Simultaneous analysis of 28 urinary VOC metabolites using ultra high performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (UPLC-ESI/MSMS)

Volatile organic compounds (VOCs) are ubiquitous in the environment, originating from many different natural and anthropogenic sources, including tobacco smoke. Long-term exposure to certain VOCs may increase the risk for cancer, birth defects, and neurocognitive impairment. Therefore, VOC exposure is an area of significant public health concern. Urinary VOC metabolites are useful biomarkers for assessing VOC exposure because of non-invasiveness of sampling and longer physiological half-lives of urinary metabolites compared with VOCs in blood and breath. We developed a method using reversed-phase ultra high performance liquid chromatography (UPLC) coupled with electrospray ionization tandem mass spectrometry (ESI/MSMS) to simultaneously quantify 28 urinary VOC metabolites as biomarkers of exposure. We describe a method that monitors metabolites of acrolein, acrylamide, acrylonitrile, benzene, 1-bromopropane, 1,3-butadiene, carbon-disulfide, crotonaldehyde, cyanide, N,N-dimethylformamide, ethylbenzene, ethylene oxide, propylene oxide, styrene, tetrachloroethylene, toluene, trichloroethylene, vinyl chloride and xylene. The method is accurate (mean accuracy for spiked matrix ranged from 84 to104%), sensitive (limit of detection ranged from 0.5 to 20 ng mL⁻¹) and precise (the relative standard deviations ranged from 2.5 to 11%). We applied this method to urine samples collected from 1203 non-smokers and 347 smokers and demonstrated that smokers have significantly elevated levels of tobacco-related biomarkers compared to non-smokers. We found significant (p < 0.0001) correlations between serum cotinine and most of the tobacco-related biomarkers measured. These findings confirm that this method can effectively quantify urinary VOC metabolites in a population exposed to volatile organics.     

Comparison of Targeted and Untargeted Approaches in Breath Analysis for the Discrimination of Lung Cancer from Benign Pulmonary Diseases and Healthy Persons

The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.     

Significant different volatile biomarker during bronchoscopic ion mobility spectrometry investigation of patients suffering lung carcinoma

Exhaled breath of patients suffering non-small bronchial carcinoma contains volatile organic compounds (VOC) different from healthy people. VOCs could be detected using ion mobility spectrometry down to the pg/L range even in air directly. To date, the origin of the different VOCs found is insecure. Such VOCs could be a direct product of the metabolism of the tumor or relatable to mostly present co-factors like infections or necrosis or a reaction of the human organism to the tumor (e.g. oxidativ stress). In the present study the breath of 19 patients suffering from confirmed NSCLC (non-small-cell lung carcinoma) with different histological types was investigated. In all cases flexible video-chip bronchoscopy was realized. Before taking samples for histological investigations in the lung on both main bronchi, samples of air were taken using a polytetrafluoroethylene (PTFE or Teflon) tube as catheter directly from the working channel of a bronchoscope and connected directly to the inlet of the ion mobility spectrometer. The measurement was started immediately. In total, 72 common peaks could be identified. 5 Peaks were significantly varying between the tumor site and the collateral lung. Considering adenocarcinoma, one peak separates both sites clearly and was relatable to the dimer of n-Dodecane. Two peaks were found on squamous cell carcinoma and relatable to 2-Butanol or 2-Methylfuran and Nonanal. The sensitivity, specificity, positive and negative predictive values were, for adenocarcinoma 100%, 75%, 80% and 100%, respectively – for squamous cell carcinoma 78%/78%, 67%/78%, 70%/80% and 75%/88%, for 2-Butanol and Nonanal respectively. Therefore, VOCs obtained from bronchoscopic sampling of breath could be detected using ion mobility spectrometry. The present study suggests that lung carcinoma with different histology will be represented by different volatile analytes.     

Pilot Study on Exhaled Breath Analysis for a Healthy Adult Population in Hawaii

Fast diagnostic results using breath analysis are an anticipated possibility for disease diagnosis or general health screenings. Tests that do not require sending specimens to medical laboratories possess capabilities to speed patient diagnosis and protect both patient and healthcare staff from unnecessary prolonged exposure. The objective of this work was to develop testing procedures on an initial healthy subject cohort in Hawaii to act as a range-finding pilot study for characterizing the baseline of exhaled breath prior to further research. Using comprehensive two-dimensional gas chromatography (GC×GC), this study analyzed exhaled breath from a healthy adult population in Hawaii to profile the range of different volatile organic compounds (VOCs) and survey Hawaii-specific differences. The most consistently reported compounds in the breath profile of individuals were acetic acid, dimethoxymethane, benzoic acid methyl ester, and n-hexane. In comparison to other breathprinting studies, the list of compounds discovered was representative of control cohorts. This must be considered when implementing proposed breath diagnostics in new locations with increased interpersonal variation due to diversity. Further studies on larger numbers of subjects over longer periods of time will provide additional foundational data on baseline breath VOC profiles of control populations for comparison to disease-positive cohorts.     

