Breath acetone as a potential marker in clinical practice

Volatile organic compound analysis of malignant pleural mesothelioma chorioallantoic membrane xenografts

Malignant pleural mesothelioma (MPM) is an aggressive cancer associated with asbestos exposure. MPM is often diagnosed late, at a point where limited treatment options are available, but early intervention could improve the chances of successful treatment for MPM patients. Biomarkers to detect MPM in at-risk individuals are needed to implement early diagnosis technologies. Volatile organic compounds (VOCs) have previously shown diagnostic potential as biomarkers when analysed in MPM patient breath. In this study, chorioallantoic membrane (CAM) xenografts of MPM cell lines were used as models of MPM tumour development for VOC biomarker discovery with the aim of generating targets for investigation in breath, biopsies or other complex matrices. VOC headspace analysis of biphasic or epithelioid MPM CAM xenografts was performed using solid-phase microextraction and gas chromatography-mass spectrometry. We successfully demonstrated the capture, analysis and separation of VOC signatures from CAM xenografts and controls. A panel of VOCs was identified that showed discrimination between MPM xenografts generated from biphasic and epithelioid cells and CAM controls. This is the first application of the CAM xenograft model for the discovery of VOC biomarkers associated with MPM histological subtypes. These findings support the potential utility of non-invasive VOC profiling from breath or headspace analysis of tissues for detection and monitoring of MPM.

Elevated blood-ethanol concentration promotes reduction of aliphatic ketones (acetone and ethyl methyl ketone) to secondary alcohols along with slower oxidation to aliphatic diols

Many people convicted for drunken driving suffer from an alcohol use disorder and some traffic offenders consume denatured alcohol for intoxication purposes. Venous blood samples from people arrested for driving under the influence of alcohol were analyzed in triplicate by headspace gas chromatography (HS-GC) using three different stationary phases. The gas chromatograms from this analysis sometimes showed peaks with retention times corresponding to acetone, ethyl methyl ketone (2-butanone), 2-propanol, and 2-butanol in addition to ethanol and the internal standard (1-propanol). Further investigations showed that these drink-driving suspects had consumed an industrial alcohol (T-Red) for intoxication purposes, which contained > 90% w/v ethanol, acetone (~ 2% w/v), 2-butanone (~ 5% w/v) as well as Bitrex to impart a bitter taste. In n = 75 blood samples from drinkers of T-Red, median concentrations of ethanol, acetone, 2-butanone, 2-propanol and 2-butanol were 2050 mg/L (2.05 g/L), 97 mg/L, 48 mg/L, 26 mg/L and 20 mg/L, respectively. In a separate GC analysis, 2,3-butanediol (median concentration 87 mg/L) was identified in blood samples containing 2-butanone. When the redox state of the liver is shifted to a more reduced potential (excess NADH), which occurs during metabolism of ethanol, this favors the reduction of low molecular ketones into secondary alcohols via the alcohol dehydrogenase (ADH) pathway. Routine toxicological analysis of blood samples from apprehended drivers gave the opportunity to study metabolism of acetone and 2-butanone without having to administer these substances to human volunteers.

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

A solid state electrolyte based enzymatic acetone sensor

This paper introduces a novel solid-state electrolyte-based enzymatic sensor designed for the detection of acetone, along with an examination of its performance under various surface modifications aimed at optimizing its sensing capabilities. To measure acetone concentrations in both liquid and vapor states, cyclic voltammetry and amperometry techniques were employed, utilizing disposable screen-printed electrodes consisting of a platinum working electrode, a platinum counter electrode, and a silver reference electrode. Four different surface modifications, involving different combinations of Nafion (N) and enzyme (E) layers (N + E; N + E + N; N + N + E; N + N + E + N), were tested to identify the most effective configuration for a sensor that can be used for breath acetone detection. The sensor's essential characteristics, including linearity, sensitivity, reproducibility, and limit of detection, were thoroughly evaluated through a range of experiments spanning concentrations from 1 µM to 25 mM. Changes in acetone concentration were monitored by comparing currents readings at different acetone concentrations. The sensor exhibited high sensitivity, and a linear response to acetone concentration in both liquid and gas phases within the specified concentration range, with correlation coefficients ranging from 0.92 to 0.98. Furthermore, the sensor achieved a rapid response time of 30-50 s and an impressive detection limit as low as 0.03 µM. The results indicated that the sensor exhibited the best linearity, sensitivity, and limit of detection when four layers were employed (N + N + E + N).

Innovations and applications of ketone body monitoring in diabetes care

Ketone bodies, comprising β-hydroxybutyric acid (BHB), acetoacetate (AcAc), and acetone, play a vital role as essential energy substrates. In individuals with diabetes, ketone bodies can be elevated under various conditions, including diabetic ketoacidosis, use of sodium-glucose transporter type 2 (SGLT2) inhibitors, and extreme carbohydrate restriction. There are three methods for measuring ketone bodies. Urine ketone analysis (AcAc) is a standard clinical test, whereas blood ketone testing (BHB+AcAc) is valuable in identifying or resolving diabetic ketoacidosis. Recently, technology for measuring breath acetone has been introduced, which provides an easy means of monitoring ketogenic diets in obese individuals. The basic breath alcohol detector also reacts with breath acetone. Therefore, it is important for professional drivers taking SGLT2 inhibitors to be cautious as workplace breath alcohol detectors may show false-positive results. Conversely, if a positive result is obtained, a detailed examination of ketosis is necessary. This review provides an overview of ketone body measurements in individuals with diabetes.

Breath biomarkers of pediatric malaria: reproducibility and response to antimalarial therapy

BACKGROUND

Many insect-borne pathogens appear to manipulate the odors of their hosts in ways that influence vector behaviors. In our prior work, we identified characteristic changes in volatile emissions of cultured Plasmodium falciparum parasites in vitro and during natural human falciparum malaria. In the current study, we prospectively evaluate the reproducibility of these findings in an independent cohort of children in Blantyre, Malawi.

