Applications of Hadamard transform-gas chromatography/mass spectrometry to the detection of acetone in healthy human and diabetes mellitus patient breath

Coupling Online Size Exclusion Chromatography with Charge Detection-Mass Spectrometry Using Hadamard Transform Multiplexing

Charge detection mass spectrometry (CD-MS) is a powerful technique for the analysis of large, heterogeneous biomolecules. By directly measuring the charge states of individual ions, CD-MS can measure the masses from spectra where conventional deconvolution approaches fail due to the lack of isotopic resolution or distinguishable charge states. However, CD-MS is inherently slow because hundreds or thousands of spectra need to be collected to produce adequate ion statistics. The slower speed of CD-MS complicates efforts to couple it with online separation techniques, which limit the number of spectra that can be acquired during a chromatographic peak. Here, we present the application of Hadamard transform multiplexing to online size exclusion chromatography (SEC) coupled with Orbitrap CD-MS, with a goal of using SEC for separating complex mixtures prior to CD-MS analysis. We developed a microcontroller to deliver pulsed injections from a large sample loop onto a SEC for online CD-MS analysis. Data showed a series of peaks spaced according to the pseudorandom injection sequence, which were demultiplexed with a Hadamard transform algorithm. The demultiplexed data revealed improved CD-MS signals while preserving retention time information. This multiplexing approach provides a general solution to the inherent incompatibilities of online separations and CD-MS detection that will enable a range of applications.

UniChromCD for Demultiplexing Time-Resolved Charge Detection-Mass Spectrometry Data

Charge detection mass spectrometry (CD-MS) enables characterization of large, heterogeneous analytes through the analysis of individual ion signals. Because hundreds to thousands of scans must be acquired to produce adequate ion statistics, CD-MS generally requires long analysis times. The slow acquisition speed of CD-MS complicates efforts to couple it with time-dispersive techniques, such as chromatography and ion mobility, because it is not always possible to acquire enough scans from a single sample injection to generate sufficient ion statistics. Multiplexing methods based on Hadamard and Fourier transforms offer an attractive solution to this problem by improving the duty cycle of the separation while preserving retention/drift time information. However, integrating multiplexing with CD-MS data processing is complex. Here, we present UniChromCD, a new module in the open-source UniDec package that incorporates CD-MS time-domain data processing with demultiplexing tools. Following a detailed description of the algorithm, we demonstrate its capabilities using two multiplexed CD-MS workflows: Hadamard-transform size-exclusion chromatography and Fourier-transform ion mobility. Overall, UniChromCD provides a user-friendly interface for analysis and visualization of time-resolved CD-MS data.

Development of a Multiplexing Injector for Gas Chromatography for the Time-Resolved Analysis of Volatile Emissions from Lithium-Ion Batteries

Multiplex sampling, so far mainly used as a tool for S/N ratio improvement in spectroscopic applications and separation techniques, has been investigated here for its potential suitability for time-resolved monitoring where chromatograms of transient signals are recorded at intervals much shorter than the chromatographic runtime. Different designs of multiplex sample introduction were developed and utilized to analyze lithium-ion battery degradation products under normal or abuse conditions to achieve fast and efficient sample introduction. After comprehensive optimization, measurements were performed on two different GC systems, with either barrier discharge ionization detection (BID) or mass spectrometric detection (MS). Three different injector designs were examined, and modifications in the pertinent hardware components and operational conditions used. The shortest achievable sample introduction time was 50 ms with an interval of 6 s. Relative standard deviations were lower than 4% and 10% for the intra- and inter-day repeatability, respectively. The sample introduction system and column head pressure had to be carefully controlled, as this parameter most critically affects the amount of sample introduced and, thus, detector response. The newly developed sample introduction system was successfully used to monitor volatile degradation products of lithium-ion batteries and demonstrated concentration changes over the course of time of the degradation products (e.g., fluoroethane, acetaldehyde and ethane), as well as for solvents from the battery electrolyte like ethyl carbonate.

