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

An optimization protocol of the volatile organic compounds analysis in earwax samples for untargeted volatilomics

Recent studies have highlighted the potential of earwax or cerumen, a non-conventional biomatrix, in volatilomics research as a valuable matrix for disease biomarker discovery. Despite that, there are still gaps in using non-conventional biomatrices in metabolomics research. In this sense, this study aimed to elucidate the main analytical factors involved in the extraction and analysis of volatile organic compounds (VOCs) in cerumen by headspace/gas chromatography-mass spectrometry (HS/GC-MS) using Design of Experiments (DoE) approaches. Furthermore, we present a repeatability study for the proposed method as a quality control process for cerumenomic assays. By applying factorial designs, it was possible to determine that the sample mass, splitless injector sampling time, headspace extraction time, headspace extraction temperature, injection volume, and vial volume were significant factors for the cerumen VOC analysis by HS/GC-MS. Throughout univariate and multivariate statistical approaches, we demonstrate that different analytical conditions lead to distinct chemical profiling of a sample. The most suitable analytical condition was determined after the optimization steps, and the proposed method's repeatability was evaluated by the metabolites coefficient variation (CV) calculation. Seventy-one earwax VOCs reached a CV considered adequate for untargeted metabolomics studies via GC-MS. In summary, this study describes a protocol for analysis optimization of a non-conventional biomatrix and also reports a quality control process in untargeted volatilomics assays using earwax. Our findings shed light on the potential of using earwax in volatolomic studies and establish analytical criteria to ensure quality in cerumenomic assays.

Recent advances in biosensors detecting biomarkers from exhaled breath and saliva for respiratory disease diagnosis

The global demand for rapid and non-invasive diagnostic methods for respiratory diseases has significantly intensified due to the wide spread of respiratory infectious diseases. Recent advancements in respiratory disease diagnosis through the analysis of exhaled breath and saliva has attracted great attention all over the world. Among various analytical methods, biosensors can offer non-invasive, efficient, and cost-effective diagnostic capabilities, emerging as promising tools in this area. This review intends to provide a comprehensive overview of various biosensors for the detection of respiratory disease related biomarkers in exhaled breath and saliva. Firstly, the characteristics of exhaled breath and saliva, including their generation, composition, and relevant biomarkers are introduced. Subsequently, the design and application of various biosensors for detecting these biomarkers are presented, along with the innovative materials employed as sensitive components. Different types of biosensors are reviewed, including electrochemical, optical, piezoelectric, semiconductor, and other novel biosensors. At last, the challenges, limitations, and future trends of these biosensors are discussed. It is anticipated that biosensors will play a significant role in respiratory disease diagnosis in the future.

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Biofluorometric Acetone Gas Sensor of Sub-ppbv Level Sensitivity

Acetone gas in exhaled breath and skin gas is produced when fatty acids are used as an energy source in the body. The selective and sensitive continuous measurement of acetone gas would be useful for the early screening of diabetes mellitus, a condition characterized by increased fatty acid metabolism. In particular, there is a growing need for acetone gas sensors that enable the wearable measurement of trace concentrations of acetone gas emitted through the skin. In this study, we improved the sensor's sensitivity by optimizing the fluorescence measurement system and flow cell of a previously developed biofluorometric acetone gas sensor (bio-sniffer) using secondary alcohol dehydrogenase. To evaluate the performance of the improved acetone bio-sniffer, we constructed a dilution system to prepare acetone gas at subparts per billion by volume (ppbv) levels and verified its accuracy using gas chromatography-mass spectrometry. As a result, the dilution system was able to prepare 0.1 ppbv of acetone gas with a coefficient of variation of 5%. The improved acetone bio-sniffer demonstrated quantitative characteristics in the concentration range of 0.5-1000 ppbv, with a lower limit of quantification that was 40 times better than that of the conventional acetone bio-sniffer. In the future, this system is expected to be used for continuous measurement of acetone gas released through the skin.

Standardized Assessment of Energy Excretion in Healthy Adults: A Novel Methodology

BACKGROUND

Accurate monitoring of energy balance is essential for effective weight management, but the role of energy excretion is often neglected.

OBJECTIVE

This study aimed to develop and validate a standardized method for assessing energy excretion using dye-labeled meal replacement bars with consistent and stable ingredients.

METHODS

We utilized baseline data from a registered cross-over trial involving twelve healthy adults (7 females, 5 males) with a body mass index of 18-25 kg/m2. Participants consumed dye-labeled meal replacement bars under a standardized protocol, and their feces and urine were collected for energy measurement using bomb calorimetry. Correlation analysis was conducted to explore associations between these variables.

RESULTS

The total energy excretion rate averaged 10.48% (SD 2.56%) of energy intake, with fecal and urinary excretion accounting for 7.95% (SD 2.67%) and 2.52% (SD 0.6%), respectively. Significant individual variability was observed, with total energy excretion ranging from 6.34% to 15.07%, resulting in a maximum difference of 209.64 kcal per day. Fecal energy excretion was positively correlated with fecal wet weight and energy density, while urinary energy excretion was associated with digestible energy.

CONCLUSIONS

This study presents a standardized and efficient methodology for accurately assessing energy excretion using dye-labeled replacement bars. The findings underscore the notable yet variable role of energy excretion in energy balance and suggest that this method could enhance the precision of future energy balance studies.

TRIAL REGISTRATION

Registered at chictr.org.cn as ChiCTR2000038421.

Improved volatiles analysis workflows using automated selected ion flow tube mass spectrometry (SIFT-MS)

Selected ion flow tube mass spectrometry (SIFT-MS) is a recent addition to the routine analysis and research laboratory toolkit, primarily as a quantitative tool. SIFT-MS employs ultra-soft chemical ionisation to directly analyse volatile organic compounds (VOCs) in air and headspace in real-time with high specificity and sensitivity. Coupling SIFT-MS with conventional laboratory automation equipment (i.e., that used with chromatography systems) has proved straightforward and enables unattended operation, processing up to 230 samples per day per SIFT-MS instrument. Automated SIFT-MS systems have been applied to analysis of headspace (static, continuous, multiple headspace extraction, and standard additions), sample bags, and thermal desorption tubes. Applications using these approaches include consumer and drug product testing for volatile impurities (such as benzene, formaldehyde, and nitrosamines), environmental samples, clinical research, and materials testing. The stability of the SIFT-MS technique, coupled with its ability to analyse diverse VOCs in a single run, removes the need for system configuration changes and hence reduces calibration demand and streamlines workflows, reducing the time to report the first results in a sequence schedule and increasing sample throughput compared to chromatographic systems. This article reviews the development of the automated-SIFT-MS approach using a variety of application examples and recommends hardware and software improvements that could further enhance its adoption.

Analysis of the Urine Volatilome of COVID-19 Patients and the Possible Metabolic Alterations Produced by the Disease

Alterations in metabolism caused by SARS-CoV-2 infection have been highlighted in various investigations and have been used to search for biomarkers in different biological matrices. However, the selected biomarkers vary greatly across studies. Our objective is to provide a robust selection of biomarkers, including results from different sample treatments in the analysis of volatile organic compounds (VOCs) present in urine samples from patients with COVID-19. Between September 2021 and May 2022, urine samples were collected from 35 hospitalized COVID-19 patients and 32 healthy controls. The samples were analyzed by headspace (HS) solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS). Analyses were conducted on untreated urine samples and on samples that underwent specific pretreatments: lyophilization and treatment with sulfuric acid. Partial Least Squares Linear Discriminant Analysis (PLS-LDA) and Subwindow Permutation Analysis (SPA) models were established to distinguish patterns between COVID-19 patients and healthy controls. The results identify compounds that are present in different proportions in urine samples from COVID-19 patients compared to those from healthy individuals. Analysis of urine samples using HS-SPME-GC-MS reveals differences between COVID-19 patients and healthy individuals. These differences are more pronounced when methods that enhance VOC formation are used. However, these pretreatments can cause reactions between sample components, creating additional products or removing compounds, so biomarker selection could be altered. Therefore, using a combination of methods may be more informative when evaluating metabolic alterations caused by viral infections and would allow for a better selection of biomarkers.

