Ionimed Analytik GmbH

Innsbruck, Austria

Ionimed Analytik GmbH

Innsbruck, Austria
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Titzmann T.,Ionimed Analytik GmbH | Titzmann T.,University of Innsbruck | Graus M.,University of Innsbruck | Muller M.,University of Innsbruck | And 3 more authors.
International Journal of Mass Spectrometry | Year: 2010

Statistical analysis of measured signals from counting systems is a common method to increase the accuracy and precision of peak position and peak area. The most common approach to analyze data gained from counting systems is to fit the data peak by peak using an appropriate probability density function (PDF) like a Gaussian function. Since a counting system creates histograms, the counted data do not represent data points of the anticipated PDF. Therefore, one should not fit any PDF directly to the histogram data. Here we present a solution to this problem by fitting distributions instead of densities. A simple formula allows to correct for Poisson statistics and dead-time effects. The improved peak analysis method is applied to mass spectra obtained from a recently developed proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF) enhancing the mass accuracy and peak quantification. © 2010 Elsevier B.V.

Luchner M.,ACIB GmbH | Gutmann R.,ACIB GmbH | Gutmann R.,Ionimed Analytik GmbH | Bayer K.,ACIB GmbH | And 9 more authors.
Biotechnology and Bioengineering | Year: 2012

We report on the implementation of proton transfer reaction-mass spectrometry (PTR-MS) technology for on-line monitoring of volatile organic compounds (VOCs) in the off-gas of bioreactors. The main part of the work was focused on the development of an interface between the bioreactor and an analyzer suitable for continuous sampling of VOCs emanating from the bioprocess. The permanently heated sampling line with an inert surface avoids condensation and interaction of volatiles during transfer to the PTR-MS. The interface is equipped with a sterile sinter filter unit directly connected to the bioreactor headspace, a condensate trap, and a series of valves allowing for dilution of the headspace gas, in-process calibration, and multiport operation. To assess the aptitude of the entire system, a case study was conducted comprising three identical cultivations with a recombinant E. coli strain, and the volatiles produced in the course of the experiments were monitored with the PTR-MS. The high reproducibility of the measurements proved that the established sampling interface allows for reproducible transfer of volatiles from the headspace to the PTR-MS analyzer. The set of volatile compounds monitored comprises metabolites of different pathways with diverse functions in cell physiology but also volatiles from the process matrix. The trends of individual compounds showed diverse patterns. The recorded signal levels covered a dynamic range of more than five orders of magnitude. It was possible to assign specific volatile compounds to distinctive events in the bioprocess. The presented results clearly show that PTR-MS was successfully implemented as a powerful bioprocess-monitoring tool and that access to volatiles emitted by the cells opens promising perspectives in terms of advanced process control. © 2012 Wiley Periodicals, Inc.

Seewald M.S.A.,University of Innsbruck | Singer W.,Ionimed Analytik GmbH | Knapp B.A.,University of Innsbruck | Franke-Whittle I.H.,University of Innsbruck | And 2 more authors.
Biology and Fertility of Soils | Year: 2010

The agronomic effects of composts, mineral fertiliser and combinations thereof on chemical, biological and physiological soil properties have been studied in an 18-year field experiment. The present study aimed at tracing treatment effects by evaluating the volatile organic compound (VOC) emission of the differently treated soils: non-amended control, nitrogen fertilisation and composts (produced from organic waste and sewage sludge, respectively) in combination with nitrogen fertiliser. Microbial community structure was determined by denaturing gradient gel electrophoresis (DGGE). Aerobic and anaerobic soil VOC emission was determined after glucose amendment using proton transfer reaction-mass spectrometry (PTR-MS). After inducing VOC production by substrate (glucose) addition and at the same time reducing oxygen availability to impair degradation of the produced VOCs, we were able to differentiate among the treatments. Organic waste compost did not alter the VOC emissions compared to the untreated control, whilst sewage sludge composts and mineral fertilisation showed distinct effects. This differentiation was supported by DGGE analysis of fungal 18S rDNA fragments and confirms earlier findings on bacterial communities. Three major conclusions can be drawn: (1) VOC patterns are able to discriminate among soil treatments. (2) Sewage sludge compost and mineral fertilisation have not only the strongest impact on microbial community composition but also on VOC emission patterns, but specific tracer VOCs could not be identified. (3) Future efforts should aim at a PTR-MS-linked identification of the detected masses. © 2010 The Author(s).

