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

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

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

Clinical applications of volatilomic assays

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

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

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

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

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

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

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

Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis

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

Internal Standard Addition System for Online Breath Analysis

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

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

BACKGROUND

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

AIM OF REVIEW

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

KEY SCIENTIFIC CONCEPTS OF REVIEW

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

Distinguish Esophageal Cancer Cells through VOCs Induced by Methionine Regulation

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

How Does Personal Hygiene Influence Indoor Air Quality?

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

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

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

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

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

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep

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

Electroactive nanofibrous membrane with antibacterial and deodorizing properties for air filtration

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

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

SCOPE

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

METHODS AND RESULTS

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

CONCLUSION

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

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

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

Predicting Chronological Age via the Skin Volatile Profile

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

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

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

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

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

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

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

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A Clinical Breathomics Dataset

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

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

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

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

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

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

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

Real-time breath analysis towards a healthy human breath profile

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

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

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

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.

The Respiratory Microbiome in Paediatric Chronic Wet Cough: What Is Known and Future Directions

Chronic wet cough for longer than 4 weeks is a hallmark of chronic suppurative lung diseases (CSLD), including protracted bacterial bronchitis (PBB), and bronchiectasis in children. Severe lower respiratory infection early in life is a major risk factor of PBB and paediatric bronchiectasis. In these conditions, failure to clear an underlying endobronchial infection is hypothesised to drive ongoing inflammation and progressive tissue damage that culminates in irreversible bronchiectasis. Historically, the microbiology of paediatric chronic wet cough has been defined by culture-based studies focused on the detection and eradication of specific bacterial pathogens. Various 'omics technologies now allow for a more nuanced investigation of respiratory pathobiology and are enabling development of endotype-based models of care. Recent years have seen substantial advances in defining respiratory endotypes among adults with CSLD; however, less is understood about diseases affecting children. In this review, we explore the current understanding of the airway microbiome among children with chronic wet cough related to the PBB-bronchiectasis diagnostic continuum. We explore concepts emerging from the gut-lung axis and multi-omic studies that are expected to influence PBB and bronchiectasis endotyping efforts. We also consider how our evolving understanding of the airway microbiome is translating to new approaches in chronic wet cough diagnostics and treatments.

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.

Advancing Colorectal Cancer Diagnosis with AI-Powered Breathomics: Navigating Challenges and Future Directions

Early detection of colorectal cancer is crucial for improving outcomes and reducing mortality. While there is strong evidence of effectiveness, currently adopted screening methods present several shortcomings which negatively impact the detection of early stage carcinogenesis, including low uptake due to patient discomfort. As a result, developing novel, non-invasive alternatives is an important research priority. Recent advancements in the field of breathomics, the study of breath composition and analysis, have paved the way for new avenues for non-invasive cancer detection and effective monitoring. Harnessing the utility of Volatile Organic Compounds in exhaled breath, breathomics has the potential to disrupt colorectal cancer screening practices. Our goal is to outline key research efforts in this area focusing on machine learning methods used for the analysis of breathomics data, highlight challenges involved in artificial intelligence application in this context, and suggest possible future directions which are currently considered within the framework of the European project ONCOSCREEN.

Global Urinary Volatolomics with (GC×)GC-TOF-MS

Urinary volatolomics offers a noninvasive approach for disease detection and monitoring. Herein we present an improved methodology for global volatolomic profiling. Wide coverage was achieved by utilizing a multiphase sorbent for volatile organic compound (VOC) extraction. A single, midpolar column gas chromatography (GC) assay yielded substantially higher numbers of monitored VOCs compared to our previously reported single-sorbent method. Multidimensional GC (GC×GC) enhanced further biomarker discovery while data analysis was simplified by using a tile-based approach. At the same time, the required urine volume was reduced 5-fold from 2 to 0.4 mL. The applicability of the methodology was demonstrated in a pancreatic ductal adenocarcinoma cohort where previous findings were confirmed while a series of additional VOCs with diagnostic potential were discovered.

