Search

Funding: This research was funded by Fundação para a Ciência e Tecnologia through CEECIND/01049/ 2020 for H.S. and CEECIND/02373/2020 for M.-J.A. For the other authors, this research received no external funding. The gut has been proposed as a potential alternative entry route for SARS-CoV-2. This was mainly based on the high levels of SARS-CoV-2 receptor expressed in the gastrointestinal (GI) tract, the observations of GI disorders (such as diarrhea) in some COVID-19 patients and the detection of SARS-CoV-2 RNA in feces. However, the underlying mechanisms remain poorly understood. It has been proposed that SARS-CoV-2 can productively infect enterocytes, damaging the intestinal barrier and contributing to inflammatory response, which might lead to GI manifestations, including diarrhea. Here, we report a methodological approach to assess the evidence supporting the sequence of events driving SARS-CoV-2 enteric infection up to gut adverse outcomes. Exploring evidence permits to highlight knowledge gaps and current inconsistencies in the literature and to guide further research. Based on the current insights on SARS-CoV-2 intestinal infection and transmission, we then discuss the potential implication on clinical practice, including on long COVID. A better understanding of the GI implication in COVID-19 is still needed to improve disease management and could help identify innovative therapies or preventive actions targeting the GI tract. publishersversion published

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues. publishedVersion

Funding Information: The work was performed under the JRC Exploratory Research project CIAO—Modelling COVID-19 pathogenesis using the Adverse Outcome Pathway (AOP). Julija Filipovska for her careful reading and valuable inputs. Funding: This research was funded by the Academy of Finland (grand number 322761) for D.G., G.d.G. and L.A.S. and by Fundação para a Ciência e Tecnologia through CEECIND/01049/2020 for H.S. For the other authors, this research received no external funding. Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues. publishersversion published

Presentation to the European Society of Toxicology in Vitro (ESTIV) November 2022 Search for CCTE records in EPA’s Science Inventory by typing in the title at this link. https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25

On 26 November 2021, the World Health Organization (WHO) classified variant B.1.1.529, reported earlier by the South African authorities as “Variant of Concern” with the name Omicron. The decision was taken because Omicron is bearing a number of mutations with a potential impact on its transmissibility, severity of disease following infection, as well as on the effectiveness of immune protection resulting from both vaccines and natural infection. In this paper, we present an in silico developed RT-PCR based detection method (named OmMet) that was designed to be highly specific for the detection of the Omicron variant. Bioinformatic prediction tests demonstrate that the sequences in the primer sets are highly accurate, and do not match with genetic sequences of other viruses, including other coronaviruses or SARS-CoV-2 variants. The methodology presented does not rely on S-gene target failure (SGTF) of existing RT-PCR assays, widely used currently, but allows the direct specific identification of the variant B.1.1.529 (Omicron).

SUMMARY The frequent association between COVID-19 disease and different extrapulmonary clinical manifestations in symptomatic patients was reported recently. The data reported here suggest an association between COVID-19 disease and the release in the body of (oligo-)peptides almost identical to toxic components of venoms from animals. The presence of these peptides opens new scenarios on the aetiology of the COVID-19 clinical symptoms observed up to now, including neurological manifestations.

RATIONALE: SARS-CoV-2 virus that causes COVID-19 disease and led to the pandemic currently affecting the world has been broadly investigated. Different studies have been performed to understand the infection mechanism and the involved human genes, transcripts and proteins. In parallel, numerous clinical extra-pulmonary manifestations co-occurring with COVID-19 disease have been reported and evidence of their severity and persistence is increasing. Whether these manifestations are linked to other disorders co-occurring with SARS-CoV-2 infection, is under discussion. In this work, we report the identification of toxin-like peptides in COVID-19 patients by application of the SANIST-Cloud Ion Mobility Mass Spectrometry (SANIST-CIMS) technology. METHODS: Plasma, urine and faecal samples from COVID-19 patients and control individuals were analysed to study toxins profiles. SANIST-CIMS instrumental parameters were selected to discriminate the ion cloud containing low and high molecular weight compounds. SANIST-Disc module was employed to investigate the differentially expressed molecules. RESULTS: Toxin-like peptides, almost identical to toxic components of venoms from animals like conotoxins, phospholipase A2, phospholipase A1, activating prothrombotic factors, phosphodiesterases, zinc metal proteinases, and bradykinins, have been identified. As they were found only in samples from COVID-19 patients, their presence is considered somehow connected to SARS-CoV-2 infection. The presence of these peptides can potentially explain a large set of heterogeneous extra-pulmonary COVID-19 clinical manifestations, like myalgia, headache, encephalopathy, dizziness, dysgeusia, and anosmia. Even if the presence of each individual symptom is not selective of the disease, their combination could be related to COVID-19 in the presence of the panel of detected toxin-like peptides. CONCLUSIONS: The data reported here suggest an association between COVID-19 disease and the release in the body of (oligo-)peptides almost identical to toxic components of venoms from animals. The presence of these peptides opens new scenarios on the aetiology of the COVID-19 clinical symptoms observed up to now, including neurological manifestations., DECLARATION The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication.

This document presents the contributions discussed at the second institutional workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 05th July 2019 at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI and Big Data and share their experience, identify opportunities for meeting EC demands on AI, and explore synergies among the different JRC's working groups on AI. In comparison with the first event, according to the JRC Director General Vladimír Šuchav, the activities and results presented in this second workshop demonstrated a significant development of AI research and applications by JRC in different policy areas. He suggested to think about replicating the event at the premises of diverse policy DGs in order to present and discuss the clear opportunities created by JRC activities. After the opening speech by the JRC Director General Vladimír Šuchav, the research and innovation presentation were anticipated by two presentations by Alessandro Annoni and Stefano Nativi. The first presentation dealt with the results of one year of AI@JRC and six months of fully operational AI&BD community of practice1. The second presentation reported the results of the AI competences survey at JRC. The research and innovation contributions consisted in flash presentations (5 minutes) covering a wide range of areas. This report is structured according to the diverse domain areas addressed by the presenters. While the first part of the workshop was mainly informative, in the second part we collectively discussed about how to move on and evolve the AI&BD community of practice., JRC.B.6-Digital Economy

The COVID-19 pandemic event has shown how communicable diseases can spread faster and wider than ever before due to globalisation. The early detection of threats plays a crucial role to reduce their impact. It is essential to combine alert systems with contextual information for triggering adequate measures that may prevent or mitigate the risk in a timely manner. This report illustrates how early warning and rapid assessment activities can be supported by the systematic collection and analysis of publicly available information from official sources and the media., JRC.E.1-Disaster Risk Management

Additional file 1. Supplementary material.