The analysis of healthy volunteers' exhaled breath by the use of solid-phase microextraction and GC-MS

Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms

Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent attention from researchers, the link between exhaled breath and ozone-induced injury remains poorly understood. This study aimed to identify novel exhaled biomarkers in ozone-exposed mice using ultra-sensitive photoinduced associative ionization time-of-flight mass spectrometry and machine learning. Distinct ion peaks for acetonitrile (m/z 42, 60, and 78), butyronitrile (m/z 70, 88, and 106), and hydrogen sulfide (m/z 35) were detected. Integration of tissue characteristics, oxidative stress-related mRNA expression, and exhaled breath condensate free-radical analysis enabled a comprehensive exploration of the relationship between ozone-induced biological responses and potential biomarkers. Under similar exposure levels, C57BL/6 mice exhibited pulmonary injury characterized by significant inflammation, oxidative stress, and cardiac damage. Notably, C57BL/6 mice showed free radical signals, indicating a distinct susceptibility profile. Immunodeficient non-obese diabetic Prkdc-/-/Il2rg-/- (NPI) mice exhibited minimal biological responses to pulmonary injury, with little impact on the heart. These findings suggest a divergence in ozone-induced damage pathways in the two mouse types, leading to alterations in exhaled biomarkers. Integrating biomarker discovery with comprehensive biopathological analysis forms a robust foundation for targeted interventions to manage health risks posed by ozone exposure.

Real-time breath analysis towards a healthy human breath profile

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant (p< 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

Unraveling the potential of breath and sweat VOC capture devices for human disease detection: a systematic-like review of canine olfaction and GC-MS analysis

The development of disease screening methods using biomedical detection dogs relies on the collection and analysis of body odors, particularly volatile organic compounds (VOCs) present in body fluids. To capture and analyze odors produced by the human body, numerous protocols and materials are used in forensics or medical studies. This paper provides an overview of sampling devices used to collect VOCs from sweat and exhaled air, for medical diagnostic purposes using canine olfaction and/or Gas Chromatography-Mass spectrometry (GC-MS). Canine olfaction and GC-MS are regarded as complementary tools, holding immense promise for detecting cancers and infectious diseases. However, existing literature lacks guidelines for selecting materials suitable for both canine olfaction and GC-MS. Hence, this review aims to address this gap and pave the way for efficient body odor sampling materials. The first section of the paper describes the materials utilized in training sniffing dogs, while the second section delves into the details of sampling devices and extraction techniques employed for exhaled air and sweat analysis using GC-MS. Finally, the paper proposes the development of an ideal sampling device tailored for detection purposes in the field of odorology. By bridging the knowledge gap, this study seeks to advance disease detection methodologies, harnessing the unique abilities of both dogs and GC-MS analysis in biomedical research.

Alveolar gradients in breath analysis. A pilot study with comparison of room air and inhaled air by simultaneous measurements using ion mobility spectrometry

Analyzing exhaled breath samples, especially using a highly sensitive method such as MCC/IMS (multi-capillary column/ion mobility spectrometry), may also detect analytes that are derived from exogenous production. In this regard, there is a discussion about the optimal interpretation of exhaled breath, either by considering volatile organic compounds (VOCs) only in exhaled breath or by additionally considering the composition of room air and calculating the alveolar gradients. However, there are no data on whether the composition and concentration of VOCs in room air are identical to those in truly inhaled air directly before analyzing the exhaled breath. The current study aimed to determine whether the VOCs in room air, which are usually used for the calculation of alveolar gradients, are identical to the VOCs in truly inhaled air. For the measurement of inhaled air and room air, two IMS, each coupled with an MCC that provided a pre-separation of the VOCs, were used in parallel. One device was used for sampling room air and the other for sampling inhaled air. Each device was coupled with a newly invented system that cleaned room air and provided a clean carrier gas, whereas formerly synthetic air had to be used as a carrier gas. In this pilot study, a healthy volunteer underwent three subsequent runs of sampling of inhaled air and simultaneous sampling and analysis of room air. Three of the selected 11 peaks (P4-unknown, P5-1-Butanol, and P9-Furan, 2-methyl-) had significantly higher intensities during inspiration than in room air, and four peaks (P1-1-Propanamine, N-(phenylmethylene), P2-2-Nonanone, P3-Benzene, 1,2,4-trimethyl-, and P11-Acetyl valeryl) had higher intensities in room air. Furthermore, four peaks (P6-Benzaldehyde, P7-Pentane, 2-methyl-, P8-Acetone, and P10-2-Propanamine) showed inconsistent differences in peak intensities between inhaled air and room air. To the best of our knowledge, this is the first study to compare simultaneous sampling of room air and inhaled air using MCC/IMS. The simultaneous measurement of inhaled air and room air showed that using room air for the calculation of alveolar gradients in breath analysis resulted in different alveolar gradient values than those obtained by measuring truly inhaled air.

Direct mass spectrometry analysis of exhaled human breath in real-time

The molecular composition of exhaled human breath can reflect various physiological and pathological conditions. Considerable progress has been achieved over the past decade in real-time analysis of exhaled human breath using direct mass spectrometry methods, including selected ion flow tube mass spectrometry, proton transfer reaction mass spectrometry, extractive electrospray ionization mass spectrometry, secondary electrospray ionization mass spectrometry, acetone-assisted negative photoionization mass spectrometry, atmospheric pressure photoionization mass spectrometry, and low-pressure photoionization mass spectrometry. Here, recent developments in direct mass spectrometry analysis of exhaled human breath are reviewed with regard to analytical performance (chemical sensitivity, selectivity, quantitative capabilities) and applications of the developed methods in disease diagnosis, targeted molecular detection, and real-time metabolic monitoring.

