Department of Biomedical Engineering, University of Texas at Dallas, 800 W Campbell Rd., Richardson, TX, 75080, USA.
Sotech Health, 17217 Waterview Pkwy, Dallas, TX, 75252, USA.
Sci Rep. 2022 Mar 14;12(1):4370. doi: 10.1038/s41598-022-08321-x.
Breathomics is widely emerging as a strategy for non-invasive diagnosis of respiratory inflammation. In this study, we have evaluated the metabolic signals associated with Coronavirus (SARS COV-2), mainly the release of nitric oxide in breath. We have demonstrated the utility of a breath analyzer-based sensor platform for the detection of trace amounts of this target species. The sensor surface is modified with Room Temperature Ionic Liquid (RTIL) that allows faster diffusion of the target gas and can be used for gas sensing application. A low limit of detection (LOD) of 50 parts per billion has been achieved with a 95% confidence interval for detection of nitric oxide.. This inhouse designed sensor is incorporated into a breath analyzer system that displays enhanced sensitivity, specificity, linearity, and reproducibility for NO gas monitoring. The developed sensor platform can detect target concentrations of NO ranging from 50 to 250 ppb, using 1-Ethyl-3-methylimidazolium Tetrafluoroborate ([EMIM]BF) as RTIL and displays fast response time of 5 s, thereby allowing easy detection of the target gas species. The sensor successfully quantifies the diffusion current and charge modulations arising within the electrical double layer from the RTIL-NO interactions through DC-based chronoamperometry (CA). The subjects tested negative and positive are significantly different (p < 0.01). The prototype can potentially be used for human health monitoring and screening, especially during the pandemic due to its portability, small size, an embedded RTIL sensing element, integrability with a low-power microelectronic device, and an IoT interface.
呼吸组学作为一种非侵入性诊断呼吸炎症的策略正在广泛出现。在这项研究中，我们评估了与冠状病毒（SARS COV-2）相关的代谢信号，主要是呼吸中一氧化氮的释放。我们已经证明了基于呼吸分析仪的传感器平台在检测痕量目标物种方面的实用性。传感器表面用室温离子液体（RTIL）修饰，允许目标气体更快地扩散，可用于气体传感应用。已经实现了对一氧化氮的检测的 50 部分每十亿的低检测限（LOD），置信区间为 95%。这个内部设计的传感器被集成到一个呼吸分析仪系统中，该系统显示出对 NO 气体监测的增强的灵敏度、特异性、线性和可重复性。所开发的传感器平台可以检测 50 到 250 ppb 范围内的目标浓度的 NO，使用 1-乙基-3-甲基咪唑四氟硼酸盐 ([EMIM] BF) 作为 RTIL，并显示出 5 s 的快速响应时间，从而可以轻松检测目标气体。传感器通过基于 DC 的计时安培法（CA）成功地量化了来自 RTIL-NO 相互作用的双层内扩散电流和电荷调制。测试的阴性和阳性受试者明显不同（p < 0.01）。由于其便携性、小尺寸、嵌入式 RTIL 传感元件、与低功耗微电子设备的集成性以及物联网接口，该原型有可能用于人体健康监测和筛查，特别是在大流行期间。