SPME arrow-based extraction for enhanced targeted and untargeted urinary volatilomics

BACKGROUND

Volatile organic compounds (VOCs) present in human urine are promising biomarkers for various health conditions and environmental exposures. However, their reliable detection is challenging due to the complexity of urinary matrices and the low concentrations of VOCs. Moreover, untargeted approaches present considerable challenges in terms of data interpretation, increasing the complexity of method development. Here we address these challenges by developing a new method that combines solid-phase microextraction (SPME) Arrow with gas chromatography-high resolution mass spectrometry (GC-HRMS), using a design of experiments (DOE) approach for targeted and untargeted compounds. This methodology, specifically tailored for SPME Arrow, represents a significant advancement in untargeted urinary analysis.

RESULTS

The method was developed based on targeted and untargeted outcomes, were ranking results focus on the highest response area of 11 spiked target VOCs representative of urinary volatilomics, and on identifying the maximum untargeted number of VOCs. The method was developed focusing on the highest response area of 11 spiked target VOCs representative of urinary volatilomics and identifying the maximum number of VOCs. A univariate method determined the optimal coating type, urine volume, and salt addition. Subsequently, a central composite design (CCD) DOE was used to determine ideal temperature, extraction, and incubation times. The best method obtained has an extraction time of 60 min at a temperature of 53 °C, with an SPME Arrow CAR/PDMS using 2 mL of urine, with 0.25 % w/v of NaCl and a pH of 2. Compared to conventional SPME fibers, the SPME Arrow showed improved extraction efficiency, detecting more VOCs. Finally, the enhanced method was successfully applied to urine samples from children exposed and non-exposed to tobacco smoke, identifying specific VOCs, like p-cymene and p-isopropenyl toluene related to tobacco exposure.

SIGNIFICANCE

By integrating both targeted and untargeted approaches, the developed method comprehensively captures the complexity of urinary metabolomics. This dual strategy ensures the precise identification of known compounds and the discovery of novel biomarkers, thereby providing a more complete metabolic profile. Such an approach is crucial for advancing in non-invasive diagnostics and environmental health studies, as it offers deeper insights into the intricate relationships between metabolic processes and various health conditions.

Development of a new breath collection method for analyzing volatile organic compounds from intubated mouse models

A new pre-clinical method for capturing breath samples from intubated mice is presented. This method significantly reduces background levels, allowing more accurate measurements of VOCs originating from the breath ("on-breath") as opposed to background contamination. The method was developed by integrating industry-standard volatile-capturing sorbent tubes with respiratory mechanics measurement equipment (flexiVent®), resulting in a mouse breath sample that can be transported and analyzed by TD-GC-MS and other central lab technologies. Using the methodology, the discrimination between on-breath VOCs from background compounds provides a cleaner dataset, which can accelerate the validation of VOCs identified from mouse models and their translation to clinical trials. Three metrics were developed to identify on-breath VOCs, with 22 identified using Type 1 (50% of the breath samples exceeding three standard deviations above the mean signal of the system blanks), 34 with Type 2 (P-value ≤ .05 between paired breath and blank samples), and 61 with Type 3 (ROC-AUC value ≥ 0.8 to differentiate between breath and blank samples). The number of compounds seen at elevated levels on mouse breath was quantified and compared to the levels seen on human breath samples to compare methodologies.

Study protocol: the 'Endoscope CRC' cohort, a prospective biobank study on the development and evaluation of diagnostic and prognostic biomarker profiles for colorectal cancer and premalignant lesions

INTRODUCTION

Early detection of colorectal cancer (CRC) and clinically relevant (advanced) adenomas leads to a significant reduction of CRC-related mortality and morbidity. However, the faecal immunochemical test (FIT) suffers from a high number of false-positive results and is insensitive to detecting advanced adenomas, resulting in false-negative results for these premalignant lesions. Therefore, more accurate, non-invasive screening tools are needed for the detection and prognostication of colorectal neoplasia. Previous research on volatile organic compounds (VOCs) analysis in breath and faeces has shown to be promising potential biomarkers for this purpose. Several VOC-sampling methods, including breath sampling, have improved significantly over the recent years resulting in an increased reliability of measurements. Therefore, we aim to identify relevant VOC profiles in exhaled breath and faeces for the diagnosis of colorectal neoplasia while taking into account relevant confounding factors. Follow-up data will be used to identify relevant VOC profiles in exhaled breath and faeces for the prognostication of colorectal neoplasia. Finally, a biobank will be set up for future research questions on this topic.

METHODS AND ANALYSIS

Subjects with positive FIT within the Dutch national CRC cancer screening programme are included. Subjects are asked to fill in questionnaires and exhaled breath, faeces and blood are sampled prior to colonoscopy. All subjects are asked to fill in follow-up questionnaires at years 1 and 5 of the study. In case of surveillance colonoscopies, subjects are asked to provide exhaled breath, faeces and blood prior to the colonoscopy again. Breath sampling is performed using the ReCIVA breath sampler. VOCs in breath and faeces are analysed using gas-chromatography-mass spectrometry (GC-MS). Raw GC-MS data is preprocessed and analysed using machine learning techniques.

ETHICS AND DISSEMINATION

The study is approved by the medical ethics committee at the Maastricht University Medical Center (NL74844.068.20) in November 2021 and started inclusion in January 2022.

Ultrasonic spraying quercetin chitosan nonwovens with antibacterial and deodorizing properties for sanitary napkin

With economic and social development, there is a growing focus on menstrual hygiene, and traditional sanitary napkins are no longer sufficient to meet women's needs. In this study, quercetin (QC) was efficiently and uniformly ultrasonic sprayed on thermally bonded chitosan nonwovens (CS) to prepare a multifunctional surface layer of sanitary napkins (QCX@CS). CS sprayed with 3 layers of QC (QC3@CS) exhibits excellent mechanical properties and high antibacterial rates against Escherichia coli (99.51 %) and Staphylococcus aureus (99.87 %), respectively. Besides, QC3@CS demonstrates strong free radical scavenging abilities, which have great potential to reduce the effects of reactive oxygen species on immune and metabolic functions during menstruation. QC3@CS demonstrates strong deodorizing abilities, with rates of 87.22 % for acetic acid and 90.88 % for ammonia, which could effectively eliminate the unpleasant odor associated with menstruation. Moreover, QC3@CS ensures excellent water absorption, anti-return properties, and cytocompatibility. This study may provide valuable insights into developing functional sanitary napkin materials based on natural extracts.

Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers

The exhaled breath represents an ideal matrix for noninvasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review, we specifically address volatile organic compounds in the breath, with a view toward fulfilling the promise of these as actionable biomarkers, in particular, for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

A matrix-centered view of mass spectrometry platform innovation for volatilome research

Volatile organic compounds (VOCs) are carbon-containing molecules with high vapor pressure and low water solubility that are released from biotic and abiotic matrices. Because they are in the gaseous phase, these compounds tend to remain undetected when using conventional metabolomic profiling methods. Despite this omission, efforts to profile VOCs can provide useful information related to metabolic status and identify potential signaling pathways or toxicological impacts in natural or engineered environments. Over the past several decades mass spectrometry (MS) platform innovation has instigated new opportunities for VOC detection from previously intractable matrices. In parallel, volatilome research linking VOC profiles to other forms of multi-omic information (DNA, RNA, protein, and other metabolites) has gained prominence in resolving genotype/phenotype relationships at different levels of biological organization. This review explores both on-line and off-line methods used in VOC profiling with MS from different matrices. On-line methods involve direct sample injection into the MS platform without any prior compound separation, while off-line methods involve chromatographic separation prior to sample injection and analyte detection. Attention is given to the technical evolution of platforms needed for increasingly resolved VOC profiles, tracing technical progress over time with particular emphasis on emerging microbiome and diagnostic applications.

Volatile organic compounds (VOCs) in terrestrial extreme environments: implications for life detection beyond Earth

Covering: 1961 to 2024Discovering and identifying unique natural products/biosignatures (signatures that can be used as evidence for past or present life) that are abundant, and complex enough that they indicate robust evidence of life is a multifaceted process. One distinct category of biosignatures being explored is organic compounds. A subdivision of these compounds not yet readily investigated are volatile organic compound (VOCs). When assessing these VOCs as a group (volatilome) a fingerprint of all VOCs within an environment allows the complex patterns in metabolic data to be unravelled. As a technique already successfully applied to many biological and ecological fields, this paper explores how analysis of volatilomes in terrestrial extreme environments could be used to enhance processes (such as metabolomics and metagenomics) already utilised in life detection beyond Earth. By overcoming some of the complexities of collecting VOCs in remote field sites, a variety of lab based analytical equipment and techniques can then be utilised. Researching volatilomics in astrobiology requires time to characterise the patterns of VOCs. They must then be differentiated from abiotic (non-living) signals within extreme environments similar to those found on other planetary bodies (analogue sites) or in lab-based simulated environments or microcosms. Such an effort is critical for understanding data returned from past or upcoming missions, but it requires a step change in approach which explores the volatilome as a vital additional tool to current 'Omics techniques.

Evaluation of urinary volatile organic compounds as a novel metabolomic biomarker to assess chronic kidney disease progression

BACKGROUND

There is a need to develop accurate and reliable non-invasive methods to evaluate chronic kidney disease (CKD) status and assess disease progression. Given it is recognized that dysregulation in metabolic pathways occur from early CKD, there is a basis in utilizing metabolomic biomarkers to monitor CKD progression. Volatile Organic Compounds (VOCs), a form of metabolomic biomarker, are gaseous products of metabolic processes in organisms which are typically released with greater abundance in disease conditions when there is dysregulation in metabolism. How urinary VOCs reflect the abnormal metabolic profile of patients with CKD status is unknown. Our study aimed to explore this.

METHODS

Individuals aged 18-75 years undergoing kidney biopsy were included. Pre-biopsy urine samples were collected. All biopsy samples had an interstitial fibrosis and tubular atrophy (IFTA) grade scored by standardized assessment. Urine supernatant was extracted from residue and sampled for stir bar sorptive extraction followed by Gas chromatography-mass spectrometry (GC-MS) analysis. Post-processing of GC-MS data separated complex mixtures of VOCs based on their volatility and polarity. Mass-to-charge ratios and fragment patterns were measured for individual VOCs identification and quantification. Linear discriminant analysis (LDA) was performed to assess the ability of urinary VOCs in discriminating between IFTA 0 ('no or minimal IFTA' i.e. <10%, IFTA), IFTA 1 ('mild IFTA' i.e. 10-25% IFTA) and IFTA ≥ 2 ('moderate or severe IFTA' i.e. >25% IFTA). Linear regression analysis adjusting for age, sex, estimated glomerular filtration rate, diabetes mellitus (DM) status, and albuminuria was conducted to determine significantly regulated urinary VOCs amongst the groups.

RESULTS

64 study participants (22 individuals IFTA 0, 15 individuals IFTA 1, 27 individuals IFTA ≥ 2) were included. There were 34 VOCs identified from GC-MS which were statistically associated with correct classification between the IFTA groups, and LDA demonstrated individuals with IFTA 0, IFTA 1 and IFTA ≥ 2 could be significantly separated by their urinary VOCs profile (p < 0.001). Multivariate linear regression analysis reported 4 VOCs significantly upregulated in the IFTA 1 compared to the IFTA 0 group, and 2 VOCs significantly upregulated in the IFTA ≥ 2 compared to the IFTA 1 group (p < 0.05). Significantly upregulated urinary VOCs belonged to one of four functional groups - aldehydes, ketones, hydrocarbons, or alcohols.

CONCLUSIONS

We report novel links between urinary VOCs and tubulointerstitial histopathology. Our findings suggest the application of urinary VOCs as a metabolomic biomarker may have a useful clinical role to non-invasively assess CKD status during disease progression.

Comparative analysis of feature annotation methods for SESI-HRMS in exhaled breath analysis

Secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a powerful method for the analysis of exhaled breath in real time. However, feature annotation is challenging due to the flow-injection nature of the technique. To evaluate alternative methods for enhancing feature annotation, a study was conducted where the exhaled breath of sixteen subjects was condensed and analyzed using dynamic headspace vacuum in-trap extraction gas chromatography-mass spectrometry (DHS-V-ITEX-GC-MS) and liquid chromatography coupled to mass spectrometry (LC-MS) using polar and reverse-phase conditions along with a data-independent MS2-acquisition method based on multiple injections. The annotation results obtained from these methods were compared to those from SESI-HRMS. The use of these techniques on breath condensate is unprecedented. The GC-MS method primarily detected compounds of exogenous origin, particularly additives in oral hygiene products like menthol. On the other hand, LC-MS detected a vast number of features, especially with the utilized data-independent acquisition method. Chemical classes to these features were assigned in-silico. In positive ion mode, mostly amino acids and amines were detected, while the largest group in negative ion mode consisted of carboxylic acids. Approximately 25% and 5% of SESI features had a corresponding match with LC-MS and GC-MS. While both GC-MS and LC-MS methods partially overlapped with the SESI features, there was limited overlap of both in the mass-to-charge range from 150 to 200. In conclusion, both GC-MS and LC-MS analysis of breath condensate can serve as supplementary tools for annotating features obtained from SESI-MS. However, to increase confidence in the annotation results, combining these methods with additional on-line fragmentation techniques is recommended.

Breath Analysis via Gas Chromatography-Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study

Background: This proof-of-concept study aimed to assess the diagnostic potential of gas chromatography-mass spectrometry (GC-MS) in profiling volatile organic compounds (VOCs) from exhaled breath as a diagnostic tool for the chronic coronary syndrome (CCS). Methods: Exhaled air was collected from patients undergoing invasive coronary angiography (ICA), with all samples obtained prior to ICA. Post hoc, patients were divided into groups based on coronary lesion severity and indications for revascularization. VOCs in the breath samples were analyzed using GC-MS. Results: This study included 23 patients, of whom 11 did not require myocardial revascularization and 12 did. GC-MS analysis successfully classified 10 of the 11 patients without the need for revascularization (sensitivity of 91%), and 7 of the 12 patients required revascularization (specificity 58%). In subgroup analysis, GC-MS demonstrated 100% sensitivity in identifying patients with significant coronary lesions requiring intervention when the cohort was divided into three groups. A total of 36 VOCs, including acetone, ethanol, and phenol, were identified as distinguishing markers between patient groups. Conclusions: Patients with CCS exhibited a unique fingerprint of exhaled breath, which was detectable with GC-MS. These findings suggest that GC-MS analysis could be a reliable and non-invasive diagnostic tool for CCS. Further studies with larger cohorts are necessary to validate these results and explore the potential integration of VOC analysis into clinical practice.

