Breath acetone analysis with miniaturized sample preparation device: In-needle preconcentration and subsequent determination by gas chromatography–mass spectroscopy

Microextraction techniques for occupational biological monitoring: Basic principles, current applications and future perspectives

The application of green microextraction techniques (METs) is constantly being developed in different areas including pharmaceutical, forensic, food and environmental analysis. However, they are less used in biological monitoring of workers in occupational settings. Developing valid extraction methods and analytical techniques for the determination of occupational indicators plays a critical role in the management of workers' exposure to chemicals in workplaces. Microextraction techniques have become increasingly important because they are inexpensive, robust and environmentally friendly. This study aimed to provide a comprehensive review and interpret the applications of METs and novel sorbents and liquids in biological monitoring. Future perspectives and occupational indicators that METs have not yet been developed for are also discussed.

A Novel Acetone Sensor for Body Fluids

Ketones are well-known biomarkers of fat oxidation produced in the liver as a result of lipolysis. These biomarkers include acetoacetic acid and β-hydroxybutyric acid in the blood/urine and acetone in our breath and skin. Monitoring ketone production in the body is essential for people who use caloric intake deficit to reduce body weight or use ketogenic diets for wellness or therapeutic treatments. Current methods to monitor ketones include urine dipsticks, capillary blood monitors, and breath analyzers. However, these existing methods have certain disadvantages that preclude them from being used more widely. In this work, we introduce a novel acetone sensor device that can detect acetone levels in breath and overcome the drawbacks of existing sensing approaches. The critical element of the device is a robust sensor with the capability to measure acetone using a complementary metal oxide semiconductor (CMOS) chip and convenient data analysis from a red, green, and blue deconvolution imaging approach. The acetone sensor device demonstrated sensitivity of detection in the micromolar-concentration range, selectivity for detection of acetone in breath, and a lifetime stability of at least one month. The sensor device utility was probed with real tests on breath samples using an established blood ketone reference method.

Growth and Characterization of Sputtered InAlN Nanorods on Sapphire Substrates for Acetone Gas Sensing

The demand for highly sensitive and selective gas sensors has been steadily increasing, driven by applications in various fields such as environmental monitoring, healthcare, and industrial safety. In this context, ternary alloy indium aluminum nitride (InAlN) semiconductors have emerged as a promising material for gas sensing due to their unique properties and tunable material characteristics. This work focuses on the fabrication and characterization of InAlN nanorods grown on sapphire substrates using an ultra-high vacuum magnetron sputter epitaxy with precise control over indium composition and explores their potential for acetone-gas-sensing applications. Various characterization techniques, including XRD, SEM, and TEM, demonstrate the structural and morphological insights of InAlN nanorods, making them suitable for gas-sensing applications. To evaluate the gas-sensing performance of the InAlN nanorods, acetone was chosen as a target analyte due to its relevance in medical diagnostics and industrial processes. The results reveal that the InAlN nanorods exhibit a remarkable sensor response of 2.33% at 600 ppm acetone gas concentration at an operating temperature of 350 °C, with a rapid response time of 18 s. Their high sensor response and rapid response make InAlN a viable candidate for use in medical diagnostics, industrial safety, and environmental monitoring.

Rapid and non-invasive diagnosis of type 2 diabetes through sniffing urinary acetone by a proton transfer reaction mass spectrometry