Methods to Detect Volatile Organic Compounds for Breath Biopsy Using Solid-Phase Microextraction and Gas Chromatography-Mass Spectrometry

Volatile organic compounds (VOCs) are byproducts from metabolic pathways that can be detected in exhaled breath and have been reported as biomarkers for different diseases. The gold standard for analysis is gas chromatography-mass spectrometry (GC-MS), which can be coupled with various sampling methods. The current study aims to develop and compare different methods for sampling and preconcentrating VOCs using solid-phase microextraction (SPME). An in-house sampling method, direct-breath SPME (DB-SPME), was developed to directly extract VOCs from breath using a SPME fiber. The method was optimized by exploring different SPME types, the overall exhalation volume, and breath fractionation. DB-SPME was quantitatively compared to two alternative methods involving the collection of breath in a Tedlar bag. In one method, VOCs were directly extracted from the Tedlar bag (Tedlar-SPME) and in the other, the VOCs were cryothermally transferred from the Tedlar bag to a headspace vial (cryotransfer). The methods were verified and quantitatively compared using breath samples (n = 15 for each method respectively) analyzed by GC-MS quadrupole time-of-flight (QTOF) for compounds including but not limited to acetone, isoprene, toluene, limonene, and pinene. The cryotransfer method was the most sensitive, demonstrating the strongest signal for the majority of the VOCs detected in the exhaled breath samples. However, VOCs with low molecular weights, including acetone and isoprene, were detected with the highest sensitivity using the Tedlar-SPME. On the other hand, the DB-SPME was less sensitive, although it was rapid and had the lowest background GC-MS signal. Overall, the three breath-sampling methods can detect a wide variety of VOCs in breath. The cryotransfer method may be optimal when collecting a large number of samples using Tedlar bags, as it allows the long-term storage of VOCs at low temperatures (-80 °C), while Tedlar-SPME may be more effective when targeting relatively small VOCs. The DB-SPME method may be the most efficient when more immediate analyses and results are required.

Acetone sensing in liquid and gas phases using cyclic voltammetry

This paper presents the use of cyclic voltammetry to measure acetone concentration in liquid and vapor forms at disposable screen-printed electrodes of platinum working electrode, platinum counter electrode, and silver/silver chloride reference electrode. The main characteristics of the acetone sensor including its linearity, sensitivity, reproducibility, and limit of detection (LOD) were studied by doing different experiments to test both liquid and vapor samples in the physiological range of 1 µM to 10 mM. The change in acetone concentration was monitored by comparing the lineshape of butterfly region before and after injecting the acetone sample in the baseline solution that contains 0.5 M H₂SO₄. The sensor was shown to have a good sensitivity, reproducibility, and a linear response with respect to the acetone concentration in both liquid and gas phases over a range of 1 µM to 10 mM with R² > 0.97 and LOD of 0.1 µM. The system stability was improved by building a closed glass system to reduce the exchange of acetone with the surrounding air in an open environment. The closed system was tested using vapor samples and the error bars in the calibration curve were reduced to more than half of their values before using the closed system. The new system will be used extensively in future for an enzyme-based acetone sensor that will be used for diabetes monitoring.

Effect of household air pollutants on the composition of exhaled breath characterized by solid-phase microextraction and needle-trap devices

Exposure to household air pollutants is becoming a serious environmental health risk. Various methods can be applied to assess humans' exposure status to indoor pollutants, with breath monitoring being among the best options. Breath sampling is fast and non-invasive, and contains compounds that can be used as markers for evaluating exposure length and estimating internal concentrations of pollutants. However, the distribution of compounds between gas and droplets in breath samples represents one of the key challenges associated with this analytical method. In this work, a needle-trap device (NTD) was prepared by packing the needle with a porous filter, divinyl benzene, and Carboxen to enable the exhaustive capture of both droplet-bound and gaseous components. Furthermore, fiber-based solid-phase microextraction (SPME) was also applied to extract compounds from only the gas phase to distinguish this portion of analytes from the total concentration in the sample. Dynamic, real-time breath sampling was enabled via a new sampling tube equipped with 2 one-way valves, which was specially designed for this work. Both methods provided satisfactory reproducibility, repeatability, and sensitivity, with detection limits as low as 0.05 ng mL^-1. To investigate the real-world applicability of the proposed devices, breath samples were obtained from volunteers who had been exposed to candle and incense smoke and aerosol sprays, or had smoked cannabis. The results revealed the high concentration of organic air pollutants in inhaled air (maximum of 215 ng mL^-1) and exhaled breath (maximum of 14.4 ng mL^-1) and a correlation between the components in inhaled air and exhaled breath. Significantly, the findings further revealed that the developed NTD has enhanced breath-sample determinations, especially for polar compounds, which tend to remain trapped in breath droplets.

Volatile organic compound emissions during HOMEChem

Quantifying speciated concentrations and emissions of volatile organic compounds (VOCs) is critical to understanding the processes that control indoor VOC dynamics, airborne chemistry, and human exposures. Here, we present source strength profiles from the HOMEChem study, quantifying speciated VOC emissions from scripted experiments (with multiple replicates) of cooking, cleaning, and human occupancy and from unperturbed baseline measurements of the building and its contents. Measurements using a proton transfer reaction time-of-flight mass spectrometer were combined with tracer-based determinations of air-change rates to enable mass-balance-based calculations of speciated, time-resolved VOC source strengths. The building and its contents were the dominant emission source into the house, with large emissions of acetic acid, methanol, and formic acid. Cooking emissions were greater than cleaning emissions and were dominated by ethanol. Bleach cleaning generated high emissions of chlorinated compounds, whereas natural product cleaning emitted predominantly terpenoids. Occupancy experiments showed large emissions of siloxanes from personal care products in the morning, with much lower emissions in the afternoon. From these results, VOC emissions were simulated for a hypothetical 24-h period, showing that emissions from the house and its contents make up nearly half of total indoor VOC emissions.