Machine-Learning-Aided NO2 Discrimination with an Array of Graphene Chemiresistors Covalently Functionalized by Diazonium Chemistry

Boosted by the emerging need for highly integrated gas sensors in the internet of things (IoT) ecosystems, electronic noses (e-noses) are gaining interest for the detection of specific molecules over a background of interfering gases. The sensing of nitrogen dioxide is particularly relevant for applications in environmental monitoring and precision medicine. Here we present an easy and efficient functionalization procedure to covalently modify graphene layers, taking advantage of diazonium chemistry. Separate graphene layers were functionalized with one of three different aryl rings: 4-nitrophenyl, 4-carboxyphenyl and 4-bromophenyl. The distinct modified graphene layers were assembled with a pristine layer into an e-nose for NO2 discrimination. A remarkable sensitivity to NO2 was demonstrated through exposure to gaseous solutions with NO2 concentrations in the 1-10 ppm range at room temperature. Then, the discrimination capability of the sensor array was tested by carrying out exposure to several interfering gases and analyzing the data through multivariate statistical analysis. This analysis showed that the e-nose can discriminate NO2 among all the interfering gases in a two-dimensional principal component analysis space. Finally, the e-nose was trained to accurately recognize NO2 contributions with a linear discriminant analysis approach, thus providing a metric for discrimination assessment with a prediction accuracy above 95 %.

Smelling the Disease: Diagnostic Potential of Breath Analysis

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

Online mass spectrometry of exhaled breath with a modified ambient ion source

Exhaled breath (EB) may contain metabolites that are closely related to human health conditions. Real time analysis of EB is important to study its true composition, however, it has been difficult. A robust ambient ionization mass spectrometry method using a modified direct analysis in real time (DART) ion source was developed for the online analysis of breath volatiles. The modified DART ion source can provide a confined region for direct sampling, rapid transmission and efficient ionization of exhaled breath. With different sampling methods, offline analysis and near real-time evaluation of exhaled breath were also achieved, and their unique molecular features were characterized. High resolution MS data aided the putative metabolite identification in breath samples, resulting in hundreds of volatile organic compounds being identified in the exhalome. The method was sensitive enough to be used for monitoring the breath feature changes after taking different food and over-the-counter medicine. Quantification was performed for pyridine and valeric acid with fasting and after ingesting different food. The developed method is fast, simple, versatile, and potentially useful for evaluating the true state of human exhaled breath.

A Chemiresistor Sensor Array Based on Graphene Nanostructures: From the Detection of Ammonia and Possible Interfering VOCs to Chemometric Analysis

Sensor arrays are currently attracting the interest of researchers due to their potential of overcoming the limitations of single sensors regarding selectivity, required by specific applications. Among the materials used to develop sensor arrays, graphene has not been so far extensively exploited, despite its remarkable sensing capability. Here we present the development of a graphene-based sensor array prepared by dropcasting nanostructure and nanocomposite graphene solution on interdigitated substrates, with the aim to investigate the capability of the array to discriminate several gases related to specific applications, including environmental monitoring, food quality tracking, and breathomics. This goal is achieved in two steps: at first the sensing properties of the array have been assessed through ammonia exposures, drawing the calibration curves, estimating the limit of detection, which has been found in the ppb range for all sensors, and investigating stability and sensitivity; then, after performing exposures to acetone, ethanol, 2-propanol, sodium hypochlorite, and water vapour, chemometric tools have been exploited to investigate the discrimination capability of the array, including principal component analysis (PCA), linear discriminant analysis (LDA), and Mahalanobis distance. PCA shows that the array was able to discriminate all the tested gases with an explained variance around 95%, while with an LDA approach the array can be trained to accurately recognize unknown gas contribution, with an accuracy higher than 94%.

Targeting biomarkers in the gas phase through a chemoresistive electronic nose based on graphene functionalized with metal phthalocyanines

Electronic noses (e-noses) have received considerable interest in the past decade as they can match the emerging needs of modern society such as environmental monitoring, health screening, and food quality tracking. For practical applications of e-noses, it is necessary to collect large amounts of data from an array of sensing devices that can detect interactions with molecules reliably and analyze them via pattern recognition. The use of graphene (Gr)-based arrays of chemiresistors in e-noses is still virtually missing, though recent reports on Gr-based chemiresistors have disclosed high sensing performances upon functionalization of the pristine layer, opening up the possibility of being implemented into e-noses. In this work, with the aim of creating a robust and chemically stable interface that combines the chemical properties of metal phthalocyanines (M-Pc, M = Fe, Co, Ni, Zn) with the superior transport properties of Gr, an array of Gr-based chemiresistor sensors functionalized with drop-cast M-Pc thin layers has been developed. The sensing capability of the array was tested towards biomarkers for breathomics application, with a focus on ammonia (NH₃). Exposure to NH₃ has been carried out drawing the calibration curve and estimating the detection limit for all the sensors. The discrimination capability of the array has then been tested, carrying out exposure to several gases (hydrogen sulfide, acetone, ethanol, 2-propanol, water vapour and benzene) and analysing the data through principal component analysis (PCA). The PCA pattern recognition results show that the developed e-nose is able to discriminate all the tested gases through the synergic contribution of all sensors.

