Literature DB >> 25843213

The inflammatory response to influenza A virus (H1N1): An experimental and mathematical study.

Ian Price1, Ericka D Mochan-Keef2, David Swigon3, G Bard Ermentrout3, Sarah Lukens4, Franklin R Toapanta5, Ted M Ross5, Gilles Clermont6.   

Abstract

Mortality from influenza infections continues as a global public health issue, with the host inflammatory response contributing to fatalities related to the primary infection. Based on Ordinary Differential Equation (ODE) formalism, a computational model was developed for the in-host response to influenza A virus, merging inflammatory, innate, adaptive and humoral responses to virus and linking severity of infection, the inflammatory response, and mortality. The model was calibrated using dense cytokine and cell data from adult BALB/c mice infected with the H1N1 influenza strain A/PR/8/34 in sublethal and lethal doses. Uncertainty in model parameters and disease mechanisms was quantified using Bayesian inference and ensemble model methodology that generates probabilistic predictions of survival, defined as viral clearance and recovery of the respiratory epithelium. The ensemble recovers the expected relationship between magnitude of viral exposure and the duration of survival, and suggests mechanisms primarily responsible for survival, which could guide the development of immuno-modulatory interventions as adjuncts to current anti-viral treatments. The model is employed to extrapolate from available data survival curves for the population and their dependence on initial viral aliquot. In addition, the model allows us to illustrate the positive effect of controlled inflammation on influenza survival.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian inference; Immune response; Inflammation; Mathematical model; Survival curve

Mesh:

Substances:

Year:  2015        PMID: 25843213      PMCID: PMC4426089          DOI: 10.1016/j.jtbi.2015.03.017

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  49 in total

1.  An ensemble method for identifying regulatory circuits with special reference to the qa gene cluster of Neurospora crassa.

Authors:  D Battogtokh; D K Asch; M E Case; J Arnold; H-B Schuttler
Journal:  Proc Natl Acad Sci U S A       Date:  2002-12-11       Impact factor: 11.205

2.  A reduced mathematical model of the acute inflammatory response II. Capturing scenarios of repeated endotoxin administration.

Authors:  Judy Day; Jonathan Rubin; Yoram Vodovotz; Carson C Chow; Angela Reynolds; Gilles Clermont
Journal:  J Theor Biol       Date:  2006-04-17       Impact factor: 2.691

3.  A reduced mathematical model of the acute inflammatory response: I. Derivation of model and analysis of anti-inflammation.

Authors:  Angela Reynolds; Jonathan Rubin; Gilles Clermont; Judy Day; Yoram Vodovotz; G Bard Ermentrout
Journal:  J Theor Biol       Date:  2006-04-03       Impact factor: 2.691

4.  Towards a quantitative understanding of the within-host dynamics of influenza A infections.

Authors:  Andreas Handel; Ira M Longini; Rustom Antia
Journal:  J R Soc Interface       Date:  2009-05-27       Impact factor: 4.118

Review 5.  Influenza A virus infection kinetics: quantitative data and models.

Authors:  Amber M Smith; Alan S Perelson
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010-12-31

Review 6.  Respiratory epithelial cells in innate immunity to influenza virus infection.

Authors:  Catherine J Sanders; Peter C Doherty; Paul G Thomas
Journal:  Cell Tissue Res       Date:  2010-09-17       Impact factor: 5.249

7.  A dynamical model of human immune response to influenza A virus infection.

Authors:  Baris Hancioglu; David Swigon; Gilles Clermont
Journal:  J Theor Biol       Date:  2006-12-19       Impact factor: 2.691

8.  Fewer CTL, not enhanced NK cells, are sufficient for viral clearance from the lungs of immunocompromised mice.

Authors:  Haley D Neff-LaFord; Beth A Vorderstrasse; B Paige Lawrence
Journal:  Cell Immunol       Date:  2003-11       Impact factor: 4.868

