A review of the volatiles from the healthy human body

Recapitulating COVID-19 detection methods: RT-PCR, sniffer dogs and electronic nose

In December 2019, a number of subjects presenting with an unexplained pneumonia-like illness were suspected to have a link to a seafood market in Wuhan, China. Subsequently, this illness was identified as the 2019-novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the World Committee on Virus Classification. Since its initial identification, the virus has rapidly sperad across the globe, posing an extraordinary challenge for the medical community. Currently, the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) is considered the most reliable method for diagnosing SARS-CoV-2. This procedure involves collecting oro-pharyngeal or nasopharyngeal swabs from individuals. Nevertheless, for the early detection of low viral loads, a more sensitive technique, such as droplet digital PCR (ddPCR), has been suggested. Despite the high effectiveness of RT-PCR, there is increasing interest in utilizing highly trained dogs and electronic noses (eNoses) as alternative methods for screening asymptomatic individuals for SARS-CoV-2. These dogs and eNoses have demonstrated high sensitivity and can detect volatile organic compounds (VOCs), enabling them to distinguish between COVID-19 positive and negative individuals. This manuscript recapitulates the potential, advantages, and limitations of employing trained dogs and eNoses for the screening and control of SARS-CoV-2.

Pristine and aurum-decorated tungsten ditellurides as sensing materials for VOCs detection in exhaled human breath: DFT analysis

In this research, we employed density functional theory (DFT) to evaluate the sensing capabilities of transition metal-decorated two-dimensional WTe2 TMDs nanosheets toward VOCs such as (acetone, ethanol, methanol, toluene, and formaldehyde) that are exhaled in human breath and can serve as potential biomarkers for detecting specific physiological disorders and also gases interfering in exhaled breath (CO2 and H2O) detection. Au can be physically decorated onto the surface of WTe2. We analyzed the density of states (DOS), adsorption energy, charge transfer, and sensing behavior. The pristine WTe2 monolayer, exhibiting a semiconductor characteristic with a band gap of 0.63 eV, transitions to a metallic state upon Au-decoration, due to its actively stable nature and promising negative adsorption energy value, it triggers the emergence of novel states within the DOS. Computed adsorption energies of VOCs range from -0.08 to -0.57 eV, with greater interaction distances confirming the physisorption behavior of these VOCs biomarkers on Au-WTe2. Ethanol displays greater sensitivity compared to other considered VOCs. Au-WTe2 exhibits promising potential as a viable option for detecting VOCs in breath analysis applications at room temperature, owing to its excellent adsorption capabilities and sensitivity. Overall, our results highlight aurum-decorated tungsten ditelluride's potential as an efficient nano-sensor for detecting VOCs associated with early-stage lung cancer diagnoses.

A feasibility study of sample re-collection in the analysis of selected volatile compounds in breath samples using GC×GC-TOFMS

In this study, we aimed to assess the feasibility of re-collecting breath samples using the Centri® (Markes International, Bridgend, UK) followed by two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) analysis. The work was conducted in two main phases. In the first phase, we evaluated the re-collection performance by analyzing two sets of standards, including a Grob mix primary solution and a standard mixture of 20 selected volatile compounds (VCs) covering different classes of organic species commonly found in breath samples. The intra-day and inter-day precision (reported as relative standard deviation (RSD),%) for the re-collection of the Grob mix primary solution were in the range of 1 % to14 % and 3 % to12 %, respectively. The re-collection accuracy ranged from 78 % to 97 %. The intra-day RSD for the re-collection of the standard mixture of selected VCs was within 20 % for all compounds, except for acetone and nonane. The precision was within 25 % for all compounds, except for nonane, n-hexane, 1,4-dichlorobenzene, and decane, which exhibited less than 36 % RSD. The re-collection accuracy was in the range of 67 % to 129 %. In the second phase of the study, the re-collection performance in breath analysis was evaluated via five repetitive splitting and re-collection of six breath samples obtained from healthy adults, realizing a total of 30 breath analyses. Initially, we evaluated the re-collection performance by considering all features obtained from breath analysis and then focused on the 20 VCs commonly found in breath samples. The re-collection accuracy for total breath features ranged from 86 to 103 %, and the RSDs were in the range of 1.0 % to 10.4 %. For the selected VCs, the re-collection accuracy of all compounds, except for undecane and benzene, was in the range of 71 % to 132 %.

The breath volatilome is shaped by the gut microbiota

The gut microbiota is widely implicated in host health and disease, inspiring translational efforts to implement our growing body of knowledge in clinical settings. However, the need to characterize gut microbiota by its genomic content limits the feasibility of rapid, point-of-care diagnostics. The microbiota produces a diverse array of xenobiotic metabolites that disseminate into tissues, including volatile organic compounds (VOCs) that may be excreted in breath. We hypothesize that breath contains gut microbe-derived VOCs that inform the composition and metabolic state of the microbiota. To explore this idea, we compared the breath volatilome and fecal gut microbiomes of 27 healthy children and found that breath VOC composition is correlated with gut microbiomes. To experimentally interrogate this finding, we devised a method for capturing exhaled breath from gnotobiotic mice. Breath volatiles are then profiled by gas-chromatography mass-spectrometry (GC-MS). Using this novel methodology, we found that the murine breath profile is markedly shaped by the composition of the gut microbiota. We also find that VOCs produced by gut microbes in pure culture can be identified in vivo in the breath of mice monocolonized with the same bacteria. Altogether, our studies identify microbe-derived VOCs excreted in breath and support a mechanism by which gut bacterial metabolism directly contributes to the mammalian breath VOC profiles.

An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO2-triggered breath sampling system, which collected alveolar breath over several minutes in sterile and inert containers. A real-time mass spectrometer is coupled to serve as a reference device for calibration measurements and subsequent breath analysis. The new sensor system provided a 3σ detection limit of 8.3 ppbV and an NNEA of 1.4E-9 Wcm-1Hz-0.5. In terms of the performed breath analysis measurements, 12 out of 13 fell within the error margin of the photoacoustic measurement system, demonstrating the reliability of the measurements in the field.

A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

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.

Image Sensing of Gaseous Acetone Using Secondary Alcohol Dehydrogenase-Immobilized Mesh for Exhaled Air

Human-borne acetone is a potent marker of lipid metabolism. Here, an enzyme immobilization method for secondary alcohol dehydrogenase (S-ADH), which is suitable for highly sensitive and selective biosensing of acetone, was developed, and then its applicability was demonstrated for spatiotemporal imaging of concentration distribution. After various investigations, S-ADH-immobilized meshes could be prepared with less than 5% variation by cross-linking S-ADH with glutaraldehyde on a cotton mesh at 40 °C for 15 min. Furthermore, high activity was obtained by adjusting the concentration of the coenzyme nicotinamide adenine dinucleotide (NADH) solution added to the S-ADH-immobilized mesh to 500 μM and the solvent to a potassium phosphate buffer solution at pH 6.5. The gas imaging system using the S-ADH-immobilized mesh was able to image the decrease in NADH fluorescence (ex 340 nm, fl 490 nm) caused by the catalytic reaction of S-ADH and the acetone distribution in the concentration range of 0.1-10 ppm-v, including the breath concentration of healthy people at rest. The exhaled breath of two healthy subjects at 6 h of fasting was quantified as 377 and 673 ppb-v, which were consistent with the values quantified by gas chromatography-mass spectrometry.

