ABSTRACT
From a cognitive linguistics perspective it is widely known that well known conceptual domains are used to explain complex or emerging concepts. As of recent, in the context of the Coronavirus pandemic, a wider usage of metaphors has been noticed in various public discourses. This paper aims to explore the most common metaphorical expressions used in the Albanian public discourse from the period of March 2020 until June 2020, in official political statements and media reports. It draws on the concepts of discourse metaphors and metaphor scenarios. The findings suggest that the pandemic in Albania is mostly framed in terms of WAR, NATURAL DISASTER and JOURNEY. However, even though these metaphors are used within the pandemic context they are not specific to Covid-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
BACKGROUND: Omics data, driven by rapid advances in laboratory techniques, have been generated very quickly during the COVID-19 pandemic. Our aim is to use omics data to highlight the involvement of specific pathways, as well as that of cell types and organs, in the pathophysiology of COVID-19, and to highlight their links with clinical phenotypes of SARS-CoV-2 infection. METHODS: The analysis was based on the domain model, where for domain it is intended a conceptual repository, useful to summarize multiple biological pathways involved at different levels. The relevant domains considered in the analysis were: virus, pathways and phenotypes. An interdisciplinary expert working group was defined for each domain, to carry out an independent literature scoping review. RESULTS: The analysis revealed that dysregulated pathways of innate immune responses, (i.e., complement activation, inflammatory responses, neutrophil activation and degranulation, platelet degranulation) can affect COVID-19 progression and outcomes. These results are consistent with several clinical studies. CONCLUSIONS: Multi-omics approach may help to further investigate unknown aspects of the disease. However, the disease mechanisms are too complex to be explained by a single molecular signature and it is necessary to consider an integrated approach to identify hallmarks of severity.