The clinical potential of exhaled breath analysis for diabetes mellitus

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

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

Chemical Analysis of Exhaled Vape Emissions: Unraveling the Complexities of Humectant Fragmentation in a Human Trial Study

Electronic cigarette smoking (or vaping) is on the rise, presenting questions about the effects of secondhand exposure. The chemical composition of vape emissions was examined in the exhaled breath of eight human volunteers with the high chemical specificity of complementary online and offline techniques. Our study is the first to take multiple exhaled puff measurements from human participants and compare volatile organic compound (VOC) concentrations between two commonly used methods, proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and gas chromatography (GC). Five flavor profile groups were selected for this study, but flavor compounds were not observed as the main contributors to the PTR-ToF-MS signal. Instead, the PTR-ToF-MS mass spectra were overwhelmed by e-liquid thermal decomposition and fragmentation products, which masked other observations regarding flavorings and other potentially toxic species associated with secondhand vape exposure. Compared to the PTR-ToF-MS, GC measurements reported significantly different VOC concentrations, usually below those from PTR-ToF-MS. Consequently, PTR-ToF-MS mass spectra should be interpreted with caution when reporting quantitative results in vaping studies, such as doses of inhaled VOCs. Nevertheless, the online PTR-ToF-MS analysis can provide valuable qualitative information by comparing relative VOCs in back-to-back trials. For example, by comparing the mass spectra of exhaled air with those of direct puffs, we can conclude that harmful VOCs present in the vape emissions are largely absorbed by the participants, including large fractions of nicotine.

Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis

Purpose

This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy.

Methods

Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS).

Results

SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis.

Conclusion

This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

Non-invasive blood glucose monitoring technology in diabetes management: review

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual's quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the development of non-invasive BG approaches. However, the current research progress is slow, and only a few BG self-monitoring devices have made considerable progress. Hence, we evaluate the available non-invasive glucose monitoring technologies validated against BG recordings to provide future research direction to design, develop, and deploy self-monitoring of BG with integrated emerging technologies. We searched five databases, Embase, MEDLINE, Proquest, Scopus, and Web of Science, to assess the non-invasive technology's scope in the diabetes management paradigm published from 2000 to 2020. A total of three approaches to non-invasive screening, including saliva, skin, and breath, were identified and discussed. We observed a statistical relationship between BG measurements obtained from non-invasive methods and standard clinical measures. Opportunities exist for future research to advance research progress and facilitate early technology adoption for healthcare practice. The results promise clinical validity; however, formulating regulatory guidelines could foresee the deployment of approved non-invasive BG monitoring technologies in healthcare practice. Further, research prospects are there to design, develop, and deploy integrated diabetes management systems with mobile technologies, data analytics, and the internet of things (IoT) to deliver a personalised monitoring system.

Acetone Detection and Classification as Biomarker of Diabetes Mellitus Using a Quartz Crystal Microbalance Gas Sensor Array

A gas sensor array was developed and evaluated using four high-frequency quartz crystal microbalance devices (with a 30 MHz resonant frequency in fundamental mode). The QCM devices were coated with ethyl cellulose (EC), polymethylmethacrylate (PMMA), Apiezon L (ApL), and Apiezon T (ApT) sensing films, and deposited by the ultrasonic atomization method. The objective of this research was to propose a non-invasive technique for acetone biomarker detection, which is associated with diabetes mellitus disease. The gas sensor array was exposed to methanol, ethanol, isopropanol, and acetone biomarkers in four different concentrations, corresponding to 1, 5, 10, and 15 µL, at temperature of 22 °C and relative humidity of 20%. These samples were used because human breath contains them and they are used for disease detection. Moreover, the gas sensor responses were analyzed using principal component analysis and discriminant analysis, achieving the classification of the acetone biomarker with a 100% membership percentage when its concentration varies from 327 to 4908 ppm, and its identification from methanol, ethanol, and isopropanol.

Low-Cost ZnO Spray-Coated Optical Fiber Sensor for Detecting VOC Biomarkers of Diabetes

A non-invasive optical fiber sensor for detecting volatile organic compounds (VOCs) as biomarkers of diabetes is proposed and experimentally demonstrated. It offers a low-cost and straightforward fabrication approach by implementing a one-step spray coating of a ZnO colloidal solution on a glass optical fiber. The structure of the optical fiber sensor is based on a single-mode fiber-coreless silica fiber-single-mode fiber (SMF-CSF-SMF) structure, where the CSF is the sensor region spliced between two SMFs. The ZnO layer of a higher refractive index coated over the sensing region improves the light interaction with the surrounding medium, leading to sensitivity enhancement. The optical properties, morphology, and elemental composition of the ZnO layer were analyzed. The sensing mechanism of the developed sensor is based on a wavelength interrogation technique showing wavelength shifts when the sensor is exposed to various VOC vapor concentration levels. Various concentrations of the three VOCs (including acetone, isopropanol, and ethanol) ranging from 20% to 100% were tested and analyzed. The sensor noticeably shows a significant response towards acetone vapor, with a better sensitivity of 0.162 nm/% vapor than for isopropanol (0.082 nm/% vapor) and ethanol (0.075 nm/% vapor) vapors. The high sensitivity and selectivity towards acetone, a common biomarker for diabetes, offers the potential for further development of this sensor as a smart healthcare system for monitoring diabetic conditions.