Exhaled breath analysis using GC-MS and an electronic nose for lung cancer diagnostics

Exhaled breath analysis is an interesting and promising approach for the diagnostics of various diseases. Being non-invasive, convenient and simple, this approach has tremendous potential utility for further translation into clinical practice. In this study, gas chromatography-mass spectrometry (GC-MS) and quartz microbalance sensor-based "electronic nose" were applied for analysis of the exhaled breath of 40 lung cancer patients and 40 healthy individuals. It was found that the electronic nose was unable to distinguish the samples of different groups. However, the application of GC-MS allowed identifying statistically significant differences in compound peak areas and their ratios for investigated groups. Diagnostic models were created using random forest classifier based on peak areas and their ratios with the sensitivity and specificity of peak areas (ratios) of 85.7-96.5% (75.0-93.1%) and 73.3-85.1% (90.0-92.5%) on training data and 63.6-75.0% (72.7-100.0%) and 50.0-69.2% (76.9-84.6%) on test data, respectively. The exhaled breath samples of lung cancer patients and healthy volunteers could be distinguished by GC-MS with the use of individual compounds, but application of their ratios could help to determine specific differences between investigated groups and the level the influence of individual metabolism features alternating from one person to another as well as daily instrument reproducibility deviations. The electronic nose has to be significantly improved to apply it to lung cancer diagnostics of exhaled breath analysis and the influence of water vapour has to be lowered to increase the sensitivity of the sensors to detect lung cancer biomarkers.

Rapid and sensitive detection of acetone in exhaled breath through the ambient reaction with water radical cations

The levels of acetone and other ketones in exhaled human breath can be associated with various metabolic conditions, e.g. ketosis, lung cancer, dietary fat loss and diabetes. In this study, ketones in breath samples were charged through the reaction with water radical cations to form [M + H₂O]˙⁺ ions, which were detected by mass spectrometry. Our experimental data indicate that under the optimized experimental conditions, the limit of detection for acetone using our approach is 0.14 ng L^-1 (∼0.06 ppb). The linear dynamic range of detection spans four orders of magnitude. The developed approach was applied to real-time semi-quantitative analysis of acetone in the exhaled breath of human volunteers, revealing significantly higher levels of acetone in the breath of smokers compared to non-smokers. The developed approach features the obviation of sample collection, easy operation, high speed of analysis (10 s per run), high sensitivity, and spectral interpretation, which indicates the potential of ambient corona discharge ionization mass spectrometry as a selective, sensitive and noninvasive technique for the determination of exhaled ketones in clinical diagnosis including lung cancer, diabetes, etc.

Modular Breath Analyzer (MBA): Introduction of a Breath Analyzer Platform Based on an Innovative and Unique, Modular eNose Concept for Breath Diagnostics and Utilization of Calibration Transfer Methods in Breath Analysis Studies

Exhaled breath analysis for early disease detection may provide a convenient method for painless and non-invasive diagnosis. In this work, a novel, compact and easy-to-use breath analyzer platform with a modular sensing chamber and direct breath sampling unit is presented. The developed analyzer system comprises a compact, low volume, temperature-controlled sensing chamber in three modules that can host any type of resistive gas sensor arrays. Furthermore, in this study three modular breath analyzers are explicitly tested for reproducibility in a real-life breath analysis experiment with several calibration transfer (CT) techniques using transfer samples from the experiment. The experiment consists of classifying breath samples from 15 subjects before and after eating a specific meal using three instruments. We investigate the possibility to transfer calibration models across instruments using transfer samples from the experiment under study, since representative samples of human breath at some conditions are difficult to simulate in a laboratory. For example, exhaled breath from subjects suffering from a disease for which the biomarkers are mostly unknown. Results show that many transfer samples of all the classes under study (in our case meal/no meal) are needed, although some CT methods present reasonably good results with only one class.

A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome

This paper comprises an updated version of the 2014 review which reported 1846 volatile organic compounds (VOCs) identified from healthy humans. In total over 900 additional VOCs have been reported since the 2014 review and the VOCs from semen have been added. The numbers of VOCs found in breath and the other bodily fluids are: blood 379, breath 1488, faeces 443, milk 290, saliva 549, semen 196, skin 623 and urine 444. Compounds were assigned CAS registry numbers and named according to a common convention where possible. The compounds have been included in a single table with the source reference(s) for each VOC, an update on our 2014 paper. VOCs have also been grouped into tables according to their chemical class or functionality to permit easy comparison. Careful use of the database is needed, as a number of the identified VOCs only have level 2-putative assignment, and only a small fraction of the reported VOCs have been validated by standards. Some clear differences are observed, for instance, a lack of esters in urine with a high number in faeces and breath. However, the lack of compounds from matrices such a semen and milk compared to breath for example could be due to the techniques used or reflect the intensity of effort e.g. there are few publications on VOCs from milk and semen compared to a large number for breath. The large number of volatiles reported from skin is partly due to the methodologies used, e.g. by collecting skin sebum (with dissolved VOCs and semi VOCs) onto glass beads or cotton pads and then heating to a high temperature to desorb VOCs. All compounds have been included as reported (unless there was a clear discrepancy between name and chemical structure), but there may be some mistaken assignations arising from the original publications, particularly for isomers. It is the authors' intention that this work will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals; for example more work is required to confirm the identification of these VOCs adhering to the principles outlined in the metabolomics standards initiative. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.

Impact of Cognitive Tasks on CO2 and Isoprene Emissions from Humans

The human body emits a wide range of chemicals, including CO₂ and isoprene. To examine the impact of cognitive tasks on human emission rates of CO₂ and isoprene, we conducted an across-subject, counterbalanced study in a controlled chamber involving 16 adults. The chamber replicated an office environment. In groups of four, participants engaged in 30 min each of cognitive tasks (stressed activity) and watching nature documentaries (relaxed activity). Measured biomarkers indicated higher stress levels were achieved during the stressed activity. Per-person CO₂ emission rates were greater for stressed than relaxed activity (30.3 ± 2.1 vs 27.0 ± 1.7 g/h/p, p = 0.0044, mean ± standard deviation). Isoprene emission rates were also elevated under stressed versus relaxed activity (154 ± 25 μg/h/p vs 116 ± 20 μg/h/p, p = 0.041). The chamber temperature was held constant at 26.2 ± 0.49 °C; incidental variation in temperature did not explain the variance in emission rates. Isoprene emission rates increased linearly with salivary α-amylase levels (r² = 0.6, p = 0.02). These results imply the possibility of considering cognitive tasks when determining building ventilation rates. They also present the possibility of monitoring indicators of cognitive tasks of occupants through measurement of air quality.

