Can volatile compounds in exhaled breath be used to monitor control in diabetes mellitus?

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

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

Breath biomarkers in Non-Carcinogenic diseases

The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.

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.

Artificial Neural Processing-Driven Bioelectronic Nose for the Diagnosis of Diabetes and Its Complications

Diabetes and its complications affect the younger population and are associated with a high mortality rate; however, early diagnosis can contribute to the selection of appropriate treatment regimens that can reduce mortality. Although diabetes diagnosis via exhaled breath has great potential for early diagnosis, research on such diagnosis is restricted to disease detection, requiring in-depth examination to diagnose and classify diseases and their complications. This study demonstrates the use of an artificial neural processing-based bioelectronic nose to accurately diagnose diabetes and classify diabetic types (type I and II) and their complications, such as heart disease. Specifically, an M13 phage-based electronic nose (e-nose) is used to explore the features of subjects with diabetes at various levels of cellular and organismal organization (cells, liver organoids, and mice). Exhaled breath samples are collected during culturing and exposed to the phage-based e-nose. Compared with cells, liver organoids cultured under conditions mimicking a diabetic environment display properties that closely resemble the characteristics of diabetic mice. Using neural pattern separation, the M13 phage-based e-nose achieves a classification success rate of over 86% for four conditions in mice, namely, type 1 diabetes, type 2 diabetes, diabetic cardiomyopathy, and cardiomyopathy.

Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS)

Selected ion flow tube mass spectrometry (SIFT-MS) is now recognized as the most versatile analytical technique for the identification and quantification of trace gases down to the parts-per-trillion by volume, pptv, range. This statement is supported by the wide reach of its applications, from real-time analysis, obviating sample collection of very humid exhaled breath, to its adoption in industrial scenarios for air quality monitoring. This review touches on the recent extensions to the underpinning ion chemistry kinetics library and the alternative challenge of using nitrogen carrier gas instead of helium. The addition of reagent anions in the Voice200 series of SIFT-MS instruments has enhanced the analytical capability, thus allowing analyses of volatile trace compounds in humid air that cannot be analyzed using reagent cations alone, as clarified by outlining the anion chemistry involved. Case studies are reviewed of breath analysis and bacterial culture volatile organic compound (VOC), emissions, environmental applications such as air, water, and soil analysis, workplace safety such as transport container fumigants, airborne contamination in semiconductor fabrication, food flavor and spoilage, drugs contamination and VOC emissions from packaging to demonstrate the stated qualities and uniqueness of the new generation SIFT-MS instrumentation. Finally, some advancements that can be made to improve the analytical capability and reach of SIFT-MS are mentioned.

A Metabolomic Approach for Predicting Diurnal Changes in Cortisol

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.

Nanomaterial-based gas sensors used for breath diagnosis

Gas-sensing applications commonly use nanomaterials (NMs) because of their unique physicochemical properties, including a high surface-to-volume ratio, enormous number of active sites, controllable morphology, and potential for miniaturisation.

An overview on the exponential growth of non-invasive diagnosis of diabetes mellitus from exhaled breath by nanostructured metal oxide Chemi-resistive gas sensors and μ-preconcentrator

The characterization of acetone in exhaled breath reflects the internal metabolism of glucose in bloodstream and airways. This phenomenon provides a great potential for non-invasive diagnosis of diabetes mellitus and has inspired medical sodalities as an alternative diagnostic tool. This review discusses about the origination of acetone in breath, its correlation with blood glucose level along with the ways to collect breath sample. Furthermore, we also discuss the detection of acetone by chemical sensors with emphasis on the use of pre-concentrators on a single lab-on-chip for the diagnosis of diabetes mellitus. Finally, this review outlines the future directions for the detection of acetone from exhaled breath. The first part of the review introduces the biochemistry and prevalence of diabetes in India along with the existing techniques to estimate the concentration of acetone. The second part focuses on the semiconducting metal oxide and polymer gas sensors which discusses about tailoring the dynamic sensitivity range and selectivity towards acetone in breath. The third part elaborates on the ways to pre-concentrate the target biomarkers along with future perspectives for non-invasive diabetes diagnosis. Finally we also provide the perspectives on future challenges to make it to clinical practice. Graphical abstract .

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.

