Correlation analysis on data sets to detect infectious agents in the airways by ion mobility spectrometry of exhaled breath

A correlation analysis of peaks found in IMS-Chromatograms was carried out to show the potential of the method in clinical applications. As an example, the data of exhaled breath of patients suffering infections of Pseudomonas were compared to healthy non-smokers. Using a rank sum calculation and providing a correlation table of all peaks found, delivers the basis for visualisation of highest ranked analytes. In addition, a consideration of positive and negative correlated peaks could support sub-grouping, if present. A set of signals could be found for discriminating the two groups of patients using MCC-IMS. Investigations of exhaled breath using ion mobility spectrometry seems to provide a promising means for the non-invasive identification of patients which are colonized or infected with bacteria such as Pseudomonas aeruginosa.     

Detection of volatile organic compounds (VOCs) in exhaled breath of patients with chronic obstructive pulmonary disease (COPD) by ion mobility spectrometry

COPD is a disease characterised by a chronic inflammation of the airways and a not fully reversible airway obstruction. The spirometry is considered as gold-standard to diagnose the disease and to grade its severity. In this study we used the methodology of Ion Mobility Spectometry in order to detect Volatile Organic Compounds (VOCs) in exhaled breath of patients with COPD. The purpose of this study was to investigate if the VOCs detected in patients with COPD were different from the VOCs detected in exhaled breath of healthy controls. 13 COPD patients and 33 healthy controls were included in the study. Breath samples were collected via a side-steam Teflon tube and directly measured by an ion mobility spectrometer coupled to a multi capillary column (MCC/IMS). One peak was identified only in the patients group compared to the healthy control group. Consequently, the analysis of exhaled breath could be a useful tool to diagnose COPD.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

Human exhaled air analytics: biomarkers of diseases

Over the last few years, breath analysis for the routine monitoring of metabolic disorders has attracted a considerable amount of scientific interest, especially since breath sampling is a non-invasive technique, totally painless and agreeable to patients. The investigation of human breath samples with various analytical methods has shown a correlation between the concentration patterns of volatile organic compounds (VOCs) and the occurrence of certain diseases. It has been demonstrated that modern analytical instruments allow the determination of many compounds found in human breath both in normal and anomalous concentrations. The composition of exhaled breath in patients with, for example, lung cancer, inflammatory lung disease, hepatic or renal dysfunction and diabetes contains valuable information. Furthermore, the detection and quantification of oxidative stress, and its monitoring during surgery based on composition of exhaled breath, have made considerable progress. This paper gives an overview of the analytical techniques used for sample collection, preconcentration and analysis of human breath composition. The diagnostic potential of different disease-marking substances in human breath for a selection of diseases and the clinical applications of breath analysis are discussed.     

人体呼出气中挥发性有机化合物的检测方法

呼出气检测作为一种潜在的新型临床检测手段受到广泛关注。本文详细综述了人体呼出气中挥发性有机化合物(VOCs)的各类检测方法和技术,分别对色谱法、质谱法和光谱及传感器法的原理、特点和最新研究进展进行了介绍,对照总结了目前已确定的异戊二烯、丙酮等疾病生物标志物的各种分析方法和实测数据,并展望了未来的研究动向。     

纳米材料在用于癌症诊断的呼出气挥发性有机物检测中的应用

细胞新陈代谢的变化会导致挥发性有机化合物（VOCs）类型及含量发生变化,因此可通过分析某些标志性VOCs简立起多种疾病早期诊断的模型. 人体呼出物中特征VOCs的检测作为一种非侵入性、无损的检测手段,近些年在疾病检测领域已成为世界范围内的研究热点. 其中,纳米材料可用于增强传感器性能,并使传感器便携式小型化,推进检测传感器进入临床. 在这篇综述中,作者将种类繁多的传感器中用到的纳米材料归纳总结为金属、金属氧化物、碳基、复合物和MOFs基纳米材料等几类,并讨论了不同类纳米材料在VOCs检测中的优劣势. 本文所建立起的分析方法及讨论有助于进一步了解检测技术的优越性与局限性. 最后,作者对利用VOCs的检测实现癌症早期筛选的研究及发展提出了个人观点.     

Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry

Human breath analysis is a powerful and especially a non-invasive technique for the monitoring and hopefully also for the diagnosis of respiratory diseases, including chronic obstructive pulmonary disease (COPD). The exhaled breath of 95 patients suffering COPD and of 35 healthy controls was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. Starting with the results from a Mann–Whitney-Wilcoxon rank sum test to find analytes with the highest potential with respect to differentiation, box and whisker plots, metabolic maps and probability charts were introduced and compared. In addition, the sensitivity, specificity, positive and negative predictive values and the accuracy of the relation were also summarized. The findings were compared to the results of a principal component analysis. Finally, decision trees were introduced to visualize the interdependencies between the analytes and the classifications. The application of these biostatistical methods with simultaneous inclusion of several VOCs for disease classification by ion mobility spectrometry of human breath will provide much more information than using single peaks and single concentration dependencies for disease classification and discrimination of various groups. Towards the future application of potential biomarkers for clinical diagnostic procedures, complex analytical methods, such as ion mobility spectrometry, need statistical and bioinformatical tools which are simple in application, visualize the results and support decisions on the basis of the data obtained from measurements of analytes in exhaled human breath.     

Volatile Organic Compounds Analysis in Breath Air in Healthy Volunteers and Patients Suffering Epidermoid Laryngeal Carcinomas

Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that may be used as non-invasive markers of head and neck epidermoid cancer. We hypothesized that solid phase micro-extraction coupled to gas chromatography–mass spectrometry can discriminate patients with epidermoid head and neck cancer from healthy controls by analyzing the gaseous volatile organic compounds, VOC-profile, in exhaled breath, thus identifying some non-invasive biomarkers to be used in early detection. Twenty healthy subjects participated in a cross-sectional study plus 11 patients with epidermoid supraglottic laryngeal cancer. VOCs from T3 supraglottic cancer were clustered distinctly from those of T1 and healthy subjects. Up to seven VOCs were detected differently from healthy volunteers, mainly 2-butanone and ethanol. Thus VOC-patterns of exhaled breath may discriminate patients with epidermoid head and neck cancer from healthy controls.     

Detection of human metabolites using multi-capillary columns coupled to ion mobility spectrometers

The human breath contains indicators of human health and delivers information about different metabolism processes of the body. The detection and attribution of these markers provide the possibility for new, non-invasive diagnostic methods. In the recent study, ion mobility spectrometers are used to detect different volatile organic metabolites in human breath directly. By coupling multi-capillary columns using ion mobility spectrometers detection limits down to the ng/L and pg/L range are achieved. The sampling procedure of human breath as well as the detection of different volatiles in human breath are described in detail. Reduced mobilities and detection limits for different analytes occurring in human breath are reported. In addition, spectra of exhaled air using ion mobility spectrometers obtained without any pre-concentration are presented and discussed in detail. Finally, the potential use of IMS with respect to lung infection diseases will be considered.     

Colorimetric Artificial Nose for Identification of Breath Volatile Organic Compounds of Patients with Lung Cancer

A novel and highly sensitive colorimetric sensor array was developed for the detection and identification of breath volatile organic compounds（VOCs） of patients with lung cancer.Employing dimeric metalloporphyrins,metallosalphen complexes,and chemically responsive dyes as the sensing elements,the developed sensor array of artificial nose shows a unique pattern of colorific changes upon its exposure to eight less-reactive VOCs and their mixture gas at a concentration of 735 nmol/L within 3 min.Potential of quantitative analysis of VOCs samples was proved.A good linear relationship of 490-3675 nmol/L was obtained for benzene vapor with a detection limit of 49 nmol/L（S/N=3）.Data analysis was carried out by Hierarchical cluster analysis（HCA） and principal component analysis（PCA）.Each category of breath VOCs clusters together in the PCA score plot.No errors in classification by HCA were observed in 45 trials.Additionaly,the colorimetric sensor array showed good reproducibility under the cyclic sensing experiments.These results demonstrate that the developed colorimetric artificial nose system is an excellent sensing platform for the identification and quantitative analysis of breath VOCs of patients with lung cancer.     

Comprehensive Two-Dimensional Gas Chromatography–Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography–mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.     

Signals in human breath related to Sarcoidosis. — Results of a feasibility study using MCC/IMS

Using a ⁶³Ni—Ion Mobility Spectrometer (IMS) coupled with a Multi-Capillary Column (MCC) the signals obtained are considered to identify characteristic peaks of volatile compounds in exhaled human breath samples of 10 mL volume. The breath of 20 patients with sarcoidosis and suspicion of sarcoidosis because of mediastinal lymp node enlargement was investigated. It could be shown that a procedure related to a single peak in the IMS-chromatogram delivers a differentiation into the two groups of patients with confirmed sarcoidosis and such suffering no sarcoidosis. The potential biomarker is characterised by the following parameters inverse mobility (1/K₀) 0.53 ± 0.01 Vs/cm²—retention time 22 ± 5 s. These results are a first step in breath analysis by MCC/IMS in patients with sarcoidosis.     

