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- W2113531497 abstract "Abstract Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating inflammation is incomplete. Knowledge of such critical regulatory processes and informative indicators of chronic inflammation is necessary for efficacious therapeutic interventions and diagnostic support to clinicians. We used a computational modeling approach to elucidate the critical factors responsible for chronic inflammation and to identify robust molecular indicators of chronic inflammatory conditions. Our kinetic model successfully captured experimentally observed cell and cytokine dynamics for both acute and chronic inflammatory responses. Using sensitivity analysis, we identified macrophage influx and efflux rate modulation as the strongest inducing factor of chronic inflammation for a wide range of scenarios. Moreover, our model predicted that, among all major inflammatory mediators, IL-6, TGF-β, and PDGF may generally be considered the most sensitive and robust indicators of chronic inflammation, which is supported by existing, but limited, experimental evidence." @default.
- W2113531497 created "2016-06-24" @default.
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- W2113531497 creator A5020594190 @default.
- W2113531497 creator A5030271505 @default.
- W2113531497 creator A5040908704 @default.
- W2113531497 date "2014-02-15" @default.
- W2113531497 modified "2023-09-27" @default.
- W2113531497 title "Computational Approach To Characterize Causative Factors and Molecular Indicators of Chronic Wound Inflammation" @default.
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- W2113531497 doi "https://doi.org/10.4049/jimmunol.1302481" @default.
- W2113531497 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24453259" @default.
- W2113531497 hasPublicationYear "2014" @default.