Volatile compounds in human breath: critical review and meta-analysis

Technical approaches for breath aldehyde biomarker detection and disease diagnosis: A review

Exhaled breath analysis holds promise as a non-invasive approach for disease diagnosis. Aldehydes represent a class of volatile organic compounds with diagnostic potential as breath biomarkers for cancers and other conditions. However, aldehydes exist at low concentrations in breath and have stability challenges. This review summarizes recent studies on breath aldehyde analysis, focusing on sample collection methodology, analytical techniques implemented, and key findings regarding aldehyde alterations in disease. Breath collection methods examined include commercial bags, end-tidal sampling devices, condensates, and direct analysis. Analytical techniques evaluated gas chromatography, mass spectrometry, and microextraction approaches. Emerging microextraction and sensing technologies are advancing real-time, non-invasive aldehyde detection. Overall, breath aldehyde biomarkers offer immense potential for diagnosis and screening, but continued research is needed to address current limitations. This review provides insights to guide future efforts focused on exhaled aldehyde analysis and disease detection.

Early Screening and Subtype Identification of High-Risk Lung Nodules via Breathprint by Graphene eNose Platform: A Large Cohort Study

Early screening of individuals with high-risk lung nodules can significantly improve the prognosis of lung cancer patients, and accurate identification of lung nodule subtypes can provide guidance for medical treatment. Exhaled breath (EB) analysis via eNoses offers a quick and noninvasive approach, but current eNose technology lacks quality control and solid validation in large population studies. Herein, an eNose platform integrated with a metal ion-decorated graphene sensor array and a breath sampling accessory was established. EB samples from 427 healthy subjects and 2586 subjects with lung nodules, including various benign and malignant subtypes, were collected through the breath sampling accessory for quality control. The large-cohort clinical EB samples were analyzed by the eNose platform to acquire the cross-reactive resistance response. Breathprint analysis for high-risk lung nodules using SVM and age-matched training sets yielded strong and robust performance. Combined with baseline data, the model achieved an AUC of 0.93 (95% CI, 0.89-0.96) on the external test set, with 97% sensitivity and 73% specificity. Moreover, dimensionality reduction analysis of breathprints demonstrated separability across different lung nodule subtypes. This study demonstrates the reliability of the graphene eNose platform to identify high-risk lung nodules and classify lung nodule subtypes in a noninvasive and rapid method.

Assessing the impact of volatile organic compounds on cardiovascular health: Insights from the National Health and Nutrition Examination Survey 2011-2020

Volatile organic compounds (VOCs) are environmental pollutants that may negatively impact cardiovascular health. This study investigates the association between VOC mixtures, measured through urinary VOC metabolites (VOCMs), and cardiovascular health using Life's Essential 8 (LE8) scores. Data from the National Health and Nutrition Examination Survey (NHANES) 2011-2020 were analyzed for 2967 adults aged 20-79 years. Multiple statistical methods, including correlation analysis, variance inflation factor (VIF) analysis, quantile g-computation (q-gcomp), and Bayesian kernel machine regression (BKMR), were applied to assess the association between VOCMs and LE8 scores. Sensitivity analyses were conducted with different random seeds and subsampling techniques to confirm robustness. Correlation and VIF analyses revealed strong collinearity among VOCMs, highlighting the need for advanced models. Survey-weighted regression indicated that lower VOC exposure was associated with better cardiovascular health. Q-gcomp identified both positive and negative associations between individual VOCMs and LE8 scores, with some unexpected positive associations. BKMR highlighted the complex mixture effects of VOCMs on cardiovascular health. Sensitivity analyses confirmed the consistency of these findings. This study underscores the intricate relationship between VOC exposure and cardiovascular health and the necessity of advanced statistical methods for mixture analysis. Despite some unexpected findings, the results suggest that VOC exposure, as reflected by urinary VOCMs, is associated with adverse cardiovascular health outcomes. Further research is needed to clarify the biological mechanisms and implications of these associations.

Exhaled Breath Analysis: From Laboratory Test to Wearable Sensing

Breath analysis and monitoring have emerged as pivotal components in both clinical research and daily health management, particularly in addressing the global health challenges posed by respiratory and metabolic disorders. The advancement of breath analysis strategies necessitates a multidisciplinary approach, seamlessly integrating expertise from medicine, biology, engineering, and materials science. Recent innovations in laboratory methodologies and wearable sensing technologies have ushered in an era of precise, real-time, and in situ breath analysis and monitoring. This comprehensive review elucidates the physical and chemical aspects of breath analysis, encompassing respiratory parameters and both volatile and non-volatile constituents. It emphasizes their physiological and clinical significance, while also exploring cutting-edge laboratory testing techniques and state-of-the-art wearable devices. Furthermore, the review delves into the application of sophisticated data processing technologies in the burgeoning field of breathomics and examines the potential of breath control in human-machine interaction paradigms. Additionally, it provides insights into the challenges of translating innovative laboratory and wearable concepts into mainstream clinical and daily practice. Continued innovation and interdisciplinary collaboration will drive progress in breath analysis, potentially revolutionizing personalized medicine through entirely non-invasive breath methodology.

Optimized breath analysis: customized analytical methods and enhanced workflow for broader detection of VOCs

INTRODUCTION

Breath Volatile organic compounds (VOCs) are promising biomarkers for clinical purposes due to their unique properties. Translation of VOC biomarkers into the clinic depends on identification and validation: a challenge requiring collaboration, well-established protocols, and cross-comparison of data. Previously, we developed a breath collection and analysis method, resulting in 148 breath-borne VOCs identified.

OBJECTIVES

To develop a complementary analytical method for the detection and identification of additional VOCs from breath. To develop and implement upgrades to the methodology for identifying features determined to be "on-breath" by comparing breath samples against paired background samples applying three metrics: standard deviation, paired t-test, and receiver-operating-characteristic (ROC) curve.

METHODS

A thermal desorption (TD)-gas chromatography (GC)-mass spectrometry (MS)-based analytical method utilizing a PEG phase GC column was developed for the detection of biologically relevant VOCs. The multi-step VOC identification methodology was upgraded through several developments: candidate VOC grouping schema, ion abundance correlation based spectral library creation approach, hybrid alkane-FAMES retention indexing, relative retention time matching, along with additional quality checks. In combination, these updates enable highly accurate identification of breath-borne VOCs, both on spectral and retention axes.

