Human exhaled air analytics: biomarkers of diseases

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry

BACKGROUND

Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).

OBJECTIVE

To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.

METHODS

102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z).

RESULTS

PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing.

CONCLUSION

PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

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.

Exhaled breath analyses for bronchial thermoplasty in severe asthma patients

BACKGROUND

Bronchial thermoplasty (BT) is a bronchoscopic treatment for severe asthma. Although multiple trials have demonstrated clinical improvement after BT, optimal patient selection remains a challenge and the mechanism of action is incompletely understood. The aim of this study was to examine whether exhaled breath analysis can contribute to discriminate between BT-responders and non-responders at baseline and to explore pathophysiological insights of BT.

METHODS

Exhaled breath was collected from patients at baseline and six months post-BT. Patients were defined as responders or non-responders based on a half point increase in asthma quality of life questionnaire scores. Gas chromatography-mass spectrometry was used for volatile organic compounds (VOCs) detection and analyses. Analytical workflow consisted of: 1) detection of VOCs that differentiate between responders and non-responders and those that differ between baseline and six months post-BT, 2) identification of VOCs of interest and 3) explore correlations between clinical biomarkers and VOCs.

RESULTS

Data was available from 14 patients. Nonanal, 2-ethylhexanol and 3-thujol showed a significant difference in intensity between responders and non-responders at baseline (p = 0.04, p = 0.01 and p = 0.03, respectively). After BT, no difference was found in the compound intensity of these VOCs. A negative correlation was observed between nonanal and IgE and BALF eosinophils (r = -0.68, p < 0.01 and r = -0.61, p = 0.02 respectively) and 3-thujol with BALF neutrophils (r = -0.54, p = 0.04).

CONCLUSIONS

This explorative study identified discriminative VOCs in exhaled breath between BT responders and non-responders at baseline. Additionally, correlations were found between VOC's and inflammatory BALF cells. Once validated, these findings encourage research in breath analysis as a non-invasive easy to apply technique for identifying airway inflammatory profiles and eligibility for BT or immunotherapies in severe asthma.

Carbon dioxide shapes parasite-host interactions in a human-infective nematode

Skin-penetrating nematodes infect nearly one billion people worldwide. The developmentally arrested infective larvae (iL3s) seek out hosts, invade hosts via skin penetration, and resume development inside the host in a process called activation. Activated infective larvae (iL3as) traverse the host body, ending up as parasitic adults in the small intestine. Skin-penetrating nematodes respond to many chemosensory cues, but how chemosensation contributes to host seeking, intra-host development, and intra-host navigation - three crucial steps of the parasite-host interaction - remains poorly understood. Here, we investigate the role of carbon dioxide (CO2) in promoting parasite-host interactions in the human-infective threadworm Strongyloides stercoralis. We show that S. stercoralis exhibits life-stage-specific preferences for CO2: iL3s are repelled, non-infective larvae and adults are neutral, and iL3as are attracted. CO2 repulsion in iL3s may prime them for host seeking by stimulating dispersal from host feces, while CO2 attraction in iL3as may direct worms toward high-CO2 areas of the body such as the lungs and intestine. We also identify sensory neurons that detect CO2; these neurons are depolarized by CO2 in iL3s and iL3as. In addition, we demonstrate that the receptor guanylate cyclase Ss-GCY-9 is expressed specifically in CO2-sensing neurons and is required for CO2-evoked behavior. Ss-GCY-9 also promotes activation, indicating that a single receptor can mediate both behavioral and physiological responses to CO2. Our results illuminate chemosensory mechanisms that shape the interaction between parasitic nematodes and their human hosts and may aid in the design of novel anthelmintics that target the CO2-sensing pathway.

Metal oxide-based gas sensor array for VOCs determination in complex mixtures using machine learning

Detection of volatile organic compounds (VOCs) from the breath is becoming a viable route for the early detection of diseases non-invasively. This paper presents a sensor array of 3 component metal oxides that give maximal cross-sensitivity and can successfully use machine learning methods to identify four distinct VOCs in a mixture. The metal oxide sensor array comprises NiO-Au (ohmic), CuO-Au (Schottky), and ZnO-Au (Schottky) sensors made by the DC reactive sputtering method and having a film thickness of 80-100 nm. The NiO and CuO films have ultrafine particle sizes of < 50 nm and rough surface texture, while ZnO films consist of nanoscale platelets. This array was subjected to various VOC concentrations, including ethanol, acetone, toluene, and chloroform, one by one and in a pair/mix of gases. Thus, the response values show severe interference and departure from commonly observed power law behavior. The dataset obtained from individual gases and their mixtures were analyzed using multiple machine learning algorithms, such as Random Forest (RF), K-Nearest Neighbor (KNN), Decision Tree, Linear Regression, Logistic Regression, Naive Bayes, Linear Discriminant Analysis, Artificial Neural Network, and Support Vector Machine. KNN and RF have shown more than 99% accuracy in classifying different varying chemicals in the gas mixtures. In regression analysis, KNN has delivered the best results with an R2 value of more than 0.99 and LOD of 0.012 ppm, 0.015 ppm, 0.014 ppm, and 0.025 ppm for predicting the concentrations of acetone, toluene, ethanol, and chloroform, respectively, in complex mixtures. Therefore, it is demonstrated that the array utilizing the provided algorithms can classify and predict the concentrations of the four gases simultaneously for disease diagnosis and treatment monitoring.

Comb spectroscopy of CO2 produced from microbial metabolism

We have developed a direct frequency comb spectroscopy instrument, which we have tested on Saccharomyces cerevisiae (baker's yeast) by measuring its CO2 output and production rate as we varied the environmental conditions, including the amount and type of feed sugar, the temperature, and the amount of yeast. By feeding isotopically-enhanced sugar to the yeast, we demonstrate the capability of our device to differentiate between two isotopologues of CO2, with a concentration measurement precision of 260 ppm for 12C16O2 and 175 ppm for 13C16O2. We also demonstrate the ability of our spectrometer to measure the proportion of carbon in the feed sugar converted to CO2, and estimate the amount incorporated into the yeast biomass.

