SCH: INT: Collaborative Research: A Non-Invasive and Wearable Molecular Diagnostic Platform for Remote and Passive Monitoring of Patients at Risk for Sepsis

这个项目将设计一个综合的传感和分析框架，通过一个可穿戴的诊断平台，对有脓毒症风险的家庭/住院患者进行非侵入性远程监测。脓毒症是住院患者死亡的主要原因，也是美国医院治疗的最昂贵的疾病之一(每年200亿美元)。早期发现和及时干预是改善这些患者预后的最关键因素，但脓毒症的症状是非特异性的，需要进行适当监测的重复血液测试非常耗时，而且执行速度不佳。这些局限性显著降低了早期目标导向疗法的疗效。该项目的核心假设是，通过对汗液的实时分析，可以检测到脓毒症，并对其严重程度进行分类。在这方面，将开发一个综合传感/分析框架，将汗液读数与败血症状态相关联。具体地说，研究计划包括：1)设计化学增强的汗液提取界面，2)开发针对疾病的推理模型和汗液分析框架，3)评估应用于脓毒症患者的框架。这些努力将集中在患者监测平台的开发上，该平台只需最小限度的重新配置，即可针对其他临床和生理应用进行优化。这项计划中的研究将解决对推进汗液生物传感领域至关重要的基本问题。一种集成的传感技术和分析框架，根据多条件诱导的分泌参数对纵向汗液读数进行标准化，将提供对汗液分泌过程的定量洞察，并促进我们对这一复杂和多变量系统的理解。要做到这一点，需要解决多个方面的各种科学瓶颈，从以调制速率进行不明显的出汗诱导、纵向/多条件现场传感以及开发和验证可解释各种不确定因素的统计模型。研究团队将利用他们在灵活设备制造、生物接口/传感器设计、药理学、汗腺生理学、临床研究和统计建模方面的专业知识来实现拟议的目标。通过现场分析作为血乳酸替代品的汗液乳酸，利用可穿戴的汗液提取/分析设备，该项目可以检测血液中的急剧升高，并检测/分类脓毒症的严重程度。该项目的外展部分将侧重于通过创建一个多样化的、以STEM为动力的社区，促进未被充分代表的少数群体在高中和本科一级参与STEM。此外，该项目的教育部分将把计划中的研究活动的结果纳入课程材料。

This project will devise an integrated sensing and analytical framework to enable non-invasive remote monitoring of in-home/in-hospital patients at risk for sepsis with a wearable diagnostic platform. Sepsis is the leading cause of admitted patient mortality and is one of the most expensive conditions ($20 billion per year) treated in U.S. hospitals. Early detection and timely intervention are the most crucial factors in improving the outcome for these patients, but the symptoms of sepsis are nonspecific and the repeated blood tests that are required to appropriately monitor are time-consuming and performed at suboptimal rates. These limitations significantly degrade the efficacy of early goal-directed therapy. The core hypothesis of this project is that through the real-time analysis of sweat, sepsis can be detected and its severity can be classified. In that regard, an integrated sensing/analytical framework will be developed to correlate the sweat readings to the sepsis status. Specifically, the research plan includes: 1) devising a chemically-enhanced sweat extraction interface, 2) developing disease-specific inference models and sweat analysis framework, and 3) evaluating the framework applied to septic patients. These efforts will converge toward the development of a patient monitoring platform, which with minimal reconfiguration, can be optimized toward other clinical and physiological applications. The planned research will address fundamental questions critical to advancing the field of sweat-based biosensing. An integrated sensing technology and analytical framework that normalizes longitudinal sweat readings with respect to multi-conditionally induced secretion parameters will provide quantitative insight into sweat secretion processes and promote our understanding of this complex and multivariate system. Achieving this requires resolving various scientific bottlenecks at multiple fronts spanning from inconspicuous sweat induction at modulated rates, longitudinal/multiconditional in-situ sensing and development and validation of statistical models that can account for the various sources of uncertainty. The team of investigators will capitalize upon their expertise in flexible device fabrication, bio-interface/sensor design, pharmacology, sweat gland physiology, clinical research, and statistical modeling to deliver the proposed objectives. Through in-situ analysis of sweat lactate as a proxy for blood lactate, with a wearable sweat extraction/analysis device, the project can detect the dramatic elevation in blood and detect/classify the severity of sepsis. The outreach component of this project will focus on promoting the STEM participation of underrepresented minorities at high school and undergraduate levels by creating a diverse, STEM-motivated community. Moreover, the educational component of this project will integrate findings from the planned research activities into the course materials.