RESULTS

A total of 621 features were statistically determined as on-breath by at least one metric (standard deviation, paired t-test, or ROC). A total of 38 on-breath VOCs were able to be confidently identified from comparison to chemical standards.

CONCLUSION

The total confirmed on-breath VOCs is now 186. We present an updated methodology for high-confidence VOC identification, and a new set of VOCs commonly found on-breath.

Stability of volatile organic compounds in thermal desorption tubes and in solution

Exhaled breath volatile organic compounds (VOCs) are often collected and stored in sorbent tubes before thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) analysis. Information about the stability of VOCs during storage is needed to account for potential artifacts and monitor for losses. Additionally, information about the stability of VOC standards in solution is required to assess their performance as quality control and internal standards. We evaluated the stability of a standard mixture of 42 VOCs in dual-sorbent tubes containing Tenax® TA and Carbotrap 1TD over 60 d at commonly used storage conditions: room temperature (∼21 °C), 4 °C, and -80 °C. The same 42 VOCs were also evaluated for their stability in methanol over 60 d while stored at -20 °C. All samples were analyzed using TD-GC-MS. During storage, most VOCs were stable on sorbent after 60 d: 36/42 (86%), 39/42 (93%), and 41/42 (98%) had not statistically changed for room temperature, 4 °C and -80 °C, respectively, based on Spearman rank correlation coefficients and linear regression analysis. The isotopically labeled VOCs tested here are well-suited to serve as internal standards for pre-analysis or storage. Degradation of VOCs in solution was apparent after 60 d: 27/42 (64%) of VOCs had statistically decreased. The total VOC mixture had dropped to 90% of its original intensity after ∼22 d and a subset of VOCs typically used as internal standards dropped to 90% in ∼16 d. Analysts using similar mixtures should make a fresh solution at least every two weeks to ensure analytical accuracy. This study provides important insights into storage practices for both sorbent tubes and standard solutions, guiding analysts toward improved reliability and accuracy in exhaled breath analysis.

A Study of Volatile Organic Compounds in Patients with Obstructive Sleep Apnea

Background: Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder characterized by intermittent upper airway obstruction, leading to significant health consequences. Traditional diagnostic methods, such as polysomnography, are time-consuming and resource-intensive. Objectives: This study explores the potential of proton-transfer-reaction mass spectrometry (PTR-MS) in identifying volatile organic compound (VOC) biomarkers for the non-invasive detection of OSA. Methods: Breath samples from 89 participants, including 49 OSA patients and 40 controls, were analyzed using PTR-MS. Significance analysis was performed between OSA patients and controls to identify potential biomarkers for OSA. To as-sess the differences in VOC concentrations between OSA patients and control subjects, the Wilcoxon rank-sum test was employed. partial least squares discriminant analysis (PLS-DA) analysis and heatmap plot was conducted to visualize the differentiation between OSA patients and control subjects based on their VOC profiles.In order to further investigate the correlation between identified biomarkers and the severity of OSA measured by Apnea-Hypopnea Index (AHI), regression analysis was conducted between biomarkers and AHI Index. Results: The results identified specific VOCs, including m045 (acetaldehyde), m095.950, and m097.071, which showed significant differences between OSA patients and controls. Advanced statistical analyses, including PLS-DA and correlation mapping, highlighted the robustness of these biomarkers, with m045 (acetaldehyde) specifically emerging as a potential biomarker associated with the AHI Index. Conclusions: This study underscores the potential of VOCs as biomarkers for identifying patients with severe AHI levels. The analysis of VOCs using PTR-MS presents a rapid, non-invasive, and cost-effective method that could be seamlessly integrated into clinical practice, allowing clinicians to better stratify patients based on their need for polysomnography and prioritize those requiring earlier testing. Future studies are necessary to validate these findings in larger cohorts and to explore the integration of PTR-MS with other diagnostic modalities for improved accuracy and clinical utility.

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.

Scalable Photonic Nose Development through Corona Phase Molecular Recognition

Breath sensors promise early disease diagnosis through noninvasive, rapid analysis, but have struggled to reach clinical use due to challenges in scalability and multivariate data extraction. The current breath sensor design necessitates various channel materials and surface functionalization methods, which delays the process. Additionally, the limited options for channel materials that provide optimum sensitivity and selectivity further restrict the array size to a maximum of only 10 to 20 channels. To address these limitations, we propose a breath sensing array design process based on Corona Phase Molecular Recognition (CoPhMoRe), which enables the creation of an expansive library of nanoparticle interfaces and broad fingerprints for multiple analytes in the breath. Although CoPhMoRe has predominantly been utilized for liquid-phase sensing, its recent application to gas-phase sensing has shown significant potential for breath sensing. We introduce the recent demonstrations in the field and present the concept of a CoPhMoRe-based photonic-nose sensor array, leveraging fluorescent nanomaterials such as near-infrared single-walled carbon nanotubes. Additionally, we identified four critical milestones for translating CoPhMoRe into breath sensors for practical clinical applications.

Evaluation of N-NOSE as a surveillance tool for recurrence in gastric and esophageal cancers: a prospective cohort study

OBJECTIVE

Early detection of recurrent gastric and esophageal cancers remains a critical challenge. Innovative and non-invasive cancer screening technologies, such as N-NOSE, can improve early detection. N-NOSE is a urine-based scent test that leverages the olfactory abilities of the nematode C. elegans. For the first time, this prospective study evaluates the efficacy of the N-NOSE chemotaxis index as a novel biomarker for postoperative surveillance and recurrence in patients with upper gastrointestinal cancers.

METHODS

A two-year prospective cohort study was conducted at The University of Tokyo Hospital, involving 40 patients with gastric and esophageal cancers. Urine samples were collected pre- and postoperatively and analysed using the N-NOSE technique.

RESULTS

In cases of recurrence with vascular invasion, the chemotaxis index at 100-fold urine dilution was significantly elevated compared to the non-recurrence group.