Mixed Potential Type Acetone Sensor with Ultralow Detection Limit for Diabetic Ketosis Breath Analysis

Breath analysis using gas sensors is an emerging method for disease screening and diagnosis. Since it is closely related to the lipid metabolism and blood ketone concentration of the body, the detection of acetone content in exhaled breath is helpful for the screening and monitoring of diabetes and ketosis. The development of an acetone sensor with high selectivity, stability, and low detection limit has been the research focus for this purpose. Here, we developed a mixed potential type acetone sensor based on Gd2Zr2O7 solid electrolyte and CoSb2O6 sensing electrode. The developed sensor exhibits an extremely low detection limit of 10 ppb, enabling linear detection for acetone in an extremely wide range of 10 ppb-100 ppm. The good results of systematic evaluation on selectivity, repeatability, and stability prove the superior reliability of the sensor, which is a prerequisite for the application in actual breath detection. The ability of the sensor to distinguish healthy people from diabetic ketosis patients was confirmed by using the sensor to detect the breath of healthy people and diabetic patients, proving the feasibility of the sensor in the diagnosis and monitoring of diabetic ketosis.

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.

Non-invasive detection of renal disease biomarkers through breath analysis

Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry (MS), gas chromatography (GC), and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.

Unlocking Diabetic Acetone Vapor Detection by A Portable Metal-Organic Framework-Based Turn-On Optical Sensor Device

Despite exhaled human breath having enabled noninvasive diabetes diagnosis, selective acetone vapor detection by fluorescence approach in the diabetic range (1.8-3.5 ppm) remains a long-standing challenge. A set of water-resistant luminescent metal-organic framework (MOF)-based composites have been reported for detecting acetone vapor in the diabetic range with a limit of detection of 200 ppb. The luminescent materials possess the ability to selectively detect acetone vapor from a mixture comprising nitrogen, oxygen, carbon dioxide, water vapor, and alcohol vapor, which are prevalent in exhaled breath. It is noteworthy that this is the first luminescent MOF material capable of selectively detecting acetone vapor in the diabetic range via a turn-on mechanism. The material can be reused within a matter of minutes under ambient conditions. Industrially pertinent electrospun luminescent fibers are likewise fabricated alongside various luminescent films for selective detection of ultratrace quantities of acetone vapor present in the air. Ab initio theoretical calculations combined with in situ synchrotron-based dosing studies uncovered the material's remarkable hypersensitivity toward acetone vapor. Finally, a freshly designed prototype fluorescence-based portable optical sensor is utilized as a proof-of-concept for the rapid detection of acetone vapor within the diabetic range.

Toward the development of sensors for lung cancer: The adsorption of 1-propanol on hydrophobic zeolites

A healthy breath is mainly composed of water, carbon dioxide, molecular nitrogen, and oxygen and it contains many species, in small quantities, which are related to the ambient atmosphere and the metabolism. The breath of a person affected by lung cancer presents a concentration of 1-propanol higher than usual. In this context, the development of specific sensors to detect 1-propanol from breath is of high interest. The amount of propanol usually detected on the breath is of few ppb; this small quantity is a handicap for a reliable diagnostic. This limitation can be overcome if the sensor is equipped with a pre-concentrator. Our studies aim to provide an efficient material playing this role. This will contribute to the development of reliable and easy to use lung cancer detectors. For this, we investigate the properties of a few hydrophobic porous materials (chabazite, silicalite-1, and dealuminated faujasite). Hydrophobic structures are used to avoid saturation of materials by the water present in the exhaled breath. Our experimental and simulation results suggest that silicalite -1 (MFI) is the most suitable structure to be used as a pre-concentrator.

Diabetes noninvasive diagnostics and monitoring through volatile biomarkers analysis in the exhaled breath using optical absorption spectroscopy

The review is aimed on the analysis the abilities of noninvasive diagnostics and monitoring of diabetes mellitus (DM) and DM-associated complications through volatile molecular biomarkers detection in the exhaled breath. The specific biochemical reactions in the body of DM patients and their associations with volatile molecular biomarkers in the breath are considered. The applications of optical spectroscopy methods, including UV, IR, and terahertz spectroscopy for DM-associated volatile molecular biomarkers measurements, are described. The applications of similar technique combined with machine learning methods in DM diagnostics using the profile of DM-associated volatile molecular biomarkers in exhaled air or "pattern-recognition" approach are discussed.

A feasibility study on exhaled breath analysis using UV spectroscopy to detect COVID-19

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Sensors Based on Tin and Indium Oxides for the Determination of Acetone in Human Breath

The properties of planar sensors based on tin dioxide and indium oxide used for the determination of acetone vapors have been studied. Sensors based on synthesized SnO2 and In2O3 nanopowders showed high sensitivity to low concentrations of acetone in a humid environment which simulates human exhalation. The addition of a small amount of AuIII ions to hydroxide sols significantly increases the threshold sensitivity and the sensor response in a wide range of acetone concentrations. In2O3-Au sensors have the maximum sensitivity at an operating temperature of 325 °C. The In2O3-Au-sensors reliably record the change in acetone concentration in the concentration range from a minimum of 0.1 to 5 ppm with high accuracy, which is necessary for rapid diagnostics of the condition of patients with diabetes (1.8-5.0 ppm). The high sensitivity of the obtained sensors is explained by the structural features and the surface conditions of oxides and gold nanoparticles, which depend on the sample synthesis conditions.