Early diagnosis of breast cancer from exhaled breath by gas chromatography-mass spectrometry (GC/MS) analysis: A prospective cohort study

BACKGROUND

It has proved that there is an association between cancer and volatile organic compounds (VOCs) of exhaled breath. This study targets on verifying the existence of specific VOCs in breathing in breast cancer patients, especially those with ductal carcinoma in situ (DCIS).

METHODS

There were a total of 203 participants included in the final analysis, which included 71 (35.0%) patients with histologically confirmed breast cancer (including 13 with DCIS, 31 with lymph node metastasis-negative status, and 27 with lymph node metastasis-positive status), 78 (38.4%) healthy volunteers, and 54 (26.6%) patients with histologically confirmed gastric cancer. Gas chromatography-mass spectrometry and solid-phase microextraction were used to analyze the breath samples for the presence of VOCs.

RESULTS

There were significant differences in the volatile organic metabolites between the DCIS, lymph node metastasis-negative breast cancer, and lymph node metastasis-positive breast cancer groups compared with the healthy controls as well as between the breast cancer and gastric cancer patients. An overlapping set of seven VOCs, including (S)-1,2-propanediol, cyclopentanone, ethylene carbonate, 3-methoxy-1,2-propanediol, 3-methylpyridine, phenol, and tetramethylsilane, was significantly different between the breast cancer patients and healthy individuals as well as between the breast cancer and gastric cancer patients. The combination of these seven compounds was considered as a biomarker for breast cancer. The sensitivity for predicting DCIS by this set of seven compounds was determined to be 80.77%, and the specificity was determined to be 100%.

CONCLUSIONS

This set of seven breast cancer-specific VOCs can be regarded as one particular expiratory marker for DCIS and will help to establish new screening methods for early breast cancer.

BALSAM-An Interactive Online Platform for Breath Analysis, Visualization and Classification

The field of breath analysis lacks a fully automated analysis platform that enforces machine learning good practice and enables clinicians and clinical researchers to rapidly and reproducibly discover metabolite patterns in diseases. We present BALSAM-a comprehensive web-platform to simplify and automate this process, offering features for preprocessing, peak detection, feature extraction, visualization and pattern discovery. Our main focus is on data from multi-capillary-column ion-mobility-spectrometry. While not limited to breath data, BALSAM was developed to increase consistency and robustness in the data analysis process of breath samples, aiming to expand the array of low cost molecular diagnostics in clinics. Our platform is freely available as a web-service and in form of a publicly available docker container.

Investigation of different approaches for exhaled breath and tumor tissue analyses to identify lung cancer biomarkers

Development of early noninvasive methods for lung cancer diagnosis is among the most promising technologies, especially using exhaled breath as an object of analysis. Simple sample collection combined with easy and quick sample preparation, as well as the long-term stability of the samples, make it an ideal choice for routine analysis. The conditions of exhaled breath analysis by preconcentrating volatile organic compounds (VOCs) in sorbent tubes, two-stage thermal desorption and gas-chromatographic determination with flame-ionization detection have been optimized. These conditions were applied to estimate differences in exhaled breath VOC profiles of lung cancer patients and healthy volunteers. The combination of statistical methods was used to evaluate the ability of VOCs and their ratios to classify lung cancer patients and healthy volunteers. The performance of diagnostic models on the test data set was greater than 90 % for both VOC peak areas and their ratios. Some of the exhaled breath samples were analyzed using gas chromatography coupled with mass spectrometry (GC-MS) to identify VOCs present in exhaled breath at lower concentration levels. To confirm the endogenous origin of VOCs found in exhaled breath, GC-MS analysis of tumor tissues was conducted. Some of the VOCs identified in exhaled breath were found in tumor tissues, but their frequency of occurrence was significantly lower than in the case of exhaled breath.

Modification of an atmospheric pressure photoionization source for online analysis of exhaled breath coupled with quadrupole time-of-flight mass spectrometry

Breath analysis is a promising method for metabolomics studies and clinical diagnosis, as it enables the observation of metabolites in a convenient and noninvasive way. In this work, an atmospheric pressure photoionization (APPI) source was modified for online analysis of exhaled breath by coupling with quadrupole time-of-flight mass spectrometry (QTOFMS). Three parameters, namely, the capillary voltage, the sampling flow and the curtain gas flow of the APPI source, were optimized. Five healthy volunteers, three males and two females, were enrolled to test the performance of modified APPI-QTOFMS by analyzing their exhaled breath. A total of 21 compounds were tentatively identified, and four metabolites, namely, dimethyl selenoxide, δ-valerolactam, hydroxymandelic acid and palmitic amide were detected in the exhaled breath for the first time. The result shows that modified APPI-QTOFMS can be used for the online study of exhaled breath. Graphical abstract.

Human respiratory system as sink for volatile organic compounds: Evidence from field measurements

Human exposure to volatile organic compounds (VOCs) via inhalation might increase the risk of specific diseases. Human breath has been widely investigated as a source of VOCs. However, the role of the human respiratory system as a sink for VOCs is much less studied. In this observational study, the VOC concentrations in inhaled and exhaled air in different environmental conditions were investigated. A total of 98 healthy non-smoking subjects who were exposed to a wide variation in levels of VOCs participated in this study. Individual and statistical results show that human breath could serve as a source for some VOCs and a sink for others, and even when human breath serves as a sink, not all VOCs were 100% absorbed. Interestingly, an increase in inhaled concentrations of toluene was observed to convert human breath from being a source to being a sink. Attention could be given to those VOCs for which humans act as a strong sink.