CONCLUSION

This study suggests the potential of N-NOSE as an effective follow-up tool for patients with upper gastrointestinal cancer, particularly those with vascular invasion. While N-NOSE has been validated to distinguish between cancer and non-cancer, and its performance compared to traditional markers has been proven, it has not been studied for recurrence. Our data highlights, for the first time, the capability of N-NOSE in the surveillance of cancer recurrence.

A comprehensive guide to volatolomics data analysis

Volatolomics (or volatilomics), the study of volatile organic compounds, has emerged as a significant branch of metabolomics due to its potential for non-invasive diagnostics and disease monitoring. However, the analysis of high-resolution data from mass spectrometry and gas sensor array-based instruments remains challenging. The careful consideration of experimental design, data collection, and processing strategies is essential to enhance the quality of results obtained from subsequent analyses. This comprehensive guide provides an in-depth exploration of volatolomics data analysis, highlighting the essential steps, such as data cleaning, pretreatment, and the application of statistical and machine learning techniques, including dimensionality reduction, clustering, classification, and variable selection. The choice of these methodologies, along with data handling practices, such as missing data imputation, outlier detection, model validation, and data integration, is crucial for identifying meaningful metabolites and drawing accurate diagnostic conclusions. By offering researchers the tools and knowledge to navigate the complexities of volatolomics data analysis, this guide emphasizes the importance of understanding the strengths and limitations of each method. Such informed decision-making enhances the reliability of findings, ultimately advancing the field and improving the understanding of metabolic processes in health and disease.

An Ultrasensitive Ethanol Gas Sensor Based on a Dual-Nanoparticle In2O3/SnO2 Composite

As a VOC, ethanol can be found in human exhaled breath, and its concentration can be used as a biomarker of human liver disease. To detect trace-level concentrations of ethanol, an ultrasensitive ethanol sensor was developed based on a dual-nanoparticle In2O3/SnO2 composite that was prepared by hydrothermal synthesis, and its suspension was dipped on a flat electrode to form a gas sensor. The nanocomposite was characterized by an SEM (scanning electron microscope), XRD (X-ray diffraction), and a TEM (transmission electron microscope), and the nanoparticle structure was observed. The experimental results showed that gas sensors based on the In2O3/SnO2 nanocomposite had higher responses compared to sensors based on pure In2O3. Among the nanocomposites, the one with a In2O3-to-SnO2 mol ratio of 1:8 was used in the sensor with the highest response of 1.41 to 100 ppb ethanol at 150 °C, which also exhibited good repeatability. The ultrasensitive response to ethanol can be attributed to the faster electron migration rate and the increase in oxygen-absorbing sites caused by the n-n heterojunction in the nanocomposite. Due to its low detection limit, good repeatability, and relatively high responses in high humidity, this sensor has a potential application in exhaled breath detection.

Microbial functional pathways based on metatranscriptomic profiling enable effective saliva-based health assessments for precision wellness

It is increasingly recognized that an important step towards improving overall health is to accurately measure biomarkers of health from the molecular activities prevalent in the oral cavity. We present a general methodology for computationally quantifying the activity of microbial functional pathways using metatranscriptomic data. We describe their implementation as a collection of eight oral pathway scores using a large salivary sample dataset (n = 9350), and we evaluate score associations with oropharyngeal disease phenotypes within an unseen independent cohort (n = 14,129). Through this validation, we show that the relevant oral pathway scores are significantly worse in individuals with periodontal disease, acid reflux, and nicotine addiction, compared with controls. Given these associations, we make the case to use these oral pathway scores to provide molecular health insights from simple, non-invasive saliva samples, and as molecular endpoints for actionable interventions to address the associated 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.

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.

Identifying viral infections through analysis of head space volatile organic compounds

Volatile organic compounds (VOCs) produced by human respiratory cells reflect metabolic and pathophysiological processes which can be detected with the use of modern technology. Analysis of exhaled breath or indoor air may potentially play an important role in screening of upper respiratory tract infections such as COVID-19 or influenza in the future. In this experimental study, air samples were collected and analyzed from the headspace of anin vitrocell culture infected by selected pathogens (influenza A H1N1 and seasonal coronaviruses OC43 and NL63). VOCs were measured with a real-time proton-transfer-reaction time-of-flight mass spectrometer and a differential mobility spectrometer. Measurements were performed every 12 h for 7 d. Non-infected cells and cell culture media served as references. In H1N1 and OC43 we observed four different VOCs which peaked during the infection. Different, individual VOCs were also observed in both infections. Activity began to clearly increase after 2 d in all analyses. We did not see increased VOC production in cells infected with NL63. VOC analysis seems to be suitable to differentiate the infected cells from those which are not infected as well as different viruses, from another. In the future, this could have practical value in both individual diagnostics and indoor environment screening.

Development and validation of the Thai Halitosis Associated Life-Quality Test (T-HALT): an evaluation of psychometric properties

BACKGROUND

Halitosis appears to have significant impacts on quality of life, necessitating reliable assessment tools. The Halitosis Associated Life-Quality Test (HALT) has been validated in various populations, but not among Thai people. While HALT provides a valuable foundation, there is a need for a culturally adapted and expanded instrument for the Thai context. Consequently, this study aimed to develop and validate a comprehensive questionnaire for assessing halitosis-related quality of life in Thai populations, incorporating a Thai version of HALT (T-HALT) as a core component.

MATERIALS AND METHODS

This cross-sectional study involved 200 dental patients at Mahidol University. The original HALT was translated into Thai using forward-backward translation. Cultural adaptation and psychometric properties of T-HALT were evaluated through multiple approaches. Content validity was ensured through expert reviews, while face validity was assessed by patient feedback. Reliability was examined via test-retest and internal consistency measures. Criterion and discriminant validity was evaluated by correlating T-HALT scores with self-perceived halitosis and volatile sulfur compound (VSC) measurements, respectively. VSCs were quantified using the OralChroma™ device, which analyzes breath samples collected directly from patients' mouths. Construct validity was assessed through exploratory (EFA) and confirmatory factor analysis (CFA), providing insights into the questionnaire's underlying structure.