Gold Nanoparticles-Functionalized Cotton as Promising Flexible and Green Substrate for Impedometric VOC Detection

This work focuses on the possible application of gold nanoparticles on flexible cotton fabric as acetone- and ethanol-sensitive substrates by means of impedance measurements. Specifically, citrate- and polyvinylpyrrolidone (PVP)-functionalized gold nanoparticles (Au NPs) were synthesized using green and well-established procedures and deposited on cotton fabric. A complete structural and morphological characterization was conducted using UV-VIS and Fourier transform infrared (FT-IR) spectroscopy, atomic force microscopy (AFM), and scanning electron microscopy (SEM). A detailed dielectric characterization of the blank substrate revealed interfacial polarization effects related to both Au NPs and their specific surface functionalization. For instance, by entirely coating the cotton fabric (i.e., by creating a more insulating matrix), PVP was found to increase the sample resistance, i.e., to decrease the electrical interconnection of Au NPs with respect to citrate functionalized sample. However, it was observed that citrate functionalization provided a uniform distribution of Au NPs, which reduced their spacing and, therefore, facilitated electron transport. Regarding the detection of volatile organic compounds (VOCs), electrochemical impedance spectroscopy (EIS) measurements showed that hydrogen bonding and the resulting proton migration impedance are instrumental in distinguishing ethanol and acetone. Such findings can pave the way for the development of VOC sensors integrated into personal protective equipment and wearable telemedicine devices. This approach may be crucial for early disease diagnosis based on nanomaterials to attain low-cost/low-end and easy-to-use detectors of breath volatiles as disease markers.

Influence of ventilatory parameters on the concentration of exhaled volatile organic compounds in mechanically ventilated patients

Analysis of volatile organic compounds (VOC) within exhaled breath is subject to numerous sources of methodological and physiological variability. Whilst breathing pattern is expected to influence the concentrations of selected exhaled VOCs, it remains challenging to investigate respiratory rate and depth accurately in awake subjects. Online breath sampling was performed in 20 mechanically ventilated patients using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS). The effect of variation in respiratory rate (RR) and tidal volume (TV) on the VOC release profiles was examined. A panel of nineteen VOCs were selected, including isoprene, acetone, propofol, volatile aldehydes, acids and phenols. Variation in RR had the greatest influence on exhaled isoprene levels, with maximum and average concentrations being inversely correlated with RR. Variations in RR had a statistically significant impact on acetone, C3-C7 linear aldehydes and acetic acid. In comparison, phenols (including propofol), C8-C10 aldehydes and C3-C6 carboxylic acids were not influenced by RR. Isoprene was the only compound to be influenced by variation in TV. These findings, obtained under controlled conditions, provide useful guidelines for the optimisation of breath sampling protocols to be applied on awake patients.

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust "electronic nose" (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using "leave-one-out" training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

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.

V2CTX MXene-based hybrid sensor with high selectivity and ppb-level detection for acetone at room temperature

High-performance, room temperature-based novel sensing materials are one of the frontier research topics in the gas sensing field, and MXenes, a family of emerging 2D layered materials, has gained widespread attention due to their distinctive properties. In this work, we propose a chemiresistive gas sensor made from V₂CT_x MXene-derived, urchin-like V₂O₅ hybrid materials (V₂C/V₂O₅ MXene) for gas sensing applications at room temperature. The as-prepared sensor exhibited high performance when used as the sensing material for acetone detection at room temperature. Furthermore, the V₂C/V₂O₅ MXene-based sensor exhibited a higher response (S% = 11.9%) toward 15 ppm acetone than pristine multilayer V₂CT_x MXenes (S% = 4.6%). Additionally, the composite sensor demonstrated a low detection level at ppb levels (250 ppb) at room temperature, as well as high selectivity among different interfering gases, fast response-recovery time, good repeatability with minimal amplitude fluctuation, and excellent long-term stability. These improved sensing properties can be attributed to the possible formation of H-bonds in multilayer V₂C MXenes, the synergistic effect of the newly formed composite of urchin-like V₂C/V₂O₅ MXene sensor, and high charge carrier transport at the interface of V₂O₅ and V₂C MXene.

Recent Advances in Sensing Materials Targeting Clinical Volatile Organic Compound (VOC) Biomarkers: A Review

In general, volatile organic compounds (VOCs) have a high vapor pressure at room temperature (RT). It has been reported that all humans generate unique VOC profiles in their exhaled breath which can be utilized as biomarkers to diagnose disease conditions. The VOCs available in exhaled human breath are the products of metabolic activity in the body and, therefore, any changes in its control level can be utilized to diagnose specific diseases. More than 1000 VOCs have been identified in exhaled human breath along with the respiratory droplets which provide rich information on overall health conditions. This provides great potential as a biomarker for a disease that can be sampled non-invasively from exhaled breath with breath biopsy. However, it is still a great challenge to develop a quick responsive, highly selective, and sensitive VOC-sensing system. The VOC sensors are usually coated with various sensing materials to achieve target-specific detection and real-time monitoring of the VOC molecules in the exhaled breath. These VOC-sensing materials have been the subject of huge interest and extensive research has been done in developing various sensing tools based on electrochemical, chemoresistive, and optical methods. The target-sensitive material with excellent sensing performance and capturing of the VOC molecules can be achieved by optimizing the materials, methods, and its thickness. This review paper extensively provides a detailed literature survey on various non-biological VOC-sensing materials including metal oxides, polymers, composites, and other novel materials. Furthermore, this review provides the associated limitations of each material and a summary table comparing the performance of various sensing materials to give a better insight to the readers.

