Volatolomics: A broad area of experimentation

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.

Vineyard soil heterogeneity and harvest date affect volatolomics and sensory attributes of Cabernet Sauvignon wines on a meso-terroir scale

To produce premium wines in a specific region is the goal of local oenologists. This study aimed to investigate the influence of soil properties and harvest date on the volatolomics of wine to provide a better insight into single-vineyard wines. Six Cabernet Sauvignon vineyards were selected in a semi-arid region to produce their wines at three harvest ripeness levels ranging from 23°Brix-28°Brix in three seasons (2019-2021). Results showed that among all six vineyards, the vineyard with the highest soil pH produced wines with lower C6 alcohols and herbaceous aroma. Moderate nutrition in soils was beneficial for the accumulation of β-damascenone and enhanced fruity and floral aroma in wines while over-fertile soil produced wines with the lowest sensory score. As the harvest ripeness elevated, the wine's fruity and floral aroma intensity decreased. Through advanced network analysis, the key volatiles such as β-damascenone, ethy1 lactate, and isoamyl octanoate, and their interaction in affecting wine sensory scores were evaluated. Our study provided a concept for producing premium single-vineyard wines.

Continuous Monitoring of Psychosocial Stress by Non-Invasive Volatilomics

Stress is becoming increasingly commonplace in modern times, making it important to have accurate and effective detection methods. Currently, detection methods such as self-evaluation and clinical questionnaires are subjective and unsuitable for long-term monitoring. There have been significant studies into biomarkers such as HRV, cortisol, electrocardiography, and blood biomarkers, but the use of multiple electrodes for electrocardiography or blood tests is impractical for real-time stress monitoring. To this end, there is a need for non-invasive sensors to monitor stress in real time. This study looks at the possibility of using breath and skin VOC fingerprinting as stress biomarkers. The Trier social stress test (TSST) was used to induce acute stress and HRV, cortisol, and anxiety levels were measured before, during, and after the test. GC-MS and sensor array were used to collect and measure VOCs. A prediction model found eight different stress-related VOCs with an accuracy of up to 78%, and a molecularly capped gold nanoparticle-based sensor revealed a significant difference in breath VOC fingerprints between the two groups. These stress-related VOCs either changed or returned to baseline after the stress induction, suggesting different metabolic pathways at different times. A correlation analysis revealed an association between VOCs and cortisol levels and a weak correlation with either HRV or anxiety levels, suggesting that VOCs may include complementary information in stress detection. This study shows the potential of VOCs as stress biomarkers, paving the way into developing a real-time, objective, non-invasive stress detection tool for well-being and early detection of stress-related diseases.

Identification of Green-Leaf Volatiles Released from Cabbage Palms (Sabal palmetto) Infected with the Lethal Bronzing Phytoplasma

Lethal bronzing (LB) is a fatal infection that affects over 20 species of palms (Arecaceae) and is caused by the phytoplasma 'Candidatus Phytoplasma aculeata'. This pathogen causes significant economic losses to landscape and nursery companies in Florida, USA. Recently, the vector was determined to be the planthopper Haplaxius crudus, which was more abundant on LB-infected palms. Herein, the volatile chemicals emitted from LB-infected palms were characterized using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Infected Sabal palmetto were identified and confirmed as positive for LB via quantitative PCR. Healthy controls of each species were selected for comparison. All infected palms exhibited elevated levels of hexanal and E-2-hexenal. Threatened palms showed high releasing concentrations of 3-hexenal and Z-3-hexen-1-ol. The volatiles characterized herein are common green-leaf volatiles (GLVs) emitted by plants under stress. This study considers the first documented case of GLVs in palms attributed to phytoplasma infection. Due to the apparent attraction of LB-infected palms to the vector, one or several of the GLVs identified in this study could serve as a lure for the vector and supplement management programs.

How to Build Live-Cell Sensor Microdevices

There is a lot of discussion on how viruses (such as influenza and SARS-CoV-2) are transmitted in air, potentially from aerosols and respiratory droplets, and thus it is important to monitor the environment for the presence of an active pathogen. Currently, the presence of viruses is being determined using primarily nucleic acid-based detection methods, such as reverse transcription- polymerase chain reaction (RT-PCR) tests. Antigen tests have also been developed for this purpose. However, most nucleic acid and antigen methods fail to discriminate between a viable and a non-viable virus. Therefore, we present an alternative, innovative, and disruptive approach involving a live-cell sensor microdevice that captures the viruses (and bacteria) from the air, becomes infected by them, and emits signals for an early warning of the presence of pathogens. This perspective outlines the processes and components required for living sensors to monitor the presence of pathogens in built environments and highlights the opportunity to use immune sentinels in the cells of normal human skin to produce monitors for indoor air pollutants.