RESULTS

T-HALT demonstrated excellent internal consistency (Cronbach's alphas = 0.940-0.943) and test-retest reliability (ICC = 0.886). Criterion validity was supported by a significant correlation between T-HALT scores and self-perceived halitosis (r = 0.503, P < 0.001). Discriminant validity was confirmed by the absence of a significant correlation between T-HALT scores and VSC levels (r = 0.071, P = 0.32). EFA revealed a four-factor structure, which was subsequently confirmed by CFA. However, Items 1 and 7 were excluded due to poor standardized factor loadings.

CONCLUSION

T-HALT demonstrates good reliability and validity for assessing halitosis-related quality of life in Thai populations. It performs well as a unidimensional measure, but its multidimensional application requires modifications. Future research should validate a modified version excluding Items 1 and 7 across diverse Thai populations, potentially enhancing its cultural specificity.

Volatile organic compound analysis of malignant pleural mesothelioma chorioallantoic membrane xenografts

Malignant pleural mesothelioma (MPM) is an aggressive cancer associated with asbestos exposure. MPM is often diagnosed late, at a point where limited treatment options are available, but early intervention could improve the chances of successful treatment for MPM patients. Biomarkers to detect MPM in at-risk individuals are needed to implement early diagnosis technologies. Volatile organic compounds (VOCs) have previously shown diagnostic potential as biomarkers when analysed in MPM patient breath. In this study, chorioallantoic membrane (CAM) xenografts of MPM cell lines were used as models of MPM tumour development for VOC biomarker discovery with the aim of generating targets for investigation in breath, biopsies or other complex matrices. VOC headspace analysis of biphasic or epithelioid MPM CAM xenografts was performed using solid-phase microextraction and gas chromatography-mass spectrometry. We successfully demonstrated the capture, analysis and separation of VOC signatures from CAM xenografts and controls. A panel of VOCs was identified that showed discrimination between MPM xenografts generated from biphasic and epithelioid cells and CAM controls. This is the first application of the CAM xenograft model for the discovery of VOC biomarkers associated with MPM histological subtypes. These findings support the potential utility of non-invasive VOC profiling from breath or headspace analysis of tissues for detection and monitoring of MPM.

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.

A study of 9 common breath VOCs in 504 healthy subjects using PTR-TOF-MS

INTRODUCTION

This study employs Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) to analyze exhaled breath profiles of 504 healthy adults, focusing on nine common volatile organic compounds (VOCs): acetone, acetaldehyde, acetonitrile, ethanol, isoprene, methanol, propanol, phenol, and toluene. PTR-MS offers real-time VOC measurement, crucial for understanding breath biomarkers and their applications in health assessment.

OBJECTIVES

The study aims to investigate how demographic factors-gender, age, and smoking history-affect VOC concentrations in exhaled breath. The objective is to enhance our understanding of breath biomarkers and their potential for health monitoring and clinical diagnosis.

METHODS

Exhaled breath samples were collected using PTR-MS, measuring concentrations of nine VOCs. The data were analyzed to discern distribution patterns across demographic groups.

RESULTS

Males showed higher average VOC levels for certain compounds. Propanol and methanol concentrations significantly increased with age. Smoking history influenced VOC levels, with differences among non-smokers, current smokers, and ex-smokers.

CONCLUSION

This research provides valuable insights into demographic influences on exhaled VOC profiles, emphasizing the potential of breath analysis for health assessment. PTR-MS's real-time measurement capabilities are crucial for capturing dynamic VOC changes, offering advantages over conventional methods. These findings lay a foundation for advancements in non-invasive disease detection, highlighting the importance of considering demographics in breath biomarker research.

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.

The Role of Exhaled Breath Condensate in Chronic Inflammatory and Neoplastic Diseases of the Respiratory Tract

Asthma and chronic obstructive pulmonary disease (COPD) are among the most common chronic respiratory diseases. Chronic inflammation of the airways leads to an increased production of inflammatory markers by the effector cells of the respiratory tract and lung tissue. These biomarkers allow the assessment of physiological and pathological processes and responses to therapeutic interventions. Lung cancer, which is characterized by high mortality, is one of the most frequently diagnosed cancers worldwide. Current screening methods and tissue biopsies have limitations that highlight the need for rapid diagnosis, patient differentiation, and effective management and monitoring. One promising non-invasive diagnostic method for respiratory diseases is the assessment of exhaled breath condensate (EBC). EBC contains a mixture of volatile and non-volatile biomarkers such as cytokines, leukotrienes, oxidative stress markers, and molecular biomarkers, providing significant information about inflammatory and neoplastic states in the lungs. This article summarizes the research on the application and development of EBC assessment in diagnosing and monitoring respiratory diseases, focusing on asthma, COPD, and lung cancer. The process of collecting condensate, potential issues, and selected groups of markers for detailed disease assessment in the future are discussed. Further research may contribute to the development of more precise and personalized diagnostic and treatment methods.

The Non-Invasive Detection of Pulmonary Exacerbations in Disorders of Mucociliary Clearance with Breath Analysis: A Systematic Review

Background: Disorders of mucociliary clearance, such as cystic fibrosis (CF), primary ciliary dyskinesia (PCD) and bronchiectasis of unknown origin, are characterised by periods with increased respiratory symptoms, referred to as pulmonary exacerbations. These exacerbations are hard to predict and associated with lung function decline and the loss of quality of life. To optimise treatment and preserve lung function, there is a need for non-invasive and reliable methods of detection. Breath analysis might be such a method. Methods: We systematically reviewed the existing literature on breath analysis to detect pulmonary exacerbations in mucociliary clearance disorders. Extracted data included the study design, technique of measurement, definition of an exacerbation, identified compounds and diagnostic accuracy. Results: Out of 244 identified articles, 18 were included in the review. All studies included patients with CF and two also with PCD. Age and the definition of exacerbation differed between the studies. There were five that measured volatile organic compounds (VOCs) in exhaled breath using gas chromatography with mass spectrometry, two using an electronic nose and eleven measured organic compounds in exhaled breath condensate. Most studies showed a significant correlation between pulmonary exacerbations and one or multiple compounds, mainly hydrocarbons and cytokines, but the validation of these results in other studies was lacking. Conclusions: The detection of pulmonary exacerbations by the analysis of compounds in exhaled breath seems possible but is not near clinical application due to major differences in results, study design and the definition of an exacerbation. There is a need for larger studies, with a longitudinal design, international accepted definition of an exacerbation and validation of the results in independent cohorts.