Exhaled acetone and isoprene in perioperative lung cancer patients under intensive oral care: possible indicators of inflammatory responses and metabolic changes

One of the most severe complications of lung resection is postoperative pneumonia, and its prevention and prediction are critical. Exhaled acetone and isoprene are thought to be related to metabolism; however, little is known on their relationship with bacteria living in the oral cavity or their meaning in the acute phase in perioperative lung cancer patients. We measured acetone and isoprene in exhaled breath of 13 Japanese patients with lung cancer (3 women and 10 men, age range 62-82 years, mean 72.4 years) before breakfast during hospitalization, and compared with two acute-phase proteins, C-reactive protein (CRP) and albumin in blood serum, as well as the total number of bacteria in saliva and their activity to produce acetone and isoprene. Before operation, intensive oral care was carried out for each patient to prevent postoperative pneumonia, and swallowing and cough reflexes were measured for 12 of 13 patients to assess risk of postoperative pneumonia. Breath and saliva were sampled before intensive oral care (T1), after oral care but before operation (T2), and after operation (T3) during hospitalization. The total number of oral bacteria in saliva decreased significantly from T1 to T2 among 13 patients. No acetone or isoprene was detected from saliva after in vitro incubation under anaerobic or aerobic conditions, but both acetone and isoprene were detected in breath. After operation, breath acetone correlated significantly with CRP (Spearman's ρ = 0.559, P = 0.03), but not with albumin. Breath isoprene correlated significantly with albumin (Spearman's ρ = 0.659, P = 0.008), but not with CRP after operation. Although the number of subjects was small, our results support the hypothesis that breath acetone and isoprene may be related with these acute-phase proteins, which reflect inflammatory reactions and subsequent changes in metabolism in the early postoperative phase of lung resection.

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.

Ion mobility spectrometry: the diagnostic tool of third millennium medicine

Ion mobility spectrometry (IMS) is a fast, low cost, portable, and sensitive technique that separates ions in a drift tube under the influence of an electric field according to their size and shape. IMS represents a non-invasive and reliable instrumental alternative for the diagnosis of different diseases through the analysis of volatile metabolites in biological samples. IMS has applications in medicine in the study of volatile compounds for the non-invasive diagnose of bronchial carcinoma, chronic obstructive pulmonary disease, and other diseases analysing breath, urine, blood, faeces, and other biological samples. This technique has been used to study complex mixtures such as proteomes, metabolomes, complete organisms like bacteria and viruses, monitor anaesthetic agents, determine drugs, pharmaceuticals, and volatile compounds in human body fluids, and others. Pharmaceutical applications include analysis of over-the-counter-drugs, quality assessment, and cleaning verification. Medical practice needs non-invasive, robust, secure, fast, real-time, and low-cost methods with high sensitivity and compact size instruments to diagnose different diseases and IMS is the diagnostic tool that meets all these requirements of the Medicine of the future.

Biomedical applications of mid-infrared quantum cascade lasers - a review

Mid-infrared spectroscopy has been applied to research in biology and medicine for more than 20 years and conceivable applications have been identified. More recently, these applications have been shown to benefit from the use of quantum cascade lasers due to their specific properties, namely high spectral power density, small beam parameter product, narrow emission spectrum and, if needed, tuning capabilities. This review provides an overview of the achievements and illustrates some applications which benefit from the key characteristics of quantum cascade laser-based mid-infrared spectroscopy using examples such as breath analysis, the investigation of serum, non-invasive glucose monitoring in bulk tissue and the combination of spectroscopy and microscopy of tissue thin sections for rapid histopathology.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.

Design of a novel filter paper based construct for rapid analysis of acetone

The present work was focused to design a cheap, rapid, portable and easy to use filter paper based assay for the qualitative and quantitate analysis of acetone. Sodium alginate gel was loaded with the acetone specific optical signal probe, and subsequently coated onto filter paper surface to design portable colorimetric assays for acetone monitoring. The color of the paper sensor strip was observed to change from dark yellow to light yellowish in the presence of varying concentrations of acetone. Three different color analyzing models including RGB, HSV, and LAB were employed to probe the output optical signal, and their performance was compared in terms of better interpretation of the generated signal. The LAB model was found to provide better analytical figures of merit with a linear response for the acetone concentration ranging from 2.5 to 1500 ppm, and a limit of detection of 0.5 ppm. Furthermore, the specificity of the designed filter paper based sensor was demonstrated against different common interfering compounds. The results demonstrated the potential of our proposed filter paper based sensor as a novel tool for the analysis of acetone.

