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The Use of Interdisciplinary Approaches to Understand the Biology of Campylobacter jejuni.
Dzianach, Paulina A; Pérez-Reche, Francisco J; Strachan, Norval J C; Forbes, Ken J; Dykes, Gary A.
Afiliação
  • Dzianach PA; Geospatial Health and Development, Telethon Kids Institute, Perth 6009, Australia.
  • Pérez-Reche FJ; School of Natural and Computing Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK.
  • Strachan NJC; School of Natural and Computing Sciences, University of Aberdeen, Aberdeen AB24 3FX, UK.
  • Forbes KJ; School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen AB24 3FX, UK.
  • Dykes GA; School of Agriculture and Food Sciences, University of Queensland, Brisbane 4072, Australia.
Microorganisms ; 10(12)2022 Dec 16.
Article em En | MEDLINE | ID: mdl-36557751
ABSTRACT
Campylobacter jejuni is a bacterial pathogen recognised as a major cause of foodborne illness worldwide. While Campylobacter jejuni generally does not grow outside its host, it can survive outside of the host long enough to pose a health concern. This review presents an up-to-date description and evaluation of biological, mathematical, and statistical approaches used to understand the behaviour of this foodborne pathogen and suggests future avenues which can be explored. Specifically, the incorporation of mathematical modelling may aid the understanding of C. jejuni biofilm formation both outside and inside the host. Predictive studies may be improved by the introduction of more standardised protocols for assessments of disinfection methods and by assessment of novel physical disinfection strategies as well as assessment of the efficiency of plant extracts on C. jejuni eradication. A full description of the metabolic pathways of C. jejuni, which is needed for the successful application of metabolic models, is yet to be achieved. Finally, a shift from animal models (except for those that are a source of human campylobacteriosis) to human-specific data may be made possible due to recent technological advancements, and this may lead to more accurate predictions of human infections.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article