Stimulated C2C12 Myotube Headspace Volatile Organic Compound Analysis

Understanding exercise metabolism and the relationship with volatile organic compounds (VOCs) holds potential in both health care and sports performance. Exercise metabolism can be investigated using whole body exercise testing (in vivo) or through the culture and subsequent electrical pulse stimulation (EPS) of myotubes (in vitro). This research investigates the novel headspace (HS) analysis of EPS skeletal muscle myotubes. An in vitro system was built to investigate the effect of EPS on the volatile constituents in the HS above EPS skeletal muscle. The C2C12 immortalised cell line was chosen. EPS was applied to the system to induce myotube contraction. The in vitro system was applied to the analysis of VOCs using thermal desorption (TD) sampling. Samples were collected under four conditions: environmental samples (enviro), acellular media HS samples (blank), skeletal muscle myotubes without stimulation HS samples (baseline) and EPS of skeletal muscle myotube HS samples (stim). TD sampling combined with gas-chromatography mass spectrometry (GC-MS) detected two compounds that, after multivariate and univariate statistical analysis, were identified as changing due to EPS (p < 0.05). These compounds were tentatively assigned as 1,4-Dioxane-2,5-dione, 3,6-dimethyl- and 1-pentene. The former is a known lactide and the latter has been reported as a marker of oxidative stress. Further research should focus on improvements to the EPS system, including the use of more relevant cell lines, quantification of myotube contractions, and the application of targeted analysis, metabolic assays and media analysis.

Generating pooled quality control samples of volatile organic compounds

Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace are influenced by several confounding factors not represented in reference standards. In this study, we propose a method of generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow with thermal desorption tubes. Sample tubes were desorbed and split from each sample and recollected onto a single tube, generating a pooled QC sample. This QC sample was then repeatedly desorbed and recollected with a sequentially lower split ratio allowing injection of multiple QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects.

Performance of a Novel Electronic Nose for the Detection of Volatile Organic Compounds Relating to Starvation or Human Decomposition Post-Mass Disaster

There has been a recent increase in the frequency of mass disaster events. Following these events, the rapid location of victims is paramount. Currently, the most reliable search method is scent detection dogs, which use their sense of smell to locate victims accurately and efficiently. Despite their efficacy, they have limited working times, can give false positive responses, and involve high costs. Therefore, alternative methods for detecting volatile compounds are needed, such as using electronic noses (e-noses). An e-nose named the 'NOS.E' was developed and has been used successfully to detect VOCs released from human remains in an open-air environment. However, the system's full capabilities are currently unknown, and therefore, this work aimed to evaluate the NOS.E to determine the efficacy of detection and expected sensor response. This was achieved using analytical standards representative of known human ante-mortem and decomposition VOCs. Standards were air diluted in Tedlar gas sampling bags and sampled using the NOS.E. This study concluded that the e-nose could detect and differentiate a range of VOCs prevalent in ante-mortem and decomposition VOC profiles, with an average LOD of 7.9 ppm, across a range of different chemical classes. The NOS.E was then utilized in a simulated mass disaster scenario using donated human cadavers, where the system showed a significant difference between the known human donor and control samples from day 3 post-mortem. Overall, the NOS.E was advantageous: the system had low detection limits while offering portability, shorter sampling times, and lower costs than dogs and benchtop analytical instruments.

High-quality identification of volatile organic compounds (VOCs) originating from breath

INTRODUCTION

Volatile organic compounds (VOCs) can arise from underlying metabolism and are detectable in exhaled breath, therefore offer a promising route to non-invasive diagnostics. Robust, precise, and repeatable breath measurement platforms able to identify VOCs in breath distinguishable from background contaminants are needed for the confident discovery of breath-based biomarkers.

OBJECTIVES

To build a reliable breath collection and analysis method that can produce a comprehensive list of known VOCs in the breath of a heterogeneous human population.

METHODS

The analysis cohort consisted of 90 pairs of breath and background samples collected from a heterogenous population. Owlstone Medical's Breath Biopsy® OMNI® platform, consisting of sample collection, TD-GC-MS analysis and feature extraction was utilized. VOCs were determined to be "on-breath" if they met at least one of three pre-defined metrics compared to paired background samples. On-breath VOCs were identified via comparison against purified chemical standards, using retention indexing and high-resolution accurate mass spectral matching.

RESULTS

1471 VOCs were present in > 80% of samples (breath and background), and 585 were on-breath by at least one metric. Of these, 148 have been identified covering a broad range of chemical classes.

CONCLUSIONS

A robust breath collection and relative-quantitative analysis method has been developed, producing a list of 148 on-breath VOCs, identified using purified chemical standards in a heterogenous population. Providing confirmed VOC identities that are genuinely breath-borne will facilitate future biomarker discovery and subsequent biomarker validation in clinical studies. Additionally, this list of VOCs can be used to facilitate cross-study data comparisons for improved standardization.

Combination of real-time and hyphenated mass spectrometry for improved characterisation of exhaled breath biomarkers in clinical research

Exhaled breath volatilomics is a powerful non-invasive tool for biomarker discovery in medical applications, but compound annotation is essential for pathophysiological insights and technology transfer. This study was aimed at investigating the interest of a hybrid approach combining real-time proton transfer reaction-time-of-flight mass spectrometry (PTR-TOF-MS) with comprehensive thermal desorption-two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (TD-GCxGC-TOF-MS) to enhance the analysis and characterization of VOCs in clinical research, using COVID-19 as a use case. VOC biomarker candidates were selected from clinical research using PTR-TOF-MS fingerprinting in patients with COVID-19 and matched to the Human Breathomic Database. Corresponding analytical standards were analysed using both a liquid calibration unit coupled to PTR-TOF-MS and TD-GCxGC-TOF-MS, together with confirmation on new clinical samples with TD-GCxGC-TOF-MS. From 26 potential VOC biomarkers, 23 were successfully detected with PTR-TOF-MS. All VOCs were successfully detected using TD-GCxGC-TOF-MS, providing effective separation of highly chemically related compounds, including isomers, and enabling high-confidence annotation based on two-dimensional chromatographic separation and mass spectra. Four VOCs were identified with a level 1 annotation in the clinical samples. For future applications, the combination of real-time PTR-TOF-MS and comprehensive TD-GCxGC-TOF-MS, at least on a subset of samples from a whole study, would enhance the performance of VOC annotation, offering potential advancements in biomarker discovery for clinical research.

Analysis of urinary volatile organic compounds for prostate cancer diagnosis: A systematic review

Context

Prostate-specific antigen is non-specific for prostate cancer. This is improved by multiparametric MRI but a significant amount of indolent prostate cancer is detected by the current MRI pathway and data is emerging that clinically significant cancers maybe missed using a standard PSA threshold. Volatile organic compound (VOC) analysis may offer novel biomarkers for prostate cancer and clinically significant disease.

Objective

To perform a systematic review of the literature to evaluate the current evidence for the use of VOCs as novel biomarkers for prostate cancer and clinically significant prostate cancer.