METHODS

We enrolled febrile children under evaluation for malaria and collected breath from children with and without malaria, as well as healthy controls. Using gas-chromatography/mass spectrometry, we characterized breath volatiles associated with malaria. By repeated sampling of children with malaria before and after antimalarial use, we determined how breath profiles respond to treatment. In addition, we investigated the stage-specificity of biomarkers through correlation with asexual and sexual stage parasitemia.

RESULTS

Our data provide robust evidence that P. falciparum infection leads to specific, reproducible changes in breath compounds. While no individual compound served as adequate classifier in isolation, selected volatiles together yielded high sensitivity for diagnosis of malaria. Overall, the results of our predictive models suggest the presence of volatile signatures that reproducibly predict malaria infection status and determine response to therapy, even in cases of low parasitemia.

Non-contact immunological signaling for highly-efficient regulation of the transcriptional map of human monocytes

The different immune system cells communicate and coordinate a response using a complex and evolved language of cytokines and chemokines. These cellular interactions carry out multiple functions in distinct cell types with numerous developmental outcomes. Despite the plethora of different cytokines and their cognate receptors, there is a restricted number of signal transducers and activators to control immune responses. Herein, we report on a new class of immunomodulatory signaling molecules based on volatile molecules (VMs, namely, volatile organic compounds [VOCs]), by which they can affect and/or control immune cell behavior and transcriptomic profile without any physical contact with other cells. The study demonstrates the role of VMs by analyzing non-contact cell communication between normal and cancerous lung cells and U937 monocytes, which are key players in the tumor microenvironment. Integrated transcriptome and proteome analyses showed the suggested regulatory role of VMs released from normal and cancer cells on neighboring monocytes in several molecular pathways, including PI3K/AKT, PPAR, and HIF-1. Presented data provide an initial platform for a new class of immunomodulatory molecules that can potentially mirror the genomic and proteomic profile of cells, thereby paving the way toward non-invasive immunomonitoring.

Ultratrace eNose Sensing of VOCs toward Breath Analysis Applications Utilizing an eNose-Based Analyzer

This proof-of-principle study presents the ability of the recently developed iLovEnose to measure ultratrace levels of volatile organic compounds (VOCs) in simulated human breath based on the combination of multiple gas sensors. The iLovEnose was developed by our research team as a test bed for gas sensors that can be hosted in three serially connected compact low-volume and temperature-controlled compartments. Herein, the eNose system was equipped with conventional semiconducting metal oxide (MOX) gas sensors using a variety of base technologies providing 11 different sensor signals that were evaluated to determine six VOCs of interest at eight low to ultralow concentration levels (i.e., ranging from 3 to 0.075 ppm) at humid conditions (90% rh at 22 °C). The measurements were randomized and performed four times over a period of 2 weeks. Partial least-squares regression analysis was applied to estimate the concentration of these six analytes. It was shown that the iLovEnose system is able to discriminate between these VOCs and provide reliable quantitative information relevant for future applications in exhaled breath analysis as a diagnostic disease detection or monitoring device.

Single-Component Adsorption Equilibria of CO2, CH4, Water, and Acetone on Tapered Porous Carbon Molecular Sieves

Engineered carbon molecular sieves (CMSs) with tapered pores, high surface area, and high total pore volume were investigated for their CO2, CH4, water, and acetone adsorption properties at 288.15, 298.15, 308.15 K, and pressures of <1 bar. The results were compared with BPL carbon. The samples exhibited higher adsorption capacity for CO2 compared to BPL carbon, with Carboxen 1005 being the highest due to the presence of ultramicropores (pores smaller than 0.8 nm). Similar observations were made for CH4 except at 288.15 K. Although the CMSs exhibited higher hydrophobicity than BPL carbon, the latter had the highest acetone uptake for all investigated temperatures due to its higher oxygen content, which facilitates stronger interactions with polar VOC molecules. Heats of adsorption were calculated using the Clausius-Clapeyron equation after fitting the isotherms with the dual-site Langmuir-Freundlich model, and results largely corroborated the order of adsorption capacities of CO2, CH4, and water on the carbon materials.

Toxicity of chemical-based hand sanitizers on children and the development of natural alternatives: a computational approach

The unintended exposure of children to hand sanitizers poses a high risk of potentially fatal complications. Skin irritation, dryness, cracking, peeling, hypoglycemia, apnea, and acidosis are examples of unintended consequences of hand sanitizer. The sanitizer reportedly kills normal microbial flora on hands, which usually promotes innate immunity among children under 12. Children are more susceptible to the toxicity associated with the chemical constituents of marketed chemical-based hand sanitizers; however, the studies to develop sanitizer formulations for children are rudimentary. The adverse events limit the use of hand sanitizers specifically in children because of their sensitive and delicate skin. Additionally, it is reported that many chemical-based hand sanitizer formulations, especially alcohol-based ones may also contain contaminants like methanol, acetaldehyde, benzene, isopropanol, and ethyl-acetate. These contaminants are found to be hazardous to human health exhibiting toxicity on ingestion, inhalation, or dermal exposure, especially in children. Therefore, it is important to design novel, innovative, safer sanitizer formulations for children. The study aims to discuss the toxic contaminants in chemical-based sanitizer formulations and propose a design for novel herbal formulations with minimal toxicity and adverse effects, especially for children. The review focuses on ADMET analysis of the common contaminants in hand sanitizers, molecular docking, Lipinski's rule of five analysis, and molecular simulation studies to analyze the efficacy of interaction with the receptor leading to anti-microbial activity and drug-likeness of the compound. The in silico methods can effectively validate the potential efficacy of novel formulations of hand sanitizers designed for children as an efficient alternative to chemical-based sanitizers with greater efficacy and the absence of toxic contaminants.

Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review

The development of a simple and fast cancer detection method is crucial since early diagnosis is a key factor in increasing survival rates for lung cancer patients. Among several diagnosis methods, the electrochemical sensor is the most promising one due to its outstanding performance, portability, real-time analysis, robustness, amenability, and cost-effectiveness. Conducting polymer (CP) composites have been frequently used to fabricate a robust sensor device, owing to their excellent physical and electrochemical properties as well as biocompatibility with nontoxic effects on the biological system. This review brings up a brief overview of the importance of electrochemical biosensors for the early detection of lung cancer, with a detailed discussion on the design and development of CP composite materials for biosensor applications. The review covers the electrochemical sensing of numerous lung cancer markers employing composite electrodes based on the conducting polyterthiophene, poly(3,4-ethylenedioxythiophene), polyaniline, polypyrrole, molecularly imprinted polymers, and others. In addition, a hybrid of the electrochemical biosensors and other techniques was highlighted. The outlook was also briefly discussed for the development of CP composite-based electrochemical biosensors for POC diagnostic devices.

