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Development of a Computational Model of Abscess Formation.
Pigozzo, Alexandre B; Missiakas, Dominique; Alonso, Sergio; Dos Santos, Rodrigo W; Lobosco, Marcelo.
Affiliation
  • Pigozzo AB; Department of Computer Science, Federal University of São João Del-Rei, São João Del-Rei, Brazil.
  • Missiakas D; Department of Microbiology, University of Chicago, Chicago, IL, United States.
  • Alonso S; Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
  • Dos Santos RW; Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
  • Lobosco M; Graduate Program in Computational Modeling, Federal University of Juiz de Fora, Juiz de Fora, Brazil.
Front Microbiol ; 9: 1355, 2018.
Article in En | MEDLINE | ID: mdl-29997587
ABSTRACT
In some bacterial infections, the immune system cannot eliminate the invading pathogen. In these cases, the invading pathogen is successful in establishing a favorable environment to survive and persist in the host organism. For example, S. aureus bacteria survive in organ tissues employing a set of mechanisms that work in a coordinated and highly regulated way allowing (1) efficient impairment of the immune response; and (2) protection from the immune cells and molecules. S. aureus secretes several proteins including coagulases and toxins that drive abscess formation and persistence. Unless staphylococcal abscesses are surgically drained and treated with antibiotics, disseminated infection and septicemia produce a lethal outcome. Within this context, this paper develops a simple mathematical model of abscess formation incorporating characteristics that we judge important for an abscess to be formed. Our aim is to build a mathematical model that reproduces some characteristics and behaviors that are observed in the process of abscess formation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Microbiol Year: 2018 Document type: Article Affiliation country: Brasil

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Microbiol Year: 2018 Document type: Article Affiliation country: Brasil