Optical sensory arrays for the detection of urinary bladder cancer-related volatile organic compounds

Non-invasive detection of urinary bladder cancer remains a significant challenge. Urinary volatile organic compounds (VOCs) are a promising alternative to cell-based biomarkers. Herein, we demonstrate a novel diagnosis system based on an optic fluorescence sensor array for detecting urinary bladder cancer VOCs biomarkers. This study describes a fluorescence-based VOCs sensor array detecting system in detail. The choice of VOCs for the initial part was based on an extensive systematic search of the literature and then followed up using urinary samples from patients with urinary bladder transitional cell carcinoma. Canonical discriminant analysis and partial least squares discriminant analysis (PLS-DA) were employed and correctly detected 31/48 urinary bladder cancer VOC biomarkers and achieved an overall 77.75% sensitivity and 93.25% specificity by PLS-DA modelling. All five urine samples from bladder cancer patients, and five healthy controls were successfully identified with the same sensor arrays. Overall, the experiments in this study describe a real-time platform for non-invasive bladder cancer diagnosis using fluorescence-based gas-sensor arrays. Pure VOCs and urine samples from the patients proved such a system to be promising; however, further research is required using a larger population sample.

Comparison of dermal vs internal light administration in human lungs using the TDLAS-GASMAS technique-Phantom studies

Oxygen and water vapor content, in the lungs of a 3D-printed phantom model based on CT-images of a preterm infant, is evaluated using Tunable Diode Laser Absorption Spectroscopy (TDLAS) in Gas in Scattering Media Absorption Spectroscopy (GASMAS), that is, the TDLAS-GASMAS technique. Oxygen gas is detected through an absorption line near 764 nm and water vapor through an absorption line near 820 nm. A model with a lung containing interior structure is compared to a model with a hollow lung. Compared to the model with the hollow lung, both the mean absorption path length and the transmitted intensity are found to be lower for the model with the structured lung. A new approach, where laser light is delivered internally into the model through an optical fiber, is compared to dermal light administration, that is, illumination onto the skin, for the model with structure inside the lung. The internal light administration generally resulted in larger gas absorption, and higher signal-to-noise ratios, compared to the dermal light administration. The results from the phantom measurements show great promise for the internal illumination approach and a natural next step would be to investigate it further in clinical studies.

Endogenous volatile organic compounds in acute myeloid leukemia: origins and potential clinical applications

Not unlike many cancer types, acute myeloid leukemia (AML) exhibits many metabolic changes and reprogramming, causing changes in lipid metabolism. Some of the distinct molecular abnormalities associated with AML also modify the metabolic changes. Both processes result in changes in the production of endogenous volatile organic compounds (VOCs). The increasing availability of highly sensitive methods for detecting trace chemicals provides the opportunity to investigate the role of patient-specific VOC finger-prints as biomarkers for detecting early relapse or minimal residual disease in AML. Since VOC production is reliant on metabolic activities, when combined with currently available methods, VOC analysis may identify within a group of patients with flow cytometric or molecular evidence of residual disease those most at risk for disease relapse.

Sensing Technologies for Detection of Acetone in Human Breath for Diabetes Diagnosis and Monitoring

The review describes the technologies used in the field of breath analysis to diagnose and monitor diabetes mellitus. Currently the diagnosis and monitoring of blood glucose and ketone bodies that are used in clinical studies involve the use of blood tests. This method entails pricking fingers for a drop of blood and placing a drop on a sensitive area of a strip which is pre-inserted into an electronic reading instrument. Furthermore, it is painful, invasive and expensive, and can be unsafe if proper handling is not undertaken. Human breath analysis offers a non-invasive and rapid method for detecting various volatile organic compounds thatare indicators for different diseases. In patients with diabetes mellitus, the body produces excess amounts of ketones such as acetoacetate, beta-hydroxybutyrate and acetone. Acetone is exhaled during respiration. The production of acetone is a result of the body metabolising fats instead of glucose to produce energy. There are various techniques that are used to analyse exhaled breath including Gas Chromatography Mass Spectrometry (GC-MS), Proton Transfer Reaction Mass Spectrometry (PTR-MS), Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS), laser photoacoustic spectrometry and so on. All these techniques are not portable, therefore this review places emphasis on how nanotechnology, through semiconductor sensing nanomaterials, has the potential to help individuals living with diabetes mellitus monitor their disease with cheap and portable devices.

Volatile organic metabolites identify patients with gastric carcinoma, gastric ulcer, or gastritis and control patients

Background

Gastric cancer ranks 4th among the most common cancers worldwide, and the mortality caused by gastric cancer is 2nd only to lung cancer. Gastric cancer shows a lack of specific symptoms in its early stages. In addition, its clinical symptoms often do not match the corresponding stage. Upper gastrointestinal endoscopy with biopsy is the gold standard for the diagnosis of gastric cancer because of its high accuracy. However, this operation is invasive, patient compliance is poor, and high demands for medical staff and equipment are typical of this procedure. Recent studies have demonstrated a connection between specific breath volatile organic compounds (VOCs) and various forms of cancers.

Methods

We collected expired air from patients with gastric cancer, chronic atrophic gastritis or gastric ulcers as well as from healthy individuals. Solid-phase microextraction, gas chromatography-mass spectrometry and principal component analysis statistics were applied to identify potential biomarkers of gastric cancer among VOCs.

Results

Fourteen differential metabolites were annotated using the NIST 11 database, with a similarity threshold of 70%. Currently, the metabolic origin of VOCs remains unclear; however, several pathways might explain the decreasing or increasing trends that were observed.

Conclusions

The results of this study demonstrate the existence of specific VOC profiles associated with patients with carcinoma. In addition, these metabolites may contribute to the diagnosis and screening of patients with carcinoma.

Detection of gas traces using semiconductor sensors, ion mobility spectrometry, and mass spectrometry

This article deals with the state-of-the-art instrumentation and application in the field of solid state gas sensorics, ion mobility spectrometry and mass-spectrometry-related research for the detection and measurements of low gas and vapor concentrations. The advantages and disadvantages of gas-analytical devices and systems are discussed, as well as the possibilities of its complex and/or complementary applications. Ion mobility spectrometry-mass spectrometry and subsequent techniques based on solid-state gas sensors are proposed for planned medical study.