Impact of breath sample collection method and length of storage of breath samples in Tedlar bags on the level of selected volatiles assessed using gas chromatography-ion mobility spectrometry (GC-IMS)

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec®device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results.

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.

Differences in Volatile Organic Compounds Between Concussed and Non-concussed Division I Athletes

Introduction Diagnosing a concussion is challenging because of complex and variable symptoms. Establishing a viable biomarker of injury may rely on physiologic measurements rather than symptomology. Volatile organic compounds (VOCs) such as breath acetone have been identified as potential physiological markers that can capture changes in the utilization of energy substrates post-concussion. Here, we aimed to explore whether differences in VOCs exist between concussed and non-concussed athletes at the initial and later stages of injury recovery. Methods Six (N=6) non-concussed athletes were enrolled as control participants prior to the competitive season. Control participants' breath acetone, heart rate, and anthropometric measures were obtained at rest and throughout a single exercise challenge by breathalyzer. Six (N=6) athletes diagnosed with concussion during the competitive season had breath acetone measured daily until cleared to return to activity or approximately four weeks following enrollment where they participated in an exit exercise challenge having breath acetone, heart rate, and anthropometric measures obtained. Comparisons were made between at-rest measures of concussed and non-concussed participants at multiple time points during the recovery period. Paired t-test comparisons with individuals serving as their own control were used to determine individual differences in recovery. Visual graphs were used to demonstrate differences in obtained measures amongst individuals and between groups during the exercise challenges. Results Results demonstrated statistically significant differences in breath acetone between concussed and control participants when the highest day measured during the first week of concussion was compared to the control participant's resting values (P=0.017). Additionally, when the concussed participants served as their own control and their highest measured day of the first week post-concussion was compared to values when cleared to return to activity or at 26 days post-concussion, there was a significant difference in breath acetone (P=0.028). Comparing breath acetone during exercise between non-concussed and cleared concussed participants or four weeks post-injury, demonstrated no significant differences throughout the challenge or at rest prior. Visual graph comparisons in a single participant before and after concussion suggest differences may appear following exercise during the recovery period. Discussion These results suggest VOCs, particularly breath acetone, have the potential to serve as diagnostic markers of concussion. However, longitudinal research within larger cohorts and with equipment able to expel VOCs other than acetone from measures are needed to make informed recommendations.

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.

Towards detection of cancer biomarkers in human exhaled air by transfer-learning-powered analysis of odor-evoked calcium activity in rat olfactory bulb

Detection of volatile organic compounds in exhaled air is a promising approach to non-invasive and scalable gastric cancer screening. This work proposes a new approach for the detection of volatile organic compounds by analyzing odor-evoked calcium responses in the rat olfactory bulb. We estimate the feasibility of gastric cancer biomarker detection added to the exhaled air of healthy participants. Our detector consists of a convolutional encoder and a similarity-based classifier over encoder outputs. To minimize overfitting on a small available training set, we involve a pre-training where the encoder is trained on synthetic data representing spatiotemporal patterns similar to real calcium responses in the olfactory bulb. We estimate the classification accuracy of exhaled air samples by matching their encodings with encodings of calibration samples of two classes: 1) exhaled air and 2) a mixture of exhaled air with the cancer biomarker. On our data, the accuracy increased from 0.68 on real data up to 0.74 if pre-training on synthetic data is involved. Our work is focused on proving the feasibility of proposed new approach rather than on comparing its efficiency with existing methods. Such detection is often performed with an electronic nose, but its output becomes unstable over time due to a sensor drift. In contrast to the electronic nose, rats can robustly detect low concentrations of biomarkers over lifetime. The feasibility of gastric cancer biomarker detection in exhaled air by bio-hybrid system is shown. Pre-training of neural models for images analysis increases the accuracy of detection.

Application of p and n-Type Silicon Nanowires as Human Respiratory Sensing Device

Accurate and fast breath monitoring is of great importance for various healthcare applications, for example, medical diagnoses, studying sleep apnea, and early detection of physiological disorders. Devices meant for such applications tend to be uncomfortable for the subject (patient) and pricey. Therefore, there is a need for a cost-effective, lightweight, small-dimensional, and non-invasive device whose presence does not interfere with the observed signals. This paper reports on the fabrication of a highly sensitive human respiratory sensor based on silicon nanowires (SiNWs) fabricated by a top-down method of metal-assisted chemical-etching (MACE). Besides other important factors, reducing the final cost of the sensor is of paramount importance. One of the factors that increases the final price of the sensors is using gold (Au) electrodes. Herein, we investigate the sensor's response using aluminum (Al) electrodes as a cost-effective alternative, considering the fact that the electrode's work function is crucial in electronic device design, impacting device electronic properties and electron transport efficiency at the electrode-semiconductor interface. Therefore a comparison is made between SiNWs breath sensors made from both p-type and n-type silicon to investigate the effect of the dopant and electrode type on the SiNWs respiratory sensing functionality. A distinct directional variation was observed in the sample's response with Au and Al electrodes. Finally, performing a qualitative study revealed that the electrical resistance across the SiNWs renders greater sensitivity to breath than to dry air pressure. No definitive research demonstrating the mechanism behind these effects exists, thus prompting our study to investigate the underlying process.

The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study

OBJECTIVE

Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present.

METHODS

Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k-Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference.

RESULTS

A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k-nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%.

CONCLUSIONS

The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air.

Comparative Evaluation of Volatile Organic Compounds in Two Bottle Gourd Accessions with Distinct Fruit Shapes

Bottle gourd (Lagenaria siceraria L.) belongs to the cucurbit family and has a long history of cultivation in tropical and subtropical regions worldwide, both for food and medicine. Popularized by its unique fruit shapes, gourds are used to make ornaments and musical instruments. However, there is limited information on volatile organic compounds (VOCs) in the bottle gourd fruit. In the present study, we conducted a comparative analysis of VOCs profiled in two accessions (USVL5 and USVL10) with distinct fruit shapes: bottle and cylinder. While USVL5 only produced long cylinder fruits, USVL10 produced two fruit types, cylinder (USVL10CYN) and bottle (USVL10A and USVL10B). VOCs in each line were analyzed using headspace solid-phase microextraction-gas chromatography/mass spectrometry (HS-SPME-GC/MS). Aliphatic aldehydes and alcohols were the most abundant compounds found in these bottle gourd accessions. Based on the functional profile of the identified VOCs, our results reveal the suitability of our tested line (USVL10), enriched in functionally important VOCs such as hexanal (abundance = 381.07), nonanal (abundance = 9.85), 2-methoxy-2-methylpropane (abundance = 21.26) and D-limonene (abundance = 31.48). The VOCs profiling and functional analyses support the notion that the bottle gourd accession USVL10 can be a good candidate for its use in agriculture, the health care industry and domestic uses.