Hollow Mesoporous SnO2/Zn2SnO4 Heterojunction and RGO Decoration for High-Performance Detection of Acetone

In this article, the synthesis procedure and sensing properties toward acetone of rGO-HM-SnO₂/Zn₂SnO₄ composites with a hollow mesoporous structure are presented comprehensively. The rGO-HM-SnO₂/Zn₂SnO₄ heterojunction structure is prepared through a self-sacrificial template strategy with a concise acid-assisted etching method. The as-prepared hollow mesoporous architectures are investigated by SEM, TEM, and HRTEM. The phase structure and valence state are also characterized by XRD and XPS, respectively. It is obvious that the hollow mesoporous architecture affords a large specific surface area, which can provide more reaction active sites of sensing materials significantly. Compared to the initial SnO₂/Zn₂SnO₄ composites, the gas sensor fabricated by rGO-HM-SnO₂/Zn₂SnO₄ shows the best gas-sensing properties, and the response value toward 100 ppm acetone is as high as 107 at 200 °C. Moreover, the rGO-HM-SnO₂/Zn₂SnO₄ sensing material reveals excellent properties of shorter response-recovery times and higher long-term stability. This excellent performance can be ascribed to the synergistic effect of the hollow mesoporous n-n heterojunction and abundant-defect rGO. The relevant sensing mechanism of rGO-HM-SnO₂/Zn₂SnO₄ sensing materials is investigated in detail.

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.

Recent Progress on Flexible Room-Temperature Gas Sensors Based on Metal Oxide Semiconductor

With the rapid development of the Internet of Things, there is a great demand for portable gas sensors. Metal oxide semiconductors (MOS) are one of the most traditional and well-studied gas sensing materials and have been widely used to prepare various commercial gas sensors. However, it is limited by high operating temperature. The current research works are directed towards fabricating high-performance flexible room-temperature (FRT) gas sensors, which are effective in simplifying the structure of MOS-based sensors, reducing power consumption, and expanding the application of portable devices. This article presents the recent research progress of MOS-based FRT gas sensors in terms of sensing mechanism, performance, flexibility characteristics, and applications. This review comprehensively summarizes and discusses five types of MOS-based FRT gas sensors, including pristine MOS, noble metal nanoparticles modified MOS, organic polymers modified MOS, carbon-based materials (carbon nanotubes and graphene derivatives) modified MOS, and two-dimensional transition metal dichalcogenides materials modified MOS. The effect of light-illuminated to improve gas sensing performance is further discussed. Furthermore, the applications and future perspectives of FRT gas sensors are also discussed.

Research Progress of Graphene and Its Derivatives towards Exhaled Breath Analysis

The metabolic process of the human body produces a large number of gaseous biomarkers. The tracking and monitoring of certain diseases can be achieved through the detection of these markers. Due to the superior specific surface area, large functional groups, good optical transparency, conductivity and interlayer spacing, graphene, and its derivatives are widely used in gas sensing. Herein, the development of graphene and its derivatives in gas-phase biomarker detection was reviewed in terms of the detection principle and the latest detection methods and applications in several common gases, etc. Finally, we summarized the commonly used materials, preparation methods, response mechanisms for NO, NH₃, H₂S, and volatile organic gas VOCs, and other gas detection, and proposed the challenges and prospective applications in this field.