Sensitive Spectroscopy of Acetone Using a Widely Tunable External-Cavity Quantum Cascade Laser

We employed a single-mode, widely tunable (~300 cm⁻¹) external-cavity quantum cascade laser operating around 8 µm for broadband direct absorption spectroscopy and wavelength modulation spectroscopy where a modulation frequency of 50 kHz was employed with high modulation amplitudes of up to 10 GHz. Using a compact multipass cell, we measured the entire molecular absorption band of acetone at ~7.4 µm with a spectral resolution of ~1 cm⁻¹. In addition, to demonstrate the high modulation dynamic range of the laser, we performed direct absorption (DAS) and second harmonic wavelength modulation spectroscopy (WMS-2f) of the Q-branch peak of acetone molecular absorption band (HWHM ~10 GHz) near 1365 cm⁻¹. With WMS-2f, a minimum detection limit of 15 ppbv in less than 10 s is achieved, which yields a noise equivalent absorption sensitivity of 1.9 × 10⁻⁸ cm⁻¹ Hz^−1/2.

Transilient Response to Acetone Gas Using the Interlocking p+n Field-Effect Transistor Circuit

Low concentration acetone gas detection is significantly important for diabetes diagnosis as 1.8⁻10 ppm of acetone exists in exhaled breath from diabetes patients. A new interlocking p+n field-effect transistor (FET) circuit has been proposed for Mn-doped ZnO nanoparticles (MZO) to detect the acetone gas at low concentration, especially close to 1.8 ppm. It is noteworthy that MZO in this interlocking amplification circuit shows a low voltage signal of <0.3 V to the acetone <2 ppm while it displays a transilient response with voltage signal >4.0 V to >2 ppm acetone. In other words, the response to acetone from 1 ppm to 2 ppm increases by ~1233%, which is competent to separate diabetic patients from healthy people. Moreover, the response to 2 ppm acetone is hardly influenced by high relative humidity of 85%. In the meanwhile, MZO in this interlocking circuit possesses a high acetone selectivity compared to formaldehyde, acetaldehyde, toluene and ethanol, suggesting a promising technology for the widespread qualitative screening of diabetes. Importantly, this interlocking circuit is also applicable to other types of metal oxide semiconductor gas sensors. The resistance jump of p- and n-FETs induced by the change of their gate voltages is deemed to make this interlocking circuit produce the transilient response.

Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Biomimetic cross-reactive sensor arrays (B-CRSAs) have been used to detect and diagnose a wide variety of diseases including metabolic disorders, mental health diseases, and cancer by analyzing both vapor and liquid patient samples. Technological advancements over the past decade have made these systems selective, sensitive, and affordable. To date, devices for non-invasive and accurate disease diagnosis have seen rapid improvement, suggesting a feasible alternative to current standards for medical diagnostics. This review provides an overview of the most recent B-CRSAs for diagnostics (also referred to electronic noses and tongues in the literature) and an outlook for future technological development.

A rapidly-reversible absorptive and emissive vapochromic Pt(II) pincer-based chemical sensor

Selective, robust and cost-effective chemical sensors for detecting small volatile-organic compounds (VOCs) have widespread applications in industry, healthcare and environmental monitoring. Here we design a Pt(II) pincer-type material with selective absorptive and emissive responses to methanol and water. The yellow anhydrous form converts reversibly on a subsecond timescale to a red hydrate in the presence of parts-per-thousand levels of atmospheric water vapour. Exposure to methanol induces a similarly-rapid and reversible colour change to a blue methanol solvate. Stable smart coatings on glass demonstrate robust switching over 10⁴ cycles, and flexible microporous polymer membranes incorporating microcrystals of the complex show identical vapochromic behaviour. The rapid vapochromic response can be rationalised from the crystal structure, and in combination with quantum-chemical modelling, we provide a complete microscopic picture of the switching mechanism. We discuss how this multiscale design approach can be used to obtain new compounds with tailored VOC selectivity and spectral responses.

Toward breath analysis on a chip for disease diagnosis using semiconductor-based chemiresistors: recent progress and future perspectives

Semiconductor gas sensors using metal oxides, carbon nanotubes, graphene-based materials, and metal chalcogenides have been reviewed from the viewpoint of the sensitive, selective, and reliable detection of exhaled biomarker gases, and perspectives/strategies to realize breath analysis on a chip for disease diagnosis are discussed based on the concurrent design of high-performance sensing materials and miniaturized pretreatment components. Carbon-based sensing materials that show relatively high responses to NO and NH₃ at low or mildly raised temperatures can be applied to the diagnosis of asthma and renal disease. Halitosis can be diagnosed by employing sensing or additive materials such as CuO and Mo that have high chemical affinities for H₂S, while catalyst-loaded metal oxide nanostructure sensors or their arrays have been used to diagnose diabetes via the selective detection of acetone or by pattern recognition of sensor signals. For the ultimate miniaturization of a breath-analysis system into a tiny chip, preconditioning that includes preconcentration, dehumidification, and flow sensing needs to be either improved through the design of gas/moisture adsorbents or removed/simplified through the design of highly sensitive sensing materials that are less impervious to interference from humidity and temperature. Moreover, an abundant sensing library needs to be provided for the diagnosis of diseases (e.g. lung cancer) that are associated with multiple biomarker gases and for finding new methods to diagnose other diseases. For this aim, p-type oxide semiconductors with high catalytic activities, as well as combinatorial approaches, can be considered for the development of sensing materials that detect less-reactive large molecules, and high-throughput screening, respectively. Selectivity for a specific biomarker gas will simplify the system further. Breath analysis on a tiny chip using semiconductor chemiresistors with ultralow power consumption that is connected to the 'Internet of Things' will pave new roads for disease diagnosis and patient monitoring.

