Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.

Fièvre jaune: nouvelles recommandations [Yellow fever: new recommendations].

Indication for yellow fever vaccination is not always easy to assess. The decision to immunize is not only based on the actual risk of the disease in a specific location, but also on public health considerations in the visited country (in order to respectively avoid epidemics in endemic countries or the introduction of the virus in zones where the vectors mosquitoes are present) and on travelers' risk factors for severe or even fatal vaccine adverse events. WHO has recently published new recommendations regarding vaccination against yellow fever after concluding that one dose of vaccine generates a life-long protection. This article tends to clarify the strategy to adopt in 2013 using cases frequently encountered in the practice of travel medicine.

Sensitivity of genome-wide-association signals to phenotyping strategy: the PROP-TAS2R38 taste association as a benchmark.

Natural genetic variation can have a pronounced influence on human taste perception, which in turn may influence food preference and dietary choice. Genome-wide association studies represent a powerful tool to understand this influence. To help optimize the design of future genome-wide-association studies on human taste perception we have used the well-known TAS2R38-PROP association as a tool to determine the relative power and efficiency of different phenotyping and data-analysis strategies. The results show that the choice of both data collection and data processing schemes can have a very substantial impact on the power to detect genotypic variation that affects chemosensory perception. Based on these results we provide practical guidelines for the design of future GWAS studies on chemosensory phenotypes. Moreover, in addition to the TAS2R38 gene past studies have implicated a number of other genetic loci to affect taste sensitivity to PROP and the related bitter compound PTC. None of these other locations showed genome-wide significant associations in our study. To facilitate further, target-gene driven, studies on PROP taste perception we provide the genome-wide list of p-values for all SNPs genotyped in the current study.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Améliorer la prise en charge de l'hypertension arterielle en favorisant la collaboration avec les pharmaciens et les infirmières [Team-based care involving pharmacists and nurses to improve the management of hypertension].

Only half of hypertensive patients has controlled blood pressure. Chronic kidney disease (CKD) is also associated with low blood pressure control, 25-30% of CKD patients achieving adequate blood pressure. The Community Preventive Services Task Force has recently recommended team-based care to improve blood pressure control. Team-based care of hypertension involves facilitating coordination of care among physician, pharmacist and nurse and requires sharing clinical data, laboratory results, and medications, e.g., electronically or by fax. Based on recent studies, development and evaluation of team-based care of hypertensive patients should be done in the Swiss healthcare system.

An alternative socio-ecological strategy? International Trade Unions' engagement with climate change

In the context of a global ecological crisis, it is an important move when trade unions turn to environmentalism. Yet, the form that this environmentalism takes is often overlooked. This is especially the case with international trade unions. Based on an empirical study of international trade unions' engagement with the climate change issue, this article argues that international trade unions follow three different (and partially conflicting) strategies. I label these strategies as 'deliberative', 'collaborative growth' and 'socialist', and I examine each in turn. I argue that such analysis is important if we want to identify the potential for transforming the social relations of production that are at the root of the current climate crisis, and for identifying an alternative socio-ecological strategy.

RECHERCHE TRANSLATIONNELLE EN NEUROSCIENCES PSYCHIATRIQUES: DE L'ANIMAL MODELE DE SCHIZOPHRENIE A LA DETECTION D'UNE DESORIENTATION SPATIALE, PRATIQUE OU SYMBOLIQUE CHEZ DES PATIENTS

