Thermal stability of hepatitis E virus assessed by a molecular biological approach

Background: Hepatitis E virus (HEV) is a pathogen of emerging concern in industrialized countries. The consumption of wild boar meat has been identified as one risk factor for autochthonous HEV infections. Only limited information is available about thermal stability of HEV, mainly due to the lack of rapid and efficient cell culture systems for measurement of HEV infectivity. Methods: A molecular biological method was implemented in order to distinguish disassembled from intact viral particles using RNase treatment followed by quantitative real-time RT-PCR. The method was applied to a wild boar liver suspension containing HEV genotype 3. Results: Time-course analyses indicated that the decline of protected RNA could be described by a biphasic model with an initial decrease followed by a stationary phase. The stationary phase was reached after 1 hour at 4°C, 3 days at 22°C and 7 days at 37°C with log reductions of 0.34, 0.45 and 1.24, respectively. Protected RNA was detectable until the end of the experiments at day 50 or 70. Heat exposure for 1 minute resulted in a log reduction of 0.48 at 70°C and increased with higher temperatures to 3.67 at 95°C. Although HEV infectivity titration by inoculation of the liver suspension onto three cell lines did not succeed, the results of the RNase-based method are in accordance with published cell culture-based data. Conclusions: Measurement of intact viral particles using the RNase-based method may provide data on the stability of RNA viruses when cell culture-based infectivity titrations are not efficient or not available. The method enables processing of large sample numbers and may be suitable to estimate stability of HEV in different types of food

Minimum Information Required to Annotate Food Safety Risk Assessment Models (MIRARAM)

Abstract In the last decades, mathematical models and model-based simulations became important elements not only in the area of risk assessment concerning microbiological and chemical hazards but also in modelling biological phenomena in general. Unfortunately, many of the developed models are published in non-standardized ways, which hinders efficient exchange, re-use and continuous improvement of models within the risk assessment domain. The establishment of guidelines for model annotation is an important pre-condition to overcome these obstacles. Additionally, implementation of annotation guidelines can improve transparency, quality control and even aid the clarification of intellectual property rights. Here, we address the question of "What is the minimum set of metadata that should be provided for a model in the risk assessment domain?". The proposed guideline focuses on food safety risk assessment models and is called "Minimum Information Required to Annotate food safety Risk Assessment Models (MIRARAM)". MIRARAM supports the model creator during the model documentation step and could also be used as a checklist by scientific journal editors or database curators. Software developers could take up MIRARAM and develop easy-to-use software tools or new features in existing programs that can help model creators to provide proposed model annotations in harmonized file formats. Based on experiences from similar guidelines in related scientific disciplines (like systems biology), it is expected that MIRARAM could contribute to the promotion of application and re-use of models as well as to implementing more standardized quality control in the food safety modelling domain

Harmonized terms, concepts and metadata for microbiological risk assessment models: the basis for knowledge integration and exchange

In the last decades the microbial food safety community has developed a variety of valuable knowledge (e.g., mathematical models and data) and resources (e.g., databases and software tools) in the areas of quantitative microbial risk assessment (QMRA) and predictive microbiology. However, the reusability of this knowledge and the exchange of information between resources are currently difficult and time consuming. This problem has increased over time due to the lack of harmonized data format and rules for knowledge annotation. It includes the lack of a common understanding of basic terms and concepts and of a harmonized information exchange format to describe and annotate knowledge. The existence of ambiguities and inconsistencies in the use of terms and concepts in the QMRA and predictive microbial (PM) modelling necessitates a consensus on their refinement, which will allow a harmonized exchange of information within these areas. Therefore, this work aims to harmonize terms and concepts used in QMRA and PM modelling spanning from high level concepts as defined by Codex Alimentarius, Food and Agriculture Organization (FAO) and World Health Organization (WHO), up to terms generally used in statistics or data and software science. As a result, a harmonized schema for metadata that allows consistent annotation of data and models from these two domains is proposed. This metadata schema is also a key component of the Food Safety Knowledge Markup Language (FSK-ML), a harmonized format for information exchange between resources in the QMRA and PM modelling domain. This work is carried out within a research project that aims to establish a new community resource called Risk Assessment Modelling and Knowledge Integration Platform (RAKIP). This platform will facilitate the sharing and execution of curated QMRA and PM models using the foundation of the proposed harmonized metadata schema and information exchange format. Furthermore, it will also provide access to related open source software libraries, converter tools and software-specific import and export functions that promote the adoption of FSK-ML by the microbial food safety community. In the future, these resources will hopefully promote both the knowledge reusability and the high quality information exchange between stakeholders within the areas of QMRA and PM modelling worldwide

