Hillmann, Andreas ORCID: 0000-0002-6517-1615, Crane, Martin ORCID: 0000-0001-7598-3126 and Ruskin, Heather J. ORCID: 0000-0001-7101-2242 (2020) Assessing the impact of HIV treatment interruptions using stochastic cellular automata. Journal of Theoretical Biology, 502 . ISSN 0022-5193
Abstract
Chronic HIV infection causes a progressive decrease in the ability to maintain homeostasis resulting, after some time, in eventual break down of immune functions. Recent clinical research has shed light on a significant contribution of the lymphatic tissues, where HIV causes accumulation of collagen, (fibrosis). Specifically, where tissue is populated by certain types of functional stromal cells designated Fibroblastic Reticular Cells (FRCs), these have been found to play a crucial role in balancing out apoptosis and regeneration of naïve T-cells through 2-way cellular signaling. Tissue fibrosis not only impedes this signaling, effectively reducing T-cell levels through increased apoptosis of cells of both T- and FRC type but has been found to be irreversible by current HIV standard treatment (cART). While the therapy aims to block the viral lifecycle, cART-associated increase of T-cell levels in blood appears to conceal existing FRC impairment through fibrosis. This hidden impairment can lead to adverse consequences if treatment is interrupted, e.g. due to poor adherence (missing doses) or through periods recovering from drug toxicities. Formal clinical studies on treatment interruption have indicated possible adverse effects, but quantification of those effects in relation to interruption protocol and patient predisposition remains unclear. Accordingly, the impact of treatment interruption on lymphatic tissue structure and T-cell levels is explored here by means of computer simulation. A novel Stochastic Cellular Automata model is proposed, which utilizes all sources of clinical detail available to us (though sparse in part) for model parametrization. Sources are explicitly referenced and conflicting evidence from previous studies explored. The main focus is on (i) spatial aspects of collagen build up, together with (ii) collagen increase after repeated treatment interruptions to explore the dynamics of HIV-induced fibrosis and T-cell loss.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Additional Information: | Article number: 110376 |
Uncontrolled Keywords: | Cellular automata; Modeling; Tissue; Disease; Treatment interruption |
Subjects: | Medical Sciences > Biomechanics Medical Sciences > Diseases |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > Scientific Computing and Complex Systems Modelling (Sci-Sym) |
Publisher: | Elsevier |
Official URL: | https://dx.doi.org/10.1016/j.jtbi.2020.110376 |
Copyright Information: | © 2020 The Authors. Open Access (CC-BY 4.0) |
ID Code: | 27486 |
Deposited On: | 04 Aug 2022 14:20 by Thomas Murtagh . Last Modified 04 Aug 2022 14:20 |
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