Handheld device quantifies breath acetone for real-life metabolic health monitoring

Non-invasive breath analysis with mobile health devices bears tremendous potential to guide therapeutic treatment and personalize lifestyle changes. Of particular interest is the breath volatile acetone, a biomarker for fat burning, that could help in understanding and treating metabolic diseases. Here, we report a hand-held (6 × 10 × 19.5 cm³), light-weight (490 g), and simple device for rapid acetone detection in breath. It comprises a tailor-made end-tidal breath sampling unit, connected to a sensor and a pump for on-demand breath sampling, all operated using a Raspberry Pi microcontroller connected with a HDMI touchscreen. Accurate acetone detection is enabled by introducing a catalytic filter and a separation column, which remove and separate undesired interferents from acetone upstream of the sensor. This way, acetone is detected selectively even in complex gas mixtures containing highly concentrated interferents. This device accurately tracks breath acetone concentrations in the exhaled breath of five volunteers during a ketogenic diet, being as high as 26.3 ppm. Most importantly, it can differentiate small acetone changes during a baseline visit as well as before and after an exercise stimulus, being as low as 0.5 ppm. It is stable for at least four months (122 days), and features excellent bias and precision of 0.03 and 0.6 ppm at concentrations below 5 ppm, as validated by proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). Hence, this detector is highly promising for simple-in-use, non-invasive, and routine monitoring of acetone to guide therapeutic treatment and track lifestyle changes.

Flexible Paper-Based Room-Temperature Acetone Sensors with Ultrafast Regeneration

Paper-based lightweight, degradable, low-cost, and eco-friendly substrates are extensively used in wearable biosensor applications, albeit to a lesser extent in sensing acetone and other gas-phase analytes. Generally, rigid substrates with heaters have been employed to develop acetone sensors due to the high operating/recovery temperature (typically above 200 °C), limiting the use of papers as substrates in such sensing applications. In this work, we proposed fabricating the paper-based, room-temperature-operatable acetone sensor using ZnO-polyaniline-based acetone-sensing inks by a facile fabrication method. The fabricated paper-based electrodes showed good electrical conductivity (80 S/m) and mechanical stability (∼1000 bending cycles). The acetone sensors showed a sensitivity of 0.02/100 ppm and 0.6/10 μL with an ultrafast response (4 s) and recovery time (15 s) at room temperature. The sensors delivered a broad sensitivity over a physiological range of 260 to >1000 ppm with R² > 0.98 under atmospheric conditions. Further, the role of the surface, interfacial, microstructure, electrical, and electromechanical properties of the paper-based sensor devices has been correlated with the sensitivity and room-temperature recovery observed in our system. These versatile, green, flexible electronic devices would be ideal for low-cost, highly regenerative, room-/low-temperature-operable wearable sensor applications.

A sub-ppbv-level Acetone and Ethanol Quantum Cascade Laser Based Photoacoustic Sensor - Characterization and Multi-Component Spectra Recording in Synthetic Breath

Trace gas analysis in breath is challenging due to the vast number of different components. We present a highly sensitive quantum cascade laser based photoacoustic setup for breath analysis. Scanning the range between 8263 and 8270 nm with a spectral resolution of 48 pm, we are able to quantify acetone and ethanol within a typical breath matrix containing water and CO2. We photoacoustically acquired spectra within this region of mid-infra-red light and prove that those spectra do not suffer from non-spectral interferences. The purely additive behavior of a breath sample spectrum was verified by comparing it with the independently acquired single component spectra using Pearson and Spearman correlation coefficients. A previously presented simulation approach is improved and an error attribution study is presented. With a 3σ detection limit of 6.5 ppbv in terms of ethanol and 250 pptv regarding acetone, our system is among the best performing presented so far.

Longitudinal Changes in Circulating Ketone Body Levels in Patients With Acute Heart Failure: A Post Hoc Analysis of the EMPA-Response-AHF Trial

BACKGROUND

Ketone bodies are endogenous fuels produced by the liver under conditions of metabolic or neurohormonal stress. Circulating ketone bodies are increased in patients with chronic heart failure (HF), yet little is known about the effect of acute HF on ketosis. We tested the hypothesis that ketogenesis is increased in patients with acute decompensated HF.

METHODS AND RESULTS

This was a post hoc analysis of 79 patients with acute HF included in the EMPA-RESPONSE-AHF trial, which compared sodium-dependent glucose-cotransporter protein 2 inhibitor treatment with empagliflozin for 30 days with placebo in patients with acute HF [NCT03200860]. Plasma concentrations of ketone bodies acetone, β-hydroxybutyrate, and acetoacetate were measured at baseline and 5 different timepoints. Changes in ketone bodies over time were monitored using repeated measures analysis of variance. In the total cohort, median total ketone body concentration was 251 µmol/L (interquartile range, 178-377 µmol/L) at baseline, which gradually decreased to 202 µmol/L (interquartile range, 156-240 µmol/L) at day 30 (P = .041). Acetone decreased from 60 µmol/L (interquartile range, 34-94 µmol/L) at baseline to 30 µmol/L (interquartile range, 21-42 µmol/L) ( P < .001), whereas β-hydroxybutyrate and acetoacetate remained stable over time. Higher acetone concentrations were correlated with higher N-terminal pro brain natriuretic peptide levels (r = 0.234; P = .039). Circulating ketone bodies did not differ between patients treated with empagliflozin or placebo throughout the study period. A higher acetone concentration at baseline was univariately associated with a greater risk of the composite end point, including in-hospital worsening HF, HF rehospitalizations, and all-cause mortality after 30 days. However, after adjustment for age and sex, acetone did not remain an independent predictor for the combined end point.