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.

Volatile Organic Compounds on Rhodes Island, Greece: Implications for Outdoor and Indoor Human Exposure

Volatile organic compounds (VOC) are considered a class of pollutants with a significant presence in indoor and outdoor air and serious health effects. The aim of this study was to measure and evaluate the levels of outdoor and indoor VOCs at selected sites on Rhodes Island, Greece, during the cold and warm periods of 2023. Spatial and seasonal variations were evaluated; moreover, cancer and non-cancer inhalation risks were assessed. For this purpose, simultaneous indoor-outdoor air sampling was carried out on the island of Rhodes. VOCs were determined by Thermal Desorption-Gas Chromatography/Mass Spectroscopy (TD-GC/MS). Fifty-six VOCs with frequencies ≥ 50% were further considered. VOC concentrations (∑56VOCs) at all sites were found to be higher in the warm period. In the warm and cold sampling periods, the highest concentrations were found at the port of Rhodes City, while total VOC concentrations were dominated by alkanes. The Positive Matrix Factorization (PMF) model was applied to identify the VOC emission sources. Non-cancer and cancer risks for adults were within the safe levels.

A review of phyto- and microbial-remediation of indoor volatile organic compounds

Volatile organic compounds (VOCs) are crucial air pollutants in indoor environments, emitted from building materials, furniture, consumer products, cleaning products, smoking, fuel combustion, cooking, and other sources. VOCs are also emitted from human beings via breath and whole-body skin. Some VOCs cause dermal/ocular irritation as well as gastrointestinal, neurological, cardiovascular, and/or carcinogenic damage to human health. Because people spend most of their time indoors, active control of indoor VOCs has garnered attention. Phytoremediation and microbial remediation, based on plant and microorganism activities, are deemed sustainable, cost-effective, and public-friendly technologies for mitigating indoor VOCs. This study presents the major sources of VOCs in indoor environments and their compositions. Various herbaceous and woody plants used to mitigate indoor VOCs are summarized and their VOCs removal performance is compared. Moreover, this paper reviews the current state of active phytoremediation and microbial remediation for the control of indoor VOCs, and discusses future directions.

Electronic nose based analysis of exhaled volatile organic compounds spectrum reveals asthmatic shifts and consistency in controls post-exercise and spirometry

Analyzing exhaled volatile organic compounds (VOCs) with an electronic nose (e-nose) is emerging in medical diagnostics as a non-invasive, quick, and sensitive method for disease detection and monitoring. This study investigates if activities like spirometry or physical exercise affect exhaled VOCs measurements in asthmatics and healthy individuals, a crucial step for e-nose technology's validation for clinical use. The study analyzed exhaled VOCs using an e-nose in 27 healthy individuals and 27 patients with stable asthma, before and after performing spirometry and climbing five flights of stairs. Breath samples were collected using a validated technique and analyzed with a Cyranose 320 e-nose. In healthy controls, the exhaled VOCs spectrum remained unchanged after both lung function test and exercise. In asthmatics, principal component analysis and subsequent discriminant analysis revealed significant differences post-spirometry (vs. baseline 66.7% cross validated accuracy [CVA],p< 0.05) and exercise (vs. baseline 70.4% CVA,p< 0.05). E-nose measurements in healthy individuals are consistent, unaffected by spirometry or physical exercise. However, in asthma patients, significant changes in exhaled VOCs were detected post-activities, indicating airway responses likely due to constriction or inflammation, underscoring the e-nose's potential for respiratory condition diagnosis and monitoring.

A multi-omics method for breast cancer diagnosis based on metabolites in exhaled breath, ultrasound imaging, and basic clinical information

Background and aims

Through a nested cohort study, we evaluated the diagnostic performance of breath-omics in differentiating between benign and malignant breast lesions, and assessed the diagnostic performance of a multi-omics approach that combines breath-omics, ultrasound radiomics, and clinic-omics in distinguishing between benign and malignant breast lesions.

Materials and methods

We recruited 1,723 consecutive patients who underwent an automated breast volume scanner (ABVS) examination. Breath samples were collected and analyzed by high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOF-MS) to obtain breath-omics features. 238 of 1,723 enrolled participants have received pathological confirmation of breast nodules finally. The breast lesions of the 238 participants were contoured manually based on ABVS images for ultrasound radiomics feature calculation. Then, single- and multi-omics models were constructed and evaluated for breast nodules diagnosis via five-fold cross-validation.

Results

The area under the curve (AUC) of the breath-omics model was 0.855. In comparison, the multi-omics model demonstrated superior diagnostic performance for breast cancer, with sensitivity, specificity, and AUC of 84.1 %, 89.9 %, and 0.946, respectively. The multi-omics performance was comparable to that of the Breast Imaging Reporting and Data System (BI-RADS) classification via senior ultrasound physician evaluation.

Conclusion

The multi-omics approach combining metabolites in exhaled breath, ultrasound imaging, and basic clinical information exhibits superior diagnostic performance and promises to be a non-invasive and reliable tool for breast cancer diagnosis.

The Impact of Artificial Intelligence on Microbial Diagnosis

Traditional microbial diagnostic methods face many obstacles such as sample handling, culture difficulties, misidentification, and delays in determining susceptibility. The advent of artificial intelligence (AI) has markedly transformed microbial diagnostics with rapid and precise analyses. Nonetheless, ethical considerations accompany AI adoption, necessitating measures to uphold patient privacy, mitigate biases, and ensure data integrity. This review examines conventional diagnostic hurdles, stressing the significance of standardized procedures in sample processing. It underscores AI's significant impact, particularly through machine learning (ML), in microbial diagnostics. Recent progressions in AI, particularly ML methodologies, are explored, showcasing their influence on microbial categorization, comprehension of microorganism interactions, and augmentation of microscopy capabilities. This review furnishes a comprehensive evaluation of AI's utility in microbial diagnostics, addressing both advantages and challenges. A few case studies including SARS-CoV-2, malaria, and mycobacteria serve to illustrate AI's potential for swift and precise diagnosis. Utilization of convolutional neural networks (CNNs) in digital pathology, automated bacterial classification, and colony counting further underscores AI's versatility. Additionally, AI improves antimicrobial susceptibility assessment and contributes to disease surveillance, outbreak forecasting, and real-time monitoring. Despite a few limitations, integration of AI in diagnostic microbiology presents robust solutions, user-friendly algorithms, and comprehensive training, promising paradigm-shifting advancements in healthcare.

