934 research outputs found

    Fusion collaboration in global teams.

    Get PDF
    This essay introduces a new model for facilitating collaboration in global teams that leads to creatively realistic solutions to global problems. The conceptualization for the fusion model of global team collaboration draws on the culinary tradition of fusion cooking and current political theorizing about pluralistic societies. We describe how the fusion principle of coexistence facilitates information extraction and decision making, and we recommend formal interventions to counterbalance the unequal power relations among team members. We contrast the fusion model to models of collaboration based on principles of the dominant coalition and of integration/identity, pointing out why fusion should produce superior solutions to global problems.Model; Problems; Information; Decision; Decision making; Models; Principles;

    PredictABEL: an R package for the assessment of risk prediction models

    Get PDF
    The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL (http://www.genabel.org) and CRAN (http://cran.r-project.org/)

    Nutrient scarcity as a selective pressure for mast seeding

    Get PDF
    Mast seeding is one of the most intriguing reproductive traits in nature. Despite its potential drawbacks in terms of fitness, the widespread existence of this phenomenon suggests that it should have evolutionary advantages under certain circumstances. Using a global dataset of seed production time series for 219 plant species from all the continents, we tested whether masting behaviour appears predominantly in species with low foliar N and P concentrations, when controlling for local climate and productivity. Here we show that masting intensity is higher in species with low foliar N and P concentrations and especially imbalanced N:P ratios, and that the evolutionary history of masting behaviour has been linked to that of nutrient economy. Our results support the hypothesis that masting is stronger in species growing under limiting conditions and suggest that this reproductive behaviour might have evolved as an adaptation to nutrient limitations and imbalances

    A Methodological Perspective on Genetic Risk Prediction Studies in Type 2 Diabetes: Recommendations for Future Research

    Get PDF
    Fueled by the successes of genome-wide association studies, numerous studies have investigated the predictive ability of genetic risk models in type 2 diabetes. In this paper, we review these studies from a methodological perspective, focusing on the variables included in the risk models as well as the study designs and populations investigated. We argue and show that differences in study design and characteristics of the study population have an impact on the observed predictive ability of risk models. This observation emphasizes that genetic risk prediction studies should be conducted in those populations in which the prediction models will ultimately be applied, if proven useful. Of all genetic risk prediction studies to date, only a few were conducted in populations that might be relevant for targeting preventive interventions

    <Book Reviews> Ingemar Fagerlind and Lawrence J Saha Education and National Development : A Comparative Perspective

    Get PDF
    textabstractVarious modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicative risk model of independent genetic effects, but they either assumed per allele, per genotype or dominant/recessive effects for the genetic variants. Modeling strategy and input parameters differed. Methods used simulation analysis or analytical formulas with effect sizes quantified by odds ratios (ORs) or relative risks. Estimated AUC values were similar for lower ORs (0.7) due to variants with strong effects, differences in estimated AUCs between methods increased. The simulation methods accurately reproduced the AUC values of empirical studies, but the analytical methods did not. We conclude that despite differences in input parameters, the modeling methods estimate similar AUC for realistic values of the ORs. When one or more variants have stronger effects and AUC values are higher, the simulation methods tend to be more accurate

    Family physicians' perceptions of academic detailing: a quantitative and qualitative study

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>The efficacy of academic detailing in changing physicians' knowledge and practice has been the subject of many primary research publications and systematic reviews. However, there is little written about the features of academic detailing that physicians find valuable or that affect their use of it. The goal of our project was to explore family physicians' (FPs) perceptions of academic detailing and the factors that affect their use of it.</p> <p>Methods</p> <p>We used 2 methods to collect data, a questionnaire and semi-structured telephone interviews. We mailed questionnaires to all FPs in the Dalhousie Office of Continuing Medical Education database and analyzed responses of non-users and users of academic detailing. After a preliminary analysis of questionnaire data, we conducted semi-structured interviews with 7 FPs who did not use academic detailing and 17 who did use it.</p> <p>Results</p> <p>Overall response rate to the questionnaire was 33% (289/869). Response rate of non-users of academic detailing was 15% (60/393), of users was 48% (229/476). The 3 factors that most encouraged use of academic detailing were the topics selected, the evidence-based approach adopted, and the handout material. The 3 factors that most discouraged the use of academic detailing were spending office time doing CME, scheduling time to see the academic detailer, and having CME provided by a non-physician. Users of academic detailing rated it as being more valuable than other forms of CME. Generally, interview data confirmed questionnaire data with the exception that interview informants did not view having CME provided by a non-physician as a barrier. Interview informants mentioned that the evidence-based approach adopted by academic detailing had led them to more critically evaluate information from other CME programs, pharmaceutical representatives, and journal articles, but not advice from specialists.</p> <p>Conclusion</p> <p>Users of academic detailing highly value its educational value and tend to view information from other sources more critically because of its evidence-based approach. Non-users are unlikely to adopt academic detailing despite its high educational value because they find using office time for CME too much of a barrier. To reach these physicians with academic detailing messages, we will have to find other CME formats.</p

