ArticlePloS one2016
Modeling Granulomas in Response to Infection in the Lung.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Article
- Mathematical model of oxygen, nutrient, and drug transport in tuberculosis granulomas.PLoS computational biology · 2024Article
- A brief overview of mathematical modeling of the within-host dynamics of Mycobacterium tuberculosis.Frontiers in applied mathematics and statistics · 2024Article
- Within-Host Mathematical Models of Antibiotic Resistance.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Modulation of TDM-induced granuloma pathology by human lactoferrin: a persistent effect in mice.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2023Article
- Human M1 macrophages express unique innate immune response genes after mycobacterial infection to defend against tuberculosis.Communications biology · 2022Article
- Micro-Computed Tomography Analysis of the Human Tuberculous Lung Reveals Remarkable Heterogeneity in Three-dimensional Granuloma Morphology.American journal of respiratory and critical care medicine · 2021Article
- The Pathogenesis of Tuberculosis-The Koch Phenomenon Reinstated.Pathogens (Basel, Switzerland) · 2020Review
- VapBC22 toxin-antitoxin system fromScience advances · 2020Article
- A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination.PLoS computational biology · 2020Article
- Analysis of a mathematical model of rheumatoid arthritis.Journal of mathematical biology · 2020Article
- Modelling the dynamics of tuberculosis lesions in a virtual lung: Role of the bronchial tree in endogenous reinfection.PLoS computational biology · 2020Article
- A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development.Integrative biology : quantitative biosciences from nano to macro · 2020Article
- Mycobacterial Trehalose 6,6'-Dimycolate-Induced M1-Type Inflammation.The American journal of pathology · 2020Article
- A reaction-diffusion model to understand granulomas formation inside secondary lobule during tuberculosis infection.PloS one · 2020Article
- Modeling Macrophage Polarization and Its Effect on Cancer Treatment Success.Open journal of immunology · 2018Article
- Mathematical Modeling of Tuberculosis Granuloma Activation.Processes (Basel, Switzerland) · 2017Article
- Combination therapy for melanoma with BRAF/MEK inhibitor and immune checkpoint inhibitor: a mathematical model.BMC systems biology · 2017Article
- A review of computational and mathematical modeling contributions to our understanding of Mycobacterium tuberculosis within-host infection and treatment.Current opinion in systems biology · 2017Article
- Combination therapy of cancer with cancer vaccine and immune checkpoint inhibitors: A mathematical model.PloS one · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Alveolar macrophages play a large role in the innate immune response of the lung. However, when these highly immune-regulatory cells are unable to eradicate pathogens, the adaptive immune system, which includes activated macrophages and lymphocytes, particularly T cells, is called upon to control the pathogens. This collection of immune cells surrounds, isolates and quarantines the pathogen, forming a small tissue structure called a granuloma for intracellular pathogens like Mycobacterium tuberculosis (Mtb). In the present work we develop a mathematical model of the dynamics of a granuloma by a system of partial differential equations. The 'strength' of the adaptive immune response to infection in the lung is represented by a parameter α, the flux rate by which T cells and M1 macrophages that immigrated from the lymph nodes enter into the granuloma through its boundary. The parameter α is negatively correlated with the 'switching time', namely, the time it takes for the number of M1 type macrophages to surpass the number of infected, M2 type alveolar macrophages. Simulations of the model show that as α increases the radius of the granuloma and bacterial load in the granuloma both decrease. The model is used to determine the efficacy of potential host-directed therapies in terms of the parameter α, suggesting that, with fixed dosing level, an infected individual with a stronger immune response will receive greater benefits in terms of reducing the bacterial load.
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