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3. DRomics, a workflow to exploit dose-response omics data in ecotoxicology

Author

Delignette-Muller, Marie Laure, Siberchicot, Aurélie, Larras, Floriane, and Billoir, Elise

Subjects
Dose-response modeling, BenchMark Dose (BMD), Adverse Outcome Pathway (AOP), Mode of Action (MoA), environmental risk assessment, transcriptomics, proteomics, metabolomics, multiomics, Archaeology, CC1-960, Science
Abstract

Omics technologies has opened new possibilities to assess environmental risks and to understand the mode(s) of action of pollutants. Coupled to dose-response experimental designs, they allow a non-targeted assessment of organism responses at the molecular level along an exposure gradient. However, describing the dose-response relationships on such high-throughput data is no easy task. In a first part, we review the software available for this purpose, and their main features. We set out arguments on some statistical and modeling choices we have made while developing the R package DRomics and its positioning compared to others tools. The DRomics main analysis workflow is made available through a web interface, namely a shiny app named DRomics-shiny. Next, we present the new functionalities recently implemented. DRomics has been augmented especially to be able to handle varied omics data considering the nature of the measured signal (e.g. counts of reads in RNAseq) and the way data were collected (e.g. batch effect, situation with no experimental replicates). Another important upgrade is the development of tools to ease the biological interpretation of results. Various functions are proposed to visualize, summarize and compare the responses, for different biological groups (defined from biological annotation), optionally at different experimental levels (e.g. measurements at several omics level or in different experimental conditions). A new shiny app named DRomicsInterpreter-shiny is dedicated to the biological interpretation of results. The institutional web page https://lbbe.univ-lyon1.fr/fr/dromics gathers links to all resources related to DRomics, including the two shiny applications.

Published
2023
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7. Hierarchical modelling of species sensitivity distribution: development and application to the case of diatoms exposed to several herbicides

Author

King, Guillaume Kon Kam, Larras, Floriane, Charles, Sandrine, and Delignette-Muller, Marie Laure

Subjects
Statistics - Applications
Abstract

The Species Sensitivity Distribution (SSD) is a key tool to assess the ecotoxicological threat of contaminant to biodiversity. It predicts safe concentrations for a contaminant in a community. Widely used, this approach suffers from several drawbacks: i)summarizing the sensitivity of each species by a single value entails a loss of valuable information about the other parameters characterizing the concentration-effect curves; ii)it does not propagate the uncertainty on the critical effect concentration into the SSD; iii)the hazardous concentration estimated with SSD only indicates the threat to biodiversity, without any insight about a global response of the community related to the measured endpoint. We revisited the current SSD approach to account for all the sources of variability and uncertainty into the prediction and to assess a global response for the community. For this purpose, we built a global hierarchical model including the concentration-response model together with the distribution law for the SSD. Working within a Bayesian framework, we were able to compute an SSD taking into account all the uncertainty from the original raw data. From model simulations, it is also possible to extract a quantitative indicator of a global response of the community to the contaminant. We applied this methodology to study the toxicity of 6 herbicides to benthic diatoms from Lake Geneva, measured from biomass reduction.

Published
2015

9. MOSAIC_SSD: a new web-tool for the Species Sensitivity Distribution, allowing to include censored data by maximum likelihood

Author

King, Guillaume Kon Kam, Veber, Philippe, Charles, Sandrine, and Delignette-Muller, Marie Laure

Subjects
Statistics - Applications
Abstract

Censored data are seldom taken into account in Species Sensitivity Distribution (SSD) analysis. However, they are found in virtually every dataset and sometimes represent the better part of the data. Stringent recommendations on data quality often lead to discard a lot of this meaningful data, often resulting in datasets of reduced size, which lack representativeness of any realistic community. However, it is reasonably simple to include censored data into SSD by using an extension of the standard maximum likelihood method. In this paper, we detail this approach based on the use of the R-package \emph{fitdistrplus}, dedicated to the fit of parametric probability distributions. In particular, we introduce the new web-tool MOSAIC$\_$SSD to fit an SSD on datasets containing any kind of data, censored or not. MOSAIC$\_$SSD allows predicting any Hazardous Concentration (HC) and provides in addition bootstrap confidence intervals on the prediction. In the end, taking examples from published data, we illustrate the added value of including censored data in SSD., Comment: 26 pages, 2 figures

