Statistical analysis of MCC-IMS data for two group comparisons-an exemplary study on two devices.

The Multi-capillary-column-Ion-mobility-spectrometry (MCC-IMS) technology for measuring breath gas can be used for distinguishing between healthy and diseased subjects or between different types of diseases. The statistical methods for classifying the corresponding breath samples typically neglects potential confounding clinical and technical variables, reducing both accuracy and generalizability of the results. Especially measuring samples on different technical devices can heavily influence the results. We conducted a controlled breath gas study including 49 healthy volunteers to evaluate the effect of the variables sex, smoking habits and technical device. Every person was measured twice, once before and once after consuming a glass of orange juice. The two measurements were obtained on two different devices. The evaluation of the MCC-IMS data regarding metabolite detection was performed once using the software VisualNow, which requires manual interaction, and once using the fully automated algorithm SGLTR-DBSCAN. We present statistical solutions, peak alignment and scaling, to adjust for the different devices. For the other potential confounders sex and smoking, in our study no significant influence was identified.

Integrated statistical learning of metabolic ion mobility spectrometry profiles for pulmonary disease identification.

Exhaled air carries information on human health status. Ion mobility spectrometers combined with a multi-capillary column (MCC/IMS) is a well-known technology for detecting volatile organic compounds (VOCs) within human breath. This technique is relatively inexpensive, robust and easy to use in every day practice. However, the potential of this methodology depends on successful application of computational approaches for finding relevant VOCs and classification of patients into disease-specific profile groups based on the detected VOCs. We developed an integrated state-of-the-art system using sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy controls and COPD patients (best accuracy COPD vs CG: 94%). However, further examination of the impact of bronchial carcinoma on COPD/no-COPD classification performance is necessary (best accuracy CG vs COPD vs COPD + BC: 79%). We also extracted 20 high-scoring VOCs that allowed differentiating COPD patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to well-structured, medical MCC/IMS data.

Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of patients with lung cancer: results of a pilot study.

BACKGROUND: Analysis of exhaled breath, especially of volatile organic compounds (VOCs), is of increasing interest in the diagnosis of lung cancer. Compared with other methods of breath analysis, ion mobility spectrometry (IMS) offers a tenfold higher detection rate of VOCs. By coupling the ion mobility spectrometer with a multicapillary column as a pre-separation unit, IMS offers the advantage of an immediate twofold separation of VOCs with visualisation in a three-dimensional chromatogram. The total analysis time is about 500 s compared with gas chromatography/mass spectrometry (GC/MS) of about 1 h. It therefore seemed reasonable to test IMS in breath analysis. METHODS: In a pilot study, 32 patients with lung cancer were subjected to a breath analysis by IMS. Their IMS chromatograms were compared with those of 54 healthy controls. An IMS that was built for special clinical application was used to identify characteristic peaks of VOCs which might be relevant for the diagnosis of lung cancer in exhaled air of 10 ml volume. RESULTS: By a combination of 23 peak regions within the IMS chromatogram, patients with lung cancer, including a patient with carcinoma in situ, were classified and differentiated from healthy persons with an error rate of zero. CONCLUSION: Breath analysis by IMS can detect a discriminating combination of VOCs in patients with lung cancer. By pattern recognition without the need for chemical analysis of the underlying VOCs, IMS has the potential to facilitate lung cancer diagnosis.

Ion mobility spectrometry of gas-phase ions from laser ablation of solids in air at ambient pressure.

A mobility spectrometer was used to characterize gas-phase ions produced from laser ablation of solids in air at 100 degrees C and at ambient pressure with a beam focused to a diameter of

Role of undecan-2-one on ethanol-induced apoptosis in HepG2 cells.

Based on the reduced expression of ethanol-oxidizing enzymes in human hepatocellular carcinoma (HepG2) cells, we analyzed the role of nonoxidative metabolites in ethanol-induced apoptosis in HepG2 cells. For this purpose, an analysis of volatile metabolites of ethanol using ion-mobility spectrometry and gas chromatography-mass spectrometry was performed. HepG2 cells exposed to 1 mmol/L ethanol exhibited significant synthesis of undecan-2-one compared to untreated cells. Undecan-2-one is a fatty acid ethyl ester metabolite synthesized through a nonoxidative pathway. Undecan-2-one had a dose-dependent cytotoxic effect on HepG2 cells as shown by release of lactate dehydrogenase (LDH). The most notable finding of this study was the potentiation of ethanol-induced apoptosis demonstrated by an increased apoptotic rate induced by undecan-2-one in ethanol-treated HepG2 cells. The data presented in this study contribute to the better understanding of the molecular mechanisms of ethanol exposure at low concentration in HepG2 cells, a human hepatocellular carcinoma-derived cell line.

Detection of sulfur-free odorants in natural gas using ion mobility spectrometry.

Beside the primary motivation of the public gas suppliers for odorizing natural gas with a sulfur-free odorant, which relates to the image of the environment-friendly fuel, natural gas, competing with low-sulfur heating fuel and diesel, a question of crucial importance of how to detect such sulfur-free odorants comes up. Concerning the replacement of sulfur-containing by sulfur-free odorization, the availability of a fast and sensitive detection method that can, further, be used on-site plays a key role. The minimum concentration of the new sulfur-free odorant Gasodor S-Free (S-Free) in natural gas should be added at a level of at least 8.8 mg m(-3) to assure a significant warning smell. Therefore, a dynamic range between 0 and approx. 25 mg m(-3) must be realised in the rather complex matrix of natural gas. By means of a handheld ion mobility spectrometer, the odorant content in natural gas is determined within less than 80 s total analysis time directly at the gas pipe. The concentration of S-Free is monitored between 4 and 23 mg m(-3) respecting the quality of the natural gas (high- and low-caloric gas). Results of the validation using a gas chromatograph as a reference standard will be discussed in detail.

Ion mobility spectrometry in the diagnosis of sarcoidosis: results of a feasibility study.

A feasibility study with ion mobility spectrometry (IMS) was started to find characteristic peaks of volatile organic compounds in exhaled air of 10 mL sampling volume, which might be relevant for the diagnosis of sarcoidosis. Therefore, breath samples of 9 patients with sarcoidosis and suspicion of sarcoidosis because of mediastinal lymph node enlargement were investigated. The 5 patients with confirmed sarcoidosis showed a highly congruent distribution of metabolites in exhaled air which was different in main component analyses from patients with unspecific mediastinal lymph node enlargement. These results are a first step in breath analysis by IMS in patients with sarcoidosis. The IMS as a new method in breath analysis and the first results of the investigations are presented and discussed in detail.