A new method to evaluate macaque health using exhaled breath: A case study of M. tuberculosis in a BSL-3 setting

Breath is hypothesized to contain clinically relevant information, useful for the diagnosis and monitoring of disease, as well as understanding underlying pathogenesis. Nonhuman primates, such as the cynomolgus macaque, serve as an important model for the study of human disease, including over 70 different human infections. In this feasibility study, exhaled breath was successfully collected in less than 5 min under Biosafety Level 3 conditions from five anesthetized, intubated cynomolgus and rhesus macaques, before and after lung infection with M. tuberculosis The breath was subsequently analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. A total of 384 macaque breath features were detected, with hydrocarbons being the most abundant. We provide putative identification for 19 breath molecules and report on overlap between the identified macaque breath compounds and those identified in previous human studies.NEW & NOTEWORTHY To the best of our knowledge, this is the first time the volatile molecule content of macaque breath has been comprehensively sampled and analyzed. We do so here in a Biosafety Level 3 setting in the context of M. tuberculosis lung infection. The breath of nonhuman primates represents a novel fluid that could provide insight into disease pathogenesis.

Exhaled gases online measurements for esophageal cancer patients and healthy people by proton transfer reaction mass spectrometry

BACKGROUND

Esophageal cancer is a prevalent malignancy. There is a considerable demand for developing a fast and noninvasive method to screen out the suspect esophageal cancer patients who may undergo further clinical diagnosis.

METHODS

The exhaled breathes from 29 esophageal cancer patients and 57 healthy people were directly measured using our home-made proton transfer reaction mass spectrometer (PTR-MS). Mann-Whitney U test and stepwise discriminant analysis were applied to identify the ions in the breath mass spectral data which can distinguish cancer cohort from healthy group. Receiver operating characteristics (ROC) analysis was also performed.

RESULTS

Seven kinds of ions in the breath mass spectrum, viz., m/z 136, m/z 34, m/z 63, m/z 27, m/z 95, m/z 107 and m/z 45, have been found to distinguish between the esophageal cancer patients and healthy people with a sensitivity of 86.2% and a specificity of 89.5%, respectively. Compared with that from the healthy people, the breath mass spectra from esophageal cancer patients show that the mediant intensities of five kinds of ions were decrease and the rest two kinds of ions were increase. ROC analysis gave the area under the curve (AUC) of 0.943.

CONCLUSIONS

This pilot study shows that the ionic characteristics of exhaled VOCs detected by PTR-MS may be used to differentiate between the esophageal cancer patients and the healthy people. Although the breath tests for more patients are needed to confirm such results, the present work indicates that the PTR-MS may be a promising method in the esophageal cancer screening.

Breath Analysis Based on Surface-Enhanced Raman Scattering Sensors Distinguishes Early and Advanced Gastric Cancer Patients from Healthy Persons

Fourteen volatile organic compound (VOC) biomarkers in the breath have been identified to distinguish early gastric cancer (EGC) and advanced gastric cancer (AGC) patients from healthy persons by gas chromatography-mass spectrometry coupled with solid phase microextraction (SPME). Then, a breath analysis approach based on a surface-enhanced Raman scattering (SERS) sensor was developed to detect these biomarkers. Utilizing hydrazine vapor adsorbed in graphene oxide (GO) film, the clean SERS sensor is facilely prepared by in situ formation of gold nanoparticles (AuNPs) on reduced graphene oxide (RGO) without any organic stabilizer. In the SERS sensor, RGO can selectively adsorb and enrich the identified biomarkers from breath as an SPME fiber, and AuNPs well dispersed on RGO endow the SERS sensor with an effective detection of adsorbed biomarkers. Fourteen Raman bands associated with the biomarkers are selected as the fingerprints of biomarker patterns to distinguish persons in different states. The approach has successfully analyzed and distinguished different simulated breath samples and 200 breath samples of clinical patients with a sensitivity of higher than 83% and a specificity of more than 92%. In conclusion, the VOC biomarkers and breath analysis approach in this study can not only diagnose gastric cancer but also distinguish EGC and AGC. This work has great potential for clinical translation in primary screening diagnosis and stage determination of stomach cancer in the near future.

Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science

Environmental health science aims to link environmental pollution sources to adverse health outcomes to develop effective exposure intervention strategies that reduce long-term disease risks. Over the past few decades, the public health community recognized that health risk is driven by interaction between the human genome and external environment. Now that the human genetic code has been sequenced, establishing this "G × E" (gene-environment) interaction requires a similar effort to decode the human exposome, which is the accumulation of an individual's environmental exposures and metabolic responses throughout the person's lifetime. The exposome is composed of endogenous and exogenous chemicals, many of which are measurable as biomarkers in blood, breath, and urine. Exposure to pollutants is assessed by analyzing biofluids for the pollutant itself or its metabolic products. New methods are being developed to use a subset of biomarkers, termed bioindicators, to demonstrate biological changes indicative of future adverse health effects. Typically, environmental biomarkers are assessed using noninvasive (excreted) media, such as breath and urine. Blood is often avoided for biomonitoring due to practical reasons such as medical personnel, infectious waste, or clinical setting, despite the fact that blood represents the central compartment that interacts with every living cell and is the most relevant biofluid for certain applications and analyses. The aims of this study were to (1) review the current use of blood samples in environmental health research, (2) briefly contrast blood with other biological media, and (3) propose additional applications for blood analysis in human exposure research.