Urinary acetone in urine is produced from fat metabolism in human body, which can be accelerated in diabetic patients because of insufficient utilization and storage of glucose. In this study, we tried to develop a novel diagnosis method of type 2 diabetes (T2D) through sniffing urinary acetone by a proton transfer reaction mass spectrometry (PTR-MS). A total of 180 T2D patients and 180 healthy volunteers were recruited from three hospitals for multicenter study. Urine samples were collected in the morning when donators were fasting and stored in glass bottles. Acetone in the headspace of these bottles was qualitatively and quantitatively detected by the PTR-MS in 8 h. Using a threshold of 690.1 ppbv, a diagnostic model was established using urinary acetone with an accuracy of 81.3% (sensitivity: 73.3%, specificity: 89.3%) in hospital Ⅰ. In the verification studies, the accuracies were 92.5% (sensitivity: 88.7%, specificity: 96.2%) in hospital Ⅱ and 83.7% (sensitivity: 76.9%, specificity: 90.4%) in hospital Ⅲ, respectively. The accuracy is comparable to that of clinically used diagnosis methods, fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), and glycosylated hemoglobin A1c (HbA1c) test. The sensitivity for 35 newly diagnosed patients was 85.7%. The newly developed technology is completely non-invasive and much more rapid than clinical FPG, OGTT, and HbA1c tests. It has a promising prospect in clinical use. But the applicability in different human races still need more validations.

A metal-organic framework loaded paper-based chemiluminescence sensor for trace acetone detection in exhaled breath

Trace acetone determination in breath can be regarded as a noninvasive method for diagnosis of diabetes. Here, a paper-based CL gas sensor combined with UiO-66 as the preconcentrator was established for sensitive detection of trace acetone in exhaled breath. UiO-66 with excellent adsorption performance and unique water stability was used for the adsorption and enrichment of acetone gas under high humidity conditions in exhaled breath. As acetone can remarkably increase the chemiluminescence (CL) of the 2,4-dinitrophenylhydrazine (DNPH)-potassium permanganate (KMnO₄) system, a sensitive CL device based on a paper substrate for trace acetone detection was established and the detection limit was 0.03 ppm. The fabricated method was used to assess the content of trace acetone in exhaled breath with satisfactory recoveries of 90-110%. It is expected to realize the noninvasive determination of acetone for diabetic patients in exhaled breath.

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

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

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.

Breath profile as composite biomarkers for lung cancer diagnosis

OBJECTIVES

Lung cancer is continuously the leading cause of cancer related death, resulting from the lack of specific symptoms at early stage. A large-scale screening method may be the key point to find asymptomatic patients, leading to the reduction of mortality.

METHODS

An alternative method combining breath test and a machine learning algorithm is proposed. 236 breath samples were analyzed by TD-GCMS. Breath profile of each sample is composed of 308 features extracted from chromatogram. Gradient boost decision trees algorithm was employed to recognize lung cancer patients. Bootstrap is performed to simulate real diagnostic practice, with which we evaluated the confidence of our methods.

RESULTS

An accuracy of 85 % is shown in 6-fold cross validations. In statistical bootstrap, 72 % samples are marked as "confident", and the accuracy of confident samples is 93 % throughout the cross validations.

CONCLUSION

We have proposed such a non-invasive, accurate and confident method that might contribute to large-scale screening of lung cancer. As a consequence, more asymptomatic patients with early lung cancer may be detected.

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review

Diabetes mellitus, commonly measured through an invasive process which although is accurate, has manifold drawbacks especially when multiple reading are required at regular intervals. Accordingly, there is a need to develop a dependable non-invasive diabetes detection technique. Recent studies have observed that other human serums such as tears, saliva, urine and breath indicate the presence of glucose in them. These parameters open quite a few ways for non-invasive blood glucose level prediction. The analysis of a persons breath poses as a good non-invasive technique to monitor the glucose levels. It is seen that in breath, there are many bio-markers and monitoring the levels of these bio-markers indicate the possibility of various chronic diseases. Among these bio-markers, acetone a volatile organic compound found in breath has shown a good correlation to the glucose levels present in blood. Therefore, by evaluating the acetone levels in breath samples it is possible to monitor diabetes non-invasively. This paper reviews the various approaches and sensory techniques used to monitor diabetes though human breath samples.

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.