CONCLUSIONS

Circulating ketone body concentrations, and acetone in particular, were significantly higher during an episode of acute decompensated HF compared with after stabilization. Treatment with empagliflozin did not affect ketone body concentrations in patients with acute HF.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Cow's microbiome from antepartum to postpartum: A long-term study covering two physiological challenges

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.

Breath Analysis in Children with Ketogenic Glycogen Storage Diseases

(1) Background: The treatment goal of ketogenic glycogen storage diseases (GSDs) is appropriate control of hypoglycemia and other disturbances such as dyslipidemia. Monitoring and treatment of ketosis are known to improve outcomes. We used breath analysis to identify volatile organic compounds (VOCs) that correlate with serum ketones in order to provide a non-invasive method of monitoring ketosis. (2) Methods: Consecutive children with ketogenic GSDs were recruited from a single center during routine admission to monitor serum glucose and ketone levels. Five breath samples were collected from every patient at the same time of blood draws. SIFT-mass spectrometry was used to analyze breath samples. Univariate linear mixed-effects regression models for 22 known VOCs and either serum ketones or glucose were performed. (3) Results: Our cohort included 20 patients aged 5–15 years with a mean BMI of 20 kg/m2 (72% tile). Most patients had GSD type 0 (35%), while 25% had type IX. VOCs that showed a significant correlation with serum ketone levels included acetone (p < 0.0001), trimethylamine (p < 0.0001), pentane (p = 0.0001), 3-methylhexane (p = 0.0047), and carbon disulfide (p = 0.0499). No correlation was found between serum glucose and any VOC. (4) Conclusions: Breath analysis is a promising noninvasive tool that can be used to predict ketone serum levels in patients with GSD.

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.

Analysis of volatile organic compounds from deep airway in the lung through intubation sampling

Exhaled volatile organic compounds (VOCs) have been widely applied for the study of disease biomarkers. Oral exhalation and nasal exhalation are two of the most common sampling methods. However, VOCs released from food residues and bacteria in the mouth or upper respiratory tract were also sampled and usually mistaken as that produced from body metabolism. In this study, exhalation from deep airway was first directly collected through intubation sampling and analyzed. The exhalation samples of 35 subjects were collected through a catheter, which was inserted into the trachea or bronchus through the mouth and upper respiratory tract. Then, the VOCs in these samples were detected by proton transfer reaction mass spectrometry (PTR-MS). In addition, fast gas chromatography proton transfer reaction mass spectrometry (FGC-PTR-MS) was used to further determine the VOCs with the same mass-to-charge ratios. The results showed that there was methanol, acetonitrile, ethanol, methyl mercaptan, acetone, isoprene, and phenol in the deep airway. Compared with that in oral exhalation, ethanol, methyl mercaptan, and phenol had lower concentrations. In detail, the median concentrations of ethanol, methyl mercaptan, and phenol were 7.3, 0.6, and 23.9 ppbv, while those in the oral exhalation were 80.0, 5.1, and 71.3 ppbv, respectively, which meant the three VOCs mainly originated from the food residues and bacteria in the mouth or upper respiratory tract, rather than body metabolism. The research results in our study can provide references for expiratory VOC research based on oral and nasal exhalation samplings, which are more feasible in clinical practice.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition

The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) approach has been widely used to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, instead of using it alone, clinicians often prefer to diagnose the coronavirus disease 2019 (COVID-19) by utilizing a combination of clinical signs and symptoms, laboratory test, imaging measurement (e.g., chest computed tomography scan), and multivariable clinical prediction models, including the electronic nose. Here, we report on the development and use of a low cost, noninvasive method to rapidly sniff out COVID-19 based on a portable electronic nose (GeNose C19) integrating an array of metal oxide semiconductor gas sensors, optimized feature extraction, and machine learning models. This approach was evaluated in profiling tests involving a total of 615 breath samples composed of 333 positive and 282 negative samples. The samples were obtained from 43 positive and 40 negative COVID-19 patients, respectively, and confirmed with RT-qPCR at two hospitals located in the Special Region of Yogyakarta, Indonesia. Four different machine learning algorithms (i.e., linear discriminant analysis, support vector machine, stacked multilayer perceptron, and deep neural network) were utilized to identify the top-performing pattern recognition methods and to obtain a high system detection accuracy (88–95%), sensitivity (86–94%), and specificity (88–95%) levels from the testing datasets. Our results suggest that GeNose C19 can be considered a highly potential breathalyzer for fast COVID-19 screening.

Mach-Zehnder interferometer based integrated-photonic acetone sensor approaching the sub-ppm level detection limit

The detection of acetone in the gaseous form in exhaled breath using an integrated sensor can provide an effective tool for disease diagnostics as acetone is a marker for monitoring human metabolism. An on-chip acetone gas sensor based on the principle of Mach-Zehnder interferometer is proposed and demonstrated. The sensing arm of the device is activated with a composite film of polyethyleneimine and amido-graphene oxide as the gas-sensitive adsorption layer. The composite film demonstrates good selectivity to acetone gas, can be used repeatedly, and is stable in long-term use. Room temperature operation has been demonstrated for the sensor with high sensitivity under a 20 ppm acetone environment. The detection limit can reach 0.76 ppm, making it feasible to be used for the clinical diagnosis of diabetes and the prognosis of heart failure.

Acetone sensing in liquid and gas phases using cyclic voltammetry

This paper presents the use of cyclic voltammetry to measure acetone concentration in liquid and vapor forms at disposable screen-printed electrodes of platinum working electrode, platinum counter electrode, and silver/silver chloride reference electrode. The main characteristics of the acetone sensor including its linearity, sensitivity, reproducibility, and limit of detection (LOD) were studied by doing different experiments to test both liquid and vapor samples in the physiological range of 1 µM to 10 mM. The change in acetone concentration was monitored by comparing the lineshape of butterfly region before and after injecting the acetone sample in the baseline solution that contains 0.5 M H₂SO₄. The sensor was shown to have a good sensitivity, reproducibility, and a linear response with respect to the acetone concentration in both liquid and gas phases over a range of 1 µM to 10 mM with R² > 0.97 and LOD of 0.1 µM. The system stability was improved by building a closed glass system to reduce the exchange of acetone with the surrounding air in an open environment. The closed system was tested using vapor samples and the error bars in the calibration curve were reduced to more than half of their values before using the closed system. The new system will be used extensively in future for an enzyme-based acetone sensor that will be used for diabetes monitoring.