Evidence Acquisition

A systematic search of MEDLINE, Scopus, Web of Science and the Cochrane Library was undertaken by two independent reviewers and papers were assessed for inclusion in the review. Study characteristics, sensitivity and specificity of GC-MS or eNose were extracted. Risk of bias and applicability issues were determined using QUADAS 2 and the quality of reporting using the STARD checklist.

Evidence Synthesis

Nineteen studies were included, of which 6 utilised eNose and 13 GC-MS. eNose sensitivity and specificity were 0.71-0.95 and 0.79-0.96, respectively, and GC-MS found a sensitivity and specificity of 0.66-1.00 and 0.53-0.97, respectively. There were concerns about bias in patient recruitment due to differences in the timing of the index test relative to the reference standard.

Conclusion

This review has found promising early results for urinary metabolomics in the detection of prostate cancer. However, there is a need for larger, high-quality studies to validate this. Future work should focus on the detection of clinically significant prostate cancer.

Prospect and Challenges of Volatile Organic Compound Breath Testing in Non-Cancer Gastrointestinal Disorders

Breath analysis, despite being an overlooked biomatrix, has a rich history in disease diagnosis. However, volatile organic compounds (VOCs) have yet to establish themselves as clinically validated biomarkers for specific diseases. As focusing solely on late-stage or malignant disease biomarkers may have limited relevance in clinical practice, the objective of this review is to explore the potential of VOC breath tests for the diagnosis of non-cancer diseases: (1) Precancerous conditions like gastro-esophageal reflux disease (GERD) and Barrett's esophagus (BE), where breath tests can complement endoscopic screening; (2) endoluminal diseases associated with autoinflammation and dysbiosis, such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and coeliac disease, which currently rely on biopsy and symptom-based diagnosis; (3) chronic liver diseases like cirrhosis, hepatic encephalopathy, and non-alcoholic fatty liver disease, which lack non-invasive diagnostic tools for disease progression monitoring and prognostic assessment. A literature search was conducted through EMBASE, MEDLINE, and Cochrane databases, leading to an overview of 24 studies. The characteristics of these studies, including analytical platforms, disorder type and stage, group size, and performance evaluation parameters for diagnostic tests are discussed. Furthermore, how VOCs can be utilized as non-invasive diagnostic tools to complement existing gold standards is explored. By refining study designs, sampling procedures, and comparing VOCs in urine and blood, we can gain a deeper understanding of the metabolic pathways underlying VOCs. This will establish breath analysis as an effective non-invasive method for differential diagnosis and disease monitoring.

Innovative Approach for Human Semen Quality Assessment Based on Volatilomics

The volatilome profile of some biofluids (blood, urine, and human semen) identified by Solid-Phase Microextraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and collected from young men living in two high-pollution areas in Italy, i.e., Land of Fires and Valley of Sacco River, have been coupled to sperm parameters obtained by spermiogram analysis to build general multiple regression models. Panels of volatile organic compounds (VOCs) have been selected to optimize the models and used as predictive variables to estimate the different sperm quality parameters (sperm cell concentration, total and progressive motility/immotile cells, total/head/neck/tail morphology anomalies, semen round cell concentration). The results of the multiple linear regression models based on the different subgroups of data joining VOCs from one/two or three biofluids have been compared. Surprisingly, the models based on blood and urine VOCs have allowed an excellent estimate of spermiogram values, paving the way towards a new method of indirect evaluation of semen quality and preventive screening. The significance of VOCs in terms of toxicity and dangerousness was discussed with the support of chemical databases available online.

Rapid differentiation of cystic fibrosis-related bacteria via reagentless atmospheric pressure photoionisation mass spectrometry

Breath analysis is an area of significant interest in medical research as it allows for non-invasive sampling with exceptional potential for disease monitoring and diagnosis. Volatile organic compounds (VOCs) found in breath can offer critical insight into a person's lifestyle and/or disease/health state. To this end, the development of a rapid, sensitive, cost-effective and potentially portable method for the detection of key compounds in breath would mark a significant advancement. Herein, we have designed, built and tested a novel reagent-less atmospheric pressure photoionisation (APPI) source, coupled with mass spectrometry (MS), utilising a bespoke bias electrode within a custom 3D printed sampling chamber for direct analysis of VOCs. Optimal APPI-MS conditions were identified, including bias voltage, cone voltage and vaporisation temperature. Calibration curves were produced for ethanol, acetone, 2-butanone, ethyl acetate and eucalyptol, yielding R2 > 0.99 and limits of detection < 10 pg. As a pre-clinical proof of concept, this method was applied to bacterial headspace samples of Escherichia coli (EC), Pseudomonas aeruginosa (PSA) and Staphylococcus aureus (SA) collected in 1 L Tedlar bags. In particular, PSA and SA are commonly associated with lung infection in cystic fibrosis patients. The headspace samples were classified using principal component analysis with 86.9% of the total variance across the first three components and yielding 100% classification in a blind-sample study. All experiments conducted with the novel APPI arrangement were carried out directly in real-time with low-resolution MS, which opens up exciting possibilities in the future for on-site (e.g., in the clinic) analysis with a portable system.

Defining a core breath profile for healthy, non-human primates

Non-human primates remain the most useful and reliable pre-clinical model for many human diseases. Primate breath profiles have previously distinguished healthy animals from diseased, including non-human primates. Breath collection is relatively non-invasive, so this motivated us to define a healthy baseline breath profile that could be used in studies evaluating disease, therapies, and vaccines in non-human primates. A pilot study, which enrolled 30 healthy macaques, was conducted. Macaque breath molecules were sampled into a Tedlar bag, concentrated onto a thermal desorption tube, then desorbed and analyzed by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry. These breath samples contained 2,017 features, of which 113 molecules were present in all breath samples. The core breathprint was dominated by aliphatic hydrocarbons, aromatic compounds, and carbonyl compounds. The data were internally validated with additional breath samples from a subset of 19 of these non-human primates. A critical core consisting of 23 highly abundant and invariant molecules was identified as a pragmatic breathprint set, useful for future validation studies in healthy primates.

Sample Collection and Processing in Volatile Organic Compound Analysis for Gastrointestinal Cancers

Volatile organic compounds have drawn significant attention in recent years as a novel tool for non-invasive detection of a wide range of diseases, including gastrointestinal cancers, for which the need for effective, affordable, and non-invasive screening methods is substantial. Sample preparation is a fundamental step that greatly influences the quality of results and the feasibility of wide-range applications. This review summarizes sampling methods used in studies aiming at testing the diagnostic value of volatile organic compounds in gastrointestinal cancers, discussing in detail some of the recent advancements in automated sampling techniques. Finally, we propose some directions in which sample collection and processing can improve for VOC analysis to be popularized in clinical settings.

Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis

Monitoring health conditions in neonates for early therapeutic intervention in case deviations from physiological conditions is crucial for their long-term development. Due to their immaturity preterm born neonates are dependent on particularly careful physical and neurological diagnostic methods. Ideally, these should be noninvasive, noncontact, and radiation free. Infrared spectroscopy was used to analyze exhaled breath from 71 neonates with a special emphasis on preterm infants, as a noninvasive, noncontact, and radiation-free diagnostic tool. Passive sample collection was performed by skilled clinicians. Depending on the mode of respiratory support of infants, four different sampling procedures were adapted to collect exhaled breath. With the aid of appropriate reference samples, infrared spectroscopy has successfully demonstrated its effectiveness in the analysis of breath samples of neonates. The discernible increase in concentrations of carbon dioxide, carbon monoxide, and methane in collected samples compared to reference samples served as compelling evidence of the presence of exhaled breath. With regard to technical hurdles and sample analysis, samples collected from neonates without respiratory support proved to be more advantageous compared to those obtained from intubated infants and those with CPAP (continuous positive airway pressure). The main obstacle lies in the significant dilution of exhaled breath in the case of neonates receiving respiratory support. Metabolic analysis of breath samples holds promise for the development of noninvasive biomarker-based diagnostics for both preterm and sick neonates provided an adequate amount of breath is collected.