Scalable approach to fabricate paper-based biomass reduced graphene sensor for the detection of exhaled diabetic breath

Herein, we demonstrate a microwave-assisted chemical reduction technique to exfoliate a few layers of graphene from the natural waste material, 'coconut shell'. The microwave irradiation coconut shell is subjected to structural, morphological and functional groups characterization methods including SEM, Raman, FTIR and XPS spectroscopic analyses. The formation of biomass reduced graphene (BRG) has been confirmed through Raman and FTIR spectroscopic analyzes with the presence of D, G and 2D and other functional spectral bands, respectively. The surface topography of the BRG exhibits two-dimensional mat structures with wrinkle topography, imaged by electron microscopic techniques. The metallic behaviour of the BRG is evaluated by band structure calculation using density functional theory. The synthesized nanostructure has been evaluated for exhaled diabetic breath sensing application by fabricating sensor device on the paper-based substrate by roll-to-roll coating technique. The BRG sensor exhibited enhanced sensing response at a very lower concentration of diabetic biomarker with long term stability and rapid response/recovery time of 1.11 s/41.25 s, respectively. Based on our findings, the microwave-assisted BRG is a potential candidate for fabricating highly scalable, inherently safe, economically viable and excellent sensing performance to detect exhaled diabetic breath at room temperature.

Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time

Volatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.

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.

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

Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. - methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.

Biomarker Metabolites Discriminate between Physiological States of Field, Cave and White-nose Syndrome Diseased Bats

Analysis of volatile organic compound (VOC) emissions using electronic-nose (e-nose) devices has shown promise for early detection of white-nose syndrome (WNS) in bats. Tricolored bats, Perimyotis subflavus, from three separate sampling groups defined by environmental conditions, levels of physical activity, and WNS-disease status were captured temporarily for collection of VOC emissions to determine relationships between these combinations of factors and physiological states, Pseudogymnoascus destructans (Pd)-infection status, and metabolic conditions. Physiologically active (non-torpid) healthy individuals were captured outside of caves in Arkansas and Louisiana. In addition, healthy and WNS-diseased torpid bats were sampled within caves in Arkansas. Whole-body VOC emissions from bats were collected using portable air-collection and sampling-chamber devices in tandem. Electronic aroma-detection data using three-dimensional Principal Component Analysis provided strong evidence that the three groups of bats had significantly different e-nose aroma signatures, indicative of different VOC profiles. This was confirmed by differences in peak numbers, peak areas, and tentative chemical identities indicated by chromatograms from dual-column GC-analyses. The numbers and quantities of VOCs present in whole-body emissions from physiologically active healthy field bats were significantly greater than those of torpid healthy and diseased cave bats. Specific VOCs were identified as chemical biomarkers of healthy and diseased states, environmental conditions (outside and inside of caves), and levels of physiological activity. These results suggest that GC/E-nose dual-technologies based on VOC-detection and analyses of physiological states, provide noninvasive alternative means for early assessments of Pd-infection, WNS-disease status, and other physiological states.

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.

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

The electronic nose as a rule-out test for tuberculosis in an indigenous population

INTRODUCTION

To end the tuberculosis (TB) epidemic, efficient diagnostic tools are needed. In a previous calibration study, a portable 'point of care' electronic nose device (Aeonose^TM ) proved to be a promising tool in a hospital setting. We evaluated this technology to detect TB in an indigenous population in Paraguay.

METHODS

A total of 131 participants were enrolled. eNose results were compared with anamnesis, physical examinations, chest radiography and mycobacterial cultures in individuals with signs and symptoms compatible with TB. The eNose analysis was performed in two stages: first, the training with a combination of a previous study population plus 47 participants from the new cohort (total n = 153), and second, the 'blind prediction' of 84 participants.

RESULTS

21% of all participants (n = 131) showed symptoms and/or chest radiography abnormalities suspicious of TB. No sputum samples resulted culture positive for Mycobacterium tuberculosis complex. Only one patient had a positive smell print analysis. In the training model, the specificity was 92% (95% confidence interval (CI): 85%-96%) and the negative predictive value (NPV) was 95%. In the blind prediction model, the specificity and the NPV were 99% (95% CI: 93%-99%) and 100%, respectively. Although the sensitivity and positive predictive value of the eNose could not be assessed in this cohort due to the small sample size, no active TB cases were found during a one year of follow-up period.

CONCLUSION

The eNose showed promising specificity and negative predictive value and might therefore be developed as a rule-out test for TB in vulnerable populations.

Artificial Breath Classification Using XGBoost Algorithm for Diabetes Detection

Exhaled breath analysis has become more and more popular as a supplementary tool for medical diagnosis. However, the number of variables that have to be taken into account forces researchers to develop novel algorithms for proper data interpretation. This paper presents a system for analyzing exhaled air with the use of various sensors. Breath simulations with acetone as a diabetes biomarker were performed using the proposed e-nose system. The XGBoost algorithm for diabetes detection based on artificial breath analysis is presented. The results have shown that the designed system based on the XGBoost algorithm is highly selective for acetone, even at low concentrations. Moreover, in comparison with other commonly used algorithms, it was shown that XGBoost exhibits the highest performance and recall.