Mass Specthoscope: A Hand-held Extendable Probe for Localized Noninvasive Sampling of Skin Volatome for Online Analysis

Human skin emits a unique set of volatile organic compounds (VOCs). These VOCs can be probed in order to obtain physiological information about the individuals. However, extracting the VOCs that emanate from human skin for analysis is troublesome and time-consuming. Therefore, we have developed "Mass Specthoscope"─a convenient tool for rapid sampling and detecting VOCs emitted by human skin. The hand-held probe with a pressurized tip and wireless button enables sampling VOCs from surfaces and their transfer to the atmospheric pressure chemical ionization source of quadrupole time-of-flight mass spectrometer. The system was characterized using chemical standards (acetone, benzaldehyde, sulcatone, α-pinene, and decanal). The limits of detection are in the range from 2.25 × 10-5 to 3.79 × 10-5 mol m-2. The system was initially tested by detecting VOCs emanating from porcine skin spiked with VOCs as well as unspiked fresh and spoiled ham. In the main test, the skin of nine healthy participants was probed with the Mass Specthoscope. The sampling regions included the armpit, forearm, and forehead. Numerous skin-related VOC signals were detected. In the final test, one participant ingested a fenugreek drink, and the participant's skin surface was probed using the Mass Specthoscope hourly during the 8 h period. The result revealed a gradual release of fenugreek-related VOCs from the skin. We believe that this analytical approach has the potential to be used in metabolomic studies and following further identification of disease biomarkers─also in noninvasive diagnostics.

The volatilome signatures of Plasmodium falciparum parasites during the intraerythrocytic development cycle in vitro under exposure to artemisinin drug

Volatile organic compounds (VOCs) comprise a diverse range of metabolites with high vapour pressure and low boiling points. Although they have received attention, they are a largely unexplored part of the metabolome. Previous studies have shown that malaria infections produce characteristic, definitive, and detectable volatile signatures. Many transcriptional and metabolic differences are observed at different stages of the parasite Intraerythrocytic Developmental Cycle (IDC) as well as when artemisinin-resistant parasites are put under drug pressure. This prompted our research to characterize whether these responses are reflected at a volatile level in malaria during the IDC stages using gas chromatography-mass spectrometry. We investigated whether the resistant P. falciparum parasites would produce their own characteristic volatilome profile compared to near-isogenic wild-type parasite in vitro; firstly at three different stages of the IDC and secondly in the presence or absence of artemisinin drug treatment. Finally, we explored the VOC profiles from two media environments (Human serum and Albumax) of recently lab-adapted field parasite isolates, from Southeast Asia and West/East Africa, compared to long-term lab-adapted parasites. Recognizable differences were observed between IDC stages, with schizonts having the largest difference between wild type and resistant parasites, and with cyclohexanol and 2,5,5-trimethylheptane only present for resistant schizonts. Artemisinin treatment had little effect on the resistant parasite VOC profile, whilst for the wild type parasites compounds ethylbenzene and nonanal were greatly affected. Lastly, differing culturing conditions had an observable impact on parasite VOC profile and clustering patterns of parasites were specific to geographic origin. The results presented here provide the foundation for future studies on VOC based characterization of P. falciparum strains differing in abilities to tolerate artemisinin.

Mass Spectrometry Analysis for Clinical Applications: A Review

Mass spectrometry (MS) has become an attractive analytical method in clinical analysis due to its comprehensive advantages of high sensitivity, high specificity and high throughput. Separation techniques coupled MS detection (e.g., LC-MS/MS) have shown unique advantages over immunoassay and have developed as golden criterion for many clinical applications. This review summarizes the characteristics and applications of MS, and emphasizes the high efficiency of MS in clinical research. In addition, this review also put forward further prospects for the future of mass spectrometry technology, including the introduction of miniature MS instruments, point-of-care detection and high-throughput analysis, to achieve better development of MS technology in various fields of clinical application. Moreover, as ambient ionization mass spectrometry (AIMS) requires little or no sample pretreatment and improves the flux of MS, this review also summarizes its potential applications in clinic.