Assessing individual performance and maintaining breath sample integrity in biomedical detection dogs

In empirical tests of biomedical detection dogs, exhaled breath samples are often used because breath contains volatile organic compounds that can signal metabolic states, infection, or disease. However, in studies that present dogs with breath samples, results show a notable degree of variability both between and within studies. Differing protocols for the collection and storage of exhaled breath samples may contribute to this observed variability. The goal of the current study was therefore to test whether there was a difference in the detectability of breath samples collected using silicone-coated versus uncoated cotton balls. This was tested in two experiments. In the first experiment, breath samples were prepared using both silicone-coated and uncoated cotton balls, which were then left exposed to the surrounding air. Four dogs' detection of the samples was tested using a cued, three alternative forced choice (3AFC) procedure at regular intervals up to two hours after the samples were prepared. The results of Experiment 1 showed that the dogs' performance was above chance and there was no significant difference in the dogs' detection of the breath samples across conditions. In the second experiment, a series of breath samples were prepared and stored for one, two, three, and four week periods. The same four dogs' ability to detect the breath samples was tested each week using the same cued 3AFC procedure. The results of Experiment 2 showed that when silicone-coated cotton balls were used, all four dogs could detect the breath samples at above chance levels after the samples were stored for three weeks, and two dogs could detect the samples that were stored for four weeks. When the dogs were tested on their ability to detect the breath samples prepared using uncoated cotton, two dogs' performance fell to below chance levels at one week of storage time, while the other two dogs could detect the breath samples at above chance levels after the samples were stored for four weeks. Taken together, the results of the two experiments illustrate that silicone-coated cotton balls do not improve detectability of breath samples within two hours, but can greatly improve the detectability of breath samples stored over longer periods of time. Since the use of silicone-coated cotton balls only improved the detectability of the breath samples for two of the four dogs, these results highlight the importance of examining individual differences in dogs' performance. Furthermore, we argue that, given the inherent differences in olfactory ability across dogs, widespread use of silicone-coated cotton balls for the collection of breath samples would increase the pool of testable dogs for biomedical detection studies and would decrease the degree of variability both within and between studies.

Analytical methodologies for broad metabolite coverage of exhaled breath condensate

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.

Diet-derived changes by sourdough-fermented rye bread in exhaled breath aspiration ion mobility spectrometry profiles in individuals with mild gastrointestinal symptoms

The potential of utilising exhaled breath volatile organic compound (VOC) profiles in studying diet-derived metabolic changes was examined. After a four-week initial diet period with white wheat bread (WW), seven participants received in randomised order high-fibre diets containing sourdough whole grain rye bread (WGR) or white wheat bread enriched with bioprocessed rye bran (WW + BRB), both for 4 weeks. Alveolar exhaled breath samples were analysed with ChemPro^®100i analyser (Environics OY, Mikkeli, Finland) at the end of each diet period in fasting state and after a standardised meal. The AIMS signal intensities in fasting state were different after the WGR diet as compared to other diets. The result suggests that WGR has metabolic effects not completely explained by the rye fibre content of the diet. This study encourages to utilise the exhaled breath VOC profile analysis as an early screening tool in studying physiological functionality of foods.