Kaser L.,University of Innsbruck | Kaser L.,U.S. National Center for Atmospheric Research | Karl T.,U.S. National Center for Atmospheric Research | Karl T.,University of Innsbruck | And 11 more authors.
Atmospheric Chemistry and Physics | Year: 2013

We present the first eddy covariance flux measurements of volatile organic compounds (VOCs) using a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS) above a ponderosa pine forest in Colorado, USA. The high mass resolution of the PTR-TOF-MS enabled the identification of chemical sum formulas. During a 30 day measurement period in August and September 2010, 649 different ion mass peaks were detected in the ambient air mass spectrum (including primary ions and mass calibration compounds). Eddy covariance with the vertical wind speed was calculated for all ion mass peaks. On a typical day, 17 ion mass peaks, including protonated parent compounds, their fragments and isotopes as well as VOC-H+-water clusters, showed a significant flux with daytime average emissions above a reliable flux threshold of 0.1 mg compound m-2 h-1. These ion mass peaks could be assigned to seven compound classes. The main flux contributions during daytime (10:00-18:00 LT) are attributed to the sum of 2-methyl-3-buten-2-ol (MBO) and isoprene (50%), methanol (12%), the sum of acetic acid and glycolaldehyde (10%) and the sum of monoterpenes (10%). The total MBO + isoprene flux was composed of 10% isoprene and 90% MBO.

There was good agreement between the light-and temperature dependency of the sum of MBO and isoprene observed for this work and those of earlier studies. The above canopy flux measurements of the sum of MBO and isoprene and the sum of monoterpenes were compared to emissions calculated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1). The best agreement between MEGAN 2.1 and measurements was reached using emission factors determined from site-specific leaf cuvette measurements. While the modeled and measured MBO + isoprene fluxes agree well, the emissions of the sum of monoterpenes is underestimated by MEGAN 2.1. This is expected as some factors impacting monoterpene emissions, such as physical damage of needles and branches due to storms, are not included in MEGAN 2.1.

After a severe hailstorm event, 22 ion mass peaks (attributed to six compound classes plus some unknown compounds) showed an elevated flux for the two following days. The sum of monoterpene emissions was 4-23 times higher compared to emissions prior to the hailstorm while MBO emissions remained unchanged. The monoterpene emission (in mg compound m−2) during this measurement period is underestimated by 40% if the effect of this disturbance source is not considered. © 2013 Author(s).

Singer W.,Ionimed Analytik GmbH | Herbig J.,Ionimed Analytik GmbH | Gutmann R.,Ionimed Analytik GmbH | Winkler K.,Ionimed Analytik GmbH | And 2 more authors.
American Laboratory | Year: 2011

Biological systems produce a large variety of volatile metabolites. A sensitive and fast analytical instrument is needed to measure these VOCs in real time. PTR-MS technology is ideally suited for this task. The authors have presented a variety of PTR-MS application examples in the fi elds of medicine and biotechnology. The applications in medicine-based on exhaled breath analysis- can be used for diagnosis of disease, or to monitor isolated metabolic processes via ingestion of 13C-labeled compounds, or to study human exposure to harmful volatile substances, e.g., those present at the workplace. Application of PTR-MS in biotechnology allows monitoring of the composition of biogases or fermentor off-gas. Monitoring biogases in "white biotech" allows detection of u nwanted compounds such as silicon- or sulfur-containing substances. In the "red biotech" application, the gas-phase composition of VOCs in the fermentor headspace is analyzed to obtain more in-depth information on the present fermentation status, which can then be utilized for fermentation process control. (White biotechnology is the application of biotechnology for industrial purposes. Red biotechnology refers to pharmaceutical and medical biotechnology.) In contrast to conventional gas analytical techniques, which require sample preparation and off-line measurements, or are simply not sensitive enough, PTR-MS systems offer essential advantages. All of these applications benefi t from the ultrasensitive, realtime analysis and quantifi cation of VOCs offered by proton transfer reaction mass spectrometry.