Association between volatile organic compounds and serum neurofilament light chain in US adults

OBJECTIVE

This study aimed to investigate the associations between exposure to blood volatile organic compounds (VOCs) and the level of serum neurofilament light chain (NfL) in adults.

METHODS

We analyzed data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), including 2008 participants aged 20 to 75 years old. Multiple linear regression models were used to examine the associations between 28 VOCs and NfL after adjusting for multiple potential confounders. Restricted cubic spline (RCS) was used to examine the potential non-linear associations.

RESULTS

The linear regression models showed that higher levels of 2,5-dimethylfuran (β = 0.042, 95 % confidence interval [CI]: 0.001, 0.096), ethyl acetate (β = 0.118, 95 % CI = 0.008, 0.304), and m-/p-xylene (β = 0.043, 95%CI = 0.012, 0.074) were associated with higher NfL levels. These estimates were largely consistent after adjusting for multiple confounders.

CONCLUSION

The findings of our study suggest a potential association between certain volatile organic compounds (2,5-dimethylfuran, ethyl acetate, and m-/p-xylene) and blood NfL levels, implying that they may have a role in revealing neurodegeneration and influencing neurological health.

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.

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.

Breath Markers of Oxidative Stress in Children with Severe Viral Lower Respiratory Tract Infection

Severe viral lower respiratory tract infection (LRTI), resulting in both acute and long-term pulmonary disease, constitutes a substantial burden among young children. Viral LRTI triggers local oxidative stress pathways by infection and inflammation, and supportive care in the pediatric intensive care unit may further aggravate oxidative injury. The main goal of this exploratory study was to identify and monitor breath markers linked to oxidative stress in children over the disease course of severe viral LRTI. Exhaled breath was sampled during invasive ventilation, and volatile organic compounds (VOCs) were analyzed using gas chromatography and mass spectrometry. VOCs were selected in an untargeted principal component analysis and assessed for change over time. In addition, identified VOCs were correlated with clinical parameters. Seventy breath samples from 21 patients were analyzed. A total of 15 VOCs were identified that contributed the most to the explained variance of breath markers. Of these 15 VOCs, 10 were previously linked to pathways of oxidative stress. Eight VOCs, including seven alkanes and methyl alkanes, significantly decreased from the initial phase of ventilation to the day of extubation. No correlation was observed with the administered oxygen dose, whereas six VOCs showed a poor to strong positive correlation with driving pressure. In this prospective study of children with severe viral LRTI, the majority of VOCs that were most important for the explained variance mirrored clinical improvement. These breath markers could potentially help monitor the pulmonary oxidative status in these patients, but further research with other objective measures of pulmonary injury is required.

Early-life house dust mite aeroallergen exposure augments cigarette smoke-induced myeloid inflammation and emphysema in mice

BACKGROUND

Longitudinal studies have identified childhood asthma as a risk factor for obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO) where persistent airflow limitation can develop more aggressively. However, a causal link between childhood asthma and COPD/ACO remains to be established. Our study aimed to model the natural history of childhood asthma and COPD and to investigate the cellular/molecular mechanisms that drive disease progression.

METHODS

Allergic airways disease was established in three-week-old young C57BL/6 mice using house dust mite (HDM) extract. Mice were subsequently exposed to cigarette smoke (CS) and HDM for 8 weeks. Airspace enlargement (emphysema) was measured by the mean linear intercept method. Flow cytometry was utilised to phenotype lung immune cells. Bulk RNA-sequencing was performed on lung tissue. Volatile organic compounds (VOCs) in bronchoalveolar lavage-fluid were analysed to screen for disease-specific biomarkers.

RESULTS

Chronic CS exposure induced emphysema that was significantly augmented by HDM challenge. Increased emphysematous changes were associated with more abundant immune cell lung infiltration consisting of neutrophils, interstitial macrophages, eosinophils and lymphocytes. Transcriptomic analyses identified a gene signature where disease-specific changes induced by HDM or CS alone were conserved in the HDM-CS group, and further revealed an enrichment of Mmp12, Il33 and Il13, and gene expression consistent with greater expansion of alternatively activated macrophages. VOC analysis also identified four compounds increased by CS exposure that were paradoxically reduced in the HDM-CS group.

CONCLUSIONS

Early-life allergic airways disease worsened emphysematous lung pathology in CS-exposed mice and markedly alters the lung transcriptome.

The role of volatile organic compounds for assessing characteristics and severity of non-cystic fibrosis bronchiectasis: an observational study

Background

Hypoxic conditions and Pseudomonas aeruginosa (P. aeruginosa) infection are significant factors influencing the prognosis and treatment of patients with bronchiectasis. This study aimed to explore the potential for breath analysis to detect hypoxic conditions and P. aeruginosa infection in bronchiectasis patients by analyzing of volatile organic compounds (VOCs) in exhaled breath condensate (EBC).

Methods

EBC samples were collected from stable bronchiectasis patients and analyzed using solid phase microextraction-gas chromatography-mass spectrometry (SPME-GCMS). The association of VOCs with bronchiectasis patients' phenotypes including hypoxic conditions and P. aeruginosa isolation was analyzed, which may relate to the severity of bronchiectasis disease.

Results

Levels of 10-heptadecenoic acid, heptadecanoic acid, longifolene, and decanol in the hypoxia group were higher compared to the normoxia group. Additionally, the levels of 13-octadecenoic acid, octadecenoic acid, phenol, pentadecanoic acid, and myristic acid were increased in P. aeruginosa (+) group compared to the P. aeruginosa (-) group. Subgroup analysis based on the bronchiectasis severity index (BSI)reveled that the levels of 10-heptadecenoic acid, heptadecanoic acid, decanol, 13-octadecenoic acid, myristic acid, and pentadecanoic acid were higher in the severe group compared to the moderate group. Multivariate linear regression showed that 10-heptadecenoic acid and age were independent prognostic factors for bronchiectasis patients with hypoxia. Furthermore, octadecenoic acid, phenol and gender were identified as independent prognostic factors for bronchiectasis patients with P. aeruginosa isolation.

Conclusion

The study provides evidence that specific VOCs in EBC are correlated with the severity of bronchiectasis, and 10-heptadecenoic acid is shown to be a predictive marker for hypoxia condition in bronchiectasis patients.

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.

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.

