses. A better comprehension of arenavirus virulence may open new avenues for vaccine development and may suggest new antiviral targets for therapeutic intervention against arenavirus infections. - Les arenavirus sont des virus enveloppés à ARN simple brin qui comportent un grand nombre de pathogènes humains. Le pathogène humain le plus important parmi les arenavirus est le virus de Lassa qui est endémique en Afrique de l'Ouest, du Sénégal au Cameroun. Le virus de Lassa est l'agent étiologique d'une fièvre hémorragique sévère appelée fièvre de Lassa, et dont le taux de mortalité peut atteindre 30% chez les patients hospitalisés. L'une des caractéristiques principales des infections fatales à arenavirus chez l'Homme est l'absence de réponse immunitaire innée et adaptative. Dans la nature, les arenavirus sont hébergés par différentes espèces de rongeur, qui représentent à la fois les réservoirs naturels et les vecteurs de transmission des arenavirus. Dans leur hôte naturel, les arenavirus ont la capacité d'établir une infection persistante sans symptôme manifeste d'une quelconque pathologie. Nous pensons que la modulation de système immunitaire inné de la cellule hôte par les arenavirus est un paramètre clé pour la persistance au sein de l'hôte naturel, ainsi que pour la pathogenèse chez l'Homme. L'objectif de cette thèse était d'étudier l'interaction des arenavirus avec deux branches essentielles de la défense antivirale innée de la cellule hôte, le système interféron (IFN) de type I et l'apoptose. La nucléoprotéine virale (NP) est responsable de l'activité anti-IFN des arenavirus. Plus spécifiquement, la NP bloque 1'activation et la translocation nucléaire du facteur de transcription IRF3 qui conduit à la production des IFNs de type I. La NP du virus de Lassa et celle du virus de la chorioméningite lymphocytaire (LCMV), l'arénavirus prototypique, possèdent dans leur extrémité C-terminale un domaine 3'-5' exoribonucléase qui a été associé à l'activité anti-IFN de ces protéines. Dans un premier projet, nous avons cherché à identifier des composants cellulaires de la cascade de signalisation induisant la production d'IFNs de type I qui pourraient être ciblés par la NP virale. Nos recherches ont révélé que la NP de LCMV empêche 1'activation d'IRF3 en bloquant la phosphorylation du facteur de transcription. Nous avons découvert que la NP de LCMV cible spécifiquement la kinase IKKe, et que cette interaction spécifique est conservée à travers la famille des Arenaviridae. Notre étude a aussi permis de démontrer que la NP de LCMV interagit avec le domaine kinase d'IKKe et que l'extrémité C-terminale de la NP est impliquée. Pour finir, nous avons pu établir que l'association avec la NP de LCMV inhibe l'activité kinase d'IKKe. Cette première étude présente la découverte d'un nouveau facteur cellulaire d'interaction avec la NP des arenavirus. Cette association pourrait jouer un rôle dans l'activité anti-IFN des arénavirus, mais aussi potentiellement dans d'autres aspects des infections à arénavirus. Pour le second projet, nous nous sommes intéressés à la capacité des arénavirus à éviter et/ou supprimer l'apoptose mitochondriale. En tant que virus persistants, les arénavirus ont évolué vers une stratégie de survie "hit and stay" pour laquelle l'apoptose de la cellule hôte serait néfaste. Nous avons observé qu'à aucun moment durant l'infection LCMV n'induit l'apoptose mitochondriale. Spécifiquement, aucune activité de caspase, aucune libération mitochondriale de cytochrome c ainsi qu'aucun clivage de la polymerase poly(ADP-ribose) (PARP) n'a été détecté pendant l'infection à LCMV. Il est intéressant de noter que l'apoptose mitochondriale induite par les virus reste parfaitement fonctionnelle dans les cellules infectées par LCMV, alors que l'induction de la réponse IFN de type I est bloquée dans les mêmes cellules. La production des IFNs de type I et l'apoptose mitochondriale induite par les virus dépendent toutes deux du récepteur de reconnaissance de motifs moléculaires RIG-I. Nous avons, par conséquent, investigué le rôle de RIG-I dans l'apoptose qui a lieu dans les cellules infectées par LCMV lorsqu'on les surinfecte avec un autre virus pro-apoptotique. En particulier, l'apoptose mitochondriale induite par les surinfections s'est révélée indépendante de RIG-I et MDA5, mais dépendante de MAVS dans les cellules précédemment infectées par LCMV. Notre étude démontre ainsi l'existence d'un nouveau mécanisme par lequel les arénavirus altèrent la cascade de signalisation pro-apoptotique de la cellule hôte. Il est possible que les arénavirus aient développé une stratégie permettant de maintenir fonctionnelle cette branche de la défense antivirale innée en l'absence de réponse IFN de type I. En conclusion, ces résultats nous amènent à mieux comprendre l'interaction des arénavirus avec l'immunité innée de la cellule hôte, ce qui contribue aussi à améliorer notre connaissance des propriétés pathogéniques de ces virus. Une meilleure compréhension des facteurs de virulence des arénavirus permet, d'une part, le développement de vaccins et peut, d'autre part, servir de base pour la découverte de nouvelles cibles thérapeutiques utilisées dans le traitement des infections à arénavirus.