A ratiometric solid AIE sensor for detection of acetone vapor

Acetone serves as a routine solvent and synthetic intermediate in chemical factories and laboratories. Monitoring the level of acetone vapor in working environment is of great necessity to employee health due to its strong volatility and toxicity, but there is still in lack of simple and easy-to-use portable sensors. In this study, we report a portable and intuitive indicator for real-time displaying acetone vapor concentration in air, based on the ratiometric fluorescence response of the designed organic molecule, PhB-SSB, to acetone. As an aggregation-induced emission (AIE) fluorophore, PhB-SSB underwent specific reaction with acetone through the salicylaldehyde Schiff base and phenylboronate groups to realize ratiometric fluorescence change from green to red after acetone vapor treatment. The reaction mechanism was proposed as acetone-induced breakage of the imine bond in PhB-SSB. We further fabricated PhB-SSB into a film fluorescent sensor for acetone vapor with good sensitivity and selectivity. Taking advantage of its intuitive fluorescent color contrast, acetone-specific response and small size, our sensor is practical in real-time alarming the acetone vapor hazard in the workplaces.

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

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

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.

Nanosensor-Based Flexible Electronic Assisted with Light Fidelity Communicating Technology for Volatolomics-Based Telemedicine

Telemedicine provides an attractive vision for tele-monitoring human health conditions and, thus, offers the opportunity for timely preventing chronic disease. A key limitation of promoting telemedicine in clinic application is the lack of a noninvasive med-tech and effective monitoring platform, which should be wearable and capable of high-performance tele-monitoring of health risk. Here we proposed a volatolomics-based telemedicine for continuously and noninvasively assessing human health status through continuously tracking the variation of volatile markers derived from human breath or skin. Particularly, a nanosensor-based flexible electronic was specifically designed to serve as a powerful platform for implementing the proposed cost-effective healthcare. An all-flexible and highly packed makeup (all functional units were integrated in a 2*2*0.19 cm³ plate) enables an electronic, compact configuration and the capability of resisting negative impact derived from customers' daily movement. Notably, the nanosensor-based electronic demonstrates high specificity, quick response rate (t_90% = 4.5 s), and desirable low detection limit (down to 0.117 ppm) in continuous tele-monitoring chronic-disease-related volatile marker (e.g., acetone). Assisted by the power saved light fidelity (Li-Fi) communicating technology, a clinic proof on the specifically designed electronic for noninvasively and uninterrupted assessing potential health risk (e.g., diabetics) is successfully implemented, with the accuracy of around 81%. A further increase in the accuracy of prewarning is predicted by excluding the impact of individual differences such as the gender, age, and smoking status of the customer. These promising pilot results indicate a bright future for the tailor-made nanosensing-device-supported volatolomics-based telemedicine in preventing chronic diseases and increasing patients' survival rate.

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

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

Development of a Sensing Array for Human Breath Analysis Based on SWCNT Layers Functionalized with Semiconductor Organic Molecules

A sensor array based on heterojunctions between semiconducting organic layers and single walled carbon nanotube (SWCNT) films is produced to explore applications in breathomics, the molecular analysis of exhaled breath. The array is exposed to gas/volatiles relevant to specific diseases (ammonia, ethanol, acetone, 2-propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). Then, to evaluate its capability to operate with real relevant biological samples the array is exposed to human breath exhaled from healthy subjects. Finally, to provide a proof of concept of its diagnostic potential, the array is exposed to exhaled breath samples collected from subjects with chronic obstructive pulmonary disease (COPD), an airway chronic inflammatory disease not yet investigated with CNT-based sensor arrays, and breathprints are compared with those obtained from of healthy subjects. Principal component analysis shows that the sensor array is able to detect various target gas/volatiles with a clear fingerprint on a 2D subspace, is suitable for breath profiling in exhaled human breath, and is able to distinguish subjects with COPD from healthy subjects based on their breathprints. This classification ability is further improved by selecting the most responsive sensors to nitrogen dioxide, a potential biomarker of COPD.

Blood Ketone Bodies and Breath Acetone Analysis and Their Correlations in Type 2 Diabetes Mellitus

