Program

How to be successful in your scientific publication

Context 

This course is designed to help junior and senior scientists write scientific articles in English for specialized journals in order to build or strengthen their careers. 

Objectives 

This course will describe how to overcome common barriers to article publication, such as targeting journals, writing an attractive introduction to the manuscript, presenting tables and data, etc. 

Prerequisites 

No prerequisites for this course. 

Pedagogical scenario 

This course will take the form of a discussion around the presentation of a document whose support will be distributed at the end of the session.
At the end of the course, the trainer will suggest that you go back over the notions that were not clear, while making sure that most of the elements have been acquired. An evaluation of the knowledge will be done collectively at the end of the session. 

Program of the day 

Morning: 10 am – 12.00 am 

• Organize and build a poster 

• Communicate toward the general public
  
  

Afternoon: 1.30pm – 5.30pm 

• How to prepare good papers and how to write them

  1. • Learn how to write in science

     • Knowing what tone to use for writing

     • Targeting a journal related to your research topic

     • Use an agenda to write

     • Structure your manuscript correctly

     • Use data, graphs and tables correctly

     • Knowing how to surround yourself with the right people: Contacts with referees and editors

• Ask yourself the right questions

  • • Who is my audience?

    • What are their objectives in reading my writing?

    • What message do I want them to get out of it

Instructors 

Philippe Garrigues  (https://www.ism.u-bordeaux.fr/_GARRIGUES-Philippe_.html)

The course is provided by Dr. Philippe Garrigues, CNRS research director at the University of Bordeaux. and editor-in-chief of the Environmental Science and Pollution Research (ESPR) journal. Philippe gives courses worldwide on environmental pollutants and their effects, with a specific focus on analytical detection and biological effect quantification. 

Introduction to R programming for reproducible research

Context 

R is a programming language now very commonly used for statistical analysis of data. Reproducible research is highly recommended at each step of a scientific study, including the statistical analysis of data. A good knowledge of the basic R language and of modern tools available in RStudio constitutes a great asset for a correct, efficient and highly reproducible interpretation of scientific results, and also for their publication. 

Objectives 

Make participants more comfortable and efficient to  

• Import, export and manipulate data (libraries: readr, dplyr) 

• Organize a project to distinguish between data, outputs, scripts, and notebooks

• Produce reliable and high-quality R code to automate data analysis (notion: versioning with git)

• Visualize data (libraries: ggplot2, plotly) 

• Produce complete analysis reports  (libraries: rmarkdown)

Prerequisites 

No prerequisites except the installation of the following software (open source and free softwares) on your personal laptops: 

• A recent version of R (> 4.0.0) 

• A recent version of RStudio (Help / Check for Updates) 

• A recent version of the packages that are already installed on your machine (for this purpose go in Tools / Check for Package Updates)

• Not mandatory (could be done during the lecture): install the tidyverse packages (ggplot2, dplyr, readr, …) as well as fitdistrplus, morse, rbioacc.  

Pedagogical scenario 

The various skills will be acquired essentially through guided practical exercises, based in great part on ecotoxicological data, either from regulatory laboratory tests (OECD) or from research data. It is also appreciated if students bring their own ecotoxicology datasets. We will use a set of R libraries that are used in the MOSAIC application on day 3 (fitdistrplus, morse, rbioacc), and we will see how to integrate them with R standards (tidyverse)."ample from ecotoxicology. 

Program of the day 

Morning: 9 am – 12.30 am 

•    About R

  • • What is R?

    •  The packages

    •  RStudio project and working directory

    • Help and support

    • How to cite R and R packages?

    • A few tips for a good start

    •  Presentation of the dataset from ecotoxicology we will use as a  thread all along the presentation and exercices

•     Data

  • • Variables

    • Typology of data

    • Data structures

    • Importing and exporting data

    • Manipulation of data (to sort, filter, tidy, reformat, …)

    • Structure of the working directory (data, scripts, notebook, outputs)

Afernoon: 2 pm – 5.30 pm 

• Programming elements

  • • Control structures

    •  Functions

• Graphics and reporting

  • • Basic graphics

• • • • Advanced graphics

      • Use of the package “rmarkdown” to create reports

Instructor: 

Virgile Baudrot : il est docteur en éco-épidémiologie et dirige le cabinet d'ingénierie logicielle en écotoxicologie Qonfluens, qu'il a fondé en 2022. Il est mainteneur de plusieurs bibliothèques R dédiées à l'écotoxicologie (morse, rbioacc, rPBK) qu'il a développées avec le département d'écotoxicologie de l'Université Lyon 1 (MEPS). Il enseigne en tant qu'intervenant extérieur aux étudiants du Master EMME de l'Université de Franche-Comté ainsi qu'auprès de l'EFSA en tant qu'expert en modélisation écotoxicologique. 

MOSAIC : Learn how to evaluate the toxicity of a substance 

Context 

The European guidelines on risk assessment of chemicals have recently been amended (pesticides and biocides directives) in order to improve their ecological realism while limiting the use of tests on laboratory animals. 

