Tailored Co1-xZnxFe2O4 Spinel Bulk Heterojunction Composites for Acetone Detection toward Diabetes Diagnosis.

Introduction Acetone (CH3COCH3) is a colorless transparent liquid with a special pungent smell, which is categorized as important member of volatile organic compounds (VOCs). It offers many important information in early medical diagnosis of diabetes. In exhaled breath of healthy human, the average concentration of acetone is 0.3-0.9 ppm, which is far below lowest detection limit of 1.8 ppm in exhaled breath of diabetes patients. Taking into consideration of the practical detection demand for healthy medical diagnosis, the highly performance gas sensor is to be expected. Here, a stabilized zirconia (YSZ) based acetone sensor based on mixed potential sensing mechanism was fabricated using NiTa2O6 sensing electrode (SE) calcinated at 1000 °C. The NiTa2O6 sensing material was characterized by TG/DSC, XRD, SEM, Raman and XPS measurement. The gas sensing performance of developed sensing device demonstrated that the sensor based on NiTa2O6-SE displayed low detection limit of 200 ppb acetone and rapid response and recovery times of 9 s and 18 s to 2 ppm acetone at 600 °C. Between the response value to wide concentration range of 0.2-200 ppm acetone and the acetone concentration logarithm for the developed sensor presented piecewise linear function. The fabricated acetone sensor also possessed good wet fastness, reproducibility and stability of 20 days, portending great potential in aspect of low and high acetone concentration detection. More importantly, the solid electrolyte type acetone sensor utilizing NiTa2O6-SE open up a new possibility for noninvasive diagnosis of diabetes through detecting exhaled breath of healthy people and diabetes patients. Results and Conclusions The operating temperature affects the activation degree for the electrochemical reaction and adsorption and desorption process of sensing electrode, which results in the change of gas sensing performance for the fabricated sensor. Thus, the response and recovery curves of the sensor utilizing NiTa2O6-SE sintered at 1000 °C to 50 ppm acetone at temperature range of 475-650 °C are tested. Accordingly, 600 °C was selected as the optimal operating temperature to investigate the corresponding sensing characteristics of present device. In the acetone concentration range of 0.2-200 ppm, the sensor exhibited good response and recovery characteristics and the response signal increased gradually with the increase of acetone concentration. Notably, a spike appears at larger tested gas concentration, which is also observed by other reported works [1, 2, 3, 4]. Therefore, to avoid disturbance of the spike and to render certain the accuracy of sensing performance, the exposed time of 2.5 min in acetone gas and exposed time of 3.5 min in air is performed. The potential values at the last second were used for calculation of the response. The low detection limit of the sensor was 200 ppb acetone and the response and recovery times to 2 ppm acetone were 9 s and 18 s, respectively. The ΔV of the sensor to 0.2–2 ppm and 2-200 ppm acetone and concentration logarithm of acetone displayed linear relationship at 600 °C and the sensitivity of the sensor to 0.2-2 ppm and 2-200 ppm acetone were -11 and -27 mV/decade, which demonstrated the good acetone detection ability in aspects of lower and higher concentration. Comparison of the acetone sensing performances of developed sensor in this work and those of solid electrolyte sensing devices reported in literatures. More importantly, the present sensor attached with NiTa2O6-SE possessed significant advantages of low detection limit of acetone and response or recovery speeds in the lower acetone concentration, indicating the good potential alternative device for effectively monitoring acetone.To evaluate the possibility of the present sensor to be a practical acetone device, clinical detection for acetone biomarker in real exhaled breath of healthy volunteers and diabetes is further performed based on the sensor attached with NiTa2O6-SE. Here, the exhaled breath samples are taken from three healthy volunteers and diabetes patients. The blood ketone level of three diabetes patients is 0.6 mmol/L, 2.0 mmol/L and 6.3 mmol/L. The sensor exhibited low response signal and relatively good consistence to exhaled breath of three healthy volunteers. However, the response signal of the sensor to exhaled breath of three diabetes patients apparently higher than that of healthy peoples. Furthermore, the response value of the sensing device enhanced gradually with the increase of blood ketone levels of three diabetes patients. In this case, the difference in response value between diabetes and healthy people becomes more obvious, namely, the sensor can well distinguish between diabetic patients and healthy people. Accordingly, the developed acetone sensor attached with NiTa2O6-SE possessed good possibility to diagnosis diabetes.