Analysis of volatile organic compounds in the breath for disease detection and monitoring has gained momentum and clinical significance due to its rapid test results and non-invasiveness, especially for diabetes mellitus (DM). Studies have suggested that breath gases, including acetone, may be related to simultaneous blood glucose (BG) and blood ketone levels in adults with types 2 and 1 diabetes. Detecting altered concentrations of ketones in the breath, blood and urine may be crucial for the diagnosis and monitoring of diabetes mellitus. This study assesses the efficacy of a simple breath test as a non-invasive means of diabetes monitoring in adults with type 2 diabetes mellitus. Human breath samples were collected in Tedlar™ bags and analyzed by headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME/GC-MS). The measurements were compared with capillary BG and blood ketone levels (β-hydroxybutyrate and acetoacetate) taken at the same time on a single visit to a routine hospital clinic in 30 subjects with type 2 diabetes and 28 control volunteers. Ketone bodies of diabetic subjects showed a significant increase when compared to the control subjects; however, the ketone levels were was controlled in both diabetic and non-diabetic volunteers. Worthy of note, a statistically significant relationship was found between breath acetone and blood acetoacetate (R = 0.89) and between breath acetone and β-hydroxybutyrate (R = 0.82).

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.

Continuous online process analytics with multiplexing gas chromatography by using calibrated convolution matrices

The development of fast and precise measurement techniques for process analytical technology is important to operate chemical processes safely and efficiently. For quantitative measurements of multiple components at a trace level, often gas chromatographic methods are used which have a response time of several minutes or of up to one hour. For fast changing processes, this can be too slow for efficient control. For reducing the dead time of a control loop by increasing the measurement frequency, a multiplexing gas chromatography (mpGC) technique for a chromatographic system exhibiting a systematic non-linear response has been developed. For mpGC, superimposed chromatograms are measured by injecting consecutive samples before all components of previous samples have eluted from the column. The deconvolution of a superimposed chromatogram yields a computed chromatogram which is an average over the single chromatograms forming the superimposed chromatogram. Such a computed chromatogram typically shows so called correlation noise depending on the degree by which the single chromatograms forming the superimposed chromatogram will differ from each other (non-linear response). A technique is presented to calibrate the convolution matrix in order to suppress correlation noise introduced by systematic errors of the chromatographic system. The remaining correlation noise in the computed chromatogram is then exclusively caused by changing concentrations in the sample stream. For the method presented here, the sample is injected five times during the run time of a single chromatogram. The computed chromatogram is obtained three times within this timespan while representing each time an averaged chromatogram over the last five injections. Therefore, the sample throughput is increased by a factor of three compared to conventional GC.

Conductometric acetone vapor sensor based on the use of gold-doped three-dimensional hierarchical porous zinc oxide microspheres

A versatile nanoprobe for acetone vapor was designed and fabricated. It is based on the use of gold-doped three-dimensional (3D) hierarchical porous zinc oxide microspheres (Au/ZnO HPMSs). The nanoprobe was synthesized by annealing zinc hydroxide carbonate precursor (obtained by a hydrothermal method) doped with gold nanoparticles. The resulting products possess a 3D open framework structure built of 2D porous nanosheets with a nanoporous wormhole-like shape. The microspheres doped with 0.5 mol% gold display a good selectivity towards acetone. The conductometric nanoprobe, typically operated at a voltage of 5 V, can detect sub-ppm levels of acetone, and the detection limit is as low as 0.2 ppm. The response (at a level of up to 100 ppm of acetone at 325 °C) was high (74 ± 1.9), and the response and recovery time are 6 and 3 s, respectively. This superior performance is ascribed (a) to the hierarchical porous ZnO architecture that warrants a large surface area; and (b) to the presence of gold nanoparticles that facilitate the chemisorption and dissociation of gas molecules. Graphical abstract Gold-doped 3D hierarchical porous ZnO microspheres (Au/ZnO HPMSs) architectures assembled by interconnected 2D porous nanosheets structures. The resistive sensor using these Au/ZnO HPMSs demonstrates outstanding acetone vapor sensing behaviors and 0.2 ppm detection limits.

A Versatile Method to Enhance the Operational Current of Air-Stable Organic Gas Sensor for Monitoring of Breath Ammonia in Hemodialysis Patients

