An Gary, Namas Rami A, Vodovotz Yoram
Department of Surgery, University of Chicago, Chicago, IL 60637, USA.
Crit Rev Biomed Eng. 2012;40(4):341-51. doi: 10.1615/critrevbiomedeng.v40.i4.80.
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.
脓毒症是一种临床实体,其中不仅涉及一系列细胞和分子相互作用,还涉及床边可获取的临床相关生理信号,从而引发复杂的炎症和生理过程。需要从机制上理解将生理变异性的临床现象与炎症生物学的潜在模式联系起来,并且我们断言通过使用动态数学和计算建模可以促进这种理解。实验室实验与数学/计算建模的迭代方法有潜力跨越生物尺度整合细胞生物学、生理学、控制理论和系统工程,从而深入了解控制结构,这些控制结构支配着产生被检测为生物模式的现象的机制。这种方法可以用数学和计算的形式语言来表示假设,并将跨尺度和领域的行为联系起来,从而为更好地解释、诊断和干预脓毒症患者的护理提供机会。