Breathing Rhythm Variations during Wash-In Do Not Influence Exhaled Volatile Organic Compound Profile Analyzed by an Electronic Nose

E-noses are innovative tools used for exhaled volatile organic compound (VOC) analysis, which have shown their potential in several diseases. Before obtaining a full validation of these instruments in clinical settings, a number of methodological issues still have to be established. We aimed to assess whether variations in breathing rhythm during wash-in with VOC-filtered air before exhaled air collection reflect changes in the exhaled VOC profile when analyzed by an e-nose (Cyranose 320). We enrolled 20 normal subjects and randomly collected their exhaled breath at three different breathing rhythms during wash-in: (a) normal rhythm (respiratory rate (RR) between 12 and 18/min), (b) fast rhythm (RR > 25/min) and (c) slow rhythm (RR < 10/min). Exhaled breath was collected by a previously validated method (Dragonieri et al., J. Bras. Pneumol. 2016) and analyzed by the e-nose. Using principal component analysis (PCA), no significant variations in the exhaled VOC profile were shown among the three breathing rhythms. Subsequent linear discriminant analysis (LDA) confirmed the above findings, with a cross-validated accuracy of 45% (p = ns). We concluded that the exhaled VOC profile, analyzed by an e-nose, is not influenced by variations in breathing rhythm during wash-in.     

Wounding-Induced VOC Emissions in Five Tropical Agricultural Species

Leaf mechanical wounding triggers a rapid release—within minutes—of a blend of volatile organic compounds. A wounding-induced VOC blend is mainly composed of oxygenated ubiquitous stress volatiles such as methanol and volatile products of lipoxygenase (LOX) pathway (mainly C5 and C6 alcohols and aldehydes and their derivatives), but also includes multiple minor VOCs that collectively act as infochemicals, inducing defences in non-damaged plant leaves and neighbouring plants and attracting herbivore enemies. At present, the interspecific variability of the rate of induction and magnitude of wounding-induced emissions and the extent to which plant structural traits and physiological activity alter these emissions are poorly known. Particularly scarce is information on the induced emissions in tropical agricultural plant species, despite their economic importance and large area of cultivation at regional and global scales. We chose five tropical crops with varying photosynthetic activity and leaf structural characteristics—Abelmoschus esculentus, Amaranthus cruentus, Amaranthus hybridus, Solanum aethiopicum, and Telfairia occidentalis—to characterize the kinetics and magnitude of wounding-induced emissions, hypothesizing that the induced emission response is greater and faster in physiologically more active species with greater photosynthetic activity than in less active species. Rapid highly repeatable leaf wounds (12 mm cuts) were generated by a within-leaf-chamber cutting knife. Wounding-induced VOC emissions were measured continuously with a proton-transfer reaction time-of-flight mass spectrometer and gas-chromatography mass spectrometry was used to separate isomers. Twenty-three ion VOCs and twelve terpenoid molecule structures were identified, whereas ubiquitous stress volatiles methanol (on average 40% of total emissions), hexenal (24%), and acetaldehyde (11%) were the main compounds across the species. Emissions of low-weight oxygenated compounds (LOC, 70% of total) and LOX products (29%) were positively correlated across species, but minor VOC components, monoterpenoids and benzenoids, were negatively correlated with LOC and LOX, indicating a reverse relationship between signal specificity and strength. There was a large interspecific variability in the rate of induction and emission magnitude, but the hypothesis of a stronger emission response in physiologically more active species was only partly supported. In addition, the overall emission levels were somewhat lower with different emission blend compared to the data reported for wild species, as well as different shares for the VOCs in the blend. The study demonstrates that wounding-dependent emissions from tropical agricultural crops can significantly contribute to atmospheric volatiles, and these emissions cannot be predicted based on current evidence of wild plant model systems.     

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.     