Evaluation of the user-friendliness of seven new generation intensive care ventilators.

OBJECTIVE: To explore the user-friendliness and ergonomics of seven new generation intensive care ventilators. DESIGN: Prospective task-performing study. SETTING: Intensive care research laboratory, university hospital. METHODS: Ten physicians experienced in mechanical ventilation, but without prior knowledge of the ventilators, were asked to perform eight specific tasks [turning the ventilator on; recognizing mode and parameters; recognizing and setting alarms; mode change; finding and activating the pre-oxygenation function; pressure support setting; stand-by; finding and activating non-invasive ventilation (NIV) mode]. The time needed for each task was compared to a reference time (by trained physiotherapist familiar with the devices). A time >180 s was considered a task failure. RESULTS: For each of the tests on the ventilators, all physicians' times were significantly higher than the reference time (P < 0.001). A mean of 13 +/- 8 task failures (16%) was observed by the ventilator. The most frequently failed tasks were mode and parameter recognition, starting pressure support and finding the NIV mode. Least often failed tasks were turning on the pre-oxygenation function and alarm recognition and management. Overall, there was substantial heterogeneity between machines, some exhibiting better user-friendliness than others for certain tasks, but no ventilator was clearly better that the others on all points tested. CONCLUSIONS: The present study adds to the available literature outlining the ergonomic shortcomings of mechanical ventilators. These results suggest that closer ties between end-users and manufacturers should be promoted, at an early development phase of these machines, based on the scientific evaluation of the cognitive processes involved by users in the clinical setting.

Automated identification of minimal myocardial motion for improved image quality on MR angiography at 3 T

OBJECTIVE: Imaging during a period of minimal myocardial motion is of paramount importance for coronary MR angiography (MRA). The objective of our study was to evaluate the utility of FREEZE, a custom-built automated tool for the identification of the period of minimal myocardial motion, in both a moving phantom at 1.5 T and 10 healthy adults (nine men, one woman; mean age, 24.9 years; age range, 21-32 years) at 3 T. CONCLUSION: Quantitative analysis of the moving phantom showed that dimension measurements approached those obtained in the static phantom when using FREEZE. In vitro, vessel sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were significantly improved when coronary MRA was performed during the software-prescribed period of minimal myocardial motion (p < 0.05). Consistent with these objective findings, image quality assessments by consensus review also improved significantly when using the automated prescription of the period of minimal myocardial motion. The use of FREEZE improves image quality of coronary MRA. Simultaneously, operator dependence can be minimized while the ease of use is improved.

The immunological, environmental, and phylogenetic perpetrators of metastatic leishmaniasis.

Cutaneous leishmaniases have persisted for centuries as chronically disfiguring parasitic infections affecting millions of people across the subtropics. Symptoms range from the more prevalent single, self-healing cutaneous lesion to a persistent, metastatic disease, where ulcerations and granulomatous nodules can affect multiple secondary sites of the skin and delicate facial mucosa, even sometimes diffusing throughout the cutaneous system as a papular rash. The basis for such diverse pathologies is multifactorial, ranging from parasite phylogeny to host immunocompetence and various environmental factors. Although complex, these pathologies often prey on weaknesses in the innate immune system and its pattern recognition receptors. This review explores the observed and potential associations among the multifactorial perpetrators of infectious metastasis and components of the innate immune system.

