This project aims to delineate the molecular mechanisms underlying the healing of trauma-induced wounds, using models of the temporal dependence and interactions of cells and cytokines involved in the inflammatory phase during normal and impaired healing. We will then use this knowledge to suggest new routes of external interventions, in order to prevent chronic inflammation and minimize scarring sequelae.
Nagaraja, S., L. Chen, L. A. DiPietro, J. Reifman, and A. Y. Mitrophanov. Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds. Journal of Translational Medicine. 2018 February 20; 16:32. [PDF, 29458433]
Chen, L., S. Nagaraja, J. Zhou, Y. Zhao, D. Fine, A. Y. Mitrophanov, J. Reifman, and L. A. DiPietro. Wound healing in Mac-1 deficient mice. Wound Repair and Regeneration. 2017 May; 25(3):366-376. [PDF, 28370678]
Nagaraja, S., L. Chen, J. Zhou, Y. Zhao, D. Fine, L. A. DiPietro, J. Reifman, and A. Y. Mitrophanov. Predictive analysis of mechanistic triggers and mitigation strategies for pathological scarring in skin wounds. Journal of Immunology. 2017 January 15; 198(2):832-841. [PDF, 27956530]
Nagaraja, S., J. Reifman, and A. Y. Mitrophanov. Computational identification of mechanistic factors that determine the timing and intensity of the inflammatory response. PLOS Computational Biology. 2015 December 3; 11(12):e1004460. [PDF, 26633296]
Nagaraja, S., A. Wallqvist, J. Reifman, and A. Y. Mitrophanov. Computational approach to characterize causative factors and molecular indicators of chronic wound inflammation. Journal of Immunology. 2014 February 15; 192(4):1824-1834. [PDF, 24453259]