Breath Analysis: Comparison among Methodological Approaches for Breath Sampling

Despite promising results obtained in the early diagnosis of several pathologies, breath analysis still remains an unused technique in clinical practice due to the lack of breath sampling standardized procedures able to guarantee a good repeatability and comparability of results. The most diffuse on an international scale breath sampling method uses polymeric bags, but, recently, devices named Mistral and ReCIVA, able to directly concentrate volatile organic compounds (VOCs) onto sorbent tubes, have been developed and launched on the market. In order to explore performances of these new automatic devices with respect to sampling in the polymeric bag and to study the differences in VOCs profile when whole or alveolar breath is collected and when pulmonary wash out with clean air is done, a tailored experimental design was developed. Three different breath sampling approaches were compared: (a) whole breath sampling by means of Tedlar bags, (b) the end-tidal breath collection using the Mistral sampler, and (c) the simultaneous collection of the whole and alveolar breath by using the ReCIVA. The obtained results showed that alveolar fraction of breath was relatively less affected by ambient air (AA) contaminants (p-values equal to 0.04 for Mistral and 0.002 for ReCIVA Low) with respect to whole breath (p-values equal to 0.97 for ReCIVA Whole). Compared to Tedlar bags, coherent results were obtained by using Mistral while lower VOCs levels were detected for samples (both breath and AA) collected by ReCIVA, likely due to uncorrected and fluctuating flow rates applied by this device. Finally, the analysis of all data also including data obtained by explorative analysis of the unique lung cancer (LC) breath sample showed that a clean air supply might determine a further confounding factor in breath analysis considering that lung wash-out is species-dependent.     

Detection of infectious agents in the airways by ion mobility spectrometry of exhaled breath

Diseases of the lung, e. g. chronic obstructive pulmonary disease (COPD), interstitial lung diseases, bronchiectasis or cystic fibrosis, often lead to recurrent severe respiratory infections that cause exacerbations of the underlying disease. These acute or chronic inflammatory processes can result in a progressive destruction of the lung and in an ongoing decline in lung function. Therefore longer inpatient stays for intravenous antibiotic treatment are necessary and the quality of life in these patients is severely limited. A rapid detection of infectious agents in human lungs is often crucial, because the choice of the appropriate therapeutic regime depends at first on the identification of the infecting species. Standard methods for detection and identification are either time consuming, of low sensitivity or expensive. It is known that bacteria, and also mitosporic fungi, produce volatile organic compounds (VOCs) that can be detected in exhaled breath by ion mobility spectrometry (IMS), were a distinct detection of a specific VOC is related to a “peak”. We investigated, whether the detection and characterisation of VOCs by Multi-capillary column coupled to IMS in exhaled breath of patients whose airways are either infected or colonized by Pseudomonas aeruginosa compared to healthy non-smoker controls is capable of identifying those infectious agents. To realize a non invasive identification of pathogens, the exhaled breath of 53 persons (24 patients suffering chronic or infectious on Pseudomonas and 29 healthy controls) was investigated using an ion mobility spectrometer type BioScout. In total 224 different signals were found. Actually, 21 different signals are able to differentiate the two groups, Control and Pseudomonas, with rank sum values less than 0.2. For all 224 signals Box-and-Wisker plots were realized. The peaks with the lowest rank sum values F (0,107) and PS0 (0,112) show rather good separation of both groups. Our preliminary results demonstrate that distinct patterns of a small number of IMS-peaks are sufficient for the identification of these infectious agents. Therefore MCC-IMS seems to be a promising method for the non-invasive identification of patients which are colonized or infected with bacteria such as Pseudomonas aeruginosa.     

Investigating Bacterial Volatilome for the Classification and Identification of Mycobacterial Species by HS-SPME-GC-MS and Machine Learning

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography–quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.     

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.     

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces,Alveolar Gas,and Stable Air

Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC–MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4–5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.     

Hybrid Volatolomics and Disease Detection

This Review presents a concise, but not exhaustive, didactic overview of some of the main concepts and approaches related to “volatolomics”—an emerging frontier for fast, risk‐free, and potentially inexpensive diagnostics. It attempts to review the source and characteristics of volatolomics through the so‐called volatile organic compounds (VOCs) emanating from cells and their microenvironment. It also reviews the existence of VOCs in several bodily fluids, including the cellular environment, blood, breath, skin, feces, urine, and saliva. Finally, the usefulness of volatolomics for diagnosis from a single bodily fluid, as well as ways to improve these diagnostic aspects by “hybrid” approaches that combine VOC profiles collected from two or more bodily fluids, will be discussed. The perspectives of this approach in developing the field of diagnostics to a new level are highlighted.     

A Study on VOCs Released by Lung Cancer Cell Line Using GCMS-SPME

The gas chromatography mass spectrometry (GCMS) with combination of Solid Phase Micro-extraction (SPME) was used to study the volatile organic compounds (VOCs) which emitted by the in-vitro cultured human cells and compared with documented volatile biomarker of lung cancer. For this purpose, the lung cancer cell (A549) and non-cancerous lung cell (WI38VA13) were cultured in identical growth medium, concurrently. The VOCs in the headspace of the cell cultures and the blank growth media (reference sample) were collected directly from the culture flask using SPME for 15minutes. The results show that two different volatile metabolites were screened out between A549 cells and Wi38VA13 cells. A549 cell found to emit 2 noticeable VOC which are decane and heneicosane. While for WI38VA13, the VOCs released were 1-Heptanol and heptadecane. The acquired VOCs were compared with the previous studies. The findings in this work conclude that the specific VOC of cells can be act as their odour signature and can be used to provide non-invasively screening of lung cancer using gas array sensor devices.     