Socio-economic demands and challenges for non-invasive disease diagnosis through a portable breathalyzer by the incorporation of 2D nanosheets and SMO nanocomposites

Breath analysis for non-invasive clinical diagnostics and treatment progression has penetrated the research community owing to the technological developments in novel sensing nanomaterials. The trace level selective detection of volatile organic compounds (VOCs) in breath facilitates the study of physiological disorder and real-time health monitoring. This review focuses on advancements in chemiresistive gas sensor technology for biomarker detection associated with different diseases. Emphasis is placed on selective biomarker detection by semiconducting metal oxide (SMO) nanostructures, 2-dimensional nanomaterials (2DMs) and nanocomposites through various optimization strategies and sensing mechanisms. Their synergistic properties for incorporation in a portable breathalyzer have been elucidated. Furthermore, the socio-economic demands of a breathalyzer in terms of recent establishment of startups globally and challenges of a breathalyzer are critically reviewed. This initiative is aimed at highlighting the challenges and scope for improvement to realize a high performance chemiresistive gas sensor for non-invasive disease diagnosis.

Breath analysis for non-invasive clinical diagnostics and treatment progression has penetrated the research community owing to the technological developments in novel sensing nanomaterials.

Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.

Accuracy of breath test for diabetes mellitus diagnosis: a systematic review and meta-analysis

The review aimed to investigate the accuracy of breath tests in the diagnosis of diabetes mellitus, identify exhaled volatile organic compounds with the most evidence as potential biomarkers, and summarize prospects and challenges in diabetic breath tests. Databases including Medline, PubMed, EMBASE, Cochrane Library and Science Citation Index Expanded were searched. Human studies describing diabetic breath analysis with more than 10 subjects as controls and patients were included. Population demographics, breath test conditions, biomarkers, analytical techniques and diagnostic accuracy were extracted. Quality assessment was performed with the Standards for Reporting Diagnostic Accuracy and a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2). Forty-four research with 2699 patients with diabetes were included for qualitative data analysis and 14 eligible studies were used for meta-analysis. Pooled analysis of type 2 diabetes breath test exhibited sensitivity of 91.8% (95% CI 83.6% to 96.1%), specificity of 92.1% (95% CI 88.4% to 94.7%) and area under the curve (AUC) of 0.96 (95% CI 0.94 to 0.97). Isotopic carbon dioxide (CO₂) showed the best diagnostic accuracy with pooled sensitivity of 0.949 (95% CI 0.870 to 0.981), specificity of 0.946 (95% CI 0.891 to 0.975) and AUC of 0.98 (95% CI 0.97 to 0.99). As the most widely reported biomarker, acetone showed moderate diagnostic accuracy with pooled sensitivity of 0.638 (95% CI 0.511 to 0.748), specificity of 0.801 (95% CI 0.691 to 0.878) and AUC of 0.79 (95% CI 0.75 to 0.82). Our results indicate that breath test is a promising approach with acceptable diagnostic accuracy for diabetes mellitus and isotopic CO₂ is the optimal breath biomarker. Even so, further validation and standardization in subject control, breath sampling and analysis are still required.

Materials, Actuators, and Sensors for Soft Bioinspired Robots

Biological systems can perform complex tasks with high compliance levels. This makes them a great source of inspiration for soft robotics. Indeed, the union of these fields has brought about bioinspired soft robotics, with hundreds of publications on novel research each year. This review aims to survey fundamental advances in bioinspired soft actuators and sensors with a focus on the progress between 2017 and 2020, providing a primer for the materials used in their design.

Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds

Previous studies have shown that volatile organic compounds (VOCs) are potential biomarkers of breast cancer. An unanswered question is how urinary VOCs change over time as tumors progress. To explore this, BALB/c mice were injected with 4T1.2 triple negative murine tumor cells in the tibia. This typically causes tumor progression and osteolysis in 1-2 weeks. Samples were collected prior to tumor injection and from days 2-19. Samples were analyzed by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry. Univariate analysis identified VOCs that were biomarkers for breast cancer; some of these varied significantly over time and others did not. Principal component analysis was used to distinguish Cancer (all Weeks) from Control and Cancer Week 1 from Cancer Week 3 with over 90% accuracy. Forward feature selection and linear discriminant analysis identified a unique panel that could identify tumor presence with 94% accuracy and distinguish progression (Cancer Week 1 from Cancer Week 3) with 97% accuracy. Principal component regression analysis also demonstrated that a VOC panel could predict number of days since tumor injection (R2 = 0.71 and adjusted R2 = 0.63). VOC biomarkers identified by these analyses were associated with metabolic pathways relevant to breast cancer.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Exhaled breath analysis in disease detection

Investigating the use of exhaled breath analysis to diagnose and monitor different diseases has attracted much interest in recent years. This review introduces conventionally used methods and some emerging technologies aimed at breath analysis and their relevance to lung disease, airway inflammation, gastrointestinal disorders, metabolic disorders and kidney diseases. One section correlates breath components and specific diseases, whereas the other discusses some unique ideas, strategies, and devices to analyze exhaled breath for the diagnosis of some common diseases. This review aims to briefly introduce the potential application of exhaled breath analysis for the diagnosis and screening of various diseases, thereby providing a new avenue for the detection of non-invasive diseases.

