ArticlePLoS computational biology2019
Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 44 citations in OpenAlex.
- Article
- Stochastic intracellular replication dynamics shape population-level evolution in Influenza A Virus.Virus evolution · 2026Article
- PulmonaromFrontiers in cellular and infection microbiology · 2026Article
- Article
- A dominant role of cell death in limiting Chandipura virus propagation at cell-saturating high multiplicity of infection.bioRxiv : the preprint server for biology · 2025Article
- Continuous Production of Influenza VLPs Using IC-BEVS and Multi-Stage Bioreactors.Biotechnology and bioengineering · 2025Article
- Quantification of intracellular influenza A virus protein dynamics in different host cells after seed virus adaptation.Applied microbiology and biotechnology · 2025Article
- Quantitative analysis of proteomic changes in two monoclonal suspension MDCK cell lines infected with human influenza A virus (H1N1).PloS one · 2025Article
- Innovations in cell culture-based influenza vaccine manufacturing - from static cultures to high cell density cultivations.Human vaccines & immunotherapeutics · 2024Review
- Parallel Multifactorial Process Optimization and Intensification for High-Yield Production of Live YF17D-Vectored Zika Vaccine.Vaccines · 2024Article
- Mathematical model calibrated toiScience · 2024Article
- Generation of "OP7 chimera" defective interfering influenza A particle preparations free of infectious virus that show antiviral efficacy in mice.Scientific reports · 2023Article
- Multiscale Asymptotic Analysis Reveals How Cell Growth and Subcellular Compartments Affect Tissue-Scale Hormone Transport.Bulletin of mathematical biology · 2023Article
- Article
- Article
- Impact of Influenza A Virus Infection on Growth and Metabolism of Suspension MDCK Cells Using a Dynamic Model.Metabolites · 2022Article
- Uncovering viral RNA-host cell interactions on a proteome-wide scale.Trends in biochemical sciences · 2022Review
- Altered gene expression in human brain microvascular endothelial cells in response to the infection of influenza H1N1 virus.Animal diseases · 2022Article
- Influenza A virus NS1 protein represses antiviral immune response by hijacking NF-κB to mediate transcription of type III IFN.Frontiers in cellular and infection microbiology · 2022Article
- The evolution of cheating in viruses.Nature communications · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mathematical models of IAV replication have paid little attention to the impact of the MOI on infection dynamics and virus yields. To address this issue, we extended an existing model of IAV replication in adherent MDCK cells with kinetics that explicitly consider the time point of cell infection. This modification does not only enable the fitting of high MOI measurements, but also the successful prediction of viral release dynamics of low MOI experiments using the same set of parameters. Furthermore, this model allows the investigation of defective interfering particle (DIP) propagation in different MOI regimes. The key difference between high and low MOI conditions is the percentage of infectious virions among the total virus particle release. Simulation studies show that DIP interference at a high MOI is determined exclusively by the DIP content of the seed virus while, in low MOI conditions, it is predominantly controlled by the de novo generation of DIPs. Overall, the extended model provides an ideal framework for the prediction and optimization of cell culture-derived IAV manufacturing and the production of DIPs for therapeutic use.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.