Published
2013

10. Statistical handling of reproduction data for exposure-response modelling

Author

Delignette-Muller, Marie Laure, Lopes, Christelle, Veber, Philippe, and Charles, Sandrine

Subjects
Statistics - Applications
Abstract

Reproduction data collected through standard bioassays are classically analyzed by regression in order to fit exposure-response curves and estimate ECx values (x% 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 ECx 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 datasets 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 ECx values. Furthermore, a non-classical negative-binomial model was shown to correctly describe the inter-replicate variability observed in the studied datasets.

Published
2013

15. Meta-transcriptomics reveals stress adaptation processes in microbial communities differing in exposure history

Author

Larras, Floriane, Billoir, Elise, Lips, Stefan, Schreiber, Stephan, Veber, Philippe, Delignette-Muller, Marie Laure, Schmitt-Jansen, Mechthild, Direction de l'évaluation (DEV INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), and EC2CO DROMADERE, EUR’H2O Lyon

Subjects
dose-response, DRomics, PICT, [SDE.MCG]Environmental Sciences/Global Changes, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, mechanistic understanding, [STAT.ME]Statistics [stat]/Methodology [stat.ME], microbial ecotoxicology
Abstract

International audience; In a changing environment, communities have to adapt continuously to survive. When microbial communities are chronically exposed to stress, adaptive mechanisms render them more tolerant. Yet a mechanistic understanding of differential adaptation processes to stress at a molecular level is lacking. Transcriptomics is a relevant methodology to tackle this challenge because it provides comprehensive functional information at molecular level. However, it was rarely applied for discriminating adaptive processes in communities differing in their exposure history and leading to community tolerance acquisition. Our study contributed to understanding acute stress responses of microbial communities differing in chronic pre-exposure to the photosynthesis inhibitor diuron, combining untargeted meta-transcriptomics (RNA-seq) and dose-response design. Freshwater microbial communities were incubated for 5-weeks in microcosms 1/ under constant exposure to 4μg/L diuron (stressed community) or 2/ without contamination (non-stressed community). Afterwards, both communities were exposed for 1 hour to a diuron concentration gradient to investigate differences in stress responses after chronic exposure. The meta-transcriptome analysis was handled by the DRomics R package, which provides a workflow dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of three replicates). This experimental design and the DRomics workflow enabled the determination of response trends as well as sensitivity thresholds for thousands of contigs and an accurate selection of responsive contigs within a dataset of more than three million contigs. Among the numerous responsive cellular processes, clear differences in gene expression and sensitivity were especially observed between both communities for photosynthesis-related processes. However, processes related to the carbon metabolism like fatty acid, lipid or glycolytic processes displayed impairment in both cases. In conclusion, meta-transcriptomics applied in a dose-response design provided key mechanistic insights for the understanding of adaptive processes and tolerance acquisition on environmental communities.

Published
2022

16. Development and validation of an OECD reproductive toxicity test guideline with the pond snail Lymnaea stagnalis (Mollusca, Gastropoda)

Author

Ducrot, Virginie, Askem, Clare, Azam, Didier, Brettschneider, Denise, Brown, Rebecca, Charles, Sandrine, Coke, Maïra, Collinet, Marc, Delignette-Muller, Marie-Laure, Forfait-Dubuc, Carole, Holbech, Henrik, Hutchinson, Thomas, Jach, Arne, Kinnberg, Karin L., Lacoste, Cédric, Le Page, Gareth, Matthiessen, Peter, Oehlmann, Jörg, Rice, Lynsey, Roberts, Edward, Ruppert, Katharina, Davis, Jessica Elphinstone, Veauvy, Clemence, Weltje, Lennart, Wortham, Ruth, and Lagadic, Laurent