Internal Standard Addition System for Online Breath Analysis

Breath analysis with secondary electrospray ionization (SESI) coupled to mass spectrometry (MS) is a sensitive method for breath metabolomics. To enable quantitative assessments using SESI-MS, a system was developed to introduce controlled amounts of gases into breath samples and carry out standard addition experiments. The system combines gas standard generation through controlled evaporation, humidification, breath dilution, and standard injection with the help of mass-flow controllers. The system can also dilute breath, which affects the signal of the detected components. This response can be used to filter out contaminating compounds in an untargeted metabolomics workflow. The system's quantitative capabilities have been shown through standard addition of pyridine and butyric acid into breath in real time. This system can improve the quality and robustness of breath data.

Progress and challenges of developing volatile metabolites from exhaled breath as a biomarker platform

BACKGROUND

The multitude of metabolites generated by physiological processes in the body can serve as valuable biomarkers for many clinical purposes. They can provide a window into relevant metabolic pathways for health and disease, as well as be candidate therapeutic targets. A subset of these metabolites generated in the human body are volatile, known as volatile organic compounds (VOCs), which can be detected in exhaled breath. These can diffuse from their point of origin throughout the body into the bloodstream and exchange into the air in the lungs. For this reason, breath VOC analysis has become a focus of biomedical research hoping to translate new useful biomarkers by taking advantage of the non-invasive nature of breath sampling, as well as the rapid rate of collection over short periods of time that can occur. Despite the promise of breath analysis as an additional platform for metabolomic analysis, no VOC breath biomarkers have successfully been implemented into a clinical setting as of the time of this review.

AIM OF REVIEW

This review aims to summarize the progress made to address the major methodological challenges, including standardization, that have historically limited the translation of breath VOC biomarkers into the clinic. We highlight what steps can be taken to improve these issues within new and ongoing breath research to promote the successful development of the VOCs in breath as a robust source of candidate biomarkers. We also highlight key recent papers across select fields, critically reviewing the progress made in the past few years to advance breath research.

KEY SCIENTIFIC CONCEPTS OF REVIEW

VOCs are a set of metabolites that can be sampled in exhaled breath to act as advantageous biomarkers in a variety of clinical contexts.

Distinguish Esophageal Cancer Cells through VOCs Induced by Methionine Regulation

Detection of exhaled volatile organic compounds (VOCs) is promising for noninvasive screening of esophageal cancer (EC). Cellular VOC analysis can be used to investigate potential biomarkers. Considering the crucial role of methionine (Met) during cancer development, exploring associated abnormal metabolic phenotypes becomes imperative. In this work, we employed headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) to investigate the volatile metabolic profiles of EC cells (KYSE150) and normal esophageal epithelial cells (HEECs) under a Met regulation strategy. Using untargeted approaches, we analyzed the metabolic VOCs of the two cell types and explored the differential VOCs between them. Subsequently, we utilized targeted approaches to analyze the differential VOCs in both cell types under gradient Met culture conditions. The results revealed that there were five/six differential VOCs between cells under Met-containing/Met-free culture conditions. And the difference in levels of two characteristic VOCs (1-butanol and ethyl 2-methylbutyrate) between the two cell types intensified with the increase of the Met concentration. Notably, this is the first report on VOC analysis of EC cells and the first to consider the effect of Met on volatile metabolic profiles. The present work indicates that EC cells can be distinguished through VOCs induced by Met regulation, which holds promise for providing novel insights into diagnostic strategies.

How Does Personal Hygiene Influence Indoor Air Quality?

Humans are known to be a continuous and potent indoor source of volatile organic compounds (VOCs). However, little is known about how personal hygiene, in terms of showering frequency, can influence these emissions and their impact on indoor air chemistry involving ozone. In this study, we characterized the VOC composition of the air in a controlled climate chamber (22.5 m3 with an air change rate at 3.2 h-1) occupied by four male volunteers on successive days under ozone-free (∼0 ppb) and ozone-present (37-40 ppb) conditions. The volunteers either showered the evening prior to the experiments or skipped showering for 24 and 48 h. Reduced shower frequency increased human emissions of gas-phase carboxylic acids, possibly originating from skin bacteria. With ozone present, increasing the number of no-shower days enhanced ozone-skin surface reactions, yielding higher levels of oxidation products. Wearing the same clothing over several days reduced the level of compounds generated from clothing-ozone reactions. When skin lotion was applied, the yield of the skin ozonolysis products decreased, while other compounds increased due to ozone reactions with lotion ingredients. These findings help determine the degree to which personal hygiene choices affect the indoor air composition and indoor air exposures.

The Potential of Fecal Volatile Organic Compound Analysis for the Early Diagnosis of Late-Onset Sepsis in Preterm Infants: A Narrative Review

Early diagnosis and treatment of late-onset sepsis (LOS) is crucial for survival, but challenging. Intestinal microbiota and metabolome alterations precede the clinical onset of LOS, and the preterm gut is considered an important source of bacterial pathogens. Fecal volatile organic compounds (VOCs), formed by physiologic and pathophysiologic metabolic processes in the preterm gut, reflect a complex interplay between the human host, the environment, and microbiota. Disease-associated fecal VOCs can be detected with an array of devices with various potential for the development of a point-of-care test (POCT) for preclinical LOS detection. While characteristic VOCs for common LOS pathogens have been described, their VOC profiles often overlap with other pathogens due to similarities in metabolic pathways, hampering the construction of species-specific profiles. Clinical studies have, however, successfully discriminated LOS patients from healthy individuals using fecal VOC analysis with the highest predictive value for Gram-negative pathogens. This review discusses the current advancements in the development of a non-invasive fecal VOC-based POCT for early diagnosis of LOS, which may potentially provide opportunities for early intervention and targeted treatment and could improve clinical neonatal outcomes. Identification of confounding variables impacting VOC synthesis, selection of an optimal detection device, and development of standardized sampling protocols will allow for the development of a novel POCT in the near future.

Volatile Organic Compounds in Cellular Headspace after Hyperbaric Oxygen Exposure: An In Vitro Pilot Study

Volatile organic compounds (VOCs) might be associated with pulmonary oxygen toxicity (POT). This pilot study aims to identify VOCs linked to oxidative stress employing an in vitro model of alveolar basal epithelial cells exposed to hyperbaric and hyperoxic conditions. In addition, the feasibility of this in vitro model for POT biomarker research was evaluated. The hyperbaric exposure protocol, similar to the U.S. Navy Treatment Table 6, was conducted on human alveolar basal epithelial cells, and the headspace VOCs were analyzed using gas chromatography-mass spectrometry. Three compounds (nonane [p = 0.005], octanal [p = 0.009], and decane [p = 0.018]), of which nonane and decane were also identified in a previous in vivo study with similar hyperbaric exposure, varied significantly between the intervention group which was exposed to 100% oxygen and the control group which was exposed to compressed air. VOC signal intensities were lower in the intervention group, but cellular stress markers (IL8 and LDH) confirmed increased stress and injury in the intervention group. Despite the observed reductions in compound expression, the model holds promise for POT biomarker exploration, emphasizing the need for further investigation into the complex relationship between VOCs and oxidative stress.

