ArticleFrontiers in neuroinformatics2024
A computational model of Alzheimer's disease at the nano, micro, and macroscales.
Article in Frontiers in neuroinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Alzheimer's Disease and MERC Dysfunction: Integrating Mechanisms, Biomarkers, and Therapeutic Strategies.Molecular neurobiology · 2026Review
- Neurosenescence, inflammaging and neuroinflammation in neurodegenerative disorders.Frontiers in aging · 2026Review
- Mechanistic modeling of amyloid dynamics relating to Alzheimer's disease progression.Frontiers in aging neuroscience · 2026Article
- Advancing Alzheimer's Therapy: Computational strategies and treatment innovations.IBRO neuroscience reports · 2025Review
- Research models to study lewy body dementia.Molecular neurodegeneration · 2025Review
- The role of IPFrontiers in computational neuroscience · 2025Article
- Sensitivity analysis of a mathematical model of Alzheimer's disease progression unveils important causal pathways.Frontiers in neuroinformatics · 2025Article
- Challenges and Future Perspectives in Modeling Neurodegenerative Diseases Using Organ-on-a-Chip Technology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Mathematical models play a crucial role in investigating complex biological systems, enabling a comprehensive understanding of interactions among various components and facilitating Methods: In this paper, we present a multiscale mathematical model that describes the progression of AD through a system of 19 ordinary differential equations. The equations describe the evolution of proteins (nanoscale), cell populations (microscale), and organ-level structures (macroscale) over a 50-year lifespan, as they relate to amyloid and tau accumulation, inflammation, and neuronal death. Results: Distinguishing our model is a robust foundation in biological principles, ensuring improved justification for the included equations, and rigorous parameter justification derived from published experimental literature. Conclusion: This model represents an essential initial step toward constructing a predictive framework, which holds significant potential for identifying effective therapeutic targets in the fight against AD.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.