La modélisation, chez l'animal, de maladies psychiatriques telles que la schizophrénie repose sur différentes démarches visant à induire des perturbations cérébrales similaires à celles observées dans la maladie. Nous avons cherché à étudier chez le rat les effets d'une diminution (50%) transitoire en glutathion (GSH) durant le développement (PND 5 à PND 16) à partir de l'implication, chez des adultes, des conséquences de cette perturbation dans des mécanismes fondamentaux de traitement de l'information sensorielle. Cette thèse évalue et documente les déficits de compétences de navigation spatiale dans ce modèle. Nous avons mis en évidence des effets comportementaux à partir de l'identification de différences particulières dans des tâches d'orientation: des difficultés, chez les rats ayant subi un déficit en GSH, à élaborer une représentation globale de l'environnement dans lequel ils se déplacent, difficultés compensées par une attention particulière aux détails visuels le composant. Cette stratégie réactive compensatoire est efficace lorsque les conditions permettent un ajustement continu aux repères visuels environnementaux. Elle ne permet cependant pas des prédictions et des attentes sur ce qui devrait être rencontré et perçu dans une certaine direction, dès qu'une partie des informations visuelles familières disparaît. Il faudrait pour cela une capacité fondée sur une représentation abstraite, à distance des modalités sensorielles qui en ont permis son élaboration. Notre thèse soutient que les déficits, supposés participer à l'émergence de certains symptômes de la maladie, auraient également des conséquences sur l'élaboration de la représentation spatiale nécessaire à des capacités d'orientation effectives et symboliques. - The study of a psychiatric disease such as schizophrenia in an animal model relies on different approaches attempting to replicate brain perturbations similar to those observed in the illness. In the present work, behavioural consequences of a functional deficit in brain connectivity and coordination were assessed in rats with a transitory glutathione (GSH) deficit induced during the postnatal development (PND 5-PND 16) with daily injections of BSO (1- buthionine-(S,R)- sulfoximine). We searched for a theoretical syndrome associating ecologically relevant behavioural adaptive deficits and resulting from the weakening of sensory integration processes. Our results revealed significant and specific deficit of BSO treated rats in spatial orientation tasks designed to test for cognitive mapping abilities. Treated rats behaved as if impaired in the proactive strategies supported by an abstract representation such as a cognitive map. In contrast their performances were preserved whenever the environmental conditions allowed for adaptative reactive strategies, an equivalent of the visual affordances described by Gibson (1958). This supports our thesis that BSO treated rats expressed difficulties in elaborating a global representation of the environment. This deficit was completely - or - partially compensated by the development of an increased attention to the environment's visual details. This compensatory reactive strategy requires a rich environment allowing for continuous adjustment to visual cues. However, such adjustment doesn't allow to predictions and expectancies about what should be met and perceived in a certain direction, when familiar visual spatial cues are missing. Such competencies require orientation based on the use of an abstract spatial representation, independent from the specific sensory modalities that have participated to its elaboration. The impairment of BSO rats such spatial representation could result from a deficit in the integration and organization of perceptual information. Our model leads to the hypothesis that these fundamental deficits might account for certain symptoms of schizophrenia. They would also interfere with in the capacity to elaborate spatial representation necessary for optimal orientation in natural, artificial or symbolic environment.

Evidence-based Economic Policy - Three Essays in Applied Microeconometrics

Over thirty years ago, Leamer (1983) - among many others - expressed doubts about the quality and usefulness of empirical analyses for the economic profession by stating that "hardly anyone takes data analyses seriously. Or perhaps more accurately, hardly anyone takes anyone else's data analyses seriously" (p.37). Improvements in data quality, more robust estimation methods and the evolution of better research designs seem to make that assertion no longer justifiable (see Angrist and Pischke (2010) for a recent response to Leamer's essay). The economic profes- sion and policy makers alike often rely on empirical evidence as a means to investigate policy relevant questions. The approach of using scientifically rigorous and systematic evidence to identify policies and programs that are capable of improving policy-relevant outcomes is known under the increasingly popular notion of evidence-based policy. Evidence-based economic policy often relies on randomized or quasi-natural experiments in order to identify causal effects of policies. These can require relatively strong assumptions or raise concerns of external validity. In the context of this thesis, potential concerns are for example endogeneity of policy reforms with respect to the business cycle in the first chapter, the trade-off between precision and bias in the regression-discontinuity setting in chapter 2 or non-representativeness of the sample due to self-selection in chapter 3. While the identification strategies are very useful to gain insights into the causal effects of specific policy questions, transforming the evidence into concrete policy conclusions can be challenging. Policy develop- ment should therefore rely on the systematic evidence of a whole body of research on a specific policy question rather than on a single analysis. In this sense, this thesis cannot and should not be viewed as a comprehensive analysis of specific policy issues but rather as a first step towards a better understanding of certain aspects of a policy question. The thesis applies new and innovative identification strategies to policy-relevant and topical questions in the fields of labor economics and behavioral environmental economics. Each chapter relies on a different identification strategy. In the first chapter, we employ a difference- in-differences approach to exploit the quasi-experimental change in the entitlement of the max- imum unemployment benefit duration to identify the medium-run effects of reduced benefit durations on post-unemployment outcomes. Shortening benefit duration carries a double- dividend: It generates fiscal benefits without deteriorating the quality of job-matches. On the contrary, shortened benefit durations improve medium-run earnings and employment possibly through containing the negative effects of skill depreciation or stigmatization. While the first chapter provides only indirect evidence on the underlying behavioral channels, in the second chapter I develop a novel approach that allows to learn about the relative impor- tance of the two key margins of job search - reservation wage choice and search effort. In the framework of a standard non-stationary job search model, I show how the exit rate from un- employment can be decomposed in a way that is informative on reservation wage movements over the unemployment spell. The empirical analysis relies on a sharp discontinuity in unem- ployment benefit entitlement, which can be exploited in a regression-discontinuity approach to identify the effects of extended benefit durations on unemployment and survivor functions. I find evidence that calls for an important role of reservation wage choices for job search be- havior. This can have direct implications for the optimal design of unemployment insurance policies. The third chapter - while thematically detached from the other chapters - addresses one of the major policy challenges of the 21st century: climate change and resource consumption. Many governments have recently put energy efficiency on top of their agendas. While pricing instru- ments aimed at regulating the energy demand have often been found to be short-lived and difficult to enforce politically, the focus of energy conservation programs has shifted towards behavioral approaches - such as provision of information or social norm feedback. The third chapter describes a randomized controlled field experiment in which we discuss the effective- ness of different types of feedback on residential electricity consumption. We find that detailed and real-time feedback caused persistent electricity reductions on the order of 3 to 5 % of daily electricity consumption. Also social norm information can generate substantial electricity sav- ings when designed appropriately. The findings suggest that behavioral approaches constitute effective and relatively cheap way of improving residential energy-efficiency.