The investigation of volatile organic compounds in diagnosing (early) esophageal squamous cell carcinoma and gastric adenocarcinoma

PURPOSE

The diagnosis of upper gastrointestinal cancer (UGIC) and early UGIC is currently based on endoscopy and histopathology. In this study, we aimed to explore whether intraluminal and exhaled volatile organic compounds (VOCs) could be used to diagnose (early) esophageal squamous cell carcinoma (ESCC) and gastric adenocarcinoma (GC).

METHODS

We prospectively recruited 259 patients and first collected intraluminal gas simples directly from upper GI tract via our designed device after passing endoscopic biopsy channel and collected exhaled gas samples in pairs.

RESULTS

509 gas samples were totally collected and VOCs composed by peak compounds detected by gas chromatography-mass spectrometry (GC-MS) were used to train and test Multilayer Perceptron Network (MPN) for discrimination. Intraluminal and exhaled gas had more than 0.95 area under the curve (AUC) to discriminate UGIC (ESCC and GC) and early UGIC from benign control with different VOCs compositions.

CONCLUSION

Both intraluminal and exhaled VOCs had cancer-specific compositions to accurately discriminate early UGIC and UGIC, and the ability of intraluminal VOCs was better than that of exhaled VOCs. These suggested the potential role of VOCs in diagnosing and screening early UGIC and UGIC in the future.

Dynamic Breath Limonene Sensing at High Selectivity

Liver diseases (e.g., cirrhosis, cancer) cause more than two million deaths per year worldwide. This is partly attributed to late diagnosis and insufficient screening techniques. A promising biomarker for noninvasive and inexpensive liver disease screening is breath limonene that can indicate a deficiency of the cytochrome P450 liver enzymes. Here, we introduce a compact and low-cost detector for dynamic and selective breath limonene sensing. It comprises a chemoresistive sensor based on Si/WO₃ nanoparticles pre-screened by a packed bed Tenax separation column at room temperature. We demonstrate selective limonene detection down to 20 parts per billion over up to three orders of magnitude higher concentrated acetone, ethanol, hydrogen, methanol, and 2-propanol in gas mixtures, as well as robustness to 10-90% relative humidity. Most importantly, this detector recognizes the individual breath limonene dynamics of four healthy volunteers following the ingestion (swallowing or chewing) of a limonene capsule. Limonene release and subsequent metabolization are monitored from breath measurements in real time and in excellent agreement (R² = 0.98) with high-resolution proton transfer reaction mass spectrometry. This study demonstrates the potential of the detector as a simple-to-use and noninvasive device for the routine monitoring of limonene levels in exhaled breath to facilitate early diagnosis of liver dysfunction.

A SIFT-MS study of positive and negative ion chemistry of the ortho-, meta- and para-isomers of cymene, cresol, and ethylphenol

Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) is a soft ionisation technique based on gas phase ion-molecule reaction kinetics for the quantification of trace amounts of volatile organic compound vapours. One of its previous limitations is difficulty in resolving isomers, although this can now be overcome using different reactivities of several available reagent cations and anions (H₃O⁺, NO⁺, O₂⁺˙, O^-˙, OH^-, O₂^-˙, NO₂^-, NO₃^-). Thus, the ion-molecule reactions of these eight ions with all isomers of the aromatic compounds cymene, cresol and ethylphenol were studied to explore the possibility of their immediate identification and quantification without chromatographic separation. Rate coefficients and product ion branching ratios determined experimentally for the 72 reactions are reported. DFT calculations of their energetics confirmed the feasibility of the suggested reaction pathways. All positive ion reactions proceeded fast but largely did not discriminate between the isomers. The reactivity of the anions was much more varied. In all cases, OH^- reacts by proton transfer forming (M-H); NO₂^- and NO₃^- were unreactive. The differences observed for product ion branching ratios can be used to identify isomers approximately.

Raman Spectroscopy for Urea Breath Test

The urea breath test is a non-invasive diagnostic method for Helicobacter pylori infections, which relies on the change in the proportion of 13CO2 in exhaled air. Nondispersive infrared sensors are commonly used for the urea breath test in laboratory equipment, but Raman spectroscopy demonstrated potential for more accurate measurements. The accuracy of the Helicobacter pylori detection via the urea breath test using 13CO2 as a biomarker is affected by measurement errors, including equipment error and δ13C measurement uncertainty. We present a Raman scattering-based gas analyzer capable of δ13C measurements in exhaled air. The technical details of the various measurement conditions have been discussed. Standard gas samples were measured. 12CO2 and 13CO2 calibration coefficients were determined. The Raman spectrum of the exhaled air was measured and the δ13C change (in the process of the urea breath test) was calculated. The total error measured was 6% and does not exceed the limit of 10% that was analytically calculated.

GC/MS analysis of hypoxic volatile metabolic markers in the MDA-MB-231 breast cancer cell line

Hypoxia in disease describes persistent low oxygen conditions, observed in a range of pathologies, including cancer. In the discovery of biomarkers in biological models, pathophysiological traits present a source of translatable metabolic products for the diagnosis of disease in humans. Part of the metabolome is represented by its volatile, gaseous fraction; the volatilome. Human volatile profiles, such as those found in breath, are able to diagnose disease, however accurate volatile biomarker discovery is required to target reliable biomarkers to develop new diagnostic tools. Using custom chambers to control oxygen levels and facilitate headspace sampling, the MDA-MB-231 breast cancer cell line was exposed to hypoxia (1% oxygen) for 24 h. The maintenance of hypoxic conditions in the system was successfully validated over this time period. Targeted and untargeted gas chromatography mass spectrometry approaches revealed four significantly altered volatile organic compounds when compared to control cells. Three compounds were actively consumed by cells: methyl chloride, acetone and n-Hexane. Cells under hypoxia also produced significant amounts of styrene. This work presents a novel methodology for identification of volatile metabolisms under controlled gas conditions with novel observations of volatile metabolisms by breast cancer cells.