Screening of Chorioamnionitis Using Volatile Organic Compound Detection in Exhaled Breath: A Pre-clinical Proof of Concept Study

Chorioamnionitis is a major risk factor for preterm birth and an independent risk factor for postnatal morbidity for which currently successful therapies are lacking. Emerging evidence indicates that the timing and duration of intra-amniotic infections are crucial determinants for the stage of developmental injury at birth. Insight into the dynamical changes of organ injury after the onset of chorioamnionitis revealed novel therapeutic windows of opportunity. Importantly, successful development and implementation of therapies in clinical care is currently impeded by a lack of diagnostic tools for early (prenatal) detection and surveillance of intra-amniotic infections. In the current study we questioned whether an intra-amniotic infection could be accurately diagnosed by a specific volatile organic compound (VOC) profile in exhaled breath of pregnant sheep. For this purpose pregnant Texel ewes were inoculated intra-amniotically with Ureaplasma parvum and serial collections of exhaled breath were performed for 6 days. Ureaplasma parvum infection induced a distinct VOC-signature in expired breath of pregnant sheep that was significantly different between day 0 and 1 vs. day 5 and 6. Based on a profile of only 15 discriminatory volatiles, animals could correctly be classified as either infected (day 5 and 6) or not (day 0 and 1) with a sensitivity of 83% and a specificity of 71% and an area under the curve of 0.93. Chemical identification of these distinct VOCs revealed the presence of a lipid peroxidation marker nonanal and various hydrocarbons including n-undecane and n-dodecane. These data indicate that intra-amniotic infections can be detected by VOC analyses of exhaled breath and might provide insight into temporal dynamics of intra-amniotic infection and its underlying pathways. In particular, several of these volatiles are associated with enhanced oxidative stress and undecane and dodecane have been reported as predictive biomarker of spontaneous preterm birth in humans. Applying VOC analysis for the early detection of intra-amniotic infections will lead to appropriate surveillance of these high-risk pregnancies, thereby facilitating appropriate clinical course of action including early treatment of preventative measures for pre-maturity-associated morbidities.

A highly electropositive ReS2 based ultra-sensitive flexible humidity sensor for multifunctional applications

Flexible 2D ReS₂ based humidity sensor for multifunctional applications.

Recent Progress in Graphene Derivatives/Metal Oxides Binary Nanocomposites Based Chemi-resistive Sensors for Disease Diagnosis by Breath Analysis

Background::

The scientific and clinical interest of breath analysis for non-invasive disease diagnosis has been focused by the scientific community over the past decade. This was due to the exhalation of prominent volatile organic compounds (VOCs) corresponding to the metabolic activities in the body and their concentration variation. To identify these biomarkers, various analytical techniques have been used in the past and the threshold concentration was established between a healthy and diseased state. Subsequently, various nanomaterials-based gas sensors were explored for their demand in quantifying these biomarkers for real-time, low cost and portable breathalyzers along with the essential sensor performances.

Methods::

We focus on the classification of graphene derivatives and their composites’ gas sensing efficiency for the application in the development of breathalyzers. The review begins with the feasibility of the application of nanomaterial gas sensors for healthcare applications. Then, we systematically report the gas sensing performance of various graphene derivatives/semiconductor metal oxides (SMO) binary nanocomposites and their optimizing strategies in selective detection of biomarkers specific to diseases. Finally, we provide insights on the challenges, opportunity and future research directions for the development of breathalyzers using other graphene derivatives/SMO binary nanocomposites.

Results::

On the basis of these analyses, graphene and its derivatives/metal oxides based binary nanocomposites have been a choice for gas sensing material owing to their high electrical conductivity and extraordinary thickness-dependent physicochemical properties. Moreover, the presence of oxygen vacancies in SMO does not only alter the conductivity but also accelerates the carrier transport rate and influence the adsorption behavior of target analyte on the sensing materials. Hence researchers are exploring the search of ultrathin graphene and metal oxide counterpart for high sensing performances.

Conclusion::

Their impressive properties compared to their bulk counterpart have been uncovered towards sensitive and selective detection of biomarkers for its use in portable breathalyzers.

Determination of peppermint compounds in breath by needle trap micro-extraction coupled with gas chromatography-tandem mass spectrometry

Breath analysis is an alternative approach for disease diagnosis and for monitoring therapy. The lack of standardized procedures for collecting and analysing breath samples currently limits its use in clinical practice. In order to overcome this limitation, the "Peppermint Consortium" was established within the breath community to carry out breath wash-out experiments and define reference values for a panel of compounds contained in the peppermint oil capsule. Here, we present a needle trap micro-extraction technique coupled with gas chromatography and tandem mass spectrometry for a rapid and accurate determination of alpha-pinene, beta-pinene, limonene, eucalyptol, menthofuran, menthone, menthol and menthyl acetate in mixed breath samples. Detection limits between 1 and 20 pptv were observed when 25 mL of a humidified standard gas mixture were loaded into a needle trap device at a flow rate of 10 mL/min. Inter- and intra-day precisions were lower than 15%, thus confirming the reliability of the assay. Our procedure was used to analyse breath samples taken from a nominally healthy volunteer who were invited to swallow a 200 mg capsule of peppermint oil. Six samples were collected at various times within six hours of ingestion. Analyte concentrations were not affected by the sampling mode (i.e. mixed vs. end-tidal fraction), whereas respiratory rate and exhalation flow rate values slightly influenced the concentration of the target compounds in breath samples.