This study employs Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) to analyze exhaled breath profiles of 504 healthy adults, focusing on nine common volatile organic compounds (VOCs): acetone, acetaldehyde, acetonitrile, ethanol, isoprene, methanol, propanol, phenol, and toluene. PTR-MS offers real-time VOC measurement, crucial for understanding breath biomarkers and their applications in health assessment. The study aims to investigate how demographic factors-gender, age, and smoking history-affect VOC concentrations in exhaled breath. The objective is to enhance our understanding of breath biomarkers and their potential for health monitoring and clinical diagnosis. Exhaled breath samples were collected using PTR-MS, measuring concentrations of nine VOCs. The data were analyzed to discern distribution patterns across demographic groups. Males showed higher average VOC levels for certain compounds. Propanol and methanol concentrations significantly increased with age. Smoking history influenced VOC levels, with differences among non-smokers, current smokers, and ex-smokers. This research provides valuable insights into demographic influences on exhaled VOC profiles, emphasizing the potential of breath analysis for health assessment. PTR-MS's real-time measurement capabilities are crucial for capturing dynamic VOC changes, offering advantages over conventional methods. These findings lay a foundation for advancements in non-invasive disease detection, highlighting the importance of considering demographics in breath biomarker research.

YSZ-based acetone sensor using a Cd2SnO4 sensing electrode for exhaled breath detection in medical diagnosis

The World Health Organization reports that metabolic disorders are responsible for a significant proportion of global mortality. Considering this, breath sensors have gained prominence as effective tools for monitoring and diagnosing metabolic disorders, thanks to recent advancements in science and technology. In human exhaled breath, over 870 distinct volatile organic components (VOCs) have been identified. Among several VOCs, the detection of acetone in exhaled breath has received considerable attention in biomedical applications. Research indicates a strong correlation between high acetone levels in human breath and several diseases, such as asthma, halitosis, lung cancer, and diabetes mellitus. For instance, acetone is particularly noteworthy as a biomarker in diabetes, where its concentration in exhaled breath often surpasses 1.76 parts per million (ppm), compared to less than 0.8 ppm in healthy individuals. Early diagnosis and intervention in diseases associated with elevated acetone levels, aided by such non-invasive techniques, have the potential to markedly reduce both mortality and the financial burden of healthcare. Over time, various nanostructured gas sensing technologies have been developed for detecting acetone in both ambient air and exhaled breath. This article presents a mini review of cutting-edge research on acetone gas sensing, focusing specifically on nanostructured metal oxides. It discusses critical factors influencing the performance of acetone gas sensors, including acetone concentration levels and operational temperature, which affect their sensitivity, selectivity, and response times. The aim of this review is to encourage further advancements in the development of high-performance acetone gas sensors utilizing nanostructured materials, contributing to more effective management of metabolic disorders.

Analysis of exhaled breath is a promising diagnostic method. Sampling of exhaled breath is non-invasive and can be performed as often as considered desirable. There are indications that the concentration and presence of certain of volatile compounds in exhaled breath of lung cancer patients is different from concentrations in healthy volunteers. This might lead to a future diagnostic test for lung cancer. Exhaled breath samples from 65 patients with different stages of lung cancer and undergoing different treatment regimes were analysed. Mixed expiratory and indoor air samples were collected. Solid phase microextraction (SPME) with carboxen/polydimethylsiloxane (CAR/PDMS) sorbent was applied. Compounds were analysed by means of gas chromatography (GC) and mass spectrometry (MS). The method we used allowed identification with the spectral library of 103 compounds showing at least 15% higher concentration in exhaled breath than in inhaled air. Among those 103 compounds, 84 were confirmed by determination of the retention time using standards based on the respective pure compound. Approximately, one third of the compounds detected were hydrocarbons. We found aromatic hydrocarbons, alcohols, aldehydes, ketones, esters, ethers, sulfur compounds, nitrogen-containing compounds and halogenated compounds. Acetonitrile and benzene were two of 10 compounds which correlated with smoking behaviour. A comparison of results from cancer patients with those of 31 healthy volunteers revealed differences in the concentration and presence of certain compounds. The sensitivity for detection of lung cancer patients based on eight different compounds not seen in exhaled breath of healthy volunteers was 51% and the specificity was 100%. These eight potential markers for detection of lung cancer are 1-propanol, 2-butanone, 3-butyn-2-ol, benzaldehyde, 2-methyl-pentane, 3-methyl-pentane, n-pentane and n-hexane. SPME is a relatively insensitive method and compounds not observed in exhaled breath may be present at a concentration lower than LOD. The main achievement of the present work is the validated identification of compounds observed in exhaled breath of lung cancer patients. This identification is indispensible for future work on the biochemical sources of these compounds and their metabolic pathways.

