预测年轻男性内毒素诱导的炎症反应的个性化数学模型
Personalized Mathematical Model Predicting Endotoxin-Induced Inflammatory Responses in Young Men
摘要：
机体对病原微生物感染或严重组织创伤的最初反应是急性炎症反应。这种反应的程度至关重要，因为不受控制的反应可能导致进一步的组织损伤、脓毒症和最终死亡，而反应不足可能导致病原体清除不足。正常的炎症反应有助于消除微生物致病配体（如内毒素）造成的威胁，从而使身体恢复健康状态。使用个性化的数学模型，理解和详细描述的促炎和抗炎细胞因子之间的相互作用，可以提供重要的洞察力，在评估脓毒症患者或手术中的易感患者。我们的模型根据从测量促炎细胞因子的实验中获得的实验数据进行校准在20名健康年轻男性受试者中，给予低剂量的脂多糖（LPS）静脉注射，导致内毒素刺激的炎症。通过校准过程，我们创建了一个个性化的数学模型，可以准确地确定受试者之间的个体差异，以及识别那些表现出异常反应的人。
英文摘要：
The initial reaction of the body to pathogenic microbial infection or severe tissue trauma is an acute inflammatory response. The magnitude of such a response is of critical importance, since an uncontrolled response can cause further tissue damage, sepsis, and ultimately death, while an insufficient response can result in inadequate clearance of pathogens. A normal inflammatory response helps to annihilate threats posed by microbial pathogenic ligands, such as endotoxins, and thus, restore the body to a healthy state. Using a personalized mathematical model, comprehension and a detailed description of the interactions between pro- and anti-inflammatory cytokines can provide important insight in the evaluation of a patient with sepsis or a susceptible patient in surgery. Our model is calibrated to experimental data obtained from experiments measuring pro-inflammatory cytokines (interleukin-6 (IL-6), tumor necrosis factor (TNF-), and chemokine ligand-8 (CXCL8)) and the anti-inflammatory cytokine interleukin-10 (IL-10) over 8 hours in 20 healthy young male subjects, given a low dose intravenous injection of lipopolysaccharide (LPS), resulting in endotoxin-stimulated inflammation. Through the calibration process, we created a personalized mathematical model that can accurately determine individual differences between subjects, as well as identify those who showed an abnormal response.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
