Project description:An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.
Project description:Concentration- and time- response and human lower EpiAveolar™ respiratory tract tissues comparison of transcriptional responses following 12-day exposure with different test materials. Differential expression and pathway analyses were performed to estimate the lowest transcriptional point of departure (PoD) - minimum effect concentration when a biological perturbation as estimated by gene expression changes could be identified.
Project description:Background : Candida albicans is a diploid pathogenic fungus not yet amenable to routine genetic investigations. Understanding aspects of the regulation of its biological functions and the assembly of its protein complexes would lead to further insight into the biology of this common disease-causing microbial agent. Results: We have developed a toolbox allowing in vivo protein tagging by PCR-mediated homologous recombination with TAP, HA and MYC tags. The transformation cassettes were designed to accommodate a common set of integration primers. The tagged proteins can be used to perform tandem affinity purification (TAP) or chromatin immunoprecipitation coupled with microarray analysis (ChIP-CHIP). Tandem affinity purification of C. albicans Nop1 revealed the high conservation of the small processome composition in yeasts. Data obtained with in vivo TAP-tagged Tbf1, Cbf1 and Mcm1 recapitulates previously published genome-wide location profiling by ChIP-CHIP. We also designed a new reporter system for in vivo analysis of transcriptional activity of gene loci in C. albicans. Conclusion: This toolbox provides a basic setup to perform purification of protein complexes and increase the number of annotated transcriptional regulators and genetic circuits in C. albicans. Two independent biological replicates of ChIP-CHIP of Mcm1-TAP in yeast and hyphal states. ChIP-CHIP of Cbf1-TAP and Tbf1-TAP.
Project description:The American Cancer Society and The Centers for Disease Control and Prevention in collaboration with The National Colorectal Cancer Roundtable published "How to Increase Colorectal Cancer Screening rates in Practice: A Primary Care Clinician’s Evidence-Based Toolbox and Guide" in 2005. This toolbox outlines evidence-based interventions aimed at increasing colorectal cancer screening by primary care providers and their office staff. The Toolbox contains the tools to design a multifaceted intervention to increase primary care physician rates of colorectal cancer screening (CRCS). This is a pilot study to look at implementing the toolbox and its affects.
Project description:<p><strong>INTRODUCTION:</strong> Although it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.</p><p><strong>OBJECTIVES:</strong> The study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.</p><p><strong>METHOD:</strong> The robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.</p><p><strong>RESULTS:</strong> Our results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.</p><p><strong>CONCLUSION:</strong> This work demonstrates the potential of fast multidimensional 1H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues. </p>
Project description:safety versus fear conditioning. Mice were trained with 4 unpaired (Safety) or paired (Fear) CS-US presentations over 3 days. Mice were killed by decapitation 4hrs after the last training session.
Project description:We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrency to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.