Published
2014
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17. Interpretation of the results of ELISA tests commercialized for the serological diagnosis of Coxiella burnetii infection in domestic ruminants: a user-friendly Shiny application based on latent class models in a Bayesian framework

Author

Lurier, T., Delignette-Muller, Marie Laure, Ayral, Florence, Jourdain, Elsa, Rousset, Elodie, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Sophia Antipolis, Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), National Association of Spanish Specialists in Bovine Medicine (ANEMBE), and World Association for Buiatrics (WAB)

Subjects
Coxiella burnetii, [SDV]Life Sciences [q-bio]
Abstract

International audience; Q fever is a worldwide zoonotic disease, due to the bacterium Coxiella burnetii, responsible for reproductive disorders, such as abortion in domestic ruminants. Although direct detection of C. burnetii by quantitative PCR is primarily recommended for the direct diagnosis of Q fever in abortive contexts and identification of bacterial shedding, serological approaches aiming at detecting antibodies specific for C. burnetii are also useful at both the individual and herd levels. At the individual level, ELISA tests may be used to identify animals that were previously infected (with or without clinical signs and shedding) and may still be latently infected (carriers with or without shedding). At the herd level, ELISA tests may be used to reveal a past or recent exposure to C. burnetii within a considered farm, a key tool for a rapid screening (prevalence, current evolutive circulation). Recent investigations about the diagnostic accuracy of the three ELISA tests currently commercialized for their use in domestic ruminants showed that these tests are moderately sensitive (sensitivity values ranged between 40% and 94%) and that their specificities are inferior to 100% (specificity values ranged between 95% and 99%). As a consequence, the diagnostic uncertainty should be considered to limit potential misinterpretations of the individual or herd serological status.ObjectivesThe objectives of this study were (1) to build a methodological framework allowing calculating predictive values of Q fever ELISA tests at both the individual and the herd levels and (2) to provide a user-friendly application that could be easily used by veterinarians to interpret the results of a serological sample plan applied to a ruminant herd. Materials and methodsWe developed an advanced computing method based on latent class modeling, implemented using JAGS and R to calculate predictive values corresponding to the results obtained with any of the three commercialized ELISA tests, at both the individual and the herd levels. This method was integrated within an open source web application, using Shiny, to favor its accessibility to all the potential users of these ELISA tests (e.g., veterinarians, veterinary diagnostic laboratories, research laboratories). After completing the characteristics of the herd (species, herdsize, type of production) and the Q fever epidemiological context (if known), the users obtain the probability of true seropositivity of the tested herd and animals given the ELISA test results. The operation of this application is illustrated on a true clinical case where a Charolais bull originating from an apparently ‘free of infection’ herd was tested positive for Q fever by one ELISA test at introduction. To confirm or infirm these test results, additional animals in the herd of origin were tested with the same ELISA, considering firstly five heifers raised with the bull and secondly all males and females more than two-year-old (N=149). Probabilities of true seropositivity of the bull and its originating herd were calculated thanks to the developed application.ResultsThe five other animals initially tested animals that were raised with the seropositive bull were negative to the ELISA test, which corresponds, in regard to the test used and to the herd characteristics to a probability of the bull’s true seropositivity estimated at 0.85 with a 95% credibility interval (CI) of [0.14; 0.98].Among the animals older than two years present in the herd, 5 out of the 149 tested animals tested positive which corresponds for each positive animal to a probability of true seropositivity estimated at 0 with a 95% CI of [0 ; 0.65]. At the herd level, the probability that the proportion of seropositive animals was above 0 was estimated at 0 with a 95% CI of [0 ; 0.58]; and if the herd was truly seropositive, the proportion of truly seropositive animals in the herd was assessed to 0.06 with a 95% CI of [0.02; 0.12].ConclusionThis application assists veterinarians in a proper interpretation of the results of Q fever ELISA tests according to the sampling size and to available epidemiological and herd information. Veterinarians can therefore easily take advantage of a complex statistical model in a Bayesian framework to support their daily work related to Q fever risk analysis in ruminants. In the absence of a perfect reference test, this application could also be useful for local and reference laboratories for the confirmatory diagnosis of an ELISA test result.