Beauchamp J.,Ionimed Analytik GmbH | Beauchamp J.,Fraunhofer Institute for Process Engineering and Packaging | Herbig J.,Ionimed Analytik GmbH | Herbig J.,IONICON Analytik GmbH | And 5 more authors.
Measurement Science and Technology | Year: 2013

The accuracy of quantitative volatile organic compound (VOC) detection by proton-transfer-reaction mass spectrometry (PTR-MS) is substantially enhanced if the instrument is calibrated. Although quantification of a compound is in principle possible by mathematical methods based on kinetic theory, the underlying picture can become complicated depending on the gas matrix, leading to error. A simple, reliable method to overcome this is to calibrate the instrument using standard gas mixtures containing VOCs at known concentrations, which enables the compound-dependent sensitivity of the instrument to be determined. A dynamic gas calibration unit was developed to generate variable but known quantities of selected standard compounds in a carrier gas of variable relative humidity (RH; up to 100% at 37 °C) and CO2 content (≤10%v) to reflect the changing conditions of a breath-gas sample matrix. Besides individual compound sensitivities, calibration also yields the limits of detection and quantification of the experimental method. Extensive calibrations of PTR-MS with several breath-relevant compounds were made at varying RH and CO2. Gas matrix effects of several compounds were negligible when appropriate mass-dependent transmission correction and normalization to the primary ions (m/z 21 and m/z 37) were applied. Two compounds are discussed in particular, namely acetaldehyde, which interferes with a CO2-related background, and formaldehyde, which shows a nonlinear dependence on sample gas humidity. © 2013 IOP Publishing Ltd.

Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: HEALTH.2010.1.2-1 | Award Amount: 5.41M | Year: 2011

The LCAOS project will develop and test a new diagnostic tool, able to detect: (i) the presence of lung cancer (LC), and (ii) an increased risk of a patient developing LC in the future. Diagnostic tests currently available are unsuitable for widespread screening because they are costly, occasionally miss tumours, are not time-efficient, nor free of complications. LCAOS will overcome these problems by using an approach based on volatile biomarkers emitted from cell membranes. A multidisciplinary effort, incorporating nanotechnology, biomedical engineering, medical oncology, and computation strategies, will develop a highly-sensitive, inexpensive, and fast-response, non-invasive, artificial nose (known as, NaNose), building on the coordinators earlier success in this area. The NaNose will be able to detect pre-neoplastic volatile biomarkers that indicate an increased genetic risk of LC, and the presence of LC. It has already been established that these biomarkers can be detected either directly from the headspace of the cancer cells or via exhaled breath. LCAOS will: (i) develop arrays of chemically-sensitive field effect transistors (FETs) of non-oxidized, molecule-terminated silicon nanowires (Si NWs); (ii) test the ability of these devices to sense volatile LC biomarkers from in-vitro tissue, and exhaled human breath; (iii) study the signal transduction mechanism of the volatile biomarkers, using pattern recognition; (iv) improve systems to enable the NaNose to distinguish the targeted biomarkers from environmental clutter, using methylation, expression profiling, and genome-wide sequencing; and (v) perform clinical-related studies to assess LC conditions in actual patients & tissues, and in the presence of real-world confounding signals. Validation will be carried out by clinician partners and professional mathematicians and computer scientists. Resources will also be allocated to ensure the commercial potential of the sensor device layout.