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

A Portable Real-Time Ringdown Breath Acetone Analyzer: Toward Potential Diabetic Screening and Management

Breath analysis has been considered a suitable tool to evaluate diseases of the respiratory system and those that involve metabolic changes, such as diabetes. Breath acetone has long been known as a biomarker for diabetes. However, the results from published data by far have been inconclusive regarding whether breath acetone is a reliable index of diabetic screening. Large variations exist among the results of different studies because there has been no “best-practice method” for breath-acetone measurements as a result of technical problems of sampling and analysis. In this mini-review, we update the current status of our development of a laser-based breath acetone analyzer toward real-time, one-line diabetic screening and a point-of-care instrument for diabetic management. An integrated standalone breath acetone analyzer based on the cavity ringdown spectroscopy technique has been developed. The instrument was validated by using the certificated gas chromatography-mass spectrometry. The linear fittings suggest that the obtained acetone concentrations via both methods are consistent. Breath samples from each individual subject under various conditions in total, 1257 breath samples were taken from 22 Type 1 diabetic (T1D) patients, 312 Type 2 diabetic (T2D) patients, which is one of the largest numbers of T2D subjects ever used in a single study, and 52 non-diabetic healthy subjects. Simultaneous blood glucose (BG) levels were also tested using a standard diabetic management BG meter. The mean breath acetone concentrations were determined to be 4.9 ± 16 ppm (22 T1D), and 1.5 ± 1.3 ppm (312 T2D), which are about 4.5 and 1.4 times of the one in the 42 non-diabetic healthy subjects, 1.1 ± 0.5 ppm, respectively. A preliminary quantitative correlation (R = 0.56, p < 0.05) between the mean individual breath acetone concentration and the mean individual BG levels does exist in 20 T1D subjects with no ketoacidosis. No direct correlation is observed in T1D subjects, T2D subjects, and healthy subjects. The results from a relatively large number of subjects tested indicate that an elevated mean breath acetone concentration exists in diabetic patients in general. Although many physiological parameters affect breath acetone, under a specifically controlled condition fast (<1 min) and portable breath acetone measurement can be used for screening abnormal metabolic status including diabetes, for point-of-care monitoring status of ketone bodies which have the signature smell of breath acetone, and for breath acetone related clinical studies requiring a large number of tests.

Fiber content of diet affects exhaled breath volatiles in fasting and postprandial state in a pilot crossover study

Our pilot study examined the potential of exhaled breath analysis in studying the metabolic effects of dietary fiber (DF). We hypothesized that a high-fiber diet (HFD) containing whole grain rye changes volatile organic compound (VOC) levels in exhaled breath and that consuming a single meal affects these levels. Seven healthy men followed a week-long low-fiber diet (17 g/d) and HFD (44 g/d) in a randomized crossover design. A test meal containing 50 g of the available carbohydrates from wheat bread was served as breakfast after each week. Alveolar exhaled breath samples were analyzed at fasting state and 30, 60, and 120 minutes after this meal parallel to plasma glucose, insulin, and serum lipids. We used solid-phase microextraction and gas chromatography-mass spectrometry for detecting changes in 15 VOCs. These VOCs were acetone, ethanol, 1-propanol, 2-propanol, 1-butanol, acetic acid, propionic acid, butyric acid, valeric acid, isovaleric acid, 2-methylbutyric acid, hexanoic acid, acetoin, diacetyl, and phenol. Exhaled breath 2-methylbutyric acid in the fasting state and 1-propanol at 120 minutes decreased (P = .091 for both) after an HFD. Ingestion of the test meal increased ethanol, 1-propanol, acetoin, propionic acid, and butyric acid levels while reducing acetone, 1-butanol, diacetyl, and phenol levels. Both DF diet content and having a single meal affected breathVOCs. Exploring exhaled breath further could help to develop tools for monitoring the metabolic effects of DF.

Microextraction techniques in breath biomarker analysis

Breath volatile organic compound analysis may open a non-invasive window onto (patho)physiological and metabolic processes in the body. Breath tests require controlled sampling with respect to different breath phases and on-site and point-of-care applicability. Microextraction techniques such as solid phase microextraction (SPME) or needle-trap microextraction (NTME) meet these requirements. Small sample volumes and fast and controlled sample preparation combine on-site sampling and pre-concentration in one step. Detection limits in the low ppbV range and fast and simple processing facilitate the application of distribution-based SPME for screening and targeted analysis. Exhaustive NTME has shown further advantages such as fast and automated sampling, improved stability and reproducibility with improved detection limits. Combinations of different sorbents and thermal expansion desorption have shown most promising properties when applied to water saturated breath samples. This article addresses major challenges and advantages of microextraction techniques in breath analysis. Important progress, current applications and future trends are discussed.

Oxidative stress and volatile organic compounds: interplay in pulmonary, cardio-vascular, digestive tract systems and cancer

Oxidative stress (OS) can be defined as an imbalance between antioxidant systems and various pro-oxidants. This loss of balance is closely associated with initiation and development of a wide range of systemic or organ specific diseases.

