Ion-molecule reaction mass spectrometry may allow the continuous and noninvasive monitoring of expiratory propofol levels in patients undergoing general anesthesia.

The algorithm SFR and IMR-MS datasets are available under http://biomed.umit.at/page.cfm?pageid=526.

No abstract

Analysis of volatile organic compounds (VOCs) in exhaled breath offers diagnostic potential in research and clinical medicine. Mass spectrometry of expiratory air allows VOC measurements in a concentration range from parts per trillion to parts per million. For the reduction of dilution-related measurement errors due to dead space admixture, the precise identification of the end-expiratory phase of expiration is essential. We used a combination of two integrated MS systems consisting of a conventional MS capable of fast CO(2) tracing controlling a second, highly sensitive MS for the measurement of VOCs based on ion-molecule-reaction-MS (IMR-MS). This study intended to test the applicability of a software-based method of CO(2)-controlled alveolar breath-gas sampling in 12 ventilated patients using acetaldehyde, acetone, ethanol and isoprene as target VOCs (IMR-MS compound integration time 500 ms, cycle time 2 ms, measurement time 120 min). CO(2)-controlled versus mixed inspiratory/expiratory results are as follows: acetaldehyde 71* (61-133) versus 63 (47-87); acetone 544* (208-1174) versus 504 (152-950); ethanol 133 (99-166) versus 123 (108-185); isoprene 118* (69-253) versus 58 (44-112) (values in ppbv as medians with 25-75%; *p < 0.05 versus mixed inspiratory/expiratory values). The applied software-based CO(2)-controlled sampling method of expiratory air resulted in significant higher concentrations of acetaldehyde, acetone and isoprene.

Aims Fast and reliable methods for the early detection and identification of micro‐organism are of high interest. In addition to established methods, direct mass spectrometry–based analysis of volatile compounds (VCs) emitted by micro‐organisms has recently been shown to allow species differentiation. Thus, a large number of pathogenic Gram‐negative bacteria, which comprised Acinetobacter baumannii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Pseudomonas aeruginosa, Proteus vulgaris and Serratia marcescens, were subjected to headspace VC composition analysis using direct mass spectrometry in a low sample volume that allows for automation. Methods and Results Ion‐molecule reaction–mass spectrometry (IMR‐MS) was applied to headspace analysis of the above bacterial samples incubated at 37°C starting with 102 CFU ml−1. Measurements of sample VC composition were performed at 4, 8 and 24 h. Microbial growth was detected in all samples after 8 h. After 24 h, species‐specific mass spectra were obtained allowing differentiation between bacterial species. Conclusions IMR‐MS provided rapid growth detection and identification of micro‐organisms using a cumulative end‐point model with a short analysis time of 3 min per sample. Significance and impact of the study Following further validation, the presented method of bacterial sample headspace VC analysis has the potential to be used for bacteria differentiation.