Scour Around Bridge Piers and Abutments, HR-30 and Iowa Highway Research Board Bulletin No. 4, 1956

Man’s never-ending search for better materials and construction methods and for techniques of analysis and design has overcome most of the early difficulties of bridge building. Scour of the stream bed, however, has remained a major cause of bridge failures ever since man learned to place piers and abutments in the stream in order to cross wide rivers. Considering the overall complexity of field conditions, it is not surprising that no generally accepted principles (not even rules of thumb) for the prediction of scour around bridge piers and abutments have evolved from field experience alone. The flow of individual streams exhibits a manifold variation, and great disparity exists among different rivers. The alignment, cross section, discharge, and slope of a stream must all be correlated with the scour phenomenon, and this in turn must be correlated with the characteristics of the bed material ranging from clays and fine silts to gravels and boulders. Finally, the effect of the shape of the obstruction itself-the pier or abutment-must be assessed. Since several of these factors are likely to vary with time to some degree, and since the scour phenomenon as well is inherently unsteady, sorting out the influence of each of the various factors is virtually impossible from field evidence alone. The experimental approach was chosen as the investigative method for this study, but with due recognition of the importance of field measurements and with the realization that the results must be interpreted so as to be compatible with the present-day theories of fluid mechanics and sediment transportation. This approach was chosen because, on the one hand, the factors affecting the scour phenomenon can be controlled in the laboratory to an extent that is not possible in the field, and, on the other hand, the model technique can be used to circumvent the present inadequate understanding of the phenomenon of the movement of sediment by flowing water. In order to obtain optimum results from the laboratory study, the program was arranged at the outset to include a related set of variables in each of several phases into which the whole problem was divided. The phases thus selected were : 1. Geometry of piers and abutments, 2. Hydraulics of the stream, 3. Characteristics of the sediment, 4. Geometry of channel shape and alignment.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease.

OBJECTIVE: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.

Nuclear translocation and DNA recognition signals colocalized within the bZIP domain of cyclic adenosine 3',5'-monophosphate response element-binding protein CREB.

CREB is a cAMP-responsive nuclear DNA-binding protein that binds to cAMP response elements and stimulates gene transcription upon activation of the cAMP signalling pathway. The protein consists of an amino-terminal transcriptional transactivation domain and a carboxyl-terminal DNA-binding domain (bZIP domain) comprised of a basic region and a leucine zipper involved in DNA recognition and dimerization, respectively. Recently, we discovered a testis-specific transcript of CREB that contains an alternatively spliced exon encoding multiple stop codons. CREB encoded by this transcript is a truncated protein lacking the bZIP domain. We postulated that the antigen detected by CREB antiserum in the cytoplasm of germinal cells is the truncated CREB that must also lack its nuclear translocation signal (NTS). To test this hypothesis we prepared multiple expression plasmids encoding carboxyl-terminal deletions of CREB and transiently expressed them in COS-1 cells. By Western immunoblot analysis as well as immunocytochemistry of transfected cells, we show that CREB proteins truncated to amino acid 286 or shorter are sequestered in the cytoplasm, whereas a CREB of 295 amino acids is translocated into the nucleus. Chimeric CREBs containing a heterologous NTS fused to the first 248 or 261 amino acids of CREB are able to drive the translocation of the protein into the nucleus. Thus, the nine amino acids in the basic region involved in DNA recognition between positions 287 and 295 (RRKKKEYVK) of CREB contain the NTS. Further, mutation of the lysine at position 290 in CREB to an asparagine diminishes nuclear translocation of the protein.(ABSTRACT TRUNCATED AT 250 WORDS)

Toxicity of triclosan, penconazole and metalaxyl on Caulobacter crescentus and a freshwater microbial community as assessed by flow cytometry.

