Presently, 2 to 4 days elapse between sampling at infection suspicion and result of microbial diagnostics. This delay for the identification of pathogens causes quite often a late and/or inappropriate initiation of therapy for patients suffering from infections. Bad outcome and high hospitalization costs are the consequences of these currently existing limited pathogen identification possibilities. For this reason, we aimed to apply the innovative method multi-capillary column–ion mobility spectrometry (MCC-IMS) for a fast identification of human pathogenic bacteria by determination of their characteristic volatile metabolomes. We determined volatile organic compound (VOC) patterns in headspace of 15 human pathogenic bacteria, which were grown for 24 h on Columbia blood agar plates. Besides MCC-IMS determination, we also used thermal desorption–gas chromatography–mass spectrometry measurements to confirm and evaluate obtained MCC-IMS data and if possible to assign volatile compounds to unknown MCC-IMS signals. Up to 21 specific signals have been determined by MCC-IMS for Proteus mirabilis possessing the most VOCs of all investigated strains. Of particular importance is the result that all investigated strains showed different VOC patterns by MCC-IMS using positive and negative ion mode for every single strain. Thus, the discrimination of investigated bacteria is possible by detection of their volatile organic compounds in the chosen experimental setup with the fast and cost-effective method MCC-IMS. In a hospital routine, this method could enable the identification of pathogens already after 24 h with the consequence that a specific therapy could be initiated significantly earlier.

MCC-IMS may be a suitable method to determine propofol concentrations in exhaled air, and may be used to predict propofol concentrations in serum.

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This experiment observed the evolution of metabolite plumes from a human trapped in a simulation of a collapsed building. Ten participants took it in turns over five days to lie in a simulation of a collapsed building and eight of them completed the 6 h protocol while their breath, sweat and skin metabolites were passed through a simulation of a collapsed glass-clad reinforced-concrete building. Safety, welfare and environmental parameters were monitored continuously, and active adsorbent sampling for thermal desorption GC-MS, on-line and embedded CO, CO(2) and O(2) monitoring, aspirating ion mobility spectrometry with integrated semiconductor gas sensors, direct injection GC-ion mobility spectrometry, active sampling thermal desorption GC-differential mobility spectrometry and a prototype remote early detection system for survivor location were used to monitor the evolution of the metabolite plumes that were generated. Oxygen levels within the void simulator were allowed to fall no lower than 19.1% (v). Concurrent levels of carbon dioxide built up to an average level of 1.6% (v) in the breathing zone of the participants. Temperature, humidity, carbon dioxide levels and the physiological measurements were consistent with a reproducible methodology that enabled the metabolite plumes to be sampled and characterized from the different parts of the experiment. Welfare and safety data were satisfactory with pulse rates, blood pressures and oxygenation, all within levels consistent with healthy adults. Up to 12 in-test welfare assessments per participant and a six-week follow-up Stanford Acute Stress Response Questionnaire indicated that the researchers and participants did not experience any adverse effects from their involvement in the study. Preliminary observations confirmed that CO(2), NH(3) and acetone were effective markers for trapped humans, although interactions with water absorbed in building debris needed further study. An unexpected observation from the NH(3) channel was the suppression of NH(3) during those periods when the participants slept, and this will be the subject of further study, as will be the detailed analysis of the casualty detection data obtained from the seven instruments used.

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Ion mobility spectrometry is a fast and sensitive analytical method for the detection of gas phase analytes in the ppb(v)-ppt(v) range under ambient conditions (pressure and temperature). Ion mobility spectrometers coupled with rapid pre-separation like multi-capillary columns (MCC/IMS) are suitable for the selective characterization of complex and humid mixtures. Recently, MCC/IMS have been applied to analyses of human breath for early diagnosis as well as medication and therapy control. The complete procedure of breath analyses including evaluation and interpretation of the data obtained is demonstrated for the first time on exhaled breath after the consumption of a particular candy as an example. An MCC/IMS equipped with a β-radiation source ((63)Ni) requires 5 to 10 min for a complete analysis of exhaled breath. Retention time and reduced ion mobility of the detected signals are compared to an analyte database for the identification of the related analytes. These findings were successfully validated by gas-chromatographic mass spectroscopy of the headspace of the candy via solid-phase micro-extraction and of breath samples on Tenax adsorption tubes. Furthermore, signal height of particular analyte signals as a measure for their concentration was used to monitor the concentration development with time. This exemplary investigation demonstrates that MCC/IMS is a powerful and rapid non-invasive tool for human breath analyses. The method can be used for medical applications (diagnosis, therapy control, metabolic profiling) as well as for a general determination of the metabolic state of a subject (medication, nutrition, fasting). The demonstrated procedure is independent of whether the analytes detected in breath are caused by nutrition or medication or whether they are metabolite characteristics for a particular disease. Therefore, it can directly be transferred to any relevant peak pattern.

Major questions of all investigations of analytes using ion mobility spectrometer (IMS) are peak finding and in case of proper finding the reliable referencing. In case of rather complex mixtures like human breath or water impurities, automatic procedures should be found to support peak finding and referencing. A visualisation software tool will be described bringing the summarised results of peak finding methods and the reference lists used as input to data bases together in a single system. The details of the software developed are described briefly and the procedures behind are referenced.