Point-of-care (POC) application for monitoring of breath ammonia (BA) in hemodialysis (HD) patients has emerged as a promising noninvasive health monitoring approach. In this context, many organic gas sensors have been reported for BA detection. However, one of the major challenges for its integration with affordable household POC application is to achieve stable performance for accuracy and high operational current at low voltage for low-cost read-out circuitry. Herein, we exploited the stability of the Donor-Acceptor polymer on the cylindrical nanopore structure to realize the sensors with a high sensitivity and stability. Then, we proposed a double active layer (DL) strategy that exploits an ultrathin layer of Poly(3-hexylthiophene-2,5-diyl) (P3HT) to serve as a work function buffer to enhance the operational current. The DL sensor exhibits a sustainable enhanced operational current of microampere level and a stable sensing response even with the presence of P3HT layer. This effect is carefully examined with different aspects, including vertical composition profile of DL configuration, lifetime testing on different sensing layer, morphological analysis, and the versatility of the DL strategy. Finally, we utilize the DL sensor to conduct a tracing of BA concentration in two HD patients before and after HD, and correlate it with the blood urea nitrogen (BUN) levels. A good correlation coefficient of 0.96 is achieved. Moreover, the feasibility of DL sensor integrated into a low-cost circuitry was also verified. The results demonstrate the potential of this DL strategy to be used to integrate organic sensor for affordable household POC devices.

Comparative Study on the Preparation and Gas Sensing Properties of Reduced Graphene Oxide/SnO2 Binary Nanocomposite for Detection of Acetone in Exhaled Breath

Reduced graphene oxide/tin dioxide (RGO/SnO₂) binary nanocomposite for acetone sensing performance was successfully studied and applied in exhaled breath detection. The influence of structural characteristics was explored by synthesizing the composite (RGO/SnO₂) using the solvothermal method (GS-I) and the hydrothermal method (GS-II) by the chemical route and mechanical mixing, respectively. The nanocomposites characterized by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), Fourier transform-infrared spectroscopy (FT-IR), and Brunauer-Emmett-Teller (BET) revealed that GS-I exhibited better surface area, surface energy and showed enhanced gas response than GS-II at an operating temperature of 200 °C. These sensors exhibited comparable response in humid environment as well, suitable for acetone sensing in exhaled breath that clearly distinguishes between healthy and diabetes subjects. The enhanced response at lower concentrations was attributed to the synergistic effect at the RGO/SnO₂ interface. These results indicate that modification in the structural characteristics of RGO/SnO₂ nanocomposite enhances the sensing property. Furthermore, it proved to be a promising material for potential application for point-of care, noninvasive diabetes detection.

Floral and lamellar europium(iii)-based metal–organic frameworks as high sensitivity luminescence sensors for acetone

Floral Eu-BDC and lamellar Eu-BTC as high sensitivity luminescence sensor for acetone.

Online High Throughput Measurements for Fast Catalytic Reactions Using Time-Division Multiplexing Gas Chromatography

Developing new catalysts is crucial for optimization of chemical processes. Thus, advanced analytical methods are required to determine the catalytic performance of new catalysts accurately. Usually, gas chromatographic methods are employed to analyze quantitatively the product distribution of volatile compounds generated by a specific catalyst. However, the characterization of rapidly changing catalysts, e.g., due to deactivation, still poses an analytical challenge because gas chromatographic methods are too slow for monitoring the change of the complex product spectra. Here, we developed a gas chromatographic technique based on the concept of multiplexing gas chromatography (mpGC) for fast and comprehensive analysis of the product stream from a catalytic testing unit. This technique is applied for the study of the catalytic reaction of methanol-to-olefins (MTO) conversion. For this method, the time distance between two measurements is chosen so that the chromatograms but not the peaks themselves are superimposed. In this way, stacked chromatograms are generated in which the components from successively injected samples elute baseline separated next to each other from the column. The peaks from different samples are interlaced, and for this reason, the method is referred to as time-division multiplexing gas chromatography (td-mpGC). The peaks are analyzed by direct peak integration not requiring a Hadamard transformation for deconvolution of the raw data as usual for many mpGC applications. Therefore, the sample can be injected equidistantly. The integrated peaks have to be allocated to the correct retention times. The time distance between two measurements for studying the reaction and regeneration cycles of MTO catalysts is 4.3 min and 38 s, respectively. Column switching techniques such as back-flush and heart-cut are introduced as general tools for multiplexing gas chromatography.

