Mathematical Modeling of Inflammation in ARDS

描述（由申请人提供）：创伤和全身感染引起急性炎症反应。炎症涉及白细胞及其产物（细胞因子、自由基和蛋白酶）之间复杂的相互作用，以及随之而来的组织损伤/功能障碍。这种多器官功能障碍通常表现为感染性休克和严重肺功能障碍，统称为急性呼吸窘迫综合征（ARDS），美国每年有215,000人死于败血症。这一过程的复杂性阻碍了免疫调节性ARDS治疗的进展。我们已经开发了这些元素的数学模型，以揭示在各种急性炎症情况下这种复杂的相互作用，并使用来自小鼠、大鼠、猪和人类的数据校准了该模型的不同变体（匹兹堡大学炎症分析/建模组件）。我们的建模平台已被用于获得基础和转化见解，后者包括模拟（计算机）临床试验。结合这些努力，我们开发了一个脓毒症+肠道缺血/再灌注（脓毒症+I/R）猪模型，模拟人类脓毒症休克和ARDS的发病机制（Upstate Medical University ARDS动物模型组件）。我们假设，对脓毒症+I/R模型中生成的复杂生化和生理数据的数学分析将使我们能够分离关键的治疗靶点并测试新的治疗方法；其中一种药物是改性四环素COL-3。我们的具体目标是：1)建立一个强大的数学模型，描述猪脓毒症+I/R诱导的休克和ARDS，其病理后果，以及可能的治疗方法；2)利用col3作为工具进一步校准数学模型；3)证明NE， MMP-2和MMP-9是脓毒症+I/R诱导的脓毒症休克和ARDS发病机制的关键成分。我们的校准数学模型将用于进行计算机临床试验，并为新型ARDS治疗方法的合理开发建立平台。计算机试验将在动物实验中得到验证。这些转化研究将建立一个强大的数学模型，能够描述脓毒症诱导的ARDS的复杂发病机制，并确定其调节将显著改善临床结果的靶分子。在美国，败血症和感染性休克每年导致超过21.5万人死亡，每年的医疗费用超过160亿美元。由于脓毒症发病机制的复杂性，开发降低这种高死亡率的药物非常困难。在本研究中，我们将使用一个复杂的机制，部分校准的数学模型来分析脓毒症死亡率的机制，该模型将能够识别分子“瓶颈”，如果阻断这些“瓶颈”，将阻止这种疾病的进展，并显着降低脓毒症引起的发病率和死亡率。（摘要结束）

DESCRIPTION (provided by applicant): Trauma and systemic infection elicit an acute inflammatory response. Inflammation involves complex interactions among leukocytes, their products (cytokines, free radicals, and proteases), and the tissue damage/dysfunction that ensues. This multiple organ dysfunction often manifests as septic shock and severe lung dysfunction, referred to collectively as the acute respiratory distress syndrome (ARDS), and contributes to the 215,000 annual deaths in the U.S. from sepsis. The complexity of this process has stymied the progress towards immunomodulatory ARDS therapeutics. We have developed a mathematical model of these elements in order to unravel this complex interplay in various settings of acute inflammation, and have calibrated distinct variants of this model with data from mice, rats, swine, and humans (University of Pittsburgh Inflammatory Analyte/Modeling Component). Our modeling platform has been used to gain both basic and translational insights, the latter including simulated (in silico) clinical trials. In conjunction with these efforts, we developed a sepsis + gut ischemia/reperfusion (Sepsis+I/R) porcine model that mimics the pathogenesis of human septic shock and ARDS (Upstate Medical University ARDS Animal Model Component). We hypothesize that mathematical analysis of the complex biochemical and physiologic data generated in our Sepsis+I/R model will enable us to isolate key therapeutic targets and to test novel therapeutics; one such agent is the modified tetracycline COL-3. Our Specific Aims are: 1) to develop a robust mathematical model describing Sepsis+I/R- induced shock and ARDS in swine, its pathologic consequences, and possible therapies, 2) to utilize COL-3 as a tool to further calibrate the mathematical model and 3) to demonstrate that NE, MMP-2 and MMP-9 are critical components in Sepsis+I/R-induced septic shock and ARDS pathogenesis. Our calibrated mathematical model will be used to conduct in silico clinical trials and establish a platform for the rational development of novel ARDS therapeutics. The in silico trials will be validated in animal experiments. The proposed translational studies will develop a robust mathematical model capable of describing the complex pathogenesis of sepsis-induced ARDS and identify target molecules whose modulation would significantly improve clinical outcome. Sepsis and septic shock are responsible for more that 215,000 deaths in the United States per year with an annual healthcare cost of over $16 billion dollars. Due to the complexity of sepsis pathogenesis, it has been exceedingly difficult to develop drugs that will reduce this high mortality. In the proposed study, we will analyze the mechanisms of sepsis mortality with a sophisticated mechanistic, partially-calibrated mathematical model that will be able to identify molecular "choke points" that if blocked will arrest the progression of this disease and significantly reduce sepsis-induced morbidity and mortality. (End of Abstract)