Noninvasive Detection of Stress by Biochemical Profiles from the Skin

Stress is a leading cause of several disease types, yet it is underdiagnosed as current diagnostic methods are mainly based on self-reporting and interviews that are highly subjective, inaccurate, and unsuitable for monitoring. Although some physiological measurements exist (e.g., heart rate variability and cortisol), there are no reliable biological tests that quantify the amount of stress and monitor it in real time. In this article, we report a novel way to measure stress quickly, noninvasively, and accurately. The overall detection approach is based on measuring volatile organic compounds (VOCs) emitted from the skin in response to stress. Sprague Dawley male rats (n = 16) were exposed to underwater trauma. Sixteen naive rats served as a control group (n = 16). VOCs were measured before, during, and after induction of the traumatic event, by gas chromatography linked with mass spectrometry determination and quantification, and an artificially intelligent nanoarray for easy, inexpensive, and portable sensing of the VOCs. An elevated plus maze during and after the induction of stress was used to evaluate the stress response of the rats, and machine learning was used for the development and validation of a computational stress model at each time point. A logistic model classifier with stepwise selection yielded a 66-88% accuracy in detecting stress with a single VOC (2-hydroxy-2-methyl-propanoic acid), and an SVM (support vector machine) model showed a 66-72% accuracy in detecting stress with the artificially intelligent nanoarray. The current study highlights the potential of VOCs as a noninvasive, automatic, and real-time stress predictor for mental health.

On-Site Detection of Volatile Organic Compounds (VOCs)

Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.

A GABA Receptor Modulator and Semiochemical Compounds Evidenced Using Volatolomics as Candidate Markers of Chronic Exposure to Fipronil in Apis mellifera

Among the various "omics" approaches that can be used in toxicology, volatolomics is in full development. A volatolomic study was carried out on soil bacteria to validate the proof of concept, and this approach was implemented in a new model organism: the honeybee Apis mellifera. Emerging bees raised in the laboratory in pain-type cages were used. Volatolomics analysis was performed on cuticles, fat bodies, and adhering tissues (abdomens without the digestive tract), after 14 and 21 days of chronic exposure to 0.5 and 1 µg/L of fipronil, corresponding to sublethal doses. The VOCs analysis was processed using an HS-SPME/GC-MS method. A total of 281 features were extracted and tentatively identified. No significant effect of fipronil on the volatolome could be observed after 14 days of chronic exposure. Mainly after 21 days of exposure, a volatolome deviation appeared. The study of this deviation highlighted 11 VOCs whose signal abundances evolved during the experiment. Interestingly, the volatolomics approach revealed a VOC (2,6-dimethylcyclohexanol) that could act on GABA receptor activity (the fipronil target) and VOCs associated with semiochemical activities (pheromones, repellent agents, and compounds related to the Nasonov gland) leading to a potential impact on bee behavior.

Membrane inlet mass spectrometry method for food intake impact assessment on specific volatile organic compounds in exhaled breath

This research work describes the development of a novel bioanalytical method for the assessment of food impact on selected exhaled breath volatile organic compounds (VOCs) using a fast and portable screening VOC prototype sensor based on membrane inlet mass spectrometry (MIMS). Method and sensor prototype functionality was verified by obtaining good response times, linearity in the examined concentration ranges, and sensitivity and repeatability for several breath VOCs—acetone, ethanol, n-pentane, and isoprene. A new VOC sensor prototype was also proven to be sensitive enough for selected breath VOC quantification with limits of detection at low part per billion (ppb) levels—5 ppb for n-pentane, 10 ppb for acetone and ethanol, and 25 ppb for isoprene. Food impact assessment was accomplished by tracking the levels of acetone, ethanol, n-pentane, and isoprene in exhaled breath samples collected from 50 healthy participants before the meal and 60 min and 120 min after the meal. For acetone, isoprene, and n-pentane, a larger impact was noticed 120 min after the meal, while for ethanol, it was after 60 min. Obtained VOC levels were in the expected concentration ranges. Mean values at all time points were ~ 500–900 ppb for acetone and ~ 400–600 ppb for ethanol. Most of the results for n-pentane were below 5 ppb, but the mean value for those which were detected was ~ 30 ppb. Along with samples, data about participants’ lifestyle were collected via a short questionnaire, which were compared against obtained VOC levels in order to reveal some significant correlations between habits of participants and their breath VOC levels.