Software tool for coupling chromatographic total ion current dependencies of GC/MSD and MCC/IMS

More than 90,000 ion mobility spectrometer (IMS) are in use worldwide, mostly without coupling to chromatographic columns for pre-separation of the neutrals entering the ionization region of the IMS. Related to new application fields e.g. breath analysis or determination of volatile metabolites of cell cultures and bacteria/fungi an effective way for pre-separation is needed strongly. The acceptance of IMS within the analytical world will be enhanced by supplying automatic procedures for peak finding, referencing and database-related identification of the signals within IMS-Chromatograms. Some papers are available concerning the internal loop of relation of IMS signals between different instruments, alignment for automatic interpretation with respect of reference analytes used and interpolation within the different members of classes of analytes in case that some missed e.g. within a homologous row of chemicals. With respect to inter comparison of recent findings using MCC/IMS and GC/MS experiments effective alignment procedures are developed. In the present paper we describe a software tool making the visualization of the total ion current (TIC) from chromatograms of GC/MSD possible in direct relation to the corresponding IMS-Chromatogram of MCC/IMS. Thus, parallel measurements of e.g. samples of human breath using MCC/IMS and thermodesorption (TD)-GC/MSD become comparable directly. On the other hand, the direct identification and relation of so far unknown peaks found in IMS-Chromatograms will be supported using the TIC results of GC/MSD.     

A novel microreactor approach for analysis of ketones and aldehydes in breath

We report a fabricated microreactor with thousands of micropillars in channels. Each micropillar surface is chemically functionalized to selectively preconcentrate gaseous ketones and aldehydes of exhaled breath and to enhance ultra-trace, rapid analysis by direct-infusion Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry (MS). The micropillar reactive coating contains the quaternary ammonium aminooxy salt 2-(aminooxy)ethyl-N,N,N-trimethylammonium iodide (ATM) for capturing trace carbonyl VOCs by means of an oximation reaction. We demonstrate the utility of this approach for detection of C(1) to C(12) aldehydes and ketones in exhaled breath, but the approach is applicable to any gaseous sample.     

Fast screening for presence of muddy/earthy odorants in wine and in wine must using a hyphenated gas chromatography-differential ion mobility spectrometry (GC/DMS)

Rapid, hyphenated detection techniques involving a gas chromatograph (GC) coupled to a classical time-of-flight ion mobility (IMS) spectrometer, or more recently, to a micro-machined, miniature differential ion mobility spectrometer (DMS) are quite attractive for in-situ detection of many kinds of volatile organic compounds (VOCs) of concern and notably of natural contaminants appearing in the headspaces of selected foodstuff. This work aims at a rapid detection, identification and quantification of geosmin in the headspace of grape must and of wine. Samples of white and red wines have both been analyzed with a hyphenated GC/DMS and by Solid Phase Micro-Extraction (SPME) coupled to GC/MS taken as a reference. The detection of geosmin at concentrations below the human olfactory threshold of 50 ng/L has been demonstrated.     

New MSPQC Method for Rapid Identification and Quantification of Pseudomonas aeruginosa

Abstract

A new method for the rapid identification and quantification of Pseudomonas aeruginosa using multichannel series piezoelectric quartz crystal (MSPQC) was proposed. The identification of P. aeruginosa was based on the development of acetamide broth, which can selective culture P. aeruginosa and performed perfectly in MSPQC. The quantitative detection of P. aeruginosa was based on the fact that the frequency detection time (FDT) detected by MSPQC in developed medium had a linear relationship with the logarithm of its initial concentration in the range of 10–10⁸ colony ? forming units (cfu) ml^–1 (R=?0.984). The detection limit was 10 cfu ml^–1.     