Exhaled breath of healthy humans contains a large number of volatile organic compounds (VOCs) derived from cellular metabolism, released by microorganisms or taken up from the environment. Qualitative or quantitative changes in their composition are associated with diseases and various pathological conditions, also characterized by increased production of reactive oxygen species (ROS), such as superoxide radical, hydrogen peroxide, hydroxyl anion, peroxinitrite, etc. Several volatile organic compounds such as ethane and pentane are direct end-products of the reaction of ROS with various biological compounds (e.g., lipid peroxidation, DNA or protein damage). Being able to accurately identify ROS-generated VOCs could be of particular importance in devising sensitive tests that can diagnose and follow-up oxidative stress-related diseases.

This review describes current knowledge on the associations between oxidative stress and free radicals and the release of several marker volatile organic compounds in a number of diseases. A special focus will be placed on such VOCs in the cardiovascular pathologies, pulmonary diseases and gastro-intestinal tract affections.

SIFT-MS and FA-MS methods for ambient gas phase analysis: developments and applications in the UK

The origins of SIFT created to study interstellar chemistry and SIFT-MS developed for ambient gas and exhaled breath analysis and the UK centres in which these techniques are being exploited.

Exhaled breath analysis using electronic nose in cystic fibrosis and primary ciliary dyskinesia patients with chronic pulmonary infections

The current diagnostic work-up and monitoring of pulmonary infections may be perceived as invasive, is time consuming and expensive. In this explorative study, we investigated whether or not a non-invasive exhaled breath analysis using an electronic nose would discriminate between cystic fibrosis (CF) and primary ciliary dyskinesia (PCD) with or without various well characterized chronic pulmonary infections. We recruited 64 patients with CF and 21 with PCD based on known chronic infection status. 21 healthy volunteers served as controls. An electronic nose was employed to analyze exhaled breath samples. Principal component reduction and discriminant analysis were used to construct internally cross-validated receiver operator characteristic (ROC) curves. Breath profiles of CF and PCD patients differed significantly from healthy controls p = 0.001 and p = 0.005, respectively. Profiles of CF patients having a chronic P. aeruginosa infection differed significantly from to non-chronically infected CF patients p = 0.044. We confirmed the previously established discriminative power of exhaled breath analysis in separation between healthy subjects and patients with CF or PCD. Furthermore, this method significantly discriminates CF patients suffering from a chronic pulmonary P. aeruginosa (PA) infection from CF patients without a chronic pulmonary infection. Further studies are needed for verification and to investigate the role of electronic nose technology in the very early diagnostic workup of pulmonary infections before the establishment of a chronic infection.

Micropreconcentrator in LTCC Technology with Mass Spectrometry for the Detection of Acetone in Healthy and Type-1 Diabetes Mellitus Patient Breath

Breath analysis has long been recognized as a potentially attractive method for the diagnosis of several diseases. The main advantage over other diagnostic methods such as blood or urine analysis is that breath analysis is fully non-invasive, comfortable for patients and breath samples can be easily obtained. One possible future application of breath analysis may be the diagnosing and monitoring of diabetes. It is, therefore, essential, to firstly determine a relationship between exhaled biomarker concentration and glucose in blood as well as to compare the results with the results obtained from non-diabetic subjects. Concentrations of molecules which are biomarkers of diseases’ states, or early indicators of disease should be well documented, i.e., the variations of abnormal concentrations of breath biomarkers with age, gender and ethnic issues need to be verified. Furthermore, based on performed measurements it is rather obvious that analysis of exhaled acetone as a single biomarker of diabetes is unrealistic. In this paper, the author presents results of his research conducted on samples of breath gas from eleven healthy volunteers (HV) and fourteen type-1 diabetic patients (T1DM) which were collected in 1-l SKC breath bags. The exhaled acetone concentration was measured using mass spectrometry (HPR-20 QIC, Hiden Analytical, Warrington, UK) coupled with a micropreconcentrator in LTCC (Low Temperature Cofired Ceramic). However, as according to recent studies the level of acetone varies to a significant extent for each blood glucose concentration of single individuals, a direct and absolute relationship between blood glucose and acetone has not been proved. Nevertheless, basing on the research results acetone in diabetic breath was found to be higher than 1.11 ppmv, while its average concentration in normal breath was lower than 0.83 ppmv.