A PVDF-based colorimetric sensor array for noninvasive detection of multiple disease-related volatile organic compounds

Detection of human-generated volatile organic compounds (VOCs) is a new pathway for assessing health. Herein, a polyvinylidene fluoride (PVDF)-based colorimetric sensor array was designed for detecting disease-related VOCs (DVOCs) within 15 min, using a complex of Cu metal-organic framework, graphene aerogel, and dyes as response materials. Fingermaps derived from 28 DVOCs were obtained for further data processing. Pattern recognition was successfully employed in the correct discrimination of 28 DVOCs in low (10 μM), medium (100 μM), and high (300 μM) concentrations. Importantly, the sensor array also presented excellent discrimination ability and application potential when detecting VOCs produced by human cancer and normal cells. In general, VOC acquisition is noninvasive and harmless, and the PVDF-based sensor arrays are simple and visual. Such advantages expand their further application potential.

Elucidating the Role of Ion Suppression in Secondary Electrospray Ionization

Ion suppression is a known matrix effect in electrospray ionization (ESI), ambient pressure chemical ionization (APCI), and desorption electrospray ionization (DESI), but its characterization in secondary electrospray ionization (SESI) is lacking. A thorough understanding of this effect is crucial for quantitative applications of SESI, such as breath analysis. In this study, gas standards were generated by using an evaporation-based system to assess the susceptibility and suppression potential of acetone, deuterated acetone, deuterated acetic acid, and pyridine. Gas-phase effects were found to dominate ion suppression, with pyridine exhibiting the most significant suppressive effect, which is potentially linked to its gas-phase basicity. The impact of increased acetone levels on the volatiles from exhaled breath condensate was also examined. In humid conditions, a noticeable decrease in intensity of approximately 30% was observed for several features at an acetone concentration of 1 ppm. Considering that this concentration is expected for breath analysis, it becomes crucial to account for this effect when SESI is utilized to quantitatively determine specific compounds.

Human scent as a first-line defense against disease

Individuals may have a different body odor, when they are sick compared to healthy. In the non-human animal literature, olfactory cues have been shown to predict avoidance of sick individuals. We tested whether the mere experimental activation of the innate immune system in healthy human individuals can make an individuals' body odor be perceived as more aversive (intense, unpleasant, and disgusting). Following an endotoxin injection (lipopolysaccharide; 0.6 ng/kg) that creates a transient systemic inflammation, individuals smelled more unpleasant compared to a placebo group (saline injection). Behavioral and chemical analyses of the body odor samples suggest that the volatile components of samples from "sick" individuals changed qualitatively rather than quantitatively. Our findings support the hypothesis that odor cues of inflammation in axillary sweat are detectable just a few hours after experimental activation of the innate immune system. As such, they may trigger behavioral avoidance, hence constituting a first line of defense against pathogens of infected conspecifics.

Quantifying Mosquito Attraction Behavior Using Olfactometry

When blood feeding from human hosts, female mosquitoes can transmit life-threatening pathogens to humans, including dengue virus, chikungunya virus, and Zika virus. Olfaction is the primary sense mosquitoes use to locate and differentiate hosts and studying it can lead to new strategies to reduce the risk of disease. To effectively study host-seeking behavior in mosquitoes, a repeatable, quantitative assay that isolates olfaction from other cues is critical for interpreting mosquito behavior. Here, we contribute an overview of methods and best practices for the study of mosquito attraction (or lack thereof) by using olfactometry to quantify behavior. In the accompanying protocols, we present an olfactory-based behavioral assay using a uniport olfactometer that measures mosquito attraction rate to specific stimuli. We include construction details, setup of the uniport olfactometer, details of the behavioral assay, and data analysis guidelines, as well as how to prepare the mosquitoes before their introduction into the olfactometer. This uniport olfactometer behavioral assay is currently one of the most reliable methods to study mosquito attraction to a single olfactory stimulus.