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

Electroactive nanofibrous membrane with antibacterial and deodorizing properties for air filtration

Water vapor from respiration can severely accelerate the charge dissipation of the face mask, reducing filtration efficiency. Moreover, the foul odor from prolonged mask wear tends to make people remove their masks, leading to the risk of infection. In this study, an electro-blown spinning electroactive nanofibrous membrane (Zn/CB@PAN) with antibacterial and deodorization properties was prepared by adding zinc (Zn) and carbon black (CB) nanoparticles to the polyacrylonitrile (PAN) nanofibers, respectively. The filtration efficiency of Zn/CB@PAN for PM0.3 was > 99% and could still maintain excellent durability within 4 h in a high-humidity environment (25 ℃ and RH = 95%). Moreover, the bacterial interception rate of the Zn/CB@PAN could reach 99.99%, and it can kill intercepted bacteria. In addition, the deodorization rate of Zn/CB@PAN in the moist state for acetic acid was 93.75% and ammonia was 95.23%, respectively. The excellent filtering, antibacterial, and deodorizing performance of Zn/CB@PAN can be attributed to the synergistic effect of breath-induced Zn/CB galvanic couples' electroactivity, released metal ions, and generated reactive oxygen species. The developed Zn/CB@PAN could capture and kill airborne environmental pathogens under humid environments and deodorize odors from prolonged wear, holding promise for broad applications as personal protective masks.

Curry-Odorants and Their Metabolites Transfer into Human Milk and Urine

SCOPE

The excretion of dietary odorants into urine and milk is evaluated and the impact of possible influencing factors determined. Furthermore, the metabolic relevance of conjugates for the excretion into milk is investigated.

METHODS AND RESULTS

Lactating mothers (n = 20) are given a standardized curry dish and donated one milk and urine sample each before and 1, 2, 3, 4.5, 6, and 8 h after the intervention. The concentrations of nine target odorants in these samples are determined. A significant transition is observed for linalool into milk, as well as for linalool, cuminaldehyde, cinnamaldehyde, and eugenol into urine. Maximum concentrations are reached within 1 h after the intervention in the case of milk and within 2-3 h in the case of urine. In addition, the impact of glucuronidase treatment on odorant concentrations is evaluated in a sample subset of twelve mothers. Linalool, eugenol, and vanillin concentrations increased 3-77-fold in milk samples after treatment with β-glucuronidase.

CONCLUSION

The transfer profiles of odorants into milk and urine differ qualitatively, quantitatively, and in temporal aspects. More substances are transferred into urine and the transfer needs a longer period compared with milk. Phase II metabolites are transferred into urine and milk.

Skin emitted volatiles analysis for noninvasive diagnosis: the current advances in sample preparation techniques for biomedical application

Human skin emits a series of volatile compounds from the skin due to various metabolic processes, microbial activity, and several external factors. Changes in the concentration of skin volatile metabolites indicate many diseases, including diabetes, cancer, and infectious diseases. Researchers focused on skin-emitted compounds to gain insight into the pathophysiology of various diseases. In the case of skin volatolomics research, it is noteworthy that sample preparation, sampling protocol, analytical techniques, and comprehensive validation are important for the successful integration of skin metabolic profiles into regular clinical settings. Solid-phase microextraction techniques and polymer-based active sorbent traps were developed to capture the skin-emitted volatile compounds. The primary advantage of these sample preparation techniques is the ability to efficiently and targetedly capture skin metabolites, thus improving the detection of the biomarkers associated with various diseases. In further research, polydimethyl-based patches were utilized for skin research due to their biocompatibility and thermal stability properties. The microextraction sampling tools coupled with high sensitive Gas Chromatography-Mass Spectrometer provided a potential platform for skin volatolomes, thus emerging as a state-of-the-art analytical technique. Later, technological advancements, including the design of wearable sensors, have enriched skin-based research as it can integrate the information from skin-emitted volatile profiles into a portable platform. However, individual-specific hydration, temperature, and skin conditions can influence variations in skin volatile concentration. Considering the subject-specific skin depth, sampling time standardization, and suitable techniques may improve the skin sampling techniques for the potential discovery of various skin-based marker compounds associated with diseases. Here, we have summarised the current research progress, limitations, and technological advances in skin-based sample preparation techniques for disease diagnosis, monitoring, and personalized healthcare applications.

Predicting Chronological Age via the Skin Volatile Profile

Skin volatile emissions offer a noninvasive insight into metabolic activity within the body as well as the skin microbiome and specific volatile compounds have been shown to correlate with age, albeit only in a few small studies. Building on this, here skin volatiles were collected and analyzed in a healthy participant study (n = 60) using a robust headspace-solid phase microextraction (HS-SPME) gas chromatography-mass spectrometry (GC-MS) workflow. Following processing, 18 identified compounds were deemed suitable for this study. These were classified according to gender influences and their correlations with age were investigated. Finally, 6 volatiles (of both endogenous and exogenous origin) were identified as significantly changing in abundance with participant age (p < 0.1). The potential origins of these dysregulations are discussed. Multiple linear regression (MLR) analysis was employed to model age based on these significant volatiles as independent variables, along with gender. Our analysis shows that skin volatiles show a strong predictive ability for age (explained variance of 68%), stronger than other biochemical measures collected in this study (skin surface pH, water content) which are understood to vary with chronological age. Overall, this work provides new insights into the impact of aging on the skin volatile profiles which comprises both endogenously and exogenously derived volatile compounds. It goes toward demonstrating the biological significance of skin volatiles and will help pave the way for more rigorous consideration of the healthy "baseline" skin volatile profile in volatilomics-based health diagnostics development going forward.

New perspectives on 'Breathomics': metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS

Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. "Breathomics" as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath.

[Therapeutics in cystic fibrosis: Clinical revolution and new challenges]

Over time, cystic fibrosis has become a model of synergy between research in pathophysiology and cell biology, and clinical advances. Therapies targeting the CFTR protein, in particular CFTR modulators, have transformed the prognosis of patients, bringing the hope of a normal life with the possibility of starting a family and growing old, challenging established statistics. However, patients are not yet cured, and side effects remain insufficiently documented. Epidemiological changes create new challenges for the management of cystic fibrosis. Approximately 10 % of patients still lack a therapeutic option. The community of researchers, pharmaceutical industries, patient associations, and health authorities remains committed to monitor the long-term effects of these still poorly characterised treatments, and to explore new pharmacological approaches, such as gene therapies.