Novel 1D/2D KWO/Ti3C2Tx Nanocomposite-Based Acetone Sensor for Diabetes Prevention and Monitoring

The acetone content in the exhaled breath of individuals as a biomarker of diabetes has become widely studied as a non-invasive means of quantifying blood glucose levels. This calls for development of sensors for the quantitative analysis of trace concentration of acetone, which is presents in the human exhaled breath. Traditional gas detection systems, such as the Gas Chromatography/Mass Spectrometry and several types of chemiresistive sensors are currently being used for this purpose. However, these systems are known to have limitations of size, cost, response time, operating conditions, and consistent accuracy. An ideal breath acetone sensor should provide solutions to overcome the above limitations and provide good stability and reliability. It should be a simple and portable detection system of good sensitivity, selectivity that is low in terms of both cost and power consumption. To achieve this goal, in this paper, we report a new sensing nanomaterial made by nanocomposite, 1D KWO (K2W7O22) nanorods/2D Ti3C2Tx nanosheets, as the key component to design an acetone sensor. The preliminary result exhibits that the new nanocomposite has an improved response to acetone, with 10 times higher sensitivity comparing to KWO-based sensor, much better tolerance of humidity interference and enhanced stability for multiple months. By comparing with other nanomaterials: Ti3C2, KWO, and KWO/Ti3C2Tx nanocomposites with variable ratio of KWO and Ti3C2Tx from 1:1, 1:2, 1:5, 2:1, 4:1, and 9:1, the initial results confirm the potential of the novel KWO/Ti3C2 (2:1) nanocomposite to be an excellent sensing material for application in sensitive and selective detection of breath acetone for diabetics health care and prevention.

Recent advances in breath analysis to track human health by new enrichment technologies

Detection of biomarkers in exhaled breath has been gaining increasing attention as a tool for diagnosis of specific diseases. However, rapid and accurate quantification of biomarkers associated with specific diseases requires the use of analytical methods capable of fast sampling and preconcentration from breath matrix. In this regard, solid phase microextraction and needle trap technology are becoming increasingly popular in the field of breath analysis due to the unique benefits imparted by such methods, such as the integration of sampling, extraction, and preconcentration in a single step. This review discusses recent advances in breath analysis using these sample preparation techniques, providing a summary of recent developments of analytical methods based on breath volatile organic compounds analysis, including the successful identification of various biomarkers related to human diseases.

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 .

Factors influencing breath analysis results in patients with diabetes mellitus

Breath analysis is used to detect the composition of exhaled gas. As a quick and non-invasive detection method, breath analysis provides deep insights into the progression of various kinds of diseases, especially those with metabolism disorders. Abundant information on volatile compounds in diabetic patients has been studied in numerous articles in the literature. However, exhaled gas in diabetic patients can be altered by various complications. So far, little attention has been paid to this alteration. In our paper, we found that under air pollution conditions, diabetic patients exhale more nitric oxide. Diabetic patients with heart failure exhale more acetone than those without heart failure. After ¹³C-labeled glucose intake, patients infected with Helicobacter pylori exhaled more ¹³C and less ¹⁸O than those without infection. Exhalation with chronic kidney disease changes volatile organic compounds on a large scale. Diabetic patients with ketoacidosis exhale more acetone than those without ketoacidosis. Some specific volatile organic compounds also emanate from diabetic feet. By monitoring breath frequency, diabetic patients with obstructive sleep apnea syndrome exhibit a unique breath pattern and rhythm as compared with other diabetic patients, and sleep apnea is prevalent among diabetic patients. In addition to clinical findings, we analyzed the underlying mechanisms at the levels of molecules, cells and whole bodies, and provided suggestions for further studies.

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.

On-line monitoring human breath acetone during exercise and diet by proton transfer reaction mass spectrometry

Aim: This study aims to develop a method for monitoring fat loss by detection of breath acetone. Methods: A new method combining direct breath sampling system and proton transfer reaction MS (PTR-MS) was developed for on-line detection of breath acetone. The breath acetone of 272 volunteers was detected respectively when exercise or diet. Results: Exercises perennially can make the breath acetone increase by 40–130%. Dinner fasting for 1 week can make it increase by 140%. Conclusion: Exercise and diet are two useful methods to lose fat. Determination of breath acetone concentration using the direct breath sampling system-proton transfer reaction MS can help design scheme of exercise and diet for losing weight.