The Olfaction Ability of Medical Detection Canine to Detect Prostate Cancer From Urine Samples: Progress Captured in Systematic Review and Meta-Analysis

Background

To date, early cancer detection is considered vital to reduce the global cancer burden through low-cost, but accurate screening modalities. The anatomical positioning of prostate cancer (PCa) created a potentially distinctive diagnostic method through the identification of volatile organic compounds (VOCs) in urine, which might be detectable not by humans but by canine species. This review aimed to capture the potential of the medical detection canine (MDC) to detect PCa by providing its diagnostic accuracy estimation on urine odor testing.

Methods

Databases, e.g., MEDLINE, Cochrane, ScienceDirect, and ProQuest, were searched to identify the studies. We focused on accessible original research, comparing the diagnostic utility of trained female MDC and histopathology examination as the gold standard for PCa diagnosis. The statistical analysis was performed in Meta-DiSc 1.4 and presented in diagnostic values, i.e., sensitivity (Sn), specificity (Sp), positive or negative likelihood ratio (LR+ or LR-), diagnostic odd ratio (DOR), and area under the curve (AUC) value, to conclude the Sn-Sp in a single outcome.

Results

Female German Shepherds were the most commonly utilized MDC from the five studies included in the final analysis. We estimate the pooled diagnostic value of eight different MDCs, with the findings as follows: Sn (0.95 (0.94 - 0.97)), Sp (0.92 (0.90 - 0.93)), LR+ (4.48 (1.90 - 10.58)), LR- (0.12 (0.01 - 1.42)), DOR (35.39 (2.90 - 432.53)), and an AUC value of 0.9232.

Conclusions

MDC's olfaction ability holds considerable potential on its diagnostic accuracies to distinguish the urine of PCa individuals by identifying its volatilome property.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Past, Present, and Future of Human Chemical Communication Research

Although chemical signaling is an essential mode of communication in most vertebrates, it has long been viewed as having negligible effects in humans. However, a growing body of evidence shows that the sense of smell affects human behavior in social contexts ranging from affiliation and parenting to disease avoidance and social threat. This article aims to (a) introduce research on human chemical communication in the historical context of the behavioral sciences; (b) provide a balanced overview of recent advances that describe individual differences in the emission of semiochemicals and the neural mechanisms underpinning their perception, that together demonstrate communicative function; and (c) propose directions for future research toward unraveling the molecular principles involved and understanding the variability in the generation, transmission, and reception of chemical signals in increasingly ecologically valid conditions. Achieving these goals will enable us to address some important societal challenges but are within reach only with the aid of genuinely interdisciplinary approaches.

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.

HS-SPME-GC-MS Untargeted Analysis of Normal Rat Organs Ex Vivo: Differential VOC Discrimination and Fingerprint VOC Identification

The investigation of volatile organic compounds (VOCs) in human metabolites has been a topic of interest as it holds the potential for the development of non-invasive technologies to screen for organ lesions in vivo. However, it remains unclear whether VOCs differ among healthy organs. Consequently, a study was conducted to analyze VOCs in ex vivo organ tissues obtained from 16 Wistar rats, comprising 12 different organs. The VOCs released from each organ tissue were detected by the headspace-solid phase microextraction-gas chromatography-mass spectrometry technique. In the untargeted analysis of 147 chromatographic peaks, the differential volatiles of rat organs were explored based on the Mann-Whitney U test and fold change (FC > 2.0) compared with other organs. It was found that there were differential VOCs in seven organs. A discussion on the possible metabolic pathways and related biomarkers of organ differential VOCs was conducted. Based on the orthogonal partial least squares discriminant analysis and receiver operating characteristic curve, we found that differential VOCs in the liver, cecum, spleen, and kidney can be used as the unique identification of the corresponding organ. In this study, differential VOCs of organs in rats were systematically reported for the first time. Profiles of VOCs produced by healthy organs can serve as a reference or baseline that may indicate the presence of disease or abnormalities in the organ's function. Differential VOCs can be used as the fingerprint of organs, and future integration with metabolic research may contribute to the development of healthcare.

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.

