ArticleCritical care medicine2012
A two-compartment mathematical model of endotoxin-induced inflammatory and physiologic alterations in swine.
Article in Critical care medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
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- The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation.Frontiers in immunology · 2021Article
- Computational Derivation of Core, Dynamic Human Blunt Trauma Inflammatory Endotypes.Frontiers in immunology · 2020Article
- Inhibition of gap junction composed of Cx43 prevents against acute kidney injury following liver transplantation.Cell death & disease · 2019Article
- Cytokine patterns in critically ill patients undergoing percutaneous tracheostomy.Clinical and experimental immunology · 2019Article
- Article
- Inflammation and Disease: Modelling and Modulation of the Inflammatory Response to Alleviate Critical Illness.Current opinion in systems biology · 2018Article
- A computational analysis of dynamic, multi-organ inflammatory crosstalk induced by endotoxin in mice.PLoS computational biology · 2018Article
- A System Dynamics Model to Predict the Human Monocyte Response to Endotoxins.Frontiers in immunology · 2017Article
- "Thinking" vs. "Talking": Differential Autocrine Inflammatory Networks in Isolated Primary Hepatic Stellate Cells and Hepatocytes under Hypoxic Stress.Frontiers in physiology · 2017Article
- Individual-specific principal component analysis of circulating inflammatory mediators predicts early organ dysfunction in trauma patients.Journal of critical care · 2016Article
- Effectiveness of Multiple Blood-Cleansing Interventions in Sepsis, Characterized in Rats.Scientific reports · 2016Article
- Reverse Engineering the Inflammatory "Clock": From Computational Modeling to Rational Resetting.Drug discovery today. Disease models · 2016Article
- Inflammation Following Traumatic Brain Injury in Humans: Insights from Data-Driven and Mechanistic Models into Survival and Death.Frontiers in pharmacology · 2016Article
- Modeling and Hemofiltration Treatment of Acute Inflammation.Processes (Basel, Switzerland) · 2016Article
- A Biomathematical Model of Pneumococcal Lung Infection and Antibiotic Treatment in Mice.PloS one · 2016Article
- Insights into the Role of Chemokines, Damage-Associated Molecular Patterns, and Lymphocyte-Derived Mediators from Computational Models of Trauma-Induced Inflammation.Antioxidants & redox signaling · 2015Review
- Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response.PLoS computational biology · 2015Article
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16 authors.
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Abstract
objectiveTo gain insights into individual variations in acute inflammation and physiology.
designLarge-animal study combined with mathematical modeling.
settingAcademic large-animal and computational laboratories. SUBJECTS: Outbred juvenile swine.
interventionsFour swine were instrumented and subjected to endotoxemia (100 µg/kg), followed by serial plasma sampling. MEASUREMENTS AND MAIN
resultsSwine exhibited various degrees of inflammation and acute lung injury, including one death with severe acute lung injury (PaO(2)/FIO(2) ratio μ200 and static compliance μ10 L/cm H(2)O). Plasma interleukin-1β, interleukin-4, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-α, high mobility group box-1, and NO(2)/NO(3) were significantly (p μ .05) elevated over the course of the experiment. Principal component analysis was used to suggest principal drivers of inflammation. Based in part on principal component analysis, an ordinary differential equation model was constructed, consisting of the lung and the blood (as a surrogate for the rest of the body), in which endotoxin induces tumor necrosis factor-α in monocytes in the blood, followed by the trafficking of these cells into the lung leading to the release of high mobility group box-1, which in turn stimulates the release of interleukin-1β from resident macrophages. The ordinary differential equation model also included blood pressure, PaO(2), and FIO(2), and a damage variable that summarizes the health of the animal. This ordinary differential equation model could be fit to both inflammatory and physiologic data in the individual swine. The predicted time course of damage could be matched to the oxygen index in three of the four swine.
conclusionsThe approach described herein may aid in predicting inflammation and physiologic dysfunction in small cohorts of subjects with diverse phenotypes and outcomes.
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