Intrinsic and extrinsic factors affecting axillary odor variation. A comprehensive review

Humans produce odorous secretions from multiple body sites according to the microbiomic profile of each area and the types of secretory glands present. Because the axilla is an active, odor-producing region that mediates social communication via the sense of smell, this article focuses on the biological mechanisms underlying the creation of axillary odor, as well as the intrinsic and extrinsic factors likely to impact the odor and determine individual differences. The list of intrinsic factors discussed includes sex, age, ethnicity, emotions, and personality, and extrinsic factors include dietary choices, diseases, climate, and hygienic habits. In addition, we also draw attention to gaps in our understanding of each factor, including, for example, topical areas such as the effect of climate on body odor variation. Fundamental challenges and emerging research opportunities are further outlined in the discussion. Finally, we suggest guidelines and best practices based on the factors reviewed herein for preparatory protocols of sweat collection, data analysis, and interpretation.

Suitability of Short- and Long-Term Storage of Volatile Organic Compounds Samples in Syringe-Based Containers: A Comparison Study

The employment of advanced analytical techniques and instrumentation enables the tracing of volatile organic compounds (VOCs) in vestigial concentrations (ppbv-pptv range) for several emerging applications, such as the research of disease biomarkers in exhaled air, the detection of metabolites in several biological processes, and the detection of pollutants for air quality control. In this scope, the storage of gaseous samples is crucial for preserving the integrity and stability of the collected set of analytes. This study aims to assess the suitability of three commercially available syringes as air containers (AC) that are commonly used for the collection, storage, isolation, and transportation of samples: glass syringes with glass plungers (AC1), and two plastic syringes, one with plastic plungers (AC2), and one with rubbered plungers (AC3). For this purpose, 99 air samples with different times of storage (from 10 min to 24 h) were analyzed using a Gas Chromatography-Ion Mobility Spectrometry device and the degradation of the samples was properly assessed by comparing the changes in the VOCs' emission profiles. The quality of the method was assured by via the measurement of the blank's spectra before each experimental run, as well as by the consecutive measurement of the three replicates for each sample. A statistical analysis of the changes in the VOCs' emission patterns was performed using principal component analysis (PCA). The results, with a total explained variance of 93.61%, indicate that AC3 is the most suitable option for the long-term storage of air samples. Thus, AC3 containers demonstrated a higher capacity to preserve the stability and integrity of the analytes compared to AC1 and AC2. The findings of the short-term effects analysis, up to 1 h, confirm the suitability of all analyzed syringe-based containers for sample-transferring purposes in onsite analysis.

Volatile Organic Compound Identification-Based Tuberculosis Screening among TB Suspects: A Diagnostic Accuracy Study

Tuberculosis (TB) affects a third of the global population, and a large population of infected individuals still remain undiagnosed-making the visible burden only the tip of the iceberg. The detection of tuberculosis in close-proximity patients is one of the key priorities for attaining the Sustainable Development Goals (SDG) of TB elimination by 2030. With the current battery of screening tests failing to cover this need, the authors of this paper examined a simple and inexpensive point-of-care breath analyzer (TSI-3000(I)), which is based on detecting the volatile organic compounds that are emitted from infected cells and released in exhaled breath as a screening tool for the detection of TB. A single-center pilot study for assessing the diagnostic accuracy of the point-of-care Tuberculosis Breath Analyzer was conducted, and it was compared against the WHO-recommended TrueNat assay, which is a rapid molecular test and was also treated as the reference standard in this study. Of the 334 enrolled participants with TB signs/symptoms, 42.51% were TrueNat positive for Mycobacterium tuberculosis. The sensitivity of the Tuberculosis Breath Analyzer was found to be 95.7%, with a specificity of 91.3% and a ROC area of 0.935. The test kit showed considerable/significant high sensitivity and specificity as reliability indicators. The performance of the Tuberculosis Breath Analyzer tested was found to be comparable in efficiency to that of the TrueNat assay. A large cohort-based multicentric study is feasibly required to further validate and extrapolate the results of the pilot study.

Assessment of an exhaled breath test using ultraviolet photoionization time-of-flight mass spectrometry for the monitoring of kidney transplant recipients

Continuous monitoring for immunosuppressive status, infection and complications are a must for kidney transplantation (KTx) recipients. Traditional monitoring including blood sampling and kidney biopsy, which caused tremendous medical cost and trauma. Therefore, a cheaper and less invasive approach was urgently needed. We thought that a breath test has the potential to become a feasible tool for KTx monitoring. A prospective-specimen collection, retrospective-blinded assessment strategy was used in this study. Exhaled breath samples from 175 KTx recipients were collected in West China Hospital and tested by online ultraviolet photoionization time-of-flight mass spectrometry (UVP-TOF-MS). The classification models based on breath test performed well in classifying normal and abnormal values of creatinine, estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN) and tacrolimus, with AUC values of 0.889, 0.850, 0.849 and 0.889, respectively. Regression analysis also demonstrated the predictive ability of breath test for clinical creatinine, eGFR, BUN, tacrolimus level, as the predicted values obtained from the regression model correlated well with the clinical true values (p < 0.05). The findings of this investigation implied that a breath test by using UVP-TOF-MS for KTx recipient monitoring is possible and accurate, which might be useful for future clinical screenings.

Development of an analytical chip for colorimetric detection of medium-chain aldehydes by reaction with pararosaniline in porous glass

Medium-chain aldehydes are common human biogases that can be detected in the breath of patients with lung diseases. As such, the measurement of medium-chain aldehyde gases in human breath can provide significant, noninvasive, and diagnostic information related to the potential presence of such diseases. In this study, an analytical chip is developed for the detection of medium-chain aldehydes without interference from short-chain aldehydes. This analytical chip is composed of porous glass impregnated with pararosaniline and an acid (i.e., acetic acid with small amount of phosphoric acid). After exposure to medium-chain aldehydes, the red analytical chip became violet in color, and an absorption peak was observed at 620 nm. It was found that a non-reversible reaction occurred in the porous glass, therefore, the analytical chip functions in a cumulative manner. A linear relationship was determined between the absorbance change of the analytical chip at 620 nm and the nonanal exposure concentration. Importantly, the developed analytical chip successfully detected nonanal at concentrations of 8-270 ppb as calculated from the absorbance change at 620 nm after a 24 h exposure time. In addition, nonanal concentration was estimated using the change in the R value of the analytical chip photograph. This method is suitable for point-of-care breath analysis. Finally, the analytical chip was also found to be active toward octanal and decanal with a relative sensitivity of 0.7 compared to that of nonanal; it was not active toward short-chain aldehydes.

