Explore the words cloud of the OPTIMISE project. It provides you a very rough idea of what is the project "OPTIMISE" about.
The following table provides information about the project.
THE QUEEN'S UNIVERSITY OF BELFAST
|Coordinator Country||United Kingdom [UK]|
|Total cost||212˙933 €|
|EC max contribution||212˙933 € (100%)|
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
|Duration (year-month-day)||from 2019-08-01 to 2021-07-31|
Take a look of project's partnership.
|1||THE QUEEN'S UNIVERSITY OF BELFAST||UK (BELFAST)||coordinator||212˙933.00|
Aging populations and the increasing use of immune modulatory medical treatments have given rise to a growing incidence of opportunistic infections. Legionella species are Gram-negative environmental bacteria, which after accidental inhalation can cause respiratory infections with symptoms reaching from a mild flu to a severe pneumonia, called Legionnaires’ disease. Disease progression, i.e. clearance or exacerbation of infection, is determined by the immune status of the host and acute pneumonia usually associated with immune suppression and/or underlying pulmonary conditions, but the molecular mechanisms enhancing susceptibility are poorly understood. The infection biology of Legionella has been studied mostly in cellular infection models and mice, which do not develop human-like disease. As patients typically present only at late stages of infection, it is unclear to which extent findings from these models reflect the early processes which occur in the human lung during infection and how these drive the clinical outcomes. Similarly, these models fail to explain, why L. pneumophila serogroup 1 strains are the predominant cause of more than 90% of Legionnaires’ disease cases. In this project I, the applicant Dr. Flavia Viana, will tackle these knowledge gaps by establishing and using human precision cut lung tissue slices (hPCLS) and excorporeal perfused whole human lungs (Ex vivo lung perfusion (EVLP)) as infection models for Legionella. I will determine if and how virulence of different Legionella isolates in these models correlates with their relevance in the clinical practice, analyse the transcriptional responses of all cell types in the infected human tissue using single cell transcriptomics and employ histology, state-of-the-art confocal and light sheet live microscopy, to visualise infection dynamics and host responses, providing unprecedented insight into the molecular events leading to the development of Legionnaires’ disease.
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The information about "OPTIMISE" are provided by the European Opendata Portal: CORDIS opendata.
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