Detection of volatile malodorous compounds in breath: current analytical techniques and implications in human disease

For the last few decades intense scientific research has been placed on the relationship between trace substances found in exhaled breath such as volatile organic compounds (VOC) and a wide range of local or systemic diseases. Although currently there is no general consensus, results imply that VOC have a different profile depending on the organ or disease that generates them. The association between a specific pathology and exhaled breath odor is particularly evident in patients with medical conditions such as liver, renal or oral diseases. In other cases the unpleasant odors can be associated with the whole body and have a genetic underlying cause. The present review describes the current advances in identifying and quantifying VOC used as biomarkers for a number of systemic diseases. A special focus will be placed on volatiles that characterize unpleasant breath 'fingerprints' such as fetor hepaticus; uremic fetor; fetor ex ore or trimethylaminuria.

Breath analysis in disease diagnosis: methodological considerations and applications

Breath analysis is a promising field with great potential for non-invasive diagnosis of a number of disease states. Analysis of the concentrations of volatile organic compounds (VOCs) in breath with an acceptable accuracy are assessed by means of using analytical techniques with high sensitivity, accuracy, precision, low response time, and low detection limit, which are desirable characteristics for the detection of VOCs in human breath. "Breath fingerprinting", indicative of a specific clinical status, relies on the use of multivariate statistics methods with powerful in-built algorithms. The need for standardisation of sample collection and analysis is the main issue concerning breath analysis, blocking the introduction of breath tests into clinical practice. This review describes recent scientific developments in basic research and clinical applications, namely issues concerning sampling and biochemistry, highlighting the diagnostic potential of breath analysis for disease diagnosis. Several considerations that need to be taken into account in breath analysis are documented here, including the growing need for metabolomics to deal with breath profiles.

Laser-based method and sample handling protocol for measuring breath acetone

A robust method is demonstrated to measure acetone in human breath at sub parts-per-million by volume (ppmv) concentrations using diode laser cavity enhanced absorption spectroscopy. The laser operates in the near-infrared at about 1690 nm probing overtone transitions in acetone in a spectral region relatively free from interference from common breath species such as CO2, water, and methane. Using an optical cavity with a length of 45 cm, bound by mirrors of 99.997% reflectivity, a limit of detection of ∼180 parts-per-billion by volume (ppbv) (1σ) of breath acetone is achieved. The method is validated with measurements made with an ion-molecule reaction mass spectrometer. A technique to calibrate the optical cavity mirror reflectivity using a temperature dependent water vapor source is also described.

Exhaled breath analysis by electronic nose in airways disease. Established issues and key questions

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test.

Detection of volatile organic compounds as biomarkers in breath analysis by different analytical techniques

Breath is a rich mixture containing numerous volatile organic compounds at trace amounts (ppbv–pptv level) such as: hydrocarbons, alcohols, ketones, aldehydes, esters or heterocycles. The presence of some of them depends on health status. Therefore, breath analysis might be useful for clinical diagnostics, therapy monitoring and control of metabolic or biochemical cell cycle products. This Review presents an update on the latest developments in breath analysis applied to diagnosing different diseases with the help of high-quality equipment. Efforts were made to fully and accurately describe traditional and modern techniques used to determine the components of breath. The techniques were compared in terms of design, function and also detection limit of different volatile organic compounds. GC with different detectors, MS, optical sensor and laser spectroscopic detection techniques are also discussed.

Monitoring states of altered carbohydrate metabolism via breath analysis: are times ripe for transition from potential to reality?

PURPOSE OF REVIEW

To introduce the potential of breath analysis as a diagnostic or monitoring tool in diabetes.

RECENT FINDINGS

Blood testing for plasma glucose and other metabolic variables is the base for the diagnosis and management of diabetes, whose two main types (type 1 and type 2, T1DM, T2DM) are projected to affect 450 million by 2030. As blood testing is often uncomfortable, painful, costly, and in some situations unreliable, the quest for alternative, noninvasive methods has been ongoing for decades. Breath analysis has emerged as an ideal alternative as sample collection is easy, painless, flexible, noninvasive, practical, and inexpensive. No single exhaled gas can reflect systemic glucose concentrations. Multiple gases, however, have been linked to various aspects of glucose metabolism, and integrated analysis of their simultaneous profiles during prolonged glycemic fluctuations has yielded accurate predictions of plasma values, building expectation that a clinically usable breath-based glucometer may be developed within a few years.

SUMMARY

While prototypes of hand-held breath testing glucometers may still be several years away, current research shows the imminent promise of this methodology and the widening support for its development.

