Counselor motivational interviewing skills and young adult change talk articulation during brief motivational interventions.

The process of eliciting client language toward change (change talk [CT]) is implicated as a causal mechanism in motivational interviewing (MI) and brief motivational interventions (BMI). We investigated the articulation of counselor behaviors and CT during BMI with young men. We coded 149 sessions using the Motivational Interviewing Skill Code and summarized these codes into three counselor categories (MI-consistent [MICO], MI-inconsistent [MIIN], other) and three client categories (CT, counter CT [CCT], follow/neutral [F/N]). We then computed immediate transition frequencies and odds ratios using sequential analysis software. CT was significantly more likely following MICO behaviors, whereas MIIN behaviors only led to CCT and F/N. This strongly supports the use of MI skills to elicit CT during BMI with young men, whose speech also predicted counselor behaviors (particularly CT to MICO and CCT to MIIN). Additional analyses showed that among MICO behaviors, reflective listening may be a particularly powerful technique to elicit CT.

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder.

BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Cannabis and tobacco co-consumptions: can cannabis consumers quit cigarette smoking?

Purpose: To assess the relation between cannabis and tobacco consumption among adolescents in Switzerland and whether cannabis and tobacco co-users can quit cigarette smoking. Methods: Based on individual interviews and focus groups, 22 youths aged 15-20 discussed cannabis consumption behaviours. Twenty (14 males) were cannabis consumers - of which 18 also smoked tobacco and 2 quit tobacco smoking - and 2 were former cannabis consumers (both females and daily smokers). Data were transcribed verbatim and analyzed using Atlas.ti qualitative analysis software. Results: Among the co-consumers, 9 started with tobacco, 7 with cannabis, and 2 with both. The main consumption mode among all cannabis consumers is joints, while other ways of consuming such as food preparations and water pipes are rare and experimental. Joints always mix cannabis with tobacco for 3 reasons: to burn correctly, pure cannabis is too strong, and smoking cannabis alone is too expensive. Two cannabis consumers - one former tobacco smoker and one occasional tobacco smoker - consider rolling tobacco less addictive than cigarette tobacco alone, and hence use it in their joints. Overall cannabis is considered 'natural' and less harmful to health than tobacco. Thus, many users describe their wish, in the longer term, to quit tobacco consumption without excluding occasional cannabis consumption. Nonetheless, all coconsumers declare that they smoke cigarettes as a substitute for cannabis: For example, "If I don't have a joint, I need fags; if I don't have fags, I need joints; and if I don't have anything, I go crazy!" or "About 20 minutes after smoking a joint we feel like smoking something again, because in the joint there is pure tobacco without a filter as in cigarettes, and that creates a crazy dependency!". Finally, all co-consumers state that the consumption of one of the substances increases when trying to diminish the other: "A few months ago I stopped smoking joints for a month. Well I was smoking more than a pack [of cigarettes] a day." Similarly, the 2 former cannabis consumers increased their cigarette use since quitting cannabis. Conclusions: The majority of cannabis users co-consume tobacco as a way of compensating for one substance or the other. Using tobacco within joints implies that there is a risk that even occasional joints can revive nicotine addiction. Consequently, health professionals wishing to help adolescents in substance use cessation and prevention efforts should consider both substances in a global perspective. Sources of Support: Dept. of Public Health of the canton of Vaud.

Cannabis Users Identifying Themselves as Non-Cigarette Smokers : Who Are They?