Markers of Chemical and Microbiological Contamination of the Air in the Sport Centers

This study aimed to assess the markers of chemical and microbiological contamination of the air at sport centers (e.g., the fitness center in Poland) including the determination of particulate matter, CO₂, formaldehyde (DustTrak™ DRX Aerosol Monitor; Multi-functional Air Quality Detector), volatile organic compound (VOC) concentration (headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry), the number of microorganisms in the air (culture methods), and microbial biodiversity (high-throughput sequencing on the Illumina platform). Additionally the number of microorganisms and the presence of SARS-CoV-2 (PCR) on the surfaces was determined. Total particle concentration varied between 0.0445 mg m^-3 and 0.0841 mg m^-3 with the dominance (99.65-99.99%) of the PM_2.5 fraction. The CO₂ concentration ranged from 800 ppm to 2198 ppm, while the formaldehyde concentration was from 0.005 mg/m³ to 0.049 mg m^-3. A total of 84 VOCs were identified in the air collected from the gym. Phenol, D-limonene, toluene, and 2-ethyl-1-hexanol dominated in the air at the tested facilities. The average daily number of bacteria was 7.17 × 10² CFU m^-3-1.68 × 10³ CFU m^-3, while the number of fungi was 3.03 × 10³ CFU m^-3-7.34 × 10³ CFU m^-3. In total, 422 genera of bacteria and 408 genera of fungi representing 21 and 11 phyla, respectively, were detected in the gym. The most abundant bacteria and fungi (>1%) that belonged to the second and third groups of health hazards were: Escherichia-Shigella, Corynebacterium, Bacillus, Staphylococcus, Cladosporium, Aspergillus, and Penicillium. In addition, other species that may be allergenic (Epicoccum) or infectious (Acinetobacter, Sphingomonas, Sporobolomyces) were present in the air. Moreover, the SARS-CoV-2 virus was detected on surfaces in the gym. The monitoring proposal for the assessment of the air quality at a sport center includes the following markers: total particle concentration with the PM_2.5 fraction, CO₂ concentration, VOCs (phenol, toluene, and 2-ethyl-1-hexanol), and the number of bacteria and fungi.

Gas chromatography-mass spectrometry pilot study to identify volatile organic compound biomarkers of childhood obesity with dyslipidemia in exhaled breath

Objectives

Childhood obesity affects multiple organs in the body and is associated with both significant morbidity and ultimately premature mortality. Childhood obesity, especially dyslipidemia, can lead to early atherosclerosis and premature cardiovascular disease (CVD) in adulthood. The detection of exhaled volatile organic compounds (VOCs) in the breath offers the opportunity for the discovery of novel disease-specific biomarkers. This study aimed to identify VOCs that correlate with childhood obesity accompanied by dyslipidemia.

Methods

A total of 82 overweight or obese children between the ages of 8 and 12 years were recruited from the exercise on obesity adolescents in Peking (EXCITING) study (NCT04984005). The breath VOCs of the participants were measured by gas chromatography-mass spectrometry (GC-MS). The classification was performed using principal component analysis (PCA) of the relative abundance of VOCs. The difference between the obese and overweight groups with or without dyslipidemia was analyzed.

Results

Among the 82 children, 25 were overweight, of whom 10 had dyslipidemia. The other 57 children were obese, and 17 of them had dyslipidemia. Obese children with dyslipidemia had higher triglycerides and elevated non–high-density lipoprotein-cholesterol compared to overweight children without dyslipidemia. We confirmed 13 compounds based on database well matches (average score > 80) for mass spectra and refractive index. These 13 VOCs were grouped into three chemical functional groups: saturated hydrocarbons, aromatic hydrocarbons and unsaturated aldehydes. For obese children with dyslipidemia, the PCA scatter plot of the three chemical groups was obviously separated from the other groups. Some of the candidates, including heptadecane, naphthalene, and cis-6-nonnenol, were significantly higher in obese children with dyslipidemia than in overweight groups with or without dyslipidemia.

Conclusion

A suite of VOCs from three chemical function groups, saturated hydrocarbons, aromatic hydrocarbons, and unsaturated aldehydes, were separated in the obese children with dyslipidemia. Heptadecane, naphthalene, and cis-6-nonenol were significantly elevated in obese children with dyslipidemia. Our findings underscore the potential value of the candidate VOCs for future risk categorization.

An efficient transition metal chalcogenide sensor for monitoring respiratory alkalosis

For many biomedical applications, high-precision CO₂ detection with a rapid response is essential. Due to the superior surface-active characteristics, 2D materials are particularly crucial for electrochemical sensors. The liquid phase exfoliation method of 2D Co₂Te₃ production is used to achieve the electrochemical sensing of CO₂. The Co₂Te₃ electrode performs better than other CO₂ detectors in terms of linearity, low detection limit, and high sensitivity. The outstanding physical characteristics of the electrocatalyst, including its large specific surface area, quick electron transport, and presence of a surface charge, can be credited for its extraordinary electrocatalytic activity. More importantly, the suggested electrochemical sensor has great repeatability, strong stability, and outstanding selectivity. Additionally, the electrochemical sensor based on Co₂Te₃ could be used to monitor respiratory alkalosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03497-z.

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study

Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.

Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm

OBJECTIVE(S)

To investigate the predictive performances of exhaled breath volatile organic compounds (VOCs) for development of bronchopulmonary dysplasia (BPD) in infants born preterm.

METHODS

Exhaled breath was collected from infants born <30 weeks' gestation at days 3 and 7 of life. Ion-fragments detected by gas-Chromatography-mass-spectrometry analysis were used to derive and internally validate a VOC prediction model for moderate or severe BPD at 36 weeks postmenstrual age. We tested the predictive performance of the National Institute of Child Health and Human Development (NICHD) clinical BPD prediction model with and without VOCs.

