ArticleBMC systems biology2019
How to prevent viremia rebound? Evidence from a PRRSv data-supported model of immune response.
Article in BMC systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- An Exploratory Pilot Study to Investigate the Potential Relationship Between Porcine Reproductive and Respiratory Syndrome (PRRS) Virus Viremia Changes and Barn Manure Pit Management Procedures.Pathogens (Basel, Switzerland) · 2026Article
- Full Factorial Comparison of the Diagnostic Performance of Three Nucleic Acid Extraction Kits and Three PRRSV RT-qPCR Assays Using Swine Oral Fluids of Known Status.Microorganisms · 2026Article
- Article
- Research perspectives on animal health in the era of artificial intelligence.Veterinary research · 2021Review
- Modelling infectious viral diseases in swine populations: a state of the art.Porcine health management · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundUnderstanding what determines the between-host variability in infection dynamics is a key issue to better control the infection spread. In particular, pathogen clearance is desirable over rebounds for the health of the infected individual and its contact group. In this context, the Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is of particular interest. Numerous studies have shown that pigs similarly infected with this highly ubiquitous virus elicit diverse response profiles. Whilst some manage to clear the virus within a few weeks, others experience prolonged infection with a rebound. Despite much speculation, the underlying mechanisms responsible for this undesirable rebound phenomenon remain unclear.
resultsWe aimed at identifying immune mechanisms that can reproduce and explain the rebound patterns observed in PRRSv infection using a mathematical modelling approach of the within-host dynamics. As diverse mechanisms were found to influence PRRSv infection, we established a model that details the major mechanisms and their regulations at the between-cell scale. We developed an ABC-like optimisation method to fit our model to an extensive set of experimental data, consisting of non-rebounder and rebounder viremia profiles. We compared, between both profiles, the estimated parameter values, the resulting immune dynamics and the efficacies of the underlying immune mechanisms. Exploring the influence of these mechanisms, we showed that rebound was promoted by high apoptosis, high cell infection and low cytolysis by Cytotoxic T Lymphocytes, while increasing neutralisation was very efficient to prevent rebounds.
conclusionsOur paper provides an original model of the immune response and an appropriate systematic fitting method, whose interest extends beyond PRRS infection. It gives the first mechanistic explanation for emergence of rebounds during PRRSv infection. Moreover, results suggest that vaccines or genetic selection promoting strong neutralising and cytolytic responses, ideally associated with low apoptotic activity and cell permissiveness, would prevent rebound.
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Registered trials
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