Impact of food intake on in vivo VOC concentrations in exhaled breath assessed in a caprine animal model

Physiological processes within the body may change emitted volatile organic compound (VOC) composition, and may therefore cause confounding biological background variability in breath gas analyses. To evaluate the effect of food intake on VOC concentration patterns in exhaled breath, this study assessed the variability of VOC concentrations due to food intake in a standardized caprine animal model. VOCs in (i) alveolar breath gas samples of nine clinically healthy goats and (ii) room air samples were collected and pre-concentrated before morning feeding and repeatedly after (+60 min, +150 min, +240 min) using needle trap microextraction (NTME). Analysis of VOCs was performed by gas chromatography and mass spectrometry (GC-MS). Only VOCs with significantly higher concentrations in breath gas samples compared to room air samples were taken into consideration. Six VOCs that belonged to the chemical classes of hydrocarbons and alcohols were identified presenting significantly different concentrations before and after feeding. Selected hydrocarbons showed a concentration pattern that was characterized by an initial increase 60 min after food intake, and a subsequent gradual decrease. Results emphasize consideration of physiological effects on exhaled VOC concentrations due to food intake with respect to standardized protocols of sample collection and critical evaluation of results.

Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles

Computational breath analysis is a growing research area aiming at identifying volatile organic compounds (VOCs) in human breath to assist medical diagnostics of the next generation. While inexpensive and non-invasive bioanalytical technologies for metabolite detection in exhaled air and bacterial/fungal vapor exist and the first studies on the power of supervised machine learning methods for profiling of the resulting data were conducted, we lack methods to extract hidden data features emerging from confounding factors. Here, we present Carotta, a new cluster analysis framework dedicated to uncovering such hidden substructures by sophisticated unsupervised statistical learning methods. We study the power of transitivity clustering and hierarchical clustering to identify groups of VOCs with similar expression behavior over most patient breath samples and/or groups of patients with a similar VOC intensity pattern. This enables the discovery of dependencies between metabolites. On the one hand, this allows us to eliminate the effect of potential confounding factors hindering disease classification, such as smoking. On the other hand, we may also identify VOCs associated with disease subtypes or concomitant diseases. Carotta is an open source software with an intuitive graphical user interface promoting data handling, analysis and visualization. The back-end is designed to be modular, allowing for easy extensions with plugins in the future, such as new clustering methods and statistics. It does not require much prior knowledge or technical skills to operate. We demonstrate its power and applicability by means of one artificial dataset. We also apply Carotta exemplarily to a real-world example dataset on chronic obstructive pulmonary disease (COPD). While the artificial data are utilized as a proof of concept, we will demonstrate how Carotta finds candidate markers in our real dataset associated with confounders rather than the primary disease (COPD) and bronchial carcinoma (BC). Carotta is publicly available at http://carotta.compbio.sdu.dk [1].

Application of an artificial neural network model for selection of potential lung cancer biomarkers

Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In order to compensate for the volatile exogenous contaminants, ambient air blank samples were also collected and analyzed. We recruited a total of 123 patients with biopsy-confirmed lung cancer and 361 healthy controls to find the potential lung cancer biomarkers. Automatic peak deconvolution and identification were performed using chromatographic data processing software (AMDIS with NIST database). All of the VOCs sample data operation, storage and management were performed using the SQL (structured query language) relational database. The selected eight VOCs could be possible biomarker candidates. In cross-validation on test data sensitivity was 63.5% and specificity 72.4% AUC 0.65. The low performance of the model has been mainly due to overfitting and the exogenous VOCs that exist in breath. The dedicated software implementing a multilayer neural network using a genetic algorithm for training was built. Further work is needed to confirm the performance of the created experimental model.

Current Challenges in Volatile Organic Compounds Analysis as Potential Biomarkers of Cancer

An early diagnosis and appropriate treatment are crucial in reducing mortality among people suffering from cancer. There is a lack of characteristic early clinical symptoms in most forms of cancer, which highlights the importance of investigating new methods for its early detection. One of the most promising methods is the analysis of volatile organic compounds (VOCs). VOCs are a diverse group of carbon-based chemicals that are present in exhaled breath and biofluids and may be collected from the headspace of these matrices. Different patterns of VOCs have been correlated with various diseases, cancer among them. Studies have also shown that cancer cells in vitro produce or consume specific VOCs that can serve as potential biomarkers that differentiate them from noncancerous cells. This review identifies the current challenges in the investigation of VOCs as potential cancer biomarkers, by the critical evaluation of available matrices for the in vivo and in vitro approaches in this field and by comparison of the main extraction and detection techniques that have been applied to date in this area of study. It also summarises complementary in vivo, ex vivo, and in vitro studies conducted to date in order to try to identify volatile biomarkers of cancer.

Volatile Organic Compounds during Inflammation and Sepsis in Rats

Background:

Multicapillary column ion-mobility spectrometry (MCC-IMS) may identify volatile components in exhaled gas. The authors therefore used MCC-IMS to evaluate exhaled gas in a rat model of sepsis, inflammation, and hemorrhagic shock.

Methods:

Male Sprague–Dawley rats were anesthetized and ventilated via tracheostomy for 10 h or until death. Sepsis was induced by cecal ligation and incision in 10 rats; a sham operation was performed in 10 others. In 10 other rats, endotoxemia was induced by intravenous administration of 10 mg/kg lipopolysaccharide. In a final 10 rats, hemorrhagic shock was induced to a mean arterial pressure of 35 ± 5 mmHg. Exhaled gas was analyzed with MCC-IMS, and volatile compounds were identified using the BS-MCC/IMS-analytes database (Version 1209; B&S Analytik, Dortmund, Germany).

Results:

All sham animals survived the observation period, whereas mean survival time was 7.9 h in the septic animals, 9.1 h in endotoxemic animals, and 2.5 h in hemorrhagic shock. Volatile compounds showed statistically significant differences in septic and endotoxemic rats compared with sham rats for 3-pentanone and acetone. Endotoxic rats differed significantly from sham for 1-propanol, butanal, acetophenone, 1,2-butandiol, and 2-hexanone. Statistically significant differences were observed between septic and endotoxemic rats for butanal, 3-pentanone, and 2-hexanone. 2-Hexanone differed from all other groups in the rats with shock.

Conclusions:

Breath analysis of expired organic compounds differed significantly in septic, inflammation, and sham rats. MCC-IMS of exhaled breath deserves additional study as a noninvasive approach for distinguishing sepsis from inflammation.