Millimeter-wave gas spectroscopy for breath analysis of COPD patients in comparison to GC-MS

The analysis of human breath is a very active area of research, driven by the vision of a fast, easy, and non-invasive tool for medical diagnoses at the point of care. Millimeter-wave gas spectroscopy (MMWGS) is a novel, well-suited technique for this application as it provides high sensitivity, specificity and selectivity. Most of all, it offers the perspective of compact low-cost systems to be used in doctors' offices or hospitals. In this work, we demonstrate the analysis of breath samples acquired in a medical environment using MMWGS and evaluate validity, reliability, as well as limitations and perspectives of the method. To this end, we investigated 28 duplicate samples from chronic obstructive lung disease patients and compared the results to gas chromatography-mass spectrometry (GC-MS). The quantification of the data was conducted using a calibration-free fit model, which describes the data precisely and delivers absolute quantities. For ethanol, acetone, and acetonitrile, the results agree well with the GC-MS measurements and are as reliable as GC-MS. The duplicate samples deviate from the mean values by only 6% to 18%. Detection limits of MMWGS depend strongly on the molecular species. For example, acetonitrile can be traced down to 1.8 × 10^-12mol by the MMWGS system, which is comparable to the GC-MS system. We observed correlations of abundances between formaldehyde and acetaldehyde as well as between acetonitrile and acetaldehyde, which demonstrates the potential of MMWGS for breath research.

Optical Detection of Acetone Using "Turn-Off" Fluorescent Rice Straw Based Cellulose Carbon Dots Imprinted onto Paper Dipstick for Diabetes Monitoring

Persistent bad breath has been reported as a sign of serious diabetes health conditions. If an individual's breath has a strong odor of acetone, it may indicate high levels of ketones in the blood owing to diabetic ketoacidosis. Thus, acetone gas in the breath of patients with diabetes can be detected using the current easy-to-use fluorescent test dipstick. In another vein, rice straw waste is the most well-known solid pollutant worldwide. Thus, finding a simple technique to change rice straw into a valuable material is highly important. A straightforward and environmentally friendly approach for reprocessing rice straw as a starting material for the creation of fluorescent nitrogen-doped carbon dots (NCDs) has been established. The preparation process of NCDs was carried out via one-pot hydrothermal carbonization using NH₄OH as a passivation substance. A testing strip was developed on the basis of cellulose CD nanoparticles (NPs) immobilized onto cellulose paper assay. The NCDs demonstrated a quantum yield of 23.76%. A fluorescence wavelength was detected at 443 nm upon applying an excitation wavelength of 354 nm. NCDs demonstrated remarkable selectivity for acetone gas as their fluorescence was definitely exposed to quenching by acetone as a consequence of the inner filter effect. A linear correlation was observed across the concentration range of 0.5-150 mM. To detect and measure acetone gas, the present cellulose paper strip has a "switch off" fluorescent signal. A readout limit was accomplished for an aqueous solution of acetone as low as 0.5 mM under ambient conditions. The chromogenic fluorescence of the cellulose assay responsiveness depends on the fluorescence quenching characteristic of the cellulose carbon dots in acetone. A thin fluorescent cellulose carbon dot layer was deposited onto the surface of cellulose strips by a simple impregnation process. CDs were made using NP morphology and analyzed using infrared spectroscopy and transmission electron microscopy. The carbon dot distribution on the paper strip was evaluated by scanning electron microscope and energy-dispersive X-ray analysis. The absorption and fluorescence spectral analyses were investigated. The paper sheets' mechanical qualities were also examined.

Green Phosphorene as a Promising Biosensor for Detection of Furan and p-Xylene as Biomarkers of Disease: A DFT Study

In this work, Green Phosphorene (GP) monolayers are studied as an electronic sensing element for detecting prostate cancer biomarkers from human urine. The adsorption of furan, C₈H₁₀ (p-xylene), and H₂O on pristine GP and S- and Si-doped GP are investigated using the density functional theory (DFT) calculation. Furan and C₈H₁₀ molecules have been considered as important biomarkers of prostate cancer patients. First-principles DFT calculations are applied, and the results divulged that pristine GP could be a promising candidate for furan and C₈H₁₀ detection. It is manifested that furan and C₈H₁₀ are physisorbed on the S-, and Si-doped GP with small adsorption energy and negligible charge transfer. However, the calculations disclose that furan and C₈H₁₀ are chemically adsorbed on the pristine GP with adsorption energy of −0.73, and −1.46 eV, respectively. Moreover, we observe that a large charge is transferred from furan to the pristine GP with amount of −0.106 e. Additionally, pristine GP shows short recovery time of 1.81 s at room temperature under the visible light, which make it a reusable sensor device. Overall, our findings propose that the pristine GP sensor is a remarkable candidate for sensing of furan and other biomarkers of prostate cancer in the urine of patients.

Deep Learning for Type 1 Diabetes Mellitus Diagnosis Using Infrared Quantum Cascade Laser Spectroscopy

An estimated 10.5% of the world’s population aged 20–79 years are currently living with diabetes in 2021. An urgent task is to develop a non-invasive express-diagnostics of diabetes with high accuracy. Type 1 diabetes mellitus (T1DM) diagnostic method based on infrared laser spectroscopy of human exhaled breath is described. A quantum cascade laser emitting in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3–12.8 μm and Herriot multipass gas cell with an optical path length of 76 m were used. We propose a method for collecting and drying an exhaled human air sample and have measured 1200 infrared exhaled breath spectra from 60 healthy volunteers (the control group) and 60 volunteers with confirmed T1DM (the target group). A 1-D convolutional neural network for the classification of healthy and T1DM volunteers with an accuracy of 99.7%, recall 99.6% and AUC score 99.9% was used. The demonstrated results require clarification on a larger dataset and series of clinical studies and, further, the method can be implemented in routine medical practice.

