ArticleNPJ systems biology and applications2024
Mathematical model of the inflammatory response to acute and prolonged lipopolysaccharide exposure in humans.
Article in NPJ systems biology and applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Combining machine learning and physiological network models for sepsis prediction.Frontiers in network physiology · 2026Article
- When to initiate immunomodulatory therapy in sepsis.Frontiers in immunology · 2026Review
- Dynamic nomogram predicts sepsis risk in patients with acute liver failure: Analysis of intensive care database with external validation.World journal of gastroenterology · 2025Article
- Supramolecular Detoxification Approach of Endotoxin Through Host-Guest Complexation by a Giant Macrocycle.Molecules (Basel, Switzerland) · 2025Article
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Authors and funding
6 authors.
Funding
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Abstract
One in five deaths worldwide is associated with sepsis, which is defined as organ dysfunction caused by a dysregulated host response to infection. An increased understanding of the pathophysiology of sepsis could provide improved approaches for early detection and treatment. Here we describe the development and validation of a mechanistic mathematical model of the inflammatory response, making use of a combination of in vitro and human in vivo data obtained from experiments where bacterial lipopolysaccharide (LPS) was used to induce an inflammatory response. The new model can simulate the responses to both acute and prolonged inflammatory stimuli in an experimental setting, as well as the response to infection in the clinical setting. This model serves as a foundation for a sepsis simulation model with a potentially wide range of applications in different disciplines involved with sepsis research.
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