Interaction of the III-As monolayer with SARS-CoV-2 biomarkers: implications for biosensor development

The emergence of SARS-CoV-2 in 2019 led to the global COVID-19 pandemic, highlighting the urgency for developing cost-effective and non-invasive methods to detect diseases at an early stage. Human breath, rich in volatile organic compounds (VOCs), is promising for cost-effective and rapid disease detection, with specific VOCs like methanol, ethanal, butanone, acetone, and ethyl butyrate linked to COVID-19. Recent advances in biomarker detection and gas sensing with 2D materials, particularly III-As monolayers like BAs, GaAs, and AlAs, offer high sensitivity at low concentrations, providing a novel avenue for exploring their potential in detecting COVID-19 biomarkers. This article aims to examine the effects of adsorption on different properties of III-Arsenide (BAs, GaAs and AlAs) monolayers, particularly in connection with SARS-CoV-2 biomarkers. In order to examine the interaction between the monolayers and biomarkers, first-principles computations within the framework of density functional theory (DFT) are utilized. The present study involves an investigation of the modifications in the band structure, density of states (DOS), work function, electron density difference, and optical properties (reflectance and absorbance) of III-As monolayers, with the aim of assessing their viability for the detection of SARS-CoV-2 biomarkers along with interfering gases such as CO2 and H2O. It is observed that VOCs induce a notable change in the work function of GaAs which serves as an indicator of the presence of these biomarkers. However, the changes in work function are not as substantial as those for AlAs and BAs. Additionally, the chemiresistive sensitivity, optical sensitivity and recovery time of III-As are investigated. The findings suggest that the pristine GaAs monolayer displays a significant level of sensitivity and selectivity towards the SARS-CoV-2 biomarkers, rendering it a material with potential for utilization in sensing applications. Furthermore, it has been observed that the recovery time of the GaAs monolayer subsequent to its exposure to the VOC biomarkers lies within an acceptable threshold. Upon exposure to UV light, the recovery time is further reduced. The outcomes of our study indicate that GaAs monolayers exhibit considerable potential as chemiresistive, work function-based and optical sensors for the precise and discerning identification of VOCs linked to the SARS-CoV-2 virus compared to the other two III-As monolayers.

Exploiting volatile fingerprints for bladder cancer diagnosis: A scoping review of metabolomics and sensor-based approaches

Bladder cancer (BC) represents a significant global health concern, for which early detection is essential to improve patient outcomes. This review evaluates the potential of the urinary volatile organic compounds (VOCs) as biomarkers for detecting and staging BC. The methods used include gas chromatography-mass spectrometry (GC-MS)-based metabolomics and electronic-nose (e-nose) sensors. The GC-MS studies that have been published reveal diverse results in terms of diagnostic performance. The sensitivities range from 27 % to an impressive 97 %, while specificities vary between 43 % and 94 %. Furthermore, the accuracies reported in these studies range from 80 to 89 %. In the urine of BC patients, a total of 80 VOCs were discovered to be significantly altered when compared to controls. These VOCs encompassed a variety of chemical classes such as alcohols, aldehydes, alkanes, aromatic compounds, fatty acids, ketones, and terpenoids, among others. Conversely, e-nose-based studies displayed sensitivities from 60 to 100 %, specificities from 53 to 96 %, and accuracies from 65 to 97 %. Interestingly, conductive polymer-based sensors performed better, followed by metal oxide semiconductor and optical sensors. GC-MS studies have shown improved performance in detecting early stages and low-grade tumors, providing valuable insights into staging. Based on these findings, VOC-based diagnostic tools hold great promise for early BC detection and staging. Further studies are needed to validate biomarkers and their classification performance. In the future, advancements in VOC profiling technologies may significantly contribute to improving the overall survival and quality of life for BC patients.

Emissions of Volatile Organic Compounds from Human Occupants in a Student Office: Dependence on Ozone Concentration

Human occupants themselves constitute an important source of volatile organic compounds (VOCs) in indoor environments through breath and dermal emissions. In order to quantify VOC emissions from occupants under real-world settings, previous indoor observational studies often determined emission factors (i.e., average emission rates per person). However, the values obtained across these studies exhibited large variability, and the causes of this variability still need to be understood. Herein we report 10-day real-time VOC measurements in a university student office, using a proton transfer reaction-quadrupole interface-time-of-flight mass spectrometer. A method was developed to identify VOCs of primary human origin and to quantify the corresponding emission factors, accounting for the dynamically changing occupancy level and ventilation rate in the assessed office. We found that the emission factors of many dermally emitted VOCs strongly increased as the ozone concentration increased from <3 to 10-15 ppb. These VOCs include geranyl acetone, 6-methyl-5-hepten-2-one (6-MHO), and C10-C12 saturated aldehydes, which align with characteristic first-generation ozonolysis products of skin oil. The strongest increase occurred for 6-MHO, from 113 to 337 μg/h/p. In comparison, acetone and isoprene, which are primarily emitted from human breath, varied little with the ozone level. In light of this finding, we conducted an integrated analysis of emission factors reported in the literature for two frequently reported species, namely, 6-MHO and decanal. Ozone concentration alone can explain 94-97% of the variation in their emission factors across previous studies, and the best-estimated ozone dependence obtained using the literature data is consistent with those obtained in the current study. These results suggest that the ozone concentration is a key factor regulating emission factors of many dermally emitted VOCs in real indoor environments, which has to be considered when reporting or using the emission factors.

Cancer evaluation in dogs using cerumen as a source for volatile biomarker prospection

Cancer is one of the deadliest diseases in humans and dogs. Nevertheless, most tumor types spread faster in canines, and early cancer detection methods are necessary to enhance animal survival. Here, cerumen (earwax) was tested as a source of potential biomarkers for cancer evaluation in dogs. Earwax samples from dogs were collected from tumor-bearing and clinically healthy dogs, followed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS) analyses and multivariate statistical workflow. An evolutionary-based multivariate algorithm selected 18 out of 128 volatile metabolites as a potential cancer biomarker panel in dogs. The candidate biomarkers showed a full discrimination pattern between tumor-bearing dogs and cancer-free canines with high accuracy in the test dataset: an accuracy of 95.0% (75.1-99.9), and sensitivity and specificity of 100.0% and 92.9%, respectively. In summary, this work raises a new perspective on cancer diagnosis in dogs, being carried out painlessly and non-invasive, facilitating sample collection and periodic application in a veterinary routine.

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.

An electronic nose can identify humans by the smell of their ear

Terrestrial mammals identify conspecifics by body odor. Dogs can also identify humans by body odor, and in some instances, humans can identify other humans by body odor as well. Despite the potential for a powerful biometric tool, smell has not been systematically used for this purpose. A question arising in the application of smell to biometrics is which bodily odor source should we measure. Breath is an obvious candidate, but the associated humidity can challenge many sensing devices. The armpit is also a candidate source, but it is often doused in cosmetics. Here, we test the hypothesis that the ear may provide an effective source for odor-based biometrics. The inside of the ear has relatively constant humidity, cosmetics are not typically applied inside the ear, and critically, ears contain cerumen, a potent source of volatiles. We used an electronic nose to identify 12 individuals within and across days, using samples from the armpit, lower back, and ear. In an identification setting where chance was 8.33% (1 of 12), we found that we could identify a person by the smell of their ear within a day at up to ~87% accuracy (~10 of 12, binomial P < 10-5), and across days at up to ~22% accuracy (~3 of 12, binomial P < 0.012). We conclude that humans can indeed be identified from the smell of their ear, but the results did not imply a consistent advantage over other bodily odor sources.