Smelling the Disease: Diagnostic Potential of Breath Analysis

Breath analysis is a relatively recent field of research with much promise in scientific and clinical studies. Breath contains endogenously produced volatile organic components (VOCs) resulting from metabolites of ingested precursors, gut and air-passage bacteria, environmental contacts, etc. Numerous recent studies have suggested changes in breath composition during the course of many diseases, and breath analysis may lead to the diagnosis of such diseases. Therefore, it is important to identify the disease-specific variations in the concentration of breath to diagnose the diseases. In this review, we explore methods that are used to detect VOCs in laboratory settings, VOC constituents in exhaled air and other body fluids (e.g., sweat, saliva, skin, urine, blood, fecal matter, vaginal secretions, etc.), VOC identification in various diseases, and recently developed electronic (E)-nose-based sensors to detect VOCs. Identifying such VOCs and applying them as disease-specific biomarkers to obtain accurate, reproducible, and fast disease diagnosis could serve as an alternative to traditional invasive diagnosis methods. However, the success of VOC-based identification of diseases is limited to laboratory settings. Large-scale clinical data are warranted for establishing the robustness of disease diagnosis. Also, to identify specific VOCs associated with illness states, extensive clinical trials must be performed using both analytical instruments and electronic noses equipped with stable and precise sensors.

Regulating the Electron Depletion Layer of Au/V2O5/Ag Thin Film Sensor for Breath Acetone as Potential Volatile Biomarker

Human exhaled breath has been utilized to identify biomarkers for diseases such as diabetes and cancer. The existence of these illnesses is indicated by a rise in the level of acetone in the breath. The development of sensing devices capable of identifying the onset of lung cancer or diabetes is critical for the successful monitoring and treatment of these diseases. The goal of this research is to prepare a novel breath acetone sensor made of Ag NPs/V₂O₅ thin film/Au NPs by combining DC/RF sputtering and post-annealing as synthesis methods. The produced material was characterized using X-ray diffraction (XRD), UV-Vis, Raman, and atomic force microscopy (AFM). The results revealed that the sensitivity to 50 ppm acetone of the Ag NPs/V₂O₅ thin film/Au NPs sensor was 96%, which is nearly twice and four times greater than the sensitivity of Ag NPs/V₂O₅ and pristine V₂O₅, respectively. This increase in sensitivity can be attributed to the engineering of the depletion layer of V₂O₅ through the double activation of the V₂O₅ thin films with uniform distribution of Au and Ag NPs that have different work function values.

GC-MS analysis of exhaled gas for fine detection of inflammatory diseases

Exhaled gas analysis is a non-invasive test ideal for continuous monitoring of biological metabolic information. We analyzed the exhaled gas of patients with inflammatory diseases for trace gas components that could serve as biomarkers that enable early detection of inflammatory diseases and assessment of treatment efficacy. Furthermore, we examined the clinical potential of this method. We enrolled 34 patients with inflammatory disease and 69 healthy participants. Volatile components from exhaled gas were collected and analyzed by a gas chromatography-mass spectrometry system, and the data were examined for gender, age, inflammatory markers, and changes in markers before and after treatment. The data were tested for statistical significance through discriminant analysis by Volcano plot, Analysis of variance test, principal component analysis, and cluster analysis comparing healthy and patient groups. There were no significant differences in the trace components of exhaled gas by gender or age. However, we found differences in some components of the exhaled gas between healthy and untreated patients. In addition, after treatment, gas patterns including the patient-specific components changed to a state closer to the inflammation-free status. We identified trace components in the exhaled gas of patients with inflammatory diseases and found that some of these regressed after treatment.

Nonanal Gas Sensors Using Porous Glass as a Reaction Field for Ammonia-Catalyzed Aldol Condensation

Transmittance in porous-glass gas sensors, which use aldol condensation of vanillin and nonanal as the detection mechanism for nonanal, decreases because of the production of carbonates by the sodium hydroxide catalyst. In this study, the reasons for the decrease in transmittance and the measures to overcome this issue were investigated. Alkali-resistant porous glass with nanoscale porosity and light transparency was employed as a reaction field in a nonanal gas sensor using ammonia-catalyzed aldol condensation. In this sensor, the gas detection mechanism involves measuring the changes in light absorption of vanillin arising from aldol condensation with nonanal. Furthermore, the problem of carbonate precipitation was solved with the use of ammonia as the catalyst, which effectively resolves the issue of reduced transmittance that occurs when a strong base, such as sodium hydroxide, is used as a catalyst. Additionally, the alkali-resistant glass exhibited solid acidity because of the incorporated SiO₂ and ZrO₂ additives, which supported approximately 50 times more ammonia on the glass surface for a longer duration than a conventional sensor. Moreover, the detection limit obtained from multiple measurements was approximately 0.66 ppm. In summary, the developed sensor exhibits a high sensitivity to minute changes in the absorbance spectrum because of the reduction in the baseline noise of the matrix transmittance.

Potential Role of Oxidative Stress in the Production of Volatile Organic Compounds in Obesity

Obesity is associated with numerous health issues such as sleep disorders, asthma, hepatic dysfunction, cancer, renal dysfunction, diabetes, cardiovascular complications, and infertility. Previous research has shown that the distribution of excess body fat, rather than excess body weight, determines obesity-related risk factors. It is widely accepted that abdominal fat is a serious risk factor for illnesses associated with obesity and the accumulation of visceral fat promotes the release of pro-oxidants, pro-inflammatory, and reactive oxygen species (ROS). The metabolic process in the human body produces several volatile organic compounds (VOCs) via urine, saliva, breath, blood, skin secretions, milk, and feces. Several studies have shown that VOCs are released by the interaction of ROS with underlying cellular components leading to increased protein oxidation, lipid peroxidation, or DNA damage. These VOCs released via oxidative stress in obese individuals may serves as a biomarker for obesity-related metabolic alterations and disease. In this review, we focus on the relationship between oxidative stress and VOCs in obesity.