Published
2022

19. Coxiella burnetii within- and between-herd true seroprevalence assessment in domestic ruminants in France accounting for diagnostic uncertainty with latent class

Author

Lurier, T., Rousset, Elodie, Sala, Carole, Gache, Kristel, Delignette-Muller, Marie Laure, Jourdain, Elsa, Ayral, Florence, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Sophia Antipolis, Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Unité Fièvre Animale Q (Fièvre Q), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Unité Epidémiologie et Appui à la Surveillance (EAS), Laboratoire de Lyon [ANSES], Université de Lyon-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Université de Lyon-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Fédération nationale des Groupements de Défense Sanitaire (GDS France), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP), American Rickettsia Society, European Society for Chlamydia Research, and European Society on intracellular bacteria (ESCCAR)

Subjects
Q fever Coxiella burnetii, [SDV]Life Sciences [q-bio], [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract

International audience

Published
2022

20. Interpretation of the results of Q fever ELISA tests in domestic ruminants : a user-friendly Shiny appli-cation based on latent class models in a Bayesian framework

Author

Lurier, T., Delignette-Muller, Marie Laure, Jourdain, Elsa, Ayral, Florence, Rousset, Elodie, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP), Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), American Rickettsia Society, European Society for Chlamydia Research, and European Society on intracellular bacteria (ESCCAR)

Subjects
Q fever Coxiella burnetii, [SDV]Life Sciences [q-bio], [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract

International audience

Published
2022

22. Diagnostic performances study of three ELISA tests commercialized for Q fever diagnosis in domestic ruminants using latent class models

Author

Lurier, Thibaut, Rousset, Elodie, Gasqui, Patrick, Sala, Carole, Claustre, Clément, Abrial, David, Dufour, Philippe, de Crémoux, Renée, Gache, Kristel, Delignette-Muller, Marie Laure, Ayral, Florence, Jourdain, Elsa, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité Fièvre Animale Q (NRL Fièvre Q), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Laboratoire de Sophia Antipolis, Laboratoire de Lyon [ANSES], Institut de l'élevage (IDELE), Fédération nationale des Groupements de Défense Sanitaire (GDS France), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP), ANSESDGALGDS FranceINRAEVetagro Sup, and Friedrich Loeffler Institut

Subjects
Sheep, Conditional dependence, Goats, [SDV]Life Sciences [q-bio], Latent class model, Cattle, Bayesian, Diagnostic accuracy, Q fever, Herd sensitivity
Abstract

International audience; Q fever is a worldwide zoonotic disease mainly res-ponsible for reproductive disorder such as abortion in domestic ruminants. The serological diagnosis in domestic ruminants is mainly performed using ELISA tests. In France, there are three ELISA tests that are commercialized with little information about their sensitivities and specificities.

Published
2021

23. Evaluation, à l’aide de modèles à classes latentes, des performances diagnostic des tests ELISA commercialisés pour le diagnostic sérologique des infections par Coxiella burnetii chez les ruminants domestiques

Author

LURIER, T., Rousset, Elodie, Gasqui, Patrick, Sala, Carole, Caustre, Clément, Abrial, David, Morignat, Eric, Dufour, Pascal, De Cremoux, Renée, Gache, Kristel, Delignette-Muller, Marie Laure, Ayral, Florence, Jourdain, Elsa, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Sophia Antipolis, Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Université de Lyon, Institut de l'élevage (IDELE), Fédération nationale des Groupements de Défense Sanitaire (GDS France), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP), Unité Fièvre Animale Q (Fièvre Q), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Laboratoire de Lyon [ANSES], and Université de Lyon-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)