Breath chemical markers of sexual arousal in humans

The chemical composition of exhaled breath was examined for volatile organic compound (VOC) indicators of sexual arousal in human beings. Participants (12-male, 12-female) were shown a randomized series of three emotion-inducing 10-min film clips interspersed with 3-min neutral film clips. The films caused different arousals: sports film (positive-nonsexual); horror film (negative-nonsexual); and erotic (sexual) that were monitored with physiological measurements including genital response and temperature. Simultaneously the breath was monitored for VOC and CO₂. While some breath compounds (methanol and acetone) changed uniformly irrespective of the film order, several compounds did show significant arousal associated changes. For both genders CO₂ and isoprene decreased in the sex clip. Some male individuals showed particularly strong increases of indole, phenol and cresol coincident with sexual arousal that decreased rapidly afterwards. These VOCs are degradation products of tyrosine and tryptophan, precursors for dopamine, noradrenalin, and serotonin, and therefore represent potential breath markers of sexual arousal.

Volatile Organic Compounds as Potential Biomarkers for Noninvasive Disease Detection by Nanosensors: A Comprehensive Review

Biomarkers are biological molecules associated with physiological changes of the body and aids in the detecting the onset of disease in patients. There is an urgent need for self-monitoring and early detection of cardiovascular and other health complications. Several blood-based biomarkers have been well established in diagnosis and monitoring the onset of diseases. However, the detection level of biomarkers in bed-side analysis is difficult and complications arise due to the endothelial dysfunction. Currently single volatile organic compounds (VOCs) based sensors are available for the detection of human diseases and no dedicated nanosensor is available for the elderly. Moreover, accuracy of the sensors based on a single analyte is limited. Hence, breath analysis has received enormous attention in healthcare due to its relatively inexpensive, rapid, and noninvasive methods for detecting diseases. This review gives a detailed analysis of how biomarker imprinted nanosensor can be used as a noninvasive method for detecting VOC to health issues early using exhaled breath analysis.

Detection of trace volatile organic compounds in spiked breath samples: a leap towards breathomics

Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV-vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class.

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

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

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.

NMR metabolomic and microarray-based transcriptomic data integration identifies unique molecular signatures of hypersensitivity pneumonitis

Hypersensitivity pneumonitis (HP) is an immune-mediated granulomatous interstitial lung disease (ILD) that results from repeated inhalation of certain antigens. Despite major advances in research, pathophysiology of the disease remains poorly understood. The present study combines metabolomic and transcriptomic data to determine alterations in HP subjects as compared with healthy controls. Metabolic signatures were identified in serum, exhaled breath condensate (EBC) and bronchoalveolar lavage fluid (BALF) of HP patients using proton nuclear magnetic resonance (NMR) metabolomics. The expression of three metabolites, i.e., lactate, pyruvate, and proline, was found to be significantly altered in all three biofluids. The potential of differential diagnosis based on these three metabolites was investigated by including a group of patients with sarcoidosis, which is another type of granulomatous ILD. In addition, differentially expressed transcriptomic fingerprints in blood samples were identified by analyzing a Gene Expression Omnibus (GEO) database. The transcriptomics analysis of these microarray-based data revealed 59 genes to be significantly dysregulated in patients with HP. Over representation analysis of the metabolites and genes of interest was performed using IMPaLA (Integrated Molecular Pathway Level Analysis) version 12. Integrated analysis of serum metabolite signatures and blood gene expression suggests dysregulation of PI3K-AKT signaling and TCA cycle pathways in these patients. This preliminary study is a step towards better understanding of the pathogenesis of HP by identification of differentially expressed metabolites and transcriptomic fingerprints. These molecular signatures may be explored as diagnostic markers for differentiating HP from other lung diseases.

Dynamic Monitoring of Systemic Biomarkers with Gastric Sensors

Continuous monitoring in the intensive care setting has transformed the capacity to rapidly respond with interventions for patients in extremis. Noninvasive monitoring has generally been limited to transdermal or intravascular systems coupled to transducers including oxygen saturation or pressure. Here it is hypothesized that gastric fluid (GF) and gases, accessible through nasogastric (NG) tubes, commonly found in intensive care settings, can provide continuous access to a broad range of biomarkers. A broad characterization of biomarkers in swine GF coupled to time-matched serum is conducted . The relationship and kinetics of GF-derived analyte level dynamics is established by correlating these to serum levels in an acute renal failure and an inducible stress model performed in swine. The ability to monitor ketone levels and an inhaled anaesthetic agent (isoflurane) in vivo is demonstrated with novel NG-compatible sensor systems in swine. Gastric access remains a main stay in the care of the critically ill patient, and here the potential is established to harness this establishes route for analyte evaluation for clinical management.

Breath acetone concentration: too heterogeneous to constitute a diagnosis or prognosis biomarker in heart failure? A systematic review and meta-analysis

Introduction. Exhaled breath acetone (ExA) has been investigated as a biomarker for heart failure (HF). Yet, barriers to its use in the clinical field have not been identified. The aim of this systematic review and meta-analysis was to assess the ExA heterogeneity and factors of variability in healthy controls (HC), to identify its relations with HF diagnosis and prognostic factors and to assess its diagnosis and prognosis accuracy in HF patients.Methods. A systematic search was conducted in PUBMED and Web of Science database. All studies with HC and HF patients with a measured ExA were included and studies providing ExA's diagnosis and prognosis accuracy were identified.Results. Out of 971 identified studies, 18 studies involving 833 HC and 1009 HF patients were included in the meta-analysis. In HC, ExA showed an important heterogeneity (I²= 99%). Variability factors were fasting state, sampling type and analytical method. The mean ExA was 1.89 times higher in HF patients vs. HC (782 [531-1032] vs. 413 [347-478] ppbv;p< 0.001). One study showed excellent diagnosis accuracy, and one showed a good prognosis value. ExA correlated with New York Heart Association (NYHA) dyspnea (p< 0.001) and plasma brain natriuretic peptide (p< 0.001). Studies showed a poor definition and reporting of included subjects.Discussion. Despite the between-study heterogeneity in HC, the evidence of an excellent diagnosis and prognosis value of ExA in HF from single studies can be extended to clinical populations worldwide. Factors of variability (ExA procedure and breath sampling) could further improve the diagnosis and prognosis values of this biomarker in HF patients.