Genometric analyses of the organization of circular chromosomes: a universal pressure determines the direction of ribosomal RNA genes transcription relative to chromosome replication.

Selective pressures related to gene function and chromosomal architecture are acting on genome sequences and can be revealed, for instance, by appropriate genometric methods. Cumulative nucleotide skew analyses, i.e., GC, TA, and ORF orientation skews, predict the location of the origin of DNA replication for 88 out of 100 completely sequenced bacterial chromosomes. These methods appear fully reliable for proteobacteria, Gram-positives, and spirochetes as well as for euryarchaeotes. Based on this genome architecture information, coorientation analyses reveal that in prokaryotes, ribosomal RNA (rRNA) genes encoding the small and large ribosomal subunits are all transcribed in the same direction as DNA replication; that is, they are located along the leading strand. This result offers a simple and reliable method for circumscribing the region containing the origin of the DNA replication and reveals a strong selective pressure acting on the orientation of rRNA genes similar to the weaker one acting on the orientation of ORFs. Rate of coorientation of transfer RNA (tRNA) genes with DNA replication appears to be taxon-specific. Analyzing nucleotide biases such as GC and TA skews of genes and plotting one against the other reveals a taxonomic clusterization of species. All ribosomal RNA genes are enriched in Gs and depleted in Cs, the only so far known exception being the rRNA genes of deuterostomian mitochondria. However, this exception can be explained by the fact that in the chromosome of the human mitochondrion, the model of the deuterostomian organelle genome, DNA replication, and rRNA transcription proceed in opposite directions. A general rule is deduced from prokaryotic and mitochondrial genomes: ribosomal RNA genes that are transcribed in the same direction as the DNA replication are enriched in Gs, and those transcribed in the opposite direction are depleted in Gs.

Communication skills training in oncology: a position paper based on a consensus meeting among European experts in 2009.

BACKGROUND: Communication in cancer care has become a major topic of interest. Since there is evidence that ineffective communication affects both patients and oncology clinicians (physicians and nurses), so-called communication skills trainings (CSTs) have been developed over the last decade. While these trainings have been demonstrated to be effective, there is an important heterogeneity with regard to implementation and with regard to evidence of different aspects of CST. METHODS: In order to review and discuss the scientific literature on CST in oncology and to formulate recommendations, the Swiss Cancer League has organised a consensus meeting with European opinion leaders and experts in the field of CST, as well as oncology clinicians, representatives of oncology societies and patient organisations. On the basis of a systematic review and a meta-analysis, recommendations have been developed and agreed upon. RESULTS: Recommendations address (i) the setting, objectives and participants of CST, (ii) its content and pedagogic tools, (iii) organisational aspects, (iv) outcome and (v) future directions and research. CONCLUSION: This consensus meeting, on the basis of European expert opinions and a systematic review and meta-analysis, defines key elements for the current provision and future development and evaluation of CST in oncology.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Adaptive strategy for the statistical analysis of connectomes.

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

VIKI : a semiotic-based system for multilingual knowledge retrieval

Abstract Since its creation, the Internet has permeated our daily life. The web is omnipresent for communication, research and organization. This exploitation has resulted in the rapid development of the Internet. Nowadays, the Internet is the biggest container of resources. Information databases such as Wikipedia, Dmoz and the open data available on the net are a great informational potentiality for mankind. The easy and free web access is one of the major feature characterizing the Internet culture. Ten years earlier, the web was completely dominated by English. Today, the web community is no longer only English speaking but it is becoming a genuinely multilingual community. The availability of content is intertwined with the availability of logical organizations (ontologies) for which multilinguality plays a fundamental role. In this work we introduce a very high-level logical organization fully based on semiotic assumptions. We thus present the theoretical foundations as well as the ontology itself, named Linguistic Meta-Model. The most important feature of Linguistic Meta-Model is its ability to support the representation of different knowledge sources developed according to different underlying semiotic theories. This is possible because mast knowledge representation schemata, either formal or informal, can be put into the context of the so-called semiotic triangle. In order to show the main characteristics of Linguistic Meta-Model from a practical paint of view, we developed VIKI (Virtual Intelligence for Knowledge Induction). VIKI is a work-in-progress system aiming at exploiting the Linguistic Meta-Model structure for knowledge expansion. It is a modular system in which each module accomplishes a natural language processing task, from terminology extraction to knowledge retrieval. VIKI is a supporting system to Linguistic Meta-Model and its main task is to give some empirical evidence regarding the use of Linguistic Meta-Model without claiming to be thorough.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.