Non-labeling multiplex surface enhanced Raman scattering (SERS) detection of volatile organic compounds (VOCs)

In this paper, we report multiplex SERS based VOCs detection with a leaning nano-pillar substrate. The VOCs analyte molecules adsorbed at the tips of the nano-pillars produced SERS signal due to the field enhancement occurring at the localized surface plasmon hot spots between adjacent leaning nano-pillars. In this experiment, detections of acetone and ethanol vapor at different concentrations were demonstrated. The detection limits were found to be 0.0017 ng and 0.0037 ng for ethanol and acetone vapor molecules respectively. Our approach is a non-labeling method such that it does not require the incorporation of any chemical sensing layer for the enrichment of gas molecules on sensor surface. The leaning nano-pillar substrate also showed highly reproducible SERS signal in cyclic VOCs detection, which can reduce the detection cost in practical applications. Further, multiplex SERS detection on different combination of acetone and ethanol vapor was also successfully demonstrated. The vibrational fingerprints of molecular structures provide specific Raman peaks for different VOCs contents. To the best of our knowledge, this is the first multiplex VOCs detection using SERS. We believe that this work may lead to a portable device for multiplex, specific and highly sensitive detection of complex VOCs samples that can find potential applications in exhaled breath analysis, hazardous gas analysis, homeland security and environmental monitoring.     

Identification of volatile lung cancer markers by gas chromatography–mass spectrometry: comparison with discrimination by canines

In this work, a chromatographic method for identification of volatile organic compounds was compared with canine recognition. Gas chromatography and mass spectrometry (GC-TOF MS) were used for determination of concentrations of trace gases present in human breath. The technique enables rapid determination of compounds in human breath, at the parts per billion level. Linear correlations were from 0.83-234.05 ppb, the limit of detection was the range 0.31-0.75 ppb, and precision, expressed as relative standard deviation (RSD), was less than 10.00 %. Moreover, trained dogs are able to discriminate breath samples of patients with diagnosed cancer. We found a positive correlation between dog indications and the ethyl acetate and 2-pentanone content of breath (r = 0.85 and r = 0.97, respectively). The methods presented for detection of lung cancer markers in exhaled air could be used as a potential non-invasive tool for screening. In addition, the canine method is relatively simple and inexpensive in comparison with chromatography.     

Sampling and analysis of volatile organic compounds in bovine breath by solid-phase microextraction and gas chromatography-mass spectrometry

A relatively noninvasive method consisting of a face mask sampling device, solid-phase microextraction (SPME) fibers, and a gas chromatography-mass spectrometry (GC-MS) for the identification of volatile organic compounds (VOCs) in bovine breath was developed. Breath of three morbid steers with respiratory tract infections and three healthy steers were sampled seven times in 19 days for 15 min at each sampling. The breath VOCs adsorbed on the divinylbenzene (DVB)-Carboxen-polydimethyl siloxane (PDMS) 50/30 microm SPME fibers were transported to a laboratory GC-MS system for separation and identification with an in-house spectral library of standard chemicals. A total of 21 VOCs were detected, many of them for the first time in cattle breath. Statistical analyses using Chi-square test on the frequency of detection of each VOC in each group was performed. The presence of acetaldehyde (P < or = 0.05) and decanal (P < or = 0.10) were associated more with clinically morbid steers while methyl acetate, heptane, octanal, 2,3-butadione, hexanoic acid, and phenol were associated with healthy steers at P < or = 0.10. The results suggest that noninvasive heath screening using breath analyses could become a useful diagnostic tool for animals and humans.     

Human breath analysis: methods for sample collection and reduction of localized background effects

Solid-phase microextraction (SPME) was applied, in conjunction with gas chromatography–mass spectrometry, to the analysis of volatile organic compounds (VOCs) in human breath samples without requiring exhaled breath condensate collection. A new procedure, exhaled breath vapor (EBV) collection, involving the active sampling and preconcentration of a breath sample with a SPME fiber fitted inside a modified commercial breath-collection device, the RTube™, is described. Immediately after sample collection, compounds are desorbed from the SPME fiber at 250 °C in the GC-MS injector. Experiments were performed using EBV collected at −80 °C and at room temperature, and the results compared to the traditional method of collecting exhaled breath condensate at −80 °C followed by passive SPME sampling of the collected condensate. Methods are compared in terms of portability, ease-of-use, speed of analysis, and detection limits. The need for a clean air supply for the study subjects is demonstrated using several localized sources of VOC contaminants including nail polish, lemonade, and gasoline. Various simple methods to supply clean inhaled air to a subject are presented. Chemical exposures are used to demonstrate the importance of providing cleaned air (organic vapor respirator) or an external air source (tubing stretched to a separate room). These techniques allow for facile data interpretation by minimizing background contaminants. It is demonstrated herein that this active SPME breath-sampling device provides advantages in the forms of faster sample collection and data analysis, apparatus portability and avoidance of power or cooling requirements, and performance for sample collection in a contaminated environment.