An Update on the Use of Exhaled Breath Analysis for the Early Detection of Lung Cancer

Lung cancer has historically been the main responsible for cancer associated deaths. Owing to this is our current inability to screen for and diagnose early pathological findings, preventing us from a timely intervention when cure is still achievable. Over the last decade, together with the extraordinary progress in therapeutical alternatives in the field, there has been an ongoing search for a biomarker that would allow for this. Numerous technologies have been developed but their clinical application is yet to come. In this review, we provide an update on volatile organic compounds, a non-invasive method that can hold the key for detecting early metabolic pathway changes in carcinogenesis. For its compilation, web-based search engines of scientific literature such as PubMed were explored and reviewed, using articles, research, and papers deemed meaningful by authors discretion. After a brief description, we depict how this technique can complement current methods and present the value of electronic noses in the identification of the “breathprint”. Lastly, we bring some of the latest updates in the field together with the current limitations and final remarks.

Quantification of Volatile Acetone Oligomers Using Ion-Mobility Spectrometry

BACKGROUND

Volatile acetone is a potential biomarker that is elevated in various disease states. Measuring acetone in exhaled breath is complicated by the fact that the molecule might be present as both monomers and dimers, but in inconsistent ratios. Ignoring the molecular form leads to incorrect measured concentrations. Our first goal was to evaluate the monomer-dimer ratio in ambient air, critically ill patients, and rats. Our second goal was to confirm the accuracy of the combined (monomer and dimer) analysis by comparison to a reference calibration system.

METHODS

Volatile acetone intensities from exhaled air of ten intubated, critically ill patients, and ten ventilated Sprague-Dawley rats were recorded using ion-mobility spectrometry. Acetone concentrations in ambient air in an intensive care unit and in a laboratory were determined over 24 hours. The calibration reference was pure acetone vaporized by a gas generator at concentrations from 5 to 45 ppb_v (parts per billion by volume).

RESULTS

Acetone concentrations in ambient laboratory air were only slightly greater (5.6 ppb_v; 95% CI 5.1-6.2) than in ambient air in an intensive care unit (5.1 ppb_v; 95% CI 4.4-5.5; p < 0.001). Exhaled acetone concentrations were only slightly greater in rats (10.3 ppb_v; 95% CI 9.7-10.9) than in critically ill patients (9.5 ppb_v; 95% CI 7.9-11.1; p < 0.001). Vaporization yielded acetone monomers (1.3-5.3 mV) and dimers (1.4-621 mV). Acetone concentrations (ppb_v) and corresponding acetone monomer and dimer intensities (mV) revealed a high coefficient of determination (R ² = 0.96). The calibration curve for acetone concentration (ppb_v) and total acetone (monomers added to twice the dimers; mV) was described by the exponential growth 3-parameter model, with an R ² = 0.98.

CONCLUSION

The ratio of acetone monomer and dimer is inconsistent and varies in ambient air from place-to-place and across individual humans and rats. Monomers and dimers must therefore be considered when quantifying acetone. Combining the two accurately assesses total volatile acetone.

Rapid and sensitive detection of acetone in exhaled breath through the ambient reaction with water radical cations

The levels of acetone and other ketones in exhaled human breath can be associated with various metabolic conditions, e.g. ketosis, lung cancer, dietary fat loss and diabetes. In this study, ketones in breath samples were charged through the reaction with water radical cations to form [M + H₂O]˙⁺ ions, which were detected by mass spectrometry. Our experimental data indicate that under the optimized experimental conditions, the limit of detection for acetone using our approach is 0.14 ng L^-1 (∼0.06 ppb). The linear dynamic range of detection spans four orders of magnitude. The developed approach was applied to real-time semi-quantitative analysis of acetone in the exhaled breath of human volunteers, revealing significantly higher levels of acetone in the breath of smokers compared to non-smokers. The developed approach features the obviation of sample collection, easy operation, high speed of analysis (10 s per run), high sensitivity, and spectral interpretation, which indicates the potential of ambient corona discharge ionization mass spectrometry as a selective, sensitive and noninvasive technique for the determination of exhaled ketones in clinical diagnosis including lung cancer, diabetes, etc.

Nanostructured ZnO and ZnO: Pd with MXene overlayer SPR biosensors

The development of biosensors based on various novel techniques has become highly significant in the context of the outburst of a pandemic like COVID 19. The present work reports the theoretical modeling of two surface plasmon resonance (SPR) based biosensing probe configurations on optical fiber employing Metal/ZnO/MXene and Metal/ZnO: Pd/MXene. Maximum sensitivities of 19,400 nm/RIU and 8350 nm/RIU are calculated with Metal/ZnO/MXene and Metal/ZnO: Pd/MXene, respectively. The sensors are suitable for analytes with refractive index values ranging from 1.354 to 1.422. The refractive index of mucus and serum being in this range, the proposed biosensor, can be a potential tool for COVID-19 detection.

Surface Plasmon Resonance-Based Fiber-Optic Metallic Multilayer Biosensors

Accurate and quick sensing of various biomolecules relevant to different health conditions is indispensable in modern diagnosis and treatment procedures. Different multilayer metallic surface plasmon resonance (SPR) biosensor configurations comprising Au, Ag, Al, and Cu are analyzed in this work by employing an N-layer matrix formalism as applied to the fixed-angle spectral SPR sensing methodology. Stringent standards for sensitivity, detection accuracy, and figure of merit (FOM) of the sensor configurations are set to analyze the relative merits of one configuration over another. It is observed that three- and four-layer configurations using Al and Cu provide the best FOM among all sensors that passed the set standard criteria. The highest FOM (1433.82/RIU) is observed for the four-layer Al/Cu/Al/Cu sensor for an analyte refractive index of 1.408. The sensors are best suited for detecting analytes with a refractive index range of 1.350-1.414.

