ArticlePloS one2017
Exploring virus release as a bottleneck for the spread of influenza A virus infection in vitro and the implications for antiviral therapy with neuraminidase inhibitors.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Pathogen virulence genes: Advances, challenges and future directions in infectious disease research (Review).International journal of molecular medicine · 2025Review
- Review
- Potential roles of medicinal plants for the treatment of viral diseases focusing on COVID-19: A review.Phytotherapy research : PTR · 2021Review
- A mathematical model describing the localization and spread of influenza A virus infection within the human respiratory tract.PLoS computational biology · 2020Article
- Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions.PLoS computational biology · 2019Article
- Host-pathogen kinetics during influenza infection and coinfection: insights from predictive modeling.Immunological reviews · 2018Review
- Investigating Different Mechanisms of Action in Combination Therapy for Influenza.Frontiers in pharmacology · 2018Article
- Inhibition of sialidase activity as a therapeutic approach.Drug design, development and therapy · 2018Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mathematical models (MMs) have been used to study the kinetics of influenza A virus infections under antiviral therapy, and to characterize the efficacy of antivirals such as neuraminidase inhibitors (NAIs). NAIs prevent viral neuraminidase from cleaving sialic acid receptors that bind virus progeny to the surface of infected cells, thereby inhibiting their release, suppressing infection spread. When used to study treatment with NAIs, MMs represent viral release implicitly as part of viral replication. Consequently, NAIs in such MMs do not act specifically and exclusively on virus release. We compared a MM with an explicit representation of viral release (i.e., distinct from virus production) to a simple MM without explicit release, and investigated whether parameter estimation and the estimation of NAI efficacy were affected by the use of a simple MM. Since the release rate of influenza A virus is not well-known, a broad range of release rates were considered. If the virus release rate is greater than ∼0.1 h-1, the simple MM provides accurate estimates of infection parameters, but underestimates NAI efficacy, which could lead to underdosing and the emergence of NAI resistance. In contrast, when release is slower than ∼0.1 h-1, the simple MM accurately estimates NAI efficacy, but it can significantly overestimate the infectious lifespan (i.e., the time a cell remains infectious and producing free virus), and it will significantly underestimate the total virus yield and thus the likelihood of resistance emergence. We discuss the properties of, and a possible lower bound for, the influenza A virus release rate.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.