Common Strategies and Factors Affecting Off-Line Breath Sampling and Volatile Organic Compounds Analysis Using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS)

An analysis of exhaled breath enables specialists to noninvasively monitor biochemical processes and to determine any pathological state in the human body. Breath analysis holds the greatest potential to remold and personalize diagnostics; however, it requires a multidisciplinary approach and collaboration of many specialists. Despite the fact that breath is considered to be a less complex matrix than blood, it is not commonly used as a diagnostic and prognostic tool for early detection of disordered conditions due to its problematic sampling, analysis, and storage. This review is intended to determine, standardize, and marshal experimental strategies for successful, reliable, and especially, reproducible breath analysis.

Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year

BACKGROUND

Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found.

METHODS

As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year.

RESULTS

We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites.

CONCLUSIONS

This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.

A handheld electronic device with the potential to detect lung cancer biomarkers from exhaled breath

Lung cancer is the leading cause of cancer death in the United States. It has the lowest 5-year survival rate among the most common cancers and therefore, early diagnosis is critical to improve the survival rate. In this paper, a new handheld electronic device is proposed to detect nine lung cancer biomarkers in the exhaled breath. An electrochemical gas sensor was produced through deposition of a thin layer of graphene and Prussian blue on a chromium-modified silicon substrate. Selective binding of the analyte was formed by molecular imprinting polymer (MIP). Subsequent polymerization and removal of the analyte yielded a layer of a conductive polymer on top of the sensor containing molecularly imprinted cavities selective for the target molecule. The sensors were tested over 1-20 parts per trillion (ppt) level of concentration while the sensor resistance has been monitored as the sensors react to the analyte by resistance change. Pentane sensor was also tested for selectivity. A printed circuit board was designed to measure the resistance of each sensor and send the data to a developed application in smartphone through Bluetooth. This handheld device has the potential to be used as a diagnostic method in the near future.

Structure Effect on the Response of ZnGa2O4 Gas Sensor for Nitric Oxide Applications

We fabricated a gas sensor with a wide-bandgap ZnGa₂O₄ (ZGO) epilayer grown on a sapphire substrate by metalorganic chemical vapor deposition. The ZGO presented (111), (222) and (333) phases demonstrated by an X-ray diffraction system. The related material characteristics were also measured by scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. This ZGO gas sensor was used to detect nitric oxide (NO) in the parts-per-billion range. In this study, the structure effect on the response of the NO gas sensor was studied by altering the sensor dimensions. Two approaches were adopted to prove the dimension effect on the sensing mechanism. In the first approach, the sensing area of the sensors was kept constant while both channel length (L) and width (W) were varied with designed dimensions (L × W) of 60 × 200, 80 × 150, and 120 ×100 μm². In the second, the dimensions of the sensing area were altered (60, 40, and 20 μm) with W kept constant. The performance of the sensors was studied with varying gas concentrations in the range of 500 ppb~10 ppm. The sensor with dimensions of 20 × 200 μm² exhibited a high response of 11.647 in 10 ppm, and 1.05 in 10 ppb for NO gas. The sensor with a longer width and shorter channel length exhibited the best response. The sensing mechanism was provided to explain the above phenomena. Furthermore, the reaction between NO and the sensor surface was simulated by O exposure of the ZGO surface in air and calculated by first principles.

Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

Emerging Development of Auto-Charging Sensors for Respiration Monitoring

In recent years, the development of biomedical monitoring systems, including respiration monitoring systems, has been accelerated. Wearable and implantable medical devices are becoming increasingly important in the diagnosis and management of disease and illness. Respiration can be monitored using a variety of biosensors and systems. Auto-charged sensors have a number of advantages, including low cost, ease of preparation, design flexibility, and a wide range of applications. It is possible to use the auto-charged sensors to directly convert mechanical energy from the airflow into electricity. The ability to monitor and diagnose one's own health is a major goal of auto-charged sensors and systems. Respiratory disease model output signals have not been thoroughly investigated and clearly understood. As a result, figuring out their exact interrelationship is a difficult and important research question. This review summarized recent developments in auto-charged respiratory sensors and systems in terms of their device principle, output property, detecting index, and so on. Researchers with an interest in auto-charged sensors can use the information presented here to better understand the difficulties and opportunities that lie ahead.

Prospects and Challenges of AI and Neural Network Algorithms in MEMS Microcantilever Biosensors

This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System) biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into our daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a number of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. As a result, this paper examines the fundamentals of the neural algorithm and goes into great detail on the fundamentals and uses of the principal component analysis approach. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Our investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors. Focusing on AI and neural networks, this paper introduces Micro-Electro-Mechanical System biosensors using artificial intelligence, which greatly promotes the development of next-generation intelligent sensing systems, and the potential applications and prospects of neural networks in the field of microcantilever biosensors.

A Family of 2D-MXenes: Synthesis, Properties, and Gas Sensing Applications

Gas sensors, capable of detecting and monitoring trace amounts of gas molecules or volatile organic compounds (VOCs), are in great demand for numerous applications including diagnosing diseases through breath analysis, environmental and personal safety, food and agriculture, and other fields. The continuous emergence of new materials is one of the driving forces for the development of gas sensors. Recently, 2D materials have been gaining huge attention for gas sensing applications, owing to their superior electrical, optical, and mechanical characteristics. Especially for 2D MXenes, high specific area and their rich surface functionalities with tunable electronic structure make them compelling for sensing applications. This Review discusses the latest advancements in the 2D MXenes for gas sensing applications. It starts by briefly explaining the family of MXenes, their synthesis methods, and delamination procedures. Subsequently, it outlines the properties of MXenes. Then it describes the theoretical and experimental aspects of the MXenes-based gas sensors. Discussion is also extended to the relation between sensing performance and the structure, electronic properties, and surface chemistry. Moreover, it highlights the promising potential of these materials in the current gas sensing applications and finally it concludes with the limitations, challenges, and future prospects of 2D MXenes in gas sensing applications.