Direct Hadamard Transform Capillary Zone Electrophoresis without Instrumental Modifications

We report the first successful implementation of a multiplexing method on a standard capillary electrophoresis system with UV detection that is independent of additional hardware. This was achieved using the Hadamard transform approach and employing vial exchange and voltage suspensions for translation of pseudorandom binary sequence elements into sample and background electrolyte injections of a capillary zone electrophoresis separation. Sequences exceeding peak capacity of the capillary were subdivided into shorter subsequences measured successively and realigned afterward based on EOF marker or analyte peaks. This way, we realized and deconvoluted modulation sequences as long as 8-bit (255 injections) for two systems containing either AMP or a mixture of the nucleotides (A,C,G,U)MP resulting in electropherograms of considerably improved signal-to-noise ratio. We achieved factors of intensity enhancement of around 6.9 and 5.2, respectively (theoretical maximum 8.0). This contribution, further, presents experimental and simulation studies on the effects on zones during injection and separation when experiencing voltage suspensions. Besides analysis of EOF behavior and influence of diffusion dispersion, we also provide data on the significance of specific electrophoretic errors such as peak position shift, inconsistent sample injection, and peak broadening on the quality of the inverse Hadamard transform. Moreover, the application of our approach to the practical analysis of a milk sample is described. The results demonstrate the applicability of multiplexing on unmodified standard CE instrumentation and establish a new suitable methodology to enhance the low sensitivity of on-column UV detection in capillary electrophoresis.

Novel Zinc(II) Bis(Dipyrromethenate)-Doped Ethyl Cellulose Sensors for Acetone Vapor Fluorescence Detection

In this paper, we report on the results of spectrofluorimetric study of new fluorescent sensor based on [Zn₂L₂] doped in ethyl cellulose. The sensor optical signal is based on the rapid fluorescence quenching in the presence of acetone vapor. The acetone vapor detection limit in a gas mixture by means of sensor based on [Zn₂L₂] doped in ethyl cellulose is 1.68 ppb. Being highly sensitive to the acetone acetone presence, instant in response and easy to use, the sensor can find an application for the noninvasive diagnostics of diabetes as well as for the monitoring of the content of acetone acetone in the air at industrial and laboratory facilities. Graphical Abstract.

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.

Organic Gas Sensor with an Improved Lifetime for Detecting Breath Ammonia in Hemodialysis Patients

In this work, a TFB (poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(4,4'-(N-(4-s-butylphenyl)diphenylamine)]) sensor with a cylindrical nanopore structure exhibits a high sensitivity to ammonia in ppb-regime. The lifetime and sensitivity of the TFB sensor were studied and compared to those of P3HT (poly(3-hexylthiophene)), NPB (N,N'-di(1-naphthyl)-N,N'-diphenyl-(1,1'-biphenyl)-4,4'-diamine), and TAPC (4,4'-cyclohexylidenebis[N,N-bis(4-methylphenyl) benzenamine]) sensors with the same cylindrical nanopore structures. The TFB sensor outstands the others in sensitivity and lifetime and it shows a sensing response (current variation ratio) of 13% to 100 ppb ammonia after 64 days of storage in air. A repeated sensing periods testing and a long-term measurement have also been demonstrated for the test of robustness. The performance of the TFB sensor is stable in both tests, which reveals that the TFB sensor can be utilized in our targeting clinical trials. In the last part of this work, we study the change of ammonia concentration in the breath of hemodialysis (HD) patients before and after dialysis. An obvious drop of breath ammonia concentration can be observed after dialysis. The reduction of breath ammonia is also correlated with the reduction of blood urea nitrogen (BUN). A correlation coefficient of 0.82 is achieved. The result implies that TFB sensor may be used as a real-time and low cost breath ammonia sensor for the daily tracking of hemodialysis patients.

Online Continuous Trace Process Analytics Using Multiplexing Gas Chromatography

The analysis of impurities at a trace level in chemical products, nutrition additives, and drugs is highly important to guarantee safe products suitable for consumption. However, trace analysis in the presence of a dominating component can be a challenging task because of noncompatible linear detection ranges or strong signal overlap that suppresses the signal of interest. Here, we developed a technique for quantitative analysis using multiplexing gas chromatography (mpGC) for continuous and completely automated process trace analytics exemplified for the analysis of a CO₂ stream in a production plant for detection of benzene, toluene, ethylbenzene, and the three structural isomers of xylene (BTEX) in the concentration range of 0-10 ppb. Additional minor components are methane and methanol with concentrations up to 100 ppm. The sample is injected up to 512 times according to a pseudorandom binary sequence (PRBS) with a mean frequency of 0.1 Hz into a gas chromatograph equipped with a flame ionization detector (FID). A superimposed chromatogram is recorded which is deconvoluted into an averaged chromatogram with Hadamard transformation. Novel algorithms to maintain the data acquisition rate of the detector by application of Hadamard transformation and to suppress correlation noise induced by components with much higher concentrations than the target substances are shown. Compared to conventional GC-FID, the signal-to-noise ratio has been increased by a factor of 10 with mpGC-FID. Correspondingly, the detection limits for BTEX in CO₂ have been lowered from 10 to 1 ppb each. This has been achieved despite the presence of detectable components (methane and methanol) with a concentration about 1000 times higher than the target substances. The robustness and reliability of mpGC has been proven in a two-month field test in a chemical production plant.