Enzyme-embedded electrospun fiber sensor of hydrophilic polymer for fluorometric ethanol gas imaging in vapor phase

Non-invasive measurement of volatile organic compounds (VOCs) emitted from living organisms is a powerful technique for diagnosing health conditions or diseases in humans. Bio-based gas sensors are suitable for the sensitive and selective measurement of a target VOC from a complex mixture of VOCs. Conventional bio-based sensors are normally prepared as wet-type probes to maintain proteins such as enzymes in a stable state, resulting in limitations in the commercialization of sensors, their operating environment, and performance. In this study, we present an enzyme-based fluorometric electrospun fiber sensor (eFES) mesh as a gas-phase biosensor in dry form. The eFES mesh targeting ethanol was fabricated by simple one-step electrospinning of polyvinyl alcohol with an alcohol dehydrogenase and an oxidized form of nicotinamide adenine dinucleotide. The enzyme embedded in the eFES mesh worked actively in a dry state without pretreatment. Substrate specificity was also maintained, and the sensor responded well to ethanol with a sufficient dynamic range. Adjustment of the pH and coenzyme quantity in the eFES mesh also affected enzyme activity. The dry-form biosensor-eFES mesh-will open a new direction for gas-phase biosensors because of its remarkable performance and simple fabrication, which is advantageous for commercialization.

A comparative study of plant volatiles induced by insect and gastropod herbivory

Insect and gastropod herbivores are major plant consumers and their importance in the evolution of plant defensive traits is broadly recognized. However, their respective effects on plant responses have rarely been compared. Here we focused on plant volatile emissions (VOCs) following herbivory and compared the effects of herbivory by caterpillars of the generalist insect Spodoptera littoralis and by generalist slugs of the genus Arion on the VOCs emissions of 14 cultivated plant species. Results revealed that plants consistently produced higher amounts of volatiles and responded more specifically to caterpillar than to slug herbivory. Specifically, plants released on average 6.0 times more VOCs (total), 8.9 times more green leaf volatiles, 4.2 times more terpenoids, 6.0 times more aromatic hydrocarbons, and 5.7 times more other VOCs in response to 1 cm² of insect damage than to 1 cm² of slug damage. Interestingly, four of the plant species tested produced a distinct blend of volatiles following insect damage but not slug damage. These findings may result from different chemical elicitors or from physical differences in herbivory by the two herbivores. This study is an important step toward a more inclusive view of plant responses to different types of herbivores.

Novel sampling strategy for alive animal volatolome extraction combined with GC-MS based untargeted metabolomics: Identifying mouse pup pheromones

In this study, we identify 11 mouse pup volatiles putatively involved in maternal care induction in adult females. For this purpose, we have adapted the dynamic headspace methodology to extract the volatolome of whole alive animals. Untargeted metabolomic methodology was used to compare the volatolome of neonatal (4-6 days) with elder pups until the age of weaning (21-23 days old). Pup volatolome was analyzed by gas chromatography (GC) coupled to single quadrupole mass spectrometry (MS) using automated thermal desorption for sample introduction. After data processing and multivariate statistical analysis, comparison with NIST spectral library allowed identifying compounds secreted preferentially by neonatal pups: di(propylen glycol) methyl ether, 4-nonenal, di(ethylene glycol) monobutyl ether, 2-phenoxyethanol, isomethyl ionone, tridecanal, 1,3-diethylbenzene, 1,2,4,5-tetramethylbenzene, 2-ethyl-p-xylene and tri(propylene glycol) methyl ether. Palmitic acid was enriched in the volatolome of fourth week youngsters compared to neonatal pups. The results demonstrated the great potential of the new sampling procedure combined with GC-MS based untargeted volatolomics to identify volatile pheromones in mammals.

