Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent
Abstract Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by excessive scarring and fibrosis due to the abnormal accumulation of extracellular matrix components, primarily collagen. This study aims to design and solve an optimal control problem to regulate M2 macrophage ac...
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-76561-0 |
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| author | Fatemeh Bahram Yazdroudi Alaeddin Malek |
| author_facet | Fatemeh Bahram Yazdroudi Alaeddin Malek |
| author_sort | Fatemeh Bahram Yazdroudi |
| collection | DOAJ |
| description | Abstract Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by excessive scarring and fibrosis due to the abnormal accumulation of extracellular matrix components, primarily collagen. This study aims to design and solve an optimal control problem to regulate M2 macrophage activity in IPF, thereby preventing fibrosis formation by controlling the anti-M1 agent. The research models the diffusion of M2 macrophages in inflamed tissue using a novel dynamical system with partial differential equation (PDE) constraints. The control problem is formulated to minimize fibrosis by regulating an anti-M1 agent. The study employs a two-step process of discretization followed by optimization, utilizing the Galerkin spectral method to transform the M2 diffusion PDE into an algebraic system of ordinary differential equations (ODEs). The optimal control problem is then solved using Pontryagin/s minimum principle, canonical Hamiltonian equations, and extended Riccati differential equations. The numerical simulations indicate that without control, M2 macrophage levels increase and stabilize, contributing to fibrosis. In contrast, the optimal control strategy effectively reduces M2 macrophages, preventing fibrosis formation within 120 days. The results highlight the potential of the proposed optimal control approach in modulating tissue repair processes and mitigating the progression of IPF. This study underscores the significance of targeting M2 macrophages and employing mathematical methods to develop innovative therapies for lung fibrosis. |
| format | Article |
| id | doaj-art-757f1c0456fc469882dfe2fe9dc0604d |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-757f1c0456fc469882dfe2fe9dc0604d2025-02-09T12:37:51ZengNature PortfolioScientific Reports2045-23222025-02-0115112510.1038/s41598-024-76561-0Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agentFatemeh Bahram Yazdroudi0Alaeddin Malek1Department of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares UniversityDepartment of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares UniversityAbstract Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by excessive scarring and fibrosis due to the abnormal accumulation of extracellular matrix components, primarily collagen. This study aims to design and solve an optimal control problem to regulate M2 macrophage activity in IPF, thereby preventing fibrosis formation by controlling the anti-M1 agent. The research models the diffusion of M2 macrophages in inflamed tissue using a novel dynamical system with partial differential equation (PDE) constraints. The control problem is formulated to minimize fibrosis by regulating an anti-M1 agent. The study employs a two-step process of discretization followed by optimization, utilizing the Galerkin spectral method to transform the M2 diffusion PDE into an algebraic system of ordinary differential equations (ODEs). The optimal control problem is then solved using Pontryagin/s minimum principle, canonical Hamiltonian equations, and extended Riccati differential equations. The numerical simulations indicate that without control, M2 macrophage levels increase and stabilize, contributing to fibrosis. In contrast, the optimal control strategy effectively reduces M2 macrophages, preventing fibrosis formation within 120 days. The results highlight the potential of the proposed optimal control approach in modulating tissue repair processes and mitigating the progression of IPF. This study underscores the significance of targeting M2 macrophages and employing mathematical methods to develop innovative therapies for lung fibrosis.https://doi.org/10.1038/s41598-024-76561-0Anti-M1 agentCanonical HamiltonianDiffusion equationDynamical systemExtended Riccati equationsLung fibrosis |
| spellingShingle | Fatemeh Bahram Yazdroudi Alaeddin Malek Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent Scientific Reports Anti-M1 agent Canonical Hamiltonian Diffusion equation Dynamical system Extended Riccati equations Lung fibrosis |
| title | Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent |
| title_full | Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent |
| title_fullStr | Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent |
| title_full_unstemmed | Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent |
| title_short | Reducing M2 macrophage in lung fibrosis by controlling anti-M1 agent |
| title_sort | reducing m2 macrophage in lung fibrosis by controlling anti m1 agent |
| topic | Anti-M1 agent Canonical Hamiltonian Diffusion equation Dynamical system Extended Riccati equations Lung fibrosis |
| url | https://doi.org/10.1038/s41598-024-76561-0 |
| work_keys_str_mv | AT fatemehbahramyazdroudi reducingm2macrophageinlungfibrosisbycontrollingantim1agent AT alaeddinmalek reducingm2macrophageinlungfibrosisbycontrollingantim1agent |