34 research outputs found

    Alignment of retention time obtained from multicapillary column gas chromatography used for VOC analysis with ion mobility spectrometry

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    Multicapillary column (MCC) ion mobility spectrometers (IMS) are increasingly in demand for medical diagnosis, biological applications and process control. In a MCC-IMS, volatile compounds are differentiated by specific retention time and ion mobility when rapid preseparation techniques are applied, e.g. for the analysis of complex and humid samples. Therefore, high accuracy in the determination of both parameters is required for reliable identification of the signals. The retention time in the MCC is the subject of the present investigation because, for such columns, small deviations in temperature and flow velocity may cause significant changes in retention time. Therefore, a universal correction procedure would be a helpful tool to increase the accuracy of the data obtained from a gas-chromatographic preseparation. Although the effect of the carrier gas flow velocity and temperature on retention time is not linear, it could be demonstrated that a linear alignment can compensate for the changes in retention time due to common minor deviations of both the carrier gas flow velocity and the column temperature around the MCC-IMS standard operation conditions. Therefore, an effective linear alignment procedure for the correction of those deviations has been developed from the analyses of defined gas mixtures under various experimental conditions. This procedure was then applied to data sets generated from real breath analyses obtained in clinical studies using different instruments at different measuring sites for validation. The variation in the retention time of known signals, especially for compounds with higher retention times, was significantly improved. The alignment of the retention time—an indispensable procedure to achieve a more precise identification of analytes—using the proposed method reduces the random error caused by small accidental deviations in column temperature and flow velocity significantly

    Processos de remoção de material particulado atmosférico: uma modelagem numérica de estudo de casos

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    Below cloud scavenging processes have been investigated considering a numerical simulation, local atmospheric conditions and particulate matter (PM) concentrations, at different sites in Germany. The below cloud scavenging model has been coupled with bulk particulate matter counter TSI (Trust Portacounter dataset, consisting of the variability prediction of the particulate air concentrations during chosen rain events. The TSI samples and meteorological parameters were obtained during three winter Campaigns: at Deuselbach, March 1994, consisting in three different events; Sylt, April 1994 and; Freiburg, March 1995. The results show a good agreement between modeled and observed air concentrations, emphasizing the quality of the conceptual model used in the below cloud scavenging numerical modeling. The results between modeled and observed data have also presented high square Pearson coefficient correlations over 0.7 and significant, except the Freiburg Campaign event. The differences between numerical simulations and observed dataset are explained by the wind direction changes and, perhaps, the absence of advection mass terms inside the modeling. These results validate previous works based on the same conceptual model.Os processos de remoção atmosféricos foram investigados em simulação numérica, levando-se em conta as condições atmosféricas locais e a concentração de matéria particulada (MP) em diferentes lugares na Alemanha. Um modelo de remoção foi desenvolvido com intuito de predizer a variabilidade da concentração no ar da matéria particulada observada por um contador de partículas totais TSI, durante eventos de precipitação. As amostras de TSI, bem como os dados meteorológicos, foram coletadas em três Campanhas em Deuselbach, em três diferentes eventos; Sylt e Freiburg, respectivamente durante os meses de março de 1994, abril de 1994 e março de 1995. Os resultados mostram boa concordância entre os dados modelados e observados, com altos coeficientes de correlação quadráticos acima de 0.70, dentro da significância, exceto na Campanha de Freiburg. As diferenças apresentadas são devidas a alterações significativas da direção do vento e, talvez, devido à ausência de advecção de massa dentro do modelo. Estes resultados auxiliam a validação de trabalhos prévios baseados no mesmo modelo conceitual

    Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria

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    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

    Multi-capillary column-ion mobility spectrometry (MCC-IMS) as a new method for the quantification of occupational exposure to sevoflurane in anaesthesia workplaces: an observational feasibility study

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    BACKGROUND: Occupational exposure to sevoflurane has the potential to cause health damage in hospital personnel. Workplace contamination with the substance mostly is assessed by using photoacoustic infrared spectrometry with detection limits of 10 ppbv. Multi-capillary column-ion mobility spectrometry (MCC-IMS) could be an alternative technology for the quantification of sevoflurane in the room air and could be even more accurate because of potentially lower detection limits. The aim of this study was to test the hypothesis that MCC-IMS is able to detect and monitor very low concentrations of sevoflurane (<10 ppbv) and to evaluate the exposure of hospital personnel to sevoflurane during paediatric anaesthesia and in the post anaesthesia care unit (PACU). METHODS: A MCC-IMS device was calibrated to several concentrations of sevoflurane and limits of detection (LOD) and quantification (LOQ) were calculated. Sevoflurane exposure of hospital personnel was measured at two anaesthesia workplaces and time-weighted average (TWA) values were calculated. RESULTS: The LOD was 0.0068 ppbv and the LOQ was 0.0189 ppbv. During paediatric anaesthesia the mean sevoflurane concentration was 46.9 ppbv (8.0 - 314.7 ppbv) with TWA values between 5.8 and 45.7 ppbv. In the PACU the mean sevoflurane concentration was 27.9 ppbv (8.0 – 170.2 ppbv) and TWA values reached from 8.3 to 45.1 ppbv. CONCLUSIONS: MCC-IMS shows a significantly lower LOD and LOQ than comparable methods. It is a reliable technology for monitoring sevoflurane concentrations at anaesthesia workplaces and has a particular strength in quantifying low-level contaminations of sevoflurane. The exposure of the personnel working in these areas did not exceed recommended limits and therefore adverse health effects are unlikely

    Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data

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    Loyek C, Bunkowski A, Vautz W, Nattkemper TW. Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data. Journal of Integrative Bioinformatics. 2011;8(2):158.In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data

    Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data

    No full text
    In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data
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