Evaluation of two family-based intervention programs for children affected by rare disease and their families – research network (CARE-FAM-NET): study protocol for a rater-blinded, randomized, controlled, multicenter trial in a 2x2 factorial design

Background: Families of children with rare diseases (i.e., not more than 5 out of 10,000 people are affected) are often highly burdened with fears, insecurities and concerns regarding the affected child and its siblings. Although families caring for children with rare diseases are known to be at risk for mental disorders, the evaluation of special programs under high methodological standards has not been conducted so far. Moreover, the implementation of interventions for this group into regular care has not yet been accomplished in Germany. The efficacy and cost-effectiveness of a family-based intervention will be assessed. Methods/design: The study is a 2x2 factorial randomized controlled multicenter trial conducted at 17 study centers throughout Germany. Participants are families with children and adolescents affected by a rare disease aged 0 to 21 years. Families in the face-to-face intervention CARE-FAM, online intervention WEP-CARE or the combination of both will be treated over a period of roughly 6 months. Topics discussed in the interventions include coping, family relations, and social support. Families in the control condition will receive treatment as usual. The primary efficacy outcome is parental mental health, measured by the Structured Clinical Interview for DSM-IV (SCID-I) by blinded external raters. Further outcomes will be assessed from the parents’ as well as the children’s perspective. Participants are investigated at baseline, 6, 12 and 18 months after randomization. In addition to the assessment of various psychosocial outcomes, a comprehensive health-economic evaluation will be performed. Discussion: This paper describes the implementation and evaluation of two family-based intervention programs for Children Affected by Rare Disease and their Family’s Network (CARE-FAM-NET) in German standard care. A methodologically challenging study design is used to reflect the complexity of the actual medical care situation. This trial could be an important contribution to the improvement of care for this highly burdened group. Trial registration: German Clinical Trials Register: DRKS00015859 (registered 18 December 2018) and ClinicalTrials.gov: NCT04339465 (registered 8 April 2020). Protocol Version: 15 August 2020 (Version 6.1). Trial status: Recruitment started on 1 January 2019 and will be completed on 31 March 2021. © 2020, The Author(s)

Making Linked Data accessible for One Health Surveillance with the "One Health Linked Data Toolbox"