Volatilomes of human infection

The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.

Impact of thermal desorption tubes on the variability of exhaled breath data

Due to the overall low abundance of volatile compounds in exhaled breath, it is necessary to preconcentrate the sample prior to traditional thermal desorption (TD) gas chromatography mass spectrometry analysis. While certain aspects of TD tubes, such as volatile storage, have been evaluated, many aspects remain uncharacterized. Two common TD tubes, Tenax TA and Biomonitoring 5TD tubes, were evaluated for background content and flow rate variability. The data illustrate that the Biomonitoring 5TD tubes have the highest number (23) and abundance of background contamination greater than 3x the mean noise when compared to Tenax TA (13) and empty tubes (9). Tentative identifications of the compounds in the background contamination experiment show that greater than 59% (16/27) of the compounds identified have been reported in the breath literature. The data illustrate the TD tube background abundance could account for more than 70% of the chromatographic signal from exhaled breath for these select compounds. Flow rate measurements of 200 Tenax TA and 200 Biomonitoring 5TD tubes show a large range in measured flow rates among the TD tubes (Tenax: 252.9-284.0 ml min-1, 5TD: 220.6-255.1 ml min-1). Finally, TD tubes of each type, Tenax TA and Biomonitoring 5TD, previously established to have high, medium, and low flow rates, show insignificant differences (p> 0.05) among the tubes of different flow rates, using both gas standards and an exhaled breath from a peppermint experiment. Collectively, these results establish overall background compounds attributed to each TD tube type tested. Additionally, while measured flow rate variability is present and plausibly impacts exhaled breath results, the data demonstrate no statistically significant difference was observed between tubes showing high, medium, and low flow rates from two separate sample types.

Graphene-based chemiresistive gas sensors

Gas sensors allow the monitoring of the chemical environment of humans, which is often crucial for their wellbeing or even survival. Miniaturization, reversibility, and selectivity are some of the key challenges for serial use of chemical sensors. This tutorial review describes critical aspects when using nanomaterials as sensing substrates for the application in chemiresistive gas sensors. Graphene has been shown to be a promising candidate, as it allows gas sensors to be operated at room temperature, possibly saving large amounts of energy. In this review, an overview is given on the general mechanisms for gas-sensitive semiconducting materials and the implications of doping and functionalization on the sensing parameters of chemiresistive devices. It shows in detail how different challenges, like sensitivity, response time, reversibility and selectivity have been approached by material development and operation modes. In addition, perspectives from the area of data analysis and intelligent algorithms are presented, which can further enhance these sensors' usability in the field.

Exhaled VOC Biomarkers from Rats Injected with PMs from Thirty-One Major Cities in China

Particulate matter (PMs) of different origins can cause diverse health effects. Here, a homemade box was used to facilitate real-time measurements of breath-borne volatile organic compounds (VOCs) by gas chromatography-ion mobility spectrometry. We have tracked exhaled VOC changes in 228 Wistar rats that were injected with water-soluble PM suspension filtrates (after 0.45 μm) from 31 China cities for 1 h to up to 1-6 days during the experiments. Rats exposed to the filtrates exhibited significant changes in breath-borne VOCs within hours, featuring dynamic fluctuations in the levels of acetone, butan-2-one, heptan-2-one-M, acetic acid-M, and ethanol. Subsequently, on the fifth to sixth day after the injection, there was a notable increase in the proportion of aldehydes (including hexanal-M, hexanal-D, pentanal, heptanal-M, and (E)-2-hexenal). The 10 dynamic VOC fingerprint patterns mentioned earlier showcased the capability to indirectly differentiate urban PM toxicity and categorize the 31 cities into four distinct groups based on their health effects. This study provides valuable insights into the mechanisms of exhaled VOCs and underscores their critical role as biomarkers for differentiating the toxicity of different PMs and detecting the early signs of potential diseases. The results from this work also provide a scientific basis for city-specific air pollution control and policy development.

Assessment of indoor air quality in health clubs: insights into (ultra)fine and coarse particles and gaseous pollutants

Introduction

Exercising on regular basis provides countless health benefits. To ensure the health, well-being and performance of athletes, optimal indoor air quality, regular maintenance and ventilation in sport facilities are essential.

Methods

This study assessed the levels of particulate, down to the ultrafine range (PM10, PM2.5, and particle number concentration in size range of 20-1,000 nm, i.e., - PNC20-1000 nm), gaseous pollutants (total volatile organic compounds - TVOCs, CO2, and O3) and comfort parameters (temperature - T, relative humidity - RH) in different functional spaces of health clubs (n = 8), under specific occupancy and ventilation restrictions.

Results and Discussion

In all HCs human occupancy resulted in elevated particles (up to 2-3 times than those previously reported), considering mass concentrations (PM10: 1.9-988.5 μg/m3 PM2.5: 1.6-479.3 μg/m3) and number (PNC 1.23 × 103 - 9.14 × 104 #/cm3). Coarse and fine PM indicated a common origin (rs = 0.888-0.909), while PNC showed low-moderate associations with particle mass (rs = 0.264-0.629). In addition, up to twice-higher PM and PNC were detected in cardiofitness & bodybuilding (C&B) areas as these spaces were the most frequented, reinforcing the impacts of occupational activities. In all HCs, TVOCs (0.01-39.67 mg/m3) highly exceeded the existent protection thresholds (1.6-8.9 times) due to the frequent use of cleaning products and disinfectants (2-28 times higher than in previous works). On contrary to PM and PNC, TVOCs were higher (1.1-4.2 times) in studios than in C&B areas, due to the limited ventilations combined with the smaller room areas/volumes. The occupancy restrictions also led to reduced CO2 (122-6,914 mg/m3) than previously observed, with the lowest values in HCs with natural airing. Finally, the specific recommendations for RH and T in sport facilities were largely unmet thus emphasizing the need of proper ventilation procedures in these spaces.

Changes in total volatile organic compound concentration in Seoul subway stations before (2019) and after (2021) the COVID-19 outbreak

Volatile organic compounds (VOCs) are major air pollutants often designated as specific hazardous or toxic. This study analyzed the trends in concentration changes and influencing factors of VOCs in underground subway stations in the Seoul Metro before (2019) and after (2021) the COVID-19 pandemic. A total of 506 samples were collected from 253 stations on lines 1-8 between May 2019 and September 2021. Total VOC concentrations in Seoul Metro increased after the COVID-19 pandemic 3.8 times over. The deeper the underground station platform, the greater the difference in the VOC concentrations between 2019 and 2021, which was positively related. Average VOC concentration was the highest (52.8 µg/m3) at a depth of 25-30 m and the lowest (23.9 µg/m3) at a depth of < 10 m in 2019. In conclusion, excessive disinfection during the COVID-19 pandemic resulted in increased VOC concentrations in the Seoul Metro, especially in the deeper underground stations. Less frequent quarantine disinfection is recommended to improve air quality.