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.

Highly Sensitive Acetone Gas Sensor Based on g-C₃N₄ Decorated MgFe₂O₄ Porous Microspheres Composites

The g-C₃N₄ decorated magnesium ferrite (MgFe₂O₄) porous microspheres composites were successfully obtained via a one-step solvothermal method. The structure and morphology of the as-prepared MgFe₂O₄/g-C₃N₄ composites were characterized by the techniques of X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), thermal gravity and differential scanning calorimeter (TG–DSC) and N₂-sorption. The gas sensing properties of the samples were measured and compared with a pure MgFe₂O₄-based sensor. The maximum response of the sensor based on MgFe₂O₄/g-C₃N₄ composites with 10 wt % g-C₃N₄ content to acetone is improved by about 145 times, while the optimum temperature was lowered by 60 °C. Moreover, the sensing mechanism and the reason for improving gas sensing performance were also discussed.

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.

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.

Measurement of breath acetone in patients referred for an oral glucose tolerance test

Breath acetone concentrations were measured in 141 subjects (aged 19-91 years, mean = 59.11 years, standard deviation = 12.99 years), male and female, undergoing an oral glucose tolerance test (OGTT), having been referred to clinic on suspicion of type 2 diabetes. Breath samples were measured using an ion-molecule-reaction mass spectrometer, at the commencement of the OGTT, and after 1 and 2 h. Subjects were asked to observe the normal routine before and during the OGTT, which includes an overnight fast and ingestion of 75 g glucose at the beginning of the routine. Several groups of diagnosis were identified: type 2 diabetes mellitus positive (T2DM), n = 22; impaired glucose intolerance (IGT), n = 33; impaired fasting glucose, n = 14; and reactive hypoglycaemia, n = 5. The subjects with no diagnosis (i.e. normoglycaemia) were used as a control group, n = 67. Distributions of breath acetone are presented for the different groups. There was no evidence of a direct relationship between blood glucose (BG) and acetone measurements at any time during the study (0 h: p = 0.4482; 1 h: p = 0.6854; and 2 h: p = 0.1858). Nor were there significant differences between the measurements of breath acetone for the control group and the T2DM group (0 h: p = 0.1759; 1 h: p = 0.4521; and 2 h: p = 0.7343). However, the ratio of breath acetone at 1 h to the initial breath acetone was found to be significantly different for the T2DM group compared to both the control and IGT groups (p = 0.0189 and 0.011, respectively). The T2DM group was also found to be different in terms of ratio of breath acetone after 1 h to that at 2 h during the OGTT. And was distinctive in that it showed a significant dependence upon the level of BG at 2 h (p = 0.0146). We conclude that single measurements of the concentrations of breath acetone cannot be used as a potential screening diagnostic for T2DM diabetes in this cohort, but monitoring the evolution of breath acetone could open a non-invasive window to aid in the diagnosis of metabolic conditions.

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.

A Novel Medical E-Nose Signal Analysis System

It has been proven that certain biomarkers in people’s breath have a relationship with diseases and blood glucose levels (BGLs). As a result, it is possible to detect diseases and predict BGLs by analysis of breath samples captured by e-noses. In this paper, a novel optimized medical e-nose system specified for disease diagnosis and BGL prediction is proposed. A large-scale breath dataset has been collected using the proposed system. Experiments have been organized on the collected dataset and the experimental results have shown that the proposed system can well solve the problems of existing systems. The methods have effectively improved the classification accuracy.

