RNA stem alignment (125 sequences)

This alignment is a concatenation of rRNA stem sites from small and large rRNA subunits. It contains 125 sequences and is in Fasta format

Statistical Handling of Reproduction Data for Exposure-Response Modeling

Reproduction data collected through standard bioassays are classically analyzed by regression in order to fit exposure-response curves and estimate EC_<i>x</i> values (<i>x</i>% effective concentration). But regression is often misused on such data, ignoring statistical issues related to (i) the special nature of reproduction data (count data), (ii) a potential inter-replicate variability, and (iii) a possible concomitant mortality. This paper offers new insights in dealing with those issues. Concerning mortality, particular attention was paid not to waste any valuable databy dropping all the replicates with mortalityor to bias EC_<i>x</i> values. For that purpose we defined a new covariate summing the observation periods during which each individual contributes to the reproduction process. This covariate was then used to quantify reproductionfor each replicate at each concentrationas a number of offspring per individual-day. We formulated three exposure-response models differing by their stochastic part. Those models were fitted to four data sets and compared using a Bayesian framework. The individual-day unit proved to be a suitable approach to use all the available data and prevent bias in the estimation of EC_<i>x</i> values. Furthermore, a nonclassical negative-binomial model was shown to correctly describe the inter-replicate variability observed in the studied data sets

Universal protein alignment (38 sequences)

This universal protein alignment is a concatenation of 56 proteins from 38 species

New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for <i>Lymnaea stagnalis</i> Exposed to Cd

Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose–response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose–response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC_{<i>x</i>,<i>t</i>}), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC_{<i>x</i>,<i>t</i>} are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice

Assessment of the <i>in vitro</i> genotoxicity of TiO₂ nanoparticles in a regulatory context

<p>A review of <i>in vitro</i> genotoxicity studies on titanium dioxide nanoparticles (TiO₂-NPs) published between 2010 and 2016 was performed by France in the framework of the CLP Regulation 1272/2008/EC. Neither the few <i>in vivo</i> studies of low quality nor the larger number of acceptable <i>in vitro</i> studies available for genotoxicity allowed France to conclude on the genotoxicity of TiO₂-NPs. Based on this work, it was decided to compare the acceptable <i>in vitro</i> studies to understand the reasons for the diverging results observed, such as the materials tested or of the protocols used and their inherent interferences. The systematic review performed on <i>in vitro</i> genotoxicity data for TiO₂-NPs was then restricted to studies with the highest level of confidence among studies following OECD guidelines and the largely applied comet assay. Indeed, the aim of this article is to understand why, even if judged of good quality, the 36 publications selected and analyzed did not lead to a clear picture. Some recommendations to be taken into account before performing new <i>in vitro</i> genotoxicity assays for insoluble particles such as TiO₂-NPs are proposed. Although secondary genotoxic effects consequent to oxidative stress seem to be the major mechanism responsible for the genotoxicity of TiO₂-NPs reported in some studies, primary genotoxic effects cannot be excluded. Further studies are needed to clarify the exact mode of action of TiO₂-NPs and to highlight which physicochemical properties lead to their genotoxicity <i>in vitro</i> to ultimately identify a specific combination of parameters that could represent a risk <i>in vivo.</i></p