Breath carbonyl levels in a human population of seven hundred participants

Oxidative stress is associated with numerous health conditions and disorders, and aldehydes are known biomarkers of oxidative stress that can be non-invasively measured in exhaled human breath. Few studies report breath aldehyde levels in human populations, and none claim participant numbers in the hundreds or more. Further, the breath community must first define the existing aldehyde concentration variance in a normal population to understand when these levels are significantly perturbed by exogenous stressors or health conditions. In this study, we collected breath samples from 692 participants and quantified C₄-C₁₀ straight chain aldehyde levels. C₉ aldehyde was the most abundant in breath, followed by C₆. C₄ and C₅ appear to have bimodal distributions. Post hoc, we mined our dataset for other breath carbonyls captured by our assay, which involves elution of breath samples onto a solid phase extraction cartridge, derivatization and liquid chromatography-quadrupole time of flight mass spectrometry (LC-qTOF). We found a total of 21 additional derivatized compounds. Using self-reported demographic factors from our participants, we found no correlation between these breath carbonyls and age, gender, body mass index (BMI), ethnicity or smoking habit (tobacco and marijuana). This work was preceded by a small confounders study, which was intended to refine our breath collection procedure. We found that breath aldehyde levels can be affected by participants' using scented hygiene products such as lotions and mouthwashes, while collecting consecutive breath samples, rinsing the mouth with water, and filtering inspired air did not have an effect. Using these parameters to guide our sampling, subjects were instructed to avoid the prior conditions to provide a breath sample for our study.

Non-invasive and Time-dependent Blood-sugar Monitoring via Breath-derived CO2 Correlation Using Gas Chromatograph with a Milli-whistle Gas Analyzer

A clear and positive correlation between the CO₂ concentration and the blood-sugar level has been observed via a non-invasive and time-dependent monitoring of CO₂ concentration from human breath, which is carried out by using a home-made gas chromatography (GC)/milli-whistle compact analyzer. The time-dependent sampling of the CO₂ concentration correlated between 5.0 to 5.6% (1% = 10⁴ ppm) in accordance with blood-sugar level variations of 80 to 110 mg/dL. The analytical method results in a rapid, continuous and non-invasive determination of blood-sugar level via measurement of the CO₂ concentration exhaled from the lungs.

Microbiota and Malodor-Etiology and Management

Accumulating evidence indicates that microbiota plays a critical role in physiological processes in humans. However, it might also contribute to body malodor by producing numerous odorous molecules such as ammonia, volatile sulfur compounds or trimethylamine. Although malodor is commonly overlooked by physicians, it constitutes a major problem for many otherwise healthy people. Thus, this review aims to investigate most common causes of malodor and describe potential therapeutic options. We searched PUBMED and Google Scholar databases to identify the clinical and pre-clinical studies on bad body smell, malodor, halitosis and microbiota. Unpleasant smell might originate from the mouth, skin, urine or reproductive fluids and is usually caused by odorants that are produced by resident bacterial flora. The accumulation of odorous compounds might result from diet, specific composition of microbiota, as well as compromised function of the liver, intestines and kidneys. Evidence-based guidelines for management of body malodor are lacking and no universal treatment exists. However, the alleviation of the symptoms may be achieved by controlling the diet and physical elimination of bacteria and/or accumulated odorants.

Exhaled volatile substances in children suffering from type 1 diabetes mellitus: results from a cross-sectional study

Monitoring metabolic adaptation to type 1 diabetes mellitus in children is challenging. Analysis of volatile organic compounds (VOCs) in exhaled breath is non-invasive and appears as a promising tool. However, data on breath VOC profiles in pediatric patients are limited. We conducted a cross-sectional study and applied quantitative analysis of exhaled VOCs in children suffering from type 1 diabetes mellitus (T1DM) (n = 53) and healthy controls (n = 60). Both groups were matched for sex and age. For breath gas analysis, a very sensitive direct mass spectrometric technique (PTR-TOF) was applied. The duration of disease, the mode of insulin application (continuous subcutaneous insulin infusion vs. multiple daily insulin injection) and long-term metabolic control were considered as classifiers in patients. The concentration of exhaled VOCs differed between T1DM patients and healthy children. In particular, T1DM patients exhaled significantly higher amounts of ethanol, isopropanol, dimethylsulfid, isoprene and pentanal compared to healthy controls (171, 1223, 19.6, 112 and 13.5 ppbV vs. 82.4, 784, 11.3, 49.6, and 5.30 ppbV). The most remarkable differences in concentrations were found in patients with poor metabolic control, i.e. those with a mean HbA1c above 8%. In conclusion, non-invasive breath testing may support the discovery of basic metabolic mechanisms and adaptation early in the progress of T1DM.

Non-Invasive Assessment of Metabolic Adaptation in Paediatric Patients Suffering from Type 1 Diabetes Mellitus

An analysis of exhaled volatile organic compounds (VOC) may deliver systemic information quicker than available invasive techniques. Metabolic aberrations in pediatric type 1 diabetes (T1DM) are of high clinical importance and could be addressed via breathomics. Real-time breath analysis was combined with continuous glucose monitoring (CGM) and blood tests in children suffering from T1DM and age-matched healthy controls in a highly standardized setting. CGM and breath-resolved VOC analysis were performed every 5 minutes for 9 hours and blood was sampled at pre-defined time points. Per participant (n = 44) food intake and physical activity were identical and a total of 22 blood samples and 93 minutes of breath samples were investigated. The inter-individual variability of glucose, insulin, glucagon, leptin, and soluble leptin receptor relative to food intake differed distinctly between patients and controls. In T1DM patients, the exhaled amounts of acetone, 2-propanol, and pentanal correlated to glucose concentrations. Of note, the strength of these correlations strongly depended on the interval between food intake and breath sampling. Our data suggests that metabolic adaptation through postprandial hyperglycemia and related oxidative stress is immediately reflected in exhaled breath VOC concentrations. Clinical translations of our findings may enable point-of-care applicability of online breath analysis towards personalized medicine.

