Mathematical and computational approaches in understanding the immunobiology of granulomatous diseases

Magombedze, Gesham; Marino, Simeone

doi:10.1016/j.coisb.2018.07.002

Cited by 5 publications

(3 citation statements)

References 103 publications

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“…As for the signalling pathway of cytokine activation by the pathogen, processes involving the activation or inhibition of MMPs, in particular M 1 , have been considered (see Figure 1). 3,4) are in-and out-fluxes of the metabolites; α, β determine pathogen reproduction and depletion due to treatment; Mtb-pathogen population; M i (i = 1, 3, 8, 9)-matrix metalloproteinases/enzymes, involved in the destruction of lung tissue during the tuberculosis process; pM i (i = 1, 3, 8, 9)-pro-matrix metalloproteinases/enzymes, activating M i synthesis; TIMP-matrix metalloproteinase inhibitor; Cyt,TNF − α denote key metabolites of immune reactions; A and I define a pool of reactions that activate and inhibit the overexpression (oversynthesis) of matrix metalloproteinase-1 (pM 1 ).…”

Section: Model Statementmentioning

confidence: 99%

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Modelling of Interaction Dynamics of a Pathogen and Bio-Markers (Matrix Metalloproteinases) of Tissue Destruction in Pulmonary Tuberculosis

Lavrova,

Esmedljaeva,

Postnikov

2023

Mathematics

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Tuberculosis (TB) has a long history as a serious disease induced by its causative agent Mycobacterium tuberculosis. This pathogen manipulates the host’s immune response, thereby stimulating inflammatory processes, which leads to an even greater imbalance of specific enzymes/inhibitors that contribute to tissue destruction. This work addresses a model consisting of two ordinary differential equations obtained by reducing a previously developed large-scale model describing lung damage, taking into account key metabolic pathways controlled by bacteria. The resulting system is explored as a dynamical system simulating the interaction between bio-markers (matrix metalloproteinases) of tissue destruction and the pathogen. In addition to the analysis of the mathematical model’s features, we qualitatively compared the model dynamics with real clinical data and discussed their mutual correspondence.

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Section: Model Statementmentioning

confidence: 99%

“…A decade ago, the problem of exploring the host-pathogen interactions accompanying the development of tuberculosis was claimed as one of the crucial goals for exploration and modelling in this field [1]. Despite certain advances achieved during these years (see for review, e.g., [2][3][4][5]), the problem is far from a complete resolution.…”

Section: Introductionmentioning

confidence: 99%

Modelling of Interaction Dynamics of a Pathogen and Bio-Markers (Matrix Metalloproteinases) of Tissue Destruction in Pulmonary Tuberculosis

Lavrova,

Esmedljaeva,

Postnikov

2023

Mathematics

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“…The formation/evolution of the hepatic schistosomal granuloma is a non‐linear dynamic phenomenon (Lenzi et al ., 2006) that can be studied using mathematical modelling (Lenzi, Romanha & Pelago‐Machado, 2004) as has been done for granulomas induced by other pathogens (Hao, Crouser & Friedman, 2014; Siewe et al ., 2017; Magombedze & Marino, 2018). The Schistosoma granuloma evolves from an initial disordered phase (pre‐granulomatous stage) to a highly organized cellular assembly (granulomatous stage) (Fig.…”

Section: Colonization By the Cell Community During Granuloma Formation: An Ecological Successionmentioning

confidence: 99%

Changing our view of the Schistosoma granuloma to an ecological standpoint

et al. 2021

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Schistosomiasis, a neglected parasitic tropical disease that has plagued humans for centuries, remains a major public health burden. A primary challenge to understanding schistosomiasis is deciphering the most remarkable pathological feature of this disease, the granuloma – a highly dynamic and self‐organized structure formed by both host and parasite components. Granulomas are considered a remarkable example of how parasites evolved with their hosts to establish complex and intimate associations. However, much remains unclear regarding life within the granuloma, and strategies to restrain its development are still lacking. Here we explore current information on the hepatic Schistosoma mansoni granuloma in the light of Ecology and propose that this intricate structure acts as a real ecosystem. The schistosomal granuloma is formed by cells (biotic component), protein scaffolds, fibres, and chemical compounds (abiotic components) with inputs/outputs of energy and matter, as complex as in classical ecosystems. We review the distinct cell populations (‘species’) within the granuloma and examine how they integrate with each other and interact with their microenvironment to form a multifaceted cell community in different space–time frames. The colonization of the hepatic tissue to form granulomas is explained from the point of view of an ecological succession whereby a community is able to modify its physical environment, creating conditions and resources for ecosystem construction. Remarkably, the granuloma represents a dynamic evolutionary system that undergoes progressive changes in the ‘species’ that compose its community over time. In line with ecological concepts, we examine the granuloma not only as a place where a community of cells is settled (spatial niche or habitat) but also as a site in which the functional activities of these combined populations occur in an orchestrated way in response to microenvironmental gradients such as cytokines and egg antigens. Finally, we assert how the levels of organization of cellular components in a granuloma as conventionally defined by Cell Biology can fit perfectly into a hierarchical structure of biological systems as defined by Ecology. By rethinking the granuloma as an integrating and evolving ecosystem, we draw attention to the inner workings of this structure that are central to the understanding of schistosomiasis and could guide its future treatment.

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Deciphering the virulence of Mycobacterium avium subsp. paratuberculosis isolates in animal macrophages using mathematical models

Alonso‐Hearn

Magombedze

Abendaño

et al. 2019

Journal of Theoretical Biology

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Mathematical and computational approaches in understanding the immunobiology of granulomatous diseases

Cited by 5 publications

References 103 publications

Modelling of Interaction Dynamics of a Pathogen and Bio-Markers (Matrix Metalloproteinases) of Tissue Destruction in Pulmonary Tuberculosis

Modelling of Interaction Dynamics of a Pathogen and Bio-Markers (Matrix Metalloproteinases) of Tissue Destruction in Pulmonary Tuberculosis

Changing our view of the Schistosoma granuloma to an ecological standpoint

Deciphering the virulence of Mycobacterium avium subsp. paratuberculosis isolates in animal macrophages using mathematical models

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