Biocides are widely used for domestic hygiene, agricultural and industrial applications. Their widespread use has resulted in their introduction into the environment and raised concerns about potential deleterious effects on aquatic ecosystems. In this study, the toxicity of the biocides triclosan, penconazole and metalaxyl were evaluated with the freshwater bacterium Caulobacter crescentus and with a freshwater microbial community using a combination of single- and double-stain flow cytometric assays. Growth of C.  crescentus and the freshwater community were repressed by triclosan but not by penconazole or metalaxyl at concentrations up to 250 μM. The repressive effect of triclosan was dependent on culture conditions. Caulobacter crescentus was more sensitive to triclosan when grown with high glucose at high cell density than when grown directly in sterilized lake water at low cell density. This suggests that the use of conventional growth conditions may overestimate biocide toxicity. Additional experiments showed that the freshwater community was more sensitive to triclosan than C.  crescentus, with 10 nM of triclosan being sufficient to repress growth and change the phylogenetic composition of the community. These results demonstrate that isolate-based assays may underestimate biocide toxicity and highlight the importance of assessing toxicity directly on natural microbial communities. Because 10 nM of triclosan is within the range of concentrations observed in freshwater systems, these results also raise concerns about the risk of introducing triclosan into the environment.

Compendium of projects in the European nanosafety cluster

This is the fourth edition of the Nanosafety Cluster compendium. It documents the status of important projects on nanomaterial toxicity and exposure monitoring, integrated risk management, research infrastructure and coordination and support activities. The compendium is not intended to be a guidance document for human health and environmental safety management of nanotechnologies, as such guidance documents already exist and are widely available. Neither is the compendium intended to be a medium for the publication of scientific papers and research results, as this task is covered by scientific conferences and the peer reviewed press. The compendium aims to bring researchers closer together and show them the potential for synergy in their work. It is a means to establish links and communication between them during the actual research phase and well before the publication of their results. It thus focuses on the communication of projects' strategic aims, extensively covers specific work objectives and the methods used in research, and documents human capacities and available laboratory infrastructure. As such, the compendium supports collaboration on common goals and the joint elaboration of future plans, whilst compromising neither the potential for scientific publication, nor intellectual property rights.

Oops! Another medication error : a literature review of contributing factors and methods to prevent medication errors

The purpose of this bachelor's thesis was to chart scientific research articles to present contributing factors to medication errors done by nurses in a hospital setting, and introduce methods to prevent medication errors. Additionally, international and Finnish research was combined and findings were reflected in relation to the Finnish health care system. Literature review was conducted out of 23 scientific articles. Data was searched systematically from CINAHL, MEDIC and MEDLINE databases, and also manually. Literature was analysed and the findings combined using inductive content analysis. Findings revealed that both organisational and individual factors contributed to medication errors. High workload, communication breakdowns, unsuitable working environment, distractions and interruptions, and similar medication products were identified as organisational factors. Individual factors included nurses' inability to follow protocol, inadequate knowledge of medications and personal qualities of the nurse. Developing and improving the physical environment, error reporting, and medication management protocols were emphasised as methods to prevent medication errors. Investing to the staff's competence and well-being was also identified as a prevention method. The number of Finnish articles was small, and therefore the applicability of the findings to Finland is difficult to assess. However, the findings seem to fit to the Finnish health care system relatively well. Further research is needed to identify those factors that contribute to medication errors in Finland. This is a necessity for the development of methods to prevent medication errors that fit in to the Finnish health care system.

Targeting Toll-Like Receptors: Promising Therapeutic Strategies for the Management of Sepsis-Associated Pathology and Infectious Diseases.

Toll-like receptors (TLRs) are pattern recognition receptors playing a fundamental role in sensing microbial invasion and initiating innate and adaptive immune responses. TLRs are also triggered by danger signals released by injured or stressed cells during sepsis. Here we focus on studies developing TLR agonists and antagonists for the treatment of infectious diseases and sepsis. Positioned at the cell surface, TLR4 is essential for sensing lipopolysaccharide of Gram-negative bacteria, TLR2 is involved in the recognition of a large panel of microbial ligands, while TLR5 recognizes flagellin. Endosomal TLR3, TLR7, TLR8, TLR9 are specialized in the sensing of nucleic acids produced notably during viral infections. TLR4 and TLR2 are favorite targets for developing anti-sepsis drugs, and antagonistic compounds have shown efficient protection from septic shock in pre-clinical models. Results from clinical trials evaluating anti-TLR4 and anti-TLR2 approaches are presented, discussing the challenges of study design in sepsis and future exploitation of these agents in infectious diseases. We also report results from studies suggesting that the TLR5 agonist flagellin may protect from infections of the gastrointestinal tract and that agonists of endosomal TLRs are very promising for treating chronic viral infections. Altogether, TLR-targeted therapies have a strong potential for prevention and intervention in infectious diseases, notably sepsis.

