PREDICTIVE MATHEMATICAL MODEL OF INFLAMMATION FOR SHOCK/TRAUMA

休克/创伤炎症的预测数学模型

• 批准号: 7274165
• 负责人: YORAM VODOVOTZ
• 金额: $ 25.86万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7274165
• 关键词: T lymphocyte; biological signal transduction; cell differentiation; computer program /software; computer system design /evaluation; dendritic cells; enzyme inhibitors; hemorrhagic shock; human subject; inflammation; injury; laboratory mouse; laboratory rat; macrophage; mathematical model; mitogen activated protein kinase; model design /development; natural killer cells; nitric oxide; organ; patient oriented research; regulatory gene; resuscitation; stress; trauma

Trauma and hemorrhage elicit an acute inflammatory response. This process involves migration and activation of leukocytes, secretion of cytokines, and the production of free radicals. Together, these changes may result in severe organ dysfunction and death. We have developed a mathematical model that describes the mediators of acute inflammation, and is calibrated in mice subjected to endotoxemia, surgical trauma, and hemorrhagic shock. This model was further calibrated in human endotoxemia. Though informed by circulating mediators, this model expresses the physiological derangement experienced by individual organs in terms of a global tissue dysfunction equation. The close correlation between the output of the mathematical model of inflammation and experimental data suggests that a common inflammatory response underlies diverse shock states, raising the possibility of modeling the inflammatory process in vivo. We hypothesize that a validated and calibrated mathematical model of inflammation and its pathologic consequences will be useful for predicting outcome in patients suffering from traumatic/hemorrhagic shock. We will test this hypothesis in two Specific Aims. In Aim 1, we will augment our mathematical model in rodents, including elements of adaptive immunity, and simulate therapeutic interventions. We will modify our model to include natural killer (NK) cells, NKT cells, mast cells, dendritic cells, and TH1 and TH2 cells. We will modify how we model reactions of nitric oxide, examine the roles of HMG-B1 and hyaluronic acid as pro-inflammatory alarm molecules, and model the impact of MAP kinase inhibitors. Furthermore, the mathematical model will inform and will be informed by the hypotheses presented in Projects I-IV. For example, we hypothesize that we can predict the optimal timing and dosage of anti-lL-6, Ringer's Ethyl Pyruvate solution, and NAD in rodent models of shock/trauma. We will carry out detailed time course studies in mice to validate and calibrate this model and the proposed interventions. In Aim 2, we will adapt the mathematical model of trauma/hemorrhage-induced inflammation to humans and create a platform for integration into individualized clinical decision-making. In a prospective clinical study of 500 trauma patients, we will obtain data on the course of inflammation and organ dysfunction as well as cytokine gene polymorphisms needed for our mathematical model, in addition to clinical data that will be used to construct a series of statistical models. Selected interventions from Aim 1 will be tested in simulated clinical trials. We will also create a platform, based on the mathematical model, for integration into individualized clinical decision-making in shock/trauma. The research proposed herein will impact both basic and translational research on the inflammatory process of shock/trauma.

创伤和出血引起急性炎症反应。该过程涉及白细胞的迁移和激活，细胞因子的分泌以及自由基的产生。这些变化在一起可能会导致严重的器官功能障碍和死亡。我们已经开发了一个数学模型，描述了急性炎症的介体，并在患有内肌毒素，手术创伤和出血性休克的小鼠中进行了校准。在人内毒素血症中进一步校准了该模型。尽管由循环介体告知，但该模型表达了各个器官在全球组织功能障碍方程方面经历的生理危险。炎症数学模型的输出与实验数据之间的密切相关表明，常见的炎症反应 构成了多种冲击状态的基础，增加了对体内炎症过程进行建模的可能性。我们假设炎症的验证和校准数学模型及其病理后果将有助于预测患有创伤/出血性休克患者的预后。我们将以两个具体的目的来检验这一假设。在AIM 1中，我们将在啮齿动物中增强我们的数学模型，包括适应性免疫的元素和模拟治疗干预措施。我们将修改我们的模型以包括天然杀伤（NK）细胞，NKT细胞，肥大细胞，树突状细胞以及Th1和Th2细胞。我们将修改如何建模一氧化氮的反应，检查HMG-B1和透明质酸作为促炎的作用 警报分子，并建模MAP激酶抑制剂的影响。此外，数学模型将为I-IV项目中提出的假设提供信息，并将告知。为了 例如，我们假设我们可以预测抗lll-6，林格丙酮酸乙基溶液的最佳时机和剂量，而在冲击/创伤的啮齿动物模型中，我们可以预测NAD。我们将在小鼠中进行详细的时间课程研究，以验证和校准该模型和建议的干预措施。在AIM 2中，我们将适应创伤/出血引起的对人的炎症的数学模型，并创建一个平台以整合到个性化的临床决策中。在一项针对500名创伤患者的前瞻性临床研究中，我们还将获得有关炎症和器官功能障碍以及我们的数学模型所需的细胞因子基因多态性的数据，此外还将使用临床数据来构建一系列统计模型。 AIM 1中选定的干预措施将在模拟临床试验中进行测试。我们还将基于数学模型创建一个平台，以集成到个性化的临床中 震惊/创伤的决策。本文提出的研究将影响冲击/创伤的炎症过程的基本和转化研究。