This paper presents the Bacteria Biotope task of the BioNLP Shared Task 2016, which follows the previous 2013 and 2011 editions. The task focuses on the extraction of the locations (biotopes and geographical places) of bacteria from PubMed abstracts and the characterization of bacteria and their associated habitats with respect to reference knowledge sources (NCBI taxonomy, OntoBiotope ontology). The task is motivated by the importance of the knowledge on bacteria habitats for fundamental research and applications in microbiology. The paper describes the different proposed subtasks, the corpus characteristics, the challenge organization, and the evaluation metrics. We also provide an analysis of the results obtained by participants.

Oxygen and carbon dioxide solubility and diffusivity are 2 key parameters to understand gas transfer in food matrices. Knowledge of these parameters could help to predict gas concentration in modified atmosphere packaging and, consequently, to predict shelf-life of the product through the development of appropriate mathematical models. The aim of this review is to present the existing methodologies to quantify O 2 and CO 2 contents in food, especially in solid food matrices which is very challenging. There is a focus on how these methodologies could be used to determine gas transfers kinetics. Data of O 2 /CO 2 solubilities and diffusivities in food are collected and compared with a specific emphasis on the food characteristics and factors impacting them. An analysis of the current state of knowledge in solid food matrices is carried out to tentatively build a general predictive model of the O 2 and CO 2 solubility and diffusivity extendable to any kind of food matrix.

Temperature and relative humidity are major factors determining virus inactivation in the environment. This article reviews inactivation data of coronaviruses on surfaces and in liquids from published studies and develops secondary models to predict coronaviruses inactivation as a function of temperature and relative humidity. A total of 102 D-values (time to obtain a log10 reduction of virus infectivity), including values for SARS-CoV-2, were collected from 26 published studies. The values obtained from the different coronaviruses and studies were found to be generally consistent. Five different models were fitted to the global dataset of D-values. The most appropriate model considered temperature and relative humidity. A spreadsheet predicting the inactivation of coronaviruses and the associated uncertainty is presented and can be used to predict virus inactivation for untested temperatures, time points or any coronavirus strains belonging to Alphacoronavirus and Betacoronavirus genera. Importance: The prediction of the persistence of SARS-CoV-2 on fomites is essential to investigate the importance of contact transmission. This study collects available information on inactivation kinetics of coronaviruses in both solid and liquid fomites and creates a mathematical model for the impact of temperature and relative humidity on virus persistence. The predictions of the model can support more robust decision-making and could be useful in various public health contexts. Having a calculator for the natural clearance of SARS-CoV-2 depending on temperature and relative humidity could be a valuable operational tool for public authorities.