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 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.

An acetone bio-sniffer (gas phase biosensor) enabling assessment of lipid metabolism from exhaled breath

Several volatile organic compounds (VOCs) are released from human breath or skin. Like chemical substances in blood or urine, some of these vapors can provide valuable information regarding the state of the human body. A highly sensitive acetone biochemical gas sensor (bio-sniffer) was developed and used to measure exhaled breath acetone concentration, and assess lipid metabolism based on breath acetone analysis. A fiber-optic biochemical gas sensing system was constructed by attaching a flow-cell with nicotinamide adenine dinucleotide (NADH)-dependent secondary alcohol dehydrogenase (S-ADH) immobilized membrane onto a fiber-optic NADH measurement system. The NADH measurement system utilizes an ultraviolet-light emitting diode with peak emission of 335 nm as an excitation light source. NADH is consumed by the enzymatic reaction of S-ADH, and the consumption is proportional to the concentration of acetone vapor. Phosphate buffer which contained NADH was circulated into the flow-cell to rinse products and the excessive substrates from the optode. The change of fluorescent emitted from NADH is analyzed by the PMT. Hence, fluorescence intensity decreased as the acetone concentration increased. The relationship between fluorescence intensity and acetone concentration was identified from 20 ppb to 5300 ppb. This interval included the concentration of acetone vapor in the breath of healthy people and those suffering from disorders of carbohydrate metabolism. Finally, the acetone bio-sniffer was used to measure breath acetone during an exercise stress test on an ergometer after a period of fasting. The concentration of acetone in breath was shown to significantly increase after exercise. This biosensor allows rapid, highly sensitive and selective measurement of lipid metabolism.

Pitfalls in the analysis of volatile breath biomarkers: suggested solutions and SIFT-MS quantification of single metabolites

The experimental challenges presented by the analysis of trace volatile organic compounds (VOCs) in exhaled breath with the objective of identifying reliable biomarkers are brought into focus. It is stressed that positive identification and accurate quantification of the VOCs are imperative if they are to be considered as discreet biomarkers. Breath sampling procedures are discussed and it is suggested that for accurate quantification on-line real time sampling and analysis is desirable. Whilst recognizing such real time analysis is not always possible and sample collection is often required, objective recognition of the pitfalls involved in this is essential. It is also emphasized that mouth-exhaled breath is always contaminated to some degree by orally generated compounds and so, when possible, analysis of nose-exhaled breath should be performed. Some difficulties in breath analysis are mitigated by the choice of analytical instrumentation used, but no single instrument can provide solutions to all the analytical challenges. Analysis and interpretation of breath analysis data, however acquired, needs to be treated circumspectly. In particular, the excessive use of statistics to treat imperfect mass spectrometry/mobility spectra should be avoided, since it can result in unjustifiable conclusions. It is should be understood that recognition of combinations of VOCs in breath that, for example, apparently describe particular cancer states, will not be taken seriously until they are replicated in other laboratories and clinics. Finally, the inhibiting notion that single biomarkers of infection and disease will not be identified and utilized clinically should be dispelled by the exemplary and widely used single biomarkers NO and H2 and now, as indicated by recent selected ion flow tube mass spectroscopy (SIFT-MS) results, triatomic hydrogen cyanide and perhaps pentane and acetic acid. Hopefully, these discoveries will provide encouragement to research workers to be more open-minded on this important and desirable issue.

Rapid identification of false peaks in the spectrum of Hadamard transform ion mobility spectrometry with inverse gating technique

With the introduction of inverse gating technique to Hadamard multiplexing ion mobility spectrometry, the false peaks in the spectrum of Hadamard transform could be rapidly identified.

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.