Volatile organic compounds (VOCs) in exhaled breath as a marker of hypoxia in multiple chemical sensitivity

In the history of diagnostics, breath analysis was one of the first method used until the breakthrough of biochemical testing technology. Today, breath analysis has made a comeback with the development of gas analyzers and e‐noses, demonstrating its power in its applicability for diagnosing a wide range of diseases. The physical basis of multiple chemical sensitivity (MCS), an emerging environmental disease, is difficult to understand because it is based on the scenario of chronic hypoxia, with a complex of chemical compounds that trigger the syndrome and result in multiple symptoms.

The aim of this study was to investigate MCS by analyzing exhaled volatile organic compounds (VOCs). The volatile, metabolic picture could be a putative gold standard for understanding and diagnosing the disease. The study was based on recording in resting condition using the noninvasive passive e‐nose contactless breath test, the Olfactory Real‐Time Volatile Organic Compounds (ORT‐VOC) test in MCS, and control samples. The VOCs profile distinguished between disease and health. It also distinguished the gender‐related volatile profile with significant robustness. The results trace a putative compensatory physiological pathway elicited by increased lactate, leading to acidosis, and hyperventilation, resulting in the production of specific VOCs. We conclude that breath testing is a valuable tool to investigate the hypoxia‐related VOC profile, facilitating MCS diagnosis.

Analysis of Volatiles in Food Products

The evaluation of volatiles in food is an important aspect of food production. It gives knowledge about the quality of foods and their relationship to consumers’ choices. Alcohols, aldehydes, acids, esters, terpenes, pyrazines, and furans are the main chemical groups that are involved in aroma formation. They are products of food processing: thermal treatment, fermentation, storage, etc. Food aroma is a mixture of varied molecules. Because of this, the analysis of aroma composition can be challenging. The four main steps can be distinguished in the evaluation of the volatiles in the food matrix as follows: (1) isolation and concentration; (2) separation; (3) identification; and (4) sensory characterization. The most commonly used techniques to separate a fraction of volatiles from non-volatiles are solid-phase micro-(SPME) and stir bar sorptive extractions (SBSE). However, to study the active components of food aroma by gas chromatography with olfactometry detector (GC-O), solvent-assisted flavor evaporation (SAFE) is used. The volatiles are mostly separated on GC systems (GC or comprehensive two-dimensional GCxGC) with the support of mass spectrometry (MS, MS/MS, ToF–MS) for chemical compound identification. Besides omics techniques, the promising part could be a study of aroma using electronic nose. Therefore, the main assumptions of volatolomics are here described.

Tripartite relationship between gut microbiota, intestinal mucus and dietary fibers: towards preventive strategies against enteric infections

The human gut is inhabited by a large variety of microorganims involved in many physiological processes and collectively referred as to gut microbiota. Disrupted microbiome has been associated with negative health outcomes and especially could promote the onset of enteric infections. To sustain their growth and persistence within the human digestive tract, gut microbes and enteric pathogens rely on two main polysaccharide compartments, namely dietary fibers and mucus carbohydrates. Several evidences suggest that the three-way relationship between gut microbiota, dietary fibers and mucus layer could unravel the capacity of enteric pathogens to colonise the human digestive tract and ultimately lead to infection. The review starts by shedding light on similarities and differences between dietary fibers and mucus carbohydrates structures and functions. Next, we provide an overview of the interactions of these two components with the third partner, namely, the gut microbiota, under health and disease situations. The review will then provide insights into the relevance of using dietary fibers interventions to prevent enteric infections with a focus on gut microbial imbalance and impaired-mucus integrity. Facing the numerous challenges in studying microbiota-pathogen-dietary fiber-mucus interactions, we lastly describe the characteristics and potentialities of currently available in vitro models of the human gut.

Preliminary accuracy of COVID-19 odor detection by canines and HS-SPME-GC-MS using exhaled breath samples

The novel coronavirus SARS-CoV-2, since its initial outbreak in Wuhan, China has led to a worldwide pandemic and has shut down nations. As with any outbreak, there is a general strategy of detection, containment, treatment and/or cure. The authors would argue that rapid and efficient detection is critical and required to successful management of a disease. The current study explores and successfully demonstrates the use of canines to detect COVID-19 disease in exhaled breath. The intended use was to detect the odor of COVID-19 on contaminated surfaces inferring recent deposition of infectious material from a COVID-19 positive individual. Using masks obtained from hospitalized patients that tested positive for COVID-19 disease, four canines were trained and evaluated for their ability to detect the disease. All four canines obtained an accuracy >90% and positive predictive values ranging from ~73 to 93% after just one month of training.

