SHB: Type I (EXP): Personalized Asthma Monitor Detecting Nitric Oxide in Breath

该项目探索使用气体选择性电阻型传感技术来检测和定量呼气中的一氧化氮(NO)以用于诊断目的。该项目的目标是开发一种个性化监测呼气中一氧化氮(FeNO)分数的技术，长期目标是预防或控制哮喘等呼吸道疾病。FeNO是一种已知的用于测量呼吸道炎症的生物标志物，本项目所研究的技术为定量呼吸中的NO水平提供了一种相对简单和非侵入性的有效和实用的手段。这项工作涉及使用单晶金属氧化物纳米线，有望将非选择性传感纳米探测器的检测阈值提高至少两个数量级，降至几ppb或更低。一种传感器微系统正在开发中，该系统可以量化气体传感器的响应，以生成并显示一次呼气中NO浓度的准确测量。设计独立分量分析(ICA)算法，以增强气体识别能力，提高传感器响应的稳健性，是本项目的目标之一。在混合信号VLSI中实现ICA算法和包含基线跟踪的读出电路将导致一种低功耗自主片上系统解决方案，用于测量手持气体测量单元的气体浓度。被刺激产生NO和CO的细胞培养的头部空间与模拟呼吸的样本一起被用来评估NO呼气测定仪的性能和可靠性。同样的研究有助于理解炎症反应中NO产生的生物化学。这项工作的预期结果是一种智能健康呼吸分析工具，它将使可能受到呼吸道疾病影响的个人保持健康，并提供一种在家里自我监测早期疾病迹象的手段，而不是需要医疗保健专业人员协助进行监测的医院环境。正在开发的用于个性化诊断的新工具应该很容易被普通公众使用，以促进他们的健康和福祉。此外，该设备将特别适合范围广泛的受影响个人使用，如非常年长的人、年幼的儿童和其他丧失行为能力的患者。该项目将使学生，包括代表性不足的群体，参与一个跨学科领域的研究活动，该领域涉及纳米材料、传感器纳米技术、微电子设备制造和诊断仪器、生物物理学和生物化学，并最终涉及纳米医学。预计将与国家实验室和医疗诊断行业进行互动。这些相互作用有望导致将实验室这项工作所产生的无呼气测定仪中所包含的技术转化为市场。这项工作的成果将通过出版物、专题介绍、外联活动和多媒体产品进行传播，并将张贴在项目网站(https://web.stonybrook.edu/cnsd/formservertemplates/pro7.html).上

This project explores the use of a gas selective resistive type sensing technology to detect and quantitate nitric oxide (NO) in exhaled breath for diagnostic purposes. The goal of the project is to develop a technique for personalized monitoring of the fraction of nitric oxide (FeNO) in exhaled breath, with the long term objective of prevention or control of airway diseases, such as asthma. FeNO is a known biomarker for measuring airway inflammation and the technology studied in this project provides an effective and practical means to quantitate NO levels in breath in a relatively simple and noninvasive way. This work involves the use of single crystal metal oxide nanowires that are expected to improve the detection threshold of NO-selective sensing nanoprobes by at least two orders of magnitude down to the few ppb level and below. A sensor microsystem is being developed that quantifies the gas sensor response to generate and display an accurate measure of the NO concentration in a single exhaled breath. The design of independent component analysis (ICA) algorithms, to enhance the gas discrimination and improve the robustness of the sensor response, is one of the objectives of this project. The implementation of the ICA algorithms and readout circuitry incorporating baseline tracking in mixed-signal VLSI will lead to a low-power autonomous system-on-chip solution for the measurement of gas concentrations from a handheld gas-measuring unit. The head space from cell cultures that have been stimulated to generate NO and CO are being used, along with breath-simulating samples, to assess the performance and reliability of the NO-breathalyzer. The same studies help to understand the biochemistry of NO production in response to inflammation. The expected outcome of this work is a smart health breath analysis tool that will empower the individual who may be susceptible to airway diseases to stay healthy and that provides a means for self-monitoring of early signs of illness in the home, instead of the hospital setting in which monitoring would require the assistance of health care professionals. The new tools being developed for personalized diagnostics should be easily employed by the lay public to promote their health and well-being. Furthermore, the device will be especially suitable for use by a wide range of compromised individuals, such as the very elderly, young children and otherwise incapacitated patients. This project will engage students, including underrepresented groups in research activities in an interdisciplinary field spanning nanomaterials, sensor nanotechnology, microelectronic device fabrication and diagnostic instrumentation, biophysics and biochemistry, and ultimately nanomedicine. Interactions with National Laboratories and the medical diagnostics industry are anticipated. These interactions are expected to lead to the translation of the technology embodied in the NO-breathalyzer resulting from this work in the laboratory to the marketplace. The results of this work will be disseminated through publications, presentations, outreach events and multimedia products to be posted on the project web site (https://web.stonybrook.edu/cnsd/formservertemplates/pro7.html).