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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Imprimir: 0278-940X
ISSN On-line: 1943-619X

Volumes:
Volume 47, 2019 Volume 46, 2018 Volume 45, 2017 Volume 44, 2016 Volume 43, 2015 Volume 42, 2014 Volume 41, 2013 Volume 40, 2012 Volume 39, 2011 Volume 38, 2010 Volume 37, 2009 Volume 36, 2008 Volume 35, 2007 Volume 34, 2006 Volume 33, 2005 Volume 32, 2004 Volume 31, 2003 Volume 30, 2002 Volume 29, 2001 Volume 28, 2000 Volume 27, 1999 Volume 26, 1998 Volume 25, 1997 Volume 24, 1996 Volume 23, 1995

Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.v40.i4.80
pages 341-351

Sepsis: From Pattern to Mechanism and Back

Gary An
Department of Surgery, University of Chicago, Chicago, IL 60637; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219
Rami A. Namas
Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213
Yoram Vodovotz
Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219; Department of Surgery, University of Pittsburgh, Pittsburgh, PA 15213

RESUMO

Sepsis is a clinical entity in which complex inflammatory and physiological processes are mobilized, not only across a range of cellular and molecular interactions, but also in clinically relevant physiological signals accessible at the bedside. There is a need for a mechanistic understanding that links the clinical phenomenon of physiologic variability with the underlying patterns of the biology of inflammation, and we assert that this can be facilitated through the use of dynamic mathematical and computational modeling. An iterative approach of laboratory experimentation and mathematical/computational modeling has the potential to integrate cellular biology, physiology, control theory, and systems engineering across biological scales, yielding insights into the control structures that govern mechanisms by which phenomena, detected as biological patterns, are produced. This approach can represent hypotheses in the formal language of mathematics and computation, and link behaviors that cross scales and domains, thereby offering the opportunity to better explain, diagnose, and intervene in the care of the septic patient.