Comparison of Targeted and Untargeted Approaches in Breath Analysis for the Discrimination of Lung Cancer from Benign Pulmonary Diseases and Healthy Persons

The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.

Induced volatolomics of pathologies

Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.

Analysis of volatile emissions from grape berries infected with Aspergillus carbonarius using hyphenated and portable mass spectrometry

Mycotoxins represent a serious risk for human and animal health. Οchratoxin A (OTA) is a carcinogenic mycotoxin produced by A. carbonarius that constitutes a severe problem for viticulture. In this study, we investigate the development of novel detection and on-line monitoring approaches for the detection of OTA in the field (i.e. out of the chemical laboratory) using advanced molecular sensing. Both stand-alone and hyphenated mass spectrometry (MS) based systems (e.g. Time-of-Flight ToF-MS and gas chromatography GC combined with MS) and compact portable membrane inlet MS (MIMS) have been employed for the first time to detect and monitor volatile emissions of grape berries infected by the fungus Aspergillus carbonarius. In vacuo (electron impact-EI) and ambient ionisation (electrospray ionisation-ESI) techniques were also examined. On-line measurements of the volatile emissions of grape berries, infected by various strains of A. carbonarius with different toxicity levels, were performed resulting in different olfactory chemical profiles with a common core of characteristic mass fragments, which could be eventually used for on-site detection and monitoring allowing consequent improvement in food security.

Activated carbon/titanium dioxide composite to adsorb volatile organic compounds associated with human body odor

The human body generates various malodor compounds in different body parts and even in the same parts. A more effective and versatile deodorant material that can suppress various key contributors to the body odor must be developed to improve the quality of life of affected individuals. In this study, activated carbon (AC) was found to have higher adsorption ability toward key body odor-generating compounds than zinc oxide (ZnO), which is a well-known deodorant material. To prevent pigmentation of human skin induced by the direct application of AC, white activated carbon (WAC) was developed by blending AC, titanium dioxide (TiO₂), and ammonium acrylate copolymer. AC to TiO₂ ratio of 1:6 was found to be the optimum blending ratio to form WAC. Compared with ZnO, this optimal WAC exhibited higher adsorption ability toward five key body odor compounds. The in vivo evaluation of the sample containing WAC revealed that it significantly suppressed the generation of axillary odor without a bactericidal effect. The developed WAC can effectively suppress the human body odor in different body parts. These findings are valuable for individuals experiencing psychological stress attributed to their unpleasant body odor.

Transcutaneous Blood VOC Imaging System (Skin-Gas Cam) with Real-Time Bio-Fluorometric Device on Rounded Skin Surface

A skin-gas cam that allows continuous imaging of transcutaneous blood volatile organic compounds (VOCs) emanated from human skin was developed. The skin-gas cam is able to reveal the relationship between the local skin conditions and transcutaneous blood VOCs in the field of volatile metabolomics (volatolomics). A ring-type ultraviolet (UV) light-emitting diode was mounted around a camera lens as an excitation light source, which enabled the simultaneous excitation and imaging of fluorescence. A nicotinamide adenine dinucleotide (NAD)-dependent alcohol dehydrogenase (ADH) was used to detect ethanol as a model sample. When gaseous ethanol was applied to an ADH-immobilized mesh that was wetted with an oxidized NAD solution placed in front of the camera, a reduced form of NAD (NADH) was produced through an ADH-mediated reaction. NADH emits fluorescence by UV excitation, and thus, the concentration distribution of ethanol was visualized by measuring the distribution of the fluorescence light intensity from NADH on the ADH-immobilized mesh surface. In this study, a new gas application method that mimicked the release mechanism of transcutaneous gas for quantification of the transcutaneous gas concentration was evaluated. Also, spatiotemporal changes of transcutaneous ethanol for various body parts were measured. As a result, we revealed a relationship between local skin conditions and VOCs that could not be observed previously. In particular, we demonstrated the facile measurement of transdermal gases from around the ear where capillaries are densely distributed below a thin stratum corneum.