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

该项目将设计一个集成传感和分析框架，通过可穿戴诊断平台对有败血症风险的家庭/医院患者进行无创远程监测。败血症是入院患者死亡的主要原因，也是美国医院治疗费用最高的疾病之一（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，需要适当监测的反复血液检查耗时且执行率不理想。这些限制显著降低了早期目标导向治疗的疗效。该项目的核心假设是通过对汗液的实时分析，检测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联系起来。具体而言，研究计划包括：1)设计化学增强的汗液提取界面；2)开发疾病特异性推理模型和汗液分析框架；3)评估该框架在脓毒症患者中的应用。这些努力将集中在患者监测平台的开发上，该平台可以通过最小的重新配置来优化其他临床和生理应用。计划中的研究将解决对推进基于汗液的生物传感领域至关重要的基本问题。一个集成的传感技术和分析框架，使纵向汗液读数与多条件诱导的分泌参数标准化，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元系统的理解。实现这一目标需要解决多个方面的各种科学瓶颈，包括调制速率下的不明显出汗感应，纵向/多条件原位传感以及可以解释各种不确定性来源的统计模型的开发和验证。研究团队将利用他们在柔性设备制造、生物界面/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提出的目标。本项目通过原位分析汗液乳酸作为血乳酸的代用物，配合可穿戴式汗液提取/分析装置，检测血液中的急剧升高，对脓毒症的严重程度进行检测/分级。该项目的外展部分将侧重于通过创建一个多元化的、以STEM为动力的社区，促进未被充分代表的少数民族在高中和本科阶段的STEM参与。此外，这个项目的教育部分将把计划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.