These new official texts all recommend the use of appropriate mathematical and statistical modeling tools for cognitive and predictive purposes. 

Mosaic (univ-lyon1.fr.) 

Objectives 

Participants will learn to use MOSAIC, through a step-by-step guidance based on concrete practical examples. The objectives of this training are primarily to : 

• understand the issues of modeling as a tool for environmental risk assessment (ERA) related to the presence of xenobiotics; 

• know how to determine for a given species/substance combination critical effect concentrations on life history traits classically collected according to standard experimental protocols (e.g. for the constitution of marketing authorization dossiers for new molecules). 

Prerequisites  

• Basic knowledge of statistics; 

• Notions of standardized bioassays in biology or ecotoxicology, whether in a research or regulatory setting. 

• Two-year technical degree (BAC+2) 

Pedagogical scenario 

The training will be based exclusively on the 

free MOSAIC web platform. Understanding in a theoretical part the need to use such a tool, know how to use MOSAIC in practice with a dataset 

Program of the day  

Morning: 9 am – 12.30 am 

• Interest of modeling as a decision-help tool for environmental risk assessment (including the regulatory context) and presentation of the MOSAIC platform. 

• Using MOSAIC (self-paced) to determine standard toxicity values: 

• From survival or mobility data 

• From reproductive data 

• From growth data
  
  

Afternoon: 2 pm – 5.30 pm 

• Processing of practical examples (survival/reproduction/growth) continues 

• Using MOSAIC (self-paced) to determine bioaccumulation metrics (BCF/BSAF/BMF) 

• Improvements in environmental risk assessment (including the regulatory context) to evaluate the bioaccumulation capacity of chemical substances. 

Instructor 

Sandrine Charles Charles Sandrine | LABORATOIRE DE BIOMÉTRIE ET BIOLOGIE ÉVOLUTIVE (univ-lyon1.fr) 

Professor at the University of Lyon in the Biometrics Laboratory – Evolutionary Biology (LBBE - CNRS), Research as part of the evaluation quantitative risk in ecotoxicology through the development of methods and tools for identifying substances potentially dangerous, to define thresholds of Acceptable concentrations at different levels of organization biological, to develop quality indicators environment, but also to characterize causal links between toxicity and ecological impact. 

In silico approaches : (Q)SAR models for ecotoxicological endpoints  

Context 

In silico approaches, considered as New Approach Methods (NAMs), represent a great potential for regulatory ecotoxicological hazard assessment. They also represent a promising alternative method in response to the need to reduce testing on vertebrates, time to market and cost compared to standard methods. The aims of this course are 1/ to understand the regulatory context of chemicals in Europe, 2/ to identify the ecotoxicological endpoints and related OECD guidelines required under regulatory framework and 3/ to appreciate the potential of (Q)SAR models to predict these endpoints with confidence. Trainees will have the opportunity to put their new skills/knowledge into practice by testing different models during the session.

Objectives 

Present the ecotoxicological endpoints, and related OECD guidelines, required under a regulatory framework,

Understand the principles of ecotoxicological hazard assessment,

Discover and apply (Q)SAR models for ecotoxicological endpoints,

Appreciate the reliability of predictions obtained from in silico approaches.

Prerequisites  

English speaking. Participants should bring their own laptop to follow the course. Basic learning in ecotoxicology would be an asset. No knowledge of statistical methodology or coding is required.

Target audience : 

Students, academics, regulators, environmental risk assessor.

Teaching scenario : 

Mix between lecture course and practical session

Program of the day  

Morning: 9 am – 12.30 am 

•           Presentation of the regulatory context of chemicals in Europe,

•         Introduction to the different OECD guidelines that are required under regulatory framework to assess the ecotoxicity (e.g. acute and chronic ecotoxicity of chemicals to algae, daphnids and fish), the biodegradability and the bioaccumulation of chemicals.

Afternoon: 2 pm – 3.30 pm 

•          Introduction to the (Q)SAR approaches and to the OECD principles for model validity and prediction reliability.

•          Practical session using freeware (Q)SARs:

o   Introduction to several (Q)SAR freeware,

o   Run different models on several chemicals,

o   Expertise the predictions and the models.

Skills expected to be acquired at the end of the training:

Basic knowledge on regulatory ecotoxicology.

Basic knowledge on (Q)SAR modelling.

Be able to use a (Q)SAR model to predict an ecotoxicological endpoint.

Basic knowledge on the key elements to control to assess the validity of a model and the reliability of a prediction.

Evaluation method : QCM

Instructors : 

• Floriane Larras   (https://www.researchgate.net/profile/Floriane-Larras) 

• Paul Thomas 

Other information :

A satisfaction survey will be sent to you by email at the end of the training course, in order to collect your feedback, comments and suggestions for further improvement. Your answers will be strictly anonymous.

Need more information? Do not hesitate to contact us : contact@everteafee.com