Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
Anal Chim Acta. 2024 Sep 1;1320:343029. doi: 10.1016/j.aca.2024.343029. Epub 2024 Jul 26.
Diagnosis of stress generally involves uses of questionnaires which can provide biased results. The more reliable approach relies on observation of individual symptoms by psychiatrists which is time consuming and could not be applicable for massive scale screening tests. This research established alternative approaches with gas chromatography-ion mobility spectrometry (GC-IMS) and electronic nose (e-nose) to perform fast stress screening based on fingerprinting of highly volatile compounds in headspaces of sweat. The investigated samples were obtained from 154 female nurse volunteers who also provided the data of questionnaire-based mental health scores with the high stress cases confirmed by psychiatrists.
The interviews by psychiatrists revealed 14 volunteers with high stress. Their axillary sweat samples and that from 32 nurses with low/moderate stress (controls) were collected onto cotton rods and analysed with GC-IMS. The possible marker peaks were selected based on the accuracy data. They were tentatively identified as ammonia, diethyl ether, methanol, octane, pentane, acetone and dimethylamine which could involve different endogenous mechanisms or the relationships with the local microbiomes. The data were further analysed using partial least squares discriminant analysis with the receiver operating characteristic curves showing the optimum accuracy, sensitivity and selectivity of 87%, 86% and 88%, respectively. Providing that the samples were obtained from the nurses without deodorant uses, the high stress cases could be screened using e-nose sensors with the accuracy of 89%. The sensor responses could be correlated with the marker peak area data in GC-IMS with the coefficients ranging from -0.70 to 0.80.
This represents the first investigation of highly volatile compound markers in sweat for high stress screening. The established methods were simple, reliable, rapid and non-invasive, which could be further adapted into the portable platform of e-nose sensors with the practical application to perform the screening tests for nurses in Phra Nakorn Si Ayutthaya hospital, Thailand.
一般来说,压力的诊断涉及使用可能产生偏差的问卷。更可靠的方法是依靠精神病医生观察个体症状,但这种方法既耗时又不适用于大规模的筛选测试。本研究建立了替代方法,使用气相色谱-离子迁移谱(GC-IMS)和电子鼻(e-nose),通过分析汗液顶空的高挥发性化合物指纹图谱,快速进行压力筛选。研究对象为 154 名女性护士志愿者,她们提供了基于问卷调查的心理健康得分数据,其中精神病医生确认了 14 名高压力案例。
精神病医生的访谈显示,有 14 名志愿者压力较大。他们的腋窝汗液样本和 32 名低/中度压力(对照组)护士的汗液样本被收集到棉签上,并用 GC-IMS 进行分析。根据准确率数据选择了可能的标记峰,它们被初步鉴定为氨、二乙醚、甲醇、辛烷、戊烷、丙酮和二甲胺,这些可能涉及不同的内源性机制或与局部微生物组的关系。进一步使用偏最小二乘判别分析对数据进行分析,ROC 曲线显示最佳准确性、敏感性和特异性分别为 87%、86%和 88%。如果从没有使用过除臭剂的护士身上采集样本,高压力案例可以使用电子鼻传感器以 89%的准确率进行筛选。传感器的响应与 GC-IMS 中的标记峰面积数据相关,相关系数范围为-0.70 至 0.80。
这是首次研究汗液中的高挥发性化合物标志物用于压力高筛选。所建立的方法简单、可靠、快速且非侵入性,可以进一步适应电子鼻传感器的便携式平台,用于泰国 Pra Nakorn Si Ayutthaya 医院的护士进行筛选测试。