Collision Enhanced Raman Scattering (CERS): An Ultra-High Efficient Raman Enhancement Technique for Hollow Core Photonic Crystal Fiber Based Raman Spectroscopy Gas Analyzer

Raman enhancement techniques are essential for gas analysis to increase the detection sensitivity of a Raman spectroscopy system. We have developed an efficient Raman enhancement technique called the collision-enhanced Raman scattering (CERS), where the active Raman gas as the analyte is mixed with a buffer gas inside the hollow-core photonic-crystal fiber (HCPCF) of a fiber-enhanced Raman spectroscopy (FERS) system. This results in an enhanced Raman signal from the analyte gas. In this study, we first showed that the intensity of the 587 cm-1 stimulated Raman scattering (SRS) peak of H2 confined in an HCPCF is enhanced by as much as five orders of magnitude by mixing with a buffer gas such as helium or N2. Secondly, we showed that the magnitudes of Raman enhancement depend on the type of buffer gas, with helium being more efficient compared to N2. This makes helium a favorable buffer gas for CERS. Thirdly, we applied CERS for Raman measurements of propene, a metabolically interesting volatile organic compound (VOC) with an association to lung cancer. CERS resulted in a substantial enhancement of propene Raman peaks. In conclusion, the CERS we developed is a simple and efficient Raman-enhancing mechanism for improving gas analysis. It has great potential for application in breath analysis for lung cancer detection.

Water interference in the chromatographic analysis of exhaled breath samples: Challenges and mitigation strategies

This study demonstrates the adverse effects of water in exhaled breath samples on the accuracy of breath biomarker analysis when using gas chromatography. The presence of water in exhaled breath significantly modifies the retention times and peak areas of compounds, particularly for low-boiling, early eluting compounds. To tackle this issue, a two-step approach is introduced. The process begins with thorough desorption of the sorbent tube using a high split ratio and a short analysis duration, followed by a secondary analysis of the same tube. The efficacy of the new, straightforward approach was illustrated using humid breath samples and 57 compound standard mixture. This study highlights the importance of proper sample pretreatment and analysis to ensure reliable and accurate results in clinical research.

Characterization of the microbiome and volatile compounds in anal gland secretions from domestic cats (Felis catus) using metagenomics and metabolomics

Many mammals rely on volatile organic chemical compounds (VOCs) produced by bacteria for their communication and behavior, though little is known about the exact molecular mechanisms or bacterial species that are responsible. We used metagenomic sequencing, mass-spectrometry based metabolomics, and culturing to profile the microbial and volatile chemical constituents of anal gland secretions in twenty-three domestic cats (Felis catus), in attempts to identify organisms potentially involved in host odor production. We found that the anal gland microbiome was dominated by bacteria in the genera Corynebacterium, Bacteroides, Proteus, Lactobacillus, and Streptococcus, and showed striking variation among individual cats. Microbiome profiles also varied with host age and obesity. Metabolites such as fatty-acids, ketones, aldehydes and alcohols were detected in glandular secretions. Overall, microbiome and metabolome profiles were modestly correlated (r = 0.17), indicating that a relationship exists between the bacteria in the gland and the metabolites produced in the gland. Functional analyses revealed the presence of genes predicted to code for enzymes involved in VOC metabolism such as dehydrogenases, reductases, and decarboxylases. From metagenomic data, we generated 85 high-quality metagenome assembled genomes (MAGs). Of importance were four MAGs classified as Corynebacterium frankenforstense, Proteus mirabilis, Lactobacillus johnsonii, and Bacteroides fragilis. They represent strong candidates for further investigation of the mechanisms of volatile synthesis and scent production in the mammalian anal gland.

Breath biopsy, a novel technology to identify head and neck squamous cell carcinoma: A systematic review

Head and neck cancers are a heterogeneous group of neoplasms, which together comprise the sixth most common cancer globally. Breath biopsies are a non-invasive clinical investigation that detect volatile organic compounds (VOCs) in exhaled breath. This systematic review examines current applications of breath biopsy for the diagnosis of head and neck squamous cell carcinoma (HNSCC), including data on efficacy and utility, and speculates on the future uses of this non-invasive detection method. Medline, PubMed, Web of Science, Cochrane and Scopus, as well as the grey literature were searched using a search strategy developed to identify relevant studies on the role of breath biopsy in the diagnosis of HNSCC. All included studies were subject to a thorough methodological quality assessment. The initial search generated a total of 1443 articles, 20 of which were eligible for review. A total of 660 HNSCC samples were investigated across the included studies. 3,7-dimethylundecane and benzaldehyde were among several VOCs to be significantly correlated with the presence of HNSCC compared to healthy controls. We show that current breath biopsy methods have high accuracy, specificity and sensitivity for identifying HNSCC. However, further studies are needed given the reported poor quality of the included studies.

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

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

Volatile profiling distinguishes Streptococcus pyogenes from other respiratory streptococcal species

Sore throat is one of the most common complaints encountered in the ambulatory clinical setting. Rapid, culture-independent diagnostic techniques that do not rely on pharyngeal swabs would be highly valuable as a point-of-care strategy to guide outpatient antibiotic treatment. Despite the promise of this approach, efforts to detect volatiles during oropharyngeal infection have yet been limited. In our research study, we sought to evaluate for specific bacterial volatile organic compounds (VOC) biomarkers in isolated cultures in vitro, in order to establish proof-of-concept prior to initial clinical studies of breath biomarkers. A particular challenge for the diagnosis of pharyngitis due to Streptococcus pyogenes is the likelihood that many metabolites may be shared by S. pyogenes and other related oropharyngeal colonizing bacterial species. Therefore, we evaluated whether sufficient metabolic differences are present, which distinguish the volatile metabolome of Group A streptococci from other streptococcal species that also colonize the respiratory mucosa, such as Streptococcus pneumoniae and Streptococcus intermedius. In this work, we identified 27 discriminatory VOCs (q-values < 0.05), composed of aldehydes, alcohols, nitrogen-containing compounds, hydrocarbons, ketones, aromatic compounds, esters, ethers, and carboxylic acid. From this group of volatiles, we identify candidate biomarkers that distinguish S. pyogenes from other species and establish highly produced VOCs that indicate the presence of S. pyogenes in vitro, supporting future breath-based diagnostic testing for streptococcal pharyngitis. IMPORTANCE Acute pharyngitis accounts for approximately 15 million ambulatory care visits in the United States. The most common and important bacterial cause of pharyngitis is Streptococcus pyogenesis, accounting for 15%-30% of pediatric pharyngitis. Distinguishing between bacterial and viral pharyngitis is key to management in US practice. The culture of a specimen obtained by a throat swab is the standard laboratory procedure for the microbiologic confirmation of pharyngitis; however, this method is time-consuming, which delays appropriate treatment. If left untreated, S. pyogenes pharyngitis may lead to local and distant complications. In this study, we characterized the volatile metabolomes of S. pyogenes and other related oropharyngeal colonizing bacterial species. We identify candidate biomarkers that distinguish S. pyogenes from other species and provide evidence to support future breath-based diagnostic testing for streptococcal pharyngitis.