9.  Effects of aging on influenza virus infection dynamics.

Authors:  Esteban A Hernandez-Vargas; Esther Wilk; Laetitia Canini; Franklin R Toapanta; Sebastian C Binder; Alexey Uvarovskii; Ted M Ross; Carlos A Guzmán; Alan S Perelson; Michael Meyer-Hermann
Journal:  J Virol       Date:  2014-01-29       Impact factor: 5.103

10.  Assessing mathematical models of influenza infections using features of the immune response.

Authors:  Hana M Dobrovolny; Micaela B Reddy; Mohamed A Kamal; Craig R Rayner; Catherine A A Beauchemin
Journal:  PLoS One       Date:  2013-02-28       Impact factor: 3.240

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  20 in total

1.  A spatial model of the efficiency of T cell search in the influenza-infected lung.

Authors:  Drew Levin; Stephanie Forrest; Soumya Banerjee; Candice Clay; Judy Cannon; Melanie Moses; Frederick Koster
Journal:  J Theor Biol       Date:  2016-02-23       Impact factor: 2.691

2.  CD33 is downregulated by influenza virus H1N1pdm09 and induces ROS and the TNF-α, IL-1β, and IL-6 cytokines in human mononuclear cells.

Authors:  Silvia Guzmán-Beltrán; Maria Teresa Herrera; Martha Torres; Yolanda Gonzalez
Journal:  Braz J Microbiol       Date:  2022-01-24       Impact factor: 2.476

3.  Discrete Dynamical Modeling of Influenza Virus Infection Suggests Age-Dependent Differences in Immunity.

Authors:  Ericka Keef; Li Ang Zhang; David Swigon; Alisa Urbano; G Bard Ermentrout; Michael Matuszewski; Franklin R Toapanta; Ted M Ross; Robert S Parker; Gilles Clermont
Journal:  J Virol       Date:  2017-11-14       Impact factor: 5.103

4.  Compartmental Model Suggests Importance of Innate Immune Response to COVID-19 Infection in Rhesus Macaques.

Authors:  Ericka Mochan; T J Sego; Lauren Gaona; Emmaline Rial; G Bard Ermentrout
Journal:  Bull Math Biol       Date:  2021-05-26       Impact factor: 1.758

Review 5.  Modeling Influenza Virus Infection: A Roadmap for Influenza Research.

Authors:  Alessandro Boianelli; Van Kinh Nguyen; Thomas Ebensen; Kai Schulze; Esther Wilk; Niharika Sharma; Sabine Stegemann-Koniszewski; Dunja Bruder; Franklin R Toapanta; Carlos A Guzmán; Michael Meyer-Hermann; Esteban A Hernandez-Vargas
Journal:  Viruses       Date:  2015-10-12       Impact factor: 5.048

6.  A comparison of RSV and influenza in vitro kinetic parameters reveals differences in infecting time.

Authors:  Gilberto Gonzàlez-Parra; Filip De Ridder; Dymphy Huntjens; Dirk Roymans; Gabriela Ispas; Hana M Dobrovolny
Journal:  PLoS One       Date:  2018-02-08       Impact factor: 3.240

Review 7.  Host-pathogen kinetics during influenza infection and coinfection: insights from predictive modeling.

Authors:  Amber M Smith
Journal:  Immunol Rev       Date:  2018-09       Impact factor: 12.988

8.  Investigating Different Mechanisms of Action in Combination Therapy for Influenza.

Authors:  Kelli Melville; Thalia Rodriguez; Hana M Dobrovolny
Journal:  Front Pharmacol       Date:  2018-10-23       Impact factor: 5.810

9.  In-host modeling.

Authors:  Stanca M Ciupe; Jane M Heffernan
Journal:  Infect Dis Model       Date:  2017-04-29

10.  Modelling the linkage between influenza infection and cardiovascular events via thrombosis.

Authors:  Zachary McCarthy; Shixin Xu; Ashrafur Rahman; Nicola Luigi Bragazzi; Vicente F Corrales-Medina; Jason Lee; Bruce T Seet; Dion Neame; Edward Thommes; Jane Heffernan; Ayman Chit; Jianhong Wu
Journal:  Sci Rep       Date:  2020-08-31       Impact factor: 4.379

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