Introduction and Aims. About 20% of cannabis consumers report not smoking cigarettes. Studies that have compared cannabis and cigarette smokers, cigarette smokers, and cannabis users who do not smoke cigarettes (CNSs) have shown that CNSs have better outcomes across a range of indicators compared to the others. Therefore, we conducted a qualitative study to determine why CNSs did not smoke cigarettes and how they managed to resist cigarette smoking in order to better inform prevention efforts. Design and Methods. We conducted five focus groups (FG) with a total of 19 CNSs between ages 16 and 25. A narrative analysis of FGs was conducted using qualitative analysis software. Results. CNSs' non-smoking choice was rooted in a negative opinion of cigarettes and a harm-reduction strategy. They were unique cases within their peer groups, but there were no CNSs groups. All participants were confronted to the mulling paradox. Discussion and Conclusions. While tobacco-use prevention seems to have been successful, CNSs need to be informed of harmful consequences of chronic cannabis use. Given their habit of adding tobacco to cannabis, CNSs need to be alerted that they may be nicotine dependent even though they do not smoke tobacco on its own. This exploratory study brings essential insight concerning this specific population of cannabis consumers which future research should continue to develop.

Comparison of Inoculation with the InoqulA and WASP Automated Systems with Manual Inoculation.

The quality of sample inoculation is critical for achieving an optimal yield of discrete colonies in both monomicrobial and polymicrobial samples to perform identification and antibiotic susceptibility testing. Consequently, we compared the performance between the InoqulA (BD Kiestra), the WASP (Copan), and manual inoculation methods. Defined mono- and polymicrobial samples of 4 bacterial species and cloudy urine specimens were inoculated on chromogenic agar by the InoqulA, the WASP, and manual methods. Images taken with ImagA (BD Kiestra) were analyzed with the VisionLab version 3.43 image analysis software to assess the quality of growth and to prevent subjective interpretation of the data. A 3- to 10-fold higher yield of discrete colonies was observed following automated inoculation with both the InoqulA and WASP systems than that with manual inoculation. The difference in performance between automated and manual inoculation was mainly observed at concentrations of >10(6) bacteria/ml. Inoculation with the InoqulA system allowed us to obtain significantly more discrete colonies than the WASP system at concentrations of >10(7) bacteria/ml. However, the level of difference observed was bacterial species dependent. Discrete colonies of bacteria present in 100- to 1,000-fold lower concentrations than the most concentrated populations in defined polymicrobial samples were not reproducibly recovered, even with the automated systems. The analysis of cloudy urine specimens showed that InoqulA inoculation provided a statistically significantly higher number of discrete colonies than that with WASP and manual inoculation. Consequently, the automated InoqulA inoculation greatly decreased the requirement for bacterial subculture and thus resulted in a significant reduction in the time to results, laboratory workload, and laboratory costs.

Coltop3D: A new software for structural analysis with high resolution 3D point clouds and DEM

Coltop3D is a software that performs structural analysis by using digital elevation model (DEM) and 3D point clouds acquired with terrestrial laser scanners. A color representation merging slope aspect and slope angle is used in order to obtain a unique code of color for each orientation of a local slope. Thus a continuous planar structure appears in a unique color. Several tools are included to create stereonets, to draw traces of discontinuities, or to compute automatically density stereonet. Examples are shown to demonstrate the efficiency of the method.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

3D visualization software to analyze topological outcomes of topoisomerase reactions.

The action of various DNA topoisomerases frequently results in characteristic changes in DNA topology. Important information for understanding mechanistic details of action of these topoisomerases can be provided by investigating the knot types resulting from topoisomerase action on circular DNA forming a particular knot type. Depending on the topological bias of a given topoisomerase reaction, one observes different subsets of knotted products. To establish the character of topological bias, one needs to be aware of all possible topological outcomes of intersegmental passages occurring within a given knot type. However, it is not trivial to systematically enumerate topological outcomes of strand passage from a given knot type. We present here a 3D visualization software (TopoICE-X in KnotPlot) that incorporates topological analysis methods in order to visualize, for example, knots that can be obtained from a given knot by one intersegmental passage. The software has several other options for the topological analysis of mechanisms of action of various topoisomerases.

A protocol for preparing GFP-labeled neurons previously imaged in vivo and in slice preparations for light and electron microscopic analysis.