Introduction There has been considerable effort to detect volatile organic compounds (VOCs) by metal oxide semiconductor gas sensors for their high sensitivity, low cost, easy production, and compact size [1]. In recent times, acetone in exhaled breath have studied for biomarkers more than hazardous air pollutants. According to the previous studies, breath acetone may be correlated with fat burning [2-3] not only a specific breath marker for type-1 diabetes [4]. However, there are many drawbacks of metal oxide based acetone sensors to apply diet monitoring since the concentration of breath acetone for healthy humans are from 300 to 900 ppb, which require to develop highly sensitive sensing materials and systems. From this point of view, addition of noble metals for catalytic effect, formation of p-n heterojunction and synthesis of hierarchical and hollow nanostructures for high surface area are suggested to improve the sensing performances. In this study, we describe the novel nanostructure of hollow CuO nanocubes decorated on hollow TiO2 nanosphere and investigate their acetone gas response properties. Method TEM images of the nanoparticles were obtained by FEI Tecnai G2 F30 S-Twin (300 kV, KAIST). For the preparation of gas sensing devices based on TiO2-CuO nanocomposites, interdigitated electrodes on 8-inch oxidized silicon wafers were formed using conventional photo lithographic techniques. A sub micrometer layer of the photoresist was spin-coated onto the silicon oxide wafer at 5000 rpm and baked at 90 ℃ for 3 min before ultraviolet (UV) exposure in a photo mask aligner. After the exposure, the wafer was developed for 30 s in a developing solution. The Au electrode with 10 μm gaps on silicon substrate were successfully patterned with thin films (10 nm Cr/100 nm Au) deposited by e-beam evaporation and a metal lift-off process in acetone. Then, TiO2-CuO dispersed in ethanol spin-coated onto interdigitated electrodes. The dynamic sensing responses were measured using a data-acquisition system consisting of Agilent 34970A and BenchLink Data logger program, and the sensor devices were located in a temperature-controlled chamber. Dry air was used as a balance gas at a flow rate of 1000 cc/min. In addition, the acetone gas was used as an analyte (obtained from RIGAS Co. in Korea) at a concentration of 10 ppm/100ppm and blended with a balance gas to achieve the desired analyte concentrations of 20 ppb to 10 ppm by using mass-flow controllers. The gas response was measured by allowing the concentration-controlled acetone gas to flow into the reaction chamber, and then allowing only the balance gas to flow into the chamber for recovering the gas sensor. Results and Conclusions Figure 1 shows the TEM images of the formation of TiO2-CuO hollow nanocubes. First, 300 nm of hollow TiO2 nanosphere was synthesized as shown in figure 1 (a). Then, Cu2O nanocubes were decorated on TiO2 (figure 1 (b)) and diameter of nanocubes was approximately 20 nm. For the TiO2-CuO hollow nanocubes, TiO2-Cu2O need additional thermal oxidation process and the oxidized CuO hollow nanocubes are shown in figure 1 (c-d). Acetone-sensing properties of TiO2-CuO hollow nanocubes were studied at optimized operating temperature, 200 ℃, under a dry condition. Figure 2 shows the response curve of TiO2-CuO hollow nanocubes for acetone 1 ppm and the response value is estimated to 12.1. Here, TiO2-CuO hollow nanocubes shows the p-type semiconductor properties even TiO2 is typical n-type semiconductor because p-type CuO hollow nanocubes are covered the surface of TiO2 hollow nanosphere so that the ratio of p-p contact becomes higher and therefore, its electrical property is dominated by p-type. Figure 3 shows the abbreviation curve of sensitivity as a function of acetone concentration from 20 ppb to 500 ppb. The response values were increased with increasing acetone concentration and limit of detection was calculated as 2.23 ppb using the noise of base resistance [5]. And the responses of TiO2-CuO hollow nanocubes toward other gases existing in VOCs was also examined. As shown in figure 4, response of 1 ppm acetone, formaldehyde, benzene and ammonia gas at 200 ℃ were measured and TiO2-CuO showed the highest response to acetone gas among the tested gases.