RESULTS

Breath samples were collected from 117 infants (mean gestation 26.8 [±1.5] weeks). Thirty-three percent of the infants developed moderate or severe BPD. The VOC model showed a c-statistic of 0.89 (95% confidence interval [CI] 0.80-0.97) and 0.92 (95% CI 0.84-0.99)) for the prediction of BPD at days 3 and 7, respectively. Adding the VOCs to the clinical prediction model in non-invasive supported infants resulted in significant improvement in discriminative power on both days (day 3: c-statistic 0.83 versus 0.92, p-value 0.04; day 7: c-statistic 0.82 versus 0.94, p-value 0.03).

CONCLUSIONS

This study showed that VOC profiles in exhaled breath of preterm infants on non-invasive support in the first week of life differ between those developing and not developing BPD. Adding VOCs to a clinical prediction model significantly improved its discriminative performance.

Breath VOC analysis and machine learning approaches for disease screening: a review

Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.

Real-time measurements of product compounds formed through the reaction of ozone with breath exhaled VOCs

Human presence can affect indoor air quality because of secondary organic compounds formed upon reactions between gaseous oxidant species, e.g., ozone (O₃), hydroxyl radicals (OH), and chemical compounds from skin, exhaled breath, hair and clothes. We assess the gas-phase product compounds generated by reactions of gaseous O₃ with volatile organic compounds (VOCs) from exhaled human breath by real time analysis using a high-resolution quadrupole-orbitrap mass spectrometer (HRMS) coupled to a secondary electrospray ionization (SESI) source. Based on the product compounds identified we propose a reaction mechanism initiated by O₃ oxidation of the most common breath constituents, isoprene, α-terpinene and ammonia (NH₃). The reaction of O₃ with isoprene and α-terpinene generates ketones and aldehydes such as 3,4-dihydroxy-2-butanone, methyl vinyl ketone, 3-carbonyl butyraldehyde, formaldehyde and toxic compounds such as 3-methyl furan. Formation of compounds with reduced nitrogen containing functional groups such as amines, imines and imides is highly plausible through NH₃ initiated cleavage of the C-O bond. The detected gas-phase product compounds suggest that human breath can additionally affect indoor air quality through the formation of harmful secondary products and future epidemiological studies should evaluate the potential health effects of these compounds.

Reversible colorimetric sensing of volatile analytes by wicking in close proximity to a photonic film

Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array. This allows precise planar alignment and microscale separation (310 μm) of the optical and fluidic structures. This configuration offers rapid and homogeneous color changes over large areas that permits detection by low-resolution optics or eye, which is well-suited to portable/wearable devices. For our proof-of-principle demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated the sensor's response (color change) to ethanol vapor. We show that the RGB color value is quantitatively linked to the spacer swelling, which is reversible and repeatable. The optofluidic platform reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response was examined, confirming the potential of the reported sensing platform for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples, such as biofluids.

The Effect of Human Occupancy on Indoor Air Quality through Real-Time Measurements of Key Pollutants

The primarily emitted compounds by human presence, e.g., skin and volatile organic compounds (VOCs) in breath, can react with typical indoor air oxidants, ozone (O₃), and hydroxyl radicals (OH), leading to secondary organic compounds. Nevertheless, our understanding about the formation processes of the compounds through reactions of indoor air oxidants with primary emitted pollutants is still incomplete. In this study we performed real-time measurements of nitrous acid (HONO), nitrogen oxides (NO_x = NO + NO₂), O₃, and VOCs to investigate the contribution of human presence and human activity, e.g., mopping the floor, to secondary organic compounds. During human occupancy a significant increase was observed of 1-butene, isoprene, and d-limonene exhaled by the four adults in the room and an increase of methyl vinyl ketone/methacrolein, methylglyoxal, and 3-methylfuran, formed as secondary compounds through reactions of OH radicals with isoprene. Intriguingly, the level of some compounds (e.g., m/z 126, 6-methyl-5-hepten-2-one, m/z 152, dihydrocarvone, and m/z 194, geranyl acetone) formed through reactions of O₃ with the primary compounds was higher in the presence of four adults than during the period of mopping the floor with commercial detergent. These results indicate that human presence can additionally degrade the indoor air quality.

C. elegans as a Powerful Tool for Cancer Screening

Regular cancer screening is critical for early cancer detection. Cancer screening tends to be burdensome, invasive, and expensive, especially for a comprehensive multi-organ check. Improving the rate and effectiveness of routine cancer screenings remain a challenge in health care. Multi-cancer early detection (MCED) is an exciting concept and a potentially effective solution for addressing current issues with routine cancer screening. In recent years, several technologies have matured for MCED, such as identifying cell-free tumor DNA in blood or using organisms such as Caenorhabditis elegans as a tool for early cancer detection. In Japan, N-NOSE is a commercially available multi-cancer detection test based on the chemotaxis of C. elegans using a urine sample showing 87.5% sensitivity and 90.2% specificity. In this review, we focus on using C. elegans as a powerful biosensor for universal cancer screening. We review N-NOSE clinical research results, spotlighting it as an effective primary cancer screening test.

Sampling and Analysis of Low-Molecular-Weight Volatile Metabolites in Cellular Headspace and Mouse Breath

Volatile compounds, abundant in breath, can be used to accurately diagnose and monitor a range of medical conditions. This offers a noninvasive, low-cost approach with screening applications; however, the uptake of this diagnostic approach has been limited by conflicting published outcomes. Most published reports rely on large scale screening of the public, at single time points and without reference to ambient air. Here, we present a novel approach to volatile sampling from cellular headspace and mouse breath that incorporates multi-time-point analysis and ambient air subtraction revealing compound flux as an effective proxy of active metabolism. This approach to investigating breath volatiles offers a new avenue for disease biomarker discovery and diagnosis. Using gas chromatography mass spectrometry (GC/MS), we focus on low molecular weight, metabolic substrate/by-product compounds and demonstrate that this noninvasive technique is sensitive (reproducible at ~1 µg cellular protein, or ~500,000 cells) and capable of precisely determining cell type, status and treatment. Isolated cellular models represent components of larger mammalian systems, and we show that stress- and pathology-indicative compounds are detectable in mice, supporting further investigation using this methodology as a tool to identify volatile targets in human patients.