Biosensor development for low-level acetaldehyde gas detection using mesoporous carbon electrode printed on a porous polyimide film

Acetaldehyde, which is an intermediate product of alcohol metabolism, is known to induce symptoms, including alcohol flushing, vomiting, and headaches in humans. Therefore, real-time monitoring of acetaldehyde levels is crucial to mitigating these health issues. However, current methods for detecting low-concentration gases necessitate the use of complex measurement equipment. In this study, we developed a low-cost, low-detection-limit, enzyme-based electrochemical biosensor for acetaldehyde gas detection that does not require sophisticated equipment. The sensor was constructed by screen-printing electrodes onto a porous polyimide film, using grafted MgO-templated carbon (GMgOC) as working electrode material, carbon for the counter electrode, and silver/silver chloride for the reference electrode. Pyrroloquinoline-quinone-dependent aldehyde dehydrogenase was immobilized on the working electrode, and a chamber was attached to the electrode chip and filled with 1-methoxy-5-methylphenazinium methyl sulfate solution. The sensor can be used to measure acetaldehyde gas concentrations from 0.02 to 0.1 ppm, making it suitable for monitoring human skin gas. This low detection limit was achieved by delivering the analyte through the porous polyimide film on which the electrodes were printed and accumulating acetaldehyde in the mesoporous GMgOC of the working electrode. This mechanism suggests that this sensor design can be adapted to develop other low-detection limit gas sensors, such as those for screening skin gas biomarkers.

A New Gas Analysis Method Based on Single-Beam Excitation Stimulated Raman Scattering in Hollow Core Photonic Crystal Fiber Enhanced Raman Spectroscopy

We previously developed a hollow-core photonic crystal fiber (HCPCF) based Raman scattering enhancement technique for gas/human breath analysis. It enhances photon-gas molecule interactions significantly but is still based on CW laser excitation spontaneous Raman scattering, which is a low-probability phenomenon. In this work, we explored nanosecond/sub-nanosecond pulsed laser excitation in HCPCF based fiber enhanced Raman spectroscopy (FERS) and successfully induced stimulated Raman scattering (SRS) enhancement. Raman measurements of simple and complex gases were performed using the new system to assess its feasibility for gas analysis. We studied the gas Raman scattering characteristics, the relationship between Raman intensities and pump energies, and the energy threshold for the transition from spontaneous Raman scattering to SRS. H2, CO2, and propene (C3H6) were used as test gases. Our results demonstrated that a single-beam pulsed pump combined with FERS provides an effective Raman enhancement technique for gas analysis. Furthermore, an energy threshold for SRS initiation was experimentally observed. The SRS-capable FERS system, utilizing a single-beam pulsed pump, shows great potential for analyzing complex gases such as propene, which is a volatile organic compound (VOC) gas, serving as a biomarker in human breath for lung cancer and other human diseases. This work contributes to the advancement of gas analysis and opens alternative avenues for exploring novel Raman enhancement techniques.

Exhaled volatile fatty acids, ruminal methane emission, and their diurnal patterns in lactating dairy cows

To date, the commonly used methods to assess rumen fermentation are invasive. Exhaled breath contains hundreds of volatile organic compounds (VOC) that can reflect animal physiological processes. In the present study, for the first time, we aimed to use a noninvasive metabolomics approach based on high-resolution mass spectrometry to identify rumen fermentation parameters in dairy cows. Enteric methane (CH4) production from 7 lactating cows was measured 8 times over 3 consecutive days using the GreenFeed system (C-Lock Technology Inc.). Simultaneously, exhalome samples were collected in Tedlar gas sampling bags and analyzed offline using a secondary electrospray ionization high-resolution mass spectrometry system. In total, 1,298 features were detected, among them targeted exhaled volatile fatty acids (eVFA; i.e., acetate, propionate, butyrate), which were putatively annotated using their exact mass-to-charge ratio. The intensity of eVFA, in particular acetate, increased immediately after feeding and followed a similar pattern to that observed for ruminal CH4 production. The average total eVFA concentration was 35.5 count per second (CPS), and among the individual eVFA, acetate had the greatest concentration, averaging 21.3 CPS, followed by propionate at 11.5 CPS, and butyrate at 2.67 CPS. Further, exhaled acetate was on average the most abundant of the individual eVFA at around 59.3%, followed by 32.5 and 7.9% of the total eVFA for propionate and butyrate, respectively. This corresponds well with the previously reported proportions of these VFA in the rumen. The diurnal patterns of ruminal CH4 emission and individual eVFA were characterized using a linear mixed model with cosine function fit. The model characterized similar diurnal patterns for eVFA and ruminal CH4 and H2 production. Regarding the diurnal patterns of eVFA, the phase (time of peak) of butyrate occurred first, followed by that of acetate and propionate. Importantly, the phase of total eVFA occurred around 1 h before that of ruminal CH4. This corresponds well with existing data on the relationship between rumen VFA production and CH4 formation. Results from the present study revealed a great potential to assess the rumen fermentation of dairy cows using exhaled metabolites as a noninvasive proxy for rumen VFA. Further validation, with comparisons to rumen fluid, and establishment of the proposed method are required.

MOF-Based Chemiresistive Gas Sensors: Toward New Functionalities

The sensing performances of gas sensors must be improved and diversified to enhance quality of life by ensuring health, safety, and convenience. Metal-organic frameworks (MOFs), which exhibit an extremely high surface area, abundant porosity, and unique surface chemistry, provide a promising framework for facilitating gas-sensor innovations. Enhanced understanding of conduction mechanisms of MOFs has facilitated their use as gas-sensing materials, and various types of MOFs have been developed by examining the compositional and morphological dependences and implementing catalyst incorporation and light activation. Owing to their inherent separation and absorption properties and catalytic activity, MOFs are applied as molecular sieves, absorptive filtering layers, and heterogeneous catalysts. In addition, oxide- or carbon-based sensing materials with complex structures or catalytic composites can be derived by the appropriate post-treatment of MOFs. This review discusses the effective techniques to design optimal MOFs, in terms of computational screening and synthesis methods. Moreover, the mechanisms through which the distinctive functionalities of MOFs as sensing materials, heterostructures, and derivatives can be incorporated in gas-sensor applications are presented.