The application of exhaled breath analysis in racing Thoroughbreds and the influence of high intensity exercise and ambient temperature on the concentration of carbon monoxide and pH in exhaled breath

The rapid transfer of volatiles from alveolar blood into the lungs and then out of the body in exhaled breath leads to the common and natural conclusion that these volatiles provide information on health and metabolic processes, with considerable potential as biomarkers for use in the screening, diagnosis and monitoring of diseases. Whilst these exhaled volatiles could well serve as biomarkers for human metabolic processes, thereby providing insights into the clinical and nutritional status of individuals, there exist various confounding factors that limit their easy application. A major confounding factor is the introduction of microbially produced oral volatiles into the exhaled breath, yet these volatiles are often ignored in discovery volatile research studies. Here, we provide a comparative cross-sectional study of selected volatiles commonly found in exhaled breath. Using gas chromatography-ion mobility spectrometry, we monitored these selected volatiles in nasal and oral end-tidal exhaled breath samples from twenty-one volunteers. The signal intensities from untargeted volatile detection were analysed for variances using principal component analysis (PCA), revealing a clear separation correlated with the sampling method. Four compounds representing sampling method-independent (acetone, isoprene, methanol, and 2-pentanone) and four corresponding to sampling method-dependent (1-propanol, 2-propanol, ethanol, and acetoin) were identified and selected based on their high PCA loadings. These compounds are further analysed and discussed to illustrate the extent to which the oral microbiome can influence volatile concentrations in exhaled breath. An additional noteworthy finding of this study is that the nasally sampled selected exhaled volatiles are little influenced by the inhalation route (oral or nasal). The outcome from this study is clear, namely that in order to reduce the influence of the oral microbiome on untargeted discovery breath research studies, end-tidal exhaled nasal breath samples should be taken for endogenous volatile analysis, otherwise oral microbial volatiles could be falsely identified as biomarkers. This is particularly important given the continuous rise in the use of machine learning algorithms and artificial intelligence to identify variations in volatilomes. The development and commercialisation of simple, user-friendly and comfortable end-tidal exhaled nasal sample collection devices are required for nasal sampling to become widely adopted.

Background Following creation of an IPAA in patients with ulcerative colitis (UC), more than 60% of subjects develop inflammatory complications. The current objective assessment for inflammation of the pouch is limited to surrogate stool and blood biomarkers or endoscopy. The development of non-invasive and accurate biomarkers for the assessment of IPAA inflammation is an area of unmet need. Measurement of exhaled breath volatile organic metabolome compounds (VOCs) has shown promise as a biomarker for the diagnosis and monitoring of inflammatory disorders. We here aimed to characterize the pattern of VOCs in the exhaled breath of patients with an IPAA and assess whether VOC analysis is able to discriminate patients with endoscopically active IPAA inflammation from patients without IPAA inflammation. Methods This is a cross-sectional study of patients with an IPAA created for the management of UC. Exhaled breath samples were collected at time of endoscopic evaluation of the pouch and 97 VOC metabolites assessed via selective ion flow tube mass spectrometry (SIFT-MS). The IPAA cohort was dichotomized using the endoscopic pouch disease activity index (PDAI) into endoscopic PDAI of >= 4 (severe inflammation), or endoscopic PDAI score <= 1 (mild or no inflammation). Principle component analysis (PCA) was conducted to reveal the VOCs with the strongest discriminatory capability and principle component regression (PCR) was performed to assess the association of exhaled breath VOC analysis in differentiating the groups. Results Exhaled breath metabolome analysis was performed on 10 subjects with PDAI >=4 and 7 subjects with PDAI <=1. Demographics are provided in Table 1. PCA indicated robust discrimination of the two groups based on breath VOCs (Figure 1). 10 out of 97 VOCs were up-regulated in the PDAI >=4 group compared to control, including ammonia and hydrogen sulfide. Isopropenyltoluene, tetrachloroethylene, and 3-pentanone provided the highest contribution to differentiate between the cohorts (Figure 2). Receiver operative curve (ROC) analysis of the PCR model indicated an area under the curve (AUC) of 0.81 (0.61-99), suggesting a strong association of breath VOCs with inflammation of the pouch (Figure 1). Conclusion VOC exhaled breath metabolome analysis shows a strong ability to discriminate patients with severe endoscopic pouch inflammation from patients with minimal to no endoscopic inflammation. The differences in reported VOCs point toward metabolic differences in bacterial fermentation, lipid and carbohydrate metabolism, and an increase in reactive oxygen species in patients with endoscopic pouch inflammation. Validation studies addressing the role of VOC analysis for non-invasive disease assessment patients with IPAA are ongoing.