Tin Dioxide Thin Film with UV-enhanced Acetone Detection in Microwave Frequency Range

In this paper, the UV illumination effect for microwave gas sensors based on the tin dioxide was verified. A UV LED with emission wavelength close to the absorption edge of the SnO₂ gas-sensing layer was selected as the UV source. The developed gas sensors were tested under exposure to acetone in the 0-200 ppm range at room temperature. The sensor's complex reflection coefficient corresponding to target gas concentration was measured with the use of a five-port reflectometer system exhibiting enhanced uncertainty distribution, which allows for the detection of low gas concentration. The UV illumination significantly emphasizes the sensors' response in terms of both magnitude and phase for low gas concentrations, in contrast to previously reported results, in which only the reflection coefficient's phase was affected. The highest responses were obtained for modulated UV illumination.

Ultrasensitive Sniff-Cam for Biofluorometric-Imaging of Breath Ethanol Caused by Metabolism of Intestinal Flora

We developed a gas-imaging system (sniff-cam) for gaseous ethanol (EtOH) with improved sensitivity. The sniff-cam was applied to measure the extremely low concentration distribution of breath EtOH without the consumption of alcohol, which is related to the activity of the oral or gut bacterial flora. A ring-type ultraviolet-light-emitting diode was mounted around a camera lens as an excitation light source, which enabled simultaneous excitation and imaging of the fluorescence. In the EtOH sniff-cam, a nicotinamide adenine dinucleotide (NAD)-dependent alcohol dehydrogenase (ADH) was used to catalyze the redox reaction between EtOH and the oxidized form of NAD (NAD⁺). Upon application of gaseous EtOH to the ADH-immobilized mesh that was soaked in an NAD⁺ solution and placed in front of the camera, NADH was produced through an ADH-mediated reaction. NADH expresses fluorescence at an emission wavelength of 490 nm and excitation wavelength of 340 nm. Thus, the concentration distribution of EtOH was visualized by measuring the distribution of the fluorescence light intensity from NADH on the ADH-immobilized mesh surface. First, a comparison of image analysis methods based on the red-green-blue color (RGB) images and the optimization of the buffer pH and NAD⁺ solution concentration was performed. The new sniff-cam showed a 25-fold greater sensitivity and broader dynamic range (20.6-300000 ppb) in comparison to those of the previously fabricated sniff-cam. Finally, we measured the concentration distribution of breath EtOH without alcohol consumption using the improved sniff-cam and obtained a value of 116.2 ± 35.7 ppb (n = 10).

A Prototype of a Portable Gas Analyzer for Exhaled Acetone Detection

The paper presents the development of a portable gas analyzer prototype for exhaled acetone detection, employing an application-suited gas sensor array and 3D printing technology. The device provides the functionality to monitor exhaled acetone levels, which could be used as a potential tool for non-invasive diabetes monitoring. The relationship between exhaled acetone concentrations and glucose in blood is confirmed in the literature, including research carried out by the authors. The design process is presented including a general consideration for the sensor array construction, which is the core for sensing gases, as well as requirements for the measurement chamber it is to be placed in. Moreover, the mechanical design of the 3D-printed housing is discussed to ensure the ergonomics of use as a hand-held device while keeping the hardware integrity. Also, the processing hardware is discussed to provide sufficient computing power to handle the stand-alone operation while being energy efficient, enabling long battery-powered operation. Finally, calibration and measurement, as well as the analyzer operation, are shown, validating the proposed class of exhaled acetone-detection capable meters.

An Idiographic Investigation of Diabetic Alert Dogs' Ability to Learn From a Small Sample of Breath Samples From People With Type 1 Diabetes

OBJECTIVE

There is a growing market for diabetes-alert dogs but little has been published regarding their ability to reliably detect hypoglycemia. We aimed to determine whether 2 dogs could detect hypoglycemic breath samples from people with type 1 diabetes (T1D) and then transfer detection to novel hypoglycemic breath samples.

METHODS

Breath samples were collected from individuals with T1D during times of normo-, hypo- and hyperglycemia. Two dogs, previously trained (3 alternative forced choice) with breath samples from 3 different individuals with T1D, were presented with 3 breath samples from the same individual: 1 hypoglycemic, 1 normoglycemic and 1 hyperglycemic, and trained to identify the hypoglycemic sample using a "yes/no" procedure. The dogs' ability to transfer detection was then tested by presenting them with a novel sample set from the same individual. Then we tested whether 1 dog could transfer detection of the odour of hypoglycemia by presenting new samples from a different individual.

RESULTS

One dog was able to transfer detection of the odour of hypoglycemia to samples from the same individual (specificity 89%, sensitivity 62%), but a second dog was not. Results were inconclusive regarding the ability of 1 dog to transfer detection of the odour of hypoglycemia across 2 individuals.

CONCLUSIONS

The results suggest that some dogs can be trained to detect hypoglycemic breath of an individual with T1D, but detection may not transfer to novel samples from other individuals. Results should be interpreted with caution, as the dogs were trained with only a small number of breath samples before testing.

