Species non-exchangeability in probabilistic ecotoxicological risk assessment

Current ecotoxicological risk assessment for chemical substances is based on the assumption that tolerances of all species in a specified ecological community are a priori exchangeable for each new substance. We demonstrate non-exchangeability by using a large database of tolerances to pesticides for fish species and extend the standard statistical model for species tolerances to allow for the presence of a single species which is considered non-exchangeable with others. We show how to estimate parameters and adjust decision rules that are used in ecotoxicological risk management. Effects of parameter uncertainty are explored and our model is compared with a previously published less tractable alternative. We conclude that the model and decision rules that we propose are pragmatic compromises between conflicting needs for more realistic modelling and for straightforwardly applicable decision rules

Toxoplasma gondii‐infected natural killer cells display a hypermotility phenotype in vivo

Toxoplasma gondii is a highly prevalent intracellular protozoan parasite that causes severe disease in congenitally infected or immunocompromised hosts. T. gondii is capable of invading immune cells and it has been suggested that the parasite harnesses the migratory pathways of these cells to spread through the body. Although in vitro evidence suggests that the parasite further enhances its spread by inducing a hypermotility phenotype in parasitized immune cells, in vivo evidence for this phenomenon is scarce. Here we use a physiologically relevant oral model of T. gondii infection, in conjunction with two‐photon laser scanning microscopy, to address this issue. We found that a small proportion of natural killer (NK) cells in mesenteric lymph nodes contained parasites. Compared with uninfected ‘bystander’ NK cells, these infected NK cells showed faster, more directed and more persistent migratory behavior. Consistent with this, infected NK cells showed impaired spreading and clustering of the integrin, LFA‐1, when exposed to plated ligands. Our results provide the first evidence for a hypermigratory phenotype in T. gondii‐infected NK cells in vivo, providing an anatomical context for understanding how the parasite manipulates immune cell motility to spread through the host

Statistical and data reporting guidelines for the European Journal of Cardio-Thoracic Surgery and the Interactive CardioVascular and Thoracic Surgery

As part of the peer review process for the European Journal of Cardio-Thoracic Surgery (EJCTS) and the Interactive CardioVascular and Thoracic Surgery (ICVTS), a statistician reviews any manuscript that includes a statistical analysis. To facilitate authors considering submitting a manuscript and to make it clearer about the expectations of the statistical reviewers, we present up-to-date guidelines for authors on statistical and data reporting specifically in these journals. The number of statistical methods used in the cardiothoracic literature is vast, as are the ways in which data are presented. Therefore, we narrow the scope of these guidelines to cover the most common applications submitted to the EJCTS and ICVTS, focusing in particular on those that the statistical reviewers most frequently comment o

joineRML: a joint model and software package for time-to-event and multivariate longitudinal outcomes

Background: Joint modelling of longitudinal and time-to-event outcomes has received considerable attention over recent years. Commensurate with this has been a rise in statistical software options for fitting these models. However, these tools have generally been limited to a single longitudinal outcome. Here, we describe the classical joint model to the case of multiple longitudinal outcomes, propose a practical algorithm for fitting the models, and demonstrate how to fit the models using a new package for the statistical software platform R, joineRML. Results: A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process. The models are fitted using a Monte Carlo Expectation-Maximisation algorithm, and inferences are based on approximate standard errors from the empirical profile information matrix, which are contrasted to an alternative bootstrap estimation approach. We illustrate the model and software on a real data example for patients with primary biliary cirrhosis with three repeatedly measured biomarkers. Conclusions: An open-source software package capable of fitting multivariate joint models is available. The underlying algorithm and source code makes use of several methods to increase computational speed

Statistical primer: sample size and power calculations-why, when and how?

When designing a clinical study, a fundamental aspect is the sample size. In this article, we describe the rationale for sample size calculations, when it should be calculated and describe the components necessary to calculate it. For simple studies, standard formulae can be used; however, for more advanced studies, it is generally necessary to use specialized statistical software programs and consult a biostatistician. Sample size calculations for non-randomized studies are also discussed and two clinical examples are used for illustration