    Protocol for the saMS trial (supportive adjustment for multiple sclerosis): a randomized controlled trial comparing cognitive behavioral therapy to supportive listening for adjustment to multiple sclerosis

    Get PDF
    BackgroundMultiple Sclerosis (MS) is an incurable, chronic, potentially progressive and unpredictable disease of the central nervous system. The disease produces a range of unpleasant and debilitating symptoms, which can have a profound impact including disrupting activities of daily living, employment, income, relationships, social and leisure activities, and life goals. Adjusting to the illness is therefore particularly challenging. This trial tests the effectiveness of a cognitive behavioural intervention compared to supportive listening to assist adjustment in the early stages of MS.MethodsThis is a two arm randomized multi-centre parallel group controlled trial. 122 consenting participants who meet eligibility criteria will be randomly allocated to receive either Cognitive Behavioral Therapy or Supportive Listening. Eight one hour sessions of therapy (delivered over a period of 10 weeks) will be delivered by general nurses trained in both treatments. Self-report questionnaire data will be collected at baseline (0 weeks), mid-therapy (week 5 of therapy), post-therapy (15 weeks) and at six months (26 weeks) and twelve months (52 weeks) follow-up. Primary outcomes are distress and MS-related social and role impairment at twelve month follow-up. Analysis will also consider predictors and mechanisms of change during therapy. In-depth interviews to examine participants’ experiences of the interventions will be conducted with a purposively sampled sub-set of the trial participants. An economic analysis will also take place. DiscussionThis trial is distinctive in its aims in that it aids adjustment to MS in a broad sense. It is not a treatment specifically for depression. Use of nurses as therapists makes the interventions potentially viable in terms of being rolled out in the NHS. The trial benefits from incorporating patient input in the development and evaluation stages. The trial will provide important information about the efficacy, cost-effectiveness and acceptability of the interventions as well as mechanisms of psychosocial adjustment.Trial registrationCurrent Controlled Trials ISRCTN91377356<br/

    Master equation simulation analysis of immunostained Bicoid morphogen gradient

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>The concentration gradient of Bicoid protein which determines the developmental pathways in early <it>Drosophila </it>embryo is the best characterized morphogen gradient at the molecular level. Because different developmental fates can be elicited by different concentrations of Bicoid, it is important to probe the limits of this specification by analyzing intrinsic fluctuations of the Bicoid gradient arising from small molecular number. Stochastic simulations can be applied to further the understanding of the dynamics of Bicoid morphogen gradient formation at the molecular number level, and determine the source of the nucleus-to-nucleus expression variation (noise) observed in the Bicoid gradient.</p> <p>Results</p> <p>We compared quantitative observations of Bicoid levels in immunostained <it>Drosophila </it>embryos with a spatially extended Master Equation model which represents diffusion, decay, and anterior synthesis. We show that the intrinsic noise of an autonomous reaction-diffusion gradient is Poisson distributed. We demonstrate how experimental noise can be identified in the logarithm domain from single embryo analysis, and then separated from intrinsic noise in the normalized variance domain of an ensemble statistical analysis. We show how measurement sensitivity affects our observations, and how small amounts of rescaling noise can perturb the noise strength (Fano factor) observed. We demonstrate that the biological noise level in data can serve as a physical constraint for restricting the model's parameter space, and for predicting the Bicoid molecular number and variation range. An estimate based on a low variance ensemble of embryos suggests that the steady-state Bicoid molecular number in a nucleus should be larger than 300 in the middle of the embryo, and hence the gradient should extend to the posterior end of the embryo, beyond the previously assumed background limit. We exhibit the predicted molecular number gradient together with measurement effects, and make a comparison between conditions of higher and lower variance respectively.</p> <p>Conclusion</p> <p>Quantitative comparison of Master Equation simulations with immunostained data enabled us to determine narrow ranges for key biophysical parameters, which for this system can be independently validated. Intrinsic noise is clearly detectable as well, although the staining process introduces certain limits in resolution.</p
    corecore