Subjects
MESH: Q Fever, Fièvre Q, [SDV]Life Sciences [q-bio], Humans, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, France, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2021

26. Additional file 2 of Evaluation using latent class models of the diagnostic performances of three ELISA tests commercialized for the serological diagnosis of Coxiella burnetii infection in domestic ruminants

Author

Lurier, Thibaut, Rousset, Elodie, Gasqui, Patrick, Sala, Carole, Claustre, Clément, Abrial, David, Dufour, Philippe, De Crémoux, Renée, Gache, Kristel, Delignette-Muller, Marie Laure, Ayral, Florence, and Jourdain, Elsa

Abstract

Additional file 2: Output of the model. R-Markdown Word document containing R code, summary of the models, Gelman and rubin’s statistics, trace plots and prior vs posterior density plots.

Published
2021
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27. Additional file 1 of Evaluation using latent class models of the diagnostic performances of three ELISA tests commercialized for the serological diagnosis of Coxiella burnetii infection in domestic ruminants

Author

Lurier, Thibaut, Rousset, Elodie, Gasqui, Patrick, Sala, Carole, Claustre, Clément, Abrial, David, Dufour, Philippe, De Crémoux, Renée, Gache, Kristel, Delignette-Muller, Marie Laure, Ayral, Florence, and Jourdain, Elsa

Abstract

Additional file 1. Supplementary material. Appendix A. Cross-classified test results in each department and verification of the hypothesis of constant accuracy across populations. Appendix B. Complete specifications of the model. Appendix C. Simulation study. Appendix D. Herd sensitivity, herd specificity. Appendix E. Estimations of the model. Appendix F. Sensitivity analysis.

Published
2021
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33. Developmental variability channels mouse molar evolution

Author

Hayden, Luke, primary, Lochovska, Katerina, additional, Sémon, Marie, additional, Renaud, Sabrina, additional, Delignette-Muller, Marie-Laure, additional, Vilcot, Maurine, additional, Peterkova, Renata, additional, Hovorakova, Maria, additional, and Pantalacci, Sophie, additional

Published
2020
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36. Characterization of unexpected growth of Escherichia coli O157:H7 by modeling

Author

Cornu, Marie, Delignette-Muller, Marie Laure, and Flandrois, Jean-Pierre

Subjects
Escherichia coli -- Physiological aspects, Bacterial growth -- Research, Biological sciences
Abstract

Unexpected growth of Escherichia coli O157:H7 has been characterized by modeling of batch kinetics in minimal synthetic medium. The growth seemed to differ from the exponential growth expected in minimal synthetic medium and seen for E. coli K-12. In mixed cultures, E. coli K-12 had a positive effect on E. coli. O157:H7 and corrected its growth anomaly, so commensalism took place, with the E.coli K-12 growth curve not affected. The interaction might be explained by an exchange of methionine.

Published
1999

37. Outils d'observation des boiteries

Author

Poulain, Valentin, Mounier, Luc, Delignette Muller, Marie-Laure, Ledoux, Dorothee, VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)

Subjects
observation, [SDV]Life Sciences [q-bio], movement disorders, trouble locomoteur
Abstract

Outils d'observation des boiteries. Journées Nationales des Groupements Techniques Vétérinaires (JNGTV)

Published
2019

38. Approche de Modélisation Hiérarchique pour la Description de l'Effet de la Compétition Interspécifique sur la Tolérance Chimique d'Herbacées

Author

Baillard, Vincent, Delignette-Muller, Marie Laure, Sulmon, Cécile, Bittebière, Anne‐kristel, Mony, Cendrine, Devin, Simon, Billoir, Elise, BAILLARD, Vincent, Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Terre et Environnement de Lorraine (OTELo), Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), and Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDE] Environmental Sciences, [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