Significance of Exhaled Breath Test in Clinical Diagnosis: A Special Focus on the Detection of Diabetes Mellitus

Analysis of volatile organic compounds (VOCs) emanating from human exhaled breath can provide deep insight into the status of various biochemical processes in the human body. VOCs can serve as potential biomarkers of physiological and pathophysiological conditions related to several diseases. Breath VOC analysis, a noninvasive and quick biomonitoring approach, also has potential for the early detection and progress monitoring of several diseases. This paper gives an overview of the major VOCs present in human exhaled breath, possible biochemical pathways of breath VOC generation, diagnostic importance of their analysis, and analytical techniques used in the breath test. Breath analysis relating to diabetes mellitus and its characteristic breath biomarkers is focused on. Finally, some challenges and limitations of the breath test are discussed.

Measurement of natural carbon isotopic composition of acetone in human urine

The natural carbon isotopic composition of acetone in urine was measured in healthy subjects using gas chromatography-combustion-isotope ratio mass spectrometry combined with headspace solid-phase microextraction (HS-SPME-GC-C-IRMS). Before applying the technique to a urine sample, we optimized the measurement conditions of HS-SPME-GC-C-IRMS using aqueous solutions of commercial acetone reagents. The optimization enabled us to determine the carbon isotopic compositions within ±0.2 ‰ of precision and ±0.3‰ of error using 0.05 or 0.2 mL of aqueous solutions with acetone concentrations of 0.3-121 mg/L. For several days, we monitored the carbon isotopic compositions and concentrations of acetone in urine from three subjects who lived a daily life with no restrictions. We also monitored one subject for 3 days including a fasting period of 24 h. These results suggest that changes in the availability of glucose in the liver are reflected in changes in the carbon isotopic compositions of urine acetone. Results demonstrate that carbon isotopic measurement of metabolites in human biological samples at natural abundance levels has great potential as a tool for detecting metabolic changes caused by changes in physiological states and disease.

A fully integrated standalone portable cavity ringdown breath acetone analyzer

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

A Negative Correlation Between Blood Glucose and Acetone Measured in Healthy and Type 1 Diabetes Mellitus Patient Breath

BACKGROUND

Exhaled acetone analysis has long been recognized as a supplementary tool for diagnosis and monitoring diabetes, especially type 1 diabetes. It is essential, therefore to determine the relationship between exhaled acetone concentration and glucose in blood. Usually, a direct linear correlation between this both compounds has been expected. However, in some cases we can observe a reverse correlation. When blood glucose was increasing, breath acetone declined.

METHODS

The breath analysis as a supplementary tool for diagnosing and monitoring diabetes makes sense only in case of utilization of portable analyzers. This need has created a market for gas sensors. However, commercially available acetone gas sensors are developed for measuring samples at several tens part per million. The exhaled acetone concentration was measured using commercial acetone gas sensor (TGS 822, 823 Figaro, Arlington Heights, IL, USA Inc) with micropreconcentrator in low temperature cofired ceramics. The reference analyzer-mass spectrometry (HPR-20 QIC, Hiden Analytical, Warrington, UK) was used.

RESULTS

Twenty-two healthy volunteers with no history of any respiratory disease participated in the research, as did 31 patients diagnosed with type 1 diabetes. Respectively, 3 healthy volunteer and 5 type 1 diabetes mellitus subjects with reverse trend were selected. The linear fitting coefficient various from 0.1139 to 0.9573. Therefore, it is necessary to determine the correlation between blood glucose concentrations and under different conditions, for example, insulin levels, as well as correlate the results with clinical tests, for example, Hb1Ac.

CONCLUSIONS

It is well known that the concentration of acetone is strongly influenced by diet, insulin treatment, and so on. Therefore, much more complex analysis with long-term measurements are required. Thus, presented results should be regarded as tentative, and validation studies with the analysis of clinical test and in a large number of patients, including control groups, need to be carried out.

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.