Quantitative Analysis of Exhaled Breath Collected on Filter Substrates via Low-Temperature Plasma Desorption/Ionization Mass Spectrometry

Breath analysis has attracted increasing attention in recent years due to its great potential for disease diagnostics at early stages and for clinical drug monitoring. There are several recent examples of successful development of real-time, in vivo quantitative analysis of exhaled breath metabolites via mass spectrometry. On the other hand, current mass spectrometer accessibility limitations restrict point-of-care applications. Here now, an offline method is developed for quantitative analysis of exhaled breath collected on inexpensive filter substrates for direct desorption and ionization by using low-temperature plasma-mass spectrometry (LTP-MS). In particular, different operating conditions of the ionization source were systematically studied to optimize desorption/ionization by using glycerol, a low volatility compound. Applications with respect to propofol, γ-valprolactone, and nicotine analysis in exhaled breath are demonstrated in this study. The effects of several filter substrate properties, including filter material and pore size, on the analyte signal were characterized. Cellulose filter papers performed best with the present analytes. In addition, filters with smaller pores enabled a more efficient sample collection. Furthermore, sample-collection flow rate was determined to have a very significant effect, with slower flow rates yielding the best results. It was also found that filters loaded with sample can be successfully stored in glass vials with no observable sample loss even after 3 days. Limits of detection under optimized conditions are shown to be competitive or significantly better compared with relevant techniques and with additional benefits of cost-efficiency and sample storage capabilities.

Study on Ammonia Content and Distribution in the Microenvironment Based on Covalent Organic Framework Nanochannels

A crack-free micrometer-sized compact structure of 1,3,5-tris(4-aminophenyl)benzene-terephthaldehyde-covalent organic frameworks (TAPB-PDA-COFs) was constructed in situ at the tip of a theta micropipette (TMP). The COF-covered theta micropipette (CTP) then created a stable liquid-gas interface inside COF nanochannels, which was utilized to electrochemically analyze the content and distribution of ammonia gas in the microenvironments. The TMP-based electrochemical ammonia sensor (TEAS) shows a high sensing response, with current increasing linearly from 0 to 50,000 ppm ammonia, owing to the absorption of ammonia gas in the solvent meniscus that connects both barrels of the TEAS. The TEAS also exhibits a short response and recovery time of 5 ± 2 s and 6 ± 2 s, respectively. This response of the ammonia sensor is remarkably stable and repeatable, with a relative standard deviation of 6% for 500 ppm ammonia gas dispensing with humidity control. Due to its fast, reproducible, and stable response to ammonia gas, the TEAS was also utilized as a scanning electrochemical microscopy (SECM) probe for imaging the distribution of ammonia gas in a microspace. This study unlocks new possibilities for using a TMP in designing microscale probes for gas sensing and imaging.

Metabolites From Trypanosome-Infected Cattle as Sensitive Biomarkers for Animal Trypanosomosis

Trypanosomes are important global livestock and human pathogens of public health importance. Elucidating the chemical mechanisms of trypanosome-relevant host interactions can enhance the design and development of a novel, next-generation trypanosomosis diagnostics. However, it is unknown how trypanosome infection affects livestock volatile odors. Here, we show that Trypanosoma congolense and Trypanosoma vivax infections induced dihydro-β- ionone and junenol, while abundance of dihydro-α-ionone, phenolics, p-cresol, and 3-propylphenol significantly elevated in cow urine. These biomarkers of trypanosome infection are conserved in cow breath and the urine metabolites of naturally infected cows, regardless of population, diet, or environment differences. Furthermore, treating trypanosome-infected cows reduced the levels of these indicators back to the pre-infection levels. Finally, we demonstrated that the potential of some specific biomarkers of phenolic origin may be used to detect active trypanosome infections, including low-level infections that are not detectable by microscopy. The sensitivity and specificity of biomarkers detection are suited for rapid, robust, and non-invasive trypanosomosis diagnosis under field conditions.

Heterostructures Based on Cobalt Phthalocyanine Films Decorated with Gold Nanoparticles for the Detection of Low Concentrations of Ammonia and Nitric Oxide

This work is aimed at the development of new heterostructures based on cobalt phthalocyanines (CoPc) and gold nanoparticles (AuNPs), and the evaluation of the prospects of their use to determine low concentrations of ammonia and nitric oxide. For this purpose, CoPc films were decorated with AuNPs by gas-phase methods (MOCVD and PVD) and drop-casting (DC), and their chemiresistive sensor response to low concentrations of NO (10–50 ppb) and NH₃ (1–10 ppm) was investigated. A comparative analysis of the characteristics of heterostructures depending on the preparation methods was carried out. The composition, structure, and morphology of the resulting hybrid films were studied by X-ray photoelectron spectroscopy (XPS) and inductively coupled plasma atomic emission (ICP-AES) spectroscopy, as well as electron microscopy methods to discuss the effect of these parameters on the sensor response of hybrid films to ammonia and nitric oxide. It was shown that regardless of the fabrication method, the response of Au/CoPc heterostructures to NH₃ and NO gases increased with an increase in the concentration of gold. The sensor response of Au/CoPc heterostructures to NH₃ increased 2–3.3 times compared to CoPc film, whereas in the case of NO it increased up to 16 times. The detection limits of the Au/CoPc heterostructure with a gold content of ca. 2.1 µg/cm² for NH₃ and NO were 0.1 ppm and 4 ppb, respectively. It was shown that Au/CoPc heterostructures can be used for the detection of NH₃ in a gas mixture simulating exhaled air (N₂—74%, O₂—16%, H₂O—6%, CO₂—4%).