Exhaled Breath and Oxygenator Sweep Gas Propionaldehyde in Acute Respiratory Distress Syndrome

Background: Oxidative stress-induced lipid peroxidation (LPO) due to neutrophil-derived reactive oxygen species plays a key role in the early stage of the acute respiratory distress syndrome (ARDS). Monitoring of oxidative stress in this patient population is of great interest, and, ideally, this can be done noninvasively. Recently, propionaldehyde, a volatile chemical compound (VOC) released during LPO, was identified in the breath of lung transplant recipients as a marker of oxidative stress. The aim of the present study was to identify if markers of oxidative stress appear in the oxygenator outflow gas of patients with severe ARDS treated with veno-venous extracorporeal membrane oxygenation (ECMO). Methods: The present study included patients with severe ARDS treated with veno-venous ECMO. Concentrations of acetone, isoprene, and propionaldehyde were measured in inspiratory air, exhaled breath, and oxygenator inflow and outflow gas at corresponding time points. Ion-molecule reaction mass spectrometry was used to measure VOCs in a sequential order within the first 24 h and on day three after ECMO initiation. Results: Nine patients (5 female, 4 male; age = 42.1 ± 12.2 year) with ARDS and already established ECMO therapy (pre-ECMO PaO₂/FiO₂ = 44.0 ± 11.5 mmHg) were included into analysis. VOCs appeared in comparable amounts in breath and oxygenator outflow gas (acetone: 838 (422–7632) vs. 1114 (501–4916) ppbv; isoprene: 53.7 (19.5–244) vs. 48.7 (37.9–108) ppbv; propionaldehyde: 53.7 (32.1–82.2) vs. 42.9 (24.8–122) ppbv). Concentrations of acetone, isoprene, and propionaldehyde in breath and oxygenator outflow gas showed a parallel course with time. Conclusions: Acetone, isoprene, and propionaldehyde appear in breath and oxygenator outflow gas in comparable amounts. This allows for the measurement of these VOCs in a critically ill patient population via the ECMO oxygenator outflow gas without the need of ventilator circuit manipulation.     

Searching for Potential Markers of Glomerulopathy in Urine by HS-SPME-GC×GC TOFMS

Volatile organic compounds (VOCs) exiting in urine are potential biomarkers of chronic kidney diseases. Headspace solid phase microextraction (HS-SPME) was applied for extraction VOCs over the urine samples. Volatile metabolites were separated and identified by means of two-dimensional gas chromatography and time of flight mass spectrometry (GC × GC TOF MS). Patients with glomerular diseases (n = 27) and healthy controls (n = 20) were recruited in the study. Different VOCs profiles were obtained from patients and control. Developed methodology offers the opportunity to examine the metabolic profile associated with glomerulopathy. Four compounds found in elevated amounts in the patients group, i.e., methyl hexadecanoate; 9-hexadecen-1-ol; 6,10-dimethyl-5,9-undecadien-2-one and 2-pentanone were proposed as markers of glomerular diseases.     

An adaptive breath sampler for use with human subjects with an impaired respiratory function

An adaptive sampler for collecting 2.5 dm(3) samples of exhaled air from human subjects with an impaired respiratory function is described. Pressure in the upper respiratory tract is continuously monitored and the data used to control an automated system to collect select portions of the expired breathing cycle onto a mixed bed Tenax(trade mark) and Carbotrap(trade mark) adsorbent trap for analysis by GC-MS. The sampling approach is intended for use in metabolomic profiling of volatiles in human breath at concentrations greater than microg m(-3). The importance of experimental reproducibility in metabolomic data is emphasised and consequently a high purity air supply is used to maintain a stable exogenous volatile organic compound profile at concentrations in the range 5 to 30 microg m(-3). The results of a 90 day stability study showed that exogenous VOCs were maintained at significantly lower levels (40 times lower for isopropyl alcohol) and with significantly higher reproducibility (80 times lower standard deviation for isopropyl alcohol) than would have been be the case if ambient air had been used. The sampling system was evaluated with healthy controls alongside subjects with chronic obstructive pulmonary disease. Subjects were able to breathe normally with control subjects observed to breathe at a rate of 9 to 17 breaths per minute, compared to 16 to 30 breaths per minute for subjects with COPD. This study presents, for the first time, observations and estimates of intra-subject breath sample reproducibility from human subjects. These reproducibility studies indicated that VOCs in exhaled breath exhibit a variety of dynamic behaviours, with some species recovered with a RSD <30%, while other species were observed to have significantly more variable concentrations, 30 to 130% RSD. The approach was also demonstrated to reliably differentiate the differences in the VOC profiles between alveolar and dead space air.     

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.     

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.     

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.