A cross-sectional study of breath acetone based on diabetic metabolic disorders

Breath acetone is a known biomarker for diabetes mellitus in breath analysis. In this work, a cross-sectional study of breath acetone based on clinical metabolic disorders of type 2 diabetes mellitus (T2DM) was carried out. Breath acetone concentrations of 113 T2DM patients and 56 apparently healthy individuals were measured at a single time point. Concentrations varied from 0.22 to 9.41 ppmv (mean 1.75 ppmv) for T2DM, which were significantly higher than those for normal controls (ranged from 0.32 to 1.96 ppmv, mean 0.72 ppmv, p = 0.008). Observations in our work revealed that breath acetone concentrations elevated to different degrees, along with the abnormality of blood glucose, glycated hemoglobin (HbA1c), triglyceride and cholesterol. Breath acetone showed obviously positive correlations with blood ketone and urine ketone. Possible metabolic relations between breath acetone and diabetic disorders were also discussed. This work aimed at giving an overall assessment of breath acetone from the perspective of clinical parameters for type 2 diabetes.

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.

Real-time monitoring of exhaled drugs by mass spectrometry

Future individualized patient treatment will need tools to monitor the dose and effects of administrated drugs. Mass spectrometry may become the method of choice to monitor drugs in real time by analyzing exhaled breath. This review describes the monitoring of exhaled drugs in real time by mass spectrometry. The biological background as well as the relevant physical properties of exhaled drugs are delineated. The feasibility of detecting and monitoring exhaled drugs is discussed in several examples. The mass spectrometric tools that are currently available to analyze breath in real time are reviewed. The technical needs and state of the art for on-site measurements by mass spectrometry are also discussed in detail. Off-line methods, which give support and are an important source of information for real-time measurements, are also discussed. Finally, some examples of drugs that have already been successfully detected in exhaled breath, including propofol, fentanyl, methadone, nicotine, and valproic acid are presented. Real-time monitoring of exhaled drugs by mass spectrometry is a relatively new field, which is still in the early stages of development. New technologies promise substantial benefit for future patient monitoring and treatment.

Optimization of the in-needle extraction device for the direct flow of the liquid sample through the sorbent layer

In-needle extraction was applied for preparation of aqueous samples. This technique was used for direct isolation of analytes from liquid samples which was achieved by forcing the flow of the sample through the sorbent layer: silica or polymer (styrene/divinylbenzene). Specially designed needle was packed with three different sorbents on which the analytes (phenol, p-benzoquinone, 4-chlorophenol, thymol and caffeine) were retained. Acceptable sampling conditions for direct analysis of liquid sample were selected. Experimental data collected from the series of liquid samples analysis made with use of in-needle device showed that the effectiveness of the system depends on various parameters such as breakthrough volume and the sorption capacity, effect of sampling flow rate, solvent effect on elution step, required volume of solvent for elution step. The optimal sampling flow rate was in range of 0.5-2 mL/min, the minimum volume of solvent was at 400 µL level.

Design of a breath analysis system for diabetes screening and blood glucose level prediction

It has been reported that concentrations of several biomarkers in diabetics' breath show significant difference from those in healthy people's breath. Concentrations of some biomarkers are also correlated with the blood glucose levels (BGLs) of diabetics. Therefore, it is possible to screen for diabetes and predict BGLs by analyzing one's breath. In this paper, we describe the design of a novel breath analysis system for this purpose. The system uses carefully selected chemical sensors to detect biomarkers in breath. Common interferential factors, including humidity and the ratio of alveolar air in breath, are compensated or handled in the algorithm. Considering the intersubject variance of the components in breath, we build subject-specific prediction models to improve the accuracy of BGL prediction. A total of 295 breath samples from healthy subjects and 279 samples from diabetic subjects were collected to evaluate the performance of the system. The sensitivity and specificity of diabetes screening are 91.51% and 90.77%, respectively. The mean relative absolute error for BGL prediction is 21.7%. Experiments show that the system is effective and that the strategies adopted in the system can improve its accuracy. The system potentially provides a noninvasive and convenient method for diabetes screening and BGL monitoring as an adjunct to the standard criteria.