Introduction: Exposure to hyperbaric hyperoxic conditions can lead to pulmonary oxygen toxicity. Although a decrease in vital capacity has long been the gold standard, newer diagnostic modalities may be more accurate. In pulmonary medicine, much research has focussed on volatile organic compounds (VOCs) associated with inflammation in exhaled breath. In previous small studies after hyperbaric hyperoxic exposure several methyl alkanes were identified. This study aims to identify which VOCs mark the development of pulmonary oxygen toxicity.Methods: In this randomized crossover study, 12 divers of the Royal Netherlands Navy made two dives of one hour to 192.5 kPa (comparable to a depth of 9 msw) either with 100% oxygen or compressed air. At 30 min before the dive, and at 30 min and 1, 2, 3, and 4 h post-dive, exhaled breath was collected and followed by pulmonary function tests (PFT). Exhaled breath samples were analyzed using gas chromatography–mass spectrometry (GC–MS). After univariate tests and correlation of retention times, ion fragments could be identified using a standard reference database [National Institute of Standards and Technology (NIST)]. Using these fragments VOCs could be reconstructed, which were then tested longitudinally with analysis of variance.Results: After GC–MS analysis, seven relevant VOCs (generally methyl alkanes) were identified. Decane and decanal showed a significant increase after an oxygen dive (p = 0.020 and p = 0.013, respectively). The combined intensity of all VOCs showed a significant increase after oxygen diving (p = 0.040), which was at its peak (+35%) 3 h post-dive. Diffusion capacity of nitric oxide and alveolar membrane capacity showed a significant reduction after both dives, whereas no other differences in PFT were significant.Discussion: This study is the largest analysis of exhaled breath after in water oxygen dives to date and the first to longitudinally measure VOCs. The longitudinal setup showed an increase and subsequent decrease of exhaled components. The VOCs identified suggest that exposure to a one-hour dive with a partial pressure of oxygen of 192.5 kPa damages the phosphatidylcholine membrane in the alveoli, while the spirometry and diffusion capacity show little change. This suggests that exhaled breath analysis is a more accurate method to measure pulmonary oxygen toxicity.