A comparison of online and offline measurement of exhaled breath for diabetes pre-screening by graphene-based sensor; from powder processing to clinical monitoring prototype

Several breath analysis studies have suggested a correlation between blood glucose (BG) levels and breath acetone, indicating acetone as a primary biomarker in exhaled breath for diabetes diagnosis. Herein, we have (i) fabricated and validated graphene-based chemi-resistive sensors for selective and sensitive detection of acetone, (ii) performed offline breath analysis by a static gas sensing set-up to acquire olfactory signals, and (iii) developed an LED-based portable on/off binary e-nose system for pre-screening diabetes through online analysis. The fabricated sensors showed selective detection for acetone with high sensitivity (5.66 for 1 ppm acetone vapor) and fast response and recovery times (10 s and 12 s) at low concentrations. The sensor responses of end tidal fractional breath (collected in Tedlar bags) in the fasting and postprandial conditions were compared with BG levels and glycated hemoglobin (HbA1c) levels taken at the same time in 30 volunteers (13 healthy and 17 diabetic subjects). The mean sensor responses of the diabetic subjects as obtained by offline analysis were 1.1 times higher than those of the healthy subjects. The optimal regression equation framed with the significant correlating variables for HbA1c estimation achieved an accuracy of 66.67%. The online breath analysis by on/off binary prototype exhibited an accuracy of 60.51%. Though there exists a minimal uncertainty in classification, the on/off type portable prototype is easy to operate, gives a quicker response with a refresh/recovery rate of 19 s and can be used for preliminary diagnosis, and can be used for preliminary diagnosis. This inexpensive sensor technology may revolutionize personalized medicine in the near future and greatly benefit the underprivileged.

Diabetes alert dogs: a narrative critical overview

Owing to their virtually incomparable olfactory apparatus and the mutual loving relationship with man, the use of dogs for assisting humans in many activities has become commonplace. Dogs have been used for long for livestock herding, hunting and pulling. More recently, they have been employed for servicing or assisting people with disabilities, for rescuing, for pet therapy and, last but not least, for detecting a vast array of volatile organic compounds related to drugs, narcotics, explosives and foods. Although cancer detection seems the most distinguished use of “man’s best friends” in science and medicine, increasing emphasis is being placed on their capacity to perceive chemical changes or human expressions associated with harmful, even life-threating, blood glucose variations. The evidence available in the current scientific literature attests that diabetes alerting dogs (DADs) have a heterogeneous efficiency for warning owners of episodes of hypoglycemia or hyperglycemia, with sensitivities and specificities ranging between 0.29–0.80 and 0.49–0.96, respectively. Although the adoption of DADs seems effective for improving the quality of life of many diabetics patients, some important drawbacks can be highlighted. These typically include adoption and keeping expenditures, lack of certification or accreditation of dog providers, poor harmonization of training procedures, significant inter-breed, intra-breed and intra-dog variabilities, wide-ranging alert behaviors, ability of owners to identify dog’s alerts, as well as lack of quality assessment of a dog’s “diagnostic” performance. Overcoming many of these limitations shall probably make DADs more efficient tools for improving diabetes management.

Sensors for Enhanced Detection of Acetone as a Potential Tool for Noninvasive Diabetes Monitoring

Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for exhaled breath analysis are based on spectrometry techniques, however, the development of gas sensors has made them more and more attractive from a medical point of view. This review focuses on the latest achievements in gas sensors for exhaled acetone detection. Several different methods and techniques are presented and discussed as well.

Volatile organic compounds discrimination based on dual mode detection

We report on a volatile organic compound (VOC) sensor that can provide concentration-independent signals toward target gases. The device is based on a dual-mode detection mechanism that can simultaneously record the mechanical (resonant frequency, f _r) and electrical (current, I) responses of the same gas adsorption event. The two independent signals form a unique I-f _r trace for each target VOC as the concentration varies. The mechanical response (frequency shift, Δf _r) resulting from mass load on the device is directly related to the amount of surface adsorptions, while the electrical response (current variation, ΔI) is associated with charge transfer across the sensing interface and changes in carrier mobility. The two responses resulting from independent physical processes reflect intrinsic physical properties of each target gas. The ΔI-Δf _r trace combined with the concentration dependent frequency (or current) signals can therefore be used to achieve target both recognition and quantification. The dual-mode device is designed and fabricated using standard complementary metal oxide semiconductor (CMOS) compatible processes. It exhibits consistent and stable performance in our tests with six different VOCs including ethanol, methanol, acetone, formaldehyde, benzene and hexane.

Sensing Technologies for Detection of Acetone in Human Breath for Diabetes Diagnosis and Monitoring

The review describes the technologies used in the field of breath analysis to diagnose and monitor diabetes mellitus. Currently the diagnosis and monitoring of blood glucose and ketone bodies that are used in clinical studies involve the use of blood tests. This method entails pricking fingers for a drop of blood and placing a drop on a sensitive area of a strip which is pre-inserted into an electronic reading instrument. Furthermore, it is painful, invasive and expensive, and can be unsafe if proper handling is not undertaken. Human breath analysis offers a non-invasive and rapid method for detecting various volatile organic compounds thatare indicators for different diseases. In patients with diabetes mellitus, the body produces excess amounts of ketones such as acetoacetate, beta-hydroxybutyrate and acetone. Acetone is exhaled during respiration. The production of acetone is a result of the body metabolising fats instead of glucose to produce energy. There are various techniques that are used to analyse exhaled breath including Gas Chromatography Mass Spectrometry (GC-MS), Proton Transfer Reaction Mass Spectrometry (PTR-MS), Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS), laser photoacoustic spectrometry and so on. All these techniques are not portable, therefore this review places emphasis on how nanotechnology, through semiconductor sensing nanomaterials, has the potential to help individuals living with diabetes mellitus monitor their disease with cheap and portable devices.