On the features, successes and challenges of selected ion flow tube mass spectrometry

The major features of the selected ion flow tube mass spectrometry (SIFT-MS) analytical method that was conceived and designed for the analysis, in real time, of air obviating sample collections into bags or extraction by pre-concentration of trace compounds onto surfaces are reviewed. The unique analytical capabilities of SIFT-MS for ambient analysis are stressed that allow quantification of volatile organic and inorganic compounds directly from the measurement of physical parameters without the need for regular instrumental calibration using internal or external standards. Then, emphasis is placed on the challenging real-time accurate analysis of single exhalations of humid breath, which is now achieved and readily facilitates wider applications of SIFT-MS in other fields where trace gas analysis has value. The quality of the data obtained by SIFT-MS is illustrated by the quantification of some exhaled breath metabolites that are of immediate relevance to physiology and medicine, including that of hydrogen cyanide in the breath of patients with cystic fibrosis. The current status of SIFT-MS is revealed by a form of a strengths, weakness, opportunities and threats (SWOT) analysis intended to present an objective view of this analytical technique and the likely way forward towards its further development and application.

Demonstration of a mid-infrared cavity enhanced absorption spectrometer for breath acetone detection

A high-resolution absorption spectrum of gaseous acetone near 8.2 μm has been taken using both Fourier transform and quantum cascade laser (QCL)-based infrared spectrometers. Absolute absorption cross sections within the 1215-1222 cm(-1) range have been determined, and the spectral window around 1216.5 cm(-1) (σ = 3.4 × 10(-19) cm(2) molecule(-1)) has been chosen for monitoring trace acetone in exhaled breath. Acetone at sub parts-per-million (ppm) levels has been measured in a breath sample with a precision of 0.17 ppm (1σ) by utilizing a cavity enhanced absorption spectrometer constructed from the QCL source and a linear, low-volume, optical cavity. The use of a water vapor trap ensured the accuracy of the results, which have been corroborated by mass spectrometric measurements.

Machine learning applied to chemical analysis: sensing multiple biomarkers in simulated breath using a temperature-pulsed electronic-nose

Monitoring of chemical species in breath offers an approach for the detection of disease and other conditions that cause homeostatic imbalance. Here, we demonstrate the use of microsensor-based devices for detecting select biomarkers in simulated exhaled breath as a step toward enabling fast and inexpensive breath-screening technology. Microhotplate elements functionalized with three chemiresistive metal-oxide films (SnO(2), In(2)O(3), and CuO) were used to acquire data in simulated breath containing single targets [(5 to 20) μmol/mol ammonia, methanol, and acetone], as well as mixtures of those species. All devices were operated with programmed thermal cycles featuring rapid temperature excursions, during which film resistances were measured. Material-specific temperature programs were optimized to achieve temperature-dependent metal-oxide sensing film conductance levels and target selectivity. A supervised hierarchical machine-learning algorithm using linear discriminant analysis for dimensional reduction of sensing data and discrimination was developed. This algorithm was employed in the classification and quantification of biomarkers. This approach to microsensor data collection and processing was successful in classifying and quantifying the model biomarkers in validation-set mixtures.

Human breath gas analysis in the screening of gestational diabetes mellitus

BACKGROUND

We present a pilot study on the feasibility of the application and advantages of online, noninvasive breath gas analysis (BGA) by proton transfer reaction quadrupole mass spectrometry for the screening of gestational diabetes mellitus (GDM) in 52 pregnant women by means of an oral glucose tolerance test (OGTT).

SUBJECTS AND METHODS

We collected and identified samples of end-tidal breath gas from patients during OGTT. Time evolution parameters of challenge-responsive volatile organic compounds (VOCs) in human breath gas were estimated. Multivariate analysis of variance and permutation analysis were used to assess feasibility of BGA as a diagnostic tool for GDM.

RESULTS

Standard OGTT diagnosis identified pregnant women as having GDM (n = 8), impaired glucose tolerance (n = 12), and normal glucose tolerance (n = 32); a part of this latter group was further subdivided into a "marginal" group (n = 9) because of a marginal high 1-h or 2-h OGTT value. We observed that OGTT diagnosis (four metabolic groups) could be mapped into breath gas data. The time evolution of oxidation products of glucose and lipids, acetone metabolites, and thiols in breath gas after a glucose challenge was correlated with GDM diagnosis (P = 0.035). Furthermore, basal (fasting) values of dimethyl sulfide and values of methanol in breath gas were inversely correlated with phenotype characteristics such as homeostasis model assessment of insulin resistance index (R = -0.538; P = 0.0002, P(corrected) = 0.0034) and pregestational body mass index (R = -0.433; P = 0.0013, P(corrected) = 0.022).

CONCLUSIONS

Noninvasive BGA in challenge response studies was successfully applied to GDM diagnosis and offered an insight into metabolic pathways involved. We propose a new approach to the identification of diagnosis thresholds for GDM screening.