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Updated: Mar 12, 2026

Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry
Published on: March 9, 2018
Real-Time Quantitative Analysis of Valproic Acid in Exhaled Breath by Low Temperature Plasma Ionization Mass
Xiaoxia Gong1, Songyue Shi1, Gerardo Gamez2
1Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, 79409-1061, USA.
Abstract:
Real-time analysis of exhaled human breath is a rapidly growing field in analytical science and has great potential for rapid and noninvasive clinical diagnosis and drug monitoring. In the present study, an LTP-MS method was developed for real-time, in-vivo and quantitative analysis of γ-valprolactone, a metabolite of valproic acid (VPA), in exhaled breath without any sample pretreatment. In particular, the effect of working conditions and geometry of the LTP source on the ions of interest, protonated molecular ion at m/z 143 and ammonium adduct ion at m/z 160, were systematically characterized. Tandem mass spectrometry (MS/MS) with collision-induced dissociation (CID) was carried out in order to identify γ-valprolactone molecular ions (m/z 143), and the key fragment ion (m/z 97) was used for quantitation. In addition, the fragmentation of ammonium adduct ions to protonated molecular ions was performed in-source to improve the signal-to-noise ratio. At optimum conditions, signal reproducibility with an RSD of 8% was achieved. The concentration of γ-valprolactone in exhaled breath was determined for the first time to be 4.83 (±0.32) ng/L by using standard addition method. Also, a calibration curve was obtained with a linear range from 0.7 to 22.5 ng/L, and the limit of detection was 0.18 ng/L for γ-valprolactone in standard gas samples. Our results show that LTP-MS is a powerful analytical platform with high sensitivity for quantitative analysis of volatile organic compounds in human breath, and can have potential applications in pharmacokinetics or for patient monitoring and treatment. Graphical Abstract ᅟ.
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