Human scent guides mosquito thermotaxis and host selection under naturalistic conditions

The African malaria mosquito Anopheles gambiae exhibits a strong innate drive to seek out humans in its sensory environment, classically entering homes to land on human skin in the hours flanking midnight. To gain insight into the role that olfactory cues emanating from the human body play in generating this epidemiologically important behavior, we developed a large-scale multi-choice preference assay in Zambia with infrared motion vision under semi-field conditions. We determined that An. gambiae prefers to land on arrayed visual targets warmed to human skin temperature during the nighttime when they are baited with carbon dioxide (CO2) emissions reflective of a large human over background air, body odor from one human over CO2, and the scent of one sleeping human over another. Applying integrative whole body volatilomics to multiple humans tested simultaneously in competition in a six-choice assay, we reveal high attractiveness is associated with whole body odor profiles from humans with increased relative abundances of the volatile carboxylic acids butyric acid, isobutryic acid, and isovaleric acid, and the skin microbe-generated methyl ketone acetoin. Conversely, those least preferred had whole body odor that was depleted of carboxylic acids among other compounds and enriched with the monoterpenoid eucalyptol. Across expansive spatial scales, heated targets without CO2 or whole body odor were minimally or not attractive at all to An. gambiae. These results indicate that human scent acts critically to guide thermotaxis and host selection by this prolific malaria vector as it navigates towards humans, yielding intrinsic heterogeneity in human biting risk.

On-Field Test of Tuberculosis Diagnosis through Exhaled Breath Analysis with a Gas Sensor Array

Tuberculosis (TB) is among the more frequent causes of death in many countries. For pulmonary TB, early diagnosis greatly increases the efficiency of therapies. Although highly sensitive tests based on nucleic acid amplification tests (NAATs) and loop-mediated isothermal amplification (TB-LAMP) are available, smear microscopy is still the most widespread diagnostics method in most low-middle-income countries, and the true positive rate of smear microscopy is lower than 65%. Thus, there is a need to increase the performance of low-cost diagnosis. For many years, the use of sensors to analyze the exhaled volatile organic compounds (VOCs) has been proposed as a promising alternative for the diagnosis of several diseases, including tuberculosis. In this paper, the diagnostic properties of an electronic nose (EN) based on sensor technology previously used to identify tuberculosis have been tested on-field in a Cameroon hospital. The EN analyzed the breath of a cohort of subjects including pulmonary TB patients (46), healthy controls (38), and TB suspects (16). Machine learning analysis of the sensor array data allows for the identification of the pulmonary TB group with respect to healthy controls with 88% accuracy, 90.8% sensitivity, 85.7% specificity, and 0.88 AUC. The model trained with TB and healthy controls maintains its performance when it is applied to symptomatic TB suspects with a negative TB-LAMP. These results encourage the investigation of electronic noses as an effective diagnostic method for future inclusion in clinical practice.

Biological studies with comprehensive 2D-GC-HRMS screening: Exploring the human sweat volatilome

A key issue in GCxGC-HRMS data analysis is how to approach large-sample studies in an efficient and comprehensive way. We have developed a semi-automated data-driven workflow from identification to suspect screening, which allows highly selective monitoring of each identified chemical in a large-sample dataset. The example dataset used to illustrate the potential of the approach consisted of human sweat samples from 40 participants, including field blanks (80 samples). These samples have been collected in a Horizon 2020 project to investigate the capacity of body odour to communicate emotion and influence social behaviour. We used dynamic headspace extraction, which allows comprehensive extraction with high preconcentration capability, and has to date only been used for a few biological applications. We were able to detect a set of 326 compounds from a diverse range of chemical classes (278 identified compounds, 39 class unknowns, and 9 true unknowns). Unlike partitioning-based extraction methods, the developed method detects semi-polar (log P < 2) nitrogen and oxygen-containing compounds. However, it is unable to detect certain acids due to the pH conditions of unmodified sweat samples. We believe that our framework will open up the possibility of efficiently using GCxGC-HRMS for large-sample studies in a wide range of applications such as biological and environmental studies.