Inter-limb coordination and energy cost in swimming.

OBJECTIVES: This study investigated the relationship between inter-arm coordination and the energy cost of locomotion in front crawl and breaststroke and explored swimmers' flexibility in adapting their motor organization away from their preferred movement pattern. DESIGN: Nine front-crawlers performed three 300-m in front crawl and 8 breaststrokers performed three 200-m in breaststroke at constant submaximal intensity and with 5-min rests. Each trial was performed randomly in a different coordination pattern: freely chosen, 'maximal glide' and 'minimal glide'. Two underwater cameras videotaped frontal and side views to analyze speed, stroke rate, stroke length and inter-limb coordination. METHODS: In front crawl, inter-arm coordination was quantified by the index of coordination (IdC) and the leg beat kicks were counted. In breaststroke, four time gaps quantified the arm to leg coordination (i.e., time between leg and arm propulsions; time between beginning, 90° flexion and end of arm and leg recoveries). The energy cost of locomotion was calculated from gas exchanges and blood lactate concentration. RESULTS: In both front crawl and breaststroke, the freely chosen coordination corresponded to glide pattern and showed the lowest energy cost (12.8 and 17.1Jkg(-1)m(-1), respectively). Both front-crawlers and breaststrokers were able to reach 'maximal glide' condition (respectively, +35% and +28%) but not 'minimal glide' condition for front crawl. CONCLUSIONS: The freely chosen pattern appeared more economic because more trained. When coordination was constrained, the swimmers had higher coordination flexibility in breaststroke than in front crawl, suggesting that breaststroke coordination was easier to regulate by changing glide time.

Retinal Image Analysis Using Machine Vision

The topic of this thesis is studying how lesions in retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. Methods for equalizing uneven illumination in fundus images, detecting regions of poor image quality due toinadequate illumination, and recognizing abnormal lesions were developed duringthe work. The developed methods exploit mainly the color information and simpleshape features to detect lesions. In addition, a graphical tool for collecting lesion data was developed. The tool was used by an ophthalmologist who marked lesions in the images to help method development and evaluation. The tool is a general purpose one, and thus it is possible to reuse the tool in similar projects.The developed methods were tested with a separate test set of 128 color fundus images. From test results it was calculated how accurately methods classify abnormal funduses as abnormal (sensitivity) and healthy funduses as normal (specificity). The sensitivity values were 92% for hemorrhages, 73% for red small dots (microaneurysms and small hemorrhages), and 77% for exudates (hard and soft exudates). The specificity values were 75% for hemorrhages, 70% for red small dots, and 50% for exudates. Thus, the developed methods detected hemorrhages accurately and microaneurysms and exudates moderately.

Das GRADE-System: ein internationaler Ansatz zur Vereinheitlichung der Graduierung von Evidenz und Empfehlungen in Leitlinien. [The GRADE System: an international approach to standardize the graduation of evidence and recommendations in guidelines]

Clinical practice guidelines have become an important source of information to support clinicians in the management of individual patients. However, current guideline methods have limitations that include the lack of separating the quality of evidence from the strength of recommendations. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) working group, an international collaboration of guideline developers, methodologists, and clinicians have developed a system that addresses these shortcomings. Core elements include transparent methodology for grading the quality of evidence, the distinction between quality of the evidence and strength of a recommendation, an explicit balancing of benefits and harms of health care interventions, an explicit recognition of the values and preferences that underlie recommendations. The GRADE system has been piloted in various practice settings to ensure that it captures the complexity involved in evidence assessment and grading recommendations while maintaining simplicity and practicality. Many guideline organizations and medical societies have endorsed the system and adopted it for their guideline processes.