In vivo imaging of green fluorescent protein (GFP)-labeled neurons in the intact brain is being used increasingly to study neuronal plasticity. However, interpreting the observed changes as modifications in neuronal connectivity needs information about synapses. We show here that axons and dendrites of GFP-labeled neurons imaged previously in the live mouse or in slice preparations using 2-photon laser microscopy can be analyzed using light and electron microscopy, allowing morphological reconstruction of the synapses both on the imaged neurons, as well as those in the surrounding neuropil. We describe how, over a 2-day period, the imaged tissue is fixed, sliced and immuno-labeled to localize the neurons of interest. Once embedded in epoxy resin, the entire neuron can then be drawn in three dimensions (3D) for detailed morphological analysis using light microscopy. Specific dendrites and axons can be further serially thin sectioned, imaged in the electron microscope (EM) and then the ultrastructure analyzed on the serial images.

Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data.

Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

Conceptual models for designing information systems supporting the strategic analysis of technology environments

1 6 STRUCTURE OF THIS THESIS -Chapter I presents the motivations of this dissertation by illustrating two gaps in the current body of knowledge that are worth filling, describes the research problem addressed by this thesis and presents the research methodology used to achieve this goal. -Chapter 2 shows a review of the existing literature showing that environment analysis is a vital strategic task, that it shall be supported by adapted information systems, and that there is thus a need for developing a conceptual model of the environment that provides a reference framework for better integrating the various existing methods and a more formal definition of the various aspect to support the development of suitable tools. -Chapter 3 proposes a conceptual model that specifies the various enviromnental aspects that are relevant for strategic decision making, how they relate to each other, and ,defines them in a more formal way that is more suited for information systems development. -Chapter 4 is dedicated to the evaluation of the proposed model on the basis of its application to a concrete environment to evaluate its suitability to describe the current conditions and potential evolution of a real environment and get an idea of its usefulness. -Chapter 5 goes a step further by assembling a toolbox describing a set of methods that can be used to analyze the various environmental aspects put forward by the model and by providing more detailed specifications for a number of them to show how our model can be used to facilitate their implementation as software tools. -Chapter 6 describes a prototype of a strategic decision support tool that allow the analysis of some of the aspects of the environment that are not well supported by existing tools and namely to analyze the relationship between multiple actors and issues. The usefulness of this prototype is evaluated on the basis of its application to a concrete environment. -Chapter 7 finally concludes this thesis by making a summary of its various contributions and by proposing further interesting research directions.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

The appropriateness of renal angioplasty: the ANPARIA software: a multidisciplinary expert panel approach

Percutaneous transluminal renal angioplasty (PTRA) is an invasive technique that is costly and involves the risk of complications and renal failure. The ability of PTRA to reduce the administration of antihypertensive drugs has been demonstrated. A potentially greater benefit, which nevertheless remains to be proven, is the deferral of the need for chronic dialysis. The aim of the study (ANPARIA) was to assess the appropriateness of PTRA to impact on the evolution of renal function. A standardized expert panel method was used to assess the appropriateness of medical treatment alone or medical treatment with revascularization in various clinical situations. The choice of revascularization by either PTRA or surgery was examined for each clinical situation. Analysis was based on a detailed literature review and on systematically elicited expert opinion, which were obtained during a two-round modified Delphi process. The study provides detailed responses on the appropriateness of PTRA for 1848 distinct clinical scenarios. Depending on the major clinical presentation, appropriateness of revascularization varied from 32% to 75% for individual scenarios (overal 48%). Uncertainty as to revascularization was 41% overall. When revascularization was appropriate, PTRA was favored over surgery in 94% of the scenarios, except in certain cases of aortic atheroma where sugery was the preferred choice. Kidney size [7 cm, absence of coexisting disease, acute renal failure, a high degree of stenosis (C70%), and absence of multiple arteries were identified as predictive variables of favorable appropriateness ratings. Situations such as cardiac failure with pulmonary edema or acute thrombosis of the renal artery were defined as indications for PTRA. This study identified clinical situations in which PTRA or surgery are appropriate for renal artery disease. We built a decision tree which can be used via Internet: the ANPARIA software (http://www.chu-clermontferrand.fr/anparia/). In numerous clinical situations uncertainty remains as to whether PTRA prevents deterioration of renal function.