Winkler K.,Ionimed Analytik GmbH | Herbig J.,Ionimed Analytik GmbH | Kohl I.,Ionimed Analytik GmbH
Journal of Breath Research | Year: 2013

We analysed the time evolution of several volatile organic compounds formed by the catabolism of ingested isotope-labelled ethanol using real-time breath gas analysis with proton-transfer-reaction mass spectrometry. Isotope labelling allowed distinguishing the emerging volatile metabolites from their naturally occurring, highly abundant counterparts in the human breath. Due to an extremely low detection limit of the employed technologies in the parts per trillion per volume range, it was possible to detect the emerging metabolic products in exhaled breath within ∼10 min after oral ingestion of isotope-labelled ethanol. We observed that ethanol was in part transformed into deuterated acetone and isoprene, reflecting the different fates of activated acetic acid (acetyl-coenzyme A), formed in ethanol metabolism. Using ethanol as a model clearly demonstrated the value of the here presented technique for the search for volatile markers for metabolic disorders in the exhaled breath and its potential usefulness in the diagnosis and monitoring of such diseases. © 2013 IOP Publishing Ltd.

Miekisch W.,University of Rostock | Herbig J.,Ionimed Analytik GmbH | Schubert J.K.,University of Rostock
Journal of Breath Research | Year: 2012

Most - if not all - potential diagnostic applications in breath research involve different marker concentrations rather than unique breath markers which only occur in the diseased state. Hence, data interpretation is a crucial step in breath analysis. To avoid artificial significance in breath testing every effort should be made to implement method validation, data cross-testing and statistical validation along this process. The most common data analysis related problems can be classified into three groups: confounding variables (CVs), which have a real correlation with both the diseased state and a breath marker but lead to the erroneous conclusion that disease and breath are in a causal relationship; voodoo correlations (VCs), which can be understood as statistically true correlations that arise coincidentally in the vast number of measured variables; and statistical misconceptions in the study design (SMSD). CV: Typical confounding variables are environmental and medical history, host factors such as gender, age, weight, etc and parameters that could affect the quality of breath data such as subject breathing mode, effects of breath sampling and effects of the analytical technique itself. VC: The number of measured variables quickly overwhelms the number of samples that can feasibly be taken. As a consequence, the chances of finding coincidental; voodoo correlations grow proportionally. VCs can typically be expected in the following scenarios: insufficient number of patients, (too) many measurement variables, the use of advanced statistical data mining methods, and non-independent data for validation. SMSD: Non-prospective, non-blinded and non-randomized trials, a priori biased study populations or group selection with unrealistically high disease prevalence typically represent misconception of study design. In this paper important data interpretation issues are discussed, common pitfalls are addressed and directions for sound data processing and interpretation are proposed. © 2012 IOP Publishing Ltd.

PubMed | Ionimed Analytik GmbH
Type: Journal Article | Journal: Journal of breath research | Year: 2013

We report on the search for low molecular weight molecules-possibly accumulated in the bloodstream and body-in the exhaled breath of uremic patients with kidney malfunction. We performed non-invasive analysis of the breath gas of 96 patients shortly before and several times after kidney transplantation using proton-transfer-reaction mass spectrometry (PTR-MS), a very sensitive technique for detecting trace amounts of volatile organic compounds. A total of 642 individual breath analyses which included at least 41 different chemical components were carried out. Correlation analysis revealed one particular breath component with a molecular mass of 114u (unified atomic mass units) that clearly correlated with blood serum creatinine, which is the currently accepted marker for assessing the function of the kidney. In particular, daily urine production showed good correlation with the identified breath marker. An independent set of seven samples taken from three patients at the onset of dialysis and three controls with normal kidney function confirmed a significant difference in concentration between patients and controls for a compound with a molecular mass of 114.1035u using high mass resolving proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS). A chemical composition of C7H14O was derived for the respective component. Fragmentation experiments on the same samples using proton-transfer-reaction triple-quadrupole tandem mass spectrometry (PTR-QqQ-MS) suggested that this breath marker is a C7-ketone or a branched C7-aldehyde. Non-invasive real-time monitoring of the kidney function via this breath marker could be a possible future procedure in the clinical setting.

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