69 research outputs found

    Direct detection and quantification of malondialdehyde vapour in humid air using selected ion flow tube mass spectrometry supported by gas chromatography/mass spectrometry

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    RATIONALE: It has been proposed that malondialdehyde (MDA) reflects free oxygen-radical lipid peroxidation and can be useful as a biomarker to track this process. For the analysis of MDA molecules in humid air by selected ion flow tube mass spectrometry (SIFT-MS), the rate coefficients and the ion product distributions for the reactions of the SIFT-MS reagent ions with volatile MDA in the presence of water vapour are required. METHODS: The SIFT technique has been used to determine the rate coefficients and ion product distributions for the reactions of H3O(+), NO(+) and O2 (+•) with gas-phase MDA. In support of the SIFT-MS analysis of MDA, solid-phase microextraction, SPME, coupled with gas chromatography/mass spectrometry, GC/MS, has been used to confirm the identification of MDA. RESULTS: The primary product ions have been identified for the reactions of H3O(+), NO(+) and O2 (+•) with MDA and the formation of their hydrates formed in humid samples is described. The following combinations of reagent and the analyte ions (given as m/z values) have been adopted for SIFT-MS analyses of MDA in the gas phase: H3O(+): 109; NO(+): 89, 102; O2 (+•): 72, 90, 108, 126. The detection and quantification of MDA released by a cell culture by SIFT-MS are demonstrated. CONCLUSIONS: This detailed study has provided the kinetics data required for the SIFT-MS analysis of MDA in humid air, including exhaled breath and the headspace of liquid-phase biogenic media. The detection and quantification by SIFT-MS of MDA released by a cell culture are demonstrated. Copyright © 2015 John Wiley & Sons, Ltd

    Volatile organic compounds in breath can serve as a non-invasive diagnostic biomarker for the detection of advanced adenomas and colorectal cancer

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    Contains fulltext : 220031.pdf (Publisher’s version ) (Open Access)BACKGROUND: Colorectal cancer (CRC) is the third most common cancer diagnosis in the Western world. AIM: To evaluate exhaled volatile organic compounds (VOCs) as a non-invasive biomarker for the detection of CRC and precursor lesions using an electronic nose. METHODS: In this multicentre study adult colonoscopy patients, without inflammatory bowel disease or (previous) malignancy, were invited for breath analysis. Two-thirds of the breath tests were randomly assigned to develop training models which were used to predict the diagnosis of the remaining patients (external validation). In the end, all data were used to develop final-disease models to further improve the discriminatory power of the algorithms. RESULTS: Five hundred and eleven breath samples were collected. Sixty-four patients were excluded due to an inadequate breath test (n = 51), incomplete colonoscopy (n = 8) or colitis (n = 5). Classification was based on the most advanced lesion found; CRC (n = 70), advanced adenomas (AAs) (n = 117), non-advanced adenoma (n = 117), hyperplastic polyp (n = 15), normal colonoscopy (n = 125). Training models for CRC and AAs had an area under the curve (AUC) of 0.76 and 0.71 and blind validation resulted in an AUC of 0.74 and 0.61 respectively. Final models for CRC and AAs yielded an AUC of 0.84 (sensitivity 95% and specificity 64%) and 0.73 (sensitivity and specificity 79% and 59%) respectively. CONCLUSIONS: This study suggests that exhaled VOCs could potentially serve as a non-invasive biomarker for the detection of CRC and AAs. Future studies including more patients could further improve the discriminatory potential of VOC analysis for the detection of (pre-)malignant colorectal lesions. (https://clinicaltrials.gov Identifier NCT03488537)

    Laser spectroscopy for breath analysis : towards clinical implementation

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    Detection and analysis of volatile compounds in exhaled breath represents an attractive tool for monitoring the metabolic status of a patient and disease diagnosis, since it is non-invasive and fast. Numerous studies have already demonstrated the benefit of breath analysis in clinical settings/applications and encouraged multidisciplinary research to reveal new insights regarding the origins, pathways, and pathophysiological roles of breath components. Many breath analysis methods are currently available to help explore these directions, ranging from mass spectrometry to laser-based spectroscopy and sensor arrays. This review presents an update of the current status of optical methods, using near and mid-infrared sources, for clinical breath gas analysis over the last decade and describes recent technological developments and their applications. The review includes: tunable diode laser absorption spectroscopy, cavity ring-down spectroscopy, integrated cavity output spectroscopy, cavity-enhanced absorption spectroscopy, photoacoustic spectroscopy, quartz-enhanced photoacoustic spectroscopy, and optical frequency comb spectroscopy. A SWOT analysis (strengths, weaknesses, opportunities, and threats) is presented that describes the laser-based techniques within the clinical framework of breath research and their appealing features for clinical use.Peer reviewe

    Tvorba a zánik komplexních molekulárních iontů v plynné fázi

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    Katedra fyziky povrchů a plazmatuDepartment of Surface and Plasma ScienceFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

    Teoretické studium difúze iontů dúležitých pro analýzu dechu metodou SIFT-MS

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    Accuracy of quantitative Selected Ion Flow Tube Mass Spectrometry SIFT-MS is ultimately determined by the proper accounting in the data analysis for the effect of differential diffusion. Diffusion loss of the product ions can be typically lower by a factor of up to 3 in comparison with the precursor ions. Hard sphere model of diffusion of polyatomic ions in helium has been used to calculate diffusion coefficients of the precursor and product ions involved in SIFT-MS quantification of common breath metabolites ammonia, acetone, isoprene, acetaldehyde and ethanol. Calculation involves semiempirical PM3 method for determination of the geometries of the ions, numerical averaging of the geometrical cross section for collisions with helium atoms and construction of a model interaction (12, 4) model potential followed by the analytical calculation of ionic mobility using momentum-transfer collision integral. Finally the values of diffusion enhancement factors have been calculated

    Increase of methanol in exhaled breath quantified by SIFT-MS following aspartame ingestion

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    Aspartame, methyl-L-α-aspartyl-L-phenylalaninate, is used worldwide as a sweetener in foods and drinks and is considered to be safe at an acceptable daily intake (ADI) of 40 mg per kg of body weight. This compound is completely hydrolyzed in the gastrointestinal tract to aspartic acid, phenylalanine and methanol, each being toxic at high levels. The objective of the present study was to quantify the volatile methanol component in the exhaled breath of ten healthy volunteers following the ingestion of a single ADI dose of aspartame. Direct on-line measurements of methanol concentration were made in the mouth and nose breath exhalations using selected ion flow tube mass spectrometry, SIFT-MS, several times before aspartame ingestion in order to establish individual pre-dose (baseline) levels and then during two hours post-ingestion to track their initial increase and subsequent decrease. The results show that breath methanol concentrations increased in all volunteers by 1082   ±   205 parts-per-billion by volume (ppbv) from their pre-ingestion values, which ranged from 193 to 436 ppbv to peak values ranging from 981-1622 ppbv, from which they slowly decreased. These observations agree quantitatively with a predicted increase of 1030 ppbv estimated using a one-compartment model of uniform dilution of the methanol generated from a known amount of aspartame throughout the total body water (including blood). In summary, an ADI dose of aspartame leads to a 3-6 fold increase of blood methanol concentration above the individual baseline values
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