Biomarkers in exhaled breath condensate as fingerprints of asthma, chronic obstructive pulmonary disease and asthma-chronic obstructive pulmonary disease overlap: a critical review

Asthma, chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap are the third leading cause of mortality around the world. They share some common features, which can lead to misdiagnosis. To properly manage these conditions, reliable markers for early and accurate diagnosis are needed. Over the past 20 years, many molecules have been investigated in the exhaled breath condensate to better understand inflammation pathways and mechanisms related to these disorders. Recently, more advanced techniques, such as sensitive metabolomic and proteomic profiling, have been used to obtain a more comprehensive understanding. This article reviews the use of targeted and untargeted metabolomic methodology to study asthma, COPD and asthma-COPD overlap.

Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19

Background

Although rapid screening for and diagnosis of coronavirus disease 2019 (COVID-19) are still urgently needed, most current testing methods are long, costly or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time mass spectrometry breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19.

Methods

In two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata.

Results

We obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72% and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by COVID-19 vaccination status.

Conclusions

Real-time, noninvasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.

Detection of Propionic Acids Trapped in Thin Zeolite Layer Using Thermal Desorption Analysis

Volatile organic compounds (VOCs) have recently received considerable attention for the analysis and monitoring of different biochemical processes in biological systems such as humans, plants, and microorganisms. The advantage of using VOCs to gather information about a specific process is that they can be extracted using different types of samples, even at low concentrations. Therefore, VOC levels represent the fingerprints of specific biochemical processes. The aim of this work was to develop a sensor based on a photoionization detector (PID) and a zeolite layer, used as an alternative analytic separation technique for the analysis of VOCs. The identification of VOCs occurred through the evaluation of the emissive profile during the thermal desorption phase, using a stainless-steel chamber for analysis. Emission profiles were evaluated using a double exponential mathematical model, which fit well if compared with the physical system, describing both the evaporation and diffusion processes. The results showed that the zeolite layer was selective for propionic acid molecules if compared to succinic acid molecules, showing linear behavior even at low concentrations. The process to define the optimal adsorption time between the propionic acid molecules was performed in the range of 5 to 60 min, followed by a thermal desorption process at 100 °C. An investigation of the relationship between the evaporation and diffusion rates showed that the maximum concentration of detected propionic acid molecules occurred in 15 min. Other analyses were performed to study how the concentration of VOCs depended on the desorption temperature and the volume of the analysis chamber. For this purpose, tests were performed using three analysis chambers with volumes of 25 × 10-6, 50 × 10-6, and 150 × 10-6 m3 at three different desorption temperatures of 20 °C, 50 °C, and 100 °C, respectively. The results demonstrated that the evaporation rate of the VOCs increased rapidly with an increasing temperature, while the diffusion rate remained almost constant and was characterized by a slow decay time. The diffusion ratio increased when using a chamber with a larger volume. These results highlight the capabilities of this alternative technique for VOC analysis, even for samples with low concentrations. The coupling of a zeolite layer and a PID improves the detection selectivity in portable devices, demonstrating the feasibility of extending its use to a wide range of new applications.

Breath analysis combined with cardiopulmonary exercise testing and echocardiography for monitoring heart failure patients: the AEOLUS protocol

This paper describes the AEOLUS pilot study which combines breath analysis with cardiopulmonary exercise testing (CPET) and an echocardiographic examination for monitoring heart failure (HF) patients. Ten consecutive patients with a prior clinical diagnosis of HF with reduced left ventricular ejection fraction were prospectively enrolled together with 15 control patients with cardiovascular risk factors, including hypertension, type II diabetes or chronic ischemic heart disease. Breath samples were collected at rest and during CPET coupled with exercise stress echocardiography (CPET-ESE) protocol by means of needle trap micro-extraction and were analyzed through gas-chromatography coupled with mass spectrometry. The protocol also involved using of a selected ion flow tube mass spectrometer for a breath-by-breath isoprene and acetone analysis during exercise. At rest, HF patients showed increased breath levels of acetone and pentane, which are related to altered oxidation of fatty acids and oxidative stress, respectively. A significant positive correlation was observed between acetone and the gold standard biomarker NT-proBNP in plasma (r= 0.646,p< 0.001), both measured at rest. During exercise, some exhaled volatiles (e.g., isoprene) mirrored ventilatory and/or hemodynamic adaptation, whereas others (e.g., sulfide compounds and 3-hydroxy-2-butanone) depended on their origin. At peak effort, acetone levels in HF patients differed significantly from those of the control group, suggesting an altered myocardial and systemic metabolic adaptation to exercise for HF patients. These preliminary data suggest that concomitant acquisition of CPET-ESE and breath analysis is feasible and might provide additional clinical information on the metabolic maladaptation of HF patients to exercise. Such information may refine the identification of patients at higher risk of disease worsening.

Human scent characterization: A review

Human scent has long been cited as a probable parameter that can be exploited as a biometric measure. Identifying the scent of individual persons using specially trained canines is a well-known forensic method which is frequently used in criminal investigations. To date there has been limited research on the chemical components present in human scent and their usefulness in distinguishing between people. This review delivers insight into studies which have dealt with human scent in forensics. Sample collection methods, sample preparation, instrumental analysis, compounds identified in human scent and data analysis techniques are discussed. Methods for sample collection and preparation are presented, but to date, there is no available validated method. Instrumental methods are presented and from the overview it is clear that gas chromatography combined with mass spectrometry is the method of choice. New developments such as two-dimensional gas chromatography offer exiting possibilities to collect more information. Given the amount and complexity of data, data processing is used to extract the relevant information to discriminate people. Finally, sensors offer new opportunities for the characterization of human scent.

Long-term in situ air quality assessment in closed environments: A gas chromatography-ion mobility spectrometry applicability study

Contemporary life is mostly spent in indoor spaces like private houses, workplaces, vehicles and public facilities. Nonetheless, the air quality in these closed environments is often poor which leads to people being exposed to a vast range of toxic and hazardous compounds. Volatile organic compounds (VOCs) are among the main factors responsible for the lack of air quality in closed spaces and, in addition, some of them are particularly hazardous to the human organism. Considering this fact, we conducted daily in situ air analyses over 1 year using a gas chromatography-ion mobility spectrometry (GC-IMS) device in an indoor location. The obtained results show that 10 VOCs were consistently present in the indoor air throughout the entire year, making them particularly important for controlling air quality. All of these compounds were successfully identified, namely acetic acid, acetone, benzene, butanol, ethanol, isobutanol, propanoic acid, propanol, 2-propanol and tert-butyl methyl ether. The behaviour of the total VOCs (tVOCs) intensity during the period of analysis and the relative variation between consecutive months were studied. It was observed that the overall trend of tVOCs closely mirrored the variation of air temperature throughout the year suggesting their strong correlation. The results obtained from this study demonstrate the high quality and relevance of the data, highlighting the suitability of GC-IMS for in situ long-term air quality assessment in indoor environments and, consequently, for identifying potential health risks for the human organism in both short-term and long-term exposure scenarios.