In times of emerging diseases, data sharing and data integration are of particular relevance for One Health Surveillance (OHS) and decision support. Furthermore, there is an increasing demand to provide governmental data in compliance to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Semantic web technologies are key facilitators for providing data interoperability, as they allow explicit annotation of data with their meaning, enabling reuse without loss of the data collection context. Among these, we highlight ontologies as a tool for modeling knowledge in a field, which simplify the interpretation and mapping of datasets in a computer readable medium; and the Resource Description Format (RDF), which allows data to be shared among human and computer agents following this knowledge model. Despite their potential for enabling cross-sectoral interoperability and data linkage, the use and application of these technologies is often hindered by their complexity and the lack of easy-to-use software applications.To overcome these challenges the OHEJP Project ORION developed the Health Surveillance Ontology (HSO). This knowledge model forms a foundation for semantic interoperability in the domain of One Health Surveillance. It provides a solution to add data from the target sectors (public health, animal health and food safety) in compliance with the FAIR principles of findability, accessibility, interoperability, and reusability, supporting interdisciplinary data exchange and usage. To provide use cases and facilitate the accessibility to HSO, we developed the One Health Linked Data Toolbox (OHLDT), which consists of three new and custom-developed web applications with specific functionalities. The first web application allows users to convert surveillance data available in Excel files online into HSO-RDF and vice versa. The web application demonstrates that data provided in well-established data formats can be automatically translated in the linked data format HSO-RDF. The second application is a demonstrator of the usage of HSO-RDF in a HSO triplestore database. In the user interface of this application, the user can select HSO concepts based on which to search and filter among surveillance datasets stored in a HSO triplestore database. The service then provides automatically generated dashboards based on the context of the data. The third web application demonstrates the use of data interoperability  in the OHS context by using HSO-RDF to annotate meta-data, and in this way link datasets across sectors. The web application provides a dashboard to compare public data on zoonosis surveillance provided by EFSA and ECDC.The first solution enables linked data production, while the second and third provide examples of linked data consumption, and their value in enabling data interoperability across sectors. All described solutions are based on the open-source software KNIME and are deployed as web service via a KNIME Server hosted at the German Federal Institute for Risk Assessment. The semantic web extension of KNIME, which is based on the Apache Jena Framework, allowed a rapid an easy development within the project. The underlying open source KNIME workflows are freely available and can be easily customized by interested end users.With our applications, we demonstrate that the use of linked data has a great potential strengthening the use of FAIR data in OHS and interdisciplinary data exchange

A network model of the egg supply chain in Germany implemented as a FSKX compliant object

In our days, food supply chains are becoming more and more complex, generating global networks involving production, processing, distribution and sale of food products. To follow the "farm to fork" paradigm when assessing risks from various hazards linked to food products, supply chain network models are useful and versatile tools.The objective of the present "egg supply chain network model" is to allow users to predict and visualise the spatial commodity flow within the German egg supply chain. The network model provides for the user the option to select values for the input parameter "actor" in order to allow simulation of estimates for different supply chain scenarios. It generates a data frame as output regarding the estimates of food flows for the product "chicken eggs" in Germany on NUTS-3 level according to the selected parameter and a chloropleth map for illustrating the distribution of product quantities.The network model and all required resources are provided as a fully annotated file compliant to the community standard Food Safety Knowledge Exchange (FSKX) and can be executed online or with the desktop FSK-Lab software

Thermal stability of hepatitis E virus assessed by a molecular biological approach

Abstract Background Hepatitis E virus (HEV) is a pathogen of emerging concern in industrialized countries. The consumption of wild boar meat has been identified as one risk factor for autochthonous HEV infections. Only limited information is available about thermal stability of HEV, mainly due to the lack of rapid and efficient cell culture systems for measurement of HEV infectivity. Methods A molecular biological method was implemented in order to distinguish disassembled from intact viral particles using RNase treatment followed by quantitative real-time RT-PCR. The method was applied to a wild boar liver suspension containing HEV genotype 3. Results Time-course analyses indicated that the decline of protected RNA could be described by a biphasic model with an initial decrease followed by a stationary phase. The stationary phase was reached after 1 hour at 4°C, 3 days at 22°C and 7 days at 37°C with log reductions of 0.34, 0.45 and 1.24, respectively. Protected RNA was detectable until the end of the experiments at day 50 or 70. Heat exposure for 1 minute resulted in a log reduction of 0.48 at 70°C and increased with higher temperatures to 3.67 at 95°C. Although HEV infectivity titration by inoculation of the liver suspension onto three cell lines did not succeed, the results of the RNase-based method are in accordance with published cell culture-based data. Conclusions Measurement of intact viral particles using the RNase-based method may provide data on the stability of RNA viruses when cell culture-based infectivity titrations are not efficient or not available. The method enables processing of large sample numbers and may be suitable to estimate stability of HEV in different types of food.</p