39. Evaluation de méthodes diagnostiques en l’absence de gold standard sur la base de variables binaires et continues : intérêt de l'approche bayésienne

Author

Lurier, Thibaut, Delignette Muller, Marie-Laure, Jourdain, Elsa, Ayral, Florence, Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Centre National de la Recherche Scientifique (CNRS), UPE, European Union Reference Laboratory for equine diseases (EURL), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), and Rongeurs Sauvages, Risques Sanitaires et Gestion des Populations - UR 1233 (RS2GP)

Subjects
[SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2018

41. Assessment of Ozone or Not-Treated Wastewater Ecotoxicity Using Mechanism-Based and Zebrafish Embryo Bioassays

Author

Wigh, Adriana, primary, Aït-Aïssa, Selim, additional, Creusot, Nicolas, additional, Terrisse, Hugo, additional, Delignette-Muller, Marie-Laure, additional, Bergé, Alexandre, additional, Vulliet, Emmanuelle, additional, Domenjoud, Bruno, additional, Gonzalez-Ospina, Adriana, additional, Brosselin, Vanessa, additional, Devaux, Alain, additional, and Bony, Sylvie, additional

Published
2018
Full Text
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46. A Toolbox for Nonlinear Regression in R: The Package nistools

Author

Baty, F., Ritz, C., Charles, Sandrine, Brutsche, M., Flandrois, Jean-Pierre, Delignette-Muller, Marie Laure, Modélisation et écotoxicologie prédictives, Département biostatistiques et modélisation pour la santé et l'environnement [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Bioinformatique, phylogénie et génomique évolutive (BPGE), Département PEGASE [LBBE] (PEGASE), Ecologie quantitative et évolutive des communautés, and Département écologie évolutive [LBBE]

Subjects
[SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

48. An accept-and-reject algorithm to determine performance objectives that comply with a food safety objective

Author

Guillier, Laurent, Augustin, J.C., Denis, Jean-Baptiste, Delignette-Muller, Marie-Laure, Laboratoire de Sécurité des Aliments, Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Unité de biométrie et intelligence artificielle de jouy, Institut National de la Recherche Agronomique (INRA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Ecole Nationale Vétérinaire de Lyon (ENVL), and Unité de biométrie et intelligence artificielle de Jouy (MIA-JOUY)

Subjects
exposure assessment, objectif de performance, aliment, [INFO]Computer Science [cs], performance objective, [MATH]Mathematics [math], accepter et rejeter l'algorithme, évaluation de l'exposition, accept and reject algorithm, securité alimentaire
Abstract

International audience; Quantitative risk assessment of microbiological hazards in foods (QMRA) can assess the impact of control measures on risk and can help to achieve food safety targets. Generally, the effect of a particular input variable of a QMRA model is assessed by comparing the results corresponding to the default situation to those obtained from scenarios modifying its behaviour. The purpose of this work is to handle and propose alternative methods to scenario testing for determining PO (performance objective) or process criterion from a given FSO (food safety objective). These methods were applied in the framework of a QMRA model that considered the fate of a hazard from raw material to the consumption stage. A second order Monte-Carlo simulation approach separately assessing the uncertainty and variability on the final exposure, we applied an accept-and-reject algorithm to measure the importance of each variable of the model and to determine, with its uncertainty, the probability of compliance with an FSO according to the range of values that these variables can take. Within a first order Monte-Carlo simulation approach, we applied the Saltelli sensitivity analysis method to select the most influential variables on the compliance with the FSO. Then, an accept-and- reject algorithm was applied for the most influential variables. With both approaches, we managed to identify influential variables and were able to determine which ranges of values should be met to respect the FSO. Complications originated from correlated variables or QMRA models with low probability to reach the FSO were also tackled. It is concluded that accept and-reject algorithms are simple methods to apply and that they allow extrapolation of the classical point estimate scenario analysis to the entire range of values taken by input variables.

Published
2011

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