To investigate dietary influences on the volatilome, the volatile subcategory of the metabolome, we performed a comparative untargeted volatilome analysis of exhaled breath, ruminal fluid, serum, urine, and milk from lactating Holstein cows fed different diets. Thirty-two cows (83.3 ± 31.40 DIM, 30.6 ± 5.03 kg of milk/d) were assigned to 4 diets. The experiment lasted 16 wk. Throughout the experiment, half of the animals were fed a hay-based diet (HD; n = 16), and the other half were fed a silage-based diet (SIL; n = 16). In experimental wk 5 to 12, half of the animals in each group received the control concentrate (CON), and the other half was fed with the CON supplemented with a blend of essential oils (EXP). We hypothesized that the basal diet and the essential oils influence the volatile organic compound (VOC) profiles of the cows through potential changes in ruminal fermentation, digestion, and metabolism (hypothesis 1). Furthermore, we hypothesized that the potential effects of essential oils would have a delayed onset and a carryover effect (hypothesis 2). Every 4 experimental weeks (i.e., in wk 4, wk 8, wk 12, and wk 16), samples of exhaled breath, ruminal fluid, serum, urine, milk, and feed were collected for dynamic headspace extraction and gas chromatographic analysis of VOC in their gaseous phase. Milk yield, milk composition, BW, and feed intake were recorded regularly. Linear mixed models and multivariate and univariate data analyses were performed. The total DMI and basal diet intake was similar between cows fed HD and SIL diets. However, SIL cows consumed less of the concentrate, NDF, and water-soluble carbohydrates and more starch than HD cows. The SIL cows had a higher milk production than the HD cows. No effect was found regarding the concentrate type on feed intake or milk production. Irrespective of diet, 2,957 VOC were detected in the gaseous phase of serum; 2,771 in exhaled breath; 1,016 in urine; 1,001 in milk; and 921 in ruminal fluid. Across the experimental wk 4, 8, 12, and 16, the basal diet altered the VOC profiles of ruminal fluid, urine, and exhaled breath but not those of serum and milk. The concentrate type affected only the VOC profiles of the exhaled breath. Most diet-influenced VOC in the affected biological matrices were identified as dietary components. The experimental week influenced the VOC profiles of all matrices, especially those of exhaled breath. The VOC profile of exhaled breath strongly correlated with that of urine, followed by that of ruminal fluid, milk, and serum. This study provides the first description of diet- and time-specific VOC profiles from the biological matrices of dairy cows. The identified discriminatory VOC seem suitable as markers to discriminate between HD and SIL cows. Exhaled breath may be a promising, sensitive, and less invasive tool to follow diet- and time-related metabolic changes.

Exhaled breath analysis is a potential non-invasive tool for diagnosing and monitoring airway diseases. Gas chromatography–mass spectrometry and electrochemical sensor arrays are the main techniques to detect volatile organic compounds (VOC) in exhaled breath. We developed a broadband quantum cascade laser spectroscopy technique for VOC detection and identification.The objective of this study was to assess the repeatability of exhaled breath profiling with broadband quantum cascade laser-based spectroscopy and to explore the clinical applicability by comparing exhaled breath samples from healthy children with those from children with asthma or cystic fibrosis (CF).Healthy children and children with stable asthma or stable CF, aged 6–18 years, were included. Two to four exhaled breath samples were collected in Tedlar bags and analyzed by quantum cascade laser spectroscopy to detect VOCs with an absorption profile in the wavenumber region between 832 and 1262.55 cm−1.We included 35 healthy children, 39 children with asthma and 15 with CF. Exhaled breath VOC profiles showed poor repeatability (Spearman’s rho = 0.36 to 0.46) and agreement of the complete profiles. However, we were able to discriminate healthy children from children with stable asthma or stable CF and identified VOCs that were responsible for this discrimination.Broadband quantum cascade laser-based spectroscopy detected differences in VOC profiles in exhaled breath samples between healthy children and children with asthma or CF. The combination of a relatively easy and fast method and the possibility of molecule identification makes broadband quantum cascade laser-based spectroscopy attractive to investigate the diagnostic and prognostic potential of volatiles in exhaled breath.

The correlation between propofol concentration in exhaled breath (C E) and plasma (C P) has been well-established, but its applicability for estimating the concentration in brain tissues (C B) remains unknown. Given the impracticality of directly sampling human brain tissues, rats are commonly used as a pharmacokinetic model due to their similar drug-metabolizing processes to humans. In this study, we measured C E, C P, and C B in mechanically ventilated rats injected with propofol. Exhaled breath samples from the rats were collected every 20 s and analyzed using our team’s developed vacuum ultraviolet time-of-flight mass spectrometry. Additionally, femoral artery blood samples and brain tissue samples at different time points were collected and measured using high-performance liquid chromatography mass spectrometry. The results demonstrated that propofol concentration in exhaled breath exhibited stronger correlations with that in brain tissues compared to plasma levels, suggesting its potential suitability for reflecting anesthetic action sites’ concentrations and anesthesia titration. Our study provides valuable animal data supporting future clinical applications.

Gas sniffer (YSZ-based electrochemical gas phase sensor) toward acetone detection

A portable acetone detector based on SmFeO3 can pre-diagnose diabetes through breath analysis