Development of an automated human scent olfactometer and its use to evaluate detection dog perception of human scent

Working Dogs have shown an extraordinary ability to utilize olfaction for victim recovery efforts. Although instrumental analysis has chemically characterized odor volatiles from various human biospecimens, it remains unclear what perceptually constitutes human scent (HS) for dogs. This may be in part due to the lack of methodology and equipment to train and evaluate HS perception. The aims of this research were 1) to develop an automated human scent olfactometer (AHSO) to present HS to dogs in a controlled setting and 2) use the AHSO to evaluate dogs' response to different scented articles and individual components of HS. A human volunteer was placed in a clear acrylic chamber and using a vacuum pump and computer-controlled valves, the headspace of this chamber was carried to one of three ports in a different room. Dogs were trained to search all three ports of the olfactometer and alert to the one containing HS. In Experiment 1 and 2, the AHSO was validated by testing two dogs naïve to HS (Experiment 1) and five certified Search and Rescue (SAR) teams naïve to the apparatus (Experiment 2). All dogs showed sensitivity and specificity to HS > 95% in the apparatus. In Experiment 3, we used a spontaneous generalization paradigm to evaluate generalization from the HS chamber to different scented articles exposed to the same volunteer and to a breath sample. Dogs' response rate to the different scented articles was < 10% but exceeded 40% for the breath sample. In Experiment 4, we replicated this result by re-testing spontaneous generalization to breath and when the volunteer had breath exhausted/removed from the chamber. Dogs' response rate to breath alone was 88% and only 50% when breath was removed. Altogether, the data indicate that exhaled breath is an important and salient component of HS under these conditions.

Exhaled breath and urinary volatile organic compounds (VOCs) for cancer diagnoses, and microbial-related VOC metabolic pathway analysis: a systematic review and meta-analysis

BACKGROUND

The gradual evolution of the detection and quantification of volatile organic compounds (VOCs) has been instrumental in cancer diagnosis. The primary objective of this study was to assess the diagnostic potential of exhaled breath and urinary VOCs in cancer detection. As VOCs are indicative of tumor and human metabolism, our work also sought to investigate the metabolic pathways linked to the development of cancerous tumors.

MATERIALS AND METHODS

An electronic search was performed in the PubMed database. Original studies on VOCs within exhaled breath and urine for cancer detection with a control group were included. A meta-analysis was conducted using a bivariate model to assess the sensitivity and specificity of the VOCs for cancer detection. Fagan's nomogram was designed to leverage the findings from our diagnostic analysis for the purpose of estimating the likelihood of cancer in patients. Ultimately, MetOrigin was employed to conduct an analysis of the metabolic pathways associated with VOCs in relation to both human and/or microbiota.

RESULTS

The pooled sensitivity, specificity and the area under the curve for cancer screening utilizing exhaled breath and urinary VOCs were determined to be 0.89, 0.88, and 0.95, respectively. A pretest probability of 51% can be considered as the threshold for diagnosing cancers with VOCs. As the estimated pretest probability of cancer exceeds 51%, it becomes more appropriate to emphasize the 'ruling in' approach. Conversely, when the estimated pretest probability of cancer falls below 51%, it is more suitable to emphasize the 'ruling out' approach. A total of 14, 14, 6, and 7 microbiota-related VOCs were identified in relation to lung, colorectal, breast, and liver cancers, respectively. The enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in the aforementioned tumor types.

CONCLUSIONS

The analysis of exhaled breath and urinary VOCs showed promise for cancer screening. In addition, the enrichment analysis of volatile metabolites revealed a significant enrichment of butanoate metabolism in four tumor types, namely lung, colorectum, breast and liver. These findings hold significant implications for the prospective clinical application of multiomics correlation in disease management and the exploration of potential therapeutic targets.

A Clinical Breathomics Dataset

This study entailed a comprehensive GC‒MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature. The highlighted noninvasive approach for detecting these breath molecules significantly enhances diagnostic and monitoring capacities. This dataset cataloged volatile organic compounds (VOCs) from the breath of individuals with asthma, bronchiectasis, and chronic obstructive pulmonary disease. Uniform and consistent sample collection protocols were strictly adhered to during the accumulation of this extensive dataset, ensuring its reliability. It encapsulates extensive human clinical breath molecule data pertinent to three specific diseases. This consequential clinical breathomics dataset is a crucial resource for researchers and clinicians in identifying and exploring important compounds within the patient's breath, thereby augmenting future diagnostic and therapeutic initiatives.

The optimization and comparison of two high-throughput faecal headspace sampling platforms: the microchamber/thermal extractor and hi-capacity sorptive extraction probes (HiSorb)

Disease detection and monitoring using volatile organic compounds (VOCs) is becoming increasingly popular. For a variety of (gastrointestinal) diseases the microbiome should be considered. As its output is to large extent volatile, faecal volatilomics carries great potential. One technical limitation is that current faecal headspace analysis requires specialized instrumentation which is costly and typically does not work in harmony with thermal desorption units often utilized in e.g. exhaled breath studies. This lack of harmonization hinders uptake of such analyses by the Volatilomics community. Therefore, this study optimized and compared two recently harmonized faecal headspace sampling platforms:High-capacity Sorptive extraction (HiSorb) probesand theMicrochamber thermal extractor (Microchamber). Statistical design of experiment was applied to find optimal sampling conditions by maximizing reproducibility, the number of VOCs detected, and between subject variation. To foster general applicability those factors were defined using semi-targeted as well as untargeted metabolic profiles. HiSorb probes were found to result in a faster sampling procedure, higher number of detected VOCs, and higher stability. The headspace collection using the Microchamber resulted in a lower number of detected VOCs, longer sampling times and decreased stability despite a smaller number of interfering VOCs and no background signals. Based on the observed profiles, recommendations are provided on pre-processing and study design when using either one of both platforms. Both can be used to perform faecal headspace collection, but altogether HiSorb is recommended.

Development and integration of a hierarchical Pd/WO3 acetone-sensing device for real-time exhaled breath monitoring with disposable face mask

This study introduces an inventive acetone-sensing device seamlessly integrated into a disposable face mask, enabling real-time continuous breath monitoring. The sensor demonstrates exceptional sensitivity, registering a response of 8.22 at 1 ppm and an impressive sensor response of 57.33 at 100 ppm of acetone concentration. Particularly noteworthy is the remarkable lower limit of detection (LOD) of 0.076 ppm within the concentration range of 0.1-0.8 ppm, underscored by a robust R2 value of 0.994. To validate practicality, the Pd/WO3 sensor was fabricated onto cellulose paper and utilized for real-time breath analysis, yielding a substantial sensor response of 1.70 at 8 vol% (equivalent to a single exhale breath volume). The unique design incorporates a built-in disposable face mask, facilitating dependable and convenient real-time breath analysis. Additionally, this research explores the profound impact of introducing acetone and Pd atoms on the energy levels and dipole moments. The species elucidated through density functional theory (DFT) investigations encompassing WO3, WO3-acetone, Pd-WO3, and Pd-WO3-acetone species. This work presents an innovative and cost-effective approach for developing a portable, non-invasive, and highly sensitive acetone-sensing device, effectively integrated into a disposable face mask for real-time breath analysis. This pioneering technology holds immense potential for various applications in healthcare and beyond.

Combining Thermal Desorption with Selected Ion Flow Tube Mass Spectrometry for Analyses of Breath Volatile Organic Compounds

An instrument integrating thermal desorption (TD) to selected ion flow tube mass spectrometry (SIFT-MS) is presented, and its application to analyze volatile organic compounds (VOCs) in human breath is demonstrated for the first time. The rationale behind this development is the need to analyze breath samples in large-scale multicenter clinical projects involving thousands of patients recruited in different hospitals. Following adapted guidelines for validating analytical techniques, we developed and validated a targeted analytical method for 21 compounds of diverse chemical class, chosen for their clinical and biological relevance. Validation has been carried out by two independent laboratories, using calibration standards and real breath samples from healthy volunteers. The merging of SIFT-MS and TD integrates the rapid analytical capabilities of SIFT-MS with the capacity to collect breath samples across multiple hospitals. Thanks to these features, the novel instrument has the potential to be easily employed in clinical practice.

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.

GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review

Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.