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

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

Review on Volatolomic Studies as a Frontier Approach in Animal Research

This paper presents a comprehensive review of the research studies in volatolomics performed on animals so far. At first, the procedures proposed for the collection, preconcentration, and storing of the volatile organic compounds emitted by various biological samples of different animals are presented and discussed. Next, the results obtained in the analysis of the collected volatile samples with analytical equipment are shown. The possible volatile biomarkers identified for various diseases are highlighted for different types of diseases, animal species, and biological samples analyzed. The chemical classes of these compounds, as well as the biomarkers found in a higher number of animal diseases, are indicated, and their possible origin is analyzed. The studies that dealt with the diagnosis of various diseases from sample measurement with electronic nose systems are also presented and discussed. The paper ends with a final remark regarding the necessity of optimization and standardization of sample collection and analysis procedures for obtaining meaningful results.

Room-Temperature Catalyst Enables Selective Acetone Sensing

Catalytic packed bed filters ahead of gas sensors can drastically improve their selectivity, a key challenge in medical, food and environmental applications. Yet, such filters require high operation temperatures (usually some hundreds °C) impeding their integration into low-power (e.g., battery-driven) devices. Here, we reveal room-temperature catalytic filters that facilitate highly selective acetone sensing, a breath marker for body fat burn monitoring. Varying the Pt content between 0-10 mol% during flame spray pyrolysis resulted in Al2O3 nanoparticles decorated with Pt/PtOx clusters with predominantly 5-6 nm size, as revealed by X-ray diffraction and electron microscopy. Most importantly, Pt contents above 3 mol% removed up to 100 ppm methanol, isoprene and ethanol completely already at 40 °C and high relative humidity, while acetone was mostly preserved, as confirmed by mass spectrometry. When combined with an inexpensive, chemo-resistive sensor of flame-made Si/WO3, acetone was detected with high selectivity (≥225) over these interferants next to H2, CO, form-/acetaldehyde and 2-propanol. Such catalytic filters do not require additional heating anymore, and thus are attractive for integration into mobile health care devices to monitor, for instance, lifestyle changes in gyms, hospitals or at home.

Breath Acetone Sensing Based on Single-Walled Carbon Nanotube-Titanium Dioxide Hybrids Enabled by a Custom-Built Dehumidifier

Acetone is a metabolic byproduct found in the exhaled breath and can be measured to monitor the metabolic degree of ketosis. In this state, the body uses free fatty acids as its main source of fuel because there is limited access to glucose. Monitoring ketosis is important for type I diabetes patients to prevent ketoacidosis, a potentially fatal condition, and individuals adjusting to a low-carbohydrate diet. Here, we demonstrate that a chemiresistor fabricated from oxidized single-walled carbon nanotubes functionalized with titanium dioxide (SWCNT@TiO₂) can be used to detect acetone in dried breath samples. Initially, due to the high cross sensitivity of the acetone sensor to water vapor, the acetone sensor was unable to detect acetone in humid gas samples. To resolve this cross-sensitivity issue, a dehumidifier was designed and fabricated to dehydrate the breath samples. Sensor response to the acetone in dried breath samples from three volunteers was shown to be linearly correlated with the two other ketone bodies, acetoacetic acid in urine and β-hydroxybutyric acid in the blood. The breath sampling and analysis methodology had a calculated acetone detection limit of 1.6 ppm and capable of detecting up to at least 100 ppm of acetone, which is the dynamic range of breath acetone for someone with ketosis. Finally, the application of the sensor as a breath acetone detector was studied by incorporating the sensor into a handheld prototype breathalyzer.

Exhaled Breath Reflects Prolonged Exercise and Statin Use during a Field Campaign

Volatile organic compounds (VOCs) in exhaled breath provide insights into various metabolic processes and can be used to monitor physiological response to exercise and medication. We integrated and validated in situ a sampling and analysis protocol using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) for exhaled breath research. The approach was demonstrated on a participant cohort comprising users of the cholesterol-lowering drug statins and non-statin users during a field campaign of three days of prolonged and repeated exercise, with no restrictions on food or drink consumption. The effect of prolonged exercise was reflected in the exhaled breath of participants, and relevant VOCs were identified. Most of the VOCs, such as acetone, showed an increase in concentration after the first day of walking and subsequent decrease towards baseline levels prior to walking on the second day. A cluster of short-chain fatty acids including acetic acid, butanoic acid, and propionic acid were identified in exhaled breath as potential indicators of gut microbiota activity relating to exercise and drug use. We have provided novel information regarding the use of breathomics for non-invasive monitoring of changes in human metabolism and especially for the gut microbiome activity in relation to exercise and the use of medication, such as statins.

Terahertz high-resolution spectroscopy of thermal decomposition gas products of diabetic and non-diabetic blood plasma and kidney tissue pellets

SIGNIFICANCE

One of the modern trends in medical diagnostics is based on metabolomics, an approach allowing determination of metabolites which can be the specific features of disease. High-resolution gas spectroscopy allows investigation of the gas metabolite content of samples of biological origin. We present the elaboration of a method of studying diabetic and non-diabetic biological samples, prepared as pellets, by terahertz (THz) high-resolution spectroscopy.

AIM

The main idea of the work is studying the content of thermal decomposition gas products of diabetic and non-diabetic dried blood plasma and kidney tissues for revealing the set of gas-markers that characterized the diabetes by the THz high-resolution spectroscopy method.

APPROACH

We present an approach to study the diabetic and non-diabetic blood plasma (human and rats) and kidney tissues (rats), using high-resolution spectroscopy based on the non-stationary effect of THz frequency range. The methods of preparing the blood and kidney tissue samples as pellets and of vaporizing the samples were developed.

RESULTS

The measurements of rotational absorption spectra of vapors at heating the pellets prepared from blood and kidney tissue were carried out in 118 to 178 GHz frequency range. The absorption lines appearing in spectra of the sample vapors were detected and identified. The molecular contents of thermal decomposition products differed for non-diabetic and diabetic samples; e.g., main marker is acetone appearing in the diabetic blood (human and rats) and in the diabetic kidney tissue.

CONCLUSIONS

Our paper illustrates the potential ability for determining the metabolite content of biological samples for diagnostics and prognosis of diseases for clinical medicine.