Utility of SIFT-MS to evaluate volatile organic compounds in nephropathic patients' breath

Several studies highlighted a correlation between exhaled air volatile organic compounds (VOCs) and some pathological conditions, such as chronic kidney disease (CKD), chronic liver disease, etc. In fact, in literature has been reported that CKD is characterized by an increased concentration of ammonia, trimethylamine (TMA) and isoprene compared to healthy subjects. Currently, there is not a validate and standardized method to detect VOCs. For this purpose, we examined the utility of selected ion flow tube-mass spectrometry (SIFT-MS) to measure VOCs in CKD patients and we evaluated the possible correlation between VOCs and the presence of CKD and its stage. We enrolled 68 CKD patients under conservative therapy and 54 healthy subjects. The analysis of the VOCs of the exhaled air of the enrolled subjects was performed by SIFT-MS. Among all the VOCs analyzed, the most relevant results by ROC curves were observed for TMA, acetone, ammonia and dimethyl sulfide. We found that a breath TMA concentration superior to 26 ppbv characterizes a 6.11 times greater risk of CKD, compared to subjects with lower levels. Moreover, we detected an increased concentration of acetone and ammonia in CKD patients compared to healthy subjects. We highlight the potential utility of SIFT-MS in CKD clinical management.

Clinical trial registry: R.S. 15.19 of 6 February 2019.

Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year

BACKGROUND

Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found.

METHODS

As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year.

RESULTS

We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites.

CONCLUSIONS

This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.

Predictive performance of selected breath volatile organic carbon compounds in stage 1 lung cancer

Background

Lung cancer remains the leading cause of cancer deaths accounting for almost 25% of all cancer deaths. Breath-based volatile organic compounds (VOCs) have been studied in lung cancer but previous studies have numerous limitations. We conducted a prospective matched case to control study of the ability of preidentified VOC performance in the diagnosis of stage 1 lung cancer (S1LC).

Methods

Study participants were enrolled in a matched case to two controls study. A case was defined as a patient with biopsy-confirmed S1LC. Controls included a matched control, by risk factors, and a housemate control who resided in the same residence as the case. We included 88 cases, 88 risk-matched, and 49 housemate controls. Each participant exhaled into a Tedlar^® bag which was analyzed using gas chromatography-mass spectrometry. For each study participant’s breath sample, the concentration of thirteen previously identified VOCs were quantified and assessed using area under the curve in the detection of lung cancer.

Results

Four VOCs were above the limit of detection in more than 10% of the samples. Acetoin was the only compound that was significantly associated with S1LC. Acetoin concentration below the 10^th percentile (0.026 µg/L) in the training data had accuracy of 0.610 (sensitivity =0.649; specificity =0.583) in the test data. In multivariate logistic models, the best performing models included Acetoin alone (AUC =0.650).

Conclusions

Concentration of Acetoin in exhaled breath has low discrimination performance for S1LC cases and controls, while there was not enough evidence for twelve additional published VOCs.

A compact gas chromatography platform for detection of multicomponent volatile organic compounds biomarkers

Some human exhaled volatile organic compounds (VOCs) can be employed to diagnose related human endogenous diseases as characteristic biomarkers, which is expected to be applied to rapid screening and grading because of their non-invasive and cost-effective advantages. In this study, we developed a compact gas chromatography (GC) platform mainly composed of an integrated silicon-based micro-column chip using micro-electromechanical system techniques and a miniaturized metal oxide semiconductor gas detector. In addition, the sampling/switching valve with related components and embedded microcontrollers was used for airflow control. The fabricated system selectively detected the five VOCs (pentane, acetone, toluene, octane, and decane) considered the typical endogenous disease biomarkers. In the experiments, the functional parameters of the system were investigated, and the optimum temperature conditions of the system for separation were determined. The results show that the system can successfully test the studied five VOCs as low as 1 ppm. In addition, the influence of interfering gas (carbon dioxide and ammonia) on the system for the VOC mixture is also investigated. Moreover, to prove the possibility of breath analysis of the fabricated system, the detection performance of isoprene and acetone at the ppb level is studied. Then, the concentration changes of the isoprene at the ppb concentration for human breath are successfully detected in the system. Therefore, we believe that the prepared compact GC system has potential applications in the human endogenous disease diagnosis for the VOC biomarkers.

Advanced wearable biosensors for the detection of body fluids and exhaled breath by graphene

Given the huge economic burden caused by chronic and acute diseases on human beings, it is an urgent requirement of a cost-effective diagnosis and monitoring process to treat and cure the disease in their preliminary stage to avoid severe complications. Wearable biosensors have been developed by using numerous materials for non-invasive, wireless, and consistent human health monitoring. Graphene, a 2D nanomaterial, has received considerable attention for the development of wearable biosensors due to its outstanding physical, chemical, and structural properties. Moreover, the extremely flexible, foldable, and biocompatible nature of graphene provide a wide scope for developing wearable biosensor devices. Therefore, graphene and its derivatives could be trending materials to fabricate wearable biosensor devices for remote human health management in the near future. Various biofluids and exhaled breath contain many relevant biomarkers which can be exploited by wearable biosensors non-invasively to identify diseases. In this article, we have discussed various methodologies and strategies for synthesizing and pattering graphene. Furthermore, general sensing mechanism of biosensors, and graphene-based biosensing devices for tear, sweat, interstitial fluid (ISF), saliva, and exhaled breath have also been explored and discussed thoroughly. Finally, current challenges and future prospective of graphene-based wearable biosensors have been evaluated with conclusion. Graphene is a promising 2D material for the development of wearable sensors. Various biofluids (sweat, tears, saliva and ISF) and exhaled breath contains many relevant biomarkers which facilitate in identify diseases. Biosensor is made up of biological recognition element such as enzyme, antibody, nucleic acid, hormone, organelle, or complete cell and physical (transducer, amplifier), provide fast response without causing organ harm.