SIFT-MS and FA-MS methods for ambient gas phase analysis: developments and applications in the UK

The origins of SIFT created to study interstellar chemistry and SIFT-MS developed for ambient gas and exhaled breath analysis and the UK centres in which these techniques are being exploited.

Reactions of the selected ion flow tube mass spectrometry reagent ions H3O(+) and NO(+) with a series of volatile aldehydes of biogenic significance

RATIONALE

It has been shown that aldehydes are often present in biogenic media. For their analysis by selected ion flow tube mass spectrometry (SIFT-MS), the rate coefficients and the product ion distributions for the reactions of the analyte ions H3O(+) and NO(+) with volatile aldehydes in the presence of water vapour are required.

METHODS

The reactions of H3O(+) and NO(+) ions have been studied with a series of n-aldehydes ranging from acetaldehyde (designated as C2), through undecanal (C11) under the conditions used for SIFT-MS analyses (1 Torr He, 0.1 Torr air sample, 300 K) and over a range of sample gas absolute humidity from 1% to 7%. For comparison, the C5 pentanal isomer 3-methyl butanal, the unsaturated trans-2-pentenal and trans-2-octenal and the aromatic benzaldehyde were also included in the study.

RESULTS

The H3O(+) reactions led to the formation of protonated molecules MH(+) and their hydrates MH(+)(H2O)0,1,2,3 , and (MH(+)-H2O). The NO(+) reactions resulted in the production of NO(+)M adduct ions and of [M-H](+) fragment ions. The percentages of the different product ions for each aldehyde are seen to be dependent on the air sample humidity. Kinetic modelling was used to quantitatively explain these observations and to obtain rate coefficients for the association reactions producing NO(+) M adduct ions.

CONCLUSIONS

This detailed study has provided the kinetics data, in particular the product ion distributions, for the reactions of a number of volatile aldehydes, which allows their analyses by SIFT-MS in humid air, including exhaled breath, food emanations and other biogenic media.

Chemical analysis of whale breath volatiles: a case study for non-invasive field health diagnostics of marine mammals

We explored the feasibility of collecting exhaled breath from a moribund gray whale (Eschrichtius robustus) for potential non-invasive health monitoring of marine mammals. Biogenic volatile organic compound (VOC) profiling is a relatively new field of research, in which the chemical composition of breath is used to non-invasively assess the health and physiological processes on-going within an animal or human. In this study, two telescopic sampling poles were designed and tested with the primary aim of collecting whale breath exhalations (WBEs). Once the WBEs were successfully collected, they were immediately transferred onto a stable matrix sorbent through a custom manifold system. A total of two large volume WBEs were successfully captured and pre-concentrated onto two Tenax^®-TA traps (one exhalation per trap). The samples were then returned to the laboratory where they were analyzed using solid phase micro extraction (SPME) and gas chromatography/mass spectrometry (GC/MS). A total of 70 chemicals were identified (58 positively identified) in the whale breath samples. These chemicals were also matched against a database of VOCs found in humans, and 44% of chemicals found in the whale breath are also released by healthy humans. The exhaled gray whale breath showed a rich diversity of chemicals, indicating the analysis of whale breath exhalations is a promising new field of research.

Investigation of C3-C10 aldehydes in the exhaled breath of healthy subjects using selected ion flow tube-mass spectrometry (SIFT-MS)

Aldehydes have attracted great scientific and clinical interest as potential disease biomarkers. We have investigated selected ion flow tube-mass spectrometry (SIFT-MS) in detecting and quantifying C3 to C10 saturated aldehydes (propanal, butanal, pentanal, hexanal, heptanal, octanal, nonanal and decanal) from the exhaled breath of 26 healthy human volunteers. To assess the reliability of the Nalophan® bag sampling method employed, the water level in the breath sample was measured up to 4 h after collection and showed no significant degradation. Propanal was found to be the most abundant aldehyde in the exhaled breath of healthy volunteers. For the C4-C10 aldehydes, their median concentrations were all less than 3 ppbv, demonstrating only trace quantities are present in the exhaled breath of the 26 healthy volunteers.

The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva

Breath analysis is a young field of research with its roots in antiquity. Antoine Lavoisier discovered carbon dioxide in exhaled breath during the period 1777-1783, Wilhelm (Vilém) Petters discovered acetone in breath in 1857 and Johannes Müller reported the first quantitative measurements of acetone in 1898. A recent review reported 1765 volatile compounds appearing in exhaled breath, skin emanations, urine, saliva, human breast milk, blood and feces. For a large number of compounds, real-time analysis of exhaled breath or skin emanations has been performed, e.g., during exertion of effort on a stationary bicycle or during sleep. Volatile compounds in exhaled breath, which record historical exposure, are called the 'exposome'. Changes in biogenic volatile organic compound concentrations can be used to mirror metabolic or (patho)physiological processes in the whole body or blood concentrations of drugs (e.g. propofol) in clinical settings-even during artificial ventilation or during surgery. Also compounds released by bacterial strains like Pseudomonas aeruginosa or Streptococcus pneumonia could be very interesting. Methyl methacrylate (CAS 80-62-6), for example, was observed in the headspace of Streptococcus pneumonia in concentrations up to 1420 ppb. Fecal volatiles have been implicated in differentiating certain infectious bowel diseases such as Clostridium difficile, Campylobacter, Salmonella and Cholera. They have also been used to differentiate other non-infectious conditions such as irritable bowel syndrome and inflammatory bowel disease. In addition, alterations in urine volatiles have been used to detect urinary tract infections, bladder, prostate and other cancers. Peroxidation of lipids and other biomolecules by reactive oxygen species produce volatile compounds like ethane and 1-pentane. Noninvasive detection and therapeutic monitoring of oxidative stress would be highly desirable in autoimmunological, neurological, inflammatory diseases and cancer, but also during surgery and in intensive care units. The investigation of cell cultures opens up new possibilities for elucidation of the biochemical background of volatile compounds. In future studies, combined investigations of a particular compound with regard to human matrices such as breath, urine, saliva and cell culture investigations will lead to novel scientific progress in the field.