Researchers from the University of Coimbra (UC) carried out studies that can help with the early detection of thrombotic events in people, the higher education institution announced this Tuesday.
“A team of scientists from the Department of Physics of the Faculty of Science and Technology of the University of Coimbra (FCTUC) developed advanced computer simulations to model the shape and deformation of red blood cells under different flow and adhesion conditions“, the school reported in a statement sent to the Lusa agency.
Within the scope of the project, led by the Institute of Molecular Medicine (iMM), “Experts are studying increased blood viscosity, often associated with elevated levels of the protein fibrinogen.”.
This protein “plays a crucial role in the connection between red blood cells, increasing their adhesion, which can aggravate several clinical conditions.”
“The team is analyze the concentration of fibrinogen in patients with different levels of pathology and relate these levels to the adhesion of red blood cellsusing an advanced set of experimental techniques,” said Professor Rui Travasso.
Cited in the note, the researcher from the UC Physics Center explained that the ongoing work aims to “create a computational model that simulates different interactions between red blood cells, allowing a rigorous comparison with the experimental results” obtained by the iMM.
“The tests carried out so far indicate that, in the presence of higher concentrations of fibrinogen, red blood cells show greater adhesion. With the support of ‘machine learning’ and image processing techniques, we were able to automatically identify changes in the shape of red blood cells before and after the collision between them, establishing correlations between simulations and experimental data,” explained the physicist responsible for the research at UC.
The next step will be “the creation of an extensive database that integrates both computational simulations and laboratory experiments.”
“This database will allow for more robust quantitative analysis and classification of changes in red blood cells in an automated manner. In addition, a tool based on machine learning is being developed to identify the shocks most representative of the changes observed experimentally,” he added.
With “Promising preliminary results”, the long-term goal of the project “is to obtain a deeper understanding of the adhesion and deformation processes of red blood cells in various pathologies“, reinforcing scientific knowledge and “the development of potential therapeutic interventions.”
Source: Observadora