Eco-Friendly Disposable WS2 Paper Sensor for Sub-ppm NO2 Detection at Room Temperature

We developed inexpensive and disposable gas sensors with a low environmental footprint. This approach is based on a biodegradable substrate, paper, and features safe and nontoxic electronic materials. We show that abrasion-induced deposited WS2 nanoplatelets on paper can be employed as a successful sensing layer to develop high-sensitivity and selective sensors, which operate even at room temperature. Its performance is investigated, at room temperature, against NO2 exposure, finding that the electrical resistance of the device drops dramatically upon NO2 adsorption, decreasing by ~42% (~31% half a year later) for 0.8 ppm concentration, and establishing a detection limit around~2 ppb (~3 ppb half a year later). The sensor is highly selective towards NO2 gas with respect to the interferents NH3 and CO, whose responses were only 1.8% (obtained for 30 ppm) and 1.5% (obtained for 8 ppm), respectively. Interestingly, an improved response of the developed sensor under humid conditions was observed (tested for 25% relative humidity at 23 °C). The high-performance, in conjunction with its small dimensions, low cost, operation at room temperature, and the possibility of using it as a portable system, makes this sensor a promising candidate for continuous monitoring of NO2 on-site.

Non-Invasive Monitoring of Inflammation in Inflammatory Bowel Disease Patients during Prolonged Exercise via Exhaled Breath Volatile Organic Compounds

The aim of this study was to investigate volatile organic compounds (VOCs) in exhaled breath as possible non-invasive markers to monitor the inflammatory response in inflammatory bowel disease (IBD) patients as a result of repeated and prolonged moderate-intensity exercise. We included 18 IBD patients and 19 non-IBD individuals who each completed a 30, 40, or 50 km walking exercise over three consecutive days. Breath and blood samples were taken before the start of the exercise event and every day post-exercise to assess changes in the VOC profiles and cytokine concentrations. Proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) was used to measure exhaled breath VOCs. Multivariate analysis, particularly ANOVA-simultaneous component analysis (ASCA), was employed to extract relevant ions related to exercise and IBD. Prolonged exercise induces a similar response in breath butanoic acid and plasma cytokines for participants with or without IBD. Butanoic acid showed a significant correlation with the cytokine IL-6, indicating that butanoic acid could be a potential non-invasive marker for exercise-induced inflammation. The findings are relevant in monitoring personalized IBD management.

Case Report: The effect of intravenous and oral antibiotics on the gut microbiome and breath volatile organic compounds over one year

BACKGROUND

Antimicrobial resistance (AMR) is a global concern and better understanding of the gut microbiome, a known 'amplifier' of AMR, may allow future clinicians to tailor therapy to minimise this risk and offer a personalised medicine approach. To examine the gut microbiome, patients are required to provide faecal samples; more convenient and cheaper solutions need to be found.

METHODS

As part of a pilot study looking at how routes of administration affect the gut microbiome in NHS patients undergoing routine clinical management for infections, we hypothesised that effects on the gut microbiome varied with the route and metabolism of antibiotic used, and these changes may be reflected in breath metabolites. We present a case report of a patient with an unusual clinical history, alongside breath metabolite and gut microbiome data taken before, during and after antibiotic therapy over a period of one year.

RESULTS

We noted a shift in the dominant Bacteroides strain in the patient's gut microbiome between pre- and post-therapy samples, along with an alteration in the composition of breath metabolites.

CONCLUSIONS

This study provides a framework for similar future work and highlights the need for further research on the relationships between changes in microbial gut communities and antimicrobial exposure, patient clinical status, and the metabolites of human breath.

Graphene-enabled wearable sensors for healthcare monitoring

Wearable sensors in healthcare monitoring have recently found widespread applications in biomedical fields for their non- or minimal-invasive, user-friendly and easy-accessible features. Sensing materials is one of the major challenges to achieve these superiorities of wearable sensors for healthcare monitoring, while graphene-based materials with many favorable properties have shown great efficiency in sensing various biochemical and biophysical signals. In this paper, we review state-of-the-art advances in the development and modification of graphene-based materials (i.e., graphene, graphene oxide and reduced graphene oxide) for fabricating advanced wearable sensors with 1D (fibers), 2D (films) and 3D (foams/aerogels/hydrogels) macroscopic structures. We summarize the structural design guidelines, sensing mechanisms, applications and evolution of the graphene-based materials as wearable sensors for healthcare monitoring of biophysical signals (e.g., mechanical, thermal and electrophysiological signals) and biochemical signals from various body fluids and exhaled gases. Finally, existing challenges and future prospects are presented in this area.

Effects of long-term vegan diet on breath composition

The composition of exhaled breath derives from an intricate combination of normal and abnormal physiological processes that are modified by the consumption of food and beverages, circadian rhythms, bacterial infections, and genetics as well as exposure to xenobiotics. This complexity, which results wide intra- and inter-individual variability and is further influenced by sampling conditions, hinders the identification of specific biomarkers and makes it difficult to differentiate between pathological and nominally healthy subjects. The identification of a "normal" breath composition and the relative influence of the aforementioned parameters would make breath analyses much faster for diagnostic applications. We thus compared, for the first time, the breath composition of age-matched volunteers following a vegan and a Mediterranean omnivorous diet in order to evaluate the impact of diet on breath composition. Mixed breath was collected from 38 nominally healthy volunteers who were asked to breathe into a two-liter handmade Nalophan bag. Exhalation flow rate and carbon dioxide values were monitored during breath sampling. An aliquot (100 mL) of breath was loaded into a sorbent tube (250 mg of Tenax GR, 60/80 mesh) before being analyzed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Breath profiling using TD-GC-MS analysis identified five compounds (methanol, 1-propanol, pentane, hexane, and hexanal), thus enabling differentiation between samples collected from the different group members . Principal component analysis showed a clear separation between groups, suggesting that breath analysis could be used to study the influence of dietary habits in the fields of nutrition and metabolism. Surprisingly, one Italian woman and her brother showed extremely low breath isoprene levels (about 5 ppbv), despite their normal lipidic profile and respiratory data, such as flow rate and pCO2. Further investigations to reveal the reasons behind low isoprene levels in breath would help reveal the origin of isoprene in breath.

Review of the algorithms used in exhaled breath analysis for the detection of diabetes

Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.